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IL-33 is a tissue-derived cytokine that induces and amplifies eosinophilic inflammation and has emerged as a promising new drug target for asthma and allergic disease . Common variants at IL33 and IL1RL1 , encoding the IL-33 receptor ST2 , associate with eosinophil counts and asthma . Through whole-genome sequencing and imputation into the Icelandic population , we found a rare variant in IL33 ( NM_001199640:exon7:c . 487-1G>C ( rs146597587-C ) , allele frequency = 0 . 65% ) that disrupts a canonical splice acceptor site before the last coding exon . It is also found at low frequency in European populations . rs146597587-C associates with lower eosinophil counts ( β = -0 . 21 SD , P = 2 . 5×10–16 , N = 103 , 104 ) , and reduced risk of asthma in Europeans ( OR = 0 . 47; 95%CI: 0 . 32 , 0 . 70 , P = 1 . 8×10–4 , N cases = 6 , 465 , N controls = 302 , 977 ) . Heterozygotes have about 40% lower total IL33 mRNA expression than non-carriers and allele-specific analysis based on RNA sequencing and phased genotypes shows that only 20% of the total expression is from the mutated chromosome . In half of those transcripts the mutation causes retention of the last intron , predicted to result in a premature stop codon that leads to truncation of 66 amino acids . The truncated IL-33 has normal intracellular localization but neither binds IL-33R/ST2 nor activates ST2-expressing cells . Together these data demonstrate that rs146597587-C is a loss of function mutation and support the hypothesis that IL-33 haploinsufficiency protects against asthma .
Asthma is characterized by airflow obstruction , airway hyper-responsiveness and airway inflammation , that promotes mucus obstruction . The inflammatory cytokine IL-33 is widely expressed[1 , 2] and abundantly in the bronchial epithelium . IL-33 resides in the nucleus due to chromatin-binding motifs[3] but is released after exposure to e . g . viruses or allergens . IL-33 binds to its receptor ST2[4] ( also called IL1RL1 , IL-33R ) and activates eosinophils and other immune cells promoting inflammation[5] , particularly in the lung[6 , 7] . IL-33 also binds to a soluble isofrom IL1RL1-a/sST2 , which is thought to act as a decoy receptor and ameliorates airway inflammation[8] . Through GWAS , we previously discovered common sequence variants in IL1RL1 and IL33 that associate strongly with blood eosinophil counts and risk of asthma , consistent with the link between eosinophilic inflammation and asthma [9] . The association between IL1RL1 and IL33 variants and asthma risk is well established [10] and has been replicated in ethnically diverse populations[11 , 12] , and in severe forms of adult asthma[11] and in particular with early childhood[13] asthma with exacerbations . The critical role of eosinophilic airway inflammation in asthma[14] together with robust association of eosinophil counts and asthma with common variants at the IL33 and IL1RL1 loci prompted us to search for novel sequence variants at these loci affecting eosinophil counts using high-coverage sequencing [15] . The variants were identified through sequencing of 8 , 453 Icelanders and imputed into 150 , 656 chip-typed Icelanders[15] . In light of the role of eosinophils in pathogenesis of asthma and the previously established association of common variants at the IL33 and IL1RL1 loci with eosinophil counts and asthma , individual sequence variants at these loci found to associate significantly with eosinophil counts were further assessed for their effects on asthma .
We focus on the association of sequence variants in two 800kb regions centered on IL33 ( chr9:5 . 8–6 . 6Mb ( hg38 ) ) and IL1RL1 ( chr2:101 . 9–102 . 7Mb ( hg38 ) ) with eosinophil counts in 103 , 104 Icelanders[16] . Sequence variants were weighted according to their prior probability of affecting gene function by applying different thresholds for genome-wide ( gw ) significance that depend on the variant class[17] . Stepwise conditional analysis at the IL33 locus revealed two significant uncorrelated ( pairwise r2<0 . 02 ) variants ( Fig 1 and S1 Fig , Table 1 and S1 Table ) . One association is novel: rs146597587-C a rare variant ( allelic frequency ( AF ) = 0 . 65% ) that is predicted to disrupt a canonical splice acceptor site at the beginning of the last exon of IL33[18 , 19] ( NM_001199640:exon7:c . 487-1G>C , βadj = -0 . 21 SD; Padj = 2 . 5×10–16 ) ( Table 2 ) . rs146597587-C associates with lower eosinophil counts and is not correlated with previously reported variants at the IL33 locus ( S2 Table ) . The second variant , rs2095044-T ( AF = 24 . 5% ) , upstream of IL33 , is associated with increased eosinophil count ( βadj = 0 . 051 SD; Padj = 3 . 6×10–27 ) and is highly correlated with rs2381416 ( r2 = 0 . 94 ) , originally described to associate with eosinophil counts and asthma[9] ( Table 1 , S3 and S4 Tables ) . A potential secondary signal was noted , rs10758750-G ( AF = 27 . 7% ) , an intronic variant in IL33 ( βadj = -0 . 023 SD; Padj = 5 . 7×10–7 ) ( Table 1 ) ( passing a significance threshold of 2 . 8×10–6 , corresponding to a Bonferroni correction for the number of variants tested ( 17 , 935 ) at the two loci[20] ) , uncorrelated ( pairwise r2<0 . 02 ) to the novel variant reported here ( Fig 1 and S1 Fig , Table 1 and S1 Table ) and to the previously reported variants at the IL33 locus ( S2 Table ) . Among the two significant variants , the splice acceptor mutation rs146597587-C has the largest effect . The splice acceptor mutation is present in both Europeans ( AF = 0 . 35% ) and South-Asians ( AF = 0 . 10% ) in the Exome Aggregation Consortium ( ExAC ) database where it is >10 times more frequent than any other predicted loss-of-function variant in IL33 ( S5 Table , URLs ) . In total we tested six predicted missense , splice region or loss-of-function variants in IL33 ( S6 Table ) and only the association with the splice acceptor mutation rs146597587-C is significant ( P>0 . 2 for the others ) . None of the twelve variants highly correlated ( r2>0 . 8 ) with the splice acceptor mutation were coding , making it most likely to be responsible for the effect ( S7 Table ) . Neither of the two other associating variants , rs2095044 nor rs10758750 , were correlated with a coding variant ( S4 and S8 Tables ) . The IL33 splice acceptor mutation , rs146597587-C was genotyped in 1 , 370 Dutch samples and its effect on eosinophil counts was replicated ( β = -0 . 48 SD , P = 0 . 036 , AF = 0 . 69% ) ( Table 2 ) . Once the eosinophil count association of the splice acceptor variant was established , we assessed its effect on asthma , based on the prior association of IL33 and with asthma risk and the role of eosinophils in the pathogenesis of asthma . We assessed the effect of rs146597587-C on asthma in Iceland[9] , The Netherlands[21–23] , Germany [24] and Denmark[25 , 26] , including Danish children with severe asthma with at least 2 exacerbations leading to hospitalization between 2 and 6 years of age ( COPSACexacerbation ) [13] . The IL33 splice acceptor mutation protects against asthma ( OR = 0 . 47; 95% CI: 0 . 32–0 . 70 , P = 1 . 8×10–4 ) ( Table 2 ) . We did not observe heterogeneity of the effect in the different sample sets ( Phet = 0 . 24 , I2 = 26 . 8 ) . Thus , this rare splice acceptor mutation reduces eosinophil counts and protects against asthma , whereas the minor allele of the common rs2095044-T associates with higher eosinophil counts and increased risk of asthma ( Tables 1 and 2 ) . Stepwise conditional analysis of the association with eosinophil counts ( N = 103 , 104 ) at the IL1RL1 locus revealed two significant variants , an intronic variant , rs13020553-G ( MAF = 41 . 9% ) , increasing eosinophil counts ( β = 0 . 043 , Padj = 1 . 6×10–24 ) and an intergenic variant , rs6719123-G ( MAF = 14 . 2% ) , decreasing eosinophil counts ( β = -0 . 037 , Padj = 7 . 0×10–10 ) ( Table 1 and S9 Table ) ; no other variant at the locus remained significant after adjusting for these two ( Fig 2 and S10 Table ) . rs13020553 is highly correlated with rs1420101 ( r2 = 0 . 96 , D’ = 1 . 00 ) , originally reported to associate with eosinophil counts and asthma[9] ( S3 and S10 Tables ) . Despite the high correlation , rs1420101-T ( that is on the background of rs13020553-G ) does not fully explain the eosinophil association of rs13020553 , whereas rs13020553 fully explains the eosinophil association for rs1420101 ( S10 Table ) . Together rs13020553 and rs6719123 explain all the reported effects on eosinophil counts and asthma at the locus ( S3 Table ) ; however , the reported variants do not fully explain the signal captured by rs13020553 and rs6719123 ( S11 Table ) . We found and tested 75 coding or splice region variants at the IL1RL1 locus . Among those not in IL1RL1 , only one was significant ( P>0 . 001 for all other coding variants not in IL1RL1 ) , rs1420098-C , a splice region variant in IL18R1 ( MAF = 42 . 5% , P = 3 . 8×10–24 , β = 0 . 042 ) . The eosinophil counts association of rs1420098 was fully accounted for by rs13020553 ( r2 = 0 . 81 , Padj = 0 . 53 ) , whereas the association of rs13020553 could not be accounted for by rs1420098 ( Padj = 1 . 2×10–8 , βadj = 0 . 054 ) . We observed two significant coding signals in IL1RL1 among the sixteen detected and tested ( 14 missense , one splice region variant and one frameshift variant ) ( S12 Table ) . Both coding signals were previously reported to associate with concentration of ST2 in soluble form ( sST2 ) [27] . The first , represented by rs10192157-T ( MAF = 39 . 0% , P = 4 . 2×10–20; HGVSp: NP_057316 . 3:p . Thr549Ile ) , corresponds to five perfectly correlated missense variants ( r2 = 1 . 00 , D’ = 1 . 00 for all pairs ) moderately correlated with rs13020553 ( r2 = 0 . 35 ) ; the second rs1041973-A ( MAF = 17 . 7% , P = 3 . 5×10–9 , HGVSp: NP_057316 . 3:p . Ala78Glu ) is correlated with rs6719123 ( r2 = 0 . 68 ) ( S13 Table ) . These two eosinophil counts associations are fully accounted for by rs13020553 and rs6719123 ( S14 Table ) . We conclude that the eosinophil counts signals corresponding to rs13020553 and rs6719123 ( correlated variants: S15 and S16 Tables ) could not be explained by the observed coding variants or reported variants at the locus . Our results are in agreement with the notion that variants at this locus influence eosinophil counts by affecting IL1RL1; and IL-33 is known to mediate its biological effects through ST2/IL1RL1[4] . The splice acceptor mutation in IL33 changes AG to AC at the 3’ splice junction between the last two exons and is thus predicted to disrupt splicing between them [18 , 19] . IL33 is primarily expressed by stromal cells and is expressed at a relatively low level in hematopoetic tissues . Of the two tissues with mRNA sequencing data available to us IL33 is essentially absent from whole blood but is expressed in subcutaneous adipose tissue[1] ( median RPKM of 12 . 9 in 350 samples ) , according to the GTExV6 database[2] . We therefore analyzed the effect of the splice acceptor mutation on the IL33 transcript quantity and processing using the adipose tissue mRNA sequencing ( N = 675 ) dataset ( Materials and methods , and Fig 3 ) . Heterozygote carriers ( N = 10 ) of the splice acceptor mutation showed about 40% lower total IL33 expression than non-carriers ( P = 6 . 8×10–6 ) ( Fig 3 ) . Comparable results were obtained by accessing total IL-33 expression with microarray ( S2 Fig ) . Allele-specific analysis of the RNA sequencing data shows that only 20% of total IL33 transcripts are from the mutated chromosomes ( P = 1 . 3×10–4 ) indicating that a large fraction of mRNA originating from the mutated chromosomes is likely eliminated through nonsense-mediated decay ( NMD ) [28] . Analysis of read coverage in the RNA sequencing data , shows retention of the last intron of IL33 in about half of the RNA generated from the mutated chromosome ( ~11% of total RNA ) in heterozygotes compared to 0 . 6% of that in non-carriers ( P = 5 . 6×10–8 ) . Taken together these data demonstrate that the splice acceptor mutation leads both to elimination of the mutated transcripts and a retention of the last intron , introducing a premature stop codon in about half of the remaining mutated transcripts . The IL-33 protein generated from the intronic retention transcripts is predicted to lack the last 66 amino acids ( out of 270 ) . IL-33 folds as a 12-stranded “β-barrel” structure , prototypical for the IL-1 family . Elimination of the last 66 amino acids removes 5 of the 12 core β-strands and is predicted to disrupt the tertiary structure of the protein . To determine whether IL-33 lacking these residues is functional we expressed recombinant IL-33 lacking the last exon ( termination at residue 204 , Fig 4 ) . IL-331–204 was detectable in transfected mammalian cellular lysates as a 27kD protein , compared to the 35 kD wild type IL-331–270 ( S3 Fig ) . IL-331–204 was in the nucleus in a manner indistinguishable from IL-331–270 ( Fig 4 ) , indicating that the truncation does not disrupt nuclear trafficking . Computational modeling [29] indicates that truncated IL-33 lacks core structural folds and key surface residues predicted to contribute to receptor binding ( Fig 4A ) . To determine whether the truncated form binds ST2 we generated IL-3395–270 ( wild type ) and IL-3395–204 ( truncated mutant ) recombinant proteins . The N-terminus starting residue at amino acid position 95 was chosen based on natural processing of IL-33 before receptor binding[30] ( S4 Fig ) . Using surface plasmon resonance we found that IL-3395–270 bound rapidly to IL-33R/ST2 ( Fig 4 ) , consistent with high affinity binding to IL-33R that we previously reported[31] , whereas IL-3395–204 showed no interaction signal , indicating a complete lack of receptor binding . Furthermore , IL-3395–270 induced a concentration- and IL-33R-dependent CCL1 release in human mast cell line expressing IL-33R ( Fig 4C and S5 Fig ) , whereas IL-3395–204 did not at any concentration tested , consistent with a complete loss of cytokine activity . The mutant IL-33 was also inactive compared to wild type inducing IFN-γ release from human CD4+ T cells ( Fig 5 ) . In il33 knock-out mice , 30% reduced fertility by has been reported[32] . Nine imputed rs146597587-C homozygotes were found in the Icelandic data and they neither show reduced life expectancy nor reduced fertility ( S16 Table ) , indicating that a predicted very low level of IL-33 is compatible with long life and healthy reproduction . Moreover , rs146597587-C homozygosity ( recessive model ) does not confer risk of any other disease that was tested in the Icelandic data[15 , 33] , indicating that IL-33 is largely dispensable . Two homozygotes of the splice acceptor mutation are reported in ExAC ( S5 Table , URLs ) . An association of il33 polymorphism with eosinophil numbers in rats has been reported[34] and we found that deletion of il33 leads to significant reduction in blood eosinophils in unchallenged mice ( P = 0 . 014 males , P = 0 . 00010 females ) ( Fig 6 ) , mimicking our human observations .
Resequencing of 100 genes implicated in asthma only revealed a few coding variants associating with asthma[35] . Since eosinophils are known to play a key role in inflammation of the airway in asthma[12] we used high-coverage sequencing [13] to search for novel sequence variants affecting eosinophil counts at the well established asthma loci , the IL33 and IL1RL1 loci , and tested their effects on asthma . Our results indicate that variants at the IL1RL1 locus affect eosinophil counts and the risk of asthma most likely by affecting IL1RL1 itself . IL-33 is known to mediate its biological effects through ST2/IL1RL1[4] and sensitized mice with il1rl1 ( ST2-/- ) knocked out show less eosinophil numbers in bronchoalveolar lavage fluid upon allergen exposure than wild-type mice , reduced levels of Th2 cytokines and chemoattractants in the lungs , and reduced goblet cell hyperplasia around the peripheral airways in murine models of allergy and asthma[36 , 37] . We report a rare variant , rs146597587 , in IL33 representing a loss-of-function mutation in this known asthma gene . This splice acceptor mutation associates with lower eosinophil counts and protection against asthma , with the largest protective effect from severe asthma with frequent exacerbations in young Danish children ( OR = 0 . 24 , Table 2 ) . This is in agreement with increasing risk conferred by the common IL33 variant rs2381416 with increasing severity of asthma in these children , with OR from 1 . 27 to 1 . 69 for severity groups 1 to 4 ( S17 Table ) . The splice acceptor mutation caused reduced expression of IL33 transcripts , likely due to NMD , and production of truncated IL-33 that lacks the cytokine function due to lack of binding to IL-33R/ST2 resulting in abrogation of IL-33R-dependent release of CCL1 from mast cells and IFN-γ release from human CD4+ T cells . We therefore infer that asthma risk is mediated through IL-33 . Accordingly , common variants in IL1RL1 that associate with increased asthma risk associate with reduced expression of soluble ST2[38 , 39] , with the predicted effect being increased IL-33 activity , due to reduced level of this decoy receptor . Thus , human genetics support the rationale for therapeutically inhibiting the IL-33-ST2 pathway in an attempt at containing asthma .
The Icelandic study was approved by the National Bioethics Committee ( VSN_14–099 ) and the Data Protection Authority ( no . PV_2014060841/ÞS ) in Iceland . All participating subjects who donated blood provided informed consent . Personal identities of the participants and biological samples were encrypted by a third-party system approved and monitored by the Icelandic Data Protection Authority . The Denmark-1 study was approved by the local ethics committee of Copenhagen , Denmark ( Approval no . KF01-400/98 and KF01-074/01 ) . All participants signed informed consent . The COPSAC study research protocol was approved by The Danish National Ethical Committee on Health Research ( KF 01-289/96 , H-B-2008-093 , H-16039498 and H-B-2998-103 ) and is in accordance with the ethical scientific principles of the Helsinki Declaration II . All parents in the cohorts signed informed consent . The German study was approved by the Ethical Commission of the University of Freiburg ( Approval no . 96/05 ) . All participants signed informed consent . The Dutch European ancestry asthma study was approved by the Medical Ethics Committee of the University Hospital Groningen ( Approvals no . MEC 90/09/178 , MEC 96/04/077 , MEC 97/10/184 ) . All participants signed informed consent . The Dutch Vlagtwedde/Vlaardingen study protocol was approved by the local university medical hospital ethics committee , University of Groningen , University Medical Center Groningen , The Netherlands and all participants gave their written informed consent . In 1984 , the Committee on Human Subjects in Research of the University of Groningen reviewed the study and affirmed the safety of the protocol and study design . The mouse experiments were performed at Amgen Inc . All animal use procedures were in accordance with Amgen animal use and care guidelines and approved by IACUC . Genotyping of all Icelandic samples was carried out at deCODE genetics in Reykjavik , Iceland , using methods recently described[15] . In brief , whole-genome sequencing was performed for 8 , 453 Icelanders who were recruited as part of various genetic programs at deCODE genetics , to an average depth of at least 10× ( median 32× ) using Illumina technology . The sequencing was performed using the following three different library preparation methods and sequencing instruments from Illumina: ( i ) standard TruSeq DNA library preparation method; Illumina GAIIx and/or HiSeq 2000 sequencers; ( ii ) TruSeq DNA PCR-free library preparation method; Illumina HiSeq 2500 sequencers; and ( iii ) TruSeq Nano DNA library preparation method; Illumina HiSeq X sequencers ( S1 Method ) . SNPs and indels identified in the whole-genome sequencing data were identified using the Genome Analysis Toolkit HaplotypeCaller ( GATK version 3 . 3 . 0 ) [43] and imputed into 150 , 656 Icelanders who had been genotyped with various Illumina SNP chips and their genotypes phased using long-range phasing chip-genotyped individuals using long-range phasing[44] . In addition , using the Icelandic genealogical database , genotype probabilities were calculated for first- and second-degree relatives of chip-genotyped individuals[15] . The effects of sequence variants on protein-coding RefSeq genes[18] were annotated using the Variant Effect Predictor ( VEP ) version 80[19] . Single SNP genotyping in the replication sample sets was carried out by deCODE Genetics in Reykjavik , Iceland , applying the Centaurus ( Nanogen ) platform[45] except that genotyping single SNPs in the Danish cohort of children with severe asthma was carried out at the AROS Applied Biotechnology AS center ( http://arosab . com/services/microarrays/genotyping/ ) , in Aarhus , Denmark , applying the Illumina Infinium HumanOmniExpressExome Bead chip platform and genome studio software[46] . Generalized linear regression models were used to test for associations between sequence variants and quantitative traits , assuming an additive genetic model . Let y be the vector of quantitative measurements , and let g be the vector of expected allele counts for the sequence variant being tested . We assume the quantitative measurements follow a normal distribution with a mean that depends linearly on the expected allele at the variant and a variance covariance matrix proportional to the kinship matrix: y~N ( α+βg , 2σ2Φ ) , where Φij={12 , i=j2kij , i≠j . is the kinship matrix as estimated from the Icelandic genealogical database . Logistic regression was used to test for association between sequence variants and binary traits . Other available individual characteristics that correlate with disease status were also included in the model as nuisance variables . These characteristics were: sex , county of birth , current age or age at death ( first- and second-order terms included ) , blood sample availability for the individual and an indicator function for the overlap of the lifetime of the individual with the timespan of phenotype collection . Testing was performed using the likelihood ratio statistic . Conditional analysis was performed by including the sequence variant being conditioned on as a covariate in the model under the null and the alternative in the generalized linear regression . Sequence variants were weighted according to their prior probability of affecting gene function by applying different thresholds for genome-wide ( gw ) significance that depend on the variant class[17] . Association summary statistics are provided in supplementary tables for the IL33 locus ( S18 Table ) and the IL1RL1 locus ( S19 Table ) . Samples of RNA from human peripheral blood and adipose tissue were hybridized to Agilent Technologies Human 25K microarrays as described previously[48] and the effect of SNPs on the IL33 expression in adipocytes evaluated . We quantified expression changes between two samples as the mean logarithm ( log10 ) expression ratio ( MLR ) compared to a reference pool RNA sample . In comparing expression levels between groups of individuals with different genotypes , we denoted the expression level for each genotype as 10 ( average MLR ) , where the MLR is averaged over individuals with the particular genotype . We determined s . e . m . and significance by regressing the MLR values against the number of risk alleles carried . We took into account the effects of age , gender and differential cell type count in blood as explanatory variables in the regression . The effect of on the IL33 expression in adipocytes was evaluated by RNA sequencing as previously described[20] . IL-33 variant-expressing vectors as shown in Fig 4D were transfected into HEK293–EBNA1 cells ( obtained from National Research Council of Canada ) using the protocols described elsewhere[51] . At 24 hours post transfection , cells were either seeded onto polylysine-coated glass coverslips and cultured for 24 hours for imaging , or fed with Difco yeastolate cell culture supplement ( BD Biosciences ) . Cell culture media were collected and whole cell lysates were prepared 2 , 4 , and 7 days post transfection . At 48 hrs post transfection , cells were fixed with 4% paraformaldehyde in 0 . 1 M sodium phosphate , pH 7 . 2 , for 30 minutes at room temperature . After a wash in PBS containing 0 . 1 M glycine , the fixed cells were incubated with permeabilization buffer ( PBS containing 0 . 4% saponin , 1% BSA , 5% fish gelatin ) for 15 minutes , followed by incubation with primary antibody in permeabilization buffer for 60 min . Primary antibodies included anti-IL33 mature domain ( R&D Systems ) , anti-FLAG ( clone M2 , Amgen ) , anti-GAPDH ( clone 6C5 , Amgen ) , anti-gianin ( Covance ) and anti-GM130 ( BD Transduction Lab ) . After 3 washes in permeabilization buffer , the cells were incubated with Alexa Fluor 488- or 594-conjugated secondary antibody in permeabilization buffer for 60 minutes . Slides were analyzed using a Nikon Eclipse 80i microscope using a 100× or 60× CFI Plan Apo oil objective lens . Images were acquired using a Cool SNAP HQ2 digital camera ( Photometrics ) and Nikon Elements imaging software . Harvested cell culture media and processed cell pellets were heated for 5 min at 90°C in lithium dodecyl sulfate sample buffer ( Life Technologies ) containing 5% ( v/v ) beta-mercaptoethanol . NuPAGE 4–12% Bis–Tris gradient gel and the accompanying running buffer system ( both from Life Technologies ) were used to perform SDS-PAGE . Resolved proteins were electrotransferred to a nitrocellulose membrane , blocked with fluorescent Western blocking buffer ( Rockland ) , and probed with primary antibodies ( described above ) . After 3–4 washes in PBS containing 0 . 05% ( v/v ) Tween-20 , the nitrocellulose membranes were incubated with AlexaFluor 680- conjugated secondary antibodies ( Life Technologies ) , followed by 2–3 additional washing steps in PBS containing 0 . 05% ( v/v ) Tween-20 . The fluorescent Western images were acquired by using an Odyssey infrared imaging system from LI-COR Biosciences . IL-33 was cloned into the pET24a expression plasmid in frame with an amino terminus poly-His tag and thrombin cleavage site such that thrombin cleavage would release IL-33 proteins corresponding to residues 95–270 ( wild type ) or 95–204 ( mutant ) . For IL-3395–270 , following E . coli culture , cell pellets were lysed and the supernatants were collected and purified on a nickel HisTrap column ( GE Healthcare Life Sciences ) . The material was eluted from the column using an imidazole gradient . Appropriate fractions were pooled and further purified by preparative size exclusion chromatography ( SEC ) using a Superdex 75 column ( GE Healthcare Life Sciences ) with PBS , pH 7 . 2 , 1 mM DTT as the running buffer . Recovered material was cleaved using the Thrombin CleanCleave Kit ( Sigma ) with a 1 hour incubation at 4°C . Preparative SEC was used to remove the free His tag and any aggregated material , followed by an additional SEC step to further reduce endotoxin contamination . IL-3395–270 was formulated in PBS , pH 7 . 2 , 1 mM DTT , 1 mM EDTA and filtered through a 0 . 2 μm filter . Endotoxin was undetectable . IL-3395–204 was not recoverable from the cell pellet supernatant due to low expression in the soluble fraction . Instead , inclusion bodies were solubilized 1/10 ( w/v ) with 8 M guanidine , 50 mM Tris , 8mM DTT , pH 9 . 0 for 1 hour . This was followed by dilution 1/25 ( v/v ) with PBS buffer , pH 7 . 6 and the material was concentrated and loaded onto a Superdex 75 column using PBS , pH 7 . 2 as the running buffer . The huIL-33 peak was then buffer-exchanged into 1X thrombin cleavage buffer ( 50 mM Tris-HCl , pH 8 . 0 , 100 mM CaCl2 ) and concentrated to 1 mg/mL . 0 . 1 mL of thrombin agarose resin ( Sigma ) was added to 1 mg of huIL-33 and rotated at 4°C for 1 hour . Cleaved huIL-33 was then passed over a HisTrap column to capture free cleaved His tag . The flow-through material was further purified using preparative SEC , as for IL-3395–270 , prior to formulation in PBS , pH 7 . 2 , 1 mM EDTA . Fractions were analyzed by SDS-PAGE and Coomassie staining ( total protein ) or Western blot ( with anti-IL-33 ) before and after thrombin cleavage to confirm cleavage and IL-33 identity ( S4 Fig ) . The structure model of the ST2/IL-33 complex was provided by Lingel et al . [29] . The receptor and ligand are shown with a molecular surface , computed with default parameters in the Molecular Operating Environment ( MOE , Chemical Computing Group Inc . , Montreal , QC , Canada , H3A 2R7 , 2011 . ( n . d . ) ) , with ST2 shown in gold and IL-33 shown in blue , with amino acids 205–270 , which are derived from exon 7 , shown in magenta ( Fig 4A ) . All experiments were performed using a Biacore T200 optical biosensor ( Biacore AB ) . HBS-P buffer ( 10 mM HEPES , pH 7 . 4 , 150 mM NaCl , 0 . 05% Surfactant P20 ) was purchased from Teknova . The CM5 sensor chip , sodium dodecyl sulphate ( SDS ) ( 0 . 5% w/v ) , NaOH ( 50 mM ) , coupling reagents ( N-ethyl-N’- ( 3-dimethylaminopropyl ) -carbodiimide hydrochloride ( EDC ) / N-hydroxy-succinimide ( NHS ) ) , ethanolamine ( 1 . 0 M Ethanolamine-HCl , pH 8 . 5 ) , Acetate 5 . 0 ( 10 mM sodium acetate ) and Glycine 1 . 5 ( 10 mM glycine , pH 1 . 5 ) were purchased from GE Healthcare Life Sciences . The HCl solution ( 100 mM ) was purchased from Bio Rad Labs . The penta-His antibody ( BSA-free ) was purchased from 5Prime . All other reagents were prepared by Amgen . Biosensor analysis was conducted at 25°C in HBS-P buffer . The CM5 sensor chip was conditioned with twice with serial injections ( 30 seconds ) of SDS ( 0 . 1% ) , NaOH ( 10 mM ) , HCl ( 10 mM ) and again with SDS ( 0 . 1% ) at a flow rate of 30 uL/min ( first two injections ) or 60 ul/min ( last three injections ) . The penta-His antibody was diluted ( 200 ug/mL ) in water and then buffer exchanged via desalting spin column ( Zeba , 0 . 5 mL , 40 K ) into Acetate 5 . 0 buffer . This buffer-exchanged antibody was immobilized to flow cells 1 ( 3148 RU ) and 2 ( 7554 RU ) of the sensor chip via standard amine coupling ( EDC/NHS ) and ethanolamine blocking[52] . Human ST2-Flag-His ( 8 ug/mL in HBS-P , Amgen ) was injected ( 300s at 10 uL/min ) over flow cell 2 . This captured between 600 and 900 RU of antibody . After the capture step , the human E . coli-derived IL-33 variants ( 200 nM ) were injected ( 180s , 50 ul/min ) over flow cells 1–2 to observe the association ( 180 s ) of human IL-33 to human ST2 . Each flow cell was then flushed with running buffer to observe the dissociation of human IL-33 ( 300 s ) from the chip surface . Each sample of IL-33 was tested individually as a single replicate . A blank buffer injection was tested before the first sample injection and the surface was regenerated ( 15 ul at 50 uL/min ) with 10 mM glycine pH 1 . 5 and a reloading of ST2 was captured to the chip surface before each sample injection . The data was prepared and analyzed with Scrubber 2 . 0 software ( BioLogic Software Pty Ltd , Campbell , Australia ) as follows . The raw data from each experiment was x and y-axis normalized just prior to the injection of IL-33 and then cropped to include the ST2 capture step and the association/dissociation of IL-33 . LAD2 human mast cells were seeded into 48-well tissue culture plates at 250 , 000 cells/375 μL media ( Stem-Pro-34 serum-free media ( Life Technologies , Grand Island , NY , USA ) supplemented with 2 mM L-glutamine , 100 IU/ml penicillin , 50 μg/ml streptomycin ( complete SFM ) and 100ng/ml SCF ( Peprotech ) . The following day cells were stimulated with medium only or increasing concentrations ( 10 pg/mL– 100 ng/mL ) of wild-type ( 95–270 ) or mutant ( 95–204 ) IL-33 for 24 hours at 37°C . Culture supernatants were then collected followed by removal of cell debris by centrifugation and stored at -80°C until ready for use . The concentration CCL1 in the collected supernatants was determined using an R&D Human CCL1 DuoSet ELISA kit under manufacturer’s specifications . To demonstrate the ST2-dependence of the assay , stimulations were performed as described with the addition of a final concentration of 20 ug/mL human IgG2 isotype control ( Amgen ) or human anti-huST2 blocking antibody ( Amgen ) 30 minutes prior to addition of 100 ng/mL IL-33 . Highly purified human CD4+ T cells were seeded at 200 , 000 cells/well in 96-well round bottom plates . E . coli-produced human IL-33 , either beginning at amino acid 95 , as described above , or using IL-33 ( 112–270 ) ( R&D Systems ) was either titrated as a dose-response or added to a final concentration of 10ng/mL along with human IL-12 and human IL-2 , each at a final concentration of 10ng/mL . For ST2 blocking , anti-huST2 IgG2 or IgG2 control was added to a final concentration of 25 ug/mL 30 minutes prior to addition of cytokines . Cultures were incubated for 72hrs at 37°C in a 5% CO2 incubator . Cell-free supernatants were collected and IFN-γ was quantitated by ELISA ( R&D Systems ) . Blood was collected from 10–12 week old wild-type and il33-deficient Bl/6 under isoflurane anesthesia and analyzed on a Siemens Advia 120 hematology analyzer with mouse-specific software . Blood smears were air-dried and stained with Wright-Giemsa . Automated differentials generated on the Advia 120 were confirmed by slide evaluation for any sample with eosinophil counts greater than 4% or with evidence of platelet clumps on the Advia scatterplots or on the blood smear . Predicted loss-of-function variants in IL33 and their genotype counts in the Exome Aggregation Consortium ( ExAC ) database were retrieved from http://exac . broadinstitute . org/gene/ENSG00000137033 , accessed November 24 , 2015 . LD Score database ( accessed 23 June 2015 ) , ftp://atguftp . mgh . harvard . edu/brendan/1k_eur_r2_hm3snps_se_weights . RDS | Only a few genes have been found to play a role in asthma . These include the genes IL33 and IL1RL1 , and sequence variants in the human genome close to these genes were initially found to affect the number of eosinophils , cells that play a role in inflammation of the airways in asthma . Based on this knowledge , we decided to use high resolution sequencing technology to search for variants in these genes that cause changes in structure and function of the proteins they encode . We found a rare ( 0 . 65% ) sequence variant in the IL33 gene , that causes less production of the IL33 protein and some of the protein formed lacks the capacity to bind to its receptor on cells and promote inflammation . This rare mutation causes reduced number of eosinophils in blood and protects against asthma . These results suggest that drugs that could interfere with the inflammatory activity of the IL33 protein may be beneficial for treatment of asthma . | [
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"pul... | 2017 | A rare IL33 loss-of-function mutation reduces blood eosinophil counts and protects from asthma |
Immune responses and DNA damage repair are two fundamental processes that have been characterized extensively , but the links between them remain largely unknown . We report that multiple bacterial , fungal and oomycete plant pathogen species induce double-strand breaks ( DSBs ) in host plant DNA . DNA damage detected by histone γ-H2AX abundance or DNA comet assays arose hours before the disease-associated necrosis caused by virulent Pseudomonas syringae pv . tomato . Necrosis-inducing paraquat did not cause detectable DSBs at similar stages after application . Non-pathogenic E . coli and Pseudomonas fluorescens bacteria also did not induce DSBs . Elevation of reactive oxygen species ( ROS ) is common during plant immune responses , ROS are known DNA damaging agents , and the infection-induced host ROS burst has been implicated as a cause of host DNA damage in animal studies . However , we found that DSB formation in Arabidopsis in response to P . syringae infection still occurs in the absence of the infection-associated oxidative burst mediated by AtrbohD and AtrbohF . Plant MAMP receptor stimulation or application of defense-activating salicylic acid or jasmonic acid failed to induce a detectable level of DSBs in the absence of introduced pathogens , further suggesting that pathogen activities beyond host defense activation cause infection-induced DNA damage . The abundance of infection-induced DSBs was reduced by salicylic acid and NPR1-mediated defenses , and by certain R gene-mediated defenses . Infection-induced formation of γ-H2AX still occurred in Arabidopsis atr/atm double mutants , suggesting the presence of an alternative mediator of pathogen-induced H2AX phosphorylation . In summary , pathogenic microorganisms can induce plant DNA damage . Plant defense mechanisms help to suppress rather than promote this damage , thereby contributing to the maintenance of genome integrity in somatic tissues .
Organisms continuously encounter many types of DNA damage and have evolved elegant mechanisms to maintain their genomic integrity [1] , [2] . DNA damage can be induced by a variety of exogenous stresses such as ultraviolet light or genotoxic chemicals , and by endogenous insults such as reactive oxygen species and DNA replication errors [1]–[3] . DNA double-strand breaks ( DSBs ) can trigger cell cycle arrest and programmed cell death , and are among the most serious types of DNA damage . Surveillance for DSBs and signaling in response to DSBs are therefore critical for cells to orchestrate DNA repair pathways not only in the germ line but also in somatic tissues , to sustain genome stability and survival of the organism [1] , [2] . Pathogen management of their own ( microbial ) DNA integrity has a long history of study [4] , as does the study of interactions between viruses and host DNA damage repair processes [5] . There have been far fewer reports or studies of damage to host DNA caused by microbial pathogens . However , it has recently been established that microbial pathogens of animals can induce host DNA damage [6]–[12] . Multicellular organisms are continuously exposed to microbes and have developed effective immune systems to resist attacks by pathogens [13] , [14] . Organisms are challenged to balance the health-promoting impacts of antimicrobial responses and the potential toxic effects on surrounding tissue caused by excessive or chronic inflammation . In animal pathogenesis studies , carcinogenic effects of innate immune responses mediated by Toll-like receptors have been reported [15] . An oxidative burst is a common element of plant and animal antimicrobial responses [14] , [16] , [17] , but reactive oxygen species ( ROS ) also have well-known DNA damaging activities [3] , [18] . There is evidence that a significant component of the host genotoxicity of certain microbial infections in animals is attributable to host-generated ROS [8]–[11] . In plants , the relative contribution of the defense-associated ROS burst to pathogen restriction as opposed to genotoxicity ( DNA damage ) remains to be explored . Plant DNA damage repair pathways have received extensive study [19] , [20] . Although the tie-ins of plant DNA damage to other aspects of organismal physiology are often plant-specific , many elements of the plant DNA damage repair pathways resemble those of animals due to conservation of core DNA damage repair mechanisms [19] , [20] . A hallmark DNA damage response conserved across multicellular organisms is the rapid phosphorylation of histone variant H2AX in the chromatin that flanks break sites , forming γ-H2AX [21] , [22] . The phosphatidylinositol 3-kinase-like kinases ATM ( ataxia telangiectasia mutated ) and ATR ( ataxia telangiectasia mutated and Rad3-related ) are central mediators of these and other cellular responses to DSBs [23]–[25] . γ-H2AX is one of the most sensitive indicators of DNA DSBs [26] . Associations between DNA damage and plant immune responses have been identified . Exposure of plants to the salicylic acid analogs BTH or INA , or inoculation with the oomycete pathogen H . arabidopsidis , was shown to increase the frequency of somatic homologous recombination [27] . Infection of tobacco and Arabidopsis leaves with either tobacco masaic virus or oilseed rape mosaic virus ( ORMV ) results in both local and systemic increases in homologous recombination frequency , and ORMV inoculations elicited DNA damage [28] , [29] . DNA damaging agents induce pathogenesis-related gene expression [30] , [31] , and the DNA damage repair proteins RAD51D , BRCA2 and SSN2 are now known to be involved in regulation of gene expression during plant immune responses [32]–[34] . Poly ( ADP-ribosyl ) ation , a process frequently associated with DNA damage repair , has been shown to impact plant responses to microbial pathogens [35] , [36] . Lastly , during the programmed cell death of the hypersensitive response to pathogens expressing effectors ( Avr gene products ) recognized by a corresponding plant R gene product , increased signal in TUNEL ( terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling ) assays can be observed , as is also common in animal cell apoptosis [37] , [38] . In spite of the above , DNA damage during plant interactions with virulent pathogens is largely undescribed , and whether DNA damage arises during responses activated by core plant defense mediators such as salicylic acid , jasmonic acid or activated microbe-associated molecular pattern ( MAMP ) receptors also is not known . Here , we demonstrate that diverse microbial pathogens induce DNA double-strand breaks in host plant genomes . Surprisingly ( in light of the mutagenic nature of ROS in many settings ) , infection-associated AtrbohD- and AtrbohF-dependent ROS production is not required for pathogen-induced elevation of γ-H2AX . Instead , we find that plant antimicrobial defense mechanisms contribute to suppressed formation and/or rapid repair of γ-H2AX-associated lesions . DNA DSB damage is apparently a common aspect of plant pathogenesis by virulent microbial pathogens , and protection against DNA damage is an important feature of effective plant disease resistance .
To investigate interactions between pathogen infection and genome stress , we used γ-H2AX [21] , [26] to monitor the extent of DNA damage in response to bacterial pathogens in Arabidopsis . Wild-type Arabidopsis Col-0 plants were challenged with virulent Pseudomonas syringae pv . tomato ( Pst ) strain DC3000 and levels of γ-H2AX at various time points after infection were determined using an anti-γ-H2AX antibody . Accumulation of γ-H2AX was readily detected as early as 2 h after infiltration , with a progressive increase at the indicated time points after infiltration ( Figures 1A and 1B ) . No γ-H2AX accumulation was observed after mock treatment with 10 mM MgCl2 , suggesting that the elevated levels of DNA damage were triggered by the pathogen rather than by any physical perturbations associated with plant inoculation . We also measured the phosphorylation of H2AX in response to Pst DC3000 ( avrRpt2 ) , a strain that is isogenic with Pst DC3000 except for its expression of the effector AvrRpt2 . AvrRpt2 induces a strong host resistance response ( an R gene-mediated incompatible interaction ) in plants that express the resistance gene RPS2 [39] , [40] . Across four independent experiments , the induction of γ-H2AX levels between 2 and 48 h after inoculation was relatively similar between Pst DC3000 ( avrRpt2 ) and Pst DC3000 . At the early 2 , 4 and 8 h time points , minor differences between the two strains in the γ-H2AX levels induced at the same time after inoculation were not reproducible across experiments . To determine whether the high γ-H2AX accumulation after infection is related to the suite of virulence-promoting bacterial effectors delivered via type III secretion , Arabidopsis Col-0 plants were infected with Pst DC3000 ( ΔhrcC ) that carries a deletion in the hrcC gene that encodes a key component of the type III secretion system [41] . Decreased γ-H2AX accumulation was observed with Pst DC3000 ( ΔhrcC ) 4 to 8 h after infiltration compared with virulent Pst DC3000 treatment , and the difference became statistically significant at 24 and 48 h after infiltration ( Figures 1A , 1B and S1 ) . As points of reference , our group and other laboratories have previously found that the onset of Pst DC3000-induced plant cell death is not observed until ∼16–24 h after infection , and Pst DC3000 ( avrRpt2 ) -induced hypersensitive response cell death also occurs relatively late , with an onset ∼14–18 h after inoculation [e . g . ] , [ 42] , [43]–[45] . Electrolyte leakage ( an early sign of the resistance response ) is first detected 5–6 h after inoculation of resistant Arabidopsis with Pst DC3000 ( avrRpt2 ) [46] , and with Pst DC3000 , cytosolic Ca2+ increases are not observed for at least 150 min after inoculation [47] , well after the 2 h time point at which γ-H2AX accumulation is first detected ( Figure 1A ) . Independent evidence that P . syringae pv . tomato infection increases DSBs in Arabidopsis was obtained in comet assays ( Figure 1C and 1D ) . Comet assays measure DNA damage by directly monitoring the increased capacity of fractured DNA to electrophoretically migrate out of isolated nuclei [48] , [49] . The roughly comparable levels of DNA damage caused by Pst DC3000 ( avrRpt2 ) and Pst DC3000 may be a result of infiltration directly into the leaf interior of the relatively high ( 1×107 cfu/ml ) and equivalent populations of the two pathogen strains . However , these initial results also suggested that stress may be imposed on plant DNA by plant defense responses . A number of non-pathogenic bacteria were then tested for their ability to induce DNA DSBs in the host plant . When wild-type Arabidopsis Col-0 plants were infiltrated with E . coli strain DH5α at a dose similar to the above Pst inoculations , no γ-H2AX was observed ( Figure 2A ) . Three plant-associated bacterial strains that are not pathogenic on Arabidopsis were also tested: P . syringae pv . glycinea ( Psg ) is a soybean pathogen that multiplies and produces few visible symptoms when introduced into Arabidopsis leaf mesophyll [50] , [51] , Psg ( avrRpt2 ) expresses the effector AvrRpt2 and induces R gene-mediated defenses in Arabidopsis Col-0 despite the low virulence of the parent strain [44] and P . fluorescens WCS417r is a biological control strain that has been widely used to trigger induced systemic resistance ( ISR ) in plants [52] , [53] . Similar to E . coli strain DH5α , P . fluorescens WCS417r did not induce detectable levels of γ-H2AX . However , Psg and Psg ( avrRpt2 ) caused elevated phosphorylation of H2AX ( Figure 2B ) . To compare the extent of Pst-induced DSB damage to other known stress conditions , Col-0 plants were irradiated with gamma-rays . Phosphorylation of H2AX was readily detected after exposure to 100 Gy of ionizing gamma irradiation ( Figure 2C ) . Interestingly , the γ-H2AX band induced by Pst migrated slightly slower in SDS-PAGE than that induced by gamma-rays , suggesting that additional sites may be phosphorylated upon pathogen infection other than the highly conserved serine at the C-terminus of H2AX protein ( Figure 2C ) . Similarly , when plants were treated with bleomycin , a DNA damage agent that generates DNA DSBs , accumulation of γ-H2AX was induced and a small size difference was observed when compared with the γ-H2AX triggered by Pst ( Figure 2D ) . To investigate whether DSBs are induced by pathogens other than bacteria , and in other plant species , we examined the level of γ-H2AX in potato and tomato in response to strains of the oomycete pathogen Phytophthora infestans . Katahdin , a potato variety susceptible to late blight disease , was challenged with a US23 isolate of P . infestans . Figure 3 shows that accumulation of γ-H2AX was induced 3 days after inoculation and significantly increased between 5–7 days after inoculation , a time coincident with visible lesion formation . Extensive γ-H2AX accumulation was similarly detected in tomato variety Bonny Best after inoculation with a US22 isolate of P . infestans that is virulent on Bonny Best ( Figure 3 ) . At late time points after compatible interactions of potato or tomato with P . infestans ( i . e . , 7 days post-infection ) an additional more slowly migrating band was also detected with the anti-γ-H2AX antibody ( Figures 3A and 3B ) . We speculate that H2AX may by that point carry other post-translational modifications [54] , [55] . For example , ionizing radiation can induce formation of a ubiquitinated H2AX that migrates at a higher molecular weight and is detected using anti-γ-H2AX antibodies [56] . Incompatible interactions were also tested with these pathogens , to determine if a net increase or decrease in DNA damage is observed relative to compatible interactions in which R gene-mediated defenses are not prominent . US23 isolates of P . infestans are recognized by the product of the RB resistance gene , and RB mediates a mild hypersensitive response in potato [57] , [58] . Much less accumulation of γ-H2AX was detected when the US23 isolate infected the resistant Katahdin SP951 transgenic potato line ( Figure 3A ) , relative to Katahdin lines that lack the single transgene copy of RB . In tomato as well ( Figure 3B ) , significantly less γ-H2AX accumulation was observed when the above-noted US22 P . infestans isolate was sprayed onto the tomato variety Mountain Magic that carries the Ph-2 and Ph-3 loci that confer resistance to P . infestans [59] . This is consistent with the finding that TMV triggered systemic activation of homologous recombination is blocked when resistance gene N is absent [28] . The inducibility of DSBs by microbial plant pathogens was further examined in Arabidopsis infected by the necrotrophic fungal pathogen Botrytis cinerea . γ-H2AX was induced and its presence sustained between 2 and 4 days after inoculation , and then γ-H2AX increased significantly on the 5th day after inoculation ( Figure 3C ) . Host cell death and leaf collapse also became prevalent on the 5th day after inoculation . Virulent P . syringae , P . infestans and B . cinerea all eventually cause tissue necrosis and plant cell death . To investigate the hypothesis that the elevation of DSBs in plants infected with these virulent pathogens is an event common to any dying plant cells , experiments were conducted with paraquat ( methyl viologen ) . Paraquat is an herbicide that blocks photosynthetic electron transport and causes excess superoxide generation leading to plant cell death [60] , but we found no evidence of strong DSB induction by paraquat . Paraquat was applied to Arabidopsis in the same experiment described above in which Botrytis cinerea induced γ-H2AX accumulation prior to the appearance of necrotic lesions . With application of 50 µM paraquat , leaves started to wilt 8 h after spraying and developed extensive necrotic lesions by 24 h , but only minimal increases in γ-H2AX abundance were observed ( Figure 3C ) . When 5 µM paraquat was misted onto Arabidopsis leaves in a separate experiment , multiple isolated necrotic lesions formed over the next few days but no elevation of γ-H2AX was observed ( in contrast to the Pst-inoculated positive control; Figure S2 ) . Elevated ROS are a primary feature of plant defense responses and a possible source of the host DNA damage associated with pathogen infections [3] , [17] , [18] , [61] , [62] . Virulent P . syringae elicit a rapid but transient accumulation of ROS in plants over approximately the first half hour after infection , while P . syringae expressing a recognized avirulence gene induce the first wave as well as a second wave of elevated ROS that is more massive and prolonged [16] . However , ROS production induced by bacterial and oomycete pathogens is nearly eliminated in Arabidopsis atrbohD single and atrbohDF double mutants with disruptions in the corresponding NADPH oxidase catalytic subunits [17] , [63] . We examined the γ-H2AX level in response to pathogen infections in the atrbohD and atrbohDF mutant plants . There was no obvious reduction of γ-H2AX ( Figure 4 ) , in response to either virulent Pst DC3000 or avirulent Pst DC3000 ( avrRpt2 ) , indicating that pathogen-triggered NADPH-derived ROS production is not the primary cause or a required component of the formation of pathogen-induced DSBs . Salicylic acid ( SA ) is a key signaling molecule that activates defense responses against pathogens in plants , including cellular redox shifts and other physiological responses that could lead to DNA damage [64]–[66] . We investigated if SA induces γ-H2AX accumulation . After wild-type Arabidopsis plants were sprayed with 1 mM SA ( a defense-inducing level [67] ) , no γ-H2AX accumulation was detected at time points up to 48 h after SA treatment ( Figure S3 ) . To test if SA-mediated defenses reduce pathogen-induced DNA damage , plants were treated with 1 mM SA for 1 day to induce systemic acquired resistance ( SAR ) , then vacuum-inoculated with virulent Pst DC3000 . Pretreatment with SA strongly reduced the γ-H2AX accumulation caused by Pst DC3000 , compared with H2O-pretreated controls ( Figures 5A and S4A ) . The finding that SAR reduces Pst-induced DNA damage prompted us to investigate the accumulation of γ-H2AX in the SAR-deficient Arabidopsis mutant npr1 . We detected increased γ-H2AX accumulation induced by Pst DC3000 in the npr1mutant ( Figures 5B and S4B ) . These data indicate that , rather than causing greater DNA damage , SA-mediated signaling reduces Pst-induced damage to host DNA . Other defense mutants that exhibit altered SA perception and/or signaling were also examined . Arabidopsis cpr5 plants exhibit constitutive defense responses such as PR gene expression , and constitutively elevated levels of SA [68] , [69] . A low but constitutive presence of γ-H2AX was detected in the cpr5 mutant prior to pathogen infection ( Figures 5C and S4C ) . In the Arabidopsis SA signaling mutants eds1 and pad4 , and in the SA synthesis mutant sid2 , no detectable changes of γ-H2AX accumulation after Pst infection were observed ( Figures 5D and S4D ) . We also tested the plant defense signaling molecule jasmonic acid [66] . Similar to SA , jasmonic acid did not induce γ-H2AX accumulation ( Figure S3 ) . We then investigated whether pathogen-free activation of MAMP-induced defense signaling induces γ-H2AX accumulation . The response was monitored from 15 min . to 2 h , which is beyond the half-hour time period when the ROS burst , MAP kinase activation , ethylene synthesis , changes in gene expression and the other primary responses to MAMPs arise [70] . When wild-type Arabidopsis Col-0 seedlings were exposed to 0 . 1 µM of the bacterial EF-Tu epitope elf18 ( a dose sufficient to saturate induction of most elf18-induced plant defense responses [71] ) , no γ-H2AX accumulation was detected ( Figure S5A ) . The ability of MAMPs to induce γ-H2AX accumulation was also investigated using the flagellin epitope flg22 . Again , no γ-H2AX accumulation was observed after a high-dose 1 µM flg22 treatment ( Figure S5B ) , suggesting that typical MAMP-induced plant defense responses do not in general induce sufficient DNA DSBs to cause detectable phosphorylation of H2AX . The DNA damage ( DNA protection ) proteins SNI1 , SSN2 , and RAD51D have been shown to play roles in both homologous recombination and defense gene transcription [32] , [34] . To test for a possible contribution of these proteins to prevention or reduction of Pst-induced DNA damage , the level of γ-H2AX in response to Pst was examined in the respective Arabidopsis Col-0 mutants . SNI1 is a subunit of the Structural Maintenance of Chromosome ( SMC ) 5/6 complex involved in DNA damage response [72] and functions as a negative regulator of some plant defense responses [32]–[34] . The sni1 single mutant was recently reported to exhibit a constitutive DNA damage response [72] . Consistent with this , we observed phosphorylation of H2AX in -sni1 plants in the absence of pathogen infection ( Figures 6 and S6A ) . However , no reproducibly significant changes in the time course of Pst-induced γ-H2AX were observed . SSN2 is a SWIM-domain containing protein that acts at early steps of homologous recombination , and the ssn2 mutation partially suppresses sni1 [34] , [73] . Rad51D complexes with SSN2 and SNI1 during homologous recombination and the rad51d mutation also suppresses sni1 [32] . With rad51d and ssn2 single mutants , we found that the time course of Pst-induced γ-H2AX again was comparable to that in wild-type plants ( Figures 6 and S6A ) . When the rad51d mutant was grown under short-day conditions , it displayed a spontaneous lesion phenotype and exhibited elevated levels of γ-H2AX without pathogen infection ( Figures 6 and S6B ) . The accumulation of γ-H2AX after exposure to ionizing radiation is largely dependent on ATM in Arabidopsis , although ATR can contribute to formation of DSBs to a lesser extent [25] . To determine whether Arabidopsis ATR or ATM is required for the phosphorylation of H2AX in response to pathogen infection , we examined γ-H2AX levels in atr and atm single mutants and in atr atm double mutant plants . We used SALK T-DNA insertion lines atr-2 and atm-2 in the Col-0 background , that carry an insertion in exon 10 of ATR and intron 64 of ATM respectively , and have been characterized previously [74] , [75] . Similar levels of γ-H2AX were induced by virulent Pst DC3000 in the atr-2 and atm-2 single mutants and the atr-2 atm-2 double mutants compared with wild-type Col-0 ( Figure 7A ) . To verify this result we also tested atr-3 and atm-1 , which carry in the Ws genetic background a T-DNA insertion in the highly conserved C-terminal kinase domain ( atr-3 ) or in the 3′ region of the gene ( atm-1 ) , and both likely act as null alleles [74] . γ-H2AX induction after Pst infection was detected in atr-3 and atm-1 single mutants and in atr-3 atm-1 double mutants at comparable levels to wild-type ( Figure S7 ) . Similar results were obtained in two independent experiments with the Col atr and atm mutants , and in three independent experiments with the Ws atr and atm mutants . These experiments are consistent with the slightly larger γ-H2AX band observed after Pst treatment as opposed to gamma-rays or bleomycin ( Figure 2 ) , and suggest that protein kinases other than ATR and ATM are engaged to mediate pathogen-induced γ-H2AX formation . The response of atr-2 and atm-2 mutants to pathogen infection was examined using Pst DC3000 . The atr-2 atm-2 double mutants were more susceptible to infection than wild type plants whereas the atr-2 and atm-2 single mutants were similar to wild type ( Figure 7B ) , indicating that ATR and ATM play overlapping roles in basal defense . To test whether ATR and ATM are required for effector triggered immunity , atr-2 and atm-2 lines were inoculated with the avirulent pathogen Pst DC3000 ( avrRpt2 ) . As shown in Figure 7B , the atr-2 atm-2 double mutants exhibited enhanced susceptibility . Taken together with previously published findings [74]–[78] , these bacterial growth data provide another example that Arabidopsis ATR and ATM can play broad roles in plant development , DNA damage repair , and now , plant immunity .
The present study discovered that host DNA damage is induced , both in the model organism Arabidopsis thaliana and in tomato and potato crop plants , in response to plant pathogens with diverse life styles including a hemibiotrophic bacterial species , an oomycete and a necrotrophic fungus . Similar or reduced levels of DNA DSBs were induced during incompatible interactions when compared with compatible interactions . Plant defense mediators such as ROS , jasmonic acid and MAMP receptors did not on their own increase DSBs , and SA-mediated defenses reduced rather than elevated pathogen-induced DNA damage . These findings provide a new type of evidence of links between the plant immune and DNA damage responses . Prevention and repair of DNA damage is needed , to a greater extent than was previously understood , as an element of the plant defense response . Previously discovered associations between DNA damage and plant immune responses were noted in the introduction [27]–[38] . In addition , Yan et al . very recently reported that salicylic acid activates DNA damage responses as part of the plant immune response [72] . Similar associations have been established in animal systems . For example , DNA damage can regulate human inflammatory responses through activation of the tumor suppressor p53 and elevated expression of Toll-like receptors [79] , and the DNA damage response induces expression of innate immune system ligands of the NKG2D receptor [80] . The fact that DNA damage induces immune responses suggests that multicellular organisms associate DNA damage with , among other things , microbial infections . The present work and [29] provide experimental evidence for a key part of this arrangement , by showing that diverse plant pathogens elicit plant DNA damage . One point of note is the short time after Pst infection at which γ-H2AX becomes apparent . The flagellin or EF-Tu MAMPs flg22 or elf18 did not elicit detectable DNA DSBs , but γ-H2AX was reproducibly present within 2 h after Pst infection . The pathbreaking findings of [27] , [28] indicate that pathogens do not even need to be physically present at a cell for that cell to experience pathogenesis-associated genome stress . They measured homologous recombination rather than directly monitoring DNA damage , but as one example , those researchers reported increased homologous recombination in non-inoculated leaves as early as 8 h after inoculation of tobacco with Tobacco mosaic virus [28] . This is faster than the virus itself moves . The SA analogs BTH or INA induced a 1 . 5 to 7 fold increase of homologous recombination frequency 14 days after chemical treatment [28] , while we did not observe increases in DNA DSBs after treatment with SA or JA . However , we examined the level of γ-H2AX at much earlier times points 12 , 24 and 48 h after SA or JA application . Yan et al . reported , from comet assays , that SA can induce DNA damage in wild-type and npr1 mutant plants [72] . This discrepancy between the two studies may have been caused by the use of different DNA damage detection methods or by differences in plant growth and treatment conditions . The main conclusion of Yan et al . [72] , that SA activates DNA damage responses to potentiate plant immunity , is highly consistent with our main finding that pathogenic microorganisms can induce plant DNA damage and that plant defense mechanisms help to suppress rather than promote this damage . Production of ROS is one of the earliest cellular responses of plants to pathogens and is also a common response to pathogens in animals [14] , [16] , [17] . The genotoxicity of certain microbial infections in animals has been attributed to host-generated ROS [8]–[11] . We found that Arabidopsis rbohD and rbohDF mutants that are defective in pathogenesis-induced ROS burst still produced extensive pathogenesis-induced DSBs . In addition , the strong ROS inducer paraquat failed to induce extensive DSBs . Furthermore , despite the contrasting induction of a less strong early ROS burst in response to virulent pathogens vs . the combined early ROS burst and a stronger and more prolonged later ROS burst in response to avirulent pathogens [16] , both types of Pst DC3000 pathogens induced similar formation of DSBs . Recognition of diverse MAMPs including both flg22 and elf18 also triggers an oxidative burst [70] but failed to induce the generation of DSBs . Collectively , these findings indicate that ROS are not key mediators required for pathogen induction of DSBs in the plant pathosystems that we analyzed . A recent paper has analogously suggested that the host ROS triggered by H . pylori infection is not required for DSB formation in animals [7] . Because in our studies the MAMPs flg22 and elf18 , the signaling molecules salicylic acid and jasmonic acid , and ROS-generating paraquat each failed to induce detectable level of DSBs , we postulate that direct interaction with one or more pathogen-derived effectors , toxins , or other molecules is required for pathogen induction of DNA damage . Type-III secretion-defective Pst DC3000 ΔhrcC induced fewer DSBs , suggesting a contribution of one or more Type III-secreted effectors to bacteria-induced plant DNA damage . However , that contribution may be direct , or indirect through effector elicitation of specific host responses , or indirect due to general enhancement of pathogen population sizes . The more significant result of the DC3000 ΔhrcC experiments may be that substantial DSB induction was evident even when the Type-III secretion system was disabled . In the present study , host DNA DSB induction was observed following infection by plant pathogens but not after introduction of non-pathogenic bacteria . Prior work provides some context for this result . For example , the non-pathogenic bacteria E . coli DH5α and P . fluorescens Pf101 elicit defense transcript accumulation and phytoalexin biosynthesis in bean [81] . Inoculation of Arabidopsis roots with P . fluorescens strain WCS417r ( the strain used in this study ) activates induced systemic resistance , which is independent of SA accumulation and pathogenesis-related ( PR ) gene activation but primes plants to respond faster or stronger to pathogen attack [82] , [83] . Induction of those responses , then , is not likely to elicit DNA DSBs , although the failure of those non-pathogenic bacteria to induce DNA DSBs may alternatively be attributable to the weak defense response they trigger . In contrast to P . fluorescens WCS417r , the soybean pathogen Psg was previously shown to trigger a marked systemic increase of SA level and PR gene expression in Arabidopsis , leading to elevated systemic resistance to secondary infection , although to a lesser extent compared to those induced by virulent Pst and avirulent Pst avrRpm1 [50] . So although we do not yet know the mechanism of DNA DSB induction by plant pathogens , and did not observed its induction by ROS , SA , JA , or MAMPs , strength of host defense induction is a feature that correlates with the DNA DSB-inducing behavior of the strains we studied . Recent work with Psg on Arabidopsis reminds us that molecular mechanisms of non-host resistance against different plant pathogens can be distinct . The Arabidopsis non-host resistance gene PSS1 confers a new form of non-host resistance against both a hemibiotrophic oomycete pathogen , P . sojae and a necrotrophic fungal pathogen , F . virguliforme , but not the bacterial pathogen Psg [84] . ATM and ATR are the two primary known signal transducers of DNA breakage , and they initiate a phosphorylation-mediated signal transduction cascade that leads to cell-cycle arrest and repair of DSBs [23]–[25] . In addition to ATM and ATR , a related mammalian enzyme , the DNA-dependent protein kinase ( DNA-PK ) , is capable of phosphorylating H2AX in response to DSBs [85] . The relative roles of ATM and ATR in DSB-dependent γ-H2AX induction have been debated , and apparently vary depending on the biological context . For example , Kuhne et al . provided evidence that ATM contributes to ionizing radiation-induced γ-H2AX formation in mouse fibroblasts [86] , whereas a separate report suggested that ATM was not required or played minor role in ionizing radiation-dependent γ-H2AX accumulation [87] . In Arabidopsis the accumulation of γ-H2AX in response to ionizing radiation-induced DSBs is dependent on both ATM and ATR , with a predominant role for ATM [25] . We found that pathogen-induced γ-H2AX accumulation was not reduced in two different Arabidopsis atr atm double mutant lines . Our finding unsettles the concept that only ATR and ATM carry out this process in plants . Because no obvious homologs of DNA-PK are present in nonvertebrates , our experiments suggest that plants have one or more kinases other than ATM , ATR or DNA-PK that can phosphorylate H2AX , and which do so in response to pathogen infection . This finding of pathogen-induced γ-H2AX accumulation in Arabidopsis atr atm double mutants is supported by a recent discovery made using primary cultures of human renal proximal tubule epithelial cells , where knockdown of all three major phosphatidylinositol 3-kinase-like kinases ( ATM , ATR , and DNA-PKcs ) did not abolish the activation of γ-H2AX during viral infection by BKPyV [88] . Viral infection by BKPyV did cause severe DNA damage in the absence of ATM or ATR [88] , and as previously noted , numerous animal and plant studies have shown that ATM and ATR play central roles in DNA damage repair [19] , [24] , [25] . Hence it is not overly surprising that Arabidopsis atr atm double mutant plants exhibit heightened disease susceptibility , even though ATM and ATR are not the sole means through which plant H2AX can be phosphorylated after pathogen infection . The discovery of pathogen-induced plant DNA damage [present study and 29] opens intriguing avenues for future study . For example , research to pinpoint pathogenesis-induced DSB sites may reveal if preferential sites exist . Investigation of the pathogen factors or pathogen-induced plant factors that lead to infection-associated DNA damage will be a priority , and this may lend insight into disease management mechanisms that can protect the genome from the damage induced by pathogens . The subject has clear implications for improved crop productivity under conditions of biotic stress [19] , [20] .
Arabidopsis plants were grown at 22°C under 9-h light/15-h cycles in Fison's Sunshine Mix #1 . The rad51d mutant line was also grown at 16-h light/8-h dark cycles . Five-week-old Arabidopsis plants were typically used in various treatments unless otherwise indicated . Pseudomonas syringae pv . tomato bacterial strains used in this study were Pst DC3000 , Pst DC3000 ( avrRpt2 ) [39] and Pst DC3000 ( ΔhrcC ) [41] . Nonpathogenic bacteria strains included in this study were E . coli DH5α grown on LB plates , or P . syringae pv . glycinea ( Psg ) , Psg ( avrRpt2 ) [44] or P . fluorescens WCS417r [52] grown on NYGA plates . For DNA damage experiments , above-soil portions of intact plants were briefly inverted into a bacterial solution at 1×107 cfu/ml in 10 mM MgCl2 , bacteria were introduced into leaf mesophyll by vacuum infiltration [89] , plants were returned to their normal growth environment , and samples were collected at the specified time points . For SAR induction , plants were pretreated with 10 mM MgCl2 or 1 mM SA for 1 day followed by vacuum-infiltration with virulent Pst DC3000 at 1×106 cfu/ml . For ionizing radiation , Arabidopsis Col-0 plants were irradiated at 100 Gy with a 137Cs source and collected at indicated times . For bleomycin treatment , Arabidopsis Col-0 plants were incubated with 2 . 5 µg/ml of bleomycin for indicated times . For Botrytis cinerea infection [90] , plants were sprayed with 1×105 spores/ml and samples were collected 1 to 5 days post inoculation . Inoculation of Phytophthora infestans was carried out by spraying plants with sporangial suspensions according to previously described procedures [57] . Potato and tomato plants were infected with US23 or US22 P . infestans isolates , respectively , provided courtesy of Amilcar Sánchez-Pérez and Dennis Halterman . Treatment with paraquat ( methyl viologen; Sigma-Aldrich , St . Louis , MO ) was performed on Arabidopsis plants by spraying an aqueous suspension to run-off at concentrations of 5 or 50 µM . To obtain atr atm double mutants , progeny plants from self-fertilized atr-3/atr-3 , ATM/atm-1 or atr-2/atr-2 , ATM/atm-2 lines [74] , [75] were genotyped by PCR for presence of the relevant T-DNA insertion and separately for absence of the wild-type allele using the methods of http://signal . salk . edu/tdnaprimers . 2 . html . The resulting double mutant lines were observed to be sterile . Five-week-old Arabidopsis seedlings were inoculated with Pst DC3000 or Pst DC3000 ( avrRpt2 ) at 1×105 cfu/ml by infiltration of leaf mesophyll using a 1 cc plastic syringe with no needle or vacuum infiltration of immersed rosette leaves . After 3 days , leaf discs were taken from eight inoculated fully expanded rosette leaves and samples from two leaves were combined to form a single replicate and macerated in 10 mM MgCl2 . The samples were then diluted serially , plated on NYGA plates and colony counts were recorded two days after incubation at 28°C . Histones were extracted from plant leaf tissue nuclear preparations as previously described [25] , [91] . Protein samples were subjected to SDS-PAGE , blotted and immunodetected with rabbit anti-human γ-H2AX antibody at 1∶5000 dilution ( Sigma-Aldrich , St . Louis , MO ) . Band intensity on immunoblots was quantified using Image Studio Lite software version3 . 1 ( LI-COR Biosciences , Lincoln , Nebraska ) and statistical tests of significance were performed on the resulting data as described . Comet assays [48] , [49] were performed using the CometAssay kit from Trevigen ( Gaithersburg , MD ) with minor modifications . Leaf tissues were cut into pieces with a razor blade in 500 µl 1× PBS buffer supplemented with 20 mM EDTA on ice . Nuclei suspension was filtered into an Eppendorf tube through 50 µm nylon mesh , combined with Comet low-melting-point agarose at a ratio of 1∶ 10 and pipetted onto CometSlides . After incubation in lysis solution for 1 h at 4°C , the slides were placed in 1× Tris-Acetate electrophoresis buffer for 30 min prior to electrophoresis in the same buffer for 10 min at 4°C . Nuclei were stained with SYBR green . Images were captured and quantified with CometScore software ( Tritek Co . , Sumerduck , VA ) . At least 200 nuclei were scored per slide . H2AXa: AT1G08880; H2AXb: AT1G54690; NPR1: AT1G64280; CPR5: AT5G64930; EDS1: AT3G48090; PAD4: AT3G52430; SID2: AT1G74710; FLS2: AT5G46330; EFR: AT5G20480; SNI1: AT4G18470; SSN2: AT4G33925; RAD51D: AT1G07745; ATR: AT5G40820; ATM: AT3G48190 . | Multicellular organisms are continuously exposed to microbes and have developed sophisticated defense mechanisms to counter attack by microbial pathogens . Organisms also encounter many types of DNA damage and have evolved multiple mechanisms to maintain their genomic integrity . Even though these two fundamental responses have been characterized extensively , the relationship between them remains largely unclear . Our study demonstrates that microbial plant pathogens with diverse life styles , including bacteria , oomycete and fungal pathogens , induce double-strand breaks ( DSBs ) in the genomes of infected host plant cells . DSB induction is apparently a common feature during plant-pathogen interactions . DSBs are the most deleterious form of DNA damage and can lead to chromosomal aberrations and gene mutations . In response to pathogen infection , plant immune responses are activated and contribute to suppressing pathogen-induced DSBs , thereby maintaining better genome integrity and stability . The findings identify important ways that the plant immune and DNA damage repair responses are interconnected . Awareness of the above phenomena may foster future development of disease management approaches that improve crop productivity under biotic stress . | [
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"p... | 2014 | Microbial Pathogens Trigger Host DNA Double-Strand Breaks Whose Abundance Is Reduced by Plant Defense Responses |
The evolutionary transition from outcrossing to self-fertilization ( selfing ) through the loss of self-incompatibility ( SI ) is one of the most prevalent events in flowering plants , and its genetic basis has been a major focus in evolutionary biology . In the Brassicaceae , the SI system consists of male and female specificity genes at the S-locus and of genes involved in the female downstream signaling pathway . During recent decades , much attention has been paid in particular to clarifying the genes responsible for the loss of SI . Here , we investigated the pattern of polymorphism and functionality of the female specificity gene , the S-locus receptor kinase ( SRK ) , in allotetraploid Arabidopsis kamchatica . While its parental species , A . lyrata and A . halleri , are reported to be diploid and mainly self-incompatible , A . kamchatica is self-compatible . We identified five highly diverged SRK haplogroups , found their disomic inheritance and , for the first time in a wild allotetraploid species , surveyed the geographic distribution of SRK at the two homeologous S-loci across the species range . We found intact full-length SRK sequences in many accessions . Through interspecific crosses with the self-incompatible and diploid congener A . halleri , we found that the female components of the SI system , including SRK and the female downstream signaling pathway , are still functional in these accessions . Given the tight linkage and very rare recombination of the male and female components on the S-locus , this result suggests that the degradation of male components was responsible for the loss of SI in A . kamchatica . Recent extensive studies in multiple Brassicaceae species demonstrate that the loss of SI is often derived from mutations in the male component in wild populations , in contrast to cultivated populations . This is consistent with theoretical predictions that mutations disabling male specificity are expected to be more strongly selected than mutations disabling female specificity , or the female downstream signaling pathway .
The evolutionary transition from outcrossing to predominant self-fertilization ( selfing ) is one of the most prevalent events in flowering plants [1]–[4] . Although increased homozygosity caused by selfing often leads to reduced fitness in the offspring ( inbreeding depression ) , the inherent transmission advantage would favor selfing [5] , [6] . This is because selfers can transmit gametes in three ways—as both the ovule and pollen donor for their own selfed progeny and as the pollen donor for outcrossed progeny—whereas outcrossers cannot serve as pollen donors for their selfed progeny . Thus , an allele promoting selfing has a 3∶2 transmission advantage relative to an allele promoting outcrossing . Selfing would also be advantageous , because selfers can reproduce when pollinators or mates are scarce ( “reproductive assurance” [6]–[9] ) . Theory suggests that selfing should evolve when these advantages outweigh the costs of inbreeding depression [6] , [10] , [11] . In many flowering plants , predominant selfing evolved through the loss of self-incompatibility ( SI ) [2] , [3] . SI systems have evolved multiple times in diverse lineages of flowering plants . They generally consist of female and male specificity genes at the S-locus and other genes involved in signaling pathways [12]–[14] . In SI species , the S-locus region is subject to negative frequency-dependent selection , which is a classic example of multiallelic balancing selection [15] . The molecular basis of the SI system has been studied extensively and is well characterized in the Brassicaceae . Here , female specificity is known to be determined by the S-locus receptor kinase ( SRK ) and male specificity is determined by the S-locus cysteine-rich protein ( SCR; also known as S-locus protein 11 , SP11 ) . SRK is a transmembrane serine/threonine receptor kinase that functions on the stigma , and SCR is a small cysteine-rich protein present in the pollen coat that acts as a ligand for the SRK receptor protein [12]–[14] , [16]–[19] . SRK and SCR are tightly linked at the S-locus , where dozens of highly divergent sequence groups , called S-haplogroups ( or S-haplotypes or S-alleles ) , are segregating . S-haplogroups confer specificity in self-recognition: direct interaction between SRK and SCR of the same S-haplogroup leads to the inhibition of pollen germination at the stigma [13] , [20] . In the Brassicaceae , several genes involved in the female downstream signaling pathway of SRK have also been reported , such as M-locus protein kinase ( MLPK ) and ARM-repeat containing 1 ( ARC1 ) [13] , [21]–[23] . The genetic basis for the recurrent loss of SI has been a major focus from both theoretical and empirical viewpoints [4] , [24]–[29] . In particular , much attention has been paid to clarifying which mutations are responsible for the loss of SI , and whether these mutations are in the female specificity gene , the male specificity gene or in downstream signaling pathways [4] , [24]–[29] . With the advantage of a suite of molecular tools , the most extensively studied species in the Brassicaceae is the diploid self-compatible Arabidopsis thaliana [4] , [29]–[42] . Whereas a number of mutations disabling the male and female components have been identified in wild accessions of A . thaliana [30] , [33] , [36] , [38] , [39] , many accessions still retain full-length and expressed SRK sequences [38] , [41] . Importantly , interspecific crossings using the self-incompatible Arabidopsis halleri revealed that some A . thaliana accessions , including Wei-1 , retain a functioning female SI reaction , demonstrating that all female components including SRK and the female downstream signaling pathway are still functional [41] . In addition , Tsuchimatsu et al . [41] reported that a 213-base-pair ( bp ) inversion ( or its derivative haplotypes ) in the SCR gene is found in 95% of European accessions . When the 213-bp inversion in SCR was inverted and expressed in transgenic Wei-1 plants , the functional SCR restored the SI reaction . These results suggested that degradation of SCR ( the male specificity gene ) was primarily responsible for the evolutionary loss of SI of the S-haplogroup in European A . thaliana , while other mutations at genes involved in the downstream signaling pathway might have contributed to some extent [35] , [39] . To understand whether such mutations in the male components of the S-locus are common in the recurrent evolution of self-compatibility in the Brassicaceae , empirical examples need to be investigated in other self-compatible species . In addition to A . thaliana , there are a few reports on the pattern of polymorphism at the S-locus in self-compatible species in Brassicaceae , such as Capsella rubella [43] and Leavenworthia alabamica [44] . However , the genetic and molecular bases responsible for the loss of SI are still unknown in these species . A major obstacle to charting the history of the S-locus in self-compatible species has been in distinguishing the primary inactivating mutation from subsequent decay of the nonfunctional S-haplogroups by further mutations . This is because all genes involved in this signaling pathway are expected to be released from selection pressure and to evolve neutrally once the SI system ceases to function [4] , [28] , [39] , [41] , although pleiotropy of these genes could play a role in maintaining the functionality of the signaling pathway [42] , [45] . To study the primary mutations , a powerful approach would be to combine experiments confirming gene function with population genetic analyses finding gene-disruptive mutations . Arabidopsis kamchatica would be a good model system to address this issue . It is a self-compatible species , and originated through allopolyploidization of two species , A . halleri and A . lyrata , which are reported to be diploid [46]–[51] . Shimizu-Inatsugi et al . [48] reported that multiple haplotypes of nuclear and chloroplast sequences of A . kamchatica are identical to those of their parental species , indicating that multiple diploid individuals of A . halleri and A . lyrata contributed to the origin of A . kamchatica . In particular , A . kamchatica and A . halleri share four chloroplast haplotypes , strongly suggesting that at least four diploid individuals of A . halleri contributed independently to the multiple origins of A . kamchatica [48] . The two parental species are predominantly self-incompatible , although some of North American populations of A . lyrata are known to be self-compatible [26] , [29] . Their SI systems have been extensively studied [26] , [52]–[61] . Most of these studies have focused on SRK to characterize S-haplogroups , because novel SRK haplogroups can be isolated relatively easily by using PCR primers that were designed in the conserved regions of SRK [52] , [55] , while much fewer SCR sequences have been isolated because of its extreme polymorphism [30] , [40] , [62] , [63] . To date , 40 and 30 SRK haplogroups have been reported in A . lyrata and A . halleri , respectively , and studies of nucleotide polymorphisms and divergence using large sets of SRK sequences revealed various characteristics of the S-locus , such as the spatial distribution of S-haplogroups , complex dominance interactions and transspecific sharing of S-haplogroups among species [55]–[57] , [59] , [60] , [64] . The wealth of knowledge available on these parental species enabled us to investigate nucleotide polymorphisms of the S-locus in self-compatible A . kamchatica . In addition , A . kamchatica would be a novel model to investigate the mechanism underlying the loss of SI in polyploid species . The relationship between self-compatibility and polyploidy has been debated for more than 60 years , as it is argued that polyploids have higher selfing rates than their diploid relatives [1] , [65] ( but see also [66] for controversy ) . Hypotheses have been proposed to explain this association , such as: ( 1 ) self-compatible individuals in polyploids would not suffer from limitation of mates of the same ploidy level [1] , [66]–[70]; and ( 2 ) inbreeding depression would be reduced by having multiple gene copies [10] , [66] , [71] , [72] . Despite numerous ecological and evolutionary studies , the molecular mechanisms underlying the evolution of self-compatibility of polyploid species are still poorly understood . To understand the mechanisms underlying the loss of SI in A . kamchatica , we first isolated SRK haplogroups from A . kamchatica by examining 48 populations across its distribution range ( Table S1 ) . Based on the analyses of nucleotide divergence from parental species and the distribution of SRK haplogroups with respect to population structure , we studied how S-haplogroups in A . kamchatica have originated from the parental species . To understand the approximate timescale of this evolutionary event , we also estimated the divergence time of A . kamchatica from its parental species based on the nucleotide divergence of multiple nuclear genes other than SRK . This is because speciation time would be used as the upper boundary of the time estimate of the evolution of self-compatibility in a species , when the progenitor species was self-incompatible [43] , [73] . We tested the function of SRK haplogroups through interspecific crossing with self-incompatible A . halleri , and confirmed the disomic inheritance and allelic relationships of SRK haplogroups by segregation analyses in experimental and natural populations of A . kamchatica . Most importantly , our interspecific crossing with A . halleri also indicated the retained function of the female component of SI in A . kamchatica , suggesting that the degradation of male components was responsible for the loss of SI . We suggest that the degradation of male components among the Brassicaceae might represent a general trend in the evolution of self-compatibility in wild populations in contrast to cultivated populations .
Through PCR-based screening , we obtained five partial SRK-like sequences from A . kamchatica , named AkSRK-A , AkSRK-B , AkSRK-C , AkSRK-D and AkSRK-E . Our five SRK sequences were aligned with S-domain sequences available for SRK from A . halleri and A . lyrata [52] , [54] , [55] , [58] , [59] , [61] , and a phylogenetic tree including a total of 76 SRK sequences was generated using the neighbor-joining method ( Figure 1 ) . While previous studies reported that the SRK haplogroups are transspecifically shared among A . halleri , A . lyrata and A . thaliana [59] , [62] , the tree clearly shows that the SRK haplogroups are also transspecifically shared between A . kamchatica , A . halleri and A . lyrata ( Figure 1 ) . In A . lyrata and A . halleri , SRK sequences that presumably share the same specificities are highly homologous , while sequences with different specificities show at most 91–92% nucleotide sequence identity [59] , [74] . Here , four out of the five A . kamchatica SRK sequences ( AkSRK-A , AkSRK-C , AkSRK-D and AkSRK-E ) showed more than 98% sequence identity to SRK sequences previously reported in both A . halleri and A . lyrata ( Figure 1 ) , suggesting that they also share specificities with the corresponding A . halleri and A . lyrata SRK sequences . In contrast , no previously reported sequence showed any particularly high similarity with AkSRK-B . The most similar ones were AhSRK12 ( 81% identity over 576 bp ) and AlSRK23 ( 87% identity over 558 bp ) , suggesting that they are unlikely to share specificity with AkSRK-B . Using specific primers for AkSRK-B , we successfully amplified a sequence from an A . halleri plant ( lowland habitat in Western Honshu , Japan; No . 61 in Table S1 ) that showed 100% sequence identity to AkSRK-B of A . kamchatica and , as shown later by the interspecific crosses , they shared the functional specificity of SI . This newly discovered A . halleri ortholog was named AhSRK-B ( Figure 1 ) . Using specific primers , we also isolated orthologous sequences of AkSRK-A and AkSRK-C from A . halleri , which were nearly identical to AhSRK26 and AhSRK01 , respectively ( Figure S1 ) . These sequences were named AhSRK26-Ibuki and AhSRK01-Ibuki , respectively ( see the section “Retained full-length SRK sequences as well as multiple gene-disruptive mutations” for details ) . Despite their transspecificity , several species-specific nucleotide substitutions have been reported within the same S-haplogroups in A . lyrata and A . halleri , respectively [61] . Thus , to obtain insight into which parental species the SRK-like sequences found in A . kamchatica were derived from , we compared the nucleotide divergence of SRK-like sequences of A . kamchatica with corresponding orthologous genes from A . halleri and A . lyrata . AkSRK-A and AkSRK-C were closer to their orthologs of A . halleri ( AhSRK26 and AhSRK01 , respectively ) than to those of A . lyrata ( AlSRK22 and AlSRK01 , respectively ) ( Figure 2; Figure S1; Table S2 ) . Conversely , AkSRK-D and AkSRK-E showed higher sequence identity to orthologs from A . lyrata ( AlSRK42 and AlSRK17 , respectively ) ( Figure 2; Figure S1; Table S2 ) . These results suggest that AkSRK-A and AkSRK-C are derived from A . halleri and that AkSRK-D and AkSRK-E are derived from A . lyrata . In addition , because we found that AhSRK-B in A . halleri showed 100% identity to AkSRK-B in A . kamchatica , AkSRK-B is most likely derived from A . halleri . Based on this pattern of nucleotide divergence from the parental species , mutually exclusive distribution of SRK haplogroups and a segregation analysis in the F2 population ( see below ) , hereafter we denote AkSRK-A , AkSRK-B and AkSRK-C as the “A . halleri-derived SRK” and AkSRK-D and AkSRK-E as the “A . lyrata-derived SRK” ( see below and Discussion ) . Using PCR-based genotyping of SRK haplogroups , we investigated the frequencies and geographic distribution of the five S-haplogroups identified in this study . Altogether , 49 accessions from 46 populations were genotyped by primer pairs that could specifically amplify AkSRK-A , AkSRK-B , AkSRK-C , AkSRK-D or AkSRK-E ( Figure 3; Figure 4; Table S1; see Table S3 for the primer pairs used ) . Two copies of SRK were amplified from all accessions except those from Hokkaido in Japan that had only one copy ( Nos . 25 , 27 and 28 ) , and one from Kamchatka in Russia that had three copies ( No . 33 ) . This finding is consistent with reports that A . kamchatica is a self-compatible allotetraploid , which usually harbors two homeologs from the parental species , supposing rare heterozygosity because of selfing and rare duplication [46] , [48] . The distributions of AkSRK-A , AkSRK-B and AkSRK-C were mutually exclusive except for one accession ( No . 33 , see below ) and showed a strong geographic structure . AkSRK-A and AkSRK-B were found in about half of our samples ( 46 . 9% and 41 . 8% , respectively; Figure 3; Figure 4 ) ; all AkSRK-A were found in the southwestern part of the distribution range of the species ( Taiwan and Japan ) , whereas AkSRK-B was mainly located in the northern and eastern part of the species range ( North America and the Kamchatka Peninsula in Russia; Figure 3; Figure 4; Table S1 ) . In contrast , the frequency of AkSRK-C was lower than those of AkSRK-A and AkSRK-B ( 5 . 1%; Figure 3; Figure 4 ) , and was found only in three accessions from the Kamchatka Peninsula ( Figure 3; Figure 4 ) . One of them ( No . 33 ) harbored both AkSRK-B and AkSRK-C , indicating heterozygosity or duplication of the A . halleri-derived SRK , AkSRK-B and AkSRK-C sequences . We further genotyped nine additional individuals in that population ( Table S4 ) and found that AkSRK-B and AkSRK-C segregated at intermediate frequencies ( AkSRK-B: 0 . 55; AkSRK-C: 0 . 45 ) . This is consistent with the hypothesis that No . 33 is a rare heterozygote of AkSRK-B and AkSRK-C , because it would occasionally arise even by rare outcrossing events under predominant selfing , in particular when the allele frequencies were intermediate . Moreover , the distributions of AkSRK-D and AkSRK-E were completely mutually exclusive in our 49 samples and AkSRK-D was nearly fixed ( 91 . 8% frequency; Figure 3; Figure 4 ) . The geographic distribution of the A . halleri-derived S-haplogroups is concordant with the population structure inferred from polymorphisms of four other nuclear loci ( two homeologous genes each of WER and CHS ) ( Figure 3 ) . The high values of the mean posterior probability of data ln P ( X|K ) , ΔK and the symmetric similarity coefficient supported the clustering of K = 2 , which reflect the spatial structure of the distribution well ( Figure 3; Figure S2; Table S1 ) . The distributions of A . halleri-derived S-haplogroups—AkSRK-A , AkSRK-B and AkSRK-C—are significantly correlated with the population structure ( Cramer's coefficient: 1; p = 7 . 62×10−12 ) ; that is , most of accessions bearing AkSRK-A belong to cluster 1 ( orange in Figure 3 ) and most of others belong to cluster 2 ( blue in Figure 3 ) . This significant correlation indicates that the pattern of distribution of these A . halleri-derived S-haplogroups is consistent with the genome-wide pattern of polymorphism . The correlations were also significant with the clustering of K = 3 ( Cramer's coefficient: 0 . 675; p = 6 . 37×10−11 ) and of K = 4 ( Cramer's coefficient: 0 . 577; p = 5 . 39×10−12 ) . In contrast , the distributions of A . lyrata-derived S-haplogroups—AkSRK-D and AkSRK-E—are not correlated significantly with the population structure ( Cramer's coefficient: 0 . 302; p = 0 . 109 ) . The correlations were also not significant with the clustering of K = 3 ( Cramer's coefficient 0 . 194; p = 0 . 393 ) and of K = 4 ( Cramer's coefficient 0 . 163; p = 0 . 517 ) . In fact , the frequency of AkSRK-D is markedly higher than that of AkSRK-E and it is widespread throughout the geographically wide range , resulting in no significant correlation between these A . lyrata-derived S-haplogroups and population structure . In A . kamchatica subsp . kawasakiana ( formerly , A . lyrata subsp . kawasakiana ) , a previous survey of SRK identified two sequences , Aly13-1 and Aly13-22 [57] . The result of our PCR-based genotyping is consistent with those findings , as we also found AkSRK-A ( orthologous to Aly13-22 ) in all accessions of A . kamchatica subsp . kawasakiana ( Table S1; Figure 3 ) . However , AkSRK-C ( orthologous to Aly13-1 ) was not found in our samples of subsp . kawasakiana but only in subsp . kamchatica . Using the nucleotide divergence estimate K and the synonymous substitution rate Ks of four nuclear loci ( two homeologous genes each of CHS and WER; Table S5 ) , we estimated the divergence time of A . kamchatica from the parental species ( Table S6 ) . When we employed the mutation rate given by Koch et al . [75] , which is based on the synonymous substitution rate calibrated by fossil records , the mean divergence time was 20 , 417 years ( with a 95% confidence interval of 0–75 , 460 years ) . When we employed the mutation rate given by Ossowski et al . [76] , estimated using mutation accumulation lines , the mean divergence time was 245 , 070 years ( with a 95% confidence interval of 37 , 385–532 , 953 years ) . Overall , estimates based on the mutation rate given by Koch et al . [75] were smaller than those based on Ossowski et al . [76] , although the 95% confidence intervals overlapped . Two clusters were suggested in the analysis of population structure ( Figure 3 ) . Whereas here we estimated the divergence averaged over population clusters , it is possible that it varies between clusters , given that population structure is profoundly affected by the multiple origins of A . kamchatica [48] . We also calculated the clusterwise nucleotide divergence from A . halleri and A . lyrata but no significant difference from each other was found in the current dataset and clustering ( Table S5 ) . Based on the pattern of nucleotide divergence from the parental species and the mutually exclusive distribution of SRK , we predicted the following allelic relationships: the A . halleri-derived SRK ( AkSRK-A , AkSRK-B and AkSRK-C ) should be allelic and the A . lyrata-derived SRK ( AkSRK-D and AkSRK-E ) should be allelic with each other , respectively . This prediction also assumes the disomic inheritance of the A . halleri- and A . lyrata-derived SRK , respectively . To confirm our predictions , we investigated the pattern of segregation of the A . halleri-derived SRK ( AkSRK-A and AkSRK-B ) in an F2 population that was generated by crossing individuals bearing AkSRK-A and AkSRK-D , and individuals bearing AkSRK-B and AkSRK-D ( Table 1 ) . We genotyped 95 F2 individuals with specific primers for AkSRK-A and AkSRK-B , and compared the goodness-of-fit of four inheritance models: ( 1 ) disomic and allelic , ( 2 ) disomic and nonallelic , ( 3 ) tetrasomic and allelic and ( 4 ) tetrasomic and nonallelic ( Table 1 ) . We found that the observed pattern of segregation better fitted model ( 1 ) , i . e . , the disomic and allelic model , rather than the other three models ( p = 0 . 27; Table 1 ) . We also confirmed the amplification of AkSRK-D in all 95 F2 plants and in the F1 generation , which indicates that AkSRK-D segregates neither with AkSRK-A nor with AkSRK-B in the F2 population . We isolated entire coding sequences of SRK from several A . kamchatica individuals for each haplogroup ( three AkSRK-A , three AkSRK-B , one AkSRK-C , five AkSRK-D and one AkSRK-E; Figure 5 and Table S1 ) . In addition , we also isolated entire coding sequences of orthologs of AkSRK-A , AkSRK-B and AkSRK-C from A . halleri . Alignment of the coding regions of SRK from A . kamchatica and A . halleri indicates that at least one accession of four haplogroups—A , B , D and E—retains the full-length SRK , without any apparent disruptive mutations such as frameshifts or inverted repeats . Furthermore , four single nucleotide polymorphisms were identified among three sequences of AkSRK-A and 13 among five sequences of AkSRK-D ( Figure 5 ) . No obvious gene-disruptive mutations were found in the sequences of A . halleri , but we found three in multiple haplogroups of A . kamchatica ( Figure 5; Figure S3 ) . First , we found that AkSRK-A from an accession from Biwako , a lowland region of Japan , contained an approximately 1 , 700-bp insertion in exon 6 . PCR-based genotyping revealed that this insertion is shared by all the accessions of A . kamchatica subsp . kawasakiana living in lowland regions in western Japan ( Table S1; see Table S3 for the PCR primers used ) . We also found a 1-bp deletion in AkSRK-C from a Kamchatka accession that caused a frameshift . In addition , we found that AkSRK-D of an accession from mountains in central Honshu contains a 45-bp deletion in exon 1 . Although this deletion does not change the reading frame , it is likely to abolish the recognition function , because it lies within the S-domain and encompasses one of the 12 conserved cysteine residues suggested to be important for protein structure [77] , [78] ( Figure 5; Figure S3; see also the section on interspecific crosses for the degraded female SI in the Murodo accession ) . To test whether these full-length SRK sequences and other components involved in the female signaling pathway are functional in A . kamchatica , we first conducted interspecific crosses between A . halleri ( male ) and A . kamchatica ( female ) . As S-haplogroups are shared transspecifically among A . lyrata , A . halleri and A . kamchatica ( Figure 1 ) , an incompatible reaction should occur even in interspecific crosses in which pollen and stigma share the same haplogroup [41] . We used the three most frequent haplogroups in A . kamchatica—A , B and D—as all of the accessions surveyed contain at least one of them . In eight accessions of A . kamchatica , incompatible reactions were observed when pollen of A . halleri was used to pollinate pistils of A . kamchatica sharing the same haplogroups ( Figure 6 ) . These interspecific crosses verified the shared specificities of the SI system between A . halleri and A . kamchatica . More importantly , these results indicate that the female components of the SI system are functional in these accessions of A . kamchatica . Specifically , we found incompatible reactions in the following combinations of crosses: pollen of A . halleri bearing haplogroup A with pistils of A . kamchatica accessions bearing AkSRK-A from Murodo and Tsurugi-Gozen; pollen of A . halleri bearing haplogroup D with pistils of A . kamchatica bearing AkSRK-D from Biwako and Potter; and pollen of A . halleri bearing haplogroup B with pistils of A . kamchatica bearing AkSRK-B from Darling Creek and Potter . In the Potter accession , incompatible reactions were observed when haplogroups B and D of A . halleri were pollinated , respectively , suggesting that these haplogroups are codominant on pistils . As control experiments , we also carried out crosses of the following combinations: ( 1 ) where the S-haplogroups of pollen and stigmas differ , and ( 2 ) where the SRK of A . kamchatica possessed any gene-disruptive mutations ( Figure 6 ) . In these combinations , we consistently observed compatible reactions , indicating that the reduced pollen growth observed in this experiment was caused not by interspecific reproductive isolation between A . halleri and A . kamchatica , but by the SI system . It is worth noting that , in the Murodo accession , incompatible reactions were observed when plants were pollinated by A . halleri containing haplogroup A , but not by those containing haplogroup D . Because all components of the signaling pathway except for SRK are thought to be shared among different specificities , the data strongly suggest that a mutation in AkSRK-D—most likely the 45-bp deletion—was responsible for this decay of the female SI reaction . Likewise , compatibility of haplogroup A of the Biwako population is also attributable to a mutation in SRK , the approximately 1 , 700-bp insertion , because the functionality of the downstream signaling pathway was shown by crosses with A . halleri containing haplogroup D . Because all these accessions of A . kamchatica are self-compatible and retain functional female components of SI including downstream signaling pathways , the data indicate that the male components of S-haplogroups A , B and D are not functional in these accessions . To confirm the degradation of the male components , we conducted interspecific crosses between A . halleri ( female ) and A . kamchatica ( male ) , using A . halleri bearing haplogroups A , B or D as pistil donors and A . kamchatica as a pollen donor . In these combinations , we consistently observed compatible reactions , indicating that the male components of S-haplogroups A , B and D are not functional in these accessions of A . kamchatica ( Figure S4 ) . In addition , we conducted intraspecific crosses among A . kamchatica , with the Biwako accession as a pollen donor and the Murodo accession , which retains the functional female specificity of haplogroup A , as a pistil donor ( Table S7 ) . Incompatible reactions were not observed , thus excluding the possibility that the male components of haplogroup A of the Biwako accession remain functional . Similarly , we found that the male components of haplogroup D of Murodo are also not functional . All these data confirm that the male components of haplogroups A , B and D are not functional in these accessions of A . kamchatica . These nonfunctional male components and functional female components including downstream signaling pathways suggest that degradation of the male components was primarily responsible for their loss of SI . We do not exclude the possibility that recombination events between the male and female components on the S-locus may have also been involved , although their occurrence is reported to be very rare ( reviewed in [56] ) .
In this study , we identified the full-length SRK sequences of five S-haplogroups in A . kamchatica ( Figure 1 ) . Through interspecific crosses with A . halleri , we confirmed that the intact SRK sequences of the three most frequent S-haplogroups in our dataset—AkSRK-A , AkSRK-B and AkSRK-D—are indeed associated with the female specificities of SI . Although associations with SI specificities for the other less frequent haplogroups—AkSRK-C and AkSRK-E—were not confirmed experimentally , they also exhibited very high similarities with known SRK sequences from A . lyrata and A . halleri ( >98% ) , suggesting that specificities of SI are shared between species [59] , [74] . Our investigation on nucleotide polymorphism and divergence , as well as the pattern of segregation in natural and experimental populations , allows us to address how these five S-haplogroups in allotetraploid A . kamchatica originated from their parental diploid species , A . halleri and A . lyrata . First , AkSRK-A and AkSRK-C of A . kamchatica are closer to the orthologs of A . halleri than to those of A . lyrata , and AkSRK-D and AkSRK-E of A . kamchatica are closer to the orthologs of A . lyrata than to those of A . halleri ( Figure 2; Figure S1; Table S2 ) . We also found that AkSRK-B in A . kamchatica showed 100% identity to AhSRK-B in A . halleri , although its ortholog of A . lyrata was not isolated in the present study . Second , the distributions of AkSRK-A , AkSRK-B and AkSRK-C were mutually exclusive , as were those of AkSRK-D and AkSRK-E , except for a minor presumable heterozygote of AkSRK-B and AkSRK-C ( Figure 3; Figure 4 ) . Third , the pattern of segregation in the F2 population significantly supports the model in which AkSRK-A and AkSRK-B are allelic while AkSRK-D is not allelic to them ( Table 1 ) . In addition , the pattern of polymorphism within a Kamchatka population is consistent with the model in which AkSRK-B and AkSRK-C are also allelic and segregating in a local population ( Table S4 ) . These independent lines of evidence suggest that AkSRK-A , AkSRK-B and AkSRK-C are S-alleles of the A . halleri-derived S-locus and that AkSRK-D and AkSRK-E are S-alleles of the A . lyrata-derived S-locus . Although we confirmed the association between AkSRK-D and the SI specificity of A . halleri in this study , the specificity is also likely to be shared with A . lyrata ( discussed in [59] , [61] , [62] ) . While there are a few reports on the evolutionary history of the S-locus in cultivated allotetraploid species , particularly Brassica napus [79] , [80] , to our knowledge , this study is the first to demonstrate clearly how multiple S-haplogroups in a wild allotetraploid species originated from the parental species and spread throughout a geographically wide area . Shimizu-Inatsugi et al . [48] reported that multiple haplotypes of nuclear and chloroplast sequences were shared between allotetraploid A . kamchatica and its parental diploid species , suggesting independent origins of A . kamchatica . In particular , A . kamchatica and A . halleri share four identical chloroplast haplotypes , suggesting that at least four diploid individuals of A . halleri contributed independently to the multiple origins of A . kamchatica [48] . As three of the four suggested independent origins are manifested as distinct clusters of population structure , independent origins combined with range expansion out of Asia appear to affect the population structure of A . kamchatica profoundly [48] . A comparison between the geographic distribution of S-haplogroups and the population structure inferred from other loci thus illustrates how independent origins of A . kamchatica contributed to form the current pattern of polymorphism of two S-loci: the A . halleri-derived S-locus and the A . lyrata-derived S-locus . We found that the distribution of three A . halleri-derived S-haplogroups was significantly correlated with population structure . Given that the population structure of A . kamchatica is profoundly affected by its multiple independent origins , the concordance between population structure and the distribution of A . halleri-derived S-haplogroups suggests that the composition of the gene pool of the A . halleri-derived S-locus would be explained at least partially by the independent origins of this species . In contrast , there was no significant correlation found for the A . lyrata-derived S-locus , on which AkSRK-D is markedly more frequent than AkSRK-E . A similar pattern was observed in the European population of A . thaliana , in which the haplogroup A was much more frequent than the haplogroup C and thus the pattern of polymorphism at the S-locus showed deviation from the population structure [41] . A coalescent approach based on SRK sequences of species-wide samples as well as genome-wide polymorphism data would serve to unveil more precisely how the five S-haplogroups originated in A . kamchatica , especially by quantifying the effects of random genetic drift , population expansion out of Asia , and independent origins of species , respectively . Such a population genomic approach should also reveal the demographic history during the loss of SI in A . kamchatica . The retained functionality of the female SI components including the downstream signaling pathway shown in this study implies a fairly recent loss of SI in A . kamchatica . Indeed , estimates of the average divergence time of the nuclear loci ( WER and CHS ) are less than 250 thousand years ( kyrs ) , although this divergence time may not necessarily correspond to the timing of the loss of SI ( Table S6 ) . Dating of the loss of SI has also been estimated in other self-compatible lineages , A . thaliana ( <314 kyrs [62]; <500 kyrs [81] ) , C . rubella ( ∼27 kyrs [43] ) and L . alabamica ( ∼150 kyrs and 12–48 kyrs in two independent lineages [44] ) , assuming the substitution rate published by Koch et al . [75] . These timings of evolutionary transitions are generally concordant with the recent glacial–interglacial period that greatly influenced the distribution of many plant and animal species [82] . Indeed , recent genetic bottlenecks and/or population expansions have been suggested for A . thaliana [83]–[85] , C . rubella [43] , [73] , L . alabamica [44] and in selfing populations of A . lyrata in North America [86]–[88] . The low nucleotide diversity of A . kamchatica in comparison with its parental species is also consistent with a bottleneck during polyploidization ( 0 . 0006–0 . 0012 in A . lyrata-derived homeologs of A . kamchatica and 0 . 0008–0 . 0026 in A . halleri-derived homeologs of A . kamchatica , versus 0 . 0150 in A . halleri , 0 . 0230 in A . lyrata subsp . petraea and 0 . 0031 in A . lyrata subsp . lyrata [48] , [89] ) . As range expansions could be accompanied by reduced mate availability and increased pollen limitation [7] , [90]–[92] , reproductive assurance might have played a role in these examples of the loss of SI . Particularly , mates with the same ploidy level would be limited after polyploidization in A . kamchatica [1] , [66]–[70] . Another possibility has been suggested by recent theoretical and simulation studies , which proposed that range expansion might promote the evolution of selfing [93] . This is because inbreeding depression would be reduced in marginal populations where deleterious mutations are fixed or purged by strong genetic bottlenecks [93]–[95] . If inbreeding depression falls below a certain threshold , disrupted S-haplogroups causing self-compatibility are expected to rapidly replace all functional S-haplogroups via an inherent transmission advantage [24] , [27] . Although this is not mutually exclusive to reproductive assurance [44] , [96] , further analyses on the demographic history and the dating of the loss of SI should contribute to our ability to address the relative importance of transmission advantage and reproductive assurance for the evolution of self-compatibility during range expansions . The molecular mechanism underlying the loss of SI in polyploid species is still not well understood , although the relationship between polyploidy and self-compatibility has been debated for more than 60 years [1] , [65] , [66] . Whereas polyploidization is known to disrupt SI almost invariably in gametophytic SI systems where specificities are determined by haploid genotypes of gametes [97] , [98] , in sporophytic SI systems where specificities are determined sporophytically by the diploid parental genotypes , polyploidization in itself does not necessarily induce the loss of SI ( e . g . , [57] ) . We speculate that , in sporophytic SI systems such as those of the Brassicaceae , dominance interactions among S-haplogroups might have played an important role in the loss of SI in polyploid species , as is also implied in a study of synthetic interspecific hybrids by Nasrallah et al . [99] . In the Brassicaceae , complex dominance interactions among S-haplogroups have been reported [52] , [55] , [56] , [60] , [100]–[103] . Given that the female components are functionally intact in A . kamchatica , as shown by our interspecific crosses , both homeologous copies of the SCR gene ought to have lost their function . However , gene-disruptive mutations at both of the homeologous SCR genes might not necessarily be required if the dominant SCR harboring a gene-disruptive mutation suppresses the expression of the recessive SCR [80] , [104] . Thus , dominance interactions could facilitate the evolution of self-compatibility by a single mutation in polyploid species . This is indeed suggested for Brassica napus , which is also an allotetraploid species that originated from hybridization of B . rapa and B . oleracea [80] . In a cultivar of B . napus , neither of the homeologous SP11/SCR genes is expressed . In artificially synthesized B . napus lines , SP11/SCR alleles from B . rapa showed dominance over SP11/SCR alleles from B . oleracea , suggesting that the nonfunctional dominant SP11/SCR allele suppressed the expression of the recessive SP11/SCR allele [80] . In A . lyrata and A . halleri , such dominance relationships between S-haplogroups have been characterized . Thus , the S-haplogroup of S12 in A . halleri , which is orthologous to haplogroup D of A . kamchatica , has been suggested to belong to a relatively dominant class [60] . Given that the dominance relationship is consistent between A . halleri and A . kamchatica , haplogroup D would also be dominant in A . kamchatica and might have suppressed the expression of its homeologous counterparts , such as haplogroup C , which is orthologous to the most recessive S-haplogroup of S1 in A . lyrata and A . halleri [52] , [60] , [61] , [103] . While we showed that haplogroups B and D are codominant in pistils in A . kamchatica ( Figure 6 ) , their dominance rank might be different in pollen , as dominance is known to occur more frequently in pollen than in pistils [60] . It is worth noting that haplogroup C , which is orthologous to the most recessive S-haplogroup of S1 in A . lyrata and A . halleri , was found at a relatively low frequency in A . kamchatica ( 5 . 1% ) . In contrast , S1 shows the highest frequencies in self-incompatible populations of A . lyrata ( 33%; [55] ) and A . halleri ( 26 . 3%; [60] ) , because recessive haplogroups are hidden from negative frequency-dependent selection in heterozygotes , whereas the most dominant S-haplogroups are always exposed to selection [60] , [105] , [106] . While random genetic drift due to population bottlenecks could explain this contrasting change in frequency , we hypothesize that dominant haplogroups are more likely to be found in self-compatible populations . This is because a dominant haplogroup with gene-disruptive mutations should repress the expression of another specificity , and thus spread more rapidly than a recessive self-compatible mutation [42] . Consistent with this hypothesis , a nearly fixed haplogroup in A . thaliana has been shown experimentally to be a dominant allele in A . halleri [42] , [60] . The molecular basis of the dominance relationship has recently been unveiled in Brassica , where the expression of the recessive haplogroups is specifically silenced by methylation of promoter regions induced by trans-acting small noncoding RNAs originated from dominant haplogroups [101] , [107] , [108] . Investigation of the dominance relationships among S-haplogroups found in A . kamchatica , the pattern of expression of the SCR genes and their methylation status in A . kamchatica will allow us to understand how dominance interactions might have contributed to the loss of SI among polyploid species . The retained functionality of the female SI components shown by the sequence analysis of SRK and interspecific crosses suggests that the degradation of male components , possibly the SCR gene , was responsible for the loss of SI in A . kamchatica . We also suggest that the gene-disruptive mutations found in the SRK gene of some accessions are not primary mutations causing the loss of SI but rather represent secondary and independent decay . Thus , these would represent mutations that have accumulated after the evolution of self-compatibility , although pleiotropy of SRK might have played a role in maintaining its functionality and slowed this process [42] , [45] . Interestingly , evolutionary models predict that mutations disabling the male specificity of the SI system are expected to be more strongly selected than mutations disabling female specificity [25] , [28] . This is because these disabled pollen grains are transmitted as outcrossing pollen to offspring with a higher probability than other wild-type ( functional ) pollen . In contrast , mutations disabling the female specificity are not likely to benefit from the increased fitness over other functional pistils , as long as pollinators frequently visit and supply pollen grains that belong to various specificities [109] . Our finding in A . kamchatica is thus consistent with the prediction of these models . Mutations driving the loss of SI in the male component have also been reported in A . thaliana [41] . Similarly , the loss of SI in C . rubella might have been driven by a gene-disruptive mutation in the male component , because SRK appears to retain the full-length coding region in some accessions , indicating that mutations at SRK are unlikely to have been the primary cause for the loss of SI ( [43]; reviewed in [110] ) . Busch et al . [44] also reported that self-compatibility in L . alabamica might have originated by the loss of function of the male component , possibly SCR . These recent extensive studies in wild Brassicaceae species demonstrate that the evolution of self-compatibility tends to be driven by mutations in the male rather than in the female components ( Table 2 ) . In contrast , in cultivated Brassica , extensive functional analyses have identified gene-disruptive mutations both in male and in female components , and the pattern is significantly different from that observed in wild populations ( Table 2; Table S8; two-tailed Fisher's exact test p = 0 . 0476; one-tailed p = 0 . 0238; [79] , [80] , [111] , [112] ) . This contrasting pattern suggests that the male-skewed frequency of mutations found in recent studies of wild populations could be attributed to the process of natural selection and spread in wild populations [25] , [28] , rather than to the mechanistic natures of mutations , such as differences in mutation rate between male and female components . If such mechanistic reasons were important , similar patterns would have been observed in both wild and cultivated populations . Indeed , the context of selective pressure would be very different between wild and cultivated populations . In a wild population , as mentioned above , mutations disabling SI would be selected in terms of the transmission advantage , i . e . , number of compatible mates in a population [25] , [28] . In cultivated populations , these gene-disruptive mutations would be positively selected by humans based on the self-compatible phenotype per se . Moreover , because the female SRK gene is about 10 times longer than the male SCR , it may decay even faster than the male component during domestication , as indeed shown in cultivated Brassica ( Table 2; Table S8 ) . Our combination of population genetic analyses and crossing experiments suggests that degradation of the male components was primarily responsible for the loss of SI in A . kamchatica . As we have demonstrated in the present study , functional confirmations , such as crossings between individuals sharing the same SI specificity , will further corroborate the genetic basis for the loss of SI in other selfing species . First , sequence analysis alone cannot provide definitive evidence of gene function . For example , in previous studies of the evolution of self-compatibility in A . thaliana , a splicing mutation in the female gene SRK-B was found in the Cvi-0 accession while the male gene SCR-B did not have any obvious gene-disruptive mutations [38] . However , transgenic experiments suggested that SCR-B was also nonfunctional , possibly due to some amino acid changes , so it is not clear whether the primary mutation occurred in male or female components [40] . Second , functional analyses may reveal multiple origins of self-compatibility within species and contribute to an increase in the number of empirical examples , although in the present study , which took a conservative approach , each wild species was counted as one example ( Table 2 ) . While more empirical examples in various species should be gathered to better understand the general pattern of mutations in the evolution of self-compatibility , functional confirmations and analyses of the pattern of polymorphisms are both essential to disentangle mutational histories in the loss of SI .
Arabidopsis kamchatica consists of two subspecies , A . kamchatica subsp . kamchatica and A . kamchatica subsp . kawasakiana [46] . A . kamchatica subsp . kamchatica is a perennial , described originally from Kamchatka , Russia . It is also reported from East Asia ( Far East Russia , China , Korea , Japan and Taiwan ) and North America ( Alaska , Canada and the Pacific Northwest of the USA ) . The second subspecies , A . kamchatica subsp . kawasakiana , is an annual found in sandy open habitats along seashores or lakeshores in lowlands in western Japan . Tetraploid chromosome number counts ( 2n = 32 and n = 16II ) were reported from samples in Japan , Far East Russia , Alaska and Canada , representing both subspecies 46 , 48 . Altogether , 48 populations of A . kamchatica were sampled ( 43 from A . kamchatica subsp . kamchatica and five from A . kamchatica subsp . kawasakiana ) , including one to three individuals per population , giving a total of 60 accessions ( Table S1 ) . The sample locations included Far East Asia ( Taiwan and Japan ) , Far East Russia ( Kamchatka Peninsula and Okhotsk ) , Alaska , Canada and the northwest of the USA ( Washington ) , covering the majority of the distribution range of both subspecies . In addition , five accessions of A . halleri were used for interspecific crosses with A . kamchatica and for obtaining full-length sequences of SRK ( Table S1; see also the section “Interspecific crosses between A . halleri and A . kamchatica” for details ) . Genomic DNA was isolated from young leaves using Plant DNeasy Mini kits ( Qiagen , Hilden , Germany ) . Total RNA was extracted from floral buds and flower tissues with RNeasy kits ( Qiagen ) . The 5′ and 3′ ends of complementary DNA ( cDNA ) sequences were isolated by 5′ and 3′ Rapid Amplification of cDNA Ends ( RACE ) with the 5′/3′ 2nd Generation RACE Kit ( Roche Applied Science , Indianapolis , IN , USA ) . PCR was performed with ExTaq ( TaKaRa Bio Inc . , Shiga , Japan ) or iProof High Fidelity DNA Polymerase ( Bio-Rad , Hercules , CA , USA ) . Primers used for amplification and genotyping are shown in Table S3 , with the respective annealing temperatures and elongation times . Genotyping was based on the presence or absence of PCR products . Direct DNA sequencing was conducted at the Institute of Plant Biology , University of Zurich , using a PRISM 3730 48-capillary automated sequencer ( Applied Biosystems , Foster City , CA , USA ) . Sequence assemblies and alignments were performed in CodonCode Aligner 3 . 7 . 1 ( CodonCode , Dedham , MA , USA ) and BioEdit v 7 . 0 . 5 [113] . Minor adjustments to optimize the alignments were made by eye . Sequence data have been deposited in GenBank under accession numbers JX114752–JX114778 . MEGA 5 was used for the construction of a phylogenetic tree [114] . Phylogenetic trees were obtained using the neighbor-joining method on pairwise proportions of nucleotide divergence . The evolutionary distances were computed using the Kimura two-parameter method . To survey the S-haplogroups in A . kamchatica across its distribution range , we performed a PCR-based screening of the SRK gene using two kinds of primer sets: ( 1 ) “general primers” , designed in conserved regions of the S-domain of SRK and known to amplify SRK sequences that belong to a number of haplogroups ( “Aly13F1” and “SLGR” [52] , [55] ) ; and ( 2 ) “haplogroup-specific primers” , designed in polymorphic regions of the S-domain of SRK [55] . Based on the obtained sequences , new haplogroup-specific primers were designed for each haplogroup ( Table S3 ) . Although we found sequences in several accessions that were highly similar to the Aly13-7 sequence , Mable et al . [55] reported that Aly13-7 is not associated with SI . Thus , these sequences were excluded from further analyses . To investigate the functionality of SRK , the entire coding sequences of SRK were obtained by RACE PCR using the haplogroup-specific primers designed in the S-domain of SRK . The primers used for RACE PCR are listed in Table S3 . To examine the associations between the geographic distribution of the S-haplogroups and the population structure ( see the next section for details ) , we reexamined the population structure of A . kamchatica , which was originally inferred by Shimizu-Inatsugi et al . [48] , by adding the Okhotsk population that was not included in the former study . From two accessions of this population , we obtained nucleotide sequences of the genes WER ( WEREWOLF ) and CHS ( CHALCONE SYNTHASE ) . By including these data in the dataset of Shimizu-Inatsugi et al . [48] , population structure was inferred by the Bayesian clustering algorithm implemented in the InStruct program [115] . The programs CLUMPP [116] , DISTRUCT [117] and ΔK statistic [118] were used to summarize and interpret the outputs . The parameters used were the same as in Shimizu-Inatsugi et al . [48] , except for the number of independent runs: 10 instead of 20 . In addition to the software InStruct , we also used the software STRUCTURE 2 . 2 . 3 , which is not able to consider inbreeding explicitly [119] . ( See Text S1 and Figure S5 for details . ) To examine associations between the geographic distribution of the S-haplogroups and the population structure inferred from polymorphisms of other nuclear loci ( WER and CHS ) , Cramer's coefficient V ( also called φ ) was calculated for two sets of SRK ( A . halleri-derived AkSRK-A , AkSRK-B and AkSRK-C and A . lyrata-derived AkSRK-D and AkSRK-E ) . Cramer's coefficient V measures the strength of association or interdependence between two categorical variables [120] , [121] . Its statistical significance was assessed using Fisher's exact test . ( See Table S9 for cluster assignments based on K = 2 , 3 , or 4 . ) Heterozygotes or accessions that did not bear corresponding SRK were excluded from the analysis . All statistical analyses were conducted with R 2 . 10 . 0 [122] . To obtain insight into which parental species SRK of A . kamchatica were derived from , we calculated mean values of K , Ks ( the proportion of synonymous substitutions per synonymous site ) and Ka ( the proportion of nonsynonymous substitutions per nonsynonymous site ) from the outgroups A . halleri and A . lyrata for all SRK sequences obtained in A . kamchatica , using MEGA 5 [114] . We used all the sequences of A . kamchatica and A . halleri obtained in this study ( see Table S1 for which accessions were used ) . In addition , we used the following publicly available sequences for the calculation: AlSRK22 [52] , AhSRK26 [59] , AlSRK01 [61] , AhSRK01 [61] , AlSRK42 [59] , AhSRK12 [58] , AlSRK17 [54] and AhSRK02 [58] . Specifically , we calculated the nucleotide divergence of the following sequence pairs: ( 1 ) AkSRK-A from AlSRK22 and from AhSRK26; ( 2 ) AkSRK-B from AhSRK-B; ( 3 ) AkSRK-C from AlSRK01 and from AhSRK01; ( 4 ) AkSRK-D from AlSRK42 and from AhSRK12; and ( 5 ) AkSRK-E from AlSRK17 and from AhSRK02 . To understand the approximate timescale of the evolutionary loss of SI in A . kamchatica , the divergence time of A . kamchatica from two parental species was calculated based on four nuclear loci ( CHS-lyr , CHS-hal , WER-lyr and WER-hal ) . We first calculated the nucleotide divergence on these loci using publicly available data [48] as well as newly obtained sequence data ( see the section “Bayesian clustering for the inference of population structures” ) . For A . lyrata , two accessions from Far East Russia were reported to show the highest nucleotide similarities with A . lyrata-derived homeologs of A . kamchatica among those surveyed by Shimizu-Inatsugi et al . [48] , suggesting that they are closest to one of the founding parents of A . kamchatica . In contrast , other individuals of A . lyrata from Europe and North America were not as close to the lyrata-derived homeologs of A . kamchatica . Therefore , we calculated the divergence of A . kamchatica from these two A . lyrata accessions from Far East Russia , as this would better represent the split from the parental species . Standard errors and 95% confidence intervals were calculated for all estimates . All estimates were corrected using the Jukes–Cantor method [123] . As two clusters were suggested in the InStruct analysis ( Figure 3 ) , we also calculated the clusterwise nucleotide divergence from A . halleri and A . lyrata ( Table S10 . ) . ( See the above section , “Association analysis of SRK genotypes and population structures” , for the cluster assignment . ) Based on the calculated nucleotide divergence , we estimated the divergence time between A . kamchatica and the two parental species A . lyrata and A . halleri . The estimation was based on the expression T = K/2r , where T is the time to the most recent common ancestor , K is the nucleotide divergence and r is the substitution rate [124]–[126] . Note that our estimation of divergence time assumes a constant rate of evolution throughout the tree [127] . Here we employed two estimates of mutation rates: the synonymous mutation rate of 1 . 5×10−8±0 . 5×10−8 per site per year [75] , which is commonly used in studies of the evolution of self-compatibility [44] , [62] , and a mutation rate of 7 . 1×10−9±0 . 7×10−9 per site per generation , which was estimated using mutation accumulation lines [76] . While we assumed a generation time of two years [128] , we note that this could cause an overestimation or an underestimation , because some accessions of A . kamchatica are reported to be annual plants [47] , [48] and because an effect of seed dormancy was not considered , respectively . Note that estimates based on the mutation rate given by Koch et al . ( 2000 ) are independent from the generation time , because its unit is base pair per year , not per generation . For calculating the 95% upper and lower bounds of divergence time , the 95% upper and lower bounds of nucleotide divergence and the 95% lower and upper bounds of mutation rates were used , respectively . For estimating the divergence time , we used the nucleotide divergence values of CHS-hal and WER-hal from corresponding orthologs in A . halleri , and those of CHS-lyr and WER-lyr from corresponding orthologs in A . lyrata from Far East Russia . We conducted interspecific crosses between A . halleri and A . kamchatica to test whether the full-length SRK sequences and other components involved in the female signaling pathway are functional , and also to test whether the male components are not functional in A . kamchatica . To screen A . halleri plants bearing haplogroups A , B or D , genotypes of AkSRK were surveyed in A . halleri from Mt Ibuki ( 35 . 42°N , 136 . 40°E ) , Ohara ( 35 . 16°N , 135 . 84°E ) and Tada-Ginzan ( 34 . 90°N , 135 . 35°E ) in Japan . We used them as both pollen and pistil donors for the crossing experiments , because individuals that bear SRK-A , SRK-B or SRK-D should bear the haplogroup A , B or D of the S-locus ( encompassing SCR-A , SCR-B or SCR-D ) , respectively , given the tight linkage between SRK and SCR . Three A . halleri plants were used for each haplogroup . The haplogroup-specific primers listed in Table S3 were used for this screening . Two A . halleri plants from Boden and Beride in Switzerland , which bear neither SRK-A , SRK-B , nor SRK-D , were also used as pollen donors ( Table S1 ) . To confirm the SRK genotypes , eight A . kamchatica accessions were used for the crossing experiments ( Table S1 ) . Three of these eight accessions are reported to be capable of selfing [48] , and the other five accessions were confirmed in this study ( data not shown ) . Plants used in the pollination assay were grown at 22°C under a 16 h light/8 h dark cycle . We removed anthers from flower buds and carefully confirmed that stigmas were not contaminated by self-pollen using a stereomicroscope . Flowers were harvested 2–3 h after pollination when A . kamchatica was the pistil donor , or 24 h after pollination when A . halleri was the pistil donor . Harvested flowers were fixed in a 9∶1 mixture of ethanol and acetic acid , softened for 10 min in 1 M NaOH at 60°C and stained with aniline blue in a 2% K3PO4 solution . Pistils were mounted on slides to examine the pollen tubes using epifluorescence microscopy [41] , [129] . In compatible crosses , more than 100 pollen tubes typically penetrate the stigma and penetration of <20 pollen tubes was considered as a criterion of incompatible crosses , following the common criteria of previous work in Arabidopsis [31] , [41] . The results did not change even if a more stringent criterion of <10 pollen tubes was used . Although pollen tube growth was observed in most of the crosses to evaluate incompatible and compatible reactions , in a few combinations of crosses where A . halleri was the pistil donor , we alternatively used the lengths of siliques as a criterion of incompatible crosses ( see Figure S4 ) . A silique length of <5 mm was considered to be the criterion of an incompatible cross . To confirm the disomic inheritance and the allelic relationship of AkSRK-A and AkSRK-B , F2 segregation analysis was conducted using A . kamchatica . F1 plants were generated using the Biwako accession from Japan as the pistil donor and the Potter accession from Alaska as the pollen donor . ( See Table S1 for the detailed geographic locations of these accessions . ) Ninety-five F2 plants were generated by selfing of two F1 plants and genotyped using haplogroup-specific primers for AkSRK-A , AkSRK-B and AkSRK-D ( Table S3 ) . While AkSRK-A and AkSRK-D were amplified in the Biwako accession and AkSRK-B and AkSRK-D were amplified in the Potter accessions ( see Table S1 for details ) , all of AkSRK-A , AkSRK-B and AkSRK-D were amplified in F1 plants . Using χ2 tests with R 2 . 10 . 0 [122] , the goodness-of-fit for each of the following inheritance models was calculated: ( 1 ) disomic and allelic , ( 2 ) disomic and nonallelic , ( 3 ) tetrasomic and allelic and ( 4 ) tetrasomic and nonallelic . The expected frequencies of segregants are described in Table 1 . | Since Charles Darwin recognized the extraordinary diversity of plant mating systems , deciphering their origins has been a central theme for evolutionary biologists . Among various sexual systems , the evolution of self-fertilization ( selfing ) from cross-fertilization is one of the most frequent transitions in flowering plants , but the genetic basis responsible for these changes is still poorly understood . Here , we have focused on the evolution of selfing in the Brassicaceae , where cross-fertilization is usually enforced by a self-incompatibility ( SI ) system , determining specific recognition between the pistil ( female component ) and the pollen ( male component ) . Through sequencing analysis and crossing experiments , we studied the genetic changes leading to the loss of SI in the selfing species Arabidopsis kamchatica . We found that the female components of the SI system remain functional in many accessions , suggesting that degradation of the male component was responsible for the loss of SI . Recent studies in the Brassicaceae suggest that such a male-driven loss of SI is more common in wild than in cultivated populations . Furthermore , this pattern is consistent with theories predicting that mutations disabling male specificity have a higher probability of leading to successful mating and are thus more likely to spread than those disabling female specificity . | [
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] | 2012 | Recent Loss of Self-Incompatibility by Degradation of the Male Component in Allotetraploid Arabidopsis kamchatica |
B cell follicles in secondary lymphoid tissues represent an immune privileged sanctuary for AIDS viruses , in part because cytotoxic CD8+ T cells are mostly excluded from entering the follicles that harbor infected T follicular helper ( TFH ) cells . We studied the effects of native heterodimeric IL-15 ( hetIL-15 ) treatment on uninfected rhesus macaques and on macaques that had spontaneously controlled SHIV infection to low levels of chronic viremia . hetIL-15 increased effector CD8+ T lymphocytes with high granzyme B content in blood , mucosal sites and lymph nodes , including virus-specific MHC-peptide tetramer+ CD8+ cells in LN . Following hetIL-15 treatment , multiplexed quantitative image analysis ( histo-cytometry ) of LN revealed increased numbers of granzyme B+ T cells in B cell follicles and SHIV RNA was decreased in plasma and in LN . Based on these properties , hetIL-15 shows promise as a potential component in combination immunotherapy regimens to target AIDS virus sanctuaries and reduce long-term viral reservoirs in HIV-1 infected individuals . Trial registration: ClinicalTrials . gov NCT02452268
Interleukin-15 ( IL-15 ) is a gamma-chain cytokine essential for the production and maintenance of NK cells and plays an important role in the expansion and long-term preservation of memory T cells [1–7] . IL-15 is produced by stromal cells in several tissues , some blood endothelial cells and antigen presenting cells [8–10] . Although a single-chain form of IL-15 has been produced and evaluated in early stage clinical trials [11] , several experiments have suggested that IL-15 in vivo acts in concert with a transmembrane polypeptide designated IL-15 Receptor alpha ( IL-15Rα ) [12–22] . We have characterized the native form of IL-15 as the highly glycosylated heterodimeric cytokine ( hetIL-15 ) formed by the tight association of the single-chain IL-15 with IL-15Rα during production , and we showed that IL-15Rα does not serve a receptor function but rather is an integral component of the natural heterodimeric cytokine [19 , 22–24] . The IL-15/IL-15Rα complex is active on the surface of the IL-15 producing cells and is also rapidly shed into plasma upon proteolytic cleavage of the IL-15Rα chain [18 , 19 , 23 , 24] . hetIL-15 has an extended half-life in vivo and stimulates proliferation and cytotoxic commitment of NK cells and CD8+ effector T cells by binding to the IL-2/IL-15βγ receptor . We have shown that recombinant hetIL-15 induces proliferation , activation and increased cytotoxic potential of lymphocytes and , importantly , induces migration of lymphocytes into tumors in a murine model [25] . Due to these properties and its ability to delay tumor progression in animal models , hetIL-15 has progressed to clinical trials for metastatic cancer ( NCT02452268 ) . Studies monitoring the systemic effects of IL-15 in non-human primates using recombinant E . coli-derived rhIL-15 , glycosylated CHO cell produced single-chain IL-15 , or ALT-803 , a IL-15 mutant Fc fusion protein , showed expansion of memory T cells and NK cells in blood [6 , 26–34] . IL-15 has potential applications in the treatment of human diseases where enhanced cytotoxicity is desired , for example in the therapy of cancer and certain chronic infections such as HIV infection . HIV infection in humans and SIV/SHIV infection in macaques lead to the establishment of long-term viral reservoirs able to persist despite antiretroviral therapy ( ART ) and give rise to recrudescent infection when treatment is interrupted . Although long-lived latently infected CD4+ T cells have been identified as an important contributor to this viral reservoir , it has also been shown , in both HIV infected humans and SIV infected macaques , that cells actively producing virus can persist in privileged anatomic locations including B cell follicles within secondary lymphoid tissues [35–44] . Similar to HIV infected elite controllers , macaques infected with SIV that suppress viremia to low or undetectable levels continue to harbor virus infected cells within the follicles [41 , 42] . CD8+ T cell depletion increases virus production [45–47] , suggesting CD8-dependent immunological mechanisms of control [36 , 37 , 40–42 , 48–52] . Virus is able to persist in infected CD4+ TFH at least in part due to the relative inability of cytotoxic CD8+ T cells to enter the follicles [52–55] . Most CD8+ T cells lack CXCR5 , the chemokine receptor that allows CXCL13-guided chemotactic trafficking to the B cell areas in the LN [56] . Interventions that facilitate targeting of infected cells in the follicles will likely be required as part of an effective combinatorial treatment to reduce or eliminate viral reservoirs . In the present study , we used a two-week hetIL-15 treatment regimen to evaluate the effects in both uninfected macaques and macaques that had spontaneously controlled SHIV infections and maintained low levels of chronic viremia . We investigated the effect of hetIL-15 on lymphocytes of treated macaques using flow cytometry and confocal image analysis of LN . hetIL-15 treatment resulted in increased frequency of granzyme B ( GrzB ) expressing CD8+ T cells in B cell follicles , associated with decreases in cell-associated viral RNA within LN and reduced plasma viral RNA in the SHIV+ rhesus macaques . Thus , hetIL-15 treatment shows potential to target LN AIDS virus sanctuaries as part of combinatorial immunotherapy regimens .
To study the effects of hetIL-15 , we applied a two-week treatment protocol to 9 uninfected rhesus macaques ( Table 1 ) . The treatment consisted of 6 subcutaneous doses over two weeks with increasing quantities of recombinant hetIL-15 ( 2–64 μg/kg , Fig 1A , “step-dosing” ) . This regimen was designed based on the homeostatic nature of hetIL-15 [57 , 58] , and greatly expands lymphocyte numbers in rhesus macaques while minimizing toxicity . Treatment with this hetIL-15 regimen was well tolerated without clinically apparent toxicity or significant abnormalities in blood chemistry measurements . Both human and macaque hetIL-15 were used in this study as specified in Table 1 . These purified cytokines were shown to be equipotent in their ability to induce proliferation of macaque primary CD4+ and CD8+ T cells and NK cells in vitro ( S1 Fig ) . Lymph nodes ( LN ) ( Fig 1 ) , blood ( Fig 2 ) , and mucosal samples ( Fig 3 ) , collected before the first injection ( pre ) and 3 days after the last hetIL-15 injection , were analyzed by flow cytometry using the gating strategy shown in S2 Fig . As shown in the flow cytometry plots from a representative macaque ( R921 ) in Fig 1B , with group data summarized in Fig 1C , hetIL-15 significantly increased the relative frequency of effector CD8+ T cells ( TEM , CD28-CD95+ ) in LN mononuclear cells ( LNMC ) in all 9 uninfected rhesus macaques ( filled symbols ) . The frequencies of cycling ( Ki67+ ) CD8+ T cells and cells expressing GrzB , measured in the same 9 macaques , were also significantly increased in LNMC ( Fig 1D , 1E and 1F ) . To study the effects of hetIL-15 in the setting of chronic virus infection , we analyzed hetIL-15 treatment effects on 7 chronically SHIV-infected rhesus macaques that had spontaneously controlled their infections ( Table 1 ) . The SHIV+ macaques were selected based on their low persistent plasma viral loads and were asymptomatic throughout the chronic period of infection . At treatment initiation , the animals had been infected for a median of 9 months ( range 5–45 months ) with either clade B or C SHIV ( Table 1 ) . The selection of these otherwise asymptomatic SHIV-infected macaques allowed examination of effects on both immunological and virological parameters upon hetIL-15 treatment . We applied the two-week hetIL-15 treatment protocol to these SHIV+ macaques , collected the same samples ( LN , blood , mucosal tissues ) and performed the analysis described above for the uninfected macaques ( Figs 1 , 2 and 3; open symbols ) . Treatment with this regimen was equally well tolerated in these SHIV+ macaques as in uninfected animals . Analysis of LN samples showed that hetIL-15 treatment had a significant effect on the frequency of LNMC TEM CD8+ cells ( Fig 1C ) , GrzB+ CD8+ T cells ( Fig 1E ) and the cycling status of CD8+ T cells ( Fig 1F ) of the SHIV+ macaques ( open symbols ) . Thus , hetIL-15 treatment had significant and similar effects on LNMC in both uninfected and SHIV+ animals . In contrast to the TEM CD8+ LNMC , no significant change in the distribution of CD4+ T cells ( naïve , CM , EM ) was found within the LN after hetIL-15 treatment ( S3 Fig ) . To complement the analysis of LNMC , the effects of hetIL-15 on blood lymphocytes were examined ( Fig 2 ) in 12 of the 16 treated animals ( indicated by * in Fig 1C ) . hetIL-15 treatment had significant effects on the cycling status and frequencies of different memory differentiation subsets of CD8+ ( Fig 2A and 2B ) and CD4+ ( Fig 2C and 2D ) T lymphocytes and NK cells ( Fig 2G and 2H ) in blood of both uninfected ( N = 7; filled symbols ) and SHIV+ ( N = 5; open symbols ) macaques . These data are in general agreement with previous reports on blood lymphocytes using IV or SC administered single-chain IL-15 or the mutant IL-15 fusion protein , ALT-803 [6 , 27 , 30 , 32–34 , 59–61] . hetIL-15 treatment resulted in the highest levels of Ki67+ in effector CD8+ T cells ( CD28-CD95+ ) , followed by central memory and naïve CD8+ T cells ( Fig 2A ) . hetIL-15 also increased the percentage of total TEM cells and decreased the percentage of naïve ( TN , CD28+CD95 ) cells within the circulating CD8+ T cell pool ( Fig 2B ) . We also analyzed the effect of hetIL-15 on the circulating CD4+ T cells ( Fig 2C and 2D ) . hetIL-15 treatment increased the frequency of cycling ( Ki67+ ) CD4+ TCM ( CD28+CD95+ ) and TEM cell subsets , but had minimal effect on frequency of different CD4+ T cell memory subsets ( Fig 2D ) . The net effect of hetIL-15 in blood was a significant decrease in the CD4/CD8 ratio ( Fig 2E ) . hetIL-15 stimulated cell cycling and GrzB production in both CD8+ and CD4+ T cells , consistent with induction of a cytotoxic phenotype ( Fig 2F ) . A significant increase in the frequency of NK cells , which , like the EM CD8+ T cells , also showed greatly increased expression of Ki67 , was also found ( Fig 2G and 2H ) . HetIL-15 effects on cell populations at mucosal sites were examined in the same macaques after rectal ( 12 macaques ) and vaginal biopsies ( 10 females ) ( Fig 3 ) . The effects of hetIL-15 treatment were similar in uninfected ( filled symbols ) and SHIV+ ( open symbols ) macaques . hetIL-15 treatment significantly increased the frequency of cycling lymphocytes with increased frequencies of Ki67+ cells seen in both CD95+CD28high TCM and CD95+CD28low TEM subsets of CD8+ T cells , and in lymphocytes expressing γδ TCR in rectal ( Fig 3A , left panel ) and vaginal tissues ( Fig 3B , left panel ) . In both mucosal sites , the highest frequencies of Ki67+ cells were found among CD95+CD28low TEM cells and , especially , γδ T cells ( Fig 3A and 3B ) . Similar to the CD8+ T cells , an increase in cycling CD4+ T lymphocytes was observed in both mucosal sites ( Fig 3A and 3B , right panels ) and this increase was mainly driven by the increase of Ki67 among the CD95+CD28low TEM CD4+ T cells . In aggregate , these results show that subcutaneous administration of hetIL-15 at this dosing schedule affected lymphocyte cycling and cytotoxic potential in different compartments , including LN , blood , and mucosal effector sites . Since LN are sites of persistent HIV/SIV infection , at least in part due to the inability of most CD8+ cytotoxic T cells to effectively access infected TFH in B cell follicles , we evaluated the localization of CD8+ T lymphocytes within LN before and after hetIL-15 treatment using multispectral confocal imaging in combination with histo-cytometry ( S4 Fig ) . This technology provides quantitative and spatial information on the phenotype and location of cells in tissues [55 , 63] . LN sections were stained with fluorophore-labeled Abs and a nuclear dye ( JOJO-1 , S4 Fig ) , and visualized by confocal fluorescent microscopy ( Fig 4 ) . Use of formalin-fixed , paraffin-embedded tissues ( FFPE ) preserves tissue architecture but precludes the use of available antibody clones reactive with rhesus macaque CD8 . For this reason , we measured CD3+CD4- cells in LN as a surrogate for CD8+ T cells . Flow cytometry analysis showed that more than 90% of CD3+CD4- lymphocytes in LNMC express CD8 ( 91 . 1% +/-3 . 6 StdDev , average of 20 determinations before and after hetIL-15 treatment ) , supporting the use of CD3+CD4- measurement as a surrogate for CD3+CD8+ cells . Consistent with the flow cytometry analysis of LNMC , imaging analysis of FFPE LN samples demonstrated increased numbers of Ki67+ and GrzB+ cells throughout the LN after hetIL-15 treatment ( compare top and bottom panels in Fig 4A–4D ) as shown in a representative uninfected macaque ( R902 ) and a SHIV+ ( 5787 ) macaque . This increase was found throughout the LN sections , including the follicular areas ( Fig 4B and 4D ) . Higher magnification views show co-localization of GrzB primarily with CD3+CD4- ( CD8 ) T cells ( Fig 4C , white arrowheads ) . Quantitative analysis using histo-cytometry was performed on individual follicles from 4 uninfected and 6 SHIV+ macaques ( Fig 4E ) . A histo-cytometry software platform was used to project the follicular areas in a 2D plot format using the CD20 intensity ( CD20hi/dim , see S4 Fig ) . The same criteria were applied to all analyzed tissues . Follicular areas localized in areas displaying tissue fragmentation or insufficiently resolved due to planar limitations that prevented an accurate follicular mapping were not used for our analysis . hetIL-15 treatment resulted in significantly increased numbers of GrzB+ CD8+ T cells/mm2 in the follicles ( Fig 4E ) . The low numbers of GrzB+ CD8+ T cells/mm2 before treatment are consistent with previous findings in HIV infected humans and SIV infected macaques that cytotoxic CD8+ T cells accumulate within lymphoid tissues , but not within follicles [52–55] . These results demonstrate that hetIL-15 treatment can facilitate localization of GrzB+CD8+ T cells in follicles in both uninfected and SHIV+ macaques . Therefore , hetIL-15 treatment increases the number of GrzB+ lymphocytes not only in peripheral effector sites , but also in LN follicles , a well-documented sanctuary site for HIV/SIV [35–40 , 64] . This increase in GrzB+CD8+ cell numbers in B cell follicles raised the possibility that productively infected cells within follicles may become more accessible to immune surveillance . Since hetIL-15 drives cytotoxic cells into areas of persistent HIV/SIV reservoirs , we examined its effect in two SIV-infected macaques rendered aviremic by cART treatment . hetIL-15 step-dose treatment was well tolerated and resulted in CD8+GrzB+ cell infiltration of the LN ( S5 Fig ) . The animals remained aviremic during and after treatment . These results show that macaques infected with SIV and treated with cART can be treated with hetIL-15 and accumulate large numbers of cytotoxic CD8+ lymphocytes into the areas of persistent reservoirs . We next used flow cytometry to examine whether hetIL-15 treatment could increase , in addition to the total CD8+ T cell population , the frequency of virus-specific lymphocytes within the LN . We analyzed two uninfected MamuA*01+ animals ( P082 and P090 , Table 1 ) that had received prior an SIV gag DNA vaccine [62] . Gag CM9-specific CD8+ T cells were detected in LNMC and blood by MHC-peptide/tetramer analysis of both animals prior to treatment ( Fig 5 ) . hetIL-15 treatment increased ( 2 . 5 to 8-fold ) the frequency of CM9+ CD8+ T cells in LNMC ( 0 . 5% to 1 . 2% in P082; 0 . 3% to 2 . 4% in P090 ) ( Fig 5A , upper panels ) . This increase was associated with a decrease of Gag CM9+ CD8+ T cell frequency in the circulation ( Fig 5B , lower panels ) , suggesting that the change in SIV-specific CD8+ T cells within the LN may have reflected changes in lymphocyte trafficking . The Gag CM9-specific CD8+ T cells detected in both LNMC and blood showed increased Ki67+ ( Fig 5B ) , granzyme B ( Fig 5C ) and perforin expression ( Fig 5D ) , compared to matched pre-treatment samples , indicative of an activated , proliferative phenotype with cytotoxic potential . Thus , hetIL-15 treatment not only increased total CD8+ effector T cells ( Fig 1 ) but also SIV-specific effector T cells in LN . We also analyzed whether the expanded SIV-specific CD8+ T cells had preserved functional properties after hetIL-15 treatment . We monitored at different time points the production of IFN-γ and TNFα , as well as the release of cytotoxic granules measured by CD107 ( Fig 6A and 6B ) on T lymphocytes stimulated with the MamuA*01-restricted SIV Gag181-189 peptide from both PBMC and LNMC isolated before and after hetIL-15 treatment of the two MamuA*01+ macaques shown in Fig 5 . The data from macaque P082 are shown in Fig 6 . The cytokines were rapidly produced by the CM9-specific CD8+ T cells in both PBMC and LNMC . Simultaneously to the cytokine production , the cells became CD107+ . In contrast to these results , no functional responses , neither cytokine production nor degranulation were observed in any of the samples after stimulation with an unrelated Vif peptide pool ( Fig 6A and 6B , bottom plots ) . These data demonstrate that the expanded CM9+ CD8+ T cells were able to respond by cytokine production and release of cytotoxic granules upon specific TCR stimulation by their cognate antigen , which is the hallmark of cytotoxic T cells . In a different experiment , we also compared the kinetics of these responses in samples collected before and after in vivo hetIL-15 treatment ( Fig 6C ) . We found that , as early as 1 hour upon specific TCR stimulation , the samples obtained after hetIL-15 treatment had higher levels of IFN-γ and TNFα production and were already actively degranulating ( CD107+ ) as demonstrated also by the decrease in the intracellular content of both granzyme B and perforin , and these differences were maintained during the six hours of monitoring after stimulation . Like in previous experiments ( Fig 6A and 6B , bottom plots ) , none of these responses were found in samples treated with the unrelated Vif peptide pool . Finally , to monitor the cytotoxic potential against virus-expressing cells , we performed a killing assay using autologous CFSE-labeled bone marrow cells loaded with the CM9 peptide as targets . Target cells and unsorted LNMC were mixed at a ratio 1:1 and active killing among the CFSE population was monitored by flow cytometry after adding the fluorescent reagent 660-DEVD-FMK to the samples . This compound actively enters the cells and binds irreversibly to the active site of caspase 3 and 7 , the two main caspases activated by granzyme B . We found similar levels of caspase 3 and 7 in cells loaded with the unrelated Vif peptide pool and exposed to LNMC taken either before or after hetIL-15 treatment ( Fig 6D ) . In contrast , the frequency of cells actively undergoing apoptosis was clearly increased in the samples loaded with the specific CM9 peptide and this increase was higher when LNMC recovered after hetIL-15 treatment were used as effectors ( Fig 6D ) . Taken together these data demonstrate that hetIL-15 enhances the cytolytic responses by CD8+ T cells upon specific TCR stimulation . To further characterize the effects of hetIL-15 , cell associated viral RNA was measured in PBMC and LN by quantitative RT-PCR before and after hetIL-15 treatment in 4 macaques ( Fig 7 ) . These animals were infected with and spontaneously controlled clade B or C SHIVs as indicated . These measurements showed significant decreases of cell-associated viral RNA in axillary and inguinal LN ( p = 0 . 0001 , Mann-Whitney test ) ( Fig 7A ) . The decrease was more prominent in axillary ( range 11−103 fold ) than inguinal LN ( range 12−102 fold ) or PBMC ( 3−102 fold ) . Viral DNA levels were not appreciably affected by hetIL-15 treatment ( Fig 7B ) . Thus , viral RNA/DNA ratios decreased significantly upon treatment ( Fig 7C ) in all samples ( p = 0 . 0001 , Mann-Whitney test ) . The differential effects of hetIL-15 treatment on viral RNA and viral DNA are consistent with the observation that a substantial fraction of DNA PCR signal for SIV gag likely reflect proviral genomes that are not replication competent , due to deletions and/or hypermutations [65] , while virus specific CTL are expected to only affect cells capable of expressing viral antigens . We also measured plasma VL in 13 SHIV+ macaques treated with the same two-week hetIL-15 protocol , including the animals in Fig 7A above ( Table 2 ) . The median time of SHIV infection was 10 months ( range 5–45 months ) at the time of initiation of hetIL-15 treatment ( day 0 ) . The low but measurable persistent viremia in these animals allowed evaluation of potential changes in plasma VL during and after treatment . Plasma VL was measured at the study entry during the chronic phase of infection ( when animals were enrolled in the protocol ) ; 0–3 days before hetIL-15 treatment ( day 0 ) ; at 1 week of treatment; and at the end of the treatment ( day 15 , necropsy ) ( Table 2 ) . Comparing day 0 to day 15 showed a decrease in VL ( >15-fold ) upon hetIL-15 treatment in 6 animals . The rest of the animals had smaller changes in PVL ( below 10 fold ) . Two animals had increases ( 5 fold and 1 . 3 fold for T421 and R591 , respectively ) and five animals had decreases ( 3–7 fold ) . Our results do not support a strong latent virus activating effect by hetIL-15 in vivo , rather , the results support the conclusion that the net effect of hetIL-15 treatment was decreased virus RNA in the plasma and in LN .
We report that hetIL-15 treatment changes the lymphocyte populations within LN and significantly increases the number of potentially cytotoxic GrzB+CD8+ T cells within B cell follicles , a finding associated with reduced levels of viral RNA within LN . Follicular helper CD4+ T cells are critical targets for HIV infection , represent a major compartment for residual virus under conditions of immunologic or pharmacologic control of viral replication , and constitute a long-term reservoir of chronically infected cells in HIV+ patients and in SIV+ macaques , including elite controllers and persons receiving ART . In elite controller rhesus macaques infected with SIVmac239 , cellular immune responses targeting the virus were very effective in eliminating most infected CD4+ T cells within LN except for the TFH population within the follicles [36] . These results together with reports of low CTL density in areas of HIV replication within the LN [52–55] are consistent with the interpretation that B cell follicles represent an immune privileged site where infected TFH cells are shielded from cytotoxic T cells capable of eliminating infected cells elsewhere . Recent studies have shown the presence of scattered CD8+ T cells within the B cell follicles of LN in HIV-infected patients [55 , 66] and SIV infected macaques [52] . Although these studies did not address the granzyme content and cytotoxic capacity of such cells in vivo , these cells maintained their capacity for in vitro killing of infected CD4+ cells . The finding that hetIL-15 increased the frequency of effector CD8+ T cells ( including Gag CM9-specific Ki67+GrzB+ cells ) with cytotoxic phenotype within the LN and the follicles suggests a potential role for the use of hetIL-15 for therapeutic interventions against HIV aiming to reduce the virus reservoir . The strong induction of cytolytic molecules ( granzyme , perforin ) and the demonstration that CD8+ cells produce multiple cytokines and degranulate upon specific TCR stimulation ex vivo demonstrate that hetIL-15 enhances the cytolytic ability of CD8+ T cells . The immunohistochemistry results show that follicular CD8+ T cells also have high granzyme . By boosting the frequency of follicular CD8+ T cells and increasing their cytotoxicity , hetIL-15 potentially increases the possibility of follicular CD8+ T cells to find and eliminate infected cells in such environment . The decrease in cell-associated viral RNA in both LN and blood together with the decrease in plasma viral load suggests the elimination of virus producing cells . An alternative hypothesis that cannot be excluded at present , is that virus-producing CD4 cells may leave the LN . Infected CD4 cells leaving the LN sanctuary may become more vulnerable to elimination . The decrease in plasma VL and cell associated viral RNA suggests that , even if infected CD4 cells change location , hetIL-15 treatment results in their elimination . Lack of significant changes in the composition of CD4 T cell subsets in the LN ( S3 Fig ) does not support the preferential exit of infected CD4+ cells . It has been reported that IL-15 can act as a HIV latency reversing agent in vitro , especially in synergy with other compounds [67 , 68] . Our results do not provide evidence for such an activity for hetIL-15 in vivo , although this could be the result of low activation that is not reflected in the blood , or that is rapidly masked by the elimination of infected cells . In any case , there may be advantages to combining hetIL-15 treatment with latency reversing agents for targeting long-term viral reservoirs , including latently infected cells . hetIL-15 treatment resulted in reduction of plasma viremia and cell-associated viral RNA in LN samples without significantly affecting the levels of viral DNA . Only a fraction of the SIV DNA signal detected in the quantitative PCR assay is expected to represent replication competent proviruses [65] . This may affect the number of infected cells susceptible to immune mediated clearance dependent on expression of viral antigens . The most dramatic decrease of LN viral RNA upon hetIL-15 treatment was observed in axillary LN , which were the draining LN for the site of SC hetIL-15 administrations . This suggests that more prolonged treatment or a different schedule or route of administration may further increase the beneficial effects of hetIL-15 . The low toxicity of the optimized regimen described here indicates that additional regimens can be tested and opens the possibility for combinations with other interventions . Further studies , including more sustained treatment , will be required to monitor the long-term effects of hetIL-15 on virus levels in different compartments , in order to maximize effects on virus in reservoir sites . In this context , use of macaque hetIL-15 described in this report allows long-term treatment and facilitates future macaque studies . The observed reduction in viral RNA in LN indicates that hetIL-15 mediated effects provide new opportunities for exposure of HIV/SIV infected cells to immune clearance . The ability of hetIL-15 to increase the number of cytotoxic CD8+ T cells within secondary lymphoid tissues makes the cytokine an interesting potential component in combination therapeutic interventions aiming to reduce or eradicate persistent viral reservoirs in secondary lymphoid tissues . Interventions that facilitate targeting of infected cells in the follicles may become an important component of combinatorial treatment to reduce or eliminate viral reservoirs and sanctuaries . Long-term studies in ART-treated macaques and measurements of virus reservoirs in additional nonhuman primate models of AIDS virus infection will be required to further evaluate the effects and therapeutic potential of hetIL-15 in treating chronic viral infection . The present results establish that hetIL-15 can be safely delivered and is equally effective in increasing cytotoxic cells in B cell follicles in uninfected and SHIV infected , as well as in chronically SIV-infected cART-treated macaques . hetIL-15 is presently being evaluated in clinical trials for cancer immunotherapy due to its ability to increase effector lymphocytes in tumors , and to delay tumor growth in animal models . Its ability to increase infiltration of B cell follicles by CD8+ may also be beneficial for other viral infections and malignancies affecting the LN .
All animals were cared for and procedures performed under a protocol approved by the Institutional Animal Care and Use Committee of BIOQUAL , Inc . ( animal welfare assurance no . A3086-01; protocol numbers 14-A478-11 and 17–024 ) and USDA Certificate number 51-R0036 . Furthermore , the macaques in this study were managed accordingly to the animal husbandry program . which aims at providing consistent and excellent care to nonhuman primates at the vivarium . This program operates based on the laws , regulations , and guidelines promulgated by the United States Department of Agriculture ( e . g . , the Animal Welfare Act and its regulations , and the Animal Care Policy Manual ) , Institute for Laboratory Animal Research ( e . g . , Guide for the Care and Use of Laboratory Animals , 8th edition ) , Public Health Service , National Research Council , Centers for Disease Control , and the Association for Assessment and Accreditation of Laboratory Animal Care ( AAALAC ) International . The nutritional plan utilized by the BIOQUAL , Inc . Facility consisted of twice daily feeding of Labdiet 5045 High Protein Primate Diet and food intake was closely monitored by Animal Research Technicians . This diet was also supplemented with a variety of fruits , vegetables , and other edible objects as part of the environmental enrichment program established by the Veterinary staff and enrichment Technician . Pairing of animals as part of the environmental enrichment program was managed by the enrichment technician . All primary enclosures and animal rooms were cleaned daily with water and sanitized at least once every two weeks . Macaques ( N = 24 ) used in this study were 9 males and 15 females . Their average weight was 6 kg ( range: 3 . 4–10 . 2 kg ) and their average age was 8 years ( range: 4–15 years ) . Vaccinations were performed under anesthesia ( Ketamine administered at 10 mg/kg ) and all efforts were made to minimize suffering . No adverse effects were found . All animals were euthanized as part of this study . The objectives of the study were to determine the safety and in vivo bioactivity of a step-dose hetIL-15 treatment delivered subcutaneously in rhesus macaques , focusing on the effects on cytotoxic lymphocytes within secondary lymphoid tissue , especially in B cell follicles , an immune privileged area where chronically HIV-infected CD4+ T cells are located . We assessed the impact of treatment on immunologic parameters in uninfected animals and in SHIV-infected macaques that had spontaneously controlled infection and were maintaining low level plasma viremia which also allowed assessment of virologic parameters . Lymph node , blood , and mucosal samples were analyzed before and after hetIL-15 treatment by flow cytometry , multiparameter flow cytometry , quantitative multiplexed confocal imaging ( histo-cytometry ) and quantitative PCR/quantitative RT PCR . The study was carried out in accordance with the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health . Indian rhesus macaques ( Macaca mulatta ) were housed and handled in accordance and approval by the Institutional Animal Care and Use Committee of BIOQUAL , Inc . The cohort of macaques described in Table 1 consists of 9 uninfected animals and 15 ( SHIV+ ) animals chronically infected with clade B SHIV ( SHIV-SF162 [69] ) or clade C SHIV [ ( SHIV CH505 [70] , SHIV-1157ipd3N4 [71] , SHIV-327C [72]] . The SHIV+ macaques were asymptomatic with low levels of persistent chronic viremia . Twenty-two animals received six SC injections during a two-week treatment cycle ( day 1 , 3 , 5 , 8 , 10 , and 12 ) with increasing doses of hetIL-15 ( 2 , 4 , 8 , 16 , 32 and 64 μg/kg , “step dose” ) . Two animals received two-week treatment cycle of hetIL-15 using either a dose-escalation of 5–120 μg/kg ( P934 ) or repeated administration of 50 μg/kg ( P995 ) . We took advantage of the role of hetIL-15 as homeostatic cytokine [57 , 58] to develop the step-dose treatment regimen , which provides increasing doses of the cytokine as the lymphocytes divide and increase in numbers . This allowed optimal lymphocyte expansion with lower drug exposure . hetIL-15 treatment was well tolerated and the macaques did not have any clinically apparent adverse effects or laboratory abnormalities described with other IL-15 treatment regimens [28] . Animals treated with the step dose protocol did not develop edema , fever or low blood pressure . Several had increases in the size of axillary and inguinal LN . Eight of the 24 macaques were treated with macaque hetIL-15; the remainder received the human molecule ( Table 1 ) . Human and macaque hetIL-15 were produced in HEK293 cells ( Invitrogen ) and purified as described [19 , 24] , except that crude macaque hetIL-15 was subjected to two additional steps , first concentration using tandem tangential flow filtration ( TangenX ) and then anion exchange chromatography using Capto Q resin ( GE Healthcare Science ) . Human and macaque purified hetIL-15 cytokines were equipotent in macaque cells in vitro ( S1 Fig ) . All hetIL-15 concentrations are given as single-chain IL-15 polypeptide mass equivalents within the heterodimer . Three days before treatment initiation and 3 days after the last hetIL-15 injection , peripheral LN , peripheral blood , vagina , and rectum samples were collected , lymphocytes were isolated and analyzed as previously described [73] . Two macaques ( R905 , R913 ) infected rectally with repeated low dose of SIVmac251 and treated with combination antiretroviral therapy ( cART ) were used to compare the effects of hetIL-15 with the uninfected and SHIV infected macaques . At weeks 10–12 postinfection , the animals were placed on cART given in a single formulation s . c . daily at 1 ml/kg comprising Tenofovir [PMPA] ( 20 mg/kg ) , Emcitrabine [FTC] ( 50 mg/kg ) and Dolutegravir [DTG] ( 2 . 5 mg/ml ) ( Gilead and ViiV ) . The animals maintained plasma VL below 50 copies/ml during 35 weeks in cART and were treated twice with the step-dose hetIL-15 two-week regimen , with a 4-week rest period . The following fluorophore conjugated monoclonal antibodies were used: CD3 ( clone SP34-2 ) , CD4 ( clone L200 ) , CD95 ( clone DX2 ) , Ki67 ( clone B56 ) , CD16 ( clone 3G8 ) , γδ TCR ( clone B1 ) , IFN-© ( clone B27 ) , TNFα ( clone Mab11 ) ( BD Biosciences ) , Perforin ( clone Pf-344 ) ( Mabtech ) , CD107a ( clone eBioH4A3 ) , CD28 ( clone CD28 . 2 ) ; CD8 ( clone 3B5 ) and Granzyme B ( clone GB12; Life Technologies ) . Briefly , lymphocyte single cell suspensions were washed with PBS supplemented with 0 . 2% heat-inactivated human serum ( Sigma ) , and incubated with different cocktails of fluorophore-labelled monoclonal antibodies during 20 minutes at room temperature [73] , fixed and permeabilized using the FoxP3 permeabilization reagent ( eBioscience ) . After 30 minutes incubation at 4°C , the cells were washed with FoxP3 washing buffer and intracellularly stained with Ki67 and GrzB for 20 minutes . The cells were washed and resuspended in PBS for flow cytometry analysis . For tetramer staining using samples from MamuA*01+ macaques , the CM9 tetramer was added to the samples 5 minutes prior to the addition of the antibody cocktail for surface staining [73] . The samples were acquired on a Fortessa or LSRII flow cytometer ( BD Biosciences , San Jose , CA ) and the data were analyzed using the FlowJo software platform ( Tree Star , Inc . , Ashland , OR ) . Two different assays were used to monitor cytotoxic responses by cryopreserved CD8+ lymphocytes from MamuA*01+ rhesus macaques: degranulation and direct target cell killing . For the degranulation assay , PBMC and LNMC were thawed and incubated in RPMI supplemented with 10% FBS , antibiotics and 30 units/ml of recombinant DNase I . After 24 hours , the cells were washed , seeded in 96-well plates ( 3x105 cells/well ) and stimulated with the MamuA*01-restricted SIV Gag181-189 CM9 peptide at a final concentration of 1μg/ml in the presence of Monensin . As negative control , cells were also stimulated with a pool of peptides ( 15-mers overlapping by 11 aa ) covering HIV-1 Vif . At different time points , samples were washed , stained with the CM9 tetramer followed by a surface antibody cocktail containing CD3 , CD4 , CD8 and CD107a to monitor degranulation and release of cytotoxic enzymes . After permeabilization , the cells were intracellularly stained with antibodies for IFN-© , TNFα , granzyme B and perforin . Direct target cell killing: autogous bone marrow cells were used as targets . Briefly , the cells were labeled with CFSE at a concentration of 1 μM for 30 minutes at 37°C . After the incubation , the cells were washed with PBS to remove the excess of dye and cultured overnight at 37°C . Next day , the cells were loaded with the Gag181-189 CM9 peptide at a concentration of 5 μg/ml . After 30 minutes , the cells were washed and mixed with autologous LNMC at a ratio of 1:1 . After 2 hours at 37°C , the fluorescent 660-DEVD-FMK reagent , an inhibitor of caspase 3 and caspase 7 that difuses into the cells and irreversibly binds to the active forms of the caspases ( FLICA assay , ImmunoChemistry Technologies ) was added to the samples . After 1 hour , the samples were washed with the FLICA kit buffer and analyzed for apoptosis by flow cytometry . Confocal imaging was performed with formalin fixed paraffin embedded ( FFPE ) lymph node sections ~10 μm in thickness . Tissue sections were deparaffinized by bathing in xylene and serial ethanol dilutions . Antigen retrieval was performed at 110°C for 15 minutes using Borg RTU ( Biocare Medical ) . Tissue sections were then blocked , permeabilized for 1 hour at room temperature and stained with the following primary and conjugated antibodies: anti-CD20 Pacific Blue ( in house conjugated ) ( clone L26 ) , anti-CD3 Alexa Fluor 680 or 594 ( clone F7 . 2 . 38 ) , anti-CD4 Alexa Fluor 488 ( goat polyclonal IgG , FAB8165G , R&D systems ) , anti-Granzyme B Alexa Fluor 647 or 680 ( clone GrB-7 ) , anti-Ki67 Brilliant Violet 421 or 510 ( clone B56 ) and the nuclear marker JOJO-1 ( Life Technologies ) . Stainings were carried out consecutively with the primary antibodies being added first and incubated overnight at 4° C , followed by staining with the appropriate secondary antibody Alexa Fluor 647 for PD-1 ( goat polyclonal , BAF1086 , R&D ) . Conjugated antibody stainings were performed for 2 hours at room temperature , after which sections were stained with Jo-Pro-1 for nucleus identification . Images were acquired at a 512 x 512 pixel density using a 40x objective ( NA 1 . 3 ) either on a Leica TCS SP8 confocal platform running LAS-X or a NIKON C2si confocal microscope running NIS-elements AR . Depending on the platform , fluorophore spectral spillover was corrected either by acquiring single stained tissue controls and calculating a spillover matrix that was then used to correct for cross-talk ( Leica ) or through live spectral un-mixing ( NIKON ) . Post-acquisition analysis was performed using the Imaris software ( Bitplane , version 8 . 3 . 1 ) . Histo-cytometry was performed as previously described [55 , 63] . Briefly , 3-TFH dataset dimensional imaging datasets were segmented based on their nuclear staining signal and average voxel intensities for all channels were extrapolated in Imaris after iso-surface generation . Data were then exported to Microsoft Excel , concatenated into a single comma separated values ( cmv ) format and imported into FlowJo version 10 for further analysis . To account for variations in the size of tissues screened , data were normalized to cells/mm2 follicle area . Areas were calculated in Imaris post-acquisition using the iso-surface generation modality . Plasma SIV gag RNA and cell associated SIV gag DNA and RNA in LN and PBMC were measured using quantitative PCR and RT PCR methods , essentially as described using high sensitivity assay formats [70 , 74] . Statistical analyses were performed using Prism version 7 ( Graph Pad software ) or SAS . Comparisons were done using nonparametric t tests , as appropriate and ANOVA . For the analysis of data in Fig 4E , a Box-Cox power transformation was applied to the data before analysis to meet the normality assumption of the model . Two-way ANOVA was used for the SHIV+ versus uninfected and pre- versus post-hetIL-15 effects , with random effects to account for the clustered values by animal . | Heterodimeric interleukin-15 ( hetIL-15 ) , the stable native complex of IL-15 and IL-15 Receptor α ( IL-15/IL-15Rα ) , activates and expands cytotoxic T and NK cells . Based on these properties , hetIL-15 is currently being evaluated in clinical trials in advanced cancer . To explore potential utility in AIDS virus infection , we evaluated the effects of hetIL-15 in uninfected rhesus macaque monkeys or monkeys with low levels of chronic viremia after SHIV infection . hetIL-15 treatment increased CD8+ lymphocytes within the B cell follicles of lymph nodes and decreased cell-associated viral RNA in LN as well as plasma viremia . These results suggest hetIL-15 may have beneficial effects in chronic HIV infection by allowing CD8+ T cells to access infected cells within otherwise immune privileged sanctuary sites in B cell follicles of secondary lymphoid tissues . | [
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"... | 2018 | Treatment with native heterodimeric IL-15 increases cytotoxic lymphocytes and reduces SHIV RNA in lymph nodes |
Melioidosis , caused by the flagellated bacterium Burkholderia pseudomallei , is a life-threatening and increasingly recognized emerging disease . Toll-like receptor ( TLR ) 5 is a germline-encoded pattern recognition receptor to bacterial flagellin . We evaluated the association of a nonsense TLR5 genetic variant that truncates the receptor with clinical outcomes and with immune responses in melioidosis . We genotyped TLR5 c . 1174C>T in 194 acute melioidosis patients in Thailand . Twenty-six ( 13% ) were genotype CT or TT . In univariable analysis , carriage of the c . 1174C>T variant was associated with lower 28-day mortality ( odds ratio ( OR ) 0 . 21 , 95% confidence interval ( CI ) 0 . 05–0 . 94 , P = 0 . 04 ) and with lower 90-day mortality ( OR 0 . 25 , 95% CI 0 . 07–086 , P = 0 . 03 ) . In multivariable analysis adjusting for age , sex , diabetes and renal disease , the adjusted OR for 28-day mortality in carriers of the variant was 0 . 24 ( 95% CI 0 . 05–1 . 08 , P = 0 . 06 ) ; and the adjusted OR for 90-day mortality was 0 . 27 ( 95% CI 0 . 08–0 . 97 , P = 0 . 04 ) . c . 1174C>T was associated with a lower rate of bacteremia ( P = 0 . 04 ) and reduced plasma levels of IL-10 ( P = 0 . 049 ) and TNF-α ( P < 0 . 0001 ) . We did not find an association between c . 1174C>T and IFN-γ ELISPOT ( T-cell ) responses ( P = 0 . 49 ) , indirect haemagglutination titers or IgG antibodies to bacterial flagellin during acute melioidosis ( P = 0 . 30 and 0 . 1 , respectively ) . This study independently confirms the association of TLR5 c . 1174C>T with protection against death in melioidosis , identifies lower bacteremia , IL-10 and TNF-α production in carriers of the variant with melioidosis , but does not demonstrate an association of the variant with acute T-cell IFN-γ response , indirect haemagglutination antibody titer , or anti-flagellin IgG antibodies .
Melioidosis is caused by the Gram-negative , flagellated bacillus and environmental saprophyte , Burkholderia pseudomallei , which the US Centers for Disease Control and Prevention ( CDC ) have identified as a Tier 1 bioterrorism agent . Clinical presentations of melioidosis range from acute sepsis to chronic and persistent infections , and the overall mortality rate can exceed 40% in endemic regions including northeast Thailand [1–3] . Pre-existing conditions such as diabetes , renal disease , excessive alcohol use and increasing age are known risk factors [1 , 2] . Further expansion of endemic boundaries of melioidosis [4–7] , increasing prevalence of diabetes [8] , and population ageing [9] lead to an urgent demand for a vaccine against melioidosis , especially in at-risk populations . Understanding host defense mechanisms against B . pseudomallei infection is crucial for vaccine design and development , to allow selection of the best vaccine platform including adjuvant , and may drive development of novel therapeutics . Emerging evidence suggests the importance of membrane-bound Toll-like receptors ( TLRs ) in defense against B . pseudomallei infection in vitro and in vivo [10–12] , and the TLR5 ligand flagellin has potential as a vaccine adjuvant [13] . Single nucleotide variants ( SNV ) in TLR genes may influence the innate immune response by altering the magnitude and quality of intracellular signaling cascades with implications for susceptibility to infection and disease outcomes [14] . A recent analysis demonstrated a significant association of the TLR5 SNV c . 1174C>T with protection against organ failure and death in melioidosis [15] . This variant encodes a stop codon at position 392 , truncating the receptor in the extracellular domain [16] . c . 1174C>T is associated with lower TLR5-mediated innate immune responses in vitro and in healthy subjects whose blood was stimulated ex vivo [15] . This hypofunction in TLR5 signaling may result in lower immunopathology and in turn a reduction in sepsis-induced organ failure and death . Furthermore , reduced TLR5 signaling could result in lower levels of the regulatory cytokine interleukin-10 ( IL-10 ) , leading to less suppression of the host immune defense against the bacteria [15] . However , the relationship between c . 1174C>T and innate immune responses has not been studied in patients with melioidosis . TLRs activate signals crucial for the initiation and modulation of adaptive immune responses such as TLR-dependent dendritic cell control of T-cell activation [17] . Many individuals living in northeast Thailand become seropositive to B . pseudomallei at a young age , indicating that environmental exposure to the bacterium and the development of adaptive immune responses in the absence of clinical infection is common [18] . A previous study in this cohort reported reduced T-cell responses in patients with acute melioidosis that did not survive [19] , raising the possibility that c . 1174C>T may protect against death by enhancing T-cell mediated immunity against B . pseudomallei . Therefore it was important to characterize the association between c . 1174C>T and adaptive immune responses in melioidosis . The objective of this study was to confirm in an independent , prospectively designed cohort the previously reported association of c . 1174C>T with survival in acute melioidosis , and to determine whether c . 1174C>T is associated with innate and adaptive immune responses in patients with melioidosis .
The study was approved by the ethics committees of Faculty of Tropical Medicine , Mahidol University ( Submission number TMEC 12–014 ) ; of Sappasithiprasong Hospital , Ubon Ratchathani ( reference 018/2555 ) ; and the Oxford Tropical Research Ethics Committee ( reference 64–11 ) . The study was conducted according to the principles of the Declaration of Helsinki ( 2008 ) , and the International Conference on Harmonization ( ICH ) Good Clinical Practice ( GCP ) guidelines . Written informed consent was obtained for all patients enrolled in the study . The prospective recruitment of patients with melioidosis for immunological studies at Sappasithiprasong Hospital , Ubon Ratchathani , Thailand has been described previously [19] . Two hundred in-patients aged 18 years or older with melioidosis were enrolled , at a median of 5 days ( IQR 3–6 , range 2–13 ) after admission . Melioidosis was defined as isolation of B . pseudomallei from any clinical sample ( blood , sputum , throat , endotracheal , bronchoalveolar lavage , pus , or urine ) , submitted to the laboratory . HIV status was not tested but previous work in the hospital has shown HIV rates are low and HIV is not a major risk factor for melioidosis [20] . Whole blood samples were collected at the time of enrollment ( week 0 ) , as well as again at weeks 12 and 52 after admission to hospital in surviving patients . 194 patients were successfully genotyped and analyzed in this study . Genomic DNA was extracted from blood samples using QIAamp DNA Blood Midi kit ( QIAgen , Hilden , Germany ) according to the company’s instruction and stored at -20°C . The TLR5 c . 1174C>T ( rs5744168 ) SNV was genotyped using TaqMan® SNP genotyping assay ( Applied Biosystems , CA , USA ) on a CFX96 Touch Real-Time PCR Detection System ( BioRad , Hercules , USA ) . The SNV context sequence was TGAATGGTTGTAAGAGCATTGTCTC[A/G]GAGATCCAAGGTCTGTAATTTTTCC . The magnitude of cellular responses to B . pseudomallei was determined by ex vivo IFN-γ ELISPOT assay , as previously described [19] . Briefly , 96-well Multiscreen-I plates ( Millipore , UK ) were coated with 1D1K anti-human IFN-γ ( Mabtech , AB , Sweden ) and stored at 4°C overnight . Fresh peripheral blood mononuclear cells ( PBMC ) at 2 x 105 cells per well were added in duplicate and whole heat-inactivated B . pseudomallei ( HIA-Bp ) clinical isolates 199a and 207a [21] at concentration of 20 μg/ml were then added . Phytohemagglutinin ( PHA ) at final concentration of 5 μg/ml and RPMI-1640 were used as positive and negative controls , respectively . A T cell peptide pool ( CEF , ( Mabtech ) at concentration of 1 μg/ml was used as control antigens . After 18 hours , secreted IFN-γ was detected following the manufacturer’s protocol ( Mabtech ) and read under CTL ELISPOT reader . Results are expressed as IFN-γ spot-forming cells ( SFC ) per million PBMC . Titers of antibodies against B . pseudomallei were assessed by IHA following a standard protocol at the Mahidol-Oxford Tropical Medicine Research Unit , as modified from a protocol previously described [18 , 22] . Briefly , two-fold dilutions of patient serum were added to 96-well U bottom microplate containing 25 μl of HIA-Bp-sensitized sheep red blood cells . Plates were left at room temperature for 2 hours before incubation at 4°C overnight . The results were recorded as the highest dilution when a positive reaction was observed . The cut off was set at a dilution of 1:40 . Plasma levels of IgG antibodies specific to flagella of B . pseudomallei were determined by rapid Enzyme-Linked Immunosorbant Assay ( ELISA ) , as described in a previous study [23] using recombinant flagellin ( rFliC ) as the coating antigen . The fliC gene ( BPSL3319 ) was PCR amplified from B . pseudomallei K96243 genomic DNA , cloned into pBAD/HisA ( Invitrogen , USA ) and expressed in E . coli as previously described [24] . To perform ELISA , the purified rFliC antigen was added to wells of a 96-well U-bottom immunoplate ( Nunc MaxiSorp U-bottom 96-Well plates; Thermo Scientific , Denmark ) at a concentration of 15 μg/ml and incubated overnight at 4°C . Between each step , the ELISA plate was washed with 0 . 05% Tween-20 in PBS 4 times . After blocking at 37°C for 2 hours with 5% skim milk in PBS , patients’ plasma was diluted 1:300 and added to the pre-coated ELISA plate in duplicate then incubated at room temperature for 2 hours . The secondary antibody , HRP-conjugated rabbit antihuman IgG ( DAKO , Copenhagen , Denmark ) , was diluted 1:2000 then added to the plate and incubated for 30 minutes . ELISAs were developed using TMB substrate . Results were determined as absorbance value ( OD450 ) . Pooled plasma from five melioidosis patients and five healthy controls were used as positive and negative controls , respectively . Heparinized plasma for immunoassays was separated from blood by density centrifugation within three hours of blood draw . Cytokine levels in the plasma were quantified by using ELISA kits according to manufacturers’ instructions; The Human IL-10 and TNF-α Instant ELISA kits ( eBioscience , San Diego , CA , USA ) , human granulocyte colony-stimulating factor ( G-CSF ) ELISA kit ( Abcam , Cambridge , MA , USA ) , and human transforming growth factor beta 1 ( TGF-β1 ) DuoSet ELISA kit ( R&D systems , Minneapolis , MN , USA ) . Concentrations of cytokines were calculated from standard curves . Categorical variables were displayed as counts and proportions , and were compared using Pearson’s chi squared test or Fisher’s exact test . Non-normally distributed continuous data were reported as median and interquartile range ( IQR ) . The significance of differences between two groups was analyzed by Mann-Whitney U-test in Graphpad Prism Version 6 ( San Diego , USA ) . In addition , immunological data was divided into tertiles and the distribution of the TLR5 genotype was compared between the highest third and lowest third of responses by Mann-Whitney U-test . To test the association of genotype with outcome , we performed univariable logistic regression and multivariable logistic regression adjusting for age , sex , diabetes and pre-existing renal disease using Stata version 14 . 0 for Window ( StataCorp LP , TX , USA ) . Survival analysis was assessed with log-rank test of Kaplan-Meier curve by Stata version 11 . 1 . A P value <0 . 05 was considered significant .
To confirm the previously reported association of the TLR5 variant c . 1174C>T ( rs5744168 ) with protection against death in acute melioidosis patients , we genotyped the variant in 194 Thai patients with culture-proven melioidosis admitted at Sappasithiprasong Hospital . Of these , 168 ( 86 . 6% ) were genotype CC , 25 ( 12 . 8% ) were CT and one ( 0 . 5% ) was TT . The characteristics of the melioidosis patient cohort have been described in detail elsewhere [19] , with key clinical information including demographics and risk factors shown in Table 1 . Despite receiving appropriate antibiotic treatment , 25 . 3% ( 49/194 ) of patients died within 28 days of admission to hospital ( 28-day mortality ) . A further 12 patients died between days 29 and 90 after admission resulting in a 90-day mortality rate of 31 . 4% ( 61/194 ) . We confirmed Hardy–Weinberg equilibrium in survivors ( P = 1 ) before testing the association of c . 1174C>T with mortality . When 28-day mortality was selected as outcome , 16 . 6% of survivors were CT or TT genotypes , whereas 4 . 1% of non-survivors were these genotypes ( P = 0 . 055 , Table 2 ) . We also observed the same pattern in analysis of 90-day mortality: 17 . 3% of survivors were heterozygotes or minor homozygotes , compared with 4 . 9% of non-survivors ( P = 0 . 03 ) . In a dominant genetic model ( combining CT and TT subjects into the same group ) , the c . 1174C>T variant was significantly associated with survival at both 28 days and 90 days [odds ratio ( OR ) for death 0 . 21 , 95% Confidence Interval ( CI ) 0 . 05–0 . 94 , P = 0 . 04 for 28-day mortality , and OR 0 . 25 , 95% CI 0 . 07–086 , P = 0 . 03 for 90-day mortality] . We also plotted the Kaplan Meier survival curve by c . 1174C>T genotype for melioidosis subjects ( Fig 1 ) . The risk of death for subjects carrying the CC genotype was significantly higher than those carrying CT or TT genotypes by the log-rank test ( P = 0 . 03 ) . We next evaluated the association between the c . 1174C>T variant and bacteremia . In this cohort of melioidosis patients , 99 patients ( 51% ) had bacteremia and bacteremia was tightly associated with mortality ( P < 0 . 0001 , Table 1 ) [19] . Thus , bacteremia can be considered an intermediate outcome measure for control of B . pseudomallei . Our results in the present study show that 8 . 1% ( 8/99 ) of patients with bacteremia were CT or TT genotypes , compared with 19 . 0% ( 18/95 ) of patients who had no bacteremia ( P = 0 . 04 , Table 2 ) . We found that the c . 1174C>T variant was associated with a lower rate of bacteremia in an unadjusted dominant model ( OR for bacteremia 0 . 38 , 95% CI 0 . 15–0 . 91 , P = 0 . 03 ) . Taken together , these results demonstrate a decrease in fatality and bacteremia in patients carrying the TLR5 c . 1174C>T variant compared to those without the variant . To take into account other drivers of immune responses to bacterial infection , we next tested the association of the c . 1174C>T variant with death using an adjusted multivariable model including potential confounding variables . The odds ratio point estimates of the effect of c . 1174C>T on mortality did not change appreciably from the univariable model . The c . 1174C>T variant showed a borderline evidence of an association with 28-day mortality ( P = 0 . 06 ) but remained significantly associated with 90-day mortality ( P = 0 . 04 ) and bacteremia ( P = 0 . 04 ) when sex , age and the major pre-existing conditions of diabetes and renal disease were incorporated into the model ( S1 Table ) . We also found a significant association between increasing age and 28-day mortality ( OR 1 . 037 95% CI 1 . 009–1 . 066 for each year of age ) and 90-day mortality ( OR 1 . 030 95% CI = 1 . 012–1 . 067 for each year of age ) in the multivariable-adjusted logistic regression model . In our cohort , the odds of bacteremia for melioidosis patients with pre-existing renal disease were 3 . 7 times higher than for those without renal disease ( P = 0 . 003 , S1 Table ) . We did not observe any significant association gender or diabetes and 28-day mortality , 90-day mortality or bacteremia . We then examined the relationship between c . 1174C>T and absolute neutrophil and lymphocyte counts during acute melioidosis . As shown in Table 3 , the median peripheral blood neutrophil count of patients with the CC genotype was comparable to that of patients with CT or TT genotypes ( P = 0 . 87 ) . In contrast , absolute lymphocyte counts in patients with the CC genotype were significantly lower than those of patients with CT or TT genotypes ( Table 3; P = 0 . 02 ) . T cell responses as quantified by IFN-γ ELISPOT and IHA titers to B . pseudomallei are lower in patients with melioidosis who do not survive [19] . In the previous study , we found undetectable or very low mean IFN-γ ELISPOT response in healthy controls ( 15 SFC per million PBMC ) when compared with melioidosis patients ( 133 SFC per million PBMC ) [19] . We therefore evaluated the association of c . 1174C>T with these adaptive immune responses to B . pseudomallei in melioidosis patients . At the time of enrollment with acute melioidosis ( median day 5 of hospitalization ) , the median IFN-γ ELISPOT response of subjects with the CC genotype was not different from those having CT or TT genotypes after stimulation with either the T-cell control peptide pool CEF ( P = 0 . 32 ) or heat-killed B . pseudomallei ( P = 0 . 49; Table 3 , S1A and S1B Fig ) . When subjects’ responses were grouped in tertiles according to IFN-γ ELISPOT results , we did not observe any difference in low ( ≤ 7 . 5 SFC/106 PBMC ) and high responders ( ≥65 SFC/106 PBMC ) by genotype . The median IFN-γ ELISPOT result of low responder with CC and CT or TT genotypes was 1 ( IQR 1–2 . 5 ) and 3 ( IQR 1–5 ) , respectively ( P = 0 . 47 ) ; and those result of high responder with CC and CT or TT genotypes was 201 . 25 ( IQR 92 . 5–380 ) and 262 . 5 ( IQR 105–625 ) , respectively ( P = 0 . 43 ) . We assessed the relationship of c . 1174C>T with IHA titer . There was no difference based on genotype as the median IHA titer at the time of enrollment of patients carrying CC was 160 ( IQR 40 to 1280 ) and those of individuals carrying CT or TT was 80 ( IQR 18 to 640 , P = 0 . 30; Table 3 and S1C Fig ) . Grouping the IHA titer by low ( titer ≤ 1:160 ) and high responder ( titer > 1: 160 ) status also did not demonstrate any relationship with genotype . Likewise , plasma levels of IgG antibodies to B . pseudomallei flagellin , a known ligand of TLR5 , ( anti-FliC ) , obtained at enrollment , were not statistically significantly different between melioidosis patients with CC ( median 0 . 53 , IQR 0 . 23–1 . 45 ) and CT or TT genotypes ( median 0 . 92 , IQR 0 . 42–1 . 45 , P = 0 . 10 , Table 3 and S1D Fig ) . We also found that plasma anti-FliC antibody levels were not significantly different between survivors ( median 0 . 57 , IQR 0 . 25–1 . 37 ) and fatal cases ( median 0 . 48 , IQR 0 . 26–1 . 59 , P = 0 . 64 ) . We also evaluated the relationship between c . 1174C>T and the kinetics of the T-cell IFN-γ response and IHA titer over one year ( sample were collected at week 0 , 12 and 52 ) . We did not see a significant difference of kinetics in IFN-γ ELISPOT response between these two patients groups ( S2A Fig ) . However , we found that the median IHA titer of patients with CT or TT genotypes ( median 10 . 5 , IQR 1–160 ) was significantly lower than those having CC genotype ( median 320 , IQR 80–640 ) at week 12 after admission ( P < 0 . 001 ) but not at the other time points ( S2B Fig ) . Although we found a reduced IHA titer in survivors of melioidosis with CT or TT genotypes at week 12 after admission , the results in the present study do not demonstrate an effect of c . 1174C>T on the measured T-cell IFN-γ response , IHA titer , or plasma levels of anti-FliC IgG antibodies during the acute phase of B . pseudomallei infection . Stimulation of whole blood with B . pseudomallei has been previously shown to induce lower levels of monocyte-normalized IL-10 and granulocyte colony-stimulating factor ( G-CSF ) in healthy individuals with CT or TT genotypes [15] . To determine whether this association of c . 1174C>T with experimentally induced inflammatory responses holds during acute melioidosis , we measured the levels of these two cytokines in the plasma of melioidosis patients in our cohort . IL-10 levels were significantly lower in carriers of CT or TT ( Table 3 and S3A Fig; median 8 . 6 , IQR 0 . 34 to 21 . 74 ) than in those with CC ( median 17 . 0 , IQR 6 . 0 to 35 . 2 , P = 0 . 049 ) . However , we did not observe a difference of plasma G-CSF levels by genotype ( Table 3 and S3B Fig; P = 0 . 83 ) . We next assayed plasma levels of the pro-inflammatory cytokine TNF-α that has been previously associated with death in melioidosis [25] . We found that plasma TNF-α levels in patients with the CC genotype ( Table 3 and S3C Fig; median 4 . 73 , IQR 0 . 605 to 7 . 66 ) were significantly higher than those having CT or TT genotypes ( mostly undetectable ) . In addition , the patients with bacteremia also showed a trend toward higher levels of TNF-α in plasma ( median 3 . 65 , IQR 0–7 . 28 ) compared with those with no bacteremia ( median 0 . 53 , IQR 0–4 . 51 , P = 0 . 06 ) . We also measured plasma levels of transforming growth factor beta 1 ( TGF-β1 ) , another immunoregulatory cytokine , but we did not observe a significant difference between patients with CC compared to CT or TT genotypes ( Table 3 and S3D Fig; P = 0 . 21 ) .
Data in this study confirm a previous report [15] demonstrating a significant association between the nonsense TLR5 c . 1174C>T variant and survival in melioidosis patients . We also identified a relationship between c . 1174C>T and lower rates of bacteremia , which represents improved control of the infection . These data underscore the importance of TLR5-dependent signaling in driving clinical outcomes in human melioidosis . In melioidosis patients , c . 1174C>T was also associated with lower plasma levels of both pro-inflammatory cytokine TNF-α and anti-inflammatory cytokine IL-10 , implicating differential activation of innate immunity in the mechanism of increased survival attributable to c . 1174C>T . In this population with likely broad subclinical exposure to B . pseudomallei and the development of adaptive immunity , suppressed T-cell responses to B . pseudomallei are associated with death from acute melioidosis [19] . However , we did not find evidence that the TLR5 c . 1174C>T variant drives the T-cell IFN-γ response , IHA titer , or anti-FliC antibody response during acute melioidosis , suggesting that the mechanism of enhanced survival in carriers of the TLR5 variant may be independent of these adaptive immunological responses . Our finding of an inhibitory effect of c . 1174C>T on IL-10 production in acute melioidosis extends findings from a previous study [15] in which blood from healthy individuals carrying the c . 1174C>T variant released less IL-10 upon stimulation with B . pseudomallei . Together these data suggest a possible role for TLR5-driven IL-10 release in modulating risk of death in melioidosis [25 , 26] . Low concentrations of IL-10 in plasma may diminish suppressive activity of immune responses , resulting in augmentation of pro-inflammatory activity , and control of bacterial infection . However , our study does not establish causation , and more in-depth investigation is required to clarify the mechanism of TLR5-dependent IL-10 function in melioidosis . In contrast to whole blood stimulation studies in healthy subjects [15] , we found significantly lower levels of plasma TNF-α in melioidosis patients carrying c . 1174C>T . This result agrees with studies in rheumatoid arthritis and Salmonella infections , in which flagellin-induced TLR5 ligation leads to upregulation of TNF-α in monocytes or macrophages [27–29] . TNF-α plays a key role in neutrophil recruitment in the inflammatory response to infections; nevertheless , it can also enhance bacterial growth [30 , 31] . Interestingly , we also found a strong trend towards higher plasma TNF-α levels and the presence of bacteremia . As bacteremia is tightly linked with death , this is consistent with a previous study reporting increased TNF-α levels in non-survivors of melioidosis [25] . In our study , carriers of c . 1174C>T had no effect on G-CSF or TGF-β1 production . It is postulated that the release of these cytokines might pass through or compensate by other pathways . TLR5 plays a critical role in connecting innate and adaptive immunity in other bacterial infections . Accumulating evidence demonstrates that flagellin ligation of TLR5 can simultaneously initiate MyD88-dependent and Spleen tyrosine kinase ( Syk ) -dependent pathways leading to pro-inflammatory cytokine secretion and antigen presentation to flagellin-specific CD4 T cells , respectively [32–34] . TLR5 activation can also lead to suppression of adaptive immune responses by pathways involving IL-10 as discussed , myeloid-derived suppressor cells ( MDSC ) [35] and regulatory T-cells ( Treg ) [36] . However , we did not observe an association between the TLR5 c . 1174C>T genotype and IFN-γ secreting B . pseudomallei-specific T-cell responses nor serum anti-B . pseudomallei antibody titers during the acute stage ( week 0 ) of bacterial infection in this study . The stimuli used in the assays of adaptive immunity in this study may have induced too broad a response to identify the distinct downstream responses of c . 1174C>T variant . The T-cell IFN-γ response and IHA titer in our study were assessed using heat-killed whole-cell B . pseudomallei , which contains a large number of immunogenic antigens . Many bacterial antigens including lipopolysaccharide ( LPS ) and acyl hydroperoxide reductase ( AhpC ) can elicit both B- and T-cell responses via other immunogenic pathways besides TLR5 [37 , 38] . We observed comparable plasma levels of anti-FliC IgG between patients with CC and CT or TT genotypes during acute melioidosis . Sanders et al [39] demonstrated that Salmonella flagellin elicits a strong IgG response in TLR5-/- mice , indicating that TLR5 is not required for antibody responses to flagellin . Therefore , it is postulated that B . pseudomallei flagellin may also promote humoral immunity via a TLR5-independent pathway similar to that reported during Salmonella infection . Although we did not see a relationship between TLR5 genotype and IHA titer during acute melioidosis , we found an association between c . 1174C>T variant and reduced IHA titer in survivors during convalescence from disease ( 12 weeks after admission ) . This could be due to the impact of TLR5 engagement on antibody production and secretion of terminally differentiated plasma cells compared with B-cells at an earlier maturation stage [40] . However , further study on the detailed mechanism of TLR5 triggering on memory B cells is required . The TLR5 c . 1174C>T variant was associated with a higher absolute lymphocyte count , but not with T-cell responses . The increased number of lymphocytes in patients carrying the variant may result from the reduced suppressive effect of IL-10 induced during acute melioidosis . Further studies should aim to characterize this increased lymphocyte population with a particular focus on B-cells , NK cells or subsets of T cells that do not produce IFN-γ . In our study , the TLR5 c . 1174C>T variant did not influence the quantity of neutrophils in melioidosis patients . TLR5 c . 1174C>T might play a critical role only in inflammatory cytokine responses against melioidosis , contributing to control of bacterial infection before adaptive immunity takes place . Otherwise , the relationship between TLR5 c . 1174C>T and adaptive immunity may be present but our study had insufficient power or did not measure the relevant T-cell or antibody response . Additional studies focusing on the relationship between the TLR5 c . 1174C>T and adaptive immune responses against B . pseudomallei flagellin may uncover an association . Further studies will address the direct and crucial link between innate and adaptive immunity of TLR5 in B . pseudomallei . In summary , the results of our study provide critical confirmation of the association of TLR5 c . 1174C>T genotype with protection against death in acute melioidosis patients . Our results also suggest that the genotype c . 1174C>T in melioidosis patients is associated with reduced production of both pro-inflammatory cytokine TNF-α and anti-inflammatory cytokine IL-10 at the early stage of infection . Although TLR5 genotype is associated with protection against melioidosis , other factors underlying host defense mechanisms merit exploration in further studies . | Melioidosis is a high-mortality infectious disease in Southeast Asia and northern Australia caused by Burkholderia pseudomallei , which is a flagellated , rod-shaped Gram-negative bacterium . Understanding protective host immune responses to melioidosis is fundamental for effective vaccine development . A previous study demonstrated a strong relationship between a TLR5 stop codon polymorphism that encodes a truncated receptor for bacterial flagellin and protection against death from melioidosis . In this study , we confirmed the relationship of this genetic variant with survival from acute melioidosis in adult patients in northeast Thailand , and identified an association with a lower rate of bacteremia . We also demonstrated that this variant was associated with an increase in peripheral lymphocyte count , but we did not find an association with B . pseudomallei-specific lymphocyte responses; i . e . , IFN-γ secreted T cell response , indirect haemagglutination titers or anti-flagellin IgG antibodies . In addition , patients with the TLR5 variant have significantly lower levels of IL-10 and TNF-α cytokines in plasma . Our findings further the understanding of the role of TLR5 in protective host immune responses against fatal melioidosis , and inform efforts to develop novel vaccines and therapeutics for melioidosis . | [
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"bi... | 2017 | A nonsense mutation in TLR5 is associated with survival and reduced IL-10 and TNF-α levels in human melioidosis |
The cerebral cortex performs complex cognitive functions at the expense of tremendous energy consumption . Blood vessels in the brain are known to form stereotypic patterns that facilitate efficient oxygen and nutrient delivery . Yet little is known about how vessel development in the brain is normally regulated . Radial glial neural progenitors are well known for their central role in orchestrating brain neurogenesis . Here we show that , in the late embryonic cortex , radial glial neural progenitors also play a key role in brain angiogenesis , by interacting with nascent blood vessels and regulating vessel stabilization via modulation of canonical Wnt signaling . We find that ablation of radial glia results in vessel regression , concomitant with ectopic activation of Wnt signaling in endothelial cells . Direct activation of Wnt signaling also results in similar vessel regression , while attenuation of Wnt signaling substantially suppresses regression . Radial glial ablation and ectopic Wnt pathway activation leads to elevated endothelial expression of matrix metalloproteinases , while inhibition of metalloproteinase activity significantly suppresses vessel regression . These results thus reveal a previously unrecognized role of radial glial progenitors in stabilizing nascent brain vascular network and provide novel insights into the molecular cascades through which target neural tissues regulate vessel stabilization and patterning during development and throughout life .
The brain consumes approximately10 times as much energy per unit volume as the rest of the body and thus requires a highly efficient vascular network for oxygen and nutrient delivery as well as waste disposal . Cortical blood vessels display a highly complex and hierarchical pattern [1] , [2] , of which a most striking feature is the regularity by which large vessels penetrate the cortex from the pia at right angles . These vessels then give off branches and capillaries at various depths , yielding an intricate network . Such stereotypic organizations provide a unique opportunity for understanding how target-specific cell types and signals regulate vascular network formation and patterning and coordinate neural and vascular function during development and throughout life . Vascular patterning , in principle , may be regulated by guided growth as well as selective stabilization , as is probably best demonstrated in the formation of another cellular network , the neural circuitry 3 , 4 . Indeed , several axon guidance cues have been identified that direct vessel growth [5] , [6] . For example , semaphorins and netrins have been found to restrict vessel growth to intersomitic regions during embryogenesis [7] , [8] , while peripheral nerves appear to determine patterns of vessel branching and differentiation , in part through local secretion of vascular endothelial growth factor ( VEGF ) [9] . In contrast , little is known about how target neural tissues regulate the later step of vessel stabilization . Neural cells have long been known to play a key role in vessel differentiation in the central nervous system ( CNS ) . In the developing retina , endothelial cells ( ECs ) follow a meshwork laid down by astrocytes [10] . Astrocytes also appear to induce CNS-specific EC differentiation [11] . In the embryonic cerebral cortex , astrocytes are known to be largely absent . However , there is another cell type with notable similarities [12]–[14] . These are the radial glia , primary neural progenitors of the developing cortex that also closely interact with growing vessels [15] , [16] . Moreover , several neural-specific mutations also result in compromised brain vessel development [17]–[20] , which further supports a role of neural cells in regulating CNS angiogenesis . Studies have shown that , both inside and outside the nervous system , canonical Wnt signaling is a major pathway that regulates several steps of blood vessel development , including initial neural-tube vessel ingression , retinal vessel stabilization , intersomitic vessel remodeling , and hyaloid vessel regression [19] , [21]–[25] . Interestingly , during early CNS vessel development , Wnt signaling from neural progenitors has been found to be essential for initial vessel ingression from outside into the neural tube [19] , [23] . By contrast , in the eye , Wnt signaling from macrophages induces hyaloid vessel regression [21] , [22] . This suggests that Wnt signaling can have distinct , and even opposite , effects at different stages of angiogenesis and/or in different tissues . Moreover , constitutively active Wnt signaling also leads to compromised vessel development throughout the embryo [25] . This indicates that the level of Wnt signaling is also crucial for normal angiogenesis . Thus , these results suggest that canonical Wnt signaling is tightly and dynamically regulated and plays a multifaceted role during blood vessel development . Here we investigate the role of radial glial progenitors in vessel stabilization during late embryonic corticogenesis , following the formation of a primitive vascular network . We find that ablation of radial glia at this stage results in vessel regression , which suggests a role of radial glia in vessel stabilization . Vessel regression under these conditions is closely linked to ectopic activation in ECs of canonical Wnt signaling and is mimicked by activation , but substantially suppressed by attenuation , of Wnt pathway activity . This indicates that radial glia control vessel stabilization , in large part , through inhibition of Wnt signaling . Furthermore , we find that radial glia inhibits EC Wnt signaling at E15 . 5 but not E13 . 5 . This indicates a stage-specific inhibition of EC Wnt signaling by radial glia . Lastly , we find that ablation of radial glia and activation of Wnt signaling each leads to elevated expression in ECs of matrix metalloproteinases , while attenuation of metalloproteinase activity substantially suppresses vessel regression . This suggests that vessel stabilization by radial glia may be in part mediated through inhibition of metalloproteinase expression . Together , these results reveal novel insights into the molecular cascade ( s ) through which neural progenitors regulate vessel stabilization and patterning during brain development .
Previous studies have documented bursts of vessel sprouting at different depths in the postnatal rat cortex [26] . To determine how vessel growth in the prenatal murine cortex is regulated , we systematically examined isolectin B4 ( IB4 ) staining from embryonic day12 . 5 ( E12 . 5 ) to postnatal day 0 ( P0 ) ( Figure 1A–D , and unpublished data ) . We found that vessels from the pial perineural vascular plexus first invade the cortical plate around E12 . 5 ( unpublished data ) . By E14 . 5 , a significant density of vessels can be observed in the cortical plate ( Figure 1A ) . As the cortical plate expands , vessel density increases at E15 . 5 ( Figure 1B ) . Subsequently , at E16 . 5 , a primitive vascular network begins to appear ( Figure 1C ) . By E17 . 5 , prominent vertically oriented vessels are observed ( Figure 1D ) . Quantification revealed that vessel density in the cortical plate first rises sharply from E13 . 5 to E15 . 5 but stays relatively stable after E15 . 5 ( Figure 1E ) . Concomitantly , vessel branch point frequency increases substantially from E13 . 5 to E15 . 5 and E16 . 5 ( Figure 1F ) , suggesting sprouting as a major mode of growth during this early period . By E17 . 5 , however , although vessel density remains comparable to those of E15 . 5 and E16 . 5 ( Figure 1E ) , branch point frequency becomes dramatically lower than those of the earlier stages ( Figure 1F ) . This suggests that most of the vessel growth from E16 . 5 to E17 . 5 likely results from elongation of existing vessels . At E17 . 5 , the vast majority of cortical plate vessels are aligned vertically ( Figure 1D ) , in contrast to E16 . 5 , when frequent horizontal branches are observed ( Figure 1C ) . These changes suggest preferential elongation and stabilization of vertically oriented vessels and/or elimination of horizontal branches . Indeed , using an mTomato/mEGFP dual fluorescent cre reporter [27] , which , under the control of a neural specific nestin-cre [28] , [29] , expresses mEGFP in targeted neural precursors and mTomato in unrecombined vascular cells , we also observed similar changes in the pattern of cortical plate vessels ( Figure 1G–H″ ) . At E16 . 5 , we found that mTomato positive vessels show significant lateral branches ( Figure 1G′ ) . By contrast , at E17 . 5 , the vast majority of vessels appear oriented vertically , with few lateral branches ( Figure 1H′ ) . Quantification of IB4 positive vessels also showed that there is not only a decrease in the frequency of vessel branch points from E16 . 5 to E17 . 5 ( Figure 1F ) , but also a reduction in the absolute number of branch points over the entire cortical plate during this period ( E16 . 5 , 26±0 . 6; E17 . 5 , 17±1 . 8; p<0 . 004 , n = 3 ) . Thus , vessel development in the embryonic cortical plate appears to go through an initial phase of sprouting , followed by remodeling during which vertically oriented vessels are stabilized . The vertical orientation of cortical plate vessels at E17 . 5 is reminiscent of that of radial glial fibers . Previously , close interactions have been observed between blood vessels and intermediate progenitors in the subventricular zone [30] . To examine the interactions between blood vessels and radial glial fibers in the cortical plate at these late embryonic stages , we employed triple labeling and three-dimensional reconstruction to examine , simultaneously , the spatial relationship between radial glia , ECs , and pericytes at E16 . 5 ( Figure 1I–J ) . We found that , despite significant coverage of blood vessels by percicytes at this stage , there is a similar proportion of EC surface areas that are exposed and through which ECs physically interact with radial glial fibers . Indeed , radial glia and pericytes frequently appear to interdigitate in their interactions with ECs ( see also Movies S1 and S2 ) . Similar direct interactions between radial glia and ECs were also observed when we used an anti–brain lipid binding protein ( BLBP ) antibody to label radial glia ( Figure 1K–L ) . These findings suggest a potential role of radial glia in regulating vessel development at this stage . They are also consistent with previous electron microscopy data showing that ECs directly interact with astrocytes in the postnatal cortex [31] . In addition , in the late embryonic cortex of β1 integrin/emx1-cre mutants where radial glial fibers sometimes run obliquely , we also observed blood vessels running at the same angle ( unpublished data ) . This further suggests a role of radial glia in regulating blood vessel development at this stage . Thus , these findings altogether raise the possibility that radial glia may play a role in regulating cortical plate vessel stabilization during late embryogenesis . Radial glia constitute a major population of neural progenitors in the embryonic cortex , the rest being intermediate progenitors as well as a very small number of outer radial glia-like progenitors [12] , [13] . Thus , we reasoned that neural lineage-specific blockade of cell cycle progression during late embryogenesis may allow relatively selective ablation of radial glia and an evaluation of their role in cortical vessel stabilization . To this end , we employed a conditional knockout allele we generated of orc3 , a gene encoding a core subunit of origin recognition complex ( ORC ) , a complex composed of Orc1–6 , of which all are essential for DNA replication [32] . We targeted orc3 locus by floxing exons 5–7 , creating an early truncation ( Figure S1A–C ) . We found that homozygotes of the floxed orc3 allele are viable and fertile , without obvious phenotypes , while germline deletion of orc3 results in early embryonic lethality . We also confirmed that Orc3 protein is lost from mutant cortices ( Figure S1D–E ) . To block radial glial division , we deleted orc3 using the nestin-cre we employed above ( Figure 1G–H″ ) . Nestin is known to be expressed in neural as well as vascular cells , and several lines of nestin-cre transgenic mice , using the neural-specific nestin enhancer element , have been generated , with distinct expression patterns . To avoid cre-induced recombination in vascular cells , we selected the specific nestin-cre line used in our study for several reasons . First , several groups have independently confirmed that the nestin-cre line used in the present study does not induce recombination in vascular cells of the forebrain [17] , [19] , [29] . We have also directly assessed cre activity in the cortex and found that , despite near complete recombination in neural cells , no vascular recombination was observed ( Figure S2 ) . Furthermore , we observed increased EC proliferation in orc3/nestin-cre mutant brains ( see results below ) , a phenotype opposite to what would have been predicted , had orc3 been deleted in ECs . Lastly , we found that pericyte density along the cortical vasculature is quantitatively normal in orc3 mutants ( see results below ) , which indicates that orc3 is not being deleted by nestin-cre in pericytes . Thus , these lines of evidence indicate that this nestin-cre is suitable for neural-specific deletion of orc3 . To determine effects of orc3 deletion on cortical neural progenitors , we first evaluated cell proliferation ( the effects of orc3 mutation on cortical neural development , as analyzed in the following experiments , are summarized in Table S1 ) . We found that orc3 deletion by nestin-cre did not obviously perturb ventricular zone cell division at E13 . 5 ( Figure 2A , B ) , but substantially reduced division at E15 . 5 ( Figure 2C , D ) . The intense band of BrdU+ cells normally observed at the ventricular surface in controls is almost absent in mutants at E15 . 5 . Indeed , quantification showed that the density of BrdU+ cells in the mutant ventricular zone was not significantly affected at E13 . 5 ( control , 37 . 33±2 . 33/10 , 000 µm2; mutant , 37 . 75±2 . 06/10 , 000 µm2; p = 0 . 90 , n = 4 ) but was significantly reduced at E15 . 5 ( control , 51 . 83±3 . 52/10 , 000 µm2; mutant , 28 . 00±0 . 86/10 , 000 µm2; p = 0 . 0008 , n = 6 ) . Similar reductions were also observed in phospho-histone 3 ( PH3 ) staining at the ventricular surface at E16 . 5 ( control , 23 . 80±2 . 24/10 , 000 µm2; mutant , 4 . 25±0 . 25/10 , 000 µm2; p = 0 . 0009 , n = 5 ) ( Figure 2I′ , J′ ) . In addition , quantification of nuclei in the ventricular zone showed an over 20% reduction at E15 . 5 ( control , 125 . 4±2 . 6 per field; mutant , 99 . 9±3 . 1; p = 4×10−7 , n = 18 ) . Furthermore , Ki67 staining also revealed a 24% reduction at E15 . 5 ( control , 228 . 5±15 . 8 per field; mutant , 174±8 . 3; p = 0 . 02 , n = 6; see also Figure 2O′ , P′ ) . nestin-cre induces fairly widespread recombination in the cortex at E12 . 5 [29] . Yet we did not observe substantial reductions in radial glial division until E15 . 5 . This suggests that the delay may result from perdurance of orc3 mRNA and/or protein . On the other hand , since by E15 . 5 , the early stages of cortical angiogenesis are close to complete ( Figure 1A–F ) , this provides a unique opportunity to determine the effects of radial glial loss on the late step of vessel stabilization . To further evaluate effects of orc3 deletion on radial glial development , we next assessed radial glial density . We found that radial glial density is substantially reduced , by ∼36% at E15 . 5 ( control , 6 . 0±0 . 4/100 µm; mutant , 3 . 8±0 . 3/100 µm; p<0 . 005 , n = 5 ) ( Figure 2E–F′ ) and ∼58% at E16 . 5 ( p<0 . 01 , n = 3 ) . By P0 , radial glial fibers are only observed sporadically across the mutant cortex ( Figure 2G–H′ ) . Nonetheless , the overall organization appears intact , with radial glial endfeet properly anchored at the pia and parallel fibers spanning the cortical wall . Throughout these stages , the density of radial glia also appears consistently more severely affected in the medial than the lateral cortex ( unpublished data , see also Figure 2H ) , suggesting earlier and/or more complete recombination by nestin-cre in the medial cortex . On the other hand , we did not observe obvious apoptosis ( unpublished data ) , consistent with previous data showing that blockade of cell cycle progression in radial glia does not trigger significant cell death [33] . To determine whether cell cycle blockade affects radial glial progenitor fate , we next stained sections with antibodies against Pax6 , a transcription factor regulating radial glial development [34] . We found that , although the number of Pax6+ cells is reduced in mutants ( control , 59 . 5±2 . 4/10 , 000 µm2; mutant , 30 . 9±1 . 2/10 , 000 µm2; p = 0 . 004 , n = 4 ) , the expression level in individual cells remains normal at E16 . 5 ( Figure 2I , J; quantified in Figure 2K , L ) . This is also supported by our Western blotting results showing that , although the level of total Pax6 protein is reduced in the mutant cortex , after normalizing against the number of radial glial progenitors , Pax6 protein level is comparable between controls and mutants ( Figure S3 ) . Staining intensity in individual radial glial cells for Nestin and Vimentin , intermediate filament proteins specific for radial glia , also appears unchanged ( unpublished data ) . Furthermore , although the number of intermediate progenitors is reduced at E16 . 5 ( control , 134 . 0±3 . 1/100 , 000 µm2; mutant , 29 . 1±1 . 9/100 , 000 µm2; p = 3×10−15 , n = 9 ) , their Tbr2 expression level appears unaffected in mutants ( Figure 2M , N , Q ) . In addition , at E15 . 5 , the number of Tbr2 positive intermediate progenitors is also quantitatively unaffected ( control , 91 . 9±9 . 3/100 , 000 µm2; mutant , 80 . 7±10 . 3/100 , 000 µm2; p = 0 . 44 , n = 7 ) ( Figure S4Q , R , W ) . The normal expression of these dorsal forebrain markers also indicates that dorsoventral patterning is unaffected . This is further supported by our finding that expression of the ventral marker Dlx1 is also unaffected ( Figure S4O , P ) . Lastly , the fates of neuronal progeny produced by radial glia also appear unperturbed ( see results below ) . Thus , these results together indicate that blockade of neural cell division by orc3 deletion substantially reduces radial glial number , but does not affect the specification and maintenance of their cell fate . Radial glia are not only progenitors for nearly all cortical neurons and glia , but they are also scaffolds for neuronal migration [12] , [13] . Thus , ablation of radial glia is likely to affect cortical neuron production as well as migration . Indeed , we observed significant reduction in cortical thickness in mutants at P12 ( Figure S4A , B ) , which suggests potential defects in neuronal production . Analysis by BrdU birthdating revealed that the generation as well as migration of upper but not deeper layer neurons are substantially compromised ( Figure S4C–H ) , consistent with the observed loss of radial glia after E15 . 5 ( Figure 2 ) . In addition , in accordance with unperturbed radial glial progenitor fate ( Figure 2 ) , we found that , although the number of upper layer neurons is reduced , the intensity in each cell of expression for Cux1 , a transcription factor specific for layer II–V neurons , appears normal at P0 ( Figure S4I , J ) . Expression in deep layer neurons of Ctip2 , a marker for layer V–VI neurons , also appears unaffected at P0 ( Figure S4K , L ) . Furthermore , in the embryonic cortex , although we observed increased cell cycle exit by mutant progenitors at E15 . 5 ( Figure 2O–P″ , R ) , the total number of cortical neurons is quantitatively normal at E16 . 5 ( Cux1: control , 81 . 8±5 . 7 per field; mutant , 81 . 0±4 . 9; p = 0 . 70 , n = 6; Ctip2: control , 279±16 per field; mutant , 276±15; p = 0 . 42 , n = 6 ) ( Figure S4S–V , X ) . This apparent lack of effects is likely due to the smaller number of progenitors present in mutants after E15 . 5 , which may offset effects of increased cell cycle exit during this period . Lastly , at E16 . 5 , we observed a normal pattern of layer-specific marker expression ( Figure S4S–V ) . Thus , these results indicate that , although radial glial ablation results in compromised upper layer neuron production and migration , it largely spares neuronal fate specification . To determine effects of radial glial ablation on cortical angiogenesis , we next compared vessel development in control and mutant brains . We observed neonatal cerebral hemorrhage in all mutants , a phenotype most severe in areas close to the midline ( Figure 3A , B ) . This is consistent with our earlier observation of more severe radial glial loss in the medial cortex ( see also Figure 2H ) . IB4 ( Figure 3C , D ) and laminin ( Figure 3E , F ) staining further revealed dramatic defects in cortical vascular network along the entire anterior-posterior axis ( Figure 3D , F ) . Quantification showed that , at P0 , vessel density across the cortex is reduced by ∼83% and branch point frequency by ∼79% in mutants ( p = 1 . 76×10−14 and 1 . 01×10−8 , n = 9 ) ( Figure 3G , H ) . Similar to hemorrhage , vessel development also appears most severely affected in areas close to the midline ( see Figure 3F ) . In addition , we sometimes observed tissue cavitations at P0 . However , since we did not observe them at the embryonic stages ( unpublished data ) , we assumed that these are due to secondary effects of vascular mal-development . Furthermore , we did not observe similar vascular defects in other regions of the CNS , including the hindbrain and the spinal cord ( Figure S5 ) . This is likely due to the late onset of expression of the nestin-cre relative to the ( shorter ) period of radial glial proliferation in these regions [35] , [36] . Consistent with this interpretation , we found that , in contrast to the cortex ( Figure 2E–F′ ) , there were no significant changes in radial glial density in the hindbrain at E15 . 5 ( control , 164 . 3±9 . 3/mm; mutant , 160 . 5±9 . 5/mm; p = 0 . 79 , n = 4 ) . To further assess the specificity of orc3 deletion in the forebrain , we employed hGFAP-cre , a well-established neural-specific cre , the activity of which peaks around E14 . 5 in the neocortex , about 2 d after nestin-cre [37] , [38] . We found that orc3 deletion by hGFAP-cre results in a similar , albeit less severe , phenotype in cortical angiogenesis ( Figure S6A–D ) . At P0 , the vessel density and branching frequency are reduced by ∼71% and 67% , respectively , in the medial cortex ( p = 5 . 25×10−8 and 8 . 48×10−6 , n = 6 ) , while no significant effects were observed in the lateral cortex ( Figure S6A–D ) . This is consistent with another gradient of radial glial loss in orc3/hGFAP-cre mutant cortices ( unpublished data ) , similar to , although shallower than , that observed in orc3/nestin-cre cortices . In addition , we also consistently observed significant , although also milder , hemorrhage near the midline of orc3/hGFAP-cre mutant cortices ( unpublished data ) . Thus , these results altogether strongly indicate that neural cells play an essential role in cortical angiogenesis during late embryogenesis . Since nestin-cre targets radial glia and , as a consequence , their progeny including intermediate progenitors , neurons , and astrocytes , this raises the question of whether defects in neuronal production and migration may be responsible for the observed vascular defects . To address this possibility , we examined neonatal brains from single and double mutants of β1 integrin/emx1-cre and brca1/emx1-cre , mutations that have been shown to result in disrupted cortical lamination and reduced neuron number , respectively [29] , [39] , [40] . We found that neither single nor double mutations in β1 integrin and brca1 consistently affect cortical vessel density or branching frequency ( Figure S6E–J ) . This indicates that defective angiogenesis following radial glial ablation is unlikely a result of reduced cortical neuronal number or defective migration , alone or in combination . This interpretation is also supported by previous analyses showing that , despite lamination defects , reelin mutation does not affect development of the cortical vasculature [41] , [42] . Furthermore , specific loss of upper layer neurons in Pax6 mutants , similar to that in orc3 mutants , also does not lead to obvious hemorrhage [43] . In addition , we found that deletion of orc3 from intermediate progenitors and postmitotic neurons in the cortex , using nex-cre [44] , [45] , also has no obvious effects on vessel development ( unpublished data ) . Lastly , at E16 . 5 , when vessel regression begins , we found no quantitative defects in the density of either upper or deep layer cortical plate neurons ( Figure S4S–V , X ) . Thus , these lines of evidence together strongly argue against the involvement of neuronal defects in orc3 mutant vascular phenotype and suggest a role played by cortical neural progenitors . Of the various cortical neural progenitors , studies showed that severe loss of intermediate progenitors does not result in obvious brain hemorrhage [46] , [47] . This suggests that loss of radial glia is likely responsible for cortical angiogenesis defects in orc3 mutants . To further evaluate this interpretation , we analyzed the quantitative relationship between radial glial density and vessel development in the medial cortex of controls as well as orc3/nestin-cre and orc3/hGFAP-cre mutants ( Figure 3I–J ) . We found that , at P0 , orc3 deletion by nestin-cre results in a severe reduction in radial glial density in the medial cortex ( ∼79% ) , leading to a severe reduction in both vessel density ( ∼91% ) and branch point frequency ( ∼98% ) . By contrast , orc3 deletion by hGFAP-cre results in an intermediate reduction in radial glial density ( ∼51% ) , in correspondence to intermediate reductions in vessel density ( ∼75% ) and branching frequency ( ∼68% ) . This indicates a positive relationship between radial glial density and cortical vessel density as well as branch point frequency . Indeed , further quantitative analysis showed that the correlation coefficient between radial glial density and vessel density ( r = 0 . 97 , p = 0 . 000015 ) as well as that between radial glial density and vessel branching frequency ( r = 0 . 98 , p = 0 . 000004 ) are both close to 1 ( Figure 3I–J ) . Thus , these results demonstrate a tight , positive correlation of radial glial density with both cortical vessel density and branch point frequency . This not only further implicates a specific role of radial glia in cortical vessel development but also suggests the involvement of local cell-cell interaction . To determine how vascular defects in orc3/nestin-cre mutants arise , we next examined cortical vessel morphology during embryogenesis ( Figure 4A–H ) . We found that , at E15 . 5 , vessel development appears completely normal , with the emergence of a primitive vascular network close to complete in all mutants ( Figure 4A , B ) . This indicates that early cortical angiogenesis is not affected by nestin-cre–mediated orc3 deletion , an interpretation consistent with our finding that neither neural progenitor proliferation nor radial glial density is substantially affected until after E15 . 5 ( Figure 2A–F′ ) . By contrast , at E16 . 5 , we observed vessel defects in the vast majority of mutants . While some mutants showed relatively moderate deficits , most showed severe defects ( Figure 4C , D ) . By E17 . 5 and E18 . 5 , all mutants showed severe defects in vessel development ( Figure 4E–H ) . Quantification revealed that the vessel density and branching frequency first begin to decrease at E16 . 5 and continue to decline afterwards ( Figure 4I , J ) . Most importantly , we found that , even after adjustment for cortical area expansion , mutant vessel density still decreases by ∼30% from E16 . 5 to E17 . 5 ( p = 0 . 0009 , n = 5 ) and by another 39% from E17 . 5 to P0 ( p = 0 . 0007 , n = 5 ) . This indicates that the total vessel length is being severely reduced during each of these intervals . Loss of radial glia during late embryogenesis therefore results in a distinct phenotype of vessel regression . Since during early corticogenesis , radial glia promote CNS vessel development by expressing high levels of Wnt7a and Wnt7b , factors essential for initial vessel ingression into the neural tube [19] , [23] , our results above indicate that radial glia play a different role during late embryogenesis , by regulating nascent vessel stabilization . Consistent with this interpretation , after E14 . 5 , Wnt ligand expression , especially that of Wnt7b , substantially shifts to the cortical plate [48] , the main area of vessel development during these later periods . This suggests that radial glia may no longer play a primary role in promoting cortical plate vessel growth during late embryogenesis , a role likely taken over by neurons . To further assess our interpretation of vessel regression , we examined expression of Collagen IV , a basement membrane component frequently left behind by regressing vessels [24] . We found that , while there are rarely Collagen IV+ basement membrane sleeves in controls , the density of empty sleeves , albeit still low , is significantly increased in mutants ( control , 0 . 72±0 . 45/mm2; mutant , 7 . 90±0 . 66/mm2; p = 1 . 5×10−5; n = 6 ) ( Figure 4P–Q′ ) . Furthermore , mutant vessels also appeared less well-perfused ( Figure 4R , S ) . Thus , these results reinforce the interpretation that radial glia regulate cortical vessel stabilization during late embryogenesis and their loss results in vessel regression . Pericytes are critical support cells for vessel development . Previous studies show that absence of pericytes , although resulting in an altered , torturous vessel morphology , does not affect either vessel density or branch point frequency in the developing brain [49] . Since we observed severe reductions in vessel density and branch point frequency ( Figure 3 ) , this suggests that potential defects in pericyte loss are unlikely a primary cause for vessel regression in orc3 mutants . Nonetheless , to further assess their potential contribution , we examined pericyte investment of cortical vasculature . We found that , at E17 . 5 , despite clear signs of vessel regression , cells positive for Desmin , a pericyte marker , similarly surround all cortical endothelia in mutants as in controls ( Figure 4K , L ) . Comparable results were also obtained at E16 . 5 , at the onset of vessel regression , using antibodies against PDGFRβ , another well-known pericyte marker ( Figure 4M , N ) . Indeed , quantification showed that the density of PDGFRβ+ cells along all cortical plate vessels at E16 . 5 is statistically identical between controls and mutants ( Figure 4O ) , arguing against pericyte loss or defective recruitment due to orc3 deletion by nestin-cre . In addition , we observed a similar vascular phenotype in mutants where orc3 was deleted using hGFAP-cre ( Figure S6A–D ) , a cre line with well-established neural-lineage specificity [37] , [38] . This further argues against primary defects in pericytes . Thus , these results indicate that pericyte defects do not play a primary role in vessel regression following radial glial ablation . The above results indicate that loss of radial glia during late embryogenesis results in destabilization and regression of nascent brain vessels . To determine the underlying molecular mechanisms , we evaluated potential involvement of several pathways . VEGF is a survival factor for ECs in a number of tissues [50]–[53] . Thus , compromised VEGF expression may result in vessel regression . However , we found that the overall mRNA and protein levels of the three VEGF A isoforms are either not obviously changed at E16 . 5 ( Figure S7 ) or even slightly increased at E17 . 5 ( unpublished data ) , suggesting that the phenotype is unlikely a result from primary defects in the VEGF pathway . Similarly , angiopoietin 1 mRNA expression at E16 . 5 was also unchanged ( Figure S7 ) , arguing against primary defects in angiopoietin 1 signaling . A third candidate pathway is TGFβ signaling [54] . Indeed , perturbations of TGFβ signaling result in hemorrhage in a large number of mutants . However , no obvious vessel regression has been observed , including in the developing brain [17] , [55] , [56] . In orc3 mutants , we observed severe vessel loss in the perinatal brain ( Figure 3 ) . Yet despite extensive hemorrhage , no quantitative reductions in total vessel length were observed in the perinatal brain following Smad4 deletion from the vasculature [56] . Furthermore , in Smad4 mutants , brain vessels appear obviously dilated throughout the capillary network [56] . Yet no similar dilations were observed in orc3 mutants ( see also Figure 4A–H ) . Thus , although defects in TGFβ signaling , if any , may contribute to the vascular phenotype , they cannot be solely or primarily responsible for vessel regression . These findings therefore suggest primary involvement of pathways other than VEGF , angiopoietin , or TGFβ signaling . Canonical Wnt signaling has been implicated in several steps of vessel development , including initial neural-tube vessel ingression , retinal vessel stabilization , intersomitic vessel remodeling , and hyaloid vessel regression [19] , [21]–[25] . In the embryonic neocortex , similar to the hindbrain [57] , we found strong EC expression of a BAT-lacZ Wnt reporter during early development ( Figure S8A–E ) [58] . This suggests a role of Wnt signaling in early cortical angiogenesis . The expression , however , is strongly down-regulated after E16 . 5 , coincident with onset of the later periods of vessel stabilization ( Figure 1 ) . In contrast to reductions in Wnt pathway activity , however , the expression of Wnt ligands , including Wnt7a and Wnt7b , continues in the cortex , even though substantially part of it , especially that of Wnt7b , shifts to the cortical plate [48] . Thus , these findings suggest that down-regulation of EC Wnt signaling , independent of changes in Wnt ligand expression levels , may play a role in cortical vessel stabilization during late embryogenesis . Hyaloid vessel regression induced by Wnt signaling is associated with enhanced EC division [21] , [22] . To determine whether this is the case in orc3 mutants , we examined EC proliferation at E16 . 5 ( Figure 5A–B′ ) , the stage when vessel phenotypes first appear . In contrast to sporadic BrdU+ ECs in controls ( Figure 5A , A′ ) , we found frequent clusters of dividing ECs in mutants ( Figure 5B , B′ ) , which suggests increased EC proliferation . Indeed , quantification showed a >100% increase in the density of BrdU+ ECs ( p = 0 . 001; n = 4 ) ( Figure 5K ) . Similar increases were also observed using Ki67 antibodies ( Figure 5C–D′ ) . To more directly evaluate Wnt pathway activity , we examined expression of Glut-1 , a blood brain barrier transporter regulated by Wnt signaling [19] . We found that Glut-1 staining is up-regulated by >65% in mutant vessels ( p = 10−16 , n = 22 ) ( Figure 5E , F ) , suggesting elevation of Wnt signaling . This was further corroborated by Western blot analysis ( Figure 5I , J ) . In addition , expression of LEF1 , a canonical Wnt signal mediator as well as a transcriptional target expressed in spinal cord ECs [19] , also appears up-regulated ( unpublished data ) . Lastly , we employed the BAT-lacZ reporter for directly evaluating Wnt pathway activity in ECs ( Figure 5G , H ) . We found that the density of lacZ+ ECs is approximately 150% higher in mutants than in controls ( p = 0 . 001; n = 4 ) ( Figure 5L ) . Furthermore , we consistently observed higher degrees of elevation of BAT-lacZ expression along mutant vessels in the medial cortex ( unpublished data ) , corresponding to more severe angiogenesis defects in the midline region ( Figure 3 ) . Thus , these results demonstrate a close correlation between elevated EC Wnt signaling and vessel regression and strongly suggest a role of ectopic Wnt signaling in vessel regression . To determine how EC Wnt pathway activity becomes elevated in orc3 mutants , we next examined the expression of Wnt ligands and inhibitors in the cortex . We found that the levels of Wnt ligands Wnt7a and Wnt7b were not significantly changed at the mRNA level at E16 . 5 ( Figure S8F ) , consistent with the finding that their expression has shifted substantially to cortical neurons at this stage [48] and that the number of cortical neurons is not significantly changed at E16 . 5 ( Figure S4S–V , X ) . Interestingly , however , we found that the levels of several secreted Wnt inhibitors , including sfrp1 , sfrp2 , wif1 , and Dkk1 , were also not significantly affected at E16 . 5 ( Figure S8F ) . Although this characterization was not exhaustive , this suggests that ectopic Wnt pathway activation in orc3 mutants is not a result of an overall altered Wnt ligand/inhibitor ratio . This is also consistent with our finding that radial glial regulation of cortical vessel stabilization appears to depend on cell density ( Figure 3I–J ) . In addition , although macrophage expression of Wnt7b has been found responsible for hyaloid vessel regression [21] , we observed no obvious accumulation of microglia in the cortical plate until birth ( Figure S9 ) , days after the onset of vessel regression ( Figure 4 ) . This argues against a significant contribution of microglia . Thus , these results together suggest that radial glia likely regulate cortical vessel stabilization through local cell-cell interactions , which in turn inhibit Wnt signal reception by and/or transduction within ECs . To more directly assess the nature of radial glial regulation of EC Wnt signaling , we next employed in vitro culture , using dissociated cortical cells from BAT-lacZ reporter mice . We first assessed effects of radial glia on EC Wnt signaling at E15 . 5 . We evaluated Wnt pathway activity by X-gal reaction and identified ECs and radial glia by CD31 and BLBP staining , respectively ( Figure 6Aa–Be ) . In these cultures , we observed strong X-gal staining in many cells , indicating robust Wnt pathway activation . To confirm effectiveness of cell dissociation especially of pericytes , we double-stained for CD31 and NG2 . We found that less than 3% of ECs were associated with pericytes . This indicates that under these conditions , ECs and pericytes are near completely separated . Next , we evaluated effects of radial glial interaction on EC BAT-lacZ expression . We found that ECs in contact with radial glia overwhelmingly showed minimal BAT-lacZ activity ( Figure 6Aa–f ) , while those not in contact with radial glia ( Figure 6Ba–f ) showed strong lacZ expression . Quantitative analysis confirmed a highly significant inhibitory effect of radial glial contact on EC Wnt pathway activity ( Figure 6C , D ) . These results thus indicate that radial glia inhibit EC Wnt signaling in a contact-dependent manner at E15 . 5 . Importantly , in these experiments , we found no significant effects on Wnt pathway activity by EC interaction with nonradial glial cells ( Figure 6D ) , which at this stage consist mainly of cortical neurons . This further indicates the specificity of radial glial regulation of EC Wnt signaling . Interestingly , at E13 . 5 , we found no similar inhibitory effects of radial glial contact ( Figure 6E ) , which suggests a stage-specific interaction between radial glia and ECs . Thus , these results altogether demonstrate a direct and specific role of radial glia in inhibiting cortical EC Wnt signaling during late embryogenesis . To determine whether aberrant Wnt pathway activation is responsible for vessel regression in orc3 mutants , we next sought to directly activate Wnt signaling . Glycogen synthase kinase 3β ( GSK-3β ) is a key component of canonical Wnt pathway , and inhibition of GSK-3β by LiCl mimics Wnt pathway activation in many developmental contexts [59] , [60] . To assess effects of GSK-3β inhibition on Wnt signaling , we treated E16 . 5 embryos with LiCl . We found that LiCl quickly up-regulated expression of several Wnt target genes/reporters , a change most prominent in cortical ECs ( Figure S10A–I ) . Indeed , we found that , about 10 h after treatment , the density of BAT-lacZ+ ECs is significantly increased , to ∼55% higher than in controls ( Figure S10A–C ) . This increase , however , is not nearly as dramatic as that in orc3 mutants ( Figure 5L ) , consistent with the finding that LiCl is quickly cleared from the plasma in mice [61] . In addition , we found that , unlike in orc3 mutants where EC BAT-lacZ expression is most dramatically up-regulated in the medial cortex , the up-regulation by LiCl appears more uniform ( unpublished data ) , consistent with the fact that LiCl is being delivered by the brain vasculature . Furthermore , we found that the level of Glut-1 expression is also significantly elevated by LiCl ( Figure S10D–F ) . Lastly , we found that LiCl also significantly up-regulated EC proliferation ( Figure S10G–I ) . Thus , these results indicate that LiCl treatment efficiently elevates EC Wnt signaling in the embryonic cortex . To assess the specificity of LiCl treatment , we next examined its effects on the expression of a panel of Wnt ligands and extracellular inhibitors . We found that LiCl did not significantly affect the expression of either the Wnt ligands Wnt7a and Wnt7b or the inhibitors sfrp1 , sfrp2 , wif1 , and Dkk1 , as assayed by qRT-PCR ( Figure S11A ) . Furthermore , we found that LiCl treatment also had no significant effects on either the expression pattern or the density of Cux1 or Ctip2 positive neurons ( Figure S11B–E , H–I ) . Thus , these results together indicate that LiCl provides a relatively specific and efficient tool for activating EC Wnt signaling throughout the embryonic cortex . To determine effects of GSK-3β inhibition on vessel stabilization , we next examined vessel density and branching frequency at E18 . 5 , following LiCl treatment starting at E16 . 5 , in comparison to NaCl treatment ( Figure 7A–D ) . We found that LiCl treatment results in mild hemorrhage throughout the cortex , which , as a consequence , appears pink in color , a phenotype that we confirmed by Ter119 staining ( Figure 7A ) . These moderate effects are consistent with the mild elevation of Wnt signaling by LiCl ( Figure S10A–C ) . The widespread nature of the hemorrhage also appears consistent with activation of EC Wnt signaling by LiCl throughout the cortex . These results thus indicate that ectopic activation of EC Wnt signaling can result in hemorrhage . To determine effects on vessel stabilization , we next quantified cortical vessel density at E18 . 5 in control and treated embryos . We found that LiCl treatment results in a vessel density not only lower than that of E18 . 5 controls ( Figure 7B ) but also lower than that of E17 . 5 controls ( E17 . 5 control , 10 , 112±440 µm/mm2; E18 . 5 LiCl treated , 6 , 832±794 µm/mm2; p = 0 . 004 , n = 7 ) . This indicates that elevation of EC Wnt signaling by LiCl can also result in vessel regression . To assess the specificity , we examined effects of LiCl on vessel development outside the cortex . We found that , despite its dramatic impact on the cortex , LiCl had no significant effects on vessel density in either the striatum or the heart at this stage ( Figures 7B and S10J–O ) . To further address the issue of specificity , we also determined effects of SB216763 , a more specific GSK-3β inhibitor . We found that , similar to LiCl , SB216763 also had no significant effects on either the expression pattern or the density of Cux1 or Ctip2 positive neurons in the cortex ( Figure S11F–I ) . However , SB216763 treatment resulted in significant reductions in vessel density ( control , 7 , 772±199 µm/mm2; SB216763 treated , 4 , 351±229 µm/mm2; p = 3 . 4×10−5 , n = 4 ) as well as branching frequency ( control , 37 . 8±2 . 3/mm2; SB216763 treated , 15 . 8±2 . 0/mm2; p = 0 . 0004 , n = 4 ) in E18 . 5 cortices ( Figure 7E–F ) . Thus , these results altogether indicate that Wnt pathway activation is sufficient to trigger cortical vessel regression , suggesting that ectopic Wnt pathway activation likely plays a significant role in vessel regression following radial glial ablation . To determine whether ectopic Wnt pathway activation indeed contributes to vessel regression in orc3 mutants , we next sought to attenuate Wnt signaling ( Figure 7G–L ) . Wnt7a and Wnt7b are two redundant Wnt ligands expressed in the embryonic cortex . They are initially expressed in radial glial progenitors during early corticogenesis but shift expression to cortical plate neurons after E14 . 5 [19] , [23] , [48] . We reasoned that , even though Wnt7a and Wnt7b are functionally redundant during normal CNS angiogenesis , removing one of them in the orc3 mutant background may still attenuate elevated Wnt signaling . To this end , we introduced homozygous wnt7b mutation into the orc3 mutant background . We found that , although deleting wnt7b alone has no significant effects on cortical vessel Glut-1 expression , deleting wnt7b from orc3 mutants significantly suppresses the up-regulation of Glut-1 expression ( p<0 . 01 , n = 13; ANOVA and Tukey's post hoc test ) ( Figure 7G , H ) . This indicates that wnt7b mutation suppresses the up-regulation of EC Wnt signaling in orc3 mutants . On the other hand , we observed no significant effects of wnt7b deletion on the number of Tbr2+ cells in either the wild-type or orc3 mutant background ( p>0 . 1 , n = 10 ) , which suggests a relatively specific effect on ECs . Consistent with the suppression effects of wnt7b deletion on EC Wnt signaling , we also found that , although deleting wnt7b alone has no significant effects on cortical vessel development ( Figure 7J ) , deleting wnt7b from orc3 mutants not only substantially ameliorates cerebral hemorrhage ( hemorrhage area in cross-sections: orc3 mutant , 0 . 146±0 . 021 mm2; orc3/wnt7b dKO , 0 . 059±0 . 006 mm2; p = 0 . 003 , n = 5 ) ( Figure 7I ) , but also substantially restores cortical vessel density ( orc3 mutant , 1 , 487±189 µm/mm2; orc3/wnt7b dKO , 3 , 945±218 µm/mm2; p<0 . 01 , n = 4 ) , as well as branch point frequency ( orc3 mutant , 11 . 8±2 . 7/mm2; orc3/wnt7b dKO , 24 . 8±2 . 6/mm2; p<0 . 01 , n = 4 ) ( Figure 7J–L ) . The suppression , however , is not complete , suggesting that , even in the orc3 mutant background , there are still substantial degrees of redundancy between Wnt ligands . Thus , these results indicate that ectopic activation of EC Wnt signaling plays a large role in vessel regression following radial glial ablation . Radial glia therefore appear to stabilize nascent cortical plate vessels in large part through inhibiting EC Wnt signaling . Canonical Wnt signaling directly promotes , at the transcriptional level , expression of several matrix metalloproteinases ( MMPs ) , including MMP-2/9 , membrane type 1 MMP ( MT1-MMP ) , and MT3-MMP [62] . Since precise regulation of MMP activity is crucial for the delicate balance between vessel basement membrane breakdown and stabilization during angiogenesis [63] , elevated MMP expression may result in excessive basement membrane breakdown , leading or contributing to vessel regression . Indeed , along orc3 mutant vessels , we frequently observed bright puncta of laminin staining ( Figure 8A , B ) ( 0 . 56±0 . 30/mm vessel length for controls; 2 . 99±0 . 29/mm for mutants; p = 0 . 006 , n = 10 ) , which suggests excessive basement membrane breakdown . To assess the role of MMPs , we first examined MMP-2 expression in cortical plate vessels during normal development . Consistent with moderate levels of Wnt pathway activity in wild-type ECs at E15 . 5 and E16 . 5 ( see Figure 5G ) , we found low numbers of vascular cells expressing MMP-2 at these stages ( Figure 8C ) . By contrast , with elevated EC Wnt pathway activity in orc3 mutants ( see Figure 5H ) , we found substantially increased numbers of vascular cells expressing MMP-2 ( Figure 8D ) . To corroborate these observations , we performed gel zymography ( Figure 8E , F ) . We found that the activities of both full-length pro-MMP-2 and cleaved MMP-2 are dramatically elevated in mutants at E16 . 5 , while the activity of pro-MMP-9 , another MMP expressed in the cortex , appears moderately increased ( Figure 8E ) . Quantification showed an over 170% increase in pro-MMP-2 activity ( p = 0 . 006; n = 3 ) ( Figure 8F ) , as well as a roughly 90% increase in pro-MMP-9 activity ( p = 0 . 007; n = 3 ) . This suggests that elevated MMP-2/9 activity may both play a role in vessel regression . Furthermore , we found that , in brains treated with LiCl , MMP-2 expression is also dramatically up-regulated ( Figure 8G , H ) . On the other hand , unlike MMP-2 and MMP-9 , MT1-MMP expression appears not significantly changed ( Figure S12A ) . Thus , these results indicate that , during corticogenesis , Wnt signaling positively regulates MMP-2 ( and possibly MMP-9 ) expression in vessels , while radial glia suppress MMP-2/9 expression . To assess the functional significance of MMP-2 up-regulation , we sought to block MMP-2 activity in orc3 mutants . Timp2 , a tissue inhibitor of MMPs , is essential for the cleavage and activation of pro-MMP-2 [64] , [65] . We confirmed that , in Timp2 mutants , cleaved MMP-2 is completely absent ( Figure S12B ) . To block MMP-2 activation , we introduced homozygous Timp2 mutation into orc3 mutant background and evaluated vessel development ( Figure 8I–L ) . We found that Timp2 mutation alone does not significantly affect vessel development ( Figure 8L ) . However , introduction of homozygous Timp2 mutation greatly reduces the extents of brain hemorrhage in comparison to that in orc3 single mutants ( Figure 8I ) . Quantification showed that the cross-section area covered by hemorrhage is significantly reduced in double mutants ( orc3 mutant , 0 . 146±0 . 021 mm2; orc3/Timp2 dKO , 0 . 068±0 . 006 mm2; p = 0 . 007 , n = 5 ) . Introduction of Timp2 mutation also significantly restores vessel morphology as well as density in the orc3 mutant cortex ( Figure 8J , K ) . Quantification showed that both vessel density ( orc3 mutant , 1 , 487±189 µm/mm2; orc3/Timp2 dKO , 3 , 420±157 µm/mm2; p<0 . 01 , n = 6; ANOVA and Tukey's post hoc test ) and branch point frequency ( orc3 mutant , 11 . 8±2 . 7/mm2; orc3/Timp2 dKO , 25 . 7±2 . 1/mm2; p<0 . 01 , n = 6 ) are significantly higher in orc3/Timp2 double mutants than in orc3 single mutants ( Figure 8L ) . The suppression , however , is partial , suggesting potential contribution by other Wnt target genes . Thus , these results argue that MMP-2 up-regulation may play a functionally significant role in vessel regression following radial glial ablation . They indicate that nascent cortical vessel stabilization by radial glia may be mediated , in part , by inhibition of MMP-2 expression in vascular cells .
Previous studies have observed close interactions between radial glia and blood vessels during development [15] , [16] , suggesting a role of radial glia in EC guidance . Our results show that radial glia also play an unexpected role in cortical vessel stabilization , a later step of brain angiogenesis . First , we show that the nestin-cre we use specifically targets neural cells , while sparing the cortical endothelia ( Figures S2 ) , confirming work by others [19] . This indicates that vessel regression in orc3/nestin-cre mutants is due to primary defects in neural but not ECs . Second , we observe increased proliferation of cortical ECs in mutants , which further argues against orc3 deletion in ECs ( Figure 5 ) . In addition , we observe normal pericyte density along vessels ( Figure 4 ) , which argues against orc3 deletion by nestin-cre in pericytes . Furthermore , we find severely reduced cortical vessel density and branch point frequency in orc3/nestin-cre mutants ( Figure 3 ) , a phenotype not observed in mutants without pericytes [49] . Lastly , we find that deletion of orc3 using an independent neural-specific hGFAP-cre also results in similar vascular defects ( Figures 3I–J and S6 ) . Thus , these lines of evidence strongly argue for a role of neural cell types in cortical vessel stabilization . Among the cortical neural cell types , our results strongly argue against involvement of postmitotic neurons . By taking advantage of β1 integrin and brca1 mutants , we show that general defects in cortical neuron production and migration , alone or in combination , do not result in vessel regression ( Figure S6 ) . This is consistent with previous results from analyzing reelin mutants [41] , [42] . Furthermore , we find that specific deletion of orc3 from cortical neurons also has no effects on vessel development . Lastly , at E16 . 5 , when vessel regression begins , we found no quantitative defects in the density of either upper or deep layer cortical plate neurons ( Figure S4S–V , X ) . These results thus strongly argue against involvement of cortical neurons and implicate a role by neural progenitors . Of the neural progenitors , previous studies show that severe loss of intermediate progenitors does not result in similar brain hemorrhage [46] , [47] . We also did not observe obvious defects following orc3 deletion by nex-cre from intermediate progenitors and neurons . This suggests a likely role by radial glia . Indeed , our quantitative analysis shows a strong , positive correlation between radial glial density and vessel density as well as branch point frequency ( Figure 3I–J ) . Our cell culture experiments further demonstrate a stage-specific and contact-dependent inhibition by radial glia , but not by other cell types , of EC Wnt signaling ( Figure 6 ) , a pathway that we also functionally implicate in vessel regression ( Figures 7 and 8 ) . Thus , these results strongly indicate that radial glia are the neural cell type responsible for cortical vessel stabilization during late embryogenesis . Canonical Wnt signaling has been implicated in several steps of vessel development , including CNS vessel ingression , blood brain barrier differentiation , retinal vessel stabilization , intersomitic vessel remodeling , and hyaloid vessel regression [19] , [21]–[25] . Our results argue that Wnt signaling down-regulation in ECs is essential for cortical vessel stabilization during late embryogenesis . We observe a tight correlation between ectopic Wnt pathway activation and vessel regression . We find that EC expression of Wnt target genes/reporters is substantially elevated at the onset of vessel regression ( Figure 5 ) . We also find that radial glia normally inhibit cortical EC Wnt signaling during late embryogenesis ( Figure 6 ) . Furthermore , we find that direct activation of Wnt pathway induces vessel regression , while attenuation of Wnt signaling significantly suppresses regression ( Figure 7 ) . Lastly , ectopic activation of Wnt signaling up-regulates MMP-2 expression in ECs , while blocking MMP2 activity using Timp2 mutation appears to substantially suppress vessel regression ( Figure 8 ) . Thus , these results strongly indicate that down-regulation of EC Wnt signaling may be a key step through which radial glia regulate cortical vessel stabilization . The multiple and sometimes opposite roles played by canonical Wnt signaling during vascular development suggest that Wnt pathway activation may elicit , in a stage- and tissue-dependent manner , dramatically different responses in ECs . This raises the question of how these distinct effects are mediated in the same cell type . Our findings that Wnt signaling regulates MMP-2 expression may provide some clues . In the CNS , vessel ingression from outside the neural tube necessitates penetration of the neural tube basement membrane and thus likely increased expression of extracellular matrix degrading enzymes such as MMPs , the activities of which are known to facilitate angiogenesis [66] . By contrast , vessel stabilization following initial formation likely requires not only assembly but also maintenance of basement membrane and thus , as a prerequisite , tight control of MMP activity [63] . In this light , it would appear to make sense that activation of Wnt signaling is necessary for the initial vessel ingression into the neural tube as well as , potentially , their continued growth in the neural tissues [19] , [23] , while Wnt signaling down-regulation may be essential for vessel stabilization after their initial formation ( our results ) . Patterning of cellular networks during development typically involves guided initial growth as well as subsequent selective stabilization [3] , [4] . As such , it is likely that tissue-specific patterning of vascular networks also involves similar mechanisms . Indeed , a large number of axon guidance cues have been implicated in recent years in directed vessel growth [5] , . In contrast , little is known about what roles selective stabilization may play in vascular patterning and how it is regulated . In the neonatal retina , pericyte recruitment and astrocyte VEGF signaling regulate hyperoxia-induced vascular pruning , a process that matches local vessel density with oxygen supply level [53] , [67] . In the developing eye , pericyte signaling is also responsible for macrophage-dependent hyaloid vessel regression [21] , [22] . However , it remains unknown how tissue-specific cell types regulate vessel stabilization . Our results show that , in the developing cortex , radial glia are the tissue-specific cell type responsible for vessel stabilization . Our results also implicate contact-dependent radial glial down-regulation of EC Wnt signaling in this process . This therefore provides novel insights into not only the cellular but also the molecular mechanisms that coordinate tissue development and vascular patterning in the nervous system and potentially throughout the body . Increasing evidence suggests that cerebrovascular dysfunction , including vessel regression , plays an important role in the pathogenesis of a significant number of developmental and degenerative diseases [68] , [69] . For example , perinatal stroke , which includes hemorrhagic stroke , affects 1 in 1 , 600 to 5 , 000 live births and often results in long-term disabilities [69] . Yet little is known about the mechanisms underlying these conditions . Our results raise the possibility that dys-regulated neural progenitor and Wnt signaling may play a role . Consistent with this , recent studies show that cell-autonomous functions of CCM3 in neural cells play a significant role in the pathogenesis of cerebral cavernous malformation [20] . In aged humans , reduced capillary density , and even collapsed or degenerated endothelia , have been observed in Alzheimer's brains [70] . Missing vasculatures have also been detected , at sites of amyloid plaques , in models of Alzheimer's disease [71] . These findings highlight a role of vessel regression in the pathogenesis of Alzheimer's disease , while our results suggest that studies on the possible role of dys-regulated neural-to-vascular and Wnt signaling may be informative . Thus , further investigation into vessel stabilization by radial glia may not only enhance knowledge of mechanisms that coordinate neural and vascular development and function in the normal brain , but may also facilitate better understanding of human diseases .
BAC recombineering technology was employed for generating conditional orc3 allele . qRT-PCR was performed according to the manufacturer's instructions ( see Text S1 for details ) . This study was approved by the Animal Care and Use Committee of the University of Wisconsin–Madison ( Animal Welfare Assurance #A3368-01 ) . nestin-cre ( #003771 ) , Timp2 , wnt7b , as well as BAT-lacZ and mTomato/mEGFP reporters were purchased from the Jackson Lab . nestin-cre was introduced paternally into the orc3 background for phenotypic analyses . Males triply heterozygous for orc3 , nestin-cre , and Timp2 or wnt7b were crossed to females doubly heterozygous for orc3 and Timp2 or wnt7b , to produce double mutants . emx1-cre and β1 integrin conditional alleles were as published previously [39] . brca1 conditional alleles were purchased from the National Cancer Institute Mouse Models of Human Cancers Consortium repository . For LiCl and NaCl injection , pregnant females were treated on E16 . 5 at 17 µmoles/g body weight ( gbw ) , followed by three treatments on E17 . 5 ( once every 5 h ) at 10 µmoles/gbw , and embryos were collected on E18 . 5 . For SB216763 injection , pregnant females were treated once on E15 . 5 at 0 . 27 µmole/gbw , followed by two treatments each on E16 . 5 and E17 . 5 . BrdU was injected at 100 µg/gbw . Animal use was in accordance with institutional guidelines . Stainings were performed as described previously [39] and analyzed under a Nikon eclipse Ti microscope . For 3-D reconstruction , Z-stacks were collected under an Olympus confocal microscope and processed using ImageJ software ( see Text S1 for details ) . Standard Western blot procedures were employed , using Bio-Rad eletrophoresis and transfer apparatus . Gelatin zymography was performed using purified human pro-MMP-2 ( Calbiochem ) as well as neonatal lung lysates as standards . Dissociated cortical cells from BAT-lacZ mice were cultured overnight . ECs and radial glia were identified by immunostaining , while lacZ expression was analyzed by X-gal reaction ( see Text S1 for details ) . Vessel length and branching frequency from every fourth of 50 µm coronal sections of each brain were manually quantified using Nikon NIS-Elements BR 3 . 0 software . For BAT-lacZ expression and pericyte density analysis , total numbers of lacZ+ ECs or PDGFRβ+ pericytes were counted and normalized against total vessel length . At least three brains were used for each genotype under each condition , and matching sections were used for controls and mutants . Statistics was performed using Student's t test when involving two conditions , and ANOVA followed by Tukey's post hoc test when involving more conditions . All data are represented as mean ± SEM . | The brain is an energy-intensive organ that consumes about 10 times as much energy per unit volume as the rest of the body . It therefore requires a highly efficient vascular network for oxygen and nutrient delivery , and as a result compromises in blood vessel networks influence a wide array of brain diseases . Our current understanding is that brain-specific neural cell types are involved in shaping its vascular network , but unfortunately little is known about the cellular or molecular mechanisms involved . Using a mouse genetic model , we have found that radial glial cells , a stem cell type well known for its fundamental role in neural circuit formation , also play an unexpected role in brain vessel development . We find that radial glial cells are essential for the stabilization of newly formed blood vessels in the late embryonic brain , and do so in large part through down-regulating canonical Wnt signaling in endothelial cells ( which line the interior surface of blood vessels ) . These findings provide new insight into how new vessels in the brain are normally stabilized and how this process may be compromised and contribute to diseases . | [
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"developmen... | 2013 | Radial Glial Neural Progenitors Regulate Nascent Brain Vascular Network Stabilization Via Inhibition of Wnt Signaling |
The fibrinogen ( Fg ) binding MSCRAMM Clumping factor A ( ClfA ) from Staphylococcus aureus interacts with the C-terminal region of the fibrinogen ( Fg ) γ-chain . ClfA is the major virulence factor responsible for the observed clumping of S . aureus in blood plasma and has been implicated as a virulence factor in a mouse model of septic arthritis and in rabbit and rat models of infective endocarditis . We report here a high-resolution crystal structure of the ClfA ligand binding segment in complex with a synthetic peptide mimicking the binding site in Fg . The residues in Fg required for binding to ClfA are identified from this structure and from complementing biochemical studies . Furthermore , the platelet integrin αIIbβ3 and ClfA bind to the same segment in the Fg γ-chain but the two cellular binding proteins recognize different residues in the common targeted Fg segment . Based on these differences , we have identified peptides that selectively antagonize the ClfA-Fg interaction . The ClfA-Fg binding mechanism is a variant of the “Dock , Lock and Latch” mechanism previously described for the Staphylococcus epidermidis SdrG–Fg interaction . The structural insights gained from analyzing the ClfANFg peptide complex and identifications of peptides that selectively recognize ClfA but not αIIbβ3 may allow the design of novel anti-staphylococcal agents . Our results also suggest that different MSCRAMMs with similar structural organization may have originated from a common ancestor but have evolved to accommodate specific ligand structures .
Staphylococcus aureus is a Gram-positive commensal organism that permanently colonizes 20% of healthy adults and transiently colonizes up to 50% of the general population [1] . For many years , S . aureus has been a major nosocomial pathogen causing a range of diseases from superficial skin infections to life-threatening conditions , including septicemia , endocarditis and pneumonia [1] , [2] . Within the last decade a dramatic increase in the number of invasive infections caused by community-acquired S . aureus have been recorded in otherwise healthy children and young adults [3] , [4] . This outbreak together with the continued increase in antibiotic resistance among clinical strains underscores the need for new prevention and treatment strategies [1] . A detailed characterization of the molecular pathogenesis of S . aureus infections may expose new targets for the development of novel therapeutics . Several staphylococcal virulence factors have been identified including capsule , surface adhesins , proteases , and toxins ( reviewed in [5] , [6] , [7] , [8] ) . One of these virulence factors is the MSCRAMM ( microbial surface components recognizing adhesive matrix molecules ) clumping factor A ( ClfA ) . ClfA is the major staphylococcal fibrinogen ( Fg ) binding protein and is responsible for the observed clumping of S . aureus in blood plasma [9] , [10] . Essentially all S . aureus clinical strains carry the clfA gene [11]; ClfA is a virulence factor in a mouse model of septic arthritis [12] and in rabbit and rat models of infective endocarditis [13] , [14] , [15] . ClfA generates strong immune responses and has shown potential as a vaccine component in active and passive immunization studies . In one study , mice vaccinated with a recombinant ClfA segment containing the Fg-binding domain and subsequently challenged with S . aureus showed significantly lower levels of arthritis compared to mice vaccinated with a control protein [12] . In another study , mice passively immunized with polyclonal or monoclonal antibodies against the ClfA Fg-binding domain were protected in a model of septic death [16] . The humanized monoclonal antibody , Aurexis® , has a high affinity for ClfA and inhibits ClfA binding to Fg [17] . Aurexis is currently in clinical trials in combination with antibiotic therapy for the treatment of S . aureus bacteremia [18] . Thus ClfA is a viable target for both vaccine and therapeutic strategies . ClfA belongs to a class of cell wall-localized proteins that are covalently anchored to the peptidoglycan [5] , [19] , [20] . Starting from the N-terminus , ClfA contains a signal sequence followed by the ligand-binding A region composed of three domains ( N1 , N2 , and N3 ) , the serine-aspartate repeat domain ( R region ) , and C-terminal features required for cell wall anchoring such as the LPXTG motif , a transmembrane segment and a short cytoplasmic domain [21] , [22] , [23] . A crystal structure of a Fg-binding ClfA segment ( residues 221–559 ) which includes two of the domains ( N2N3 ) demonstrates that each domain adopts an IgG-like fold [24] . This domain architecture was also determined from the crystal structure of the ligand binding segment of SdrG from Staphylococcus epidermidis , an MSCRAMM that binds to the N-terminal region of the Fg β-chain [25] . A dynamic mechanism of Fg binding termed “Dock , Lock and Latch” ( DLL ) has been proposed for SdrG based on a comparison of the crystal structures of SdrG N2N3 as an apo-protein and in complex with a synthetic peptide mimicking the targeted site in Fg [25] . In the SdrG DLL model , the apo-form of the protein adopts an open conformation that allows the Fg ligand access to a binding trench between the N2 and N3 domains . As the ligand peptide docks into the trench , a flexible C-terminal extension of the N3 domain is redirected to cover the ligand peptide and “lock” it in place . Subsequently the C-terminal part of this extension interacts with the N2 domain and forms a β-strand complementing a β-sheet in the N2 domain . This inserted β-strand serves as a latch to form a stable MSCRAMM ligand complex . ClfA binds to the C-terminus of the Fg γ-chain [10] , [23] and a synthetic 17 amino acid peptide corresponding to this region was shown to bind to ClfA . Interestingly , the A-region of the staphylocccal MSCRAMM FnbpA protein also binds to the same region in Fg [23] . Moreover residues in this Fg segment are also targeted by the platelet αIIbβ3 integrin [26] , [27] , [28] and a recombinant form of ClfA has been shown to inhibit platelet aggregation and the binding of platelets to immobilized Fg [10] , [29] , [30] . The current study was undertaken to characterize the interaction of ClfA and Fg to define in detail the binding of the C-terminus of Fg's γ-chain and to explore if compounds can be constructed that antagonize the ClfA-Fg interaction but does not affect the Fg interaction with the platelet-integrin αIIbβ3 .
In previous studies , a segment of ClfA composed of residues 221–559 was shown to bind to the C-terminal end of the human Fg γ-chain [10] . We designed , based on structural similarities with SdrG , a smaller ClfA construct ( 229–545 ) predicted to be composed only of the N2 N3 domains and showed that ClfA229–545 retained the Fg-binding activity . To identify specific residues in Fg that are important for binding to ClfA229–545 , a panel of peptides ( Fig . 1A ) based on the Fg γ-chain sequence 395–411 ( referred to as γ1–17 ) were synthesized in which each position was sequentially substituted with an alanine residue ( alanines 11 and 14 were changed to serines ) . These peptides were tested as inhibitors in solid-phase binding assays , using a peptide concentration giving about 50% inhibition by the wild-type peptide . Peptides γ1–17H6A , γ1–17H7A , γ1–17G10A , γ1–17Q13A , γ1–17A14S and γ1–17G15A were significantly less potent inhibitors than the native sequence suggesting that the Fg residues H6 , H7 , G10 , Q13 , A14 and G15 interact with ClfA ( Fig . 1B ) . Remarkably , peptides γ1–17A11S , γ1–17D16A and γ1–17V17A showed enhanced inhibition of ClfA binding to a recombinant form of residues 395–411 of the Fg γ-chain fused to a GST protein ( GST-Fg γ1–17 ) compared to a peptide with the wild-type sequence , indicating a higher affinity of the peptide variants for ClfA . The ability of ClfA229–545 to bind to the peptide containing the γ1–17D16A mutation was further characterized . In solid-phase assays , ClfA binds to immobilized GST-Fg γ1–17 fusion protein with a lower affinity ( Kd = 657 nM ) compared to the mutated GST-Fg γ1–17D16A ( Kd = 35 nM ) ( Fig . 1C ) . In solution , using isothermal titration calorimetry ( ITC ) assays , ( Fig . 1D ) , ClfA also binds with a lower affinity to the native γ1–17 peptide ( Kd of 5 . 8 µM ) compared to the mutant Fg γ1–17D16A ( Kd of 3 µM ) . Thus , although the apparent dissociation constants differ according to the assays used to estimate them , similar trends in affinity between the wild-type and the D16A mutation were observed . Our results showed that alanine substitution at the C-terminal but not in the N-terminal region of the peptide affected MSCRAMM binding suggesting that the ClfA binding site is located at the very C-terminus of the Fg γ-chain ( Fig . 1 ) . Results also show that certain amino acid changes in the γ1–17 sequence enhance ClfA binding compared to the wild-type Fg sequence indicating that the human Fg γ C-terminal 17 residues may not be the optimum ligand for ClfA . Analysis of the previously solved SdrG-Fg peptide complex crystal structure showed that only 11 out of the 18 peptide residues interacted with the MSCRAMM . Similarly , only a part of the 17-residue γ-chain segment may be required for binding to ClfA . In order to establish the minimum Fg peptide required for binding to ClfA229–545 , a series of N- and C-terminal truncations of the γ1–17D16A peptide were synthesized ( Fig . 2A ) . Truncations of 2 , 4 , 6 or 8 amino acids at the N-terminus of the Fg γ-peptide resulted in a reduced but detectable binding affinity when tested using ITC . There was a direct relationship between the length of the peptide and its affinity for ClfA . The smaller the peptide , the lower was the observed affinity for the MSCRAMM ( Fig . 2B ) . Thus , the N-terminal residues of the Fg peptide ( residues 1–8 ) are not critical for the interaction but may either contribute to or stabilize the binding of the peptide to ClfA . On the other hand , deletions of 2 or 4 residues from the C-terminal end of the γ1–17D16A peptide abolished binding . These results indicate that the C-terminal amino acids of Fg are critical for binding to ClfA and are in agreement with a previous report that showed that Fg lacking the C-terminal residues AGDV in the γ chain ( corresponding to residues 14–17 in the peptide ) or a Fg-variant that replaces the last four γ-chain residues with 20 amino acids lacks the ability to bind recombinant ClfA221–550 and induce S . aureus clumping [10] . The Fg binding mechanism of SdrG276–596 involves a transition from an open conformation , where the peptide binding trench between the N2 and N3 domains is exposed for ligand docking , to a closed conformation of the SdrG276–596 seen for the MSCRAMM in complex with the ligand peptide . The insertion of the N3 extension into the latching trench on N2 , which represents the last step in the dynamic DLL binding mechanism , stabilizes the closed conformation of SdrG237–596 [31] . A closed conformation of apo SdrG N2N3 , stabilized by introducing a disulfide bond between the end of the N3 latch and the “bottom” of N2 , no longer binds Fg [31] demonstrating that for SdrG an open conformation is required for the initial docking of the ligand peptide . To explore if the binding of ClfA to Fg is also dependent on a movement of the latch we constructed a ClfA protein containing two cysteine substitutions . The locations of the cysteine mutations were determined using computer modeling and by sequence alignment to corresponding mutations in SdrG [31] . The mutant ClfAD327C/K541C generated a stable , closed conformation form . This recombinant His-tag fusion protein was purified by Ni+ chelating chromatography; ion-exchange and gel permeation chromatography . The ClfAD327C/K541C open and closed conformation forms were examined by SDS-PAGE analysis ( Fig . 2C ) . Under non reducing conditions , the disulfide bonded closed form of ClfAD327C/K541C migrated faster on SDS-PAGE than its non-disulfide bonded open form . Presumably , under non-reducing conditions , closed conformation mutants are more compact and migrate faster on SDS-PAGE than open conformation constructs . Under reducing conditions , the disulfide mutant and the wild-type protein migrate at the same rate . Surprisingly , the closed conformation of the disulfide mutant ClfAD327C/K541C was able to bind Fg ( Fig . 2C ) . Elisa-type binding assays where Fg or GST Fg γ1–17 peptide were coated in microtiter wells and incubated with ClfA showed that the closed conformation ClfAD327C/K541C bound the ligand with a much lower apparent Kd ( 34 nM Fg; 20 nM GST-Fg γ1–17 ) compared to the wild-type ClfA229–545 ( apparent Kd 305 nM Fg; 222 nM GST-Fg γ1–17 ) ( Fig . 2D ) . These results demonstrate that an open conformation may not be required for Fg binding to ClfA and that Fg binding by ClfA involves a mechanism that is different from the DLL mechanism employed by SdrG . Crystallization screens were carried out with ClfAD327C/K541C in complex with several N-terminal truncations of the γ1–17D16A peptide that were shown to bind ClfA . Crystals of the stable closed conformation of ClfA229–545 in complex with several peptides were obtained , but structure determination was attempted for only the ClfA ( 229–545 ) D327C/K541C-γ5–17D16A peptide . The crystals of the ClfA-peptide complex diffracted to a 1 . 95 Å resolution . Two copies of the ClfA-peptide complex were found in the asymmetric part of the unit cell and are referred to as A∶C and B∶D . Although the 13 residue Fg γ5–17 chain synthetic peptide was used for crystallization , only 11 residues were identified completely in both copies of the complex . The two molecules of ClfAD327C/K541C ( A and B ) are nearly identical with rms deviation of 0 . 3 Å for 312 Cα atoms and 0 . 55 Å for backbone atoms . As observed in the apo-ClfA221–559 structure [24] , the ClfA ( 229–545 ) D327C/K541C N2 and N3 domains adopt the DE-variant IgG fold . The overall structure of the ClfAD327C/K541C peptide complex ( A∶C ) and the two different orientations of the complex are shown in Figure 3A and 3B respectively . The C-terminal extension of the N3 domain makes a β-sheet complementation with strand E of the N2 domain . This conformation is locked by the engineered disulfide bond as predicted by SDS-PAGE analysis ( Fig . 2C ) and confirmed by the crystal structure ( Fig . S1 ) . The two copies of the Fg γ-peptide molecules are nearly identical with rms deviation of 0 . 5 Å for 11 Cα atoms and 0 . 89 Å for backbone atoms . The interaction between the ClfAD327C/K541C and the peptide buries a total surface area of 1849 Å2 and 1826 Å2 in the A∶C and B∶D complex , respectively . The interaction of the peptide with the N2 domain is predominantly hydrophobic in nature , in addition to a few main-chain hydrogen bonds ( Fig . 3C ) . Interactions between the Fg peptide and the N3 domain are both hydrophobic and electrostatic with the electrostatic contribution coming almost entirely from the main chain-main chain hydrogen bonds due to the parallel β-sheet formation of the peptide with strand G of the N3 domain ( Fig . 3C ) . The side-chain interactions between the peptide and ClfA are predominantly hydrophobic . The 11 C-terminal residues of the Fg γ-chain peptide sequence that interact with ClfA are composed of only two polar residues , Lys12 and Gln13 . Side chain atoms of Lys12 point away and do not interact with the ClfA protein whereas Gln13 makes two hydrogen bonds with the main chain atoms of Ile384 in ClfA ( Fig . 3D ) . A water-mediated interaction is also observed between Gln13 of the peptide and Asn525 of ClfA . Tyr338 in the N2 domain and Trp523 in the N3 domain play an important role in anchoring the peptide molecule . Tyr338 and Trp523 are stacked with residues Gly15 and Gly10 , respectively . In addition , Met521 and Phe529 make hydrophobic interactions with Ala7 and Val17 , respectively . The C-terminal residues of the peptide Ala14 , Gly15 , Ala16 , and Val17 are buried between the N2–N3 domain interface with the terminal Val residue , presumably threaded through a preformed ligand binding tunnel after ClfAD327C/K541C adopted its closed conformation . A hydrogen bond is observed between Lys389 of ClfA and the C-terminal carboxyl group of the peptide ( Fig . 3D ) . Mutational studies showed that Tyr338Ala and Lys389Ala mutant ClfA showed significantly reduced binding to Fg [24] which corroborates with the structural results . Also an earlier study showed that E526A and V527S affected the binding [32] . The structure shows that these residues make main-chain interactions with the peptide ( Fig . 3C ) . These residues are critical for the anchoring the peptide ( Lock ) and redirection of the latch . The individual N2 and N3 domains in the apo-ClfA221–559 and the closed form of ClfAD327C/K541C are almost identical with rms deviations of 0 . 33 and 0 . 42 Å for molecule A and 0 . 35 and 0 . 42 Å for molecule B , but the relative orientation of the N2 and N3 domains are significantly different ( Fig . 4A ) . This difference affects the association of the N2 and N3 domains . In the apo conformation , the buried surface area between the N2 and N3 domains is 87 Å2 compared to 367 Å2 in the closed form of the ClfA ( 221–559 ) D327C/K541C-peptide complex . In the apo-ClfA221–559 , the C-terminal residues ( Ala528-Glu559 ) of the N3 domain fold back and do not interact with the N2 domain . Moreover the folded-back segment completely occupies the binding site ( Fig . 4B ) . Therefore , in the folded-back conformation , the ligand binding site appears not to be accessible to the peptide and thus this conformation appears to be inactive . It is presently unclear what the spatial arrangements of the N2N3 domains are in intact ClfA expressed on the surface of a staphylococcal cell . The two structures of these domains solved so far where one is active and the other inactive form suggests a possible regulation of ClfA's Fg binding activity by external factors . One such factor may be Ca2+ which has been shown to inhibit ClfA-Fg binding [32] . Alternatively , it is possible that the folded-back conformation ( which is a larger protein construct ) is only one of the many possible conformations adopted by the unbound protein . Molecular modeling shows that the two domains in the folded-back conformation could adopt an orientation similar to their orientation in the ClfA-peptide complex ( Fig . S2 ) . Most likely , the structural rearrangements responsible for the transition of ClfA from an open unbound to the closed bound form are complex and involve different intermediate forms . The major difference between Fg-binding to ClfA and SdrG is that the directionality of the bound ligand peptide is reversed ( Fig . 4C ) . The C-terminal residues of the ligand is docked between the N2 and N3 in ClfA and makes a parallel β-sheet complementation with strand G of the N3 domain , whereas in SdrG , the N-terminal residues of the ligand are docked between the N2 and N3 domains and form an anti-parallel β-sheet with the G strand . In both cases there are 11 ligand residues that make extensive contact with the MSCRAMM but with one residue shifted towards the N3 domain in ClfA . Of these 11 residues , 7 and 11 residues participate in the β-strand complementation of SdrG and ClfA , respectively . Although the peptide binding model of ClfA is different to that of SdrG , the inter-domain orientations of the two MSCRAMMS are very similar [25] . Superposition of 302 corresponding atoms in the N2 and N3 domains of ClfA and SdrG showed a small rms deviation of 0 . 65 Å indicating the high structural similarity between the two MSCRAMMS . Another striking difference is that ClfA does not require an open-conformation for ligand binding , whereas Fg can not bind to a stabilized closed conformation of SdrG . ClfA binds the C-terminal end of Fg and the last few residues of the γ-chain presumably can be threaded in to the binding pocket . In the SdrG-Fg interaction , the binding segment in Fg does not involve the seven N-terminal residues of the ligand and therefore an open conformation may be required for ligand binding . The C-terminus of Fg γ-chain , which is targeted by ClfA , is also recognized by the αIIbβ3 integrin in Fg induced platelet aggregation , a vital step in thrombosis [10] , [33] . The Fg γ-chain complex with αIIbβ3 structure is not available but structures of related complexes provide clues on how αIIbβ3 likely interact with Fg [34] . In addition , the crystal structure of the αvβ3 integrin in complex with an RGD ligand provided a structural model of a similar ligand-integrin interaction [35] . In this structure , the Asp ( D ) residue of the RGD sequence coordinates with the metal ion in the Metal Ion Dependent Adhesion Site ( MIDAS ) of the integrin and thus plays a key role in the interaction . The platelet specific integrin αIIbβ3 recognizes ligands with an RGD sequence or the sequence Lys-Gln-Ala-Gly-Asp-Val found in Fg [34] . Structural studies with drug molecules that antagonize the integrin-RGD or -Fg interaction showed that each of the drug molecules contains a carboxyl group moiety that mimics the aspartic acid and a basic group that mimics the Arg ( or Lys in the case of Fg ) in the ligand [34] . These results suggest that the Lys and Asp residues in the C-terminal γ-chain sequence are critical for the interaction with integrin . Interestingly , our studies have shown that these Lys and Asp residues in Fg are not critical for ClfA binding ( Fig . 1B ) . In fact , substitution of Asp with Ala ( γ1–17D16A ) results in a higher binding affinity . Absence of a strong interaction with Lys12 in the ClfA-peptide complex structure also correlates with the biochemical data , suggesting that Arg is not a key player in the ClfA-Fg interaction . In general , our studies show that K406 and D410 , which are essential for the platelet integrin αIIbβ3-Fg interaction , are dispensable for the ClfA-Fg interaction . To experimentally examine this proposed difference , the ability of the synthesized Fg WT γ1–17 and mutated peptides ( γ1–17D16A and γ1–17K12A ) to inhibit full length Fg binding to αIIbβ3 was analyzed by an inhibitory ELISA type assay ( Fig . 5 ) . The WT γ1–17 peptide completely inhibited the binding of full-length fibrinogen to αIIbβ3 whereas γ1–17D16A and γ1–17K12A weakly inhibited Fg binding to αIIbβ3 . These results clearly demonstrated that the γ1–17D16A and γ1–17K12A peptides bind weakly to platelet integrin and therefore could serve as specific antagonists of Fg-ClfA interaction . Based on the results presented here , we postulate that the mechanism of interaction between ClfA and Fg is a variation of the “Dock , Lock and Latch ( DLL ) ” model of SdrG binding to Fg . In the DLL model of binding , the apo-form of the SdrG is in an open conformation to allow the ligand access to the binding cleft . A closed conformation of SdrG is unable to bind Fg . In the ClfA model , we believe that the peptide may thread into the cavity formed in a stabilized closed configuration and therefore the ClfA-Fg binding mechanism could be called “Latch and Dock” . In the case of CNA , a collagen binding MSCRAMM from S . aureus , the collagen molecule binds to CNA through a “collagen hug” model [36] which represents yet another variant of the DLL binding mechanism . All three MSCRAMM-ligand structures determined so far , SdrG , CNA and the ClfA have different ligand binding characteristics and mechanisms , although the overall structures of the ligand binding regions of these MSCRAMMs are very similar . These observations suggest that an ancestral MSCRAMM has evolved along different paths to accommodate different ligands without greatly altering the overall organization of the proteins . The co-crystal structure of ClfA in complex with the C-terminal region of the γ-chain of Fg will allow the design of potent antagonist of the ClfA-Fg interaction . The Fg based peptide analogs that antagonize the ClfA-Fg interaction but not affect the αIIbβ3 integrin interaction could serve as a starting point to develop novel anti-staphylococcal therapeutic agents that do not affect the αIIbβ3 .
Escherichia coli XL-1 Blue ( Stratagene ) was used as the host for plasmid cloning and protein expression . Chromosomal DNA from S . aureus strain Newman was used to amplify the ClfA DNA sequence . All E . coli strains containing plasmids were grown on LB media with ampicillin ( 100 µg/ml ) . DNA restriction enzymes were used according to the manufacturer's protocols ( New England Biolabs ) and DNA manipulations were performed using standard procedures [37] . Plasmid DNA used for cloning and sequencing was purified using the Qiagen Miniprep kit ( Qiagen ) . DNA was sequenced by the dideoxy chain termination method with an ABI 373A DNA Sequencer ( Perkin Elmer , Applied Biosystems Division ) . DNA containing the N-terminal ClfA sequences were amplified by PCR ( Applied Biosystems ) using Newman strain chromosomal DNA as previously described [38] . The synthetic oligonucleotides ( IDT ) used for amplifying clfA gene products are listed in Table S1 . Cysteine mutations were predicted by comparing ClfA221–559 to SdrG ( 273–597 ) disulfide mutant with stable closed conformations [31] and by computer modeling . A model of ClfA in closed conformation was built based on the closed conformation of the SdrG-peptide complex [25] . The Cβ-Cβ distances were calculated for a few residues at the C-terminal end of the latch and strand E in the N2 domain . Residue pairs with Cβ-Cβ distance less than 3 Å were changed to cysteines to identify residues that could form optimum disulfide bond geometry . The D327C/K541C mutant was found to form a disulfide bond at the end of the latch . The cysteine mutations in ClfAD327C/K541C were generated by overlap PCR [39] , [40] . The forward primer for PCR extension contained a BamHI restriction site and the reverse primer contained a KpnI restriction site . The mutagenesis primers contained complementary overlapping sequences . The final PCR product was digested with BamHI and KpnI and was ligated into same site in the expression vector pQE-30 ( Qiagen ) . All mutations were confirmed by sequencing . The primers used are listed in Table S1 . E . coli lysates containing recombinant ClfA and GST-Fg γ-chain fusion proteins were purified as previously described [32] . PCR products were subcloned into expression vector pQE-30 ( Qiagen ) to generate recombinant proteins containing an N-terminal histidine ( His ) tag as previously described [10] . The recombinant ClfA His-tag fusion proteins were purified by metal chelation chromatography and anion exchange chromatography as previously described [23] . To generate recombinant ClfA229–545 and ClfA221–559 proteins , PCR-amplified fragments were digested with BamHI and KpnI and cloned into BamHI/KpnI digested pQE-30 . The primers used to generate the recombinant constructs are listed in Table S1 . The reactions contained 50 ng of strain Newman DNA , 100 pmol of each forward and reverse primers , 250 nM of each dNTP , 2 units of Pfu DNA polymerase ( Stratagene ) and 5 µl Pfu buffer in a total volume of 50 µl . The DNA was amplified at 94°C for 1 min , 48°C for 45 sec; 72°C for 2 min for 30 cycles , followed by 72°C for 10 min . The PCR products were analyzed by agarose gel electrophoresis using standard methods [37] and purified as described above . The ability of the wild-type ClfA229–545 and disulfide ClfA mutants to bind Fg was analyzed by ELISA-type binding assays . Immulon 4HBX Microtiter plates ( Thermo ) were coated with human Fg ( 1 µg/well ) in HBS ( 10 mM HEPES , 100 mM NaCl , 3 mM EDTA , pH 7 . 4 ) over-night at 4°C . The wells were washed with HBS containing 0 . 05% ( w/v ) Tween-20 ( HBST ) and blocked with 5% ( w/v ) BSA in HBS for 1 h at 25°C . The wells were washed 3 times with HBST and recombinant ClfA proteins in HBS were added and the plates were incubated at 25°C for 1 h . After incubation , the plates were washed 3 times with HBST . Anti-His antibodies ( GE Healthcare ) were added ( 1∶3000 in HBS ) and the plates were incubated at 25°C for 1 h . The wells were subsequently washed 3 times with HBST and incubated with goat anti-mouse-AP secondary antibodies ( diluted 1∶3000 in HBS; Bio-Rad ) at 25°C for 1 h . The wells were washed 3 times with HBST and AP-conjugated polyclonal antibodies were detected by addition of p-nitrophenyl phosphate ( Sigma ) in 1 M diethanolamine ( 0 . 5 mM MgCl2 , pH 9 . 8 ) and incubated at 25°C for 30–60 min . The plates were read at 405 nm in a ELISA plate reader ( Thermomax , Molecular Devices ) . For the inhibition assays , recombinant ClfA229–545 was pre-incubated with Fg γ peptides in HBS for 1 h at 37°C . The recombinant protein-peptide solutions were then added to plates coated with 1 µg/well GST fusion protein containing the native human Fg γ 395–411 sequence ( called GST-Fg γ1–17 ) and bound protein was detected as described above . If the peptide binds ClfA it would inhibit binding of the GST-Fg γ1–17 to the MSCRAMM . For αIIbβ3 inhibition assay , Immulon 4HBX Microtiter 96-well plates ( Thermo ) were coated with αIIbβ3 ( 0 . 25 µg/well ) in TBS ( 25 mM Tris , 3 mM KCl , 140 mM NaCl , pH 7 . 4 ) over night at 4°C . The wells were washed with TBS containing 0 . 05% ( w/v ) Tween-20 ( TBST ) . After blocking with 3% ( w/v ) BSA dissolved in TBS for 1 h at RT , 10 nM of full length Fg was applied in the presence of either WT γ1–17 , γ1–17D16A or γ1–17K12A peptides and plates were incubated at RT for another hour . The bound full length Fg was then detected by goat anti human Fg ( 1∶1000 dilution , Sigma ) antibody followed by horseradish peroxidase-conjugated rabbit anti-goat IgG antibody ( 1∶1000 dilution , Cappel ) . After incubation with 0 . 4 mg/ml of substrate , o-phenylenediamine dihydrochloride ( OPD , Sigma ) dissolved in phosphate-citrate buffer , pH 5 . 0 , bound antibodies were determined in an ELISA reader at 450 nm . The proteins , antibodies and peptides were diluted in TBST containing 1% ( w/v ) BSA , 2 mM MgCl2 , 1 mM of CaCl2 and MnCl2 . The wild-type and mutated peptides corresponding to the 17 C-terminal residues of the fibrinogen γ-chain ( 395–411 ) and truncated versions of this peptide ( listed in Figure 2A ) were synthesized as previously described and purified using HPLC [10] . The interaction between ClfA proteins and soluble Fg peptides was analyzed by Isothermal titration calorimetry ( ITC ) using a VP-ITC microcalorimeter ( MicroCal ) . The cell contained 30 µM ClfA and the syringe contained 500–600 µM peptide in HBS buffer ( 10 mM HEPES , 150 mM NaCl , pH 7 . 4 ) . All samples were degassed for 5 min . The titration was performed at 30°C using a preliminary injection of 5 µl followed by 30 injections of 10 µl with an injection speed of 0 . 5 µl/sec . The stirring speed was 300 rpm . Data were fitted to a single binding site model and analyzed using Origin version 5 ( MicroCal ) software . The ClfAD327C/K541C protein was purified as described earlier and concentrated to 30 mg/ml . The synthetic γ-chain peptide analogs , P16 and N-terminal truncations of P16 ( P16 -2Nt , P16 -4Nt and P16 -6Nt ) were mixed with the protein at 1∶20 molar ratio and left for 30 min at 5° C . This mixture was screened for crystallization conditions . Small needles of the ClfA/P16 -2Nt , -4Nt and -6Nt were obtained during initial search of the crystallization condition , but we could only successfully optimize ClfA/P16 -4Nt and ClfA/P16 -6Nt . Diffraction quality crystals were obtained by mixing 2 µl of protein solution with 2 µl of reservoir solution containing 16–20% PEG 8K , 100 mM succinic acid pH 6 . 0 . Crystals of ClfA/ P16 -4Nt were flash frozen with a stabilizing solution containing 20% glycerol . Diffraction data were measured on Rigaku R-Axis IV++ detector . A total of 180 frames were collected at a detector distance of 120 mm with 1° oscillation . Data were indexed , integrated and scaled using d*terk [41] . The crystals diffracted to 1 . 95 Å and the data statistics were listed in Table 1 . Calculation of the Matthews coefficient suggested the presence of 2 copies of the molecule in the unit cell of the triclinic cell . The structure was solved by molecular replacement ( MR ) with the program PHASER [42] using individual N2 and N3 domains of ClfA as search model . Solutions for the N3 domain were obtained for the two copies followed by the solutions of N2 domains . Data covering 2 . 5–15 Å were used for the molecular replacement solution . Electron density maps calculated during the initial rounds of refinement showed interpretable density for 11 out of 13 peptide residues in both the copies of the complex . Modeling building of the peptide and rebuilding of a few loop regions were performed using the program COOT [43] . A few cycles of ARP/WARP [44] were performed to improve the map and for the building of water model . After a few cycles of refinement using Refmac5 . 2 [45] , electron density was clear for only the backbone atoms for two remaining N-terminal residues of the peptide molecule D and one residue for peptide C . The final model of ClfA included residues 230–299 , 303–452 , 456–476 and 479–545 in molecule A and 230–438 , 440–476 and 479–542 in molecule B . The structure was refined to a final R-factor of 21 . 1% and R-free of 27 . 9% . Stereochemical quality of the model was validated using PROCHECK [46] . Molecular modeling studies were performed using InsightII software ( Accrelys Inc ) . Figures were made using RIBBONS [47] . The atomic coordinates and structure factors of the complex structure have been deposited in Protein data bank with accession number; 2vr3 . | Staphylococcus aureus ( S . aureus ) is a common pathogen that can cause a range of diseases from mild skin infections to life-threatening sepsis in humans . Some surface proteins on S . aureus play important roles in the S . aureus disease process . One of these bacterial surface proteins is clumping factor A ( ClfA ) that binds to the C-terminal region of one of the three chains of fibrinogen ( Fg ) , a blood protein that plays a key role in coagulation . We carried out biochemical and structural studies to understand the binding mechanism of ClfA to Fg and to define the residues in Fg that interact with ClfA . Interestingly , the platelet integrin , which is important for platelet aggregation and thrombi formation , also binds to the same region of Fg as ClfA . Despite the fact that the two proteins bind at the same region , the mode of recognition is significantly different . Exploiting this difference in recognition , we have demonstrated that agents could be designed that inhibit the ClfA–Fg interaction but do not interfere with the interaction of Fg with the platelet integrin . This opens the field for the design of a novel class of anti-staph therapeutics . | [
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"and... | 2008 | A Structural Model of the Staphylococcus aureus ClfA–Fibrinogen Interaction Opens New Avenues for the Design of Anti-Staphylococcal Therapeutics |
There is increasing evidence that heritable variation in gene expression underlies genetic variation in susceptibility to disease . Therefore , a comprehensive understanding of the similarity between relatives for transcript variation is warranted—in particular , dissection of phenotypic variation into additive and non-additive genetic factors and shared environmental effects . We conducted a gene expression study in blood samples of 862 individuals from 312 nuclear families containing MZ or DZ twin pairs using both pedigree and genotype information . From a pedigree analysis we show that the vast majority of genetic variation across 17 , 994 probes is additive , although non-additive genetic variation is identified for 960 transcripts . For 180 of the 960 transcripts with non-additive genetic variation , we identify expression quantitative trait loci ( eQTL ) with dominance effects in a sample of 339 unrelated individuals and replicate 31% of these associations in an independent sample of 139 unrelated individuals . Over-dominance was detected and replicated for a trans association between rs12313805 and ETV6 , located 4MB apart on chromosome 12 . Surprisingly , only 17 probes exhibit significant levels of common environmental effects , suggesting that environmental and lifestyle factors common to a family do not affect expression variation for most transcripts , at least those measured in blood . Consistent with the genetic architecture of common diseases , gene expression is predominantly additive , but a minority of transcripts display non-additive effects .
Understanding the nature of genetic variation for complex traits , including disease , is important in human medicine , evolutionary biology and plant and animal breeding . Both the nature of complex trait variation , including the importance of non-additive genetic variation , and its dissection into contributions from individual genetic loci , have been debated for a century [1]–[5] . Traditionally , inference about genetic variation for complex traits comes from the resemblance ( or recurrence risk ) of relatives but more recently genotyping and sequencing technologies have been developed that allow the attribution of genetic variation to specific loci . Recently , the debate on genetic variation has focussed on ‘missing heritability’ for human disease , the discrepancy between estimates of heritability from pedigree data and the cumulative variation explained by validated associated DNA variants . Many explanations of missing heritability have been proposed in the literature , including that pedigree estimates of narrow sense heritability may be inflated due to epistatic variance [5] , causal variants not being in sufficient linkage disequilibrium with common SNPs because they are rare [6] and effect sizes too small to be detected with genome-wide significance [7] . Gene expression is an important complex trait because of increasing evidence of its correlation with disease susceptibility [8]–[11] . It is also an ideal model trait for genetic dissection: it can be measured genome-wide using array or sequencing methods so for each sample thousands of expression phenotypes can be obtained and analysed . Almost all studies looking at genetic variation influencing transcript levels in humans have done so using an additive model , however , studies in several model organisms have identified a substantial fraction of genes with non-additive or dominance inheritance patterns [12]–[15] . If gene expression variation is to be utilized more fully to inform on the biological mechanisms leading to disease susceptibility [11] , then knowledge of the inheritance patterns and resemblance between individuals is clearly important . In this study , we combine the power of pedigree and SNP-based designs to quantify and dissect the contribution of additive and non-additive variation using gene expression on 17 , 994 probes measured on 862 individuals from 312 nuclear families ( the Brisbane Systems Genetics Study , BSGS ) [16] . We find strong evidence and consistency for prevailing additivity , but also detect and replicate dominance variation and dominant SNP effects for a number of probes . We detect and replicate a single over-dominant locus where the heterozygous genotype at a SNP is associated with increased expression at a gene that is 4MB downstream .
Additive ( Va ) and non-additive ( Vd ) genetic variance components were estimated for RNA expression levels measured at 17 , 994 probes on 862 individuals across 312 families in BSGS , using restricted maximum likelihood . Of 17 , 994 probes that passed QC ( methods ) , 14 , 753 ( 82% ) had narrow-sense heritability ( h2 ) estimates >0 ( Figure 1 and Figure S1 ) . Under the assumption of no additive genetic variance for any probe , we would expect to observe ∼9 , 000 probes ( ∼50% ) with estimates of Va = 0 as our estimates are constrained to non-negative . Here we find that the proportion of probes with h2 estimates >0 is 0 . 82 . Therefore , accounting for sampling variance of h2 estimates we expect the proportion of probes that have true heritable variation is 2 ( 0 . 82–0 . 50 ) = 0 . 64 , in concordance with other studies [18] , [19] . Although non-additive variance is more difficult to detect due to higher sampling variances and confounding with estimates of additive and shared environmental variance [2] , [3] , we find 5 , 798 probes ( 32% ) have a non-zero estimate of Vd ( Figure 1 and Figure S1 ) . The observation that greater than 50% of probes have a zero estimate of Vd is due to the estimation of Vd within a model that jointly estimates Va ( Text S1 and Figure S2 ) . The results for dominance are consistent with the majority of probes not displaying dominance variation . The conclusions from the number of non-zero estimates are also consistent with that from employing a false discovery rate ( FDR = 0 . 05 ) approach: 11 , 957 ( 66% ) of probes had an estimate of additive variation significantly different from zero , while for only 960 ( 5 . 3% ) was dominance variation significantly different from zero ( corresponding P-value thresholds , 1 . 3e-5 and 9 . 7e-6 , respectively ) ( Table 1 ) . A small number of probes ( 678 , or 3 . 7% ) had both significant additive and dominance variation . For those probes , the additive component was much larger than the dominance component ( Figure S3 ) . Hence , by jointly estimating additive and dominance variation in pedigrees on ∼18 , 000 genome-wide RNA transcripts , we conclude that the majority of probes display genetic variation , most of which appears additive ( Figure S3 ) . We next estimated the proportion of phenotypic variation attributable to familial non-genetic factors ( Vf ) . The proportion of phenotypic variance attributed to within families was partitioned by inclusion of a family term alongside the additive genetic relationship term ( see equation [3] in methods ) . In total 3 , 373 probes had a non-zero estimate of ( Figure 1 ) , which is consistent with estimates from expression levels measured in skin and fat tissue [18] . As with Vd , the high proportion of zero estimates is likely due to the estimation of Vf jointly with Va . However , non-zero estimates do not fully represent the true underlying level of common family variance as a proportion of non-zero estimates are expected by chance due to sampling error ( Figure S4 and Text S2 ) . This is important when we consider that the expected sampling variance of Vd and Vf are greater than Va [2] , [3] . Indeed , at an FDR 0 . 05 ( corresponding to p<2 . 3e-7 ) only 17 probes ( in 17 genes ) ( Table S1 ) show a significant estimate of non-genetic familial variation . On average , the phenotypic correlations between parent pairs ( n = 71 ) for probes with significant Vf were 4 standard deviations above the mean correlation of all probes ( Figure S5 ) . We investigated shared biological functionality among the 17 genes by performing a GO term [20] enrichment analysis using GOEAST [21] . No GO terms were found to be significantly enriched suggesting that common environmental effects that influence the transcript levels act independently of a shared biological network . A possible and likely explanation is that there are numerous environmental effects that independently influence the transcription of specific genes [22] , [23] . From these analyses we conclude that on average , environmental factors shared by all family members do not have a strong effect on gene expression measured in blood samples . We then performed a global eQTL analysis of additive and dominance effects , associating the 17 , 994 expression traits with SNP genotypes in a dataset of 339 unrelated individuals drawn from BSGS . In total , we identify a total of 5 , 033 eQTL [FDR 0 . 05 , corresponding to p<4 . 8e−4 ( cis ) and p<6 . 2e−10 ( trans ) ] with an additive effect across 3 , 364 probes ( Table 1 and Table 2 ) . The majority ( 84% ) of these eQTL are located in cis-regions and on average the top eSNP ( SNP with the strongest association ) explained 11 . 3% of the phenotypic variance of the probe with which it is associated . Our analysis of dominance eQTL fits a model that includes a dominance effect ( d ) as well as the main additive effect . From this analysis we identify 208 eQTL ( 179 cis-acting and 29 trans-acting ) that have a study-wide significant [FDR 0 . 05 , corresponding to p<4 . 1e−4 ( cis ) and p<4 . 7e-10 ( trans ) ] dominance effect , including 7 with over-dominance . Despite the power to detect dominance-acting eQTL being considerably lower than that to detect additive effects in SNP-trait association studies [24] , we sought to replicate the dominance eQTL in an independent sample of 139 individuals . Of the 208 eQTL with dominance effects , 32 replicated at p<2 . 4e−4 = 0 . 05/208 , the Bonferoni threshold ( Table 1 ) . For the remaining 176 SNPs not significant in the replication data we tested for differences in their estimates of d from CHDWB_EA , comparing the groups of SNPs that were +d against −d from BSGS ( Figure S6 ) . The significant difference between the +d and −d groups ( P = 0 . 0031 ) indicates that these loci are enriched for dominance effects . Of the six associations with significant over-dominance in BSGS , we replicate the association between rs12313805 ( chr12:16 , 523 , 922; hg19 ) and a probe in ETV6 ( TSS chr12:11 , 938 , 923; hg19 ) , an ETS family transcription factor ( Figure 2 ) . Individuals carrying the heterozygous genotypes ( A/G ) for rs12313805 have an up-regulation of ILMN_1789596 , the probe in ETV6 , compared to individuals with the two homozygous genotypes that show no significant difference in expression levels . The average fold difference between heterozygous and homozygous individuals is 2 . 1 and 1 . 6 in BSGS and CHDWB_EA , respectively . One possible explanation for the observed over-dominance association is that it is caused by two tightly linked SNPs with additive effects in opposite allelic directions . To investigate this possibility we analysed a 10MB imputed ( against 1000 Genomes V1 . 3 ) region , +/−5MB of rs12313805 , for additive and non-additive associations ( Figure S7 ) . In this region there are no two SNPs with additive effects large enough that should they be in opposite directions , could combine to cause a spurious over-dominance association of the magnitude observe here . Furthermore , we performed a haplotype analysis using a three-SNP sliding window and looking at additive and non-additive haplotype associations [25] . Only haplotypes whose association models included non-additive terms showed significant associations ( Figure S7 ) . To characterise the network effects of large cis-eSNP we calculated the inverse covariance matrix ( V−1 ) [26] , otherwise known as the precision matrix , of the gene expression levels for the 17 , 994 probes in the dataset of unrelated individuals . Because the normalised expression data follows a multivariate normal distribution , element [i , j] of V−1 represents the partial correlation between probes i and j , conditional on remaining probes . The matrix is sparse with non-zero elements representing conditional correlations between probes [27] . For the 10 probes with eSNP that explain the largest proportion of ( Table 3 ) ( hereon termed primary probes ) , we extracted a list of their conditionally correlated probes based on non-zero elements in V−1 . For each of the conditionally correlated probes we extracted their association with the eSNP for the primary probe . On average , eSNPs were significantly associated with 64% of the conditionally correlated probes ( Table 3 ) ( multiple testing threshold of 0 . 05/n , where n is the number of conditionally correlated probes for a given primary probe ) . Within the population-based eQTL analysis , these eSNPs were significantly [P<4 . 8e-4 ( cis ) and P<6 . 2e-10 ( trans ) ] associated with their respective conditionally correlated probes in only 3% of cases , implying that in almost all cases they were not identified as contributing to the additive genetic variance of the conditionally correlated probe ( Details of conditionally correlated probes are given in Table S2 ) . To further evaluate the impact of the additive effect of the eSNP on the additive genetic variation of the conditionally correlated probes we re-estimated the variance components but included the genotyped eSNP as a fixed covariate in the family based analysis . The mean reduction in caused by fitting the genotypes of the eSNP is 3 . 67% . If the conditional correlations were caused by environmental correlations then we would expect no change in the estimate of . These results demonstrate that a SNP with a cis-effect on a particular probe also has trans-effects by leading to expression variation of other probes that are within a gene expression network . This approach also allows the identification of links between probes that are caused by genetic effects . This approach also allows the identification of links between probes that are caused by genetic effects . There is a strong relationship between narrow-sense heritability estimated from the pedigree and the proportion of variance that is explained by additive eSNPs that can be identified from an eQTL association analysis ( Figure 3 and Figure S8 ) . For many transcripts the vast majority of additive variance is accounted for by a few loci , with the proportion of explained by eSNPs greater than 80% for 721 probes ( 4% of total probes and 21% of probes with an eQTL ) ( Figure S9 ) . All SNPs accounting for >80% of a probe's are located within the cis-region of the transcription start site ( TSS ) . This is in strong contrast to a mean proportion of variance for trans-acting eSNP of 3 . 2% . Such observations imply that proximal transcription-factor binding sites involved in RNA polymerase II recruitment and subsequent transcription are key components of the regulatory architecture and suggest that distal-acting elements exert a weaker influence . The two approaches , the first a decomposition of the variance among related individuals and the second an association analysis of SNP genotypes in unrelated individuals , provide independent estimation of the genetic effects influencing transcript levels . We identified additive eQTL for 30% ( 3 , 364/11 , 279 ) of the probes that had only a significant additive component in the pedigree analysis , which contrasts sharply with only 2% ( 7/282 ) of additive eQTL for probes with only significant dominance variance in the pedigree analysis ( Table 1 ) . Conversely , 67 dominance eQTL were identified ( 61 with additive and dominance effects and 6 with over-dominance effects ) and 9 replicated for 282 of the probes with just dominance variance in the pedigree analysis , although for the majority of these eQTL a significant additive effect was also identified , reflecting the shared genetic covariance between additive and dominance terms [2] .
We have used a complementary analysis of pedigree and SNP data to partition variation for gene expression in whole blood into components of additive , dominance and environmental variation , and have attributed a proportion of additive and dominance variation to specific cis and trans acting loci . The extent of non-additive genetic variance for gene expression has been investigated in theory [28] and empirically in plant species [14] , [29] and model organisms [30]–[32] . This is the first , systematic investigation of non-additive genetic variance influencing RNA transcript variation in humans . Due to low power to estimate three variance components jointly , we have estimated non-additive and common environmental components in separate models , and show little confounding with estimates of additive variance ( Text S1 and Figure S2 ) . Our pedigree design did not allow the separation of dominance variation and that due to epistatic interactions , and our SNP analysis lacked power to detect and replicate specific epistatic interactions . In our pedigree design , epistatic variation is partially confounded with dominance . The inference we draw from the pedigree and SNP analyses are consistent and although we cannot rule out variation due to epistasis , it is unlikely to contribute a large proportion of phenotypic variation . One possibility is that common environmental and non-additive effects are manifesting as the additive component . However , our strong relationship between additive variance estimated from pedigree and SNPs data is not consistent with this hypothesis . It is also possible but unlikely that the variance due to common environmental factors and non-additive genetic factors cancel each other out by chance . Thus the most parsimonious explanation of the results is that additive variance explains most of the observed similarity between relatives and non-additive variance is generally of small magnitude and cannot explain a large proportion of the genetic ( and therefore phenotypic ) variance . The large-scale additive genetic contribution to phenotypic variance is in line with predictions from theory [4] and is important in the context of understanding the impact of gene expression variance on complex disease . How strong is the relationship between the pedigree and SNP based estimates of additive variation ? For heritable probes with a significant eQTL the relationship is very strong , with the mean proportion of the estimate of narrow sense heritability from the pedigree explained by SNPs of = 0 . 38 ( Figure S9 ) . For many of these probes the identification of SNPs explaining the majority of additive variance , located in cis-regions , provides strong support that the underlying molecular mechanisms that influence expression at these transcript positions can be identified through targeted sequencing . Significant non-additive effects are identified for a few probes; with one particularly interesting finding of the SNP associations showing over-dominance with probe transcript levels . As a component of maintaining genetic variance , over-dominance has been discussed in livestock and model species [33] , [34] , however , in humans , other than Sickle-Cell Anaemia , few examples of over-dominance have been shown . Whilst the exact mechanism by which rs12313805 acts in an over-dominant manner to influence transcription levels in ETV6 is unknown , non-additive effects at the gene expression level raise the possibility of the contribution of non-additive modes of inheritance to higher order phenotypes such as disease susceptibility . If we examine the total of the components of variation for expression of all probes , then we see that non-genetic factors play the largest role ( Figure S3 ) . However , there is strong evidence that for the majority of probes the extent of genetic variation as well as the overlap of genetic effects can differ greatly between tissues [18] , [19] , [35] . Therefore , it is likely that the components of variation for the same probe measured in other tissues will be different . Despite the similar inference on mode of gene action from the pedigree and SNP analyses , there appears to be “missing heritability” for many probes ( Figure 3 and Figures S8 and S9 ) . Missing heritability for transcript probes is likely to be due to similar factors as that for other complex traits , where there is increasing evidence for large numbers of common SNPs with small effect [7] , [36] . For gene expression , one explanation for the occurrence of SNPs with small effects is the impact of an eQTL on the transcription of multiple probes across a pathway or gene network . When we observe probes whose additive variance can almost entirely be attributed to a single locus , what is the impact of that SNP on the transcription of other genes involved in the same pathway ? In other words , if accounts for 90% of for , and the product of influences transcription at , and , then what effect does have on , and ? We have presented an approach that demonstrates a causal genetic relationship between large cis-acting eQTL and multiple conditionally correlated probes ( Table 3 ) . The majority of such associations would have been missed from a conventional eQTL mapping study due to high significance thresholds imposed when searching for trans-associations . In conclusion , we used a complementary pedigree and SNP-based design and analysis to dissect phenotypic variation for gene expression to inform on the underlying genetic architecture . We show that whilst a small proportion of genetic variance acts in a non-additive manner , the vast majority is additive . We also demonstrate a genetic causal link between eQTL with large cis-effects and secondary probes acting within a gene expression network .
All participants gave informed consent and the study protocol was approved by the appropriate institutional review boards . The Brisbane Systems Genetics Study ( BSGS ) comprises 862 Individuals of European descent from 312 independent families [16] . Families consist of adolescent monozygotic ( MZ ) and dizygotic ( DZ ) twins , their siblings , and their parents ( Table S3 ) . DNA samples from each individual were genotyped on the Illumina 610-Quad Beadchip by the Scientific Services Division at deCODE Genetics Iceland . After standard QC filters were applied 528 , 509 SNPs with MAF>1% remained for further analysis . Full details of genotyping procedures are given by Medland et al . [37] . Gene expression profiles were generated from whole blood collected with PAXgene TM tubes ( QIAGEN , Valencia , CA ) using Illumina HT12-v4 . 0 bead arrays . Expression levels were corrected for batch , sex and age effects using linear models . The Illumina HT-12 v4 . 0 chip contains 47 , 323 probes , although some probes are not assigned to RefSeq genes . SNPs within the probe sequence have the potential to lead to spurious associations [38] . We removed any probe which had a genotyped or imputed SNP with MAF>0 . 05 located within their probe sequence ( Illumina manifest file used for probe coordinates ) . Non-genotyped SNPs were determined by imputing against 1000 Genomes ( V1 . 3; hg19 ) data . After quality control to remove poorly imputed SNPs we removed a total of 1 , 027 probes with SNPs in their probe sequence . For the eQTL analysis , any probes where less than 10% of samples had a detection P-value>0 . 05 were removed from the dataset . Of the 24 , 317 probes retained , the mean call rate of the proportion of samples with detection P-values , 0 . 05 was 97% , implying that relatively little missing data remained within the expression dataset . After removing 6 , 322 putative and/or not well-characterised genes i . e . probe names starting with HS ( n = 1 , 841 ) , KIAA ( n = 158 ) and LOC ( n = 4 , 323 ) , 17 , 994 well-characterised probes remained for analysis , which corresponds to 13 , 486 RefSeq genes . Gene expression quantification and normalisation are described in Powell et al . [16] . Analyses of variance components were carried out using the full BSGS dataset of 862 individuals . Mapping of additive and non-additive SNP associations was conducted on a subset BSGS comprising of 339 unrelated individuals . Including the two parents from families with parents and children in BSGS and a randomly chosen individual from families with no parent in BSGS formed the unrelated dataset . We calculated the pairwise Identity-By-State ( IBS ) from common SNPs ( MAF>0 . 05 ) to ensure the unrelated dataset contained no genetic relationships greater than would be expected by sampling from an unrelated population ( Figure S10 ) [7] , [39] , [40] . The CHDWB study comprises of 139 Caucasian ( CHDWB_EA ) healthy individuals , between the ages of 26 and 79 . Gene expression profiles were generated using RNA extracted from whole blood collected with Tempus tubes ( Applied Biosystems , Foster City , CA , USA ) and hybridized to Illumina HT12 v3 . 0 bead arrays . Genotypes were measured using Illumina OmniQuad arrays . Full details of individuals , generation of RNA transcript abundance and genotype calling are given in Qin et al . [17] . Gene expression levels were normalized using the same procedures as applied to BSGS data . After quality control filtering there were 312 , 151 SNPs that overlapped between BSGS and CHDWB datasets ( MAF>0 . 01 ) . We fitted the following mixed linear model: ( 1 ) with y is an n×1 vector of gene expression levels . Random additive genetic effects a and random dominance effects d are related to y by incidence matrices Z1 and Z2 respectably . The n×1 vector e contains the error terms . The joint distribution of all variables in [1] is the following: ( 2 ) where . The matrix A ( n×n ) is the additive relationship matrix and D ( n×n ) is the dominance relationship matrix and I is an identity matrix . A and D are calculated from the pedigree relationship information between individuals . Lynch and Walsh [3] detail the calculation of A and D given pedigree information . For each probe genetic variance components , and , are estimated using an average information REML algorithm [41] implemented in ASREML [42] . Iterations were performed until the minimum variance of the function ( −2logL ) was less than 1e-7 . The estimated variance components are expressed as ratios of the total phenotypic variance ( ) for each model: the additive variance ratio as , i . e . the heritability , and the dominance genetic variance ratio as . There is not enough information contained between the relative pairs to accurately separate , additional genetic and non-genetic variance components in [1] . In [1] it is assumed that the environmental values of different individuals are independent and uncorrelated with genetic values and so the model does not test for effects such as common family environment . By fitting a model including additive genetic ( a ) and family ( f ) effects to the expression levels of each probe we can estimate the proportions of variance attributable to common environment ( variance due to environmental effects shared within a family ) . Estimates of h2 and f2 ( ) were obtained from ( 3 ) where the joint distribution follows [2] , with replacing and F replacing D . Here , F ( 1×n ) is a vector containing family identifiers . For each probe the significance of a , d and f estimates were determined by comparing the full model to a reduced model where the relevant term was dropped from the model ( Table S4 ) . Full and reduced models were compared using likelihood ratio ( LR ) tests . From resulting P-values a transcript-wise FDR was calculated . We tested for association between the 528 , 509 genotyped SNPs and the normalised expression levels of 17 , 994 probes using the linear regression functions in PLINK [43] . In order to detect independent eQTL we performed a series of conditional regression analyses . For each probe with an identified eQTL we corrected for the main effects of the top eSNP ( SNP with the strongest association ) by regressing its genotypes against the expression levels . Residuals from this analysis were then used for second round of eQTL mapping , allowing us to detect independent eQTL . If additional eQTL were identified from this second round of analysis , the process was repeated , correcting for the main effects of the top eSNP from the first and second eQTL using multivariate regression . This process was repeated until either a ) no additional significant eQTL were identified or b ) four independent eQTL had been identified . Cis-eQTLs were defined as associations between SNPs within 1MB of either the 3′ or 5′ end of the TSS . We defined trans-associations as associations involving SNPs elsewhere in the genome . To correct for multiple testing , we controlled the FDR [44] at 0 . 05: the distribution of observed P-values was used to calculate the FDR , by comparing it with the distribution obtained from permuting expression phenotypes relative to genotypes 100 times . At an FDR = 0 . 05 level , the significance P–value thresholds were 4 . 8e-4 ( cis ) and 6 . 2e-10 ( trans ) . For probes that were included for series of conditional analyses , the false discovery was again controlled at 0 . 05 by correcting for the number of running 100 permutations where the top associations were included as conditional main effects . In addition to testing additive effects , we tested for associations that included a dominance component for each SNP by probe . Associations were tested using the –genotypic command in PLINK [43] which fits a 2 degree of freedom joint test for both additive and dominance terms . As described above , we controlled for multiple testing by using an FDR of 0 . 05 calculated from a 1000 cycle permutation analysis where the permuted phenotype was tested for association using a 2 degrees of freedom model . At an FDR = 0 . 05 level , the significance P–value thresholds for the dominance term ( deviation ) were 4 . 1e-4 ( cis ) and 4 . 7e-10 ( trans ) . | Gene expression levels are known to influence common disease susceptibility in humans , with GWAS significant SNPs frequently found in regulatory regions . The expression levels of most genes are influenced by genetic variants , often located close to the gene itself . Expression Quantitative Trait Loci ( eQTL ) mapping studies have been very successful in identifying SNPs associated with expression levels; however , little is currently known about the extent of additive and non-additive genetic variance and the role of common environment on gene expression . Here we report a comprehensive study of the sources of genetic and non-genetic variation for gene expression levels using both pedigree and genotype information . We show that the majority of transcripts exhibit only additive genetic variance with congruence from independent methods using pedigree and genotype approaches . However , there are a small number of probes whose expression levels are influenced by non-additive genetic variance . For some of these probes we identify SNPs acting in a dominant and over-dominant manner that replicate in an independent sample . Surprisingly , only 17 probes exhibit significant levels of common environmental effects , suggesting that environmental and lifestyle factors common to a family do not affect expression variation for most transcripts , at least those measured in blood . | [
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] | 2013 | Congruence of Additive and Non-Additive Effects on Gene Expression Estimated from Pedigree and SNP Data |
The Gram-positive bacterium Staphylococcus aureus , similar to other pathogens , binds human complement regulators Factor H and Factor H related protein 1 ( FHR-1 ) from human serum . Here we identify the secreted protein Sbi ( Staphylococcus aureus binder of IgG ) as a ligand that interacts with Factor H by a—to our knowledge—new type of interaction . Factor H binds to Sbi in combination with C3b or C3d , and forms tripartite Sbi∶C3∶Factor H complexes . Apparently , the type of C3 influences the stability of the complex; surface plasmon resonance studies revealed a higher stability of C3d complexed to Sbi , as compared to C3b or C3 . As part of this tripartite complex , Factor H is functionally active and displays complement regulatory activity . Sbi , by recruiting Factor H and C3b , acts as a potent complement inhibitor , and inhibits alternative pathway-mediated lyses of rabbit erythrocytes by human serum and sera of other species . Thus , Sbi is a multifunctional bacterial protein , which binds host complement components Factor H and C3 as well as IgG and β2-glycoprotein I and interferes with innate immune recognition .
In order to establish an infection pathogens have developed multiple mechanisms to avoid immune recognition and to escape host immune attack [1] , [2] . Complement , which mediates a powerful immediate innate immune defense of vertebrate hosts , is activated , within seconds upon entry of a foreign invader [1] , [2] . Activation of the complement system occurs through three pathways , the alternative , the classical , or the lectin binding pathway . The activated system cleaves the central complement protein C3 into the fragments C3a and C3b , and deposits C3b onto the surface of a microbe , which normally results in opsonization and elimination of the microbe by phagocytosis . This surface deposited C3b initiates further activation of the complement cascade and results ultimately in the formation of the membrane attack complex ( MAC ) , which forms a pore in the membrane and destroys the microbe by complement-mediated lyses . However for Gram positive bacteria MAC mediated lyses seems of minor significance . The cleavage products C3a and C5a serve as potent anaphylatoxins , which attract immune effector cells to the site of infection . Non-pathogenic microbes are effectively killed and eliminated by the complement system [3] . In order to restrict complement activation to the surface of an invading microbe host cells are protected from complement attack by membrane bound and soluble regulators . Factor H is the major fluid-phase complement regulator that controls alternative pathway activation at the level of C3 . The 150-kDa Factor H protein is exclusively composed of 20 structural repetitive protein domains , termed short consensus repeats ( SCR ) [4] . Factor H is a member of a protein family , that includes the Factor H like protein 1 ( FHL-1 ) , encoded by an alternatively spliced transcript of the Factor H gene , and five Factor H related proteins ( FHRs ) that are encoded by separate genes [5] . Factor H controls complement activation by acting as a cofactor for the serine protease Factor I , which cleaves surface-bound C3b into iC3b . In addition , by competing with Factor B for C3b binding Factor H accelerates the decay of the alternative pathway C3 convertase . Thus , Factor H blocks C3b deposition and amplification of the complement cascade on the cell surface [5] , [6] . In order to survive and to establish an infection , pathogens need to inhibit the host complement attack and apparently utilize diverse escape mechanisms . Several pathogens acquire host fluid-phase complement regulators , like Factor H , FHL-1 , FHR-1 and C4b-binding protein ( C4BP ) from host plasma and body fluids . Bound to the surface of a pathogen , these host regulators retain complement regulatory functions , and inhibit complement activation . Therefore , acquisition of host regulators masks the pathogenic surface , which results in survival of the pathogen [7] , [8] . This common strategy of complement evasion has been identified for multiple pathogens , including Gram-positive and Gram-negative bacteria , human pathogenic fungi , parasites and viruses and several of the corresponding surface proteins were identified [1] . The vast majority of these pathogenic surface proteins bind additional host plasma proteins and display multiple functions . The M protein of Streptococcus pyogenes binds the complement regulators Factor H , FHL-1 and C4BP as well as other plasma proteins , i . e . plasminogen , fibronectin , thrombin , fibrinogen , IgA , IgG and kininogen [1] , [9]–[14] . The Candida albicans surface protein Glyceratphosphat-Mutase 1 ( Gpm1 ) binds Factor H , FHL-1 and plasminogen [15] . In addition , Complement Regulator Acquiring Surface Protein 1 ( CRASP-1 ) of Borrelia hermsii and Tuf of P . aeruginosa , bind Factor H , FHR-1 and plasminogen [16] , [17] . The additional Factor H binding pathogenic surface proteins e . g . CRASP1 of Borrelia burgdorferei , PspC of S . pneumoniae and porin protein 1A of Neisseria gonorrhoeae are candidates for combined Factor H and plasminogen binding [18]–[20] . These pathogenic surface proteins display multiple functions and interfere with the complement regulation and coagulation . Thus , multiple or potentially all pathogens acquire soluble host factors and utilize these proteins for immune evasion [1] . S . aureus is a major human pathogen responsible for hospital- and community-acquired infection . The Gram-positive bacterium permanently colonizes the human skin and mucous membranes of approximately 20% of the population [21] . Once the pathogen has crossed host immune barriers S . aureus can cause superficial skin infection , toxin-mediated diseases or serious invasive infections depending on the interaction of the pathogen's virulence factors and the defense mechanisms of the host [22] . The pathogen utilizes complex strategies to survive and disseminate within the host and expresses several virulence factors to block both innate and adaptive immune response [23] . S . aureus utilizes several proteins to control and evade the host complement attack . The cell wall-anchored protein A ( SpA ) binds the Fc region of IgG [24] . S . aureus expresses the zymogen staphylokinase , that cleaves human plasminogen into active plasmin , which in turn cleaves IgG . In both cases recognition of the pathogen by C1q , the initial component of the classical complement activation pathway , is inhibited [25] , [26] . Sbi is an additional staphylococcal IgG-binding protein that similar to SpA interacts with the Fc part of IgG [27] . Furthermore , Sbi binds β2-glycoprotein I , which is also termed apolipoprotein H [28] . Recently , additional effector molecules of S . aureus are identified , that directly interfere with complement activation at the level of C3 . The extracellular fibrinogen-binding protein ( Efb ) , the Efb homologous protein ( Ehp ) , and the extracellular complement-binding protein ( Ecb ) , bind C3 and C3d , prevent further activation of C3b and consequently block the activity of C3b-containing convertases [29] , [30] , [31] , [32] , [33] . The staphylococcal complement inhibitor ( SCIN ) acts on surface-bound C3 convertases , C3bBb and C4b2a , by stabilizing these complexes , thereby reducing the enzymatic activity [34] , [35] . Here we show binding of Factor H and FHR-1 to the surface of intact S . aureus and in addition identify the secreted staphylococcal Sbi protein as a Factor H binding protein . Native Factor H from human serum binds to Sbi , and this binding is mediated by a second serum factor , which was identified as C3 . Factor H binding is increased in the presence of C3b or C3d suggesting formation of a tripartite complex . This complex blocks activation of the alternative complement pathway . The Factor H binding site of Sbi which was located to domains III and IV is distinct from the IgG binding sites which are contained in the N-terminal domains I and II [28] . Here , we demonstrate a novel mechanism for Factor H binding by Sbi . Sbi forms a tripartite complex with Factor H and C3b or C3d and this complex interferes with complement activation .
In order to analyze binding of host complement regulators to S . aureus , strain H591 was incubated in human serum . After extensive washing bound proteins were eluted , separated by SDS-PAGE , transferred to a membrane and analyzed by Western blotting . This approach identified three bands of 150 , 43 and 37 kDa , which represent Factor H , FHR-1β and FHR-1α , respectively ( Figure 1A , lane 2 ) . These proteins were absent in the final wash fraction , thus suggesting specific binding ( Figure 1A , lane 1 and lane 2 ) . The same proteins were also identified in human serum ( Figure 1A , lane 3 ) . When bacteria were incubated with purified Factor H binding of the purified protein was also detected in the eluted fraction ( Figure 1B , lane 2 ) . In order to characterize the bacterial ligand mediating this interaction we hypothesized that the staphylococcal Sbi protein might represent the binding protein . The N-terminal region of Sbi ( i . e . Sbi-E ) is composed of four domains and includes the IgG binding domains I and II , whereas domains III and IV lack antibody binding properties ( Figure 2A and C ) ( [28] , Burman et al . JBC in press ) . IgG binding of Sbi-E and Sbi-I was confirmed for one polyclonal antiserum and two monoclonal antibodies ( mABs ) , which are directed to Factor H ( Figure 2C , columns 1 and 2 ) . Antibody binding was rather strong and exceeded the reactivity for the specific ligand Factor H ( Figure 2 , compare columns 5 and 1 ) . Sbi is an IgG binding protein , therefore Sbi-E and Sbi-I interaction with additional ligands cannot be studied by standard ELISA . Consequently we used the previously described combined ELISA and Western blot approach ( CEWA ) to study binding of human serum proteins to Sbi [36] . CEWA , which allows the identification of Sbi bound serum proteins by size and by reactivity with specific antisera , revealed that Factor H as well as both FHR-1α and FHR-1β bind to Sbi-E , comprising domains I–IV ( Figure 3A , lane 1 ) . Both Factor H and FHR-1α/FHR-1β bound to the deletion constructs Sbi-III/IV and with lower intensity to Sbi-IV ( Figure 3A , lanes 3 and 4 ) . The IgG binding domain Sbi-I did not bind the host complement regulators ( Figure 3A , lane 2 ) . As described previously Factor H bound to borrelial CRASP-1 and CRASP-5 and FHR-1α/FHR-1β to CRASP-5 ( Figure 3A , lanes 5 and 6 ) [36] . Having demonstrated binding of Factor H , FHR-1α and FHR-1β from human serum to Sbi via domains III and IV , we wanted to confirm this interaction with purified proteins . However purified Factor H did not bind to Sbi , but did bind to CRASP-1 and CRASP-5 ( Figure 3B ) . These results suggest that binding of Factor H to Sbi is mediated by an additional serum factor . In order to identify the additional serum factor that mediates binding of the host complement regulatory , we hypothesized that the central complement component C3 , which binds to the staphylococcal inhibitors Efb , Ehp and Ecb [29] , [30] , [32] might be such a mediator . Consequently binding of purified Factor H in the presence of the complement proteins C3b and C3d was analyzed by CEWA . When coincubated with either C3b or C3d Factor H bound to Sbi-E , Sbi-III/IV and Sbi-IV , but not to Sbi-I ( Figure 4A ) . This binding suggests that Sbi forms a tripartite complex with Factor H and C3 . Factor H binds to domains III and IV of Sbi , but not to the IgG binding domain I . The interaction to the non-IgG binding domains was confirmed by standard ELISA . Purified Factor H together with C3b or C3d bound to Sbi-III/IV ( Figure 4B , columns 1 ) . Binding of Factor H together with C3b or C3d to Sbi-IV was rather low . In this assay the binding of Factor H together with C3b/C3d to Sbi-III/IV was more pronounced as compared to borrelial CRASP-1 ( Figure 4B , compare columns 1 and 3 ) . In addition the C3 fragment responsible for complex formation with Factor H was assayed by CEWA and ELISA ( Figure 4D and 4E ) . The C3d-containing fragments C3 , C3b and C3d mediate complex formation of Factor H with Sbi , but not C3a , C3c nor to iC3b . This result reveals a novel mechanism of capturing host immune regulators , as Sbi binds Factor H in combination with a second host ligand , namley C3 . Having identified staphylococcal Sbi as a protein that binds the host complement components Factor H together with C3b or C3d , we analyzed C3 binding and tripartite complex formation in more detail . First binding of the various forms of C3 was analyzed to immobilized Sbi-E in real time using surface plasmon resonance . C3 showed a strong association and a relative fast dissociation ( Figure 5A: C3 ) . C3b , used at the same molar ratio showed slower association , but the Sbi∶C3b complex was rather stable ( Figure 5A: C3b ) . In addition C3d , the degradation product of C3 , showed a more pronounced association and also a slow rate of dissociation ( Figure 5A: C3d ) . This slow dissociation profile of both C3d and C3b suggests a high stability of the Sbi∶C3b and Sbi∶C3d complexes . Based on the apparent stronger association of C3d to Sbi-E , this interaction was analyzed in more detail . Sbi-E showed a dose-dependent binding to immobilized C3d when used at a range of 200 , 400 and 800 nM ( Figure 5B ) . The same dose-dependent binding was observed in a reverse setting with immobilized Sbi-E ( data not shown ) . These results demonstrate that C3 , C3b and C3d bind directly to the staphylococcal Sbi . In order to further analyze the interaction and complex formation Sbi-E representing domains I-IV were immobilized and complex formation was followed in real time . In this setting purified Factor H bound rather weakly to immobilized Sbi-E , while C3b binding was stronger ( Figure 5C ) . An increase was observed in the presence of both Factor H and C3b confirming formation of a tripartite complex ( Figure 5C ) . Formation of the tripartite complex was also analyzed with Factor H and C3d ( Figure 5D ) . In this setting binding of C3d was similar to that of C3b ( compare Figure 5D and Figure 5C ) and based on the RLUs the tripartite Sbi∶C3d∶Factor H complex showed more pronounced interaction . Binding and tripartite complex formation was analyzed to immobilized Sbi-constructs , i . e . Sbi-E , Sbi-I and Sbi-III/IV , to localize the C3 binding domains in Sbi . C3d did not bind to the IgG binding domain Sbi-I , but to Sbi-E and also to the construct Sbi-III/IV ( Figure 5E ) . C3d interaction to Sbi-E and Sbi-III/IV was comparable , thus confirming the role of domains III and IV for the contact . Based on the strong interaction of the Sbi∶C3d∶Factor H complex to Sbi-E and to Sbi-III/IV ( Figure 5E ) it is concluded that the C3/Factor H interaction region of Sbi is located exclusively in Sbi domains III and IV . To characterize the formation of Sbi∶C3d∶Factor H complex Sbi-E was coupled to an NTA-chip and complex formation was followed upon sequential addition of C3d and Factor H . Immobilization of Sbi-E was observed ( Figure 5F , phase I ) and upon addition of C3d formation of the Sbi∶C3d complex was followed in real time ( Figure 5F , phase II ) . Upon addition of Factor H , a further association was detected by the increase in the surface plasmon resonance signals . These results demonstrate that Factor H binds directly to the Sbi∶C3d complex and that Factor H does not compete with C3b for Sbi-E binding ( Figure 5F , phase III ) . The observed mass increase at the surface of the sensor chip during association of Factor H to the Sbi∶C3d complex was higher than that of Factor H to immobilized C3d ( data not shown ) . To further characterize this novel type of Factor H acquisition with C3 , we decided to identify the Factor H domains that are involved in this interaction . Factor H deletion constructs were immobilized and used in an ELISA experiment . In the presence of C3b , Sbi-E and Sbi-III/IV , but not to Sbi-I bound to immobilized Factor H SCRs 19–20 and SCRs 15–20 ( Figure 6 , columns 5 and 6 ) . In addition Sbi-I did not bind to any Factor H deletion construct . Thus the Sbi binding site was localized within the C-terminal surface binding region of Factor H , within SCRs 19–20 and is restricted to Sbi domains three and four . Factor H bound to pathogenic ligands maintains complement regulatory activity which relates to complement evasion [1] . It was therefore of importance to assay if Factor H fixed in this tripartite complex is functionally active and has complement regulatory activity . Factor H and C3b were incubated simultaneously with immobilized Sbi-E or the deletion fragments Sbi-I , Sbi-III/IV and Sbi-IV . Subsequently , Factor I was added and the mixture was incubated further . Following this treatment the proteins were eluted , separated by SDS-PAGE and after transfer to a membrane the C3b degradation products were identified by Western blotting . Factor H bound to Sbi-E in the presence of C3b displayed cofactor activity as indicated by the disappearance of the α' band and the appearance of the α'68- and α'43 bands ( Figure 7 , lane 1 ) . The same degradation profile of C3b was observed when Factor H was bound to Sbi-III/IV ( Figure 7 , lane 3 ) or to borrelial CRASP-1 ( Figure 7 , lane 5 ) . In the absence of Factor H no degradation of C3b was observed ( Figure 7 , lanes 7 and 8 ) . These results show that Factor H attached to Sbi in a tripartite complex maintains complement regulatory activity . Tripartite Sbi∶C3d∶Factor H complexes represent –to our knowledge- a novel mechanism for Factor H attachment . Factor H has a C3b/C3d binding region within the C-terminal recognition region , which also forms the major contact with Sbi . Therefore we asked whether the tripartite complex is based on a sandwich type interaction , by which Sbi binds first intact C3 , C3b or C3d and then Factor H . Alternatively a tripartite complex may be formed , in which Factor H directly contacts Sbi and C3 . Inhibition experiments were performed to test this hypothesis and to characterize this interaction in more detail . First Factor H and C3b were incubated in the presence of Factor H antiserum and Factor H binding to immobilized Sbi was studied . Preincubation of Factor H with the specific antiserum decreased binding to Sbi-E and blocked binding to the fragments Sbi-III/IV and Sbi-IV ( Figure 8A , lower panel ) . The weak binding of antiserum treated Factor H to intact Sbi-E and to Sbi-I is explained by binding of the Factor H∶IgG complex via the IgG binding site of Sbi located within domain I . First binding of Factor H to immobilized Sbi-III/IV in the presence of increasing amounts of C3d was studied . Already 1 ng of C3d , resulting in a molar Factor H∶C3d ratio of 25∶1 enhanced Factor H∶Sbi interaction ( Figure 8B ) . Secondly , Sbi-III/IV was immobilized , C3d was added and Sbi-III/IV bound C3d was blocked with increasing amounts of specific C3d antiserum . Subsequently , the binding of Factor H was analyzed . Factor H binding was not impaired with antisera titers up to 1∶1000 , and was reduced but not completely blocked at the highest titers ( 1∶100 and 1∶10 ) ( Figure 8C ) . This result shows direct binding of Factor H to Sbi and indicates that the presence of C3d , Sbi enhances formation of the tripartite complex . Similarly , Sbi-III/IV was immobilized and a saturating amount of C3d was bound . In order to block C3d binding sites on the Factor H protein , Factor H was preincubated with increasing concentrations of C3d prior to binding . The preincubated Factor H∶C3d complexes were added to the immobilized Sbi∶C3d complexes and after incubation Factor H binding was analyzed . Again tripartite Sbi∶C3d∶Factor H complexes were detected and complex formation was independent of the amount of C3d used for preincubation ( Figure 8D ) . This result is in agreement with a direct Factor H∶Sbi contact . In summary the inhibition and blocking experiments reveal that Factor H binds directly to Sbi and that binding is assisted by C3d . Staphylococcal Sbi forms a tripartite complex with host complement proteins Factor H and C3 . Consequently the complement inhibitory activity of Sbi was assayed in a standard hemolysis assay , using human serum and rabbit erythrocytes . In this assay Sbi-E and also Sbi-III/IV inhibited complement-mediated lyses of rabbit erythrocytes in a dose-dependent manner . Complete inhibition was observed at a concentration of 600 ng of either Sbi-E or Sbi-III/IV ( Figure 9A ) . In contrast , Sbi-I had no effect ( data nor shown ) indicating that C3b and Factor H binding is relevant for complement inhibitory activity . These results demonstrate that Sbi acts as a potent complement inhibitor . Hemolysis of rabbit erythrocytes in human serum was dose-dependent over a range from 5 to 15% and Sbi blocked hemolysis efficiently at all serum concentrations ( Figure 9B ) . To analyze the species range of Sbi-E the inhibitory effect of Sbi-E was tested using sera of different species . Complement mediated inhibition was observed in human , mouse and guinea pig sera , and no effect was detected in dog , goat and sheep sera ( Figure 9C ) . Thus Sbi acts in human serum but also displays a broader species range . Sbi is a potent complement inhibitor . Therefore we investigated the inhibitory effect of Sbi-E in all three complement pathways . Sbi-E clearly inhibited alternative pathway activity ( Figure 9D , column 2 and 3 ) . When all pathways were activated hemolysis was reduced in a dose-dependent manner , indicating that the alternative pathway , which was blocked by Sbi-E , is involved and that the classical and lectin pathway are unaffected ( Figure 9D , columns 7 and 8 ) . This effect was confirmed upon analyzing the impact on the classical and the lectin pathway . Sbi-E did not inhibit hemolysis of rabbit erythrocytes when complement was activated via the classical and the lectin pathway ( Figure 9D , columns 12 and 13 ) . As Sbi inhibits complement we asked whether Sbi protects S . aureus from phagocytosis mediated killing . S . aureus was incubated with complement active human serum in presence or absence of Sbi-E . Subsequently bacteria were harvested and incubated together with activated phagocytic THP-1 macrophages . At the indicated times points bacteria were recovered and the survival rate was quantitated . The presence of Sbi increased bacterial survival ( Figure 9E ) , thus indicating that the inhibitor Sbi protects bacteria from opsonisation and phagocytosis . These results demonstrate that Sbi-E efficiently inhibits the alternative , complement pathway and aids in bacterial resistance against complement mediated phagocytosis .
The Gram-positive bacterium S . aureus , similar to other human pathogens binds the complement regulators Factor H and FHR-1 from human serum . We identify the staphylococcal Sbi protein as a ligand for the two host complement regulators . Apparently Sbi binds Factor H by a new mechanism , as this human regulator binds to Sbi together with C3 , which likely results in formation of a tripartite Sbi∶C3∶Factor H complex . Arranged in this tripartite complex Factor H is functionally active and displays complement regulatory activity . Thus Sbi is a potent complement inhibitor , and inhibits the hemolytic activity of human and rodent serum on rabbit erythrocytes via the alternative pathway . Thus the multifunctional bacterial Sbi protein interferes with innate immune recognition , by acquisition of multiple host proteins in form of the complement components Factor H , C3 as well as IgG and β2-glycoprotein I . Purified Factor H bound to intact bacteria , but dependent on the assay showed weak or even no binding to Sbi ( compare Figure 1 , Figure 3B and Figure 5C , D ) . This difference in binding suggests that intact S . aureus bacteria express an additional Factor H binding surface protein . The identification of this protein is subject to further studies . The staphylococcal Sbi protein was identified as a ligand for Factor H . However Factor H binding is enhanced in the presence of an additional complement protein C3 . A tripartite Sbi∶C3b∶Factor H complex is formed ( Figure 4 and Figure 5 ) . The Factor H contact region for Sbi is located within SCRs 19–20 ( Figure 6 ) . Very similar contact domains were identified for other microbial Factor H binding proteins , e . g . CRASP-1 and CRASP-2 of B . burgdorferi , Tuf of P . aeruginosa and Gpm1 of C . albicans [12] , [14] , [16] , [37] . Inhibition experiments showed that polyclonal Factor H antiserum blocks Factor H binding to Sbi ( Figure 8A ) . In the proposed tripartite complex the regulatory region of Factor H ( i . e . SCRs 1–4 ) is freely accessible as demonstrated by the Factor I mediated cleavage of C3b ( Figure 7 ) . The staphylococcal Sbi protein is composed of four globular N-terminal domains connected to a tyrosine-rich C-terminal domain via a prolin-rich region ( Figure 2A ) [38] . A recombinant fragment with domains I–IV ( Sbi-E ) , as well as constructs Sbi-III/IV and Sbi-IV , but not Sbi-I bound Factor H in combination with C3b or C3d ( Figure 4 and Figure 5 ) , thus localizing the Factor H binding region to Sbi domains III and IV . As the Factor H/C3b binding sites in domain III and IV and the IgG binding sites in domain I and II are separated , the Sbi protein may simultaneously bind several host proteins . The binding properties of Sbi are unique , as –to our knowledge– Sbi is the first bacterial protein identified that forms such a tripartite complex with Factor H and C3 , C3b or C3d . It will be of interest to demonstrate whether other proteins of pathogen origin or virulence factors form similar tripartite complexes . The Sbi∶C3 interaction appears rather complex , as intact C3 and the two processed forms C3b and C3d display different binding profiles resulting in different stabilities ( Figure 5A ) . C3d complexed to Sbi showed the highest binding intensity of binding , and C3b or C3 a lower interaction . In addition the rate constants of C3d and Sbi-III/IV when assayed by surface plasmon resonance did not fit a 1∶1 langmuir model of interaction , but rather fit a bivalent analyte model ( Figure S2A and S2B , Figure S3 ) . The proposed bivalent analyte interaction together with the different binding profiles for the three C3 forms suggest that C3 undergoes a conformational change upon binding to Sbi and exposes additional binding epitopes , which affect Sbi interaction , or that these C3b/C3d binding region ( s ) is/are differently accessible to the bacterial Sbi protein . During complement activation C3 is cleaved , the C3 cleavage products bind to Sbi , increase Factor H binding and enhance the stability of the tripartite complex . Such a feed back regulation may increase the amount of inhibitory host regulators like Factor H at the site of infection and result in protection of the pathogen from complement attack and thus improves bacterial survival ( Figure 9E ) . This inhibition of the alternative pathway by Sbi indicates that Factor H bound to Sbi affects the C3 convertase . Within the tripartite complex Factor H displays complement regulatory activity ( Figure 7 ) and seems responsible for hemolytic activity ( Figure 9A and data not shown ) . This explains why Sbi domains III and IV display an inhibitory effect . Compared to the other staphylococcal complement regulators Efb and Ecb , Sbi does not interfere with the activity of the classical pathway and did not affect hemolysis mediated by the classical pathway ( Figure 9D ) [29] . Thus Sbi forms a tripartite complex with the two human complement proteins Factor H and C3 , revealing- to our knowledge- a novel mechanism for complement inhibition . The inhibitory activity of Sbi is not restricted to human complement as the protein also blocks complement of other species i . e . mouse and guinea pig . Demonstrating that Sbi is a staphylococcal virulence factor with a broader species range as compared to the human specific inhibitor SCIN , which acts specifically in the human system [29] , [34] . Sbi is a potent complement inhibitor , which interferes with the hemolytic activity of human serum . In hemolytic assays with rabbit erythrocytes Sbi used at 2 µg/ml ( = 0 . 3 µg ) exclusively blocked the alternative pathway whereas the classical and the lectin pathways were unaffected ( Figure 9D ) . However when used at higher concentrations of 1000 µg/ml in an ELISA approach the Sbi-III/IV fragment blocks all three activation pathways of human complement but the Sbi-IV fragment is a specific inhibitor for the alternative pathway ( Burman et al . JBC in press ) . This activity differs from that of SCIN and its homologues SCIN-B and SCIN-C , which affects all three complement pathways [29] , [34] . The staphylococcal Sbi protein is a multifunctional protein which binds the complement effectors Factor H , FHR-1 and C3 and also the processed forms C3b and C3d , as well as IgG and β2-glycoprotein I . Thus Sbi mediates innate and adaptive immune escape ( i ) by acquiring host complement inhibitors , which correlates with the activation state of complement , ( ii ) by inhibiting complement activation at the level of alternative pathway C3 convertase , ( iii ) by binding and inactivation of IgG to avoid recognition by phagocytes , and ( iv ) most likely by blocking C3dg binding to complement receptor 2 ( CR2 ) ( Burman et al . JBC in press ) .
S . aureus strain H591 ( MSSA clinical isolate , UK ) was grown at 37°C in tryptic soy broth ( TSB , Sigma ) . The strain was characterized for the presence of Sbi on DNA and protein level ( Figure S1A , S1B and S1C ) . Overnight cultures of S . aureus were diluted to OD600 = 0 . 2 in TSB and incubated for about 1 . 5 h at 37°C to OD600 = 1 . 0 ( approximately 1 . 2×109 cfu ) . Cells ( 2×109 cfu ) were harvested by centrifugation ( 6000 g , 8 min at room temperature ) , resuspended in veronal buffered saline ( GVB2+ , Sigma ) supplemented with 10 mM EDTA and incubated with either normal human serum ( NHS , diluted 1∶10 ) or Factor H ( 100 µg/ml , Aventis Behring ) for 1 h at 37°C with agitation . Subsequently , the cells were washed four times with EDTA-GVB2+ and bound proteins were eluted with SDS buffer ( 60 mM Tris-HCl , pH 6 . 8 , 2% SDS , 25% glycerine ) for 5 min at 98°C . Wash and elute fractions were separated by SDS-PAGE , transferred to a membrane and analyzed by Western blotting using a polyclonal goat Factor H antiserum ( Merck ) and horseradish peroxidase ( hrp ) coupled rabbit anti goat antiserum ( DAKO ) for detection . Recombinant fragments of the N-terminal region of Sbi ( adjacent to the poly-proline region ) were engineered , expressed and purified as described previously by ( Burman et al . JBC in press ) . The following Sbi constructs were used in this study: Sbi-E ( amino acids 28–266 ) containing IgG-binding domains I and II and C3 interacting domains III and IV; Sbi-I ( amino acids 42–94 ) ; Sbi-III-IV ( amino acids 150–266 ) and Sbi-IV ( amino acids 197–266 ) . The Factor H deletion mutants SCRs 1–7 , SCRs 8–11 , SCRs 11–15 , SCRs 15–18 and SCRs 19–20 were expressed in insect cells infected with recombinant baculovirus as described earlier [39] . Briefly , Spodoptera frugiperda cells ( Sf9 ) were grown at 28°C in monolayer cultures in protein-free expression medium for insect cells ( BioWhittaker ) . Adherent Sf9 cells were infected with recombinant virus using a multiplicity of infection of five . The culture supernatant was harvested after 9 days and recombinant Factor H constructs were purified by affinity chromatography using Ni-NTA-Agarose ( Qiagen ) . The complete extra cellular region , Sbi-E , and the extra cellular deletion mutants Sbi-I , Sbi-III/IV , Sbi-IV , BSA ( 2 µg/ml each ) and Factor H ( 1 µg/ml ) were immobilized onto a microtiter plate for 2 h at room temperature . Unspecific binding sites were blocked with 0 . 2% gelatine in DPBS ( Lonza ) over night at 4°C . After extensive washing with PBSI ( 3 . 3 mM NaH2PO4×H2O , 6 . 7 mM Na2HPO4 , 145 mM NaCl , pH 7 . 2 ) supplemented with 0 . 05% Tween 20 a polyclonal rabbit SCR1–4 antiserum and the two mABs B22 and C18 ( all specific for Factor H ) were added for 2 h at room temperature . Protein-antibody complexes were detected using secondary horseradish peroxidase ( HRP ) -coupled antiserum ( e . g . rabbit anti goat-hrp ( DAKO ) rabbit anti mouse-hrp ( DAKO ) ) Respectively . All antibodies and antisera were used at 1∶1000 dilutions . The reaction was developed with 1 , 2-phenylenediamine dihydrochloride ( OPD , Dako ) and the absorbency was measured at 490 nm . A combined ELISA and Western blot approach ( CEWA ) was used to assay Factor H binding to Sbi-E and the deletion constructs Sbi-I , Sbi-III/IV and Sbi-IV [36] . The proteins ( 10 µg/ml ) were immobilized onto a microtiter plate over night at 4°C . After blocking with 0 . 2% gelatine in DPBS ( Lonza ) for 6 h at 4°C , NHS ( diluted 1∶10 ) , Factor H ( 5 µg/ml ) , a combination of Factor H ( 5 µg/ml ) and C3b ( 10 µg/ml , Merck ) , or Factor H ( 5 µg/ml ) and C3d ( 2 , 6 µg/ml , Merck ) were added . For the C3-CEWA a mixture of Factor H ( 5 µg/ml ) and C3b or C3 , iC3b , C3d ( each 10 µg/ml , Merck ) , C3c , C3a ( each 10 µg/ml , Comptech ) were added . Samples were incubated over night at 4°C . After extensive washing protein complexes were removed with SDS buffer , separated by SDS-PAGE and analyzed by Western blotting using a polyclonal anti C3 antibody ( Calbiochem ) and anti-goat – hrp ( DAKO ) was used for the detection of C3 and its degradation products . For Factor H detection the mAB C18 , which is specific for SCR 20 of Factor H and rabbit anti mouse-hrp ( DAKO ) as secondary antibody was used . As positive controls the borrelial Factor H binding protein CRASP-1 , and also the Factor H/FHR1 binding protein CRASP-5 ( kindly provided by Dr . Peter Kraiczy ( University of Frankfurt a . M . ) and by Prof . Dr . Reinhard Wallich ( University of Heidelberg ) ) and as negative control BSA were used . The Factor H deletion constructs SCRs 1–7 , SCRs 8–11 , SCRs 11–15 , SCRs 15–18 , SCRs 19–20 and SCRs 15–20 were immobilized equimolar onto a microtiter plate over night at 4°C . After blocking with Blocking Buffer I ( AppliChem ) for 2 h at 37°C , a combination of C3b ( 5 µg/ml ) and the Sbi deletion mutants Sbi-E , Sbi-I and Sbi-III/IV used at equimolar amounts were added and incubated for 1 h at room temperature . After excessive washing bound Sbi deletion mutants were detected with polyclonal Sbi antiserum ( 1∶1000 ) and a secondary horseradish peroxidase-coupled anti rabbit antiserum ( 1∶1000 , DAKO ) . To analyze the complex formation , Sbi-III/IV ( 10 µg/ml ) was coated and a combination of Factor H ( 15 µg/ml ) and C3 , C3b , C3d , C3c ( Calbiochem ) or C3a ( 15 µg/ml; Comptech ) was added . The complex was detected by polyclonal goat anti Factor H ( 1∶1000 ) and rabbit anti goat-hrp ( 1∶1000 , Dako ) . The reaction was developed with 1 , 2-phenylenediamine dihydrochloride ( OPD , Dako ) and the absorbency was measured at 490 nm . Sbi-E and the extra cellular deletion mutants Sbi-I , Sbi-III/IV , Sbi-IV or CRASP-1 , and BSA ( 10 µg/ml ) were immobilized and unspecific binding sites were blocked as described . Factor H ( 5 µg/ml ) , polyclonal Factor H antiserum ( diluted 1∶100 ) and C3b ( 10 µg/ml ) were preincubated for 2 h at 4°C . Subsequently the mixture was added to the immobilized proteins and incubated over night at 4°C . After extensive washing protein complexes were removed from the well with SDS buffer , separated by SDS-PAGE and analyzed by Western blotting with the polyclonal rabbit SCR1–4 antiserum and swine anti rabbit-hrp ( DAKO ) as secondary antibody . For determining the regulatory activity of Sbi-bound Factor H , the regulator ( 3 µg/ml ) together with C3b ( 6 µg/ml ) or C3b ( 6 µg/ml ) alone were added to immobilized Sbi-E , Sbi-I , Sbi-III/IV , Sbi-IV , CRASP-1 , or BSA ( 10 µg/ml ) incubated over night at 4°C . After extensive washing Factor I ( 0 . 8 µg ) was added and the mixture was incubated for 30 min at 37°C . C3b conversion to inactive C3b ( iC3b ) was detected after separating the protein solution by SDS-PAGE with Western blot analysis using a polyclonal goat C3 antiserum ( 1∶1000 , Merck ) and rabbit anti goat-hrp ( DAKO ) as secondary antibody . Samples were separated by SDS-PAGE using 10% and 12% gels . After the transfer of the proteins onto nitrocellulose membranes by semi-dry blotting [40] , the membranes were blocked with 5% ( w/v ) dried milk in PBSI for 30 min at room temperature and incubated with the indicated primary antibodies over night at 4°C . Antibodies were diluted in 2 . 5% ( w/v ) dried milk in PBSI . The proteins were detected by ECL using appropriate secondary antisera that was coupled with horseradish peroxidase . Protein-protein interactions were analyzed by the surface plasmon resonance technique using a Biacore 3000 instrument ( Biacore AB ) as described [41] . Briefly , the staphylococcal proteins Sbi-E , Sbi-I , Sbi-III/IV or human C3d were coupled to the surface of the flow cells of the sensor chip via a standard amine-coupling procedure ( carboxylated dextran chip CM5 , Biacore AB ) until about 2000 resonance units were reached . A control cell was prepared under identical conditions that lacked a protein . Sbi-E , Factor H , C3 , C3b or C3d were diluted in DPBS ( Lonza ) , adjusted to equal molarities and injected with a flow rate of 5 µl/min at 25°C . Alternatively , Ni2+ and Sbi-E was loaded to a NTA-chip , and C3d followed by Factor H were injected at equimolar amounts . Each interaction was analyzed at least three times . In order to analyze the complement regulatory effect of Sbi , hemolytic assays were performed using rabbit erythrocytes ( rE , Rockland ) . Rabbit erythrocytes represent activator surfaces for human serum and lyse due to MAC formation . Thus the complement activity correlates directly with the erythrocyte lysis as monitored by the increase in absorbance . Following preincubation of NHS with Sbi-E or Sbi-III/IV for 30 min at 37°C , 5×106 rE were added ( 150 µl total volume ) and further incubated for 30 min at 37°C . After centrifugation ( 2 min , 5000 rpm ) the absorbency of the supernatant was measured at 414 nm . NHS , Sbi-E and Sbi-III/IV were used at the indicated concentrations . Samples were diluted in HEPES buffer ( 20 mM HEPES , 144 mM NaCl , 7 mM MgCl2 , 10 mM EGTA , 1% BSA , pH 7 . 4 ) . The effect of Sbi on different animal sera ( Innovative Research ) was assayed using 30% animal serum and 2 µg ( 13 µg/ml ) Sbi-E . In order to analyze and distinguish between the alternative and the classical/lectin pathway complement activation was pursued in different buffers . Alternative pathway activity was measured in EGTA-HEPES buffer . Activation of all three pathways was assayed in Ca2+-HEPES buffer ( 20 mM HEPES , 144 mM NaCl , 5 mM CaCl2 , 2 , 5 mM MgCl2 , pH 7 . 4 ) . The effect of the classical and the lectin pathway was assayed in Factor B deficient serum ( Complement Technology Inc . ) and the Ca2+-HEPES buffer . All three approaches ( AP , AP+CP/LP and CP/LP ) were analyzed in the presence of none , 0 . 3 µg ( 2 µg/ml ) and 1 . 0 µg ( 6 , 7 µg/ml ) Sbi-E . Bacteria S . aureus strain H591 ( 6×104 ) were incubated in 40% NHS supplemented with HEPES EGTA in presence or absence of Sbi-E for 15 min at 37°C . Samples were added to 8×105 PMA primed THP-1 macrophages in antibiotic free RPMI-1640 resulting in a final Sbi-E concentration of 2 µg/ml . THP-1 cells incubated without S . aureus were used as negative control . After shaking 20 µl sample were plated hourly . Plates were incubated overnight and colonies were counted . National Centre for Biotechnology Information ( www . ncbi . nlm . nih . gov ) : Homo sapiens complement factor H ( CFH ) , gi|62739185|ref|NM_000186 . 2|[62739185]; Homo sapiens complement factor H-related 1 ( CFHR1 ) , NM_002113 . 2 GI:118442838; Homo sapiens complement component 3 ( C3 ) , NM_000064 . 2 GI:115298677; immunoglobulin G-binding protein Sbi [Staphylococcus aureus subsp . aureus str . Newman] , YP_001333351 . 1 GI:151222529 . | Staphylococcus aureus is a Gram-positive bacterium that can live as a commensal but can also cause severe life threatening infections in humans . Upon infection the bacterium is attacked by the host immune system , and in particular by the complement system which forms the immediate , first defence line of innate immunity . In order to survive , S . aureus has developed multiple evasion strategies and uses several virulence factors to evade and inactivate the host complement attack . Here we show that this pathogen binds the host complement regulators Factor H from human serum with the secreted and surface exposed Sbi protein , by a—to our knowledge—new type of interaction . Factor H binds to Sbi in combination with another host complement protein C3 , C3b or C3d , and forms tripartite Sbi∶C3∶Factor H complexes . As part of this tripartite complex , Factor H is functionally active and inhibits further complement activation . Sbi , by recruiting Factor H and C3b , acts as a potent complement inhibitor , and inhibits alternative pathway-mediated lyses of rabbit erythrocytes by human serum and sera of different species . Thus , Sbi is a multifunctional bacterial protein , which binds host complement components Factor H and C3 as well as IgG and β2-glycoprotein I and interferes with innate immune recognition . | [
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] | 2008 | The Staphylococcus aureus Protein Sbi Acts as a Complement Inhibitor and Forms a Tripartite Complex with Host Complement Factor H and C3b |
Kaposi’s sarcoma-associated herpesvirus ( KSHV ) is an oncogenic herpesvirus associated with various AIDS-related malignancies . Like other herpesviruses , multiple processes required for KSHV lytic replication , including viral transcription , viral DNA synthesis and capsid assembly occur in virus-induced intranuclear structures , termed replication and transcription compartments ( RTCs ) . Here we utilised a novel methodology , combining subcellular fractionation and quantitative proteomics , to identify cellular proteins which are recruited to KSHV-induced RTCs and thus play a key role in KSHV lytic replication . We show that several isoforms of the HSP70 chaperone family , Hsc70 and iHsp70 , are redistributed from the cytoplasm into the nucleus coinciding with the initial formation of KSHV-induced RTCs . We demonstrate that nuclear chaperone foci are dynamic , initially forming adjacent to newly formed KSHV RTCs , however during later time points the chaperones move within KSHV RTCs and completely co-localise with actively replicating viral DNA . The functional significance of Hsp70 isoforms recruitment into KSHV RTCs was also examined using the specific Hsp70 isoform small molecule inhibitor , VER-155008 . Intriguingly , results highlight an essential role of Hsp70 isoforms in the KSHV replication cycle independent of protein stability and maturation . Notably , inhibition of Hsp70 isoforms precluded KSHV RTC formation and RNA polymerase II ( RNAPII ) relocalisation to the viral genome leading to the abolishment of global KSHV transcription and subsequent viral protein synthesis and DNA replication . These new findings have revealed novel mechanisms that regulate KSHV lytic replication and highlight the potential of HSP70 inhibitors as novel antiviral agents .
Molecular chaperones represent a large group of proteins that are essential for maintaining cellular homeostasis and survival . As such , the roles of these proteins are numerous; facilitating correct protein folding or unfolding , assembly or disassembly of multimeric protein complexes , participating in translocation of proteins and vesicles into organelles , stabilising a wide range of signalling molecules and preventing aggregation of non-native proteins ( reviewed in [1 , 2] ) . Heat shock proteins ( HSP ) are classified according to their molecular weight into several families: HSP40 , HSP60 , HSP70 , HSP90 , HSP100 , HSP110 and the small HSP ( less than 34 kDa ) [3] . The functional importance of the HSP70 and HSP90 families of molecular chaperones is exemplified by their emerging implications in a variety of diseases , including cancer [4 , 5] , neurodegeneration [6] or viral infection [7 , 8] . As such they have gained significant interest recently as potential drug targets . Eukaryotes have multiple genes encoding for chaperones of the HSP70 family , which are amongst the most conserved proteins in evolution [9–11] . The major Hsp70 isoforms are the constitutively expressed Hsc70 , the stress-inducible Hsp70 ( iHsp70 ) , the endoplasmic reticulum resident ( Grp78 ) and the mitochondrial form ( Grp75 ) . All Hsp70 isoforms have an N-terminal domain which harbours a highly conserved ATPase and a C-terminal substrate binding domain [1] . Hsp90 isoforms which comprise the inducible and constitutively-expressed isoforms ( Hsp90α and Hsp90β respectively ) , the ER resident ( Grp74 ) and the mitochondrial form ( TRAP1 ) , also possess a N-terminal ATP binding domain , although this has no similarity to the ATP-binding domain found in the chaperones of the HSP70 family [5] . The presence of ATPase pockets in both families of chaperones makes these proteins desirable targets for small molecule inhibitors [12 , 13] . The therapeutic potential of these compounds is especially evident for several HSP90 inhibitors , having already reached phase II and III clinical trials [14 , 15] . Targeting of Hsp70 isoforms has been more challenging [12] , but recently specific inhibitors have also undergone clinical trials [16 , 17] . Importantly , the development of highly specific inhibitors for Hsp70 isoforms may have potential for the treatment of a diverse group of viruses as the functional importance of Hsp70 isoforms in the life cycle of numerous viruses has been highlighted over the past few years [8] . Distinct Hsp70 isoforms are usurped to aid in many stages of viral replication as varied as viral entry , uncoating , transcription , envelope protein maturation , morphogenesis or DNA replication [8] . Therefore , the importance of these chaperones in the life cycle of such a wide range of viruses suggests the potential of these proteins as targets for broad-spectrum antivirals . Kaposi’s sarcoma-associated herpesvirus ( KSHV ) is the causative agent of several AIDS-associated malignancies , including Kaposi’s sarcoma ( KS ) , a highly vascular tumour of endothelial lymphatic origin . Similar to other herpesviruses , KSHV exists in two distinct life cycles , latent persistence or lytic replication phases . However , unlike other human oncogenic viruses where the latent cycle is predominantly responsible for tumorigenesis , both the latent and lytic replication phases are essential for KSHV tumorigenicity in KS [18 , 19] . During latency , which is established in B cells and in the tumour setting , viral gene expression is highly restricted , only involving expression of the latency-associated nuclear antigen ( LANA ) , the viral FLICE inhibitory protein , viral cyclin , kaposins and several virally-encoded miRNAs [20] . However , upon reactivation , the virus enters the lytic reactivation cycle leading to expression of more than 80 protein-coding sequences and replication of viral genomes [21] in a highly orchestrated sequential manner . Infectious virions can then spread to endothelial cells where tumours develop . Moreover in KS lesions , where most infected cells harbour the virus in a latent state , a small proportion of cells undergo lytic replication which leads to secretion of lytically-expressed angiogenic , inflammatory and proliferative factors that act in a paracrine manner on latently-infected cells enhancing tumourigenesis [20] . Furthermore , lytic replication enhances genomic instability [22] and also sustains the population of latently-infected cells that would otherwise be reduced due to the poor persistence of KSHV episomes during cell division [23] . Therefore , inhibiting KSHV lytic replication may lead to a novel therapeutic intervention for the treatment of KSHV-associated diseases . KSHV initiates lytic replication upon transcription of the ORF50/RTA gene which encodes the conserved lytic master switch RTA protein . RTA is then able to trigger the entire lytic gene expression cascade in KSHV and other γ-2 herpesviruses [24 , 25] . KSHV transcription , DNA replication and packaging , and capsid assembly all occur in virus-induced nuclear structures , termed replication and transcription compartments ( RTCs ) [26] . Early in herpesvirus infection , viral transcription of early genes and viral DNA replication takes place in small RTCs [27] , that generally concentrate at the nuclear periphery [28–30] . As infection progresses , the nuclear architecture undergoes a striking re-organization to facilitate viral replication . Small RTCs coalesce into single large globular or kidney-shaped structures that ultimately fill most of the nuclear space compressing and marginalizing the cellular chromatin to the nuclear periphery [28 , 29] . These large RTCs support late viral gene expression , viral DNA synthesis and capsid assembly [27] . Previous efforts to identify the protein composition , both viral and cellular , of herpesvirus RTCs have been carried out using immunoprecipitation-based assays , identifying proteins that associate either with the KSHV lytic origin of DNA replication ( ori-Lyt ) [31] or with known HSV-1 viral proteins which accumulate in RTCs [32] . However , these immunoprecipitation-based approaches restrict the number of proteins identified and are not quantitative , thus a more quantifiable and high-throughput method is highly desirable . In recent years , the use of shotgun proteomics has proved an invaluable tool to investigate global analysis of protein composition , allowing the elucidation of new aspects of viral biology [33] . An enhanced approach to this methodology is the combined use of subcellular fractionation with shotgun proteomics [34] . This allows the identification of cellular proteins that can easily be masked by more abundant proteins in studies which interrogate the global proteome using whole cell lysates or large cellular regions ( e . g . nuclear or cytoplasmic ) . Therefore , we have utilised a novel quantitative proteomic approach to identify cellular proteins which are either recruited to or present at significant levels in KSHV-induced RTCs and thus play a key role during KSHV lytic replication . Herein , we have utilised subcellular fractionation coupled to stable isotope labelling by amino acids in cell culture ( SILAC ) -based quantitative proteomics followed by liquid chromatography ( LC ) -tandem mass spectrometry ( MS/MS ) . We uniquely isolated the nuclear envelope ( NE ) region from unreactivated ( harbouring latent virus ) and KSHV-reactivated ( harbouring lytic virus ) cells using a recently developed method [35] and notably demonstrate the enrichment of purified RTCs . A rationale of this approach is that the NE cannot be purified completely due to its multiple subcellular connections . The outer nuclear membrane is continuous with the endoplasmic reticulum and interacts with the cytoskeleton [36 , 37] while the inner nuclear membrane binds to host chromatin [38–40] . Thus , we took advantage of its incomplete purity so that we could isolate not only the NE and embedded nuclear pore complexes , but also components found in the NE neighbourhood , such as RTCs . Utilising this novel approach we demonstrate that cellular chaperones from the HSP70 family ( Hsc70 and iHsp70 ) are significantly increased in the NE-associated RTCs of reactivated cells . Functional dissection further demonstrates that these chaperones were specifically recruited to the periphery of incipient RTCs coinciding in time with their formation . When actively replicated viral DNA was synthesised the chaperones were recruited within RTCs . Strikingly , inhibition of Hsp70 isoforms precluded RTC formation , curtailed chaperone redistribution within RTCs and RNAPII recruitment to viral promoters . Importantly , abrogation of lytic replication occurred without affecting cell viability , suggesting that the cellular housekeeping functions carried out by these chaperones were not compromised . As such , HSP70 inhibitors may provide a novel therapeutic approach for the treatment of KSHV-associated malignancies , in particular it would be interesting to determine the efficacy of combining the potential of inhibiting lytic replication using HSP70 inhibitors with the previous reported effect of HSP90 inhibitors to eradicate latent KSHV reservoirs [41] .
To investigate differential proteome changes which occur during KSHV lytic replication in NE-associated RTCs , we utilised the HEK-293T cell line containing a latent recombinant KSHV virus ( rKSHV . 219 ) [42] . This cell line can be reactivated into a full lytic replication cycle via chemical induction . Unreactivated cells were grown in isotopically labelled media ( R6K4 ) , while cells to be reactivated were grown in label-free media ( R0K0 ) . After isotopic labelling was complete , cells were reactivated for 48 h and nuclear envelopes ( NEs ) were then successfully purified using a recently described method [35] , with minor modifications . Western blot analysis of the NE preparations demonstrated an enrichment of nucleoporins ( Nups ) , lamins and histones and a loss of cytoplasmic ( GAPDH ) and nucleolar ( B-23 , C-23 ) proteins compared with whole cell ( WC ) lysates ( Fig 1 ) . The essential KSHV mRNA processing protein , ORF57 [43] , and viral RTA served as markers for lytic viral replication and RTC enrichment , as both of these proteins are known to be recruited to KSHV RTCs [31 , 44] . The monoclonal antibody ( Mab414 ) , which recognises the phenylalanine-glycine ( FG ) -repeat motif present in numerous Nups , and the polyclonal antibodies against Nup160 and lamin B1 were used to assess enrichment of the NE region . NE preparations showed a higher number of Nups ( closed arrows ) than their respective WC preparations; although some Nups were lost following 0 . 3 M salt wash ( open arrow ) . Following LC-MS/MS analysis and using a minimum of three unique peptides assigned to a single protein , most proteins ( 1072 ) remained unchanged in their abundance irrespectively of KSHV lytic infection and only five proteins had a significant reduction ( ratio cut-off <0 . 5 ) in NEs of reactivated cells . In contrast , 216 proteins showed a significant increase ( ratio cut-off >1 . 9 ) during lytic replication . Importantly , multiple cellular proteins that are known or expected to localize within herpesvirus RTCs; such as those associated with KSHV ori-Lyt , the HCMV transactivator IE2-p86 protein or the herpes simplex virus-1 ( HSV-1 ) ICP8 protein were found significantly increased in the NE regions of reactivated cells using the less stringent ratio cut-off of 1 . 5 ( S1 Table ) . Some of these cellular proteins included CSNK2A1 [45] , BLM [32] , topoisomerases I and II [31 , 46 , 47] and DEAD box helicases DDX5 [32] and DDX17 [45] . Thus , LC-MS/MS results confirmed the correct isolation of the NE region and accompanying RTCs . Importantly , many of the 216 identified proteins most likely represent novel cellular proteins hijacked by KSHV , not only due to the subcellular fractionation carried out but also to the uncommon use of urea for protein extraction before LC-MS/MS . All proteins identified by LC-MS/MS can be seen on S1 Dataset . Bioinformatical analysis revealed several upregulated pathways ( ratio cut-off >1 . 9 ) in reactivated cells ( S2 Table ) . Of particular interest was an upregulated pathway which related to protein folding . This included several Hsp70 isoforms and their associated co-chaperones from the HSP40 ( DNAJ ) family ( Table 1 ) . Notably , the constitutively expressed chaperone Hsc70 presented a 4 . 1-fold increase with 41 unique peptides assigned . This protein had the highest fold increase associated with the most unique peptide number of all the proteins identified by LC-MS/MS . This could be due to increased Hsc70 expression or to the redistribution of Hsc70 from the cytoplasm into the NE region during KSHV lytic replication . Therefore , due to the vital importance of Hsp70 isoforms in the replication cycle of a wide range of viral families , we focussed our studies herein on the roles of the three main Hsp70 isoforms ( Hsc70 , iHsp70 and Grp78 ) during KSHV lytic replication . To verify the enrichment of Hsc70 in the NE-associated RTCs of reactivated cells detected by our quantitative proteomic approach , indirect immunofluorescence was used to label endogenous Hsc70 protein in TREx BCBL1-RTA cells , a KSHV latently infected B-lymphocyte cell line containing a Myc-tagged version of viral RTA under the control of a doxycycline-inducible promoter [48] . Hsc70 protein was equally distributed between the cytoplasm and nucleus of unreactivated cells in a fine punctuate pattern ( Fig 2Ai ) . Similar Hsc70 localization was seen during early lytic replication ( 12 h reactivation ) , when RTA protein was diffuse in the nucleus , prior to RTC formation ( Fig 2Aii ) . In contrast , at later reactivation time points ( 20 h ) , in which RTA was organised into small viral RTCs peripherally located in the nucleus , numerous nuclear Hsc70 foci that were predominantly adjacent to RTCs were observed ( Fig 2Aiii ) . During late reactivation time points ( 26 h ) , cellular chromatin was marginalised to the nuclear periphery ( Fig 2Aiv , nucleus highlighted in yellow ) and larger Hsc70 foci avidly accumulated within these fully-developed RTCs ( Fig 2Aiv ) . Reduced levels of cytoplasmic Hsc70 were also observed at this time point ( Fig 2Aiv arrows ) , suggesting that Hsc70 is redistributed from the cytoplasm to the nucleus during KSHV lytic replication . This is further supported by the fact that fractionation of TREx BCBL1-RTA cells into nuclear ( N ) and cytoplasmic ( C ) fractions displayed an enrichment of Hsc70 in the nuclei of reactivated cells which occurred without a noticeable increase in Hsc70 protein levels in whole cell ( WC ) lysates ( Fig 2B ) . Due to the observed redistribution of Hsc70 to KSHV RTCs , further co-localization studies between Hsc70 and the sites of viral DNA replication were performed in TREx BCBL1-RTA cells . Here , cells were triple-labelled with Click-iT EdU Alexa Fluor 647 and antibodies specific for RTA and Hsc70 . In unreactivated cells , newly synthesized cellular DNA during mid-S-phase ( EdU incorporated ) occurred mainly at the nuclear periphery as previously observed in other cell types [49 , 50] ( Fig 2Ci ) . During early reactivation , Hsc70 was adjacent to RTA which was present in small viral RTCs containing actively replicating viral DNA ( Fig 2Cii arrow ) . At this stage , a proportion of Hsc70 also co-localised with RTA ( Fig 2Cii’ ) . During late reactivation , when cellular chromatin was marginalised , much larger RTCs were visible and newly synthesized cellular DNA was not apparent , here Hsc70 completely co-localised with newly synthesized viral DNA and RTA ( Fig 2Ciii and 2Ciii’ ) . The location of the other two main Hsp70 isoforms ( iHsp70 and Grp78 ) during KSHV lytic replication was also investigated by indirect immunofluorescence microscopy . iHsp70 was cytoplasmic in unreactivated TREx BCBL1-RTA cells ( S1Ai Fig ) , in contrast , an increase in nuclear iHsp70 labelling was observed in reactivated cells , which displayed similar chaperone foci as those seen during early reactivation for Hsc70 ( S1Aii Fig ) . Occasionally , cells displayed RTCs completely filled by iHsp70 ( S1Aiii and S1Aiv Fig , asterisks ) . Large iHsp70 foci positioned adjacent to RTCs were also seen in reactivated cells at later time points ( S1Aiv Fig arrows ) . Co-localisation of iHsp70 with actively replicating viral DNA was also observed during late reactivation ( S1B Fig ) . Hsc70 and iHsp70 nuclear foci appeared at the same time as KSHV RTCs were assembled , suggesting that these chaperones could be involved in RTC assembly . Additionally , complete co-localization of Hsc70 and iHsp70 with viral DNA indicated that these chaperones could also participate in viral DNA replication and/or capsid assembly . In contrast , the endoplasmic reticulum ( ER ) Hsp70 isoform , Grp78 , was not redistributed in reactivated TREx BCBL1-RTA cells ( S2 Fig ) , consistent with its ER retention signal [51] . Nevertheless , reactivated cells seemed to accumulate larger amounts of Grp78 in the ER . To confirm these results , immunoflourescence studies were also performed using HEK-293T rKSHV . 219 cells , in which the presence of the recombinant virus is tracked by expression of the green fluorescent protein ( GFP ) from the EF-1alpha promoter and lytic reactivation levels are monitored by expression of the red fluorescent protein ( RFP ) from the KSHV lytic non-coding polyadenylated nuclear ( PAN ) RNA promoter . Unreactivated cells displayed cytoplasmic iHsp70 and Hsc70 labelling , whereas ~ 40% of reactivated cells ( 24 h reactivation ) revealed nuclear iHsp70 and Hsc70 accumulations that appeared to assemble within small RTCs ( S3A Fig arrows and S3B Fig arrows respectively ) . The incomplete redistribution of iHsp70 and Hsc70 foci into RTCs was likely due to a more asynchronous progression through the lytic cycle in induced cells by TPA and sodium n-butyrate than in doxycycline-induced TREx BCBL1-RTA cells . Similarly to TREx BCBL1-RTA cells , Grp78 was not redistributed in HEK-293T rKSHV . 219 cells , although larger amounts appeared to accumulate in the ER of reactivated cells ( S3C Fig ) , in agreement with the significantly increased amounts of Grp78 detected in the NE region of these cells ( Table 1 ) . These results clearly demonstrate that KSHV specifically redistributes the molecular chaperones , Hsc70 and iHsp70 , from the cytoplasm to the nucleus , in contrast to Grp78 , which coincides with the initial formation of KSHV RTCs . Members of the HSP70 chaperone family possess an N-terminal nucleotide binding domain with ATPase activity which is essential for their function . To examine the implications of Hsc70 and iHsp70 redistribution into KSHV RTCs , a small molecule inhibitor , VER-155008 , ( a dibenzyl-8-aminoadenosine analog ) was utilised . This is the only inhibitor that has been demonstrated to specifically target the highly homologous ATPase pocket present in the three main human Hsp70 isoforms [12 , 13 , 52 , 53] , which is highly divergent structurally from the ATPase pocket found in chaperones of the HSP90 family [12 , 54] . As such , VER-155008 functions as an ATP mimetic that specifically inhibits the ATPase activity of members of the HSP70 family . Initially , cytotoxicity of this compound was assessed in unreactivated TREx BCBL1-RTA cells . Following 24 h inhibitor exposure , using a non-radioactive MTS assay , which quantitatively assesses cell proliferation , a drastic reduction in cell metabolic activity was seen for inhibitor concentrations higher than 6 μM ( S4 Fig ) , thus concentrations ranging from 1 to 4 μM were used for further cytotoxicity characterization ( Fig 3Ai ) . The inhibitor triggered apoptosis in a dose-dependent manner as demonstrated by the caspase 3-mediated cleavage of full length poly [ADP-ribose] polymerase ( FL-PARP1 ) protein into cleaved PARP1 ( CL-PARP1 ) ( Fig 3Aii ) . Small amounts of CL-PARP1 were seen at 1 μM and 2 μM with a significant increase of this form after 3 μM . These results were confirmed with ApoTox-Glo Triplex Assay by quantitatively measuring viability , cytotoxicity and activation of effector caspases-3/7 in the same sample well after 24 h inhibitor treatment . A dose-dependent decrease in viability was evident from 2 μM to 50 μM while cytotoxicity and activation of caspases-3/7 were only considerably increased at concentrations higher than 3 μM ( Fig 3B ) . Next , TREx BCBL1-RTA cells were reactivated for 24 h in the presence of drug vehicle DMSO ( 0 . 1% ) or a range of increasing inhibitor concentrations . Cells treated with the inhibitor at non-cytotoxic concentrations ( 1 to 2 . 5 μM ) revealed a drastic reduction in the levels of early ORF57 and late minor capsid ( mCapsid ) proteins . A moderate reduction in the immediate-early RTA protein was also seen ( Fig 3C ) . Of note , when detecting the fusion protein RTA-Myc , which expression is not from the KSHV genome , with anti-Myc antibody , the decrease in RTA-Myc was not as dramatic as that seen for viral RTA , suggesting that the decrease in viral proteins was not due to a general cytotoxic effect of the inhibitor on the cells , and that viral , but not cellular proteins were specifically affected . As an additional cellular control , protein levels of the large subunit of RNAPII , which has a half-life of 12–16 h [55] , was assessed with antibodies specific for the different phosphorylated forms of RNAPII . Protein levels of these forms were not significantly changed in the presence of the inhibitor , nor were those of Hsc70 or Hsp90 proteins . Importantly , in the presence of VER-155008 , iHsp70 levels were not upregulated . iHsp70 upregulation is a universal hallmark of Hsp90 inhibition not only in vitro [56] but also in clinical trials [57] , pointing to selectivity for Hsp70 isoforms by VER-155008 . Hsp90 and Hsp70 chaperone machineries have been reported to be crucial for the stability and/or maturation of multiple viral proteins [7 , 41 , 58–62] . Therefore to ascertain whether Hsp70 isoforms could stabilise the essential KSHV lytic proteins RTA and ORF57 , TREx BCBL1-RTA cells were reactivated for 24 h to allow sufficient viral protein expression followed by addition of DMSO control or VER-155008 in conjunction with cycloheximide ( CHX ) at 50 μg/ml to block de novo protein synthesis . Protein lysates were then collected at different times after addition of CHX . The half-life of RTA and ORF57 proteins from inhibitor-treated cells were not altered compared with DMSO-treated cells ( Fig 3D ) . These results indicate that the observed decrease in viral protein synthesis was prior to translation and that neither viral RTA nor ORF57 protein were client proteins of the Hsp70 isoforms . As such , this highlights a potentially novel role of Hsp70 isoforms in the KSHV replication cycle independent of viral protein stability and maturation . To further corroborate these results , experiments were also repeated in HEK-293T rKSHV . 219 cells . Again , cell metabolic activity , PARP1 cleavage , viability , cytotoxicity and activation of caspases-3/7 in unreactivated cells were all assessed at a range of increasing inhibitor concentrations ( Fig 4A and 4B ) . On this occasion , the inhibitor did not trigger apoptosis ( Fig 4Aii and 4B ) but it caused a pronounced cell cycle arrest at 24 h exposure at concentrations of ≥ 20 μM demonstrated by a reduced number of metabolically active cells that exhibited no increased cytotoxicity [63] ( Fig 4B ) . It is known that the apoptotic potential of VER-155008 is cell line-dependent and that VER-155008 can cause cell cycle arrest in human colon , breast and lung tumour cell lines [54 , 64] . HEK-293T rKSHV . 219 cells were also reactivated for 24 h in the presence of drug vehicle DMSO ( 0 . 1% ) or increasing inhibitor concentrations . Endogenous RTA , ORF57 and mCapsid protein levels were moderately reduced in cells treated at an inhibitor concentration of 10 μM and severely reduced at 40 μM while cellular proteins remain unaffected ( Fig 4C ) . These were relatively high inhibitor concentrations compared with TREx BCBL1-RTA cells; nonetheless a concentration of 40 μM has been shown before to be necessary for inhibition of Hsp70 isoforms in human carcinoma cell lines [54] . As previously seen in TREx BCBL1-RTA cells , when blocking de novo protein synthesis with CHX at 100 μg/ml in HEK-293T rKSHV . 219 cells , the half-life of RTA and ORF57 proteins were not reduced even in the presence of VER-155008 at 50 μM ( Fig 4D ) . This supports the findings seen in TREx BCBL1-RTA cells , suggesting that the decrease in viral protein production was due to a pre-translation event . As the block in KSHV protein synthesis occurred pre-translationally , viral gene expression was quantified in the absence or presence of VER-155008 . TREx BCBL1-RTA cells were reactivated for 24 h and two-step quantitative reverse transcription PCR ( qRT-PCR ) was carried out to quantify a range of viral transcripts . A significant decrease in early ( PAN , ORF57 , K12 and vGPCR ) , late ( gL and gB ) viral transcripts and ori-Lyt transcripts was observed in a dose-dependent manner , with all transcripts with the exception of vGPCR being significantly reduced at an inhibitor concentration of 1 μM ( Fig 5A ) . To determine whether cellular transcription was negatively affected in the presence of VER-155008 , firstly the stability of GAPDH transcript was determined in mRNA decay assays using the transcriptional inhibitor actinomycin D ( AcD ) ( 2 . 5 μg/ml ) in TREx BCBL1-RTA cells . After 6 h of AcD treatment , the amount of GAPDH mRNA was reduced by half ( Fig 5B ) , indicating a short stability of GAPDH mRNA in this cell line . We then plotted the raw cycle threshold ( CT ) for GAPDH transcript from the same samples in which viral transcripts had been quantified after 24 h of VER-155008 treatment . As the same amount of total RNA was converted into cDNA for all samples , if cellular transcription was not compromised a very similar CT is expected for all samples . Indeed , samples treated with up to 3 μM VER-155008 were all within 0 . 4 CT from the 12 . 7 CT of DMSO-treated samples . Only after concentrations higher than 3 μM GAPDH mRNA levels were significantly reduced compared to DMSO-treated samples as shown by a significantly higher CT value ( Fig 5C ) . This is consistent with the cytotoxicity profile of VER-155008 in TREx BCBL1-RTA cells ( Fig 3A and 3B ) and the clear decrease in RTA-myc protein ( which expression is not from the KSHV genome ) at inhibitor concentrations higher than 3 μM ( Fig 3C ) . Taken together , these results suggest that cellular transcription was compromised at concentrations of VER-155008 higher than 3 μM while at concentrations lower than 3 μM transcription was occurring normally . Interestingly , transcription of viral genes which also require host RNAPII for their expression was negatively affected even at VER-155008 concentrations lower than 3 μM . Next , we assessed whether the inhibitor also caused a reduction in viral DNA replication . TREx BCBL1-RTA cells were reactivated for 72 h , total DNA was isolated and real-time qPCR was performed using primers specific for ORF57 . While DMSO-treated cells reached ~ 9-fold increase in viral DNA load , inhibitor concentrations of 2 μM or higher resulted in a significant reduction ( > 30% ) in viral DNA ( Fig 5D ) . Moreover , the production of infectious KSHV virions in TREx BCBL1-RTA cells was evaluated in the presence of VER-155008 at 2 . 5 μM or vehicle drug DMSO . For this , cells were reactivated and treated for 72 h , culture medium was centrifuged and incubated for 24 h with HEK-293T cells . Total RNA was then isolated and qRT-PCR carried out . A significant reduction ( ~ 80% ) in the release of infectious viral progeny was observed in inhibitor-treated cells ( Fig 5E ) . Viral transcripts were also quantified at 24 h reactivation in HEK-293T rKSHV . 219 cells in the absence or presence of VER-155008 . At non-cytotoxic concentrations of 10 μM there was a drastic decrease for all early viral transcripts and ori-Lyt transcripts ( Fig 6A ) . It is intriguing that ORF57 mRNA levels did not show a clear dose-response with the inhibitor as seen for ORF57 mRNA in TREx BCBL1-RTA cells; however the levels were decreased compared with DMSO-control cells . This is the only transcript of all the viral transcripts tested in both cell lines that did not show a dose-response . However , Western blotting did reveal a complete reduction of ORF57 protein in cells treated with > 40 μM VER-155008 ( Fig 4C ) . This suggests that Hsp70 isoforms may also play a role in the folding of ORF57 protein . In fact , Hsc70 has been previously reported to associate with at least 15–20% of newly synthesized proteins during their biogenesis [65] , thus , a role for Hsp70 isoforms in folding viral proteins cannot be ruled out . In order to evaluate cellular transcription activity in the presence of VER-155008 , we first determined GAPDH transcript stability in mRNA decay assays using AcD ( 10 μg/ml ) in HEK-293T rKSHV . 219 cells . In contrast to TREx BCBL1-RTA cells , GAPDH transcripts were very stable , with no significant reduction in their levels after 10 h of AcD treatment ( Fig 6B ) . The half-lives of two cellular transcripts , SRAG ( a cellular mRNA export adapter ) and histone H2A ( H2A . 1 ) were also determined in HEK-293T rKSHV . 219 cells . SRAG transcripts were reduced to 50% following 4 h AcD treatment ( Fig 6C ) , while the H2A . 1 mRNA was very unstable with nearly 100% reduction after 2 h AcD treatment ( Fig 6D ) . We then plotted the raw CT values for GAPDH transcript from samples in which viral transcripts had been quantified after 24 h of VER-155008 treatment; these did not significantly change in the presence of VER-155008 ( Fig 6E ) . Next , the unstable SRAG and H2A . 1 mRNAs were measured in the same samples in which viral transcripts had been quantified after 24 h of VER-155008 treatment . In contrast to viral transcripts , both cellular transcripts were not significantly reduced , indicating that transcription of cellular genes was occurring normally even in the presence of high VER-155008 concentrations ( Fig 6F ) . Taken together , these results demonstrate that inhibition of Hsp70 isoform function abrogated the expression of viral genes from various temporal classes; however cellular RNAPII-mediated transcription was not compromised when using VER-155008 at non-cytotoxic concentrations . Following quantification of viral transcripts in both cell lines , it appeared that the reduction seen in viral gene expression , protein production and infectious virion production could be a consequence of a significant global reduction of viral transcripts in inhibitor-treated cells . This led to the possibility that Hsp70 isoforms could be implicated in activation of viral promoters and subsequent transcription or alternatively Hsp70 isoforms were required for KSHV RTC formation . Because viral RTA and Hsc70 co-localized in TREx BCBL1-RTA cells and RTA is the master latent-lytic transactivator for multiple KSHV immediate-early , delayed-early and late promoters [66–70] , we further investigated the possibility that Hsc70 was required for RTA-mediated transactivation . Initially we assessed whether an interaction occurred between Hsc70 and RTA in the absence of other viral proteins or DNA . For this , HEK-293T cells were transiently transfected for 24 h with control pEGFP or pRTA-EGFP and immunoprecipitations were carried out using a GFP-specific antibody . RTA-EGFP precipitated endogenous Hsc70 in contrast to the control EGFP protein ( Fig 7A ) . In addition , HEK-293T cells were transfected with control pEGFP or pRTA-EGFP for 24 h and examined by immunofluorescence . In cells expressing EGFP protein , endogenous Hsc70 remained cytoplasmic ( Fig 7Bi ) , while in EGFP-RTA-expressing cells Hsc70 strongly co-localised with RTA in the nuclei , suggesting RTA expression alone is sufficient to redistribute Hsc70 into the nucleus ( Fig 7Bii ) . Similar nuclear redistribution was also seen for endogenous iHsp70 ( S5 Fig ) . Next , we determined whether VER-155008 was able to disrupt the interaction between EGFP-RTA and Hsc70 in HEK-293T cells . HEK-293T cells exhibited a very similar cytotoxicity profile to that seen in HEK-293T rKSHV . 219 cells ( S6 Fig ) . HEK-293T cells were transiently transfected with pRTA-EGFP or control pEGFP . To allow maximal protein expression and avoid interference of the inhibitor with the transfection , the inhibitor was added at 24 h post-transfection and incubated for a further 24 h , prior to immunoprecipitations being performed . Western blot analysis revealed that the inhibitor did not disrupt the interaction between Hsc70 and RTA even at high inhibitor concentrations ( 55 μM ) ( Fig 7C ) , suggesting that the ATPase function of Hsc70 is not required for the interaction with RTA protein . Therefore , to investigate whether Hsc70 was required for RTA-mediated transactivation of the RTA-responsive ORF57 promoter , a dual-luciferase reporter assay system was utilised . HEK-293T cells were co-transfected with pRTA-EGFP along with the Renilla luciferase vector and either the ORF57 promoter firefly luciferase reporter vector , or the empty reporter vector ( pGL3-BASIC ) . The same co-transfections were performed using pEGFP , as a negative control . 24 h post-transfection , cells were exposed for 2 h to increasing concentrations of VER-155008 and luciferase activities were measured . Longer exposure times to the inhibitor affected the formation of the control Renilla luciferase protein which has a half-life of 3 h , suggesting that Hsp70 isoforms may be required for the folding/maturation of this enzyme . In the presence of EGFP-RTA and the ORF57 promoter reporter construct , the ORF57 promoter activity was increased ~ 30-fold , while the empty vector had a ~ 4-fold increase . However , ORF57 promoter activity was not significantly decreased in the presence of VER-155008 ( Fig 7D ) . To confirm this result , HEK-293T cells were also transiently co-transfected with pPAN-WT , a plasmid encoding the genomic region of wild type PAN RNA including its promoter region [71] , and either pRTA-EGFP or control pEGFP . 24 h post-transfection either vehicle drug DMSO or VER-155008 at 45 μM was added and incubated for a further 24 h followed by qRT-PCR . In the presence of EGFP-RTA , but not of control EGFP protein , PAN RNA was synthesised . However , no significant decrease in the amount of PAN RNA was seen in inhibitor-treated cells ( Fig 7E ) , indicating that RTA-mediated promoter transactivation and subsequent synthesis of PAN RNA was occurring normally in the presence of VER-155008 . These data demonstrate that Hsp70 isoforms did not directly enhance RTA-mediated transactivation . To assess the transcription activity of cellular RNAPII in the presence of the inhibitor , the half-life of PAN RNA was determined in HEK-293T cells co-transfected with pPAN-WT and pRTA-EGFP . Following 24 h post-transfection , AcD ( 5 μg/ml ) or DMSO control ( 0 . 5% ) was added . After 7 h of transcription inhibition , PAN RNA levels were reduced to 25% compared to DMSO-treated cells ( Fig 7F ) . This quick reduction in the stability of PAN RNA in the absence of ORF57 protein is in agreement with previous reports [72] . Thus , if VER-155008 was blocking general RNAPII transcription , a significant reduction in PAN RNA levels should be observed after 7 h of inhibitor treatment; however , PAN RNA levels were not reduced in cells treated with VER-155008 for 24 h ( Fig 7E ) . A dramatic reduction in early , late and ori-Lyt transcripts after 24 h treatment with VER-155008 was evident during KSHV infection in both cell lines used . However , Hsp70 isoforms were not required for RTA-mediated transactivation of KSHV promoters in transiently transfected cells . Thus , we next monitored KSHV RTC formation in the absence or presence of the inhibitor during KSHV lytic infection . TREx BCBL1-RTA cells were reactivated and treated with either control DMSO or 2 μM inhibitor . At 24 h reactivation cells were fixed and immunofluorescence was performed using RTA- and Hsc70-specific antibodies . DMSO-treated cells displayed abundant RTCs and numerous nuclear Hsc70 foci that partially co-localised with RTCs . Hsc70 cytoplasmic depletion was also observed ( Fig 8A and 8A’ ) . In contrast , inhibitor-treated cells showed diffuse nuclear RTA that was not able to assemble into RTCs ( Fig 8B and 8B’ ) . In these cells , Hsc70 nuclear foci were still visible , but these were much less numerous and smaller compared with the foci seen in DMSO-treated cells . Significantly , following VER-155008 treatment , Hsc70 was observed in the cytoplasm of reactivated cells ( Fig 8B and 8B’ ) . Hsc70 subcellular localization was also analysed in DMSO- and inhibitor-treated cells by confocal profiling . Profiling was performed by drawing a line long enough ( ~ 20 μm ) to cover the nucleus and cytoplasm at either side of the nucleus . If an Hsc70 pixel intensity data point was equal or greater than to the data point in the previous and subsequent pixel and above the background noise , it was considered as an Hsc70 peak , representing an Hsc70 foci . DMSO-treated cells predominantly showed Hsc70 peaks only within the DAPI boundaries , that is , within the nucleus ( Fig 8A” ) . Inhibitor-treated cells displayed Hsc70 peaks outside the DAPI boundaries , that is , in the cytoplasm ( Fig 8B” asterisk ) more often than control cells . A significant increase in cytoplasmic Hsc70 peaks was seen in inhibitor-treated cells compared with DMSO control cells ( Fig 8C ) . Fractionation of reactivated TREx BCBL1-RTA cells in the presence or absence of VER-155008 , also pointed to slightly higher levels of Hsc70 in the cytoplasm and a decrease in nuclear Hsc70 in inhibitor-treated cells compared with DMSO control cells ( Fig 8D ) . Cells were also labelled with Click-iT EdU Alexa Fluor 647 and an antibody specific for Hsc70 ( S7 Fig ) . The percentage of assembled RTCs in DMSO- and inhibitor-treated cells was also calculated . In DMSO-treated cells ~ 44% of cells presented assembled RTCs while only 13% of inhibitor-treated cells showed assembled RTCs ( Fig 8E ) . This demonstrates that chaperone recruitment to the nucleus is essential for the assembly of KSHV RTCs and treatment with VER-155008 was sufficient to impair nuclear chaperone recruitment and KSHV RTC formation . The subcellular localisation of RNAPII was also assessed by indirect immunoflourescent labelling in TREx BCBL1-RTA cells with the monoclonal antibody CTD4H8 , which specifically recognises unphosphorylated and serine-5 phosphorylated RNAPII . In unreactivated cells , RNAPII exhibited a nuclear localization , excluding the nucleolus ( Fig 9Ai arrow ) irrespective of the presence of DMSO ( Fig 9Ai ) or the inhibitor ( Fig 9Aii ) . However , in reactivated and DMSO-treated cells , RNAPII was clearly hijacked to RTCs ( Fig 9Bi ) . In contrast , in reactivated cells treated with the inhibitor , RNAPII was diffuse throughout the nucleus , but excluding the nucleoli , and formed very small foci ( Fig 9Bii arrow ) ( see higher magnification on S8 Fig ) . This suggests that in the presence of Hsp70 isoform inhibition , RNAPII failed to assemble into developed RTCs and instead aberrantly formed what resembled pre-replicative sites . Cells were also labelled with Click-iT EdU Alexa Fluor 647 and an antibody specific for RNAPII ( S9 Fig ) . Similar RNAPII subcellular localisation and cellular DNA replication levels were seen in DMSO-treated and 2 μM inhibitor-treated unreactivated cells ( S9Ai and S9Aii Fig respectively ) . In DMSO-reactivated cells , cell cycle arrest was evident as shown by fewer Edu-labelled cells ( S9Bi Fig ) consistent with previous reports that lytic KSHV in primary effusion lymphoma cell lines causes G1 cell cycle arrest [73] . DMSO-treated cells displayed well assembled RTCs , with few of them showing actively replicating viral DNA ( S9Bi Fig ) . Inhibitor-treated cells exhibited very small RNAPII foci and diffuse nuclear Edu labelling ( S9Bii Fig ) . To confirm that inhibition of Hsp70 isoform function was able to abolish RNAPII recruitment to viral genomes , we also utilised chromatin immunoprecipitation ( ChIP ) assays in TREx BCBL1-RTA cells that were either reactivated for 24 h in the presence of DMSO or 2 μM VER-155008 ( Fig 9C ) . In unreactivated control cells , there was a clear enrichment of RNAPII at the promoter of GAPDH gene , while RNAPII occupancy at viral promoters was minimal . However , KSHV reactivation in DMSO-treated cells led to a drastic reduction of RNAPII at the promoter of GAPDH and a significant increase of RNAPII at the viral promoters in agreement with the previous immunofluorescence results , showing RNAPII recruitment to RTCs ( Fig 9Bi ) . Conversely , upon treatment of the HSP70 inhibitor , the amount of RNAPII bound at the promoters of ori-Lyt , K12 and ORF59 was decreased by ~ 65% , ~ 70% and ~ 50% respectively compared with DMSO-treated reactivated cells . Importantly , these results indicate for the first time that inhibition of Hsp70 isoforms leads to a severe impairment in RNAPII recruitment at multiple viral promoters including that of ori-Lyt . To further confirm the essential role of Hsc70 and iHsp70 in the formation of KSHV RTCs , specific individual siRNA-mediated depletion of both isoforms was performed in HEK-293T rKSHV . 219 cells . Following four days post-siRNA transfection , cells were reactivated for 24 h and RNA and protein were extracted from the same sample . Hsc70 depletion was evaluated by Western blotting and by qRT-PCR , the latter showing ~ 85% Hsc70 mRNA knockdown ( Fig 10A ) . In contrast , iHsp70 mRNA levels were not affected confirming specificity of the Hsc70 siRNA . Despite a successful knockdown at the mRNA level , significant amounts of Hsc70 protein remained in Hsc70-depleted cells ( Fig 10B ) . However , even with this modest amount of depletion at the protein level , all viral transcripts ( with the exception of PAN ) displayed a significant reduction in Hsc70 siRNA-treated samples compared with the scramble siRNA-treated cells as demonstrated by qRT-PCR analysis ( Fig 10C ) . ORF57 , ORF74 and gL mRNA levels were decreased by ~ 40% following Hsc70 knockdown . Ori-Lyt and RTA transcripts were reduced by ~ 30% and gB levels by ~ 20% . This suggests that depletion of Hsc70 impaired the expression of viral genes from various temporal classes and thus Hsc70 may be necessary for KSHV RTC formation . Viral DNA replication was also assessed following Hsc70 knockdown . For this , after four days post-siRNA transfection , cells were reactivated for a further 72 h . There were no significant differences between scramble and depleted cells ( Fig 10D ) . The production of infectious KSHV virions was also evaluated after 72 h reactivation . Again , no significant differences were seen between scramble and depleted cells ( Fig 10E ) ; however this result is not surprising due to incomplete Hsc70 depletion even after seven days post-transfection ( Fig 10F ) . This highlights the remarkable stability of Hsc70 protein in this cell line and it suggests that Hsc70 depletion was enough to cause a reduction in viral transcripts but not enough to cause a reduction in the amount of viral proteins , thus KSHV lytic replication remained unaffected . It is also possible that iHsp70 was able to functionally compensate for Hsc70 . Next , specific depletion of iHsp70 was performed in HEK-293T rKSHV . 219 cells . iHsp70 depletion at the mRNA level reached ~ 75% knockdown ( Fig 11A ) which correlated with efficient depletion at the protein level ( Fig 11B ) . However , in iHsp70-depleted cells , the majority of viral gene expression was unaffected , apart from gL and PAN transcripts which were decreased by ~ 40% and ~ 20% respectively ( Fig 11C ) . Importantly , taken together these results indicate that partial depletion of Hsc70 at the protein level is sufficient to cause a reduction in viral transcription , suggesting an essential role of this chaperone in the formation of KSHV RTCs , whereas iHsp70 may have a more subtle effect on viral gene expression . To further support the essential role of Hsc70 during KSHV RTC formation , Hsc70 was specifically silenced in TREx BCBL1-RTA cells . For this , nucleofection was carried out . Transfection efficiency was monitored co-transfecting the Hsc70 siRNA together with pmaxGFP , which encodes maxGFP , a green fluorescent protein from the copepod Pontellina p . ( Fig 12A ) . Note that higher transfection efficiency is expected for the siRNA due to the smaller size of this compared with the plasmid DNA . After four days post-nucleofection , Hsc70 mRNA levels showed ~ 90% knockdown ( Fig 12B ) with a minor depletion at the protein level ( Fig 12C ) . Due to the stability of Hsc70 protein , cells were incubated for six days post-nucleofection followed by a further 24 h reactivation and immunofluorescence for Hsc70 and RTA was carried out . RTC formation dramatically decreased after nucleofection . Similar impairment in KSHV lytic replication has previously been reported in electroporated TREx BCBL1-RTA cells [74]; nevertheless , in scramble siRNA-treated cells , groups of cells could still be seen displaying RTCs to which Hsc70 was relocated ( Fig 12D ) . In contrast , in Hsc70 siRNA-treated cells , fewer RTCs were visible and these exhibited nuclear Hsc70 ( Fig 12E yellow arrow ) while cells fully depleted of Hsc70 , as identified by lack of Hsc70-labelling , did not form RTCs ( Fig 12D white arrows ) . This result strongly suggests that Hsc70 is an essential chaperone for the formation of KSHV RTCs in TREx BCBL1-RTA cells .
Current quantitative proteomics approaches have become an invaluable tool for large-scale , high-throughput identification of proteins in complex biological samples . Moreover , advances in subcellular fractionation offer a way to further reduce the complexity of the samples to be analysed by LC-MS/MS , allowing identification of low abundance proteins . In this present study , we have developed a novel quantitative proteomic approach enhanced by subcellular fractionation that has enabled us to elucidate the cellular protein composition of KSHV RTCs . This novel approach led to the identification of several upregulated pathways in reactivated cells associated with the NE fraction ( S2 Table ) . The first scored pathway was RNA post-transcriptional modification , the second highlighted pathway was protein synthesis with 26 different ribosomal proteins identified and the third scored pathway was DNA replication , recombination and repair . In addition , the isolation of the NE regions from unreactivated and reactivated cells followed by the uncommon use of urea for protein extraction led to the mass spectrometric identification of several Hsp70 isoforms and their respective co-chaperones at significant levels in NE-associated RTCs of reactivated cells . Immunoflourescence analysis confirmed that endogenous Hsc70 and iHsp70 were redistributed from the cytoplasm to the periphery of KSHV RTCs where they formed multiple nuclear foci during early lytic replication . The formation of RTCs coincided in time with the appearance of nuclear chaperone foci . Similar virus-induced-chaperone-enriched ( VICE ) domains that form adjacent to HSV-1 RTCs , have also been observed in HSV-1-infected cells and contain sequestered Hsc70 , iHsp70 , Hsp40 and Hsp90 [58 , 75 , 76] . HSV-1 induced-VICE domains also accumulate ubiquitinated proteins and components of the proteasome and function to sequester misfolded proteins away from RTCs and serve as protein quality control centers [75 , 77] . iHsp70 redistribution very similar to that seen in HSV-1 induced-VICE domains was observed in multiple cells undergoing KSHV lytic replication , moreover this labelling was also observed for Hsc70 in some cells . Hsc70 and iHsp70 remain positioned exclusively adjacent to HSV-1 RTCs . However , in contrast; these chaperones were very dynamic during KSHV lytic replication and surprisingly very large chaperone foci were recruited within KSHV RTCs when viral DNA was actively synthesised ( Fig 2C and S1B Fig ) . Therefore , our results strongly suggest that these chaperones may also aid replication of KSHV genomes during lytic replication . We therefore further suggest that Hsp70 isoforms may have an important role in the assembly and activation of pre-initiation complexes on the origin of DNA replication . This is supported by observations in prokaryotes , such as in plasmid P1 [78 , 79] , and eukaryotes , such as Saccharomyces cerevisiae [80] , human papillomavirus-11 [81 , 82] , HSV-1 [83] and bacteriophage λ [84 , 85] . Interestingly , Hsp70 isoforms have also been identified in the KSHV virion [86 , 87] and therefore an additional role of these chaperones in KSHV capsid assembly may also be possible . Cancer cells greatly rely on members of the HSP70 and HSP90 chaperone families for their growth and survival [5 , 88] , consequently , significant efforts have been invested to design small molecule inhibitors specific for these ATPases as novel anticancer therapeutics . This has been successfully achieved for the HSP90 family with several inhibitors undergoing phase III clinical trials [14] , although the clinical efficacy of these inhibitors has been somewhat limited because of the inevitably upregulation of iHsp70 , when inhibiting Hsp90 [56 , 57] . The development of HSP70 inhibitors has substantially lagged behind that of HSP90 inhibitors due to lack of natural product inhibitors specific for Hsp70 isoforms , due to the highly polar nature of the Hsp70/Hsc70 ATP binding site and the high affinity for ATP displayed by these ATPases [12] . Nevertheless , in recent years several HSP70 inhibitors have been designed and tested in pre-clinical or clinical trials [88] . However , a major challenge remains in finding inhibitors which can specifically discriminate between iHsp70 and Hsc70 . To date , only peptide aptamers targeting iHsp70 are selective for a specific Hsp70 isoform [89] and also recently , methyl blue was reported to specifically inhibit iHsp70 by oxidizing a cysteine in its ATPase domain , the same residue is absent in Hsc70 allowing differential targeting of the isoforms [90] . Because both Hsc70 and iHsp70 were specifically redistributed to KSHV RTCs during lytic replication , we made use of a recently developed small molecule inhibitor , VER-155008 , which targets the ATPase pocket of the main three human Hsp70 isoforms . This inhibitor used at non-cytotoxic concentrations was able to effectively abrogate early and late KSHV transcription together with viral protein production , viral DNA replication and viral progeny . Therefore , our study highlights the potential of VER-155008 or other novel HSP70 inhibitors to prevent KSHV lytic replication in KSHV-associated tumours . One could expect that HSP70 inhibition would be directly detrimental not only to cancer cell survival but also the virus-specific functions that are dependent on Hsp70 isoforms . These results may have exciting implications in combination with the recently demonstrated efficacy of ATP-competitive HSP90 inhibitors in blocking KSHV latent cycle in vitro and in a xenograft KSHV tumour model [41] . It may be the case that combining HSP70 inhibitors with HSP90 inhibitors may lead to enhanced efficacy in eradicating latent KSHV reservoirs . Excitingly , in our cell culture models VER-155008 abrogated lytic replication without severely affecting cell viability or triggering apoptosis . It is intriguing that inhibition of constitutively expressed Hsc70 chaperone did not result in cell death . However , it is important to highlight previous studies carried out on the susceptibility of tumour cells versus normal cells to HSP90 inhibitors . In tumour cells , Hsp90 is present entirely in multi-chaperone complexes with high ATPase activity; in contrast , in normal cells Hsp90 is in an uncomplexed conformation . These two distinct Hsp90 presentations result in tumour Hsp90 exhibiting a 100-fold higher binding affinity to an HSP90 inhibitor than normal Hsp90 [91] . Thus , it is tempting to speculate that the multi-chaperone HSP70 foci that are recruited to KSHV RTCs during lytic replication ( Fig 2 and S1 Fig ) are more sensitive to VER-155008 than the chaperones not assembled in VICE domains which carry out the housekeeping functions for cell survival . This would explain why HSP70 inhibition had a profound effect on KSHV lytic replication without affecting cell viability and support the idea that isoform specificity may not be a requirement for treatment of KSHV-associated tumours . To establish the essential role of Hsp70 isoforms during KSHV lytic replication , we examined several possible functions . It could be hypothesised that Hsp70 isoforms could be implicated in 1 ) stabilization of essential viral proteins , 2 ) clearing stalled RNAPII during times of robust viral transcription , 3 ) activation of viral promoters , 4 ) formation of KSHV RTCs . Initially we hypothesised that Hsp70 isoforms may be necessary for maintaining the stability of the key KSHV viral proteins RTA and/or ORF57 . This was deemed a possibility as during KSHV latency , the essential viral latency associated nuclear antigen ( LANA ) protein has been recently shown to be a client protein of the Hsp90 chaperone and several HSP90 inhibitors reduced the expression of LANA [41] . In addition , the lytic KSHV K1 glycoprotein has also been reported to be a client protein of Hsp90 [92] . However , inhibition of Hsp70 isoforms did not alter the half-life of RTA or ORF57 ( Figs 3D and 4D ) . Alternatively , Hsc70 has been observed at the periphery of HSV-1 RTCs where it is also believed to aid in clearing stalled RNAPII from viral genomes during times of active transcription [76] . Indeed , the serine-2 phosphorylated form of RNAPII undergoes ubiquitination and robust proteasomal degradation during HSV-1 infection [93] . In contrast , in KSHV-reactivated cells , there was only a slight reduction of serine-2 phosphorylated RNAPII in comparison with unreactivated cells even at late times ( 24 h ) post-reactivation ( Fig 3C ) and a significant decrease in the other RNAPII forms was not evident ( Fig 3C ) . This suggests that although robust RNAPII degradation is a feature observed in virus infection , such as HSV-1 and influenza virus [55 , 93] , it may not be universally conserved . It is interesting to note that expression of a dominant-negative Hsc70 ( K71M ) that cannot hydrolyze ATP during HSV-1 infection resulted in prevention of serine-2 RNAPII degradation and RTCs formation [76] . However , inhibition of Hsp70 isoforms by VER-155008 did not prevent the slight degradation of phospho-serine-2 RNAPII protein ( Fig 3C ) . Using transient transfections , we also demonstrated that Hsp70 isoforms were not directly involved in the activation of viral promoters ( Fig 7D and 7E ) . Strikingly however , inhibition of Hsp70 isoforms precluded KSHV RTCs formation ( Fig 8 ) and RNAPII re-localization to viral promoters ( Fig 9 ) , thus , blocking KSHV RTCs formation led to abolishment of global viral transcription and subsequent protein synthesis and viral DNA replication . These results , taken together with the differential Hsc70 and iHsp70 labelling seen in HSV-1 and KSHV-infected cells , suggest that these chaperones may be playing additional roles , such as participating in viral DNA replication and/or capsid assembly , in KSHV lytic infection compared with HSV-1 infection . Importantly , in both viruses , HSV-1 and KSHV , inhibition of Hsc70 ATPase function leads to a clear impediment in RTCs formation and presents a novel antiviral target for multiple herpesviruses . Moreover , as HSV-1 and KSHV belong to different subfamilies of the Herpesviridae family ( α and γ subfamily respectively ) , the key role of Hsp70 isoforms in RTC formation may be conserved across all subfamilies . In support of this notion is the fact that Hsc70 and iHsp70 have also been reported to be incorporated in the virion of the β-herpesvirus HCMV [94] and the γ-herpesvirus EBV [95] . Our results also support that the finding of Hsc70 and iHsp70 chaperones in the KSHV virion [86 , 87] a decade ago was not casual , and that these chaperones are essential for KSHV RTCs formation during lytic replication . iHsp70 has also been detected in the HSV-1 virion [96] . To support the conserved role of Hsp70 isoforms in herpesvirus infection , a recent study showed that cellular depletion of Hsc70 protein significantly reduced HSV-1 viral output in cell culture without adversely affecting cell viability . Depleting Hsc70 from the HSV-1 virion also significantly reduced viral production by more than 50% [97] . Hsp70 isoforms may be recruited to RTCs for several reasons . Firstly , the chaperone may sequester misfolded , modified or unwanted proteins away from RTCs . Alternatively , Hsp70 could produce a site for protein remodelling and/or degradation which may regulate or delay cellular pathways , such as the apoptosis cascade . Finally , it may aid subtlety to clear stalled RNAPII complexes during robust viral transcription and replication . An additional question which is yet to be addressed is the mechanism by which Hsp70 isoforms are recruited to RTCs . One intriguing possibility is observations made during HSV-1 infection . Here , HSV-1 ICP27 has been shown to interact with Hsc70 and is required for Hsc70 nuclear foci formation [76] . It will now be interesting to determine if the functional KSHV homologue ORF57 , also interacts with Hsc70 and whether its nucleocytoplasmic shuttling ability is essential for Hsc70 nuclear import . In summary , we have identified a new essential role for Hsp70 isoforms during the formation of RTCs in KSHV lytic replication . Importantly , our results suggest that HSP70 inhibitors have the potential as novel KSHV antiviral agents and it would now be interesting to test these in conjunction with other molecular chaperone inhibitors , specifically HSP90 inhibitors [41] , which have the potential to eradicate latent KSHV reservoirs in both in vitro and in vivo tumour models .
TREx-BCBL-1-RTA cells ( kindly provided by Dr . Jae Jung , University of Southern California ) are a BCBL-1-based , primary effusion lymphoma ( PEL ) B cell line that has been engineered to inducibly express exogenous Myc-tagged RTA by the addition of doxycycline , leading to a robust reactivation of the full KSHV lytic cycle [48] . The rKSHV . 219 cell line ( kindly provided by Dr . Jeffery Vieira , University of Washington , Seattle , USA ) maintains KSHV as a latent infection and was generated by infecting HEK-293T cells ( ATCC ) with a recombinant KSHV that contains a constitutively active puromycin resistance and GFP gene , and an RFP gene that is fused to an RTA-responsive lytic cycle ( PAN ) promoter; hence , expression of RFP can be used as a reporter of RTA activity [42] . HEK-293T rKSHV . 219 cells were grown in DMEM ( Life Technologies ) supplemented with 10% foetal calf serum ( FCS ) ( Life Technologies ) and 1% penicillin/streptomycin ( P/S ) . This cell line was kept under puromycin ( Sigma ) selection ( 0 . 2 μg/ml ) . Reactivation into the lytic cycle was achieved by addition of 12-O-tetradecanoylphorbol 13-acetate ( TPA ) ( 20 ng/ml ) and sodium n-butyrate ( NaB ) ( Sigma ) ( 4 mM ) . The TREx BCBL1-RTA cell line was grown in RPMI 1640 medium ( Life Technologies ) supplemented with 10% FCS and 1% P/S . This cell line was kept under hygromycin B ( Life Technologies ) selection ( 100 μg/ml ) and inductions were performed using 2 μg/ml doxycycline hyclate ( Sigma ) as previously described [98] . All cells were maintained at 37°C in a humidified incubator with 5% CO2 . Plasmid transfections were carried out using Lipofectamine 2000 ( Life Technologies ) , as previously described [99] . Luciferase assay plasmids Renilla luciferase vector pRL-TK and firefly luciferase vector pGL3-BASIC were purchased from Promega , pEGFP-N1 was obtained from Clontech , pRTA-EGFP and pPAN-WT have been previously described [71 , 100] . The monoclonal mouse antibodies to anti-nuclear pore complex proteins ( mAb414 ) ( ab24609 ) , GAPDH ( 6C5 ) , rabbit polyclonal anti-lamin B1 and anti-Ser2 RNAPII were purchased from Abcam . The rabbit polyclonal anti-histone H3 C-terminus ( 39164 ) was purchased from Active Motif . The rabbit polyclonal anti-Nup160 was obtained from Bethyl Laboratories . Monoclonal antibodies to KSHV ORF57 ( 207 . 6 ) , to Hsc70 ( B-6 ) , to Grp78 ( A-10 ) , to Hsp90 ( 4F10 ) , to B-23 ( 0412 ) and to C-23 ( H6 ) were obtained from Santa Cruz . The mouse monoclonal ( C92F3A-5 ) anti-iHsp70 was from Enzo Life Sciences . The rabbit polyclonal anti-PARP1 was purchased from Cell Signalling . The mouse monoclonal ( CTD4H8 ) anti-RNAPII was purchased from Millipore . The mouse monoclonal ( 9E10 ) anti-c-Myc was from Sigma . Sheep anti-KSHV minor capsid protein was purchased from Exalpha Biologicals , Inc . The rabbit polyclonal anti-RTA was a gift from Professor David Blackbourn ( University of Surrey , UK ) . The mouse monoclonal ( JL-8 ) anti-GFP was supplied by Clontech . The inhibitor for Hsp70 isoforms ( VER-155008 ) was obtained from Tocris Bioscience . For SILAC , HEK-293T cells rKSHV . 219 were fed with either medium ( R6K4 ) or light ( R0K0 ) labelled medium ( Dundee Cell Products ) containing 10% dialysed FCS ( Dundee Cell Products ) for six passages to allow incorporation of the isotopes , as previously described [101] . Subsequently , to induce lytic replication three T175 flasks were reactivated with TPA ( 20 ng/ml ) and NaB ( 4mM ) for 48 h , while another three T175 flasks remained unreactivated as control . To isolate NEs a protocol published by Korfali et al . , [35] was used with minor modifications . 75 million cells were used per experimental condition . Cells were washed with PBS and incubated in hypotonic lysis buffer ( 10 mM HEPES pH 7 . 4 , 1 . 5 mM MgCl2 , and 10 mM KCl ) for 30 min followed by homogenization with a tight Dounce homogenizer . To stabilise and avoid lysing the nuclei after the hypotonic swelling step , cells were resuspended in 2 . 2M SHKM ( 2 . 2 M sucrose , 50 mM HEPES pH 7 . 4 , 25 mM KCl , and 5 mM MgCl2 ) and 1M KCl . The resuspended cells were then underlayed with 30% SHKM ( 0 . 9 M sucrose , 50 mM HEPES pH 7 . 4 , 25 mM KCl , and 5 mM MgCl2 ) and nuclei were pelleted at 2 , 000xg for 20 min at 4°C in a Eppendorf centrifuge 5804 R . Nuclei were resuspended in 1 . 9 M SHKM , underlayed with 2 . 2 M SHKM and transferred to 38 . 5-ml ultracentrifuge tubes ( Beckman Coulter ) . Nuclei were then centrifuged at 82 , 000xg for 2h at 4°C in a Sorvall Discovery 90SE ultracentrifuge . Pellets were resuspended in 0 . 25 M SHKM ( 50 mM HEPES pH 7 . 4 , 25 mM KCl , and 5 mM MgCl2 ) , treated with 1% Triton-X in 10% SHM ( 0 . 3 M sucrose , 10 mM HEPES , pH 7 . 4 , 2 mM MgCl2 and 0 . 5 mM Ca Cl2 ) for 10 min and centrifuged at 2 , 000xg for 10 min . Nuclei were then treated with RNase A ( Thermo Scientific ) and DNase I ( Life Technologies ) for 15 min , pelleted at 6 , 000xg for 10 min , resuspended in 10% SHM and treated again with RNase A and DNase I for 15 min . Nuclei were centrifuged at 2 , 000xg for 10 min , resuspended and incubated for 15 min in 10% SHM containing 0 . 3 M NaCl to remove nucleoplasmic contents . Nuclear envelopes were then pelleted at 1 , 500xg for 15 min . Insoluble nuclear envelope proteins were solubilised for 10 min in PBS supplemented with 0 . 1% Triton-X100 and 6 M urea . Samples were centrifuged at 6 , 000 g for 2 min to remove insoluble material and the supernatant containing nuclear envelope proteins was stored at -80°C for further Western blotting and mass spectrometry analysis . All solutions had freshly added 1x Complete , EDTA-free protease inhibitors ( Roche ) . DTT ( 2 mM ) was also freshly added to the solutions specified on Korfali’s protocol . LC-MS/MS was performed as previously described [22] . Bioinformatical analysis was performed with the Ingenuity Systems software packet , IPA 9 . 0 ( Ingenuity Systems , Inc ) . Protein samples were extracted using lysis buffer containing 50 mM Tris ( pH 7 . 4 ) , 150 mM NaCl , 1% NP-40 and 1x Complete , EDTA-free protease inhibitors ( Roche ) for 30 min on ice , as previously described [102] . Protein samples were run on SDS-PAGE gels and transferred to nitrocellulose membranes ( Amersham ) via wet transfer . Membranes were blocked with TBS + 0 . 1% Tween 20 and 5% dried skimmed milk powder . Membranes were probed with relevant primary and secondary antibodies , treated with EZ-ECL ( Geneflow ) and exposed to Amersham hyperfilm ECL ( GE Healthcare ) . Secondary antibodies were horseradish peroxidase ( HRP ) -conjugated polyclonal goat anti-mouse and polyclonal goat anti-rabbit ( Dako ) . HRP-conjugated polyclonal rabbit anti-sheep was from Santa Cruz . GFP-Trap ( Chromotek ) experiments were performed as previously described [103] . Nuclear/cytoplasmic fractionations were performed as previously described [44] , with the exception that nuclear pellets were solubilised for 20 min in PBS supplemented with 0 . 1% Triton-X100 and 6 M urea . Vigorous pipetting and vortexing was applied to the nuclear pellet . After urea treatment , insoluble material was removed by centrifugation at 6 , 000 g for 2 min and the supernatant kept for further analysis . Cells were cultured overnight on poly-L-lysine ( Life Technologies ) coated glass coverslips in 24-well plates . Cells were fixed with 4% formaldehyde ( Calbiochem ) for 10 min and permeabilised with 0 . 1% Triton X-100 for 20 min as previously described [104] . For labelling with Grp78 antibody cells were fixed with ice-cold 100% methanol for five min . After permeabilization , cells were then incubated in blocking solution ( PBS with 1% BSA ) for 1 h at 37°C . Primary antibodies anti-Hsc70 ( diluted 1:200 ) , anti-iHsp70 ( 1:50 ) , anti-Grp78 ( 1:50 ) , anti-RNAPII ( CTD4H8 ) ( 1:500 ) or rabbit RTA ( 1:1 , 000 ) were incubated for 1 h at 37°C . Coverslips were washed five times with PBS , incubated with appropriate secondary antibody for 1 h at 37°C , washed five times with PBS again and mounted in VECTASHIELD with DAPI ( Vector Labs ) . Images were obtained using a LSM 510 META confocal microscope ( Carl Zeiss ) and processed using ZEN 2009 imaging software ( Carl Zeiss ) as previously described [105] . Fluorescently-conjugated secondary antibodies were all obtained from Life Technologies: Alexa Flour 633 goat anti-mouse IgG , Alexa Flour 488 goat anti-mouse IgG , Alexa Flour 488 goat anti-rabbit IgG , Alexa Flour 546 donkey anti-mouse IgG and Alexa Flour 546 goat anti-rabbit IgG . TREx BCBL1-RTA cells were labelled using the Click-iT EdU Alexa Fluor 647 Imaging Kit ( Life Technologies ) according to the manufacturer’s instructions with minor modifications as follows . Cells were seeded onto poly-L-lysine treated coverslips in 24-well plates followed by induction and incubation at 37°C for 24 hours . Prior to cell fixation , 10 μM EdU ( 5-ethynyl-2’-deoxyuridine ) was added to each well for 45 min . Cells were then fixed for 10 min in 4% formaldehyde and permeabilised in 1% Triton X-100 for 20 min . Edu detection was carried out adding the Click-iT reaction cocktail for 30 min and immunofluorescent labelling for RTA and Hsc70 was performed as above . Cells were mounted in VECTASHIELD with DAPI ( Vector Labs ) . Total RNA from cells was extracted using TRIzol ( Life Technologies ) according to the supplier’s protocol . DNA-free DNA Removal Kit ( Ambion ) was used to remove any contaminating DNA from RNA samples . Reverse transcription was performed with ProtoScript II ( NEB ) and oligo ( dT ) primers and 1 . 5 μg of total RNA . Negative control reactions were performed in the same manner but without reverse transcriptase . Quantitative PCR ( qPCR ) reactions ( 20 μl ) included 1X SensiMix SYBR green master mix ( Bioline ) , 0 . 5 μM of each primer and 5 μl template cDNA ( used at 1:200 dilution in RNase-free water ) . Cycling was performed in a RotorGene Q machine ( Eppendorf ) . The cycling programme was a 10 min initial preincubation at 95°C , followed by 40 cycles of 95°C for 15 sec , 60°C for 30 sec and 72°C for 20 sec . After qPCR , a melting curve analysis was performed between 65 and 95°C ( with 0 . 2°C increments ) to confirm amplification of a single product . Relative expression compared to control cells was calculated using the ΔΔCT method as previously described [106] . For each gene of interest and housekeeping gene ( GAPDH ) a standard curve was constructed using a pool of cDNA derived from unreactivated and reactivated cells . Six different dilutions of the standards were quantified , these included 1:100 , 1:200 , 1:400 , 1:800 , 1:1 , 600 and 1:3 , 200 dilution . The slope of the standard curve was used to calculate the amplification efficiency ( AE ) of the primers using the formula: AE = ( 10−1/slope ) . The mean cycle threshold ( CT ) was determined from three independent biological replicates . All genes of interest were normalised against the housekeeping gene GAPDH ( ΔCT ) . ΔΔCT was calculated subtracting ΔCT of unreactivated cells from ΔCT of reactivated cells and the fold change was then determined using AE ( -ΔΔCT ) . Statistical significance was validated by Student’s t-test . Unreactivated TREx BCBL1-RTA cells treated with DMSO ( 0 . 1% ) were used as control to assess viral reactivation . Reactivated cells were exposed to doxycycline for 72 h . Total DNA was then isolated with the use of a QIAamp DNA mini kit ( Qiagen ) as per the manufacturer’s instructions . qPCR was carried out as described above . 10 ng of template DNA and primers specific for the ORF57 gene were used . Quantification of GAPDH gene was used to normalize between samples and the mean cycle threshold ( CT ) was determined from three independent biological replicates . Relative levels of viral DNA compared with unreactivated cells were calculated using the ΔΔCT method as previously described [106] . TREx BCBL1-RTA cells that had been seeded on 12-well plates were reactivated and treated with control DMSO ( 0 . 1% ) or VER-155008 . Unreactivated cells treated with DMSO ( 0 . 1% ) were used as control to evaluate viral reactivation . After 72 h reactivation , 700 μl of the RPMI 1640 culture medium was centrifuged at 800 g for five min , immediately mixed with 300 μl of DMEM supplemented with 10% FCS and 1% P/S and incubated for a further 24 h with HEK-293T cells that had been seeded in 12-well plates the previous day . Total RNA was then extracted with TRIzol ( Life Technologies ) and qRT-PCR carried out as described above . Relative expression compared to control cells was calculated using the ΔΔCT method as previously described [106] . Determination of the cellular metabolic activity was performed using a non-radioactive CellTiter 96 AQueous One Solution Cell Proliferation Assay ( MTS ) ( Promega ) , according to the manufacturer's manual . 20 , 000 cells TREx BCBL1-RTA or 10 , 000 HEK-293T rKSHV . 219 cells were seeded in triplicate in a flat 96-well culture plate ( Corning ) . After 24 h inhibitor exposure , CellTiter 96 AQueous One Solution Reagent was added and cells were incubated for 1 h in a humidified incubator in 5% CO2 at 37 °C . Absorbance was measured at 490 nm using an Infinite F50 ( Tecan ) plate reader . Background control had culture medium without cells and the signal from this was subtracted to all other absorbance values . This assay allows evaluation of viability , cytotoxicity and effector caspases activation within a single assay well . The assay was carried out as specified on the supplier’s manual . 20 , 000 TREx BCBL1-RTA cells or 10 , 000 HEK-293T rKSHV . 219 cells were seeded in triplicate in tissue culture treated black microplates ( Greiner Bio-One ) . No-cell control ( background ) contained only culture medium and the signal from this was subtracted to all other absorbance and luminescence values . Fluorescence and luminescence readings were collected using a GloMax System ( Promega ) ( kindly provided by Dr . John Boyle , University of Leeds , UK ) . Luciferase activity was detected using the Dual-Luciferase Reporter Assay System ( Promega ) as previously described [107] . HEK-293T cells were seeded in triplicate in flat 96-well culture plate ( Corning ) at a density of 10 , 000 cells per well . Following the respective plasmid transfections and inhibitor exposure , media was removed from the culture wells and cells washed gently with 100 μl PBS . 30 μl 1x passive lysis buffer was added to the cell monolayer which was rocked for 15 min and then 20 μl of each lysate was transferred to tissue culture treated white microplates ( Greiner Bio-One ) . Luciferase measurements were carried out in a FLUOstar Optima microplate reader ( BMG Labtech Ltd ) , with injectors 1 and 2 being used to dispense 50 μl of Luciferase Assay Reagent II and Stop & Glo Reagent respectively . Firefly luciferase activity was normalized to Renilla luciferase activity . Formaldehyde-crosslinked chromatin was prepared using the Pierce Chromatin Prep Module ( Thermo Scientific ) following the manufacturer’s protocol . 2 x 106 cells were used per experimental sample and digested with six units of micrococcal nuclease ( MNase ) per 100 μl of MNase Digestion buffer in a 37°C water bath for 15 min . These conditions resulted in optimal sheared chromatin with most chromatin fragments ranging from 150–300 base pairs . Immunoprecipitations were carried out using EZ-ChIP kit ( Millipore ) according to the supplier’s instructions and as previously described [44] . Immunoprecipitations were done overnight at 4°C and contained 50 μl of digested chromatin ( 2 x 106 cells ) , 450 μl of ChIP dilution buffer and 1 . 5 μg of RNAPII antibody ( clone CTD4H8 ) ( Millipore ) or isotype antibody , normal mouse IgG ( Millipore ) . Both antibodies were provided with the EZ-ChIP kit . Prior to qPCR analysis , eluted DNA was subjected to a DNA clean up step using UltraClean PCR Clean-Up Kit ( Mo Bio Laboratories ) according to the supplied protocol with the exception of using 500 μl of SpinClean buffer instead of 300 μl . qPCR reactions were performed as described above and using either 2 μl of ChIP’ed DNA or 2 μl of input DNA as template . HEK-293T rKSHV . 219 cells seeded on 12-well plates were reverse transfected with either 100 nM of the specific Silencer Select siRNA ( Life Technologies ) or 100 nM AllStars negative control siRNA ( Qiagen ) using 7 μl of siPORT NeoFX transfection agent ( Life Technologies ) per transfection . The siRNA ID for Hsc70 and iHsp70 were s6985 and s6968 respectively . s6968 siRNA targets the two major iHsp70 proteins ( HSP70-1 and HSP70-2 ) . Two days post-transfection , cells were transfected again in the same manner . Four days after the first transfection , cells were reactivated and incubated for the desired time . Proteins and total RNA were isolated with TRIzol ( Life Technologies ) and subsequent Western blot and qRT-PCR were performed . 8 × 106 TREx BCBL1-RTA cells were transfected once with 100 μl of Nucleofector solution V ( Lonza ) to which 2 μM siRNA ( scramble or Hsc70 ) was added . In addition , to monitor transfection efficiency , 1 μg of the control plasmid pmaxGFP was also co-transfected . Cells were transfected using program T-01 of an Amaxa nucleofector I ( Lonza ) . After nucleofection cells were maintained in six-well plates . Medium was freshly replaced every day . Confocal images were subjected to profiling analysis using Zeiss Zen 2011 software . This involved drawing a line in a confocal image to measure the relative intensity of each channel at every pixel along the line . Profiling was conducted for each cell in two representative confocal images taken with a 40-times objective . These data were then analysed using Microsoft Excel 2010 . Firstly , a function was used to define whether the relative intensity of a pixel could be defined as a “peak” and thus an Hsc70 foci . This function asked whether the data point for one specific pixel of the rhodamine channel was ≥ 20 , this was set as the arbitrary threshold to eliminate background noise . If this condition was met , the function then asked whether the data point was greater than or equal to the data point in the previous and subsequent pixel . If these conditions were true , then this data point was counted as a peak . This was performed for every data point measured in the line profile providing the total number of Hsc70 peaks in the profile of one cell . Next , another function was used to determine whether the relative intensity in the DAPI channel was ≥ 25 , a threshold determined from visualising the line profiling data as a graph . If a pixel was shown to exceed the threshold in the DAPI channel and also in the rhodamine channel , then it was counted as a nuclear Hsc70 peak . These measurements were conducted for each pixel in each profile allowing counting Hsc70 nuclear peaks in each profile . Hsc70 peaks outside the nucleus corresponded to cytoplasmic Hsc70 peaks . Oligonucleotide primer sequences are available upon request . All primers were purchased from Sigma ( UK ) . | Molecular chaperones from the HSP70 and HSP90 families have important roles in cell survival . Recent evidence has also implicated their functioning in a variety of diseases , including cancer . As such they have been identified as emerging drug targets . Kaposi’s sarcoma-associated herpesvirus ( KSHV ) is an oncogenic herpesvirus which , like other herpesviruses , lytically replicates in virus-induced structures within the nucleus , termed replication and transcription compartments ( RTCs ) . Here we developed a novel proteomic approach enhanced by subcellular fractionation to study the cellular protein composition of KSHV-induced RTCs . Results revealed that the constitutively expressed Hsc70 and the stress-inducible iHsp70 chaperones were significantly increased in the KSHV-induced RTCs . Importantly , inhibition of the ATPase function of these chaperones led to a marked reduction in KSHV RTCs formation and KSHV lytic replication . Notably , these results highlight the therapeutic potential of HSP70 inhibitors for the treatment of KSHV-related diseases , such as Kaposi’s sarcoma . | [
"Abstract",
"Introduction",
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] | [] | 2015 | Hsp70 Isoforms Are Essential for the Formation of Kaposi’s Sarcoma-Associated Herpesvirus Replication and Transcription Compartments |
The lipid composition of cell membranes has increasingly been recognized as playing an important role in the function of various membrane proteins , including G Protein-Coupled Receptors ( GPCRs ) . For instance , experimental and computational evidence has pointed to lipids influencing receptor oligomerization directly , by physically interacting with the receptor , and/or indirectly , by altering the bulk properties of the membrane . While the exact role of oligomerization in the function of class A GPCRs such as the μ-opioid receptor ( MOR ) is still unclear , insight as to how these receptors oligomerize and the relevance of the lipid environment to this phenomenon is crucial to our understanding of receptor function . To examine the effect of lipids and different MOR conformations on receptor oligomerization we carried out extensive coarse-grained molecular dynamics simulations of crystal structures of inactive and/or activated MOR embedded in an idealized mammalian plasma membrane composed of 63 lipid types asymmetrically distributed across the two leaflets . The results of these simulations point , for the first time , to specific direct and indirect effects of the lipids , as well as the receptor conformation , on the spatio-temporal organization of MOR in the plasma membrane . While sphingomyelin-rich , high-order lipid regions near certain transmembrane ( TM ) helices of MOR induce an effective long-range attractive force on individual protomers , both long-range lipid order and interface formation are found to be conformation dependent , with a larger number of different interfaces formed by inactive MOR compared to active MOR .
Elucidating the impact of the lipid environment on membrane proteins , including G Protein-Coupled Receptors ( GPCRs ) , is increasingly being recognized as a crucial part of understanding how these proteins function . Cholesterol ( CHOL ) , the lipid for which the most is known about its effect on GPCRs , has been shown to affect receptor thermal stabilization [1 , 2] , agonist affinity [3 , 4] , and oligomerization [5–8] . The conformational equilibrium of the prototypic GPCR rhodopsin is known to be sensitive not only to CHOL levels , but also to phospholipid headgroup and chain saturation [9] . Lipid headgroup charges have also been shown to play a role in the function of the β2 adrenergic ( β2AR ) [10] and the neurotensin NTS1 receptors [11] . The role of the lipids has primarily been attributed to indirect effects such as changing the physical properties of the membrane ( e . g . , thickness , curvature , surface tension , and elastic properties ) . Transmembrane proteins frequently experience hydrophobic mismatch in which the lengths of the hydrophobic chains of the lipids and the hydrophobic part of the protein are different . To rectify this mismatch , the protein adopts several strategies , including conformational changes and remodeling of the membrane thickness by changing the order of the lipids [12] . On a larger scale , heterogeneous membranes are organized into domains which are either liquid-ordered ( lo ) or liquid-disordered ( ld ) regions . Notably , some of these domains ( e . g . , lipid rafts ) are enriched in CHOL and sphingolipids , two lipids which have a high propensity of being ordered [13] , i . e . , parallel to the membrane normal . While the exact role of lipids rafts is debated , they appear to aid in lateral organization of the proteins in the membrane , increasing the propensity of the necessary components of a cell signaling complex to come together [13 , 14] . In addition to modulating the physical properties of the plasma membrane , lipids can interact directly with membrane proteins . Several crystal structures of GPCRs , including β2AR [2] and the adenosine A2A receptor [15] , have been crystallized with interacting CHOL , suggesting that these molecules are strongly bound to the protein . A conserved consensus CHOL binding motif ( CCM ) has been identified in a number of GPCRs [2] , while a sphingolipid binding site has been proposed for the serotonin 5HT1A receptor [16] . CHOL-receptor interactions have also been suggested to play a role in oligomerization based on inferences from crystal structures of GPCRs ( e . g . , the β2AR [17] and the metabotropic mGlu2 receptor [18] ) showing CHOL molecules at putative dimeric interfaces . Molecular dynamics ( MD ) simulations of membrane mimetic systems continue to complement experiments by offering a mechanistic understanding of the dynamics not readily available to most experimental techniques . Early coarse-grained ( CG ) simulations of rhodopsin embedded in bilayers of lipids with different chain lengths and saturation levels showed that the membrane deforms to adapt to the protein [19] . Activation of rhodopsin was also shown to be affected by the physical properties of the membrane [20]; while lipids with unsaturated chains promote activation , CHOL , which is a much more rigid molecule , inhibits activation . Furthermore , while unsaturated lipids were shown by MD to preferentially cluster at the receptor in a non-specific manner [21 , 22] putative binding sites were identified for CHOL , notwithstanding the typically dynamic interaction between CHOL and GPCRs [23–26] . Notably , MD simulations of β2AR performed with different concentrations of CHOL showed that CHOL binding to conserved sites could prevent some dimer interfaces from forming [6] . While most published MD simulations have been performed in a single or dual component membrane , an average idealized multi-component plasma membrane parameterized recently within the Martini CG force-field [27] offers an unprecedented opportunity to study the impact of lipid composition on the spatio-temporal organization of GPCRs in a more realistic environment . This 63-component membrane mimetic contains combinations of all major lipid headgroups with different fatty acid tails , asymmetrically distributed between two plasma leaflets ( see Ref . [27] for more details ) . Specifically , the following lipid species were included: i ) the charged species phosphatidylinositol ( PI ) , phosphatidylserine ( PS ) , and phosphatic acid ( PA ) , phosphatidylinositol mono- , bis- , and tri-phosphate ( PIP1-3 ) , and gangliosides ( GM ) ; ii ) the zwitterionic lipid species phosphatidylcholine ( PC ) , phosphatidylethanolamine ( PE ) , and sphingomyelin ( SM ) , and iii ) the minor species diacylglycerol ( DAG ) , ceramide ( CER ) , and lysophosphatidylcholine ( LPC ) . Simulating receptor self-association in this membrane model provides further insight into how lipids can affect oligomerization , adding to what we had previously concluded from simulations of opioid receptors in an environment composed of 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine ( POPC ) and 10% CHOL [28] . The μ-opioid receptor ( MOR ) is an ideal test case to examine the role of lipids and receptor conformation on oligomerization . First and foremost , the crystal structures of both inactive [29] and activated [30] MOR have been solved with the latter showing the expected outward swing-out movement of TM6 . While a crystallographic TM1 , 2 , H8/TM1 , 2 , H8 interface was observed in both active and inactive structures , a TM5 , 6/TM5 , 6 interface was identified in the crystal structure of the inactive receptor , but not in that of its activated form . Furthermore , although the exact role of MOR oligomerization in signaling is still under debate , the potential of developing new , more effective therapies in the treatment of pain [31] by selectively targeting MOR heterodimers makes these systems worthy of further investigation . Finally , while there is evidence both for [32] and against [33] the association of MOR with lipid rafts , CHOL has been shown to be important in the spatio-temporal signaling by MOR [34] . In fact , it has been shown to promote homodimerization of MOR [5] , agonist binding [35] , coupling with G-proteins [5 , 35] , and translocation of β-arrestin [36] . Here , we present the results of CG MD simulations of arrays of 16 inactive and/or activated MORs in the aforementioned multi-component plasma membrane carried out to further evaluate the role of both lipid environment and protein conformation on MOR oligomerization .
The 63 lipid types in the plasma membrane model were grouped by their headgroup to examine the preferred regions of association between the lipids and the receptors during simulation . Specifically , for this analysis , we used the final 2 μs of membrane equilibration of four sets of simulations: 16 inactive or active receptors in either a 50×50 nm2 or 25×25 nm2 membrane ( referred to as low and high receptor density membranes , respectively ) . To analyze the behavior of the lipids , the GL1 or AM1 bead was used for all non-sterol lipids while the ROH bead was used for CHOL ( See S1 Fig for a depiction of representative lipids ) . The normalized 2D probability distributions of lipids with zwitterionic headgroups ( i . e . , PC , PE , SM ) in the simulations of the plasma membrane model with low density of inactive or active receptors are shown in Fig 1 whereas the distributions of all charged lipid types ( i . e . , GM , PS , PI , PIP1-3 , and PA ) are shown in S2 Fig . Unlike the distributions of PA , PI and PIP1-3 , the distributions of PC , PE , SM , PS , or GM appear to be qualitatively similar around inactive and activated receptors . To confirm these observations , we calculated the standard deviation of the distribution of each lipid type at each grid point for five runs of inactive or active receptors , and compared it to the difference between the average lipid distributions around inactive and active receptors . The distributions of PC and PE , which are the most populated glycerophospholipids in the plasma membrane , show a depletion of lipids immediately next to certain receptor TM helices . For instance , comparing Fig 1A and Fig 2 , we observe that the lipid depletion at TM5 and TM6 ( yellow and green dots in Fig 1A ) is due to the presence of CHOL immediately next to the protein . The remaining glycerophospholipids , PA , PI , PS , and PIP1-3 , make up approximately 19% of the lower leaflet and are not present in the upper leaflet ( See S3 Fig for the composition of the membrane ) . Despite their random initial position , these lipids diffuse towards the proteins during equilibration . Since there are a number of positively charged Lys ( specifically , residue number 98 , 100 , 1854 . 43 , 174 , 2605 . 66 , 2696 . 24 , 2716 . 26 , and 344 ) and Arg ( i . e . , 951 . 59 , 1653 . 50 , 179 , 1824 . 40 , 2585 . 64 , 263 , 2736 . 28 , 2766 . 31 , 2776 . 32 , 2806 . 35 , 345 , 348 ) residues on the intracellular side of MOR , it is not surprising to see PA , PI , PS , and PIP1-3 , which are all negatively charged , localize in this region of the proteins ( S2A–S2D Fig for PA , PI , PIP1-3 and PS , respectively ) . Specifically , PIP1-3 molecules are found to be predominantly in contact with the intracellular ends of TM4 , TM6 , and TM7 of inactive MOR . Upon activation , the outward swing of TM6 away from TM3 leaves the positively charged residues on TM5 and TM6 more exposed to negatively charged lipids , so that their concentration is reduced in the space between TM6 and TM7 and increased near TM5 and H8 . See S1 Table for a list of the residues most frequently in contact with PIP1-3 . Despite the small concentration of these PIP1-3 lipids in the membrane , the maximum difference between their distributions around inactive and active receptors ( 0 . 03 ) is much larger than the maximum standard deviation ( 0 . 005 ) of the PIP1-3 distribution at each grid point for the five runs of inactive or active receptors , suggesting that the observed conformation-dependent changes are larger than the sampling error . On the other hand , the PA and PI lipids ( S2 Fig Panels A and B , respectively ) do not show significant changes in distribution around the two receptor conformations , because the differences in lipid distribution around inactive and active receptors ( PA: 0 . 003 , PI: 0 . 006 ) are the same order of magnitude as the maximum standard deviation at each grid point ( PA: 0 . 002 , PI: 0 . 002 ) . In addition to the glycerophospholipids , the plasma membrane contains a large fraction of the sphingolipid SM . These two groups of lipids are distinguished by the linker beads connecting their headgroup to the lipid tails . While each of the two linker beads of the glycerophospholipids represents a nonpolar ester group , in the case of SM , one linker bead represents a hydroxyl group and the other an amide group , both of which are polar . Similar to the PC distribution ( Fig 1A ) , SM ( Fig 1C ) is depleted immediately next to the protein except at TM1 , TM5 , and TM6 , where the sidechains of several polar and charged residues form strong Lennard-Jones interactions with the polar linker beads of SM . Finally , the GM lipids ( S2E Fig ) are sphingolipids which have an oligosaccharide and sialic acid head group and comprise ~5% of the upper leaflet . During the initial portion of the membrane equilibration the GMs diffuse to the proteins where they remain , very rarely moving back into the bulk membrane . Determining the precise protein-GM interaction , which dictates their segregation propensity , is difficult due to the large headgroup of these lipid species , but it does not appear to be different depending on the receptor conformation . The GMs tend to cluster together in line with the observations of Ingólfsson et al . [27] and Gu et al . [37] . Composing about 30% of the idealized plasma membrane ( S3 Fig ) , CHOL is one of its largest components . Fig 2 shows the distribution of CHOL around the simulated inactive and active MOR protomers . In agreement with experimental evidence [38] , CHOL flip-flops between the upper and lower leaflets and was frequently found to be interacting with the helical bundle region of the receptors , as shown by the structures ( Fig 2 ) colored white to blue to green by the probability of each residue being in contact with the ROH bead of CHOL . For inactive MOR , the highest density of CHOL was found near TM6 and TM7 in the hydrophobic region of the membrane . Notably , an identified CHOL hotspot near TM6 corresponds to the location of the electron density that was attributed to a CHOL molecule in the MOR inactive crystal structure ( PDB ID: 4DKL ) . While a hotspot near the palmitoylation site C1703 . 55 was also observed in the simulations of the inactive MOR , in those of the active MOR , the CHOL was preferentially found between TM2 and TM5 and between TM5 and TM6 . Notably , the maximum difference between the CHOL distributions around inactive and active receptors was 0 . 003 while the maximum standard deviation of CHOL distribution at each grid point of the individual simulation runs was 0 . 0006 , indicating that the differences are substantial . We quantified the local properties of the lipids in the plasma membrane model by calculating the order parameter of each non-flipping lipid species ( i . e . excluding CHOL , CER , and DAG ) during the final 2 μs of membrane equilibration in which the receptors are kept fixed or the production runs in which the receptors are permitted to freely move in both the high and low receptor density simulations . The lipid order parameter was defined as the angle between the membrane normal and a vector between the first and last bead of the tail . Specifically , as described in the Methods section , a value of the order parameter of 0 means that lipid tails are on average ordered and parallel to the membrane normal , while larger values imply that the lipid tails assume disordered conformations . The extreme value of π/2 means the lipid tail forms a 90° angle with the membrane normal . In Fig 3 and S4 Fig we report , as an example , the results of one of the simulation runs where the active or inactive receptors are fixed in the low or high receptor density systems , respectively . The other trajectories show a similar behavior , as do the trajectories of the mixed-arrays ( i . e . , 50% inactive/50% active MOR; S5 Fig ) , which were only simulated in the high receptor density membrane . Since the pattern of ordered and disordered regions near the inactive or active receptors in the mixed-arrays is similar to that in the arrays of only inactive or active protomers , respectively , only the results for all inactive or all active arrays are discussed . There are clear regions of order and disorder in the membrane . As expected , lipid order is correlated with bilayer thickness ( see Fig 3 , S4 Fig , S5 Fig and S6 Fig ) , since a lipid with a fully extended tail has a greater z-projection of the head to tail distance than that of a disordered lipid . Fig 3 suggested that the regions close to TM5 , TM6 , and–to a lesser extent–TM1 , show more order while the regions near TM4 show more disorder . To confirm this behavior , we calculated the average membrane thickness and lipid order near the individual helices ( shown in top and lower panels , respectively , of Fig 4 for the low receptor density simulations in which the receptor was permitted to move freely ) . Interestingly , the extent of the order is not only helix dependent , but also conformation dependent ( Fig 4 ) . The region near TM5 and TM6 ( yellow and green dots in Fig 3 , yellow and green lines in Fig 4 ) is thicker ( and more ordered ) in the simulations with the inactive receptor than those with active receptors , while the region near TM4 ( orange in Figs 3 and 4 ) is more disordered next to both the active and inactive protomers . The trends in the helix-dependent lipid order are not influenced by the overall protein density nor by the restraints imposed during the equilibration . In fact , similar results were obtained for the low receptor density simulations in which the proteins were permitted to move freely ( Fig 4 ) as well as the low and high receptor density simulations of restrained receptors ( S7 Fig and S8 Fig , respectively ) despite the inability of the receptors to tilt when they were kept fixed ( S9 Fig ) . The correlation between the locations of ordered regions with SM enrichment was confirmed by calculating a 55% to 45% ratio for the probability to find a SM molecule in a region with order parameter larger or smaller than the average in the high receptor density simulations . For all other lipid species , including CHOL , the two probabilities are equivalent . Notably , the presence of inactive receptors shifts the overall distribution of the order parameter towards smaller values ( i . e . , higher order ) with respect to the active protomers ( S10 Fig ) . Snapshots of the production runs are shown in S11 Fig for representative high receptor density simulations of inactive and active MOR ( upper and lower panels , respectively ) , and the first 10 μs of a representative inactive trajectory is shown in S1 Movie . All high receptor density simulations show a similar behavior . The lipids closest to the proteins are those that show the broadest distribution of angles . In contrast , in the regions far from the protein , the distribution of order values is much narrower . Thus , the introduction of proteins into a membrane promotes the formation of lipid regions that are either more ordered or more disordered than in the membrane simulated alone . When two receptors get closer together , the lipid regions between them become disordered for the interface to form . We then investigated the interplay between the relative lateral position of protomers and the profile of membrane properties , by calculating , for selected interfaces ( Fig 5 and S12 Fig ) , the average order and thickness of the lipids in the region separating two receptors as a function of the distance from the protein center d and of the relative protein-protein distance r . Not surprisingly , in agreement with the distinct effect of different helices reported above ( Fig 4 ) , the membrane profile is also strikingly dependent on the relative orientation of the proteins . We show this for the two protein regions that are maximally involved in the observed dimers , i . e . TM1 , 2 , H8 and TM5 ( see below ) . Despite both these protein regions favoring the formation of ordered lipid domains , the dependence of such effect on distance is , interestingly , different . In the TM5/TM5 case ( Fig 5A and S12A Fig , for the inactive and active receptors , respectively ) , for well-separated protomers ( r≫r0 , where r0 is protomer average radius ) , the membrane is perturbed up to d≈2 . 5 nm from the protein center , confirming that isolated protomers are accompanied in this case by a stable region of ordered lipids and a thicker membrane . A second regime is established when the protomers are within r≈7 nm of each other and cooperative effects of the nearby protomers start to appear . Thus , each protomer appears to start experiencing the influence of the other one at a distance of ~7 nm , which is larger than the sum of the range of the perturbations for the isolated protomers ( ~2 . 5×2 ≈ 5 nm ) . In contrast , for the TM1 , 2 , H8/ TM1 , 2 , H8 interface , the modulation of the membrane properties when protomers are far from each other ( r≫r0 ) is very weak on average ( Fig 5B and S12B Fig , for the inactive and active receptors , respectively ) , and the lipid ordering arises almost exclusively from cooperative effects when two protomers are closer than r≈6 nm . The results obtained for asymmetric interfaces , e . g . , the TM1 , 2 , H8/TM5 interface ( S12 Fig Panels C and D for the simulated systems with inactive or active receptors , respectively ) are similar to those obtained for symmetric interfaces , although the recorded cooperative effect is weaker for r<6 nm . Since CHOL is a key player in the stabilization of ordered phases in plasma membranes [13] and it flips between leaflets , we investigated its ordering behavior separately . While CHOL does not have a tail , it is possible to calculate an order parameter ( see Methods section for details ) which reveals the orientation of the molecule with respect to the membrane normal ( Fig 6 ) . Since CHOL was seen to flip-flop between the leaflets in all simulations , its order was calculated separately for the headgroup regions and the hydrophobic core of the bilayer . Most of the CHOL molecules in the headgroup region were found to be in ordered regions ( orange in Fig 6 ) , i . e . they were parallel to the membrane normal , but there were regions close to the protein in which CHOL was tilted ( purple in Fig 6 ) , mostly between TM4 and TM5 ( orange and yellow dots , respectively ) . The regions in which the CHOL molecules were tilted roughly correspond to the regions in which the remaining lipids were also disordered ( Figs 3 and 4 ) . On the other hand , CHOL molecules away from the protein were , on average , always ordered ( i . e . , close to parallel to the membrane normal ) , even when the other lipid regions were disordered . In contrast , CHOL molecules in the hydrophobic part of the membrane exhibited a much broader range of order values ( see S13 Fig ) , which are skewed toward 90° . Niemelä et al . used CG simulations to show that the mobility of lipids is reduced when they are in the vicinity of proteins [39] . To assess the mobility of lipids near MOR in the high receptor density simulations with freely moving receptors , local residence times were calculated for the lipids with the largest mole fraction ( i . e . , CHOL and the PC lipids; see S3 Fig ) in the proximity of each helix ( S14 Fig ) . Consistent with their homogeneous distribution around the proteins , the residence time of the PC lipids is similar for all the helices ( ~3 . 5 ns on average ) of both inactive ( blue points in S14 Fig ) and active ( red points in S14 Fig ) MOR . In contrast , the residence time of CHOL differs depending on the helix to which the molecule is in proximity . The CHOL molecules nearest to TM6 stay close to these helices for longer ( ~5–6 ns for inactive and active MOR , respectively ) than the CHOL molecules near the other helices ( ~4 ns , on average ) . The CHOL residence time at TM6 or TM7 is longer for the inactive receptor than the active receptor , possibly due to the outward swing of TM6 upon activation . The only lipids that moved transversely through the bilayer in our simulations , i . e . flip-flopped between the leaflets , were CHOL , CER , and DAG , which are the same lipids that were seen to flip-flop in the published simulations of the plasma membrane without proteins [27] . The rate of CHOL flipping in our low receptor density membrane ( inactive: 7 . 23±0 . 07×106 s-1 , active: 7 . 29±0 . 03×106 s-1 ) was comparable to the rate of 6 . 53±0 . 01×106 s-1 in the plasma membrane without proteins [27] as was the rate of DAG flipping ( inactive: 6 . 34±0 . 30×106 s-1 , active: 6 . 62±0 . 21×106 s-1 , plasma membrane: 5 . 87±0 . 05×106 s-1 ) . The flipping rates of CHOL ( inactive: 3 . 97±0 . 04×106 s-1 , active: 4 . 03±0 . 04×106 s-1 ) and DAG ( inactive: 3 . 38±0 . 39×106 s-1 , active: 3 . 37±0 . 46×106 s-1 ) in the high receptor density membrane were much slower than in the low receptor density membrane and plasma membrane without proteins . Consistent with the very low rate of flipping seen by Ingólfsson et al . [27] , the CER switched leaflets very infrequently , on the time scale of our simulations . To determine the effect of the protein on the equilibrium distribution of these lipids , we used the final 2 μs of the membrane equilibration of the high receptor density simulations to calculate the density of molecules as a function of the z-coordinate of CHOL’s ROH or CER/DAG’s linker beads ( AM1 or GL1 ) and either ( a ) the minimum distance to the backbone ( BB ) beads of inactive or active MOR ( S15 Fig ) or ( b ) the lipid order in the plasma membrane with embedded inactive MOR , embedded active MOR , or no receptors ( Fig 7 for CHOL and S16 Fig for DAG and CER ) . The majority of CHOL molecules were found close to parallel to the membrane normal in both the upper and lower leaflets of the plasma membrane with or without receptors . As also seen in S13 Fig , Fig 7 shows CHOL molecules in the hydrophobic region of the membrane that are perpendicular to the membrane normal . Notably , there are more of these perpendicular CHOL molecules in simulations of the plasma membrane with receptors than without them . To confirm that the CHOL distributions are substantially different near the inactive or active receptors , we repeated the analysis for each individual run and found a similar CHOL density in the hydrophobic part of the membrane for all of them . While the concentration of CHOL in the upper and lower leaflets is asymmetric in the simulations of both the inactive receptors and the plasma membrane without receptors , the distribution of these molecules is symmetric in the case of the active receptors . Lastly , an additional distribution of CHOL at an angle between π/3 and π/4 with respect to the membrane normal is seen only in the simulations of the active receptors . The calculated z-coordinate of CHOL’s ROH beads as a function of their minimum distance from the protein’s BB beads ( S15 Fig ) shows minima in the middle of the bilayer ( -0 . 8 nm < z < 0 . 8 nm ) that are immediately next to the protein ( minimum distance ~0 . 5 nm ) , suggesting that the protein binds CHOL at these sites , consistent with the regions of high cholesterol density seen in Fig 2 . A kinetic model was built to determine whether these minima in the hydrophobic region of the bilayer next to the protein are involved in the flipping mechanism of CHOL . The five most frequently occurring pathways of CHOL movement in the z-direction are shown in S17 Fig . The two largest states ( 6 and 7 in S17 Fig ) in the models for both the active and inactive simulations correspond to CHOL in the upper or lower leaflets , respectively , which have no contacts with the protein . For both the inactive and active protomers , the largest fluxes were between states 6 and 7 indicating that the main route of CHOL flipping is through the membrane away from the proteins . The most probable pathway for a CHOL molecule from the upper to lower leaflet through a bound state is via state 1 for the inactive protomer and state 4 for the active protomer , although the flux is much lower through this pathway than through the membrane . The distributions of CER and DAG lipids were also examined , although these lipids each make up less than 1% of the membrane . The location of the deepest minimum in the plots of the order of DAG lipids as a function of z are different in the simulations of the plasma membrane with or without receptors ( S16 Fig ) . For the inactive receptors , the deepest minimum of DAG lipids is in the middle of the bilayer , while it is in the lower or upper leaflet for the active receptors or membrane without proteins , respectively . In contrast , the distributions of the CER lipids are similar among themselves , except for a shallow minimum in the middle of the bilayer in the case of the simulations of the inactive receptors . Removing the position restraints on the receptor BB beads allowed the receptors to move freely in the membrane and to eventually self-assemble within the initial microseconds of the high receptor density simulations . While a quantitative assessment of the dimer formation kinetics cannot be obtained with our data , the time decay of the number of monomers in the membrane ( S18 Fig ) shows that the inactive system forms aggregates slightly more quickly than the active . However , once formed , the interfaces did not dissociate over the 20 μs of simulation time . To characterize the structural features of the formed complexes , the interfaces formed by the final microsecond of simulation time were clustered by their contact maps . While the simulations do not provide enough statistics to definitively quantify the stability of each interface , their formation or absence is telling . The fraction of interfaces formed is listed in S2 Table and depicted in Fig 8A , 8B and 8C for dimers formed between two inactive receptors , two active receptors , or one active and one inactive receptor , respectively . There is only one interface that was formed by inactive/inactive , active/active , or inactive/active receptors , i . e . irrespectively of the conformation of the participating protomers: TM1 , 2 , H8/TM5 . In this interface , TM2 only forms extracellular contacts with TM5 , while H8 and TM5 form intracellular contacts . For the inactive proteins , nine different interfaces were formed , but over 50% of them involved the TM1 , 2 , H8 region of one protomer and the TM4/TM5 region of the other . In particular , the TM1 , 2 , H8/TM4 , 5 interface constituted the ~15% of the observed interfaces while the similar interfaces TM1 , 2 , H8/TM4 and TM1 , 2 , H8/TM5 made up ~31% and 8% , respectively , of all observed interfaces . In the TM1 , 2 , H8/TM4 and TM1 , 2 , H8/TM5 interfaces , the second protomer is slightly rotated either clock- or counter-clockwise relative to that of the TM1 , 2 , H8/TM4 , 5 interface , such that no contacts are formed with TM5 and TM4 , respectively . In all of these interfaces , TM2 forms extracellular contacts with TM4 , 5 , while the majority of the contacts are formed by TM1 . The inactive receptors formed two interfaces involving TM7 , which were not observed in the active or mixed proteins . In the TM4/TM7 ( ~7% ) interface , TM7 is in contact with TM4 on the intracellular side , while TM7 forms extracellular contacts with TM1 in the TM1 , H8/TM6 , 7 interface ( ~8% ) . The TM1 , 2 , H8/TM1 , 2 , H8 ( ~8% ) , one of the crystallographic interfaces , TM4/TM5 ( ~8% ) and TM5/TM5 ( ~8% ) interfaces were also observed in the simulations of inactive MOR . While the TM5/TM5 interface met our criteria for interface formation ( see Methods section ) , it is not as compact as the other interfaces with some lipid tails located in between the protomers . The most frequently formed interfaces in the simulation of all active MORs are the TM1 , 2 , H8/TM5 , 6 , TM1 , 2 , H8/TM1 , 2 , H8 , and TM1 , 2 , H8/TM5 interfaces which are all seen with approximately the same frequency ( ~25% ) . In the TM1 , 2 , H8/TM5 , 6 interface , TM6 forms contacts on the extracellular side only , which allows the interface to form without preventing the outward swing of TM6 in the active structure . The contacts formed by TM1 and TM2 in the TM1 , 2 , H8/TM1 , 2 , H8 interface are on the extracellular side , while H8 forms contacts on the intracellular side . Another frequently seen interface between active receptors is the TM4/TM4 interface ( ~17% ) in which contacts are formed only by TM4 . Both the TM4/TM4 and TM1 , 2 , H8/TM5 , 6 interfaces were unique to the active protomers . In the case of the dimers in which one protomer was in the inactive conformation and one was in the active conformation , only two interfaces were formed . However , what appeared as a new interface , TM2 , H8/TM4 , was structurally very similar to the TM1 , 2 , 8/TM4 interface formed by inactive receptors except that one protomer was slightly rotated , lengthening the distances between TM1 and TM4 beyond our threshold to form a contact . The TM1 , 2 , H8/TM5 asymmetric interface is the most favored ( ~60% ) and is formed by either an inactive/active or active/inactive combination . The symmetric TM1 , 2 , H8/TM1 , 2 , H8 interface was not formed by the combination of one active and one inactive protomer , which is surprising since it was formed by either two inactive protomers or two active protomers . In the crystal structures of the two conformations , the intracellular ends of TM7 do not overlap , shifting H8 slightly . Thus , formation of the TM1 , 2 , H8/TM1 , 2 , H8 interface in this mixed system may require some adjustments in the position of H8 , which the model is not able to capture due to the elastic network required to maintain the receptor tertiary structure . The highest-order oligomer seen in the simulations was a trimer , but only few of them were recorded . For instance , only three trimers were seen in the simulations of inactive receptors with the following interfaces: 1 ) TM7A/TM4B and TM4A/TM1 , 2 , H8C , 2 ) TM5A /TM5B and TM4A /TM5C , and 3 ) TM4A/TM1 , H8B and TM1 , 2 , H8A/TM4C , where subscripts A , B , and C identify the three protomers participating in the trimer . Only one trimer was seen in simulations of all active receptors , and it consisted of a TM1 , 2 , H8A/TM1 , 2 , H8B interface and a TM5 , 6A/TM1 , 2 , H8C interface . In the mixed-array simulations , one trimer formed as the result of the association of two active receptors ( B and C ) with an inactive receptor ( A ) in the middle . In this configuration , the inactive protomer contributed TM5 to a TM5A/TM1 , 8B interface and TM2 , H8 to a TM2 , H8A/TM4C interface . The distribution of the lipids around frequently occurring interfaces in the inactive ( e . g . , TM1 , 2 , H8/TM4 and TM1 , 2 , H8/TM4 , 5 ) and active ( e . g . , TM1 , 2 , H8/TM5 , 6 , TM1 , 2 , H8/TM1 , 2 , H8 , or TM1 , 2 , H8/TM5 ) dimers was calculated to determine possible correlations between the location of lipids near the protomers and the formation of specific dimeric interfaces . The concentration of the PA , PS , PI , and PIP1-3 lipids in the lower leaflet is too low to draw robust conclusions on any role these lipids play at the interface . While the distributions of the PC , PE , and SM lipids revealed no specific hotspots at dimer interfaces , CHOL molecules were always present at the dimer interfaces for the five interfaces listed above . The model structures in S19 Fig , which are colored according to the probability of a CHOL molecule being in contact with the helices involved in a dimer interface , provide an example of these interactions at the TM1 , 2 , H8/TM4 and TM1 , 2 , H8/TM1 , 2 , H8 interfaces formed between inactive or active receptors , respectively and the residues frequently in contact with the bundle are listed in S3 Table . All of the residues with which CHOL forms contacts for more than 50% of the simulation are on the helical bundle . As seen in S3 Table , four out of five interfaces involving TM1 exhibit contacts of CHOL with A731 . 37 , S761 . 40 , I771 . 41 , and T1202 . 56 . All five interfaces exhibit CHOL contacts with L1162 . 52 and S1192 . 55 . While S1192 . 55 has one of the highest probabilities of being in contact with CHOL when MOR is monomeric , I2425 . 48 is frequently in contact with CHOL in both protomeric and dimeric configurations . The three interfaces involving TM5 have CHOL most frequently bound at I2385 . 44 , F2415 . 47 , I2425 . 48 , M2435 . 49 , and V2455 . 51 .
Studies from several groups [6 , 19 , 40–43] , including ourselves [28 , 44] , have computationally explored the effects of the lipid bilayer on the formation of GPCR complexes . In this work , we further investigate the impact of the lipid environment on the spatio-temporal organization of inactive and/or active MOR employing , for the first time , a more realistic 63-component plasma membrane [27] model . The effects of lipids on protein association in the membrane are classified as either specific ( i . e . , direct ) or non-specific effects [45] . Specific effects refer to possible interactions of individual lipid molecules with specific residues on the protein surface , whereas non-specific effects are attributed to the modulation of the properties of the membrane ( e . g . bilayer thickness ) . Our analysis of MOR simulations shows an interesting interplay between these two types of effects with individual helices of the receptor promoting regions of the membrane with different average order . Specifically , the enrichment of SM at helices TM1 , 5 and 6 promotes regions of ordered lipid molecules next to these helices , while helix TM4 is most frequently adjacent to less ordered regions of the lipid . Recently , Katira et al . [46] suggested a mechanism by which the stabilization of phases with specific order by proteins in a homogeneous membrane can lead to membrane-mediated interactions between proteins . In their model , a disordered phase of a simple DPPC membrane was stabilized around an idealized protein by setting the length of the protein hydrophobic core to be less than the thickness of the surrounding ordered membrane . When two proteins , each surrounded by their own disorder lipid phase , approach each other , it is energetically favorable for the two regions of disordered lipids to merge to minimize the size of the order/disorder interface , resulting in an effective , long-range , induced interaction between the proteins . A similar mechanism appears to be occurring in the MOR simulations reported here . However , in contrast to the homogeneous idealized proteins studied by Katira et al . , MOR in the heterogeneous membrane appears to induce order/disorder depending on the helix and the lipids closest to it . In the complex plasma membrane in our simulations , the hydrophobic length of the individual helices as well as the modulation of the local bilayer compositions by the protein produce specific hydrophobic mismatches that lead to helix-dependent regions of order and disorder . Despite these important differences , the simulations reported here show how ordered lipid regions will tend to coalesce to reduce the energetic cost of merging ordered and disordered regions in the membrane . Although the high-protein concentration in our high receptor density simulations , and the limited length of the low receptor density simulations prevent us from addressing the effect of this mechanism on the translational dynamics of the proteins since the average protein-protein distance is relatively small in our system , it is clear that the lipid order influences the orientation of protomers that eventually come together to dimerize . Specifically , interfaces formed by helices next to order-inducing regions ( e . g . TM1 , 2 , H8/TM5 ) are more frequently formed than those next to disorder-inducing regions ( e . g . TM4/TM4 ) or those next to regions with opposite order preference . At a shorter range , the proteins will then proceed to form bona fide dimeric structures depending on specific residues at the interface , shape complementarity , and physico-chemical properties of the interface . The presence of ordered lipid regions next to helices TM1 , 5 , and 6 fades when the distance between protomers is only a few nm . On the nanometer length scale it is reasonable to assume that shape complementarity and specific interactions start playing a role in dictating the shape of the interaction free-energy and ultimately determining whether an interface can form or not . Thus , whether the helices involved in interface formation induce ordered or disordered lipid regions ceases to play a role once the protomers are close together . Our simulations show an area of high CHOL density near the palmitoylated C1703 . 55 located between TM4 and TM5 of MOR , which had been previously suggested to trap CHOL molecules and to promote dimerization [5] . This palmitoylation site appears to help order the lipids around TM5 in simulations of the inactive but not the active MOR which may explain why the TM5/TM5 interface is formed between inactive but not active receptors . While increasing the lipid order and the membrane thickness near TM4 enhances the propensity of inactive MOR to form a dimerization interface involving this helix , the outward movement of TM6 upon activation appears to affect the ability of this helix to be involved in dimerization of active MOR by virtue of a decreased lipid order and membrane thickness near that helix . The results presented here offer testable hypotheses for experimental investigation . For instance , regions of lipid order immediately next to the MORs are found to be rich in SM , which is known to contribute to ordered regions of a membrane [47] . We find that the polar linker beads of SM lipids associate with polar/charged side chains on TM 5 and 7 of MOR ( e . g . Y2275 . 33 , N2305 . 36 , F3137 . 30 , Q3147 . 31 ) . Mutating these residues to Ala might decrease lipid order and interface formation since the attraction between SM and the protein is predicted to decrease . Lipid rafts have long been thought to compartmentalize cellular processes by contributing to the assembly of signaling molecules [48] . There is support for localization of activated MOR in lipid rafts [32 , 35] , but the involvement of lipid rafts in GPCR signaling is likely dependent on the signaling pathway and the cell type [49] . The plasma membrane used in the simulations reported herein is too small to eventually see formation of lipid rafts , but we can speculate that the ordered/disordered lipid regions mimic the role of lipid rafts in guiding the assembly of receptors , and may also contribute to orienting the receptors so as to guide their interaction with specific regions of the intracellular proteins , e . g . , the G-proteins , that are in contact with the membrane . Transmembrane lipid translocation , or flip-flop , is essential to maintain the required composition of cell membranes . In the simulation reported here , only three lipid types were observed to flip-flop from one leaflet to the other , specifically CHOL , CER , and DAG , which are the same three lipids found to flip-flop in published simulations of the plasma membrane without proteins [27] . Although GPCRs have recently been shown to act as phospholipid scramblases [50] , helping them move from one leaflet to the other , phospholipids did not flip within the 20 μs of our simulations . This is likely due to the timescale of our simulations . Notably , published umbrella sampling simulations of different sets of lipid bilayers showed that the energy barrier for a dipalmitoylphosphatidylcholine ( DPPC ) lipid to flip-flop though a DPPC bilayer is increased by 26 kJ/mol for a 20% CHOL membrane relative to a pure DPPC bilayer [51] . The flipping rate of DPPC was estimated to be on the order of hours in a pure membrane and on the order of years in a DPPC/CHOL membrane . The distribution of CHOL in the hydrophobic region of the bilayer ( S13 Fig , solid lines ) show that the CHOL molecules are either perpendicular to the membrane normal or close to perpendicular , which is consistent with neutron scattering experiments showing the presence of disordered CHOL in a PC membrane with polyunsaturated tails [52] . Previous simulations have shown that CHOL flips in a membrane by first tilting , and then migrating to the middle of the bilayer where it is perpendicular with respect to the membrane normal [53–55] . While we also see CHOL in the middle of the membrane where it is bound to the protein , our kinetic model shows that the main route for CHOL flipping is through the membrane away from the proteins . The mechanism by which transmembrane proteins promote lipid flip-flopping has been attributed to either thinning of the membrane near the protein or the formation of hydrophilic interactions between lipid and protein , both of which would reduce the energy barrier to flipping . Here we see that CHOL flipping via states that are bound to the protein reduces the overall translocation rate , suggesting that the same would be true for other lipids with hydrophilic heads . The dimer structures also showed CHOL bound to the helical bundle . The helices to which CHOL binds when MOR is isolated are not the same helices to which it binds when the receptor is in a dimeric configuration . However , there is no correlation between CHOL bound at specific regions of the helical bundle and dimerization . It is unclear if the CHOL molecules bind an individual protomer before the interface forms or if they insert themselves between protomers after dimerization . The limited statistics of the simulations presented here does not allow us to derive quantitative inferences about the behavior of individual CHOL molecules at the dimer . A new set of simulations is currently being performed to answer this question . The non-sterol lipids which make up the bulk of the membrane ( PC , PE , SM; 60% in the upper leaflet and 53% in the lower leaflet ) show a ring-like distribution around the individual receptor protomers . While some of these zwitterionic lipids are localized around the helices , these preferences are mostly independent of the protein conformation . In contrast , the negatively charged PIP lipids which are present only in the lower leaflet have significant differences in their distribution around the inactive and active conformations supporting experimental inferences that they favor the latter conformation . The PA , PS , and PI lipids all have a charge of -1 , but the PIP1-3 lipids are derivatives of the PI lipids which have been phosphorylated once ( PIP1 ) , twice ( PIP2 ) , or three times ( PIP3 ) and thus have charges of -3 , -5 , and -7 respectively . These lipid distributions are consistent with experimental and computational evidence showing that negatively charged residues promote activation not only in GPCRs [10 , 11 , 56] but also in ion channels and transporters [57] . For instance , in the case of β2AR , the presence of the negatively charged lipid phosphatidylglycerol ( PG ) promoted agonist binding and activation while the neutral PE lipid promoted antagonist binding and the inactive conformation [10] . Recent all-atom MD simulations of β2AR showed that a PG lipid can insert itself inside the receptor between TM6 and TM7 , forming a salt bridge with R3 . 50 and stabilizing active conformations [56] . While the rigidity of the elastic network applied to the coarse-grained receptor structure in our simulations prevents lipids from entering the MOR , the PIP1-3 and PA lipids prefer to localize at the crevice between TM6 and TM7 formed upon activation of the receptor as a result of TM6 swinging outward . The ability of negatively charged lipids to promote activation has also been shown for another GPCR , the neurotensin receptor NTS1 , as coupling between NTS1 and Gq-proteins increased with PG content [11] . The results of our simulations are consistent with a conformation-dependent role of negatively charged lipids in membrane protein function , but due to the low concentration of these lipids in the idealized plasma membrane , we cannot derive a clear conclusion about their role , if any , in oligomerization . Early cysteine cross-linking experiments have suggested that inactive and active GPCRs do form different interfaces [58–60] . The present simulation results show that the interfaces formed by the MOR receptors are also dependent on the conformation of the protein . Specifically , while both the inactive and active receptors formed the TM1 , 2 , H8/TM1 , 2 , H8 , TM1 , 2 , H8/TM4 , and the TM1 , 2 , H8/TM5 interfaces , each conformation also formed mutually exclusive interfaces . Both the inactive and active crystal structures of MOR show dimeric packing interactions involving TM1 , TM2 , and H8 . The Cα RMSD of TM1 and TM2 of the simulated inactive/inactive dimer was 4 . 2 Å ( referenced to the MOR inactive crystal structure 4DKL ) or 2 . 8 Å ( referenced to the MOR active crystal structure 5C1M ) . In the case of the active/active simulated dimer , the RMSD was 4 . 8 Å ( referenced to 4DKL ) or 2 . 9 Å ( referenced to 5C1M ) . Unlike the crystal structure of active MOR , the crystal structure of inactive MOR also showed a symmetric TM5 , 6/TM5 , 6 packing interaction [29] . The fact that this interface is neither seen here nor in previous simulations we carried out on the inactive MOR in a POPC/10% CHOL environment [28] further supports the suggestion that the TM5 , 6/TM5 , 6 interface is either kinetically impaired or it may represent a crystallographic artifact . Similar to the results of our previous simulations of inactive MOR in a POPC/CHOL membrane [28] , the simulations carried out here suggest that interfaces TM1 , 2 , H8/TM1 , 2 , H8 , TM1 , 2 , H8/TM4 , 5 , and TM5/TM5 are likely to form in a mimetic membrane environment . In contrast , the TM1 , 2 , H8/TM5 , 6 and TM4 , 5/TM5 , 6 interfaces seen in the POPC/CHOL membrane did not form between inactive protomers in the 63-component plasma membrane , but we believe that this is most likely due to differences in the modeled intracellular loop 3 ( IL3 ) . Several other GPCR crystal structures show packing interactions that are similar to those seen in our simulations . Both the inactive δ-OR ( DOR , PDB ID: 4DJH ) [61] and inactive β1 adrenergic receptor ( β1AR , PDB ID: 4GPO ) [62] crystal structures form TM1 , 2 , H8/TM1 , 2 , H8 interfaces . The Cα RMSD of the inactive/inactive simulated dimer was 3 . 8 Å relative to DOR and 2 . 8 Å relative to β1AR . Two of the asymmetric interfaces resulting from the simulations of inactive MOR were seen in the crystal packing of chemokine receptors: TM1 , H8/TM6 , 7 in CXCR4 ( PDB ID: 3OE8 ) [63] and TM4/TM7 in CCR5 ( PDB ID: 4MBS ) [64] , with RMSD of 4 . 5 Å and 4 . 4 Å , respectively . Interestingly , the chemokine receptors have been suggested to form heterodimers with MOR [65] . Another interesting observation is that no higher-order oligomers other than trimers are identified in our simulations , but this may be due to our choice of strict interface criteria , which limits the higher-order complexation to trimers in the afforded timescale . In summary , we have performed over 300 μs of CG MD simulations of inactive and/or active MOR in an idealized plasma membrane and concluded that the impact MOR conformation has on dimerization is two-fold . First , the two conformations induce different patterns of order and disorder with merging ordered regions determining protomer orientation with respect to one another . Second , the shape complementarity between different conformations affects both the number and type of interfaces formed . While indirect lipid effects are found to play a major role in receptor dimerization , direct effects through specific lipid-receptor interactions require further investigation .
The inactive and active crystal structures of the mouse MOR ( PDB ID: 4DKL [29] and 5C1M [30] , respectively ) were used as the starting structures after removal of all non-receptor atoms ( e . g . the ligands , as well as the fused T4L lysozyme and the nanobody in the inactive and the active crystal structures , respectively ) . The missing intracellular loop 3 ( IL3 ) of the inactive structure was added using the high-resolution structure of the δ-OR ( PDB ID: 4N6H ) [61] as a template for homology modeling . The N-terminal region of the active structure was removed , while the missing residues of helix 8 ( Η8 ) were added so that both proteins consisted of residues 65 to 352 . All missing residues and side chains were added using MODELLER [66] . The resulting structures were coarse-grained according to the Martini force field version 2 . 1 [67–69] using the martinize . py script . Receptor tertiary structure was maintained with a modified version of the elastic network [70 , 71] . Specifically , a harmonic force was applied between all BB beads within a cutoff of 0 . 9 nm using a force constant of 1000 kJ mol-1 nm-2 for helical residues , or 250 kJ mol-1 nm-2 for residues in unstructured regions . In agreement with experimental inferences [5] , C1703 . 55 ( the superscript follows the Ballesteros-Weinstein numbering scheme [72] ) was palmitoylated by adding four C1 beads with a bond length of 0 . 47 nm and force constant of 1250 kJ mol-1 nm-2 and angles of 180° with a force constant of 25 kJ mol-1 rad-2 . Two membrane sizes were used for the simulations reported in this work . Arrays of 16 coarse-grained proteins were placed in either a large membrane patch of 50×50 nm2 or a smaller patch of 25×25 nm2 , corresponding , respectively , to 6 . 4×103 and 2 . 5×104 receptors/μm2 . We use “low receptor density” to refer to the large membrane patch and “high receptor density” to refer to the small membrane patch . The proteins were evenly spaced , and each of the protomers was randomly rotated around its z-axis . Two types of arrays were created , using all inactive or all active receptors , respectively . For each of the four protein set-ups ( active and inactive conformations , high and low receptor density ) , five sets of arrays were created for a total of 20 starting protein configurations . Furthermore , a third type of array , containing 50% inactive/50% active ( hereafter indicated as “mixed arrays” ) receptors , was prepared ( in five replicas ) for the high receptor density setup , adding 5 more starting receptor configurations . In the case of the mixed arrays , 50% of the proteins were randomly assigned to be inactive , while the others were in the active conformation ( see S20C Fig for an example of an initial configuration of mixed arrays for the high density system , while S20 Fig Panels A and B show examples of all inactive and all active receptor set-ups for the high receptor density systems , respectively ) . Using the insane . py [73] script , the protein arrays were then embedded in a coarse-grained 63-component plasma membrane with the same composition as that obtained by Ingólfsson et al . [27] ( see S3 Fig ) scaled so that the protein to lipid ratio was approximately 1:200 and 1:100 , respectively for the low and high receptor density setups . The total number of lipids in each membrane was approximately 3200 ( or 800 ) in the upper leaflet and 3000 ( or 750 ) in the lower leaflet for the low receptor density ( or high receptor density ) systems . As in Reference [27] , a 2 kJ mol-l nm-2 restraint was placed on the phosphate bead of POPC and PIPC lipids in the upper leaflet in the z direction to prevent large membrane undulations . The height of the box was set to 11 nm . The protein-membrane systems were solvated with water , and ions were added to neutralize the total charge . To provide a direct comparison of the plasma membrane without proteins , the final structure from the 40 μs trajectory of Ingólfsson et al . [27] was retrieved from the Martini force field website ( http://md . chem . rug . nl ) and used as the starting point for a 700 ns trajectory using the same settings as the simulations with the receptors . Following 10 , 000 steps of steepest descent energy minimization , the systems were simulated for 100 ns using a timestep of 10 fs keeping position restraints on the backbone beads of the receptor . To equilibrate the membrane and determine the distribution of the lipids around the individual protomers , each system was run for 5 μs using a timestep of 20 fs , while still maintaining position restraints on the receptors . In preparation for the production run , four 10 ns runs with decreasing restraints on the proteins ( 500 , 100 , 50 , and 10 kJ mol-1 nm-2 ) were performed . The production runs were 20 μs and 3 to 5 μs long for the high receptor density and the low receptor density systems , respectively , giving a cumulative time of over 300 μs for the three simulated protein combinations . The simulations were run in the NPT ensemble , with reference temperature of 310 K controlled with the v-rescale algorithm ( τt = 1 . 0 ps ) [74] , and reference pressure of 1 bar , controlled with the Berendsen algorithm ( τp = 5 . 0 ps ) [75] . The Coulomb interactions between 0 and 1 . 2 nm decayed smoothly to 0 , while the van der Waals interactions between 0 . 9 and 1 . 2 nm decayed smoothly to 0 . All simulations were performed with GROMACS 4 . 6 [76 , 77] . The analysis of the lipids around receptor protomers was performed on the final 2 μs of the membrane equilibration part of the simulation–in which the proteins were kept fixed with position restraints–and on the protomers extracted from the production runs . In the latter , a receptor was considered monomeric if the distance between the center of mass of the protein and every other protein was at least 5 nm . Since the atomic coordinates were recorded every ns and each frame has 16 receptors , each lipid distribution around the receptors was calculated from 5×2000×16 sets of lipid-protein positions . The analysis of the lipids around the dimers was performed on the frames from the final 1 μs of simulation time of the high receptor density production runs , which was also used for interface clustering . The ROH beads of the CHOL or the first linker bead ( GL1 or AM1 ) of the non-sterol lipids were used for the lipid analysis ( see S1 Fig for a depiction of representative lipids ) . Lateral lipid density was calculated by binning the position of the lipid beads into 50×50 square bins with a side of 0 . 2 nm in the membrane plane and calculating the normalized probability distribution . In order to quantify the order and disorder of the lipid tails , the angle between the average membrane normal ( z direction ) and the vector from the linker bead ( AM1/2 or GL1/2 ) to the last bead of the tail was calculated for both tails of each lipid . While the metric used to calculate the lipid order , which is akin to that suggested by Katira et al . [46] , does not follow the traditional definition of lipid order parameter , it is more computationally efficient , and it allows us to use the same metric to characterize the order of non-sterol lipids and CHOL . While CHOL does not have a tail , the angle was calculated between the membrane normal and the vector from the ROH bead to the final bead . For CHOL , the membrane was split in three parts with the middle of the bilayer defined to be 1 . 6 nm thick by plotting the histogram of the z-coordinate of the ROH bead . Order distribution plots were obtained by averaging the order in 1 . 75×1 . 75 Å2 square bins parallel to the xy plane . The local thickness of the membrane was defined as the difference between the average z-coordinate of the linker bead to which the headgroup is attached ( AM1 or GL1 ) in each of the two leaflets , on the same 1 . 75×1 . 75 Å2 grid used to calculate the order . The dependence of the membrane modulation on the relative position of proteins was analyzed by selecting all frames in both the high receptor density and low receptor density production runs with two protomers at a given distance r = ||R1–R2|| ( where R1 and R2 denote the COMs of the two proteins ) , and with relative orientation described by angles α and β in the regions α∈Ωα = [α0–π/6 , α0+π/6] and β∈Ωβ = [β0–π/6 , β0+π/6] , where α0 and β0 specify the region of the two protomers facing the dimerization interface ( 0 or –3/4π , respectively for the TM1 , 2 , H8 and TM5 , 6 , interfaces ) . The position lipid molecules relative to the protomers was described as dvd+nnd in the frame of reference given by the versor vd∝R1–R2 and its normal nd . We report averages of membrane thickness and order over Ωα , Ωβ , and n<r0 ( where r0 = 1 . 7 nm is the average protomer radius ) , as a function of r ( protomer distance ) and d ( lipid position ) . Only frames for which no other protein was found within r0 from the line connecting the COMs ( i . e . , n<r0 ) of the two protomers were included in the analysis . The averages are calculated and reported for d∈[r0 , r–r0] . A kinetic model of the CHOL movement was generated with PyEmma [78] using the contacts formed between the ROH and BB beads to perform the geometric clustering . A hidden markov model was used to kinetically lump the clusters into 8 macrostates . The mean residence time of the lipids around a helix of the monomer was calculated for the production runs together with the last 2 μs of their corresponding equilibration runs . For every lipid , the length of time spent within 1 . 2 nm of any sidechain bead ( SC ) of each helix was calculated in order to obtain a distribution of residence times per lipid species and helix per run . The total mean residence times and standard deviation were obtained by averaging over the distributions from each replica . All interface analysis was performed on the high-density simulations . To characterize the interfaces formed during the production runs , k-means clustering was performed on the final 1 μs of the trajectories , using the Euclidean norm d2 = Tr ( DTD ) of the difference of contacts maps D as a dissimilarity measure . An interface was considered to be formed when at least ten residues on each protomer formed contacts with the other protomer , with a contact defined as two backbone beads lying within 0 . 8 nm of each other . Helices with three or more residues forming contacts were used in the interface name . The relative frequency of each observed interface and their variance were estimated using a multinomial model Xj ~ Multinomial ( n , pj ) , where Xj is the number of observed dimers for interface j and n is the total number of observed dimers . Specifically , the well-known relation to the Poisson model was exploited to rewrite the model as Xj ~ Poisson ( λj ) and pj = λj/∑ λj . We took a Bayesian approach , and sampled the posterior distributions of pj with normal uninformative ( standard deviation 100 ) priors on γj = log ( λj ) using the observed values of Xj for each trajectory . Results are reported as mean and 95% credible intervals . Sampling was performed with the rstan 2 . 8 . 0 interface to the Stan language [79] . The RMSD of the simulated interfaces relative to the crystal structures was determined after aligning the Cα of the two dimers . The RMSD was calculated using only the Cα atoms of the helices participating in the interface to ensure that the RMSD captured only the differences between the interfaces . The structures of the interfaces were rendered in pymol . Scripts for the lipid analysis and interface clustering employed the MDAnalysis python libraries [80] . | The μ-opioid receptor ( MOR ) is an important pharmaceutical target in the treatment of pain . In order to develop novel pain therapies , devoid of the serious side-effects of present opioid analgesics , we need to understand the fundamentals of how MOR works on the molecular level . While some studies suggest that oligomers of MOR could play a role in signaling , how MOR forms dimers , which interfaces form , and the exact role of oligomers in MOR function remain unclear . While research has shown that the membrane environment can affect membrane protein function , most previous computational work to study oligomerization has been performed in a very simple membrane . Here , we use molecular dynamics simulations of MOR in a heterogeneous plasma membrane model ( comprising 63 lipid types ) to investigate how the presence of the protein modulates its lipid environment , affecting species distribution and sculpting characteristic order and thickness profiles around the receptors . Such modulations , in turn , induce long-range interactions between the proteins and favor the formation of specific dimeric conformations . | [
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"sta... | 2016 | Impact of Lipid Composition and Receptor Conformation on the Spatio-temporal Organization of μ-Opioid Receptors in a Multi-component Plasma Membrane Model |
Current sequencing methods produce large amounts of data , but genome assemblies based on these data are often woefully incomplete . These incomplete and error-filled assemblies result in many annotation errors , especially in the number of genes present in a genome . In this paper we investigate the magnitude of the problem , both in terms of total gene number and the number of copies of genes in specific families . To do this , we compare multiple draft assemblies against higher-quality versions of the same genomes , using several new assemblies of the chicken genome based on both traditional and next-generation sequencing technologies , as well as published draft assemblies of chimpanzee . We find that upwards of 40% of all gene families are inferred to have the wrong number of genes in draft assemblies , and that these incorrect assemblies both add and subtract genes . Using simulated genome assemblies of Drosophila melanogaster , we find that the major cause of increased gene numbers in draft genomes is the fragmentation of genes onto multiple individual contigs . Finally , we demonstrate the usefulness of RNA-Seq in improving the gene annotation of draft assemblies , largely by connecting genes that have been fragmented in the assembly process .
Genome comparisons have revealed significant variation in gene family size , both within and between species , e . g . [1]–[7] . This variation can result from either the gain or loss of genes , each of which in turn may be favored by selection . Variation in the number of genes may have important consequences for understanding differences between species , especially for key morphological , physiological , and behavioral traits , e . g . [8] , [9] , [10] . The observed variation in gene numbers may represent genetic diversity resulting from the evolution of gene families [11] , but may also have been incorrectly inferred from sequencing and assembly artifacts . In order to assess the genomic content of a particular species , current methods rely on published genome assemblies . Unfortunately , a major problem in genomics is assembly quality , especially given that it is very difficult to determine the accuracy of de novo assemblies [12] , [13] and the fact that different assembly algorithms may give very different results [14] . Both computational and experimental methods have been applied to improve upon an assembly: computational approaches include innovations in the assembly algorithms themselves , e . g . [15] , as well as methods developed to compare , validate , and gauge the quality of a particular assembly , e . g . [16]–[19] . Experimental approaches have been aimed at improving the connectivity of contigs and scaffolds e . g . [20] , assigning and ordering scaffolds on chromosomes , e . g . [21] , [22] , and validating and refining the annotated genes using RNA data , e . g . [23] , [24] , [25] . Often computational and experimental methods are used in conjunction to improve an assembly , as further experimental evidence will be integrated or reassembled with the original draft assembly , e . g . [26] . Improvements in sequencing technology do not necessarily mean that assemblies as a whole have improved; indeed , shorter reads have increased the computational complexity of the assembly problem , e . g . [27] , [28] and have resulted in more fragmented assemblies ( i . e . there are a larger number of contigs ) . A number of factors confound accurate assembly , including the presence of transposable elements and other repetitive sequences [29] , and the allelic variation present when heterozygous individuals are sequenced , e . g . [30] . Despite these obvious problems the number of assemblies produced is increasing , and thousands of genome sequencing projects are planned or in progress [31] . In many cases , gene annotation from the closest annotated relative will be transferred to these new genomes , and will further propagate the annotation problems to many new genome sequences . Low-quality assemblies result in low-quality annotations [18] , [27] , and these annotation errors cause both the over- and under-estimation of gene numbers , e . g . [32] , [33] . One cause of the over-estimation of gene numbers is the splitting of allelic variation ( i . e . haplotypes present in heterozygous individuals ) into separate loci ( Fig . 1A ) ; we refer to such cases as “split” genes . Split genes appear as highly similar duplicated loci within genome assemblies , and are often placed in tandem to one another or with one copy on a small scaffold by itself , e . g . [34] , [35] . A second cause of the over-estimation of gene numbers is the fragmentation of a single gene onto multiple contigs or scaffolds ( Fig . 1B ) ; we refer to such cases as “cleaved” genes . Because ab initio gene predictors less likely to accurately infer gene models across sequence gaps , genes fragmented onto multiple contigs or scaffolds will be predicted as multiple separate genes , e . g . [30] . Note that gene models may also be cleaved simply because ab initio predictors have failed to join distant exons together in a single transcript , e . g . [36] , [37] , though this type of error may be independent of the underlying assembly quality . A common cause of the under-estimation of gene number is the collapse of truly paralogous gene copies into a single locus ( Fig . 1C ) . This occurs because newly formed duplicates are highly similar in sequence , and therefore hard to assemble as separate loci , e . g . [30] , [38] . A second cause of under-estimation is simply that genes may not be represented in low-coverage genomes due to a large number of gaps ( Fig . 1D ) . In such cases both total gene numbers and the size of individual gene families may be severely underestimated , e . g . [39] . Many genome assemblies and annotations have improved over time due to further efforts aimed at both increasing sequence contiguity and adding functional data ( e . g . RNA-seq ) in order to correct gene models . Individual researchers may also contribute to the deconvolution of specific assembly errors , e . g . [27] , [40] or to the improvement of specific gene models , e . g . [41] , [42] . However , it is often the case that a great deal of research will be based upon the draft assembly before it has reached a finished state , and erroneous conclusions may result , e . g . [40] . As an extreme example , the initial draft human genome contained 223 bacterial genes thought to have been gained by horizontal gene transfer [43] . Closer analysis of this result suggested that many of these cases were simply bacterial contaminants incorrectly assembled into the human genome [44] . As a less extreme example , the initial human genome predicted between 30–40 , 000 protein-coding genes [43] , [45] . As the draft assembly was updated and the gene annotation process was improved , the estimated number of genes in human has continued to fall , and is 20 , 805 as of February 2014 according to Ensembl [46] . This pattern repeats itself for nearly every draft genome , but is especially true of vertebrate genomes because of their size and complexity [28] , [40] . The cascading effects of these errors may affect many downstream conclusions , from inferences about the evolutionary histories of genes to the ability to map genes involved in disease . Although many consequences of low-quality assemblies have been described , e . g . [27] , [28] , [47]–[49] , few analyses have specifically examined the effect on gene copy-number but see [32] , [33] . Because many new , next-generation sequencing technologies are being used to construct genome sequences , we would also like to know the error-characteristics inherent to different platforms . Here we examine gene numbers in multiple genome assemblies , using multiple sequencing technologies , and from multiple species . Our results suggest that low-quality assemblies can result in huge numbers of both added and missing genes , and that most of the additional genes are due to genome fragmentation ( “cleaved” gene models ) . Based on these results we present simulation analyses that suggest that published genomes with surprisingly high numbers of genes may be in error , and further show how these problems can be corrected .
To determine how total gene numbers are affected by genome assembly quality we compared predicted gene models in multiple versions of the chicken genome . We examined five different assemblies that were based on different sequencing technologies and sequencing depths . These assemblies vary in size and average coverage ( Table 1; for more details on these assemblies , see [28] ) . The 2X fosmid-based assembly ( average read length ∼950 bp ) may be considered the least complete assembly , as it is the most fragmented , smallest in size , and has the least coverage of the five assemblies considered . The 13X 454-based assembly of the chicken genome was built with 454 single-end reads ( average length ∼330 bp ) , 3 kb mate-pair inserts , and 20 kb mate-pair inserts using the Newbler assembler . The 82X Illumina-based assembly was built with high coverage of paired-end short-insert reads ( average length 100 bp ) and integrated with inserts of 2 kb in length using the SOAP assembler . The draft chicken reference genome ( v2 . 1 ) was a 6X Sanger-based assembly that was improved with fosmid and BAC-end sequencing and reassembled with the PCAP assembler ( it is also referred to as Galgal3 in some repositories ) . The final assembly used as a reference , the current chicken reference ( v4 . 0; also referred to as Galgal4 in some repositories ) , was a further improvement to version 2 . 1 . This hybrid assembly , which was already covered to 6X with Sanger reads , improved to 6 . 6X with BAC and fosmids , was again reassembled using the following additional 454 sequences: 10X fragment reads , 1 . 7X 3 kb inserts , and 1 . 2X 20 kb inserts; again , the PCAP assembler was used to integrate all the data into the final reference assembly . Although it is of high quality , even this reference is considered a “draft” genome . We predicted genes on each of these five assemblies using the ab initio prediction methods implemented in GENSCAN [50] and Fgenesh [51] . GENSCAN was used with the “eukaryotic” model specified , and Fgenesh was used with the specific model for chicken available in the package . GENSCAN ( Table 1 ) found a greater number of genes than Fgenesh ( S1 Table ) , which typically produced more conservative counts but also more complete gene models . Both gene predictors found tens of thousands of genes for each assembly , and we found that the assemblies with the most scaffolds also had the most predicted genes ( Table 1 ) . However , a great many of the predicted genes ( often more than 50%; Table 1 ) were lacking either a start or stop codon , or both . We suspected that the enrichment of small scaffolds was increasing the number of incomplete predictions , and filtered very small scaffolds ( <1000 bp ) from the assemblies . This decreased the total number of predictions while also providing a greater proportion of complete gene models . We then extracted only complete gene models—those with both start and stop codons—from each set of predictions . This yielded a similar number of predictions ( ∼36 , 000 ) for all but one of the assemblies . That particular assembly was built solely from fosmids and plasmids: it has an average genome coverage of only 2X and is missing roughly 150 Mb relative to the other assemblies; we were only able to extract 20 , 000 complete genes from the predictions on this assembly . The fosmid assembly also has the most total predicted genes ( when including those without both start and stop codons ) as well as the most scaffolds , though both genes and scaffolds were shorter on average than in the other chicken assemblies . As an alternative method to assess assembly quality , we applied the CEGMA pipeline [52] . CEGMA maps a set of core eukaryotic genes to assemblies in order to determine their completeness—that is , how many of them are represented as full-length gene models [53] . This method has been used by the Assemblathon [14] as one measure of the quality of different genome assemblies . Table 2 reports the completeness of CEGMA genes in each of the chicken assemblies analyzed here . The most up-to-date assembly ( v4 . 0 ) shows the highest percentage of full-length CEGMA genes ( 80 . 7% ) , while the fosmid-only assembly shows the lowest ( 14 . 1% ) . As the average gene length in the current chicken annotation is 27 . 8 kb , it is clear that many genes have large pieces missing or are fragmented onto multiple contigs in these assemblies . After clustering the filtered predictions into groups of homologous genes based on sequence similarity ( equivalent to gene families; see Methods ) , we were able to compare gene family sizes in each assembly relative to the predicted sizes in the current chicken reference assembly ( Fig . 2 ) . As expected based on quality and coverage , the fosmid assembly shows the largest deviation in terms of gene family size relative to the reference chicken assembly . For each assembly no more than 60% of all gene families were the same size as in the reference assembly , meaning that the remaining 40% or more of families were inferred to have the wrong size . These gene families were either missing one or more genes relative to the reference or contained one or more additional members relative to the size of gene families inferred from the reference assembly . The fosmid assembly was a clear outlier , with more than half of all gene families missing gene copies relative to the reference . Overall , these results show that different next-generation sequencing technologies have produced assemblies of largely equal quality in terms of gene copy-number , though of course these assemblies have very different coverage levels . For all non-reference assemblies , a huge number of gene families have an incorrect number of copies ( assuming that the current reference is correct ) , which will lead to incorrect inferences about rates of gene family evolution , and false inferences of specific gene gains and losses . We performed a similar analysis on the chimpanzee genome , comparing the original chimpanzee annotation ( Pan_troglodytes-1 . 0 ) with an updated version of the same genome ( Pan_troglodytes-2 . 1 ) . This analysis differs from the chicken analysis in that we relied solely on the published annotations , and therefore improvements to the predicted gene set may be due to improvements to the assembly , improvements to the ab initio gene predictors , and/or additional functional data . However , this analysis also removes the gene-prediction step from our hands , allowing us to evaluate predictions done by the Ensembl pipeline on two different assemblies . We find a similar result in chimpanzee as to that found in chicken , with a large proportion of the gene families having incorrect estimates for the number of genes ( Fig . 3 ) . Overall , 74% of families had the same number of genes in the two annotations , while 26% had either a greater or smaller number of genes . A major difference between the chicken analysis and the results found for chimpanzee is that the most common error in the draft chimpanzee genome was the addition of a single gene rather than the loss . The earlier assembly and annotation had predicted almost 1 , 800 more genes than the updated assembly and annotation . In order to determine the cause of these additions we asked whether the genes in the earlier assembly version were full-length copies of each other ( indicative of split alleles; Fig . 1A ) or were instead made up of two non-overlapping fragments of the full-length gene found in the updated assembly ( indicative of cleaved genes; Fig . 1B ) . We were able to determine the cause of the additional gene in 1 , 693 families ( Methods ) . Of these , 1 , 279 were cleaved genes and 414 were split alleles . This was an unexpected result as the donor chimpanzee , Clint , was heterozygous for over 1 million SNPs [54] and we therefore expected many split alleles; however , the genome also had many gaps , effectively fragmenting it into a large number of pieces . Our results from chimpanzee and chicken suggest that the fragmentation of genomes into thousands of contigs may play a large role in falsely increasing predicted gene numbers . Such assembly fragmentation may have played a part in the extremely large number of genes predicted in several published genomes . For example , the crustacean , Daphnia pulex , has 30 , 907 predicted genes [55] . However , the first draft assembly available for this species is extremely fragmented , with a very low N50 scaffold size ( <400 kb ) , over 5 , 000 scaffolds , and over 19 , 000 contigs [55] . We suspected that the fragmented nature of the draft assembly , in conjunction with the lack of a high-quality genome annotation from a closely related species , was inflating the gene counts . To indirectly test this hypothesis—and to directly examine the effect of fragmentation on predicted gene numbers—we developed a method to produce increasingly fragmented assemblies of the high-quality Drosophila melanogaster genome ( Methods ) . Comparing the genes predicted from these simulated assemblies should reveal the effect of fragmentation . We produced nine simulated D . melanogaster assemblies with between 707 and 17 , 941 contigs , and compared the number of predicted gene models in each . We again applied the GENSCAN and Fgenesh gene predictors , as well as the AUGUSTUS predictor [56] and the MAKER gene prediction pipeline [57] . As expected if fragmentation is a cause of increased gene number , the number of predicted genes in each simulated D . melanogaster assembly increased as the genomes become more fragmented ( Table 2 ) . Strikingly , in the simulated genome with 17 , 941 contigs—each of which has a length drawn from the distribution of contig lengths in the Daphnia pulex genome ( Methods ) —we find 32 , 025 GENSCAN-predicted genes with start and stop codons , a handful more than are present in the published Daphnia pulex genome ( Fig . 4 ) . Although the other predictors all give more modest increases in gene number with increasing fragmentation , they all predict 6 , 000–10 , 000 additional genes on the most fragmented assemblies ( Table 2 ) . When we examined specific genes in our prediction sets we often found them to be cleaved , sometimes into multiple pieces , with single exons or groups of exons isolated on individual contigs . Gene prediction software will often call these exons as genes , and the process of gene prediction in these highly fragmented genomes has essentially become one of exon prediction . Zhang et al . [40] found similar instances of spurious gene calls from cleaved or isolated exons when looking at the draft rhesus macaque assembly and annotation ( see [58] for examples from the pig genome ) . Although these random cleavages of the Drosophila genome may not be a perfect approximation of fragmentation in real assemblies , the increasing fragmentation causes the number of exons per gene in the predicted sets to decline . Comparing the number of exons per gene in the simulated dataset to the number in the reference D . melanogaster genome , we see a huge enrichment for single-exon genes and a general decline in the average number of exons ( Fig . 5 ) . Due to the highly fragmented nature of this assembly almost none of the genes with over a dozen exons have remained full-length , and the longest genes have often been cleaved into more than two predicted genes . While the results of our simulated genomes do not directly demonstrate the causes of the over-prediction of genes in published genomes , they do strongly indicate that genome fragmentation can play an outsized role in this problem . However , although many new genomes are highly fragmented , most do not have such large numbers of predicted genes . So why are there differences in predicted gene numbers ? For many newly sequenced genomes , high-quality genomes from closely related species can be used to improve the assembly [59] , [60] , or to directly improve gene models [61] . In the case of Daphnia pulex there are no closely related complete genomes , and therefore little comparative data for improvement; as expected from severe fragmentation , 22% of annotated Daphnia genes do not have both a start and stop codon . Other data and methods can be used to improve gene annotations , however , and in the next section we show how one such method can be utilized . In addition to data from closely related species and genomes , RNA-seq data ( or any kind of transcript sequencing data ) has been used to improve both genome assemblies [62] , [63] and gene annotations , e . g . [23] , [24] , [25] . RNA-seq offers an effective method for improving an annotation set , especially when a single gene may span multiple contigs [24] . The sequencing of mRNAs is equivalent to sequencing reads with an insert size of the order of intron sizes—because these regions are removed from mRNAs , even large gaps can be crossed if they coincide with introns . In terms of fragmented genome assemblies , the sequencing of mRNAs allows genes cleaved onto multiple contigs to be identified as a single locus , and therefore for inflated gene numbers to be reduced . While gene models from related species offer an alternative method for identifying fragmented genes [61] , RNA-seq can be used for any species , regardless of whether there is a genome with a high-quality annotation that is closely related . To determine the effectiveness of RNA-seq data in restoring fragmented gene models we obtained reads from 11 published experiments in D . melanogaster ( Table 2 ) . After mapping paired-end reads from these experiments back to our simulated assembly with 17 , 941 contigs , we asked whether there were any cases in which two different predicted gene models were uniquely hit by a connected pair of reads . In other words , we looked for pairs of reads for which one hit one predicted gene and the other read hit another predicted gene on a different contig . Even with a single RNA-seq experiment , thousands of predicted genes could be linked by paired-end evidence ( Table 3 ) . Although on average only 2% of paired-ends per experiment met our conditions for connecting genes on different contigs , this small percentage represents hundreds of thousands of total connections . As more RNA-seq datasets were analyzed , many of the same connected exons were identified , but each new dataset also added a significant number of novel connections ( Table 3; this analysis was only carried out once , with individual datasets added in a random order ) . If we require only a single RNA-seq read as evidence of connected exons , almost 12 , 000 predicted genes were removed by combining them with other genes , and the remaining estimate of ∼20 , 000 predicted genes closely resembles the number predicted from the uncut D . melanogaster reference genome ( Fig . 4 ) . Increasing the number of reads required to connect exons before considering them to be in the same gene resulted in a linear decrease in the number corrected ( Table 4 ) . This is to be expected , as even a very large RNA-seq dataset may not have many reads covering the same exon-exon junction; however , increasing the number of required reads may also increase accuracy of inferences [63] . These results demonstrate that RNA-seq can be used effectively to improve gene annotations in highly fragmented genomes . This result is in contrast to the use of microarrays in improving gene annotations , as arrays will only establish that predicted exons are parts of genes , and not unique genes themselves , cf . [55] . It must also be noted that RNA-seq cannot help to improve cases of split alleles ( Fig . 1A ) —in these cases both of the predicted gene models will be full-length , and the RNA-seq data will not contain any information about the nature of the misassembly . Our results suggest that low-quality assemblies may contain a great many added or missing genes , especially as cleavage and separation of genes across multiple contigs hinders the ability of gene predictors to correctly identify genes . We have shown that most additional genes are due to such cleavage , and specific cases examined in the chicken and chimpanzee genomes support this finding . Our simulation analyses of fragmented Drosophila assemblies indicate that published genomes with surprisingly high numbers of genes may be in error , and simply a result of severe fragmentation . Finally , we have found that RNA-seq offers the ability to correct annotation errors that result from such fragmentation , as fragmented predicted genes can be collapsed with paired end information .
Four chicken assemblies of varying quality ( Table 1 ) were obtained from The Genome Institute at Washington University; they are partially described in [28] , [64] . A fifth chicken assembly , the current reference genome ( v4 . 0 ) , was obtained from Ensembl [46] . For each of these assemblies , we first filtered out short scaffolds ( <1000 bp ) before predicting genes using GENSCAN and Fgenesh . We extracted all predicted genes that were considered complete: that is , their sequence contained both a start and stop codon . After using BLAST [65] to compare all GENSCAN genes from all assemblies to one another , the graph clustering algorithm MCL [66] , [67] was used with default parameters to cluster genes into gene families based on these similarity scores . The 29 , 763 gene families resulting from this procedure contained differing numbers of genes from each assembly , including from the current reference assembly . For each gene family the number of genes in each assembly was compared to the number in the reference chicken assembly . Two assemblies and annotations of chimpanzee , Pan_troglodytes-1 . 0 and an updated version of the same genome , Pan_troglodytes-2 . 1 , were obtained from Ensembl ( versions 35 and 56 , respectively ) . The first version was sequenced to 4X using the PCAP assembler [54]; the second version represents an additional 2X coverage from plasmid reads , and reassembly using PCAP . Following the methods described above for chicken , but with the annotated gene models from Ensembl , we again clustered genes from both assemblies into 11 , 959 gene families . For all families with a larger number of members in the low-coverage assembly and annotation , we used BLAST to search full-length gene models from the high-coverage against the predicted set of genes in the family . In order to classify genes as “cleaved” we required that there be at least two complementary gene models in the low-coverage set . That is , we required that genes in the low-coverage annotation be non-overlapping , but to match complementary parts of the full-length models . Multiple genes from the low-coverage annotation that matched both the full-length gene model and each other ( i . e . were overlapping with >95% similarity over 80% of their length ) were classified as “allelic splits . ” We attempted to transform the high-quality , near-complete D . melanogaster assembly into one resembling the Daphnia pulex assembly . In order to do this , we first collected information about the Daphnia pulex assembly from wFleabase ( [68] , http://wfleabase . org/ ) , specifically , the scaffold lengths as well as positions and lengths of all gaps within those scaffolds . This filtered scaffold set contained 5 , 191 scaffolds [68] . However , when we examined the assembled scaffolds we found that nearly 25% of bases were gaps , represented by stretches of N's in the sequence . To understand how gene prediction software would handle such gaps , we manually inserted stretches of N's into the sequence of known D . melanogaster genes , and then predicted genes on the artificially created sequence . We found a limitation in the length of a gap that the gene prediction software could span and still predict a single gene . GENSCAN , for instance , could not predict a single full-length gene across a gap of length 50 or greater . This implies that individual contigs are the fundamental unit useful for predicting genes , and that even individual large scaffolds fragmented into many contigs may result in the over-prediction of genes . We therefore chose 50 bp as a minimum cutoff length for the length of gaps , separating scaffolds into individual contigs when stretches of N's longer than fifty characters were found . Applying this cutoff to the Daphnia pulex assembly revealed 17 , 924 “contigs” useful for gene prediction . Drosophila melanogaster assembly release 5 . 44 was obtained from Flybase [69] , in the form of six chromosome files . Using the distribution of contig sizes found in the Daphnia pulex assembly , we generated 10 simulated D . melanogaster assemblies with different numbers of contigs ( Table 4 ) . To do this , for any specified number , x , of contigs needed for the simulated D . melanogaster genome we took the longest x contigs from the Daphnia pulex assembly . The reference D . melanogaster genome was then fragmented into x pieces by randomly cutting contigs of the lengths drawn from the Daphnia pulex assembly , while ensuring that the entire D . melanogaster sequence was included in each simulated dataset . Because the Daphnia pulex genome is roughly 170 Mb in length ( not including N's ) while the D . melanogaster genome is 138 Mb , we are conservatively excluding the class of extremely small scaffolds found in Daphnia pulex from our simulated genomes . We predicted genes on each simulated assembly using GENSCAN , Fgenesh , AUGUSTUS , and MAKER . Although GENSCAN was used with a pre-specified human model , this has been shown to be sufficient for most eukaryotes e . g . [51] . Fgenesh has a specific Drosophila model , and as a consequence produced much lower gene counts . Paired-end RNA-seq data from an experiment by the Berkeley Drosophila Genome Project [70] , was obtained from the public database ENA ( [71] , http://www . ebi . ac . uk/ena/ ) . These paired end reads were mapped against the simulated D . melanogaster assembly that had ∼18 , 000 contigs using the software BWA [72] with default parameters . Additional processing of the alignment was performed using samtools [73] . We filtered by read quality and mapping quality , and sought connecting paired-end reads where each end mapped to different scaffold . We used the positions of every exon in the predicted gene set for our simulated assembly to determine which exons were associated by the connecting paired-end reads . A set-merging algorithm was applied to chain together connected exons before the resulting gene set was analyzed . | The initial publication of the genome sequence of many plants , animals , and microbes is often accompanied with great fanfare . However , these genomes are almost always first-drafts , with a lot of missing data , many gaps , and many errors in the published sequences . Compounding this problem , the genes identified in draft genome sequences are also affected by incomplete genome assemblies: the number and exact structure of predicted genes may be incorrect . Here we quantify the extent of such errors , by comparing several draft genomes against completed versions of the same sequences . Surprisingly , we find huge numbers of errors in the number of genes predicted from draft assemblies , with more than half of all genes having the wrong number of copies in the draft genomes examined . Our investigation also reveals the major causes of these errors , and further analyses using additional functional data demonstrate that many of the gene predictions can be corrected . The results presented here suggest that many inferences based on published draft genomes may be erroneous , but offer a way forward for future analyses . | [
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"biol... | 2014 | Extensive Error in the Number of Genes Inferred from Draft Genome Assemblies |
Male mammals produce sperm for most of postnatal life and therefore require a robust germ line stem cell system , with precise balance between self-renewal and differentiation . Prior work established doublesex- and mab-3-related transcription factor 1 ( Dmrt1 ) as a conserved transcriptional regulator of male sexual differentiation . Here we investigate the role of Dmrt1 in mouse spermatogonial stem cell ( SSC ) homeostasis . We find that Dmrt1 maintains SSCs during steady state spermatogenesis , where it regulates expression of Plzf , another transcription factor required for SSC maintenance . We also find that Dmrt1 is required for recovery of spermatogenesis after germ cell depletion . Committed progenitor cells expressing Ngn3 normally do not contribute to SSCs marked by the Id4-Gfp transgene , but do so when spermatogonia are chemically depleted using busulfan . Removal of Dmrt1 from Ngn3-positive germ cells blocks the replenishment of Id4-GFP-positive SSCs and recovery of spermatogenesis after busulfan treatment . Our data therefore reveal that Dmrt1 supports SSC maintenance in two ways: allowing SSCs to remain in the stem cell pool under normal conditions; and enabling progenitor cells to help restore the stem cell pool after germ cell depletion .
Mammalian spermatogenesis begins at puberty and most mammals make sperm throughout much of adult life , relying on a pool of spermatogonial stem cells ( SSCs ) ( reviewed in [1] ) . In the mouse , individual SSCs are found among the cohort of GFRα1-positive undifferentiated type A spermatogonia ( Aundiff ) . Aundiff occur as single cells ( Asingle , or As ) , connected pairs ( Apaired , or Apr ) or chains of 4 to 16 cells ( Aaligned , or Aal ) formed by incomplete cytokinesis [1 , 2] . Differentiation begins when Aal cells transition to c-KIT-positive A1 spermatogonia [3] . A1 spermatogonia subsequently undergo five additional rounds of amplifying mitotic divisions accompanied by further differentiation , producing A2 , A3 , A4 , Intermediate ( In ) , and type B spermatogonia . The type B spermatogonia divide and differentiate into preleptotene spermatocytes that undergo meiosis [1] . SSC maintenance requires somatic niche factors including GDNF , which is produced by Sertoli cells and signals through the SSC cell surface receptors RET and GFRα1 [4] . Loss of Gdnf or either of its coreceptors Ret and Gfra1 causes SSC depletion , while overexpression of GDNF causes accumulation of undifferentiated As cells [4–6] . SSC maintenance also is controlled by intrinsic factors including the transcriptional regulator PLZF , whose loss causes a progressive failure of spermatogenesis [7 , 8] . The precise identity of the SSC pool is still being established . The original SSC model , known as the As model , proposed that As cells are definitive stem cells and that formation of chains reflects commitment to differentiation [1 , 9] . However , in recent years , the As model has been challenged and refined by approaches including detailed expression analysis and live imaging . It is now clear that the As population is heterogeneous , with only a subset of As cells normally functioning as SSCs [2 , 10–14] . In addition , two major pools of Aundiff cells can be distinguished by the expression GFRα1 and NGN3 . The GFRα1-positive population contains the great majority of SSC activity [11 , 12] , while the NGN3-positive population normally functions as a pool of transit-amplifying cells that will eventually undergo differentiation and meiosis [15] . Recently , the transcriptional regulator ID4 was shown to be expressed in a small subset of undifferentiated spermatogonia that closely correlate with SSC activity in functional assays , such as transplantation [12 , 16 , 17] . However , the pool of GFRα1-positive cells that includes the SSCs is dynamic . Lineage tracing and live imaging experiments showed that Apr and Aal chains can fragment to generate As cells and shorter chains that are proposed to function as SSCs [2] . Moreover , even NGN3-positive spermatogonia , which normally will proceed to differentiation and meiosis , can form SSCs when the germ line is challenged by stresses such as cytotoxic busulfan treatment or transplantation [2 , 10] . Thus while much SSC activity resides in ID4-positive cells , cell fate commitment in the early spermatogonial lineage is surprisingly fluid . How the interconversion of undifferentiated spermatogonial cell types is regulated to achieve homeostasis and steady state spermatogenesis is yet to be established . DMRT1 is a gonad-specific transcription factor related to the invertebrate sexual regulators Doublesex and MAB-3 and plays a key role in both germline and somatic development in the testis [18] . DMRT1 is expressed in spermatogonia but not in meiotic or postmeiotic germ cells [19] . DMRT1 has at least three distinct functions in male germ cell development in mice . First , during late fetal development on sensitive strain backgrounds DMRT1 acts as a tumor suppressor that promotes mitotic arrest and silences pluripotency genes including Sox2 . Dmrt1 mutant germ cells form testicular teratomas with high incidence in mice of a susceptible strain background [20] and GWAS studies linking DMRT1 to human germ cell cancer suggest that DMRT1 may act analogously in human germ cells [21] . Second , DMRT1 is required perinatally for reactivation of mitosis and migration of prospermatogonia to the stem cell niche and for their subsequent survival [22 , 23] . Third , DMRT1 regulates the mitosis/meiosis decision during adult steady state spermatogenesis: DMRT1 in NGN3-positive progenitor cells promotes spermatogonial proliferation and differentiation and inhibits premature meiotic initiation [24] . In addition to these germ line functions , DMRT1 is required to prevent testicular Sertoli cells from transdifferentiating into their ovarian equivalents , granulosa cells [25 , 26] . In this study we used conditional gene targeting to investigate whether Dmrt1 plays a role in maintaining a functional SSC population . We found that loss of Dmrt1 in putative SSCs caused progressive loss of spermatogenesis that was associated with reduced PLZF expression and loss of ID4- and GFRα1-positive spermatogonia . We also investigated the role of DMRT1 in recovery from spermatogonial depletion and found that DMRT1 is required in Ngn3-Cre expressing spermatogonia for the repopulation of the Id4-GFP-positive spermatogonia after their depletion by cytotoxic busulfan treatment . Our results therefore suggest that DMRT1 plays a dual role in SSC homeostasis , promoting both maintenance and replenishment of the SSC pool . In addition , our data demonstrate that Ngn3-positive spermatogonia can give rise to Id4-GFP positive cells and repopulate the SSC pool under conditions of stress . Based on its diverse and context-dependent functions , we propose a model in which DMRT1 functions as an essential partner for more specialized regulators of male gametogenesis .
DMRT1 is expressed throughout spermatogonial development , in all As through type B spermatogonia , and then it is silenced in preleptotene spermatocytes at the onset of meiosis [19 , 24] . To confirm DMRT1 expression in SSCs , we performed immunofluorescence ( IF ) on wholemount seminiferous tubules from mice carrying a Id4-Gfp transgene [12] , using anti-DMRT1 and anti-SALL4 antibodies . All As and Apr cells expressing Id4-GFP also were positive for DMRT1 and SALL4 ( S1A–S1M Fig ) . To test the role of DMRT1 in SSCs , we sought to conditionally delete Dmrt1 . Because As and short-chain undifferentiated spermatogonia express Oct3/4 [27] we tested a tamoxifen-inducible Oct4-CreER transgene [28] for activity in SSCs . To identify SSCs and detect Cre activity , respectively , we included Id4-Gfp and CRE-responsive Rosa26-tdTomato transgenes [16] . Mice were treated with tamoxifen at postnatal day 8 , when SSCs are abundant [17] and the mechanistically distinct first wave of spermatogenesis has already initiated [15 , 29]; testes were analyzed eight hours later . IF on wholemount seminiferous tubules using an anti-RFP antibody to detect tdTomato showed that many tdTomato-positive As and Apr cells co-expressed Id4-GFP and GFRα1 and thus were putative SSCs ( Fig 1A–1C ) . We also detected short chains of tdTomato-positive Aal cells that expressed GFRα1; some were weakly positive and some negative for Id4-GFP ( Fig 1A–1C ) . We conclude that Oct4-Cre is active in GFRα1-positive undifferentiated spermatogonia including some of the Id4-Gfp positive SSCs . Next we used Oct4-Cre to delete Dmrt1 , comparing Dmrt1flox/+;Oct4-cre/+; tdTomato; Id4-Gfp ( hereafter , “control” ) mice to the same strain homozygous for Dmrt1flox ( hereafter , “mutant” ) . Cre recombination of Dmrt1flox removes the proximal promoter and exon 1 , which contains the DNA binding domain , generating a null allele of Dmrt1 [30] . Four days post-tamoxifen injection ( 4 DPT ) , IF confirmed that DMRT1 was absent from tdTomato-positive As and Apr as well as Aal cells ( Fig 1D–1I ) . To follow the fates of undifferentiated tdTomato-labeled control and Dmrt1 mutant spermatogonia , we traced these cells using IF on sectioned tubules to detect tdTomato and cell type-specific markers , including PLZF ( undifferentiated spermatogonia ) , SOHLH1 ( differentiating spermatogonia ) and SYCP3 ( primary spermatocytes ) . At 10 DPT , tdTomato-positive cells expressing PLZF or SOHLH1 were present in both control and mutant testes ( Fig 2A–2L ) , indicating that in mutants , as in controls , a proportion of undifferentiated spermatogonia could progress to SOHLH1-positive differentiating spermatogonia . At 15 DPT , tdTomato-positive cells expressing SYCP3 were observed in both the control and mutant testes , indicating that Dmrt1 mutant spermatogonia were able to enter meiosis ( Fig 2M–2R ) . The reduced number of SYCP3-positive cells in mutants is consistent with our previous finding that Dmrt1-mutant undifferentiated spermatogonia can enter meiosis but they do so precociously , without completing the normal number of mitotic divisions [24] . Taken together , these data suggest that DMRT1 is not required for differentiation of SSCs or for initiation of meiotic prophase . Next , we asked whether deletion of Dmrt1 in As , Apr and Aal cells impairs SSC maintenance , which would be expected to cause a progressive loss of mutant germ cells . We followed tdTomato-positive cells for a full round of spermatogenesis ( approximately 40 days ) starting at 10 DPT . tdTomato-positive spermatogonia and early spermatocytes were present at 10 DPT ( Fig 3A and 3E ) in both control and mutant testes . In controls , at 15 , 21 and 40 DPT , tdTomato-positive late spermatocytes , round and elongated spermatids were present ( Fig 3B–3D ) . Importantly , all tubules were labeled with tdTomato and all germ cell types became tdTomato-positive in controls by 40 DPT , indicating that spermatogenesis was maintained via tdTomato-positive SSCs . In mutant testes , by contrast , tdTomato-positive cells were completely absent from ~40% of tubules at 21 DPT ( N = 85/213 ) , and from ~60% by 40 DPT ( N = 101/167 ) ( Fig 3G and 3H ) . After 16 DPT , spermatogonia that persisted in mutant testes expressed DMRT1 , indicating that they had escaped deletion by Oct4-cre . Collectively these results indicate that deletion of Dmrt1 in As , Apr and Aal cells causes progressive loss of spermatogenesis that affects all germ cell types . We more closely followed the fate of mutant germ cells by examining expression of Id4-GFP , GFRα1 and tdTomato at 10 and 15 DPT . Many Id4-GFP and tdTomato double-positive cells were present in the control testes at both time points ( Fig 4A–4C and 4I ) but double-positive cells were decreased in the mutants by 10 DPT and were rarely observed in the mutants by 15 DPT ( N>300 tubule sections ) ( Fig 4D–4F and 4I ) . Similarly , IF of wholemount seminiferous tubules revealed that the remaining Id4-GFP- and GFRα1-positive cells in mutant testes were virtually all negative for tdTomato ( Fig 4G and 4H; S2A–S2D Fig ) , indicating that they had escaped inactivation of Dmrt1 . From these results we conclude that deletion of Dmrt1 in As , Apr and Aal cells causes a failure to maintain SSCs . We next investigated how SSCs are lost in mutants . TUNEL labeling at 10 and 15 DPT and activated Caspase3 staining at 12 DPT showed no apparent increase in mutants and did not detect apoptosis of Id4-GFP positive cells , suggesting that loss of spermatogonia in mutants is not due to elevated apoptosis ( S3A–S3J Fig ) . However , apoptosis in SSCs might be infrequent and difficult to detect . We therefore examined the dynamics of spermatogenesis using lineage tracing and BrdU labeling . Specifically , we asked whether SSCs that were tdTomato-labeled by Oct4-Cre continue to contribute to spermatogenesis after Dmrt1 is deleted . In controls , Id4-GFP-positive cells were only rarely BrdU-labeled ( 15 . 3%; N>300 tubule sections ) ; however Id4-GFP negative spermatogonia that were PLZF-positive or c-KIT-positive efficiently incorporated BrdU ( 61 . 9% and 70 . 8% , respectively; N>100 for each staining ) ( Fig 5A–5D ) . This differential labeling provides a means to distinguish between fates of SSCs versus other spermatogonial cell types . Next we injected BrdU at 6 DPT ( N = 3 for each genotype ) , when SSCs were still present in mutant testes , and compared controls and mutants after a 12-day chase . In controls , the SSCs produced a population of BrdU-negative spermatogonia that replaced the differentiating BrdU-positive cells ( Fig 5E and 5H ) . In mutants , we anticipated one of two possible outcomes after the chase . If the BrdU-negative SSCs survived but were not maintained , they would produce a transient population of BrdU-negative spermatogonia that would eventually enter meiosis ( Fig 5F ) . Alternatively , if the BrdU-negative mutant SSCs died , no further BrdU-negative spermatogonia would be formed and remaining germ cells would be primarily BrdU-positive ( Fig 5G ) . We observed the former result ( Fig 5I ) , with many tdTomato-positive ( Dmrt1 mutant ) but BrdU-negative spermatogonia present for at least 18 days after the chase . Because some Id4-GFP negative spermatogonia were BrdU negative this experiment is not definitive . However , based on the lack of detectable apoptosis and the prolonged presence of BrdU negative differentiating spermatogonia , we conclude that the loss of SSCs in Dmrt1 conditional mutants likely is due mainly to failed SSC maintenance/self-renewal rather than cell death . We next investigated the molecular basis of SSC loss in Dmrt1 mutants . A key regulator of SSC maintenance is the transcription factor PLZF , which is expressed in undifferentiated spermatogonia . In Plzf mutants spermatogenesis fails after one round in some tubules [7] , similar to the phenotype of conditional Dmrt1 mutants described above . All PLZF-positive spermatogonia normally express DMRT1 and SALL4 ( Fig 6A–6C ) . IF analysis of Dmrt1 mutant testes indicated that PLZF expression was severely reduced in DMRT1-negative and SALL4-positive mutant spermatogonia relative to nearby SALL4 and DMRT1-positive cells that escaped deletion by Oct4-cre ( Fig 6D–6F ) . Although we cannot distinguish which of the PLZF/SALL4 double-positive cells are SSCs in this experiment , all SALL4-positive cells without DMRT1 had low PLZF expression . We therefore conclude that one function of DMRT1 in undifferentiated spermatogonia is to maintain PLZF expression , and reduced PLZF is likely to be a key contributor to SSC loss in Dmrt1 mutants . ChIP-Seq in intact adult testes showed that DMRT1 binds near Plzf ( Fig 6G ) . Because DMRT1 is expressed both in spermatogonia and Sertoli cells we used a high dose of busulfan ( 30 mg/kg ) to deplete germ cells and repeated the ChIP-seq , asking whether binding was reduced in the absence of germ cells . Indeed , DMRT1 binding was substantially reduced in busulfan-treated testes . Although we cannot distinguish in which spermatogonial cells DMRT1 binds Plzf , this result indicates that most of the binding is germ cell-dependent and therefore DMRT1 may directly activate Plzf in spermatogonia ( Fig 6G ) . The DNA sequence centered under the DMRT1 binding peak contained a DMRT1 consensus half-site rather than the canonical palindromic sequence element ( Fig 6G ) [31 , 32] . The lack of a complete canonical DMRT1 binding sequence suggests that DMRT1 might bind with a non-DMRT partner protein at this site . During steady state spermatogenesis , NGN3 expression marks a transition from strong SSC potential to committed transit-amplifying cells that normally proliferate and differentiate , eventually entering meiosis . Lineage tracing using Ngn3-Cre has shown that NGN3-positive cells only rarely function as SSCs during steady state , but some of them can be induced to form stable SSCs by stresses including transplantation or germ cell chemical depletion using busulfan [2 , 10 , 19] . Thus NGN3-positive spermatogonia have been suggested to provide a reserve stem cell pool for times of stress [10] . Because Dmrt1 is required perinatally to establish SSCs [23] and subsequently for SSC maintenance ( this work ) , we asked whether it also plays a role in replenishment of SSCs from NGN3-positive spermatogonia in response to cytotoxic stress . We used a moderate dose of busulfan ( 20 mg/kg ) to deplete most undifferentiated spermatogonia [33] and tested whether loss of Dmrt1 in Ngn3-Cre expressing cells compromises SSC regeneration . To follow cell fates we again used Rosa26-tdTomato as a lineage tracer and employed Id4-GFP to identify putative SSCs . We first confirmed that in adult mice under steady-state conditions Ngn3-Cre expressing cells rarely contribute to the pool of Id4-GFP positive SSCs . In controls , tdTomato expression activated in Ngn3-Cre-positive undifferentiated spermatogonia could be traced through to elongated spermatids but we detected no tdTomato in Id4-GFP-positive SSCs ( S4A Fig ) . In Dmrt1 conditional mutants , the number of differentiating spermatogonia was severely reduced by precocious meiotic initiation that occurs upon loss of Dmrt1 in NGN3-positive spermatogonia [24] . As in controls , there was no tdTomato labeling of Id4-GFP-positive spermatogonia ( N>200 tubules for each genotype ) ( S4B Fig ) . Thus , in both wild-type and mutant testes , Ngn3-positive spermatogonia normally proceed to meiosis and do not form Id4-GFP-positive SSCs . We next followed the fate of Ngn3-cre positive cells during recovery after busulfan injection . Four-week-old mice were injected with busulfan and examined 60 days post-injection , which should allow full restoration of spermatogenesis [33] . To confirm that Id4-GFP positive cells were lost after busulfan treatment , we quantified the number of Id4-GFP positive cells in cross-sections from untreated and treated control and mutant testes at 7 , 10 and 20 days after busulfan injection . In the untreated control and mutant testes , we detected 1 . 7 and 1 . 4 Id4-GFP positive cells per tubule cross-section , respectively ( N>400 ) , indicating that starting SSC populations were similar . In controls at 7 days post injection we detected 0 . 11 Id4-GFP positive cells per tubule and <0 . 001 at 10 and 20 days ( N>300 ) ( S5 Fig ) . Similarly , in mutant testes at 7 days we detected 0 . 07 Id4-GFP cells per tubule and <0 . 001 at 10 and 20 days post injection , respectively ( N>300 ) ( S5 Fig ) . By 60 days post-busulfan treatment , controls had recovered abundant TRA98-expressing germ cells and spermatogenesis appeared normal in 68% of seminiferous tubules ( 146/216 ) ( Fig 7A ) . All major stages of spermatogonia and spermatocytes were present after recovery , as reflected by expression of PLZF , SOHLH1 and SYCP3 ( Fig 7B–7D ) . The majority of germ cells in the recovered testes of busulfan-treated control mice , including the Id4-GFP-positive putative SSCs , expressed tdTomato ( Figs 7A–7D and 8A ) , indicating that they were derived from Ngn3-Cre-positive spermatogonia . In contrast , 60 days post-busulfan treatment , 95% of mutant seminiferous tubules ( 177/187 ) were completely devoid of TRA98-positive germ cells and lacked Id4-GFP , PLZF- , and SOHLH1-positive spermatogonia along with SYCP3-positive primary spermatocytes ( Figs 7E–7H and 8B ) . While Id4-GFP-positive cells were present in mutants after recovery , all of these were negative for tdTomato , indicating that they had not passed through an Ngn3-positive stage and were not derived from Dmrt1 mutant cells ( Fig 8C ) . A simple interpretation of our results is that replenishment of SSCs from Ngn3-positive cells requires Dmrt1 . However , we considered two other possibilities . First , loss of Dmrt1 may render spermatogonia more susceptible to busulfan treatment , and thus fewer undifferentiated spermatogonia might survive to help replenish spermatogenesis in mutants . To test this possibility , we counted the number of PLZF and SALL4 double-positive undifferentiated spermatogonia at 7 , 10 and 20 days post busulfan treatment in control and mutant mice . At the two earlier time points the number of PLZF/SALL4-positive spermatogonia was similar between controls and mutants ( S5 Fig ) , indicating that undifferentiated spermatogonia were not unusually busulfan-sensitive in the mutants . At 20 days PLZF/SALL4-positive cells were starting to recover in controls but not in mutants . Second , NGN3-positive cells might be able to revert back to SSCs in the mutant but , due to lack of DMRT1 , they would not be maintained and would differentiate . However , there was no evidence of an additional wave of spermatogenesis derived from such cells . Therefore a likely model is that DMRT1 is required in Ngn3-positive spermatogonia for their re-expression of ID4 and re-establishment as SSCs .
Here we have found that Dmrt1 plays two roles , both of which are expected to support SSC homeostasis , as diagrammed in Fig 8D . First , Dmrt1 is required within the SSC pool for efficient maintenance , with mutant SSCs losing PLZF expression and undergoing differentiation , resulting in a progressive loss of spermatogenesis . Second , under cytotoxic stress , Dmrt1 is required in NGN3-positive spermatogonia for renewal of the SSC pool . In vivo lineage tracing and apoptosis assays together suggested that Dmrt1 mutant SSCs do not undergo apoptosis but instead at least some of them lose PLZF expression and undergo differentiation . The resulting deficiency in SSC self-renewal causes a gradual failure of spermatogenesis . While our data suggest that transcriptional activation of Plzf by DMRT1 may be a key component of SSC maintenance , it will be important to identify additional targets of DMRT1 regulation in this cell type . Our results suggesting survival and differentiation of Dmrt1 mutant SSCs contrast with an in vitro study that found depletion of Dmrt1 can cause apoptosis of cultured multipotent germline stem cells [34] . The different behavior of Dmrt1 mutant germ cells in these two studies might reflect differences between the stem cell microenvironment in vivo and in vitro or differences in the specific cell types studied . Given the findings here and those of prior in vivo studies suggesting that DMRT1 function in germ cells is highly context-dependent , different requirements for Dmrt1 in vivo and in cell culture are perhaps unsurprising . Although recovery from busulfan germ cell depletion was documented decades ago [33] , the genetic basis of the process is uncertain . Yoshida and colleagues [35] showed that some NGN3-positive cells can provide SSC function after damage or transplantation . It has been unclear whether damage or transplantation triggers the regeneration of normal SSCs or perhaps instead they trigger formation of a less primitive self-renewing cell population , analogous to that found in the hematopoetic cell lineage [36] . Our lineage tracing data indicate that NGN3-positive cells can give rise to Id4-GFP-positive cells after busulfan-induced cytotoxic stress , suggesting that normal SSCs are restored . These data are in good agreement with a recent study that demonstrated the recovery of ID4-positive cells after busulfan treatment but did not address the source of the new SSCs [17] . The possibility that transit-amplifying germ cells could undergo conditional reversion to SSC function was proposed previously and is consistent with our data [37 , 38] . In this regard SSC recovery may operate analogously to the conditional germ cell regeneration system found in the Drosophila testis [39–41] . However , while lineage tracing shows that the replenished Id4-GFP positive SSCs pass through an Ngn3-positive state , it is important to note that we cannot yet resolve the detailed path by which SSCs are reestablished . The simplest model is that SSCs are replenished by activating latent stem cell potential in the NGN3-positive transit-amplifying cells that normally supply steady-state spermatogenesis . However , it also remains possible that SSCs are not killed by busulfan , but instead they transiently activate Ngn3 in response to germ cell depletion . In such a scenario , the disappearance of Id4-GFP positive cells that we observed after busulfan treatment might reflect a temporary switch from Id4 to Ngn3 expression . Distinguishing between these possibilities will require lineage tracing of ID4-positive cells after busulfan treatment . Also , while lineage tracing showed that Ngn3-positive cells contribute to SSC replenishment , we cannot exclude that Ngn3-negative spermatogonia also can contribute . Regardless of the initial source of the replenishing spermatogonia , our data show that replenishment of Id4-GFP positive SSCs requires DMRT1 activity and involves NGN3-positive spermatogonia , since loss of Dmrt1 in NGN3-positive germ cells led to a complete failure to recover from busulfan treatment . We previously found that loss of Dmrt1 in NGN3-positive spermatogonia during steady state spermatogenesis in essence flips a switch , truncating the spermatogonial differentiation and mitotic proliferation program and sending spermatogonia toward meiosis [24] . DMRT1 promotes spermatogonial proliferation and differentiation by suppressing retinoic acid ( RA ) signaling and transcriptionally repressing the RA target Stra8 [42] . It is possible that DMRT1 acts similarly in replenishment of SSCs: mutant cells may be forced to proceed toward meiosis and thus unable to form SSCs , or they may be unable to remain undifferentiated long enough to reactivate the SSC program . The reduced expression of PLZF in Dmrt1-mutant undifferentiated spermatogonia also seems likely to limit SSC replenishment , either because SSCs cannot be formed or because they cannot be maintained once they are reestablished . Our findings add to a surprisingly long list of essential roles for DMRT1 in germ cells and somatic cells of the gonad . The multiplicity of its functions and their context-dependence strongly suggest that DMRT1 cannot be a purely instructive regulatory factor and must serve a permissive role in some contexts . This context-dependence is particularly clear in spermatogonial development , where DMRT1 promotes maintenance of SSCs , promotes differentiation of NGN3-positive cells during steady state spermatogenesis , and promotes SSC regeneration after germ cell depletion . While some of these functions are likely to be mechanistically related , it seems likely that DMRT1 functionally interacts with other more specialized factors to accomplish these distinct roles . In this view DMRT1 would be an essential partner for regulators that act in specific cell types or physiological conditions . Working with different partners could allow different regulatory outcomes at particular sites under different conditions or could allow recognition of non-canonical DNA sequences , for example the sequence bound by DMRT1 upstream of Plzf . Identifying these hypothetical partners and defining their functions should be informative . In summary , our findings indicate that DMRT1 is an important regulator of SSC homeostasis , acting in two distinct roles . Under normal conditions we suggest that DMRT1 promotes SSC maintenance at least in part by regulating self-renewal via activation of Plzf transcription . After busulfan-induced cytotoxic stress , DMRT1 enables Ngn3-positive germ cells to replenish the SSC pool and restore spermatogenesis . These findings provide a basis to further explore SSC homeostasis and may have relevance to male infertility .
Dmrt1flox/flox mice were bred to either Oct4-CreERT2 [28] ( gift of Dr . Yoav Segal ) or Ngn3-Cre [29]; ( gift of Dr . Shosei Yoshida ) and to Id4-Gfp [12] and Rosa26-tdTomato transgenic mice ( Jackson Laboratories Cat #: 0007914 ) . For experiments involving conditional deletion of Dmrt1 , Dmrt1flox/+ mice were used as controls and Dmrt1flox/flox mice were used as experimentals . Both controls and experimental animals carried the Oct4-cre transgene and were treated with tamoxifen . In busulfan depletion experiments , controls and experimental animals carried the Ngn3-cre transgene and were either Dmrt1flox/+ ( control ) or Dmrt1flox/flox ( experimental ) . Experimental protocols were approved by the University of Minnesota Institutional Animal Care and Use Committee . Immunofluorescence ( IF ) was described [43] . Staining was performed on >5 animals from each genotype . Antibodies are listed in S1 Table . Expression of tdTomato from the cre activity reporter transgene was detected using an anti-RFP antibody . Whole mount IF was described [35] . All whole mount images were captured with a LSM 710 confocal . Staining was performed on >5 animals from each genotype . Antibodies used are listed in S1 Table . BrdU incorporation and TUNEL assay were as described [24] . Busulfan administration was described [35] except that we used 4-week-old male mice and concentration of 20 mg/kg . 4-Hydroxy-tamoxifen injection was described [24] except that mice were injected at postnatal day 8 mice . Chromatin from testes of adult wild-type B6 and 129Sv mixed genetic background mice was cross-linked with formaldehyde , sheared , and immunoprecipitated with anti-DMRT1 antibody as described previously [44] . | The Dmrt1 gene is a deeply conserved gonadal regulator that is expressed in all mitotic germ cells of the mouse , including spermatogonial stem cells ( SSCs ) . We previously showed that Dmrt1 controls the mitosis/meiosis switch in differentiating mouse spermatogonia . Here we have examined the role of Dmrt1 in undifferentiated spermatogonia and found that Dmrt1 plays two crucial roles in sustaining the population of SSCs . First , Dmrt1 is required to maintain the SSC pool during normal conditions: loss of Dmrt1 in SSCs causes loss of the SSC maintenance factor PLZF and differentiation of SSCs . This result suggests that Dmrt1 is necessary for SSC self-renewal . Second , Dmrt1 is required to replenish SSCs after germ line depletion . We found that Ngn3-positive transit amplifying cells normally do not contribute to Id4-positive SSCs , but can do so when germ cells are chemically depleted by busulfan treatment . However , when Dmrt1 is lost in committed progenitor cells the ability to replenish SSCs after cytotoxic stress is completely lost . Our results suggest that Dmrt1 is important for SSC homeostasis and may provide new avenues for SSC manipulation . | [
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"developmenta... | 2016 | DMRT1 Is Required for Mouse Spermatogonial Stem Cell Maintenance and Replenishment |
The control of cutaneous leishmaniasis ( CL ) is facilitated by knowledge of factors associated with the treatment failures in endemic countries . The aim of this evaluation was to identify the potential risk determinants which might affect the significance of demographic and clinical characteristics for the patients with anthroponotic CL ( ACL ) and the outcome of meglumine antimoniate ( MA ) ( Glucantime ) treatment . This current was executed as a cohort spanning over a period of 5 years which centered in southeastern part of Iran . Altogether , 2 , 422 participants were evaluated and 1 , 391 eligible volunteer patients with ACL caused by Leishmania tropica were included . Overall , 1 , 116 ( 80 . 2% ) patients received MA intraleisionally ( IL ) , once a week for 12 weeks along with biweekly cryotherapy , while 275 ( 19 . 8% ) patients received MA alone ( 20 mg/kg/day for 3 weeks ) ( intramuscular , IM ) . The treatment failure rate in ACL patients was 11% using IL combined with cryotherapy plus IM alone , whilst 9% and 18 . 5% by IL along with cryotherapy or IM alone , respectively . Multivariate logistic regression model predicted 5 major associated-risk determinants including male ( odds ratio ( OR ) = 1 . 54 , confidence interval ( CI ) = 1 . 079–2 . 22 , p = 0 . 018 ) , lesion on face ( OR = 1 . 574 , CI = 1 . 075–2 . 303 , p = 0 . 02 ) , multiple lesions ( OR = 1 . 446 , CI = 1 . 008–2 . 075 , p = 0 . 045 ) , poor treatment adherence ( OR = 2 . 041 , CI = 1 . 204–3 . 46 , p = 0 . 008 ) and disease duration > 4 months ( OR = 2 . 739 , CI = 1 . 906–3 . 936 , p≤0 . 001 ) . The present study is the original and largest cohort of ACL patients who treated with MA . A comprehensive intervention and coordinated action by the health authorities and policy-makers are crucial to make sure that patients strictly follow medical instructions . Early detection and effective therapy < 4 months following the onset of the lesion is critical for successful treatment of the patients . Since a significant number of patients are still refractory to MA , reducing man-vector exposure and development of new effective alternative drugs are essential measures against ACL due to L . tropica .
Leishmaniasis is a neglected disease with growing social and public health concern [1] in many parts of the tropical and subtropical countries , especially in the Eastern Mediterranean Basin such as Iran . Cutaneous leishmaniasis ( CL ) is the most prevalent form of the disease which comprises approximately 70–75% of the total global cases [2] . Recent studies demonstrated that CL increased significantly and reached hyper-endemic levels in the Middle East war zones of Afghanistan , Pakistan , Iraq and Syria [3] and concurrently affecting refugees from those areas [4] . It is suggested that if the scarred CL cases are considered in the prevalence estimates of global burden of disease reports ( nearly 40 million cases ) , instead of those simply with active infection ( approximately 4 million patients ) [1 , 5] , then the overall burden of the disease as measured by the Disability Adjusted Life Years ( DALY ) would be increased by a factor of 10 . Two species are mainly responsible for CL in Iran: anthroponotic CL ( ACL ) caused by Leishmania tropica , transmitted by Phlebotomus sergenti and zoonotic CL ( ZCL ) which is caused by Leishmania major and transmitted by Ph . papatasi and small rodents are the main reservoirs primarily in rural life cycle [6] . Currently , there is no vaccine available against any form of leishmaniasis . Control of CL is complex due to the diversity of Leishmania species , biological vectors and reservoir hosts . Various risk determinants play crucial roles in the proliferation of the disease both in respect of increasing incidence rate and spreading of the disease to new foci . Such risk factors consist of environmental modification , host immune status , travel/migration , population displacement , drug resistance and parasite species [5 , 7–9] . Standard treatment of CL is pentavalent antimonial ( SbV ) which is not always effective and resistance have been reported; this is mainly attributed to parasite species , host factors and quality and quantity of the treatment measures [8 , 10–12] . Control of ACL caused by L . tropica is primarily based on early detection of the cases , diagnosis , identification of the causative agent , and prompt treatment of the patients via an effective surveillance system . Given that humans are the only reservoir host , untreated chronic cases such as leishmaniasis recidivans ( lupoid leishmaniasis ) , remain the infective reservoir for the dissemination of the organism [13 , 14] . Over the last decades , chemotherapy using antimonials remains the only and first-choice management approach for various forms of CL . Unfortunately , the compliance of the basic recommended treatment is low , mainly due to the long duration of therapy , toxic effects , painful parenteral administration , poor therapeutic response and the emergence of resistance [10 , 14 , 15] . Cutaneous leishmaniasis response to meglumine antimoniate ( MA ) ( Glucantime ) is rather poor in Iran , treatment failures and relapses [10 , 16 , 17] have been documented following MA treatment from various endemic regions . Public health surveillance personnel could be an essential tool for rigorous case-detection approaches to address critical concerns . This study was aimed to evaluate the associated-risk determinants which might potentially affect the treatment outcome in a major ACL focus in southeastern Iran . We conducted this prospective cohort study reporting on treatment outcomes of ACL due to L . tropica to identify the potentially effective treatment regimen .
The project was reviewed and approved by the Ethics Committees of the Leishmaniasis Research Center and the Institutional Review Board ( IRB ) of Kerman University of Medical Sciences; protocol no . 94/305 and Ethics no . IR . KMU . REC . 1394 . 276 , respectively . A national guideline for management of leishmaniasis was developed based on WHO recommendations . The patients with proven parasitological CL were treated according to the national leishmaniasis guideline free of charge . A short prophylactic and therapeutic educational training program was planned during the first visit of the patients by face-to-face communications to familiarize the patient with the clinical characteristics of the disease , risk-associated factors , treatment approaches , the probable relapses and other possible control measures related to CL . The patients were advised to stick to the follow up schedule and final assessment . Patients , who were suspected of having other diseases , were referred to the Kerman University of Medical Sciences Hospitals for further diagnosis and proper treatment . The patients only received routine diagnosis and treatment free of charge and no extra intervention was performed . The reasons to obtain oral instead of written consent was that the residents were mostly illiterate; moreover , the patients only received routine treatment and if we asked them to sign written consent some of the patients might refuse to participate and receive treatment , although they orally accepted to participate . Since the disease is anthroponotic , the Ministry of Health ( MoH ) emphasizes to treat all patients to prevent further dissemination of ACL . A case report form ( CRF ) was completed for every patient; demographic characteristics including sex , age , nationality and also clinical data such as location , number and dressing of the lesion ( s ) , route and duration of treatment and the outcome of treatment failure and relapse , were recorded . In the CRF , the patient was asked if she/he permits publication of her/his disease information including lesion photo ( s ) . This large scale project was carried out due to recent consecutive earthquakes in southeastern Iran with consequential environmental changes and population displacement . This study was conducted as a cohort study from March 2012 to January 2016 at Dadbin Health Clinic , affiliated with the School of Medicine , Kerman University of Medical Sciences and Kerman Leishmaniasis Research Center , in southeastern Iran . The clinic manages CL patients who referred from different endemic areas of the province . Only patients with the first episode of CL were included to avoid various biases and confounders linked to clinical failure . Male and female patients with all age groups were recruited . The screening profile and treatment outcome is summarized in Fig 1 . Totally , 2 , 422 participants were screened , interviewed and physically examined . At this stage , 218 patients ( 9% ) with a history of chronic or acute diseases were excluded and 2 , 204 patients with suspected CL lesion were referred to the diagnostic laboratory for confirmation . Overall , lesion of 168 ( 6 . 9% ) of the patients was not CL while lesions of 2 , 036 of the patients ( 84 . 1% ) showed a history of CL . Initially , 144 ( 5 . 9% ) of the patients refused to receive treatment , of the remaining ( n = 1 , 892 ) , 501 subjects ( 26 . 5% ) were lost to follow up for the following reasons: migration , death , absence and withdrawal consent n = 231; allergic reaction , acute and underlying chronic diseases , n = 69; non-residents patients from other districts and provinces , n = 119 and those who received other treatment modalities , n = 82 . Overall , a total of 1 , 391 ( 57 . 4% ) eligible patients completed the study ( S1 Checklist ) . Skin scraping tissues were collected from the periphery of an active lesion and two glass slide smears were prepared; one smear was fixed with methanol and stained by Giemsa for direct microscopic examination and the other smear was used for identification of the causative agent using nested-PCR . From a total of 1 , 391 positive smear preparation samples , 207 slide smear preparations were randomly selected for DNA extraction using the high pure Template Purification Kit ( Roche , Germany ) and identification of Leishmania parasite using PCR methods . The nested–PCR assay was basically performed according to the previously described method [18] . Briefly , two consecutive sets of general and specific primers were used for amplification of variable mini circle kinetoplast DNA fragments ( kDNA ) . Products were visualized from the second round of PCR on 1 . 5% gel electrophoresis . The treatment of parasitological proven cases was done by daily administration of 20 mg/kg of MA , at most 3 ampoules per day IM for 21 days . Some of the patients received IL administration of MA into the base of the lesion by a fine gauge needle ( 25G ) , every week for a maximum of 12 weeks along with cryotherapy using liquid nitrogen which was given biweekly for a maximum of 12 weeks [6] . The patients who received IL treatment were actively referred to the designated health centers for injection , and if they did not come to the centers for any reason , the personnel of these centers called them or visited at home . Whilst , in case of systemic injections the ampoules were delivered to the patients to receive the medication in the nearest rural or urban health clinic , although the patients had to deliver their checklists and empty ampoules to the responsible heath personnel indicating the date and the number of injections . The treatment strategy was based on national guideline which was originated from WHO protocol with minor modifications [14] . The criteria for assigning IM route was the number of lesions > 5 and/or lesions ≥ 3 cm in diameter or the lesion close to vital organs . The criteria for cure were complete re-epithelialization of every lesion ( nodule , plaque or ulceration ) following therapy with one or two courses of MA at three months post-treatment follow–up assessment . Treatment failure was defined as patients who demonstrated active lesion ( s ) or relapse at three months follow-up visit . Reappearance of a nodule , plaque or ulceration following cure . Poor treatment adherence was referred to the patients who did not follow the instruction of treatment recommendation or received the medication partially and not according to the national guideline , or the patients who missed the scheduled appointments; although , both groups received two-thirds of the treatment schedules . The data was analyzed using a SPSS software version 21 ( Chicago , IL , USA ) and standard statistical tests were used to assess the significance of the differences between proportion ( χ2 ) and means ( t-test ) . Overall , 10 potential demographic and clinical risk determinants for patients with ACL and MA ( intralesional and intramuscular collectively or alone ) treatment outcome were evaluated . The incidence of MA failure among sexes , age groups , nationality , patients with lesion on the face vs . cases with lesion on other locations , multiple lesions vs . single lesion , lesions' size , lesion dressing , complete treatment adherence vs . poor treatment adherence , duration of lesion ( s ) and patients with IL vs . IM injections . P<0 . 05 was considered as statistically significance . Odd ratio ( OR ) is the ratio of treatment outcome in the patients who received IM MA vs . IL MA injection plus cryotherapy . The univariate logistic regression method was used to analyze variables individually and the probability of variables to be used in multivariate logistic regression . Therefore , variables with p- value <0 . 2 were analyzed by the multivariate for controlling confounding variables and assessment of any possible association . Then , the backward elimination stepwise process was used to obtain the better possible model . Kaplan-Meier curve was used to present survival experience of two treatments ( IL and IM ) over time . Log-rank test was applied to compare survival curves . Analysis of Kaplan-Meier graphical presentation and log-rank test was performed using Stata 14 . 2 .
Eligible patients comprised 701 males ( 50 . 4% ) and 690 females ( 49 . 6% ) . The proportion of male to female population was similar and the majority of the patients were Iranian ( n = 1 , 245 , 89 . 5% ) , whereas the remaining ( n = 146 , 10 . 5% ) were Afghan migrants ( Table 1 ) ( S1 Table ) . There was no significant difference between the demographic characteristics and ACL disease . The mean age of 1 , 391 patients was 25 . 55±19 . 35 years old , equally distributed among those who responded to the treatment ( mean age: 25 . 72±19 . 16 years ) and those who failed to cure ( mean age: 24 . 12±20 . 82 years ) . Clinical characteristics of the patients are presented in Table 1 . Most of the lesions were on the hands ( 47 . 5% ) , followed by the face ( 25 . 4% ) , legs ( 9 . 7% ) and other parts of the body ( 17 . 4% ) ( Fig 2 ) . The majority of ACL patients showed single lesion ( 64 . 0% ) , 19 . 5% showed two lesions and the rest of the patients showed ≥ 3 lesions ( 16 . 5% ) . The mean size of the lesions ( induration or ulcer ) was 14 . 4 mm and most of the lesions were less than 10 mm ( 58 . 0% ) in diameter and the remaining ( 42% ) , > 10 mm . In general , there was no significant difference between the clinical status and the disease . Overall , n = 1 , 116 ( 80 . 2% ) and n = 275 ( 19 . 8% ) received intralesional MA plus cryotherapy and intramuscular MA treatment , respectively . Of those who received the treatment protocol by IL route plus cryotherapy , 91% showed cure , either by one course ( 77 . 7% ) or two courses ( 22 . 3% ) of treatment . In contrast , the cure rate in patients who received systemic MA alone was 81 . 4% including 65 . 2% and 34 . 8% with one or two courses of treatment which was significantly ( p < 0 . 05 ) lesser than those with IL route . A similar proportion of relapse was observed among the two treatment regimens ( IL 24 . 0% vs . IM 25 . 5% ) . Total of 1 , 391 ACL patients 1 , 116 patients who received intralesional MA along with cryotherapy , and 275 patients who received intramuscular MA alone , were assessed for potential demographic and clinical treatment risk determinants ( Table 2 ) . The univariate analysis showed 6 major risk determinants including male ( OR = 1 . 616 , CI = 1 . 144–2 . 282 , p = 0 . 006 ) , age < 25 ( OR = 1 . 485 , CI = 1 . 047–2 . 107 , p = 0 . 027 ) , face ( OR = 1 . 61 , CI = 1 . 124–2 . 307 , p = 0 . 009 ) , patients with poor treatment regimen ( OR = 2 . 541 , CI = 1 . 53–4 . 218 , p≤0 . 001 ) , patient with disease duration , > 4 months seeking treatment modality ( OR = 2 . 706 , CI = 1 . 896–3 . 862 , p≤0 . 001 ) and intramuscular route ( OR = 2 . 313 , CI = 1 . 603–3 . 339 , p≤0 . 001 ) , were significantly associated with the treatment failure ( Table 2 ) . The multivariate regression analysis model confirmed only 5 major risk determinants including males ( OR = 1 . 548 , CI = 1 . 079–2 . 22 , p = 0 . 018 ) than females , lesion on face ( OR = 1 . 574 , CI = 1 . 075–2 . 303 , p = 0 . 02 ) than other anatomical locations , multiple lesions ( OR = 1 . 446 , CI = 1 . 008–2 . 075 , p = 0 . 045 ) than single lesion , poor treatment adherence ( OR = 2 . 041 , CI = 1 . 204–3 . 46 , p = 0 . 008 ) than complete treatment regimen and duration of lesion in the patients referred > 4 months ( OR = 2 . 739 , CI = 1 . 906–3 . 936 , p≤0 . 001 ) than lesion with ≤ 4 months of age , were significantly associated with treatment failure for ACL patients who treated collectively with intralesional administration coupled with cryotherapy plus meglumine antimoniate alone . Among the patients with ACL ( n = 1 , 116 ) , multivariate regression models showed 4 similar risk- determinants: male ( OR = 1 . 708 , CI = 1 . 108–2 . 632 , p = 0 . 015 ) , age <25 years old ( OR = 1 . 865 , CI = 1 . 182–2 . 943 , p = 0 . 007 ) , poor treatment adherence ( OR = 3 . 016 , CI = 1 . 22–7 . 447 , p = 0 . 017 ) and duration of lesion > 4 months ( OR = 2 . 679 , CI = 1 . 745–4 . 112 , p≤ 0 . 001 ) , were significantly associated with the treatment failure ( Table 3 ) . Among the ACL patients ( n = 275 ) , multivariate method validated one identical risk factor consisting of duration > 4 months of the lesion ( OR = 2 . 063 , CI = 1 . 019–4 . 175 , p = 0 . 44 ) was significantly associated with treatment failure ( Table 4 ) . Kaplan-Meier graphical checks revealed that intralesional administration of meglumine antimoniate included cure of the lesion ( s ) more rapidly compared to intramuscular administration . Kaplan-Meier graph showed around 75% of those with intralesional administration cured around four weeks after starting treatment , however this time and percentage for intramuscular administration was around 12 weeks after initiating treatment ( p ≤0 . 001 ) ( Fig 3 ) . The molecular results of nested PCR exhibited that all 207 randomly selected isolates were confirmed to be L . tropica , the causative agent of ACL in the Old World ( Fig 4 ) .
In the present study , the current MA therapy demonstrated an overall cure rate of 89% ( n = 1 , 240/1 , 391cases ) using a combination of IL plus cryotherapy and IM . However , the risk of failure was significantly more common among IM MA treatment ( 18 . 6% ) in comparison with IL route ( 9% ) by only univariate analysis , although the rate of relapse was similar in both routes of therapy . Moreover , the speed of recovery was higher in IL administration than the IM route . Cryotherapy alone is effective to treat CL lesions . This additional therapy could contribute to such a difference [19 , 20] . The mode of action by which cryotherapy destroys cells is compound , it consist of a rapid freeze , which in turn produces extremely damaging intracellular ice creation and ultimately cellular destruction [19] . The failure rate was comparable for ACL-affected patients following the completion of one course of therapy in Central Iran [21] and Peru [22] . On the other hand the treatment failure was different from the patients from Pakistan [23] . These variable ranges of treatment failures are attributed to multiple factors such as Leishmania species , different dosages , treatment schedules and evaluation time [24] . It should be noted that cases of re-infections may be confused with relapse in ACL endemic areas . However , recent evidence substantiates the general notion that recurrence is certainly the cause of leishmaniasis recidivans ( lupoid leishmaniasis; LR ) which is seen in ACL patients following successful treatment [25] . Leishmaniasis recidivans is usually a sequel of ACL infection caused by L . tropica and may last for many years and rarely respond to conventional treatment . Although it is difficult to show amastigotes in the lesion by direct smear microscopy , Leishman bodies remain in the lesion for several sessions of transmission cycles and therefore serve as a source of reservoir parasite to infect female sand flies [14] . An incidence rate of 18 . 7% among ACL cases has already been recorded in endemic foci in school age children [13] and 4 . 7% in all age groups and predominantly in male individuals [26] . A possible explanation for males being at higher risk of treatment failure than females might be attributed to the immunological status of the host . There are fundamental differences in innate and adaptive immune responses of both sexes in the pathogenesis of infectious diseases . Females elicit a more robust and efficient response to a wide range of microbial and parasitic infections [27] . It is clear that an efficient cell-mediated responses is essential for rapid parasite clearance and for maximal efficacy of pentavalent antimonial compounds in the treatment of leishmaniasis [28] . Moreover , such sex-based immunological divergence contributes to variations in the incidence of infectious diseases . The precise association between gender and the risk of CL is complex and needs to be investigated further . The exact reasons for face particularly in males being the main risk factor for treatment failure are not well understood . Based on our findings most of the lupoid leishmaniasis manifestation ( LR ) occurred on the face of male patients . This clinical presentation is a common form of ACL caused by L . tropica in the Old World [13 , 29] . The majority of the LR lesions are highly resistant to pentavalent antimonials [30 , 31] . Several precipitating factors have been implicated as the cause of LR . Male patients with ACL often do not complete the standard course of therapy with MA , largely due to partial treatment adherence . Such low adherence to treatment might be the primary reason for the development of failure . Other contributing factors could be involved in the generation of such resistant features as the result of specific types of immune response , the causative species and even due to particular characteristics of genetic variants . Previous investigations reported two L . tropica genotypes ( Mon-39 and Mon-55 ) from this area [29] . Among determinants of treatment outcome , multiple lesions possibly play an important role in the failure of the disease compared with single lesion . Various studies have already documented that the failure rate considerably increases with each additional skin lesion . Hence , multiple lesions could be a reflex of high parasite burden and , in turn , impair Leishmania clearance [32] . There may be multiple lesions notably when the patient has faced a nest of sand flies as the consequence of multiple female sand flies bites [33 , 34] . In this instance presumably different genotypes with diverse susceptibility levels could be introduced to the susceptible host . Such genotype differences within the same species might behave differently to chemotherapy , as a number of intraspecific genetic variants have already been documented for L . tropica from the same area [7 , 35 , 36] . Also failure caused by patients bearing multiple lesions could be a consequence of a decreased capability of the immune system against the Leishmania species [32] . Adherence to treatment has a profound influence in the consequence of chemotherapy; however , poor compliance declines optimum outcome . The present finding represents that adherence to both treatment modalities ( IL plus cryotherapy and IM alone ) was a major challenge for patients and healthcare providers , as a significant number of cases did not follow advice from the physicians and primary health care providers . This problem remains a limiting factor in the achievement of the therapeutic cure . Various reports indicate that across a wide variety of clinical settings and treatment recommendations , an important number of patients do not comply with the treatment regimen and schedule [37] . Poor adherence to the treatment occurs for a wide variety of reasons including doubt about the expected benefits , efficacy of treatment , unpleasant side-effects , work constraints or economic situation , traveling away from home , feeling sick or depressed and simple forgetfulness [38] . In the present study a considerable number of patients showed difficulty in adhering to their recommended therapeutic regimens . This fact represents the mismanagement of MA in the endemic areas of the present study as major contributor to the development of failure . Treatment failure should be monitored in order to maintain the life time of existing antileishmanial drugs , their delivery and clinical response [15] . It is worth mentioning that cases with shorter durations of lesions ( ≤ 4 months ) showed a lower risk of failure . Importantly , lesions caused by L . tropica have the tendency to undertake chronic course and in some occasions , the lesion develop to LR lesion , which is extremely resistant to standard treatments [13 , 14 , 31] . In addition , management of the disease within few weeks of onset is not beneficial due to inadequate effector response , as this significantly increases the failure rate [22 , 39] . It is found that early treatment within 5 weeks of the infection onset significantly enhances the failure rate to 47% [22] . A previous investigation by Machado and colleagues reported a similar treatment failure ( 46% ) [40] . In general , the problem of treatment failure has been rather neglected in the mainstream delivery of primary healthcare services . A robust commitment to a multidisciplinary approach is necessary in order to make advancement in this area . This will require coordinated action from health professionals , researchers , health providers and policy–makers . Treatment outcome is a multidimensional phenomenon [41] determined by the interplay of compound factors . No single intervention has been shown to be effective for all the patients , conditions and settings . Consequently , physicians and healthcare surveillance systems need to develop means of accurately assessing not only adherence , but also those determinants which contribute to treatment failure [38] . To the best of our knowledge , this cohort study represents the first and largest observation to assess treatment risk determinants in a large scale number of patients with ACL in Iran . The main strength of the present study is CL treatment center with a robust registry system and adequate infrastructure , which manages the patients through a team of well-trained , experienced physicians and health personnel and well equipped diagnostic laboratory facilities , supported by the Leishmaniasis Research Center which is affiliated with the Kerman University of Medical Sciences . On the other hand , the present study had a number of limitations . First , although , CL is a part of primary health care ( PHC ) surveillance system , one limitation was the lack of active case-detection approaches in a systematic manner to follow-up the patients through house–to–house visits due to the vast and remote areas of coverage . An active case-detection strategy could assist in determining the actual burden of ACL in the area . This would help in planning future control strategies . However , the patients had been advised to report any suspected skin lesion resembling CL at the earliest time , following the schedule . Second , another limitation was the low number of patients who received IM therapy in this study . Due to the presence of solitary skin lesions in ACL ( average; 1 . 5 ) ; inevitably , the majority of cases fell in the IL route of administration along with cryotherapy . Third , a considerable number of eligible patients who were primarily screened and entered in the cohort did not meet the inclusion criteria and therefore were excluded ( n = 501/1 , 892 , 26 . 5% ) during the course of treatment and follow up examinations . Nevertheless , the number of patients were considerably high and they came from different areas within the County , as one of the main focus of ACL in the country and this increases the general validity of the study . Four , finally the last caveat has to be mentioned; we randomly confirmed 207 samples that were obtained from the patients ( 14 . 9% out of 1 , 391 ) . Finally , the advance of more effective drugs for the treatment of ACL is extremely important because , at present , chemotherapy is the only measure to control the disease for reducing the reservoir of infection in endemic areas . Combination therapy is now being recommended for many infectious diseases , including ACL . This modality offers the potential of preventing drug resistance , because organisms resistant to one of the drugs may be susceptible to the other drug; and also the potential to diminish drug therapy duration and thus side effects [42] . In conclusion , treatment failure is a complex and multifactorial phenomenon; therefore , a comprehensive intervention and coordinated action by the health authorities and policy-makers are crucial to make sure that patients strictly follow medical instructions . Early detection and effective therapy < 4 months following the onset of the lesion is critical for successful treatment of the patients . Since primary reasons for the major determinants of treatment failure and relapse are not yet well understood , additional efforts is more likely advisable to focus on ACL education and preventive measures which might protect high risk people and reduce man-vector exposure . The present findings also highlight an urgent need for new effective alternative drugs against ACL caused by L . tropica for planning future therapeutic strategies . | Cutaneous leishmaniasis ( CL ) is a serious neglected tropical disease with social stigma and associated disfiguring with health burden , especially in poor endemic regions of the world . Iran is among the seven high burden CL-infected countries . Limited data are available in regarding to CL treatment and related risk determinants . Parasitologically confirmed ACL patients caused by Leishmania tropica were treated over a 5-year period ( 2012–2016 ) , with IL meglumine antimoniate ( MA ) ( Glucantime ) , combined with cryotherapy or with IM MA alone . The objective of this study was to identify the potential risk factors that are associated with response to treatment . The ensuing results with both therapeutic routes identified 5 major risk determinants namely male patients , lesion on face , multiple lesions , poor treatment regimen and disease duration >4 months . The extent to which medical instructions related to patients , therapy and the healthcare system should be seriously monitored . This requires multidisciplinary actions to address specific barriers which directly threaten the treatment outcome . Furthermore , early detection and prompt treatment <4 months following the disease duration together with implementations of public health education and prophylactic measures should receive priority in high risk areas . | [
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"symptom... | 2019 | Associated-risk determinants for anthroponotic cutaneous leishmaniasis treated with meglumine antimoniate: A cohort study in Iran |
CTP synthase ( CTPsyn ) is essential for the biosynthesis of pyrimidine nucleotides . It has been shown that CTPsyn is incorporated into a novel cytoplasmic structure which has been termed the cytoophidium . Here , we report that Myc regulates cytoophidium formation during Drosophila oogenesis . We have found that Myc protein levels correlate with cytoophidium abundance in follicle epithelia . Reducing Myc levels results in cytoophidium loss and small nuclear size in follicle cells , while overexpression of Myc increases the length of cytoophidia and the nuclear size of follicle cells . Ectopic expression of Myc induces cytoophidium formation in late stage follicle cells . Furthermore , knock-down of CTPsyn is sufficient to suppress the overgrowth phenotype induced by Myc overexpression , suggesting CTPsyn acts downstream of Myc and is required for Myc-mediated cell size control . Taken together , our data suggest a functional link between Myc , a renowned oncogene , and the essential nucleotide biosynthetic enzyme CTPsyn .
CTP synthase ( CTPsyn ) is the rate limiting enzyme of the de novo synthesis pathway for the nucleotide cytidine-5’-triphosphate ( CTP ) [1–5] . We and others have observed that CTPsyn is able to form evolutionarily conserved filamentous structures in diverse organisms including C . crescentus , S . cerevisiae , S . pombe and Drosophila as well as mammalian cultured cells [6–11] . These structures have been termed cytoophidia . Recently , it has been demonstrated by independent studies that polymerisation of CTPsyn into cytoplasmic filaments acts to attenuate or activate enzymatic activity in response to various environmental and developmental stimuli [12–15] . The coordination of tissue growth and development requires tight control of cellular homeostasis and metabolism . The production of purine and pyrimidine nucleotides is central to these processes . As the rate-limiting enzyme in pyrimidine synthesis , it is particularly important to understand how CTPsyn is regulated at a transcriptional , translational , and post-translational level . Previously we have shown that reversible compartmentalisation of CTPsyn into cytoophidia is involved in the regulation of developmental processes , neuroblast quiescence and cell cycle re-entry [14] . However , the mechanisms by which cytoophidia assembly and nucleotide metabolism are regulated during developmental processes remain little understood . Cytoophidia are consistently observed in several different cell types in Drosophila [6 , 8 , 9 , 15 , 16] . It has been reported that cytoophidia are highly abundant in both the germline nurse cells and the somatic follicle cells of Drosophila ovaries [17] ( Fig 1A ) . The follicle cell epithelium provides a particularly attractive system in which to study CTPsyn compartmentalisation , as a single large cytoophidium is present reliably during much of oogenesis . It is unsurprising that CTPsyn is required in large amounts in these tissues as they have a high demand for nucleotides due to their role in synthesising nutrients for the developing oocytes . The basic-helix-loop-helix transcription factor , Myc , is essential for the regulation of development in Drosophila larval and adult tissues [18–24] . Myc is highly expressed in the female germline and is required for generating large polyploid cells through the regulation of endoreplication [22] . To gain a greater understanding of cytoophidia function and regulation , we have characterised the formation of cytoophidia in follicle cells throughout oogenesis . Using Drosophila oogenesis as a model system , here we report that Myc regulates cytoophidium formation . We have found that reducing Myc levels results in cytoophidium loss and small nuclear size in follicle cells . Conversely , overexpression of Myc increases the length of cytoophidia and the nuclear size of follicle cells . In addition , we find that cytoophidia can be induced in late stage follicle cells if Myc is ectopically expressed . Furthermore , we show evidence supporting that CTPsyn is required for Myc-mediated cell size control . We conclude that Myc is necessary and sufficient for normal CTPsyn distribution in follicle cells , and that CTPsyn in turn is required for Myc mediated overgrowth .
We previously noted that cytoophidia are consistently observed with a stereotypical distribution in ovarian follicle cells , in which Myc is highly expressed and necessary for cell growth . We decided to investigate the relationship between these two components , initially by further characterising their relative distributions in follicle cells . We stained Drosophila egg chambers with two antibodies specifically against Drosophila Myc ( Fig 1 ) . Both antibodies have revealed that Myc protein levels are high at the germline stem cells and low in cystoblasts at Region 1 ( Fig 1B; S1 Fig ) . This observation is consistent with previous studies [25 , 26] . The biogenesis of follicle cells starts at Region 2 , where follicle stem cells reside . Myc is present at high levels in follicle cells during early- and mid-oogenesis . i . e from Region 2 until Stage 10a ( Fig 1C–1F; S2–S5 Figs ) . Myc levels then drop dramatically at Stage 10b ( Fig 1G; S6 Fig ) and remain low during late oogenesis ( Fig 1H; S7 Fig ) . Cytoophidium formation correlates to Myc expression in Drosophila follicle cells ( Fig 1B–1H ) . Cytoophidia appear at Region 2 where Myc protein levels also increase . Cytoophidia persist in follicle cells during early- and mid-oogenesis , reaching to 4–5 μm at stage 9 and 10a . Coinciding with the dramatic drop of Myc protein at stage 10b , cytoophidia disappear in the majority of stage-10b follicle cells . Cytoophidia remain undetectable in follicle cells during late oogenesis ( i . e . from stage 11 to stage 14 ) . Quantification of cytoophidia length in follicle cells indicates that whilst the length of follicle cell cytoophidia varies throughout oogenesis , cytoophidia length during any particular stage display vary little variation ( Fig 1I ) . It has been reported that the human and mouse orthologues of Myc regulate nucleotide production through expression of nucleotide metabolising enzymes such as CTPsyn in tumour models [27 , 28] . Having observed that CTPsyn and Myc are both highly expressed in Drosophila follicle cells in a similar pattern , we investigated whether Myc is required for cytoophidia assembly . To determine whether Myc has a functional relationship with CTPsyn , Myc levels were knocked down using RNAi in clonal populations in the somatic follicle cell epithelium of the Drosophila egg chambers using two independent UAS driven short hairpin RNAs ( shRNA ) ( Fig 2; S8 Fig ) . Immunostaining with antibodies against Myc confirmed the efficacy of RNAi mediated Myc knockdown ( Fig 2C; S8C Fig ) . Knockdown of Myc resulted in reduced nuclear size ( Fig 2A; S8 Fig ) , consistent with the well-known function of Myc in cell size control . The nuclear area in cells with Myc knockdown is less than half of that in non-clonal cells ( Fig 2I ) , which is consistent with what is known about Myc’s role on cell size . Expression of shRNAs targeting Myc resulted in a loss of visible cytoophidium formation in GFP marked clones compared to the normal filament formation observed in their neighbours ( Fig 2A–2D; S8A–S8E Fig ) . Quantification showed that the length of residual cytoophidia is less than 5% of the length of cytoophidia in neighbouring cells ( Fig 2J ) . The effect of Myc RNAi on cytoophidium disassembly is not limited to mid-stage egg chambers . In follicle cells at early stage egg chambers , we also observed that Myc RNAi results in cytoophdium disassembly ( S9 Fig ) . To further investigate the correlation between Myc levels and CTPsyn , we overexpressed Myc in clones in follicle epithelia . During early- and mid-oogenesis , overexpression of Myc resulted in increased length of cytooophidia . At stage 8 , cytoophidia in follicle cells overexpressing Myc increased about 50% in length compared to those in GFP negative cells ( Fig 3 ) . During late oogenesis , cytoophidia are barely detectable in wild-type cells ( S6 Fig ) . However , Myc overexpression is sufficient to induce cytoophidium formation in late-stage follicle cells ( Fig 4 ) . Overexpression of Myc was confirmed by increased level of Myc protein in clonal cells as revealed by immunostaining ( Fig 4 ) . Cytoophidia observed in all GFP marked Myc overexpression clones in stage 10b can reach 5 μm in length , in contrast to neighbouring cells , which either did not display any cytoophidia , or contained residual cytoophidia with reduced length ( Fig 4 ) . Previous studies have indicated that cytoophidia length can be a function of CTPsyn protein concentration . To determine whether increased cytoophidia prevalence was due to Myc mediated upregulation of CTPsyn expression , we performed qRT-PCR measurements of CTPsyn transcript abundance in Myc overexpressing follicle cells , using a 1-hour heat shock of the inducible driver line ( S10 Fig ) . Although the experimental subjects are clonal in nature ( with the germline not expressing the Myc transgene ) , CTPsyn expression was significantly upregulated when Myc was overexpressed in the follicle cells . Having established that Myc overexpression was sufficient to increase CTPsyn transcript abundance , we asked whether reduction of Myc levels would have a negative effect on CTPsyn transcription . qRT-PCR experiments indicated that CTPsyn transcript levels were indeed reduced when Myc levels were reduced by two RNAi lines ( UAS-Myc-RNAiJF01761 and UAS-Myc-RNAiJF01762 ) . Myc has been shown to be a regulator of organ size in Drosophila . This regulation occurs partly by regulation of cell size through endocycling [21 , 22] . When Myc is overexpressed in a clonal population , the overexpressing cells become much larger than their neighbours ( Figs 3–6 ) . Given that CTPsyn appears to be acting downstream of Myc signalling we asked whether CTPsyn expression was necessary for Myc dependent control of cell size . To answer this question CTPsyn levels were reduced by RNAi in clonal populations of cells also overexpressing Myc . Overxpression of Myc was confirmed by high levels of Myc protein within GFP labelled clones ( Figs 5B , 5D and 6 ) . Ectopic expression of Myc led to cytoophidia with increased length ( Fig 6B and 6D ) . When CTPsyn was knocked down in cells also overexpressing Myc , cytoophidia were no longer detectable indicating effective reduction of CTPsyn levels ( Fig 5B and 5C , cells marked with GFP ) . Quantification of nuclear area of cells that overexpressed Myc , and knocked-down CTPsyn by RNAi ( UAS-Myc , CTPsynRNAi ) revealed that there was a significant decrease in nuclear area compared to Myc overexpression alone ( Fig 5F ) . Nuclear size in UAS-Myc , CTPsynRNAi cells is comparable to neighbouring cells without CTPsynRNAi or Myc overexpression . These results indicate that CTPsyn is required for Myc-dependent cell size control . We also asked whether altering CTPsyn levels alone was sufficient to interfere with follicle cell size control . To determine whether the reduction of CTPsyn alone was sufficient to reduce cell size , we used a previously characterised CTPsyn null mutant to generate mitotic clones in follicle cells [16] . Mutant clones showed no difference in cell size compared to adjacent heterozygous or homozygous cells ( S11 Fig ) . Furthermore , CTPsynRNAi clones alone , also showed no difference in nuclear area ( S12 Fig ) . Surprisingly , we could not detect any overt cellular phenotypes in CTPsyn mutant or RNAi cells . Not only was nuclear area unchanged , but nuclear morphology appeared normal ( i . e . no pyknosis/karyorrhexis indicating apoptotic cell death ) . To determine whether increasing CTPsyn concentration had an effect on nuclear area , we clonally overexpressed Myc in follicle cells . CTPsyn overexpressing cells showed no significant difference in nuclear area . We also observed no difference in Myc staining in CTPsyn overexpressing cells ( S13 Fig ) . Together , these data indicate that an interaction between CTPsyn and Myc is necessary for cell size control , whilst altering CTPsyn levels alone has no effect .
The regulation of nucleotide metabolism during metazoan development must be closely controlled for the proper coordination of growth and organogenesis . Interestingly , both the human orthologue of Myc ( c-Myc ) and CTPsyn have been implicated in tumourigenesis . The proto-oncogene , c-Myc has been previously implicated in mediating aberrant nucleotide synthesis in tumourigenesis [27 , 28] . c-Myc has been shown to be upregulated in a large number of different tumours and it has been proposed to be involved in as many as 80% of human cancers [29] . Similarly , CTPsyn levels have been shown to frequently be elevated in tumour cells and clustered mutations within the CTPsyn locus in Chinese hamster tumours have been associated with increased proliferative capacity [30] . Myc is central to the regulation of Drosophila cell size , cell survival and cell proliferation . It is therefore fundamental for specifying overall tissue size and shape . It is conceivable , therefore , that Myc acts to regulate nucleotide metabolism through CTPsyn , as CTP nucleotides are essential for the synthesis of DNA , RNA and lipids . In a previous study it was noted that several nucleotide metabolising enzymes are upregulated in response to c-Myc expression in a human cancer cell line [28] . Furthermore ChIP-seq experiments have shown that c-Myc binds at the CTPsyn locus in human cells [31] . Several large scale screening studies in fly and human cells have suggested that c-Myc regulates the expression of up to 15% of genes in the genome [32–34] . Although there is evidence to suggest that Myc regulates nucleotide metabolism in tumour models and cell culture , the extent to which this relationship is relevant in normal animal developmental processes , has been less well defined . Our data indicate that Myc regulates pyrimidine synthesis during oogenesis through control of CTPsyn expression and cytoophidia abundance . The control of CTPsyn filamentation via Myc is likely to be complex , with both direct and indirect control mechanisms . Firstly , Myc , a transcription factor that stimulates the expression of all three RNA polymerases [35] , may control CTPsyn expression at a transcriptional level . In support of this , ChIP-seq experiments have identified c-Myc binding sites at the CTPsyn locus in human cells [31 , 36] . Furthermore , microarray experiments have shown CTPsyn downregulation following dMyc knockdown in Drosophila cells , with a predicted E-box Myc-binding motif being present in close proximity to the transcriptional start site [37] . Conversely , some studies have reported no changes being detected following dMyc knockdown [28 , 38] . Our data suggest that CTPsyn expression is indeed under the control of Myc ( S10 Fig ) . Secondly , Myc may also regulate CTPsyn translation . MYC has been shown to directly regulate ribosome biogenesis in Drosophila , and this may have an impact on CTPsyn translation . Both ribosome protein/RNA [39] and CTPsyn upregulation are seen to be a common feature of a number of MYC dependent cancers , while CTPsyn overexpression has been shown to increase filament abundance and size [14 , 16] . In addition to direct transcriptional and translational control , Myc may also control filamentation of CTPsyn on a metabolic level . Myc has been shown to control both glycolytic and glutaminolytic processes that support the energy needs of the cell . However , both glucose and glutamine ( a substrate of CTPsyn ) are also required for nucleotide biosynthesis , so their use as both anabolic and catabolic substrates must be regulated to coincide with the changing demands of the cell [40] . Nutritional stress has been shown to result in cytoophidia formation , whilst the re-addition of key nutrients promotes the subsequent dissociation of the enzyme from the filament . In addition , the inactivation of the Ser/Thr kinase Akt also modifies filament formation in neural stem cells [14] . Akt is a key kinase that both activates and deactivates metabolic proteins in response to changing nutrient availabilities [41] . Changes in Akt activity , in response to changing nutrients or mitogens , have also been shown to increase Myc translation [42] . Furthermore , Myc upregulation has also been shown to increase levels of phospho-Akt in Drosophila [43] . CTPsyn filamentation has been shown to control enzymatic activity [13 , 14] , and CTPsyn stored in the filament may act as a rapidly accessible pool of enzyme that can be used by the cell in response to nutritional changes . How filamentation , and thus enzyme inactivation , is used to help the cell switch between different metabolic programs is now a pertinent direction of inquiry . It is also therefore imperative that the study of how Myc , along with other convergent and differentially regulated factors , regulate CTPsyn filamentation on the post-translational level to maintain metabolic homeostasis . The observation that cells overexpressing Myc are sensitive to changes in CTPsyn levels , whilst cells with endogenous Myc levels are not , has important implications for tumour biology . Our data suggests that cells with abnormal Myc activity may be more affected by CTPsyn inhibition than cells with normal Myc activity . Determining whether this is also the case in tumour cells could yield therapeutic benefits . It will be interesting to see in future studies whether CTPsyn has synthetic lethal properties in Myc-dependent tumours . Interestingly , our data indicate that whilst reducing CTPsyn levels in tissues where Myc is overexpressed is sufficient to rescue the Myc dependent cell size phenotype , CTPsyn knockdown in follicle cells had no obvious effect . This is surprising due to the essential role of CTPsyn in the synthesis of pyrimidine nucleotides , and our previous observations noting that CTPsyn null mutants are lethal at an early stage [16] . Our observations were restricted to narrow time intervals , so it is possible that more noticeable effects may be seen later in the development of mutant clones . Furthermore , it is possible that these cells are able to continue growing normally due to non cell-autonomous contribution of nucleotides from neighbouring cells in the follicle epithelium . It has been shown previously that diffusion may occur through ring canals ( cytoplasmic bridges between adjacent cells ) [44] . Diffusion of CTP through the ring canals may be sufficient to supply follicle cells with the required nucleotides for normal cell growth . However , further study is necessary to identify subtle phenotypes resulting from lowered CTPsyn levels . Previous studies have shown that sequestration of CTPsyn into cytoophidia can downregulate CTPsyn enzymatic activity [12–14] . We showed that this process is involved in developmentally regulated changes in metabolism [14] . Our observation that loss of cytoophidia does not result in severe cellular phenotypes is consistent with these previous observations . Our previous data , together with the evidence presented here , suggests that although large amounts of CTPsyn are present within the follicle cells , the majority is inactive and compartmentalised into cytoophidia throughout much of oogenesis . There is a dramatic reduction in observable cytoophidia during stage 10a-b follicle cells ( Fig 1I ) . This period corresponds to the rapid growth and start of chorion gene amplification [45] . We speculate that previously inactive CTPsyn becomes diffuse and enzymatically active to facilitate growth and rapid chorion gene amplification by upregulating nucleotide production . Further study will be required to determine the cellular stimuli which initiate this change in CTPsyn localisation . That observation that upregulation of Myc signalling promotes cytoophidia formation whilst increasing cell growth , initially seems paradoxical due to the fact that CTPsyn enzymatic activity is downregulated by filament formation . However , we previously showed that filamentous and diffuse CTPsyn exist in equilibrium , with more enzyme sequestered as protein concentration increases . It was shown that as CTPsyn concentration increases , both diffuse CTPsyn concentration and cytoophidia length increase . However , the ratio of free CTPsyn to filamentous increases only modestly as protein concentration is increased , thereby buffering intracellular CTP pools within narrow limits ( within around three-fold ) [13 , 14] . Therefore , it seems that cellular overgrowth driven by Myc overexpression results in a relatively small increase in active CTPsyn , which is nonetheless required for increased cellular growth . It is likely that in Myc overexpressing cells , surplus CTPsyn continues to be sequestered in cytoophidia due to toxicity of CTP concentrations in excess of the constraints imposed by filament formation . In conclusion , our data describe the interplay between Myc and the essential pyrimidine biosynthesis enzyme , CTPsyn , in the regulation of Drosophila tissue development . These results suggest that Myc regulates the coordination of cellular growth and metabolic regulation through transcriptional control of nucleotide biosynthetic enzyme expression and filament formation . Furthermore , this study may help to provide fresh insights into the aetiology of cancers by establishing a connection between two major factors implicated in tumourigenesis .
All stocks were maintained at 25°C on standard Drosophila medium ( 80g/l maize , 18g/l dried yeast , 10g/l soya flour , 80g/l malt extract , 40g/l molasses , 8g/l agar , 6 . 6ml acid mix ) . w1118 ( Bloomington stock centre ) was used as a wild-type control unless stated otherwise . All RNAi stocks were from the TRiP collection ( Bloomington stock centre ) . For ovary dissections , flies were fed with wet yeast for at least one day before dissection to ensure reasonable numbers of egg chambers at all stages . All tissues were dissected into Grace’s Insect Medium , fixed in 4% paraformaldehyde in PBS for 10 minutes and washed with PBT ( 1X PBS + 0 . 5% horse serum + 0 . 3% Triton X-100 ) . Tissues were incubated in primary antibodies at room temperature overnight , washed with PBT then incubated at room temperature overnight in secondary antibodies . Primary antibodies used were rabbit anti-CTPsyn ( Santa Cruz 134457 ) , goat anti CTPsyn ( Santa Cruz 33304 ) , rabbit anti Drosophila Myc ( d1-717 , Santa Cruz 28207 ) and rabbit anti Drosophila MycN ( d46-507 , Santa Cruz 28208 ) . Secondary antibodies used were: donkey anti-rabbit Cy5 ( Jackson 711-175-152 ) , donkey anti-goat Cy5 ( Molecular Probes A11055 ) , donkey anti-goat 549 ( Jackson 711-585-152 ) . Hoescht 33342 ( 1μg/ml ) was used to label DNA . All samples were imaged using a Leica SP5II confocal microscope . All UAS “flip-out” clones were generated using the inducible driver: HsFLP , UAS-GFPnls; UAS-Dcr2; tub>GAL80>GAL4 / SM5 , Cyo-TM6 , Tb . Virgin females of this genotype were crossed to males with UAS-shRNA or UAS-ORFs for clonal knockdown or overexpression respectively . Males from the following genotypes have been used in this study: Progeny were heat shocked at 96 hours after egg deposition for follicle cell clones . For follicle cell clones female flies without curly wings were selected after eclosing and fed with wet yeast for 24 hours before dissecting . Gal4 expressing clones were identified by presence of nuclear GFP marker . CTPsyn mitotic clones were generated using FLP induced mitotic recombination as previously detailed [46] . w HsFlp; Ubi-GFP FRT2A virgin females were crossed to w; CTPsynd06996 FRT2A / Cyo males to generate heterozygous progeny in which recombination could occur . Larvae were heat shocked at 37°C for 45 minutes at 96 hours after egg deposition ( AED ) to produce follicle cell clones . Upon eclosing , non-curly flies were selected and fed wet yeast for 24 hours before dissection . Mitotic clones were identified by absence of GFP . Image processing and analysis was conducted using Leica Application Suite Advanced Fluorescence Lite and ImageJ . Nuclear areas are expressed as a ratio of the average nuclear area in GFP marked clones to neighbouring cells ( GFP negative ) . For each genotype over 50 cells were quantified from at least three egg chambers derived from separate animals . ANOVA was performed to check for significant differences between data groups . Significant differences were attributed for p<0 . 05 . Total RNA was prepared from cells using the miRNeasy kit ( Qiagen ) as per manufacturer’s instructions . 1 μg of RNA was used for reverse transcription using the QuantiTect Reverse Transcription Kit ( Qiagen ) . For qRT-PCR , the cDNA was diluted 1:10 , mixed with primers and SYBRGreen Jumpstart Taq readymix ( Sigma ) and amplified using Applied Biosystems Fast Real-Time PCR platform , using the primers: for CTPsyn , GAGTGATTGCCTCCTCGTTC and TCCAAAAACCGTTCATAGTT; and for rp49 , GCTAAGCTGTCGCACAAA and GAACTTCTTGAATCCGGTG . The Ct values for CTPsyn were normalised with rp49 , and ΔΔCt values were calculated . The data was calculated using at least two independent biological replicates , each of which utilised three technical replicates . | The coordination of metabolism with cell growth is critical for regulation of organismal development . Therefore there is significant interplay between metabolic enzymes and key developmental regulators such as transcription factors . The enzyme CTP synthase ( CTPsyn ) is essential for metabolic homeostasis as well as growth and development , due to its role in synthesising precursors for many fundamental cellular macromolecules such as RNA and lipids . However , the mechanisms by which CTPsyn is regulated during development are little understood . Here we have shown that Myc , an oncogene and a key developmental regulator , is necessary and sufficient for the assembly of CTPsyn-containing macrostructures termed cytoophidia . We show that the presence of CTPsyn is required for Myc to mediate its effect on cell growth during Drosophila oogenesis . Roles for CTPsyn and Myc in tumourigenesis have been well established and both proteins have been considered promising therapeutic targets . By better understanding the relationship between these two proteins , we can gain important insights , not only into tumour pathology and aetiology , but also metazoan developmental processes . | [
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"tech... | 2016 | The Interplay between Myc and CTP Synthase in Drosophila |
Hepatitis C virus ( HCV ) infection is a leading cause of chronic liver diseases and hepatocellular carcinoma ( HCC ) and Golgi protein 73 ( GP73 ) is a serum biomarker for liver diseases and HCC . However , the mechanism underlying GP73 regulates HCV infection is largely unknown . Here , we revealed that GP73 acts as a novel negative regulator of host innate immunity to facilitate HCV infection . GP73 expression is activated and correlated with interferon-beta ( IFN-β ) production during HCV infection in patients’ serum , primary human hepatocytes ( PHHs ) and human hepatoma cells through mitochondrial antiviral signaling protein ( MAVS ) , TNF receptor-associated factor 6 ( TRAF6 ) and mitogen-activated protein kinase kinase/extracellular regulated protein kinase ( MEK/ERK ) pathway . Detailed studies revealed that HCV infection activates MAVS that in turn recruits TRAF6 via TRAF-interacting-motifs ( TIMs ) , and TRAF6 subsequently directly recruits GP73 to MAVS via coiled-coil domain . After binding with MAVS and TRAF6 , GP73 promotes MAVS and TRAF6 degradation through proteasome-dependent pathway . Moreover , GP73 attenuates IFN-β promoter , IFN-stimulated response element ( ISRE ) and nuclear factor κB ( NF-κB ) promoter and down-regulates IFN-β , IFN-λ1 , interleukin-6 ( IL-6 ) and IFN-stimulated gene 56 ( ISG56 ) , leading to the repression of host innate immunity . Finally , knock-down of GP73 down-regulates HCV infection and replication in Huh7-MAVSR cells and primary human hepatocytes ( PHHs ) , but such repression is rescued by GP73m4 ( a mutant GP73 resists to GP73-shRNA#4 ) in Huh7-MAVSR cells , suggesting that GP73 facilitates HCV infection . Taken together , we demonstrated that GP73 acts as a negative regulator of innate immunity to facilitate HCV infection by interacting with MAVS/TRAF6 and promoting MAVS/TRAF6 degradation . This study provides new insights into the mechanism of HCV infection and pathogenesis , and suggests that GP73 is a new potential antiviral target in the prevention and treatment of HCV associated diseases .
Innate immune response is critical for host defense against microbial infection including bacteria , fungi and viruses . Upon microbial infection , pathogen-associated molecular patterns ( PAMPs ) are recognized by pattern recognition receptors ( PRRs ) , which lead to the production of type I interferons ( IFNs ) , proinflammatory cytokines and downstream effectors [1] . Among PRRs , Toll-like-receptors ( TLRs ) and RIG-I-like receptors ( RLRs ) recognize viral RNAs . Certain TLRs detect viral RNA in endosome , such as TLR3 senses viral double-stranded RNA ( dsRNA ) and TLR7/8 recognizes single-stranded RNA ( ssRNA ) [2 , 3] . While RLRs , including retinoic acid inducible gene I ( RIG-I ) and melanoma differentiation-associated gene 5 ( MDA5 ) , sense viral RNA in the cytoplasm , which in turn recruit and activate mitochondrial antiviral signaling protein ( MAVS ) [4–7] . MAVS further recruits TNF receptor associated factors ( TRAF2/3/5/6 ) to activate nuclear factor κB ( NF-κB ) and interferon regulatory factors ( IRF3/7 ) leading to the production of IFNs and cytokines [1 , 8 , 9] . Hepatitis C virus ( HCV ) infection is a major cause of chronic liver diseases , chronic hepatitis , fibrosis and cirrhosis , which have a marked risk of developing hepatocellular carcinoma ( HCC ) [10] . HCV contains a 9 . 6-kb positive-sense RNA genome encoding a 3000-amino acids polyprotein that is cleaved into four structural proteins ( Core , E1 , E2 and P7 ) and six nonstructural proteins ( NS2 , NS3 , NS4A , NS4B , NS5A and NS5B ) [11] . NS3/4A protease is essential for generating mature proteins required for virus replication and abrogating host antiviral innate immunity by cleaving MAVS and TIR-domain-containing adaptor-inducing IFN-β ( TRIF ) [5 , 12 , 13] . Previous studies showed that in vitro transcribed HCV genomic RNA and 3’untranslated region ( 3’UTR ) of RNA are recognized by RIG-I to trigger IFN response [14 , 15] . Recent study reported that MDA5 plays a major role in IFN response during HCV infection by introducing a mutant MAVS ( MAVS-C508R , resistant to NS3/4A cleavage ) into human hepatoma Huh7 cells [16] . Golgi protein 73 ( GP73 ) is a resident Golgi membrane protein initially identified in adult giant-cell hepatitis [17] . It is constitutive expressed in normal livers , but up-regulated in liver diseases [17 , 18] . Clinical reports showed that GP73 is a novel HCC serum marker with high specificity and sensitivity [19–23] . HCV facilitates GP73 expression that in turn enhances HCV secretion [24] . Mammalian target of rapamycin complex-1 ( mTORC1 ) up-regulates GP73 that subsequently promotes HCC cell proliferation and xenograft tumor growth in mice [25] . However , the mechanism by which GP73 regulates HCV infection and pathogenesis is largely unknown . Here , we revealed a novel mechanism by which GP73 facilitates HCV infection through repressing IFN signaling . Initially , HCV infection activates GP73 in patients’ serum , primary human hepatocytes ( PHHs ) and human hepatoma cells by regulating MAVS/TRAF6 and MEK/ERK pathway . Subsequently , GP73 binds with MAVS/TRAF6 to promote MAVS and TRAF6 degradation by proteasome-dependent pathway , which leads to the repression of host innate immunity and facilitation of HCV infection .
The effect of HCV infection on GP73 expression was initially investigated . First , secreted GP73 protein was determined in the serum of HCV-infected patients ( n = 60 ) and healthy individuals ( n = 60 ) ( Table 1 ) . Serum GP73 protein was significantly higher in HCV infected patients compared to healthy individuals ( mean ± standard error of the mean [SEM] 161±14 . 2 versus 47 . 6 ±2 . 6 ng/ml ) ( Fig 1A ) , suggesting that GP73 is activated in infected patients . Second , GP73 mRNA was determined in primary human hepatocytes ( PHHs ) infected with HCV ( JFH1 HCVcc ) . GP73 and IFN-β mRNAs were up-regulated by HCV ( Fig 1B ) , indicating that GP73 is activated and correlated with IFN-β during HCV infection . Third , GP73 mRNA was determined in Huh7 . 5 . 1 and Huh7 cells infected with JFH1 HCVcc . To our surprise , GP73 and IFN-β mRNAs were relatively unchanged ( less then 1 . 5-fold ) in HCV-infected cells ( Fig 1C and 1D ) , the protein levels of GP73 were also unchanged in HCV-infected Huh7 cells ( Fig 1E and 1F ) , suggesting that GP73 is not activated by HCV in Huh7 . 5 . 1 and Huh7 cells with the defective in IFN response in the cells . It was reported that MDA5 senses HCV RNA to trigger IFN response after introducing a C508R mutant of MAVS ( MAVSR ) into Huh7 cells [16] . We next investigated the expression status of GP73 and IFN-β in HCV-infected Huh7-MAVSR cells . The results demonstrated that in Huh7-MAVSR cells , GP73 and IFN-β mRNAs were up-regulated by at least 3-fold during HCV infection ( Fig 1G ) , the protein levels of GP73 were also significantly enhanced during HCV infection in Huh7-MAVSR cells ( Fig 1H and 1I ) . We also showed that GP73 and IFN-β were activated by other RNA viruses , vesicular stomatitis virus ( VSV ) and enterovirus 71 ( EV71 ) ( S1A and S1B Fig ) . These results demonstrated that GP73 production is activated and correlated with IFN-β activation during viral infection , probably through MAVS . After MAVS activation during viral infection , IRF3/NF-κB is stimulated to induce IFN , whereas TAK1/MAPK is also activated to modulate cell proliferation . Thus , we determined which pathway is involved in GP73 activation . GP73 mRNA level was not affected by the treatments of recombinant IFN-α or recombinant IFN-λ1 , suggesting that GP73 is not an interferon-stimulated gene ( ISG ) ( S1C Fig ) . GP73 mRNA was repressed by PD98059 and U0126 ( MEK/ERK inhibitors ) , but not by GF109203 , LY294002 , SP600125 , SB203580 or BAY11-7082 ( PKC , PI3K , JNK , P38 or NF-κB inhibitors ) ( S1D Fig ) , and GP73 mRNA was attenuated by PD98059 and U0126 in dose-dependent manners ( S1E Fig ) , suggesting that GP73 expression is modulated by MEK/ERK pathway , but not PKC , PI3K , JNK , P38 or NF-κB pathways . Since mTORC1 pathway activates GP73 in HCC [25] , we examined the effect of rapamycin ( mTORC1 inhibitor ) on GP73 expression . GP73 mRNA was not affected by rapamycin ( S1F Fig ) , but GP73 protein was repressed by rapamycin or U0126 ( S1G Fig ) , suggesting that GP73 transcription is dependent on ERK pathway . Thus , GP73 expression is activated and correlated with IFN activation through MAVS and probably through MAVS-mediated MEK/ERK pathway during HCV infection in human serum , primary human hepatocytes and human hepatoma cells . Because GP73 production is correlated with IFN activation , we evaluated the effect of GP73 on the regulation of IFN signaling in HEK293 cells transfected with IFN-β-Luc , ISRE-Luc or NF-κB-Luc reporters and infected with SeV . IFN-β-Luc , ISRE-Luc and NF-κB-Luc were activated by SeV , but such activation was attenuated by GP73 ( Fig 2A ) , indicating that GP73 represses IFN-β , ISRE and NF-κB activities . GP73 contains an N-terminal trans-membrane ( TM ) domain required for membrane localization , a C-terminal acidic tail , and a middle coiled-coil domain required for endosome-to-Golgi traffic [26–28] . Based on the functional domains , we constructed a series of truncations of GP73 ( S2A Fig ) and examined the effects of mutants on the regulation of IFN-β . Activation of IFN-β reporter mediated by SeV was repressed by GP73 , D1 ( 1–348 ) and D2 ( 1–205 ) , enhanced by D4 ( 56–401 ) , D5 ( 56–348 ) and D6 ( 56–205 ) , but not affected by D3 ( 1–55 ) or D7 ( 206–401 ) ( S2B Fig ) , indicating that TM domain plus coiled-coil domain , but not coiled-coil domain alone , repress SeV-mediated activation of IFN-β . These results also implicated that inhibitory effect of GP73 dependents on Golgi membrane targeting or sub-cellular compartments trafficking . Further expression analysis showed the protein levels of GP73 D1 and GP73 D2 were comparable to FL GP73 , but GP73 D4 and GP73 D6 were lower than FL GP73 ( S2C Fig ) , suggesting the TM domain plus coiled-coil domain were sufficient to inhibit IFN-β activation , and that the expression level of GP73 may affect its repression effect on IFN-β activation . The role of endogenous GP73 in virus-triggered IFN signaling was examined by three shRNAs targeting to GP73 gene ( GP73-shRNA#2 , #3 and #4 ) , which could attenuate GP73 mRNA and GP73 protein level ( S2D Fig ) . IFN-β and NF-κB activities were induced by SeV and further facilitated by GP73-shRNA #3 and GP73-shRNA#4 in HEK293 cells ( Fig 2B ) , indicating that knock-down of GP73 up-regulates virus-induced IFN-β and NF-κB . The effect of GP73 on the regulation of innate immunity was assessed . We initially showed that GP73 mRNA was highly expressed in Huh7 and Huh7 . 5 . 1 cells , at low levels in L02 , HEK293 , THP-1 and HeLa cells , but not detected in HepG2 cells ( S2E Fig ) . Thus , we generated three stable cell lines: Huh7-MAVSR/lentivirus-Con-shRNA , Huh7-MAVSR/lentivirus-GP73-shRNA#3 and Huh7-MAVSR/lentivirus-GP73-shRNA#4 . IFN-β , IL-6 and IFN-stimulated gene 56 ( ISG56 ) were enhanced by GP73-shRNA#3 and GP73-shRNA#4 in the presence of JFH1 HCV genomic RNA ( Fig 2C ) , indicating that knock-down of GP73 up-regulates IFN-β , IL-6 and ISG56 . In addition , p-IRF3 and p-IκBα were facilitated by GP73-shRNA#3 and GP73-shRNA#4 in the presence of HCV genomic RNA ( Fig 2D ) , suggesting that knock-down of GP73 enhances IRF3 and IκBα phosphorylation . Moreover , IFN-β , IFN-λ1 , IL-6 and TNF-α mRNAs were activated by SeV in the presence of GP73-shRNA #4 ( Fig 2E and 2F ) , indicating that knock-down of GP73 facilitates IFN-β , IFN-λ1 , IL-6 and TNF-α expression . Furthermore , IFN-β , IFN-λ1 , IL-6 and ISG56 mRNAs were also activated by SeV in the presence of GP73-shRNA #4 , compared with a seed sequence-matched control ( S2F Fig ) , indicating that the effect was not due to non-specific off-targets of GP73-shRNA#4 . Thus , GP73 acts as a negative regulator to repress host innate immunity during viral infection . The role of GP73 in the regulation of IRF3 and NF-κB was evaluated in HEK293 cells co-transfected with plasmids encoding GP73 , components of IFN pathway , and ISRE-Luc or NF-κB-Luc . ISRE activities induced by RIG-I , MDA5 , MAVS and TBK1 were repressed by GP73 , but ISRE activation mediated by IRF3 was not affected by GP73 ( Fig 3A , left panel ) ; and NF-κB-Luc activities mediated by TRAF6 and TAK1 were attenuated by GP73 , but NF-κB-Luc activation induced by p65/p50 was not affected by GP73 ( Fig 3A , right panel ) ; suggesting that GP73 represses IFN signaling downstream of RIG-I/MDA5 and upstream of IRF3/NF-κB . We then determined whether GP73 is associated with components of IFN pathway in HEK293 cells co-transfected with HA-GP73 and Flag-tagged signaling components . Co-IP revealed that GP73 interacted with MAVS and TRAF6 , but not with RIG-I , TRAF3 , TBK1 or IRF3 ( Fig 3B , top panel ) . An additional faster band of GP73 was detected in the presence of MAVS or TRAF6 ( Fig 3B , bottom panel ) . We thus determined which band of GP73 was associated with MAVS/TRAF6 in HEK293 cells co-transfected with plasmids expressing GP73 containing both N-terminal HA-tag and C-terminal c-Myc-tag , MAVS or TRAF6 . The results demonstrated that the faster band of GP73 containing both the N-terminal HA-tag and the C-terminal c-Myc-tag interacted with MAVS ( Fig 3C , left panel ) and TRAF6 ( Fig 3C , right panel ) . It was reported GP73 is a glycosylated Golgi-localized protein , depending on the TMD with a positively charged residue in the cytoplasmic N-terminal tail [17 , 28] . In vitro endoglycosidase digestion assay indicated the faster band of GP73 was lack of glycosylation ( S3A Fig ) . Endogenous CoIP also demonstrated GP73 interacted with MAVS during SeV infection ( Fig 3D ) or HCV infection ( Fig 3E ) . Further GST pull-down assays ( Fig 3F ) and confocal microscopy analyses ( Fig 3G ) , indicated that GP73 interacted and co-localized with MAVS/TRAF6 . Because the mitochondrial associated membrane ( MAM ) is the major site of MAVS-mediated IFN signaling [13 , 29] , while GP73 is a Golgi membrane protein and thus , we analyzed which sub-cellular compartment is the site for MAVS and GP73 interaction . Differential centrifugation and WB demonstrated that GP73 was co-localized with MAVS to the Mito/MAM fraction ( P5K ) upon SeV infection ( Fig 3H ) . CoIP results of MAVS with Golgi-defective GP73 mutants ( WT2-K2E and WT2-ΔK2 ) also indicated the GP73/MAVS interaction was not dependent on its Golgi localization ( S3B Fig ) . Since GP73 binds with MAVS/TRAF6 , we determined which domain of MAVS/TRAF6 is required for such interaction . Initially , we constructed plasmids expressing TRAF6 and four deletion mutants ( Fig 4A , top panel ) as described previously [30] . In co-transfected HEK293 cells , GP73 interacted with FL TRAF6 , TRAF6-aa 1–357 and TRAF6-aa 289–522 , but failed to bind to TRAF6-aa 1–288 or TRAF6-aa 358–522 ( Fig 4A , bottom panel ) , indicating that GP73 binds to coiled-coil domain of TRAF6 . As a central adaptor of IFN signaling , MAVS contains an N-terminal CARD domain required for RIG-I-mediated oligomerization , a proline-rich domain involved in protein-protein interaction , and a C-terminal transmembrane domain ( TM ) inserting MAVS into mitochondrial outer membrane [4 , 31] . MAVS also carries three TRAF-interacting motifs ( TIMs ) required for the binding of TRAF2/3/5/6 to activate downstream signaling [8 , 9 , 31] . To determine the functions of MAVS domains in the binding with GP73 , we generated a series of MAVS truncations and deletions ( Fig 4B ) . In co-transfected HEK293 cells , GP73 only interacted with FL MAVS ( 1–540 ) , but not with C-terminal deletions MAVS ( 1–510 ) , MAVS ( 1–467 ) , MAVS ( 1–440 ) , MAVS ( 1–360 ) or MAVS ( 1–180 ) ( Fig 4C ) , indicating that C-terminal TM domain is required for the interaction with GP73 . Similarly , GP73 only interacted with MAVS ( 1–540 ) , but not with N-terminal deletions MAVS ( 91–540 ) , MAVS ( 181–540 ) or MAVS ( 361–540 ) ( Fig 4D ) , suggesting that N-terminal CARD domain is involved in the interaction with GP73 . Moreover , GP73 was interacted with MAVS ( 1–540 ) and M11 MAVS ( 1–90/441–540 ) , but not with MAVS ( 91–540 ) , MAVS ( 1–510 ) or M15 MAVS ( 1–90/468–540 ) ( Fig 4E ) . These results indicated that CARD domain , TM domain and TIM3 domain are sufficient and efficient for the binding with GP73 . Although M14 MAVS ( 1–90/181–540 ) contains M11 MAVS and middle sequence of MAVS , it is less efficient in the binding with GP73 , which can be explained with an auto-inhibitory effect of middle sequence of MAVS [32] . Interestingly , M15 MAVS ( compared with M11 , lacking TIM3 and surrounding 20 aa ) failed to bind to GP73 , which highlighted the importance of TIM3 in MAVS and GP73 interaction . Further analysis of mutations in TIM3 ( ΔTIM3: AAANEY instead of PEENEY ) , that lost the ability of TIM3 to bind TRAF6 [8 , 31] , showed that GP73 strongly interacted with MAVS ( 1–540 ) , M11 MAVS ( 1–90/441–540 ) and M12 MAVS ( 1–180/441–540 ) , weakly interacted with FL MAVS ΔTIM3 , M12 MAVS ΔTIM3 and M17 MAVS ( 1–180/468–540 ) , but not with M11 MAVS ΔTIM3 ( Fig 4F ) . In vitro GST pull-down assays showed GP73 can directly bind M11 and T6CC ( TRAF6 coiled-coil domain ) ( S4A Fig ) . To analysis whether putative polyubiquitination of MAVS mediated by activated TRAF6 is necessary in MAVS and GP73 interaction , we made a series of lysine-to-arginine ( K to R ) point mutations on M11 , which contains only four lysine residues . CoIP results showed the M11-KO mutant still interacted with GP73 , suggesting polyubiquitination is not necessary for MAVS and GP73 interaction ( S4B Fig ) . Taken together , these results demonstrated that TIMs ( TIM1 , TIM2 and TIM3 ) are required for MAVS to interact with GP73 , probably through activated TRAF6 . Since GP73 interacts with MAVS/TRAF6 , we determined whether GP73 affects the stability of MAVS/TRAF6 . In HEK293 cells , MAVS and TRAF6 proteins were reduced in the presence of GP73 ( Fig 5A ) , whereas TRAF3 and STING proteins were not affected by GP73 ( S5 Fig ) . In addition , endogenous MAVS protein was attenuated by GP73 over-expression ( Fig 5B ) . Furthermore , endogenous MAVS and TRAF6 , but not IRF3 or IκBα , were up-regulated by GP73-shRNA#4 ( Fig 5C ) . These results suggested that over-expression of GP73 down-regulates MAVS/TRAF6 , whereas knock-down of GP73 up-regulates MAVS/TRAF6 . Interestingly , MAVS and TRAF6 mRNAs were relatively unaffected by over-expression of GP73 ( Fig 5D , left panel ) or knock-down of GP73 ( Fig 5D , right panel ) , indicating that GP73 does not regulate transcription of MAVS/TRAF6 . We speculated that GP73 attenuates MAVS/TRAF6 at post-transcriptional level , probably by promoting MAVS/TRAF6 degradation . Moreover , CHX chase results indicated HCV infection promoted MAVS degradation in Huh7-MAVSR cells ( Fig 5E ) . There are at least three main systems for protein degradation: ubiquitin-proteasome , autophagosome and lysosome pathways . We evaluated which pathway is involved in GP73-mediated MAVS/TRAF6 degradation . MAVS protein was attenuated by GP73 , and the degradation of MAVS was diminished by MG132 ( proteasome inhibitor ) , but not by 3-MA ( autophagosome inhibitor ) , CQ ( lysosome inhibitor ) or Z-VAD-FMK ( apoptosis inhibitor ) ( Fig 5F ) . Similarly , TRAF6 protein was reduced by GP73 , and such reduction was blocked by MG132 and BTZ ( proteasome inhibitors ) , but not by CQ ( lysosome inhibitor ) or BFA ( an inhibitor that disrupts the ER-to-Golgi trafficking of GP73 ) [27 , 33] ( Fig 5G ) . Thus , GP73 promotes MAVS/TRAF6 degradation through proteasome-dependent pathway . Since HCV activates GP73 in immune-competent cells ( PHHs and Huh7-MAVSR ) and GP73 promotes MAVS/TRAF6 degradation , leading to the attenuation of IFN signaling , we determined the function of GP73 in the regulation of HCV infection and replication . Huh7 and Huh7-MAVSR cells stably expressing GP73-shRNAs were transfected with in vitro transcribed J6/JFH-Rluc HCV genomic RNA . HCV infection ( indicated by Renilla luciferase activity ) ( Fig 6A ) , HCV genomic RNA replication ( indicated by HCV RNA copy ) ( Fig 6B ) and HCV core protein production ( Fig 6C ) were attenuated by GP73-shRNA#3 and GP73-shRNA#4 . These results demonstrated that knock-down of GP73 down-regulates HCV infection , viral RNA replication and protein production . In addition , the role of GP73-shRNA#4 in HCV replication was evaluated by rescue experiments . A GP73-rescue construct ( GP73m4 ) that is resistant to GP73-shRNA#4 targeting without changing the sequence of GP73 was generated . HCV RNA expression ( Fig 6D ) and core protein production ( Fig 6E ) were repressed by GP73-shRNA#4 , and such repressions were rescued by GP73m4 . We further showed that lentivirus transduced GP73m4 fully rescued the HCV RNA and core protein production , repressed by GP73-shRNA#4 ( S6A and S6B Fig ) . Moreover , the effect of GP73 on HCV replication was determined in PHHs transduced with lentivirus-GP73-shRNA#4 and infected with HCV . HCV RNA was repressed by GP73-shRNA#4 ( Fig 6F ) , indicating knock-down of GP73 down-regulates HCV replication . Finally , we evaluated the effect of GP73 on the replication of VSV in VSV-GFP-infected Huh7-GP73-shRNAs cells . VSV infection was attenuated by GP73-shRNA#3 and repressed by GP73-shRNA#4 ( S6C Fig ) , suggesting that GP73 plays a stimulatory role in VSV replication . Taken together , GP73 facilitates HCV infection , viral RNA replication and protein production .
We discovered a key function of GP73 in the regulation of host innate immunity and revealed a novel mechanism by which GP73 regulates HCV replication ( Fig 7 ) . Initially , we showed that HCV infection activates GP73 in patients’ serum , PHHs and human hepatoma cells . Subsequently , we demonstrated that GP73 in turn binds directly with MAVS and TRAF6 to promote MAVS/TRAF6 degradation , which result in the repression of host innate immunity and facilitation of HCV infection . It is known that the mitochondrial-associated ER membrane ( MAM ) is the major site of MAVS signaling , and HCV NS3/4A protease cleaves MAVS synapse from MAM , but not from mitochondria , to ablate immune defenses [29] . Upon RIG-I/MDA5 activation , MAVS forms large prion-like aggregates to propagate antiviral innate immunity by recruiting TRAF2/3/6 E3 ubiquitin ligases [34] . ER-to-Golgi transport compartments mediate the dynamic association of TRAF3 with MAVS at MAM , leading to inducing innate immune responses [35] . Our studies showed that GP73 , a resident Golgi membrane protein , is recruited to MAVS/TRAF6 signalosome on MAM to inhibit immune defenses against HCV infection , which highlight the roles of Golgi apparatus and membrane compartments traffic in modulating innate immunity . Proteomic analysis during RNA virus infection also indicates GP73 traffic to MAM during RNA virus infection [36] . Knock-down of GP73 in Huh7-MAVSR cells transfected with in vitro transcribed HCV genomic RNA activates IFN production , whereas in Huh7 cells transfected with J6/JFH1-Rluc RNA impairs HCV replication . We could not exclude the possibility that GP73 may have other strategies to facilitate HCV infection , such as promoting HCV particle assembly and secretion [24] , or mediating MAVS-NS3/4A interaction on MAM . We also reported that GP73 mediates the interaction of ApoE and HCV NS5A to promote viral secretion [37] . Further studies are needed to clarify other functions of GP73 in HCV life cycle and HCV associated liver diseases . Negative regulation of innate immunity plays an important role in maintaining the balance of cell signaling . The adaptor protein MAVS and the ubiquitin E3 ligase TRAF6 play central roles in virus-triggered innate immunity . We revealed that GP73 interacts with TRAF6/MAVS and the interaction of GP73 with MAVS is dependent on TRAF-interacting-motifs . Because after TRAF6 recruitment by MAVS activation , TRAF6 synthesizes polyubiquitin chains on MAVS followed by the recruitment of TBK1 and IKKβ , leading to MAVS phosphorylation and subsequent IRF3 activation [9] . Possibilities are existed that the polyubiquitination or phosphorylation modifications serve as scaffolds for GP73 binding , just likes the model of TBK1 and IRF3 binding to MAVS [9] . The M11-KO mutant CoIP and in vitro GST pull-down experiments further indicated the direct binding of GP73 with MAVS , but not the polyubiquitin chains . TRAF6 is known as an E3 ubiquitin ligase that mediates synthesis of K63-linked polyubiquitin chains , while K48-linked polyubiquitination chains target proteins for proteasome-mediated degradation . As not an E3 ubiquitin ligase , GP73 must recruit E3 ligases to MAVS/TRAF6 signalosome to synthesize K48-linked polyubiquitin chains . The exact E3 ligase involved in GP73-mediated proteasome degradation of MAVS/TRAF6 remains unidentified . More recently , it reported that single-nucleotide polymorphism ( SNP ) of GP73 is associated with cytokine signaling in peripheral blood mononuclear cells ( PBMCs ) upon bacteria and fungi stimulation [38] . This study further expands that GP73 acts as a negative regulator of innate immunity to facilitate HCV infection by interacting with MAVS/TRAF6 to promote MAVS/TRAF6 degradation . We also showed that GP73 plays a stimulatory role in VSV replication . Taken together , these results suggested that GP73 plays a broad role in the regulation of pathogen infection , including fungi , bacteria and viruses . This study provides new insights into the mechanism of HCV infection and pathogenesis , and also suggests that GP73 acts as a potential antiviral target in the prevention and treatment of pathogen infections .
Participants included 60 HCV patients randomly retrieved from Renmin Hospital of Hubei Province from September 2015 to January 2016 . All participants were diagnosed with HCV infection by the presence of anti-HCV antibodies and serum HCV RNA ( Table 1 ) , and confirmed as negative for hepatitis B virus ( HBV ) and human immunodeficiency virus-1 ( HIV-1 ) . Serum samples from healthy individuals were randomly selected from a local blood donation center . The study was conducted according to the principles of the Declaration of Helsinki and approved by the Institutional Review Board of the College of Life Sciences , Wuhan University , in accordance with its guidelines for the protection of human subjects . All participants have provided written informed consent to participate in the study . Primary human hepatocytes ( PHHs ) were purchased from Research Institute for Liver Diseases ( Shanghai , China ) and cultured as described previously [16] . Cells were infected with JFH1 HCVcc at MOI of 2 for indicated times . To study the effect of knock-down of GP73 on HCV infection in PHHs , plated PHHs were transduced with lentiviruses expressing shRNA targeting GP73 for 48 h , and then infected with JFH1 HCVcc at MOI of 2 for 2 days followed by RT-PCR analysis . Human hepatoma cell lines ( HepG2 and Huh7 , human normal liver cell line ( L02 ) , human embryonic kidney HEK cell line ( HEK293 ) , human acute monocytic leukemia cell line ( THP-1 ) and human epitheloid cervix carcinoma cell line ( HeLa ) were purchased from American Type Culture Collection ( ATCC ) ( Manassas , VA , USA ) and described previously [39] . Human hepatoma cell line ( Huh7 . 5 . 1 ) was kindly provided by Dr . Francis V Chisari of Scripps Research Institute , USA . Huh7-MAVSR cell line was provided by Dr . Jin Zhong of Institute Pasteur , Shanghai , China [16] . THP-1 cells were cultured in RPMI 1640 medium containing 10% heat-inactivated fetal bovine serum ( FBS ) ( Gibco , Grand Island , NY , USA ) . Other cell lines were cultured in Dulbecco’s modified Eagle’s medium ( DMEM ) purchased from Gibco ( Grand Island , NY , USA ) containing 10% FBS . All cell cultures were maintained at 37°C in a 5% CO2 incubator . JFH1 HCVcc supernatant was prepared from Huh7 . 5 . 1 cells transfected with in vitro-transcribed JFH1 genomic RNA . The amplification , concentration , purification and titration of HCVcc were performed as described previously [40] . Briefly , Huh7 . 5 . 1 cells were infected with HCVcc at an MOI of 0 . 01 for 7–9 days . Cells were sub-cultured once before confluence . The supernatant were collected and concentrated at 28 , 000 rpm for 4 h at 4°C ( SW28 rotor ) , the pellets were resuspended and loaded to a 20–60% sucrose gradient at 120 , 000 × g for 16 h at 4°C ( SW41i rotor ) . Fractions of 1 ml were collected from the top of gradient and determined by RT-qPCR . High HCV RNA fractions were titrated on Huh7 . 5 . 1 cells by immunofluorescence staining against HCV NS5A 3 days postinfection . The infections of recombinant vesicular stomatitis virus-green fluorescent protein ( VSV-GFP ) and enterovirus 71 ( EV71 ) were as described previously [41] . Briefly , VSV-GFP were produced in HEK293 cells and titrated by counting GFP-positive cell numbers . EV71 were produced in RD cells and titrated by TCID50 . SeV were propagated in embryonated eggs and titrated by blood coagulation test . FL-J6/JFH5’C19Rluc2Aubi was a gift from Dr . Charles M . Rice of Rockefeller University and prepared as described previously [42] . JFH1 HCV replicon was kindly provided by Dr . Takaji Wakita of National Institute of Infectious Diseases , Tokyo and prepared as described previously [43] . IFN-β-Luc , ISRE-Luc or NF-κB-Luc reporter plasmids and HA-tagged full length ( FL ) TRAF6 and its truncations were gifts from Dr . Ying Zhu of Wuhan University , China and constructed as previously described [30 , 41] . Mammalian expression plasmids for HA- , Flag- or c-Myc-tagged GP73 , RIG-I , MDA5 , MAVS , STING , TRAF3 , TRAF6 , TBK1 , IRF3 , TAK1 , TAB1 , p65 , p50 , β-actin and the truncated proteins were constructed by standard molecular cloning method from cDNA templates . Unless otherwise described , GP73 constructs were C-terminal tagged . To generate GST-GP73 plasmid , GP73 coding sequence lacking the N-terminal transmembrane domain ( aa36-401 ) was sub-cloned into the BamHI/XhoI sites of pGEX-6p-1 vector . MBP-M11 and MBP-T6CC were constructed by inserting the M11 or T6CC sequences into the EcoRI/SalI sites of pMAL-c2x vector . All constructs were confirmed by DNA sequencing . The following primers were used to generate GP73-rescue construct GP73m4 by site-directed mutagenesis: M4F: 5’-GTgGAaAAgGAaGAgACgAAcGAGATCCAGGTGGTGAATGAG-3’; M4R: 5’-gTTcGTcTCtTCcTTtTCcACTTGTCTCTTTGAATCCAAAACCAC-3’ . Antibodies against GP73 , MAVS , GAPDH , AIF , MBP and GST were purchased from Proteintech ( Wuhan , Hubei , China ) . Antibody against HCV NS5A ( 2F6 ) was purchased from BioFront ( Anhui , Hefei , China ) . Antibodies against HCV Core and p-IRF3 were purchased from Abcam ( Cambridge , MA , USA ) . Antibody against IRF3 was purchased from Santa Cruz Biotechnology ( Dallas , Texas , USA ) . Antibodies against Flag , HA , c-Myc , TRAF6 , Calnexin , Syntaxin 6 , p-IκBα and IκBα were purchased from Cell Signaling Technology ( Danvers , MA , USA ) . All inhibitors were purchased from Selleck Chemicals ( Houston , TX , USA ) . Total RNA was extracted from cells using TRIzol reagent ( Invitrogen ) , then 1 μg of total RNA was used to synthesize cDNA with Moloney murine leukemia virus reverse transcriptase ( Promega ) and N6 random primer for 1 h at 37°C and subjected to real-time PCR analysis with specific primers . HCV RNA levels were also determined relative to a standard curve composed of serial dilutions of DNA template containing the JFH1 NS5B cDNA . Gene-specific primer sequences were as described previously [7 , 16] and listed in S1 Table . The short hairpin targeting sequences for specific genes were cloned into the pLKO . 1-TRC control vector ( A gift from David Root , addgene #10879 ) . Lentivirus were produced in HEK293 cells by co-transfection of pMD2 . G ( Addgene #12259 ) , psPAX2 ( Addgene #12260 ) and pLKO . 1-shRNA plasmids ( Ratio 1:3:4 ) . Virus supernatant was collected at 48 and 72 h post transfection , and passed through a 0 . 45 μm filter , followed by PEG-8000 precipitation , aliquots were stored at -80°C . To establish a stable knockdown cell line , the shRNA lentivirus stocks were used to transduce Huh7 cells or THP-1 cells with 8 μg/ml polybrene . At 48 h post transduction , cells were cultured in puromycin ( 2 . 5 μg/ml for Huh7 cells and 1 μg/ml for THP-1 cells ) selection medium for at least 7 days . To establish stable knockdown cells in Huh7-MAVSR , we made a neomycin-resistant version of pLKO . 1 by replacing the Puro to Neo , and the lentivirus-transduced cells were selected in G418 ( 500 μg/ml ) for 10 days . The following sequences were targeted for human GP73 CDS: #2: 5’-CCACAGGATTTGAGATGCTAA-3’; #3: 5’-CGAATAGAAGAGGTCACCAAA-3’; #4: 5’-GTTGAGAAAGAGGAAACCAAT-3’ . The target sequence of the seed sequence-matched control of #4 were as followed: S4C , 5’-GTTGAGAAActcGAAACCAAT-3’ . Cells were collected and lysed in IP-lysis buffer ( 50 mM Tris-HCl , 150 mM NaCl , 1% Triton X-100 , 1 mM EDTA , 10% glycerol , and protease inhibitor cocktail , pH7 . 4 ) . Supernatants were collected by centrifugation ( 15 , 000 g , 15 min , 4°C ) , and were pre-cleared with 30 μl protein G-conjugated agarose ( GE Healthcare Life Sciences ) followed by centrifugation ( 2 , 000 g , 2 min , 4°C ) . The pre-cleared supernatants were incubated with the indicated antibodies ( 1 μg/ml ) for 3 h or overnight at 4°C , followed by immunoprecipitation with 30 μl protein G-conjugated agarose for 2 h at 4°C . The precipitates were washed 5–7 times with IP-wash buffer ( 50 mM Tris-Cl , 300 mM NaCl , 1% Triton X-100 , 1 mM EDTA , pH7 . 4 ) and detected through WB . Cells were fixed with 4% paraformaldehyde for 15 min , followed by permeabilization with 0 . 5% Triton X-100 for 20 min at room temperature . Primary antibodies ( 0 . 2 μg/ml ) were added for 2 h at room temperature post blocking with 5% bovine serum albumin for 1 h . Samples were further stained with FITC- , DyLight649-conjugated secondary antibodies , followed by visualization with confocal microscopy ( Olympus FV1000 ) . For an in vitro endoglycosidase digestion assay , HEK293 cells ( 5×105 ) were co-transfected with HA-GP73-Myc ( 1 μg ) and Flag-MAVS or Flag-TRAF6 ( 1 μg ) for 24 h . Cells were lysed in 50 μl IP-lysis buffer , and half lysates were denatured and digested with 500 U Endo H ( NEB ) for 3 h at 37°C before WB analysis . The cell fractionation assay was performed by differential centrifugation as described [44] . Briefly , HEK293 cells ( 1×107 ) were left un-treated or treated with SeV for 8 h and were washed in PBS followed by dousing 40 times in 2 ml homogenization buffer ( 10 mM Tris-HCl , pH7 . 4 , 2 mM MgCl2 , 10 mM KCl , and 250 mM sucrose ) . The homogenate was centrifuged at 500 g for 10 min to pellet un-broken cells and nuclei ( twice ) . The supernatant was centrifuged at 5 , 000 g for 10 min to precipitate crude mitochondira ( P5K , wash once ) . The supernatant ( S5K , pellet twice ) was further centrifuged at 50 , 000 g for 60 min to precipitate membrane fractions ( P50K ) . For an in vitro binding assay , the GST-fused GP73 or GST alone was expressed in BL21 cells and purified with glutathione Sepharose 4B ( GE Healthcare Life Sciences ) according to the supplier’s instructions . HEK293 cells transfected with Flag-MAVS or Flag-TRAF6 were washed twice with PBS and lysed in GST-lysis buffer ( 20 mM Tris-Cl , 200 mM NaCl , 1 mM EDTA , 0 . 5% NP-40 and protease inhibitor cocktail , pH7 . 5 ) . Supernatants were subjected to GST pull down with 10 μg of GST or 20 μg of GST-GP73 overnight at 4°C . After being washed with GST-lysis buffer for four times , proteins were extracted from the Sepharose beads by boiling in 2× SDS loading buffer , and detected through WB . The MBP-fused M11 , T6CC or MBP alone was expressed in BL21 cells and purified with amylose resin ( NEB ) according to the supplier’s instructions . For an in vitro binding assay , purified MBP , MBP-M11 or MBP-T6CC ( 20 μg ) were subjected to GST pull-down with 10 μg of GST or 20 μg of GST-GP73 overnight at 4°C as described above . HEK293 cells were plated and transfected the following day by lipofectamine 2 , 000 ( Invitrogen ) . Empty control plasmids were added to ensure that each transfection receives the same amount of total DNA . Luciferase reporter vectors were co-transfected with pRL-TK ( as an internal control reporter vector ) into HEK293 cells . Dual luciferase assays were performed with guidelines provided by the manufacturer ( Promega ) . Serum samples of healthy individuals or HCV patients were collected and stored at -80°C . Supernatants from cultured cells were collected at the indicated time points . The GP73 protein levels were analyzed by ELISA kits with the manufacturer’s instructions ( Hotgen Biotech , China ) . Statistical graphs were created with Origin or GraphPad Prism software , and statistical analysis was performed with two-tailed Student’s t tests . The graphs represent the mean values ± the standard deviations ( SD ) of at least three independent experiments . P < 0 . 05 was considered statistically significant , and P < 0 . 01 and P < 0 . 001 were considered highly significant . | Golgi protein 73 ( GP73 ) is a serum biomarker for liver diseases and hepatocellular carcinoma ( HCC ) . In this study , the authors reveal that GP73 acts as a novel negative regulator of host innate immunity to facilitate hepatitis C virus ( HCV ) infection . GP73 expression is activated and correlated with IFN-β production during HCV infection in patients’ serum , primary human hepatocytes ( PHHs ) and human hepatoma cells through mitochondrial antiviral signaling protein ( MAVS ) , TNF receptor-associated factor 6 ( TRAF6 ) and MEK/ERK pathway . They further demonstrate that during viral infection , MAVS recruits TRAF6 that subsequently directly binds with GP73 . After binding with MAVS and TRAF6 , GP73 promotes MAVS and TRAF6 degradation . Moreover , GP73 attenuates IFN-β promoter , IFN-stimulated response element ( ISRE ) and NF-κB promoter and down-regulates IFN-β , IFN-λ1 , interleukin-6 ( IL-6 ) and IFN-stimulated gene 56 ( ISG56 ) , leading to the repression of host innate immunity and the facilitation of virus infection . These results reveal a novel mechanism by which GP73 acts as a novel negative regulator of host innate immunity to facilitate virus infection and also provide new insights into the therapeutic design of anti-HCV drugs . | [
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"microbiolo... | 2017 | GP73 represses host innate immune response to promote virus replication by facilitating MAVS and TRAF6 degradation |
Mutations in transmembrane inner ear ( TMIE ) cause deafness in humans; previous studies suggest involvement in the mechano-electrical transduction ( MET ) complex in sensory hair cells , but TMIE’s precise role is unclear . In tmie zebrafish mutants , we observed that GFP-tagged Tmc1 and Tmc2b , which are subunits of the MET channel , fail to target to the hair bundle . In contrast , overexpression of Tmie strongly enhances the targeting of Tmc1-GFP and Tmc2b-GFP to stereocilia . To identify the motifs of Tmie underlying the regulation of the Tmcs , we systematically deleted or replaced peptide segments . We then assessed localization and functional rescue of each mutated/chimeric form of Tmie in tmie mutants . We determined that the first putative helix was dispensable and identified a novel critical region of Tmie , the extracellular region and transmembrane domain , which is required for both mechanosensitivity and Tmc2b-GFP expression in bundles . Collectively , our results suggest that Tmie’s role in sensory hair cells is to target and stabilize Tmc channel subunits to the site of MET .
The auditory and vestibular systems detect mechanical stimuli such as sound , gravity , and acceleration . These two systems share a sensory cell type called hair cells . The somas of hair cells are embedded in the sensory epithelium and extend villi-like processes from their apex into the surrounding fluid . The shorter of these , the stereocilia , are arranged in a staircase-like pattern adjacent to a single primary cilium known as a kinocilium . Long proteins linkages tether neighboring cilia together . Deflection of the kinocilium along the excitatory axis tugs the interconnected stereocilia , which move as a single unit called the hair bundle [1] . When tension is placed on the upper-most linkages known as tip links , the force is thought to open mechanosensitive channels at the distal end of the shorter stereocilia [2 , 3] . These channels pass current , depolarizing the cell and permitting electrical output to the brain via the eighth cranial nerve . The conversion of a mechanical stimulus into an electrical signal is known as mechano-electrical transduction ( MET ) [4] . Aside from the channel , several other proteins converge at the base of the tip links to form a molecular complex that gates the channel . While a handful of essential members of this MET complex have been identified , we do not fully understand how all of these proteins interact . It is also not known how the MET channel is localized to and maintained at the stereocilia tips . To characterize the molecular underpinnings of MET and the underlying cause of pathology in human patients , it is essential to examine the individual components of the transduction complex in a comprehensive fashion . Thus far , only a few proteins have been designated as members of the MET complex , and more than one protein may comprise the channel subunits . Because the MET channel has yet to be reconstituted in a hetereologous system , the identity of the pore-forming subunits of the channel remains uncertain . However , several studies in recent years have revealed strong candidates for the pore-forming subunits: the Transmembrane Channel-like ( TMC ) proteins TMC1 and TMC2 . Mutations in TMC1 cause human deafness [5] , and double knock-outs of mouse Tmc1/2 result in the loss of MET currents [6–8] . In zebrafish , Tmc2a and Tmc2b are required for MET in hair cells of the lateral line organ [9] , and overexpression of a fragment of Tmc2a generates a dominant negative effect on hair-cell mechanosensitivity , suggestive of direct interference with the channel [10] . The TMCs localize to the tips of stereocilia , the site of MET , in mice and zebrafish [3 , 6 , 8 , 9 , 11 , 12] . In TMC2 knockout mice , permeation properties of the MET channel are altered [13] . Likewise , a point mutation in mouse Tmc1 results in altered channel properties , suggesting direct changes to the pore [7 , 14] . A recent paper used a cysteine modification assay to demonstrate that modification of certain residues lining the predicted pore of TMC1 results in changes to channel conductance [15] . Furthermore , the authors demonstrated that adding a MET channel blocker during exposure to the cysteine modifier prevented their modification , implying that the unaffected residues line the inner pore and are thus inaccessible when the channel is blocked . This body of evidence concludes that the TMCs are essential subunits of the MET channel , and are likely to at least partially constitute the pore . Another key component of the complex is Protocadherin-15 ( PCDH15 ) , which comprises the lower end of the tip link [16 , 17] and interacts with the TMCs [8 , 10] . A fourth membrane protein , Lipoma HMGIC fusion partner-like 5 ( LHFPL5 , formerly called TMHS ) , interacts with PCDH15 and is critical for localizing PCDH15 to the site of MET [18 , 19] . LHFPL5 is also required to properly localize TMC1 in mouse cochlear hair cells [8] . However , loss of LHFPL5 in cochlear hair cells does not completely abolish MET currents , and currents can be rescued by overexpression of PCDH15 [19] . This evidence suggests that LHFPL5 is not essential but rather acts as an accessory protein . Another TMC1/2 interacting partner is Calcium and integrin binding protein 2 ( CIB2 ) , which is a cytosolic protein that is localized in stereocilia and required for MET in cochlear hair cells [20] . A sixth essential member of the MET complex is the transmembrane inner ear ( TMIE ) protein . Loss of TMIE results in deafness in fish , mice and humans [21–26] . A recent study suggested that TMIE is required for mechanosensitivity in cochlear hair cells of mice [27] . These authors showed that despite normal morphology of the inner ear , hair cells lacking TMIE fail to label with aminoglycosides or FM 1–43 , both of which are known to permeate the MET channel [28 , 29] . TMIE was first localized to the stereocilia of hair cells [30 , 31] , and then to the stereocilia tips where MET occurs [26] . Zhao et al . [26] further demonstrated that loss of TMIE ablates MET currents , that TMIE interacts with both LHFPL5 and the CD2 isoform of PCDH15 , and that interfering with the TMIE-CD2 interaction alters MET . They proposed that TMIE could be a force-coupler between the tip link and channel . However , the CD2 isoform of PCDH15 is only essential in cochlear hair cells and not vestibular hair cells [32] . Zebrafish do not possess the CD2 isoform [10 , 33] , and yet they still require Tmie for hair-cell function [22] . These findings raised the tantalizing possibility that Tmie might have an additional role in MET that is independent from the tip links . Here , we present an alternative role for Tmie in hair-cell function . We first confirmed that mechanosensitivity is absent in a previously reported zebrafish mutant of tmie , ru1000 [22] , and demonstrated that this defect is rescued by transgenic Tmie-GFP . The localization of Tmie-GFP is maintained in the absence of other transduction components , suggesting that Tmie trafficks independently to hair bundles . Unexpectedly , GFP-tagged Tmcs fail to localize to the hair bundle in tmie mutants , and overexpression of Tmie leads to a corresponding increase in bundle expression of Tmc1 and Tmc2b . To determine which regions of Tmie are involved in regulating the Tmcs , we performed a domain analysis of Tmie by expressing mutated or chimeric transgenes of tmie in tmieru1000 larvae , and made three key discoveries: ( i ) Tmie can function without its putative first transmembrane domain , ( ii ) the remaining helix ( 2TM ) and adjacent regions are responsible for Tmie’s function in hair cells , and ( iii ) dysfunctional versions of Tmie have reduced efficacy in localizing the Tmcs , supporting the conclusion that impaired MET is due to reduction of Tmc protein in hair bundles . Our evidence suggests that Tmie’s role in the MET complex is to promote localization of Tmc1/2 to the site of MET in zebrafish sensory hair cells .
The literature on TMIE’s role in sensory hair cells is somewhat contradictory . Earlier studies proposed a developmental role for TMIE [21–23] , while later studies evidenced a role in MET [26 , 27] . To begin our analysis and attempt to clarify the issue in zebrafish , we examined live tmieru1000 larvae at 5–7 days postfertilization ( dpf ) using confocal microscopy . The ru1000 allele harbors a nonsense mutation leading to an N-terminal truncation , L25X [22] . We observed that mature hair cells of tmieru1000 larvae were grossly normal compared to wild type siblings in both the inner ear lateral crista and the lateral line organ , an organ specific to fish and amphibians ( Fig 1A ) . We detected a slight thinning of the mutant hair bundles , as revealed using a transgene Actin-GFP [34] . The underlying reason for the observed bundle thinning is not known , however we note that thin bundles have been observed in other zebrafish MET mutants such as those carrying mutations in ap1b1 [35] and tomt [11] . Both genes have been previously implicated in protein trafficking in hair cells , with tomt having a specific role in targeting Tmc1/2 proteins to the hair bundle [11 , 35] . We conclude that morphology is grossly normal in tmie-deficient zebrafish , suggesting that tmie does not have a developmental role in hair bundle formation . Our findings are consistent with the grossly normal hair-bundle morphology observed in Tmie-/- mice [26] . Next , we used an assay for the auditory evoked behavior response ( AEBR ) to quantify hearing loss in tmieru1000 mutants . We exposed 6 dpf larvae to a pure tone stimulus ( 157 dB , 1000 Hz , 100 ms ) once every 15 seconds for three minutes and recorded their startle responses ( sample traces in Fig 1B ) . Larvae deficient in tmie appeared to be profoundly deaf , with little to no response compared to wild type siblings ( Fig 1B and 1C ) . We then determined basal ( unevoked ) hair-cell activity of tmieru1000 larvae using FM 1–43 or FM 4–64 . Both are vital dyes that permeate open MET channels , making them useful for detecting the presence of active MET channels in hair cells [28 , 29 , 34] . A 30-second bath application of FM dye readily labels hair cells of the lateral line organ , which are arranged in superficial clusters called neuromasts . We briefly exposed wild type and tmieru1000 larvae to FM dye and then imaged the neuromasts ( Fig 1D ) . Consistent with previous findings [22 , 23 , 27] , tmieru1000 neuromasts have a severe reduction in FM labeling , suggesting that these hair cells have a MET defect . To characterize mechanically evoked responses of hair cells , we recorded extracellular potentials , or microphonics ( Fig 1H ) . Using a piezo actuator , we applied a 200 Hz sine wave stimulus to 3 dpf larvae while simultaneously recording voltage responses from hair cells of the inner ear . In agreement with results from our FM dye assay and with microphonic recordings previously reported [22] , microphonics are absent in tmieru1000 larvae ( Fig 1H , gray trace ) . To rescue mechanosensitivity in tmieru1000 larvae , we generated a construct expressing Tmie tagged with GFP on its C-terminus , then expressed this transgene using a hair cell-specific promoter , myosin 6b ( myo6b ) . Our Tmie-GFP rescued the FM labeling in tmieru1000 hair cells ( Fig 1E , quantified in Fig 1F ) . Tmie-GFP also restored microphonic potentials to wild-type levels ( Fig 1H , orange trace ) . In a stable line with a single transgene insertion , we observed that Tmie-GFP expression varies among hair cells , even within the same patch of neuroepithelium ( lateral crista , S1A Fig ) . Immature hair cells , which can be identified by their shorter stereocilia and kinocilia ( S1A Fig , bracket and arrow , respectively ) , consistently show a bright and diffuse pattern of labeling . This high expression level in immature bundles is characteristic of transgenes expressed using the myo6b promoter , which drives expression more strongly in young hair cells [18 , 34] . In mature hair cells , expression patterns of Tmie-GFP are variable . At high expression levels , Tmie-GFP signal is enriched in the bundle in a broader pattern ( S1B Fig ) . At reduced levels , the signal appears to be concentrated at the beveled edge of the hair bundle ( S1C Fig ) . At very low levels , we can observe puncta along the stereocilia staircase , consistent with localization at stereocilia tips ( S1D Fig ) . We suspect that the diffuse “bundle fill” pattern is due to overexpression , and that lower levels of Tmie-GFP recapitulate the endogenous pattern of localization at the site of MET , as previously observed in mice [26] . Having confirmed that our exogenously expressed Tmie-GFP is functional , we used this transgene to probe Tmie’s role in the MET complex . First , we characterized Tmie’s interactions with other MET proteins in vivo by expressing transgenic Tmie-GFP in mutant pcdh15a , lhfpl5a , and tomt larvae ( Fig 2 ) . Because a triple knock-out of the zebrafish tmc genes is not available , we used tomt mutants as a proxy for tmc-deficient fish based on recent reports of defective Tmc bundle localization in tomt-deficient fish and mice [11 , 36] . As in wild type bundles ( Fig 2A ) , we detected Tmie-GFP signal in each of these MET mutants ( Fig 2B–2D ) , even in splayed hair bundles ( Fig 2B and 2C , arrowheads ) . While normal localization of Tmie in the MET mutants could be in part due to overexpression , the presence of Tmie-GFP in stereocilia suggests that Tmie does not absolutely require any individual MET protein for entry into the hair bundle . We next wanted to test whether loss of Tmie affects the integrity of the MET complex . To confirm the presence of tip links , we examined TEM images from 5 dpf wild type and tmieru1000 larvae , n = 3 each ( Fig 3A ) . Of 67 wild type sections examined , we observed 22 tip links , 23 insertion plaques , and 36 examples of tenting . Of 87 tmieru1000 sections examined , we observed 27 tip links , 26 insertion plaques , and 39 examples of tenting . We then used an antibody against the tip-link protein Pcdh15a and observed punctate expression along stereocilia in tmieru1000 larvae ( Fig 3B ) . Finally , we stably expressed GFP-tagged Pcdh15aCD3 and its trafficking partner , Lhfpl5a , in tmieru1000 larvae . Stable expression of transgenes in zebrafish is achieved through random genomic insertion of a plasmid containing promoter and gene . To ascertain comparable expression of a given transgene across larvae , we used transgenic lines with 50% transmission , indicative of a single insertion event . Siblings produced in the same clutch of eggs were used as controls throughout this study . In 6 dpf tmieru1000 larvae , we observed punctate expression of transgenic Pcdh15aCD3-GFP ( Fig 3C ) and GFP-Lhfpl5a ( Fig 3D ) along stereocilia tips , similar to the pattern obtained with antibody labeling of Pcdh15a . These three assays confirmed that tip links were intact in tmieru1000 larvae , which agrees with our in vivo data ( Fig 1A ) and previous results in Tmie-/- mice [26] . To test for the presence of the Tmc proteins in tmieru1000 stereocilia , we again used stable GFP-tagged transgenic lines with single insertions: Tg ( myo6b:tmc1-GFP ) and Tg ( myo6b:tmc2b-GFP ) [11] . Unfortunately , we were unable to successfully express a tmc2a transgene . The Tmc1-GFP signal was very dim and only reliably visualized in a subset of the tall and accessible hair bundles of the lateral cristae , where we detected severely reduced GFP fluorescence in the stereocilia of tmieru1000 hair cells as compared to wild type siblings ( Fig 3E ) . The Tmc2b-GFP signal was more robust and we detected it in the hair bundles of the lateral cristae ( Fig 3G ) , anterior maculae ( Fig 3I ) , and lateral line organ ( Fig 3J ) . We imaged anterior maculae at 2 dpf , which are closer the surface of the fish at this stage of development; the GFP signal was too faint in the posterior maculae , which are located in a deeper , medial position next to the brain . In all of these hair cell types , we observed a severe reduction in Tmc2b-GFP fluorescence in the hair bundles of tmieru1000 larvae . Although Tmc2b was previously reported to have differential effects in lateral line neuromasts [9] , we did not observe a difference in Tmc2b-GFP expression among head or trunk neuromasts , likely because the myo6b promoter drives expression in all hair cells . In the lateral cristae , mature tmieru1000 hair cells expressing Tmc2b-GFP often displayed fluorescence within the apical soma near the cuticular plate , suggesting a trafficking defect ( Fig 3G , arrows; position of cuticular plate denoted in Fig 1G ) . We quantified the loss of Tmc1-GFP ( Fig 3F ) and Tmc2b-GFP ( Fig 3H ) from the hair bundle region of lateral cristae and found a striking and consistent reduction in tmie mutants . Loss of Tmc1/2b could be a result of disruption of the MET complex , but we previously showed that localization of transgenic Tmc1-GFP and Tmc2b-GFP is normal in pcdh15a mutants [11] . The aforementioned study and our experiments demonstrated that mislocalization of Tmc1/2b is not a hallmark of all MET mutants , and thus their mislocalization in tmie mutants is a specific effect . We hypothesized that if the loss of Tmie reduces Tmc localization in the hair bundle , then overexpression of Tmie would have the opposite effect . To test the consequence of overexpression of Tmie on Tmc localization , we created a second construct of tmie coupled with p2A-NLS ( mCherry ) . The p2A linker is a self-cleaving peptide , which leads to translation of equimolar amounts of Tmie and NLS ( mCherry ) . Hence , mCherry expression in the nucleus denotes Tmie expression in the cell ( Fig 4B and 4D , lower panels ) . We generated a stable tmieru1000 fish line carrying the tmie-p2A-NLS ( mCherry ) transgene driven by the myo6b promoter . Semi-quantitative PCR revealed that the myo6b promoter produces higher transcript levels of tmie than in non-transgenic siblings ( Fig 4A ) . We then crossed tmieru1000 fish carrying Tg ( myo6b:tmie-p2A-NLS ( mCherry ) ) to tmieru1000 fish carrying either Tg ( myo6b:tmc1-GFP ) or Tg ( myo6b:tmc2b-GFP ) . In the lateral cristae , we observed that overexpression of Tmie led to a robust increase in bundle expression of both Tmc1-GFP ( Fig 4B ) and Tmc2b-GFP ( Fig 4D ) . We quantified GFP fluorescence in the hair bundle region of tmieru1000 larvae and found that , compared to wild type siblings expressing only one of the tmc-GFP transgenes , co-overexpression with Tmie increased bundle expression of Tmc1-GFP by 2 . 4-fold ( Fig 4C ) and Tmc2b-GFP by 2 . 5-fold ( Fig 4E ) . Combined with the finding that Tmc expression is lost in hair bundles lacking Tmie , our data suggest that Tmie positively regulates Tmc localization to the hair bundle . We questioned whether Tmie was affecting the level of translation of tmc1/2b transcripts , but examination of GFP fluorescence in the soma region of the lateral crista revealed no difference between tmieru1000 and sibling larvae expressing the Tmc2b-GFP transgene ( S2A Fig ) . There was also no difference in whole-cell GFP fluorescence ( S2B Fig ) . Subtracting the soma signal from the whole cell signal revealed that the difference was in the bundle region ( S2C Fig ) . This difference is likely not detected in whole cell fluorescence because the relative contribution of signal from the bundle is small . Our observations were similar when we examined soma fluorescence from tmieru1000 larvae co-expressing Tmie and Tmc2b-GFP ( S2D–S2F Fig ) . These results indicate that Tmie is unlikely to affect translation of tmc transcripts , reinforcing our hypothesis that Tmie regulates Tmc bundle localization . To gain a better understanding of Tmie’s role in regulating the Tmcs , we characterized a new allele of tmie , t26171 , which was isolated in a forward genetics screen for balance and hearing defects in zebrafish larvae . Sequencing revealed that tmiet26171 fish carry an A→G mutation in the splice acceptor of the final exon of tmie , which leads to use of a nearby cryptic splice acceptor ( S3A Fig , DNA , cDNA ) . Use of the cryptic acceptor causes a frameshift that terminates the protein after amino acid 139 ( A140X ) , thus removing a significant portion of the cytoplasmic C-terminus ( S3A Fig , Protein ) . Homozygous mutant larvae exhibit severe auditory and vestibular deficits , being insensitive to acoustic stimuli and unable to maintain balance ( S3A Fig , Balance ) . FM 4–64 labeling of tmiet26171 mutant hair cells suggests that the effect of the mutation is similar to the ru1000 mutation ( S3B Fig , quantified in S3D Fig ) . This finding implicates the C-terminal tail , a previously uncharacterized region , in Tmie’s role in MET . However , when we overexpressed a near-mimic of the predicted protein product of tmiet26171 ( 1-138-GFP ) using the myo6b promoter , we observed full rescue of FM labeling defects in tmieru1000 larvae ( S3C Fig , quantified in S3D Fig ) , as well as behavioral rescue of balance and acoustic sensitivity ( n = 19 ) . These results revealed that when expressed at higher levels , loss of residues 139–231 does not have a significant impact on Tmie’s ability to function . This paradoxical finding highlighted an important advantage of the use of transgenes over traditional mutants when identifying domains that are fundamentally essential to the function of a protein . There are myriad reasons why a genomic mutation may lead to dysfunction , including reduced transcription or translation , protein misfolding and degradation , or mistrafficking . In cases where a mutated protein retains partial efficacy , exogenous expression may overcome these deficiencies by producing proteins at higher levels . This overexpression can reveal domains that are truly essential or non-essential to protein function , as seen with the differential rescue results in the tmiet26171 mutant and its transgene mimic ( S3D Fig ) . Moreover , the use of transgenes enabled us to carry out a comprehensive structure/function analysis of Tmie . To this end , we systematically deleted or replaced regions of tmie to generate 13 unique tmie constructs ( Fig 5A ) , and then expressed these constructs in hair cells of the tmieru1000 mutants . Earlier studies in zebrafish and mice proposed that Tmie undergoes cleavage , resulting in a single-pass mature protein [22 , 37] . To test this hypothesis , we generated the SP44-231 construct of Tmie , which replaced the N-terminus with a known signal peptide ( SP ) from a zebrafish Glutamate receptor protein ( Gria2a ) . The unrelated signal peptide serves to preserve the predicted membrane topology of Tmie . We also generated a similar construct that begins at amino acid 63 , where the sequence of Tmie becomes highly conserved ( SP63-231 ) . Three of the constructs contained internal deletions ( Δ63–73; Δ97–113; Δ114–138 ) . In three more constructs , we replaced part of or the entire second transmembrane helix ( 2TM ) with a dissimilar helix from the CD8 glycoprotein ( CD8; CD8-2TM; 2TM-CD8 ) . We included our mimic of the zebrafish tmiet26171 mutant , which truncates the cytoplasmic C-terminus ( 1–138 ) . Further manipulating the C-terminus , we made a construct that mimics the truncation seen in the mouse srJ mutant ( 1–113 ) . In mice , this truncation recapitulates the phenotype seen in a complete deletion of Tmie [21] . In addition , the Δ114–138 construct deletes the internal region of tmie that differentiates constructs 1–113 and 1–138 . We included an alternate splice isoform of tmie with a different final exon , altering the C-terminal sequence ( Tmie-short ) . This isoform is found only in zebrafish [22] and its function has not been explored . Finally , we expressed a fragment of the C-terminus that is lost in our zebrafish tmiet26171 mutant ( 139–231 ) . To determine subcellular localization of the transgenic tmie constructs , we inserted the coding sequence of each construct into a plasmid containing the myo6b promoter for expression , including a C-terminal GFP tag for visualization . These plasmids were then individually co-injected into tmieru1000 eggs with transposase mRNA to generate mosaic expression of the constructs in a subset of hair cells . At 4–6 days post injection , we imaged hair cells expressing each transgene ( Fig 5B ) . To quantify the enrichment in the bundle versus soma , we measured the integrated density of GFP fluorescence in a small central area of mature bundles ( Fig 5C , black oval ) and separately in the plasma membrane or soma-enriched compartments ( Fig 5C , magenta oval ) . Correcting for area , we then divided the bundle values by the total values ( bundle/bundle + soma ) and expressed this as a ratio ( Fig 5D ) . Values closer to 1 are bundle enriched , while values closer to 0 are soma-enriched . We excluded two constructs from this analysis: CD8-GFP because it was detected only in immature bundles ( Fig 5B , CD8 , and S4A Fig ) , and 139-231-GFP because it filled all regions of the hair cell ( S4C Fig ) . Localization fell into three broad categories: bundle-enriched , soma-enriched , and equally distributed . Most of the fusion proteins were bundle-enriched , similar to full-length Tmie-GFP expression ( Fig 5B and 5D ) . Three constructs were trafficked to the bundle but also expressed strongly in the soma ( SP63-231 , CD8-2TM , 1–138 ) . This result suggests that the deleted regions in these constructs have some role in designating Tmie as a bundle-localized protein . Also of note , the full replacement of the 2TM helix ( CD8 ) was unable to maintain stable expression in mature bundles ( S4A Fig ) , and did not show rescue of FM label in lateral line hair cells of tmieru1000 larvae ( S4B Fig ) . Half-TM replacements ( CD8-2TM , 2TM-CD8 ) revealed that loss of the first half of the helix affects trafficking , whereas alteration of the second half had no effect . Only two constructs that included the second TM were soma-enriched ( Tmie-short and 1–113 ) , suggesting an inability to traffic to the bundle . These two constructs were thus excluded from further analyses . Since three of our constructs that manipulated the C-terminus showed impaired bundle targeting , we expressed a fragment of the C-terminus ( 139-231-GFP ) to determine if it contained a bundle targeting signal . Expression of this fragment was restricted to the soma and kinocilium with little to no bundle expression ( S4C Fig ) , and showed no functional rescue of MET activity ( S4D Fig ) . Together , our results suggest that no single motif but rather multiple regions of Tmie contribute to its bundle localization . To identify regions of Tmie involved in the mechanosensitivity of hair cells , we measured the functionality of the nine tmie constructs that yielded hair-bundle expression . As in Fig 1F , we generated stable lines of each transgenic construct and quantified fluorescence in lateral line neuromasts after exposure to FM 4–64 ( Fig 6 ) . We used larvae at 6 dpf , a later stage that maximizes the number of hair cells in each neuromast . In all but one case ( CD8-2TM-GFP ) , these fish lines contained single transgene insertions to equalize expression of the tmie construct within a clutch . In the case of CD8-2TM-GFP , we used larvae from a founder that transmitted the transgene to >10% of offspring with consistently bright expression . Of nine constructs examined , four generated wild type levels of FM fluorescence in tmieru1000 neuromasts ( Tmie , SP44-231 , Δ114–138 , and 1–138; Fig 6A and 6B ) . Two constructs ( Δ97–113 and Δ63–73 ) did not rescue above mutant levels of FM 4–64 . While residues 63–73 have not been characterized , the Δ97–113 result is consistent with the findings of previous publications in humans and mice , showing that mutations in this intracellular region impair hearing and hair cell function [24 , 26] . Three constructs were capable of producing partial rescue ( SP63-231 , CD8-2TM , and 2TM-CD8 ) . Each one of the five dysfunctional constructs altered part of a contiguous region of Tmie: the 2TM and adjacent domains . These results highlight this region of Tmie as vital for function . To determine whether any of the constructs also produce a dominant effect on hair-cell function , we compared FM label in wild type larvae with or without the individual transgenic tmie constructs ( Fig 6D ) . Expression of GFP-tagged SP63-231 or Δ63–73 , which yielded impaired rescue in tmieru1000 larvae , caused reduced FM label in transgenic wild type cells ( Fig 6C and 6D ) . Interestingly , both dominant negative constructs delete parts of the extracellular region of Tmie . Bath applied FM dye demonstrates the presence of permeable MET channels , but does not reveal any changes in mechanically evoked responses in hair cells . Therefore , we also recorded microphonics of mutant larvae expressing individual tmie transgenes . Reduced hair-cell counts have been observed in neuromasts of MET mutants at 6 dpf but not at 2 dpf [11] , however , the amplitude of microphonics increases with age and cell counts [38] . As a compromise , we used 3 dpf larvae and recorded from the inner ear where there is a larger population of hair cells . This earlier time point additionally allowed us to determine MET activity near the onset of mechanotransduction to rule out indirect or progressive effects of Tmie loss . We inserted a recording pipette into the inner ear cavity and pressed a glass probe against the head ( Fig 7A ) . Using a piezo actuator to drive the probe , we delivered a step stimulus at increasing driver voltages while recording traces in current clamp ( Fig 7B ) . For each transgenic tmie line , we measured the amplitude of the response at the onset of stimulus ( Fig 7C–7I ) . We limited our analysis to the lines expressing constructs that failed to fully rescue FM labeling ( Fig 7E–7I ) . As positive controls , we used the full-length tmie-GFP line ( Fig 7C ) and also included the SP44-231-GFP line ( Fig 7D ) , expressing the cleavage product mimic . Both control constructs fully rescued the responses in tmieru1000 larvae . Consistent with a reduction in labeling with FM dye , we found that the microphonic responses were strongly or severely reduced in tmieru1000 larvae expressing the GFP-tagged constructs SP63-231 , Δ63–73 , CD8-2TM , 2TM-CD8 or Δ97–113 ( Fig 7E–7I ) . We again saw dominant negative effects in wild type larvae expressing transgenic SP63-231-GFP or Δ63-73-GFP ( Fig 7E and 7F , blue traces ) . After identifying functional regions of Tmie , we asked whether these regions are involved in regulating Tmc localization . To answer this question , we quantified hair bundle expression of transgenic Tmc2b-GFP in hair cells of tmieru1000 mutant larvae stably co-expressing individual transgenic tmie constructs ( Fig 8H ) . As in Fig 4 , we tagged our tmie constructs with p2A-NLS ( mCherry ) so that Tmc2b-GFP expression in the hair bundles could be imaged separately . Because we did not generate stable transgenic lines for all constructs , we were concerned that variable levels of Tmie protein expression among siblings , particularly low levels , might confound the experiment . However , examination of our lowest expressing p2A-NLS ( mCherry ) constructs ( Tmie , CD8-2TM , and Δ97–113 ) revealed no correlation between the mCherry and GFP signals; higher levels of nuclear mCherry signal did not correlate with higher bundle expression of GFP-tagged Tmc protein ( S5A Fig ) . Additionally , the Tmie-p2A-NLS ( mCherry ) line used in S5A Fig was also used for semi-qPCR as well as quantification of Tmc1-GFP signal . This low level of mCherry signal ( visualized in Fig 4B , lower panel ) corresponded to a 6 . 5-fold increase in tmie transcript ( Fig 4A ) and resulted in a 2 . 4-fold increase in Tmc1-GFP ( Fig 4C ) , comparable to the 2 . 5-fold increase of Tmc2b-GFP ( Fig 4E ) seen in a different Tmie-p2A-NLS ( mCherry ) line with brighter mCherry signal ( visualized in Fig 4D , lower panel ) . Taken together , these results indicate that even very low-expressing transgenes produce saturating levels of Tmie protein . We confirmed the lack of correlation between mCherry and Tmc2b-GFP signals with our other tmie constructs ( S5B Fig ) . We then proceeded to examine bundle expression of Tmc2b-GFP when co-expressed with the positive control of SP44-231 and the five tmie constructs that yielded impaired mechanosensitivity . As an additional positive control , we also included analysis of the deletion Δ114–138 , a construct with full functional rescue and normal localization . As in Figs 3 and 4 , we used the taller and more accessible bundles of the lateral crista for quantification . Four constructs showed full rescue of Tmc2b-GFP levels in the bundles of tmieru1000 larvae . The SP44-231 cleavage mimic produced highly variable levels with examples in the wild type range and others increasing Tmc2b-GFP expression well above wild type levels ( Fig 8B and 8H ) . The higher levels of Tmc2b-GFP achieved with SP44-231 are comparable to the signal increase caused by overexpression of full-length Tmie ( Figs 4D , 4E and 8A , right panel ) . We suspect that the exogenous Gria2a signal peptide leads to variable processing of SP44-231 and thus contributes to this variability in Tmc2b-GFP fluorescence . In tmieru1000 larvae expressing the positive control construct Δ114–138 , we observed values of Tmc2b-GFP fluorescence in the wild type range , as expected ( Fig 8H , Δ114–138 ) . Surprisingly , constructs SP63-231 ( Fig 8C ) and 2TM-CD8 ( Fig 8F ) also gave rise to wild type levels of Tmc2b-GFP ( Fig 8H ) . When we recorded microphonics in these larvae , we found that co-expression of Tmc2b-GFP with either SP63-231 ( S6A Fig ) or 2TM-CD8 ( S6C Fig ) resulted in better functional rescue of tmieru1000 than when either tmie construct was expressed without Tmc2b-GFP ( Fig 7E and 7H ) . We also determined that microphonic potentials correlated with the levels of Tmc2b-GFP in the bundles of tmieru1000 larvae co-expressing 2TM-CD8 , r = 0 . 879 , p = 0 . 0018 ( S6D Fig ) . The same analysis of SP63-231 showed a positive trend , r = 0 . 722 , yet was statistically non-significant ( p = 0 . 1682 ) , which may be due to small sample size ( S6B Fig ) . These results suggest that in the lines of SP63-231 and 2TM-CD8 , functional rescue is Tmc dose-dependent . Of the three constructs that produced little to no functional rescue , CD8-2TM ( Fig 8E ) and Δ97–113 ( Fig 8G ) had severely reduced levels of Tmc2b-GFP in hair bundles ( Fig 8H ) . In tmieru1000 larvae expressing the Δ63–73 construct , there was severely reduced but still faintly detectable Tmc2b-GFP signal ( Fig 8D ) . As with the functional rescue experiments , this difference was not statistically significant ( Fig 8H ) . Interestingly , the bulk of this signal was observed in immature bundles ( Fig 8D , arrows , and S7 Fig ) , but there was some detectable Tmc2b-GFP signal in mature bundles ( S7 Fig ) . To generalize our findings to Tmc1 , we examined Tmc1-GFP localization in tmieru1000 larvae co-expressing the null-function construct CD8-2TM ( S8 Fig ) . As with Tmc2b-GFP , we detected no bundle expression of Tmc1-GFP . Overall , these results suggest that the level of functional rescue by the tmie constructs is correlated to the amount of Tmc1/2b present in the hair bundle .
There are still many open questions regarding the sequence of events for assembly of the MET complex . One question is whether assembly occurs before or after ascension of stereocilia . Previous reports demonstrate that bundle targeting of Pcdh15a relies upon the presence of Lhfpl5a [18 , 19 , 40] . Likewise , LHFPL5 requires PCDH15 for localization at stereociliary tips [19 , 40] . Here , we demonstrate that Tmc1 and 2b require Tmie for targeting to the bundle , while Pcdh15a and Lhfpl5a are unaffected in tmie mutants . Collectively , these findings suggest that Pcdh15a-Lhfpl5a traffick together in one unit , and Tmie-Tmcs traffick in a separate unit . This conclusion supports the idea that the MET complex proteins traffick to stereocilia in multiple groups and then assemble the full MET complex at the site of transduction . Another interesting finding from our data is that Tmie may be the exception to the rule of co-dependent transport to the hair bundle because it retains normal trafficking patterns in the absence of individual MET proteins ( Pcdh15a , Lhfpl5a , or Tmc1/2a/2b ) . As our experiment used an overexpressed Tmie transgene , measurement of endogenous levels of Tmie in other MET mutants would be an important follow-up experiment for future studies . Using our transgenic tmie constructs , we identified specific regions of Tmie that are required for trafficking or function ( Fig 9 ) . Despite reduced bundle targeting , a truncated version of Tmie containing amino acids 1–138 showed full functional rescue , though only when it was overexpressed as a transgene ( S3 Fig ) . We speculate that higher levels of expression enabled this truncated version to overcome inefficient trafficking . Conversely , despite normal localization to the bundle , expression of the Δ97–113 construct did not rescue function at all , even when it was likewise overexpressed . These results demonstrate that Tmie’s functional role is separate from its ability to target to the bundle . In total , three constructs resulted in reduced targeting of Tmie to the bundle , namely SP63-231 , CD8-2TM , and the 1–138 construct , the last of which truncates the C-terminus . As the predicted topology of Tmie places the C-terminus on the cytoplasmic side of a vesicle , this topology would expose amino acids 97–231 for recognition by trafficking machinery . Alteration of the C-terminus results in partial or full mistargeting of Tmie . We suspected a potential bundle targeting signal in amino acids 139–231 . However , when we express this peptide ( 139-231-GFP ) , fluorescence is diffused throughout the cell , including the kinocilium and nucleus . These results suggest that while the C-terminus is integral to bundle targeting , there are other regions of Tmie that are required for proper stereocilia localization . These regions include a portion of the external peptide sequence and residues in the 2TM domain of Tmie ( Fig 9B , blue outline ) . Reduced efficiency in bundle targeting may be due to impaired interactions with externally localized components of the MET complex or partial misfolding . This idea is supported by the finding that expression of constructs SP63-231 and 2TM-CD8 lead to impaired rescue of function in tmieru1000 larvae , while the partially mislocalized truncation construct ( 1–138 ) showed full functional rescue when overexpressed as a transgene . The regulatory role of Tmie with respect to the Tmcs is strongly supported by the strikingly different effects of loss of Tmie versus overexpression of Tmie . When Tmie is absent from the bundles , so are Tmc 1 and 2b; when Tmie is overexpressed , the bundle levels of Tmc1 and 2b are boosted as well . These results disagree with a previous finding in mice showing that Myc-TMC2 is present in hair bundles of TMIE-deficient cochlear hair cells [26] . This discrepancy may be due to different methods of expression , different hair cell types , or species-specific effects . Zhao et al . used a cytomegalovirus promoter to drive high levels of expression of Myc-TMC2 in an in vitro explant of cochlear tissue . Vestibular hair cells were not characterized , and the effects of TMIE-deficiency on localization of TMC1 , which is the dominant TMC protein in mature cochlear hair cells , was not reported in their study . Further investigation is warranted to determine if the Tmie-Tmc relationship uncovered by our experiments is a conserved feature or is potentially dependent on the type of hair cell , as MET components may vary among different cell types . One important question is whether Tmie and the Tmcs can physically interact to form a complex that is transported to the hair bundle . A direct interaction of the mouse TMC1/2 and TMIE proteins was not detected in a heterologous system [26] . However , our in vivo analysis suggests a strong dependency of the Tmcs on Tmie . There may be an indirect interaction , or an as-yet-undetected direct interaction between the Tmcs and Tmie , perhaps missed by previous experiments because the native hair cell environment is essential for the interaction to occur . When mammalian TMCs are expressed in heterologous cell types , they mainly populate inner membrane compartments such as the endoplasmic reticulum [8 , 10 , 11 , 15 , 26] . Successful folding and trafficking of the TMCs to the plasma membrane may require specialized trafficking components in the hair-cell secretory pathway . One example of such as factor is the Golgi-enriched Tomt protein , which is essential for Tmc1/2 trafficking in hair cells [11 , 36]; there are likely to be other components as well . While the membrane topology of Tmie has not been biochemically determined , Phobius software predicts an N-terminal signal peptide in mouse and human TMIE , and a transmembrane helix in zebrafish Tmie [41] . Interestingly , the orthologues in C . elegans and D . melanogaster do not contain this first hydrophobic region of Tmie . Upon removal of this region from zebrafish Tmie ( construct SP44-231 ) , we observed a localization pattern identical to full-length Tmie and full functional rescue of tmie-deficient fish . In addition , expressing the SP44-231 construct in tmieru1000 larvae rescues Tmc2b-GFP bundle expression to wild type levels or higher . To our knowledge , these results are the first in vivo evidence that vertebrate Tmie can function without the first hydrophobic domain . Our study supports the notion that Tmie undergoes cleavage , resulting in a single-pass membrane protein that functions in the MET complex ( Fig 9B ) . Only two of our Tmie constructs displayed dominant negative effects in wild type larvae ( SP63-231 and Δ63–73 ) , suggesting successful integration into the MET complex and competition or interference with endogenous Tmie . Both of these constructs delete unique parts of the extracellular region of Tmie , and have little to no rescue of mechanosensitivity in tmieru1000 mutants . The transmembrane chimeras in our study also yield impaired rescue but do not appear to affect the function of endogenous Tmie in wild-type hair cells . These data suggest that the entire 2TM domain is required to produce the dominant negative effect on endogenous Tmie . Combined with the finding that replacement of the 2TM with an unrelated helix causes instability of Tmie in mature hair cells , we propose that the 2TM is essential for integration of Tmie into the MET complex . One construct does not fit this hypothesis: Δ97–113 , which contains the full 2TM and has no functional rescue , but does not have a dominant negative effect . However , this region contains arginine residues that have previously been implicated in human deafness [24 , 42–44] and that in mice were linked to interactions with PCDH15-CD2 [26] . It is possible that the cytoplasmic region adjacent to the 2TM is also required for full integration into the MET complex , perhaps through interactions unrelated to the Tmcs . Interestingly , one of the mouse mutations , R93W , resulted in loss of TMIE localization at the site of MET in cochlear hair cells . In contrast to these findings , when we remove this entire intracellular region from zebrafish Tmie , it is still capable of targeting to hair bundles . This result may reflect different targeting motifs for different hair-cell types or species differences in recognition sequences for trafficking machinery . When co-expressed with Tmc2b-GFP , our Tmie constructs reveal a strong link between function and Tmc bundle expression . In addition to defects in targeting Tmcs to the hair bundle ( constructs Δ97–113 and CD8-2TM ) , our data also suggest a role for Tmie in maintaining the levels of Tmc2b in stereocilia . We previously reported that trafficking and stability/maintenance are two distinct events that can be separated experimentally by examining transgene expression in immature vs mature bundles [18] . The only region of Tmie with a clear effect on maintenance of bundle Tmc signal was amino acids 63–73 . Loss of these residues resulted in Tmc2b-GFP signal in immature hair cells suggesting proper trafficking , but a large reduction in mature cells suggesting poor maintenance in the MET complex . Based on our data , we conclude that the first half of the transmembrane domain and the intracellular residues 97–113 are required for targeting the Tmc subunits to the site of MET ( Fig 9B , yellow fill ) , while the extracellular residues 63–73 stabilize Tmc expression in the MET complex ( Fig 9B , orange fill ) . Since co-expression of Tmc2b-GFP can overcome the functional deficits in constructs SP63-231 and 2TM-CD8 , we propose that residues 44–62 and the second half of the 2TM are important but not absolutely essential to regulating Tmc bundle expression . This finding reinforces the significance of our data obtained with the constructs Δ63–73 , CD8-2TM , and Δ97–113 , which still fail to rescue Tmc2b-GFP levels . In addition , we demonstrated that CD8-2TM also does not rescue expression of Tmc1-GFP , suggesting that similar mechanisms are employed for trafficking of both Tmc1 and Tmc2 members of the Tmc superfamily . In sum , through a systematic in vivo analysis of tmie via transgenic expression , we identified new functional domains of Tmie . We demonstrated a strong link between Tmie’s function and Tmc1/2b expression in the bundle . Evidence continues to mount that the Tmcs are pore-forming subunits of the MET channel , and our results implicate Tmie in promoting and maintaining the localization of the MET channel . The precise mechanism underlying Tmie’s regulation of the Tmcs awaits further investigation .
Animal research was in compliance with guidelines from the Institutional Animal Care and Use Committee at Oregon Health and Science University ( protocol # IP00000100 ) . We maintained zebrafish ( Danio rerio , txid7955 ) at 28°C and bred according to standard conditions . In this study , we used the following zebrafish mutant lines: tmieru1000 [22] , tmiet26171 , pcdh15apsi7 [10] , lhfpl5atm290d [45] , and tomttk256c [11] . We maintained all zebrafish lines in a Tübingen or Top long fin wild type background . We examined larvae at 3–7 days post-fertilization ( dpf ) , of undifferentiated sex . For experiments involving single transgenes , non-transgenic heterozygotes were crossed to transgenic fish in the homozygous or heterozygous mutant background . We genotyped larvae by PCR and subsequent digestion or DNA sequencing , or by behavior phenotype prior to experiments , as detailed for each experiment below . Primers are listed in Table 1 . tmie ( accession no . F1QA80 ) , tmc1 ( accession no . F1QFU0 ) , tmc2b ( accession no . F1QZE9 ) , tomt ( accession no . A0A193KX02 ) , pcdh15a ( accession no . Q5ICW6 ) , lhfpl5a ( accession no . F1Q837 ) , actba ( accession no . Q7ZVI7 ) . The following previously published transgenic lines were used: Tg ( -6myo6b:β-actin-GFP-pA ) [34] , Tg ( -6myo6b:pcdh15aCD3-mEGFP-pA ) [18] , and Tg ( -6myo6b:GFP-lhfpl5a-pA ) , Tg ( -6myo6b:Tmc1-mEGFP-pA ) , Tg ( -6myo6b:Tmc2b-mEGFP-pA ) [11] . To generate the tmie expression vectors , we used the Tol2/Gateway system [46] . The pDestination vector contained either a cmlc2:GFP heart marker or α-ACry:mCherry eye marker for sorting . pDESTtol2pACrymCherry was a gift from Joachim Berger and Peter Currie ( Addgene plasmid # 64023 , [47] ) . The 5’ entry vector contained the promoter for the myosin 6b gene , which drives expression only in hair cells . All tmie transgenic constructs were subcloned into the middle entry vector using PCR or bridging PCR and confirmed by sequencing . The primers for each vector are listed in Table 1 . For GFP-tagging , we used a 3’ entry vector with a flexible linker ( GHGTGSTGSGSS ) followed by mEGFP . For NLS ( mCherry ) experiments , a p2A self-cleaving peptide ( GSGATNFSLLKQAGDVEENPGP ) was interposed between the tmie construct and the NLS ( mCherry ) . This causes translation of a fusion protein that is subsequently cleaved into the two final proteins . The 2TM helix replacements from residues 21–43 result in the following chimeric helices: CD8 ( YIWAPLAGTCGVLLLSLVITLYC ) , CD8-2TM ( YIWAPLAGTCGILAIIITLCCIF ) , and 2TM-CD8 ( LWQVVGIFSMFVLLLSLVITLYC ) . Multisite Gateway LR reactions [48 , 49] were performed to generate the following constructs: pDest ( -6myo6b:tmie-GFP-pA ) , pDest ( -6myo6b:tmie-short-GFP-pA ) , pDest ( -6myo6b:SP44-231-GFP-pA ) , pDest ( -6myo6b:SP63-231-GFP-pA ) , pDest ( -6myo6b:Δ63-73-GFP-pA ) , pDest ( -6myo6b:CD8-GFP-pA ) , pDest ( -6myo6b:CD8-2TM-GFP-pA ) , pDest ( -6myo6b:2TM-CD8-GFP-pA ) , pDest ( -6myo6b:Δ97-113-GFP-pA ) , pDest ( -6myo6b:Δ114-138-GFP-pA ) , pDest ( -6myo6b:1-113-GFP-pA ) , pDest ( -6myo6b:1-138-GFP-pA ) , pDest ( -6myo6b:tmie-p2A-NLS ( mCherry ) -pA ) , pDest ( -6myo6b:SP63-231-p2A-NLS ( mCherry ) -pA ) , pDest ( -6myo6b:Δ63-73-p2A-NLS ( mCherry ) -pA ) , pDest ( -6myo6b:CD8-2TM-p2A-NLS ( mCherry ) -pA ) , pDest ( -6myo6b:Δ97-113-p2A-NLS ( mCherry ) -pA ) . To generate transgenic fish , plasmid DNA and tol2 transposase mRNA were co-injected into single-cell fertilized eggs , as previously described ( Kwan et al . , 2007 ) . For each construct , 200+ eggs from an incross of tmieru1000 heterozygotes were injected . To obtain stable transgenic lines , >24 larvae with strong marker expression were raised as potential founders . For each GFP-tagged transgene , at least two founder lines were generated and examined for visible bundle expression . To equalize expression of each transgene within a clutch , for each tmie construct we isolated a line with a transgene transmission rate of 50% , indicating single transgene insertion . The CD8-2TM-GFP construct was the exception; we instead identified a single adult with mosaic transmission of the transgene ( transmitted to >10% of offspring ) and used this line in FM and microphonics experiments . Imaging during the FM experiment confirmed that CD8-2TM-GFP was consistently highly expressed ( Fig 6A , CD8-2TM ) . For NLS ( mCherry ) experiments , injected fish were raised to adulthood and genotyped to identify tmieru1000 heterozygotes and homozygotes . We identified founders for each construct and then crossed these founders to tmieru1000 heterozygotes carrying Tg ( myo6b:tmc2b-GFP ) . This generated offspring that expressed both transgenes in the tmieru1000 mutant background , and we used these larvae for experiments . In SP44-231 , SP63-231 , and CD8-2TM , and full-length tmie in the Tmc1-GFP background , stable transgenic lines were generated from the founder before experiments were carried out . We anesthetized live larvae with E3 plus 0 . 03% 3-amino benzoic acid ethylester ( MESAB; Western Chemical ) and mounted in 1 . 5% low-melting-point agarose ( Sigma-Aldrich cas . # 39346-81-1 ) , with the exception of the morphology images from Figs 1A and 7A in which larvae were pinned with glass rods and imaged in E3 or extracellular solution containing MESAB . We captured the image in Fig 7A at room temperature using a Hamamatsu digital camera ( C11440 , ORCA-flash2 . 8 ) , MetaMorph Advanced NX software , and an upright Leica DMLFS microscope . We used differential interference contrast ( DIC ) with a Leica HC PL Fluotar 10x/0 . 3 lens . For all imaging except Fig 7A , images were captured at room temperature using an Axiocam MrM camera , Zeiss Zen software , and an upright Zeiss LSM700 laser-scanning confocal microscope . We used DIC with one of two water-immersion lenses: Plan Apochromat 40x/1 . 0 DIC , or Acroplan 63x/0 . 95 W . Laser power and gain were unique for each fluorophore to prevent photobleaching . We averaged 2x or 4x for each image , consistent within each experiment . The Tmc1-GFP and Tmc2b-GFP transgenes are very dim , and high laser power ( 4% ) and gain ( 1100 ) were necessary to detect signal in wild types . At these settings , autofluorescence from other wavelengths can falsely enhance the emission peak at 488 . To reduce detection of autofluorescence , we simultaneously collected light on a second channel with an emission peak at 640 nm . We sorted 5 dpf zebrafish larvae by behavior ( tap sensitivity and balance ) , then fixed them overnight at 4°C in PBS containing fresh 1% EM-grade formaldehyde ( Electron Microscopy Sciences , Hatfield , PA ) and fresh 2% EM-grade glutaraldehyde ( Tousimis Research Corporation , Cat # 1060A ) . For further fixation and contrast , we incubated larvae for 10 min on ice with 1% osmium tetroxide ( Electron Microscopy Sciences , Hatfield , PA ) , followed by 1 hr on ice in 1% uranyl acetate ( Electron Microscopy Sciences , Hatfield , PA ) . We dehydrated larvae in a graded series of EM-grade acetone ( Electron Microscopy Sciences , Hatfield , PA ) , then embedded in Embed-812 ( Electron Microscopy Sciences , Hatfield , PA ) . We collected thin sections on PELCO 200 mesh nickel grids ( Ted Pella , Redding , CA ) , and stained with 4% uranyl acetate and Reynolds lead citrate . We collected electron microscopy images on an FEI Tecnai 12 BioTWIN transmission electron microscope ( ThermoFisher Scientific , Hillsboro , OR ) operated at an 80 kV accelerating voltage . Experiments were conducted as previously described [50] . Briefly , 6 dpf larvae were placed in six central wells of a 96-well microplate mounted on an audio speaker . Pure tones were played every 15 s for 3 min ( twelve 100 ms stimuli at 1 kHz , sound pressure level 157 dB , denoted by asterisks in Fig 1B ) . Responses were recorded in the dark inside a Zebrabox monitoring system ( ViewPoint Life Sciences ) . Peaks represent pixel changes from larval movement . A response was considered positive if it occurred within two seconds after the stimulus and surpassed threshold to be considered evoked , not spontaneous ( Fig 1B , green indicates movement detected , magenta indicates threshold surpassed ) . For each larva , we used the best response rate out of three trials . Response was quantified by dividing the number of positive responses by total stimuli ( 12 ) and converting to a percent . If the larvae moved within two seconds before a stimulus , that stimulus was dropped from the trial data set ( i . e . the number of total stimuli would become 11 ) . Each data point on the graph in Fig 1C is the percent response of an individual larva . We used a two-tailed unpaired t-test with Welch’s correction to determine significance , ****p < 0 . 0001 . Wild type and mutant larvae were genotyped by FM 1–43 labeling . We used an anti-Pcdh5a monoclonal antibody directed against amino acids 1–324 [10] as described previously [18] . In brief , we sorted wild type and ru1000 larvae at 5 dpf by behavior ( tap response and balance ) . We then fixed 8 larvae per 2ml microtube in Phosphate Buffered Saline + 0 . 01% Tween-20 ( PBST ) + 4% paraformaldehyde , rotating overnight on a nutator at 4°C . We washed with PBST 3x for 10 min each , then permeabilized with PBS + 0 . 5% TritonX100 on a shaking table ( 50 rpm ) for 1 hour , then at 4°C overnight without shaking . We blocked with PBS + 1% DMSO + 5% goat serum + 1% Bovine Serum Albumen ( BSA , Sigma-Aldrich Lot # SLSF5374V ) for 2 hours minimum at room temperature on a shaking table ( 50 rpm ) . We applied the mouse anti-1C4 Pcdh15a antibody at 1:200 in blocking buffer overnight on the nutator at 4°C . We washed with PBST 3x for 15 minutes each on the shaking table ( 50 rpm ) . We applied blocking buffer + secondary antibody , 546-conjugated goat anti-mouse IgG at 1:500 concentration ( Life Technologies ) , and also included phalloidin-488 at 1:100 to visualize Beta-actin filaments in hair bundles , on a shaking table ( 50 rpm ) for 4–5 hours in the dark at room temperature . We washed with PBST 3x for 10 minutes each and stored at 4°C before imaging . For S3 Fig and Fig 4A , we extracted total RNA using the RNeasy mini kit ( Qiagen ) . Larvae were homogenized using a 25 gauge syringe ( Becton Dickinson , ref # 309626 ) . To reverse transcribe cDNA we used the RNA to cDNA EcoDry Premix ( Clontech , Cat # 639549 ) . We then performed PCR on the cDNA using High Fidelity Phusion polymerase ( New England Biolabs , Cat # M0530 ) . To amplify the short isoform of Tmie ( Tmie-short ) and the t26171 allele , we sorted 30 wild type and 30 t26171 larvae by behavior ( tap sensitivity and balance defect ) at 5 dpf and used the pooled cDNA as template for the PCR reactions . Primers are listed in Table 1 . Both transcripts were verified by DNA sequencing . For Fig 4A , we sorted non-transgenic wild type ( hetereozygote ) and tmieru1000 ( homozygote ) larvae by behavior at 5 dpf; the transgenic pool contained a mix of tmieru1000 hetereozygotes and homozygotes ( no behavior difference because full-length tmie transgene rescued phenotype ) . The tmie transgene was a single insert with low mCherry expression , the same line used for the data in Fig 4B and 4C , and S5 Fig , Tmie . For each genotype , n = 20 larvae were homogenized . We performed PCR at 30 , 35 , and 40 cycles . We ran on 2% gel and loaded 25 ul of tmie PCR product; we loaded only 10 ul of gapdh product to avoid saturating the bands . We quantified the 40 cycle bands in ImageJ using gapdh levels to normalize tmie levels . Primers are listed in Table 1; both tmie and gapdh produced 98 bp amplicons . The primers for tmie amplified a region within exon 4 in order to detect transcripts from both transgene and endogenous tmie . Larvae were briefly exposed to E3 containing either 3μM N- ( 3-Triethylammoniumpropyl ) -4- ( 4- ( Dibutylamino ) styryl ) Pyridinium Dibromide ( FM 1–43 , Life Technologies ) or 3μM of the red-shifted N[scap]- ( 3-triethylammoniumpropyl ) -4- ( 6- ( 4- ( diethylamino ) phenyl ) hexatrienyl ) pyridinium dibromide ( FM4-64; Invitrogen ) . After exposure for 25–30 seconds , larvae were washed 3x in E3 and neuromasts were imaged from top-down . Neuromasts were chosen based upon their orientation , bundles pointing upward preferred . Typically , three neuromasts were examined per larvae , from the head or trunk depending on best angle; we never observed differences in posterior/anterior labeling . Laser power was adjusted for each experiment to avoid saturation of pixels but was consistent within a clutch . FM levels were quantified in ImageJ [51] as described previously [10] . In brief , maximum projections of each neuromast were generated using seven optical sections , beginning at the cuticular plate and moving down through the soma ( magenta bracket , Fig 1G ) . We then measured the integrated density of the channel with an emission peak at 640 nm for FM 4–64 , and at 488 nm for FM 1–43 . This integrated density value was divided by the number of cells , thus converting each neuromast into a single plot point of integrated density per cell ( IntDens/cell ) . Statistical analyses were always performed between direct siblings . For Fig 6 , individual values were divided by the mean of the sibling wild type neuromasts in order to display the data as a percent of wild type , making it easier to compare across groups . Statistical significance was determined within an individual clutch using one-way ANOVA . We PCR-genotyped all larvae from the Tmie-GFP line; after confirming results , for all other tmie construct experiments , we continued to genotype transgenic larvae by PCR but genotyped non-transgenic wild type and tmieru1000 larvae by behavior and expected FM labeling patterns . Larvae at 3 dpf were anesthetized in extracellular solution ( 140mM NaCl , 2mM KCl , 2mM CaCl2 , 1mM MgCl2 , and 10mM 4- ( 2-hydroxyethyl ) -1-piperazineethanesulfonic acid ( HEPES ) ; pH 7 . 4 ) containing 0 . 02% 3-amino benzoic acid ethylester ( MESAB; Western Chemical ) . Two glass fibers straddled the yolk to pin the larvae against a perpendicular cross-fiber . Recording pipettes were pulled from borosilicate glass with filament , O . D . : 1 . 5 mm , O . D . : 0 . 86 mm , 10 cm length ( Sutter , item # BF150-86-10 , fire polished ) . Using the Sutter Puller ( model P-97 ) , we pulled the pipettes into a long shank with a resistance of 10-20MΩ . We then used a Sutter Beveler with impedance meter ( model BV-10C ) to bevel the edges of the recording pipettes to a resistance of 3–6 MΩ . We pulled a second pipette to a long shank and fire polished to a closed bulb , and then attached this rod to a piezo actuator ( shielded with tin foil ) . The rod was then pressed to the front of the head behind the lower eye , level with the otoliths in the ear of interest , to hold the head in place while the recording pipette was advanced until it pierced the inner ear cover . Although it has been demonstrated that size of response is unchanged by entry point [52] , we maintained a consistent entry point dorsal to the anterior crista and lateral to the posterior crista ( see Fig 7A ) . After the recording pipette was situated , the piezo pipette was then moved back to a position in light contact with the head . We drove the piezo with a High Power Amplifier ( piezosystem jena , System ENT/ENV , serial # E18605 ) , and recorded responses in current clamp mode with a patch-clamp amplifier ( HEKA , EPC 10 usb double , serial # 550089 ) . Each stimulus was of 20 ms duration , with 20 ms pre- and post-stimulus periods . We used either a sine wave or a voltage step and recorded at 20 kHz , collecting 200 traces per experiment . In Fig 1H , we used a 200 Hz sine wave at 10V , based on reports that 200 Hz elicited the strongest response [38] . In Fig 7 , we used multiple step stimuli at varying voltages ( 2V , 3V , 4V , 5V , 6V , and 10V ) . The piezo signal was low-pass filtered at 500Hz using the Low-Pass Bessel Filter 8 Pole ( Warner Instruments ) . Microphonic potential responses were amplified 1000x and filtered between 0 . 1–3000 Hz by the Brownlee Precision Instrumentation Amplifier ( Model 440 ) . We used Igor Pro for analysis . We averaged each set of 200 traces to generate one trace response per fish , then measured baseline-to-peak amplitude . These amplitudes were used to generate the graphs in Fig 7 . Statistical significance was determined by 2-way ANOVA comparing all groups to wild type non-transgenic siblings . We used PCR to genotype larvae . Using ImageJ , maximum projections of each crista were generated for analysis ( 5 sections per stack for Tmc1-GFP in Fig 3D and Tmc2b-GFP in Fig 3F , and 13 sections per stack for Tmc1-GFP in Fig 4C and Tmc2b-GFP in Fig 4E . Quantification of Tmc-GFP bundle fluorescence was achieved by outlining each bundle to encompass the entire region of interest ( ROI ) in a single hand-drawn area ( Fig 8A , right panel , black outline ) . For S2 Fig , the ROI was the soma region of the crista or the entire cell including soma and bundle ( max projection of 13 sections ) . For S5 Fig , the ROI was the soma region containing nuclei of hair cells . In the ROI , we quantified the integrated density of the channel with an emission peak at 480 nm for GFP-tagged constructs , and with an emission peak at 640nm for mCherry . For GFP-tagged constructs , this was repeated in the region above the bundles containing only inner ear fluid and the kinocilia in order to subtract background fluorescence . Background for nuclear mCherry was measured from the soma region between the bundle and nuclei . Each lateral crista generated one data point in all quantification graphs . In some cases , we saw single cells that appeared to have a GFP-fill , probably due to clipping of the GFP tag . We excluded these cells from analyses , since they falsely increased the signal . Likewise , for quantification of soma GFP , we excluded crista with immature hair cells that highly expressed the myo6b driven transgene . Due to the 3D nature of the mound-shaped cristae , it was difficult to completely exclude the apical soma region , leading the bundle signals to average above zero in tmieru1000 expressing either Tmc1-GFP or Tmc2b-GFP . For determination of significance , we used the Kruskal-Wallis test for quantification of Tmc2b-GFP bundle signal in the background of co-expressed SP44-231 , SP63-231 , and 2TM-CD8; all others quantifications with three or more groups are one-way ANOVA . For comparison of two groups , we used two-tailed unpaired t-tests with Welch’s correction . We PCR-genotyped all larvae from Fig 3B–3J; when introducing co-expression of tmie constructs , we continued to PCR-genotype larvae containing the tmie-transgene but genotyped non-tmie-transgene wild type and tmieru1000 larvae by behavior . In experiments subjected to quantitative analysis , we used G*power [53] to determine the sample size required . For microphonics , we used the strongest driver stimulus setting ( 10V ) in these determinations . | Hair cells mediate hearing and balance through the activity of a mechanosensitive channel in the cell membrane . The transmembrane inner ear ( TMIE ) protein is an essential component of the protein complex that gates this so-called mechanotransduction channel . While it is known that loss of TMIE results in deafness , the function of TMIE within the complex is unclear . Using zebrafish as a deafness model , Pacentine and Nicolson demonstrate that Tmie is required for the localization of the channel subunits , transmembrane channel-like ( Tmc ) proteins Tmc1/2b . They then evaluate thirteen unique versions of Tmie , each containing mutations in different domains of Tmie . This analysis reveals that specific mutated versions of Tmie reduce hair cell activity , and that these same dysfunctional versions also cause reduced Tmc expression at the normal site of the channel . These findings link hair cell activity with the levels of Tmc in the bundle , reinforcing the notion that the Tmcs are the pore-forming subunits of the mechanotransduction channel . The authors conclude that Tmie , through distinct regions , is involved in both trafficking and stabilizing the channels at the site of mechanotransduction . | [
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"model... | 2019 | Subunits of the mechano-electrical transduction channel, Tmc1/2b, require Tmie to localize in zebrafish sensory hair cells |
Bacterial pathogenicity relies on a proficient metabolism and there is increasing evidence that metabolic adaptation to exploit host resources is a key property of infectious organisms . In many cases , colonization by the pathogen also implies an intensive multiplication and the necessity to produce a large array of virulence factors , which may represent a significant cost for the pathogen . We describe here the existence of a resource allocation trade-off mechanism in the plant pathogen R . solanacearum . We generated a genome-scale reconstruction of the metabolic network of R . solanacearum , together with a macromolecule network module accounting for the production and secretion of hundreds of virulence determinants . By using a combination of constraint-based modeling and metabolic flux analyses , we quantified the metabolic cost for production of exopolysaccharides , which are critical for disease symptom production , and other virulence factors . We demonstrated that this trade-off between virulence factor production and bacterial proliferation is controlled by the quorum-sensing-dependent regulatory protein PhcA . A phcA mutant is avirulent but has a better growth rate than the wild-type strain . Moreover , a phcA mutant has an expanded metabolic versatility , being able to metabolize 17 substrates more than the wild-type . Model predictions indicate that metabolic pathways are optimally oriented towards proliferation in a phcA mutant and we show that this enhanced metabolic versatility in phcA mutants is to a large extent a consequence of not paying the cost for virulence . This analysis allowed identifying candidate metabolic substrates having a substantial impact on bacterial growth during infection . Interestingly , the substrates supporting well both production of virulence factors and growth are those found in higher amount within the plant host . These findings also provide an explanatory basis to the well-known emergence of avirulent variants in R . solanacearum populations in planta or in stressful environments .
Studies in a number of bacterial pathogens in recent years have made it increasingly clear that the ability to assimilate nutrients in the course of host infection is crucial for pathogenesis [1–5] . Pathogens are known to specifically employ amino acid and sugar transporters to gain access to nutrients [6–7] and may subvert the host cell metabolism to re-orientate metabolic fluxes for its own purpose [8–10] . Consequently , the term of ‘nutritional virulence’ has emerged to describe the increasing evidence that , in addition to metabolic adaptation , specific virulence mechanisms enable pathogens to exploit host resources [11] . Metabolic potential ( i . e versatility ) is considered a critical element governing a pathogen’s virulence as well as its ability to survive in its host [12] . Beyond the necessity to collect resources within their host , pathogens face a resource allocation dilemma . In one hand they have to use nutritional resources to proliferate inside the host , and in the other hand they need to mobilize matter and energy for the production of essential virulence factors . Indeed , production and secretion of virulence factors are key steps of many infectious strategies to overcome the host immune system [13–14] , subvert the host metabolism [8 , 15–16] , and/or kill the host and succeed in transmission [17] . The resource allocation trade-off is well documented in bacteria [18]: it has been shown for example to occur in the survival / multiplication balance under stress conditions [19] and there is evidence that bacterial growth strategies are the result of trade-offs in the economy of the cell [20–21] . However , this aspect has been poorly studied in the case of pathogens which have to simultaneously acquire nutrients , multiply and produce costly virulence factors in a stressful host environment . Although it is logical to presume that many pathogens experience a resource allocation trade-off to maintain both the proliferation ( growth ) and the virulence factor production traits during infection , the quantification of the cost for virulence is not documented . The present study was aimed at understanding how bacterial metabolism supports simultaneously the burden of proliferation and the production of a broad array of virulence factors in the plant pathogen Ralstonia solanacearum . R . solanacearum strains belong to the beta class of Proteobacteria and collectively represent one of the most destructive plant pathogens worldwide due to their unusual wide range of host plants , long persistence in soil and water environments and their broad geographical distribution [22] . Cytological studies have shown that the bacterium invades plants through root wounds and rapidly colonizes the xylem vessels , where it multiplies extensively and produces large amounts of exopolysaccharide ( EPS ) [23–24] . EPS accumulation in the vascular system and the ensuing collapse of the water flow causes the wilting symptoms and eventually plant death . Expression of virulence factors in R . solanacearum is controlled by a sophisticated , multicomponent regulatory network that responds to environmental conditions , the sensing of host cells , and bacterial density [25] . More than 20 genes encoding transcriptional regulators , transmembrane sensors or signaling components have been described to control many virulence determinants such as EPS production , plant cell wall degrading enzymes , phytohormones or the Type III secretion system , and virulence-associated functions such as twitching or swarming motility . Much has been learned about how this virulence network functions in culture , but we still have few insights on the coordinated processes that occur during pathogenesis [26–27] . In this study , we used a genome-scale level approach to identify how the allocation of nutritional resource is orchestrated at the molecular level in the context of plant infection when virulence factors are abundantly produced . We conducted a genome-scale reconstruction of the metabolic network of R . solanacearum , together with a macromolecule network module , including many secreted virulence determinants , which could be used for constraint-based modeling [28–29] . By coupling modeling and experimental approaches , we provide evidence of a trade-off between the expression of growth-supporting pathways and virulence factors . This trade-off mechanism is controlled by the regulatory protein PhcA in a quorum-sensing depending fashion . By using metabolic flux analysis , we show that the cost for virulence factor production in R . solanacearum strongly impacts bacterial growth and can restrict the metabolic versatility of the pathogen in specific environmental conditions .
We generated a metabolic reconstruction consisting of the chemical reactions that transport and interconvert metabolites in R . solanacearum strain GMI1000 . This network reconstruction was achieved through the development of a bioinformatic pipeline ( see Material and Methods and S1 Material for details ) based on the functional annotation of the genome [30] , literature and database searches , and a manual curation protocol [31] . The reconstructed genome-scale metabolic network of strain GMI1000 encompasses 1825 biochemical reactions as well as 280 exchange reactions with the environment linking 1203 unique metabolites localized in three distinct compartments ( cytoplasm , periplasm , extracellular ) . The gene to protein to reaction ( GPR ) association network , which describes the logical relationship between the genes and the catalyzed chemical reaction , includes 1206 open reading frames . The general features of the metabolic reconstruction are displayed in Fig 1 . The full list of genes , metabolites , reactions and GPRs in the metabolic network can be found in S1 Table . The cell biomass composition was both determined experimentally and collected from bibliography ( S2 Table ) . We added to this reconstructed metabolic network a large subset of reactions involved in biosynthesis , activation and secretion of macromolecules , based on a large body of experimental data . Most of these secreted macromolecules are well-known extracellular virulence factors such as plant cell wall-degrading enzymes , extracellular polysaccharides or pathogenicity effector proteins [25] , see Fig 2 . This macromolecule module , thereafter called macromolecule network , encompasses 365 biochemical and transport reactions , in addition to 174 exchange reactions with the environment ( Fig 1 ) . Among biochemical reactions , 135 correspond to macromolecule biosynthesis reactions and 165 are specifically devoted to secretion processes ( Fig 1 , S1 Table ) . Because biosynthesis of macromolecule consumes substrates present within the metabolic network , the macromolecule network and the metabolic network were grouped in a global biochemical reaction network called iRP1476 . In total , 109 bibliographic references support the presence of biochemical reactions in the biochemical model ( S1 Table ) . The global model was converted into Systems Biology Markup Language ( SBML ) format suitable for constraint-based computing . It is available from S2 Material or can be downloaded on the website: http://lipm-bioinfo . toulouse . inra . fr/systemsbiology/models/rsolanacearum . In order to evaluate the performance of the biochemical reaction module in predicting the metabolic versatility of R . solanacearum , we first determined experimentally the global metabolic capacities of strain GMI1000 using Biolog phenotype microarrays ( see Material and Methods ) . We tested 864 environmental conditions with various Carbon , Nitrogen , Phosphorus and Sulfur sources . This included 190 carbon substrates , and 24 of them were also tested for promoting growth when supplemented to a minimal medium ( S1 Fig , S3 Table ) . The results revealed the usage of 36 carbon substrates by R . solanacearum ( Fig 3A , S3 Table ) . Dipeptides and nucleotides were neither significantly used as carbon substrates nor as nitrogen sources . Results from phenotype microarray assay were then compared to the model predictions using Flux Balance Analysis ( FBA ) [32] which calculates the feasibility of cell growth under the different environmental constraints ( see Material and Methods ) . The accuracy of the model prediction was 91 . 3% over 576 phenotypes , covering 91 . 4% of the substrates used by strain GMI1000 ( Fig 3B ) . However , 40% of all substrates predicted to be used by the model were not validated in the tested experimental conditions . A similar discrepancy was observed when comparing the results anticipated from the biochemical reaction network with the in vitro growth experiments ( 81 . 8% of precision ) . Hence , some metabolites appeared to be not used by strain GMI1000 although the corresponding transporters and the catabolic pathways were predicted to be present from the genome annotation . This observation was suggestive of a potential catabolite repression operating under the conditions tested . To validate the reconstructed model quantitatively , we compared the maximal growth rate predicted using FBA with experimental data . For this purpose , we monitored the rate of L-glutamate consumption ( Fig 4A ) and release of compounds in the medium by 1H nuclear magnetic resonance or release of macromolecule using biochemical assays . The kinetics of molecule secretion in the supernatant of cell cultures in minimal medium are shown in Fig 4B and detailed in S4 Table: we found the polyamine putrescine to be strongly produced ( S2 Fig ) , as well as EPS and proteins . The predicted maximal growth rate of the wild-type strain ( 0 . 439 h-1 ) was found to be 57% higher than the experimentally measured value ( 0 . 280 h-1 ± 0 . 017 , 2*σ ) based on the amount of consumed L-glutamate ( S4 Table ) . We therefore reasoned that this observed lower growth rate could be due to the metabolic cost for the secretion of virulence factors which adds up to the biosynthesis cost already included in the FBA analysis ( Fig 4C ) . We first investigated the cost for EPS production because EPS is known to be abundantly produced by R . solanacearum in planta when bacteria reach high cell density [27 , 33] . Simulations performed through FBA revealed that the expected gain of growth rate of an EPS-defective mutant was 0 . 012 h-1 , which is only 4 . 2% higher than the wild-type strain ( 0 . 280 h-1 ) . However , a more important difference was observed experimentally: we created a Δeps mutant impaired for EPS production and found that at high cell density ( i . e above 107 cells/ml ) in minimal medium , this eps mutant had a growth rate significantly higher ( 22% ± 6 CI ( 95% ) ) than the wild-type ( Fig 4D ) . The difference between the predicted cost for EPS biosynthesis and the global cost experimentally measured could be attributed to the energetic cost of EPS secretion . This cost was estimated to be around 8 , 5 mmol ( ATPeq ) ·g-1·h-1 in ATP equivalent . It cannot be excluded that this estimation includes additional indirect cost for EPS production in addition to its secretion . These results indicated that EPS biosynthesis and its secretion in the environment already represent a significant cost for the pathogen which has a clear impact on bacterial growth . The ‘cost for virulence’ hypothesis was further assessed by monitoring the growth rate of the phcA and xpsR regulatory mutants . xpsR encodes a regulator acting as a downstream cascade component required for activation of EPS biosynthesis [34] . phcA encodes a global phenotypic switch regulator under the control of a specific quorum sensing system [35] . PhcA is known to indirectly regulate the production of many virulence factors including EPS via xpsR , plant cell wall degrading enzymes and the type III secretion system [25] . At high cell density , the maximal growth rate of the xpsR mutant was significantly higher than the one of the wild-type strain ( 47% ± 8 CI ( 95% ) ) and the eps mutant ( 20% ± 6 CI ( 95% ) ) , see Fig 5A . An even sharper increase was observed with the phcA mutant since its measured maximal growth rate was 198% ± 15 CI ( 95% ) higher than the wild-type . Accordingly , competition experiments conducted in complete medium using an initial 1:1 ratio of the wild-type strain and the phcA mutant revealed that after only four hours the fitness of the phcA mutant was significantly higher than the wild-type ( S3 Fig ) . We then performed FBA with the phcA mutant grown in minimal medium to determine if the spectacular increased growth rate of this strain was due to an increased substrate consumption rate or to a rerouting of the metabolic fluxes from virulence factor production toward growth . We monitored a similar consumption rate of L-glutamate for the phcA mutant ( 7 . 68 mmol·g-1·h-1 ± 0 . 85 2σ ) compared to the wild-type strain ( 7 . 25 mM·g-1·h-1 ± 1 . 71 2σ ) ( p-value 0 . 57 ) . Based on the rate of L-glutamate usage and measured exchange fluxes , the optimal growth rate of the phcA mutant was calculated to be 0 . 435 h-1 , and found to be close ( only 6% deviation ) from the measured growth rate , 0 . 46 h-1 ± 0 . 01 ( 2*σ ) ( Fig 5B ) . This good match between the predicted and observed growth rate further supported the view that the phcA mutant had optimal metabolic capacities to sustain growth due to the absence of a cost for virulence factor production/secretion , contrary to the wild-type . Finally , we inferred from the metabolic flux analysis of the wild-type strain the overall cost of virulence factor production dependent on PhcA . To do so , we optimized an ATP hydrolyzing flux using FBA by setting the biomass production and the L-glutamate consumption rates determined for the wild-type . We found that the cost ( in ATP equivalent ) for the production of virulence factors controlled by PhcA corresponds to the significant amount of 38 . 9 mmol ( ATP ) ·g-1·h-1 . This amount of energy is indeed comparable to the amount of ATP ( 34 . 10 mmol·g-1·h-1 ) generated to supply biomass biosynthesis in the phcA mutant . The metabolic activity of the phcA mutant appeared to be focused toward proliferation with a specific usage of resources to sustain optimal growth . Because the activation of PhcA is under the control of a quorum-sensing system , we hypothesized that the wild-type strain should have a similar optimal growth rate at low cell-density ( i . e when PhcA is inactive , as in the phcA mutant ) . Therefore , we monitored the growth kinetics of the wild-type and the eps , xpsR and phcA mutant strains from low cell-density to high-cell density ( Fig 6 ) . The measured growth rate for the phcA strain at low cell density was in the same range than at high cell density . However , the growth rate of the wild-type strain at low cell density was similar to that of the phcA mutant at high cell density ( p value = 0 . 28 ) , thus confirming that the cost for the production of virulence factors which reduces the growth rate of the wild-type strain at high cell density is relieved at low cell density . The FBA performed above used L-glutamate as sole carbon source . L-glutamate is abundant in the xylem and apoplasm of the tomato host [36] and supports a strong growth of the bacteria in minimal medium . However , if a substrate does not support a strong proliferation rate due to a low efficiency of the corresponding catabolic pathways or a low substrate uptake rate , the cost for virulence factor production might impair bacterial proliferation . We defined a ‘substrate usage capacity’ value that corresponds to the quantification of a phenotypic trait ( such as proliferation or virulence ) that the bacterial cell produces from a given substrate upon a period of time ( for details see S3 Material ) . Model simulation then showed that below a certain threshold of substrate usage capacity , the expression of virulence functions prevents bacterial proliferation ( S4 Fig ) . This suggested that the trade-off relationship between these two traits is strongly dependent on the nature of the resources collected in the environment . In order to explore whether the proliferation is impacted by virulence factors production upon usage of various nutritional resources , we determined the metabolic profile of the phcA mutant and two other strains defective for major virulence transcription factors ( hrpB and hrpG ) . hrpB encodes the downstream regulator of the Type III secretion system and dependent substrates , and hrpG encodes a plant signal-responsive coordinator of multiple pathogenicity functions [37] . Microarray phenotyping revealed that the metabolic profile of the hrpB and hrpG mutants was similar to those of the wild-type strain whereas the phcA mutant displayed remarkable expanded versatility ( Fig 7A and S5 Fig , S5 Table ) . Indeed , the phcA mutant possessed a wider substrate usage than the wild-type strain , being able to catabolize 17 additional substrates to sustain proliferation . For example , L-proline , myo-inositol and L-serine were significantly used as carbon substrates only by the phcA mutant strain ( p-value 4 . 0e-6 , 2 . 7e-5 , and 5 . 0e-5 , respectively ) . Comparison of the versatility predicted by the biochemical reaction network and the versatility experimentally observed using the phcA mutant indicated a high accuracy of the model prediction ( Fig 7B ) . Indeed , the precision increased from 57% with the wild-type strain to 89% with the phcA mutant . To confirm the effect of the phcA mutation on metabolic versatility observed using substrate microarrays , we monitored bacterial growth of the hrpB , hrpG and phcA mutants in minimal medium supplemented with five substrates found to be differentially metabolized ( p-value<0 . 01 ) . Results shown on Fig 7C indicate that the phcA mutant had a significantly enhanced growth rates ( p-value<0 . 01 ) on these five carbon substrates , indicating that not only usage of additional substrates but also quantitative increase of the usage of several substrates is dependent upon PhcA . Altogether these observations confirmed that the metabolic network is optimally oriented toward proliferation in the phcA mutant . In order to determine if the observed reduced versatility was dependent on the metabolic cost of virulence factor production , we performed a FBA through the reconstructed genome-scale model . Previous FBA results indicated that the phcA mutant and the wild-type strain had a similar substrate uptake rate in presence of L-glutamate , a substrate which supports growth of both strains . We therefore estimated the minimal consumption rate of various substrates supporting the growth of the phcA mutant ( such as L-serine , L-proline , L-threonine , sucrose , D-fructose , D-glucose and myo-inositol ) . The uptake rate for seven tested substrates was estimated in the range of 0 . 91 ( for sucrose ) to 6 . 24 mmol . g-1 . h-1 ( for L-Serine ) . The correlation ( R² 0 . 53 , see S6 Fig ) between the substrate uptake rates ( in C-mole ) with the growth rates observed experimentally indicates that the difference in substrate usage capacity of the phcA mutant does not only rely on difference in uptake of substrates but also in the efficiency of metabolic pathways used for their assimilation . Then , we performed FBA simulations using as additional constraint the cost for virulence factor production ( as determined previously in ATP equivalent ) . For all tested substrates , the optimal growth rate predicted through FBA matched remarkably well ( R² 0 . 80 ) with the one monitored experimentally ( S7 Fig ) . This analysis also revealed that certain carbon substrates ( those supporting a growth rate of the phcA mutant below 0 . 15 h-1 ) are unable to support bacterial growth of the wild-type strain since their metabolic conversion into biomass cannot be realized due to the imposed cost for virulence factor production . This explains why certain carbon sources such as L-serine and D-fructose , as well as compounds just above the threshold in liquid culture like L-threonine and myo-inositol , do not support the wild-type strain proliferation on the phenotype microarray ( Fig 8 ) . Hence , a fixed cost of virulence factor production satisfactorily explains in most cases the observed reduction of versatility in the wild-type strain and allows defining ( i ) a critical substrate usage capacity threshold around 0 . 15 h-1 , and ( ii ) a list of substrates which are not enough metabolized to promote substantial growth beyond this threshold ( see S6 Table ) .
A first achievement of this study was the reconstruction of a R . solanacearum genome-scale cell model integrating knowledge collected on this microorganism over the last 40 years . With more than 2644 reactions manually curated , this reconstruction is in the range of the highest standards for bacterial models [32 , 38–39] . Moreover , this reconstruction associates a metabolic network with a macromolecule network to account for the production and secretion of virulence factors since R . solanacearum is known to produce hundreds of extracellular proteins involved in pathogenesis [40–41] . R . solanacearum , as many other bacteria in the Burkholderiales order , can adapt to many different habitats and host plants [42–43] . These bacteria generally possess a large genome ( > 5 . 5 Mb ) with a significant proportion of variable genes which are presumably involved in adaptive responses to changes in environment , permitting the bacteria to thrive in diverse ecological niches [44–46] . The presence in the reconstructed model of specific pathways devoted to plant pathogenesis ( such as phytohormone biosynthesis , Type III secretion or EPS production ) provides a first estimate of the functional overlap between the bacterial metabolism and the establishment of the pathogenicity program . In addition , this first description of R . solanacearum versatility through a fine mapping of the used metabolic substrates opens the way to a global correlative analysis of the trophic abilities of the bacterium and its colonization capacity of a broad set of environmental niches including a large host spectrum . Flux balance analyses using the reconstructed model along with the measurements of the metabolites/macromolecules uptake and secretion rates unexpectedly revealed that the wild-type strain , when grown under non-limiting nutrient availability ( i . e . batch culture in minimal medium ) , had a significantly restricted growth rate when it exceeds the threshold of 107 cells/ml . The measured growth rate at high cell density is indeed around 60% lower than the one predicted by simulations when considering the full metabolic potential inferred from the reconstructed R . solanacearum model . We found that this optimal growth rate of the wild-type strain can be reached at low cell density and that the growth rate decrease observed above 107 cells/ml is therefore dependent upon a quorum-sensing mechanism . We have shown that this growth rate restriction is dependent on the phcA gene , a master regulator controlling multiple virulence traits of the pathogen [47] . As expected from the behavior of the wild-type strain at low cell density , we found that the growth rate of the phcA mutant is more than 60% higher than the wild-type strain at high cell density , while it approximates the optimal growth rate predicted through model simulations ( 6% deviation ) . phcA is known to control a phenotypic switch from non-mucoid to mucoid EPS-producing colonies in response to cell density [35 , 48] and in vitro expression studies have shown that , in addition to EPS , this gene controls multiple virulence functions including the production and secretion of plant cell wall degrading enzymes , flagellar motility , twitching motility , siderophore production or the Type III secretion system ( reviewed in [25] ) . Accordingly , a phcA mutant is unable to cause disease symptoms when inoculated on plants [47] . Constraint-based modeling was used to predict and quantify the cost of the huge EPS production observed in R . solanacearum . These results were confirmed by monitoring growth rates of eps or xpsR mutants , and we showed that EPS biosynthesis indeed represents a significant cost for bacteria but this remains a marginal value compared to the growth rate gain observed in the phcA mutant . This strong phenotype certainly results from the pleiotropic nature of the phcA mutation since this gene orchestrates a so-called ‘phenotypic conversion’ [47] and controls multiple virulence functions encoded by hundreds of genes , including xpsR and the eps gene cluster . Future determination of the PhcA regulon will provide clues on the additional biological functions which may represent a significant cost for the cell . This approach should also reveal the probable rewiring of the PhcA-downstream regulatory network which occurs in the mutant . The picture emerging from these results is the existence in R . solanacearum of a clear trade-off between functions dedicated to proliferation ( bacterial growth ) and functions required to produce virulence factors . Bacteria use a complex regulatory network to organize the preferential allocation of metabolic resources to growth or virulence functions depending on the cell density status . PhcA appears to be the key regulatory component that governs this developmental switch occurring when bacterial populations reach 107 cells/ml . This trade-off implies that this pathogen , despite its huge multiplication in plant xylem vessels , doesn’t need to grow fast as theoretically possible to achieve a successful infection . It also highlights that bacterial virulence and metabolism are intertwined and illustrates how resource allocation is a critical mechanism with a profound impact on pathogenic fitness . Diverse range of growth/virulence balances have been described among various pathogens [49] . For instance Salmonella deals with the trade-off between a fast growth in order to outcompete commensals or defective variants and the production of the Type III secretion system required to complete infection [50–51] . Another strategy is to delay the massive production of a virulence factor until the success of host colonization [49 , 52] . As observed for R . solanacearum , these traits are often under a social control system , such as quorum sensing or environmental stimuli , to ensure the coordination of the costly production of the virulence toxin [49] . We discovered that the phcA mutation had also a dramatic impact on the R . solanacearum metabolic versatility . The phcA mutant strain is indeed able to metabolize 17 carbon substrates that the wild-type strain is unable to use to support its growth . In addition , the phcA mutant has an increased ability to use many other substrates , better than the wild-type . Interestingly , this increased substrate usage pattern matches well ( 63% ) with the list of substrates identified in the apoplasm and xylem fluids of the host plant tomato [36] . For example , many amino acids , including L-proline and L-serine , which are present in xylem and apoplastic tissues , enable growth of the phcA mutant but not the wild-type strain . Rather paradoxically , these results indicate that metabolic versatility is reduced when PhcA is active , i . e at high cell density and so presumably at the onset of the massive plant colonization . The growth/virulence trade-off hypothesis can explain this reduction of versatility as evidenced by FBA . However , it cannot be excluded that PhcA also negatively controls the expression of several metabolic transporters or catabolic pathways . On many substrates , R . solanacearum harbors a low substrate usage capacity and those substrates are unable to sustain efficient bacterial growth when PhcA is active . But the pathogen has also a clear nutritional preference towards certain compounds that are abundant in planta such as L-glutamine , L-glutamate and D-glucose , and which promote strong bacterial growth . The compounds detected in low amount in tomato fluids ( <90 μM ) were associated with a low substrate usage capacity by the wild-type strain ( chi-test p-value 4·10−7 ) whereas the used compounds correlated with the range of the most abundant compounds in planta ( p-value 0 . 033 ) . Hence , it is tempting to speculate that R . solanacearum specialized to preferentially metabolize those prominent substrates in plant tissues , especially when it reaches high cell density in xylem vessels . This hypothesis is supported by the finding that L-glutamate has the higher uptake rate in C-mol by R . solanacearum over all the compounds tested . This also implies that despite a broad host range and a wide metabolic versatility , this pathogen tends to specialize to relatively few compounds present in planta . On the other hand , it suggests that at low cell density ( in the soil or at the very early stages of infection ) the phcA-dependent repression of virulence functions leads to an increased metabolic versatility that could be beneficial in a low-resource and competitive environment [53] , see Fig 9 . Altogether , these results also highlight how the maintenance of a pathogenicity trait can be challenging for the pathogen since the existence of this growth/virulence trade-off can lead to the emergence of non-virulent variants with a better growth rate than their wild-type ancestor . Interestingly , it is known for more than fifty years that when inoculated into tomato plants , some members of the R . solanacearum population spontaneously undergo a phenomenon called ‘phenotypic conversion’ [54] . Phenotypic conversion ( PC ) was shown to be the consequence of DNA replication errors and transposition of insertion sequence elements that inactivate phcA [48 , 55] . Recently , serial passage experiments of R . solanacearum on various hosts over 300 hundred generations also resulted in the occurrence and propagation of PC-type mutants that outcompeted the ancestor strain in several lineages [56] , indicating that such mutants can be strongly selected in planta . Our results provide an explanatory hypothesis to this well-described occurrence of PC-type variants since such variants ( i ) do not pay the cost for virulence factor production and thus reach an optimal growth rate , and ( ii ) escape the restriction of metabolic versatility that takes place at high cell density in the wild-type strain . Both properties provide a clear competitive advantage to the variant in presence of the wild-type strain . Because PC-type mutants do not produce many virulence factors and are unable to cause disease symptoms , this raises the question of whether such variants that do not contribute to the public goods but exploit the resources can be considered as ‘cheaters’ in the infecting population . The fast-growing and highly motile phenotype of phcA mutants rather incites to view such variants as ‘colonizers’ when populations face stressful conditions or environments . Interestingly , the reversion of natural PC-type ( phcA ) mutants to the wild-type form after in planta multiplication was reported [55] , suggesting that the balance in infecting populations between low-growing , virulent bacteria and ‘colonizer’ , low-pathogenic variants could have a wider impact on the pathogenic strategy and global life cycle of R . solanacearum . Future work aimed to study the transmission of the pathogen and its persistence in the environment should provide further clues to evaluate the role of PC-type mutants in dissemination and ecological success of the pathogen . | Metabolic versatility is a critical element for pathogen’s virulence and their ability to survive in the host . Beyond the necessity to collect resources during infection , pathogens face a resource allocation dilemma: they have to use nutritional resources to proliferate inside the host , and in the other hand they need to mobilize matter and energy for the production of essential virulence factors . In this study , we provide evidence of that such a trade-off constrains antagonistically bacterial proliferation and virulence in the bacterial plant pathogen Ralstonia solanacearum . We determined the energetic cost required by R . solanacearum to produce and secrete exopolysaccharide , which is a major virulence factor required for wilting symptom appearance . We validated this result by showing that bacterial mutants defective for exopolysaccharide production or other virulence factor indeed have an increased growth rate compared to the wild-type strain . We provide evidence that this trade-off mechanism is orchestrated by the phcA master regulatory gene , which directly connects quorum-sensing regulation to metabolic versatility and virulence . Our results also support the view that R . solanacearum specializes towards a restricted number of substrates used during in planta growth . | [
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... | 2016 | A Resource Allocation Trade-Off between Virulence and Proliferation Drives Metabolic Versatility in the Plant Pathogen Ralstonia solanacearum |
The advancement of high-throughput sequencing ( HTS ) technologies and the rapid development of numerous analysis algorithms and pipelines in this field has resulted in an unprecedentedly high demand for training scientists in HTS data analysis . Embarking on developing new training materials is challenging for many reasons . Trainers often do not have prior experience in preparing or delivering such materials and struggle to keep them up to date . A repository of curated HTS training materials would support trainers in materials preparation , reduce the duplication of effort by increasing the usage of existing materials , and allow for the sharing of teaching experience among the HTS trainers’ community . To achieve this , we have developed a strategy for materials’ curation and dissemination . Standards for describing training materials have been proposed and applied to the curation of existing materials . A Git repository has been set up for sharing annotated materials that can now be reused , modified , or incorporated into new courses . This repository uses Git; hence , it is decentralized and self-managed by the community and can be forked/built-upon by all users . The repository is accessible at http://bioinformatics . upsc . se/htmr .
The advent of high-throughput sequencing ( HTS ) has revolutionized biological and biomedical research [1] , allowing researchers to generate an overwhelming amount of genome-wide data . Now that sequencing is accessible to most , the major bottleneck has shifted from HTS data generation to analysis and interpretation . These remain challenging tasks due to the complexity of the analytical pipelines , the extensive list of available tools , and the evolving nature of the field . To support the need of researchers to carry out their data analysis , institutions worldwide offer highly specialized training on HTS data analysis ( Table 1 ) . However , despite the increase in the number of training solutions , the demand still largely exceeds what is currently offered . Typically , the training offered by most institutions consists of short ( 2–6 days ) , intense courses , often focusing on a particular HTS pipeline—e . g . , RNA-Seq , ChIP-Seq , whole genome sequencing , or variant analysis . During training , instructors and course organizers aim to provide a well-balanced mixture of lectures , which cover the data generation steps and illustrate the theory behind the analysis , and practical sessions , in which trainees can practice running HTS pipelines on real datasets [2] . Post-course surveys have revealed that participants regard the practical sessions as the most valuable components of a training course , as they represent an opportunity to run complex pipelines under the supervision of highly skilled trainers and discuss the issues associated with the analysis of such datasets with the experts in this field [3] . Years of experience in delivering such courses has taught us that the best-suited trainers are scientists who deal with HTS data analysis on a daily basis . Trainers can therefore include researchers working on HTS projects , computer scientists developing relevant algorithms and software , as well as bioinformaticians providing data analysis support to research groups . Consequently , for most instructors training is not formally part of their job and is done in addition to an already heavy workload . Generating effective training materials ( e . g . , lectures and practical exercises ) and testing them to ensure the smooth and successful delivery of a training course are time-consuming activities that all trainers need to undertake prior to a training event . In the last few years , a large body of training material on HTS data analysis has been generated; however , the sharing of such materials among trainers rarely happens , leaving instructors around the world with the need to constantly reinvent the wheel . Therefore , there is a need to develop mechanisms and best practices to both increase the visibility of complete training materials and enable their reusability , ensuring a reduction of trainers’ workload and fostering interactions within the trainers community . Several initiatives have been established in recent years to support bioinformatics training and create community resources , most notably ELIXIR [4] , a research infrastructure for coordinating biological data across Europe , which collaborates with global efforts such as GOBLET [5 , 6] to ensure that an adequate provision of training is put in place to reach a large and diversifying user base . Both initiatives are developing training portals ( ELIXIR’s TeSS [7] and the GOBLET training portal [8 , 9] ) to allow for collation of training materials , increasing their discoverability . The establishment of such portals is of great importance , but this does not guarantee materials’ reusability . The development and production of training materials is usually undertaken by individual trainers for their personal use , often with a particular course or learning context in mind . As there is a sole developer and initial user of the materials , they are often lacking in detailed description or documentation , thereby making it difficult for another trainer to determine what the purpose of the training session was , who the materials were aimed at , and what resources are required to run such a session . Additionally , there is often great variety in the style of training materials presented ( due to personal preference ) and the level of detail in the content ( e . g . , PowerPoint slides annotated with notes ) . If materials could be described consistently , so that either trainers or trainees understood what they could gain from using these materials , reusability of materials may be easier to achieve . For consistent description to take place , however , some form of guidance or best practice standard is required that allows for the addition of metadata to describe the materials and their use . HTS-related material also has additional issues when sharing is considered: ( i ) the constant evolution of the technologies that requires frequent materials revision; ( ii ) the incessant development of analysis tools , which prevents the establishment of standardized analytical procedures and training materials; and ( iii ) their complexity , as training materials are often linked to large datasets that require dedicated storage . The ability to easily share materials via online portals is a fairly new phenomenon , and while providing guidance or best practice standards to trainers for describing their materials is a step in the right direction for more reusability , these also need to be adopted by those who provide the portals enabling the appropriate and correct information to be displayed . This raises the following questions: What can trainers do to improve the sharing and reusability of their materials ? What best practice can they adopt to enable the effective delivery of materials developed by another trainer ? To tackle these issues , on 13–14 January 2015 , a workshop on “Best practices in next-generation sequencing data analysis” took place at the University of Cambridge , bringing together 29 trainers in the field of HTS data analysis , representing seven ELIXIR nodes and ten GOBLET partners ( see S1 Table ) , with the aim to: ( i ) meet and discuss issues associated with the reusability of training materials , ( ii ) define a collective strategy to tackle such issues and identify an approach to the curation of training materials to enable their reusability among trainers , and ( iii ) implement this curation strategy by creating a unified collection of consistently described and well-annotated training materials . This article provides a summary of the issues that were discussed during the workshop and presents the workshop’s major outcomes: the best practices guidelines that have been adopted for the curation of HTS training materials and a curated set/repository of materials that is now accessible to the entire training community through Git and is discoverable via TeSS and GOBLET portals .
Developing a strategy for sharing training materials is a key step towards reusability . The first step of this approach is the identification of training materials that should be shared and in which modality . Materials that most trainers want to share include , but are not limited to , presentations , hands-on practicals , and datasets . Presentations are rarely reused as they are . Typically , trainers would use this type of material as a source of inspiration , to see how other instructors cover a particular topic , ending up reusing a subset of slides or just following the overall structure to then create their own set of slides . Tutorials instead tend to be reused in their original format; therefore , their completeness and consistency are crucial . Obtaining a well-documented tutorial would substantially speed up course preparation and trainers were unanimous in indicating that finding adequate datasets ( in terms of size , content , and relevance to the audience ) is often challenging . Datasets should be derived from real experiments , as opposed to simulated data; they need to be publicly available and also suitable to demonstrate particular analysis steps and their caveats . Moreover , they should be reasonable in size to allow for the fast execution of a typical HTS pipeline and be well annotated . The ideal solution for sharing materials among trainers would be to build a unified collection of consistently annotated materials , easy to search and expand , and link this collection to existing training portals for the benefit of the trainers community at large . Such a collection would provide a framework ( i ) where trainers could share ideas , ( ii ) where materials could be tested , improved , or further developed in a collaborative manner , and ( iii ) where iterative versions of the same material could be archived . Solutions to achieve these goals , and to address most of the issues discussed in the introduction , have already been developed in other contexts , e . g . , software carpentry ( http://software-carpentry . org/lessons/ ) . It is common practice in computer science to collaboratively document , develop , test , and version programs . Based on this observation , it was decided to draft and develop a common collection of materials using a concurrent versioning system , namely Git [10] , as the backbone . To address the reusability issue , a core set of descriptors and a controlled vocabulary were devised and implemented as part of the chosen annotation strategy . Utilizing a minimal set of descriptors will allow for training materials that have been developed independently to be annotated in a consistent manner . The aim of such metadata would be to summarize basic information about the training material , describing its content , suitability for different audiences , and provenance , capturing all the information that we consider essential for the materials to be reused by someone else rather than the original author . In particular , clear and concise learning objectives ( LOs ) should be adopted to describe courses and annotate training materials . LOs should help trainers to identify materials that they might want to reuse , to plan a course based on what individuals need to be able to achieve by the end of it , and also to track learning progression throughout a course . LOs should also help trainees to gather if a course or training materials are suitable for their needs and what they can expect to learn by attending a course or utilizing training materials . The minimal set of descriptors agreed upon to describe each training material is described in Table 2 ( including exemplary usage of the descriptors and , for the dataset descriptor , the exemplary use of a study by Buecker et al . [11] ) . Once the minimal set of descriptors was agreed upon , the training workflows for which training materials were available at the workshop were selected and , for each workflow’s module , materials were collaboratively annotated . Three workflows were selected , “RNA-Seq , ” “ChIP-Seq , ” and “variant analysis , ” alongside two general topics: “Prerequisites” and “NGS-Introduction , ” which provide the basic building blocks for the three workflows . “Prerequisites” includes materials covering basic skills and knowledge in programming and statistics . For example , familiarity with the Unix shell and the R environment are crucial prerequisites . Depending on the target audience , introductions to Unix and R should be incorporated into a course’s program or training materials , possibly utilizing materials developed by the Software Carpentry Foundation [12 , 13] . “NGS-introduction” covers common concepts such as sequencing platforms , sequencing applications , and data formats . The three workflows , “RNA-Seq , ” “ChIP-Seq , ” and “Variant calling , ” aim to provide introductory as well as advanced training for these types of HTS analysis . Each workflow was discussed and a set of modules was defined for each . As an example , the RNA-Seq topic contains the following modules: Pre-processing , Alignment , Alignment Quality Control ( QC ) , Feature summarization , Feature summarization QC , Exploratory analysis , De-novo transcriptome assembly , and Differential Expression ( DE ) . All the topics , their modules , and corresponding description are detailed in Table 3 . The modules were furthermore grouped into essential and optional , highlighting those that are fundamental for each analysis workflow over others that can be used at the discretion of the trainer . A set of controlled vocabularies—adapted from the EMBRACE Data and Methods ( EDAM ) ontology [14]–was selected to tag individual modules in order to facilitate annotation and enable keyword-based searching of the repository content . All materials provided by the trainers attending the workshop were assigned to the appropriate workflow module , annotated as described in the previous session , and uploaded to a Git repository . The current implementation of the HTS training materials repository has two components: a back-end , based on Git to handle the content , and a front end [15] , served as web-content , which builds on the Git repository , as detailed in Fig 1 . The Git versioning system is used to keep track of materials’ updates , in the same way as it is used in software development to keep track of changes applied to source code . Contributors who wish to apply changes to the repository content can do so by forking it . Modified materials can then be reloaded , after passing consistency checks in order to prevent accidental data modification or deletion . Additionally , the API associated with the selected Git implementation ( GitLab [16] ) allows for the development of applications that programmatically access the materials and their metadata . This API was used to: ( i ) index the module metadata repository content and ( ii ) program the search functionality , which is available from the repository’s landing page . Leveraging on such metadata , a trainer can query the repository based on their teaching interests and retrieve relevant training materials . Finally , to ensure an easier navigation within the repository , hyperlinks are used to connect related materials , e . g . , to collate all the material used in a given course . The project’s wiki provides contributors with templates for the submission of new materials , the set of descriptors ( i . e . , the controlled vocabulary necessary to tag materials ) , and submission instructions , including an introduction to the minimal set of Git commands essential to contribute to the repository . Trainers who wish to contribute to the repository can do so either programmatically or by interacting with a curator . In either case , they need to provide the materials and the corresponding metadata ( see descriptors in Table 2 ) . For a programmatic submission , the contributor can either login via an existing Google or GitHub account or create a new repository’s user account and then follow the afore-mentioned instructions . If necessary , e . g . , for a novel type of data or analysis , descriptors could be extended . For interactive submissions , we provide online forms , available from the repository’s landing page , to create the material’s metadata . Upon successful generation of the metadata , the contributor will be contacted by a curator for completing the submission . Regardless of the submission approach , new materials are checked for annotation inconsistencies before being made publicly available . During the initial testing phase , the repository was met with great interest from the community . Currently , 47 members have created an account in the system , of which 29 have attended the workshop and 28 have submitted materials . To facilitate communication between contributors , we have set up a mailing list , which currently includes 26 people .
We have developed a strategy for the curation of HTS training materials and established a working framework for the sharing of such materials among trainers for promoting and strengthening interactions among them and learning from each other's teaching experience . The Git repository of curated HTS materials that we have created is now publicly available at http://bioinformatics . upsc . se/htmr and discoverable through both ELIXIR and GOBLET training portals . It now provides the potential to ease the preparation of training courses via a community driven sharing strategy . In addition , it enables trainers to update and modify their material while keeping track of the changes . This solution is scalable and has been made robust through the use of an easily manageable API in combination with consistent curation . Community initiatives are already planned to refine the training materials curation strategy and extend the coverage of this collection . ELIXIR has recently organized a thematic hackathon focusing on the use of the EDAM ontology to annotate training materials currently available in the collection . The workshop had the dual purpose of tagging materials with EDAM ontology annotations and , at the same time , improving the ontology’s coverage . Additionally , training materials were mapped to the bioinformatics tools and resources from the ELIXIR’s Tool and Data Service registry [17 , 18] to increase the simultaneous discoverability of bioinformatics tools and related training materials . GOBLET and ELIXIR are now planning a second workshop that will bring together trainers working in the field of metagenomics , to enhance the training network within this field . The strategy presented in this paper will be applied to the curation of existing metagenomics analysis training materials , with the aim to define a generic approach for the curation and dissemination of training materials through training portals such as TeSS and GOBLET . We encourage trainers active in delivering HTS training , as well as trainers that might be new to this field , to get involved , utilize the materials already available in the repository to deliver training in this area , and contribute to this initiative with new materials . | In recent years , the advancement of high-throughput sequencing ( HTS ) and the rapid development of numerous analysis algorithms and pipelines in this field have resulted in an unprecedentedly high demand for training scientists in HTS data analysis . Generating effective training materials is time-consuming , and a large body of training materials on HTS data analysis has already been generated but is rarely shared among trainers . In this paper we provide guidelines to trainers for describing training materials to increase their reusability . The best practices standards proposed here have been used to annotate a collection of HTS training materials , which is now available to the trainers’ community in Git and discoverable through the ELIXIR and GOBLET portals . Efforts are now underway to utilize the strategy presented in this paper to annotate a wider collection of training materials and define a generic approach for the curation and dissemination of materials that should be adopted by existing training portals and new emerging initiatives . | [
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"w... | 2016 | Training in High-Throughput Sequencing: Common Guidelines to Enable Material Sharing, Dissemination, and Reusability |
The increased transcription of the Cyp6g1 gene of Drosophila melanogaster , and consequent resistance to insecticides such as DDT , is a widely cited example of adaptation mediated by cis-regulatory change . A fragment of an Accord transposable element inserted upstream of the Cyp6g1 gene is causally associated with resistance and has spread to high frequencies in populations around the world since the 1940s . Here we report the existence of a natural allelic series at this locus of D . melanogaster , involving copy number variation of Cyp6g1 , and two additional transposable element insertions ( a P and an HMS-Beagle ) . We provide evidence that this genetic variation underpins phenotypic variation , as the more derived the allele , the greater the level of DDT resistance . Tracking the spatial and temporal patterns of allele frequency changes indicates that the multiple steps of the allelic series are adaptive . Further , a DDT association study shows that the most resistant allele , Cyp6g1-[BP] , is greatly enriched in the top 5% of the phenotypic distribution and accounts for ∼16% of the underlying phenotypic variation in resistance to DDT . In contrast , copy number variation for another candidate resistance gene , Cyp12d1 , is not associated with resistance . Thus the Cyp6g1 locus is a major contributor to DDT resistance in field populations , and evolution at this locus features multiple adaptive steps occurring in rapid succession .
The genetic basis of adaptation remains one of the central unresolved issues within evolutionary biology . From a genome-wide perspective , recent studies of Drosophila and bacteria suggest that a large proportion of nucleotide fixations in these genomes are adaptive , although their individual effects on fitness are typically small [1]–[5] . From the perspective of an individual adaptive trait , the number of genetic variants that contribute to the trait needs to be quantified , and for each variant , its phenotypic effect estimated , including any pleiotropic fitness costs [6] , [7] . Ultimately a complete understanding of the genetics of adaptation requires the synthesis of both perspectives . Currently however there are few examples of adaptive traits in which the genetic basis is understood at a high resolution . In bacteria the best examples come from chemostat experiments [8] . In eukaryotes , the predominant examples come from Quantitative Trait Loci ( QTL ) studies , which suffer from biases , notably that genes of small effect will generally not be identified . Another bias is that a single Quantitative Trait Locus may result from multiple allelic substitutions and hence QTL studies by themselves could underestimate the number of changes in a bout of adaptive evolution . Here we use insecticide resistance as a model adaptive trait in a eukaryote organism . It offers an opportunity to view an adaptive response to a change in a single environmental component and it occurs on a timescale that allows multiple genetic changes to be observed . Historically , insecticide resistance has provided a good model for adaptation because a novel selective agent is applied to large natural populations . A key insight provided by many insecticide resistance studies is the frequency of parallel mutation . Often , exactly the same mutations arise independently in a gene or in orthologous genes , as adaptive responses to insecticide selection . For example , at the Resistance to dieldrin ( Rdl ) locus , a single A302S substitution has independently occurred across a diverse array of insect species . In the case of Tribolium casteneum , this mutation has occurred multiple times in different geographically defined populations [9] , [10] . Similarly , the L1014F mutation in the para voltage gate sodium channel , the molecular target of pyrethroids and Dichloro-Diphenyl-Trichloroethane ( DDT ) , has arisen independently in numerous species [11] . Such parallel evolution is not restricted to the target molecules of insecticides , but is also seen in detoxifying enzymes , one example being the G137D change in the Resistance to organophosphate ( Rop1 ) esterase locus in Lucilia cuprina and Musca domestica [12] . Parallel evolution is one manifestation of the limits to adaptation , because it suggests that there are a limited number of alternatives . Or more precisely , if there are alternatives , they are harder to reach via mutation , provide less of a benefit , or impose greater fitness costs . The Cyp6g1 locus of Drosophila melanogaster and Drosophila simulans provides another example of parallel evolution . In D . melanogaster the insertion of transposable element sequence into the 5′ regulatory region correlates with increased transcription of the Cyp6g1 gene that encodes a cytochrome P450 enzyme capable of metabolising multiple insecticides , most notably DDT [13] , [14] . The 491 bp insertion is derived from the long terminal repeat ( LTR ) of an Accord transposable element ( TE ) , and lies 287 bp from the transcription start site [13] . Transgenic studies have demonstrated that the 491 bp Accord insertion can drive expression of a GFP reporter gene in detoxification tissues [15] , implicating the insertion as the mutation that causes resistance and thereby providing a robust example of cis-regulatory adaptation [16] . Furthermore the Accord insertion is not found in flies collected before 1940 but is found at high frequency ( 32–100% ) in 34 contemporary populations around the world , and its presence correlates with resistance [17] . In D . simulans , a 4 , 803 bp Doc element , a non-LTR TE , has inserted about 200 bp upstream of the putative transcription start site . This insertion correlates with a two-fold increase in transcription and appears to have recently swept to high frequency in a Californian population . Direct evidence of a phenotypic effect of the Doc insertion is equivocal , but the large window of reduced nucleotide variation around D . simulans Cyp6g1 is consistent with insecticide based selection [18] . DDT resistance in Drosophila is an engaging case study of adaptive evolution , partly because the results of genetic mapping studies have reached different conclusions about the basis of resistance . Most early research , including the classic studies of J . F . Crow , indicated that DDT resistance was polygenic with genes contributing to DDT resistance distributed among all three major chromosomes [19]–[22] . In contrast , work by Kikkawa in 1964 showed that the resistance in the Hikone-R strain was due to a single dominant locus , which mapped to 64 . 5 cM on chromosome II [23] . This was subsequently identified as Cyp6g1 [24] . Since the identification of Cyp6g1 as a resistance locus , researchers have identified the molecular mechanism of the upregulation [15] , looked for selective sweeps centred at this locus [17] , and have contended that other loci also play important roles in DDT resistance [25] . Other than Cyp6g1 , two additional loci have been implicated in DDT resistance , and both are also cytochrome P450 genes . CYP6A2 has DDTase activity that has been shown to be reliant on three amino acid substitutions that distinguish a lab resistant strain from susceptible strains [26] . The other locus , Cyp12d1 , is highly inducible by DDT [27] . Its overexpression in flies using transgenic techniques increases DDT resistance [28] , and the locus exhibits high frequency copy number variation in natural populations . However Cyp6g1 is the only locus shown to have alleles that contribute to variation in DDT resistance in field populations of D . melanogaster . We , and others [29] , [30] , have found copy number variation and extra alleles at the Cyp6g1 locus of D . melanogaster . This casts a new light on the nature of the resistance mutations , the phenotypic contribution to DDT resistance and the adaptive significance of Cyp6g1 variation . The aims of the research reported here are to: ( i ) characterise this molecular variation , focussing on additional transposable element insertions in the locus and gene copy number variation , ( ii ) determine if this molecular variation correlates with phenotypic variation in the form of DDT dosage-mortality relationships , ( iii ) assess whether the variation is adaptive by analysing the genotypic frequencies of this newly described variation in historical and contemporary populations of D . melanogaster and ( iv ) quantify the contribution that Cyp6g1 locus variation makes to overall DDT resistance in a natural population .
We sequenced Cyp6g1 from seven D . melanogaster isochromosomal lines ( chr . II ) , which revealed that six lines had double peaks on their sequence chromatograms . Since the isochromosomal lines should only have one allele for genes on the second chromosome we inferred that there must be CNV for Cyp6g1 . We confirmed this by determining that both alternate states of sequence variants were passed to all individuals in the next generation ( data not shown ) . To determine the details of this CNV we initially characterized the Cyp6g1 loci in a single isochromosomal line ( RK146 ) . In situ hybridisation of a Cyp6g1 probe to polytene chromosomes indicated that the copies of Cyp6g1 were within the same cytological band ( Figure S1 ) . Assuming that these were arrayed in a direct tandem manner , we performed a PCR and identified one breakpoint of the locus duplication , adjacent to the previously identified Accord LTR . To ascertain the other breakpoint associated with this CNV , inverse PCR was performed . Unexpectedly this revealed a ∼7 kb insertion of an HMS-Beagle TE within another Accord insertion . Notably the size of the HMS-Beagle insertion means that it would not have been detected using the Accord spanning PCR assays of previous studies , thus the copy lacking HMS-Beagle is presumably the locus scored previously [13] , [17] , [31] . To determine the extent of Cyp6g1 CNV we generated a model of the locus using Southern blots that we tested using PCR . A primer located within the HMS-Beagle sequence was used in combination with primers within Cyp6g1 and the resulting amplicons were cloned and sequenced . The longest amplicon was 12 . 5 kb and spans the distance between the HMS-Beagle element in the first copy ( hereafter called Cyp6g1-a ) and the beginning of the second full copy of Cyp6g1 ( hereafter referred to as Cyp6g1-b Figure 1A ) . A similar approach , using a primer within Accord was used to amplify all of Cyp6g1-b . In this case the HMS-Beagle insertion was used to advantage as it prevented amplification of Cyp6g1-a . Table S1 shows the differences between Cyp6g1-a and Cyp6g1-b , none of which alter the predicted amino acid sequence . Aside from these two full-length copies of Cyp6g1 a repeat unit that contains a fusion of partial copies of both Cyp6g1 and Cyp6g2 was identified . Cyp6g1 and Cyp6g2 are transcribed from opposite strands and are arranged in a convergent orientation . The repeat unit starts at ∼codon 323 of Cyp6g1 and continues to about codon 73 of Cyp6g2 . The repeat unit can be seen in Southern blots as a 2 . 7 kb fragment common to different restriction enzyme digests ( Figure S2 ) . It is also demonstrated by the multiple digests of the A-D amplicon clone shown in Figure 1B , where this structure is inferred by the consistent 2 . 7 kb size difference between different restriction enzyme digests . While we are confident that the structure shown in Figure 1 occurs in the RK146 strain , it remains a formal possibility that there are Cyp6g1 associated elements outside this region . Previously a partial P element had been identified nested within the Accord element upstream of Cyp6g1 [17] , [31] . We designed PCR assays to score flies for this partial P insertion , the Accord insertion , the HMS-Beagle insertion and the presence of the gene duplication . We could not develop a co-dominant assay for the duplication i . e . we could identify lines carrying the duplication with a PCR bridging a breakpoint but we could not develop an assay that uniquely amplified the single copy allele and not the double copy alleles . Therefore we performed PCR assays on isochromosomal lines , highly inbred lines and F1 crosses to a known genotype ( Table S2 for details ) . These assays revealed even more variation; specifically alleles derived from the partial P-element insertion where most of that P-element had been removed leaving small scrambled portions of the terminal repeats ( Figure S3 ) . Thus we describe six alleles ( M , A , AA , BA , BP , BPΔ ) defined on the basis of this molecular variation ( Figure 2 ) . The facts that the two full length copies both have an Accord LTR insertion , some TEs are nested , and that all lines containing the P-element insertion also have the HMS-Beagle insertion , suggests an order to the molecular events at this locus , which is indicated in Figure 2 . We conducted three surveys of Cyp6g1 alleles in D . melanogaster populations: a survey from historical samples , a survey of lines from contemporary global populations , and a survey of wild males collected on the east coast of Australia ( Figure 3 ) . These studies included a re-analysis of lines scored for the Accord element in earlier studies to determine whether the lines had the duplicated locus or had other variants not originally described [13] , [18] . Consistent with previous studies , the ancestral Cyp6g1-[M] allele is rare in most contemporary populations except for the population from Malawi , Africa [17] , [18] . The historic samples show that the M allele was more frequent in the 1950–1980 samples and was the only allele observed among the lines established in the 1930s ( Figure 3A ) . Surprisingly the Cyp6g1-[A] allele , which was the presumed state of previous studies , is not observed in three population surveys . Most flies in Europe , Asia , and the USA have Cyp6g1 duplicated and are of the Cyp6g1-[AA] or Cyp6g1-[BA] class . A re-analysis of 13 lines collected before 1966 that had been classified as having the Accord insertion [13] , found that all contained the Cyp6g1 duplication and 11 also carried the “HMS-Beagle” insertion ( Table S2 ) . The latter includes Hikone-R , which is derived from flies collected in Japan in 1952 [32] , and which was the DDT resistant strain that was initially used to map resistance to the map position where Cyp6g1 resides [21] , [24] . Our survey of 190 alleles from historic and contemporary global populations found the Cyp6g1-[BP] allele only in current Australian populations ( Figure 3A ) . The BP allele is not seen in any population before 1980 ( n = 39 ) , they are not seen in the non-Australian flies surveyed by us in 2002–2005 ( n = 51 ) , and Catania et al reports them at a frequency of 10/683 in a worldwide sample[17] . However the sample from Australia represented in Figure 3A shows that they are at a frequency of 40/100 , which is highly significantly different from the Catania et al study ( p<0 . 0001 ) and our own survey of non-Australian alleles ( p = 0 ) . Our third survey , which was of ∼40 males caught in each of eight populations , specifically addressed the frequency of the BP allele in Australia . The BP allele frequency ranged from 29–80% with the highest being in the most northerly populations ( Figure 3B ) . This level of population differentiation between Australian and other populations is highly unusual in D . melanogaster and suggests positive selection has recently driven the BP allele to these high frequencies [33]–[35] . We identified two types of Cyp6g1-[BPΔ] alleles . Both were extremely rare being observed a combined total of three times; all from northern Australia . Because of their rarity we have not considered them further in this manuscript except to record their sequence in Figure S3 . For genetic variation to be adaptive it needs to contribute to phenotypic variance . So we asked whether the molecular variation described above contributes to DDT resistance – the phenotype originally attributed to this locus . To answer this , DDT resistance was calculated by contact assay [24] on four day old adults of 19 isochromosomal lines and 3 inbred lines , most of which were derived from Australian populations ( Table S2 and Table S3 ) . Males and females were assayed separately for at least five strains of each genotype: M , AA , BA and BP . Figure 4 shows that M strain males are on average 7 fold less resistant than AA strain males . For females there is 10 fold difference ( see Table S3 for more details ) . Furthermore , with each new Cyp6g1 allele there is an increase in resistance level . There is about a 50% increase from AA to BA flies although this is only significant in the case of males . The males of the BP strains are on average 40 fold more resistant than the M strains and the females are 80 fold more resistant . The fact that the Cyp6g1 allelic classes strongly correlate with resistance , despite the diverse genetic background of the strains assayed , suggests Cyp6g1 is a major determining factor of the DDT resistance phenotype in these lines . Transgenic studies have previously shown that the Accord LTR can act as a tissue specific enhancer of gene expression [15] . To test whether transcription levels correlate with the remaining steps in the allelic series , we analysed Cyp6g1 expression in 18 of the lines analysed for DDT resistance . The tissue and cell types where DDT detoxification occurs are currently unknown , but we chose to analyse the adult midgut and adult Malpighian tubules because a UAS-Cyp6g1 transgene confers resistance when over-expressed in these tissues using the Accord LTR Gal4 driver [28] . Furthermore , RNAi knockdown of Cyp6g1 in the tubules increases susceptibility of flies to DDT [36] . We found a positive and significant correlation between DDT resistance and transcription levels among the 18 lines assayed for both the midgut and the tubules ( Spearmans rank; midgut = 0 . 62 , p<0 . 02 , tubule = 0 . 52 , p<0 . 05 ) . However when the 18 lines are grouped by allelic class , as shown in Figure 5 , significant differences in transcription levels are observed for only some of the steps in the allelic progression . In the midgut , the derived alleles clearly exhibit higher gene expression than Cyp6g1-[M]; with AA having a 2 . 6 fold increase ( P = 0 . 036 , one tailed t-test ) and BA and BP both showing a 5 fold increase . There is also a significant 2-fold increase of BA over AA ( P = 0 . 0006 , one tailed t-test ) . In tubule , only the step between M and AA results in a significant increase in transcription ( P = 0 . 04 , one tailed t-test; Figure 5B ) , and all three derived alleles exhibited ∼3 fold increases in gene expression . There is a formal possibility that some other background genetic factor is by chance correlated with Cyp6g1 allele and that it contributes to the phenotypic trend shown among the lines we analysed for DDT resistance . This is unlikely , partly because most isochromosomal lines were generated in such a way that 100% of the X chromosome material and 75% of the third chromosome material would be derived from the Prl/CyO stock ( Table S2 ) . Nevertheless we decided to take a quantitative genetics association study approach to confirm and quantify the role of the most derived high frequency allele , Cyp6g1-[BP] , in a field population . The population for our association study consisted of 7500 non-virgin females that derived from 750 females caught in the field two generations earlier . A subset of our population was used to determine a dosage mortality curve that allowed an estimation of the population LC5 and LC95 values ( i . e . the most susceptible 5% and most resistance 5% of the population to DDT exposure ) . The mortality of flies on a probit scale was close to linear to the log of the dose of DDT indicating that the underlying phenotype approximates a normal distribution ( Figure 6A ) . Based on this we chose 2 µg/scintillation vial ( = 0 . 05 µg/cm2 ) of DDT to be the exposure that would only kill the individuals from the susceptible tail of the distribution and 120 µg/scintillation vial ( = 3 . 2 µg/cm2 ) to be the exposure to kill all but the most resistant individuals . Four replicates of 500 flies were then exposed to the lower dose of DDT and five replicates of 500 were exposed to the high dose of DDT . Nearly exactly 95% of the flies died ( all but 124/2500 ) on the 120 µg treatment and close to 7% of flies died on the 2 µg treatment ( 133/2000 ) . All the flies that survived the high dose and all those that died on the low dose , were genotyped for Cyp6g1 allele status . These were compared to 86 field caught males and to random samples of flies that lived on the low dose or died on the high dose . The BP allele is greatly enriched above field frequency among survivors of the high dose but was depleted among those that died at the low dose ( Figure 6 ) . Thus the association study confirmed the inbred and isochromosomal line analysis . Trend tests give a very significant association between BP and survival at LC95 ( Cochrane Armitage test , chi square 42 , p<<0 . 0001; [37] ) . In fact flies homozygous for the BP allele are twelve times more likely to survive than non BP homozygotes . For comparison we also genotyped the same flies for a CNV at another candidate DDT resistance locus , Cyp12d1 , which is on chromosome 2 approximately 1 Mb away from Cyp6g1 . The assay we used bridged the breakpoints of the distal and proximal copies of this locus , which is thus not a codominant assay and therefore individuals either heterozygous or homozygous for the duplication were not discriminated ( Flybase release FB2010_01 ) . Therefore a 2×2 test comparing the presence and absence of the Cyp12d1 duplication in resistant and susceptible flies was used which showed there is no correlation with the duplication of this locus and resistance or susceptibility ( Fishers exact test P = 0 . 60 , Figure 6 ) . These data can also be used to quantify the contribution of Cyp6g1 alleles to DDT resistance . Table 1 shows the survivorship of individuals partitioned by Cyp6g1-[BP] genotype . Heterozygotes are less than midway between the two homozygotes indicating this allele is slightly recessive at this dose ( Figure S4 ) . To calculate the contribution of this allele in the population , this recessiveness ( k = −0 . 63 ) , the survivorship difference between the two homozygotes ( 2a = 0 . 18 ) , and the population frequency of Cyp6g1-[BP] ( p = 0 . 28 ) , need to be taken into account . Thus the average allelic effect of Cyp6g1-[BP] is to increase survivorship of a genotype by 6 . 5% ( [38] equation 4 . 10b ) . The additive genetic variance attributable to this allele is 0 . 0017 ( [38] equation 4 . 12a ) and therefore the heritability on the observed scale , at an LC95 dose , attributable to this allele , is 3 . 7% . For a threshold trait such as this , we are observing binary phenotypes; alive or dead at a particular dose . However , as illustrated by the dose response relationship in Figure 6A , we can assume that there is a normal distribution underlying the DDT resistance trait across doses . Thus the heritability on the observed scale can be converted to an estimate of the heritability on the underlying scale and that indicates that approximately 16 . 5% of the ‘liability’ to survive is explained by the Cyp6g1-[BP] allele ( [38] equation 25 . 8b ) . We have not calculated the variance of all genetic factors influencing DDT resistance , and thus do not know the heritability of the trait as a whole , but whatever that heritability is ( it has to be between 0 . 16 and 1 ) , the Cyp6g1-[BP] allele makes a major contribution to phenotypic variation in this population .
Recently , others have identified CNV at the Cyp6g1 locus using genome-wide tiling arrays [29] , [30] . In the study of Emerson et al . the resolution of CNV boundaries is such that repeats containing a fusion of partial Cyp6g1 and Cyp6g2 genes were identified . Not only has the present work determined that the CNV represents at least two full-length copies of Cyp6g1 , it has also established the way in which this locus has evolved . Furthermore , we have shown how this contributes to increasing DDT resistance using two separate approaches . Firstly we showed that the LC50 to DDT increases with the allelic progression in a set of 19 isochromosomal and 3 inbred lines ( M<< AA< BA << BP ) . Secondly we performed an association study that clearly demonstrates that the BP allele makes a major contribution to the phenotypic variance in a single population where it is at high frequency . D . melanogaster is not a pest and is generally not targeted by insecticide application . Could it be that variation we detect with our DDT assays is non-adaptive ? As discussed in more detail below we present historical and geographic surveys of Cyp6g1 allelic variation that clearly demonstrate that at least two of the steps have been adaptive ( the world-wide spread of the Accord bearing alleles and the spread of the BP alleles within Australia ) . Further support for adaptive change at this locus could come in the form of patterns in the patterns of polymorphism and fixation that support selective sweep models . In fact others have shown evidence for a selective sweep at the Cyp6g1 locus [17] , [18] , although they have not shown that there have been recurrent sweeps at this locus . The data presented here shows that an adaptive walk has occurred at the Cyp6g1 locus . Although not a classic adaptive walk , where evolution is conceived in coding sequence space [39] , the allelic succession that we describe is explained as a sequential process where each new allele is derived directly from that preceding it . In the following we discuss each proposed step in this allelic succession . The first step of the walk would seem to have been the insertion of the Accord LTR into the Cyp6g1 promoter . As we did not detect the A allele ( single copy Cyp6g1 with Accord LTR ) in our sample , and thus cannot determine its phenotypic effect , the identification of the AA allele , in which both Cyp6g1 and the Accord LTR are duplicated , indicates that this insertion most likely occurred at or before the duplication event . A question that arises from the failure to detect the single copy A allele , is deciding which molecular variant , the partial Accord TE insertion or the CNV , was the first target of natural selection . A recent study using transgenic reporter genes showed that the Accord LTR acts as an enhancer increasing transcription in tissues consistent with the Cyp6g1 changes observed in ‘Accord flies’ [15] . This suggests the Accord insertion itself could cause the up-regulation and be the target of selection . We propose that the second step was the duplication event producing two copies of Cyp6g1 . Sequence analysis of cDNA from RK146 ( not shown ) indicates two full-length copies of Cyp6g1 are transcribed in adult flies , indicating that the duplication acts to increase transcriptional output . It is possible that the Accord insertion and the duplication happened from the one complex event . Thus a minimum of one selective sweep is required to explain the rapid change in frequency of the AA alleles . Alternatively it is possible that there have been two adaptive steps , one that is the Accord insertion and the other the generation of the CNV . In that scenario the A allele may never have reached high frequencies before being replaced by the AA allele . Whichever the case , the net result is a 7–10 fold increase in resistance phenotype in comparison to the ancestral M allele ( Figure 4 ) . The third step in the walk involved the insertion of the HMS-Beagle insertion into the Accord LTR that lies proximal to Cyp6g1-a . From the DDT resistance data it is hard to determine whether the AA→BA step is adaptive , as the increase in DDT resistance phenotype is only significant for males in our current data set . Our population surveys confirm previous results , which suggest that the Accord alleles ( which we now know as A , AA and BA alleles ) were either absent or at low frequencies pre-DDT . They also show that both AA and BA alleles began to spread at the same time , and have now spread globally . Among the lines carrying the BA allele is Hikone-R , which was the DDT resistant strain that was initially used to map Cyp6g1-based resistance [21] , [24] . Hikone-R was collected in Japan in 1952 and although the AA and BA alleles may have existed for some time before the 1950's , historic fly collections show they have only reached high frequencies recently ( Figure 3 ) . These results concur with previously reported skews in the polymorphism frequency spectrum around Cyp6g1 , which suggests recent strong positive selection [17] , [40] . The fourth step in the walk is the insertion of a partial P-element into the Accord LTR that lies proximal to Cyp6g1-b . Since all flies that carry a P-element insertion also contain an HMS-Beagle element upstream of Cyp6g1-a we infer the insertion would have occurred in a Cyp6g1-[BA] background . This results in a significant increase in DDT resistance phenotype over AA and BA alleles with BP males 6 and 3 fold more resistant respectively . BP females are 8 and 5 fold more resistant than their AA and BA counterparts . Furthermore the association study shows a highly significant association between the BP allele and DDT resistance . Curiously , the robust association between the BP allele and the DDT resistance phenotype is not reflected in our transcriptional analysis . This may be because the P-element insertion may simply be a marker in linkage disequilibrium with the causal variant – which could be an amino acid change in an uncharacterised copy of Cyp6g1 . Another possibility is that the BP allele gives resistance by altering the transcript abundance in tissues that have not been assayed here . The possibility that there is tissue specific variation in transcript levels is illustrated by the observed differences in expression between Malpighian tubules and midgut . Thus it is possible , for instance , that Cyp6g1 transcription is higher in the head , fat body or reproductive tissues in BP lines . Regardless of the exact details of the molecular mechanism of resistance we have no doubt that the fourth step is adaptive , as analysis of eight Australian populations suggests the Cyp6g1-[BP] variant has recently and rapidly increased to be the most frequent allele in Australia . Thus Australian flies are very different from other parts of the world where BP alleles were recorded in only 10 out of 683 lines [17] . The lack of BP alleles in fly lines established from Papua New Guinea and Australia in the 1980s ( Figure 4A ) supports this selection model as do reports that the P-element transposable element itself was only detected in Australia in the late 1970's [41] . Neither drift nor population bottlenecks can satisfactorily account for the high frequency of BP alleles in Australia . We conducted three independent surveys of contemporary Australian populations ( our original survey , a survey of east Australian clinal samples and the association study collection ) sampling from multiple locations spanning the east coast of Australia . Thus a local bottleneck ( i . e . from a single collection site ) could not explain the data . Similarly D . melanogaster populations from the east coast of Australia exhibit extensive gene flow and share the same diversity as non-African populations [35] , [42] , indicating populations are not isolated . There has also been enough time since their introduction to Australia for the establishment of strong latitudinal clines that parallel those found in other parts of the globe [43]–[45] . Furthermore the flies used here to survey allele frequency across the east coast of Australia have been previously characterized for many other loci and are consistent with other Australian surveys , ruling out the possibility that our samples are somehow biased , non-representative or corrupted[43] . Finally if the P element did not enter Australia until the 1970's [41] then the BP alleles of Cyp6g1 must have entered into established populations . There is no way that genetic drift could explain the frequencies of BP alleles , rather the BP alleles must have spread through these populations with positive selection . This raises the interesting proposition that the BP alleles may increase in frequency in other parts of the world in the future . It is worth noting that DDT has been banned from use in most of the world including Australia since the 1980s [46] and yet we are postulating that the BP allele has risen to high frequency in Australian populations since then . Notwithstanding the possibility that DDT still persists in the environment , we also note that it is well established that Cyp6g1 upregulation provides resistance to a number of insecticides and other chemicals [13] , [24] . Thus DDT resistance may be considered as a phenotypic marker of this allelic variation rather than the actual selective agent . Our population surveys also identified two different Cyp6g1-[BPΔ] alleles , formed by imprecise excision of the P-element insertion . These alleles are at low frequency , and we have not characterised their contribution to DDT resistance . Their formation questions the stability of the locus structure that we have defined . Over evolutionary time we would expect this structure to be simplified . For instance if the BPΔ alleles have the same phenotype as their BP parent , it may indicate that only discrete functional DNA sequences need be preserved , with the rest free to be deleted . Opposing this simplification is the instability introduced by the gene duplications , which may increase the rate of copy number variation by molecular slippage . We have shown that in the RK146 strain there are at least two full-length copies of Cyp6g1 , but in light of the above it is possible that even more copies exist in other strains . Allelic succession , the process whereby different adaptive alleles are substituted sequentially , has also been characterised in several studies of insecticides resistance . In Culex pipiens mosquitoes , alleles at the Ester ‘super-locus’ ( so called because some alleles contain CNV of more than one gene ) confer organophosphate ( OP ) resistance . Ester1 and Ester4 both result in the overproduction of an insecticide metabolising esterase [47] . Ester1 was first detected in 1972 , while Ester4 appeared over a decade later . Despite a moderately lower level of OP resistance Ester4 has replaced Ester1 due to a lower overall fitness cost [48] . In a second Culex example , the resistance allele of the target of OP insecticides , Ace1R , also confers a fitness cost , but this cost seems to have been reduced through gene duplication by the creation of a permanent heterozygous allele , consisting of a copy each of the susceptible and resistant alleles [49] . Allelic succession in both these cases appears to be driven by selection removing a fitness cost introduced with the preceding resistance allele . Two previous studies have associated fitness costs with Cyp6g1 upregulation . A study in which males were selected for reduced competitive mating success indicated that Cyp6g1 was significantly upregulated [50] . In contrast , females seem to carry no cost for a range of fitness traits [51] . It would be worthwhile revisiting these earlier experiments in light of the complex variation we have shown to exist for Cyp6g1 . However it is not necessary to invoke fitness costs , as the data shown in Figure 4 suggests that the allelic succession occurring at Cyp6g1 is driven by selection for ever-greater resistance . Cyp6g1 has become a highly cited example of adaptive evolution [52]–[54] . Cyp6g1 resistance alleles are not only selected , in parallel , in sibling species , we show that they have also been repeatedly selected , in series , in D . melanogaster . These results are pertinent to a long-standing evolutionary debate concerning the number of steps that have to occur to move a species to a new adaptive optimum [6] , [55] . Support for a model requiring only a moderate number of steps includes mapping experiments , where the number of loci that contribute to a given adaptive trait are calculated , and their relative phenotypic effects apportioned . However , as recently described by the careful dissection of a morphological trait that differs between species , mapping experiments may hide the number of steps that have occurred at a single locus over evolutionary time [56] . Here we have described at least four steps at a single locus that have occurred within 70 years . The intense selection of insecticides has provided the opportunity to see the adaptive process at a resolution invisible in many other examples of adaptation .
The stocks used for the DDT toxicology experiment were made isochromosomal for the II chromosome by backcrossing to Prl/CyO flies ( Bloomington Stock 3079 ) . For stock list see Table S2 . Probes were made using the PCR DIG Probe Synthesis kit of Roche Boehringer Mannheim ( version# 2003 ) . The primers: 5′-CAGCCTAGAGAATCCCAACG-3′ and 5′GCCATGGCCACTATGTTCTT-3′ were used to amplify exon 3 and exon 4 from a Cyp6g1 subclone . The chromosomes were prepared following the method of Phillips et al [57] . Roche Expand High Fidelity PCR system was used to generate all PCR products greater than 2 . 5 kb following the manufacturers protocol except with the following cycling parameters: 94°C 2 mins , 10 cycles of 94°C 15s , 62°C* 30s , 68°C 10 mins , 30 cycles of 94°C 15s , 56°C 30s , 68°C 10# mins , and a final 60 min extension at 68°C . * A touchdown cycle , with the annealing temperature decreasing by 0 . 5°C per cycle . # Extension time increases 10 s per cycle . Primers used ( refer Figure 2 ) listed 5′-3′: A CGTCTTAGAAAGAAACAGGAAACTG , B ACATTTGGGAGATGCCTTTG , C ATTAAACACAACCGGCTTTCTCG , D GTCTCACCACCCAGGAAAGA , E CTTTTTGTGTGCTATGGTTTAGTTAG , F GGGTGCAACAGAGTTTCAGGTA , G TTTCAGCCAGTTGGACATTG . PCR products were gel purified and cloned using the TOPO XL PCR Cloning Kit ( Invitrogen ) following manufacturers instructions . 125 ng of RK146 genomic DNA was digested with EcoR1 in a total volume of 100 uL , then 5 uL of the digest was diluted to 100 uL in a ligation reaction mix , left overnight at 14°C . This allowed linear EcoR1 fragments to circularise . PCR's using primers 5′-GATCCGCGGCTGAAGGACGA-3′ and 5′-TGCGGCGACCACCACAAAGA-3′ were conducted with the 30 cycles of: 94°C for 30 s , 62°C for 30 s and 68°C for 2minutes . A nested PCR was then performed using a new reverse primer ( 5′-TGCCAGTGCCCTCAGCATTATCTTATC-3′ ) and the original forward primer ( 5′-GATCCGCGGCTGAAGGACGA-3′ ) . The product was cloned into pGEM-T easy and sequenced . DNA was prepared from single flies . Diagnostic assays to detect TE insertions and the Cyp6g1 gene duplication used standard PCR conditions with the following cycling parameters: 94°C 2 mins , 30 cycles of 94°C 15 s , *°C 30 s , 72°C # mins . Reactions used the following primers ( refer Figure 2 ) listed 5′-3′: H GAAAGCCGGTTGTGTTTAATTAT , I CTTTTTGTGTGCTATGGTTTAGTTAG , J CGAGTACGAGAGCGTGGAG , K ATTAAACACAACCGGCTTTCTCG , L TGCGATCATCTGCACTTCTC . Annealing temperatures , * , and extension times , # , for each primer pair: HI 57°C 2 mins , JK 56°C 1 min , LI 58°C 45 secs . 4 day old non-virgin male and female flies were treated separately . DDT was coated on the inside of glass scintillation vials by applying 200 µl of acetone containing varying concentrations of DDT and rolling the vial until the acetone had evaporated . 20 flies per vial were used with the vials plugged with cotton soaked in 5% sucrose . Mortality was scored after 24 h . LC50 estimation was performed using PriProbit[58] , using five concentrations and three replicates per concentration . Midguts and Tubules were dissected separately from 4 day old adult males , 5 strains per genotype , and pooled in groups of 6–10 tissues , for 3 biological replicates per strain . mRNA was extracted in 200 ul Trizol and 60 ul chloroform . After being pelleted all the extracted RNA from each sample was used in cDNA synthesis , and cDNA was reverse transcribed and quantified according to standard procedures . For quantitative PCR ( qPCR ) , samples were split and amplified with Cyp6g1 primers , using Rpl11 as a reference gene . 750 isofemale lines were established from field caught females . At the F2 , 10 4–8 day non-virgin females were collected from each line , in essence recapitulating the extant genetic variation of this population . Our experimental design involved comparing the two tails of the DDT resistance phenotype distribution . To this end a subset of the F2 flies were used to determine a dosage mortality curve for the population and allow estimation of the population LC5 and LC95 values ( 2 µg and 190 µg respectively ) . The large 95% confidence interval for the LC95 estimate suggested a dose of 190 µg would be inaccurate , so instead we used a dose of 120 µg , a dose slightly higher than the highest dose used in the DMC assay ( 112 . 5 µg ) which had ∼92% mortality . These doses were scaled , by internal surface area , to allow exposure of 500 individuals in 2 L Schott bottles , which were stoppered by cotton wool wrapped around a 10 ml disposable pipette . After exposure for 24 hours a vacuum pump was attached to the pipette to remove the flies into separate dead and alive cohorts . For the LC5 , all dead flies ( 133 in total ) and an equivalent number of surviving flies were assayed . For the LC95 all surviving flies ( 124 ) and an equivalent number of dead flies were assayed . Flies were assayed using the HI primer pair to detect Accord/P-element status as described above . Determination of the Cyp12d1 duplication genotype status ( u/u or D/− ) of these flies utilised a four primer PCR reaction using the same general PCR conditions described above . Primers used were; Rout TCCTAAGAATTCCCACCATCAC , Rin GGTCCATCATCCCTACCATTT , Fout GGCCATTACGTTCCCCTTC and Fin GGTCTCGGAAAATGAGCAAC . The Rin/Fout and Rout/Fin primer pairs amplify products from both single copy and duplicated Cyp12d1 loci 767 bp 933 bp in length respectively . The pair Rout/Fout is specific to the presence of the gene duplication , and gives a product of 389 bp . | The study of insecticide resistance has greatly enriched our understanding of the genetic basis of adaptation , because it represents some of the most intense selection pressures acting on any natural population of eukaryote . Thus it can inform us about the limits of natural selection , both in terms of the number and type of mutations that can arise and also in terms of the rate at which these spread throughout populations . Fifty years ago , studies in Drosophila melanogaster indicated that many genes contributed to DDT resistance . Subsequent research into the Hikone-R strain indicated much of the resistance in this particular strain could be attributed to a single gene known as Cyp6g1 . Here we show that there have been successive DDT resistance mutations occurring at the Cyp6g1 locus . They include an increase in gene copy number and the insertion of transposable elements into the regulatory regions of the Cyp6g1 gene . These mutations have swept to high frequencies in natural populations since World War II , when insecticides were first used . D . melanogaster is not a pest and has not been targeted by insecticides , and yet profound changes are occurring within its genome in response to man-made chemicals in the environment . | [
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] | 2010 | Copy Number Variation and Transposable Elements Feature in Recent, Ongoing Adaptation at the Cyp6g1 Locus |
The endosymbiotic bacteria Wolbachia pipientis ( wMel strain ) has been successfully established in several populations of Aedes aegypti , the primary dengue vector . The virulent Wolbachia strain wMelPop is known to cause several pathological impacts ( increased egg mortality , life shortening , etc . ) reducing overall fitness in the mosquito Ae . aegypti . Increased egg mortality could substantially reduce egg banks in areas with a lengthy monsoonal dry season , and be employed to eliminate local populations . We tested this application under semi-field cage conditions . First , we determined that wMelPop infection significantly reduced the survival of desiccation-resistant eggs of the dengue vector Ae . aegypti , with shade and temperature having a significant impact; nearly all wMelPop-infected eggs failed to hatch after 6 and 10 weeks in summer and winter conditions , respectively . In laboratory selection experiments we found that egg desiccation resistance can be increased by selection , and that this effect of wMelPop infection is due to the nuclear background of the host rather than Wolbachia . We then conducted an invasion of wMelPop within a semi-field cage using sustained weekly releases of wMelPop infected mosquitoes , with fixation achieved after 9 weeks . The egg populations wMelPop infected and an uninfected control were then subjected to a simulated prolonged monsoonal dry season ( 2 . 5 months ) before flooding to induce hatching . The wMelPop infected eggs suffered significantly greater mortality than the controls , with only 0 . 67% and 4 . 35% of respective infected and uninfected eggs held in 99% shade hatching after 80 days . These studies suggest that wMelPop could be used to locally eliminate populations of Ae . aegypti that are exposed to prolonged dry conditions , particularly if combined with vector control .
Dengue is the leading cause of arboviral disease in humans . An estimated 390 million infections and 90 million clinical cases occur annually [1] . There is no commercially available vaccine , so vector control and mosquito avoidance are the only methods to limit transmission . Traditional control of the mosquito vector Aedes aegypti is increasingly hampered by physiological resistance against insecticides , especially synthetic pyrethroids [2–5] . Furthermore , the logistics of controlling a vector that exploits artificial containers that are often cryptic , subterranean and difficult to access ( eg . , elevated sites such as rain water tanks ) makes effective control difficult to achieve [6–8] . The adult Ae . aegypti is endophilic , and is often found inside dark , quiet areas within premises [9] . These areas are not effectively targeted by insecticidal sprays applied by air or ground [9 , 10] . Collectively , vector control efforts to control dengue are generally not successful , and dengue continues to expand in breadth and reach globally . New vector population manipulation methods have been developed to overcome the issues of traditional vector control . The release of insects infected with a dominant lethal gene ( RIDL ) employs the release of male Ae . aegypti that induce sterility by passing a lethal gene to wild females they mate with [11] . Serial releases of these genetically modified male mosquitoes thus lead to collapse of the resident wild population [11 , 12] . The vector capacity of resident populations of Ae . aegypti can also be reduced to lessen dengue transmission . Strains of the endosymbiotic bacteria Wolbachia were transinfected into Ae . aegypti eggs , and are then passed on maternally [13] . Male Ae . aegypti infected with Wolbachia induce embryo death when mating with uninfected females [13 , 14] . This creates a powerful drive mechanism that allows Wolbachia to spread naturally within a population of uninfected Ae . aegypti , and to persist once fixed [15–17] . The presence of Wolbachia infection also interrupts dengue ( and other arboviruses ) replication in Ae . aegypti , interfering with transmission [18–20] . Two virus blocking strains of Wolbachia ( wMel and wMelPop ) have been established in Ae . aegypti . To date , populations of wMel-infected Ae . aegypti have been released and established in seven localities around Cairns , Australia . The more virulent wMelPop over-replicates inside the mosquito , inducing a variety of physiological manifestations . These include early death ( life-shortening ) [13] , egg mortality [21 , 22] , reduced blood feeding [23] , delayed larval development [24] and reduced overall fitness [25] . The high density of wMelPop probably contributes to its almost complete blocking of dengue replication and transmission in Ae . aegypti [18] , but efforts to introduce this infection into wild populations have proved challenging [25] , although it has been accomplished in semi-field cages [19] . One implication of high mortality , especially reduced egg longevity , is that wMelPop could lead to reduced population size of Ae . aegypti [26] . In areas with a pronounced monsoonal dry season , mosquitoes survive for up to several months as desiccation resistant eggs [27] . If wMelPop can be established in these populations during the wet season , populations might naturally die off during the dry season . In this paper we measure the relative survival of wMelPop infected Ae . aegypti eggs under natural conditions . Because this strategy could be thwarted if there is evolution in wMelPop to counter any deleterious fitness effect , we also explore strain variation involved in egg survival . Finally , we simulate a wMelPop intervention from invasion to subsequent death of the eggs in a semi-field cage to test the concept that wMelPop could be used to crash and locally eliminate Ae . aegypti egg banks under a prolonged monsoonal dry season .
A protective awning with three different shade regimes was built to house mosquito eggs in the survival study . The awning ( 17 m x 3 . 3 m ) was built between 2 semi-field cages [29] and divided into three sections that provided 30% , 70% and 99% shade ( Fig 1 ) . The awning roof consisted of waterproof translucent vinyl to protect eggs from rainfall . Two 5 . 6 m sections of the vinyl had an interior piece of 40% and 95% shade cloth to provide additional shade to create the 70% and 99% shade; the section with vinyl alone provided 30% shade . Temperatures and relative humidity within each section were monitored using data loggers ( Hygrochron iButton DS1923 , Dallas Semiconductors ) set atop and below the table , supplemented with data from the Bureau of Meteorology ( BOM ) site 15 km SE of the site when loggers failed . Preliminary trials indicated that ambient temperatures ( under table ) in the 70% and 99% shade ( S1 Fig ) were nearly identical to screen height temperatures at the Cairns Airport BOM site . However , loggers on the table that were exposed to sunlight ( 30% and 70% shade ) experienced a spike in temperatures that exceeded 50°C and 60°C in the winter and summer , respectively ( S2 Fig ) . Egg strips were obtained by exposing sandpaper strips to gravid mosquitoes . Eggs were allowed to incubate within the flooded oviposition cup for 3 days , then dried . Viable ( non flattened ) eggs on strips were counted and each strip labeled with egg count using masking tape on a bulldog clip ) . Eggs strips were attached vertically to the inside of a wire mesh basket that was set on a card table within each section ( Fig 1 ) . The legs of the table were set inside a saucer containing talcum powder to prevent ants from invading the table and predating eggs . Three egg strips were randomly picked and hatched in a dilute yeast solution at 0 , 1 , 2 , 3 , 4 , 6 , 8 , 12 and 16 weeks post exposure . The experiment was conducted in the cool dry ( 10 May– 30 Aug . 2012 ) and warm dry season ( 11 Oct . 2012–3 Jan . 2013 ) . Percent hatch was calculated as the number of hatched eggs ( 1st instar larvae ) divided by total viable eggs . To assess changes in hatch rates across time in the summer and winter egg quiescence experiment , we considered rates observed in the first 6 weeks or less and then ran General Linear Models ( GLMs ) examining the impact of strain and shade on hatch rates , with time treated as a linear and quadratic variable . We were particularly interested in the interaction between time and strain reflecting changes in hatch rate over time . GLMs were run with and without angularly transforming hatch rates but only the latter are represented because the conclusions were identical . We conducted a trial to see if establishing a fixed population of wMelPop infected Ae . aegypti could be used to crash the viable egg bank during the dry season and potentially eliminate the local population under semi-field cage conditions . Two semi-field cages ( 4 x 7 x 4 m ) were populated with wild ( F1-2 ) Cairns Ae . aegypti . Each cage contained 4 10-L buckets and 4 potplants with flooded potplant base ( PPB ) . Three times per week a volunteer sat in the cage for 10 min to bloodfed mosquitoes; 1 pellet of lucerne was added to each bucket and the potplant base was refilled with water . Buckets and PPBs were flooded weekly to hatch new eggs . The populations were introduced into the cage on 28 April 2013 and allowed to establish for 4 weeks . Then populations were crashed ( simulated source reduction campaign ) by emptying 3 of the 4 buckets and PPBs to kill immatures then spraying the inside of each with 4% sodium hypochlorite ( commercial bleach ) to kill eggs [30] . One week after population suppression , PPB and buckets were refilled with water . Mean pupal counts were used to estimate the adult population in both cages by integrating estimated adult populations for 0 . 8 and 0 . 9 daily survival over 14 days [31 , 32] . Single Biogents Sentinel traps ( BGS ) were run for 3 hr in each cage 2–3 times/week to monitor adult populations . We used the relative change in BGS captures during the 2 weeks before and after releases of wMelPop-infected mosquitoes to estimate the size of the released cohort [33] . On 6 June 2013 weekly release of wMelPop infected mosquitoes began in the treatment cage . A colony of AOMB wMelPop cultured at a constant temperature was the source of release material . Two cups of 50 ( 1:1 male:female ) adult Ae . aegypti infected with wMelPop were released into the north ( treatment cage ) . This equated to a relative release ratio of 1 . 4 and 2 . 0 for female and male infected mosquitoes , respectively , based on the relative change in BGS captures from 2 weeks before and after release [33] . Mosquito populations were also monitored in both cages by counting pupae in buckets and PPBs once week . Mosquitoes in the control and treatment cage were monitored for Wolbachia infection by PCR analysis of sample of up to 30 larvae/week; larvae were reared to adults for PCR . We also conducted another source reduction ( 3/4 of buckets and PPBs treated as before ) supplemented with removal of adults using a sweepnet on 5 July . Releases of Wolbachia infected mosquitoes continued until 100% of sampled mosquitoes in the treatment cage were infected with wMelPop for two successive weeks; the last release was on 26 Sept . 2013 . We characterized the infection frequency in the cage by testing samples of 30–90 adults ( collected as larvae ) for the Wolbachia infection . DNA was extracted from adult mosquitoes by using a Chelex 100 resin ( Bio-Rad Laboratories , Hercules , CA ) extraction method . 38 mosquitoes were ground in 3 L of proteinase K ( 20 mg/mL ) ( Roche Diagnostics Australia Pty . Ltd . , Castle Hill New South Wales , Australia ) and 250 L of 5% Chelex solution , incubated at 65°C for 1 hour , followed by incubation for 10 minutes at 90°C and storage at -20°C . Wolbachia infection status was determined by using methods developed for a Roche LightCycler 480 [34] with a modification to the primers used as described elsewhere [25] . Quantitative real-time polymerase chain reaction ( PCR ) was used to amplify three markers with three primer sets: a mosquito primer set to detect mosquitoes from the Aedes genus , Ae . aegypti specific primers to differentiate Ae . aegypti from other Aedes species , and Wolbachia specific primers to determine Wolbachia infection status , as well as density . PCR conditions were as follows: 95°C for 10 minutes , 40 cycles of 95°C for 5 seconds , 58°C for 15 seconds and 72°C for 15 seconds , ending with a 95°C 1-minute heating followed by cool down to 40°C for 20 seconds before raising to 65°C . A melting curve analysis was performed via a gradual increase of temperature from 65°C to 95°C . Diagnosis was based on crossing-point values for the PCR and melting temperature from high resolution melt analysis . We tested the potential for wMelPop to eliminate the field cage population of Ae . aegypti . Mosquitoes in both the treatment and control cages were allowed oviposit for three weeks after the last release . To provide a substrate that could be easily divided into separate egg cohorts to measure survival , we placed a roughened plastic liner inside each bucket for oviposition [30] . Sections of each liner were then cut off with scissors , viable eggs counted microscopically , and placed within the 70% and 99% shade sections of the awning used to measure egg survival . Strips of wMelPop infected and uninfected eggs were hatched in dilute yeast solution after 29 , 59 and 80 days exposure ( 7 Nov , 16 Dec and 6 Jan ) . Strips were dried for 1 week then reflooded to hatch any viable eggs not initially hatched . Percent hatch was calculated as with the egg survival study . In the final hatch all potplant bases and buckets were flooded to see if any eggs that may have been laid on the container rather than the ovistrip survived . We compared the total percent hatch between treatment and control for exposure period using chi square . Selection experiments were conducted to examine if egg desiccation resistance was due to a nuclear or Wolbachia effect . Eggs were collected daily for four days using sandpaper ovistrips and were fully conditioned as per the standard protocol [22] . All ovistrips were placed into a desiccation chamber set at ~60% Relative Humidity ( RH ) using a saturated solution of sodium bromide [22] . RH was monitored using a hygrochron ( 1-wire , iButton . com ) . To select a wMelPop desiccation resistant line ( AOMB-DS ) , we were aiming to obtain around 10% hatch rate over four rounds of selection . Previous experiments have shown that a 10% hatch rate occurred around Day 20–21 . Therefore , the ovistrips were divided into batches and hatched over a range of days ( 18–26 ) to obtain a hatch rate close to 10% . Eggs were hatched using Reverse Osmosis ( RO ) water , Tetramin fish food and yeast [22] . Hatch rate was determined by ( number of eggs/number of larvae ) x 100 . In each generation of selection , at least 100 eggs were used in the next generation . Each round of selection was followed by a non-selected generation to increase the number of adults for producing eggs available for selection in the next generation . There were four rounds of selection and the colony was then maintained in the laboratory over several generations . To determine if the selection response in AOMB-DS was due to a nuclear or Wolbachia effect , the selected line was crossed to unselected lines . Two new lines ( AX1 , AX2 ) were created by backcrossing AOMB-DS to males or females of the original AOMB line . Backcrossing was continued for three generations to place Wolbachia from the selected line onto the nuclear background of the infected ( AX1 ) stock ( Fig 2 ) or to place Wolbachia from the unselected line onto the nuclear background of the selected infected line ( AX2 ) . To test for viability , eggs were collected over four day periods from the AOMB-DS , AOMB , and C20 colonies as well as the backcrossed AX1 and AX2 lines . These were placed in the 60% desiccation chamber once conditioned . Three days later , eggs were cut into 10 batches of at least 25 eggs then counted and hatched into separate cups filled with 170 ml RO water and TetraMin fish food . Larvae were counted one week later as an estimate of viability . This process was carried out on eggs aged for 3 days and then repeated after 10 , 17 , 24 , 31 , 38 , 45 , 52 , 59 and 66 days [22] . Following selection , to compare the association between hatch rates and time in the different strains , we truncated the changes in hatch rates at 32 days ( ie before all the unselected wMelPop eggs had become non-viable ) and ran GLMs that included linear and quadratic terms for time as well as line type . These parameters provided an adequate fit to the data or each line ( R2>0 . 90 ) . We then considered whether lines differed for estimated parameters in these models . Because multiple strains were compared we computed parameter estimates for the different treatments and interactions and tested their significance using bootstrapped confidence intervals estimated in IBM SPSS Statistics 22 . To determine if the selection response in AOMB-DS was due to a nuclear or Wolbachia effect , the selected line was crossed to unselected lines . Two new lines ( AX1 , AX2 ) were created by backcrossing AOMB-DS to males or females of the original AOMB line . Backcrossing was continued for three generations to place Wolbachia from the selected line onto the nuclear background of the infected ( AX1 ) stock ( Fig 2 ) or to place Wolbachia from the unselected line onto the nuclear background of the selected infected line ( AX2 ) . To test for viability , eggs were collected over four day periods from the AOMB-DS , AOMB , and C20 colonies as well as the backcrossed AX1 and AX2 lines . These were placed in the 60% desiccation chamber once conditioned . Three days later , eggs were cut into 10 batches of at least 25 eggs then counted and hatched into separate cups filled with 170ml RO water and TetraMin fish food . Larvae were counted one week later as an estimate of viability . This process was carried out on eggs aged for 3 days and then repeated after 10 , 17 , 24 , 31 , 38 , 45 , 52 , 59 and 66 days [22] . All summary data can be accessed in Dryad Digital Repository at http://dx . doi . org/10 . 5061/dryad . 3vg33 [35] .
The wMelPop infected Ae . aegypti eggs exposed to a range of shade ( Fig 1 ) suffered higher mortality rates than uninfected eggs ( Fig 3 ) . Mortality ( decrease in % hatch ) was highest in summer and in sun exposed ( 30% , 70% shade ) eggs . Indeed , mortality of wMelPop infected eggs was nearly 100% after 8 weeks in all shade groups in summer . Uninfected eggs also suffered high mortality , but only in the highly exposed 30% shade treatment . The GLM on data from the summer experiment indicated a significant effect of shade and strain overall as well as time as a linear and quadratic term ( Table 1 ) . Interactions between strain and the time variables were not significant , although the quadratic—strain interaction approached significant . Increased shade led to lower viability across time ( Fig 3 ) and the parameter estimates indicated significant differences between the 99% shade and the 30% treatment , but there was no interaction between shade and strain or other interactions with shade ( all P>0 . 25 ) . The wMelPop strain had lower viability overall and tended to show a more rapid decrease in viability over time . For the winter experiment , the strain-shade interaction effects were also non-significant ( P > 0 . 25 ) . All other effects except for the main effect of strain were highly significant ( Table 1 ) . There were different patterns of changes in the hatch rates of strains across weeks , with linear and quadratic components . The wMelPop infection had a sharper drop in hatch rates compared to the uninfected line ( Fig 3 ) . The temperature in the winter trial ranged from ca . 15–28°C , with slightly higher temperatures in the 30% shade section ( S1 Fig ) . In winter , temperatures recorded from loggers on tables exposed to direct sunlight ( 30% and 70% shade ) peaked at 40–50°C in the afternoon ( S2 Fig ) . Relative humidity was generally high , ranging from ca . 50% to nearly 100% at night , although the maximum values are likely too high ( S3 Fig ) . In summer , temperature range increased to ca . 20–35°C ( S4 Fig ) , with exposed loggers peaking at 40–60°C at mid day for 30% and 70% shade ( S2 Fig ) . Relative humidity ranged from 50% to 90% ( S3 Fig ) . Releases resulted in the wMelPop infection gradually moving to fixation within the semi-field cage . Two successive weeks of 100% wMelPop infection rates were achieved after 16 consecutive weekly releases and two source reduction/vector control interventions ( Fig 4 ) . The mean temperature in the 70% and 99% shade sections was 26 . 2°C and 25 . 4°C , respectively , and ranged from 20–35°C ( S5 Fig ) . Relative humidity ranged from 50% to 95% . While we did not record temperatures in the exposed data loggers ( set on tables ) , results from the earlier egg survival study indicate that temperatures of 50°C would have occurred in the 70% shade section for a few hours on sunny days ( S2 Fig ) . Mean ( ± SE ) pupal counts for individual PPB and buckets in the wMelPop and uninfected cages were 0 . 62 ± 0 . 96 and 1 . 06 ± 1 . 37; and 28 . 9 ± 30 . 6 and 50 . 4 ± 27 . 2 , respectively . Collectively , the mean pupal production/day was 59 ± 49 and 103 ± 46 for the wMelPop and control cages , respectively . Based on a 0 . 8 and 0 . 9 adult daily survival ( DS ) , this would equate to a mean adult population , using the integration method [30] , of 280–451 and 490–790 adults for the wMelPop and uninfected cages , respectively . Eggs infected with wMelPop suffered significantly higher mortality than uninfected eggs for each exposure period except for 80 days at 70% shade , where no eggs hatched for either cohort ( Fig 5 ) . wMelPop infected egg survival dropped noticeably after 59 days , and only 3/443 ( 0 . 67% ) eggs hatched from the 99% shade cohort after 80 days . Mortality was also high in the uninfected eggs , but 7/154 ( 4 . 4% ) eggs hatched in the 99% shade cohort . No wMelPop infected eggs hatched from the PPB and buckets flooded at the end of the trial , while 9 hatched from a PPB with uninfected eggs . After four rounds of selection for desiccation resistant mosquitoes , there was an increase in the time required to produce a hatch rate of around 10% from around 17 days to almost 40 days ( Table 2 ) . This followed a rapid extension after two rounds of selection . In the backcrossed lines , the AOMB-DS line maintained a higher hatch rate in aged eggs compared to the AOMB line despite several generations without selection ( Fig 6 ) . The AX2 line showed a similar pattern to that of the AOMB-DS line . As expected , the uninfected C20 had the highest hatch rate . The unselected AOMB and AX1 lines had similar low hatch rates . The GLM showed that there was a significant effect of line on hatch rate ( F ( 4 , 285 ) = 4 . 097 , P = 0 . 003 ) and there were also significant interactions between line and the linear time component ( F ( 4 , 285 ) = 6 . 974 , P<0 . 001 ) and between line and the quadratic time component ( F ( 4 , 285 ) = 5 . 042 , P = 0 . 001 ) . These analyses indicate differences among strains in hatch rate changes across time involving both a linear and non-linear component . The time effects point to an increase in the hatch rate ( survival ) of the selected line with the wMelPop infection associated with the nuclear background of the line rather than the Wolbachia background . The AX1 line and AOMB did not differ in any way and all parameter estimates overlapped for these strains ( main effects of strain , interactions with linear and quadratic time components ) . This was also the case for AX2 and AOMB-DS . In contrast , the linear parameter for AX2 and week ( -0 . 103 ) fell outside the 95% confidence intervals for the equivalent value for AOMB ( -0 . 582 , -0 . 192 ) and this was also the case for the quadratic component ( 0 . 001 ) which fell outside the 95% confidence intervals for AOMB ( 0 . 015 , 0 . 101 ) . The quadratic component also differed between the selected and unselected AOMB lines ( AOMB , 0 . 058 , 95% CIs 0 . 015 , 0 . 101; AOMB-DS , -0 . 031 , 95% -0 . 074 , 0 . 013 ) as did the linear component ( AOMB , -0 . 387 , 95% CIs -0 . 582 , -0 . 192; AOMB-DS , 0 . 051 , 95% -0 . 144 , 0 . 246 ) .
Aedes aegypti eggs infected with wMelPop suffer significantly higher mortality than uninfected eggs . Nearly all of the infected eggs failed to hatch after 2 months for all shade and temperature exposures ( Fig 2 ) . Our semi-field cage experiment indicted that if releases of wMelPop successfully establish fixation , the population will potentially collapse during prolonged dry periods . Indeed , the hatching rate ( survival ) of wMelPop infected eggs was significantly lower after 59 and 80 days exposure ( Fig 3 ) . This points to the feasibility of using releases of wMelPop infected Ae . aegypti to eliminate local populations of Ae . aegypti and confirms the potential of this approach as first proposed and modelled in Rasic et al . [26] . Nevertheless , using wMelPop releases for elimination of Ae . aegypti populations will be more difficult than invasions involving wMel releases . To obtain fixation in the semi-field cage , we conducted 16 weeks of releases and two rounds of vector control . This is considerably more difficult than the invasions of wMel that have successfully established in Cairns after 11 weeks of releases , and at a faster rate in semi-field cages [17 , 19] . Indeed , sustained releases of wMelPop-infected Ae . aegypti failed to establish fixation by wMelPop at two field sites in Cairns in 2012 [25] . We could have improved efficacy of the releases by increasing the number of infected mosquitoes released . At the start of releases , the population in the treatment cage , based on pupal integration , was ca . 200 adults . We released 100 per week , or a release rate equivalent to 50% of uninfected adult population , although BGS captures suggested the initial 2 weeks of release cohorts were 150% of the uninfected population . The successful wMel invasions in Cairns involved releases at numbers roughly equivalent to wild populations . Higher releases rates should have improved the speed at which wMelPop became fixed in our semi-field cage . The use of wMelPop to eliminate local populations of Ae . aegypti will likely be limited by several constraints . It took 16 weeks of releases , with 2 cycles of vector control , to fix wMelPop in a small semi-field cage . Thus , releases without vector control , population suppression or another mechanism to assist invasion like the use of insecticide resistance are likely to be challenging [36] . The site will likely need to be isolated to avoid rapid re-infestation from adjacent areas , and will likely need to be relatively small , such as an isolated township [26] . Also the locale must have a prolonged dry period to facilitate egg death , as modelled in Rasic et al . [26] . Indeed , there were 4 viable infected eggs ( 3 from a bucket , and 1 from a PPB ) after 80 days in the full shade cohort , suggesting that wMelPop may persist at a very low level requiring additional vector control for elimination . Finally , candidate areas need to be focused on the elimination of Ae . aegypti , rather than simply a reduction of dengue risk , which will be more easily achieved by releases of wMel rather than wMelPop . The data generated from this study could be used to identify geographic areas through modelling where the use of virulent Wolbachia and vector control for population suppression would be most effective . Vector control and population manipulation can be used to facilitate wMelPop releases [36] . Improved vector control methods that target cryptic breeding sites , such as the use of auto-dissemination application of pyriproxyfen [37] , could temporarily remove cryptic foci of uninfected mosquitoes , enhancing invasion . Other temporary vector control methods , such as use of bleach to treat larval habitat [30] and non-persistent adulticides such as metofluthrin [38] , could provide a quick knockdown and avoid residual effects that would impact released mosquitoes ( crash and release strategy ) . A novel approach would be to couple genes for pesticide resistance to wMelPop , in effect engendering protection of the wMelPop mosquitoes from insecticides [39] , although this approach may be coupled with the fear of introducing resistant strains , and could be difficult to sell to the public , regulators and government officials . While the wMelPop infection has deleterious effects on egg viability when these are in a dried state , these effects are attenuated by strong selection . The crosses point to this attenuation being due to a nuclear background effect ( Fig 6 ) . Previous research has shown that the expression of Wolbachia effects on the host can be influenced by host background . Perhaps the most dramatic example of this is where Wolbachia causing cytoplasmic incompatibility or male killing in one host and then transfected into a different host species no longer expresses the same phenotype [40] . In addition , lifespan effects generated by Wolbachia in Drosophila melanogaster are altered through longevity selection and involve the nuclear background [41] . Once wMelPop have been successfully introduced into populations , evolution in Wolbachia may attenuate fitness effects , as recently documented in Drosophila [42] although this is clearly not always the case . Evolution seems likely to change the nuclear background and lead to attenuation , but this process may be countered by other selective pressures . Does use of a virulent Wolbachia strain such as wMelPop to eliminate local Ae . aegypti populations have advantages over traditional releases of sterile ( sterile insect technique ( SIT ) ) or incompatible ( incompatible insect technique ( IIT ) ) males ? Certainly use of Wolbachia eliminates the need for costly irradiation equipment and any potential fitness cost associated with irradiating males . Reared Wolbachia-infected cohorts do not need to be sexed before release , and the relative numbers of released insects should be much lower that SIT programs where overwhelming release ratios of high quality males are required [43] . There is no sudden population “bounce back” if releases of Wolbachia infected mosquitoes stopped ( assuming Wolbachia is nearly fixed in the population ) unlike SIT/IIT where residual wild populations can rapidly rebound . Wolbachia is seen as a biological control program with generally strong community support [44] , whereas some IIT programs involve genetically modified organisms , and may be relatively difficult to obtain public and regulatory support for . Disadvantages of use of virulent Wolbachia include the release of biting females , of the need to create a suitable infected line , and the potential requirement to conduct complimentary vector control . The survival of uninfected Ae . aegypti eggs exposed to direct sun ( 30 and 70% shade ) deserves comment . While egg survival was highest in full shade , many eggs exposed to sunlight ( 30% and 70% shade ) survived several weeks ( Fig 2 ) . Ae . aegypti eggs exposed to temperatures > 46°C suffer rapid mortality [45 , 46] . Our data loggers recorded mid day temperature spikes of up to 40°C to 60°C , 20–30°C higher than ambient temperature , lasting several hours ( S2 Fig ) . We suspect that the loggers , oriented horizontally on top of the sample jar ( Fig 1 ) , were subject to high solar gain and heating , and thus misleadingly high temperature readings . The Aedes eggs , on the other hand , are oriented vertically , minimizing their silhouette area when the sun is overhead and thus reducing solar gain . The small size of eggs would also facilitate cooling by the air . In summary , we have established the effects of the wMelPop infection on egg mortality when these are maintained in a dried state under semi-field conditions . This provides the possibility of using wMelPop to suppress and even eliminate mosquito populations in relatively isolated populations particularly where there is a long dry season . | Dengue is a leading cause of morbidity in the tropics . As a commercial vaccine is not available , control or modification of the mosquito vectors is employed to prevent transmission . Strains of the endosymbiotic bacteria Wolbachia affect the survival and ability of the dengue vector Aedes aegypti to transmit dengue . The Wolbachia strain wMelPop over-replicates within Ae . aegypti , inducing strong dengue virus blocking and early mortality of both egg and adult mosquitoes . We investigated whether this life-shortening Wolbachia strain can be used to eliminate local populations of Ae . aegypti in a semi-field cage . Our results indicate that Ae . aegypti eggs infected with wMelPop died at a significantly higher rate than uninfected eggs , and were nearly eliminated during a simulated dry season of 2–3 months . This suggests that that releases of wMelPop could facilitate control and elimination of Ae . aegypti if used in concert with vector control . | [
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] | [] | 2015 | Application of wMelPop Wolbachia Strain to Crash Local Populations of Aedes aegypti |
Fear learning is highly adaptive if utilized in appropriate situations but can lead to generalized anxiety if applied too widely . A role of predictive cues in inhibiting fear generalization has been suggested by stress and fear learning studies , but the effects of partially predictive cues ( ambiguous cues ) and the neuronal populations responsible for linking the predictive ability of cues and generalization of fear responses are unknown . Here , we show that inhibition of adult neurogenesis in the mouse dentate gyrus decreases hippocampal network activation and reduces defensive behavior to ambiguous threat cues but has neither of these effects if the same negative experience is reliably predicted . Additionally , we find that this ambiguity related to negative events determines their effect on fear generalization , that is , how the events affect future behavior under novel conditions . Both new neurons and glucocorticoid hormones are required for the enhancement of fear generalization following an unpredictably cued threat . Thus , adult neurogenesis plays a central role in the adaptive changes resulting from experience involving unpredictable or ambiguous threat cues , optimizing behavior in novel and uncertain situations .
The dentate gyrus in the mammalian hippocampal formation adds new granule neurons throughout life . Despite intense interest in recent years , the precise function of these adult-born neurons is not well understood . Over the past several years , one idea that has gained considerable support is that adult neurogenesis is important for pattern separation , or the ability to discriminate between highly similar cues [1 , 2] . Mice with disruptions of adult neurogenesis show impairments in fear context discrimination , discriminating spatially close arms in a radial maze , and object investigation tasks when the correct choice is similar to the incorrect choice [3–5] . Such impairments are thought to reflect a deficit in generating or recalling memories due to ineffective encoding of distinct features of cues or contexts that share many perceptual similarities [1 , 2 , 6] . New neurons , however , also have effects on emotional behavior . Inhibiting adult neurogenesis prevents the effects of antidepressants on some anxiety- and/or depressive-like ( anxiodepressive-like ) behaviors and enhances hormonal and behavioral responses to acute stress [7–10] . Notably , the behaviors affected in these studies ( novelty-suppressed feeding , grooming latency , and forced swim ) are assessed in one-trial tests that contain no explicit role for associative learning or memory , suggesting that these changes in emotional behavior are not caused by impairments in discrimination performance and pattern separation . However , one common feature of both pattern separation tasks and anxiodepressive behavioral tasks is a high degree of ambiguity or conflict . In the emotionality tasks , uncertainty arises from the conflict between possible behavioral choices that could be made in response to novel and ambiguous cues ( e . g . , approach versus avoid ) in potentially threatening situations , while in the aforementioned pattern separation tasks ambiguity arises from the difficulty of discriminating the highly similar cues . Unpredictability , or ambiguity , is in fact a defining feature of stressful or anxiogenic situations [11–13] . We hypothesize that a key role for new neurons may be in resolving or biasing responses to ambiguous information when potential threats generate uncertainty—a possibility that is consistent with a hippocampal role in processing ambiguity or conflict [13–19] . To test this possibility , we investigated the role of adult neurogenesis in partially predictable situations by assessing mice lacking new neurons on an ambiguously cued fear conditioning task . Mice with pharmacogenetic ablation of adult neurogenesis ( TK mice ) were trained either with a cue that predicted footshock 50% of the time ( ambiguous condition ) or in a control condition in which the cue perfectly predicted footshock ( reliable condition ) . This paradigm utilizing a partially predictive cue models situations in which a stimulus , e . g . , a stranger in a dark alley or a plane overhead in a war zone , sometimes predicts a threat but can also occur without negative consequences . TK mice responded normally to the reliable cue but exhibited reduced defensive behavior , and showed less hippocampal activation in response to ambiguous cues relative to wild-type ( WT ) mice . They also displayed less anxiodepressive-like behavior 2 d after the shock training with an ambiguous cue but more after the reliable cue . These findings suggest that new neurons enable animals to use information about the predictability of aversive events in order to modulate fear generalization in subsequent novel and ambiguous situations .
Prior reports have indicated that ablation of new neurons has no effect on cued fear conditioning , consistent with a lack of requirement for the hippocampus in this task [7 , 20–23] . These studies , however , have used cues that are consistently associated with shock and thus fully predictive of the outcome . To test whether responses to ambiguous cue-outcome relationships are dependent on adult neurogenesis , we asked whether mice lacking new neurons show normal freezing behavior in response to cues that are only partially reinforced , i . e . , partially predictive of shock . To specifically eliminate adult neurogenesis , we treated 8-wk-old mice expressing herpes thymidine kinase in neuronal precursors with the antiviral drug valganciclovir , which inhibits adult neurogenesis without affecting mature neurons or astrocytes [9] . As expected , adult neurogenesis was virtually eliminated in the dentate gyrus ( S1 Fig ) . Mice lacking adult neurogenesis ( TK mice ) and WT littermate controls ( WT mice ) were trained in a 3-day cued fear conditioning paradigm ( Fig 1A ) . In a between-subjects design , half of the mice of each genotype were exposed to a tone cue that always coterminated with a shock ( reliable fear conditioning ) , while the other half were exposed to a tone cue that coterminated with a shock only 50% of the time ( ambiguous fear conditioning ) . Different groups of mice were used for the two cue conditions in order to avoid potential overshadowing or interference between the cues [24 , 25] . TK mice were indistinguishable from WT controls in response to the reliable cue ( Figs 1B and S2 ) , consistent with previous studies [7 , 20 , 21 , 26 , 27] . However , the TK mice trained with the ambiguous cue showed significantly less cue-induced freezing than their WT counterparts ( Figs 1C and S2 ) . A similar effect was seen in a separate cohort of mice using visual cues as conditioned stimuli , indicating that this effect is independent of the specific sensory modality . Although higher baseline freezing levels were seen after conditioning with light cues as expected [28 , 29] , mice lacking adult neurogenesis froze less than wild types in the ambiguous fear condition but not in the reliable fear condition ( S3 Fig ) . Unconditioned responses to initial presentations of tone , light , and shock were similar in both genotypes , indicating normal sensitivity to the cue and shock in mice lacking adult neurogenesis ( S4A–S4D Fig ) . Freezing in the conditioning ( shock ) context was low and not different across groups ( S4E and S4F Fig ) , suggesting that both groups attributed predictive salience to the cue . Freezing levels decreased gradually and were well matched for both genotypes across several days of extinction following reliable tone-cued fear conditioning , suggesting that the lack of a deficit in reliable cue fear conditioning was not due to a ceiling effect ( Figs 1E and S5 ) . Furthermore , freezing after a reliably cued but weak training protocol using a very mild shock showed no effect of genotype ( Fig 1D ) , suggesting that cue-shock association learning was equivalent across genotypes . We also measured fear-potentiated startle as an alternative performance measure of fear/anxiety-like behavior , as it may be less prone to contamination by locomotor activity [30] . Separate groups of mice were fear conditioned with a reliable or ambiguous cue , as above , and startle responses were measured both in the presence and absence of the conditioned tones ( Fig 1A ) . The reliable tone cue increased startle responses to the same degree in WT and TK mice ( Figs 1F and S6 ) . In contrast , the ambiguous cue increased startle in the WT mice but had no effect in TK mice ( Figs 1G and S6 ) , consistent with the findings obtained with freezing measures . To better understand how the loss of such a small population of new granule neurons can affect behavior under ambiguous threat conditions , we investigated the impact of new neuron ablation on hippocampal and amygdala network activity during reliably and ambiguously cued shock . Expression of the immediate early gene Fos ( c-fos ) was analyzed as a measure of neuronal population activity [31–33] . Reliable and ambiguous tone-cued fear training were carried out as above , but mice were perfused shortly after the third training session . In WT mice , there was no effect of training condition on hippocampal neuron activation; equivalent numbers of Fos-expressing neurons were seen after reliable and ambiguous shock training in the overall granule cell population , new granule neurons , CA3 pyramidal neurons , and CA1 pyramidal neurons ( Fig 2A–2D ) . TK mice , however , had fewer activated mature granule cells and fewer activated CA3 and CA1 pyramidal cells in the ambiguous fear condition relative to the reliable fear condition , resulting in a statistically significant genotype x cue type ( reliable/ambiguous ) interaction across all three hippocampal subfields ( Fig 2B ) . Similar effects were observed in both the dorsal and ventral subregions of the hippocampus ( S7 Fig ) . There were no significant genotype differences in total freezing behavior across the entire session on the last training day , immediately prior to perfusion ( S8 Fig ) , suggesting that the observed differences in hippocampal neuron activation were unlikely simply to reflect a direct readout of the preceding behavioral performance ( locomotor activity levels ) of the animals . Within the basolateral nucleus of the amygdala ( Fig 2E ) , the number of Fos-expressing cells did not differ across genotypes , but fewer Fos-expressing cells were seen after ambiguous conditioning compared to reliable conditioning in both genotypes ( Fig 2F ) . No significant differences were found in the central nucleus ( Fig 2F ) . Taken together , these findings indicate that the new neurons influence the wider hippocampal network activation under conditions of ambiguous threat and suggest that the hippocampus , but not the amygdala , contributes to the behavioral changes observed in TK mice in response to ambiguously cued shock . We next asked whether exposure to reliable or ambiguous tone-shock relationships influences subsequent behavior in novel situations and whether new neurons play a role in such adaptive responses . To do this , we assessed novelty-suppressed feeding ( NSF ) behavior , a hippocampus-dependent test of anxiodepressive-like behavior [34] , in a novel setting 2 d after fear conditioning ( Fig 3A ) . In mice with normal levels of adult neurogenesis , exposure to reliable shock had no effect on subsequent NSF latency relative to a control group that experienced tones with no shocks ( Fig 3B ) . In contrast , reliably cued fear conditioning increased latency to feed in mice lacking adult neurogenesis ( Fig 3B ) . Thus , although the WT and TK mice had similar conditioned freezing responses ( and hippocampal activation ) to the reliable conditioned cue ( Figs 1 and 2 ) , they later showed differences in behavior when tested in a novel situation , with TK mice failing to suppress anxiodepressive-like responses . NSF behavior in a separate cohort of mice , which underwent fear conditioning using either the reliable or ambiguous cues , showed a genotype x predictor type interaction . WT mice took longer to eat after being conditioned with the ambiguous cue relative to mice trained with the reliable cue ( Figs 3C and S9 ) . TK mice , on the other hand , were unaffected by cue predictability , as demonstrated by their similar latencies following reliable or ambiguous cue training . The TK mice exhibited longer latencies than WT mice after reliable fear conditioning ( as in the previous experiment shown in Fig 3B ) yet shorter latencies than WT mice after ambiguous fear conditioning ( Fig 3C ) . These findings demonstrate that normal mice utilize information about the predictability of prior threat to adapt their level of cautious , or anxiodepressive-like , behavior in future situations . Mice without adult neurogenesis increase anxiodepressive-like behavior as a result of being shocked , but they do so without regard to the predictability of the shock . Taken together , these data suggest that new neurons have a bidirectional adaptive effect , suppressing neophagia in novel contexts following predictable shock while enhancing cautious behavior in new situations following ambiguous threat . Behavior was also tested in the elevated plus maze ( EPM ) , but no effects of cue predictability or genotype were observed ( S10 Fig ) . The key difference between the NSF and EPM tests is unclear , but previous studies have also found that even though both tests are sensitive to hippocampal lesions [34 , 35] , the EPM is less sensitive to changes in adult neurogenesis [7 , 9 , 26] ( but see [36] ) . Glucocorticoids enhance fear/anxiety in a strong shock model of posttraumatic stress disorder and play an important role in adaptive matching of stress resilience to the developmental environment [37 , 38] . We therefore asked whether these stress hormones also mediate the adaptive changes observed here following unpredictable shock in ambiguous cue fear conditioning . To do this , we assessed NSF in mice that were adrenalectomized prior to fear conditioning , preventing stress-induced glucocorticoid release . In these mice , we found increased latency to eat in TK mice relative to WTs , regardless of predictor type ( Fig 3D ) . Compared with the previous , adrenal-intact , experiment ( Fig 3C ) , the primary difference appears to occur in the WT mice trained with the ambiguous cue , which failed to show the strong increase in NSF latency after adrenalectomy . This finding indicates that glucocorticoids produced during fear conditioning ( S11 Fig ) can increase future anxiogenic ( neophagic ) behavior in novel situations , but only after ambiguously cued shocks and only in animals with new neurons . Loss of adrenal stress hormones had no effect on mice trained in the reliable cue condition , consistent with the idea that unpredictability is a critical feature of stress [11] .
Here , we show that neurons born in the adult hippocampus enable bidirectional adaptive changes in defensive behavior under conditions of ambiguously cued threat . Control mice , with normal levels of adult neurogenesis , freeze similarly to a cue that reliably predicts shock and to a partially predictive ( ambiguous ) cue . In a novel environment without shock-associated cues , control mice that experience predictable shocks show no increase in feeding latency , an anxiodepressive-like behavior , relative to unshocked mice . However , normal mice that received the same number of shocks , but in a less predictable manner with respect to the conditioned stimulus , show a strong glucocorticoid-dependent increase in their feeding latency . When mice lacking adult neurogenesis are trained with the ambiguous cue , they show less defensive behavior than controls in three different tests: decreased freezing to the cue following fear conditioning , decreased startle in the presence of the cue following fear conditioning , and decreased latency to eat during the NSF test in a novel environment . However , following reliably cued shock , mice without adult neurogenesis exhibit greater neophagia than normal mice in a novel context . Taken together , these findings suggest that defensive behavior in mice following an adverse experience reflects a combination of processes: ( i ) an increase in defensive behavior resulting from ambiguity in cues predicting threat ( similar to a stress response ) , which is mediated by adult neurogenesis and glucocorticoids , and ( ii ) inhibition , or contextualizing , of fear/anxiety following a reliably cued threat , which also requires adult neurogenesis but is glucocorticoid-independent . Strikingly , the changes in defensive behavior following reliably and ambiguously cued shock were paralleled by changes in neuronal activation in the dentate gyrus , CA3 , and CA1 . This finding , i . e . , decreased activation throughout the hippocampus in TK mice in response to an unreliable predictor of threat ( ambiguous cue ) , suggests that adult-born granule neurons normally recruit additional granule neurons and pyramidal neurons under partially predictable threat conditions . Adult-born granule cells likely increase hippocampal activity via direct synaptic connections with CA3 pyramidal cells [39] and disynaptic connections with CA1 pyramidal cells via CA3 Schaffer collaterals . Hilar mossy cells provide a possible link between new granule cells and mature granule cell activity [39 , 40] . Previous studies have described the excitability of adult-born neurons [41–43] , but the role of adult neurogenesis on hippocampal networks has remained unclear , with competing hypotheses suggesting that new neurons preferentially excite or inhibit the dentate gyrus and CA3 [40] . The current findings support the idea that new granule cells excite the hippocampus , in contrast to the preferential inhibition predicted by a role in sparse encoding/pattern separation or observed in slice physiology experiments [40] . However , the bidirectional effects we observe in behavior suggest that adult-born granule cells could potentially also diminish activity in the hippocampal network under certain circumstances , e . g . , in novel situations following reliably cued threat , although this has not been tested . The results of this study and others suggest an association between hippocampal activation and increased fear/anxiety . In one study , more ventral CA1/subiculum neurons are activated following a conditioned fear cue compared to an extinguished cue [44] . Similarly , more granule neurons are activated in rats during swimming , either in a water maze learning task or in a control condition lacking a platform , than under cage control conditions [42] . Consistent with these earlier findings , the treatment group showing the lowest level of freezing to the tone on the test day in the current study , the TK mice trained with the ambiguous cue , had the fewest activated granule neurons and pyramidal neurons on the prior day . The only previous study to look at fear-related neuronal activity in mice lacking adult neurogenesis found that irradiated mice had more activated mature granule cells than intact mice in an active place avoidance task on a rotating platform [45] , which appears inconsistent with the decreased granule cell activation in TK mice in the current study . However , in the current study all mice received the same number of shocks , whereas in the place avoidance study the mice without new neurons received more shocks than control mice , so their increased granule cell activation is also consistent with a positive relationship between hippocampal activation and fear . No previous studies have looked for changes in experience-induced neuronal activation outside the dentate gyrus associated with loss of adult neurogenesis . The decreased recruitment of neurons throughout the hippocampus observed here may explain how loss of a relatively small number of adult-born granule cells [21 , 46] can have significant effects on behavior . The effects of new neuron ablation on hippocampal network activation in the current study did not extend to the amygdala , which therefore seems unlikely to drive the behavioral changes observed in TK mice relative to wild types . Under reliable threat conditions , the hippocampus is strongly activated , with or without new neurons , but this activation may be unnecessary or redundant , as the hippocampus is usually not required for normal behavior when a straightforward cue-shock relationship exists [22 , 47] . Under conditions of ambiguous threat , however , the decreased freezing seen in TK mice may reflect the decreased lateral/basolateral amygdala activation in this condition seen in both genotypes . In normal WT mice , decreased amygdala activation may be offset by activation of young granule neurons , leading to enhanced activation throughout the hippocampal network and a resulting increase in behavioral inhibition and thus greater freezing [13] . Decreased freezing behavior in TK mice in response to the ambiguous cue could in principle reflect impaired fear learning , but several observations argue against an associative learning deficit . First , the TK mice showed normal fear conditioning with a reliable cue , even in the more difficult version of the task using a very weak shock , and showed equivalent freezing levels to controls throughout extinction of reliable cue fear conditioning . Both of these findings argue against the masking of a learning impairment by a ceiling effect . Second , although freezing levels were different in the ambiguous condition , TK mice significantly increased freezing in the presence of the cue relative to baseline and pre-cue time points , indicating that they learned the cue-shock association . Previous work found that levels of conditioned freezing are determined by a relatively fixed associative learning component and a highly variable nonassociative component [48] , suggesting that differential freezing in the current study reflects a change other than the strength of associative learning . Third , contextual fear was low in TK mice , suggesting that they , like WT mice , attributed greater weight or salience to the cue as a predictor of the shock [24 , 25 , 49] . This was true under ambiguous as well as reliable conditions . Finally , the behavioral changes in the NSF test are unlikely to reflect impaired associative learning , as this test involved no explicit role for conditioned stimuli , i . e . , no specific cue or context to guide learned behavior . Because the fear conditioning tasks in our study utilized one single cue , which was exactly the same in shock and no-shock trials , the behavioral effects in TK mice cannot be explained by an impairment in the discrimination of highly similar cues [2] , as in “pattern separation” tasks described previously [3–5] . However , it is possible that the observed changes in freezing and startle behavior to the ambiguous cues in the TK mice reflect an impairment in “pattern separation” or disambiguation at the level of retrieval of overlapping tone-shock and tone-no shock associative memories or , similarly , the meaning behind the tone ( tone-safety and tone-danger ) . A related possibility is that TK mice are impaired in choosing between the competing behavioral responses associated with those memories ( tone-freeze versus tone-don’t freeze ) [15 , 50] . Performance impairments resulting from response competition , in the absence of memory impairment , have also been described in partial reinforcement spatial tasks performed under stressful conditions [51–53] . The adult neurogenesis-dependent effects on neophagia most likely reflect a form of fear generalization . The parallel results across experiments suggest that the enhancement of freezing and startle in normal mice may also reflect the same process . Such generalization is critical to survival , as it enables an organism to enhance alertness and quickly respond to threats not specifically encountered before [54] . It is frequently viewed as being driven by perceptual similarity to previously encountered threat cues ( i . e . , stimulus generalization ) . Recent evidence from human studies , however , supports an alternative to this perceptual model in which fear generalization is instead driven by an active process triggered by ambiguity in threat outcome , which is then integrated with passive cue similarity information [12] . This view of generalization as an active ambiguity-driven process fits with our findings that both stress hormones and signals from new neurons enhance fear generalization following ambiguous , potentially threatening events . The hippocampus has previously been implicated in fear generalization , a role variously described as supporting pattern separation of perceptually similar cues to minimize stimulus-based fear generalization [55] or as biasing behavior during uncertain expectation by strengthening the representation of aversive potential outcomes [13 , 56] . The current findings support a hippocampal role in ambiguity-based fear generalization and suggest an important role for ongoing neurogenesis , in particular , possibly in predicting or weighting possible outcomes associated with different behavioral options [57 , 58] and/or in emotional biasing of decisions [13 , 16 , 56 , 59] . Fear generalization in response to severe threat , a possible model for posttraumatic stress disorder , occurs even when shock is reliably cued and is known to rely on plasticity in a population of neurons in the lateral amygdala [48 , 54] . A recent study found that nonassociative , or generalization , effects of strong shock are enhanced in mice lacking new neurons [36] , consistent with enhancement of stress response in these animals [9] . The persistent behavioral effects of strong shock , i . e . , increased freezing in shock-associated and/or novel contexts , are not observed in mice exposed to mild shock [36] . The current study demonstrates that fear generalization can also occur in response to mild shock if it is ambiguously cued . The relationship between fear generalization induced by strong threat and by ambiguously cued threat is unclear; differences in the behavioral changes observed by Seo et al . and in the current study could indicate that these two forms of fear generalization are entirely distinct , or they may simply reflect differences in fear intensity . Conceptually , fear generalization might describe a transition from fear , the emotional response to a specific stimulus that indicates that danger is imminent , to anxiety , a longer-lasting emotional state generated by less specific , less predictable , or potential threats [13 , 60 , 61] . Fear generalization is highly adaptive , yet hyperactivity in fear generalization circuits may drive excessive or inappropriate fear responses , which can limit more rewarding actions and lead to generalized anxiety disorder [60 , 62 , 63] . Too little generalization can be equally detrimental , posing a threat to survival or welfare by failing to promote active defensive behaviors and avoidance of danger . Thus , there is an optimal level of fear generalization , resulting in a balance between competing approach and avoidance behaviors [63 , 64] , but exactly where this balance lies is specific to a given situation . The current results suggest that adult hippocampal neurogenesis plays a role in continually and flexibly optimizing this balance based on prior experience . The adaptive nature of fear generalization has been highlighted in the “predictive adaptive response hypothesis” [65 , 66] , which suggests that the level of adversity in the developmental environment biases protective stress or anxiety responses in adulthood to better adapt an organism to the environment into which it is born . The current findings suggest that adult neurogenesis , through a role in predicting or biasing outcomes of ambiguous events , allows for this type of matching between the environment and the level of fear generalization to continue into adulthood [67]—in effect extending a behavioral form of developmental plasticity . By enhancing or inhibiting fear generalization according to the predictive ability of environmental cues , changes in the production of new neurons can potentially affect behavior in any situation featuring ambiguity generated by a potential threat or , more broadly , any difficult choice [11 , 12 , 57] . The current findings therefore provide a potential link between the roles of new neurons in the stress response , anxiodepressive-like behavior , and pattern separation .
Transgenic male mice ( TK mice ) expressing the herpes simplex virus thymidine kinase under the human glial fibrillary acidic protein promoter and maintained on a CD-1 background [9] and WT littermate controls were generated from heterozygous x WT matings , weaned at 3 wk of age , genotyped via PCR , and housed 3 to 4 per cage with mixed genotype siblings . Beginning at 8 wk of age , mice were treated with valganciclovir p . o . ( 0 . 3% , 35 mg/kg/d ) , 4 d/wk , for 8–9 wk before behavior testing . Mice were housed under a 12-h light:dark cycle , and all testing took place during the dark phase . All procedures were approved by the NIMH Animal Care and Use Committee and comply with NIH guidelines ( PHS Animal Welfare Assurance A4149-01 ) . Mice were identified by randomly assigned ear tag numbers so investigators were blind to genotype . Mice were handled 3–5 min/d for 3 d prior to behavioral testing and were brought to a dark holding area 30 min prior to testing on each day . Fear conditioning was conducted in a clear-walled , 30 x 30 x 24 cm chamber ( Coulbourn Instruments ) , which was cleaned with 70% EtOH after each session . The unconditioned stimulus ( US ) was a 0 . 5-mA ( except in the weak shock experiment , where it was 0 . 3 mA ) , 1-s scrambled shock delivered through the grid floor . Cues ( Coulbourn bright light or 2 kHz , 85 dB ( A ) tone ) lasting 20 s served as conditioned stimuli . Mice in the “reliable” groups received three cue-shock pairings per session , with the cue always coterminating with a shock . Mice in “ambiguous” groups received the same three cue-shock pairings and three additional cue-only trials in each session , so the cue coterminated with a shock in only 50% of trials . Sessions lasted 600 s with a 120-s habituation period prior to cue presentation for tone fear conditioning ( 660 s with 180-s habituation for light fear conditioning ) . To look at IEG expression , a separate cohort of mice received tone-cued fear conditioning but were perfused 2 h after the third training day for histological analysis ( see below ) . Mice were trained in 3 sessions separated by 24 h . The timing of cues , and order of cue-shock and cue-only trials for the ambiguous group , was pseudorandom and differed across consecutive days . Freezing to the conditioned tone ( or light ) was tested in a novel arena 24 h after the last training day . Freezing during six 20-s cue presentations was compared with freezing during the 100-s baseline prior to the first cue . Activity response to the first shock was analyzed using TopScan ( CleverSys , Inc ) . For the reliable auditory cue fear conditioning groups , six daily extinction sessions , each with six 20-s tones and no shocks , beginning 1 d after cued fear recall testing , were given back in the original training context . Freezing during the first 2 min ( habituation ) of the first extinction day served as a measure of contextual freezing . Context freezing was analyzed following cued fear conditioning in the light conditioning experiment . Freezing was analyzed using FreezeView software ( Coulbourn Instruments ) . Fear conditioning and startle testing were conducted in acoustic startle boxes ( Med Associates Inc . ) in naïve mice . The 9-d experiment included a habituation day , 2 noise burst intensity test days , a rest day , a preconditioning test , 3 d of “reliable” or “ambiguous” fear conditioning , and a postconditioning test , following a published protocol [68] . Reliable and ambiguous groups were run during consecutive weeks . During preconditioning , startle to noise burst alone ( NBA ) and noise bursts preceded by an unconditioned tone ( TNB ) served as a baseline . Tones were 20 s , 2 kHz , and 70 dB ( A ) . After a 2-min acclimation period , noise bursts ( 75 , 80 , and 85 dB ( A ) ) were presented 3 times alone ( 9 trials ) in a pseudorandom order , followed by NBA trials intermixed with TNB trials . An internal chamber fan ( 63 dB ) was used to mask external sounds throughout the startle experiment . All ITIs were 30 s . For fear conditioning , the same protocol as the tone-cued fear conditioning experiments was used , except the shock was 250 ms in duration ( 0 . 5 mA ) . Startle was tested using the same protocol as in preconditioning ( above ) , except with variable ITIs ranging between 80–120 s ( reliable conditioning group ) or 50–70 s ( ambiguous conditioning group ) . Different variable ranges were used in order to keep time in the chambers the same between each group . Peak-to-peak startle amplitudes were collected 600 ms following the noise burst , and the average of the difference scores from the 75 and 80 dB ( A ) trials were used . Mice were tested in a white arena ( 50 x 50 x 40 cm ) with bedding just covering the floor . One pellet of familiar food was placed on top of a 1-cm-high white dish in the center of the arena where light was set to 290 lux . Latency to begin eating the food was scored ( maximum trial time of 10 min ) . This maze had four arms , each 50 x 10 cm , two of which had 40 cm high walls ( closed arms ) , and a 10-cm2 center zone . The maze was elevated 50 cm above the ground , surrounded by black curtains , illuminated to 700 lux , and cleaned with 70% EtOH between trials . Mice were allowed to explore freely for 5 min . Time spent in each arm was determined using TopScan ( CleverSys , Inc . ) . To clamp corticosterone levels , adrenal glands were removed from mice under isoflurane anesthesia 5 d prior to behavior . Adrenalectomized mice were given saline ( 0 . 9% NaCl ) with low-dose corticosterone replacement ( 25 μg/ml with 0 . 15% v/v ethanol ) in drinking water to maintain baseline levels of corticosterone [69] . After behavior testing , corticosterone replacement was discontinued for 4 d , blood was sampled under isoflurane , and serum corticosterone was measured via radioimmunoassay ( MP Biomedicals ) . Two mice were excluded due to incomplete adrenalectomy ( levels >40 ng/ml ) . To measure corticosterone responses to fear conditioning in adrenal-intact mice , submandibular blood was sampled from unanesthetized mice 30 min after fear conditioning ( ambiguous and reliable ) , and serum corticosterone levels were measured as above . To confirm ablation of neurogenesis , brains from all mice were fixed in 4% paraformaldehyde , sectioned , and stained with anti-doublecortin ( Santa Cruz Biotech , sc-8066 ) [9] . To identify adult-born neurons in the IEG experiment , mice were given BrdU ( 1 mg/mL , Roche; with 1% sucrose ) in drinking water for 6 d and underwent tone-cued fear conditioning 4 wk after BrdU treatment began . Mice were perfused with 4% paraformaldehyde 2 h after the start of the third training session . Brains were sectioned at 40 μm through the entire rostral-caudal extent of the hippocampus . For IEG analysis , 1:8 series of sections were triple-stained using 2 h denaturation in 2N HCl and 3-day incubation in rat anti-BrdU ( 1:200; Accurate Chemical OBT0030 ) , goat anti-c-fos ( 1:250; Santa Cruz Biotechnology sc-52-G ) , and mouse anti-NeuN ( 1:250; Chemicon MAB377 ) [70] . Staining was visualized with anti-rat Alexa 488 , anti-goat Alexa 555 , and anti-mouse Alexa 633 ( all 1:200 , Life Technologies A21208 , A21432 , and A31571 , respectively ) . Sections were mounted , coverslipped with PermaFluor ( Thermo Scientific ) , and coded prior to analysis . Total counts of Fos+ cells in the dorsal and ventral dentate gyrus granule cell layer dorsal and ventral CA3 and CA1 pyramidal cell layer , and basolateral and central amygdala in stained series were multiplied by the series interval to obtain stereological counts . All BrdU+ cells in the granule cell layer were counted and examined for colabeling with Fos , using optical stacks of 1 μm confocal sections and examination of orthogonal planes ( Olympus FV300 , 60X ) to confirm double-labeling . One mouse was excluded from BrdU analysis because it did not have enough BrdU+ cells to meet the criterion of 100 cells analyzed . Another data point was excluded because it was >3 SD higher than the mean; removal of this point did not affect the outcome of the test . Experiments were run on mixed genotype litters born in the same week ( cohorts ) , pseudorandomly assigned by cage to treatment conditions . Data were analyzed with GraphPad Prism and SPSS software . All t tests were independent samples ( two-tailed ) . All other comparisons were two-way or three-way mixed or between-subjects ANOVA , as appropriate . All post hoc comparisons were made with corrections for multiple comparisons . | The ability to predict whether an experience will end favorably is critical for well-being . Cues associated with specific outcomes can aid in prediction , enabling adaptive behaviors , but cue-outcome relationships are often difficult to learn or inherently ambiguous . Human studies have suggested that the hippocampus , a brain region involved in learning and memory , is also important for predicting outcomes and mediating behavior in situations of uncertainty and conflict . We tested the role of a subtype of hippocampal neurons born in adulthood in responding to ambiguously cued shock . We found that mice without these young neurons show less defensive behavior than normal mice when they hear an ambiguous cue , paired with shock in 50% of trials , but react normally when the cue perfectly predicts the shock . In a novel situation , normal mice behave defensively after ambiguously cued shocks but show very little anxiety-like ( defensive ) behavior if shocks were predictable . Mice without new neurons fail to make this adaptive change , showing moderate levels of anxiety-like behavior regardless of the predictability of earlier threats . Our findings suggest that an important role for the continued neurogenesis in the hippocampus is to enable adaptive changes to future behavior depending upon predictability of prior threats . | [
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"fea... | 2017 | Ongoing neurogenesis in the adult dentate gyrus mediates behavioral responses to ambiguous threat cues |
The neuraminidase inhibitor oseltamivir is currently used for treatment of patients infected with the pandemic A/H1N1 ( pH1N1 ) influenza virus , although drug-resistant mutants can emerge rapidly and possibly be transmitted . We describe the characteristics of a pair of oseltamivir-resistant and oseltamivir-susceptible pH1N1 clinical isolates that differed by a single change ( H274Y ) in the neuraminidase protein . Viral fitness of pH1N1 isolates was assessed in vitro by determining replication kinetics in MDCK α2 , 6 cells and in vivo by performing experimental infections of BALB/c mice and ferrets . Despite slightly reduced propagation of the mutant isolate in vitro during the first 24 h , the wild-type ( WT ) and mutant resistant viruses induced similar maximum weight loss in mice and ferrets with an identical pyrexic response in ferrets ( AUC of 233 . 9 and 233 . 2 , P = 0 . 5156 ) . Similarly , comparable titers were obtained for the WT and the mutant strains on days 1 , 3 , 6 and 9 post-infection in mouse lungs and on days 1–7 in ferret nasal washes . A more important perivascular ( day 6 ) and pleural ( days 6 and 12 ) inflammation was noted in the lungs of mice infected with the H274Y mutant , which correlated with increased pulmonary levels of IL-6 and KC . Such increased levels of IL-6 were also observed in lymph nodes of ferrets infected with the mutant strain . Furthermore , the H274Y mutant strain was transmitted to ferrets . In conclusion , viral fitness of the H274Y pH1N1 isolate is not substantially altered and has the potential to induce severe disease and to disseminate .
The novel influenza A ( H1N1 ) virus was initially detected in Mexico and California in April 2009 and then officially became the first pandemic influenza virus of the 21st century on June 11 , 2009 [1] , [2] . Most confirmed cases of pandemic A/H1N1 ( pH1N1 ) infection have been characterized so far by self-limited flu-like symptoms and signs although a significant proportion of infected patients also presented with vomiting and diarrhea [2] . A minority of cases , notably those involving pregnant women , have been associated with a more severe clinical outcome leading to intensive care admission and death [3] , [4] , [5] . Mouse , ferret and non-human primate studies have indicated that pH1N1 isolates replicate more efficiently and produce more severe pathological lesions in the lungs than recent human A/H1N1 viruses [6] , [7] , [8] . Seroprevalence studies have indicated that children were initially serologically naïve to the novel pH1N1 strain whereas some degree of pre-existing immunity to this virus existed in the elderly population [6] , [9] , [10] . Antivirals are the cornerstone of treatment for severe influenza cases requiring hospitalization and can also be used as prophylactic agents in high-risk individuals . Early reports demonstrated that pH1N1 strains were resistant to the adamantanes due to a S31N mutation in the M2 gene but remained susceptible to neuraminidase inhibitors ( NAIs ) such as oseltamivir and zanamivir [6] , [11] . However , oseltamivir resistance has been on the rise in recent seasonal influenza A/H1N1 viruses . Indeed , during the 2008–09 influenza season , almost all characterized influenza A/Brisbane/59/2007-like ( H1N1 ) strains from North America and Europe were resistant to oseltamivir due to a H274Y ( N2 numbering ) mutation in the neuraminidase ( NA ) gene [12] , [13] , [14] . The sudden and large dissemination of this mutant A/H1N1 virus occurred in the apparent absence of antiviral pressure suggesting that it had no impairment in viral fitness . This drug resistance mutation has also been reported in some A/H5N1 viruses [15] , [16] and , more recently , in several pH1N1 strains recovered from both immunocompromised and immunocompetent subject [17] , [18] , [19] , [20] . We recently reported the emergence of such an oseltamivir-resistant H274Y mutant in a familial cluster of pH1N1 infections [21] . In this outbreak , we identified a drug-susceptible virus recovered before therapy from a 13-year old boy and a drug-resistant virus collected a few days later from his father who was receiving oseltamivir prophylaxis . We now describe the in vitro and in vivo replicative characteristics of the drug-resistant and wild-type ( WT ) viruses isolated from this outbreak .
As shown in Table 1 , the pH1N1 isolate from the index case collected before oseltamivir therapy ( A/Québec/147023/2009-WT ) was susceptible to all NAIs whereas the pH1N1 isolate from the contact case recovered during post-exposure oseltamivir prophylaxis ( A/Québec/147365/2009-H274Y ) was resistant to oseltamivir and peramivir . Both isolates were susceptible to zanamivir and A-315675 similarly to 20 other pH1N1 isolates collected from untreated subjects in the same period . The pattern of NAI resistance of the pH1N1 H274Y mutant was similar to that of another H274Y mutant from a seasonal A/H1N1 strain ( A/Brisbane/59/2007-H274Y ) . A pH1N1 H274Y recombinant mutant virus generated from an unrelated pH1N1 strain also exhibited high levels of resistance to oseltamivir and peramivir but remained susceptible to zanamivir and A-315675 ( Table 1 ) . Sequence analysis of the original clinical isolates revealed the presence of only one substitution ( H274Y; N2 numbering ) in the NA gene of the contact case ( GenBank accession number FN434454 ) compared to that of the index case ( accession number FN434445 ) . There was no change in the remaining 7 segments between these two strains ( accession number FN434440 to FN434447 for the index case virus and FN434448 to FN4456 for the contact case virus ) . Phylogenetic analysis of the NA and HA genes showed that the two pH1N1 isolates described in this study were closely related to pH1N1 strains identified in North America , Europe and Asia ( data not shown ) . The viral populations in the two clinical isolates were homogenous as 100% ( 16/16 ) of clones from the index case had the H274 sequence whereas 100% ( 16/16 ) of clones from the contact case harboured the 274Y sequence . In vitro experiments performed in MDCK cells expressing the α2 , 6 sialic acid receptor indicated that the oseltamivir-resistant pH1N1 isolate replicated less efficiently than the WT pH1N1 during the first 24 h . However , there was no significant difference in viral titers subsequently i . e . from 36 to 72 h ( Figure 1 ) . The two pH1N1 isolates produced lower viral titers than seasonal A/H1N1 viruses ( A/Brisbane/59/2007 ) including both a WT and a H274Y mutant at 36 and 48 h . Thus , the H274Y mutation resulted in either no impairment or only initial reduction in replicative capacities when inserted in seasonal and pandemic A/H1N1 backgrounds , respectively . Of note , the two pH1N1 viruses produced less well defined viral plaques on α2 , 6-transfected MDCK cells compared to seasonal strains ( data not shown ) . Two separate mouse experiments were conducted to assess weight loss , clinical signs , viral titers ( on days 3 and 6 in the first experiment and on days 1 , 6 and 9 in the second experiment ) and histopathological changes . In the first experiment , the WT and oseltamivir-resistant pH1N1 isolates induced similar maximum weight loss , which peaked on day 8 at 16 . 3% for both groups ( P = 0 . 81 ) although there was a more pronounced weight loss from days 3 to 7 with the mutant strain ( Figure 2 ) . In the second experiment , more weight loss was induced after infection with the H274Y mutant from days 3 to 8 . By day 12 , all mice from the two experiments had returned to their initial weight with no mortality . Lung viral titers , which were determined on days 1 , 3 , 6 and 9 post-infection , did not significantly differ between the WT and H274Y mutant viruses when assessed by quantitative viral culture ( Figure 3 ) and real-time RT-PCR ( Figure S1 ) . Importantly , there was no unexpected change in the NA sequence of viruses recovered from lungs of euthanized mice . Transcript levels for various cytokines/chemokines ( KC [CXCL1] , MCP-1 [CCL2] , MIP-1α , IFN-γ , IL-4 , IL-5 , IL-6 and IL-10 ) were determined in lungs of infected mice on days 1 , 6 and 9 post-infection . All cytokines/chemokines were equally expressed following infection with either of the two pH1N1 isolates ( Figure S2 ) , with the exception of increased expression of IL-6 and KC levels on day 1 , following infection with the H274Y mutant virus ( Figure 4 ) . Both pH1N1 isolates induced significant pulmonary inflammation including peribronchial , interstitial , perivascular , alveolar and pleural inflammation that peaked on day 6 post-infection ( Figure S3 ) . There was significantly more perivascular ( day 6 ) and pleural ( days 6 and 12 ) inflammation visualized in the lungs of mice infected with the H274Y mutant compared to the WT virus ( Figure 5 ) . A mild to moderate vascular congestion was observed in both groups of mice although pulmonary oedema was not noted in any mice . Inflammatory cellular infiltration was characterized by both acute ( neutrophilic ) and chronic ( lymphohistiocytic ) infiltrates in all mice . Thus , mouse experiments indicated that the mutant pH1N1 isolate induced more pronounced weight loss than the WT virus which correlated with increased expression of IL-6 and KC and more significant lung inflammation despite similar lung viral titers . Intranasal inoculation of ferrets with the WT and H274Y mutant pH1N1 isolates resulted in a strong anti-A/California/07/2009 serum antibody response on day 14 ( hemagglutination inhibition reciprocal geometric mean titers went from <20 to 4208 and from <20 to 3135 , respectively ) . Notably , all ferrets had preexisting HI antibodies against seasonal A/H1N1 ( A/Brisbane/59/07 ) but titers were similar in the two groups of ferrets pre- and post-infection ( Table S1 ) . A pyrexic response was seen between days 2 and 8 post-inoculation ( Figure 6 ) . Interestingly , temperature curves were biphasic with a major peak on days 2–3 and another lower peak on days 5–6 in both groups of ferrets . The area under the curve ( AUC ) of temperatures over the course of the 14-day experiment was similar for both groups of ferrets i . e . 233 . 9±0 . 5787 for the WT and 233 . 2±0 . 8669 for the H274Y mutant ( P = 0 . 5156 ) . Also , the mean percentage of body weight loss over time was not significantly different in animals infected with the WT or the H274Y mutant virus ( Figure S4 ) . The maximum weight loss ( day 7 and day 3 ) was 7 . 54% and 4 . 15% for the WT and H274Y mutant viruses , respectively ( P = 0 . 0515 ) . By the end of the 14-day observation period , the ferrets had returned to their initial weight with no mortality . Viruses could be recovered from nasal wash of ferrets up to 7 days post-infection with a peak on day 2 post-infection ( Figure 7 ) . Viral titers did not significantly vary at any time points when comparing the two groups of ferrets . Increased levels of IL-6 , IL-12 and IFN-γ mRNA were observed in retropharyngeal lymph nodes of ferrets infected with the H274Y mutant compared to the WT on day 14 with ratios of 1 . 174 , 1 . 38 and 1 . 183 , respectively ( not shown ) . Expression of IL-2 was decreased in ferrets infected with the mutant virus compared to the WT with a ratio of 0 . 8 . Thus , ferret experiments showed no significant differences in clinical parameters ( temperature and weight ) and viral titers in the upper respiratory tract for the WT and mutant pH1N1 isolates . However , some cytokines ( IL-6 , IL-12 and IFN-γ ) were specifically upregulated in lymph nodes of ferrets infected with the H274Y mutant . A limited transmission study was conducted in ferrets and it demonstrated that the H274Y mutant strain was transmitted from ferrets experimentally infected intranasally to ferrets placed in the same cage 24 h after infection . All contact ferrets seroconverted for A/California/07/2009 when tested 14 days after contact ( hemagglutination inhibition reciprocal geometric mean titers went from <20 to 993 ) . All contact ferrets also shed virus and had a mean peak viral titer of 8 . 32×104 PFU/ml in their nasal washes .
Oseltamivir , the most frequently used NAI , is recommended for treatment of patients with severe pH1N1 infections leading to hospitalization or those with underlying diseases which place them at risk of complications . We have recently described the rapid emergence of oseltamivir resistance in a family cluster of pH1N1 infection due to the H274Y NA mutation [21] , and now report on the viral fitness of this mutant in vitro and in vivo . Despite slightly reduced propagation of the mutant isolate in vitro during the first 24 h of infection compared to the original WT virus , both isolates replicated as efficiently in the lower respiratory tract of mice and in the upper respiratory tract of ferrets inducing similar maximum weight loss and pyrexic response between days 2 and 8 post-infection . Interestingly , the H274Y NA mutant induced a slightly more pronounced weight loss than the WT virus in mice , and this observation correlated with increased production of IL-6 and KC and a more important pulmonary inflammation involving the perivascular ( day 6 ) and pleural ( days 6 and 12 ) compartments . Previous studies have demonstrated that oseltamivir resistance results from subtype-specific NA mutations [15] . In influenza viruses of the N1 subtype , including seasonal A/H1N1 viruses and avian A/H5N1 strains , oseltamivir resistance is mainly conferred by the H274Y ( N2 numbering ) mutation [16] , [22] , [23] . This mutation has also been recently detected in pH1N1 viruses [17] , [18] , [19] , [20] , [21] . The larger tyrosine residue at codon 274 prevents the re-orientation of glutamic acid at position 276 within the catalytic site , which is required to accommodate the bulky side chain of oseltamivir but not zanamivir [24] . In agreement with previously-described seasonal A/H1N1 viruses containing the H274Y NA mutation , our oseltamivir-resistant pH1N1 mutant showed cross-resistance to peramivir , a parenteral NAI that is in phase 3 clinical trials [15] , [25] and also readily available through an emergency access program [26] . On the other hand , our phenotypic findings demonstrate an interesting potential for inhaled zanamivir and the investigational orally-available A-322278 NAI compound ( the prodrug of A-315675 ) [27] , as alternative agents for treatment of oseltamivir-resistant pH1N1 infections . The impact of mutations conferring NAI resistance on viral fitness and transmissibility may vary depending on the genetic background of influenza viruses . In the N1 subtype , the H274Y mutation has been initially reported as impairing the viral fitness of older seasonal strains such as A/New Caledonia/20/99-like and A/Texas/36/91 when evaluated in the ferret model [28] , [29] . However , transmission of the H274Y mutant strain was documented in ferrets [28] . More recently , our group showed that the same mutation had a different effect , i . e . it was associated with conserved viral fitness in the seasonal A/Brisbane/59/2007 ( H1N1 ) background when assessed both in vitro and in ferrets [30] . In the present study , the replication of the pH1N1 H274Y mutant was initially impaired in vitro compared to the WT virus but viral titers were virtually identical on days 2 and 3 post-infection . The two pH1N1 isolates replicated less efficiently ( lower titers and reduced plaque formation ) than the recent WT and H274Y mutant A/Brisbane/59/2007 strains in ST6Gal I-expressing MDCK cells , which may indicate a greater affinity of the seasonal strain for α2 , 6 sialic acid receptors . Different groups have reported the use of exprimental animal models for studying WT pH1N1 infection . For instance , Itoh et al . [6] and Maines et al . [7] observed significant weight loss in BALB/c mice associated with efficient viral replication in lungs when an intranasal inoculum ≥104 plaque forming units ( PFUs ) was used . Some mice even died from a viral challenge consisting of 106 PFUs [6] . Those results indicate that pH1N1 strains can replicate efficiently in mice in contrast to most seasonal A/H1N1 strains . The selective replication of pH1N1 virus in the BALB/c mouse model without prior animal adaptation is reminiscent of features described for highly pathogenic A/H5N1 viruses and the 1918 Spanish flu virus although they are generally less severe with pH1N1 [31] , [32] . In agreement with these reports , we observed that pH1N1 can efficiently infect BALB/c mice inducing weight loss , high viral lung titers and also significant pulmonary histopathological changes . Moreover , we now report that the H274Y pH1N1 mutant virus is clearly as fit as the WT virus in this animal model . In fact , more weight loss was induced by the H274Y mutant compared to the WT virus during the first 7–8 days post-infection although all mice eventually returned to their initial weight . On the other hand , we found no significant differences in lung viral titers between the two groups of mice when assessed on days 1 , 3 , 6 and 9 . The more prounounced weight loss observed with the mutant strain compared to the WT virus was confirmed in two separate experiments using similar viral inoculum ( as confirmed by back titration ) and unaltered viral genomes ( as confirmed by sequencing the virus from lungs of euthanized mice ) . These important clinical signs correlated with slightly more severe histopathological changes observed in lungs of mutant-infected mice in particular on days 6 and 12 post-infection and more specifically in the perivascular and pleural compartments . Altogether , those results suggest that the H274Y pH1N1 mutant isolate stimulated a more important inflammatory response in mice compared to WT virus , which could be due to rapid induction of IL-6 and KC in the former . It has been reported for different influenza viruses that the early secretion of pro-inflammatory cytokines was associated with the development of pulmonary inflammation at a later stage [33] as shown here for pH1N1 . Interestingly , the H274Y mutant also induced preferential expression of IL-6 , IL-12 and IFN-γ in the retropharyngeal lymph nodes of ferrets compared to the WT virus . In humans , IL-6 has been shown to be the first cytokine to appear in nasal wash of infected individuals and the one likely responsible for much of the clinical symptoms [34] , [35] , [36] . Additional studies are required to assess the mechanism leading to increased IL-6 levels in animals infected with the H274Y NA mutant . As shown in some but not all studies [6] , [7] , [8] , our two pH1N1 isolates induced a strong pyrexic response ( increased in temperature of 2°C ) and slight weight loss ( 3–7% ) in ferrets . Interestingly , we noticed a biphasic temperature curve for both groups of ferrets . The first and major febrile peak correlated with maximum viral titers and the second minor increase in temperature seen on day 6 might be due to cytokine release . Similar biphasic temperature curves were also seen in ferrets infected with WT A/H5N1 viruses ( data not shown ) . Previous investigators have shown that both pH1N1 and seasonal A/H1N1 strains replicate to similar levels in the upper respiratory tract of ferrets but only the former could replicate to high levels in the lungs [6] , [7] , [8] . As for the comparison of the WT and mutant pH1N1 isolates , we found no significant difference in nasal wash viral titers of ferrets as determined at several time points but did not assess lung viral titers . Among the strengths of our study is the use of two clinical isolates from the same familial cluster that differed by a single a . a . and that were only passaged twice before animal studies . Also , the use of two different animal models to characterize the virulence of these strains and the relatively similar results observed in both of them reinforce our conclusions . A limitation of our study is the incomplete assessment of the transmissibility of our pH1N1 strains . Some groups have shown that the WT pH1N1 strain can be transmitted efficiently via aerosol or respiratory droplets [6] , [8] . We report here that the H274Y mutant could be transmitted by contact to uninfected ferrets but did not compare the efficiency of transmission with the WT strain and neither evaluated aerosol transmission . A confounder is the seropositive status of our ferrets for the seasonal A/Brisbane/59/2007 ( H1N1 ) strain before challenge with pH1N1 viruses . In guinea pigs , preexisting immunity to recent seasonal A/H1N1 viruses reduced viral load and transmission of pH1N1 [37] whereas a ferret study with the seasonal A/H1N1 vaccine showed little protection from challenge with pH1N1 [38] . Although preexisting antibody levels against an heterologous strain could have an effect on pathogenicity and transmission of pH1N1 , the geometrical mean antibody titers were similar for our two groups of ferrets , which should not change our conclusion about the relative pathogenicity of the H274Y mutant compared to the WT strain . Furthermore , we found similar results with the two strains in non-immune mice . Finally , our animal results may not be completely relevant to humans due to differences in distribution of HA cell receptors . In summary , although some slight differences were observed in the two animal models , we can conclude that the H274Y pH1N1 mutant seems as virulent as the WT isolate with no obvious impairment in viral fitness . Although reports of limited person-to-person transmission in several epidemiological settings have been observed [39] , currently no evidence of widespread dissemination of oseltamivir-resistant pH1N1 has been reported indicating the continued value of this drug for treatment of severe cases . Other H274Y pH1N1 mutants ( with different genetic backgrounds ) should be studied in terms of virulence and efficiency of transmission to confirm our conclusions . In the meantime , careful monitoring of the H274Y mutation during pH1N1 outbreaks is mandatory to rapidly identify transmission events that could lead to large-scale dissemination of an oseltamivir-resistant pH1N1 strain .
The two pH1N1 viruses that differed by only a single mutation in the NA gene were recovered from a family cluster of infection and passaged twice in ST6Gal I-expressing MDCK cells before testing . The two seasonal A/H1N1 viruses were collected in 2007 and passaged 3 times before testing . Susceptibility profiles of pandemic and seasonal influenza A/H1N1 strains as well as recombinant pH1N1 viruses against oseltamivir carboxylate ( Hoffmann La Roche , Basel , Switzerland ) , zanamivir ( GlaxoSmithKline , Stevenage , UK ) , peramivir ( BioCryst , Birmingham , AL ) and A-315675 ( Abbott Laboratories , North Chicago , IL ) were determined by NA inhibition assays using methylumbelliferyl-N-acetyl neuraminic acid ( MUNANA , Sigma , St . Louis , MO ) as a fluorescent substrate [40] . The eight segments of pandemic influenza A/H1N1 virus ( A/Quebec/141447/09 ) were amplified by RT-PCR and inserted into the recently-described bidirectional pLLB-A/G expression/translation plasmids by recombination in E . coli [41] . The pLLBA plasmid containing the NA segment was used in PCR-mediated site-directed mutagenesis kit ( Stratagene , La Jolla , CA ) for the introduction of the H274Y mutation . Plasmids were then used to cotransfect 293T cells for the rescue of recombinant viruses as previously described [42] . RNA was isolated directly from human nasopharyngeal aspirates or mouse lungs by using the QIAamp Viral RNA kit ( Qiagen , Mississauga , ON , Canada ) . Complementary DNA ( cDNA ) was synthesized by using 500 ng of the influenza specific Uni12 primer [43] and the SuperScript II reverse transcriptase ( GIBCO-BRL , Burlington , ON , Canada ) . Viral cDNA was used to amplify the eight influenza viral segments by PCR using the Pfu Turbo Polymerase ( Stratagene , La Jolla , CA ) and primers specific for each influenza gene [43] . PCR products were gel-purified and sequenced using an automated DNA sequencer ( ABI Prism 377 DNA sequencer , Applied Biosystems , Foster City , CA ) . For evaluation of viral quasispecies , cDNAs of the NA gene from the original clinical samples were cloned into the pJET vector ( Fermentas , Burlington , ON ) . Sixteen clones were sequenced to establish the ratios of WT and mutant populations within each clinical strain . ST6Gal I-expressing MDCK cells ( kindly provided by Dr . Y . Kawaoka , University of Wisconsin , WI ) [44] were infected at a multiplicity of infection ( MOI ) of 0 . 001 with pandemic or seasonal A/H1N1 viruses ( A/Brisbane/59/2007 ) containing or not the H274Y NA mutation . Supernatants were serially collected post-infection and assayed for numbers of PFUs using standard plaque assays . Six to eight week old female BALB/c mice ( Charles River , ON , Canada ) were used to evaluate weight loss as well as lung viral titers , cytokines transcript levels and histopathological changes following pH1N1 infection . Anesthetized mice were challenged by intranasal inoculation of 5×105 PFUs in 50 µl virus diluent ( Minimal Essential Media ( MEM ) , 0 . 3% Bovine Serum Albumin ( BSA ) , penicillin/streptomycin ) of the WT or H274Y mutant influenza virus isolate . After challenge , animals were weighed daily for 12 days and monitored for clinical signs . On days 1 , 3 , 6 and 9 post-infection ( days varied according to the experiment ) , 3 mice per group were sacrificed and lung tissue was placed into RNAlater ( Qiagen ) for RNA preservation and subsequent RNA extraction . Additional samples of fresh tissues were immediately frozen for viral isolation . All procedures were approved by the Institutional Animal Care Committee at the National Microbiology Laboratory ( NML ) of the Public Health Agency of Canada ( PHAC ) according to the guidelines of the Canadian Council on Animal Care . All infectious work was performed in biocontainment level 4 at the NML . Lung tissues were harvested during necropsies and homogenized in MEM/BSA using a bead mill homogenizer ( Tissue Lyser , Qiagen ) . Debris was pelleted by centrifugation ( 2 , 000 g , 5 min ) and 10-fold serial dilutions of supernatant were plated on MDCK cells with six replicates per dilution . At 72–96 h post-infection , the plates were scored for cytopathic effects ( CPE ) and the TCID50 virus titers were calculated using the method of Reed and Muench [45] . Tissues preserved in RNAlater were homogenized using a bead mill homogenizer and RNA was isolated using the RNeasy Mini Kit ( Qiagen ) . Pandemic H1N1 copy numbers were determined by Q-RT-PCR using the LightCycler 480 RNA Master Hydrolysis Probes ( Roche Diagnostics , Laval , QC ) assay targeting the hemagglutinin gene ( nt position 714–815 , GenBank number GQ160606 ) . Reaction conditions were the following: 63°C – 3 min , 95°C – 30 s and cycling of 95°C – 15 s , 60°C – 30 s for 45 cycles using a Lightcycler 480 ( Roche ) . The lower detection limit for this pH1N1 assay is 0 . 1 PFU/ml . The primer/probe sequences are as follow: HAForward– GGATCAAGAAGGGAGAATGAACTATT; HAReverse – AATGCATATCTCGGTACCACTAGATTT and HAProbe ( TET ) – CCGGGAGACAAAA-TAACATTCGAAGCAAC . For measuring cytokines expression on days 1 , 6 and 9 , extracted RNA was first analyzed with the RNA 6000 Nano LabChip and Bioanalyser ( Agilent , Switzerland ) . cDNA was prepared using RNA of standardized quality ( RIN>8 ) and quantity ( 3 . 68 µg of total RNA ) , the Superscript II RNase H ( Invitrogen , Burlington , ON , Canada ) and 250 ng of random primer hexamers ( Invitrogen ) . Equal amounts of cDNA were run in triplicate and amplified/detected using the Amplifluor UniPrimer system ( Applied Biosystem , Foster City , CA ) in which the forward or the reverse primers are tailed with the Z sequence 5′-ACTGAACCTGACCGTACA . The results were normalized based on amplification of an internal gene ( 18S ribosome ) and amounts of target gene were calculated according to a standard curve . The primer sequences for the cytokines/chemokines IL-4 , IL-5 , IL-6 , IL-10 , KC , MCP-1 , MIP-1α and IFN-γ are available upon request [46] . For lung histopathological studies , one pulmonary lobe was removed at serial times and fixed with 10% buffered formalin . Tissues were embedded in paraffin , sectioned in slices of 4 µm and stained with hematoxylin-eosin . The histopathological scores ( HPS ) were determined by two independent pathologists with experience in pulmonary pathology who were unaware of the infection status of the animals . A semi-quantitative scale was used to score bronchial/endobronchial , peribronchial , perivascular , interstitial , pleural and intra-alveolar inflammation [47] . Capillary vascular congestion and pulmonary edema were also evaluated using a semi-quantitative scale and the inflammatory cellular infiltrate was characterized to determine if the inflammation was acute ( neutrophilic ) or chronic ( lymphohistiocytic ) . Groups of five male ferrets ( 900–1500 g ) ( Triple F Farms , Sayre , PA ) were lightly anesthetized by isoflurane and received by intranasal instillation 250 µl ( 125 µl/nare ) of PBS containing 4 . 5log TCID50/ml of pH1N1 viruses with or without the H274Y NA mutation . Telemetric transmitters ( DST micro-T , Star-Oddi , Iceland ) were subcutaneously implanted and temperature profiles of ferrets were recorded every 15 min starting 2 days prior and up to 14 days post-inoculation . Ferrets were weighed daily and nasal wash samples were collected from animals on a daily basis during 14 days post-inoculation by instillation of 5 ml of PBS into the external nares of the animals . The work was performed in biocontainment level 2+ according to procedures approved by the Institutional Animal Care Committee of Armand Frapier Institute . Virus titers were determined by standard plaque assays using ST6Gal I-expressing MDCK cells . In addition , serum was also collected from each ferret before intranasal infection and on day 14 post-infection to evaluate specific antibody levels against the pH1N1 A/California/07/2009 and the seasonal A/Brisbane/59/2007 strains using standard hemagglutination inhibition assays . For transcripts analysis of IL-2 , IL-6 , IL-12 and IFN-γ on day 14 post-infection , RNA was isolated from retropharyngeal lymph nodes using the RNAqueous Micro ( Ambion , Streetsville , Ontario ) and cDNA was generated with the Transcriptor First Strand cDNA Synthesis Kit ( Roche ) . Amplification of cytokine cDNA was performed as previously described [48] . The results were normalized based on amplification of an internal gene ( GAPDH ) . Five male ferrets ( 900–1500 g ) ( Triple F Farms , Sayre , PA ) were lightly anesthetized by isoflurane and received by intranasal instillation 250 µl ( 125 µl/nare ) of PBS containing 4 . 5log TCID50/ml of pH1N1 virus with the H274Y NA mutation . Each ferret was placed individually in a cage . Approximately 24 h following viral infection , inoculated-contact animal pairs were established by placing a naïve ferret into each cage allowing the exchange of respiratory droplets by direct contact . Inoculated and contact animals were monitored for clinical signs and nasal wash samples were collected for viral titers every day over a 14-day period . Serum was also collected from each ferret before intranasal infection and on day 14 post-infection to evaluate specific antibody levels against the pH1N1 A/California/07/2009 virus using standard hemagglutination inhibition assays . All ferrets were seronegative for pH1N1 A/California/07/2009 before intranasal infection . Paired and unpaired t test analyses were done to compare the mutant and WT virus characteristics during in vitro and in vivo studies , respectively . | During the 2009 pandemic of the novel A/H1N1 ( pH1N1 ) virus , the World Health Organization recommended oseltamivir as first-line agent for treatment of patients with severe infections leading to hospitalization and for those with underlying diseases predisposing to pulmonary complications . Oseltamivir-resistant isolates started to emerge at the end of June 2009 with now more than 100 strains reported worldwide including a few outbreaks where transmission of resistant viruses may have occurred . We characterized the fitness of a pair of oseltamivir-susceptible and oseltamivir-resistant strains emerging from the same familial cluster and that differed by only a single change ( H274Y ) in the neuraminidase protein . We found that the drug-resistant ( mutant ) virus was at least as virulent as the drug-susceptible ( wild-type ) virus in mice and ferrets . Based on these data , we believe that the H274Y pH1N1 mutant strain has the potential to disseminate in the population and to eventually replace the susceptible strain , a phenomenon that has been already observed with seasonal A/Brisbane/59/2007-like ( H1N1 ) viruses . | [
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] | 2010 | Oseltamivir-Resistant Pandemic A/H1N1 Virus Is as Virulent as Its Wild-Type Counterpart in Mice and Ferrets |
Simultaneous electrical stimulation and recording using multi-electrode arrays can provide a valuable technique for studying circuit connectivity and engineering neural interfaces . However , interpreting these measurements is challenging because the spike sorting process ( identifying and segregating action potentials arising from different neurons ) is greatly complicated by electrical stimulation artifacts across the array , which can exhibit complex and nonlinear waveforms , and overlap temporarily with evoked spikes . Here we develop a scalable algorithm based on a structured Gaussian Process model to estimate the artifact and identify evoked spikes . The effectiveness of our methods is demonstrated in both real and simulated 512-electrode recordings in the peripheral primate retina with single-electrode and several types of multi-electrode stimulation . We establish small error rates in the identification of evoked spikes , with a computational complexity that is compatible with real-time data analysis . This technology may be helpful in the design of future high-resolution sensory prostheses based on tailored stimulation ( e . g . , retinal prostheses ) , and for closed-loop neural stimulation at a much larger scale than currently possible .
Simultaneous electrical stimulation and recording with multi-electrode arrays ( MEAs ) serves at least two important purposes for investigating neural circuits and for neural engineering . First , it enables the probing of neural circuits , leading to improved understanding of circuit anatomy and function [1–6] . Second , it can be used to assess and optimize the performance of brain-machine interfaces , such as retinal prostheses [7 , 8] , by exploring the patterns of stimulation required to achieve particular patterns of neural activity . However , identifying neural activity in the presence of artifacts introduced by electrical stimulation is a major challenge , and automation is required to efficiently analyze recordings from large-scale MEAs . Furthermore , closed-loop experiments require the ability to assess neural responses to stimulation in real time to actively update the stimulus and probe the circuit , so the automated approach for identifying neural activity must be fast [9 , 10] . Spike sorting methods [11–13] allow identification of neurons from their spatio-temporal electrical footprints recorded on the MEA . However , these methods fail when used on data corrupted by stimulation artifacts . Although technological advances in stimulation circuitry have enabled recording with significantly reduced artifacts [14–18] , identification of neural responses from artifact-corrupted recordings still presents a challenging task—even for human experts—since these artifacts can be much larger than spikes [19] , overlap temporally with spikes , and occupy a similar temporal frequency band as spikes . Although a number of approaches have been previously proposed to tackle this problem [20–23] , there are two shortcomings we address here . First , previous approaches are based on restrictive assumptions on the frequency of spikes and their latency distribution ( e . g , stimulation-elicited spikes have to occur at least 2ms following stimulus onset ) . Consequently , it becomes necessary to discard non-negligible portions of the recordings [19 , 24] , leading to biased results that may miss the low-latency regimes where the most interesting neuronal dynamics occur [25 , 26] . Second , all of these methods have a local nature , i . e . , they are based on electrode-wise estimates of the artifact that don’t exploit the shared spatio-temporal information present in MEAs . In general this leads to suboptimal performance . Therefore , a scalable computational infrastructure for spike sorting with stimulation artifacts in large-scale setups is necessary . This paper presents a method to idesectionntify single-unit spike events in electrical stimulation and recording experiments using large-scale MEAs . We develop a modern , large-scale , principled framework for the analysis of neural voltage recordings that have been corrupted by stimulation artifacts . First , we model this highly structured artifact using a structured Gaussian Process ( GP ) to represent the observed variability across stimulation amplitudes and in the spatial and temporal dimensions measured on the MEA . Next , we introduce a spike detection algorithm that leverages the structure imposed in the GP to achieve a fast and scalable implementation . Importantly , our algorithm exploits many characteristics that make this problem tractable , allowing it to separate the contributions of artifact and neural activity to the observed data . For example , the artifact is smooth in certain dimensions , with spatial footprints that are different than those of spikes . Also , artifact variability is different than that of spikes: while the artifact does not substantially change if the same stimulus is repeated , responses of neurons in many stimulation regimes are stochastic , enhancing identifiability . The effectiveness of our method is demonstrated by comparison on simulated data and against human-curated inferred spikes extracted from real data recorded in primate retina . Although some features of our method are context-dependent , we discuss extensions to other scenarios , stressing the generality of our approach .
All experiments were performed in accordance with IACUC guidelines for the care and use of animals . The research was approved on 2016-08-18 and the assurance number is A3213-01 . In this section we develop a method for identifying neural activity in response to electrical stimulation . We assume access to voltage recordings Y ( e , t , j , i ) in a MEA with e = 1 , … , E electrodes ( here , E = 512 ) , during t = 1 , … T timepoints ( e . g . , T = 40 , corresponding to 2 milliseconds for a 20Khz sampling rate ) after the presentation of j = 1 , … , J different stimuli , each of them being a current pulse of increasing amplitudes aj ( in other words , the aj are magnification factors applied to an unitary pulse ) . For each of these stimuli nj trials or repetitions are available; i indexes trials . Each recorded data segment is modeled as a sum of the true signal of interest s ( neural spiking activity on that electrode ) , plus two types of noise . The first noise source , A , is the large artifact that results from the electrical stimulation at a given electrode . This artifact has a well defined structure but its exact form in any given stimulus condition is not known a priori and must be estimated from the data and separated from occurrences of spikes . Although in typical experimental setups one will be concerned with data coming from many different stimulating electrodes , for clarity we start with the case of just a single stimulating electrode; we will generalize this below . The second source of noise , ϵ , is additive spherical Gaussian observation noise; that is , ϵ ∼ N ( 0 , σ 2 I d ′ ) , with d ′ = T × E × ∑ j = 1 J n j . This assumption is rather restrictive and we assume it here for computational ease , but refer the reader to the discussion for a more general formulation that takes into account correlated noise . Additionally , we assume that electrical images ( EI ) [27 , 28]—the spatio-temporal collection of action potential shapes on every electrode e—are available for all the N neurons under study . In detail , each of these EIs are estimates of the voltage deflections produced by a spike over the array in a time window of length T′ . They are represented as matrices with dimensions E × T′ and can be obtained in the absence of electrical stimulation , using standard large-scale spike sorting methods ( e . g . [12] ) . Fig 1 shows examples of many EIs , or templates , obtained during a visual stimulation experiment . Finally , we assume the observed traces are the linear sum of neural activity , artifact , and other noise sources; that is: Y = A + s + ϵ . ( 1 ) Similar linear decompositions have been recently utilized to tackle related neuroscience problems [12 , 29] . Fig 2 illustrates the difficulty of this problem: even if 1 ) for low-amplitude stimuli the artifact may not heavily corrupt the recorded traces and 2 ) the availability of several trials can enhance identifiability—as traces with spikes and no spikes naturally cluster into different groups—in the general case we will be concerned also with high amplitudes of stimulation . In these regimes , spikes could significantly overlap temporarily with the artifact , and occur with high probability and almost deterministically , i . e . , with low latency variability . For example , in the rightmost columns of Fig 2 , spike identification is not straightforward since all the traces look alike , and the shape of a typical trace does not necessarily suggest the presence of neural activity . There , inference of neural activity is only possible given a reasonable estimate of the artifact: for instance , under the assumption that the artifact is a smooth function of the stimulus strength , one can make a good initial guess of the artifact by considering the artifact at a lower stimulation amplitude , where spike identification is relatively easier . Therefore , a solution to this problem will rely on a method for an appropriate separation of neural activity and artifact , which in turn requires the use of sensible models that properly capture the structure of the latter; that is , how it varies along the different relevant dimensions . In the following we develop such a method , and divide its exposition in five parts . We start by describing how to model neural activity . Second , we describe the structure of the stimulation artifacts . Third , we propose a GP model to represent this structure . Fourth , we introduce a scalable algorithm that produces an estimate of A and s given recordings Y . Finally , we provide a simplified version of our method and extend it to address multi-electrode stimulation scenarios . We assume that s is the linear superposition of the activities sn of the N neurons involved , i . e . s = ∑ n = 1 N s n . Furthermore , each of these activities is expressed in terms of the binary vectors bn that indicate spike occurrence and timing: specifically , if s j , i n is the neural activity of neuron n at trial i of the j-th stimulation amplitude , we write s j , i n = M n b j , i n , where Mn is a matrix that contains on each row a copy of the EI of neuron n ( vectorizing over different electrodes ) aligned to spiking occurring at different times . Notice that this binary representation immediately entails that: 1 ) on each trial each neuron fires at most once ( this will be the case if we choose analysis time windows that are shorter than the refractory period ) and 2 ) that spikes can only occur over a discrete set of times ( a strict subset of the entire recording window ) , which here corresponds to all the time samples between 0 . 25 ms and 1 . 5 ms . We refer the reader to [30] for details on how to relax this simplifying assumption . Electrical stimulation experiments where neural responses are inhibited ( e . g . , using the neurotoxin TTX ) provide qualitative insights about the structure of the stimulation artifact A ( e , t , j , i ) ( Fig 3 ) ; that is , how it varies as a function of all the relevant covariates: space ( represented by electrode , e ) , time t , amplitude of stimulus aj , and stimulus repetition i . Repeating the same stimulation leads to the same artifact , up to small random fluctuations , and so by averaging several trials these fluctuations can be reduced , and we can conceive the artifact as a stack of movies A ( e , t , j ) , one for each amplitude of stimulation aj . We treat the stimulating and non-stimulating electrodes separately because of their observed different qualitative properties . From the above discussion we conclude that the artifact is highly non-linear ( on each coordinate ) , non-stationary ( i . e . , the variability depends on the value of each coordinate ) , but structured . The Gaussian process ( GP ) framework [31] provides powerful and computationally scalable methods for modeling non-linear functions given noisy measurements , and leads to a straightforward implementation of all the usual operations that are relevant for our purposes ( e . g . extrapolation and filtering ) in terms of some tractable conditional Gaussian distributions . To better understand the rationale guiding the choice of GPs , consider first a simple Bayesian regression model for the artifact as a noisy linear combination of B basis functions Φb ( e , t , j ) ( e . g . polynomials ) ; that is , A ( e , t , j ) = ∑ b = 1 B w b Φ b ( e , t , j ) + ϵ , with a regularizing prior p ( w ) on the weights . If p ( w ) and ϵ are modeled as Gaussian , and if we consider the collection of A ( e , t , j ) values ( over all electrodes e , timesteps t , and stimulus amplitude indices j ) as one large vector A , then this translates into an assumption that the vector A is drawn from a high-dimensional Gaussian distribution . The prior mean μ and covariance K of A can easily be computed in terms of Φ and p ( w ) . Importantly , this simple model provides us with tools to estimate the posterior distribution of A given partial noisy observations ( for example , we could estimate the posterior of A at a certain electrode if we are given its values on the rest of the array ) . Since A in this model is a stochastic process ( indexed by e , t , and j ) with a Gaussian distribution , we say that A is modeled as a Gaussian process , and write A ∼ GP ( μ , K ) . The main problem with the approach sketched above is that one has to solve some challenging model selection problems: what basis functions Φi should we choose , how large should M be , what parameters should we use for the prior p ( w ) , and so on . We can avoid these issues by instead directly specifying the covariance K and mean μ ( instead of specifying K and μ indirectly , through p ( w ) , Φ , etc . ) . The parameter μ informs us about the mean behavior of the samples from the GP ( here , the average values of the artifact ) . Briefly , we estimate μ ^ by taking the mean of the recordings at the lowest stimulation amplitude and then subtract off that value from all the traces , so that μ can be assumed to be zero in the following . We refer the reader to S1 Text and S1 Fig for details , and stress that all the figures shown in the main text are made after applying this mean-subtraction pre-processing operation . Next we need to specify K . This “kernel” can be thought of as a square matrix of size dim ( A ) × dim ( A ) , where dim ( A ) is as large as T × E × J ∼ 106 in our context . This number is large enough so all elementary operations ( e . g . kernel inversion ) are prohibitively slow unless further structure is imposed on K—indeed , we need to avoid even storing K in memory , and estimating such a high-dimensional object is impossible without some kind of strong regularization . Thus , instead of specifying every single entry of K we need to exploit a simpler , lower-dimensional model that is flexible enough to enforce the qualitative structure on A that we described in the preceding section . Specifically , we impose a separable Kronecker product structure on K , leading to tractable and scalable inferences [32 , 33] . This Kronecker product is defined for any two matrices as ( A ⊗ B ) ( ( i1 , i2 ) , ( j1 , j2 ) ) = A ( i1 , j1 ) B ( i2 , j2 ) . The key point is that this Kronecker structure allows us to break the huge matrix K into smaller , more tractable pieces whose properties can be easily specified and matched to the observed data . The result is a much lower-dimensional representation of K that serves to strongly regularize our estimate of this very high-dimensional object . In S2 Text we review the main operations from [34] that enable computational speed-ups due to this Kronecker product representation We state separate Kronecker decompositions for the non-stimulating and stimulating electrodes . For the non-stimulating electrode we assume the following decomposition: K = ρ K t ⊗ K e ⊗ K s + ϕ 2 I T × E × J , ( 2 ) where Kt , Ke , and Ks are the kernels that account for variations in the time , space , and stimulus magnitude dimensions of the data , respectively . One way to think about the Kronecker product Kt ⊗ Ke ⊗ Ks is as follows: to draw a sample from a GP with mean zero and covariance Kt ⊗ Ke ⊗ Ks , start with an array z ( t , e , s ) filled with independent standard normal random variables , then apply independent linear filters in each direction t , e , and s so that the marginal covariances in each direction correspond to Kt , Ke , and Ks , respectively . The dimensionless quantity ρ is used to control the overall magnitude of variability and the scaled identity matrix ϕ2Idim ( A ) is included to allow for slight unstructured deviations from the Kronecker structure . Notice that we distinguish between this extra prior variance ϕ2 and the observation noise variance σ2 , associated with the error term ϵ of Eq 1 . Likewise , for the stimulating electrode we consider the kernel: K ′ = ∑ r = 1 R ρ r K t r ⊗ K s r + ϕ ′ 2 I T × J . ( 3 ) Here , the sum goes over the stimulation ranges defined by consecutive breakpoints; and for each of those ranges , the kernel K s r has non-zero off-diagonal entries only for the stimulation values within the r-th range between breakpoints . In this way , we ensure artifact information is not shared for stimulus amplitudes across breakpoints . Finally , ρ′ and ϕ′ play a similar role as in Eq 2 . Now that this structured kernel has been stated it remains to specify parametric families for the elementary kernels Kt , Ke , Ks , K t r , K s r . We construct these from the Matérn family , using extra parameters to account for the behaviors described in Stimulation artifacts . Now we introduce an algorithm for the joint estimation of A and s , based on the GP model for A . Roughly , the algorithm is divided in two stages: first , the hyperparameters that govern the structure of A have to be found . After , given the inferred hyperparameters we perform the actual inference of A , s given these hyperparameters . We base our approach on posterior inference for p ( A , s|Y , θ , σ2 ) ∝ p ( Y|s , A , σ2 ) p ( A|θ ) , where the first factor in the right hand side is the likelihood of the observed data Y given s , A , and the noise variance σ2 , and the second stands for the noise-free artifact prior; A ∼ GP ( 0 , Kθ ) . A summary of all the involved operations is shown in pseudo-code in algorithm 1 . Algorithm 1 Spike detection and Artifact cancellation with electrical stimulation Input: Traces Y = ( Yj ) j = 1 , … , J , in response to J stimuli . Output: Estimates of artifact A ^ and neural activity s ^ n for each neuron . EIs of N neurons ( e . g . obtained in a visual stimulation experiment ) . Initialization 1: Estimate ϕ2 ( artifact noise ) and θ . ▹ Hyperparameter estimation , Eq ( 7 ) 2: Also , estimate σ2 ( neural noise ) from traces . Artifact/neural activity inference via coordinate ascent and extrapolation 3: for j = 1 , … J do 4: Estimate A j 0 from A[j−1] ( A 1 0 ≡ 0 ) . ▹ Extrapolation , Eq ( 11 ) 5: while some s ^ j , i n change from one iteration to the next do ▹ Coordinate ascent 6: • Estimate s ^ j , i n ( for each i , n ) greedily . ▹ Matching pursuit , Eq ( 9 ) 7: until no spike addition increases the likelihood . 8: • Estimate A ^ j from residuals Y j - ∑ n = 1 N s j n . ▹ Artifact filtering , Eq ( 10 ) . 9: end while 10: end for
We validated the algorithm by measuring its performance both on a large dataset with available human-curated spike sorting and with ground-truth simulated data ( we avoid the term ground-truth in the real data to acknowledge the possibility that the human makes mistakes ) . A prominent application of our method relates to the development of high-resolution neural prostheses ( particularly , epi-retinal prosthesis ) , whose success will rely on the ability to elicit arbitrary patterns of neural activity through the selective activation of individual neurons in real-time [28 , 39 , 40] . For achieving such selective activation in a closed-loop setup , we need to know how different stimulating electrodes activate nearby neurons , information that is easily summarized by the activation curves , with the activation thresholds themselves as proxies . Unfortunately , obtaining this information in real time—as required for prosthetic devices—is currently not feasible since estimation of thresholds requires the analysis of individual responses to stimuli . In Online data analysis we discuss in detail how , within our framework , to overcome the stringent time limitations required for such purposes . Figs 9 , 10 , 11 and 12 show pictorial representations of different features of the results obtained with the algorithm , and their comparison with human annotation . Axonal reconstructions from all of the neurons in the figures were achieved through a polynomial fit to the neuron’s spatial EI , with soma size depending on the EI strength ( see [28] for details ) . Each of these figures provides particular insights to inform and guide the large-scale closed-loop control of the neural population . Importantly , generation of these maps took only minutes on a personal computer , compared to many human hours , indicating feasibility for clinical applications and substantial value for analysis of laboratory experiments [28 , 40] . Fig 9 focuses on the stimulating electrode’s point of view: given stimulation in one electrode , it is of interest to understand which neurons will get activated within the stimulation range , and how selective that activation can be made . This information is provided by the activation curves , i . e , their steepness and their associated stimulation thresholds . Additionally , latencies can be informative about the spatial arrangement of the system under study , and the mode of neural activation: in this example , one cell is activated through direct stimulation of the soma , and the other , more distant cell is activated through the indirect and antidromic propagation of current through the axon [41] . This is confirmed by the observed latency pattern . Fig 10 depicts the converse view , focusing on the neuron . Here we aim to determine the cell’s electrical receptive field [37 , 42] to single-electrode stimulation; that is , the set of electrodes that are able to elicit activation , and in the positive cases , the corresponding stimulation thresholds . These fields are crucial for tailoring stimuli that selectively activate sub-populations of neurons . Fig 11 shows how the algorithm enables the analysis of responses to bipolar stimulation . This strategy has been suggested to enhance selectivity [43] , by differentially shifting the stimulation thresholds of the cells so the range of currents that lead to activation of a single cell is widened . More generally , multi-electrode spatial stimulation patterns have the potential to enhance selectivity by producing an electric field optimized for activating one cell more strongly than others [28] , and Fig 11 is a depiction of how our algorithm permits an accurate assessment of this potential enhancement . Finally , Fig 12 shows a large-scale summary of the responses to single-electrode stimulation . There , a population of ON and OFF parasol cells was stimulated at many different electrodes close to their somas , and each of those cells was then labeled by the lowest achieved activation threshold . These maps provide a proxy of the ability to activate cells with single-electrode stimulation , and of the different degrees of difficulty in achieving activation . Since in many cases only as few as 20% of the neurons can be activated [44] , the information about which cells were activated can provide a useful guide for the on-line development of more complex multiple electrode stimulation patterns that activate the remaining cells .
Figs 6B , 7B and 8C , and S3 Fig illustrate some cases where the full kernel-based estimator outperforms the simplified artifact estimator . These cases correspond to heavy sub-sampling or small signal-to-noise ratios , where the data do not adequately constrain simple estimators of the artifact and the full Bayesian approach can exploit the structure in the problem to obtain significant improvements . In closed-loop experiments ( discussed below in Online data analysis ) experimental time is limited , and the ability to analyze fewer trials without loss of accuracy opens up the possibility for new experimental designs that may not have been otherwise feasible . That said , it is useful to note that simplified estimators are available and accurate in regimes of high SNR and where many trials are available . We showed that our method strongly outperforms the simple proposal by [20] . Although this competing method was successful on its intended application , here it breaks down since neural activity tends to appear rather deterministically ( i . e . , spikes occur with very high probability and have low variability in time across trials ) for stimuli of high amplitude . This phenomenon is documented in S5 , and can be also observed in Fig 2 ( see traces in responses to the strongest stimulus ) . As a consequence , the mean-of-traces estimator of the artifact also contains the neural activity that is being sought , leading to a dramatic failure in detecting spikes , explaining the high false negative rate . Two other prominent artifact cancellation methods exist , but neither applies directly to our context . The method of [22] considers high-frequency stimulation ( 5khz ) . In that context , since action potentials follow a much larger time course than of this very short latency artifact , it is relatively easy to cancel the artifact and recover neural activity by linearly interpolating the recordings whenever stimulation occurs . However , here , as seen in Fig 2 , the artifact’s time course can be larger than of spikes ( especially at the stimulating electrode ) . Additionally , the method of [21] has guarantees of success only for latencies greater than 2ms after the onset of stimulus , much larger than the ones addressed here ( as small as 0 . 3 ms ) . Their 2ms threshold comes from the observation that it is at that time when spikes and artifacts become spectrally separable . However , in our case , at smaller latencies the artifact has a highly transient nature and there is much diversity of artifact shapes ( Fig 3 ) for different electrodes and pulse amplitudes . This immediately excludes the possibility of considering an algorithm based on the spectral differentiation between the spikes and the artifacts in the low-latency context we care about . The present findings open a real possibility for the development of closed-loop experiments to achieve selective activation of neurons , [10 , 45] featuring online data analysis at a much larger scale scale than was previously possible . We briefly discuss a hypothetical pipeline for a closed loop-experiment , involving four steps: i ) visual stimulation and subsequent spike sorting to identify neurons and their EIs; ii ) single-electrode stimulation scans to map the excitability of those neurons with respect to each of the electrodes in the MEA; iii ) additional multi-electrode stimulation to further explore ways to activate cells ( optional ) ; and iv ) computation of optimal stimulation patterns to match a desired spike train . Step ( iii ) might be helpful to enhance combinatorial richness ( i . e . the number of ways in which ways neurons can be stimulated ) if the available stimulus space resulting from single-electrode stimulation does not lead to a complete selective activation of neurons ( in the retina , this will often be the case [44] ) . There is a caveat , though: allowing for arbitrary stimulation patterns is not possible without further assumptions , since the number of possible amplitude series , i . e . , sequences of multi-dimensional stimuli with increasing amplitude , increases exponentially with the number of stimulating electrodes . We propose two solutions: 1 ) focus on patterns for which there is a clear underlying biophysical interpretation in terms of interactions between the neural tissue and the applied electrical field ( e . g . , the bipolar and local return stimulation patterns explored here ) so that the number of patterns remains bounded , and 2 ) relax the amplitude series assumption; i . e . allows modes of data collection where recordings are not in response to a sequence of stimulus with increasing strength . This would be possible if artifacts obeyed linear superposition ( i . e . the artifact to arbitrary stimulation breaks down into the linear sum of the individual artifacts ) , since then we would simply need to save the artifacts to single electrode stimulation , and subtract them as required from traces to arbitrary stimuli . In S6 we provide some elementary evidence that supports this linear superposition hypothesis in the simplest , two-electrode stimulation case . However , we stress that further research is required to establish artifact linearity more generally . Here we comment on the current limitations of our method while suggesting some possible extensions . We have developed a method to automate spike sorting in electrical stimulation experiments using large MEAs , where artifacts are a concern . We believe our developments will be useful to enable closed-loop neural stimulation at a much larger scale than was previously possible , and to enhance the ability to actively control neural activity . Also , our algorithm has the potential to constitute an important computational substrate for the development of future neural prostheses , particularly epi-retinal prostheses . We have made available , in the first author’s website , MATLAB code that contains an example applying the algorithm to process one of the datasets analyzed in this paper . | Simultaneous electrical stimulation and recording using multi-electrode arrays can provide a valuable technique for studying circuit connectivity and engineering neural interfaces . However , interpreting these recordings is challenging because the spike sorting process ( identifying and segregating action potentials arising from different neurons ) is largely stymied by electrical stimulation artifacts across the array , which are typically larger than the signals of interest . We develop a novel computational framework to estimate and subtract away this contaminating artifact , enabling the large-scale analysis of responses of possibly hundreds of cells to tailored stimulation . Importantly , we suggest that this technology may also be helpful for the development of future high-resolution neural prosthetic devices ( e . g . , retinal prostheses ) . | [
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"mod... | 2017 | Electrical stimulus artifact cancellation and neural spike detection on large multi-electrode arrays |
Many cells in mammals exist in the state of quiescence , which is characterized by reversible exit from the cell cycle . Quiescent cells are widely reported to exhibit reduced size , nucleotide synthesis , and metabolic activity . Much lower glycolytic rates have been reported in quiescent compared with proliferating lymphocytes . In contrast , we show here that primary human fibroblasts continue to exhibit high metabolic rates when induced into quiescence via contact inhibition . By monitoring isotope labeling through metabolic pathways and quantitatively identifying fluxes from the data , we show that contact-inhibited fibroblasts utilize glucose in all branches of central carbon metabolism at rates similar to those of proliferating cells , with greater overflow flux from the pentose phosphate pathway back to glycolysis . Inhibition of the pentose phosphate pathway resulted in apoptosis preferentially in quiescent fibroblasts . By feeding the cells labeled glutamine , we also detected a “backwards” flux in the tricarboxylic acid cycle from α-ketoglutarate to citrate that was enhanced in contact-inhibited fibroblasts; this flux likely contributes to shuttling of NADPH from the mitochondrion to cytosol for redox defense or fatty acid synthesis . The high metabolic activity of the fibroblasts was directed in part toward breakdown and resynthesis of protein and lipid , and in part toward excretion of extracellular matrix proteins . Thus , reduced metabolic activity is not a hallmark of the quiescent state . Quiescent fibroblasts , relieved of the biosynthetic requirements associated with generating progeny , direct their metabolic activity to preservation of self integrity and alternative functions beneficial to the organism as a whole .
Proliferating and quiescent cells are expected to have vastly different metabolic needs . Proliferating cells must replicate the entirety of their cellular contents in order to divide . As a result , much of the metabolic energy in a proliferating cell is devoted to synthesizing DNA , proteins , and lipids . Quiescent cells are relieved of this massive metabolic requirement since they are not dividing and , in several well-studied model systems , they decrease their metabolic rates in accordance with their decreased proliferation rates . Yeast cultures , for instance , enter stationary phase when liquid cultures are grown to saturation in rich medium [1] . Within this population , the quiescent yeast cells fail to accumulate mass and volume [2] , in part because quiescent yeast cells induce autophagy , or self-cannibalism [3] . In addition , the overall transcription rate is three to five times slower in stationary-phase than in logarithmic-phase cultures [4] , and protein synthesis is reduced to approximately 0 . 3% of the rate in logarithmically growing cultures [5] . Therefore , the quiescent cells within a stationary-phase culture of yeast likely represent an example of a quiescent cell that has significantly reduced its metabolic activity . Lymphocytes also undergo a major metabolic shift upon transitioning between proliferation and quiescence . Early studies showed that lectin stimulation of lymphocytes led to increased glucose uptake , and an increased rate of glycolysis and pentose phosphate pathway ( PPP ) activities [6] , [7] . More recent experiments have focused on a murine pro-B cell lymphoid cell line , FL5 . 12 , that proliferates in response to the cytokine interleukin IL-3 [8] . IL-3 stimulation results in an 8-fold increased glycolytic flux . IL-3 also induces the cells to consume less oxygen per glucose consumed , and to excrete much more lactate , indicating a shift away from oxidative toward glycolytic metabolism . For human peripheral blood T lymphocytes , stimulation resulted in a 30-fold increase in glycolysis [9]; for thymocytes , the increase was 50-fold [10] . These differences in quiescent and proliferating lymphocytes have played a pivotal role in our understanding of the quiescent state , and experiments with lymphocytes as a model system have been important contributors to the development of the idea that quiescence is characterized by decreased metabolic activity . Lymphocytes , however , are relatively unique among mammalian cells in having primarily a “watching and waiting” function when quiescent and performing much of their physiological role only after activation . Our studies focus on newborn dermal fibroblasts as a model system of quiescence [11]–[13] . In vitro , primary fibroblasts isolated directly from newborn foreskin can be induced into reversible quiescence by serum withdrawal or contact inhibition . Unlike most primary cells , fibroblasts remain healthy in culture in a quiescent state for as long as 30 d with little apoptosis or senescence , and can then re-enter the cell cycle [13] . In vivo , quiescent fibroblasts are central to normal physiology as the primary synthesizers of extracellular matrix necessary for the formation of cellular tissues . In response to a wound , fibroblasts enter the cell cycle from quiescence , proliferate , and secrete a collagen-rich extracellular matrix [14] , pro-angiogenesis factors that recruit new blood vessels [13] , and other molecules that facilitate the wound healing response [15] . A better understanding of the transition between proliferation and quiescence in fibroblasts would have broad implications for physiology and medicine . Scarring and fibrosis result from excessive fibroblast proliferation and secretion of extracellular matrix during and after wound healing [16] , [17] . Additionally , tumors may contain quiescent cells that contribute to cancer dormancy [18] , [19] . Thus , a better understanding of the transition between proliferation and quiescence , including the metabolic changes that occur , could have implications for a wide range of medical conditions . The emerging field of metabolomics promises to augment our understanding of mammalian cell physiology through the systems-level characterization of cell-wide metabolite concentrations and fluxes . Using liquid chromatography–triple quadrupole mass spectrometry , we have developed a methodology for monitoring the pool size and turnover of a large number of metabolites simultaneously [20]–[22] . Here we apply metabolomic technology , flux analysis , and biochemical assays to investigate metabolic changes after primary dermal fibroblasts enter quiescence . We discovered that contact-inhibited primary fibroblasts remain highly metabolically active while adjusting their metabolic emphasis to produce NADPH , steadily renew their proteins and lipids , and enhance secretion of specific extracellular matrix proteins .
We have developed a model system that allows us to monitor metabolic differences between proliferating and quiescent cells . Primary dermal fibroblasts were expanded and analyzed while actively proliferating , after 1 wk of growth to confluence ( contact-inhibited for 7 d [CI7] ) , after 2 wk of confluence ( contact-inhibited for 14 d [CI14] ) , or after 2 wk of confluence with serum concentrations decreased for the final week from 10% to 0 . 1% ( contact-inhibited for 14 d and serum-starved for 7 d [CI14SS7] ) . Alternatively , fibroblasts were plated sparsely so that they did not touch each other and induced into quiescence by serum starvation and monitored after 4 d ( serum-starved for 4 d [SS4] ) or 7 d ( serum-starved for 7 d [SS7] ) . In quiescent fibroblasts , the fraction of cells with 2N DNA content increased so that 80% or more of the cells were in the G0/G1 phase of the cell cycle ( Figure 1A ) . The fraction of cells in S phase was significantly reduced , indicating that very few cells were actively dividing under these conditions . In both contact-inhibited and serum-starved fibroblasts , levels of the cyclin-dependent kinase inhibitor p27Kip1 were upregulated , as expected for cells that entered quiescence ( Figure 1B ) [23] . In addition , staining with pyronin Y for total RNA indicated that the fraction of cells with low pyronin Y , interpreted as cells in G0 [24] , increased in fibroblasts induced into quiescence by all of these methods ( Figure 1C ) . Pyronin Y labeling data indicate that in the contact-inhibited and serum-starved cell populations investigated as quiescence models , approximately 60%–75% of the cells are in G0 and most of the remainder are in G1 . Previous studies have reported that lymphocytes induced to exit the cell cycle in response to mitogen withdrawal exhibit decreased glycolytic activity [8] . We used several methods to assess metabolic rates in proliferating , CI7 , CI14 , and CI14SS7 cells . We monitored the rates at which glucose and glutamine were consumed from the medium , and lactate and glutamate were secreted into the medium . As shown in Figure 2A , the rate of glucose consumption was approximately 2-fold lower in the contact-inhibited than in the proliferating fibroblasts . Lactate secretion decreased less than 2-fold with contact inhibition alone , and roughly 2-fold with additional serum deprivation . Glucose consumption actually slightly increased in fibroblasts induced into quiescence by serum starvation ( without contact inhibition ) for 4 or 7 d ( Figure S1 ) . We also monitored metabolic rates in fibroblasts cultured in medium conditions containing physiological levels of glucose and glutamine ( 1 g/l glucose and 0 . 7 mM glutamine compared with 4 . 5 g/l glucose and 4 mM glutamine in Dulbecco's Modified Eagle Medium [DMEM] ) [25] , [26] . Metabolic rates were somewhat lower in proliferating fibroblasts in these low glucose/low glutamine conditions compared with proliferating fibroblasts in standard medium ( Figure S1 ) . Quiescent fibroblasts cultured in these conditions exhibited consumption and excretion rates approximately half that of proliferating fibroblasts . Our finding that glycolytic rates are similar within a factor of two in proliferating and quiescent fibroblasts is surprising given that changes in glycolytic rate have been shown to mirror changes in proliferative rate in multiple model systems [8]–[10] . Indeed , while there is a dramatic decrease in the fraction of cells in the proliferative cell cycle , even the CI14SS7 condition resulted in only a 2-fold change in glucose consumption , much less than reported in other systems . Thus , decreased metabolic activity is not a universal hallmark of quiescence . To further assess glycolytic rates in proliferating and contact-inhibited fibroblasts , we monitored the steady state pool sizes of glycolytic intermediates using liquid chromatography coupled to tandem mass spectrometry [20]–[22] . In total , we monitored the levels of 172 metabolites , 62 of which gave signals above background in proliferating , CI7 , and CI14 fibroblasts . Metabolite levels were normalized per microgram of protein in cells plated at the same density because quiescent fibroblasts are smaller and contain less protein per cell than proliferating fibroblasts ( E . M . Haley , A . L . -M . , and H . A . C . , unpublished data ) . The ratio of metabolite levels in the contact-inhibited ( CI7 and CI14 ) to proliferating fibroblasts was determined for each metabolite . Some metabolites were present at consistently higher levels in proliferating fibroblasts , while others were enriched in contact-inhibited fibroblasts , although the magnitude of these changes in metabolite levels was generally modest ( Figure S2 ) . Levels of five glycolytic intermediates and pentose-5-phosphate ( a combination of ribose-5-phosphate , ribulose-5-phosphate , and xylulose-5-phosphate , which could not be reliably differentiated in our liquid chromatography–tandem mass spectrometry [LC-MS/MS] method ) are shown in Figure 2B . No statistically significant differences were observed in the levels of glycolytic intermediates between contact-inhibited ( CI7 or CI14 ) and proliferating fibroblasts at a false discovery rate of 0 . 05 . Some glycolytic metabolites were present at lower levels in contact-inhibited , serum-deprived ( CI14SS7 ) fibroblasts . Thus , the transition between proliferation and quiescence induced by contact inhibition alone has little effect on the pool sizes of glycolytic metabolites in primary fibroblasts . While pool sizes are not a direct indication of changes in flux , the constant levels of glycolytic metabolites in proliferating , CI7 , and CI14 fibroblasts are consistent with our finding that there is little change in the rate of glucose uptake or lactate secretion among fibroblasts in these different states . To more directly assess the rate of flux through glycolytic pathways , we incubated fibroblasts with [U-13C]-glucose and determined how quickly the label was incorporated into glycolytic intermediates ( Figure 2C ) . For hexose phosphate ( a combination of glucose-1-phosphate , glucose-6-phosphate , and fructose-6-phosphate ) , fructose-1 , 6-bisphosphate ( FBP ) , dihydroxyacetone phosphate ( DHAP ) , and phosphoenolpyruvate , the unlabeled pools of intermediates were converted into fully 13C-labeled intermediates at a similar rate in proliferating , CI7 , and CI14 fibroblasts . We also developed a computational model based on ordinary differential equations ( ODEs ) of central carbon metabolism for the proliferating , CI7 , CI14 , and CI14SS7 fibroblasts . The ODEs in the model quantify the isotope labeling dynamics of the relevant metabolites after switching into 13C-labeled carbon sources ( Figure S3 ) . Model parameters ( i . e . , metabolic fluxes and some unmeasured pool sizes ) were identified by fitting all of the available laboratory data ( labeling dynamics , pseudo-steady-state labeling patterns , measured pool sizes , and uptake and excretion rates ) . This systems-level approach enabled quantitation of flux through different metabolic pathways in proliferating , CI7 , CI14 , and CI14SS7 fibroblasts ( Figure S4 and Table S1 ) . For glycolysis , the inferred fluxes from hexose phosphate to FBP , and from DHAP to 3-phosphoglycerate , were similar in proliferating , CI7 , and CI14 conditions ( Figures 3 and S4 and Table S1; see Materials and Methods for information regarding statistical significance ) . In CI14SS7 fibroblasts , hexose phosphate–to-FBP and DHAP-to–3-phosphoglycerate fluxes are approximately half those in the other conditions ( Figure S4 and Table S1 ) , consistent with an approximately 2-fold reduction in glucose consumption . We conclude that glucose consumption and lactate excretion proceed rapidly in fibroblasts induced into quiescence by contact inhibition . The PPP produces ribose-5-phosphate , needed for the biosynthesis of nucleotides , and NADPH , which can be used as a cofactor for the biosynthesis of macromolecules including fatty acids . We anticipated that proliferating cells would have higher demands for both ribose-5-phosphate and NADPH than quiescent cells , and thus higher PPP flux . Surprisingly , the pentose phosphate pool incorporated 13C label very rapidly in proliferating , CI7 , and CI14 fibroblasts when the cells were incubated with labeled [U-13C]-glucose ( Figure 4A ) . Indeed , according to our computational model , hexose phosphate–to–pentose phosphate flux was actually slightly higher in contact-inhibited ( both CI7 and CI14 ) fibroblasts than in proliferating fibroblasts ( though the effect was not statistically significant ) . Additional serum deprivation only slightly decreased oxidative PPP flux , with the oxidative PPP flux–to–glycolytic flux ratio highest in CI14SS7 fibroblasts . Thus , the oxidative PPP is actively utilized in both proliferating and quiescent cells . We anticipated that ribose generated from the PPP would be incorporated into nucleotide triphosphates more rapidly in proliferating than quiescent cells because of their increased need for nucleotide triphosphates for RNA and DNA synthesis . Indeed , in proliferating fibroblasts , ATP and UTP with labeled ribose rings accumulate more rapidly in proliferating fibroblasts ( Figure 4A ) . The results confirm that biosynthesis of nucleotides is more rapid in the proliferating cells . Given that quiescent fibroblasts do not commit ribose phosphate to nucleotide biosynthesis , we reasoned that quiescent cells might recycle ribose phosphate back to glycolytic intermediates through the non-oxidative branch of the PPP . To test this hypothesis , we monitored the ratio of 1×13C-lactate to 2×13C-lactate after incubating the cells with [1 , 2-13C]-glucose . As previously described [27] , 1×13C-lactate is formed when glucose is metabolized through the oxidative portion of the PPP to ribulose-5-phosphate . In this pathway , glucose molecules lose one 13C atom in the form of CO2 , and are then returned to glycolysis through the non-oxidative branch of the PPP ( Figure 4B ) . 2×13C-lactate is formed by the canonical glycolysis pathway from glucose to lactate . The ratio of 1×13C-lactate to 2×13C-lactate provides an indication of the extent to which the non-oxidative branch of the PPP is utilized . This ratio is significantly higher in CI7 than proliferating fibroblasts , and even higher in CI14 fibroblasts ( Figure 4C ) . As another indication of the rate of flux through the non-oxidative branch of the PPP , we monitored labeling of sedoheptulose-7-phosphate , a metabolic intermediate in the non-oxidative PPP . Sedoheptulose-7-phosphate is labeled rapidly in CI7 and CI14 but not proliferating fibroblasts fed [U-13C]-glucose ( Figure 4A ) , indicating higher flux through the non-oxidative branch of the PPP in quiescent cells . Our systems-level flux analysis confirmed increased flux from ribose phosphate back to glycolysis in contact-inhibited compared with proliferating fibroblasts ( Figures 3 and S4 and Table S1 ) . Thus , ribose phosphate generated from the PPP is utilized for nucleotide biosynthesis in proliferating fibroblasts but is recycled back to glycolytic intermediates in quiescent fibroblasts . To investigate the mechanistic basis for the high PPP flux in quiescence fibroblasts , we monitored protein levels of two key enzymes in the PPP , both of which generate NADPH: glucose-6-phosphate dehydrogenase ( G6PD ) and 6-phosphogluconate dehydrogenase ( PGD ) . Protein levels of both G6PD and PGD were elevated in fibroblasts induced into quiescence by either contact inhibition or serum starvation in comparison to proliferating fibroblasts ( Figure 5A ) . These results suggest that contact-inhibited and serum-starved fibroblasts may activate a program that results in increased levels of PPP enzymes . Both proliferating and quiescent fibroblasts generate NADPH through the PPP . The NADPH may be used for biosynthesis or to regenerate the reduced forms of glutathione or thioredoxin . We monitored reduced and oxidized glutathione ( GSH and GSSG , respectively ) in proliferating , CI7 , CI14 , and CI14SS7 fibroblasts . As shown in Figure 5B and 5C , GSH was slightly increased , and the ratio of GSH to GSSG significantly enhanced , in quiescent ( CI7 , CI14 , and CI14SS7 ) compared with proliferating fibroblasts . The results are consistent with a model in which quiescent fibroblasts upregulate NADPH production in part to ensure adequate GSH as protection against free radicals [28] . We then tested the functional importance of the PPP in quiescent and proliferating fibroblasts . We incubated proliferating or CI14 fibroblasts with dehydroepiandrosterone ( DHEA ) , a small molecule inhibitor of the PPP [29] , [30] for 4 d and monitored the fraction of cells that were dead with propidium iodide ( PI ) labeling followed by flow cytometry . We discovered that the contact-inhibited fibroblasts exhibited a statistically significant increase in cell death compared with the proliferating fibroblasts from DHEA treatment at 100 µM and 250 µM doses ( p<0 . 01 ) ( Figure 6A ) . This result is particularly impressive given that almost all known metabolic inhibitors and cytotoxins preferentially kill proliferating cells [18] , [31] , [32] . Assaying for caspase-3/7 activity revealed that the mechanism of DHEA-induced cell death in the quiescent fibroblasts is via apoptosis ( Figure 6B ) . The apoptosis-inducing effect of DHEA was significantly stronger in fibroblasts that were confluent for 11 d than in proliferating fibroblasts , and yet stronger in fibroblasts serum-starved for 7 d in the absence of contact inhibition . Previous studies concluded that proliferating lymphocytes actively utilize glycolytic pathways to generate ATP while quiescent lymphocytes generate energy via an influx of fatty acids and proteins that are metabolized through the tricarboxylic acid ( TCA ) cycle [8] . To investigate TCA cycle usage , we monitored metabolite labeling through the TCA cycle after addition of [U-13C]-glucose , [3-13C]-glucose or [U-13C]-glutamine in proliferating , CI7 , and CI14 fibroblasts . As shown in Figure 7 , proliferating and contact-inhibited fibroblasts incorporate two carbon units from glucose into citrate via acetyl-CoA at comparable rates . In CI7 and CI14 fibroblasts , the labeled carbons progress through the TCA cycle to form 2×13C-α-ketoglutarate , as expected . In proliferating fibroblasts , however , there is a substantial decrease in the transmission of labeled carbons from citrate to α-ketoglutarate , succinate , and malate . Experiments using [U-13C]-glutamine further support the truncation of the TCA cycle ( Figure 8 ) . While carbon from glutamine effectively transverses the left side of the TCA cycle in the standard clockwise direction to yield 4×13C-citrate in both proliferating and quiescent fibroblasts , subsequent formation of 3×13C-α-ketoglutarate by isocitrate dehydrogenase hardly occurs in proliferating fibroblasts . The decreased flux from citrate to α-ketoglutarate in proliferating fibroblasts was confirmed via our systems-level flux identification ( Figures 3 and S4 and Table S1 ) . When carbon skeletons are removed from the TCA cycle for the synthesis of macromolecular precursors including amino acids , other long carbon skeletons are needed to replace them . This anaplerotic refilling should be especially important for proliferating fibroblasts since their TCA cycle activity is truncated at citrate . The major anaplerotic reaction from glycolysis involves the carboxylation of pyruvate to form oxaloacetate . This reaction can be monitored by feeding cells [3-13C]-glucose and monitoring the fraction of citrate or malate with label , since the 13C is retained only when the anaplerotic reaction via pyruvate carboxylase is utilized . Surprisingly , the ratios of 1×13C-citrate to unlabeled citrate and/or 1×13C-malate to unlabeled malate were significantly increased in CI7 , CI14 , and CI14SS7 fibroblasts compared with proliferating fibroblasts ( Table S2 ) . In addition , quantitative flux analysis revealed that anaplerotic flux from pyruvate to oxaloacetate is elevated in CI7 , CI14 , and CI14SS7 compared with proliferating fibroblasts ( Figure S4 and Table S1 ) , while the flux from pyruvate to acetyl-CoA is lower in CI14 and CI14SS7 fibroblasts than in proliferating fibroblasts . Thus , contact inhibition was associated with both an increase in canonical TCA cycle activity past citrate , and an increase in anaplerotic TCA cycle flux from pyruvate to oxaloacetate . Proliferating fibroblasts , in contrast , seem unlikely to have sufficient carbon skeletons from glucose for the production of proteogenic amino acids not present in the cell growth medium . We hypothesized that proliferating fibroblasts rely on another source for carbon skeletons . Supplementation with glutamine has been shown to be necessary for cultured cells , especially actively proliferating cells [33]–[36] . Accordingly , we monitored the rate of glutamine consumption by proliferating , CI7 , CI14 , and CI14SS7 fibroblasts ( Figures 2A and S1 ) . CI7 , CI14 , and CI14SS7 fibroblasts consume approximately half as much glutamine per microgram of protein as proliferating fibroblasts . CI7 and CI14 fibroblasts secrete glutamate at a lower rate compared with proliferating fibroblasts , and CI14SS7 fibroblasts secrete glutamate at a lower rate than CI7 or CI14 fibroblasts . SS4 and SS7 fibroblasts , on the other hand , consume glutamine and secrete glutamate at a faster rate than proliferating fibroblasts ( Figure S1 ) . The relative rate of glutamine consumption in proliferating versus CI14 fibroblasts in low glucose/low glutamine conditions is similar to that in standard medium . As shown in Figure 8 , incubation of proliferating , CI7 , and CI14 fibroblasts with [U-13C]-glutamine results in rapid labeling of glutamate , α-ketoglutarate , succinate , malate , and citrate , indicating that glutamine is used by both proliferating and contact-inhibited fibroblasts for TCA cycle anaplerosis . Since very few glucose carbons are incorporated into the TCA cycle in proliferating fibroblasts , glutamine may serve as the major anaplerotic precursor in proliferating fibroblasts [36]–[39] . [U-13C]-glutamine is converted into 5×13C-glutamate and subsequently to 5×13C-α-ketoglutarate . 5×13C-α-ketoglutarate can proceed through the TCA cycle in the forward direction to generate 4×13C-succinate , or , alternatively , it can be reductively carboxylated to 5×13C-citrate using NADPH as the electron source [40] , [41] . As shown in Figure 8A , introduction of [U-13C]-glutamine led to conversion of approximately 15% of the citrate to the 5×13C form in proliferating , CI7 , and CI14 fibroblasts by 8 h , with more rapid labeling in contact-inhibited fibroblasts . These results support a model in which there is both forward and reverse flux between citrate and α-ketoglutarate , with greater flux in both directions in contact-inhibited than in proliferating fibroblasts ( Figures 3 and S4 and Table S1 ) . The forward and reverse flux likely occur in different compartments , with α-ketoglutarate reductively carboxylated by isocitrate dehydrogenase 2 ( IDH2 ) in the mitochondrion , and the resulting citrate reconverted to α-ketoglutarate by IDH1 in the cytosol [42] . As both IDH1 and IDH2 use NADP ( H ) as their redox cofactor , the net effect is transfer of high energy electrons in the form of NADPH to the cytosol . Consistent with greater flux through this pathway in contact-inhibited fibroblasts , IDH1 protein is increased by contact inhibition at the transcript and protein levels ( Figure 8C ) . Thus , two major pathways to cytosolic NADPH , the PPP and the IDH2/IDH1 shuttle , are upregulated at both the protein and flux level in contact-inhibited fibroblasts . Quiescent cells do not dilute out older macromolecules , organelles , or membranes with cell division , and thus may be more dependent than proliferating cells on mechanisms to break down and resynthesize membrane components and macromolecules . Our data are consistent with increased fatty acid degradation in contact-inhibited fibroblasts . Carnitine , a metabolite involved in the transport of fatty acids from the cytoplasm to the mitochondria during fatty acid degradation , is present at higher levels in CI7 and CI14 fibroblasts than in proliferating fibroblasts ( Figure S2 ) . Also , quantitative flux identification revealed , based on long-term labeling patterns of citrate , increased fatty acid breakdown in CI7 and CI14 fibroblasts , but lower rates of fatty acid breakdown in CI14SS7 fibroblasts ( Figures 3 and S4 and Table S1 ) . The enhanced rate of fatty acid degradation in contact-inhibited fibroblasts seems to be enabling fatty acid biosynthesis to occur at a similar rate in proliferating and contact-inhibited fibroblasts . During fatty acid synthesis , citrate is transported out of the mitochondria to the cytoplasm , where it is broken down by ATP citrate lyase into oxaloacetate and acetyl-CoA used in fatty acid biosynthesis . ATP citrate lyase activity can be monitored based on the conversion of 5×13C-citrate to 2×13C-acetyl-CoA and 3×13C-oxaloacetate ( measured as 3×13C-malate ) . As shown in Figure 8A , 3×13C-malate is produced similarly in proliferating , CI7 , and CI14 cells , consistent with fibroblasts in all of these states being actively engaged in fatty acid biosynthesis . To more directly assess fatty acid biosynthesis in proliferating and quiescent fibroblasts , we extracted lipids from proliferating , CI7 , CI14 , and CI14SS7 fibroblasts fed [U-14C]-glutamine . The contribution of carbons to fatty acids from glutamine was significantly higher in all of the quiescent fibroblasts compared with the proliferating fibroblasts ( Figure 8B ) , consistent with higher “backwards” flux from α-ketoglutarate to citrate ( Figures 3 and S4 and Table S1 ) . The higher levels of fatty acid synthesis in contact-inhibited fibroblasts may contribute to the maintenance of membrane integrity , and may also provide a major sink for cytosolic NADPH . Similarly , our results suggest that contact-inhibited fibroblasts may also be actively degrading existing protein , and thus resynthesizing protein to replace the degraded proteins . As shown in Figure 9 , the fraction of glutamate that is labeled in fibroblasts under all conditions increases rapidly after switching cells into [U-13C]-glutamine and then drops off in CI7 and CI14 fibroblasts , but not in proliferating fibroblasts . This decline in the fraction of glutamate molecules with five labeled carbons corresponds to an increase in the fraction of unlabeled glutamate . One possible explanation for these data is a breakdown of unlabeled proteins and release of free amino acids into the glutamate pool . These results are in agreement with our quantitative flux analysis: protein synthesis rates are similar across all conditions [43] , [44] ( Figures 3 and S4 and Table S1 ) . Protein synthesis rates in the best-fit model are 3 . 3 nmol/min/µg protein for proliferating fibroblasts , 4 . 3 nmol/min/µg protein for CI7 fibroblasts , 4 . 1 nmol/min/µg protein for CI14 fibroblasts , and 2 . 9 nmol/min/µg protein for CI14SS7 fibroblasts . Thus , one reason for the active metabolism observed in contact-inhibited fibroblasts may be to rebuild and thus refresh their lipid and protein contents . The high metabolic activity of quiescent fibroblasts might also be partially explained by their synthesis and secretion of extracellular matrix molecules needed for the structural integrity of tissue . While proliferating fibroblasts would be expected to secrete molecules important for wound healing [15] , quiescent fibroblasts might be expected to secrete extracellular matrix molecules required at the end of a wound healing process or for maintenance of quiescent tissue [45] . We monitored the levels of secreted protein in conditioned medium collected from plates containing proliferating or CI14 fibroblasts [13] . Because serum interferes with immunoblotting for specific proteins , these experiments were performed in no serum and 0 . 1% serum conditions . As shown in Figure 9 , the levels of fibronectin , collagen 21A1 , and laminin alpha 2 in conditioned medium from CI14 fibroblasts was higher than the levels in conditioned medium from proliferating fibroblasts , thus demonstrating a biosynthetic commitment for contact-inhibited fibroblasts that may contribute to their high metabolic rate . The metabolic profiles of proliferating and CI14 fibroblasts are summarized in Figure 3 . Fibroblasts in both proliferating and contact-inhibited states utilize glycolysis extensively . Proliferating fibroblasts rely on the PPP to generate ribose for nucleotide biosynthesis and NADPH for biosynthetic purposes . Contact-inhibited fibroblasts employ the oxidative PPP to generate NADPH , and the carbon skeletons are largely returned to glycolysis as glyceraldehyde-3-phosphate and fructose-6-phosphate . Fibroblasts in both proliferating and contact-inhibited states contribute some glucose carbons to the TCA cycle . In contact-inhibited fibroblasts , carbons contributed by glucose are transmitted through the TCA cycle; in proliferating fibroblasts , there is little forward flux between citrate and α-ketoglutarate . Contact-inhibited fibroblasts rely more heavily on anaplerotic flux from pyruvate to oxaloacetate via pyruvate carboxylase; proliferating fibroblasts rely more heavily on glutamine , perhaps because of their higher demand for nitrogen . Glutamine drives the forward flux through the TCA cycle and also reverse flux from α-ketoglutarate to citrate , especially in the contact-inhibited fibroblasts . This reverse flux provides a mechanism for shuttling NADPH from mitochondria to the cytosol .
We discovered that fibroblasts induced into quiescence by contact inhibition maintain a high metabolic rate . In contact-inhibited fibroblasts , nucleotide biosynthesis is reduced , yet the rate of glycolytic , PPP , and TCA flux is almost completely maintained . Even fibroblasts that have been contact-inhibited for 2 wk and starved of serum for the final week show only a 2-fold reduction in glycolytic flux . Contact-inhibited fibroblasts also presumably generate substantial energy through the TCA cycle , where we observed flux of both glucose- and glutamine-derived carbons through more than a complete cycle . Consistent with these multiple routes of energy generation , the ATP/AMP ratio is high in contact-inhibited fibroblasts ( Figure S2 ) . What then do the quiescent fibroblasts do with all of their energy ? Our data suggest three avenues for energy utilization . First , contact-inhibited fibroblasts may continuously degrade and resynthesize their macromolecules and membrane components via increased autophagy [43] , [44] ( E . M . Haley , A . L . -M . , and H . A . C . , unpublished observation ) , a strategy that would help to ensure that old and potentially damaged macromolecules and membranes do not accumulate . Our data suggest that contact-inhibited fibroblasts may degrade protein and fatty acids at an enhanced rate compared with proliferating fibroblasts . The conclusion most consistent with our data is that the proliferating and contact-inhibited fibroblasts synthesize amino acids and fatty acids at rates that are comparable , with the new biomass contributing to new cells in proliferating fibroblasts and the new biomass replacing degraded molecules in the contact-inhibited fibroblasts . Second , contact-inhibited and serum-starved fibroblasts induce pathways that generate NADPH . We discovered that three NADPH-generating enzymes , G6PD , PGD , and IDH1 , are expressed at higher levels in quiescent than in proliferating fibroblasts . The results suggest that quiescent fibroblasts activate an NADPH-generating program of enzyme induction . One role of the NADPH may be to ensure the availability of GSH and thioredoxin for the detoxification of free radicals . Indeed , levels of total free radicals are lower in the contact-inhibited than in proliferating fibroblasts ( E . M . Haley and H . A . C . , unpublished data ) . Another role for the NADPH generated may be to support resynthesis of fatty acids , as fatty acid degradation yields NADH while synthesis requires NADPH . Third , quiescent fibroblasts may acquire new cell-type-specific functions . In contrast to lymphocytes , which , with the exception of plasma cells , lack a major biosynthetic function in their quiescent state , fibroblasts secrete proteins and other molecules needed for the extracellular matrix even when they are quiescent . Contact-inhibited fibroblasts direct some of their metabolic activity toward this biosynthetic purpose , as we observed elevated levels of specific extracellular matrix proteins in contact-inhibited compared with proliferating fibroblasts ( Figure 10 ) . Thus , quiescent fibroblasts , relieved of the biosynthetic requirements associated with creating progeny , can turn their protein synthesis machinery toward the synthesis of proteins that are beneficial for the organism as a whole . Our findings shed light on some larger questions about quiescence: What are the fundamental attributes of a quiescent state ? Is there a single quiescent state or are there multiple quiescent states ? Our results suggest that quiescence is not necessarily associated with a shutdown of glycolysis , as reported for lymphocytes and thymocytes [6]–[10] . Quiescent cells can actually be highly metabolically active . In this respect , quiescent fibroblasts resemble terminally differentiated cells like cardiomyocytes , neurons , and renal tubular epithelial cells , which are among the highest energy consumers in mammals . These terminally differentiated cells are well-known to employ nutrients to achieve their contractile , signaling , and transport functions . Whether their metabolic activity , like that of contact-inhibited fibroblasts , is also directed to continuously refreshing their protein and lipid composition merits further study . In addition to differing from quiescent lymphocytes , different types of quiescent fibroblasts can vary . While CI7 , CI14 , and CI14SS7 fibroblasts are indistinguishable morphologically or by traditional cell cycle analysis , they differ with regard to their metabolic profiles . Compared with fibroblasts induced into quiescence by contact inhibition , fibroblasts also deprived of serum exhibited a decrease in lactate excretion rates , smaller pool sizes of glycolytic intermediates , and decreased flux from pyruvate to acetyl-CoA . Our findings suggest that cells of different types may actually be in distinct quiescent states , and may have discovered distinct solutions to the metabolic challenges associated with quiescence . Finally , our findings suggest that contact-inhibited and serum-starved fibroblasts are particularly susceptible to apoptosis induced by treatment with DHEA , a pentose phosphate pathway inhibitor . The ability to selectively kill quiescent cells could have therapeutic potential [46] , [47] . For instance , tumor stem cells may exist in a quiescent state for years , while retaining the capacity to emerge from dormancy , proliferate , and initiate a tumor recurrence . Small molecules that target the pathways invoked by these cells to facilitate their survival during dormancy could be useful additions to our therapeutic arsenal . We discovered that contact-inhibited and serum-starved fibroblasts rely on the PPP and possibly other NADPH-generating reactions for viability . Small molecule inhibitors like DHEA might ultimately prove valuable for targeting quiescent tumor cells .
Primary human fibroblasts were isolated from foreskin as previously described ( see Supplemental Data in [48] ) . Fibroblasts were maintained in DMEM ( Hyclone , Thermo Fisher Scientific ) supplemented with 10% fetal bovine serum ( Hyclone ) and 100 µg/ml penicillin and streptomycin ( Invitrogen ) . Cells were collected while proliferating , after 1 wk of confluent maintenance ( CI7 ) , after 2 wk of confluent maintenance ( CI14 ) , after 2 wk of maintenance with the last 7 d in 0 . 1% serum ( CI14SS7 ) , and after serum starvation in 0 . 1% serum for 3 d , 4 d ( SS4 ) , or 7 d ( SS7 ) . Cells made quiescent by serum starvation alone were plated sufficiently sparsely so that they did not contact surrounding cells . Medium was changed every 2 d . Proliferating cells were sampled the day after seeding . In order to better simulate conditions in vivo , we also used low glucose/low glutamine conditions in which the glucose level was 1 g/l and the glutamine level was 0 . 7 mM , compared with a glucose level of 4 . 5 g/l and a glutamine level of 4 mM in standard DMEM . While cells were confluent , the medium was changed regularly . For analysis , cells were transferred to DMEM ( Invitrogen ) with 7 . 5% dialyzed fetal bovine serum ( Atlanta Biologicals or Hyclone ) the day before the experiment . Fibroblasts were photographed through a Nikon Eclipse TS100 microscope using a Scion 8-bit color firewire 1394 digital camera . Images were captured with Scion VisiCapture software ( Scion ) . Cells were trypsinized and collected into phosphate-buffered saline ( PBS ) containing 5% bovine growth serum ( Hyclone ) . Cells were pelleted , resuspended in 67% ethanol in PBS , and stored at 4°C . For flow cytometry , cells were pelleted , washed with PBS , and resuspended in PBS with PI ( 40 µg/ml ) ( VWR ) and RNAse A ( 200 µg/ml ) ( Thermo Fisher Scientific ) . Samples were incubated in the dark for 1 h at room temperature , and analyzed using a FACSort flow cytometer ( BD Biosciences ) . The PI was excited at 488 nm , and emitted fluorescence was collected on detector FL2 with a bandpass filter of 585/42 nm . At least 20 , 000 cells were collected and analyzed with CellQuest software ( BD Biosciences ) . Cell cycle distributions were calculated with ModFit LT software using the Watson Pragmatics algorithm . To differentiate cells in G0 versus G1 , fibroblasts representing each quiescence condition were trypsinized and suspended in cold Hank's buffered saline solution at a concentration of 2×106 cells/ml , then added to a fixative of ice-cold 70% ethanol . Cells were fixed for at least 2 h , washed , and resuspended at 4×106 cells/ml . A solution of 4 µg/ml pyronin Y and 2 µg/ml Hoechst 33342 was added to the cell suspension and incubated on ice for 20 min before measuring cell cycle status by flow cytometry . To determine RNA content , pyronin Y was excited at 488 nm and emission was measured at 562–588 nm . DNA content was determined by Hoechst 33342 . Excitation was measured at 355 nm and emission was measured at 425–475 nm . Cells in G0 were identified as the population with 2N DNA content and an RNA content lower than the level in S phase [49] . Cells were made quiescent by contact inhibition , serum starvation , or a combination as indicated in the text or figure , and collected at the indicated times . The cells were lysed in RIPA buffer ( 50 mM Tris-Cl [pH 7 . 4] , 150 mM NaCl , 1% Triton X-100 , 1% sodium deoxycholate , and 0 . 1% SDS ) containing protease and phosphatase inhibitors ( 10 mM NaPO4 [pH 7 . 2] , 0 . 3 M NaCl , 0 . 1% SDS , 1% NP40 , 1% Na deooxycholate , 2 mM EDTA , protease inhibitor cocktail [Roche , Basel , Switzerland] and Halt Phosphatase inhibitors [Thermo Fisher Scientific] ) . Lysates were sonicated with five pulses for 15 s each at 60 J/W . Lysates were then incubated for 30 min on ice with periodic vortexing and cleared by centrifugation for 2–5 min at 4°C at 10 , 000 rpm . Total protein amount was assessed by the Lowry method using the Bio-Rad DC Protein Assay Kit II ( Bio-Rad ) as described by the manufacturer . Spectrophotometer readings taken at 650 nm were compared against a standard curve to determine lysate concentration . Total protein content was determined as the product of lysate concentration and lysate volume . Equal amounts of total cellular proteins were resolved on 12% SDS-PAGE and electro-transferred onto a PVDF membrane . Membranes were blocked for 1 h at room temperature in Tris-buffered saline containing 0 . 1% Tween-20 ( TBS-T ) ( 10 mM Tris [pH 7 . 6] , 15 mM NaCl , and 0 . 1% Tween-20 ) or phosphate-buffered saline containing 0 . 1% Tween-20 ( PBS-T ) containing 5% nonfat dried milk . Membranes were incubated with antibodies to p27 ( 1∶500 diluted in TBS-T/5% milk ) ( Santa Cruz Biotechnology ) , IDH1 ( 1 µg/ml diluted in PBS-T/1% milk ) ( Lifespan Biosciences ) , G6PD ( 1∶1 , 500 diluted in PBS-T/1% milk ) ( Novus Biologicals ) , or PGD ( 1∶1 , 000 diluted in PBS-T/1% milk ) ( GeneTex ) overnight . Following incubation , the membranes were washed three times in TBS-T or PBS-T and incubated for 1 h with horseradish peroxidase–conjugated anti-rabbit secondary antibody ( 1∶3 , 000 diluted into TBS-T/5% milk for p27 or 1∶10 , 000 diluted in PBS-T/1% milk for IDH1 and G6PD ) ( GE Healthcare ) . The membranes were washed three times with TBS-T or PBS-T , and immunoreactive bands were detected with an enhanced chemiluminescence kit ( Pierce , Thermo Scientific ) . The membranes were stripped using Restore Western Blot Stripping Buffer ( Thermo Scientific ) according to the manufacturer's instructions and immunoblotted with GAPDH ( Abcam ) ( 1∶5 , 000 dilution ) in PBS-T/1% milk or TBS-T/5% milk as a loading control . Highly parallel measurement of intracellular metabolites was performed as previously described [21] . Metabolites were extracted from proliferating , CI7 , CI14 , or CI14SS7 cells by aspirating the medium from the plate and flash-quenching metabolic activity with 80% methanol maintained at −80°C . Cells were incubated in methanol for 15 min , scraped on dry ice , and pelleted with centrifugation at 4 , 400 rpm for 5 min . Samples were re-extracted twice with 80% methanol on dry ice . The three extractions were pooled and dried under nitrogen gas , dissolved in 300 µl of 50% methanol , and spun at 13 , 000× g for 5 min . Methanol supernatant was then passed through an aminopropyl column [50] . Eluate from the column was analyzed with positive ion mass spectrometry via a Finnigan TXQ Quantum Ultra triple-quadrupole mass spectrometer equipped with an electrospray ionization source ( Thermo Fisher Scientific ) [22] . A TSQ Quantum Discovery MAX mass spectrometer , also equipped with an electrospray ionization source , was used to collect data on negative mode ions after separation on a 25-cm C18 column coupled with a tributylamine ion pairing agent to aid in the retention of polar compounds [51] , [52] . To quantify metabolites , peak heights were initially assigned using XCalibur software ( Thermo Fisher Scientific ) and then evaluated manually . Metabolites enriched at least 5-fold in a sample compared with a control plate containing only medium were retained in the analysis . Of the 172 metabolites monitored , 62 met these criteria . Signals that were below the limit of detection were assigned 100 . Metabolite levels were normalized by the amount of protein present . To monitor the flux through metabolic pathways , samples were incubated with medium containing isotope-labeled nutrient for different amounts of time . Dulbecco's medium lacking glucose and glutamine was isotope-labeled by adding back glucose or glutamine ( [U-13C]-glucose , [1 , 2-13C]-glucose , [3-13C]-glucose , or [U-13C]-glutamine; Cambridge Isotope Laboratories ) to a final concentration of 4 . 5 g/l glucose or 0 . 584 g/l glutamine . Samples were taken at the indicated time points after medium change and processed as described above . Levels of 12C and 13C forms of metabolic intermediates were monitored with LC-MS/MS [53] . Medium was sampled from cells under a variety of conditions: proliferating , CI7 , CI14 , CI14SS7 , SS4 , SS7 , low glucose/low glutamine proliferating , and low glucose/low glutamine CI14 . Conditioned medium was sampled over a time course from 0 to 96 h for fibroblasts , depending upon the experiment . The levels of glucose , lactate , glutamine , and glutamate were measured using a YSI 7100 Select Biochemistry Analyzer ( YSI Incorporated ) . The rate of glucose consumption , lactate excretion , glutamine consumption , and glutamate excretion was determined as the rate that these metabolites appeared or disappeared from the medium divided by the time integral of the protein mass of cells on the plate during that time period . The total GSH and GSSG content of proliferating , CI7 , CI14 , and CI14SS7 fibroblasts were determined using Cayman Chemical's Glutathione Assay Kit according to the manufacturer's instructions ( Cayman Chemical ) . Cayman's GSH assay kit employs a carefully optimized enzymatic recycling method , using glutathione reductase for the quantification of GSH . Briefly , cells were harvested using a cell lifter in 1 . 5 ml of cold buffer ( i . e . , 50 mM MES or phosphate buffer [pH 6–7] containing 1 mM EDTA ) and were centrifuged at 10 , 000× g for 15 min at 4°C , followed by metaphosphoric acid deproteinization and addition of triethanolamine solution . Half of the samples were then treated with 2-vinylpyridine to allow quantification of the GSSG pool exclusively . Assay Cocktail ( a mixture of 2- ( N-morpholino ) ethanesulfonic acid Buffer [11 . 25 ml] , reconstituted Cofactor Mixture [0 . 45 ml] , reconstituted Enzyme Mixture [2 . 1 ml] , water [2 . 3 ml] , and reconstituted 5 , 5′-dithiobis- ( 2-nitrobenzoic acid ) [0 . 45 ml] ) was added , and total GSH and GSSG in the deproteinated samples were measured at 405 nm in a spectrophotometer . GSH concentration of the samples was determined by the endpoint method and expressed in micromolar concentrations . Proliferating and CI14 fibroblasts were treated with DHEA dissolved in ethanol or dimethylsufoxide ( 0 . 1% vol/vol ) for 4 d . On the fourth day of treatment with the inhibitor , cells were trypsinized and collected into conditioned medium . Cells were then centrifuged for 5 min at 1 , 000 rpm . The supernatant was aspirated and cells were taken up in PBS with 1 µg/ml PI ( VWR ) . Cells were kept on ice and immediately analyzed by flow cytometry using a BD LSRII multi-laser analyzer ( BD Biosciences ) . PI was excited at 488 nm , and emitted fluorescence was collected through a 610/20 bandpass filter . At least 40 , 000 cells were collected and analyzed with FACSDiVa software ( BD Biosciences ) . PI-negative cells were counted as live cells , and PI-positive cells were counted as dead cells . Apoptosis was measured based on the levels of caspase-3/7 released into the medium using the ApoTox-Glo Triplex Assay according to the manufacturer's instructions ( Promega ) . Cells were plated in triplicate at 10 , 000 cells per well in white-walled , clear-bottom 96-well plates ( Costar , Corning Life Sciences ) . For contact inhibition , cells were plated 7 d prior to the start of treatment; for serum starvation , cells were plated 4 d prior to treatment and switched to 0 . 1% serum medium for the remaining 3 d; proliferating cells were plated the day prior to the start of treatment . Increasing concentrations of DHEA or ethanol vehicle alone were added to the medium in each well , and treatment proceeded for 4 d . Cells in serum starvation conditions were incubated in 0 . 1% serum during treatment as well . The apoptosis reagent was added at 100 µl per well and incubated for 1 h prior to reading . Luminescence was read from the top using a Synergy-2 plate reader ( Biotek ) . Luminescence data were normalized to the vehicle only condition . Lipid synthesis from glutamine was measured using a modified version of a previously published protocol [53] . Briefly , proliferating , CI7 , CI14 , and CI14SS7 fibroblasts were incubated in medium containing 5 µCi/ml [U-14C]-glutamine at 4 mM ( 0 . 4% labeled ) . After incubation for 24 h , the culture medium was aspirated , cells were washed with PBS , and phospholipids were extracted by addition of 500 µl of 3∶2 hexane∶isopropanol . The culture dishes were then washed with an additional 500 µl of the hexane∶isopropanol mixture . The resulting total extract was dried using a speed-vac , resuspended in 500 µl of 1 N KOH in 90∶10 methanol∶water , and incubated at 70°C for 60 min to saponify lipids . Sulfuric acid ( 100 µl , 2 . 5 M ) was then added , followed by hexane ( 700 µl ) to extract the saponified fatty acids . The organic and aqueous phases were separated by centrifugation and scintillation-counted . To monitor gene expression levels , proliferating , CI7 , or CI14 fibroblasts were trypsinized , removed from the plate , pelleted , and stored at −80°C . Total RNA was isolated using the mirVana miRNA Isolation kit ( Ambion ) according to the manufacturer's instructions . RNA quality was verified using a Bioanalyzer 2100 ( Agilent Technology ) , and the amount was determined with a NanoDrop spectrophotometer ( NanoDrop Technologies ) . Total RNA ( 325 ng ) was amplified using the Low RNA Input Fluorescent Labeling Kit ( Agilent Technologies ) according to the manufacturer's protocol . Cy-3 ( PerkinElmer ) was directly incorporated into the cRNA from proliferating cells during in vitro transcription . Cy-5 was incorporated into complementary RNA from CI7 or CI14 fibroblasts . Mixtures of Cy-3-labeled and Cy-5-labeled cRNA were co-hybridized to Whole Human Genome Oligo Microarray slides ( Agilent Technologies ) at 60°C for 17 h and subsequently washed according to the Agilent Technologies standard hybridization protocol . Slides were scanned with a dual laser scanner ( Agilent Technologies ) . Images were monitored for quality control . The Agilent Technologies feature extraction software , in conjunction with the Princeton University MicroArray database ( http://puma . princeton . edu/ ) , was used to compute the log ratio of the two samples for each gene after background subtraction and dye normalization . The entire experiment was performed twice . For the analysis of extracellular matrix proteins in conditioned medium , we could not perform the experiments in the presence of high amounts of serum because serum inhibited protein transfer after immunoblotting . As previously described [13] , proliferating fibroblasts were conditioned at low cell density in the presence of platelet-derived growth factor with either no serum or 0 . 1% serum . Quiescent fibroblasts were cultured at high density in the absence of platelet-derived growth factor with either no serum or 0 . 1% serum . Medium was conditioned over 4 d and during that time , protein lysates were collected over a time course . The protein content of the cell lysates was plotted against the time of lysate collection . A curve that fit the data was generated and the area under the curve , the integrated protein–hour quantity , was divided by the volume of medium collected from the proliferating or quiescent plate . The total protein–hour/volume for each sample was used to adjust the volume of conditioned medium , which was then mixed with 25% volume of trichloroacetic acid ( Sigma-Aldrich ) containing 0 . 1% sodium deoxycholate ( Sigma-Aldrich ) , and incubated for 30 min on ice . Following centrifugation , samples were washed 3–4 times with −20°C acetone , resuspended in sodium dodecyl sulfate-polyacrylamide gel electrophoresis sample buffer and separated under reducing conditions on 5% ( for fibronectin and COL21A1 ) or 12% ( for LAMA2 ) sodium dodecyl sulfate-polyacrylamide gels . Proteins were transferred for 1 h at 100 V to Westran polyvinylidene fluoride membranes ( PerkinElmer ) . Membranes were blocked for 1 h at room temperature in 5% nonfat dried milk in PBS-T . Membranes were then incubated overnight at 4°C with a mouse monoclonal anti-fibronectin clone HFN7 . 1 ( 1∶2 , 000 dilution , generous gift of Jean Schwarzbauer , Princeton University ) , mouse polyclonal antibody against COL21A1 ( 1∶750 dilution , Abcam ) , or mouse monoclonal antibody against LAMA2 ( 3 µg/ml , Abnova ) diluted in PBS-T/1% milk . Following overnight incubation in the primary antibody , membranes were washed three times in PBS-T , incubated for 1 h in a 1∶10 , 000 dilution of horseradish peroxidase–conjugated sheep anti-mouse secondary antibody ( GE Healthcare ) in PBS-T/1% milk . Membranes were exposed to X-ray film , and film was scanned with a Hewlett-Packard Scanjet 4890 using Hewlett-Packard software . The intensity of individual bands was determined with ImageJ analysis software . Fluxes were determined by integration of all available forms of experimental data within a quantitative flux-balanced framework using the same strategy as described in Munger et al . [53] . An ODE model ( Figure S3 ) of central carbon metabolism was constructed . The model assumes steady-state , mass-balanced flux and simulates the resulting labeling dynamics after switching cells from unlabeled medium to uniformly 13C-labeled glucose or glutamine . The model consists of 55 ODEs , describing the rate of loss of unlabeled metabolites and the rate of accumulation of labeled metabolites . It builds upon the previously described model [53] with a few changes . An exchange flux ( F12 ) was introduced in glycolysis between DHAP and FBP . Backward flux ( F11 ) from α-ketoglutarate to citrate , together with a latent citrate pool that is never labeled ( determined by the lowest unlabeled citrate pool size observed in all experiments ) , was introduced in the TCA cycle . The latent citrate pool was added because for citrate , but not other metabolites , a substantial fraction of the pool ( approximately 40% for the proliferating cells ) did not label over the course of the experiment . Beyond labeling dynamics , additional input data included metabolite levels , rates of metabolite consumption and excretion , and the glycolysis–PPP flux convergence ratio determined after feeding [1 , 2-13C]-glucose for 2 h . Model parameters ( fluxes , as well as pool sizes of a small number of metabolites that could not be directly experimentally measured ) were identified by a genetic algorithm that minimizes a cost function defined as the sum of weighted differences between the experimental data and computational results ( Table S3 ) [54] . As a global search algorithm , the genetic algorithm computationally probes for alternative flux solutions consistent with the experimental results . For each cell type , the algorithm was run until 1 , 000 consistent solutions ( i . e . , parameter sets that produced the lowest cost values when the algorithm reached convergence ) were obtained . The distribution of the 1 , 000 values was then used to quantitatively represent each identified parameter . Since the distributions are not Gaussian , a flux is considered quantitatively different between proliferating and quiescent cells only when the distributions from the proliferating and quiescent fibroblasts do not overlap . This measure minimizes the false positives that may occur when only one or a few solutions are identified [54] . Although qualitatively supportive of the model-inferred enhancement of anapleurotic flux from glucose in quiescent fibroblasts , labeling data for [3-13C]-glucose , which was taken at 8 h , were quantitatively inconsistent with the other labeling data , which covered the first 2 h of incubation only . The [3-13C]-glucose data were accordingly excluded from the computational analysis . The computer code is available upon request . The Entrez Gene ( http://www . ncbi . nlm . nih . gov/gene ) accession numbers for the proteins discussed in this paper are G6PD , 2539; IDH1 , 3417; IDH2 , 3418; and PGD , 5226 . | Many cells in the human body are in a reversible state of quiescence , where they have exited the cell cycle but retain the capacity to re-enter it and divide again . Previous experiments in lymphocytes had suggested that quiescent cells reduce their glucose uptake and metabolic rate . In our studies , we have investigated the metabolism of fibroblasts , cells found in connective tissue and skin . Using “metabolomics” to monitor flux through metabolic pathways , we discovered that fibroblasts remain highly metabolically active even though they are not dividing . They degrade and resynthesize protein and fatty acid , and secrete large amounts of protein into the extracellular environment . Despite our expectation that quiescent cells would not have a high demand for nucleotide biosynthesis , we found that they do divert glucose to the pentose phosphate pathway , presumably to generate NADPH . The NADPH created may help the quiescent fibroblasts to detoxify free radicals or to synthesize fatty acids . Experiments in which we inhibited the pentose phosphate pathway resulted in increased apoptosis in quiescent cells , suggesting a possible strategy for selectively killing nondividing cells . | [
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] | [
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] | 2010 | Quiescent Fibroblasts Exhibit High Metabolic Activity |
The physiological functions of epidermal cells are largely determined by their diverse morphologies . Most flowering plants have special conical-shaped petal epidermal cells that are thought to influence light capture and reflectance , and provide pollinator grips , but the molecular mechanisms controlling conical cell shape remain largely unknown . Here , we developed a live-confocal imaging approach to quantify geometric parameters of conical cells in Arabidopsis thaliana ( A . thaliana ) . Through genetic screens , we identified katanin ( KTN1 ) mutants showing a phenotype of decreased tip sharpening of conical cells . Furthermore , we demonstrated that SPIKE1 and Rho of Plants ( ROP ) GTPases were required for the final shape formation of conical cells , as KTN1 does . Live-cell imaging showed that wild-type cells exhibited random orientation of cortical microtubule arrays at early developmental stages but displayed a well-ordered circumferential orientation of microtubule arrays at later stages . By contrast , loss of KTN1 prevented random microtubule networks from shifting into well-ordered arrays . We further showed that the filamentous actin cap , which is a typical feature of several plant epidermal cell types including root hairs and leaf trichomes , was not observed in the growth apexes of conical cells during cell development . Moreover , our genetic and pharmacological data suggested that microtubules but not actin are required for conical cell shaping . Together , our results provide a novel imaging approach for studying petal conical cell morphogenesis and suggest that the spatio-temporal organization of microtubule arrays plays crucial roles in controlling conical cell shape .
Plant epidermal cells have diverse shapes that enable these cells to perform unique physiological functions . Floral petals of nearly 79% of angiosperm species contain conical epidermal cells that are usually found on the adaxial epidermis ( the upper surface ) , oriented towards potential pollinators but rarely present on leaves or any other organ epidermis [1–4] . Conical cells exhibit a three-dimensional ( 3D ) geometric shape with a cone tip and a pentagonal or hexagonal base , which influences petal color , light capture and reflectance , petal wettability , and pollinator grips [5–8] . However , despite the important physiological roles and the special shape of conical cells , little is known about the mechanisms that control their shape formation . Currently , our knowledge of conical cells derived from images acquired by scanning electron microscopes or optical microscopes . The MIXTA gene encodes a MYB transcription factor in Antirrhinum majus , whose loss-of-function mutants result in petal epidermis with flat hexagonal-based cells instead of wild-type conical cells [9] . This change in cell morphology has been shown to reduce the mutant flowers’ chances of being visited by pollinators and thus affects pollination success [10] . A . thaliana studies using scanning electron microscopes to visualize epidermal cells have identified several transcriptional factors that function in regulating the outgrowth of conical cells [5 , 11–16] , but the molecular and genetic mechanisms controlling conical cell morphogenesis remain largely unknown . Plant cells achieve their final shapes with the aid of cytoskeletal elements , which include actin filaments and microtubules [17] . Actin filaments play an important role in cell shape formation by guiding vesicle trafficking to promote cell elongation [18] . Cortical microtubules play a key role in orienting the deposition of cellulose microfibrils during cell wall biosynthesis and thus affect cell morphogenesis [19–22] . Owing to the advancement of live-cell imaging technologies , extensive studies have provided critical insights into the reorganization of microtubule arrays , an event that is in part mediated by self-organization processes involving severing , polymerization , depolymerization , and zippering [23–25] . The microtubule-severing protein KTN1 was originally identified from a screen for mutations that led to defects in the mechanical strength of inflorescence stems [26 , 27] . Loss-of-function mutations of KTN1 result in a remarkable defect in leaf epidermal cell shape , associated with disordered microtubule arrays and abnormal orientation of cellulose microfibrils , as well as loss of layers in the secondary cell walls of fibers [26–28] . Previous results have shown that KTN1 is recruited to both the microtubule nucleation sites and microtubule crossovers to perform its microtubule-severing function , which is required for the generation of well-ordered microtubule arrays [29–31] . Moreover , it has been shown that KTN1 plays essential roles in organizing diverse patterns of microtubule arrays in response to mechanical stress [32 , 33] , and the environmental signal stimuli , such as blue light [34] . Despite the central roles of the cytoskeletal systems in regulating plant cell morphogenesis , functional analyses of cytoskeletal control of petal conical cell morphogenesis remain as a missing research field . In contrast to the detailed understanding of molecular mechanisms that control the morphogenesis of diverse plant epidermal cell types [35–40] , including leaf trichomes and pavement cells , and root hairs , the genetic and molecular mechanisms that control the morphogenesis of conical cells remain elusive , probably owing to the lack of available live-confocal scanning imaging approaches . In this study , we established a live-confocal scanning imaging approach for the quantitative study of conical cell morphogenesis . In addition , genetic and pharmacological experiments demonstrated that microtubules but not actin filaments play a major role in regulating formation of the final shape of conical cells . Our findings not only provide significant insights into the functional analysis of cytoskeletal control of the morphogenesis of flower petal conical cells , but also may pave the way for a new model system to study cell shape in A . thaliana .
A . thaliana conical cells protrude outwards from the plane of the adaxial epidermis; therefore , the conical cells’ lateral cell walls that are not in the plane of the focal axis of the confocal laser scanning microscope cannot be observed from the top view of a conical cell from a petal sample that is faced up ( S1A Fig ) , and only hexagonal outlines of the conical cell's basal part were visualized ( S1B Fig ) . To make the lateral cell walls of conical cells into the focal plane of the microscope , petal blades were transversally folded back to expose the adaxial interface to the fold ( Fig 1A and S1C Fig ) , which enables a side visualization of the conical cells ( Fig 1B and S1D Fig ) . Z stacks of optical sections were taken from the top view of the adaxial epidermis from a folded petal , and projected onto a plane at maximum intensity to generate a quantifiable serrated shape of the conical cells ( Fig 1B and S1D Fig ) . By contrast , exposing the abaxial interface to the fold resulted in the observation of flat abaxial epidermal cells ( S1E Fig ) . These results are consistent with previous reports that the petal adaxial epidermis has conical cells while the abaxial epidermis has flat-shaped cells ( S1F and S1G Fig ) [3 , 7] . We quantified the structural parameters of conical cells ( S1H Fig ) , including cell heights and cone angles . We found that A . thaliana wild type Col-0 and WS conical cells from mature petals displayed similar cell heights , with 13μm on average , and the apex angles of these two ecotypes were 80°on average ( Fig 1C and 1D ) . To verify the accuracy and reproducibility of these analyses , we further quantified structural parameters using images of histological sections of fixed samples ( S2 Fig ) . Our results showed that the cone structural parameters calculated using these two techniques were comparable to each other ( S2 Fig ) . Therefore , we developed a live-confocal imaging approach for fast quantitative analyses of the structural parameters of conical cells . To uncover the genetic and molecular mechanisms controlling the shape formation of conical cells , we mutagenized wild-type Col-0 with ethyl methane sulfonate ( EMS ) , and performed a genetic screen for mutants with abnormal conical cell shapes using our newly developed confocal-imaging approach . A mutant showing swollen apexes of conical cells compared with the wild type was identified ( Fig 1E ) . We mapped the mutation to an interval of the short arm of chromosome 1 , containing the KTN1 locus . Sequencing of the KTN1 gene itself revealed a C-to-T mutation , resulting in an A-to-V amino acid substitution ( S3A and S3B Fig ) ; this new mutation was designated as ktn1-6 . To determine whether the phenotype of swollen conical cell apexes was caused by the mutation in KTN1 , we performed a genetic complementation test . Expression of KTN1 by transforming pKTN1::KTN1 into the ktn1-6 mutant complemented its phenotype ( S3C and S3D Fig ) . In addition , the T-DNA insertion mutant ktn1-4 ( SAIL_343_D12 ) for the KTN1 gene ( Lin et al . , 2013 ) displayed the cell phenotype similar to the ktn1-6 mutant ( Fig 1E ) . Quantitative analyses revealed that both the ktn1-6 and ktn1-4 mutant showed increased radial expansion of conical cell apexes but no change in the basal parts in comparison with the wild type , ( Fig 1G and S4A–S4E Fig ) , with larger cone angles and reduced heights in the gaps ( indentation heights ) between two neighboring cells ( Fig 1G–1I ) . These observations suggest that KTN1 function is required for the morphogenesis of conical cells . The morphological events of petal development have been well characterized in A . thaliana [41] , whereas the development of conical cells has not been described . We first characterized this process in wild-type A . thaliana petals via quantitative analyses of the serrated geometry of conical cells from various petal development stages . Because it is extremely difficult to track the same cell to observe changes in the cell morphology of growing petals , we measured temporal morphological changes of conical cells in the average height , width , and cone angle from petal development stage 8 to stage 14 . Cells from petal development stage 8 have a relatively flat surface with a 2 . 02-μm height , 6 . 18-μm width , and 143 . 90°cone angle on average , which have just begun to initiate conical outgrowth ( Fig 2 ) . After initiating the outgrowth from the petal epidermis , conical cells undergo both radial expansion and longitudinal elongation , with increased sharpening of apexes over the course of petal development stages 8 to 14 , and a decrease in cone angles ranging from143° to 72° ( Fig 2 ) . Cells from petal development stage 9 have clearly expanded and established elongated longitudinal axes , with 4 . 18-μm height , 7 . 23-μm width , and 111 . 43°cone angle on average ( Fig 2 ) . After petal development stage 9 , cells undergo fast anisotropic expansion with an increase in radial expansion , longitudinal elongation , and thus results in apparent conical shape . Cone angles of conical cells from stages 9 to 11 range from 111° to 72° , whereas after petal development stage 11 , a slight increase in cone angle of conical cells was observed , which was caused by increased radial expansion of the cell base but relatively slow elongation of the cell’s longitudinal axis ( Fig 2 ) . The conical cell of the mature petal ( stage 14 ) has a characteristic cone morphology with 12-μm height , 17-μm width , and 80° cone angle on average . We next asked how KTN1 influences conical cell development at various development stages by comparing the phenotype of conical cells of wild type with the ktn1 mutants at petal developmental stages 10–14 . Measuring cell heights and cone angles at development stages 8–10 showed that the ktn1 mutants had similar cell sizes as the wild type ( Fig 2 ) , while at developmental stage 11 and beyond , ktn1 mutant cells displayed a decrease in tip sharpening , resulting in swollen apexes with larger cone angles compared with the wild type ( Fig 2 ) . Taken together , these results show that KTN1 plays an important role in promoting the tip sharpening of the conical cell during late development stages , thus influencing the final characteristic shape formation of the conical cell . Recent advances in 3D plant imaging have been made at both the organ scale and cellular level [42–47] , which are critical for understanding morphogenesis . Having a 3D view of conical epidermal cells allows for the investigation of the contribution of spatiotemporal patterns of gene expression to 3D cell shape . To obtain a 3D surface reconstruction of conical cells , Z stacks of images from the distal regions of PI-stained petal samples were taken from the top view along their Z-axis at steps of 0 . 8μm to reconstruct a 3D image of conically shaped cells . As a result , we were able to obtain high-quality 3D images of conical cells ( Fig 1F ) . We next reconstructed a 3D surface of the ktn1 mutants and found that the 3D geometry of the mutant cells displayed increased apical isotropic expansion compared to the wild type ( Fig 1F ) . Consistent with this result , cell morphologies visualized via scanning electron microscopy in the adaxial epidermis of wild type and the ktn1 mutants were comparable to those observed via 3D reconstruction of Z stacks of confocal images ( S4F Fig ) . We next performed detailed phenotype analyses of the 3D geometry of conical cells between the wild type and the ktn1 mutants at different developmental stages . Our results showed that the 3D geometry of conical cells of the ktn1 mutants was similar to that of wild type at the early stages ( S5 Fig ) , but the ktn1 mutants displayed swollen conical cell apexes after stage 11 ( S5 Fig ) . ROP GTPases have been extensively studied for their functions in polarized cell growth [35 , 48 , 49] , but their roles in regulating the morphogenesis of conical cells remain unknown . KTN1 is activated by ROP6 GTPase to restrict the indentation outgrowth of leaf pavement cells [28] . We investigated whether ROP GTPases contribute to conical cell development . A previous study has shown that ROP GTPases have redundant functions during petal growth , and that neither the single rop2 or rop6 mutant had an altered petal phenotype , whereas the rop2 rop6 ROP4 RNAi plants , generated by transforming a specific ROP4 RNAi construct into the rop2 rop6 double mutant , had severe petal phenotypes [50] . Three rop2 rop6 ROP4 RNAi lines ( referred to as rop2 rop6 ROP4i ) that have been shown to have significantly decreased ROP4 transcriptional levels [50] were used for phenotype analysis of conical cells . Our results showed that all three rop2 rop6 ROP4 RNAi lines had increased radial swelling of conical cell apexs but displayed no change in cell heights compared to the wild type ( Fig 3 ) ; this phenotype is less severe than that of the ktn1 mutants . SPIKE1 ( SPK1 ) is a dock homology region 2 ( DHR2 ) -type ROP guanine nucleotide exchange factors ( ROPGEF ) and has been reported to function upstream of ROP GTPases [50 , 51] . We therefore investigated the role of SPK1 during conical cell development by analyzing the spk1-4 mutant , which was predicted to have aberrant messenger RNA splicing [50] . Our results showed that the spk1-4 mutant also displayed swollen apexes of conical cells ( Fig 3 ) , as observed in the rop multiple mutants . Together , these findings suggest that SPK1 , ROP GTPases , and KTN1 may function in the same pathway in the regulation of the final shape formation of conical cells . To investigate the cellular mechanism by which KTN1 affects the morphogenesis of conical cells , we monitored microtubule organization patterns at different stages of conical cells via live imaging of A . thaliana plants expressing green fluorescent protein ( GFP ) -tagged α-tubulin 6 ( GFP-TUA6 ) [52] in the control and the ktn1-4 mutant . We observed the organization of microtubule arrays in the serrated shape of conical cells from folded petals . We used circular statistics to collect quantitative data by quantifying the orientation angle and anisotropy of microtubules via FribrilTool [53] , which was used for the quantification of the orientation and anisotropy of fibrillar structures in a given region of interest ( ROI ) from raw images using the software ImageJ . The average fibril orientation is defined by the circular average of the tangent direction in the ROI region , and the circular variability of tangent directions defines the score of the fibril array anisotropy [53] . Our results showed that , at the early developmental stages , wild-type conical cells observed from folded petals exhibited a network of microtubule arrays that were randomly oriented ( Fig 4A , 4C and 4D ) , whereas at later development stages , conical cells with sharpening apexes were associated with transverse microtubule arrays ( Fig 4A , 4C and 4D ) . By contrast , ktn1-4 mutant cells had randomly oriented microtubule arrays at both the early and late developmental stages ( Fig 4B–4D ) . We also observed microtubule arrays via maximum projections of Z stacks from the top view of non-folded petals , and found that wild-type cells exhibited microtubule arrays with random orientation at early stages but well-ordered circumferential orientations at later stages ( Fig 5A , 5C and 5D ) . By contrast , the ktn1-4 mutant cells had random microtubule arrays at both early and late developmental stages ( Fig 5B–5D ) . Furthermore , we visualized microtubule arrays configuration via 3D reconstruction of conical cells from the top view of non-folded petals . We examined patterns of microtubule arrangements in detail throughout development stages 8–14 . Similarly to the observation in serrated conical cells from folded petals , microtubule arrays in wild-type conical cells were randomly oriented at the early developmental stages ( S6A Fig ) , and then became increasingly ordered during later development stages ( stages 12 to 14 ) ( S6A Fig ) . Highly ordered transverse microtubule rings encircling wild-type conical cells were found at stage 14 ( S6A Fig ) . By contrast , loss of KTN1 function prevented random microtubule networks from shifting into transverse microtubule rings encircling conical cells ( S6B Fig ) . We next examined microtubule organization patterns in both petal abaxial epidermal blade cells and claw cells; these epidermal cells have flat shape [50] . Cortical microtubule arrays in wild-type abaxial blade cells were randomly oriented and a few transverse microtubules were associated with indentation regions of these cells , and microtubules in the ktn1-4 abaxial blade cells were disordered compared with the wild type ( S7A and S7B Fig ) . By contrast , microtubule arrays in wild-type petal claw cells were highly parallel and transversely oriented to the axis of cell elongation ( S7C and S7D Fig ) . Microtubules in the ktn1-4 petal claw cells were organized into “net-like” arrays in which microtubules display no particular alignment ( S7C and S7D Fig ) . Taken together , KTN1-dependent microtubule organization patterns appear to differ between cell types , which is important for shaping diverse plant epidermal cells . Previous results have shown that actin filaments play pivotal roles during plant cell shape formation and that trichome mutants with defects in the plant actin-related protein ARP2/3 complex serve as an excellent system for the study of actin-dependent cell morphogenesis [54–56] . We investigated whether the arp2 mutant showed defects in conical cell shape . Consistently with previous reports , we found that arp2 mutant plants had swollen trichomes , with stunted branch outgrowth ( Fig 6A and 6B ) . However , the conical cell shape in the arp2 mutant was similar to the wild type ( Fig 6C–6F ) . A previous report has shown that both transverse microtubule rings and the cortical actin cap are required for branch tip sharpening during leaf trichome development in wild type , and that these cytoskeletal organization patterns are disrupted in the loss-of-function mutant of KCBP ( kinesin-like calmodulin-binding protein ) that has trichomes with swollen tips [57] . We next investigated whether the kcbp mutant showed tip defects in conical cells . Consistently with previous reports , we found that the kcbp mutant trichomes with two branches showed swollen branch tips ( S8 Fig ) ; however , the shape of conical cells was similar to the wild type ( S8 Fig ) . We next investigated whether the ktn1-4 mutant showed defects in trichome branch tips . Strikingly , we found that the ktn1-4 mutant had two-branched leaf trichomes displaying no swollen tips compared with the wild type ( S9 Fig ) . Taken together , our findings suggest that KTN1-dependent microtubule organization is involved in the tip sharpening of conical cells but is not essential for the branch tip sharpening during leaf trichome development . We next examined the organization patterns of actin filaments . Live-cell imaging of the actin marker GFP-fABD2 line [58] showed that actin filaments displayed a disordered array in conical cells throughout development stages 7–14 ( Fig 6G and 6H and S10 Fig ) . In addition , actin filaments cables became thick and dense at late stages during conical cell development ( Fig 6G and 6H ) . Surprisingly , over the course of conical cell development , we could not observe an apical cap of actin filaments ( Fig 6G and 6H and S10 Fig ) , which is a typical feature of diverse cell types , such as root hairs , leaf trichomes , and zygotes [59–61] . To examine the respective roles of microtubules and actin , we investigated how their inhibitors influenced conical cell development . We depolymerized the microtubules and actin with the use of the microtubule polymerization inhibitor ( oryzalin ) and the actin polymerization inhibitor [latrunculin A ( LatA ) ] , and analyzed their influence on cell morphologies . Both the filamentous pattern of the microtubule and the actin signal diffused when oryzalin or LatA were applied ( S11A Fig and Fig 6I ) , confirming that these inhibitors were efficient in our experimental setup . We next examined the effects of these inhibitors on conical cell morphologies . Floral buds before stage 8 were immersed in a solution containing 30 μg/ml oryzalin for 5 min . To prevent repolymerization of the microtubules , the same treatment was repeated once or twice 24 h later . Three situations were investigated , where the oryzalin treatment was applied one , two , and three times . To observe the geometry of cells , cell phenotypes of mature petals at stage 14 after the oryzalin treatment were analyzed . In contrast to the control treatments , the application of oryzalin had significant effects on cell morphology , causing increased radial swelling at the tip of conical cells with increased cone angle and reduced cell height ( Fig 7 ) . In addition , visualization of conical cells via both 3D reconstruction and scanning electron microscope further confirmed that oryzalin treatment caused the isotropic growth of the tip of the conical cell ( Fig 7 and S11B Fig ) . By contrast , treatment with LatA did not cause significant alterations on conical cell morphology ( Fig 7J ) , suggesting that actin filaments may not play a major role in the final shape formation of conical cells . Furthermore , depolymerizing actin filaments by treatment with LatA had no effect on the configuration of transverse ring of microtubules ( S12 Fig ) , suggesting that actin is not required for organizing microtubules during conical cell development .
In this study , we presented a confocal laser scanning microscopy-based imaging technique that can be used for the quantitative study of conical cells' geometry in A . thaliana . Our results showed that petal folding had no effect on the geometry of conical cells by comparing the serrated images generated by the side view of conical cells from petal folding with images of histological sections of fixed samples . In addition , petal folding in our experimental condition ( with gently folding the petal ) , allowing for the side view of conical cells , did not alter microtubule organization patterns . Therefore , the use of the live-confocal imaging technique will open exciting new avenues of research to study the genetic and molecular mechanisms controlling the final shape formation of conical cells . Although the mechanisms underlying microtubule organization have been extensively studied in diverse cell types [24 , 25 , 57 , 62–64] , the configuration of microtubule arrays in petal conical cells remains unknown . Live-cell imaging of GFP-TUA6 to study microtubule organization in A . thaliana petal conical cells suggests that in the early stages , microtubule arrays are randomly oriented , which results in isotropic expansion of conical cells , and that at later stages , microtubule arrays are reoriented into well-ordered circumferential arrays , which leads to an increase in tip sharpening of the conical apex over the course of the conical cell development , and thus forming the final characteristic conical-shaped cell with an average cone angle of 80° . We propose that conical cell is an excellent model system for investigating the spatio-temporal orientation of microtubule arrays . Therefore , conical cell shaping could become a valuable complement to other more popular systems used to study cell shape , such as leaf pavement cells [35] . Our results showed that the microtubule organization in conical cells appears essentially identical to that observed in leaf trichomes , whose morphogenesis is cooperatively regulated by microtubules and actin filaments [57 , 60] . By combining genetic and pharmacological experiments using specific inhibitors for different cytoskeletal elements , our results suggested that microtubules but not actin filaments play pivotal roles in conical cell development . Strikingly , a cap of actin filaments , which is frequently found in diverse cell types in plants , such as root hairs , leaf trichomes , pollen tubes and zygotes [59–61] , was not observed in the growth apexes of conical cells during cell development . A previous report has shown that the actin-related protein ARP2/3 complex drives an actin meshwork that functions within a tip-localized , microtubule-depleted region to regulate cell wall anisotropy and leaf trichome morphogenesis [65] . Our findings showed that the arp2 mutant and the kcbp mutant showed normal conical cell shape and that depolymerizing of actin filaments had no effect on the configuration of transverse ring of microtubules in mature conical cells , suggesting that actin filaments is not critical for conical cell development . Thus , we propose that distinct mechanisms are required for the cytoskeletal control of leaf trichome morphogenesis and conical cell development . Given that actin appears more important for the initial outgrowth , while microtubules are more important for later elongation during leaf trichomes and root hairs development , we cannot exclude the roles of actin filaments in the initial conical outgrowth during conical cell development . Our findings showed that KTN1 mainly functions at late development stages to generate parallel circumferential microtubule arrays , which may lead to the tip sharpening of the conical cell apex over the course of development , probably through affecting cell wall patterns [20–22] . Previous studies have shown that the activity of KTN1 is precisely controlled by two microtubule-associated proteins in A . thaliana: RIC1 and SPR2 [28 , 30] . RIC1 , an effector of ROP6 GTPase , activates KTN1 to promote parallel ordering of microtubule arrays in leaf pavement cells [28 , 29] . SPR2 accumulates at the microtubule crossover sites to prevent severing by KTN1 , allowing randomly oriented microtubule arrays to persist [30] , suggesting that SPR2 may also function to activate KTN1 during conical cell development . It is more likely that SPR2 is more mobile in conical cells ( especially during later development stages ) as found in leave petiole cells , which is required for the activation of KTN1 during the tip sharpening of conical cells at later stages . Our results showed that SPK1 and ROP GTPases function in the regulation of the final characteristic shape formation of conical cells , suggesting that SPK1 and ROP GTPase may be required for the spatio-temporal activation of KTN1 during conical cell development . Given that our results showed that both SPK1 and ROP GTPases ( ROP2 , ROP4 and ROP6 ) had more modest effects on cone angle of conical cells in comparison with KTN1 , it is possible that other ROPs may also participate in conical cell development and that other novel signaling components that need to be identified in future studies are also required for the activation of KTN1 . Future studies should aim to investigate the mechanisms by which KTN1's activity is spatio-temporally regulated during conical cell development . In addition , it will be important to examine the contributions of patterns of cell wall stiffness to the morphogenesis of conical cells .
A . thaliana ecotypes Col-0 and WS were used in this study . The ktn1-4 ( SAIL_343_D12 ) , arp2 ( SALK_003448C ) , and kcbp-1 ( SALK_017886C ) were obtained from the Arabidopsis Biological Resource Centre . Seeds were sterilized , plated on Murashige and Skoog medium agar petri dishes supplemented with 1% ( w/v ) sucrose , and germinated . Plants were grown in a growth room at 22°C under 16-hr light/8-hr dark cycles . To visualize the geometry of conical cells , A . thaliana petals from flowers at stages 10 to 14 were carefully dissected . We developed a rapid imaging method for observing the serrated shape of conical cell using fluorescent microscopy . Conical cells protrude outwards from the plane of the adaxial epidermis , so the lateral cell walls that are not in the plane of the focal axis of the confocal microscope cannot be observed from the top view of a faced-up petal sample . To make a side view of the conical cells , petal blades were transversally folded back to expose the adaxial interface to the fold , thus allowing observation of the serrated shape of conical cells . The petal samples were put onto a micro slide and then were folded back . A cover slide was slightly put on the samples . Then , a staining solution containing 10 μg/ml propidium iodide was added through the cover slide edge and samples were incubated for at least 10 min . Then , the serrated shape of cones was visualized at the position of the folded interface by fluorescent microscopy . This fast observation of conical cells enables high-throughput genetic screening for mutants with abnormal conical cell shapes . For quantifications of cell shape , samples were imaged with a Zeiss LSM 880 confocal laser scanning microscope . Z stacks of optical sections were taken and projected on a plane to generate a quantifiable serrated geometry of conical cells . For imaging 3D geometry of conical cells , Z stacks of confocal images from the distal regions of PI-stained petal samples from the indicated development stages were taken from the top view along their Z axis at steps of 0 . 8 μm , and were used to reconstruct the 3D images using Zeiss LSM 880 software . For observations of cortical microtubules , petal samples stably expressing GFP-Tubulin6 were imaged by confocal scanning , and serial optical sections were taken at 0 . 6 μm increments with a 63× oil lens , and then projected on a plane ( i . e . maximum intensity ) , or were used to reconstruct the 3D images using Zeiss LSM 880 software for 3D view of the configuration of microtubule arrays . Approximately 5 , 000 seeds of wild-type Col-0 were mutagenized using ethyl methane sulfonate . M2 seeds were harvested from self-fertilized M1 plants individually , and M2 lines were screened for altered phenotypes of petal conical cells in comparison with wild-type Col-0 . Candidate mutants were backcrossed to Col-0 three times before further phenotype analyses . For complementation experiments , the promoter region of KTN1 gene was amplified by PCR from Col-0 genomic DNA using the following primers: KTN1Pro-EcoR1-F:5’ GCGAATTCTTTCTTGTATCCAATAAAGTGACCAC 3’ , KTN1Pro-Sac1-R: 5’GCGAGCTCAAAACAAAATCAAGGGTTCCGA 3’ . And the KTN1 coding sequence was amplified by PCR from Col-0 total mRNA reversed cDNA using the following primers:KTN1CDS-Sac1-F: 5’GCGAGCTCATGGTGGGAAGTAGTAATTCG 3’ , KTN1CDS-Sal1-R: 5’GCGTCGACTTAAGCAGATCCAAACTCAGAG3’ . The resulting DNA fragments were cloned into the pCambia1300 vector . The resulting pKTN1::KTN1 was introduced into the ktn1-6 mutant by Agrobacterium tumefaciens-mediated floral dip transformation . For oryzalin treatment , a 30 mg/ml oryzalin ( Sigma , 36182 ) stock solution dissolved with DMSO was prepared ( working solution: 30 μg/ml oryzalin containing 0 . 01% silwet L-77 ) . Floral buds at stage 8 that had flat epidermal cells were immersed in the solution containing 30 μg/ml oryzalin for 5-min treatment . To prevent repolymerization of the microtubules , the same treatment was repeated 24 h later for twice . For Latrunculin A treatment , a 100 μg/mL Latrunculin A ( Sigma , L5163 ) stock solution dissolved with DMSO was prepared ( working solution: 0 . 5 μg/mL Latrunculin A containing 0 . 01% silwet L-77 ) . Floral buds at stage 8 that had flat adaxial epidermal cells were immersed in the Latrunculin A working solution for 5-min treatment . To prevent repolymerization of the microfilaments , the same treatment was repeated twice24 h later . To observe petal epidermal cells , detached petal samples were directly observed with a TM-3000 table-top scanning electron microscope ( Hitachi ) equipped with a cool stage . For the quantification of the geometric parameters of conical cells , cell heights , cell angles , and gap heights were manually measured using ImageJ software . More than 300 cells of 6 petals from independent plants were measured . For the quantification of the average orientation and anisotropy of microtubule arrays in wild-type and ktn1-4 conical cells . FribrilTool [53] , an ImageJ plug-in , was used for quantification of the orientation angle and the anisotropy of microtubule arrays in a given region of interest of the wild type and ktn1-4 . Anisotropy values range from 0 to 1 . 0 indicates pure isotropy , and 1 represents pure anisotropy . Statistical analyses were performed using student’s t test , and one-way or two-way ANOVA . Data were represented as the mean ± SEM from at least three independent experiments . Not significant P > 0 . 05 , 0 . 01 <*P < 0 . 05 , 0 . 001<**P < 0 . 01 , ***P < 0 . 001 . Sequence data from this article can be found in the Arabidopsis Genome Initiative or GenBank/EMBL databases under the following accession numbers: AT1G80350 ( KTN1 ) , AT1G20090 ( ROP2 ) , AT1G75840 ( ROP4 ) , AT5G65530 ( ROP6 ) , AT4G16340 ( SPK1 ) , AT3G27000 ( ARP2 ) , AT5G65930 ( KCBP ) . | How cells achieve their final shapes is a fundamental question in biology . Most flowering plants have special conical-shaped petal epidermal cells that are thought to attract pollinators , but the molecular and genetic mechanisms that control conical cell shape remain unknown . In this study , we developed a live-confocal imaging approach for the quantitative study of conical cell morphogenesis . Through genetic screens , we showed that A . thaliana KTN1 , ROP GTPases , and SPIKE1 are required for conical cell shaping . Live-cell imaging showed that loss of KTN1 prevented random microtubule networks from shifting into well-ordered microtubule arrays at later developmental stages , which is correlated with the tip sharpening of conical cells . Moreover , genetic and pharmacological data suggested that microtubules but not actin are required for conical cell shaping . Together , our findings provide significant insights into the spatio-temporal organization of microtubules that controls conical cell development . | [
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"organism",... | 2017 | Spatio-temporal orientation of microtubules controls conical cell shape in Arabidopsis thaliana petals |
Discovery and characterization of functional RNA structures remains challenging due to deficiencies in de novo secondary structure modeling . Here we describe a dynamic programming approach for model-free sequence comparison that incorporates high-throughput chemical probing data . Based on SHAPE probing data alone , ribosomal RNAs ( rRNAs ) from three diverse organisms – the eubacteria E . coli and C . difficile and the archeon H . volcanii – could be aligned with accuracies comparable to alignments based on actual sequence identity . When both base sequence identity and chemical probing reactivities were considered together , accuracies improved further . Derived sequence alignments and chemical probing data from protein-free RNAs were then used as pseudo-free energy constraints to model consensus secondary structures for the 16S and 23S rRNAs . There are critical differences between these experimentally-informed models and currently accepted models , including in the functionally important neck and decoding regions of the 16S rRNA . We infer that the 16S rRNA has evolved to undergo large-scale changes in base pairing as part of ribosome function . As high-quality RNA probing data become widely available , structurally-informed sequence alignment will become broadly useful for de novo motif and function discovery .
RNA is a central participant in gene expression and regulation [1] . However , for a vast majority of RNA transcripts , the positions and roles of higher-order structure are unknown . Sequence comparison approaches can be powerful tools in the discovery and annotation of functional RNA motifs . In related functional RNAs , critical structural elements are conserved despite changes in primary sequence . As RNA structure appears to be more conserved than primary sequence [2 , 3] , functional RNA discovery and transcriptome annotation can be improved by taking into account RNA structure . Currently , structure-guided RNA sequence comparison approaches perform poorly and are limited by the pervasive difficulty of predicting RNA structures from sequence alone [4–6] . Moreover , optimization and benchmarking of current structure prediction approaches are confined to known RNA structure motifs , themselves limited to structures that are amenable to high-resolution structure characterization or comparative sequence analysis . RNA structure modeling is thus biased by a small number of well-characterized elements . RNA comparison and alignment that considers some model-free metric of underlying structure is an attractive alternative to comparisons that use ab initio or concurrent structure prediction . RNA chemical probing is structurally robust and is not limited by the current , relatively poor , understanding of RNA structure . The SHAPE structure probing approach [7 , 8] interrogates virtually all nucleotides of any RNA target . The adaptation of RNA chemical probing approaches to readout by massively parallel sequencing allows for high-throughput analysis and is rapidly advancing toward transcriptome-scale assays [9 , 10] . In this work , we introduce and evaluate a sequence comparison approach that considers chemical probing data . We find that SHAPE-directed alignment , performed entirely independently of base identity information , generates sequence alignments with accuracies comparable to traditional nucleobase identity-directed methods . Approaches that consider both SHAPE reactivities and base identity improve accuracy relative to approaches considering base identity or chemical probing data alone . Chemical probing data were compared using a simple , general pair-wise scoring function that is broadly applicable to diverse sequence comparison methods and should significantly facilitate discovery of novel structurally conserved functional RNA motifs in large RNAs . SHAPE-directed alignments were then used to predict RNA secondary structures conserved among diverse ribosomal RNAs . Novel base pairing patterns were identified in 16S rRNA , suggestive of new RNA-based features of ribosome function .
Ribosomal RNA was used for development and evaluation of SHAPE-dependent RNA structure alignment . Ribosomal RNA has been extensively characterized: Currently 83% of RNA nucleotides in high-resolution structures in the RCSB Data Bank belong to ribosomal RNAs . Thousands of ribosomal RNA sequences have been curated and aligned , with secondary and tertiary structures predicted based on covariation analysis [11] . Moreover , the diverse secondary and tertiary structure elements found in ribosomal RNA form the basis for much of our structural knowledge of RNA . RNA structure analysis and modeling methods based on analysis of ribosomal sequences have proven robust when extended to other RNAs [4 , 12 , 13] . Ribosomal RNA samples were obtained from three cultured organisms , eubacteria Escherichia coli and Clostridium difficile and archaea Haloferax volcanii . Differences among these organisms are reflected in the distinct culturing and cell lysis conditions required for each ( see Methods ) . The ribosomal RNAs from these organisms are highly diverse; compared to E . coli , C . difficile and H . volcanii have percent nucleotide identities of only 72 . 6% and 59 . 7% , respectively . The three ribosomal samples were analyzed by SHAPE probing in which local nucleotide structural flexibility at a given position is determined by the extent of modification by a chemical probe [7] . Quantitative , nucleotide-resolution SHAPE reactivity values were determined using our recently described mutational profiling ( MaP ) approach , in which chemical modifications are recorded as mutation rates in the cDNA products generated during reverse transcription of chemically-modified RNAs [10] . Chemical modification-induced mutations are quantified with nucleotide resolution using massively parallel sequencing . SHAPE-MaP data for E . coli ribosomal RNA were reported previously [10]; SHAPE-MaP data for C . difficile and H . volcanii were newly obtained in this work . We first characterized the relationship between SHAPE reactivities for related RNA nucleotides in accepted sequence alignments . Related nucleotides for the ribosomal RNAs studied here were defined using annotated sequence comparisons from the Comparative RNA Web Site and Project ( CRW ) [11] . Related nucleotides were taken as nucleotide pairs in CRW alignments . For the 16S and 23S ribosomal RNAs , 24 , 467 nucleotide pairs were considered; for each nucleotide pair , we calculated absolute differences in SHAPE reactivities ( Fig 1A , in red ) . The distribution of SHAPE reactivity differences in related RNA nucleotides followed an exponential decay . When SHAPE data were randomly resorted , differences in SHAPE reactivities between two related nucleotides were , on average , smaller than the differences between unrelated nucleotides ( Fig 1B , in blue ) . The distribution describing related nucleotides is significantly different from the distribution describing randomly resorted nucleotide pairs ( p-value< 10-6 , Student's t-test ) . Global SHAPE-dependent sequence comparisons were performed using a pair-wise dynamic programming algorithm ( see Methods ) [14] . The algorithm uses recursion to align two sequences based on a pair-wise scoring function between individual nucleotides . The algorithm also incorporates penalties based on gap openings and gap extensions , where gaps are unaligned regions of sequence . We implemented a SHAPE comparison scoring function where small differences in SHAPE reactivities were given high ( favorable ) scores . Alignments were ultimately scored as the sum of individual SHAPE comparison scores and gap penalties over the entire alignment . Pair-wise SHAPE comparisons were scored by a linear function ( Fig 1B ) , and scoring function parameters and gap opening and extension penalties were optimized by an exhaustive parameter search . Parameters were selected on the basis of sensitivity of alignments ( fraction of aligned nucleotides shared with the accepted alignment ) generated for 16S and 23S ribosomal RNAs relative to CRW pairwise alignments [11] . SHAPE-based alignments were performed for all 16S and 23S ribosomal RNA pairs ( Fig 2 ) . The accuracies of the SHAPE-only alignments were compared to global sequence alignments obtained with the Needle algorithm [14 , 15] . Sequence alignments based only on SHAPE data ( without using any sequence information ) were comparable in quality to Needle-based sequence alignments ( Table 1 ) . For example , for 16S rRNA , SHAPE-based alignments had sensitivities of 83% and 71% for alignments of E . coli to C . difficile and to H . volcanii , respectively; whereas , conventional sequence identity-based alignments using the Needle algorithm had sensitivities of 84% and 72% , respectively . For 23S rRNA , SHAPE-based alignments performed well but not quite at the level of sequence-based alignment ( Table 1 ) . An additional scoring term considering base identity was then included in the alignment algorithm , allowing sequence comparison based on both base identity and SHAPE structure reactivity values . In a pairwise comparison , if two nucleotides had the same base identity , the pair was scored as a match , and a match bonus was included in the scoring function . Otherwise , a mismatch penalty was included . These scores were added to the values generated by the SHAPE comparison function . The score terms associated with both matches and mismatches were optimized by a parameter search . Gap opening and gap extension penalties were also re-optimized given this new scoring system . Alignments considering both sequence identity and SHAPE data showed significant improvements relative to alignments considering SHAPE structure data or base identity alone ( Table 1 ) . For 16S rRNA , alignments of E . coli to C . difficile and to H . volcanii had sensitivities of 94% and 92% , respectively , when both base identity and SHAPE data are considered . The E . coli 23S rRNA alignments to C . difficile and to H . volcanii had sensitivities of 89% and 84% , respectively . We note that we performed benchmarking and parameter optimization using the same RNAs . This is because there are very few large RNA molecules with accepted sequence alignments , especially for culturable organisms . In independent work , we have applied SHAPE-based alignment , using the parameters defined using our three-species ribosomal RNA training data , to align single-stranded HIV-related viral RNA genomes . The viral RNAs constitute a fully independent test set . Based on nucleobase identity and SHAPE reactivities , HIV-1 strain NL4-3 ( 9 , 173 nts ) and SIVcpz strain MB897 ( 9 , 167 nts; 77% sequence identity ) aligned with a sensitivity of 97% relative to extensively manually curated and hand-annotated alignments ( see following companion article in this issue ) . Pairwise SHAPE-based alignments were also used to generate multiple sequence alignments [16] . Alignment quality did not change significantly with the multiple sequence alignment ( Table 1 ) . Alignment quality may increase in future applications with larger numbers of diverse sequences . Lack of significant change also likely reflects that the quality of the pairwise alignments was already high , leaving relatively little room for improvement . Both sequence comparisons and SHAPE data have been successfully used to direct RNA secondary structure modeling [17] . Given that SHAPE-based alignments effectively combine both of these classes of information , we examined the usefulness of using SHAPE-based alignments to model secondary structures . Sequence comparison-based secondary structure predictions are highly dependent on alignment quality [18 , 19] . Therefore , success in secondary structure prediction would offer further support for model-free SHAPE-based alignment . The SHAPE-defined sequence alignments were incorporated as arguments for secondary structure modeling using the RNAalifold algorithm in the Vienna RNA package [20–22] . RNAalifold uses a pseudo-free energy potential to bias predictions based on covariation information . In this scheme , base pairs supported by covariation are given a free-energy bonus . For this work , RNAalifold was updated to accept SHAPE reactivities as an additional pseudo-free energy term [4 , 23] . Free energy calculations with RNAalifold were therefore the sum of three terms corresponding to thermodynamic parameters , sequence covariation , and SHAPE reactivity . A consensus structure from the sequence alignment was obtained from a partition function calculation as base pairs with pairing probabilities greater than 95% . Overall , ~77% of base pairs were identified in this first step ( reported as sensitivity values in Table 2 , column 4 ) . Consensus base pairs identified in the first step were in turn used to constrain modeling of individual structures for each RNA in a given alignment , allowing additional base pairs to be identified . Finally , structure prediction was performed by free-energy minimization that included a pseudo-free energy term based on SHAPE reactivities . Structure models were generated for 16S and 23S ribosomal RNAs ( Fig 3; S1 and S2 Figs ) . The modeled structures were compared to those based on covariation models in the CRW . A local refolding allowance of 5 nucleotides was used in sensitivity and positive predictive value calculations ( Methods ) to allow for modest local rearrangements of base pairs , which we find are broadly supported by experimental SHAPE reactivities ( Fig 3; S1 and S2 Figs ) . All SHAPE reactivity-based structures had sensitivities greater than 90% relative to the accepted structures , indicating that models were of high accuracy ( Table 2 , column 5 ) . Given the strong dependence of covariation-based prediction approaches on alignment quality , this successful modeling further validated the strong utility of SHAPE-structure alignment of RNA sequences . Importantly , a significant subset of base pairs in the reference covariation models were incompatible with observed SHAPE reactivities . Of base pairs in reference covariation models not supported by SHAPE data , a significant number involve one or more nucleotides with SHAPE reactivities greater than or equal to 0 . 5 ( E . coli 16S , 70%; C . difficile 16S , 64%; H . volcanii 16S , 39%; E . coli 23S , 46% ) . This suggests that these nucleotides are weakly base paired or form alternate structures under the experimental conditions used in this work . Secondary structure predictions based on SHAPE-directed alignment were compared with sequence-only predictions and with predictions directed by sequence-only alignment or SHAPE reactivities ( Table 2 ) . Secondary structure predictions for ribosomal RNA based on sequence alone have sensitivity values of roughly 65% ( predictions by RNAfold of the Vienna RNA package ) . At this accuracy , a bare majority of base pairs are predicted correctly , and it remains difficult to develop meaningful biological hypotheses regarding RNA structure . When we used sequence-only alignments to constrain secondary structure prediction using RNAalifold [21] , E . coli and C . difficile 16S rRNA predictions improved ( Table 2 ) , but H . volcanii 16S and E . coli 23S rRNA predictions actually had lower sensitivities . The mixed results of structure modeling based on sequence-only alignments reflect the sensitivity of a prediction to the accuracy of the initial alignment . Secondary structure predictions directed by SHAPE reactivities improve sensitivity relative to predictions based only on thermodynamic parameters [4 , 23] , and models that consider sequence alignment and SHAPE reactivities had higher sensitivity and positive predictive values than models considering SHAPE data alone ( Table 2 ) .
Functional RNA elements commonly exhibit conservation at the levels of both sequence and structure , and wide variations in primary sequence can be compatible with nearly identical higher-order structures [2 , 3] . Thus , incorporating a model-free metric for RNA structure , such as SHAPE reactivity , holds significant promise in functional RNA motif discovery . In the case of the ribosomal RNAs , sequence alignments based on SHAPE reactivities were roughly as accurate as approaches that used only sequence information ( Table 1 ) . When both SHAPE reactivities and base identity were considered together , alignment quality increased . Alignments taking into account both SHAPE reactivities and base identity achieved sensitivities exceeding 90% for alignments of E . coli ribosomal RNA to C . difficile sequences . SHAPE reactivities provide information that is orthogonal to the sequence of nucleobase identities [24] . SHAPE-based alignments were performed with a dynamic programming algorithm using a pair-wise scoring system , analogous to the substitution matrices commonly used in standard alignment approaches . Given this , the scoring system should be broadly applicable to other sequence alignment approaches , including methods that use heuristic scoring systems , such as BLAST [25] , or probabilistic approaches , such as trained Markov-based alignment methods [26] . Given the success using datasets generated efficiently by massively parallel sequencing using the MaP approach [10] , SHAPE-based alignments will likely prove broadly useful in future high-throughput structure-based RNA motif discovery and structure modeling . Secondary structure models , generated from SHAPE-based alignment , include the vast majority of base pairs in the accepted covariation-based models of the 16S and 23S ribosomal RNAs ( Fig 3 and Tables 1 and 2 ) . However , there was notable localized disagreement between the alignment-based predictions from this work and covariation models in two regions in the 3' major domain of 16S rRNA: in helix 36 ( h36; Figs 3 and 4 ) and in the decoding site ( h28 and h44; Figs 3 and 5 ) . These alternate structures are predicted to exist in each of the E . coli , C . difficile , and H . volcanii 16S rRNAs . Moreover , in each case , the alignment-directed model shows much better agreement with the experimental SHAPE reactivities than does the covariation model . For example , positions corresponding to base pairs in h36 in the covariation structure had high SHAPE reactivities ( Fig 4B , in red ) , indicating structural flexibility . Similarly , many nucleotides in the h28 and h44 helices in the covariation model were highly reactive to the SHAPE reagent and were not present in the alignment-based consensus model ( Fig 5B ) . For the h28 and h44 helices , the SHAPE-based alignment and the underlying individual nucleotide reactivities strongly support a novel alternate base-paired secondary structure ( Fig 5 ) . Taken together , the SHAPE reactivity data indicate that these alternate structures describe the conformation predominantly assumed by the protein-free rRNA sampled during chemical probing . Exclusion of these regions from the E . coli 16S rRNA sensitivity calculations increased the sensitivity of the secondary structure prediction from 93 . 8% to 96 . 8% ( Table 2 , column 6 ) . Ribosomal RNAs were assayed in the absence of protein to generate the SHAPE data used in this study . Total cellular RNA was obtained from each organism under conditions that avoided denaturing or heating steps and were thus supportive of maintenance of native-like RNA structure . We therefore infer that the alternate 16S secondary structure discovered in this work describes a low-energy state that is readily sampled by protein-free ribosomal RNA . Crystallographic studies of the ribosomal subunits are in agreement with the structure inferred by covariation analysis . However , given that the alternate conformation predominates for the free RNA based on SHAPE analysis , this alternate state may be adopted by ribosomal RNA prior to small subunit assembly and may reflect a conformation that occurs during small subunit assembly or during specific phases of the translation cycle . This view is supported by nucleotide-resolution chemical modification and interference assays that suggest that nucleotides in h36 and in the decoding site ( h28 and h44 ) undergo a conformational change during conversion of the 30S subunit from an inactive to active conformation [27] and are involved in rate determining steps during 30S subunit assembly [28 , 29] . In addition , helices in the decoding region ( h28 and h44 ) are conspicuously lacking base-pair level covariation [30] . The striking absence of covariation support is consistent with the idea that these helices are subject to additional structural constraints beyond formation of a single set of conventional helices and instead form additional conserved alternate secondary structures . Critically , no covariation or other evidence contradicts the alternate base pairs proposed here . Strikingly , all regions that structure-directed alignment suggests form alternate structures in the 16S rRNA are located close to each other in three-dimensional space , in the neck of the intact small ribosomal subunit ( Fig 3 , inset ) . Given that these alternate structures occur in and near the codon-anticodon decoding site , we propose that these structures form a switch involving low energy base-pairing rearrangements important for regulation of translation . The strategies developed here allow for highly accurate , structure-informed alignments of large ( Table 2 ) and likely small ( Fig 2 ) RNAs and are accurate even for RNAs that show high levels of sequence divergence . These alignments may in turn be used to predict consensus secondary structures with high accuracy . Given that structural information is derived from the SHAPE-MaP high-throughput strategy for nucleotide-level quantitation of chemical probing data [10] , this approach for structure-informed alignment and secondary structure modeling will be broadly useful for large-scale analysis of entire transcriptomes and large families of functional RNA molecules . Using SHAPE-structure informed alignments , we discovered structural rearrangements in the base pairing patterns of 16S that are conserved in three diverse organisms . These structural rearrangements are likely to have mechanistic functions in ribosome assembly or regulation of translation . This analysis of ribosomal RNA indicates that SHAPE-based alignment methods will prove especially powerful in discovering functional motifs in RNA elements with low sequence covariation .
Total E . coli RNA ( DH5α strain ) was prepared as described [4]; SHAPE-MaP data for the ribosomal RNAs were reported previously [10] . C . difficile ( strain 630 ) was grown in BHIS medium [31] at 37°C under anaerobic conditions ( 90% N2 , 5% CO2 , and 5% H2 ) [32] to an OD600 of 1 . 0 . Cells were collected by centrifugation ( 10 min , 4°C , 4000×g ) . The pellet was washed with 1× TE [10 mM Tris ( pH 8 . 0 ) , 1 mM EDTA] . The supernatant was discarded , and the pellet was allowed to air-dry for 5 minutes . To lyse the cells , 1 mL TRIsure ( Bioline ) was added to the pellet . The resultant mixture was incubated at room temperature for 5 minutes . The mixture was then transferred to a vial containing 250 μL 0 . 1-mm glass beads . Cells were lysed using a bead beater over two 90 second pulses , with cells held on ice between pulses . The resultant mixture was extracted with 200 μL chloroform , and the aqueous layer was extracted three times with phenol ( pH 8 . 0 ) :chloroform:isoamyl alcohol ( 25:24:1 ) , followed by three extractions with chloroform . The RNA-containing solution was exchanged for folding buffer ( 50 mM Hepes ( pH 8 . 0 ) , 200 mM potassium acetate ( pH 8 . 0 ) , and 5 mM MgCl2 ) using a pre-equilibrated gel filtration column ( G-25 column , GE ) . Growth medium was prepared by bringing 600 ml 30% salt solution [4 M sodium chloride , 150 mM magnesium chloride hexahydrate , 150 mM magnesium sulfate heptahydrate , 100 mM potassium chloride , 5 mM Tris ( pH 7 . 5 ) ] , 5 g bacteriological peptone ( LP37; Oxoid ) , and 1 g yeast extract ( LP21; Oxoid ) to 1 L with deionized water . H . volcanii cells ( strain DS70 ) were grown to an OD600 of 0 . 8 and collected by centrifugation ( 5 min , 4°C , 14000×g ) . Cells were lysed by incubation in low salt solution [220 μL 50 mM Hepes ( pH 8 . 0 ) and 5 mM MgCl2; incubation at 22°C for 5 min , followed by incubation on ice for 5 min] . Following lysis , this solution was extracted three times with phenol ( pH 8 . 0 ) :chloroform:isoamyl alcohol ( 25:24:1 ) , followed by three extractions with chloroform . The RNA-containing solution was exchanged for folding buffer [50 mM Hepes ( pH 8 . 0 ) , 200 mM potassium acetate ( pH 8 . 0 ) , and 5 mM MgCl2] using a pre-equilibrated gel filtration column ( G-25 column , GE ) . Determination of SHAPE reactivity by SHAPE-MaP employs three experiment conditions: chemical modification of native RNA , chemical modification of denatured RNA , and a no-modification control . All chemical modifications were performed using 1-methyl-7-nitroisatoic anhydride ( 1M7 ) [33] . Chemical modification of native RNA and the no-modification control were performed in parallel . To 1× folding buffer [50 mM HEPES ( pH 8 . 0 ) , 200 mM potassium acetate ( pH 8 . 0 ) , and 5 mM MgCl2] was added to a concentrated RNA solution ( 280 ng H . volcanii total RNA or 70 ng C . difficile total RNA; amounts determined using absorption spectroscopy ) to a final volume of 90 μL . The RNA solution was incubated at 37°C for 30 minutes . Following incubation , 10 μL DMSO ( no-modification control ) or 10 μL 100 mM 1M7 in DMSO ( native 1M7-modified sample ) was added to the RNA solution . The RNA solution was then incubated at 37°C for 3 minutes . For the denatured control , 25 μL 4× denaturing control buffer [200 mM HEPES ( pH 8 . 0 ) , 16 mM EDTA] and 50 μL deionized formamide were added to a concentrated RNA solution ( 280 ng H . volcanii or 70 ng C . difficile total RNA ) , and deionized water was added to a final volume of 90 μL . This solution was held at 95°C for 1 minute , and then 10 μL 100 mM 1M7 in DMSO was added; the combined solution was incubated at 95°C for 1 minute . After modification , all three samples were purified by affinity chromatography ( RNeasy Min-Elute; Qiagen ) with elution into 22 μL buffer . To prepare sequencing libraries , the purified RNA samples were first fragmented; 20 μL of RNA solution was combined with 30 μL fragmentation buffer [250 mM Tris ( pH 8 . 3 ) , 375 mM KCl , 15 mM MgCl2] , incubated at 94°C for 4 minutes , and then transferred immediately to ice . Fragmented RNA was purified using a G-25 column ( GE ) with elution into 1× TE [10 mM Tris ( pH 8 . 0 ) , 1 mM EDTA] . Following fragmentation , reverse transcription was performed using a 20-μL aliquot of fragmented RNA and 2 μL random DNA nonamers ( 200 ng/μL ) . The solution was incubated at 65°C for 5 minutes and then placed on ice . To this solution , 7 μL reaction buffer [286 mM Tris ( pH 8 . 0 ) , 429 mM KCl , 57 mM DTT , 2 . 9 mM dNTP mix ( dATP , dCTP , dGTP , and dTTP , 2 . 9 mM each ) ] , 4 μL 60 mM MnCl2 , and 5 μL water were added . The solution was pre-incubated at 25°C for 2 minutes prior to adding 2 μL Superscript II ( Invitrogen ) . The reaction was incubated at 25°C for 10 minutes , 42°C for 180 minutes , and 70°C for 15 minutes . Following reverse transcription , the RNA was purified using a G-25 column ( GE ) with elution into 1× TE . The cDNA was converted to a double-stranded DNA library with Illumina platform-specific sequence tags . First , 40 μL of the purified reverse transcription product was used in an 80-μL second-strand synthesis reaction ( NEBNext Second Strand Synthesis Module , New England Biolabs ) . The product of the second-strand synthesis reaction was purified ( PureLink PCR Micro Kit; Life Technologies ) and eluted into 12 μL elution buffer . A 10-μL aliquot of the purified DNA solution was then used in a 50-μL end repair reaction ( NEBNext End Repair Module , New England Biolabs ) . Following end repair , the DNA was purified ( 1 . 6× Ampure XP Bead clean-up; Agencourt , Beckman Coutler ) and eluted into a final volume of 30 μL 1× TE . To incorporate Illumina platform-specific sequence tags , a dA-tailing reaction was used to incorporate a single-nucleotide overhang at the 3′ ends of the double-stranded DNA . A 15-μL aliquot of purified DNA from the end repair step was used in a 20-μL dA-tailing reaction ( NEBNext dA-Tailing Module , New England Biolabs ) . Illumina sequences were incorporated using a ligation step with Illumina iAdapters ( prepared in house ) . Immediately following completion of the dA-tailing reaction , 7 . 5 μL of 5× reaction buffer ( NEBNext Quick Ligation Module , New England Biolabs ) , 2 . 5 μL 125 nM DNA adapter , 3 . 75 μL Quick T4 DNA Ligase ( New England Biolabs ) , and 3 . 75 μL water were added to the dA-tailing reaction mix . The ligation reaction was then incubated at 20°C for 15 minutes . The ligation reaction was purified twice ( 1 . 0× Ampure XP Bead clean-up; Agencourt , Beckman Coutler ) with final elution into 20 μL 10 mM Tris ( pH 8 . 0 ) . Illumina libraries were prepared using emulsion PCR [10 , 34] . The aqueous phase was composed of 5 μL of double-stranded DNA , 10 μL 10 μM Illumina-specific forward strand primer , 10 μL 10 μM Illumina-specific reverse strand primer , 40 μL Q5 5× reaction buffer ( New England Biolabs ) , 100 μL 20 g/L bovine serum albumin , 4 μL dNTP mix ( 10 mM each , dATP , dCTP , dGTP , dTTP ) , 2 μL Q5 high-fidelity polymerase ( New England Biolabs ) , and 29 μL water . The DNA was amplified in a 35-cycle PCR reaction ( denaturation: 94°C for 30 sec; annealing: 67°C for 30 sec; extension: 72°C for 30 sec ) . To purify the PCR product , the reaction was first applied to a PureLink PCR cleanup column ( Life Technologies ) . The column eluent was then purified using a 1 . 0× Ampure XP Bead clean-up ( Agencourt , Beckman Coutler ) . This bead cleanup was performed twice with elution into 12 μL 10 mM Tris ( pH 8 . 0 ) . The concentrations of sequencing samples were determined by Qubit High Sensitivity DNA fluorescence assays ( Life Technologies ) and High Sensitivity DNA Bioanalyzer assays ( Agilent ) . Each sample was diluted to 2 nM and pooled . The pooled library was sequenced using an Illumina MiSeq ( 300 cycles—PE kit ) . Sequences were aligned and mutation events counted using the SHAPE-MaP analysis pipeline [10] . SHAPE reactivities were computed based on mutation rates in the native 1M7-modified sample , minus the denatured 1M7-modified sample , and normalized by the background control . SHAPE-based alignment was based on the Gotoh algorithm with affine gap penalties [35] . SHAPE-based alignment of two sequences x and y began with declaration of matrices D , P , and Q . Each matrix had dimensions m by n , where m and n were the lengths of sequences x and y plus 1 , respectively . Considering alignment of ( x0…xi ) and ( y0…yj ) , Di , j corresponds to the score associated with alignment , Pi , j corresponds to the score associated with alignment that ends with a gap in x , and Qi , j corresponds to the score of alignment that ends with a gap in y . To initialize each matrix , D0 , 0 was set to 0 , Di , 0 was set to GOP + i × GEP , and D0 , j was set to GOP + j × GEP , where GOP and GEP are the gap opening penalty and gap extension penalty , respectively; P0 , j and Qi , 0 were set to arbitrarily large negative numbers . Every other cell in the matrix was populated by the following recursion , where s ( xi , yj ) describes a pair-wise comparison score , and xi and yj are the SHAPE values of each sequence at i-th and j-th positions: Pi , j = maxPi-1 , j+GEPDi-1 , j+GOP+GEP Qi , j = maxQi , j-1+GEPDi , j-1+GOP+GEP Di , j = maxsxi , yj+Di-1 , j-1Pi , jQi , j The scoring function ( see Fig 1B ) is described by the following equation , with parameters m and b: sxi , yj = maxmxi-yj+b-m+b If base identity was taken into account during alignment , it was added as an additional scoring term b in the recursion , where x'i and y'j were the base identities at positions i and j in sequences x and y , respectively: Pi , j = maxPi-1 , j+GEPDi-1 , j+GOP+GEP Qi , j = maxQi , j-1+GEPDi , j-1+GOP+GEP Di , j = maxsxi , yj+bx'i , y'j+ Di-1 , j-1Pi , jQi , j The scoring function b is described by the following equation with parameters MATCH and MISMATCH . Following population of the matrices by recursion , a trace-back operation was used to find the optimal alignment . The trace-back operation began at position i , j , representing the 3′-most position of the alignment . The next position in the alignment was found using the following comparison: if Di , j was equal to sum of Di-1 , j-1 and the score of the pairwise comparison between xi-1 and yj-1 , the next position was aligned nucleotides xi-1 and yi-1; if Di , j was equal to Pi , j , the next position was a gap in sequence y; if Di , j was equal to Qi , j , the next position was a gap in sequence x . The trace-back operation was finished when a position was encountered where i = 0 or j = 0 . The SHAPE scoring parameters m and b , base-identity scoring parameters MATCH and MISMATCH , and gap penalty parameters GOP and GEP were optimized by exhaustive search over the 16S and 23S rRNA aligned sequence pairs . The best parameter set was then selected based on the average sensitivity across all alignments . In experiments considering only SHAPE values , m = -2 , b = 2 , GOP = -5 , and GEP = -0 . 25 . Scoring function parameters were preserved across SHAPE-only and combined SHAPE and base identity alignments , but GOP and GEP parameters were reoptimized for alignments considering both SHAPE reactivity and base identity . When both SHAPE and base identity were considered , m = -2 , b = 2 , GOP = -6 , GEP = -1 , MATCH = 2 , and MISMATCH = -2 . From multiple sequence alignments on the CRW , pairwise alignments between E . coli and C . difficile and E . coli and H . volcanii were obtained for both 16S and 23S rRNAs . RNA sequence alignments generated in this work were then evaluated by comparison to these alignments . Sensitivities were calculated as the percentage of matched nucleotides in the CRW alignments found in a given alignment . Multiple sequence alignments were generated using T-Coffee [16] . First , pairwise alignments were generated for all possible pairs between sequences under consideration . These pair-wise alignments were then used as arguments for T-Coffee using default parameters . T-Coffee creates a multiple sequence alignment based on the consensus of individual alignments . Only alignments generated by the methods described in this work were used to make multiple sequence alignments . To establish a base-line for comparison , sequence-only secondary structure predictions were performed with RNAfold from the Vienna RNA package with a maximum base paring distance of 600 nucleotides [20] . Secondary structure models were also generated using sequence-only alignments or SHAPE reactivities . Pairwise Needle alignments were used to generate a multiple sequence alignment using T-Coffee [16] . This multiple sequence alignment was in turn used by RNAalifold [21] to create a consensus secondary structure . Default RNAalifold parameters were used with the exceptions that the ribosum matrix [36] and a maximum base pairing distance of 600 nucleotides were imposed . Individual SHAPE-directed predictions were made using RNAfold , with SHAPE data incorporated as a pseudo-free energy term [4 , 23] . Multiple sequence alignments were used as input for RNAalifold from the Vienna RNA package [21] . SHAPE data were incorporated as an additional pseudo-free energy term to constrain secondary structure prediction [4 , 23] using a new implementation of the RNAalifold algorithm . Secondary structure prediction and partition function calculations were performed using the ribosum matrix [36] with a maximum base pairing distance of 600 nucleotides . Following RNAalifold modeling , all base pairs in the consensus sequence with pairing probabilities greater than 95% were used as constraints in individual follow-up models using RNAfold , also of the Vienna RNA package [20] . SHAPE data were also used to constrain secondary structure modeling in this step , using a maximum base pairing distance of 600 nucleotides . The SHAPE-aware implementations of RNAfold and RNAalifold are part of the upcoming release of the Vienna RNA Package 2 . 2 . A release candidate of this software is available at http://www . tbi . univie . ac . at/RNA . Secondary structure models were evaluated by calculating sensitivity ( sens ) as the percentage of base pairs from the CRW covariation model found in predicted structures and by calculating positive predictive values ( ppv ) as the percentage of predicted pairs found in the covariation model . It should be emphasized that these reference structures are themselves experimental models , and base pairs in these models may show slight local rearrangements in terms of base-pairing partners [4 , 37] . To account for this , when comparing base pairs between the covariation and predicted models , a modest local refolding allowance of 5 nucleotides was permitted . To be considered matched , a base pair in the covariation model at positions x and y and any base pair in the predicted model at positions xʹ and yʹ were required to meet the following criterion: [x = x'and y-y'≤5] or [y = y'and x-x'≤5] Pseudoknots and non-canonical base pairs ( with the exception of G-U pairs ) were not considered in sens and ppv calculations . | Despite the clear functional importance of structure in RNA molecules , it remains very difficult to correctly identify and annotate similar RNA structures because their sequences are often poorly conserved even for RNAs that form very similar higher-order structures . A solution is to use a metric that identifies structural motifs but this , too , is difficult because RNA structure modeling based on sequence alone is generally not very accurate . In this work , we use SHAPE chemical probing to obtain model-free information about RNA structure and then exploit this information to align RNAs by sequence . We show for ribosomal RNAs that sequence alignments based on SHAPE experimental information alone are as accurate as those that actually use sequence information . In addition , we identify regions in the 16S ribosomal RNA that form conserved secondary structures that are different from currently accepted models . These differences , rather than being errors , reveal sites of conformational flexibility that may underlie mechanistic functions in ribosome assembly and translation regulation . We anticipate that structure-informed sequence alignment and structure modeling will become broadly useful tools in RNA function analysis . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] | [] | 2015 | Model-Free RNA Sequence and Structure Alignment Informed by SHAPE Probing Reveals a Conserved Alternate Secondary Structure for 16S rRNA |
Information on global human movement patterns is central to spatial epidemiological models used to predict the behavior of influenza and other infectious diseases . Yet it remains difficult to test which modes of dispersal drive pathogen spread at various geographic scales using standard epidemiological data alone . Evolutionary analyses of pathogen genome sequences increasingly provide insights into the spatial dynamics of influenza viruses , but to date they have largely neglected the wealth of information on human mobility , mainly because no statistical framework exists within which viral gene sequences and empirical data on host movement can be combined . Here , we address this problem by applying a phylogeographic approach to elucidate the global spread of human influenza subtype H3N2 and assess its ability to predict the spatial spread of human influenza A viruses worldwide . Using a framework that estimates the migration history of human influenza while simultaneously testing and quantifying a range of potential predictive variables of spatial spread , we show that the global dynamics of influenza H3N2 are driven by air passenger flows , whereas at more local scales spread is also determined by processes that correlate with geographic distance . Our analyses further confirm a central role for mainland China and Southeast Asia in maintaining a source population for global influenza diversity . By comparing model output with the known pandemic expansion of H1N1 during 2009 , we demonstrate that predictions of influenza spatial spread are most accurate when data on human mobility and viral evolution are integrated . In conclusion , the global dynamics of influenza viruses are best explained by combining human mobility data with the spatial information inherent in sampled viral genomes . The integrated approach introduced here offers great potential for epidemiological surveillance through phylogeographic reconstructions and for improving predictive models of disease control .
The emergence and worldwide dispersal of novel human pathogens is increasingly challenging global public health [1] . Notable recent examples include novel influenza strains , severe acute respiratory syndrome ( SARS ) virus and Methicillin-resistant Staphylococcus aureus , which all exploit today's complex and voluminous transport networks to rapidly disseminate in a globalized world . In the context of human infectious diseases , the worldwide air transportation network is by far the best studied system of global mobility [2] . Air travel likely drives the global circulation of seasonal influenza A ( H3N2 ) viruses [3] , and may explain seasonal dynamics in the absence of locally-persistent strains between epidemic seasons . Retrospective modeling of the ‘Hong Kong flu’ H3N2 pandemic in 1968 indicates that the virus spread through a global network of cities interconnected by air travel [4] . Numerous modeling and simulation studies have subsequently explored the potential influence of air travel on influenza virus spread , e . g . [5]–[8] , but few have attempted to verify such models against underlying empirical data on human movement patterns [9] . Two studies on the timing and rate of seasonal influenza transmission across the United States of America ( USA ) highlight the difficulty of using standard epidemiological data to disentangle the relative contributions of different human transportation systems to influenza spread . Using weekly time series of excess mortality due to pneumonia and influenza ( P&I ) , Viboud et al . [9] demonstrated that the patterns of timing and incidence of outbreaks across the continental USA are most strongly associated with rates of movement of people to and from their workplaces , and to a lesser extent with the distance between locations and various measures of domestic transportation . In contrast , Brownstein et al . [10] concluded that the rate of inter-regional spread and timing of influenza in the USA , as measured using weekly P&I mortality statistics , is predicted by domestic airline travel volume in November . These discordant findings generated significant debate [11] , especially in the context of a potential pandemic of pathogenic influenza [12] , which would require rapid decisions to be made on the implementation of travel restrictions . As a historical record of epidemic spread , viral genetic sequence data may offer a valuable source of information for the empirical verification of epidemiological models . Several studies have demonstrated their utility and power , for example by revealing the genetic dynamics of influenza A H3N2 seasonality [13] and the spatial patterns of global H3N2 circulation [3] , [14] . More generally , it is recognized that the genetic diversity of rapidly evolving viruses like influenza should be analysed in a framework that unifies evolutionary and ecological dynamics [15] . Current attempts to reconstruct viral spread through time and space from genetic data , however , typically fit parameter-rich models to sparse spatial data and result in phylogeographic patterns that are difficult to relate directly to underlying ecological processes [16] . Together with potential sampling bias , this complicates phylogeographic tasks , such as the characterization of source-sink dynamics in seasonal influenza . It is therefore unsurprising that different studies on the global circulation of H3N2 are sometimes inconsistent [3] , [14] , [17] , despite the importance of such work for influenza surveillance and vaccine strain selection . Here we use a model-based approach to explicitly tests spatial epidemiological hypotheses by integrating empirical data on human movement patterns with viral genetic data . This framework enables us to measure the relative contribution of different predictive variables to viral spatial spread . We apply this approach to seasonal H3N2 dynamics and use it to identify key drivers of the global dissemination of influenza viruses . Analysis of different sampling schemes , including one that represents the community structure in global air transportation , provides consistent support for air travel governing the spatial dynamics of seasonal H3N2 infections . Using epidemiological simulations , we further demonstrate that estimates resulting from the merger of human air travel and H3N2 influenza genetics best capture the observed global expansion of pandemic H1N1 influenza in 2009 .
We complemented a previously collected hemagglutinin sequence data set , comprising 1 , 441 sequences sampled globally from 2002 to 2007 [3] , with publicly available sequences sampled within the same time interval . The allocation of the sequence data into 15 and 26 geographic regions as well as into 14 air communities is described in detail in Supporting information Text S1 . The worldwide air transportation network is defined by a passenger flux matrix that quantifies the number of passengers traveling between each pair of airports . We use a dataset provided by OAG ( Official Airline Guide ) Ltd . ( http://www . oag . com ) , containing 4 , 092 airports and the number of seats on scheduled commercial flights between pairs of airports during the years 2004–2006 . We take the number of seats on scheduled commercial flights from airport i to j to be proportional to the number of passengers traveling . To identify air transportation communities , we approximate a maximal-modularity subdivision of the 1 , 227-largest-airport network by employing a recently described stochastic Monte-Carlo approach [18] . Modularity provides a measure of how well the connectivity of a network is described by partitioning its nodes into non-overlapping groups; for a definition we refer to [19] . For any given partition , modularity will be high if connectivity within groups is high and connectivity among groups is low . For large networks , a variety of methods have been introduced to approximate their optimal subdivision . The method we employ here generates an ensemble of high modularity subdivisions and computes the consensus in this ensemble by superposition . For further details we refer to [18] , [20] and in Text S1 we describe how we incorporate subdivision uncertainty in our phylogeographic approach . We employ a novel approach to simultaneously reconstruct spatiotemporal history and test the contribution of potential predictors of spatial spread . The approach extends a recently developed Bayesian method of phylogeographic inference [21] into a generalized linear model ( GLM ) , by parameterizing each rate of among-location movement in the phylogeographic model as a log linear function of various potential predictors . For each predictor j , the GLM parameterization includes a coefficient , which quantifies the contribution or effect size of the predictor ( in log space ) , and a binary indicator variable , that allows the predictor to be included or excluded from the model . We estimate the variables using a Bayesian stochastic search variable selection ( BSSVS ) [22] , [23] , resulting in an estimate of the posterior inclusion probability or support for each predictor . This approach uses the data to select the explanatory variables and their effect sizes from a pre-defined set of predictors that can explain the phylogenetic history of among-location movement while simultaneously reconstructing the ancestral locations in the evolutionary history . In Text S1 , we ( i ) provide more mathematical detail of the GLM model , ( ii ) describe novel transition kernels for efficient statistical inference , ( iii ) propose prior specifications and ( iv ) explain how Bayes factors can be calculated for each predictor based on estimates . The method introduced here is implemented in the BEAST software package [24] . The GLM approach offers many statistical advantages over other approaches [25] in efficiently testing spatial hypotheses ( see Text S1 for a detailed comparative analysis ) . Commonly-used Bayesian measures of model fit ( such as marginal likelihood estimation using the harmonic mean ) , which can be applied to models with among-location movement rates fixed to a particular predictor , have been shown to perform poorly [26]–[28] . Although more accurate alternatives have recently been proposed [26]–[28] , they are computationally prohibitive on large data sets such as those studied here . Importantly , the previous approach provides only a relative ranking of different models and , unlike the GLM model , cannot identify which of the top-ranked predictors need to be jointly considered as explanatory variables . A further advantage of the GLM approach is that in addition to providing a measure of support for each predictor , it can also quantify the contribution or effect size of each predictor by estimating the associated coefficients ( ) . For the spread of seasonal influenza , we consider several potential predictors of global migration , including different log-transformed measures of geographical distance , absolute latitude , air transportation data , demographic and economic data , viral surveillance data , antigenic evolution and sequence sample sizes ( described in more detail in Text S1 ) . Text S1 also reports the evolutionary and demographic models used in BEAST and describes how phylogenetic uncertainty is approximated during phylogeographic inference . Phylogeographic movement events among locations are modeled by a continuous-time Markov chain ( CTMC ) process along each branch of the viral phylogeny . Although both the transitions among locations ( Markov jumps ) and the waiting times between transitions ( Markov rewards ) are not directly observed , posterior expectations of these values can be efficiently computed [29] , [30] . Here , we implement posterior inference of the complete Markov jump history through time in BEAST and use these estimates to assess the source-sink dynamics of influenza and to evaluate the predictive performance of phylogeographic models . To compare the performance of different migration rate models in predicting global pandemic spread , we simulate a stochastic meta-population susceptible-infected-recovered ( SIR ) model with n = 14 populations , matching the 14 air communities analyzed in the phylogeographic model . The model tracks the number of susceptible ( S ) , infected ( I ) and recovered ( R ) individuals in each population each day of the simulation . The simulations begin with a single initial infection in Mexico on January 5th 2009 [31] . Infection spreads through mass-action within each population according to the following epidemiological parameters . Population-specific host population size is equal to human population size ( Text S1 ) . Basic epidemiological parameters are based on empirical estimates from H1N1: the duration of infection was chosen as 3 days [31] and the basic reproductive number ( ) or average number of secondary infections arising from a primary infector during their infectious period in a completely susceptible population was chosen as 1 . 3 [31] . This results in a transmission rate . Although estimates of for pandemic H1N1 vary across studies , the exact value is unlikely to affect the comparative simulations we perform as this is expected to equally impact the overall expansion rate and not the relative migration dynamics across populations . Force of infection within population scales with infected frequency across populations following , where the coupling coefficient represents the rate of contacts from population i to population j relative to within-population contacts and . Other pairwise coupling coefficients are taken to be proportional to pairwise migration estimates , so that , where is the air travel based or phylogenetically estimated rate of migration from population i to population j per year and parameter c is fitted to the data . Parameter c is the only free parameter in this model and we set this to the value that maximizes correspondence between simulations and observations ( see below ) . This ensures that we can use phylogeographic migration rates as per capita migration rates in the simulation model , despite their different scales . Compartments are updated according to a -leaping algorithm [32] with one-day intervals . Migration rates between populations in the SIR model are defined according to four scenarios , as follows: ( A ) equal rates , ( B ) rates proportional to the amount of air travel occurring between them ( in terms of the number of passengers moving from one population to another ) , ( C ) rates proportional to Markov jump estimates based on a standard phylogeographic model ( undertaken with and without BSSVS to reduce the number of rate parameters ) and ( D ) a GLM model that only considers air travel as a predictor . To compare the spread of influenza under these simulated models to recorded H1N1 pandemic spread , we measure the relative correspondence between the mean peak times ( across 100 simulations ) and the observed peak times for all locations except Mexico ( based on World Health Organization data; Text S1 ) . Correspondence was measured using the Spearman's rank correlation coefficient , and tested with associated -values obtained using a permutation test ( Text S1 ) , as well as using the mean average error ( MAE; in days ) . We consider the Spearman's rank correlation coefficients to be more appropriate for our comparison because they are more robust to outliers , which are clearly present in the observed peaks . Therefore , the scaling of between-population coupling c for the various migration matrices was also adjusted so as to maximize Spearman's rank correlation .
To identify key factors in the seasonal dispersal of human influenza viruses , we use a Bayesian model selection procedure to estimate the phylogeographic history of H3N2 viruses sampled worldwide between 2002 and 2007 ( Text S1 ) , while concurrently evaluating the contribution of several potential predictors of spatial spread . In addition to considering two geographic discretizations of the available data , we also identify community structure in global air travel by determining partitions with high intra-community connectivity and low inter-community connectivity ( Methods ) . Although this approach is blind to the airports' geographic locations , the 14 resulting global air communities are spatially compact with few exceptions ( Fig . 1 ) . We find air communities that are largely specific to Oceania , China , Japan , Sub-Saharan Africa , Mexico and Canada . Madagascar , Réunion and some Caribbean destinations are examples of exceptions that are , as non-European locations , connected to a European air community . Our analysis reveals that many potential predictors of global influenza virus spread are not associated with viral lineage movement , specifically , geographical proximity , demography and economic measures , antigenic divergence , epidemiological synchronity and seasonality do not yield noticeable support ( Fig . 2 ) . Instead , we find consistent and strong evidence that air passenger flow is the dominant driver of the global dissemination of H3N2 influenza viruses . This is reflected in both the estimated size of the effect of this variable ( on a log scale ) and the statistical support for its inclusion in the model ( posterior probability >0 . 93 and Bayes factor >760 ) . This effect size means that viral lineage movement rates are about 15 times higher for connections with the highest passenger flow compared to connections with the lowest flow , controlling for all other predictors . The result is robust when we repeat the analysis ( i ) using different partitions of sampling locations ( air communities and different geographic partitions , Fig . 2 ) , ( ii ) using different sequence sub-samples for the air communities ( Fig . S1 ) , ( iii ) using the full data set or a small but more balanced number of sub-samples ( Fig . S2 ) , and ( iv ) using a more liberal prior specification on predictor inclusion ( Fig . S3 ) . We down-sampled particular air communities or geographic regions relative to their population sizes ( Text S1 ) , which still leaves considerable heterogeneity in sample sizes , explaining why they are included as an explanatory variable in the GLM model . Our aim is not to demonstrate a role for sample sizes in phylogeography , but by explicitly including them as predictive variables , we raise the credibility that other predictors are not included in the model because of sampling bias . We note that the sample size predictors may in fact absorb some of the effect of air travel because a GLM model that only considers passenger flux as a predictor of H3N2 movement among the air communities results in a higher mean effect of size of about 1 . 5 . To also explore spatial dynamics at smaller scales , we further partition large geographical regions that are administratively coherent , such as the USA , China , Japan and Australia , resulting in 26 global sampling regions ( Text S1 ) . In this analysis , air travel again predicts viral movement ( posterior probability >0 . 99 and Bayes factor >18000 ) , but the movement is also inversely associated with geographical distance between locations ( posterior probability = 0 . 76 and Bayes factor = 87 ) , and , less intuitively , with origin and destination population densities ( although the size of the latter effects are weaker , Fig . 2 ) . The negative association of population density with viral movement may suggest that commuting is less likely , per capita , to occur out of , or into , dense subpopulations . Although not the main focus of the current study , our integrated approach also provides phylogeographic reconstructions that offer insights into the global source-sink dynamics of human influenza . The trunk or backbone of phylogenies reconstructed from temporally-sampled hemagglutinin genes ( Fig . 3 ) represents the lineage that successfully persists from one epidemic year to the next [14] , [33] . We determine the spatial history of this lineage using Markov rewards in the posterior tree distribution , thereby estimating the contribution of each location to the persistence of the trunk lineage from 2002 to 2006 ( Fig . 3 ) . These estimates provide strong support for mainland China as the principal H3N2 source population , occupying close to 60% of the trunk time in the H3N2 phylogenies ( Fig . 3 ) , followed by Southeast Asia , which comprises about 15% of the trunk time . We further examine temporal heterogeneity in the source-sink process by combining a summary of the estimated trunk location through time together with an phylogenetic summary in Fig . 3 , which suggests that the above-mentioned proportions arose from the presence of the trunk lineage in China during 2002 to mid 2003 and late 2004 to 2006 , interrupted by a period when the virus appeared to have a Southeast Asian H3N2 source . However , we cannot rule out the impact of temporal sampling heterogeneity on these estimates because the Southeast Asian trunk dominance precedes a period of higher sampling availability for Southeast Asia relative to mainland China ( Fig . 3 ) . The important role of mainland China in seeding the global seasonal spread of human influenza results in a high net migration out of this air community ( Fig . S4 ) . However , air communities that do not contribute significantly to the trunk can also maintain high net outflow , in particular the USA , which may be seeded by relatively few introductions each year whilst exporting comparatively more viruses to other locations during the epidemic season . In order to assess the extent to which evolutionary analyses such as ours benefit from integrating host mobility data , we examine their predictive performance by using them to predict the relative timing of the geographic spread of the pandemic H1N1 influenza variant that emerged in 2009 . We conduct simulations of the spread of a novel pathogen out of Mexico using an SIR model whose transmission parameters are informed by epidemiological estimates obtained for pandemic H1N1 [31] and whose spatial spread is determined by one of four different migration rate models , each defined by a different matrix of movement rates among all pairs of locations ( Methods ) . We measure the relative correspondence between the simulated and observed H1N1 peaks for each location except Mexico using a Spearman's rank correlation coefficient ( ) and mean absolute error ( MAE; in days ) ( Fig . 4 ) . An equal rates model ( A ) , which does not express any migration rate preference , results in a weak match ( , P = 0 . 73 , MAE = 40 . 9 days ) between the simulations and the observed spatial spread of H1N1 ( Fig . 4 ) , indicating that the population sizes included in the SIR model for each region offer limited predictive performance . As expected , adding information on the number of airline passengers ( model B ) yields a large improvement in correspondence between simulations and observations ( , P = 0 . 03 , MAE = 35 . 8 days ) . In contrast , a standard parameter-rich phylogeographic model that is only informed by sequence data and not air traffic information ( model C ) yields only part of this improvement in predictive performance ( , P = 0 . 10 , MAE = 39 . 4 days ) . However , if inference under model C is made more efficient by focusing on a small set of parameters ( using BSSVS , [21]; see Methods ) then phylogeographic estimates yield a predictive performance ( , P = 0 . 02 , MAE = 36 . 4 days , Fig . S5 ) that is close to that of the air travel model ( B ) . Finally , the GLM model ( D ) predicts the observed spread of H1N1 more accurately than all other models ( , P<0 . 01 , MAE = 32 . 3 ) , suggesting that global influenza transmission is best predicted by combining passenger flux data with the information on viral lineage movement contained in sequence data . The simulations generally correspond better with observed H1N1 peaks during the initial period of pandemic expansion , while the epidemic peaks for Russia and Africa occur significantly earlier in the simulations than in reality . This is likely due to the multi-peaked character of the regional epidemics ( Text S1 ) ; the H1N1 virus spreads to most of the world during the first pandemic wave , whereas regions like Russia and Africa appeared to miss the first wave entirely . Seasonal effects that are unaccounted for by our simulation may at least partly explain the outliers , but they affect the models we aim to compare in a very similar way . Because of the outliers , we consider the non-parametric Spearman's to be a more appropriate measure of correspondence than the MAE , but they are consistent in their model ranking . We note that absolute prediction errors can be considerably improved by only considering the 9 air communities that peaked prior to September , 2009 , which returns a MAE of 11 . 2 day for the GLM model . However , because of the difficulties in establishing initial waves and their peaks , and the uncertainty in our epidemiological model , we caution against more detailed interpretation of these simulations beyond the general trends we extract here .
The prevention and control of influenza at the global scale relies critically on our understanding of its mode of geographical dissemination . Here , we demonstrate that such dynamics are most powerfully investigated by combining phylogeographic history with empirical data on the patterns of human movement worldwide . Our analysis strongly suggests that air travel is key to global influenza spread , an intuitive result that has long been predicted by modeling studies ( e . g . [5] ) , but has , until now , remained difficult to obtain from empirical data . The dominant predictors of influenza spread will undoubtedly be scale-dependent , as indicated here by the importance of geographic distance as a predictor within more confined geographic areas ( Fig . 2 ) , which may represent forms of human mobility other than air travel , such as workplace commuting [9] . This indicates that our statistical framework could also prove valuable in testing hypotheses at smaller scales , where the underlying spatial processes may be less obvious , provided adequate sequence and empirical movement data are available . One of the limitations of the current heterogeneous sampling of H3N2 sequences worldwide is that geographic partitions need to be adjusted to account for the number of samples per location , which results in regions of widely different areas and population sizes . More representative sampling across the globe , or within a more geographically confined area of interest , will allow for more appropriate geographic partitioning and may facilitate more detailed spatial hypothesis testing based on the associated demographic and mobility measures . In particular , if sequences were sampled appropriately then our inference method could incorporate the rich geographic data that is currently available as global gridded population data sets [34] . In addition , many of the predictors used here can be improved in accuracy and resolution , for example by accounting for seat occupancy and actual origin-destination flows in air traffic passenger fluxes . Due to the difficulties associated with geographic partitioning , we used algorithms to optimally define communities in the global air transportation network as an alternative strategy to specify phylogeographic states , and subsequently show that our GLM results are robust to the different partitions used . Because air travel is a consistent and highly supported explanatory variable for global influenza dispersal , communities within the air transportation network are likely to provide the most appropriate spatial structuring of our data . However , in addition to the partitioning itself , further research is also needed to select the appropriate number of samples from the resulting regions to improve on ad hoc down-sampling based on population size . Although identifying the causes of pathogen spread is of great importance in spatial epidemiology , integrating this information in evolutionary models also offers major advantages for phylogeographic reconstructions and their relevance to infectious disease surveillance and pandemic preparedness . By capturing a more realistic process of spatial spread , our novel approach results in more credible reconstructions of spatial evolutionary history , which may shed further light on the persistence and migration dynamics of human influenza viruses . Because of the importance of influenza dynamics for vaccine strain selection , different phylogeographic reconstructions have attempted to characterize the global population structure of the virus and have arrived at somewhat mixed findings [3] , [14] , [17] . This may be explained by the use of both different sampling and different methodology . The data and methods used here corroborate the explorations of antigenic and genetic divergence by [3] and demonstrate the prominence of mainland China and Southeast Asia as locations of trunk lineage persistence . Our findings are however based on roughly the same genetic data , and our approach of inferring the spatial history of the trunk lineage through Markov reward estimates may be viewed as the more direct , statistical equivalent of measuring strain location distance from the trunk [3] . Although we find a strong signal for the presence of the trunk lineage in mainland China and Southeast Asia , our analysis is restricted to the period 2002 to 2006 , and thus we make no conclusions about the location of the trunk lineage outside of this period . The degree of temporal stochasticity in the source location of seasonal influenza and its heterogeneity among different influenza variants has yet to be determined and requires datasets of longer duration . Moreover , we suggest that analyses of future data sets that are more comprehensively sampled through time will also benefit from phylogeographic models that can accommodate temporal heterogeneity in movement rates . Such models may also improve the performance of some explanatory variables . For example , in the analysis presented here , we do not consider the absence of support for seasonality as a predictor in our GLM model as evidence against seasonality in H3N2 spread . Rather , it simply reflects the difficulty in incorporating seasonality into a time-homogeneous model of lineage movement . Developments are now underway to appropriately accommodate heterogeneity in spatial spread through time . By using models to predict the observed global emergence of pandemic H1N1 , we demonstrate that an approach that integrates passenger flux data with viral genetic data provides a more accurate prediction of global epidemic spread than those which include only one source of information . Although the prediction improvement of the combined data over the passenger flux data alone is not very large , it remains remarkable because we attempt to predict the spatial expansion of an epidemic lineage ( pandemic H1N1 ) from the seasonal dynamics of another lineage ( H3N2 ) and because the main process underlying the global dispersal of H3N2 influenza appears to be air travel itself . Passenger flux data among pairs of locations is symmetric , thus it is possible that the phylogeographic data is capable of capturing asymmetry in the seasonal process of viral spread , which may also be important in explaining the spatial expansion of pandemic H1N1 . Investigations using more advanced simulation techniques , e . g . [35] , may be able to build upon the conceptual bridge between genetic data and epidemiological modeling implied by our findings . Future prediction efforts may also need to focus on alternative scenarios of spatial spread , as highlighted by the recent emergence of a novel avian influenza H7N9 lineage in China [36] . Should this virus evolve sustained human-to-human transmissibility , then airline-passenger data and flight routes from the outbreak regions in particular , would be able to pinpoint worldwide regions of immediate risk . If the virus remains restricted to avian hosts , however , risk maps for the transmission of avian influenza viruses ( perhaps based on predictors calibrated against H5N1 avian influenza ) may help to target H7N9 surveillance and control efforts . In conclusion , our framework is applicable to different infectious diseases and provides new opportunities for explicitly testing how host behavior and ecology shapes the spatial distribution of pathogen genetic diversity . | What explains the geographic dispersal of emerging pathogens ? Reconstructions of evolutionary history from pathogen gene sequences offer qualitative descriptions of spatial spread , but current approaches are poorly equipped to formally test and quantify the contribution of different potential explanatory factors , such as human mobility and demography . Here , we use a novel phylogeographic method to evaluate multiple potential predictors of viral spread in human influenza dynamics . We identify air travel as the predominant driver of global influenza migration , whilst also revealing the contribution of other mobility processes at more local scales . We demonstrate the power of our inter-disciplinary approach by using it to predict the global pandemic expansion of H1N1 influenza in 2009 . Our study highlights the importance of integrating evolutionary and ecological information when studying the dynamics of infectious disease . | [
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] | [
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] | 2014 | Unifying Viral Genetics and Human Transportation Data to Predict the Global Transmission Dynamics of Human Influenza H3N2 |
The osteoblast-lineage consists of cells at various stages of maturation that are essential for skeletal development , growth , and maintenance . Over the past decade , many of the signaling cascades that regulate this lineage have been elucidated; however , little is known of the networks that coordinate , modulate , and transmit these signals . Here , we identify a gene network specific to the osteoblast-lineage through the reconstruction of a bone co-expression network using microarray profiles collected on 96 Hybrid Mouse Diversity Panel ( HMDP ) inbred strains . Of the 21 modules that comprised the bone network , module 9 ( M9 ) contained genes that were highly correlated with prototypical osteoblast maker genes and were more highly expressed in osteoblasts relative to other bone cells . In addition , the M9 contained many of the key genes that define the osteoblast-lineage , which together suggested that it was specific to this lineage . To use the M9 to identify novel osteoblast genes and highlight its biological relevance , we knocked-down the expression of its two most connected “hub” genes , Maged1 and Pard6g . Their perturbation altered both osteoblast proliferation and differentiation . Furthermore , we demonstrated the mice deficient in Maged1 had decreased bone mineral density ( BMD ) . It was also discovered that a local expression quantitative trait locus ( eQTL ) regulating the Wnt signaling antagonist Sfrp1 was a key driver of the M9 . We also show that the M9 is associated with BMD in the HMDP and is enriched for genes implicated in the regulation of human BMD through genome-wide association studies . In conclusion , we have identified a physiologically relevant gene network and used it to discover novel genes and regulatory mechanisms involved in the function of osteoblast-lineage cells . Our results highlight the power of harnessing natural genetic variation to generate co-expression networks that can be used to gain insight into the function of specific cell-types .
The osteoblast-lineage consists of a spectrum of cells beginning with osteoprogenitors derived from mesenchymal stem cells that then differentiate to form mature bone-forming osteoblasts and bone-lining cells . The final stage in the life-cycle of the lineage occurs when a subset of mature osteoblasts become entombed in bone as mechanosensitive osteocytes [1] . As the only known bone-forming cell , osteoblasts are essential for skeletal development , growth and maintenance [1] . In addition to their critical role in the skeleton , osteoblast-lineage cell have been shown to be important for other physiological systems . Osteoprogenitors can support and modulate erythropoiesis [2] and mature osteoblasts are responsible for many of the endocrine functions of bone , including the regulation of energy expenditure [3]–[5] and male fertility [6] . Furthermore , osteocytes play important roles in mineral metabolism [7] and bone resorption [8] , [9] . Therefore , the development of a more comprehensive understanding of the molecular networks operative in osteoblast-lineage cells will have important implications not only for osteoporosis , but many other common complex diseases . Genetic , molecular and biochemical approaches have been used over the last decade to identify many of the key genes that are required for osteoblast progenitor commitment , proliferation , differentiation and apoptosis as well as mature osteoblast and osteocyte activity [1] . An example of this has been the discovery that the Wnt signaling pathway plays a central role in many functional aspects of the osteoblast lineage [10] . However , these investigations have been reductionist in nature and therefore have not provided information on how key signaling genes interact in complex cellular networks , which is critical to fully understand the molecular mechanisms that underlie cellular processes and disease . In many cases , the insight gained regarding how genes interact in networks goes well beyond what can be learned about a process using only traditional approaches [11] . Systems genetics is an emerging approach that provides a systems-level perspective of the role of genetic variation in cell function and disease [12] . Systems genetics relies on the principles and methods of systems biology , but focuses on determining how naturally occurring genetic variation perturbs cellular phenotypes [13] . The foundation of systems genetics is a suite of analytical approaches that include genome-wide association , expression quantitative trait locus ( eQTL ) discovery , causality modeling and network analysis [14] . One of the most powerful systems genetics tools is network analysis . Biological networks can be based on many different types of interactions [15] , such as genetic , protein-protein and transcription factor binding . However , the most common networks used in systems genetics research are based on co-expression . In a systems genetics context , co-expression networks are generated using global expression data collected across many genetically unique individuals [16] . The patterns of gene expression that result from each unique set of genetic perturbations are used to quantify correlational relationships among genes on a genome-wide scale . Co-expression networks typically display two important behaviors , i ) they are modular , with distinct modules representing dense clusters of genes that are highly co-expressed and ii ) the co-expression modules are often enriched for genes that share similar functions [17] . Because modules contain functionally similar gene sets , they can be used to extract many pieces of information about a system . For instance , a number of studies have shown that summarized measures of module behavior often correlate with complex processes or disease phenotypes [18]–[20] . The identification of such modules provides a list of genes and pathways that likely play a role in the process or disease . In addition , genes within a module can be organized by connectivity . Highly connected genes are called “hubs” and in a co-expression network hub genes are those that are the most strongly correlated with the largest number of other module genes [21] . Importantly , a number of studies have found that connectivity correlates with biologically relevant properties . For example , hubs in yeast networks have been found to be more likely essential for growth than non-hub genes [22] and connectivity was found to be predictive of survival in a human brain co-expression module associated with glioblastoma [23] . Recently , we demonstrated that in a co-expression module associated with Bone Mineral Density ( BMD ) in humans , hub genes were more likely to be genetically associated with BMD than non-hub genes [24] . We have also shown that hubs within a chrondrocyte co-expression network play key roles in chrondrocyte differentiation [20] . In this study , we reconstructed a bone co-expression network using Weighted Gene Co-expression Network Analysis ( WGCNA ) and gene expression microarray profiles from femur samples collected from 96 Hybrid Mouse Diversity Panel ( HMDP ) strains . The resulting network was used to identify a core module of genes ( module 9; M9 ) specific to cells of the osteoblast-lineage . We then demonstrated that the top two M9 hub genes were regulators of osteoblast function and one was a regulator of BMD in vivo . In addition , we showed that a local eQTL regulating the expression of secreted frizzled-related protein 1 ( Sfrp1 ) , orchestrated the transcriptional behavior of the M9 . Notably , Sfrp1 is an antagonist of Wnt signaling , which is a major pro-osteoblastic signal , and Sfrp1 transgenic and knockout mice display alterations in BMD and osteoblast functions [25] , [26] . We further demonstrated the physiologically relevant nature of the M9 by identifying a strong non-linear relationship between the M9 and BMD in the HMDP and that the M9 is enriched for genes implicated in the regulation of human BMD through genome-wide association studies . In summary , our results begin to clarify the composition and role of cellular networks in the osteoblast cell lineage .
A genome-wide co-expression network for bone was constructed by applying WGCNA to microarray gene expression profiles from femur samples collected on 96 HMDP strains [27] , [28] . The network was generated using all 45 , 719 expression probes ( representing 30 , 264 unique genes ) present on the Illumina Mouse WG6 microarrays . Of the total , 13 , 759 probes ( 10 , 968 unique genes ) were assigned to one of 21 co-expression modules ( Table 1 ) . All other probes were not assigned to a module . Of the 21 modules , all but module 15 was enriched for genes belonging to similar genome ontology ( GO ) or Kyoto Encyclopedia of Genes and Genomes ( KEGG ) functional groupings ( Table 1 ) . Lists of module assignments for all genes and all significant ( FDR≤0 . 05 ) functional enrichments are provided in File S1 and File S2 . Given that bone is a heterogeneous tissue , we expected that a subset of modules from the network would represent cell-type specific networks . Therefore , we next set out to identify the co-expression module that was the most relevant for the function of osteoblast-lineage cells . We calculated two metrics , the Gene Significance ( GS ) and Module Significance ( MS ) scores . The GS for each network gene was defined as the absolute value of the correlation between its expression and the eigengene summarizing the expression of a group of nine ( Col1a1 , Col1a2 , Akp2 , Bglap1 , Sp7 , Ibsp , Sost , Mmp13 , Tnfrsf11b , Dmp1 and Phex ) osteoblast/osteocyte markers . These genes were selected prior to the network analysis based on mining the literature for widely used markers of osteoblasts and osteocytes . The MS was defined as the mean GS for each module . In bone , the above marker genes are preferentially ( or exclusively ) expressed in cells of the osteoblast-lineage; therefore , a module with a high MS would be expected to represent a sub-network of genes that function specifically in these cells . Of the 21 modules , module 9 ( M9 ) had the highest MS ( MS = 0 . 62±0 . 02; P<0 . 002 ) . The next highest MS scores were observed for module 6 ( MS = 0 . 32±0 . 02; P<0 . 002 ) and module 16 ( MS = 0 . 27±0 . 01; P<0 . 002 ) ( Figure 1A ) . All other modules had MS scores at or below 0 . 20 ( P>0 . 002 ) . We also expected that the most relevant module would contain genes more highly expressed in osteoblasts than other bone cells . To evaluate the expression patterns of all network genes we utilized an independent set of microarray data which surveyed global gene expression in primary osteoblasts ( at 5 , 14 and 21 days of in vitro differentiation ) , primary osteoclasts , bone marrow and whole bone [29] . M9 genes were over 4-fold ( P<0 . 05 ) more highly expressed in osteoblasts than whole bone or bone marrow and 2 . 8-fold ( P<0 . 05 ) more highly expressed in osteoblasts than osteoclasts ( Figure 1B–1D ) . The M9 was significantly ( FDR≤0 . 05 ) enriched for 53 GO and KEGG pathway terms ( File S1 ) . These included terms such as “extracellular matrix” ( FDR = 1 . 9×10−16 ) , “collagen” ( FDR = 4 . 9×10−7 ) , “ossification” ( FDR = 3 . 0×10−5 ) , “bone development” ( FDR = 8 . 6×10−5 ) , “skeletal system development” ( FDR = 4 . 9×10−4 ) , “Wnt receptor signaling pathway” ( FDR = 1 . 2×10−3 ) and “regulation of bone mineralization” ( FDR = 3 . 7×10−2 ) , which are relevant to osteoblasts . Additionally , we found that the M9 was enriched ( Fisher's exact test P = 2 . 8×10−8 ) in genes belonging to a list of 254 that were members of 11 GO terms containing the term “osteoblast” ( such as “regulation of osteoblast differentiation” ( GO:0045667 ) and “osteoblast proliferation” ( GO:0033687 ) ) or their perturbation in a mouse model has been observed to affect osteoblast function . Lastly , the M9 contained many known genes that , in bone , are specific to or define the osteoblast-lineage . Examples include Akp2 ( alkaline phosphatase ) , Bglap1 ( bone gamma carboxyglutamate protein; osteoclacin ) , Cd276 ( CD276 molecule ) , Col1a1 ( collagen , type I , alpha 1 ) , Col1a2 ( collagen , type I , alpha 2 ) , Lrp5 ( low density lipoprotein receptor-related protein 5 ) , Mmp2 ( matrix metallopeptidase 2 ) , Pthr1 ( parathyroid hormone receptor 1 ) , Sp7 ( Sp7 transcription factor 7 ) , Tnfrsf11b ( tumor necrosis factor receptor superfamily , member 11b ) and Wnt5a ( wingless-related MMTV integration site 5A ) . Together , these data indicate that M9 represents a core gene network specific to cells of osteoblast-lineage . To characterize the M9 network we first determined if M9 topology was important for the function of osteoblast lineage cells . We began by evaluating connectivity , a parameter of network topology . Recently , a number of studies have shown that highly connected “hub” genes tend to play critical roles in module organization [19] , [24] . We defined connectivity ( kme ) for each gene as the correlation between its expression and its module eigengene [21] . Importantly , kme is a property inherent to each gene and would not be expected to correlate with other individual gene metrics ( such as GS ) , unless the organization of the module was an important property of the system . A strong positive correlation was observed between M9 gene kme and GS ( r = 0 . 89 , P = 7 . 7×10−141 ) ( Figure 2 ) , indicating that the more highly connected an M9 gene , the more closely its expression resembles that of a prototypical gene of the osteoblast lineage . The immediate implication of this finding is that we could use kme to determine if M9 hubs play a role in osteoblast function . The top 10 M9 hub genes are listed in Table 2 . We focused on the two genes with the highest kme ( Table 2 ) , melanoma antigen , family D , 1 ( Maged1 ) and par-6 partitioning defective 6 homolog gamma ( C . elegans ) ( Pard6g ) . Maged1 is a transcriptional co-activator that has been implicated in the regulation of myogenic differentiation [30] , sexual behavior [31] , obesity [31] and the transcriptional function of Dlx5 [32] , a positive regulator of osteoblast differentiation and bone mass [33] , [34] . Pard6g is a homologue of the Par ( partitioning defective ) family of proteins that are involved in the regulation of cell polarity . We characterized the broad expression profiles of Maged1 and Pard6g using microarray data from 96 mouse tissues and cell-types [29] . Maged1 and Pard6g were expressed in multiple samples including primary calvarial osteoblasts ( pcOBs ) ( Figure 3A ) . To confirm these data , the expression of both genes was measured during differentiation in an independent set of pcOBs . Maged1 and Pard6g were differentially expressed ( P = 0 . 03 for both genes ) as a function of osteoblast differentiation ( Figure 3B ) . Maged1 expression increased rapidly after the induction of differentiation , peaked at day 6 and then decreased through day 20 , possibly indicating a more important role for Maged1 in early osteoblastogenesis . In contrast , Pard6g expression increased more slowly , peaking at day 14 and then decreasing by day 20 . The expression of Pard6g was highly similar to established markers of osteoblast maturation ( Figure 3C–3F ) , especially Sp7 , Akp2 and Ibsp . We next determined the effects of Maged1 and Pard6g knockdown on osteoblast proliferation and differentiation . Two independent siRNAs ( M1 and M2 for Maged1 and P1 and P2 for Pard6g ) were used to target each gene . At 48 hours post-transfection in undifferentiated pcOBs , Maged1 transcript levels were reduced to 18% and 14% of control in M1 and M2 transfected cells , respectively ( P<0 . 05 ) ( Figure 4A ) . At 96 hours post-transfection in these cells , Maged1 knockdown was lower at 42% and 33% of control in M1 and M2 transfected cells , respectively ( P<0 . 05 ) ( Figure 4A ) . Knockdown at the transcript level resulted in similar reductions in MAGED1 protein levels 48 hours after transfection ( Figure 4B ) . Maged1 knockdown resulted in a 12% ( P<0 . 10 ) and 31% ( P<0 . 05 ) increase in proliferation rate in M1 and M2 transfected undifferentiated pcOBs , respectively ( Figure 4C ) . In differentiating pcOBs ( 4 days ) , M1 and M2 treatment led to 40% ( P<0 . 10 ) and 118% ( P<0 . 05 ) increases in alkaline phosphatase activity ( a marker of maturing osteoblasts ) , respectively ( Figure 4D ) . We also observed 69% and 74% increases in the transcript levels of the osteoblastic genes Sp7 and Akp2 , respectively , in M2 treated cells ( P<0 . 05 ) ( Figure 4E ) . No differences were observed for the other osteoblast markers assayed ( Figure 4E ) . Surprisingly , we observed a significant ( P<0 . 05 ) decrease in the ability of M1 and M2 transfected osteoblasts to form mineralized nodules ( a marker of mature osteoblast function ) at 14 days post-differentiation ( Figure 4F–4H ) . All the differences demonstrated a dose-dependent relationship with the extent of Maged1 knockdown a the transcript level ( the effect of M2>M1 ) , suggesting that the effects were specific for the reduction in Maged1 levels . At 48 hours post-transfection in undifferentiated pcOBs , Pard6g transcript levels were reduced to 50% and 33% of control in P1 and P2 transfected cells , respectively ( P<0 . 05 ) ( Figure 4I ) . At 96 hours post-transfection , Pard6g knockdown was lower at 74% and 63% of control in P1 and P2 transfected cells , respectively ( P<0 . 05 ) ( Figure 4I ) . Knockdown at the transcript level resulted in similar reductions in PARD6G protein levels 48 hours after transfection ( Figure 4J ) . Pard6g knockdown resulted in a 12% ( P = 0 . 10 ) and 62% ( P<0 . 05 ) decrease in proliferation rate in P1 and P2 transfected cells , respectively ( Figure 4K ) . In differentiating pcOBs ( 4 days ) , P1 and P2 treatment led to 66% and 71% decreases ( P<0 . 05 ) in alkaline phosphatase activity , respectively ( Figure 4L ) . Additionally , 40% to 95% decreases ( P<0 . 05 ) were seen in the levels of the osteoblast markers Sp7 , Runx2 , Akp2 , Col1a1 , Bglap1 and Ibsp ( Figure 4M ) . Consistent with these observations , there was a significant ( P<0 . 05 ) impairment in the formation of mineralized nodules in P1 and P2 transfected cells ( Figure 4N–4P ) . All the differences demonstrated a dose-dependent relationship with the extent of Pard6g knockdown at the transcript level ( the effect of P2>P1 ) , suggesting that the effects were specific for the reduction in Pard6g levels . These data indicate that the M9 hub genes , Maged1 and Pard6g , are novel regulators of osteoblast activity . To further assess the physiological function of Maged1 , we measured total body BMD in Maged1 deficient mice ( Maged1− ) . In 18 week-old male Maged1− mice , we observed significantly ( P<0 . 05 ) decreased BMD , relative to wild-type littermates ( Maged1+ ) ( Figure 5A ) . This difference was primarily due to a decrease in bone mineral content ( BMC ) and not skeletal size ( Figure 5B and 5C ) . Additionally , the difference was not a reflection of alterations in lean body mass that would alter BMD ( Figure 5D ) . We next sought to identify genetic loci responsible for the coordinate expression of M9 genes . Two strategies were employed for this analysis , the identification of expression QTL ( eQTL ) hotspots and genome-wide association ( GWA ) . Based on previous studies [35] , we anticipated that the identification of eQTL hotspots would have more statistical power than genome-wide association , but less mapping resolution . In contrast , genome-wide association would be less powerful , but would allow us to more precisely define the location of potential regulators . We choose a priori to focus only on regions that were implicated by both analyses , as these were the most likely to harbor true regulators . We used the Efficient Mixed Model Algorithm ( EMMA ) [36] to perform GWA for all network genes . The number of M9 genes with eQTLs ( −logP>4 ) in 5 Mbp bins across the genome was counted and compared to the frequency of eQTL for all other network genes . Several significant ( Bonferroni corrected P<9 . 4×10−5 ) bins were identified , suggesting that the regulation of M9 gene expression was polygenic . The most prominent hotspots were located on Chrs . 8 ( P = 6 . 1×10−32 ) and 3 ( P = 5 . 1×10−19 ) ( Figure 6A ) . We next used EMMA to directly identify associations for the M9 eigengene . In both cases , the top two hotspots/associations were concordant . The SNP ( rs33030926 , P = 9 . 0×10−6 ) that was the most strongly associated with the M9 eigengene was located on Chr . 8 at 24 . 587852 Mbp . ( Figure 6B ) . Both analyses provided strong evidence for the presence of a regulator of the M9 on Chr . 8 at ∼24 . 5 Mbp . It is possible that such a regulator influences M9 gene expression through a genetically regulated difference in its own expression and this would be detectable as a local eQTL . To determine if this was the case we identified all microarray probes mapping between 20 and 30 Mbp on Chr . 8 . A total of 237 probes corresponding to 137 unique genes were located within the region . EMMA was used to perform genome-wide association for each probe [36] . We then selected the probe for each gene with the most significant local eQTL . A total of 15 genes were found to be regulated by significant ( P≤3 . 6×10−4 ) local eQTL after correcting for multiple comparisons ( Table 3 ) . We would expect that the causal genes expression should be correlated with M9 gene expression . Thus , we calculated the proportion of M9 genes whose expression was correlated ( r>|0 . 25| , nominal P<0 . 01 ) with the expression of each candidate regulator . Most of the 15 candidates showed little overlap ( between 0 and 24% ) . However , the expression of Sfrp1 correlated with 88 . 8% of M9 genes at a threshold of r>|0 . 25| ( Table 3 ) . Sfrp1 was correlated with all 400 M9 probes if the threshold was reduced to r>|0 . 15| . The most significant SNP regulating Sfrp1 expression was rs33030926 ( P = 5 . 0×10−11 ) located at 24 . 587852 Mbp . This SNP was also the most significantly associated with the M9 eigengene ( P = 9 . 0×10−6 ) . Rs33030926 is located 27 . 7 Kbp downstream of the 3′ end of Sfrp1 . We hypothesized that rs33030926 ( or the causal variant linked to rs33030926 ) regulates Sfrp1 expression , which in turn influences the co-expression of M9 genes . To test this hypothesis , we used the Network Edge Orienting ( NEO ) causality modeling R package [37] . NEO is statistical approach used to determine the relationship between genetic variation and two traits . In our case we wanted to determine if rs33030926 affected Sfrp1 expression and if this in turn perturb the M9 . NEO was used to orient the relationships between rs33030926 , each of the 15 candidate regulators and the M9 eigengene by determining if the data best fit a causal model ( rs33030926→candidate eQTL→M9 eigengene ) or one of four competing models that could be used to explain the data . The causal model was the best fit for the Sfrp1 expression data with a causal score ( LEO . nb . AtoB ) of 2 . 80 ( Table 3 ) . The LEO . nb . AtoB scores for the other 14 candidate eQTLs were negative ( Table 3 ) . To further characterize the effect of Sfrp1 on the bone network we stratified mice by rs33030926 genotype and calculated the percent difference in transcript level in Sfrp1 and all M9 probes . For Sfrp1 , there was a 10 . 1% increase in transcript levels in strains ( N = 52 ) homozygous for the rs33030926 “C” allele , relative to strains ( N = 44 ) homozygous for the rs33030926 “T” allele . Similarly , its effect on M9 gene expression was subtle . The max percent difference in expression between rs33030926 genotypes for M9 probes was 27 . 2% with a mean of 7 . 4% ( Table 4 ) . We conclude that Sfrp1 induces strong correlations between M9 genes through the subtle coordinate regulation of their expression . To add additional support for the causal role of Sfrp1 , RNAi was used to knockdown Sfrp1 expression in pcOBs . At four days post differentiation , the expression of Sfrp1 was measured using qPCR and network-wide gene expression using microarrays . In cells transfected with a siRNA targeting Sfrp1 , its expression was reduced to 44% ( P = 0 . 001 ) of the level seen in cells transfected with the scrambled control . Similar to the in vivo data in the HMDP , the knockdown of Sfrp1 early in differentiation ( four days post-differentiation ) exerted only minor perturbations in network gene expression . Only a small number of the network genes were classified as differentially expressed ( FDR<0 . 05 ) . However , significant ( P<0 . 002 ) mean differences in expression ( difference in expression between pcOBs transfected with Sfrp1 siRNA and the scrambled siRNA ) were observed for modules 9 and 21 . In addition , the M9 was the only module with a significant mean percent difference in module gene expression in which there was a significant correlation ( r = 0 . 32 , P = 4 . 8×10−8 ) between the mean percent difference in the HMDP and in response to Sfrp1 knockdown , indicating that the same M9 genes that were perturbed in the HMDP were also altered due to Sfrp1 knockdown ( Table 4 ) . Our in vitro experiments are consistent with Sfrp1 regulating the coordinate expression of the M9 . Together , with the systems genetics analysis from the HMDP , these data identify Sfrp1 as a regulator of the M9 . If M9 behavior in the HMDP is reflective of osteoblast/osteocyte activity then we would expect that it would be associated with changes in bone mass in the HMDP strains . We previously measured BMD in all HMDP strains [27] . To assess its relationship with BMD , we determined the correlation between the M9 eigengene and BMD . The M9 eigengene was not linearly correlated ( r = −0 . 03; P = 0 . 71 ) with femoral BMD , however , as shown in Figure 7 there was a U-shaped relationship between the two . Based on this observation we fit a quadratic model ( M9 eigengene = BMD+BMD∧2 ) to the data ( Figure 7 ) . The quadratic model was a highly significant fit ( P = 1 . 1×10−6 ) . A shown in Figure 7 , strains with the highest M9 had either low or high BMD . As would be expected based on the observation that rs33030926 regulates Sfrp1 and the M9 eigengene , all the strains with high expression of the M9 eigengene and the lowest and highest BMD were ‘TT’ homozygotes ( Figure 7 ) . Similar patterns were observed for total body and spinal BMD ( data not shown ) . Importantly , these data provide additional evidence of the biological relevance of the M9 . It also suggests that the M9 reflects the complex , and often contradictory , role of osteoblast-lineage cells in bone homeostasis . To evaluate the potential relevance of the M9 to BMD in humans we determined if it contained genes that have been implicated in the regulation of BMD through human GWA studies . We used information from the largest GWA analysis for BMD performed to date . This study meta-analyzed data from 17 BMD GWA studies ( N = ∼32 K in the discovery phase and N = ∼50 K in the replication phase ) [38] . In this meta-analysis , a total of 64 independent SNPs reached genome-wide significance implicating 56 regions and 61 unique genes ( these genes were the closest to the most significant independent GWA SNPs ) . We were able to identify a mouse homolog for 57 of the 61 genes ( 93% ) and 39 were located within one of the 21 network modules ( Table 5 ) . Of these , five ( 8 . 7% of the total ) ( Lrp5 , Tnfrsf11b , Wnt4 , Gpr177 and Sp7 ) were members of the M9 . The probability of identifying five M9 genes among 57 randomly chosen genes from the network was P = 5 . 0×10−4 . After a Bonferroni correction for the 21 modules , the M9 was the only module to demonstrate this enrichment . These data indicate the M9 is enriched for genes that have been implicated in the regulation of BMD in humans .
In this study , we generated a co-expression network for bone that consisted of 21 “modules” , each of which contained genes that shared similar expression patterns and were enriched for functionally similar genes . We then focused on one module , the M9 , which was predicted to be specific for cells of the osteoblast-lineage . We demonstrated that the perturbation of M9 hub genes altered osteoblast proliferation and differentiation and for one hub , Maged1 , BMD in vivo . Additionally , we discovered that an Sfrp1 local eQTL was the key driver of M9 gene expression , that the M9 was associated with BMD in the HMDP and was enriched for the homologs of genes implicated in the regulation of BMD through human GWA studies . Traditional genetic and molecular approaches are powerful tools for dissecting cellular function , however , reductionist techniques may not be able to capture the overall organization of cellular interactions . Systems genetics is an approach that can provide an unbiased and more comprehensive view of not only the genes involved in cell function , but also key gene-gene interactions . By using the hundreds of thousands of genetic perturbations that exist in the HMDP to identify correlational patterns between genes on a genome-wide scale we were able to discover a core group of 354 genes that are highly co-expressed and function together in a network . We believe that this network acts to propagate or modulate major osteoblastic stimuli , such as Wnt signaling . Importantly , the M9 represents a wealth of information that can be mined in future experiments to increase our understanding of the genes and interactions that are critical for proper osteoblast-lineage function . The use of network analysis provided a number of unique advantages . First , WGCNA gave us the opportunity to group genes into modules based on their in vivo patterns of expression in whole bone and then determine which module was the most relevant to cells of the osteoblast-lineage . Second , in a traditional differential expression analysis across strains , only a small percentage of M9 genes would have been identified as differentially expressed and thus , potentially important in bone . Third , the discovery that M9 connectivity was highly correlated with GS could have only been made via network analysis . Lastly , integrating network analysis and GWA identified Sfrp1 as a regulator of the M9 . Although Sfrp1 is known to play an important role in the osteoblast lineage , our results have identified an entire network of genes that are novel downstream targets of Sfrp1 . A number of recent works have identified “module quantitative trait loci ( mQTL ) ” ( as examples [35] , [39] , [40] ) . Here , we identified Sfrp1 as the gene and its local eQTL as the mechanism underlying the mQTL regulating the M9 eigengene . This represents one of the first successful attempts at identifying the molecular basis of an mQTL . This was possible due to the ability to perform high-resolution genome-wide association in the HMDP and the tools of systems genetics . This study highlights the advantages of disentangling the genetics of co-expression module regulation using a high-resolution genetic reference population such as the HMDP . We observed that the M9 eigengene was inversely correlated with BMD in low bone mass mice and positively correlated with BMD in high bone mass mice . This nonlinear association is likely due the complex roles of osteoblast-lineage cells in bone [1] . Osteoblasts directly control bone formation and secrete Osteoprotegerin , a strong inhibitor of bone-resorbing osteoclasts [1] . Moreover , pre-osteoblasts and recently osteocytes , have been shown to secrete RANKL , which promotes osteoclastogenesis and bone resorption [8] , [9] , [41] . Therefore , M9 “activity” likely represents a balance between osteoblast-mediated bone formation and osteoblast/osteocyte-directed bone resorption . It is possible that the differential effect of high M9 activity in the HMDP is due to differences cell composition ( e . g . differences in the relative numbers of osteoprogenitors , mature osteoblasts and osteocytes ) or other factors that are determined by genetic background . Consistent with the role of genetic background , many of the low BMD HMDP strains with high M9 eigengene expression belonged to the AXB recombinant inbred set . More detailed phenotyping of strains with high M9 expression and low or high BMD will be needed to clarify the difference . At any rate , the association between M9 and BMD indicates that it reflects physiologically relevant differences in the activities of osteoblast-lineage cells . We identified a strong correlation between M9 connectivity ( kme ) and GS . This finding is important since it suggests that not only are M9 genes important , but the topology of the M9 network is also important for the function of osteoblast-lineage cells . This finding allowed us to use kme information to prioritize genes for validation . Because the most highly connected genes were the most correlated with GS , we choose the top two hubs for further investigation . Many of the top ten hubs are known to function in osteoblasts ( Table 2 ) ; however , the top two , Maged1 and Pard6g , have not been shown to directly participate in osteoblast proliferation , differentiation or mineralization . Using RNA interference we demonstrated that both genes play a role in osteoblast activity . The siRNA knockdown of Maged1 increased the proliferation of primary calvarial osteoblasts . It also increased the early expression of alkaline phosphatase , a marker of maturing osteoblasts . Surprisingly though , we found that it decreased mineralized nodule formation . Maged1 is a transcriptional co-activator involved in a wide-array of cellular processes such as the regulation of myogenic differentiation , circadian rhythms , sexual behavior and obesity , to name a few [30] , [31] , [42] . Maged1 has been shown to bind to the homeodomain protein DLX5 and is required for its transcriptional function [32] . Consistent with Maged1 affecting osteoblast function through DLX5 , mineralized nodule formation in osteoblasts from Dlx5−/− knockout mice is also lower . However , proliferation in Dlx5−/− osteoblasts is also decreased in contrast to the increase in proliferation we observed when Maged1 is knocked-down . The effect of Maged1 on proliferation in osteoblasts , however , is consistent with the observations that it inhibits proliferation in other cell-types [43] , [44] . This suggests the Maged1 may have effects on osteoblast function independent of DLX5 activity . The increase in alkaline phosphatase and Sp7 expression at 4 days post-differentiation ( both markers of osteoblast differentiation ) is hard to reconcile with the decreased mineralized nodule formation at 14 days post-differentiation . It is worth noting that Sp7 and Akp2 were the only osteoblast markers that were increased , which suggests that Maged1 knockdown may selectively result in increased Sp7 and Akp2 expression without inducing the complete differentiation cascade . However , as suggested above it could also reflect diverse roles for Maged1 in the osteoblast . An alternative explanation is that the conflicting early increase and late decrease in osteoblast differentiation is a result of the transient nature of Maged1 knockdown with siRNA . Most importantly , however , we demonstrate that Maged1 deficiency in vivo results in decreased BMD . This is consistent with decreased mineralized nodule formation in vitro . It is also consistent with Maged1 mediating its effects on osteoblast function through DLX5 , as Dlx5 deficient mice also have decreased bone mass [33] . Further work is needed to define the precise role of Maged1 in osteoblasts and how this translates into lower bone mass . The Par6 ( partition defective ) family of proteins was first identified in C . elegans and Drosophila as proteins required to establish cell polarity [45] . There are three homologues of Par6 in mammals , PARD6A , 6B and 6G [46] . The siRNA knockdown of Pard6g decreased both osteoblast proliferation and differentiation . It is possible that these effects of Pard6g are due strictly to the fact that cell polarity is an essential cellular process and are not necessarily reflective of Pard6g function in osteoblasts . However , we feel this is unlikely given its membership in the M9 and the fact that its expression is high in osteoblasts and its expression differs as a function of osteoblast differentiation . In addition , Par6 has recently been shown to be involved in skeletogenesis and biomineralization in the sea urchin [47] . Although more work is needed it is tempting to speculate that Pard6g is involved in Wnt signaling . Non-canonical Wnt signaling is a major regulator of cell polarity and the M9 contains non-canonical Wnts such as Wnt4 ( also a gene associated with BMD in humans ) [48] . The Wnt signaling pathway is a major pro-osteoblast stimulus [10] . In osteoblasts , Wnts bind frizzled ( Fzd ) receptors and their co-receptors ( LRP5 and LRP6 ) and induce the stabilization and translocation of ß-catenin to the nucleus [10] . Sfrp1 antagonizes Wnt signaling by interfering with the interaction between Wnts and Fzd receptors [49] . Sfrp1 knockout mice are resistant to age-related decreases in trabecular bone mass and display reduced osteoblast/osteocyte apoptosis and increased osteoblast proliferation and differentiation [50] . Conversely , Sfrp1 transgenic mice have decreased trabecular and cortical BMD and decreased osteoblast proliferation and differentiation [25] . Using genome-wide association we identified Sfrp1 as a regulator of M9 . Based on its known role in cells of the osteoblast-lineage , its discovery as a major regulator of the M9 is consistent with M9 representing a core network operative in osteoblasts/osteocytes . There has been interest in developing therapeutics targeting Wnt signaling in general and Sfrp1 specifically . In fact , Bodine et al . demonstrated that piperidinyl diphenylsulfone sulfonamide could bind and inhibit the activity of SFRP1 [51] , [52] . However , there is concern that Sfrp1 is a poor drug target based on its broad tissue expression and the link between Wnt signaling and various cancers [26] . Given that Sfrp1 regulates M9 gene expression it is likely that many M9 genes are downstream targets of Sfrp1 and more generally Wnt signaling . This notion is supported by the observation that the perturbation of Maged1 and Pard6g expression resulted in similar effects on pcOBs as did Sfrp1 alteration [25] . Targeting M9 genes could promote increased bone formation in a more bone-specific manner . Recent studies have demonstrated that co-expression modules can be conserved across species; therefore , it is of significant interest to know if the human homologs of M9 genes function in a similar network . We will directly investigate this in future studies , however , the fact that conserved pathways ( primarily Wnt signaling ) are represented in the M9 suggests that the majority of M9 genes will also play a role in the function of osteoblast-lineage cells in humans . Additionally , the fact that nearly 10% of genes implicated in the most comprehensive BMD GWA meta-analysis performed to date are members of the M9 further support the notion that the M9 is relevant to the regulation of human BMD . It is worth noting that 4 of the 5 M9 human BMD genes are involved directly in Wnt signaling , which again suggests that this signaling pathway is a major component of the M9 . Our approach is not without limitations . One possible limitation , which also may have been an advantage , was the generation of expression data from bone tissue . An alternative approach would have been to profile isolated cell populations . This may have been more informative since it is clear that the different cells in the osteoblast-lineage perform distinct and often contradictory functions . On the other hand , the profiling of bone cells in their native complex cellular milieu may have resulted in expression profiles that were more representative of their true in vivo state . At any rate , we do believe that it will be informative in future studies to repeat this analysis using isolated cell populations as this may remove some of the noise associated with averaging expression across multiple cell-types . A second limitation was our use of siRNA in primary calvarial osteoblasts to validate the role of Sfrp1 , Maged1 and Pard6g . In terms of Sfrp1 , we perturbed its expression in vitro at one time point in osteoblasts isolated from neonatal mice . Although this system allowed us to test the hypothesis that Sfrp1 preferentially modulated the expression of M9 genes , it did not fully recapitulate the effects of Sfrp1 expression differences in the HMDP . It is known that Sfrp1 has many effects on osteoprogenitors , mature osteoblasts and osteocytes [50] . Thus , it would have been more ideal to test the effect of Sfrp1 perturbation in vivo , which will be the focus of future investigations . The same is true for Maged1 and Pard6g . Although we clearly demonstrate their involvement in osteoblast proliferation and differentiation , it is possible that we missed many aspects of their function by focusing on just two stages in the complicated life-cycle of an osteoblast-lineage cell . This is especially true in the case of Maged1 were we observed that its reduction increased certain aspects of early osteoblast differentiation , but later decreased mineralized nodule formation . In summary , we have used a systems genetics approach consisting of co-expression network analysis , eQTL analysis , genome-wide association and causality modeling in a powerful mouse genetic reference population to identify a module ( M9 ) of co-expressed genes that play an important role in the function of osteoblast-lineage cells . These data improve our understanding of the gene networks important for osteoblast function and demonstrates the ability of systems genetics to unravel gene networks involved in complex cellular processes .
The Institutional Care and Use Committee ( IACUC ) at the University of California , Los Angeles approved the animal protocol for the HMDP . The animal protocol for the isolation of primary calvarial osteoblasts was approved by the University of Virginia IACUC . The manipulations of Maged1-deficient mice has been approved by the local ethics committee of the University of Namur and follow the European legislation . Data from Hybrid Mouse Diversity Panel ( HMDP ) were generated from 16-week old male mice from 96 inbred strains . More details regarding the population can be found in [27] , [28] . RNA isolation and Illumina microarray processing for bone tissue samples from the HMDP are described in [26] . The expression data are available from the NCBI Gene Expression Omnibus ( GEO ) database ( GSE27483 ) . The quantification of femoral , spinal and total BMD in the HMDP has been described in [27] . The Maged1-deficient mice and control littermates used in this study have already been described [53] . Experiments were done with male mice aged 18 weeks backcrossed for >10 generations in the C57Bl/6J genetic background . Body composition and BMD was measured using a dual-energy X-ray absorptiometry ( DEXA ) scanner ( Lunar PIXImus2; GE Healthcare ) . All scans were analyzed using the PIXImus2 software ( version 2 . 10 ) . For the calculation of total body BMD the skull was excluded from the analysis . Network analysis was performed using the WGCNA R package [54] . All 45 , 759 array probes were used to construct the bone network . We did not collapse multiple probes per genes down to a single probe representing each gene since many of the seemingly redundant probes actually recognize alternatively spliced isoforms . We also did not have to worry that the inclusion of probes that were not expressed would add noise , since the vast majority of such probes would not be expected to exhibit biologically meaningful correlations with a large number of other transcripts . The approach also allowed for the inclusion of probes that are truly expressed , but at a level that may not have exceeded a particular “expressed/not expressed” threshold . To generate the co-expression network , we first calculated Pearson correlation coefficients for all gene-gene comparisons across all microarray samples . The matrix of correlations was then converted to an adjacency matrix of connection strengths . The adjacencies were defined as where and are the and gene expression traits . The power was selected using the scale-free topology criterion previously outlined by Zhang and Horvath [55] . In this study a = 8 was used . Modules were defined as sets of genes with high topological overlap [21] . The topological overlap measure ( TOM ) between the and gene expression traits was taken as , where denotes the number of nodes to which both and are connected , and indexes the nodes of the network . A TOM-based dissimilarity measure was used for hierarchical clustering . Gene modules corresponded to the branches of the resulting dendrogram and were precisely defined using the “Dynamic Hybrid” branch cutting algorithm [56] . A principal component analysis was used to generate a vector of values ( first principal component ) that summarized or were the most representative of each modules expression . Intramodular connectivity ( kme ) was defined as the correlation between a gene's expression and its module eigengene . Highly similar modules were identified by clustering and merged together . Network depictions were constructed using Cytoscape [57] . The gene content of each module was characterized using the DAVID gene enrichment analysis tool [58] , [59] . Gene Significance ( GS ) for each network gene was defined as the absolute value of its correlation with the eigengene of a set of nine osteoblast/osteocyte marker genes identified from the literature . Module Significance ( MS ) was calculated as the mean GS for each module . Significance of the MS was determined for each module by randomly selecting x GS scores from the set of 13 , 579 network GS scores; where x is equal to the number of genes in that module . The mean for each set was then calculated and this was repeated 10 , 000 times . The true MS score was then compared to the distribution of random mean GS scores and P-values were calculated by counting the number of random mean GS scores that were greater than the true MS score divided by 10 , 000 . An MS score with a P<0 . 002 ( Bonferroni adjusted for the 21 modules tested ) was deemed significant . To determine the expression patterns of network genes in bone and bone cells microarray data on primary osteoclasts , primary osteoblasts , whole bone and bone marrow were downloaded from GEO ( GSE11339 and GSE10246 ) . The samples were derived from C57BL6/J mice in triplicate . The osteoblast samples were comprised of three different time-points ( 5 , 14 and 21 days of differentiation ) assayed in triplicate . For each module the log2 fold expression of its genes in osteoblasts ( highest of the three time-points ) were compared to the other samples . Statistical significance of the increase in expression in osteoblasts was determined as described above for GS and MS . EMMA and its application to HMDP data has been described in [27] , [28] , [36] , [60] . EQTL hotspots for the M9 were identified by performing genome-wide association for the expression of all 13 , 759 network probes using EMMA . SNPs were clustered into 531 , 5-Mbp bins across the genome and for each network probe , the minimum association p-value was recorded for each bin and the number of probes with p-values that exceeded −logP≥4 were counted . Enrichment P-values were then assigned to each bin using a Fisher's exact test to compare the frequency of significant associations for M9 probes relative to all other network probes . Bins with P<0 . 05/531 = 9 . 4×10−5 were deemed significant . Causality modeling was performed as described in [61] , [62] . Briefly , NEO is an R function designed to orient the relationships between genetic markers , gene expression traits and clinical traits [37] . NEO utilizes the fact that all cellular information begins with DNA and therefore , the many possible relationships that can exist between DNA variation , gene expression and clinical traits can be distilled to three . The three relationships ( or models ) are: 1 ) causal – flow of information goes from DNA to gene to BMD ( gene's expression is causing the change in the trait ) ; 2 ) reactive – flow of information goes from DNA to BMD to gene ( gene's expression is reacting to the change in the trait ) and 3 ) independent – DNA variation affects both traits independently . NEO uses structural equation modeling to estimate the probabilities for each of the three relationships . The log10 ratio of the causal model probability relative to the next best model probability ( of the two remaining ) is then calculated . This ratio ( referred to as the LEO next best or LEO . NB score ) quantifies the relative likelihood that a gene's expression is causal for a trait such as BMD . Simulation studies have demonstrated that single marker LEO . NB scores above 1 . 0 are highly suggestive of causal relationships [37] . The mouse homologs for human genes nearest the most significant SNP for all genome-wide significant associations identified in [38] were identified . A clear homolog was identified for 57 associations . The module membership for each of the 57 genes was then determined . Enrichment p-values for each module were calucated by randomly selecting×genes , where x is the number of genes in a given module , out of the 30 , 264 unique genes used to generate the network . This was repeated 10 , 000 times . The number of randomly selected genes that overlapped the GWA set in each random selection was then recorded . The enrichment P-value was calculated as the number of times ( out of 10 , 000 ) the overlap equaled or exceeded the actual number observed for each module . An enrichment P-value corrected for the 21 modules ( 0 . 05/21 = 0 . 0023 ) was deemed significant . Three to nine day old neonates from C57BL/6J breeding pairs ( obtained from Jackson Laboratory , Bar Harbor , ME ) were euthanized by CO2 inhalation followed by decapitation . The heads were sprayed with 70% ethanol and placed in sterile cold DPBS ( Gibco ) . Using sterile instruments , the skin was removed from the skull , calvariae were removed and placed into sterile cold DPBS ( Gibco ) . Harvested calvariae were then placed in sterile digestion solution ( 0 . 05% Trypsin-EDTA , 1 . 5 U/ml Collagenase P , MEM Alpha ) and incubated at 37°C , with 120 rpm shaking for 15 minutes . Four digests were performed , the first being discarded . For the remaining three digests an equal volume of sterile plating media ( DMEM , 10% heat-inactivated FBS , 100 U/ml penicillin , 100 ug/ml streptomycin ) was added to each immediately following its collection and stored on ice . The fractions were combined , filtered through a 100 uM sterile vacuum filtration tube and counted . Cells isolated from 4–6 independent groups of 3–9 day old neonates were plated into 6 well plates at 300 , 000 cells/2 ml sterile plating media ( DMEM , 10% heat-inactivated FBS , 100 U/ml penicillin , 100 ug/ml streptomycin ) per well . After 24 hours , confluent cells ( Day 0 ) were washed 1× with DPBS ( Gibco ) and placed in sterile differentiation media ( DMEM , 10% FBS , 100 U/ml penicillin , 100 ug/ml streptomycin , 0 . 1 M ascorbic acid , 1 M B-glycerophosphate ) . Every 48 hours thereafter cells were washed one time with DPBS ( Gibco ) and differentiation media replaced . PcOBs were plated at 150 , 000 cells/2 ml plating media per well . Transfections were performed using Lipofectamine 2000 Reagent ( Invitrogen ) according to manufacturer's directions . A total of three Stealth Select RNAi siRNAs ( Invitrogen ) per gene were first tested using three different concentrations ( 0 . 2 nM , 2 . 0 nM or 10 nM ) . Knockdown of the target gene was tested at 48 hours using qPCR in undifferentiated pcOBs ( see below ) . All siRNAs demonstrated the most effective knockdown at 10 nM . The two most effective siRNAs for each gene were used for all downstream experiments with the exception of Sfrp1 and only one of the three provided more than 50% knockdown . The sense strand of the duplex siRNA sequences were as follows: Sfrp1 - MSS277026; CCGAGAUGCUCAAAUGUGACAAGUU; Maged1 – MSS294723; GCAAGGUUAAUAACUUGAAUGUGGA and MSS235163; UCAGAACGUGGAGUCCCGGACUAUA; Pard6g MSS234948; GCAACGGCAGCAUCCACAGAUUUCU and MSS234949; CAUAAGUCUCAGACCCUACGCUUCU . The Stealth RNAi Negative Control Duplex ( Invitrogen ) was used as a scrambled control . As a control , we also demonstrate in File S3 that knockdown of Kdelr3 ( a gene expressed in primary calvarial osteoblasts ) has no effect on mineralized nodule formation , providing additional support that the effects of target gene siRNA are due specific to the knockdown of Maged1 and Pard6g ( File S3 ) . At 24 hours post-transfection , cells were trypsinized ( 0 . 25% Trypsin-EDTA ) and re-plated in a 12 well plate . The following day cells reached 100% confluency ( Day 0 ) and were washed 2× with sterile DPBS ( Gibco ) and placed in sterile differentiation media ( DMEM , 10% FBS , 100 U/ml penicillin , 100 ug/ml streptomycin , 0 . 1 M ascorbic acid , 1 M B-glycerophosphate ) . Every 48 hours thereafter cells were washed 1× with DPBS ( Gibco ) and differentiation media replaced . Protein was extracted from pcOBs in 10% NP40 detergent containing protease inhibitors ( Thermo Scientific ) . The extracts were separated on 12% NativePAGE™ Novex Bis-Tris Gels ( Life Technologies ) and transferred to PVDF membranes . Antibodies were obtained from Santa Cruz Biotechnology ( PARD6G ) and Milipore ( MAGED1 ) . Bound antibodies were visualized using the Western Lightning Plus-ECL ( Perkin-Elmer ) . ImageJ ( NIH ) was used to quantify individual bands by normalizing the density of the target band ( MAGED1 or PARD6G ) by the density of the ß-ACTIN band for each sample . Total RNA was isolated using RNeasy Mini-Kit ( Qiagen ) according to manufacturer's instructions followed by genomic DNA decontamination using DNA-free kit ( Applied Biosystems ) according to manufacturer's directions . cDNA was synthesized using the High-Capacity cDNA Reverse Transcription kit ( Applied Biosystems ) according to manufacturer's instructions using C1000 Thermal Cycler ( Bio-Rad ) . Quantitative real-time PCR ( qPCR ) was performed on 50 ng cDNA template , 10 uM each forward and reverse primer , and SensiMix Plus SYBR kit ( Quantace ) according to manufacturer's directions in 20 ul total volume using an ABI 7900 thermocycler . The following primer sets were used ( all sequences 5′-3′ ) : Maged1–F , AGATGGCTCCCAGACTCAGA; Maged1–R , CCTTTGATCCCCACTGTTGT; Pard6g–F , TGACGACAACTTCTGCAAGG; Pard6g–R , GCTCCGAAGCTGTAATGGTC; Sfrp1-F , TACCACGGAAGCCTCTAAGC; Runx2-F , ACAGTCCCAACTTCCTGTGC; Runx2-R , CACAGTCCCATCTGGTACCTC; Sfrp1-R , TCGCTTGCACAGAGATGTTC; Sp7–F , TGCCCCAACTGTCAGGAG; Sp7–R , GATGTGGCGGCTGTGAAT; Akp2–F , CCTTGAAAAATGCCCTGAAA; Akp2–R , TTACTGTGGAGACGCCCATA; Ibsp-F , GAGGAGACTTCAAACGAAGAGG; Ibsp-R , ACACCCGAGAGTGTGGAAAG; Col1a1-F , CCCAAGGAAAAGAAGCACGTC; Col1a1-R , AGGTCAGCTGGATAGCGACATC; Bglap2–F , GAACAGACAAGTCCCACACAGC; Bglap2–R , AGAGACAGAGCGCAGCCAG; 36B4-F , ACTGAGATTCGGGATATGCTGT; 36B4-R , TCCTAGACCAGTGTTCTGAGCTG . Relative quantification was determined by the 2 ( −Delta Delta CT ) ) method using the 36B4 gene as reference gene [63] . The results were obtained from N = 4 independent experiments . Microarray expression profiles were generated using the MouseWG-8v2 BeadChips ( Illumina , San Diego , CA ) . Briefly , biotin-16-UTP labeled cRNA was synthesized using the Illumina TotalPrep RNA Amplification Kit ( Ambion , Austin , TX ) . A total of 850 ng of cRNA was then hybridized to the Illumina BeadChips . Microarrays were scanned using the Illumina iScan system and background corrected signal intensities were extracted using the GenomeStudio software ( Illumina ) . The lumi R package was used to transform the data using a Variance Stabilizing Transformation ( VST ) and normalized using quantile normalization [64] . Proliferation was measured in pcOBs by plating cells at a density of 2000 cells/dish in 96 wells , treating as indicated and proliferation rate was determined using the BrdU ELISA assay ( Roche ) . The results were obtained from N = 6 independent experiments . Quantitative analysis of soluble alkaline phosphatase activity in cell extracts was performed using a colorimetric kit ( AnaSpec ) that measures the conversion of p-nitrophenyl phosphate to p-nitrophenol according to the manufacturer's instructions . Alkaline phosphatase activity was normalized to protein concentration . Protein levels were determined using using the bicinchoninic acid ( BCA ) assay according to the manufacturer's instructions ( Pierce ) . Mineralized nodule formation was measured by staining cultures at 12 days post-differentiation with Alizarin Red ( 40 mM ) ( pH 5 . 6 ) . The stained cells were imaged and nodule number was measured using ImageJ ( NIH ) . Alizarin Red was quantified by destaining cultures with 10% Acetic Acid and determining the optical density ( 405 nM ) of the resulting solution . The results were obtained from N = 4 independent experiments . | The osteoblast-lineage consists of a range of cells from osteogenic precursors that mature into bone-forming osteoblasts to osteocytes that are entombed in bone . Each cell in the lineage serves a number of distinct and critical roles in the growth and maintenance of the skeleton , as well as many extra-skeletal functions . Over the last decade , many of the major regulatory pathways governing the differentiation and activity of these cells have been discovered . In contrast , little is known regarding the composition or function of gene networks within the lineage . The goal of this study was to increase our understanding of how genes are organized into networks in osteoblasts . Towards this goal , we used microarray gene expression profiles from bone to identify a group of genes that formed a network specific to the osteoblast-lineage . We used the knowledge of this network to identify novel genes that are important for regulating various aspects of osteoblast function . These data improve our understanding of the gene networks operative in cells of the osteoblast-lineage . | [
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] | 2012 | Systems Genetic Analysis of Osteoblast-Lineage Cells |
Several medically important mosquito-borne flaviviruses have been detected in Argentina in recent years: Dengue ( DENV ) , St . Louis encephalitis ( SLEV ) , West Nile ( WNV ) and Yellow Fever ( YFV ) viruses . Evidence of Bussuquara virus ( BSQV ) and Ilheus virus ( ILHV ) activity were found , but they have not been associated with human disease . Non-human primates can act as important hosts in the natural cycle of flaviviruses and serological studies can lead to improved understanding of virus circulation dynamics and host susceptibility . From July–August 2010 , we conducted serological and molecular surveys in free–ranging black howlers ( Alouatta caraya ) captured in northeastern Argentina . We used 90% plaque-reduction neutralization tests ( PRNT90 ) to analyze 108 serum samples for antibodies to WNV , SLEV , YFV , DENV ( serotypes 1and 3 ) , ILHV , and BSQV . Virus genome detection was performed using generic reverse transcription ( RT ) -nested PCR to identify flaviviruses in 51 antibody-negative animals . Seventy animals had antibodies for one or more flaviviruses for a total antibody prevalence of 64 . 8% ( 70/108 ) . Monotypic ( 13/70 , 19% ) and heterotypic ( 27/70 , 39% ) patterns were differentiated . Specific neutralizing antibodies against WNV , SLEV , DENV-1 , DENV-3 , ILHV , and BSQV were found . Unexpectedly , the highest flavivirus antibody prevalence detected was to WNV with 9 ( 8 . 33% ) monotypic responses . All samples tested by ( RT ) -nested PCR were negative for viral genome . This is the first detection of WNV-specific antibodies in black howlers from Argentina and the first report in free-ranging non-human primates from Latin-American countries . Given that no animals had specific neutralizing antibodies to YFV , our results suggest that the study population remains susceptible to YFV . Monitoring of these agents should be strengthened to detect the establishment of sylvatic cycles of flaviviruses in America and evaluate risks to wildlife and human health .
Emerging and re-emerging diseases are one of the main threats to global public health; 60% of these diseases are zoonoses ( diseases shared between humans and vertebrate animals ) and the majority originated from wildlife [1] . The increasing incidence of these diseases is related to the intense ecological changes that occur at local , regional , and global scales . Several unexpected emergences of zoonotic flaviviruses worldwide were recently recognized . The introduction of West Nile virus ( WNV ) and Zika virus ( ZIKV ) into the New World [2 , 3] and the emergence of Japanese encephalitis virus in Australia a few prominent examples [4] . Currently there are 39 defined members of the mosquito-borne viruses of the genus Flavivirus [5] . They usually infect a variety of vertebrate and mosquito species . Some flaviviruses have a limited number of hosts and vectors , others replicate in many hosts and vectors . Some have an extremely widespread distribution; others are spatially restricted . The potential of flaviviruses to cause disease in humans is significant and they have a potential to induce losses in livestock or wild animals of economic and ecological importance . Several of the most prominent and medically important mosquito-borne flaviviruses were detected in Argentina in recent years: Dengue virus ( DENV ) , St . Louis encephalitis virus ( SLEV ) , WNV and Yellow Fever virus ( YFV ) . During 2016 , Zika virus was also detected in Argentina with autochthonous circulation restricted to Tucuman Province [6] . Other flaviviruses circulating in Argentina include Bussuquara virus ( BSQV ) and Ilheus virus ( ILHV ) , which have not yet been associated with human disease [7] . Dengue viruses have emerged as the most important human arboviral pathogens from non-human primate enzootic reservoirs to humans resulting in an urban endemic transmission cycle . In Africa and Southeast Asia the viruses have been maintained in a sylvatic cycle , most likely involving non-human primates as reservoirs . These cycles have not been recognized in South America , but serological studies have suggested a possible secondary amplification cycle involving mammals other than non-human primates . The question of whether mammals maintain DENV in enzootic cycles and can play a role in its reemergence in human populations remains to be answered [8 , 9] . Argentina was free of dengue for more than 80 years before the disease was detected in 1998 . However , in the last 18 years , indigenous DENV circulation has been reported in Northern and Central Argentina , representing a growing public health problem [6 , 10 , 11] . Since 2002 Argentina has experience the re-emergence of SLEV , with febrile illness and encephalitis outbreaks in humans , mainly in temperate areas of the country [12–14] . Genotypes II , III , V , and VII of SLEV were detected in mosquitoes and rodents [15 , 16] . High SLEV antibody prevalence was demonstrated in black howlers in Argentina and southern Brazil but the role that primates could play in viral maintenance in nature is unknown [17 , 18] . The isolation of WNV from equines in Argentina in 2006 was the first direct evidence of its circulation in the Southern Cone . Nucleotide sequences showed that the virus belonged to clade 1a of lineage 1 and clustered in a subclade with American strains isolated during 1999–2002 [19 , 20] . Public health surveillance in Argentina detected sporadic human cases in 2006–2007 in five provinces of the northeast and central areas of the country ( Chaco , Entre Ríos , Formosa , Santa Fé , and Córdoba Provinces ) but the impact on animal and human public health was considerably lower than in the northern hemisphere until now [21 , 22] . Detection of WNV in resident birds in 2005–2006 suggested that it was introduced into Argentina and maintained naturally in enzootic foci where numerous bird species from many families were exposed [23] . The transmission cycle of WNV commonly involves birds and Culex mosquitoes , but it is not well known in Argentina . Recent studies of vector competence showed that Argentine Culex are competent vectors , but they were characterized as moderately efficient vectors of WNV and less susceptible to infection than US mosquito strains [24] . Yellow fever is an infectious disease that remains endemic or enzootic in rainforests of South America and sub-Saharan Africa . The sylvatic yellow fever cycle is maintained by viral circulation between monkeys and diurnally active mosquitoes that breed in tree holes in the forest canopy . Many species of non-human primates are hosts of this cycle . The species most commonly involved in virus transmission are New World monkeys of the genera Cebus , Alouatta , and Callithrix . The susceptibility of monkeys to lethal infections of YFV in America has been considered a major indicator for enzootic disease outbreaks in forest areas [25–27] . Sylvatic cases of yellow fever in humans were often preceded by epizootics in animals in Brazil and Argentina [28 , 29] . Black howlers inhabit the Chaco and Pantanal ecoregions in Brazil , Paraguay , Bolivia , and north-northeastern Argentina , a small portion of the Atlantic Forest in Misiones Province , Argentina , and the state of Rio Grande do Sul , Brazil [30–32] . Epizootics were reported in Argentina during 2007–2009 in Misiones and Corrientes Provinces where four native species of monkeys live , including the black howler ( Alouatta caraya ) [33 , 34] . This species has the southernmost distribution of all primate species in the Neotropics , reaching latitude 29°S . In Argentina , black howlers inhabit a complex forest consisting of humid Chaco forest , savannas , gallery forest , and flooded forest ( Chaco , Formosa , Corrientes , and Santa Fe provinces ) . Their populations in the upper Paraná Atlantic Forest are fragile and recurrence of YFV circulation or other pathogens could be harmful to the species maintenance [35 , 36] . Viruses and viral disease outbreaks play an ecological role increasingly recognized in populations of wild animals . At least 27 viruses have been reported to infect both humans and wild primates and most of them are classified as emerging threats to human populations [37 , 38] . The rapid expansion of human activities into habitats of primates has resulted in increased potential for exchange of pathogens , creating challenges for biodiversity conservation and global health . The role of many wildlife species as reservoirs for arthropod-borne viral pathogens is poorly understood . Virus-specific antibody detection in a wildlife species could indicate a reservoir host or a species that could serve as a sentinel for virus activity in nature . Due to the impact of recent yellow-fever epidemics , there was special concern about the status of the black howler , which is the monkey species most affected by epizootics in Argentina . We conducted serological and molecular tests to detect flavivirus circulation in free-living black howlers in Northeast Argentina in 2010 .
The study was carried out in July–August 2010 in San Cayetano ( SC ) , Corrientes province ( 27 ° 34 'S , 58 ° 41' W ) ; Isla del Cerrito ( IC ) ( 27° 17´S , 58° 37´W ) , and Isla Brasilera ( IB ) , Chaco province ( 27 ° 20 'S , 58 ° 40' W ) in northeastern Argentina ( Fig 1 ) . San Cayetano is a savanna with degraded and fragmented semi-deciduous forest . Forest fragments have been modified by deforestation , cattle introduction , the reuse of land for plantations , and burning trees allowing humans and monkeys to live in close association [39] . Isla del Cerrito and Isla Brasilera are at the confluence of the Paraguay and Paraná Rivers and are characterized by continuous flooded forest . Sites were classified following two criteria: areas where primate habitat overlapping human populations and agricultural activities ( SC and IC ) and wild areas where human contact is rare ( IB ) . Captured black howlers were immobilized with methomidine hydrochloride combined with ketamine hydrochloride , administered via a dart driven by compressed air . To maintain body temperature at optimum conditions , animals were covered with blankets and warm water bottles were placed with them throughout the procedure . From 109 captured black howlers , we collected 108 blood samples . Distribution by provinces was 51 ( 51 . 5% ) captures in Chaco and 58 ( 48 . 5% ) in Corrientes . Sex , weight , and measurements were recorded [40] . Of the animals studied , 43 ( 39 . 8% ) were female and 65 ( 60 . 2% ) were male; 85% were adults and the rest were immature . Blood samples were obtained by puncture of the femoral vein . After evaluation of their health , each animal was transferred to the exact site of capture and observed until it moved into the habitat . Blood samples were centrifuged for at least 10 min at 2000 x g for serum separation and stored in liquid nitrogen in the field . At the laboratory , samples were frozen at -80°C until tested . This research complied with the Code of Best Practices for Field Primatology ( International Primatological Society ) , the guidelines for the ethical treatment of primates ( IACUC protocol 09267 ) and the laws of Argentina ( through Dirección de Recursos Naturales , Provincia de Corrientes and Dirección de Fauna , Provincia de Chaco , plus approval of the National Institute of Human Viral Diseases , Dr . Julio I . Maiztegui , Ethics Committee for Biomedical Research . The animal capture and identification techniques were designed to be less invasive to preserve the welfare of the animals and relieve potential stress . Serum samples were heat inactivated at 56°C for 30 min . Two-fold serial dilutions from 1:10 to 1:2560 of each sample were incubated with 100 plaque-forming units ( PFU ) of WNV ( strain ChimeriVax TM WNV ) , SLEV ( strain ChimeriVax TM SLEV ) , DENV-1 ( strain Hawaii ) , DEN-3 ( strain H87 ) , YFV ( vaccine strain 17D-YEL ) , ILHV ( Original ) and BSQV [41] . Vital dye neutral red was used at 5% for plaque visualization . Plaques were counted and titers were calculated and expressed as the reciprocal of the serum dilution yielding a ≥90% reduction in PFU on Vero cells ( PRNT90 ) . Titers ≥10 were considered positive . Monotypic or heterotypic patterns were differentiated according to whether the animal was positive to one or several flaviviruses , respectively . In heterotypic patterns , interpretation of PRNT data was as follows: animals with a neutralizing antibody titer ( PRNT90 ) ≥ four-fold higher than the other flavivirus titers were considered positive for antibody to that virus . Animals with neutralizing antibody titers against multiple viruses without four-fold difference in titer were considered flavivirus antibody positive with no specific virus identified and labeled as “undetermined” flavivirus . The molecular approach was performed on sera from 27 animals that were PRNT90 antibody negative for all the flaviviruses in our panel and 24 animals that were YFV antibody negative . Viral RNA was extracted from 140 uL of serum using QIAamp viral RNA extraction kit ( Qiagen , Inc . , Valencia , California , USA ) and then generic reverse transcription ( RT ) -nested PCR was used to identify flaviviruses . This procedure was used to amplify a specific 143-bp fragment of the NS5 gene [42] . The amplified products were visualized by ethidium bromide staining after electrophoresis on a 2 . 0% high-resolution agarose gel .
Of the 108 black howlers studied , 64 . 8% ( 70/108 ) had evidence of past flavivirus infection . Monotypic ( 13/70 , 19% ) and heterotypic ( 27/70 , 39% ) patterns were differentiated . The remaining 42% of antibody-positive animals was classified as undetermined for virus identification . We identified specific neutralizing antibodies against WNV , SLEV , DENV-1 , DENV-3 , ILHV and BSQV . Antibody prevalences were 22 . 2% ( 24/108 with 9 monotypic responses ) for WNV , 10 . 2% ( 11/108 ) for SLEV , 1 . 85% ( 2/108 , 100% monotypic ) for DENV ( 1/108 DENV-3 and 1/108 DENV-1 ) , 0 . 93% ( 1/108 , monotypic ) for ILHV , and 0 . 93% ( 1/108 , monotypic ) for BSQV . Distribution of PRNT90 titers are shown in Table 1 ( monotypic pattern ) and Table 2 ( heterotypic pattern ) . The WNV antibody titers ( and frequency ) in antibody-positive animals with monotypic pattern were: 20 ( 1 ) ; 40 ( 4 ) , 80 ( 3 ) , and 160 ( 1 ) ( Table 1 ) . The WNV antibody titer distribution in animals with heterotypic pattern was: 40 ( 6 ) ; 80 ( 2 ) ; 160 ( 2 ) ; 320 ( 4 ) , >1280 ( 1 ) ( Table 2 ) . There were no statistically significant differences in the prevalences of infection for each flavivirus between sexes or among study sites or habitat classes . When antibody distribution was analyzed by age , a statistical difference was observed only for WNV antibody prevalence in adult black howlers ( p = 0 . 0075 ) . In 30 of 70 animals ( 43% ) results were inconclusive because of neutralizing antibody titers against multiple viruses without fourfold difference; those were considered positive for an undetermined flavivirus ( Table 3 ) . We observed different reactivity among these: 73% ( 22/30 ) for WNV , 61% ( 18/30 ) for SLEV , 61% ( 18/30 ) for ILHV , 53% DENV-3 ( 16/30 ) , 47% ( 14/30 ) for DENV-1 , 33% ( 10/30 ) for BSQV and 7% ( 2/30 ) for YFV . For molecular studies , we selected serum samples from 51 animals . These were 27 animals without flavivirus antibodies and 24 that were YFV antibody negative . All animals analyzed by ( RT ) –nested PCR were negative for flavivirus genome .
Our goal was to understand the potential role of free-living black howlers as hosts in the natural cycles of flaviviruses in Argentina . The PRNT90 used to identify specific antibodies in black howler serum samples indicated a variable prevalence for one or more of six of the seven flaviviruses tested including WNV , SLEV , DENV-1 , DENV-3 , ILHV , and BSQV . No specific immune response to YFV was detected . Thirty-four groups of black howlers have been identified in the study area , in about 3 , 000 ha , several of these groups have been under behavioral study since 2000 [43 , 44] in undisturbed forest and in forest fragmented by human activities . These regions provide favorable conditions for the occurrence of outbreaks or for enzootic maintenance of arthropod-borne diseases . Yellow fever outbreaks occurred near this region in November 2007–October 2008 , seriously affecting the populations of two howler monkey species: the brown howler ( Alouatta guariba clamitans ) and the black howler . In these epizootics , the deaths of 65 monkeys were detected in Misiones and Corrientes provinces [33] . Herein we focused on the prevalence of infection in black howlers with those flaviviruses of recognized public health impact in Argentina ( YFV , DENV , SLEV , and WNV ) . We also included ILHV and BSQV because of their known occurrence in Argentine wildlife . All flaviviruses are serologically related , which can be demonstrated by binding assays suchas ELISA and by hemagglutination-inhibition tests using polyclonal and monoclonal antibodies . The PRNT90 is one of the most specific test available often used to define several serocomplexes of more closely related flaviviruses . The viral panel was employed to evaluate serological cross-reactions . To increase specificity , we selected a conservative threshold of 90% for PRNT . According with 9thReport of the International Committee of Taxonomy of Viruses [5] , WNV and SLEV have been placed together in the Japanese encephalitis group . DENV-1 , DENV-2 , DENV-3 and DENV-4 compose the dengue virus group . Ilheus virus was included in the Ntaya virus group and BSQV in Aroa virus group . Yellow fever virus is the prototype of the genus Flavivirus and is in its own virus group . Analysis of serological results requires careful evaluation especially when co-circulation of multiple flaviviruses is expected , as in Argentina . We found different immune patterns in the positive animals: 19% monotypic , 39% heterotypic , and 43% classified as undetermined for viral identification according to our criteria . We included 6 animals in the last group which had only titer of 10 for WNV ( 3 ) , SLEV ( 1 ) , DENV-3 ( 1 ) and ILHV ( 1 ) ; we couldn´t use 4 fold criteria because the lowest dilution studied was 1:10 . When individuals with no previous exposure to a flavivirus are infected with one , a monotypic response to the infecting virus is demonstrated in serological tests , such as PRNT , and the etiologic agent can be accurately identified . Interpretation of heterotypic patterns is complex and 4-fold difference in titers could be a limited criterion to provide distinction of the most recent infection . The antibody response in sequential experimentally infected animals illustrates the difficulty for a serologic diagnosis of WNV infection in animals ( or humans ) with preexisting flavivirus immunity [45] . Sequential infections with other flavivirus elicit strong cross-reactive anamnestic responses , which may confer immunity , especially within members of the same serogroup [46] . For example , sequential infections SLEV-WNV or WNV-SLEV would present different immune patterns that hinder serological differentiation of each [45] . Monotypic serologic responses were the most reliable as these samples reacted with only one of the 7 viruses employed in the tests . Selection of the virus in the panel is critically important . Future similar studies in Argentina might also include ZIKV . Prevalence of antibody to WNV antibody was the highest among the flaviviruses evaluated . The monotypic WNV prevalence was 8 . 33% ( 9/108 ) and represents the clearest serologic evidence of WNV activity in a new host in Argentina . We found WNV-positive black howlers at all sampling sites , demonstrating a widespread distribution in the study region . Higher WNV antibody titers were detected in the group with a heterotypic pattern . This type of response could reflect sequential infections or cross reactions originated by the higher antibody titers . We also detected WNV reactivity in 22 black howlers in the group classified as undetermined flavivirus , thus increasing the WNV antibody prevalence . Because of conservation considerations , we avoided capturing immature individuals or pregnant females . Thus , the higher prevalence in adults may reflect this capture bias . However , we should not rule out the possibility that this result could be due to undetected circulation of WNV in Argentina for some time before its isolation in 2006 [20 , 23] . Prevalence of detectable antibody to SLEV in our study was 11% ( 12/108 ) without monotypic reaction . This value would be increased if we considered the animals that were SLEV positive among the group classified as “undetermined flavivirus” . Investigations in black howlers from this zone in 2001 confirmed infections with SLEV with prevalences of 35% ( by hemagglutination test ) and 32% ( by PRNT ) . Studies in 2004–2005 demonstrated SLEV antibody prevalence ( 12% by hemagglutination test , 2% by mouse neutralization test ) in free ranging black howlers in the upper Parana River basin in southern Brazil [17 , 18] . St . Louis encephalitis virus is endemically established in Argentina and was recognized in several human encephalitis outbreaks in the last decade [12 , 13 , 14] . Our results indicate that SLEV and WNV could have been co-circulating within the region complicating the interpretation of serologic tests . Only four animals had low neutralizing antibody titers for YFV despite recent epizootics , two of those had specific heterotypic reactions for WNV and SLEV and the others were in the positive group for undetermined flavivirus . These results could represent cross-serologic reaction or past infection . On the other hand , 51 animals were negative for viral genome . We did not detect YFV circulation in black howlers . This small and fragmented population suffers habitat destruction , hunting pressure , and cyclical yellow fever and thus , is at risk of disappearing in the long term [47] . The low antibody prevalence detected suggests that the population remains susceptible to YFV . An interesting aspect would be to know if preexisting antibodies for other flaviviruses could play a protective role in future YFV infections . We detected monotypic reactions in PRNT90 against DENV-3 ( 0 . 93% ) and DENV-1 ( 0 . 93% ) . Titers obtained were low but serum samples were previously heat inactivated to eliminate nonspecific reactions . These dengue serotypes were selected because their previous circulation was confirmed in human cases detected in Misiones , Corrientes , and Chaco provinces in 2000–2008 . Besides , 47% of the animals were positive to DENV-1 and 53% for DENV-3 in the group of animals labeled us undetermined . As we mentioned previously , these results could be originated by cross reaction or they could represent limited spillback through contact with human environment , but we have to consider that other studies suggest the presence of sylvatic DENV in the Americas [48 , 49 , 50] . The establishment of a derived sylvatic cycle , as has happened with YFV in the Americas , will hinder the control of DENV in Latin America . Detection of DENV antibodies in black howlers in Northern Argentina underscores the importance of continuing the surveillance of these flaviviruses in non-human primate populations . Ilheus virus is believed to be maintained in zoonotic cycles between birds and mosquitoes and has been isolated in Central and South America primarily from mosquitoes but also from sentinel monkeys and birds [51] . There are few reports of isolation of ILHV from humans in Central and South America with symptoms ranging from subclinical to severe febrile disease . Mild unspecific symptoms , brief viremia , and lack of laboratory screening techniques in situ are some of the impediments to diagnosis of ILHV infection in disease-endemic areas . The situation is similar for BSQV . We detected low specific prevalences to ILHV and BSQV antibodies , but higher among the animals found positive for an undetermined flavivirus . Our work evidences circulation of WNV , SLEV , DENV-1 , DENV-3 , ILHV , and BSQV in wild , non-human primate populations of Corrientes and Chaco provinces , Argentina . Future studies might include ZIKV detection , which has been recognized in South America since 2015 . To our knowledge this is the first detection of WNV-specific antibodies in black howlers from Argentina and the first report in free-ranging non-human primates from Latin America . Additionally , our results show that our study population remains susceptible to YFV as no specific neutralizing antibodies were detected . The black howler population remains tentative in the upper Paraná Atlantic Forest . Recurrence of YFV circulation or other pathogens could be detrimental to the population’s existence . Improved monitoring of these agents is needed to evaluate risk to wildlife and human health in the region . | Flaviviruses are responsible for a growing disease burden in Argentina and other countries in the Americas . Non-human primates , such as monkeys , can be important hosts in the natural cycle of several flaviviruses . Yellow Fever virus outbreaks occurred in Argentina during 2007–2009 in areas of Misiones and Corrientes provinces inhabited by black howlers ( Alouatta caraya ) , a monkey that is highly susceptible to the virus . During 2010 we tested 108 black howlers from Northeastern Argentina for flaviviruses . Most of these animals were negative for Yellow Fever virus but had antibodies to several other flaviviruses . Unexpectedly , the highest specific neutralizing antibody prevalence was to West Nile Virus; these results represent the first evidence of West Nile Virus circulation in a new host in Argentina . Detection of Dengue virus antibodies in black howlers highlights the potential for establishment of a dengue sylvatic cycle , not yet demonstrated in the Americas . We call for strengthening the monitoring of flaviviruses to evaluate risk for wildlife and human health in the region . | [
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"vertebrat... | 2017 | Detection of the mosquito-borne flaviviruses, West Nile, Dengue, Saint Louis Encephalitis, Ilheus, Bussuquara, and Yellow Fever in free-ranging black howlers (Alouatta caraya) of Northeastern Argentina |
Clonal hematopoiesis of indeterminate potential ( CHIP ) is a recently identified process where older patients accumulate distinct subclones defined by recurring somatic mutations in hematopoietic stem cells . CHIP’s implications for stem cell transplantation have been harder to identify due to the high degree of mutational heterogeneity that is present within the genetically distinct subclones . In order to gain a better understanding of CHIP and the impact of clonal dynamics on transplantation outcomes , we created a mathematical model of clonal competition dynamics . Our analyses highlight the importance of understanding competition intensity between healthy and mutant clones . Importantly , we highlight the risk that CHIP poses in leading to dominance of precancerous mutant clones and the risk of donor derived leukemia . Furthermore , we estimate the degree of competition intensity and bone marrow niche decline in mice during aging by using our modeling framework . Together , our work highlights the importance of better characterizing the ecological and clonal composition in hematopoietic donor populations at the time of stem cell transplantation .
Hematopoiesis is a clonal process [1] . Hematopoietic stem cells ( HSCs ) are a small population of multipotent cells with self-renewal capacity for lifelong hematopoiesis . However , the very self-renewal capabilities of HSCs which make them so unique and versatile also make them vulnerable to the accumulation of somatic mutations [2] . Recently , studies have demonstrated that somatic mutation accumulation in hematopoietic cells in key cancer-related genes is cumulative over a patient’s lifetime [3–5] . The acquisition of somatic mutations that drive clonal expansion of hematopoietic stem cells is considered hematopoiesis of indeterminate potential ( CHIP ) [1] . From an evolutionary and ecological perspective , CHIP can be understood as the slow process of clonal diversification in the specific ecosystem of the bone marrow . Taking place over the course of a patient’s lifetime , the stem cell dynamics of hematopoiesis involve genetic variation , inheritance and potentially selection pressures . These are the pre-requisites necessary for evolution to occur and can eventually lead to mutations that convey dominant phenotypic changes and clinically manifest as malignancies [6] . Importantly , CHIP underscores the uncertainty in terms of health outcomes for patients that have these mutant hematopoietic clones . While CHIP has been linked with both cancers and other diseases [7] , the challenge of the condition is that the heterogeneity and range of genetic variation that could be present in a patient are poorly characterized and do not guarantee disease progression [1] . An area where the impact of CHIP has been less studied is the interaction between clonal diversity and stem cell transplantation . Stem cell or bone marrow transplantation ( BMT ) remains one of the most common treatments for myeloid and lymphoid leukemias . Transplantation types include allogenic donor marrow or the patient’s own marrow harvested before administration of high dose chemotherapy ( autologous ) [8] . However , the process of autologous BMT raises potential causes for concern when examined from an ecological point of view . Specifically , autologous BMT involves the sub-sampling of a genetically heterogeneous population and then repopulation in a recently emptied bone marrow microenvironment . It applies a population bottleneck to multiple clones without any clinical assessment of the composition of the reintroduced clones . Additionally , many of the cancers which are treated with autologous BMT occur in elderly patients [9] . Nationally , in the United States between 2012 and 2016 , roughly 70% of all autologous BMT patients were older than 51 years of age with approximately 40% of all patients being older than 61 years [10] . The age-association with CHIP has been examined to show that elderly patients at 65 years and above are far more likely to have both driver and non-driver mutations in their hematopoietic cells [3 , 4 , 11] . These include mutations in important cancer-protective genes such as p53 [3] . The frequency and potential impact of these clones in BMT remains unexamined . Indeed , clinical assessments prior to autologous transplantation do not consider clonal composition [12] , which raises the troubling possibility that autologous BMT from donors with CHIP may lead to the development of post-transplantation acute leukemias derived from a preexisting clonal population . Moreover , allogenic transplantation outcomes may be similarly impacted by the age of the donor . In order to investigate how clonal composition impacts transplantation outcomes , we use a mathematical framework that integrates the competition dynamics between healthy and mutant clones with the unique biological feedback mechanisms of the hematopoietic system . We specifically investigate the repopulation trajectories of patient bone marrow after differing compositions of healthy and mutant cells were transplanted . Of main concern is how the intensity of competition and the disparity in growth rate between healthy and mutant clones impact overall bone marrow outcomes . Finally , we broaden our investigation to understand the possible interactions of CHIP and patient marrow conditions . Just as aging leads to CHIP in donors , older patients also have compromised bone marrow . Specifically , aging has been associated with a decline in the capacity of bone marrow niches to support stem cells [13] . We investigate how differing degrees of bone marrow niche decline might interact with CHIP to influence transplantation outcomes . In this process , we use comparative stem cell measurements from mouse cohorts to estimate clonal competition parameters . In doing so , we suggest that poor patient marrow condition can potentially magnify the detrimental outcomes associated with CHIP . Our analyses underscore the importance of understanding the clonal composition of cells that may be undergoing transplantation and also the bone marrow microenvironment into which they are transplanted . The level of clonal competition has the potential to lead to very divergent outcomes in final patient hematopoietic states . However , ecological modeling provides a potential avenue for estimating these parameters and understanding the diversity contained within CHIP .
In order to model clonal competition during hematopoiesis , the bone marrow system was divided into healthy and mutant , pre-malignant clones . In addition to hematopoietic stem cells ( HSCs ) , mature myeloid , and mature lymphoid cells ( Fig 1 ) were also modeled . HSCs differentiate into mature cells after a period of time ( τ ) that represents cell cycle times as well as transit times from stem to progenitor then finally differentiated states . Recent studies with greater genetic resolution have demonstrated that even in healthy patients , the hematopoietic population is not uniform [3] . As patients age , there is increasing genetic heterogeneity that leads to a divergence between healthy and mutant hematopoietic clones [1] . Even if these mutant clones are not clinically defined as cancerous , they often exhibit mutations that could potentially lead to cancer later on [1] . In addition , these mutants are known to be different than healthy populations in multiple ways including their proliferation rates and their consumption of resources in the bone marrow microenvironment [1] . In this context , the goal of our modeling framework was to create a model of hematopoietic competition which takes into account the unique physiological feedback channels which control hematopoiesis [14] . We have modeled two separate but competing clonal lineages to represent the broad qualitative division of HSCs into healthy and mutant clones which were designated as clones 1 and 2 , respectively . However , we have made their differences quantitative to characterize , more clearly , how the degree of differences in parameters , such as competition intensity and growth rates , can impact reconstitution and disease dynamics . The degree of divergence in the healthy and mutant lineages is reflected in these ecological parameters . By representing the hematopoietic stem cell system as a composition of two major clonal lineages with different ecological characteristics , we both reflect current understanding of the diversity of HSCs in CHIP , but also retain and allow enough flexibility in the model framework to examine the spectrum of differences between these two extremes . We are able to quantitatively interrogate the relationship between these healthy and mutant lineages in overall HSC dynamics . Other mathematical models , notably from Ashcroft et al . [15] , have looked at clonal dynamics in transplantation from a stochastic perspective . However , while those analyses approximated clonal competition and growth as a Moran process , they do not take into account some of the biological complexities that distinguish the hematopoietic system . Our framework seeks to extend these studies by explicitly describing physiological demand as being a driver of differentiation [16] . In addition , we constrain our analysis to dynamics in the bone marrow , but incorporate daughter lineages of mature lymphoid and myeloid cells , as well as HSCs . Our framework models healthy ( H1 ) and mutant ( H2 ) hematopoietic stem cells , coupled to the dynamics of myeloid ( M1 , M2 ) and lymphoid ( L1 , L2 ) cells ( see Fig 1 ) . The two clones that are modeled interact with each other through interspecific ( Lotka-Volterra ) competition dynamics ( h1 , h2 ) in expression I of Eqs 1 and 2 . There is a common carrying capacity of HSCs ( KH ) which is limited by the availability of cytokines and other cellular growth factors . These interspecific competition dynamics are contained in a general logistic growth model with the maximum growth rate of stem cells described by r1 and r2 . While it is true that hematopoietic stem cells have been further classified depending on subsets of cell surface markers associated with differences in proliferative behavior , we have chosen to model them as one compartment with the dynamics focusing instead on the competition between the clones . Competition dynamics between healthy and leukemic stem cells have been explored in multiple other modeling paradigms . Our model seeks to describe pre-leukemic clones involved in CHIP instead of explicit competition between HSCs and leukemic stem cells . Other modeling works such as [17] have approached hematopoetic competition dynamics with an explicit division between healthy and malignant stem cells . In our framework , however , by implementing competition coefficients , we can describe dynamics in which the niches of different clones overlap and increase competition . This is in contrast to other systems which have used fixed niches and competition intensities [17] . Finally , in our daughter cell populations ( see Eqs 4 and 5 below ) , we implement a delay ( τ ) , which we show is significant in the context of recovering healthy cell levels post-transplantation . These previous competition models , even if using a similar differential equation method as ours , do not take developmental delays into account . A principal source of stem cell loss comes from differentiation to , eventually , mature myeloid and lymphoid cells and is modeled in expression II . Differentiation loss is due to a series of factors . Firstly , differentiated cells do not equally become myeloid or lymphoid cells . Instead , there is a specific fraction of cells which differentiate into the myeloid lineage ( ϕ ) with the remainder becoming lymphoid cells . Lineage determination fractions are then moderated by lineage-specific physiological demand [14 , 16] . Eq 3 represents the demand terms ( σM , σL ) which reflect how differentiation can increase for each lineage based on physiological necessity . Importantly , this is one of two mechanisms by which the two clones are intertwined ( with the other being the interspecific stem cell competition dynamics ) . Our model utilizes a demand-control design that integrates the current levels of myeloid and lymphoid cells and ties them to physiological demand [18] . The demand terms reflect the biological reality that stem cells are under constant feedback control . Both local ( adhesion , niche-specific growth factors ) and remote ( hormones such as erythropoietin ) mechanisms act to either promote or suppress stem cell activity based on the overall state of the hematopoietic system and the body . As in [18] , feedback mechanisms are dependent on the fully differentiated cells ( in this case the myeloid and lymphoid cells ) . Previous models [19] have used the means of the two clones’ output in calculating feedback . We have a similar implementation that takes into account the output of both clones but instead evaluates them relative to what is necessary to satisfy physiological demand . Dynamically , this demand signal decreases as the total myeloid and lymphoid cells reach the biologically-satisfying carrying capacities ( KM , KL ) . The gamma term ( γ ) represents a scaling relationship between physiological demand and differentiation fraction for the HSC compartment . Used together , our model views homeostasis as a state that is achieved when the final , mature myeloid and lymphoid daughter cells are close to carrying capacity . As cell populations drop from that desired level , there is an increase in upstream stem cell differentiation demand in order to remedy this gap . Finally , stem cells undergo apoptosis via expression III . While healthy stem cell apoptosis rates are relatively low due to their infrequent cell cycling , aging-related bone marrow degradation can lead to elevation of stem cell death ( see below ) . It should be noted , though , that this is an approximation that our model makes over the short term since our primary investigation is to simulate repopulation . Over the course of a lifetime , there are mutation accumulation processes which lead to the emergence of CHIP [3] . However , there are also aging processes which change the growth and division rates of stem cells . Other models have sought to quantitatively characterize this stem cell aging dynamic by dividing stem cell populations into dormant and proliferative stages [20] . In the short post-transplantation time frame , however , we make the approximation that these growth and death rates are invariant . Myeloid and lymphoid cells mature after a specific delay , τ , in expression I . A common delay term was used for both myeloid and lymphoid cells due to the high overlap in the variability of maturation times for lymphoid and myeloid cells . An alternative implementation of delay could have been a distributed delay . The common formulation is to use a gamma distribution as a representation of cells which are transiting through a series of compartments ( the ‘linear chain’ as in [21] ) . However a fundamental assumption of the linear chain model and distributed delays is that the flux ( number of cells transiting through each compartment ) is equal . This is not the case in stem cell systems where there are multiple rounds of proliferation which cause cells to amplify in number . This is how 105 hematopoietic stem cells can populate a hematopoietic system with 109 − 1010 of certain types of cells . Due to this violation of a key linear chain assumption , we instead opted to model differentiation as a simple average discrete delay . In addition , the α coefficients represent the amplification of the number of cells as successive rounds of reproduction and differentiation occur when cells transit from the HSC compartment to a final mature stage . This amplification is also modulated by the lineage bias terms from Eqs 1 and 2 . Lastly , there is a cell death term in expression II . This term , like the death term for stem cells , can be impacted by niche status . For multiple types of hematopoietic malignancies , including multiple myeloma [22] , acute lymphoblastic leukemia [23] and acute myeloid leukemia [24] , autologous BMT remains a widely implemented therapy . However , it has long been acknowledged that stem cells can only properly grow to fulfill physiological function when placed into the proper microenvironmental niche [25] . Additionally , it is increasingly understood that the bone marrow microenvironment also degrades with age and impedes the ability for HSCs to properly function . One prominent process is the loss of HSC-supporting endothelial cells via a reduction in vasculature within the bone marrow [13] . Specifically , type H endothelial cells are responsible for production of stem cell factor ( SCF ) which is crucial to HSC maintenance . SCF has been implicated for roles in both homing as well as promoting HSC self-renewal and survival [26] . In addition , defects in HSC homing mean that stem cells have a more difficult time entering the bone marrow from circulation to proliferate . From a bone marrow point of view , this is a functional loss of stem cells since HSC function is very microenvironmentally controlled [27] . Further , the lower degree of vascularization has been also attributed to lower levels of nitric oxide ( NO ) in aged bone marrow . This can cause greater oxygenation , since low NO levels trigger vasodilation , and increased damage to HSCs via reactive oxygen species ( ROS ) [28] . This production is on top of the fact that aging bone marrow has been shown to exhibit greater pro-inflammatory signaling which further leads to ROS production and toxicity for HSCs . Specifically , damage associated molecular patterns ( DAMPs ) increase in aged bone marrow and trigger TNFα and IL-6 signaling , which lead to ROS release and associated apoptosis [29] . Taken together , there is compelling molecular and experimental evidence that the aging bone marrow is far more hostile to hematopoietic cell survival than young , healthy marrow due to declines in niche quality and function . However , the quantitative impact has been so far unexamined in the context of clonal competition dynamics . In order to understand how this degradation of the microenvironment into which stem cells are transplanted influences their competition and repopulation dynamics , we varied the levels of niche degradation and cell death: δ H = δ H 0 + Δ , δ L 0 + Δ , δ M 0 + Δ . ( 6 ) The death rate of each type of cell was modeled as the sum of two components: baseline cell death ( δ H 0 , δ L 0 , δ M 0 ) which would be expected in a healthy , young bone marrow and the augmented death rate attributable to microenvironmental degradation ( Δ ) . The multiplicity of mechanisms by which the HSC niche in the bone marrow loses its integrity during aging means that Δ represents an average approximation . However , we have attempted to understand the impact that its variation could have with our sensitivity analysis ( see Results ) . In order to parameterize our simulations , we used values inferred from the literature and previous modeling works ( Table 1 ) . Measurements of HSC growth rates in the literature are challenging due to the variable activity states of stem cells [30] . While most cells are in a quiescent state , cell cycling does occur on a long timescale but with significant differences in observed rates . Spatially , this is represented by separate niches near either the vasculature or the endosteal surface of the bone [43] . Oxygen gradients along this axis are believed to be the main determinant of stem cell activity . Greater oxygenation near the vasculature , versus the more hypoxic bone surface , means that stem cells grow at a faster rate in the vascular and perivascular niche [32] . Studies of relative rates have also been carried out to find that the replication rate of HSCs is at least 10 times larger than their apoptosis rate [44] . Importantly , the values of r1 and r2 represent the maximum HSC growth rates under strong demand . Previous work by Stiehl et al . have implemented a similar growth rate for modeling clonal dynamics [45] . Stem cells are given a maximum possible self-renewal rate which becomes regulated by feedback control . For our model , we used various stem cell growth rates in order to understand how this biological variability might impact hematopoietic dynamics . A general order of magnitude approximation based on literature values was used to reflect the heterogeneity in growth rates that has been observed . Some in vivo estimates of HSC replication rates have suggested roughly 1 cell replication every 14 days [31] . This is representative of a general estimation of HSC growth rates being in the range of 0 . 1–0 . 01 cells/day . For our model we chose a baseline of 0 . 1 cells/day but evaluated growth rates smaller than that by altering the growth ratio between the two clones ( ρ ) . Stem cell growth is moderated by competition between mutant and healthy clones . This is biologically rooted in the fact that HSCs are competing for a finite pool of pro-growth cytokines [46] . In fact , it is the variation of these cytokines during exceptional biological circumstances , such as emergency hematopoiesis , which allows the body to regulate and augment stem cell activity [46] . Specific growth factors , such as erythropoetin , also elicit targeted effects for hematopoietic daughter lineages which might be in greater demand at a given time [47] . Pro-growth cytokines are also used therapeutically in the form of granulocyte colony stimulating factor ( G-CSF ) to help patients’ recovery from chemotherapy [48 , 49] . However , in spite of the mechanistic underpinnings of the competition dynamics for cytokines , quantitative measures between stem cell clones in the bone marrow remain elusive . In order to acknowledge this gap in the literature , we specifically investigated a range of stem cell competition rates and their cross-interactions with other hematopoietic parameters . A value of h = 1 was used as a basis in our analysis as a healthy baseline which we varied to understand its impact ( see Results ) . This is reasonable because in a healthy hematopoietic system there would be no difference between mutant and healthy cells . They exert the same amount of competition intensity on each other and they are governed by the same carrying capacity . Mathematically , this is reflected by how when h = 1 and r1 = r2 , Eqs 1 and 2 are identical . Stem cell carrying capacities , as mentioned above , are limited by available pro-growth cytokines . Literature estimates have centered on a total HSC population of 10 , 000 cells [32 , 44] . HSCs have been recognized to be a heterogeneous group of cells with differing levels of activity . This corresponds to , among other differences , their localization in separate niches in the bone and the growth rate differences that are attendant . But even in spite of the variation in HSC repopulation kinetics after transplantation , a general carrying capacity of 10 , 000 cells has been observed in experimentation and also shown to be robust in reproducing patient dynamics in modeling [31 , 32] ) . Stem cell death and clearance rates were harder to determine due to the longevity and self-renewing abilities of HSCs [33] . Our estimates are derived from modeling studies which have tried to reproduce experimental and animal data . In these cases , stem cell apoptosis rates were significantly lower than the growth rates ( 1/10 of the value ) . However , models have found this growth rate to be sufficiently low that its variation has a relatively minor effect on outcomes [32] . This supports the experimental model view that HSCs are very long lived , and whose dynamics are not significantly impacted ( at least in a healthy state ) by their apoptosis rates . We chose a very small death rate that is 1/100 of the growth rate in order to emphasize this . However , the impact of increasing death rates was also investigated when exploring the cancer dynamics ( see Results ) . Lastly , we introduced a differentiation term , γ , in order to reflect the demand of asymmetric differentiation on loss from the HSC compartment . In general , stem cells characteristically have the ability to replenish daughter cell populations without leading to significant loss of their own through asymmetric division . However , symmetric ( HSC-loss ) division is still possible due to heightened physiological demand . Previous modeling works have examined how this loss is controlled by the larger state of the hematopoietic system [16] . We chose to mimic this approach and use a differentiation term which , at maximum , could be on the same order of magnitude as the stem cell replication rate ( similarly used in [32] ) . However , in practice , since the model simulations were not in such extreme conditions , the demand was an order of magnitude lower than the replication rate . Other important parameters for our model were the asymmetric allocation of daughter cells to myeloid vs lymphoid cells as well as the delays in maturation . Lineage commitment is an important step in stem cell differentiation during hematopoiesis , but cells do not become lymphoid or myeloid in equal proportions . We used a generally agreed upon proportion of 3:2 myeloid:lymphoid cells . Previous studies [34] found similar ratios through in vivo murine studies . In humans , the ratio is similar , although there is the complicating factor in that there is variation throughout life . The murine approximation of 3:2 is what we chose as a relatively balanced approximation given that human ratios change from lymphoid dominant to myeloid dominant by approximately the age of 21 [34] . This has also been supported in studies which measured common myeloid and common lymphoid progenitor cells and imbalances caused by secreted osteopontin ( Supplementary figure 1 in [35] ) . Maturation delays for daughter hematopoietic cells were highly variable since myeloid and lymphoid cells are heterogeneous populations . Neutrophils , for example , have a delay lag time of approximately 5 days as measured in [42] . However , more detailed RNA studies have shown differentiation to occur after as long as 14 days [41] . We chose this estimate of 14 days as a baseline to cover the breadth of phenotypic change that cells undergo during differentiation . We believe this is biologically reasonable and our investigation of delay variation showed how this maturation time could interact with disease ( see Results ) . Daughter cell amplification factors were based on the modeling done in [36] . We used their method of describing amplification rates of daughter cells based on a multiplicative factor of stem cell division . They have modeled this amplification factor as on the order of magnitude of a 10 , 000-100 , 000 fold change from stem cells to daughter cells . We have followed this and use a parameter of 10 , 000 times the HSC differentiation rate ( γ = 0 . 1 ) . Daughter cell carrying capacities were also based on the modeling of [36] . While they had variable final capacities as a function of body mass and feedback parameters , we chose a more simplified method of fixing the total capacity at 100 , 000 cells . This was because we did not seek to model the entire hematopoietic system but instead a subset of two connected niches . In doing so , we used 100 , 000 as an estimate of the ‘local’ carrying capacity for these connected niches . Our model was intended to present a local , view of repopulation dynamics . Within these 100 , 000 myeloid and lymphoid cells , we further divided the ratio as 9:1 in favor of myeloid cells . While the exact composition can vary [34] , we used this to represent how lymphoid cells typically exit the marrow more than myeloid cells . Finally , hematopoietic daughter cell death rates were another highly variable parameter for which we used an average estimate . Lymphocyte death rates were used from [39] , which assumed death rates are dependent on IL-2 cytokine concentration but generally in the range of 0 . 1 day−1 . In terms of specific cell types , effector T cell populations have been indicated to have clearance rates of 0 . 05 day−1 , which is also similar to the value we have chosen [40] . Myeloid death rates are even more variable due to the heterogeneity of mature myeloid cells . However , their turnover is characteristically higher , especially when they are recruited to fight infection [38] . Neutrophils have also been found to have a half life of hours [37] . Our value of 0 . 25 day−1 reflects their faster turnover and cell death . We analyzed the impact of variation in both competition strength between the clones as well as their relative growth rates . From Eqs 1 and 2 , the growth rates of the healthy and mutant clones are r1 and r2 , respectively . In order to simplify the parameter variation , for our analysis we set r1 as a constant ( Table 1 ) and then set r2 as a multiple , ρ of r1: r 2 = ρ r 1 , r 1 = 0 . 1 cells - 1 day - 1 ( 7 ) This allowed us to treat ρ as the relative growth rate of mutant clones as compared to healthy HSCs . All other parameters were held constant at the values in Table 1 . In addition , initial population numbers of the cell types that were modeled were set at 100 cells each to represent a small initial population of cells from which the hematopoietic system would be reconstituted . For the delay differential equations , the historical values for times t < 0 were also set at 100 cells for each cell type . While this could have been changed , we believed that a constant history buffer of this size for each population would accurately represent hematopoietic populations regrowing in nearly empty niches . In Eqs 1 and 2 , stem cells differentiated into both myeloid and lymphoid daughter cells . The rate of loss by differentiation from the HSC compartment was modeled as: D H i where D = γ ( ϕ σ M + ( 1 - ϕ ) σ L ) ( 8 ) This value , D , represents the differentiation demand the HSC compartment experiences due to feedback to satisfy myeloid and lymphoid demand . In our simulations of HSC growth as described above , we used D as a measure of differentiation demand and measured it at homeostasis at the end of the simulation . Myeloablative treatment of patient bone marrow is a traditional precursor to hematopoietic stem cell transplant [50] . While other options have been used , high dose chemotherapy regimens have been widely employed in acute myeloid leukemia ( AML ) , acute lymphocytic leukemia ( ALL ) , chronic myelogenous leukemia ( CML ) , and other myeloproliferative disorders due to their ability to offset the toxicity impacts of total body irradiation ( TBI ) . While TBI has been shown to have a dose-dependent increase in the ability to prevent relapse , studies have shown that this is often offset by transplant-related deaths due to secondary radiation-related toxicities [51] . Chemotherapy-only regimens have been devised to address this toxicity by using a combination of high dose alkylating agents , busulfan and cyclophosphamide , to still achieve maximal leukemic cell death and clearance of host hematopoietic cells . Myeloablative chemotherapy before hematopoiesis has profound differences when compared to total body irradiation . HSC visualization studies have shown that irradiation destroys sinusoidal cells , one of the anchors of the vascular niche in the bone marrow [43 , 52] . In contrast , busulfan and cyclophosphamide have directed effects to the hematopoietic cells , including nonproliferating ones , and leukemic cells [50 , 53] . To simulate post-transplantation hematopoietic growth dynamics after myeoablative chemotherapy , each empty niche was seeded with 100 stem cells , lymphocytes , and myeloid cells . This mimics the immediate state of homing of transplanted cell populations to the different niches . Growth was then simulated using the parameter set in Table 1 as default , except for specific parameters that were varied for investigation . The total growth time of the simulation was 280 days with a temporal resolution of 1/100 of a day . In determining the length of time to run the simulation , 280 days was found to be long enough to establish steady state with little change after this time . In simulations where aged bone marrow was studied , the degradation-augmented death rates ( Eq 6 ) were used instead of the baseline death rates . Lastly , we also simulated situations in which growth factor support was employed to restore proper microenvironmental support for hematopoietic cells . This rejuvenation was simulated as a removal of the degradation-augment on the hematopoietic cell death rates on day 15 of the simulation ( Δ = 0 when t > 15 days ) . While the day of simulated growth factor impact was arbitrary , using a Heaviside function ( i . e . immediate effect ) to simulate the sudden removal of disease , represents scenarios where treatment can lead to dramatic and rapid improvements in patient hematopoietic health . Furthermore , another advantage of our modeling of microenvironmental impact is that a reduction in hematopoietic cell death due to treatment is not solely tied to one type of growth factor or treatment mechanism in supporting the transplanted cells . While we focus on the use of growth factors , supportive treatments for transplanted cells also help engraftment and stem cell homing . This overall improves stem cell retention in the marrow and reflects a low Δ versus damaged marrow . A numerical integration scheme ( Runge-Kutta 4/5 method ) was adapted for delay differential equations ( DDEs ) in order to solve , numerically , the system of equations for our model . Source code for the simulation is available at osf . io/f7gqb . All simulations were coded and visualized using Python ( version 2 . 7 , Python Software Foundation , www . python . org/ ) and the Scipy , Numpy , and Matplotlib computing libraries . Mouse LSK measurements were taken from C56BL/6J mice purchased from The Jackson Laboratory ( strain 000664 , www . jax . org ) . Bone marrow samples were from five young mice ( aged 3 months ) and six old mice ( aged 11 months ) . Bone marrow was harvested using a protocol modified from [54] . Harvested marrow was then prepared for fluorescence activated cell sorting ( FACS ) measurement . Harvested bone marrow were lysed with ACK lysis buffer ( ebiosciences ) and then were stained on ice for 30 minutes with a cocktail of antibodies; Fc Block ( Becton Dickinson ) , biotin-conjugated anti-CD3e ( clone 145-2C11 , Biolegend ) , biotin-conjugated anti-CD4 ( clone RM4-5 , eBioscience ) , biotin-conjugated anti-CD8 ( clone 53-6 . 7 ) , biotin-conjugated anti-CD11b ( clone M1/70 , Becton Dickinson ) , biotin-conjugated anti-CD19 ( clone 6 . D5 , Biolegend ) , biotin-conjugated anti-CD127 ( clone B12-1 , Becton Dickinson ) , biotin-conjugated anti-B220 ( clone RA3-6B2 , Biolegend ) , biotin-conjugated anti-Gr1 ( clone RB6-8C5 , Becton Dickinson ) , and biotin-conjugated anti-Ter119 ( clone TER-119 , Biolegend ) . Afterwards , harvested whole bone marrow samples were stained for one hour on ice with: streptavidin-APC-Cy7 ( Becton Dickinson ) , APC-conjugated anti-CD117 ( clone 2B8 , Becton Dickinson ) , PE-Cy7-conjugated anti-Sca-1 ( clone D7 , Becton Dickinson ) , Pacific Blue-conjugated anti-CD48 ( clone HM48-1 , Biolegend ) , PE-conjugated anti-CD135 ( clone A2F10 ) , BrilliantViolet510-conjugated anti-CD150 ( clone TC15-12F12 . 2 , Biolegend ) , FITC-conjugated anti-CD34 ( RAM34 , eBioscience ) . Flow cytometry was run on a FACS LSRII and analyzed with FlowJo software ( Treestar Inc . ) . Total LSK measurements were extrapolated based on the total cell counts and an established surface marker profile [54] .
The intensity of competition and difference in growth rates between mutant and healthy HSC clones are two significant , but poorly characterized , parameters of CHIP . Measuring competition and growth differences is challenging due to the nonlinear accumulation of mutations with age and the variable impacts of the acquired mutations [1 , 3] . For example , while mouse models with mutations in both copies of p53 exhibited greater HSC growth than wild-type mice , there were no differences between wild-type and p53 mutation heterozygotes [55] . Ecologically , competition and growth rates are important for predicting whether mutant clones dominate healthy clones . Furthermore , the ultimate outcome is not obvious since there may be interactions between competition intensity and growth rate differences . In order to clarify how these two ecological variables may impact hematopoietic trajectories after transplantation , our model first examined the impact of competition between healthy and mutant HSCs . The tested outcomes were compared to the dynamics of a healthy patient without CHIP . Specifically , a healthy patient would have no divergence between healthy and mutant cells ( i . e . there are no mutant cells ) . In this case , the competition coefficients should be equal ( h1 = h2 = 1 ) and there should be no growth rate disparity ( ρ = 1 ) . Under these conditions , the two clonal HSC populations modeled in Eqs 1 and 2 become equal . Our analysis focused on the case where symmetric competition intensity is occurring ( h1 = h2 ) between mutant and healthy clones . Ecologically , this represents a situation of significant overlap between the niches of healthy and mutant HSCs . In this case , the mutant and the healthy HSCs exert similar competitive pressures on each others’ populations . There is significant evidence to suggest that such a dynamic is a good approximation for CHIP and pre-malignant , pre-clinically-cancerous hematopoiesis . Spatially , HSCs are extremely dependent upon occupying the correct niche in order to sustain their populations [43] . Even when hematopoietic mutants have become clinically cancerous , these new leukemic stem cells are still dependent upon the same niches as healthy stem cells [56] . A situation where competition intensity would not be symmetric might be when the niche of the mutant clone is a superset of the niche of the healthy clone . This occurs in metastasis when leukemic cells have been liberated from their constraint to bone marrow stem cell niches and can move to other organs . Here , the competitive impact of healthy cells on mutant cells would be rather low . But the competitive effect of mutant cells on healthy cells would still be high since leukemic cells are still competing for bone marrow niches ( h2 > h1 ) . However we restricted our analysis to pre-cancerous mutant HSCs , as is the case in CHIP , and took the more limited approximation that the relative competitive impact of each clone on the other is approximately equal . Under this regime , hematopoietic repopulation was simulated after the autologous transplantation of a population of cells into the empty bone marrow . Competition intensities and relative growth rates were varied to understand their impact on both the ratio of mutant and healthy stem cells ( Fig 2 ) as well as the final overall stem cell numbers ( Fig 3 ) . The relative ratio was examined as an indicator of clonal dominance in the hematopoietic system after repopulation . However , the total number of stem cells was also critical to understanding the downstream production and ability for the bone marrow to fulfill physiological demand . A primary observation was that final hematopoietic compositions favored the faster growing clone , but increasing competition served to magnify this imbalance . In situations where inter-clonal competition was less intense than healthy patient levels ( h1 = h2 < 1 ) , competition had a minimal impact in determining the final clonal ratio . While there was still a skew towards the more rapidly growing clone , there was no competitive exclusion of the slower growing stem cells . Overall , when competition intensity was below normal levels there was an increase in total stem cells . While it may first seem paradoxical that these total population sizes are larger than the carrying capacity ( KH ) , this is because the carrying capacity is , ecologically , determined by competition . Under Lotka-Volterra competition dynamics , if h1 = h2 = 1 , then the two stem cell clones are exerting the same competition pressure upon each other . This means that , if all other parameters are equal , H1 and H2 are essentially halves of the same population of stem cells . Their final populations will be K H 2 for each clone . However , if competition intensity decreases so that h1 = h2 < 1 , then each clone can reach a final population value greater than before and the sum of H1 and H2 will be greater than KH . Biologically , total population sizes greater than the total carrying capacity simply reflect the fact that the mutant and healthy HSCs are no longer competing for the same set of resources and so their total numbers can grow to be greater than KH even though each individual clone size remains smaller than KH . Competitive exclusion became much more apparent when competition intensities were greater than normal levels ( h1 = h2 > 1 ) . For a given discrepancy in growth rate , as competition intensified , so too did the imbalance between healthy and mutant stem cells . In situations of extreme clonal competition , even small differences in growth rate led to competitive exclusion of the slower growing lineage . Importantly , though , even though there was dominance of one clone over the other , the total number of stem cells remained unchanged ( Fig 3A ) . The only exception was when ρ = 1 . Under this condition , with indicates no growth rate difference , greater competition led to final HSC populations which were lower than those of a healthy patient . These upstream stem cell impacts of competition and growth rate were propagated to downstream daughter cells and physiological demand on the hematopoietic system ( Fig 4 ) . Previous experimental and theoretical studies have shown that stem cell dynamics have a significant determining effect on differentiated hematopoietic daughter cell dynamics [19 , 36] . These top down effects were similarly present in our model in the context of clonal competition . Similar to stem cells , in low-competition regimes the lymphoid and myeloid daughter cells both exhibited the increased final populations relative to healthy baselines . In addition , weaker competition also allowed the coexistence of myeloid and lymphoid cells from both the healthy and mutant clones . Finally , this increased productivity was also reflected in the physiological demand at homeostasis . Greater daughter cell populations meant reduced differentiation demand on HSCs ( Fig 4C ) . Lastly , as with the stem cells , greater competition led to competitive exclusion of daughter cells from the slower growing lineage . This is unsurprising as exclusion of stem cells would be predicted to lead to a decrease in their daughter cells . Moreover , it emphasizes the systemic impact that competition has on exacerbating stem cell growth rate differences . Greater competition at the stem cell level will lead to a more extreme exclusion of both the slower growing lineage of stem and daughter cells from the final hematopoietic populations . In addition to understanding how repopulation after transplantation occurs in healthy bone marrow niches , we also investigated the impact of a degraded or aging-damaged bone marrow ( Δ in Eq 6 ) . A significant element of the difficulty in treating hematopoietic malignancies is that many of them occur in older patients who have compromised bone marrow conditions compared to young patients [9] . A number of aging-related declines in bone marrow quality have been studied , which lead directly to impeded HSC growth and function [13 , 29] . HSCs give rise to the committed bone marrow lineages and mature blood compartment , whereas the bone marrow niche is a vast compartment of mesenchymal or endothelial cells that produce growth factors necessary to support hematopoiesis [57] . Genotoxic stress induced by pre-transplantation regimens deplete HSCs but also damage bone marrow niche cells . Reduced-intensity stem cell transplantation or non-myeloablative transplantation is a modification of the chemotherapy or radiation dose that spare the niche compartment . The outcomes of CHIP with varying levels of damage to the bone marrow niche has not been investigated . To understand CHIP’s interactions with clonal competition in compromised niches , we measured total stem cell numbers during recovery after transplantation in variable bone marrow niche conditions ( Fig 5C ) . Our analysis revealed that there are two major regimes of dynamics . If bone marrow damage is too high , then that leads to a situation where , irrespective of competition intensity , the stem cell population cannot be sustained . For our analysis , the value of Δ ≈ 0 . 10 day−1 ( Fig 5C , white dashed line ) was the threshold above which there was stem cell extinction . This dividing boundary represents an approximate extinction threshold since simulated recoveries in niches with more than this level of damage have less than 10 HSCs at homeostasis . For values of Δ < 0 . 10 day−1 , greater competition intensity led to lower final stem cell populations . Greater competition between healthy and mutant stem cell clones in increasingly degraded bone marrow niches led to lower final stem cell counts and reflected an hematopoietic system less able to meet physiological demands . In light of the impact that an inadequate bone marrow niche and clonal competition had on HSCs populations , we examined to what extent support for stem cells via growth factors could recover healthy hematopoietic productivity ( Fig 6 ) . We simulated hematopoietic repopulation after transplantation into variably-damaged bone marrow niches . However , to simulate the impact of growth factors , we then improved the bone marrow condition at 15 days after the start of repopulation ( Δ = 0 ) . Even under the most favorable conditions , the application of growth factors to the bone marrow niche did not recover healthy hematopoietic productivity . Our simulations used healthy populations where h1 = h2 = 1 given that our previous analysis of competition intensity showed that optimal outcomes in degraded bone marrow environments occur when the competition intensity is lower ( Fig 5C ) . However , even under this regime of minimal increased competition between clones , we still found that stem cell population numbers at homeostasis were much lower than for healthy niches . The amount of improvement from treatment increased with poorer initial bone marrow condition , but HSC extinction was still possible . This investigation also implicitly took the effect of a maturation delay of 14 days into account . By having marrow improvement occur at 15 days , it meant that the bone marrow had remained degraded during the early post-transplantation period when there were few myeloid and lymphoid daughter cells and mostly HSCs . Stem cells had borne the brunt of the bone marrow-mediated cell death rate increases , while daughter cells had been unaffected ( because they had not yet matured since the start of the simulation ) . By showing relatively unchanged productivity numbers between growth factor-supported and unsupported transplantation , our results indicated that it was primarily the impact of niche condition on the HSCs which led to an uncorrectable decrease in bone marrow productivity . Based on our model , this inability to recover a healthy bone marrow system is due to the finite limits of demand on the stem cell compartment . On initial repopulation of the bone marrow , HSCs experience expansion growth as they fill niches that have been emptied before transplant . As they grow , physiological need triggers differentiation and asymmetric division from HSCs to eventually lead to mature daughter myeloid and lymphoid cells . However , a degraded bone marrow niche yields problems during this repopulation by leading to greater HSC death . This means that the overall productivity during repopulation , before a steady state is established , is lowered . Growth factors given to support HSC populations only moderately improved bone marrow outcome because stem cells have limited productivity in terms of the maximum growth rates , r1 , r2 . There is a limit to the maximum flux out of the stem cell compartment , because while HSCs may have very large reproductive potentials over a patient’s lifetime , their rates of reproduction can only increase to a finite limit due to demand . Our model accounts for the fact that stem cells have great longevity ( low δH ) but their differentiation rate is finitely limited . This reflects the fact that HSCs still have to go through the cell cycle when they need to divide—imposing biological limits on their maximum rate of differentiation . Under our model , this maximum rate of differentiation is not enough to repopulate the bone marrow when HSCs have been depleted by competition and disease and so full bone marrow rejuvenation is not possible . Our simulated experiments highlighted the interaction between competition intensity and bone marrow condition in their ability to compromise hematopoietic productivity . However , one of the difficulties in determining the heterogeneity that may be encapsulated by CHIP is due to competitive niche interactions where multiple marrow condition/competition intensity combinations may yield the same overall stem cell numbers . Clinically , this becomes potentially problematic since gross hematopoietic numbers are often used as a marker of general health during the course of therapy [12] . In an effort to more realistically estimate what range of bone marrow declines and clonal competition intensities could lead to a given outcome , we estimated hematopoietic states from older and younger mouse bone marrow ( Fig 5 ) . Lin−Sca-1+c-Kit+ cells have been characterized as containing lineage uncommitted HSCs and progenitors [58] and serve as a good approximation of our modeled stem cell compartment . Marrow was harvested from young ( 3 month old ) mice and old ( 11 month old ) mice which displayed a significant decrease in total LSK numbers . More gated LSK-SLAM cells were also measured , but their smaller numbers and higher variability , in addition to our cohort sizes , limited our ability to detect a significant difference ( see supplementary S1 Fig ) . Using our model and the dynamic interactions between competition and age-related bone marrow niche decline we could then isolate a specific contour line as representing the possible bone marrow states of the older mouse cohort ( Fig 5C , black line ) . This range of combinations of bone marrow condition and competition intensity yields a few important insights . Firstly , the decline in total stem cell number could be explained by a broad range of competition intensities but a relatively narrow range of declines in bone marrow condition . This suggests that the 80% decline in stem cells observed in our mouse cohort is significantly influenced by the loss of niche support in the bone marrow . In terms of competition , the intensity among clones could be normal ( h1 = h2 = 1 ) or could be significantly elevated ( h > 2 ) . Furthermore , our resolution in estimating the decline with age was challenged by the necessity of using LSK cells instead of the more gated LSK-SLAM populations due to statistical limitations . While we attempted to correct this by looking at the proportional decline , it is possible that there is higher variability in the LSK-SLAM population ( see S1 Fig ) . True HSC decline could be greater than 80% which would suggest that our extrapolated competition intensity of h = 8 . 85 is an underestimation of the true degree of competition between mutant and healthy HSCs . The actual degree of competition could be much higher . This uncertainty adds urgency to efforts to have a higher-resolution study of aging niche decline and stem cell loss . In addition , this mapping offers a way forward to estimate CHIP in terms of clonal competition intensity in patients before transplantation . Specifically , since the ability of bone marrow niches to support stem cells declines with age , this decline in bone marrow niche integrity can act as a proxy for patient age . If age-dependent niche decline could be more finely quantified , then the age of a patient and the stem cell numbers of a patient could be used to infer the inter-clonal competition intensity of HSCs ( see Conclusion ) .
Clonal hematopoiesis of indeterminate potential ( CHIP ) poses many challenges for predicting patient health outcomes due to the uncertain dynamics between healthy and mutant hematopoietic clones [1 , 3 , 59] . However one area in which the implications of CHIP have been poorly explored is how it may impact the outcomes of autologous bone marrow transplant . For a number of hematopoietic cancers , autologous stem cell transplantation remains preferred over allogenic transplantation to avoid the life-threatening potential of graft-versus-host disease ( GVHD ) . Moreover , reduced intensity conditioning regimes have allowed transplantation in older patients due to lower stresses from chemotoxicity [50] . Transplantation in patients over 60 years of age in the US now represents nearly 40% of all autologous BMTs [10] . In these older patients , CHIP provides a complicating factor for predicting outcomes due to the possibility that sampling effects could lead to transplanted mixtures of mutant and healthy hematopoietic clones that may contribute to post-transplant leukemia . In order to investigate the dynamics that could lead to divergent outcomes from CHIP , we employed a mathematical model of clonal competition between healthy and mutant HSCs and studied the outcomes of simulated autologous stem cell transplant . Our model analyses addressed the open question of how variation in cell competition and growth parameters of the transplanted stem cell population could alter the final composition of marrow due to competition between healthy and mutant HSC clones . We focused on the interaction between variation in competition intensity and the variation in growth rate discrepancy between healthy and mutant clones . Our results suggest that competition intensity between clones exacerbates the impact of growth rate differences . For divergent growth rates between healthy and mutant HSCs , competitive exclusion is not guaranteed . Instead , in order for competitive exclusion to occur , there must be greater competition intensity between healthy and mutant HSCs than would be expected in a healthy patient . This increase in competition helps to drive the slower-growing clone to extinction . In cases where mutant stem cells have a faster growth rate than healthy cells , this could lead to dominance by the mutant clone . Conversely , if the mutant is less fit than the healthy cells , it could be driven to extinction . Studies using empirical observations of leukemic cells support our model and current conclusions . In addition to HSCs , transplantation outcomes are impacted by the stem cell niche . The degree of vascularity , oxygen availability , and stroma-derived cytokine concentration are non-uniform in the bone marrow [60] . HSCs are primarily located in the inner surface of the bone ( endosteum ) in specific bone marrow niches which can uniquely support HSC populations . In competitive transplantation experiments between leukemic and healthy cells , these niches have been shown to be completely dominated by either healthy or leukemic cells [56] . This represents a local , microenvironmental version of our model’s outcome and would be supported by the fact that leukemic cells are considered to have faster growth rates than healthy cells [56] . In addition , there have been notable cases in allogenic BMT which have demonstrated the ability for transplanted pre-leukemic clones to later mutate into fully leukemic populations . For example , the use of trisomy 11 as a genetic marker present in the transplantation sample was used to show the origins of leukemia 14 years after the original transplant [61] . In another situation that also involved allogenic BMT , investigators specifically used CHIP as a motivating hypothesis to identify two cases of donor cell leukemia from a population of donors older than 61 years of age [62] . While these cases are specific to allogenic transplantation , the mechanism that we have provided in our modeling framework offers an ecological explanation and understanding in both allogenic and autologous transplant settings about how CHIP and donor cell mutants may lead to leukemic clones in the transplant recipient . Moreover , our data suggest that younger donors lacking CHIP may improve the outcomes of allogenic transplantation . A possible solution to preventing CHIP in allogenic transplants is through cord blood transplantation , which is already being implemented in the clinic . Since cord blood is collected at birth , it represents the most diverse populations of newborn stem cells without any age-related induction in clonal hematopoiesis . Thus , cord blood transplants pose a minimal risk of clonal heterogenenity with the possibility of a final , dominant mutant clone . Retrospective studies looking at cord blood transplants have shown that they can perform well enough to minimize the difference in survival in patients with and without minimal residual disease at the time of transplantation [63] . This result is notable because it is a direct test of the clonal competitiveness of transplanted cord blood populations against a known leukemic population ( minimal residual disease ) . But even aside from cord blood , our results provide evidence for the importance in choosing younger donors who are less likely to have mutant hematopoietic clones to be transplanted both in allogenic transplantation and autologous BMT . In the larger context of BMT , our results emphasize the risk that CHIP poses for transplant recipients . Autologous BMT , when conducted in older CHIP patients , raises the possibility of transplanting a clonal population which could lead to dominance of a mutant hematopoietic clone . Dominance of a mutant clone could then easily set up the marrow for relapse through further mutation accumulation and the emergence of a novel , cancerous population . BMT and repopulation dynamics are complicated by the fact that aging leads to decline in the ability for bone marrow niches to support stem cells . Our analyses revealed that , similar to growth rate differences , increased competition between stem cell clones leads to a worsening of the already poorer outcomes due to this bone marrow niche decline . Greater interclonal competition between healthy and mutant hematopoietic cells means that the already depleting bone marrow niche is able to sustain even fewer overall cells . This leads to detrimental impacts on the fully differentiated myeloid and lymphoid cells and to a final hematopoietic system which is far from a healthy state . A question that immediately follows from this conclusion is whether or not the use of supportive growth factors , as commonly employed in bone marrow transplants , offer benefits [64] . Clinically , there are a number of growth factor support regimens which have attempted to improve patient bone marrow condition after transplantation . By simulating the impact of growth factor support on repopulation under differing bone marrow damage conditions , we examined whether or not these treatments could improve repopulation dynamics . While gains could be achieved , the combination of maturation delay , as well as competition between stem cell clones , led to the inabilty to fully recover a healthy hematopoietic state . Specifically , we found that while aggressive and totally restorative growth factor support could help increase stem cell numbers and total hematopoietic production , the early destabilization due to a damaged bone marrow had a lasting effect . Total production is dependent on rapid stem cell growth to large populations . This occurs as delays in hematopoietic maturation led to a lag time between stem cell population increases and daughter cell population increases . A rapid increase in stem cell numbers means that daughter cell production will approach physiologically-sufficient levels quickly . This can be considered a window in which HSCs are not experiencing negative feedback in terms of renewal and differentiation , in spite of the fact that they are actively proliferating . However , there is a trade-off in HSC growth during repopulation in that stem cells lost due to symmetric differentiation directly take away from helping to reconstitute the HSC population . Since there is a maturation delay , even though HSCs may have reached a level that would be sufficient to fulfill physiological demand , they will still experience a large symmetric differentiation demand because daughter cell populations have not ‘caught up’ . In a damaged bone marrow , this lag will take even longer because the augmented cell death and loss will functionally add more time to a response between HSC growth and daughter cell growth . This damage—even if transient—to repopulation dynamics may mean that the total cumulative production of hematopoietic cells is not sufficient to satisfy physiological demand . This situation is made even worse due to higher interclonal competition . Once negative feedback starts to take effect as myeloid and lymphoid daughter cells are produced , it leads to a decrease in stem cell activity . However , competitive inhibition between the clones reduces the full expansion that can take place in this window of maturation delay where feedback inhibition has not yet started to increase . In the clinic , there has been evidence to support the important role that improving bone marrow condition has in allowing hematopoietic recovery . Recently , it has been reported that after the failure of an initial stem cell transplantation , a secondary allogenic transplant was successful when mesenchymal stromal cells ( MSCs ) were contemporaneously intraosseously administered [57] . MSCs are responsible for creating and maintaining the stem cell niches in the bone marrow which are necessary for proper HSC function . Increasing the number of intraosseous MSCs at the time of transplantation was hypothesized to have given the microenvironmental support necessary for proper hematopoietic growth . This is a similar conclusion to our modeling results which showed that any kind of damage to the bone marrow microenvironment should be repaired as early as possible if proper recovery is to be achieved . It could be argued that while hematopoietic clonal competition dynamics are theoretically interesting , they are clinically less useful . More generally , one of the chief criticisms of the utility of CHIP in the clinic is that assays for clonal diversity or the ecological state of a patient’s bone marrow are not currently widely employed . In fact , clinical assessments of a patient’s hematopoietic state are generally limited to assessing gross hematopoietic cell population sizes [12] . It has been argued that in light of this lack of ecological ( population-level and microenvironmental ) assaying , and since clonal dynamics are not explicitly tested , better understanding of CHIP and patient bone marrow microenvironment can provide little utility to clinical treatment . However , our model offers insights into the importance of measuring both the ecological condition of patient marrow as well as the clonal dynamics in transplanted stem cell populations . To highlight this importance , we compared LSK cell numbers in a cohort of old and young mice . We measured a significant ( 80% ) reduction in LSK cells in aged mice . Based on our model , this empirical reduction in stem cell numbers was used to estimate a range of bone marrow decline/competition intensity combinations which could yield these results . Importantly , this suggests that the same dramatic loss in stem cells can be attributable to either very little CHIP but significant bone marrow decline , or vice versa . Furthermore , in terms of predictive utility , our results highlight the importance of understanding the bone marrow microenvironmental condition into which stem cells will be transplanted . Even small amounts of clonal competition could lead to the observed dramatic declines in stem cells if the bone marrow condition is sufficiently poor . Successful clinical management requires understanding CHIP in the context of the patient microenvironment . Our model is an initial attempt to gain a more robust understanding of how ecological competition parameters could influence final bone marrow states . However , as its focus was on the broad ecological dynamics , there are notable limitations which also provide avenues for future extension and research . One simplifying feature of the model design was the fact that the model divided HSC clones into two broad ‘healthy’ and ‘mutant’ categories . While it is clear that there are multiple types of clones present in CHIP , the exact dynamics during their origin are poorly understood . This mirrors the origins of clonal diversity in different cancers which suggest that stochasticity may have a large role in determining the dominant populations [65] . Nonetheless , while our model’s division into just two major clones is a more simple approximation , there are still insights to be gained , especially given the sensitivity analyses which can suggest how broad changes in the average mutant phenotype could impact hematopoietic outcomes . We recognize that there are alternative ways that this diversity could be modeled , including in previously published stochastic schemes [15] . Other works have sought to explore the specific impacts of mutations in leading to clonal dominance [66] . By implementing a stochastic Moran process , there is evidence that mutations in dominant clones may have arisen through stochastic clonal expansion instead of through an explicit fitness benefit . In addition , our model does not attempt to model the stochastic processes of engraftment of transplanted cells . Simulations with experimental data have shown that transplantation can be a severe population bottleneck which influences the dynamics of which clones actually engraft at the start of repopulation [67] . Our model could be extended to combine its predictions of mean-field dynamics in addition to the stochastic drift processes that are likely present in pre-leukemic stem cells . This extension could potentially help explain why CHIP may not always lead to malignancy . Lastly , our estimate of competition parameters could be narrowed even further through research to quantify , more rigorously , the degradative impact of aging on the bone marrow . One of our major conclusions is that predicting the outcome of CHIP requires also understanding host marrow condition since multiple combinations of marrow decline and competition intensity could lead to similarly dramatic losses of stem cells . This does , however , pose a limitation in our parameter estimation , as HSC numbers could not be mapped 1:1 with the level of interclonal competition . A better understanding of the degradation due to aging would help narrow down the range of competition values by narrowing down the range of reasonably expected bone marrow damage in older patients . Current biological understanding supports a model of the bone marrow which degrades over a patient’s lifetime due to inflammation , stromal changes , and oxidative damage [29] . In fact , stem cell niche degradation due to aging is a process that has been observed to be present in tissues beyond the hematopoietic system [68] . The exact quantitative relationship between age and the increase in stem and daughter cell loss is poorly characterized . Small cohort studies of patients between 16-28 years and 63-92 years have shown increases in nitrogen oxide production and lowered Ki67 and p53 expression [69] . There are also notable declines in function of mesenchymal stem cells which are a crucial progenitor of stromal cells necesary for HSC function [70] . Extrapolating the stem cell and daughter cell death rates are more difficult , however , and are a logical avenue to extend investigation in order to help improve the utility of our modeling framework . In conclusion , our research suggests that CHIP in the context of bone marrow transplants and repopulation dynamics should be investigated through an ecological lens . Repopulation should not be considered as a clonally homogeneous process , but instead a competitive one . Depending on the competition level , growth rate difference , and bone marrow condition , transplantation can lead to very different hematopoietic outcomes in terms of clonal composition . Clonal dominance of mutant clones may lay the seed for reemergence of disease or other hematopoietic and health disorders due to CHIP presence in donors . We advocate a further adoption of this ecological paradigm as a way of both investigating CHIP during transplantation and treating disease more effectively overall . | We investigated the impact of clonal hematopoiesis of indeterminate potential on stem cell transplantation outcomes . Interclonal competition intensity was identified as an important determinant of ultimate hematopoietic trajectory . We also investigated the impact of age-related marrow changes and show that , from a mouse model , these ecological parameters can be estimated . | [
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"te... | 2019 | Clonal hematopoiesis of indeterminate potential and its impact on patient trajectories after stem cell transplantation |
Helminth parasites are known to be efficient modulators of their host’s immune system . To guarantee their own survival , they induce alongside the classical Th2 a strong regulatory response with high levels of anti-inflammatory cytokines and elevated plasma levels of IgG4 . This particular antibody was shown in different models to exhibit immunosuppressive properties . How IgG4 affects the etiopathology of lymphatic filariasis ( LF ) is however not well characterized . Here we investigate the impact of plasma and affinity-purified IgG/IgG4 fractions from endemic normals ( EN ) and LF infected pathology patients ( CP ) , asymptomatic microfilaraemic ( Mf+ ) and amicrofilaraemic ( Mf- ) individuals on IgE/IL3 activated granulocytes . The activation and degranulation states were investigated by monitoring the expression of CD63/HLADR and the release of granule contents ( neutrophil elastase ( NE ) , eosinophil cationic protein ( ECP ) and histamine ) respectively by flow cytometry and ELISA . We could show that the activation of granulocytes was inhibited in the presence of plasma from EN and Mf+ individuals whereas those of Mf- and CP presented no effect . This inhibitory capacity was impaired upon depletion of IgG in Mf+ individuals but persisted in IgG-depleted plasma from EN , where it strongly correlated with the expression of IgA . In addition , IgA-depleted fractions failed to suppress granulocyte activation . Strikingly , affinity-purified IgG4 antibodies from EN , Mf+ and Mf- individuals bound granulocytes and inhibited activation and the release of ECP , NE and histamine . In contrast , IgG4 from CP could not bind granulocytes and presented no suppressive capacity . Reduction of both the affinity to , and the suppressive properties of anti-inflammatory IgG4 on granulocytes was reached only when FcγRI and II were blocked simultaneously . These data indicate that IgG4 antibodies from Mf+ , Mf- and EN , in contrast to those of CP , natively exhibit FcγRI/II-dependent suppressive properties on granulocytes . Our findings suggest that quantitative and qualitative alterations in IgG4 molecules are associated with the different clinical phenotypes in LF endemic regions .
Lymphatic filariasis ( LF ) also known as elephantiasis is a potentially disabling and disfiguring disease caused in human by vector-borne nematodes Wuchereria bancrofti , Brugia malayi and Brugia timori [1] . The disease has significant social and economic consequences for affected individuals as well as for their families and communities [2] . The current strategy to control the infection is based on mass administration ( MDA ) of diethylcarbamazine or ivermectin combined to albendazole [2] . After 13 years of the MDA programme , recent estimations in 2015 indicate that 38 . 47 million LF cases remain [3] . In endemic regions , exposure to the infection leads to different clinical phenotypes . The first group includes putatively immune individuals or endemic normals ( EN ) who remain infection and disease-free despite continuous exposition to mosquito-transmitted infective larvae ( L3 ) [4] . The second group is defined by a hyper-reactive phenotype and is characterized by chronic lymphatic pathologies ( CP ) such as lymphedema or elephantiasis . The patients elicit a strong T helper ( Th ) 1 and Th17 immune response that eliminate the microfilarial stage [5] while inducing the production of angiogenic factors like VEGF known to be associated with the development of filarial lymphedema [6] . This severe clinical profile is characterized by high antigen-specific immunoglobulin ( Ig ) E and low IgG4 [5] [7 , 8] . The third group includes asymptomatic individuals with latent infection who are free of microfilaria ( Mf- ) but are positive for circulating filarial antigens ( CFA ) [9] . The last clinical phenotype includes the majority of infected individuals and is associated with an hyporesponsive immune profile . In this group , individuals present few visible clinical manifestations despite large numbers of circulating microfilariae ( Mf+ ) [10–12] . Subjects from this group commonly present a modified Th2 immune profile with a strong parasite-specific immunoregulatory arm allowing both the presence of adult worms and microfilariae . This modified Th2 response is associated with increased numbers of regulatory cells ( Tregs ) and alternatively activated macrophages as well as with the secretion of anti-inflammatory cytokines such as IL-10 and TGF-β . This predominantly immunosuppressed environment is associated with elevated levels of antigen specific IgG4 and is directly linked with parasite survival [4 , 10 , 13] . These clinical phenotypes strongly correlate with specific antibody isotypes produced in response to the infection . IgG4 antibodies , for example , correlate with the hyporesponsive state observed in Mf+ individuals whereas IgE , IgG1 and IgG3 correlate with CP [7 , 10 , 14–16] . IgG4 is structurally and functionally different from its co-class members [17–19] . While IgG1 , IgG2 and IgG3 can fix and activate complement , IgG4 has no affinity for the complement and cannot induce antibody-dependent cell mediated cytotoxicity ( ADCC ) . In addition , IgG4 was shown to inhibit antibody dependent complement activation [20] and to compete with IgE for fixation sites on mast cells and eosinophils [21 , 22] . In contrast , IgE induces mast cell and basophil degranulation [23–25] . These anti-inflammatory properties of IgG4 antibodies were associated with its unique ability to undergo Fab-arm exchange ( FAE ) ; resulting in the creation of bispecific , functionally monovalent antibodies [26 , 27] . However , the role played by filaria-induced antibodies in disease manifestations in LF is still not well understood . No data currently exist on how IgG4 antibodies participate in the modulation of the pathophysiology of filarial infections . Granulocytes ( eosinophils , neutrophils , and basophils ) are key effector cells at the frontline against infections with filarial worms [28 , 29] . During helminth infection , granulocytes are rapidly activated and recruited to sites of infection where they are key producers of Th2 cytokines such as IL-4 and IL-13 [28 , 30 , 31] . They also produce “alarmins” which are constitutively available endogenous molecules that are released upon activation and act as chemo-attractants while providing maturation signals to antigen-presenting cells such as dendritic cells ( DCs ) and macrophages [32–35] . Granulocytes can also attack helminth infections through antibody-dependent cell mediated cytotoxicity ( ADCC ) , which implies the killing of antibody-coated parasites via the release of cytotoxic granules ( degranulation ) . The degranulation is triggered by Fc-receptors ( FcRs ) recognizing antibody-bound antigen complexes on the cell surface and several cytokines mainly IL-3 and IL-5 [36 , 37] . Human granulocytes express FcγRI , FcγRIIa/b , FcγRIII , FcɛRI/II and FcαR and can be activated by IgGs , IgE and IgA . The activation of granulocytes can be measured in vitro by monitoring the expression of several activation markers including mainly CD63 , a member of the tetraspan membrane glycoprotein family [38 , 39] . CD63 is an activation marker specific for neutrophils and basophils and , among other markers , for eosinophils [38 , 40 , 41] and it is responsible for the retention and sorting of pro-neutrophil elastase in the primary granules of neutrophils [38 , 40] . Upon degranulation , complete granule contents are released by fusion with the cellular membrane and cytolysis [42] . Granulocytes are characterized by six major granule proteins: major basic protein ( MBP ) , eosinophil peroxidase ( EPO ) , eosinophil cationic protein ( ECP ) , eosinophil-derived neurotoxin ( EDN ) , neutrophil elastase ( NE ) and histamine . MBP , EPO and ECP are potent helminth toxins [43 , 44] . These granule proteins have been shown to be involved in the killing of microfilariae of Brugia spp . and are associated in both allergy and helminth models with the development of immunopathology [45–49] . Since granulocytes play a central role in the elimination of large parasites , we hypothesized that antibodies present in plasma of EN , Mf+ , Mf- and CP might differently impact granulocyte activation and functions . After comparing the suppressive properties of plasma and purified IgG antibodies from EN , Mf+ , Mf- and CP , we found that granulocyte activation was significantly inhibited by plasma from EN and Mf+ individuals whereas plasma of Mf- and CP have no effect . This suppression was dependent on IgG4 in plasma of Mf+ whereas IgG-independent factors seem to be involved in EN . We have also demonstrated that IgG4 actively suppressed granulocyte activation and release of granule contents via FcγRI and FcγRII .
Patients and endemic controls’ samples were collected between 2008 and 2010 in villages of the Ahanta West and Nzema East Districts in the western region of Ghana endemic for LF ( S1 Table ) . No other human filarial species were endemic in the region . The donors were recruited as part of a diagnostic and a clinical trial in LF ( Clinical Trials Registration: ISRCTN15216778 and ISRCTN14757 ) [9 , 50 , 51] . Written informed consent was obtained from all participants . Persons eligible for participation were male adults in good health , 18–60 years of age , with a minimum body weight of more than 40 kg and without any clinical condition requiring chronic medication . Exclusion criteria included abnormal hepatic and renal enzyme levels ( γ-glutamyltransferase > 28 U/L , glutamyl pyruvic transaminase > 30 U/L , creatinine > 1 . 2 mg/100 mL ) assessed by dipstick chemistry , alcohol , drug abuse or antifilarial therapy in the past 10 months . Study participants were examined by a clinician using physical methods and a portable ultrasound machine ( 180 Plus; SonoSite , Bothell , WA ) as described previously [51] . In addition , the presence of infections with other helminths ( Ascaris lumbricoides , Trichuris trichiura , Schistosoma spp . ) and protozoa ( Plasmodium ) was investigated using respectively Kato-Katz and finger prick tests . All samples included in the present study were free of such infections as previously described [9] . Ethical clearance was given by the Committee on Human Research Publication and Ethics at the University of Science and Technology in Kumasi , and the Ethics Committee at the University Hospital Bonn . Microfilarial load was determined by microscopic examination of fingerprick night blood samples as published [51] . Subsequently , 10 mL of venous blood was collected from each eligible volunteer and plasma was taken , aliquoted , and frozen at −80°C until used . Samples included EN , residing in the endemic region but free of infection ( CFA- , Mf- , n = 14 ) , clinically asymptomatic microfilaraemic ( CFA+ , Mf+ , n = 14 ) and amicrofilaraemic ( CFA+ , Mf- , n = 14 ) subjects , positive for circulating filarial antigen and a group of chronic pathological individuals with lymphedema and/or elephantiasis termed “CP” ( n = 14 ) , negative for filarial antigen . Also , plasma from European non-endemic blood donors ( NEC , n = 14 ) was used as controls . Serum samples were obtained in an anonymized and de-identified form . All samples and controls used in the present study were randomly picked from the initial batches using a computer-based simple random algorithm as previously described [52] . Each sample in the initial batch was assigned a unique number and the samples corresponding to computer generated list were picked in each group and used in the study . Brugia malayi worms recovered from the peritoneal cavity of jirds ( Meriones unguiculatus ) were obtained from NAID Filariasis Research Reagent Resource , FR3 ( University of Georgia , Athens , GA ) . To prepare B . malayi antigen extract ( BmAg ) , 100–300 frozen adult worms were thawed and transferred to a Petri dish pre-filled with sterile PBS ( PAA , Pasching , Austria ) . Following several washes in PBS , worms were placed inside a glass mortar ( VWR , Langenfeld , Germany ) . 3–5 ml of medium ( RPMI without supplements ) were added and worms were crushed until the solution was homogenous . The extract was then centrifuged for 10 minutes at 300 x g at 4°C to remove insoluble material . The supernatant was carefully transferred to a new tube . Protein concentration was measured using Bradford Assay . Aliquots were stored at -80°C until use . The extract was titrated to determine the optimal concentration for cell stimulation and the level of endotoxin was defined using the Pierce Limulus amoebocyte lysate ( LAL ) Chromogenic quantification kit ( Thermo Fisher Scientific , Schwerte , Germany ) . The endotoxin level was below the detection limit of 0 . 1 EU/ml . Granulocytes used in this study were purified from buffy coats of healthy European donors provided by the Institute for Experimental Haematology and Transfusion Medicine , University Clinic Bonn , Germany . Ethical clearance was given by the Ethics Committee of the University of Bonn ( “Ethikkommission der Medizinischen Fakultät der Rheinischen Friedrich-Wilhelms-Universität Bonn” ) . Granulocytes were isolated using Ficoll-Hypaque ( Pancoll , PAN Biotech , Aidenbach Germany ) method . The density gradient was performed according to the manufacturer's instructions . Briefly , 15 mL heparinized venous blood samples were diluted with an equal volume of cold phosphate-buffered saline ( PBS ) in a 50 mL conical centrifuge tube , layered over Ficoll and centrifuged at 900 x g for 30 min at 4°C in a swinging bucket centrifuge ( Thermo Scientific , Germany ) with brake off . The opaque layer below the Ficoll/plasma interface containing granulocytes was transferred to another tube . After that , red cells were lysed by 10 min incubation at room temperature in 1x red blood cell lysis solution ( Miltenyi Biotech , Bergisch Gladbach , Germany ) . Granulocytes were then centrifuged at 200 x g for 8 min at 4°C to remove contaminating red blood cells . Cell pellets were washed twice at 200 x g for 8 min in RPMI 1640 ( Life Technologies , NY , USA ) . Supernatants were discarded and the purity of isolated granulocytes was assessed by flow cytometry . The purity was routinely ≥ 96% . Total IgG was isolated from the plasma of EN , Mf+ , Mf- and CP using prepacked HiTrap Protein G columns ( GE Healthcare , Freiburg , Germany ) according to the manufacturer’s instructions . Briefly , 100 μl of plasma samples were diluted with 1400 μl PBS and passed through a pre-equilibrated protein G-Sepharose column ( GE Healthcare , Freiburg , Germany ) . Since Protein G binds to all human IgG subclasses , non-IgG plasma components were washed out from the column . Bound IgG was eluted in 1 ml fractions using IgG Elution Buffer ( 0 . 2 M Glycine/HCl , pH 3 . 0 ) and neutralized with saturated Tris-HCl ( pH 9 . 0 ) . The antibody concentration was then assessed at 280 nm using a NanoDrop 1000 spectrophotometer ( Thermo Fischer Scientific , Wilmington , USA ) . IgG4 antibodies were purified from IgG-enriched fractions using the CaptureSelect Human IgG4 affinity matrix ( Life Technologies , Paisley , UK ) according to the manufacturer’s instructions . Briefly , CaptureSelect affinity matrix was gently loaded and equilibrated in 10 ml affinity chromatography column with 1x PBS ( pH 7 . 3 ) . Diluted IgG-enriched fractions ( 1:1 volume PBS ) were loaded onto the column and the linear flow rate was set at 15 cm/hour . After washing with 1x PBS , the column was eluted with 0 . 1 M Glycine ( pH 3 . 0 ) and the fractions were immediately neutralized with Tris-HCl ( pH 9 . 0 ) . IgG4 fractions were collected and the purity of fractions assessed by determining the level of IgG subclasses , IgA , IgE and IgM antibodies by Luminex assay . In addition , the total protein concentration in plasma , IgG and IgG4 fractions was determined using a Bradford Protein Assay Kit ( Thermo Fischer Scientific , Wilmington , USA ) . IgA purification was done using immobilized Peptide M/Agarose ( InvivoGen , San Diego , USA ) according to the manufacturer’s instructions . 1 ml of peptide M/Agarose gel was loaded into an appropriate microcentrifuge spin column ( Thermo Scientific , Rockford , USA ) . 1 ml of IgG-depleted plasma from EN were then added to the column and incubated at room temperature for 30 min . After incubation , the column was washed and the flow-through was collected and labeled as IgA negative fractions ( IgA- ) . The bound antibodies were then eluted with IgG elution buffer as described above . The resulting IgA positive ( IgA+ ) fractions were neutralized immediately with neutralization buffer ( 1 M Tris–HCl , pH 9 . 0 ) and store at 4°C until use . Purity was assessed by Luminex analysis as described above . The purity was routinely > 90% To determine the protein concentration of plasma and purified IgA , IgG and IgG4 fractions , a Bradford protein assay kit ( Thermo Scientific , Rockford , USA ) was used according to the manufacturer’s instructions . In brief , serial dilutions of bovine serum albumin ( BSA ) was performed and used as standards against the samples . Another serial dilution of the samples was done in PBS . 300 μl per well of Coomassie blue G-250 ( Cytoscelecton , Denver , USA ) reagent was distributed in duplicate in a 96 well plate ( Greiner Bio-One , Frickenhausen , Germany ) and 3 μl of diluted samples and standard were added . The protein concentration in plasma , IgA , IgG and IgG4 fractions was then measured at 595 nm using a SpectraMAX 190 microplate reader ( Molecular Devices , California , USA ) . To analyze the isotype composition in IgA , IgG/IgG4 positive and negative fractions and in the plasma of EN and LF patients , ProcartaPlex Human Antibody Isotyping Panels ( eBioscience , Vienna , Austria ) were used according to manufacturer’s instructions . Briefly , antibody coated magnetic bead mixtures were incubated with 25 μl of assay buffer , kit standards or diluted plasma samples in a ProcartaPlex 96-wells plates at room temperature for 1 hour . 25 μl of detection antibodies mixture was then added and the plates were incubated on an orbital shaker at 500 rpm for 30 min . After that , each well was incubated with 50 μl of diluted Streptavidin-Phycoerythrin for 30 min . Plates were then washed using a hand-held magnetic plate washer . All incubations were performed at room temperature in the dark . Afterwards , samples were suspended in 120 μl reading buffer . Data were acquired using a MAGPIX Luminex system ( Luminex Cooperation ) and analyzed with ProcartaPlex Analyst software 1 . 0 . The purity of eluted IgG fractions was analyzed by western blot . Samples were treated with 50 mM 2-mercaptoethanol for 5 min , and equal quantities ( 2 . 5 μg ) of the purified proteins and controls were loaded onto separate lanes of a polyacrylamide gel ( 10–12% ) and resolved by SDS-PAGE ( 100 v , 45–60 min ) . The resolved proteins were transferred onto nitrocellulose membranes ( GE Healthcare , Freiburg , Germany ) using a Bio-Rad Trans-Blot Turbo Transfer system ( Bio-Rad , Germany ) . The membranes were then blocked with gelatin blocking buffer ( 3% gelatin in Tris Buffered Saline ( TBS ) ) ( Bio-Rad , Germany ) for 1 hour prior incubation with the primary antibody ( polyclonal mouse anti-human IgG ( H+L ) ) ( Thermo Scientific , Rockford , USA ) for 1 . 5 hours at room temperature . The nitrocellulose membranes were then washed with TBS/0 . 05% Tween 20 before incubation for 1 hour with alkaline phosphatase-conjugated goat anti-mouse IgG ( Bio-Rad Laboratories , USA ) . Immune complexes were finally detected with NBT ( nitro blue tetrazolium ) and BCIP ( 5-bromo-4-chloro-3-indolyl-phosphate , Bio-Rad Laboratories , USA ) . Experiments were repeated at least three times . After establishing the optimal concentrations of IgE , anti-IgE and rIL-3 to induce granulocyte activation and degranulation ( S1 Fig ) , the cells were purified as described above and 2 x 105 cells/well were plated and pre-incubated with 40 ng/ml of natural human IgE antibody ( Abcam , Cambridge , UK ) for 30 min at 37°C/5% CO2 as previously described [53 , 54] . The cells were first preactivated at 37°C/5% CO2 for 10 min in the presence of 2 ng/ml rIL-3 ( Miltenyi Biotech , Bergisch Gladbach , Germany ) , before being stimulated with 25 ng/ml anti-IgE mAb ( Clone BE5 ) ( Abnova , Taipei , Taiwan ) and 10 μg/ml Brugia malayi Ag . Thereafter , the granulocytes were further incubated for 18 hours at 37°C/5% CO2 either alone ( with culture medium ) , or in the presence of appropriately diluted plasma samples ( 5% v:v , containing 5 μg/ml of total proteins ) , IgG and corresponding IgG depleted fractions ( 5 μg/ml of total proteins ) or 2 . 5 μg/ml IgG4 antibodies purified from the IgG positive fractions from the different clinical groups . Granulocyte culture supernatants were collected after 30 min and 18 hours to assess the level of histamine , and after 18 hours to investigate the release of ECP and NE using ELISA-Kits respectively from Abnova ( Taipei , Taiwan ) , Abbexa ( Cambridge , UK ) and eBioscience ( Vienna , Austria ) according to the manufacturer’s recommendations . For histamine detection , samples and standards were first acylated by reacting 50 μl of samples , 25 μl of standards or control with 25 μl of acylation reagent and 25 μl of acylation buffer supplied in the test kit for 45 minutes . 25 μl aliquots of acylated standards , controls and samples were pipetted into wells of the antibody-coated microplate provided with the kit . Then the wells received 100 μl of histamine antiserum and the mixture was allowed to incubate for 3 hours at room temperature . The plates were then washed with the provided washing buffer to remove unbound materials . After that , the bound antibodies were detected using 100 μl of anti-rabbit IgG-peroxidase conjugate using TMB as a substrate . The color was allowed to develop for 20 minutes at room temperature in the dark . The reaction was stopped and the resulting OD values were measured at 450 nm . The histamine concentration , inversely proportional to the OD , was calculated using the SoftMax Pro Data Acquisition and Analysis Software . For the assessment of ECP and NE , pre-coated ELISA plates were incubated with supernatants and standards for 1 hour at room temperature . The plates were then washed and incubated for 1 hour with HRP-conjugated anti-ECP and anti-NE polyclonal antibodies . After a final wash , the plates were developed using the provided TMB substrate and analyzed at 450 nm . To assess granulocyte activation and degranulation , the cells were harvested and washed with FACS buffer ( PBS/2% FCS ) at 1300 rpm for 8 min . 1x105 cells were then resuspended in 100 μl of FACS buffer and blocked with 1 μl of FC- block ( Affymetrix eBioscience , San Diego , CA , USA ) for 15 min . 5μg/1x105 cells of either anti-human CD66b-FITC ( clone: G10F5 ) or CD63-PE ( clone: H5C6 ) and HLADR-FITC ( clone: LN3 ) ( all from Affymetrix eBioscience ) were then added and the cell suspension was incubated for 30 min at 4°C . Cells were then washed two times with FACS buffer and fixed in 200 μl PFA ( 4% ) . To correct spectral overlaps , fluorescence compensation was done using UltraComp ebeads ( Affymetrix eBioscience ) . Data were acquired and analyzed using a FACS Canto flow cytometer and the BD-FACS-DIVA analysis software ( BD Biosciences ) . Before the analysis , granulocyte viability was assessed by FACS using propidium iodide ( PI-PE ) and annexin-V ( Annexin-FITC ) ( all from BD Biosciences , Heidelberg , Germany ) . All samples presented less than 1 and 10% necrotic cells respectively before and after 18 hours incubation . Granulocytes were cultured as previously described and 2 x 105 cells were harvested and washed with PBS . Then 100 μl of diluted cells were aliquoted into cytospin funnels and spun at 500 x g for 5 min onto glass slides ( Engelbrecht , Edermünde , Germany ) in a Hettich Cytospin centrifuge ( Hettich , Tuttlingen , Germany ) and immediately fixed in 4% PFA for 15 min . The slides were then blocked with PBS/1% BSA for 30 min and incubated with the primary antibody ( mouse anti-human monoclonal IgG4 ) ( Thermo Fischer Scientific , Rockford , USA ) for 1 hour . After washing 3 times , the slides were incubated with the Alexa Fluor 488 coupled secondary antibody ( goat anti-mouse polyclonal IgG antibody ) ( Thermo Fischer Scientific , Rockford , USA ) for 1 hour at room temperature in a humidifying chamber . For the investigation of the Fc-receptors associated with IgG4-mediated granulocyte suppression , blocking antibodies against human FcγRI ( 2 μg/ml ) ( Biolegend , San Diego , CA , USA , clone:10 . 1 ) , FcγRII ( 1 μg/ml ) ( Biolegend , San Diego , CA , USA , clone: FUN-2 ) and FcγRIII ( 4 μg/ml ) ( Biolegend , San Diego , CA , USA , clone: 3G8 ) were added before the incubation with purified IgG4 antibodies . Nuclear DNA was labeled with 0 . 25 μg/ml DAPI ( Thermo Fischer Scientific , Rockford , USA ) in PBS for 5 min . Cells were then mounted in VECTASHIELD-Antifade mounting medium ( Vector Laboratories , CA , USA ) and the slides were analyzed using a Zeiss LM-Set Axiocam MRm microscope ( Carl Zeiss , Thornwood , NY , USA ) . To evaluate the capacity of purified IgG4 from EN , Mf+ , Mf- and CP individuals to interact with Brugia antigen , 50 μl Brugia antigen ( 10 μg/ml ) were coated on high binding ELISA plates ( Greiner Bio-One , Frickenhausen , Germany ) overnight at 4°C . The plates were then washed 5 times with PBS/0 . 05% Tween 20 and blocked with PBS/1% BSA for 1 hour at room temperature . The wash step was repeated and 50 μl/well of purified IgG4 from EN , Mf+ , Mf- and CP ( 2 . 5 μg/ml ) were added and the plates were incubated again at 4°C overnight . The wells were washed again as described above and diluted biotin-conjugated mouse anti-human IgG4 ( clone JDC-14 ) ( 1:1000 ) ( from BD Biosciences , Heidelberg , Germany ) was added , followed by incubation at room temperature for 2 hours . After an additional washing step , the plates were incubated with 50 μl/well of Streptavidin-HRP for 45 min in the dark . After a final washing step , 50 μl/well TMB substrate solution were added and the reaction was stopped with 25 μl/well 2N H2SO4 ( Merck KGAA , Darmstadt , Germany ) . Optical density was measured at 450 nm using the SpectraMAX ELISA reader and the results were expressed as arbitrary units ( AU ) using as a standard a plasma sample arbitrarily set at 5 AU . All statistical analyzes were performed using Prism 5 . 03 software ( GraphPad Software , Inc . , La Jolla , USA ) . Comparative analyzes among groups were conducted using the Kruskal-Wallis test with a Dunn’s nonparametric post-hoc test ( > 2 groups ) . Significance was accepted when p < 0 . 05 . Correlation between the levels of antibodies in IgG negative fractions and inhibition capacity was analyzed using Spearman’s rank correlation .
To define the initial antibody profile of EN , Mf+ , Mf- and CP , we compared the plasma levels of IgG1 , IgG2 , IgG3 , IgG4 , IgE , IgM and IgA in different groups using a Luminex-based immunoassay . We found that the IgG1 expressions observed in EN and CP were similarly high . In contrast , Mf+ and Mf- individuals presented reduced IgG1 levels ( Fig 1A ) . However , while the highest levels of IgG2 were detected in the plasma of CP individuals , plasmatic IgG2 in EN and Mf- were significantly lower compared to Mf+ and CP ( Fig 1B ) . The differences observed in the expression of IgG3 between the four groups were not statistically significant ( Fig 1C ) . Interestingly , the expression of IgG4 was relatively low in EN , Mf- and CP but significantly elevated in Mf+ ( Fig 1D ) . This contrasts with lower levels of IgE in those patients in comparison to Mf- and patients with chronic pathological manifestations ( Fig 1E ) . In addition , plasma of EN expressed higher IgA levels compared to Mf+ , Mf- and CP ( Fig 1F ) , whereas no significant differences were seen in the expression of IgM ( Fig 1G ) . Because plasma samples from Mf+ individuals presented high levels of IgG4 antibody and since IgG4 antibodies are known to exhibit anti-inflammatory properties , we hypothesized that plasma from Mf carriers , and specifically IgG4 molecules , would preferentially down-modulate granulocyte activation and degranulation . We then next investigated how crude plasma of NEC , EN , Mf+ , Mf- or CP modulates the function of IL-3/anti-IgE/BmAg activated granulocytes by monitoring the expression levels of CD63/HLADR and analyzing the release of granule components ( histamine , ECP and NE ) . While plasma from NEC , CP and Mf- had no effect on granulocytes ( Fig 2 and S2 Fig ) , those from EN and Mf+ significantly inhibited activation of granulocytes as indicated by the lower percentages of CD63+HLADR- cells ( Fig 2A ) . Interestingly , the plasma of EN presented a higher inhibitory potential on granulocyte activation when compared to those of Mf+ . In line with the activation data , plasma from both EN and Mf+ significantly suppressed the release of histamine ( Fig 2B and S2 Fig ) and NE ( Fig 2C ) . In addition , histamine levels were higher after 30 min and were lower , but detectable , after 18 hours . However , while the plasma of Mf+ individuals significantly inhibited the release of ECP in granulocyte cultures , those of EN failed to suppress the release of ECP ( Fig 2D ) . These results indicate that , in lymphatic filariasis , active factors in EN and Mf+ infected patients’ plasma environment but not present in Mf- and CP patients impaired granulocyte activation . To define the role of IgGs in the suppression of granulocytes by plasma of EN and Mf , we depleted IgG antibodies per affinity chromatography . The purity was analyzed ( S3 Fig ) , and the ability of IgG positive and negative fractions to modulate granulocyte activation was tested . Interestingly , while IgG negative ( IgG- ) fractions of EN significantly suppressed granulocyte activation , IgG positive ( IgG+ ) fractions showed no effect ( Fig 3A ) . Both IgG+ and IgG- fractions from Mf+ significantly inhibited granulocyte activation ( Fig 3B ) whereas neither IgG+ nor IgG- fractions from NEC , Mf- and CP affected granulocyte activation ( Fig 3C–3E ) . Moreover , in Mf+ , the IgG-related inhibition was significantly higher than that observed with negative fractions . These trends were also reflected in the release of histamine ( Fig 3F ) and NE ( Fig 3G ) . Surprisingly both fractions from EN did not impair ECP release ( Fig 3H ) when compared with histamine and NE . These data suggest that whereas total IgG from Mf+ individuals inhibited granulocyte activation , IgG-independent factors , seem to be involved in the suppression by plasma of both EN and Mf+ individuals . To define the IgG-independent factors responsible for granulocyte suppression in EN , we correlated the expression of the remaining antibodies in the IgG-negative fractions ( IgA , IgE and IgM ) with the ability of these plasma to inhibit granulocyte functions . Interestingly , while IgE and IgM presented no correlation with the inhibitory capacity of IgG-negative fractions of EN ( Fig 4A and 4B ) , IgA expression significantly correlated with the inhibition capacity on activated granulocytes ( Fig 4C ) . In addition , while IgA-depleted fractions [ ( EN ) IgA-] lose their ability to suppress granulocyte activation as shown by similar expression of CD63+ cells when compared to the control , peptide M purified IgA+ fractions significantly reduced granulocyte activation ( Fig 4D ) . These data strongly suggest that IgA expression in EN is associated with the inhibition effect observed when their plasma were incubated with activated granulocytes . We next investigated whether the modulation of granulocyte activation and degranulation by Mf+ IgG fractions is associated with the presence of the anti-inflammatory isotype IgG4 . Highly pure fractions of IgG4 antibodies were prepared and the purity validated ( S4 Fig ) . Thereafter the purified fractions were tested on activated granulocytes . Strikingly , while IgG4 antibodies from EN , Mf+ and Mf- significantly suppressed granulocyte activation ( Fig 5A–5C and S4 Fig ) , those from CP have failed to suppress granulocyte activation ( Fig 5D ) compared to the control . In addition , the suppressive effect was completely abrogated after IgG4 removal from IgG fractions ( Fig 5A–5C ) , suggesting that the suppressive effect of IgG fractions stems from IgG4 molecules and not from other IgG antibodies . Furthermore , we investigated whether these effects were dose-dependent . Whereas increasing concentrations of IgG4 from EN , Mf+ and Mf- proportionally reduced the percentage of activated cells ( CD63+/HLADR- ) in a dose-dependent manner , no dose effect was seen when IgG4 from CP patients were used ( Fig 5E ) . Interestingly , the suppressive effect of IgG4 affected mostly neutrophils and basophils but not eosinophils ( S5 Fig ) . Consistent with the granulocyte activation data , we detected lower levels of histamine and NE in supernatants of granulocyte cultures treated with IgG4 antibodies from EN , Mf+ and Mf- compared to those treated with CP-IgG4 ( Fig 5F and 5G ) . However , no significant reduction in the release of ECP was observed after incubation with IgG4 from EN or Mf- ( Fig 5H ) . Table 1 summarizes the effects of plasma , IgG and IgG4 fractions on granulocyte activation . To further explore the mechanisms by which IgG4 interfere with granulocyte activities , we examined the ability of purified IgG4 antibodies from each group to bind to granulocytes and Brugia antigen . While IgG4 molecules from EN , Mf+ and Mf- were able to interact with effector cells , those from CP had no affinity to granulocytes ( Fig 6 ) . However , IgG4 from Mf+ presented a much higher affinity for the cells in comparison to those from Mf- and EN ( Fig 6A–6C and 6E ) . Since differences in the affinity of IgG4 from EN , Mf+ , Mf- and CP to form complex with Brugia antigen can also affect granulocyte modulation , we analyzed the capacity of IgG4 from the different groups to interact with Brugia antigen . We detected no significant differences in the capacity of IgG4 from EN , Mf+ , Mf- and CP to form a complex with Brugia antigen ( Fig 6F ) . Because IgG4 from Mf+ , Mf- and EN bound to granulocytes , we next investigated which FcγRs are involved in their fixation by using blocking antibodies against FCγRI , FCγRII , and FCγRIII . We observed that the blockade of FcγRI ( Fig 7B and 7H ) and FcγRII ( Fig 7C and 7H ) but not FcγRIII ( Fig 7D and 7H ) significantly reduced IgG4 binding to granulocytes . Interestingly , the capacity of IgG4 to bind to granulocytes was completely abrogated when FcγRI and FcγRII were simultaneously blocked ( Fig 7E and 7H ) . Corresponding results were also observed when the activation of granulocytes in the presence of IgG4 and anti-FCγRs was measured ( Fig 7I ) . These findings suggest that IgG4-mediated granulocyte suppression in Mf+ patients involves FcγRI and FcγRII but not FcγRIII .
The pathology of lymphatic filariasis results from the complex interplay between the pathogenic potential of the parasite , the host’s immune response and collateral bacterial and/or fungal infections [55] . Even though the role of IgG4 in immunosuppression in filariasis is well known [56] , only few data exist on their impact on effector cells . Recent investigations suggest that different granulocyte subsets may be important in the immune response to helminth infections [28 , 29] . Here we used a sequential depletion/purification approach to define the immune components that are responsible for granulocyte suppression in the plasma of individuals from the different LF clinical groups . The advantage of this approach is that , in addition to analysing quantitative differences among these groups , it can be investigated whether a given antibody retains functional capacity when used at normal concentrations . We tested both IgG positive and negative fractions and could show that while IgG+ fractions from Mf+ suppressed granulocytes , those of EN , Mf- and CP had no effect . A further purification step on the IgG+ fractions using anti-IgG4 in the purification matrix indicated that IgG4+ fractions from Mf+ , Mf- and EN displayed comparable suppressive capacities . This apparent contradiction with the data obtained using plasma and total IgG is due to the level of purification of IgG4 used here at the same concentration and confirms that quantitative differences in the expression of IgG4 play a significant role in the suppressive properties observed in the plasma of the different clinical groups . These data suggest that IgG4 antibodies from EN , Mf+ and Mf- might have the same overall suppressive properties and the alterations observed when using total IgG or crude plasma are due to differences in the ratios IgG4/total IgG as previously postulated [10 , 57] . These observations are in line with findings of Mohapatra et al . , indicating that plasma of asymptomatic individuals ( Mf+ ) in contrast to those of CP mediated suppression of mitogen-induced proliferation of human PBMCs [58] . Bennuru et al . further demonstrated that sera from CP patients promoted the proliferation of lymphatic endothelial cells whereas those of EN suppressed this proliferation [59] . Plasma of Mf- and CP contain higher levels of pro-inflammatory IgG1-3 and IgE antibodies , known to be relevant for parasite clearance as demonstrated in different animal models of filariasis [60–66] but are also associated with pathology development in CP-patients [4 , 9 , 67] . The data obtained using the plasma of CP patients were initially similar to those for EN and Mf- , since they displayed low levels of IgG4 and presented no inhibition effect on granulocytes . However purified IgG4 from this clinical group fundamentally lack suppressive properties even when higher concentrations were used , suggesting the existence of two distinct mechanisms of inhibition of the immunoregulatory antibody IgG4 in CP patients , first by down-modulating its level and second by modifying the properties of the remaining IgG4 molecules . This is likely associated with the proinflammatory environment including Th17 and Th22 characteristic of the CP profile [68] . A recent study on patients undergoing cardiac surgery indicated a strong connection between glycosylation features related to fucosylation , sialylation and bisecting GlcNAc and severity of inflammatory response [69] . Since glycosylation features can affect the function of antibodies [70] , this is a possible explanation for the lack of suppressive properties of IgG4 antibodies purified from CP patients . Since no differences were detectable in the purity of the IgG4 positive fractions , and because IgG4 is known to present no allotypic variations [71] , post-translational alterations could , as mentioned above , explain why functional differences are observed between IgG4 molecules in our settings . Indeed , different investigations have shown that all IgGs contain a conserved glycosylation site at N297 in CH2 domain that is important for the structural conformation of the Fc region necessary for binding to FcRs and complement factors [71–73] . Differences in the glycosylation states may ultimately influence the effector pathways elicited by the Fc domain [73] . Fucosylation and sialylation for example are two extensively investigated glycan modifications of Fc that significantly modulate the affinity of Fc regions to FcRs [70 , 73] . In several health and disease settings , a shift toward certain Fab- and Fc-glycoforms of antibodies has been reported [70] . It is very likely that the degree of glycosylation differs in the IgG4 molecules from EN , Mf+ , Mf- and CP and subsequently modulates their affinity to FcγRs . In addition to post-translational alterations , other factors such as the previously described differential recognition of filarial antigens by antibodies in the different clinical groups [74] , could also have an impact on the ability of IgG4 antibodies to bind granulocytes . Indeed , differential recognition of filarial antigens could differently affect the formation of antigen-antibody complexes and thus modulate the inhibition capacity of IgG4 on activated granulocytes . Other parameters that potentially can explain the different affinity and inhibition capacity of IgG4 antibodies from the four LF clinical groups are FcR cross-linking and steric hindrance that can respectively reduce availability and access to FcγRs on granulocyte surface [75] . Differences in the inhibition effect could also be modulated by differences in the levels of autoantibodies in the different clinical groups as suggested by Mishra et al . [76] . The most unexpected finding in the present work is the suppression of granulocyte activation by the plasma of EN since this clinical group is usually associated with putative immunity and strong pro-inflammatory responses [77] . Our data indicated an elevated expression of IgA in the plasma of EN and revealed a significant correlation between IgA expression and the suppressive properties in the IgG-negative fractions of EN . Sahu et al . observed similar trends when comparing the expression of filarial-specific IgA in LF endemic populations [78] . In addition , recent investigations indicated that IgA is a multifaceted molecule that can display both pro- and anti-inflammatory properties depending on the environment and can interact with FcαRI on the surface of eosinophils and neutrophils [79 , 80] . Our data also indicate that plasma from EN failed to significantly inhibit the release of ECP but suppressed histamine and NE suggesting that IgA in the plasma of EN selectively modulate neutrophil and basophil but have less effect on eosinophils . Our data also indicate that except CP , IgG4 from all clinical groups suppress granulocytes after interaction with both FcγRI and FcγRII confirming results of previous studies indicating that IgG4 binds to FcγRI , FcγRIIa , FcγRIIb and FcγRIIc [81–83] . Activatory FcγRs typically signal through an immunoreceptor tyrosine-based activation motif ( ITAM ) whereas the inhibitory FcγRIIb triggers signals via immunoreceptor tyrosine-based inhibitory motif ( ITIM ) [84 , 85] . Stimulation through ITAM pathway leads to pro-inflammatory activity resulting in destruction and clearance of antigens by phagocytosis , ADCC and promotion of antigen presentation [84] . Bruhns et al . further suggested that IgG4 antibodies display a higher affinity for the inhibitory receptor FcγRIIb [86] . This suggests , in our settings , that IgG4 antibodies may exert their suppressive properties via two distinct but complementary pathways . Suppressive IgG4 antibodies very likely bind to the inhibitory FcγRIIb and deliver a direct anti-inflammatory signal while impeaching pro-inflammatory antibodies ( IgG-1-3 ) to interact with FcγRI . While investigating the role of immunoglobulins in the modulation of granulocyte activation , we used affinity-purified total IgG , IgA and IgG4 . The use of non-antigen specific antibodies was due to technical limitations associated with the amount of patient’s material available . However , the incubation of granulocytes with anti-IgE and IL-3 allows non-antigen specific stimulation of granulocyte subpopulations . Also , due to the well-known technical difficulties associated to the cryopreservation of granulocytes [87 , 88] , the present study used a heterologous system where sera and purified antibody fractions from Ghanaian patients and controls were tested on heterologous granulocytes from healthy European blood donors . Even though a certain level of alloreaction cannot be excluded , our data are validated by the use of the same background for all tested samples . Indeed , all plasma or purified antibody fractions were tested on granulocytes of the same group of donors ( n = 9 ) . Also , the use of both heterologous and autologous settings for non-endemic controls showed no impact on the granulocyte activation and histamine release ( S6 Fig ) . Even though the sample size is relatively small due to the difficulty to recruit patients that have received no anti-filarial treatment after extensive mass drug administration programs and the significant reduction of the disease burden in this region [89 , 90] , the current study extends previous findings suggesting that expression of IgG4 in asymptomatic Mf+ individuals is associated with inhibition of granulocyte functions [10 , 91 , 92] and suggests that prominent IgA expression in EN also affects granulocytes’ functions . Our data also provide new insights on a possible role of functional modulation of IgG4 antibodies in CP-patients , providing possible novel clarifications of the mechanisms through which tolerance or pathology is induced in LF , and suggest that IgA and IgG4 may represent meaningful candidates for targeted therapy against LF . Modulating IgG4 and IgA expression and functional properties may for example contribute in the future to the reduction of inflammatory damages in patients with chronic filarial infections . | Lymphatic Filariasis , also known as elephantiasis , infects an estimated 39 million people in 73 tropical and sub-tropical countries . The most severe clinical manifestations of the disease include swelling of the scrotal area and lower limbs ( hydrocele and lymphedema ) . It is well admitted that host immune reactivity plays a critical role in the pathogenesis of the disease . Previous investigations have linked the non-cytolytic antibody IgG4 to the hyporesponsive states in filarial infections . However , few data exist on how this antibody is involved in the pathogenesis of human filariasis . Here we investigated the role of this antibody in disease pathogenesis by comparing the effect of plasma , IgG and IgG4 fractions from the four clinical categories of individuals; chronic pathology individuals ( CP ) , asymptomatic microfilaria positive ( Mf+ ) and negative ( Mf- ) and uninfected endemic normal individuals ( EN ) on activated granulocytes . We could show that granulocyte activation was significantly inhibited in the presence of plasma from EN and Mf+ and that , affinity-purified IgG4 antibodies from EN , Mf+ and Mf- individuals inhibited granulocyte activation in a dose-dependent manner via the immune receptors FcγRI and FcγRII . Our data also reveal significant functional differences between IgG4 molecules from EN , Mf+ , Mf- and CP . | [
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"granulo... | 2017 | Pathological manifestations in lymphatic filariasis correlate with lack of inhibitory properties of IgG4 antibodies on IgE-activated granulocytes |
Influenza A virus pandemics and emerging anti-viral resistance highlight the urgent need for novel generic pharmacological strategies that reduce both viral replication and lung inflammation . We investigated whether the primary enzymatic source of inflammatory cell ROS ( reactive oxygen species ) , Nox2-containing NADPH oxidase , is a novel pharmacological target against the lung inflammation caused by influenza A viruses . Male WT ( C57BL/6 ) and Nox2−/y mice were infected intranasally with low pathogenicity ( X-31 , H3N2 ) or higher pathogenicity ( PR8 , H1N1 ) influenza A virus . Viral titer , airways inflammation , superoxide and peroxynitrite production , lung histopathology , pro-inflammatory ( MCP-1 ) and antiviral ( IL-1β ) cytokines/chemokines , CD8+ T cell effector function and alveolar epithelial cell apoptosis were assessed . Infection of Nox2−/y mice with X-31 virus resulted in a significant reduction in viral titers , BALF macrophages , peri-bronchial inflammation , BALF inflammatory cell superoxide and lung tissue peroxynitrite production , MCP-1 levels and alveolar epithelial cell apoptosis when compared to WT control mice . Lung levels of IL-1β were ∼3-fold higher in Nox2−/y mice . The numbers of influenza-specific CD8+DbNP366+ and DbPA224+ T cells in the BALF and spleen were comparable in WT and Nox2−/y mice . In vivo administration of the Nox2 inhibitor apocynin significantly suppressed viral titer , airways inflammation and inflammatory cell superoxide production following infection with X-31 or PR8 . In conclusion , these findings indicate that Nox2 inhibitors have therapeutic potential for control of lung inflammation and damage in an influenza strain-independent manner .
The early host innate immune response directed against influenza A virus infection in the absence of pre-existing immunity is typically characterised by activation of airway epithelium and resident alveolar macrophages , and release of inflammatory mediators resulting in the trafficking of additional macrophages , neutrophils and T lymphocytes into the lung [1] . The recruitment of macrophages and neutrophils into the lung controls seasonal influenza virus and results in mild clinical symptoms . However , some pandemic influenza A viruses initiate an aggressive persistent trafficking of large numbers of inflammatory cells , which is now considered to be associated with lethal disease , culminating in severe lung injury as seen for H5N1 and 1918 pandemic influenza virus infection [2] . Recent evidence suggests that much of the acute lung injury caused by H5N1 can be attributed to excessive ROS production ( i . e . oxidative stress ) initiated by an overactive innate immune response [3] , [4] . ROS including superoxide anion and its derivatives peroxynitrite ( OONO− ) , hydrogen peroxide ( H2O2 ) and hydroxyl radical ( OH . ) are indiscriminately toxic to cells when produced in excess and capable of regulating pro-inflammatory cytokine production . The cellular source of ROS is most likely to be infiltrating inflammatory cells , which on a cell-to-cell basis generate more ROS than any other cell type [5] , [6] . Identification of the enzymatic sources of ROS may pave the way for therapies that combat the oxidative stress-dependent lung injury caused by influenza A virus infection . A number of enzyme systems expressed in mammalian cells are capable of generating superoxide ( for reviews see [5] , [6] ) . However , NADPH oxidase is the primary source of superoxide production by inflammatory cells [5] , [6] . The inflammatory cell NADPH oxidase enzyme consists of a number of protein subunits including the catalytic subunit Nox2 , the smaller α-subunit , p22phox , as well as multiple regulatory subunits , including the organizer protein p47phox , the activator protein p67phox , p40phox and the small G protein Rac1 . Nox2 was recently shown to play a role in the clearance of influenza infection and in lung dysfunction [7] . However , it remains to be determined if Nox2 influences: ( i ) low and high pathogenicity influenza A virus infection , ( ii ) the infiltration of sub-populations of inflammatory cells into the airways , ( iii ) superoxide and peroxynitrite production by key inflammatory cells in the airways , ( iv ) alveolar epithelial cell apoptosis , ( v ) the levels of potential antiviral nitric oxide ( NO ) generated and ( vi ) crucial adaptive immune responses that clear influenza virus . Moreover , it is unknown if pharmacological inhibitors of Nox2 protect against influenza virus-induced airways inflammation and damage . The present study clearly shows that Nox2 is critical for the control of influenza infection and that inhibition of Nox2 may be a way of controlling future pandemics by modulating the host instead of the virus .
Naïve ( i . e . no virus ) Nox2−/y mice had similar total cell numbers in the BALF to naïve WT mice ( Figure 1A ) . We then analysed the extent of cellular infiltration in the BALF of WT and Nox2−/y mice infected with X-31 virus 3 and 7 days post infection . Three days following infection , the cellular infiltrate in WT mice increased by ∼12 . 5 fold from basal levels ( Figure 1A ) , which was similar in Nox2−/y mice ( Figure 1A ) . However , by Day 7 post infection , the total number of cells in Nox2−/y mice was significantly lower ( ∼40% , P<0 . 05 ) when compared to WT controls ( Figure 1A ) . Close analyses of the infiltrating and resident populations by differential cell counting revealed that both 3 and 7 days post X-31 infection , BALF from Nox2−/y mice contained significantly less ( P<0 . 05 ) macrophages than WT mice ( Figure 1B ) . There was a trend for neutrophil numbers to be higher in Nox2−/y mice compared to WT mice infected with X-31 although this was not statistically significant ( Figure 1C ) . We also examined the degree of airway inflammation caused by X-31 in H&E stained lung sections from WT and Nox2−/y mice killed at Day 3 post infection . We chose this time point to examine the lung inflammation as we have previously shown this to represent the peak of airways inflammation and viral load following X-31 virus infection [8] . Lungs from WT mice had obvious peri-bronchial inflammation and prominent bronchial infiltrates consisting of mononuclear cells and neutrophils ( Figure 2A , B ) . In contrast , histological examination of Nox2−/y mice showed considerably less bronchial cell infiltrate and peri-bronchial inflammation ( Figure 2C , D ) . We examined basal and phorbol dibutyrate ( PDB ) -stimulated superoxide production by inflammatory cells in BALF of naïve and X-31-infected WT and Nox2−/y mice . BALF cells isolated from naïve WT mice produced superoxide under basal conditions ( data not shown ) , which was increased in the presence of PDB stimulation ( Figure 3 ) . In comparison , BALF cells isolated from naïve Nox2−/y mice produced very little superoxide under both basal conditions ( not shown ) and following PDB stimulation ( Figure 3 ) . Ex vivo treatment of BALF cells with SOD ( 300U/ml ) significantly reduced the chemiluminescence signal at 3 days following infection confirming that chemiluminescence resulted from superoxide detection ( data not shown ) . BALF inflammatory cells from WT mice infected with X-31 produced significantly higher amounts ( ∼7-fold ) of basal ( not shown ) and PDB-stimulated superoxide than BALF cells obtained from naïve mice ( Figure 3 ) . Again , superoxide production was virtually abolished in BALF cells isolated from lungs of Nox2−/y mice ( Figure 3 ) . Superoxide gives rise to toxic reactive nitrogen species such as peroxynitrite when it reacts rapidly with NO . Thus , we examined 3-nitrotyrosine immunofluorescence as a measure of peroxynitrite production . Lung sections from WT mice infected with X-31 displayed strong immunofluorescence for 3-nitrotyrosine in the inflammatory cells that infiltrated the airways , as well as in the alveolar tissue ( Figures 4A and C ) . By contrast , little immunofluorescence was observed in similar lung sections obtained from Nox2−/y mice infected with X-31 ( Figures 4B and D ) . To determine if reduced inflammation of Nox2−/y mice correlated with lower levels of virus , we measured lung virus titers using the plaque assay . Lung virus titers were significantly lower ( ∼45% , P<0 . 05 ) in Nox2−/y mice than WT mice at the day 3 time-point ( Figure 5A ) . We explored whether Nox2 deletion had an impact on X-31-induced body weight loss . WT and Nox2−/y mice lost similar amounts of weight following X-31 infection ( Figure 5B ) . We hypothesized that the enhanced clearance of virus from the lungs of Nox2−/y mice could be attributed to an enhanced level of NO in the absence of superoxide . To address this we measured nitrite levels in BALF using the Griess reaction 3 days after X-31 infection . BALF from Nox2−/y mice had similar levels of nitrite ( 26 . 42±4 . 37 µM ) , and thus NO , to WT mice ( 22 . 05±4 . 48 µM ) ( P = 0 . 08; n = 9 ) . Accumulating evidence suggests that apoptosis of lung alveolar epithelial cells underlies alveolar injury and lung leakage , which are hallmarks of the acute lung injury/primary pneumonia following influenza A virus infection . Thus , we examined alveolar epithelial apoptosis using cleaved caspase 3 immunohistochemistry . Lung sections from WT mice infected with X-31 displayed strong immunofluorescence for cleaved caspase 3 in the alveolar tissue ( Figures 6A and C ) . By contrast , there was strikingly very little immunofluorescence observed in similar lung sections obtained from Nox2−/y mice infected with X-31 ( Figure 6B and D ) . We hypothesised that the reduced macrophage infiltrate observed in Nox2−/y mice following infection might be due to a decrease in chemokines responsible for macrophage recruitment . MCP-1 levels in WT lungs were significantly ( P<0 . 05 ) increased 3 days post X-31 infection compared to naïve controls ( Figure 7A ) . However , Nox2−/y mice infected with X-31 virus had significantly ∼40% lower levels of MCP-1 compared to X-31-infected WT mice ( Figure 7A ) . We also examined the expression of the cytokine IL-1β , which has been shown to enhance influenza virus clearance , protect from virus-induced mortality and stimulate neutrophil recruitment [9] , [10] . Following infection with X-31 virus , the levels of IL-1β mRNA expression in Nox2−/y mouse lungs were ∼3-fold higher than that in WT lungs ( Figure 7B ) . The TNF-α expression level was also assessed given that it has been previously implicated in influenza immunopathology . There was no difference in TNF-α expression between Nox2−/y mice and WT mice ( Figure 7C ) . There were no significant differences in levels of MCP-1 , IL-1β and TNFα between strains in naïve mice ( Figure 7 ) . We also explored whether there were changes in the neutrophil chemoattractant KC . QPCR revealed a small and significant increase in KC expression in both naïve and X-31 infected Nox2−/y mice lungs compared to WT lungs , which supports the small , albeit insignificant increase in neutrophilia in the Nox2−/y lungs ( Figure 7D ) . NADPH oxidase-deficient T cells have been previously shown to produce a Th1 skewed cytokine profile following TCR stimulation with cross-linking antibody [11] . Therefore we investigated the effect of Nox2−/y deficiency on the magnitude and polyfunctionality of two immunodominant CD8+ T cell specificities . Tetramer staining of the BALF ( Figure 8A–C ) and spleen ( Figure 8D–F ) showed no significant differences in CD8+ T cell numbers between WT and Nox2−/y animals . Furthermore influenza-specific CD8+DbNP366+ and DbPA224+CD8+ T cells were stimulated in vitro with relevant peptide and cytokine expression ( IFN-γ , TNF-α and IL-2 ) detected using intracellular cytokine staining . There were no differences in cytokine expression observed between Nox2−/y and WT animals ( data not shown ) . This suggests that absence of Nox2 does not affect CD8+ T cell effector function . As genetic deletion of Nox2 suppresses lung injury associated with influenza A virus infection , we examined whether pharmacological inhibition of Nox2 in vivo with apocynin similarly protects against X-31 influenza A virus infection . Apocynin treatment of influenza A virus-infected WT mice resulted in significant reductions in BALF cellularity and numbers of macrophages and neutrophils ( P<0 . 05 ) ( Figure 9A ) . Basal and PDB-stimulated superoxide production were significantly lower ∼60% ( P<0 . 05 ) in BALF cells isolated from apocynin-treated mice than in cells from untreated mice ( Figure 9B ) . Strikingly , apocynin-treated mice displayed ∼50% reduction in viral titers when compared to untreated controls indicating that apocynin not only has anti-inflammatory properties but also facilitates virus clearance ( Figure 9C ) . We also examined the effect of apocynin treatment following PR8 influenza A virus infection in WT mice . As with X-31 infection , apocynin significantly suppressed BALF cellularity and superoxide production ( Figure 9D–E ) . Nitrite levels were similar in BALF taken from X-31 and PR8 virus-infected control ( 18 . 98±1 . 17 µM and 21 . 31±5 . 23 µM , respectively ) and apocynin-treated mice ( 16 . 23±1 . 11 µM and 17 . 14±2 . 5 µM , respectively ) . ( n = 4–7 ) .
The recent outbreak of pandemic H1N1 influenza A virus has reinforced the urgent need for new pharmacological strategies that not only reduce virus replication but also the often-lethal , lung injury . Ideally , new therapies should show strong clinical efficacy against emerging and seasonal influenza A virus strains . The present study has shown that the absence of Nox2 ( i . e . Nox2−/y mice ) or inhibition of Nox2 activity ( apocynin-treated mice ) substantially reduces inflammatory cell superoxide production , lung peroxynitrite levels , airways inflammation and apoptosis following infection with low and high pathogenicity influenza A virus strains . Strikingly , it also enhances clearance of the virus . Thus , modulation of Nox2 oxidase activity may represent a new therapeutic approach for controlling the lung inflammation caused by influenza A virus strains for which the population has no pre-existing immunity . Snelgrove et al . , 2006 provided evidence for a significant improvement in lung function and for a reduced level of lung tissue damage in Nox2−/− mice following low pathogenicity infection with X-31 influenza A virus [7] . In the present study we utilized a dose of X-31 that causes substantially greater BALF inflammation . We found that pulmonary challenge of wild type mice with X-31 resulted in a substantial degree of lung inflammation characterised by an accumulation of inflammatory cells around the peri-bronchial regions . By contrast the same viral infections caused markedly less peri-bronchial inflammation in Nox2−/y mice . It is widely regarded that influenza A virus infection can cause extensive alveolar epithelial damage due to apoptosis resulting in alveolar leakage and consequently lung oedema and dysfunction [12] . In the present study , we show for the first time a substantial reduction in alveolar epithelial apoptosis in Nox2−/y mice compared to WT controls . Previous studies examining the effects of infection with the highly lethal avian H5N1 virus in mice genetically deficient in the regulatory subunit of Nox2 activity , p47phox , demonstrated similar protective effects to those seen here in Nox2−/y mice including significantly less pulmonary oedema [4] . Thus , Nox2-containing NADPH oxidase appears to be detrimental to the host following influenza A virus infections that cause mild , modest and even severe lung injury [4] , [7] . The lethal lung pathology caused by pandemic strains of influenza A virus is believed to be due , at least in part , to an excessive host innate response characterized by a massive infiltration of macrophages and neutrophils [2] , [13] . Activated macrophages and neutrophils produce large amounts of superoxide to limit the virus . However , in excess amounts , superoxide is toxic and capable of inducing significant injury to surrounding tissue . Indeed , this was exemplified by studies that showed that mice survived a potentially lethal influenza A virus infection when treated with pyran conjugated superoxide dismutase ( SOD ) to inactivate superoxide [3] . Although superoxide possesses considerable oxidising power to modify redox sensitive pathways and cause oxidative damage to cells , its biological toxicity is most likely due to its ability to rapidly give rise to a number of ROS and reactive nitrogen species with greater oxidising capacity such as OONO− . . These molecules have detrimental biological effects including nitration and oxidation of macromolecules , including proteins and DNA . Furthermore , it is well established that peroxynitrite is a powerful stimulant of apoptosis via the caspase 3 pathway ( for review see [14] ) . Previously , it was concluded that one of the most important pathogenic factors in influenza A virus–induced pneumonia is peroxynitrite [15] . In the present study we show that the source of superoxide was solely Nox2 oxidase — as BALF cells isolated from Nox2−/y mice produced almost no superoxide both basally and following stimulation with PDB . Moreover , we show for the first time , substantially less peroxynitrite in the lungs of Nox2−/y mice compared to WT mice , indicating unequivocally that Nox2 is the major source of peroxynitrite induced by influenza A virus infection . Thus , it is highly likely that the protective effects of Nox2 inhibition are due to a reduction in superoxide and one of its major downstream derivatives , peroxynitrite . Although from the present study , it appears that Nox2 is the predominant source of BALF inflammatory cell superoxide and the major source of lung tissue peroxynitrite production following influenza A virus infection , previous studies have implicated xanthine oxidase expressed in airways epithelium as a source of pathogenic superoxide [3] . Therefore , perhaps the most efficacious therapeutic approach against influenza A virus-induced lung oxidative stress would be to abolish the activities of both Nox2-containing NADPH oxidase and xanthine oxidase . Pulmonary challenge with influenza A virus initiates a persistent infiltration of cells into the lungs , which marks the beginning of the innate immune response . Our study has shown that at 3 days post infection , the predominant cell types in the airway are the macrophages followed by neutrophils . By contrast , lungs of infected Nox2−/y mice had generally less cells compared with wild type controls particularly at Day 7 . Interestingly , this reduced airways cellularity in Nox2−/y lungs appeared to be due to a specific reduction in macrophage numbers which were ∼40% lower than in wild type controls . The reason for a reduction in macrophage numbers in Nox2−/y lungs is likely due to a reduction in their recruitment as levels of the chemotactic factor MCP-1 in these lungs were significantly lower . Indeed , studies performed with MCP-1 knockout mice showed a significant reduction in macrophage recruitment into the lungs during influenza infection [16] . MCP-1 production can occur in a number of cells including the airways epithelium . Although ROS are classically considered to cause lung damage when produced in excess because they are toxic to cells , they may also be involved in signal transduction pathways that regulate release of pathogenic cytokines such as MCP-1 from airways epithelium . Irrespective of the mechanism of ROS-dependent cytokine release , our study indicates that inhibition of Nox2-derived ROS has the potential to reduce the overall numbers of infiltrating inflammatory cells into the airways and hence the overall immunopathological clinical features induced by pandemic-inducing strains of influenza A viruses . In this respect our study contradicts the Snelgrove et al . study in that macrophage numbers and overall inflammatory cell numbers were significantly lower in Nox2−/y mice whereas Snelgrove et al . , showed a heightened level of these cells . We hypothesize that differences may be attributed to the gender of the host i . e . male mice in our study as opposed to female mice by Snelgrove et al . , 2006 [7] . Although currently , we have no experimental evidence to suggest a potential gender difference in the airways inflammation caused by influenza virus infection , we have previously demonstrated a considerable gender difference in Nox2 activity under the settings of experimental stroke in mice [17] . Specifically , we showed that Nox2 oxidase activity in cerebral arteries is substantially higher in male mice compared to female mice [17] . A potential gender difference in the airways inflammation caused by influenza A virus infection certainly warrants further investigation . Our study reveals a protective anti-inflammatory effect of Nox2 inhibition that could potentially modulate the fatal immune response triggered by pandemic influenza . That is , inhibition of Nox2 not only suppresses the production of toxic ROS by infiltrated macrophages and neutrophils but it also results in a reduction in the actual numbers of these cells in the airways . Although this would appear to be an attractive way of modulating an aggressive host immune response triggered by influenza A viruses , the dampening of this pro-inflammatory response might be predicted to compromise the ability of the host to effectively eliminate the virus . This has been well documented with the use of immunomodulators such as the COX2 inhibitors celecoxib and mesalazine , and for steroids . These compounds are effective at suppressing the early innate immune response but this comes with the cost of compromising viral clearance [18] , [19] . In the present study , we showed that Nox2 deletion results in a reduction in lung viral titers . However , how inhibition of Nox2 derived ROS results in a ‘paradoxical’ reduction in virus titer in the lungs is unknown , for ROS are classically believed to be necessary for clearance of pathogens . One possibility is that the protective effect of superoxide inhibition is due to a resulting increase in bioavailability of anti-viral NO ( for review see [20] ) . In the present study we show that NO levels in the BALF of Nox2−/y mice are unlikely to be different to WT mice , at least after 3 days post infection . Whilst this appears surprising , it is consistent with previous reports that have shown unequivocally that NO levels only seem to increase in the lungs after 4 days post infection [15] . Thus , at least at Day 3 post infection where we observe a considerable improvement in outcome , NO is unlikely to be contributing to this protection . Snelgrove et al proposed the reduced virus titers were due to heightened macrophage numbers in the airways in the Nox2−/− mice and presumably enhanced clearance of the virus by these cells [7] . As mentioned , in the present study we show a reduction in macrophages in the Nox2−/y lungs , and thus , this is unlikely to explain the reduction in viral titers observed here . Although we currently have no experimental evidence to suggest how suppression of Nox2 results in a reduction in viral titers , one strong possibility is a reduction in virus replication within the airways epithelium . A number of studies have shown evidence that removal of ROS with antioxidants such as N-acetyl-cysteine suppresses replication of influenza A viruses including H5N1 in airway epithelial cells [21] . ROS are proliferative mediators and thus , may be crucial for viruses to replicate within cells . Overall , it appears that suppression of Nox2 and its production of ROS may have a dual beneficial effect , which includes suppression of lung apoptosis/inflammation and viral titers . We also addressed whether inhibition of Nox2 influences important processes of the adaptive immune system . For example , does Nox2 oxidase play a role in antigen processing and presentation to CD8+ T lymphocytes ? [22] . This process is crucial for effective activation of the adaptive immune response as it stimulates proliferation of CD8+ T lymphocytes that recognize viral antigens presented by infected cells . Snelgrove et al . , 2006 showed a modest increase in CD8+ T cell numbers in the BALF of Nox2−/− mice compared to WT mice and suggested this is likely to explain the enhanced viral clearance in this strain of mice . In the present study we quantified virus antigen specific CD8+ T lymphocytes in the spleen and BALF using tetrameric complexes targeting influenza-specific CD8+DbNP366+ and DbPA224+CD8+ T cells . Our findings indicate that in the absence of Nox2 , antigen specific T cell-mediated immunity is preserved . To demonstrate therapeutic relevance of our findings , we examined whether inhibition of Nox2 activity with apocynin similarly protects against influenza A virus infection . Over the past decade apocynin has gained recognition as the gold standard inhibitor of Nox2 activity by preventing the association of p47phox with the Nox2 subunit ( for review see [5] ) . There have been numerous reports describing a beneficial effect of apocynin in the settings of hypertension , cerebral ischemia-reperfusion injury , stroke outcome and myocardial infarction via its ability to inhibit Nox2 [5] . In the present study , mice were treated with apocynin at a dose ( i . e . 2 . 5 mg/kg/day ) shown previously to protect mice against ischemia damage caused by stroke [23] . Importantly , the effect of this dose of apocynin was similar to that seen in Nox2−/y mice and apocynin did not provide further protection in Nox2−/y mice , confirming a Nox2 specific action of apocynin [23] . Our study shows that administration of apocynin causes a powerful suppression of airways inflammation characterised by a decrease in the infiltration of macrophages , and neutrophils . This culminated in a substantial and visible reduction in oedematous bloody lung tissue following PR8 infection . In addition , apocynin significantly reduced virus titers . Thus , our study demonstrates an important and potentially clinically attractive effect of apocynin . That is , not only does apocynin possess potent anti-inflammatory effects but also it has the ability to promote viral clearance . Future studies will examine the use of apocynin , and other novel Nox2 inhibitors , as potential therapeutics . To summarize , current strategies for the treatment of influenza A virus-induced lung disease are focussed primarily at halting mechanisms of viral infection and replication [24] . Far less attention has been directed to investigating mechanisms that modulate host responses , which lead to lung inflammation and pathology . In the present study we evaluated the role of Nox2 oxidase , the primary source of ROS in immune cells in the lung immunopathology caused by influenza A virus of varying virulence . The absence of Nox2 reduced airways inflammation , lung oxidative stress and apoptosis . Moreover , Nox2 may impede with virus clearance and/or stimulate virus replication . We envisage that use of Nox2 inhibitors , in combination with antiviral strategies , may be effective tools against morbidity and mortality induced by seasonal and pandemic stains of influenza A virus .
Specific pathogen-free male C57BL/6 ( wild type ) and Nox2 deficient ( Nox2−/y ) mice ( C57BL/6 background ) aged between 7 and 10 weeks and weighing ∼25 g were bred at the Department of Pharmacology at Monash University . The animals were housed at 20°C on a 12 h day/night cycle in sterile micro-isolators and fed a standard sterile diet of Purina mouse chow with water allowed ad libitum . The experiments described in this manuscript were approved by the Animal Experimentation Ethics Committee of The University of Melbourne and conducted in compliance with the guidelines of the National Health and Medical Research Council ( NHMRC ) of Australia on animal experimentation . Male naïve WT control and Nox2−/y mice were anaesthetized by penthrane inhalation and infected intranasally ( i . n . ) with 1×104 plaque forming units ( PFU ) X-31 ( H3N2 ) or 50 PFU PR8 ( H1N1 ) in a 35 µl volume , diluted in PBS . All mice were killed at day 3 ( peak of viral titres ) or day 7 ( resolution of infection ) following influenza infection . The Nox2 selective inhibitor , apocynin ( 2 . 5 mg/kg ) was administered to WT mice via intraperitoneal ( i . p . ) injection daily for 3 days prior to either X-31 or PR8 influenza A virus infection , and for up to 3 days following infection . We have previously shown that 2 . 5 mg/kg apocynin can selectively inhibit Nox2 oxidase activity [23] . Mice were killed by an i . p . injection of sodium pentobarbitone ( 360 mg/kg ) and BAL performed as we have previously shown [25] , [26] . Briefly , lungs from each mouse were lavaged in situ with a 400 µl aliquot , followed by three 300 µl of PBS . The total number of viable cells in the BALF was determined by using ethidium bromide and acridine orange ( Molecular Probes , San Diego , USA ) on a standard Neubauer hemocytometer using a Zeiss Axioscope Fluorescence microscope . Cytospins were prepared using 20–50 µl BALF at 350 rpm for 10 min on a Cytospin 3 ( Shandon , UK ) . Cytospin preparations were stained with DiffQuik ( Dade Baxter , Australia ) and 500 cells per slide were differentiated into macrophages , neutrophils , eosinophils , and lymphocytes by standard morphological criteria . The remaining BALF was spun at 3000 rpm for 5 min to pellet cells for flow cytometry and superoxide detection . In addition , the spleens of virus-infected mice were collected for flow cytometry . Histology was performed as previously described [26] . Briefly , mice were killed by i . p . anaesthesia ( 360 mg/kg sodium pentobarbitone ) overdose and then perfusion fixed via a tracheal cannula with 10% neutral buffered formalin at exactly 200mm H2O pressure . After 10 min , the trachea was ligated , the lungs were removed from the thorax and immersed in 10% neutral buffered formalin for 24 h . After fixation of the lung tissue and processing in paraffin wax , sections ( 3–4 µm thick ) were cut longitudinally through the left and right lung so as to include all lobes . Sections were stained with hematoxylin and eosin ( H&E ) for assessment of general histopathology . BALF inflammatory cells were exposed to the chemiluminescent probe , L-O12 ( 100 µM; Wako laboratories , Japan ) in the absence or presence of the PKC and NADPH oxidase activator , phorbol dibutyrate ( 1 µM; Sigma ) and dispensed into 96 well white opti-plates for luminescence reading with the TopCount ( Packard ) . Photon emission was recorded from each well every 2 min and averaged over 45min . Individual data points for each group were derived from the average of 3 replicates . In some cases , cells were incubated with superoxide dismutase ( SOD; 600U/ml ) to inactivate superoxide and to verify that the L-O12 chemiluminescence signal was due to superoxide . Lung sections from WT and Nox2−/y mice infected with X-31 were deparaffinised and fixed in acetone for 15 min . Tissues were then washed in 0 . 01 M phosphate buffered saline ( PBS , pH 7 . 4; 3×10 min ) before incubation in a Mouse on Mouse Ig blocking reagent ( Vector Laboratories ) for 1 h to reduce non-specific binding . Tissue mounted sections were incubated in either mouse monoclonal anti-3-nitrotyrosine ( 1∶50 , AbCAM ) or rabbit polyclonal anti-cleaved caspase 3 antibody ( 1∶250 , AbCAM ) overnight in a humid box . The following day , tissues were washed in 0 . 01 M PBS ( 3×10 min ) to remove any excess antibody , and incubated in a biotinylated anti-mouse IgG reagent for 10 min for 3-nitrotyrosine studies or a goat anti-rabbit Alexa fluor 488 ( Invitrogen; 1∶500 ) secondary antibody for caspase 3 . Lung sections were then washed in 0 . 01 M PBS ( 3×10 min ) and Fluorescein Avidin DCS ( Vector Laboratories ) was applied for 5 min . Sections were washed in 0 . 01 M PBS ( 3×10 min ) and cover slipped . Slides were viewed and photographed on an Olympus fluorescence microscope . Researchers were blinded throughout the experiment and all the appropriate primary and secondary controls were performed . Lungs from influenza virus-infected mice were removed , weighed and homogenised in 2 ml of RPMI medium 1640 containing 24 µg/ml gentamycin and 100 units/ml penicillin/streptomycin . Viral titres ( PFU/ml ) were determined by plaque assay on Madin-Darby Canine Kidney ( MDCK ) cell monolayers as previously published [27] . NO levels in BALF were determined by quantifying its product , nitrite , using the Griess reaction kit according to the manufacturer's instructions ( Molecular Probes ) . Nitrite levels were determined from 150 µl of BALF , which was obtained from WT and from either Nox2−/y or apocynin ( 2 . 5 mg/kg/day ) treated mice killed Day 3 post X-31 or PR8 infection . Whole lungs were perfused free of blood via right ventricular perfusion with 10 ml of pre-warmed saline , rapidly excised en bloc , blotted and snap frozen in liquid nitrogen . Total RNA was extracted from 15 mg of whole lung tissue pooled from 5 mice per treatment group using RNeasy kits ( Qiagen ) , reverse transcription with SuperScript III ( Invitrogen ) and triplicate real time PCR reactions with Applied Biosystems pre-developed assay reagents and 18S rRNA internal control were done as previously described [25] , [26] . The numbers of BALF and spleen influenza-specific CD8+DbNP366+ and DbPA224+ T cells was assessed using tetramer and intracellular cytokine staining as we have previously described . Splenocyte suspensions were initially depleted of B cells by panning on 150-mm petri dishes coated with goat anti-mouse IgG/IgM ( Jackson ImmunoResearch , CA , USA ) for 1 h at 37°C . BALF was placed on plastic for 1 h at 37°C to remove macrophage populations . Enriched CD8+ lymphocyte populations from the spleen and BALF were then stained with fluorescently labelled tetrameric complexes directed against two immunodominant influenza-specific CD8+ T cells epitopes ( DbNP366–372 or DbPA224–232 ) to determine the numbers of the responding population . In addition , enriched CD8+ T cells were incubated for 5 h in 96-well round bottom plates with 1 mM influenza NP366–372 or PA224–232 peptide in the presence of Brefeldin and IL-2 and then fixed and stained for the presence of CD8α , IFN-γ , TNF-α and IL-2 as previously described [28] . Data was acquired on a BD FACS Calibur ( Becton Dickinson , USA ) and analysed using Cell Quest Pro software . As data were normally distributed , they are presented as grouped data expressed as mean±standard deviation of the mean ( SD ) ; n represents the number of mice . Differences in BALF cell types and whole lung mRNA expression were determined by analysis of variance ( ANOVA ) followed by Dunnett post hoc test for multiple comparisons , where appropriate . In some cases , Student's unpaired t-test was used to determine if there were significant differences between means of pairs . All statistical analyses were performed using GraphPad Prism for Windows ( Version 5 . 0 ) . In all cases , probability levels less than 0 . 05 ( *P<0 . 05 ) were taken to indicate statistical significance . | Influenza A virus pandemics are imminent and with emerging anti-viral resistance highlight an ongoing , urgent need for novel generic pharmacological strategies . Ideally these strategies should reduce both viral replication and lung inflammation , irrespective of the infecting strain by modulating the host immune response . An important paradigm strongly suggests that the lung damage arising from not only influenza A viruses but other pathogens including , but not restricted to , SARS , parainfluenza viruses , human respiratory syncytial virus and Streptococcus pneumoniae consists of an excessive host response characterised by a rapid , influx of inflammatory cells into the lungs leading to excessive reactive oxygen species ( ROS ) production . Our study demonstrates that the primary enzymatic source of inflammatory cell ROS , Nox2-containing NADPH oxidase , promotes airways inflammation to low and high pathogenicity influenza A virus infection and impedes with the host's ability to clear the virus . Thus , Nox2 inhibitors could be considered individually or in combination with current antiviral strategies for control of future influenza A virus pandemics . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [
"infectious",
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] | 2011 | Inhibition of Nox2 Oxidase Activity Ameliorates Influenza A Virus-Induced Lung Inflammation |
The zebrafish is a powerful experimental system for uncovering gene function in vertebrate organisms . Nevertheless , studies in the zebrafish have been limited by the approaches available for eliminating gene function . Here we present simple and efficient methods for inducing , detecting , and recovering mutations at virtually any locus in the zebrafish . Briefly , double-strand DNA breaks are induced at a locus of interest by synthetic nucleases , called TALENs . Subsequent host repair of the DNA lesions leads to the generation of insertion and deletion mutations at the targeted locus . To detect the induced DNA sequence alterations at targeted loci , genomes are examined using High Resolution Melt Analysis , an efficient and sensitive method for detecting the presence of newly arising sequence polymorphisms . As the DNA binding specificity of a TALEN is determined by a custom designed array of DNA recognition modules , each of which interacts with a single target nucleotide , TALENs with very high target sequence specificities can be easily generated . Using freely accessible reagents and Web-based software , and a very simple cloning strategy , a TALEN that uniquely recognizes a specific pre-determined locus in the zebrafish genome can be generated within days . Here we develop and test the activity of four TALENs directed at different target genes . Using the experimental approach described here , every embryo injected with RNA encoding a TALEN will acquire targeted mutations . Multiple independently arising mutations are produced in each growing embryo , and up to 50% of the host genomes may acquire a targeted mutation . Upon reaching adulthood , approximately 90% of these animals transmit targeted mutations to their progeny . Results presented here indicate the TALENs are highly sequence-specific and produce minimal off-target effects . In all , it takes about two weeks to create a target-specific TALEN and generate growing embryos that harbor an array of germ line mutations at a pre-specified locus .
The zebrafish has emerged as a leading model organism for the study of vertebrate biology , because of the remarkable cellular resolution with which the embryo can be studied , the ease of assaying its development and physiology in the laboratory , and its amenability to genetic analyses . Forward genetic screens have been used to discover genes that contribute to tissue specification and morphogenesis , cell biology processes including growth regulation and genome maintenance , specificity of neural wiring , metabolism , behavior , and other aspects of the life cycle [1] , [2] , [3] , [4] , [5] , [6] , [7] , [8] . Reverse genetics approaches have been used to uncover the biological processes controlled by genes of interest , and thus the zebrafish is being used increasingly to discover the immediate cellular and molecular functions of genes identified by virtue of their association with disease processes [9] , [10] , [11] . The methods developed here are aimed at improving and simplifying reverse genetics approaches in the zebrafish . Several methods exist for perturbing the function of selected genes in the zebrafish , but until recently none reliably and efficiently eliminated the function of any specified gene [5] , [12] . Gene function can be attenuated in the embryo with antisense morpholino oligonucleotides ( MOs ) [13] , [14] , but the rules for designing effective antisense oligonucleotides have not been perfected , the MOs themselves frequently have unintended off-target effects on development , and even when effective , MOs can only disrupt gene expression transiently [5] , [15] . Therefore methods to isolate bona fide mutations in pre-selected genes continue to be pursued . Genome-screening methods have been used to identify and recover locus-specific mutations following random mutagenesis [16] , [17] , but although these methods are effective , they are highly labor-intensive and not very efficient . In recent years the development of zinc finger nuclease ( ZFN ) technology portended the ability to induce mutations in any locus of any genome [18] , [19] , [20] . In this approach a double strand break ( DSB ) is induced at a unique site in the genome with a synthetic nuclease and host machinery repairs the chromosome break via the error-prone Non-Homologous End-Joining ( NHEJ ) pathway . Repair of such lesions often produces small insertions and/or deletions ( indels ) centered at the site of the DSB . Recent studies demonstrated that locus-specific mutations could be readily induced in zebrafish using ZFNs , and it appeared this approach might be applied to any locus [21] , [22] , [23] . However severe limitations still constrain the ability to generate zinc finger domains that can bind specifically to any desired genomic target sequence . Thus although ZFN-mediated targeted mutagenesis appeared promising , widespread implementation of the strategy requires a new approach for generating nucleases that exhibit very high sequence specificity . The recent discovery of the Transcription Activator-Like Effector ( TALE ) proteins produced by plant pathogenic bacteria of the genus Xanthomonas has uncovered a new type of DNA-binding motif that can be used to create peptides that bind DNA with high affinity and sequence selectivity [24] , [25] , [26] , [27] . TALE DNA binding is mediated by arrays of 33–35 amino acid DNA recognition motifs , each of which interacts with a single target nucleotide . As illuminated by X-ray crystallographic analysis of a TALE-DNA complex [28] , [29] , the process of DNA recognition occurs in a remarkably modular fashion , so that adjacent recognition motifs interact with adjacent nucleotides in a manner that does not appear to be affected by the presence of neighboring motifs . Nucleotide discrimination is determined by a pair of adjacent amino acid residues within the motif , called the Repeat Variable Di-Residue ( RVD ) ; hence the recognition motif is referred to as the RVD repeat module . Combining the simple modular TALE recognition cipher with a few empirically based guidelines , web-based algorithms have been established for designing RVD repeat-based DNA binding peptides that can bind genomic target sequences of interest [30] . Fusion of TALE-based DNA binding domains with the sequence-non-specific nuclease domain derived from the type IIS FokI restriction enzyme has been used to create sequence-specific nucleases , called TALENs [27] , [31] . Preliminary studies have demonstrated the promise of TALENs for inducing locus-specific mutations in the zebrafish [12] , [32] . Here we describe very simple methods , using reagents that are available for research without restriction , for generating TALENs that are extremely effective for inducing mutations at any locus in the zebrafish . The TALE-based DNA binding domains are generated quickly using a strategy that extracts sequences encoding RVD repeat modules from a library of plasmids and joins them in an ordered sequence using the Golden Gate cloning system [30] . We also establish easy and rapid methods for detecting the mutations induced by TALENs . Using the methods presented here , every embryo injected with mRNA encoding a TALEN will acquire mutations at the targeted locus in somatic tissues and approximately 90% of the animals that reach adulthood transmit newly induced specific locus mutations through their germ lines . In all , it takes about two weeks to create target-specific TALENs and generate growing embryos that harbor an array of germ line mutations at a pre-specified locus .
The TALENs we generate function as sequence-specific heterodimer endonucleases . Each monomer component is a chimeric protein composed of the FokI nuclease domain fused with a synthetic DNA binding domain consisting of an array of RVD repeat modules . Nuclease activity requires the binding of the two components on opposing strands of the duplex at a small interval distance . Although the FokI enzyme normally functions as a homodimer , we utilize mutant derivatives of the nuclease domain [23] so that the TALENs function as obligate heterodimers , thus demanding that both ‘Left’ and ‘Right’ monomers simultaneously recognize their cognate binding sites to achieve nuclease activity . The RVD repeat assembly reagents generated by Cermak et al . [30] allow construction of sequences encoding DNA binding domains composed of up to 31 recognition motifs . However , generally we design monomer TALEN components that each contain 16–20 RVD repeats and that , including the DNA interaction function of the N-terminal portion of the TALEN [28] , [29] , bind a half-target site of approximately 17–21 nt present on opposing strands and spaced apart by 14–17 bp ( target site configuration ≥17 bp – N14–17 – ≥17 bp ) . Applying parameters described in Materials and Methods to the TALEN Targeter program ( https://boglab . plp . iastate . edu/node/add/talen ) , TALENs can be designed that recognize only a single target site in the zebrafish genome . Such unique target sites can be identified in many exons , as well as introns and promoter sequences ( see Discussion ) . The gene sequences targeted and the RVD repeat arrays of the TALENs used in this study are presented in Figure S1 . To generate a plasmid encoding a Left or Right monomer component consisting of n RVD repeats ( see Materials and Methods for details ) , an initial Golden Gate cloning step is used to assemble two arrays , encoding repeats 1–10 and repeats 11 – n-1 , as in [30] . The final expression plasmid encoding an entire TALEN monomer is generated in a second Golden Gate cloning assembly , which brings together the two partial arrays , sequences encoding the nth motif , and a modified CS2+ backbone vector , pCS2TAL3RR or pCS2TAL3DD ( Figure S2; see Materials and Methods ) . Assembly results in a fusion gene that encodes: vector-provided N-terminal TALE-derived sequences , an RVD repeat array , C-terminal TALE-derived sequences , and a modified nuclease domain . TALENs can be expressed directly from the CMV promoter resident in these CS2+ vectors . However , for the zebrafish experiments described below , mRNA encoding Left or Right monomer components were generated individually by in vitro transcription of linearized plasmids and equal amounts of each mRNA were co-injected into embryos at the 1 cell stage . To estimate the efficiency with which targeted mutations can be induced , we measured the ability of TALENs to induce somatic tissue mutations in the golden ( gol ) gene , which governs pigmentation in the embryo and adult without compromising viability [33] , [34] . Mutations at gol are recessive: embryos with at least one WT allele are darkly pigmented at 2 days postfertilization ( dpf ) , whereas homozygous gol mutants appear pigmentless at this stage . To maximize the chance of inducing complete loss-of-function alleles , we chose to develop a TALEN that would generate DSBs within coding sequences residing toward the 5′ end of the gol locus . Using criteria described in Materials and Methods , a potential TALEN target site was identified in the second exon of gol and the gol-ex2 TALEN was designed ( Figure 1A , Figure S1 ) . As imprecise repair of targeted DSBs is likely to produce recessive loss-of-function mutations at gol , we injected embryos heterozygous for the golb1 null mutation [33] , [34] with gol-ex2 TALEN mRNA and measured the appearance of golb1/* mutant pigmentless cells in the Retinal Pigmented Epithelium ( RPE ) ( Figure 1 ) . At 2 dpf the RPE is a monolayer of approximately 550 pigmented cells that envelops each eye , and the presence of even small clones of pigmentless tissue can be detected easily [35] . Whereas it is extremely rare for pigmentless cells to be found in the RPEs of control golb1/+ heterozygous embryos [36] , all but one of 20 TALEN-injected golb1/+ embryos had large patches of gol mutant cells ( Figure 1B–1F , Table 1 ) . The TALEN-injected embryos had multiple patches of mutant tissue , indicating they were genetically mosaic . On average ≥50% of the RPE cells in TALEN RNA-injected embryos were golden ( Figure 1C–1F ) , indicating the majority of genomes in the embryos acquired TALEN-induced mutations . Three experiments demonstrated the new mutations were indeed induced by the gol-ex2 TALEN . First , the gol-ex2 TALEN could induce pigmentless tissue in the RPEs of gol+/+ embryos ( Figure 1G–1K ) , indicating the induction of mutant tissue did not require a pre-existing gol mutant allele . Mutant cells were observed in almost 100% of these injected WT embryos ( Table 1 ) and occasionally even wholly gol embryos were observed ( Figure 1L , 1M; see Table S2 for frequencies ) , highlighting the efficiency with which these TALENs can induce mutations in both genomes of a cell . Second , as discussed below , analysis of exon 2 sequences amplified from gol-ex2 TALEN RNA-injected embryos revealed a diverse set of indel mutations were induced , typical of those produced by NHEJ-mediated repair of DSBs . Third , gol mutant alleles were transmitted to the F1 offspring of TALEN-injected WT embryos ( see below ) . We conclude the gol-ex2 TALEN is extremely effective at inducing mutations at gol . Whereas newly induced mutations at golden are simple to detect , TALEN-induced mutations at most loci are unlikely to present a phenotype that can be scored in individual somatic cells . As the repair of DSBs can lead to an assortment of indels centered at the TALEN target site , it is desirable to detect induced mutations with a method that can detect any DNA change arising at a selected target site . Furthermore , as DSBs are induced only following translation of injected TALEN mRNAs , an individual embryo may acquire several independent mutations , each of which may arise in a mosaic fashion during development . Therefore a sensitive method is required that can detect mixtures of TALEN-induced DNA polymorphisms at a targeted locus present among the genomes of a single embryo . We find High Resolution Melt Analysis ( HRMA ) is a simple , rapid , and sensitive method for detecting TALEN-induced somatic mutations . HRMA has been used in the past to detect known sequence polymorphisms in the zebrafish [37] , but it is also useful for discovering polymorphisms of unknown sequence that lie in a small , defined region of the genome . We developed standard conditions for detecting sequence alterations resulting from TALEN activity at targeted loci ( Materials and Methods ) . To detect the occurrence of a DNA polymorphism at a particular locus , short PCR amplicons ( 90–120 bp ) that include the region of interest are generated from a genomic DNA ( gDNA ) sample , subjected to denaturation and rapid renaturation , and the thermostability of the population of renatured amplicons is analyzed ( Materials and Methods ) . If TALEN-induced polymorphisms are present in the template gDNA , heteroduplex as well as different homoduplex molecules will be formed ( Figure 2A ) . The presence of multiple forms of duplex molecules is detected by HRMA , which records the profile of temperature-dependent denaturation and detects whether duplex melting acts as a single species or more than one species . For example , three prominent duplex types with distinct melting temperatures ( Tm's ) are evident in the analysis of renatured lef1 amplicons generated from an embryo heterozygous for an intragenic 18 bp deletion in lef1 ( Figure 2B ) . We determined the sensitivity of HRMA for detecting the presence of a mutant genome mixed among a population of WT genomes using standard conditions of analysis ( Materials and Methods ) . gDNA prepared from an embryo heterozygous for the lef1Δ18 mutation was mixed with differing amounts of WT gDNA , and the ability of HRMA to detect the mutant allele was determined . As the mutant genome is present as a decreasing fraction of all template genomes , the relative abundance among amplicons of homoduplex mutant and heteroduplex populations changes , but the presence of mutant genomes can be detected unambiguously even when mutant genomes represent 1/70th of the total mix ( Figure 2C ) . Figure S3 shows a 4 bp insertion mutation in the lef1 gene can be detected with similar sensitivity . In genetically mosaic embryos , when multiple mutant alleles are present as minor populations within a mixture of genome , the melt curves become more complex , but deflections away from the WT profile are additive and therefore simple to detect ( see examples in Figure 3 ) . Given our findings ( presented below ) that the majority of mutations induced using the methods described here consist of alterations of >4 bp , we estimate our standard conditions of analysis can routinely detect one mutant genome present among 50 WT genomes . To test the efficacy of our methods for generating and detecting TALEN-induced somatic mutations at any locus , we injected 1 cell embryos with mRNAs encoding the gol-ex2 TALEN or TALENs designed to recognize and cleave sequences in exon 3 of tbx6 , exon 5 of ryr3 , or exon 6 of ryr1a ( Figure S1 ) . Under standard conditions of injection with 100 pg total TALEN RNA , approximately 95% of the embryos developed normally ( Table S3 ) . gDNA was prepared from individual 1–2 dpf TALEN-injected or control embryos and analyzed by HRMA for the presence of DNA sequence variants at the targeted loci using primer pairs listed in Table S1 . Nearly all TALEN RNA-injected embryos had targeted mutations , including the gol-ex2 TALEN RNA-injected embryos that did not have gol mutant cells in the RPE ( Table 2 , Figure 3 ) . Sequence analysis of PCR amplicons covering the targeted loci ( Figure 3 ) indicated the induction of a spectrum of indel mutations , consistent with what is expected from NHEJ repair . Analysis of loci amplified from 9 embryos targeted at tbx6 , ryr3 , or ryr1a indicated approximately half the genomes ( 26/52 ) of TALEN-injected embryos harbored targeted mutations . As gol does not encode an essential function , the induction of gol mutant cells is not detrimental to development . However for other targeted genes it may be advantageous to avoid inducing bi-allelic mutations in many cells of the embryo . The frequency with which mutant cells are induced is dependent on the amount of TALEN RNA that is injected ( Table 1 , Table S2 ) , so the frequency of cells harboring bi-allelic mutations can be adjusted . As shown in Figure 4 , HRMA can be used to determine the dose-dependent induction of mutations that cannot be easily measured in somatic tissues . The amount of TALEN RNA delivered to embryos affects both the fraction of embryos that harbor detectable mutations as well as the average abundance of mutant genomes present in any individual injected embryo . To determine if induced mutations detected in 1–2 dpf embryos enter the germ line , we raised TALEN-injected ( G0 ) embryos to adulthood and analyzed the transmission of mutations to progeny . Individual adult G0 animals were mated with WT partners and gDNA isolated from individual F1 embryos was analyzed by HRMA . Targeted germ line mutations were transmitted by 51 of the 57 G0 animals ( approximately 90% ) that had been exposed to TALENs directed at the golden , tbx6 , ryr3 , or ryr1a genes ( complete transmission data is provided in Tables S4 , S5 , S6 , S7; data is summarized in Table 3 ) . The fraction of G0s carrying germ line mutations induced by each TALEN ranged from 77% to 100% . Analysis of the sequence alterations inherited by F1 embryos revealed the range of induced indel mutations among the germ line transmitted mutations mimicked those that had been observed in embryos ( Figure 5A ) . The majority of TALEN-induced mutations identified here in injected G0 , 1–2 dpf F1 , or adult F1 individuals were sequence changes of 3–20 bp ( Figure 3 , Figure 5 , Table S8 ) . Larger indels were identified , but rarely . Most if not all mutations identified among the 1 dpf F1 offspring were viable in the heterozygous state , as adult F1s descended from G0 founders harbored a distribution of mutations similar to that found among the F1 embryos ( Table S8 ) . To date all the F1 fish heterozygous for TALEN-induced mutations at tbx6 , ryr1a , and ryr3 that have been bred ( n = 16 ) have transmitted their mutations to the F2 generation . We have no evidence of mutations in the F1 generation that could not be further propagated . Most G0 animals transmitted multiple mutant alleles and most mutations were transmitted by significantly less than 50% of the gametes ( Table 3; Tables S4 , S5 , S6 , S7 , S8 ) , indicating the germ lines of G0 founders were mosaic . HRMA analysis of heterozygous F1 offspring was used to distinguish transmitted mutant alleles , and sibling individuals that appeared to carry a common DNA sequence alteration were grouped based on common melt curve shapes . As illustrated in Figure 5B and 5C , individual sibling F1 embryos descended from a single mutagenized G0 founder could harbor different alleles , indicated by the multiple distinct HRMA melting profiles of amplicons derived from sibling F1 offspring . On average , two new alleles were recovered from the germ lines of each mutagenized G0 founder ( Table 3 ) . The finding that the germ lines of most G0 founders were genetically mosaic is consistent with the interpretation that TALENs induce mutations independently in different cells of the embryo and mutations accrue as the embryo develops . Indeed we found that following injection of 1 cell stage embryos with gol-ex2 TALEN mRNAs , the fraction of embryos with detectable levels of targeted mutations increased with developmental time ( Figure S4 ) . Whereas 100% of injected embryos had mutations at 6 or 24 hours postfertilization ( hpf ) , only a fraction of the 3 hpf embryos had detectable mutations , and among the early stage embryos , HRMA genotype analyses indicated a relatively low abundance of mutant genomes ( Figure S4 ) . Altogether these data indicate numerous targeted indel mutations can be recovered routinely from a small set of adults arising from TALEN mRNA-injected embryos . The very high frequency with which mutations were induced raised the possibility that the TALENs were simply mutagenic in a sequence-non-specific manner . However , in contrast with published reports [21] , [22] , [23] and our own experience with ZFNs ( data not shown ) , TALENs exhibit very low toxicity . For example , although injection of only 4 pg total RNA encoding any of the TALENs used here was sufficient to induce mutations in the majority of embryos ( Figure 4 and data not shown ) , approximately 95% of the embryos developed normally even after being injected with 100 pg total TALEN RNA ( Table S3 ) . These observations are consistent with the interpretation that random chromosome breaks are generally not produced by the TALENs . As one test of the specificity of the TALENs used here , we generated TALENs to recognize a specific target sequence and measured the induction of mutations at very closely related sequences present in homologues of the targeted gene . The ryr genes encode related Ryanodine Receptor intracellular calcium release channels . We designed TALENs targeted to the ryr3 or ryr1a genes and measured the induction of mutations in the homologous sequences present in the ryr1a , ryr1b , or ryr3 genes . The ryr3-ex5 TALEN recognizes a Left half-site of 19 nt and Right half-site of 18 nt ( Figure S1 ) . As illustrated in Figure 6A , the homologous sites in the ryr1a and ryr1b genes present a 3 base mismatch for the Left monomer and 4 base mismatch for the Right monomer of the ryr3-ex5 TALEN . Although HRMA indicated every embryo injected with ryr3-ex5 TALEN had induced mutations in ryr3 , the embryos did not have detectable levels of mutations at the ryr1a or ryr1b loci ( Figure 6B ) . In a second experiment we analyzed the off-target activity of the ryr1a-ex6 TALEN , which recognizes a Left half-site of 19 nt and Right half-site of 17 nt . As shown in Figure 6C , the homologous site in ryr3 differs at 3 positions in both the Left and the Right half-sites , but the homologous site in ryr1b differs only at 2 positions in the Left half-site and presents a perfect match with the Right half-site . HRMA analysis revealed the ryr1a-ex6 TALEN induced targeted mutations at the cognate locus in 100% of the injected embryos but failed to induce detectable mutations at the homologous ryr3 target ( Figure 6D ) . In contrast , the ryr1a-ex6 TALEN did induce mutations in ryr1b gene of all of the injected embryos ( Figure 6D ) . These results indicate the TALENs display high but not perfect sequence specificity under the conditions described here .
Sequence-specific TALENs that can target almost any zebrafish gene can be generated simply and rapidly using the target site design parameters , the reagents , and the cloning strategy described here . The TALENs generated using these reagents are very effective at inducing DSBs whose repair often produces mutations at the target sites . Using our standard methods to generate mutations at four different loci , we found virtually every embryo injected with TALEN mRNA harbored targeted mutations . As demonstrated with the gol-ex2 TALEN , in some cases over half the genomes in a TALEN RNA-injected embryo may acquire mutations at targeted loci . Almost all treated animals acquire new germ line mutations , which are subsequently inherited in a stable Mendelian fashion . We have found many additional sites in the genome can be targeted with the ease and efficiency of the four genes described here: during the course of the current study we induced mutations at 19 of the 21 sites we attempted to target ( 90% ) . The genes that have been successfully targeted are present at many different locations in the genomes ( Figure S1 ) including the gol locus , which is close to a telomere [33] . Further , as shown by the induction of gol mutations in early stage embryos ( Figure S4 ) , mutations can be induced in genes that are not being expressed . Given the modular mode of RVD repeat module binding , the flexibility in the design and the length of repeat arrays that can be generated , and the relatively few guidelines that restrict TALEN design , it appears TALENs can be used to induce loss-of-function mutations in almost every zebrafish gene . The system we present here for constructing TALENs that are effective in the zebrafish is easy to implement: 1 ) it employs a very simple and rapid cloning strategy , using the Golden Gate cloning method system to assemble RVD repeats; 2 ) the RVD repeats are available in plasmids that can be used directly for Golden Gate cloning without need to PCR amplify or otherwise alter the repeat sequences; 3 ) the cloning strategy leads to accurate constructions of arrays ( we typically analyze only 2 transformants from each cloning step ) ; 4 ) the TALENs function as obligate heterodimers , increasing specificity of target sites recognized by the TALENs; and 5 ) all reagents are readily available through Addgene . Although the studies presented here focus on induction of mutations in the zebrafish , our preliminary results indicate that TALENs assembled using the reagents described here are also effective at inducing mutations in Drosophila and mammalian cell culture systems . We developed High Resolution Melt Analysis as a principal method for measuring the induction of mutations with TALENs in zebrafish embryos . HRMA can detect almost any newly arising polymorphism at a pre-specified region of the genome , and thus it allows detection of the large variety of sequence changes that may be produced by NHEJ repair . As HRMA can detect sequence alterations arising at any target site , this method of mutation detection does not bias or affect the choice of a target site and thus is an improvement over previous assays that detected loss of a restriction site . We show HRMA is an extremely sensitive method for detecting mutant genomes among a mixed population of genomes . Hence it is particularly useful for detecting TALEN-induced mutations , any one of which is likely to be present in only a subset of the cells of an embryo injected with TALEN RNAs . Furthermore , because HRMA is sensitive to the total fraction of mutant genomes in a mixture , it is particularly well-suited for detecting the heterogeneous set of mutations that is likely to arise in a single embryo . Finally , HRMA is simple to apply and does not involve manipulation of samples following PCR amplification . The entire procedure for generating amplicons and analyzing the thermostability of the heteroduplexes can be performed in less than 2 hours . We consider several practical issues concerning implementation of the methods presented here to induce mutations in the zebrafish: 1 ) the kinds of mutations generated and implications for target design considerations; 2 ) the frequency with which potential TALEN target sites can be identified; 3 ) the possibility that TALEN-injected embryos express mutant phenotypes; and 4 ) the ability of TALENs to induce unintended mutations . Most of the mutations we have recovered from G0 germ lines are indels that affect ≤20 bp stretches of genomic sequence . Many of these sequence changes cause frameshift mutations . If TALENs are used with the goal of inducing null mutations in a targeted gene , it is best to target a region of the gene in which a frameshift mutation is likely to produce a protein product that lacks important functional elements . We routinely target the second or third exon of a gene . Among 40 genes for which we have designed TALENs , we have always been able to identify targets in the second and/or third exons of the genes using the design parameters presented in the Materials and Methods . Among searches of 116 stretches of ( mostly coding ) sequences with an average size 238 bp , we identified at least one suitable target in 77% of the sequences ( the average size of the sequences without a best-fit target was 158 bp ) . Using the guidelines we suggest , optimal TALEN target sites can be identified for most genes . The parameters that govern the specificity and activity of TALENs are not completely understood . It is clear from our studies and those of others that the Left and Right TALEN monomer components can bind at various distances from each other and still cooperate effectively to accomplish target site cleavage [27] . The spacer length for achieving optimal activity has not been determined , and we can only say the 14–17 bp spacer length we routinely use in the design of TALEN target sites consistently allows for effective target cleavage in the zebrafish . Importantly , the extreme minimum or maximum spacer distance at which some cleavage activity may occur has yet to be determined in vivo , an uncertainty that affects the identification of unintended sites in the genome that may be susceptible to TALEN activity . As expected from previous work on the specificity and selectivity of TALE binding [25] , [27] , the TALENs function as highly sequence-specific nucleases . Given that we identify potential TALEN target sites on the basis of a reference genome , and as the common laboratory WT strains of zebrafish harbor polymorphisms , we have found it prudent to sequence genomic regions of the zebrafish used in any series of experiments to verify the existence of a presumed target site in the embryos that are injected with TALEN RNA . Furthermore , it should be noted HRMA can detect pre-existing polymorphisms , and thus we choose to inject embryos shown to be free of polymorphisms near the TALEN target site . We routinely verify the in vivo activity of a TALEN before growing injected G0 embryos to adulthood . Typically we inject 1 cell stage embryos with different amounts ( 4 pg , 20 pg , 100 pg total RNA ) of a 1∶1 mixture of Left TALEN and Right TALEN RNAs and measure the presence of mutations in individual 1 dpf embryos . In our experience to date , most animals that have evidence of mutations at 1 dpf will grow to become adults that transmit mutations through the germ line . As demonstrated with the gol-ex2 TALENs , cells with two mutant alleles can be induced following injection of 1 cell embryos with TALEN RNA . Mutations are induced in a mosaic fashion and using the conditions described here , it is rare that TALEN-injected embryos exhibit strong mutant phenotypes . It may be possible to augment the activity of the TALENs to uncover mutant phenotypes in G0 animals . In addition , it is worth considering the possibility that some mutations cannot survive in the germ line in a homozygous state . As a result , it may be desirable to raise G0 animals with sub-maximal levels of mutations . As demonstrated in our studies , the frequency of TALEN-induced mutations is a function of the amount of TALENs introduced into an animal . Thus , it is possible to raise animals that carry different mutation loads . Finally , although we have not made extensive measurements of the frequency with which unintended sequences are recognized and cleaved by TALENs in these experiments , our studies indicate off-target mutations can occur but they are sufficiently infrequent so that they are unlikely to confound analysis of targeted gene function . We found TALENs failed to cleave potential target sites that differed at about 6 positions of a 36 nt binding target , but that targets differing at only 2 positions could be effectively cleaved . The effects of off-target mutations can be minimized by studying hetero-allelic combinations of targeted mutations derived from independently mutagenized G0 founders . In sum , the current conditions for TALEN-induced mutagenesis appear sufficient for uncovering the function of almost any selected gene in the zebrafish . HRMA sensitively detects polymorphisms . To minimize detection of polymorphisms present in the backgrounds of WT fish , we typically amplify only a small region of the genome bordering the TALEN target site and analyze that for newly induced mutations . As a result of using small amplicons , we will be unable to detect some TALEN-induced mutations that delete primer-binding sites . As we only rarely observed deletions of >30 bp in the present studies , we believe the majority of TALEN-induced mutations can be identified with the methods described here . It is also possible to detect induced mutations by HRMA using larger amplicons . Finally , although the HRMA studies presented here were performed with a LightScanner ( Idaho Technology ) , we have obtained identical results with similar sensitivity using an Eco Real-Time PCR System ( Illumina ) . Additional instruments initially designed for qPCR analysis are capable of performing HRMA and have been used successfully to detect TALEN-induced mutations ( Tatjana Piotrowski and Steven Leach , personal communication ) .
All experiments were performed in accordance with , and under the supervision of , the Institutional Animal Care and Use Committee ( IACUC ) of the University of Utah , which is fully accredited by the AAALAC . Wild type zebrafish Danio rerio were of the Tuebingen strain . Zebrafish were maintained under standard conditions and embryos were generated , cultured and staged as described [38] , [39] . Exon sequences identified from the Zv9 Zebrafish Genome Assembly were scanned for potential TALEN target sites , which were identified using the TALEN Targeter program at https://boglab . plp . iastate . edu/node/add/talen . The following parameters were used: 1 ) spacer length: 14–17; 2 ) repeat array length of 16–21; 3 ) apply all additional options that restrict target choice . Preference was given to target sites: 1 ) close to the 5′ terminus of the gene to maximize chances of inducing premature translation stop mutations and 2 ) not in the first exon in case alternative promoters exist . Target sequences that are unique in the genome should be chosen following BLAST analysis to determine that highly similar Left and Right binding sites in close proximity did not exist at other sites in the genome ( see Figure 6 ) . New final backbone vectors used to construct and express genes encoding Left and Right TALEN monomer components were generated here . The new backbone plasmids , pCS2TAL3DD and pCS2TAL3RR , were modified from pCS2-Flag-TTGZFP-FokI-DD and pCS2-HA-GAAZFP-FokI-RR plasmids [23] . First , to render the plasmids suitable for Golden Gate cloning , the single Esp3I restriction enzyme site ( in the FokI nuclease domain ) of each plasmid was changed from GAGACG to GCGCCG , a mutation that did not alter coding . Second , sequences encoding the ZFP domain were removed following KpnI and BamHI digestion , leaving a backbone vector with sequences 5′ to the KpnI site that provided a 5′UTR , start codon , NLS , and Flag or HA tags and sequences 3′ to the BamHI site that provided a heterodimeric FokI domain , translation termination codon , and SV40 polyA signal . Third , sequences derived from the tal1c gene and ready to accept an RVD repeat array by Golden Gate cloning were placed in frame at the KpnI and BamHI sites . The tal1c sequences were obtained from pTAL3 ( sequence positions 1214–2210 , www . addgene . org ) using primers that added a KpnI site at the 5′ end ( TAL3N153F-GTAGGATCCGGTACCGTGGATCTACGCACGCTCGG ) and a BamHI site at the 3′ end ( TAL3C63R-GTGGGATCCGGCAACGCGATGGGACG ) of the amplified pTAL3 sequence . The amplified sequence encoded only a central portion of TAL1c , in which lacZ sequence had been substituted for the RVD repeat array . Cloning into the KpnI/BamHI sites of the backbone vector transferred sequence that provided 136 aa of TALE immediately N′-terminal to the RVD repeat array , an Esp3I restriction enzyme site , lacZ sequences , an Esp3I restriction enzyme site , and 63 aa of TALE immediately C′-terminal to the RVD repeat array . The TALE backbone truncations were designed after TALENs that previously had been shown to function well [27] . Golden Gate cloning of RVD repeat arrays into pCS2TAL3DD or pCS2TAL3RR results in replacement of the lacZ sequences with sequences encoding a designed RVD repeat array and yields a gene encoding an intact TALEN monomer . The pCS2TAL3-DD and pCS2TAL3-RR plasmids are available through Addgene ( #37275 and #37276 , respectively ) with complete sequence information accessible at GenBank ( accession numbers JX051360 and JX051361 , respectively ) . The TALEN Golden Gate assembly system described in Cermark et al [30] was used with modifications . RVD repeat arrays were assembled exactly as described [30] . Plasmids providing RVD repeats for Golden Gate cloning are described in [30] and are available through Addgene . Briefly , two rounds of Golden Gate cloning assembly were used to generate a TALEN gene with n RVD repeat modules . First , two arrays were generated , corresponding to repeat modules 1–10 and 11 – n-1 . Resulting vectors that acquired arrays were identified as white transformants on IPTG/X-gal plates . Correct assembly was determined first by the size of repeat array inserts liberated following XbaI and AflII restriction enzyme digestion and then sequencing of plasmids with the correct insert size . Second , the two arrays and sequences encoding the nth motif were transferred into the backbone vectors . RVD repeat array sequences were cloned into pCS2TAL3DD to generate a Left TALEN gene and into pCS2TAL3RR to generate a right TALEN gene . Backbone vectors that acquired arrays were identified as white transformants on IPTG/X-gal plates . Correct assembly was determined first by the size of the insert liberated by SphI and BamHI restriction enzyme digestion and second by sequencing junction regions . 5′-capped mRNA was generated by transcription in vitro of pCS2TAL3DD and pCS2TAL3RR TALEN plasmid templates that had been linearized with NotI ( mMESSAGE mMACHINE SP6 kit , Ambion/Invitrogen ) . Equal amounts of Left and Right TALEN mRNA were injected together into the cytoplasm of 1 cell stage zebrafish embryos . To prepare genomic DNA from embryos , individual 1 or 2 dpf embryos were incubated in 50 ul DNA extraction buffer [10 mM Tris-HCl ( pH 8 . 0 ) , 1 mM EDTA , 50 mM KCl , 0 . 3% Tween-20 , 0 . 3% NP-40] containing 500 ug/ml proteinase K at 55°C , 2 h . The reaction was terminated by incubation at 99°C , 5 min . The average gDNA concentration was roughly 60 ng/ul . To detect TALEN-induced mutations by HRMA , a 90–120 bp amplicon that included the entire genomic target site was generated . Primers flanking the target site were used to amplify the genomic region in a 10 ul PCR reaction containing: 1 ul embryonic gDNA , 1X LightScanner Master Mix ( containing the LC Green Plus dye , Idaho Technology ) , 200 uM each dNTP , and 200 nM each Forward and Reverse primers ( see Table S1 ) . Amplification/duplex formation conditions were: denaturation at 95°C , 3 min; 50 cycles {95°C , 30 s–70°C , 18 s}; denaturation at 95°C , 30 s; renaturation at 25°C , 30 s; 10°C . HRMA data was collected on a LightScanner ( Idaho Technology ) and analyzed using the LightScanner Call-IT Software . | Many genes are being discovered solely on the basis of their association with a trait or disease , or their relatedness to other known genes , but nevertheless the precise biological functions of these genes remain mysterious . We need new tools to discover the immediate molecular , cellular , and developmental functions of genes of interest . Increasingly , the zebrafish is being used as a model organism to discover gene functions that are shared among all vertebrates . In this study we develop new , highly efficient , and very easy to apply methods for generating zebrafish that lack the function of any desired gene . We also introduce sensitive and easy-to-apply methods for detecting newly arising mutations . The approach developed here can also be used to quickly eliminate the function of any chosen gene in other animals or in tissue culture cells . In all , we anticipate the methods described here will be widely applied to study gene function in many different contexts . | [
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] | 2012 | Simple Methods for Generating and Detecting Locus-Specific Mutations Induced with TALENs in the Zebrafish Genome |
Ticks are serious haematophagus arthropod pests and are only second to mosquitoes as vectors of diseases of humans and animals . The salivary glands of the slower feeding hard ticks such as Haemaphysalis longicornis are a rich source of bioactive molecules and are critical to their biologic success , yet distinct molecules that help prolong parasitism on robust mammalian hosts and achieve blood-meals remain unidentified . Here , we report on the molecular and biochemical features and precise functions of a novel Kunitz inhibitor from H . longicornis salivary glands , termed Haemangin , in the modulation of angiogenesis and in persistent blood-feeding . Haemangin was shown to disrupt angiogenesis and wound healing via inhibition of vascular endothelial cell proliferation and induction of apoptosis . Further , this compound potently inactivated trypsin , chymotrypsin , and plasmin , indicating its antiproteolytic potential on angiogenic cascades . Analysis of Haemangin-specific gene expression kinetics at different blood-feeding stages of adult ticks revealed a dramatic up-regulation prior to complete feeding , which appears to be functionally linked to the acquisition of blood-meals . Notably , disruption of Haemangin-specific mRNA by a reverse genetic tool significantly diminished engorgement of adult H . longicornis , while the knock-down ticks failed to impair angiogenesis in vivo . To our knowledge , we have provided the first insights into transcriptional responses of human microvascular endothelial cells to Haemangin . DNA microarray data revealed that Haemangin altered the expression of 3 , 267 genes , including those of angiogenic significance , further substantiating the antiangiogenic function of Haemangin . We establish the vital roles of Haemangin in the hard tick blood-feeding process . Moreover , our results provide novel insights into the blood-feeding strategies that enable hard ticks to persistently feed and ensure full blood-meals through the modulation of angiogenesis and wound healing processes .
Angiogenesis or neovascularization , the formation of new blood vessels from pre-existing ones , is involved in a variety of physiological processes , such as corpus luteum formation , embryonic development , and wound healing [1] , [2] . Also , angiogenesis plays a vital role in the development and progression of various pathological conditions , including rheumatoid arthritis , diabetic retinopathy , and tumor metastasis [3] . The process of angiogenesis involves activation and release of angiogenic factors , release of proteolytic enzymes to degrade extracellular matrix protein ( ECM ) , migration and proliferation of endothelial cells , and microvessel formation [4] . Pericellular proteinases , comprised of membrane-type matrix metalloproteinases ( MT-MMPs ) , serine proteinases ( SPs ) , and membrane-bound aminopeptidases , are known to play key roles in angiogenesis [5] . The proteinase inhibitors of SPs belonging to the Kunitz , Kazal , α-macroglobulin , and serpin families play critical roles in physiological and pathophysiological states such as coagulation , intravascular fibrinolysis , wound healing , angiogenesis , and tumor metastasis [6] , [7] . The best studied serine proteinase inhibitors ( SPIs ) to date in angiogenesis , tumor invasion , and metastasis are the plasminogen activator inhibitor-1 ( PAI-1 ) , PAI-2 [8] , and maspin [9] . Kunitz-type SPIs such as tissue factor pathway inhibitor ( TFPI ) inhibit the proliferation of basic fibroblast growth factor ( bFGF ) -induced endothelial cells ( ECs ) in addition to their inhibitory activity against tissue factor–mediated blood coagulation cascade [10] . Snake venoms contain many unique proteins , including Kunitz-type SPIs [11] . These Kunitz proteins are potent inhibitors of trypsin , chymotrypsin , kallikrein , and plasmin; however , little is known about their physiologic roles in angiogenesis and angiogenesis-dependent diseases such as cancer . Hard ticks are notorious ectoparasites that feed on blood for quite a long period ( e . g . , 10 days or more ) in contrast to fast-feeder soft ticks , which usually feed for an hour [12] . Tick feeding is a complex process and involves severe tissue damage caused by the probing actions of barbed mouthparts and release of salivary secretions to the feeding lesions , leading to host's haemostatic , inflammatory , and immune responses . However , despite the host's armoury of rejection mechanisms , the ticks manage to remain attached and achieve engorgement [12] , [13] . Increasing evidence suggests that success in blood-feeding relies on a pharmacy of chemicals located in the salivary glands ( SGs ) [14] . A recent study has reported that the saliva of the hard tick Ixodes scapularis is a negative modulator of angiogenesis and wound healing [15] , though the specific molecular component ( s ) is yet to be identified . Moreover , the implications of hard-tick-modulated angiogenesis and wound healing in persistent blood-feeding remain unknown . To this end , we have looked for a novel salivary-specific molecule ( s ) of interest in the hard tick Haemaphysalis longicornis . We have selected a full-length cDNA that shows moderate sequence homologies with Kunitz-type proteinase inhibitors from the SG-specific expressed sequence tag ( EST ) library of adult female H . longicornis [16] for its functional analysis . Here , we show that an Escherichia coli–expressed recombinant protein , herein called Haemangin , inhibits trypsin , chymotrypsin , and plasmin . Also , we provide novel evidence that this Haemangin-like modulatory protein is the key to the modulation of angiogenesis and angiogenesis-dependent wound healing during persistent blood-feeding and is vital for hard ticks in achieving host blood-meals .
The composite full-length Haemangin cDNA sequence was 583 nucleotides long with a single open reading frame ( ORF ) of 363 bases . The ORF coded for a protein of 120 amino acids , including a signal peptide of 19 residues ( data not shown ) . The putative mature protein has a molecular mass of 14 , 157 Da and an isoelectric point ( pI ) of 10 . 65 . The deduced protein has three potential N-glycosylation sites . The unique primary structure of the predicted protein consists of 10 cysteines forming 5 disulfide bonds , a lysine- and histidine-rich carboxy terminus , and a single Kunitz-like inhibitory domain that belongs to bovine pancreatic trypsin inhibitor ( BPTI ) /Kunitz family of SPI , as detected with Scan-Prosite program . A BLASTX analysis of the translated product deduced from the ORF revealed that Haemangin shares the greatest sequence identity ( 56% ) with kalicludine 1 , a K+ channel inhibitor that belongs to the BPTI/Kunitz family of SPI , obtained from the toxin of Anemonia sulcata ( accession number AAB35413 ) . Haemangin also shares 51% sequence identity with venom trypsin inhibitor isolated from the venom of Naja naja ( P20229 ) , 49% with isoinhibitor K , a trypsin-kallikrein inhibitor K from Helix promatica ( P00994 ) , 48% with TFPI from Homo sapiens ( AA089075 ) , and 47% with venom basic protease inhibitor I of Vipera ammodytes ammodytes ( P00992 ) . A comparison of the deduced amino acid sequence of Haemangin with those of venom basic proteinase inhibitors belonging to the BPTI/Kunitz family of SPIs is shown ( Figure 1A ) . Alignment data revealed that out of 5 disulfide bonds , 3 were conserved . The predicted signal peptides , however , were not conserved . Phylogenetic data revealed that Haemangin within the BPTI/Kunitz family of SPIs forms a separate single cluster and is distantly related to Kunitz-type inhibitors of snake-venom origin ( data not shown ) . Haemangin-specific transcript profiling at different blood-feeding stages was analyzed by quantitative RT-PCR . Data revealed that the target transcript was up-regulated as blood-feeding progressed . A dramatic increase of Haemangin expression was observed at 96 h of blood-feeding prior to acquisition of a full blood-meal , which then sharply declined to a minimal level ( data not shown ) , indicating that Haemangin plays a role in the acquisition of blood-meals . The endogenous expression of Haemangin in SGs of a partial-fed adult H . longicornis was shown to be localized in the salivary acini by immunofluorescence staining ( Figure 1B , left panel ) , but was not detected in the SGs treated with pre-immune mouse sera ( Figure 1B , right panel ) . A chick aortic ring assay was employed to examine whether Haemangin inhibited angiogenesis in vitro . The absence of Haemangin ( control ) allowed the formation of dense vascular sprouts in aortic ring explants , while its presence ( ∼500 nM ) potently inhibited vascular sprouting in a dose-dependent manner ( Figure 2A ) . HlSGE ( ∼500 µg/ml ) also strongly inhibited vascular sprouting in a dose-response manner . The IC50 for Haemangin and HlSGE was 100 . 81 nM and 129 . 63 µg/ml , respectively . A dose-dependent inhibition curve of vascular sprouting is shown ( Figure 2B ) . We also observed that transfected E . coli lysate ( ∼100 µl/well ) but not non-transfected E . coli lysate ( ∼100 µl/well ) exerted an inhibitory activity ( data not shown ) . Addition of rTpx ( 500 nM ) did not show any inhibitory effect on vascular sprouting ( Figure 2A ) . OmSGE ( ∼500 µg/ml ) completely failed to inhibit vascular sprouting ( Figure 2A ) . To further evaluate the potential of Haemangin in inhibiting angiogenesis , we used human umbilical vein endothelial cells ( HUVECs ) in a 96-well plate to examine Matrigel-induced morphogenic differentiation of ECs into capillary-like tubes . Data revealed that in the absence of Haemangin , HUVECs were rapidly organized , forming a number of well-defined capillary-like structures in Matrigel ( Figure 3A ) . The presence of Haemangin ( ∼250 nM ) strikingly inhibited tube formation . HlSGE ( ∼200 µg/ml ) also inhibited tube formation in a dose-dependent manner . Tube formation was also inhibited by transfected E . coli lysate ( ∼100 µl/well ) , but not by non-transfected E . coli lysate ( ∼100 µl/well ) ( data not shown ) or by rTpx ( 250 nM ) . Of interest , OmSGE ( ∼200 µg/ml ) did not inhibit tube formation . Dose-dependent inhibition curves of tube formation are shown in Figure 3B . The IC50 for Haemangin and HlSGE was 55 . 82 nM and 20 . 13 µg/ml , respectively . Haemangin distinctly abolished angiogenesis from the preexisting blood vessels , while chick chorioalantoic membranes ( CAMs ) treated with PBS alone revealed normal angiogenesis ( Figure 4A ) . HlSGE also inhibited angiogenesis in CAMs . Data on quantitative analysis showed that Haemangin at 500 ng/disc and HlSGE at 2 . 5 µg/disc inhibited approximately 80% and 72% neovascularization , respectively ( Figure 4B ) . Haemangin potently blocked proliferation of HUVECs in a dose-dependent manner with an IC50 of 20 . 07 nM ( Figure 5A ) . Consistent results were obtained with HlSGE with an IC50 of 10 . 11 µg/ml ( Figure 5A ) . The cell cytotoxicity effect of both Haemangin and HlSGE was determined by measuring the lactate dehydrogenase ( LDH ) activity . Neither Haemangin nor HlSGE showed any cytotoxic effect at concentrations used for cell proliferation assays ( data not shown ) , suggesting that Haemangin is non-toxic to mammalian cells . To investigate whether Haemangin-induced inhibition of cell proliferation is associated with apoptosis , HUVECs were incubated with Haemangin and were stained with Hoechst 33258 for observing changes characteristic of apoptosis . Haemangin markedly induced apoptosis of HUVECs at a concentration of 250 nM ( Figure 5B ) . The nuclei of living cells stained with Hoechst 33258 are shown as intact , with smooth and regular contour , while the apoptotic cells show shrinkage and rounding , with highly condensed , marginated , and fragmented nuclei , which are the hallmarks of apoptosis [17] . HlSGE also caused apoptosis at a concentration of 25 µg/ml ( Figure 5B ) . A DNA-ladder assay was performed to detect the typical DNA ladder , which is the characteristic of apoptotic cells [17] . DNA extracted from Haemangin- and HlSGE-treated cells showed an apparent laddering pattern of DNA fragmentation ( Figure 5C ) . We have hypothesized that hard ticks evolved novel strategies to suppress wound healing to avoid rejection by the host . To test this hypothesis , we examined the ability of Haemangin to thwart wound healing using artificially created wounds in a monolayer of HUVECs ( Figure 5D ) . In the absence of Haemangin , wound healing was completed within 12 h ( Figure 5D ) . Notably , Haemangin dose-dependently inhibited wound healing with an IC50 of 49 . 49 nM ( Figure 5E ) . Similar results were obtained with HlSGE with an IC50 of 10 . 49 µg/ml ( Figure 5E ) . Haemangin dose-dependently inhibited trypsin and chymotrypsin , showing maximum inhibition of 90% and 82% with an IC50 of 64 . 65 nM and 294 . 61 nM , respectively ( Figure 6A ) . Haemangin poorly inhibited elastase ( 21% ) ( Figure 6A ) . HlSGE also potently inhibited the activity of trypsin and chymotrypsin and slightly inhibited elastase by 77% , 78% , and 14% , respectively ( Figure 6A ) . The IC50 was 6 . 43 µg/ml and 51 . 71 µg/ml for trypsin and chymotrypsin , respectively . Data on BSA proteolysis inhibition assays showed that Haemangin inhibited BSA proteolysis by trypsin and chymotrypsin in a dose-dependent fashion ( Figure 6B ) . Consistent results were obtained with HlSGE ( Figure 6B ) . Haemangin was able to efficiently stimulate degradation of both the plasmin heavy and light chains during fibrinolysis ( Figure 6C ) . However , relatively little activity was detectable with HlSGE ( Figure 6C ) . To further evaluate whether Haemangin directly inhibit plasmin activity , in vitro fibrin polymer lysis assays were conducted . A fibrin polymer was initially prepared and then fibrinolysis was initiated by the addition of plasmin in the absence or presence of increasing concentrations of Haemangin . An increase in turbidity was detected as polymerization of fibrin proceeded ( data not shown ) , and reached a maximum value when a stable fibrin polymer was formed ( Figure 6D ) . A plasmin-induced fibrinolysis yielded a clear suspension of the fibrin polymer and exhibited a decrease in turbidity ( Figure 6D ) . Haemangin strongly inhibited plasmin-dependent fibrinolysis while HlSGE moderately blocked fibrinolytic activity of the added plasmin ( Figure 6D ) , suggesting that Haemangin is able to inhibit the proteolytic activity of plasmin on cross-linked fibrin polymer . An attempt was made to examine the global gene expression profiles of HUVECs stimulated with Haemangin to gain a precise understanding of the molecular signaling cascades that facilitate feeding and engorgement of hard ticks . By comparing the expression profiles between Haemangin-exposed and nonexposed HUVECs , gene ontology data based on molecular functions revealed a total of 506 responsive genes out of 35 , 000 genes expressed on the microarray chips . Of 506 altered genes , 317 were up-regulated and 189 were down-regulated genes ( Figures S1 and S2 ) . On the other hand , gene ontology data based on biological processes demonstrated a total of 2 , 761 induced genes , of which 2 , 199 genes were up-regulated and 562 were down-regulated ( Tables S1 and S2 ) . To explore Haemangin's function in vivo , adult H . longicornis were allowed to feed on rabbits ( Figure 7A ) . Tick feeding progression and engorgement were monitored and transcriptional responses at different feeding stages were analyzed by semi-quantitative RT-PCR . Data were consistent with that of quantitative RT-PCR ( Figure 7B ) . Tick feeding progression is summarized in Figure 7B . Haemangin expression was steadily up-regulated with the progression of feeding , showing a dramatic peak prior to acquisition of full blood-meals , and then sharply declined upon engorgement . Healing of the feeding wounds commenced immediately after ticks dropped off the host ( Figure 7C , left panel ) , and completed within 10–14 days ( Figure 7C , right panel ) . To validate gene functions in vivo , an RNA interference ( RNAi ) tool was employed using Haemangin-specific double-stranded RNA ( dsRNA ) . Data revealed very scanty expression of Haemangin-specific mRNA upon feeding , indicating that gene knockdown was successful ( Figure 7D ) . Notably , knockdown ticks completely failed to make blood pools by 72 h and achieved significantly diminished engorgement by 144 h , while control ticks become engorged by 120 h , as shown by engorged body weights of 32 . 89±18 . 36 and 314 . 18±63 . 17 mg ( p<0 . 001 ) , respectively ( Figure 7E ) . Histologically , knockdown tick-fed lesions showed an increased neovascularization compared with controls , suggesting a novel antiangiogenic role for Haemangin ( Figure 7F ) .
Prior studies suggest that slower feeding hard ticks heavily rely on salivary molecules for acquisition of blood-meals [12] , [13] , [18] . Here , we report on a salivary Kunitz inhibitor of H . longicornis that modulates angiogenesis and wound healing , enabling ticks to feed and engorge . Furthermore , our results substantiate a diversified role of Kunitz proteins in angiogenesis-dependent human diseases . We have shown that Haemangin pronouncedly disrupted angiogenesis through inhibition of EC proliferation and induction of apoptosis . These observations conform to the report of Francischetti et al . [15] , who described similar roles for tick saliva , suggesting that tick saliva has MP activity that may cause inhibition of cell proliferation and induction of apoptosis , although the salivary molecule ( s ) responsible for the inhibition of angiogenesis was not confirmed . Angiogenesis is dependent on fibrinolytic MPs and plasmin , indicating that cleavage of fibrin is required for angiogenic cascades [19] , [20] . Angiogenesis is characterized by EC proliferation , migration , and capillary tube formation , and is dependent on cell adhesion molecules and proteinases [19] , [21] . In contrast , inhibition of cell proliferation and induction of apoptosis are among the most effective means of disruption of angiogenesis . Proteolytic degradation of ECM and the vascular basement membrane , and remodeling of the ECM components is essentially required to allow ECs to migrate into and invade the surrounding stroma [5] , [22] , [23] . However , excessive degradation of ECM is incompatible with efficient migration of EC [24] . It has been anticipated that the maintenance of a certain degree of ECM integrity is indeed essential for capillary morphogenesis [25] . We hypothesized that Haemangin exerts an antiangiogenic function through the inhibition of proteolytic cascades , although we cannot rule out alternative roles , such as the inhibition of cell adhesion mechanisms by inactivating angiogenic growth factors . Plasmin cleaves fibrinogen and fibrin , and activates various MMPs . Once activated , plasmin can act by itself on ECM proteins and activates MMP-1 , MMP-2 , MMP-3 , and MMP-9 [26] , [27] . Furthermore , in addition to MT1-MMP , plasmin has been indicated to be involved in endothelial tube formation in a fibrin matrix [19] , [20] , [28] . Of note , the ECM is known to act as a sequestration for angiogenic growth factors , for example , vascular endothelial growth factor ( VEGF ) , bFGF , and transforming growth factor ( TGF ) -β1 , which can be released upon proteolytic degradation of the ECM [29] , suggesting that plasmin is critical for angiogenesis . Overall , our data indicate that Haemangin-induced plasmin proteolysis plays an important role in the inhibition of angiogenesis during blood-feeding by hard ticks . For the suppression of tumor angiogenesis , however , a tightly controlled proteolysis by proteinase inhibitors ( for example , uPA , plasmin , and probably MPs ) is required [25] . Growth factors and their receptors are important mediators of angiogenesis . The VEGF and bFGF are the two most potent angiogenic factors that stimulate angiogenic cascades independently [30] . Growth factors specifically bind and interact with their receptors , which are all tyrosine kinases , present on the EC surface , and in turn activate different signal transduction pathways , leading to alteration of the transcription of genes involved in cell migration , apoptosis , proliferation , and tube formation [31] . Haemangin markedly induced apoptosis and blocked EC proliferation directly , indicating that it may simultaneously alter expression of angiogenic factors and/or inactivate cell surface receptors . To explore molecular pathways of Haemangin-modulated angiogenesis , high-throughput studies were performed . Data revealed that Haemangin induces a wide spectrum of genes associated with various biological processes , including apoptosis , angiogenesis , and wound healing . An enhanced expression of genes in response to cytokine and chemokine activity , VEGF receptor activity , IL-6 receptor binding , and receptor tyrosine kinase binding might reflect a process of activation of inflammation and wounding , and higher demand for cell proliferation and differentiation to supply oxygen and nutrients for tissues in repairing process [32] , [33] . Haemangin was also shown to repress a number of genes of angiogenic significance . Extracellular signal–regulated kinase/mitogen-activated protein kinase ( ERK/MAPK ) signaling plays crucial roles in diverse cellular functions , including cell proliferation , differentiation , migration , and survival [34] . Also , FGF receptor signaling is known to modulate a wide variety of cellular functions , including epithelial cell morphogenesis [35] . Adenosine 3′ , 5′-cyclic monophosphate ( cAMP ) -binding proteins directly activate Rap1 , a member of the Ras superfamily of small G proteins that , in turn , stimulate and inhibit the activity of MAPK , such as B-Raf and Raf-1 , respectively , leading to altered activity of ERK/MAPK that is critical for growth factor–induced cell proliferation and angiogenesis [36] , [37] . Thus , Haemangin appears to utilize multiple intracellular signaling pathways to negatively regulate angiogenesis and angiogenesis-dependent wound healing . Angiogenesis plays a central role in the wound healing process [38] . Proteolytic degradation of ECM by serine proteinases , particularly plasmin , and MMPs is crucial in this process [39] . EC proliferation is one of the important steps in angiogenesis and is critical for granulation tissue formation , a hallmark of wound healing [40] . Data presented above strongly suggest that Haemangin is capable of inhibiting different phases of wound healing , from proteolytic degradation of ECM to EC proliferation and differentiation , and eventually affects the tissue repair process . This may likely slow tick rejection and favor feeding and engorgement . Salivary anticoagulants ( Salp14 and its paralogs ) and cysteine protienase inhibitors in I . scapularis are reported to contribute to blood-feeding success [41] , [42] , although their roles in angiogenesis and wound healing are still unclear . Of note , a dramatic upregulation of Haemangin-specific mRNA prior to the acquisition of full blood-meals indicated its crucial role in blood-meal acquisition . This finding , together with RNAi data , strongly supports such a role for Haemangin . Interestingly , the fast-feeder counterpart Ornithodoros moubata lacks both Haemangin-like Kunitz inhibitor and antiangiogenic functions , and is similar to other fast-feeder haematophagus arthropods , for example , mosquitoes and sand flies , whose SGs do not affect ECs [15] . This may likely explain the functional significance of Haemangin in blood-feeding strategies and success by slower feeding arthropods like hard ticks . In conclusion , these results show that unlike fast-feeder arthropods , slow-feeder hard ticks evolve novel strategies to remain attached on large mammalian counterparts and achieve engorgement through the modulation of angiogenesis and wound healing processes . Furthermore , the Haemangin-like modulatory peptide ( s ) is considered vital for the hard tick's survival and can be a potential therapeutic target against ticks and tick-borne pathogens , including tumor angiogenesis .
H . longicornis and O . moubata ( soft tick ) were maintained in the Laboratory of Parasitic Diseases , National Institute of Animal Health ( NIAH ) , Japan . SGs were obtained from adult H . longicornis at different blood-feeding stages . SGs from adult soft ticks were collected after partial blood-feeding on rabbits . Animal experimentation was done in accordance with the protocol approved by the NIAH Animal Care and Use Committee . Recently , our group generated a total of 8 , 000 ESTs from the SGs cDNA libraries of adult H . longicornis [16] . Of these , a full-length cDNA clone encoding a protein called Haemangin showing moderate homologies with Kunitz-type inhibitors was selected for this study . The BLAST program for alignment was used to compare the Haemangin sequence with previously reported sequences available in GenBank . The coding region of the Haemangin gene including the signal sequence was amplified by PCR . A sense primer ( 5′- GGAATTCCTCACTCCATGTTGTTATGTAA-3′ ) containing an EcoRI site upstream of the start codon and an antisense primer ( 5′-CCGAGCTCGAGACGAGAGCCATTTCGCCAACCA-3′ ) containing a XhoI site just downstream of amino acid residue were used ( Promega ) . The purified PCR product was inserted into the EcoRI and XhoI sites of plasmid expression vector pTrcHisB ( Invitrogen ) . The resultant plasmid was transformed into E . coli strain TOP10F′ ( Invitrogen ) cells and expressed as a fusion protein . Recombinant proteins were produced and solubilized under denaturing conditions using 20 mM sodium phosphate , 500 mM sodium chloride , and 8 M urea ( pH 7 . 8 ) , and then purified by histidine binding affinity chromatography ( Bio-Rad ) followed by dialysis against 20 mM Tris-HCl ( pH 8 . 0 ) and 150 mM NaCl . The purity of Haemangin was judged by SDS-PAGE . Protein concentrations were measured with the Micro BCA Protein Assay Reagent ( Pierce ) . SGs were washed in PBS containing 0 . 1% Tween 20 ( PBS-T ) and were fixed in acetone . After fixation , they were blocked with 10% goat serum ( Wako ) for 1 h and were incubated with anti-mouse IgG to Haemangin overnight . FITC-conjugated goat anti-mouse IgG ( Sigma ) was used as a secondary antibody and the fluorescence was visualized under a Leica microscope . Proteinase inhibition assays were performed by measuring the residual hydrolytic activity after preincubation with Haemangin . To detect the inhibitory activity of endogenous Haemangin , soluble extracts of H . longicornis SG extract ( HlSGE ) were prepared in 20 mM Tris-HCl ( pH 8 . 0 ) . The enzymes were preincubated with Haemangin or HlSGE for 30 min at 37°C . Then , appropriate substrates in a 200 µl reaction mixture consisting of 100 mM Tris-HCl ( pH 8 . 0 ) , 100 mM NaCl , and 20 mM CaCl2 in a 96-well plate were added , followed by incubation for 1 h at 37°C . Fluorogenic substrates for trypsin ( Boc-Gln-Ala-Arg-MCA ) ( 1 mM ) , chymotrypsin ( Suc-Ala-Ala-Pro-Phe-MCA ) ( 1 mM ) , and elastase ( Suc-Ala-Ala-Ala-MCA ) ( 1 mM ) ( Peptide Institute Inc . ) were used . Substrate hydrolysis was monitored by measuring excitation and emission wavelength at 360 nm and 460 nm , respectively , over time . Percentage of inhibition by Haemangin of enzyme activity was assessed by the following formula: % inhibition = ( 1–inhibited rate/uninhibited rate ) ×100 . Inhibitory activity of Haemangin and HlSGE on BSA proteolysis by trypsin and chymotrypsin was examined by pre-incubating the enzymes with Haemangin or HlSGE in a total reaction mixture of 40 µl for 1 h at 37°C for inhibition . Then , BSA ( 500 µg/ml ) was added to inhibited and control ( uninhibited ) enzymes ( 250 µg/ml ) and was further incubated overnight at 37°C . The tryptic digests were then analyzed by SDS-PAGE . A chick aortic ring assay was performed [15] . A twelve-day-old chick embryo was removed by cracking the egg; the thoracic cavity was opened and the heart and aortic arch were carefully removed . The aortic arch was cut into ∼1 . 0-mm pieces . A 96-well tissue culture plate was coated with 3 µl Matrigel/well ( BD Biosciences ) and aortic rings were placed into the wells; they were then held in place by overlaying 20 µl Matrigel/well . Then , 100 µl of EBM-2 ( BD Biosciences ) supplemented with antibiotics was added followed by the addition of Haemangin or HlSGE/OmSGE . A SG-specific recombinant protein from H . longicornis , peroxiredoxin ( rTpx ) [43] , served as a negative control . Formation of vascular sprouts was observed for 3 days under a Leica microscope . A blind observer scored the density of vessel sprouts by comparing responses with media alone ( control ) to that observed with Haemangin . Results were scored as ( i ) 100% , sprout formation achieved with media alone ( control ) ; ( ii ) 75% , high levels of sprout formation; ( iii ) 50% , moderate levels of sprout formation; ( iv ) 25% , low levels of sprout formation; and ( v ) 10% , very low levels of sprout formation . A chick chorioalantoic membrane ( CAM ) assay as an in vivo model of angiogenesis was performed to determine the antiangiogenic activity of Haemangin [44] . Haemangin or HlSGE in a total volume of 20 µl was loaded onto Thermanox discs , 13 mm in diameter ( Nunc ) , and was applied to the CAM of 8-day-old embryos . PBS was used as a control . After 48 h of incubation at 37°C , a negative or positive response was assessed by two observers in a double-blind manner . HUVECs ( Cell Applications , Inc . ) were cultured in growth medium at 37°C , 5% CO2 according to the manufacturer's instructions . Cells were incubated in T-25 tissue culture flasks to >80% confluency . Trypsinization was performed using the Subculturing Reagent Kit according to the manufacturer's instructions . Tube formation assay was performed in a 96-well plate coated with 50 µl Matrigel [45] . After trypsinization , HUVECs were seeded at 7 . 5×103/well . Then , 100 µl/well growth medium was added . Cells were grown in the absence or presence of Haemangin or HlSGE/OmSGE at 37°C , 5% CO2 . Tube formation was observed for 6 h under a Leica microscope . The number of tubes formed in individual wells was counted and data were expressed as a percentage compared to control . A cell proliferation assay was conducted using a cell proliferation assay kit ( Promega ) [46] . The 96-well plate was seeded with HUVECs at 3×103/well . Cells were grown in 150 µl growth medium for 24 h at 37°C , 5% CO2 . Then , medium was refreshed and Haemangin or HlSGE was added . After 3 days incubation , 30 µl MTS solution was added to each well . The plate was further incubated and the absorbance at 490 nm was measured using a spectrophotometer ( Spectra Fluor ) . Results were expressed as percent inhibition of HUVEC proliferation in the presence of Haemangin or HlSGE compared to 100% cell proliferation achieved with growth medium alone . A cell cytotoxicity assay was performed using Cytotoxicity Detection KitPLUS ( LDH ) ( Roche ) as described by the manufacturer to determine the cytotoxic effect of Haemangin or HlSGE , if any . Apoptosis was analyzed by Hoechst 33258 ( Invitrogen ) staining and by DNA-ladder assay . Hoechst 33258 staining of cells was performed by culturing HUVECs ( 1×105 cells per well ) onto glass coverslips in a 6-well plate ( Sumitomo Bakelite ) in growth medium at 37°C , 5% CO2 . Cells were grown to 90% confluency . Then , Haemangin or HlSGE was added to the wells and cells were further incubated for 48 h at 37°C , 5% CO2 . Cells were washed in PBS , fixed in 4% paraformaldehyde for 15 min , and stained with 8 µg/ml Hoechst 33258 ( Hoechst ) in H2O for 10 min . Cells were analyzed for nuclear morphologic changes using a Leica microscope equipped with fluorescence , DAPI , and composite filters ( 360/420 nm excitation and emission , respectively ) , and images were taken using Leica FW4000 Software . The DNA-ladder assay was carried out using the Apoptotic DNA Ladder Kit ( Roche ) . Cells were cultured in a T-25 tissue culture flask ( 2 . 5×105 cells/flask ) in the absence or presence of Haemangin or HlSGE for 48 h at 37°C , 5% CO2 as mentioned above . The total cytoplasmic DNA was extracted from 2×106 cells . Isolated DNA was analyzed using 1% agarose gel electrophoresis . The wound healing assay was performed in a 6-well plate [47] . HUVECs were seeded ( 1 . 25×105 cells/well ) in 6-well plate and were grown at 37°C , 5% CO2 to confluency . A wound was made by scratching a line across the monolayer of cells with a sterile pipette tip . The width of the cell-free gap was measured continuously under a Leica microscope by using Leica Application Suite . The response of wound healing was measured by the percentage reduction of the width of the scratch . Haemangin-stimulated plasmin degradation assay was performed [48] . Fibrinogen ( 8 µM; Sigma ) and thrombin ( 0 . 83 NIH unit/ml; Sigma ) were incubated in a 400 µl buffer containing 50 mM Tris-HCl ( pH 7 . 5 ) , 100 mM NaCl , and 5 mM CaCl2 at 25°C for 30 min . After the fibrin was completely polymerized , lysis of fibrin polymer was then initiated by adding 100 µl of buffer containing 20 µM plasminogen ( Calbiochem ) and 15 nM t-PA ( Calbiochem ) in the absence or presence of Haemangin or HlSGE . The reaction mixtures were then incubated overnight at 25°C and were subjected to SDS-PAGE . Plasmin degradation was examined by Coomassie staining of the proteins . To further examine the effect of Haemangin on fibrinolytic activity of plasmin , plasmin-dependent fibrinolysis inhibition assays were performed at 25°C to monitor changes in turbidity at 450 nm [48] . Fibrin polymer was prepared in a volume of 400 µl buffer and 1 . 5 µM plasmin ( Sigma ) without or with Haemangin , or HlSGE was added to initiate fibrinolysis . After the sample was incubated at 25°C for 12 h , plasmin-dependent fibrinolysis was observed and turbidity as function of plasmin was measured at an absorbance of 450 nm . RNAi studies were carried out using dsRNA [42] . The coding sequence of Haemangin was cloned into pBluescript II SK+ plasmid ( Toyobo ) . The dsRNA complementary to the E . coli malE gene was used as a negative control [49] . cDNA corresponding to malE mRNA was synthesized and was cloned into pBluescript II SK+ plasmid using the oligonucleotides 5′-CCGCTCGAGCGGTTATGAAAATAAAAACAGGTGCA-3′ and 5′-GAATTCGCTTGTCCTGGAACGCTTTGTC-3′ as forward and reverse primers , respectively . The inserted sequences of Haemangin and malE were amplified by PCR using the oligonucleotide T7 ( 5′-GTAATACGACTCACTATAGGGC-3′ ) and CM0422 primers ( 5′-GCGTAATACGACTCACTATAGGGAACAAAAGCTGGAGCT-3′ ) to attach T7 promoter recognition sites at both ends . The PCR products were purified using a gel extraction kit ( Qiagen ) . dsRNA complementary to the DNA insert was synthesized by in vitro transcription using T7 RNA polymerase ( Promega ) . One microgram each of Haemangin and malE dsRNA in 0 . 5 µl of PBS separately was injected into each unfed adult tick . Ticks were allowed to rest for 24 h at 25°C prior to placement on the host [16] . Rabbit tissues were also processed for H&E and silver nitrate staining . The total RNA from tick SGs was isolated using an RNAeasy Mini Kit ( Qiagen ) and was submitted to reverse transcription ( RT ) before PCR . cDNA was synthesized and was employed to perform PCRs using either Haemangin-specific oligonucleotides ( 5′-CATTTCGCCAACCATCTTTC-3′ and 5′-TGACAGGTCCAGCAGCTATG-3′ ) or oligonucleotides specific for β-actin . Quantitative RT-PCR was done using LightCycler FastStart DNA Master SYBR Green I ( Roche ) in a LightCycler 1 . 5 instrument ( Roche ) [16] . To perform oligonucleotide microarray analysis , HUVECs were cultured in the absence ( control ) or presence of Haemangin ( 100 nM ) for 48 h as described above . Approximately 2×106 cells were harvested and the total RNA was extracted as described above . The mRNAs were then prepared and analyzed by hybridization to microarrays ( Filgen Array Human35k , oligo DNA microarray ) . Data are reported as means±standard errors , where appropriate . The statistical significance ( p<0 . 05 ) was determined by Student's t test/Mann-Whitney's U test . The nucleotide sequence data reported in this paper will appear in the DDBJ/EMBL/GENBANK nucleotide sequence databases with the accession number AB434485 . | Ticks are notorious ectoparasites that exclusively feed on a host's blood for a period of 10 days or longer . Upon blood-feeding , an adult female tick gains 100–200 times its body weight compared to its pre-feeding stage . Despite the host's armoury of rejection mechanisms , ticks manage to remain attached until a full blood-meal is ensured . The molecular machineries that make the tick a success with its feeding , however , remain unknown . We demonstrate that the Kunitz-like protein Haemangin , identified from the salivary glands of the tick Haemaphysalis longicornis , plays vital roles in blood-feeding success . Using both cell- and chick embryo–based bioassays , we have shown that Haemangin efficiently disrupted angiogenesis and wound healing processes , enabling ticks to remain attached and allowing persistent feeding . Additionally , in a rabbit model , we reveal that an elevated expression of Haemangin is associated with the acquisition of full blood-meals . Importantly , Haemangin-knockdown ticks fail to prevent angiogenesis in the host's tissues and consequently achieve only a poor blood-meal as compared to normal ticks . We conclude that Haemangin is vital for ticks' survival and can be a novel therapeutic target against ticks and tick-borne diseases , including tumor angiogenesis . | [
"Abstract",
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] | [
"infectious",
"diseases/neglected",
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] | 2009 | The Kunitz-Like Modulatory Protein Haemangin Is Vital for Hard Tick Blood-Feeding Success |
Bacteria can acquire new traits through horizontal gene transfer . Inappropriate expression of transferred genes , however , can disrupt the physiology of the host bacteria . To reduce this risk , Escherichia coli expresses the nucleoid-associated protein , H-NS , which preferentially binds to horizontally transferred genes to control their expression . Once expression is optimized , the horizontally transferred genes may actually contribute to E . coli survival in new habitats . Therefore , we investigated whether and how H-NS contributes to this optimization process . A comparison of H-NS binding profiles on common chromosomal segments of three E . coli strains belonging to different phylogenetic groups indicated that the positions of H-NS-bound regions have been conserved in E . coli strains . The sequences of the H-NS-bound regions appear to have diverged more so than H-NS-unbound regions only when H-NS-bound regions are located upstream or in coding regions of genes . Because these regions generally contain regulatory elements for gene expression , sequence divergence in these regions may be associated with alteration of gene expression . Indeed , nucleotide substitutions in H-NS-bound regions of the ybdO promoter and coding regions have diversified the potential for H-NS-independent negative regulation among E . coli strains . The ybdO expression in these strains was still negatively regulated by H-NS , which reduced the effect of H-NS-independent regulation under normal growth conditions . Hence , we propose that , during E . coli evolution , the conservation of H-NS binding sites resulted in the diversification of the regulation of horizontally transferred genes , which may have facilitated E . coli adaptation to new ecological niches .
The Escherichia coli species consists of genetically diverse strains , for example , in terms of nutrient metabolism , stress responses , and pathogenicity [1] . One of the well-known factors causing genetic diversity in bacteria is horizontal gene transfer; an estimated 10–16% of genes in E . coli strains have been acquired horizontally [2] . However , unregulated expression of newly acquired genes could disrupt the physiology of the host cell [3 , 4] . Both E . coli and Salmonella express the protein H-NS , which preferentially binds adenine and thymine ( AT ) -rich DNA [3 , 5–7] . Many horizontally transferred genes ( HTGs ) have a high AT content relative to E . coli genes , which facilitates H-NS binding to , and repression of , the foreign genes [8] . This repression guards host cells from potential physiological perturbations caused by expression of HTGs [3 , 5] . Deficiency in the gene hns impairs Salmonella growth during laboratory cultivation [9] . Compensatory mutations for this growth impairment have been identified in the gene stpA , encoding StpA , which is the H-NS paralog . These mutations alter StpA functionality to resemble that of H-NS [9] . In addition , loss of virulence genes in the Salmonella pathogenic island-1 ( SPI-1 ) and frameshift and missense mutations in phoPQ , which encodes the positive transcriptional regulator of virulence genes , could also compensate for the fitness loss of hns deficiency [9] . Therefore , the major role of H-NS in Salmonella is purportedly the silencing of genes within SPI-1 [9] . In addition , H-NS suppresses transcription of pervasive non-coding and antisense sequences in both coding regions and intergenic regions [10–12] by inhibiting the recruitment of RNA polymerase to promoters , trapping this polymerase at promoters , or inhibiting transcriptional elongation [8 , 10 , 11 , 13–17] . However , AT-rich sequences bound by H-NS can be highly expressed when both hns and stpA are disrupted [18] . In this scenario , the spurious expression of non-coding and antisense RNAs and the higher expression of AT-rich genes impose high metabolic costs and reduce the fitness of hns-deficient cells [11 , 18] . Furthermore , H-NS can both directly and indirectly regulate global gene expression in E . coli [19 , 20] . Mutations that counter the slow growth observed for the hns/stpA double mutant have been identified . One mutation inactivates the sigma factor for stress response , namely RpoS , which is involved in the expression of many genes induced by the hns/stpA double mutation . The other mutation amplifies ~40% of the E . coli chromosome centered near the origin of replication , which causes remodeling of the transcriptome and partially reverses the imbalance in global gene expression caused by the double mutation [21] . Interestingly , the transcriptional repression activity of H-NS is affected by the location of H-NS binding sites throughout the E . coli chromosome . H-NS is a strong repressor of the hns promoter when this promoter is ectopically placed in the Ter or Left macrodomain of the chromosome [22] . It is also known that environmental factors , such as pH , temperature , and osmolarity , can alter H-NS-mediated gene repression [23] . Hence , a change in environmental conditions , i . e . , an abiotic stressor , can activate a large number of genes that normally are repressed by H-NS , thereby potentiating the stress response . [5 , 23] . Any HTG should be expressed only when its function is beneficial to the host bacteria . However , transcriptional regulators are not well conserved and transcriptional networks are highly diversified among bacterial species [24] . For acquired genes , therefore , the regulation that occurs via a host-cell transcriptional regulator ( s ) and/or regulatory element ( s ) would need to be optimized [25] . It has been suggested that , in bacteria , such optimization requires a long time , and this is accomplished through several steps: 1 ) upon integration of the HTG ( s ) into the host genome , the initial expression would be lower than for native host genes; 2 ) a host-cell activator is required to express HTGs; and 3 ) the expression of the transferred genes must be fine-tuned to match the needs of host cells [25] . On the other hand , Dorman [3] proposed that H-NS-mediated repression of HTGs could be an effective way to reduce the risk of inappropriate expression of such genes until expression could be optimized . Although H-NS-mediated repression of virulence genes , which are HTGs , may reduce the fitness cost raised by the expression of virulence genes and contributes to the evolution of the Salmonella [9] , it remains unclear whether H-NS actually contributes to the optimization of expression of transferred genes so as to benefit host cells . The aim of our study was to improve our knowledge of how H-NS contributes to the integration of HTGs into E . coli . Genome-wide H-NS binding profiles were recently obtained with the E . coli K-12 genome using chromatin immunoprecipitation ( ChIP ) -chip and ChIP-seq analyses [19 , 26–28] . Using this information , it is possible to examine the conservation/diversification of H-NS-bound regions within the E . coli genome during evolution . Hence , we used chromatin affinity precipitation ( ChAP ) -seq to compare H-NS-bound regions within the genomes of genetically diverse E . coli strains belonging to different subgroups , specifically , laboratory strain K-12 ( subgroup A ) , commensal strain SE11 ( subgroup B1 ) , and commensal strain SE15 ( subgroup B2 ) [29 , 30] . This analysis enabled us to investigate the influence of H-NS binding on the diversification of genomic sequences . Our analysis suggests that the distribution of H-NS-bound regions within E . coli genomes has been highly conserved during evolution . In addition , sequence diversity in the H-NS-bound regulatory regions tended to be greater than in H-NS-unbound regulatory regions . Hence , we propose that transcriptional repression by H-NS increases the propensity for nucleotide substitutions in transcriptional regulatory regions of HTGs , which may alter the expression of transferred genes to facilitate adaptation of E . coli cells to new habitats .
Phylogenetic analysis has indicated that group B2 is the ancestral phylogroup in the E . coli lineage , whereas groups A and B1 have diverged [31–33] . To assess the impact of E . coli evolution on H-NS binding , we comprehensively compared the localization of H-NS-bound regions on chromosomes among the three E . coli strains K-12 ( group A ) , SE11 ( group B1 ) , and SE15 ( group B2 ) . Notably , the amino acid sequence of H-NS is completely conserved among these strains . We created H-NS-12His-expressing recombinant K-12 ( W3110 ) , SE11 , and SE15 strains and determined H-NS binding profiles on the chromosomes for the three strains using ChAP-seq . Each strain was grown to mid-log phase ( OD600 ≈ 0 . 4 ) in LB medium under aerobic condition and treated with formaldehyde to crosslink H-NS-12His to DNA , followed by ChAP of the crosslinked DNA fragments with H-NS , as described [34] . Purified DNA from ChAP and whole-cell extract ( WCE; pre-ChAP ) was subjected to high-throughput Illumina sequencing , and the H-NS-bound regions were determined ( See details in Materials and Methods ) . We performed duplicate ChAP analyses for each strain , and the H-NS binding profiles were highly reproducible ( Fig 1A ) . Thus , we defined overlapping regions of H-NS binding regions in duplicate ChAP analyses as reproducible H-NS binding regions , and used these defined regions in subsequent analyses . We identified H-NS-bound regions covering 802 , 561 bp in SE11 , 642 , 859 bp in SE15 , and 697 , 762 bp in K-12 , corresponding to 14–16% of each genome ( Table 1 ) . To compare the H-NS-bound regions among the E . coli strains , we aligned the three chromosome sequences using the Mauve program developed for the multiple alignment of bacterial chromosome sequences [35 , 36] . We identified the “common” ( conserved in all three strains ) , “shared” ( conserved in two strains ) , and “specific” ( unique for each strain ) chromosome segments ( Table 1 ) . Whereas the common segments would have been in the ancestral genome before divergence of the E . coli lineage , the “shared” and “specific” segments would have become integrated in the E . coli genome after the divergence . We calculated the proportions of H-NS-bound regions in each of the “common” , “shared” , and “specific” segments of the three strains ( Table 1 ) . The proportion of H-NS-bound sequences was higher in the “specific” and “shared” segments ( ~30–38% ) than in the “common” segments ( ~10–12% ) , suggesting that many genes in the “specific” and “shared” regions were horizontally transferred during E . coli evolution and retained preferential binding to H-NS . Although many of the “specific” and “shared” segments were bound by H-NS , more than half of the H-NS-bound regions were located within “common” segments , with similar total length among the chromosomes of SE11 ( 451 , 643 bp ) , SE15 ( 383 , 226 bp ) , and K-12 ( 427 , 731 bp ) ( Table 1 ) . Specifically , 76 . 2% ( SE11 ) , 89 . 8% ( SE15 ) , and 80 . 4% ( K-12 ) of H-NS-bound regions in “common” segments overlapped among the three strains ( Fig 1B left [Common] and Fig 1C–1F ) . In addition , very few H-NS-bound regions in “common” segments ( 3 . 4% to 7 . 7% ) were identified as unique in each strain , and the remainder of the binding regions were shared by two strains ( Fig 1B left [Common] ) . We manually examined these unique and shared H-NS-bound regions and found that most of these regions ( 84% of the unique and shared H-NS-bound regions in common segments ) had H-NS binding signals on a certain level in all three strains , although signal intensities were below the threshold to be categorized as H-NS-bound regions in one or two strains . We concluded that the H-NS-bound regions in “common” segments are highly conserved in the three strains . It has been reported that H-NS binding to orthologous genes in E . coli and Salmonella is highly conserved [19] . This and our current result indicate that the H-NS-bound regions have been retained in the E . coli lineage during evolution . Notably , the H-NS-bound regions within “shared” segments between two strains are also conserved ( 85 . 0–94 . 7% , Fig 1B right [Shared] ) . We concluded that the H-NS binding in “common” segments has been conserved during the evolution of E . coli . Therefore , we were interested in the effects of the conservation of H-NS binding on sequence diversification/conservation among the E . coli genomes . We initially compared sequence diversities between the H-NS-bound and -unbound orthologous genes . OrthoMCL was used to search for conserved orthologs that are present in SE15 , SE11 , and K-12 and at least 37 other E . coli strains , of the 44 strains in the curated non-redundant genome collection of reference sequences ( RefSeq ) at NCBI , when we started this analysis [37] ( See details in Materials and Methods and S1 Fig ) . Then , 2 , 702 genes were selected as being well conserved orthologs ( S2 Table ) , and these were used to estimate the synonymous ( dS ) and non-synonymous ( dN ) substitution rates based on multiple sequence alignment . Genes among these were defined as H-NS bound if their coding regions overlapped with H-NS-bound regions identified in at least one of the SE15 , SE11 , and K-12 strains as determined by ChAP-seq analysis . As expected , dS was higher than dN for the orthologous genes regardless of H-NS binding ( see sequence diversity scales of Fig 2A and 2B ) , whereas dN in the H-NS-bound genes tended to be higher than that in the H-NS-unbound genes ( Fig 2A; p < 0 . 001 , Wilcoxon rank-sum test ) . In contrast , the dS between H-NS-bound and -unbound genes was not significantly different ( Fig 2B; p = 0 . 08 ) . These observations indicated that the non-synonymous sites in the H-NS-bound genes evolved faster than those in the H-NS-unbound genes . Because H-NS preferentially binds to horizontally transferred genes ( HTGs ) [3 , 6 , 7 , 27] , this apparent faster evolution of non-synonymous sites in H-NS-bound genes could simply reflect the rapid evolution of genes recently transferred to host cells , which was indicated in the Bacillus cereus group [38] and E . coli lineages [39] . To assess the effect of H-NS binding and horizontal transfer , orthologous genes were classified into HTGs which were estimated as HTGs in at least one of previous predictions [40–42] or Core genes ( other non-HTGs ) , and the tendency of dS and dN in each class of H-NS-bound and—unbound genes was evaluated . The dN of HTGs with or without H-NS binding was greater than that of Core genes ( Fig 2C ) , which is consistent with previous observations [38 , 39] . In addition , dN of H-NS-bound Core genes was greater than that of H-NS-unbound Core genes ( Fig 2C Core genes; p < 0 . 001 ) . Furthermore , dS of H-NS-bound Core genes was also greater than that of H-NS-unbound Core genes; this difference in dS was smaller than that of dN , but statistically significant ( Fig 2D Core genes; p = 0 . 0072 ) . These results indicated that the non-synonymous and synonymous sites in H-NS-bound Core genes evolve faster than those in H-NS-unbound Core genes in the E . coli lineage . In contrast , dN of H-NS-bound and -unbound HTGs indicated no significant difference ( Fig 2C HTGs; p = 0 . 097 ) . However , the variance of dN of H-NS-bound HTGs and that of H-NS-unbound HTGs were significantly different ( Fig 2C HTGs; p = 0 . 010 , Levene's test ) . As shown in Fig 2C , the 75th percentile of dN for H-NS-bound HTGs was shifted upward compared with that for H-NS-unbound HTGs ( Fig 2C HTGs; compare the height of the upper edges in boxes and whiskers for H-NS-bound [red] and -unbound HTGs [gray] ) , suggesting that dN of a certain fraction of H-NS-bound HTGs tended to be greater than that of H-NS-unbound HTGs . These results suggested that the observed larger dN for H-NS-bound regions did not result only from the tendency of HTGs to evolve rapidly . To characterize H-NS-bound Core genes , we investigated the conservation of each class of genes in proteobacteria classified into the same family , the same class , or the same phylum with E . coli , using the ortholog table acquired from the Microbial Genome Database for Comparative Analysis ( MBGD ) [43–46] . The results indicated that H-NS-bound Core genes have been less conserved in proteobacteria than H-NS-unbound Core genes , but more conserved than H-NS-bound HTGs ( Fig 2E ) . This result suggested that H-NS-bound Core genes were acquired by ancient ancestors of E . coli . In contrast , the conservation of H-NS-bound HTGs was lowest in bacteria belonging to the same family as E . coli , suggesting that the genes were more recently acquired by ancestors of E . coli . To evaluate whether the adaptation of H-NS-bound Core genes to host cells could be assessed based on gene expression level , quantitative RNA-seq data [47] were analyzed ( Fig 2F ) . This analysis revealed that the expression of both H-NS-bound and -unbound Core genes was greater than that of H-NS-bound and -unbound HTGs , respectively ( Fig 2F; p < 0 . 001 ) . This suggested that H-NS-bound Core genes have adapted to host cells . However , the expression level of H-NS-bound Core genes tended to be lower than that of H-NS-unbound Core genes ( Fig 2F; p < 0 . 001 ) . Interestingly , the analysis indicated that cellular protein level , rather than functional category , essentiality , or metabolic cost of a protein’s amino acid composition , has been the principal driving force constraining non-synonymous substitutions [48] . Therefore , one possible explanation for the tendency of a higher dN in the H-NS-bound Core genes than in H-NS-unbound Core genes might be the H-NS-mediated transcriptional repression of H-NS-bound Core genes . To investigate the relationship between H-NS binding and the evolution of the intergenic regions , we compared sequence diversity between the H-NS-bound and -unbound intergenic regions . To avoid spurious alignments of the intergenic regions caused by recombination , insertion , or deletion , we selected the “conserved” intergenic regions , i . e . , those that were 10–300 bp and were located between two neighbouring orthologous genes in E . coli strains . In addition , after the multiple alignment of each conserved intergenic region , if there was a difference of ≥ 10% in the length of the aligned sequence with at least one strain , the region was considered as a region with an insertion/deletion and it was removed from the set of “conserved” intergenic regions . Furthermore , after the likelihood phylogenetic analysis , the intergenic regions that showed too large an evolutionary distance for accurate alignment ( evolutionary distance > 1 . 0 ) were removed from the analysis . Ultimately , 703 intergenic regions , which included 94 H-NS-bound intergenic regions , were selected for the purpose of calculating sequence diversity ( S3 Table ) . The results indicated that sequence diversity in H-NS-bound intergenic regions tended to be higher than in H-NS-unbound intergenic regions ( Fig 3A; p < 0 . 001 ) , suggesting that the H-NS-bound intergenic regions have evolved faster than the H-NS-unbound intergenic regions . In general , H-NS functions as a transcriptional repressor in E . coli [8] . We investigated whether the higher sequence diversification in the H-NS-bound intergenic regions is related to the regulation of gene expression . We categorized the intergenic regions into two classes ( Fig 3B ) based on the assumption that the regulatory elements for transcription ( i . e . , promoters and binding sites of transcriptional regulators ) are more frequently present upstream of genes than downstream of genes . Class I was defined as the region sandwiched between the tails ( 3’ ends ) of two convergently transcribed genes , representing the non-regulatory intergenic region ( Fig 3B ) ; class II included two subtypes , namely the region sandwiched between the heads ( 5’ ends ) of two divergently transcribed genes ( head-to-head region ) or that between the tail and the head of two genes ( tail-to-head region ) , representing the regulatory intergenic regions ( Fig 3B ) . Then , we compared the sequence diversification between the H-NS-bound and -unbound regions in each class . The sequence diversity of the class I regions tended to be greater than that of the class II regions ( Fig 3C; p < 0 . 001 ) . In addition , there was no significant difference in sequence diversity between the H-NS-bound and -unbound class I regions ( Fig 3D , class I; p = 0 . 29 ) . In contrast , the sequence diversity in the H-NS-bound regions tended to be greater than in the H-NS-unbound regions within the class II regions ( Fig 3D , class II; p < 0 . 001 ) . These results suggested that the regulatory intergenic regions have evolved slower than non-regulatory intergenic regions , whereas the H-NS-bound regions have evolved faster than the H-NS-unbound regions among the regulatory intergenic regions . In addition , we extracted the horizontally transferred intergenic regions ( HTG-intergenic ) sandwiched by HTGs and core intergenic regions ( Core-intergenic ) sandwiched by Core genes , respectively , from the class II intergenic regions to evaluate any difference in the effects of H-NS binding on sequence diversification of HTG- and Core-intergenics . To avoid mixing the Core-intergenic and HTG-intergenic characteristics , which might have occurred in the intergenic regions between Core genes and HTGs , we used the intergenic regions that were uniquely sandwiched only by HTGs or Core genes , as “HTG-intergenic” or “Core-intergenic” , respectively . The sequence substitution rates for H-NS-bound HTG-intergenic were higher than that for H-NS-unbound HTG-intergenic ( Fig 3E; p = 0 . 031 ) . This tendency was also observed in Core-intergenics ( Fig 3E; p < 0 . 001 ) . We thus concluded that the higher sequence substitution rates of H-NS-bound class II intergenic regions could not be explained exclusively by the rapid adaptation of the regulatory regions of recent HTGs . Our analysis indicated that the sequence substitution rate of H-NS-bound regulatory regions was higher than that of H-NS-unbound regulatory regions . We hypothesized that these sequence substitutions in H-NS-bound transcriptional regulatory regions could alter the expression of HTGs . To test this , we selected one of the H-NS-bound HTGs , namely ybdO , which has a large number of sequence substitutions in the upstream intergenic and coding regions ( within the rank of top 50 for sequence substitution rate in the class II and coding regions , S1 Fig ) , and seems to be a single cistron in strains SE11 , SE15 and K12 . In addition , the H-NS binding profile encompassing the upstream and/or coding regions of ybdO was highly conserved among strains SE11 , SE15 , and K-12 , suggesting that H-NS represses ybdO expression in these strains ( S2A Fig ) . Thus , the effects of sequence substitutions within ybdO on its transcriptional regulation were examined . Although the transcription start site of ybdO in K-12 was recently identified [49] ( Fig 4A ) , the transcriptional regulation of ybdO has not been thoroughly investigated . We , therefore , identified transcriptional regulatory elements for ybdO . We systematically constructed ybdO-lac operon fusions on the low-copy-number plasmid , pRW50 [50] , by inserting DNA segments containing upstream intergenic regions and the 5'-proximal coding region of ybdO or its deleted derivatives ( Fig 4A ) . The activities of the ybdO promoters from different E . coli strains were monitored using the recombinant pRW50 plasmids introduced into the E . coli K-12 wild-type and the hns mutant strains . The presence of the Shine-Dalgarno sequence for the lac operon on the plasmids implies that the β-galactosidase activity of transformants represented the transcriptional activity of the particular DNA segment inserted into pRW50 . First , we examined the β-galactosidase activity for ybdO promoters from SE11 , SE15 , and K-12 in cloned L2 fragments , which contained the region from –250 bp to +239 bp ( Fig 4A , L2 , nucleotide positions are relative to the first nucleotide of the initiation codon [+1] of K-12 ybdO ) in growing cells . We found that transcription from the ybdO promoters was maximally induced from the early stationary phase in LB medium ( S2B Fig ) . In addition , ybdO transcription in all strains was higher in the hns mutant cells compared with wild-type cells ( S2B Fig ) , suggesting that H-NS repressed ybdO transcription in all strains . We also determined transcription start sites of ybdO in SE11 and SE15 during the early stationary phase using 5’-RACE as described in Materials and Methods . The 5’ end of SE11 and SE15 ybdO mRNAs was mapped at 1 bp downstream of the transcription start site of K-12 ybdO ( S3A and S3B Fig ) , which localized at 107 bp upstream from the initiation codon of ybdO [49] ( S3B Fig ) . The results suggested that the promoters of ybdO in the three strains overlap ( S3B Fig; putative –10 element is indicated by a red line ) . We then looked closely at regions both upstream and downstream of the ybdO promoter , which revealed a number of sequence substitutions in the promoter proximal region among E . coli strains ( S1B Fig ) . We also determined the elements necessary for H-NS dependent repression by comparing the activities of ybdO-lac operon fusions with systematic deletions in the wild-type and hns mutant strains . The results indicated that deletions of two specific regions , namely upstream ( from –250 to –176 bp ) and downstream ( from +27 to +164 bp ) of the region of the genome surrounding the ybdO promoter in SE11 , SE15 , and K-12 , enhanced β-galactosidase activity in the wild-type cells ( Fig 4B–4D , compare blue bars of L2 and L3 , R2 and R1 ) . In addition , comparison of transcriptional activities of L3 and R1 fragments in the wild type cells with those in the hns mutant indicated that H-NS-mediated repression was abolished or weakened in L3 and R1 fragments in the wild type cells ( Fig 4B–4D , compare blue bars with red bars in L3 and R1 ) , indicating that there are H-NS-dependent negative transcriptional regulatory elements in these regions . We concluded that H-NS represses ybdO expression dependent on these two specific regions—upstream and downstream regulatory regions ( URE and DRE ) —which are in the same location in each of the three E . coli strains ( Fig 4A , bottom of the panel , H-NS-dependent regions ) . URE and DRE are required for H-NS-mediated repression of the bgl and proU operons and repression via URE and DRE is synergistic in both operons [51] . H-NS may bind both URE and DRE to form a bridge and a stable nucleoprotein complex with consequent spreading of H-NS binding away from the high-affinity H-NS binding sites [51] . The URE and DRE of ybdO may also function in a manner similar to that of the URE and DRE for the bgl and proU operons with respect to the effect of H-NS binding . The β-galactosidase assays of the systematic deletions surrounding the ybdO promoter also indicated that there are sequences involved in repression of promoter activity independent on H-NS . The β-galactosidase activity for fragment R2 of SE15 was greater than that for fragment F of SE15 in the hns mutant cells ( Fig 4C , compare red bars in R2 and F ) , suggesting that the region from +164 bp to +239 bp is sufficient to reduce ybdO transcription independent of H-NS in SE15 . In contrast , in the case of SE11 and K-12 , deletion of the same region did not increase the activity for fragment F in the hns mutant cells ( Fig 4B and 4D , compare red bars in R2 and F ) . Rather , deletion of the region from +27 bp to +164 bp ( fragment R1 lacking +27 bp to +164 bp in fragment R2 and +27 bp to +239 bp in fragment F ) increased β-galactosidase activity ( Fig 4B and 4D , compare red bars in R1 and F ) , suggesting that this region reduces ybdO transcription independent of H-NS in SE11 and K-12 . These results indicated that there are H-NS-independent transcriptional regulatory elements that reduce ybdO transcription , and that the location of these elements differs in the ybdO loci of SE11 and K-12 , and SE15; these elements were designated as negative elements ( NE , Fig 4A , bottom panel ) . The β-galactosidase activity for the longest DNA fragment , F , of SE15 was ~2-fold higher than that for SE11 and K-12 in the hns mutant cells ( Fig 4B , 4C and 4D , compare red bars for F of Fig 4C to those of Fig 4B and 4D ) , whereas the fragment LR , lacking negative elements ( URE , DRE and NE ) , showed similar β-galactosidase levels amongst all strains ( Fig 4B , 4C and 4D , compare red and blue bars for LR of Fig 4B or 4C to those of Fig 4D ) . This suggested that in addition to the difference in the locations of NEs for SE15 , and SE11 and K-12 , the ability of NEs to reduce transcription in SE15 , and SE11 and K-12 differed . To confirm the different effects of NEs on the promoter activity , we constructed hybrid DNA fragments of the upstream and downstream regions of ybdO promoter for SE11 and SE15 ( Fig 4E ) . As seen in Fig 4F , the transcription for all hybrid fragments containing the SE11 coding region ( Fig 4F , red bars in lanes a–d ) tended to be lower than all hybrid fragments containing the SE15 coding region in the hns mutant cells ( Fig 4F , red bars in lanes e–h ) . We thus concluded that the diversity of ybdO transcription between SE11 and SE15 is a consequence of sequence divergence downstream of the ybdO promoter , including NEs .
In this analysis , we determined that H-NS-bound regions in E . coli genome have been highly conserved during E . coli evolution . This is supported by the previous finding that H-NS-bound genes are conserved in Salmonella and E . coli [19] . Phylogenetic analysis indicated that the sequence diversity in H-NS-bound regions tended to be greater than that in H-NS-unbound regions . This tendency was limited to the regulatory intergenic regions ( upstream of genes ) and coding regions , in which transcriptional regulatory elements often exist . These findings suggest that H-NS-bound regulatory regions are much freer to evolve than H-NS-unbound regulatory regions because H-NS-mediated repression of genes would reduce the negative impact of sequence substitutions for instances in which such substitutions result in altered expression and/or function of genes that are toxic to host cells . We have also evaluated whether sequence diversity in H-NS-bound regions contributes to variations in transcription using ybdO as a test gene . The results indicate that transcription of ybdO differs among E . coli strains and that ybdO expression is repressed by H-NS in wild-type E . coli . This observation supports our hypothesis that sequence substitutions in H-NS-bound regions contribute to the observed diversity of transcriptional regulation of H-NS-bound genes among E . coli strains , which may provide E . coli strains the opportunity to adapt to new habitats by integrating HTGs . Interestingly , the H-NS-bound orthologous genes located within the “common” segments among SE11 , SE15 , and K-12 significantly overlapped with HTGs ( p < 0 . 001 , Fisher’s exact test; S2 Table ) , which were predicted as HTGs based on at least one prediction method [40–42] . We have also showed , that , in proteobacteria , H-NS-bound Core genes were less conserved than H-NS-unbound Core genes ( Fig 2E ) , suggesting that the H-NS-bound Core genes tend to be genes acquired by ancestors of E . coli . These observations suggest that H-NS-bound genes located within the “common” segments were horizontally transferred into the ancestors of E . coli , and these genes persist in contemporary E . coli strains . Our analysis reveals that the tendency for greater sequence divergence of H-NS-bound intergenic regions compared with those in H-NS-unbound intergenic regions has been limited to regions upstream of genes ( class II intergenic regions ) . This relative greater sequence diversity of H-NS-bound intergenic regions was observed in both types of intergenic regions: HTG-intergenic regions sandwiched by HTGs , and Core-intergenic regions sandwiched by Core genes ( Fig 3E ) . Therefore , the relatively greater sequence diversity in the H-NS-bound class II intergenic regions cannot be explained only by the rapid adaptation of horizontally transferred DNAs to host cells . It is likely that , compared with H-NS-unbound class II intergenic regions , H-NS has made H-NS-bound class II intergenic regions much freer to evolve by repressing the expression of HTGs . It was difficult to clearly determine the contribution of H-NS binding to the observed greater dN values calculated for H-NS-bound genes . We found that the dN values for H-NS-bound Core genes were significantly greater than that for H-NS-unbound Core genes . This can be simply explained by the apparently slower evolution of the H-NS-unbound Core genes because these include many essential genes , including “information” proteins , e . g . , translation-related proteins that have evolved at a significantly slower rate compared with metabolic proteins including those encoded by HTGs [48] , and H-NS-bound Core genes may have been horizontally transferred in ancient ancestors of E . coli . Interestingly , we found that the dS values for H-NS-bound Core genes were also greater than those of H-NS-unbound Core genes ( Fig 2D , Core genes ) . In addition , the expression of H-NS-bound Core genes tended to be lesser than that of H-NS-unbound Core genes ( Fig 2F , Core genes ) . It was known that the dN and dS values for low-expression genes are greater than those of high-expression genes [48] . Therefore , H-NS-mediated repression may increase the sequence diversification of H-NS-bound genes by reducing the expression of H-NS-bound genes . Furthermore , there are H-NS-bound HTGs that have a greater dN than many H-NS-unbound HTGs ( Fig 2C ) . Taken together , our results suggest that H-NS-mediated repression contributes , at least partially , to the observed higher rate of sequence substitution in H-NS-bound coding regions compared with H-NS-unbound coding regions . Recent work indicated that the average mutation rate in regions bound by one of four E . coli nucleoid association proteins ( NAPs ) , H-NS , Fis , IHF-A , IHF-B , in the E . coli genome , is lower than that of NAP-unbound regions [52] . In contrast to the analysis by Warnecke et al . , our analysis indicated that the rate of sequence substitution in H-NS-bound regions was higher than that of H-NS-unbound regions . In our analysis , the effects of H-NS binding were limited to class II intergenic regions and coding regions , while Warnecke et al . reported an average of sequence substitutions at four-fold non-synonymous sites in coding and intergenic regions [52] . Therefore , the apparent discrepancy between our results and those of Warnecke et al . may be a consequence of differences in the genes and protein binding regions used for the two analyses . We also evaluated whether the sequence diversity in H-NS-bound regions could alter transcription of the affected genes . This indeed was the case for at least one of the H-NS-bound genes , namely ybdO . We identified H-NS-independent NEs in the coding regions of ybdO , whose locations and activities differed among E . coli strains ( Fig 4A ) . Although further analyses are needed to reveal the molecular mechanism by which an NE inhibits ybdO transcription , our results suggest that sequence substitutions downstream of ybdO promoters , including NE , dictate the ybdO transcription level . Recently , hundreds to ~20 , 000 RNA polymerase ( RNAP ) pause sites were identified in exponentially growing E . coli cells , and it was suggested that RNAP pausing is one of the common mechanisms by which gene expression is controlled [53–55] . It is difficult to directly evaluate the possibility that RNAP will pause at NEs based on the data from those studies because ybdO expression remained low in exponentially growing cells . Nevertheless , differential pausing of the transcription machinery at NE sites constitutes one possible explanation for the observed variation in NE potency among E . coli strains . The assignment of transcription start sites for ybdO in SE11 , SE15 , and K-12 indicated that the location of the ybdO promoter is conserved among E . coli strains , although we found that the nucleotide sequences in ybdO promoter proximal regions were different ( S3B Fig ) . Although we could not find any typical transcriptional regulator that recognizes sequences affected by substitutions near the ybdO promoter , such substitutions would provide the opportunity to acquire positive regulation because it has been shown that , during evolution , HTGs acquired positive regulation when they became integrated in the host transcriptional network [25] . Because HTGs have contributed to the evolution of host-cell metabolic networks that allow adaptation to new environments [56] , further investigation of ybdO transcriptional regulation under different growth conditions , e . g . , in minimal medium , will be needed to clearly define the effects of sequence substitutions on ybdO promoter function . In our present study , the β-galactosidase assay did not allow us to directly evaluate whether H-NS-mediated repression is crucial for introducing sequence substitutions that alter the transcriptional regulation of HTGs . It is possible that H-NS directly enhances the sequence substitution rate in class II intergenic regions and coding regions by unknown mechanisms . To delineate the importance of H-NS-mediated repression in the evolution of the transcriptional regulation , further investigations must directly evaluate the relationship between transcriptional repression and sequence substitutions , i . e . , in vitro evolution experiments using the hns deletion mutant . It has been reported that variance in gene expression contributes to the heterogeneity of E . coli strains , which could potentiate the ability of E . coli strains to adapt new ecological niches . The mat ( meningitis-associated and temperature regulated ) fimbrial gene cluster is conserved across many E . coli strains [57] . However , B2 group strains have acquired the ability to express mat genes despite H-NS-mediated repression at low temperature , low pH , and high acetate concentration , conditions under which mat is not expressed in strains of groups A and B1 [57] . Differences in mat regulation among E . coli strains is caused by polymorphisms in gene promoters repressed by H-NS [57] . Thus , mat and ybdO might exemplify the biological importance of sequence diversity in H-NS-bound regions for adaptation of E . coli strains to different ecological niches . Based on our observations , we hypothesize that H-NS-mediated repression helps HTGs to adapt their transcriptional regulation to the local environment for host E . coli strains by accelerating the rate of sequence polymorphism in H-NS-bound regulatory regions . This hypothesis is supported by the finding that the optimization of HTG expression was initially found to occur via the evolution of regulatory regions rather than coding regions [58] . Our results support the proposal that H-NS-mediated repression is a valuable mechanism by which host cells can integrate HTGs into the host transcriptional regulatory network [3] .
The primers used in this study are listed in S4 Table . Strains used in this study are listed in S5 Table . To generate the K-12 ( W3110 ) derivative expressing H-NS C-terminally tagged with 12 histidines ( 12His ) , we used a modified one-step gene inactivation method [59] . Plasmid pSTV28-C-12His , which was kindly provided by Dr . Mika Yoshimura , was constructed by inserting the chemically synthesized 12His coding sequence and a kanamycin resistance gene derived from plasmid pKD4 [59] into the multiple cloning site of pSTV28 ( Takara Bio , Japan ) . We amplified a DNA fragment containing the 12His sequence flanked with the Arg-Gly-Ser linker and kanamycin resistance gene by PCR using pSTV28-C-12His and the TOP705-TOP706 primer set . To facilitate insertion of the PCR product into the chromosome , we added a ~70-bp sequence of the hns coding region and its downstream region to the TOP705 and TOP706 primer sequences , respectively . The BW25113 cells harboring pKD46 encoding Red recombinase [59] were transformed with the amplified DNA fragment , and transformants in which linker and 12His sequences were inserted at the 3’ end of the chromosomal hns through a double-crossover at the coding and downstream regions of hns , were selected with kanamycin to obtain the K-12 ( BW25113 ) H-NS-12His strain . hns fused with the 12His sequence was transferred into the K-12 ( W3110 ) chromosome , together with the kanamycin resistance gene , via phage P1 transduction . Because the SE11 and SE15 strains are resistant to P1 , to construct the derivatives expressing 12His-tagged H-NS , we adopted the gene-doctoring method [60] using plasmid pDEX harboring an I-SceI recognition site and sucB and pACBSR harboring I-SceI and the kanamycin resistance gene [61] . The 12His coding sequence and kanamycin resistance gene in pSTV28-C-12His were amplified by PCR using primers hns-His12-H1 and hns-His12-H2-1 ( for SE11 ) or primers hns-His12-H1 and hns-His12-H2-2 ( for SE15 ) . Amplified fragments were inserted into the EcoRV site of pDEX . SE11 and SE15 were co-transformed with two plasmids—pACBSR and the appropriate pDEX-H-NS-His12—with subsequent selection for kanamycin and sucrose resistance . Transformants were cultured in LB liquid medium containing 25 μg/ml chloramphenicol and 0 . 2% arabinose for a few hours , inducing inactivation of pDEX-H-NS-His12 by I-Sce1 . Cells were harvested by centrifugation and regrown in LB liquid medium containing 5% sucrose at 30°C for 2 h to cure pACBSR . Finally , kanamycin- and sucrose-resistant colonies were selected on an LB plate containing 50 μg/ml kanamycin and 5% sucrose to isolate transformants in which the 12His sequence and kanamycin resistance gene were integrated into the chromosome via homologous recombination at the hns coding sequence and sequences downstream of hns introduced at the 5’ and 3’ ends of the PCR products , respectively . Expression of H-NS-12His in the created strains was confirmed by western blotting using an antibody against His tag ( MBL , Japan ) . Sequencing of the introduced hns tagged with 12His revealed a point mutation within the hns coding region in the K-12 derivative , probably attributable to an error during synthesis of the primer used to generate the strain . Because the identified point mutation ( from AAG [136K] to AAA [136K] ) did not lead to an amino acid substitution in H-NS , the strain was employed for further analysis . Noteworthy , the C-terminal 12His tag did not negatively affect the growth of K-12 , SE11 and SE15 in Luria-Bertani ( LB ) medium under aerobic conditions . The hns deletion mutant ( MC4100 Δhns::Km ) used in the β-galactosidase assay was constructed using P1 transduction of the hns::km allele from K-12 ( W3110 ) hns::km [62] into MC4100 . ChAP was performed according to the reported procedure [34] using 50-ml cultures of E . coli grown in LB medium under aerobic conditions at 37°C . DNA fragments that co-purified with H-NS-12His and in the supernatant fraction before ChAP were sequenced using the Illumina GA sequencer ( Illumina , USA ) . We performed ChAP-seq experiments twice for each strain , and 36-bp single-end reads provided 8–11 million reads ( first set of sequencing results of ChAP and WCE fractions of three strains ) and 5–10 million reads ( second set ) . The sequence data used in this publication have been deposited in the DRA database ( DDBJ Sequence Read Archive: http://trace . ddbj . nig . ac . jp/dra/index_e . shtml ) with accession number: DRA000539 . Complete sequences and annotations of genes in the three genomes ( SE11 [AP009240 . 1] , SE15 [AP009378 . 1] , and K-12 [W3110; AP009048 . 1] ) were obtained from the NCBI GenBank database . We compared the three chromosome sequences and their synteny of gene arrangement using the Mauve 2 . 3 . 1 program for Progressive Mauve algorithm with default parameters [35 , 36] and determined the segments that were conserved in all three strains ( “common” ) and unique to two ( “shared” ) or one ( “specific” ) strain ( s ) . The K-12 ( W3110 ) chromosome contains a large inverted region ( ~800 kbp ) surrounded by two ribosomal operons ( 3 , 423 , 096–4 , 216 , 800 bp ) . To avoid eliminating this region from “common” segments by the above analysis , we manually reversed this region in the chromosome sequence of K-12 ( W3110 ) before alignment using the Mauve program . The sum of the consensus sequences of “common” segments was 3 , 888 , 365 bp . However , the DNA sequences of “common” segments in each strain occasionally had small gaps compared with the consensus “common” segments of all three strains . Thus , the total length of the “common” segment in each strain was shorter than that of the consensus segments , specifically , SE11: 3 , 886 , 369 bp , SE15: 3 , 886 , 157 bp , K-12 ( W3110 ) : 3 , 886 , 242 bp . Short reads ( 36 bp ) obtained from the Illumina GA sequencer were uniquely mapped on to the reference genome sequences of K-12 ( W3110 ) , SE11 , and SE15 , allowing no gaps and up to two mismatches using the BLAT program [63] . Because the purpose of this study was to compare the DNA binding profiles of H-NS in these three strains , we mapped the short reads only on the chromosome in each strain . Uniquely aligned reads were specifically used for further analysis . In addition , because it is impossible to specifically map 36-bp reads to one of seven rRNA genes in the E . coli genome and the rRNA genes were not used for the phylogenetic analysis , rRNA coding regions were not included in this study . Next , mapped reads were extended to 200 bp in length from the 3’ end of each read , taking into account the length of DNA fragments to construct the sequence library . We subsequently normalized the number of mapped read numbers at every nucleotide in each experiment by global scaling , in which the number of mapped reads at each nucleotide was divided by the median number of mapped reads at all nucleotides in each sample . Finally , to estimate the H-NS binding intensity at every nucleotide , we divided the scaled number of mapped reads for DNA from the ChAP fraction by that from WCE before ChAP-mediated purification to remove the effects of sequence preference of Illumina GA . In cases where the number of mapped reads at some positions was zero for the ChAP or WCE fraction , the H-NS binding intensity of the position was defined as zero . As H-NS binding intensity spanned a wide range of values , log10-scaled values were used for subsequent analysis . To evaluate our normalization procedure in the comparison of different sequencing outputs , the average H-NS binding intensity in 200-bp windows was calculated in 100-bp steps along whole-genome sequences . Scatter plots shown in S4A Fig demonstrate that correlation coefficients of estimated average H-NS binding intensities in each window obtained in all experiments for each strain were high ( r > 0 . 8 ) . In addition , correlation coefficients of the binding intensities of corresponding windows in “common” segments of different strains were greater than 0 . 69 for all combinations ( S4B Fig ) , indicating that our normalization procedure was adequate . H-NS binding intensity showed a bimodal distribution of “noise” components at ~1 . 0 , and “signal” components , which ranged from 10 . 0 to 1000 . 0 ( S5 Fig ) . In four experiments ( all data from the 1st experiment and K-12 data from the 2nd experiment ) , the bimodal distribution was clear , and noise components could be clearly discriminated from signal components . In these cases , noise components could be approximated as a normal distribution in which μ represents mode and σ is 0 . 2 ( S5 Fig ) . Thus , we set the threshold value to remove noise components as mode + 3σ ( = 0 . 6 ) . In the two remaining experiments ( data for SE11 and SE15 in the 2nd experiment ) , noise components were not clearly separable from signal components , and the two possibly overlapped . However , we referred to the threshold value from other experiments ( mode + 0 . 6 ) to infer signal components in these cases ( S5 Fig ) . Next , we searched for regions in which H-NS binding intensity was greater than the threshold . To remove the effects of the remaining noise signals by our threshold setting , we extracted regions longer than 200 bp as possible H-NS binding sequences . Finally , we compared the H-NS-bound regions obtained in the two experiments for each strain , and overlapping regions were identified as H-NS-bound regions for further analysis . To evaluate the accuracy of our mapping and determination of H-NS-bound regions , we required the second mapping result of our short reads that was acquired with a different mapping program , namely Bowtie 2 [64] , and we also required a determination of H-NS-bound regions with the Bowtie 2 mapping results . Comparison of H-NS-bound regions determined by BLAT mapping ( original result ) and by Bowtie 2 mapping ( second mapping ) indicated that the H-NS-bound regions that were determined with the two mapping procedures were 97% identical . This result clearly indicated that our mapping and determination of H-NS-bound regions were highly reliable , and thus we conducted subsequent analyses using the BLAT mapping results for the H-NS-bound regions . The reproducibility of H-NS binding profiles for the whole genome of each strain ( SE11 , SE15 , K-12 ) are indicated in S6 Fig . In addition , the conservation of H-NS-bound regions in “common” segments within each whole genome is presented in S7 Fig . The 44 E . coli strains whose genome sequences had been annotated in RefSeq were used for our phylogenetic analysis ( S1 Table ) . All chromosome sequences and the annotations of the 44 strains were obtained from the RefSeq ( NCBI Reference Sequence database ) . Because RefSeq represents reference sequences for which gene annotation is consistent and standardized , it enabled us to precisely identify orthologous genes in the E . coli lineage . To identify the conserved orthologous genes in the E . coli strains , we initially evaluated the level of conservation of the amino acid sequence translated from each gene . We carried out all-against-all reciprocal BLASTP comparisons for all proteins in all strains followed by clustering of the BLASTP hits using OrthoMCL [65] . To remove genes encoding mobile elements , duplicate genes , and pseudogenes , which have repetitive sequences , and paralogs that interfere with phylogenetic analysis , the proteins encoded by prophage and insertion ( IS ) genes were searched by BLASTP against the ACLAME database [66] and ISFinder [67] and excluded from further analysis . Paralogs and hidden paralogs were also removed from the orthologous proteins by excluding the gene clusters containing more than two copies of the proteins present in one strain . Then , we selected the 3 , 107 orthologous proteins ( gene clusters ) that were conserved in >90% of strains ( 40 of 44 ) , in which K-12 , SE11 , and SE15 were always included . From the selected orthologous proteins , the 405 orthologous proteins encoded by genes that had at least one broken codon with one or two nucleotide deletions or insertions in at least one strain were excluded to remove pseudogenes . Ultimately , 2 , 702 orthologous protein clusters were selected for subsequent analysis ( S8 Fig ) . Multiple sequence alignment for each orthologous protein cluster was performed using MAFFT [68] ( G-INS-i algorithm ) and back-translated into the aligned nucleotide sequence . GBLOCKs [69] ( codon model , default settings ) was used to remove gaps and unreliably aligned positions . To assess the accuracy of our orthologous gene sets , we constructed a representative phylogenetic tree based on the concatenated super-alignment . We concatenated the alignments of 100 randomly chosen orthologous genes and inferred the maximum likelihood ( ML ) tree using PhyML [70] with the following parameters: -b 100 -d nt -m HKY85 -v 0 -c 4 -a 1 . The resulting ML tree reflected the phylogenic relationships revealed in previous studies [71] ( S9 Fig ) . The dN and dS values for orthologous genes were computed using Codeml from PAML [72] ( settings: tree = ML gene tree from PhyML , CodonFreq = F3X4 , clock = 0 , kappa = estimated by ML , omega = estimated by ML , alpha = 0 , rho = 0 ) . In this analysis , we identified H-NS-bound genes as those that overlapped with H-NS-bound regions determined in at least one strain of SE11 , SE15 , and K-12 , because the H-NS-bound regions in common segments were essentially overlapping . To evaluate this classification , we manually inspected H-NS binding signals in each H-NS-bound gene , which also indicated that , even if the H-NS-bound region overlapped with the H-NS-bound gene in only one or two strains , possible H-NS binding signals were observed in the H-NS-bound gene in the other strains , albeit the H-NS binding intensity for the gene was lower than the threshold value in most cases . There were 42 genes ( S6 Table ) that were specifically bound by H-NS in only one or two strains , in which H-NS binding was dependent on the specific or shared segments that were localized in the vicinity ( in many cases , neighbors ) of these 42 genes in the chromosomes ( a typical example is presented in S10 Fig , where ytfI is the H-NS-bound specific segment ) , because H-NS binding was not detected for strains in which the specific segments were absent from the chromosomes . Therefore , we regarded these 42 genes as H-NS-unbound genes . We verified the significance of the higher dN in the H-NS-bound regions compared with that in the H-NS-unbound regions by modifying the definition of the H-NS-bound genes . The results indicated that the dN of the H-NS-bound genes was significantly greater than that of the H-NS-unbound genes , even when we excluded the genes in which H-NS binding was limited to the 3’ end and the length overlapping with the H-NS-bound regions was ≤10% of the total gene length or if the genes included in transcriptional units whose promoters , intergenic , or coding regions could bind H-NS were considered as H-NS-bound genes ( S11B and S11C Fig ) . Furthermore , even when we regarded the 42 genes that bound to H-NS in a specific- or shared segment—dependent manner ( described above ) as H-NS-bound genes , the dN in the H-NS-bound genes was still significantly greater than that in the H-NS-unbound genes ( p < 0 . 001 ) . These results suggested that our conclusion concerning the sequence diversity of H-NS-bound genes was not affected by the definition of the H-NS-bound genes . Although we carefully selected orthologous genes based on the above criteria , it was possible that horizontal gene transfer and recombination events among E . coli strains might have affected our results—particularly the horizontal transfer and recombination events in H-NS-bound orthologous genes . To validate the potential effects of horizontal transfer and recombination events on our analysis , we calculated minimal tree split compatibilities between H-NS-bound and -unbound orthologs by which we could evaluate whether the genes had been vertically evolved in the E . coli lineage [73 , 74] . If the orthologs were present in the ancestral E . coli genome before the divergence of the E . coli lineage and had not been involved in horizontal transfer or recombination events among E . coli strains , their phylogenies should be similar . Therefore , if H-NS-bound orthologs tend to be transferred horizontally more so than H-NS-unbound orthologs , phylogenies of trees would differ between H-NS-bound and -unbound orthologs . To avoid a sample-size bias , we reconstructed five datasets: set A , trees of H-NS-unbound orthologs ( N = 2 , 183 ) ; set B , trees of H-NS-bound orthologs ( N = 519 ) ; set C , trees of downsampled H-NS-unbound orthologs ( N = 519 , randomly sampled without replacement ) ; set D , trees of H-NS-bound orthologs with a simulated horizontal transfer event ( N = 519 , constructed by a minimal perturbation of set B where for each tree a randomly selected branch was pruned and then regrafted at a random branch ) ; set E , trees of H-NS-bound orthologs with two simulated horizontal transfer events ( N = 519 ) . We used set A as a reference dataset and calculated minimal tree split compatibilities for each tree in sets B , C , D , and E against set A . The distributions of compatibility scores for each dataset were compared using the two-sided Kolmogorov-Smirnov test . We could not reject the null hypothesis that H-NS-bound and H-NS-unbound tree sets were drawn from the same distribution ( S12 Fig , p = 0 . 16 ) , whereas the slightest perturbation ( a single horizontal transfer event ) strongly rejected the null hypothesis ( S12 Fig , p < 0 . 001 ) . This suggested that there was no bias for sequence substitutions caused by horizontal gene transfer or recombination events by which the number of H-NS-bound orthologs would have been much greater than H-NS-unbound orthologs . It is also known that gaps in alignments can reduce the accuracy of the estimation of sequence diversity because of the difficulty in achieving an accurate alignment around gap positions [75] . Thus , we calculated the dN and dS values for coding regions only using the orthologous gene clusters without gaps in their alignments and compared the sequence substitution rates in H-NS-bound and -unbound regions . The results are shown in S13A and S13B Fig . The sequence diversity at non-synonymous positions in the H-NS-bound coding regions was significantly greater than that in H-NS-unbound regions . Therefore , this result suggested that our conclusion concerning the sequence diversity of coding regions was not affected by misalignment caused by insertions/deletions in coding regions . When we investigated the conservation of the four classes ( H-NS-bound HTGs , H-NS-unbound HTGs , H-NS-bound Core genes , and H-NS-unbound Core genes ) of genes in proteobacterial species classified in the same family , the same class , or the same phylum as E . coli , MBGD was used for the comparison of the conservation of genes [43–46] . First , we constructed the ortholog cluster table by using 48 completely sequenced bacterial genomes from MBGD . Of these 48 genomes , one was E . coli K-12 MG1655 , 25 strains belonged to the same family but different genus than E . coli ( family Enterobacteriaceae ) , 14 strains belonged to the same class but different family than E . coli ( class Gammaproteobacteria ) , and 8 were strains belonged to the same phylum but different class than E . coli ( phylum Proteobacteria ) . Strains used in this analysis are listed in S7 Table . For clustering parameters , we used the default values of MBGD . From this ortholog cluster table , we searched our E . coli orthologous genes by gene name . In total , 2 , 098 genes were identified ( H-NS-bound HTGs: N = 157; H-NS-unbound HTGs: N = 224; H-NS-bound Core genes: N = 174; H-NS-unbound Core genes: N = 1 , 543 ) . Then , we checked for the presence or absence of these genes in each of the 48 genomes ( S14 Fig ) . The conservation rate for each class of genes was calculated for each genome separately . Finally , the average conservation rates were calculated separately for the same family genomes , the same class genomes , and the same phylum genomes , and we compared these values for each class of genes . Intergenic regions used for phylogenetic analysis should be carefully selected because these regions often have large insertion/deletion sequences that lead to spurious alignments . We defined "conserved" intergenic regions as the regions presently between two neighbouring orthologous genes we had determined ( see above ) in the same order and direction in E . coli strains in which these orthologous genes were identified . In addition , we selected the regions whose length was no less than 10 bp nor more than 300 bp in all chromosomes . The multiple alignment of each set of conserved intergenic regions was performed using MAFFT ( G-INS-i algorithm ) . After the multiple sequence alignment , we selected a cluster in which the lengths of all intergenic regions in each cluster were different , less than 10% of the aligned sequence length of a cluster , implying that no intergenic regions with long insertions and/or deletions were used for subsequent analyses . Consequently , 712 regions were selected as conserved intergenic regions ( average length was 94 . 8 bp ) . We then estimated the sequence diversity matrices for those intergenic regions using Baseml from PAML ( setting: tree = ML tree from PhyML , model = 7 , clock = 0 , kappa = 2 . 5 ( starting value ) , fix_kappa = 0 ( ML estimation of kappa ) , alpha = 0 , fix_alpha = 1 ( fixed value ) , rho = 0 , fix_rho = 1 ( fixed value ) , npark = 0 , nhome = 0 , Mgene = 0 . ) . In addition , we removed sets in which the evolutionary distance of at least a pair of strains was >1 . 0 , meaning that the sequences of those regions were too divergent to yield a correct alignment . Finally , we selected the 703 conserved intergenic regions , including 94 H-NS-bound intergenic regions that overlapped with the H-NS-bound regions identified in at least one strain , and compared the sequence diversification rates in intergenic regions bound or not bound to H-NS . In this analysis , we also calculated the sequence substitution rate for each intergenic region only using the set of the intergenic regions without gaps and concluded that the sequence diversity of intergenic regions was not affected by any potential misalignment caused by insertions/deletions in coding regions ( S13C Fig ) . We further assessed the impact of the presence of a promoter ( s ) on the extent of proximal sequence diversification . The intergenic regions with known promoters were selected from the class II regions using the information about promoters in the K-12 strain acquired from RegulonDB [76] . The sequence diversity of the H-NS-bound regions was greater than that of the H-NS-unbound regions , although the difference in sequence diversity between H-NS-bound and H-NS-unbound was even greater in regions with known promoters than in the regions without known promoters ( S15 Fig; p < 0 . 001 [with known promoters] , p = 0 . 0079 [without known promoters] ) . These results suggested that the presence of other transcriptional regulatory elements , such as pause and termination signals , may also affect the observed H-NS binding—dependent increase of sequence substitution rates . Total RNA was extracted and purified from E . coli K-12 ( MC4100 ) transformed by pRW50 carrying LR fragments , in which the major negative regulation of ybdO in an H-NS-dependent or -independent manner were cancelled by the deletion of the NEs , URE , and DRE for SE11 and SE15 using the RNeasy Mini kit ( Qiagen ) . RACE was performed with First-Choice RLM-RACE kit ( Ambion ) using the manufacturer’s manual with modifications . Specifically , RNA ( 5 μg ) was treated with tobacco acid pyrophosphatase or left untreated , and then the 5’ RACE adaptor was ligated to each RNA molecule . cDNA was synthesized from adapter-attached RNA with a random decamer . The 5’ end of ybdO was amplified by PCR with primers ( 5’ RACE Outer Primer and ybdO-D2: CAAGTCGTAGAGATTGGCCATACA [for SE11 ybdO] or ybdO-SE15-D2: TAGATCATAAAGATTAGCCATAAC [for SE15 ybdO] ) , and products were visualized after electrophoresis in Gel-Red containing agarose gel and cloned with pGEM-easy ( Promega ) . Sequences of cloned fragments were determined and 5’ ends were mapped on the genome sequences of SE11 and SE15 . The raw data and their tables are available in our web page , http://palaeo . bio . titech . ac . jp/Resources/hns2015/ . | Horizontal gene transfer among bacteria is the major means of acquiring genetic diversity and has been a central factor in bacterial evolution . The expression of horizontally transferred genes could potentially be optimized to permit the host bacteria to expand their habitat . The results of our study suggest that DNA regions bound by the nucleoid-associated protein , H-NS , which preferentially binds to horizontally transferred genes , have been conserved during Escherichia coli evolution . Interestingly , H-NS-bound regions have evolved faster than H-NS-unbound regions , but only in gene regulatory and coding regions . We show that DNA sequence substitutions in H-NS-bound regions actually alter the regulation of gene expression in different E . coli strains . Thus , our results support the hypothesis that H-NS accelerates the diversification of the regulation of horizontally transferred genes such that their selective expression could potentially allow E . coli strains to adapt to new habitats . | [
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] | [] | 2016 | H-NS Facilitates Sequence Diversification of Horizontally Transferred DNAs during Their Integration in Host Chromosomes |
Household contacts of multibacillary leprosy patients ( HCMB ) constitute the group of individuals at the highest risk of developing leprosy . Early diagnosis and treatment of their index cases combined with Bacille Calmette-Guerin ( BCG ) immunization remain important strategies adopted in Brazil to prevent HCMB from evolving into active disease . In the present study , we assessed the impact of these measures on the immune response to Mycobacterium leprae in HCMB . Peripheral blood mononuclear cells ( PBMC ) from HCMB ( n = 16 ) were obtained at the beginning of leprosy index case treatment ( T0 ) . At this time point , contacts were vaccinated ( n = 13 ) or not ( n = 3 ) in accordance with their infancy history of BCG vaccination and PBMCs were recollected at least 6 months later ( T1 ) . As expected , a significant increase in memory CD4 and CD8 T cell frequencies responsive to M . leprae whole-cell sonicate was observed in most contacts . Of note , higher frequencies of CD4+ T cells that recognize M . leprae specific epitopes were also detected . Moreover , increased production of the inflammatory mediators IL1-β , IL-6 , IL-17 , TNF , IFN-γ , MIP1-β , and MCP-1 was found at T1 . Interestingly , the increment in these parameters was observed even in those contacts that were not BCG vaccinated at T0 . This result reinforces the hypothesis that the continuous exposure of HCMB to live M . leprae down regulates the specific cellular immune response against the pathogen . Moreover , our data suggest that BCG vaccination of HCMB induces activation of T cell clones , likely through “trained immunity” , that recognize M . leprae specific antigens not shared with BCG as an additional protective mechanism besides the expected boost in cell-mediated immunity by BCG homologues of M . leprae antigens .
Leprosy is a global disease with no efficient means for early diagnosis or prevention . While disease prevalence has dropped significantly over the past three decades , it has not been completely eliminated ( averaging between 200 , 000–250 , 000 new cases each year ) [1] . Leprosy constitutes a public health threat particularly in Brazil in that about 30 , 000 new cases are reported per annum [2] . Thus , understanding the human immune response to this pathogen remains an important challenge in the development of novel tools for leprosy control . Mycobacterium leprae , the causative agent of leprosy , is a highly infectious obligate intracellular bacterium . Although the vast majority of those exposed to M . leprae becomes infected , only a small proportion evolves into active disease . Previous work in leprosy and tuberculosis has revealed the major role played by interferon-γ ( IFN-γ ) , an effector cytokine produced by pathogen-specific memory CD4 T cells , in the control of the infection by these intracellular pathogens [3][4] . Leprosy is manifested across a broad spectrum of clinical forms that are determined by the intensity of an individual´s cellular immune response to M . leprae . The paucibacillary ( PB ) [polar tuberculoid] ( TT ) , and borderline tuberculoid ( BT ) ] forms of leprosy manifest a contained , self-limited infection with few lesions in which scarce bacilli are detected in consequence of the cellular immune response against M . leprae . In contrast , the reduced specific cellular immunity in patients with the multibacillary ( MB ) forms of the disease [lepromatous ( LL ) and borderline lepromatous ( BL ) ] results in an uncontrolled proliferation of the leprosy bacillus accompanied by many lesions and extensive infiltration in the skin and nerves . MB patients are considered the main source of M . leprae transmission since they carry a high bacterial load in their skin and are able to shed large numbers of bacteria from their nasal passages at a daily average of 107 viable M . leprae [5] . Thus , household contacts of MB leprosy patients ( HCMB ) are at the highest risk of developing leprosy due to their proximity with their index cases and consequent overexposure to M . leprae . In fact , the risk of illness among HCMB is 8–10 times higher than that of healthy individuals residing in endemic areas but with no domiciliary exposure to MB leprosy [6] . Some studies have shown this risk to be even more elevated among contacts carrying specific antibodies against the phenolic glycolipid-I ( PGL-I ) antigen [7][8][9] , a unique molecule located in the M . leprae cell wall . Despite the fact that leprosy contacts constitute a group at a high risk to develop leprosy , only about 7% of them will progress to active disease[10][11] . Evidence indicates that persistent exposure to M . leprae leads to a reduced lymphoproliferation to M . leprae antigen , which improves as a result of index case treatment [12] . Recent data have confirmed and added to this previous finding , linking persistent exposure to M . leprae and/or bacillary load in leprosy patients with hyporesponsiveness to M . leprae-specific antigens . A high level of the ex vivo IFN-γ response to M . leprae-specific peptides was observed in nearly all the exposed healthy individuals . However , there was a progressive reduction in these levels that correlated with the exposure level to M . leprae infection . The IFN-γ levels were lowest among HCMB when compared to PB household contacts and individuals residing in an hyperendemic leprosy area but with no history of contact with the disease [13] . It is well established that BCG confers protection against leprosy [14][15][16] . Since 1991 , the Brazilian Ministry of Health ( BMH ) has officially recommended that household contacts ( HC ) of leprosy patients must be revaccinated with BCG to boost the efficacy of the first dose given to newborns as a tuberculosis prophylactic vaccine . The rationale for the use of BCG as a vaccine against leprosy relies on the knowledge that M . leprae and M . bovis BCG share many antigens with a high degree of homology [17] . In leprosy HC , the vaccine is administered irrespective of tuberculosis or leprosy skin test results . HC with no BCG scar at all or with only one are vaccinated with BCG . Healthy HC with two BCG scars are not vaccinated [18] . In Brazil , the impact of this policy , assessed in a cohort study of 3536 contacts of 1161 leprosy patients , revealed that the protection conferred by a booster BCG vaccine was 56% . The strain used in Brazil is known as BCG Moreau whose complete genome sequence has recently been deciphered [19] . Although both the BCG vaccination and index case treatment decrease the risk of household contacts contracting leprosy [9] , the changes in the immune response induced by these two measures that could possibly explain the resulting protective effect have yet to be investigated in detail . In the present work , a prospective study was conducted to assess the impact of BCG vaccination and index case treatment on the ex vivo frequencies of CD4+ and CD8+ T cells responsive to M . leprae specific and shared mycobacterial antigens . The patterns of the cytokine/chemokine responses of the peripheral blood mononuclear cells ( PBMC ) stimulated in vitro with the same antigens were also studied . A better understanding of the mechanisms responsible for the BCG-conferred protection against leprosy and the down modulation of the M . leprae-specific immune response by the overexposure to live bacteria among leprosy contacts could contribute to defining the biomarkers of protective immunity against mycobacteria and lead to the development of better and more effective vaccines .
Ethical approval of this study was obtained from the Oswaldo Cruz Foundation Committee for Ethics in Research . Participants were informed about the study objectives together with the required amount and kind of samples . Written and informed consent was obtained from study participants before enrollment . A total of 16 household contacts of multibacillary leprosy patients ( HCMB ) with an average age of 37 ± 13 years , consisting of 11 females and 5 males under surveillance at the Souza Araújo ( Fiocruz ) Outpatient Clinic ( Reference Center for Leprosy Diagnosis and Treatment , Oswaldo Cruz Foundation ( FIOCRUZ ) , in Rio de Janeiro , RJ , Brazil , were enrolled in the study . All participants resided in the State of Rio de Janeiro , which , in 2013 , had a new leprosy case detection rate of 7 . 36/100 000 individuals . HCMB were assessed for the presence of a BCG scar and the absence of clinical signs and symptoms of leprosy via routine examinations ( dermatological , neurological , and/or physiotherapeutic assessments ) . Serology was carried out via ML Flow or ELISA for detection of anti-PGL-I IgM . HCMB received 0 . 1 ml of BCG ( Ataulpho de Paiva Foundation , Rio de Janeiro , RJ , Brazil ) intra-dermally in the deltoid region of the arm at about one-third down the upper arm over the insertion of the deltoid muscle [20] . Irradiated armadillo-derived M . leprae whole cells were probe sonicated with a Sanyo sonicator to 95% breakage . This material was provided by the NIH/NIAID ‘‘Leprosy Research Support” Contract N01 AI-25469 from Colorado State University ( USA ) ( These reagents are now available through the Biodefense and Emerging Infections Research Resources Repository listed at https://www . beiresources . org/Catalog/antigen/NR-19329 . aspx Synthetic peptides of 15 amino acids corresponding to class II M . leprae-specific epitopes were produced by Peptide 2 . 0 Inc . ( Chantilly , VA , USA ) . For the present study , 13 HLA class II-restricted , M . leprae–specific peptides [p38 , p51 , p56 , p59 , p65 , p67 , p70 , p71 , p88 , p91 , and p92 ( 10 μg/ml each ) ] of 15 amino acids were combined and used as a pool for culture stimulation . These peptides correspond to M . leprae epitopes that share any or low similarity with BCG and are referred to as M . leprae specific in this study . They were previously tested for the induction of IFN-γ- in the PBMC of leprosy patients and their contacts , and of healthy controls in both endemic and non-endemic areas for leprosy . Only responses in leprosy patients and in healthy individuals exposed to M . leprae were observed , indicating that they specifically detect individuals infected with M . leprae [21] . Peripheral blood mononuclear cells ( PBMCs ) obtained from heparinized blood were isolated using Ficoll-Paque ( GE Healthcare Life Sciences Pittsburgh , PA , USA ) and resuspended in AIM V medium ( Invitrogen , Grand Island , NY , USA ) supplemented with 100 U/ml penicillin , 100 mg/ml streptomycin , and 2 mM L-glutamine ( Sigma Chemical , St . Louis , MO , USA ) . PBMC from each individual were seeded at 2 x 106 cells per well and stimulated with anti-CD28 [1μg/ml] and anti-CD49d monoclonal antibodies [1μg/ml] ( BioLegend , San Diego , CA , USA ) plus armadillo-derived M . leprae cell sonicate ( 20 μg/ml ) , M . leprae-specific peptides [10μg/ml each] , or staphylococcal enterotoxin B ( SEB , 1μg/ml; Sigma ) for a period of 6 hrs before the flow cytometry analysis . Protein transport inhibitor ( Brefeldin A—BD , San Jose , CA , USA ) was added during the last hour of incubation . In parallel , 2 x 105 cells were seeded in 96-well plates and stimulated with the M . leprae cell sonicate ( 20 μg/ml ) , M . leprae-specific peptides ( 10 μg/ml each ) , or SEB ( 1μg/ml ) for 5 days . Supernatants were collected and immediately stored at -20°C until use . After a 6-hr culture , the cell populations were stained with a live/dead fixable violet dead cell stain kit ( Invitrogen , Carlsbad , CA , USA ) for distinction of dead cells according to the manufacturer's instructions , and the following monoclonal antibodies were used: anti-hCD3-V500 , anti-hCD4-PerCP , anti-hCD8-Alexa 700 , anti-hCD69-APCCy-7 , anti-hCD45RO-PECY7 , or CD45RA-PECY7 / anti-hCD62L ( BioLegend , San Diego , CA and BD biosciences San Jose , CA , EUA ) . Flow cytometric analysis was performed using a FACSAria IIu flow cytometer ( BD Biosciences ) and the FlowJo software version 7 . 5 ( FlowJo LLC , Ashland , OR , USA ) . A multiplex biometric immunoassay containing fluorescent-dyed microspheres conjugated with a monoclonal-specific antibody for a target protein was used for measurement of inflammatory mediators according to the manufacturer´s instructions ( Bio-Plex Pro Human Cytokine 17-plex Assay; Bio-Rad Inc . , Hercules , CA , USA ) . The mediators measured were: IL-1β , IL-2 , IL-4 , IL-5 , IL-6 , IL-7 , IL-8 , IL-10 , IL-12 ( p70 ) , IL-13 , IL-17 , G-CSF , GM-CSF , MCP- , MIP-1β , IFN-γ , and TNF mediator levels were determined by a multiplex assay reader from the Luminex Instrumentation System ( Bio-Plex Workstation from Bio-Rad Laboratories , Inc . ) . Analyte concentration was estimated according to the standard curve using the Bio-Plex Manager software provided by the manufacturer . Values of unstimulated cultures were discounted from all stimuli . Graphs were created using the GraphPad Prism 5 software ( GraphPad Software , La Jolla , CA , USA ) , and the paired nonparametric Wilcoxon test was utilized to perform statistical analyses . A p value of 5% or less was considered significant . Medians were compared by either the Wilcox Signed Rank Test ( for paired groups ) or the Mann-Whitney Test ( for unpaired groups ) . For association analyses , Spearman's Rank Correlations Coefficient with the Bonferroni correction of the family-wise error rate was adopted . Multivariate principal component analysis ( PCA ) was performed for dimension reduction and visualization using the R version software 3 . 1 . 2 . [22][23]
A prospective study was conducted in HCMB to evaluate the impact of BCG vaccination and interruption of persistent exposure to live M . leprae by treating their index case on the ex vivo immune response to the pathogen . Blood was collected from the HCMB for comparative evaluation at the outset of the MB leprosy index case treatment prior to BCG contact vaccination ( T0 ) and at least 6 months after the beginning of treatment ( T1; Fig 1 ) . The BCG vaccine was administered to contacts according to their vaccination history . As shown in Table 1 , 13 out of the 16 HCMB were vaccinated at T0 , 5 of whom received their first BCG dose and 8 , a second dose due to their BCG scar . Three did not receive the vaccine at T0; 2 had previously received two doses ( presence of 2 BCG scars ) , and the third , with no BCG scar , was suspected of leprosy and not vaccinated . However , this particular HCMB did not become ill during follow up . Ten HCMB were found to be seropositive to anti-PGL-I . However , no correlation between seropositivity to PGL1 and index case BI was observed ( Table 1 ) . Exposure to pathogens is followed by the generation and persistence of memory T cells , which can provide long-lasting protection against these same pathogens ( 25 ) . The impact on index case treatment and BCG vaccination in M . leprae-responsive T cell frequencies in peripheral blood was evaluated by detecting the T cells expressing the early activation antigen CD69 ( CD69+ ) in response to short-term in vitro stimulation with M . leprae-specific antigens . To analyze the frequency of central memory CD4+ T cells ( TCM ) and effector memory CD4+ T cells ( TEM ) responsive to M . leprae , the gate strategy shown in S1 Fig was applied . This analysis was performed in 12 HCMB . PBMC from this group were stimulated with two antigen preparations: i ) a M . leprae cell sonicate , which is a complex antigen mixture that is mostly shared with BCG; and ii ) a pool of synthetic M . leprae-specific peptides corresponding to HLA class II-restricted epitopes . Regardless of their BCG vaccination status , almost all HCMB showed an increased frequency of CD4+ TCM responsive to the M . leprae cell sonicate at T1 ( 10 out of the 12 contacts ) ( Fig 2A and 2B ) . In addition , effector memory CD4+ TEM responsive to M . leprae frequencies increased in 8 out of 12 HCMB at T1 ( S1 Fig ) . Moreover , when analyzing CD8 T cell frequencies , a significant increase was detected in the CD8+ TCM responsive to M . leprae at T1 ( 7 out of the 12 contacts ) ( Fig 2C and 2D ) . Interestingly , the increase in CD4 and CD8 TCM frequencies was observed even in those HCMB in which the interval between the first and second evaluations was 20–26 months ( HCMB# 1 , 6 , 7 14 ) . Of note , even HCMB who were not BCG vaccinated at T0 ( HCMB#14 and 16 ) showed increased frequencies of the CD4+ T and CD8+ T cells responsive to M . leprae at T1 . No correlation was seen between individual frequencies to M . leprae-responsive T cells and seropositivity to PGL-I among HCMB at any time point . The ex vivo frequencies of CD4+ T cells in the M . leprae-specific peptides are shown in Fig 3 . It is noteworthy that a significant increase in TCM and TEM CD4+ T cell frequencies in response to the M . leprae peptides was in evidence at T1 . Interestingly , HCMB who did not receive a BCG vaccination at T0 ( HCMB#14 and 16 ) also showed increased CD4+ TCM ( Fig 3B ) and TEM frequencies ( Fig 3C ) in response to M . leprae-specific peptides at T1 . There was no difference in response between the positive or negative HCMB to PGL-I antibodies; and the frequencies of peptide-pool specific CD8+ T cells were below the detection limit . Next , comparisons were made among the cytokine , chemokine , and growth factor levels secreted in vitro by PBMC stimulated with the M . leprae cell sonicate or M . leprae-specific peptides at T0 and T1 . In the unstimulated cultures , the levels of these biomarkers were either below or , in a few cases , just above the detection limit . All the individuals responded well when their cells were cultured in the presence of the superantigen staphylococcal enterotoxin B used as a positive control . Among the 17 mediators measured by a multiplex assay , a significant increase was observed at T1 in the proinflammatory cytokines IL-1 β and IL-6 and the chemokines MCP-1 and MIP-1β . Likewise , a tendency toward higher levels of TNF ( p = 0 . 073 ) , IL-17 ( p = 0 . 083 ) , and IFN- γ ( P = 0 . 093 ) ( Fig 4A ) was demonstrated . Among the inflammatory mediators , IL-17 and IL-1 β showed a positive correlation ( R = 0 . 7 and p = 0 . 001 ) in response to M . leprae at T0 and T1 and IL-8 production levels in all individuals were above the upper detection limit . Individual behavior of each HCMB in terms of secretion of these mediators is displayed in S2 Fig . HCMB , whether vaccinated or not at T0 ( HCMB#14 , 15 and 16 ) , showed increased levels of inflammatory mediators in response to M . leprae at T1 . The increment in inflammatory mediators was observed even in those HCMB in which the interval between the first and second evaluations was 20–26 months ( HCMB# 1 , 6 , 7 , 10 , 14 ) . It is probable that a more consistent increase along with higher levels of mediator production occurred among the contacts receiving a second BCG dose at T0 . Nonetheless , the differences did not reach the level of statistical significance ( S2 Fig ) . There was no difference in response between HCMB anti-PGL-I positive and negative individuals . In cultures stimulated with M . leprae-specific peptides , only MCP-1 levels were suggestive of a more robust response ( Fig 4B ) . It was then decided to evaluate if the increased levels of MCP-1 , IL-1β , IL-17 , IL -6 , IFN- γ , MIP-1β , and TNF observed at T1 in response to M . leprae would differentiate T0 from T1 when analyzed simultaneously . In the principal component analysis ( PCA ) , 76 . 9% of the total variation in response to the 7 cytokines could be narrowed down to 2 components . The first component accounted for a full 62% of the total variation , coming close to corresponding to the average standardized log response to IL-1β , IL-6 , IFN-γ , IL17 , MCP-1 , TNF , and MIP-1β . The second component was independent of the first , totaling 14% of the remaining variation , with a close approximation to the average standardized log response to MIP-1β and IL-6 ( Table 2 ) . Together , these cytokines did not completely differentiate T0 from T1 . However , a greater heterogeneity in response at T0 was found in contrast to the homogeneity in response at T1 ( Fig 5 ) , suggesting a trend toward separation .
The current study targeted HCMB , the group of individuals exposed to leprosy at the highest risk of developing active disease . Two factors are known to decrease the risk of disease among HCMB: i ) treatment of the index case ( patient ) decreases exposure to live M . leprae[24]; and ii ) BCG vaccination[9] . In the present prospective study , the impact of these two factors on the HCMB immune response to mycobacterial antigens was investigated . The frequencies of the peripheral blood memory T cells responsive to M . leprae and the levels of inflammatory mediators produced in M . leprae-stimulated cultures among HCMB were evaluated before and after BCG vaccination and treatment of their index cases . Our findings indicate changes in the HCMB immune response to mycobacterial antigens that could account for their improved resistance to developing leprosy , as follows: i ) an increase in the frequencies of memory CD4 and CD8 T cells responsive to the M . leprae whole-cell sonicate; ii ) higher frequencies of CD4+ T cells that recognize M . leprae-specific peptides; and iii ) higher production levels of the inflammatory mediators IL1-β , IL-6 , IL-17 , TNF , IFN-γ , MIP1-β , and MCP-1 by PBMCs in response to mycobacterial antigens . Of note , the improved response against M . leprae antigens in HCMB seems to be a long-lasting effect , since it was observed even after two years of follow up . Moreover , an increment of these parameters was observed even among contacts that did not receive a BCG vaccine at T0 , suggesting that reduced exposure to live M . leprae in consequence of index cases treatment constitutes an important element in the enhanced immune response witnessed in these individuals . Interestingly , in HCMB , an increment in both M . leprae-specific memory CD4+ and CD8+ T cell frequencies was observed at T1 . CD4 and CD8 T cells have been implicated in the protective immune response against mycobacteria [25] and might , therefore , account for the improvement in their protective response against leprosy . Moreover , the borderline increment in their IFN-γ and IL-17 levels in response to M . leprae observed at T1 points to the activation of Th1 and Th17 T cell subsets , previously shown to be induced by BCG vaccination [26] and implicated in the protection against mycobacteria [27] . An important finding in the present study was the increase in CD4 T cells specific for M . leprae specific epitopes not found in BCG . This result is in agreement with a previous study in which increased levels of IFN-γ were observed in response to MMPI , a M . leprae antigen not shared with BCG , subsequent to contact vaccination [28] . This could be the result of the well-known , non-specific “adjuvant” effect of BCG on the immune response recently shown to be mediated by innate immune cell epigenetic modifications , referred to as “trained immunity” [29] . Indeed , the increase in TNF , IL-1β , IL-6 , MCP-1 , and MIP-1β mediators typically produced by monocytes supports the idea of BCG-induced “trained immunity” as a Th1/Th17 heterologous mediating mechanism of immune activation favoring disease protection of HC of leprosy patients . Other reports have shown that most of these mediators are induced by BCG vaccination [30][31][32] . The phenotypic modification of innate immune cells by BCG has been shown to last for at least one year after vaccination [26] , an interval compatible with the 6–26 month follow-up adopted in the present study . This is also in line with the long-term BCG protection effect against leprosy previously described [33] . The likely activation of Th1/Th17 T cell populations in conjunction with the simultaneous increment of the inflammatory cytokines/chemokines ( TNF , IL-1β , IL-6 , MCP-1 , and MIP-1β ) in response to BCG could explain the onset of paucibacillary leprosy ( PB ) in a small percentage of leprosy contacts after vaccination[28][10][34][35] . A similar explanation could be applied to the incidence of relatively high numbers of patients with Type 1 reactions among the previously asymptomatic contacts who developed leprosy soon after BCG[35] . According to Bagshawe et al . , [34] the manifestation of PB leprosy after BCG vaccination reflects the potential of this vaccine to accelerate evolution to clinical disease in individuals who were infected prior to or immediately after vaccination . In line with this hypothesis , Duppre et al . [10] found that , for the most part , vaccinated contacts contracted leprosy from MB index cases , suggesting that subclinical infection may become overt due to vaccination-induced immune response activation . Moreover , Duppre et al . [9] reported that the incidence of PB leprosy was highest during the first year of follow-up for the PGL-I-positive vaccinated contacts in comparison with the PGL-I negative ones . In the present study , however , no contact developed leprosy post-vaccination during the 3-year follow-up . Likewise , there was no correlation between the presence of PGL-I antibodies and the specific immune response levels observed at T1 . In a future study , it may be advisable to increase the sample size to more thoroughly evaluate the impact of anti-PGLI in the immune response to M . leprae among leprosy patient contacts . Importantly , an increased cellular immune response to both specific-and-shared M . leprae antigens was also detected in the 3 contacts who did not receive BCG at T0 . This observation is consistent with a previous finding indicating an increase in the PBMC proliferative response to M . leprae-antigenic preparations among HCMB a full 6 months after initiating index case treatment [12] . The analysis of the immune response to M . leprae specific antigens of healthy individuals with no history of household contact with leprosy patients , but living in a hyperendemic area for leprosy in Brazil , found high-level IFN-γ responses ex vivo to M . leprae in all the evaluated individuals from this group . In the same investigation , we observed a progressive reduction in IFN-γ levels with increase of persistent exposure to M . leprae in asymptomatic infected individuals and leprosy patients [13] . Altogether , these findings support the hypothesis that the continuous exposure to live M . leprae induces down regulation of the cellular effector immune response against the pathogen and that this effect is reversed upon treatment of the index case . This hypothesis is also supported by data indicating that leprosy incidence decreases significantly among household contacts after three years of index case treatment [34] . It is also known that , even among household contacts , only a small proportion of exposed individuals eventually develop active disease [11] . Overall , the sum of these observations suggests that after the initial infection , there are other yet unknown steps involved in the evolving pathogenesis of leprosy . Data accrued from previous and the present investigations showing enhancement of ex vivo cell-immunity parameters against M . leprae among HCMB after index case treatment give weight to the hypothesis that persistent exposure may facilitate the evolution of the infection to active disease by inhibiting the effector response in contacts . The negative modulation of the effector immune response to M . leprae , as a result of continuous and prolonged stimulation of the immune system by the pathogen eliminated by the index case , is a possible explanation for the known high risk of HCMB to evolve from latent infection to the active disease [15][36] . M . leprae-specific regulatory T cells ( Treg ) are a potential cause for this down regulation of the effector immune response seen in HCMB . The recent observation of in vitro inhibition of immune response to M . leprae in lepromatous leprosy by cells with Treg phenotypic characteristics supports this hypothesis . The continuous exposure of the airways immune system of the HCMB to the live M . leprae aerosols expelled by the MB leprosy patients may create conditions that favor differentiation of M . leprae-specific Tregs , perhaps by sharing some of the mechanisms inhibiting effector T cell generation in response to environmental antigens and normal microbiome [37] . Tregs have been implicated in the pathogenesis of cancer , autoimmune and infectious diseases as well as allergies . Therapeutic intervention in the Treg function has been successful in some situations , and could , together with index case treatment , be a target in the development of new and improved vaccination strategies for leprosy prevention in populations heavily exposed to leprosy . A deeper understanding of the mechanisms involved in the negative modulation of the immune response experienced by individuals persistently exposed to M . leprae may contribute to designing tools to more reliably identify infected individuals before there are any clinical manifestations of the disease , which would be a significant contribution toward interrupting the chain of transmission . To our knowledge , this is the first study demonstrating that index case treatment and/or BCG vaccination of HCMB induce activation of T cell clones that recognize M . leprae specific epitopes not shared with BCG . This activation may at least partially explain the well-known protective effect of these measures against disease progression in HCMB | Leprosy remains a global public health issue with an annual new case detection of approximately 200 , 000–250 , 000 patients . The current study targets leprosy patient contacts , who constitute the group of individuals at highest risk of developing the disease . Treatment of the index case ( patient ) and BCG vaccination of his/her contacts are among the measures known to decrease the risk of household leprosy contacts contracting the disease . In the present work , the impact of these two measures on the immune response of contacts to mycobacterial antigens was investigated , showing improvement in the cellular immune response to both specific and shared M . leprae antigens and an increase in secretion of proinflammatory mediators , which likely explains the protective effect of these measures against leprosy . | [
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... | 2017 | Interruption of persistent exposure to leprosy combined or not with recent BCG vaccination enhances the response to Mycobacterium leprae specific antigens |
The number of recombination events per meiosis varies extensively among individuals . This recombination phenotype differs between female and male , and also among individuals of each gender . In this study , we used high-density SNP genotypes of over 2 , 300 individuals and their offspring in two datasets to characterize recombination landscape and to map the genetic variants that contribute to variation in recombination phenotypes . We found six genetic loci that are associated with recombination phenotypes . Two of these ( RNF212 and an inversion on chromosome 17q21 . 31 ) were previously reported in the Icelandic population , and this is the first replication in any other population . Of the four newly identified loci ( KIAA1462 , PDZK1 , UGCG , NUB1 ) , results from expression studies provide support for their roles in meiosis . Each of the variants that we identified explains only a small fraction of the individual variation in recombination . Notably , we found different sequence variants associated with female and male recombination phenotypes , suggesting that they are regulated by different genes . Characterization of genetic variants that influence natural variation in meiotic recombination will lead to a better understanding of normal meiotic events as well as of non-disjunction , the primary cause of pregnancy loss .
Meiotic recombination is essential for cell division and is a key process that generates genetic diversity . It provides daughter cells with allelic compositions that differ from those of their parents . However , despite its important role , recombination frequency differs significantly between females and males , and also among individuals within each gender [1] , [2] , [3] . Gender differences in recombination rates are also seen in other organisms , such as mice [4] , [5] . Errors in meiotic recombination lead to chromosomal abnormalities including nondisjunction; thus cellular processes must ensure proper meiotic recombinations [6] , [7] . Proteins such as those involved in double-strand DNA breaks are known to be involved in recombination; however regulatory processes and mechanisms by which DNA breaks in meioses resolve into crossovers remain unknown [8] , [9] , [10] . The variation in recombination rates offers an opportunity to identify regulators of this key cellular process . By treating recombination rate as a quantitative trait , we can screen the genome for DNA variants that influence this process without knowing a priori the regulatory mechanisms . The genetic basis of individual differences in human meiotic recombination is poorly understood . An inversion on chromosome 17q21 . 31 [11] and sequence variants in RNF212 [12] are the only known genetic determinants . In this study , we used genotypes from high-density single nucleotide polymorphism ( SNP ) markers of 2 , 315 individuals and their children from two Caucasian samples to characterize meiotic recombinations . We treated the number of recombinations per meiotic event as a quantitative phenotype ( from hereon we will refer to this as recombination phenotype ) and carried out a genome-wide association study ( GWAS ) . From the >137 , 000 female recombination events and >87 , 000 male recombinations events in the two datasets , we found significant individual variation in the numbers and locations of recombination events . We identified six genetic loci that show allelic association with female and male recombination phenotypes . Among them are the sequence variants on chromosome 17q21 . 31 and those in RNF212 that were previously reported to be associated with recombination phenotypes in females and males , respectively . The remaining four loci were not known to contribute to individual variation in genome-wide recombination rates . These results provide new information to study the regulation of meiotic recombination .
We used genotypes from the Autism Genetic Research Exchange ( AGRE ) [13] and Framingham Heart Study ( FHS ) [14] collections to determine recombination phenotypes . For our analysis , we used the genotype data from members of two-generation families that have two or more children to infer recombination phenotypes of the parents in these families . The 511 AGRE families have an average of 2 . 26 children ( median = 2; range: 2 to 7 ) and provided data for 1 , 155 female and 1 , 155 male meioses . Using ∼400 , 000 SNP genotypes of the parents and children in these families , we inferred the recombination phenotypes of 511 mothers and 511 fathers . Briefly , we used the genotypes of the parents to identify informative markers . Then , using these markers , we compared the genotypes of the children to determine the alleles that they had inherited identical-by-descent from the mothers and fathers . Between two sibs , a switch from sharing the same maternal allele to the different maternal allele was scored as a maternal recombination event; and same for the sharing of paternal alleles ( see Materials and Methods , Figure 1 ) . From analysis of these AGRE families , we identified 47 , 573 female recombination events and 30 , 578 male recombination events over the 22 autosomes ( see Table S1 ) . The average number of maternal recombinations per meiosis was 41 . 1 ( 95% CI: 39 . 9–42 . 4 ) , and the average number of paternal recombinations per meiosis was 26 . 4 ( 95% CI: 25 . 7–27 . 2 ) . This is consistent with previous human studies which show that there are more recombination events in female meiosis than in male meiosis . The female∶male ratio in the AGRE dataset is 1 . 6 , which is very similar to those in previous studies of CEPH ( 1 . 6 ) [1] , [2] , Icelandic families ( 1 . 65 ) [15] and Hutterites ( 1 . 5 ) [3] . The distributions of recombination events for females and males in the AGRE collection are shown in Figure 2A . For the second population , we analyzed genotypes for ∼500 , 000 SNP markers from members of 784 two-generation families from the FHS . This dataset provided us with recombination phenotypes for 654 mothers and 639 fathers , with an average of 2 . 86 children per individual ( median = 3; range: 2 to 9 ) . We observed 90 , 264 female and 57 , 054 male recombinations ( Table S1 ) . The average number of maternal recombinations per meiosis was 42 . 8 ( 95% CI: 42 . 4–43 . 3 ) , and the average paternal recombinations per meiosis was 27 . 6 ( 95% CI: 27 . 3–27 . 9 ) . The female∶male ratio was also 1 . 6 . The distributions of female and male recombination events per meiosis for individuals in the FHS collection are shown in Figure 2B . We compared the recombination phenotypes in the AGRE and FHS collections ( and also with those from previous studies ) and found highly similar patterns . Previous literature reports mean maternal genome-wide recombination ranging from 38 . 4 to 47 . 2 , and mean paternal genome-wide recombination ranging from 25 . 9 to 27 . 3 [2] , [3] , [12] , [15] . The mean recombination phenotypes for AGRE and FHS fall within , or very close to , the ranges in the published data . We also compared the resolution of our ability to map crossovers with that of Coop et al . [3] . From our two samples we mapped 40 , 942 ( ∼18% ) recombinations to regions that are <30 kb in size; similarly they identified 4 , 854 ( ∼20% ) recombinations to regions <30 kb in size . Because of our larger sample size , we identified more recombinations but the resolutions in the two studies are comparable . Recombination events are not distributed evenly across the human genome [15] . We refer to genomic regions with higher recombination counts are referred to as “recombination jungles” [2] , [15] ( rather than hotspots , which are only hundreds of base pairs in size ) . To identify the location and size of recombination jungles in the AGRE and FHS samples , we sorted and plotted all recombination events by base pair position . The peaks in the derivative function of curves fitted to the recombination events were identified as recombination jungles ( see Materials and Methods and Figure S1 ) . Previously , to identify recombination jungles , we divided the genome into equal-size bins where bin sizes were picked arbitrarily [2] . The approach we used here allows us to identify jungles based on distribution of SNPs and recombination activities in different genomic regions , thus the results should better reflect the actual recombination activities . Using this approach , we identified 125 maternal recombination jungles and 69 paternal recombination jungles in the AGRE population . The average size of the maternal jungles was 2 . 1 Mb ( range: 0 . 8 to 6 . 0 ) , and that of the paternal jungles was 3 . 7 Mb ( range: 1 . 1 to 11 . 1 ) . In the FHS population , we identified 183 maternal recombination jungles , averaging 1 . 5 Mb ( range: 0 . 5 to 4 . 9 ) , and 86 paternal jungles , averaging 2 . 7 Mb ( range: 0 . 5 to 8 . 6 ) . The positions and sizes of recombination jungles throughout the genome were very similar for individuals from the AGRE and FHS collections ( Figure 3 ) . Recombinations tend to occur in the telomeric parts of chromosomes . Most of the paternal recombination jungles were found at the telomeric ends of each chromosome ( Figure 3 ) , while the maternal recombination jungles were found at the ends of the chromosomes but not always at the most telomeric parts ( Figure 3 ) . Seventy percent of male recombination jungles are located in the 5% most telomeric parts of each chromosome , while 18% of the female recombination jungles are found in the same regions . Previously , in the CEPH data , we also found that recombination jungles were found at the ends of chromosomes [2] . However , data from AGRE and FHS have provided a finer scale map of the recombination activities across the genome . We and others have shown that there are extensive individual differences in recombination phenotypes in both females [1] , [2] and males [2] , [3] . Since the AGRE and FHS samples are larger than those used for previous studies , we use the AGRE and FHS samples to assess individual variation in recombination phenotypes . For individuals with only two offspring , we are not able to identify which recombinations occur in which offspring ( see Materials and Methods ) , but for individuals with three or more offspring we can count recombinations individually in each offspring and thus we have repeated measures for each parent . Using parents with three or more offspring ( 119 AGRE mothers , 119 AGRE fathers , 374 FHS mothers , and 356 FHS fathers ) , we conducted an analysis of variance to compare the variability of recombination in different meiotic events ( offspring ) within an individual to the variability between individuals , and found highly significant individual differences in mean recombination frequency among men ( PAGRE = 5 . 14×10−12 , PFHS = 2 . 83×10−49 ) and women ( PAGRE = 1 . 09×10−16 , PFHS = 8 . 97×10−18 ) in both samples . To identify the DNA variants that influence individual variation in recombination phenotype , we carried out genome-wide association analysis . Since the distributions of female and male recombination phenotypes are different , for all the analyses , we studied female and male recombination phenotypes separately . First , we analyzed data from 511 females and 511 males from the AGRE samples . We treated the recombination phenotypes as quantitative traits . For genotypes , we used ∼350 , 000 SNP genotypes that passed a quality filter . Then , we tested for association of the recombination phenotypes with SNP alleles using an additive model . A plot of the GWA results and a QQ-Plot are shown in Figure 4 . Among the significant SNPs are ones in RNF212 , which was reported by Kong et al to be associated with recombination rate in the Icelandic population [12] . The most significant SNP ( rs11939380 ) within RNF212 has a P-value of 0 . 0009 in the paternal AGRE sample .
We used a sample of 1 , 295 two-generation families with multiple offspring to study the recombination landscape and the genetic basis of meiotic recombination . Our analysis showed that the locations of the recombination events differ across the genome; most of the crossovers occur at the ends of chromosomes . In particular , 70% of male recombination jungles are located in the 5% most telomeric parts of chromosomes . This pattern is observed in samples from the AGRE and FHS collections and also in previous studies of CEPH and Icelandic populations . We also found extensive individual variation in the number of recombination events per meiosis in both females and males . To determine the genetic basis of this variation , we carried out genome-wide association analysis . We treated the number of recombination events as quantitative traits to map the genetic variants that influence recombination phenotype . We found three loci that influence the female recombination phenotype , and three loci that influence the male recombination phenotype . Our GWAS analysis replicated the previous findings that an inversion on chromosome 17q21 . 31 is associated with higher female recombination rates , and that variants in RNF212 influence recombination rates in males . The previous work showed association between haplotypes in RNF212 and male and female recombination , with opposite effects in the two sexes [12] . Specifically , they found SNP rs1670533 associated with female recombination and rs3796619 associated with male recombination . Neither of these SNPs was in the set we examined , but the linkage disequilibrium in this region is very high , and our dataset does contain SNPs that are perfect surrogates ( r2 = 1 . 0 ) in HapMap for each of these . Our surrogates for the Icelandic male SNP include rs4045481 and rs11939380 , both of which had P-values on the order of 10−6 for male recombination in our combined dataset . Our surrogates for the Icelandic female SNP are rs6827357 and rs20114318 . Both of these showed P-values on the order of 0 . 01 for females in our combined dataset . As in the Icelandic population , we observed opposite effects on male and female recombination at these SNPs and throughout the haplotype block . While the P-values for female recombination in our dataset fall far short of genome-wide significance , they do show a weak association and are quite consistent with the Icelandic results . It is particularly notable that this is the first replication of the curious opposite effects on male and female recombination previously observed . In addition to these known loci , we uncovered additional polymorphic regions that are associated with recombination phenotypes . In females , we found variants on chromosome 10 near a poorly characterized gene , KIAA1462 , and those on chromosome 1 near PDZK1 to be associated with recombination rates . These variants along with those on chromosome 17q explain approximately 6% of the total variation in female recombination phenotype in the AGRE and FHS samples . In males , we identified variants on chromosome 9 near UGCG and on chromosome 7 near NUB1 to be associated with recombination phenotype . In the mouse , the expression of Ugcg and Nub1 in prophase I further supports their potential roles during meiosis . The variants in RNF212 and those on chromosomes 7 and 9 explain about 5 . 4% of variation in male recombination . Results from our genetic mapping study enhanced our understanding of meiotic recombination . It appears that gender differences in recombination rates and pattern result from differences in the regulation of female and male meiosis . Our genetic mapping results showed that DNA variants in different genes are associated with female and male recombination phenotypes; we did not find any variants that are significantly associated with both female and male recombination phenotypes . Second , we identified multiple unlinked SNPs that are associated with recombination phenotypes suggesting that multiple polymorphic regulators influence these phenotypes . This likely provides a mechanism for variability in recombination which is essential for genetic diversity while maintaining the number of recombination events within a range that ensures proper disjunction . Each of the variants that we identified explains only a small fraction of the individual variation in recombination . Together the three loci that contribute to female recombination explain less than 10% of the variation , and the same for male recombination . Unlike most essential cellular processes , recombination events must differ between individuals to maintain genetic diversity . However , the system cannot be so flexible that it fails to ensure proper segregation of chromosomes . Having many regulatory steps achieves the goal of allowing some range of events to occur while ensuring that the number of recombination events does not deviate too much to cause improper chromosome segregation or non-disjunction . Although , we have identified six variants that influence recombination events , we expect other variants still need to be identified . Characterization of genetic variants that influence natural variation in meiotic recombination will allow a better understanding of normal meiotic events as well as non-disjunctions which lead to chromosomal abnormalities , the primary cause of miscarriages .
We obtained SNP genotypes from samples in two collections: Autism Genetic Research Exchange ( AGRE ) [13] and Framingham Heart Study ( FHS ) [14] . For our analysis , we used the genotype data from members of two-generation families that have two or more children to infer recombination phenotypes of the parents in these families . Genotypes are available for 511 such families from AGRE ( www . agre . org ) and 784 families from the FHS collection ( http://www . ncbi . nlm . nih . gov/sites/entrez ? db=gap , FHS SHARe collection ) . The AGRE samples consist of 2 , 883 individuals genotyped at 399 , 147 markers on the Affymetrix 5 . 0 SNP Chip platform . We excluded ∼3 , 150 markers from analyses due to deviation from Hardy-Weinberg equilibrium ( P<10−7 ) or Mendelian errors . The FHS includes genotypes at 500 , 568 markers from the Affymetrix 5 . 0 SNP Chip for 9 , 237 individuals . We excluded ∼22 , 000 markers from analyses due to deviation from Hardy-Weinberg Equilibrium ( P<10−7 ) or Mendelian errors . We identified recombination events for maternal and paternal sides separately in two-generation families with at least two children using an approach similar to that of Coop et al . [3] . By looking at informative markers ( defined as SNPs where one parent is homozygous and the other parent is heterozygous ) , we determined the number of alleles shared identical-by-descent between a “reference” child and each other child . For example , assume the father has genotype AA and the mother has genotype TA at a maternal informative marker . If two of their children have genotype TA or AA at this marker , we know they both inherited the same maternal allele . If one child is TA and the other is AA , they inherited different maternal alleles . A switch from the “same maternal allele” state to the “different maternal allele” state in the sibling pair as we move along the chromosome indicates that there was a maternal recombination ( Figure 1 ) . In a family with only two children , we cannot determine in which child the recombination occurred , so the parental recombination phenotype can only be scored as an average for the two children . In a family with three or more children we can assign each recombination to a particular child . If recombination is observed between the reference child and only one sibling , that recombination can be inferred to have occurred in the sibling . But if it is observed when the reference child is paired with the majority of siblings , it can be inferred to have occurred in the reference child . Regardless of the number of children , we scored the recombination phenotype as an average per meiosis for each parent for the purposes of GWAS and most other analyses . To minimize spurious recombinations caused by genotyping errors , we required that each recombination event be supported by 5 or more consecutive informative markers . The PERL module that we used for determining recombination phenotype is available for download at http://genomics . med . upenn . edu/recombination . To identify the location and size of recombination jungles in the AGRE and FHS samples , we sorted and plotted all recombination events by base pair position ( Figure S1 ) . To model these data , we used MATLAB to fit weighted piece-wise polynomial curves . To account for different sized intervals , the inverse size of each interval was used as a weight , then , a smoothing parameter ( p = 0 . 1 ) was used for curve fitting . We then calculated the derivative function for the curves and used that as the relative frequency of recombination events along the chromosome . Regions with frequencies that are two standard deviations or more above the average value of the derivative function were identified as recombination jungles . The widths of jungles are defined as the regions around the peaks that are one standard deviation unit above the average recombination activity . To identify the DNA variants that influence individual variation in recombination phenotype , we carried out genome-wide association analysis . Since the distributions of female and male recombination phenotypes are different , for all the analyses , we studied female and male recombination phenotypes separately . All association tests were performed using the PLINK software package [21] . Recombination phenotypes were used as quantitative traits in an additive genetic model . All markers exhibiting Mendelian errors , deviation from HWE , and/or having a minor allele frequency less than 0 . 05 were excluded . Some SNP genotypes that were available in the AGRE data were not available in the FHS sample . For the GWAS analyses , these genotypes were inferred using the program , MACH [22] . We confirmed the significance of SNPs in Table 1 by permutations ( with 100 , 000 and 1 , 000 , 000 replicates ) . Mouse male meiotic cells were purified by fluorescence activated cell sorting ( FACS ) as previously described [19] , [20] . Cells from the studied fractions encompassing the entire meiosis I and II include spermatogonia , leptotene/zygotene , pachytene , diplotene and secondary spermatocytes/round spermatids . In addition , the entire meiotic population was purified and used as the reference ( calibrator ) sample for the quantitative PCR . Total RNA for all six samples were extracted using the RNAqueous micro kit ( Ambion ) and first-strand synthesis was performed using the SuperScript III reverse transcriptase kit following suppliers' instructions ( Invitrogen ) from 15 ng of total RNA for each sample . The primers used for analysis are: Rnf212/F GAA AGC CTG AGA TGT CAG CAG , Rnf212/R GGC TGG CTA CAG AGC GTA GAT , Nub1/F GTT ACA GGA TGC AGA CCC TGA , Nub1/R CAT CTG TCG AGG CAC TAG AGG , Ugcg/F GAC AGA GAA AGT GGG GTT GGT , Ugcg/R CTC CTG CCT GAT CTA GCA CAT , mActinb/F ATA TCG CTG CGC TGG TCG TC , and mActinb/R AGG ATG GCG TGA GGG AGA GC ( F: forward , R: reverse ) . Primer pairs were chosen to amplify across distant exons in order to avoid false positive amplification from contaminating genomic DNA . Quantitative PCR was performed using SYBR green mix ( Quanta Biosciences ) with ROX as a reference dye ( Invitrogen ) using Realplex Mastercycler 4S ( Eppendorf ) following the supplier's protocol . Melting curve analysis confirmed the simple nature of the amplified product for each gene . Relative expression ( RE ) was calculated following the ΔΔCt methodology with RE = 2−ΔΔCt with ΔΔCt = ΔCtSample−ΔCtReference , and ΔCtSample or Reference = CtGene−Ctb-actin . | Meiotic recombination is essential for the formation of human gametes and is a key process that generates genetic diversity . Given its importance , we would expect the number and location of exchanges to be tightly regulated . However , studies show significant gender and inter-individual variation in genome-wide recombination rates . The genetic basis for this variation is poorly understood . In this study , we used genotypes from high-density single nucleotide polymorphism ( SNP ) markers of 2 , 315 individuals and their children from two Caucasian samples in a genome-wide association study to identify genetic variants that influence the number of meiotic recombination events per gamete . We found three loci that influence female recombination and three different loci that influence male recombination . Our results suggest that gender differences in recombination result from differences in the genetic regulation of female and male meiosis . Also , each identified locus only explains a small proportion of variance; together , each set of loci explains about 10% of the variation in the gender-specific recombination phenotype . This suggests a mechanism for variability in recombination that is essential for genetic diversity while maintaining the number of recombinations within a range to ensure proper chromosome segregation . | [
"Abstract",
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"Results",
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"Materials",
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"Methods"
] | [
"genetics",
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] | 2009 | Genetic Analysis of Variation in Human Meiotic Recombination |
Rabies remains a serious problem in China with three epidemics since 1949 and the country in the midst of the third epidemic . Significantly , the control of each outbreak has been followed by a rapid reemergence of the disease . In 2005 , the government implemented a rabies national surveillance program that included the collection and screening of almost 8 , 000 samples . In this work , we analyzed a Chinese dataset comprising 320 glycoprotein sequences covering 23 provinces and eight species , spanning the second and third epidemics . Specifically , we investigated whether the three epidemics are associated with a single reemerging lineage or a different lineage was responsible for each epidemic . Consistent with previous results , phylogenetic analysis identified six lineages , China I to VI . Analysis of the geographical composition of these lineages revealed they are consistent with human case data and reflect the gradual emergence of China I in the third epidemic . Initially , China I was restricted to south China and China II was dominant . However , as the epidemic began to spread into new areas , China I began to emerge , whereas China II remained confined to south China . By the latter part of the surveillance period , almost all isolates were China I and contributions from the remaining lineages were minimal . The prevalence of China II in the early stages of the third epidemic and its established presence in wildlife suggests that it too replaced a previously dominant lineage during the second epidemic . This lineage replacement may be a consequence of control programs that were dominated by dog culling efforts as the primary control method in the first two epidemics . This had the effect of reducing dominant strains to levels comparable with other localized background stains . Our results indicate the importance of effective control strategies for long term control of the disease .
Rabies is a fatal enzootic disease caused by lyssaviruses and is distributed throughout most of the world , infecting a wide range of hosts [1] . In developed countries , where dog rabies has been effectively controlled , rabies remains epidemic in wild animals , with the Carnivora and Chiroptera orders acting as the main reservoirs [2] . However , most of the human cases are reported in the developing countries of Asia , Africa and Latin America [3] . According to WHO reports , more than 50 , 000 people die of rabies annually , with 56% of the fatalities occurring in Asia [2] , [4] . Domestic dogs act as the main reservoir and are primarily responsible for the dissemination of the disease [5] . Rabies is widely epidemic in Asia and , after India , China has the second highest number of human rabies cases [2] . Figure 1 shows a summary of the annual number of human cases in China between 1950 and the present day . In spite of the variation in the comprehensiveness of surveillance in earlier years , the figure shows three epidemic waves over this period [6] . Moreover , the gap between successive epidemics is brief , with a rapid reemergence of cases within a few years . The first wave occurred in the 1950s , reaching a peak in 1957 ( 1933 cases ) . The second wave extended from the 1960s to the middle of 1990s and was the most serious epidemic with 4000–7000 cases reported annually for most of the 1980s , with a peak of 7037 cases occurring in 1981 . China is currently in the midst of a third wave that peaked in 2007 ( 3300 cases ) . Since then , the numbers have begun to gradually decrease , although there are still around 2000 cases reported every year [6]–[8] . Thus , rabies remains a serious public health problem in China with the continuing threat of a resurgence of the disease . The Department of Viral Encephalitis , within the National Institute for Viral Disease Control and Prevention at the Chinese Center for Disease Control and Prevention ( China CDC ) , has been the national reference laboratory for national rabies surveillance in China since 2005 . The laboratory is responsible for the identification of rabies in patients and animals at a national level using WHO approved tests , and for the subsequent characterization and analysis of positive samples . From this data , together with samples collected by other laboratories , we have been able to build a picture of the emergence of the most recent epidemic over the course of several years . An initial investigation of the data indicated that most of the cases were located in the South of China and it was only later that cases began to occur in west and north China [7] . In another paper , using surveillance data , we investigated the epidemiology of rabies in southern China [9] . We concluded that the spread of rabies viruses from high incidence regions was facilitated by the long-distance movement or trans-provincial translocation of dogs associated with human-related activities and this was likely one of the factors contributing to the rapid increase in human rabies cases in new regions [9] . Nevertheless , much remains to be learned about the epidemiology of the virus in China . Lyssaviruses are an unsegmented , single-strand , negative strand RNA viruses of the Rhabdoviridae family . The lyssavirus genome is approximately 12 kb , with five genes ( 3′–5′ ) encoding the nucleoprotein ( N ) , phosphoprotein ( P ) , matrix protein ( M ) , glycoprotein ( G ) and RNA-dependent RNA polymerase ( L ) [1] . As a consequence of convenience and variability , the N and G genes are the most commonly sequenced components of the genome and , based on their genetic similarity , there are currently twelve classified species within the lyssavirus genus , with an additional two putative rabies virus species Bokeloh bat lyssavirus and Ikoma lyssavirus [10] . Of these species , rabies virus ( RABV ) is responsible for classical rabies in terrestrial mammals globally and in bats on the American continent , as well as being associated with most rabies-related human deaths worldwide [11] , [12] . Although four distinct but unclassified lyssaviruses , isolated from bats on the Asian continent , have been found in recent decades , RABV still has a major impact in Asia and remains of primary concern in China [13] , [14] . Investigation of the diversity and evolution of rabies virus strains over the course of an epidemic can help in the development of strategies to combat and control viral diseases [15] , [16] . In a recent paper we investigated the spatial and temporal dynamics of rabies in China based on N sequences from samples collected from 2003 to 2008 [17] . We found the epidemic was primarily defined by strains that could be divided into two major lineages which exhibited distinct population subdivision and translocation patterns . Since then , we have continued and expanded our surveillance and collected additional positive samples distributed throughout 13 provinces that were isolated from dog , human and ferret badger ( Melogale moschata ) . The G protein plays a pivotal role in pathogenicity and is significantly influenced by host selection pressure [18] , [19] , thus this gene is a good choice for investigating the epidemiology of a rabies outbreak and hence the impact of the pathogen . Based on this , we obtained the G sequences for all new positive specimens isolated in China . While there have been several reports on the rabies epidemic in China based on the G sequence [20]–[22] , these have incorporated relativity small datasets that have limited the analytical methods that could be used . As a consequence of the trial Chinese national surveillance program , as well as efforts by other rabies researchers , significantly more isolates and G sequences are now available , and the geographic distribution ( 23 provinces ) and the range of infected hosts ( 8 species ) has also been expanded . This more extensive dataset gives us an opportunity to reinvestigate the current epidemic to see how the characteristics have changed now the epidemic has become established across a significant portion of the country . Furthermore , given the temporal range of the samples , it allows us to compare the properties and characteristics between epidemics to try and understand how new outbreaks emerged so rapidly after a previous outbreak was brought under control . In this work we investigated the phylodynamics of RABV in China based on the analysis of a comprehensive set of G sequences collected across the course of the current epidemic and also from the previous epidemic . We considered how the geographical dispersion of the lineages predicted from our phylogenetic analysis reflected the observed epidemiology based on surveillance data from human cases in the current epidemic . We also investigated how the prevalence of particular lineages varied within and between successive epidemics . Specifically , we considered whether successive epidemics were associated with a single lineage , or characterized by the emergence of a new lineage .
The program for collection of human brain samples was approved by the Ethical Committee of the National Institute of Viral Disease Control and Prevention , China CDC , which is the national referral center for rabies diagnosis . Due to their medical condition , subjects were unable to provide consent once a rabies infection was suspected and so written informed consent was obtained in all cases from their relatives after death . Data on national human rabies cases from 1950 to 1995 were taken from the annual reports of the China CDC , formerly named the Chinese Academy of Preventive Medicine prior to 2002 ( Figure 1 ) . Data on human rabies cases from the whole of mainland China for each province and municipality ( a total of 31 ) between 1996 and 2010 were collected from the annual reports of the China CDC . The reporting methods and how cases were determined to be associated with rabies were the same as described previously [17] . Provinces were classified as high , medium , low or very low incidence regions according to the recorded number of human cases from 1996 to 2010 . In general , due to the problems of obtaining consent from relatives after a subject has died from a suspected rabies infection , human cases are not confirmed by approved by WHO laboratory testing . However , in the cases when laboratory diagnosis is performed , it was found there was a very strong correlation between positive outcome and clinical diagnosis [17] . This is primarily due to the majority of cases being associated with a bite or scratch from an animal that ( laboratory ) tested positive for rabies . Specimens were collected as part of the trial Chinese national surveillance program using the same sampling method as described previously [17] . From 2004 to 2010 , 7919 specimens were taken from dog brain , human brain or saliva , and ferret badger ( Melogale moschata ) brain collected in 13 provinces ( Hunan , Guangxi , Guizhou , Jiangsu , Zhejiang , Shandong , Shanghai , Anhui , Shaanxi , Jiangxi , Sichuan , Guangdong and Yunnan , Figure 2 ) , and tested for presence of the rabies virus using direct immunofluorescence assay ( DFA ) [9] . Ferret badgers samples were collected from euthanized animals that had exhibited rabies symptoms and which were found in farming villages . 112 out of all these samples were confirmed positive and the complete G gene coding region ( 1575 nt ) of all the specimens were sequenced by using methods described previously [23] . All sequences were submitted to GenBank and assigned accession numbers as listed in Table S1 . Additionally , all complete G sequences of rabies street strains ( as of Jan 6 , 2011 ) were downloaded from GenBank . Only isolates with full background information ( isolation time/host/location ) were considered and combined with the newly sequenced samples to form a final set of 320 sequences ( background information of all sequences are provided in Table S1 ) . To place the Chinese sequences in perspective with worldwide rabies strains , a second dataset was created that was representative in terms of host , strain and location . A total of 74 sequences were selected , 37 were selected from the China sequences ( Table S1 ) and an additional 37 sequences were selected from the major worldwide lineages ( Table S2 ) , representative of countries recording rabies cases in domestic animals , livestock and wildlife . A maximum clade credibility ( MCC ) rooted tree was generated and nucleotide substitution rates ( per site , per year ) were estimated using the Bayesian Markov Chain Monte Carlo ( MCMC ) methods implemented in the BEAST package ( v1 . 6 . 2 ) [24]–[27] . The GTR+I+G model was determined to be the best nucleotide substitution model using ModelTest [28] . The constant population size model was selected based on Bayes Factor and both strict and relaxed ( uncorrelated lognormal ) molecular clocks [29] were investigated , and the latter was determined to have the strongest support when results were analyzed in the TRACER program ( v1 . 5 ) , also consistent with previous RABV analyses results [30] . For the world rabies dataset , an NJ tree was constructed with 1000 bootstraps to verify the reliability of the predicted tree . The phylogenetic analysis predicted six major clades ( China I - China VI ) with high statistical support and which appeared to show differences in geographical composition . To investigate the significance of these differences , clades or merged sets of clades were compared to generate contingency tables and a Pearson's Chi-squared test with the Yates' continuity correction was performed . H0 , the null hypothesis , was defined as: the proportion of cases is independent of column in the contingency table . HA , the alternative hypothesis , was defined as: the proportion of cases is different between columns in the contingency table . Full details are provided in Table S3 . As the China I and China II lineages appeared to be the dominant variant strains , the differences in the geographical composition of these two clades were further investigated . The change in geographical coverage over time was investigated by ( i ) determining the number of provinces with sequenced isolates assigned to these two clades and ( ii ) determining the land area encompassed by the provinces with sequenced isolates assigned to these two clades . The land area of each province is given in Figure 3 . To investigate the contribution from wildlife to rabies in China , wildlife and domestic sequences from the dataset above were combined with the dataset generated from our earlier study based on the N gene to generate a dataset of 368 samples [31] . A complete list of the wildlife isolates are given in Table S4 . We then used Fisher's Exact test to identify significant differences between clade pairs . Full details are given in Table S5 . To investigate the possibility of sampling bias , we also investigated the connectivity between human cases ( Table S6 ) and sequenced isolates ( Figure 3 ) by calculating the Pearson's correlation coefficient , according to geographical location ( province ) and summed over isolation dates ( Table S7 ) . The correlation was tested using the Pearson test . We further investigated the connectivity between human cases/isolate numbers and provincial population density . Population density data is taken from national census data and is provided in Figure 3 . No provinces reported a significant change in population over the surveillance period .
1996 marked the beginning of a third rabies epidemic in China . From this point the number of human cases increased every year , reaching a peak in 2007 . Subsequently , there has been a gradual decrease in the annual cases . Over the course of the epidemic the geographic distribution has spread to encompass almost the entire country and certain characteristics have begun to emerge . Figure 3 ( full data is supplied in Table S6 ) shows the total number of cases by region from 1996 to 2010 . Based on this data , we divided mainland China into 4 regions according to the number of human cases . Guangxi , Hunan , Guizhou and Guangdong , located in the South of China , with 4240-2725 cases , were classified as high incidence regions . The medium incidence regions , with 1404-254 cases , were composed of 13 provinces adjacent , or close to , the high incidence regions . The low incidence regions comprised Shanxi , Shaanxi , Inner Mongolia and the three municipalities of Beijing , Tianjin and Shanghai , ( 96-23 cases ) which are located in the north and west of China . The very low incidence regions consisted of Jilin , Liaoning , Heilongjiang , Xinjiang , Gansu , Tibet , Ningxia and Qinghai , all of which are located in the northeast and west of China . These regions are the most distant from the high incidence regions and have experienced almost no human cases in the last 15 years ( 0–10 cases ) . Thus , the majority of cases are located in the south of China and there is a gradual decrease in the number of cases towards the north and west of the country . We next investigated the diversity and relationship amongst Chinese samples by constructing a phylogenetic tree based on our assembled set of G sequences of China street strains . The 320 strains , spanning 1969–2010 , were isolated from dogs , humans , deer , mice , cattle , pigs , raccoon dogs and ferret badgers ( Melogale moschata ) , and originated from 23 provinces that represent all of the high , medium and low incidence regions shown in Figure 2 , with the exception of Hainan province . In addition , samples from Ningxia province , a very low incidence region , were also included . The Maximum Clade Credibility ( MCC ) tree estimated by the BEAST software package is shown in Figure 4 . The tree shows China strains form six major lineages or clades , China I to China VI , with high support . Figure 5 shows the relationship of these clades with respect to global lineages . China I , China II , China V and China VI are sub-lineages of the Asian clade , China III corresponds to Cosmopolitan and China IV corresponds to Arctic-like . The limited number of sequences for China III to VI makes it difficult to establish the exact relationship amongst the lineages , but it appears that China I represents the youngest strain in the China tree . However , this lineage is distributed throughout 19 provinces and accounts for more than 80% of all strains ( 254/320 ) . China II , the second most prevalent clade , includes 49 strains from 7 provinces and accounts for 15% of the samples . The remaining four clades ( China III , IV , V , and VI ) only account for 5% of the strains , are circulating in limited regions and have little association with the current epidemic ( Table S3 ) . China I can be further divided into subclades I-A and I-B with high support ( Figure 4 and Table S1 ) . The I-A subclade contains almost all of the China I strains , and can be further divided into eight branches , also with strong support and are of primary interest . These branches are named A1 to A8 according to their branching order in the tree , with A1 corresponding to the oldest branch and A8 the youngest branch . A8 contains almost half of the China I isolates distributed across 15 provinces , and represents the most important branch from a epidemiological standpoint . The China II clade can also be divided into two subclades II-A and II-B . The 8 ferret badger isolates from Zhejiang and Jiangxi are placed in subclade II-A , and the other 41 strains are placed in subclade II-B and , with the exception of one Henan strain , they all originate from high incidence regions . To investigate the geographical composition of the sample set according to province or region , the 320 strains were divided according to province/incidence region and the clades , subclades or branches defined in the previous section ( Figure 3 ) . The figure summarizes the composition of each clade , subclade or branch ( column ) according to province or municipality ( row ) . The dominant role of China I is apparent from the number of samples that are placed in this clade . However , additional patterns are also apparent when considering the relationship amongst the various incidence regions and the defined clades . First of all , the number of clades , subclades or branches associated with each province appears to be greatest for the high incidence regions . The only exception is Guangdong province but this is because only a limited number strains have been made publicly available from this region . Secondly , geographical clustering is evident in the composition of the six China clades . Almost all of the strains from high incidence regions are placed in the China I and China II clades . The II-B strains originate from high incidence regions , with the exception of a Henan strain isolated in 1993 , suggesting that this subclade circulated in the early phase of the third epidemic , but failed to spread further as the epidemic became more established . The China I branches show a more complex pattern of geographical composition . Branches I-A3 , I-A5 and I-A7 are primarily composed of isolates from high incidence regions , but also contain several isolates from medium incidence regions . The remaining branches show increased mixing of isolates from high , medium and low incidence regions . I-A8 , the youngest branch , contains the largest number of sequences and these were isolated from high , medium and low incidence regions , but with the most isolates collected from the medium incidence regions and the fewest isolates collected from high incidence regions . To investigate whether the differences in the geographical composition of the branches were significant , we compared branch I-A8 and to the combined set of strains from I-A1 to A7 and performed a statistical comparison as described in the Materials and Methods . Our results indicate that an extremely significant difference exists in the proportions of isolates from high , medium and low incidence regions for I-A8 and the remaining branches ( P = 9 . 126×10−14 ) . This difference extends to the differences in the proportions of low to medium , and medium to high for these branches ( Full details of the analysis are given in Table S3 ) . Thus , the composition of the branches within the China I-A subclade reflects the observed spread of human cases over time from high to medium and low incidence regions . The older clades are primarily composed of sequences from high incidence regions . The primary exception to this pattern is the isolation of samples from the low case region of Neimenggu ( Inner Mongolia ) that are placed in the China IV/Arctic-like clade . This suggests that this lineage plays a minor role in the epidemic , further supported by our recently published results investigating the relationship amongst China rabies and lineages in neighbouring countries [31] . The classification of human case numbers into high , medium , low and very low incidence regions was based on data collected nationally between 1996 to 2010 ( Figure 1 - third wave ) . Figure 6 shows the same data for the third wave but broken down into the number of cases for the high , medium and low incidence regions . Coincident with cases at the national level , the numbers of cases for the high incidence regions peaked in 2006 and then began to decrease gradually . For the medium incidence regions , cases peaked a year later in 2007 and then began to decrease in accordance with the high incidence regions . However , for the low incidence regions , there were almost no cases until 2007 but after this point the number of cases began to increase at a similar rate to that seen at the beginning of the third wave in the high incidence regions . The maximum number of cases occurred in 2010 and it seems numbers will continue to increase . Thus , over the course of the epidemic the burden appears to have shifted from the high to medium and low incidence regions and is now encroaching into regions which have until recently recorded few events . To further examine the contributions of the China I and II lineages to the current epidemic , we next investigated the change in their geographical distribution over the course of the epidemic . Graphs of the number of provinces reporting isolates from these two lineages and the total land area for reporting provinces are shown in Figure 7a and 7b respectively . These figures show that in the early stages of the current epidemic , the two lineages spread into new regions at similar rates but , after 2004 , China I underwent a rapid geographic expansion whereas China II remained within its existing region of influence , further highlighting the dominance of the former lineage . The two major lineages also show differences in their host composition ( Figure 4 ) . Despite the geographic expansion of China I and the association of the majority of new isolates with this lineage , the samples were isolated almost exclusively from dogs , with almost all the remaining samples collected from humans and domesticated animals . Only two samples were isolated from wildlife ( deer and ferret badger ) . Conversely , for the China II , III and IV lineages , a larger proportion of isolates were collected from wildlife ( Table 1 ) . No wildlife isolates were collected for lineages China V and VI , but the total number of isolates were small for both these clades . Pairwise comparison of the China I , II , III and IV lineages using the Fisher's Exact test revealed that China I had a distinct host composition from China II ( P = 2 . 74×10−9 ) , whereas the composition of China II and China III ( Cosmopolitan ) were indistinguishable ( P = 1 ) . However , a significance difference was predicted between China III and China IV ( Arctic-like clade ) ( P = 0 . 0048 ) . Full details of the statistical tests are given in Table S5 . One of the goals of the current national rabies surveillance program is the collection of isolates from regions where rabies cases have been reported in order to obtain a characteristic dataset . To investigate whether the collection program is a reasonable representation of the current epidemic , we compared the total number of isolates collected from each province to the corresponding total number of human cases recorded for that province ( Table S7 ) . The calculated Pearson's correlation coefficient was r = 0 . 7189 ( p-value: 3 . 557×10−06 ) indicating the presence of a strong correlation and that , overall , the collected isolates were representative of the current rabies epidemic in China ( Figure 8 ) . We also compared the number of collected isolates to the population and the population density of each province respectively . We found a weaker but significant correlation for provincial population versus sampling/number of cases ( r = 0 . 4801772 , p = 0 . 006/r = 0 . 4596770 , p = 0 . 009 ) . This reflects that many of the medium and high case regions represent some of the largest provincial populations . It is more informative that there was no measurable correlation between population density and sampling/number of cases ( r = −0 . 08634058 , p = 0 . 6442/r = 0 . 04543189 , p = 0 . 8083 ) - i . e , highly populated regions , including major cities such as Beijing , Shanghai or Chongqing with better resources , are not being preferentially sampled .
In the face of the most recent rabies epidemic , the Chinese government implemented a trial national surveillance program in an attempt to gain a better understanding of the mechanisms driving the reemergence of the disease . Previous studies have revealed evidence of epidemic waves in other countries that are proposed to be synchronous with and in response to vaccination programs , as well as revealing the role of humans in the dispersion of the virus [32] , [33] , but this is the most comprehensive study to date in terms of the size of the geographic region and a time period that spanned the presence and absence of vaccination and other control programs . Traditionally , rabies epidemics have been tracked in terms of surveillance data that presents a statistic such as number of human cases . With advances in analytical techniques and the extensive virus sequence data obtained from the trial surveillance program ( as well as other sequences submitted to GenBank ) it is now possible to investigate the genetic diversity of the variant strains to learn about the origins , expansion and evolutionary dynamics of the current epidemic . In this work , we analyzed a comprehensive sequence set covering almost all epidemic regions in China . While the identification of 6 major RABV lineages is consistent with other results from recent studies , it is the change in the composition of these clades that is informative . In 2007 , only 3 RABV lineages were found in the south of China [9] , but by 2008 , rabies virus samples collected from 15 provinces were associated with 4 distinct lineages , all of which were present in the south of the country [17] . Current reports now indicate there are now 6 lineages of RABV [20] , [23] . The emergence of the China I lineage and the gradual displacement of China II is also apparent when comparing our dataset with those used in other recent studies [9] , [17] , [20] . Whereas there were comparable numbers of China I and China II strains in the earlier study , almost all the strains collected in this study in 2009 and 2010 from 9 provinces belonged to the China I lineage ( Table S1 ) . Furthermore , the geographical dispersion patterns determined in our analysis are consistent with the patterns observed in human case data . Both datasets show the south provinces are the source of the current outbreak and the number of human cases decreases according to geographical distance from this region . Our phylodynamic analysis reveals additional patterns and characteristics of the current epidemic . Figure 7 shows how rapidly China I displaced China II and gained dominance . Furthermore , comparison with Figure 6 suggests that the recent cases in previously rabies free provinces are associated with this lineage; the number of human cases in high and medium case regions began to decrease in 2006 and 2007 respectively , but this coincided with the rapid expansion of China I . Also , as China I was becoming established , the remaining lineages China III to VI were playing a progressively less significant role in the epidemic . In contrast to the second wave and early stages of the third wave , only a few strains from these clades have been isolated in recent years and have been located within a narrow geographic range , suggesting that some of them may be disappearing . The significant differences in the host range of the lineages is also informative . China I isolates are almost exclusively from dogs , domestic animals and human cases , whereas China II , III and IV contains a far higher proportion of wildlife isolates; it is only recently that China I strains have been isolated in wildlife . This data appears to highlight the fundamental role of dogs in the spread of the disease as well as the dissemination of a new lineage and it appears the spillover into wildlife only occurs once the lineage is well established . The phylogenetic analysis , together with the observation that lineages China II , China III and IV are established in wildlife , suggests that they were dominant in earlier epidemics . However , the greater number of China II isolates compared to these other lineages and the observed displacement of this lineage in recent years suggests that China II was dominant in the second epidemic and that another lineage ( possibly China III , V or VI ) was dominant in the first epidemic . It seems unlikely that China IV has played a significant role in the major rabies epidemics in China ( in terms of dog and human cases ) as isolates are few and restricted to the north west of the country , and most of the isolates were obtained from wildlife . The rapid emergence of China I indicates that , although it was present in previous epidemics , this lineage is responsible for the current epidemic . Figure S1 summarizes the temporal , geographical and phylogenetic classification of the various strains . In particular , the figure shows the minimal contribution from lineages China III , IV , V & VI in the current epidemic , and how successive sub-lineages of China I gradually spread across the country while China II remained constrained to the southwestern provinces . These dispersion patterns cannot be attributed to any identified sampling bias as our statistical analysis indicate the isolates selected for sequencing and used in this analysis are highly representative of the national situation according to human cases . Also , we identified no correlation between number of isolates and provincial population density . This suggests that the current surveillance program , based on standard reporting protocols at the local level and coordination at the national level , is effective at capturing the current rabies situation in China . The notable exception is Guangdong province , which is a high case region , but few sequences have been made publicly available . It is hoped that this situation will change in the near future so that the rabies situation in this province can be fully evaluated . One important distinction between the current and earlier epidemics is the methods that were implemented to try and bring the outbreak under control . In the first two epidemics , in the absence of widespread vaccination programs , dog culling and restrictions on dog ownership ( Notice for strengthening work on rabies prevention and control . 1984 . http://law . lawtime . cn/d564741569835 . html ) were the primary methods for containing the virus [34] . As discussed above , recordkeeping was not as precise in the earlier epidemics , but the general features of the graph in figure 1 nevertheless highlight the limitations of culling as an effective control measure . Although the widespread culling was implemented in the middle of the second epidemic , it was more than ten years before the number of cases was brought under control . Furthermore , the numbers actually increased after the introduction of a nationwide culling program . While the reasons for this are not entirely clear , it may well have been a consequence of the implementation of a national culling program . Previously , dog culling efforts were in place , but they were directed by provincial or city government and there was a delay before nationally coordinated program could become functional . Furthermore , our analysis of the geographical and temporal dispersion of RABV strains indicates that , rather than producing widespread eradication of hosts in a short time , it resulted in a number of isolated strains in specific regions . When the culling program was finally halted , there were several strains circulating which were able to compete for dominance . Of these , the China I lineage was able to emerge , while the other lineages remained within their limited geographic range . This also helps us to understand the relatively low estimates for the TMRCA of rabies in China . Despite records of the disease extending back more than 2500 years , estimates based on coalescence date the origin to no more than a few hundred years [20] , [21] . The common explanation is the original lineage has died out and been replaced by newer ones [30] , our results showing the emergence of China I in the most recent epidemic is the first evidence that this does indeed occur . The expansion of the epidemic into low incidence regions is a cause for concern . Prior to 2007 , there were less than 10 human rabies cases reported in these regions in the last 10 years ( Table S3 ) . Since then , the number of human cases in these regions has increased as the number of cases have begun to decrease at a national level [23] . New strains isolated in 2011 in Shanxi , Inner Mongolia and Ningxia are genetically close I-A8 strains [23] , indicating that this lineage is already becoming established throughout the low incidence regions and is beginning to expand into very low incidence regions . This is also supported by data that has been collected after the reported study period . In 2011 , the reported cases in Inner Mongolia , Shanxi , Shaanxi and Shanghai , corresponding to low incidence regions ( Figure 3 ) , doubled over the previous year . Moreover , Ningxia , Xinjiang , Liaoning and Heilongjiang provinces , which have had no cases reported in recent years ( Table S3 ) , began to report their first cases in 2011 or 2012 . The rapid emergence of a third epidemic wave so rapidly after the second epidemic had been controlled highlights the challenge of completely eradicating rabies . The geography of high incidence regions such as Guangxi , Hunan and Guizhou makes it possible for disease reservoirs to exist in remote or inaccessible regions and the custom of eating dog meat ensures the continual presence of localized concentrations of dog populations , which further benefits the survival of RABV [9] . On a more positive note , our analysis shows that the recent introduction of alternative control measures are proving effective in combating the spread of the disease and reducing the number of human cases . In particular , trial dog vaccination programs implemented in some high case regions in the southwest provinces have highlighted the effectiveness of vaccination for rabies control . These successes are reflected in the recent announcement of a new draft plan for rabies control by the Ministry of Agriculture and Health . These new regulations place emphasis on rabies control at the source , emphasizing vaccination of domestic animals , especially in rural areas . In the next phase of the program , vaccination will be extended to additional regions to incorporate more of the dog population . Furthermore , the integration of postexposure prophylaxis costs into welfare programs combined with rabies education as well as introduction of animal registration policies yielded a reduction in the number of cases at the national level within two years . This highlights the importance of continuing these programs as well as establishing similar programs in low incidence regions before the disease can become further established , leading to a reemergence of human cases . | Since 1949 , there have been three rabies epidemics in China . The country is currently in the midst of a third epidemic . After the first two epidemics were brought under control , there was a rapid reemergence of the disease . In 2005 , the government implemented a national surveillance program and as part of this work , samples were collected from humans and animals and screened for rabies . Positive samples were sequenced and combined with other publicly available sequences to form a dataset that spanned almost all epidemic regions in China . A phylogenetic tree was constructed the clustering of isolates according to geographic origin and lineage was investigated . We found that most isolates were grouped into two lineages China I and China II . However , the proportion of isolates in these lineages changed over time until almost all new isolates were placed in China I , indicating it has emerged as the dominant lineage . Furthermore , the significantly higher number of China II isolates compared to remaining lineages together with its established presence in wildlife suggests that it was dominant in the second epidemic , suggesting that lineage replacement also occurred during the previous epidemic . | [
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"diseas... | 2013 | Molecular Phylodynamic Analysis Indicates Lineage Displacement Occurred in Chinese Rabies Epidemics between 1949 to 2010 |
Rift Valley fever ( RVF ) is a vector-borne viral zoonosis of increasing global importance . RVF virus ( RVFV ) is transmitted either through exposure to infected animals or through bites from different species of infected mosquitoes , mainly of Aedes and Culex genera . These mosquitoes are very sensitive to environmental conditions , which may determine their presence , biology , and abundance . In East Africa , RVF outbreaks are known to be closely associated with heavy rainfall events , unlike in the semi-arid regions of West Africa where the drivers of RVF emergence remain poorly understood . The assumed importance of temporary ponds and rainfall temporal distribution therefore needs to be investigated . A hydrological model is combined with a mosquito population model to predict the abundance of the two main mosquito species ( Aedes vexans and Culex poicilipes ) involved in RVFV transmission in Senegal . The study area is an agropastoral zone located in the Ferlo Valley , characterized by a dense network of temporary water ponds which constitute mosquito breeding sites . The hydrological model uses daily rainfall as input to simulate variations of pond surface areas . The mosquito population model is mechanistic , considers both aquatic and adult stages and is driven by pond dynamics . Once validated using hydrological and entomological field data , the model was used to simulate the abundance dynamics of the two mosquito species over a 43-year period ( 1961–2003 ) . We analysed the predicted dynamics of mosquito populations with regards to the years of main outbreaks . The results showed that the main RVF outbreaks occurred during years with simultaneous high abundances of both species . Our study provides for the first time a mechanistic insight on RVFV transmission in West Africa . It highlights the complementary roles of Aedes vexans and Culex poicilipes mosquitoes in virus transmission , and recommends the identification of rainfall patterns favourable for RVFV amplification .
Rift Valley fever ( RVF ) is a vector-borne disease caused by a virus ( RVFV ) belonging to the Bunyaviridae family , genus Phlebovirus , that affects domestic livestock ( e . g . , sheep , cattle , camels , and goats ) and humans . In humans , RVF can take different forms [1] . Most human cases are characterized by a ‘dengue-like’ illness with moderate fever , joint pain , and headache . In its most severe form , the illness can progress to hemorrhagic fever , encephalitis , or ocular disease with significant death rate . In livestock , it causes abortion and high mortality of newborns and thus induces important direct and indirect economic impacts . Since the first isolation of RVFV in Kenya in 1930 [2] , major RVF outbreaks have been reported in Egypt in 1977–1978 [3] and 1993 [4] , in the Senegal River Valley in 1987 [5] , [6] , in Madagascar in 1990 [7] and 1992 [8] , and in northern Kenya and Somalia in 1997 , 1998 and 2007 [9] . In 2000 , RVF cases were reported for the first time outside the African continent , in Saudi Arabia and Yemen [10] . Recently , a new wave of RVF epidemics occurred in 2006 and 2007 in East Africa ( Kenya , Somalia and Tanzania ) [11] , [12] , in Sudan in 2007 [13] , in Madagascar in 2008 [14] , and in Southern Africa in 2010 [15] . Two main modes of transmission of RVFV are suspected: i ) a direct transmission from infected ruminants to healthy ruminants or humans , ( ii ) an indirect transmission through the bites of infected mosquito vectors [16] . The respective contribution of these different transmission routes remain unevaluated [17] . However , it is assumed that the transmission by the bite of infected mosquitoes is the main infection mechanism during inter-epizootic periods [18] . The number of mosquito species potentially involved in RVFV transmission is very large ( more than 30 species ) , with the main vectors belonging to the Aedes and Culex genera [19] . Because mosquitoes are highly dependent on environmental conditions , the distribution in space and time of RVF is also related to climatic and landscape features . Until now , the ecological areas associated with RVFV transmission were either irrigated or flooded areas located in bushed or wooded savannas of semi-arid areas [20] , although a recent study on RVF outbreaks in Madagascar showed possible transmissions in a temperate and mountainous region [17] . In semi arid areas , natural water bodies which are generally full during the rainy season allow the development of Aedes and Culex species [20] , [21] . Based on this , climate based models have been developed to predict RVF outbreaks in Eastern Africa [22] , [23] , and a strong correlation was found between extreme rainfall events and RVF outbreak occurrences in the Horn of Africa [24] . In West Africa , there is strong evidence that the disease is endemic [18]: different RVF outbreaks were reported in ruminants since the severe outbreak in the Senegal River basin in 1987 [25] , [26] , [27] , [28] , and RVFV was isolated from mosquitoes [21] , [29] ( Figure 1a ) . However , using a statistical approach , the correlation found in East Africa is not valid in the semi-arid regions of West Africa [30] , [31] where the drivers of RVFV transmission dynamics remain poorly understood . There , temporary water bodies ( ponds ) constitute the main oviposition sites of different mosquito species [32] , [33] and mosquito population dynamics are assumed to mainly depend on water availability and on pond dynamics , themselves driven by rainfall [34] . In this study , we use a mechanistic modelling approach to better understand the dynamics of RVF transmission in Northern Senegal , in relation to the population dynamics of its two main mosquito vectors in Senegal , Aedes ( Aedimorphus ) vexans arabiensis [21] , [33] and Culex poicilipes [29] . These two species are considered as the main RVF vector in the area because i ) they were proven experimentally to be competent for RVF virus transmission [35] , [36] , [37]; ii ) they were frequently found infected in nature and are the most abundant species in our field site [21] , [38]; iii ) their interaction with the RVF vertebrate hosts ( sheep , goats , and cattle ) is very important [39] . The dynamics of the two vector species is modelled by combining a hydrological model of the dynamics of the water bodies , with mosquito population models describing different stages of the mosquito life cycle . Once calibrated and validated on recent rainfall , pond water levels , and entomological data , the combined model can be used to simulate the evolution of the two species' populations during the period 1961–2003 , using only rainfall data as input . The comparison of model simulations with recorded prevalence rates and RVF outbreaks in the region is then analyzed and discussed .
The study area is an agropastoral zone of northern Senegal ( Figure 1b ) . It is representative of the Ferlo region and is characterized by a complex and dense network of ponds that are filled during the rainy season ( from July to mid-October ) . These water bodies are focal points where humans and livestock have access to water during the rainy season and are also the main breeding sites for Aedes vexans arabiensis and Culex poicilipes mosquitoes . We used a hydrologic pond model that simulates daily spatial and temporal variations ( surface , volume , and height ) of temporary ponds in arid areas [40] . The model consists in a daily water balance model taking into account the contribution from direct rainfall , the runoff volumes of inflows and the water loss through evaporation and infiltration . The relation between water volume , surface and height of a given pond depends on the 3D shape of that pond and is modelled by two volume-depth and area-depth empirical equations . Parameters of the model were estimated using detailed bathymetry of representative ponds of the study area and remotely sensed data such as a Digital Elevation Model ( DEM ) and a very high spatial resolution Quickbird image . The model was calibrated and validated with field data ( water height data and shape profile ) collected during the rainy season 2001 and 2002 in the Barkedji area . The application of the model to the ponds ( 98 ) of the study area gave fair results both for water height and water area predictions . The comparison of simulated and observed water areas show significant correlations with a coefficient of determination ( r2 ) of 0 . 89 . More details of the hydrologic model are given in [40] . In this study , two sets of rainfall data were used as model input: i ) daily rainfall data recorded during the rainy seasons ( July–December ) 2002 and 2003 with an automatic meteorological collector located in Barkedji village ( Figure 1b ) ; and ii ) daily rainfall data recorded from January 1961 to December 2001 by the Linguère meteorological station located 30 km from Barkedji ( Figure 1a ) . The output of interest of the hydrologic model for modelling mosquito population dynamics is , the water surface of any pond P at time t . The mosquito life cycle involves aquatic ( egg , larva , and pupa ) and aerial ( adult ) stages . It begins with an egg , which hatches as a larva . Depending on the species and environmental conditions , hatching may occur immediately or may be delayed . The larvae then mature through four stages before entering pupation . After pupation , the mosquito emerges as an adult ( imago ) at the surface of water . Adults rapidly mate after emergence and females then seek a blood meal necessary for developing their eggs . Following egg development of about three days , females lay eggs on specific humid surfaces ( oviposition sites ) , proceed to a new blood meal , and perform a new gonotrophic cycle , which corresponds to the period between 2 successive egg layings . The bioecology of Ae . vexans and Cx . poicilipes differs . Cx . poicilipes eggs are deposited directly on water surfaces and immediately proceed through development into larvae; they do not survive dessication . In contrast , Ae . vexans females lay their eggs on the soil just above the current water level [33] . To hatch , the eggs must first dry out for a minimum number of days before being submerged in water . Moreover , in dry Sahelian regions , Cx . poicilipes populations may survive unfavourable conditions of the dry period as adults in dormancy ( diapause ) whereas Ae . vexans survive as eggs in desiccated mud , that will hatch during the next rainy season [33] . In the context of data scarce regions , we developed a simple model that captured the main features of Ae . vexans and Cx . poicilipes dynamics at the scale of a pond . The sole dynamic input was the water surface area of pond P at a daily time step t , written as . Only female mosquitoes are modelled and the two mosquito populations of each pond are assumed independent . We followed the theoretical framework proposed by Porphyre et al . [41] for Cx . poicilipes populations , and we extended this model to better take into account specificities of the bioecology of Ae . vexans . The dynamics of the number of adult female mosquitoes of pond P , time step t , , is described by: ( 1 ) where is the daily mortality rate , T the developmental period , i . e . the elapsed time during which a newly hatching egg undergoes its development until the emergence of an adult , the number of hatching eggs in the pond P , time step t , and Tdiapause the date when mosquitoes enter into diapause . The production rate of new adults from a pool of hatching eggs is expressed as the product of the mosquito production capacity of the breeding site , , and of the availability function of the pond P , . The hydrologic model and both Cx . poicilipes and Ae . vexans models were run for two ponds in the study area , Niaka and Furdu ( Figure 1b ) . The two ponds were considered representative of the water bodies in the area , Niaka ( 363 525 m2 ) being a large pond located in the main stream of the Ferlo Valley , and Furdu ( 9 603 m2 ) being a smaller pond located outside the main stream [40] . The initial Cx . poicilipes adult population was defined proportionally to the pond perimeter covered by vegetation , with an initial density of adults of 1 adult . m−1 . The initial number of Ae . vexans eggs was defined proportionally to the pond surface , with an initial density of 1000 eggs . m−2 . Simulations started June 1st , at the beginning of the rainy season . The date of diapause was October 1st , according to [46] . A sensitivity analysis was carried out to assess the robustness of the mosquito population model . We used the OAT ( one-factor-at-a-time ) Morris's method [47] , as revised by Campolongo ( 1999 ) , allowing the estimation of the two-factor interaction [48] , [49] . The input parameters and their ranges based on the literature data were used in the analysis . When information was unavailable , the parameters space variation was defined using nominal values ±10% and a uniform distribution . Three outputs have been tested for each species: ( 1 ) the cumulated annual abundance , ( 2 ) the maximum abundance , and ( 3 ) the date of the peak of abundance . We used field mosquito collection data during two periods , 1991–1996 and 2002–2003 [21] , [33] , in an area surrounding Barkedji village to 1 ) calibrate and 2 ) assess the goodness of fit of the population dynamics models using the coefficient of determination to measure how well the predicted Ae . vexans and Cx . poicilipes abundance values fit with a set of observed mosquito data . The latter were collected at Furdu and Niaka ponds near Barkedji village , every 20 days during the 2002 and 2003 rainy seasons ( Figure 1b , Table 2 ) [34] . The mean number of Culex and Aedes collected per trap over the consecutive nights of a trapping session ( between 5 and 9 days ) was calculated . The mosquito population model was calibrated for the two species using 2002–2003 Furdu entomological data collection . The parameters identified as most sensitive by the sensitivity analysis were calibrated . The calibration was then performed with a systematic exploration of the input parameters space ( Table 3 ) . Other parameter values were determined based on literature data and expert knowledge ( Table 1 ) . To validate the model , we then compared observed and simulated relative abundances of Ae . vexans and Cx . poicilipes mosquito populations for the Niaka pond , 2002–2003 period . The degree of association between the temporal series was assessed by the calculation of the cross-correlation coefficient . This statistical index allows to test whether two temporal series are correlated . It returns values ranging from −1 ( negative correlation ) to 1 ( positive correlation ) . Between 1991 and 1996 , mosquitoes were collected each year monthly between July and November in the Barkedji area with different kinds of traps at different locations [21] ( Table 2 ) . We computed the mean number of Cx . poicilipes and Ae . vexans collected per CO2 light trap and per night over the different locations . We used only one type of trap to avoid any trap related bias in the measure of mosquito abundance . CO2 light traps collections were used because those traps were used evenly each year . The degree of association between observed and simulated abundances for each mosquito species was assessed by calculating the cross-correlation coefficient . Once validated , the models were run over a 63-year period , from 1961 to 2003 , using rainfall historical records provided by the meteorological station of Linguère . As output , we considered the dynamics of each mosquito species expressed in relative values , as well as the product of the two temporal series . The latter index expresses the synchronicity of the Ae . vexans and Cx . poicilipes populations and higher values are obtained when the two mosquito populations are both abundant at the same time . It is subsequently referred as the Index of Simultaneous Abundance ( ISA ) . Finally , we compared and discussed the outputs of the model with the occurrence dates of RVF outbreaks or seroconversion rates reported in Northern Senegal and Southern Mauritania between 1987 and 2003 ( Figure 1a ) and with the annual prevalence rates recorded between 1989 and 2003 by the FAO sentinel herd system [50] .
The sensitivity analysis ( SA ) allows identifying the key parameters of the population dynamics models for Ae . vexans and Cx . poicilipes species ( Figure 2 ) . Overall , the SA showed that the development period T and daily larval survival rate γ , which are both linked to the larval stage , are the parameters with the most effects on model outputs for the two species . Other parameters identified as influential for Cx . poicilipes were Emax and λ , two parameters concerning the oviposition , whereas the other key parameters for Ae . vexans , φ and Td , were related to the desiccation phase . These eight parameters were thus more accurately estimated through the calibration process . The T , γ , Emax , λ , φ and Td parameter values were estimated from model calibration for Cx . poicilipes and Ae . vexans species on the Furdu pond ( Table 2 ) . The comparison of Cx . poicilipes and Ae . vexans observed abundances in 2002–2003 with outputs of the model showed that the model , driven only by rainfall data , reproduces well the major trends in the intra- and inter-annual population fluctuations ( Figure 3 ) . With cross-correlation values of 0 . 78 for Culex , to 0 . 52 for Aedes , the results of the simulations regarding the dates of the peaks and the proportion of abundance are consistent with entomological field data . When considering Ae . vexans populations , for both years the model reproduces well the first abundance peak of catches occurring at the beginning of the rainy season ( July ) , generally after the first effective rainfall [33] . Moreover , the model simulates well the dates of maximum abundance at the end of the rainy season for Cx . poicilipes in 2002 and 2003 . Finally , the model is able to correctly simulate the relative levels of abundance between the two years for the two species ( higher Cx . poicilipes and Ae . vexans densities in 2003 than in 2002 ) ( Figure 3 ) . The comparison of observed and simulated mosquito abundances from 1991 to 1996 confirmed the capacity of the model to assess the inter-annual variability of Cx . poicilipes populations ( Figure 4 ) . For instance , the year of highest abundance of Cx . poicilipes observed during this six years period ( 1993 ) was clearly identified by the model . However , it failed to simulate the high abundances of Ae . vexans populations observed in 1991 and 1996 ( Figure 4 ) , suggesting that the model would only detect very high inter-annual variations in Ae . vexans abundances , like between the years 2002 and 2003 . The cross-correlation coefficient values were fair ( cor = 0 . 43 for both species ) . Finally , considering both population dynamics , the model reflects well the temporal interval between Ae . vexans and Cx . poicilipes dynamics , the former appearing at the very first rain , while the latter is stronger at the end of the rainy season , taking over from the declining Ae . vexans population . The modelled dynamics of Ae . vexans and Cx . poicilipes populations depict a high inter-annual variability over the studied period ( Figure 5 ) . Simulations put into evidence that the abundance of both species vary greatly between years . Moreover , the model shows that the peak of abundance of Ae . vexans populations generally occurs before the peak of Cx . poicilipes populations , depicting Aedes-before-Culex population cycles . Variations of the ISA reveal the variations in the temporal lag between Ae . vexans and Cx poicilipes populations . The two major RVFV circulation events in northern Senegal and southern Mauritania were recorded in 1987 [25] and 2003 [28] . For these two years the model predicted high ISA values of Ae . vexans and Cx . poicilipes populations . According to this index , 1989 and 1993 also appear as years of simultaneous abundant mosquito populations ( Figure 5 ) . This is in agreement with the results of several sero-surveys conducted in the area . Serosurveys in small ruminants performed after 1988 showed an active transmission of RVFV till 1989 [26] . In October 1993 , active RVFV transmission was detected in several locations of southern Mauritania , in association with an increase of abortions in small ruminant populations [26] ( Figure 1a ) . That same year , RVFV was isolated from Ae . vexans and Ae . ochraceus species , and from one sheep in Barkedji village [27] . Between 1993 and 2003 , no epizootic event was observed but virus circulation was detected in 1998 from Cx . poicilipes populations [29] .
For the first time , mechanistic insight is provided in this study to explain why reported RVF outbreaks in Northern Senegal cannot be correlated directly to rainfall , as it is the case in East Africa . This is done through the use of a rainfall-driven model of RVF vector populations that combines a hydrological model to simulate daily water variations of mosquito breeding sites , with mosquito population models capable of reproducing the major trends of population dynamics of the two main vectors of RVFV in Senegal , Ae . vexans and Cx . poicilipes . Results show that RVF occurs during years when both species are present simultaneously in high densities . These occur when the rainfall temporal patterns result in water variations in the pond that are favourable for the reproduction of both mosquito species , i . e . , abundant rains occurring at regular intervals throughout the rainy season . The combined model can now be used in simulation studies for identifying which rainfall patterns would result in the simultaneous abundance of both species ( high ISA ) , so that operational real-time rainfall-based monitoring systems can be developed . | Rift Valley fever ( RVF ) is a zoonotic disease that affects domestic livestock and humans . During inter-epizootic periods , the main infection mechanism is suspected to be through bites by infected mosquitoes , mainly of Aedes and Culex genera . In East Africa , RVF outbreaks are known to be closely associated with heavy rainfall events , unlike in the semi-arid regions of West Africa where the drivers of RVF emergence remain poorly understood . This study brings mechanistic insight to explain why reported RVF outbreaks in Northern Senegal cannot be correlated directly to rainfall . This is done through the use of a rainfall-driven model of RVF vector populations that combines a hydrological model to simulate daily water variations of mosquito breeding sites , with mosquito population models capable of reproducing the major trends in population dynamics of the two main vectors of RVF virus in Senegal , Ae . vexans and Cx . poicilipes . Results show that RVF occurs during years when both species are present simultaneously in high densities . Simulations of inter-annual variations in mosquito populations successfully explained the dates of RVF outbreaks observed between 1961 and 2003 . | [
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"ve... | 2012 | Combining Hydrology and Mosquito Population Models to Identify the Drivers of Rift Valley Fever Emergence in Semi-Arid Regions of West Africa |
Interspecific hybridization can introduce genetic variation that aids in adaptation to new or changing environments . Here , we investigate how hybrid adaptation to temperature and nutrient limitation may alter parental genome representation over time . We evolved Saccharomyces cerevisiae x Saccharomyces uvarum hybrids in nutrient-limited continuous culture at 15°C for 200 generations . In comparison to previous evolution experiments at 30°C , we identified a number of responses only observed in the colder temperature regime , including the loss of the S . cerevisiae allele in favor of the cryotolerant S . uvarum allele for several portions of the hybrid genome . In particular , we discovered a genotype by environment interaction in the form of a loss of heterozygosity event on chromosome XIII; which species’ haplotype is lost or maintained is dependent on the parental species’ temperature preference and the temperature at which the hybrid was evolved . We show that a large contribution to this directionality is due to a temperature dependent fitness benefit at a single locus , the high affinity phosphate transporter gene PHO84 . This work helps shape our understanding of what forces impact genome evolution after hybridization , and how environmental conditions may promote or disfavor the persistence of hybrids over time .
Comparative genomics of thousands of plants , animals , and fungi has revealed that portions of genomes from many species are derived from interspecific hybridization , indicating that hybridization occurs frequently in nature . However , the influence of processes such as selection , drift , and/or the presence or absence of backcrossing to a parental population on hybrid genome composition in incipient hybrids remains largely unknown . In some cases , hybrids will persist with both parental genomes in fairly equal proportions as new hybrid species or lineages , while in other instances , hybrid genomes will become biased towards one parent’s sub-genome over time [1–9] . Untangling the genetic and environmental factors that lead to these outcomes is a burgeoning field . Some hybrid genotypes will be unfit due to genetic hybrid incompatibilities or cytotype disadvantage; decades of work across many systems have illustrated examples of hybrid sterility and inviability [10] . Recent work has demonstrated that in hybrid genomes with a bias in parental composition like humans , in which most of the genome is comprised of modern human haplotypes with small fragments derived from archaic human , regions from the minor parent ( e . g . , Neanderthal or Denisovan ) are decreased near functional elements and hybrid incompatibilities [11–13] . Conversely , there are examples of “adaptive introgression , ” in which alleles from the minor parent confer a benefit , like wing patterning in butterflies , high altitude tolerance in the Tibetan human population , and winter color morphs in the snowshoe hare [14–22] . The environment undoubtedly plays a significant role in hybrid fitness , and genotype by environment interactions will shape hybrid fitness in a similar manner as they shape non-hybrid fitness . For example , there is general acceptance that the Saccharomyces species complex is largely void of genic incompatibilities ( with exceptions [23] ) , however most experiments looking for incompatibilities have used laboratory conditions . Hou et al . utilized different carbon sources , chemicals , and temperatures to show that over one-fourth of intraspecific crosses show condition-specific loss of offspring viability [24] . This is echoed by many examples of condition specific hybrid incompatibility in plants [25–30] . Similarly , there are numerous examples of environment dependent high fitness hybrid genotypes [31] [32–41] , exemplified by classic research showing Darwin’s finch hybrids with different beak shapes gained a fitness benefit during and after an El Niño event [15] . The budding yeasts in the genus Saccharomyces have emerged as a particularly adept system to study genome evolution following hybridization . Recent evidence supports the hypothesis that the long-recognized whole genome duplication that occurred in the common ancestor that gave rise to Saccharomyces resulted from hybridization [42] , and led to speculation that ancient hybridization could also explain other whole genome duplications in plants and animals [43] . Introgression and hybridization have also been detected across the Saccharomyces clade [44–50]; most famously , the lager brewing lineage S . pastorianus is a hybrid between S . cerevisiae and S . eubayanus [51–56] . A bias towards one parent sub-genome was identified in the ancient hybridization event and in S . pastorianus , and selection is inferred to be important in this process [1 , 42] . Experimental evolution of lab derived hybrids has provided significant new insights into the genetic architecture and influence of the environment on hybrid genome evolution [41 , 57–59] . To empirically understand the genomic changes that occur as a hybrid adapts to a new environment , we previously created de novo interspecific hybrids between two yeast species , S . cerevisiae and S . uvarum , which are approximately 20 million years divergent and differ in a range of phenotypes , notably in preferred growth temperature . S . uvarum has been isolated primarily from Nothofagus ( beech ) and associated soil in Patagonia and similar habitats across the world , and is specifically known for fermentation of cider and wines at cold temperatures [60–64] . Many S . uvarum strains show evidence of introgression from several other yeast species , and S . cerevisiae x S . uvarum hybrids have been isolated from fermentation environments [60 , 65] . We previously evolved S . cerevisiae x S . uvarum hybrids in the laboratory in several nutrient-limited environments at the preferred growth temperature of S . cerevisiae [66] . We frequently observed a phenomenon known as loss of heterozygosity ( LOH ) in these evolved hybrids , in which an allele from one species is lost while the other species’ allele is maintained . The outcome of such events is the homogenization of the hybrid genome at certain loci , and represents a way in which a hybrid genome may become biased toward one parent’s sub-genome . This type of mutation can occur due to gene conversion or break induced replication , and as previously noted , has also been observed in organisms including S . pastorianus , pathogenic hybrid yeast , and hybrid plants , but its role in adaptation has been unclear [49 , 67 , 68] . We used genetic manipulation and competitive fitness assays to show that a particular set of LOH events was the result of selection on the loss of the S . uvarum allele and amplification of the S . cerevisiae allele at the high affinity phosphate transporter PHO84 in phosphate limited conditions . By empirically demonstrating that LOH can be the product of selection , we illuminated how an underappreciated mutation class can underlie adaptive hybrid phenotypes . This prior study described an example of how the environment ( differences in nutrient availability ) can bias a hybrid genome towards one parent’s sub-genome . Due to many examples of genotype by temperature interaction in hybrids across many taxa , and a difference in species’ temperature preference in our hybrids , we speculated that temperature is an important environmental modifier that may influence parental sub-genome representation in hybrids . Temperature can perturb fundamentally all physiological , developmental , and ecological processes , and as such , temperature is an essential factor in determining species distribution and biodiversity at temporal and spatial scales [69–71] . We hypothesized that in S . cerevisiae x S . uvarum hybrids , S . cerevisiae alleles may be favored at warmer temperatures , whereas S . uvarum alleles may be preferred at colder temperatures , giving the hybrid an expanded capacity to adapt . To test how temperature influences hybrid genome composition over time , we evolved the same interspecific hybrid yeast in the laboratory at 15°C for 200 generations . In comparing laboratory evolution at 15°C and 30°C , we present evidence that temperature can indeed bias hybrid genome composition towards one parental sub-genome , and we focus on a reciprocal LOH event at the PHO84 locus . We show that which species’ allele is lost or maintained at this locus is dependent on the parental species’ temperature preference and the temperature at which the hybrid was evolved , thus revealing a genotype by environment interaction . Our results are one of the first clear examples with a molecular genetic explanation of how hybrids have expanded adaptive potential by maintaining two genomes , but also how adapting to one condition may abrogate evolutionary possibilities in heterogeneous environments .
To test whether temperature can influence the direction of resolution of hybrid genomes , we evolved 14 independent populations of a S . cerevisiae x S . uvarum hybrid in nutrient-limited media at 15° C for 200 generations ( phosphate-limited: 6 populations; glucose-limited: 4 populations; sulfate-limited: 4 populations; see S4 Table for strain details ) . Diploid S . cerevisiae and S . uvarum populations were evolved in parallel ( 4 populations of S . cerevisiae and 2 populations of S . uvarum in each of the three nutrient limited conditions; see S4 Table for strain details ) . Populations were sampled from the final timepoint and submitted for whole genome sequencing and analysis . We detected large scale copy number variants in our cold evolved populations , including whole and partial chromosome aneuploidy and loss of heterozygosity ( Table 1; S1 Table; S2 Table; S1 Fig; S2 Fig; S3 Fig; S4 Fig; S5 Fig; S6 Fig; S7 Fig ) . Copy number changes , and specifically amplification of nutrient transporter genes , are well-recognized paths to adaptation in laboratory evolution in nutrient limited conditions [50 , 66 , 72–81] . We find a preference for S . cerevisiae partial and whole chromosome amplification in hybrids evolved at both 15°C and 30°C , which may reflect an increased capacity for S . cerevisiae to acquire this type of mutation ( Table 1 ) [82] . In contrast , we observe a bias in the direction of LOH resolution dependent on temperature . Previously , we observed more LOH events in hybrids evolved at 30°C in which the S . uvarum allele was lost ( 5/9 LOH events ) [66] . In this study , we observe 6/6 LOH events in hybrids evolved at 15°C in which the S . cerevisiae allele is lost and the S . uvarum allele is maintained , suggestive of a S . uvarum cold temperature benefit . While our sample sizes are modest , together these results indicate that temperature can determine hybrid genomic composition in the generations following a hybridization event . In line with previous studies , we find both chromosomal aneuploidy and LOH are nutrient limitation specific , with repeatable genomic changes occurring in replicate populations under the same nutrient condition , but no changes shared across nutrients . In glucose limitation , 3/4 hybrid populations experienced chromosome XV LOH , losing the S . cerevisiae allele for portions of the chromosome . Haploidization of one of these implicated regions on chromosome XV was previously observed in S . cerevisiae diploids evolved at 30°C in glucose limitation [66 , 79] , but it was not observed in any previously evolved hybrids , and which genes may be responsible for fitness increases are unclear . In sulfate limitation , we recapitulate previous hybrid laboratory evolution results [66] , observing the amplification of the S . cerevisiae high affinity sulfate transporter gene SUL1 in low sulfate conditions ( 4/4 hybrids , S1 Fig; S2 Fig ) . Amplification of S . cerevisiae SUL1 therefore seems to confer a high relative fitness regardless of temperature ( see section below , “Pleiotropic fitness costs resulting from loss of heterozygosity” ) . Though prior work showed highly repeatable amplification of S . cerevisiae SUL1 at 30°C in S . cerevisiae haploids and diploids [66 , 72 , 79–81] , and amplification of S . uvarum SUL2 after approximately 500 generations at 25°C in S . uvarum diploids [81] , we never observed amplification of SUL1 or SUL2 in S . cerevisiae or S . uvarum diploids at 15°C , albeit our experiments were terminated at 200 generations . Finally and most notably , in low phosphate conditions , we discovered a LOH event in which the S . cerevisiae allele is lost and the S . uvarum allele is amplified on chromosome XIII , which encompasses the high affinity phosphate transporter PHO84 locus ( 2/6 hybrid populations; Fig 1A ) . The LOH tract length extends approximately 80kb from the telomere in both cold evolved populations ( P1-15°C: 0–82 , 283; P3-15°C: 0–79 , 085 ) , and the breakpoints are potentially due to microhomology , located in the genes GIM5 and VPS9 , respectively . This LOH event is of high interest , as we previously identified a repeated LOH event encompassing the same genomic region when hybrid populations were evolved at 30°C ( 3/6 populations , Fig 1A ) . Furthermore , the directionality of this LOH event is the opposite outcome of our observations of hybrids evolved at 30°C , in which the S . cerevisiae allele was amplified and the S . uvarum allele was lost . We are unfortunately limited by sample size in determining if these LOH events are statistically significant; however , the repeatability and directionality in resolution of these LOH events suggest they are modulated by temperature and worthy of further investigation . Based on previous results that demonstrated that LOH at the PHO84 locus conferred a high competitive fitness benefit at warm temperatures ( measured by direct competition of strains carrying the LOH vs . an ancestral strain labeled with a neutral GFP marker ) , we hypothesized that this apparent preference for the alternate species’ allele in different environments is explained by a genotype by environment interaction at the PHO84 locus itself . Pho84 is a H+-coupled inorganic phosphate transporter , responsible for both sensing phosphate in the environment and phosphate uptake , particularly when phosphate is scarce [83–86] . The two species’ proteins have a pairwise identity of 90% and are conserved at key residues identified as essential in phosphate transport , but do differ in several residues in transmembrane domains and notably in the large loop VI in the cytoplasm ( S8 Fig; S9 Fig ) . To test the hypothesis that there is a genotype by environment interaction involving the PHO84 locus , we repeated the competitive growth assays of allele-swapped strains from Smukowski Heil et al . ( 2017 ) at 15°C . These strains are either homozygous S . cerevisiae , homozygous S . uvarum , or heterozygous for both species at the PHO84 locus ( including both promoter and coding sequences ) in an otherwise isogenic hybrid background . Indeed , we find a fitness tradeoff dependent on temperature , in which hybrids homozygous for S . uvarum PHO84 show a fitness increase of 39 . 30% ( +/-5 . 16; 95% C . I . ) at 15°C relative to their hybrid ancestor , which carries a copy of each species’ PHO84 allele . In contrast , hybrids homozygous for S . cerevisiae PHO84 show a slight relative fitness decrease ( -5 . 36% +/-2 . 54; 95% C . I . ) at this temperature ( Fig 1B ) . There is a significant difference between fitness of hybrids homozygous for S . cerevisiae PHO84 at different temperatures ( p<0 . 001 , Welch Two Sample t-test ) , and between fitness of hybrids homozygous for S . uvarum PHO84 at different temperatures ( p<0 . 0001 , Welch Two Sample t-test ) suggesting that both species’ alleles of PHO84 are temperature sensitive . To further explore how genetic interactions in the hybrid influence strain fitness , we created a S . cerevisiae diploid homozygous for S . uvarum PHO84 ( including both promoter and coding sequence ) in an otherwise isogenic background . This strain exhibits a fitness increase of 48 . 56% ( +/-27 . 72 , 95% C . I . ) at 15°C and a fitness decrease of -7 . 61% ( +/-3 . 04 , 95% C . I . ) at 30°C relative to a diploid S . cerevisiae homozygous for S . cerevisiae PHO84 ( Fig 1C; p = 0 . 0071 , Welch Two Sample t-test ) . These results remain consistent with our previous results in the hybrid background , in which the S . uvarum allele is more beneficial at cold temperatures . This suggests that the PHO84 locus alone is sufficient to confer a temperature dependent fitness benefit and that no sizable genetic interactions contribute to this effect . Technical issues prevented us from testing the reciprocal combination ( S . uvarum diploid with S . cerevisiae PHO84 alleles ) . We clearly demonstrate a fitness trade-off dependent on temperature at the PHO84 locus . To explore if other mutations in evolved hybrids show antagonistic pleiotropy at divergent temperatures , we conducted a series of competitive fitness assays at 15°C and 30°C . We isolated two clones from each hybrid population evolved at 15°C , and competed the clone against a common GFP-marked unevolved hybrid ancestor in the nutrient limitation it was evolved in at both 15°C and 30°C . We observe that clones isolated from the same population often have differences in competitive fitness , which we attribute to genetically different subpopulations coexisting in the population . As all of our analyses are conducted using population sequencing as opposed to clone sequencing , the mutations present in an individual clone may be different than indicated in Table 1 ( and S1 Table; S2 Table ) . However , we are still able to detect several trends , including examples of antagonistic pleiotropy and temperature independent high fitness genotypes . First , we sought to identify how the chromosome XIII LOH event influences competitive fitness beyond the PHO84 locus . We genotyped clones isolated from evolved populations and selected clones that have chromosome XIII LOH . Clones evolved in phosphate limitation with the chromosome XIII LOH event ( homozygous S . uvarum PHO84; P1-15°C and P3-15°C ) have higher competitive fitness at 15°C and decreased competitive fitness at 30°C , displaying antagonistic pleiotropy ( Fig 2A , although note clones isolated from the same population have different magnitudes of fitness decreases ) . The competitive fitness increases seen in evolved hybrid clones at 15°C are much less extreme than the values observed for the allele swap strains ( Fig 1B ) , suggesting that other genes included in the LOH event may have a negative fitness effect , and/or that genetic interactions dampen the magnitude of the fitness increase . To compare these results to the reciprocal LOH event seen in hybrids evolved at 30°C in which the evolved strains became homozygous for S . cerevisiae PHO84 , we competed clones from populations initially evolved at 30°C at 15°C . Indeed , clones with the LOH event homozygous for S . cerevisiae PHO84 ( P3-30°C , P4-30°C , P5-30°C ) have increased fitness at 30°C and decreased fitness at 15°C ( Fig 2B ) , consistent with the PHO84 allele swap competitive fitness results . Of course , there are other mutations present in these clones , and some evidence that these fitness values may be influenced by the tract length of the LOH event , which ranges from approximately 79kb to 234kb . For example , P3-30°C has the shortest LOH tract at approximately 25kb in length and has a higher relative fitness at 15°C than either P4-30°C or P5-30°C , whose LOH tracts extend to 221kb and 234kb , respectively ( Fig 1A ) . The LOH tract length is approximately 80kb in both cold evolved populations ( P1-15°C: 82 , 283; P3-15°C: 79 , 085 ) , but is made more complex by the amplification of a portion of the S . cerevisiae sub-genome adjacent to the LOH event ( P1-15°C: 81 , 105–168 , 345; P3-15°C: 79 , 074–168 , 345; Fig 1A ) . Together , these results support a temperature sensitive fitness response at the PHO84 locus , but also imply that there may be other genes modulating fitness in the chromosome XIII LOH events , something we hope to explore in future work . In contrast , clones isolated from populations without chromosome XIII LOH ( P2-15°C , P4-15°C , P5-15°C , P6-15°C , P1-30°C , P2-30°C , P6-30°C ) generally show increased fitness at the temperature they were evolved at , but have variable fitness responses at the temperature they were not evolved at . Similarly , hybrid clones evolved in other media conditions at 15°C generally show an increase in fitness at 15°C , but variable responses at 30°C , with some clones having higher relative fitness at 15°C and lower fitness at 30°C , some clones showing the opposite trend , and some clones having similar fitness at both temperatures ( Fig 3 ) . It thus appears that temperature specific antagonistic pleiotropy , in which a clone has high fitness at one temperature and low fitness at the other temperature , is relatively rare , with the LOH encompassing PHO84 being the only clear example ( although clones P2-C2 and G9-C2 display a pattern of antagonistic pleiotropy as well ) . The only other distinct pattern in the fitness data is that all hybrids evolved in sulfate limitation at 15°C show fitness gains at both 15°C and 30°C . All sulfate-limited hybrid clones have an increased fitness ranging from 23 . 66–41 . 01% relative to their hybrid ancestor at 30°C , except for the clone from population S9-15°C ( Fig 3B ) . This result is in line with the observation of an amplification of S . cerevisiae SUL1 at very low frequency and/or low copy number in population S9-15°C compared to other sulfate limited evolved populations , which display high copy number S . cerevisiae SUL1 amplification ( S1 Fig ) . Previous work conducted at 30°C has illustrated that SUL1 amplification in sulfate-limited conditions is highly advantageous . These new data suggest that an amplification of S . cerevisiae SUL1 confers a fitness benefit at both cold and warm temperatures , but is most beneficial at warm temperatures . SUL1 thus provides a clear example of a temperature independent high fitness genotype . Through comparison of the single nucleotide variants and indels called in the hybrid populations evolved at 15°C and 30°C , we observed a slight , though not significant , increase in the number of mutations in the S . cerevisiae portion of the genome when evolved at temperatures preferred by S . uvarum ( 12/19 mutations are in the S . cerevisiae sub-genome at 15°C compared to 16/30 mutations in the S . cerevisiae sub-genome at 30°C , Fisher’s exact test p = 0 . 5636; S3 Table ) . There was no overlap in genes with variants identified in datasets from 15°C and 30°C . We suspect that the low growth temperature is a selective pressure for both the hybrids and the parental populations , and we did observe mutations in two genes ( BNA7 and OTU1 ) that were previously identified in a study of transcriptional differences of S . cerevisiae in long-term , glucose-limited , cold chemostat exposure [87] . We found no overlap with genes previously identified to be essential for growth in the cold [88 , 89] , or differentially expressed during short-term cold exposure [90 , 91] , though our screen is not saturated and growth conditions differ between these studies . Additionally , we observed some mutations in genes that are members of the cAMP-PKA pathway , which has previously been implicated in cold and nutrient-limitation adaptation [87 , 92] . Based on the mutations observed in populations evolved at 30°C , we previously hypothesized that an intergenomic conflict between the nuclear and mitochondrial genome of S . cerevisiae and S . uvarum could be an important selection pressure during the evolution of these hybrids [66] . We find further circumstantial evidence for the possibility that mitochondrial conflicts are influential in hybrid evolution as 3/19 point mutations in the hybrids are related to mitochondrial function , whereas 1/20 are related in the parental species populations ( for a total of 7/46 point mutations in hybrids and 1/46 point mutations in parentals when both temperatures are considered; p = 0 . 0585 , Fisher’s exact test ) . Finally , we did observe one recurrent mutational target . Eight independent S . cerevisiae diploid lineages had a substitution occur at 1 of 3 different amino acid positions in Tpk2 , a cAMP-dependent protein kinase catalytic subunit . Previously , it has been reported that Tpk2 is a key regulator of the cell sticking phenotype known as flocculation through inactivation of Sfl1 , a negative regulator of FLO11 , and activation of FLO8 , a positive regulator of FLO11 [93 , 94] . This mutation was detected exclusively in flocculent populations . We and others have previously established that flocculation evolves quite frequently in the chemostat , likely as an adaptation to the device itself , but we have not previously observed a flocculation phenotype caused by these mutations in other evolved populations of S . cerevisiae [95] . While we have not definitively demonstrated causation , prior literature links TPK2 to flocculation , and all evolved clones bearing a TPK2 mutation flocculated within seconds of resuspension by vortexing ( S10 Fig ) . Most mutations were heterozygous , but within several lineages , we observed evidence of a LOH event that caused the TPK2 mutation to become homozygous . Clones bearing a homozygous mutation in TPK2 showed a faster flocculation phenotype than their heterozygous counterparts . We similarly observed one lineage with a mutation causing a premature stop and subsequent LOH in SFL1 , whose isolated clones displayed a robust flocculation phenotype . We suspect that our previous lack of detection is likely due to the well-established genetic differences in the FLO8 gene between the strains used in this study and previous studies , which would alter whether a FLO8 dependent flocculation phenotype is possible [96] .
In summary , we evolved populations of interspecific hybrids at cold temperatures and show that temperature can influence parental representation in a hybrid genome . We find a variety of mutations whose annotated function is associated with temperature or nutrient limitation , including both previously described and novel genes . Most notably , we discover a temperature and species specific gene by environment interaction in hybrids , which empirically establishes that temperature can influence hybrid genome evolution . Growth temperature appears to be one of the most definitive phenotypic differences between species of the Saccharomyces clade , with S . cerevisiae being exceptionally thermotolerant , while many other species exhibit cold tolerance [97–99] . Significant work has focused on determining the genetic basis of thermotolerance in S . cerevisiae with less attention devoted to cold tolerance , though numerous genes and pathways have been implicated [88–91 , 100–104] . Hybrids may offer a unique pathway for coping with temperatures above or below the optimal growing temperature of one parent [47 , 105 , 106] , and may aid in the identification of genes important in temperature tolerance . For example , it has long been speculated that the allopolyploid hybrid yeast S . pastorianus ( S . cerevisiae x S . eubayanus ) tolerates the cold temperatures utilized in lager beer production due to the sub-genome of the cold adapted S . eubayanus [51–56 , 107–109] . Indeed , creation of de novo hybrids between S . cerevisiae and cold tolerant species S . uvarum , S . eubayanus , S . arboricola , and S . mikatae all show similar ability to ferment at 12°C [109] . A pair of recent studies show that mitochondrial inheritance in hybrids is also important in heat and cold tolerance , with the S . cerevisiae mitotype conferring heat tolerance and S . uvarum and S . eubayanus mitotypes conferring cold tolerance [106 , 110] . The hybrid ancestor used for our laboratory evolution experiments at both 15°C and 30°C has S . cerevisiae mitochondria , but exploring how this has influenced the evolution of these hybrids is worthy of further work . Though our work here is complicated by utilizing multiple selection pressures ( nutrient limitation and cold temperature ) , several patterns are suggestive of temperature specific adaptations in evolved hybrids . We observe LOH events exclusively favoring the retention of the S . uvarum allele , and we demonstrate a fitness advantage of the S . uvarum allele compared to the S . cerevisiae allele at PHO84 . The temperature sensitivity of the PHO84 allele is a curious phenomenon for which we do not yet have a clear understanding . One potential connection is the need for inorganic phosphate for various processes involved in stress response , including heat shock and activation of the PKA pathway , for which PHO84 is required [86 , 111–113] . At the level of the protein , one potential region for further investigation of causal temperature sensitivity is the cytoplasmic loop VI of the Pho84 protein , from amino acid residues 283–324 , a region which contains 13 radical substitutions between S . cerevisiae and S . uvarum ( S8 Fig; S9 Fig ) . These substitutions include changes from hydrophobic residues to charged residues , which could change temperature sensitivity . The promoter , which is quite divergent between the two species , may also be important . A genetic screen for S . cerevisiae growth at low temperatures found that uptake of phosphate is a growth limiting factor and implicated the overexpression of the genes PHO84 , PHO87 , PHO90 , and GTR1 in growth at 8°C [114] . More specifically , the authors found that both PHO84 and GTR1 ( which are located close together on chromosome XIII ) must be overexpressed to produce a growth phenotype at low temperatures . While we show that S . uvarum PHO84 alone is sufficient to produce a fitness benefit at cold temperatures , we did not assay expression nor conduct promoter swaps , which could shine light on the basis of PHO84 temperature sensitivity as well . However , our results do suggest that the introduction of S . uvarum PHO84 into S . cerevisiae strains may prove useful for industrial applications of which growth at low temperatures is required . Overall , PHO84 provides an interesting example of identifying a gene and pathway previously not appreciated for a role in temperature adaptation , and highlights using multiple environments to better understand parental species’ preferences and potentially environment specific incompatibilities . More broadly , through the lens of PHO84 , we establish LOH as an important molecular mechanism in hybrid adaptation , but we also show that this mutation type has fitness tradeoffs . The selection of a particular species’ allele may confer a fitness advantage in a given environment , but at a risk of extinction if the environment changes . Furthermore , such mutations rarely affect single genes , and instead operate on multigenic genomic segments , leading to a further pleiotropic benefit and/or risk even in environments unrelated to the initial selective regime . Relatively constant environments such as those found in the production of beer and wine may offer fewer such risks , where hybrids may find a particular niche that is less variable than their natural environment . Future efforts are warranted to explore how variable environments influence hybrid evolution and the extent of antagonistic pleiotropy in hybrid genomes . However , because LOH has been documented in a variety of different genera and taxa that experience a range of environments , it’s likely that our results have broad implications . In conclusion , we illuminate pathways in which hybridization may allow adaptation to different temperature conditions . Mounting evidence suggests that anthropogenic climate change and habitat degradation are leading both to new niches that can be occupied by hybrids , as well as to new opportunities for hybridization due to changes in species distribution and breakdown of prezygotic reproductive isolation barriers [115–117] . Some researchers have speculated that this process is particularly likely in the arctic , where numerous hybrids have already been identified [118] . Our work supports the idea that portions of these hybrid genomes can be biased in parental representation by the environment in the initial generations following hybridization , and that this selection on species’ genetic variation may be beneficial or detrimental as conditions change .
Strains used to inoculate the laboratory evolution experiments were: S . cerevisiae diploid ( YMD139 , YMD140 ) , S . uvarum diploid ( YMD366 ) , and a lab-derived diploid hybrid S . cerevisiae x S . uvarum ( YMD129 , YMD130 ) . These strains and those used to gauge relative fitness of PHO84 allele replacements in competition assays were previously utilized by Smukowski Heil et al . [66] . All strains are listed in S4 Table . Continuous cultures were established using media and conditions previously described with several modifications to account for a temperature of 15°C [66 , 72] . Individual cultures were maintained in a 4°C room in a heated water bath such that the temperature the cultures experienced was 15°C , as monitored by a separate culture vessel containing a thermometer . The dilution rate was adjusted to approximately 0 . 08 volumes per hour ( for 20 mL chemostats , 1 . 6 mL/hour ) , equating to about 3 generations per day . Samples were taken twice a week and measured for optical density at 600 nm and cell count; microscopy was performed to check for contamination; and archival glycerol stocks were made . By 200 generations , 2/16 hybrid populations , 10/12 S . cerevisiae diploid populations , and 0/6 S . uvarum diploid populations had evolved a cell-cell sticking phenotype consistent with flocculation . The experiment was terminated at 200 generations and flocculent and non-flocculent populations were sampled from the final timepoint and submitted for whole genome sequencing ( 40 populations total , some cultures had only a flocculent or non-flocculent population while some cultures had both sub-populations ) . Populations from vessels that experienced flocculation were isolated as described in [95] , and are denoted with “F” . Briefly , 1 mL of each flocculent population was pipetted directly from the vessel upon the termination of the experiment and archived in glycerol stocks . Colonies were struck out from glycerol , inoculated into liquid culture and grown overnight at room temperature . From overnight cultures that displayed a clumping , and/or settling , phenotype , new glycerol stocks were made and one clone from each evolved population was selected for sequencing . DNA was extracted from each population using the Hoffman–Winston protocol ( Hoffman and Winston 1987 ) and cleaned using the Clean & Concentrator kit ( Zymo Research ) . Nextera libraries were prepared following the Nextera library kit protocol and sequenced using paired end 150 bp reads on the Illumina NextSeq 500 machine . The reference genomes used were S . cerevisiae v3 ( Engel et al . 2014 ) , S . uvarum ( Scannell et al . 2011 ) , and a hybrid reference genome created by concatenating the two genomes . Variant calling was conducted on each population using two separate pipelines . For the first pipeline , we trimmed reads using trimmomatic/0 . 32 and aligned reads to their respective genomes ( S . cerevisiae . , S . uvarum , or a concatenated hybrid genome ) using the mem algorithm from BWA/0 . 7 . 13 , and manipulated the resulting files using Samtools/1 . 7 . Duplicates were then removed using picard/2 . 6 . 0 , and the indels were realigned using GATK/3 . 7 . Variants were then called using Samtools ( bcftools/1 . 5 with the–A and–B arguments ) , freebayes and lofreq/2 . 1 . 2 . The variants were then filtered using bcftools/1 . 5 for quality scores above 10 and read depth above 20 . For the second pipeline , reads were trimmed using Trimmomatic/0 . 32 and aligned using Bowtie2/2 . 2 . 3 , then preprocessed in the same manner as the first pipeline . Variants were then called using lofreq/2 . 1 . 2 and freebayes/1 . 0 . 2-6-g3ce827d ( using the—pooled-discrete—pooled-continuous—report-genotype-likelihood-max—allele-balance-priors-off—min-alternate-fraction 0 . 05 arguments from bcbio ( https://github . com/bcbio/bcbio-nextgen ) ) . Variants were then filtered using bedtools/2 . 25 . 0 and the following arguments ( S6 Table ) . In both variant calling pipelines , variants were filtered against their sequenced ancestors and annotated for gene identity , mutation type , and amino acid change consequence [119] . Final variant calls were manually confirmed through visual inspection in the Integrative Genomics Viewer [120] ( 1550 mutations checked in total ) . For comparisons with clones evolved at 30°C which were analyzed using a different pipeline [66] , we called variants on the previously published 30°C sequencing data using the same computational pipelines described here , and completely recapitulated the previous true positive variant calls . Overnight cultures were resuspended by vortexing for three seconds . Highly flocculant clones settled out of solution within seconds of vortexing , complicating controlled quantitative measurement of the phenotype . Instead , we relied on visual observation within the first few seconds after vortexing . We utilize competitive growth as a measurement of strain fitness . The pairwise competition experiments were performed in replicate in 20 ml chemostats as previously described [66 , 121] . Briefly , a S . cerevisiae x S . uvarum hybrid tagged with a neutral GFP marker is grown to steady state in parallel with a query strain . When cultures have achieved steady state ( approximately 10–15 generations ) , the GFP and non-GFP cultures are mixed at a 50:50 concentration . The proportion of GFP to non-GFP cells is monitored approximately every 2 generations for a total of five sampling points ( approximately 10 generations , 25 total generations ) using a BD Accuri C6 flow cytometer . Competitive fitness is calculated as the slope of the linear region of ln [dark cells/GFP+ cells] versus generations . Efforts were made to have at least two replicates for each fitness measurement , but technical errors in the running of the fitness assays resulted in some clones having no replicates . Data used to estimate fitness can be found in S1 Data . The competition experiments performed at 15°C were modified as described above for the evolution experiments . For all cold-evolved hybrid populations , one to two clones were isolated for use in competition experiments . Clones from P1-15°C and P3-15°C were PCR validated to have the chromosome XIII LOH event , but no other LOH , CNV , or single nucleotide variants were screened in these or any other clone tested . | Organisms are facing rapid alterations to their habitat due to climate change , the introduction of invasive species , habitat fragmentation , and other human mediated transformations . How species will survive and adapt to these changes is one of the biggest questions of our time . Hybridization , or the mating of different species , offers a potential solution , as it immediately introduces novel genetic variation genome wide . To investigate how hybrids adapt to new environments , and how the environment influences hybrid genomes , we created hybrid yeast in the lab and evolved them under different nutrient limited conditions and at different temperature regimes for hundreds of generations . We show that genetic variation introduced from a cold tolerant species of yeast helps a hybrid adapt to a phosphate-limited cold temperature environment , and thus that the environment can influence which species’ genes persist and which species’ genes are lost in the generations following a hybridization event . | [
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"and",
"anal... | 2019 | Temperature preference can bias parental genome retention during hybrid evolution |
The coronaviruses ( CoVs ) are enveloped viruses of animals and humans associated mostly with enteric and respiratory diseases , such as the severe acute respiratory syndrome and 10–20% of all common colds . A subset of CoVs uses the cell surface aminopeptidase N ( APN ) , a membrane-bound metalloprotease , as a cell entry receptor . In these viruses , the envelope spike glycoprotein ( S ) mediates the attachment of the virus particles to APN and subsequent cell entry , which can be blocked by neutralizing antibodies . Here we describe the crystal structures of the receptor-binding domains ( RBDs ) of two closely related CoV strains , transmissible gastroenteritis virus ( TGEV ) and porcine respiratory CoV ( PRCV ) , in complex with their receptor , porcine APN ( pAPN ) , or with a neutralizing antibody . The data provide detailed information on the architecture of the dimeric pAPN ectodomain and its interaction with the CoV S . We show that a protruding receptor-binding edge in the S determines virus-binding specificity for recessed glycan-containing surfaces in the membrane-distal region of the pAPN ectodomain . Comparison of the RBDs of TGEV and PRCV to those of other related CoVs , suggests that the conformation of the S receptor-binding region determines cell entry receptor specificity . Moreover , the receptor-binding edge is a major antigenic determinant in the TGEV envelope S that is targeted by neutralizing antibodies . Our results provide a compelling view on CoV cell entry and immune neutralization , and may aid the design of antivirals or CoV vaccines . APN is also considered a target for cancer therapy and its structure , reported here , could facilitate the development of anti-cancer drugs .
The Coronaviridae is a large family of enveloped , plus-RNA viruses . They are involved in respiratory , enteric , hepatic and neuronal infectious diseases in animals and humans that lead to important economic losses [1] , [2] , as well as to high mortality rates in severe acute respiratory syndrome CoV ( SARS-CoV ) infections [3] . The CoVs are a numerous group of Coronaviridae . They have been clustered in the Coronavirinae subfamily , which includes three approved genera , Alpha- , Beta- and Gammacoronavirus , as well as a tentative new genus , the Deltacoronavirus [4] . Representative CoV species in each genus are Alphacoronavirus 1 ( comprising transmissible gastroenteritis virus ( TGEV ) , porcine respiratory CoV ( PRCV ) and related canine and feline CoVs ) , Human coronavirus ( HCoV-229E and HCoV-NL63 , genus Alphacoronavirus ) , Murine coronavirus ( including mouse hepatitis virus ( MHV ) , genus Betacoronavirus , cluster A ) , Severe acute respiratory syndrome-related coronavirus ( SARS-related CoV , genus Betacoronavirus , cluster B ) , Avian coronavirus ( including infectious bronchitis virus ( IBV ) , genus Gammacoronavirus ) , and Bulbul-CoV ( tentative genus Deltacoronavirus ) [4] . CoV particles display characteristic large surface projections or peplomers ( 17–20 nm ) comprised of homotrimers of the spike glycoprotein ( S ) , a type I membrane protein [1] , [5] . The peplomers have a globular portion connected by a protein stalk to the transmembrane domain [6] . The globular region is formed by the N-terminal S1 region , whereas the stalk corresponds to the membrane-proximal S2 region , which mediates virus fusion to host cells and adopts a helical structure characteristic of class I virus fusion proteins [7] . Determinants of CoV tropism locate at the S1 region [1] , [8] , which mediates attachment of CoV particles to cell surface molecules , initiating virus entry into cells and infection . There is considerable variability in receptor usage among the CoVs . Most Alphacoronavirus such as TGEV and HCoV-229E use APN [9] , [10] , whereas the related HCoV-NL63 uses a distinct cell entry receptor , the human angiotensin converting enzyme 2 ( ACE2 ) [11]; SARS-CoV also recognizes the ACE2 receptor [12] . SARS and NL63 CoV bind to common regions of the ACE2 protein , although the structures of their receptor-binding domains ( RBDs ) are quite distinct [11] , [13] . MHV uses the cell adhesion molecule CEACAM1a [14]; a recent crystal structure showed that the MHV RBD adopts a galectin-like fold [8] . The use of alternative receptors that confer extended tropism has been described for SARS-CoV , MHV and TGEV [1] , [8] . The mammalian APNs ( CD13 ) are type II cell surface metalloproteases whose large glycosylated ectodomain has a zinc metal ion at the active site [15] . APN is linked to many cell functions , leading it to be termed the “moonlighting enzyme” [15] . Animal models confirmed a role for this cell surface enzyme in angiogenesis [16] . Peptides and inhibitors that target APN showed a link between this protein and tumor growth and invasion [17] , [18] . APN is a target for cancer chemotherapies; drugs that bind this protein have been developed to treat tumors , some of which are in clinical trials [19] . As mentioned above , APN is also a major CoV cell entry receptor [1] , [9] , [10] . CoV recognition of APN is species-specific , and specificity is associated with N-linked glycosylations in the APN protein [20] . Cell tropism and immune neutralization have been extensively studied in some porcine Alphacoronavirus , such as the enteropathogenic TGEV and porcine respiratory CoV ( PRCV ) , a non-enteropathogenic virus derived from TGEV [21] . Both viruses use porcine APN ( pAPN ) for cell entry . The APN-binding domain in TGEV , PRCV and other Alphacoronavirus locates at the C-terminal portion of the S1 region [8] , [22] , [23] , which bears epitopes recognized by CoV-neutralizing antibodies [22] , [23] , [24] , [25] . Most TGEV-neutralizing antibodies cluster at antigenic site A [25] , [26] , comprised within the RBD at the S1 region ( Figure 1A ) [22]; the other antigenic sites defined in the TGEV S1 region ( B through D ) are outside the RBD ( Figure 1A ) [21] . To date , there is no structural information available on antibody neutralization and APN recognition by Alphacoronavirus . We determined crystal structures of the PRCV RBD in complex with the pAPN ectodomain , and the TGEV RBD in complex with the neutralizing monoclonal antibody ( mAb ) 1AF10 [25] . The RBD adopts a β-barrel fold , with a distinct protruding tip engaged in pAPN recognition . The structures show how these porcine Alphacoronavirus recognize its cell entry pAPN receptor and how immune neutralization of these CoVs is achieved by antibody targeting of receptor-binding residues in the S protein . The mechanisms used by TGEV to escape immune neutralization and the evolution of receptor recognition in the CoV family are discussed .
APN receptor recognition and envelope S antigenicity are well documented in TGEV and related PRCV . The pAPN-binding domain was mapped within residues 506 to 655 of the mature TGEV S polypeptide [22] , whereas TGEV mAb-resistant ( mar ) mutants defined four antigenic sites ( C , B , D and A ) [24] , [26] ( Figure 1A ) . Antigenic sites C and B are not present in the PRCV S protein . Antigenic site A determinants are located within the pAPN-binding domain at the C-terminal moiety of the TGEV and PRCV S1 regions ( Figure 1A ) [21] , [22] . We recently reported the modular dissection of the N-terminal S1 region of TGEV and PRCV , and the preparation of soluble S1 length variants with single antigenic sites [27] . We produced a recombinant short S protein fragment termed SA , which comprises only residues 481 to 650 of the TGEV S protein that binds cell surface pAPN ( Figure 1B ) and displays conformational epitopes for the three antigenic A subsites ( Aa , Ab , and Ac ) ( Figure 1C ) . Antibodies clustered at the Aa ( 1BB1 ) , Ab ( 1DE7 ) and Ac ( 1AF10 and 6AC3 ) subsites blocked binding of the soluble SA protein to pAPN ( Figure 1D ) . The SA protein therefore includes the pAPN-binding domain of TGEV and epitopes for site A-neutralizing mAb . We applied X-ray crystallography to S protein variants containing the RBD of the related TGEV and PRCV , and have identified how these Alphacoronavirus bind to the cell surface pAPN and its inhibition by neutralizing antibodies . We attempted crystallization of the soluble pAPN-binding SA protein derived from the TGEV S , alone and in complex with several neutralizing mAbs . Crystals were prepared with the SA protein in complex with the Fab fragment of the 1AF10 mAb [25]; the structure of the complex was determined and refined using diffraction data extending to 3 . 0 Å resolution ( Materials and Methods; Table 1 ) . The asymmetric unit of the crystals contains two antibody-RBD complexes , one of which is shown in Figure 2 . Residues Pro507 to Val650 of the TGEV S protein , previously identified as the pAPN-binding domain ( Figure 1A ) [22] , were well defined in the crystal structure . They folded in a single domain structure , the RBD of TGEV ( Figure 2A ) . The RBD adopts a β-barrel fold formed by two β-sheets with five β-strands each ( scheme in Figure S1A ) . N- and C-terminal ends are on the same side of the domain ( terminal side ) , which presumably lies close to other S protein domains; at the opposite side , two β-turns ( β1–β2 and β3–β4 ) form the tip of the barrel ( Figure 2A ) , where the mAb binds to the RBD . The immunoglobulin ( Ig ) variable domains of the mAb heavy ( VH ) and light ( VL ) chains contact the β1–β2 , β3–β4 and β5–β6 regions of the TGEV RBD ( Figure 2B ) , burying a virus protein surface of ∼810 Å2 . The buried surface of the 1AF10 mAb is ∼750 Å2 , with equal contribution by the VH ( 51% ) and VL ( 49% ) Ig domains . Complementarity determining regions ( CDR ) of the antibody heavy ( H3 ) and light ( L1 and L3 ) chains , the N-terminus of the light chain and the C , C′ and C″ β-strands of the VH domain contact the viral RBD tip ( Figure 2B ) . The CDR-H3 of the 1AF10 mAb is relatively long , with two-residue insertion ( Tyr103H and Asp104 H ) relative to other homologous H3 loops in reported mAb structures ( Table S1 ) . The RBD β1–β2 hairpin with Tyr528 at its tip is at the center of the interacting surface and penetrates between the VL and VH Ig domains of the 1AF10 mAb ( Figure 2B and 2C ) . Similar antibody-antigen recognition is described for some peptides and is common for small hapten molecules [28] , [29] . The RBD β1–β2 region contributed 73% of the RBD surface buried by the 1AF10 mAb , and docked between the 1AF10 mAb variable domains ( Figure 2B ) . The β-turn is fully buried between the mAb Ig domains ( Figure 2C ) , forming a contact network with mAb residues ( Figure 2D ) . The RBD residue Tyr528 at the bottom of the pocket contacts mAb residues Trp47H and Tyr107H , whereas its hydroxyl group is hydrogen bonded to the side chain of Gln89L and main chain carbonyl of Tyr107H ( Figure 2C and 2D ) . These structural findings on 1AF10 recognition of the RBD β1–β2 region correlate with 1AF10 mAb binding to peptides ( MKRSGYGQPIA533 ) that include this hairpin region [24] . The RBD β3–β4 and β5–β6 regions are at the periphery of the epitope ( Figure 2B ) ; their contribution to interaction with 1AF10 is smaller than that of the β1–β2 region , representing respectively ∼17% and 10% of the RBD surface buried by the mAb . They contact either the VL or VH Ig domains ( Figure 2B ) . RBD residues Leu570 and Trp571 at the β3–β4 loop contact the N-terminus , CDR-L1 and CDR-L3 of the VL domain , whereas the β5–β6 loop contacts the long CDR-H3 loop ( Figure 2B and 2C ) . To characterize CoV attachment to its APN receptor , we attempted crystallization of the pAPN ectodomain in complex with TGEV and PRCV S protein variants comprising their RBDs ( Materials and Methods ) . Crystals were obtained only with a mixture of a PRCV S protein ( S3H ) and the pAPN . Using these crystals , we determined the structure of the PRCV RBD-pAPN complex by molecular replacement using previously solved structures of the TGEV RBD shown in Figure 2 ( 97% sequence identity ) and of the pAPN ectodomain ( Materials and Methods and Table 1 ) . The asymmetric unit of the crystals contained two macromolecular RBD-pAPN complexes ( Figure 3A ) . The PRCV RBD adopts a β-barrel fold like the TGEV RBD ( Figure S1 ) . Each pAPN molecule was engaged by the tip of a single PRCV RBD molecule , which bears two exposed aromatic residues ( Tyr and Trp ) ( Figure 3A , in red ) , and they bound to a membrane-distal region of the pAPN ectodomain ( Figure 3A ) . The RBD N- and C-terminal ends and the remaining CoV S are also distant from the pAPN , and are unlikely to contact the receptor molecule . Based on a cryo-EM structure of the SARS-CoV S [6] , the RBD must be also at the viral-membrane distal side of the S and therefore , the receptor binding edge must be accessible for CoV binding to the APN receptor . The pAPN is a type II membrane protein and the N-terminal end of the ectodomain must be near the cell membrane ( Figure 3A ) . The 25 N-terminal residues of the crystallized pAPN ectodomain are largely disordered in the structure and they might form a flexible region close to the cell membrane . The pAPN ectodomain is composed of four domains ( Figure 3A ) . Domain I ( orange ) is made of β-strands , domain II ( yellow ) adopts a thermolysin-like fold bearing a zinc ion at the catalytic site , domain III ( red ) is a small β-barrel domain , and the C-terminal domain IV ( green ) is composed of alpha-helices ( domain boundaries are shown in Figure S2 ) . The pAPN molecule structure is closely related to that of the human endoplasmic reticulum aminopeptidase-1 [30] , [31] ( root-mean-square deviation of 2 . 3 Å for 791 residues sharing 33% sequence identity , based on DALI server ) . Domain II bearing the enzyme active site is the most related domain ( 47% identity ) , whereas domain IV is the most distinct ( 22% identity ) . The zinc ion is coordinated to conserved residues at the pAPN active site in domain II ( Figure S2 ) . The active site conformation is similar to that of other aminopeptidases ( Figure S3 ) . The pAPN crystallized in complex with the PRCV RBD had an open conformation [30] , [31] , [32] , in which domain IV was ∼20–25 Å from domains I and II; this creates a central cavity in which the zinc ion at the catalytic site is highly accessible ( Figure 3A ) . The mammalian APNs are cell surface metalloproteases that form membrane-bound dimers [33] . The crystallized pAPN ectodomain also behaved as a dimer in solution ( Figure S4 ) . The pAPN dimeric assembly showed in Figure 3A buried a large accessible surface ( ∼980 Å2 ) in each monomer . The dimerization surface comprises 29 residues spread across domain IV , which are distinct from those recognized by CoV ( Figure S2 ) . Similar dimeric assemblies were observed in two crystal structures determined for the pAPN ectodomain alone ( not shown ) , crystallized using distinct conditions . The pAPN molecular assembly shown here might thus be representative of the dimer described for mammalian APN on membrane surfaces [33] . In the crystals of the PRCV RBD-pAPN complex , the RBD tip contacts a membrane-distal region of the pAPN ectodomain ( Figure 3A ) . The conformations of the receptor-binding loops ( β1–β2 and β3–β4 ) at the tips of the two PRCV β-barrel domains in the structure are identical ( Figure S1B ) , suggesting very similar RBD-pAPN interactions in both complexes of the asymmetric unit . The virus-receptor interaction buried ∼870 Å2 of the virus protein , 60% of which corresponded to the β1–β2 region ( Figure 3B ) and 30% to the β3–β4 turn ( Figure 3C ) . The size of the pAPN surface buried by the RBD was similar ( ∼770 Å2 ) , and included pAPN residues ranging from alpha helix 19 ( α19 ) to 22 ( α22 ) in domain IV , and a few domain II residues ( Figure S2 , Table S2 ) . The end of the pAPN helix α19 and helix α21 contacted the β1–β2 region of the RBD ( Figure 3B ) . The Tyr side chain ( Tyr528 in TGEV ) , which protrudes at the β-turn in PRCV and TGEV RBDs ( Figure 3B and 3D ) , is almost fully buried in the complex , locating between the first N-acetyl glucosamine ( NAG7361 ) linked to pAPN Asn736 , the end of helix α19 , and the first half of helix α21 ( Figure 3B ) . The hydroxyl group of the RBD Tyr528 was hydrogen bonded to side chains of pAPN residues Glu731 and Trp737 , and contributed to virus-receptor binding specificity . The preceding RBD Gly527 residue was at the pAPN proximal side of the β-turn , hydrogen bonded to the pAPN Asn736 main chain; at the opposite side , the RBD Gln530 side chain formed a network of hydrogen bond interactions with pAPN NAG7361 and Asn736 side chain ( Figure 3B ) . The N-acetyl moiety of the glycan also interacted with RBD residues at the β2 and β6 strands ( Figure 3B , Table S2 ) . The pAPN N-linked glycan and surrounding residues that contact the CoV RBD β1–β2 region in the structure were identified as one of the APN determinants of the CoV host range [20] . The second relevant virus-receptor interacting region engaged a β-turn at the beginning of the RBD β3–β4 loop ( Figure 3C and 3D ) . The unique RBD Trp571 residue , which protrudes at the turn , docked in a pAPN cavity formed by the coils that precede helices α22 in domain IV and α5 in domain II ( Figure 3C and S2 ) . The bulky side chain of the RBD Trp571 residue packed against pAPN residues His786 and Pro787 , and its imino group was hydrogen bonded to the main chain carbonyl of Asn783 ( Figure 3C ) . The RBD Trp571 as well as the RBD Tyr528 at the β-barrel tip in TGEV and PRCV appear to be central residues in the virus-receptor interaction , as they contact with many pAPN residues and contribute also to binding specificity by mediating polar interactions with the pAPN ( Table S2 ) . To confirm the contribution of the PRCV or TGEV RBD β-barrel tip in pAPN receptor recognition , we analyzed binding of wild type and mutant TGEV RBD proteins to cell surface-expressed pAPN ( Figure 4A ) . Mutations in the three regions ( β1–β2 , β3–β4 and β5–β6 ) that build the receptor binding edge of the β-barrel decreased RBD binding to pAPN , whereas mutations outside the receptor-binding region ( V617Ngly ) had no effect on receptor recognition . Deletion of the pAPN Asn736 glycosylation site also abolished TGEV RBD binding to cell surface-expressed pAPN ( Figure 4B ) . Deletion of the homologous glycan in feline APN similarly prevents cell infection by feline , canine and porcine CoVs , all of which share the glycan-binding Tyr residue in the β1–β2 turn ( see below ) , whereas addition of this glycan to human APN is sufficient to render it a TGEV receptor [20] . We determined the crystal structures of the related TGEV and PRCV RBDs bound to two distinct ligands . The RBDs adopt β-barrel structures with small differences in the ligand binding loops ( Figures S1 ) . In the RBD , each of the two highly twisted β-sheets that build the β-barrel is formed by five β-strands ( Figure 5A ) . The bent β-strand 5 ( β5 ) crosses both β-sheets and has a β-bulge at Asn608 ( Figure 5A , magenta ) . At one side of the β-barrel , all β-strands are antiparallel ( Figure 5A , cyan ) , whereas on the opposite β-sheet , the β1 and β3 strands run parallel ( Figure 5A , blue ) . N-linked glycans cluster at one side of the β-barrel ( Figure 5A ) . N- and C-terminal ends of the RBD , where other S protein domains presumably lie , are opposite the ligand-binding tip of the β-barrel , where the pAPN-binding Tyr and Trp residues protrude ( Figure 5A ) . A DALI search of structural homologs showed the greatest similarity ( Z score of 10 ) with the RBD of the ACE2 receptor-binding HCoV-NL63 ( root-mean-square deviation of 2 . 4 Å for 103 residues ) , the other Alphacoronavirus RBD whose structure is known [11] . The cores of the TGEV and HCoV-NL63 β-barrel domains are structurally similar , but the loops at the tips ( Figure 5B and 5D ) . The tip region of the HCoV-NL63 RBD is the ACE2 receptor-binding edge and has a “bowl”-shaped conformation ( Figure 5C ) that differs from the TGEV RBD protruding edge . Aromatic residues protrude from the β-turns at the tip of the β-barrel in TGEV , whereas they are partially buried at the center of the “bowl”-shaped edge in HCoV-NL63 ( Figure 5B and 5C ) . The distinct RBD tip conformation in ACE2-binding HCoV-NL63 and in APN-binding TGEV might be a determinant of their distinct cell entry receptor specificities . The degree of sequence identity in the RBD region among members in the species Alphacoronavirus 1 ( ∼90% identity ) suggests a structure closely related to that of TGEV , including conformation of the receptor-binding loops ( β1–β2 and β3–β4 ) at the β-barrel tip ( Figure 6 ) . Therefore , TGEV , PRCV , CCoV and FCoV must recognize the APN receptor in similar fashion . In contrast , the receptor-binding loops at the tip appear to have a different conformation from TGEV in the HCoV-229E RBD , which also binds to the APN . In this CoV , the β1–β2 region has two Cys , as in HCoV-NL63 , and lacks the APN-binding Tyr residue in Alphacoronavirus 1 , although it preserves the two Gly residues found in the TGEV β-turn ( Figure 6 ) . The β3–β4 loop in HCoV-229E is markedly shorter than in TGEV , but it also has a Trp residue . Sequence identities between the RBD of TGEV and IBV ( Gammacoronavirus ) or the Bulbul-CoV ( tentative Deltacoronavirus ) are relatively large ( ∼25% ) , and similarities are found mostly in β-strands and at the RBD C-terminal half ( Figure 6 ) . These data indicate a conserved RBD fold between Alphacoronavirus and Gamma- or Deltacoronavirus . There is less sequence similarity between the Alpha- and Betacoronavirus RBD regions ( ∼10% ) , which correlates with notable structural differences between their RBDs [8] , [11] , [13] . The RBDs of the SARS and MHV Betacoronavirus adopt folds unrelated to the β-barrel shown for Alphacoronavirus . The most TGEV-neutralizing mAbs , including 1AF10 , recognize antigenic site A in the S protein , divided into the Aa , Ab and Ac subsites [24] . To further characterize site A antigenic determinants in the TGEV RBD , we mutated RBD residues targeted by the 1AF10 mAb ( Figure 2 ) and some surrounding residues , and analyzed binding to other site A-specific mAbs . The antigenicity of residues in the β1–β2 region , in the center of the epitope for 1AF10 ( Figure 2C ) , was determined by monitoring mAb binding to RBD mutants with TGEV residue substitutions Gly527 ( G527D ) , Tyr528 ( Y528A ) and Gly529 ( G529D ) ( Figure 7A ) . All three substitutions abolished RBD binding by the Ac subsite-specific mAbs 1AF10 and 6AC3 . The Y528A RBD mutant was recognized by Aa- ( 1BB1 ) and Ab-specific ( 1DE7 ) mAbs ( Figure 7A ) , and mAb 1DE7 also bound the G529D mutant . In contrast to the antibody binding profile of the Y528A RBD mutant , Ala substitution of the TGEV Trp571 residue ( W571A ) , a pAPN-binding residue in the β3–β4 loop at the periphery of the RBD epitope for 1AF10 ( Figure 2C ) , did not affect binding by the Ac-specific mAbs ( 1AF10 and 6AC3 ) , whereas RBD recognition by 1BB1 and 1DE7 mAbs was greatly reduced ( Figure 7A ) . Deletion of the β3–β4 turn ( LWD572A mutant ) reduced 6AC3 mAb binding to the RBD markedly , with a partial reduction in 1AF10 binding ( Figure 7A ) ; this indicates that mAb 6AC3 recognizes a broader epitope , which correlates with its higher TGEV neutralization activity [25] . Replacement with Ala of RBD residues Thr631 and Asn632 at the β5–β6 hairpin , which contacts the 1AF10 mAb in the RBD-1AF10 structure ( Figure 2C ) , reduced binding by all site A-specific mAb ( Figure 7A ) . This might be a result of a conformational effect induced on the nearby β1–β2 region of the RBD . Results for antibody binding to RBD mutants showed that site A epitopes extend across the TGEV RBD tip , although there are some differences among the three A subsites ( Figure 7B ) . The epitopes recognized by Aa- and Ab-specific mAbs bear the exposed TGEV Trp571 residue at the β3–β4 loop , whereas epitopes for the Ac-specific mAbs center on Tyr528 in the β1–β2 turn . None of the mAb tested simultaneously targeted the two aromatic side chains ( Tyr and Trp ) at the tip of the TGEV RBD that bind to the pAPN . Subsite-specific residues defined by mar mutants ( Lys524 for Aa , Arg577 for Ab and Gly529 for Ac ) might be located at the periphery of their respective epitopes ( Figure 7B ) . Ab and Ac subsites appear to be relatively far apart , with the Aa epitope in an intermediate position . The RBD tip , shown here as the pAPN-binding edge of the domain ( Figure 3 ) , is the main S protein determinant of antigenic site A , recognized by the most effective neutralizing antibodies of TGEV and related CoV infections [25] , [26] .
Here we show how a group of CoVs attaches to the cell surface APN metalloprotease for entry into host cells , and how some CoV-neutralizing antibodies prevent infection . The RBD-receptor complex structures determined for Alphacoronavirus indicate that the conformation of the receptor binding edge in the envelope S proteins probably determines their receptor-binding specificity . The CoV that bind APN analyzed here have protruding receptor-binding motifs that engage recessed surfaces on the receptor . This mode of receptor recognition is essentially opposite to that reported for CoV binding to the ACE2 receptor , where recessed receptor-binding motifs in the viral RBD cradle exposed surfaces of the ACE2 ectodomain [11] , [13] . In the case of pAPN , an N-linked glycan is also engaged in the virus-receptor interaction . The inherent flexibility of this glycan might facilitate the initial contact of the CoV Tyr residue with APN amino acids , and subsequent virus-receptor interactions could lock the bound Tyr between the glycan and an α-helix ( Figure 3B ) . The glycan N-linked to Asn736 in pAPN is also conserved in canine and feline APN proteins ( Figure S2 ) , as are the viral S protein residues that interact with this glycan in the RBD β1–β2 and the β5–β6 regions ( Figure 6 ) . This unique glycan-virus interaction must thus be conserved among the different CoVs in the species Alphacoronavirus 1 , in accordance with the glycan requirement reported for cell infection by CCoV , FCoV , and TGEV/PRCV [20] . The lack of this glycan in human APN ( Figure S2 ) and the absence of the interacting Tyr residue in the β1–β2 region of HCoV-229E RBD ( Figure 6 ) imply distinct virus-APN local contacts in humans . As shown for the Alphacoronavirus 1 group , however , HCoV-229E probably has a protruding receptor-binding edge in the envelope S , responsible for its APN-binding specificity . The structure of the RBD-1AF10 complex , together with structure-guided RBD mutagenesis and mAb binding data , demonstrated that the receptor-binding region is a major antigenic determinant in the envelope S protein of CoV that bind APN . Potent TGEV-neutralizing antibodies , such as the 6AC3 mAb [25] , target key APN-binding residues in the S ( Figure 7 ) , preventing infection . Data from antibody neutralization-resistant TGEV mar mutants nonetheless show that some substitutions can be accommodated in the receptor-binding region of Alphacoronavirus , which confer the ability to escape immune neutralization , while preserving the receptor-binding affinity necessary for cell entry [24] , [26] . Our results thus demonstrate that the receptor-binding region in Alphacoronavirus is under selective pressure from the immune system , as described for other viruses [34] , [35] , [36] , [37] . It is tempting to speculate that immune pressure on exposed receptor-binding residues in the CoV S could lead to conformational changes in receptor-binding edges of CoV RBDs . This would result either in changes in the APN-recognition mode observed with HCoV-229E and TGEV , or in conformational changes in the RBD tip that lead to a receptor specificity switch for cell entry , as observed for HCoV-NL63 [11] . Virus use of recessed binding regions , as for HCoV-NL63 , is a well-defined strategy for hiding conserved receptor-binding residues from antibodies [34] , [36] . Like HCoV-NL63 , SARS-CoV uses a recessed , although broader ACE2-binding surface , which can accommodate mutations that permit cross-species receptor recognition [13] . It remains to be understood why , despite major changes in the receptor-binding region , all these CoV use metalloproteases as cell entry receptors . In the course of our studies , we also determined the crystal structure of the cell surface APN , an important target for cancer therapies . The domain architecture of APN resembles that of related aminopeptidases [30] , [31] , [32] . Here we show a unique dimer configuration for the APN , mediated by its domain IV , the most divergent domain among M1 aminopeptidases [31] . The implication of these structural findings for APN biology will require further biochemical analysis . Knowledge of the structure is leading to research on the mechanism of action of numerous anti-tumor compounds that target mammalian APN [19]; these studies will be fundamental for improving drug specificity . The detailed view of the APN-CoV interaction shown here might also lead to development of small molecules to block CoV infection . We have identified the receptor-binding region as the major antigenic site in the Alphacoronavirus envelope S , which could guide the design of immunogens that boost CoV-neutralizing immune responses to key motifs for virus cell entry .
Design of soluble S proteins variants of TGEV and PRCV has been described [27] . The SA protein containing the RBD of TGEV was derived from the SC11 strain , and contains residues 481 to 650 of the TGEV S , an N-terminal influenza hemagglutinin HA peptide , and either a FLAG mAb epitope ( monovalent SA-Flag variant ) or the human IgG1 Fc portion ( bivalent SA-Fc variant ) at the C-terminal end . The engineered soluble pAPN contains residues 36 to 963 ( ectodomain ) of the cell surface protein fused to HA and FLAG tags at the N and C terminus , respectively [27] . The soluble S protein crystallized in complex with the pAPN was derived from the PRCV HOL87 strain ( S3H in [27] ) , and contains the N-terminal 426 residues of the PRCV S protein and same C-terminus as the TGEV-derived SA protein [27] . A recombinant membrane bound pAPN with an HA tag at the C-terminal end was engineered for cell surface expression . Thrombin recognition sequences were introduced between the tags and the viral or pAPN protein sequences . Proteins were produced in transiently transfected 293T or stably transfected CHO-Lec 3 . 2 . 8 . 1 ( CHO-Lec ) cells as described [27] , and concentration in cell supernatants determined by ELISA . Proteins prepared in CHO-Lec cells were used in crystallization experiments . Hybridoma cells secreting the TGEV S mAbs were grown in DMEM supplemented with 10% FCS in roller bottles . Proteins secreted to culture supernatants were initially purified by affinity chromatography . All protein samples were further purified by size exclusion chromatography in HEPES-saline buffer ( 20 mM HEPES , 150 mM NaCl ) pH 7 . 5 . The Fab fragment of the 1AF10 mAb was prepared by papain digestion of the purified antibody . The reaction was terminated by the addition of E64 ( Sigma ) and the Fab fragment purified by size exclusion and ion exchange chromatography using HEPES-saline buffer pH 8 . 0 . The polypeptide chains of the Ig variable domains of the 1AF10 mAb were determined by sequencing of their cDNA prepared from reverse transcribed mRNA purified from hybridoma cells . Binding of anti-TGEV S or -HA ( control ) mAb to wild type and mutant SA proteins was tested in 96-well plates , using purified mAb or hybridoma supernatants . The SA-Fc fusion proteins in serum-free ( opti-MEM , Invitrogen ) cell supernatants were bound to plastic , and mAb binding monitored by optical density ( OD490 nm ) . At least four SA-Fc protein concentrations ranging from 10 to 1 µg/ml were used in duplicate and average binding determined in each experiment . Binding ratios were determined after correction for background binding . APN binding assays were also carried out with the SA-Fc fusion protein comprising the TGEV RBD . BHK-pAPN cells constitutively expressing cell surface pAPN were used for binding experiments comparing wild type and mutant RBDs , whereas transiently transfected 293T cells were used for analysis of RBD binding to pAPN glycosylation mutants . Binding was monitored as the percentage of stained cells with the Fc fusion proteins and FITC labeled anti-Fc antibodies by Fluorescence-Activated Cell Sorting ( FACS ) , as shown in Figure 1B . The percentage of cells stained was determined for each protein sample and corrected for background staining . pAPN binding ratios for wild type and mutant RBD proteins shown in Figure 4A were determined from the percentage of BHK-pAPN cells stained with same concentration of wild type and mutant SA-Fc proteins . The binding ratios for wild type and mutant pAPN glycosylation mutants shown in Figure 4B were determined from the percentage of SA-Fc stained 293T cells expressing similar amounts of HA-tagged pAPN proteins . Cell surface expression of the pAPN-HA protein was determined with the HA 12AC5 mAb . The TGEV RBD in complex with the 1AF10 Fab fragment was crystallized using the size exclusion-purified complex of a monovalent SA-Flag protein containing the TGEV RBD and the mAb fragment . Crystals of the complex were prepared by the hanging drop method with a 20 mg/ml protein sample and a crystallization solution of 16% PEG-4K , 0 . 2 M NaAc , 0 . 1 M 1 , 2 , 3-octanetriol isomer T and 0 . 1 M Tris buffer pH 8 . 5 . Crystals were frozen with crystallization solution containing 20% ethylene glycol . Diffraction data extending to 3 Å resolution were collected at the ID29 beamline ( TGEV RBD-1AF10 in Table 1 ) . Crystallization of the pAPN ectodomain in complex with porcine CoV S proteins was carried out with mixtures of the receptor protein and several TGEV and PRCV protein variants comprising the receptor-binding region ( SA , S1H and S3H in [27] ) . Crystals appeared only in trials performed with an equimolar mixture of pAPN and the S3H protein derived from the PRCV S at a final protein concentration of 13 mg/ml , and with a crystallization solution of 20% PEG-4K , 0 . 2 M lithium sulfate and 0 . 1 M Tris buffer pH 8 . 5 . Crystals were transferred to crystallization solution containing 20% ethylene glycol and frozen for diffraction data collection at the ID29 beamline ( PRCV RBD-pAPN in Table 1 ) . The structure of the TGEV RBD-1AF10 Fab fragment was initially determined by the molecular replacement ( MR ) method using the PHASER program [38] , and two search models having either the variable or constant regions of the PDB ID 1AIF mAb structure . The 1AF10 Fab model structure was built manually following electron density maps determined from the MR solution , after improvement with the DM program [39] . The 1AF10 Fab structure was refined with the program phenix . refine [40] , which provided an excellent electron density map for building residues 507 to 650 of the TGEV S , as well as four residues of a thrombin recognition site at the C-terminus . Final structure refinement of the complex was carried out with data extending to 3 . 0 Å resolution ( statistics in Table 1 ) . Three cycles of solvent correction , refinement of individual coordinates and atomic displacement parameters combined with TLS were applied in each step of structure refinement with phenix . refine , which was alternated with manual adjustment of the model to the electron density maps . All residues are in allowed regions of the Ramachandran plot . SA protein residues included in the structure of the TGEV RBD are shown in Figure 3D . The structure of the PRCV RBD-pAPN complex was resolved by the MR method using the pAPN structure determined alone ( manuscript in preparation ) and the TGEV RBD structure as search models . MR solutions were obtained for the two pAPN molecules ( chains A and B ) of the asymmetric unit and for one RBD molecule ( chain E ) . The three molecules were adjusted manually and refined with the phenix . refine program . The second RBD molecule ( chain F ) bound to pAPN molecule B was built manually into the electron density map . The 282 residues N-terminal to the PRCV RBD in the S3H protein were largely disordered or degraded during crystallization , and are absent in the structure . The complex structure was refined with the program phenix . refine applying solvent correction , NCS , refinement of individual coordinates and atomic displacement parameters combined with TLS ( Table 1 ) . The current model comprises residues 60 to 963 of the pAPN ectodomain with a zinc metal ion at the pAPN enzyme active site , and residues 283 to 426 of the PRCV S , homologous to the TGEV S residues 507 to 650 that defined the TGEV RBD structure ( Figure 3D ) . All the residues are in allowed regions of the Ramachandran plot . Coordinates and structure factors have been deposited in the Protein Data Bank with ID codes 4F2M ( TGEV RBD-1AF10 ) and 4F5C ( PRCV RBD-pAPN ) . Buried surfaces and residues at the molecular complex interfaces were determined with the PISA server ( http://www . ebi . ac . uk/msd-srv/prot_int/pistart . html ) . Only residues with at least 10% of their surface buried at interfaces in the two independent molecules of the crystal asymmetric units are shown . Figure 2D was prepared with LIGPLOT ( http://www . ebi . ac . uk/thornton-srv/software/LIGPLOT/ ) , Figure 5A with Ribbons [41] and the other structure representations with PyMOL ( pymol . org ) . Structural alignments were carried out with Modeller using a gap penalty of 3 [42] . Accession numbers of the Alphacoronavirus S proteins mentioned are Q0PKZ5 ( TGEV ) , Q65984 ( CCoV ) , P10033 ( FCoV ) , P15423 ( HCoV-229 ) , Q6Q1S2 ( HCoV-NL63 ) , B6VDW0 ( Bulbul-CoV ) and Q9Q9P1 ( IBV ) . The PRCV HOL87 S protein sequence is reported in reference [21] . Sequence identities among S proteins were determined with psiblast ( http://www . ebi . ac . uk/Tools/sss/psiblast/ ) . Accession number for the pAPN protein is P15145 . | The cell surface aminopeptidase N ( APN ) , a membranebound metalloprotease target for cancer therapy , is a major cell entry receptor for coronaviruses ( CoVs ) , agents that cause important respiratory and enteric diseases . In some CoVs , the virus envelope spike glycoprotein ( S ) mediates attachment of the virus particles to the host APN protein and cell entry , which is blocked by antibodies that prevent CoV infections . The crystal structures of the S proteins of two porcine CoV in complex with the pig APN ( pAPN ) or with a neutralizing antibody shown here , reveal how some CoV bind to its cell surface APN receptor and how antibodies prevent receptor binding and infection . The report uncovers a unique virus-receptor recognition mode that engages a glycan N-linked to the pAPN ectodomain , revealing structural determinants of the receptor-binding specificity in CoVs . Neutralizing antibodies target viral residues used for binding to the APN receptor and entry into host cells , showing that efficient CoV neutralization requires immune responses focused toward key receptor binding motifs in the virus envelope . These structural insights , together with the structure of the APN ectodomain , provide a compelling view of relevant cell membrane processes related to infectious diseases and cancer . | [
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"prote... | 2012 | Structural Bases of Coronavirus Attachment to Host Aminopeptidase N and Its Inhibition by Neutralizing Antibodies |
Ischemic strokes have been implicated as a cause of death in Chagas disease patients . Inflammation has been recognized as a key component in all ischemic processes , including the intravascular events triggered by vessel interruption , brain damage and repair . In this study , we evaluated the association between inflammatory markers and the death risk ( DR ) and stroke risk ( SR ) of patients with different clinical forms of chronic Chagas disease . The mRNA expression levels of cytokines , transcription factors expressed in the adaptive immune response ( Th1 , Th2 , Th9 , Th17 , Th22 and regulatory T cell ) , and iNOS were analyzed by real-time PCR in peripheral blood mononuclear cells of chagasic patients who exhibited the indeterminate , cardiac , digestive and cardiodigestive clinical forms of the disease , and the levels of these transcripts were correlated with the DR and SR . Cardiac patients exhibited lower mRNA expression levels of GATA-3 , FoxP3 , AHR , IL-4 , IL-9 , IL-10 and IL-22 but exhibited higher expression of IFN-γ and TNF-α compared with indeterminate patients . Digestive patients showed similar levels of GATA-3 , IL-4 and IL-10 than indeterminate patients . Cardiodigestive patients exhibited higher levels of TNF-α compared with indeterminate and digestive patients . Furthermore , we demonstrated that patients with high DR and SR exhibited lower GATA-3 , FoxP3 , and IL-10 expression and higher IFN-γ , TNF-α and iNOS mRNA expression than patients with low DR and SR . A negative correlation was observed between Foxp3 and IL-10 mRNA expression and the DR and SR . Moreover , TNF-α and iNOS expression was positively correlated with DR and SR . Our data suggest that an inflammatory imbalance in chronic Chagas disease patients is associated with a high DR and SR . This study provides a better understanding of the stroke pathobiology in the general population and might aid the development of therapeutic strategies for controlling the morbidity and mortality of Chagas disease .
Chagas disease is caused by flagellate protozoa Trypanosoma cruzi ( T . cruzi ) and affects 5 . 7 million people worldwide . The disease causes morbidity in about 300 , 000 people disabling for work or daily living activities and causes 12 , 500 deaths annually [1 , 2] . In the chronic phase of Chagas disease , the most common cause of death is sudden cardiac death ( 55–65% of patients ) , usually due to ventricular fibrillation , followed by congestive heart failure ( 25–30% of patients ) and pulmonary or cerebral ischemia ( 10–15% patients ) [3] . Death from cardiac insufficiency has been reported in individuals ( functional class III and IV ) with reduced left ventricular ejection fraction/LVEF ( <35% ) [4] . In patients with reduced or preserved systolic function , ischemic stroke has often been linked as a cause of death [5 , 6] . Postmortem analysis of Chagas disease patients reveals brain lesions in up to 60% of cases due to ischemic stroke [7–10] . Several methods to predict the death risk in patients with chronic Chagas disease have been described based on clinical features [5 , 11 , 12] . Death and stroke are not necessarily related in Chagas disease , cardiovascular diseases involving atherosclerosis and hypertension are major causes of heart attacks and stroke in the population leading to sudden death [13 , 14] . However , inflammation is one of the key drivers of atherosclerotic plaque development [13] . Other established risk factors are high cholesterol , hypertension , diabetes , alcohol use , overweight , stress , smoking , sedentary lifestyle [15] . The effects of stroke depend on which part of the brain is injured and how severely it is affected; a very severe stroke can cause sudden death . In strokes caused by arterial occlusion or ischemic stroke , inflammation has been recognized as a key component of the pathophysiology of the brain [16] . Recent studies have suggested that the immune response is involved in all ischemic processes , including the intravascular events triggered by vessel interruption , brain damage and repair [17 , 18] . A key mediator of endothelial dysfunction is the pro-inflammatory transcription factor NF-κB . This molecule is expressed in endothelial cells and leukocytes and leads to the transcription of pro-inflammatory genes , such as cytokines , chemokines and leukocyte adhesion molecules , including vascular cell adhesion molecule-1 ( VCAM-1 ) and E-selectin [19] . Acute immune activation after stroke is responsible for secondary brain injury [20] . After arterial occlusion , the production of reactive oxygen species ( ROS ) triggers the coagulation cascade and leads to the activation of complement , platelets and endothelial cells [21] . Cerebral ischemia induces the expression of TNF-α , IL-1β , IL-6 and inducible nitric oxide synthase ( iNOS ) , which leads to the upregulation of endothelin receptors in the cerebral arteries [22 , 23] . The immune response generated in this context , dominated by IFN-γ and TNF-α , may facilitate vessel contraction and increase the vulnerability of the brain to cerebral ischemia [24] . Infection by T . cruzi induces a strong inflammatory response dominated by the Th1 pattern , with IFN-γ and TNF-α production and regulated by the IL-10 production [25] . The T . cruzi antigens presented by dendritic cells ( DC ) initiate the programmed differentiation of naïve CD4+ T cells into Th1 ( T-Bet transcription factor; IFN-γ and TNF-α production ) , Th2 ( GATA-3; IL-4 , IL-5 , IL-9 , IL-10 , IL-13 ) , Th17 ( RORγt and RORα; IL-17 , IL-22 , IL-23 , IL-26 , TNF-α ) , regulatory T cells ( Treg ) ( Foxp3; IL-10 , TGF-β , IL-35 ) , Th9 cells ( PU . 1; IL-9 , IL-10 , IL-21 ) and Th22 cells ( aryl hydrocarbon receptor/AHR; IL-22 , TNF-α ) [26–32] . These cytokines and transcriptional factors are not exclusively expressed by the subsets of CD4+ T cells ( Th1 , Th2 , Th9 , Th17 , Th22 , regulatory T cell ) . However , T-Bet , GATA3 , PU . 1 , RORγt and FoxP3 are indispensable for Th1 , Th2 [33–35] , Th9 [28 , 36] , Th17 [26 , 37 , 38] and regulatory T cell [39–42] profiles , respectively . There is no evidence of a signature marker for Th22 profile , but several literature data have been shown that aryl hydrocarbon receptor ( AHR ) is critical for Th22 cells [29 , 43 , 44] . The roles of Th9 and Th22 cells during Chagas disease remain unclear . Moreover , the correlations among immunological mechanisms , stroke and death have not been investigated in depth in chronic Chagas disease patients . Here , we demonstrated that indeterminate patients exhibit increased expression of Th2- , Th9- , Th22- and Treg-related cytokines and transcription factors and reduced expression of the inflammatory cytokines IFN-γ and TNF-α . In addition , patients who exhibited a high long-term death and stroke risk also exhibited increased iNOS mRNA expression , which is positively correlated with the risks of death and stroke . Together , the data indicate that uncontrolled inflammation caused by T . cruzi influences the mechanisms that lead to stroke and death during the chronic phase of Chagas disease . This knowledge may contribute to the reduction of stroke risk and death during the chronic phase of Chagas disease and may also benefit the general population .
A total of 65 chagasic patients from the rural zone of Rio Grande do Norte , Brazil were selected using two different serological methods ( Chagatest" recombinant ELISA and HAI , and indirect immunofluorescence assay ) between 2011 and 2013 . The exclusion criteria included the following: over 70 years of age , diabetes , sustained ventricular tachycardia or ventricular fibrillation , an implanted cardiac pacemaker and non-chagasic cardiomyopathy . Individuals that tested positive for Chagas disease by two serological tests with distinct testing methods underwent a complete clinical evaluation , including electrocardiogram ( ECG ) mapping and chest X-ray , contrasted X-rays of the esophagus and colon , 2D-echocardiogram ( ECHO ) and 24-h Holter examination . They were classified according to the clinical form of the disease as: cardiac , digestive or indeterminate as recommended by Brazilian Consensus on Chagas Disease [45] . Clinical evaluations were performed as described previously [46] . Following these examinations , the patients were classified as having the indeterminate ( n = 18 ) , cardiac ( n = 17 ) , digestive ( n = 15 ) or cardiodigestive ( n = 15 ) clinical forms of the disease . Healthy , uninfected individuals ( n = 15 ) served as controls . Patient groups enrolled in this study did not exhibit a large number of cardiovascular risk factors . Concerning this topic , variables such as hypertension , obesity , dyslipidemia , sedentary behavior , and smoking were evaluated in study population ( Table 1 ) . The risks for stroke and death are multifactorial and depend on these factors . Thus , what determines whether patients are at higher risk for death or stroke is not exclusively an assignment of a particular cytokine , but refers to a set of factors . Multifactorial data analysis was not used in this cross-sectional study as this statistical approach is intended to modelling the massive amount of data collected from patients throughout longitudinal studies , being the resulting model usually adjusted or updated for other individuals in a process of external validation with new individuals to determine risk factors [47–49] . The present study is not aimed to propose or implement a predictive model for death and stroke risk in Chagas disease patients , but highlights the possible correlation between inflammation and these clinical manifestations . Written informed consent for this study was obtained from all adult participants and was approved by the Research Ethics Committee of the State University of Rio Grande do Norte ( UERN ) under protocol number 027 . 2011 and the Certificate of National System of Ethics in Research ( CAEE—SISNEP ) , protocol number 0021 . 0 . 428 . 000–11 . All of the experiments described here were performed according to the human experimental guidelines of the Brazilian Ministry of Health and the Declaration of Helsinki . The long-term risk of death over 10 years among patients with chronic Chagas disease is predicted by the presence of the six following characteristics: New York Heart Association/NYHA class III or IV ( 5 points ) , cardiomegaly on chest radiograph ( 5 points ) , abnormalities of the segmental or global left ventricular echocardiogram ( 3 points ) , nonsustained ventricular tachycardia on Holter monitoring ( 3 points ) , low-voltage QRS complex on the electrocardiogram ( 2 points ) and male sex ( 2 points ) . A risk score derived from the combination of points for each of these characteristics was used to classify the patients as having a low ( 0–6 points ) , medium ( 7–11 points ) or high ( 12–20 points ) death risk . The estimated long-term mortality over 10 years in the patients grouped in the low , medium and high death risk groups is 10% , 44% , and 84% , respectively [5] . The stroke risk was based on the presence of systolic dysfunction ( 2 points ) and left ventricular apical aneurysm ( 1 point ) , primary alteration of ventricular repolarization on the electrocardiogram ( 1 point ) and age greater than 48 years ( 1 point ) . The patients were grouped as having a low ( 0–2 points ) , medium ( 3 points ) , or high ( 4–5 points ) risk of stroke [50] . Cytokines ( IL-4 , IL-9 , L-10 , IL-17 , IL-22 , IFN-γ , TGF-β and TNF-α ) , transcription factors ( PU . 1 , GATA-3 , RORγt , AHR , T-Bet , FoxP3 ) and iNOS mRNA expression levels were determined by real-time PCR ( qPCR ) of peripheral blood mononuclear cells ( PBMCs ) isolated from Chagas disease patients . Samples from uninfected healthy individuals were used as controls . Total RNA from the PBMCs was isolated using TRIzol reagent ( Invitrogen , Carlsbad , CA , USA ) and the SV Total RNA Isolation System ( Promega , Madison , WI , USA ) , and cDNA was synthesized using the ImProm-II Reverse Transcriptase System ( Promega ) . The qPCR was performed using SYBR Green ( Invitrogen ) , and the standard PCR conditions were as follows: 50°C ( 2 min ) and 95°C ( 10 min ) followed by 40 cycles of 94°C ( 30 s ) , variable annealing primer temperature ( Table 2 ) ( 30 s ) , and 72°C ( 1 min ) . The expression mRNA levels of the target genes were determined using the mean Ct values from triplicate measurements to calculate the relative expression levels of the target genes in the chagasic patients compared to those in the healthy subjects and were normalized to the housekeeping gene β-actin using the 2–ΔΔCt formula . Data are reported as the mean ± standard deviation ( SD ) . Comparisons of mRNA expression levels between groups were performed using the Kruskal-Wallis test . In all cases , differences were considered significant when p < 0 . 05 . Spearman’s test was used to determine correlations among the mRNA expression levels of cytokines , transcription factors , iNOS , death risk score and stroke risk score . Our analyses were performed using the PRISM 5 . 0 ( GraphPad , San Diego , CA , USA ) statistical program .
Initially , we classified the 65 patients according to the clinical form of Chagas disease . The indeterminate , cardiac , digestive and cardiodigestive clinical forms were observed in 27 . 7% ( 18/65 ) , 26 . 1% ( 17/65 ) , 23 . 1% ( 15/65 ) , 23 . 1% ( 15/65 ) of patients , respectively ( Table 3 ) . Subsequently , the mRNA expression levels of transcription factors and cytokines mainly expressed in Th1 ( T-Bet/IFN-γ and TNF-α ) , Th2 ( GATA-3/IL-4 ) , Th9 ( PU . 1/IL-9 ) , Th17 ( RORγt/IL-17 ) , Th22 ( AHR/IL-22 ) and Treg ( Foxp3/IL-10 and TGF-β ) were determined in PBMCs by qPCR . Indeterminate patients exhibited higher levels of GATA-3 , Foxp3 , AHR , IL-4 , IL-9 , IL-10 , and IL-22 mRNA expression than did cardiac patients . However , cardiac patients exhibited higher levels of IFN-γ and TNF-α mRNA compared with indeterminate patients ( Fig 1A and 1B ) . Patients with chronic chagasic cardiomyopathy ( cardiac and cardiodigestive clinical forms ) were grouped according to their long-term risk of death over 10 years and were classified as having a low ( 10/32–31 . 25% ) , medium ( 12/32–37 . 50% ) , or high ( 10/32–31 . 25% ) death risk . The degree of death risk was compared with the production of cytokines and transcription factors . Patients with low death risk exhibited higher expression of FoxP3 , GATA-3 and IL-10 than did those with a high death risk ( Fig 2A and 2B ) . Subsequently , patients who exhibited the indeterminate , cardiac , digestive and cardiodigestive clinical forms of Chagas disease were grouped as having a low ( 40/65–61 . 54% ) , medium ( 18/65–27 . 69% ) or high ( 7/65–10 . 77% ) stroke risk . The expression levels of cytokines and transcription factors were compared among the patients from different groups . We observed that low stroke risk patients exhibited higher GATA-3 , Foxp3 , PU . 1 , AHR , IL-9 , IL-10 and IL-22 expression levels than did patients with high stroke risk ( Fig 3A and 3B ) . However , IFN-γ and TNF-α mRNA expression was increased in patients with high stroke risk compared with those with low risk ( Fig 3B ) . In an attempt to elucidate the inflammatory mechanism involved in stroke generation , we quantified the mRNA expression of iNOS . Nitric oxide may be involved in the inhibition of endothelial nitric oxide synthase ( eNOS ) , resulting in the vasoconstriction of cerebral arteries . Patients who exhibited different clinical forms of Chagas disease exhibited similar iNOS mRNA levels ( Fig 4A ) . However , those who exhibited high long-term death risk over 10 years and high stroke risk had higher iNOS mRNA expression than those patients with a low or medium risk of death and stroke ( Fig 4B and 4C ) . Subsequently , we analyzed the correlation between the mRNA expression of Foxp3 , IL-10 , TNF-α and iNOS with the death and stroke risks . A negative correlation was observed between Foxp3 and death risk ( r = -0 . 4983; p = 0 . 0051 ) ( Fig 5A ) and stroke risk ( r = -0 . 5359; p < 0 . 0001 ) ( Fig 5B ) . Moreover , a negative correlation between IL-10 mRNA expression and death risk ( r = -0 . 6299; p = 0 . 003 ) was also observed ( Fig 5C ) . No significant correlation between IL-10 mRNA expression and the stroke risk was observed ( r = -0 . 1401; p = 0 . 3422 ) ( Fig 5D ) . A positive correlation was observed between the TNF-α mRNA expression and death risk ( r = 0 . 5381; p = 0 . 0018 ) ( Fig 5E ) and stroke risk ( r = 0 . 5087; p < 0 . 0001 ) ( Fig 5F ) ; and a positive correlation was also observed between iNOS mRNA expression and death risk ( r = 0 . 4850; p = 0 . 0049 ) ( Fig 5G ) and stroke risk ( r = 0 . 5748; p < 0 . 0001 ) ( Fig 5H ) .
To gain a better understanding of the stroke pathobiology in Chagas disease patients , we investigated the correlation of immune mediators with the death and stroke risks in indeterminate , cardiac , digestive and cardiodigestive patients . We first analyzed the mRNA expression of cytokines ( IL-4 , IL-9 , L-10 , IL-17 , IL-22 , IFN-γ , TNF-α , TGF-β ) and transcription factors ( PU . 1 , GATA-3 , RORγt , AHR , T-Bet , FoxP3 ) in PBMCs obtained from Chagas disease patients who exhibited the indeterminate , cardiac , cardiodigestive and digestive clinical forms of the disease . Cardiac patients exhibited higher mRNA expression of IFN-γ , TNF-α and lower mRNA expression of IL-10 , Foxp3 , AHR , and GATA-3 than those with the indeterminate clinical form of Chagas disease . The immunological imbalance in cardiac patients includes reduced IL-10 production and increases of TNF-α and IFN-γ production [27 , 51–53] . Resistance to T . cruzi infection is largely dependent on the production of nitric oxide and its derived nitrogen and oxygen free radicals . The pro-inflammatory cytokines IL-12 , IFN-γ and TNF-α ( Th1 response-related ) activate macrophages to promote parasite killing through the production of trypanocidal radicals [54 , 55] . In addition , these cytokines also act as a positive feedback for Th1 differentiation . Th1 cells orchestrate an exaggerated CD8+ T cell response , causing tissue damage and fibrosis [25] . The regulation of T . cruzi-induced inflammation occurs primarily through the Th2 and Treg-related cytokines IL-4 , IL-10 , and TGF-β [27 , 31 , 56] . The regulation of inflammation was observed in indeterminate patients , who exhibited high GATA-3 and IL-10 mRNA expression . Biopsies obtained from heart tissue of patients with chronic chagasic cardiomyopathy have showed markedly up regulation of IFN-γ and T-Bet mRNA expression , and lower increases of GATA-3 , FoxP3 and CTLA-4 than healthy subjects . Moreover , expression of Th1-related genes such as T-Bet and IFN-γ was correlated with ventricular dilation as well [57] . We also described Th9- and Th22-related mediators and their correlation with clinical forms of Chagas disease . Cardiac patients exhibited lower levels of IL-9 , IL-22 and AHR mRNA expression when compared with indeterminate patients . IL-9 also can promote the development of Th17 cells and was reported to be produced by these cells [58] . We have previously demonstrated that indeterminate chagasic patients exhibit increased IL-17 production that can be correlated to the control of cardiac dysfunction [27] . The asymptomatic patients infected with Leishmania donovani another trypanosomatid parasite the etiological agent of Kala Azar ( KA ) produce enhanced amounts of IL-17 maybe contributing to host survival and control of parasite growth [59] . Thus , IL-9 and IL-22 may be involved in regulating the Th1 response and inflammatory cytokine expression in patients with the indeterminate form of the disease , and these cytokines may help prevent the development of chronic chagasic cardiomyopathy . Subsequently , cardiac patients were categorized in low , medium and high death risk groups [5] . Here , patients with low death risk exhibited increased expression of FoxP3 , GATA-3 and IL-10 compared with high death risk patients . Cardiac damage during T . cruzi infection is due to parasite multiplication and the immune response , both of which destroy cardiac muscle and the autonomous nervous system , causing electrocardiographic changes , cardiomegaly and death [6 , 60 , 61] . Patients with indeterminate Chagas disease produce higher levels of IL-10; IL-10 controls the inflammatory immune response generated by the parasitic infection and prevents damage to the myocardium [27] . During the chronic phase of Chagas disease patient mortality is mostly associated with cardiac involvement [3] . Chagasic cardiopathy starts with destruction of myocardial fibers by progressive inflammation with subsequent replacement by fibrotic tissue , an inflammatory and fibrogenic process that ends up in pathologic ventricular remodeling due to a gradual loss of the contractile elements . During remodeling ventricular dysfunction is initially compensatory but the dynamics of the inflammatory process leads to increased cardiac dilatation which evolves to a non-compensatory dilatation , with progressive loss of ventricular ejection capacity . Complex ventricular arrhythmias and failure of mitral- and tricuspid valves further contribute to the worsening of the cardiopathy and might be an additional risk factor within the pleiad of mortality-related mechanisms [61 , 62] . The fibrosing and progressive chronic myocarditis is also the key substrate for impairment of the conduction system in Chagas disease [62] . Macrophages , T lymphocytes ( CD4+ and CD8+ ) , cytokines and autoantibodies associated with the presence of the parasite and/or their antigens participate in myocardial lesion formation [27 , 46 , 63–65] . Inflammatory cytokines ( TNFα and IFNγ ) have been found in myocardial biopsies of chagasic patients [51] in association with parasitism and inflammation , a suggestive evidence for their possible relationship with neuronal depopulation [66] . Direct ganglionar parasitism is found associated with periganglionitis , and nervous fiber- and Schwann cell degenerative lesions . Direct parasitism is observed , as well as nervous fiber- and degenerative lesions [67] . Deposition of autoantibodies in structures of the neurotransmitter receptors ( β-adrenergic receptors , muscarinic receptors ) might cause desensitization resulting in progressive denervation , an event that may also be implicated in the occurrence of ventricular arrhythmias [66] . Antibodies from patients with chronic Chagas disease displaying complex arrhythmias decrease the heart rate and cause atrioventricular block in isolated rabbit hearts [68 , 69] , indicating that the immune response is an important pathophysiological factor in the development of complex arrhythmias and cardiac death in Chagas disease [70] . Despite limitations , experimental and clinical studies strongly support the notion that functional and structural microvascular abnormalities occur in Chagas cardiomyopathy , possibly as a consequence of the underlying inflammatory process [62] . Actually , as argued by Kania and co-workers [71] recent findings suggest that heart-infiltrating monocyte-like cells indeed contain a pool of progenitors , which represent the cellular source both for accumulation of differentiated monocytes during the acute inflammatory phase and for transforming growth factor-β-mediated myocardial fibrosis during the later chronic stages of disease . Obviously , a delicate balance of proinflammatory and profibrotic cytokines dictates the fate of bone marrow-derived heart-infiltrating progenitors and directly influences the morphologic phenotype of the affected heart . Given the magnitude of the question of sudden death in chronic Chagas disease patients and high cost of medical treatment , identifying the patient at risk and outlining the process that initiated or facilitated these arrhythmias is a high priority issue in such a way that those patients might be more effectively treated . Infectious and parasitic diseases contribute to stroke risk [72] . It has been previously shown that chagasic patients have an increased risk of stroke , independent of cardiac function ( LVEF ) [5 , 73] . In this study , we demonstrated that patients with low stroke risk have increased mRNA expression of GATA-3 , Foxp3 , PU . 1 , AHR , IL-9 , IL-22 and IL-10 . These mediators can regulate the inflammatory response ( TNF-α and IFN-γ ) associated with the mechanism of thrombus formation . Also , we observed that high stroke risk patients exhibited high mRNA expression of IFN-γ . Patients with Chagas disease produce inflammatory mediators that increase the chance of thromboembolic phenomena [74] . The cytokine IFN-γ induces TNF-α production and causes increased expression of ICAM-I ( intracellular adhesion molecule-I ) and VCAM-I ( intravascular adhesion molecule-I ) , both of which are involved in the cell adhesion process and surface formation of thrombi [20 , 75] . TNF-α also modulates endothelial cell coagulant properties , markedly increasing tissue factor-like procoagulant activity in cultured human endothelial cells [76]; TNF-α also stimulates increased cellular surface adhesivity in polymorphonuclear leukocytes , monocytes , lymphocytes and leukocyte cell lines [77 , 78] . The classic elements of the thrombus formation , such as endothelial damage , decreased blood flow and imbalance between coagulation factors , are increased in patients with Chagas disease . These elements are altered primarily by the inflammatory response generated against the parasite [61 , 74] . The inflammatory response to the parasite could affect the vasodilatation of the cerebral arteries , thus contributing to stroke formation . Nitric oxide produced by eNOS activates guanylate cyclase in vascular smooth muscle cells by increasing cGMP levels causing vasodilatation [79] . After T . cruzi infection there is macrophage activation with iNOS production and these cells invade endothelium and migrate to tissues . High nitric oxide production in the vascular endothelium of chagasic patients due to high iNOS activation could lead to eNOS inhibition , vasoconstriction and cerebral microvascular spasms , causing ischemic stroke [80] . In this study , patients who exhibited high long-term death risk over 10 years and patients with a high stroke risk exhibited higher iNOS mRNA expression than those patients with low risk of stroke and death . Moreover , a positive correlation was observed between iNOS expression and death and stroke risk . The nitric oxide produced by iNOS inhibits eNOS [80] . Our findings suggest that chagasic patients with high stroke and death risks exhibit reduced expression of cytokines related to Th2 , Th9 , Th22 and Treg profiles . The decreased production of these cytokines may be correlated to increased vascular inflammatory processes that subsequently lead to thrombi and atherosclerosis formation . Patients with high risks of stroke and death exhibited high iNOS mRNA expression , indicating that the patients likely had increased nitric oxide production in the vascular endothelium . The high levels of nitric oxide likely could led to eNOS inhibition and vasoconstriction , thus contributing to the stroke pathophysiology . Moreover , key cytokines of the Th2 , Th9 , Th22 and Treg profiles are correlated with the indeterminate clinical form of Chagas disease . The present study unveiled the existence of an immunopathological outcome underlying chagasic patients condition that involves an imbalanced expression of IL-10 , FoxP3 and iNOS , which increases the risk of stroke or death . An improved understanding of the immunological mechanisms involved in ischemic strokes in Chagas disease patients may also contribute to the reduction of stroke-related mortality and morbidity in the general population and may lead to the development of prophylactic or therapeutic therapies . | Chagas disease is caused by Trypanosoma cruzi ( T . cruzi ) , affects 5 . 7 million people worldwide and causes 12 , 000 deaths annually . In the chronic phase of Chagas disease the main cause of death is due to heart failure ( about 80% ) , but cerebral vascular accident or stroke ( about 10% ) contributes to death mechanisms . Strokes are caused by the interruption of the blood supply to the brain and can be ischemic or hemorrhagic . Stroke is the leading cause of death among adults in Latin America and the second in the world . Infectious diseases , such as Chagas disease , malaria , cysticercosis , tuberculosis , brucellosis and neurosyphilis , can also contribute to the development of immunopathogenic mechanisms leading to stroke and death . In this study , we evaluated the association between inflammatory markers ( cytokines , transcription factors of the adaptive immune response and iNOS ) and the death risk ( DR ) and stroke risk ( SR ) of patients with different clinical forms of chronic Chagas disease . Our data suggest that an inflammatory imbalance in chronic Chagas disease patients is correlated with a high DR and SR . The exacerbated inflammatory mechanism that leads to thrombus formation can lead to sudden death in patients with clinical indeterminate form without prior other clinical symptoms . These inflammatory mechanisms are also involved in atherosclerotic-related strokes . An improved understanding of the immunological mechanisms involved in ischemic stroke formation in Chagas disease patients may also contribute to the reduction of stroke-related mortality and morbidity in the general population and may lead to the development of prophylactic or therapeutic therapies . | [
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"... | 2016 | Inflammation Enhances the Risks of Stroke and Death in Chronic Chagas Disease Patients |
Chikungunya virus ( CHIKV ) is a re-emerging mosquito-borne virus which causes epidemics of fever , severe joint pain and rash . Between 2005 and 2010 , the East/Central/South African ( ECSA ) genotype was responsible for global explosive outbreaks across India , the Indian Ocean and Southeast Asia . From late 2013 , Asian genotype CHIKV has caused outbreaks in the Americas . The characteristics of cross-antibody efficacy and epitopes are poorly understood . We characterized human immune sera collected during two independent outbreaks in Malaysia of the Asian genotype in 2006 and the ECSA genotype in 2008–2010 . Neutralizing capacity was analyzed against representative clinical isolates as well as viruses rescued from infectious clones of ECSA and Asian CHIKV . Using whole virus antigen and recombinant E1 and E2 envelope glycoproteins , we further investigated antibody binding sites , epitopes , and antibody titers . Both ECSA and Asian sera demonstrated stronger neutralizing capacity against the ECSA genotype , which corresponded to strong epitope-antibody interaction . ECSA serum targeted conformational epitope sites in the E1-E2 glycoprotein , and E1-E211K , E2-I2T , E2-H5N , E2-G118S and E2-S194G are key amino acids that enhance cross-neutralizing efficacy . As for Asian serum , the antibodies targeting E2 glycoprotein correlated with neutralizing efficacy , and I2T , H5N , G118S and S194G altered and improved the neutralization profile . Rabbit polyclonal antibody against the N-terminal linear neutralizing epitope from the ECSA sequence has reduced binding capacity and neutralization efficacy against Asian CHIKV . These findings imply that the choice of vaccine strain may impact cross-protection against different genotypes . Immune serum from humans infected with CHIKV of either ECSA or Asian genotypes showed differences in binding and neutralization characteristics . These findings have implications for the continued outbreaks of co-circulating CHIKV genotypes and effective design of vaccines and diagnostic serological assays .
Chikungunya virus ( CHIKV ) is a re-emerging , mosquito-borne arbovirus which has caused unprecedented worldwide epidemics in recent years [1] . There are three major CHIKV genotypes circulating: West African , East/ Central/ South African ( ECSA ) and Asian [2] . After the global outbreaks of ECSA between 2005 and 2010 , the Asian genotype has re-emerged to cause large outbreaks in the Americas and the Pacific islands [3 , 4] . Malaysia has experienced CHIKV outbreaks due to two different genotypes , Asian and ECSA . The endemic Asian CHIKV strain was responsible for small , geographically-restricted outbreaks in 1998 and 2006 [5–7] . An imported ECSA outbreak was reported in 2006 prior to an explosive nationwide outbreak which affected over 15 , 000 people across different states in 2008 [8 , 9] . CHIKV is an alphavirus from the family Togaviridae . A CHIKV virion is 60-70nm in diameter , with a single-stranded positive RNA genome of approximately 11 . 8 kb in a capsid with a phospholipid envelope carrying glycoproteins E1 and E2 . Its genome has 2 open reading frames encoding the non-structural ( nsP1-nsP2-nsP3-nsP4 ) and structural polyproteins ( C-E3-E2-6K-E1 ) [10] . The E1 and E2 glycoproteins form heterodimers which enable interaction with cellular receptors and fusion of the virion envelope with the cell membrane to initiate infection [11] , while the capsid protein is required during virus assembly [12] . These proteins are highly immunogenic , and most CHIKV-infected patients develop antibodies targeting the structural proteins ( particularly E2 ) and , to a lesser extent , nsP3 [13 , 14] . After the initial induction of type I interferon [15] , CHIKV-specific antibodies have been shown as the major effector in immunity to control infection [16] . Among other immune factors , T cells may play a secondary role in suppressing infection [17] , although others have found that CD4+ T cells are more important in orchestrating joint inflammation [18] . Currently , treatment for CHIKV is supportive and no licensed vaccine or antiviral are available . Phase I clinical trials have demonstrated the safety and efficacy of vaccination with virus-like particles using structural proteins derived from the West African genotype [19] , and a recombinant measles virus-based CHIKV vaccine derived from the ECSA genotype [20] . Cross-reactivity can be achieved against heterogenous genotypes , by which CHIKV seropositive individuals infected with either ECSA or Asian CHIKV have cross-protection against both CHIKV genotypes [9] . However , the cross-neutralizing efficacy of CHIKV-specific antibodies against Asian and ECSA genotypes , which are both currently circulating in Malaysia , Brazil [21] and the Asian region [22] , is poorly understood . A distinct antigenic relationship has been established between West African and ECSA genotypes , in which mice and hamsters immunized with the ECSA genotype had 4- to 8-fold differences in neutralizing capacity when tested against a West African strain [2] . In a Singaporean cohort , CHIKV-immune sera exhibited differential antibody binding and neutralizing capacity against isolates with a naturally occurring K252Q amino acid change in the E2 glycoprotein [14] . Given the ability of CHIKV to rapidly spread across different parts of the world with displacement of one genotype with another , the understanding of cross-neutralizing antibody and antigenic variation of different genotypes will have implications for both continued outbreaks and vaccine development . In this study , we analyzed the neutralizing capacity of CHIKV ECSA and Asian immune sera against representative clinical isolates and rescued viruses of ECSA and Asian CHIKV . We demonstrated that both sets of serum panels have stronger neutralizing capacity against the ECSA isolate , which corresponded to strong epitope-antibody interaction . E1-E211K enhances the neutralization activity of ECSA serum , while E2-I2T , H5N , G118S and S194G within linear epitopes improve the neutralization activity of both sets of sera panels . Rabbit polyclonal antibody targeting a known linear neutralizing epitope ( LP1 ) from ECSA virus could only neutralize homotypic virus , but not heterotypic Asian virus due to sequence variation . These findings indicate the antigenic variation of ECSA or Asian CHIKV genotypes in naturally-acquired infection alters the spectrum of cross-genotype protective antibody immunity .
This study included 63 human samples from two independent outbreaks in Malaysia . The Asian serum panel comprised 40 samples collected from patients 11–14 months after an Asian CHIKV outbreak in Bagan Panchor in 2006 [7] . The ECSA serum panel consisted of 23 samples from patients infected by ECSA strains in 2008–2010 , collected 1–6 months after onset of symptoms , who were seen at the University Malaya Medical Centre in Kuala Lumpur [9] . Healthy controls ( n = 15 ) with no past infection of CHIKV served as negative controls . Serum neutralization assay was performed on all the sera . To determine the neutralizing activity due to IgG , heat-inactivated sera were treated for 1 hour with dithiothreitol ( DTT ) ( Life Technologies ) at a final concentration of 5mM at 37°C . This study was approved by the Medical Ethics Committee of the University Malaya Medical Centre ( reference no . 800 . 70 ) . Our institution does not require informed consent for retrospective studies of archived and anonymized samples . Baby hamster kidney ( BHK-21 ) cells ( ATCC no . CCL-10 ) were maintained in Glasgow minimum essential medium ( GMEM ) ( Life Technologies ) supplemented with 5% heat-inactivated fetal bovine serum ( Flowlab ) , 10% tryptose phosphate broth , 20mM HEPES , 5mM L-glutamine , 100 U/ml penicillin and 100μg/ml streptomycin . Infected cells were maintained in GMEM containing 2% FBS . The clinical isolates used , which have been previously characterized [23] , were MY/06/37348 , an Asian genotype strain isolated from a patient in Bagan Panchor in 2006 ( accession number FN295483 ) , and MY/08/065 , an ECSA virus isolated from a patient in Kuala Lumpur in 2008 ( accession number FN295485 ) . Both isolates had been passaged two times in Vero cells ( ATCC no . CCL-81 ) before propagated in BHK-21 cells . Virus passage ( P3 ) of clinical isolates was used for subsequent work . To study the neutralizing epitopes , viruses rescued from two different infectious clones , derived from ECSA and Asian genotypes of CHIKV , were included . The plasmid vectors capable of producing infectious viruses were constructed under the control of the human cytomegalovirus immediate-early promoter . The CHIKV infectious clone derived from the ECSA genotype was based on LR2006-OPY1 , isolated in Reunion Island in 2006 , and has been described previously [24] . The full-length infectious cDNA ( icDNA ) clone from the Asian genotype was engineered by gene synthesis and assembled by the restriction enzymes approach based on the consensus sequence for strain 3462 , isolated in Yap State in 2013 ( accession no . KJ451623 ) ; however , the protein coding regions in the non-structural and structural proteins were changed to be identical to isolate CNR20235 from the Caribbean outbreak , which was isolated in Saint Martin Island in 2013 ( http://www . european-virus-archive . com/article147 . html ) . Both molecular clones have ZsGreen gene incorporated as reporter and duplication of the subgenomic promoter . The ECSA molecular clone was named “ICRES1” , while the Asian molecular clone was designated as “CAR” . For construction of the chimeric viruses , the ectodomain regions of envelope glycoprotein genes E1 ( amino acids 1–381 ) and E2 ( amino acids 1–341 ) in the ICRES1 backbone were replaced with those of Semliki Forest virus ( SFV ) E1 ( amino acids 1–381 ) and E2 ( amino acids 1–340 ) from icDNA SFV6 [25] using NEBuilder HiFi DNA Assembly Master Mix ( NEB ) . In order to study the effects of point mutations on the neutralizing epitopes , conventional PCR-based site-directed mutagenesis was performed on the CAR construct using Q5 High-Fidelity DNA polymerase ( NEB ) with designed primers ( S1 Table ) . The sequences of all the constructs were verified by control restrictions and sequence analysis . Primers and sequences for infectious clone constructions are available upon request . The viruses were rescued from icDNA by electroporation . Stocks of rescued viruses ( P0 ) were harvested and titrated by plaque assay on BHK-21 cells . To obtain P1 stocks , confluent BHK-21 cells grown in T75-cm2 flasks were infected with P0 stocks at a multiplicity of infection ( MOI ) of 1 plaque forming unit/cell and maintained in 2% FBS GMEM . P1 stocks were harvested after 24 or 48 hours , titrated and used for the neutralization assay . Infectious center assay was performed on all the viruses rescued from icDNA . Details on virus rescue and related protocols are shown in S1 Text and S2 Table . Seroneutralization was performed with a previously described immunofluorescence-based cell infection assay in BHK-21 cells [26 , 27] , with minor modifications . The DTT-treated sera underwent 2-fold serial dilutions ( 1:100 to 1:6400 ) in 1X Dulbecco’s PBS prior to mixing with CHIKV pre-diluted with 2% FBS GMEM . Cells were infected with clinical isolates at an MOI of 10 . The virus-antibody mixture was incubated for 2 hours at 37°C before inoculation into 104 cells in 96-well CellCarrier-96 optic black plates ( Perkin Elmer ) , and further incubated for 1 . 5 hours at 37°C . The inocula were decanted and 2% FBS GMEM was added to the plates . The plates were fixed with 4% paraformaldehyde after 6 hours of incubation at 37°C , permeabilized with 0 . 25% Triton X-100 for 10 minutes , and immunostained using anti-CHIKV E2 monoclonal antibody B-D2 ( C4 ) [28] at 1μg/ml followed by rabbit anti-mouse IgG-FITC ( Thermo Scientific ) at 1:100 dilution . Cell nuclei were counter-stained with DAPI . Fluorescence intensity was analyzed with a Cellomics High Content Screening ( HCS ) ArrayScan VTI ( Thermo Fisher ) over 9 different fields at 5X magnification . Percentage of infectivity was calculated according to the following equation: % infectivity = ( mean average fluorescence intensity from serum sample/mean average fluorescence intensity from virus control ) × 100 . The neutralizing titer ( NT50 ) was expressed as the serum dilution that reduced infectivity by 50% using non-linear regression fitting in GraphPad Prism 5 ( GraphPad Software ) . For seroneutralization using rescued viruses , diluted sera were mixed with viruses pre-diluted with 2% FBS GMEM ( with infection performed at an MOI of 50 ) , followed by the steps described above . The plates were fixed after 7 hours of incubation at 37°C . The plates were only counter-stained with DAPI prior to acquisition of ZsGreen fluorescence . To investigate the cross-reactivity of CHIKV sera against another alphavirus , SFV was rescued from icDNA SFV6 as previously described [25] . Diluted sera ( 1:25 and 1:100 dilutions ) were mixed with SFV pre-diluted with 2% FBS GMEM ( with infection performed at an MOI of 10 ) , followed by the steps described above . The plates were fixed after 6 hours of incubation at 37°C , and stained with mouse anti-alphavirus monoclonal antibody ( Santa Cruz ) at 1:100 dilution . To investigate the effect of sequence variation of neutralizing epitopes in ECSA and Asian genotypes , polyclonal rabbit anti-LP1 ( STKDNFNVYKATRPY ) , anti-LP1A ( SIKDHFNVYKATRPY ) and anti-LP47 ( NHKKWQYNSPLVPRN ) were produced commercially ( GenScript ) . LP1 is similar to E2EP3 , an immunogenic peptide ( from an ECSA virus ) previously reported to elicit neutralizing antibodies [26] . LP1A is the corresponding variant peptide with Asian genotype sequences . The LP47 peptide sequence is conserved in both genotypes . Seroneutralization was performed with purified antibody at 25μg/ml against the rescued viruses . For indirect IgG ELISA ( antibody end-point assay ) and Western blot , the antigen was partially purified virus prepared by sucrose-cushion ultra-centrifugation , treated with 1% Triton X-100 in TE buffer , clarified by centrifugation , and stored in 50% glycerol at -20°C . For production of native recombinant proteins of E1 ( rE1 , from amino acids 1–412 ) and E2 ( rE2 , from amino acids 1–362 ) , viral RNA was extracted from clinical isolates ( Asian MY/06/37348 and ECSA MY/08/065 ) . cDNA was synthesized using reverse-transcription , and the genes were amplified using high fidelity Platinum Taq ( Invitrogen ) with designed primers ( S3 Table ) . The transmembrane regions and cytoplasmic tails of the glycoproteins were not included in the expression cassette , to ensure solubility of the recombinant proteins . The amplicons were ligated into a pIEX-5 vector ( Novagen ) directionally at BamH1 and Not1 restriction sites . Each plasmid construct together with a pIE1-neo vector were co-transfected into Sf9 cells ( Novagen ) using Cellfectin II reagent ( Invitrogen ) [29] . Stable clones expressing rE1 and rE2 were generated under selection with G418 sulfate at 1000μg/ml . The proteins secreted from stable clones were purified under native conditions with activated Profinity IMAC resins ( Bio-Rad ) or HisTrap FF ( GE ) . The eluates were concentrated with an Amicon centrifugal unit and the buffer was exchanged with sodium phosphate buffer ( 50mM NaH2PO4 , 300mM NaCl , pH 8 . 0 ) . The proteins were stored at -20°C in 50% glycerol , except for the proteins used in the competitive protein blocking assay , which were filter-sterilized and kept at 4°C . Fusion sequences expressing for rE2 and rE1 was generated by overlapping PCR; recombinant proteins encoded by obtained sequence were linked via linker with sequence GGGS-His ( 8X ) -GGGG ( S1 Text ) . The fusion glycoprotein constructs were transfected into TriExSf9 cells ( Novagen ) by TransIT-Insect transfection reagent ( Mirus Bio ) . The proteins were resolved with 12% SDS-PAGE under reducing and non-reducing conditions and electro-transferred onto a nitrocellulose membrane ( GE ) . The membrane was blocked with 10% skimmed milk in 0 . 05% PBS-Tween 20 ( PBST ) . The immunoreactivity of recombinant proteins was evaluated with pools of CHIKV immune sera applied at indicated dilutions in the blocking buffer . The bound antigen-antibody complex was detected by anti-human IgG-HRP ( DakoCytomation ) at 1:5000 dilution in 1% bovine serum albumin ( BSA ) -0 . 05% PBST . The membrane was visualized by chemiluminescence ( Bio-Rad ) and images were acquired with a BioSpectrum AC imaging system ( UVP ) . Mouse anti-His tag antibody ( Merck Millipore ) was included as a loading control . Mouse anti-E2 monoclonal antibody ( clone: B-D2 ( C4 ) ; EIEVHMPPDT ) [28] was also included as a control . All incubation steps were performed at 37°C for 1 hour , using 1% BSA-0 . 05% PBST as diluent for serum and antibodies . The plates were washed 4 times with 0 . 05% PBST after each incubation step . To determine the relative level of anti-E2 antibodies , the plates were coated with 250 ng of virus antigen or 100 ng of rE2 in 0 . 05M carbonate-bicarbonate buffer ( pH 9 . 6 ) . The antigens were normalized with monoclonal antibody B-D2 ( C4 ) to determine the relative level of anti-E2 antibodies . The plate was blocked with 3% BSA in 0 . 05% PBST . The sera were tested at 2-fold serial dilutions from 1:512 to 1:1 , 048 , 000 or 1:640 to 1:655 , 000 . The IgG end-point titer was determined as the reciprocal of the highest dilution that produced an optical density ( OD ) reading of three times greater than that of the negative control . Anti-human IgG-HRP at 1:5000 dilution was added to detect the bound antibodies . TMB substrate ( KPL ) was added to each well and the plates were incubated at room temperature for 5 min . The reaction was terminated by adding 1M phosphoric acid . The absorbance was measured at 450nm with 630nm as the reference wavelength using an automated ELISA reader ( Biotek Instruments ) . The cut-off value was established as the OD obtained from healthy controls sera plus three standard deviations ( SD ) . The relative level of anti-rE2 antibodies was calculated with the following formula: ( end point titer for rE2/end point titer for whole virus antigen ) × 100 . Soluble recombinant CHIKV proteins ( 15μg ) were mixed with heat-inactivated immune sera diluted at 1:200 , and incubated for 1 hour at 37°C . CHIKV ( MY/08/065 ) in amounts corresponding to an MOI of 10 was mixed with the samples , which were incubated for a further 2 hours at 37°C . Synthetic peptides were obtained from GenScript ( LP1 , STKDNFNVYKATRPY; LP24 , TDSRKISHSCTHPFH; LP38 , GNVKITVNGQTVRYK ) ; 60μg of each peptide was mixed with immune sera diluted with 1X DPBS at 1:100 and incubated for 1 . 5 hours at 37°C . All the synthetic peptides for the blocking assay have a purity grade greater than 95% and are soluble in high-grade water . ICRES1 ( sucrose-cushion purified virus in TE buffer pre-diluted using 2% FBS GMEM ) at an amount corresponding to an MOI of 1 was mixed with the samples , which were incubated for a further 2 hours at 37°C prior to infection of BHK-21 cells . The plate was replenished with plaque medium ( 2% FBS GMEM containing 0 . 8% of carboxymethylcellulose ) , fixed with 4% paraformaldehyde after 15 hours of incubation , and this was followed by ZsGreen fluorescence acquisition . Infectivity corresponded to the fluorescence intensity acquired with a Cellomics HCS reader . The effect on infectivity of antibodies in the presence and absence of blocking peptides was compared . Biotinylated synthetic peptides covering the E2 glycoprotein sequence from amino acids 1–362 from a previous study [28] were used to screen CHIKV immune sera for binding to linear epitopes . The length of each peptide is 15-mer with a 10-mer overlap based on the CHIKV MY/08/065 sequence ( accession no . FN295485; S4 Table ) . Similar steps were performed as described above except that the plates were washed 6 times after incubation with human sera and secondary antibody . The plates were coated with 20μg/ml streptavidin ( NEB ) and blocked with 5% BSA-PBST . The dissolved peptides in dimethyl sulphoxide were further diluted to a working concentration of approximately 150μg/ml in 1% BSA-PBST . CHIKV immune sera and healthy control sera were diluted at 1:1000 , and screened against peptides in duplicate . The peptides with the highest OD reading from 2 adjacent overlapping synthetic peptides were considered as identified B-cell epitopes . Computational analysis and epitope localization were performed on structural data retrieved from Protein Data Bank ( PDB , ID 3J2W ) with UCSF CHIMERA software [30] . As the LP1 sequence is unresolved in structural data , the structure of the E2 glycoprotein was predicted using the online I-TASSER server [31 , 32] . The electrostatic potential of the E2 structure ( amino acid 1–362 ) was evaluated with PDB2PQR and APBS [33–35] . Data are presented as means ± SD or means ± standard error of the mean ( SEM ) . Differences between groups and controls were analyzed using appropriate statistical tests . A P-value of <0 . 05 was considered significant . Statistical analyses were performed with GraphPad Prism 5 .
We employed a sensitive seroneutralization assay to compare the neutralizing capacity of the different sera panels against MY/08/065 ( ECSA ) and MY/06/37348 ( Asian ) ( S1 and S2 Figs ) . The heat-inactivated intact sera and DTT-treated sera had similar neutralizing capacity against MY/08/065 for both sera panels ( S3 Fig ) . ECSA sera demonstrated strong neutralizing capacity against homotypic CHIKV compared to heterotypic CHIKV ( Fig 1A ) , with a NT50 against MY/08/065 that was a median 2 . 67 ( range , 1 . 40–4 . 61 ) times greater than the NT50 against MY/06/37348 ( Fig 1B ) . Unexpectedly , Asian sera demonstrated better neutralizing capacity against heterotypic ECSA CHIKV compared to homotypic CHIKV ( Fig 1A ) , with a NT50 against MY/08/065 of a median 1 . 44 ( range , 0 . 70–3 . 19 ) times greater than the NT50 against MY/06/37348 ( Fig 1B ) . The greater neutralizing capacity corresponded to stronger antibody binding to MY/08/065 compared to MY/06/37348 by quantitative ELISA ( Fig 1C ) . Seroneutralization was performed against rescued virus from icDNA of ECSA and Asian genotypes . Both ECSA and Asian sera demonstrated better neutralizing capacity against ICRES1 ( ECSA ) compared to CAR ( Asian ) ( Fig 1D ) . Immunoblotting showed stronger reactivity of serum with the whole viral antigen ( with a band of about 50kDa , consistent with E1 or E2 , a known immunodominant antigen in alphaviruses ) and recombinant E2 glycoprotein of similar size derived from ECSA , compared to the Asian genotype . Under non-reducing conditions , ECSA sera had stronger antibody binding to its homotypic CHIKV isolate MY/08/065 , ICRES1 and recombinant E2 glycoprotein ( rE2 ) ( Fig 1E and 1F ) . Asian sera bound similarly to both genotypes of viruses ( clinical isolates and rescued viruses ) , and more strongly to rE2 glycoprotein of MY/08/065 ( Fig 1E and 1F ) . Under reducing conditions , both sets of sera retained stronger binding to ECSA CHIKV and rE2 of ECSA CHIKV . Both sets of sera had a similar proportion of total antibodies binding to rE2 ( median 50% , range 20–63% for ECSA serum; median 50% , range 16–63% for Asian serum ) ( Fig 1G ) , and these percentages suggest that antibodies also target sites other than E2 . Taken together , CHIKV serum shows strong neutralizing capacity and binding to CHIKV , particularly of the ECSA genotype , and the epitopes may be presented as part of the conformational E1-E2 glycoprotein and/or as linear determinants in the E2 glycoprotein . To determine if CHIKV immune serum targets E1 , recombinant E1 glycoprotein ( rE1 ) was probed in ELISA with serially diluted pooled sera , and signal was detected at low serum dilutions from 1: 100 to 1:800 ( Fig 2A ) . A competitive protein blocking assay was performed , and blocking of ECSA and Asian sera with native rE1 alone did not significantly alter the neutralizing capacity ( Fig 2B ) . However , when the sera was blocked by a mixture of rE1 and rE2 , significant increases of infectivity were observed in both panels of sera compared to unblocked sera or sera blocked by either rE1 or rE2 alone . We then hypothesized that antibodies may target conformational epitopes on E1 and E2 glycoproteins together . To test this hypothesis , we constructed 2 chimeras which swapped the ecto-domain regions of the E2 and E1-E2 glycoproteins with those of Semliki Forest virus ( SFV ) . Both sets of sera demonstrated a low degree of cross-neutralization against SFV , another alphavirus which is a member of the same antigenic complex as CHIKV ( S4 Fig ) . At 1:100 serum dilution , loss of neutralizing effect for both sets of sera was observed when CHIKV E2 was replaced with SFV E2 . Furthermore , in ECSA serum , loss of neutralization activity was much higher against the chimera with E1-E2 from SFV compared to the chimera with SFV E2 alone ( Fig 2C ) . This provides further evidence that neutralizing antibodies are not solely targeting E2 , but are also targeting epitopes spanning E1-E2 glycoproteins . Alternatively , E1 may affect the conformation of E2 and alter its epitopes . To further determine the importance of conformational epitopes resulting from interactions between E1 and E2 , four sets of fusion E1-E2 glycoproteins were constructed . Each hybrid fusion protein contained E1 and E2 sequences from either MY/06/37348 ( ECSA ) or MY/08/065 ( Asian ) , transiently expressed as secreted native recombinant proteins in insect cells ( Fig 3A ) . The antibody binding capacity of ECSA sera against fusion E1-E2 proteins significantly increased when either the E1 or E2 sequence was changed from that of MY/06/37348 to that of MY/08/065 , as shown in immunoblotting ( Fig 3B ) and quantitative ELISA ( Fig 3C ) . Asian sera had almost equal antibody binding capacity for the 4 fusion glycoproteins , suggesting that Asian serum was not sensitive to sequence changes in E1-E2 glycoproteins . This data shows that the greater binding and neutralization of the ECSA isolate MY/08/065 by ECSA sera ( Fig 1A , 1C and 1D ) is due to critical conformational epitopes on the E1-E2 heterodimer , which are sequence-dependent . Between ECSA ( MY/08/065 and ICRES1 ) and Asian ( MY/06/37348 and CAR ) genotypes of CHIKV in this study , there are 10 amino acids differences in E1 ( Fig 3D ) . Using the fusion rE2-E1-Asian construct as a template , site-directed mutagenesis was performed independently to replace each amino acid of Asian origin with the corresponding ECSA residue , and the proteins were expressed in insect cells . The antibody binding significantly increased with the amino acid changes at A145T , E211K , A226V and M269V , in comparison to hybrid rE2Asian-E1ECSA recombinant proteins ( Fig 3E ) . Recombinant virus carrying E1-211K demonstrated a large increase in neutralizing capacity compared to the parental virus clone ( CAR ) , while the E1-145T change caused a slight decrease in neutralizing capacity ( Fig 3F and 3G ) . The critical 211K amino acid was localized at the surface of E1-E2 heterodimers ( Fig 3H ) . To study the linear epitopes in the immunodominant E2 glycoprotein ( based on strain MY/08/065 , of the ECSA genotype ) , overlapping synthetic peptides covering amino acids 1–362 were mapped by peptide-ELISA using the ECSA and Asian sera ( Fig 4A , 4B and 4C ) . Both ECSA and Asian sera mapped to the same 9 peptides , and the Asian sera mapped to an additional 3 peptides ( Table 1 ) . Between the strains of ECSA ( MY/08/065 , ICRES1 ) and Asian ( MY/06/37348 , CAR ) genotypes of CHIKV used in this study , there are 15 amino acid differences in E2 ( from amino acids 1–362 ) , of which 4 amino acid differences fall within the identified linear epitopes ( Fig 4D ) . Using the rE2-Asian construct as a backbone , site-directed mutagenesis was performed to replace each amino acid of Asian origin with an ECSA residue , and the proteins were expressed in insect cells . The antibody binding significantly increased with I2T , H5N , G118S , R149K and S194G substitutions in comparison to the original rE2-Asian recombinant protein ( Fig 4E and S5 Fig ) . Recombinant viruses carrying either E2-2T , 5N , 118S or 194G demonstrated increases in neutralizing capacity compared to the parental virus clone ( CAR ) , while the E2-R149K change caused a decrease in neutralizing capacity ( Fig 4F ) . Competitive peptide blocking assay indicated that the anti-CHIKV antibodies interact with the LP1 , LP24 and LP38 peptides that cover amino acid sites 2 , 5 , 118 and 194 on E2 ( Fig 4G ) . These 4 neutralizing linear epitopes are localized on the surface of the E1-E2 heterodimer complex ( Fig 4H ) . As naturally-acquired infection of the Asian genotype of CHIKV leads to higher cross-neutralizing efficacy against ECSA CHIKV , we hypothesized that an epitope-based vaccine derived from the Asian genotype might provide a substantial level of cross-protection against ECSA CHIKV . The peptide LP1 ( STKDNFNVYKATRPY ) is similar to E2EP3 , a peptide derived from ECSA virus which has been found to be highly immunogenic in eliciting neutralizing antibodies in an animal model [26] . We generated a variant , LP1A ( SIKDHFNVYKATRPY ) , derived from the sequence of the Asian virus . Rabbit polyclonal antibodies were commercially prepared against LP1A and LP1 . Peptide-ELISA was performed using human ECSA and Asian serum with LP1A and LP1 as antigens . Human ECSA serum bound to LP1 but not LP1A ( Fig 5A ) . Rabbit anti-LP1 antibody showed the lowest binding capacity against CAR ( Asian ) , and demonstrated poor neutralizing activity against the CAR virus harboring the LP1A sequence ( infectivity 91±10% , Fig 5B ) . Anti-LP1 binding capacity and neutralization efficacy was partially restored with the mutations I2T and H5N . The anti-LP1 antibody had maximum binding capacity and neutralizing efficacy against CAR-E2-I2T-H5N ( Fig 5B ) , which has the LP1 sequence; a finding in line with the antibody binding of ECSA immune sera against LP1 peptide ( Fig 5A ) . Asian serum could recognize LP1A , although binding was marginally higher to LP1 ( Fig 5C ) , which supports the earlier finding that Asian serum has stronger binding against LP1 with I2T and H5N amino acid changes ( Fig 4E ) . Unexpectedly , rabbit anti-LP1A did not demonstrate significant neutralizing activity against CHIKV with either the LP1A or LP1 sequences ( Fig 5D ) . However , a competitive peptide blocking assay indicated that neutralizing antibodies from Asian sera could still recognize and interact with both LP1A and LP1 peptides ( Fig 5E ) . The electrostatic potential of the E2 surface was computed based on the CAR ecto-domain region to study the charge distribution of these epitopes which affect binding affinity [36] . The I2T change leads to higher electrostatic potential , which is associated with improved binding capacity and neutralization efficacy ( Fig 5F ) . LP47 , another linear neutralizing epitope in humans , also failed to induce any functional neutralizing antibodies in rabbits .
CHIKV has become a major public health concern worldwide and causes considerable socio-economic burden . Protective adaptive immunity is mainly provided by specific antibodies , particularly those directed against epitopes on the E2 and E1 glycoproteins [37 , 38] . Understanding cross-immunity resulting from infections with different genotypes is particularly important and timely . Many Asian countries now have both endemic Asian and epidemic ECSA strains circulating , and the recent widespread outbreaks in the Americas are due to the Asian genotype rather than the previously epidemic ECSA strains , indicating that viruses from both genotypes are capable of global spread . In this study , we showed differences in cross-genotypic neutralization efficacy of immune sera against ECSA and Asian genotypes of CHIKV . Both ECSA and Asian serum had greater neutralizing capacity against ECSA genotype ( MY/08/065 and ICRES1 ) than Asian genotype ( MY/06/37348 and CAR ) , indicating that neutralizing antibodies regardless of initial infecting genotype preferentially recognized the epitopes presented by the ECSA genotype . The presence of cross-genotype neutralization was clearly shown lasting up to 14 months post-infection . The clinical significance of the differential cross-protective capacity of ECSA and Asian sera remains unclear , as all the immune sera had more than the minimum neutralizing titer ( ≥10 ) which appears to correlate with immune protection from symptomatic CHIKV infection in humans [39] . This high degree of cross-neutralization likely contributed to the geographic restriction of CHIKV of different genotypes seen historically , which limited , for example , the spread of ECSA viruses in Asia , at least until CHIKV underwent mutations that facilitated sequential adaptation to the Aedes albopictus vector [40 , 41] . Apart from the stronger antigenicity of epitopes of the ECSA genotype , we also showed that neutralizing capacity was also affected by the target and the amount of neutralizing antibodies . Both ECSA and Asian sera contain high levels of neutralizing antibodies to numerous linear epitopes on the E2 glycoprotein as well as conformational epitopes on the E1-E2 heterodimer complex . This supports recent findings that most of the reported CHIKV neutralizing monoclonal antibodies target conformational epitopes on the exposed , topmost outer surfaces of the E2/E1 spike , particularly in domain A and domain B [42–45] . Our findings also suggest that subunit vaccine candidates derived from E1 or E2 glycoproteins alone [46–48] may be insufficient to provide full protection against all genotypes , and that virus-like particle vaccines which present epitopes on E2/E1 in their native configuration may preferentially induce the most highly protective immune response [19 , 49 , 50] . The loss of neutralization activity against chimeric CHIKV is in line with the finding that total IgG and anti-rE2 antibody titers correlate with the neutralizing titer of Asian serum ( S6 Fig ) , suggesting that most of the neutralizing epitopes are on the E2 glycoprotein . The lack of correlation between anti-rE2 antibodies and neutralizing antibodies seen in ECSA serum could be due to the greater importance of conformational epitopes at E1-E2 sites , but we cannot exclude that it may reflect differences in potency/quality of the circulating antibodies due to the different timings of collection between the Asian and ECSA serum panels ( S6 Fig ) . Correlation between serum neutralization titers and antibody binding titers has been reported in other viral infections such as dengue and influenza [51 , 52] , and is important for developing serological assays which are accurate correlates of protective immunity following infection or vaccination . Therefore , E2 , while appropriate for serological assays to diagnose acute or past infection [53] , may not be a suitable candidate for assays to measure protective immunity due to all CHIKV genotypes . Such assays are necessary for vaccine development . Amino acid changes in key epitope regions , such as naturally occurring mutations or antigenic variation between different genotypes could affect surface charge distribution and electrostatic interactions between epitopes and antibodies , affect binding affinity and ultimately alter neutralizing capacity [14] . The E211K mutation in domain II of the E1 glycoprotein is a significant change of a negatively-charged to positively-charged amino acid , and this appears to enhance antibody binding and neutralization efficacy . During the recent Indian outbreak of ECSA CHIKV , the key amino acid change E1-K211E was shown to be under positive selection pressure [54] , which may confer a selective advantage for virus dissemination and escape from the action of neutralization in humans . In addition , E211 is highly conserved in strains of the Asian genotype . Peptide-specific rabbit polyclonal antibody prepared against a short linear epitope ( GDIQSRTPESKDVY , position 201–214 ) including 211K did not show neutralization activity ( S7 Fig ) , suggesting that the neutralizing activity of immune sera targeting this amino acid is highly conformation-dependent . As for the E2 glycoprotein , I2T , H5N , G118S and S194G changes increased antibody binding and neutralization efficacy . All these amino acid changes are positioned within linear epitopes , which interacted with neutralizing antibodies . This was supported by a previous report of well-characterized human neutralizing monoclonal antibodies targeting epitopes that cluster around the LP24 and LP38 peptide regions in our study [43] . Notably , the linear epitope LP1 in our study is similar to E2EP3 , a well-characterized key neutralizing linear epitope which has been suggested as a serology marker [26 , 55] , and LP1 demonstrated cross-reactivity with ECSA and Asian serum in our study . However , we found no effect of K252Q in antibody binding capacity in our cohort , although this was reported recently [14] , and this could be due to differential immune responses in different populations . Other linear epitopes ( LP19 , LP47 , LP56 and LP70 ) were identified in this study which had higher binding than LP1 , and as all demonstrated binding to both ECSA and Asian sera , they may be potential candidates for diagnostic serological assays . Furthermore , antibodies against LP19 and LP47 demonstrated neutralizing characteristics which warrant further investigation as vaccine candidates ( S8 Fig ) . It was interesting that the Asian serum had greater neutralizing capacity against the heterologous ECSA isolates . The previously reported human CHIKV monoclonal antibodies 5F10 and 8B10 had a broad neutralization activity against isolates of the ECSA and West African genotypes , but were also less potent against an Asian isolate from Indonesia [56] . Monkeys inoculated with a virus-like particle vaccine derived from the West African strain 37997 also developed better neutralizing activity to a heterologous ECSA strain LR2006 OPY-1 than to 37997 , possibly due to better presentation of conserved epitopes by LR2006 OPY-1 [49] . ECSA and Asian CHIKV genotypes could have induced different immune mediator profiles; as shown in mice , infection with a Caribbean ( Asian ) strain was associated with a weaker pro-inflammatory Th1 and natural killer cell response and higher IgG1:IgG2c ratio compared to an ECSA CHIKV strain , resulting in less severe joint pathology [57 , 58] . Different CHIKV viruses may also trigger differential regulation of key innate immune responses such as TLR3 [59] , which plays an important role in shaping subsequent neutralizing capacity [60] . Further studies are needed to understand how differentially-induced immune mediators modulate the properties of circulating serum antibodies . Two amino acids in LP1 ( 2T , 5N ) of the ECSA virus are critical for binding and neutralization activity , and this further highlights the fact that sequence variation could impact vaccine development . The rabbit polyclonal antibody targeting the linear neutralizing epitope LP1 from the ECSA virus showed reduced cross-neutralization against the Asian genotype , and unexpectedly , rabbit anti-LP1A poorly neutralized the homotypic CAR Asian virus , despite immunization of 4 rabbits . The linear neutralizing epitope LP1A from the Asian virus was not recognized by the ECSA sera . However , clearly there are preexisting antibodies against LP1 and LP1A in the Asian sera . LP47 , another linear neutralizing epitope in humans ( S8 Fig ) , which has a sequence that is conserved in both genotypes , did not induce any functional neutralizing antibodies in rabbits despite a similar immunization approach . Future studies will be required to address these apparent underlying differences of neutralizing antibody production from either natural infection or immunization . Nevertheless , our findings indicate that the choice of virus strain for vaccines could impact the spectrum and efficacy of protection across genotypes . For antibody therapy of CHIKV , monoclonal antibodies should retain high potency against a broad diversity of CHIKV isolates [43] . In conclusion , immune serum from humans infected with CHIKV of either ECSA or Asian genotypes showed differences in neutralization and binding capacities . Our findings are relevant to current outbreaks with co-circulating genotypes and provide insights into antibody-mediated immunity resulting from infections with CHIKV of different genotypes . | Chikungunya virus ( CHIKV ) has caused large epidemics of fever , rash , and joint pain around the world in recent years . Three different CHIKV genotypes exist . Infection with one genotype is likely to lead to immune protection ( or cross-protection ) against future infections with a different genotype . However , little is known about the nature of this cross-protection . In this study , we used serum from Malaysian patients infected with CHIKV of either Asian or East/Central/South African ( ECSA ) genotypes . We compared the ability of the serum antibodies to bind to and neutralize two different viruses , from either Asian or ECSA genotypes . We found that both Asian and ECSA serum were more effective in binding and neutralizing ECSA virus . We identified the key amino acids/epitopes within the E1-E2 surface glycoprotein , and showed that variation of these impacts the efficacy of antiserum in cross-neutralizing different genotypes of CHIKV . We showed how sequence variation of a known linear neutralizing epitope could alter the cross-neutralization efficacy . This study aids understanding of the importance of different circulating genotypes within a country and has implications for the design of vaccines and diagnostic antibody tests . | [
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"diseases"... | 2016 | Antigenic Variation of East/Central/South African and Asian Chikungunya Virus Genotypes in Neutralization by Immune Sera |
Mycobacterium tuberculosis ( Mtb ) relies on a specialized set of metabolic pathways to support growth in macrophages . By conducting an extensive , unbiased chemical screen to identify small molecules that inhibit Mtb metabolism within macrophages , we identified a significant number of novel compounds that limit Mtb growth in macrophages and in medium containing cholesterol as the principle carbon source . Based on this observation , we developed a chemical-rescue strategy to identify compounds that target metabolic enzymes involved in cholesterol metabolism . This approach identified two compounds that inhibit the HsaAB enzyme complex , which is required for complete degradation of the cholesterol A/B rings . The strategy also identified an inhibitor of PrpC , the 2-methylcitrate synthase , which is required for assimilation of cholesterol-derived propionyl-CoA into the TCA cycle . These chemical probes represent new classes of inhibitors with novel modes of action , and target metabolic pathways required to support growth of Mtb in its host cell . The screen also revealed a structurally-diverse set of compounds that target additional stage ( s ) of cholesterol utilization . Mutants resistant to this class of compounds are defective in the bacterial adenylate cyclase Rv1625/Cya . These data implicate cyclic-AMP ( cAMP ) in regulating cholesterol utilization in Mtb , and are consistent with published reports indicating that propionate metabolism is regulated by cAMP levels . Intriguingly , reversal of the cholesterol-dependent growth inhibition caused by this subset of compounds could be achieved by supplementing the media with acetate , but not with glucose , indicating that Mtb is subject to a unique form of metabolic constraint induced by the presence of cholesterol .
There is an urgent need to identify new drugs to treat Mycobacterium tuberculosis ( Mtb ) . The World Health Organization estimates that 1 . 8 billion people are infected with Mycobacterium tuberculosis ( Mtb ) and approximately 1 . 3 million people die from tuberculosis ( TB ) annually . The global prevalence of TB is sustained by the ongoing HIV-AIDS pandemic , poverty , and the emergence of antibiotic resistant isolates of Mtb [1] . Unfortunately , with the notable exception of bedaquiline [2] , there have been no new drugs approved for treatment of tuberculosis , and some of the emergent drug resistant strains are virtually untreatable . Therefore identification of compounds that inhibit new biological targets and pathways is a vital component in TB drug discovery . Intracellular survival within macrophages is an important aspect of Mtb pathogenesis . In macrophages Mtb resides and replicates primarily in phagosomes , which are thought to be a nutritionally-constrained environment [3 , 4] . In order to replicate in this environment Mtb relies on particular metabolic pathways to utilize host-derived nutrients [5] . Numerous transcriptional profiling studies have indicated that the metabolism of host-derived carbon sources such as fatty acids and/or cholesterol are critical for Mtb survival in macrophages [6–10] . Additionally , genetic studies have identified key bottlenecks in Mtb carbon metabolism , which are essential for growth during infection . Specifically , mutants lacking genes involved in gluconeogenesis [11–13] , cholesterol utilization [14–17] , or the methyl citrate cycle ( MCC ) [18 , 19] fail to establish infection in macrophages . The importance of these pathways is underscored by the observation that many of these pathways are also required for full Mtb pathogenicity in small animal models of infection . For this reason , the central carbon metabolic pathways of Mtb are considered potential targets for TB drug discovery . Identifying small molecules that inhibit predetermined enzymatic targets in Mtb with target-based screens continues to be a challenge . Frequently inhibitors identified through target-based screens fail to show activity when tested against intact , live Mtb . Such failures are usually the consequence of poor permeability , drug efflux , and/or metabolic redundancy [20] . In contrast , cell-based screens typically identify compounds on the basis of their activity against live Mtb but this approach is constrained both by appropriateness of the growth condition ( s ) used in the screen , and the subsequent need to determine the mode of action of inhibitors . To circumvent at least some of these challenges , phenotypic screening against Mtb-infected macrophages represents a viable alternative strategy . In this report we conducted an unbiased chemical screen to identify compounds that inhibit Mtb replication during infection in macrophages , and subsequently in cholesterol media . To isolate compounds that specifically target cholesterol metabolism in Mtb we developed a novel chemical-rescue approach that exploits the toxicity of cholesterol-derived intermediates to identify pathway specific inhibitors in whole Mtb . With this approach we identified inhibitors of the HsaAB complex , which is required for complete degradation of the A/B rings of cholesterol , and PrpC , the gating enzyme of the MCC , which is required for effective assimilation of propionyl-CoA into central metabolism . Finally , we describe three structurally-diverse compounds that limit cholesterol utilization indirectly by perturbing cyclic-AMP ( cAMP ) levels . The sheer breadth of inhibitory compounds that reduce Mtb fitness in macrophages through the disruption of cholesterol metabolism was unexpected but provides us with a rich set of new tools to probe the metabolic re-alignment required to sustain growth within the host macrophage .
To discover compounds that limit Mtb growth within macrophages , we developed a whole-cell assay suitable for phenotypic high-throughput screening ( HTS ) . In a 384-well format , J774 macrophages were infected with an Mtb strain that constitutively expresses the fluorescent protein mCherry . In this assay , Mtb replicates and produces a 4- to 5-fold increase in mCherry signal over a six-day period . In the presence of the frontline anti-TB drug rifampicin , the Mtb mCherry signal is quenched in a concentration-dependent manner indicating that mCherry fluorescence can serve as a marker of reduced intracellular Mtb growth ( S1 Fig . ) . To identify compounds that inhibit Mtb growth in macrophages , the J774 cells were infected and screened with an experimental compound library at a single concentration of 10 μM . We quantified the Mtb derived-mCherry signal at day 6 and hit compounds were identified by their ability to reduce Mtb-derived mCherry fluorescence . For the screen we used a proprietary compound library supplied by Vertex Pharmaceuticals which contained ~340 , 000 synthetic small molecules and natural products . From this screen we identified ~4000 compounds that displayed Mtb growth inhibition in the range of 30–100% relative to the positive control rifampin ( 5 μM ) which we used as the reference for 100% inhibition . The cutoff of 30% inhibition is a low stringency filter and was chosen because this threshold is approximately 3 standard deviations from the mean signals from the experimental compounds in our screen ( S1 Fig . ) . The calculated Z’-factors for all of the ~1 , 200 screening assay plates was 0 . 65–0 . 75 , indicating that the assay is very robust [21] . We next determined the potency of the hit compounds by testing a compound dilution series against Mtb using the intracellular mCherry fluorescence assay . This assay reconfirmed activity for >90% of the hit compounds and resulted in 1 , 359 validated hits with IC50 values <50 . 0 μM in the macrophage assay . Middlebrook 7H9 OADC media has historically been used to evaluate anti-Mtb compounds . Therefore , we titrated our most potent 1 , 359 hits against Mtb cultivated in standard 7H9 OADC and quantified growth inhibition using an Alamar Blue-based assay [22] . This revealed two distinct sub-sets of compounds; those that were universally-active , inhibiting Mtb growth in 7H9 OADC and inside macrophages , and those that were conditionally-active , that inhibit intracellular Mtb growth but have little or no inhibitory activity in 7H9 OADC . Of the 1 , 359 hits tested in this assay , 141 ( 10% ) were universally-active compounds with IC50 values <5 . 0 μM in 7H9 OADC media and in the macrophage assay ( Fig . 1 ) . The screening library that we used contained known anti-Mtb compounds and greater than 70% of the universally active compounds were structurally related to compounds with reported anti-Mtb activity . The most potent conditionally-active subset contained 132 ( 9% ) compounds that inhibit Mtb replication in macrophages displaying IC50 values <5 . 0 μM . These conditionally-active compounds demonstrate little inhibitory activity against Mtb in 7H9 OADC media ( IC50 values >50 . 0 μM ) . Importantly >95% the compounds in the conditionally-active category were novel with no structurally related compounds reported in the literature . Numerous compounds displayed differential potency in these two different assays which may be a result from multiple factors including: ( i ) variable compound access to Mtb , ( ii ) , induction of bacterial drug efflux systems during infection , ( iii ) partial inactivation of the compound by host-cell metabolism , or ( iv ) the compounds target pathways ( host or bacterial ) required only during infection . Middlebrook 7H9 OADC media is a carbohydrate-rich medium that does not reflect the nutritional conditions encountered by Mtb in macrophages , or any aspect of the bacterium’s life cycle . We hypothesized that a subset of the conditionally active compounds target Mtb metabolism and inhibition by these compounds would be buffered by the nutritional redundancy provided within 7H9 OADC medium . Numerous studies have indicated that host-derived lipid ( cholesterol and fatty acid ) substrates and the metabolic pathways required for their utilization are important for Mtb replication during infection [11 , 16 , 23 , 24] . Therefore , we tested the 132 most potent conditionally-active compounds ( IC50 values < 5 . 0 μM in macrophages ) against Mtb grown in 7H12 media containing cholesterol as the main carbon source [25] . We observed that 74 ( 56% ) of these conditionally-active compounds inhibited Mtb replication in this medium with IC50 values <5 . 0 μM . These IC50 values are comparable to those observed in the macrophage assay . Additionally , 33 of these 74 compounds were also active in 7H12 media containing acetate as the carbon source with IC50 values < 5 . 0 μM . Of the 132 conditionally-active compounds , we were unable to recover inhibitory activity for 58 conditional hits despite testing various liquid culture conditions . Possible explanations for this include: ( i ) our inability to faithfully reproduce the environment of the macrophage in liquid media; ( ii ) the compounds target the host-cell; ( iii ) the compounds are pro-drugs that require activation by an unknown enzyme ( host or bacterial ) ; or ( iv ) the compounds limit bacterial growth by inducing macrophage cell death . Nonetheless , we isolated numerous potent compounds that inhibit Mtb growth in cholesterol media and we hypothesize that a subset of these compounds target Mtb metabolic pathways involved in cholesterol utilization . In Mtb , the enzyme isocitrate lyase ( Icl1 ) is bifunctional , acting both as an isocitrate lyase in the glyoxylate pathway and as a methyl-isocitrate lyase of the methylcitrate cycle ( MCC ) [26] . Mtb utilizes the MCC to assimilate propionyl-CoA into central metabolism to produce succinate and pyruvate [19 , 27] . When an Icl1 deficient strain ( Δicl1 Mtb ) is growth in 7H9 OADC supplemented with cholesterol or propionate this mutant experiences a metabolic toxicity and fails to grow despite the presence of saturating amounts of carbohydrates and fatty acids in the medium . We hypothesize that this toxicity is induced by intermediates of the MCC that accumulate in Δicl1 Mtb when the bacteria are supplied either cholesterol or propionate . We further hypothesized that chemical inactivation of key cholesterol catabolic enzymes and/or MCC enzymes will alleviate this toxicity and rescue growth inhibition in the Δicl1 Mtb mutant grown in 7H9 OADC supplemented with cholesterol . To identify compounds that suppress cholesterol toxicity in Δicl1 Mtb we evaluated our most potent 1 , 359 hit compounds for their ability to rescue cholesterol-dependent toxicity in Δicl1 Mtb . Briefly , a Δicl1 Mtb strain , which constitutively expresses mCherry , was inoculated into Middlebrook 7H9 OADC media containing 100 μM cholesterol and compounds at 10 μM . Bacterial growth was measured by quantifying the bacterial-derived mCherry fluorescence at day 12 . From this single-point analysis we identified three compounds ( V-13–009920 , V-13–012725 , and V-13–011503 ) that restored Δicl1 Mtb growth in the presence of cholesterol suggesting that these compounds target key enzymes of the MCC or the cholesterol breakdown pathway ( S2 Fig . ) . To discriminate between compounds that potentially target the MCC enzymes from those that target cholesterol catabolism , we also evaluated these compounds for their ability to rescue growth in the presence of propionate . While all three compounds restored growth of the Δicl1 Mtb in 7H9 OADC supplemented with cholesterol , only one compound , V-13–009920 , restored bacterial growth on propionate ( S4 Fig . ) . We next quantified the relative growth rates of Δicl1 Mtb in 7H9 OADC supplemented with cholesterol or propionate in the presence of these compounds . This confirmed that V-13–012725 , and V-13–011503 rescue growth of Δicl1 Mtb only in the presence of cholesterol while V-13–009920 rescues growth of Δicl1 Mtb in the presence of cholesterol and propionate ( Fig . 2 ) . Additionally , the growth rescue of Δicl1 Mtb by V-13–009920 in 7H9 OADC is equivalent to rerouting propionyl-CoA into the methyl-malonyl pathway upon the addition of vitamin B12 [28] Based on these phenotypes , we hypothesized that V-13–009920 targets enzymes of the MCC while V-13–011503 and V-13–012725 target cholesterol catabolic enzymes upstream of the MCC . Since V-13–009920 rescues Δicl1 Mtb growth in propionate , the target of this compound is most likely an enzyme in the MCC . PrpC is the 2-methylcitrate synthase that catalyzes the first dedicated reaction of the MCC in Mtb and condenses oxaloacetate with propionyl-CoA to form 2-methylcitrate [19] . We therefore tested V-13–009920 against recombinant PrpC and confirmed that V-13–009920 directly inhibits pure PrpC enzyme activity in vitro with an IC50 of 4 . 0 ± 1 . 1 μM ( Fig . 3 ) . The compound V-13–009920 has an IC50 value of 3 . 0 μM in macrophages and is 10-fold more potent in 7H12 cholesterol media with an IC50 value of 0 . 3 μM . Microbiological profiling experiments demonstrate that this compound is bacteriostatic against Mtb grown in 7H12 cholesterol media . Previous reports have established that a prpCD double mutant has a growth defect in macrophages [19] . Thus , our discovery of a PrpC inhibitor from a collection of small molecules that limit intracellular Mtb replication reassured us that we have identified compounds that target the Mtb metabolic pathways required for infection . The ability of the PrpC inhibitor to promote growth of Δicl1 Mtb in 7H9 OADC media containing cholesterol is consistent with our interpretation that a toxic MCC intermediate ( s ) is produced in Δicl1 Mtb under this condition . Eoh and Rhee recently reported that the growth defect observed in Δicl1 Mtb during growth solely on propionate is derived from a defective MCC and is principally due to a depletion of tricarboxylic acid ( TCA ) intermediates and the secondary accumulation of potentially toxic intermediates . Additionally , this study reported that vitamin-B12 rescues the Δicl1 Mtb growth defect by shunting carbons from propionyl-CoA back into the TCA cycle via the vitamin-B12 dependent methyl-malonyl pathway [28] . Under the conditions used here it is unlikely that TCA intermediate levels are limiting in 7H9 OADC cholesterol , which contains excess amounts of glucose , fatty acids , and glycerol . Additionally , unlike the vitamin-B12 rescue of Δicl1 Mtb , chemical inactivation of PrpC would not reroute carbons into the TCA cycle . Thus , we propose that growth suppression of Δicl1 Mtb under this condition is induced by accumulation of a toxic intermediate ( s ) produced from the MCC . To determine if the compounds V-13–011503 and V-13–012725 directly inhibit cholesterol catabolism , we monitored the evolution of 14CO2 from [4–14C]-cholesterol by radiorespirometry . For this , wild-type Mtb was grown in 7H9 OADC supplemented with 100 μM cholesterol and trace levels of [4–14C]-cholesterol . In this assay the bacteria are provided excess carbohydrates and fatty acids to support bacterial growth allowing us to specifically quantify inhibition of cholesterol catabolism and bacterial viability in this assay was confirmed ( Fig . 4A ) . Under this condition we observed that both V-13–012725 and V-13–011503 significantly decreased the levels of 14CO2 released in the presence of these compounds ( Fig . 4B ) . To delineate the targets of these inhibitors we next analyzed the cholesterol-derived metabolites which accumulate in Mtb following treatment with V-13–012725 and V-13–011503 . GC-MS analyses of culture extracts from cells treated with V-13–012725 and V-13–011503 revealed one diagnostic metabolite ( tR = 14 . 9 min ) that was undetectable in DMSO-treated cells ( S3 Fig . ) . The retention time and mass spectrum of this metabolite corresponded to 3-hydroxy-9 , 10-seconandrost-1 , 3 , 5 ( 10 ) -triene-9 , 17-dione ( 3-HSA ) [29] . Treatment with V-13–012725 also promoted the accumulation of two additional metabolites and the retention times and mass spectrum of these metabolites correspond to those of 3-hydroxy-9-oxo-9 , 10-seco-23 , 24-bisnorchola-1 , 3 , 5 ( 10 ) -trien-22-oic acid ( 3-HSBNC ) [30] and a derivative of 3-HSBNC with a double bond . Most importantly , accumulation of 3-HSA following treatment with V-13–011503 and V-13–012725 indicates that these compounds target enzymes involved in degrading the A/B rings of cholesterol in Mtb ( S3 Fig . ) . To identify the molecular targets of V-13–011503 and V-13–012725 we tested these two compounds for their ability to inhibit key enzymes involved in the degradation of the A/B rings of cholesterol ( HsaA , HsaB , HsaC , or HsaD ) . At concentrations up to 100 μM , neither V-13–011503 nor V-13–012725 detectably inhibited HsaC or HsaD in in vitro enzymatic assays described previously [31 , 32] . However , both compounds inhibited HsaAB , the two-component flavin-dependent hydroxylase that catalyzes the 4-hydroxylation of ring A to produce a catechol . HsaAB inhibition was measured using a coupled enzymatic reaction containing recombinant HsaAB , HsaC , and 3-HSA which allowed us to track 4 , 9-DHSA production by measuring absorbance at 392 nm as described in the methods . Dose-response assays with these compounds revealed that the IC50 values for the inhibitors V-13–011503 and V-13–012725 are 11 ± 2 μM and 5 . 0 ± 0 . 8 μM , respectively against pure enzymes ( Fig . 4C-D ) . Killing kinetic analysis revealed that these two compounds are bacteriostatic against Mtb in media containing cholesterol as a sole carbon source . Our metabolite analysis confirmed that the side chain of cholesterol is fully degraded to 3-HSA upon treatment with the HsaAB inhibitors therefore , it is likely that Mtb can support minimal growth on cholesterol as a sole carbon source in vitro by utilizing the carbons liberated from the side chain of cholesterol in the presence of these inhibitors . A large proportion of hit compounds were active against Mtb when the bacterium is grown in cholesterol medium but do not seem to target cholesterol catabolism directly . To further characterize this diverse collection of compounds we performed global gene expression profiling to identify conserved patterns of differentially expressed genes to provide indication of mode of action [33 , 34] . Using this approach , we focused on three structurally-diverse compounds from the 132 conditionally-active inhibitors that are among the most potent in macrophages and cholesterol media ( S4 Fig . ) . Briefly , Mtb was cultivated in 7H12 cholesterol media and exposed to compounds at 10x IC50 concentration for 4 hr and the global Mtb transcriptional responses were quantified by microarray . We focused on those genes which were significantly up- or down-regulated across 3 biological replicates [8] . These inhibitors induced a common set of 49 genes including genes associated with the putative drug efflux systems Rv1216–19c and Rv0677–78c ( S1 Table ) . Rv1216–19c encodes a putative ABC-type transporter ( Rv1218c ) , which has been implicated in the efflux of a wide-variety of small molecule substrates from Mtb [35] . Similarly , we noted up-regulation of the genes Rv0676–78c , which encode the putative MmpL5 efflux pump that has been implicated in azole drug , clofazimine , and bedaquiline resistance [36 , 37] . Importantly , these structurally-unrelated compounds shared a common transcriptional profile consistent with a perturbation in cholesterol utilization . The key feature of this transcriptional signature is the repression of the MCC genes despite the presence of cholesterol in the medium ( Fig . 5 ) . This is informative since the MCC is involved in assimilating cholesterol-derived propionyl-CoA and the expression of the MCC genes are normally highly induced in the presence of increasing concentrations of propionate and/or cholesterol [27 , 38] . Additionally , 21 common genes that are under control of the transcriptional regulators KstR1 and KstR2 are also repressed and these genes are also normally induced during infection or in the presence of cholesterol or cholesterol breakdown products ( Fig . 5 and S1 Table ) [39 , 40] . The concomitant repression of the MCC genes and genes within KstR1 and KstR2 regulons suggest that cholesterol utilization is blocked in the presence of these inhibitors . Growth arrest was also evident in the transcriptional response to these compounds as indicated by the reduced expression of ribosome-encoding genes ( S1 Table ) . The overlapping gene lists from these transcriptional responses is an unexpected result given the structural diversity of these compounds and we hypothesize that these compounds target aspect ( s ) early in cholesterol utilization . Although lipids appear to be favored nutrients by Mtb during infection , the bacterium likely encounters complex mixtures of nutrients in vivo . We next examined the inhibitory activities of these orphan cholesterol utilization inhibitors in the presence of multiple carbon sources . This analysis revealed that in mixed carbon source media , containing both cholesterol and a glycolytic substrate ( glucose ) , these compounds inhibit Mtb replication with potencies similar to the intracellular macrophage assay . However , in mixed carbon source media containing cholesterol and a gluconeogenic substrate ( acetate ) , these compounds do not inhibit Mtb replication ( Fig . 6A ) . Previous metabolomics analysis has shown that Mtb can co-metabolize simple carbon substrates such as glucose , glycerol and acetate , although the products of these substrates have separate fates [41] . Our observation suggests that these compounds inhibit Mtb growth by limiting cholesterol turnover and acetate likely rescues this defect by fueling the TCA cycle for energy production . To test this idea we quantified cholesterol utilization by Mtb in the same mixed carbon source media by monitoring the release of 14C-labeled CO2 from [4–14C]-cholesterol by radiorespirometry . Consistent with our inhibition observations these compounds inhibited cholesterol utilization equally in mixed carbon source media containing either a glycolytic or gluconeogenic substrate ( Fig . 6B ) . Importantly , because acetate rescues growth inhibition the reduction in the amount of 14CO2 release by these compounds is not linked to a reduction in bacterial growth when the media is supplemented with acetate . Analysis of the killing kinetics with this set of inhibitors indicates that these compounds are bacteriostatic against Mtb in both macrophages and in cholesterol media . In comparison to the HsaAB inhibitors , the orphan cholesterol inhibitors ( V-12–003679 , V-12–007958 , and V-12–007960 ) only partly inhibit cholesterol metabolism leading to a 30–50% reduction in cholesterol turnover . In addition , these inhibitors do not rescue growth of Δicl1 Mtb in 7H9 OADC supplemented with cholesterol and we could not detect accumulation of any cholesterol-derived intermediate in the presence of these compounds . These observations lead us to hypothesize that these inhibitors could indirectly inhibit cholesterol utilization in Mtb by perturbing a regulatory system that modulates cholesterol or propionyl-CoA utilization . To identify mutants resistant to growth inhibition by these compounds we grew a transposon library ( ~105 ) wild type CDC1551 background , in 7H12 cholesterol media containing V-12–007958 ( 10 μM ) for seven days and plated the mutant pool onto 7H10 agar plates without compound and cholesterol . We picked 10 mutants and , upon sequencing , we identified 5 insertions that mapped to the adenylate cyclase rv1625c/cya ( three independent insertion sites ) . The integral membrane adenylate cyclase Cya is known to generate cyclic adenosine 3′ , 5′-monophosphate from ATP [42 , 43] . We therefore hypothesized that cAMP levels are perturbed by the orphan inhibitors , which negatively regulates cholesterol utilization . We first confirmed that two of the Tn::cya mutants were resistant to the compound V-12–007958 ( Fig . 7A ) . We next quantified cAMP production by wild type Mtb following an 8-hour exposure to V-12–003679 , V-12–007958 , and V-12–007960 in 7H12 cholesterol media containing acetate . We observed that all three orphan compounds in this class significantly induced the production of cAMP ( Fig . 7B ) . Lastly we confirmed that cholesterol utilization was no longer inhibited by V-12–007958 in the Tn::cya mutant in 7H12 cholesterol media containing acetate ( Fig . 7C ) . Importantly , because acetate rescues growth inhibition by these compounds the reduction in the amount of 14CO2 and the production of cAMP in the presence of these compounds is not linked to a reduction in bacterial growth in 7H12 cholesterol media containing acetate . Although the precise molecular target for V-12–003679 , V-12–007958 , and V-12–007960 is unknown , this data suggests a role for high levels of cAMP in negatively regulating cholesterol utilization in Mtb .
One hurdle in TB drug discovery stems from a limited understanding of the growth conditions and physiological environments experienced by Mtb during infection . Historically , the conditions used to identify anti-Mtb compounds are artificial and are unlikely to resemble those conditions encountered by Mtb during infection [44] . It is known that Mtb experiences a variety of environmental stressors during the course of infection such as starvation , hypoxia and low pH [45] . We decided to directly incorporate the host macrophage into a drug screen to reproduce the most common niche exploited by Mtb in its host and to recapitulate at least some of the metabolic and physiological adaptations required for infection . We hypothesized that chemical interrogation of Mtb within the context of its host cell would reveal additional targets that would not be required in rich medium that can provide diverse metabolic escape routes that are absent within the macrophage environment . Our screening against Mtb in macrophages identified both conventional , universally-active compounds that functioned independently of the bacterial environment , and conditionally-active compounds that were active in macrophages or in medium with cholesterol as the limiting carbon source . We were surprised to find that many of conditionally-active compounds required cholesterol for inhibitory activity in liquid culture and yet many of these compounds do not appear to target cholesterol utilization directly . Our interpretation is that cholesterol exerts a dominant influence on Mtb physiology in more ways than just being a substrate for energy production , perhaps by influencing carbon flux through central metabolic and biosynthetic pathways . More particularly , the unique mixture of central metabolites produced from cholesterol catabolism , such as acetyl-CoA , pyruvate , and propionyl-CoA , dictate that the bacteria make drastic metabolic rearrangements , which opens additional vulnerability to chemical intervention [27] . The inhibitors V-13–011503 and V-13–012725 are the first two known inhibitors of cholesterol catabolism in Mtb and they inhibit HsaAB , which is required for the NADH-dependent conversion of 3-HSA into 3 , 4-DHSA during degradation of the A/B rings of cholesterol . The HsaAB proteins function as an enzyme complex , it is currently unknown which protein is actually inhibited by these compounds . Our observation that chemical inhibition of HsaAB limits Mtb replication in macrophages is novel and is consistent with the prediction that these genes are required for growth in macrophages from previous transposon studies [17] . To our knowledge , survival studies with HsaAB mutants have not been reported in macrophages or in vivo . In addition to limiting Mtb replication in macrophages , compounds that target HsaAB may also inhibit extracellular Mtb replication in tissues where Mtb may potentially rely on an abundant pool of cholesterol within caseating granulomas [46] . Thus , efforts are currently underway to optimize the compounds , determine the precise molecular mechanism of HsaAB inhibition by these compounds , and to establish whether HsaAB inhibitors alone or in combination with frontline TB drugs enhance treatment outcomes in murine chemotherapy models in vivo . Regulation of cholesterol utilization by cAMP has not been reported and this regulation may be governed at the transcriptional level or post-transcriptionally . It is known that cAMP levels can control Mtb metabolism by protein acetylation through the activity of the cAMP-dependent protein acetyltransferase Rv0998/PAT [47–49] . Importantly , several mycobacterial enzymes involved in lipid and propionate metabolism are acetylated by PAT [50 , 51] in a cAMP dependent manner , which may limit cholesterol utilization directly or act through feedback inhibition [51] . We did not identify transposon insertions in Rv0998/PAT but we cannot rule out protein acetylation as a mechanism involved here . The enzymes involved in cholesterol utilization in Mtb may be negatively regulated at the transcriptional level in the presence of high concentrations of cAMP . At present , the exact molecular target ( s ) for the orphan cholesterol utilization inhibitors remain to be determined . Our current model is that this family of compounds indirectly inhibit cholesterol utilization in Mtb by perturbing an unknown target or pathway that leads to the enhanced production of cAMP , which down regulates cholesterol utilization . More work is needed to define the precise role of cAMP in regulating cholesterol utilization . The ability of acetate to rescue growth inhibition by these compounds without impacting cholesterol utilization implies that these compounds ultimately starve Mtb by limiting entry of cholesterol-derived carbon into central metabolism . Previous metabolic studies have shown that Mtb has the capacity to catabolize multiple carbon sources simultaneously [41] , however the fates of carbons from the simple substrates glucose , glycerol and acetate are highly compartmentalized . The logical extension of this would predict that , under certain growth conditions , these substrates may not be interchangeable . Given the ability of acetate to rescue Mtb growth inhibition by these compounds in cholesterol medium it is puzzling that fatty acids or other nutrients fail to exhibit comparable activity in the macrophage . The results imply a partitioning of metabolism whereby , within in a macrophage , Mtb may preferentially utilize cholesterol for energy production while other nutrients such as carbohydrates or fatty acids may fulfill separate metabolic requirements [52–54] . Phenotypically , this appears as an unusual form of catabolite repression , however additional studies are needed to investigate this possibility directly . The majority of compounds identified in this screen result in bacteriostatic phenotypes in vitro , which may limit their potential as lead compounds for drug development . However , the surprising diversity of targets , pathways , and mechanisms of action all linking back to cholesterol metabolism uncovers an extensive , and hitherto unappreciated chink in this bacterium’s armor .
M . tuberculosis CDC1551 and M . tuberculosis H37Rv Δicl1 [18] were utilized for all experiments . Bacteria were routinely grown at 37°C in 7H9 ( broth ) or 7H11 ( agar ) media supplemented containing 0 . 05% glycerol and OADC enrichment ( 0 . 5% bovine serum albumin fraction V , 0 . 2% glucose , 0 . 085% NaCl ) . Broth cultures also contained 0 . 05% tyloxapol . E . coli cultures were grown in LB medium . Antibiotics were added as described [53] . Macrophages ( J774 cells from American Type Culture Collection ) were seeded into 384-well black clear bottom plates . M . tuberculosis CDC1551 expressing mCherry was grown to mid-log phase in Middlebrook 7H9 OADC washed , and syringed 6-times with 25G⅝ tuberculin syringe . The de-clumped bacteria were diluted into pre-warmed infection media ( DMEM , 10% fetal calf serum , 2 . 0 mM L-glutamine , and 1 . 0 mM sodium pyruvate ) and were used to infect cells at an MOI of 4:1 . Bacteria were added to the screening plates with a Janus Ministation ( Perkin Elmer ) . Compounds were added to the screening plates 1 hour after infection to a final concentration of 10 μM . Following a six day incubation period at 37°C and 6% CO2 Mtb mCherry fluorescence was quantified using an Envision Multilabel plate reader ( Perkin Elmer ) . All screening plates contained negative ( DMSO ) and positive ( 10 μM rifampicin ) controls . Percent inhibition for the experimental compounds was calculated using the formula , percent inhibition = 100x ( DMSO signal—sample signal ) / ( DMSO signal—rifampicin signal ) . The Z′ factor , a measure of variability and reproducibility [21] , was determined for each plate using the following formula: Z′ = 1-[3× ( SDrifampicin+SDDMSO ) /|Mrifampicin-MDMSO|] , where SD denotes the standard deviation and M denotes the mean for the samples and controls , respectively . To determine compound potency against Mtb in liquid culture an Alamar Blue reduction assay was used as described [22] . For inhibition assays conducted in Middlebrook 7H9 OADC the bacteria were cultured to mid-log phase ( OD600 of 0 . 4 ) in 7H9 OADC and assayed in 96-well black clear bottom plates . Briefly , 1 . 0x106 bacteria were added to each well containing 7H9 OADC and experimental compounds or controls to a final volume of 200 ul . For inhibition assays in media containing alternative carbon sources Mtb was first cultured to an ( OD600 of 0 . 4 ) in 7H12 media ( 7H9 base , 0 . 1% casamino acids , 100 mM 2-morpholinoethanesulfonic acid pH 6 . 6 ) and 0 . 1% ( wt/vol ) acetate as the carbon source and 0 . 05% tyloxapol [25] . Cholesterol was added to the culture media at a final concentration of 100 μM as ethanol/tyloxapol micelles according to [53] . For the inhibition assay , bacteria were washed in PBS tyloxapol 0 . 05% twice and 1 . 0x106 bacteria were added to 96-well microplates containing 7H12 media to a final volume of 200 μl containing the experimental compounds , controls , and supplemented with carbon substrates at 0 . 1% ( wt/vol ) unless otherwise noted . The microplates were incubated for 10 days in humidified , sealed plastic bags at 37°C . To quantify bacterial proliferation 40 ul of an Alamar Blue solution 50% was added to each well and the plates were re-incubated at 37°C for 16 hr . Alamar Blue reduction was quantified using an Envision Multilabel plate reader ( Perkin Elmer ) with λex = 492 nm and λem = 595 nm . To determine compound potency in the macrophages , J774 cells were infected and using the HTS protocol and exposed to a dilution series of the experimental compounds . All screening plates contained DMSO and 10 μM rifampicin control wells and percent inhibition for the experimental compounds was calculated . IC50 values were determined by fitting the percent inhibition dose response curves in Prism ( GraphPad Software ) , using a sigmoidal variable slope fit with the maximum % activity and the minimum % activity fixed at 100% and 0% , respectively . Bacteria were grown in vented T-25 flasks as described above and treated with the experimental compounds at 10x IC50 concentration for 4 hours . Bacterial RNA was isolated , amplified , and labeled for microarray analysis . All the microarray hybridizations and data analyses were performed as described [7] . The entire microarray dataset is publically available on ArrayExpress database ( www . ebi . ac . uk/arrayexpress/ ) accession number E-MTAB-3142 . Cholesterol utilization by Mtb was quantifying by monitoring the release of 14CO2 from [4–14C]-cholesterol by radiorespirometry . Briefly , Mtb cultures were grown in 5 ml 7H9 OADC or 7H12 medium supplemented with indicated carbon substrates in vented standing T-25 tissue culture flasks . Experimental compounds and 1 . 0 μCi of the radiolabel were added to the bacterial cultures at the same time . The culture flasks were placed air-tight vessel with an open vial containing 0 . 5 ml NaOH 1 . 0 M and sealed for incubation at 37°C . After 5 days , the NaOH vial was recovered , neutralized with 0 . 5 ml HCl 1 . 0 M , and the amount of base soluble Na214CO3 was quantified by scintillation counting . Radioactivity signal was normalized to the relative levels of bacterial growth by determining the OD600 of the bacterial cultures at day 5 . The full-length gene encoding PrpC/Rv1131 was cloned into pET23a ( Novagen ) creating a C-terminal fusion with a 6x-His tag . The recombinant PrpC was produced in E . coli BL21 ( Novagen ) following induction with isopropyl-thiogalactopyranoside 0 . 25 mM for 16 hours at 15°C . The His-tagged PrpC was purified from the E . coli lysates as described [55] . Methylcitrate synthase activity of the Mtb PrpC enzyme was monitored by detecting the release of CoASH , from propionyl-CoA during the condensation reaction with oxaloacetate , using 5 , 5′-dithiobis-2-nitrobenzoate as described [19] . The assays were conducted at 37°C in a 96-well black clear bottom plate containing 50 mM HEPES-NaOH pH 8 . 0 , 0 . 1 M NaCl , 2 mM EDTA , 0 . 1 M DTNB , 0 . 14 mM propionyl-CoA , and 0 . 2 mM oxaloacetate . Recombinant PrpC ( 10 μg ) was added and CoASH production was monitored spectrophotometrically at 412 nm using an Envision Multilabel plate reader . Background was subtracted to account for free thiol in the initial reaction mixture . The percent inhibition at each compound concentration was calculated using the equation %I = ( 1-vI/v0 ) *100 where vI and v0 are the rates observed in the presence and absence of inhibitor , respectively . The IC50 values were calculated by fitting to the inhibition data using nonlinear curve fitting . Gas chromatography coupled mass spectrometry analyses of TMS-derivatized culture extracts were performed using an HP 6890 series GC system fitted with an HP 5973 mass-selective detector and a 30 m × 250 μm HP-5MS Agilent column . The operating conditions were: TGC ( injector ) , 280°C; TMS ( ion source ) , 230°C; oven time program T0 min , 104°C , T2 min , 104°C , T14 . 4 min , 290°C ( heating rate 15°C·min-1 ) , T29 . 4 min; 290°C . HsaA , HsaB , HsaC and HsaD were purified as described previously [29 , 31 , 32] . HsaB was reconstituted with FMN [29] . 3-Hydroxy-9 , 10-secoandrosta-1 , 3 , 5 ( 10 ) -triene-9 , 17-dione ( 3-HSA ) , 3 , 4-dihydroxy-9 , 10-secoandrosta-1 , 3 , 5 ( 10 ) -triene-9 , 17-dione ( DHSA ) , and 4 , 5–9 , 10-diseco-3-hydroxy-5 , 9 , 17-tri-oxoandrosta-1 ( 10 ) , 2-diene-4-oic acid ( DSHA ) were prepared using previously described biotransformations [29 , 31 , 32] . HsaC and HsaD assays were performed as described [31 , 32] . HsaAB activity was measured spectrophotometrically by following the hydroxylation of 3-HSA in a coupled assay with HsaC at 25 ± 0 . 5°C . Reactions were performed in 200 μl potassium phosphate ( I = 0 . 1 M ) , pH 7 . 5 containing 2 . 5 μM HsaA , 1 μM HsaB , 1 μM HsaC , 400 μM NADH and 100 μM 3-HSA . Initial rates were determined over a 30 s interval . The reaction was monitored at 392 nm , the absorbance maximum of DSHA ( ε392 = 3 . 8 mM-1 cm-1 ) . Background ΔA392 was subtracted to account for uncoupled NADH consumption . Stock solutions were prepared fresh daily . The percent inhibition at each compound concentration was calculated using the equation %I = ( 1-vI/v0 ) *100where vI and v0 are the rates observed in the presence and absence of inhibitor , respectively . The IC50 values were calculated by fitting the equation %I = 100–100/ ( 1+[I]/IC50 ) to the inhibition data using nonlinear curve fitting . To isolate transposon mutants resistant to the inhibitor V-12–007958 a transposon library ( ~105 ) in a wild type Mtb background was propagated for seven days in 7H12 media containing 100 μM cholesterol and 10 μM compound . Following the growth selection the bacteria were plated onto 7H11 OADC agar to isolate individual clones . Chromosomal DNA from the individual mutants was isolated and the transposon insertion sites were PCR amplified and sequenced according to [56] . Bacteria grown in 7H12 media containing cholesterol 100 μM cholesterol and 0 . 1% acetate were exposed to the experimental compounds for 8 hours . To determine intracellular levels of cAMP , cell suspensions containing 108 cells were isolated by centrifugation . The bacterial pellet was suspended in 0 . 5 ml 0 . 1 M HCl and the cAMP containing lyaste was extracted by vigorous vortexing for 20 min . Bacterial debris was removed by centrifugation and the supernatants were used for cAMP estimation using a direct immunoassay kit ( Enzo ) . | Human beings are the sole ecological niche for M . tuberculosis ( Mtb ) , and it is estimated that 1 . 8 billion people are currently infected with Mtb . An important aspect of this infection is Mtb’s ability to maintain infection by replicating within macrophages . Within macrophages , Mtb exploits a specialized set of metabolic pathways to utilize host-derived nutrients , such as fatty acids and/or cholesterol , for energy production . Many details regarding Mtb metabolism during infection remain unknown . Here we took a chemical approach to identify small molecule probes , which target Mtb metabolism during infection in macrophages . We found that many of the small molecule inhibitors that we identified require cholesterol for activity . Here we report a novel chemical rescue approach to identify the metabolic targets of three novel inhibitors , and discovered that cAMP signaling is linked to cholesterol utilization in Mtb . Together , these data demonstrate that cholesterol exerts a dominant effect on Mtb metabolism within macrophages . Additionally , the novel inhibitors identified in this study will facilitate evaluation of cholesterol metabolism as a target for chemotherapeutic intervention . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] | [] | 2015 | Novel Inhibitors of Cholesterol Degradation in Mycobacterium tuberculosis Reveal How the Bacterium’s Metabolism Is Constrained by the Intracellular Environment |
Several highly conserved genes play a role in anterior neural plate patterning of vertebrates and in head and brain patterning of insects . However , head involution in Drosophila has impeded a systematic identification of genes required for insect head formation . Therefore , we use the red flour beetle Tribolium castaneum in order to comprehensively test the function of orthologs of vertebrate neural plate patterning genes for a function in insect head development . RNAi analysis reveals that most of these genes are indeed required for insect head capsule patterning , and we also identified several genes that had not been implicated in this process before . Furthermore , we show that Tc-six3/optix acts upstream of Tc-wingless , Tc-orthodenticle1 , and Tc-eyeless to control anterior median development . Finally , we demonstrate that Tc-six3/optix is the first gene known to be required for the embryonic formation of the central complex , a midline-spanning brain part connected to the neuroendocrine pars intercerebralis . These functions are very likely conserved among bilaterians since vertebrate six3 is required for neuroendocrine and median brain development with certain mutations leading to holoprosencephaly .
The insect head is composed of several fused segments , the number of which remains disputed ( e . g . [1]–[6] ) . The posterior labial , maxillary and mandibular segments are patterned by the well-studied trunk segmentation cascade . In contrast , the patterning of the procephalic region ( intercalary , antennal , ocular segments and anterior non-segmental region ) is less well understood . It has been suggested in the fruit fly Drosophila melanogaster that the head gap-like genes orthodenticle ( otd ) , empty-spiracles ( ems ) , buttonhead ( btd ) and sloppy-paired ( slp ) activate segment polarity genes directly or via second order regulators [7]–[9] but an instructive role could not be confirmed for btd and ems [10] , [11] . Moreover , the segment polarity interactions of head segments differ from those in the trunk . For example , hedgehog ( hh ) expression in the intercalary segment is driven by its own unique enhancer element [12] , [13] ( see [4] and [6] for further details ) . However , the development of the larval head of Drosophila is highly derived . During late stages of embryogenesis , the head gets turned outside into the thorax ( head involution ) and consequently cuticular head structures are highly reduced [14]–[16] . Also the emergence of the everted adult head from imaginal discs is derived within insects [17] , [18] . These morphological differences correlate with changes in embryonic pattern formation . Comparisons with other insects have revealed that the upstream levels of head formation differ profoundly ( e . g . no bicoid in most insects [19] , no torso signaling in head development [20] , different input of decapentaplegic ( dpp ) on head development [21] ) while some degree of conservation is found on lower levels like the head gap like genes , second order regulators and segment polarity genes ( [4] and references therein ) . Notably , the head expression of wingless ( wg ) appears to be reduced in Drosophila correlating with its derived head development . Hence , the evolution of the Drosophila head involved both structural changes and alterations of the gene regulatory network [4] , [6] , [14] , [22] . Intriguingly , orthologs of several genes required for Drosophila head patterning play a role in vertebrate neural plate patterning ( e . g . otd/otx , ems/emx , slp/bf1 , tailless ( tll ) /tlx ) . These data indicated that anterior patterning in insects and vertebrates relies on a strongly overlapping gene set [2] , [7] , [8] , [13] , [23]–[36] . Indeed , additional similarities between vertebrate and insect head and brain patterning have subsequently been revealed ( e . g . [37]–[47] ) . Furthermore , an urbilaterian origin of anterior brain patterning has also been supported by similar data in an annelid [48]–[52] . The red flour beetle Tribolium castaneum has recently been established as a model for insect head development because it has an insect typical non-involuted head developing from a ventral-posterior region of the blastoderm , reflecting the ancestral situation ( reviewed in [4] , [53] ) . Several orthologs of Drosophila head patterning genes have been studied in Tribolium revealing differences with respect to the head gap-like genes [54] and knirps [55] but also a number of similarities with respect to second order regulators [56] , [57] . Furthermore , genes required for vertebrate placode development were found to be active at similar locations in the Tribolium embryonic head [44] . Tc-six3 is a member of the six type homeobox gene family , which has three members in insects [58] while two paralogs of each family are found in mouse ( six3/six6 , six1/2 and six4/5 ) . It is required for the formation of the labrum , an appendage of the non-segmental part of the head [3] . The Drosophila ortholog , called optix , is required for eye development [59]–[61] , and for maxillary and clypeolabral structures of the larval head [62] . However , genetic interactions of this gene in the context of head development have not been analyzed in insects so far . Suggestively , the vertebrate six3 gene is essential for eye development [63]–[70] and anterior neural plate patterning [71]–[75] . Furthermore , vertebrate six3 and its paralog six6 are involved in the development of the neuroendocrine pituitary and hypothalamus [76]–[80] . As the six3 expression domain is anterior to the otd domain in arthropods , annelids and vertebrates , it is likely that this was also a feature of the last common ancestor of bilaterian animals [81] . In order to identify novel insect head patterning genes and with the high degree of conservation in mind , we comprehensively tested Tribolium orthologs of vertebrate neural plate patterning genes for a function in the insect head . Indeed , we find that many of them are required for head development . Closer examination of Tc- six3 reveals that it acts upstream of Tc-wingless ( Tc-wg ) , Tc-otd and Tc-eyeless ( Tc-ey ) in anterior median head patterning . Further , we find that Tc-six3 is required for median brain development with a specific role in central body formation .
From the literature we identified 24 genes involved in early vertebrate neural plate patterning ( see Table S1 ) [32] , [33] , [41] , [45] , [74] , [80] , [82]–[127] . Three genes do not possess orthologs in either the Tribolium or Drosophila genome ( Dmbx1/Atx , Vax1 , Hesx1/Rpx; see phylogenetic trees in Figure S1 ) . Tc-FGF8 does not cluster unequivocally with mouse FGF8 but with the Drosophila Pyramus and Thisbe proteins which have previously been identified as FGF8 orthologs [128] , [129] . Of the 21 orthologs , Tc-BarH , Tc-Wnt11 and Tc-munster/arx are not expressed in the head anlagen ( not shown ) , while the remaining 18 genes are active in the embryonic head . For these genes , we determined the expression pattern at several stages ( determined by Tc-wg counter stain ) in order to reveal their dynamics during head development . Genes that had not been described before in Tribolium are shown in Figure 1 . In order to produce a comprehensive dataset with comparable staging , we also included previously described genes ( Figures S2 and S3 ) ( Tc-otd [130] , Tc-ems [54] , Tc-tailless ( Tc-tll ) [131] , Tc-six3 [3] , Tc-hedgehog ( Tc-hh ) [132] , [133] , Tc-cubitus-interruptus ( Tc-ci ) [132] , Tc-wg [134] , Tc-fgf8 [128] , Tc-sloppy paired ( Tc-slp ) [135] , Tc-eyeless ( Tc-ey ) [136] , Tc-ptx [44] , Tc-irx [137] ) . Interestingly , a number of these genes are expressed in the head but not segmentally reiterated in the trunk ( Tc-otd , Tc-six3 , Tc-tll , Tc-lim1 , Tc-gsc , Tc-scro , Tc-rx , Tc-fez1 ) supporting the notion that the anterior patterning system differs from the one of the trunk . However , other genes do have segmentally reiterated expression in addition to anterior expression ( Tc-hh , Tc-wg , Tc-ci , Tc-irx/mirr , Tc-fgf8 , Tc-slp , Tc-ems , Tc-ey , Tc-dbx , Tc-ptx ) , linking these two systems . The embryonic preantennal region gives rise to the lateral and dorsal head capsule ( compare white area anterior to the dark grey shaded antennal segment in a flattened germband in Figure 2D with a non-flattened embryo depicted in E ) [4] , [44] . This region is marked by an invariant bristle pattern in the first instar larval cuticle [54] ( see Figure 2F for most prominent bristles and Figure S4 for more details ) , which allows the localization of cuticle defects , which arose in pre-antennal tissues . Unfortunately , previously published RNAi phenotypes had not been scored for the head bristle pattern except for Tc-otd and Tc-ems [54] and Tc-ey/toy , where a small subset of three setae was scored [136] . Therefore , we performed RNAi for all novel genes as well for those where the head capsule defects had not been described previously . We excluded Tc-hh and Tc-wg because RNAi for these genes induces severe generalized embryonic defects , which impede the analysis of the bristle pattern ( data not shown and [132] , [138] ) . Tc-ci RNAi interfered with segmentation of the entire embryo as described [132] . Head defects ranged from the total loss of the head ( 9 . 1% , n = 11 ) to the loss and malformation of gnathal segments ( 90 . 9%; Figure 3C ) . Where accessible , the head bristle pattern was analyzed , revealing mainly a disruption of the vertex setae marking the dorsal tissue ( Figure 3C′; the numbers for this and other bristle pattern defects are given in Table S2 , the names of the setae and bristles are given in Figure S4 ) . Knock down of the pair rule gene Tc-slp resulted in a pair rule phenotype [135] ( 70% , n = 10; Figure 3D ) . We found additional head defects in the median part of the vertex , the bell row and the maxilla escort bristles ( Figure 3D′ ) . Tc-six3 knock down leads to loss of the labrum and clypeolabral parts of the anterior head capsule [3] , [62] ( 100% , n = 16; Figure 3E ) . In line with the loss of anterior median cuticle , the anterior vertex seta and the anterior vertex bristle were missing ( Figure 3E′ ) , while the median part of the dorsal head cuticle often displayed an irregular pattern of additional bristles and setae . Tc-ey and Tc-toy have been shown to act synergistically in eye formation , while the respective analysis on the head bristle pattern was restricted to 3 bristles [136] . Re-analysis of single and double RNAi revealed more extensive defects than previously described ( Figure 3F , 3F′ ) . In comparison with single RNAi experiments , double RNAi revealed a 1 , 4- to 6-fold increase of penetrance of bristle pattern defects using the same final concentration of dsRNA ( Table S2 ) confirming that the two Tribolium pax6 orthologs also act synergistically in epidermis development . The head of Tc-lim1/5 RNAi larvae was compacted and shortened ( 16 . 7% , n = 12; Figure 3G ) . Head appendages were present but mostly malformed ( 41 . 7% ) . The anterior and median maxilla escort bristles failed to form ( Figure 3G′ ) , while in 20 . 8% no bell row was observed ( Figure 3G′ ) . In Tc-scro RNAi larvae the labrum failed to fuse either completely ( 60%; n = 15 ) ( black arrowheads in Figure 3H ) or partially ( 13 . 3%; not shown ) . The bristle pattern remained largely unaltered except for the anterior vertex bristle ( Figure 3H′ ) . Interestingly , the labrum quartet bristles were present even on unfused labra . In Tc-rx knock down larvae , the labrum was narrower than in wild type leading to a widened space between the labrum and the antennae ( 25% , n = 8; arrow in Figure 3I ) and the adjacent clypeus bristles of the labrum quartet were lost in more than half of the analyzed RNAi larvae ( Figure 3I′ ) . Additionally , the antenna basis bristle and the median maxilla escort seta were sensitive to Tc-rx knock down ( Figure 3I′ ) . RNAi against the remaining genes did not elicit large deletions but alterations of the head bristle pattern ( Figure 4 and Table S2 ) . Lateral defects were found after RNAi against Tc-dbx , Tc-ey single RNAi and Tc-gsc ( Figure 4A–4C ) . Tc-ptx and Tc-irx led to dorsal defects ( Figure 4D , 4E ) while the bristle defects of Tc-toy , Tc-fez and Tc-tll were more widespread ( Figure 4F–4H ) . No bristles were missing in Tc-fgf8 RNAi ( n = 29 ) , although lethality of most larvae and a bent flagellum phenotype of the antenna in 41 . 5% ( n = 53 , not shown ) confirmed the RNAi effect . In summary , we showed that all vertebrate neural plate patterning genes investigated here ( except for Tc-fgf8 ) are indeed involved in anterior head epidermis patterning in Tribolium . By and large , the cuticle defects correspond well with the location of the expression domain , but we also find some indication for indirect defects ( see red circles in Figure 3 and Figure 4 and discussion for details ) . Considering its early expression and severe RNAi phenotype , Tc-six3 was likely to play a central role in insect head patterning . Therefore , we centered our subsequent analysis on the epidermal and neural function of this gene . We tested the effect of Tc-six3 RNAi on genes that-based on our expression and RNAi data-were likely to interact . Indeed , the protocerebral neuroectodermal expression domain of Tc-wg ( pne ) [133] ( also called the ocular Tc-wg domain or the head blob in Drosophila [2] , [133] ) expanded medially and anteriorly in early elongating RNAi embryos ( black arrowheads in Figure 5B ) , resulting in massive median misexpression in fully elongated germbands ( Figure 5D ) . The lateral aspects of Tc-wg expression appeared largely unchanged ( open arrows in Figure 5C–5D ) . Moreover , loss of median embryonic tissue was apparent ( white outline in Figure 5C–5D ) including the stomodeum ( see also Figure 5U ) and labrum anlagen ( white and black stars in Figure 5C , respectively ) . As a consequence , the head lobes were not bent outwards and the antennal Tc-wg stripes became perpendicular to the body axis instead of being twisted outwards as in wildtype ( compare arrows in Figure 5D with 5C; see Figure S5L–S50 for phenotypes of more advanced stages where the assignment of the antennal stripe becomes obvious ) . The expression of Tc-otd1 was strongly expanded towards anterior and median tissue ( compare Figure 5F , 5H with Figure 5E , 5G ) while the lateral aspects appeared normal ( open arrowheads in Figure 5G–5H ) . Despite being partially coexpressed ( Tc-tll and Tc-scro ) or expressed adjacent to the Tc-six3 domain ( Tc-rx ) , the expression domains of these genes remained unchanged after Tc- six3 RNAi ( not shown ) . The effect of Tc-six3 RNAi was different with respect to the various domains of Tc-ey ( Figure 5I–5N ) . Tc-ey expression starts in a prominent ocular domain ( open arrowheads in Figure S3 H2–3 ) before an additional anterior median expression arises ( black arrowheads in Figure 5I , 5K , 5M and Figure S3 H4–5 ) . We found coexpression of Tc-dachshund with parts of the anterior median domain ( white arrowheads in Figure S5C–S5C″ ) , making it possible that it marks mushroom body anlagen as in Drosophila [139] , [140] . In Tc-six3 RNAi embryos , the early ocular domain was strongly expanded towards the midline ( compare Figure 5J with Figure 5I ) . Later , a domain remained visible at the midline ( black star in Figure 5N ) . The anterior median domain did not develop in Tc-six3 RNAi embryos ( Figure 5J , 5L , 5N ) . Again , the lateral aspects of the ocular domain as well as the segmental domains appeared unaffected . six3 has been implicated in neuroendocrine development in vertebrates [80] and protostomes [81]; and in Drosophila , it is coexpressed with the neuroendocrine markers fas2 and chx [81] , [141] . The functional relevance of this co-expression remained unknown . We confirmed co-expression in Tribolium ( Figure S5D–S5G , S5H–S5K ) and found that in Tc-six3 RNAi embryos the anterior median domains of Tc-fas2 and Tc-chx were absent ( compare domains marked by black arrowheads in Figure 5O , 5Q to Figure 5P , 5R ) . In insects , epidermal and neural precursor cells are intermingled in the neuroectoderm . The neural stem cells receive spatial patterning cues before they delaminate from the neuroectoderm and contribute to the central nervous system in a cell autonomous way . The remaining epidermal cells eventually secrete the cuticle [142] , [143] . This explains why mutations in segment polarity genes elicit both cuticular and CNS defects . With this in mind , it was likely that Tc-six3 knock down would induce brain defects . First , we determined that eight Tc-ase marked neuroblasts are found within the Tc-six3 marked neuroectoderm until 24 hours of development ( extended germband stage , white stars and arrows in Figure 6A ) . Later , in 42–48 hour old embryos , Tc-six3 is expressed in the developing brain lateral and anterior to the stomodeum ( Figure 6C , stomodeum marked by black asterisk ) . Additionally , staining is evident in the overlaying dorsal epidermis ( Figure 6B ) , the stomodeal roof ( Figure 6D ) and the labrum ( Figure 6E ) . In order to test the hypothesis of a neural function of Tc-six3 , we generated transgenic imaging lines marking neural cells , glia and mushroom bodies ( Koniszewski , Kollmann , Averof , in preparation ) and we identified the central body at the L1 larval stage ( white arrow in Figure 6F ) . Indeed , Tc-six3 RNAi at low doses led to the loss of the central body in an otherwise normal brain ( Figure 6G ) . Higher doses additionally reduced the distance between the two brain hemispheres ( Figure 6H ) . In weak phenotypes the orientation of the median lobes of the mushroom bodies towards the midline was lost ( compare white arrowheads in Figure 6J with Figure 6I ) while in strong phenotypes , upon convergence of the brain hemispheres , the mushroom bodies approached each other and were reduced in size ( see black arrow in Figure 6K ) . In the light of the Tc-six3 expression profile , these brain defects could be due to an early neuroectodermal function of Tc-six3 ( see neuroectodermal expression in Figure S2B ) or to a later function in developing neural cells ( see expression in the brain in Figure 6B–6E ) . In the first case , epidermal and neural phenotypes would be elicited at the same time and , hence , be tightly linked . In the second case , knockdown at late embryonic stages ( when epidermal patterning is already finished ) would lead to the induction of neural phenotypes in otherwise unaffected heads . To test this , we injected 1 ug/ul Tc-six3 dsRNA in embryos at 0–2 , 4–6 , 6–8 , 12–14 and 18–20 hours post egg laying and scored the resulting L1 larvae for both cuticle and brain phenotypes ( Figure 6L ) . Indeed , the severity of neural and epidermal phenotypes correlated strongly and we never observed brain phenotypes in embryos without cuticle defects . This indicates that both cuticle and brain phenotype are outcomes of the same early neuroectodermal patterning events .
With our candidate gene approach we identified five genes that had not been implicated in insect head epidermis patterning before ( goosecoid , scarecrow , fez1 , dbx , ptx ) . For four additional genes , we show involvement in embryonic head capsule development while a role in adult Drosophila head patterning had been described previously ( ci , Drx , lim1 , mirror ) [144]–[147] . Based on our fate map , the cuticle defects generally correspond well with the head expression of the respective gene . However , the bell row and the setae of the maxilla escort appear to be sensitive to indirect effects because they were affected in several RNAi experiments with genes , which-based on our fatemap-do not show expression in the respective regions ( red circles in Figure 3 Tc-lim1/5 , Tc-ptx , Tc-irx and Figure 4 Tc-six3 , Tc-rx , Tc-fez ) . Both regions are located where the head lobes are predicted to fuse either with gnathal segments ( maxilla escort ) or the trunk ( bell row; see black stars in Figure 2C ) . Hence , primary defects of a gene knockdown in head lobe morphology or size could lead to the observed secondary defects . We show that Tc-six3 is required for proper formation of the central body , which is a midline spanning neuropile and part of the central complex . To our knowledge , this is the first gene known to be required for embryonic central complex development . Our data are in line with cell lineage tracing experiments in grasshopper embryos , where neuroblasts at a corresponding anterior median position contribute to the central complex [148] . Further , expression of optix/six3 in corresponding neuroblasts was also shown in Drosophila [81] . Together , these data are consistent with the hypothesis that Tc-six3 is required in the neuroectoderm for specifying the identity of central body neuroblasts . However , tools to genetically trace the offspring of these neuroblasts [149] are needed to prove this link . In hemimetabolous insects , which represent the ancestral mode of embryogenesis , all neuropils of the central complex are formed during embryogenesis . In Drosophila , in contrast , the central complex develops during late larval stages [150]–[153] . Tribolium takes an intermediate position by forming a subset of central complex neuropils during embryogenesis , a situation apparently conserved with another tenebrionid beetle [154] . With the newly available brain imaging lines and its amenability to functional genomics Tribolium is an excellent model to investigate the genetics of embryonic central complex development . We showed that Tc-six3 is expressed in an anterior median domain from earliest stages on and that it acts as an upstream component of anterior median patterning . Drosophila optix/six3 is expressed in an anterior blastodermal ring anterior to otd , which persists at the dorsal side [58] , [70] , [81] and is required for labral and maxillary structures [62] . Its ring like expression does not support an involvement in median patterning but relevant genetic interactions remain to be studied . The later expression in the labrum and in bilateral dorsal domains , however , is similar in both species . Interestingly , aspects of dorsal median head patterning are controlled by dpp in Drosophila . Shortly before gastrulation , the action of dpp and its downstream target zen at the dorsal midline separate the neuroectoderm into paired anlagen by medial repression of genes and by promoting median cell death . This results in the establishment of bilateral expression of marker genes of the respective brain parts ( e . g . Dchx ( pars intercerebralis ) ; Fas2 and Drx ( pars lateralis ) ; sine oculis and eyes-absent ( visual system ) ) [46] , [141] , [155] , [156] . Actually , many other anterior patterning genes initiate their expression as unpaired domains across the dorsal midline that are subsequently medially subdivided in Drosophila ( e . g . otd [157] , tll [158] , fezf [159] , Dsix4 [58] ) . In contrast , the Tribolium orthologs of most of these genes are initiated as separate bilateral domains ( Tc-rx and Tc-fez ( Figure 1E and 1D ) , Tc-chx and Tc-Fas2 ( Figure S5 ) , Tc-tll [131] ) , Tc-six4 [44] , Tc-sine oculis , Tc-eyes-absent [160] ) . Tc-otd1 starts out with ubiquitous expression related to axis formation [130] , [161] , [162] but then resolves into paired head lobe domains which are separate as with the aforementioned genes . Due to differences in topology of the head anlagen ( see below ) , median repression of anterior patterning genes by Tc-dpp is not required in Tribolium . Nevertheless , it is expressed along the rim of the head anlagen at blastoderm stages , some parts of which will become the site of dorsal fusion [163] , [164] . However , Tc-Dpp activity ( detected by antibodies against pMad ) does not occur at the site of expression and is clearly distant from the arising Tc-rx , Tc-chx , Tc-six4 , Tc-sine oculis or Tc-fas2 domains [21] . Also the Tc-dpp RNAi phenotypes differ from Drosophila mutants in that the head anlagen are expanded and appear to have lost their dorso-ventral orientation ( shown by expansion of Tc-otd1 and the proneural gene Tc-ASH ) in an overall ventralized embryo [21] . Hence , the early expression of dpp at the future dorsal midline might be ancestral , but its function with respect to medially repressing gene expression has probably evolved in Drosophila . The difference in generation of paired dorsal domains in these two insect species reflects the different location of the head anlagen . In the long germ insect Drosophila , extraembryonic tissues are reduced to the dorsally located amnioserosa while the head anlagen are situated in the anterior dorsal blastoderm from earliest stages on [165] , [166] . Consequently , the head lobes are never separated along the midline . In contrast , in the short germ insect Tribolium , the anterior blastoderm gives rise to extraembryonic amnion and serosa , which eventually ensheath the embryo [166] . In contrast to Drosophila , the Tribolium head anlagen are located in the ventral median blastoderm from where they move towards anteriorly and bend dorsally . The head lobes are separate from the beginning but fuse at late stages at the dorsal midline forming the dorsal head ( bend and zipper model , see Figure 2A–2C and [4] , [137] for more details ) . During these morphogenetic movements , the initially separate expression domains of the head lobes eventually come into close proximity at the dorsal midline like in Drosophila ( Figure 2D–2F ) . Both the anterior dorsal location of extraembryonic tissue anlagen and the ventral location of the head anlagen are found in most insects [166] and in the hemimetabolous milkweed bug Oncopeltus fasciatus , gene expression data show a clear separated origin of the head lobes in the blastoderm [167] . Hence , Tribolium is likely to represent the ancestral state in insects . In striking analogy to Drosophila , the expressions of vertebrate eye field patterning genes start out as one midline spanning domain ( e . g . Rx and Pax6 [65] , [168] , [169] ) . Later , these domains split medially , which is the prerequisite for the formation of bilateral eye anlagen . shh as well as six3 are involved in medial repression of Pax6 and Rx2 [65] , [169] with six3 acting upstream of shh [170] . This appears to be more similar to the derived Drosophila situation than to the ancestral split of head lobe anlagen ( see above ) . However , the molecules involved in median split are different ( dpp in Drosophila versus six3 and shh in vertebrates ) and we find involvement of Tribolium six3 but not dpp in median patterning . Hence , the molecular data actually suggest a higher degree of conservation between Tribolium and vertebrates and convergent evolution of the similarity between Drosophila and vertebrates . Regarding the likely difference to Drosophila , it is striking that the role of vertebrate six3 in median separation of anterior expression domains is similar to what we find in Tribolium . In vertebrates , six3 represses midbrain derived Wnt signaling [72] , [73] , which we also find in Tribolium . In vertebrates , six3 and its paralog six6 are involved in pituitary and hypothalamus development [76]–[80] . Based on its expression , six3 has been predicted to contribute to neuroendocrine brain parts in annelids and Drosophila [81] . More generally , the similarity of bilaterian neuroendocrine systems and their common origin from placode like precursors have been noted [44] , [47] , [171] . Here , we have added functional data showing that Tc-six3 is indeed required for the expression of neuroendocrine markers for the pars intercerebralis ( Tc-chx ) and pars lateralis ( Tc-fas2 ) [141] placing it high in the hierarchy of neuroendocrine development in bilaterians . In mouse embryos with reduced levels of six3 and shh expression , median head and brain structures are affected ( e . g . median nasal prominence ) or absent ( e . g . nasal septum , the septum , corpus callosum ) ( see Figure 5X ) [170] . Such holoprosencephaly phenotypes are also seen in some human six3 mutations [172] . Very similarly , we see loss of median brain structures in Tribolium after RNAi for Tc-six3 Overall , these similarities functionally confirm that the ancestral role of six3 orthologs was in the anterior median patterning of the Urbilateria ( Figure 5V–5X ) [81] .
Most experiments were performed using the wild type Tribolium castaneum strain San Bernardino . For brain imaging , a transgenic line for 6XP3-ECFP ( marking glia ) and elongation factor1-alpha regulatory region-DsRedEx ( EF1-B; marking neural cells ) and the enhancer trap line Gö-11410 ( marking mushroom bodies with EGFP; identified in the GEKU screen [173] ) were used ( Koniszewski , Kollmann , Averof , in preparation ) . Mouse protein sequences of the candidate genes ( see Table S1 ) were obtained from the NCBI database ( www . ncbi . nlm . nih . gov/ ) . Tribolium orthologs were identified by BLAST at the Beetle Base server ( beetlebase . org/ ) . Test of orthology: Tribolium sequences were blasted against the NCBI protein database and the top 5–15 hits from insects , vertebrate and selected other groups were retrieved , as well as the three most similar Tribolium genes . These were BLASTed against the entire NCBI nucleotide database and the first three hits were retrieved . All these sequences were aligned using the ClustalW algorithm of Mega 4 [174] , [175] . Phylogenetic trees were calculated in Mega 4 using the Neighbor-Joining method [176] ( bootstrap consensus tree inferred from 10 . 000 replicates [177]; evolutionary distances computed using the Poisson correction method [178]; all positions containing gaps and missing data were eliminated from the dataset ( complete deletion option ) ) . See Figure S1 for phylogenetic trees . Phylogenetic relationships for the following genes were already published: Tc-wnt11 and Tc-wg/wnt1 [179] , Tc-otd1/otx and Tc-ems/emx [54] , Tc-ey/pax6 and Tc-toy/pax6 [136] , Tc-eya [160] . mRNA of 0–48 h embryos was isolated using the MicroPoly ( A ) Purist Kit ( Ambion ) and cDNA was synthesized by using the SMART PCR cDNA Synthesis Kit ( ClonTech ) . Gene fragments obtained by PCR with gene specific primers ( see Table S3 ) were cloned into the pCRII vector using the TA Cloning Dual Promotor Kit ( Invitrogen ) and their sequence was confirmed . Single ( NBT/BCIP ) and double in situ stainings ( NBT/BCIP & FastRed or INT/BCIP ) were performed and documented as described [180] , [181] . RNAi was performed by injection of dsRNA into pupae ( pRNAi ) , adults ( aRNAi ) or embryos ( eRNAi ) as described [182]–[184] . Lengths of gene fragments and mode of injection are listed in Table S1 . Concentrations used in pupal RNAi and adult RNAi: 2–4 µg/µl; in embryonic RNAi: 1–2 µg/µl . A negative control for pupal RNAi was performed by pricking pupae with the needle or injecting water , injection buffer or dsRNA against tGFP . These controls did not show significant developmental effects in the offspring ( not shown ) . In order to identify potential off-target regions , sequences were BLASTed against the Tribolium genome ( BLASTn ) at Beetle Base . For five genes , sequence similarity of 21 or more successive identical nucleotides was found to hit other gene predictions . For those , RNAi analysis was repeated by another person using subfragments that did not contain the potentially off-target sequences . The phenotypic effects were very similar with respect to the cuticle phenotype ( not shown ) and the head bristle pattern ( Table S2 ) . See Table S3 for primers for the subfragments . Because Tc-six3 was investigated in more detail , two non-overlapping fragments were cloned , injected and analyzed separately by another person . Staining of Tc-six3 in Tc-six3 RNAi embryos confirmed strongly reduced or imperceptible expression in knock down embryos . The cuticle phenotype ( not shown ) and the head bristle pattern ( Table S2 ) was very similar , confirming specificity . Image stacks of cleared first instar cuticles were gathered by using a Zeiss LSM 510 or a Zeiss Axioplan 2 microscope and projections were calculated as described previously [44] , [181] . Brain imaging was performed using a Zeiss LSM 510 . | All bilaterian animals evolved from one common ancestor . Previous gene function analyses have revealed that several genes play a role in the patterning of anterior regions in all bilaterian animals , suggesting similar mechanisms underlying anterior nervous system formation in humans and the patterning of the insect head and brain . In order to identify novel genes required for anterior development in insects , we have systematically tested genes known to be crucially involved in early nervous system development in vertebrates ( e . g . mice and humans ) for their activity in the head of the red flour beetle Tribolium casteneum . Indeed , all but one of these genes are required for head development . Intriguingly , we find that six3 is required for anterior median brain structures in insects just as it is in vertebrates , where six3 mutations lead to holoprosencephaly . | [
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] | 2011 | Candidate Gene Screen in the Red Flour Beetle Tribolium Reveals Six3 as Ancient Regulator of Anterior Median Head and Central Complex Development |
Dengue is the most prevalent mosquito-borne viral disease of humans and is caused by the four serotypes of dengue virus . To estimate the incidence of dengue and other arboviruses , we analyzed the baseline and first year follow-up of a prospective school-based cohort study and their families in three cities in the state of Yucatan , Mexico . Through enhanced surveillance activities , acute febrile illnesses in the participants were detected and yearly blood samples were collected to evaluate dengue infection incidence . A Cox model was fitted to identify hazard ratios of arboviral infections in the first year of follow-up of the cohort . The incidence of dengue symptomatic infections observed during the first year of follow-up ( 2015–2016 ) was 3 . 5 cases per 1 , 000 person-years ( 95% CI: 1 . 9 , 5 . 9 ) . The incidence of dengue infections was 33 . 9 infections per 1 , 000 person-years ( 95% CI: 31 . 7 , 48 . 0 ) . The majority of dengue infections and seroconversions were observed in the younger age groups ( ≤ 14 years old ) . Other arboviruses were circulating in the state of Yucatan during the study period . The incidence of symptomatic chikungunya infections was 8 . 6 per 1 , 000 person-years ( 95% CI: 5 . 8 , 12 . 3 ) and the incidence of symptomatic Zika infections was 2 . 3 per 1 , 000 person-years ( 95% CI: 0 . 9 , 4 . 5 ) . Our model shows that having a dengue infection during the first year of follow-up was significantly associated with being female , living in Ticul or Progreso , and being dengue naïve at baseline . Age was not significantly associated with the outcome , it was confounded by prior immunity to dengue that increases with age . This is the first report of a cohort in Latin America that provides incidence estimates of the three arboviruses co-circulating in all age groups . This study provides important information for understanding the epidemiology of dengue and other arboviruses and better informing public health policies .
Over the past 40 years , dengue virus incidence in human population has increased 30-fold and the geographic range of the virus expanding to new countries as increasing urbanization , global human travel and urban to rural migration enable opportunities for transmission [1 , 2] Currently more than 40% of the human population worldwide is at risk of dengue infections , with approximately 390 million infections estimated to occur globally each year , of which 96 million have clinical manifestations of the virus [3] . Dengue virus ( DENV ) has four serotypes , each of them can be responsible for dengue epidemics and can also be associated with severe disease depending on the sequence and time between infections , among other factors [4–6] . The clinical spectrum of dengue ranges from asymptomatic infections to life-threatening severe disease; approximately 50% to 90% of dengue infections are asymptomatic [7 , 8] . The probability of symptomatic dengue due to dengue virus infection is altered by the previous dengue immune status [9] . Currently there is no specific treatment for dengue infection or clinical predictors to prevent severe disease [10] . Surveillance systems based on the monitoring and notification of dengue symptomatic cases have low sensitivity and rarely detect low or sporadic transmission [11 , 12] . The proportion of dengue asymptomatic infections varies widely by populations , geographical areas , and over different epidemiological periods [13] . Underreporting of dengue cases to national surveillance systems hinders accurate local , regional and global estimation of disease burden [14] . Necessary steps to better understand dengue transmission in at-risk populations include strengthening passive surveillance systems by incorporating active surveillance methods ( e . g . , house-to-house visits , school absenteeism or self-identification of fever episodes ) and improving the detection of inapparent infections to rectify the underreporting of unspecified febrile dengue infections . Vector control remains the core strategy for the prevention of dengue [15 , 16] . However , current approaches that only temporarily affect mosquito populations have not been proven to be sufficient to prevent dengue transmission [17] . Effective and sustainable dengue prevention and control requires innovation , by integrating and making optimal use of the most effective control tools available like integrated vector management , and also the introduction of new tools e . g . vaccines and other novel vector control technologies , especially in growing and complex urban environments [18 , 19] . Currently five vaccine candidates are in clinical stages of development [20] . Only one vaccine has completed two Phase III trials and it is being licensed for introduction in several countries [21–23] . This vaccine has an estimated efficacy of 64 . 7% and 56 . 5% in the Latin American and Southeast Asian trials , respectively and the efficacy was significantly higher in participants with pre-existing dengue neutralizing antibodies compared to those who were seronegative [21 , 22 , 24] . The availability of a licensed vaccine poses different challenges to current dengue control programs since it is not expected to vaccinate all the susceptibles and at-risk populations or even provide complete vaccine coverage in target groups . Vaccine introduction will therefore be a gradual process . In each of these populations several questions need to be addressed regarding the clinical spectrum and transmission risks in order to target vaccination to provide the most benefit [25] . Thus , measuring the burden of disease attributable to dengue infection is imperative for understanding the potential impact of dengue control interventions and feasibility for vaccine introduction and evaluation . There are limited number of established longitudinal cohort studies characterizing dengue infection in Latin America . The aim of this study was to estimate age-specific attack rates , the proportion of inapparent infections , incidence rate ratios and assessing the covariates associated with arboviral infections and symptomatic disease in a prospective dengue cohort established in Yucatan , Mexico .
The state of Yucatan is located in the southeast peninsula of Mexico , bordering the Gulf of Mexico and the Caribbean Sea . As described elsewhere , the cities of Merida , Progreso and Ticul were selected as three settings with different epidemiological dynamics ( low , medium , high dengue transmission ) ( Table 1 ) , based on their history of dengue outbreaks in the past and the co-circulation of more than two serotypes in recent years [26] . Incidence rates of suspected and confirmed cases from 1979 to 2013 were estimated for each city . As these three cities also have different dengue incidence rates , this allowed us to explore possible differences in dengue transmission scenarios [27] . Merida , the capital city , is the largest urban center in the region with 830 , 732 inhabitants ( 2016 ) . The weather is warm and humid , the mean annual temperature is 25 . 9°C ( 19 . 5 to 33 . 6 ) and annual precipitation is 1050 ( mm ) . The rainy season is from June to October . Progreso is the main seaport in the state , 32 km away from Merida , with 54 , 000 inhabitants . This town has similar weather conditions and is a weekend and holiday resort ( July-August ) for people living in Merida , as well as a national and international tourist resort . Ticul is a town located 82 km south of Merida with 34 , 000 inhabitants whose main economic activity is dedicated to shoe manufacturing [28] . The primary aim of this study was to characterize the local epidemiology and transmission dynamics of dengue in the state of Yucatan , using a school-based , prospective cohort in the different transmission district by city , three criteria were adopted: 1 ) Proportion of epidemiological weeks with reported symptomatic dengue cases compared to epidemiological weeks with no reported cases; 2 ) Duration of the dengue epidemic waves as a proxy of persistent dengue transmission; 3 ) Intensity of transmission measured as the incidence rate during the dengue season . The school-based study is defined by a random selection of five extensive geographic areas ( districts ) with different dengue transmission risks ( high , medium or low ) . The data obtained from the epidemiological surveillance system identified those areas where dengue has been historically higher and persistent and where the transmission risk is defined as high , medium and low . The sample includes low-risk areas in Merida and Progreso , medium-risk areas in Merida and Ticul , and a high-risk area in Merida . The sample size was estimated for the school-children from each transmission risk by city . The sample size was 150 school children from each transmission risk by city and then expanded to their families . Each area of transmission included several primary public schools from which the cohort of children from first to third grade was randomly selected . The randomization was done using stratified random sampling . First , we stratified the transmission risk of the neighborhoods on the three cities ( Merida , Progreso and Ticul ) . These included two low-risk areas ( one in the north of Merida and one in Progreso ) ; two medium risk areas ( one urban area in central Merida and one in Ticul ) ; and one high-risk urban area in the south of Merida . The risk was defined based on historical epidemiological features: 1 ) the historical dengue cases reported to the epidemiological surveillance system; 2 ) the percent of cases reported every year in each setting; and 3 ) the continuous transmission during 6 to 8 or more weeks every year . Second , after selecting some areas randomly based on the transmission risk , the field team asked for the list of all the schools located on the randomized transmission settings and a simple random sampling procedure was done to select the schools . The next step was done with the list of the students from 1st to 4th grade from each school that were also randomized . Children were enrolled at the beginning of the academic year from first through third grade ( 6 to 8 years old ) and were eligible to remain in the study until they graduated from sixth grade ( 12 years-old ) . The only exclusion criterion was intent to move outside of the study area during the twelve months following enrollment . The students entering elementary school and those in second and third grade were selected and included in the cohort study with written consent granted by their parents . Each group of enrolled children and their respective families were followed-up during their education track for the period of the study . Families were defined for this study as people living in the same household ( with minimum of five nights sleping in the household ) but not necessary that belong to the same family ( blood relation ) . The strategy of establishing and maintaining a cohort of individuals and their families in a long-term project requires ongoing effort . Success of such projects requires sharing interim results , advances in the project , and deep understanding of the community-level protective measures against dengue epidemics . Therefore , each site had a team of community specialists consisting of local physicians , nurses , laboratory technicians , microbiologists , and anthropologists who gathered information and organized activities directed to sensitize and educate cohort members and their families about dengue epidemiology and control . We obtained demographic information and blood samples from the entire study population at baseline and an annual blood sample . The study participants and their families were followed from January 2015 through October 2016 at 12-month intervals for serological evidence of dengue infection after the dengue season every year . Blood samples were taken during the surveillance period each year ( January-July ) right after the typical dengue transmission season . Participants were considered lost to follow-up if a full year had passed since their previous blood draw , despite repeated attempts to locate the participant , or if there was a verifiable reason for dropping them from the study ( e . g . , direct request from the participant , movement from the study area , or death ) . During the follow-up period the infection rates in different age groups were measured as well as the proportion of inapparent infections or underreporting of febrile cases during the dengue season . The prospective follow-up of the school cohort and their families also provided information for the estimation of age group hazards of infection for those represented in this sample . This study was conducted as a collaboration between the Ministry of Health of Yucatan , Mexico and the Center for Inference and Dynamics of Infectious Diseases in Seattle , WA , USA . This study was approved by the Institutional Review Boards at Fred Hutchinson Cancer Research Center , Seattle , WA , USA and the General Hospital Agustin O’Horan , Health Services of Yucatan , Mexico . Written consent was obtained from all adult participants ( >18 years old ) after providing them with a detailed explanation of the study and procedures . Parents/guardians of all child participants ( ≤ 18 years old ) were asked to provide written consent on their behalf . The analysis using de-identified data was approved at Fred Hutchinson Cancer Research Center . The age-specific baseline seroprevalence for dengue virus was estimated for the entire cohort . For the first year of follow-up , the follow-up time was estimated as the time between enrollment and the end of the reported study period ( August 2016 ) , or withdrawal from the study . For those who were lost to follow-up , person-years were calculated as the time between enrollment and the last contact with study personnel , plus one-half the time between the last contact and the date recorded as lost to follow-up . The analysis of dengue infections was limited to those participants who completed the year and contributed a blood sample at the beginning and the end of the year . In order to provide estimates of dengue infection incidence , since the exact timing of the dengue infection could not always be ascertained , persons who experienced a dengue infection in the first year of follow-up contributed person-time for that entire year . For the analysis of dengue infections , the age of the participant was defined as the age when their annual sample was collected . The crude incidence per 1 , 000 person-years was 1 , 000 times the number of dengue infections divided by the number of person-years in the dataset as published elsewhere [29 , 35 , 45] . The incidence rate ratio was also estimated for each arboviral infection comparing dengue non-naïve and dengue naïves [46–48] . The hazard ratios ( HRs ) and 95% confidence intervals ( 95% CIs ) for dengue and other arboviral infections were estimated using a Cox proportional hazards model and adjusting for potential confounders such as age , gender , city , and prior exposure to dengue [48 , 49] . All the statistical analyses were done in R , version 3 . 2 . 1 [50] .
A total of 767 families encompassing 3 , 400 participants were enrolled from January to June , 2015 across the three sites in Yucatan . The majority of the families and participants were from Merida ( 2 , 021 ( 59 . 4% ) , followed by Ticul ( 738 ( 21 . 7% ) and Progreso ( 641 ( 18 . 9% ) ( Fig 1 ) . Among the participants 1 , 869 ( 55 . 0% ) were females , 1 , 463 ( 43 . 0% ) were 14 years old or younger , and 2 , 970 ( 87 . 4% ) of them were born in the state of Yucatan ( Table 2 ) . These participants contributed with 3430 . 87 person-years for the first year of follow-up . The mean participation time is 1 . 01 years ( 368 . 31 days ) per participant ( range 0 . 04–1 . 94 ) . A total of 1 , 096 ( 32 . 2% ) participants did not complete the first year of follow-up . A total of 320 ( 29 . 3% ) of the participants were classified as lost to follow-up ( the team lost track of the participant and the family ) , 210 ( 19 . 2% ) moved out of the state of Yucatan and 564 ( 52 . 0% ) asked for voluntary withdrawal from the study ( Fig 1 ) . The baseline seroprevalence was estimated using samples from 2 , 853 participants who authorized a blood sample collection at enrollment . The overall baseline dengue seroprevalence in the cohort was 70 . 28% ( 95% CI 68 . 6%–72% ) indicating that most of the population had already been exposed to at least one dengue infection ( Fig 2 ) . The cohort from Ticul had the highest seroprevalence ( 81 . 1% ) , followed by Merida ( 70 . 2% ) and Progreso ( 57 . 9% ) . The differences in seroprevalence estimates by city were statistically significant ( p<0 . 001 ) . Dengue seroprevalence increased with age , and females in the cohort had significantly higher seroprevalence estimates compared with males ( p = 0 . 04 ) ( Table 3 ) . In the time period after enrollment and the collection of the baseline blood sample to the first annual follow-up of the cohort , 199 suspected arbovirus infection cases or undifferentiated febrile illnesses were identified in the study population of 3 , 400 . The most common clinical diagnosis was undifferentiated fever ( 105 cases ( 52 . 76% ) ) , followed by 76 ( 38 . 19% ) suspected dengue cases , 17 ( 8 . 54% ) suspected chikungunya cases and one suspected case of Zika . ( Table 4 ) . The dengue incidence rate for suspected cases was 21 . 86 per 1 , 000 person-years . From the 199 samples tested , 148 ( 74 . 4% ) were negative for dengue , chikungunya y Zika . All the consultations were in the outpatient clinic . The most common symptoms presented by the cohort population were: fever , headache , myalgia , arthralgia , rash and conjunctivitis . No significant differences in symptoms were found among all the arboviral clinical diagnoses ( p = 0 . 560 ) . No severe symptoms were identified in the study population . As the symptoms were non-specific across the different arboviral infections , we estimated the incidence of arbovirus suspected cases to be 58 . 02 per 1 , 000 person years . A total of 199 participants with suspected arbovirus symptomatic infections or undifferentiated febrile illnesses were identified in the 2935 participants of the cohort . These participants contributed with 3236 . 48 person- years in the first annual follow-up . Among the symptomatic arboviral infections 12 ( 6 . 0% ) were laboratory-confirmed as dengue-positive , 30 ( 15 . 1% ) as chikungunya-positive , 8 ( 4 . 0% ) as Zika-positive , and 148 ( 74 . 4% ) were classified as fever of unknown origin ( Table 4 ) . The overall incidence rate of arbovirus confirmed symptomatic infections was 14 . 57 per 1 , 000 person-years ( 95% CI: 10 . 82 , 19 . 21 ) . The incidence rate of confirmed symptomatic dengue was 3 . 45 cases per 1 , 000 person-years ( 95% CI: 1 . 87 , 5 . 86 ) . In the first year of the study , 12 symptomatic acute dengue cases were serotyped; DENV1 ( 52% ) was the most isolated serotype , followed by serotype DENV4 ( 33 . 3% ) and DENV2 ( 16 . 7% ) . DENV3 was not isolated during the analyzed period . No hospitalizations or deaths resulting from symptomatic dengue infection were reported during the first year of the cohort . The highest incidence of dengue was observed in the participants in the following groups: participants that were 15-19 years of age ( IR: 6 . 88 per 1 , 000 person-years ) , females ( IR: 6 . 3 per 1 , 000 person-years ) , and participants from Merida ( IR: 4 . 2 per 1 , 000 person-years ) ( Table 5 ) . The incidence rate of confirmed symptomatic chikungunya was 8 . 62 cases per 1 , 000 person-years ( 95% CI: 5 . 81 , 12 . 30 ) . The highest incidence of chikungunya was observed in the participants in the group 50 years old or older , females and in Ticul . ( Table 5 ) . The incidence rate of confirmed symptomatic Zika was 2 . 33 cases per 1 , 000 person-years ( 95% CI: 0 . 99 , 4 . 53 ) . The highest incidence rate estimated for Zika was also in Ticul ( 7 . 32 per 1 , 000 person-years ) . One case of co-infection of dengue and chikungunya was also identified . The majority of cases occurred from August to December 2015 which is historically considered the dengue season in Yucatan , Mexico . We explored the presence of clustering at the family level on this cohort but during this first year of follow-up in just one household were detected two dengue cases so the adjustment for clustering was not needed . For the analysis of dengue infections , we included only the participants who completed the first year of follow-up and contributed with a blood sample at the beginning of the study ( starting in January 2015 through out 2015 ) and at the end of the first year of follow-up depending on the day of enrollment ( up to October 2016 ) . Of these 1 , 890 participants , 1 , 037 ( 54 . 8% ) were from Merida , 379 ( 20 . 1% ) were from Progreso and 474 ( 25 . 1% ) were from Ticul . In total , these 1 , 890 participants contributed 2271 . 14 person-years and had 83 confirmed dengue infections , for an incidence rate of 36 . 55 infections per 1 , 000 person-years ( 95%CI 29 . 29 , 45 . 07 ) ( Table 6 ) . From the total confirmed dengue infections , 14 . 5% ( 12/83 ) were confirmed using RT-PCR for dengue and the rest 85 . 5% ( 71/86 ) were confirmed by serology according to the protocol . The overall ratio of dengue infections to symptomatic cases was 8 . 22 dengue infections per dengue symptomatic case . The highest incidence of dengue was observed in the participants in the group of 15-19 years of age followed by the ≤ 8 year olds . High incidence rates were also observed in participants from Merida , females , and in the population of naïves ( Table 6 ) . The lowest rates of symptomatic cases were in the oldest age group ( ≥ 50 years-old ) and the 9 to 14 years-old group with a rate of 6 . 66 cases per 100 infections ( Additional tables by age and city can be found on the supplemental material S1 Table ) . Among the 829 participants who entered the cohort as dengue-naïve , 555 dengue-naïve participants completed the first annual of follow-up and provided a blood sample . These participants contributed 560 . 5 person-years of time . Over the first year of follow-up , 74 dengue-naïve participants experienced a primary dengue infection . The overall percent of seroconverting naïve individuals was 13 . 3% . The incidence rate of primary dengue infections was 132 . 0 infections per 1 , 000 person-years ( 95% CI: 104 . 4 , 164 . 8 ) . There were twice as many seroconverting naïve individuals in Progreso ( 14 . 8% ) and Merida ( 14 . 2% ) , as compared to Ticul ( 7 . 7% ) ( Table 7 ) . For the IRR estimations , we assumed as exposed group the population that was naïve at baseline and the unexposed the non-naïves . The IRRs were estimated for confirmed dengue symptomatic cases , confirmed chikungunya symptomatic cases , confirmed Zika cases and overall dengue infections . The IRR for total dengue infections and symptomatic Zika cases were significant using the Logrank test ( Table 8 ) . More confirmed Zika cases were detected in dengue naïves and more confirmed chikungunya cases were detected in dengue non-naïves ( Table 8 ) . Confirmed Zika cases were 3 . 7 times more likely in dengue naïve compared to non-naïve people . Also , for dengue total infections were 22 . 2 times more likely in dengue naïves compared to non-naïves . The incidence rate ratios by city and age can be found in the supplemental materials . A Cox proportional hazard model was fitted for total dengue infections . The variables included in the model were: age , prior exposure to dengue , gender , city , household size of five or more people , and one or more infections in the same household . In the univariate analysis , age as a continuous variable was significant as a protective factor for dengue infections ( HR = 0 . 98 , 95%CI: 0 . 96 , 0 . 99 ) . There was no significant association between total dengue infections and overcrowding in the household but the remaining variables were significantly associated with having a dengue infection . The highest hazard ratios were estimated for baseline exposure to dengue ( HR = 20 . 5 , 95%CI: 10 . 30 , 40 . 91 ) and having more people infected with dengue in the household ( HR = 57 . 9 , 95%CI:37 . 21 , 90 . 08 ) . Those two variables were included in the final model as potential confounders . In the final model , having a dengue infection during the first year of follow-up was significantly associated with female gender , living in Ticul or Progreso , and being dengue naïve at baseline . Age was not significantly associated with the outcome , as it was confounded by prior immunity to dengue that increases with age . ( Table 9 ) .
To our knowledge this is the first prospective cohort study to describe the incidence rates of laboratory confirmed acute dengue and other arboviral infections in a population of healthy individuals in the state of Yucatan , Mexico . Our results confirm sustained dengue transmission and also the emergence of other arbovirus ( chikungunya virus and Zika virus ) since 2015 in the state of Yucatan . This cohort enrolled 767 families ( 3 , 400 participants ) from three cities of the state of Yucatan , Mexico . The 3 , 400 participants contributed 3 , 480 person-years during the first year of follow-up . The estimated dengue baseline seroprevalence of the cohort was 70 . 28% . The city with the higher seroprevalence was Ticul ( 81 . 07% ) , followed by Merida and Progreso and these seroprevalences increased with age as expected for dengue endemic transmission settings . It is important to highlight that the seroprevalence in the age group from 9–14 years old in the three study settings were ≤ 70% and these findings could be relevant for the Mexican government to guide policies for dengue vaccine introduction . Most of the dengue cohorts in Latin America and South East Asia are pediatric cohorts [29 , 35 , 37 , 38 , 45 , 51–54] . Our cohort and the cohort from Iquitos , Peru have similar design , both have participants from all age groups and active surveillance was done at schools [55 , 56] . Our cohort provides the opportunity to collect prospective data in all ages to understand better the full burden of dengue and other arboviruses that have emerged in the region . The symptoms from the arboviral infections detected during the first year of follow-up were very similar which is why the clinical diagnosis might not be accurate . It is necessary to confirm the suspected cases in order to know which viruses are circulating in these endemic areas . The incidence rate of arboviral suspected cases was 58 . 2 per 1 , 000 person years . The dengue incidence rate for suspected cases was 21 . 86 per 1 , 000 person-years ( 95%CI 17 . 32 , 27 . 25 ) and falls in the confidence interval of incidence rates estimated in the Nicaraguan dengue cohort [29 , 57 , 58] . The incidence rates of confirmed symptomatic Zika and confirmed chikungunya were 2 . 33 cases per 1 , 000 person-years and 8 . 74 cases per 1 , 000 person-years respectively . One case with co-infection of dengue and chikungunya was also detected as in some other endemic countries with co-circulation of multiple arbovirus [59] . The incidence rate of confirmed symptomatic dengue infections was 3 . 49 per 1 , 000 person-years . This proportion of confirmation and the incidence were lower than these estimates in other dengue cohorts [29 , 35 , 37 , 38 , 45 , 51–54 , 60] . One explanation is that during the first year of follow-up chikungunya virus was introduced in the state of Yucatan and these arboviruses that are transmitted by Aedes aegypti compete in the mosquito causing lower circulation of the other arbovirus in this case dengue . [61–64] From the original cohort a total of 1 , 096 ( 32 . 2% ) participants did not complete the activities of the first year of follow-up but 2 , 304 are still being followed from the original cohort . The mobility on the population in Yucatan was higher than we anticipated so assessing potential mobility will be important for the future of the cohort . The analysis of the dengue infections was done in 1 , 890 participants who had a baseline and completed the first year of follow-up . The incidence rate for dengue infections was 36 . 55 infections per 1 , 000 person-years . This incidence rate is lower compared with other cohorts around the world but it concurs with the low transmission of dengue during this first-year of follow-up and the emergence of chikungunya in the state of Yucatan [29 , 35 , 37 , 38 , 45 , 51–54 , 60] . The highest incidence of dengue was observed in the participants in the group from 15-19 years of age followed by the ≤ 8 year-olds . The group from 15-19 years of age is just 4 . 65% of the cohort and only 25 . 64% of them were naïve at baseline . More participants from this age group have been enrolled in the last months so it is expected to have better denominators for the next years of follow-up . Among 829 participants who were naïve at baseline , 555 ( 66 . 94% ) completed the first year of follow-up . In the naïves , there were 74 confirmed dengue infections for an overall seroconversion rate of 13 . 33% . The incidence rate on primary infections was 114 . 59 per 1 , 000 person-years . This rate is very similar to estimates from other dengue prospective cohorts in endemic areas [29 , 35] . Confirmed Zika cases were 3 . 7 times more likely in dengue naïve compared to non-naïve people . Also , dengue total infections were 22 . 2 times more likely in dengue naïves compared to non-naïves , this could be a reflection of inapparent infections that were missed in the population , and/or secondary infections that were not detected . The other incidence rate ratios estimated were not significant . This is a very interesting finding given the current interest in potential cross protection of dengue and Zika antibodies . It may be that recent , within two years , dengue infection may be protective against symptomatic Zika . Our results are consistent with recent publications available on this topic but do not prove the cross-protection and more research needs to be done [65 , 66] . The hazard ratios estimated for dengue infections during the first year of follow-up were significant for females , participants living in Ticul or Progreso , one or more infections confirmed in the household , and being dengue naïve at baseline . In the final model after controlling for baseline dengue status age was not significantly associated with the outcome . To our knowledge , this is the first dengue cohort study that uses survival analysis as a tool to better understand the transmission dynamics of dengue and other arbovirus . The limitations of this study include ascertainment of cases through enhanced passive surveillance . Thus , some dengue cases may not have been detected due to participants not seeking healthcare . Another limitation is that serum samples for cohort-wide serological testing are only available for participants once per year so it will be better to have more seroprevalence data points in time but logistically this is difficult to manage . We did not test the yearly samples for inapparent infections for CHIKV and ZIKV given that it was not planned on the original protocol and also due to the cross-reactivity of DENV and ZIKV with the currently available serological assays . Also we did not use paired samples in all the symptomatic arboviral cases; this decision was made with the advise of the arbovirus State Laboratory of Yucatan . This study relies on Inhibition ELISA to assess inapparent infections . The gold standard to assess DENV infection is the plaque reduction neutralization test ( PRNT ) but it is very labor intensive and expensive so testing all the participants was not feasible . Over the last five decades , dengue has emerged as a major health problem in the tropical regions worldwide including Latin America and the Caribbean [2 , 10 , 22 , 36] . More recently chikungunya and Zika virus emerged in the Americas causing significant epidemics in most of the countries infested with Aedes aegypti [67–70] . Mexico is considered one of the endemic dengue countries in the region and since 2015 with the emergence of chikungunya and Zika virus , the three arboviruses have been co-circulating in many areas of the country [71–73] . In summary , this study reported baseline seroprevalence , incidence of dengue infections , dengue cases and other arboviral cases in a community-based cohort from three settings in Yucatan , Mexico using analytic methods . This is the first report of the results from this prospective cohort that allowed to determine the incidence of arboviral infections and to estimate the true rate of disease , which is usually underestimated by passive surveillance . These data will be used to estimate disease burden . The incidence estimates will be useful for policy makers and to evaluate interventions like vector control strategies and vaccines . Future analysis of household transmission , cluster analysis and effectiveness of interventions are planned . | Dengue is a major public health problem worldwide . The burden of dengue in Latin America is been increasing in the last years and Mexico is one of the countries with the highest burden in this region . To better understand the transmission of dengue in Mexico we established a school-based prospective cohort study of dengue virus infection in children and their families in three cities in the state of Yucatan , Mexico . In this article we show that around 70% of the cohort population has prior immunity to dengue . Also that the rate of dengue cases varied among cities and we also confirm the circulation of chikungunya and Zika virus in the cohort participants during the first year of follow-up . We found evidence that having prior dengue immunity might protect again Zika symptomatic infections . The results of this study will be useful for the scientific community and policy makers from Mexico and other countries in Latin America to properly plan and evaluate control strategies and interventions like vector control and vaccines . | [
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"... | 2018 | Epidemiology of dengue and other arboviruses in a cohort of school children and their families in Yucatan, Mexico: Baseline and first year follow-up |
Human herpesviruses are important causes of potentially severe chronic infections for which T cells are believed to be necessary for control . In order to examine the role of virus-specific CD8 T cells against Varicella Zoster Virus ( VZV ) , we generated a comprehensive panel of potential epitopes predicted in silico and screened for T cell responses in healthy VZV seropositive donors . We identified a dominant HLA-A*0201-restricted epitope in the VZV ribonucleotide reductase subunit 2 and used a tetramer to analyze the phenotype and function of epitope-specific CD8 T cells . Interestingly , CD8 T cells responding to this VZV epitope also recognized homologous epitopes , not only in the other α-herpesviruses , HSV-1 and HSV-2 , but also the γ-herpesvirus , EBV . Responses against these epitopes did not depend on previous infection with the originating virus , thus indicating the cross-reactive nature of this T cell population . Between individuals , the cells demonstrated marked phenotypic heterogeneity . This was associated with differences in functional capacity related to increased inhibitory receptor expression ( including PD-1 ) along with decreased expression of co-stimulatory molecules that potentially reflected their stimulation history . Vaccination with the live attenuated Zostavax vaccine did not efficiently stimulate a proliferative response in this epitope-specific population . Thus , we identified a human CD8 T cell epitope that is conserved in four clinically important herpesviruses but that was poorly boosted by the current adult VZV vaccine . We discuss the concept of a “pan-herpesvirus” vaccine that this discovery raises and the hurdles that may need to be overcome in order to achieve this .
The family Herpesviridae encompasses several highly prevalent human pathogens that cause a spectrum of diseases ranging from mildly symptomatic to severe life-threatening illness [1] . All herpesvirus subfamilies ( α , β , and γ ) share one important characteristic: the ability to evade the immune response while persisting as latent infections in a state of minimal gene transcription . In many individuals , latent herpesviruses cause no further disease . However , reactivations do occur that lead to considerable morbidity and mortality as well as promoting onward transmission . These events are most frequent in individuals with immunosuppression or immunosenescence [2] . However , asymptomatic reactivation can also occur in immunocompetent individuals , leading to recurrent stimulation of host immunity by herpesvirus antigens [3] , [4] . T cells are essential both for recovery from primary herpesvirus infections and prevention of symptomatic reactivation [5] . VZV-specific T cells that secrete Th1 cytokines and exhibit cytolytic activity are detectable following chicken pox [6] . While virus exposure also induces antibodies , the absence of antibodies in children with agammaglobulinemia does not lead to more severe disease [7] . Conversely , the waning T cell immunity that occurs with older age is associated with greater frequency and severity of reactivations [8] . The only herpesvirus vaccines currently available are against VZV . This live attenuated vaccine prevents primary infection in children ( i . e . chicken pox ) and , when given at high dose , reduces the frequency and/or severity of shingles in elderly adults [9] . The vaccine induces both humoral and cell-mediated immunity [10]–[12] , but vaccine-induced immunity can fail and effectiveness in the elderly is relatively poor [13] . The factors underlying this are poorly understood . Rational design of herpesvirus vaccines that elicit optimal protective T cell responses therefore remains an important goal . However , in order to achieve this , further understanding of the role of human virus-specific T cells during herpesvirus infections is required . In this study , we aimed to comprehensively analyze the breadth of the CD8 T cell response to VZV in the context of the common HLA-A*0201 allele . The VZV genome is large , containing 69 unique open reading frames . This hampers the systematic identification of T cell epitopes and the generation of tools to study them . From VZV , only 7 class I-restricted epitopes from 3 proteins ( gI , gB and IE62 ) have been reported thus far [14] . To address this , we used in silico prediction across the entire VZV proteome for epitope mapping . Screening of these candidate peptides in VZV seropositive individuals identified an immunodominant HLA-A*0201-restricted epitope that was conserved with three other herpesviruses . In this study , we characterized the phenotype and function of CD8 T cells that recognized this conserved epitope and also examined the responsiveness of these CD8 T cells to VZV vaccination in humans .
We recruited 21 HLA-A*0201 positive volunteers with a history of primary VZV infection , detectable VZV IgG but no previous VZV vaccination or clinical evidence of recent reactivation ( Table 1 ) . The median age was 63 years ( range 25–77 years ) . Epitope predictions in the context of HLA-A*0201 were made using the Immune Epitope Database consensus prediction tool with the complete published VZV sequences ( Table S1 ) . The top 0 . 5% of 9- and 10-mers ( 367 peptides ) were synthesized and peptide pools screened by IFN-γ ELISpot using PBMCs from each subject . In 15/21 subjects , the same peptide pool induced positive responses ( Figure 1a ) . Deconvolution of this pool showed that two candidate peptides ( ILIEGIFFV and MILIEGIFFV ) from ribonucleotide reductase subunit 2 ( RNR2 ) of VZV strongly induced IFN-γ production ( Figure 1b ) . The predicted MHC-binding of the 9-mer ( henceforth called ILI ) had 11-fold higher affinity than the 10-mer ( Table 2 ) , so this was used to generate the A2-ILI tetramer used to label epitope-specific cells ( Figure 1c ) . Tetramer+ cells were detected in 12/21 subjects with frequencies ranging from 0 . 01% to 1 . 8% of CD8 T cells ( Figure 1d ) . ILI was thus identified as an immunodominant HLA-A*0201-restricted class I epitope . To determine the phenotype of these ILI-specific CD8 T cells , we co-stained for memory subset markers; co-stimulatory molecules; and effector molecules . The majority of A2-ILI+ cells were CD45RA-/CCR7- indicative of an effector memory T cell phenotype ( Figure 2a & 2b ) . However , between individuals , these cells displayed marked heterogeneity , which allowed further categorization into one of three phenotypic groups . Phenotype 1 ( 6/12 subjects ) was the least effector-like , expressing high levels of the co-stimulatory receptors CD27 and CD28 with no expression of the cytotoxic molecules perforin or granzyme B; most A2-ILI+ cells of phenotype 2 ( 5/12 subjects ) still expressed CD27 and CD28 and were still negative for perforin , but now expressed granzyme B; finally , phenotype 3 ( 1/12 subject ) described the most effector-like cells with no CD27 and CD28 expression but high perforin and granzyme B ( Figure 2a & 2b ) . We also investigated the expression of granzyme K , a serine protease that marks less differentiated CD8 T cells [15] . This also differed between groups and was inversely associated with granzyme B expression ( in keeping with previous reports ) . In a subset of donors , we went on to examine the differentiation markers KLRG-1 and CD127 ( Figure S1a ) . In all subjects tested , at least half the ILI-specific cells expressed KLRG-1 ( a marker commonly expressed on terminally differentiated short-lived effectors ) , with a trend towards progressively higher expression in phenotypes 2 and 3 . A variable proportion expressed CD127 ( predominantly expressed on long-lived memory cells ) but there was a trend towards more CD127+ cells in phenotype 1 and fewer in phenotype 3 . These data were therefore consistent with those used to classify phenotypes 1 , 2 and 3 , suggesting that ILI-specific cells of phenotypes 2 and 3 were more likely to be terminally differentiated . Primary VZV infection results in a multi-system disease that includes skin and neurotropic phases and antigen-specific cells may therefore need to localise to a variety of tissues . In most individuals , a major proportion of ILI-specific cells expressed the integrin CD62L , which allows homing to lymphoid organs ( Figure S1b ) . In addition , a variable proportion expressed CCR5 , indicating potential for homing to inflamed tissues . With neither marker was there a significant difference in frequency of expression between the 3 phenotypes . A2-ILI+ cells displayed no expression of cutaneous lymphocyte antigen ( CLA ) but a variable proportion did express the integrin α4β7 . Again , there was no correlation with advancing phenotypic group . One possible explanation for the heterogeneity of phenotype might have been recent or on-going activation , since the combination of markers characteristic of phenotype 3 would also be expected to occur in short-lived effector T cells . We therefore also analysed the expression of Ki-67 to determine whether any of these cells had undergone recent proliferation ( Figure 2a & 2b ) . In a few subjects a minority of A2-ILI+ cells did express Ki-67 . However , these never made up more than 5% of the population and there was no evidence that ILI-specific cells of phenotype 2 or 3 were more likely to have had recent proliferative activity . This was supported by analysis of the activation markers CD38 and HLA-DR , neither of which was up-regulated on ILI-specific CD8 T cells ( Figure S1c ) . In addition , the combinations of markers that segregated the phenotypic groupings did not change over time . Subjects were sampled at intervals between 1 and 6 months from baseline and the frequencies of ILI-specific cells expressing these combinations of markers remained stable ( Figure 2c ) . These data therefore suggested that the ILI-specific memory T cell populations had been observed in a quiescent state and that , while they might express one of several stable phenotypes in any single subject , they were heterogeneous between individuals . In view of their phenotypic differences , we proceeded to examine the functional capacity of ILI-specific CD8 T cells by measuring their ability to produce cytokines and undergo proliferation ( Figure 3 ) . Comparing the proportions of A2-ILI+ CD8 T cells capable of producing IFN-γ and IL-2 , ILI-specific cells with phenotype 1 had the greatest cytokine producing capacity with a mean of 76% ( range 37–100% ) expressing IFN-γ ( Figure 3b ) . As the phenotype changed from 1 to 2 and 3 , the capacity of ILI-specific cells to produce IFN-γ fell . Furthermore , phenotype 1 ILI-specific cells were also the most polyfunctional , with a mean of 29% ( range 22–51% ) also staining for IL-2 ( Figure 3c ) . Again , as the phenotype advanced , fewer ILI-specific cells produced this cytokine . In subjects in whom ILI-specific cells were at sufficiently high frequency for the assay , we then analyzed their in vitro proliferative capacity . This indicated that ILI-specific CD8 T cells from the individual displaying phenotype 3 were markedly impaired in their proliferation compared with those with phenotype 1 ( Figure 3d ) . Thus the phenotypic and functional patterns displayed by the ILI-specific populations implied that they had been driven , to varying extents between individuals , towards more terminal differentiation with characteristics reminiscent of functional exhaustion . To investigate the potential mechanism underlying this , we examined the association between differentiation phenotype and the expression of the inhibitory receptors PD-1 and 2B4 , which are associated with exhaustion and up-regulated on virus-specific CD8 T cells during chronic antigen stimulation [16] . On ILI-specific cells , as the differentiation phenotype progressed , both PD-1 and 2B4 expression increased ( Figure 4a ) . This was associated with a trend towards decreased capacity to produce cytokines such that as the frequency of cells expressing PD-1 and 2B4 increased , the frequency of IFN-γ producing cells fell ( Figure 4b ) . In chronic viral infections such as HIV , antigen-specific CD8 T cells are abundant , driven by continuous antigenic stimulation via the T cell receptor [17] . However , this increase in the frequency is balanced by increasing expression of inhibitory markers including PD-1 , leading to functional exhaustion . Thus , although the frequency of memory T cells is increased , their functionality is restrained . Although herpesviruses do not continually produce antigenic proteins during latent infection , a strong correlation between the size of the population and the frequency of ILI-specific CD8 T cells that co-expressed both inhibitory receptors was seen ( Figure 4c ) . These data imply that recurrent antigen exposure , for example via reactivation , may have driven the proliferation of these cells , thus increasing their frequency but also inducing the expression of inhibitory markers , which in turn affects their functional capacity . RNR is one of a number of widely conserved proteins [18] , [19] . We therefore hypothesized that the ILI epitope might be well conserved between the human herpesviruses . Indeed , we found that not only was the epitope present in all recorded VZV sequences but that there were also conserved homologues in the α-herpesviruses HSV-1 ( ILIEGIFFA ) and HSV-2 ( ILIEGVFFA ) , and the γ-herpesvirus EBV ( LLIEGIFFI ) ( Table 2 ) . In contrast , poor homology was seen in the RNR2 of the γ-herpesvirus HHV-8 , while the RNR2 gene is absent in the β-herpesviruses CMV , HHV-6 and HHV-7 . Furthermore , the homologous epitope from the human RNR has little sequence identity with those of the herpesviruses and therefore unlikely to be responsible for any auto-reactive responses . We tested the recognition of homologous peptides from VZV , HSV-1 , HSV-2 and EBV by intracellular cytokine staining ( Figure 5a & 5b ) . In all 11 donors tested , each peptide was capable of stimulating cytokine production . This occurred even when those individuals had no serological evidence of previous infection with the originating virus , with the response to the HSV-1 epitope equivalent to that against the one from VZV even in subjects who were HSV-1 seronegative ( Figure 5b & Table 3 ) . Conversely , the reduced response to the HSV-2 epitope occurred even in seropositive individuals . All subjects had been recruited on the basis of seropositivity to VZV and all but three volunteers also had evidence of previous EBV infection ( Table 3 ) . In contrast , only 11/21 subjects were positive for HSV-1 IgG and only 3 for HSV-2 . Individuals with serological evidence of 3 or more herpesvirus infections were more likely to have detectable A2-ILI+ responses ( 9/12 subjects ) while those with no detectable ILI-specific cells were more likely to have only EBV and/or VZV ( 6/9 subjects ) . These data therefore suggest that co-infection with more than two α- or γ-herpesviruses may increase the likelihood of generating a cross-reactive ILI-specific response . In silico prediction suggested that residues at the anchor motifs of the VZV peptide ( position 2 and the C-terminus ) conferred optimal binding , while in vitro binding measurements showed that all four epitopes displayed extremely high affinities of <0 . 2 nM ( Table 2 ) . However , in vitro stimulation of CD8 T cells showed that the HSV-2 epitope was much less effective at stimulating cytokine production than those from VZV , HSV-1 and EBV ( Figure 5a , 5b & 5c ) . Despite the calculated and measured binding affinities , peptide titrations showed that the epitopes from VZV , HSV-1 and EBV induced similar responses in any given individual while the peptide from HSV-2 only stimulated cytokines at its highest concentrations ( Figure 5c ) . We therefore inferred that isoleucine at position 6 , absent in the HSV-2 epitope , must be important for efficient TCR recognition . These data support the hypothesis that herpesviruses are capable of inducing and boosting this epitope-specific response in a cross-reactive manner . Reactivations of one or several of these viruses may cause expansion of this population , increasing its size but also driving the cells towards an increasingly differentiated phenotype . In order to examine the ability of the current VZV vaccine to boost ILI-specific responses , we immunized the study cohort with the live attenuated Zostavax vaccine and tracked the A2-ILI+ response . Following vaccination , the majority of subjects had no detectable change in the frequency of ILI-specific cells irrespective of their pre-vaccination frequency ( Figure 6a ) . A greater than 2-fold increase in epitope-specific cells was seen in only one vaccinee ( subject 105 , phenotype 2 ) . This individual had one of the lower starting frequencies at 0 . 05% and incremented to 0 . 17% at day 14 post-vaccination ( Figure 6a & 6b ) . The increased ILI+ CD8 T cell frequency was associated with up-regulation of Ki-67 in 66% of epitope-specific cells , indicative of proliferation ( Figure 6c & 6d ) . This occurred between 7 and 14 days post-vaccination , with Ki-67 completely down-regulated by day 28 . In one additional subject ( subject 126 ) , there was evidence of minimal proliferation peaking at day 14 but no overall increase in the frequency of ILI-specific cells ( Figure 6c ) . However , even in the best responder , the overall increase in the frequency of ILI-specific cells was modest despite the higher frequencies being maintained to day 28 . Therefore live attenuated VZV vaccine only induced proliferation of ILI-specific cells in a single subject and even in the responding individual , the response was quantitatively poor .
Several T cell epitopes have previously been described that are conserved between HSV-1 and HSV-2 [20] , including the epitopes described here [21] . However , it is interesting to find that these conserved epitopes exist more widely in viruses as divergent as the α- and γ-herpesviruses . Here , we have shown that this epitope is , in fact , broadly conserved between 4 different clinically important herpesvirus species despite their sequence divergence . Furthermore , all epitopes were capable of stimulating CD8 T cells even in individuals with no evidence of previous exposure to that virus . Earlier studies have indeed noted that HSV-specific T cells are detectable in a proportion of individuals seronegative for HSV . It was then proposed that these T cells might be induced by subclinical infection or exposure without infection , but our findings suggest that cross-reactivity of T cells may be an alternative explanation [22] . The frequency of ILI-specific CD8 T cells varied widely between individuals . We hypothesize that the number of herpesvirus infections and frequency of reactivations is responsible for these differences . Since herpesviruses are highly prevalent , multiple viruses invariably co-exist within a host and new herpesvirus infections may contribute to further stimulation of cross-reactive T cell populations . Furthermore , although herpesviruses downregulate their transcriptional machinery during latency , chronic expression of some viral genes still occurs [23] , and subclinical reactivation has also been widely described . During stress , VZV can be detected in blood or saliva by PCR while HSV-2 often sheds in the absence of genital ulceration [4] , [24] . Chronic or periodic antigen exposure may therefore boost T cell numbers over time . However , in many experimental systems , increasing the number of antigen-specific T cells can also lead to immunopathology and there is increasing evidence in natural infections that this can be controlled by a number of feedback mechanisms . Under conditions of continuous antigen exposure in chronic infections such as HIV , antigen-specific T cells may be driven to proliferate to high frequencies and epitope-specific CD8 T cells identified by tetramer labelling are abundant [17] . However , constitutive expression of inhibitory receptors including PD-1 and 2B4 is also induced by chronic antigen stimulation , leading to reduction in further proliferative capacity and cytokine production [25]–[27] . In tandem with a decrease in co-stimulatory signalling via the down-regulation of CD27 and CD28 , immunopathology is restrained despite the higher frequency of potential effector cells . Although continuous production of antigen does not occur in the same way during herpesvirus infections , recurrent antigen stimulation during reactivations may lead to a similar process . In this context , our data suggest that the differentiation phenotype may act as a biomarker for frequency of reactivation . The phenotypic groups defined by stable expression of differentiation markers in the absence of recent proliferation ( as evidenced by Ki-67 expression ) may therefore be indicative of antigen exposure history . Furthermore , exhaustion may be one potential mechanism for the impaired T cell function that permits symptomatic reactivations in the elderly . If exhaustion could be reversed , there might be the possibility of enhancing antigen-specific immune responses in this population . Although T cell immunity is believed to be essential for the control of herpesvirus infections , little is known about the role of T cells in the efficacy of the only currently available herpesvirus vaccines , Zostavax ( which protects against shingles ) and Varivax ( which prevents chicken pox ) . Both are based on the live attenuated vOka strain of VZV , which has been passaged over 30 times in both human and animal cells . Despite the fact that Zostavax contains 14 times more virus than Varivax ( which is administered to children ) , our data indicate that it does not efficiently stimulate a secondary ILI-specific response in seropositive adults . The explanation for this is likely to be multi-factorial . The numerous mutations that the vOka strain has acquired are likely to have contributed to poor replicative capacity and altered immunogenicity [28] . However , our data also suggest that VZV-specific CD8 T cells in many adults are intrinsically suboptimal , with a balance of co-stimulatory and inhibitory receptors that favors decreased responsiveness to antigen stimulation and impaired functionality . This may partially explain the incomplete protection provided against shingles and why VZV vaccine confers no cross-protection against other herpesviruses despite the presence of this cross-reactive CD8 T cell population in some individuals . Furthermore , VZV , HSV-1 and EBV have all been shown to evade host immunity by interfering with antigen presentation [29]–[31] . Therefore neither existing vaccines nor natural infection are therefore likely to induce cross-reactive T cell responses of sufficient magnitude to provide clinically relevant cross-protection . In addition , it is possible that conserved epitopes such as the ILI homolog are not equally processed and presented in all herpesvirus infections , even when the originating protein ( e . g . RNR2 ) is expressed . The presentation of ILI homologs by HSV-1/2 and EBV in the absence of previous VZV infection was beyond the scope of our study and although CD8+ T cells specific for ILI homologs from HSV-1 and HSV-2 have been described , the VZV serostatus of donors in those studies was not assessed [21] . It therefore remains to be definitively shown whether the cross-reactive CD8+ T cell response demonstrated in vitro is effective in vivo . However , in view of the evolutionary relatedness of the herpesvirus subfamilies , we hypothesize that there are still more conserved epitopes to be discovered . Vaccines that induce cross-reactive CD8 T cells might provide protection against clinical disease caused by multiple strains or even species of virus pathogens . The existence of such epitopes could open the way to the development of novel “pan-herpesvirus” vaccines if they can be made to induce responses of sufficient magnitude and functionality . Using the tools we have developed , further identification of the proteins from which similar conserved epitopes are derived may lead us to such a goal . However , since even natural infection by virulent herpesviruses cannot adequately induce cross-protectivity , development of an effective pan-herpesvirus vaccine will require not only the identification of further cross-reactive epitopes across the major HLA supertypes but also completely new methods to specifically enhance the stimulation of cross-reactive CD8 T cells . In particular , we anticipate that novel adjuncts such as inhibitory receptor blockade will be required to tip the balance of signals that coordinate these responses in the direction of virus-specific T cell activation in order to overcome their relatively functionally impaired state . We anticipate that these strategies as well as advances in the rational design of improved immunogens will ultimately be necessary to achieve a vaccine that effectively protects against the wide array of diseases caused by herpesvirus infection .
All studies were approved by the Emory University Institutional Review Board ( IRB #00050285 ) . Study subjects provided written informed consent prior to participation . Clinical information is detailed in Table 1 . Twenty-one healthy HLA-A*0201 +ve adults were recruited . Blood was obtained at baseline and multiple time points post-vaccination with the live attenuated Zostavax vaccine ( Merck ) . Study subjects had a history of varicella zoster infection and serologic status against VZV was tested using the VZV IgG ELISAII ( Wampole Laboratories , NJ , USA ) . HLA class I loci were genotyped using the sequence-base typing ( SBT ) method as recommended by the 13th International Histocompatibility Workshop ( Tilanus et al . 2002 ) . The capacity of all VZV vOka ( GI: 26665420 , Acc . No . AB097932 ) derived 9- and 10-mer peptides to bind HLA A*02:01 was predicted using the command-line version of the consensus prediction tool available on the Immune Epitope Database ( IEDB ) web site ( http://tools . immuneepitope . org/main/html/tcell_tools . html ) . Peptides were selected if they scored in the top 0 . 5% of predictions for each length . Additional peptides from non-vOka VZV strains ( Table S1 ) were also included if they similarly scored in the top 0 . 5% of predictions . To assign gene names and locus tags to each peptide , genome sequences were run through an ORF finding algorithm ( http://mobyle . pasteur . fr/cgi-bin/portal . py ? form=getorf ) , and the corresponding data copied from the information available for orthologous Dumas proteins . MHC-epitope binding predictions were made with the Stabilized Matrix Method using the tool on the IEDB website . All peptides used in this study were synthesized by Mimotopes ( Victoria , Australia ) as crude material , and resuspended at 20 mg/ml in 100% DMSO ( v/v ) . Quantitative assays to measure the binding of peptides to HLA A*02:01 class I molecules are based on the inhibition of binding of a radiolabeled standard peptide ( HBV core 18–27 analogue , FLPSDYFPSV ) . MHC molecules were purified by affinity chromatography from the EBV transformed homozygous cell line JY , and assays performed , as described previously . Peptides were tested at six different concentrations covering a 100 , 000-fold dose range in three or more independent assays , and the concentration of peptide yielding 50% inhibition of the binding of the radiolabeled probe peptide ( IC50 ) was calculated . Under the conditions used , where [radiolabeled probe] < [MHC] and IC50 ≥ [MHC] , the measured IC50 values are reasonable approximations of the true Kd values . PBMCs were isolated using BD Vacutainer CPT tubes , washed , and resuspended in RPMI 1640 with 10% FCS ( v/v ) for immediate use or frozen in fetal calf serum with 10% dimethyl sulfoxide ( v/v ) for subsequent analysis . Plasma samples were saved at −80°C for subsequent analysis . Gamma interferon ( IFN-γ ) enzyme-linked immunospot ( ELISpot ) assays were performed using 2×105 PBMC stimulated with peptide pools ( 10 µg/ml/peptide ) . Peptide pools yielding positive responses were deconvoluted , by testing individual peptides at 10 µg/ml . After 20 h of incubation at 37°C , plates were developed , and responses were calculated . Positive wells contained ≥20 spot-forming units ( SFU ) /106 cells and a P value of ≤0 . 05 using a Student's t test in at least 2 experiments . MHC class I tetramer was prepared in-house . Surface staining of T cells was achieved by addition of tetramer to whole blood , incubation for 10 minutes at room temperature , followed by addition of antibody co-stains for 20 minutes . Whole blood was preferred to thawed PBMCs for tetramer labelling due to greater consistency and signal intensity . Following lysis of erythrocytes using BD FACS Lysing solution ( BD Biosciences ) , cells were either fixed using 2% formaldehyde ( v/v ) or permeabilized using the BD Cytofix/Cytoperm kit for intra-cellular staining . The following antibodies were used for surface and intra-cellular staining: CD3-PerCP , CD8-Horizon V500 , CD8-APCH7 , Ki-67-FITC , Bcl-2-PE , HLA-DR-Horizon V450 , HLA-DR-PerCP , Perforin-FITC , Granzyme B-Horizon V450 , CCR7-PE , CD27-Horizon V450 , CD27-FITC , CD28-PECy7 , CD28-PE ( all BD Biosciences ) and CD38-PECy7 ( eBioscience ) , Granzyme B-PE ( Caltag ) , Granzyme K-PE ( Santa Cruz ) , CD45RA-FITC ( Beckman Coulter ) , PD-1-PE and 2B4-PerCPCy5 . 5 ( Biolegend ) . Intra-cellular cytokine staining with IFN-γ-FITC , TNF-α-APC , and IL-2-PerCpCy5 . 5 ( all BD Biosciences ) was undertaken after in vitro stimulation of PBMCs using peptide for 6 hours . Flow cytometry analysis was performed BD LSRII and BD FACSCanto flow cytometers . Flow cytometry data were analyzed using FlowJo software . PBMC were labeled for 7 minutes with 2 . 5 µM carboxyfluorescein succinimidyl ester ( CFSE , Molecular Probes ) in PBS at room temperature . Cold FCS was then added and cells were washed extensively with RPMI 1640 plus 10% FCS . CFSE-labeled cells were incubated with or without the ILIEGIFFV peptide ( 10 µg/ml ) for 6 days . Responding CD8 T cells were subsequently identified by tetramer staining . | Human herpesviruses can cause a wide range of serious infections . They are extremely common and individuals remain latently infected lifelong , with reactivations often causing recurrent or severe disease . T-cells are important in controlling herpesvirus infections and preventing their reactivation , so vaccines that induce T-cells are likely to improve control . Here , we examined human T-cells against VZV that might allow focused vaccine development . We identified a dominant target against which the majority of subjects had mounted a CD8 T-cell response . We found that very similar targets also exist in three other important herpesviruses , HSV-1 , HSV-2 and EBV . We showed that CD8 T-cells recognizing the VZV target could also recognize the others and we hypothesized that recurrent encounter with these viruses could boost this common response . In some individuals , immunization with a VZV vaccine did cause activation of these cells , but in most it did not . This reflects the variable efficacy of the currently available VZV vaccine . Our findings suggest that T-cell targets may be shared between herpesvirus species and may therefore contribute to a novel “pan-herpesvirus” vaccine . However , current VZV vaccines cannot reliably stimulate these T-cells and new strategies will be necessary to achieve this goal . | [
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"cel... | 2014 | Broadly Reactive Human CD8 T Cells that Recognize an Epitope Conserved between VZV, HSV and EBV |
The pathogen Campylobacter jejuni is the principal cause of bacterial food-borne infections . The mechanism ( s ) that contribute to bacterial survival and disease are still poorly understood . In other bacterial species , type VI secretion systems ( T6SS ) are increasingly recognized to contribute to bacterial pathogenesis by toxic effects on host cells or competing bacterial species . Here we report the presence of a functional Type VI secretion system in C . jejuni . Proteome and genetic analyses revealed that C . jejuni strain 108 contains a 17-kb T6SS gene cluster consisting of 13 T6SS-conserved genes , including the T6SS hallmark genes hcp and vgrG . The cluster lacks an ortholog of the ClpV ATPase considered important for T6SS function . The sequence and organization of the C . jejuni T6SS genes resemble those of the T6SS located on the HHGI1 pathogenicity island of Helicobacter hepaticus . The C . jejuni T6SS is integrated into the earlier acquired Campylobacter integrated element CJIE3 and is present in about 10% of C . jejuni isolates including several isolates derived from patients with the rare clinical feature of C . jejuni bacteremia . Targeted mutagenesis of C . jejuni T6SS genes revealed T6SS-dependent secretion of the Hcp needle protein into the culture supernatant . Infection assays provided evidence that the C . jejuni T6SS confers contact-dependent cytotoxicity towards red blood cells but not macrophages . This trait was observed only in a capsule-deficient bacterial phenotype . The unique C . jejuni T6SS phenotype of capsule-sensitive contact-mediated hemolysis represents a novel evolutionary pathway of T6SS in bacteria and expands the repertoire of virulence properties associated with T6SS .
Gram-negative bacteria have evolved at least six types of protein secretion systems ( type I–VI ) to export proteins to the periplasmic space or the environment [1] . Several secretion systems are composed of needle-like structures that span the bacterial cell wall and protrude from the cell surface . These nanomachines include the classical type III and type IV secretion apparatus involved the injection of bacterial proteins into eukaryotic cells . One more recently discovered bacterial needle structure is the type VI secretion system ( T6SS ) as originally described for Vibrio cholerae and Pseudomonas aeruginosa [2] , [3] . Today whole genome analyses have predicted T6SS gene clusters to be present in more than 100 Gram-negative bacterial species . These gene clusters often have of a variable composition but typically contain at least 13 core genes that encode the basic elements of the injection apparatus [4]–[6] . Structurally the T6SS consists of a membrane-associated assembly platform and a needle structure that transports effector molecules into neighboring bacteria or eukaryotic cells . A number of the T6SS core proteins show similarity to elements of tailed bacteriophages . Examples are the baseplate gp-25-like protein VCA109 , the tail sheath-like proteins TssB and TssC ( VipA/VipB ) , the tail subunit-like hemolysin co-regulated protein ( Hcp ) that polymerizes into the T6SS needle structure , and the valine-glycine repeat protein ( VgrG ) that forms the spike of the nanotube [4]–[6] . The structural similarity with bacteriophage proteins has led to the hypothesis that T6SS resemble an inverted bacteriophage tail structure that is exposed at the surface of the bacterial cell wall [7] , [8] . Recently , contraction and extension of the VipA/B tubular sheath of the T6SS of V . cholerae have been visualized in vivo , supporting the model that the T6SS sheath is a dynamic contractile structure that projects the T6SS spike into the target cell analogous to bacteriophage entry [9] , [10] . Disassembly of the contracted sheath requires the T6SS ClpV ATPase [9] , [11] , [12] . Another group of T6SS building blocks ( TssM-L ) seems related to proteins of the type IV secretion system ( i . e . IcmF and IcmH/DotU ) [13] , [14] . These proteins may be involved in the recruitment of Hcp to the T6SS inner membrane assembly platform [15] . The hallmark of a functional T6SS is the presence of Hcp and VgrG in the culture supernatant [3] , [16]–[18] . Both proteins may exert effector functions on eukaryotic cells [16] , [19]–[21] . For the VgrG protein this function is often associated with the presence of an additional C-terminal effector module . Once in contact with eukaryotic cells , the extended C-terminal domain induces cross-linking or ADP-ribosylation of actin in eukaryotic cells , promoting intestinal inflammation and host cell toxicity [16] , [19] , [21] . Other identified T6SS effector molecules include the VasX protein secreted by V . cholerae that binds membrane lipids [22] and toxic proteins that target prokaryotes to provide a competitive advantage against other microorganisms occupying the same niche . Examples are the Tse2 toxin and the Tse1 and Tse3 proteins with peptidoglycan hydrolyzing activity in Pseudomonas aeruginosa [23]–[25] . These toxins may be representatives of a widespread T6SS effector superfamily with antibacterial properties [26] . Campylobacter jejuni is one of the principal bacterial food-borne pathogens causing millions of cases of gastroenteritis worldwide . Yet , the pathogenesis of C . jejuni infections is still poorly understood and a limited number of potential virulence determinants have been identified [27] . In the present study we report the identification of a functional T6SS in C . jejuni . The T6SS gene cluster is part of an integration element present in the genomes of a subset of C . jejuni strains . The system shows several unique traits compared to other bacterial T6SS including contact-dependent lysis of red blood cells and capsule expression-sensitive T6SS function .
Proteome analysis of whole bacterial lysates of C . jejuni strain 108 using two-dimensional gel electrophoresis and liquid chromatography mass-spectrometry ( LC-MS ) revealed a ∼20 kDa protein that contained 4 peptide sequences most similar to a Campyobacter coli protein annotated in the NCBI database either as hypothetical protein or as putative hemolysin co-regulated protein ( Hcp ) ( Fig . 1 ) . We amplified the putative C . jejuni hcp gene from strain 108 by PCR with primers designed on the basis of the C . coli hcp sequence . Cloning and sequence analysis of the PCR product indicated that the C . jejuni gene encodes one open reading frame of 171 amino acids and contains the DUF796 domain which is conserved among Hcp proteins . The C . jejuni Hcp shows 76% similarity to the V . cholerae Hcp protein [28] and 69% similarity to the well characterized Hcp protein of Pseudomonas aeruginosa [2] , [29] . In search for evidence of the presence of a complete T6SS gene cluster in C . jejuni strain 108 , we determined the flanking regions of the hcp gene by primer walking . This strategy yielded a putative C . jejuni T6SS gene cluster of ∼17 kilobases consisting of 13 open reading frames with tight intergenic spacing ( less than 30 bp ) ( Fig . 2A ) . The genes seemed organized in several groups based on gene orientation and were designated as C . jejuni tssA-M following the proposed nomenclature for T6SS components [5] , [30] . The organization of the T6SS genes of C . jejuni strain 108 resembled but was not identical to the organization of the cluster in C . coli and Helicobacter hepaticus ( Fig . 2B ) . Closer inspection revealed that in the first group of genes the C . jejuni hcp gene ( tssD ) of strain 108 is located in reverse orientation between the tssJ-M genes ( Fig . 2A ) . The products of these genes show 46–55% similarity with TssJ-TssM proteins which in several other species form essential components of the membrane platform of the T6SS secretion apparatus [13] , [31] . C . jejuni TssJ ( 17 kDa ) has a putative lipoprotein signal peptidase cleavage site ( LFFCA/CSSVV ) and a serine residue at position +2 which may sort the protein to the outer membrane [13] , [32] . C . jejuni TssK ( 53 kDa ) lacks an apparent signal sequence and resembles a conserved T6SS protein with unknown function . The putative C . jejuni TssL ( 30 kDa ) and TssM ( 137 kDa ) proteins are predicted to have transmembrane domains and coiled-coil structures . Both proteins share characteristics with the IcmH/DotU and IcmF proteins originally identified as non-essential components of a type IV secretion system ( T4SS ) that facilitate the translocation of bacterial effector proteins into eukaryotic target cells [33] , [34] . These proteins are now considered conserved T6SS base plate components [13] , [14] , [35] . C . jejuni TssM contains a Walker A motif ( GXXGXGKT/S ) in its cytoplasmic N-terminal domain implicated in the ATP hydrolysis energizing the recruitment of Hcp to the TssL-TssM membrane complex [15] . The larger periplasmic part harbors an icmF domain that , in analogy to IcmH and IcmF , may interact with TssL and stabilize the secretion complex [13] . A second group of predicted T6SS components in C . jejuni strain 108 comprises the proteins TssB , TssC , TssE , TssF and TssG ( Fig . 2B ) . TssB ( 18 kDa ) and TssC ( 55 kDa ) are orthologs of the T6SS proteins VipA and VipB that constitute the tubular sheath [10] , [11] . C . jejuni TssE ( 15 kDa ) has remote homology to the bacteriophage T4 baseplate protein gp25 and to the V . cholerae ortholog VCA0109 that is essential for Hcp secretion [11] . C . jejuni proteins TssF ( 66 kDa ) and TssG ( 38 kDa ) , both predicted to be inner membrane proteins , are homologous to conserved T6SS components of unknown function , although the TssF ortholog in Rhizobium leguminosarum ( ImpG ) is involved in plant root infection [36] . The C . jejuni TssA ( 50 kDa ) and TagH ( 35 kDa ) proteins resemble T6SS hypothetical proteins . C . jejuni TagH appears to have a forkhead-associated domain ( FHA ) that may confer phosphoprotein-specific protein-protein interactions and thus may have a regulatory function . The C . jejuni T6SS gene cluster lacks a ClpV-ATPase ortholog implicated in the depolymerization and recycling of the T6SS tubular sheath proteins that may wrap the Hcp inner tube structure [9]–[12] . The protein encoded by the tssI gene located at the C-terminal end of the C . jejuni T6SS gene cluster shows similarity with the Rearrangement hot spot ( Rhs ) element of the VgrG protein family and with the bacteriophage T4 tail spike protein [7] . VgrG proteins form the T6SS needle tip and can puncture and translocate across eukaryotic membranes [16] . The VgrG-like protein of C . jejuni strain 108 lacks the extended biological effector domain that is often associated with modulation of eukaryotic cell function [16] , [37] . The major characteristics of the T6SS gene cluster of C . jejuni strain 108 and its most related orthologs in several other species are summarized in Table 1 . T6SS gene clusters are usually located on pathogenicity islands or chromosomal regions that show a bias towards bacterial survival or virulence [5] . The G+C content of the C . jejuni T6SS is 26 . 5% , compared to about 30% for the C . jejuni genome . In C . jejuni strain 108 the T6SS cluster is flanked at the amino- and carboxyterminal ends by orthologs ( 98% similarity at the amino acid level ) of respectively CJE1139 and CJE1141/CJ1142 of strain RM1221 . These genes are located on CJIE3 , an integrated element present in the genome of several C . jejuni strains including RM1221 [38] . The CJIE3 element of strain RM1221 lacks the T6SS gene cluster but contains CJE1141 and CJE1142 that have Rhs elements . Rhs elements can mediate chromosomal rearrangement or acquisition of new genetic information [39] . A fused homolog of these 2 genes forms the tssL ( VgrG ) gene at the carboxyterminal end of T6SS of C . jejuni strain 108 . This gene organization strongly suggests that the T6SS of C . jejuni 108 is localized within CJIE3 and has inserted between the genes CJE1139 and CJE1141/CJE1142 of strain RM1221 . Analysis of C . jejuni strain 108 for the presence of CJIE3 by PCR using a specific primerset [38] confirmed the presence of this element in strain 108 . Fig . 2C shows a schematic representation of the insertion of the T6SS locus of C . jejuni strain 108 between genes CJE1139 and CJE1141/CJE1142 in the CJIE3 element of C . jejuni strain RM1221 . The localization of C . jejuni T6SS on genetic element CJIE3 in strain 108 and the variable presence of T6SS genes in other C . jejuni genomes led us to determine the T6SS prevalence in C . jejuni . To this end , we analyzed 80 Campylobacter strains for the presence of the hcp gene using PCR . Both human and animal isolates from different regions of the world were analyzed ( Table S1 ) . PCR products were obtained for eight C . jejuni and two C . coli strains ( Fig . 3 ) . Notably , four of T6SS-positive strains were isolates derived from patients with C . jejuni bacteremia which is a rare event that occurs in <0 . 2% of intestinal C . jejuni infections [40] . In order to investigate whether the C . jejuni strains containing the hcp gene also harbored the integrative element CJIE3 , DNA from all 80 Campylobacter strains was analyzed by PCR using CJIE3-specific primers [37] . All hcp positive strains scored positive for CJIE3 . However , we also identified several CJIE3-positive strains that lacked the hcp gene , like strain RM1221 ( Fig . 3 ) . The organization and genomic integration of the T6SS cluster in the hcp positive C . jejuni strains was further characterized with primers used for the analysis of the T6SS gene cluster in strain 108 . This confirmed that the complete T6SS locus was present in all the Hcp-positive C . jejuni strains . The T6SS clusters were flanked at the aminoterminal end by CJE1138 orthologs in 6 out of 8 C . jejuni strains and 1 of 2 C . coli strains . In all strains the carboxyterminal flanking region of T6SS was different than in strain 108 as no PCR products were obtained . Therefore we assume that the complete T6S locus has been acquired by C . jejuni in one step , while integration occurred at different positions of the earlier integrated element CJIE3 . Evidence that the C . jejuni T6SS is functional was sought by analysis of Hcp secretion . Hereto the hcp gene was expressed in Escherichia coli SE1 . A 6×His-tag was fused to the carboxy-terminal end of the protein for purification purposes . Rabbits were immunized with the purified recombinant protein to generate Hcp-specific antibodies . SDS-PAGE and Western blotting confirmed specific reactivity of the antiserum with Hcp ( Fig . 4A ) . Immunoblotting of C . jejuni whole cell lysates and ( non-concentrated ) culture supernatants using the Hcp-specific antiserum demonstrated Hcp in both fractions ( Fig . 4A ) . Secreted Hcp and cellular Hcp showed a similar apparent molecular mass , suggesting that no additional processing of the protein occurs during secretion . Inactivation of hcp by allelic replacement with a defective copy of the gene yielding strain 108ΔHcp , resulted in loss of immunoreactivity ( Fig . 4A ) . To gain evidence that Hcp secretion was conferred by the putative T6SS machinery , the C . jejuni tssM gene was inactivated keeping in mind that its ortholog in other species ( e . g . VasK in V . cholerae , IcmF in R . leguminosarum ) is required for T6SS-dependent Hcp secretion [3] . The mutant was constructed by replacement of the gene with a disrupted copy containing a chloramphenicol resistance cassette , yielding C . jejuni 108ΔTssM . The disrupted gene had inserted in the same orientation as the parent gene as verified by PCR . Western blot analysis of the TssM mutant demonstrated the presence of Hcp in whole bacterial lysates but not in the culture supernatant ( Fig . 4A ) . These results strongly suggest that C . jejuni Hcp is secreted in a T6SS-dependent fashion . Immunoblots of culture supernatants of other hcp-positive C . jejuni strains demonstrated Hcp secretion for all of the tested strains ( Fig . 4B ) . The presence of large quantities of C . jejuni Hcp in the culture medium suggested constitutive expression of the T6SS genes under standard bacterial growth conditions . In V . cholerae and several other bacterial species , Hcp production requires the alternative transcription factor sigma-54 encoded by the rpoN gene and an enhancer binding protein ( e . g . VasH ) [3] , [6] , [41] . Although an ortholog of vasH appears absent from the T6SS locus of C . jejuni 108 , we tested the effect of genetic inactivation of C . jejuni rpoN on Hcp expression . This mutant has a defect in flagella assembly and displays a motility deficient phenotype [42] . Immunoblotting of cellular and supernatant fractions of strain 108ΔRpoN revealed unaltered high levels of Hcp for the mutant and parent strain ( Fig . 4A ) . These results suggest that RpoN does not regulate Hcp secretion in C . jejuni . In search for a biological function of the C . jejuni T6SS we first tested the potential competitive advantage of C . jejuni strain 108 towards other microorganisms . In several bacterial species the presence of T6SS facilitates survival in mixed populations , often through the production of antibacterial toxins that are injected into neighboring bacteria [24] , [26] , [43] , [44] . In our hands , co-culture of C . jejuni strain 108 with E . coli DH5α either in broth or on agar plates for up to 5 days did not reveal a selective growth advantage for the T6SS expressing strain . Similar results were obtained when C . jejuni strain 108 was incubated with the TS6SS-negative C . jejuni strain 81116ΔCPS which has similar growth requirements and growth rate as strain 108 . Although C . jejuni T6SS appeared to lack the extended VgrG protein often associated with cytotoxicity toward host cells , we next tested the effects of C . jejuni strains 108 and 108ΔHcp on eukaryotic cells including Caco-2 intestinal epithelial cells and red blood cells . Confocal laser microscopy on Caco-2 cells infected with strain 108 demonstrated that internalized C . jejuni remained in a CD63-positive endolysosomal compartment for up to 24 h [45] , suggesting that T6SS apparatus did not cause lysis and bacterial escape from the intracellular vacuole . The effect of the T6SS on erythrocytes was assessed by measurement of hemolytic activity after 6 h of incubation of the red blood cells with C . jejuni . This showed that C . jejuni 108 caused strong hemolysis compared to mutant strain 108ΔHcp ( Fig . 5A ) . Complementation of the hcp mutant by the introduction of plasmid pMA1-hcp carrying an intact copy of the hcp gene restored the strong T6SS-associated cytotoxicity ( Fig . 5A ) . We also tested the tssM mutant for hemolytic activity . This mutant failed to induce Hcp-induced hemolysis consistent with the observed essential function of the TssM protein in Hcp secretion ( Fig . 5A ) . Western blotting confirmed that the complementation of the hcp mutant and inactivation of tssM resulted the expected changes in Hcp secretion ( Fig . 5B ) . Isolated culture supernatant of strain 108 lacked hemolytic activity , suggesting that the T6SS phenotype involved contact-dependent hemolysis . It is important to note that the T6SS-induced hemolysis was observed for C . jejuni grown on agar plates for 7 days and then in HI broth for 16 h ( 7 p/16 h ) ( Fig . 5C ) . C . jejuni grown on agar plates for 3 days followed by growth in HI broth for 8 h ( 3 p/8 h ) failed to consistently induce substantial hemolysis ( Fig . 5C ) . In an attempt to understand the apparent bacterial growth-related variation in T6SS phenotype , we hypothesized that perhaps the C . jejuni surface capsule polysaccharide ( CPS ) interfered with the contact-dependent hemolysis . To test this hypothesis we first analyzed the CPS of C . jejuni 108 at different age of culture using Alcian blue staining . This revealed variable intensity of capsule staining with highest levels of capsule expression for C . jejuni grown on agar plates for 3 days and then in HI broth for 16 h ( 3 p/16 h ) ( Fig . 6A ) . At earlier ( 3 p/8 h ) and later ( 7 p/16 h ) time points , CPS levels were much lower ( Fig . 6A ) . This seemed to exclude variable CPS expression as a cause of the observed variation in T6SS-mediated hemolysis at these time points ( Fig . 5C ) . To definitively exclude the capsule as an inhibitory factor of T6SS function , we tested the capsule-deficient strain C . jejuni 108ΔCPS for hemolytic activity . The mutant was constructed by allelic exchange of the kpsM gene with a disrupted copy of this gene . Unexpectedly , C . jejuni 108ΔCPS displayed strong cytotoxicity at all tested time points except during early exponential growth phase ( 3 d/8 h ) ( Fig . 6B ) . The cytotoxic effect of the CPS mutant was abolished after additional inactivation of hcp or tssM ( Fig . 6C ) , indicating that the hemolysis required a functional T6SS . Genetic inactivation of kspM in C . jejuni 81116 , which lacks the T6SS gene cluster , did not result in enhanced hemolysis ( Fig . 6C ) . Together , these results demonstrate that C . jejuni T6SS confers a cytotoxic phenotype toward red blood cells but that this function requires downregulation of the polysaccharide capsule . Notably , similar experiments with strains 108 , 108ΔCPS , 108ΔHcp and 108ΔCPS/ΔHcp and J774A . 1 macrophages caused minimal cell damage ( i . e . LDH release ) , irrespective the presence of a functional T6SS ( Fig . 6D ) . The issue that remained to be resolved was why the 3 d/8 h C . jejuni culture fails to show the T6SS phenotype even in the capsule-negative background . To address the point , we compared relative transcript levels of hcp in 3 p/8 h and 3 p/16 h cultures for C . jejuni strains 108 and 108ΔCPS . Real-time PCR analysis showed 5–10 fold more hcp transcript for the 3 p/16 cultures compared to 3 p/8 h bacteria both for the parent and cps mutant strain ( Fig . 6E ) . These results indicate that C . jejuni hcp mRNA levels vary between growth conditions and suggest that in the early logarithmic phase C . jejuni Hcp levels may be insufficiently expressed to induce the hemolytic phenotype .
Type VI secretion systems are bacterial nano-injection machines that transport macromolecules into neighboring prokaryotic or eukaryotic cells . The toxic effector molecules serve to outcompete other bacterial species [24] , [43] or to alter host cells during pathogenesis [36] , [46; for review see] [47] . Here we report the existence and function of a T6SS pathogenicity island in the principal bacterial food-borne pathogen C . jejuni . The T6SS gene cluster is present in about 10% of the C . jejuni isolates and has inserted into C . jejuni integrated element 3 ( CJIE3 ) . The function is evidenced by the secretion of the hallmark hemolysin co-regulated protein Hcp . C . jejuni T6SS is special among the T6SS family because it confers contact-dependent cytotoxicity toward red blood cells and because its function requires down-regulation of the polysaccharide capsule . The capsule controlled cytotoxicity of C . jejuni T6SS adds a new element to the growing repertoire of T6SS regulation mechanisms and phenotypes . The T6SS cluster of C . jejuni consists of 13 genes that most resemble the T6SS genes of C . coli and H . hepaticus both with regard to gene organization and content ( Fig . 2 ) . In addition to the hallmark Hcp and VgrG-like proteins , predicted C . jejuni T6SS proteins include the TssJ-M proteins encoding base plate components of the secretion apparatus [13] , and TsB ( VipA ) , TssC ( VipB ) and TssE ( gp25 protein ) that form structures that resemble the evolutionary related bacteriophage tail sheath and baseplate proteins [4] , [5] . The C . jejuni T6SS locus lacks the frequently found TssH gene ( COG0542 ) encoding a ClpV ATPase implicated in the recycling of the TssB/TssC tubular sheath [9] , [11] . Although important for sheath contraction and recycling , ClpV is not essential for T6SS function in V . cholerae [48] . Alternatively , it is possible that a related member of the ClpB family of ATPases encoded from elsewhere on the C . jejuni genome partakes in T6SS function , although analysis of the ( incomplete ) genome of strain 108 has thus far failed to detect a ClpV homologue in strain 108 ( unpublished results ) . The C . jejuni T6SS genes are only present in isolates that carry the integrative element CJIE3 ( integrated into the 3′ end of an arginyl-tRNA ) . This element is likely plasmid derived and appears to consist of modular regions of unknown function that differ between CJIE3-positive strains [38] . The prevalence of CJIE3 among our 80 tested C . jejuni isolates and those used in the Parker study , is approximately 18% . Yet , only approximately 10% of the isolates contained the T6SS locus . Based on the difference in T6SS flanking regions in our isolates , we assume that the T6SS genes have been acquired en bloc and inserted at different positions into the previously acquired CJIE3 . The function of C . jejuni T6SS as a secretion apparatus is evident from the accumulation of Hcp in the culture medium and the defective Hcp secretion ( but intact production ) in the constructed tssM-defective strain ( Fig . 4A ) . It is noteworthy that Hcp secretion was apparent under most routine laboratory growth conditions . In other bacterial species T6SS function often appears in response to distinct environmental cues . Although the signals triggering the expression of T6SS genes are still unknown , environmental conditions like temperature , pH , iron or the presence of host cells may influence their induction [49] . Involved regulatory systems include the sensor kinase RetS in Pseudomonas aeruginosa [50] and the Burkholderia mallei VirAG two-component system and AraC-type activator BMAA1517 [51] . Expression of T6SS gene clusters in Vibrio cholerae , Aeromonas hydrophyla and Pseudomonas syringae is regulated by sigma-54 and cognate enhancer binding proteins ( e . g . VasH ) [48] . We show that sigma-54 is not required for C . jejuni T6SS protein secretion ( Fig . 4A ) . The molecular basis of the relative poor Hcp expression in the early exponential growth phase remains to be determined . A plausible alternative explanation for the limited gene regulation of C . jejuni T6SS may be this pathogen has evolved the described alternative strategy of capsule-sensitive T6SS function . Our results indicate that C . jejuni T6SS causes contact-dependent lysis of red blood cells . Bacterial competition assays with T6SS-negative C . jejuni and E . coli yielded no conclusive T6SS phenotype under the conditions employed . Furthermore , incubation of C . jejuni 108ΔCPS with J774A . 1 macrophages did not result in cytotoxicity ( Fig . 6D ) and the presence of T6SS did not seem to enable the intracellular C . jejuni to escape from the endolysosomal compartment [45] . Several lines of evidence indicate that the observed hemolysis was caused by T6SS activity: ( i ) Hemolysis was strongly reduced in the hcp and tssM mutants , ( ii ) complementation of the hcp mutant with an intact copy of the gene restored the phenotype , ( iii ) hemolysis was minimal for strain 81116 that lacks the T6SS gene cluster . The low level of hemolysis measured after prolonged incubation with the mutant strains ( Fig . 6 ) may be attributed to the presence of membrane bound hemolysins , such as phospholipase A [52] . The strong T6SS-mediated hemolytic activity may benefit C . jejuni by increasing the availability of nutrient sources such as iron and nicotinamide adenine dinucleotide ( NAD ) that are abundantly present in erythrocytes . A key feature in establishing the C . jejuni T6SS phenotype was the explanation of the initially highly variable results by changes in the level of capsule expression . The use of constructed capsule- and Hcp-negative mutant strains unequivocally demonstrate C . jejuni polysaccharide capsule as a key determinant controlling T6SS-induced hemolysis . To our knowledge capsule expression has not previously been implicated as a factor influencing the activity of T6SS . We propose that the polysaccharide capsule inhibits T6SS function by acting as a steric barrier that prevents the T6SS needle structure to puncture the host cells . In addition , needle length may be of importance as suggested by the poor hemolytic activity of capsule-negative strains at early growth phase when C . jejuni hcp transcript levels were much lower ( Fig . 6 ) . Thus , capsule thickness in conjunction with needle length may determine T6SS function in C . jejuni , reminiscent of the control of the function of the type III injectisome by needle length [53] and the extent of LPS glucosylation in Shigella flexneri [54] . The factors that regulate capsule expression in C . jejuni are not well defined [27] , although recent studies indicate that downregulation of capsule does occur upon contact with host cells [55] , [56] . In addition , at least in some C . jejuni strains capsule biosynthesis is subject to phase variation [57] . This event has not been demonstrated to occur in strain 108 , but , when present , may result in a subset of the bacterial population with a functional T6SS phenotype . This scenario may explain the basal level of hemolysis observed for the wildtype C . jejuni strain 108 . An intriguing issue is as to why a subset of C . jejuni strains has acquired and maintains a seemingly genetically stable and functional T6SS pathogenicity island . Its relatively low prevalence ( 10% ) and absence in many disease isolates indicate that the T6SS is not an essential virulence factor in intestinal infections but rather may be advantageous for the bacterium in a distinct niche . We did note that four out of the eight TSS6-positive C . jejuni isolates identified in this study were derived from human patients with Campylobacter bacteremia . This seems disproportionally high considering that C . jejuni bacteremia occurs in <0 . 2% of intestinal infections , often in immunocompromised patients [40] . We tested C . jejuni growth in human blood from healthy donors . This resulted resulted in rapid bacterial killing irrespective the presence of T6SS , indicating that in healthy donors bacterial killing mechanisms dominate over the possible growth advantage of T6SS-positive strains due to e . g . the release of nutrients from red blood cells . Similar assays in horse blood revealed no differences in bacterial growth/survival between strain 108 and the T6SS mutant ( Fig . S1 ) . The T6SS-positive C . jejuni blood isolates identified in the present study were all derived from patients with hypogammaglobulinemia , which may limit rapid bacterial killing . Yet , considering the low number of available blood isolates , we feel it too early to conclude that T6SS-mediated hemolysis contributes to the development of C . jejuni bacteremia . The presence of a functional T6SS in C . jejuni has recently been confirmed in a parallel study using strain 43431 [58] . The T6SS gene cluster in this strain also lacks a ClpV homologue . Inactivation of T6SS function in this strain resulted in increased resistance to high concentrations of bile salts , possibly by preventing entry of bile salt through the opened secretion channel [58] . The mutant also showed approximately 50% reduced bacterial adhesion and invasion of host cells . Whether the observations with this strain also varied with the presence of the polysaccharide capsule was not investigated . Overall , our study provides the first evidence that ( i ) ∼10% of C . jejuni isolates carry a complete T6SS gene cluster in the integrative element CJIE3 , ( ii ) the T6SS system is functional , ( iii ) C . jejuni T6SS confers cytotoxicity toward red blood cells , and ( iv ) the T6SS phenotype requires down regulation of the polysaccharide capsule . To our knowledge , T6SS-mediated hemolysis and an effect of capsule on T6SS function has never been reported for other bacterial species . C . jejuni T6SS represents a novel direction in the evolution of T6SS , expands the existing repertoire of T6SS-mediated effects on eukaryotic cells , and may contribute to systemic C . jejuni infection .
The bacterial strains used in this study are listed in Supporting Information ( Table S1 ) . Campylobacter was grown at 37°C under micro-aerobic conditions ( 5% O2 , 10% CO2 , 85% N2 ) either on Saponin agar plates containing agar base II medium ( Oxoid Ltd . , Basingstoke , UK ) with 5% saponin lysed horse blood , or in 5 ml of Heart Infusion broth ( HI ) ( Oxoid ) in 25 cm2 tissue culture flasks at 160 rpm . Escherichia coli were grown in Luria-Bertani medium at 37°C . When appropriate , growth media were supplemented with ampicillin ( 100 µg/ml ) , kanamycin ( 20 µg/ml ) , or chloramphenicol ( 20 µg/ml ) . The nucleotide sequence of the primers used for cloning and sequencing the T6SS locus are listed in Supporting Information ( Table S2 ) . DNA fragments encoding T6SS genes were PCR amplified by primer walking using 500 ng of isolated C . jejuni 108 genomic DNA as template , 2 . 5 U of Super Taq+ polymerase ( HT Biotechnology Ltd . UK ) , 50 pmol of each primer , and 0 . 1 mM of dNTPs in a final volume of 50 µl of 10 mM of Tris-HCl , 1 . 5 mM of MgCl2 and 50 mM KCl . Standard PCR conditions were heating for 2 min at 95°C , followed by 35 cycles of 15 s at 95°C , 15 s at 52°C , and 5 min at 72°C in a BioRad iCycler . Amplified products were subjected to agarose gel electrophoresis , purified with the Qiaex II gel extraction kit ( Qiagen ) , and cloned using pGEM-Teasy ( Promega ) or PJet ( Fermentas ) in E . coli DH5α . Primers T7 and Sp6 were used to determine the nucleotide sequences of the pGEM-Teasy inserts . The PJet1 . 2 forward and reverse primers were used to sequence the pJet1 . 2 inserts ( Baseclear , Leiden , The Netherlands ) . Sequences were analyzed and aligned using the DNASTAR software package ( Lasergene ) . The complete sequence of the T6SS gene cluster of C . jejuni strain 108 is deposited at GenBank ( Accession number: JX436460 ) . Primers used for construction of mutants are listed in Supporting Information Table S3 . The hcp and tssM gene with their flanking sequences of strain 108 were amplified by PCR as described above . PCR products were cloned into pGEM-T easy . Inverse PCR on pGEMhcp was used to delete 166 bp of hcp and to introduce a BamHI restriction site . Plasmid pGEMtssM was cut with bglII . The chloramphenicol resistance gene ( Cm ) from pAV35 was ligated into the created BamHI site in hcp and into the BglII site in tssM , yielding pGEMhcp::cm and pGEMtssM::cm , respectively . Knockout plasmids carrying the Cm gene in the same orientation as the hcp and tssM genes were used to transform C . jejuni 108 by electroporation . Mutants were selected on saponin agar plates containing 20 µg/ml of chloramphenicol . Disruption of the genes was verified by PCR . For construction of C . jejuni 81116ΔCPS the kpsM gene with flanking sequences was amplified with primers listed in Table S3 and cloned into pGEM-T easy . A deletion of 300 bp was made using inverse PCR thereby creating a unique BglII restriction site . The 2 , 000 bp tetracycline resistance gene from pTetO was inserted into this BglII site , yielding pGEM-T easy kpsM::tet . Natural transformation was used to introduce the knockout plasmid into C . jejuni 81116 . Mutants were selected on saponin agar plates containing 15 µg/ml of tetracycline . BglII digestion was used to replace the tetO gene in the pGEM-T easy kpsM::tet construct with the Cm gene from pAV35 . The resulting plasmid pGEMkpsM::cm was introduced in C . jejuni 108 via electroporation , yielding strain 108ΔCPS . Chloramphenicol resistant transformants were selected and gene disruption was confirmed by PCR . The hcp gene including its ribosomal binding site was PCR amplified from strain C . jejuni 108 using primers 276 and 277 . After digestion with XhoI and XbaI , the resulting 531 bp fragment was cloned into the pMA1 vector behind the C . jejuni metK promoter [59] , yielding pMA1hcp . The plasmid was introduced by electroporation into C . jejuni 108 wild type and the hcp mutant , and kanamycin resistant transformants were selected . The hcp gene was PCR amplified from C . jejuni 108 genomic DNA with primers 210 and 211 and fused to a C-terminal 6× histidine tag using the XbaI–XhoI sites of pSCodon1 ( Delphi genetics SA ) . Selection of pSCodon1hcp was performed in E . coli CYS21 , while E . coli SE1 was used to express the Hcp protein ( Staby Codon T7 manual , Delphi genetics SA ) . An overnight culture of E . coli pSCodon1hcp in Staby Switch auto-inducible medium ( Eurogentec , Belgium ) was used to isolate His-tagged Hcp from the soluble cytosolic fraction . Recombinant protein was purified under native conditions using Ni-NTA agarose and 250 mM of imidazole in the elution buffer as described in the manual ( Qiagen ) . Eluted fractions were analyzed by SDS-PAGE . Hcp-positive fractions were pooled and dialyzed for 20 h against 3 liter of 50 mM of Tris-HCl buffer ( pH 7 . 6 ) containing 200 mM of KCl , 10 mM of MgCl2 , 0 . 1 mM of EDTA , 10% glycerol , and then against the same buffer containing 50% glycerol . Two New Zealand White rabbits ( SPF ) were immunized four times ( Days 0 , 14 , 28 and 56 ) with 100 µg of purified Hcp protein using the classical anti-protein protocol ( Eurogentec , Belgium ) . Serum aliquots were collected ( Days 0 , 38 , 66 and 87 ) and stored at −20°C . Dilutions of sera were tested by Western blot analysis for Hcp reactivity . All immunizations and handling of animals were performed by Eurogentec , Belgium . For protein detection , aliquots of bacterial cultures ( 16 h , HI broth ) were pelleted ( 4 , 000× g , 15 min ) and dissolved in the same volume of Laemmli electrophoresis solution containing 30 mM of Tris-HCl ( pH 6 . 8 ) , 4% SDS , 0 . 025% bromophenol blue and 20% glycerol . The bacterial supernatant was subjected to high speed centrifugation ( 18 , 500× g , 15 min ) to remove supramolecular structures and mixed at a 3∶1 ( v/v ) ratio with 3×-concentrated Laemmli solution . After boiling ( 10 min ) , the equivalent of 10 µl of bacterial culture was loaded onto a 12% SDS-polyacrylamide gel . Proteins were transferred to PVDF membranes ( Immobilon-P , Millipore ) . After blocking ( 5% skim milk powder ( Elk , Campina ) , 0 . 1% Tween 20 ) , Hcp was detected with rabbit anti-Hcp antiserum ( 1/500 in PBS , 2% skim milk , 0 . 1% Tween 20 ) in combination with horseradish peroxidase-conjugated goat anti-rabbit IgG ( Santa Cruz Biotechnology ) and Super signal west pico chemiluminescent substrate ( Pierce ) . Two-dimensional gel electrophoresis was generously carried out by Dr . Bas van Balkom as previously described [60] , except that precast immobilized nonlinear pH ( pH 3 to 10 ) gradient strips ( Amersham Biosciences ) were used . In-gel tryptic digestion and mass spectrometry analysis were performed as described [60] . For capsule detection , bacteria ( 2×109 ) were suspended in 100 µl of Laemmli buffer . Next , 30 µl of 20 mg/ml proteinase K in water was added and the mixture was incubated at 55°C for 2 h . Capsular polysaccharides were separated on a 12% SDS-PAGE gel . Gels were washed twice in water and stained ( 1 h ) with filtered 0 . 5% Acian Blue 8GX ( Sigma ) in 2% acetic acid/40% methanol . Gels were destained in 2% acetic acid/40% methanol until bands became visible [60] . SDS-PAGE and protein staining of non-digested aliquots of the samples confirmed equal loading of bacteria . C . jejuni grown on saponin agar plates for 3 or 7 days were transferred to HI broth ( OD550: 0 . 05 ) in 25 cm2 flask and shaken ( 160 rpm ) for 8 h or 16 h at 37°C under microaerophillic conditions . Bacterial pellets from solid and broth media were suspended in PBS to OD550 of 1 . One ml of this bacterial suspension was then mixed with 0 . 25 ml of a 5% ( v/v ) horse erythrocyte suspension ( Biotrading ) kept in PBS with 0 . 4 mM of CaCl2 in a 1 . 5 ml plastic tube with a perforated cap . After incubation ( 37°C , 6 h , microaerophilic conditions ) , the tubes were mixed and centrifuged ( 1 , 000× g , 5 min ) . The OD420 of the supernatants was then measured as indicator of the degree of hemolysis . Negative ( with PBS without bacteria ) and positive ( with added water instead of bacterial suspension ) controls were included in all assays . Cytotoxicity was scored as percentage of cell lysis of the positive control . Data are expressed as the mean ± SEM of at least three independent experiments . Cytotoxicity toward macrophages was determined using J774A . 1 macrophages ( ATCC ) grown for 24 h in a 24-well plate in DMEM+10% FCS at 37°C in a 10% CO2 atmosphere . Prior the use the medium was replaced by 1 ml of fresh DMEM ( without FCS ) . C . jejuni strains 108 , 108ΔHcp , 108ΔCPS , 108ΔCPS/ΔHcp and ( as control ) Salmonella Typhimurium strain SL1344 were grown in HI broth , collected by centrifugation ( 10 min , 3 , 000× g ) , and added to the macrophages at a bacteria to host cell ratio of 20 . After 2 h of incubation ( 37°C , 5% CO2 ) , the extracellular Salmonella were removed and 1 ml of DMEM+50 µg/ml gentamicin was added . The cells were incubated for an additional 10 h before total cellular LDH and LDH release from the cells was determined with the Cytotoxicity Detection Kit according to the protocol of the manufacturer ( Roche ) . The supernatant or the lysed cells stained with the kit was analyzed on the FLUOstar omega ( BMG Labtech ) at 492 nM and 690 nM for wavelength correction . Cytotoxicity was determined by calculating the percentage of LDH released after background subtraction . C . jejuni had no effect on the LDH itself or the assay . Presented results are from three individual assays performed in triplicate . Data were analyzed using Graphpad Prism software . C . jejuni strain 108 , 108ΔCPS and 108ΔCPS/ΔHcp grown in HI broth ( 16 h , 37°C ) were collected by centrifugation ( 15 min , 4000× g ) and suspended in 50 µl of HI broth . Bacteria ( 109 CFU ) were , added to 3 ml of heparinized human or defibrinated horse blood in 35 mm petri dishes and incubated at 37°C under micro-aerobic conditions . After 0 , 6 , 24 and 48 h , 10 µl aliquots were taken , serially diluted in PBS , and plated onto saponin agar plates . Bacterial survival was determined by counting the number of colony forming units after 48 h of incubation at 37°C under micro-aerobic conditions . Total bacterial RNA was extracted from C . jejuni strain 108 and 108ΔCPS grown in 25 ml of HI Broth for 8 or 16 h at 37°C under micro-aerobic conditions , using the RNA-Bee kit ( Tel-Test , Inc ) according to the manufacturer's specifications . Isolated RNA was treated with 1 µg of DNase ( Fermentas ) per µg of RNA for 30 min at 37°C , after which the DNase was inactivated by heating at 65°C for 10 min in the presence of EDTA ( 2 . 5 mM final concentration ) . Real time RT-PCR analysis was performed using the Brilliant III Ultrafast SYBR Green QRT-PCR master mix ( Agilent , Stratagene Inc ) . The PCR mixture ( 20 µl ) contained 40 ng of DNase treated RNA , 20 pmol of the Hcp gene specific primers hcp-RT forw ( 5′-ACCCGATTTATATCTATTGCCAAT-3′ ) and hcp-RT rev ( 5′-GAAGGTTCCACACAAGGTTTGAT-3′ ) , 10 µl of 2× SYBR green mix , 0 . 2 µl of 100 mM of DTT and 1 µl of RT/RNAse block . The reverse transcriptase cycle was 50°C for 10 min , followed by a PCR initial activation step of 95°C for 3 min . The mixtures were then amplified in 45 cycles of 95°C for 5 sec and 60°C for 10 sec in a Light Cycler 480 ( Roche ) . Total hcp mRNA in each sample was normalized against the internal controls gyrA and rpoA . Three independent experiments with two independent preparations of RNA were analyzed by real-time RT-PCR . | Bacteria contain a number of secretion systems to export macromolecules to the environment . The bacterial type VI secretion system ( T6SS ) forms a needle-like structure that delivers toxic effector molecules to neighboring eukaryotic and/or prokaryotic cells . Here we report that the important human pathogen Campylobacter jejuni contains a functional T6SS gene cluster . The cluster comprises 13 conserved T6SS genes including genes encoding the typical T6SS Hcp and VgrG proteins . The gene cluster is part of a larger DNA element and is present in about 10% of C . jejuni strains including several blood isolates . The identified C . jejuni T6SS has unique properties compared to similar systems in other bacterial species . C . jejuni T6SS lacks the ClpV ATPase that supposedly energizes part of T6SS function in other species , causes contact-dependent lysis of red blood cells , and requires downregulation of the C . jejuni capsule polysaccharide to be effective . The unique cytotoxic properties of C . jejuni T6SS , the effect of the capsule on T6SS function , and the possible association with systemic C . jejuni infection broaden the scope of the existing bacterial T6SS phenotypes and point to a different evolution of C . jejuni T6SS compared to other bacterial species . | [
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] | 2013 | Identification of a Functional Type VI Secretion System in Campylobacter jejuni Conferring Capsule Polysaccharide Sensitive Cytotoxicity |
The development of systemic approaches in biology has put emphasis on identifying genetic modules whose behavior can be modeled accurately so as to gain insight into their structure and function . However , most gene circuits in a cell are under control of external signals and thus , quantitative agreement between experimental data and a mathematical model is difficult . Circadian biology has been one notable exception: quantitative models of the internal clock that orchestrates biological processes over the 24-hour diurnal cycle have been constructed for a few organisms , from cyanobacteria to plants and mammals . In most cases , a complex architecture with interlocked feedback loops has been evidenced . Here we present the first modeling results for the circadian clock of the green unicellular alga Ostreococcus tauri . Two plant-like clock genes have been shown to play a central role in the Ostreococcus clock . We find that their expression time profiles can be accurately reproduced by a minimal model of a two-gene transcriptional feedback loop . Remarkably , best adjustment of data recorded under light/dark alternation is obtained when assuming that the oscillator is not coupled to the diurnal cycle . This suggests that coupling to light is confined to specific time intervals and has no dynamical effect when the oscillator is entrained by the diurnal cycle . This intringuing property may reflect a strategy to minimize the impact of fluctuations in daylight intensity on the core circadian oscillator , a type of perturbation that has been rarely considered when assessing the robustness of circadian clocks .
Real-time monitoring of gene activity now allow us to unravel the complex dynamical behavior of regulatory networks underlying cell functions [1] . However , understanding the collective behavior of even a few molecular actors defies intuition , as it depends not only on the topology of the interaction network but also on strengths and response times of its links [2] . A mathematical description of a regulatory network is thus necessary to qualitatively and quantitatively understand its dynamical behavior , but obtaining it is challenging . State variables and parameters are subject to large fluctuations [3] , which create artificial complexity and mask the actual network structure . Genetic modules are usually not isolated but coupled to a larger network , and a given gene can be involved in different modules and pathways [4] . It is thus important to identify gene circuits whose dynamical behavior can be modeled quantitatively , to serve as model circuits . One strategy for obtaining such circuits has been to construct synthetic networks , which are isolated by design [5]–[7] . As recent experiments have shown , an excellent quantitative agreement can be obtained by incorporating when needed detailed descriptions of various biochemical processes ( e . g . , multimerization , transport , DNA looping , etc . ) [7] . Another strategy is to study natural gene circuits whose function makes them relatively autonomous and stable . The circadian clocks that drive biological processes around the day/night cycle in many living organisms are natural candidates , as these genetic oscillators keep track of the most regular environmental constraint: the alternation of daylight and darkness caused by Earth rotation [8]–[11] . Informed by experiments , circadian clock models have progressively become more complex , evolving from single loops featuring a self-repressed gene [12] , [13] to networks of interlocked feedback loops [14]–[17] . Here we report surprisingly good agreement between the mathematical model of a single transcriptional feedback loop and expression profiles of two central clock genes of Ostreococcus tauri . This microscopic green alga is the smallest free-living eukaryote known to date and belongs to the Prasinophyceae , one of the most ancient groups of the green lineage . Ostreococcus displays a very simple cellular organization , with only one mitochondrion and one chloroplast [18] , [19] . Its small genome ( 12 . 6 Mbp ) sequence revealed a high compaction ( 85% of coding DNA ) and a very low gene redundancy [20] ( e . g . , most cyclins and CDK are present as a single copy gene [21] ) . The cell division cycle of Ostreococcus is under control of a circadian oscillator , with cell division occurring at the end of the day in light/dark cycles [21] . These daily rhythms in cell division meet the criteria characterizing a circadian clock , as they can be entrained to different photoperiods , persist under constant conditions and respond to light pulses by phase shifts that depend on internal time [21] . Very recently , some light has been shed on the molecular workings of Ostreococcus clock by Corellou et al . [22] . Since the clock of closely related Arabidopsis has been extensively studied , they searched Ostreococcus genome for orthologs of higher plant clock genes and found only two , similar to Arabidopsis central clock genes Toc1 and Cca1 [22] . These two genes display rhythmic expression both under light/dark alternation and in constant light conditions . A functional analysis by overexpression/antisense strategy showed that Toc1 and Cca1 are important clock genes in Ostreococcus . Overexpression of Toc1 led to increased levels of CCA1 while overexpression of Cca1 resulted in lower levels of TOC1 . Furthermore CCA1 was shown to bind to a conserved evening element sequence ( EE ) that is required for the circadian regulated activity of Toc1 promoter . Whether Toc1 and Cca1 work in a negative feedback loop could not be inferred from this study since Ostreococcus clock appeared to rely on more than a simple Toc1/Cca1 negative feedback loop . Interestingly , Arabidopsis genes Toc1 and Cca1 were the core actors of the first plant clock model , based on a transcriptional loop where TOC1 activates Cca1 and the similar gene Lhy , whose proteins dimerize to repress Toc1 [23] , [24] . However , this model did not reproduce well expression peaks of Toc1 and Cca1 in Arabidopsis [24] and was extended to adjust experimental data [25] . Current Arabidopsis clock models feature several interlocked feedback loops [15] , [16] . This led us to investigate whether the transcriptional feedback loop model where Toc1 activates Cca1 and is repressed by Cca1 would be relevant for Ostreococcus . We not only found that this two-gene loop model reproduces perfectly transcript profiles of Ostreococcus Toc1 and Cca1 but that excellent adjustment of data recorded under light/dark alternation is obtained when no model parameter depends on light intensity . This counterintuitive finding suggests that the oscillator is not permanently coupled to light across the 24-hour cycle but only during specific time intervals , which is supported by numerical simulations . In this article , we propose that the invisibility of coupling in entrainment conditions reflects a strategy to shield the oscillator from natural fluctuations in daylight intensity .
To characterize the temporal pattern of Toc1 and Cca1 expression in Ostreococcus , we used microarray data acquired in triplicate under 12∶12 light/dark cycle , as described in [21] ( Fig . 1 ) . One Toc1 and two Cca1 mRNA time courses had no aberrant point . Here , we use as target profiles the complete Toc1 profile and the complete Cca1 profile whose samples are obtained from the same microarray data as the Toc1 profile . We checked that the results described in this work are robust to the biological variations observed . Corellou et al . have also carried out an extensive work of genetic transformation in Ostreococcus , leading to transcriptional and translational fusion lines allowing one to monitor transcriptional activity and protein dynamics in living cells [22] . However , luciferase kinetics in this organism is still not well known and we postpone the analysis of luminescence time series to a future work . Model adjustment has thus been carried out using microarray expression data , which reflect accurately the endogeneous levels of mRNA . Although seeking quantitative agreement with luminescence time series was premature at this stage , predicted protein concentration profiles were compared with data from translational fusion lines as an additional test . A minimal mathematical model of the two-gene feedback loop comprises four ordinary differential equations ( Eq . ( 2 ) , Methods ) with 16 parameters . Since detailed models extending the basic 4-ODE model ( 2 ) could only have led to better adjustment , we purposely neglected here effects such as compartmentalisation or delays due to transcription or translation so as to minimize the risk of overfitting and reliably assess the validity of the two-gene loop hypothesis . Experimental data are recorded under 12∶12 Light/Dark ( LD ) alternation so that the coupling which synchronizes the clock to the diurnal cycle must be hypothesized . Circadian models usually assume that some parameters depend on light intensity ( e . g . , a degradation rate is higher in the dark than in the light ) , and thus take different values at day and night . Parameter space dimension then increases by the number of modulated parameters . Various couplings to light were considered , with 1 to 16 parameters depending on light intensity . We also tested adjustment to model ( 2 ) with all parameters constant , which allowed us to quantify the relevance of coupling mechanisms by measuring the difference between best-fitting profiles in the coupled and uncoupled cases . The free-running period ( FRP ) of the oscillator in constant day conditions was fixed at 24 hours , which was the mean value observed in experiments [22] , but we checked that our main results remain valid for other values of the FRP . In fact , we found that when FRP was freely adjustable , it usually converged to values close to or slightly below 24 hours . Fixing the FRP at exactly 24 hours is interesting in that coupling mechanisms are selected by adjustment only if they improve goodness of fit and not merely to achieve frequency locking . The first result is that an excellent agreement between numerical and experimental profiles is obtained , with a root mean square ( RMS ) error of a few percent ( Figs . 2 ( A ) – ( B ) ) . There is no point in extending model ( 2 ) to improve adjustment of microarray data , which are compatible with the hypothesis of a Toc1-Cca1 feedback loop . Moreover , the corresponding protein profiles ( not adjusted ) correlate well with luminescence signals from CCA1∶Luc and TOC1∶Luc translational fusion lines ( Figs . 2 ( C ) – ( F ) ) . But the more surprising is that a non-coupled model , where all parameters are kept constant , adjusts experimental data ( Fig . 2 ( B ) , RMS error 3 . 6% ) essentially as well as a fully coupled model where all parameters are allowed to vary between day and night ( Fig . 2 ( A ) , RMS error 3 . 3% ) . The corresponding parameter values are given in Table 1 . When only one or a few parameters were modulated , goodness of fit significantly degraded compared to the uncoupled and fully coupled cases . This indicates that besides being biologically unrealistic , the model with all parameters modulated fits data merely because of its large parameter space dimension , and cannot be considered seriously . Moreover we simulated the transition from LD alternation to constant light ( LL ) or constant darkness ( DD ) conditions for this model and found that it still adjusted experimental data well in LL while displaying strongly damped oscillations in DD ( Fig . S1 ) . This confirms that adjustment relies on time profiles being close to free-running oscillator profiles and that adjustment by a fully coupled model is in fact accidental . On the other hand the uncoupled model is equally unrealistic because it cannot be entrained to the day/night cycle , whereas it is observed experimentally that upon a phase shift of the light/dark cycle , CCA1 and TOC1 expression peaks quickly recover their original timings in the cycle . To verify that adjustment by a free-running oscillator model does not depend on the target profile used , we generated a large number of synthetic profiles whose samples where randomly chosen inside the interval of variation observed in biological triplicates , and adjusted a free-running oscillator model to them . In each case , we found that although RMS error slightly degraded compared our target profile ( where mCCA1 and mTOC1 samples for a given time always come from the same microarray ) , it remained on average near 10% , with visually excellent adjustment ( Fig . S2 ) . Last , it should be noted that assuming a FRP of 24 hours allows frequency locking to occur without coupling , but cannot induce by itself best adjustment in this limiting case . Thus the paradoxical result that data points fall almost perfectly on the temporal profiles of a free-running oscillator is counterintuitive but must nevertheless be viewed as a signature of the clock architecture . As we will see , this in fact does not imply that the oscillator is uncoupled but only that within the class of models considered so far , where parameters of the TOC1–CCA1 loop take day and night values , the uncoupled model is the one approaching experimental data best . Nothing precludes that there are more general coupling schemes that adjust data equally well . Before unveiling such models , we discuss now whether the simple negative feedback loop described by model ( 2 ) is a plausible autonomous gene oscillator . With two transcriptional regulations , it is a simpler circuit than the Repressilator , where three genes repress themselves circularly [5] . It is known that in this topology , oscillations become more stable as the number of genes along the loop increases . The two-gene feedback loop described by ( 2 ) could therefore seem to be a less robust oscillator than the Repressilator , and thus a poor model for the core oscillator of a circadian clock . To address this issue , we checked robustness of adjustment with respect to parameter variations . We found that the experimental profiles can be reproduced in a wide region of parameter space around the optimum , which is quite remarkable given the simplicity of the model ( Fig . S3 ) . Moreover , a distinctive feature of the best fitting parameter sets is a strongly saturated degradation , in particular for Cca1 mRNA , with an extremely low value of equal to of the maximal CCa1 mRNA concentration ( see Table 1 ) . In this situation , the number of molecules degraded per unit time is essentially constant and does not depend on the concentration except at very small values . This is consistent with the characteristic sawtooth shape of our target profile drawn in linear scale ( Fig . 1 ( B ) ) . The role of post-translational interactions in gene oscillators and circadian clocks has been recently emphasized ( see , e . g . , [26] , [27] ) , and in particular saturated degradation has since long been known to favor oscillations [9] , [28] , [29] . Recently , it has been been shown to act as a delay [30] , [31] and to be essential for inducing robust oscillations in simple synthetic oscillators [7] , [32] , [33] ( compare Fig . 1 ( B ) with Fig . 5 of [33] ) . Thus , strongly saturated degradation is very likely also a key dynamical ingredient of the natural gene oscillator studied here . Circadian models are usually coupled to diurnal cycle by changing some parameter values between day and night [12]–[17] . This assumes that all molecular actors involved in light input pathways have been incorporated and that their properties ( e . g . , degradation rates ) react directly to light . Such couplings act over the entire cycle except when light-sensitive actors are present only transiently . For example , models of Arabidopsis clock feature an intermediary protein PIF3 that is necessary for induction of CCA1 by light but is shortly degraded after dawn so that CCA1 transcription is only transiently activated [15] , [24] , [25] . Gating of light input has been observed in several circadian clocks and may be important for maintaining proper timing under different photoperiods [34] . In our case , light/dark alternation has no detectable signature in the dynamics of Toc1 and Cca1 mRNA when the clock is phase-locked to the diurnal cycle . This suggests that the actors of the two-gene loop do not sense light directly , and are driven via unknown mediators , which modify their properties inside specific temporal intervals . Since the input pathway can have complex structure and dynamics , possibly featuring separate feedback loops , the windows of active coupling may be located anywhere inside the diurnal cycle and reflect light level at other times of the cycle . Coupling activation should depend both on time of day and on the intrinsic dynamics of the light input pathway , notwithstanding a possible feedback from the circadian core oscillator [35]–[37] . For simplicity , we restrict ourselves to models in which some parameters of the TOC1–CCA1 feedback loop are modified between two times of the day , measured relatively to dawn ( ZT0 ) . The start and end times of coupling windows are then model parameters instead of being fixed at light/dark transitions . This assumes that the input pathway tracks diurnal cycle instantaneously , without loss of generality for understanding behavior in entrainment conditions . In this scheme , resetting of the two-gene oscillator can be studied by simply shifting the oscillator phase relatively to the coupling windows . The results so obtained will be sufficient to show that there exist coupling schemes which leave no signature on mRNA profiles , and to study their properties . What makes our approach original is not the gated coupling to diurnal cycle , which can be found in other models , but the fact that we do not try to model the actors of the input pathway , which can be complex . This is because we focus here on the TOC1–CCA1 feedback loop , which mostly behaves as an autonomous oscillator . Thus we only need to specify the action of the unknown mediators on TOC1 or CCA1 , the details of their dynamics being irrelevant . We systematically scanned the coupling window start and end times , adjusting model for each pair . This revealed that many coupling schemes are compatible with experimental data . For example , TOC1 degradation rate can be modified almost arbitrarily in a large temporal window between ZT22 . 5 and ZT6 . 5 without degrading adjustment . This is shown in Figs . 3 ( A ) – ( C ) , where inside this window ( here and below , denotes the uncoupled degradation rate of variable ) . Although the coupling is active for 8 hours , this coupling scheme generates mRNA and protein profiles which are indistinguishable from those of a free-running oscillator . Indeed , modifying TOC1 stability in a window where protein level is low , as is the case for any subinterval of the ZT22 . 5–ZT6 . 5 window , does not perturb the oscillator . We also found a family of time windows of different lengths centered around ZT13 . 33 , inside which the CCA1 degradation rate can be decreased without significantly modifying goodness of fit . In Figs . 3 ( D ) – ( F ) , we show the effect of having between ZT12 . 8 and ZT13 . 95 . In this coupling scheme , mRNA profiles are not affected but coupling activation has a noticeable effect on CCA1 level , which rises faster than in the uncoupled case . After the window , however , CCA1 level relaxes in a few hours to the uncoupled profile , losing memory of the perturbation . Near this time of the day , the CCA1 protein level appears to be slaved by the other variables: the perturbation induced by modified degradation does not propagate to the other variables , and when coupling is switched off , the protein level relaxes to its value in the uncoupled solution . Thus , the effect of coupling is not only small but transient . An important consequence , which we will exploit later , is that the two coupling windows shown in Fig . 3 can be combined without modifying adjustment , provided the perturbation induced by one window has vanished when the other window begins . In these examples , adjustment is sensitive to the timing of these coupling windows: when the start time is modified slightly , the end time must be changed simultaneously so as to recover good adjustment . On the other hand , we found that adjustment error depends little on the coupling strength ( measured by the ratio between degradation rates outside and inside the window ) , especially for short coupling windows . Fig . 4 ( A ) shows how adjustment error varies as a function of coupling strength for the two coupling windows used in Fig . 3 as well as for two other windows inside which the CCA1 protein degradation is reduced , one shorter and the other longer than the window in Fig . 3 ( B ) . The window of accelated TOC1 degradation is totally insentitive to modifications of the TOC1 degradation rate , which is due to protein levels being very low in this window . Windows of CCA1 stabilization are all the more insensitive to variations in CCA1 degradation rate as they are shorter . To quantify the sensitivity of a given window we define as the largest value of the ratio such that adjustment RMS error remains below 10% for any value of between and . The associated variations in mRNA profiles are visually undetectable and below experimental uncertainties . For the windows ZT12–ZT15 . 47 , ZT12 . 8–ZT13 . 95 and ZT13–ZT13 . 65 , of respective durations 3 . 47 , 1 . 15 and 0 . 65 hours , we find that the index takes the value 1 . 5 , 2 . 5 and 260 respectively . To gain better insight into the effect of a coupling window , we must take into account the fact that the induced variation in the entrained oscillations can be decomposed as a displacement along the limit cycle ( resulting in a phase shift ) and a displacement transversely to the limit cycle ( resulting in a deformation of the limit cycle ) . To this end , we apply a variable phase shift to the entrained time profile and optimize this phase shift so as to minimize the adjustment error . We define the waveform error as the minimal value of the latter , and the phase error the value of the phase shift for which it is obtained . A small waveform error indicates that we are following the same limit cycle as in the free-running case , possibly with a different phase than is observed experimentally . Waveform and phase errors for the three windows of CCA1 protein stabilization considered in Fig . 4 ( A ) are shown in Figs . 4 ( B ) and 4 ( C ) , respectively . It can be seen that only the largest window is associated with a deformation of the limit cycle for large values of , and that it remains modest ( RMS error of about 10% for ) . For the two shorter windows , degraded adjustment essentially results from a phase shift of the entrained solution as the modulation index is increased . It can also be seen that the phase error is in fact very small , approximately 7 . 5 and 2 . 5 minutes at for the two shorter windows . Thus it appears that for short enough windows , the effect of the light coupling mechanism can be entirely captured by studing the phase response induced by the mechanism and that a necessary property of a coupling window is that it induces a zero phase shift of the free-running limit cycle ( or a phase shift corresponding to the mismatch between the natural and forcing periods in the general case that we will consider later ) . Besides the two specific examples shown in Fig . 3 , other coupling schemes are compatible with experimental data . In this section , we undergo a systematic approach in order to determine those coupling schemes that do synchronize the free-running model to the day/night cycle , while leaving no signature on mRNA profiles when the phase-locking regime is achieved . To this aim , a preliminary step is to identify coupling schemes which synchronize in the limit of weak forcing using the tools of infinitesimal phase response curve , which can be defined in the framework of perturbation theory in the vicinity of periodic orbits [38]–[40] . Computation of the parametric impulse phase response curve [41] ( ) characterizing a light-coupling mechanism corresponding to parameter variation allows one to determine time intervals specified by duration and median position such that when the mechanism is applied in this time interval , it generates a zero phase shift and phase-locking is stable to small perturbations ( Text S1 ) . Such intervals satisfy: ( 1 ) Figure 5 depicts the properties of various gated couplings in the case where the light-coupling mechanism is assumed to modulate specifically a single transcription-related or degradation-related kinetic parameter . For sufficiently weak positive or negative modulation of those eight parameters , a coupling window of specific width ( ) and position ( ) can always be found to satisfy the Eq . 1 ( Figs . 5 ( A ) – ( C ) ) , thus being compatible with experimental data . However , the adjustment of these weak coupling schemes to data is expected to deteriorate progressively when coupling strength is increased , because ( i ) the locking phase may change , ( ii ) the modulation may deviate significantly the trajectory from that of the free-running oscillator or ( iii ) the entrained solution may loose its stability . Numerical simulations performed at different coupling strengths indicate that only a subset of coupling schemes determined in the limit of weak coupling keep a good adjustement irrespective of the coupling strength . Fig . 5 ( D ) shows window timings such that adjustment error remains below 10% when the kinetic parameter is multiplied or divided by 1 . 17 or 2 . Such a goodness of fit can only be obtained if limit cycle deformation remains small . As with the examples considered in the previous section , some coupling mechanisms have robust adjustment properties in that a good adjustment is obtained at the two different coupling strengths for the same timings , which coincide with the timings computed in the weak coupling limit . In these cases , adjustment is robust to variations in the coupling strength , which suggests that for these coupling mechanisms , the weak coupling approximation remains valid up to large coupling strengths . For instance , light coupling mechanisms that temporarily increase TOC protein degradation ( ) or CCA1 activation threshold ( ) in windows located during the day appear to be robust couplings . Similarly , decreasing CCA1 protein degradation ( ) or TOC repression threshold ( ) in windows occuring during the night are robust light-coupling mechanisms . Some other mechanisms do not display the same robustness because either the window timings corresponding to good adjustment depend sensitively on coupling strength ( e . g . , for positive modulation of mTOC1 degradation rate ) or because no good adjustment can be found except for very short windows ( e . g . , modulation of mCCA1 degradation rate ) . Other robust coupling mechanisms can be identified in Fig . S4 , in which the coupling mechanisms not considered in Fig . 5 are characterized . Figure 6 provides a complementary illustration of the robustness of adjustment for models with gated modulation of CCA1 or TOC1 protein degradation rate . In these plots , the window center is kept fixed at the time determined from Eq . ( 1 ) and shown in Fig . 5 ( C ) while coupling strength and window duration are freely varied . It can be seen that this timing is compatible with adjustment in a wide range of coupling strengths and window durations . Our analysis shows that several coupling mechanisms are compatible with the experimental data and that discriminating them requires more experimental data . In particular , monitoring gene expression in transient conditions will probably be crucial since the coupling mechanism leaves apparently no signature in the experimental data in entrainement conditions . For simplicity , we restrict ourselves in the following to models in which half-lives of TOC1 or CCA1 proteins are modified during a specific time interval that is determined in Fig 5 ( D ) . One may wonder about the purpose of coupling schemes with almost no effect on the oscillator . The key point is that our data have been recorded when the clock was entrained by the diurnal cycle and phase-locked to it . A natural question then is: how do such couplings behave when clock is out of phase and resetting is needed ? We found that while the two mechanisms shown in Fig . 3 have poor resetting properties when applied separately ( Fig . S5 ) , a combination of both can be very effective . In Fig . 7 ( A ) – ( B ) , we show how the two-gene oscillator recovers from a sudden phase-shift of 12 hours using a two-window coupling scheme . As described above , we assume for simplicity that the two coupling windows remain fixed with respect to the day/night cycle . The 12-hour phase shift is induced by initializing at dawn the oscillator state with the value it takes at dusk in the entrained regime . Figs . 7 ( A ) – ( B ) show that most of the lag is absorbed in the first 24 hours and the effect of the initial perturbation is hardly detectable after 48 hours . To design this coupling , we utilized the fact that modifying coupling strengths inside windows hardly affects adjustment . We could therefore choose their values so as to minimize the maximal residual phase shift after three days for all possible initial lags ( Fig . 7 ( C ) ) . Interestingly , we found that the best resetting behavior is obtained when the start time of the window of modified TOC degradation coincides with dawn . Phase locking in this example is globally stable . However , resetting becomes slow when the residual phase shift is under an hour and the residual phase shift is variable ( RMS phase error after 5 days is 25 minutes and maximum phase error is 1 hour ) , and ( Fig . 7 ( C ) ) . This inefficiency results in fact from the limitations of a model where the two parameters are modulated by a rectangular profile with fixed timing . Indeed , we will see later that impressive adjustment and resetting behavior can be simultaneously obtained when parameters are modulated with smooth profiles . Our numerical results thus show that a coupling scheme can at the same time be almost invisible when the oscillator is in phase with its forcing cycle and effective enough to ensure resetting when the oscillator is out of phase . By invisible , we mean that the time profile remains in a close neighborhood of the uncoupled one , so that the only effect of coupling is to fix the phase of the oscillation with respect to the day/night cycle . Why would it be beneficial for a circadian oscillator to be minimally affected by light/dark alternation in normal operation ? A tempting hypothesis is that while daylight is essential for synchronizing the clock , its fluctuations can be detrimental to time keeping and that it is important to shield the oscillator from them . If the entrained temporal profile remains close to that of an uncoupled oscillator at different values of the coupling parameter , then it will be naturally insensitive to fluctuations in this parameter . To gain insight into this fundamental question , we subjected the fully coupled and occasionally coupled clock models to fluctuating daylight . With the light input pathway unknown , we must allow for the fact that light fluctuations may be strongly attenuated upon reaching the Toc1-Cca1 loop . For example , the light signal could be transmitted through an ultrasensitive signaling cascade with almost constant output above an input threshold close to daylight intensities at dawn . The core oscillator would then be subjected to a driving cycle much closer to a perfect square wave than the intensity profile . We thus considered varying modulation depths for the core oscillator parameters to reflect this possible attenuation . Although the two types of model adjust experimental data equally well when subjected to a regular alternation , they have completely different responses to daylight fluctuations . In Fig . 8 , we assume that light intensity is constant throughout a given day but varies randomly from day to day . For almost zero modulation , the fully coupled model of Fig . 2 ( B ) maintains relatively regular oscillations of varying amplitude ( Fig . 8 ( B ) ) . When parameter values are modulated by only a few percent , however , this model behaves erratically: oscillations stop for a few days , expression peaks occur a few hours in advance , … ( Fig . 8 ( C ) ) . A circadian clock similarly built would be adversely affected by fluctuations in daylight intensity even with very strong attenuation in the input pathway . In contrast to this , the two occasionally coupled oscillators of Fig . 3 keep time perfectly even for extreme fluctuations ( Figs . 8 ( D ) – ( E ) ) and generate oscillations that are indistinguishable from those of the free-running oscillator which adjusts experimental data recorded under strictly periodic light/dark alternation . Obviously , this extends to models combinining the two windows , such as the one used in Fig . 7 . This simple model thus describes a robust clock that is both sensitive to phase shifts in the forcing cycle and insensitive to fluctuations in intensity . We also studied the effect of fluctuations at shorter time scales . When light intensity was varied randomly each hour , but with the same mean intensity each day , the permanently coupled model was still affected but much less than in Fig . 8 ( Fig . S6 ) . The results described above may seem to rely on the FRP being equal to 24 hours . When the FRP is smaller or larger , coupling is required to achieve frequency locking and pull the oscillation period to 24 hours . To investigate this more general case , we scaled kinetic constants of the free-running model used in Fig . 2 ( B ) to shift the FRP to 25 or 23 . 5 hours . In both cases ( short FRP and long FRP ) , we could find models with gated coupling that adjust perfectly the experimental data with a period of 24 hours ( Fig . 9 ) . These models are very similar to those shown in Fig . 3 , the only notable difference being that coupling windows are shifted so that the induced resetting corrects for the period mismatch . Interestingly , the coupling windows for a FRP of 25 hours are located near the light/dark and dark/light transitions . We found that these coupling schemes were also very robust to daylight fluctuations ( Fig . S7 ) , indicating that the modulation ratio ( equal to 3 for the two windows ) is not critical . We also found that without taking adjustment into account , the free running oscillator is entrained by the coupling windows shown in Fig . 9 ) within a wide range of modulation ratios , from a lower threshold of 1 . 05 ( resp . 1 . 25 ) for the FRP equal to 23 . 5 hours ( resp . 25 hours ) to an upper threshold of 13 for both FRPs . With a modulation ratio of 3 , free-running oscillators with FRPs ranging from 22 to 29 hours could be entrained . Gating of light input by rectangular profiles does not reflect the fact that the concentration of the mediators modulating the oscillator typically vary in a gradual way . The existence of nested coupling windows such that models with shorter windows can adjust data with larger parameter modulation ( see Fig . 4 ) suggests investigating the action of smooth gating profiles , with maximal parameter modulation near the center of the window . To this end , we considered 24-hour periodic , Gaussian-shaped , modulation profiles defined by: and , which are parameterized by the times of maximal modulation , , the coupling durations , and the modulation depths and . To assess whether good data adjustment and resetting behavior could be obtained simultaneously , these six parameters were chosen so as to minimize the RMS residual phase error 5 days after an initial random phase shift ranging from −12 to 12 hours ( see Methods ) . Note that this naturally forces adjustment to experimental RNA profiles . The behavior of the model using the optimized modulation profiles ( Figs . 10 ( A ) – ( B ) ) confirms the findings obtained with rectangular profiles ( Fig . 10 ) . The entrained RNA and protein time profiles shadow that of the reference free-running oscillator , with little evidence of the coupling ( Figs . 10 ( C ) – ( E ) ) . Phase resetting in response to a phase shift is excellent ( Fig . 10 ( F ) ) : RMS ( resp . maximum ) residual phase shift after 5 days is 2 . 4 min ( resp . , 10 min ) . This is all the more remarkable as the Gaussian shape of the modulation profile is artificial , which shows that the dynamical mechanism exploited here is robust and relatively insensitive to the shape of the modulation profile . Moreover , the oscillator is extremely resistant to daylight fluctuations ( Fig . 10 ( F ) ) . In spite of its simplicity , the two gene-oscillator studied here thus fulfills key requirements for a circadian oscillator when modulated with the right timing .
Our findings illustrate how mathematical modeling can give insight into the architecture of a genetic module . Not only can expression profiles of two Ostreococcus clock genes be reproduced accurately by a simple two-gene transcriptional feedback loop model , but furthermore excellent adjustment of mRNA data is provided by a free-running model . This counterintuitive result can be explained if coupling to the diurnal cycle occurs during specific temporal windows , where unidentified mediators interact with the TOC1-CCA1 oscillator in such a way that it experiences negligible forcing when it is in phase with the day/night cycle , and strong resetting when it is out of phase . We could exhibit many coupling schemes compatible with experimental mRNA temporal profiles , differing by the coupling mechanism or by the window timing . This indicates that identification of the actual light input pathway will require additional experimental data . Our analysis strongly supports the conjecture that Ostreococcus genes Cca1 and Toc1 are the molecular components of an oscillator at the core of Ostreococcus clock but does not exclude that other coupled oscillators or feedback loops exist . Why would a circadian oscillator decouple from the day/night cycle when in phase with it so as to generate quasi-autonomous oscillations ? A natural hypothesis is that this protects the clock against daylight fluctuations , which can be important in natural conditions [42] . In a vast majority of numerical simulations and experiments on circadian clocks reported in the literature , the day/night cycle is taken into account through a perfect alternation of constant light intensity and darkness . However , this is somehow idealized , as the primary channel through which clocks get information about Earth rotation , namely daylight , is variable . In nature , the daylight intensity sensed by an organism depends not only on time of day but also on various factors such as sky cover or , for marine organisms such as Ostreococcus , the distance to sea surface and water turbidity , which can affect perceived intensity much more than atmosphere . Therefore , the light intensity reaching a circadian clock can vary several-fold not only from one day to the next but also between different times of the day . A clock permanently coupled to light is also permanently subjected to its fluctuations . Depending on the coupling scheme , keeping time may become a challenge when fluctuations induce phase resettings and continuously drive the clock away from its desired state . Indeed , we found that a mathematical model with properly timed coupling windows was insensitive to strong light intensity fluctuations while a permanently coupled model became erratic even for very small coupling strengths . For simplicity , we only tested the robustness of a model with modulated TOC1 and CCA1 protein degradation . However , it should be stressed that all other light-coupling mechanisms that were found to be robust with respect to adjustment ( see Fig . 5 and Fig . S4 ) are naturally also robust with respect to daylight fluctuations . Indeed they adjust the experimental data for varying coupling strengths at fixed window timings . This indicates that the limit cycle is insensitive to variations in the coupling strength , which is the key to the robustness to daylight fluctuations . Another interesting result from our numerical simulations is that the most disruptive fluctuations are the variations in intensity from one day to the other , since their time scale matches the oscillator period . Indeed , faster or slower fluctuations are easily filtered out . These results lead to enquire whether similar designs exist in other circadian clocks . Although the importance of this problem was noted some time ago [42] , the robustness of circadian clocks to daylight fluctuations and how this constraint shapes their molecular architecture have been little studied until very recently [43] , [44] . The discussion on how genetic oscillators can keep daytime has essentially focused on the most important sources of noise under constant conditions : temperature variations [40] , [45] , [46] or fluctuations in concentration due to small numbers of molecules [47] , [48] . However , an operating clock is naturally subjected to an external forcing cycle , which is yet another source of fluctuations . We thus conjecture that a circadian clock must be built so as to be insensitive to daylight intensity fluctuations when entrained by the day/night cycle , just as it is insentitive to molecular or temperature fluctuations , and that this can be achieved by keeping the oscillator as close to the free-running limit cycle as possible , scheduling coupling at a time when the oscillator is not responsive . An important consequence of this principle is that it allows us to discriminate between different possible coupling mechanisms for a given model , as our analysis revealed dramatic differences in the ability of different parametric modulations to buffer fluctuations . It also allows us to determine the preferred timing for a given coupling mechanism , which may prove very helpful when trying to identify the molecular actors which mediate the light information to the clock . When the FRP is close to 24 hours , as in much of our analysis , it is easy to understand why robustness to daylight fluctuations requires that the forced oscillation shadows the free-running solution . Robustness manifests itself in the time profile remaining constant when subjected to random sequences of daylight intensity . This includes strongly fluctuating sequences as well as sequences of constant daylight intensity at different levels . Thus , the oscillator response should be the same at high and low daylight intensities , which implies that the solution must remain close to the free-running one as forcing is increased from zero . Note that this only holds in entrainment conditions , where coupling is not needed . When the clock is out of phase , strong responses to forcing are expected , with resetting being faster as forcing is stronger . When the natural and external periods are significantly different , the problem may seem more complex as coupling is required to correct the period mismatch . There is a minimal coupling strength under which the oscillator is not frequency-locked and entrainment cannot occur . Nevertheless , we showed that timing the coupling windows properly is as effective for oscillators with FRP of 23 . 5 and 25 hours as for the 24-hour example we had considered . Again , the forced solution remains close to the free-running limit cycle even if proceeding at a different speed to correct the period mismatch . This also shows that FRP is not a critical parameter for adjustment of the experimental data used here . A consequence of the small deviation of the limit cycle from the free-running one when coupling strength is varied is that oscillations should vary little upon a transition from LD to LL or DD conditions ( see , e . g . , Figs . 9 ( G ) – ( H ) ) . We searched the litterature for examples of such behavior . Ref . [13] provides a interesting comparison of models for the Drosophila and Neurospora circadian clocks which is illustrative for our discussion . In this study , the variation in amplitude is much less pronounced for the Drosophila model than for the Neurospora one ( see Fig . 2 of [13] ) . Concurrently , the sensitivity of the phase of the entrained oscillations to variations in the light-controlled parameter is much smaller for the Drosophila model ( see Fig . 3 of [13] ) , which is a necessary condition for robustness to daylight fluctuations . Another interesting comparison involves the one-loop and two-loop models of Arabidopsis clock [24] , [25] . The one-loop model clearly modifies its behavior upon entering DD conditions from LD ( see Fig . 5 of [24] ) while the two-loop model preserves its average waveform when transiting from LD to LL , except for the disappearance of the acute response to light at dawn ( see Fig . 6 of [25] ) . Thus , the two-loop model not only reproduces experimental data better but also seems more robust . The Drosophila and Neurospora clock models analyzed in [13] also differ in their response to forcing when their FRP is close to 24 hours [49] . A number of circadian models cannot be entrained when their FRP is too close to 24 hours because complex oscillations , period-doubled or chaotic ones , are observed easily for moderate to strong forcing . Indeed , it is expected that near resonance between the forcing and natural periods , the strong response exalts nonlinearities and favors complex behavior . Again , the Drosophila clock model appears to be more robust in this respect [49] . We stress that making the coupling invisible in entrainment conditions naturally addresses this issue . Dynamically uncoupling the oscillator from the diurnal cycle in entrainment conditions makes it immune both to fluctuations in daylight intensity and to destabilization in the face of strong forcing . An important problem is how a clock with occasional coupling can adjust to different photoperiods so as to anticipate daily events all along the year . We can only touch briefly this question here as it requires understanding how the temporal profile of the coupling windows changes with photoperiod and thus a detailed description of the unknown light input pathways and additional feedback loops that control the timing of these windows . The key point is that the phase of the entrained oscillations is controlled by the position of the coupling windows . Thus the role of light input pathways and additional feedback loops , whose internal dynamics will typically be affected by input from photoreceptors and feedback from the TOC1–CCA1 oscillator , is to time the coupling windows as needed for each photoperiod so that the correct oscillation timing is generated [35]–[37] . This question will be addressed in a future work , together with the analysis of the luminescence time series recorded for differents photoperiods . Our results also bring some insight into the recent observation that a circadian clock may require multiple feedback loops to maintain proper timing of expression peaks in response to noisy light input across the year [43] . We have shown here that a single two-gene loop can display impressive robustness to daylight fluctuations when its parameters are modulated with the right timing . As noted when discussing the response to different photoperiods , this requires the presence of additional feedback loops to generate the biochemical signal needed to drive the core oscillator appropriately , and which we have not yet identified and modeled in Ostreococcus . Robustness to fluctuations thus implies a minimal level of complexity . Finally , robustness to intensity fluctuations may explain why it is important to have a self-sustained oscillator at the core of the clock , as a forced damped oscillator permanently needs forcing to maintain its amplitude , and is thereby vulnerable to amplitude fluctuations . Confining the dynamics near the free-running limit cycle allows to have a pure phase dynamics for the core oscillator , uncoupled from intensity fluctuations . Understanding how to construct it will require taking into account the sensitivity of the free-running oscillator to perturbations across its cycle [50] . A simple organism as Ostreococcus can apparently combine mathematical simplicity with the complexity of any cell . The low genomic redundancy of Ostreococcus is certainly crucial for allowing accurate mathematical modeling , leading to better insight into the clock workings . Ostreococcus therefore stands as a very promising model for circadian biology , but also more generally for systems biology .
A minimal mathematical model of the transcriptional loop where Toc1 activates Cca1 which represses Toc1 , consists of the following four differential equations: ( 2a ) ( 2b ) ( 2c ) ( 2d ) Eqs ( 2 ) describe the time evolution of mRNA concentrations and and protein concentrations and for the Cca1 and Toc1 genes , as it results from mRNA synthesis regulated by the other protein , translation and enzymatic degradation . Toc1 transcription rate varies between at infinite CCA1 concentration and at zero CCA1 concentration according to the usual gene regulation function with threshold and cooperativity . Similarly , Cca1 transcription rate is ( resp . , ) at zero ( resp . , infinite ) TOC1 concentration , with threshold and cooperativity . Translation of TOC1 and CCA1 occurs at rates and , respectively . For each species , the Michaelis-Menten degradation term is written so that is the low-concentration degradation rate and is the saturation threshold . Model ( 2 ) has 16 free continuously varying parameters besides the cooperativities and which can be set to the integer values 1 or 2 by the adjustment procedure . mRNA concentrations are determined experimentally only relative to a reference value and protein profiles are not adjusted . Therefore , two solutions of Eqs . ( 2 ) that have the same waveforms up to scale factors are equivalent . Therefore , we can eliminate four parameters by scaling Eqs . ( 2 ) , with only 12 free parameters controlling adjustment when parameters do not vary in time , which optimizes parameter space exploration . Then parameters are rescaled so that the maximum value of protein profiles is 100 nM , the maximum value of Cca1 mRNA profile is 10 nM , and the Toc1 and Cca1 mRNA maximum values are in the same proportion as in microarray data . This makes it easier to compare regulation thresholds and degradation saturation thresholds relative to the maximum values of the four concentrations . When the number of modulated parameters is , parameter space is -dimensional . Adjustment was carried out by using a large number of random parameter sets as starting points for an optimization procedure based on a Modified Levenberg–Marquardt algorithm ( routine LMDIF of the MINPACK software suite [51] ) . Goodness of fit for a given parameter set was estimated by the root mean square ( RMS ) error between experimental and numerical mRNA levels , in logarithmic scale . Numerical integration was performed with the SEULEX algorithm [52] . Adjustment was carried out with 14 ( resp . 2 ) Quad-Core Intel Xeon processors at 2 . 83 GHz during 72 hours for the 28-dimensional ( resp . 12-dimensional ) parameter space . Convergence was checked by verifying that the vicinity of the optimum was well sampled . In the uncoupled case , the ODE system is invariant under time translation so that its solutions are defined up to an arbitrary phase . An additional routine was then used to select the best-fitting phase . To study the effect of daylight fluctuations , parameters were modulated as follows . is the randomly varying light intensity , with the reference level . We define the reference modulation depth of the parameter taking value at standard light level and in dark as . modifies modulation depth according to , where quantifies sensitivity to light variation . The modified modulation depth fixes a new value for the day value , the dark value being unchanged . For models with occasional coupling , we use similar definitions with dark and light parameter values replaced by parameter values respectively outside and inside of the coupling window . The CCA1 stability modulation inside the window starting after dusk depends on the intensity of the previous day . The parameters of the Gaussian-shaped modulation profiles were determined by optimizing resetting . For all possible variable initial time lag ranging from −12 to 12 hours , the effect of the coupling scheme based on the two profiles modulating TOC1 degradation and CCA1 degradation was characterized as follows . The time lag was applied to the free-running cycle adjusting experimental data . Then , the coupling scheme was applied for one or 5 days . Finally , the coupling was switched off and the residual phase error was measured after two days . The set of six parameters defining modulation profiles were obtained as those which minimize RMS residual phase error across the 24-hour interval . | Circadian clocks keep time of day in many living organisms , allowing them to anticipate environmental changes induced by day/night alternation . They consist of networks of genes and proteins interacting so as to generate biochemical oscillations with a period close to 24 hours . Circadian clocks synchronize to the day/night cycle through the year principally by sensing ambient light . Depending on the weather , the perceived light intensity can display large fluctuations within the day and from day to day , potentially inducing unwanted resetting of the clock . Furthermore , marine organisms such as microalgae are subjected to dramatic changes in light intensities in the water column due to streams and wind . We showed , using mathematical modelling , that the green unicellular marine alga Ostreococcus tauri has evolved a simple but effective strategy to shield the circadian clock from daylight fluctuations by localizing coupling to the light during specific time intervals . In our model , as in experiments , coupling is invisible when the clock is in phase with the day/night cycle but resets the clock when it is out of phase . Such a clock architecture is immune to strong daylight fluctuations . | [
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] | 2010 | Robustness of Circadian Clocks to Daylight Fluctuations: Hints from the Picoeucaryote Ostreococcus tauri |
A central question in genomic imprinting is how a specific sequence is recognized as the target for epigenetic marking . In both mammals and plants , imprinted genes are often associated with tandem repeats and transposon-related sequences , but the role of these elements in epigenetic gene silencing remains elusive . FWA is an imprinted gene in Arabidopsis thaliana expressed specifically in the female gametophyte and endosperm . Tissue-specific and imprinted expression of FWA depends on DNA methylation in the FWA promoter , which is comprised of two direct repeats containing a sequence related to a SINE retroelement . Methylation of this element causes epigenetic silencing , but it is not known whether the methylation is targeted to the SINE-related sequence itself or the direct repeat structure is also necessary . Here we show that the repeat structure in the FWA promoter is highly diverse in species within the genus Arabidopsis . Four independent tandem repeat formation events were found in three closely related species . Another related species , A . halleri , did not have a tandem repeat in the FWA promoter . Unexpectedly , even in this species , FWA expression was imprinted and the FWA promoter was methylated . In addition , our expression analysis of FWA gene in vegetative tissues revealed high frequency of intra-specific variation in the expression level . In conclusion , we show that the tandem repeat structure is dispensable for the epigenetic silencing of the FWA gene . Rather , SINE-related sequence is sufficient for imprinting , vegetative silencing , and targeting of DNA methylation . Frequent independent tandem repeat formation events in the FWA promoter led us to propose that they may be a consequence , rather than cause , of the epigenetic control . The possible significance of epigenetic variation in reproductive strategies during evolution is also discussed .
Parental imprinting , mono-allelic gene expression depending on its parent-of-origin , is an epigenetic process known in mammals and flowering plants . In both mammals and plants , many imprinted genes are under control of DNA methylation , as their imprinting is abolished by mutations in DNA methyltransferase genes [1]–[3] . Interestingly , imprinted genes often contain sequences originated from parasitic sequences such as transposons and viruses [4]–[7] . As DNA methylation works as a defense mechanism against parasitic sequences [8]–[13] , the control of imprinted genes by DNA methylation may have evolved from defense mechanisms . Another feature of imprinted genes is their frequent association with tandem repeats [14]–[17] . Despite the strength of the association , evidence is limited concerning whether the repeat structure itself is important for imprinting [15] , [17] . The FWA gene in the flowering plant Arabidopsis thaliana is one of the most extensively studied systems linking the control of DNA methylation and imprinting . The FWA gene was originally identified through characterization of epigenetic mutants causing a heritable late-flowering phenotype . The phenotype was due to ectopic expression of the FWA gene in vegetative tissue [18]–[20] . In wild type plants , the FWA gene is silent in vegetative tissues and expressed specifically in the endosperm in an imprinted manner [3] . FWA silencing depends on cytosine methylation , as it is derepressed by mutations in the maintenance methylase gene MET1 [3] , [21] , [22] . In addition , the imprinting is established in the female gametophyte by a “one-way” activation , which depends on the DNA demethylase DEMETER [23] , [24] . In addition to these trans-acting components , a cis-requirement for the epigenetic FWA silencing has also been identified . Promoter of the FWA gene has two pairs of tandem repeats that are heavily methylated [20] . Transcription starts from this region when the methylation is lost [20] . The nucleotide sequence of this region is similar to a SINE retrotransposon [6] . Using artificial de novo methylation induced by double-stranded RNA , we previously showed that the critical methylated element corresponds to the SINE-related tandem repeats [25] . However , it is still unclear whether the SINE sequence per se can direct DNA methylation , or whether the tandem repeat structure is necessary for control of methylation and imprinted expression . Here we investigate the evolution and natural variation of FWA promoters in A . thaliana and five other Arabidopsis species . The results demonstrate that the tandem repeat structure is necessary neither for imprinted FWA expression , nor for vegetative FWA silencing . Instead , the SINE-related sequence itself appears to be the primary target of the epigenetic control , which might have subsequently induced frequent tandem repeat formation during evolution . In addition , considerable intra-specific variation was found in vegetative FWA expression , which might present sources for epigenetic variation in reproductive strategy .
We have previously shown that the target of epigenetic FWA silencing in A . thaliana is a SINE-related direct repeat [25] . In order to investigate the relationship between the structure of the FWA promoter and FWA expression , we identified FWA orthologues in three related Arabidopsis species , A . halleri , A . lyrata , and A . arenosa . We found that the gene structure , including coding regions as well as introns and promoter sequences , was conserved among these species and A . thaliana ( Figure S1 ) . Notably , SINE-like sequences were found in the FWA promoters of all four species , suggesting that the insertion of this sequence occurred before divergence of these species . Unexpectedly , however , we found that duplications in the FWA promoters were highly diverse both within and among species ( Figure 1 and Figure S2 ) . The two pairs of tandem repeats found in A . thaliana were not duplicated in the other species . On the other hand , the FWA promoters of A . lyrata and A . arenosa contain other tandem repeats , which spanned different regions within the SINE-related sequences ( Figure 1B , 1C , and Figure S2 ) . Comparison of the structure of the FWA promoter of these species revealed at least four independent duplication events: two in A . thaliana , one in A . arenosa , and one in A . lyrata . In A . lyrata , the repeat number of the FWA promoter differs between subspecies ( ssp . ) lyrata ( three copies ) and ssp . petraea ( four copies ) ( Figure 1 and Figure S2 ) . In A . halleri , no tandem repeat was found in the FWA promoter ( Figure 1 and Figure S2 ) . In A . thaliana , the FWA gene is silent in vegetative tissues and expressed in the endosperm in an imprinted manner ( maternal-origin-specific ) . Both the silencing of the paternally-derived copy and silencing in vegetative tissues depend on DNA methylation in the FWA promoter . As is the case in A . thaliana , FWA transcripts were detected in immature seeds in A . lyrata and A . halleri . To determine whether the FWA gene shows imprinted expression in these species , RNA was isolated from immature seeds after inter-strain crosses , and the origin of FWA transcripts was identified using sequence polymorphisms in the transcript . In both A . lyrata and A . halleri , the transcript detected was derived from the allele of maternal origin ( Figure 2 ) . For example , in A . lyrata , FWA transcripts of ssp . petraea and ssp . lyrata could be distinguished using polymorphisms in the transcript length ( Figure 2A and 2B ) , and transcript of only the maternal allele could be detected in both of the reciprocal crosses ( Figure 2B ) . The presence of maternal transcripts in seeds may reflect imprinted expression or transmission of transcripts from the female parent . In order to distinguish between these two possibilities , we used a female parent with two FWA alleles that could be distinguished by sequence ( Figure 2A ) , and FWA transcripts were examined in 40 individual seeds . The results show segregation of the two FWA alleles expressed in these seeds; 22 seeds showed FWA RNA from one allele of the female parent and 18 seeds from the other allele ( Figure 2C ) . This observation suggests that the FWA transcripts did not originate from maternal diploid tissues but from transcription of the maternally-derived alleles after meiosis , as is predicted in other imprinted genes [26] . Similarly , in A . halleri , we could only detect FWA transcripts from the maternal allele in both of the reciprocal crosses between ssp . halleri and ssp . gemmifera ( Figure 2D , 2E , and 2F ) . In 20 individual seeds from the ssp . halleri x ssp . gemmifera cross , the 11:9 segregation of the two maternal alleles completely matches the expression pattern ( Figure 2E ) . In summary , these results demonstrate that the FWA in both A . lyrata and A . halleri shows imprinted expression in immature seeds as it does in A . thaliana . These results are striking especially in A . halleri , because the FWA promoter of this species does not contain any tandem repeats ( Figure 1 ) . We conclude that the tandem repeat structure is not essential for the imprinting of the FWA gene . We next examined vegetative FWA expression in these species . Since A . halleri does not have tandem repeats in its FWA promoter , we were able to test whether the tandem repeat is necessary for vegetative silencing . In contrast to A . thaliana , in which the FWA gene is silent in vegetative tissues [20] , a low level of FWA transcript was often detected in the vegetative tissues of A . arenosa , A . lyrata , and A . halleri ( Figure 3 ) . Interestingly , vegetative FWA expression shows considerable variation at least at the subspecies level . We could detect the vegetative FWA transcript in two strains of A . lyrata ssp . lyrata but not in a strain of A . lyrata ssp . petraea ( Figure 3A , lanes 5 and 6 ) . Similarly , we could detect vegetative FWA transcripts in A . halleri ssp . halleri , tatrica , ovirensis , but not in nine out of eleven strains of ssp . gemmifera ( Figure 3B and Figure S3 ) . Therefore , the tandem repeat structure is not essential for epigenetic silencing of FWA in vegetative tissues . The vegetative FWA silencing observed in strains of A . halleri ssp . gemmifera and A . lyrata ssp . petraea does not seems to be due to loss of promoter function , because their FWA gene was expressed in immature seeds ( Figure 2F ) and in pistils ( Figure 3A right panel ) , which contain female gametophytes . Thus , the vegetative FWA silencing is likely to have an epigenetic basis . The variation in the vegetative FWA expression was heritable; the FWA gene remained silent in the self-pollinated progeny of those plants with silent FWA , while vegetative FWA expression was detected in other strains growing in parallel ( not shown ) . We further examined FWA expression in two allotetraploid species , A . kamchatica ( ssp . kamchatica and kawasakiana ) and A . suecica . The former is an allotetraploid between A . lyrata and A . halleri [27] , and the latter between A . arenosa and A . thaliana [28] . We were able to detect vegetative FWA expression in A . kamchatica ( ssp . kamchatica and kawasakiana ) ( Figure 4A lane 1 ) . As expected from its allotetraploid origin , A . kamchatica has two copies of FWA genes , with one copy being structurally similar to the A . lyrata FWA gene and the other similar to the A . halleri FWA gene ( Supplementary Figure S4A and S4C ) . We examined the expression of each copy using polymorphisms between them . In both ssp . kamchatica and ssp . kawasakiana , the A . halleri-like FWA copy was expressed in leaves , while the A . lyrata-like copy was silent ( Figure 4B lane 1 ) . Interestingly , the lyrata-type copy was also silent in pistils , which contain the female gametophytes ( Figure 4B lane 2 ) , leaving open the possibility that the silencing of the lyrata-type copy was not epigenetic but genetic ( for example , by a mutation in the promoter ) . We were also able to detect vegetative FWA expression in A . suecica ( Figure 4C lane 1 ) , an allotetraploid between A . arenosa and A . thaliana . As expected , A . suecica has two copies of FWA genes , which are structurally similar to the FWA gene of either A . arenosa or A . thaliana ( Figure S4B and S4C ) . Vegetative FWA expression of A . suecica was mainly from the arenosa-type copy; we could not detect vegetative expression of the thaliana-type copy ( Figure 4C and 4D ) . On the other hand , both arenosa-type and thaliana-type copies were expressed in pistils ( lane 2 of Figure 4C and 4D ) . Therefore , the thaliana-type copy was specifically silenced in vegetative tissues , as is the case in the parental species A . thaliana . In the allotetraploids , vegetative FWA expression tends to be stronger than that in their parental species . In order to evaluate the direct effects of hybridization , we examined FWA expression in artificially generated inter-specific hybrids . In hybrids between A . thaliana and A . lyrata ssp . lyrata , expression level of the lyrata FWA in leaves was increased significantly compared to that in its direct parent A . lyrata ssp . lyrata ( Figure 5A and 5C ) . In hybrids between A . thaliana and A . halleri ssp . gemmifera strain Tada , the halleri–like copy was expressed ( Figure 5B and 5C ) . This result is striking considering that the FWA was completely silent in vegetative tissues of the parent strain Tada ( Figure 5B , lane 1–3 ) . On the other hand , in both the A . lyrata-A . thaliana and A . halleri-A . thaliana hybrids , the A . thaliana copy remained silent ( Figure 5C ) . In addition , in the synthetic allotetraploid of A . arenosa and A . thaliana ( synthetic A . suecica; reference [29] ) , the arenosa-type copy was expressed while the thaliana-type copy was silent ( Figure 5D ) . In summary , the FWA genes tend to be transcriptionally activated in the inter-specific hybrids . This phenomenon might be related to previous finding that the imprinted genes , such as PHERES1 and MEDEA , show abnormal expression patterns in hybrids between A . thaliana and A . arenosa [30] . In contrast to the expression of the lyrata- , halleri- or arenosa-derived FWA copies in the hybrids , thaliana-derived copies remained silent in all the hybrids . These observations are consistent with that in the situation in natural allotetraploids; the thaliana-derived copy was most stably silenced in the vegetative tissues of both the allotetraploids and hybrids . In A . thaliana , loss of DNA methylation in the FWA promoter induces release of epigenetic silencing . The tandem repeat is methylated in all 96 natural A . thaliana strains [31] . The methylated region of the FWA promoter precisely matched the tandem repeat regions and the methylation extends out of the SINE-related region to the end of the repeat [20] ( Figure 6A ) . We were therefore interested in whether the epigenetic silencing of the FWA is also related to DNA methylation in Arabidopsis species with less prominent repeat structure . Figure 6 and Table S1 show bisulfite-mediated genomic sequencing data demonstrating that the SINE-related region of the FWA promoter was methylated in all species examined , including A . halleri , indicating that the repeat structure is not necessary for directing DNA methylation to this region . CG-sites tend to be more heavily methylated than non-CG sites , as is the case in the FWA promoter of A . thaliana . The methylation level is high throughout the repeat region in A . thaliana , which shows the most stable silencing ( Figure 6 , Table S1 ) . Interestingly , intraspecific variation in the methylation level was found in A . lyrata ( Figure 6B ) . The methylation level tended to be negatively correlated with the expression level; it was highest in the strain Mue-1 ( ssp . petraea ) , which shows vegetative silencing of the FWA . In A . lyrata , the number of repeats in the FWA promoter correlated with the level of vegetative silencing . In A . lyrata ssp . petraea strain Mue-1 , which has four copies of the tandem repeat , the vegetative expression was much lower than that in the two strains of A . lyrata ssp . lyrata that have three copies of the tandem repeat ( Figure 3A and Figure S4A ) . The silencing also correlated with high level of promoter methylation ( Figure 7B ) . In order to test whether the correlation between copy number in the repeats and vegetative FWA silencing is found also in A . thaliana , we examined the structure of the FWA promoter and its expression in 96 natural strains of this species . All 96 strains had the long repeat , but the short repeat was not found in three strains , Fab-4 , Var2-1 , and Var2-6 . We then examined vegetative FWA expression in these strains and , as controls , 21 strains with two pairs of tandem repeats ( Figure 3C ) . Vegetative FWA expression was not detected in any of the 21 control strains , while two out of three strains lacking the short repeat showed a low level of vegetative FWA expression .
Here we reported variation in the structure and expression of the imprinted gene FWA in the genus Arabidopsis . The promoter sequence related to a SINE retroelement was found in the FWA locus of all Arabidopsis species examined . Most unexpectedly , the tandem repeat structure in this region is not essential for the epigenetic silencing of the FWA gene . The FWA promoter of A . halleri does not have the repeat structure , but it shows imprinted expression and vegetative silencing . Similarly , tandem repeats are often found in CpG islands of mammalian imprinted genes , but they are not always conserved between mouse and human [32] . In addition , deletion of a conserved direct repeat element upstream of H19 had no effect on imprinting [15] . One possible interpretation of these observations is that tandem duplications may be a consequence , rather than the cause , of mono-allelic expression . Consistent with this interpretation , we found four independent duplication events in the small region of the FWA promoter in closely related species , A . thaliana , A . lyrata , and A . arenosa . Silencing of the FWA gene tends to be stronger in A . thaliana than in other species . The majority of A . lyrata and A . halleri strains showed vegetative FWA expression . Vegetative FWA expression was also found in examined strains of A . arenosa , A . kamchatica and A . suecica . On the other hand , the FWA gene in A . thaliana was silent in all the examined 21 accessions that have two direct repeats . Vegetative FWA expression tends to be elevated after inter-species hybridization , the clearest example being the FWA gene of the A . halleri strain Tada . Although we could not detect vegetative transcripts in this strain , FWA transcript was detected after hybridization with A . thaliana . On the other hand , vegetative expression was not detectable for the A . thaliana-derived FWA gene , even after hybridization with A . halleri , A . lyrata , or A . arenosa . The thaliana-type FWA was also silent in the natural allotetraploid A . suecica . Stable silencing of the A . thaliana FWA in vegetative tissues might depend on the presence of tandem repeats in the promoter . Consistent with this conjecture , vegetative FWA expression , although at very low levels , was found in two of three natural accessions that do not have one of the two tandem repeats ( Figure 3 ) . The tandem direct repeats may facilitate the production of small RNA and targeting of DNA methylation to stabilize silencing [33] . Small RNA was detected in the FWA promoter of A . thaliana [6] . In this context , it might be interesting to see if small RNA is detectable corresponding to the FWA promoter of A . halleri , which does not have the tandem repeat . Results of modified transgene with various repeat structures of the FWA promoter suggest that the tandem repeat structure is effective in inducing de novo DNA methylation at least in a transgenic system [34] . Based on these observations , we propose a model for the evolution of the epigenetically controlled FWA gene ( Figure 7 ) . Tandem repeat structure does not appear to be essential for the imprinted expression , vegetative silencing , or targeting of DNA methylation in the FWA . Rather , methylation is directed to the SINE-related sequence , which functions as the core of the local heterochromatin . Subsequently , tandem repeats have been recurrently generated in this region during evolution . Repeat formation might be caused after replication arrest [35] in the epigenetically silent region . In addition , DEMETER DNA demethylase might induce tandem repeat by nick formation [23] when expressed in the embryonic cell lineage [36] . DNA methylation would have then spread to the region of the tandem repeat , which stabilizes epigenetic silencing . The methylation , especially in CG sites , function as an epigenetic mark heritable over multiple generations ( Figure 7 ) . Heritable epigenetic variation is an enigmatic genetic phenomenon , which is known both in mammals and plants [37] , [38] . The FWA gene in Arabidopsis has the potential to cause epigenetic variation in flowering time , and natural variation in vegetative FWA expression was found in this study ( Figure 3 ) . Sequence analysis of the FWA promoter in 96 natural strains of A . thaliana revealed a high level of variation in this region ( Table S2 and Figure S6 ) . C/G to T/A mutations are overrepresented , possibly reflecting high mutation rate in the methylated C to T [39] , [40] . Despite the high mutation rate , alleles of intermediate frequency are significantly underrepresented in this type of variation ( Tajima's D: −1 . 7078 , P<0 . 05 ) , suggesting that new mutations were rapidly eliminated ( Table S2 ) . Negative selection against mutation in the C/G sites may reflect an advantage of stable silencing of the FWA gene by cytosine methylation , especially in A . thaliana , which has a rapid life cycle . Unlike A . thaliana , other Arabidopsis species showed vegetative FWA expression in the majority of strains . The expression level was heritable but variable within species ( Figure 3 and Figure S3 ) . The rapid and potentially reversible changes in epigenetic states might represent an important source of variation in reproductive strategy .
The sources of the 96 natural accessions ( cs22660 ) of A . thaliana are described in Nordborg et al . [41] . The epigenetic late-flowering fwa mutant was induced in the ddm1-1 background and backcrossed to DDM1/DDM1 background as described previously [25] . The male-sterile mutant ( ms1-1 ) is a kind gift from Maarten Koornneef . A . lyrata ssp . lyrata pn3 was collected in Pores Knob , Wilkes County , NC . The A . lyrata ssp . lyrata MN47 was developed at Cornell University from material originally isolated by Charles Langley in Michigan , USA . The A . lyrata ssp . petraea strain Mue-1 , was collected in Muehlberg , Germany . A . halleri ssp . gemmifera Tada , OID06-6 , and Mino were isolated in Inagawa-cho , Osaka , Japan , Taka-cho , Hyogo , Japan , and Mino-shi , Osaka , Japan . A . halleri ssp . halleri H-RB was isolated in Bistrita , Romania , ssp . tatrica T-PLDH1 in Vysoke Tatry , Poland , ssp . ovirensis O-AUO26 in Karinthia , Austria . A . kamchatica ssp . kamchatica FJSB1 was isolated in Subashiri , Shizuoka , Japan , and ssp . kawasakiana Shirahama was isolated in Ohmi-shirahama , Shiga , Japan . A . suecica was from Sendai Arabidopsis Seed Stock Center ( JS7 ) . Synthetic suecica ( CS22665 and CS22666 ) and A . arenosa ( CS3901 ) are from Arabidopsis Biological Resource Center at Ohio State University . Sequences of all primers used are shown in Supplementary Text S1 . Genomic DNAs were isolated from leaves by Nucleon ( Amersham Biosciences , UK ) . The DNA fragments spanning the FWA gene in related species were amplified by PCR and cloned into pGEM-TEasy or pCR2 . 1-TOPO vector using the primers lyrata-7f and lyrata-10r for lyrata and arenosa alleles , lyrata-7f+lyrata-9r for halleri alleles , FWApro1+As-3 for thaliana alleles . In each strain , multiple clones were sequenced and regions of inconsistent sequences were directly sequenced from the genomic DNA again . Sequences of both alleles were determined in out-crossing species , such as A . halleri and A . lyrata . 96 ecotypes of the tandem repeat region was amplified using primer pair Ateco96F+Ateco96R , and their nucleotide sequences were determined directly from the genomic DNA . Data were analyzed using Sequencher ( Gene Codes Corporation , MI , USA ) . Harr plot analysis was performed with GENETYX-MAC software ( Software Development Co . , LTD , Tokyo , Japan ) . Unit size to compare was 10 bp , and dot plot matching number was 9 bp [42] . The sequence alignment was made using ClustalW ( http://www . ddbj . nig . ac . jp/search/clustalw-j . html ) . A phylogenetic tree was constructed by the neighbor joining method with K2P distance [43] , and bootstrap probabilities of 1 , 000 trials were calculated . Total RNA was isolated from leaves and pistils from open flowers using SV Total RNA Isolation system ( Promega , WI , USA ) . From 2 µg total RNAs , first strand cDNA was synthesized using random primers by a First-strand cDNA synthesis Kit ( Amersham , NJ , USA ) . FWA transcript was detected by RT-PCR of 40 cycles using the first strand cDNA as a template with primer pair FWA-RT-F2+FWA-RT-R1 . GAPC was used as control and amplified by RT-PCR of 25 cycles using primer pair GAP3+GAP5 . In A . suecica , allele-specific RT-PCR was performed using primer pair specific for FWA in A . thaliana ( AtFWA-RT-F1+AtFWA-RT-R1 ) and specific for FWA in A . arenosa ( FWA-RT-F5+AtFWA-RT-R4 ) . In hybrid between A . lyrata/A . halleri and A . thaliana , allele specific primer pair was used for RT-PCR to amplify FWA in A . lyrata/A . halleri ( FWA-RT-F5+AtFWA-RT-R5 ) and that of A . thaliana ( AtFWA-RT-F1+AtFWA-RT-R1 ) . The PCR condition was 95°C for 10 sec followed by 25 or 40 cycles of 95°C for 30 sec , 57°C for 30 sec , and 72°C for 30 sec . Total RNAs from one premature fertilized seed after 15DAP in A . lyrata and A . halleri were isolated by RNAqueous-Micro ( Ambion , Texas , USA ) . Using all of isolated total RNAs , first strand cDNA was synthesized using FWA-specific primer AlFWAcDNA-R by SuperScript III Reverse Transcriptase ( Invitrogen ) . FWA transcripts in seed of A . lyrata and A . halleri were amplified by RT-PCR of 35 cycles using the first strand cDNA as a template with primer pairs ( AhAlFWAcDNA-F2+lyrata2r ) and ( FWA-RT-F3+FWA-RT-R3 ) , respectively . Products from genomic DNA and mRNA could be distinguished by size . FWA transcript level was compared between two strains of A . kamchatica by real-time PCR ( Figure S5 ) with the GAP gene used as the internal control . The cDNA was amplified using SYBR Premix Ex Taq ( Takara Biomedicals , Japan ) on a LightCycler ( Roche , Rotkreuz , Switzerland ) . With the primer pairs FWAreal1+FWA-RT-R1 ( FWA ) and GAPreal2+GAPreal3 ( GAP ) . The PCR condition was 95 for 10sec followed by 25 ( GAP ) or 40 ( FWA ) cycles of 95°C for 5 sec , 55°C for 10 sec , and 72°C for 7 sec . Data were analyzed with LightCycler Software version 3 . 5 ( Roche ) . Bisulfite sequencing was performed according to Paulin et al . [44] . After chemical bisulfite reaction , PCR fragments of repeat region of FWA were amplified using primer pairs as follow . AtFWA; ( AtFWA-Bis-F1+AtFWA-Bis-R1 ) , AaFWA; ( AhFWA-Bis-F1+arenosaRTbisR ) , AlFWA; ( arenosaRTbisF+lyrataRTbisR ) , and AhFWA; ( AhFWA-Bis-F1+AhFWA-Bis-R2 ) . The amplified PCR fragments were gel purified by GENECLEAN III Kit ( Q-Biogene , CA , USA ) and cloned into pGEM-T easy vector ( Promega , WI , USA ) , and 10 independent clones were sequenced . Sequence data from this article have been deposited with DDBJ/GenBank/EMBL libraries under accession numbers AB363659–AB363674 , AB367805–AB367817 , and AB367818–AB367913 . | Genomic imprinting , mono-allelic gene expression depending on the parent-of-origin , is an epigenetic process known in mammals and flowering plants . A central question in genomic imprinting is how a specific sequence is recognized as the target for epigenetic marking . In both mammals and plants , imprinted genes are often associated with tandem repeats and transposon-related sequences , but the role of these elements in epigenetic gene silencing remains elusive . FWA is an imprinted gene in Arabidopsis thaliana expressed specifically in the female gametophyte and endosperm . The FWA promoter is comprised of two direct repeats containing a sequence related to a SINE retroelement . Methylation of this element causes epigenetic silencing , but it is not known whether the methylation is targeted to the SINE-related sequence itself or the direct repeat structure is necessary . Here we show that the direct repeat structure is highly diverse in species within the genus Arabidopsis . Unexpectedly , we found that the direct repeat structure is dispensable for the epigenetic silencing and methylation of the FWA promoter . Rather , the SINE-related promoter sequence is sufficient for these features . Frequent independent formation of the tandem repeats suggests that they may be a consequence of the epigenetically controlled system . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [
"genetics",
"and",
"genomics/epigenetics",
"plant",
"biology/plant",
"genetics",
"and",
"gene",
"expression"
] | 2008 | Evolution and Control of Imprinted FWA Genes in the Genus Arabidopsis |
Leptospirosis is the most widespread zoonosis . Chronic human infection and asymptomatic colonization have been reported . However , renal involvement in those with leptospira chronic exposure remains undetermined . In 2007 , a multistage sampling survey for chronic kidney disease ( CKD ) was conducted in a southern county of Taiwan , an area with a high prevalence of dialysis . Additionally , an independent cohort of 88 participants from a leptospira-endemic town was followed for two years after a flooding in 2009 . Risks of CKD , stages of CKD , associated risk factors as well as kidney injury markers were compared among adults with anti-leptospira antibody as defined by titers of microscopic agglutination test ( MAT ) . Of 3045 survey participants , the individuals with previous leptospira exposure disclosed a lower level of eGFR ( 98 . 3±0 . 4 vs 100 . 8±0 . 6 ml/min per 1 . 73 m2 , P<0 . 001 ) and a higher percentage of CKD , particularly at stage 3a-5 ( 14 . 4% vs 8 . 5% ) , than those without leptospira exposure . Multivariable linear regression analyses indicated the association of leptospiral infection and lower eGFR ( 95% CI -4 . 15 to -1 . 93 , P < 0 . 001 ) . In a leptospiral endemic town , subjects with a MAT titer ≥400 showed a decreased eGFR and higher urinary kidney injury molecule–1 creatinine ratio ( KIM1/Cr ) level as compared with those having lower titers of MAT ( P<0 . 05 ) . Furthermore , two participants with persistently high MAT titers had positive urine leptospira DNA and deteriorating renal function . Our data are the first to show that chronic human exposure of leptospirosis is associated significantly with prevalence and severity of CKD and may lead to deterioration of renal function . This study also shed light on the search of underlying factors in areas experiencing CKD of unknown aetiology ( CKDu ) such as Mesoamerican Nephropathy .
Chronic kidney disease ( CKD ) has an increasing prevalence worldwide [1] . According to the recent report on the global burden of diseases , there were 16 . 3 CKD-associated deaths per 100 000 individuals in 2010 , ranking 18th in the list of 86 causes . Compared to its ranking of 27th in 1990 , the rate of increasing has been only second to HIV and AIDS [2] . To reduce the global burden of CKD , effective strategies for the detection and prevention of CKD are needed . Diabetes and hypertension are the leading causes of CKD in all developed countries and in some developing countries [1 , 3] . In the developing world , besides environmental and occupational exposure to chemicals , infections are important causes of renal failure [3] . Leptospirosis , caused by the pathogenic spirochete Leptospira , is the most widespread zoonosis throughout the world , particularly in tropical and subtropical regions [4] . This is an important re-emerging infectious disease with a huge public health impact because of its increasing incidence and epidemic proportions [5] . Almost every mammal , but mainly rodents , can serve as a carrier of leptospira in the proximal renal tubules of the kidneys , from which leptospira are shed into the urine [4 , 6] . The pathogen is transmitted to humans through contaminated soil , water , or infected animal urine . Multiple organ involvement [7] may be encountered in acute severe leptospirosis , and renal involvement is commonly characterized by tubulo-interstitial nephritis and tubular dysfunction [8–10] . Besides protean acute presentations of leptospirosis , the possibility of chronic human infection was suggested with only sporadic cases [11] , such as late onset uveitis with leptospiral DNA amplified from aqueous humor [12] , central sleep apnea due to chronic neuroleptospirosis [13] and a recent report of neuroleptospirosis diagnosed by next-generation sequencing [14] . Recently , asymptomatic human renal colonization of leptospira in an area of high disease transmission was reported [15] . In the Central American nations where leptospirosis is endemic , leptospirosis was speculated as one of the possible causes of Mesoamerican nephropathy , a form of chronic kidney disease with unknown origin prevailed in young male agricultural workers [16] . However , the pathogenic significance , such as chronic kidney damage , is uncertain . In the current study , we performed a community-based survey to evaluate the risk of CKD in participants with leptospiral infection . Moreover , a two-year cohort study was conducted in the region with high transmission rates of leptospiral diseases after a natural flood . We postulated that subjects with leptospiral infection , as defined by positive microscopic agglutination test ( MAT ) , possessed an increased risk of CKD compared with those without leptospiral infection .
This study complied with the guidelines of the Declaration of Helsinki and was approved by the Medical Ethics Committee of Chang Gung Memorial Hospital , a tertiary referral center located in the northern part of Taiwan . Approval from the Institutional Review Board was obtained with specific written informed consent from patients . For any participants under the age of 18 , a parent or guardian provided informed consent . Furthermore , not only were all data securely protected ( by delinking identifying information from the main data sets ) and made available only to investigators , but they were also analyzed anonymously . Finally , all primary data were collected according to procedures outlined in epidemiology guidelines that strengthen the reporting of observational studies . In 2007 , a single-time active surveillance for leptospirosis was performed on residents older than age 15 years ( n = 1 , 026 , 288 ) in a Southern County of Taiwan . A multistage , stratified sampling method was used for selecting 3000 participants from the Household Register Database . In the first stage , in addition to the major city comprising 27 . 3% of the county population , 8 of the 27 county villages were randomly selected . In the next stage , a total of 50 districts ( Li; the smallest unit of administration ) from the city and the eight chosen villages were selected based on the sampling probability proportional to the population size of the city or the selected village . In the final stage , 60 participants were randomly selected from each of the 50 selected districts . Assuming a response rate of approximately one sixth , 18 , 000 participants were selected by the abovementioned approach and invited for the CKD screening program . In August 2009 , Typhoon Morakot flooding led to a biggest local outbreak of leptospirosis in the leptospira-endemic town within the Southern County in recent years [17 , 18] . To evaluate the long-term health effect of leptospiral infection , a baseline survey was conducted on a cohort of the town residents three months after the typhoon in 2009 . All cohort members were invited again for a follow-up visit in 2011 . No known acute leptospirosis record was reported in these residents . Blood , urine , and biochemical tests were performed on the study participants at enrolment . The MAT , a gold standard test for serological investigation and diagnosis in leptospirosis , was applied to sera of all participants , with most prevalent serovar . As Leptospira santarosai serovar Shermani is the major and most prevalent servoar in Taiwan and up to 72 . 2–77 . 3% of acute infection was related to this serovar [8 , 19] , MAT for this serovar was performed for analysis and expressed as anti-leptospira antibody seropositivity . MAT titers were reported as the reciprocal of the number of dilutions still with 50% of live bacterial antigen agglutination [20] . Cases were defined as sero-positive given a MAT titer ≥ 1: 100 , indicative of past exposure [4] . Outcomes were renal function , CKD and stages of CKD . CKD was diagnosed according to the KDIGO 2012 Clinical Practice Guidelines and classified based on eGFR ( estimated glomerular filtration rate ) category and albuminuria category [21] . Microalbuminuria was defined as a urinary albumin-to-creatinine ratio of 30 mg/g or higher using the first-morning urine . The eGFR was calculated using the Chronic Kidney Disease Epidemiology Collaboration ( CKD-EPI ) equation , which is more accurate than the Modification of Diet in Renal Disease Study equation [22] . In the prospective cohort study , deterioration of renal function and kidney injury biomarkers are two additional outcomes . Four different biomarkers were applied in 2011 , including serum and urine neutrophil gelatinase-associated lipocalin ( NGAL ) , kidney injury molecule–1 creatinine ratio ( KIM–1/Cr ) , and monocyte chemoattractant protein–1 ( MCP–1 ) . Urine DNA was extracted from the Cohort participants and tested for leptospira DNA detection using PCR primer sets as previously described [23 , 24] . For the K-County study population , participant characteristics were described overall and by the prevalence of a positive leptospiral serum testing result ( as defined by MAT titer ≥ 1:100 ) . To reflect the multi-stage sampling scheme for the K-County study population , survey-based population estimates of participant characteristics were weighted by sampling probabilities [25] . Continuous variables were presented as mean ± SD and compared between groups of subjects by t-test or ANOVA whenever appropriate . Categorical factors were displayed in weighted percentages , and the Pearson chi-squared test or Fisher’s Exact test was used to compare these covariates among groups . A survey-based linear regression on the continuous eGFR score was used in the univariate and multivariate models to appropriately account for the multistage , stratified probability sampling procedure . Regardless of the statistical significance in the univariate models , all of the variables were retained in the multivariable models to adjust for potential confounding . Data were further stratified into two groups: DM ( diabetes mellitus ) and NDM ( non-diabetes mellitus ) , and multivariate analyses were performed separately in each group . For the W-Township cohort , demographics and clinical characteristics were compared among subjects who exhibited negative , low ( MAT titer 1:100–200 ) or high ( MAT titer ≥ 1:400 ) titer testing results at baseline . The eGFR scores of the same cohort were compared between 2009 and 2011 , which was further presented among negative , low , and high MAT titers . The difference in the pre- and post- eGFR associated with MAT titer change was also evaluated . All statistical analyses were performed using Stata software , version 12 . 0 ( Stata Corp . , College Station , TX ) . A two-sided significance level at 0 . 05 was considered statistically significant .
The community-based , cross-sectional survey included 3 , 045 participants from the chosen southern county of Taiwan in 2007 , with a response rate of approximately 16 . 9% . The mean age of the sample was 47 . 5 years and the mean age of the sampling pool population was 46 . 6 years . Table 1 shows weighted results of the demographics , clinical characteristics and biomedical tests of the overall study population and by the MAT testing results . The anti-leptospira antibody-positive cases were older than anti-leptospira antibody-negative ones ( 47 . 8 vs . 45 . 0 years , P-value<0 . 01 ) . The anti-leptospira antibody positive patient population also had a 1%-higher prevalence of diabetes mellitus ( 5 . 7% vs . 4 . 6% , P-value<0 . 01 ) . However , the anti-leptospira antibody negative patient population had a higher prevalence of liver disease ( 5 . 2% vs . 7 . 6% , P-value<0 . 01 ) associated with higher positive rate of HBsAg ( 12 . 1% vs . 13 . 6% , P-value 0 . 012 ) and anti-HCV Ab ( 3 . 9% vs . 5 . 4% , P-value 0 . 02 ) . Patients with positive anti-leptospira antibody disclosed a 2% lower GFR estimated by CKD-EPI ( 98 . 3 ml/min/1 . 73m2 vs . 100 . 8 ml/min/1 . 73m2 , P-value<0 . 01 ) . Fig 1 shows the prevalence and proportion of CKD stages in anti-leptospira antibody positive and negative groups . The prevalence of CKD is significantly higher in anti-leptospira antibody positive group . Those individuals with positive anti-leptospira antibody disclosed higher percentage of CKD than those with a negative anti-leptospira antibody , particularly at stage 3a-5 ( 14 . 4% vs 8 . 5% ) . Both male and female participants with positive anti-leptospira antibody have lower eGFR . In addition to exposure to Leptospira , important characteristics strongly associated with lower eGFR was included in the variables such as diabetes mellitus , hypertension , cardiovascular disease , gout , urinary tract infection , metabolic syndrome , Chinese herbs , and analgesics . Of the 18 variables ( Table 2 ) , anti-leptospira antibody serology ( serum positive or serum negative ) is one of the 13 variables related to lower eGFR by univariate linear regression analyses . After adjusting for 17 variables , multiple linear regression analyses revealed that subjects , with a positive anti-leptospira antibody , scored 3 less points than those with a negative anti-leptospira antibody ( -3 . 0 , 95% CI = -4 . 2 , -1 . 9; P-value <0 . 001 ) . Table 3 revealed the independent factors for deterioration of eGFR in DM and NDM . Leptospiral infection , age , hypertension , and the use of Chinese herb were significantly associated with lower eGFR in both DM and NDM groups . After typhoon Morakot , we obtained data for 101 participants who had experienced the typhoon flooding without obvious clinical symptoms in one township at the southern county in 2009 . As of 2011 , 88 participants had been followed-up since 2009 , 86 . 4% of whom were positive for anti-leptospira antibody at baseline . Among these 88 subjects , 12 were negative for anti-leptospira antibody ( mean age 61 . 7 years ) , 41 having an MAT titer between 100 and 200 ( mean age 56 . 5 years ) , and 35 with MAT titer at least 400 ( mean age 53 . 1 years , Table 4 ) . The prevalence of diabetes mellitus , hypertension , micro-albuminuria did not show significant differences among three groups . Neither did subjects within three groups display significant differences in serum levels of creatinine , eGFR by CKD-EPI , or uric acid ( Table 4 ) . eGFR by CKD-EPI of every participant was followed in 2011 ( Fig 2 ) . All these cases have significantly lower eGFR in 2011 ( 102 . 9 ± 18 . 3 ml/min/1 . 73m2 ) than in 2009 ( 105 . 7 ± 17 . 4 ml/min/1 . 73m2 ) . In subgroup analysis , eGFR by CKD-EPI did not show a significant difference among three groups in 2009 . However , in 2011 , cases with MAT titer above 400 had , on average , a significantly lower eGFR ( 92 . 9 ± 15 . 8 ml/min/1 . 73m2 ) than that for participants with an MAT titer of 100–200 ( 105 . 9 ± 19 . 5 ml/min/1 . 73m2 ) and those with a negative MAT ( 104 . 7 ± 16 . 7 ml/min/1 . 73m2 , P-value = 0 . 039 ) . Since cases with MAT titer above 400 in 2011 all derived from cases with MAT titer above 400 in 2009 , we further divided cases into three different groups: group 1: MAT≥400 in 2009 and MAT = 0 in 2011; group 2: MAT≥400 in 2009 and MAT = 100–200 in 2011; group 3: MAT≥400 in 2009 and MAT≥400 in 2011 . Cases possess MAT titer above 400 in both time points disclosed deterioration of renal function in two-year follow up . To evaluate kidney injury , a set of biomarkers was tested in the 88 residents from W township in 2011 . Cases also were divided into three groups according to MAT titer level ( MAT = 0 , MAT = 100–200 , and MAT≥400 ) . Urinary KIM1/Cr ratio is higher in cases with MAT titer above 400 as compared with that in the other two groups ( 0 . 6 ± 0 . 3 ng/mg vs . 0 . 5 ± 0 . 3 ng/mg vs . 0 . 8 ± 0 . 3 ng/mg , P-value<0 . 05 ) ( Fig 3 ) . The level of urinary , serum NGAL and serum MCP1 did not show a significant difference among three groups ( Table 5 ) . Among the cohort participants , two individuals ( 2 . 3% ) presented with asymptomatic persistent high titers of MAT ( ≥1600 ) were detected to have positive urine leptospiral DNA indicating a carrier shedding status , and associated deteriorating renal function during two years follow-up ( Fig 4 ) .
Fuelled by global warming and climate change , leptospirosis , an important re-emerging infectious disease , imposes challenges not only in tropical or subtropical regions , but also in temperate regions [7 , 26] . Sporadic reports showed that tubulointerstitial nephritis caused by leptospira might lead to CKD [10 , 27] . However , the established association between chronic leptospiral infection and CKD is still lacking . This has become a critical question for CKD as a pressing public health burden all over the world . Using a multistage community-based cross-sectional survey and a cohort in the endemic town , this study , to our knowledge , is the first to establish the association between leptospiral infection and chronic kidney disease . In the two-year cohort of the Township , we further found that a higher MAT titer level ( MAT titer ≥400 ) is associated with a higher kidney injury marker KIM–1/Cr , suggesting a possible leptospirosis-associated deterioration of renal function over time . Chronic kidney disease is associated with hypertension , diabetes mellitus , cardiovascular disease , increased body-mass index , age , and smoking [3] . Additionally , while Chinese herbs containing aristolochic acid can lead to renal damage or even End-Stage Renal Disease , herbal use has been common in Taiwan [28] . In the current study , after adjusting for the abovementioned risk factors , the correlation between CKD and leptospiral infection remained statistically significant . Although participants with a positive anti-leptospira antibody had a significantly higher percentage of diabetes at baseline , the correlation between the renal function and the leptospiral exposure persisted after accounting for the presence of diabetes . As compared between patients with and without diabetes mellitus in multivariate analysis , leptospiral infection still associated with decreased renal function in both groups . The mean age was also higher in the positive group . In Table 2 , however , after adjustment with age and the other possible confounders , previous exposure to leptospira is still a significant contributor to the reduction of eGFR . Moreover , we further conducted stratified analyses by age group , the results of which show that previous leptospiral exposure remains significantly associated with a reduced eGFR in the younger ( <40 or 40–65 years ) but not in the older ( >65 years ) group ( S1 Table ) . These observations provide consistent evidence that older age per se could not fully explain for the reduction of eGFR among those with prior leptospiral exposure history , particularly in the young and middle-aged groups . Our results indicate that leptospira infection may be associated with , and have likely contributed to prevalent chronic kidney disease at least in some local towns of southern Taiwan . From the cohort of the endemic Township , 86 . 4% of participants were seropositive for anti-leptospira antibody at baseline , which is much higher than the 33 . 9% seropositive rate in the southern county as surveyed in this study . High sero-prevalence rate has been noticed in some sub-tropical regions . A random sample of 1067 persons in Seychelles , Indian Ocean showed a sero-prevalence rate of 37% [29] , whereas 54% sero-prevalence rate was observed among healthy population from the Andaman Island , India [30] The high sero-prevalence rate found in this study might be related to severe flooding during the devastating typhoon Morakot and environmental exposure to leptospira such as the highly concentrated pig farms in this Township area . Asymptomatic infection due to contacting contaminated water or soil after typhoon flooding could also contribute to this observation . People in township receive their water from private ground water wells instead of chlorinated tap water provided in the county , we thus cannot rule out the high prevalence is partially caused by contaminated well water . We also found that participants who maintained a high anti-leptospira antibody MAT titer ( ≥400 ) over the two-year follow-up period showed a significant deterioration of renal function , which represent potential risk of CKD in the long run [31] . Since the cohort participants did not report a recognizable history of acute leptospiral infection at the initial enrolment , it is conceivable that asymptomatic leptospiral infection or infection with minor symptoms were most likely the case of these participants after flooding . For kidney involvement , extensive studies suggest that in a progressive nature of kidney that has been damaged , renal function may continue to deteriorate . This is usually contributed by common secondary factors , which are unrelated to the initial disease [32–34] . Therefore , the deterioration of renal function may persist , even after the termination of carrier or chronic infection status . Our focus on Leptospira santarosai serovar Shermani as it is the major pathologic serovar identified in both animals and humans in Taiwan . As titers of MAT following acute infection may be extremely high initially and fall to lower levels in months or years , a titer of ≥100 is usually used as evidence of past exposure [4] . Two participants with a persistently high MAT titer excreted leptospira from their urine two years after the presumable primary infection during the flood in 2009 , suggesting that a repeatedly high MAT titer level may be due to a failure in clearing the pathogen . Interestingly , these two participants also disclosed a decreased renal function . A recent report of chronic neuroleptospirosis due to Leptospira santarosai was diagnosed using next generation sequencing referring to our previously published genome sequence , suggesting a chronic , persistent infection potentially caused by this serovar . [14 , 35] Since chronic leptospiral infection may be one of the reasons for CKD , it is worth investigating whether and how leptospiral infection may lead to CKD . KIM–1 , a putative epithelial cell adhesion molecule , expressed in dedifferentiated proximal renal tubular epithelial cells in damaged regions [36 , 37] was increased in the group with high titers of anti-leptospira antibody . However , the other acute injury markers such NGAL and MCP1 did not show a significant difference . KIM–1 is associated with renal fibrosis and damaging in chronic renal disease besides acute kidney injury [38 , 39] . The increase of KIM–1/Cr ratio in the group with high MAT titer in 2011 , two year after the flood-related outbreak , may reflect and indicate chronic damages including fibrosis process in the kidney ( Fig 3 ) . This suggests that chronic injury and fibrosis , a common pathological alteration in progressive CKD , may be the major contributor to CKD after leptospiral infection either via persistence injury or a sequela after acute infection under an indolent process [40] . This conjuncture found support in previous experiments by Tian et al . , who showed that the outer membrane protein of Leptospira santarosai serovar Shermani can stimulate extracellular matrix production through a TLR2-associated cascade [41 , 42] , revealing possible underlying mechanisms of tubulointerstitial fibrosis after leptospiral infection . Our study has several strengths . First , the population-based survey design suggests a better generalizability and less selection bias than a hospital-based clinical series . Second , prospective data collection in the two-year cohort study has effectively minimized the likelihood of missing data and misclassification . Moreover , the large sample size of the cross-sectional survey allows us to adjust for several important confounding factors that might also predispose to or worsen CKD while determining the independent association between a previous leptospiral infection and prevalent CKD . Finally , we also conducted a prospective cohort to monitor the renal function change over time after a leptospirosis outbreak to further confirm our observations from the cross-sectional survey . This study was limited in that the case number of the prospective cohort was not large enough to allow for a full adjustment for well-recognized confounders such as age , diabetes mellitus etc . In addition , our study was conducted in a single geographical region endemic with a single serotype- Leptospira santarosai serovar Shermani . Whether other serovars exert different effects on the deterioration of renal functions needs to be further confirmed in a prospective manner . We are currently planning for interventional studies , such as antibiotic therapy in a larger cohort in the future . In a population-based community survey , our findings suggest that previous exposure to leptospira is associated with the higher prevalence and severity of CKD . In an independent two-year cohort , leptospirosis is associated with a continual deterioration of renal function over time , especially in those with a persistent high MAT titer levels . In view of CKD as a global burden , it is worth paying attention to the relationship between CKD and the exposure to leptospira . Our results support a public health policy of screening renal function among at risk residents in leptospira-endemic areas . Also , for effective early prevention , further studies will be needed to clarify the mediating mechanisms and the role of chronic leptospirosis in causing CKD or in its progression . Finally , this study also shed light on the search of underlying factors in areas experiencing CKD of unknown aetiology ( CKDu ) . | Chronic kidney disease ( CKD ) has a high and increasing worldwide prevalence . Leptospirosis , an important re-emerging infectious disease caused by the pathogenic spirochete Leptospira , is the most widespread zoonosis throughout the world , particularly in tropical and subtropical regions . Chronic human infection and asymptomatic colonization have been reported . However , the evidence of renal involvement in those with leptospira exposure history or human carrier remains undetermined . In this study we found that those individuals with previous leptospira exposure disclosed a lower renal function and a higher percentage of CKD . Additionally , in our cohort study , those with a high serum titer by leptospira agglutination test showed decreased renal function and higher kidney injury marker . We are the first to identify the association between CKD and leptospiral infection . This information may provide a novel approach for CKD of unknown aetiology but also significantly impact global control of leptospirosis and CKD burden . | [
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] | [] | 2015 | Overlooked Risk for Chronic Kidney Disease after Leptospiral Infection: A Population-Based Survey and Epidemiological Cohort Evidence |
Localization of objects and events in the environment is critical for survival , as many perceptual and motor tasks rely on estimation of spatial location . Therefore , it seems reasonable to assume that spatial localizations should generally be accurate . Curiously , some previous studies have reported biases in visual and auditory localizations , but these studies have used small sample sizes and the results have been mixed . Therefore , it is not clear ( 1 ) if the reported biases in localization responses are real ( or due to outliers , sampling bias , or other factors ) , and ( 2 ) whether these putative biases reflect a bias in sensory representations of space or a priori expectations ( which may be due to the experimental setup , instructions , or distribution of stimuli ) . Here , to address these questions , a dataset of unprecedented size ( obtained from 384 observers ) was analyzed to examine presence , direction , and magnitude of sensory biases , and quantitative computational modeling was used to probe the underlying mechanism ( s ) driving these effects . Data revealed that , on average , observers were biased towards the center when localizing visual stimuli , and biased towards the periphery when localizing auditory stimuli . Moreover , quantitative analysis using a Bayesian Causal Inference framework suggests that while pre-existing spatial biases for central locations exert some influence , biases in the sensory representations of both visual and auditory space are necessary to fully explain the behavioral data . How are these opposing visual and auditory biases reconciled in conditions in which both auditory and visual stimuli are produced by a single event ? Potentially , the bias in one modality could dominate , or the biases could interact/cancel out . The data revealed that when integration occurred in these conditions , the visual bias dominated , but the magnitude of this bias was reduced compared to unisensory conditions . Therefore , multisensory integration not only improves the precision of perceptual estimates , but also the accuracy .
Nearly every function critical for human survival depends directly on accurate localization of objects and events in the environment . For example , our capacity to locate food , find potential mates , avoid predators , navigate new terrain , avoid obstacles , act upon objects , and orient towards sudden sounds requires a skilled aptitude to detect stimuli in the surrounding world . Spatial localization is thus a fundamental task that the brain has to solve at any given moment , and evolution has had millions of years to refine this function . Therefore , one would expect that the representation of space in all sensory modalities is generally accurate . However , the existing literature on human spatial localization contains many findings that are at odds with this assumption: representations of space in different sensory modalities appear to be biased , and no consensus yet exists regarding the direction and magnitude of the bias in a given modality . For instance , while a majority of studies investigating localizations of simple visual stimuli that differ in azimuth have shown that visual localizations often show a bias towards the center of visual space [1–8] , a few studies have reported peripheral biases or veridical perception [9–12] . In the auditory domain , findings of various studies have been mixed as well: some indicate that , on average , auditory localizations are often biased increasingly farther away from center as eccentricity increases [6 , 13–15] , while others have reported central biases for average auditory localizations [16 , 17] . Thus , previous research has provided little consensus regarding the bias present in each sensory modality . The previous investigations on spatial localization have used relatively small sample sizes , and consequently , variability in the reported findings could be due to sampling bias and/or the undue influence of outliers . Similar issues also apply to the previous reports of precision of spatial localization , particularly in the auditory domain . One study reported that the variability in auditory localizations remains relatively consistent across differences in azimuth [18] , but two recent investigations found that auditory precision declines for peripheral targets [16 , 19] . Here , we present findings from an extraordinarily large dataset ( 384 subjects ) to obtain more definitive answers regarding not only the direction and magnitude of biases in both the visual and auditory modalities , but also the precision in spatial localizations over a range of spatial positions . Previous speculations about the source of the variability in findings regarding the presence and direction of bias have focused on the specifics of the experimental paradigms , including the mechanism used to report location [11] , the role of visibility of response location [20] , the visibility of external boundaries [21] , and the memory demands of the task as related to the time before response [8] . However , the variability in the results of previous studies could be a result of any of these factors or small sample sizes . In this study , we implement a simple yet rigorous paradigm to assess bias in which subjects’ localized briefly presented flashes of light and bursts of sounds; the response cursor was visible at all times to eliminate the influence of motor error , the locations of stimuli were unknown to subjects , the display was boundary-free , the response delay was minimal , and hundreds of subjects participated , all in an attempt to capture the true perceptual biases present in each modality . By analyzing responses from our immense dataset , we aim to clarify discrepant results in the literature regarding the accuracy and precision of both visual and auditory localizations . Additionally , while previous studies on unisensory biases and variances have enhanced an overall understanding of how the senses process information from the surrounding world , in real-world settings , objects usually produce signals that simultaneously stimulate multiple sensory modalities . In conditions where auditory and visual stimuli co-occur in close spatial proximity , it has been well-documented that auditory localizations are often pulled in the direction of a visual stimulus [18 , 22–26] . Known as the “Ventriloquist illusion” [27] , this effect has been demonstrated in many experiments , lending support to the idea that the most reliable sense in a given dimension exerts a strong influence over other noisier senses as estimates about the world are produced [28] . While many studies have focused on how far this “spatial window” of audiovisual integration extends [29] , one important question remains: when visual and auditory stimuli co-occur at the same spatial location ( which is generally the case when an event produces both visual and auditory stimulation ) , which modality’s bias emerges during localization ? Is it the visual bias , the auditory bias , or something else ? If , as many studies indicate , visual localization is biased towards the center , and auditory localization is biased towards the periphery , three possibilities exist: vision dominates on most trials , and a central bias emerges; the auditory bias dominates , and a peripheral bias emerges; the biases interact , and a hybrid bias emerges in the bimodal localizations . It has been shown previously that even when the stimuli are congruent in both space and time , they may be perceived to have a common cause or independent causes . Therefore , it is also important to explore whether the nature and presence of bias in multisensory conditions is influenced by the inference of common cause . Finally , another important question that has not been previously explored is the following: if indeed the visual and/or auditory localization of stimuli in space is biased and inaccurate , what underlies this bias ? Is this bias in localization a result of bias in the sensory representation of the space , a result of general a priori expectation of location of events in the world , or the result of a combination of these two possibilities ? In the former case , the sensory encoding of the stimuli is compressed towards the center of the visual space , and this early sensory bias leads to a mislocalization of stimuli towards the center without any effect of prior expectations for the location of the stimuli . In the latter case , the sensory representation of the visual space may be perfectly accurate and unbiased , but due to the task demands or expectations about the location of the stimuli ( in this task or in general ) , the localization may be biased towards the center . The third possibility is that the localization bias stems from a combination of both of these mechanisms . Teasing apart these three different scenarios requires quantitative computational modeling of the data , as explained below . The behavioral findings in this study showed that both visual and auditory localizations were indeed biased , with visual localizations on average biased towards the center and auditory localizations on average biased away from the center . To address whether these biases in spatial perception stem from a bias in sensory representations or from a prior expectation of location , we employed the causal inference model of multisensory perception [30–32] to quantitatively characterize both sensory representations and prior expectations of each individual observer . This model has been very successful in accounting for human observers’ data in a variety of multisensory tasks [30–35] and a recent brain imaging study has provided further support for the brain utilizing this computation in the spatial localization task that is used in this study [36 , 37] . Importantly , this model can reliably provide a quantitative estimate of several components of perceptual processing for each individual observer . In a Bayesian framework , the final perceptual estimate is based upon a combination of the sensory representation ( i . e . likelihood distribution ) and pre-existing expectation ( i . e . prior ) . Fig 1 shows different kinds of underlying mechanisms that could produce biases similar to those shown by most subjects in our localization task . In the visual domain , either ( 1 ) an a priori bias for center in expectation of location of visual stimuli ( Fig 1A ) , or ( 2 ) a bias in the sensory representation of visual stimuli towards the center ( the likelihood means shifted towards center with the amount of shift being proportional to the degree of stimulus eccentricity ) could account for biased perception ( Fig 1B ) . In the auditory domain , either ( 1 ) an a priori bias towards periphery ( Fig 1C ) , or ( 2 ) a bias away from the center in sensory representations ( Fig 1D; shifts of likelihood means away from the center with the degree of shift proportional to stimulus eccentricity ) could account for participants’ behavior . The exhibited behavioral biases may also be due to a combination of biased likelihood and biased priors . To investigate which of these options is indeed the mechanism underlying the observed biases , we implemented all three types of mechanisms ( biased likelihoods , bias priors , a combination of the two ) into a Bayesian Causal Inference model and performed quantitative model comparisons to determine which computational mechanism best accounts for the behavioral data . All previous models of multisensory spatial localization assume that sensory representations are unbiased , and that the main benefit in integrating stimuli is improvement in the overall precision of the combined estimate . For example , maximum likelihood estimation models have proposed that auditory and visual signals can be represented by distributions centered at the true location of each stimulus , with the combined audiovisual estimate exhibiting a smaller variance than the unisensory estimates [38–40] . The reduced variance of the combined estimate has been considered to be the main reason why it may be advantageous for the brain to integrate redundant sensory information in a complex world [41 , 42] . Here , we explore the effect of integration on the bias of the estimates and examine whether localization estimates become less biased , more biased or remain the same as a result of integration as compared to unisensory conditions . In order to address all of these questions , we analyzed psychophysical data and quantitatively characterized the perceptual components involved in the spatial perceptual process using computational modeling . Specifically , the study had five aims: ( 1 ) to quantify unisensory spatial biases and variances in the visual and auditory modalities using a large dataset , ( 2 ) to investigate how biases are reconciled when subjects localize spatially congruent bisensory stimuli , ( 3 ) to determine whether the biases that emerge in spatially congruent bisensory trials depend on an observer’s inference about a common cause , ( 4 ) to determine whether the biases in spatial localization are due to a bias in the sensory representations , prior expectations , or both , and ( 5 ) to examine how the biases in bisensory conditions compare with biases in unisensory conditions .
This study was conducted according to the principles expressed in the Declaration of Helsinki . Each subject also signed a consent form approved by the UCLA IRB . A total of 412 subjects ( ages 18–55 ) participated in our experiment; since our measurement of localization biases are means that can be influenced by extreme outliers , 28 subjects were excluded because their responses for each of the five unisensory conditions in either the visual or auditory modalities were more than three times the inter-quartile standard deviation for the tested location . This exclusion criterion ensured that we would avoid analyzing data that may have been due to sloppiness or negligence with the response device . All participants verbally reported that they did not have a history of any neurological conditions ( seizures , epilepsy , stroke ) , had normal or corrected-to-normal vision and hearing , and had not experienced head trauma . Eligible participants sat at a desk in a dimly lit room with their chins positioned on a chinrest 52cm from a projection screen . The screen was a black , acoustically transparent cloth subtending much of the visual field ( 134° width ° x 60° height ) . Behind the screen were 5 free-field speakers ( 5 x 8 cm , extended range paper cone ) , that differed in azimuth by 6 . 5° and were placed 7° below fixation . The middle speaker was positioned directly below the fixation point , and two speakers were positioned to the right and two to the left of fixation . The visual stimuli were presented overhead from a ceiling mounted projector set to a resolution of 1280 x 1024 pixels with a refresh rate of 75 Hz . Prior to the presentation of any stimuli in the experiment , participants were required to have their gaze centered on the central fixation point . To ensure that participants’ gaze for each trial was starting from the same location , gaze position and fixation time were recorded at 60Hz with a ViewPoint eye tracker ( Arrington Research , Scottsdale , AZ ) fixed to the chinrest and PC-60 software ( version 2 . 8 . 5 , 000 ) . Stimuli were not displayed until the recorded gaze angle was within 3 . 0° of the fixation point and the fixation time was greater than 250 ms . Viewing of the stimuli was binocular , although only movements of the right eye were tracked . The eye tracker was adjusted for each participant before the test session to ensure that the entire eye was being monitored , and a calibration task was performed before trials for the experiment began . A separate computer controlled presentation of stimuli and recorded behavioral responses using MATLAB ( version 7 . 6 . 0 , R2008a ) . A wireless mouse was used to record the behavioral responses . The visual stimuli used in the experiments were white disks ( . 41 cd/m2 ) with a Gaussian envelope of 1 . 5° FWHM , presented 7° below the fixation point on a black background ( . 07cd/m2 ) , for 35 ms . The center of visual stimuli overlapped the center of one of the five speakers behind the screen positioned at -13° , -6 . 5° , 0° , 6 . 5° , and 13° . Auditory stimuli were ramped white noise bursts of 35 ms measuring 59 dB ( A ) sound pressure level at a distance of 52 cm . The speaker locations were unknown to all of the participants in the experiment . Participants began each session with 10 practice trials requiring localization of unisensory auditory stimuli . This practice session ensured that participants were using the mouse properly , understood the instructions , and were fulfilling the fixation requirements for each trial . Each trial started with the fixation cross , followed after 750 ms ( if the subject was fixating properly ) by the presentation of stimuli . 450 ms after the stimuli , fixation was removed and a cursor appeared on the screen vertically just above the horizontal line where the stimuli were presented at a random horizontal location in order to minimize response bias . Following the removal of fixation , the scene was entirely dark except for the cursor . The cursor was controlled by the trackball mouse placed in front of the subject , and could only be moved in the horizontal direction . Participants were instructed to “move the cursor as quickly and accurately as possible to the exact location of the stimulus and click the mouse . ” This enabled the capture of continuous responses with a resolution of 0 . 1 degree/pixel . No feedback about the correctness of responses was given . Participants were allowed to move their eyes as they made their response , so the fixation requirement was dropped following the presentation of the stimuli . Following the brief practice session , participants began the localization session , which consisted of 525 trials of interleaved auditory , visual , and audiovisual stimuli presented in pseudorandom order . The stimulus conditions included 5 unisensory auditory locations , 5 unisensory visual locations , and 25 combinations of auditory and visual locations ( bisensory conditions ) , for a total of 35 stimulus conditions , shown in Fig 2 below . Fifteen trials of each of the 35 conditions were presented in pseudorandom order , lasting about 45 minutes , including breaks . The Bayesian causal inference model has been shown in multiple studies to account for the human multisensory spatial perception very well [30–33] and it has been shown to outperform other proposed models of multisensory spatial perception [30] . Moreover , a human neuroimaging study recently provided further support for the Bayesian Causal Inference being carried out in human brain in the spatial localization task , using the same task used in current study [37] . Therefore , we used this model to investigate the characteristics and perceptual components of human spatial processing in our localization task . In previous formulations of this model it had been assumed that ( 1 ) the likelihood distributions of sensory stimuli are unbiased ( centered at the true locations of stimuli in the world ) , ( 2 ) visual and auditory localizations are both impacted by a meta-modal central prior over space , and ( 3 ) the variance of sensory representations ( likelihood functions ) is uniform across all eccentricities . Considering our behavioral results , which reveal non-zero biases of differing direction and magnitude in the visual and auditory modalities , it appears that these simplifying assumptions are not quite warranted , and the model would need to be enhanced to allow flexibility in the representation of likelihoods and/or priors . The nervous system does not have access to the true events s in the world . Instead , it only has access to the noisy sensory representations , xv and xa ( denoting visual and auditory sensations , respectively ) . Taking into account both the noisy sensory representations ( likelihoods ) and prior knowledge of the world ( priors ) , the brain makes an inference about whether the sensory signals come from the same source ( C = 1 ) and should be integrated or the signals come from different sources ( C = 2 ) and should be segregated ( see [30] for an image of the graphical model ) . Thus , the posterior probability of an event s is conditioned on the causal structure of the stimuli ( C = 1 or C = 2 ) : p ( s|xA , xV;C=1 ) =p ( xA|s ) p ( xV|s ) p ( s ) p ( xA , xV ) ( 1 ) p ( sA|xA;C=2 ) =p ( xA|sA ) p ( sA ) p ( xA ) ( 2 ) p ( sV|xV;C=2 ) =p ( xV|sV ) p ( sV ) p ( xV ) ( 3 ) The estimate of the location of the stimuli will be based on these posterior probabilities . However , since the causal scenario is not known by the nervous system , this also must be inferred based on the available sensory evidence and prior information . This can also be computed using Bayes’ Rule: p ( C|xA , xV ) =p ( xA , xV|C ) p ( C ) p ( xA , xV ) ( 4 ) Therefore , p ( C=1|xA , xv ) =p ( xA , xV|C=1 ) pcp ( xA , xV|C=1 ) pc+p ( xA , xV|C=2 ) ( 1−pc ) ( 5 ) where Pc is the prior probability of a common cause , and the likelihood terms can be computed by integrating over the latent variable s: p ( xA , xV|C=1 ) =∫p ( xA|s ) p ( xV|s ) p ( s ) ds ( 6 ) p ( xA , xV|C=2 ) =∫p ( xA|sA ) p ( sA ) dsA⋅∫p ( xV|sV ) p ( sV ) dsV ( 7 ) The posterior probability of independent causes is computed as follows: p ( C=2|xA , xV ) =1−p ( C=1|xA , xV ) ( 8 ) Having calculated the probabilities of each causal structure , and having calculated the optimal estimates for spatial localization under each causal structure , we now need to obtain estimates given uncertainty about the causal structure . Previously it has been shown [24] that the vast majority of observers use a probability matching strategy as follows: s^A={s^A , C=1ifp ( C=1|xA , xV ) >ξwhereξ∈[0:1]uniformdistributions^A , C=2ifp ( C=1|xA , xV ) ≤ξandsampledoneachtrials^V={s^V , C=1ifp ( C=1|xA , xV ) >ξwhereξ∈[0:1]uniformdistributions^V , C=2ifp ( C=1|xA , xV ) ≤ξandsampledoneachtrial ( 9 ) Therefore , here we used this strategy to model the observers’ data . We used a generative model to simulate 10 , 000 xA’s and xV’s for each experiment condition ( 35 total ) using the preceding equations . Trial-to-trial variability is introduced by sampling the likelihoods from Eqs 1–3 from a normal distribution centered at the true sensory location , plus a bias term that scales linearly with eccentricity of the stimulus . Thus , if subjects’ sensory representations are not centered at the true locations , this bias term could potentially reflect this systematic shift in the likelihoods . The variability in the normal distribution from which the likelihoods are sampled scales with eccentricity of the stimulus . The prior described in the above equations changes depending on the model version , and can either be the biased central prior , the biased peripheral prior , or both , ( see Fig 1 ) . We quantitatively compared six models to determine which model could best account for participants’ data . Different mechanisms were incorporated in the different models , resulting in different combinations of free parameters . All of these parameters are shown in Table 1 , with a brief description of their corresponding mechanism . Three parameters were included in every model: the prior probability of a common cause ( Pc ) , the standard deviation of the visual likelihood ( σV ) , and the standard deviation of the auditory likelihood ( σA ) . Two models incorporated the biased likelihood mechanisms , including a symmetric shift in the visual likelihood mean that increases with eccentricity ( ΔxV ) , a symmetric shift in the auditory likelihood mean that increases with eccentricity ( ΔxA ) ; one of these models included a change in the visual likelihood variance which increases with eccentricity ( ΔσV ) , while the other did not . Two models incorporated the biased prior mechanisms , including a visual central prior to capture a central bias ( σVP , xVP ) and a peripheral spatial prior to capture a peripheral auditory bias ( with the mean and variance , σAP , xAP , reflecting the symmetric aspects of each part of the bimodal distribution ) ; one of these included an additional metamodal spatial prior , while the other did not . We also included the original model [31] , which does not include either the biased likelihood nor the biased prior mechanisms , as the baseline for comparison . Finally , we included a hybrid model that incorporated all biased likelihood mechanisms ( ΔxV , ΔxA , ΔσV ) as well as a metamodal spatial prior . These models are summarized in the results section . Since the different models have different numbers of free parameters , in addition to reporting their model fits ( in log likelihood ) we also report the BIC value of each model , which is a measure of goodness of fit that penalizes models with larger number of free parameters . The six models described above were applied to the data from each of the 384 observers , and log likelihood and BIC values were computed for each model’s fit to each observer .
For each observer , the average error in localization ( across 15 trials ) in the unisensory trials was calculated for each spatial position and for each modality . The mean and distribution of these biases across observers are shown in Fig 3A , 3C and 3B , respectively . Participants’ average localizations for unisensory visual stimuli exhibited a bias for localizing peripheral stimuli closer to the center of visual space . Analysis of unisensory-visual trials showed that 63% of subjects ( 242 ) exhibited central biases for all four peripheral locations of visual stimuli , and 84% of subjects ( 319 ) exhibited central biases for three out of the four peripheral locations . This trend for a central bias tended to increase as the eccentricity of the visual stimulus increased . In the auditory domain , subjects’ average localizations for each location revealed the opposite trend: average localizations for eccentric stimuli exhibited a peripheral bias for localizing the stimuli ( Fig 3A and 3C ) . However , further analysis revealed heterogeneity among subjects for this trend: 25% of the subjects exhibited consistent peripheral biases for all four eccentric locations , but 15% of participants exhibited consistent central biases . Overall , though , 45% of the participants exhibited a peripheral bias for three out of the four locations , indicating that a substantial proportion of subjects localized eccentric auditory stimuli further away from the true locations of the sounds . Bonferonni-corrected one-sample t-tests for all peripheral localizations in both modalities were all highly significant ( p < . 0001 ) , indicating the responses in both the visual and auditory modalities for peripheral locations were biased away from the true location of the stimulus . For the central ( 0° ) localizations , there was no bias in the visual modality ( t ( 383 ) = 1 . 5 , p > . 05 ) , but a small bias to the left for the auditory modality was observed ( t ( 383 ) = -2 . 9 , p = . 0042 ) . Previous research has indicated that participants often display an auditory localization bias contralateral to the preferred hand [43] , so this slight bias could be explained by the near certain-assumption that the majority of our participants were right-handed . Finally , as can be seen in Fig 3B , the distributions of biases in both the auditory and visual modalities are unimodal , indicating that despite some variability in biases across subjects , there do not appear to be distinct subgroups ( i . e . “central-bias” subjects and “peripheral-bias” subjects ) that are easily classified . Importantly , the distributions in biases shown in this figure reveal the value of acquiring large sample sizes when investigating spatial perception: reporting averages from small samples could not only reflect skewed trends based on the influence of outliers , but also obscure important variability across subjects in terms of the extant biases . Especially in the auditory domain , studies with smaller sample sizes have not previously revealed this amount of heterogeneity in biases in auditory space [14 , 16] . Given that the average biases in the visual and auditory modalities are in opposite directions , an intriguing question arises: in which direction is this conflict resolved when auditory and visual stimuli co-occur at the same location ? Analysis of congruent bisensory trials ( i . e . , trials on which the visual and auditory stimulus co-occurred at the same spatial location ) revealed that on average , both the visual and auditory modality exhibited central biases ( Fig 4 ) . However , as shown below ( see Fig 5 ) , further analysis of these trials revealed that the bias that emerged in the auditory modality was dependent on whether the observer inferred a common cause or distinct causes for the stimuli . Previous research investigating auditory localizations has shown that the bias that emerges in the auditory domain is contingent upon whether observers perceive a simultaneous visual stimulus as unified with or independent from the auditory stimulus ( see Fig 5 in [26] ) . Observers’ explicit reports indicate that even with spatially and temporally congruent flashes and sound bursts , sometimes a common cause is perceived , but at other times discrepant causes are perceived , and this inference can affect the amount of bias that emerges during the localization task . This phenomenon has been explained quantitatively by a Bayesian causal inference model [30] . Furthermore , recalibration of auditory space by vision has been shown to strongly depend on whether or not a common cause is perceived for the two stimuli [44] . Therefore , we investigated whether the inference of a common cause influences the bias in bisensory conditions . As in [44] , we classified the congruent bisensory trials into “common-cause” and “independent-cause” trials based on the observer’s responses . If the visual and auditory localizations were within two degrees of each other , we considered the trial as a common-cause trial ( as the stimuli are perceived to have the same location , thus reflecting the inference of a common cause ) . If the visual and auditory localizations were more than five degrees apart , we considered the trial to be generated by independent causes ( as this degree of discrepancy between the two percepts is inconsistent with the inference of a common cause , and is unlikely to be due to motor error ) . Trials in which the discrepancy between visual and auditory responses were in between 2 and 5 degrees were excluded from analysis ( due to uncertainty about the inference of causal structure ) . The results are shown in Fig 5 . As can be seen in Fig 5C , on “common cause” trials both modalities show a considerable central bias , which increases as eccentricity of the target increases . Interestingly , comparing these common cause trials with the corresponding unisensory trials in each modality reveals an important effect: when trials are integrated , the amount of bias decreases in each modality , and the localizations become closer to the veridical location of the stimulus ( p < . 005 for t-tests for all eccentric locations ) . For example , in the visual modality , unisensory localizations at the -13 degree location exhibited a bias towards the center of 1 . 53 degrees , but when visual localizations are integrated with an auditory stimulus at this location , the bias decreases to 1 . 24 degrees . This reveals an important new finding: multisensory integration not only increases precision in the final spatial estimates of stimuli ( which was previously well-established ) , but also increases the accuracy of the estimates by reducing biases and bringing the final estimates closer to the true stimulus location . Localizations on trials where independent causes were inferred are much more variable: while the visual modality shows a central bias that appears to increase as eccentricity increases , the bias that emerges in the auditory modality is irregular , and the trend less clear . This variability is apparent in Fig 5C , where the irregularity in auditory localizations on trials where independent causes were inferred is evident . Thus , to summarize: in spatially congruent audiovisual trials in which a common cause is perceived , the visual bias dominates , however , the degree of bias is smaller relative to unisensory trials . In contrast , on segregated trials , while the visual modality still exhibits a central bias , auditory biases are extremely variable . Analysis of the variability in unisensory trials ( Fig 6 ) showed the following: the standard deviation of visual localizations was not equivalent across conditions ( F ( 4 , 1532 ) = 39 . 467 , p < . 001 ) , and increased as the eccentricity of the stimulus increased ( p < . 001 for all paired-samples t-tests between adjacent conditions ) . The standard deviation of auditory localizations also revealed differences contingent on stimulus eccentricity ( F ( 4 , 1532 ) = 16 . 32 , p < . 001 ) , but in a different way . That is to say , variability in the two auditory standard deviations surrounding the zero-degree location ( +6 . 5 and -6 . 5 ) degrees ) were not significantly different from the variability at the central location ( p > . 05 for both paired-samples t-tests ) , but variability in the peripheral locations ( -13 and +13 degrees ) were significantly different from the variability in localizations at the spatially adjacent neighbors ( p < . 001 for both paired-samples t-tests ) . We also evaluated the precision in visual and auditory localizations on trials where the visual and auditory stimuli co-occurred at the same locations in space . In the visual modality , similar to the unisensory trials , the standard deviations for visual localizations increased as eccentricity increased ( F ( 4 , 1532 ) = 29 . 89 , p < . 001 ) ) . In the auditory modality , although a significant effect emerged ( F ( 4 , 1532 ) = 22 . 73 , p < . 001 ) , none of the peripheral locations were significantly different from one another , and the only significant difference was that variance in peripheral locations was larger than that of the center ( p < . 001 for all paired-samples t-tests ) . Table 2 shows the results of model fits for each of the 6 models . The first two columns describe each model , columns 3 and 4 show the log likelihood and BIC values averaged across all observers , column 5 shows the number of subjects best fit by each model , and column 6 shows the average R2 values [45] across all observers . As can be seen , the 8-parameter model accounts for the observers’ data the best , as it has the best-fitting average log likelihood value , the lowest average BIC value ( i . e . the best account of the data even after penalizing it for having larger number of free parameters than some of the other models ) , the largest R2 value , and the highest number of subjects that are best fit by its iteration . In fact , the number of participants whose data is best accounted for by the 8-parameter model is one order of magnitude larger than the runner up model , providing compelling evidence for the superiority of this model over the other models in explaining the data . A one-way repeated-measures ANOVA applied to the BIC values [46] showed that the model fits were significantly different from one another ( F ( 5 , 1915 ) = 248 . 1 , p < . 001 ) . Furthermore , a post-hoc t-test between the two best models ( the 6-parameter and 8-parameter model ) showed that the 8-parameter model was significantly superior ( t ( 383 ) = 10 . 2 , p = . 001 ) . Thus , a model that incorporates biases in the sensory representations and a general ( metamodal ) prior bias for center best captures observers’ performance in our multisensory localization task . Previous versions of the model have fit data quite well ( as also evidenced in the high R2 values for all model fits ) [30 , 31] . It is therefore important to note that simpler versions of the model in this study did not do an inadequate job of fitting the overall data; instead , they were limited primarily in their abilities to account for the unisensory data , which revealed sensory biases in eccentric positions . Shown in Fig 7 are model fits for the auditory-only conditions from one randomly selected subject . When plotted , it becomes clear that the simple 4-parameter model fails to account for peripheral auditory biases , and thus more complex models are needed to fully account for the phenomenon of sensory biases . In the winning hybrid model ( 8 parameters ) , the optimized value of the mean for the general meta-modal prior was almost zero , reaffirming the central bias that had been assumed in the original 4-parameter model [30 , 31] . Therefore , the only difference between the winning model and the original 4-parameter model is in the bias in visual and auditory sensory representations , and the increase in visual likelihood variance as a function of eccentricity .
Many previous studies have suggested that humans’ visual and auditory localizations in surrounding space are biased and inaccurate [1 , 2 , 13 , 15] . If such biases are truly present in human perception of space , they would pose a riddle and warrant further investigation into their characteristics and function . However , previous studies have been based on relatively small sample sizes that render the results prone to outliers and other statistical irregularities . To examine whether these biases are real ( or reflect noise or other phenomena ) , we used a very large sample size ( 384 subjects ) and an experimental design minimizing the potential for induction of any perceptual or response biases . The experiment consisted of a large variety of unisensory and bisensory stimulus conditions presented in pseudo-random order with a uniform distribution across space , and a fairly large number of trials per condition . Furthermore , the positions of the auditory and visual sources were unknown to the observers , no feedback was provided , and the initial position of the response cursor was randomized . Thus , the experimental design could not induce any perceptual or response bias for any given position in space . By using a rigorous experimental design and acquiring a large dataset , we aimed to obtain a more definitive answer to the question of the existence and nature of any biases in the visual and auditory perception of space . The results demonstrated that when observers were asked to localize briefly presented visual and auditory targets that differ in azimuth , on average , localizations of unisensory visual targets displayed a central bias that increased with eccentricity , and localizations of unisensory auditory targets displayed a peripheral bias that increased with eccentricity . Our finding of a central bias in visual localization is consistent with most studies in this area , especially those in which the cursor was visible during response , which thus minimizes motor error [1 , 6 , 13 , 15] . While the vast majority of observers in our sample showed a clear and consistent bias towards center in vision , the biases exhibited by observers in the auditory modality were more variable and less consistent , but still on average displayed a peripheral bias . This finding is also consistent with those of several previous studies of auditory spatial localizations [6 , 13 , 14] . Localizations for spatially congruent bisensory stimuli exhibited biases that were contingent upon the subject’s inference of the causal structure of stimuli: when a common cause was inferred , the visual bias dominated . When independent causes were inferred , vision continued to exhibit a bias towards the center of space , but the auditory modality on average showed a peripheral bias ( as in the unisensory auditory condition ) . These findings are quite consistent with research requiring explicit judgments of unity or discrepancy [26] , indicating that sensory systems implicitly perform inference processes , and that the biases that emerge are contingent upon whether or not sensory signals were integrated or segregated . Interestingly , on trials for which a common cause was perceived , the opposing biases were reconciled in the following manner: the visual bias dominated , although its magnitude was reduced . This finding strongly suggests that the observed biases in the unisensory conditions stem from a bias in sensory representations . Because visual representations are significantly more precise ( and reliable ) than the auditory representations , in bisensory conditions the visual signals dominate , and therefore , the visual bias dominates the auditory bias . However , in principle , any bias in perception could originate from either a bias in sensory representations ( modeled by likelihood functions ) or a bias in the expectations or model of the world ( prior ) . While the findings discussed above suggest that biases in bisensory conditions are more consistent with a bias in the sensory representations , to address this question rigorously , one needs to quantitatively model these scenarios and perform model comparisons to determine which mechanism ( s ) account for the behavioral data the best . To do this , we used the Bayesian Causal Inference model that has been shown to account for human observers’ multisensory perception quite effectively [30–35 , 37] . We compared models incorporating a bias in likelihoods to those incorporating a bias in prior expectations , and also tested one model that incorporated both mechanisms . We fitted the model parameters to each observer’s data , and compared the models based on data from 384 observers . Consistent with the qualitative observation discussed above , the quantitative model comparison results revealed that indeed a bias in auditory and visual spatial sensory representations is necessary to account for the participants’ data . But over and above these sensory biases , a general ( metamodal ) prior bias for center appears to also exist in perception of space . Why should the visual system be biased in perceiving locations towards the center ? Upon first glance , this would appear to be a tremendously suboptimal strategy , but insights from phenomena in other perceptual domains may provide some possible explanations . For instance , saccadic undershooting for eye movements to peripheral stimuli has been demonstrated conclusively and would seem to be a suboptimal strategy [47 , 48] , but one potential explanation that has been posited is that it represents an advantageous trade-off between accuracy and the movement time needed to reasonably localize the stimulus [49] . Here , we find spatial localization biases in sensory representations . If visual sensory representations were built only for this task , then biases could be suboptimal . But sensory representations are calibrated to be optimal for acting in a complex and changing world in a variety of tasks and conditions , and thus , biases in the visual and auditory systems could be optimal if they are due to an advantageous trade-off; for example , between foveal acuity and peripheral accuracy . Due to the much larger number of neurons representing the fovea compared to peripheral regions [50] , the representation of space may be skewed in that direction if spatial representation involves a population code [51] . It seems possible that this cortical magnification effect may skew visual localizations towards the center . One recent study investigating the perception of visual orientation and spatial frequency posits another possible account: for a Bayesian observer , perceptual priors match stimulus distributions in the world , and sensory likelihoods ( i . e . sensory representations ) become distorted through a process of “efficient encoding” [52] . In this framework , likelihood functions are constrained by the Fisher information in the encoding process , and the Fisher information matches the stimulus distribution in the world . Thus , rather than positing that biased perception is driven entirely by priors ( as many previous models have proposed ) , this study shows that sensory representations can themselves be biased , and this approach can account for biases in perceptual behavior that previously appeared to be “anti-Bayesian . ” Here , in our study , we similarly find perceptual biases best characterized by biases in sensory representations . Future work should investigate whether behaviors such as orienting to sources of sensory stimulation ( objects and events ) may produce a disproportional amount of visual stimuli being located in the center and in turn result in the representation of visual space to become biased accordingly . Additionally , based on everyday subjective experience , visual biases would seem to be quite counterintuitive , as the surrounding spatial world does not appear to be compressed . However , as noted by Rahnev et al . [53] , while subjective perception of the periphery appears to be accurate and colorful , studies have demonstrated that the visual periphery has proportionally less processing resolution , likely impacting capacities for form and motion perception [54] , and color sensitivity [55] . Therefore , subjective assessments of perceptual capacities in the periphery are inaccurate , and comprehensive investigations are needed to quantify the relative impairments in perception outside the fovea . Similar to lack of subjective awareness of color deficiencies in the periphery , here , in the spatial domain , the observers seem to be unaware of their bias in spatial localization . It should also be noted that this study is not the first to document the counterintuitive phenomenon of distortions in perception of surrounding visual space . For instance , inaccuracies in visual estimates of both egocentric distance estimates and objects’ shapes have been well documented [56] . Subsequently , Bingham et al . have raised the question of how accurate movements are possible despite these visual distortions [57] , and indeed , many studies report that perceptual responses and visually-guided reaching actions are dissociated or even uncorrelated [58–61] . As these authors note , it appears likely that feedback plays an important role in minimizing the impact these distortions can have on our movement accuracy , and it also seems that ( as we report here between the auditory and visual modalities ) multisensory integration can assist in reducing biases present in a given pair of sensory modalities [57] . The findings regarding peripheral auditory biases also raise the question of why these biases should exist in the auditory domain . As noted by [15] , prolonged fixation in an eccentric direction shifts the entire map of auditory space in the direction of the fixation point , even for auditory stimuli that are at the same location as fixation . While auditory localizations still exhibit a slight peripheral bias when central fixation is maintained , it appears that when the eyes are allowed to move , auditory space is shifted in the direction of the eye movement . Further support for this idea comes from a study which included one condition where the eyes were allowed to move when localizing the target , and another condition where central fixation was enforced [16] . Results indicated that enforcing fixation greatly reduced the magnitude of auditory biases , suggesting that auditory biases may be driven in part by eye movements . Thus , in our task , as eye position was not constrained , the auditory bias may be at least partially due to this mechanism . Moreover , much is still unknown about how auditory spatial perception is encoded in the human brain . One current idea is that rather than having explicit auditory spatial maps , some form of a distributed population code is built by neurons that may have broad tuning curves [62] . As noted in a recent review [63] , this population rate code may be able to be characterized as a “hemifield code , ” where the firing rates of the relevant auditory neuron population are highest for stimuli in the periphery ( -90 and +90 degrees ) that maximize the ITD and ILD information available . This idea has substantial support from experimental findings indicating that sound source locations could be encoded by the relative firing rates of the right-tuned or left-tuned auditory cortical neurons [64 , 65] and has been further supported by recent neuroimaging work [66 , 67] . Thus , it seems possible that when peripheral stimuli are presented , enhanced activity in the auditory population code could skew perception of auditory space towards eccentric locations . Future research will need to determine exactly how activity in both cortical and subcortical regions contributes to humans’ perception of auditory space . Multisensory integration may be one of the strategies the nervous system attempts to reduce the problem of unisensory biases . Our behavioral data showed that biases in spatial perception were much smaller in bisensory congruent trials ( in which both sound and light were presented at the same location ) , relative to either the unisensory visual or unisensory auditory trials . Therefore , it appears that multisensory integration not only benefits perception by improving precision ( reducing variability ) , but also by reducing bias; a win-win approach . While the present work provides valuable insight into the computational mechanism underlying spatial biases in the visual and auditory systems , future research must address several pertinent questions . For example , future studies will need to address the extent of these biases in more complex environments , including more naturalistic settings . For instance , it has been reported that the localization of objects is often biased towards other elements in the visual field [7] . Known as the “landmark attraction effect” [68 , 69] , this effect is particularly relevant for the current paradigm; while this investigation illuminates the biases present in each modality in a sparse visual scene ( i . e . with only a fixation cross present at the start of each trial ) , the question remains as to how biases change as objects that are potential sources of the relevant auditory and visual signals are introduced to the environment . Finally , we also acknowledge that factors such as stimulus duration , response mechanism , and eye position could potentially influence the magnitude of the biases that emerge in a given modality . For example , one previous study presenting auditory stimuli for a much longer duration than our study ( 10s ) reported greater peripheral biases for eccentric auditory stimuli than what we found in this investigation [14] . Thus , future experiments should seek to systematically manipulate each of these factors to reveal the impact of each variable . Nearly every function critical for human survival depends directly on accurate localization of objects and events in the environment . While numerous studies have investigated spatial perception in humans , little consensus exists on whether representation of space in the human brain is accurate or biased , and if the latter is true , how so and why . The findings of this large-scale study revealed that on average , observers’ localizations are inaccurate , as visual localizations show a bias towards the center of space , while auditory localizations show a bias towards the periphery . Even more surprisingly , the observed biases in localization appear to be at least partly due to biases in sensory representations of space as opposed to a priori expectations of the spatial layout of objects in the environment ( which may be due to a number of non-sensory factors such as the experimental setup , instructions , learning the distribution of stimuli during experiment , etc . ) . In real-world settings , objects frequently produce signals that simultaneously stimulate multiple sensory modalities . Considering the opposing biases in the visual and auditory modalities , when visual and auditory stimuli co-occur at the same spatial location , which bias emerges during localization ? The results show that visual bias dominates , however , the magnitude of the central bias in the visual modality is reduced when the visual stimulus is integrated with a co-occurring auditory stimulus , thus revealing an additional advantage of multisensory integration: the reduction of perceptual biases . | Almost all daily tasks performed by humans require localizing objects and events . Since spatial localization is critical for survival , it is expected that the brain performs this task accurately . We tested the accuracy of localizing simple sounds and sights in hundreds of human observers . We found that , on average , localizations of sounds and sights were not accurate , and observers made systematic errors: flashes of light were perceived to be nearer the center of the visual field than they actually were , and bursts of noise were perceived farther away from center . Surprisingly , computational analyses revealed that these biases in perceived location of sounds and sights are at least partly due to a bias in how sights and sounds are encoded by the sensory systems; the visual representation of the world is compressed towards the center and the auditory representation is expanded away from the center . When flashes and noise bursts were presented at the same location simultaneously and the observers perceived a common source for both stimuli , the bias in the perceived location was smaller , showing that synthesizing information across modalities helps increase accuracy in the perceived location of objects and events , compared to when only one sensation is available . | [
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] | [] | 2015 | Biases in Visual, Auditory, and Audiovisual Perception of Space |
The sensory-motor neuron synapse of Aplysia is an excellent model system for investigating the biochemical changes underlying memory formation . In this system , training that is separated by rest periods ( spaced training ) leads to persistent changes in synaptic strength that depend on biochemical pathways that are different from those that occur when the training lacks rest periods ( massed training ) . Recently , we have shown that in isolated sensory neurons , applications of serotonin , the neurotransmitter implicated in inducing these synaptic changes during memory formation , lead to desensitization of the PKC Apl II response , in a manner that depends on the method of application ( spaced versus massed ) . Here , we develop a mathematical model of this response in order to gain insight into how neurons sense these different training protocols . The model was developed incrementally , and each component was experimentally validated , leading to two novel findings: First , the increased desensitization due to PKA-mediated heterologous desensitization is coupled to a faster recovery than the homologous desensitization that occurs in the absence of PKA activity . Second , the model suggests that increased spacing leads to greater desensitization due to the short half-life of a hypothetical protein , whose production prevents homologous desensitization . Thus , we predict that the effects of differential spacing are largely driven by the rates of production and degradation of proteins . This prediction suggests a powerful mechanism by which information about time is incorporated into neuronal processing .
Different patterns of training can lead to different types and strengths of memories . For example , training distributed over time ( spaced training ) is superior to the equivalent amount of training with no interruptions ( massed training ) for generating long-term memories for verbal tasks [1] . Spaced and massed training are known to activate different molecular signaling pathways underlying memory formation [2] . Aplysia californica , a marine mollusk , provides an ideal model system for examining the differences in molecular signaling mediated by spaced and massed training [3] . One form of behavioral sensitization in Aplysia involves an increase in defensive reflexes after a noxious stimulus . The increase in defensive reflexes is caused in part by an increase , or facilitation , of the strength of the synapse between the mechanoreceptor sensory neurons and withdrawal motor neurons [4] . Facilitation is mediated by release of serotonin ( 5HT ) from interneurons activated by the noxious stimulus [5] , [6] . Spaced noxious stimuli are superior to massed stimuli at generating long-term sensitization in the animal [3] and spaced applications of 5HT are superior to massed applications at generating long-term facilitation ( LTF ) of cultured sensory-motor neuron synapses [7] . The ability to examine the difference between spaced and massed training in cultured neurons allows the study of the differential signaling events activated by spaced and massed training . 5HT acts through at least two distinct G protein coupled receptors ( GPCRs ) in Aplysia to activate protein kinase A and protein kinase C [8] , [9] . The two kinases are differentially activated based on the type of training; spaced applications of 5HT lead to the persistent activation of PKA in the sensory neuron [10] , [11] , while massed applications of 5HT instead activate both PKA and the novel PKC Apl II in the sensory neuron ( Figure 1 ) [10] , [12] . An important mechanism for the differential activation of PKC during spaced and massed applications of 5HT involves differential desensitization of PKC Apl II translocation to the plasma membrane , where it is activated [13] . Spaced training ( 5×5 min 5HT with 15 min wash periods in between ) leads to more desensitization than one massed 25 min application of 5HT [13] . This differential desensitization is surprising , since spaced applications of 5HT allow the neuron to recover in between exposures; yet they cause a greatly increased amount of desensitization when compared to the massed application of 5HT . This effect was shown to depend on both PKA-mediated desensitization and the downstream effects of protein synthesis [13] . Importantly , protein synthesis inhibitors have opposite effects depending on the training stimulus: massed training produces a protein that prevents desensitization of PKC Apl II translocation while spaced training produces a protein that promotes desensitization of PKC Apl II translocation ( Figure 1 ) [13] . Thus , another important distinction between these two training paradigms is that they activate distinct translational pathways . While massed applications of 5HT are less effective than spaced applications at generating LTF measured at 24 h [7] , both spaced and massed training lead to protein-synthesis dependent intermediate-term facilitation ( ITF ) , measured 30 min to 2 hr after 5HT is removed [11] , [14] , [15] . However , the mechanisms underlying ITF induced by spaced or massed training are distinct; ITF induced by spaced training require PKA but not PKC for induction [16] , [17] , while ITF induced by massed training , even a continuous stimulus as short as 10 min , requires PKC but not PKA [14] ( Figure 1 ) . Thus , the differential activation of PKC during massed and spaced training appears critical for the different physiological effects of these two training paradigms . In order to better understand the signaling pathway mediating the desensitization of PKC Apl II , we developed a model consisting of a system of integro-differential equations describing the differential desensitization of PKC Apl II activation during massed and spaced training . The model provides predictions about the molecular mechanisms responsible for the differences between massed and spaced training . These predictions were validated with new experiments . Together these results suggest that the sensitivity of neurons to the time between training periods is due to the rates of protein synthesis and degradation .
We have previously described PKC Apl II translocation and its desensitization in response to 5HT application in the presence of PKA and protein synthesis inhibitors [13] , [18] , [19] . We showed that PKC translocation differentially desensitizes to spaced and massed applications of 5HT , and that this differential desensitization was dependent on protein translation and PKA activity . In order to understand the molecular mechanisms underlying desensitization of PKC Apl II translocation we designed a signaling network based on our previous experimental findings and biochemical mechanisms known to underlie G protein-coupled receptor ( GPCR ) desensitization . Our network consists of the translocation of PKC , the cycling of a GPCR , the translation of two hypothetical proteins , and activity of PKA . We have tried to simplify the network whenever possible , including bundling multiple biochemical reactions into one single rate in order to simplify its architecture . The reasoning behind the network's architecture is given in this section and the model equations are given in the Materials and Methods section . The basic unit of the model is the 5HT GPCR ( S ) that once activated leads to the production of diacylglycerol ( DAG ) , which is capable of activating and translocating PKC Apl II to the membrane [20] , [21] . While this pathway consists of multiple steps , such as G-protein activation of phospholipase C and phospholipase D [18] , these are not likely to be important for modeling of desensitization , since in most systems the amount of the activatable GPCR is the rate-limiting quantity that is decreased during desensitization [22] , [23] , [24] . GPCRs can enter a number of different pathways , such that S can exist in several different states , where the change in concentration of each state with respect to time is modeled . The base component of our model includes the activation and inactivation of S without any desensitization dynamics . This component corresponds to how quickly PKC Apl II translocates to the membrane after 5HT application and how quickly it dissociates from the membrane after 5HT is washed away . It is known that application of 5HT results in a maximal translocation of PKC Apl II within one minute , after which it remains at this maximal level for at least five minutes [18] , [19] . Washing off 5HT prompts the complete dissociation of PKC Apl II within one minute [13] , [18] , [25] . To replicate these findings , we used a simple network architecture , whereby in the presence of 5HT , SOFF becomes SON , which then transforms to SIN1 . SOFF represents the inactivated receptor that can become activated by 5HT , turning SOFF into SON , which then produces DAG allowing for the translocation of PKC Apl II . SIN1 is an inactivated receptor that needs to be recycled before it can become activated by 5HT again . At a biochemical level , the transitions from SON to SIN1 to SOFF involve multiple molecular steps including GPCR phosphorylation by G protein receptor kinases , binding of beta arrestin , possible internalization of the receptor , unbinding of the ligand , and then recycling of the receptor back to its initial state [22] , [23] , [24] . For simplicity , we have reduced these multiple steps into the two steps ( SON to SIN1 to SOFF ) since ( i ) this is sufficient to capture the behavior required to understand the questions we are addressing ( see below ) and ( ii ) we have no specific knowledge concerning regulation of these pathways in Aplysia . The major constraint from the data is that PKC comes off the membrane in less than one minute after 5HT is washed off . Thus SON to SIN1 must be fast enough to account for this inactivation . However , in the first 5 min of 5HT activation , there is little desensitization of PKC Apl II translocation . Thus , SIN1 to SOFF must be rapid enough to prevent appreciable desensitization in the first five minutes . The transitions between states of S were modeled using mass action kinetics . These model parameters were fit to the previously described PKC dynamics [13] , [18] , [25] ( equations , parameter values , and parameter estimation methods can be found in the Materials and Methods section ) . Once an appropriate fit was found these parameters were set and we were able to begin expanding the model and modeling data related to PKC Apl II desensitization . The complete model architecture is presented in Figure 2 . The model components ( color coded ) were developed sequentially , with maroon and black first then blue , red , and finally green . The maroon component represents only the translocation of PKC to the plasma membrane and its subsequent dissociation from the membrane . The black component represents the desensitization pathway in the presence of a protein translation inhibitor and a PKA inhibitor . In the presence of these inhibitors , PKC Apl II translocation desensitizes during exposure to 5HT [13] . Thus , there must be a protein translation-independent and PKA-independent desensitization pathway , or a homologous desensitization pathway , which we model as an alternate recycling pathway from SIN1 to SOFF , passing through SIN2 ( Figure 2; black network only , equations can be found in the Materials and Methods section ) . Here SIN2 acts as a secondary inactivated state that requires a longer processing time than SIN1 before recycling back to SOFF . At the biochemical level , this represents the sorting of the GPCR in the endocytic compartment from a rapid recycling pathway into a slow recycling pathway or degradative pathway . This architecture was chosen because of the abundant literature supporting this mechanism for desensitization of GPCRs [22] , [23] , [24] . PKA , which is activated by 5HT , has been shown to increase desensitization of PKC Apl II translocation in the absence of protein translation [13] . The condition where PKA is active and protein translation is inhibited is modeled by the combination of the black , maroon , and blue components . In order to model PKA-mediated protein synthesis-independent desensitization , we included a reduced and modified version of a previous model of PKA activity [26] . Our modifications to this PKA model are described in the next sections . Activity of PKA is capable of converting SOFF directly into SPKA , where SON is not immediately attainable and PKC Apl II cannot be activated ( Figure 2; black and blue networks , equations can be found in the Materials and Methods section ) . At the biochemical level , this network would represent phosphorylation of the receptor , or receptor-associated protein , by PKA causing the endocytosis of the GPCR from the plasma membrane to an endocytic compartment distinct from SIN1 and SIN2 , probably representing a regulated recycling endosome [27] . It is important to note that since PKA can convert SOFF to SPKA , conversion to SPKA does not require S to go through the active state , SON , such as the desensitization mediated by SIN2 . This network architecture is required to account for the observation that PKA activity between pulses of 5HT , when S would not be activated , is capable of desensitizing PKC Apl II translocation [13] and is consistent with data on heterologous desensitization of GPCRs in other systems [28] . This consideration also removed the alternate topology where SPKA would represent alternate sorting from SIN1 , since the receptor is only in the SIN1 state when the receptor goes through the active state . The recycling of SPKA back into SOFF is inhibited by PKA . This inhibition was not initially part of the architecture , but it was not possible to replicate both the massed training and spaced training data sets without including the PKA inhibition of SPKA recycling ( see results below ) . At a biochemical level , this suggests that PKA activity is not only required to induce sorting of the receptor to the regulated recycling endosome but its retention in this compartment as well . The reverse situation , with PKA activity inhibited but protein translation allowed to function is modeled by the combination of the black , maroon , and red components . Protein translation in the absence of PKA activity leads to a reduction in the desensitization of PKC Apl II translocation only during massed 5HT application and not spaced [13] . This observation requires that a protein , which protects PKC Apl II translocation from the constitutive desensitization pathway be translated during massed training . We name this hypothetical protein Anti-Desensitizer ( AD ) and its effects on the network are represented by the black , maroon and red components combined . We modeled the mechanism of AD mediating this protection by having AD convert SOFF into SAD , a form of S preserved from the desensitization pathways leading to SIN2 or SPKA , but similar to SOFF in its ability to become activated by 5HT and cause the translocation of PKC Apl II ( Figure 2 , black , maroon and red pathway; equations can be found in the Materials and Methods section ) . At the biochemical level , this would represent the AD protein binding to the receptor , or receptor associated protein , preventing its inactivation and internalization [29] , [30] , [31] , [32] . Since a protein-synthesis dependent protection from desensitization is seen in massed , but not spaced , training protocols , we would expect AD to be synthesized only after massed training . In order for this differential synthesis to occur , we made production of AD proportional to the mathematical integration of the level of active PKC Apl II . PKC Apl II is constantly active during massed training , but not during spaced training; thus , integrating PKC activity allows for selective activation of AD during massed training . PKC is known to regulate the translational machinery in many systems [33] , [34] including Aplysia [35] , [36] , but the exact mechanism by which PKC regulates translation in this case is not known and is not explicitly modeled here . Finally , allowing both protein translation and PKA activity to proceed normally results in an increase in the desensitization of PKC Apl II translocation during spaced training [13] . This increase in desensitization was observable only when both PKA activity and protein translation are allowed to proceed , meaning a translated protein is mediating this increase in desensitization , and its rate of translation is dependent on PKA activity . We name this hypothetical protein Desensitizer ( D ) , and we model its mechanism of action similarly to that of PKA by transforming SOFF into SPKA and inhibiting its recycling back to SOFF ( Figure 2 , complete network; equations can be found in the Materials and Methods section ) . Another possible architecture would have been to generate another state of S ( SD ) , but there was not a good biochemical rationale for this and the model worked well ( see below ) without this additional state . At the biochemical level , D would be a protein that promotes endocytosis [29] , particularly to the PKA-dependent pathway . The rate of translation of D is dependent on the amount of PKA activity , similar to the dependence of AD translation on PKC Apl II activity . One difference between the translation of D and AD is that D's production is delayed by 10 min after its induction . The use of a delay was necessary to account for the observation that desensitization of PKC Apl II translocation after a 5 min pulse of 5HT did not begin until after a 10 min wash [13] . At a biochemical level , there may be many reasons for a delay , ranging from requirements for post-translational modification , cellular trafficking , or delay in the activation of proteins synthesis . Finally , while trying to model the data we found that for D to cause enough desensitization during spaced training resulted in too powerful an inhibition during massed training . This over-inhibition resulted from the fact that unlike AD , D is synthesized during both spaced and massed training since PKA is active in both scenarios [10] . To diminish the role of D during massed training , we introduced two additional effects of the AD protein . First , AD inhibited the transition from SOFF to SPKA , and second , it could transform not only SOFF to SAD but also SPKA to SAD ( Figure 2; complete network ) . At a biochemical level , this corresponds to the ability of the AD protein to prevent endocytosis to the PKA-dependent pathway , and moreover , to bind to the GPCR in the regulated recycling endosome and enhance its recycling , similar to the mechanism by which decreased PKA activity enhanced recycling from this compartment . We also attempted to model the system with AD preventing the translation of D as opposed to opposing its actions , but were unable to achieve a good fit to the data with this architecture . For simplicity , we made the assumption that during the time course of our experiments an insignificant amount of new S is created . This assumption was also made partially because for S to enter the SOFF state , the GPCR would not only have to be synthesized , but processed through the endoplasmic reticulum , Golgi apparatus , and transported back to the membrane , so new S could only contribute to the later parts of the experimental paradigm . We do not have a term for destruction of S , however , as described below , the SIN2 pathway may be equivalent to a degradation pathway , where the GPCR enters late endosomes and lysosomes . PKC Apl II translocation still desensitizes during exposure to 5HT even when both protein translation and PKA have been inhibited [13] . Thus , there must be a homologous desensitization pathway ( Figure 3A; black network only , equations can be found in the Materials and Methods section ) . Parameter values were estimated by fitting the model to PKC Apl II translocation measurements taken during a continuous 90 min application of 5HT in the presence of the protein translation inhibitor anisomycin and the PKA inhibitor KT5720 [13] . Several parameter estimation methods were used , and surprisingly , all of them yielded recycling rates of SIN2 back to SOFF ( kA5 ) that were near zero ( parameter values can be found in Table 1 ) , resulting in an excellent fit to the data as can be seen in Figure 3C ( R2>0 . 99 ) . Note that throughout the paper , data presented in blue represents data obtained from Farah et al . ( 2009 ) used to train the model , while data presented in red represents experiments performed to confirm predictions of the model . The model predicted very little recycling of the signaling complex from SIN2 during massed training in the absence of protein translation and PKA activity ( Figure 3C , D ) . This was unexpected , since our earlier experiments showed that the desensitization seen after a 5 min pulse of 5HT recovered completely within 45 min , suggesting efficient recycling of the signaling complex [13] . However , these experiments were not done in the presence of a PKA inhibitor . To test the prediction of the model that desensitization seen in the absence of PKA activity was not reversible , we conducted a new experiment . The rate of SIN2 recycling was predicted to be slow enough that a wash period after massed training with anisomycin and KT5720 would result in little recovery of translocation to initial values . Thus , in a simulation of a 90 min exposure to 5HT followed by a 45 min wash and then a 5 min pulse of 5HT , all in the presence of anisomycin and KT5720 , the 5 min pulse of 5HT should only cause a small amount of PKC Apl II translocation , since a majority of S is held in the inactivated state SIN2 ( Figure 3C , D ) . To test this prediction of the model , we used this protocol in a new imaging experiment using Aplysia sensory neurons expressing eGFP-PKC Apl II . The initial massed training caused a similar amount of translocation to that previously observed by Farah et al . ( 2009 ) ( Figure 3B , C ) . Furthermore , the amount of desensitization after the 5 min pulse of 5HT matched the modeling prediction extremely well , demonstrating that recovery from desensitization under these conditions was indeed very slow ( Figure 3B , C ) . This protocol required that the neurons be imaged for a total of 140 min . To ensure that the lengthy exposure to room temperature ( 20–23°C ) and the drugs anisomycin and KT5720 had no effect on the health of the neurons , or their ability to translocate PKC Apl II , two 5 min pulses of 5HT were applied with a 130 min wash in between , all in the presence of both drugs . Recovery from a 5 min pulse of 5HT occurs after 45 min [13] , so we expect that a 130 min wash should result in complete recovery and that any depression in PKC Apl II translocation would be caused by injury to the neurons due to prolonged exposure to room temperature and drugs . There was no significant difference in the amount of PKC Apl II translocation between the first and second pulse of 5HT ( mean+/−sem; 1 . 08+/−0 . 18 , n = 5 ) . Thus the persistent desensitization observed in the previous experiment is due only to accumulation of S in SIN2 , as predicted by the model and not due to injury to the neurons . PKA , which is activated by 5HT , has been shown to increase desensitization of PKC Apl II translocation during both massed and spaced training [13] . In order to model PKA mediated desensitization , we included a reduced and modified version of a previous model of PKA activity [26] . We reduced the complexity of this model to only include only the dynamics of cAMP production and the association and dissociation of the subunits of PKA . This simplification was done since our experiments and simulations do not occur over long enough time periods for us to expect a contribution from the persistent activity of PKA , which was a major feature of their model . We modified the Pettigrew et al . model by altering the basal level of cAMP and the association rate of the PKA subunits to refine PKA dynamics to better match published data demonstrating PKA activity persisting for a small period after washout of 5HT [10] , [37] , [38] . This revision was necessary since PKA activity during the wash period is required for desensitization [13] . The new PKA dynamics to massed and spaced training can be seen in Figure 4A–C . Furthermore , we removed any synthesis or degradation of PKA subunits since , similar to PKC Apl II , we do not expect a significant change in the amount of protein during the time course of our experiments [10] . The black and blue networks ( Figure 3A ) make use of the previously described PKA activity model to affect the desensitization of PKC translocation . Two data sets were used to estimate the parameters of the blue component of the model: one continuous 90 min application of 5HT in the presence of anisomycin and five pulses of 5HT each lasting 5 min with 15 min washes in between , all in the presence of anisomycin [13] . The parameters were estimated to fit both data sets . The conversion of SOFF into SPKA is modeled using mass action kinetics . The recycling of SPKA back into SOFF is inhibited by PKA and is modeled using a combination of mass action kinetics and an inhibitory Hill function ( see Materials and Methods section ) . This network architecture resulted in an excellent fit to both data sets ( R2 = 0 . 99 for massed training and 0 . 88 for spaced training ) ( Figures 4D , 5B ) . It was not possible to replicate both the massed training and spaced training data sets without including the PKA inhibition of SPKA recycling . Without this inhibition , fitting the massed training data set caused too much desensitization during spaced training and fitting the spaced training data set caused insufficient desensitization during massed training . Massed training in the absence of protein synthesis leads to more desensitization of PKC Apl II translocation when PKA is active [13] . However , the model predicts that soon after 5HT is washed away , PKA becomes inactive and SPKA can recycle back to SOFF . This recycling suggests that unlike SIN2 mediated desensitization , PKA induced desensitization recovers quickly . Thus , when we simulate a 90 min exposure to 5HT followed by a 45 min wash and then a 5 min pulse of 5HT ( as above , but in the absence of a PKA inhibitor ) , the model predicts a considerable recovery of PKC translocation ( Figure 5B , C ) . This recovery happens because during the 90 min stimulation , the majority of S is held in SPKA , and during the wash most of SPKA recycles back to SOFF . This recycling allows for a greater amount of PKC translocation compared to when PKA was inhibited and the majority of S is found in SIN1 ( Figure 3C ) . To test this prediction of the model , we conducted a new imaging experiment , measuring the translocation of eGFP-PKC Apl II during the application of the above protocol ( Figure 5A ) . The translocation of PKC Apl II caused by the 5 min pulse of 5HT after the 45 min wash is in agreement with the modeling prediction , thus validating this component of the model ( Figure 5B ) . The amount of desensitization of PKC Apl II translocation during the massed training is equivalent to that observed by Farah et al . ( 2009 ) and , as in that study , PKA increases the amount of desensitization during massed training . However , despite this increased desensitization in the presence of PKA , active PKA increases the recovery from desensitization , as predicted by the model . The large difference between the recovery in the presence or absence of the PKA inhibitor , KT5720 , is illustrated in Figure 5D . The rescue from desensitization by the AD protein is modeled using the black and red network components in combination ( Figure 6A , red pathway ) . Two data sets were used to estimate the parameters of this component of the model: 90 min application of 5HT in the presence of KT5720 and five 5 min pulses of 5HT with 15 min washes in between , all in the presence of KT5720 [13] . The model produced an excellent fit to both data sets ( R2 = 0 . 95 for spaced training and 0 . 99 for massed training ) ( Figure 6B , D ) . One of the unexpected predictions of the model was both a fast degradation of AD , ( with a half-life of ∼5 min ) and a slow rate of the SAD→SOFF recycling . To validate this component of the model , we designed a protocol that would be sensitive to the fast degradation rate of AD . This protocol consisted of exposure to 25 min of 5HT in the presence of KT5720 then 65 min of 5HT in the presence of both KT5720 and anisomycin , with no wash in between . This protocol allows for the indirect observation of the degradation of AD and the recycling of SAD back into SOFF . The addition of anisomycin will terminate the translation of AD . During these last 65 min , the model predicts that AD will decay and thus be less effective at transforming SOFF into SAD ( Figure 6C ) . The model further predicts that the absence of AD will cause the remaining SAD to recycle back into SOFF , where it will lose its protection from the homologous desensitization pathway , which will manifest in decreased PKC Apl II translocation . Thus , by observing the increased amount of desensitization of this protocol in comparison to when AD translation is present throughout , we can validate the model's predicted rate of AD degradation and rate of SAD recycling back into SOFF . To test these predictions of the model , a new imaging experiment was performed by applying this protocol to Aplysia sensory neurons expressing eGFP-PKC Apl II . As expected , the amount of PKC translocation observed in these neurons during the first 25 min of 5HT was equivalent to that observed during the 25 min of massed training in the presence of KT5720 , carried out by Farah et al . ( 2009 ) ( Figure 6A , B ) . However , the final 65 min of this protocol , where both KT5720 and anisomycin are present , caused a lower amount of PKC Apl II translocation compared to that caused by massed training in the presence of only KT5720 , in agreement with the model prediction ( R2 = 0 . 99 ) confirming the fast degradation rate of AD and the slow rate of SAD to SOFF ( Figure 7C ) . During spaced training , the desensitization of PKC Apl II translocation was increased in control cells in comparison to when protein translation was inhibited . This increase in desensitization was observable only when both PKA activity and protein translation are allowed to proceed , meaning a translated protein is mediating this increase and its rate of translation is dependent on PKA activity . We name this hypothetical protein Desensitizer ( D ) , and its effects on PKC Apl II translocation are modeled by the green component of the network ( Figure 2 ) . Seven data sets were used to estimate the parameters of this component of the model: one continuous 90 min application of 5HT , five pulses of 5HT each lasting 5 min with 15 min washes in between , and five experiments , each with two pulses of 5HT each lasting 5 min but with a different wash period length ( 5 min , 10 min , 15 min , 30 min , 45 min , ) in between the pulses [13] ( Figure 8A , C , E ) . The resulting model formed an excellent fit to the data ( R2 = 0 . 99 for massed training , 0 . 99 for spaced training , and 0 . 75 for two pulses of 5HT with varying wash intervals ) . One exception is the 5 min pulse followed by a 5 min wash , where there is an increase in PKC Apl II translocation compared to the initial translocation , while our model shows no increase in translocation . We believe fitting this increase would require a more detailed dissection of the pathway between the GPCR and its downstream targets and is beyond the scope of this study . As one of the rationales for generating this model was to gain insight into the role of spacing , our final confirmation of the model tested an alternate spacing protocol . We designed an experiment that would require the functioning of all the model components and that made a specific prediction that was not obvious and could be tested . Interestingly , we found that if 15 min pulses of 5HT were used , the model predicted that longer washes would lead to increased desensitization . While 15 min pulses produce both D and AD , the model predicts that longer washes will reduce the levels of AD compared to D and thus predicts greater desensitization by longer washes ( Figure 9B and E ) . In particular note that the model predicts that with the shorter spacing ( Figure 9C ) , the amount of S complex in SAD is larger than in SPKA immediately before the second pulse , while with longer spacing ( Figure 9F ) , the model predicts that there is more S complex in SPKA , than in SAD . Thus , the second pulse of serotonin during the protocol with longer spacing should be less able to translocate PKC Apl II because of the conversion of SAD to SPKA . To test this prediction , we performed a new imaging experiment where sensory neurons were exposed to three 15 min pulses of 5HT with either 15 min or 25 min washes in between the 5HT pulses . The results of this protocol are also sensitive to the delay and rate of D translation ( parameters that had not yet been validated in a separate experiment ) . Both protocols were applied to Aplysia sensory neurons expressing eGFP-PKC Apl II . The amount of PKC translocation during both protocols matched the modeling prediction ( R2>0 . 99 ) ( Figure 9A , B , D , and E ) and thus validates this component of the model as well as the functioning of the completed model . In particular , to highlight the effect of the wash , we calculated the amount of desensitization during the 15 min or 25 min wash ( e . g . the amount of translocation at the beginning of pulse 2 compared to the end of pulse 1 , or the beginning of pulse 3 compared to the end of pulse 2 ) . The model predicted more desensitization during the longer wash and this was confirmed by the imaging experiment ( Figure 10 ) . A parameter sensitivity analysis was performed on the completed model to investigate which parameters were most important in driving the results of the model . Each parameter was varied between +/−5% and +/−50% while holding the other parameters at their defined values . The model was then simulated using a 90 min application of 5HT and its resulting PKC Apl II translocation compared to that observed by Farah et al . ( 2009 ) , which was initially used to fit the model . The sensitivity of a parameter was classified as High if either a +/−5% change in its value caused a change in the fit of the data of over 25% . Similarly , the sensitivity of a parameter was Medium if either a +/−50% change in value caused a change in the fit of the data of over 25% , and Low if the +/−50% change in value did not change the fit by more than 25% . This was then repeated using a spaced application of 5HT ( 5×5 min 5HT with 15 min washes ) . The complete sensitivity analysis is summarized in Table 1 . Of the 41 parameters , 5 were classified as High , 12 as Medium , and 6 as Low in both massed and spaced training sensitivity analysis . Interestingly , the majority of the parameters ( 3/5 ) with high sensitivity for both types of training were those associated with the initial component of the model responsible for activating PKC Apl II . The remaining two parameters involved how AD works ( the synthesis rate and its ability to stop S from going into SPKA ) . It is not surprising that changing parameters that affect the initial translocation of PKC Apl II by 5HT and its decay after 5HT is removed would have a large effect on the model output , since the model was built around this core . However , these parameters were chosen in a somewhat arbitrary fashion to fit the initial data since the actual rates of DAG synthesis and decay are not known in this system . To ensure that the set of values we chose for these parameters are not critical for the working of the model , we found another parameter set that could fit the initial translocation data ( see Table 1 ) . Reassuringly , the rest of the model still worked , suggesting that the model was not dependent on the actual values for these initial parameters , just the ability of the model to replicate the known rate of PKC Apl II translocation and dissociation by 5HT . The remaining 18 parameters had sensitivities dependent on the type of 5HT application profile . Interestingly , about the same number of parameters had specific high sensitivity for massed ( 5 ) vs spaced ( 4 ) . For spaced , two of these are again from the initial model and the others concern the synthesis rate of D and AD . Similarly , for massed , two of these are for the initial model and the others concern the synthesis rate for D . The sensitivity analysis suggests , similar to the experiments , that the critical parameters that determine the model are involved in the synthesis of D and AD .
The architecture of our model is based on the fact that desensitization and resensitization of GPCRs is due to endocytosis followed by exocytosis , the simplest biological substantiation of the states of S are distinct endocytic recycling pathways of the receptor or distinct states of the receptor after association with GPCR binding-proteins [29] , [39] . Below we review these processes and the plausibility of the parameters we have assigned to these steps . We also review other aspects of the model and whether the parameters and architecture are biologically plausible . Spaced vs . massed training occurs in a number of different time scales , thus molecular mechanisms are required that act in different time domains . For example , induction of LTP by spaced stimuli requires PKA , but not when massed stimulation is used [58] , and the spaced stimuli were required to recruit protein synthesis-dependent mechanism [59] . A recent model explains this finding based on the differential effects of calcium on PKA and CAMKII . This model depends on inter-trial intervals that range between seconds and 5 minutes [60] . The frequency dependent activation of CAMKII is sensitive to timing intervals in this period and is proposed to be the mechanism for sensing the spacing between stimuli [61] . In mice object recognition was enhanced by spacing of 15 min , compared to 5 min or massed training [62] . In mice that lacked Protein Phosphatase 1 ( PP1 ) , 5 min spacing was sufficient for learning . In this case the rate-limiting step for learning was activation of CREB , and spacing was required in order for PP1 to be deactivated before the next training trial allowing for CREB activation [62] . CREB activation is also the proposed difference between spaced and massed learning in Drosophila odor avoidance [63] . In Drosophila , spacing is regulated by waves of MAP kinase activation where both the activation and decay kinetics appear critical for the spacing interval [64] . In Aplysia , it has recently been demonstrated that for long-term facilitation , only two spaced trials are required , 45 minutes apart , but neither 30 nor 60 minute spacing is adequate [65] . Again , in this case the spacing corresponds to a wave of MAP kinase activation [65] . None of these cases directly implicate the rates of protein synthesis or degradation as critical for timing , although it is possible that the induction of MAP kinase activation at later times may require protein synthesis . Interestingly , the activation of CREB in mammals appears to require removal of CREB repressor , which requires both blockade of translation through eIF2a dephosphorylation [66] and increased degradation due to proteosomal activation [67] . Thus , in this case regulating the level of a protein also may mediate differences between spaced and massed trained determining whether or not transcription is activated . It will be interesting in the future to determine how generally neurons sense time through measuring the half-life of newly synthesized proteins .
A mathematical model of the desensitization of PKC Apl II translocation in Aplysia californica sensory neurons was constructed in the MATLAB programming environment . The model consists of a system of integro-differential equations with delays , where each equation describes the change in concentration of the proteins PKC Apl II , PKA , Desensitizer ( D ) , Anti-Desensitizer ( AD ) , and of each instance of the signaling complex ( S ) . Since we are only interested in PKC Apl II translocation occurring between the cytosol and plasma membrane [18] a single compartment model was used . The complete model is depicted in Figure 2 . The colours of this figure correspond to the components of the model . The model was constructed in a sequential manner . First , the components outlined in black and maroon were fit to data [13] at which point its parameters were specified and not allowed to change . Following these component's completion , the component outlined in blue was similarly constructed , then the red component and finally the green component . In order to illustrate this sequential construction within the model equations , we have named the parameters according to which component they reside in: A for the black component , B for blue , C for red , and D for green . The most basic component of the model is the translocation of PKC Apl II from the cytosol to the plasma membrane ( maroon component ) . This translocation is proportional to the concentration of diacylglycerol ( DAG ) on the membrane and thus the translocation is given by the following equation: ( 1 ) where kDAGp is the rate of PKC Apl II translocation to the membrane , and kDAGd the rate of PKC Apl II removal from the membrane . SON represents the proportion of S currently in the active state , which is capable of translocating PKC Apl II to the membrane . The inactive state of S is given by SOFF , and SIN1 is a transition state between SON and SOFF . S can be transformed into 3 other states , as will be described next . We require the total amount of S to remain constant by employing the following restriction: , where i = ON , OFF , IN1 , IN2 , PKA , AD , and D . We scale each S variable by 1/STOT , such that all parameters ki , i = A1–A5 , B1–B2 , C1–C2 , and D1–D3 will have units min−1 . We have set STOT = 1 , where we refrain from assigning units to the S variables since we cannot measure the concentrations of PKA or PKC in Aplysia neurons in order to accurately define a unit of measure . Furthermore , units are not assigned to any variable with concentration as a possible dimension . This simplification is justified since we have developed a single compartment model of Aplysia sensory neurons to qualitatively describe the dynamics of PKC desensitization . Using non-dimensional variables and parameters allows us to observe important dynamics , such as relative magnitudes of proteins and the time course of S recycling , which allow us to gain insight into the molecular regulatory mechanism involved in the desensitization of PKC translocation . The following equations describe the rates of change of concentration of the first four S states: ( 2 ) ( 3 ) ( 4 ) ( 5 ) where [5HT] represents the concentration of 5HT being applied to the system and is given a standard value of 10 µM during any application of 5HT , kA1 represents the transformation of SOFF into SON , kA2 of SON into SIN1 , kA3 of SIN1 into SOFF , kA4 of SIN1 into SIN2 , and kA5 of SIN2 into SOFF . The additional terms in equation ( 3 ) refer to the further transformations that SOFF can undergo . Without these additional terms these equations describe the black model in Figure 3A . The first additional transformation of SOFF is mediated by the catalytic subunit of PKA , where SOFF is converted to SPKA , which has the following equation: ( 6 ) where kB1 is rate constant of the transformation from SOFF into SPKA , which is brought about by the activity of the catalytic subunit of PKA or the protein D . However , the protein AD , through a Hill function with coefficient kD1b and half saturation kD1a , can inhibit this conversion . The recycling of SPKA into SOFF occurs with rate constant kB2 , but is inhibited by PKA and D through inhibiting Hill functions with coefficients kB2b and kD2b , respectively , and half saturations kB2a and kD2a , respectively . Also , activity of AD can convert SPKA into SAD with a rate constant kD3 and a Hill function with coefficient kD3b and half saturation kD3a . The dynamics of the catalytic and regulatory subunits of PKA are adapted from a model presented by Pettigrew et al . ( 2005 ) , where the changes to this model are described in the results . PKA dynamics are given in the following equations: ( 7 ) ( 8 ) ( 9 ) ( 10 ) Where Vm is the cAMP synthesis rate constant , and K5HT is the half saturation of the Hill function associated with cAMP synthesis . Kfpka is the rate constant associated with the dissociation of the catalytic and regulatory subunits , while the reassociation rate is given by Kbpka . The amount of PKA activity is set equal to the amount of the free catalytic subunit ( C ) ; PKA = C . The parameters associated with protein synthesis are given the subscript S to differentiate them from signaling complex dynamics . The synthesis of AD and D are given by the following equations: ( 11 ) ( 12 ) ( 13 ) ( 14 ) AD synthesis depends on the total activity of PKC Apl II over a previous time window of duration given by intPKC in equation ( 12 ) . The integration of PKC Apl II activity leads to the synthesis of AD through a Hill function with coefficient kS1b and half saturation kS1a . kS2 represents the AD degradation constant . Similarly , D synthesis depends on an integration of PKA activity over a time period of intPKA in equation ( 14 ) , which leads to the synthesis of D with a rate constant of kS3 and through a Hill function with coefficient kS3b and half saturation kS3a . The degradation of D is given by rate constant kS4 . D leads to the transformation of SOFF into SPKA , which was described above in equation ( 6 ) , while AD transforms SOFF into SAD , whose dynamics are modeled with the following equation: ( 15 ) where kC1 is the rate constant associated with the transformation of SOFF into SAD , kC2 the rate constant of the recycling of SAD into SOFF , which can be inhibited by AD through a Hill function with coefficient kC2b and half saturation kC2a . Also , SAD can become activated when 5HT transforms it into SADON , whose dynamics are given in the following equation: ( 16 ) whose transformation and recycling rate constants are identical to those of SOFF into SON . SADON activates PKC Apl II in an identical fashion to SON in equation ( 1 ) . The system was solved numerically by employing a 4th order Runga-Kutta scheme to solve the differential equations and the Trapezoid Rule to solve the integrals [68] . Parameter estimation was conducted with the help of the MATLAB Optimization Toolbox and Global Optimization Toolbox , specifically the functions lsqcurvefit , ga , and fmincon . These functions were used to minimize the least squares distance between the modeling output and experimental data . Values of individual parameters are given in Table 1 . Adult Aplysia californica ( 76 to 100 g; University of Miami Aplysia Resource Facility , RSMAS , FL ) organisms were anesthetized by an injection of 50 to 100 ml of 400 mM ( isotonic ) MgCl2 . Pleuropedal ganglia were removed and digested in L15 medium containing 1% protease type IX ( Sigma ) . L15 medium was purchased from Sigma and supplemented with 0 . 2 M NaCl , 26 mM MgSO4·7H2O , 35 mM dextrose , 27 mM MgCl2·6H2O , 4 . 7 mM KCl , 2 mM NaHCO3 , 9 . 7 mM CaCl2·2H2O , 15 mM HEPES , and the pH was adjusted to 7 . 4 . Following digestion , tail sensory neurons were isolated and plated in L15 medium containing 50% Aplysia hemolymph on MatTek glassbottom culture dishes ( MatTek Corporation , Ashland , MA ) with a glass surface of 14 mm and a coverslip thickness of 0 . 085 to 0 . 13 mm . The dishes were pretreated with poly-L-lysine ( molecular weight , >300 , 000; Sigma ) . The pNEX3 enhanced green fluorescent protein ( eGFP ) PKC Apl II has been described previously [13] , [19] , [69] . On day 1 after isolation , solutions of plasmids in distilled water containing 0 . 25% fast green were microinjected into neurons from back-filled glass micropipettes . The tip of the micropipette was inserted into the cell nucleus , and short pressure pulses ( 10–50 ms duration; 20 lb/in2 ) were delivered until the nucleus became uniformly green . The cells were incubated for 4–5 hrs at room temperature and then kept at 4°C until use . Neurons expressing eGFP-PKC Apl II were imaged on a Zeiss laser-scanning microscope ( Zeiss , Oberkochen , Germany ) with an Axiovert 200 and a ×40 or ×63 oil immersion objective with a 25-mW argon laser with 25% laser output . The laser line was attenuated to 4% transmission output prior to live imaging . 5HT ( 10 µM ) was added to the dish in L15 medium containing 50% hemolymph . 5HT was washed away with artificial seawater ( ASW; 10 mM HEPES , pH 7 . 5 , 0 . 46 M NaCl , 10 mM KCl , 11 . 2 mM CaCl2·2H2O , 55 mM MgCl2·6H2O ) . For spaced training , neurons received five applications of 10 µM 5HT ( 5 min each ) at an intertrial interval ( ITI ) of 20 min . For massed training , neurons received a single continuous application of 10 µM 5HT for 90 min . All experiments were performed at room temperature ( 20 to 23°C ) . Anisomycin ( Sigma-Aldrich ) , and KT5720 ( Calbiochem ) were used at concentrations of 50 µM , and were present in the media throughout spaced or massed training . There was no pre-incubation with these drugs prior to 5HT treatment and because of this we erred on the high side of the concentrations that have been used previously . The controls used in all experiments were always performed from the same batch of animals when the drugs were used . The translation inhibitor anisomycin was purchased from Sigma-Aldrich . The level of PKC Apl II translocation for each cell was determined by tracing three rectangles at random locations at the plasma membrane and three rectangles at random locations in the cytosol . The width of the membrane rectangles was three-five pixels wide to avoid cytoplasmic contamination , but otherwise the size of the rectangles was not constrained . The average intensity at the membrane ( Im ) and the average intensity in the cytosol ( Ic ) was then calculated and the Im/Ic ratio is the degree of membrane association . In all figures , the control used to normalize the translocations in the presence of a drug is the post 5HT #1 in the presence of that drug . | Memories are among an individual's most cherished possessions . One factor that has been shown to exert a powerful influence on memory formation is the pattern of training . Learning trials distributed over time have been shown to consistently produce longer lasting memories than trials distributed over short intervals , in every organism in which this has been studied . This observation has been investigated particularly well in the marine mollusk Aplysia californica . The nervous system of Aplysia is simple and well characterized , yet capable of forming memories , making it an ideal system for the study of learning and memory . Currently , we have a detailed understanding of memory formation in Aplysia at the cellular level . However , there remain many unanswered questions at the molecular level , particularly concerning how the effects of different patterns of learning are mediated . We have developed a mathematical model of a molecular signaling pathway known to underlie memory formation in Aplysia . Our model suggests that the rates of synthesis and degradation of proteins involved in memory regulation are essential for neurons of Aplysia to respond differentially to spaced and massed training . We were able to experimentally validate these findings , thus providing significant evidence for this model , which might underlie memory formation in more complex animals . | [
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] | 2011 | The Rates of Protein Synthesis and Degradation Account for the Differential Response of Neurons to Spaced and Massed Training Protocols |
Bacterial chromosomes are organized into polycistronic cotranscribed operons , but the evolutionary pressures maintaining them are unclear . We hypothesized that operons alter gene expression noise characteristics , resulting in selection for or against maintaining operons depending on network architecture . Mathematical models for 6 functional classes of network modules showed that three classes exhibited decreased noise and 3 exhibited increased noise with same-operon cotranscription of interacting proteins . Noise reduction was often associated with a decreased chance of reaching an ultrasensitive threshold . Stochastic simulations of the lac operon demonstrated that the predicted effects of transcriptional coupling hold for a complex network module . We employed bioinformatic analysis to find overrepresentation of noise-minimizing operon organization compared with randomized controls . Among constitutively expressed physically interacting protein pairs , higher coupling frequencies appeared at lower expression levels , where noise effects are expected to be dominant . Our results thereby suggest an important role for gene expression noise , in many cases interacting with an ultrasensitive switch , in maintaining or selecting for operons in bacterial chromosomes .
The organization of genes into operons is a prominent feature of bacterial chromosomes [1] that appear in some eukaryotes as well [2] . An operon is typically characterized as a promoter followed by multiple genes that are cotranscribed so that each transcription initiation event produces a polycistronic messenger RNA ( mRNA ) encoding multiple gene products [3] . Hypotheses explaining the emergence and maintenance of operons include proportional coregulation [4] , [5] , [6] , [7] , [8] , [9] , horizontal transfer of intact “selfish” operons [10] , emergence via gene duplication [11] , coproduction of physically interacting proteins to speed their association [12] , [13] , evolvability of co-regulation for interacting protein products [14] , and reduction of intrinsic noise [15] . Current evidence favors some hypotheses more than others , but fails to indicate a definitive explanation for how operons are maintained in bacterial chromosomes [4] , [11] , [12] , [13] . Arising from stochasticity of individual biochemical reactions and low copy numbers of reactants per cell , intrinsic noise plays a central role in network dynamics [16] , [17] . In bacteria , intrinsic noise is most evident in gene expression , caused by translational bursting arising from small numbers of mRNA producing many proteins [18] , [19] and transcriptional bursting arising from slow activation-deactivation cycles of transcriptional activity by unknown mechanism [20] , [21] . Extrinsic noise , caused by uncertainties in global parameters and states including those characterizing transcriptional and translational machinery , also contributes to overall biochemical noise [22] . Noise in protein levels is commonly characterized by coefficient of variation ( CV ) , the normalized root-mean square deviation of the protein levels from their mean value ( CV = σ/μ , where σ is the standard deviation and μ is the mean ) but other measures such as autocorrelation and covariance between concentrations of different proteins can give additional insights . The effects of intrinsic noise on operon maintenance are not well characterized , but covariance between protein levels arising from intrinsic noise depends on transcriptional coupling ( co-expression from an operon ) of the corresponding genes [15] . The order of genes within an operon may also affect noise [23] . Therefore , we hypothesize that noise-related effects contribute to the evolutionary maintenance of operons . Studies of several specific systems corroborate that correlative effects of transcriptional coupling alter posttranslational dynamics [6] , [24] , [25] . However , it is still not clear how different classes of protein interactions and co-expression from an operon may interact to alter biochemical noise . In this study we assessed these effects for different types of posttranslational interaction between gene products . In several types of interactions , the noise difference between cotranscribed and uncoupled configurations was amplified by the existence of a zero-order ultrasensitive switch [26] . We related the results to an intact naturally occurring system with simulations of cotranscribed and uncoupled configurations of the lac operon . To test our predictions bioinformatically , we classified naturally occurring interacting pairs of E . coli proteins by their type of interaction and analyzed the effect of chromosomal distance between pairs of genes with interacting products . Finally , we used single-cell protein copy number data to determine differences in operon frequencies at high and low expression levels in E . coli for physically interacting protein pairs .
Intrinsic gene expression noise is correlated in a cotranscribed two-gene configuration , but this correlation was not seen in an uncoupled configuration . Relationships between the fluctuations of two proteins can be quantitatively characterized by the covariance of concentrations for proteins A and B ( σAB ) . Using the linear noise approximation ( LNA; see Materials and Methods ) [18] , , we calculated a normalized covariance ( 1 ) where angle brackets represent average copy-number of each molecular species , and τmRNA and τprotein are the characteristic timescales of mRNA and protein decay . Increased covariance of cotranscribed genes is preserved regardless of whether the translation processes are coupled ( with a single ribosome binding site for multiple genes; Figure 1A–C ) and regardless of the source of intrinsic noise ( from translational bursting only or from both transcriptional and translational bursting; Figure 1B–C ) . We hypothesized that positive covariance can increase or decrease CV in relevant network outputs depending on the nature of the interactions between two proteins . In addition to covariance , the effect of operons on correlation between protein copy number fluctuations can be quantified by another measure , the degree of decorrelation ( Text S1 ) . This measure is useful to characterize the effect of gene expression level on noise differences between cotranscribed and uncoupled proteins ( Table S1 ) , and to assess the effects of expression level on frequencies of operon occurrence in bacterial genomes . We surveyed databases of E . coli biochemical networks [29] , [30] , [31] to identify simple two-gene modules of larger networks that represent different ways that two proteins can directly or indirectly interact . The modules represent simple models of the following interactions: catalysis of subsequent steps in a linear metabolic pathway ( Figure 2A ) , redundant catalysis of the same metabolic step ( Figure 2B ) , catalysis of diverging reactions following a branch point in a metabolic pathway ( Figure 2C ) , redundant transcriptional regulation of a downstream gene ( Figure 2D ) , physical binding between two proteins ( Figure 2E ) , and covalent modification of one protein by another ( Figure 2F ) . The list may not be fully comprehensive , but represents several classes of interactions between proteins that are building blocks of larger networks . For each module we constructed a mathematical model to calculate CV for interacting proteins transcribed from the same and different operons ( hereafter referred to as cotranscribed and uncoupled configurations , respectively ) . We then determined differences in CV for relevant network outputs between cotranscribed and uncoupled configurations . The simulations were controlled by keeping the same mean and CV for total protein from each gene between configurations . The CV calculations were performed at stationary state , both numerically ( stochastic simulation algorithm; [32] ) and analytically ( LNA [28] using Paulsson's [18] normalization ) . The results of the simulations demonstrate that predicted differences in CV for each metabolic module depend on the type of interaction between proteins ( Figure 2 ) . For the linear metabolic pathway module , cotranscription of two enzymes from the same operon results in lower CV for metabolic intermediate . Without transcriptional coupling , metabolic intermediate concentrations are prone to large spikes ( Figures 2A and S1A , B , J , K ) . Notably , no significant differences between cotranscribed and uncoupled configurations are evident in metabolic product CV ( Figure 2A ) , indicating that metabolic flux is not significantly different between the two groups . Intuitively , a spike occurs when flux from the upstream enzyme exceeds the maximal flux capacity of the downstream enzyme resulting in large increase of metabolic intermediate concentration . This increase exceeds the saturation point for the enzyme converting it to product , making product concentration insulated from these spikes . In contrast , the metabolic modules with redundant enzymes ( Figures 2B and S1C , L ) and with a branch point ( Figures 2C and S1D , M ) show an increase in metabolite CV when the two enzymes are in the same operon . In these cases , lower correlations between enzyme fluctuations reduce the chance of simultaneous stochastic drops in concentration of both enzymes . Similarly , cotranscription of multiple ( redundant ) gene regulators from the same operon results in increased CV in the regulated gene as compared to the uncoupled regulator configuration ( Figures 2D and S1E , N ) . Here , we assumed that the gene regulatory logic was an OR gate ( i . e . , each regulator by itself or both together would have the same effect ) . Noise in the output from AND gate logic ( i . e . , a multi-subunit regulator ) is expected to follow the noise pattern of the physical interaction module ( below ) . Consistent with a previous study [25] , the physical protein interaction module under transcriptional coupling shows a strong reduction in fluctuations of monomer concentrations . ( Figures 2E and S1F , G , O , P ) . With strong binding , the concentration of each free monomer changes from nearly zero when its partner is in excess to a finite value when the monomer itself is in excess . These fluctuations are more common when the binding partners are not in the same operon , so the noise is therefore high . Cotranscription slightly increases heterodimer CV compared to the uncoupled configuration ( species AB; Figure 2E ) , but to a much lesser extent than its reduction of CV in monomer concentrations . In the limit of strong binding , nearly all of one monomer is bound , so the effect on monomer noise is dominant . For the covalent modification module ( Figures 2F and S1H , I , Q , R ) , different gene configurations cause small changes in the CV of the modified form of protein A ( A* ) that can be of either sign depending on parameter values , whereas the unmodified form ( A ) has consistently lower CV in the cotranscribed configuration ( Figures 2F and S1H , Q ) . The stochastic simulation approach ( Figure 2 ) gives decisive results , but only for the parameter values tested . To determine how generally the simulation results hold in the face of different parameter values , we used the LNA to analytically determine noise differences ( here quantified as CV2 ) between cotranscribed and uncoupled forms of each network module . For each molecular species denoted by j , we calculated the noise difference between cotranscribed ( ) and uncoupled ( ) configurations as . If the value is positive , the cotranscribed configuration has lower CV2 ( and therefore , lower CV ) ; if it is negative , the uncoupled configuration has lower CV2 . A more complete analysis for each module is presented in Text S2 . Here we highlight the main results . To summarize , we found that differences in noise between cotranscribed and uncoupled configurations in stochastic simulations are qualitatively consistent with the analytical approach . Notably , in all the cases the magnitude of the differences in CV2 between two configurations is proportional to the value of covariance , but in many cases the coefficient of proportionality is very large . This qualitatively suggests posttranslational interactions in some modules are capable of amplifying noise differences between cotranscribed and uncoupled proteins . However , the LNA method likely underestimates the magnitude of non-linear amplification . We further explore these amplification mechanisms in the next section . Timecourse simulations predict that uncorrelated fluctuations of the two enzymes in a linear metabolic pathway result in large bursts of metabolic intermediate ( Figure 3A , B ) . This suggests that higher noise in the transcriptionally uncoupled linear metabolic pathway arises at least in part from the increased probability of occasionally crossing an ultrasensitive threshold . Indeed , a sharp threshold in the intermediate of the linear metabolic pathway arises when the enzyme-mediated consumption of a product saturates , leading to non-linear degradation [33] . The ultrasensitive threshold is crossed when the downstream enzyme saturates , and the flux from the upstream enzyme exceeds its maximal value ( V+/V−>1 in Figure 3C ) . Because V+ and V− are proportional to their enzyme levels , the numerator and denominator of the ratio fluctuate together when both enzymes are in the same operon . Therefore transcriptional coupling lowers noise in the flux ratio and making it unlikely to cross the threshold V+/V− = 1 . When the enzymes are uncoupled , simulations show more variability in the V+/V− ratio , allowing the ratio to cross the threshold with consequent large spikes in metabolic intermediate . Thus , the ultrasensitive switch amplifies noise differences already present between cotranscribed and uncoupled configurations . Differences in noise between cotranscribed and uncoupled configurations of all of the non-redundant modules can be amplified by ultrasensitive switches in a similar manner ( Figure S2 ) . The metabolic branch point module undergoes the same type of non-linear degradation effect as the linear metabolic pathway , but in the branch point transcriptionally coupled enzyme pairs are more likely to fluctuate downward and saturate simultaneously than uncoupled enzymes . This effect leads to a higher likelihood of substrate buildup in the cotranscribed configuration ( Figure S2B ) . The physical interaction and covalent modification modules undergo molecular titration [34] , resulting in an ultrasensitive switch for monomers ( physical interaction module ) or unmodified protein ( covalent module ) that depends on the ratio of protein production fluxes ( Figure S2C , D ) . Cotranscription of the two genes prevents the switch from amplifying transcriptional noise by reducing fluctuations in this ratio . Sensitivity analysis of mean-field models shows that the existence of ultrasensitive switches does not depend on strict parameter regimes ( Text S3 ) . To explore how conclusions drawn from models of simple network modules apply to a more complicated realistic network , we implemented stochastic simulations of a detailed lac operon model that is based on a previous deterministic model [35] . The stochastic model includes enzymatic steps reminiscent of a linear metabolic pathway with permease-mediated lactose import and conversion by β-galactosidase to allolactose and β-d-galactose+β-d-glucose ( Figure 4A , Tables S7 and S8 ) . Feedback and gene regulation are present with derepression of lacY and lacZ expression caused by allolactose binding to LacI ( Figure 4A , Tables S7 and S8 ) . We simulated three inducer concentrations representing minimal lac operon induction ( 1 . 39 µM extracellular lactose concentration or 835 molecules/femtoliter ) , intermediate induction ( 83 . 0 µM or 50 , 000 molecules/femtoliter ) , and excess inducer with maximal lac operon induction ( ∼5 , 000 µM or 3×106 molecules/femtoliter ) . Timecourses suggest that transcriptional coupling between lacY and lacZ ( wild-type situation ) eliminates the large fluctuations in allolactose ( Figures 4B and S3 ) and intracellular lactose ( not shown ) observed in the transcriptionally uncoupled form of the system . This is consistent with a reduction in the correlation between permease and β-galactosidase ( lacY and lacZ gene products , respectively ) in time ( Figure 4C ) . At all inducer concentrations , the uncoupled configuration displays higher CV in allolactose than did the cotranscribed configuration ( Figure 4D ) . This difference is most pronounced in the minimal induction region and gradually reduced with increasing lacY-lacZ induction . At the same time , there is little difference in protein CV between cotranscribed and uncoupled configurations of the model at most inducer levels . In both configurations the CV monotonically decreases with higher expression . The primary consequence of cotranscription of lac proteins in the same operon is a reduction in fluctuations of intracellular lactose and allolactose . These fluctuations may prevent disruption of other sugar uptake pathways by , for example , interfering with inducer exclusion mechanisms [36] . Physiological benefits of noise reduction are also consistent with reports that excessive lactose import is associated with significant lowering of growth rate in E . coli [37 and references therein , 38] . Thus , there may be a selective pressure to maintain high covariance between permease and β-galactosidase resulting from the wild-type genetic structure of the lac operon . To determine if global operon organization in E . coli correlates with predicted noise differences , we characterized frequencies of gene membership in the same operon bioinformatically ( Table 1 ) . We first assigned membership of known E . coli K12 MG1655 [39] biochemical networks into patterns corresponding to the 2-gene modules ( Figure 2 ) using data on E . coli operons [31] , metabolic pathways [29] , gene regulation networks [31] , covalent modification [30] , and physical protein interactions [40] , [41] . Many natural networks fall into more than one class ( e . g . , common bacterial signal mediators , two-component systems , have physical interactions between the sensor and the regulator [42] and are also in the covalent modification class ) . For the metabolic and gene regulation network modules , we eliminated physically interacting pairs to ensure that those included had true functional overlap and were not acting as subunits of a larger enzyme or regulator . Thus , the only systems that are members of more than one class are in members of both the covalent modification and physical interaction modules . In each class we created controls with randomized operon assignment of the genes ( see Materials and Methods ) . Proteins in the linear metabolic pathway , physical interaction , and covalent modification modules appear in the same operon significantly more frequently than do randomized controls ( p<<10−6; Table 1 ) . On the other hand , redundant metabolic nodes and multiple gene regulators are significantly less likely to be in the same operon than randomized controls ( p<<10−6; Table 1 ) . Metabolic branch points show a bias toward being uncoupled , but falls just short of being statistically significant ( p = 0 . 071 ) . These findings hold even after we divide each class into essential and nonessential genes using data from Taniguchi et al [43]; Table S2 ) . Thus operon overrepresentation , when it occurs , is present in essential genes , consistent with previous results contradicting the selfish operon hypothesis [12] . Our results establish a correlation between operon organization of protein pairs and their function that is consistent with noise minimization and avoidance of ultrasensitivity . To separate the specific effect of noise from that of other factors affecting selection for operons , such as proportional coregulation , we considered whether the tendency toward operon membership of posttranslationally interacting protein pairs is related to gene expression levels [23] . Intrinsic noise is stronger for genes with low expression levels [43] , covariance of protein concentrations is more pronounced ( Equation 1 ) and the degree of decorrelation is higher ( Table S1 ) . Therefore , if noise is an evolutionary factor driving operon formation , levels of gene expression may be inversely correlated with operon patterns . On the other hand , if coregulation of mean expression levels is the dominant factor in selecting for operons , the frequency of transcriptional coupling may be directly correlated with gene expression levels because the cost of differential regulation would be highest at the highest expression levels . As a result , any trend in coupling frequencies with gene expression levels would favor one hypothesis and disfavor the other . We used a dataset of average single-cell mRNA and protein copy numbers in E . coli [43] to explore this trend for constitutively expressed physically interacting protein pairs ( other network modules have insufficient data for such analysis ) . Because different conditions can shift gene expression levels and the dataset is only available for one condition , we chose to focus on the subset of interacting proteins that are constitutive , i . e . , not predicted to undergo any regulation in RegulonDB . Each gene's protein or mRNA copy number was considered once , along with a binary variable indicating whether or not the protein product interacts with a same or non-same operon protein . Further details are given in Materials and Methods . We divided the set into two subsets of expression level , one below and one above the median copy number ( Figure 5 ) . The fraction of protein pairs sharing the same operon is higher in the low-expression subset for protein ( bootstrap test p<0 . 01 ) and mRNA ( bootstrap test p<0 . 05 ) copy numbers . This suggests that evolutionary selection against decorrelation ( Table S1 ) significantly contributes to maintenance of operons in the chromosome .
Because enzymes often operate close to saturation [45] , resolving metabolic flux imbalances may prevent widespread accumulation of intermediate , which is potentially toxic [46] , [47] , [48] . Simulations of a detailed lac operon model in our study corroborate the results of the simpler linear metabolic module , suggesting a role for intrinsic noise in selecting for lac operon architecture ( in addition to the stochastic effects previously examined in this system [49] ) . Simulations that include extrinsic noise as a correlating factor indicate that it does not reduce metabolite noise as well as the stronger correlations caused by cotranscription ( Text S4 , Figure S4 ) . Many metabolic operons are large ( and with complex evolutionary histories; [50] ) , but the length of a metabolic pathway is often longer than that of a typical operon , leading to the question of where optimal operon break points for metabolic pathways may lie . Our results suggest that break points occur predominantly where the intermediate is not toxic or where it is processed by multiple downstream enzymes , such as at branch points and metabolic steps with redundant enzymes . Metabolite spikes could also potentially be buffered by reversibility of catalytic reactions , though the reversible step in the lac operon did not prevent intermediate spikes . Furthermore , if portions of metabolic pathways that are divided by intermediates with relatively low toxicity undergo upregulation as needed , there may be a trade-off between reduction of toxic intermediate spikes and just-in-time transcription [51] in the evolution of metabolic networks . Our analysis suggests that pairs of enzymes after a branch point can have lower noise ( CV ) if they are not cotranscribed ( Figure 2C ) , but with a less consistent CV difference between cotranscribed and uncoupled configurations than the other modules ( Figure S1 D , M ) . Therefore , the noise hypothesis predicts patterns of transcriptional coupling to be weaker than in other modules , as we observe to be the case in E . coli ( Table 1 ) . The simple physical protein interaction module in our study ( Figure 2E ) may result in one of two different types of physiologically meaningful output variables: an active heterodimer , in which the genes make up subunits of a functional complex , or an active monomer , in which its activity is negatively regulated by the binding partner ( as with sigma-antisigma systems [52] ) . In either case reduction in monomer noise is justified; in the latter case , to reduce noise in the physiologically relevant output . In the former case , lower noise represents a reduction in inefficient protein production that can reduce promiscuous interactions with other parts of the network . Heterodimer noise is smaller for the uncoupled configuration because upward fluctuations in its concentration are limited to being no larger than the minimum of [A] and [B] and those concentrations are less likely to simultaneously fluctuate upward simultaneously . The covalent modification system ( Figure 2F ) in its uncoupled configuration has reduced fluctuations in the unmodified protein ( A ) compared with the uncoupled configuration . Noise effects of transcriptional coupling may therefore be important in covalent modification systems where the unmodified form of the protein is capable of interacting with other systems ( Text S2 ) . Higher-order chromosome structure , such as bacterial chromatin [53] , [54] and regulatory factors such as bidirectional promoters and transcriptional terminators [55] affect the spatial proximity of genes . Operons could also play a role in spatial proximity , as suggested by the selfish operon hypothesis [10] . We explored whether chromosomal proximity can explain operon membership in linear metabolic and physically interacting gene pairs . Our bioinformatic analysis suggests that the prevalence of operons cannot be solely explained by a proximity bias of interacting gene pairs in the E . coli chromosome ( Text S4 , Figure S5 ) . A striking feature of the non-redundant protein interaction modules is that they all contain a zero-order ultrasensitive switch , which arises as a side-effect of saturation . This effect amplifies differences in CV between cotranscribed and uncoupled forms of the modules ( Figures 3 and S2 ) and may degrade performance when its threshold is crossed . In each two-gene module , the operon architecture that avoids crossing the ultrasensitive threshold is significantly over-represented in E . coli ( Table 1 ) . Signatures of selection against noise in these modules thus likely represent selection against performance-degrading ultrasensitivity as well . Gene pairs encoding constitutive physically interacting proteins are significantly more likely to be in the same operon if their expression levels are low ( Figure 5 ) . This trend could be explained by slow protein diffusion in the crowded intracellular environment , as cotranscribed gene products are more likely to be present at the same subcellular location . However even slow diffusion ( <1 µm2/s ) across a typical bacterial length of ∼1 µm is much faster than the expected time lag between translation of two proteins given typical ribosomal speeds of 12–21 AA/s [56] . Therefore , increased biochemical noise ( here , measured as decorrelations between uncoupled proteins ) at low expression levels are the most likely explanation of the observed trend . We argue that these noise effects are detrimental to the performance of some protein interaction networks . The opposite trend would be expected if proportional expression of mean concentrations or other mechanisms are the primary selective pressure on operon maintenance . In general , genes with high expression levels may operate under greater evolutionary pressure than genes with low expression levels [57] , [58] and therefore their deviation from optimal chromosomal organization is less likely . Arguably , noise minimization is the only selective force that is expected to be more important for genes with low expression levels than for genes with high expression levels [23] . Partial functional redundancy of proteins allows one protein to compensate for a downward fluctuation in concentration of the other protein , thereby reducing noise with uncorrelated protein fluctuations ( Table 1; Figure 2 ) . Therefore , just as noise minimization may explain operon membership for non-redundant interactions , it may also explain the lack of redundant proteins in operons . Differential regulation of the genes can additionally play an important role in keeping redundant interactions transcriptionally uncoupled . In yeast metabolic pathways , apparently redundant enzymes are differentially expressed in different pathways depending on external conditions [59] . This type of mechanism , if present in E . coli , may also explain why no redundant enzymes are in the same operon . Similarly , different growth conditions may result in different regulators affecting downstream expression of the same genes . Further work is necessary to distinguish the noise reduction hypothesis more decisively from differential gene regulation as a selective force in redundant pairs; differential regulation may be physiologically important in some cases and not in others . Improvement of dynamic performance of simple networks arising from cotranscription of interacting genes from the same operon raises the question of why operons are rare in eukaryotes . Eukaryotic cell volumes are much higher than prokaryotes , likely lowering the effect of intrinsic noise relative to the dominant effect of extrinsic noise [60] . Nevertheless , such benefits may still be present in some systems , and there are mechanisms that allow correlating gene expression noise in eukaryotic cells without polycistronic loci . Genes located near each other have correlated transcriptional bursts that likely arise from chromatin decondensation [61] , [62] . Clusters of co-expressed genes , particularly metabolic genes , appear in eukaryotic chromosomes at a rate higher than would be expected randomly [63] , [64] . Co-expressed , functionally related genes at distant genomic loci also appear to migrate together for co-transcription from discrete transcription initiation complexes [65] , [66] , [67] . These mechanisms , arising from the increased size and structural complexity of eukaryotic chromatin over prokaryotic chromosomes , can correlate gene expression noise with similar dynamic benefits to operons . We have developed a theory predicting that operon membership can increase or decrease noise in different types of protein interactions . Bioinformatic analysis finds that naturally occurring operon patterns in E . coli correlate with reduction of biochemical noise . Nevertheless , it would be interesting to explore operon coupling frequencies in bacterial stress response systems known to favor population-level heterogeneity , such as stress responses in B . subtilis; the amplification of noise by underlying ultrasensitive switches in non-redundant network modules may be a potential mechanism of population-level heterogeneity . The existence of implicit ultrasensitive switches also underscores the idea that dramatic non-linearities are likely present in many simple protein interaction networks . Our results suggest that ultrasensitive switches are likely undetectable in the wild-type configurations of well-adapted systems as a result of selection against them , but may be present in conditions with lower selective pressure , or recent evolutionary events . These switches nevertheless have important implications for genome evolution . Their effects , and the mechanisms for avoiding them , may in turn shape larger biochemical networks by changing global noise properties , and will be an important factor in designing synthetic networks .
Unless otherwise specified , each network module was tested with promoter-mediated noise , represented by promoters switching between “on” and “off” states of mRNA production . This process has estimated switching rates of kgoff = 0 . 0028 s−1 for switching to the “off” state and kgon = 0 . 00045 s−1 for switching to the “on” state [20] . In models including a gene regulation step , we assumed binding and unbinding of regulators to be independent of promoters switching between on and off states . Without promoter-generated bursting , gene expression noise largely arises from low mRNA copy numbers per cell and the effect of transcriptional coupling is qualitatively similar ( Figure 1 ) . Furthermore , analytical results from LNA do not include the effects of bursty transcription , showing that we arrive at qualitatively similar results without transcriptional bursts . We distinguish between three types of coupling between production of two proteins in stochastic simulation reaction schemes . Transcription may be coupled or uncoupled ( i . e . , proteins in the same or separate operons ) and when transcription is coupled , proteins may be cotranslated ( single ribosome binding site for both ) or translationally uncoupled ( two ribosome binding sites ) . These three cases represent simplified extremes; intermediate translational linkage ( e . g . , read-through from multiple ribosome binding sites ) is possible but was not further considered here . Figure 1 illustrates the three cases with promoter-mediated gene expression noise . For simplicity of presentation , we compare transcriptionally uncoupled with cotranslated models in the main text . Tables S4 , S5 , S6 , S7 , S8 give reaction schematics and parameters for the gene expression and posttranslational models used in the main text . Parameter values were chosen to be of the correct order of magnitude for realistic expression levels and binding kinetics . To ensure a fair comparison between cotranscribed and uncoupled configurations , production and degradation rates of mRNA species for proteins A and B are identical . The degradation rate kdeg corresponds to the value expected from a dilution rate for typical E . coli doubling every half hour . The basis of noise differences between networks with proteins in the same operon and those with proteins in separate operons is the covariance between the expressed proteins . We used LNA to analytically characterize noise and covariance as follows . For the mean values of copy numbers ( denoted by angular brackets ) : ( 8 ) where i = 1 with proteins A and B in the same operon , and i = 2 with proteins A and B in separate operons . Then we solved the fluctuation-dissipation matrix equation at steady state ( Mσ+σMT+ΩN = 0 ) for σ , where M is the Jacobian of the ( macroscopic ) system , Ω is cell volume , and N is the diffusion matrix [18] . Characterizing intrinsic noise as and with indices i and j taking values corresponding to molecular species ( A , B , m1 and m2 ) , we follow the methods of [18] to obtain: ( 9 ) and as in Equation 1 . Note that σAA is the variance , or the square of the standard deviation . To analytically approximate noise of physiologically relevant variables in the simple network modules ( Figure 2 ) , we made the following simplifications to make the systems tractable . For metabolic steps with a substrate as a dependent variable , we assumed a Michaelis-Menten propensity . For the covalent modification module , we assumed a simple mass-action with no saturation or complexes . For the multiple gene regulator module , we used a Hill equation propensity for regulated mRNA production . Details of the analysis are in Text S2 . Mean-field models are given in Table S3 . Bioinformatic analyses used pairs of interacting genes extracted from databases of E . coli K12 MG1655 as described below . To determine the randomized control , we needed to account for potential biases resulting from dataset size and other features of chromosome organization that we were not attempting to test . For instance , if we randomly assigned genes to extant operons in E . coli across the entire chromosome , the less frequently occurring modules would have much less same-operon membership than the modules with larger numbers of members , and would not be a useful control . We chose to randomize the genes extracted from the pairs within each module to set the random control for each class . Thus , for a list of gene pairswe determined a randomized case by flattening g intorandomly permuting the order of the genes and then re-pairing them to determine the frequency . This process was repeated 1000 times to determine the parameters of the randomized distribution . We extracted single-cell mRNA expression data ( RNAseq ) and protein copy number data from Taniguchi et al [43] . To ensure a meaningful comparison of expression levels , we considered only genes predicted to be unregulated in RegulonDB . Only the physical interaction module left enough data for analysis . For instance , the number of unregulated pairs in the same operon for the linear metabolic pathway dataset was 5 , insufficient to distinguish the established operon membership pattern from noise when partitioned between high and low expression . Each average single-cell mRNA or protein copy number was used , along with physical interaction status ( 1 = same operon; 0 = non-same operon ) . Proteins with multiple interaction partners within and between operons were represented twice , once for same-operon and once for non-same-operon interaction . We then divided the set into above- and below-median subsets and compared the fraction of same-operon interactions in the subsets using a standard bootstrap resampling test . We resampled 10 , 000 times with replacement and computed the difference in coupling frequencies between low and high expression as the test statistic . To compute error bars , we used bootstrapping of each bin by sampling each bin with replacement up to the bin size , repeated 1 , 000 times . | In some species , most notably bacteria , chromosomal genes are arranged into clusters called operons . In operons , the process of transcription is physically coupled: a single pass of the RNA polymerase enzyme reading that region of the chromosome simultaneously produces messenger RNA encoding multiple proteins . So far , we do not have a satisfying explanation for what evolutionary forces have maintained operons on bacterial chromosomes . We hypothesized that different types of interactions between operon-coded proteins affect how strongly operons are selected for between two genes . The proposed mechanism for this effect is that operons correlate gene expression noise , changing how it manifests in the post-translational network depending on the type of protein interaction . Mathematical models demonstrate that operons reduce noise for some types of interactions but not others . We found that operon-dependent noise reduction has an underlying dependence on surprisingly high sensitivity of the network to the ratio of proteins from each gene . Databases of genetic information show that E . coli has operons more frequently than random if operons reduce noise for the type of interaction various gene pairs have , but not otherwise . Our study thus provides an example of how the architecture of post-translational networks affects bacterial evolution . | [
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] | 2012 | Interplay of Gene Expression Noise and Ultrasensitive Dynamics Affects Bacterial Operon Organization |
Both constitutive secretion and Ca2+-regulated exocytosis require the assembly of the soluble N-ethylmaleimide–sensitive factor attachment protein receptor ( SNARE ) complexes . At present , little is known about how the SNARE complexes mediating these two distinct pathways differ in structure . Using the Drosophila neuromuscular synapse as a model , we show that a mutation modifying a hydrophobic layer in syntaxin 1A regulates the rate of vesicle fusion . Syntaxin 1A molecules share a highly conserved threonine in the C-terminal +7 layer near the transmembrane domain . Mutation of this threonine to isoleucine results in a structural change that more closely resembles those found in syntaxins ascribed to the constitutive secretory pathway . Flies carrying the I254 mutant protein have increased levels of SNARE complexes and dramatically enhanced rate of both constitutive and evoked vesicle fusion . In contrast , overexpression of the T254 wild-type protein in neurons reduces vesicle fusion only in the I254 mutant background . These results are consistent with molecular dynamics simulations of the SNARE core complex , suggesting that T254 serves as an internal brake to dampen SNARE zippering and impede vesicle fusion , whereas I254 favors fusion by enhancing intermolecular interaction within the SNARE core complex .
Soluble N-ethylmaleimide–sensitive factor ( NSF ) attachment protein receptor ( SNARE ) proteins are thought to mediate vesicle fusion in all eukaryotes [1–4] . In nerve terminals , there are two target-SNAREs ( t-SNAREs , also called Q-SNAREs ) , syntaxin 1A and synaptosome-associated protein-25 kDa ( SNAP-25 ) on the plasma membrane , and one vesicle-associated SNARE ( v-SNARE , also called R-SNARE ) , synaptobrevin 2 on synaptic vesicles [2] . Prior to exocytosis , the t- and v-SNAREs are thought to form a trans complex composed of a four-stranded helical bundle with one helix each from syntaxin and synaptobrevin and two helices contributed by SNAP-25 [5–9] ( Figure 1A ) . As vesicles undergo fusion , the SNARE complex rearranges from a trans to a cis configuration such that all the SNARE proteins are localized to one membrane . The cis complex is then thought to be rapidly disrupted by the ATPase NSF [5 , 10–12] , allowing the v-SNARE to be recycled into synaptic vesicles [13] . Although the specific mechanism of vesicle fusion is still in debate , it is now widely accepted that the formation of this four-helix bundle is essential for the fusion of the vesicle phospholipid bilayer with the plasma membrane phospholipid bilayer [3] . Vesicle fusion can be constitutive or triggered by calcium ion ( Ca2+ ) [14] . In the latter case , the putative Ca2+ sensor synaptotagmin I plays a critical role [2 , 3] . Constitutive vesicle fusion differs from regulated secretion in that it is relatively less dependent on intracellular Ca2+ . This has been demonstrated in reconstituted secretory cells [15] and at synapses , including mammalian [16 , 17] and invertebrate nerve terminals [18] . In these preparations , removal of extracellular Ca2+ or reduction of intraterminal [Ca2+] by Ca2+ chelators does not stop spontaneous vesicle fusion . At the Drosophila larval neuromuscular junction ( NMJ ) , Ca2+-free saline containing ethylene glycol tetraacetic acid ( EGTA ) does not alter the rate of spontaneous release [19] . These observations collectively suggest that spontaneous vesicle fusion can occur even when intracellular [Ca2+] is reduced . This implies that a mechanism exists to overcome the energy barrier for vesicle fusion at low-Ca2+ conditions . Because SNARE complexes also mediate vesicle fusion along the constitutive secretory pathway [1 , 20] , it is conceivable that this mechanism lies within the different structural and/or biochemical properties of SNARE complexes used for constitutive secretion and Ca2+-regulated exocytosis . The synapse offers an ideal site to test this hypothesis because both forms of secretion co-exist and the SNARE proteins involved in the process are well studied . Furthermore , vesicle fusion can be readily detected at single-vesicle levels using electrophysiology [14] . In this study , we focused on a point mutation , T254I in syntaxin 1A , located at the +7 layer of the SNARE core complex [6] , and its role in SNARE complex assembly and synaptic transmission in Drosophila . In an earlier study [21] , it was demonstrated that this mutation ( syx3–69 ) completely abolished the assembly of the SNARE complex at the restrictive temperature . Consequently , synaptic transmission was fully blocked and the fly paralyzed . Along with previous genetic deletion or mutation studies [22–24] , these results provided important in vivo evidence that SNARE complex assembly was essential for synaptic vesicle fusion . However , our re-investigation of the syx3–69 mutant shows that the T254I mutation blocks neither the assembly of the SNARE complex nor synaptic transmission at the restrictive temperature . Instead , we find that the T254I mutation promotes the formation of the SNARE complex as well as vesicle fusion at permissive temperatures . These findings are consistent with a molecular model of the SNARE complex , suggesting that the T254I mutation causes a structural change of the +7 layer so that the mutant layer more closely resembles those found along constitutive secretory pathways . By enhancing the hydrophobic core of the molecule in the vicinity of layer +7 , towards the C-terminal transmembrane helix , the mutant SNARE complex favors “constitutive-like” vesicle secretion either by increasing intermolecular interactions among the SNARE bundles or by stimulating vesicle docking and/or priming . These results suggest an evolutionarily conserved mechanism intrinsic to the structure of SNARE complexes that could act as a molecular switch to regulate the rate of vesicle fusion .
Syntaxin 1A is a critical component of the SNARE complex and is thought to be essential for synaptic vesicle fusion [1–3 , 24] . A previous study showed that mutation of threonine ( T ) to isoleucine ( I ) at position 254 in the Drosophila syntaxin 1A was sufficient to abolish the assembly of SNARE complexes at restrictive temperatures [21] . However , this conclusion is questionable if we take into consideration the conservation and divergence of residues at this position among different syntaxins . Our sequence analysis shows that , with the exception of syntaxin 4 , most syntaxins found at the plasma membrane have a highly conserved T254 residue at the +7 layer ( Figure 1B ) . Notably , the T254-containing syntaxins , such as syntaxin 1 , 2 , and 3 , are typically used for regulated vesicle fusion at either synapses or neurosecretory cells in a diverse range of animal species [25–27] . In contrast , syntaxins involved in most constitutive secretion pathways in both animals and plants have one of the following amino acids at their equivalent positions: isoleucine , leucine ( L ) , or valine ( V ) ( Figure 1B; see also Figure S1 ) . Valine , leucine , and isoleucine are similar in that they are hydrophobic , branch-chained amino acids . Therefore , this substitution of the residue at position 254 among syntaxins in the constitutive pathways is highly conserved throughout evolution . There are a few exceptions to this generalization . The yeast plasma membrane syntaxin orthologs have a threonine at the equivalent position ( Figures 1B and S1 ) . Furthermore , T254-containing syntaxins could also function in non-synaptic secretions , such as syntaxin 2 in postsynaptic membrane trafficking [26] and Drosophila syntaxin 1A in cuticle secretion [23 , 28] . Nonetheless , the overall feature emerging from our analysis is that syntaxins with conserved isoleucine at the +7 layer appear to be selectively involved in regulated secretion at synapses or neurosecretory cells . It is particularly interesting to note that the T254I mutation found in the syx3–69 mutant approximates a reversion to a residue of wild-type syntaxins found in the constitutive secretory pathway . Notably , syntaxin 5 isoforms place an isoleucine at the site equivalent to position 254 . Syntaxin 5 clearly functions in mammal cis Golgi networks at normal body temperature , similar to the temperature at which the syx3–69 mutant is reported to lose the ability to form SNARE complexes [21] . This prompted us to reconsider whether the T254I mutant syntaxin 1A indeed ceases to function at restrictive temperatures . To this end , we thoroughly re-examined the behavior , synaptic transmission , and SNARE complex formation of the syx3–69 mutant fly at elevated temperatures . Our tests showed that syx3–69 mutant flies were rapidly paralyzed at 38 °C and recovered within 3 min when returned to permissive temperature after a 20-min period of paralysis ( Figure 2A and 2B ) . The paralysis and recovery rates were identical to those shown previously [21] . However , different from the previous observations , we noted that the syx3–69 mutant fly was paralyzed , but not motionless: the flies constantly shook their legs and abdomens during the period of paralysis at 38 °C ( compare Video S1 with Video S2 ) . We used a wild-type fly ( Canton-S [CS] ) and two other temperature-sensitive paralytic flies , Shibirets1 ( Shits1 ) and paralyticts1 ( parats1 ) as controls . As expected , Shits1 and parats1 flies were completely paralyzed due either to a block of synaptic vesicle recycling [29] or a failure of action potential propagation [30] , respectively , and did not exhibit the shaking seen in the syx3–69 mutant . Upon returning to room temperature , Shits1 , parats1 , and syx3–69 flies all resumed their normal activities ( Video S3 ) . These behavioral observations suggest that synaptic transmission persists in syx3–69 flies at the restrictive temperature . To further test this idea , we examined leg movement upon the activation of the giant fiber pathway in adult flies [31] . We stimulated the giant fiber neurons located in the head and observed the movement of fly legs ( the body and wings were anchored with wax on a slide ) . Repetitive and phase-locked leg shaking was readily observed in syx3–69 flies at both the permissive temperature ( 20 °C; unpublished data ) and restrictive temperature ( 38 °C ) following each stimulus of the giant fiber neurons ( see Video S4 ) . In contrast , Shits1 flies moved their legs in response to each stimulus only at the permissive temperature ( 20 °C; unpublished data ) , but not at the restrictive temperature ( Video S5 ) . Figure 2C ( rightmost panels ) summarizes the spontaneous and electrical stimulation–evoked leg movement in syx3–69 flies and the lack of such movement in Shits1 flies at restrictive temperatures . The persistence of synaptically evoked leg movements at the restrictive temperature suggests that synaptic transmission remains intact through multiple synapses ( an electrical synapse and two chemical synapses ) along the giant fiber pathway [31] . To directly measure synaptic transmission , we next recorded the synaptic response of the dorsal longitudinal indirect flight muscles ( DLMs ) from syx3–69 flies maintained at 38 °C . Our results show that evoked synaptic transmission and the resulting action potential persisted at 38 °C ( n = 6; Figure 2D ) . During the course of these experiments , we noted that intracellular electrodes were often dislodged from DLMs only from syx3–69 flies , and there was a high incidence of spontaneous action potentials in the mutant DLMs ( Figure 2D , inset ) . In contrast , Shits1 flies completely lost synaptic transmission upon activation of the giant fiber neuron at restrictive temperatures [32] ( unpublished data ) . Hence , synaptic transmission is not blocked at restrictive temperatures in syx3–69 flies . As shown below , it is likely that paralysis of the syx3–69 mutant is caused by excessive or uncoordinated release of transmitter , rather than a complete block of exocytosis as suggested previously [21] . Consistent with the observation that synaptic transmission persists along the giant fiber pathway , light-induced “on” and “off” transient potentials of electroretinograms ( ERGs ) were not blocked by exposure of the syx3–69 fly to the restrictive temperature ( Figure 3 ) . These transients are thought to reflect synaptic transmission from photoreceptors to downstream interneurons in the retina [33] . The control fly , Shits1 , lost its transient potentials at 33 °C , consistent with a depletion of the vesicle pool [21 , 29 , 32] ( Figure 3B ) . However , the findings from the syx3–69 fly differ from those reported earlier [21] , which showed that the restrictive temperature reversibly blocked these transients . In our experiments , we carefully monitored the temperature of the syx3–69 fly by placing a temperature probe adjacent to the experimental fly . Additionally , we mounted another syx3–69 fly beside the experimental fly so that we could observe the paralysis during the exposure at 38 °C and the recovery afterward . In a total of eight experiments , we never saw a loss of these transient potentials . In fact , our results showed that the “on” transient potential was slightly increased in amplitude at 38 °C ( see Figure 3C ) . Additionally , we also observed spontaneous and light-induced high-frequency “bursting” activities typically indicative of enhanced neuronal activity in both the wild-type and the syx3–69 flies ( see arrowheads in Figure 3A and 3C; see also [34] ) . Hyperactivity of the thoracic ganglion was also observed independently by Dr . Bruno van Swinderen's laboratory when syx3–69 flies were exposed to the restrictive temperature ( B . van Swinderen , personal communication ) . Taken together , both our behavioral tests and electrophysiological analyses support the notion that synaptic transmission is not blocked in syx3–69 mutants at restrictive temperatures . These results further suggest that the formation of the SNARE complex is not abolished in syx3–69 mutants at the restrictive temperature . To test this hypothesis , we measured the level of SNARE complexes using the methods described previously [11 , 21] . We first established the “linear” range that allows optimal detection of changes in the sodium dodecyl sulfate ( SDS ) -resistant SNARE complex ( Figure S2 ) and then measured the level of SNARE complexes in syx3–69 mutants . Our results showed that the amount of the 7S SNARE complex and high molecular weight SNARE multimers ( or oligomers ) remained at wild-type levels in syx3–69 mutant flies at the restrictive temperature ( Figure 4A and 4B ) . The syx3–69 mutant fly was exposed to 38 °C for 20 min prior to rapid freezing with liquid nitrogen and extraction of the SDS-resistant SNARE complex , as described previously [21] . In 50 separate experiments , we consistently observed the SNARE complex . This result has also been independently noted in Dr . Leo Pallanck's laboratory ( L . Pallanck , personal communication ) . In a number of experiments , we also included the comatose ( comt ) mutant in our Western analysis and detected a consistent accumulation of the SNARE complex ( Figure 4C ) , which is thought to be caused by dysfunction of NSF at restrictive temperatures [10–12] . Taken together , all our observations show that the T254I mutation in syntaxin 1A does not block SNARE complex formation nor does it block synaptic transmission at restrictive temperatures . Because our results differ markedly from those reported earlier [21] , we sought to confirm whether the mutant fly we studied indeed carried the T254I mutation as shown in the syx3–69 mutant . Sequencing confirmed that there is a single base change from ACC to ATC in the open reading frame of syntaxin 1A ( see Figure S3 ) . Furthermore , we were able to rescue the paralysis ( unpublished data ) and electrophysiological defects by neuronal expression of the wild-type syntaxin 1A in the syx3–69 mutant background ( see below ) . These results leave little doubt that the phenotype we study here is specifically caused by the T254I mutation in syx3–69 mutant flies . To account for the hyperactivity observed in syx3–69 flies , we next examined whether the T254I mutation in syntaxin 1A has any effect on SNARE assembly and synaptic function at permissive temperatures . Upon examination of the available crystal structures of SNARE core complexes [6] , we found that many of the central layers are tightly packed with hydrophobic residues contained within the four helical bundles . An example of this tight packing in the +1 layer of the synaptic SNARE core complex is illustrated in Figure 5A and 5B . The interactions of Leu57 and Ile178 from SNAP-25 , Ile230 from syntaxin 1A , and Leu60 from synaptobrevin form square-planar geometry typical of the leucine zipper motif . In contrast , the +7 layer containing the wild-type syntaxin 1A is relatively loosely packed due to the presence of a conserved polar threonine residue at position 251 ( equivalent to position 254 in Drosophila syntaxin 1A ) [6 , 7 , 21] , which packs against more hydrophobic partners . Results of examination of homologous neuronal SNARE syntaxin proteins implied a similar loosely packed configuration in this layer [7] . Interestingly , the homologous layer of the endosomal SNARE X-ray structure ( 1GL2 ) [20] shows more reliance on hydrophobic , branched-chain amino acids , than the synaptic SNARE ( Figure 5C ) . The resulting interaction may contribute more hydrophobic stability of the zippered endosomal complex relative to the wild-type synaptic SNARE complex . We therefore propose that the tightened +7 layer in the SNARE complex containing the T254I mutant syntaxin 1A may mimic the function of the endosomal complex . Our modeling results do not support the observation that the T254I mutation debilitates SNARE complex assembly , as previously reported [21] . To further verify this , we conducted molecular dynamics simulations of the SNARE complex in a water bath at 300 K for 5 ns using GROMACS [35 , 36] . After equilibration was achieved , there was no gross difference between the interactions of wild-type SNARE components and the mutant SNARE components . Also , the wild-type SNARE structure shows some degree of “fraying” at the termini of the complex [6] . Although this fraying effect is probably not physiologically relevant , per se , it does illustrate the looser packing of residues at the periphery of the wild-type complex . In our simulations , one would expect a destabilization of the termini ( increase in fraying ) if this mutation were indeed unstable; however , none was observed . Our simulation shows that the T254I mutation does not destabilize the complex , nor does it obviously increase the fraying at the terminus relative to wild-type . Based on this structural analysis and modeling , we predict that the T254I mutation facilitates the formation or stability of the SNARE complex by enhancing intermolecular hydrophobic interactions among the four SNARE α-helices . Because this layer is near the C-terminal of the SNARE core complex , a tighter zippering of the SNARE complex may make fusion more probable by lowering the energy barrier for fusion and thereby partially abrogate the Ca2+-dependence of exocytosis . The mutant protein could also promote vesicle fusion by enhancing vesicle docking/priming . In other words , the T254I mutation may increase the rate of spontaneous release , turning the synapse into a constitutive secretion site . Alternatively , the T254I mutation could stabilize the cis SNARE complex such that it impedes vesicle recycling and ultimately reduces exocytosis upon repetitive nerve stimulation . To test these structural predictions , we first investigated the biochemistry of SNARE complex assembly in the syx3–69 mutant at room temperature . Unlike the results obtained at the restrictive temperature ( Figure 4 ) , our measurements showed that the average amount of the SDS-resistant 7S SNARE complex was significantly increased in the syx3–69 mutant compared to that in the wild type ( CS ) at 22 °C ( n = 50 , p < 0 . 05 ) ( Figure 6A and 6B ) . Similarly , the level of SNARE multimers was also significantly increased in the mutant ( n = 9 , p < 0 . 05 ) . These results show that the level of SNARE complexes is increased in the syx3–69 mutant . Concerned that the SDS-resistant SNARE complex is unique to neuronal SNAREs [37 , 38] , we next used an alternative method to immunoprecipitate the SNARE complex from fly-head extracts using a polyclonal antibody against one of the SNARE components , SNAP-25 [39 , 40] . Our results showed that the SNAP-25 antibody readily and specifically precipitated syntaxin 1A and synaptobrevin , but not tubulin ( Figure 6C ) . When normalized to the amount of proteins precipitated from the head extracts in the wild-type flies , the levels of syntaxin 1A , synaptobrevin , and SNAP-25 were all increased slightly ( Figure 6D; n = 4 ) . Even though these changes are not statistically significant , the trend is consistent with those observed for the SDS-resistant complexes . The level of the SDS-resistant SNARE complex has been shown to correlate well with the level of exocytosis [39 , 41 , 42] . We next tested whether this increase in the rate of SNARE complex assembly had any physiological effects on synaptic vesicle fusion . We recorded action potential–independent and constitutive ( or spontaneous ) miniature excitatory postsynaptic potentials ( mEPSPs or minis ) from third instar larval body-wall muscles innervated by motoneurons [43 , 44] . These mEPSPs are caused by constitutive secretion of glutamate from the nerve terminal [43] . Surprisingly , we found that the frequency of constitutive release was dramatically increased some 7-fold in the mutant ( n = 9 ) compared to the wild type ( n = 8; p < 0 . 001 ) ( Figure 7A and 7B ) . The average mini amplitude was similar in both the syx3–69 mutant ( n = 11 ) and the wild-type larvae ( n = 8; p > 0 . 1 ) ( Figure 7C ) , suggesting that quanta and postsynaptic receptors likely remain normal . Immunocytochemical studies of glutamate receptors failed to show detectable differences between the mutant and the wild type ( unpublished data ) . This mini recording was conducted in saline containing 0 . 8 mM Ca2+ and 1 μm TTX , which was also used for evoked synaptic potentials ( below ) . The resting potential was not different between these two genotypes ( −69 . 7 ± 1 . 2 mV , n = 8 , for the wild type , and −69 . 4 ± 0 . 9 mV , n = 9 , for the mutant; p > 0 . 5 ) . In these and all other larval recordings shown in this study , the muscle input resistance ( between 5–9 MΩ ) did not differ between the wild-type and the mutant larvae . To test whether this increase in mini frequency depends on extracellular Ca2+ , we recorded minis in a Ca2+-free saline . The unusually high rate of spontaneous release remained in the syx3–69 mutant in the absence of extracellular Ca2+ ( n = 8 ) , but significantly higher than that in the wild type ( n = 8; p < 0 . 001 ) ( Figure 7B ) . The resting potential was not different ( −69 . 75 ± 1 . 18 mV , n = 8 , for the wild type; −69 . 75 ± 0 . 85 mV , n = 8 , for the mutant; p > 0 . 5 ) . The lack of effects by Ca2+ removal on mini frequency is consistent with an earlier report showing that Ca2+-free saline plus EGTA did not alter mini frequency at the Drosophila larval NMJ [19] . Furthermore , mini frequency remained 13-fold higher in syx3–69 mutants compared to the wild type in Ca2+-free saline containing the membrane-permeable Ca2+ chelator EGTA-AM ( n = 4 ) . These results indicate that the T254I mutant syntaxin 1A couples the formation of SNARE complexes with constitutive vesicle fusion even when the intracellular [Ca2+] is greatly reduced . An increase in SNARE complex assembly could enhance Ca2+-evoked exocytosis . On the other hand , the dramatic increase in the rate of constitutive vesicle fusion could deplete the vesicle pool and reduce Ca2+-evoked release . To distinguish these possibilities , we recorded action potential–evoked excitatory postsynaptic potentials ( EPSPs ) from muscles bathed in 0 . 8 mM Ca2+ saline . We observed that the amplitude of evoked EPSPs was also significantly increased to 37 mV ( n = 11 ) in the syx3–69 mutant from 25 mV ( n = 9 ) in the wild type ( p < 0 . 005; Figure 7D and 7E ) . Because the average mini amplitude was not significantly different between the mutant and the wild type ( p > 0 . 1 ) , this increase in EPSP amplitude most likely reflected an enhancement in presynaptic release . Factoring in the respective average mini amplitude in these flies and after correction of EPSP amplitudes for nonlinear summation [45 , 46] , there was a 2-fold increase in quantal content from 40 . 0 ( n = 8 ) in the wild type to 79 . 9 ( n = 11 ) in the mutant ( Figure 7F; p < 0 . 001 ) . As with the mini measurement , there was no difference in resting potentials of the muscle fiber between the wild type and the mutant . These results indicate that the average number of synaptic vesicles undergoing exocytosis induced by an action potential is significantly increased in the syx3–69 mutant . Another possibility predicted by our structural modeling is that the T254I mutation may slow vesicle recycling by stabilizing post-fusion cis SNARE complexes . To test this hypothesis , we repetitively stimulated the motor nerve at 10 Hz for a prolonged period ( 5 min ) . We adjusted the extracellular [Ca2+] such that the initial EPSP amplitude was similar between the wild-type control ( at 1 . 5 mM Ca2+ ) and the syx3–69 mutant ( at 1 mM Ca2+ ) ( Figure 8A and 8B ) . At these [Ca2+] , the resting potential was −76 . 5 ± 2 . 6 mV ( n = 4 ) and −75 . 6 ± 1 . 6 mV ( n = 6 ) for the wild type and the mutant , respectively . The basal release was 52 . 8 ± 1 . 0 mV ( n = 4 ) and 49 . 5 ± 1 . 6 mV ( n = 6 ) for the wild type and the syx3–69 mutant ( p > 0 . 1 ) , respectively . As previously shown , there was an initial , rapid decline in the amplitude of EPSPs after the onset of the moderate stimulation at 10 Hz [47] . The EPSP amplitude then reached a steady-state level approximately 60%–65% of single-pulse–induced EPSPs ( Figure 8C ) . Under such stimulation conditions , the steady-state release level is thought to reflect the balance between vesicle recycling and exocytosis [47] . There were no statistical differences in the rate of EPSP decline or the steady-state levels between the wild-type and the syx3–69 mutant larvae ( p > 0 . 05 ) . EPSPs recovered at a similar rate after the 5-min stimulation ( Figure 8C ) . These results suggest that the T254I mutation does not have a detectable effect on synaptic vesicle recycling . At Drosophila NMJs , the readily releasable pool ( RRP ) of synaptic vesicles is estimated to be 230 , which can be rapidly depleted within a few stimuli [47] . We examined the RRP by measuring the relative amplitude of the first ten EPSPs after the onset of the 10-Hz stimulation . Our results showed no significant difference between the wild-type ( n = 4 ) and the syx3–69 mutant flies ( n = 5; Figure 8D ) . Thus , the RRP of synaptic vesicles is not reduced in the syx3–69 mutant despite the extraordinarily high rate of spontaneous fusion rate . Taking into consideration the high rate of spontaneous vesicle fusion , it is reasonable to assume that vesicle docking is , in effect , increased in syx3–69 mutants . Oligomerization of the 7S SNARE complex into high molecular weight complexes is proposed to be essential for vesicle fusion [39] . This implies that multiple SNARE complexes are required to promote vesicle fusion . The precise number of SNARE complexes required for vesicle fusion is unknown , but is estimated to be between three and 15 pairs [3 , 48] . Hence , one could envision a scenario in which the I254 mutant syntaxin 1A exerts a dominant positive effect on synaptic vesicle fusion in heterozygous mutant flies ( i . e . , flies that also have one copy of the wild-type syntaxin 1A ) by acting as part of the multimeric SNARE complex ( Figure 9A ) . To test this hypothesis , we generated heterozygous syx3–69/+ larvae . The resting potential of the muscle fiber in syx3–69/+ larvae was −70 . 9 mV ( n = 7 ) at 0 . 8 mM Ca2+ , which is not significantly different from those in the wild type ( +/+; −69 . 8 mV ) and the syx3–69/syx3–69 homozygous mutant ( −69 . 4 mV ) under the same [Ca2+] ( p > 0 . 3 ) . The frequency of spontaneous fusion ( 6 . 4 Hz; n = 7 ) was significantly higher than that in the wild type ( 2 . 65 Hz , p < 0 . 001 ) , but much lower than that in the homozygote ( 19 . 67 Hz , p < 0 . 001 ) . This observation is consistent with the working model that I254-containing syntaxin 1A has a dominant positive effect on vesicle fusion . We next recorded evoked release in heterozygotes and showed that the amplitude of evoked EPSPs ( 39 mV; n = 9 ) was similar to that in the homozygote ( 37 . 3 mV; p > 1 ) , but significantly higher than that in the wild type ( 25 . 3 mV , p < 0 . 001 ) ( Figure 9B–9E ) . These results indicate that the T254I mutant syntaxin 1A also has a dominant positive effect on Ca2+-triggered vesicle fusion . However , it is clear that dilution of the mutant SNARE complex by the wild-type syntaxin 1A does not reduce evoked release , as it does to constitutive secretion . This observation is inconsistent with the possibility that the T254I mutant syntaxin 1A enhances Ca2+ influx , as one would expect a greater increase in evoked release in the homozygote . A likely explanation we suggest is that the T254I mutant syntaxin 1A stimulates the formation of SNARE complexes in a dominant fashion . For a given level of SNARE complexes , the energy barrier for fusion correlates negatively with the amount of the T254I mutant syntaxin 1A . Although this energy barrier is increased for constitutive fusion in the heterozygote compared to the homozygote , this barrier should be overcome easily by the rise of intraterminal Ca2+ . Our measurement of the SDS-resistant complex confirmed that the amount of SNARE complex was similar between homozygotes and heterozygotes ( Figure S4 ) . This model further predicts that the increase in evoked release should occur in both homozygotes and heterozygotes at both low and high [Ca2+] . To this end , we recorded EPSPs at two additional Ca2+ concentrations ( 1 mM and 0 . 4 mM ) . These Ca2+ concentrations did not alter resting potentials ( unpublished data ) , but they did affect transmitter release ( Figure 9F ) . At 1 mM Ca2+ , the average EPSP amplitude was similar in the heterozygote ( syx/+ , 48 . 6 mV , n = 7 ) and homozygote ( syx/syx , 49 . 5 mV , n = 6 ) , but was consistently larger than the wild type ( +/+ , 42 . 7 mV , n = 8; p < 0 . 01 ) . At 0 . 4 mM Ca2+ , the amplitude of EPSPs in the wild type was quite small ( 3 . 5 mV , n = 9 ) . In comparison , the amplitude of EPSPs was significantly larger in both heterozygotes ( 13 . 5 mV , n = 8 ) and homozygotes ( 15 . 4 mV , n = 9 ) of syx3–69 ( p < 0 . 001 ) . The average amplitude of EPSPs was then compared with those seen at 0 . 8 mM [Ca2+] ( Figure 9F ) . The relatively smaller increase of EPSP amplitude at increasingly higher [Ca2+] reflects the ceiling effect due to non-linear summation . Nonetheless , these results show that evoked release is dramatically enhanced in I254-containing flies at a wide spectrum of extracellular [Ca2+] . The possibility remains that the dominant positive effects we have seen in the heterozygote could result from a second site mutation elsewhere rather than the T254I mutation in the syntaxin locus . To address this concern , we generated transheterozygous flies ( syx3–69/syxΔ229 ) in which the syx3–69 mutant chromosome was placed in trans to a null syntaxin mutation ( syxΔ229 ) [23] . In syx3–69/syxΔ229 mutants , the mini frequency was 22 . 3 Hz ( n = 9 ) , which is significantly higher than that in the wild-type larvae ( 3 . 2 Hz , n = 8; p < 0 . 0001 ) ( Figure 10A ) . At 0 . 8 mM Ca2+ , the evoked EPSP amplitude was also significantly increased to 37 . 9 mV ( n = 9 ) from 29 . 5 mV ( n = 8 ) in the wild-type larvae ( p < 0 . 01 ) ( Figure 10B ) . The resting potential of the mutant animal ( −72 . 4 mV ) was similar to that ( −73 . 8 mV ) in the wild-type larvae . These results are highly similar to those found in the syx3–69/syx3–69 homozygote . Along with the molecular evidence presented earlier , these results provide further genetic and electrophysiological evidence that the effects we have observed in the syx3–69 mutant is specifically caused by the T254I mutation in the syntaxin gene . To further demonstrate indeed the “neutralizing” effect on the T254I mutant syntaxin 1A is mediated by the wild-type syntaxin 1A in the heterozygote , we then performed a genetic rescue experiment in which we selectively expressed the wild-type syntaxin 1A gene in postmitotic neurons using the Gal4-UAS binary system [49 , 50] . When the wild-type syntaxin 1A gene was expressed in the wild-type background ( C155 Gal4/+; UAS-Syx 1A/+ ) , it had no significant effect on either the constitutive secretion rate or the amplitude of evoked EPSPs compared to those in the wild-type larvae carrying the pan neuronal Gal4 driver ( C155 Gal4 , n = 7; p > 0 . 05 ) ( Figure 10C and 10D ) . However , neuronal overexpression of the wild-type syntaxin 1A in the syx3–69/null mutant background ( i . e . , C155 Gal4/+; UAS-Syx 1A/+; syx3–69/syxΔ229 [23] ) resulted in a dramatic reduction in the frequency of constitutive secretion to 8 . 8 Hz ( n = 14 ) from 24 . 9 Hz ( n = 10 ) in C155 Gal4/+; syx3–69/syxΔ229 mutant larvae ( p < 0 . 001 ) . This rate is significantly higher than that in the C155 Gal4 larvae ( 5 . 3 Hz , n = 7 ) or overexpression alone ( C155 Gal4/+; UAS-Syx 1A/+ , 4 . 9 Hz , n = 9 ) ( p < 0 . 05 ) . Overexpression of the wild-type syntaxin 1A in the syx3–69/null mutant background also significantly reduced the average amplitude of EPSPs from 49 . 8 mV ( n = 10 ) in C155 Gal4/+; syx3–69/syxΔ229 mutant larvae to 39 . 3 mV ( n = 14 ) . This EPSP amplitude is similar to that in the C155 Gal4/+; UAS-Syx 1A/+ background ( 38 . 0 mV , n = 9 ) , but significantly higher compared to that in the C155 Gal4 larvae ( 32 . 8 mV , n = 7 ) . These results demonstrate that neuronal expression of the wild-type syntaxin 1A rescues the mutant phenotype by specifically neutralizing the dominant positive effects on both constitutive and evoked secretion induced by the T254I mutant syntaxin 1A .
One of the major new findings from this study is that the T254I mutant syntaxin 1A in the syx3–69 mutant dramatically stimulates vesicle fusion . At the restrictive temperature , the syx3–69 flies exhibit uncontrolled hyperactivities and enhanced neuronal firing . At the permissive temperature , SNARE complex assembly is moderately enhanced , whereas the rate of constitutive vesicle fusion is dramatically increased in the syx3–69 mutant . Importantly , this enhancement of constitutive secretion persists in Ca2+-free saline and when intracellular Ca2+ is further reduced by chelation . This implies that spontaneous vesicle fusion is less dependent upon Ca2+ , a conclusion consistent with those reported in a number of synapses [16–18] , including the Drosophila NMJ [19] . Although we do not suggest that vesicle fusion is absolutely independent of intracellular Ca2+ , our studies support the notion that the T254I mutation makes vesicle fusion more efficient , regardless of whether it is constitutive or Ca2+-regulated fusion . Another major finding is that despite the high rate of constitutive fusion , the vesicle pool is not depleted , implying that vesicle docking or priming is enhanced in the syx3–69 mutant via a yet unidentified mechanism . Consistent with the increase in mini frequency , evoked transmitter release is significantly increased in the syx3–69 mutant . Thus , the T254I mutation stimulates both constitutive and evoked vesicle fusion . This increase in evoked transmitter release correlates well with the enhanced assembly of SNARE complexes in the mutant fly . The third interesting finding is that the T254I mutant syntaxin 1A exerts a dominant positive effect on vesicle fusion . In heterozygous syx3–69 mutant ( syx3–69/+ ) , the rate of spontaneous fusion is slightly higher than that in the wild-type larvae , whereas evoked release remains at the homozygote level . Two lines of genetic and electrophysiological evidence suggest that this dominant positive effect is specifically associated with the T254I mutation in the syntaxin locus . First , the dominant positive effect persists in larvae carrying only one copy of the T254I mutation in the null mutant background ( i . e . , syx3–69/syxΔ229 ) . Second , neuronal overexpression of the wild-type syntaxin 1A effectively rescues the effect of the T254I mutant in the syx3–69/null mutant background . It is important to note that neuronal overexpression of the wild-type syntaxin 1A protein in the wild-type background has little effect on both spontaneous and evoked vesicle fusion . Therefore , the counterbalance exerted by the wild-type syntaxin 1A is specific to the T254I mutant syntaxin 1A . Taken together , these observations lend further support to the notion that the I254 mutant syntaxin 1A is more efficacious than the wild-type T254 syntaxin 1A in promoting vesicle fusion . How might the T254I mutation exert such a dramatic effect on vesicle fusion ? The precise mechanism is unknown; however , we believe the effect of the mutant protein can be better explained by examining the structural impact of the point mutation on the SNARE complex . The formation of the SNARE complex is generally accepted as an essential step in vesicle fusion . This conclusion is supported by considerable evidence accumulated over the last decade using a variety of experimental methods , including the use of specific neurotoxins to cleave SNARE proteins , and genetic mutations or deletion of SNARE genes [1–3] . Based on structural and functional studies of the core complex [6–8] , it has been postulated that the assembly of the SNARE complex involves a “zippering” process in which complex formation starts at the N-termini of the four helices , followed by zippering of the core “layer” of the SNARE bundle towards the C-terminal bundles . The process of zippering is also believed to provide the energy necessary to bring the vesicle close to the plasma membrane [2 , 3 , 9] . To date , most of the data supporting this zipper model came from observations of “loose” and “tight” states of SNARE complexes in neuroendocrine cells [51] , at crayfish neuromuscular synapses [52] , and in liposome fusion [53] . It is also indirectly supported by genetic mutations of the helical region of SNAREs ( see discussions in [7] ) and by the ability of inhibitory peptides of the helical region of SNAREs to block both core complex assembly in vitro and transmitter secretion in PC12 cells [54 , 55] . At present , both the precise mode of SNARE complex formation [56] and the role of the complex in vesicle fusion [3 , 57] are not fully resolved . Nonetheless , the zipper model serves as a good starting point for experimental testing of SNARE structure and function . The T254I mutation is located at a strategic location near the end of the zipper , a presumed final step before vesicle fusion takes place . We have made three interesting observations of the +7 layer by sequence and structural comparison . First , with a few exceptions , nearly all syntaxins involved predominantly in regulated vesicle exocytosis at synapses or neurosecretory cells have a common hydrophilic residue , threonine , at position 254 in the +7 layer . In contrast , most syntaxins acting in the constitutive secretory pathways have one of the highly conserved hydrophobic residues ( I , L , or V ) . Second , there is a conserved switch in the +7 layer packing among SNARE complexes used in different secretory pathways . This layer is loosely packed in “synaptic” SNAREs , but tightly bundled together in “constitutive” SNAREs , where hydrophobic residues ( I , L , or V ) may enhance direct intermolecular interactions among the four α-helices . Third , our structural modeling suggests that the T254I mutant +7 layer is more tightly packed than is the wild type , and that it resembles more the tight packing found in the endosomal SNARE core complex [20] . Based on our sequence and structural analyses , we favor the idea that a structural alteration of the +7 layer induced by the T254I mutation in syntaxin 1A may best account for our experimental observations . The extraordinarily high rate of spontaneous fusion detected in the syx3–69 mutant appears to support the “zipper model” or a modified zipper model [56] , suggesting that tightening the SNARE complex does promote vesicle fusion . That overexpression of T254 syntaxin 1A specifically counteracts I254 mutant syntaxin 1A in vesicle fusion implies that the relatively loose packing of the +7 layer containing the wild-type syntaxin 1A may serve as an internal brake to dampen vesicle fusion . Once this brake is removed by the T254I substitution , the mutant SNARE complex lowers the energy barrier for vesicle fusion beyond a point of no return in a manner that is relatively less dependent on intracellular Ca2+ [15–19] . This working model also explains why evoked release is enhanced in both homozygotes and heterozygotes . We should stress that our results do not permit us to conclude whether or not SNARE complexes directly mediate vesicle fusion . Although pairing of SNARE proteins has been shown to mediate liposomal vesicle fusion in vitro [57] , the rate of liposomal fusion is slow . More importantly , new evidence suggests that SNARE proteins alone may bring the membranes in close apposition , but do not drive vesicle fusion under more physiological conditions [58] . The failure to mediate fusion in vitro suggests that other factors may either assist SNARE function or directly mediate vesicle fusion in vivo . Consistent with this idea , the vesicular ATPase ( Vo ) and synaptotagmin I have been reported to act either downstream of , or synergistically with , the SNAREs in vesicle fusion [50 , 59] . It is interesting to note that a G50E mutation in the N-terminal domain of SNAP-25 has previously been found to enhance both constitutive secretion and Ca2+-evoked release in Drosophila at the permissive temperature [60] . Unlike the T254I mutation , this G50E ( G43E in mammals ) mutation is thought to cause a conformation change of SNAP-25 such that the mutant SNARE complex is more ready to mediate vesicle fusion . The precise mechanism by which the G50E mutation promotes vesicle fusion remains to be resolved . Nonetheless , the T254I and G50E mutations offer two alternative structural changes to promote SNARE-mediated vesicle fusion . It is evident that much is still to be discovered about SNARE structure and function . The results presented here reveal a novel intrinsic mechanism by which SNARE-mediated vesicle fusion is regulated . These findings not only advance the understanding of synaptic transmission , but also have broad implications on vesicle fusion at different cellular pathways .
The syx3–69 mutant fly [21] was obtained from the laboratories of Drs . Troy Littleton ( Massachusetts Institute of Technology ) , Barry Ganetzky ( University of Wisconsin-Madison ) , and Leo Pallanck ( University of Washington ) . This mutant line was maintained on a balancer chromosome ( TM6B ) and out-crossed to prevent potential accumulation of modifiers . The syntaxin null allele ( syxΔ229 [23] ) and UAS-Syntaxin [50] flies were obtained from Dr . Hugo Bellen's laboratory . The wild-type Canton S ( CS or +/+ ) strain , Shibirets1 ( Shits1 ) , and paralyticts1 ( parats1 ) originally obtained from the Bloomington Drosophila Stock Center were maintained in B . Z . 's lab . Flies were cultured on standard fly medium at room temperatures ( ∼20–22 °C ) . Unless otherwise specified , 3- to 5-d-old flies of both sexes were used in the adult experiments described . The modeling of the T251I mutation ( equivalent to the Drosophila T254I mutation ) in syntaxin 1A was accomplished using PyMol [61] . The appropriate residue was modified ( mutated ) in the SNARE complex ( 1SFC , chain B ) . Ray tracing for Figure 5C was also performed with PyMol . All dynamics calculations were carried out with GROMACS v3 . 3 , in which the Gromacs 96 force field was used throughout [35 , 36] . The X-ray structure of the SNARE complex ( chains A[synaptobrevin] , B[syntaxin] , C[SNAP-25] , and D[SNAP-25] of 1SFC ) was used as the starting model . Ordered water molecules and ordered divalent ions were excluded from this calculation . Hydrogen atom positions were calculated with the pdb2gmx program provided by GROMACS , resulting in 3 , 001 atoms ( excluding SPC water molecules ) in the native structure . Sixteen sodium ions were selected by the genion program included with GROMACS to negate the net negative charge of the SNARE bundle . A rectangular box of water ( the SPC water model ) extending 20 Å in every direction from the boundary of the protein component was calculated by the editconf program included with GROMACS [35 , 36] . Initially , the protein structure was minimized until convergence . Position-restrained molecular dynamics was used to equilibrate ( simulation time of 20 ps ) the water molecules with the protein . After energy minimization of the entire system was completed ( protein + solvent + counter-ions ) , 5 ns of molecular dynamics trajectories were computed at 300 K . Once the system was equilibrated , a representative model was extracted from the trajectory ( at 2 ns ) and examined ( Figure 5 ) . The methods described by Tolar and Pallanck ( 1998 ) [11] and by Littleton et al . ( 1998 ) [21] were closely followed for fly treatments and for the extraction of SDS-resistant SNARE complexes . Briefly , adult syx3–69 and CS flies were exposed to 38 °C for 20 min or kept at 22 °C , and then rapidly frozen in liquid nitrogen . Heads were separated from the body by brief vortexing and approximately 20 heads were collected on a sheet of paper under a constant superfusion with liquid nitrogen . Taking care to avoid introduction of air bubbles , fly heads were ground gently in 100-μl SDS sample buffer with a plastic pestle in an Eppendorf tube followed by centrifugation . The supernatant was collected , diluted to a final concentration at 0 . 25–0 . 5 heads/10 μl in sample buffer , and loaded onto gels at 10–15 μl per well . Samples were run on a discontinuous SDS-polyacrylamide gel: a 4% stacking gel , an upper 7 . 5%–8% resolving gel , and a lower 18% resolving gel to minimize excessive transfer of the monomer [11] . Commercial 4%–18% gradient gels were also used in one fourth of the experiments . Proteins were transferred to nitrocellulose membranes by running at 30 V overnight in a 4 °C room , as outlined by the manufacturer's instructions ( Bio-Rad , Hercules , California , United States ) . Membranes were probed with a monoclonal antibody to syntaxin 1A ( 8C3; 1:100 ) [21] . Bands representing monomeric syntaxin 1A and the 7S complex were detected by enhanced chemiluminescence ( ECL; GE Healthcare , Amersham Biosciences , Piscataway , New Jersey , United States ) and quantified with ImageJ ( National Institutes of Health [NIH] , http://rsb . info . nih . gov/ij/ ) . The SNARE complex level is expressed as a 7S complex to monomer ( syntaxin ) ratio and normalized to that in control ( CS ) flies at room temperature . To obtain oligomeric or multimeric complexes of the 7S complex [39] , we either prolonged the exposure time of the film or loaded up to one head equivalent volume onto the gel . The ratio of the multimeric complex to the syntaxin 1A monomer was determined similarly to that for the 7S complex [11] . In most experiments , the blot was re-probed for tubulin to ensure that the protein loading level was similar in each lane . Twenty-one adult fly heads were collected from wild-type ( CS ) and syx3–69 mutant flies ( 4- to 5-d-old ) and ground on ice in 100-μl immunoprecipitation ( IP ) buffer containing 150 mM NaCl and 20 mM Tris ( pH 7 . 5 ) , and mini complete protease inhibitors ( which were added at one tablet/10-ml IP buffer; Roche , Basel , Switzerland ) . The fly-head extract was mixed well with 4-μl 25% Triton X-100 ( BioRad , Hercules , California , United States ) and incubated for 15 min on ice . After a brief and gentle spin to remove cuticle debris , 20 μl of the supernatant was saved as “input” for control loading . The remaining supernatant was incubated with 10-μl sera against the Drosophila SNAP-25 ( rabbit , N-terminal [40] , and mixed with 20-μl prewashed CL-4B protein A Sepharose beads ( GE Healthcare , Amersham Biosciences ) by gentle rotation for 1–3 h at 4 °C . After removing the supernatant , the beads were washed four times with the IP buffer . The immunoprecipitates were eluted by boiling the beads in 50-μl sample buffer . The precipitates along with “input” were resolved on standard SDS gel and subject to Western blot analysis . SDS-resistant complexes were prepared separately and included on the gel as additional controls . The blot was sequentially probed with the 8C3 syntaxin 1A monoclonal antibody , a neuronal synaptobrevin ( N-Syb ) polyclonal antibody ( guinea pig [62] ) , and a different SNAP-25 antibody ( which also recognizes the close homolog SNAP-24 [40] ) . To ensure the specificity of immunoprecipitation , the blot was also probed with an antibody to α-tubulin ( Sigma , St . Louis , Missouri , United States ) . The ECL method was used for protein detection . The band intensity was quantified with ImageJ ( NIH ) . The standard method of third instar larval electrophysiology described by Jan and Jan ( 1976 ) [43] and by Stewart et al . ( 1994 ) [63] was used to record spontaneous mEPSPs and action potential–evoked EPSPs in current clamp mode . The saline [Ca2+] was 0 or 0 . 8 mM for mEPSP recordings and 0 . 4 , 0 . 8 , 1 , or 1 . 5 mM for EPSP recordings ( specified in the text ) . A total of 1 μM tetrodotoxin was added to the saline to block action potentials when minis were recorded [44 , 64] . Because of the unusually high rate of spontaneous minis in the syx3–69 mutant larvae , many minis were clustered together or on top of one another . This made it difficult to ascertain the amplitude of individual minis . In this case , minis were analyzed following an EPSP after the membrane potential had returned to pre-stimulation levels . Quantal content was determined as the ratio of the average EPSP amplitude and the average mini amplitude after correction of EPSP amplitude for nonlinear summation following the methods described by Stevens ( 1976 ) [45] and Feeney et al . ( 1998 ) [46] . Corrected EPSP amplitude = E{Ln[E/ ( E − recorded EPSP ) ]} , where E = difference between reversal potential and resting potential . The reversal potential used in this correction was 0 mV [46] . For simplicity , the average amplitude of EPSPs presented in Figures 9F , 10B , and 10D was not corrected for nonlinear summation . The room temperature was 19–20 °C . Mini recordings were also performed in larvae treated with EGTA-AM ( Invitrogen , Molecular Probes , Carlsbad , California , United States ) . The final concentration of EGTA-AM was 10 μm in Ca2+-free HL-3 saline , diluted from a 40 mM stock in 20% Fluronic F-127 ( a low-toxicity dispersing agent ) in dimethyl sulfoxide ( DMSO ) . The preparation was incubated in the EGTA-AM saline at room temperature for 30 min and washed with Ca2+-free saline prior to recording . The effect of Ca2+ chelation was monitored at the end of the mini recording . Upon switching back to 0 . 8 mM Ca2+ saline , evoked release was dramatically reduced ( unpublished data ) , suggesting most , if not all , of the large number of Ca2+ ions evoked by an action potential were chelated by the intraterminal EGTA . Control experiments with Ca2+-free saline containing the same final concentration ( 0 . 025% ) of the Fluronic F-127/DMSO solvent were also conducted . For the vesicle depletion assay , we used relatively higher concentrations of Ca2+ ( 1 . 5 mM for the wild type and 1 mM for the syx3–69 mutant ) to ensure achieving a rapid decline of EPSP amplitudes . Basal release was monitored at 0 . 2 Hz prior to a 5-min repetitive stimulation at 10 Hz . Usually , the recovery from the 10-Hz stimulation was also monitored by 0 . 2-Hz stimulation immediately afterwards . The basal amplitude of EPSPs was averaged from at least three consecutive EPSPs and used to normalize the average EPSP amplitude during the 10-Hz stimulation . At the onset of repetitive stimulation , three consecutive EPSPs were used to give the average amplitude at time 0 , at 30 sec , and at every minute during the remaining the 10-Hz stimulation periods . The normalized plot , as shown in Figure 8C , allows one to estimate the decline rate and vesicle pools . The first ten EPSPs were also analyzed to estimate the depletion rate of the RRP . The method of Tanouye and Wyman ( 1980 ) [31] was adapted for stimulating giant fiber neurons and for recording synaptic potentials and action potentials in DLMs . Flies were mounted on a slide with dental wax . Sharp glass microelectrodes ( 25 MΩ , filled with 3 M KCl ) were used to record intracellularly from DLMs , whereas the giant fiber neurons were stimulated with a sharp tungsten electrode placed either inside the compound eye or in the cervical connective ( 1–6 V , 120-μs duration ) . A homemade temperature stage was used to rapidly ( within 45 s ) increase the recording chamber to 38 °C . The temperature probe was placed in dental wax next to the mounted fly to ensure the accuracy of the set-point temperature . The fly chamber was then rapidly cooled to room temperature by pumping ice-cold water through the metal stage . Wild type ( CS ) , syx3–69 , and Shits1 were used for this set of experiments . The room temperature was 19–20 °C . For ERG recordings , 2- to 3-d-old flies ( CS , Shits1 , or syx3–69 ) were mounted on a slide with modeling clay and placed on a temperature-controlled stage . A sharp tungsten electrode was inserted gently in the thorax or abdomen of the fly and served as a reference electrode . A sharp glass microelectrode was inserted just through the cuticle into the compound eye . The fly was then allowed to adapt to the dark for a few minutes . ERGs were evoked by rapidly exposing the eye to white light for a brief duration ( 1–2 s ) . The fly chamber temperature was raised to 38 °C using a homemade temperature controller . To ensure the accuracy of the temperature experienced by the fly , the monitor probe was placed as close as possible to the experimental fly . Another experimental fly was mounted beside the fly being recorded so that it could be monitored for paralysis during 38 °C and recovery after the temperature was returned to the permissive temperature . Flies were incubated at 38 °C in water-warmed glass vials for 10 min and then transferred to a sheet of paper placed on the lab bench for recovery at room temperature ( ∼22 °C ) . The time and number of flies capable of standing were recorded and plotted . A total of 230 syx3–69 flies were tested in 17 different trials ( 10–15 flies per trial ) . Wild-type ( CS ) flies were used as controls ( +/+ ) in a few trials , and they were not paralyzed at this temperature . Flies ( syx3–69 and Shits1 , 1- to 2-d-old ) were mounted with their ventral sides up on a slide with modeling clay and viewed with a dissection microscope at 100× . Flies were placed in a chamber whose temperature was rapidly raised to 38 °C within 45 s by a homemade temperature controller and rapidly cooled to 20 °C ( within 1 min ) by circulating ice-cold water around the chamber . A pair of sharp tungsten electrodes was placed into the compound eyes to electrically stimulate the giant fiber neurons in the brain ( 1–6 V , 100-μs duration , 5 Hz ) . Spontaneous and evoked leg movements of these flies were recorded using a digital camera . Videos S4 and S5 are on syx3–69 and Shits1 , respectively . Still clips from these videos are presented in Figure 2C . Results are presented as mean ± standard error of the mean ( SEM ) . The paired Student t-test was used to analyze the level of SNARE complexes , whereas the unpaired t-test was used to treat the electrophysiological results . In all cases , differences of p < 0 . 05 were considered statistically significant . | Most living cells constantly renew their membrane compositions and frequently communicate with neighboring cells by delivering cargo molecules from small vesicles . A key step in cargo delivery requires the fusion of the vesicle membrane with the target membrane mediated by SNARE proteins . In most cellular compartments , fusion occurs constitutively , requiring little participation of other molecules . In other cellular compartments , such as synapses in the nervous system , vesicle fusion is predominantly triggered by intracellular calcium ions . At present , constitutive and regulated fusion modes are not well understood . In this study , we found that a mutant SNARE protein , syntaxin at the synapse , contained a building block commonly conserved for syntaxins functioning along constitutive secretory pathways . Further , our modeling predicted that the mutant syntaxin could form a tightly packed SNARE bundle closely resembling that found in the endosome , but differing from the relatively loosely packed bundle found at the wild-type synapse . Our experimental data support the hypothesis that the mutant syntaxin lowered the energy barrier for vesicle fusion by tightening the SNARE bundle . These findings reveal a novel , intrinsic structural feature of the SNARE complex that regulates vesicle fusion rate at different cellular compartments . | [
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] | 2007 | Modification of a Hydrophobic Layer by a Point Mutation in Syntaxin 1A Regulates the Rate of Synaptic Vesicle Fusion |
Essential tremor ( ET ) , a movement disorder characterised by an uncontrollable shaking of the affected body part , is often professed to be the most common movement disorder , affecting up to one percent of adults over 40 years of age . The precise cause of ET is unknown , however pathological oscillations of a network of a number of brain regions are implicated in leading to the disorder . Deep brain stimulation ( DBS ) is a clinical therapy used to alleviate the symptoms of a number of movement disorders . DBS involves the surgical implantation of electrodes into specific nuclei in the brain . For ET the targeted region is the ventralis intermedius ( Vim ) nucleus of the thalamus . Though DBS is effective for treating ET , the mechanism through which the therapeutic effect is obtained is not understood . To elucidate the mechanism underlying the pathological network activity and the effect of DBS on such activity , we take a computational modelling approach combined with electrophysiological data . The pathological brain activity was recorded intra-operatively via implanted DBS electrodes , whilst simultaneously recording muscle activity of the affected limbs . We modelled the network hypothesised to underlie ET using the Wilson-Cowan approach . The modelled network exhibited oscillatory behaviour within the tremor frequency range , as did our electrophysiological data . By applying a DBS-like input we suppressed these oscillations . This study shows that the dynamics of the ET network support oscillations at the tremor frequency and the application of a DBS-like input disrupts this activity , which could be one mechanism underlying the therapeutic benefit .
Essential tremor ( ET ) is purported to be the most common movement disorder [1–4] , affecting one percent of people . This disorder , which is characterised by an uncontrollable shaking of the affected limb ( s ) at a frequency in the range of 4-10Hz [5] , is detrimental to activities of daily living [6] . While the neurophysiological underpinnings remain elusive , a number of brain regions are implicated in the underlying pathology . The thalamus has long been known to be central to if not the generation , then the maintenance of tremor , as lesioning the motor thalamus , specifically the Ventral intermediate ( Vim ) nucleus , leads to dampening of the tremor [7] . Interestingly , more than 50 years ago , it was reported that low frequency electrical stimulation of the thalamus reinforced tremor [8] . Furthermore , while the role of the thalamus in tremor is undisputed , for essential tremor in particular , it is the involvement of the cerebellum which differentiates it from other tremors . In particular , work has shown structural changes in the cerebellum with ET , such as neurodegeneration . Interestingly , it has been reported that ET disappears after stroke in the thalamocortical-cerebellar network [9] . In addition , disturbances of cerebellar functions , such as gait and eye blink conditioning [10] have been reported in patients with ET . More recently , it has been shown that ET can be successfully treated by deep brain stimulation ( DBS ) [11] . DBS involves the surgical implantation of electrodes into disorder specific target regions , via which the neural tissue is stimulated using trains of electrical pulses . The treatment works well , with 69% of patients showing total or significant suppression of tremor ( Medtronic DBS Therapy for Parkinson's Disease and Essential Tremor Clinical Summary , 2013 ) . However , the efficacy of this method is influenced by two factors: ( i ) the accuracy with which the electrode is located in the affected region , and ( ii ) the stimulation parameter combination . While the former is typically determined using imaging prior to surgery , the scientific evidence regarding the implications of varying each DBS parameter , namely amplitude , frequency and pulse width , is relatively scarce . Thus , the latter is typically chosen by the clinician using trial and error . As such , this process of parameter determination can be time consuming and difficult , not to mention frustrating for the patient . At present , the possibility of optimising this process , by predicting stimulation parameters that would maximize the beneficial effect and minimize unwanted side effects , is limited by the lack of knowledge about the neuronal mechanisms behind either the disease itself or the therapeutic effects of DBS . One popular hypothesis about the neurophysiological mechanisms is that tremor is caused by synchronous oscillatory activity involving thalamus , cerebellum and the motor cortex [12] and that DBS disturbs pathological synchrony . DBS also allows us to record local field potentials ( LFP ) from the implanted electrodes whilst simultaneously recording muscle activity ( EMG ) . Such work has previously demonstrated that recorded LFPs contain synchronised activity at tremor and double tremor frequency [13–15] . While the thalamocortical—cerebellar network has been implicated in such activity , no modelling study has looked at whether the dynamics of this network could indeed support oscillatory activity . In this study , we therefore modelled this network and , investigated its capacity to oscillate at the frequency of synchronous activity , which we recorded from ET patients undergoing DBS surgery .
The data was recorded as part of routine clinical practice and was stored and analysed anonymously . Informed consent was obtained from patients for the use of this data for research , and this was approved by the local research ethics committee ( Charing Cross Research Ethics Committee ) . LFP signals were recorded from a total of 14 electrodes implanted in the motor thalamus ( Vim nucleus ) of seven patients with essential tremor ( see Table 1 ) . Recording techniques have been previously reported [16–18] and are summarised here: LFPs were recorded via the implanted electrodes ( model 3389; Medtronic Inc . , Minneapolis , MN , USA ) during surgical implantation with a sampling frequency of 2 kHz . Simultaneous recordings of LFPs were made with three or four adjacent pairs of electrode contacts in a bipolar configuration . Signals were filtered between 0–1 kHz , amplified with a gain of 10 , 000 ( CED1902 , Cambridge Electronic Design , Cambridge , UK ) . Simultaneously , EMG was recorded via a tripolar arrangement on the affected limbs , typically from the wrist flexors . Recordings were made while the patients were awake , off any anti-tremor medication and in up to three conditions: at rest where we asked the patient not to move ( n = 7 ) , maintaining a posture by holding the arm outstretched ( n = 5 ) and making voluntary movements such as repeatedly flexing the wrist ( n = 3 ) . We adopt a simple population representation of the network hypothesised to underlie ET ( Fig 1A ) . This is based on previous descriptions of the essential tremor network which include these brain regions ( e . g . [12] ) . To model the network , namely cortex , cerebellum and thalamus ( Fig 1A ) , we used the population-level Wilson-Cowan approach [19] . This framework has been extensively used to describe interacting populations of excitatory and inhibitory neurons [20–26] . The main assumption is that the neurons in a population are in close spatial proximity , hence the model ignores spatial interactions and deals only with temporal dynamics . The modelled variable is the proportion of cells in a population which are firing action potentials per unit time . We specifically model two thalamic populations , the excitatory Vim nucleus and the inhibitory reticular nucleus ( nRT ) . The latter has been implicated as a crucial player in thalamic oscillations [27–29] . In addition , we model an excitatory population of cortical neurons , representing the motor cortex ( Cx ) and an excitatory population of cerebellar neurons , representing the deep cerebellar nuclei ( DCN ) , the main output of the cerebellum . Therefore , the model comprises of four first-order coupled differential equations: τVimdEVimdt=−EVim ( t ) + ( ke−EVim ( t ) ) . Ze ( w1ECx ( t ) +w2EDCN ( t ) −w3InRT ( t ) ) τCxdECxdt=−ECx ( t ) + ( ke−ECx ( t ) ) . Ze ( w4EVim ( t ) ) τnRTdInRTdt=−EnRT ( t ) + ( ki−InRT ( t ) ) . Zi ( w5ECx ( t ) ) τDCNdEDCNdt=−EDCN ( t ) + ( ke−EDCN ( t ) ) . Zeext Here , Ei ( i = Vim , Cx or DCN ) and Ij ( j = nRT ) represent the number of active neurons in the relevant excitatory or inhibitory population at a given time . The strength of the connection between two populations is given by wn , where n = 1 , 2… 6 . The value of this parameter is calculated by taking the product of the average number of contacts per cell and the average postsynaptic current induced in the postsynaptic cell by a presynaptic action potential . Note that the last equation , for the DCN population , is independent of the dynamics of the other three populations , and only provides an input into the Vim population . Therefore , in this model , the DCN population will tend to a stationary value and not oscillate . The response functions Ze ( x ) and Zi ( x ) in the model represent the proportion of cells firing in a population , for a given level of average membrane potential activity x ( t ) of cells across the population . In [19] , these functions were derived by assuming that the population has a distribution of neural thresholds and that all cells in the population have the same average level of membrane potential activity . Alternatively , the cells in a population can be assumed to have the same threshold but there is a distribution of the number of afferent synapses per cell . Either approach leads to the response functions being represented by monotonically increasing sigmoid function , as follows: Zp ( x ) =11+exp ( −bp ( x−θp ) ) −11+exp ( bpθp ) where p represents e or i , bp and θp are constants , and x is the level of input activity . Following Wilson & Cowan , the following values are used for these constants are: θe = 1 . 3 , be = 4 , θi = 2 . 0 , and bi = 3 . 7 . Therefore , this model effectively assumes that the inputs to a network are weighted , summed and thresholded . The parameters ke and ki in the model are the maximum values of the response functions and are given by ke = 0 . 9945 and ki = 0 . 9994 . Each of the parameters τi represents the time constant of the change over time in the proportion of nonrefractory cells which are firing in a population , in response to the change over time in the average membrane potential activity of the cells . The value of the time constant for each population is usually assumed to be equal to the membrane time constant of the cells in the population , as in [30] and [24] . This value is usually assumed to lie within the range 10–20 ms [30] and time constants of 10 ms were chosen as nominal values for all populations , and this parameter was left unchanged throughout the simulations . The application of a high frequency input to the Vim nucleus of the thalamus was modelled using a biphasic square pulse as follows: DBS ( t ) =A*H ( sin ( 2πft ) * ( 1−H ( sin ( 2πf ( t+pw ) ) ) −Am*H ( sin ( 2πf ( t−pw*m ) ) * ( 1−H ( sin ( 2πft ) ) where A is the amplitude of the input in arbitrary ( arb . ) units , H is the Heaviside function , f is the frequency , pw is the pulse width and m is the multiple for the charge balancing pulse ( Fig 1B ) . This was included as an additional term into the equation for the Vim population , such that the Vim equation subsequently changed to the following: τVimdEVimdt=−EVim ( t ) + ( ke−EVim ( t ) ) . Ze ( w1ECx ( t ) +w2EDCN ( t ) −w3InRT ( t ) +DBS ( t ) ) To further analyse any oscillatory behaviour displayed by the modelled network , we used bifurcation analysis of our four equations using a numerical analysis approach in a software package called LOCBIF [31] . For a system of ordinary differential equations , the nature of the fixed points of the system can change as the parameters are varied . If a fixed point changes stability , appears or disappears we say that a bifurcation has occurred . At points of bifurcation the behaviour of a system changes in a way that depends upon which type of bifurcation has happened . In this study , bifurcation analysis revealed that an oscillation can arise through an Andronov–Hopf bifurcation or a SNIC bifurcation ( saddle-node on an invariant curve ) . At the point of an Andronov–Hopf bifurcation , a stable equilibrium point loses stability and a particular type of trajectory can appear in the neighbourhood of the fixed point . This trajectory is called a limit cycle , which is an isolated closed curve . Motion of the system along the limit cycle trajectory is periodic and hence oscillatory behaviour is encountered ( see for example [32] for more details ) . This limit cycle behaviour is illustrated in bifurcation diagrams for the model parameters . The curves shown in these diagrams indicate points in the parameter space where a bifurcation occurs and a limit cycle arises . Thus the curves separate the portion of the parameter space where the system has a fixed stable equilibrium point from the portion where a limit-cycle oscillation is present . These diagrams are produced in each case by keeping all but two of the parameters at their control values .
DBS patients routinely have intraoperative recordings made while they have the electrodes inserted into the thalamus . This allows us to measure the neural activity patterns associated with ET and can further aid the targeting of the thalamus by locating neural patterns associated with the thalamus . Fig 2 shows an example recording from a single patient . Fig 2A shows the power spectra for a single EMG ( left ) channel and one LFP ( right ) channel from the contralateral hemisphere . The data shows that there are clear peaks in the EMG power spectra at approximately 4 Hz and at the harmonic frequencies of 8 Hz , 12 and 16 Hz . In the LFP power spectra , a peak at tremor frequency is also seen around 4Hz , and an indication of an increase in power at 8Hz . The cross-coherence between the EMG and LFP signals is shown in Fig 2B , and clearly shows a peak at tremor frequency , double tremor frequency and somewhat at the subsequent harmonic frequencies . We split our data into the three different behavioural epochs: rest , self-paced voluntary movement and maintaining a posture . We averaged the data for each of our seven patients across channels for the two hemispheres , and Fig 3A shows the averaged EMG-LFP cross coherence across patients for each epoch ( shading indicates between subject SEM ) . In all conditions , there is increased cross-coherence within the tremor frequency band . In the rest condition , patients were instructed not to move , but the observed increase in 6–11 Hz cross-coherence may be related to movement and/or rest tremor . When moving ( hand is repeatedly open and closed ) or maintaining a posture ( arm is held up with the hand by the nose ) the cross-coherence shows a more tightly tuned , specific increase at 5–9 or 5–6 Hz depending on the epoch . Furthermore , the individual cross-coherence spectra and the histogram of peak frequency in these spectra ( Fig 3B ) in the 3–11 Hz range clearly demonstrate that there is variability amongst the patients and recordings , which may reflect a number of individual differences , including the precise electrode location and differences in the performed motor behaviour . In order to investigate the dynamics of the network suspected to be responsible or necessary for such oscillatory activity , we constructed a population model of the thalamocortical-cerebellar network as described above . This network was simulated by exploring the connection weights parameter space to uncover regions which produced oscillatory activity in the typical tremor frequency range , as observed in our EMG-LFP data . We found that the network readily oscillated at a frequency of 5 . 5Hz , when the weights were set at the values given in Table 2 . Given these baseline weights , all of the neuronal populations in the network , except the DCN , oscillate at this frequency ( the Vim oscillations are shown in Fig 4A ) . The Vim leads the cortical oscillation by 6 . 8 ms ( Fig 4B ) , which is consistent with previously measured lags [33] . This baseline oscillatory activity was examined in more detail using bifurcation analysis . Once established , we did not change any of the model parameters from those in Table 2 when subsequently applying DBS stimulation to our network . However , before doing so , we wanted to investigate the relative contribution of the connections within the network on the oscillatory activity we observed . We used bifurcation analysis to locate stable points in our parameter space and vary two parameters at a time while observing the stability of the system . All but two parameter values at a time were fixed ( as in Table 2 ) for the determination of each bifurcation curve . We used specialised software ( LOCBIF ) for the bifurcation analysis to find a region in the 2D plane of the two selected parameters corresponding to the oscillations . We found that the observed tremor frequency oscillation arises in our model through an Andronov–Hopf bifurcation nearby of which a limit cycle is observed . We plotted bifurcation diagrams for pairs of weight parameters in the model which kept the model at this bifurcation point , and these are shown in Fig 5 . The shaded regions indicate the region of parameter space for which the model will display oscillations , although the frequency of the oscillations does not remain constant throughout these shaded regions , as described below . This analysis revealed the following features about the importance of connection weights relative to one another . First , Fig 5A shows that the cortical input to the Vim and the cortical input to the nRT must be balanced in order to maintain oscillations , as the oscillatory space lies along the diagonal . Furthermore , if the cortical drive to the Vim decreases , the frequency of oscillations decreases , but if the cortical input to the nRT increases , or both weights increase together , the frequency of oscillations increases . Second , the reticular input to the Vim should on the whole be stronger than the cortical input ( shaded region is mainly below the line of equality in Fig 5B ) . Interestingly , if those inputs both increase in weight , the frequency increases , but a move to any other region of the oscillatory space results in a decrease in frequency . Third , the inhibitory loop ( cortex to nRT and nRT to Vim ) must be maintained with weights no less than the default values for oscillations to be present . All other regions of the oscillatory parameter space result in lower frequency oscillations . Finally , one of the weight parameters ( cortical input to Vim ) could be set to zero with oscillations maintained in the network , but only with a corresponding increase in cerebellar drive . Hence no population ( and its corresponding connections ) could be lost and oscillations maintained , that is all of the populations are critical to oscillatory behaviour . Given that our model network was able to oscillate at tremor frequency , the next step was to see how this behaviour changed when an input mimicking the effects of DBS was applied to the thalamus . In the following , we will call the oscillatory network activity before DBS application the baseline oscillation . We applied a biphasic square pulse at different amplitudes and frequencies into the Vim population of the model network only , to replicate targeted DBS of the thalamus . We found two effects of DBS on the network activity that we discuss in turn . First , DBS at low amplitudes altered the baseline oscillatory activity of the network , not in amplitude , but frequency . Fig 6 shows this relationship quantitatively for three different DBS amplitudes . At an amplitude of 1 arb . unit , DBS increased the frequency of the oscillatory activity at all stimulus frequencies greater than 10 Hz . The relationship between stimulation frequency and thalamic frequency was found to be linear ( r2 = 0 . 98 ) up to a DBS frequency of 200Hz , beyond which the thalamic frequency plateaued at a maximum 6 . 8 Hz . It is interesting to note that this linear relationship changed when the stimulation amplitude was increased to 3 arb . units . At this point , the DBS frequency was inversely related to the thalamic frequency ( r2 = 0 . 91 ) , with higher DBS frequencies slowing the underlying oscillatory activity until it was completely suppressed . For the 3 arb . units stimulation , this suppression occurred at frequencies greater than 175 Hz . Similarly , at an amplitude of 4 arb . units there was an inverse relationship between DBS and thalamic frequency ( r2 = 0 . 93 ) . The slope of the linear fit to the data was much steeper in this case , and the oscillations were suppressed at frequencies greater than 100 Hz . This trend was observed for increasing DBS amplitudes , such that as the amplitude increased , the frequency at which DBS would suppress the thalamic oscillations decreased . However , the limit was that for DBS frequencies less than or equal to 25Hz , even extremely large amplitudes ( 100 arb . units ) did not suppress the thalamic oscillations . Second , DBS induced a switch from large amplitude low frequency baseline activity to small amplitude high frequency activity . For a fixed value of the stimulus frequency , as we increase the DBS amplitude there is a critical point which eliminates the baseline oscillation and induces the switch to high frequency network activity . Thus , if DBS amplitude is higher than this threshold then the baseline oscillation disappears and high frequency , low amplitude activity becomes the dominating neuronal activity mode . Fig 7 shows both of the effects described above , the change in the baseline oscillation frequency and the switch to high frequency activity for a DBS stimulation frequency of 150 Hz . In Fig 7 , at 1–3 arb . units of DBS amplitude , the network activity remained low frequency and high amplitude , but the frequency decreased compared to the baseline ( no DBS ) condition . However , at 4 arb . units , this activity was abolished and there was a switch to high frequency , low amplitude activity . For all DBS frequencies between 70 Hz and 100 Hz , this switch occurred at 5 arb . units and for frequencies greater than 100 Hz this occurred at 4 arb . units . That is , DBS drove the thalamic activity at stimulation frequency up to a maximum of 167 Hz , and beyond this point the network could no longer follow the stimulus frequency . Applying DBS at different amplitudes and at therapeutic frequency or at different sub-optimal frequencies lead to the underlying oscillations changing frequency or being replaced by irregular high frequency activity depending on the stimulus amplitude . Interestingly , in the presence of the DBS stimulus , we found another bifurcation near the Andronov-Hopf bifurcation . A limit cycle is observed near an Andronov-Hopf bifurcation , and can be seen as a cyclical relationship between two of the time dependent variables in the model equations . An example of the limit cycle in the absence of DBS is shown in Fig 8A , where the thalamic and cortical activity are plotted as a function of one another . However , when DBS is applied , the limit cycle is not constant over time , but varies ( Fig 8B ) . Furthermore , the presence of this saddle-node on an invariant circle ( SNIC ) bifurcation is confirmed in the absence of DBS , when the frequency of the baseline oscillation can be decreased by altering the value of the ext parameter ( Fig 8C ) .
The thalamus has been known to be involved in oscillatory activity such as spindling [27–29] . In this study , we hypothesised that the dynamics of the thalamocortical-cerebellar network would be able to support the pathological synchronous activity , which has been thought to be the signature , if not the cause , of essential tremor [12 , 34] . Such oscillatory activity has been previously recorded not only in the muscle activity via EMG , but also in the brain via EEG , LFP and microelectrode recordings [13 , 14 , 35] . Here we tested our hypothesis , by examining the population level dynamics of the network constructed using a Wilson-Cowan approach [19] . We found that this network does indeed oscillate readily in the essential tremor frequency range , also reflecting the activity we recorded in patients with essential tremor undergoing DBS surgery . Our model demonstrates that the dynamics of this thalamocortical-cerebellar network supports oscillatory activity in the tremor range . Previous computational modelling work examining the effects of DBS has mainly been directed to studying Parkinson’s disease and either focussed on unconnected neurons [36–39] , axons [40–43] , or local networks [44] made up of conductance-based neurons . The pathophysiological state in these two diseases may have some similarities , and this study indicates that such activity is not only reliant on the biophysical properties of the neurons , but emerges from the structure of the tremor network itself , which involves different brain regions in Parkinson’s disease and Essential tremor . The thalamus has been implicated in various types of oscillatory activity [27–29] [25 , 26] [45–47] , our results are consistent with such views of the thalamus and interestingly , we find here that though the corticothalamic connection is important , it is the driving input from cerebellum which needs to be the strongest input into Vim . The oscillations in this network arise from an Andronov-Hopf bifurcation . Therefore close to the point of bifurcation , there will be small amplitude oscillations and the frequency of these oscillations will be fixed . As we move away from the bifurcation point , the amplitude and indeed frequency of the oscillations can vary . Furthermore , bifurcation analysis of the network showed that the oscillatory activity is robust under parameter variations , while important relationships between the connection weights exist . In particular , we see that quantitative relationships between connection strengths must be maintained for the pathological oscillations to be sustained . For example , we found that all of the populations in the network are critical to oscillatory behaviour . This is consistent with reports of patients with ET , who have seen improvement in their tremor following a stroke in the thalamocortical-cerebellar network [9] . We also predict that the driving input to the Vim from cerebellum must outweigh the cortical feedback to maintain oscillations . This prediction is in agreement with the hypothesis that ET occurs due to a lack of GABA in the cerebellum , which in turn leads to disinhibition [48 , 49] . Such predictions about the state of the network in disease can be further tested experimentally either in vitro or in vivo animal work , or in human work via imaging . For example , the harmaline animal model of ET , the most studied model , suggests that tremor emerges due to rhythmic inferior olive firing [50] . This model further suggests that DCN , which is part of the network modelled here , is involved in harmaline tremor as c-Fos expression is induced in the DCN as a result of the manipulation [51] . While the precise role of the DCN is unclear , the lesioning of the DCN can lead to action tremor in humans and primates [52] . High frequency stimulation of the thalamus in mice , has been shown to suppress harmaline tremor , indicating that a similar network to ET , may indeed be involved [53] . Therefore , such animal models may be used to test our predictions about the relative strength of connections between brain regions . DTI imaging of patients with ET , which until now has been limited and produced conflicting results , could also be used to further elucidate the network structure of ET . A recent review [54] indicates a difference between ET and control participants predominantly in the cerebellar peduncles . In particular , we studied the impact of a DBS like input at therapeutic frequency on our network activity . We found that such an input suppresses the oscillations and drives a higher frequency , low-amplitude activity across the network . This is consistent with previous modelling work [55 , 56] using conductance-based model neurons , indicating that the use of network models which are relatively easy to set up , analyse and relate to data is another valid methodology for studying DBS . It is important to note however , that in our model the application of DBS which is applied to the Vim nucleus alone , will affect all efferent connections of the Vim . Our model does not account for antidromic activation , as the connections are unidirectional . In future work , we could explicitly model the afferent connections , but in that case these connections would participate in the network activity even in the absence of DBS , and would change the entire dynamics of the model . Furthermore , this effect reflects a hypothesis about subthalamic DBS , which proposes that it acts to replace pathological synchrony with low amplitude activity and regain information flow through the thalamus [57–59] . Interestingly , while this hypothesis has been proposed for subthalamic DBS to treat Parkinson’s disease , our results indicate that a similar mechanism may apply for thalamic DBS for ET . Another interesting observation is that the high frequency activity which was driven by DBS , matched the DBS frequency but only up to a maximum frequency of 200Hz , we predict that a similar result would be seen in single neuron simulations or recordings . The model presented here also showed frequency dependent effects with DBS-like stimulation . While previous work has examined the impact of low or high frequency DBS [61 , 66] , there has been no in vivo study reporting the effect of systematically varying the DBS frequency , either on the clinical symptoms or electrophysiological recordings . Consequently , our model allows these experiments to be done in silica . We found that at low frequencies , DBS did not abolish the tremor band oscillatory activity as readily as at higher frequencies . In fact , the lower frequency stimuli maintained the low frequency , high amplitude activity for a wider range of stimulus amplitudes . This effect may be linked to the clinical observation that for treating essential tremor , high frequencies are necessary [60] Interestingly , for frequencies greater than 30 Hz , we were able to abolish the tremor band activity in the network if the amplitude of DBS was increase , which has also been shown previously [61] . It was shown more than 50 years ago that low frequency stimulation of the thalamus strengthen tremor , in patients undergoing stereotactic surgery [8] . This predicts that such low frequency stimulation , may not necessarily drive tremor , but allow the network to sustain the underlying pathological oscillation , rather than suppress it as with higher stimulation frequencies . Recently , it has been discussed whether uniform regular stimulation or patterned stimulation such as repeated bursts of high frequency stimulation is most effective [62] . We applied bursting stimulation patterns in this model but found it to be less effective at suppressing the pathological oscillation in this model in agreement with previous work [63] . Furthermore , it has previously been observed clinically and recently shown theoretically that kilohertz frequency stimulation is also effective at suppressing tremor , but only up to a limit of approximately 3 kHz [61 , 64] . In our model , we found that stimulation up to 3 . 5 kHz was still effective at suppressing the low frequency , high amplitude oscillations . The model also showed amplitude dependent effects of DBS . At low amplitudes , DBS increased the tremor band activity in a linear fashion , while at higher amplitudes DBS decreased the tremor band activity with an inversely linear relationship . A physiological study has previously reported an increase in tremor frequency with DBS as we observed at low amplitudes {Vaillancourt , 2003 #2396] . However , in that study the increase was independent of DBS amplitude . These differences in the frequency and amplitude dependent effects may highlight the limitation of such network level dynamic models , that they do not capture the full spectrum of neuronal dynamics . It is critical to note , that the Wilson-Cowan model however , does not account for the detailed firing properties of neurons , such as the distinction between burst and tonic firing , a critical feature of thalamic cells that has been shown to be important in ET . Instead the Wilson-Cowan representation only allows for the firing rate of a population . Consequently , this study therefore can only look at tremor as a network phenomenon and thus the impact of DBS on that activity . Similarly , the model presented here does not account for the spatial dimension within a population . While this is in fact an advantage of this modelling approach , we could represent different populations within a brain region , for example to represent somatotopy within the Vim nucleus [65] . Furthermore , the modelled network in our current work , only accounts for four populations . One brain region which is missing is the inferior olive , which is implicated in the pathogenesis of ET , particularly due to the work with the harmaline rodent model [50] . Further work could expand the model to include at least this important input to the cerebellum . Finally , in the current study we have used a computational model to replicate the data recorded from DBS patients . One clear extension to this parallel approach would be to fit the model parameters , particularly the connection weights , to the patient data . The aim would be to fit the parameters of the model to the peak frequency of the individual patient’s data . Furthermore , such patient specific models could also be used to simulate specific parameter settings tried in individual patients to correlate network changes to therapeutic effects or the emergence of side effects . In this way we could explore whether we could represent individual patients , who may show variations in the frequency of their tremor , with a patient specific model , not of the network structure , but of the relative strength of parameters across the network .
In conclusion , we have shown that the dynamics of a network of multiple brain regions thought to be involved in essential tremor are able to support oscillations in the tremor-band frequency range , as seen in LFP recordings in patients . In addition , we have shown that the application of a biphasic square pulse into the Vim nucleus disrupts this synchronous activity . The network displays frequency-dependent behaviour which may be linked to clinical observations and makes predictions about the relative strength of connections between brain regions . This may explain one mechanism by which thalamic DBS achieves suppression of tremor in ET patients . | Essential tremor ( ET ) is acknowledged to be the most common movement disorder affecting 1% of the population . Although the underlying mechanisms remain elusive , the thalamus , cortex and cerebellum are implicated in the underlying pathology . More recently , it has been shown that ET can be successfully treated by deep brain stimulation ( DBS ) . This clinical treatment involves the surgical implantation of electrodes into the brain , through which current is applied . However , the mechanisms of how DBS achieves clinical benefit continue to be debated . A key question is whether ET can be modeled as a pathological network behavior as has been suggested previously . If so , we can then ask how DBS would modulate this brain activity . Our study combines: ( i ) simultaneous electrophysiological recordings from the brain and muscle; ( ii ) computational modelling; ( iii ) mathematical analysis . We found that the network supports oscillations in the tremor range , and the application of high frequency DBS switches this to low amplitude , high-frequency activity . We propose that our model can be used to predict DBS parameter settings that suppress pathological network activity and consequently tremor . In summary , we provide the first population level model of essential tremor including the effect of DBS on network behaviour . | [
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"mapping... | 2017 | A Network Model of Local Field Potential Activity in Essential Tremor and the Impact of Deep Brain Stimulation |
Enterocytozoon bieneusi is the most common microsporidian associated with human disease , particularly in the immunocompromised population . In the setting of HIV infection , it is associated with diarrhea and wasting syndrome . Like all microsporidia , E . bieneusi is an obligate , intracellular parasite , but unlike others , it is in direct contact with the host cell cytoplasm . Studies of E . bieneusi have been greatly limited due to the absence of genomic data and lack of a robust cultivation system . Here , we present the first large-scale genomic dataset for E . bieneusi . Approximately 3 . 86 Mb of unique sequence was generated by paired end Sanger sequencing , representing about 64% of the estimated 6 Mb genome . A total of 3 , 804 genes were identified in E . bieneusi , of which 1 , 702 encode proteins with assigned functions . Of these , 653 are homologs of Encephalitozoon cuniculi proteins . Only one E . bieneusi protein with assigned function had no E . cuniculi homolog . The shared proteins were , in general , evenly distributed among the functional categories , with the exception of a dearth of genes encoding proteins associated with pathways for fatty acid and core carbon metabolism . Short intergenic regions , high gene density , and shortened protein-coding sequences were observed in the E . bieneusi genome , all traits consistent with genomic compaction . Our findings suggest that E . bieneusi is a likely model for extreme genome reduction and host dependence .
The microsporidia are a diverse group of obligate eukaryotic intracellular parasites that infect nearly all animal phyla ( recently reviewed in [1] , [2] ) and are classified as Category B organisms on the NIAID Category A , B & C Priority Pathogens List . The first report of a microsporidian infection was over 150 years ago , when Nosema bombycis , a parasite of silkworms , was described . The phylum Microsporidia contains at least 1 , 200 species , divided into over 150 genera . Microsporidia are eukaryotes containing a nucleus with a nuclear envelope , an intracytoplasmic membrane system , and chromosome separation on mitotic spindles as well as Golgi . However , they lack canonical mitochondria and centrioles , possess prokaryotic size ribosomes ( 70S: consisting of a large subunit ( LSU ) rRNA ( 23S ) and small subunit ( SSU ) rRNA ( 16S ) , and lack a discrete 5 . 8S rRNA [3]–[6] . The microsporidia were originally thought to be primitive protozoa , but were recently shown to be related to the Fungi , being either within or a sister group to this phylum ( reviewed in [7]–[10] ) . Microsporidiosis is considered a zoonotic and waterborne disease with agricultural consequence because it affects insects , livestock , wildlife , and domestic animals as well as humans . Fourteen microsporidian species are associated with human disease , but the majority of infections are caused by Enterocytozoon bieneusi [1] , [10]–[15] . Clinical symptoms include chronic diarrhea , wasting and cholangitis . The majority of microsporidian infections in humans occur in immunocompromised patients , but occurrence in immunocompetent hosts is not unusual . Presently there is no effective commercial treatment for E . bieneusi-associated human microsporidiosis; although albendazole and fumagillin have been shown to be effective against Encephalitozoon-associated infections [16]–[20] and fumagillin has efficacy against E . bieneusi [21] . Although E . bieneusi is clinically the most significant microsporidium associated with human microsporidiosis , very little is known about this pathogen . It was first reported in 1985 [22] , but progress towards the understanding of the biology of this organism has been hampered by the many challenges associated with working with E . bieneusi , including the difficulty in obtaining large quantities of purified E . bieneusi spores . E . bieneusi has also remained refractory to being reproducibly passaged in vitro , and when passage does occur , the yields are very low and inconsistent [23] , [24] . As a consequence , much of the recent research on microsporidia has focused on the family Encephalitozoonidae , which has three members associated with human microsporidiosis , Encephalitozoon intestinalis , Encephalitozoon hellem and Encephalitozoon cuniculi . The reason is less for their clinical significance , but rather because they readily propagate in cell culture and in animals . The only microsporidian genome sequenced to date is E . cuniculi , with a genome size of 2 . 9 Mb , which is among the smallest eukaryotic genomes [25] . The E . cuniculi data revealed that its genome is highly compact; a total of 1 , 997 protein-coding sequences were identified , with an average intergenic region of 129 bases . While much has been learned about microsporidia from the E . cuniculi genome project , E . cuniculi is not an adequate model for the study of E . bieneusi , which differs in a number of important characteristics . Specifically , ultrastructural examination of E . bieneusi in the biliary epithelium of rhesus macaques revealed ( 1 ) a lack of sporophorus vesicles or pansporoblastic membranes , ( 2 ) multiple rounded and elongated nuclei present within proliferative and sporogonial stages of the parasite , ( 3 ) late thickening of the sporogonial plasmodium plasmalemma , ( 4 ) presence of electron-translucent inclusions and electron-dense discs , and ( 5 ) direct contact of all stages with the host cytoplasm [26] . E . bieneusi was shown to abut the host-cell nucleic such that the nuclei are distorted and the parasite was seen in close association with the host mitochondria [26] . Significant clinical differences in sensitivity to albendazole distinguish these two microsporidia as well . Albendazole was shown to be effective against the Encephalitozoonidae , but not against E . bieneusi . The sequence of the E . bieneusi beta-tubulin gene has provided a molecular explanation for this difference in sensitivity [27] . These differences , along with the uncultivatability of E . bieneusi suggested that there would be differences between these two genomes . Thus , we undertook a genome sequence survey of E . bieneusi using recently developed purification methodology to obtain the necessary spores directly from infected humans . This sequence survey represents the first genomic sequence data available for this difficult-to-study organism . The aim of this project was to gain insight into the genomic architecture of this poorly understood microsporidian with respect to gene content and organization .
A significant challenge of this genome survey was obtaining a sufficient number of spores for library construction . With the absence of a robust in vitro cultivation method and the inability to produce enough spores in our rodent animal models , the only viable source was an infected human . Fecal samples from adult patients presenting with chronic watery diarrhea were screened by IFA and one patient with a very high E . bieneusi count was identified . Stool samples were collected , concentrated and purified using an extensive washing , filtration and centrifugation protocol ( see Methods ) . 1 , 702 E . bieneusi genes were assigned functions using the ERGO annotation pipeline , information from BLAST searches , and the KEGG automated annotation server [50] . 1 , 199 of the E . bieneusi genes with assigned functions were homologs of one of the 884 E . cuniculi proteins in eleven functional categories ( Table S4 ) . Functional domains were detected in an additional 111 proteins annotated by ERGO as “hypothetical” and these proteins are included in Table S4 . Only one gene with assigned function , methionine adenosyltransferase 1 , was found in E . bieneusi , but not E . cuniculi . The remaining proteins ( ∼615 ) showed either similarity to an E . cuniculi hypothetical or functionally undefined protein , no similarity to any protein in GenBank , high similarity to a bacterial protein , or were very short in length . The protein-coding DNA sequences of known function were assigned to one of eleven functional categories ( Figure 3 and Table S4 ) and from the distribution of these genes , a view of the parasite's lifestyle can be glimpsed . With the caveat that not all protein-coding genes have been identified in E . bieneusi , approximately 37% of the identified genes were associated with the replication of the parasite . A roughly equivalent number of genes had functions related to protein synthesis and trafficking . A significantly lower number of proteins were associated with lipid , fatty acid and isoprenoid metabolism , and energy generation functions ( 0 . 7 and 0 . 5% , respectively ) , but the moderate number of genes associated with transport of products ( 9% ) , was in line with the obligate intracellular lifestyle of E . bieneusi and its dependence on the host for most of its needed nutrients . Given the possibility that only 64% of the E . bieneusi genome had been sampled , one cannot conclude anything from the absence of any one gene , but analyzing entire pathways or classes of genes hints at the overall makeup of the genome . Indeed , a comparative analysis of the protein repertoire of E . bieneusi and E . cuniculi showed that many functional categories are most likely similarly represented in the genome but others may not be . Not surprisingly , a large proportion of the E . cuniculi protein-coding genes related to DNA replication , transcription , translation , protein folding , trafficking , and degradation were also identified in the E . bieneusi survey ( Figure 3 and Table S4 ) , suggesting these functional classes are similarly represented in the two genomes . In contrast , however , a surprising number of genes related to energy generation , lipid , fatty acid and isoprenoid metabolism and mRNA splicing found in E . cuniculi are absent from the E . bieneusi survey . In particular , genes encoding proteins for core carbon metabolism are surprisingly rare with only three of the twenty-three E . cuniculi proteins with functions in glycolysis , trehalose metabolism , and the pentose phosphate pathway identified in E . bieneusi . The absence of trehalose metabolism has particular implications for microsporidia because it has been suggested to play several roles in this lineage , including ( 1 ) rapid increase of the osmotic pressure within the spores required for polar tube extrusion upon hydrolysis of trehalose; ( 2 ) protection against freezing or desiccation; and ( 3 ) use as a potential energy source [51] , [52] . Since this pathway contains relatively few genes , its apparent absence in the survey may simply be a reflection of incomplete coverage . It is possible that the absence of genes associated with energy generation and lipid metabolism is due to sampling bias , but it is very difficult to imagine what could drive such a bias . The current draft sequence read coverage is >27 Mb , or well over 4X . If the genome size is close to the estimated 6 Mb and coverage is random , we would expect to see a combined contig length of approximately 6 Mb: the probability of sequencing any base follows a Poisson distribution and at 4X coverage , the probability that any one base has been sampled at least once is >98% . However , the draft sequence is equal to only ∼64% coverage and many contigs are over-tiled . This suggests the quantity of unique genome sequence is lower ( 3–4 Mb ) . Even if we assume that coverage is not random and that we have completely missed sequencing 2 Mb of the genome , it is improbable that ten or more genes from any one pathway are clustered in the missing sequence . The relatively even sampling of other gene classes represented in the E . cuniculi genome ( Figure 3 and Table S4 ) , suggests instead that these categories are underrepresented in the E . bieneusi genome . Microsporidia are known to rely extensively on their hosts for energy and nutrients , and it seems likely this is also true of E . bieneusi . Nevertheless , a parasite with no obvious means of deriving energy from sugars would represent an extreme form of reduction and host-dependence , a possibility that needs further investigation . The inability to cultivate a eukaryote is a serious impediment to characterizing its whole nuclear genome . Many parasites that form intimate associations with their hosts are often uncultivable . E . bieneusi is one such intracellular parasite , so to initiate a complete characterization of its genome , we generated ∼34 , 000 genome survey sequences , amounting to ∼3 . 86 Mb of unique sequence using material directly isolated from infected humans . The genome size is estimated to be 6 Mb based on the pulse field electrophoresis data . However , this may be an over-estimation since this is based on the accuracy of the calculation of the chromosomal band intensities . Indeed , comparing our genomic data to the genome of E . cuniculi supports the conclusion that there is significantly less than 6 Mb of unique sequence in the E . bieneusi genome . Specifically , the identification of 21 tRNA synthetases and 46 tRNA genes , the low number of E . bieneusi-specific protein-coding genes , as well as over-representation of reads within certain contigs , all suggest a high proportion of the unique sequence in the genome has been sampled . Though the genome size of E . bieneusi is over twice as large as E . cuniculi , a similar gene density is observed . This inconsistence between genome size and genome content could be explained if the E . bieneusi genome has chromosome heterogeneity , in particular partial duplications . Duplicate gene copies found in our E . bieneusi survey support this . Moreover , evidence for chromosome heterogeneity in two microsporidia has been reported . Molecular karyotyping analysis of Paranosema grylli identified chromosomal heterogeneity resulting from chromosomal rearrangements [53] . The Brachiola algerae survey showed a discrepancy between its predicted coding capacity and the finding that no recognizable genes were found that were not present in other microsporidian genomes [54] . Nonetheless , assuming a genome size of 6 Mb , the survey sequences represent at least 64% of the genome , a significant advance for the study of E . bieneusi since only a few genes were available prior to this survey . In addition , with these data , microarray and RT-PCR experiments for identification of genes involved with host-pathogen interactions , infection , as well as identification of potential therapeutic drug targets can be initiated , since the limitations on cultivation are substantially mitigated by the prior knowledge of many gene sequences . Only 47% of the protein-coding ORFs were assigned function , suggesting that many of the unassigned ORFs may represent novel genes . Future efforts focused on studying these proteins may identify novel proteins associated with the obligate lifestyle of E . bieneusi . This genome sequence survey demonstrates the feasibility of a complete genome analysis of E . bieneusi , despite the lack of cultivation , and points to many biologically interesting questions that would be addressed by the complete sequence . In particular , our survey suggests that a comprehensive comparison of gene complements with E . cuniculi and to other microsporidian genomes will be of tremendous interest . The severe reduction and perhaps even absence of intact pathways for core carbon metabolism is unexpected and suggestive of a unique level of host dependence; in turn suggesting many novel mechanisms for interactions with the host ( perhaps associated with the many proteins with unknown functions ) . Similarly , a number of proteins related to infection were not identified . The absence of these proteins and pathways will need to be tested using independent evidence , or the exact nature of the genome structure determined unambiguously . Nevertheless , the genome survey of E . bieneusi presented here provides the first available genomic data that will add to the growing knowledge base for understanding this organism , which should result in the development of diagnostic tools and potential therapeutics , and also highlights E . bieneusi as a potential model for extreme reduction and host dependence .
Stools were collected from adult HIV/AIDS patients admitted to the Mulago Hospital , Kampala , Uganda with chronic watery diarrhea . Stool samples were tested for E . bieneusi by immunofluorescence assay ( IFA ) using E . bieneusi-specific polyclonal antibodies [55] . Fecal samples from patients who were E . bieneusi-positive were collected , concentrated by centrifugation ( 4 , 000×g; 40 minutes ) and resuspended in phosphate-buffered saline ( PBS ) . The concentrated fecal samples were stored at 4°C until they were shipped to Tufts University for purification and analysis . E . bieneusi spores were purified from fresh stools of infected adult humans using the method described by Zhang et al . [56] . Briefly , the concentrated feces were homogenized and serially filtered through American Standard sieves of decreasing pore size ( 425 , 180 , 100 and 63 µm; Newark Wire Cloth Company , Newark , NJ ) . The spores were centrifuged at 3 , 200g for 40 minutes and the spore pellet was washed 4 times with distilled water ( 3 , 200g , 20 minutes ) . The pellet was resuspended , mixed with saturated sodium chloride and centrifuged at 1 , 000g for 15 minutes . The spores remained resuspended in the salt solution ( density ∼1 . 2 g/cm3 ) , separated from the bacteria and particulate matter , which either settled on top of the salt solution or sedimented to the bottom of the tube . The salt solution was carefully removed with a needle and syringe , and the spores collected , washed and resuspended in PBS . The spores were further purified by sequential centrifugation through 72% isotonic Percoll , 30–60% ( w/w ) sucrose gradient , and 10–50% ( w/v ) preformed iodixanol gradient prepared from OptiPrep density gradient medium ( Sigma-Aldrich Co . , St . Louis , MO ) . Purified spores were stored at 4°C . Spores purified from one patient ( isolate 348 ) were used for the genome survey . The first spore preparation ( ∼2 . 2×109 in 1 . 6 ml sterile PBS ) was checked for bacterial and fungal contamination by plating an aliquot ( 10 µl/plate ) on blood agar and Saboraud plates and the plates incubated at 37°C or 30°C , respectively . The plates were visually checked daily for contamination for 3 days . Approximately 200–300 colonies and 50 colonies were observed on the blood agar and Saboraud plates , respectively . The bacterial and fungal contamination was estimated to be <0 . 002% . A second purified spore preparation ( ∼2×109 spores ) from the same patient was performed using the same protocol ( <0 . 05% bacterial and fungal contamination ) . Genomic DNA was purified using a modified Proteinase K-phenol extraction protocol [57] , [58] . The Proteinase K , RNase and linear acrylamide solutions used in the extraction protocol were specifically selected because they were certified by the vendor to have undetectable levels of bacterial DNA and RNA . Spores ( ∼2 . 2×109 ) were collected by centrifugation ( 15 , 000×g; 4 minutes ) and resuspended in 400 µl of lysis buffer ( 100 mM EDTA , pH 8 . 0 , 0 . 2% sodium deoxycholate , 1% sodium lauryl sarcosine ) . Proteinase K ( catalog no . 03115887001; Roche Diagnostics Corp . , Indianapolis , IN ) was added to the sample . The spores were subjected to 5 freeze-thaw cycles , then incubated at 50°C for 2 days . The spores were again subjected to 2 freeze-thaw cycles , RNase ( 2 µl , 10 µg/µl; catalog no . 11119915001; Roche ) was added , and the sample incubated at 37°C for 30 minutes . Proteinase K ( 10 µl; Roche ) was added to the sample and 2 additional freeze-thaw cycles were performed before the sample was incubated at 50°C for another 2 days . An equal volume of phenol:chloroform:isoamyl alcohol ( 25∶24∶1 ) was added and the sample was mixed on a rotator for 2 hours at room temperature . The sample was centrifuged at 15 , 000×g for 7 minutes . The aqueous phase was removed and transferred to a new tube using a wide-bore pipet tip . The DNA was precipitated by the addition of 3 M sodium acetate , pH 5 . 2 ( 45 µl ) , linear acrylamide ( 3 µl; Ambion ) and 100% ethanol ( 1 ml ) and left at −80°C overnight . The DNA was collected by centrifugation ( 15 , 000×g; 15 minutes ) , the DNA pellet washed with 100% ethanol , and dried briefly . The DNA was resuspended in 50 µl TE and its concentration determined using Quant-IT™ PicoGreen® dsDNA Assay Kit ( Invitrogen Corp . , Carlsbad , CA ) . The estimated yield was 2 . 5 µg from 1 . 5×109 spores . A 100 ng aliquot of the final genomic DNA preparation was run on a 0 . 7% TAE gel and also a portion of the β-tubulin gene was amplified using E . bieneusi-specific primers for quality control purposes . A second genomic DNA preparation was performed using the 2×109 spores from the second purified spore preparation . The DNA yield of the second genomic preparation was 2 . 2 µg . Agarose plugs containing 108 purified E . bieneusi spores were prepared with 1% low melting agarose ( Bio-Rad , Richmond , CA ) . The plugs were immersed in 5 ml lysis buffer ( 0 . 5 M EDTA , pH 8 . 0 , 1% N-lauroylsarcosine , 5 mg/ml Proteinase K; Sigma Chemical Co . , St . Louis , MO ) and incubated for 72 hours at 50°C [57] . The plugs were placed into the PFGE wells of a 1% agarose gel in 0 . 5×TBE buffer ( 45 mM Tris , 45 mM boric acid , 1 mM EDTA ) and electrophoresis was performed in a contour-clamped homogenous electrical field ( CHEF DR III System , Bio-Rad ) . The gel was run with a pulse time of 90 to 200 second switches at 100 V for 72 hours at 14°C . A S . cerevisiae chromosomal size standard ( Bio-Rad ) was included on the gel . Two independent runs were performed . Using the two genomic DNA preparations , two genomic libraries with random 2–3 kb inserts were constructed by Agencourt Bioscience Corporation in their proprietary high copy number vector . Genomic DNA was hydrodynamically sheared in the Hydroshear ( GeneMachines , San Carlos , CA ) and separated on agarose gel . A fraction corresponding to ∼3 , 500 bp was excised from the gel and purified by the GeneClean procedure ( Qbiogene , Morgan Irvine , CA ) . The purified DNA fragments were blunt-ended using T4 DNA polymerase and ligated to unique BstXI-linker adapters . These linkers are complementary to an Agencourt-developed high copy vector cloning site , while the overhang is not self-complementary . Therefore , the linkers will not concatemerize nor will the cut-vector readily religate to itself . The linker-adapted inserts were separated from the unincorporated linkers on a 1% agarose gel and again purified using GeneClean . Products were ligated to BstXI-cut vector to construct a “shotgun” subclone library . Ligation products were used to transform ElectroMAX DH10B cells ( Invitrogen ) , plated onto agar containing kanamycin and incubated overnight at 37°C . Transformants were picked for sequencing and liquid cultures were grown overnight at 37°C . DNA was purified using Agencourt's proprietary large-scale automated template purification systems using solid-phase reversible immobilization or SPRI . The quality of the first library was evaluated by sequencing 192 clones . Sequences were compared against GenBank's nonredundant protein database at the National Center for Biotechnology Information ( NCBI; http://www . ncbi . nlm . nih . gov/Genbank ) using the BLASTX algorithm [31] , [32] . Only the top BLAST matches were used to classify the reads as either eukaryotic or bacterial . Approximately 17% of the sequences had highest identity to bacteria , which was higher than expected based on the assay for bacterial contamination . Thirty-three percent of the sequences showed highest similarity to E . cuniculi and 50% showed no significant homology to either eukaryotic or bacterial sequences . Although the proportion of bacterial sequences was high , we decided to proceed with this library since a new preparation of spores was not likely to be of higher quality . However , not enough clones were obtained from this library to complete the genome survey and a second 2–3 kb library was constructed using the genomic DNA from the second preparation . The quality of this library was evaluated and was estimated to have <5% bacterial sequences . The purified DNA samples were sequenced using ABI 3 . 1 BigDye terminator chemistry on ABI 3730XL automated sequencers ( Applied Biosystems , Foster City , CA ) by Agencourt Bioscience Corporation . Sequence data were transferred to Linux machines for processing . Base calls and quality scores were determined using the program PHRED [59] , [60] . Average high-quality read length ( Phred20 ) was 802 bases . Reads were assembled by Agencourt using Paracel , with default settings . Reads from both libraries were treated as a single dataset . Since validation of the genomic library showed the presence of bacterial sequences ( multiple taxa ) , the contigs were classified as from either E . bieneusi or bacteria based on BLAST analysis results . The nucleotide sequence of each contig was used to query the NCBI non-redundant nucleotide database using the BLASTN algorithm [31] , [32] . The percent AT content of each contig was determined and an obvious biphasic curve was observed . Visual examination of these data indicated that contigs with significant matches ( Expect ( E ) <e−80 ) to Pseudomonas had an AT content of 30–49% , while sequences with significant matches to E . cuniculi had an AT content of 60–79% . The majority of contigs ( >90% ) with an E value <e−5 match to a non-bacterial sequence had an AT content of ≥50% . Based on this observation , bacterial contigs were identified as those contigs whose highest sequence identity was to a bacterial sequence with an E value <e−50 and an A+T content of <50% . A total of 1 , 079 contigs met both of these criteria and were removed from the final dataset . This represents 38 . 1% of the number of contigs , 32 . 1% of the number of bases in the contigs , but only 9% of the total number of bases assembled into contigs . The largest bacterial contig was 8 , 147 bases and the average length of bacterial contigs was 1 , 689 bases . The majority of the bacterial contigs ( 77 . 7% ) were less than 2 kb in length . Approximately 86% ( 927 contigs ) of these contigs had highest similarity to Pseudomonas . Based on these criteria , 1 , 742 contigs assembled from 34 , 212 reads , remained in the E . bieneusi genome survey and represent 3 . 86 Mb . Significantly , the 38 largest contigs of the original dataset were E . bieneusi and ranged in length from 8 , 405 to 131 , 639 bases ( Table S5 ) . Of the 1 , 742 contigs , 4 were greater than 100 kb in length and 136 were greater than 2 kb . Over 90% of the contigs were less than 2 kb in length . The total number of bases represented by contigs greater than 2 kb was 1 . 91 Mb and 1 . 95 Mb were represented by contigs less than 2 kb . The E . bieneusi genome has an overall A+T content of 75% based on the 49 contigs of greater than 4 kb in length ( Table S5 ) . The A+T content of the individual contigs within this group ranged from 59% to 80% . The overall A+T content decreased to less than 62% for contigs smaller than 2 kb , presumably because of the inclusion of bacterial sequences , which failed the %A+T test ( A+T content <50% for bacteria ) but passed the similarity test ( E<e−80 to a bacterial sequence ) . Genes with known homologs were initially identified utilizing BLASTX versus the ERGO non-redundant sequence database with a similarity cutoff of e−15 . Genes identified were used to train a Hidden Markov Model-based statistical recognition program , FunGene [29] that was used to identify novel genes . Intergenic regions were further examined using Glimmer3 [30] , [61] to identify missed coding sequences . ORFs were assigned identity and function using the ERGO non-redundant database and its curated annotations using procedures previously described [28] . The Enterocytozoon bieneusi whole genome shotgun project has been deposited at DDBJ/EMBL/GenBank under the project accession ABGB00000000 . The version described in this paper is the first version , ABGB01000000 . The E . bieneusi genome survey dataset will also be deposited in the Biodefense and Public Health Database ( BioHealthBase; http://www . biohealthbase . org ) . | Enterocytozoon bieneusi is a clinically significant pathogen associated with human microsporidiosis , particularly in immunocompromised individuals . E . bieneusi is widespread in mammals , and there is no effective commercial treatment for infection . The pathogen cannot be readily cultivated , and animal models are limited . We therefore undertook a sequence survey and generated the first large-scale genomic dataset for E . bieneusi , which we used to study the organization and structure of its genome and to perform a comparative analysis with Encephalitozoon cuniculi , another microsporidian whose genome has been completely sequenced . The E . bieneusi genome showed many traits associated with genome compaction including high gene density , short intergenic regions , shortened proteins , and few introns . With one exception , all E . bieneusi proteins with assigned functions had E . cuniculi homologs . We found a paucity of genes encoding proteins associated with fatty acid and carbon metabolism . The possibility that these core functions are reduced in an intracellular parasite is intriguing , but because the genome sequence of E . bieneusi is incomplete , we cannot exclude the possibility that additional proteins associated with the various metabolic pathways would be discovered in a completed genome . | [
"Abstract",
"Introduction",
"Results/Discussion",
"Methods"
] | [
"genetics",
"and",
"genomics/genomics",
"molecular",
"biology",
"infectious",
"diseases/gastrointestinal",
"infections"
] | 2009 | Genomic Survey of the Non-Cultivatable Opportunistic Human Pathogen, Enterocytozoon bieneusi |
Non-tuberculous mycobacteria ( NTM ) are different from Mycobacterium tuberculosis ( MTB ) both in their ubiquitous environmental distribution and in their reduced capacity to cause disease . While often neglected in favour of other infectious diseases , NTM may interfere with important aspects of TB control and management , namely the efficacy of new anti-tuberculosis ( TB ) vaccines; the immuno-diagnostic Tuberculin skin test ( TST ) and QuantiFERON TB Gold In Tube assay ( QFTGIT ) ; and immune biomarkers explored for their diagnostic and/or predictive potential . Our objective was therefore to explore host immune biomarkers in children who had NTM isolated from respiratory and/or gastric specimens . The present study was nested within a prospective cohort study of BCG-vaccinated neonates in Southern India . In this setting , immune biomarkers from peripheral blood were analyzed in 210 children aged <3 years evaluated for TB using dual-colour-Reverse-Transcriptase-Multiple-Ligation-dependent-Probe-Amplification ( dcRT-MLPA ) and Bio-Plex assays . The children were classified based on clinical examination , chest X-rays and mycobacterial culture reports as either: 1 ) TB disease , 2 ) NTM present and 3 ) controls . The study shows a down-regulation of RAB33A ( p<0 . 001 ) and up-regulation of TGFβ1 , IL-2 and IL-6 ( all p<0 . 05 ) in children with TB disease , and that RAB33A , TGFBR2 and IL-10 ( all p<0 . 05 ) were differentially expressed in children with NTM present when compared to children that were culture negative for MTB and NTM ( controls ) . Carriage of NTM may reduce the specificity of future diagnostic and predictive immune biomarkers relevant to TB management .
Non-tuberculous mycobacteria ( NTM ) are widely distributed in soil and water [1] . The innumerable species comprising the genus Mycobacterium have differences in pathogenicity , virulence , response to drugs , in-vivo adaptation and growth characteristics [2] . Pathogens of the genus Mycobacteria are responsible for serious human diseases , including tuberculosis ( TB ) and leprosy . However , the host-pathogen interactions during atypical ( non-tuberculous ) mycobacterial infection remain poorly characterized [3] , [4] . In recent years , NTM infection is recognized to play a role in exacerbation of chronic pulmonary disorders , e . g . cystic fibrosis and chronic obstructive pulmonary disease and the cause of TB-like disease in the immunocompromised [5] . The data on the prevalence of NTM in TB-endemic countries is limited . The probable factors for under-reporting of NTM are lack of: awareness , standardized or accepted criteria to define NTM respiratory disease and laboratory infrastructure to identify NTM [2] . Furthermore , in the context of TB , the background prevalence of NTM is discussed [6] , as one of the factors explaining the variable efficacy of the BCG vaccine in clinical trials ( 0–90% ) [7] . Subjects with high purified protein derivative ( PPD ) -specific IFN-γ responses ( from NTM exposure ) prior to BCG-vaccination have reduced PPD-specific IFN-γ responses post-vaccination compared to subjects with lower responses pre-vaccination , suggesting an inhibition of BCG efficacy by prior NTM exposure [6] , [8] . Inhibition of BCG efficacy by prior exposure to NTM has also been demonstrated in vivo in animal models [9] . These findings indicate that NTM exposure affects anti-mycobacterial host immune responses raising the possibility of interference with novel immune read-outs , explored for their potential as new diagnostics or immune-correlates of protection from TB progression [10] , [11] . Unraveling these aspects are important , given that new diagnostics are needed , particularly in populations with a high proportion of unconfirmed TB cases , such as young children [12] and in immunocompromised subjects the latter having an increased risk of NTM-related disease . Immune-correlates of protection from TB progression are also needed for vaccine efficacy trials and targeted preventive treatment of subjects latently infected with M . tuberculosis ( MTB ) . Furthermore , the presence of NTM likely interferes with the established immuno-diagnostic methods: the Tuberculin skin test ( TST ) and the QuantiFERON TB Gold in tube assay ( QFTGIT ) , both of which demonstrate a varying degree of cross-reaction with a limited number of NTM species [13] . A recent study from a TB-endemic country shows that NTM were isolated in 6% of all children investigated for pulmonary TB [14] . In our previous study evaluating diagnostic immune biomarkers for MTB infection and disease in young children , the high prevalence of NTM isolates in clinical specimens ( from ∼30% children without TB disease ) made us query to what extent the presence of NTM may mask biomarker differences between children with TB disease , MTB infection and MTB uninfected controls [15] . To our knowledge , immune responses in children in a TB endemic setting with NTM exposure have not been previously characterized . Based on these knowledge gaps , our objective was therefore to explore immune responses in children with NTM isolated from respiratory and/or gastric specimens . In the setting of a longitudinal cohort study of BCG-vaccinated neonates in southern India , we analyzed a pre-selected panel of transcriptional and translational biomarkers in 210 children evaluated for TB and classified according to their chest X-ray ( CXR ) and mycobacterial culture reports . The immune biomarkers in children with NTM present were compared with responses in children that were culture negative for MTB and NTM ( controls ) and children with TB disease but without NTM present ( TB patients ) . Initially , children with NTM present were analyzed regardless of their TST and QFTGIT results and subsequently reanalyzed based on responses to these tests , in order to determine to what extent the results were modulated by latent MTB infection .
The sample collection and study design have been described in detail elsewhere [15] . Briefly , 4382 neonates all BCG-vaccinated within 72 hours of delivery were enrolled within 2 weeks of birth following parental consent . The study was conducted at the Palamaner Taluk , Chittoor district , Southern India . The recruited children were randomly ( based on the population units where they were born ) assigned to active ( visited bimonthly; to check for recent TB contact , symptoms and anthropometry; N = 2215 ) and passive ( TB education given to parents/guardian but with no scheduled home visits; N = 2167 ) surveillance arms , and monitored at fixed time points as outlined in the study protocol for 2 consecutive years . During the study period , 746 children were referred to a TB case verification ward ( CVW ) on suspicion of TB . Referral criteria were 1 ) respiratory symptoms suggestive of TB ( cough ≥2 weeks ) , failure to thrive ( FTT ) defined as any of the following; ( a ) unexplained weight loss or no weight-gain for two consecutive visits; ( b ) downward crossing of two percentile lines on the weight-for-age growth chart or ( c ) weight persistently tracking below the 3rd percentile of weight for age growth chart 2 ) a history of known TB exposure or 3 ) a TST ≥10 mm at study closure . The diagnostic assessment included: clinical examination , a CXR anteroposterior view , two induced sputa ( IS ) and gastric aspirates ( GA ) on consecutive days ( for smear and culture ) , TST ( 2 TU/0 . 1 mL of PPD RT-23; Span Diagnostics , Ltd . , Bangalore , India ) and QFTGIT ( Cellestis Inc , Valencia , California , USA ) . IS and GA samples were examined by fluorescent microscopy ( Auramine ) and culture using liquid ( Mycobacterial Growth Indicator Tube ) and solid ( Löwenstein-Jensen ) medium [16] . Positive cultures were confirmed by the HAIN kit ( GenoType MTBC , Hain Life Sciences , Germany ) . Direct PCR ( The COBAS TaqMan MTB Test , Roche ) was undertaken on culture negative specimens for infants with CXR findings suggestive of TB . From the 746 children investigated at the CVW , the 210 children included in this study were originally selected for an exploratory study of biomarkers with a diagnostic potential in young children assessed for TB disease and MTB infection . All children with clinical TB disease ( n = 13 ) were included . They were diagnosed by the identification of MTB in culture or by PCR ( Roche PCR test ) ( n = 4 ) or; in the case of cultures negative for MTB and NTM , by pathology consistent with TB at CXR as judged by 2/3 radiologists ( n = 9 ) . Children without TB disease ( normal CXR and culture negative for MTB ) , but presumed to be infected based on positive results for TST and/or QFTGIT ( n = 90 ) , were also included . In addition , gender matched MTB uninfected controls ( normal CXR and culture negative for MTB , TST and QFTGIT negative; n = 107 ) were selected amongst other investigated children . For the purpose of this study , the 210 children were re-classified according to whether they had TB disease ( n = 13 ) as previously defined , or no TB judged by culture negativity for MTB and a normal CXR , the latter group ( no TB ) were further subdivided as either NTM present ( defined by ≥1 specimen culture positive for NTM; n = 52 ) or culture negative for MTB and NTM , referred to as controls ( n = 145 ) ( Fig . 1 ) . Notably , none of the children with NTM present fulfilled the criteria for NTM disease suggested by the American Thoracic Society , NTM disease should be considered if there is ( i ) a compatible clinical presentation , ( ii ) a radiographic picture consistent with the diagnosis of NTM , ( iii ) exclusion of other diagnoses , and ( iv ) the recovered NTM species is present in sufficient quantities from consecutive specimens [5] . Acid fast bacteria ( AFB ) culture positive samples were speciated by the HAIN kit ( GenoType MTBC and CM ) , Hain Life Sciences , Germany ) . The HAIN CM kit identifies only 15 commonly isolated NTMs [17] . AFB culture positive samples that were identified as non-MTB complex mycobacteria , but which could not be further speciated by the HAIN CM kit are designated as NTM species in this study . For identifying biomarkers at the transcriptional level , a method which uses a pre-selected panel of genes , dual-colour reverse-transcriptase – multiplex-ligation-dependent-probe-amplification ( dcRT-MLPA ) was applied [18] . The genes in the panel consisted of 4 housekeeping genes , used as internal controls , and 45 genes identified as differentially expressed during MTB infection and/or disease in adults , by screening of different populations by qPCR and microarray [18] . Total RNA was extracted from PAXgene blood collection tubes ( n = 210 ) using the ‘PAXgene Blood RNA kit’ ( PreAnalytiX , Hilden , Germany ) according to the manufacturer's instructions . RNA concentration and purity ( A260/280 nm ratio ) was measured using a spectrophotometer ( Thermoscientific , Delaware , USA ) . For the dcRT-MLPA experiment , 130–150 ng of total RNA was used . The dcRT-MLPA experimental protocol has been described in detail previously [15] , [18] . The amplified PCR products were diluted 1∶10 with nuclease free H2O and added to a mixture of Hi-Di-Formamide with 400HD ROX size standard . The denatured ( at 95°C for 5 min ) products , were immediately cooled on ice . Fragment analysis was performed on a 3730 capillary sequencer ( Life Technologies , California , USA ) , and the data imported into the Gene mapper software ( Life Technologies , California , USA ) . The peak area data ( arbitrary units ) of replicates was averaged , normalized against GAPDH , and log2 transformed as described [18] . Of the 45 genes analyzed , 7 genes had expression levels below the cut off value of 7 . 64 ( corresponding to a peak area <200 arbitrary units ) and one gene CD14 , co-localized with a primer-dimer peak and was therefore omitted from analysis . For the identification of biomarkers at the translational level , supernatants from the QFTGIT assay ( Nil and TB-ag tubes ) ( n = 210 ) were analyzed by a customized 10-plex cytokine/chemokine kit ( Bio-Rad Laboratories Inc . , California , USA ) . For data analysis , the cytokine/chemokine concentrations ( pg/mL ) in the Nil and TB-ag tubes were used and analyzed individually . Differences in biomarkers ( as measured by dcRT-MLPA and the Bio-Plex assay ) between groups were evaluated by non-parametric analysis ( Mann-Whitney U test and Kruskal-Wallis test with Dunn's post-hoc test for multiple comparison ) using IBM SPSS software version 21 . A double sided p-value<0 . 05 was considered significant . GraphPad Prism 5 software was used for graphing the dot plots . The study was conducted according to the Helsinki ( 4th revision ) declaration and approved by the institutional ethical review board of the St . John's Medical College and an independent ethics committee contracted by the Aeras Global TB Vaccine Foundation . At the time of participant enrollment a written informed consent was obtained from parents/guardians . This study was also approved by the Ministry of Health Screening Committee of the Government of India ( No . 5/8/9/60/20006-ECD-I ) .
The participants selected for this study were a subset of 210 children selected from a larger ( n = 4382 ) longitudinal cohort study based on the availability of a full clinical workup and a full array of blood samples ( Fig . 1 ) . Baseline characteristics of the 210 children categorized by study groups are presented in Table 1 . The gender distribution was similar between the groups . Children with NTM present had the same frequency of respiratory symptoms as controls , whereas as expected , children with TB disease had more respiratory symptoms than the other two groups ( for both groups p = 0 . 03 ) . Children with NTM present had less known exposure to TB ( ∼2% ) than the other two groups , but more frequently had FTT ( 85%; p = 0 . 07 ) . NTM were isolated from IS and GA samples with the same frequency , whereas MTB was only isolated from GA . NTM isolates ( 42 . 3% ) that could not be identified at the species level by the HAIN CM kit were designated as Mycobacterium species ( M . spp . ) . The majority of NTMs that could be speciated by the HAIN test were: Mycobacterium fortuitum ( 40 . 4% ) and Mycobacterium intracellulare ( 15 . 4% ) . About 3 . 0% of children were culture positive for NTMs on two consecutive days and samples that had the same NTM species cultured on both days were low ( <1% ) ( Table 2 ) . We first assessed the effect of the presence of NTM on immune biomarkers in the presumed target population for TB booster vaccines: BCG-vaccinated children without TB disease . Of 45 biomarkers tested ( Table S1 ) , there was no appreciable change for most , but transcription of mRNA for RAB33A and TGFBR2 was down-regulated ( p<0 . 05 ) in children with NTM present ( n = 52 ) compared to controls ( Fig . 2a ) . Bio-plex analysis on unstimulated QFTGIT supernatants ( Nil tube ) showed that compared to controls , the expression of cytokine IL-10 ( p<0 . 05 ) was up-regulated in children with NTM present ( Fig . 2 b ) . We next assessed the potential effect of the presence of NTM on biomarkers in a TB diagnostic setting . Compared to controls ( n = 145 ) and children with NTM present ( n = 52 ) , the direct ex vivo transcription of RAB33A was down-regulated ( p<0 . 001; p<0 . 05 , respectively ) in children with TB disease ( n = 13; Fig . 3a ) . Furthermore , Bio-plex analysis on unstimulated whole blood QFTGIT supernatants ( Nil tube ) showed that the expression of cytokine IL-6 was up-regulated in TB disease ( p<0 . 05 ) compared to controls ( Fig . 3b ) . Similarly , the analysis from stimulated whole blood QFTGIT supernatants ( TB-ag tube ) showed that the expression of cytokine IL-2 was up-regulated ( p<0 . 05 ) in children with TB disease compared to controls ( Fig . 3c ) . Interestingly , these differences between children with TB disease and controls were not evident in our earlier study [15] , when children with TB disease were compared to controls ( TST and QFTGIT negative children ) , presumably because 33 of 107 of these controls had NTM present . In the analyses above , the groups of children with NTM present and controls contained children with divergent results for TST and QFTGIT . Children with positive TST and/or QFTGIT tests may have latent TB infection . This is likely to have increased the immunological heterogeneity within these groups . We therefore , repeated the analyses above with “cleaner” groups consisting of TST and QFT negative children only: children with NTM present ( n = 33 ) ; and controls ( n = 74 ) . This sub-analysis identified the same differences as above with regard to a down-regulation of RAB33A ( p<0 . 001 ) and an up-regulation of IL-2 ( p<0 . 001 ) in children with TB disease ( Fig . 4a and 4b ) . In addition , this analysis also revealed an up-regulated transcription of TGFβ1 ( p<0 . 05 ) in children with TB disease compared to the other two groups ( for both p<0 . 05 ) ( Fig . 4a ) .
In the context of TB disease management , a likely impact of NTM on the TB protection induced by the BCG vaccine is well recognized although the mechanisms are unclear . BCG is used as the “gold standard” for induction of protective immune responses against TB in humans , however , there is consensus that it does not induce complete protection against TB in any animal species [19] . Also , clinical trials have shown varying efficacy of the BCG vaccine , and multiple reasons have been suggested , including a potential role for NTM exposure [20] . The immuno-modulating properties of NTM are also likely to affect studies of TB-diagnostic biomarkers as well as immuno-correlates of TB protection by which it is hoped the efficacy of new TB vaccines can be evaluated [21] . In the present study of children , all BCG-vaccinated at birth and aged <3 years , we show that the genes TGFBR2 , RAB33A and the cytokine IL-10 were differentially expressed in children with NTM-positive cultures compared to controls . Background exposure of NTM in the setting of a vaccine trial might therefore interfere with these markers if used as correlates of protection . RAB33A is a member of small guanosine triphosphatase ( GTPase ) family and is involved in vesicle transport and fusion [22] . Dysregulation of GTPases has shown to play a role in blocking the phagosome maturation [23] which is a major survival strategy for MTB [24] . TGFBR2 is involved in signal transduction and mediating inhibition of cell growth and induction of cell death [25] , [26] . IL-10 is an anti-inflammatory cytokine which in the setting of MTB infection inhibits CD4 T-cell responses and dendritic cell functions [27] . We and others have shown that , RAB33A seems to have a potential as a diagnostic marker of TB disease [15] , [28] , [29] . With this study we add that the expression of RAB33A is reduced in children with TB disease compared to children without TB regardless of TST/QFTGIT results or NTM presence . When restricting the comparison of children with NTM present to those with a negative TST and QFTGIT result ( to control for potential effects of MTB infection ) , we found no significant difference in the transcription of RAB33A between children with TB disease and those with NTM present . However , the median value for NTM-positive children consistently lay between that of the TB cases and the mycobacteria-negative children so this result may reflect the smaller sample size of this group or that down-regulation of RAB33A is more strongly impacted by disease , rather than carriage/infection with mycobacteria . Nevertheless , the reduced transcription of RAB33A in children with NTM present compared to controls raises the possibility of an impact of NTM presence on the specificity if RAB33A were to be used in a diagnostic setting . Furthermore , as we have published earlier TGFβ1 appears to be up-regulated in children with TB disease compared to MTB uninfected children [15] . This study provides evidence that TGFβ1 is up-regulated in children with TB disease regardless of NTM presence , but only in TST and QFTGIT negative children , suggesting that MTB infection may also be modulating expression of this gene , but that NTM exposure does not . In contrast , increased levels of IL-2 and IL-6 in children with TB disease was only seen compared to MTB negative controls and not compared to children with NTM present , suggesting a potential interference of NTM on these read-outs in a diagnostic setting . TGF-β1 performs many cellular functions and is involved in wound healing of granulomatous lesions in TB [30] . IL-2 promotes T cell replication and is essential for maintaining adaptive cellular immunity and granuloma formation [31] . The cytokine IL-6 is produced by the innate immune cells early following a pathogen encounter and is implicated in the host inflammatory response to MTB [27] . In a study from South Africa , NTM were isolated in 6% of all children investigated for pulmonary TB and association of NTM isolation with constitutional symptoms was suggestive of host recognition [14] . In the present study , NTM were isolated in about a quarter of the infants in this study . This is a relatively high proportion , but the lack of pathology seen in CXR in children with NTM present and the lack of associated symptoms suggest no association with disease . The possibility of laboratory contamination was considered minimal , due to strict adherence to sampling and laboratory procedures including internal and external quality control . Moreover , the present study shows that NTM were less likely to be isolated from clinical samples at younger ages 0–12 months ( adjusted for gender and symptoms; OR 0 . 18 , CI 0 . 04–0 . 79 ) suggesting a reduced interaction with the environment in younger children , an unlikely finding if NTM presence was caused by contamination , since NTM are ubiquitously found in soil and water . A possible limitation of this study is that we were not able to determine the background NTM rate in a control group of children . Children were referred for investigation if they were considered to be at risk of TB , due to suspected illness or history of TB contact , thereby introducing an ascertainment bias . This factor was partly overcome by comparing children with culture-confirmed NTM or MTB only . Exposure to NTM through the oral or respiratory route is usually asymptomatic . However , our study shows that NTM carriage or transient and likely repeated exposure elicits responses which resemble the response seen in MTB infection [15] , [32] . This highlights the importance of evaluation of TB biomarkers in the context of exposure to NTM . In conclusion , it is clear that NTM presence modulates host immunity . Even though NTM exposure rarely causes a symptomatic infection in healthy individuals , this study shows that NTM carriage or transient and likely repeated exposure does elicit some of the same immune responses as MTB infection , namely down-regulation of and up-regulation of TGFβ1 . In different settings and populations , these immune biomarkers have shown a potential as discriminatory diagnostic biomarkers in MTB infection and disease . Whether these markers hold a potential as correlates of TB protection remains to be elucidated . Nevertheless , the results from the present study suggest that NTM presence should be considered when evaluating future biomarkers for this purpose , as the presence of NTM may impact the specificity of immune biomarkers for TB outcomes . | Non-tuberculous mycobacteria ( NTM ) are a ubiquitous group of mycobacteria found in the environment . They are opportunistic pathogens causing human disease , especially in immunocompromised individuals . Differentiation between NTM infection and tuberculosis ( TB ) can be difficult . Data on incidence of NTM in TB endemic countries is limited due to resource intensive methods required for identification and a considerable workload due to other diseases . The present study was based on children investigated for TB and classified according to chest X-rays and mycobacterial culture reports . We explored host immune biomarkers which are potentially relevant to TB management , in children with confirmed NTM exposure . The findings from the present study suggest that NTM exposure modulates TB-relevant immune biomarkers in the host by eliciting some of the same immune responses as MTB infection . This is may be of importance when evaluating immunological correlates of protection in the setting of TB vaccine trials and potential TB diagnostic biomarkers . | [
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] | 2014 | Effect of Non-tuberculous Mycobacteria on Host Biomarkers Potentially Relevant for Tuberculosis Management |
The peptidoglycan ( PG ) sacculus is composed of long glycan strands cross-linked together by short peptides forming a covalently closed meshwork that protects the bacterial cell from osmotic lysis and specifies its shape . PG hydrolases play essential roles in remodeling this three-dimensional network during growth and division but how these autolytic enzymes are regulated remains poorly understood . The FtsEX ABC transporter-like complex has emerged as a broadly conserved regulatory module in controlling cell wall hydrolases in diverse bacterial species . In most characterized examples , this complex regulates distinct PG hydrolases involved in cell division and is intimately associated with the cytokinetic machinery called the divisome . However , in the gram-positive bacterium Bacillus subtilis the FtsEX complex is required for cell wall elongation where it regulates the PG hydrolase CwlO that acts along the lateral cell wall . To investigate whether additional factors are required for FtsEX function outside the divisome , we performed a synthetic lethal screen taking advantage of the conditional essentiality of CwlO . This screen identified two uncharacterized factors ( SweD and SweC ) that are required for CwlO activity . We demonstrate that these proteins reside in a membrane complex with FtsX and that amino acid substitutions in residues adjacent to the ATPase domain of FtsE partially bypass the requirement for them . Collectively our data indicate that SweD and SweC function as essential co-factors of FtsEX in controlling CwlO during cell wall elongation . We propose that factors analogous to SweDC function to support FtsEX activity outside the divisome in other bacteria .
Most bacteria are encased within a cell wall exoskeleton composed of the heteropolymer peptidoglycan ( PG ) . This macromolecule is assembled from long glycan strands cross-linked together by attached peptides , generating a continuous three-dimensional meshwork that encapsulates the cytoplasmic membrane , specifies cell shape , and protects the cell from its internal turgor pressure [1 , 2] . Bacterial growth and division are intimately linked to hydrolysis of this covalently closed exoskeleton . To enlarge this meshwork during growth , bonds connecting the glycan strands must be broken to allow expansion of the meshwork and/or to incorporate new strands between the existing ones [3–5] . Similarly , during cell division , bonds must be broken in the nascent septal PG to allow invagination of the outer membrane in gram-negative bacteria and to promote cell separation in gram-positive bacteria . PG hydrolases play a central role in these processes , but their activities must be tightly regulated to prevent excessive degradation of the cell wall and the generation of lethal breaches in this protective layer . Many of the enzymes responsible for cell growth and division have been identified in a growing number of bacteria [6–20] . However , the mechanisms by which they are regulated remain incompletely understood . A deeper understanding of these regulatory systems has the potential to reveal new ways to subvert PG biogenesis for therapeutic intervention [4 , 21] . Progress in our understanding of the control of PG hydrolysis comes from studies of the broadly conserved FtsEX complex . This substrate-less ABC transporter has been found to regulate distinct PG hydrolases in diverse bacterial species including E . coli , Streptococcus pneumoniae , B . subtilis , Bacillus anthracis , Mycobacterium tuberculosis , and Caulobacter crescentus [21–27] . FtsEX is a member of the Type VII ABC transporter superfamily that is thought to function in mechanotransmission rather than as transporters [28] . FtsE is the ATPase and FtsX is the transmembrane domain subunit of the complex . The large extracellular loops of FtsX interact with species-specific PG hydrolases that contain regulatory coiled-coil domains or , in the case of E . coli , an activator of PG hydrolases with a regulatory coiled-coil domain . Structural studies of the S . pneumoniae PG hydrolase PcsB that is controlled by FtsEX [26 , 29] suggest that the coiled-coil domain resembles long molecular tweezers that hold the globular PG hydrolase domain in an inactive state [30] . Based on structural analysis of MacB , another member of the Type VII ABC transporter superfamily [28] , FtsEX is thought to function by a mechanotransmission mechanism in which the ATPase cycle of FtsE controls conformational changes in the extracellular loop domains of FtsX triggering PG hydrolase activity perhaps by releasing the catalytic domain from the clutches of its regulatory coiled-coil domain . In most bacteria in which this conserved regulatory module has been examined , FtsEX functions in the context of cell division . In the case of E . coli , FtsEX controls the activity of two PG amidases ( AmiA and AmiB ) via the coiled-coil domain-containing regulator EnvC [27 , 31] . PG hydrolysis by these enzymes allows invagination of the outer membrane through the nascent septal PG layer during cytokinesis . FtsEX is intimately linked to divisome function . The complex is recruited to the cytokinetic ring at an early step in its assembly and recent work indicates that it interacts with the actin-like division protein FtsA to promote recruitment of downstream division factors [32 , 33] . Furthermore , ATP hydrolysis by the FtsEX complex is not only required for cell wall hydrolysis by the two amidases it is also necessary for septal PG synthesis [32 , 34] suggesting that FtsEX functions as a central coordinator of these two processes . FtsEX in C . crescentus has similarly been implicated in linking PG synthesis and its remodeling during cytokinesis [24] . In S . pneumoniae , FtsEX controls the PG hydrolase PcsB during cell division [26] . The mechanism by which FtsEX is recruited to the divisome is not known but , by analogy to E . coli , is thought to involve interactions with divisome components like FtsA or FtsZ [26] . The signal ( s ) that stimulate cycles of ATP hydrolysis in any of these systems are currently unknown but are likely intimately linked to the onset of PG synthesis during cytokinesis . Interestingly , in B . subtilis , FtsEX is not involved in cell division but instead controls the PG hydrolase CwlO that plays a central role in cell wall elongation during growth [22 , 25] . CwlO contains an amino-terminal coiled-coil domain followed by a NlpC/P60 D , L-endopeptidase domain that cleaves the bond between γ-D-glutamate and meso-diaminopimelic acid within the stem peptide [35] . CwlO and a second D , L-endopeptidase ( LytE ) [36] that is not regulated by FtsEX , are functionally redundant [6 , 13] . Cells lacking either of these enzymes are viable but depletion of one in the absence of the other results in a lethal block to cell wall elongation . Consistent with the idea that CwlO is controlled by FtsEX , cells lacking either FtsE or FtsX or harboring point mutations in the putative ATPase domain of FtsE are blocked for cell wall elongation upon depletion of LytE [22 , 25] . As in the case of the division-associated FtsEX complexes , the signals that stimulate FtsEX activity during growth are currently unknown . Here , we investigate whether other factors are required for FtsEX to function outside the multi-protein divisome complex . Taking advantage of the functional redundancy of CwlO and LytE we performed a synthetic lethal screen for mutants that require lytE for growth and identified two uncharacterized genes yqzD ( sweD ) and yqzC ( sweC ) that function in the same genetic pathway as ftsEX and cwlO . We demonstrate that SweD and SweC reside in a multimeric membrane complex with FtsX and function as essential co-factors of FtsEX in the control of CwlO activity . Orthologs of SweD and SweC are present in a subset of Bacilliaceae , Lactobacillales , and Listeriaceae suggesting these factors similarly enable FtsEX to control elongation hydrolases . Interestingly , Bernhardt and co-workers have identified two unrelated membrane proteins in Corynebacterium glutamicum that function as co-factors of the FtsEX-RipC cell wall hydrolase complex to promote cell separation in this organism . Thus , FtsEX complexes employ distinct co-factors to regulate PG hydrolases during cell division , separation , and elongation .
To identify additional factors required for FtsEX-CwlO function , we took advantage of the synthetic lethal relationship between cwlO and lytE . Using transposon-sequencing ( Tn-Seq ) [37] we screened for genes that could tolerate transposon insertions in wild-type ( LytE+ ) B . subtilis but not in cells lacking lytE . Such genes are predicted to function in a genetic pathway with ftsEX and cwlO . Mariner transposon libraries with >100 , 000 unique insertions were generated in wild-type B . subtilis PY79 and an isogenic ΔlytE variant . The two libraries were separately pooled and the transposon-chromosome junctions were mapped by massively parallel DNA sequencing . As anticipated and in validation of our screen , transposon insertions in cwlO , ftsE , and ftsX were readily detected in the wild-type library but were virtually undetectable in the library generated in the ΔlytE mutant ( Fig 1A ) . In addition to these positive controls we identified two genes ( yqzD and yqzC ) of unknown function that were statistically ( P<0 . 05 Mann-Whiney U test ) underrepresented in the ΔlytE library compared to wild-type ( Fig 1A ) . Based on the experiments presented below we have renamed these genes sweD and sweC for synthetic lethal with LytE . The conditional essentiality of sweD and sweC was confirmed by depleting LytE in cells lacking either of these new factors . Fig 1B shows that depletion of LytE in ΔsweD , ΔsweC , or ΔcwlO mutants does not support colony formation . Similarly , cells lacking LytE that were depleted of SweD and SweC were inviable ( Fig 1B ) . Consistent with the idea that sweD and sweC specifically function in a genetic pathway with ftsEX and cwlO , there was no plating defect in the ΔcwlO and ΔftsEX mutants upon depletion of SweD and/or SweC ( Fig 1B and S1A Fig . ) . The sweD and sweC genes reside in an operon and are predicted to encode proteins of 13 kDa and 16 kDa , respectively ( Fig 1C ) . Both proteins are predicted to contain N-terminal transmembrane ( TM ) segments . SweD contains a predicted coiled-coil ( CC ) domain followed by a C-terminal helix-turn-helix ( HTH ) motif ( Fig 1C ) . The C-terminal region of SweC has remote homology to LysM domains that bind polysaccharides including chitin and peptidoglycan . Homologs of SweD and SweC are present in a subset of Bacilliaceae , Listeriaceae , and Lactobacillales family members ( S2 Fig ) . PSI-BLAST also identified potential SweD and SweC homologs in the gram-negative bacterium Helicobacter pylori and a small group of unculturable bacteria that are similarly not firmicutes . To investigate whether sweD and sweC are in the same genetic pathway as cwlO and ftsEX , we analyzed the cytological phenotypes of the mutants by fluorescence microscopy . Cells lacking CwlO or FtsEX ( or both ) are shorter and fatter than wild-type and often slightly curved or bent [6 , 13 , 25 , 38] . Accordingly , we directly compared the morphologies of the ΔsweDC mutant to cells lacking CwlO or FtsEX . The cells were grown in defined rich ( CH ) medium and analyzed by fluorescence microscopy using the fluorescent membrane dye TMA-DPH . The majority of the ΔsweDC mutant cells were shorter and fatter than wild-type ( Fig 2A ) . However , cells lacking sweDC appeared even more bent and curved than the ΔcwlO and ΔftsEX mutants . Importantly , these phenotypes were lost in cells that lacked both SweDC and CwlO , suggesting that these morphological defects require CwlO ( Fig 2A ) . Similar phenotypes were observed in the ΔsweC and ΔsweD single mutants ( S1B Fig ) , but as shown below the two proteins depend upon each other for stability , making it difficult to assign specific functions to either factor . Finally , as reported previously [25] , cells lacking the second elongation PG hydrolase LytE resembled wild-type ( Fig 2A ) . A ΔlytE mutant depleted of CwlO or FtsEX is impaired in elongation but remains capable of cell division , generating short fat cells that ultimately lyse . To further explore the role of SweDC function in cell elongation , we examined the morphological defects in ΔlytE cells upon depletion of SweDC ( Fig 2B ) . Cells lacking LytE and harboring an IPTG-regulated sweDC allele were grown in the presence of inducer in rich medium . Cytoplasmic mCherry and the membrane dye TMA-DPH were visualized by fluorescence microscopy before and at 30-minute intervals after removal of IPTG . As can be seen in Fig 2B , 150 minutes after IPTG removal , cell length was slightly reduced and this reduction continued over the next 60 minutes followed by the onset of lysis . Quantitative image analysis revealed a ~30% reduction in cell length over the depletion time course , similar to what was observed in a ΔlytE mutant depleted of CwlO ( S3 Fig ) [25] . Consistent with the curved and bent phenotypes observed in the LytE+ ΔsweDC mutant ( Fig 2A ) , depletion of SweD and SweC in the absence of LytE resulted in even more dramatic curved morphologies prior to lysis ( Fig 2B ) . A comparison of the terminal phenotypes of cells depleted for SweDC , CwlO and FtsEX in a ΔlytE mutant ( Fig 2C ) revealed that all three depletions generate shorter cells prior to lysis , however the dramatic curved morphologies were only observed when SweDC was depleted . Importantly , this phenotype was suppressed when LytE was depleted in cells in which both CwlO and SweDC were absent ( S4 Fig ) . Altogether , these results argue that cwlO , ftsEX and sweDC reside in the same genetic pathway , and support the idea that SweD and SweC are required for PG hydrolase activity of CwlO . To verify that SweD and SweC are integral membrane proteins and investigate their topologies , we raised antibodies against the soluble domains of both factors and analyzed the proteins by subcellular fractionation . Protoplasts were generated from exponentially growing wild-type cells and then lysed by addition of hypotonic buffer . The lysate was subjected to ultracentrifugation and the membrane fraction was homogenized with buffer in the presence and absence of the nonionic detergent TritonX-100 followed by a second round of centrifugation . As expected for integral membrane proteins , SweC and SweD fractionated with the membranes and could be solubilized with TritonX-100 ( Fig 3A ) . The integral membrane protein EzrA [39] and cytoplasmic protein ScpB [40] served as positive and negative controls for this analysis . Next , we investigated whether the soluble domains of SweC and SweD reside in the cytosol or on the extracellular face of the membrane . Membrane topology prediction programs [41 , 42] yielded equivocal results for both proteins . We performed a protease accessibility assay using a B . subtilis strain engineered to express the sporulation membrane protein SpoIVFA ( FA ) [43] . FA is an integral membrane protein with a large extracellular domain that is accessible to protease cleavage and served as our positive control . Protoplasts were generated from an exponentially growing culture and then treated with buffer , Proteinase K , or Proteinase K and the detergent N-lauroylsarcosine . As anticipated , FA was accessible to Proteinase K resulting in the loss of its extracellular C-terminal domain , which is recognized by our anti-FA antibody ( Fig 3B ) . Consistent with the idea that SweC and SweD are Type II integral membrane proteins with C-terminal intracellular domains , both proteins were inaccessible to protease degradation in protoplasts ( Fig 3B ) . The Type II integral membrane protein EzrA and the cytoplasmic protein FtsE served as protease inaccessible controls and were both resistant to Proteinase K in protoplasts . Importantly all four proteins were efficiently degraded by Proteinase K when detergent was included in the reaction . Taken together , these data indicate that the putative coiled-coil and helix-turn-helix domains of SweD and the LysM-like domain on SweC are located in the cytoplasm . Proteins that reside in complexes sometimes depend upon each other for stability . Accordingly , to explore whether SweD and SweC interact with each other or with FtsEX , we analyzed whether SweD , SweC , FtsE , FtsX , or CwlO depend on each other for stability . To this end , we compared the levels of all five proteins in wild-type and in strains lacking SweD , SweC , FtsEX , or CwlO . Cells lacking SweD had almost undetectable levels of SweC and reciprocally cells lacking SweC had barely detectable levels of SweD ( Fig 4A ) . Expression of either gene in trans restored the levels of both proteins , indicating that the effects were not due to polarity or changes in mRNA stability ( Fig 4A ) . By contrast , the levels of CwlO and FtsEX were unaffected by the absence of SweD/SweC and SweD/SweC levels were unchanged in the absence of either CwlO or FtsEX . These data are consistent with the idea that SweD and SweC interact with each other and in the absence of either one , the other is susceptible to degradation . We previously reported that cell association of CwlO does not depend on FtsEX leading us to speculate that an additional factor holds CwlO at the cell surface [25] . This observation , in part , motivated the Tn-Seq screen that identified SweD and SweC . However , we have since discovered that CwlO non-specifically binds to plastic microfuge tubes confounding our original analysis . Using a modified protocol that accounts for this ( see Methods ) we could detect a decrease in cell-associated ( C ) CwlO and an increase of the protein in the cultured medium ( M ) in cells lacking FtsEX compared to wild-type ( Fig 4B ) . These data and complementary analysis by Errington and co-workers [22] support the idea that FtsX maintains CwlO at the cell surface as has been observed in other bacteria [26 , 27 , 29] . Consistent with the topologies of SweD and SweC and the dependencies described above , the amount of surface-associated CwlO was similar in the presence and absence of SweD and SweC ( Fig 4B ) . To investigate the contribution of the intracellular domains on SweC and SweD to CwlO activity , a series of domain deletions were generated and tested for their ability to support growth in a LytE depletion strain . Strains lacking either the putative coiled-coil ( CC ) or HTH domain of SweD largely phenocopied the ΔsweD null ( Fig 5A and 5B ) suggesting both domains are critical for function . A strain lacking the LysM homology domain on SweC was impaired for growth upon LytE depletion with a >100-fold plating defect on LB agar ( Fig 5A and 5B ) . On defined rich ( CH ) medium the SweC ( ΔLysM ) truncation was viable upon LytE depletion albeit with a small colony phenotype . To establish whether these deletion variants were stably produced in vivo , we monitored their levels by immunoblot ( Fig 5C ) . Since our antibodies were raised against the soluble intracellular domains of SweD and SweC the immunoblots likely underestimate the levels of these truncations . However , because SweC and SweD require each other for stability we also used the level of the unmodified protein as a proxy for their stability . Based on this analysis , the variants appeared to be produced at levels similar to wild-type with the exception of SweD ( ΔCC ) , which was somewhat reduced ( Fig 5C ) . These data indicate that the HTH and CC domains of SweD and the LysM-like domain of SweC are important for function with SweD domains playing more critical roles . Furthermore , these data suggest that if SweD and SweC stabilize each other through interaction then they likely interact via their transmembrane segments . Finally , we analyzed a SweD variant with mutations in the second helix of the HTH domain that in other HTH DNA binding proteins is involved in interaction with DNA [44] . The mutant was stably produced and maintained SweC levels but was impaired for function ( Fig 5 ) . ChIP-seq analysis to determine whether SweD binds DNA failed to identify specific binding sites . Specifically , the ratio of sequencing reads between wild-type and ΔsweDC mutant samples was ~1 across the entire genome ( S5 Fig ) . These data indicate the HTH is important for function but probably not for DNA binding . To gain additional insight into the role of SweDC in cell wall elongation , we sought to identify suppressors of the ΔsweDC ΔlytE double mutant . To this end , we used the LytE depletion strain to screen for conditions in which the double mutant was viable . Mutants with impair cell wall biogenesis are often partially suppressed by growth in hypertonic medium ( 0 . 25 M sucrose ) supplemented with Mg2+ and these conditions were similarly suppressive for cells lacking SweDC and depleted of LytE ( Fig 6A ) . The restoration of viability under these conditions is likely due to residual activity of FtsEX-CwlO in the absence of SweDC , because these conditions did not support growth of the ΔcwlO ΔlytE or ΔftsEX ΔlytE double mutants ( S6 Fig ) . Next , we generated the ΔsweDC ΔlytE double mutant in the absence of the IPTG-regulated lytE allele using the permissive growth condition . We then grew the cells under permissive conditions and selected for suppressors on LB agar medium . Thirteen independently isolated suppressors were mapped by whole genome re-sequencing ( S7A Fig ) . Eight of the suppressors had loss-of-function mutations in walH ( yycH ) encoding a negative regulator of the WalR-WalK two-component signaling pathway [45] . WalR~P is a positive regulator of several PG hydrolases genes including lytE and cwlO and represses the expression of genes [6 , 46 , 47] that encode negative regulators of PG hydrolase activity [48 , 49] . Among the eight walH suppressors , five had second-site missense mutations in either ftsE or ftsX ( S7A Fig ) . The two mutations in ftsX mapped to the first ( S26Y ) and second ( S188F ) TM segments of the protein ( S7B Fig ) . Two mutations in ftsE ( V176F and T188A ) were located in positions predicted to lie adjacent to the nucleotide-binding domain ( S7B Fig ) . The third mutation ( L90F ) was close to the predicted interface between FtsE and FtsX . Three suppressors had missense or small in-frame deletions in walK encoding the WalK sensor kinase . One of these mutations has been previously reported to generate a constitutively active allele of an unrelated sensor kinase [50] and we suspect that all three suppressors are hypermorphic alleles . Finally , we identified two independent mutations in rny encoding RNase Y , a major endonuclease involved in mRNA decay [51 , 52] . The isolations of suppressor mutations in ftsE and ftsX provided a potential link between SweDC and FtsEX . Accordingly , we focused on these suppressors . To test whether these mutations contributed to the suppression of the ΔsweDC ΔlytE double mutant , we reconstructed ftsE ( V176F ) and ftsX ( S26Y ) alleles and tested them alone or in combination with a walH deletion mutant . As can be seen in Fig 6A , both the walH deletion and the ftsEX point mutations could suppress the lethality of ΔsweDC ΔlytE on defined ( CH ) rich medium but neither were able to support growth on LB . However , combining ΔwalH with either ftsEX allele provided suppression on LB . Next , we analyzed the morphologies of the suppressors . Depletion of LytE in the absence of SweDC leads to cell lysis in CH medium ( Fig 6B and S8B Fig ) . Under permissive growth conditions in the presence of sucrose and Mg2+ the cells are fat and curved ( Fig 6B and S8A Fig ) . These phenotypes are likely due to residual FtsEX-CwlO activity in the absence of SweDC as we observe similar morphologies in a ΔlytE mutant expressing low levels of CwlO when grown under the same permissive condition ( S9 Fig ) . We suspect that low-level PG hydrolysis by CwlO results in uneven cell wall elongation leading to the curved cell shape . Importantly , the ftsE and the ftsX suppressor mutations restored rod-shaped morphologies to the ΔsweDC ΔlytE double mutant on CH medium supplemented with sucrose and Mg2+ and partially suppressed the curved morphologies on CH medium without supplementation ( Fig 6B ) . The ΔwalH mutant also partially restored rod-shape morphology to the ΔsweDC ΔlytE double mutant on CH medium supplemented with sucrose and Mg2+ ( S8B Fig ) . Combining the ftsEX mutations with ΔwalH in the ΔsweDC ΔlytE background further restored wild-type-like morphologies on CH medium with and without supplementation ( S8 Fig ) . Collectively , these data support the idea that SweD and SweC function as co-factors of FtsEX in the control of CwlO . The molecular basis for the partial suppression of the ΔsweDC ΔlytE double mutant by ΔwalH remains unclear but could be due to the increase in CwlO levels and/or the global change in cell wall hydrolase activity resulting from high WalR~P activity . The genetic evidence presented thus far place SweD and SweC in the FtsEX-CwlO pathway . To investigate whether SweD or SweC reside in a complex with FtsX , we performed co-immunoprecipitation assays . Crude membrane preparations from wild-type and ΔftsX mutant cells were solubilized with the non-ionic detergent Digitonin . The solubilized membrane proteins were incubated with anti-FtsX polyclonal antiserum and precipitated by Protein A sepharose . The immunoprecipitated material was eluted with SDS sample buffer and analyzed by immunoblot . As can be seen in Fig 7A , the anti-FtsX antibodies efficiently immunoprecipitated FtsX and co-precipitated SweD and SweC but not an unrelated membrane protein WalI ( YycI ) . Importantly , none of these proteins were precipitated from solubilized membrane preparations that lacked FtsX . Thus , these data indicate that SweD and SweC reside in a membrane complex with FtsX . To investigate whether FtsE or FtsX interact directly with either of these factors we used the Bacterial Adenylate Cyclase Two Hybrid ( BACTH ) system . We generated fusions with complementary fragments ( T18 and T25 ) of Bordetella pertussis adenylate cyclase to FtsE , FtsX , SweD and SweC . As anticipated , we detected positive interactions between FtsE and FtsX with several but not all fusions and with the positive control TolB and Pal ( Fig 7B ) . A weak interaction was also observed between TolB and FtsE . This false positive highlights the limitations of the two-hybrid assay and the importance of interpreting positive interactions cautiously . The assay also revealed positive interactions between FtsX and SweD with two distinct fusion pairs and an interaction between SweD and itself . Furthermore , a SweD variant lacking its coiled-coil ( CC ) domain retained the ability to interact with FtsX but not with full-length SweD ( Fig 7C ) , suggesting that the CC domain functions in SweD dimerization . Finally , a SweD variant lacking its entire intracellular domain [SweD ( TM ) ] was unaffected in its ability to interact with FtsX ( Fig 7C ) , suggesting that SweD interacts with FtsX via its TM segment . Despite our in vivo data that SweC and SweD depend on each other for stability and our co-immunoprecipitation assay that identified SweC in a complex with FtsX , we were unable to detect an interaction between SweC and either of these two proteins in the two-hybrid assay .
Altogether our data indicate that SweD and SweC reside in a multimeric membrane complex with FtsX and function as essential co-factors of FtsEX in its control of CwlO activity during cell wall elongation ( Fig 8 ) . Ribosome profiling from exponentially growing B . subtilis cells suggests that the levels of SweC are similar to FtsE and FtsX while SweD levels are ~2-fold higher [53] . Based on these data and our two-hybrid analysis , we hypothesize that the SweD-SweC-FtsE-FtsX complex has a stoichiometry of 4-2-2-2 . Finally , our data indicate that both SweD and SweC have conserved intracellular domains that are important for function and could therefore play roles in maintaining or regulating the ATPase activity of FtsE; directly sensing a signal to modulate cleavage activity; and/or linking the PG hydrolase complex to PG synthesis machinery . The identification of suppressor mutations adjacent to the ATPase domain of FtsE that partially bypass the requirement for SweDC suggests that these co-factors could indeed help maintain and/or control cycles of ATP hydrolysis . However , attempts to reconstitute ATPase activity of FtsE in vitro have thus far been unsuccessful making it difficult to directly test this model . It is also noteworthy that our data indicate that the LysM-like domain on SweC resides in the cytosol rather than facing the cell wall . Since these domains bind polysaccharides , an attractive model is that this domain functions to coordinate PG hydrolase activity with cell wall synthetic capacity by monitoring cytosolic PG precursors . In vitro reconstitution of the complex in the future will allow us to explore this and related models for SweDC function . A connection between the FtsEX-CwlO PG hydrolase complex and the cell wall elongation machinery ( called the Rod complex ) has been proposed previously [22] but the evidence remains incomplete . Cells lacking LytE but not FtsEX or CwlO were found to have a synthetic growth defect when the actin-like protein Mbl was depleted . Since Mbl functions as a scaffold for the Rod complex , these data suggest that CwlO , FtsEX , Mbl and by extension the rest of the cell wall elongation machinery are in the same genetic pathway [22] . We detect similar growth defects when Mbl is depleted in a ΔlytE mutant and the absence of significant growth defects when Mbl is depleted in strains lacking FtsEX , CwlO , or SweDC ( S10 Fig ) . However , we found that a functional SweD-GFP fusion ( S11 Fig ) lacked the dynamic behavior of the Rod complex , which was shown to move in a directed and circumferential manner around the long axis of cell [54–56] . These data suggest that the SweDC-FtsEX-CwlO complex is unlikely to be a core component of the cell wall synthetic machinery but does not exclude the possibility that the two complexes transiently interact and influence each other's activity . Consistent with this idea , formaldehyde crosslinking of B . subtilis cells followed by affinity purification of Mbl and Mass Spectrometry identified FtsX and SweC in crosslinked complexes with Mbl and separately FtsE and FtsX in crosslinked complexes with MreB [57] . However , >65 proteins were identified in each of the crosslinked complexes making it difficult to draw strong conclusions from these findings . Finally , we note that the integral membrane protein RodZ , a core member of the Rod complex , has an intracellular HTH motif like SweD [58–60] . In the case of RodZ , this motif functions to position an adjacent helix such that it can interact with MreB [61] . Although we have shown that the HTH motif on SweD is important for function this domain lacks the analogous interaction helix found in RodZ . Furthermore , we did not observe an interaction between Mbl and SweD in the bacterial two-hybrid assay . Thus , it remains an open question whether the PG hydrolase activity of the SweDC-FtsEX-CwlO complex is coordinated with cell wall synthesis mediated by the Rod complex . We note that gram-positive bacteria like Bacillus subtilis are thought to synthesize their cell wall via an inside to outside mechanism in which newly synthesized layers adjacent to the cell membrane are not initially load bearing [3] . Only as these layers migrate outward during cell growth do they experience stress . It is these more distal load-bearing layers that are likely to be the target of CwlO and LytE . Thus , the activity of these D , L-endopeptidases would not necessarily need to be directly coordinated with PG synthesis as has been proposed for gram-negative bacteria [62] . Finally , we return to FtsEX . This noncanonical ABC transporter is the most broadly conserved regulator of PG hydrolases . In many cases this complex is intimately associated with the divisome where it controls cell wall cleavage during cytokinesis and potentially coordinates PG hydrolysis with septal PG synthesis ( Fig 8 ) . Here , we establish that two co-factors SweD and SweC are critical for FtsEX function outside the divisome during cell wall elongation . Homologs of SweD and SweC are present in Bacilliaceae , Lactobacillales , and Listeriaceae species , where we propose that , like the B . subtilis co-factors , they enable FtsEX to control elongation PG hydrolases . Interestingly , work from the Bernhardt lab has uncovered a distinct set of factors that function with FtsEX in Corynebacterium glutamicum , an actinobacterium that undergoes cell separation through a mechanically driven process called V snapping [88] . These two membrane proteins ( SteA and SteB ) are required for the FtsEX-RipC PG hydrolase complex to promote for V snapping . Thus , the identification of SweDC and SteAB reveal that the broadly conserved FtsEX regulatory module works with distinct co-factors to control PG hydrolases required for cell division , cell separation , and cell wall elongation .
All B . subtilis strains were derived from the prototrophic strain PY79 [63] . Unless otherwise indicated , cells were grown in LB or defined rich ( casein hydrolysate , CH ) medium at 37°C . Insertion-deletion mutations were generated by isothermal assembly [64] of PCR products followed by direct transformation into B . subtilis . Tables of strains , plasmids and oligonucleotide primers and a description of strain and plasmid construction can be found online as supplementary data ( S1 , S2 and S3 Tables , and S1 Text ) . Transposon insertion sequencing ( Tn-seq ) was performed as described previously [65–67] . Libraries of >100 , 000 independent transposants were separately generated in wild-type and a ΔlytE mutant . Genomic DNA was extracted from each and digested with MmeI , followed by adapter ligation . Transposon-chromosome junctions were amplified by PCR ( 17 amplification cycles ) . PCR products were pooled , gel-purified , and sequenced on the Illumina HiSeq platform using TruSeq reagents ( Tufts University TUCF Genomics facility ) . Reads were mapped to the B . subtilis 168 genome ( NCBI NC_000964 . 3 ) , tallied at each TA site , and genes in which reads were statistically underrepresented were identified using the Mann Whitney U test and by visual inspection using Sanger Artemis Genome Browser and Annotation tool [68] . Immunoblot analysis was performed as described previously [69] . Briefly , 1ml of culture was collected and resuspended in lysis buffer [20 mM Tris pH 7 . 0 , 10mM MgCl2 and 1mM EDTA , 1 mg/ml lysozyme , 10 μg/ml DNase I , 100 μg/ml RNase A , 1 mM PMSF , 1 μg/ml leupeptin , 1 μg/ml pepstatin] to a final OD600 of 10 for equivalent loading . The cells were incubated at 37°C for 10 min followed by addition of an equal volume of sodium dodecyl sulfate ( SDS ) sample buffer [0 . 25 M Tris pH 6 . 8 , 4% SDS , 20% glycerol , 10 mM EDTA] containing 10% 2-Mercaptoethanol . Samples were heated for 15 min at 65°C prior to loading . Proteins were separated by SDS-PAGE on 10% ( for SMC ) , 12 . 5% ( for FtsE , FtsX , CwlO , SigA , EzrA , ScpB , SpoIVFA , and WalI ) or 20% ( for SweD and SweC ) polyacrylamide gels , electroblotted onto Immobilon-P membranes ( Millipore ) and blocked in 5% nonfat milk in phosphate-buffered saline ( PBS ) with 0 . 5% Tween-20 . The blocked membranes were probed with anti-SweD ( 1:10 , 000 ) , anti-SweC ( 1:10 , 000 ) , anti-EzrA ( 1:10 , 000 ) [39] , anti-SpoIVFA ( 1:10 , 000 ) [70] , anti-SMC ( 1:10 , 000 ) [71] , anti-SigA ( 1:10 , 000 ) [72] , anti-ScpB ( 1:10 , 000 ) [73] , anti-FtsE ( 1:20 , 000 ) [25] , anti-FtsX ( 1:10 , 000 ) [25] , anti-CwlO ( 1:10 , 000 ) [25] , anti-WalI ( YycI ) [74] diluted into 3% BSA in 1x PBS with 0 . 05% Tween-20 . Primary antibodies were detected using horseradish peroxidase-conjugated goat anti-rabbit IgG ( BioRad ) and the Super Signal chemiluminescence reagent as described by the manufacturer ( Pierce ) . Signal was detected using a Bio-Techne FluorChem R System . Fluorescence microscopy was performed on a Nikon Ti microscope equipped with Plan Apo 100x/1 . 4NA phase contrast oil objective and a CoolSnapHQ2 camera . Cells were immobilized using 1 . 5% agarose pads containing CH medium . Membranes were stained with TMA-DPH ( 50μM ) ( Molecular Probes ) . Exposure times were 400 ms and 800 ms for TMA-DPH and mCherry , respectively . Quantitative image analysis was performed using Oufti [75] . Meshes were created using the cytoplasmic mCherry images . The length of the long axis of >350 cells was determined and the mean cell length was calculated . Images were cropped and adjusted using MetaMorph software ( Molecular Devices ) . Final figures were prepared in Microsoft PowerPoint . Recombinant proteins were expressed in E . coli strain BL21 ( DE3 ) . Strains were grown in 500 mL of auto-induction Overnight Express Instant TB Medium ( Novagen ) supplemented with 100 μg/ml ampicillin at 22°C . After 16 h , cultures were subjected to centrifugation at 10 , 000 × g for 10 min . Cell pellets were resuspended in 15mL Lysis Buffer ( 20 mM Tris pH 7 . 5 , 300 mM NaCl , 5 mM imidazole , 10% glycerol , 0 . 1 μM Dithiothreitol ) and Complete EDTA-free protease inhibitors ( Roche ) and lysed via passage through a French press . Cell lysates were clarified by centrifugation at 10 , 000 X g for 10 minutes at 4°C . Clarified lysates were mixed with 0 . 5 mL of Ni-NTA agarose resin ( Qiagen ) and incubated for 2 hours at 4°C . The mixture was loaded onto a BioRad column , washed with 10 mL Buffer A ( 20 mM Tris pH 7 . 5 , 300 mM NaCl , 5 mM imidazole , 10% glycerol , 0 . 1 μM Dithiothreitol ) . His6-SUMO fusion proteins were eluted with Buffer B ( 20 mM Tris pH 7 . 5 , 300 mM NaCl , 200 mM imidazole , 0 . 1 μM Dithiothreitol ) . Eluates were pooled and dialyzed into 20 mM Tris pH 7 . 5 , 300 mM NaCl , 10% glycerol , 0 . 1 μM Dithiothreitol at 4°C . The dialysates were incubated with His6-Ulp1 protease overnight on ice . Reactions were mixed with 0 . 5 mL Ni-NTA agarose and loaded onto BioRad columns . Flow through fractions containing cleaved ( untagged ) proteins were collected and used to generate rabbit polyclonal antibodies ( Covance ) . 25 mL of exponentially growing cells were collected , washed , and resuspended in 5mL 1X SMM buffer ( 0 . 5 M sucrose , 20 mM MgCl2 , 20 mM maleic acid pH 6 . 5 ) [76] supplemented with Lysozyme ( 4 mg/ml ) . Cells were incubated for 30 minutes at RT with gentle agitation . Protoplast formation was monitored by microscopic observation on 2% 1X SMM-agarose pads . When >95% of the cells were protoplasted they were collected by centrifugation ( 5 Krpm ) and resuspended in 1 mL of 1X SMM buffer and distributed into three microfuge tubes . Protoplasts were incubated with: 1X SMM buffer alone or with Proteinase K ( NEB , 50 ug/ml final ) , or Proteinase K and Sodium-lauroyl-sarcosinate ( 1% ) for 15 min at room temperature . Proteinase K was inactivated by the addition of 2X sample buffer [0 . 25 M Tris pH 6 . 8 , 4% SDS , 20% glycerol , 10 mM EDTA 10% 2-Mercaptoethanol] supplemented with 2 mM PMSF and immediately incubated at 100°C for 10 minutes . Reactions were analyzed by immunoblot . CwlO binds non-specifically to plastic microfuge tubes but can be recovered from them with SDS sample buffer . To monitor the amount of cell-associated and released CwlO , 1 . 5 mL of a mid-exponential phase culture ( grown in LB ) was collected in a plastic microfuge tube and centrifuged for 10 min at 3 , 000 × g . The culture supernatant was transferred to a fresh microfuge tube and the secreted proteins were precipitated by the addition of 15% trichloroacetic acid . The cell pellet was gently resuspended in 50 μL lysis buffer [20 mM Tris pH 7 . 0 , 10mM MgCl2 and 1mM EDTA , 10 μg/ml DNase I , 100 μg/ml RNase A , 1 mM PMSF , 1 μg/ml leupeptin , 1 μg/ml pepstatin] and transferred to a fresh microfuge tube followed by the addition of lysozyme ( 1 mg/ml ) . A whole cell lysate was then prepared as described in the immunoblot protocol above . The microfuge tube used to collect cells and culture medium was washed twice with 1 mL LB to remove any remaining cells . The proteins bound non-specifically to the tube were then released with SDS sample buffer . The sample buffer with released proteins was then used to resuspend the TCA-precipitated proteins from the culture supernatant . Equivalent amounts of cell lysate ( C ) and culture medium ( M ) were resolved by SDS-PAGE and CwlO and SMC were analyzed by immunoblot . The ΔsweDC::kan ΔlytE::cat double mutant was constructed under permissive growth conditions ( CH agar supplemented with 20 mM MgCl2 and 0 . 25 M sucrose ) . Three independent clones ( BYB366 , BYB367 , BYB368 ) were grown to early stationary phase under permissive conditions at 37°C . Cells were washed twice in fresh LB and plated under permissive and restrictive conditions ( LB agar ) at 37°C . The suppressor frequency was ~10−7 . Genomic DNA from 13 suppressors was prepared for whole genome sequencing using a modified Nextera library preparation protocol [77] . DNA concentrations were determined using the Qubit dsDNA HS Assay Kit and fragment sizes were determined using a High Sensitivity D1000 screen tape run on an Agilent 4200 TapeStation system . Sequencing was performed using a MiSeq Kit v6 , with the Miseq System ( Illumina ) . Reads were mapped using CLC Genomics Workbench software ( Qiagen ) . Co-IPs were performed as described previously [78] . Briefly , 150 mL cultures of wild-type and the ΔftsX mutant were harvested at an OD600 of 0 . 5 washed twice with 1X SMM ( 0 . 5 M sucrose , 20 mM MgCl2 , 20 mM maleic acid pH 6 . 5 ) at room temperature . Cells were resuspended in 1:10 volume 1XSMM and protoplasted with lysozyme ( 0 . 5 mg/mL final ) for 30 minutes . Protoplasts were collected by centrifugation and disrupted by osmotic lysis with 3 ml hypotonic buffer ( Buffer H ) ( 20 mM Hepes pH 8 , 200 mM NaCl , 1 mM Dithiothreitol ) with protease inhibitors: 1 mM phenylmethylsulfonyl fluoride and EDTA-free protease inhibitor cocktail complete ( Roche ) . MgCl2 and CaCl2 were added to 1 mM and lysates were treated with DNAse I ( 10 μg/ml ) ( Sigma-Aldrich ) and RNAse A ( 20 μg/ml ) ( USB ) for 1 h on ice . The membrane fraction was separated by ultracentrifugation at 100 , 000 × g for 1 h at 4°C . The supernatant was carefully removed , and the membrane pellet was dispersed in 400 μL of Buffer G ( Buffer H with 10% glycerol ) . Crude membranes were aliquoted and flash-frozen in N2 ( l ) . 200 μL crude membranes were diluted 5-fold with Buffer S ( Buffer H with 20% glycerol and 100 μg/ml lysozyme ) , and membrane proteins were solubilized by the addition of the nonionic detergent digitonin ( Sigma ) to a final concentration of 0 . 5% . The mixture was rotated at 4°C for 1 h . Soluble and insoluble fractions were separated by ultracentrifugation at 100 , 000 × g for 1 h at 4°C . The soluble fraction from the digitonin-treated membrane preparation ( the load ) was mixed with 4 μl of crude anti-FtsX antiserum [25] and rotated for 3 h at 4°C . The mixture was added to 25 μL of Protein A Sepharose resin ( GE Healthcare ) and rotated for 1 h at 4°C . The resin was pelleted at 5 Krpm , and the supernatant ( the flow-through ) was collected . The resin was washed four times with 0 . 4 mL of Buffer S + 0 . 5% digitonin . Immunoprecipitated proteins were eluted by the addition of 50 μl of sodium dodecyl sulfate ( SDS ) sample buffer ( 0 . 25 M Tris , pH 6 . 8 , 6% SDS , 10 mM EDTA , 20% glycerol ) and heated for 15 min at 50°C . The resin was pelleted , and the supernatant ( the IP ) was transferred to a fresh tube and 2-mercaptoethanol was added to a final concentration of 10% . The load , flow-through , and immunoprecipitate were analyzed by immunoblot . The Bacterial Adenylate Cyclase-based Two Hybrid ( BACTH ) system was used as previously described ( [79 , 80] . Briefly , pairs of proteins were fused to the complementary fragments ( T18 and T25 ) of the Bordetella pertusis adenylate cyclase . After co-transformation into BTH101 , independent transformants were inoculated in LB medium supplemented with ampicillin ( 100 μg/mL ) , kanamycin ( 30 μg/mL ) and 0 . 5 mM isopropyl-β-thio-galactoside ( IPTG ) . Cells were grown at 30°C overnight and spotted on LB agar plates supplemented with ampicillin ( 100 μg/mL ) , kanamycin ( 30 μg/mL ) , IPTG ( 0 . 25 mM ) and 5-bromo-4-chloro-3-indolyl-β-D-galactopyrannoside ( X-Gal ) ( 20 mg/mL ) . Plates were photographed after incubation at 30°C for 16 hours . Chromatin immunoprecipitation ( ChIP ) was performed as described previously [69] . Briefly , cells were crosslinked using 3% formaldehyde for 30 min at room temperature and then quenched , washed , and lysed . Chromosomal DNA was sheared to an average size of 250 bp by sonication using a Qsonica Q800 water bath sonicator . The lysate was then incubated overnight at 4°C with anti-SweD antisera , and was subsequently incubated with Protein A-Sepharose resin ( GE HealthCare ) for 1 hr at 4°C . After washes and elution , the immunoprecipitate was incubated at 65°C overnight to reverse the crosslinks . The DNA was further treated with RNase A , Proteinase K , extracted using Phenol-Chloroform , resuspended in 50 μl EB and used for library preparation with the NEBNext Ultra kit ( E7370S ) and sequenced using the Illumina MiSeq platform . The sequencing reads from wild-type and ΔsweDC ChIP samples were mapped to the B . subtilis PY79 genome ( NCBI Reference Sequence: NC_022898 . 1 ) using CLC Genomics Workbench ( CLC bio , QIAGEN ) . Subsequent normalization , plotting , and analyses were done using R plots as follows . Samples were first normalized to the total number of reads . Then the ratio of ChIP signal in wild-type relative to ΔsweDC was calculated and plotted in S4A Fig . The data were plotted in 1 kb windows . For S4B Fig , ChIP signals of wild-type and ΔsweDC between 2390kb and 2400kb were plotted . | Bacterial growth and division require the synthesis and remodeling of the cell wall exoskeleton . To prevent lethal breaches in this protective layer , peptidoglycan ( PG ) hydrolases that remodel the cell wall must be carefully regulated but the mechanisms underlying this control remain poorly understood . The noncanonical ABC transporter FtsEX has emerged as a broadly conserved regulator of PG hydrolases . In most characterized examples , FtsEX is integrated into the division machinery where it controls cell wall cleavage during cytokinesis . By contrast , in Bacillus subtilis the FtsEX complex functions in cell wall elongation . Here , we report the identification of two previously uncharacterized proteins ( SweD and SweC ) that function as essential co-factors of FtsEX in controlling PG hydrolase activity along the lateral cell wall . Homologs of SweD and SweC are found in a subset of firmicutes . We propose that these and analogous factors enable FtsEX to function outside the divisome to control cell wall elongation hydrolases . | [
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"immunoblotti... | 2019 | SweC and SweD are essential co-factors of the FtsEX-CwlO cell wall hydrolase complex in Bacillus subtilis |
Extended periods of waking result in physiological impairments in humans , rats , and flies . Sleep homeostasis , the increase in sleep observed following sleep loss , is believed to counter the negative effects of prolonged waking by restoring vital biological processes that are degraded during sleep deprivation . Sleep homeostasis , as with other behaviors , is influenced by both genes and environment . We report here that during periods of starvation , flies remain spontaneously awake but , in contrast to sleep deprivation , do not accrue any of the negative consequences of prolonged waking . Specifically , the homeostatic response and learning impairments that are a characteristic of sleep loss are not observed following prolonged waking induced by starvation . Recently , two genes , brummer ( bmm ) and Lipid storage droplet 2 ( Lsd2 ) , have been shown to modulate the response to starvation . bmm mutants have excess fat and are resistant to starvation , whereas Lsd2 mutants are lean and sensitive to starvation . Thus , we hypothesized that bmm and Lsd2 may play a role in sleep regulation . Indeed , bmm mutant flies display a large homeostatic response following sleep deprivation . In contrast , Lsd2 mutant flies , which phenocopy aspects of starvation as measured by low triglyceride stores , do not exhibit a homeostatic response following sleep loss . Importantly , Lsd2 mutant flies are not learning impaired after sleep deprivation . These results provide the first genetic evidence , to our knowledge , that lipid metabolism plays an important role in regulating the homeostatic response and can protect against neuronal impairments induced by prolonged waking .
Insufficient sleep adversely affects both endocrine and metabolic processes , resulting in glucose intolerance , insulin resistance , and obesity [1] . Moreover , sleep deprivation results in extensive physiological impairments in both vertebrates and invertebrates , including , but not limited to , cognitive impairments and death [2]–[6] . Sleep homeostasis is defined as the increase in sleep observed following sleep loss . It is theorized that sleep homeostasis restores vital biological functions degraded during sleep deprivation . Unfortunately , precisely which processes need restoration remains a matter of speculation and debate . A common strategy to identify pathways that regulate sleep homeostasis has been to compare animals that have been sleep deprived with a control group that has been sleeping or has had the opportunity to sleep . While many processes have been identified with this approach [7]–[10] , the extent to which they play a role in sleep homeostasis is largely unknown . An alternative strategy for identifying pathways associated with sleep homeostasis is to take advantage of the observation that environmental conditions influence the response to prolonged waking [11]–[13] . Indeed , many behaviors are influenced by interactions between genes and the environment [6] , [14]–[19] . That is , an individual will respond to the specific demands/constraints of their current environment by altering their physiological response in order to optimize their chances of success . Thus a similar challenge that occurs in two distinct environments may differentially activate specific pathways such that contrasting outcomes are observed . For example , at room temperature , flies mutant for the canonical clock gene cycle ( cyc01 ) show an exaggerated sleep rebound ( ∼10-fold greater than wild-type flies ) and begin to die if kept awake for 10 h [6] . However , if cyc01 mutants are exposed to an environment with a higher temperature , they no longer exhibit an exaggerated sleep rebound after sleep deprivation , and they do not die when kept awake for 10 h [6] , [20] . Thus , it may be possible to more efficiently identify pathways that protect flies from the negative effects of waking by evaluating the differential responses to sleep loss that occur in two distinct environments . One such environmental condition that may be particularly useful for contrasting with sleep deprivation is starvation . It has long been recognized that , in several species , the lack of food availability increases the duration of waking [21]–[25] . Moreover , rats respond to chronic total food deprivation with a linear increase in wakefulness , and when allowed access to food , they do not show increases in non-rapid eye movement sleep [26] . Similarly , fasting humans show a reduction in sleep time and increased sleep latency [27] . It has been suggested that animals that are able to remain alert and vigilant in the absence of food might have a selective advantage over animals that accrue sleep debt at a normal rate [24] . Thus , identifying the unique physiological responses to waking induced by starvation as compared to waking induced by sleep deprivation may provide insights into mechanisms underlying sleep homeostasis . We evaluated the consequences of waking induced by starvation and contrasted them to an equivalent amount of waking induced by sleep deprivation . Our results indicate that while sleep deprivation robustly activates sleep homeostasis and results in learning impairments , these negative consequences are not observed following waking induced by starvation . Although cyc01 flies die from sleep loss in 10 h , they can withstand ∼28 h of waking induced by starvation [6] . We demonstrate that cyc01 mutants have increased triglyceride stores compared to background controls , suggesting that genes involved in lipid metabolism may influence the response to extended waking . Two likely candidates are brummer ( bmm ) , a homologue of adipose triglyceride lipase , and Lipid storage droplet 2 ( Lsd2 ) , a homologue of Perilipin . bmm mutants exhibit increased triglycerides and resistance to starvation [28] , while Lsd2 mutants are lean and sensitive to starvation [29] . We show here that bmm and Lsd2 mutants play a role in sleep regulation . That is , bmm mutants displayed a large homeostatic response following sleep deprivation , while Lsd2 mutants had a suppressed sleep rebound . Importantly Lsd2 mutants maintain their ability to learn even in the face of sleep loss , indicating that they are protected from the negative effects of waking . To our knowledge , these results provide the first genetic evidence that lipid metabolism plays a role in regulating sleep homeostasis .
To begin , we investigated the effects of starvation on sleep homeostasis in flies mutant for cyc01 and period ( per01 ) . We chose to evaluate cyc01mutants first due to their extreme sensitivity to sleep loss . That is , in contrast to wild-type flies and other clock mutants , cyc01 flies show an exaggerated homeostatic response after short-term sleep deprivation and , as a group , begin to die if kept awake for 10 h [6] . When cyc01 flies are placed into recording tubes with agar and water ( starvation ) , they exhibit an immediate and sustained increase in waking behavior ( Figure 1A , Figure S1 ) ; when placed back on to their standard diet 7 h later , sleep simply returned to baseline with no evidence of a sleep rebound ( Figure 1A , squares ) . The effects of starvation were contrasted with an equivalent amount of sleep deprivation induced using the sleep nullifying apparatus ( SNAP ) , an automated sleep deprivation device that has been found to keep flies awake without nonspecifically activating stress response genes [6] . Sleep deprivation , starvation , and control treatments were conducted concurrently in arrhythmic cyc01 siblings maintained in constant darkness ( DD ) . Consistent with our previous results , cyc01flies that were sleep deprived using the SNAP displayed an exaggerated homeostatic response ( Figure 1A , diamonds ) ; locomotor activity levels between sleep deprived and starved siblings were not significantly different ( unpublished data ) . To confirm that sleep deprived flies could eat during the deprivation protocol and were not starved , we assessed food intake by placing flies on food with a blue dye . Following 7 h of sleep deprivation , 13 out of 14 cyc01 flies clearly exhibited evidence of blue dye in their abdomen while 11 out of 13 untreated baseline controls exhibited blue dye as rated by an observer blind to condition . Spectrophotometric data confirmed these results ( absorbance at 625 λ: 8 . 7×10−3/fly and 13 . 5×10−3/fly , respectively ) . Thus , both the untreated and sleep deprived flies have access to and consume food throughout the treatment period . Activity , sleep , and feeding behavior of flies immediately following sleep deprivation and starvation can be seen in Video S1 . It is important to note that with longer durations of starvation , flies begin to display sleep homeostasis indicating that the cost of waking does indeed accrue in the absence of food ( Figure S2 ) . However , our data indicate that cyc01flies have a qualitatively different response to ∼7 h of waking induced by starvation versus 7 h of waking induced by sleep deprivation . The lack of a homeostatic response following starvation may represent either an adaptation that allows animals to better withstand the negative effects of waking , or it may simply reflect a physiological impairment that globally disrupts several regulatory processes , including sleep homeostasis . To distinguish between these two possibilities , we evaluated Amylase transcript levels , a known biomarker of sleepiness in flies , to determine if it was elevated following starvation . We have previously shown that , in flies , Amylase levels are only elevated following waking conditions that are associated with increased sleep homeostasis and are not induced by stress [30] . As seen in Figure 1B , cyc01 flies that are sleep deprived for 7 h exhibit a large increase in Amylase mRNA while Amylase mRNA levels remain unchanged in cyc01 siblings starved for 7 h . Thus , both Amylase mRNA levels and the absence of a sleep rebound indicate that , although starvation increases waking , it may not increase sleep drive . Given that starvation is a metabolic challenge , waking induced by starvation could potentially disrupt the normally tight association that is typically observed between Amylase and sleepiness [30] . Therefore we utilized a second , independent behavioral assay to evaluate the functional consequences of waking induced by starvation in cyc01 flies . We chose to evaluate learning , since deficits in learning and memory are well-conserved consequences of sleep deprivation [4] , [5] , [31] . Learning was examined using Aversive Phototaxic Suppression ( APS ) [32] . In this task , flies are individually placed in a T-maze and allowed to choose between a lighted and darkened chamber . During 16 trials , flies learn to avoid the lighted chamber that is paired with an aversive stimulus ( quinine/humidity ) . The performance index is calculated as the percentage of times the fly chooses the dark vial during the last 4 trials of the 16-trial test [5] , [33] . Consistent with our previous results , 7 h of sleep deprivation resulted in a significant reduction in performance ( Figure 1C , black ) . However , no learning deficits were observed following an equivalent amount of waking induced by starvation ( Figure 1C , gray ) . Our previous studies have shown that the mechanical stimulus used to keep the animals awake does not disrupt performance [5] . Importantly , the time required for the fly to complete the 16 trials ( TCT ) was not modified by either sleep deprivation ( 15 . 5±0 . 55 min ) or starvation ( 14 . 5±0 . 76 min ) compared to controls ( 14 . 4±0 . 63 min ) , indicating that differences in performance are unlikely due to alterations in motivation . Moreover , starvation did not alter sensory thresholds ( Table S1 ) as measured by either the Photosensitivity Index ( PI; percentage of photopositive choices in 10 trials in the absence of quinine ) or the Quinine Sensitivity Index ( QSI; time in seconds flies reside on the non-quinine side of a chamber ) consistent with our previous results indicating that sleep deprivation does not alter PI or QSI [5] . The magnitude of the learning deficit observed in cyc01 flies following sleep deprivation is similar to that previously reported for sleep-deprived wild-type flies , flies lacking Mushroom Bodies and classic memory mutants [5] , [33] . Moreover , the deficits in learning following sleep loss in flies are within the range of effect sizes observed following sleep loss in humans and rodents across a number of cognitive domains [34]–[37] . Thus , in contrast to 7 h of waking induced by sleep deprivation , 7 h of waking induced by starvation does not induce ( 1 ) a homeostatic response , ( 2 ) an increase in the expression of a biomarker of sleepiness , or ( 3 ) learning impairments . We next tested whether starvation would alter behavior in per01 flies . We chose to evaluate per01 mutants since our previous results suggested that they are more sensitive to the lethal effects of starvation [6] . As seen in Figure 1D starvation resulted in an immediate and sustained increase in waking that was not compensated for by a homeostatic response when flies were placed back on to their normal diet . Similar to the effects observed in cyc01 mutants , Amylase levels were not elevated in per01 mutants following waking induced by starvation but were elevated by an equivalent amount of waking induced by sleep deprivation ( Figure 1E ) . Finally , while 7 h of waking induced by sleep deprivation resulted in significant decrements in performance in the APS , 7 h of waking induced by starvation did not result in learning deficits ( Figure 1F ) . Starvation did not alter TCT in per01 mutants compared to untreated controls ( 14 . 7±0 . 86 versus 13±0 . 38 min , respectively ) and did not alter PI or QSI . Thus , two different clock mutants exhibit similar response to sleep deprivation and starvation as measured by sleep homeostasis , Amylase and learning . The ability of starvation to increase locomotion in Drosophila is well documented [38]–[42] , suggesting that its effects are likely to extend beyond clock mutants . However , since the effects of starvation on waking have not been quantified directly , we evaluated waking following starvation in flies maintained on a typical light-dark schedule . Wild-type Canton-S ( CS ) flies and flies mutant for Clock ( Clkjrk ) were exposed to starvation for 12 h during the dark period . As seen in Figure 2 , ( CS ) flies and Clkjrk mutants also displayed an immediate increase in waking in the absence of food that is not compensated by a homeostatic response . In CS flies , starvation began at a time of day when feeding is normally low [43] and the amount of waking induced by this duration of starvation is lower than in the clock mutants . Since transgenic lines are frequently generated in a white mutant background ( w1118 ) , we further examined the effects of starvation in w1118 mutants as means to assess whether available transgenic tools can be applied to this question . As seen in Figure 2B , 12 h of sleep deprivation in w1118 mutants produces a sleep rebound that is similar to that observed for other wild-type flies [44]–[46] . Importantly , waking induced by 12 h of starvation was not compensated by a sleep rebound in w1118 flies ( Figure 2B , gray ) even though the amount of sleep lost during starvation did not differ from that induced by sleep deprivation ( p = . 22 ) . Next , we determined whether learning would remain intact in w1118 mutants following waking induced by starvation as was observed in cyc01 and per01 flies . Performance in the APS was evaluated in w1118 mutants following 12 h of sleep deprivation and 12 h of starvation . As seen in Figure 2C , waking induced by sleep deprivation resulted in a significant reduction in learning while siblings that experienced a similar amount of waking induced by starvation performed at baseline levels; the amount of sleep lost did not differ between sleep deprived and starved flies ( p = . 23 ) . Thus , starvation increases waking in wild-type flies and three independent clock mutants , suggesting that the effects of starvation are not limited to a specific genotype or genetic background . Together these data indicate that starvation may be a practical environmental intervention that can be used to identify genes underlying sleep homeostasis . We have previously shown that while cyc01 flies die from sleep loss in 10 h , they can maintain ∼28 h of waking induced by starvation [6] . This result suggested to us the possibility that cyc01 flies might have increased lipid stores . This hypothesis is consistent with recent studies showing that mice mutant for mammalian homologue of cycle , Bmal−/− , show increased total fat content [47] . Thus , we evaluated lipids in cyc01 mutants under baseline conditions . As seen in Figure 3A–Aii , cyc01 mutants had higher levels of lipid stores in their abdomen compared to genetic background controls , rosy506 ( ry506 , Figure 3B–Bii ) . This included increased lipid droplets in gut epithelial cells ( Figure 3Ai versus Bi ) and the abdominal fat bodies ( Figure 3Aii versus Figure 3Bii ) . Since the cyc01 mutation was generated in a ry506 background ( i . e . , its full genotype is cyc01 , ry506 ) ( see Materials and Methods ) [48] , ry506 is the appropriate background control for these experiments . To confirm that this phenotype maps to the cyc locus , we crossed cyc01 homozygotes with flies carrying the appropriate deficiency Df ( 3L ) kto2/TM6B , Tb1 . The resulting cyc01/Df transheterozygote flies showed an Oil Red O staining pattern that was qualitatively similar to that seen in cyc01 ( Figure 3C–Cii ) . The increased adiposity in cyc01 mutants was confirmed using biochemical measurements of organismal triglyceride ( TG ) levels [7] . As seen in Figure 3D , both cyc01 and cyc01/Df show significantly elevated TG levels compared to ry506 controls , whereas the cyc01/ry506 heterozygote displayed an intermediate phenotype . Future experiments will be required to determine whether the observed adiposity is due to a direct effect of the cyc01 mutation on lipid stores or whether the elevated TG levels are an indirect consequence of a disrupted circadian clock . These observations led us to speculate that starvation might protect flies from sleep loss by diverting lipids towards β-oxidation in mitochondria ( Figure S3 ) . To test this hypothesis , we reduced long chain free fatty acid ( FFA ) entry into the mitochondria by feeding cyc01 mutants the carnitine palmitoyltransferase antagonist , etomoxir [49] . Sleep was not modified in control flies fed 25 µM etomoxir for 7 h either during or after administration ( unpublished data ) . Thus , cyc01 flies were fed etomoxir for 7 h during sleep deprivation or 7 h during starvation and then placed back onto their normal food . Etomoxir administration during sleep deprivation did not alter the size of the subsequent homeostatic response ( Figure 3E ) . However , starved cyc01 flies fed etomoxir showed a dramatic increase in sleep homeostasis , which resembled that normally seen after sleep deprivation ( Figure 3E ) . Thus , the mobilization of FFAs may play a role in sleep homeostasis . A Drosophila mutant , bmm1 , has recently been described , which has large triglyceride stores and is resistant to starvation due to its inability to efficiently liberate FFA from triglyceride stores . To determine whether transcript levels of bmm are responsive to either sleep deprivation or starvation , we evaluated relative changes of bmm mRNA from sleep deprived and starved cyc01 mutants . As seen in Figure 4A , sleep deprived cyc01 flies that display a large sleep rebound also exhibit a>5-fold increase in bmm transcript levels . However , bmm transcripts were increased by <2-fold in cyc01 flies following a similar amount of waking induced by starvation . Together these data suggest that bmm may play a role in modulating the response to extended waking . To test this hypothesis , we obtained a deletion mutant , bmm1 , and its genetic background control ( bmmrev ) . Before evaluating sleep , we wished to confirm that the previously reported lipid phenotype was present in flies maintained under our dietary conditions . Evaluation of organismal TG levels established that bmm1 mutants exhibited increased TG in our hands; 58±6 µg TG/mg fly; n = 3 groups of 10 compared to their genetic background controls bmmrev = 18±1 µg TG/mg fly; n = 4 groups of 10 ( p<0 . 001 by Student's t test ) . Although Gronke and colleagues reported increased fat stores in the abdominal fat body , the effects of the bmm1 deletion on the head fat body were not evaluated . As seen in Figure 4B , C , Oil Red O staining of lipids reveals that bmm1 mutants show lipid droplets that are so large that they are hard to discriminate while lipid droplets in the heads of genetic controls ( bmmrev ) are small and well defined . Thus bmm1 mutants , like cyc01 mutants , display increased adiposity . Although bmm1 mutants display increased lipids , their baseline sleep parameters were not severely altered ( see Table S2 for baseline sleep characteristics ) . However , bmm1 mutants had a large sleep rebound following 12 h of sleep deprivation compared to their background controls , bmmrev ( Figure 4D ) . To determine whether the large sleep rebound in bmm1 mutants was due to an elevated sleep drive , we evaluated Amylase mRNA levels following sleep deprivation . As seen in Figure 4E , sleep deprived bmm1 mutant exhibit an elevation in Amylase mRNA while their genetic background controls , bmmrev , showed a less dramatic increase in Amylase mRNA . Given that Amylase levels are not induced by either paraquat [30] or starvation ( Figure 1B ) and are not a necessary response to sleep deprivation ( see below ) , the increase in Amylase seen in bmm1 is unlikely due to increased sensitivity to stress . Finally , we conducted a rescue experiment to re-introduce wild-type bmm ( bmmwt ) into an otherwise bmm1 mutant fly . Since lipases are likely to be ubiquitously expressed , we drove bmmwt using an Act-GAL4 driver . As seen in Figure 4F , no sleep rebound was observed following 12 h of sleep deprivation in the rescue line ( Act-GAL4/UAS-bmmwt; bmm1/bmm1 ) while both parental lines ( Act-GAL4/+ , bmm1/bmm1 and UAS-bmm/+; bmm1/bmm1 ) displayed a robust homeostatic response ( Figure 4F ) . Together , these data indicate that bmm can influence the response to sleep deprivation . Lsd2 is a lipid droplet associated protein with perilipin/ADRP/TIP47 domain ( PAT ) . PAT proteins regulate lipolysis by either blocking lipase access to droplets and by promoting access when phosphorylated [50] . Thus while Lsd2 mutants may release and re-esterify fatty acids , they would also be expected to show reduced lipolysis upon stimulation . Interestingly , Lsd2 mutants ( Lsd251 ) display lower levels of TG while bmm mutants have higher levels of TG than their respective background controls [29] . This relationship between Lsd2 and bmm makes it of particular interest for further investigation . Indeed , whereas bmm1 mutants are fat and readily survive starvation , Lsd251 are lean and die rapidly when starved [28] , [29] . Together with the observation that loss-of-function mutants for Lsd2 exhibit phenotypes that share aspects with starvation , we hypothesized that normally fed sleep-deprived Lsd2 mutants would behave as starved flies and would not compensate for lost sleep with a subsequent sleep rebound . To begin , we confirmed that Lsd251mutants were lean ( Lsd251 = 24±2 µg TG/mg fly; n = 4 groups of 10 ) compared to their genetic controls in which the P-element had been excised ( Lsd2rev = 34±6 µg TG/mg fly; n = 4 groups of 10; p = 0 . 014 by Student's t test ) [29] , [51] . In addition , we evaluated lipids in the head fat body . Although not as dramatic as the change seen in the head of bmm1 mutants , lipid droplets were qualitatively smaller in Lsd251 mutants compared to genetic background controls , Lsd2rev ( Figure 5A , B ) . As predicted , Lsd251 flies did not compensate for lost sleep with a significant increase in sleep over baseline during 48 h recovery from sleep deprivation while genetic controls showed a sleep rebound during this time ( Figure 5C ) . Importantly , Lsd251 flies did not respond to sleep deprivation with an increase in Amylase mRNA levels ( Figure 5D ) , suggesting that they were not sleepy . These data are consistent with our previous results demonstrating that , in flies , Amylase levels are responsive to conditions of high sleep drive , do not depend upon the method used to keep the animal awake , and are not simply activated by stress . Thus , Lsd251 flies showed opposite phenotypes to those seen in bmm1 mutants as measured by lower TG stores , no sleep rebound , and no induction of Amylase after sleep deprivation . As mentioned above , the failure to observe a sleep rebound may simply reflect a physiological impairment that globally disrupts several regulatory processes , including sleep homeostasis . If the genetic lesion associated with Lsd251 simply disrupts the ability to initiate a homeostatic response , then Lsd251 flies should be learning impaired following sleep deprivation . However , if disrupting Lsd2 protects a fly from sleep loss , they should learn following sleep deprivation . A direct test of this hypothesis is achieved within a genotype by determining if performance is reduced following sleep deprivation in comparison with untreated siblings [33] . If a fly is learning impaired following sleep loss , they are considered wild-type . With this in mind , we evaluated learning in Lsd251 mutants following 12 h of sleep deprivation using APS . As seen in Figure 5E , Lsd251 mutants maintained normal levels of learning even after being kept awake for 12 h and thus do not display a wild-type response . In contrast , their genetic background controls , Lsd2rev[28] , responded to 12 h of sleep deprivation with a significant reduction in learning ( Figure 5F ) and are considered to have a wild-type response to sleep loss . It is worth noting that while the performance in Lsd251 flies appears to be slightly lower than that observed in other lines , including genetic controls , the learning scores are well within the range observed for wild-type flies [5] . Moreover , flies that obtain similar performance levels can achieve lower learning scores following sleep deprivation [33] . Thus Lsd251 mutants phenocopy starvation as measured by their ability to withstand waking without initiating a homeostatic response or becoming learning impaired .
We have developed a novel strategy to identify pathways involved in sleep homeostasis . This strategy takes advantage of the observation that many behaviors are influenced by interactions between genes and the environment [6] , [14]–[19] . We chose to examine starvation because it is common in nature and therefore the response to the absence of food is likely to be evolutionarily conserved . More importantly , starvation is a simple manipulation that can be readily placed under experimental control . We report that starvation induces episodes of waking that are not compensated for by a sleep rebound and do not result in learning deficits . Based upon these results , we then evaluated two genes , brummer ( bmm ) and Lsd2 , which have been shown to modulate the response to starvation [28] , [29] . bmm1 mutants , which have increased lipid stores , display an exaggerated sleep rebound . In contrast , mutants for Lsd2 , which has been reported to mimic some aspects of starvation , are able to withstand the negative effects of waking without compensating for lost sleep or exhibiting the learning deficits that are typically observed after 12 hr of sleep deprivation . These data suggest that proper lipid handling is important for modulating an organism's response to sleep loss . Although the precise mechanisms by which these genes alter sleep regulation remains to be determined , these data represent a first step in the molecular dissection of sleep homeostasis . It is interesting to note that gene profiling studies in several species have consistently identified genes involved in metabolism as being modified by behavioral state [7] , [9] , [10] , [52] , [53] . Indeed , the first gene found to be modified by behavioral state in flies was fatty acid synthase [44] . Although many of the specific genes are not identical across studies , it is important to recognize that the categories and pathways are consistent , thereby reinforcing the view that sleep regulatory pathways and lipid metabolism are intimately involved . The impact of sleep deficits on metabolism is now well documented [3] , [54] . In humans , sleep deficits are known to result in metabolic disruption and increased adiposity [1] , [55] . Similarly , long-term chronic total-sleep deprivation in rodents is also associated with severe metabolic disruption [56] . Thus while our data confirm previous observations that sleep loss activates metabolic genes , we also present data demonstrating that metabolic genes , in turn , can influence sleep regulatory centers as measured by sleep homeostasis . Together these data imply a bi-directional relationship between sleep and metabolism . It should be noted that lipids are not just a source of energy but are important modulators of cell signaling , gene transcription , metabolism , and appetite [57] . They modify the functional responses of ion channels , synaptic function , and cellular signaling cascades [58] , [59] . Lipids also activate G-Protein coupled receptors suggesting that they have an extracellular mode of action [60] . Determining which lipid is able to influence sleep homeostasis is a considerable challenge that cannot be solved using genetic strategies alone . Thus , while our genetic studies have identified important lipid metabolism pathways , additional work will be required to fully elucidate the precise molecular mechanisms that impact the sleep regulatory centers . It is highly likely that future studies will turn to lipidomic analysis . The genes and genetic tools we have identified here may be particularly useful in guiding future lipidomic studies . We began by contrasting waking induced by sleep deprivation with waking induced by starvation . Interestingly the mutant Lsd251 , which phenocopies aspects of starvation as measured by low triglyceride stores [28] , [29] , also phenocopies starvation at the behavioral level . That is , Lsd251 mutants can withstand 12 h of sleep deprivation without exhibiting any evidence of a compensatory sleep rebound as is seen with starved flies . It is unlikely that mutations in Lsd2 disrupted the ability of the fly to recover needed sleep since they did not appear sleepy as measured by Amylase mRNA . This interpretation is bolstered by the observation that 12 h of waking in Lsd251 mutants did not result in learning impairments . Learning impairments are a robust consequence of sleep deprivation in mammals and in flies [4] , [5] , [37] . We have previously shown that neither Amylase mRNA levels nor learning impairments can be explained by the method used to keep the animals awake or stress [30] . The observations obtained in both Lsd251 mutants and starved flies provide additional confirmation of these conclusions . Moreover , these results emphasize the utility in evaluating Amylase and learning in addition to sleep homeostasis when interpreting results from genetic studies . Given that sleep homeostasis , Amylase , and learning all suggest that Lsd2 mutants are resilient in the face of sleep loss , understanding the underlying mechanisms may have clinical utility . At this stage , most of our knowledge about the role of lipid regulation , in general , and Perilipin , in particular , has been derived from mammalian studies , although great strides are being made with Drosophila [28] , [29] , [51] , [61]–[63] . The protein product of Perilipin , the mammalian homolog of Lsd2 , surrounds the lipid droplet , thereby preventing access of lipases to the TGs . In addition , Perilipin is able to sequester proteins that activate lipolysis [50] . Mice lacking a functional Perilipin gene ( PLIN−/− ) display higher levels of basal lipolysis in white adipose tissue ( WAT ) . However , PLIN−/− mice do not show the typical increase in lipolysis upon β-adrenergic receptor stimulation [64] , [65] . In contrast , mice lacking a functional Adipose triglyceride lipase gene ( Atgl−/− ) , the mammalian homolog of bmm , have decreased basal lipolysis . Yet like PLIN−/− mice , Atgl−/− do not increase lipolysis when stimulated by a β-adrenergic agonist; Atgl−/− mice also show reduced lipolysis when stimulated by starvation or cold-stress [66] . These data suggest the possibility that deficits in Perilipin may protect against the negative effects of waking , in part , via a sustained release of FFAs . In any event , future studies will be needed to determine whether the response to sleep deprivation observed in bmm1 and Lsd251 mutant flies will be observed in Perilipin and Atgl null mutant mice . Although the mechanisms underlying sleep homeostasis are largely unknown , adenosine has been implicated as playing a role in both rodents and humans [67]–[69] . Reducing adenosine release from glia or conditionally knocking out the gene adenosine A1R in mice ( AdoA1R−/− ) attenuates the homeostatic response to sleep loss [31] , [70] . Interestingly , the attenuated homeostatic response in AdoA1R−/− mice is associated with learning impairments , further supporting the hypothesis that sleep homeostasis restores vital biological functions degraded during sleep deprivation [31] . The cognitive effects of sleep deprivation may be both task and circuit dependent [31] , [70] . Indeed , blocking adenosine release from glia prevents cognitive impairment following sleep loss as measured by novel object recognition [70] . Thus , evaluating cognitive behavior following sleep deprivation provides an important tool for evaluating the functional outcome of a genetic manipulation that alters sleep homeostasis [5] . Together with our data , these results suggest that it is possible to identify genes that can attenuate the negative consequence of waking as defined by both reduced sleep homeostasis and intact cognitive ability following waking . There are many homologous characteristics of sleep between mammals and flies . In both mammals and flies , sleep and wake states are influenced by monoaminergic neurotransmitters [71]–[74] , GABA [75] , the immune system , [9] , [71] , [76] , and potassium channel activity , to name but a few . However , the evidence in mammals for a role of lipid metabolism in sleep regulation is limited . The absence of acyl-coenzyme A dehydrogenase , an enzyme that participates in β-oxidation , results in the reduction of theta waves during sleep [77] . Pharmacologic blockage of PPARγ results in altered slow wave sleep [78] , and fatty acids , such as oleamide and anandamide , that depend on fatty acid amide hydrolase for degradation appear to induce sleep alterations [79] . Although a P-element screen in Drosophila link metabolic genes to baseline sleep [80] , to our knowledge we provide the first demonstration that lipid metabolic enzymes play a role in sleep homeostasis . Given that metabolic pathways are highly conserved between mammals and flies [81] it will be interesting to determine whether lipid metabolism also plays a similar role in mammals . Diverse species such as the pigeon [11] , the white crown sparrow [12] , the killer whale [82] , the rodent [26] , and the fly have each developed adaptations that allow them to minimize the deleterious effects of wakefulness in dangerous or life-threatening situations . These observations emphasize that the environment can have a dramatic impact on how an individual responds to extended waking . Since diverse species have developed these adaptations to events which are common in nature , it is likely that they are under genetic control and provide a selective advantage . That is , in certain circumstances it may be beneficial for an animal to be able to withstand a short period of waking without becoming sleepy or cognitively impaired . Our data showing that homeostasis re-emerges with longer durations of starvation suggest these adaptations will have limits . We fully expect that studies evaluating the adaptations seen in the white crown sparrow and the killer whale will continue to provide additional insights into sleep regulation . However , these model systems are not amenable to genetic dissection . In contrast , starvation is easily applied in the laboratory and can be coupled with genetic model systems such as the fly and the mouse . Thus , one can exploit environmental conditions to provide crucial insights into both the mechanisms of sleep regulation and , perhaps , its function . While this article was in review , another group reported that starvation induces spontaneous waking [87] .
Flies were reared in standard laboratory conditions , 12∶12 light:dark schedule , standard food ( yeast , sucrose , corn syrup , molasses , and agar ) , 25°C , and 50% humidity . The cycle01 ( cyc01 ) and period01 ( per01 ) mutant flies were obtained from Dr . Jeff Hall [48] . This mutation was originally generated in a ry506 background ( i . e . , the full genotype would be +;+;cyc01 , ry506 ) , thus ry506 was used as its background control [48] . Actin-GAL4/CyO ( Act-GAL4 ) , rosy506 ( ry506 ) , and Df ( 3L ) kto2/TMB , Tb1 were obtained from the Bloomington Stock Center ( Bloomington , Indiana ) . The null mutation for brummer ( bmm1 ) and the background control ( bmmrev ) as well as the Lsd2 mutant ( Lsd251 ) and its background control ( Lsdrev ) were obtained as a generous gift from Dr . Ronald Kuhnlein . Three-day-old flies were placed into 65 mm glass tubes containing standard lab food and monitored with the Trikinetics activity-monitoring system ( Waltham , MA ) as previously described [6] , [44] . Briefly , activity was recorded in 1 min bins and episodes of quiescence ≤5 min were considered sleep . Total sleep time , sleep architecture , and sleep homeostasis were calculated using an in-house program according to criteria previously established [6] , [44] , [83] . Flies were sleep deprived using the sleep-nullifying apparatus ( SNAP ) , which asymmetrically tilted −60° to +60° such that the sleeping flies were displaced during the downward movement 6 times/minute [6] , [44] . Flies were deprived of sleep for 12 h between ZT12 ( lights out ) to ZT0 ( lights on ) at which point flies were released into recovery where they remained unperturbed for 48 h . The clock mutants cyc01 and per01 were maintained and sleep deprived under constant darkness; sleep deprivation occurred for 7 h during the day between CT0 and CT12 . Sleep homeostasis was calculated for each individual as a ratio of the minutes of sleep gained above baseline during recovery divided by the total minutes of sleep lost during sleep deprivation ( min gained/min lost ) . Cumulative difference plots were calculated for each individual fly first by subtracting the minutes of sleep during deprivation and recovery from the corresponding baseline value and summing the difference score with the preceding hour . A negative slope indicates that sleep is being lost; a positive slope indicates sleep gained; and a slope of zero indicates that recovery is complete . Starvation is operationally defined as a condition in which the animal has no access to food and during which energy intake drops below levels that the animals would normally experience at that time . Flies were placed into Trikinetics tubes containing a 1% agar solution and then switched back to their normal food at the end of the starvation period . For all genotypes , starvation was carried out in constant darkness at the same time , for the same duration , and under the same conditions as for sleep deprived flies . Durations for starvation and sleep deprivation were based on Figure S2 and [6] . For the clock mutants , cyc01 and per01 , a 7 h treatment was chosen because it maximized the difference in behavioral responses to sleep deprivation and starvation but did not result in lethality . CS flies were housed under DD for 3 d . On day 4 , starvation was carried out for 12 h during the primary sleep period . The primary sleep period was identified from the previous days' data based upon the average time that the CS flies initiated their longest sleep bout . w1118 experiments were carried out under LD conditions . Flies were transferred to starvation media prior to lights out , where they remained for the 12 h dark period . The following morning , flies were placed back on to normal food to evaluate sleep homeostasis or their performance was evaluated in the APS . For etomoxir experiments , flies were placed into tubes containing either 1% agar or standard laboratory food with a final concentration of 25 µm etomoxir . At the end of the manipulation , flies were placed back on to standard laboratory food without etomoxir . The learning paradigm requires flies to inhibit a prepotent attraction towards light and has been previously described [32] . Both dark and lighted vials are covered with filter paper . The filter paper in the lighted vial is wetted with 320 µl of a 10−1 M Quinine hydrochloride solution ( Sigma , St . Louis , MO ) . After entering the dark or lighted vial , the choice is recorded and the fly is quickly removed from the vial and placed back at the entrance of the maze . The number of times the fly enters the dark vial is tabulated during 4 blocks of 4 trials . During the test , the light and quinine/humidity appear equally on both the right and left . For an experiment , learning was evaluated by the same experimenter who was blind to genotype and condition . Unless otherwise stated , all flies were tested in the morning between ZT0 and ZT4 . For sleep deprived and starved flies , they remained in their respective conditions until tested . Learning scores are normally distributed [5] . Thus , statistical analyses were performed using Systat ( Systat , Chicago , IL ) . Differences were assessed using either a Student's t test or analyses of variance ( ANOVAs ) , which were followed by a modified Bonferroni test; unless stated otherwise , all experiments are n≥7 . Photosensitivity was evaluated in the T-maze over 10 trials in the absence of filter paper . The lightened and darkened chambers appeared equally on both the left and right . PI is the average of the scores obtained for 5–6 flies ± SEM . Five flies were individually placed at the bottom of a 14 cm cylindrical tube ( Becton-Dickson , Franklin Lakes , NJ ) , which was uniformly lighted . Each half of the apparatus contained separate pieces of filter paper , which could be wetted with quinine or kept dry . The QSI was determined by calculating the time that the fly spent on the dry side of the tube when the other side had been wetted with quinine , during a 5 min period . Total RNA was isolated from 20 fly heads with Trizol ( Invitrogen , Carlsbad , CA ) and DNAse I digested . In the case of whole flies , 3–5 flies were frozen and homogenized . cDNA synthesis was performed in triplicate using Superscript III ( Invitrogen , Carlsbad , CA ) , according to manufacturer protocol . In order to evaluate the efficiency of each reverse transcription , equal amounts of cDNA were used as a starting material to amplify RP49 as previously described [6] . cDNA from comparable reverse transcription reactions were pooled and used as a starting material to run three QPCR replicates . Expression values for RP49 were used to normalize results between groups . For flies maintained on an LD schedule , both experimental and untreated controls were collected at the exact same circadian time ZT0-1 . For clock mutants , the control , sleep deprivation , and starvation experiments were run in parallel and the flies were collected at the same time . For each genotype , 10 female flies were frozen and stored at −80°C . Lipid measurements were carried out at the Clinical Nutrition Research Unit at Washington University . Flies were weighed and homogenized in a 2∶1 ( methanol:chloroform ) solution to extract the lipids [84] . The MeOH:chloroform is evaporated using the speed vac , and the lipids were re-suspended in the starting reagent for Infinity ( ThermoElectron , Waltham , MA ) triglyceride reagent and triglyceride levels detected using the colorometric detection according to the manufacturer's specifications . Lipid levels are quantified using a standard curve of known triglyceride run in parallel . Flies were immobilized with CO2 , submerged in Optimal Cutting Temperature ( Tissue-Tek , Torrance , CA ) and frozen on dry ice . 12–15 µm frozen sections were collected on Histobond slides ( VWR , West Chester , PA ) . Sections were fixed in 4% paraformaldhyde in phosophate buffered saline ( PBS ) and subsequently rinsed in PBS . Slides were then rinsed in 60% isopropanol for 5 min . The solution was changed to Oil Red O stain ( Sigma , St . Louis , MO ) in 60% isopropanol . Sections were stained for 5–10 min . Slides were rinsed several times in distilled water to get rid of excess stain . Slides were dried and mounted using Glycergel ( Wako , Carpinteria , CA ) . Brightfield Images were taken on a Nikon Eclipse 80i microscope ( Belmont , CA ) using a Micropublisher 5 . 0 RTV camera ( Q imaging , Surrey , British Columbia , Canada ) and visualized with the software package Metamorph ( Universal Imaging , Downingtown , PA ) . Images were optimized for visualization and publication using Adobe Photoshop ( Adobe , San Jose , CA ) . Flies were transferred onto normal food with 1% ( v/v ) blue food dye ( F D & C Blue Dye no . 1 , Durkee ) . At the end of the measurement period , flies were anesthetized by CO2 and the appearance of blue dye in the abdomen through the cuticle was evaluated by an observer blinded to conditions using a Vista Vision dissecting microscope ( VWR , West Chester , PA ) . Spectrophotometric measurement of feeding was based on [43] , [85] , [86] . Flies from the visual confirmation of blue dye were frozen on dry ice . Heads were then removed to prevent eye pigment from interfering with the absorbance spectrum of the dye . Fly bodies were homogenized in 200 µL PBS buffer and centrifuged ( 13 , 000 rpm ) for 25 min . The supernatants were transferred to a new tube , again centrifuged at 13 , 000 rpm for 25 min , and absorbance was measured at 625 nm . Absorbance per fly was determined by taking the total absorbance from the group and dividing it by the total number of flies , then subtracting the absorbance per fly from control flies fed non-dyed normal food to give a final absorbance reading per fly . | It is well established in humans that sleep deficits lead to adverse outcomes , including cognitive impairments and an increased risk for obesity . Given the relationship between sleep and lipid stores , we hypothesized that metabolic pathways play a role in sleep regulation and contribute to deficits induced by sleep loss . Since starvation has a large impact on metabolic pathways and is an environmental condition that is encountered by animals living in the wild , we examined its effects on sleep in the fruit fly Drosophila melanogaster . Interestingly , when flies are starved they display an immediate increase in waking . However , in contrast to sleep deprivation , waking induced by starvation does not result in increased sleepiness or impairments in short-term memory . To identify the mechanisms underlying these processes , we evaluated mutants for genes that have been shown to alter an animal's response to starvation . Interestingly , brummer mutants , which are fat , show an exaggerated response to sleep loss . In contrast , mutants for Lipid storage droplet 2 are lean and are able to stay awake without becoming sleepy or showing signs of cognitive impairment . These results indicate that while sleep loss can alter lipids , lipid enzymes may , in turn , play a role in regulating sleep and influence the response to sleep deprivation . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [
"neuroscience/behavioral",
"neuroscience",
"neuroscience/cognitive",
"neuroscience",
"physiology/integrative",
"physiology",
"physiology/neural",
"homeostasis"
] | 2010 | The Perilipin Homologue, Lipid Storage Droplet 2, Regulates Sleep Homeostasis and Prevents Learning Impairments Following Sleep Loss |
CD4+/CD8+ double positive ( DP ) T cells have been described in healthy individuals as well as in patients with autoimmune and chronic infectious diseases . In chronic viral infections , this cell subset has effector memory phenotype and displays antigen specificity . No previous studies of double positive T cells in parasite infections have been carried out . Seventeen chronic chagasic patients ( 7 asymptomatic and 10 symptomatic ) and 24 non-infected donors , including 12 healthy and 12 with non-chagasic cardiomyopathy donors were analyzed . Peripheral blood was stained for CD3 , CD4 , CD8 , HLA-DR and CD38 , and lymphocytes for intracellular perforin . Antigen specificity was assessed using HLA*A2 tetramers loaded with T . cruzi K1 or influenza virus epitopes . Surface expression of CD107 and intracellular IFN-γ production were determined in K1-specific DP T cells from 11 chagasic donors . Heart tissue from a chronic chagasic patient was stained for both CD8 and CD4 by immunochemistry . Chagasic patients showed higher frequencies of DP T cells ( 2 . 1%±0 . 9 ) compared with healthy ( 1 . 1%±0 . 5 ) and non-chagasic cardiomyopathy ( 1 . 2%±0 . 4 ) donors . DP T cells from Chagasic patients also expressed more HLA-DR , CD38 and perforin and had higher frequencies of T . cruzi K1-specific cells . IFN-γ production in K1-specific cells was higher in asymptomatic patients after polyclonal stimulation , while these cells tended to degranulate more in symptomatic donors . Immunochemistry revealed that double positive T cells infiltrate the cardiac tissue of a chagasic donor . Chagasic patients have higher percentages of circulating double positive T cells expressing activation markers , potential effector molecules and greater class I antigenic specificity against T . cruzi . Although K1 tetramer positive DP T cell produced little IFN-γ , they displayed degranulation activity that was increased in symptomatic patients . Moreover , K1-specific DP T cells can migrate to the heart tissue .
Expression of either CD4 or CD8 on mature peripheral CD3+ T cells is considered to be a mutually exclusive event as a result of the thymic selection , reflecting the specific functions of each major T cell subpopulation . Contrary to this conventional dichotomy , circulating CD4+/CD8+ double positive ( DP ) T cells have been identified in human peripheral blood and represents between 1 and 3% of the total T lymphocytes population [1] . The role of these DP T cells in health and disease is still under investigation . Some healthy individuals can display a significant proportion of DP T cells in peripheral blood . Furthermore , previous evidence has suggested that their frequency in blood can increase or they can be localized in specific tissues during several inflammatory diseases [2]–[8] , including: a ) chronic viral diseases , like EBV infectious mononucleosis [3] and HIV [4]; b ) autoimmune pathologies characterized by chronic lymphocytes activation , such as autoimmune thyroiditis [5] , myasthenia gravis [6] and systemic sclerosis/scleroderma [7]; c ) allergy i . e . atopic dermatitis [8] and d ) some neoplasias [3] , [9] . Based on the intensity of CD4 and CD8 expression by flow cytometry , two subsets of DP T cells have been defined: CD4dim/CD8bright and CD4bright/CD8dim lymphocytes [3] . Previous studies of their phenotypic characteristics have shown that the majority of these cells have memory phenotype ( CD45RO+ ) . They are also more differentiated than mono-positive T cells , based on its low level of expression of CD27 , and they frequently produced either intracellular granzyme B or perforin [10] , [11] . Functional assays showed that during chronic viral infections , DP T cells secrete cytokines , such as IFN-γ , in response to cognate class I restricted antigens [10] . All these results suggest that , although small , DP T cells constitute a highly differentiated memory subpopulation acting in the adaptive immune response against infectious agents [1]–[4] , [10] , [11] . As this cell population is expanded in several viral and immunological mediated chronic diseases , it seems plausible that DP T cells can contribute to the immune response against chronic parasitic infections . The goal of this study was to determine the frequency , phenotype and effector potential of circulating DP T cells in patients chronically infected with T . cruzi , the etiological agent of Chagas disease . This hemoflagellate parasite , which is found in Central and South America , is transmitted by vectors of the Reduviidae family and produces both an acute and a chronic phase [12] , [13] . Prevalence of Chagas diseases in Colombia is calculated to be 1'300 , 000 , while 3'500 , 000 people are at risk of contracting the infection , representing a potential public health problem [13] , [14] . After T . cruzi inoculation , during the acute phase , the parasite extracellular stages are found in peripheral blood and infected individuals develop constitutive symptoms . Activation of the immune system allows parasite control , although it is not completely eliminated . Parasites invade cells such as monocytes/macrophages , dendritic cells , fibroblast and myocardiocytes , shedding their flagella and becoming intracellular [15] . By mechanisms not clearly understood , parasites persist leading to the chronic phase of the disease . Most of the infected individuals will remain asymptomatic for several years , being classified as indeterminate . Those patients are usually detected by routine serological tests in blood banks . Nearly 20% to 30% of the chronic infected patients will develop tissue damage , being Chagasic cardiomyopathy or digestive disease the most common pathologies [12] , [13] . What mediates the tissue damage in Chagas is not well understood , but some evidence suggests that parasite persistence and dysfunctional cellular immune response could contribute to this process [12] , [15] . During the infection , antibodies elicited against T . cruzi antigens help to control blood circulating parasite [16] , [17] and specific CD4+ and CD8+ T cells act against intracellular forms [18] , [19] . Mice models demonstrated that T cells response seemed to be crucial for parasite control [20] . Interestingly , acute infection with T . cruzi in mice showed a large increase of CD4+/CD8+ DP T cells in their subcutaneous lymph nodes [21] . Given the characteristics of the DP T cells ( memory phenotype and presence of cytotoxic granules ) , it is of special interest to determine their functional characteristics in chronic chagasic patients .
Research protocols and informed consents were approved by the Ethical Committees of the Universidad de los Andes ( 039-2009 ) , Pontificia Universidad Javeriana ( 01-2010 ) and the Fundación Abood Shaio ( 134-2010 ) , Bogotá , Colombia , following the national regulations and the Declaration of Helsinki . Forty-one volunteers who signed the informed consent were enrolled in this study and divided into three groups . The first group included 17 chronic chagasic patients with positive immunofluorescence indirect assay ( IFI ) and ELISA tests . It was composed of 13 females and 4 males with ages ranging from 36 to 67 years old , recruited at the Fundación Abood Shaio ( Bogotá , Colombia ) or at Instituto Nacional de Salud; and classified according to the Kuschnir grading system [22] . Seven individuals were classified as indeterminate chagasic patients with no significant findings during clinical assessment ( G0 or asymptomatic ) and 10 as cardiac chronic chagasic patients ( symptomatic ) graded as follows: 3 with only abnormal ECG results ( G1 ) , 5 with abnormal ECG results and cardiac enlargement ( G2 ) and 2 with abnormal ECG results , cardiac enlargement and clinical signs of heart failure ( G3 ) . The second group included 12 donors with cardiomyopathy of non-infectious etiology , including 8 females and 4 males with ages ranging from 28 to 80 years old , and whose anti-T . cruzi antibodies were negative . In this group , cardiomyopathy etiology was: ischemic cardiomyopathy ( n = 6 ) , systemic arterial hypertension ( n = 4 ) and idiopathic dilated cardiomyopathy ( n = 2 ) . This group of patients was recruited at the Department of Cardiology , Hospital Universitario San Ignacio , Bogotá , Colombia . The third group included 12 uninfected donors who never lived in a Chagas endemic area , and with negative IFI and ELISA tests . They were 9 females and 3 males with ages ranging from 34 to 68 years old . The characteristics of the three groups , denoted as chagasic patients ( CP ) , non-chagasic cardiomyopathy ( NCC ) and healthy controls ( HC ) , including main clinical , electrocardiogram and echocardiography findings , are resumed in Table 1 . Blood samples were obtained from each donor using EDTA vacuntainer tubes . Total blood ( 100 µl/tube ) was stained with anti-CD3 APC ( clone SK7 ) , anti-CD4 PerCP ( SK3 ) , anti-CD8 PE ( RPA-T8 ) , anti-HLA-DR PE-Cy7 ( L243 ) and anti-CD38 FITC ( HIT2 ) . All monoclonal antibodies were purchased from BD Bioscience ( San Jose , CA , USA ) . Blood was stained in darkness for 30 minutes at 4°C and incubated with cell lysis buffer ( BD Bioscience ) for 10 minutes at room temperature . Then , cells were washed twice in PBS 0 . 01 M pH 7 . 4 and gently re-suspended . Samples were acquired and analyzed in a FACS Canto II with FACSDiva software ( BD Bioscience ) . At least 5×104 cells were acquired in the lymphocyte population gate according to their forward scatter ( FSC ) versus side scatter ( SCC ) features . Dead cells were excluded by light scatter ( FSC-H versus FSH-A ) . All data shown for CD4+/CD8+ DP T cells are based on the CD3+ gate . Analysis was done with 2×106 of peripheral blood mononuclear cells ( PBMC ) from each individual , obtained by ficoll-hypaque density gradient ( Sigma , St . Louis , MO , USA ) . Viability was assessed by trypan blue exclusion ( Sigma ) . Surface staining was done with antibodies against CD3 APC , CD4 PerCP and CD8 PE-Cy7 for 30 minutes at 4°C . After one wash , the cell membrane was permeated with Cytofix/Cytoperm solution for 20 minutes at 4°C , followed by washing with Perm/Wash 1× ( BD Bioscience ) . Intracellular staining was done with anti-perforin FITC antibody ( clone δG9 ) or mouse IgG2b isotype control ( clone 27–35 ) for 30 min at 4°C . Lastly , cells were washed , re-suspended and analyzed as described above . At least 2×105 CD3+ cells were recorded by flow cytometry and perforin expression was determined in CD4+/CD8+ gate . As HLA-A2 is one of the most common class I allele in Colombia [23] , donors were typed for HLA-A2 and subtype for HLA-A*0201 by flow cytometry and SS-PCR as previously described [24] , [25] . Tetramer analysis was only done in HLA-A*0201+ individuals , including: 13 chagasic donors ( 6 asymptomatic and 7 symptomatic ) and 5 healthy controls . Cells were incubated with anti-CD3 APC , anti-CD4 PerCP , anti-CD8 PE-Cy7 and anti-HLA-A*0201 PE tetramers loaded either with T . cruzi or influenza virus derived epitopes . T . cruzi epitope or K1 , is a 9 mer peptide ( TLEEFSAKL ) derived from N-terminal region ( amino acids 4–11 ) of T . cruzi KMP-11 protein ( Swiss-Prot accession number: Q9U6Z1 ) [24] , [25] . Influenza virus peptide was a modified epitope derived from the viral matrix proteins ( a . a . 58–66 ) denominated MP-Flu ( GILGFVTTL ) [25] . Tetramers were synthesized by the National Institute of Health ( NIH ) Tetramer Facility ( Atlanta , USA ) . At least 2×105 cells were analyzed by flow cytometry in the CD3+ gate and tetramer expression was determined in the CD4+/CD8+ gates . PBMC from 5 asymptomatic ( G0 ) and 6 symptomatic patients ( two of each: G1 , G2 and G3 ) were isolated using density gradient as described above . A total of 2×106 PBMC were culture in the presence of anti-CD28 ( 1 µg/ml ) and anti-CD49d ( 1 µg/ml ) and one of the following conditions: medium alone , 10 µg/ml of K1 peptide or 3 . 7 µg/ml of Staphylococcal enterotoxin B ( SEB ) . Cultures were incubated for 3 hours at 37°C with 5% of CO2 , followed by an additional 6 hours of incubation in the presence of Brefeldin A 10 µg/ml ( BD Pharmingen ) . For degranulation assays , anti-CD107a and CD107b FITC ( clones H4A3 and H4B4 , respectively ) were added immediately following stimulation . For surface staining , antibodies for CD3-Pacific Blue ( UCHT1 ) , CD4-PeCy5 . 5 ( SK3 ) , CD8-APCH7 ( SK1 ) and K1 PE tetramer were used . PBMC were washed once and then fixed/permeated using Cytofix/Cytoperm ( BD Bioscience ) . Cells were washed twice with Perm/Wash 1× ( BD Bioscience ) , stained with 10 µl anti-IFN-γ PE-Cy7 ( clone B27 ) , rewashed once and re-suspended in FACs Flow ( BD Bioscience ) . Population was gated according viability and CD3 expression . Expression of CD107 and production of IFN-γ was based on the K1 tetramer positive CD4+/CD8+ cells . At least 1×103 tetramer positive cells were acquired and analyzed in a FACS Aria with FACSDiva software ( BD Bioscience ) . Cardiac tissue from a chronic chagasic patient biopsy was used for immunochemistry . This specimen was obtained from a 47 year old male who was diagnosed with cardiac failure class III ( NYHA classification ) and underwent a cardiac transplant . Formalin-fixed and paraffin-embedded cardiac biopsy tissue was cut , deparaffinized in xylene and rehydrated with alcohol . Antigen retrieval was done heating the tissue in the presence of EDTA buffer pH 9 . 0 . Slides were stained with hematoxylin/eosin to evaluate cellular infiltration and presence of parasites . Immunohistology was carried out with anti-human CD4 ( clone 1F6 , Vector Laboratories , Burlingame , CA , USA ) and CD8 ( C8/144B , DakoCytomation , Carpinteria , CA , USA ) antibodies . After blocking endogenous enzymes , antibodies were revealed with EnVision™ G|2 Doublestain System kit ( DakoCytomation ) using peroxidase/DAB+ Chromogen for CD8 and then alkaline phosphatase/Permanent Red Chromogen for CD4 . Slides were evaluated in a light microscope ( 40–100× objective magnification ) where CD8+ cells yielded a brown-color and CD4+ a red-color end product; DP T cells showed a red-brown color . Descriptive statistics ( mean , standard deviation and percentages ) was used to describe the populations and to present the flow cytometry data . Non-parametric analysis was carried out ( Statistix 8 . 0 software ) for groups comparisons by Kruskal Wallis ( K-W ) test followed by Dunn post hoc tests . Comparison of two groups was done by Mann-Whitney U test ( M-W ) . Significance was considered a p value<0 . 05 .
Cell frequency between chronic chagasic patients ( CP ) and healthy controls ( HC ) matched by age and gender were compared . The average percentage of total circulating DP T cells was higher ( p = 0 . 0017 ) in CP ( X = 2 . 1%±0 . 9 ) compared with HC group ( 1 . 1±0 . 5 ) ( Figure 1B ) . Representative flow cytometry dot plots and gating strategy are shown in Figure 1A . To determine if this difference was attributed to the chagasic patients immune response and not to the cardiac damage or its pathological consequences , DP T cells percentages from CP were compared with those from donors with non-chagasic cardiomyopathy ( NCC ) ( Figure 1A and 1B ) . Likewise , DP T cells frequency from CP was higher ( p = 0 . 034 ) compared with NCC group ( X = 1 . 2±0 . 4 ) . For the following analysis , DP T cells were divided according to their phenotype into CD4high/CD8low and CD4low/CD8high . The frequency of CD4high/CD8low T cell was higher ( p = 0 . 0058 ) in CP ( X = 1 . 61%±0 . 87 ) than in HC ( 0 . 88±0 . 56 ) and NCC ( 0 . 87±0 . 41 ) donors ( Figure 1C ) . Regarding to CD4low/CD8high T cell , significant differences were only observed between CP and HC ( p = 0 . 015 ) frequencies ( Figure 1A and 1C ) . To define the activation status of DP T cells in chronic Chagas patients , CD38 and HLA-DR surface markers were analyzed . Since , it was previously reported that CD4high/CD8low and CD4low/CD8high T cells differed in the expression of several surface markers , phenotypic analysis was done separately [1]–[4] , [10] . The percentage of DP T cells expressing HLA-DR was three times higher in CP in both CD4high/CD8low ( p = 0 . 0031 ) and CD4low/CD8high ( p = 0 . 01 ) populations than in the two control groups . No differences were observed between HC and NCC control groups ( Figure 2B ) . Representative flow cytometry density plots and percentages of HLA-DR positive DP T cells are shown in Figure 2A and Figure 2B , respectively . Analysis of CD38 in DP T cells showed that CD4high/CD8low subset had increased ( p = 0 . 002 ) percentage of cell expressing this marker in CP ( X = 38 . 9%±22 . 0 ) compared with NCC ( 9 . 6±5 . 3 ) , and not different with HC ( 20 . 6±10 . 6 ) . In contrast , the frequency of CD4low/CD8high expressing CD38 was higher in CP ( X = 30 . 0%±10 . 5 ) ( p = 0 . 0001 ) when compared with both HC ( 12 . 6±7 . 7 ) and NCC ( 11 . 0±10 . 5 ) . When co-expression of both activation markers ( CD38 and HLA-DR ) was analyzed , CP doubled the percentage of activated cells compared to HC and NCC donors in both CD4high/CD8low ( p = 0 . 009 ) and CD4low/CD8high T cells ( p = 0 . 001 ) ( Figure 2A and 2C ) . There were no differences when the analysis by clinical status was done . Due to the similarity of both subsets of DP T cells ( Table S1 ) , data is presented on the whole population in subsequent analyses . To assess the cytotoxic potential of DP T cells , intracellular perforin was measured [10]–[11] . Increased ( p = 0 . 002 ) percentages of cells containing perforin in CP ( 9 . 9±4 . 8 ) were found when compared with HC ( 3 . 3±3 . 2 ) and NCC ( 3 . 3±2 . 9 ) donors . Representative flow cytometry dot plots and percentage of perforin positive cells are shown in Figures 3A and 3B , respectively . No difference in perforin expression was found ( p = 0 . 29 ) between asymptomatic ( 9 . 9±3 . 1 ) and symptomatic ( 9 . 9±5 . 7 ) chagasic patients . Next , the antigen specificity of DP T cells was determined . To do so , the frequency of HLA-A*0201/peptide recognition was assessed using epitopes from T . cruzi and influenza virus , denominated K1 ( Figure 4A ) and MP-Flu ( Figure 4B ) , respectively [25] . We found that both asymptomatic ( X = 3 . 0%±1 . 9 ) and symptomatic ( 4 . 9±3 . 6 ) CP had higher percentages ( p = 0 . 0006 ) of circulating DP T cells specific for the K1 cytotoxic epitope than HC donors ( 0 . 6±0 . 4 ) . There was no difference according to the disease stage ( p = 0 . 267 ) ( Figure 4C and Table S2 ) . The percentage of K1-specific DP T cells in the Chagasic donors was in average 27 times higher ( p = 0 . 0005 ) than the mono-CD8+ K1-specific ones ( X = 4 . 0±2 . 9 versus X = 0 . 17±0 . 08 , respectively ) , Table S2 . Representative flow cytometry dot plots and percentage of K1 specific DP T cells are shown in Figure 4A and Figure 4C , respectively . Regarding MP-Flu response , asymptomatic ( 3 . 9±1 . 5 ) , symptomatic ( 2 . 9±2 . 0 ) and HC ( 3 . 6±2 . 0 ) donors had similar percentages of specific DP T cells ( p = 0 . 39 ) for this viral epitope . Representative flow cytometry dot plots and percentage of MP-Flu specific DP T cells are shown in Figures 4B and 4D , respectively . Production of IFN-γ and surface expression CD107 a/b , as marker of degranulation , were analyzed in K1 tetramer-positive DP T cells . The percentage of IFN-γ positive cells in medium alone was similar between asymptomatic ( n = 5 ) ( 0 . 48%±0 . 45 ) and symptomatic patients ( n = 6 ) ( 0 . 97%±0 . 97 ) ( p = 0 . 52 ) . Likewise , in the presence of K1 peptide , asymptomatic patients ( 1 . 87%±1 . 83 ) showed a no significant increase in the percentage of IFN-γ positive cells when compared with the symptomatic group ( 0 . 56%±0 . 43 ) ( p = 0 . 26 ) . However , after polyclonal stimulation ( SEB ) , this percentage was significantly higher in the asymptomatic donors ( 14 . 6%±10 . 3 versus 5 . 55%±4 . 98; p = 0 . 049 ) . Representative flow cytometry dot plots and percentage of IFN-γ positive cells are shown in Figures 5A and 5B , respectively . Furthermore , degranulation in K1 tetramer-positive DP T cells was significantly higher in than symptomatic donors in the presence of K1 peptide ( 21 . 50%±13 . 38 versus 66 . 25%±30 . 78; p = 0 . 0455 ) and SEB ( 24 . 74%±21 . 74 versus 74 . 20%±31 . 59; p = 0 . 03 ) ; this seemed to be also the trend for cell cultured in medium alone ( 16 . 58%±17 . 52 versus 67 . 0%±32 . 93; p = 0 . 052 ) , in spite that no significant difference between the asymptomatic and symptomatic groups was found . Representative flow cytometry dot plots and percentage of CD107a/b positive cells are shown in Figures 5A and 5C , respectively . Cardiac tissue from a chronic chagasic patient was analyzed in order to identify the presence of CD4+/CD8+ cells . The immunohistology analysis showed that myocardiocytes presented reparative nuclear changes such as bigger size , hyperchromatic and visible nucleoli . Moderate patchy myocardial infiltration mostly conformed by lymphocytes , some plasmocytes , macrophages and scarce eosinophils was also observed . The number of infiltrating lymphocytes was 10 or 12 per high power field , and they were mostly CD8+ cells ( near 95% , Figure 6A and 6B ) and some CD4+ cells ( Figure 6B ) . Double CD4+/CD8+ cells were found in the inflammatory infiltrate of the cardiac tissue in a frequency lower than 2% , as shown in Figure 6C .
Circulating CD4+/CD8+ double positive ( DP ) T cells represent between 1–3% of the total T lymphocytes population [1] . However , previous evidence has suggested that this frequency can increase during several inflammatory diseases [2]–[8] . In this study we demonstrated that the percentage of peripheral DP T cells was higher in chronic chagasic patients compared with control donors , including individuals with non-chagasic cardiomyopathy . This finding differs from previous studies in HVC and HIV infected patients in which virus infected and control donors did not have differences in DP T cells frequencies on peripheral blood [10] , [26] . To the best of our knowledge , this research is the first report of an augmented percentage of DP T cell in human patients with a chronic parasitic infection . Previous characterization of DP T cells indicates that this lymphocyte subpopulation is constituted mainly by terminally differentiated memory cells . A recent study showed that chronic chagasic patients had higher frequencies of CD4+ effectors memory T cells ( TEM ) and CD8+ central memory T cells ( TCM ) when compared with uninfected individuals [27] . Interestingly , in healthy donors CD4high/CD8low T cells were described as being TEM phenotype , meanwhile CD4low/CD8high were mainly TCM [10] . It will be interesting to determine if some of those CD4+ TEM and CD8+ TCM described in chagasic patients could include some DP T cells [27] . Similarly to DP T cells described in other human chronic infectious diseases with antigen persistence [10] , [26] , [28] , [29] , we found that the expression of activation markers in these cells were increased in the chagasic donors . Consistently , some studies in T . cruzi infected donors have shown that their T cells ( CD3+ , CD3+/CD4+ and CD3+/CD8+ ) tended to be more activated than cells from uninfected donors [30]–[32] . Regarding the source of the peripheral DP T cells , experimental data supports that they might either escape from the thymus [33] or represents over-stimulated mono-positive CD4+ or CD8+ T cells [34] , [35] . Interestingly , some studies have shown severe CD4+CD8+ thymocytes depletion coexisting with 16-fold increase of these cells in the periphery ( subcutaneous lymph node ) after T . cruzi acute infection in mice [21] , [36] . These findings support the “thymus escape” theory . However , expression of the “second” marker in mono-positive T lymphocytes as a consequence of antigenic over-stimulation seems also plausible in our study , given the consistent activation exhibited by the DP T cells [34] . More studies are needed to determine the origin of DP T cells in chagasic patients . Perforin-mediated cytotoxicity has proved to be very important in the protection and pathogenesis of some parasitic infection , including cerebral malaria [37] and toxoplasmosis [38] . In animal models , there is evidence that implicates perforin expression with T . cruzi elimination during the acute disease [32] , [37] . However , perforin has also been involved in tissue damage during chronic Chagas disease [39]–[41] . After T . cruzi infection , perforin- knockout mice had an increased parasite burden and increased number of IFN-γ producing T cells infiltrating their hearts . However , these perforin-deficient animals showed more preserved cardiac tissue and less electric conduction abnormalities than normal littermates [39] . Even more , it has been suggested that human cardiac damage is directly related to an increase in the ratio of perforin-positive/total inflammatory cells in heart tissue [40] . Another remarkable result in this study is that DP T cells can recognized a T . cruzi derived class I epitope during chronic infection . The percentage of DP T cells specific for the K1 peptide was exceptionally high ( 1 . 7% to 11 . 5% ) compared with previous reports of K1 specificity for mono-CD8+ T lymphocytes ( 0 . 09% to 0 . 34% ) in a similar chronic chagasic population [25] . Likewise , in human viral infections ( HCV and HIV ) upon antigen exposure , DP T cells displayed a much higher frequency of cell-single cytokine production than CD8+ and CD4+ T cells [10] , [26] . Analysis of class I antigen recognition suggests that DP T cells in chagasic patients were parasite driven . Probably , as these peripheral cells are T . cruzi antigen-specific and have memory phenotype , they could migrate to the tissue where parasites persist and contribute to T . cruzi induced pathology . In fact , in situ cytotoxic lymphocytes ( perforin or granzyme A positive cells ) have been described in human heart [41] and gastrointestinal tract [42] of patients with T . cruzi induced tissue damage . When activation markers , perforin and K1-recognition on DP T cells were compared in chagasic patients according to their clinical status ( asymptomatic versus symptomatic patients ) , no differences were found . Nevertheless , it was notable that some symptomatic donors had higher percentages of K1 T . cruzi specific cells than asymptomatic ones , while percentages of recognitions for influenza virus epitope were similar . We also found that K1 specific DP T cells from symptomatic group displayed increased degranulation activity even with medium alone . However , very low percentages of these K1 tetramer specific DP T cells produced IFN-γ after K1 peptide stimulation , as similarly described for CD8+ T cells in chronic chagasic patients [25] . This was not the case for the production of IFN-γ after polyclonal stimulation , which was significantly augmented especially in the asymptomatic patients . Interestingly , K1 specific DP T cells that produce IFN-γ did not display degranulating phenotype , indicating that DP T population is functionally heterogeneous and complex . In summary , K1 specific cells from asymptomatic donors had higher capacity of IFN-γ secretion than cells from symptomatic donors which have greater cytotoxic potential . In our study , we found a higher expression of perforin on peripheral DP T cells in the chagasic patients accompanied with an increased degranulation activity in the symptomatic ones . Also , it was demonstrated that DP T cells can migrated to the cardiac tissue . If the blood phenotype of these cells is maintained by the infiltrating ones , it might be possible to associate DP T cells with cardiac damage . A similar mechanism was suggested for HCV infected humans where DP T cells were found to infiltrate the liver [10] . Progressive loss of cytokines secretion is a characteristic of CD8+ T cells exhaustion , a phenomenon related to antigen persistence during chronic infections [43] . Indeed , IFN-γ that is associated with protection against T . cruzi infection [44] , is one of the last effector activities to be extinguished in this process [43] . So , our data suggest that K1 specific DP T cells , mainly from symptomatic donors , should be on the pathway of exhaustion , while they keep their cytotoxic potential . Lastly , as TNFα production has been associated with cardiac damage in Chagas disease [45] , it will be of interest to test the production of TNFα on T . cruzi specific DP T cells . | Chagas disease , produced by the blood parasite Trypanosoma cruzi , is considered a public health problem in Central and South America . Non sterile immunity can be achieved after acute infection . Parasite persistence can induce tissue damage in nearly 20% to 30% of chronically infected individuals . Indeed , chagasic cardiomyopathy is one of the consequences of the chronic infection . Antigen persistence and dysfunctional cellular immune response have been implicated in T . cruzi pathogenesis . Here , a higher frequency of circulating CD4+/CD8+ double positive T cells in chronic chagasic patients is reported as compared with non infected donors , including those with a non-chagasic cardiomyopathy . This cell subset also expressed more activation markers and stored more intracellular perforin . We have previously reported that CD8+ T cells from T . cruzi infected donors recognized the HLA-A*0201 restricted K1-peptide derived from the KMP-11 protein . Here , double positive T cells displayed higher percentages of recognition for the K1 peptide than single CD8+ T cells . These cells produce little IFN-γ , but display degranulation activity that was increased in the symptomatic group . Finally , double positive T cells can be localized in the heart tissue from a chronic chagasic donor . | [
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] | 2011 | Increased CD4+/CD8+ Double-Positive T Cells in Chronic Chagasic Patients |
Genotype-to-phenotype maps exhibit complexity . This genetic complexity is mentioned frequently in the literature , but a consistent and quantitative definition is lacking . Here , we derive such a definition and investigate its consequences for model genetic systems . The definition equates genetic complexity with a surplus of genotypic diversity over phenotypic diversity . Applying this definition to ensembles of Boolean network models , we found that the in-degree distribution and the number of periodic attractors produced determine the relative complexity of different topology classes . We found evidence that networks that are difficult to control , or that exhibit a hierarchical structure , are genetically complex . We analyzed the complexity of the cell cycle network of Sacchoromyces cerevisiae and pinpointed genes and interactions that are most important for its high genetic complexity . The rigorous definition of genetic complexity is a tool for unraveling the structure and properties of genotype-to-phenotype maps by enabling the quantitative comparison of the relative complexities of different genetic systems . The definition also allows the identification of specific network elements and subnetworks that have the greatest effects on genetic complexity . Moreover , it suggests ways to engineer biological systems with desired genetic properties .
Biologists currently enjoy unprecedented access to genotype and phenotype data , and as the price of DNA sequencing continues to fall and high-throughput automated experimental techniques continue to develop , the amount of data will increase exponentially . The challenge that arises is to extract as much useful information from these data as possible . Molecular , cellular , and behavioral phenotypes are amenable to experimental measurement , but connections to relevant features of the genotype are often out of reach . Likewise , DNA sequencing provides quick and inexpensive access to vast amounts of genotype data , but using the genetic sequence of an organism to predict its phenotype remains a broadly unfulfilled goal . The genotype-to-phenotype map ( GPM ) encodes the relationship between genetic variations and phenotypes of interest . It is a mapping which assigns to genotypes their corresponding phenotypes . An understanding of GPMs is desirable both to facilitate the prediction of the phenotypic results of genetic perturbations and to identify underlying genotypic features on the basis of phenotypic measurements . The elucidation of GPMs is therefore of primary interest to contemporary genetics . The properties and construction of GPMs have been the subject of recent studies ( see [1]–[3] for review ) . Another property of GPMs often invoked in the literature is that of ‘genetic complexity’ . However , this term lacks a clear and consistent meaning and has variously been taken to mean genetic trait influence that is non-Mendelian , multigenic , additive or epistatic ( in the general sense of any genetic interaction ) . These uses clearly differ from one another and can be contradictory . Furthermore , the lack of a quantitative definition prevents the meaningful comparison of the complexities of multiple genetic systems . The ability to compare the genetic complexity of multiple systems enables the identification of those features and mechanisms that give rise to complexity . Once the relevant features have been identified , the complexity of systems can be controlled . On the genotype side , systems can be engineered to produce greater phenotype resolution and less complexity . On the phenotype side , experimental design can be optimized to maximize the amount of information gained via measurement . A thorough understanding of the genetic complexity of genetic systems is necessary for an understanding of such systems on the whole , and the first step towards this goal is the precise definition of complexity . Here , we derive and investigate a rigorous quantitative definition of the genetic complexity of GPMs .
Dynamic Boolean network models ( “Boolean networks” , henceforth ) have long been used to model biological networks [5]–[7] . Boolean networks consist of a set of nodes which , at any moment of time , can either be ‘on’ or ‘off’ . For example , the formalism is often applied to genetic networks , where the two states correspond to the gene being expressed or not expressed . Although this is a great simplification of the actual biological state of a genetic network and much dynamical information is sacrificed in this formalism , Boolean networks have proven to be a surprisingly fruitful class of models for capturing the large-scale properties and behaviors of genetic networks ( see [8] for a review and further references ) . Boolean networks are an ideal arena in which to apply the definition of genetic complexity , as they provide models of genetic systems wherein all relevant quantities are well-defined and discrete . In the context of Boolean network models , a genotype is specified by selecting an update function for each node , which determines how the node updates as a function of the network state . Once a genotype is specified , any initial state will flow into an attractor state , which corresponds to a phenotype . The attractor can either be a single state which updates to itself ( a fixed attractor ) or a series of states through which the network continuously cycles ( a periodic attractor ) . The Boolean network framework allows also for asynchronous update rules for different nodes . In this work , we deal only with synchronous Boolean networks . Details on our employment of Boolean networks are given in the Methods section . As with any mapping , a GPM is not fully specified until the domain on which the mapping acts is delineated . In the case of a GPM , this consists of a specification of the genotypes present in the system . In the abstract arena of Boolean networks , we could conceivably choose any arbitrary set of genotypes to form genotype libraries . However , to identify the effects of some property of the networks on the complexity , we should compare genotype libraries ( in which each genotype takes the form of a truth table specifying a Boolean network ) that differ only in the property of interest , and that otherwise include all relevant genotypes . In this section , we compare the complexities of network libraries as a function of order ( number of nodes in the networks ) , size ( number of edges in the networks ) and topology . In all cases , the library of truth tables is generated by selecting the subset of all possible truth tables with the desired number of edges and topology from the set of all truth tables with a given number of nodes . The determination of the edge structure of a network from its truth table is described in the Methods section . Having studied the complexity of libraries of generic Boolean networks , we examined the complexity of a specific biological system . The cell cycle network ( CCN ) of S . cerevisiae has been studied extensively as a model network and is well understood . Furthermore , there exists for the CCN a Boolean network formulation [16] , allowing the straightforward computation of its genetic complexity . The CCN Boolean network formulation of Li et al . [16] uses a threshold network framework . The network is shown in Figure 4 and the details of the threshold network formalism are discussed in the Methods section . Genetic complexity characterizes a library of networks , not a single network , so in order to analyze the complexity of the CCN we must first construct a library which the yeast CCN determines . In the following analysis , for any given threshold network , its corresponding library consists of all threshold networks that have the same topology as the base network and where each node can exist in one of three states: 1 ) the wild type allele , where the update rule for the node is given by its inputs as defined by Li et al . ; 2 ) the null allele , where the node always updates to ‘off’; and 3 ) a constitutively active allele , where the node always updates to ‘on’ . This choice of library is natural , given its biological and experimental relevance , and its symmetry between null and constitutively active states . In this section , when we mention the complexity of a network , we are referring to the complexity of the library generated from the network in the manner described above . For the yeast CCN , which has 11 nodes , this leads to a library of 3∧11 = 177147 genotypes . We found that for the library generated by the yeast CCN , when all 177147 genotypes were allowed to update from all 2048 initial states , no periodic attractors were produced . Because all fixed attractors were guaranteed to be produced by our construction of the CCN library , the lack of periodic attractors indicates that the complexity of the yeast CCN is maximal . It might seem surprising that a model of a cyclic process gives rise to no periodic attractors . However , this is consistent within the framework of the model , where the G1 phase of the cell cycle is a steady state of the system and initiation of the cell cycle corresponds to an external perturbation . This reflects the biological reality that , at any given time , most cells are not actively progressing through the cell cycle . We then systematically perturbed a number of features of the yeast CCN in order to identify which aspects of the network were most crucial to maintaining its maximal complexity . First , we calculated the complexity of the 29 networks created by removing a single edge from the network . We found two edges which when removed resulted in a network with lower complexity than the CCN . One of these edges is a positive edge from Clb1 , 2 to Cdc20 , and the other is a negative edge from Clb5 , 6 to Sic1 . Both edges relay information from B-type cyclins , which govern the transition from the G2 phase to the M phase , suggesting that this process contributes significantly to the complexity of the CCN . It is known that the G2/M transition is a key checkpoint of the cell cycle , and that the B-type cyclins play a crucial role in this process [17] , [18] . We next systematically perturbed the inputs to each node . For each node , we considered all possible reassignments of its inputs , holding all other features of the network fixed . We then calculated how often the complexity is decreased by perturbing the inputs to each node . We found that there is a clear separation between nodes whose inputs are more or less important to maintaining maximal complexity , as shown in Table 3 . The core set of nodes that have the greatest impact on the complexity of the network are highlighted in Figure 4 . We found that the nodes whose inputs are more important for complexity are precisely those nodes with out-degree greater than two . This can be understood intuitively , as those nodes with greater out-degree play a larger role in determining the states of other nodes in the network . Perturbing their inputs will therefore have a larger effect on the dynamics of the network as a whole . We saw evidence in the previous section that networks with more loops tend to give rise to more periodic attractors . Investigations of the CCN also support this conclusion . This can be seen in two ways . In one analysis , we have added all possible single edges to the network and calculated the complexity . When adding an edge , we can also compute how many loops are created , and of what size . We found that those edge additions which lead to the creation of several small loops or very many large loops are more likely to produce periodic attractors ( and thereby decrease the complexity ) than a random edge addition . We can also make a connection between the large-scale loop structure and information flow in the CCN and the number of periodic attractors produced . The dominant modes of information flow in the CCN are as shown in Figure S1 . The flow of information reflects that fact that the majority of interactions present in the CCN relay information in the pattern indicated . 86% of the edges in the network account for information flowing as indicated . Initial input flows from the top of the network , down either side , and up into the center . There are few edges that connect the bottom of the network to the top , thereby completing the loops in the large-scale information flow . We have found that the addition of edges from the bottom nodes to the top nodes is more likely to decrease complexity than a random edge addition , once again confirming that topologies with more loop structure give rise to lower GPM complexity .
We have formulated a rigorous , quantitative definition of the genetic complexity of a GPM . This definition provides a tool to unravel the properties of GPMs by providing a consistent means of comparing the relative complexities of genetic networks and identifying features of networks that lead to greater or lesser complexity . Genetic complexity is a surplus of genotypic diversity for a given level of phenotypic diversity . Conversely , it is a dearth of phenotypic diversity . It is this dearth that results in the intellectual sensation of surprise when a complex phenotype arises . In biomedicine , such surprises are often unwelcome , for example when the complex phenotype is an adverse reaction to a drug or treatment . With an increased understanding of the quantitative basis of genetic complexity , such surprises can be more predictable , detrimental surprises can be avoided , and the likelihood of salubrious surprises can be increased . Potential applications of the rigorous definition of complexity include evaluating different strategies for collecting data and designing experiments , evaluating the usefulness of statistical methods to determine relevant genes in genome-wide association studies ( GWAS ) or alternatives to GWAS , and investigating how genetic complexity arises evolutionarily . We found that the genetic complexity of libraries of Boolean networks increases monotonically as a function of size and order , fulfilling a basic expectation of genetic complexity . We also found that the key determinants of the relative complexity of different topologies are the in-degree distribution and the number of periodic attractors produced by the class ( which is qualitatively related to the number of loops in the topology ) . The central role played by the in-degree distribution in determining the genetic complexity also suggests that those topology classes that are more difficult to control are additionally more genetically complex . We found that the cell-cycle network of yeast has maximal genetic complexity . In [16] , it was shown that the CCN demonstrates a substantial robustness to perturbation . This result therefore also suggests a connection between robustness and genetic complexity . A connection between complexity and robustness was also identified when considering networks with hierarchical structure . The precise nature of the relationship between robustness and complexity should be investigated further . By perturbing the CCN , we identified a core group of nodes which are most responsible for the maximal complexity , and found that interactions involving B-type cyclins make a crucial contribution . Additionally , we reinforced the picture that more loops in a topology leads to lower complexity , in agreement with the association of hierarchical and scale-free structures with complexity . The definition of complexity should continue to produce other such insights , when applied both to other computational models and to experimental results . The definition allows the identification of those features of genetic interaction networks that lead to more or less complexity and thus leads to a greater understanding of the structure of GPMs in general . Such insights can provide guidance to engineer genetic systems of desired complexity and to design experiments optimally so as to maximize the information gained by performing measurements .
In the Boolean network framework , the interacting entities ( genes , proteins , complexes , etc . ) are represented as binary nodes which can be either active ( ‘1’ ) or inactive ( ‘0’ ) . The current state of the network is then completely specified by stating whether each node is 1 or 0 . The network evolves dynamically in discrete time steps . The update rule at time t for each node depends on the states of all nodes at time t , ( 2 ) where ( t ) is the state of node i at time t . The function f can be represented as a truth table ( see Figure S2 ) . In the context of Boolean representations of genetic interaction networks , specification of a truth table for a node corresponds to specifying how a gene interacts with all other genes . We therefore equate specifying a truth table for a node with specifying an allele for the corresponding gene . In order to fully specify a genotype , then , we must assign a truth table to each node . Because there is a finite number of states available to a Boolean network of a given size , and because the update rules of the network are fully deterministic , if allowed to evolve in time a Boolean network will necessarily reach an attractor . The attractor can consist of a single state in which the network is forever stuck ( a fixed attractor ) , or it can consist of a series of states that the network continuously visits in the same order ( a periodic attractor ) . For a network with given genotype and initial state , we associate the resulting attractor with a phenotype . With definitions of genotype and phenotype in hand , we construct a library of Boolean networks according to some unifying principle . We then allow each network in this library to evolve from each possible initial state and record the resulting phenotype . We count the number of unique phenotypes reached and calculate the complexity according to our definition Equation 1 . These computations were carried out on a desktop PC , using programs written in C++ . A network can be characterized by its order ( number of nodes ) , size ( number of edges ) and topology ( how those edges are arranged ) . For a given genotype , the edges of the network can be worked out from the set of truth tables . An edge exists pointing from node j to node i if there exists at least one state such that the update result for i will change if the bit for node j is flipped . Symbolically , an edge from j to i exists if , for some set of , ( 3 ) where addition is done modulo 2 . Another way to say this is that an edge exists from node j to node i if there is any one case where the update rule of i depends on the state of node j . An example of determining the edge structure from a truth table is given in Figure S2 . Our definition of a topology class is then all genotypes ( all sets of truth tables ) of order n with precisely the same set of edges . A set of nodes and edges constitutes a topology . Two ways to characterize a topology are by its in-degree distribution and by its out-degree distribution . For an order n network , the in-degree distribution is a set of n numbers describing how many incoming edges each node has . Likewise , the out-degree distribution is a set of n numbers describing how many outgoing edges each node has . In order to prove that the second level of structure of the genetic complexity of topology classes is determined by the number of periodic attractors produced , we relied on two facts: We prove these two facts now . First , we show that all topology classes realize all fixed point attractors . Consider any network belonging to a given topology class . This network is fully described by its truth table . For an n-node network , the truth table will have 2n rows and n columns . Each column is the update rule of the nth node , specifying how that node will update for each of the 2n possible states of the network . If we flip the bits of the nth column of the truth table , the nth node will still have inputs from the same set of nodes . Its dependence on these nodes will simply be reversed . Thus , we can flip the bits of any column of the truth table and produce another network in the same topology class . Suppose that we are given any single network representing any topology class . We can construct a member of the same topology class that will realize any state of the network , S = ( S1 , S2 , … Sn ) , as a fixed point attractor , as follows . From the truth table , ( S1 , S2 , … Sn ) updates to the state ( S′1 , S′2 , … S′n ) . In order for S to be a fixed point attractor , we must find a truth table in the same topology class such that Si = S′i for all i . Such a truth table can be generated by flipping the bits for each column i in which Si≠S′i . As shown above , the resulting network will reside in the same topology class , and the state S will be a fixed point attractor of the network . Thus , every topology class will realize all fixed point attractors . Next , we prove that any two topology classes with the same in-degree distribution have the same genotypic diversity . We consider two topology classes with order n and the same in-degree distribution . The number of genotypes in either library is equal to the product of the number of truth tables with the appropriate set of edges for each node . If a given node has in-degree j , there is a one-to-one mapping between the sets of all truth tables containing edges from any set of j nodes that can be constructed by permuting the node labels . Thus , the number of truth tables accessible to each node depends only on the in-degree of the node and not on the identities of the nodes from which the incoming edges are coming . Therefore , for any two topology classes with the same in-degree distribution , the number of genotypes |G| in both classes will be the product of the same n numbers . In order to show that any two topology classes with the same in-degree distribution also have the same genotypic diversity , mn , we prove that there are no commutative alleles and , therefore , that mn = |G| . To prove this , it suffices to show that for any two non-identical Boolean-network alleles , there exists a genetic background for which those two alleles give rise to different phenotypes . Consider two alleles , A and a , of gene g . In the Boolean network framework , this means that there exists at least one state , s , for which A and a have different update rules . Consider state s in which the allele A updates to 1 and the allele a updates to 0 . The proof of the converse follows immediately . If gene g is 1 in state s , then according to the proof of point 2 above , we know there exists a genotype ( A1 , A2 , …A , …An ) in the topology class containing allele A for which state s is a fixed point . But then the genotype ( A1 , A2 , …a , …An ) , which is also a member of the topology class , does not realize s as a fixed point , because gene g will update to 0 in this genotype . Therefore , there exists a genetic background ( A1 , A2 , …An ) in which A and a give different phenotypes , and A and a are not functionally equivalent . The proof for the case where gene g is 0 in the state s is analogous , with the roles of A and a switched . Thus , all alleles are functionally unique and mn = |G| is the same for all topology classes with the same in-degree distribution . The CCN as constructed by Li et al . utilizes the threshold network formalism . In this formalism , rather than represent update rules by a set of truth tables , which become unwieldy for a large number of nodes , the update rules are specified by a set of arrows . Each arrow points from one node to another , and the arrows must be either positive or negative ( represented as green and red arrows , respectively ) . At each time step , an arrow from node A to node B is active only if node A is on . The update rule for B is determined by looking at all active inputs to B . If more active inputs are positive , then node B turns on . If more active inputs are negative , node B turns off . If there are equal numbers of active positive and negative inputs , then B either remains in its current state , or turns off if it is self-regulating ( represented by an arrow pointing from a node to itself ) . These update rules are summarized mathematically as ( 4 ) where is 1 if there is a positive edge from j to i , −1 if there is a negative edge from j to i , and zero if there is no edge between j and i . For more flexibility , one can also allow the weights to take on values other than 1 and −1 , although we will not consider such cases in this paper . A network given in the threshold formalism can always be converted to one in the truth table formalism . One potential stumbling block involves a small difference in topological notation between our earlier truth table framework and the threshold network framework . In the threshold network formalism , a self-regulation is represented by an arrow pointing from a node to itself . However , when translated into the truth table formalism , such a node will actually not have an edge pointing from it to itself . Nodes in the threshold network formalism without self-regulation will have edges pointing from them to themselves in the truth table formalism , because when their inputs sum to zero they remain in their current state; thus , their update rule depends on their own state . As mentioned in the Results section , for networks in the threshold formalism , we construct libraries of networks by allowing each node one of three possibilities: Since there are 11 nodes in the CCN , there are 3∧11 = 177147 genotypes in the CCN library . For each of these genotypes , we cycle through all possible 2048 initial states and find the resulting attractor state . We count the number of unique attractors as the number of phenotypes and calculate the complexity C . Once again , the computations are carried out on a desktop PC with programs written in C++ . Note that , due to options 2 ) and 3 ) above , we are guaranteed to realize all 2048 fixed states , because for each state there exists a network that updates to that state regardless of the current state . For the CCN , only the 2048 fixed attractors are realized , leading to a maximal complexity of 85 . 54 . For perturbations of the CCN , the calculation is carried out in an analogous manner . We start with the perturbed threshold network , construct the library as above , and count the number of unique phenotypes that result . The 2048 fixed states are always guaranteed to appear and the complexity is fully determined by the number of periodic attractors that are realized . | ‘Genetic complexity’ is an often-discussed property of genotype-to-phenotype maps , but the term is used vaguely and inconsistently in the literature . We derived a definition of genetic complexity that assigns to every genotype-to-phenotype map a unique quantitative measure of its genetic complexity . This definition allows the meaningful comparison of complexity across systems , and also allows the identification of genetic-network features that contribute most significantly to genetic complexity . We applied this definition to ensembles of Boolean networks . Because all relevant quantities are precisely defined , Boolean networks provide an ideal arena in which to study genetic complexity systematically . Using this approach , we identified relationships between topological properties of networks and their genetic complexity . We also identified features specific to the cell-cycle network of yeast that impart its genetic complexity . | [
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] | 2012 | Quantifying and Analyzing the Network Basis of Genetic Complexity |
We recently discovered an inherited cancer syndrome caused by BRCA1-Associated Protein 1 ( BAP1 ) germline mutations , with high incidence of mesothelioma , uveal melanoma and other cancers and very high penetrance by age 55 . To identify families with the BAP1 cancer syndrome , we screened patients with family histories of multiple mesotheliomas and melanomas and/or multiple cancers . We identified four families that shared an identical BAP1 mutation: they lived across the US and did not appear to be related . By combining family histories , molecular genetics , and genealogical approaches , we uncovered a BAP1 cancer syndrome kindred of ~80 , 000 descendants with a core of 106 individuals , whose members descend from a couple born in Germany in the early 1700s who immigrated to North America . Their descendants spread throughout the country with mutation carriers affected by multiple malignancies . Our data show that , once a proband is identified , extended analyses of these kindreds , using genomic and genealogical studies to identify the most recent common ancestor , allow investigators to uncover additional branches of the family that may carry BAP1 mutations . Using this knowledge , we have identified new branches of this family carrying BAP1 mutations . We have also implemented early-detection strategies that help identify cancers at early-stage , when they can be cured ( melanomas ) or are more susceptible to therapy ( MM and other malignancies ) .
Malignant mesothelioma ( MM ) is frequent ( up to 5% prevalence ) in individuals who are heavily exposed to asbestos and/or other mineral fibers [1] . Moreover , we discovered that the risk of developing MM is transmitted in an autosomal dominant fashion in certain Turkish families , in which over 50% of family members developed MM [2] . In subsequent studies in US families with high incidence of MM and of uveal melanoma ( UM ) and no apparent exposure to mineral fibers , we identified germline mutations in the BAP1 gene , as the major risk factor for MM and UM development [3] . Thereafter , we and others confirmed that germline BAP1 mutations are a common heritable factor that predispose to MM , UM , cutaneous melanoma ( CM ) , cholangiocarcinoma , renal cell carcinoma ( RCC ) , and basal cell carcinoma ( BCC ) [4–6] , and to benign atypical melanocytic lesions known as MBAITs [7 , 8] , and likely to several other malignancies including brain , breast , lung cancer , and sarcomas [9] , —recently grouped together into the “BAP1 cancer syndrome” [7] . Thus , similarly to germline TP53 mutations that cause the Li-Fraumeni syndrome [10] , germline BAP1 mutations are associated with a variety of cancers . There is , however , a preponderance of MMs and melanomas [7] . BAP1 is a deubiquitylase that associates in the nucleus with multi-protein complexes that regulate key cellular pathways , including transcription , DNA replication and the DNA damage response [9 , 11 , 12] . BAP1 tumor suppressor functions have been attributed to its ability to regulate gene transcription via ( i ) interaction to host cell factor-1 ( HCF1 ) , Ying Yang 1 ( YY1 ) , and E2F1 [13 , 14] , ( ii ) modulation of histone H2A ubiquitylation [15] , ( iii ) maintaining DNA integrity [11 , 16] and modulating DNA repair by homologous recombination [12 , 16] . All germline BAP1 mutations , identified so far , lead to inactive forms of BAP1 , lacking deubiquitylating activity or to truncated variants that lack the nuclear localization signal . Therefore , it appears that , to function as a tumor suppressor , BAP1 must maintain both nuclear localization and deubiquitylating activity [17] . All carriers of germline BAP1 mutations studied so far have developed at least one malignancy by age 55 and many developed multiple cancers [18] . Familial MMs in these individuals occur at a median age of 56 . 3 in either pleura or peritoneum ( frequency ratio: 1/1 ) , have a M:F ratio of 0 . 73:1 and are associated with prolonged survivals of 5–10 or more years; compared to a median age at diagnosis of 72 , a 86%:14% pleural/peritoneal ratio; a M:F ratio of 4:1 and a median survival of <1 year in sporadic MM [18] . Thus , MM patients carrying germline BAP1 mutations benefit from this information , and their relatives may benefit from screening programs for early cancer detection , when these malignancies can be cured by resection ( melanomas ) or are more susceptible to therapy ( MM and other cancers ) .
Twenty-two MM patients were recruited based on family histories suggestive of the BAP1 cancer syndrome and selected according to the inclusion criteria described in the Methods section . None of the individuals , who met the inclusion criteria , reported a history of asbestos exposure . Sequence analysis of DNA isolated from peripheral blood mononuclear cells of these patients revealed that 4/22 of these familial MM cases , carried germline BAP1 mutations . One patient with peritoneal MM carried a heterozygous BAP1 variant ( c . 1938T>A , p . Tyr646* ) in exon 15 , leading to a stop codon and a truncated BAP1 protein , predicted to be 646 amino acids long and lacking the nuclear localization signal . The other three MM patients with germline BAP1 mutations ( MARF11-III-1 , MARF18-III-1 , MARF40-III-1 ) carried an identical mutation ( c . 1717_1717delC , p . Leu573fs*3 , Fig 1A ) in exon 13 . MARF11-III-1 proband and family are from Maryland , MARF18-III-1 proband and family are from California , MARF40-III-1 proband and family are from Texas , and they were apparently unrelated . We previously found the same BAP1 germline deletion in another apparently unrelated patient from Texas , MARF2-IV-2 ( referred to as SP-002 in our previous study ) [3] . Based on these results , we concluded that either c . 1717_1717delC was a hotspot for “de novo” BAP1 mutations or these four families had a common ancestor and BAP1 mutation was transmitted across multiple generations . Sanger sequencing revealed that the four probands sharing the c . 1717_1717delC BAP1 mutation also shared a rare allele of a synonymous SNP ( rs71651686 , minor allele frequency = 0 . 0016 , according to NCBI dbSNP database ) in exon 11 , which is located 1770 bp upstream of the c . 1717_1717delC variant in exon 13 . Other than in the four probands , this allele was not found in any additional MM patient tested so far in our laboratory , including MM patients that were tested outside the current study . Eight individuals from the 1000 Genomes Project ( 1000G ) have this rare SNP; however , they do not have the BAP1 c . 1717_1717delC mutation . Moreover , the BAP1 c . 1717_1717delC mutation is not present in any of the three genome-wide/exome-sequencing variant databases ( 1000G+UK10K+ESP: which include a total of 8286 genomes surveyed ) . The rare allele of synonymous SNP rs71651686 is unlikely to have any functional impact , but since the probability for any given individual to carry both the rare allele of rs71651686 SNP and the c . 1717_1717delC variant was estimated to be less than 8 . 0x10-7 , their presence together in the four individuals provided an initial indication that they were shared by descent from a common ancestor . We investigated whether the mutation occurred “de novo” in separate unrelated family trees or whether it was inherited identical-by-descent ( IBD ) from a common ancestor . We genotyped these four MM patients sharing the c . 1717_1717delC BAP1 mutation and four unrelated healthy controls for 657 , 893 SNPs using the Illumina OmniExpress ( OE ) platform . We performed a population genetic and shared haplotype analysis of the data and we combined the SNP analysis with publicly available genotypes for 2141 samples from 19 worldwide population groups genotyped by 1000G [19] on the Illumina Omni 2 . 5M platform ( Omni2 . 5 ) . We analyzed the four probands and four controls , together with the 1000G data analysis , using principal component analysis ( PCA ) to estimate the ancestral populations of our samples [20] . From the PCA analysis , we found that the four probands clustered closest to 1000G populations with ancestry from Central Europe or Great Britain ( CEU , GBR; n = 205; S1 Fig ) . Next , we analyzed our samples for ‘cryptic relatedness’ , which is an unexpected relatedness between samples not known to be related based on family history [21] . We estimated relatedness between our samples and those from 1000G using a genome-wide IBD analysis [22 , 23] . The results of the IBD analysis identified measurable relatedness only between the four MM patients . The most closely related samples were MARF11-III-1 and MARF40-III-1 , which had a kinship coefficient of 0 . 0186 , suggesting relatedness approximately equal to that of second degree cousins ( S1 Table ) . We then examined the haplotype structure in these 8 samples around the BAP1 gene . We estimated phased haplotypes ( i . e , clusters of tightly linked alleles along a chromosome ) from our samples and those from the 1000G genotype data using the SHAPEIT2 [24] program . Analysis using BEAGLE [25] revealed that the only samples that shared significant haplotype segments ( LOD>3; LOD = base 10 log of the likelihood ratio ) spanning the BAP1 gene were the four probands . Fig 1B depicts the pairwise extent of those shared segments , which ranged in length from 9 . 1 to 34 . 2 megabase pairs ( Mbp ) . The heterozygous BAP1 mutation found in the four probands ( MARF2-IV-2 , MARF11-III-1 , MARF18-III-1 , MARF40-III-1 ) causes a frame shift deletion ( c . 1717_1717delC ) where Leu→Trp , leading to a premature stop codon , which occurs two amino acids downstream . The resulting truncated BAP1 protein is 573 amino acids long and lacks the nuclear localization signal . Therefore , this mutation is expected to result in the cytoplasmic localization of the truncated BAP1 protein . Immunohistochemistry ( IHC ) of MM tissues showed only cytoplasmic BAP1 staining and lack of nuclear BAP1 staining , suggesting that the remaining wild-type allele had also become altered in the tumor cells ( Fig 2A ) . Loss of heterozygosity ( LOH ) , a common somatic rearrangement of the BAP1 gene commonly found in MM and other tumors [26] , was confirmed by tumor tissue DNA sequencing in MARF11-III-1 and MARF18-III-1 , for which tumor tissue was available ( Fig 2B ) . Although MM tumor tissues were not available for MARF2-IV-2 and MARF40-III-1 , IHC of MARF2-IV-2 giant bone tumor tissue indicated lack of BAP1 nuclear staining ( S2 Fig ) , supporting presence of LOH , as our previous studies have shown a 100% correlation between LOH and lack of nuclear staining [26] . These data confirmed that the malignancies observed in the four probands are associated with BAP1 alterations . The extent of the shared haplotypes surrounding the BAP1 gene , between the four MARF probands carrying the c . 1717_1717delC BAP1 mutation , indicated that these , presumably unrelated individuals , had a common ancestor . Therefore , we performed extensive genealogical surveys of their families . Genealogical searches using historical census data , birth and death certificates , hospital records , and information from the Ancestry . com database generated data to construct a large pedigree , which we named “K4” kindred , with about 80 , 000 predicted descendants . This pedigree connected the lineage of the four probands carrying the c . 1717_1717delC BAP1 mutation and the rare allele rs71651686 to a couple born in Germany in 1710 ( male ) —whose ancestors were traced back to 1588 in Switzerland and immigrated to Germany in the 17th century—and in 1712 ( female ) . The couple immigrated to North America , where they had at least ten children . One son born in 1748 in Virginia , migrated to Kentucky and was the forebear of probands MARF11-III-1 , MARF18-III-1 , and MARF40-III-1 , while proband MARF2-IV-2 descended from another son , born in Virginia in 1750 , who migrated to Ohio ( Maps in S3 Fig , show family migration patterns , exact dates of migration are not shown to respect patient’s confidentiality ) . The condensed pedigree of 106 individuals with the most relevant information is shown in Fig 3 . This pedigree confirmed the relationship among the four c . 1717_1717delC BAP1 mutant probands , as indicated by the molecular studies . Most importantly , creating a large family pedigree allowed us to identify new branches of the K4 family ( Fig 3 , orange symbols ) and , among them , individuals affected by cancers characteristic of this syndrome ( Fig 3 , blue symbols ) .
Using our screening criteria , we found germline BAP1 mutations in 18% ( 4/22 ) MM patients . The much higher rate of germline BAP1 mutations that we found in our selected cohort , compared to the percentage ( 1–2% ) found in previous studies among “unselected” MM patients [3 , 27] , indicates that the selection criteria we used , based on patient’s and family history , are efficient to identify patients with the BAP1 cancer syndrome . We have identified a heterozygous germline BAP1 c . 1717_1717delC mutation that is responsible for a high incidence of MM , UM , and other cancers among four families ( Fig 3 and S2 Table ) . The absence of a history of asbestos exposure in all four probands suggests that the high penetrance of MM in the BAP1 mutant families may not require exposure to asbestos ( e . g . , at least professional exposure or identifiable environmental exposure , for a critical analysis of human carcinogen see ref . [28] ) . At the same time , only some BAP1 mutant families experience a high prevalence of MM , suggesting that in some families a low level of asbestos exposure may be a co-factor [28] , while other families have higher prevalence of different tumor types , such as melanomas , etc . Indeed , we recently published that BAP1+/- mice were susceptible to develop MM when exposed to very low levels of asbestos , levels that rarely trigger MM in wild-type mice [29] . Thus , it is possible that exposure to low levels of asbestos may have triggered MM also in some of these individuals carrying germline BAP1 mutations . This hypothesis is difficult to verify in non-professionally exposed individuals , due to the intrinsic difficulty of assessing low asbestos exposure levels . Through combined molecular and genealogical approaches we determined that these four probands , carrying the BAP1 c . 1717_1717delC mutation , are related to a common ancestor , traced through nine generations . The resulting members of the kindred “K4” are genetically high-risk individuals for developing MM and other BAP1-associated malignancies . K4 is the largest pedigree of its kind for the BAP1 cancer syndrome and can be used in genetic counseling for predictive testing ( Fig 3 ) . This family pedigree is still in progress as new information is added to the pedigree as it is acquired . As more branches of the family will be identified they will be offered testing for BAP1 . We performed a comprehensive analysis of all reported BAP1 germline mutations , which we compiled in S4 Fig ( see also S3 Table for reference list ) to see if additional individuals had been reported in the literature to carry this particular mutation . We found that the c . 1717_1717delC BAP1 mutation identified in our K4 was recently reported by Cebulla et al . in an apparently unrelated family from Ohio [30] . Although it is possible that the same mutations arose independently in multiple individuals , our genealogic data tracing the migration of K4 throughout the US indicated that they migrated through Ohio ( S3 Fig ) ; thus it is likely that the individuals described by Cebulla et al . [30] are related to the K4 family reported here . This hypothesis will be investigated and , if proved correct , the family will be entered into the K4 pedigree ( Fig 3 ) . Likewise , recurrent mutations in other parts of the BAP1 gene –i . e . , not the c . 1717_1717delC reported in this manuscript– have been found in several different families , see S4 Fig and S3 Table , suggesting the possibility that also those families are related . BAP1 mutations usually cause cancer after the peak of the reproductive age is passed [18] . Since these mutations do not appear to have deleterious effects , other than causing cancer in individuals after the reproductive age [18] , they are not negatively selected for , and instead they are transmitted across generations , as we discovered and reported here . Here we demonstrate and propose that a combination of a carefully taken patient and family history , together with modern molecular genetics and genealogical studies can be used to identify potential carriers of germline BAP1 mutations and to build large family trees . These family trees can be used to identify additional branches of the family that separated over the course of time , and that may be still carrying germline BAP1 mutations , and that will benefit from this information . Indeed , as shown in Fig 3 , using this approach we identified several new branches of the K4 family affected by MM and by other BAP1 cancer syndrome-associated malignancies ( those highlighted in blue in Fig 3 ) . Specifically , through genealogical analyses we identified the ancestors of these four probands , then , by “reverse genealogy” , we identified additional descendants of the original ancestors and , among them , patients with multiple BAP1 related malignancies , who have or are undergoing BAP1 testing ( Fig 3 ) . For example , from MARF 11-III-1 we identified his father MARF 11-II-1 who had nasal carcinoma and his sister , MARF 11-II-3 , who had peritoneal MM and her four children . One of them had melanoma , renal carcinoma , and peritoneal MM –diagnosed almost simultaneously at age 55 . She tested positive for BAP1 germline mutation ( Fig 3 ) . Her relatives and descendants are now been closely monitored for early cancer detection and are being tested for germline BAP1 mutations . Similarly , the identification of the ancestors of proband MARF40-III-1 and proband MARF2-IV-2 allowed us to identify additional descendants of the original ancestors , including branches of these families with multiple BAP1 related malignancies who have/are undergoing BAP1 testing ( Fig 3 ) . Once new branches of the family carrying germline BAP1 mutations are identified , these family members , affected by MM , can be informed that their malignancy is usually associated with significantly longer survival than those occurring sporadically [18] . Those that do not have disease and are found to be carriers of BAP1 germline mutations can be followed for early cancer detection [7] . Those who do not have disease and who did not inherit the mutation can be reassured they and their descendants are not at higher risk of malignancy than the general population . Early diagnosis and treatment may be partly responsible for the significantly improved prognosis of MM in germline BAP1-carriers [18] . Therefore , we have , and are , enrolling several BAP1 family members in a prospective study that includes yearly dermatological and ophthalmological evaluations for early detection of CM and UM , which are curable malignancies when detected at an early stage . Moreover , novel approaches based on biomarkers studies are being investigated in these families to improve early detection for MM and other cancers , as almost all malignancies are more susceptible to therapy when detected at an early stage . As we learn more about the pathways that are altered in individuals carrying germline BAP1 mutations , novel target approaches will be developed to benefit them . In summary , it is clinically relevant to identify carriers of BAP1 mutations and patients who developed cancer in a background of germline BAP1 mutations . Because BAP1 germline mutations are passed through multiple generations , building genealogical trees , as the one shown in Fig 3 , will lead to the identification of many more families who carry these mutations and who will benefit from this information .
Written informed consent was received from all patients . Collection and use of patient information and samples were approved by the IRB of the University of Hawaii ( IRB no . 14406 ) . Patients were recruited based on family histories suggestive of the BAP1 cancer syndrome . Inclusion criteria were: 1 ) age at MM ( either pleural or peritoneal MM ) diagnosis less than 70 years; 2 ) presence of at least one other MM in first-degree relatives across two generations , and/or presence of at least one other of the following BAP1 cancer syndrome-associated malignancy ( UM , CM , RCC , BCC or cholangiocarcinoma ) in either the proband or a first-degree relative or history of multiple cancers in the first-degree relatives . Twenty-nine MM patients were identified –all epithelioid MMs– and 22 of them agreed to participate in the study and submitted blood for DNA isolation and BAP1 sequencing . When available , tumor tissues from these individuals were collected for detection of somatic BAP1 status , according to IRB guidelines . MARF2-IV-2 proband was diagnosed with uterine leiomyosarcoma at age 32 , UM at age 48 , pleural MM at age 55 , peritoneal MM at age 60 , giant cell bone tumor at age 71 and died at 72 . MARF11-III-1 proband was diagnosed with peritoneal MM at age 51 and is presently 57 . His brother ( MARF11-III-2 ) was diagnosed with UM at age 51 and is presently 61 . MARF18-III-1 proband and her two older sisters were diagnosed with MM before age of 58 . The proband had both pleural and peritoneal MM and survived seven years from diagnosis . One of her sisters ( MARF18-III-2 ) had pleural MM and died from complications of treatment; the other sister ( MARF18-III-3 ) had peritoneal MM and survived nine years from diagnosis . MARF40-III-1 proband was diagnosed with four of the malignancies that have been conclusively demonstrated to be part of the BAP1 cancer syndrome: two basal cell carcinomas ( BCC ) diagnosed at ages 64 and 71 , peritoneal MM at age 67 , RCC at age 70 , and UM at age 71 . He died of pneumonia at age 72 . The proband’s mother ( MARF40-II-1 ) was diagnosed with breast cancer at age 50 and peritoneal MM at age 70; one maternal aunt ( MARF40-II-4 ) died at age 68 of peritoneal MM , another maternal aunt was diagnosed with UM ( MARF40-II-8 ) ; a cousin ( MARF40-III-5 ) was diagnosed at age 71 with pleural MM . Additional information can be found in S2 Table . Genomic DNA was extracted from whole blood or from tumor tissues and the BAP1 gene was directly amplified by PCR in its entirety as previously described [3] . Briefly , DNA was extracted using either DNeasy Blood & Tissue Kit ( QIAGEN , Hilden , Germany ) , or QiAamp DNA Micro Kit ( Qiagen ) following the manufacturer’s instructions . Advantage2 DNA polymerase ( Clontech ) was used with each pair of primers under the following conditions: denaturation at 95°C for 2 min; then five cycles of 95°C for 1 min and 68°C for 1 min; then 35 cycles of 95°C for 30 s , 63°C for 30 s and 68°C for 30 s; concluding with 68°C for 5 min . PCR products were gel-purified and Sanger sequenced . Genomic BAP1 PCR product sizes ranged from 560–670 bp with 100–150 bp overlap between primer sets . Sequencing was conducted using the ABI 3730XL DNA Sequencer , at the Advanced Studies in Genomics , Proteomics and Bioinformatics facility at the University of Hawaii at Manoa . The BAP1 mutation c . 1717_1717delC is detected with the following forward primer: CCTCACCCACCCCCAGCA , and reverse primer TGGGAAGAGAGGTCACAA GAAAA . The complete list of primers used for BAP1 sequencing can be found in reference no . [3] . The four MARF samples ( MARF2-IV-2 , MARF11-III-1 , MARF18-III-1 , MARF40-III-1 ) , and four control samples from the University of Hawaii Cancer Center were genotyped on the Illumina OmniExpress ( OE ) array by AROS Applied Biotechnology ( Aarhus , Denmark ) . We imported genotype data into R and converted it into snpStats genotype data format . The orientation and uniqueness of SNP positions was determined by comparing to the human hg19 reference genome ( http://hgdownload . cse . ucsc . edu/goldenPath/hg19/chromosomes ) using in-house R scripts and blat . OE SNPs were then filtered to only include those that were uniquely mapped , had 100% call-rate across the eight samples , and minor-allele frequency ( MAF ) greater than zero across the genotyped samples or in 1000G European samples . SNPs and their location in the genome were analyzed using: 1 ) 1000 Genomes Project ( 1000G Central European or British ancestry: CEU+GBR; n = 205; 2 ) UK10K Project ( n = 3781 ) ; 3 ) NHLBI Exome Sequencing Project ( ESP; n = 4300 ) . Reference 1000G Illumina Omni 2 . 5M genotype data ( Omni2 . 5 ) for 2141 samples from 19 worldwide sample populations was combined for analysis with the OE data . Quality control metrics such as call-rate , MAF , alternate-allele frequency ( AAF ) , and Hardy-Weinberg Equilibrium ( HWE ) P-value were calculated across SNPs and samples in each population . We performed principal component analysis ( PCA ) and genome-wide identity-by-descent ( IBD ) analysis of OE+Omni2 . 5 using the R statistics package SNPRelate ( http://github . com/zhengxwen/SNPRelate ) , after running LD-based pruning to remove redundant/correlated SNPs[22 , 23] . PCA is a method used to reduce a high-dimensional dataset consisting of many correlated variables down to a smaller set of uncorrelated variables termed principal components ( PCs ) and is commonly used to investigate the ancestral ethnicity and geographic origin of a set of samples using genome-wide genotype data [20] . Phased haplotypes for complete chromosome 3 genotype data were estimated using SHAPEIT2 and IBD shared segment analysis run using BEAGLE4 with default parameters . BAP1 staining was performed as previously described [3] . Briefly , Formalin-fixed paraffin embedded tissue sections were first deparaffinized and rehydrated , then immersed in 3 . 0% hydrogen peroxide in methanol for 10 min at room temperature ( RT ) to block endogenous peroxidase activity . Heat antigen retrieval was conducted at 121°C for 5 min in 0 . 01 M citrate buffer ( pH 6 . 0 ) . Staining was performed using the Vectastain Elite ABC Kit and the C-4 monoclonal mouse anti-BAP1 antibody ( Santa Cruz , CA ) diluted 1/100 . A professional genealogist ( H . H . ) investigated the common ancestors of the four MM patients carrying germline BAP1 deletion c . 1717_1717delC . Data were obtained from Ancestry . com ( http://www . ancestry . com ) , historical census , birth , death certificates , and hospitals . | Germline BAP1 mutations cause a cancer syndrome characterized by high incidence of mesothelioma ( MM ) , uveal melanoma and other cancers , and by very high penetrance , as all individuals carrying BAP1 mutations developed at least one , and usually several , malignancies throughout their lives . Through screening MM patients with histories of multiple cancers , we found four supposedly unrelated patients that shared an identical germline BAP1 mutation . We investigated whether this BAP1 mutation occurred in a ‘hot-spot’ for “de novo” mutations or whether these four MM patients shared a common ancestor . Using molecular genomics analyses we found that they are related . By genealogic studies we traced their ancestor to a couple that emigrated from Germany to North America in the early 1700’s; we traced the subsequent migration of their descendants , who are now living in at least three different US States . Our findings demonstrate that BAP1 mutations are transmitted among subsequent generations over the course of centuries . This knowledge and methodology is being used to identify additional branches of the family carrying BAP1 mutations . Our study shows that the application of modern genomic analyses , coupled with “classical” family histories collected by the treating physician , and with genealogical searches , offer a powerful strategy to identify high-risk germline BAP1 mutation carriers that will benefit from genetic counseling and early detection cancer screening . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] | [] | 2015 | Combined Genetic and Genealogic Studies Uncover a Large BAP1 Cancer Syndrome Kindred Tracing Back Nine Generations to a Common Ancestor from the 1700s |
P . vivax infection during pregnancy has been associated with poor outcomes such as anemia , low birth weight and congenital malaria , thus representing an important global health problem . However , no vaccine is currently available for its prevention . Vir genes were the first putative virulent factors associated with P . vivax infections , yet very few studies have examined their potential role as targets of immunity . We investigated the immunogenic properties of five VIR proteins and two long synthetic peptides containing conserved VIR sequences ( PvLP1 and PvLP2 ) in the context of the PregVax cohort study including women from five malaria endemic countries: Brazil , Colombia , Guatemala , India and Papua New Guinea ( PNG ) at different timepoints during and after pregnancy . Antibody responses against all antigens were detected in all populations , with PNG women presenting the highest levels overall . P . vivax infection at sample collection time was positively associated with antibody levels against PvLP1 ( fold-increase: 1 . 60 at recruitment -first antenatal visit- ) and PvLP2 ( fold-increase: 1 . 63 at delivery ) , and P . falciparum co-infection was found to increase those responses ( for PvLP1 at recruitment , fold-increase: 2 . 25 ) . Levels of IgG against two VIR proteins at delivery were associated with higher birth weight ( 27 g increase per duplicating antibody levels , p<0 . 05 ) . Peripheral blood mononuclear cells from PNG uninfected pregnant women had significantly higher antigen-specific IFN-γ TH1 responses ( p=0 . 006 ) and secreted less pro-inflammatory cytokines TNF and IL-6 after PvLP2 stimulation than P . vivax-infected women ( p<0 . 05 ) . These data demonstrate that VIR antigens induce the natural acquisition of antibody and T cell memory responses that might be important in immunity to P . vivax during pregnancy in very diverse geographical settings .
Neglected for a long time , P . vivax malaria is raising more attention lately due to the increased recognition of its burden [1–4] and the renewed call for malaria elimination in endemic areas where P . vivax is an important source of malaria . Firstly , P . vivax is the most widely-spread of the human malaria parasites , with an at-risk population of 2 . 65 billion people [5] . Secondly , P . vivax infection is not as benign as traditionally believed , with severe malaria affecting a variety of population groups , including pregnant women in whom P . vivax infection has been associated with poor outcomes such as anemia , low birth weight ( LBW ) or congenital malaria [6–13] . The adverse consequences of malaria during pregnancy , the presence of parasites in the placenta and the molecular mechanisms of sequestration ( parasite ligand and host receptor ) have been well characterized in P . falciparum but to a lesser degree in the case of P . vivax infection . In P . falciparum infection during pregnancy , parasites may adhere to placental chondroitin sulphate A ( CSA ) through VAR2CSA , a member of the P . falciparum erythrocyte membrane protein 1 ( PfEMP-1 ) family [14 , 15] . Thus , susceptibility to placental malaria has largely been attributed to a set of P . falciparum strains expressing VAR2CSA . Host immunity to this particular parasite protein has been associated with exposure to or protection against P . falciparum infection during pregnancy [16 , 17] . There is controversy about P . vivax cytoadherence properties , although we have reported placental P . vivax monoinfections in Papua New Guinea ( PNG ) with no signs of placental inflammation [18] . Rosetting seems a frequent cytoadhesive phenotype during P . vivax infections , which may contribute to the development of anemia in pregnancy [19 , 20] . Nevertheless , a P . vivax orthologue of the PfEMP-1 gene family and of VAR2CSA has not been described in parasites infecting pregnant women . Like P . falciparum , the P . vivax genome contains subtelomeric multigene families . This includes the variant vir superfamily [21–23] with 295 vir pertaining to 10 subgroups [22 , 23] . From a structural point of view , vir genes differ greatly in size ( 156–2 , 316 bp in length ) and number of exons ( 1–5 ) . Unlike PfEMP-1 , VIR proteins represent an extremely diverse family clustered in subgroups , which suggests different subcellular localizations and functions . These functions may include immune evasion [22] , although P . vivax vir genes do not undergo allelic exclusion in contrast to the clonal variant expression of P . falciparum var genes [24 , 25] . Moreover , VIR proteins can localize to the surface of infected reticulocytes [21 , 26] and induce the natural acquisition of antibodies after infection [24 , 27] . Nevertheless , the host immune responses to VIR proteins and their association with malaria outcomes have not yet been extensively characterized , even less in pregnancy , partly due to the extent of their diversity and the difficulty to express them as recombinant proteins for immunoassays . We have partially overcome these two problems by using the wheat germ cell-free expression system and by producing two long synthetic peptides containing conserved VIR sequences ( PvLP1 and PvLP2 ) based on the P . vivax line Sal-I . This strain is originally from El Salvador , which was monkey-adapted . To overcome the sequence polymorphisms , we determined conserved globular domains of presently unknown function to synthesize PvLP1 and PvLP2 for testing in immune-epidemiological field studies with parasites from different origins . A recent meta-analysis has highlighted the necessity of cohort studies representing diverse geographical regions in the field of P . vivax infections , to increase the body of evidence for protective immunity [28] . As part of the PregVax project , a multicenter study aimed at describing the burden of P . vivax malaria in pregnancy , we set out to study naturally acquired immune responses to VIR proteins during pregnancy . Women from five different P . vivax endemic countries in America ( Guatemala , Colombia , Brazil ) , Asia ( India ) and South Pacific ( PNG ) were enrolled and antigen-specific immune responses assessed . We used VIR-based recombinant proteins as well as PvLP1 and PvLP2 for antibody and cellular immunoassays . We demonstrate that despite the large diversity of vir sequences , women from all regions mounted antibody responses to the VIR antigens that increased with P . vivax infection and past exposure . Moreover , women from the highest endemic region ( PNG ) had detectable VIR-specific cellular memory immune responses with distinct patterns according with P . vivax infection status . Altogether , data indicate that VIR antigens might be targets of immunity to P . vivax during pregnancy .
A total of 16 vir genes were selected to be cloned and expressed . Twelve one-exon genes were selected for practical reasons as genomic DNA could be used as template ( S1 Table ) . In addition , four vir genes were selected after a protein BLAST against VAR2CSA domains , presenting 18 . 8–30 . 6% protein identity ( S2 Table ) . Because the var2csa-homology regions of vir genes were always located in exon 2 , only this exon was cloned . Of these 16 vir genes , four one-exon vir genes were discarded for protein expression: two of them ( PVX_006080 and PVX_241290 ) could not be cloned as the PCR reaction did not work and another two ( PVX_045190 and PVX_106220 ) did not present the expected sequence after cloning . With the classical E . coli expression system , PVX_086890 and PVX_069690 were poorly induced; and PVX_015640 , PVX_067190 , PVX_090290 and PVX_115485 were insoluble . Attempts to purify the six remaining partially soluble VIR proteins expressed in E . coli resulted in very low yields and not completely clean proteins . Therefore , these six VIR proteins were cloned in the pIVEX vector and further expressed in the cell-free wheat germ system but PVX_112125 showed mutations in the sequence . Thus , five vir genes were successfully expressed in the wheat germ cell-free expression system: vir25 ( vir25-related , PVX_001610 , group one-exon ) ; vir14 ( vir14-related , PVX_101615 , group one-exon ) ; vir2 ( vir2/15-like , PVX_107750 , group var2csa homology ) , vir24 ( vir24-like , PVX_093720 , group var2csa homology ) and vir5 ( vir5-related , PVX_124715 , group var2csa homology ) . Soluble proteins were obtained of predicted sizes as detected by SDS-PAGE ( Fig 1 ) . Because expression of VIR proteins was not very productive , we designed two peptides containing conserved VIR sequences in order to perform the immunological assays . A total of 1 , 511 peripheral blood samples collected at different time points ( recruitment , delivery or postpartum ) corresponding to 1 , 056 women , were analyzed for antibody responses . Unfortunately many of our samples were not paired due to low follow-up rates . The study population characteristics at baseline by country are provided in S3 Table . The infection rates by country and time-point are provided in Table 1 . The amount of VIR14 , VIR2 and VIR24 proteins produced was not sufficient to measure antibodies to them in all samples , therefore enrolment-delivery-postpartum matching samples were prioritized . The numbers of plasma samples per country for which anti-VIR antibody data were generated against each antigen and at different time point are summarized in S4 Table . For cellular assays , 53 samples ( any gestational age including delivery , 18 P . vivax PCR negative , 28 P . vivax PCR positive , 7 unknown infection status ) from the PNG pregnant cohort were included in the analyses . Antibody responses to all VIR antigens were detected ( value above negative control cutoff ) in all sites and timepoints , except VIR25 and VIR5 at postpartum in India ( IN ) ( Fig 2 ) . IgG levels to all VIR antigens differed among countries at all timepoints ( except VIR25 at postpartum ) ( one-way ANOVA p<0 . 05 ) . PNG presented the highest magnitudes and prevalence , followed by Guatemala ( GT ) . Overall , VIR25 appeared to be the most broadly recognized antigen , with significant responses across all endemicities , even in countries like Brazil ( BR ) and IN where IgG responses to the other VIR antigens were very low ( Fig 2 ) . In addition , VIR14 and VIR2 showed consistent and comparable responses in PNG and GT at all timepoints , stronger than those to VIR25 , and for VIR2 a peak was also detected at postpartum in Colombia ( CO ) . Finally , VIR5 and PvLP2 only appeared to be considerably recognized by plasma from PNG , and PvLP2 ( and PvLP1 ) also in CO at postpartum . The lowest responses were measured for VIR24 , only detected at moderate levels for PNG . Of note , anti-VIR seroprevalence was in range with other P . vivax antigens such as Pv200L: BR: 7%; CO: 35%; GT: 40%; IN: 5%; PNG: 76% . At recruitment , IgG responses to VIR proteins were closely correlated ( Table 2 ) , but they correlated poorly with antibody responses to VIR synthetic peptides or other P . vivax antigens such as Pv200L , which corresponds to a fragment of the merozoite surface protein 1 . PvLP2 presented the highest correlation with Pv200L ( Table 2 ) and other P . vivax antigens . We considered whether anti-VIR responses were due to cross reactivity with other Plasmodium antigens . To assess this , we studied the correlation between anti-VIR responses and antibody responses to 9 P . vivax and 6 P . falciparum additional antigens . Of note , low correlations were found between anti-VIR responses and other anti-Plasmodium responses , suggesting that there was no cross-reactivity ( S5 table ) . There were higher levels of anti-VIR24 IgGs at delivery , and more anti-VIR2 , anti-VIR25 and anti-PvLP1 antibodies at postpartum , compared to recruitment levels , although overall differences using the Wald test were only significant for PvLP1 ( S6 Table ) . We assessed how different pregnancy variables affected the IgG responses to VIR antigens . Antibody levels to VIR5 were significantly associated with gravidity ( proportional differences by [category group of previous pregnancies] [0]: 1; [1–3]: 1 . 43 , 95% CI: 0 . 91–2 . 25; [4+]: 0 . 71 , 95% CI: 0 . 34–1 . 48 , p=0 . 033 ) . IgG responses to PvLP1 and PvLP2 were significantly associated with present malaria infections ( Table 3 ) . Of note , the association with co-infections ( P . vivax and P . falciparum ) was higher than with mono-infections ( P . vivax alone ) . However , sample size for co-infections was small , especially at delivery , and these results should be considered cautiously . The magnitude of VIR-specific IgG response did not show associations with age and gestational age ( p>0 . 05 ) . We also analyzed the association between antibody levels at recruitment and future infection ( at delivery ) . Women with higher PvLP1 antibody levels at recruitment had a higher probability of having a P . vivax infection at delivery ( per doubling antibody levels , OR=1 . 84 , 95% CI=1 . 11; 3 . 04 , p=0 . 017 , adjusted analysis ) . Finally , we studied the association between antibody levels and pregnancy outcomes , i . e . hemoglobin ( Hb ) levels and birth weight . A borderline significant positive association between PvLP2 antibody levels at recruitment and birth weight was observed by unadjusted regression analyses ( Table 4 ) . At delivery , IgG responses against two VIR proteins with homology to VAR2CSA ( VIR2 and VIR24 ) were positively associated with birth weight in the adjusted analysis ( Table 4 ) . No associations were found between antibody levels and Hb levels at delivery ( p>0 . 05 ) . Peripheral blood mononuclear cells ( PBMC ) from PNG women with current P . vivax infection had a significantly lower percentage of IFN-γ-producing CD4+ and CD8+ T cells than uninfected women when stimulated with PvLP2 , as assessed by intracellular cytokine staining by flow cytometry ( Fig 3 ) . No differences in % IFN-γ+ CD4+ T cells between infected and non-infected women were observed when stimulating PBMCs with PvLP1 or in the medium and anti-CD3 controls , and significant but much lower differences compared to PvLP2 stimulus were observed in % IFN-γ+ CD8+ T cells for PvLP1 and medium control ( Fig 3 ) . We also measured the concentration of cytokines , chemokines and growth factors secreted in PBMC cultured either with medium , PvLP1 or PvLP2 . Infected women produced more G-CSF and IL-4 than those from uninfected women , independently of the stimulus ( Table 5 ) . In addition , supernatants contained more IFN-γ when PBMC were cultured with medium or PvLP2 , although the median value was the same , suggesting that differences were not very high . Of note , PBMCs stimulated only with PvLP2 secreted specifically more pro-inflammatory cytokines TNF , IL-6 and regulatory cytokine IL-10 in the infected group than in the uninfected group , although the difference did not reach statistical significance for IL-10 ( p=0 . 062 ) . No differences between the infected and uninfected cohorts were observed in the anti-CD3 control , although overall values in this positive control were higher than in the other three culture conditions .
Considering the large genetic diversity of P . vivax strains [29] and the effect that polymorphisms in host genes such as HLA can have on immune responses to certain antigens [30] , it is important to evaluate antibody and cellular immune responses to potential targets of immunity in different geographical populations . Here , significant levels of anti-VIR antibodies were detected in pregnant women from five countries with very diverse endemicity and transmission rates , further supporting the immunogenic properties of VIR antigens previously reported in non-pregnant Brazilian women [21 , 24 , 27] . This is remarkable if we consider that the Sal-I genome was used as a template for the production of all recombinant VIR proteins and suggests that despite the high sequence variability in the VIR proteins and the P . vivax circulating strains , B cell epitopes might be sufficiently conserved . This is further supported by the immunogenicity of long synthetic peptides representing conserved globular domains of VIR proteins , particularly PvLP2 . We cannot , however , exclude the possibility that low responses to some VIR proteins in particular settings are due to lack of VIR expression or that they contain less B-cell epitopes as opposed to the inability to develop a VIR-specific immune response upon exposure to that variant . Expressing recombinant Plasmodium proteins using different expression vectors has shown to be a challenging endeavor [31] , especially achieving expression of soluble and correctly folded proteins is even more difficult . The cell-free wheat germ expression system used here has proven to be an excellent system to produce soluble and correctly folded proteins [32 , 33] . In fact , expression of enzymes from the human genome consistently showed that they retain enzyme activity [34] . In spite of these advantages , vir genes are highly AT-rich and several different attempts to express all the genes listed in S1 and S2 Tables using this or other systems such as cell-free and cell-based E . coli have failed . PNG presented the highest intensity and prevalence of antibody responses against all antigens , despite P . vivax infection rates not being much higher at the time of the study within this cohort than in the other five countries [35] . The fact that asymptomatic infected women were not given treatment in PNG does not explain this difference , as the prevalence of P . vivax infection by microscopy in PNG was only 1% . Nevertheless , antibodies are a reflection of cumulative exposure , and PNG is indeed the country among the five with the highest malaria endemicity historically , even if during the PregVax study P . vivax prevalence was lower than in the past . In addition , regression analyses showed that co-infections with P . falciparum had a higher positive association with PvLP1 and PvLP2 antibody levels than P . vivax mono-infections . PNG had the highest P . falciparum microscopic infection rate in this cohort , suggesting these may boost anti-P . vivax responses . In our cohort we could rule out mostly although not totally undiagnosed submicroscopic co-infection and vir genes do not have orthologues in P . falciparum . It might be that this co-infection boosting effect is due to P . vivax-specific B cell bystander activation by noncognate T cells , which could be induced under conditions of persistent priming by P . falciparum antigens [36 , 37] . If this was the case , it may be interesting to consider this effect in programmatic terms regarding the search of a malaria vaccine . However , it is also possible that co-infections and higher antibody levels are just two parallel markers of higher previous exposure in some women . Plasmas from GT also presented significant levels of IgG antibodies to various VIR proteins . This is consistent with P . vivax positivity rates by PCR at the population level , which were the highest in GT and PNG in the whole PregVax cohort . Infections in GT were largely submicroscopic but sufficient to induce detectable antibody responses . There was heterogeneity with regards to recognition of the VIR antigens among countries . VIR25 was the most broadly immunogenic , being recognized in distant geographical regions , suggesting the presence of conserved and/or cross-reactive epitopes within its sequences . However VIR14 and VIR2 induced the highest levels of antibodies , though restricted to the two most endemic countries . Those three proteins ( VIR25 , VIR14 and VIR2 ) appeared to induce longer-lived antibodies as they were clearly detected in populations with high infection rates in the past but low at the time of sampling . Antibodies to VIR24 , VIR5 and PvLP2 were only clearly present in PNG , and this might indicate geographical diversity in immunogenicity of epitopes and/or their even longest-living nature . IgG antibodies against PvLP1 and PvLP2 were detected in all countries and timepoints but not at high levels . A peculiar pattern was observed in CO , where a significant increase in responses to most VIR antigens , but particularly VIR2 and PvLP2 , occurred at postpartum . This likely reflects increased parasite prevalence at a population level at this time rather than a booster of VIR responses after pregnancy . However , at an individual level we did not find an association between antibodies to VIR proteins and infection status , which probably reflects the diversity of vir genes in the P . vivax genome [38] . In contrast , levels of PvLP1 and PvLP2 were associated with present vivax malaria infections . Both antibody levels but specially anti-PvLP2 correlated well with other markers of malaria exposure . This suggests that the design of these peptides ( based on conserved sequences ) might have helped overcome the problem of having a large and variable gene family . Thus , collectively the data showed that VIR antigens could be markers of exposure at a population level . We also assessed association between antibodies and protection at the individual level , although this is often difficult as heterogeneity of exposure is not properly assessed and accounted for in field designs . In fact , higher PvLP1 antibodies at recruitment were associated with more risk of infection at delivery , being a correlate of risk rather than of immunity . We have previously reported that higher levels of antibodies in some individuals may indicate those who have had previous malaria episodes and are at higher risk of future episodes if past exposure is not well adjusted for [39 , 40] . Nevertheless , we also found some indications for a potential protective role of VIR antibodies in malaria in pregnancy outcomes: ( i ) a borderline significant positive association between PvLP2 antibody levels at recruitment and birth weight and ( ii ) a positive association of antibody levels to VIR2 and VIR24 ( of partial sequence homology to P . falciparum VAR2CSA domains ) at delivery and birth weight . Placental P . vivax infection has been reported [18] , as well as P . vivax adhesion to CSA [19] and inhibition of P . vivax cytoadhesion using soluble CSA [41] . However , whether VIR2 and VIR24 proteins also bind CSA and are implicated in vivax malaria during pregnancy remains speculative . Unfortunately , our study was not designed to demonstrate any protective role of antibody responses to VIR antigens in vivax malaria and therefore we cannot draw any conclusion . We present some evidence supporting a relationship between antigen-specific cytokine responses , infection and immunity in PNG pregnant women . Our data show lower PvLP2-specific IFN-γ+ CD4+ T cell frequencies and higher secretion of TNF , IL-6 and IL-10 , in P . vivax-infected pregnant women compared to uninfected women and this was not seen for PvLP1 or the control stimuli . IFN-γ has been shown to be essential for controlling experimental malaria infections in mice ( reviewed in [42] ) and clinical P . falciparum infections in humans [43 , 44] , and IL-10 is a key regulatory cytokine that prevents excessive inflammation but might contribute to the lack of control of infections . Thus , the fact that non-infected women had higher PvLP2-specific TH1 cell frequencies and lower IL-10 production could mean that cellular responses induced by this antigen ( for instance by a potential vaccine ) could help in controlling vivax infections . Nevertheless , we also observed PvLP2-specific increase of pro-inflammatory cytokines IL-6 and TNF in infected women . IL-6 has been shown to skew T cell differentiation towards TH2 and TH17 [45] , which would explain why we observe a decrease of TH1 frequencies . Thus we can assume that VIR epitopes present in PvLP2 trigger the natural acquisition of cellular memory immune responses , but whether these are protective or just markers of exposure can not be concluded from the data presented . This study presents some limitations . First , samples were not fully paired and sample size was different for some antigens/analyses . Unfortunately , many of these women lived in rural areas far from the hospital . It is highly complex to get full attendance to all antenatal clinics and , after puerperium , is even more complicated . In spite of this , we believe the cohort is quite unique and very valuable to demonstrate the immunogenicity of VIR antigens in different geographical settings . Second , due to its exploratory nature , we did not have statistical power to demonstrate strong associations between anti-VIR immune responses and protection against infection nor poor outcomes , as it was designed to be a first descriptive investigation of adaptive immune response ( antibody and T cells ) to VIR antigens during pregnancy . Third , multiple comparisons were not corrected for in all statistical assays and results are interpreted for internal coherence and biological plausibility . In summary , we present the first comprehensive study on immune responses to VIR antigens demonstrating that VIR sequences are the target of the natural acquisition of antibody and cellular responses affected by exposure to malaria infection in five distinct endemic areas . VIR 25 seems to be broadly recognized and we demonstrate that PvLP1 and PvLP2 can be used to profile antibody and cellular immune responses to VIR sequences , overcoming the problem of the large number of diverse VIR proteins . Based on our findings and the large burden of vivax malaria , we believe that larger prospective cohort immune epidemiological studies are needed to specifically address whether VIR-based antigens are targets of protective immunity against the neglected P . vivax parasite and could be considered as candidates for vaccine development towards malaria elimination .
This study was performed in the context of the PregVax project ( FP7-HEALTH-201588 , www . pregvax . net ) , a health facility-based cohort study of pregnant women to describe the burden and impact of P . vivax in pregnancy , conducted between 2008 and 2012 in five endemic countries: BR , CO , GT , IN and PNG . Approximately 2 , 000 women per country were enrolled at the first antenatal visit ( recruitment ) , and followed up until delivery . Symptomatic Plasmodium spp . infections at any time during pregnancy were also recorded though passive case detection . A random subpopulation corresponding to 10% of the entire PregVax cohort was allocated to the “immunology cohort” and was further followed up until at least 10 weeks after delivery ( postpartum group ) . In all visits , Hb levels , P . vivax and P . falciparum parasitemias by blood smear and malaria symptoms were assessed . Giemsa-stained thick and thin blood slides were read onsite following WHO standard quality-controlled procedures to establish parasite presence . External validation of a subsample of blood slides from each country was done at the Hospital Clinic and at the Hospital Sant Joan de Deu , in Barcelona , Spain . Birth weight was recorded . Women with a positive smear were treated according to national guidelines , except in PNG where blood smears could not be read at the moment of the visit for logistical reasons ( only symptomatic women were thus treated after confirmation of infection by rapid diagnostic test ) . The protocol was approved by the national and/or local ethics committees of each site , the CDC IRB ( USA ) and the Hospital Clinic Ethics Review Committee ( Barcelona , Spain ) . Written informed consent was obtained from all study participants . A venous blood sample ( 5–10 mL ) was collected aseptically in heparinized tubes from the “immunology cohort” at recruitment , delivery and postpartum visits . Submicroscopic P . vivax and P . falciparum infections were also determined by real time-polymerase chain reaction ( PCR ) , except for the Indian samples , where only P . vivax infection was examined . Submicroscopic infections were only analyzed in a random sub-sample of the cohort . Additionally , blood samples ( 10 mL ) were collected from 39 malaria naïve donors at the blood bank in Hospital Clinic ( Barcelona , Spain ) , and used as negative controls . Plasma was separated by centrifugation and stored at -80°C . Blood cells from PNG were further fractioned in a density gradient medium ( Histopaque-1077 , Sigma-Aldrich ) to obtain PBMCs and stored in liquid nitrogen . Samples from GT , CO , BR and PNG were analyzed at ISGlobal ( Barcelona , Spain ) while plasmas from IN were analyzed in Delhi . Vir genes were amplified from genomic DNA ( Sal I strain ) by PCR using “PCR Supermix” ( Life Technologies ) . PCR products were introduced in the pIVEX1 . 4d vector ( Roche ) previously modified by inserting glutathione S-transferase ( GST ) after the 6xHis tag sequence . Authenticity of all clones encoding GST-VIR fusion proteins was confirmed by double-strand sequencing before expression in the wheat germ system . Thus , GST-fusion proteins contain open reading frames encoding the predicted VIR proteins . Primers used for gene amplification are listed in S1 and S2 Tables . Proteins were expressed with a GST tag using the wheat germ cell-free system as described [46] . Expressed proteins were purified on GST SpinTrap purification columns ( GE Healthcare ) , and eluted proteins were dialyzed in phosphate buffered saline ( Tube-O-DIALYZER , GBiosciences ) . GST was also expressed separately for immune-reactivity control . Pv200L ( P . vivax merozoite surface protein 1 , fragment 121–416 ) was produced as previously described [47] . The rest of Plasmodium antigens were produced as described previously [48] . The design and synthesis of P . vivax long synthetic peptides ( PvLP ) representing conserved central core ( PvLP1 ) and C-terminal ( PvLP2 ) VIR motifs , has been reported previously [26] . The sequences are detailed in S7 Table . Measurement of plasma IgG antibodies was performed by multiplex suspension array using the Luminex technology , as described [46] . MagPlex magnetic carboxylated microspheres ( Luminex Corporation , TX , USA ) were covalently coated with 3 μg of protein/peptide per 1 . 1–1 . 4 million beads following manufacturer’s instructions . Beads were quantified in a Guava Flow Cytometer ( Millipore ) and mixed in equal amounts . A unique batch of microspheres was prepared for the whole study , including the samples analyzed in IN . Circa 1000 beads per analyte were incubated with plasma ( 1:100 dilution ) in duplicates , and subsequently with anti-human IgG-biotin ( Sigma-Aldrich ) , followed by streptavidin-conjugated R-PE ( Fluka , Madrid , Spain ) . Beads were acquired on the BioPlex100 system ( Bio-Rad , Hercules , CA ) , and results expressed as median fluorescence intensity of duplicates . Value against GST alone was subtracted for VIR proteins . Raw GST values are presented in S1 Fig . Cross-reactivity was ruled out in a pilot study analyzing a subset of plasmas in singleplex and multiplex . Samples in IN were analyzed with identical protocols and instruments . Except where indicated , all reagents were purchased from BD Biosciences . PBMCs were thawed , rested for 10–12 h and viability assessed with Guava ViaCount Reagent ( Millipore ) . Only samples with viability >70% were used for assays . Half a million cells per well were resuspended in RPMI-1640 medium plus 10% fetal bovine serum ( culture medium ) and incubated with PvLP1 or PvLP2 ( 5 μg/mL ) . Culture medium was used as negative control and anti-CD3 as the positive control . After 12 h , an aliquot of 30 μL of culture medium supernatant was collected to measure secreted cytokines , while an equal volume of media containing GolgiPlug was added for additional ( 4 h ) incubation . PBMCs were stained with LIVE/DEAD Fixable Violet Dead ( Life Technologies ) , anti-CD14 Pacific Blue , anti-CD19 Horizon V450 , anti-CD4 allophycocyanin ( APC ) and anti-CD8 Peridinin Chlorophyll Protein Complex ( PerCP ) . After washing , cells were fixed and permeabilized with Cytofix/Cytoperm , and incubated with anti-CD3 phycoerythrin ( PE ) -Cy7 , anti-interferon ( IFN ) -γ PE and anti-CD69 fluorescein isothiocyanate ( FITC ) . Cells were acquired in a LSRFortessa flow cytometer and data were analyzed by FlowJo ( FlowJo LLC , OR , USA ) . Gating strategy is provided in S2 Fig . Supernatants were frozen at -80°C until Luminex analysis with the Cytokine Magnetic 30-Plex Panel ( Invitrogen ) , according to manufacturer’s instructions . Samples from BR , CO , GT , and half of the samples from PNG were analyzed at the Istituto Superiore di Sanità ( Rome , Italy ) , as described [12] . The threshold for positivity for each species was established as a cycle threshold<45 , according to negative controls . P . vivax diagnosis for IN samples was performed in Delhi following Rome’s protocol adapted for the instrument sensitivity ( 3rd step amplification 72°C for 25 sec instead of 72°C for 5 sec ) . Approximately half of the PNG samples were analyzed for submicroscopic infections in Madang , following a similar protocol to Rome’s [49] , except that the threshold for positivity for each species was established as cycle threshold<40 , according to negative controls . DNA was extracted from whole blood-spot filter paper . Any Plasmodium infection was defined as a positive smear by microscopy and/or positive PCR . One-way ANOVA test was used to evaluate the differences in antibody levels among countries , and Chi-squared or Fisher’s exact tests to evaluate the differences in percentages of individuals with a positive antibody response ( values above the mean plus 3 standard deviations [SD] of Spanish controls , cutoff ) . To assess the differences on antibody levels between non-pregnant and pregnant women at recruitment and delivery , multilevel mixed-effects linear regressions were estimated with the samples from the five countries . Timepoint ( recruitment , delivery and postpartum ) was the fixed independent variable , while inter-site ( country of origin ) and inter-subject variability were estimated as random parts . To study the association between antibody levels and pregnancy variables , univariate ( only adjusted for country of origin ) and multivariate linear regression models were estimated with the variables country , age , gestational age , gravidity ( number of previous gestations ) and P . vivax or P . falciparum infection during pregnancy ( only accounted past or present infections but not future infections ) . The correlation between IgG responses to different antigens was evaluated with the Spearman's rank test . The association between IgG levels at enrolment and future malaria infections was evaluated with logistic regression models . The association between antibody responses at enrolment and delivery , and Hb levels at delivery and birth weight , were analyzed using univariate and multivariate linear regression models , adjusted by country , Hb at recruitment , gestational age at recruitment , age , gravidity and past or present Plasmodium infection during pregnancy . For the cellular and cytokine analyses , deviation from normality was tested using the Skewness and kurtosis test . Because none of the variables except IL-13 presented a normal distribution , data was presented as medians and comparisons between groups were done using the U-Mann-Whitney test . Cytokine/chemokine production in culture supernatants of unstimulated samples ( medium ) was not subtracted from the stimulated samples but shown side by side as it is possibly biologically relevant . Significance was defined at p<0 . 05 . Crude p values are interpreted for internal coherence , consistency of results and biological plausibility . Analyses were performed using Stata/SE 10 . 1 ( College Station , TX , USA ) . | Naturally-acquired antibody responses to novel recombinant proteins and synthetic peptides based on sequences from P . vivax VIR antigens were evaluated in women from five distinct geographical regions endemic for malaria , during and after pregnancy . Levels of IgG to VIR antigens were indicative of cumulative malaria exposure and increased with current P . vivax infection and P . falciparum co-infection . Antibody data were consistent with levels of malaria endemicity and current prevalence in the diverse geographical areas studied . In addition , the magnitude of IgG response to two VIR antigens at delivery was associated with higher birth weight . Furthermore , T cell responses to VIR antigens were naturally induced and their magnitude varied according to P . vivax infectious status . Peripheral blood mononuclear cells from uninfected pregnant women from a highly endemic area produced higher TH1 ( IFN-γ ) and lower pro-inflammatory cytokines ( TNF and IL-6 ) upon stimulation with a long synthetic peptide representing conserved globular domains of VIR antigens than P . vivax-infected women . Data suggest that further investigation on these antigens as potential targets of immunity in naturally-exposed individuals is warranted . | [
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"dis... | 2016 | Plasmodium vivax VIR Proteins Are Targets of Naturally-Acquired Antibody and T Cell Immune Responses to Malaria in Pregnant Women |
Salmonella enterica serovar Infantis is one of the prevalent Salmonella serovars worldwide . Different emergent clones of S . Infantis were shown to acquire the pESI virulence-resistance megaplasmid affecting its ecology and pathogenicity . Here , we studied two previously uncharacterized pESI-encoded chaperone-usher fimbriae , named Ipf and Klf . While Ipf homologs are rare and were found only in S . enterica subspecies diarizonae and subspecies VII , Klf is related to the known K88-Fae fimbria and klf clusters were identified in seven S . enterica subspecies I serovars , harboring interchanging alleles of the fimbria major subunit , KlfG . Regulation studies showed that the klf genes expression is negatively and positively controlled by the pESI-encoded regulators KlfL and KlfB , respectively , and are activated by the ancestral leucine-responsive regulator ( Lrp ) . ipf genes are negatively regulated by Fur and activated by OmpR . Furthermore , induced expression of both klf and ipf clusters occurs under microaerobic conditions and at 41°C compared to 37°C , in-vitro . Consistent with these results , we demonstrate higher expression of ipf and klf in chicks compared to mice , characterized by physiological temperature of 41 . 2°C and 37°C , respectively . Interestingly , while Klf was dispensable for S . Infantis colonization in the mouse , Ipf was required for maximal colonization in the murine ileum . In contrast to these phenotypes in mice , both Klf and Ipf contributed to a restrained infection in chicks , where the absence of these fimbriae has led to moderately higher bacterial burden in the avian host . Taken together , these data suggest that physiological differences between host species , such as the body temperature , can confer differences in fimbriome expression , affecting Salmonella colonization and other host-pathogen interplays .
The bacterial species Salmonella enterica ( S . enterica ) is a Gram-negative , highly ubiquitous pathogen that can infect a very wide range of animal and human hosts . This heterogeneous single species contains more than 2600 serovars that can differ in their adaptation to various hosts ( host-specificity ) and the disease they cause . For example , non-typhoidal serovars ( NTS ) such as S . enterica serovar Typhimurium ( S . Typhimurium ) or S . Enteritidis have a broad-host range and can infect many different animal species including reptiles , birds and mammals . In healthy humans , infection with NTS results in most cases in a localized self-limiting inflammation of the terminal ileum and colon , known as gastroenteritis . In contrast , S . Typhi or S . Paratyphi A can infect only humans ( or high primates ) and the disease they cause manifests as an invasive , life-threatening disease , called typhoid or enteric-fever ( reviewed in [1 , 2] ) . Similarly , the avian-restricted serovars Gallinarum and Pullorum cause septicaemic diseases in poultry known as fowl typhoid and pullorum disease , respectively . Other Salmonella serovars or strains , although not fully host-restricted are well adapted to particular animal hosts . S . Choleraesuis , S . Dublin , S . Abortusovis and S . Typhimurium phage types DT2 and DT99 are often associated with swine , bovine , sheep , and pigeons , respectively [3–5] . One of the first steps in the establishment of a bacterial infection in any host is attachment to host tissues and colonization [6] . Intimate host-pathogen attachment is mediated by surface-exposed proteinaceous hair-like structures ( pili ) with adhesive properties , known as fimbriae that can bind specific glycoproteins or glycolipids host receptors [7 , 8] . Most of Salmonella fimbriae belong to the conserved chaperone-usher ( CU ) biogenesis pathway , named after the two proteins , required for the assembly of the pili , a periplasmic chaperone and an outer-membrane , pore-forming protein , termed usher . In addition to the major pilus subunit , CU fimbria may contain one or more minor protein subunits . Some of which are placed at the tip of the fimbrial rod and contain a lectin domain , providing adhesive properties to specific host receptors [9–11] . Thus , the composition of different fimbrial adhesins synergistically expressed by a specific strain or even polymorphism within a particular fimbria are thought to play a role in Salmonella host-tropism and adaptation [7 , 10 , 12–14] . The genes encoding the CU pathway are usually arranged within clusters encoding at least a major structural pilin subunit , a chaperone , and an usher protein . More complex fimbrial operons contain accessory genes encoding structural proteins such as minor fimbrial subunits , additional chaperones , or regulators . CU fimbrial clusters can be found either on the chromosome or on the plasmids of various Gram-negative bacteria [11 , 15] . Amongst more than 2600 S . enterica serovars known , S . Infantis is one of the most ubiquitous serovar worldwide . In the European Union , S . Infantis was ranked third in the prevalence order , following serovars Enteritidis and Typhimurium [16] and in the United States , S . Infantis was recently ordered sixth in the occurrence hierarchy [17] . In Israel , during 2008 to 2015 , S . Infantis was the most predominant serovar , both in clinical ( human ) and poultry sources [18 , 19] , suggesting that this serovar is highly adapted both to poultry and to the human hosts . Previously , we showed that a rapid emergence of a new clone of S . Infantis in Israel has involved horizontal acquisition of a novel virulence-resistance megaplasmid , named pESI [18 , 19] . Recently , a related pESI-like plasmid was identified in an emergent S . Infantis populations in Italy [20] and in the USA [21] , suggesting that pESI plays a similar role in globally emergent S . Infantis clones . In addition to antibiotic resistance and the potent yersiniabactin iron acquisition system , pESI encodes for two uncharacterized chaperone-usher fimbria clusters named klf and ipf [18] . Here , we studied environmental cues and the regulatory network controlling the expression of the Klf and Ipf fimbriae and characterized their role in S . Infantis virulence . We show the role of both core ( Lrp , Fur and OmpR ) and horizontally acquired ( KlfB and KlfL ) regulators in orchestrating these fimbriae expression and demonstrate that they are induced under microaerobic conditions and at the avian physiological temperature ( 41°C ) compared to 37°C or the ambient temperature . Additionally , we establish that both fimbriae play a distinct role in the pathogenicity of S . Infantis in the mammalian vs . the avian hosts . We propose that these differences affect S . Infantis colonization and contribute to variations in host-pathogen interactions .
The virulence megaplasmid , pESI encodes for two independent chaperone-usher fimbriae , one is related to the known K88-Fae fimbria and therefore named K88-like fimbria ( Klf ) , while the other was designated Ipf ( standing for Infantis plasmid encoded fimbria ) [18] . The ipf fimbrial cluster belongs to the γ1-fimbrial clade [15] , occupies 5 . 1 kb and contains four ORFs encoding a major fimbrial subunit ( IpfA ) , a chaperone ( IpfB ) , an usher ( IpfC ) , and a putative adhesin ( IpfD ) . Interestingly , nucleotide-nucleotide BLAST ( blastn ) search against the NCBI nr database showed a very limited distribution of the ipf cluster that was found , besides pESI , only outside of subspecies enterica ( ssp . I ) , in the genome of Salmonella enterica ssp . diarizonae ( ssp . IIIb ) and in an integrative and conjugative element ICESe3 of Salmonella enterica ssp . VII ( S1 Table and Fig 1A ) . The second pESI-encoded fimbria is related to the K88-Fae fimbria and belongs to the κ-fimbrial clade [15] . Enterotoxigenic E . coli ( ETEC ) strains expressing the K88 fimbria are long known to cause diarrheal disease in piglets and calves [22 , 23] . Nevertheless , since the related fimbrial cluster in pESI shows significant rearrangements and the homologous proteins present less than 90% identity to the corresponding K88 subunits in E . coli ( S2 Table and Fig 1B ) , we renamed this pESI-encoded cluster klf as mentioned above . The klf fimbrial cluster is 9 . 3 kb long and consists of 12 putative ORFs ( Fig 1B ) encoding an usher protein ( KlfD ) , chaperone ( KlfE ) , major fimbrial subunit ( KlfG ) and four minor fimbrial subunits ( KlfC , KlfF , KlfH and KlfI ) . At the 3' end of this cluster , we identified three hypothetical proteins with unknown function: KlfJ that might be truncated , KlfK and KlfA . In addition , two putative regulatory proteins ( KlfL and KlfB ) were annotated at the 5'-end of the klf cluster . In contrast to the rare distribution of the ipf cluster , klf homologs were found in several ssp . I Salmonella genomes , including in strains from serovars Anatum , Bareilly , Bredeney , Typhimurium , Cubana , Schwarzengrund , and Montevideo . Yet , the 5'-region of 1091 bp , containing the genes klfL and klfB appeared unique to the pESI-klf cluster and was not found in any other related cluster . Furthermore , while KlfC , KlfD , KlfE , KlfF , KlfH , KlfI , KlfK and KlfA are highly conserved among S . enterica Klf homologs , KlfG corresponding proteins , although presented similar size , were greatly diverse in their sequence ( S3 Table ) . In fact , the only KlfG conserved domain was its N-terminus , containing the signal peptide sequence , required for protein export via the Sec pathway ( Fig 2 ) . These results suggested that the klf cluster was subjected to significant genetic rearrangements including an insertion of the klfL-klfB fragment and recombination in the klfG gene . This possibility was further supported by the G+C profile of these two regions , showing a distinct G+C content of 38% and 42% for the klfL-klfB and klfG regions , respectively , compared to 61% G+C composition typical to the rest of the klf cluster ( see the top histogram of Fig 1B ) , or 52% characterizing the entire S . Infantis genome . To gain further insights into the biology of Ipf and Klf fimbriae , both clusters were cloned under an arabinose-inducible promoter in pBAD18 and introduced into a non-fimbriated E . coli ORN172 strain . Cultures that were grown in minimal medium to the late logarithmic phase in the presence of arabinose ( as inducer ) or glucose ( as suppressant ) were subjected to shearing by a shaft homogenizer . Filtered bacterial cell supernatant , enriched with surface exposed macromolecules was precipitated by trichloroacetic acid ( TCA ) and protein precipitates were separated by SDS-PAGE . Protein bands with the expected molecular weight of the fimbriae subunits , which were enriched in the arabinose-induced cultures were isolated from the acrylamide gel and analyzed by LC-MS/MS . This analysis successfully identified the presence of IpfD ( the putative adhesive lectin ) and three subunits of the Klf fimbria including KlfG ( major subunit ) , KlfE ( chaperone ) and KlfI ( minor subunit ) ( Fig 3 ) , indicating successful expression of these fimbrial components in the heterologous bacterial host . E . coli ORN172 expressing klfBCDEFGHIJKA under the arabinose promoter ( Para ) and ipfABCD under the tetracycline-inducible promoter ( PtetA ) were next imaged using transmission electron microscopy ( TEM ) and atomic force microscopy ( AFM ) . Using these high-resolution microscopy techniques , we were able to image the Ipf fimbriae , which appear as short and thin pili of about 1 . 5 nm thickness ( Fig 4A ) , and the Klf fimbriae that create a complex net of thin webs around the bacteria envelope ( Fig 4CI ) . These distinct apparatuses were absent from the non-inducible cultures ( Fig 4B and 4DI ) and demonstrated structurally diverse fimbriae encoded from the pESI megaplasmid . Many of the chaperone-usher fimbriae genes identified in E . coli and Salmonella are poorly expressed under regular laboratory growth conditions [24 , 25] and were shown to be tightly regulated and assembled in response to specific environmental stimuli [26] . To study the native regulation of the Ipf and Klf fimbriae in S . Infantis we examined their expression under different growth conditions in-vitro . First , we determined their transcription during growth in rich LB broth , believed to mimic some of the intestinal environmental conditions [27] and in N-minimal medium pH 5 . 8 and 7 . 0 , thought to mimic conditions found in the intracellular milieu [28] . Reverse-transcription real-time PCR ( RT-PCR ) analysis exhibited about 5-fold induction in the transcription of ipfC ( encoding the Ipf usher ) in cultures grown aerobically in rich LB broth relative to its transcription in minimal media ( pH 7 ) . In contrast , the transcription of klfD ( encoding the Klf usher ) was similar at rich and minimal media ( Fig 5A ) . Next we examined the transcription of Ipf and Klf fimbriae genes under aerobic vs . microaerobic conditions . All four Ipf genes ( ipfA , ipfB , ipfC and ipfD ) were found to be significantly induced under microaerobic conditions , when grown in LB to the stationary phase , compared to cultures grown to the stationary phase aerobically ( Fig 5B ) . Similarly , all of the Klf genes tested ( klfC , klfD , klfE , and klfG ) were also found to be significantly induced , when grown to the stationary phase under the microaerobic growth conditions ( Fig 5C ) , indicating that microaerobiosis is a potent stimulus for klf and ipf genes expression . Next , we investigated the expression of Ipf and Klf fimbriae during incubation at 27°C , 37°C and 41°C , corresponding to the temperatures of the environment , mammalian and avian hosts , respectively . Under growth in LB at 41°C , the transcription of ipfA , ipfB , ipfC and ipfD was upregulated by 4 , 4 . 5 , 2 . 5 and 3-fold respectively compared to the transcription at 37°C ( Fig 6A ) . Similarly , the transcription of klfC , klfD , klfE and klfG was elevated by 2 . 5 to 3 . 5-fold under these growth conditions ( Fig 6B ) . Consistent with these data , induction at 41°C was also demonstrated on the protein level as the expression of a 2HA-tagged version of IpfD was moderately higher at 41°C compared to 37°C . Even more so , considerably higher expression was exhibited for KlfC-2HA at 41°C compared to 37°C ( Fig 6C ) . We concluded from these experiments that both Ipf and Klf fimbriae are induced at microaerobic conditions and under 41°C , a set of conditions found in the avian intestines . Since the expression of both fimbriae was highly affected by microaerobic conditions , we sought to test a possible role of regulators known to be involved in oxygen homeostasis including OxyR , SoxR , ArcA , ArcB and FNR , [29] . In addition , we screened for potential regulatory roles of global regulators , previously reported to control Salmonella pathogenicity including RpoS , PhoP , OmpR and Fur [30] as well as the leucine-responsive regulatory protein ( Lrp ) that was shown to regulate different types of fimbriae in E . coli [31 , 32] and Salmonella [33] . To study klf expression , qRT-PCR was applied to determine the fold change in klfD transcription in the S . Infantis wild-type strain in comparison to ten relevant isogenic regulatory mutants . This analysis showed more than 5-fold decrease in klfD transcription in the absence of Fnr and Lrp when cultures were grown at 37°C to the stationary phase ( Fig 7A ) . Furthermore , sequence analysis of the klfB ( the first gene in the operon ) promoter region identified two putative Fnr binding sites ( TTGATTAAGATCTG and CTGATGCAGAGCAG ) , similar to the known Fnr box consensus determined in E . coli ( TTGATNNNNATCAA ) [34] , where N is any nucleotide and identical positions in the klfB promoter are highlighted in bold . Additionally , this region also includes 12 putative Lrp binding sites , all containing the consensus sequence GN ( 2–3 ) TTT recognized by Lrp [35] ( S1A Fig ) , suggesting direct binding of Fnr and Lrp to this region . To further characterize the potential role of the above regulators on the protein level , western blotting was used to determine the expression of a 2HA tagged version of KlfC in the wild-type relative to its expression in the above regulatory mutants at 37°C and 41°C . Although the expression of KlfC-2HA was significantly higher at 41°C than at 37°C , western blot analysis clearly demonstrated that the lack of LrP results in considerably lower amount of KlfC-2HA at both temperatures ( Fig 7B and 7C ) . Moreover , ectopic expression of lrp from a low copy-number plasmid in the lrp background , but not the presence of the empty vector ( pWSK29 ) , complemented the KlfC-2HA expression to similar levels as in the wild-type ( Fig 7D ) . In contrast to Lrp , we could not confirm any effect of Fnr on the expression of KlfC-2HA . Similar approaches were also taken to study ipf regulation . qRT-PCR analysis that was applied for ipfD exhibited a negative regulatory role for Fur and showed moderately ( two-fold or less ) lower transcription of ipfD in the absence of Lrp , RpoS , SoxR , PhoP , OmpR , and OxyR compared to the wild-type background ( Fig 7E ) . To confirm ipfD regulation on the protein level , the expression of IpfD-2HA in these mutant strains was further tested . While the potential role of some of these regulators was not confirmed by western blotting , this analysis clearly demonstrated , that IpfD-2HA is negatively regulated by Fur and that OmpR acts as a positive regulator of ipfD at 37°C ( Fig 7F ) and 41°C ( Fig 7G ) . Moreover , expression of Fur from a plasmid that was introduced into the fur background , resulted in significantly reduced IpfD-2HA expression relative to its expression in the fur strain ( Fig 7H ) . Fur repression is known to occur due to the binding of the Fur-Fe2+ complex to a 19-bp consensus site ( GATAATGATAATCATTATC ) found in the operator of a target promoters [36] . Thus , to further confirm Ipf regulation by Fur , we studied the expression of ipfA in the presence of a Fe2+chelator , Dip ( 2 , 2'-dipyridyl ) . As shown in Fig 7I , adding Fe2+ chelating agent to the growth media resulted in more than three-fold induction of ipfA transcription , suggesting that Ipf expression is suppressed by Fe2+ , likely via the Fur-Fe2+ complex . Consistent with these results in-silico ipfA promoter analysis identified putative imperfect 19-bp Fur binding site ( TAAAATGGTAATCAAATGA ) partially overlap with the -10 and the -35 sites in the ipfA promoter ( S1B Fig ) . This observation provides further support to the possibility that Fur directly regulates ipf genes expression . Collectively , we concluded from the above set of experiments that Lrp is an activator of the klf genes , and that the ipf operon is repressed by Fur and positively regulated by OmpR . The presence of the unique region at the 5'-end of the klf cluster encoding klfL and klfB was intriguing , since it was not found in any other klf–related cluster in the database . BlastP analysis of KlfL showed a weak similarity to a Mycobacterium transcriptional regulator ( WP_068209468 ) and KlfB was identical to a known regulator of the afimbrial adhesin AFA-III found in E . coli ( WP_033555783 ) and Salmonella ( WP_031619575 ) . In addition , KlfA , located at the 3'-end of the klf cluster , also presented some homology ( E-value 6e-14 ) to an uncharacterized S . enterica regulator ( WP_061433569 . 1 ) . Thus , the possible regulatory role of KlfL , KlfB and KlfA was studied next . In-frame null deletions were constructed for the three corresponding genes and the transcription of klfD was determined in these backgrounds compared to the S . Infantis wild-type strain . qRT-PCR showed more than twofold increase and twofold decrease in the transcription of klfD in the absence of klfL and klfB , respectively ( Fig 8A ) . These results were also confirmed on the protein level , where the amount of KlfC-2HA moderately decreased in the absence of klfB , but increased in the klfL backgrounds at 37°C ( Fig 7B ) . Lower expression of KlfC-2HA in the klfB background was even more evident at 41°C ( Fig 8C ) . We concluded from these analyses that KlfB and KlfL are positive and negative transcriptional regulators of the klf genes and that together with the core protein Lrp , are involved in the regulatory network , concerting the expression of the Klf fimbria . To study the expression pattern of the Ipf and Klf fimbriae in-vivo , reporter gene fusions between the regulatory regions upstream to ipfA and klfB with the luxCDABE operon were constructed . ipf::lux and klf::lux fusions were both cloned into pCS26 and introduced to the S . Infantis wild-type strain . These strains were used to infect streptomycin pretreated C57BL/6 mice and one day-old chicks by oral gavage . At one day post infection ( p . i . ) , the mice and the chicks were sacrificed and their entire gastrointestinal tract was imaged for luciferase activity . As shown in Fig 9 , both reporter strains colonized the mouse intestines to a similar extent ( Fig 9A and 9B ) . Nonetheless , while ipf::lux expression was clearly observed in the cecum and the colon of the infected mice ( Fig 9C ) , expression of klf::lux was hardly detected ( Fig 9D ) , suggesting low expression of the Klf fimbria in the murine host . Intriguingly , in the chick model , a distinct expression pattern of these reporter genes was exhibited , compared to the one found in the mouse . First , while klf::lux was not expressed in the mouse intestines , it was noticeably expressed in the chick cecum and to a lower extent in the colon ( Fig 10D ) . Secondly , although colonization in the chick and mouse cecum was similar ( 108−109 CFU ) , ipf::lux was expressed up to 150-fold higher in the chick cecum compared to the mouse ( 4435 vs . 29 photons S-1 cm-2 sr-1 ) . Collectively , these results suggest that at day one p . i . , both fimbriae are more induced in the chick model compared to the mouse . These results are in close agreement with the in-vitro data , showing induction of Klf and Ipf at 41°C vs . 37°C , corresponding to the body temperature of the avian and mammalian hosts , respectively . To elucidate the contribution of the Klf and Ipf fimbriae to the S . Infantis virulence in the mouse and chicken hosts , competition experiments were conducted . In these infections , equal numbers of the wild-type and the mutant ( klf or ipf ) strains were used to co-infect streptomycin pretreated C57BL/6 mice and one day-old White Leghorns chicks . Four and three days p . i . the mouse and the chicks , respectively , were sacrificed and the bacterial load ratio between the fimbriae mutants and the wild-type strain ( competitive index ) was determined . Since competing strains were marked with different antibiotic cassettes , carried on the same backbone plasmid ( pWSK29 for ampicillin and pWSK129 for kanamycin ) , a control group of mice was infected with the wild-type strains harboring pWSK29 or pWSK129 . In the mouse model , competitive index was calculated for the ileum , cecum and colon since these are the main sites of S . Infantis colonization [18] . Competitive infection with S . Infantis wild-type strains carrying pWSK29 ( Amp ) or pWSK129 ( Km ) showed equal colonization in the intestinal organs of the infected mice ( Fig 11A ) , indicating equal fitness for both marked strains in-vivo . Competitive infection of the wild-type vs . the klf null strain showed no role for Klf in the pathogenicity of S . Infantis in the mouse , as equal bacterial loads of the wild-type and the klf mutant were recovered from the cecum , colon and ileum ( Fig 11B ) . These results were not surprising , considering the very low expression of klf::lux in the mouse intestines . As for Ipf , while similar colonization was found for the wild-type and the ipf mutant strain in the cecum and colon , in the ileum , the ipf mutant was outcompeted by about 10-fold by the wild-type strain ( Fig 11C ) . These results suggested that Ipf plays a role in S . Infantis colonization in the mouse ileum , possibly due to its capability to bind a yet unknown host receptor expressed at mouse ileum tissues , but not at the murine cecum or the colon . Since we showed that the ambient temperature significantly affects the expression of the Ipf and Klf fimbriae , we were interested in characterizing their role in the chicken model , as its body temperature ( 41 . 2°C ) is higher than the one of mice ( ~36 . 9°C ) . Surprisingly , when these competitive index infections were reproduced in the chick model , a different phenotype was observed . ipf outcompeted the S . Infantis wild-type strain by about 5-fold in the duodenum , jejunum , ileum , cecum , colon , and liver ( Fig 11D ) . Similar results were also obtained for Klf , as the klf null strain outcompeted the wild-type in all of the tested organs by about 3-fold ( Fig 11E ) , indicating moderately elevated colonization of the strains lacking the Klf or the Ipf fimbriae in comparison to the wild-type strain . To further examine this phenotype , we performed single infection experiment and infected three groups of one-day old chicks with 7×105 CFU of S . Infantis wild-type , klf and ipf mutant strains . Five days p . i , the chicks were sacrificed and the bacterial load was determined in the cecum , ileum and colon . Consistent with the competition experiments , we found 4 to 83-fold higher numbers of the klf or the ipf mutant strains , than the wild-type S . Infantis background ( S2 Fig ) ; however , with seven chicks per group these differences did not reach statistical significance . Accumulatively , we concluded that while the Klf fimbria is dispensable for S . Infantis colonization or that Ipf is required for maximal ileum colonization in the mouse , the expression of both fimbriae , may contribute to restrained bacterial burden of S . Infantis during chick infection , possibly due to their immunogenic nature and innate immune response to their induced expression by S . Infantis .
Salmonella Infantis is one of the clinically prevalent serovars worldwide and the most commonly reported serovar in broilers in Europe [37] . In the last two decades , emergence of resistant S . Infantis clones has been reported in many countries including USA [21] , Belgium and France [38] , Germany [39] , Italy [20] , Hungary [40] , Japan [41] , Honduras [42] and Israel [19] . Our previews work established that the clonal emergence of S . Infantis in Israel involved the acquisition of the pESI megaplasmid [18 , 43] . More recently , related plasmids were also found to be associated with the increased prevalence of S . Infantis clones in other countries [20 , 21 , 44] , inferring that gaining these related megaplasmids may play an important role in the successful spread of S . Infantis . Besides antibiotic resistant genes , dozens of other ORFs , most of which with unknown functions are encoded on these plasmids and at least some of these ORFs are expected to significantly alter Salmonella interaction with the host [18] and its microbiota [43] . Here we imaged and elucidated the genetic organization , regulation and role in virulence of two novel chaperone-usher fimbriae encoded within pESI and demonstrated how they affect S . Infantis colonization in the chicken vs . the mouse hosts . Blast search against the S . Infantis genome indicates that the 119944 strain encodes at least twelve different chaperone-usher clusters , which is comparable with the number of chaperone-usher fimbriae harbored by other subspecies I serovars , containing on average twelve fimbrial gene clusters [10] . Nevertheless , the Ipf fimbria is rather unique and Ipf homologues were identified only in subsp . diarizonae and subsp . VII . Horizontal gene transfer of the ipf cluster from a distant origin may expand the ecological niches and host adaptation of S . Infantis carrying pESI . In contrast to the scarce distribution of Ipf , homologous clusters of the Klf fimbria were found in at least seven subsp . I serovars . Yet , a detailed comparison showed that despite the high conservation of the Klf proteins , KlfG is highly diverse . The KlfG homolog in ETEC , FaeG was shown to form the major structural component of the K88 fimbria that also mediates the adhesive properties of the fibers [45 , 46] . Allelic diversity in the major adhesive subunit , is likely to provide different binding properties as was previously shown for K88 variants in ETEC [23] and for FimH [13 , 47] . The mechanisms by which genetic variation occurs only in KlfG and not in the other subunits of the Klf fimbria that are highly conserved are still unknown . Another feature unique to the pESI-klf cluster is the insertion of two ORFs ( klfL and klfB ) in the 5'-region of the cluster that were found to act as klf genes regulators . These observations demonstrate two mechanisms of fimbria evolution , occurring by: ( i ) modification of a structural adhesive subunit ( KlfG ) and ( ii ) subordinating the fimbrial expression under newly acquired regulators . Besides KlfB and KlfL that were shown to act as positive and negative regulators , respectively , Lrp was established to positively regulate Klf expression . Lrp is a global regulator that can function as a repressor or activator of transcription , controlling the expression of numerous operons in E . coli and Salmonella [48] . In addition to operons involved in amino acid metabolism , Lrp was previously shown to regulate different fimbrial operons including pap ( P pilus ) and fan ( K99 ) [31] , fim [33 , 49] , sfa , daa [50] , as well as the nonfimbrial adhesin TosA in uropathogenic E . coli [32] . Interestingly , while Lrp was previously reported to negatively regulate the fae operon ( by cooperative binding with FaeA ) in E . coli [51] , here we showed that in S . Infantis , Lrp acts as an activator , indicating substantial differences in the regulatory setup between the fae genes in ETEC and the klf genes in S . Infantis . Such differences may be due to the differences in the ecology or lifestyle of these pathogens and the necessity to coordinate klf expression with other Salmonella virulence regulons such as Salmonella pathogenicity island 1 [52] . Like Lrp , other core global regulators including , Fur and OmpR were found to control ipf expression . Negative regulation of fimbria by Fur has been previously reported for the CFA/I fimbriae of ETEC [53] and type 3 fimbriae in Klebsiella pneumonia [54] . In many bacteria , Fur is generally involved in regulation of iron homeostasis genes , but it is also known to participate in bacterial colonization , oxidative stress response , toxin secretion and pathogenicity [55] . Under iron-abundant conditions , Fur-Fe2+ dimers bind to the Fur box in target promoters , which interfere with the binding of RNA polymerase and thus preventing transcription from these genes [56] . The fact that ipf expression is upregulated in the presence of an iron chelator and the identification of putative Fur box in the promoter of ipfA strengthen the possibility that Ipf regulation by Fur is direct . Derepression of ipf in the absence of Fur-Fe2+ is expected to contribute to the induction of this fimbria when S . Infantis is translocated from the environment ( or rich iron milieu ) to the host's small intestine , thought to be scarce in free ferrous [57] . While the regulatory role of Lrp , Fur and OmpR was shown both on the RNA and the protein levels , the absence of other regulators such as Fnr , PhoP and SoxR was more evident transcriptionally , but not on the protein level . This may occur due to indirect activity of these pleiotropic regulators and additional posttranscriptional regulatory mechanisms involved in the expression of klf and ipf genes . Also , the presence of secondary promoters and internal regulatory elements within the fimbria clusters cannot be excluded and requires further investigation . Besides iron availability , another environmental stimuli that were found to regulate the expression of both fimbria are microaerobiosis and elevated temperature of 41°C , characterizing the intestinal conditions of the avian hosts . Induction of fimbria expression under oxygen limitation was previously reported for the MR/P fimbria of uropathogenic Proteus mirabilis and type 1 fimbriae of uropathogenic E . coli [58] . Thermoregulation of fimbria expression has been shown for the BAV1965-1962 fimbrial locus of Bordetella avium , which was expressed at 37°C , but not at 22°C [59] . The 987P fimbriae of ETEC was also reported to be induced at 37°C and not when grown at lower temperatures [60] . In contrast , the expression of the F9 fimbriae in uropathogenic E . coli was shown to be repressed by H-NS at 37°C or 28°C and induced at 20°C , while mediating significant biofilm formation at the lower temperature [61] . Similarly , the E . coli Mat fimbria and curli fibers were also reported to be expressed strongly at 20°C [62 , 63] . These examples suggest that both temperature and oxygen concentration are used by different pathogens to sense the environment and regulate various fimbriae expression according to their location . Here we showed that both pESI-encoded fimbriae are induced in-vitro at 41°C compared to the ambient temperature ( 27°C ) or 37°C , suggesting that these fimbriae might be expressed differently according to the type of the infected host . In agreement with this idea , we showed significantly higher induction of Ipf and Klf in chicks compared to mice , differentiated by physiological temperature of 41 . 2°C and 37°C , respectively . Intriguingly , not only the expression profile was different between the chick and the mouse hosts , but also the contribution of these fimbriae to the infection varied between these hosts . While a klf mutant did not present any detectable phenotype in competitive infections in mice ( likely due to the lack of Klf expression in this host ) , this mutant strain colonized moderately better the chick intestines than the wild-type . A different , or even an opposite effect on colonization was also found for Ipf . Whereas an ipf mutant strain showed colonization deficiency in the ileum of mice , in the chick model it outcompeted the wild-type strain by about 5-fold . Superior colonization of the klf and ipf mutants in chicks is likely to occur due to a stronger innate immune response against these fimbriae in the chick vs . the mouse , possibly as a result of their induced expression in the former host . Function of these surface exposed structures as pathogen associated molecular patterns ( PAMPs ) and their recognition by the avian innate immune system is expected to result in a better infection control of the wild-type compared to the fimbria mutant strains . Consistent with this notion , are recent studies reported that FimH , the adhesive component of the type 1 fimbriae , is a potent inducer of innate antimicrobial responses mediated by TLR4 and type 1 interferon signaling in mice , and that FimH induces significant levels of NO production [64 , 65] . Thus , our working model proposes that the higher body temperature in the avian host leads to increased expression of the Ipf and the Klf fimbriae , which induces a stronger immune response against S . Infantis infection . Efficient immune response will result in lower colonization of the fimbriae-positive strain in chicks . We further speculate that stronger immune response against strains that express these fimbriae may restrain the acute infection by S . Infantis and support persistence in the bird . These results may explain the increased prevalence of the pESI or pESI-like positive stains in poultry as was previously reported [19 , 20] . It is well established that different composition of the fimbriome contributes to host tropism and that different fimbriae or even allelic variation within a particular fimbria can change the interaction of Salmonella with its host [13 , 47 , 66] . Our study demonstrates additional mechanism affecting fimbriae diversity . We showed here that fimbriae expression can be altered between hosts , most likely , in response to their physiological temperature . We suggest that by coordinating fimbriae expression according to the host temperature , Salmonella can express a different set of fimbriae in mammalian vs . avian hosts and by that shape the outcome of the infection . While moderate expression of a particular fimbria may facilitate colonization ( as was shown for Ipf in the mouse ileum ) , it is possible that higher expression may act as a two-edged sword that elicits stronger immune response . A robust immune response will restrain bacterial burden ( as was shown for Ipf and Klf in chicks ) , in a way that may facilitate a persistent infection .
Bacterial strains utilized in this study are listed in S4 Table . Bacterial cultures were routinely maintained in Luria-Bertani ( LB; Lennox ) broth ( BD Difco ) or in N-minimal medium containing 80 mM MES ( for pH 5 . 8 ) or 100 mM Tris-HCl ( for pH 7 . 0 ) , 5 mM KCl , 7 . 5 mM ( NH4 ) SO4 , 0 . 5 mM K2SO4 , 337 μM K2HPO4/KH2PO4 , 20 mM MgCl2 , 38 mM glycerol , and 0 . 1% Casamino acids as indicated and were plated onto LB or xylose lysine deoxycholate ( XLD; BD Difco ) agar plates . To chelate Fe2+ , 2 , 2'-dipyridyl ( Dip; Sigma-Aldrich ) was added to LB at final concentration of 0 . 2 mM . Aerobic cultures were inoculated in 2 ml medium and grown in 15 ml glass tubes with vigorous shaking ( 250 RPM ) . Microaerobic cultures were grown by diluting 1:100 over-day aerobic culture into 10 ml medium transferred into 15 ml tubes that were incubated for 16 h without shacking , with the lid loosely screwed in . When appropriate , antibiotics were added to the medium as follows: tetracycline ( 20 μg/ml ) , kanamycin ( 50 μg/ml ) , ampicillin ( 100 μg/ml ) and chloramphenicol ( 25 μg /ml ) . All primers used in this study are listed in S5 Table . Oligonucleotides were purchased from IDT and PCR was carried out using Phusion Hot Start Flex DNA Polymerase ( New England BioLabs ) or with ReddyMix PCR ( Thermo Scientific ) . All S . Infantis null mutants were constructed using the λ-red-recombination system and a three step PCR method to produce an amplimer containing the antibiotic resistance gene , as described in [67] . Resistant cassette was then eliminated from the genome by using a helper plasmid encoding the FLP recombinase [68] . For western blotting , a C-terminal two-hemagglutinin ( 2HA ) tagged version of KlfC from S . Infantis was cloned into pACYC184 cut with SalI and BglII and a 2HA C-terminal IpfD tagged was cloned into pWSK29 using SacI and XbaI . For expression of ipf and klf under arabinose inducible promoter , a PCR fragment containing the ipfABCD was obtained using the primers 'ipf pBAD Fw' and ' ipf pBAD Rv' and digested with SacI and XbaI . A PCR fragment containing klfBCDEFGHIJKA was obtained using the primers ' fae-k88 pBAD Fv' and ' fae-k88 pBAD Rv' digested with NheI and SacI . Both fragments were then cloned into pBAD18 . For fur and lrp complementation , the intact sequence of the two regulators was PCR amplified using S . Infantis 119944 as a template including their native regulatory regions containing 257 and 427 nucleotides upstream from the first methionine , respectively . fur was amplified using primers 'fur SalI Fw' and 'fur HindIII Rv' , digested with SalI and HindIII and cloned into pACYC184 . lrp was amplified using primers 'lrP SacI Fw' and 'lrp XbaI Rv' , digested with SacI and XbaI and cloned into pWSK29 . The pWSK29::lrp and pACYC184::fur were transformed into S . Infantis lrp and fur null mutant strains , respectively . For in-vivo imaging of ipf and klf expression , the regulatory region containing 421 and 396 nucleotides upstream from the first methionine of IpfA and KlfB , respectively was amplified with the primers 'ipf promoter XhoI Fw' and 'ipf promoter BamHI Rv' , and 'K88 promoter XhoI Fw' and 'K88 promoter BamHI Rv' , respectively , digested with BamHI and XhoI , and cloned into pCS26 . RNA was extracted from S . Infantis cultures grown under different conditions using the Qiagen RNA protect bacterial reagent and the RNeasy mini kit ( Qiagen ) according to the manufacturer's instructions , including an on-column DNase I digest . Purified RNA was retreated with an RNase-free DNase I followed by ethanol precipitation . 200 ng of DNase I-treated RNA was subjected to cDNA synthesis using the iScript cDNA synthesis kit ( Bio-Rad Laboratories ) . Real-time PCR and data analysis were performed as previously described [69] on a StepOnePlus Real-Time PCR System ( Applied Biosystems ) . The 16S rRNA gene was used as the endogenous normalization controls . Fold-differences in gene transcription were calculated as 2-ΔΔCt . Salmonella cultures were grown in LB to the stationary phase under microaerobic conditions at 37°C or 41°C , as indicated . The cultures were OD600 normalized , centrifuged , and pellets were resuspended in 1× sodium dodecyl sulfate-polyacrylamide gel electrophoresis ( SDS-PAGE ) sample buffer . Boiled samples were separated on 10% or 12% SDS-PAGE and transferred to a polyvinylidene fluoride ( PVDF ) membrane ( Bio-Rad Laboratories ) . Blots were probed with anti-HA tag antibody ( Abcam; ab18181 , diluted 1:1 , 000 ) ; anti-RpoD antibody ( Santa Cruz Biotechnology; SC56768 , diluted 1:2 , 000 ) or anti-DnaK ( Abcam; ab69617 , diluted 1:10 , 000 ) , when the marketing of the anti-RpoD antibody was discontinued by the manufacturer . Goat anti-mouse antibody conjugated to horseradish peroxidase ( Abcam; ab6721 , diluted 1:5 , 000 ) was used as a secondary antibody , followed by detection with enhanced chemiluminescence ( ECL ) reagents ( Amersham Pharmacia ) . The regulatory regions of ipf and klf were cloned into pCS26 upstream to a promoterless luxCDABE operon ( pCS26::Pipf and pCS26::Pklf , respectively ) and transformed into S . Infantis 119944 . The reporter strains were grown for 16 h in LB supplemented with kanamycin at 37°C and ~8×108 CFU were used to infect by oral gavage female C57BL/6 mice ( Envigo , Israel ) that were pretreated with streptomycin . Similarly , one day old SPF White Leghorns chicks ( Charles River ) were infected orally ( inter crop ) with ~1×107 CFU of the reporter strains in 0 . 2 ml saline . At 24h p . i . , mice and chicks were sacrificed and their intact gastrointestinal tracts were removed and imaged using a photon-counting in-vivo imaging system ( Photon-Imager , Biospace Lab or IVIS Lumina LT , PerkinElmer ) . To determine bacterial loads , the organs were homogenized in 0 . 7 ml saline using a BeadBlaster 24 homogenizer ( Benchmark Scientific ) , serially diluted and plated on XLD agar plates supplemented with kanamycin . Eight to ten week old female C57BL/6 mice ( Envigo , Israel ) were pretreated with streptomycin ( 20 mg per mouse in 100 μl HEPES buffer ) 24 h prior to infection . Mice were infected with ~6×106 CFU of a mixed ( 1:1 ) inoculum containing the wild-type S . Infantis ( harboring pWSK129; KmR ) and ipf or klf null mutant strain ( harboring pWSK29; AmpR ) . A mixed inoculum of two S . Infantis wild-type strains carrying pWSK29 or pWSK129 was used as a control . SPF eggs of White Leghorns chicks ( Charles River ) were incubated for 21 days at 37 . 4°C in SPF chicken isolators . One day after hatching , the chicks were orally ( inter crop ) infected with ~1×107 CFU of 1:1 mixed inoculum containing the wild-type S . Infantis ( harboring pWSK129 ) and ipf or klf null mutant strain ( harboring pWSK29 ) in 0 . 2 ml saline . The bacteria strains for both hosts were grown aerobically with the appropriate antibiotics for 16 h in LB at 37°C . Four and three days p . i . mice and chicks , respectively were sacrificed and the GI organs ( including the intestinal contents ) were collected on ice and homogenized in 0 . 7 ml saline . Serial dilutions of the homogenates were plated on XLD agar plates supplemented with ampicillin or kanamycin . CFUs were counted and the competitive index was calculated as [mutant/wild-type]output/[mutant/wild-type]input . A non-fimbriated E . coli ( ORN172 ) strains carrying the ipf operon ( pBAD18::ipf ) , the klf operon ( pBAD18::klf ) or the empty vector ( pBAD18 ) were grown aerobically overnight in LB supplemented with ampicillin at 37°C . The next day , the cultures were washed twice with N-minimal medium and diluted 1:50 into N-minimal medium pH 7 containing ampicillin ( 100 μg/ml ) , L-arabinose ( 50 mM ) or glucose ( 1M ) and grown for 6 h until reaching OD600 of 1 . OD600-normalized cultures were centrifuged and resuspended in 2 ml phosphate-buffered saline ( PBS ) . Surface exposed fimbriae were separated from the cells by mechanical shearing using a shaft blender ( three cycles of 1 min each ) . Cellular debris was removed by centrifugation ( 13 , 000 rpm , 5 min at 4°C ) , the supernatant was collected and filtered using a 0 . 22-μm filter ( Merck Millipore ) . The filtered supernatant was then precipitated in 10% Trichloroacetic acid ( TCA ) for overnight on ice . Precipitated fractions were recovered by centrifugation ( 13 , 000 rpm , 45 min at 4°C ) and the pellet was washed with 0 . 8 ml of ice-cold acetone . After acetone was removed , the pellet was air-dried for 10 min at room temperature in a fume hood and resuspended in 20 μl of 1× SDS-PAGE sample buffer . The boiled samples were separated on 12% SDS-PAGE followed by Coomassie Blue staining . Bands that were unique or significantly enriched relative to the negative control ( pBAD18 ) were cut from the gel and were subjected to mass spectrometry analysis at the Smoler Proteomic Center at the Technion , Haifa , Israel . The samples were digested by trypsin , analyzed by LC-MS/MS on LTQ-Orbitrap ( Thermo ) and identified by Discoverer 1 . 4 software using two algorithms: Sequest ( Thermo ) and Mascot ( Matrix science ) against the fimbrial subunits sequences and the E . coli proteome from the Uniprot database and a decoy database , in order to determine the false discovery rate ( FDR ) . High confidence peptides have passed the 1% FDR threshold . The ipfABCD operon was amplified by PCR using primers 1f-SIN-ipf and 1r-SIN-ipf . The product was cloned under the control of a tetracycline-inducible tetR PtetA promoter element on plasmid vector pWSK29 by Gibson assembly according to manufacturer´s protocol ( NEB ) . Detailed information about the cloning strategy is given in Hansmeier et al . ( 2017 , in revision ) . The plasmid was introduced into E . coli ORN172 strain and the culture was grown in LB supplemented with 50 μg/ml carbenicillin for overnight . To induce the fimbriae expression , an overnight culture was subcultured ( 1:31 ) in fresh LB medium supplemented with 50 μg/ml carbenicillin and 100 ng/ml anhydrotetracycline ( AHT ) and grown for 3 . 5 h . 150 μl of the subculture were applied on a cover-slip of 12 mm diameter , allowed to dry at air for 1 h , and washed four times with ddH2O before imaged by AFM . Measurements were performed under ambient conditions using the NanoWizard II AFM system ( JPK Instruments AG ) in the soft contact mode using silicon nitride AFM probes with a constant nominal force of 0 . 06 N/m ( SiNi , Budget Sensors , Wetzlar ) . Scan rates were set to 1 Hz and images were recorded at a resolution of 512 x 512 pixel . Representative height and deflection images are shown in false color . Using the JPK data processing software ( JPK Instruments AG ) all images were tilt corrected , polynomial fitted and unsharpened mask filtered . Images were adjusted for brightness and contrast using PhotoShop ( Adobe ) . Height measurements of Ipf fimbriae were made with the JPK data processing software of bacteria ( n = 18 ) from three individual replicates . For TEM imaging , 500 μl of the subculture grown as described before for heterologous expression analyses were pelleted for 5 min at 1 , 000 x g . The pellets were carefully resuspended in 500 μl ddH2O . 3 μl of bacterial suspension was dropped on formvar/carbo-coated TEM grids that were glow-discharged using the plasma cleaner ( Diener electronic ) shortly before preparation . Suspensions were left for 1 min to allow absorption of bacteria . Residual suspension was removed with a filter paper . Grids were negatively stained with 0 . 5% phosphotungstic acid , pH-adjusted to 7 . 4 , blotted with filter paper and finally air dried . TEM analysis was performed using a Zeiss 902 system operating at 50 kV . The pESI-encoded ipf and klf gene clusters were compared using the Easyfig tool ( http://mjsull . github . io/Easyfig/ ) with homologous clusters found in the nr database at NCBI . Promoter location including the -10 and -35 boxes was predicted by BPROM ( http://www . softberry . com/berry . phtml ? topic=bprom&group=programs&subgroup=gfindb ) . The Fnr , and Fur binding sites were predicted by the Virtual Footprint tool ( http://www . prodoric . de/vfp/vfp_promoter . php ) . Multiple sequence alignment of the KlfG homologs was performed using CLUSTALW ( http://www . ch . embnet . org/software/ClustalW . html ) and BOXSHADE 3 . 2 ( http://www . ch . embnet . org/software/BOX_form . html ) tools . The signal peptide sequence preceding the Sec cleavage site in KlfG was predicted by the SignalP 4 . 1 program ( http://www . cbs . dtu . dk/services/SignalP/ ) . Statistical analysis was performed using the GraphPad Prism 5 software package ( GraphPad Software , Inc , ) . Analysis of variance ( ANOVA ) with Dunnett's multiple comparison test was used to determine differences between multiple data sets . A student t-Test against a theoretical mean of 1 . 0 was used to determine statistical significance of the C . I values . P-value smaller than 0 . 05 was considered statistically significant and was indicated in the figures as follow: * , P <0 . 05; ** , P <0 . 01; *** , P <0 . 001; ns , not significant . Error bars show the standard error of the mean . Mice and chicks experiments were conducted according to the ethical requirements of the Animal Care Committee of the Sheba Medical Center ( Approval numbers 933/14 and 1059/16 , respectively ) and in line with the guidelines of the National Council for Animal Experimentation . | Salmonella enterica serovar Infantis is one of the prevalent serovars worldwide and is often associated with human gastroenteritis and asymptomatic persistence in poultry . Different emergent S . Infantis populations were shown to acquire a large virulence-resistance plasmid , named pESI . Here we imaged and investigated the phylogenetic distribution , regulation and the role in virulence of two previously uncharacterized pESI-encoded fimbriae , designated Klf and Ipf . We elucidate their complex regulatory network involving core ( ancestral ) and horizontally acquired regulators and demonstrated that their expression is significantly induced under microaerobic conditions and at 41°C compared to 37°C or the ambient temperature . Furthermore , we established that Klf and Ipf present a different expression profile and play a distinct role during mouse and chick infection , characterized by body temperature of 37°C and 41 . 2°C , respectively . Different composition of fimbriae or even allelic variation within a particular fimbria contributes to host tropism and can change the interaction of Salmonella with its host . Our work suggests additional mechanism , by which fimbriome expression is altered in response to the physiological temperature of different hosts . A distinct repertoire of expressed fimbriae is expected to affect Salmonella colonization and modify the host immune response to its infection . | [
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"e... | 2017 | The plasmid-encoded Ipf and Klf fimbriae display different expression and varying roles in the virulence of Salmonella enterica serovar Infantis in mouse vs. avian hosts |
Control and elimination of zoonotic diseases requires robust information about their effect on both human and livestock health in order to enable policy formulation and the allocation of resources . This study aimed to evaluate the cost-effectiveness of controlling Taenia solium taeniasis/cysticercosis in both humans and pigs , and soil-transmitted helminths ( STH ) in humans by integrating their control to on-going human and animal health control programmes in northern Lao People’s Democratic Republic . A cross-sectional study was carried out in 49 households , focusing on the prevalence of T . solium taenias/cysticercosis and soil transmitted helminths before and after a twelve month intervention . The village data was collected using a semi-structured questionnaire through a door-to-door survey . The village data was then projected to the wider northern Lao PDR population using stochastic modelling and cost-effectiveness ratio ( after aggregating the net cost to capture both human and animal health parameters ) and GDP per capita as a threshold , to determine the cost-effectiveness of the integrated control of T . solium taeniasis/ cysticercosis and STH , assuming linear scaling out of the intervention . The zoonotic DALY ( zDALY ) approach was also used as an alternative method of estimating the cost-effectiveness ratio of controlling T . solium taeniasis/cysticercosis in humans and pigs . Using cost-effectiveness analysis after aggregating the net cost and control of T . solium taeniasis/cysticercosis alone as the base case , the study found that simultaneous control of T . solium taeniasis/cysticercosis in humans and pigs , STH in humans and Classical Swine Fever ( CSF ) in pigs was USD 14 per DALY averted and USD 234 per zDALY averted using zDALY method hence considered highly cost-effective whereas controlling T . solium taeniasis/cysticercosis without incorporating STH and CSF was the least cost-effective ( USD 3 , 672 per DALY averted ) . Additionally , the cost-effectiveness of controlling T . solium taeniasis/cysticercosis in people and pigs using zDALY as an alternative method was USD 3 , 662 per zDALY averted which was quite close to our findings using the aggregate net cost method . The study showed that control of T . solium taeniasis/cysticercosis alone in humans and pigs is not cost-effective in northern Lao PDR whereas control of STH is . Consequently , integrating T . solium taeniasis/cysticercosis control with other cost-effective programmes such as STH and CSF markedly improved the cost-effectiveness of the intervention . This is especially important in low resource countries where control of zoonotic neglected tropical diseases could be integrated with the human and animal health sectors to optimize use of the limited resources . Australia New Zealand Clinical Trials Registry ( ANZCTR ) ACTRN12614001067662 .
Taenia solium taeniasis-cysticercosis complex is a zoonotic Neglected Tropical Disease ( zNTD ) found throughout many parts of Asia , Africa and Latin America , particularly where pigs and humans co-exist in areas of poor sanitation and hygiene [1–2] . Being the most important food-borne parasite worldwide and ranked fourth among all food-borne pathogens [3] , there is a growing requirement for improved understanding of the global burden and demonstration that control is cost-effective [4] . The World Health Organization ( WHO ) has promoted a scale up of T . solium taeniasis/cysticercosis control and elimination efforts by 2020 , buoyed by its status as one of six diseases identified as ‘potentially eradicable’ by the International Task Force for Disease Eradication [5] . Amongst other things , the task force recommends integrated control strategies , consideration of economic factors and assessment of the impact of mass drug treatment on co-endemic parasitic diseases such as soil-transmitted helminths ( STH ) to help promote support for eradication [5] . Following this , there is broad consensus that the economic analysis of zoonoses control programmes should be based on a holistic measurement of ‘total societal benefits’ as compared to simply calculating the total costs of controlling disease in humans and in animal reservoirs [6] . This requires an understanding of the level of integration [7–8] and comprehensive economics metrics to compare cost-effective control methods [9] . In the past , integrated control of neglected tropical diseases such as trachoma and primary healthcare [10] , schistosomiasis and STH using common drugs [11] , rabies in the animal health sector [12] among others have been attempted with varying results . Although , a policy of integrated control of neglected tropical diseases is highly beneficial [13–15] , studies on the cost-effectiveness of such an approach are rare [16] . This study aims to quantify the overall cost-effectiveness of a successful ‘rapid impact’ T . solium taeniasis/cysticercosis control programme that treated both pigs and humans , resulting in a significant ( p < 0 . 001 ) T . solium taeniasis/cysticercosis reduction of 77 . 4% over a sixteen-month period in a smallholder farming system in Southeast Asia typically characterized by reliance on family labour , small farm size , minimal input and low income [17] . Apart from the T . solium taeniasis/cysticercosis control program in Laos , other studies have shown that the prevalence of epilepsy in Lao PDR is 7 . 7 per 1 , 000 people [18] with high fatality rates [19–20] and low levels of healthcare [21–22] . To date , whilst models have suggested that a combined therapeutic approach in both pig and human hosts will result in the greatest sustained impact on parasite levels [23] , few research interventions have explored this concept in practice [24–25] . In this study we also evaluated combined human mass drug administration ( MDA ) , oxfendazole deworming of pigs and vaccination of pigs using TSOL18 and Classical Swine Fever ( CSF ) vaccines based on the holistic One Health intervention undertaken by Okello et al . ( 2016 ) [17] which aimed to optimize its total societal value through integration into existing district-level programmes driven by the Lao PDR Ministries of Health and Agriculture in the target area and carrying out joint activities . On the human side , this was achieved through two rounds of community mass drug administration ( MDA ) with a three day albendazole 400mg protocol to decrease the level of environmental contamination with tapeworm eggs and incorporate STH control and thus align with the Ministry of Health’s ongoing STH control objectives [26–27] . During the MDA , local government medical staff visited all participating households for five consecutive days administering drugs , monitoring for adverse reactions and carrying out screening exercises for epilepsy . The human health intervention excluded pregnant women and children less than six years old . The standard porcine anti-cysticercosis intervention ( which excluded pregnant or lactating pigs as well as those earmarked for sale ) , consisting of TSOL18 vaccination and oxfendazole ( OFZ ) at 30mg/kg [28–29] , also incorporated Classical Swine Fever ( CSF ) vaccination , an important porcine production-limiting disease in Southeast Asia [30] and a priority disease for the Lao PDR Ministry of Agriculture . Classical Swine Fever , especially genotype 2 . 2 , is endemic in northern Lao PDR and it is characterized by abortions and stillbirths of sows , as well as lack of appetite , anorexia , and high-mortality ( can reach 100% ) among nursery pigs [31–32] . It is hoped that this methodology and findings will help drive similar cost analyses for T . solium taeniasis/cysticercosis and other zNTD interventions , whilst simultaneously encouraging the consideration and inclusion of possible collateral benefits into control of other diseases under a true One Health approach . Consequently , to make this study have a wider applicability , a research question and null hypothesis were developed . The research question was ‘how does the inclusion of STH and CSF affect the cost-effectiveness of T . solium taeniasis/cysticercosis control ? ’ , and based on this question , the null hypothesis was that inclusion of STH and CSF has no significant impact on the cost-effectiveness of T . solium taeniasis/cysticercosis control . The base case was the T . solium taeniasis/cysticercosis control alone without inclusion of STH and CSF while the comparators were the T . solium taeniasis/cysticercosis control strategies that included STH and CSF .
The study was conducted in Mai district , Phongsaly province in the northern region of Lao PDR . The target area consisted of a homogenous Tai Dam population of around 400 people in 55 households , where the pre-intervention T . solium taeniasis/cysticercosis prevalence was found to be one of the highest recorded globally to date [33] . The Tai Dam are an ethnic group from northern Lao PDR , Vietnam , Thailand and China with strong cultural ties to animal sacrifice , using pigs , chickens and buffalo during various ceremonies and festivities that connect them with a higher spiritual world [34] . After seeking a written consent and conducting a door to door household census , a semi-structured questionnaire was used to determine household characteristics , pig productivity and human health parameters; including reporting on epilepsy through screening [35–36] in 49/55 ( 89 . 1% ) of village households . The initial baseline survey , conducted in October 2014 , included a 12 month recall for livestock productivity data regarding pig production . During the subsequent 18-month intervention [17] , economic monitoring occurred via every six months updates on changes in the village pig population ( births , deaths , sales , purchases etc ) , human health parameters , and response to both the human and pig interventions which were concurrently undertaken . The total societal view , where all resources are captured irrespective of who incurred or benefited from them , was central to cost computation in this study . The intervention strategies being compared in this study were: i ) T . solium taeniasis/cysticercosis alone in the human population ( the base case ) , ii ) T . solium taeniasis/cysticercosis and soil transmitted helminths ( STH ) in the human population , iii ) T . solium taeniasis/cysticercosis alone in the human and pig population , iv ) T . solium cysticercosis in the pig population and STH in humans , and v ) T . solium taeniasis/cysticercosis , STH and Classical Swine Fever ( CSF ) in humans and pigs . These interventions represented all the possible scenarios public health policy makers would face in regards to control of T . solium taeniasis/cysticercosis in Laos; intervention strategies two to five were the comparators . The questionnaire captured both monetary and time expenditures borne by village inhabitants ( private costs ) resulting from symptoms or disease associated with T . solium taeniasis/cysticercosis or STHs ( direct costs of health seeking treatment ) . The questionnaire also captured private costs incurred by smallholder farmers from pig rearing , via gross margin analysis of the pig enterprise in the target area . Public ( project ) costs were allocated to either the human or pig cost centres using a micro-costing approach [37] , enabling their analysis as a constituent of the overall project cost without double counting . Capital depreciation , which was the only capital cost , was estimated using the straight line method [38] and aggregated amongst the cost centres . Examples of the human intervention project cost centre included the cost of albendazole tablets , capital depreciation and logistical costs . The project costs incurred from the pig intervention included the cost of oxfendazole , TSOL18 and CSF vaccine , plus other recurrent expenditures . Also , secondary data such as cost of treatment and drugs were fitted to gamma distribution using the fitdistrplus package for R [39] and analysed using a Monte Carlo simulation to estimate the 95% uncertainty interval . For the purposes of analysis , the costs and benefits were divided into human ( non-monetary and monetary ) and pig ( monetary ) , although execution of both interventions was combined . DALYs represent the non-monetary human disease burden , calculated through combining the years of life lost due to premature death ( YLL ) and years lived with disability ( YLD ) [40–41] . The epidemiological parameters used for the DALY calculations of neurocysticercosis ( NCC ) and STH were obtained using a combination of empirical data derived from household questionnaires and secondary literature sources inputted into R software ( version 3 . 2 . 2 ) [42] . Preference was given to secondary data obtained from the study area or in other districts of Laos . However data from south-east Asia was used in cases where there was no information available in the study area or other parts of Laos . Since the accuracy of DALY estimates rely heavily on the information obtained for its computation , secondary data were fitted to uniform and beta distribution using the fitdistrplus package for R [43] and analysed using a Monte Carlo simulation , allowing for estimation of uncertainty to the DALY estimate [44] . Also , the discount rate and social weighting ( K and r values in the YLL equation ) were set at zero to allow for comparison with other studies and the burden of T . solium taeniasis/cysticercosis and STH averted was represented as DALY [0 , 0 , 0] [40] . A door-to-door survey [45] was undertaken to estimate the number of epilepsy cases in the target area , with the prevalence converted to incidence by dividing it by illness duration [46] . The proportion of epilepsy due to NCC was estimated using secondary data , given the study did not diagnostically confirm reported epilepsy cases . The estimated STH prevalence within the target area [27] was combined with STH prevalence data from other northern Lao PDR provinces [47–48] , then converted to incidence levels [48–49] . Tables 1 and 2 provide a summary of all epidemiological parameters that were used to estimate the non-monetary burden of T . solium taeniasis/cysticercosis and STH in the broader northern Lao PDR population . The animal arm of the zoonotic disease burden is represented in this case by pig livestock production losses , incorporating the costs of both livestock death and morbidity such as lowered fecundity , weight loss leading to a reduced sale price , or carcass condemnation due to the presence of cysts . Losses to the pig production enterprise were determined via a ‘livestock production’ section of the household questionnaire which evaluated the numbers of pigs bought ( including the prices they were bought ) , sold ( including prices they were sold ) , died ( including reasons for the death ) and born per household over the given time period . A second element considered the private ( borne by livestock keepers ) and public ( project ) animal health expenditure in terms of both time and money , expressed as a component of the variable costs . The gross margin ( expressed as the net benefit ) was then calculated to determine the change in household income pre and post intervention according to the standard formula: Gross margin = [livestock output]–[variable cost] [60] , where livestock output is defined as = [ ( animals and produce ‘out’ ) – ( animals and produce ‘in’ ) ] plus change in herd value . The change in herd value is expressed as [closing valuation ( the total number of pigs at the end of the year multiplied by their value ) —opening valuation ( the total number of pigs at the beginning of the year multiplied by their value ) ] . The value of the pig is a function of its weight which is correlated with its age and health status; a pig’s weight is influential in determining its selling or buying price . Typically younger pigs ( piglets and weaners ) cost less to buy and sell compared to older pigs ( growers , sows and boars ) . The value of the pigs which was not captured by the questionnaire was obtained from key informant interviews ( which composed of 12 farmers , 9 traders , 3 animal health technicians and 2 veterinarians ) by determining the most probable , minimum and maximum selling of each pig type and then using beta-PERT distribution in r software ( mc2d r package ) to determine the mean selling price in a smooth parametric distribution [42] . Variable costs include the costs of pig rearing incurred by the farmer plus any expenses of project participation ( for example repair of pig pens ) . The cost-benefit analysis was projected to the broader northern Lao population over the course of one year in order to estimate the cost-benefit of control at a regional level that would more accurately reflect future control programmes assuming linear scaling . The total human population in the four Northern provinces considered for this projection ( Phongsaly , Huaphan , Luang Prabang and Oudomxay ) was 1 , 141 , 785; comprising 572 , 211 females ( 0–4 years age group had 71 , 194 females , 5–14 years age group had 150 , 213 females , 15–44 years age group 261 , 812 females , 45–59 years age group had 54 , 544 females and over 60 years age group had 34 , 448 females ) and 569 , 574 ( 0–4 years age group had 71 , 766 males , 5–14 years age group had 154 , 355 males , 15–44 years age group had 258 , 017 males , 45–59 years age group had 53 , 540 males and over 60 age group had 31 , 896 males ) males [50] . The number of pig rearing households , total number of pigs in each province and the average number of pigs per household in each of the four provinces was obtained from the Lao agricultural census [61] . In the four northern Lao provinces there were a total of 104 , 700 pig rearing households and the total number of pigs was 351 , 200 . Computation of the gross margin per household entailed adjusting the income from the pig enterprise depending on the mean number of pigs per province , since the gross margin is highly dependent on the herd size . The overall capacity of a public health intervention to prevent unwanted human health outcomes ( such as mortality and prolonged morbidity resulting from disease presence ) may be indicated by the number of DALYs averted [62] . The total cost-effectiveness of this T . solium taeniasis/cysticercosis control programme , in relation to the total costs and benefits accrued in both the human and pig arms of the intervention , were evaluated using cost-effectiveness ratio a standard measure of cost utility analyses [63] . However , since the study had both costs from the agricultural and health sectors , the aggregated net cost was calculated by subtracting the reduced human health cost ( i . e . decrease in expenditure incurred by medical services , patients and their households ) , reduced animal health losses ( i . e . mortality , weight etc . ) , reduced animal health expenditure ( i . e . decrease in expenditure incurred by veterinary services and farmers ) from the project cost as shown in Eq 1 [61] . Where NC/DALY averted is the net cost per DALY averted for each intervention , CI is the total project cost ( in USD ) , REH is the reduced human health expenditure ( in USD ) , RLA is the reduced animal health losses , and RBH is the DALY averted . The zoonotic DALY ( zDALY ) was also used as an alternative approach to estimate the cost-effectiveness ratio of controlling T . solium taeniasis/cysticercosis [64–65] . Just like the aggregate net cost method , the zDALY also provides a framework for combining the human burden and the losses incurred by livestock keepers in single metric and it does this by considering the monetary impact on livestock keepers in terms of a time trade-off , in the sense of the value of people’s time required to recoup these losses , and by using gross domestic product ( GDP ) as a numéraire , it convert these into a non-monetary time unit called ‘animal loss equivalent’ ( ALE ) [65] . Equally , the reduced expenditure on health due to an intervention is converted into ‘health loss equivalent’ ( HLE ) . Another method for analysing total societal benefit of controlling zoonotic diseases is the separable cost method [16] . Although the main method used in this study was aggregated net cost , zDALY approach was also used to; i ) capture the cost of zDALY averted for T . solium taeniasis/cysticercosis , and ii ) costs per zDALY averted across all diseases rather than just for T solium utilising the ALE component of CSF . To estimate the cost-effectiveness of controlling T . solium taeniasis/cysticercosis , the study applied the WHO cost-effectiveness thresholds , which considers an intervention as ‘highly cost-effective’ if the cost per DALY averted is less than the country’s GDP per capita; ‘cost-effective’ if the cost per DALY is between one and three times the GDP per capita; and ‘not cost-effective’ if the cost per DALY exceed three times the country’s GDP per capita [66] . In Lao PDR the GDP per capita at the time of the study was USD 1 , 793 [67] . Nominal current ( year 2015 without adjusting for price inflation ) market prices were used throughout for both disease control costs and livestock production costs and returns , thus reflecting the realities facing the health and veterinary services , pig producers and human patients in Lao . Accordingly the GDP value selected was also the nominal , or Atlas value , rather than being in international dollars adjusted for purchasing power parity . Ethical approval for this study was granted by the Lao PDR Council of Medical Science National Ethics Committee for Health Research ( NECHR ) , approval number 013/NECHR , and Australia’s Commonwealth Scientific and Industrial Research Organisation ( CSIRO ) Animal , Food and Health Sciences Human Research Ethics Committee ( CAFHS HREC ) , approval number 13/10 . The study was registered with the Australia New Zealand Clinical Trials Registry ( ANZCTR ) , trial number ACTRN12614001067662 .
From a total of 55 target area households , 49 ( 89% ) were included in the study; six households had relocated during the course of the study , hence were not included in the final calculations . The total number of people in the 49 households was 375 comprising 178 males ( 0–4 years age group had 20 males , 5–14 years age group had 45 males , 15–44 years age group 85 males , 45–59 years age group had 18 males and over 60 years age group had 10 males ) and 197 females ( 0–4 years age group had 27 females , 5–14 years age group had 55 females , 15–44 years age group had 86 females , 45–59 years age group had 18 females and over 60 age group had 11 females ) . According to information obtained from key informant interviews , all pigs were left to roam freely , with the larger ones penned during the rice harvesting season . Questionnaires indicated the average weight of sold pigs was around 23 kilograms ( kg ) and the price of pork around USD 3/kilogram . Out of the 49 households , 41 ( 83% ) did not have toilets , whereas 8 ( 16% ) had toilets and used them . The baseline pig population in the target area was 270 , with a mean number of 5 . 2 ( standard deviation 4 . 9 ) pigs per household . The herd structure consisted of 28 boars ( 10% ) , 64 sows ( 24% ) , 53 weaners ( 20% ) , 32 growers ( 12% ) and 93 ( 34% ) piglets . Post intervention , pig numbers had increased by 53% to 414 , with a mean number of 8 . 4 ( SD 6 . 1 ) pigs per household . Changes in the herd structure , particularly in the grower category , were evident with 27 boars ( 7% ) , 74 sows ( 18% ) , 34 weaners ( 8% ) , 182 growers ( 44% ) and 97 piglets ( 23% ) post intervention ( Fig 1 ) . Before intervention , mortality was 48 . 3% ( 185/386 ) comprising of 138 piglets , 32 weaners , 7 growers , 5 sows and 3 boars . After the intervention the mortality dropped to 8 . 4% ( 37/440 ) comprising of 16 piglets , 9 weaners , 6 growers , 3 sows and 3 boars . There were 386 responses on the reasons for death and these were mentioned as follows; diseases ( 69% ) , lack of feed ( 13% ) , accidents ( 1% ) , dog bites ( 2% ) , poisoning ( 1% ) , gunshot wounds ( 1% ) , and piglets dying from low milk supply from sow during lactation ( 1% ) and still birth ( 12% ) . By estimating the human MDA coverage to be 63% [27] of 622 , 960 eligible participants over 4 years old , the total annual cost of MDA across all 4 Northern provinces was estimated to be USD 5 , 606 , 640 . In the agricultural sector , the regional cost of treating pigs using TSOL18 , CSF and OFZ was estimated to be USD 3 , 476 , 213 , USD 3 , 125 , 013 and USD 3 , 722 , 053 respectively; totalling USD 10 , 323 , 279 . Combining these figures resulted in a total project cost of USD 15 , 929 , 919 for the simultaneous control of T . solium taeniasis/cysticercosis , STH and CSF in the broader northern Lao PDR region . By subtracting the livestock benefits ( increased gross margin from pig enterprise and decreased value of condemned pork ) and the averted cost in health expenditure from the project cost , the total cost from TSOL18 , OFZ , CSF and human MDA was USD 833 , 785 . Subsequently , the net cost-effectiveness of simultaneously controlling T . solium taeniasis/cysticercosis , CSF and STH was USD 14 per DALY averted . By computing the cost-effectiveness of T . solium taeniasis/cysticercosis control in the human population without integrating STH , and T . solium taeniasis/cysticercosis and STH ( without addressing the pig population ) , the net cost-effectiveness of these approaches would be USD 1 , 609 and USD 93 per DALY averted respectively . By incorporating the pig intervention ( TSOL18 and OFZ ) with T . solium taeniasis/cysticercosis control only , the net cost-effectiveness was projected to be USD 3 , 672; by using the same regime but including STH in the calculations , the net DALY averted is USD 214 . Table 7 provides a summary of the net cost per DALY averted for each of the T . solium taeniasis/cysticercosis control approaches . By comparing the cost per DALY averted for each intervention approach with the Lao PDR GDP per capita as a measure of cost-effectiveness , it was found that the highly cost-effective approaches were i ) control of T . solium taeniasis/cysticercosis in the human and pig populations , incorporating both CSF and STH control ( 14 USD/DALY averted ) ii ) control of T . solium taeniasis/cysticercosis and STH in the human population only ( 214 USD/DALY averted ) and iii ) control of T . solium taeniasis/cysticercosis in both the human and pig populations , incorporating STH control ( 93 USD/DALY averted ) . Control of T . solium taeniasis/cysticercosis only ( 1 , 609 USD/DALY averted ) was found to be cost-effective while the least cost-effective approach was incorporating the pig intervention ( TSOL18 and oxfendazole ) with T . solium cysticercosis control only ( 3 , 672 USD/DALY averted ) . Using zDALY approach , ALE for controlling T . solium taeniasis/cysticercosis was 13 and the HLE was 6 . By adding DALY averted , which in this case was 3 , 478 as estimated in Table 7 , ALE and HLE , the T . solium taeniasis/cysticercosis zDALY was 3 , 497 . To compute the cost-effectiveness ratio of controlling T . solium taeniasis/cysticercosis in people and pigs without incorporating STH and CSF , the project cost ( USD 5 , 606 , 640 as estimated in Table 7 ) was divided by the zDALY yielding USD 3 , 662 per zDALY averted . Also , to compute the overall cost effectiveness ratio of combined control of all the three diseases ( T . solium taeniasis/cysticercosis , STH and CSF ) , the ALE , HLE and DALY averted were totaled to determine the zDALY . Livestock benefit in terms of ALE was found to be 8 , 398 , the HLE was 21 and the DALY averted was 59 , 556 , thus the zDALY was 67 , 975 and the cost effectiveness ratio for the combined control of all the three diseases was USD 234 per zDALY averted; representing 13% of Laos per capita GDP and this was well within the WHO’s threshold of very cost-effective interventions . Sensitivity analysis using partial correlation coefficients showed that prevalence , mortality rate and disability weights were very influential in the disease burden models . For example , the prevalence of NCC , mortality rate , disability weight of the untreated , prevalence rate of epilepsy and disability weight of the epilepsy cases treated were the most influential in modelling the burden of T . solium taeniasis/cysticercosis as shown in Fig 2 .
Although methods to estimate the costs of zoonotic disease to both livestock productivity and humans have been proposed [68–69] , there has been no totally satisfactory conceptual framework for analyzing the total societal burden of zoonotic disease; that is the combined costs of disease from both the humans and animals [70] . The recently developed concept of the zDALY addresses this gap [65] . This study had both zoonotic ( T . solium cysticercosis ) and non-zoonotic ( STH and CSF ) diseases . T . solium cysticercosis as a zoonotic disease had YLL , YLD , HLE and ALE components of burden of disease , while STH as a non-zoonotic disease had YLL , YLD and HLE components . Given CSF is an animal disease it only had the ALE metric . Therefore based on the YLL , YLD , HLE and ALE disease burden metrics both aggregate net cost and zDALY approaches were used to estimate the changes in cost effectiveness ratio when externalities generated by treatment of T . solium taeniasis/cysticercosis are included . The aggregate net method revealed that the ‘highly cost-effective’ approach for northern region of Lao PDR is the combined human-animal approach incorporating T . solium taeniasis/cysticercosis control with two additional diseases; STH and CSF control ( USD 14 per DALY averted ) and zDALY approach corroborated this finding given the overall cost effectiveness ration of controlling all the three diseases ( T . solium taeniasis/cysticercosis , STH and CSF ) was USD 234 per zDALY averted representing 13% of the GDP per capita falling well within WHO’s threshold of very cost-effective interventions . Other cost-effective approaches included the human MDA intervention targeting both T . solium taeniasis/cysticercosis and STH ( USD 93 per DALY averted ) , and the combined human-pig intervention that targeted both T . solium taeniasis/cysticercosis and STH ( USD 214 per DALY averted ) . The least cost-effective intervention approaches were those that addressed T . solium taeniasis/cysticercosis in isolation , regardless of whether this was in the human population ( USD 1 , 609 per DALY averted ) , or jointly with an intervention in the pigs ( USD 3 , 672 per DALY averted ) . Consequently , the results show that control of T . solium taeniasis/cysticercosis alone in humans and pigs is not cost-effective whereas control of STH in humans is . Also , the results obtained from using zDALY approach confirmed that it is not cost-effective to control T . solium taeniasis/cysticercosis alone in humans and pigs without incorporating STH and CSF in northern Lao; zDALY metric was very close to the findings from the aggregate net cost method . Also , the null hypothesis was rejected given that addition of STH and CSF markedly improved the overall cost effectiveness of controlling T . solium taeniasis/cysticercosis . Therefore , this study concluded that integrating T . solium taeniasis/cysticercosis control with other cost-effective programmes is recommended to effectively control it in Laos . Information obtained from the semi-structured questionnaire supported previous findings that revealed smallholder pig rearing to be an important farming activity in the study area as also revealed by Bardosh et al ( 2014 ) [71] . The intervention resulted in improved pig productivity , seen as an increase in the average number of pigs reared per household from 5 . 2 to 8 . 4 after 12 months of the intervention , and a reduction in pre-weaning mortality from 48 . 3% to 8 . 4% due to CSF vaccination; low mortality was probably the main course of increased number of growers as most piglets were surviving and reaching this age . Apart from CSF vaccination , deworming of pigs ( especially free ranging ones ) with OFZ potentially played a role in improving the overall cost effectiveness of the intervention by protecting pigs from new T . solium cysticercosis infections thus protecting humans; as well as improving the health of pigs as it has an effect on nematode infections which are a source of disease and production losses . These results corresponded to the increased gross margin from the pig enterprise; remarkably the greatest production age increase was seen in growers , from 12% to 44% of the overall herd composition , highlighting the importance of integrating disease interventions into future pig productivity improvement projects . In the study area , the combination of animal health interventions with the availability of improved feeding , which had been established prior to the intervention , allowed farmers to take full advantage of the production capacity of their livestock , once animal health had been restored . Although the human health benefits alone fully justify the investment as demonstrated through the economic impact of averted DALYs , the combination of such an intervention with improved production approaches adds considerable value to the overall intervention . It might also give an additional incentive to farmers if the effect is large enough for them to notice the production–and in consequence economic–benefit . Also , vaccinating pigs with TSOL18 ensured a lifetime immunity to T . solium cysticercosis for pigs , reducing the risk of acquiring infection long term . This study has shown that the inclusion of approaches that are effective against pig production diseases such as CSF has played a major role in increasing the cost-effectiveness in regions where T . solium cysticercosis and CSF are co-endemic . To achieve high cost-effectiveness in future , pig vaccination against T . solium cysticercosis could be done together with CSF or an equivalent bivalent ‘One Health’ vaccine developed for regions where CSF is endemic; T . solium cysticercosis does not typically affect pig productivity , it will be difficult to convince farmers to pay for T . solium cysticercosis vaccine unless they are likely to be penalized for cystic pork . Equally , where meat inspection practices are not well managed , T . solium cysticercosis interventions should focus on diseases or management practices that decrease pig mortality ( pre-weaning mortality in particular ) , so as to achieve a higher survival rate and thus increase the overall livestock productivity benefits of the T . solium cysticercosis intervention . There is a need for sharing resources between agricultural and health sectors , especially where the inclusion of secondary diseases such as STH and CSF play a major role in the benefits accrued to each sector . Joint disease control is a critical component of enhancing household health , wealth and overall wellbeing , given the biggest beneficiaries are the affected households . Unfortunately , integrated sectoral approaches under the One Health movement are rare , despite an acknowledged need to tackle societal problems such as zNZDs in a comprehensive manner [72] . A major reason observed for the lack of sustainable One Health approaches in veterinary public health is related to the concept of who should fund what , particularly where cost sharing between sectors is expected . However , this study clearly demonstrates that integrated actions at a larger scale are significantly more cost effective than ‘vertical’ disease approaches that address issues individually , and thus should be the guiding principle for addressing future T . solium taeniasis/cysticercosis interventions , or those against the zNTDs more generally . This study has limitations , the primary observation being the large amount of secondary data used to simulate and estimate the cost-effectiveness of controlling T . solium taeniasis/cysticercosis , STH and CSF in the northern Lao region after assuming a linear scaling out of the intervention . The use of significant secondary data sources is not without precedent for estimations of T . solium taeniasis/cysticercosis burden [73–74] , and highlights the current dearth of data globally for this disease resulting from and contributing to its neglected status . Further studies are needed to establish the T . solium taeniasis/cysticercosis , STH and CSF prevalent regions in northern Lao PDR , or indeed the broader southeast Asia region more generally; it would be prudent to focus initially on potential hyper-endemic T . solium taeniasis/cysticercosis ‘hotspots’ , identified by a combination approach of both social and epidemiological methods . A second limitation , when looking at the aggregated societal benefits and the net monetary benefit , high livestock benefits may mean that monetary benefits exceed monetary costs . This would show that the programme is dominant: effective and cost-saving; in this situation , calculating incremental cost-effectiveness ratio is not relevant . This is a difficult result to interpret , or rank , and could have the unwanted effect of skewing the allocation of cost entirely towards the livestock sector , since livestock benefits outweigh costs . This would be a particularly unhelpful outcome , as the strength of this intervention is that it simultaneously deals with both the human and livestock disease reservoirs , resulting in greater sustainability . However other methodologies such as zDALY can be used to estimate monetary losses in livestock which can then be incorporated into the DALY estimate particularly if the intervention only involves zoonotic diseases . Other limitations include use of the village data with small sample size , use of data from a hyper-endemic foci to project the cost effectiveness of the intervention and lack of definitive diagnosis of NCC . Consequently the attribution of NCC to epilepsy in northern Lao PDR might be lower than stated in this study and further studies are needed to find out if this is the case and whether more T . solium taeniasis/cysticercosis hyper-endemic foci exist in northern Lao PDR . However , information obtained from the study area coupled with the sensitivity analysis on the assumptions used to estimate the DALY provides a good basis of understanding the impact of simultaneously controlling T . solium taeniasis/cysticercosis , STH and CSF .
Control of T . solium taeniasis/cysticercosis in the northern Lao PDR is currently heavily dependent on therapeutic interventions in the human or pig populations–ideally both–to reduce the disease prevalence . However , sustainable control of T . solium taeniasis/cysticercosis should not be taken in isolation; incorporating the control of other pig production diseases ( such as CSF ) and/or soil transmitted helminth control is recommended to maximize the intervention cost-effectiveness . This is especially true for interventions that the farmer is expected to pay for; incorporating production-impacting diseases into T . solium taeniasis/cysticercosis control will incentivize farmers to pay for its control . This cost-effectiveness analysis clearly shows that controlling T . solium taeniasis/cysticercosis in isolation is not cost effective , and more holistic , innovative methods to build zNTD control into existing human health or livestock production and development programmes would be beneficial . | A study was conducted in northern Lao PDR to ascertain the cost-effectiveness of controlling Taenia solium ( T . solium taeniasis/cysticercosis ) using five approaches namely: i ) T . solium taeniasis/cysticercosis alone in the human population ( the base comparator ) , ii ) T . solium taeniasis/cysticercosis and soil transmitted helminths ( STH ) in the human population , iii ) T . solium taeniasis/cysticercosis alone in the human and pig population , iv ) T . solium taeniasis/cysticercosis in the pig population and STH in humans , and v ) T . solium taeniasis/cysticercosis , STH and Classical Swine Fever ( CSF ) in humans and pigs . Using cost-effectiveness ratio ( after aggregating the net cost and using zDALY approach as an alternative method ) , the study found that the simultaneous control of T . solium taeniasis/cysticercosis , STH and CSF in human and pig population was USD 14 per DALY averted and USD 234 per zDALY averted thus considered highly cost-effective whereas control of T . solium taeniasis/cysticercosis alone in the human and pig population was the least cost-effective as it was found to be USD 3 , 672 per DALY averted using the aggregate net cost method and USD 3 , 662 using the zDALY approach , . We concluded that inclusion of STH and CSF to T . solium taeniasis/cysticercosis mitigation efforts drastically improved the overall cost-effectiveness of the intervention in northern Laos where all the three diseases are endemic . | [
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"epile... | 2018 | Improved methods to capture the total societal benefits of zoonotic disease control: Demonstrating the cost-effectiveness of an integrated control programme for Taenia solium, soil transmitted helminths and classical swine fever in northern Lao PDR |
We present a framework for designing cheap control architectures of embodied agents . Our derivation is guided by the classical problem of universal approximation , whereby we explore the possibility of exploiting the agent’s embodiment for a new and more efficient universal approximation of behaviors generated by sensorimotor control . This embodied universal approximation is compared with the classical non-embodied universal approximation . To exemplify our approach , we present a detailed quantitative case study for policy models defined in terms of conditional restricted Boltzmann machines . In contrast to non-embodied universal approximation , which requires an exponential number of parameters , in the embodied setting we are able to generate all possible behaviors with a drastically smaller model , thus obtaining cheap universal approximation . We test and corroborate the theory experimentally with a six-legged walking machine . The experiments indicate that the controller complexity predicted by our theory is close to the minimal sufficient value , which means that the theory has direct practical implications .
The goal of this article is to provide a framework that allows us to determine the complexity of a control architecture in accordance with the cheap design principle from embodied artificial intelligence [1 , 2] . Cheap design in this context refers to the relatively low complexity of the brain or controller in comparison with the complexity of an observed behavior . A classical example is given by the Braitenberg vehicles [3] , which are Gedankenexperiments designed to show how a seemingly complex behavior can result from very simple control structures . Braitenberg discusses several artificial creatures with simple wirings between sensors and actuators . He then describes how these systems produce a behavior that an external observer would classify as complex if the internal wirings were not revealed . Most interestingly , he then relates the wiring of his vehicles to various neural structures in the human brain . The idea of a simple wiring that leads to complex behaviors is also discussed in [1 , 2] , who present the walking behavior of an ant as an example . Without taking the embodiment and , in particular , the sensorimotor loop into account , the complex behavior ( of a complex morphology ) seems to require a complex control structure [2] . A strong indication that cheap design is a common principle in biological systems is given by the fact that the human brain accounts for only 2% of the body mass but is responsible for 20% of the entire energy consumption [4] , which is also remarkably constant [5] . Further support for cheap design as a common principle is given by a recent study on the brain sizes of migrating birds . It is known that migrating birds have a reduced brain size compared with their resident relatives . Sol et al . [6] have studied various species and the affected brain regions and point out that the reduced brain sizes could be a direct result from the need to reduce energetic , metabolic and cognitive costs for migrating birds . It is generally believed that cheap design of control architectures is possible whenever the morphology of the system can contribute to the control of behaviors , which is referred to as morphological computation [7 , 8] . This kind of computation can be illustrated in the context of the human walking behavior , which only needs to be actively controlled during the stance phase . The swing phase results mainly from the interaction of the physical properties of the leg with the environment ( gravity ) . This is demonstrated by the Passive Dynamic Walker [9] , which is a purely mechanical system that resembles the physical properties of human legs . The human walking behavior is emulated as a result of the interaction of the mechanical system with its environment ( gravity and a slope ) . It is an extreme example of cheap design that requires no active control at all . Morphological computation has been identified as a prime concept within the field of embodied cognition about two decades ago [7] . However , only recently one has begun to develop a theoretical understanding of this concept [10–15] . Currently , the field does not provide sufficiently conclusive definitions that would allow us to analytically reveal the design principles of cheap control based on high values of morphological computation . Experimental evidence of such a coupling has been provided in evolutionary settings . For instance , the work of Auerbach and Bongard [16] shows that complex environments increase the selection pressure for complex morphologies , given a low-complexity controller . This suggests an evolutionary coupling between morphological computation and cheap design . We are interested in quantifying to what extent a control structure can be reduced if the physical constraints are taken into account . Above , we referred to a system as cheaply designed , if it has a control structure of low complexity that produces behaviors which an external observer would classify as complex . In this work , we are not concerned with the complexity of the behavior . Instead , we present an approach to determine the minimal complexity of a control structure that is able to produce a given set of desired behaviors with a given morphology in a given environment . In other words , rather than comparing the complexities of the control structure and the behavior , we ask: what is the minimal brain complexity ( or size ) that can control all ( desired ) behaviors that are possible with the body in a given environment ? We follow a bottom-up–understanding by building–approach to cognitive science [17] , which is also known as behavior-based robotics [18] and embodied artificial intelligence [1 , 2] . The core concept is that cognitive systems are considered as embedded and situated agents which cannot be understood if they are detached from the sensorimotor loop . This implicitly means that we assume sensor state sparsity and continuity of physical constraints . Consider the human retina as an example . We do not see random images but structured patterns and , moreover , the sequence of these patterns is also highly dependent on our behavior . This behavior-dependent structuring of information is also known as information self-structuring and has been identified as one of the key principles of learning and development [19 , 20] . The second implication from the sensorimotor loop is continuity , e . g . natural systems are unable to teleport themselves from one place to another . Therefore , we can safely assume that the world around us will not be too different from the recent past and the recent future . The sensorimotor loop ( SML ) [21 , 22] is described by a type of partially observable Markov decision process ( POMDP ) where an embodied agent chooses actions based on noisy partial observations of its environment . An illustration of this causal structure is given in Fig 1 . We aim at optimizing the design of policy models for controlling these processes . One aspect of the optimal design problem is addressed by working out the optimal complexity of the policy model . In particular , we are interested in the minimal number of units or parameters needed in order to obtain an artificial neural network that can represent or approximate a desired set of behaviors . A first step towards resolving this problem is to address the minimal size of a universal approximator of policies . In realistic scenarios , universal approximation is out of question , since it demands an enormous number of parameters , many more than actually needed . In this paper we reconsider the universal approximation problem by exploiting embodiment constraints and restrictions in the desired behavioral patterns . We introduce the notions of embodied behavior dimension and embodied universal approximation , which quantify the effective dimension of a system that is subject to sensorimotor constraints ( embodiment ) and formalize the minimal control paradigm of cheap design in the context of the sensorimotor loop . We substantiate these ideas with theoretical results on the representational capabilities of conditional restricted Boltzmann machines ( CRBMs ) as policy models for embodied systems . CRBMs are artificial stochastic neural networks where the input and output units are connected in a bipartite and undirected manner to a set of hidden units . Given the embodied behavior dimension , we derive bounds on the number of hidden units of CRBMs that is sufficient to generate a set of behaviors by appropriate tuning of interaction weights and biases . In order to test our theory , we present an experimental study with a six-legged walking robot and find a clear corroboration . The experiments indicate that the sufficient controller complexity bounds predicted by our theory are tight , which means that the theory has direct practical implications . CRBMs are defined by clamping an input subset of the visible units of a restricted Boltzmann machine ( RBM ) [23 , 24] . Conditional models of this kind have found a wide range of applications , e . g . , in classification , collaborative filtering , and motion modeling [25–28] , and have proven useful as policy models in reinforcement learning settings [29] . These networks can be trained efficiently [30 , 31] and are well known in the context of learning representations and deep learning [32] . Although estimating the probability distributions represented by RBMs is hard [33] , approximate samples can be generated easily from a finite Gibbs sampling procedure . The theory and in particular the expressive power of RBM probability models has been studied in numerous papers [34–37] . Recently also the representational power of CRBMs has been studied in detail [38] . CRBMs can model non-trivial conditional distributions on high-dimensional input-output spaces using relatively few parameters , and their complexity can be adjusted by simply increasing or decreasing the number of hidden units . Hence we chose this model class for illustrating our discussion about the complexity of SML control problems . This paper is organized as follows . Section “The Causal Structure of the Sensorimotor Loop” contains a description of the sensorimotor loop . Section “From Policies to Behaviors” presents the notions of embodied behavior dimension and embodied universal approximation . In section “Cheap Representation of Embodied Behaviors” we use these two notions in order quantify and enforce dimensionality reduction . Section “A Case Study with Conditional Restricted Boltzmann Machines” contains our theoretical discussion on the representational power of CRBM models , comparing the non-embodied and the embodied settings . Section “Experiments with a Hexapod” validates the theory experimentally . In “Discussion” we offer our conclusions and outlook . In the Supporting Information S1–S4 Videos show the walking hexapod controlled by four CRBMs of different complexity , S1 Text contains technical proofs , S2 Text contains details about the estimation of the embodied behavior dimension , and S3 Text discusses possible generalizations of the ideas presented in the main part of the paper .
What is an embodied agent ? In order to develop a theory of embodied agents that allows us to cast the core principles of the field of embodied intelligence into rigorous theoretical and quantitative statements , we need an appropriate formal model . Such a model should be general enough to be applicable to all kinds of embodied agents , including natural as well as artificial ones , and specific enough to capture the essential aspects of embodiment . How should such a model look like ? First of all , obviously , an embodied agent has a body . This body is situated in an environment with which the agent can interact , thereby generating some behavior . In order to be useful , this behavior has to be guided or controlled by the agent’s brain or controller . Drawing the boundary between the brain on one side and the body , together with the environment , on the other side suggests a black box perspective of the brain . The brain receives sensor signals from and sends effector or actuator signals to the outside world . All it knows from the world is based on this closed loop of signal transmission . In other words , the world is a black box for the brain with which it interacts through sensing and acting . In particular , the boundary between the body and the environment is not directly “visible” for the brain . Both are parts of that black box and interact with the brain in an entangled way . Therefore , we consider them as being one entity , the outside world or simply the world . The brain is causally independent of the world , given the sensor signals , and the world is causally independent of the brain , given the actuator signals . This is the black box perspective . Let us now develop a formal description of this sensorimotor loop . We denote the set of world states by 𝒲 . This set can be , for instance , the position of a robot in a static 3D environment . Information from the world is transmitted to the brain through sensors . Denoting the set of sensor states by 𝒮 , we can consider the sensor to be an information transmission channel from 𝒲 to 𝒮 as it is defined within information theory [39] . Given a world state w ∈ 𝒲 , the response of the sensor can be characterized by a probability distribution β ( w; ds ) of possible sensor states s ∈ 𝒮 as result of w . For instance , if the sensor is noisy , then its response will not be uniquely determined . If the sensor is noiseless , that is , deterministic , then there will be only one sensor state as possible response to the world state w . In any case , the response of the sensor given w can be described in terms of a Markov kernel β : 𝒲 ⟶ Δ 𝒮 , where Δ𝒮 denotes the set of probability distributions on the set 𝒮 of sensor states . The set of all such sensor channels is denoted by Δ 𝒮 𝒲 . Whenever the base set 𝒮 is discrete , we simply write s instead of ds and β ( w; s ) instead of β ( w; ds ) . Note that , as a Markov kernel , β satisfies various measure-theoretic conditions ( positivity , normalization , measurability; for the technical definitions of Markov kernels see , e . g . , [40] ) . Markov kernels are closely related to conditional probabilities , which would justify the notation p ( s∣w ) instead of β ( w; s ) . However , we prefer the latter notation . Following Pearl’s concept of causal networks [41] , the Markov kernels formalize the mechanisms of the sensorimotor loop . This means that the Markov kernels play the more fundamental role , and we want to distinguish this role also by the notation . Once the mechanisms are defined , they generate distributions so that we can also compute the conditional distributions from them . For instance , one could compute the conditional distribution p ( s∣w ) and compare this with the mechanism β ( w; s ) . Clearly , they coincide whenever p ( w ) > 0 , which we consider as a consistency property . However , there is an important difference , reflecting the fact that β is a mechanism: it is defined for all w . If the behavior of an agent is restricted to only a few world states , then the conditional distribution p ( s∣w ) will be defined only for these world states . After having described the mathematical model of a sensor in detail , it is now straightforward to consider a corresponding formalization of the other components of the sensorimotor loop . We continue with the notion of a policy . The agent can generate an effect in the world in terms of its actuators . Since we consider the body as part of the world , this can lead , for instance , to some body movement of the agent . In order to guide this movement , it is beneficial for the agent to choose its actuator state based on the information about the world received through its sensors . Denoting the state set of the actuators by 𝒜 , we can again consider a channel from 𝒮 to 𝒜 as formal model of a policy , represented by a Markov kernel π : 𝒮 ⟶ Δ 𝒜 , where Δ𝒜 denotes the set of probability distributions on 𝒜 . Note that this definition of a policy also allows us to consider a random choice of actions , leading to so-called non-deterministic policies . The set of policies is denoted by Δ 𝒜𝒮 . Finally , we consider the change of the world state from w to w′ in the context of an actuator state 𝒶 as a channel , denoted by α , which assigns a distribution α ( w , a; dw′ ) to w , a . With the set Δ𝒲 of probability distributions on 𝒲 , we have α : 𝒲 × 𝒜 ⟶ Δ 𝒲 . We refer to α as world channel and denote the set of all world channels by Δ 𝒲 𝒲 × 𝒜 . Similar causal structures , involving Markov kernels , have been considered in the general context of control and systems theory [42] as well as in the context of population dynamics [43] . We have defined three mechanisms that are involved in a ( reactive ) sensorimotor loop of an embodied agent . Clearly , the agent’s embodiment poses constraints to this loop , which we attribute to the mechanisms β and α . The agent is equipped with these mechanisms , but they are both considered to be determined and not modifiable by the agent . On the other hand , the policy π can be modified by the agent in terms of learning processes . In order to describe the process of interaction of the agent with the world , we have to sequentially apply the individual mechanisms in the right order . Starting with an initial world state wt at time t , first the sensor state st is generated in terms of the channel β . Then , based on the state of the sensor , an actuator state at is chosen according to the policy π . Finally , the world makes a transition , governed by α , from the state wt to a new state wt+1 , which is influenced by the actuator state at of the agent . Altogether , this defines the combined mechanism ℙ π ( w t ; d s t , d a t , d w t + 1 ) ≔ β ( w t ; d s t ) π ( s t ; d a t ) α ( w t , a t ; d w t + 1 ) . ( 1 ) Note that we consider β and α fixed and therefore emphasize only the dependence on π . Now , with the new state wt+1 of the world , the three steps are iterated . This generates a process which is shown in Fig 2 . Formally , the process is a probability distribution over trajectories that start with w0: w 0 , s 0 , a 0 , w 1 , s 1 , a 1 , w 2 , s 2 , a 2 , w 3 , … , s T - 1 , a T - 1 , w T . ( 2 ) In order to describe this probability distribution , we have to iterate the mechanism Eq ( 1 ) by multiplication: ℙ π ( w 0 ; d s 0 , d a 0 , d w 1 , … , d s T - 1 , d a T - 1 , d w T ) ≔ ∏ t = 0 T - 1 ℙ π ( w t ; d s t , d a t , d w t + 1 ) . ( 3 ) Now , what aspects of the sequence Eq ( 2 ) represent the behavior of the agent ? Let us consider , for instance , a walking behavior . It is given as a movement of the agent’s body in physical space , which is completely determined by the world process . Remember that the body is part of the world . Clearly , the particular sequence of sensor and actuator states does not matter as long as they contribute to the generation of the same body movement . Therefore , we consider the world process wt as the one in which behavior takes place and marginalize out the other processes from Eq ( 3 ) , which leads to: ℙ π ( w 0 ; d w 1 , … , d w T ) . ( 4 ) One can show that , with weak assumptions , the limit for T → ∞ exists , so that we can write ℙ π ( w 0 ; d w 1 , d w 2 , … ) , which is a Markov kernel from an initial world state w0 to the set of all infinite future sequences w1 , w2 , … . Denoting the set of such Markov kernels by Δ 𝒲 ∞𝒲 , we can formalize the policy-behavior map , which assigns to each policy the corresponding behavior: ψ ∞ : Δ 𝒜 𝒮 ⟶ Δ 𝒲 ∞ 𝒲 , π ↦ ℙ π ( w 0 ; d w 1 , d w 2 , … ) . ( 5 ) Two policies π1 and π2 will be considered equivalent , if they generate the same behavior , that is , ψ ∞ ( π 1 ) = ψ ∞ ( π 2 ) . ( 6 ) We argue that embodiment constraints render many policies equivalent . We can exploit this fact in order to design a concise control architecture . This will lead to a quantitative treatment of the notion of cheap design within the field of embodied intelligence . Let us treat this systems design problem in a more rigorous way . As we pointed out , the agent is equipped with the mechanisms β and α which constitute the embodiment of the agent . In a biological system these mechanisms will change due to developmental processes . However , we want to restrict our attention to the learning processes and disentangle them from developmental processes by assuming that the latter ones have already converged and therefore consider them as fixed . Learning refers to a process in which the policy is changing in time . Clearly , in order to model this change the agent has to be equipped with a family of possible policies , which we denote by 𝓜 , and refer to as policy model . For instance , we can consider a neural network as a policy model that is parametrized by synaptic weights and threshold values for the individual neurons . Changing the weights and the thresholds will lead to a change of the policy ( although there may be degeneracies , in general ) . In any case , going through all the possible parameter values will generate a set 𝓜 of policies with which the agent is equipped for its behavior . Intuitively , it is clear that the embodiment constraints cause restrictions in the set of behaviors that an agent can realize . For example , inertia restricts the pace at which an embodied system can change its direction of motion ( imagine a train switching the traveling direction instantaneously ) . In turn , not all world-state transitions may be possible in a single time step , regardless of what the policy specifies as a desirable action to take . These restrictions create a bottleneck between the set of policies on one side and the set of possible behaviors on the other . The consequence is that , generically , infinitely many policies parametrize the same behavior , in the sense of Eq ( 6 ) . Therefore , it should be possible to find a concise model 𝓜 that is capable of generating all possible behaviors . In particular , we consider a model 𝓜 that satisfies ψ ∞ ( 𝓜 ¯ ) = ψ ∞ ( Δ 𝒜 𝒮 ) , where 𝓜 ¯ denotes the set of limit points of 𝓜 . We refer to this property of 𝓜 as being an embodied universal approximator . In order to highlight the exploitation of embodiment constraints for cheap design , we compare this kind of universal approximation to the standard notion of universal approximation , 𝓜 ¯ = Δ 𝒜𝒮 , which we refer to as non-embodied universal approximation . If we understand the way in which different policies are mapped to the same , or to different , behaviors , then we can parametrize all the behaviors that can possibly emerge in the SML by a low-dimensional ( or low-complexity ) set of policies . We develop the necessary tools in this section . For clarity we will focus on the reactive SML with finite sensor and actuator state spaces but allowing the possibility of a continuous world state . In particular we will use β ( w; s ) instead of β ( w; ds ) and π ( s; a ) instead of π ( s; da ) . Possible generalizations of these settings are discussed in supporting information S3 Text . See S3 Fig for an illustration of a generalization to non-reactive systems . For a reactive SML , the condition stated in Eq ( 6 ) is equivalent to ℙ π 1 ( w ; d w ′ ) = ℙ π 2 ( w ; d w ′ ) , where ℙ π ( w ; d w ′ ) = ∑ s ∈ 𝒮 ∑ a ∈ 𝒜 β ( w ; s ) π ( s ; a ) α ( w , a ; d w ′ ) ( 7 ) is the one-step world state transition kernel . Therefore , the mechanism ℙπ ( w; dw′ ) will play an important role in our analysis and we consider the one-step formulation of the policy-behavior map: ψ : Δ 𝒜 𝒮 ⟶ Δ 𝒲 𝒲 , π ↦ ℙ π ( w ; d w ′ ) . ( 8 ) The map ψ is an affine map from the convex set Δ 𝒜𝒮 to the convex set Δ 𝒲 𝒲 . Its image 𝔅 ≔ ψ ( Δ 𝒜 𝒮 ) represents the set of all possible behaviors that the SML can generate . We refer to the dimension of 𝔅 as the embodied behavior dimension d ≔ dim ( 𝔅 ) . The embodied behavior dimension d is equal to the maximal number of affinely independent vectors in the set 𝔅 . This is given by the number of linearly independent vectors in the set β ( w ; s ) ( α ( w , a 0 ; d w ′ ) - α ( w , a ; d w ′ ) ) , s ∈ 𝒮 , a ∈ 𝒜 ∖ { a 0 } , ( 9 ) for some arbitrary a0 ∈ 𝒜 . See supporting information S1 Text for more details about this . In order to illustrate the effect of the embodiment on the embodied behavior dimension d , we formulate a simple upper bound in terms of β and α . In order to do so , we interpret the expression Eq ( 9 ) as a product of two vectors . More precisely , for each s ∈ 𝒮 consider the vector β ( ⋅; s ) that assigns to each w ∈ 𝒲 the number β ( w; s ) , and denote by rank ( β ) the maximal number of linearly independent vectors β ( ⋅; s ) . If 𝒲 is finite , rank ( β ) is simply the rank of the matrix with entries ( β ( w; s ) ) w ∈ 𝒲 , s ∈ 𝒮 . Furthermore , for each a ∈ 𝒜 ∖ {a0} consider the difference vector α ( ⋅ , a0; dw′ ) − α ( ⋅ , a; dw′ ) that assigns to each w the difference α ( w , a0; dw′ ) − α ( w , a; dw′ ) of probability distributions . Let rank ( α ) denote the maximal number of linearly independent difference vectors of that form . If 𝒲 is finite , rank ( α ) is simply the rank of the matrix with entries ( α ( w , a0; w′ ) − α ( w , a; w′ ) ) a ∈ 𝒜∖{a0} , ( w , w′ ) ∈ 𝒲 ×𝒲 . With these definitions , Eq ( 9 ) yields d ≤ rank ( β ) · rank ( α ) . ( 10 ) The upper bound Eq ( 10 ) may not provide an accurate estimate of the embodied behavior dimension . However , it illustrates how the embodiment constraints , represented by β and α , can lead to an embodied behavior dimension d that is much smaller than the dimension of the set of all policies Δ 𝒜 𝒮 , which is ∣𝒮∣ ( ∣𝒜∣ − 1 ) . In the following , we present simple examples that illustrate why the rank of β and α is expected to be small in embodied systems . The sensors are usually insensitive to a large number of variations of the world state w . This means that β outputs the same distribution for several different w . Furthermore , the sensors implement a certain degree of redundancy , meaning that , for each 𝒲 the probability distribution β ( w; ⋅ ) ∈ Δ𝒮 has certain types of symmetries . Consider , for example , the 20 × 20 maze shown in Fig 3 ( left-hand side ) . The world state includes the location of the agent in the maze , ( i , j ) ∈ {1 , … , 20}2 . The agent is endowed with two sensors: a left eye and a right eye . Each eye measures a weighted sum of the light intensity arriving from the walls in the immediate vicinity of the agent . The left eye outputs the value Sleft = 0 . 8 xw + 0 . 2 xn + 0 . 1 xs + 0 xe ( with probability one ) , where xw , n , s , e = 1 if there is a wall to the immediate west , north , south , east , respectively , and 0 otherwise . Similarly , Sright = 0 xw + 0 . 2 xn + 0 . 1 xs + 0 . 8 xe . Each eye can produce a total of 8 states: 0 , 0 . 1 , 0 . 2 , 0 . 3 , 1 , 1 . 1 , 1 . 2 , 1 . 3 . The naive number of joint sensor states ( Sleft , Sright ) is 8 × 8 = 64 . However , both eyes are partially redundant , and the actual total number of possible joint states is 15 ( the case of four walls surrounding a location is excluded ) . In this example , 400 world states are mapped onto 15 sensor states , which implies that the rank of β is 15 . This example illustrates the two typical properties of the sensor measurement mentioned above: the ambiguity of the measurement , mapping several world states to the same sensor state , and the redundancy , by which several sensors measure partially overlapping information about the world state . In the case of α , usually several actions a produce the same world state transition , such that , for any fixed world state w , α ( w , ⋅; ⋅ ) is piece-wise constant with respect to a . Furthermore , for any given w , only very few states w′ ∈ 𝒲 are possible at the next time step , regardless of a , such that α ( w , a; ⋅ ) assigns positive probability only to a very small subset of 𝒲 . This means that rank ( α ) is usually much smaller than ( ∣𝒜∣ − 1 ) ( the maximum theoretically possible rank ) . An example for this kind of constraints on α is a robot’s knee , which in a time step can only be moved to adjacent positions , as the one shown in Fig 4 . So far we have discussed the embodied behavior dimension of an embodied system and reasoned why it can be much smaller than the dimension of the policy space . Since the policy-behavior map ψ is affine , for any generic behavior that can possibly emerge in the SML , there is a d ˜-dimensional set ( in fact a polytope ) of equivalent policies generating that same behavior , where d + d ˜ equals the full dimension ∣𝒮∣ ( ∣𝒜∣ − 1 ) . By selecting representatives from each set of equivalent policies , we can define low-dimensional policy models which are just as expressive as the much higher dimensional set Δ 𝒜𝒮 of all possible policies , in terms of the representable behaviors . The following example shows that it is possible to define a smooth manifold of policies which translate in a one-to-one fashion to the set of all possible behaviors in the SML . Example . Embodied universal approximator of minimal dimension . Consider the matrix E ∈ ℝd× ( 𝒮×𝒜 ) that represents the policy-behavior map ψ with respect to some basis . Then the exponential family 𝓔 𝒜𝒮 of policies defined by π θ ( s ; a ) = exp ( θ ⊤ E ( s , a ) ) ∑ a ′ ∈ 𝒜 exp ( θ ⊤ E ( s , a ′ ) ) , θ ∈ ℝ d , ( 11 ) is an embodied universal approximator of dimension d . In fact , each behavior from the set 𝔅 is realized by exactly one limit point of the set 𝓔 𝒜𝒮 . See Fig 5 for an illustration and supporting information S1 Text for technical details . The previous discussion shows that the set of behaviors 𝔅 that can possibly emerge in the SML usually has a much lower dimension than the set of all policies . Furthermore , it shows that it is possible to construct low-dimensional embodied universal approximators . Nonetheless , among all behaviors that are possible in the SML , we can expect that only a smaller subset 𝓑 ⊆ 𝔅 is actually relevant to the agent . For instance , among all locomotion gaits that an agent could possibly realize with its body in a given environment , we can expect that it will only utilize those which are most successful ( e . g . , in terms of maximizing some reward function or the predictive information [44–46] ) . The notion of embodied behavior dimension can be directly generalized in order to accurately account for such behavioral restrictions . Given any set of behaviors 𝓑 , we are interested in the following problem . Problem . For a given set of behaviors 𝓑 ⊆ 𝔅 = ψ ( Δ 𝒜 𝒮 ) and a class 𝔐 of policy models , what is the smallest model 𝓜 ∈ 𝔐 that can generate all these behaviors; that is , 𝓑 ⊆ ψ ( 𝓜 ¯ ) ? Later below we will consider a class 𝔐 of policy models defined in terms of CRBMs . In what follows , we focus on sets 𝓑 of behaviors that take place within a subset 𝓦 ⊆ 𝒲 of world states and consider the corresponding subset 𝓢 ≔ { s ∈ 𝒮 : s ∈ supp ( β ( w ; ⋅ ) ) for some w ∈ 𝓦 } of sensor values that can be observed at these world states . When controlling behaviors from the set 𝓑 , only states in 𝓢 are relevant for the policy , as the other sensor states are never observed . Furthermore , in order to stay in 𝓦 only a restricted set 𝓐s of actuator states is allowed given that the state 𝒲 is observed . This motivates us to study a set of policies that is assigned to a sensor state set and a family of corresponding positive probability actuator state sets . In order to simplify the notation , we denote the family 𝓐s , s ∈ 𝓢 , simply by 𝓐 and consider the set Δ 𝓐𝓢 ⊆ Δ 𝒜 𝒮 of policies π that satisfy s ∈ 𝓢 , π ( s ; a ) > 0 → a ∈ 𝓐 s . Next we consider the set 𝓑 𝓢 , 𝓐 ≔ ψ ( Δ 𝓐𝓢 ) ∣ 𝓦 of behaviors on 𝓦 that are generated by policies with the given sensor and actuator restrictions . With its dimension d𝓢 , 𝓐: = dim ( 𝓑𝓢 , 𝓐 ) , we have the following result , which gives us a simple and powerful combinatorial tool for addressing the above problem of representing specific behavior sets . Lemma 1 . Any model 𝓜 ⊆ Δ 𝒜 𝒮 with the following property can approximate any behavior from the set 𝓑𝓢 , 𝓐 arbitrarily well: for every policy π ∈ Δ 𝒜 𝒮 whose 𝓢-rows have a total of ∣𝓢∣ + d𝓢 , 𝓐 or less non-zero entries , there exists a policy π * ∈ 𝓜 ¯ with π ( s; ⋅ ) = π* ( s; ⋅ ) for all s ∈ 𝓢 . See supporting information S1 Text for technical details and S1 Fig for an illustration of this result . This lemma states that for universal approximation of embodied behaviors it suffices to approximate the policies that assign positive probability only to a limited number of actions ( for a relevant set of sensor values ) . The number of actions is determined by the embodied behavior dimension . Keep in mind that the relevant set 𝓢 of sensor values may be much smaller than 𝒲 not only due to behavioral constraints but also due to the redundancy of the sensors . Recall the maze example from Fig 3 , where there are 64 theoretically possible sensor values but only 15 that are actually measured . This kind of redundancy is typical for embodied systems and generally leads to a strong reduction of the sensor states . Furthermore , redundancy in the sensor process results not only from the nature of the sensory apparatus , as in the maze example , but also from the agent’s behavior . This important mechanism , which is exploited by embodied agents , is known as information self-structuring [20] . It is worthwhile mentioning that the exponential family from Eq ( 11 ) and Lemma 1 describe two complementary types of universal approximators of embodied behaviors . The first type , described in the example , is composed of maximum entropy policies , whereas the second type , described in the lemma , is composed of minimum entropy policies . If we consider the set of equivalent policies that map to a given behavior , the exponential family selects the one with the most random state-action assignments that are possible for generating that behavior . On the other hand , Lemma 1 selects the ones with the most deterministic state-action assignments that are possible for generating that behavior . Geometrically , the set of equivalent policies of a given behavior is the convex hull of the minimum entropy policies , with the maximum entropy policy lying in the center . The exponential family has nice geometric properties , but it is very specific to the kernels β and α , which define the sufficient statistics E . The set described in Lemma 1 can also be considered as a policy model . It offers several advantages that we will exploit later on . First , it has a very simple combinatorial description . Second , it only depends on the embodied behavior dimension d , irrespective of the specific kernels β and α ( which are not directly accessible to the agent ) . Third , it selects policies with the minimum possible number of positive probability actions .
In the previous sections we have derived a theoretical bound for the complexity of a CRBM based policy . In this section , we want to evaluate that bound experimentally . For this purpose , we chose a six-legged walking machine ( hexapod ) as our experimental platform ( see Fig 7 left panel ) , because it has a well-studied morphology in the context of artificial intelligence , with one of its first appearances as Ghengis [47] . The purpose of this section is not to develop an optimal walking strategy for this system . Contrary , this morphology was chosen , because the tripod gait ( see Fig 7 right panel ) is known to be one of the optimal locomotion behaviors , which can be implemented efficiently in various ways . This said , learning a control for this gait is not trivial , and hence it is a good testbed to evaluate our complexity bound for CRBM based policies . This section is organized in three parts . The first part presents the experimental set-up as far as it is required to understand the results . The second part describes how the CRBM complexity parameter m was estimated form the data . The third part presents the results of the experiment and compares them with the theoretical bound .
We presented an approach for studying and implementing cheap design in the context of embodied artificial intelligence . In this context , we referred to cheap design as the reduction of the controller complexity that is possible through an exploitation of the agent’s body and environment . We developed a theory to determine the minimal controller complexity that is sufficient to generate a given set of desired behaviors . Being more precise , we studied the way in which embodiment constraints induce equivalent policies in the sense that they generate the same observable behaviors . This led to the definition of the effective dimension of an embodied system , the embodied behavior dimension . In this way , we were able to define low-dimensional policy models that can generate all possible behaviors . Such policy models are related to the classical notion of universal approximation . We used CRBMs as a platform of study , for which we presented non-trivial universal approximation results in both the non-embodied and the embodied settings . While the non-embodied universal approximation requires an enormous number of hidden units ( exponentially many in the number of input and output units ) , embodied universal approximation can be achieved using a much smaller number , depending on the effective dimension of the system . Experiments conducted on a walking machine demonstrate the tightness of the estimated number of hidden units for a CRBM controller . This shows the practical utility of our theoretical analysis for embodied artificial intelligence . To the best of our knowledge , the presented formalism and results are amongst the first quantitative contributions to cheap design . In artificial intelligence , learning is one of the central fields of interest . Crucial for the success of any learning method is the complexity of the underlying model , e . g . a neural network . If the model is chosen too complex , the learning algorithm will likely require too much time and get stuck in a suboptimal solution . If it is chosen too simple , it might not be able to solve the problem at all . This paper deals with the design of concise controller structures with main focus on the model class of conditional restricted Boltzmann machines . In this context , we find that the number m of hidden nodes naturally reflects the idea of a cheap or concise control . On the other hand , the total number m ( k + n + 1 ) + n of parameters of the conditional restricted Boltzmann machine , increases linearly in m , which suggests that a concise control is not only beneficial in terms of mass and energy consumption but also in terms of the quality of learning . It is well known from statistical learning theory [50] that the number of parameters is not always the right measure for controlling the quality of learning . However , for the purpose of this discussion it is sufficient to take an intuitive perspective and interpret low-dimensional models as being beneficial for learning . A central problem within learning theory is the problem of finding the right model complexity for optimal generalization properties . Regularization theory and statistical learning theory provide the right theoretical settings for optimizing the generalization ability of a learning system [50 , 51] . Here , an increasing sequence of model complexities is considered , depending on the available data at each time , so that universal approximation is achieved only in the limit of infinite data . The choice of the right model is dynamically adjusted to the available data . In our context , however , the choice of the model is fixed and based on the embodiment of the system . More precisely , we can choose a low-dimensional model , depending on the embodiment dimension , which is our main observation . Whether or not the replacement of a universal approximator by an embodied universal approximator solves the problem of generalization remains an open problem . In any case , the generalization abilities of embodied systems have to be further studied , where concepts from regularization theory and statistical learning theory , such as the structural risk minimization principle [50] , will be helpful . In this regard , the freezing-freeing concept [52] seems to point in a similar direction . Finally , we would like to comment on the applicability of our work to biological systems . The general field of embodied intelligence emerged from the observation that natural intelligent systems tend to incorporate and exploit their morphological properties for the generation of behavior . This suggests the hypothesis that brains of naturally evolved systems are optimized towards concise architectures , referred to as cheap design . Given a fully developed theory of embodied intelligence , this hypothesis should be testable for various biological systems . Although our approach is guided by this long-term vision , in its current form it is not directly applicable to biological systems . In order to approach applicability , it is important to develop methods for efficiently estimating β and α from biological data . Furthermore , conditional restricted Boltzmann machines represent very simple and unrealistic brain models . Therefore , our results have to be extended to more realistic brain models . Our work may be seen as a guideline for extensions towards understanding cheap design in biological systems . | Given a body and an environment , what is the brain complexity needed in order to generate a desired set of behaviors ? The general understanding is that the physical properties of the body and the environment correlate with the required brain complexity . More precisely , it has been pointed that naturally evolved intelligent systems tend to exploit their embodiment constraints and that this allows them to express complex behaviors with relatively concise brains . Although this principle of parsimonious control has been formulated quite some time ago , only recently one has begun to develop the formalism that is required for making quantitative statements on the sufficient brain complexity given embodiment constraints . In this work we propose a precise mathematical approach that links the physical and behavioral constraints of an agent to the required controller complexity . As controller architecture we choose a well-known artificial neural network , the conditional restricted Boltzmann machine , and define its complexity as the number of hidden units . We conduct experiments with a virtual six-legged walking creature , which provide evidence for the accuracy of the theoretical predictions . | [
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] | [] | 2015 | A Theory of Cheap Control in Embodied Systems |
The effect of calorie restriction ( CR ) on life span extension , demonstrated in organisms ranging from yeast to mice , may involve the down-regulation of pathways , including Tor , Akt , and Ras . Here , we present data suggesting that yeast Tor1 and Sch9 ( a homolog of the mammalian kinases Akt and S6K ) is a central component of a network that controls a common set of genes implicated in a metabolic switch from the TCA cycle and respiration to glycolysis and glycerol biosynthesis . During chronological survival , mutants lacking SCH9 depleted extracellular ethanol and reduced stored lipids , but synthesized and released glycerol . Deletion of the glycerol biosynthesis genes GPD1 , GPD2 , or RHR2 , among the most up-regulated in long-lived sch9Δ , tor1Δ , and ras2Δ mutants , was sufficient to reverse chronological life span extension in sch9Δ mutants , suggesting that glycerol production , in addition to the regulation of stress resistance systems , optimizes life span extension . Glycerol , unlike glucose or ethanol , did not adversely affect the life span extension induced by calorie restriction or starvation , suggesting that carbon source substitution may represent an alternative to calorie restriction as a strategy to delay aging .
Mutations that decrease the activities of the Akt/PKB , Tor , and Ras pathways extend the lifespan of several model organisms , suggesting that the underlying mechanisms of longevity regulation are conserved in many eukaryotic organisms [1] , [2] . Akt/PKB is a highly conserved serine-threonine kinase shown to function in the Daf-2 longevity pathway of Caenorhabditis elegans [3] . Homologous longevity modulating pathways were also identified in Drosophila and mice [2] . In yeast , Sch9 , which shares high sequence identity with the mammalian kinases Akt/PKB and S6K , is part of a nutrient-sensing pathway whose downregulation extends the chronological lifespan ( CLS , the survival time of a population of non-dividing yeast ) by up to 2-fold [4] . The Ras G-proteins are also evolutionary conserved and implicated in cell division in response to glucose/growth factors . The deletion of RAS2 doubles the CLS of yeast [5] . In mammals , a role for Ras in longevity control has not been established conclusively but , together with Akt , Ras is one of the major mediators of IGF-I signaling , which has been shown to promote aging [6] , [7] . Another conserved nutrient-responsive pathway , regulating cell growth and cell-cycle progression , involves the protein kinase target of rapamycin , TOR , which has been associated with life span regulation in C . elegans and Drosophila . Knockdown of LET-363/CeTOR , starting at the first day of the adult life , more than doubled the life span of worm [8] . Similarly , a reduced activity of Daf-15 , the worm ortholog of the mammalian mTOR-interacting protein raptor , promotes life span extension [9] . In flies , overexpression of dominant-negative dTOR or TOR-inhibitory dTsc1/2 proteins also leads to longevity extension [10] . Moreover , knockdown of CeTOR does not further extend the life span of worms subject to dietary restriction ( DR ) and inhibition of TOR protects flies from the deleterious effects of rich food , suggesting the beneficial effect of DR is , at least in part , mediated by TOR [10] , [11] . Two TOR orthologs , TOR1 and TOR2 , have been identified in yeast . Both Tor1 and Tor2 mediate growth-related signaling in a rapamycin-sensitive manner , whereas Tor2 has an additional rapamycin-insensitive function in controlling the cell-cycle-dependent organization of actin cytoskeleton [12] . Reduction of the TOR complex I ( TORC1 ) activity results in an extension of yeast replicative life span ( RLS ) , the number of daughter cells generated by individual mother cells [13] , 14 , comparable to that obtained when Sch9 is inactivated [15] , [16] . Furthermore , a high throughput assay to measure the CLS of individual yeast deletion mutants identified several long-lived strains carrying deletions of genes implicated in the Tor pathway [17] . Additional evidence supporting an inverse correlation between Tor1 activity and CLS has recently been provided [18] . The aging-regulatory function of both yeast Tor1 and Sch9 mediates the calorie restriction ( CR ) -dependent RLS extension . The down-regulation of either pathway mimics the effect of lowering the glucose content of the medium , and no further extension of RLS is observed when the sch9Δ or the tor1Δ mutants are calorie restricted [19] . Ethanol produced during fermentative growth is used as carbon source during diauxic shift and post-diauxic phase , when the yeast cells switch from rapid growth to slow budding and eventually cease proliferation [20] , [21] . Switching yeast grown in glucose/ethanol medium to water models an extreme CR/starvation condition for non-dividing cells . This severe form of CR doubles chronological survival of wild type yeast [22] . In contrast to RLS , CR-induced increase of CLS is only partially mediated by Sch9 [23] , [24] . Despite the extensive body of work demonstrating a link between nutrient-sensing pathways and life span regulation in different organisms , the key mechanisms responsible for delaying the aging process are still elusive . The direct correlation between life span extension and the ability to withstand different stress challenges , which has been observed in different model organisms , indicates that the activation of cellular protection represents an important survival strategy [25] . Our previous studies suggest that superoxide plays an important role in aging and age-dependent mortality , but protection against superoxide only accounts for a small portion of the potent effect of mutations in SCH9 and RAS2 on life span [5] . The connection between calorie restriction and the Sch9 , Tor and Ras2 pathways as well as the mechanisms of CR-dependent effects on life span remain poorly understood . Here we present evidence that changes in the expression of a set of genes controlled by Sch9 as well as Tor and Ras lead to a metabolic switch to glycerol production , which , together with the direct regulation of stress resistance systems , causes enhanced cellular protection and life span extension . Unlike the pro-aging carbon sources glucose and ethanol , glycerol does not elicit adverse effect on calorie restriction-induced cellular protection and life span extension suggesting that Tor1/Sch9-regulated glycerol biosynthesis leads to a carbon source substitution ( CSS ) that is as effective as calorie restriction in life span extension .
Using a genetic approach , we examined the relationship between Sch9 , Tor1 , and Ras2 in regulating cellular protection against stress and life span . The effects on life span and stress resistance caused by deficiency in Tor1 activity are less robust than those observed in the strains lacking Sch9 or Ras2 . We did not observe any significant difference in mean lifespan or stress resistance between sch9Δ and the tor1Δ sch9Δ double knockout strains ( Figure 1A , G , and Table S1 ) . By contrast , the deletion of TOR1 in a mutant carrying a transposon insertion in the promoter region of SCH9 , which only reduces SCH9 expression [4] , caused a further increase of resistance to heat and to the superoxide-generating agent menadione , but not to H2O2 ( Figure 1B ) , suggesting that the lack of TOR1 contributes to the further inactivation of the Sch9 pathway . This result is in agreement with the recent study showing that Sch9 is a direct target of rapamycin-sensitive Tor complex I ( TORC1 ) [26] . In fact , reducing the TORC1 activity either by deleting TCO89 , which encodes a TORC1 component , or by rapamycin treatment increased cell resistance to heat and H2O2 ( Figure S1 ) . Since Sch9 activity is associated with an age-dependent increase of mutation frequency [23] , we examined the interaction between Sch9 and Tor1 in the regulation of genomic instability during chronological aging . Whereas the tor1Δ mutant was slightly less susceptible than wild type cells to genomic instability ( measured as age-dependent frequency of mutations of the CAN1 gene ) between day 1 and 7 , there was no additive effect of TOR1 and SCH9 double deletion in the mutation frequency compared to that of the sch9Δ mutant ( Figure 1E ) . Overexpression of TOR1 only slightly reduced the stress resistance phenotype of sch9Δ ( data not shown ) . However , resistance to stress and life span extension of tor1Δ was abolished by overexpressing SCH9 ( Figure 1F and data not shown ) . Taken together , these data are in agreement with a shared signaling pathway between Tor and Sch9 in life span regulation and suggest an upstream role of Tor1 in Sch9 signaling ( Figure 1H ) . Both Tor and Ras/cAMP-PKA pathways are known to regulate stress-responsive ( STRE ) genes [27] . Elevating Ras activity by ectopically expressing constitutively active Ras2 ( ras2Val19 ) reversed the life span extension and the stress resistance of tor1Δ mutants ( Figure 1F and data not shown ) . Conversely , deletion of RAS2 had an additive effect to tor1Δ with respect to stress resistance but not life span ( Figure 1C , G , and Table S1 ) , suggesting an overlap in longevity modulation by Tor1 and Ras2 . We have previously shown that longevity regulation controlled by Tor1 , Sch9 and Ras2 converges on the protein kinase Rim15 [24] . Rim15 positively regulates stress response transcription factors ( TFs ) Msn2/4 and Gis1 , which activate genes involved in cellular protection . Interestingly , enhancement of stress resistance and life span extension associated with Ras2 deficiency requires both the STRE-binding TFs Msn2/4 and PDS-binding Gis1 , whereas the sch9Δ-mediated longevity regulation mainly depends on the latter [4] , [24] . These results indicate that the common downstream effectors are differentially modulated by the Sch9 and Ras2 . In fact , the ras2Δ sch9Δ double knockout cells exhibited higher stress resistance than either of the single deletion mutants ( Figure 1D ) . It also showed a 5-fold increase in mean life span compared to wild type cells ( Figure 1G and Table S1 ) . The triple sch9Δ ras2Δ tor1Δ deletion mutant , however , did not show any further increase of life span or stress resistance ( Figure 1D , G , and Table S1 ) . These results depict a life-span regulatory network composed of parallel but partially connected signaling pathways controlled by Tor/Sch9 and Ras ( Figure 1H ) . To identify the mediators of life span extension downstream of the Tor/Sch9 and Ras pathways , we carried out DNA microarray analyses for all three long-lived mutants: sch9Δ , tor1Δ and ras2Δ . Total RNA was extracted from 2 . 5 day-old cultures of long-lived mutants and wild type cells . This age was selected to avoid both the noise that may arise from a small fraction of cells that are still dividing at younger ages ( day1–2 ) and the general decrease in metabolism and consequently in gene expression that normally occurs at older ages ( day 4–5 ) [22] . The cRNA obtained from total RNA was hybridized to gene chips that allow the detection of 5841 of the 5845 genes present in S . cerevisiae . Three independent populations of each genotype were analyzed . A total of 800 genes showed a greater than 2-fold change in expression relative to those in wild type cells . Among these , 63 genes were consistently up-regulated more than 2-fold in all three mutants , and 25 genes were consistently down-regulated ( Figure 2A , for complete microarray data , see Table S2 ) . The mRNA levels of seven of the most up-regulated and one most down-regulated genes in both the tor1Δ and sch9Δ mutants were confirmed by quantitative RT-PCR and/or Northern blot ( Figure S2 ) . Based on the pair-wise comparison of the long-lived mutants , the up- and down-regulation of genes in these long-lived mutants are significantly overlapping , suggesting that the Ras , Tor , and Sch9-centered longevity regulatory network controls a common set of down-stream genes ( Table 1 and Table S3 ) . To identify features common to the three long-lived mutants , we performed a gene ontology ( GO ) analysis of the microarray data by Wilcoxon rank test . Although the data point to common changes in all 3 long-lived mutants , the GO category analysis indicated a divergence in expression pattern between ras2Δ and the other two mutants ( Table S4 ) , which is in agreement with our genetic analysis of two parallel signaling pathways controlled by Sch9 and Ras2 , and is consistent with the role of Sch9 and Tor1 in the same life span regulatory pathway ( Table 1 and Figure 1H ) [24] . Gene expression profile comparison between long-lived mutants and wild type cells reveals a consistent down-regulation of the genes encoding mitochondrial proteins , including proteins functioning in the TCA cycle and oxidative phosphorylation , mitochondrial ribosomal proteins , as well as proteins targeted to mitochondria ( Table S5 ) . The expression of glycolytic/fermentative genes , but not of gluconeogenic genes , was instead up-regulated ( Table S5C ) . Interestingly , several genes coding for high-affinity glucose transporters or putative glucose transporters , known to be inhibited by high glucose concentrations [28] , were up-regulated indicating that the long-lived mutants may have entered a starvation-like mode in which glucose uptake is maximized ( Table S5D ) . Considering that the extracellular glucose was exhausted in mutants as well as wild type cells by day 1–2 ( data not shown ) , the major substrate available for fermentation by day 2 . 5 is probably glycogen , which is normally accumulated by yeast in the late phases of exponential growth [29] . Genes involved in stationary phase survival , sporulation , meiosis , and stress response ( FMP45 , GRE1 , IME1 , RPI1 , SPS100 , and TAH1 ) were among the most upregulated genes in all three long-lived mutants ( Table S2 ) . To test their contribution to life span extension and stress resistance in long-lived mutants , we originated a set of double mutants carrying the deletion of SCH9 , RAS2 or TOR1 in combination with that of one of the most up-regulated genes . Whereas the deletion of either FMP45 or YDL218W slightly reduced the mean life span of the sch9Δ mutants ( Figure 2B ) , they have no effect on ras2Δ mutants ( Figure S3B ) . The deletion of IME1or RPI1 did not affect either the stress resistance or the life span extension caused by the lack of Sch9 ( Figure 2B and data not shown ) . Deletion of YLR012C , the most down-regulated gene , did not affect significantly the life span or the stress resistance of the cell ( Figure S3A ) . Several genes coding for proteins that function in the ergosterol biosynthesis were up-regulated in the long-lived mutants ( Table S7 ) . Ergosterol is the predominant sterol in yeast and is structurally closely related to cholesterol . Besides being a structural component of the cellular membrane , ergosterol affects phospholipid synthesis , lipid rafts formation , signal transduction as well as aerobic energy metabolism [30] . The deletion of either ERG4 or ERG28 caused a small decrease in both heat and oxidative stress resistance in the sch9Δ mutants ( Figure S3D ) . However , the deletion of ERG5 , the most up-regulated ergosterol biosynthesis gene in our microarray analysis , did not reverse longevity extension or reduce stress resistance associated with the sch9Δ mutants ( data now shown ) . Notably , the ergosterol biosynthetic genes that were upregulated in all three long-lived mutants are those involved in converting squalene to ergosterol , which require molecular oxygen and often involve oxidation of NADPH to NADP+ ( Table S7 ) . The upregulation may reflect a hypoxic environment during the post-diauxic phase survival of these long-lived mutants and suggests a link between redox state of the cell and survival . Taken together , these results indicate that the single deletion of many genes among the most up-regulated in long-lived mutants has little effect on life span . In addition to the lower expression of TCA cycle and respiratory genes and higher expression of glycolytic/fermentative genes , we also observed an up-regulation of the genes implicated in the metabolism of glycerol , a byproduct of the overflow metabolism when there is enhanced glycolytic flux and limited respiration capacity ( Figure 3A and B ) . Significant up-regulation of genes involved in glycerol metabolism ( 21 genes , Table S6 ) was observed in sch9Δ and ras2Δ mutants ( p-value of 0 . 0058 and 0 . 0142 , Wilcoxon rank test , one-sided , respectively ) . In yeast , glycerol is produced from either triacylglycerol or dihydroxy-acetone-phosphate ( DHAP ) , a glycolysis intermediate ( Figure 3A ) . Whereas the genes encoding the lipases responsible for the hydrolysis of triacylglycerol were slightly up-regulated , GPD1 and GPD2 , encoding the key enzymes required for glycerol production from DHAP , showed higher levels of expression in all the long-lived mutants ( Figure 3B and C ) , suggesting that part of the glucose utilized by these mutants is redirected towards glycerol biosynthesis . A search in the 800 bp upstream promoter region of the glycerol biosynthesis genes revealed that GPD1 , GPD2 , HOR2 , DAK1 , and DAK2 contain the DNA binding elements of Gis1- and Msn2/4 ( Figure 3B ) , stress resistance transcription factors downstream of Tor1 , Sch9 , and Ras2 [24] . Furthermore , the up-regulation of glycerol biosynthesis genes were partially reversed in sch9Δ gis1Δ double mutants ( Figure 3C; Figure S2J and K ) , indicating that regulation of glycerol biosynthesis is part of the regulatory repertoire of Sch9 signaling . In fact , higher level of intracellular glycerol was observed in the sch9Δ mutants compared to that in wild type cells at day 3 ( Figure 4A ) . In wild type cells the level of extracellular glycerol reached a peak at day 2 but was mostly depleted by day 3 . In the sch9Δ culture , however , a much elevated level of glycerol was measured in the medium up to day 9 ( Figure 4B ) . By contrast , ethanol produced during the exponential growth , and most likely in the post-diauxic phase as well , was depleted early in sch9Δ mutants but not in wild type cells ( Figure 4C and D ) [23] , suggesting a metabolic switch from biosynthesis and release of ethanol in wild type cells to that of glycerol in sch9Δ mutants . Glycerol accumulation could be accompanied by the depletion of other carbon sources as well . Nile red staining of the lipid body indicated that the levels of triacylglycerol and other neutral lipids in sch9Δ mutants were consistently lower compared to that in wild type cells across all ages ( Figure 4E and data not shown ) , which is in agreement with a modest but consistent increase of lipolytic enzyme mRNA levels ( Table S6 ) . Accumulation of extracellular glycerol also occurred in tor1Δ and ras2Δ mutants , but was lower than that observed in sch9Δ mutants ( Figure S4 ) . To further examine the role of glycerol biosynthesis in life span regulation , we generated strains lacking Rhr2 , the yeast DL-glycerol-3-phosphatase , in the sch9Δ background . The rhr2Δ sch9Δ double mutant failed to accumulate glycerol extracellularly ( Figure 5A ) . Deletion of RHR2 abolished the life span extension as well as the resistance to heat and oxidative stresses associated with the sch9Δ mutants in the DBY746 genetic background ( Figure 5B and C ) . Interestingly , ethanol was still present in the medium of rhr2Δ sch9Δ mutants at day 5 ( Figure 5D ) , when ethanol is mostly depleted in the sch9Δ culture ( Figure 4D ) , although in 3 independent cultures ( 3 independent isolates ) assayed , we observed high variation in ethanol concentration . Utilizing the yeast KO collection ( BY4741 genetic background ) , we deleted SCH9 in strains lacking key glycerol biosynthetic genes . Deficiency in either of the NAD-dependent glycerol 3-phosphate dehydrogenase genes , GPD1 or GPD2 , did not cause a significant life span change in wild type BY4741 cells ( Figure S5A ) . However , the deletion of either GPD1 or GPD2 , led to the reversion of the longevity extension associated with Sch9 deficiency ( Figure 5E ) . Similarly , the deletion of RHR2 abolished the life span extension in the sch9Δ mutant ( Figure 5E ) . In contrast , lack of Hor2 , a redundant isoenzyme of DL-glycerol-3-phosphatase , did not affect the life span of the sch9Δ mutant ( data not shown ) . The difference between these two isoenzymes may be explained by the fact that Rhr2 is the predominant isoenzyme in the cell [31] . In agreement with the major role of Rhr2 , the mRNA level of YIG1 , coding for an inhibitor of Rhr2 [32] , was down-regulated in all long-lived mutants ( Figure 3B ) . Notably , the life span of rhr2Δ mutants in the BY4741 genetic background was similar to that of wild type cells , although some rhr2Δ cultures showed regrowth/gasping ( data not shown ) [33] . Cells lacking both Rhr2 and Hor2 have been shown to be hypersensitive to the superoxide anion generator , paraquat , suggesting a role for glycerol biosynthesis in cellular protection beyond osmotic stress [34] . We also tested the role of glycerol biosynthetic genes in the stress resistance of sch9Δ mutants in the BY4741 background . Hypersensitivity to heat and hydrogen peroxide-induced oxidative stress was observed in the RHR2-null strain , but not in gpd1Δ , gpd2Δ , or hor2Δ mutants in the BY4741 background ( Figure 5F ) . Furthermore , cells lacking Yig1 , the Rhr2 inhibitor , were slightly more resistant to stress compared to wild type cells ( Figure 5F ) . The stress resistance phenotype of sch9Δ mutants was reversed by the deletion of GPD1 or GPD2 , but not of RHR2 or HOR2 ( Figure 5F ) . There appears to be redundancy in glycerol-mediated response to stress such that deficiency of one enzyme can be compensated by activation of others in the glycerol biosynthesis pathway . Deletion of SCH9 greatly enhanced stress resistance to heat and H2O2 of rhr2Δ mutants ( Figure 5F ) , possibly due to the upregulation of the Hor2 level . Since glycerol phosphatases ( Rhr2 and Hor2 ) are not the rate-limiting enzymes for glycerol production [34] , the upregulation of Gpd1 and Gpd2 may also contribute to the rescue of the rhr2Δ stress sensitive phenotype in cells lacking SCH9 . A similar redundancy exists between Gpd1 and Gpd2 . Although little or no effect was seen in either of the single deletion mutants , gpd1/2Δ double knockout strain is hypersensitive to heat and hydrogen peroxide treatment ( data not shown ) . The triple sch9Δ gpd1Δ gpd2Δ mutant showed severe growth defects and low saturation density in the liquid culture , which prevented us from utilizing this mutant for epistatic studies ( data not shown ) . Taken together , these results underscore the importance of glycerol biosynthesis in promoting cellular protection and life span extension in the SCH9 deficient mutants . Glycerol can protect against stress in part because of its function as a chemical chaperone [35]–[37] . To test the role of glycerol in protecting against heat-induced protein misfolding , we examined the activity loss and recovery of a heat sensitive bacterial luciferase [38] in wild type and sch9Δ cells . Whereas exposing wild type cells to heat stress ( 42°C for 1 hour ) led to a ∼80% reduction of luciferase activity , only a 20–40% loss of activity was observed in sch9Δ mutants ( Figure 6A ) , which is consistent with the enhanced stress resistance phenotype of sch9Δ ( Figure 1 ) . However , pre-treatment of wild type cells with low concentration of glycerol had no protective effect on the heat-induced loss and the recovery of luciferase activity ( Figure 6B ) , indicating the heat resistance phenotype of sch9Δ does not depend on the short-term exposure to extracellular glycerol . Similar results were obtained in the BY4741 genetic background ( Figure S5B and C ) . Intracellular accumulation of glycerol also contributes to protection against osmotic stress [37] , [39] . Addition of 0 . 1% of glycerol to the medium slightly enhanced the resistance to osmotic stress of wild type yeast ( Figure 6C ) . When exposed to high concentration of NaCl , the sch9Δ and ras2Δ mutants exhibited enhanced resistance to hyperosmolarity compared to the tor1Δ mutant , which in turn was better protected than wild type cells ( Figure 6C and Figure S4B ) , suggesting that increased resistance against hyperosmolarity may be part of the general stress response shared by all long-lived mutants . These data are also consistent with the reports that high osmolarity growth conditions extend both RLS and CLS in yeast [40] , [41] . With regard to life span , however , extracellular supplementation of glycerol ( 0 . 1% and 1% ) to the wild type yeast culture at day 3 , when the glycerol level is high in the long-lived sch9Δ mutants ( Figure 4B ) , did not show any beneficial effect ( Figure 6D ) . Ethanol , as a carbon source , elicits pro-aging signaling and promotes cell death . Removing ethanol either by evaporation or by switching yeast cells from expired medium to water , which represents a condition of extreme calorie restriction/starvation , extends yeast chronological life span [23] . The metabolic switch to ethanol utilization and glycerol biosynthesis removes the detrimental effect of pro-aging carbon sources ( glucose and ethanol ) and creates an environment that mimics calorie restriction in the sch9Δ mutant culture ( Figure 4D ) . To elucidate the role of different carbon sources on life span , we used an in situ assay to monitor chronological survival of yeast on plate [42] , which allowed us to: a ) study the effect of different carbon sources in the presence of all the other nutrients , b ) control the exact amount of carbon source to which the cells are exposed over the whole experiment , similarly to the experimental conditions used for the RLS studies of calorie restriction . The survival curve of approximately 200 wild type DBY746 cells plated onto SC-Trp plates supplemented with 2% glucose is reminiscent of that in the standard liquid medium paradigm ( Figure 6E ) . Extreme CR/starvation ( agar plate ) or removal of carbon source from the SC-Trp plates leads to life span extension , which was partially reversed by the presence of low concentration of ethanol ( Figure 6E ) in agreement of our earlier findings [23] . The adverse effect of glucose on life span was also observed on the long-lived sch9Δ and ras2Δ cells ( Figure S6C and D ) . Substitution of glucose with high level of glycerol ( 3% ) , however , did not trigger the pro-aging signaling as seen with glucose or ethanol ( Figure 6E ) . Thus , the metabolic switch to glycerol biosynthesis in the long-lived sch9Δ mutants may represent a genetically induced “carbon source substitution” that can be as effective as calorie restriction in the regulation of protection . Calorie restriction-induced cellular protection and life span extension in yeast depends on the protein kinase Rim15 and the activation of its downstream stress response transcription factors , which are negatively regulated by Sch9 , Tor , and Ras [24] . Extreme CR/starvation , achieved by switching yeast to water , activates Msn2/4 and Gis1 transactivation , via the STRE and PDS elements , respectively [24] . Addition of glucose and , to a lesser extent , ethanol significantly represses CR-induced STRE- and PDS-driven LacZ reporter gene expression ( Figure 6F and G ) . However , no reduction in STRE and PDS transactivation were observed when CR yeast were exposed to glycerol ( Figure 6F and G ) . Similar to extreme CR/starvation , reduction concentration of glucose in the culture medium also extends yeast life span [43]–[47] and requires the Msn2/4 and Gis1 [24] . When yeast were grown in medium containing either low glucose ( 1% ) or glucose/glycerol ( 1% each ) , a 1 . 5-fold increase in mean life span was observed compared to that in the standard medium ( Figure 6H ) . This pro-longevity effect of the low glucose/glycerol diet was mostly dependent , as is that of calorie restriction , on the stress response transcription factors ( Figure 6H ) . Notably , the beneficial effect of calorie restriction on longevity does not require glycerol biosynthesis . Cells deficient of RHR2 still lived long when cultured in reduced glucose or incubated in water ( Figure S6A and B ) . The metabolic switch in the sch9Δ mutants may not only remove the pro-aging/death signaling from glucose/ethanol or other carbon sources but also produce a carbon source , glycerol , for long-term survival . We switched wild type cells from the ethanol-containing medium to water containing 0 . 1% glycerol . A small extension of life span was observed in addition to that of extreme calorie restriction ( Figure 6I ) , suggesting that glycerol may provide nutritional support or additional protection under the starvation condition . In fact , we show that yeast cells actively uptake the exogenous [1 , 2 , 3-3H] glycerol during the post-diauxic phase , entered by S . cerevisiae after most of the extracellular glucose is depleted ( Figure 6J and Figure S4C ) . The utilization of glycerol is also supported by our microarray analysis , which showed that the genes involved in the catabolic metabolism of glycerol are up-regulated under the extreme CR/starvation ( water ) condition in wild type cells ( Table S6 ) .
Model organisms such as yeast , worms , and flies have been instrumental in the discovery of life span regulatory pathways that have a common evolutionary origin . Among these , the insulin/IGF-I-like pathways control longevity in organisms as phylogenetically distant as yeast and mice . Akt , Tor , and Ras function in the mammalian IGF-I signaling pathway and have been implicated in life span regulation in different model organisms [1] , [48] . In this study , we show that longevity regulatory pathways control the shift from respiration to glycolysis and glycerol biosynthesis . This metabolic switch , which leads to the removal of pro-aging carbon sources and glycerol accumulation , creates an environment in the sch9Δ culture that mimics calorie restriction ( Figure 7 ) . The genetic and genomic data revealed two parallel longevity signaling pathways controlled by Tor1/Sch9 and Ras , in agreement with our previous work [4] . The beneficial effects of reduced activities of both pathways is additive ( Figure 1D and G ) , and the sch9Δ ras2Δ double mutant is one of the longest lived genetic mutants [49] . In agreement with the genetic data , the gene expression profile of the day 2 . 5-old ras2Δ mutant shows that approximately 67% of the genes differentially expressed are not significantly changed in the other two mutants ( Figure 2A ) . Our genetic analysis of the interactions between the Tor , Sch9 and Ras2 indicates a stronger overlap between the Tor1 and Sch9 pathways in the regulation of stress resistance , longevity , and age-dependent genomic instability . It also suggests that TORC1 functions upstream of Sch9 in the regulation of these readouts in agreement with what has been proposed by others [50] and with the demonstration of the direct phosphorylation of Sch9 by TORC1 [26] . Our microarray analysis indicates similarities but also differences between the set of genes controlled by Tor and Ras . On the one hand , TOR1 deletion further increased the heat-shock resistance of ras2Δ mutants , and on the other hand no additional life span extension was observed . Furthermore , the overexpression of constitutively active Ras2 abolished CLS extension associated with deficiency of TOR1 , suggesting an overlapping of the two pathways and possibly an upstream role of TORC1 . Despite the higher degree of differential expression profile observed in ras2Δ mutants , there are remarkable similarities in the expression pattern of genes involved in key metabolic pathways in all three long-lived mutants . The genome-wide association ( transcription factor binding motif enrichment test ) and the genetic analyses indicate that longevity modulation by the Tor/Sch9 and Ras signaling depends on the protein kinase Rim15 and its downstream stress response transcription factors , Msn2/4 and Gis1 [24] , [51] . The most striking result is that genes involved in glycolysis/fermentation are consistently upregulated , while mitochondrial related genes are down-regulated , in all three long-lived mutants , suggesting a cellular state that favors glycolysis and diminished mitochondrial functions including TCA cycle and oxidative phosphorylation . Part of our results may appear to contradict recent results showing that respiration is upregulated in the tor1Δ mutant [18] . This discrepancy may be explained by the difference in the time point of observation . Bonawitz and colleagues measured higher respiration rates in exponentially growing or day 1 tor1Δ cultures relative to wild type yeast . By day 2 this difference was no longer observed [18] . The role of respiration in replicative life span regulation is still unclear . On the one hand , increased respiration has been shown to mediate the beneficial effect of CR ( 0 . 5% glucose ) [52]; on the other hand , growth on lower glucose-containing medium ( 0 . 05% glucose ) can extend the replicative life span of respiratory-deficient yeast [15] . Moreover , a study from the Jazwinski's group indicated that respiration does not directly affect replicative longevity [53] . The different effect of respiration on life span may also be contributed to the experimental systems used for life span studies . The replicative life span analysis is mostly carried out on the solid rich YPD medium , where cells are constantly exposed to glucose and other nutrients . The energy required for growth is mainly derived from fermentation . In contrast , our chronological longevity studies are performed by monitoring population survival in a non-dividing phase in which fermentation is minimized [22] . The gene expression profiles of long-lived mutants showed the induction of key genes required for glycerol biosynthesis . High levels of extracellular and intracellular glycerol were detected in the sch9Δ culture and triglyceride catabolism appeared to contribute to glycerol generation ( Figure 4 ) . This shift towards the production of glycerol represents a fundamental metabolic change in the physiology of the long-lived mutants . Genetic analysis performed by deleting genes required for glycerol biosynthesis in the sch9Δ mutant indicates that glycerol production is required for life span regulation ( Figure 5 ) . Increased glycerol biosynthesis may contribute to life span regulation through several distinct mechanisms . First , cells lacking Sch9 utilize glucose and ethanol and accumulate glycerol , a carbon source that does not promote aging and cell death . This metabolic change creates an environment that mimics calorie restriction . CR , achieved by either lowering glucose in growth medium or by removing ethanol , extends the yeast CLS [23] , [24] , [47] . Conversely , addition of low concentration of ethanol reverses life span extension induced by CR [23] . Here we show that cells lacking Sch9 deplete pro-aging carbon sources and activate glycerol biosynthesis . Whereas glucose and , to a lesser extent , ethanol promotes aging , glycerol acts as a “phantom carbon source” and does not inhibit the transactivation of stress response transcription factors Msn2/4 and Gis1 , which play important roles in stress resistance and longevity modulation in both long-lived mutants and cells under calorie restriction ( Figure 6 ) [24] . Since glycerol was taken up by the cells and caused a minor enhancement of survival under starvation conditions , it is likely that its uptake provides nutritional support for long term survival ( Figure 6I ) . Second , production and accumulation of glycerol may contribute to cellular protection since glycerol enhances resistance to osmotic stress and functions as molecular chaperone stabilizing/renaturing the newly synthesized or heat-inactivated proteins . However , our present and past results indicate that Sch9 also down-regulates stress resistance systems independently of the generation of glycerol . For example , in the BY4741 background Sch9 deficiency increased the resistance to multiple stresses in mutants with defects in glycerol biosynthesis ( Fig . 5F ) . Third , glycerol production may affect aging through the modulation of the redox balance of the cell , since its production contributes to the maintenance of NAD:NADH ratio [54]–[56] . Easlon et al . have recently shown that overexpression of the malate-aspartate NADH shuttle components extends yeast replicative life span [57] . The latter two mechanisms , however , are less likely to contribute significantly to chronological life span extension , as addition of exogenous glycerol to the culture had little or no effect on heat-induced protein inactivation ( Figure 6B ) or chronological survival in wild type cells ( Figure 6D ) . Additionally , we overexpressed in wild type cells the bacterial NADH oxidase ( NOX ) or alternative oxidase ( AOX ) , both of which increase NADH oxidation in yeast [58] , did not significant alter the life span of the wild type cells ( unpublished data ) . In summary , we presented data showing enhanced expression of glycerol biosynthetic genes in three long-lived yeast mutants lacking SCH9 , TOR1 , or RAS2 , whose homologs also play important roles in life span modulation in organisms ranging from worms , flies , to mammals . Our data also suggest that the switch to glycerol biosynthesis is required for life span extension in the sch9Δ mutants . We argue that the genetically induced carbon source substitution in the long-lived tor1Δ and sch9Δ cells creates a beneficial environment that mimics calorie restriction which , together with the intracellular regulation of stress resistance via transcription factors Gis1 and Msn2/4 , results in life span extension and stress resistance ( Figure 7 ) . In light of the conservation of the longevity regulatory pathways and the role of calorie restriction in extending life span of a wide range of species , it will be important to investigate further the possibility of an anti-aging role for glycerol in higher eukaryotes .
Mutant strains used were originated in DBY746 ( MATα , leu2-3 , 112 , his3Δ , trp1-289 , ura3-52 , GAL+ ) or BY4741 ( MATa , his3Δ1 , leu2Δ0 , met15Δ0 , ura3Δ0 ) by one-step gene replacement as described previously [59] . Strains overexpressing SCH9 or ras2val19 were generated by transforming DBY746 with plasmids pHA-SCH9 ( a gift from Dr . Morano University of Texas Medical School ) or pMW101 ( plasmid RS416 carrying Cla I-ras2val19-Hind III fragment of pMF100 , a gift from Dr . Broach , Princeton University ) , respectively . Strains expressing a heat sensitive bacterial luciferase ( Parsell , 1994 ) were generated by transforming yeast with plasmid pGPD-luxAB ( Addgene . com ) . Yeast chronological life span was measured as described previously [22] . For in situ viability assay [42] , day 1 SDC cultures of tryptophan auxotrophic strains were diluted and plated on to SC-Trp plates ( ∼200 cells/plate ) with no carbon source , or supplemented with glucose ( 2% , as in standard SDC ) , glycerol ( 3% ) , or ethanol ( 0 . 8% , a concentration reached in wild type cultures during diauxic shift , see Figure 4C ) , or agar plates ( starvation/water ) . Plates were incubated at 30°C for the duration of the experiment . Every two days , 0 . 5 ml of 2 mg/ml tryptophan was added to the plates . For plates without glucose , 1 ml of 5% glucose was added to the plates in additional to tryptophan . For agar plates , 1 ml of 2× YPD was added . Colony formation was monitored after 2–3 days incubation at 30°C . Total RNA were extracted from 2 . 5-day old wild type and mutants cultures ( in SDC , n = 3 ) by the acid phenol method . The cRNA was hybridized to Affymetrix GeneChip Yeast 2 . 0 array to obtain the measurement of gene expression . Procedures for microarray data analysis have been described previously [51] , [60] . The Gene Ontology ( GO , ftp://genome-ftp . stanford . edu/pub/go/ontology/ ) data were organized as a directed acyclic graph , in which each node corresponded to a set of genes with specific annotations . Only the GO categories that were well annotated and contain ≥30 genes were included , which were defined as terminal informative GO ( TIGO ) categories: 44 cellular components , 53 molecular functions , and 109 biological processes . Wilcoxon rank test was performed to examine whether a TIGO category was significantly up- or down-regulated . Finally , q-values for each test were calculated to correct the multiple testing errors using the “qvalue” package [61] . For quantitative RT-PCR analysis , total mRNA was extracted from cells harvested from 2 . 5-day-old cultures . RNA was reverse-transcribed using RetroScript III ( Invitrogen ) . Quantitative real time PCR was performed using the DNA Engine Opticon 2 ( BioRad ) . Primers used are listed in Figure S2 legend . Gene expression levels were normalized to actin ( ACT1 ) and expressed as the percentage of wild type . Day 3 cells grown in SDC were used for stress resistance assay . For heat shock resistance , serial dilutions of cells were spotted onto YPD plates and incubating at 55°C ( heat-shocked ) for 60–150 min . Plates were then transferred to 30°C and incubated for 2–3 days . For oxidative stress resistance assays , cells were diluted to an OD600 of 1 in K-phosphate buffer ( pH6 ) , and treated with 100–200 mM of hydrogen peroxide for 60 minutes . Alternatively , cells were treated with 250 µM of menadione for 30 min in K-phosphate buffer ( pH7 . 4 ) . Serial dilutions of control or treated cells were spotted onto YPD plates and incubated at 30°C for 2–3 days . For osmotic stress resistance assay , cells were washed twice with water and resuspended in salt buffer ( 2 or 4 M NaCl ) . After incubating at 30°C for 24 h with shacking , cells were washed with water to eliminate salt , serially diluted , and then plated on to YPD plates . Plates were incubated 2–3 days at 30°C . Cells ( 1 ml SDC culture ) were washed once with PBS and resuspended in 1 ml PBS . 10 µl of Nile Red ( 0 . 1 mg/ml in acetone ) was added to the cell suspension and incubated at room temperature , in the dark , for 5 min . Cells were washed once with PBS and imaged with a Leica fluorescent microscope . For intracellular glycerol content , cells were washed three times with water . Cell pellets from 1 ml culture were resuspended in 0 . 5 ml of Tris buffer ( 0 . 1 M , pH7 . 4 ) and , then , boiled for 5 min followed by a 30 sec spin to remove cell debris . The supernatant from the cell extract or the medium cleared of cells was used to determine intracellular or extracellular glycerol level , respectively . Glycerol concentration was measured using an UV-based glycerol assay kit ( Boehringer Mannheim/R-Biopharm ) . The manufacturer recommended protocol was modified to adapt the assay to a 96-well plate format . Each sample was assayed in duplicates and data were fitted to standard curve generated by serial dilutions of stock glycerol . For intracellular glycerol measurement , glycerol concentrations were normalized to cell number based on viability assay . Ethanol concentration in medium was measured using the UV-based ethanol assay kit ( Boehringer Mannheim/R-Biopharm ) according to the manufacturer recommended protocol . Heat inactivation of luciferase was measured as previously described ( Parsell , 1994 ) . Briefly , cells expressing heat-sensitive bacterial luciferase were subject to heat shock ( 42°C for 60 min ) . Ten minutes before the end of heat shock , cycloheximide ( 20 µM , final ) was added to the culture . The culture was sampled and mixed with the luciferase substrate decanol ( Sigma ) ; and the signal was immediately measured in a luminometer ( Luminoskan Ascent , Thermo Scientific ) . DBY746 strains with either 4xSTRE- or 1xPDS-LacZ integrated in the URA3 locus have been described previously [24] . One-day old cells grown in SDC were washed 3 times with water and resuspended in water ( extreme CR/starvation ) . Four hours after the initiation of CR , glucose , glycerol , or ethanol ( 0 . 8% , final ) were added to the cultures . Samples were collected after 2 and 4 hours of further incubation at 30°C with shaking . LacZ activity was measured as described previously [24] . | Studies using model organisms have pointed to the existence of evolutionarily conserved genes and signaling pathways that regulates life span . Changes in the activity of these genes/pathways have also been implicated in mediating the beneficial effect of calorie restriction , a well-recognized intervention that extends the life span from yeast to mammals . We investigated the global gene expression changes and identified genes involved in the metabolism of various kinds of carbon sources that are associated with longevity in the single cell organism , the baker's yeast . Although glucose and ethanol are common carbon sources for growth , they also have detrimental pro-aging effects in yeast . Long-lived yeast mutants actively utilize available glucose and ethanol and produce glycerol , which does not adversely affect the yeast life span extension . Our finding suggest that this “carbon source substitution” observed in long-lived yeast creates an environment mimicking calorie restriction , which together with the direct regulation of stress resistance systems optimizes life span extension . Findings using these simple genetic models will help to elucidate fundamental longevity regulatory mechanisms and identify similar pathways in mammals . | [
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] | 2009 | Tor1/Sch9-Regulated Carbon Source Substitution Is as Effective as Calorie Restriction in Life Span Extension |
Adenosine-to-inosine RNA editing diversifies the transcriptome and promotes functional diversity , particularly in the brain . A plethora of editing sites has been recently identified; however , how they are selected and regulated and which are functionally important are largely unknown . Here we show the cis-regulation and stepwise selection of RNA editing during Drosophila evolution and pinpoint a large number of functional editing sites . We found that the establishment of editing and variation in editing levels across Drosophila species are largely explained and predicted by cis-regulatory elements . Furthermore , editing events that arose early in the species tree tend to be more highly edited in clusters and enriched in slowly-evolved neuronal genes , thus suggesting that the main role of RNA editing is for fine-tuning neurological functions . While nonsynonymous editing events have been long recognized as playing a functional role , in addition to nonsynonymous editing sites , a large fraction of 3’UTR editing sites is evolutionarily constrained , highly edited , and thus likely functional . We find that these 3’UTR editing events can alter mRNA stability and affect miRNA binding and thus highlight the functional roles of noncoding RNA editing . Our work , through evolutionary analyses of RNA editing in Drosophila , uncovers novel insights of RNA editing regulation as well as its functions in both coding and non-coding regions .
Adenosine-to-inosine ( A-to-I ) RNA editing converts adenosine to inosine in RNA , which is then read by the cellular machinery as guanosine ( G ) [1–3] . This process is co-transcriptionally catalysed by adenosine deaminase acting on RNA ( ADAR ) , which recognizes double-stranded RNA ( dsRNA ) structures as editing substrates [4] . A-to-I RNA editing plays a critical role in neuronal function and integrity through the fine-tuning of editing [5–8] . In humans , changes in editing are associated with neurological disorders such as amyotrophic lateral sclerosis [9] and autism [10] . In Drosophila , the knockout of ADAR leads to severe neurological defects such as locomotion impairment , heat sensitive-paralysis , and age-dependent tremors [11] . The widespread presence of A-to-I editing at thousands to millions of sites in various organisms , from flies to humans , has been recently revealed ( e . g . [4 , 12–18] ) . However , only a handful of sites have been functionally studied [6] and it is unknown what fraction of editing events is functionally important . Recent studies have found that , although human RNA editing events are generally non-adaptive [19] possibly because the vast majority are in primate-specific Alu repeats , high-level nonsynonymous editing events , which cause amino acid changes , are most likely beneficial in humans [20 , 21] . In species such as squid and Drosophila , a significant fraction of editing events are located in coding regions , and many are likely to be beneficial [22–24] . While these studies have highlighted the potential functions of coding editing events , little is known about noncoding events . Few instances of noncoding RNA editing functions have been found: For example , RNA editing in the intron of mammalian ADAR2 alters splicing and thus truncates the protein [25] . In this study , we systematically examine both coding and noncoding editing events by comparing different species in the Drosophila genus and find that a surprisingly large fraction of both types are under selective pressure and therefore likely functionally important . Furthermore , we examine the potential functions of editing events in 3’ UTRs using a fly with catalytically inactive ADAR . Although there are thousands of editing events in Drosophila , this only represents a small fraction of the adenosines in the genome , and why particular adenosines are edited is not fully explored . Our analysis of the evolution of RNA editing gives us an opportunity to study how the evolution of RNA editing substrates alters editing . By making incremental changes to editing substrates , evolution has conducted a natural experiment allowing us to test the effects of various changes on RNA editing . Therefore , we can examine the characteristics of editing substrates . dsRNA is a well-known requirement for A-to-I RNA editing [26–28]; we recently found that genetic variants associated with editing level changes are enriched in areas with secondary structure , and the structures around editing sites were more stable in the allele with higher editing levels [29 , 30] . Furthermore , an RNA sequence motif associated with editing has been found [31] . However , it is unknown how these two factors , dsRNA structure and RNA sequence , work together to determine editing levels . Here , we explore the combined contributions of dsRNA structure and sequence to the evolution of RNA editing in the Drosophila genus .
We first assembled a master list of editing sites in the Drosophila genus to use for our analyses . Although we and others have recently identified a large number of RNA editing sites in D . melanogaster ( D . mel ) [4 , 13 , 16] , it is unlikely that their discovery has been saturated . To discover more editing sites in D . mel and identify additional editing sites unique in other Drosophila species , we applied our previously developed methods [16] to RNA-seq data ( male and female whole body ) from 13 Drosophila species ( S1 Table ) . We identified 627 novel exonic editing sites , including 545 novel ones edited in non-D . mel species only ( Fig 1A and 1B , S1A and S1B Fig , S2 Table ) . We combined this list with three other sets of sites identified in D . mel [4 , 13 , 16] . Using RNA-seq data from a D . mel ADAR null mutant [16] , we estimated that the false positive rates of these four sets range from 1 to 7% ( S1C Fig ) . We removed the false positive sites to obtain 2 , 380 exonic editing sites ( counting orthologous sites only once ) ( S2 Table ) . These sites are located in 909 genes , preferentially in coding regions and 3’UTRs . 56% alter amino acid coding ( S1D and S1E Fig ) . We next used publicly available RNA-seq data , supplemented with our targeted sequencing assay covering ~600 editing sites , to measure the editing levels of the 2 , 380 exonic editing sites in D . mel and 5 other Drosophila species that spanned a range of evolutionary distances from D . mel and had well assembled genomes and deeper RNA-seq coverage ( Fig 1A ) . To accurately measure editing levels in the RNA-seq data , only sites covered by ≥20 or 50 reads ( medium or high stringency ) were included , which leads to an average of 95 or 127 reads per editing site , respectively . While RNA-seq has been used to quantify RNA editing [12 , 16] , its inaccuracy in lowly and moderately expressed genes hinders the accurate measurement of a consistent set of sites . Therefore , to validate and extend measurements in the RNA-seq data , we used the microfluidic multiplex PCR and deep sequencing ( mmPCR-seq ) assay [32] to quantify the editing levels of an average of ~600 sites in male and female whole body samples of the 6 selected species ( S3 Table , S4 Table ) . We obtained ~2 , 400 reads per editing site per sample ( S2A and S2B Fig ) . Editing levels are highly consistent between biological replicates ( S2C Fig ) and with the RNA-seq quantification when sufficient RNA-seq reads are available ( S2D Fig ) . Finally , we combined the RNA-seq and mmPCR-seq datasets to obtain a more comprehensive and accurate RNA editing level measurement ( Fig 1C ) . When we compared editing levels between all pairs of the six species ( Fig 1D , S2E Fig ) and , separately , eight D . mel strains ( S2F Fig ) , we found that there was a clear positive correlation between editing level divergence and species divergence time ( Fig 1E ) . Furthermore , the editing level divergence tree recapitulates the topology of the phylogenetic tree ( Fig 1F ) . These observations suggest that editing level evolution is generally neutral . Since ADAR expression levels were very similar across species ( S3 Fig ) , we reasoned that changes in cis regulatory elements may account for editing level variation at individual sites . Cis regulatory elements , namely the primary ADAR sequence motif and dsRNA structure around editing sites , are believed to play an important role in editing regulation across species , as demonstrated in a few case studies [23 , 28 , 33–35] and our recent larger scale studies [29 , 30] . Therefore , we first examined whether the underlying mechanism behind RNA editing divergence between pairs of species involved both RNA sequence motif and dsRNA structure . We also distinguished between sequence differences that removed editing entirely and ones that merely tweaked editing levels . ADAR’s preferred sequence motif , in particular the triplet containing nucleotides immediately adjacent to the edited adenosine [31] , is essentially identical in our six selected species ( S4 Fig ) . To evaluate the effect of ADAR motif changes on editing level variation , we first deduced the ADAR motif weight matrix and used it to calculate motif scores for each of the 16 possible nucleotide triplets ( S5 and S6 Tables ) . We compared “Presence/Absence” sites , whose editing was present ( ≥10% level ) in the “anchor” species but absent ( ≤1 . 5% level ) in the other species under comparison to the control “Presence/Presence” sites , which were edited ( ≥10% ) in both species . With D . mel as an example anchor species , we found that ~25% of Presence/Absence sites had higher motif scores in D . mel , while only 8% of them had higher motif scores in the other , non-edited species , indicating an excess of better ADAR motifs in the “anchor” species ( p = 0 . 065 , 1 . 9e-3 , 5 . 7e-5 , and 6 . 4e-3 for D . mel vs . D . yak , D . ana , D . pse , and D . vir , binomial test ) ( Fig 2A ) . Strikingly , <1% of the “Presence/Presence” control sites had motif differences between species , although many of the sites were edited at different levels between two species . We observed similar results when performing the same analyses using the other 5 species as the anchor ( S5A Fig ) . Therefore , ADAR motif preference plays an important role to determine whether a site is edited rather than how much a site is edited . To examine the effect of secondary structure on editing level variation , we used a computational pipeline we previously developed [29] to predict editing complementary sequences ( ECSs ) , the sequences base-paired with editing sites , for 1 , 664 ( 70% ) editing sites in at least one species . Using these ECS predictions , we found that editing differences generally correlate well with secondary structure changes across species as exemplified in Fig 2B . This observation is also supported by our recent analyses of secondary structure changes within D . mel strains [29] . To systematically evaluate how secondary structure changes contribute to editing variation across Drosophila species , we dissected the dsRNA structures into 8 structural features and examined their roles separately ( Materials and Methods ) . Using the set of Presence/Absence editing sites and its control set of Presence/Presence sites described above , we observed that Presence/Absence of RNA editing best correlated with free energy , stem length , and number of paired bases ( Fig 2C , S5B Fig ) . This suggests that the stability and length of the RNA duplex play an important role for editing . While we showed that both motif and dsRNA structure changes are associated with editing changes , their relative importance is unknown . To study how these two regulatory elements work together , we determined the relative importance of the features for the establishment of editing in Presence/Absence sites and the variation in editing levels observed in Presence/Presence sites . We used random forests , a machine learning technique [36] , to predict the changes of editing between species using the motif and structural feature changes as predictor variables ( Materials and Methods ) . The difference in the prediction accuracy before and after permuting the predictor variable is used as an importance measure ( Fig 2D ) . For both scenarios , structural features such as folding energy , base-pairing , and stem length were important . While motif score and maximum bulge size were important in determining the presence or absence of editing , they were less informative for explaining editing level variation . Thus , our observations suggest that both motif and structural features determine whether ADAR can bind and edit a substrate , while changes in structural features contribute to editing level variation . It was previously shown that mutations in the ADAR motif can increase or decrease editing levels in vitro [26] . But our data suggests that structural features are generally used to tune editing levels in vivo , perhaps because such tuning allows for greater flexibility . To estimate the contribution of cis-regulatory elements to editing divergence , we examined how well these features could be combined together to predict changes in editing using random forests [36] . The difference in the predictive accuracy between two models , with and without ADAR motif and dsRNA structure features , is used as a measure of the contribution of cis-elements to editing divergence . In particular , given the editing levels in D . mel , we predicted the editing levels of orthologous sites in other species . The predictive accuracy of the model with motif and structural features are substantially higher than those of the model without these features ( Fig 2E ) . Therefore , a large portion of the editing level divergence across species can be accounted for by changes in cis regulation . Taken together , our cis regulatory element analyses reveal the structural landscape of editing and demonstrate how cis regulatory element changes lead to editing changes . Our cross-species data allowed us to examine how RNA editing events may be born or persist during evolution . We used a combination of phylostratigraphy and transcriptome data to deduce the evolutionary age of each D . mel editing site ( Fig 3A , Materials and Methods ) . We found that evolutionarily long-lived ( older ) editing sites have higher editing levels than younger sites ( Fig 3B ) , suggesting that the older sites with higher editing levels might be optimized for ADAR binding and editing . We observed similar results when using the other Drosophila species as the anchor ( S6 Fig ) . Our observation that older sites are much more likely to be clustered with other nearby editing sites ( Fig 3C ) further supports the idea that the sequences around older editing events can be edited at multiple positions and thus might be optimized for editing . Additionally , we found that the correlation of editing levels between species for old editing sites is higher than that for young editing sites ( S7 Fig ) , suggesting that older sites are under stronger purifying selection . Furthermore , we examined the functional enrichment of genes containing the younger and older editing sites . We observed no significant enrichment for genes containing the younger editing sites . However , the older sites gradually became enriched in genes with functions that are mostly neuron-related ( Fig 3D ) . This data agrees with the mostly neurological and behavioral phenotypes of ADAR knockout flies [11] , and suggests that older editing sites may have neurological functions . To determine whether editing tended to affect slowly or quickly evolving genes , we also examined the evolution rate of edited versus unedited genes . We only analyzed RNA editing sites identified from D . mel RNA-seq data alone [4 , 13] , in order to avoid potential bias from using sites identified from cross-species comparisons . The evolution rate was measured using Omega ( Ka/Ks ) , the ratio of the nonsynonymous site substitution rate ( Ka ) to the synonymous site substitution rate ( Ks ) [37] . We found that genes with nonsynonymous editing sites tend to evolve more slowly than unedited genes ( Fig 4A , S8A Fig ) . This pattern persists when comparing genes with and without editing sites within the same functional categories ( Fig 4B ) . Furthermore , the number of nonsynonymous editing sites per gene is negatively correlated with the evolution rate of edited genes ( Fig 4C , S8B & S8C Fig ) . In contrast , no significant correlation was observed for genes with intronic editing sites ( S8D Fig ) . Consistent with the findings above , we found that younger sites reside in genes evolving at a rate similar to the rest of the genome , while older editing sites tend to be in slowly evolved genes ( Fig 4D ) . Additionally , neuronal genes evolved more slowly ( S8E Fig ) . Taken together , these results suggest that individual editing events arise in genes of diverse functions and are subsequently selected to remain in slowly evolved genes , particularly with neuronal functions . We next separated exonic D . mel editing sites based on whether they resulted in nonsynonymous , synonymous , or 3’UTR editing ( 5’UTR sites were not examined because only a few were available ) and examined their evolution with respect to both editing levels and surrounding DNA sequences . First , we examined the editing levels of the eight D . mel strains . The editing levels of nonsynonymous sites are least variable , suggesting the strongest selective pressure . Unexpectedly , the editing levels of the 3’UTR sites are much less variable than those of the synonymous sites , indicating the presence of purifying selection around the 3’UTR sites ( Fig 4E , S9A Fig ) . We observed a similar pattern between species , except that the editing levels of 3’UTR sites were more variable , probably because of the increased sequence divergence rate in noncoding regions between species ( S9B and S9C Fig ) . Second , we examined the conservation levels of DNA sequences surrounding editing sites . We used RNA editing sites identified from D . mel RNA-seq data alone [4 , 13] , in order to avoid the potential bias of using sites identified from the cross-species comparisons . We found that , compared to more distal flanking regions , the regions spanning editing sites and separately , their ECS sequences , had a decreased sequence divergence rate for nonsynonymous and 3’UTR sites , but not for synonymous sites ( Fig 4F , S9D Fig ) . This is likely due to the evolutionary constraint in maintaining the dsRNA structure for many nonsynonymous and 3’UTR sites . Additionally , we observed higher editing levels of nonsynonymous and 3’UTR sites ( Fig 4G ) . These data suggest that a large number of nonsynonymous and 3’UTR , but not synonymous , sites are functionally important . Our observations prompted us to identify sites that were under evolutionary constraint and thus more likely to be functional ( S2 Table ) . By examining the conservation of the regions spanning the editing sites and the more distal flanking regions , we categorized each editing site as highly constrained , moderately constrained , or unconstrained ( Materials and Methods ) . We found 514 highly constrained and 466 moderately constrained sites ( S2 Table ) . As expected , the surrounding DNA sequences of evolutionarily older sites tended to be highly or moderately constrained ( S10 Fig ) . In addition , the highly constrained nonsynonymous and 3’UTR sites had the highest editing levels , and the moderately constrained sites had higher editing levels than the unconstrained ones ( Fig 4G ) , further supporting the functional importance of highly and moderately constrained sites . If one assumes that lowly edited ( <1 . 5% ) events are functionally neutral and uses the fraction of lowly edited sites in highly or moderately constrained regions as a baseline , one can roughly estimate that 14 . 2% ( = 75 . 4%–61 . 2% , Fisher’s exact test p-value = 5 . 5e-05 ) of nonsynonymous editing events and 12 . 0% ( = 50 . 5%–38 . 5% , Fisher’s exact test p-value = 0 . 048 ) of 3’UTR editing events are in highly or moderately constrained regions and therefore likely functionally important . For synonymous events , the difference is not significant ( Fisher’s exact test p-value = 0 . 42 , difference = 2 . 7% = 45 . 1%–42 . 4% ) . ( The fraction of editing events that are functionally important could be greater than this estimate if some lowly edited events are functionally important . ) This further supports the idea that a fraction of nonsynonymous and 3’UTR editing events are likely functionally important . While nonsynonymous amino acid changes affect protein sequence , the function of 3’UTR editing is unclear and under studied . 3’UTR regions often play a regulatory role in gene expression [38] . Therefore , we examined gene expression changes when RNA editing is removed , using RNA-seq data of an ADAR deaminase inactive ( EA ) mutant fly we generated , which contains a point mutation ( E374A ) that abolishes the catalytic activity of ADAR but retains the protein [39] . This allows us to examine only the editing-dependent function of ADAR , rather than other possible functions of ADAR . We found that the expression levels of 3’UTR-edited genes increased more in the ADAR mutant than genes edited elsewhere ( p = 0 . 016 ) ( Fig 5A ) . This effect was more dramatic in genes that were edited in more than one site in the 3’UTR ( p = 0 . 004 ) ( Fig 5B ) . Additionally , we found that the expression levels of genes with high 3’UTR editing levels or constrained 3’UTR sites increased more than those of genes with low editing levels or unconstrained sites , respectively ( Fig 5C and 5D ) . Thus , 3’UTR editing is associated with changes in gene expression , and this further supports the functional importance of 3’UTR editing . The association of the presence of 3’UTR editing and decrease in gene expression prompted us to hypothesize that RNA editing in the 3’UTR may lead to mRNA degradation . To test this , we compared editing levels from nascent RNA-seq to those from polyA+ RNA-seq in publicly available data4 ( S1 Table ) . Because RNA editing is co-transcriptional [4] , one would expect the editing levels of nascent RNA to be lower than those of mature polyA+ mRNA . For CDS sites , as expected , RNA editing levels are indeed lower in nascent RNA than polyA+ mRNA ( Fig 5E ) . On the contrary , 3’UTR editing sites have very similar editing levels in nascent RNA and polyA+ mRNA ( Fig 5E ) . This suggests that , among other possibilities , the edited 3’UTR transcripts may be degraded post-transcriptionally , thus lowering the editing levels in the mature polyA+ mRNA . Further experiments are needed to provide direct evidence for this hypothesis . We further explored the possible roles of miRNAs in regulating gene expression via differential binding to edited and unedited 3’UTRs [40 , 41] . We examined if editing sites create or destroy putative miRNA targets for genes with expression differences between WT and catalytically inactive EA flies ( log2 Fold change >0 . 2 or <-0 . 2 , 14 genes in total ) . We only used miRNAs that are co-expressed in fly male head samples for target prediction . We identified two editing events that create binding sites for miR-282-5p and miR-1017-3p; in both cases , the host genes have increased gene expression levels in the EA mutant compared to the WT flies ( Fig 5F ) . Therefore , RNA editing in the 3’UTR may affect miRNA binding , thus at least partially explaining the gene expression .
In this work , we examined the birth , death , and persistence of editing events as well as the quantitative changes of editing levels during ~60 million years of evolution in the Drosophila genus . We used changes in both RNA primary sequence and secondary structure to predict differences in editing level between species . This highlights the importance of local cis-regulatory changes in the evolution of individual RNA editing events , consistent with the findings of recent studies of RNA editing variation across more closely related Drosophila [29 , 30] , and shows that what is known about editing cis-regulation can account for a large fraction of the variation observed . We gained insights into the cis regulatory architecture of RNA editing and demonstrated how these features can be used to explain and predict the occurrence of an editing event as well as differences of RNA editing across species . For example , unexpectedly , we found that the ADAR binding motif is a feature that is a lot more important to determine whether a site can be edited compared to what level a site is edited ( Fig 2D ) . Our work lays a foundation for future work towards a cis regulatory code of RNA editing . In addition , our data suggests that RNA editing is selected to be enriched in slowly evolved neuronal genes . While neuronal genes evolve slowly , the nervous system acquires high complexity at least partially through the means of RNA editing . Thus , RNA editing , rather than nucleotide substitution at the genomic DNA level , may be the preferred evolutionary means of fine-tuning neuronal functions . While this manuscript was under preparation , another study on Drosophila RNA editing evolution was published [42] . Yu and colleagues examined the evolution of RNA editing in the Drosophila genus and found that editing events conserved in at least two members of a gene family were enriched in genes with neurological functions and in regions subject to purifying selection . These conserved editing events tended to cause amino acid changes , which is consistent with the idea that nonsynonymous editing events are more likely functionally important . This is echoed by our analyses that employ a targeted deep sequencing method to achieve much more accurate measurements of RNA editing levels . We both find that highly conserved editing events tend to be nonsynonymous , in neurological genes , and in regions or genes with a lower substitution rate . In addition to examining coding events , our work delves further into the often ignored non-coding RNA editing events . We found that 3’UTR editing is evolutionarily constrained at the DNA level and highly conserved at the RNA level . This is surprising to us given that the non-coding 3’UTRs are generally not evolutionarily conserved compared to coding regions . While the nonsynonymous editing events may have a more obvious function because of their ability to alter amino acid sequences , our work suggests that many 3’UTR sites are under negative selection . Thus , we identify a large fraction of both nonsynonymous and 3’UTR editing events that are likely functionally important . Our list of candidate functional sites will be valuable for further identification and characterization of truly functional , individual editing sites among the large number of sites that have been recently identified ( e . g . [4 , 12–14] ) . Our work further provides evidence of potential functions of 3’UTR editing events . Our finding that 3’UTR editing is associated with mRNA degradation in vivo suggests a new role for RNA editing in the regulation of RNA expression levels . We also pinpoint examples of 3’UTR editing sites that alter miRNA binding , thus affecting gene expression . Our findings would add another element to the array of tools by which RNA editing could fine-tune gene function in complex neurological systems . Further experimental work needs to be done to establish whether 3’UTR editing causes gene expression changes , and to explore the mechanism of action . In sum , our analyses provide strong evidence for a set of functional RNA editing sites and indicate an association between 3’UTR editing and mRNA regulation . By comparative evolutionary analyses , we found that nonsynonymous and 3’UTR sites are edited at high levels and located in highly or moderately constrained genomic regions . These data suggest that nonsynonymous and 3UTR edited sites are functionally important . However , it should be noted that little is known about the dominance of post-editing phenotypes , and editing divergence is only moderately correlated with the editing level ( S11 Fig ) , so caution should be exercised when using editing level alone as a proxy for fitness or negative selection . The approaches used in this study can be applied to identify functionally important editing events in other species , such as the primates where RNA editing is a lot more abundant particularly in non-coding regions [17] .
We obtained RNA-seq data for 13 Drosophila species from the NCBI Sequence Read Archive ( SRA ) ( http://www . ncbi . nlm . nih . gov/sra ) and modENCODE project ( http://www . modencode . org/ ) . We obtained the Anopheles gambiae whole body RNA-seq data from NCBI SRA . A list of datasets is shown in S1 Table . We obtained D . mel yellow white ( yw ) strain nascent RNA-seq , ADAR null mutant nascent RNA-seq , yw genomic DNA-seq , ADAR wild type and null mutant RNA-seq from NCBI SRA ( GSE37232 , GSE42815 ) . We adopted a pipeline that can accurately map RNA-seq reads to the genome [12] . In brief , we used BWA [44] to align individual RNA-seq datasets to a combination of the reference genome and exonic sequences surrounding known splicing junctions from available gene models ( obtained from the UCSC genome browser ) . We chose the length of the splicing junction regions to be slightly shorter than the RNA-seq reads to prevent redundant hits . After mapping , we used SAMtools [45] to extract uniquely mapped reads , merged uniquely mapped reads of individual datasets from the same sample , and detected nucleotide variants between the RNA-seq data and reference genome . We took variant positions in which the mismatch was supported by ≥2 reads and both base and mapping quality scores were at least 20 . We used additional filters to remove wrongly assigned mismatches as previously described [12] . We inferred the strand information of the sites based on the strand of the genes . Regions with bidirectional transcription ( sense and antisense gene pairs ) were discarded . ANNOVAR was used to annotate the editing sites [46] . The LiftOver tool was used to convert genomic positions between different species . Since LiftOver does not provide strand information between two species ( for example , a sense strand in one species may correspond to a reverse stand in another species ) , we obtained the strand information between different species using pairwise alignment data from UCSC genome browser . For the 6 species without genome alignments available on the UCSC genome browser ( D . eug , D . tak , D . fic , D . ele , D . kik , and D . bip ) , the sequences were aligned using Lastz with the following parameters: H = 2000 , Y = 3400 , L = 4000 , K = 2200 , O = 400 , and E = 30 [47] . Then , these were chained , netted , and converted to axt files using the tools axtChain ( with a minimum chain score of 3000 ) , chainPreNet , chainNet , and netToAxt from UCSC [48] . RNA-seq data of the wild-type strain and ADAR null mutant were obtained from two recent studies [4 , 16] . Sequences were mapped as described above . We examined all identified A-to-G sites that are edited in the wild type strain ( defined as having more than two altered reads and editing levels ≥ 1 . 5% ) . Sites that do not have altered reads in the ADAR null mutant were considered to be genuine A-to-I RNA editing sites . For sites that have altered reads in both the wild-type and ADAR null mutant , statistically significant editing sites in the wild-type were determined by applying Fisher’s exact test to compare the A-to-G occurrences between the wild-type and ADAR null sample [16] . P values were corrected using the Benjamini-Hochberg method , and a confidence level of 0 . 05 was used as the cutoff . We have recently developed a cross-species transcriptome comparison method that accurately identifies exonic RNA editing events [16] . We modified this method and applied it to the transcriptomes of 13 Drosophila species ( S1A Fig ) . RNA variants were called separately for each species as described above . Shared RNA variants that are present in any of the species pairs were obtained using various frequency cutoffs . As expected , the majority of the resulting RNA variants are A-to-G mismatches , indicative of A-to-I editing ( S1B Fig ) . To achieve a high accuracy in editing site calling without a substantial reduction in sensitivity , we chose a frequency cutoff such that the fraction of variants that were A-to-G was at least 80% [26] . In total , we identified a list of 1 , 564 exonic A-to-I editing sites ( Fig 1B , S2 Table ) . We next combined this list with three other lists [4 , 13 , 16] . We estimated the false positive rates of all studies using RNA-seq data from the D . mel wild type strain and from the Adar null mutant that eliminates RNA editing ( S1C Fig ) . We then removed the sites we found to be false positives to obtain 2 , 380 exonic editing sites . We note that we did not include a recently published D . mel editing site list [15] because all our experiments and data analyses had been done before the publication of the study . In addition , the number of novel sites from that study only accounted for 13% of the sites collected in our current list . Therefore , the exclusion of sites from this recent study is unlikely to affect our conclusions . A list of all species and strains used for mmPCR-seq are listed in S3 Table . All stocks were grown on standard molasses media ( Stanford fly media center ) . Ten whole bodies were collected from adult flies ( eclosion + ~5 days ) for each sample . The ADAR E374A mutant ( “Adar EA” ) contains 2 point mutations: C1725T ( synonymous ) and A1733C ( leading to the E374A mutation ) , was produced using CRISPR reagents described in [49] , and is on a y sc background , backcrossed to white Canton-S ( CS ) for 7 generations . For the RNAseq , stocks were grown at 18°C , and heads were collected from 3 day old male adult flies . Total RNA was extracted with the RNeasy Kit ( Qiagen ) . After DNase I treatment , 3 ug of total RNA was used to synthesize the cDNA using iScript™ Advanced cDNA Synthesis Kit ( Bio-Rad ) . cDNA was purified with MinElute PCR Purification Kit ( Qiagen ) . For the ADAR EA mutant RNAseq , total RNA was extracted using RNAdvance magnetic beads ( Agencourt ) , treated using TURBO DNase ( Thermo Fisher Scientific ) , depleted of ribosomal RNA [50] , and treated again using TURBO DNase . We used a microfluidic multiplex PCR and sequencing method [32] to quantify the RNA editing levels of selected sites . We selected sites that are edited at ≥5% editing levels in adult D . mel using RNA-seq data for primer design . Using the D . mel genome , we designed 48 pools of 12 to 15-plex multiplex PCR primers [32] , which covered a total of 605 loci , allowing us to examine all of these loci on a single chip . The sizes of the amplicons range from 150 to 350 bp . For distantly related species D . ana , D . pse , and D . vir , we also designed additional multiplex primers , which covered 192 , 211 , and 232 editing loci , respectively , that could not be amplified using the primers designed for D . mel . All primer sequences are listed in S4 Table . We next loaded cDNAs and primer pools into the 48 . 48 Access Array IFC ( Fluidigm ) and performed target amplification as previously described [32] . PCR products of each sample were then subject to 15 cycle barcode PCR and pooled together . All pools were combined at equal volumes and purified via QIAquick PCR purification kit ( Qiagen ) . The library was sequenced using Illumina HiSeq with 101 bp pair-end reads . We used the FASTX Toolkit ( FASTQ/A short-reads pre-processing tools , hannonlab . cshl . edu/fastx_toolkit ) to demultiplex the raw reads . We used Tophat [51] to align the pair-end reads to the corresponding genome . For editing level quantification , sites covered by ≥50 mmPCR-seq reads were used . We performed two rounds of targeted RNA sequencing . In the first round , we used mmPCR-seq to amplify and sequence all selected editing loci for all samples from six species with the primers designed for D . mel . For the non-D . mel species , because of the presence of the mismatches between some of the D . mel primers and templates , we expected that the amplification efficiency of different loci would be variable; in addition , some loci could not be amplified . As expected , we found a higher variability in coverage of various loci in non-D . mel data ( S2B Fig ) . Since we are only comparing the ratios of two alleles of the same amplicon , we expect that the amplification efficiency difference should not affect the accuracy of editing level measurement . Both the high reproducibility of biological replicates ( S2C Fig ) and the general consistency between RNA-seq and mmPCR-seq ( S2D Fig ) support this notion . In the mmPCR-seq data , for closely related species D . sim and D . yak , we were able to amplify about 80% and 70% of the selected sites , respectively . For distantly related species D . ana , D . pse and D . vir , we were only able to amplify about 56% , 50% and 48% of the loci , respectively . Therefore for these 3 species , we designed additional multiplex primers for ~210 loci that could be amplified in D . mel , D . sim and D . yak but not in D . ana , D . pse and D . vir . We used these primers for the second round of targeted RNA sequencing . We amplified these loci using a regular PCR machine . All samples were then barcoded , pooled and sequenced in one Illumina MiSeq run with 150 bp paired-end reads . For editing level divergence related analyses , sites covered by ≥20 reads were used unless otherwise specified . To maximize the number of sites used for analysis , we combined the whole body RNA-seq data with the mmPCR-seq data . For mmPCR-seq , sites with ≥50 reads and editing level differences ≤10% between biological replicates were used . For sites with both RNA-seq and mmPCR-seq measurements , we used the mmPCR-seq measurement . Editing level divergence was defined as 1 –Spearman’s rho , where rho was the correlation between editing levels in two species . The motif weight matrix was deduced using the nucleotide triplets ( the editing site and its immediately adjacent nucleotides ) of highly edited sites ( ≥50% ) . The motif weight matrices are very similar across species so we used the average motif weight matrix for analysis . Motif scores of each of the 16 possible nucleotide triplets were calculated by FIMO [52] and then scaled to the range of 0–10 . To maximize the number of sites used for “Presence/Absence” site analysis , we combined the male and female whole body data . For an editing site to be considered as absence , we required that the observed A-to-G frequency was less than 1 . 5% in all datasets with editing level measurements for the site . For an editing site to be considered as presence , we required that the A-to-G frequency was at least 10% in at least one dataset . To estimate if an absent site has evidence of editing , we examined if the editing level of this site was significantly higher than the typical A-to-G sequencing error rate ( 1% ) [32] based on the read coverage of this site using Binomial Test . For example , with D . mel as an anchor species , we found 492 Presence/Absence sites . 90% of the Presence/Absence sites had statistically significant higher editing levels in D . mel ( p<0 . 05 , Fisher’s exact test ) . And 99% of the absence sites had similar editing level to the typical A-to-G sequencing error rate , indicating no evidence of editing . We used the proximal and distal ECS prediction pipelines previously described [29] . Briefly , to predict proximal ECSs , we predicted the secondary structure of the region within 200 bp of each editing site using the programs partition , MaxExpect , and ct2dot from the RNAStructure package [53] , and identified ECS-like sequences with at least 20 bases paired in the stems and a max bulge of 8 . The same method was used to predict proximal ECSs in all 6 Drosophila species . To predict distal , intronic ECSs , we predicted conserved ECSs located in intronic regions . We smoothed phastCons scores using a sliding window of 51 bp [34] . We selected regions that were within 2 , 500 bp of the editing site and at least 20 bases long with a smoothed phastCons score of at least 0 . 90 ( determined using known intronic ECSs ) . Next , we folded candidate sequences and identified ECSs as with the proximal ECSs . Since the intronic ECS predictions could bias our analyses towards D . mel , the species in which they were identified , we used only the proximal ECSs for our cross-species evolutionary analyses . Both the intronic and proximal ECSs were used for comparisons within the D . mel population . We used our ECS predictions for two types of analyses to examine how differences in various features of orthologous sites are related to differences in editing level . First , we examined changes of editing in two scenarios . In the “Presence/Absence” scenario , we examined features of sites that were edited ( ≥10% ) in an “anchor” species and unedited ( ≤1 . 5% ) in another species . As a control , comparisons were also made in the “Presence/Presence” scenario , in which both the anchor and other species were edited ( ≥10% ) . Sites with predicted ECSs that passed the filter in the anchor species were used . ( The ECS was not required to pass the filter in the other species since it may or may not be present . ) Secondly , we predicted the editing level in a second species , given the editing level in the first species . In this analysis , sites with ECS predictions that passed the filter in at least one of the two species were used . We dissected the dsRNA structures into 8 structural features ( free energy , stem length , max bulge size , percent of the stem that is base-paired , distance between editing site and closest stem edge , number of paired bases in the entire stem , and , separately , number of paired bases in the stem downstream and upstream of the editing site ) . To determine the free energy of the dsRNA stem , we joined the editing stem with the complementary region stem by a 100 base linker of adenosines and ran the RNA secondary structure prediction program fold from the RNAStructure package . The relationship between editing changes and the ADAR motif and 8 structural features was modeled using random forests [36] ( R package: randomForest; parameters: ntree = 10000 , mtry = 3 , importance = TRUE ) . The random forests algorithm is particularly resistant to overfitting and uses the out-of-bag error ( for each iteration , calculated using the unused samples ( roughly one-third ) ) to obtain an unbiased estimate of the accuracy rate [54] . To predict whether a site is edited ( “Presence/Absence” ) , classification trees were used . ( Classification trees are decision tree models in which , at each branch , decisions based on features ( ie: RNA structure or sequence ) are made to classify items ( ie: sites ) . ) To predict the editing level changes ( “Presence/Presence” ) , regression trees , which are decision tree models that use continuous values , were used . The relative importance of the features ( accuracy importance for classification , percent increase in mean squared error for regression ) was calculated by randomly permuting each feature , taking the average difference between the accuracy of predictions using the permuted data and the accuracy using the non-permuted data , and then dividing by their standard deviation [36] . The percent variation ( R2 ) = 1 – ( the mean squared error of the editing level prediction / the variance in editing levels ) . For predicting the editing level in one species using the editing level in D . mel without motif and structural features , there was only one feature , so only one was sampled at each split ( parameters: ntree = 10000 , mtry = 1 , importance = TRUE ) . To calculate the conservation levels of DNA sequences surrounding the editing sites , we used a 30 bp sliding window size because the editing stem regions are usually 30–50 bp long [24] . For nonsynonymous and synonymous sites , we did not use flanking regions if they fell into a non-CDS region . For 3’UTR sites , we did not use flanking regions if they overlapped with any annotated CDS regions . To categorize each editing site as highly constrained , moderately constrained or unconstrained , we examined the conservation of the region spanning the editing sites ( S_region , 15 bp upstream and 30bp downstream of the editing site ) and the more distal flanking region ( F_region , 46bp before and after the S_region ) . We first defined sites with high conservations ( average PhastCons score > 0 . 9 ) for both S_region and F_region as highly constrained sites . For the remaining sites , we defined sites with a statistically significant higher conservation in the S_region compared to the F_region to be moderately constrained sites , and the ones with similar or lower conservation of S_regions as unconstrained sites . The significance was determined using two-sample Kolmogorov-Smirnov test ( fdr corrected p value < 0 . 05 ) . We obtained a total of 59 D . mel RNA-seq datasets , including 30 RNA-seq datasets from 30 developmental stages spanning the whole life cycle and 29 tissue-specific RNA-seq datasets in various tissues dissected from various stages ( http://www . modencode . org/ ) . For each dataset , we calculate editing levels for editing sites covered by ≥20 reads . For each site , the maximal editing level across all samples was used as the representative editing level of a site . We defined the age of each D . mel editing event using a combination of the male and female whole body data . We used 5 fly species ( D . sim , D . yak , D . ana , D . pse , D . vir ) and 1 mosquito species ( Anopheles gambiae ) representing 6 time points compared to D . mel . We posited that editing events rarely independently originate from different lineages so the age of each D . mel editing site was based on the most distantly related species in which sites were also edited ( parsimony principle ) . To determine if a site is edited , we required the editing level to be ≥2% in at least one dataset . With this cutoff , 89% of the editing sites have significantly higher editing levels than the typical A-to-G sequencing error rate ( 1% ) [32] ( p < 0 . 05 , Binomial Test ) . To determine if a site is unedited , we required that the site be covered by ≥20 reads and that the editing level be ≤1 . 5% in all datasets . With this cutoff , <1% of the editing sites have significantly higher editing levels than the typical A-to-G sequencing error rate ( p < 0 . 05 , Binomial Test ) . A site that was not an A at the DNA level was defined as unedited . Only sites that could be well defined as edited or unedited in at least 5 species were used for analysis . Gene ontology ( GO ) term analysis was done using DAVID [55] . P-values were corrected for multiple hypotheses testing using the Bonferroni method . All statistically significant GO terms ( p ≤ 0 . 01 ) with at least 5 genes were shown for all age groups except the D . vir age group for which we showed the top 10 GO terms from the total of 33 significant GO terms . The ω values of each gene were obtained from Larracuente and colleagues [56] . In brief , all single-copy orthologs in the melanogaster group were obtained . Paralogs were excluded because of difficulties in computationally verifying the accuracy of phylogenies and of alignments . We further selected genes that have orthologs in all fly species compared for analysis . The orthologous gene information was obtained from flybase . Only the melanogaster group was used because divergence at silent sites is too great ( saturated ) beyond the melanogaster group , which prevents an accurate estimation of dS and thus would erode the power to accurately estimate both rates of evolution ( dS and ω ) [56] . PAML ( Phylogenetic Analysis by Maximum Likelihood ) was used to calculate ω [37] . RNA sequencing libraries of the Adar EA mutant and wild type control were produced using the KAPA RNA-Seq Kit ( Kapa Biosystems ) . Libraries were sequenced on an Illumina NextSeq 500 Sequencer using paired-end 75-bp cycles . Reads were mapped using TopHat [51] and DESeq2 [57] was used to obtain gene expression levels . Only genes with editing levels above 5% and at least 20 reads at the editing site were used in the analysis . We obtained nascent and polyA RNA-seq data for yw male head samples from a recent study [4] . Reads were mapped using BWA to a combination of the reference genome and exonic sequences surrounding known splicing junctions , as described above . Only sites covered by at least 20 reads were used in the analysis . We used the TargetScan algorithm [58] to predict miRNA binding sites for the unedited and edited form of 3’UTRs using head expressed D . mel miRNAs . miRNAs were obtained from miRBase database Release 20 . Male head miRNA expression data was from GSM322543 . Only miRNAs expressed in male heads ( with >0 . 1% of the total miRNA reads , 62 miRNAs in total ) were used for analysis . | Many important modifications are made to RNA to fine-tune genomic information . One type , Adenosine-to-Inosine ( A-to-I ) RNA editing , changes certain adenosines to inosines and is essential for the neurological well-being of many animals . Although RNA editing occurs at thousands of sites across the genomes of various animals , the functions of nearly all editing events–particularly those in non-coding regions–have not been studied , and what determines whether particular adenosines across the genome are edited has not been fully explored . Here , using the Drosophila genus as model organisms , we analyze the evolution of A-to-I RNA editing to identify a large fraction of both coding and non-coding editing events that are under evolutionary constraint and therefore likely functionally important . We find that non-coding editing events in the 3’UTRs of genes could affect miRNA binding and are associated with a decrease in gene expression levels . | [
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"bi... | 2017 | Evolutionary analysis reveals regulatory and functional landscape of coding and non-coding RNA editing |
The ability of plants to provide a plastic response to environmental cues relies on the connectivity between signaling pathways . DELLA proteins act as hubs that relay environmental information to the multiple transcriptional circuits that control growth and development through physical interaction with transcription factors from different families . We have analyzed the presence of one DELLA protein at the Arabidopsis genome by chromatin immunoprecipitation coupled to large-scale sequencing and we find that it binds at the promoters of multiple genes . Enrichment analysis shows a strong preference for cis elements recognized by specific transcription factor families . In particular , we demonstrate that DELLA proteins are recruited by type-B ARABIDOPSIS RESPONSE REGULATORS ( ARR ) to the promoters of cytokinin-regulated genes , where they act as transcriptional co-activators . The biological relevance of this mechanism is underpinned by the necessity of simultaneous presence of DELLAs and ARRs to restrict root meristem growth and to promote photomorphogenesis .
Plant development is highly plastic in order to respond to a changing environment . Plants are able to trigger specific differentiation programs , promote growth over differentiation , or favour defense strategies over growth in response to environmental cues . Although the molecular mechanisms by which plants integrate environmental and endogenous signals are not completely understood , there is clearly a high degree of connectivity between the various elements of plant signaling pathways [1] . DELLA proteins represent one such common element by functioning as nuclear-localized transcriptional regulators , whose accumulation largely depends on the cellular levels of the hormone gibberellin ( GA ) . Increased GA levels promote the GID1 receptor-mediated polyubiquitination of DELLAs and their subsequent degradation by the 26S proteasome [2] . Research published over the past 17 years has demonstrated multiple roles of DELLAs throughout development and in the response to biotic and abiotic stress . For example , genetic and genomic studies in Arabidopsis and rice have shown that DELLAs: ( i ) promote the maintenance of seed dormancy [3 , 4]; ( ii ) restrict cell elongation and division in almost all plant tissues and organs [5 , 6]; ( iii ) promote the gravitropic response in shoots and roots [7 , 8]; ( iv ) enhance the resistance to cold temperatures [9]; ( v ) set up the program to prevent photo-oxidative damage [10]; ( vi ) help establish the photomorphogenic program [11 , 12]; and ( vii ) activate the defense against necrotrophic fungi [13] . These observations reinforce the hypothesis that DELLAs are regulatory elements that impinge on–and modulate–multiple cellular pathways [14 , 15] . A likely explanation for the multiplicity of DELLAs’ roles is their promiscuous ability to interact with many transcription factor ( TF ) families [16–18] . In Arabidopsis , the DELLA proteins GAI and RGA were first found to interact physically with PHYTOCHROME INTERACTING FACTOR 3 ( PIF3 ) and PIF4 , two bHLH TFs of the PIF family and prevent their binding to target promoters [19 , 20] . Since then , several additional TFs have been found as partners of DELLA proteins [21–29] , and the total number of interactors has been estimated to be above sixty [30] . Interestingly , this molecular mechanism can simultaneously explain two important features: the regulation of gene expression by DELLAs , and the long-standing observation of physiological crosstalk between GAs and other signaling pathways . However this exclusion of TFs from promoters is not a universal mode of action by which DELLAs can control gene expression and development since DELLA proteins are also found to be enriched at the promoters [31–33] . Cytokinins ( CKs ) and GAs are known to exert antagonistic regulation of multiple developmental processes [34] . For example , shoot apical meristem activity is restricted by GAs and promoted by CKs [35] , while hypocotyl elongation in etiolated seedlings [12 , 36 , 37] and root growth [36 , 38 , 39] are promoted by GAs and repressed by cytokinins ( CKs ) . At least two mechanisms have been proposed to account for this antagonistic action: a marginal repression by GAs of the expression of type-B ARABIDOPSIS RESPONSE REGULATORS ( ARRs ) ( the DNA-binding TFs that mediate CK signaling ) [40]; and independent transcriptional regulation of common targets [41] . However , the validity of these mechanisms to explain the antagonistic modulation of gene expression by GAs and CKs throughout development has not been demonstrated . Here we examine the genome-wide presence of a DELLA protein , RGA , in gene regulatory regions and define the putative cis elements that mediate the role of DELLAs as transcriptional coactivators . The biological relevance of this finding is supported by the identification of a novel regulatory module involving physical interaction between DELLAs and type-B ARRs that recruits DELLA proteins to generate transcriptionally active complexes at target loci .
To identify the loci at which DELLA proteins may act as transcriptional co-regulators , we incubated ten-day old Arabidopsis seedlings expressing GFP-RGA under the control of the native RGA promoter [42] in the presence of the GA biosynthesis inhibitor paclobutrazol ( PAC ) to induce GFP-RGA accumulation . We then performed chromatin immunoprecipitation ( ChIP ) with anti-GFP antibodies followed by deep sequencing ( see Materials and Methods ) . We identified 842 reproducible binding regions . From those , only 310 could be faithfully assigned to known genes ( 421 genes in total ) because of their proximity ( 2 . 5 kbp up- or 500 bp downstream of a gene or within introns or UTRs ( Fig 1A; S1 Table ) . We hypothesized that this subset of genes were putative RGA targets . Gene ontology ( GO ) analysis indicated a statistically significant enrichment in categories related to the response to stimuli , including abiotic stress , red- and far-red light , and GA signalling ( Fig 1B ) . Given that DELLAs are unlikely to bind DNA directly , we were interested in identifying TFs that facilitate their association with target promoters . We examined over-represented cis elements within the central 200 bp of the ChIP binding regions , as most relevant cis elements have been reported to locate in that window [43 , 44] . We screened all the plant TF binding sites matrices from open-access libraries [45–47] with the MotifLab software [48] , and found significant enrichment for the cis elements of 12 different TF families ( Fig 1C ) , including bZIP and INDETERMINATE DOMAIN ( IDD ) binding sites . Interestingly , two recent reports have shown that both RGA and at least another DELLA protein ( GAI ) can interact with the bZIP TF ABI5 to activate the expression of the SOMNUS gene [49] , and with several IDD family proteins to promote the expression of SCARECROW-LIKE3 [33] . This supports the biological relevance of the over-representation of at least these elements in the set of RGA targets . RGA has also been reported to act as a transcriptional co-activator through physical association with SQUAMOSA PROMOTER BINDING-LIKE9 ( SPL9 ) at the promoter of APETALA1 [50] , and SPL-binding sites were also enriched in the set of RGA targets in seedlings , but with very low statistical support ( S2 Table ) . It is likely that the enrichment of DELLAs at the promoters of flowering-related genes occurs at a much later developmental stage . The activity of DELLAs as transcriptional co-activators is also supported by two additional observations . First , the meta-analysis of published transcriptomic data involving DELLAs [14 , 17] indicates that the 421 genes associated with RGA ChIP peaks are preferentially induced ( and not repressed ) by DELLAs ( see Fig 1C for a breakdown of expression behaviour depending on the enrichment of specific cis elements ) ; and , second , DELLAs have been found to activate transcription in heterologous systems [51] and it has been proposed that interaction with the GID1 GA-receptors masks this activity in rice as one of the mechanisms by which GAs antagonize DELLA function [52] . To find additional evidence for the physiological relevance of the enriched cis elements among RGA ChIP peaks , we scanned a comprehensive list of DELLA interactors [30] and found that twelve of them represented TF families with reported preference for binding to the enriched elements , including GARP-ARR , HD-ZIP , and MYB among others ( S3 Table ) . The fact that not only ARR14 , but also other type-B ARRs had appeared in yeast two-hybrid ( Y2H ) screenings performed in our labs using GAI and RGA as baits ( Fig 2A and S1 Fig ) , prompted us to investigate ( 1 ) if DELLAs would act as transcriptional co-activators of these TFs , and ( 2 ) if these interactions could underlie the crosstalk between GA and CK signaling . Importantly , the identified ARRs ( ARR1 , ARR2 and ARR14 ) could indistinctly interact with both DELLA proteins . This result is in tune with the idea that the diversification of DELLA function relies primarily in their expression patterns , rather than in differential biochemical activities [53] , also supported by the observation that all DELLA interactors analyzed to date do not show a preference for particular DELLAs . Further analysis by Y2H showed that complete removal of the LHR1 motif of GAI ( del1 ) does not impair interaction with ARR1 , whereas it was prevented by further deletion of the VHIID motif ( del2; Fig 2A ) . These results contrast with the requirement of the LHR1 to sustain interaction of GAI or RGA with BZR1 , PIF4 , and JAZ1 [19 , 22 , 25] . On the other hand , the LHR1 domain was not sufficient for the interaction ( Fig 2A ) , as occurs with BZR1 [24] , in agreement with the requirement for the region close to the C-terminus to support DELLA interactions [54] . Indeed , point mutations in DELLA genes that create a premature stop codon close to the very end of the coding sequence and that produce truncated proteins represent loss-of-function alleles [55–59] , most likely because of their incapacity to interact with downstream partners . Contrary to what has been observed for other DELLA interactors , the DNA binding domain ( B motif ) of ARR1 was not involved in the interaction , while the glutamine-rich region responsible for the transactivation activity of ARR1 [60] was necessary and sufficient to sustain the interaction with GAI ( Fig 2B ) . The modular nature of ARR1 , demonstrated by the ability of the isolated B motif to bind DNA [60] , and by the hyperactivity of the DDK-deleted version of ARR1 , would be compatible with the model that DELLA binding to the C-terminus does not interfere with the regulation of ARR1 by CKs through the DDK domain or with the binding of ARR1 to the promoters . To confirm that the interaction between GAI and ARR1 also occurs in planta , we performed both Bimolecular Fluorescence Complementation ( BiFC ) and co-immunoprecipitation ( co-IP ) assays . BiFC analysis showed fluorescence from the reconstituted YFP in the nuclei of epidermal cells of leaves of Nicotiana benthamiana co-infiltrated with YFN-GAI and YFC-ARR1 , whereas the controls were below the threshold level ( Fig 2C ) . The co-IP experiments were performed in N . benthamiana leaves transiently expressing HA-ARR1 and YFP-GAI transgenes . HA-tagged versions of both full-length ARR1 , and a deleted version lacking the DDK domain ( ARR1ΔDDK ) , could be co-immunoprecipitated with YFP-GAI , using an anti-GFP antibody ( Fig 2D ) . Similarly , HA-ARR1 was also co-immunoprecipitated with an anti-myc antibody in Arabidopsis protoplasts co-transfected with myc-GAI ( Fig 2E ) . Remarkably , the endogenous RGA was pulled-down by anti-GFP antibodies from extracts of transgenic Arabidopsis seedlings expressing ARR1-YFP-HA ( Fig 2F ) . The absence of GAI in the immunoprecipitated complexes might be a consequence of the stringent conditions and likely reflects a weaker interaction between this DELLA and ARR1 in the conditions tested . These results support the Y2H studies , demonstrating that the interaction between the DELLA proteins GAI and RGA and ARR1 occurs in plant cells , and that the DDK domain of ARR1 is dispensable for the interaction ( Fig 2B and 2D ) . Given that GAs are responsible for DELLA degradation [2] , and that they antagonize the effect of CKs , a reasonable hypothesis is that the interaction with DELLAs promotes the activity of the CK-activated type-B ARRs . A model in which GAs regulate the activity of ARRs is supported for example by the observation that the expression of a reporter construct in Arabidopsis roots with GFP under the control of the type-B ARR responsive TCS synthetic promoter [61] was enhanced by an 18-h treatment with 0 . 5 μM of trans-zeatin , but not in plants pretreated with 1 μM GA4 ( Fig 3A and S2 Fig ) . Similarly , the same GA treatment in the absence of added trans-zeatin already caused a reduction in basal TCS::GFP activity ( Fig 3A and S2 Fig ) , probably reflecting the effect on endogenous CKs . To establish whether DELLAs act as transcriptional co-activators of ARR1 , we used a reporter construct containing the firefly LUCIFERASE ( LUC ) gene under the control of the TCS synthetic promoter and assayed its activity by transient expression in N . benthamiana leaves . As previously reported [60 , 61] , HA-ARR1 increased the expression of the wild-type version , but not a mutated version of the TCS::LUC reporter ( Fig 3B ) . Remarkably , the expression of TCS::LUC was significantly higher when YFP-GAI was co-expressed with either HA-ARR1 or ARR1-YFP-HA in the same leaves ( Fig 3B and S3A Fig ) , whereas expression of YFP-GAI alone showed only a marginal increase of LUC expression driven by the TCS element ( Fig 3B ) . The cooperative effect of GAI upon ARR1 activity was even more dramatic when the stabilized version of GAI ( M5-GAI ) was used . Importantly , higher LUC expression was also observed when HA-ARR1 was co-expressed with YFP-RGA , while YFP-RGA had no effect on its own ( S3B Fig ) , indicating that the transactivation ability of ARR1 is enhanced upon interaction with at least these two DELLA proteins . Next , we tested whether the enhanced expression of the TCS::LUC reporter upon co-expression of YFP-GAI and HA-ARR1 was due to the intrinsic transactivation of the DELLA protein . We co-expressed a truncated version of GAI , M5GAI , that still interacts with ARR1 ( Fig 2A and 2B ) but lacks the N-terminal part in which the transactivation activity resides [52] . As shown in Fig 3B , the activity of the reporter was enhanced when HA-ARR1 was co-expressed with myc-M5GAI , indicating that the enhanced transactivation is not due to the N-terminal part of the DELLA protein . These results also suggest that either the DELLA protein recruits additional transcriptional co-activators to the complex or other regions of the DELLA acquire transactivation ability upon interaction with ARR1 . To identify the most relevant targets for co-regulation by ARR1 and DELLAs , we chose to perform a microarray analysis on seedlings that expressed the conditional ARR1ΔDDK:GR allele under the 35S promoter [62] in the presence or absence of PAC ( Silverstone et al . 2001 ) . In these seedlings , a treatment with dexamethasone ( DEX ) causes translocation of ARR1ΔDDK to the nucleus , where it regulates the transcription of its target genes . Therefore , we searched for genes displaying differential expression after a 3-h treatment with 5 μM DEX depending on the presence of 10 μM PAC ( see Materials and Methods for details ) . In parallel , we also examined transcriptomic changes induced by 5 μM N6-benzyladenine ( BA ) both in the presence and in the absence of PAC , to identify those targets in which regulation by CKs would be primarily dependent on ARR1 . Statistical analysis of the transcriptome data by Z-score transformation [63 , 64] revealed 638 genes were up-regulated and 1070 down-regulated by activated ARR1 . From those , only 99 were still up-regulated both under high or low DELLA levels , and included well-known targets of CK signaling , like type-A ARR genes , and CK Response Factors ( S4 Table ) . Most interestingly , 140 genes were identified whose expression was induced by ARR1ΔDDK only when DELLA levels were high , while 99 genes were repressed in those conditions ( Fig 4A ) . GO analysis of the genes induced by ARR1 preferentially in the presence of DELLAs indicates a statistically significant enrichment of several categories , with a preference for ribosome biogenesis , translation , and protein metabolism ( Fig 4B ) . Among the genes differentially expressed in the presence of both DELLAs and ARR1 , only four displayed a statistically significant ChIP peak for RGA ( S1 Table ) . This low overlap probably reflects the difference in the experimental set-up . Given that ARR1 can act as a transcriptional activator , we selected six of the induced genes to further test the functional and molecular relationship between ARR1 and DELLAs . First we examined the consequence of short-term activation of ARR1ΔDDK:GR in light-grown seedlings that had high or low levels of DELLA proteins . Four of the six genes showed a much stronger induction by ARR1ΔDDK in seedlings with high DELLA levels ( Fig 4C ) , in agreement with the global transcriptomic analyses performed under similar conditions . Then we did the reciprocal test in which we examined the influence of an activated CK pathway on the ability of gai-1 to induce gene expression using HS::gai-1 seedlings [65] . In this case , five of the six genes displayed a stronger induction in gai-1 seedlings that had been pretreated with 5 μM BA , than in the untreated plants ( Fig 4D ) , which supports the idea that type-B ARRs and DELLAs jointly promote transcription of the target genes . If the co-regulation of the target genes by DELLAs and ARR1 is mediated by physical interactions between these two proteins , then DELLAs should be present at the promoters of these particular targets in an ARR1-dependent manner . To test this prediction , we first performed ChIP on RGA::GFP-RGA seedlings . In fact , the presence of RGA was significantly enriched in the promoters of the six genes tested ( Fig 4E ) and , what is more important , the presence of GFP-RGA at the promoters of three of the six genes tested was much higher in seedlings when ARR1ΔDDK:GR accumulated in nuclei after DEX treatment ( Fig 4F ) . The requirement for ARR1 in the binding of RGA was further supported by the loss of enrichment in the arr1 arr12 double mutant , compared with the wild type , in some of the loci examined ( Fig 4G ) . Our results suggest that ARR1 mediates the binding of DELLAs to the target promoters , and together they promote the expression of target genes . A physical interaction between ARR1 and DELLAs provides a likely mechanism for the antagonistic effect of CKs and GAs in the regulation of gene expression . To probe the physiological relevance of this particular mechanism in the control of plant development we decided to test the impact of altering this interaction on two processes known to be regulated both by CKs and GAs . DELLA accumulation has been shown to reduce cell division at the root meristem [38 , 39] resembling the arrest caused by ARR1 overproduction [66 , 67] . Indeed , it has been shown that ARR1 mediates the reduction of cell division via DELLAs , and the proposed mechanism involves the promotion of ARR1 gene expression by DELLAs [40] . To test the relevance of the interaction between the ARR1 and DELLA proteins in this context and separate the possible effect on ARR1 expression , we examined the ability of the constitutively expressed version of ARR1 ( 35S::ARR1ΔDDK:GR ) to block root meristem growth depending on the presence of DELLAs . Induction of ARR1ΔDDK:GR translocation into the nucleus by DEX treatment caused a reduction in root meristem size ( Fig 5A ) . Importantly , this effect could be completely reversed by GA treatment that depletes DELLAs from root cells ( Fig 5A ) , indicating that this class of proteins are required for full ARR1 function , rather than for ARR1 expression . At a different developmental stage , exogenous CKs have been shown to promote photomorphogenesis [37] , while GAs repress photomorphogenic development in dark-grown seedlings [11 , 12 , 65] . Accordingly , nuclear accumulation of ARR1ΔDDK:GR in dark-grown seedlings resulted in cotyledon expansion , a well known photomorphogenic trait ( Fig 5B ) . This effect was milder in GA-treated seedlings , indicating that DELLAs enhance the photomorphogenic activity of ARR1 . This conclusion was supported by the observation that the photomorphogenic effect caused by ARR1ΔDDK:GR induction was also attenuated in a gai rga null mutant background ( Fig 5C ) , also in agreement with these two being the most relevant DELLA proteins in the control of several aspects of photomorphogenesis [12] . Conversely , the stimulation of cotyledon opening by DELLAs , achieved by PAC treatment as previously reported [11 , 12 , 65] , was completely suppressed in the arr1 arr12 double mutant ( Fig 5D ) , supporting the idea that ARRs and DELLAs jointly regulate various physiologically relevant developmental processes . Taken together , our results and other recent reports [33 , 50] expand the mechanism by which DELLA proteins regulate transcriptional programs in plants . The observation that DELLAs modulate not only the binding , but also the activity of TFs at target loci , together with the indications that they may also regulate chromatin remodeling through their interaction with SWI/SNF complexes [68] delineates a landscape in which DELLA proteins act as molecular hubs in signaling networks , with a profound effect on plant physiology . Equivalent central roles have been found in other systems only for mitogen-activated protein kinases ( MAPKs ) . For instance , mammalian p38 kinases and their yeast ortholog Hog1 modulate gene expression in a very wide sense by regulating the activity of DNA-binding TFs , transcriptional elongation , chromatin remodeling , and mRNA stability in response to environmental stress [69] . However , the activity of DELLA proteins relies on their intrinsic ability to interact with elements of the transcriptional regulation machinery . Under this perspective , at least two relevant issues would need to be solved: the molecular features of DELLA proteins that allow them to display such a promiscuous set of interactors and activities; and the spatial requirements that may constrain the different DELLA interactions to specific cell-types .
Arabidopsis thaliana accessions Col-0 and Ler were used as wild type as indicated . The transgenic lines 35S::ARR1ΔDDK-GR , TCS::GFP , RGA::GFP-RGA , HS::gai-1 and the mutants gai-td1 , rga-100 and arr1-3 arr12-1 in the Col-0 background have been described previously [36 , 42 , 61 , 62 , 65 , 70] . To over-express ARR1 , the open reading frame without stop codon was amplified from an Arabidopsis seedlings cDNA pool and cloned into the pEarleyGate-101 binary vector to create the ARR1-YFP-HA fusion . Wild type Col-0 Arabidopsis plants were transformed by the floral dip method . Primers used for amplification of the ARR1 ORF are in S5 Table . Seedlings were grown on MS at 22°C in continuous fluorescent white light ( ~50 μmol m−2 s−1 ) unless otherwise indicated . For TCS::GFP activity , 6-day-old seedlings growing in MS plates were transferred to liquid MS containing 1 μM GA4 ( Duchefa ) for 3 h and then trans-zeatin ( Sigma ) was added to a final concentration of 0 . 5 μM for 18 h . For root meristem growth assays , 5-day-old seedlings were incubated in liquid MS for 16 h in the presence of 30 μM dexamethasone ( Sigma ) and/or 1 μM GA4 , and then transferred to MS plates for 2 days . For cotyledon opening assays , stratified seeds were incubated for 8 h in the light , and then transferred to darkness in MS plates supplemented with 0 . 1 μM dexamethasone ( DEX ) and/or 1 μM GA4 , or with 0 . 5 μM PAC ( Duchefa ) for 7 days . Transgenic RGA::GFP-RGA and the control non-transgenic seeds were sown on MS plates and stratified for 4 days at 5°C . Seedlings were grown at 150 μmol m-2 s-1 for 10 days under long day conditions before being transferred to a hormone liquid treatment with 10 μM PAC for 18 h . This was the minimum incubation time required to cause an effective block in GA biosynthesis and deplete previously synthesized GAs , as indicated by the analysis of several marker genes [30] . ChIP assays were performed from 2 g of fresh weight each as previously described ( Gendrel et al . , 2005 ) . Nuclear extracts were split in two and incubated each with 20 μl of GFP-Trap_A ( ChromoTek ) for 4 h at 5°C for immunoprecipitation . MinElute Reaction Cleanup Kit columns ( Qiagen ) were used for purification of the DNA fragments . Enrichment of specific DNA fragments was validated by qPCR at the SCL3 promoter region by comparing immunoprecipitated DNA to the corresponding input sample . Three independent sequencing libraries were generated for the GFP-RGA and WT ChIP using pooled DNA from 7 to 10 individual ChIP preparations . Six independently bar-coded libraries were pooled in a single lane and sequenced by 51-cycle single-end sequencing on the Illumina HiSeq 2000 platform . Sequencing and library construction was performed by the Deep Sequencing Core Facility of the CellNetworks cluster of the University of Heidelberg . All reads were mapped to chromosomes 1–5 of the TAIR10 genome using bowtie2 ( v2 . 0 . 5 ) [71] with default settings of the—fast option . Identification of binding sites was performed independently for each biological replicate using MACS ( v1 . 4 . 2 ) [72] with the following options:—nomodel—shiftsize 75—keep-dup auto-g 1 . 2e8-w-S . Binding summits were considered reproducible between biological replicates when located within 200 bp of each other . For each reproducible binding region a new mean summit position was calculated at the average position of the individual summits using bedtools multiinter ( v2 . 17 . 0 ) [73] and subsequently extended equally on both sides to define a 200 bp binding site . Annotation of bound genes was performed with the help of a toolset ( "Operate on Genomic Intervals" ) provided by the Galaxy server [74–76] as well as the gene annotations of the TAIR10 genome . GFP-RGA-bound genes were defined as those having one or more binding sites within 2 . 5 kb upstream of their transcription start sites ( TSS ) , or 500 bp downstream of the transcriptional end ( TSE ) with no intervening gene between the binding site and the TSS/TSE . Additionally genes were also annotated as bound by GFP-RGA when binding sites occurred within the untranslated region ( UTR ) or intron of a gene . By these criteria , GFP-RGA-associated genes were , in some cases , identified as having more than one binding site , and individual binding sites were found that are associated with up to two genes on opposing DNA strands . A cDNA library from three-day-old etiolated seedlings , prepared in the pACT vector [77] , was screened by Y2H using M5GAI and RG52 ( the equivalent M5 truncated version of RGA ) fused to the Gal4-DNA binding domain ( DBD ) in the pGBKT7 vector ( Invitrogen ) as bait . To test truncated versions of ARR1 , all constructs were made by recombining entry clones to GATEWAY destination vectors via LR Clonase II ( Invitrogen ) . Primers used for plasmid construction are listed in S5 Table . PCR products were cloned into pCR8/GW/TOPO ( Invitrogen ) , then transferred into pDEST22 ( Invitrogen ) to create Gal4-AD fusion ( ARR1-GAL4DBD versions display strong activation of the HIS3 reporter on their own ) . GAI deletions have been previously described [24] . Yeast AH109 cells were cotransformed with specific bait and prey constructs . All yeast transformants were grown on SD/-Trp/-Leu/-His/-Ade medium for selection or interaction tests , in the presence of different concentrations of 3-aminotriazol ( 3-AT ) ( Sigma ) . pENTR clones containing the full length of ARR1 and GAI were transferred into pMDC43-YFC and pMDC43-YFN vectors respectively [78] . BiFC experiments were performed as previously described [79] . Co-IP of GAI and ARR1 in N . benthamiana leaves was performed as previously described [23] , using the corresponding constructs in pEarleyGate-201 ( ARR1 , ARR1ΔDDK ) and pEarleyGate-104 ( GAI ) [80] . Arabidopsis cell suspension derived from wild type Col-0 roots was used for protoplast isolation [81] . Transfections of protoplasts were performed as described [82] , with 3 μg each of myc-GAI and HA-ARR1 expression constructs . Transfected protoplast were cultured for 16 h at RT and then lysed in extraction buffer [25 mM Tris-HCl ( pH 7 . 8 ) , 5 mM EGTA , 10 mM MgCl2 , 75 mM NaCl , 10% ( v/v ) glycerol , 0 . 2% ( v/v ) Tween-20 , 2 mM DTT and 1% ( v/v ) plant protease inhibitor cocktail ( Sigma ) ] . In co-IP assays , proteins were incubated in a total volume of 100 μl of extraction buffer containing 150 mM NaCl , 0 . 2 mg ml-1 BSA and 1 . 5 μg of anti-c-myc antibody ( clone 9E10 , Covance ) . Immunocomplexes were captured on Protein G-Sepharose beads ( GE Healthcare ) , washed three times in 500 μl of washing buffer [1xTBS , 5% ( v/v ) glycerol , 0 . 1% ( v/v ) Igepal CA-630] and eluted by boiling in 25 μl of 1 . 5x Laemmli sample buffer . Proteins were then resolved by SDS-PAGE and blotted to a PVDF membrane ( Millipore ) . The presence of HA-ARR1 protein was detected by a monoclonal anti-HA-peroxidase conjugate antibody ( clone 3F10 , Roche ) with ECL Reagent ( GE Healthcare ) . For co-IP assays in Arabidopsis , 35S::ARR1-YFP-HA and Col-0 wild-type seedlings were grown in MS plates at 22°C under continuous fluorescent white light ( ~50 μmol s-1 m-2 ) for 7 days , being the media supplemented with 10 μM PAC for the last 2 days . Finally , seedlings were soaked in a solution containing 10 μM N6-benzyladenine ( Sigma ) for 2 h . Frozen seedlings were ground with a mortar and a pestle and the resulting powder homogenized in one volume ( 700 μl ) of cold extraction buffer [50 mM Tris-HCl pH 7 . 5 , 100 mM NaCl , 1% ( v/v ) Nonidet P-40 , 1 mM PMSF , and 1x complete protease inhibitor cocktail ( Roche ) ] . Extracts were centrifuged twice for 15 min at full speed in a top bench microcentrifuge at 4°C . Total soluble proteins in the supernatant were quantified by Bradford assay . Forty micrograms of soluble proteins were saved to be used as input , and 500 μg were used for the co-IP . First the extract was pre-cleared by incubating with 15 μl of Dynabeads Protein A ( Life Technologies ) at 4°C for 1 h and 15 min in a total volume of 650 μl . The anti-GFP antibody ( A6465 , Life Technologies ) was cross-linked to Dynabeads Protein A following manufacturer’s instructions ( Life Technologies ) . Pre-cleared extracts were incubated with the cross-linked antibody at 4°C for 1 h and 40 min . Forty micrograms of unbound proteins were saved as control . Beads were washed three times with 300 μl of cold washing buffer [50 mM Tris-HCl pH 7 . 5 , 100 mM NaCl , and 1% ( v/v ) Nonidet P-40] . Proteins were eluted in 70 μl of 1x Laemmli sample buffer by incubating at 95°C for 5 min . Immunoprecipitated proteins were run in an 8% SDS-PAGE , immunoblotted , and detected with anti-GAI antibodies [3] . Subsequently , blots were stripped-out and incubated with anti-HA- peroxidase conjugate antibody ( clone 3F10 , Roche ) . The reporter construct contained six copies of a sequence containing duplicate cis elements bound by type-B ARRs binding site in its wild-type ( TCS ) ( AAAATCTACAAAATCTTTTTGGATTTTGTGGATTTTCTAGC ) and mutant forms ( TCSm ) ( AAAATGTACAAAATGTTTTTGCATTTTGTGCATTTTCTAGC ) as reported ( Müller and Sheen , 2008 ) , upstream of the minimal 35S promoter and the Ω translational enhancer in the pGreenII 0800-LUC vector [83] . DNA fragments containing the cis elements were amplified from the corresponding constructs in pUC18 [61] using the primers indicated in S5 Table . The effector constructs were prepared in pEarleyGate-201 and pEarleyGate-101 ( ARR1 ) , pEarleyGate-203 ( M5GAI ) and pEarleyGate-104 ( GAI and RGA ) . Transient expression in leaves of N . benthamiana was achieved by infiltrating mixtures of Agrobacterium cultures . The reporter:effector ratio was 1:4 for ARR1 , while was 1:4 for GAI and M5GAI . Firefly and the control Renilla LUC activities were assayed from leaf extracts with the Dual-Glo Luciferase Assay System ( Promega ) and quantified with a GloMax 96 Microplate Luminometer ( Promega ) . Control Western blots were performed with proteins extracted from the same experiment , and the ARR1 , GAI , M5GAI , and RGA fusions were detected with anti-HA ( 3F10; Roche ) , anti-GFP ( ab290; Abcam ) , anti-GAI [3] and anti-c-myc ( 9E10; Roche ) antibodies . For gene expression analysis , total RNA was extracted with E . Z . N . A . Plant RNA Mini Kit ( Omega Bio-tek ) according to the manufacturer’s instructions . cDNA synthesis was performed with SuperScript II First-Strand Synthesis System ( Invitrogen ) . qPCR was performed as previously described [84] , using the EF1-α gene for normalization . For microarray analyses , RNA was extracted with RNeasy Plant Mini kit ( Qiagen ) according to manufacturer’s instructions . RNA labeling and hibridization to Affymetrix ATH1 arrays were performed by GeneCore facility at EMBL Heidelberg . Statistical analysis of microarray data was performed using Z-score transformation [63] , and selecting differential genes with p<0 . 05 . Ten-day-old Ler wild type seedlings and the RGA::GFP-RGA line grown in continuous light ( ~50 μmol s-1 m-2 ) were treated with 10 μM PAC ( Duchefa ) for 18 h . Then , N6-benzyladenine ( Sigma ) was added to a final concentration of 5 μM for 6 h; a mock treatment was used as control . ChIP was performed as previously described [85] , using Dynabeads Protein A ( Life Technologies ) and an anti-GFP polyclonal antibody ( ab290; Abcam ) . Relative enrichment was calculated by normalizing the amount of target DNA , first to the internal control gene HSF ( At4g17740 ) and then to the corresponding amount in the input . The same was done with 35S::ARR1ΔDDK:GR x RGA::GFP-RGA F1 crosses . Data are mean and SD of three technical replicates from a representative experiment , out of the two biological replicates performed . To examine the localization of RGA at chromatin in the arr1 arr12 mutant background , ChIP was performed using anti-RGA antibodies [86] . | Plants respond to environmental cues by modulating transcriptional circuits . One mechanism for such modulation involves DELLA proteins . They are promiscuous interactors of transcription factors and , in most cases , this interaction impairs the recognition of the DNA target sequences . Here we show that DELLA proteins are also recruited to multiple locations of the genome where they act as transcriptional coactivators , and we demonstrate how physical interaction with type-B ARRs is relevant for the regulation of meristem maintenance and photomorphogenesis . | [
"Abstract",
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] | [] | 2015 | Genome Wide Binding Site Analysis Reveals Transcriptional Coactivation of Cytokinin-Responsive Genes by DELLA Proteins |
Dengue viral infection is a global health threat without vaccine or specific treatment . The clinical outcome varies from asymptomatic , mild dengue fever ( DF ) to severe dengue hemorrhagic fever ( DHF ) . While adaptive immune responses were found to be detrimental in the dengue pathogenesis , the roles of earlier innate events remain largely uninvestigated . Invariant natural killer T ( iNKT ) cells represent innate-like T cells that could dictate subsequent adaptive response but their role in human dengue virus infection is not known . We hypothesized that iNKT cells play a role in human dengue infection . Blood samples from a well-characterized cohort of children with DF , DHF , in comparison to non-dengue febrile illness ( OFI ) and healthy controls at various time points were studied . iNKT cells activation were analyzed by the expression of CD69 by flow cytometry . Their cytokine production was then analyzed after α-GalCer stimulation . Further , the CD1d expression on monocytes , and CD69 expression on conventional T cells were measured . iNKT cells were activated during acute dengue infection . The level of iNKT cell activation associates with the disease severity . Furthermore , these iNKT cells had altered functional response to subsequent ex vivo stimulation with α-GalCer . Moreover , during acute dengue infection , monocytic CD1d expression was also upregulated and conventional T cells also became activated . iNKT cells might play an early and critical role in the pathogenesis of severe dengue viral infection in human . Targeting iNKT cells and CD1d serve as a potential therapeutic strategy for severe dengue infection in the future .
Public health threat of dengue viral infection is expanding globally and most prominent in tropical and subtropical countries . It is the most significant mosquito- borne viral illness affecting mankind . An estimated 2 . 5 billion people live in the area at risk resulting in 50 to 390 million dengue infections per year [1]–[3] . Dengue infection causes significant morbidity , mortality and leads to hospitalization that consume vast amount of health care spending mostly in endemic areas where resource is scarce [1]–[3] . Currently , there is still no vaccine nor specific treatment , in part due to our incomplete understanding of the disease pathogenesis . Dengue virus ( DV ) is a single stranded RNA virus in the Flaviviridae family . Four serotypes of dengue virus are circulating and cause human illness . The transmission from human to human requires Aedes mosquito vectors [4] . Once infected with DV , the clinical manifestation varies widely from asymptomatic infection , undifferentiated febrile illness to a more typical dengue fever ( DF ) characterized by fever associated with severe headache , myalgia , and bone pain , which are mild and self limited . A small percentage of patients develop a more severe , life threatening dengue hemorrhagic fever ( DHF ) , which could result in dengue shock syndrome ( DSS ) [1] . The hallmarks of DHF/DSS are plasma leakage and hemorrhage that could lead to shock and death which invariably occur within 1–2 days after fever subsided [1] , [5] . Both viral and host factors were shown to contribute to the severity of dengue infection [1] , [6] . While protective immune response is required for viral clearance , the detrimental immune reaction was suggested to be the major cause of severe DHF/DSS [6] . Most previous investigations focused on the detrimental effects of cross-reactive adaptive immune responses known as antibody dependent enhancement [7]–[9] and T cell antigenic sin [10] . However , the study on innate and innate-like immune response in dengue infection that could initiate or even dictate the type of subsequence adaptive immune response is still very limited . Invariant natural killer T ( iNKT ) cells represent a unique population of T cells with innate-like function . iNKT cells express invariant T cell receptor ( iTCR ) recognizing lipid antigens on CD1d , a non-polymorphic MHC class I –like molecule [11] . α-Galactosylceramide ( α-GalCer ) is a potent and specific iNKT cell antigen widely used for iNKT cell activation and identification [11] . A number of exogenous lipid antigens from microbes [12]–[15] and endogenous lipid antigens [16]–[19] were also shown to activate iNKT cells . Upon activation , iNKT cells can rapidly secrete a variety of preformed cytokines such as IFN-α , IL-4 , IL-17A , IL-10 and crosstalk with conventional T cells , B cells , NK cells , macrophages and dendritic cells [11] . iNKT cells were shown to play a role in many disease processes including cancer , autoimmunity , asthma , and infections [11] , [20] , [21] . Their roles in infections were demonstrated for a variety of microorganisms including viruses [13]–[15] , [22]–[25] . The critical roles of iNKT cells were demonstrated in several virus infections [24] , [25] such as herpes simplex virus type 1 and 2 [26]–[28] , respiratory syncytial virus [29] , influenza A virus [30]–[32] , hepatitis B virus [33] , cytomegalovirus [34] , [35] , hepatitis C virus [36] , and HIV-1 [37] . Moreover , patients with primary immune deficiency resulting in iNKT cell defect are more susceptible to severe varicella-zoster virus [38] and EBV infections [39] . Because of these evidence , iNKT cells activation by α- GalCer have been tested as vaccine adjuvant with promising results in animal models of hepatitis B virus [40] , influenza A virus [41] and HIV infections [42] , [43] . The potential role of iNKT cells in pathogenesis of DV infection has never been investigated in human . Two previous reports showed increased number and recruitment of T cells bearing NK cell markers to skin infected with DV in mouse [44] and marmoset models [45] . However , these reports did not use standard methods to identify iNKT cells , so it is unclear if these cells are truly iNKT cells . The only study of iNKT cells in DV infection was done in experimental murine model [46] and suggested a detrimental role of iNKT cells in severe form of DV infection . However , DV does not naturally infect mice and the use of mouse model to represent DV infection pathogenesis in human remains controversial [47]–[49] . Therefore , the study of iNKT cells in human patients is needed . Here , we investigated the potential role of iNKT cells in DV infection in human by examining well-defined clinical samples from a cohort of DV infected children of varying disease severity and at different time points , in comparison to controls . We found that iNKT cells were activated in acute DV infection , and suggesting the involvement of iNKT cells in human severe DV infection . A better understanding of the role of iNKT cells in human DV infection will lead to a better understanding of the intricate control of complex immune responses and immunopathogenesis in dengue infection . Altogether , the advancement in our knowledge will enable the development of novel preventive and therapeutic approaches in the future .
Blood samples were collected from healthy controls and 1–15 year-old patients admitted to Khon Kaen and Songkhla hospitals , Thailand , following written parental informed consent . This project was approved by the ethical committees of Khon Kaen hospital , Songkhla hospital and Mahidol University . Peripheral blood mononuclear cells ( PBMC ) were separated from whole blood by Ficoll-Hypaque density gradient centrifugation and kept in liquid nitrogen for subsequent study . Acute dengue infection was determined by dengue gene identification using reverse transcription PCR ( RT-PCR ) and dengue virus-specific IgM capture ELISA as previously described [50] , [51] . Dengue disease severity was classified according to the World Health Organization criteria ( 1997 ) [5] into dengue fever ( DF ) and dengue hemorrhagic fever ( DHF ) . Other non-dengue febrile illness ( OFI ) patients were defined as patients hospitalized with fever without the presence of dengue infection by both RT-PCR and dengue virus-specific IgM capture ELISA . Blood samples from each patient were collected at different time points during the course of infection . The date were called in relation to the day fever subsided ( day of defervescence , day 0 ) so that “day -1” is one day before the day of defervescence and “week 2” and “month 6” are 2 weeks and 6 months after the day of defervescence , respectively . Random PBMC samples from DF , DHF and OFI were used for analysis in this study . Samples from 11 DF , 19 DHF , 11 OFI patients and 10 healthy controls were evaluated for percentage and phenotype of peripheral blood iNKT cells . The demographic and clinical characteristics , including age , gender , DV serotype , lowest white blood cells count ( WBC ) , highest hematocrit ( Hct ) , lowest platelet ( Plt ) , highest serum aspartate transaminase ( AST ) , alanine transaminase ( ALT ) enzyme , and lowest albumin of each patient with DF and DHF are shown in Table S1 . A different set of patient samples were used to study the function of iNKT cells by ex vivo stimulation due to limited number of PBMC available from each patient . Fourteen DF , 12 DHF , 11 OFI patients and 10 healthy controls were used in these experiments . Table S2 shows demographic and clinical characteristics of the DHF and DF patients whose PBMC were used for functional analysis . All patients studied had secondary DV infection . To analyze the number and phenotypes of iNKT cells and conventional T cells , cryopreserved PBMCs were thawed and rested in cold complete RPMI medium . Cell numbers and viability were estimated by trypan blue exclusion assay . More than 90% cell viability were observed in all samples . Cells were then washed , Fc blocked and stained with the following fluorescence-conjugated monoclonal antibodies; PEcy7-conjugated anti-human CD3 ( BioLegend; CA ) , PE-conjugated PBS57-loaded CD1d tetramer or PE-conjugated unloaded CD1d tetramer ( NIH tetramer facility , USA; PBS57 is an α-GalCer analog ) , FITC-conjugated anti-human CD4 ( BD Pharmingen ) , APCcy7-conjugated anti-human CD8 ( BioLegend; CA ) , and PerCP- conjugated anti-human CD69 ( or isotype control ) ( BD Biosciences ) according to the manufacturer's protocol . Cells were then analyzed by flow cytometry . Cryopreserved PBMCs were thawed and cultured in the presence or absence of α-GalCer 100 ng/ml ( KRN7000 , Funakoshi , Tokyo , Japan ) for 12 hours with brefeldin A ( 10 mg/ml; Sigma-Aldrich ) . Cells were then harvested and stained for the following surface markers and intracellular cytokines after permeabilization according to manufacturer's protocol: PEcy7 conjugated anti-human CD3 antibody ( BioLegend; CA ) , PE conjugated PBS57-loaded CD1d tetramer ( NIH , USA ) , PerCP conjugated anti-human CD69 antibody ( BD Biosciences ) , FITC-conjugated anti-human IFN-γ ( BD Pharmingen ) , APC-conjugated anti-human IL-4 ( eBioscience ) and Alexa700-conjugated anti-human IL-17A ( BD Pharmingen ) or isotype controls . Cells were then fixed with 1% formaldehyde in PBS and analyzed by flow cytometry . PBMC were stained with FITC-conjugated anti-human CD14 antibody ( BD Pharmingen ) , and PE-conjugated anti-CD1d antibody ( BD Pharmingen ) or isotype control ( BD Pharmingen ) . Cells were then fixed and acquired by flow cytometry . Monocytes were gated based on their characteristic appearance on FSC/SSC dotplot and upon CD14 expression . The level of CD1d expression was expressed as the difference in mean fluorescence intensity ( DMFI ) between CD1d staining and isotype control of each sample as baseline . Flow cytometry analysis was performed using BD FACS Canto or BD LSRII flow cytometer via FACS Diva version 4 . 1 . 1 software . FlowJo version 8 . 7 ( Tree star ) was used for data analysis . Data analysis was performed using GraphPad Prism 5 . 0 software and SPSS version 20 . Mann-Whitney test was used for comparison of unpaired data . Wilcoxon signed rank test was used to compare paired data . Spearman's rho correlation test was used for correlation analysis of non-parametric data . P-value of <0 . 05 was considered as statistically significant difference .
The age and gender of patients with DF and DHF in this study were not significantly different . The most common DV serotypes in both groups were DV serotype 1 ( DV1 ) , followed by DV2 , DV3 , and DV4 , respectively . As expected , patients with DHF had significantly lower platelet count , serum albumin and higher liver transaminases when compared to those with DF ( Table S1 and S2 ) . To examine whether the percentage of iNKT cells changes during the course of DV infection , PBMC from DF and DHF patients were evaluated at 3 different time points ( day -1 , day 0 and day 2 weeks ) as previously described ( Figure 1a ) . Lymphocytes were pregated based on their characteristic appearance on forward and side scattered dot plot . iNKT cells were then identified by the expression of both CD3 and PBS57- loaded CD1d tetramer ( as compared to unloaded CD1d tetramer control ) ( Figure 1a , 2a ) . The percentage of iNKT cells within total lymphocytes were not significantly changed over the course of DV infection in both patients with DF ( Figure 1b , Figure S1a ) and DHF ( Figure 1c , Figure S1b ) . When comparing iNKT cells from patients with various severities during febrile phase and controls , the percentage of iNKT cells were also not significantly different between groups of patients ( Figure 1d ) . Absolute number of iNKT cells also showed similar results ( Figure S1c-g ) . To investigate whether iNKT cells are activated in vivo during human DV infection , peripheral blood iNKT cells from dengue-infected individuals with various disease severities were evaluated at different time points . Expression of CD69 in comparison to isotype control was used as an activation marker of iNKT cells ( Figure 2a ) . iNKT cells were activated during acute phase ( day -1 and day 0 ) of dengue infection in both DF and DHF patients ( Figure 2b ) . The percentage of CD69 positive iNKT cells was significantly higher during febrile phase ( day -1 ) ( median 3 . 02%; interquartile range 2 . 18–20 . 33% ) and defervescence phase ( day 0 ) ( 7 . 42%; 3 . 91–13 . 23% ) compared to 2 weeks after fever subsided ( 0 . 50%; 0 . 13–2 . 08% ) in patients with DF ( p<0 . 05 and p<0 . 005 respectively ) ( Figure 2c ) . In patients with DHF , the percentage of CD69 positive iNKT cells was also higher during febrile phase ( day -1 ) ( 27 . 40%; 17 . 20–36 . 80% ) and defervescence phase ( 10 . 00%; 5 . 26–22 . 70% ) when compared to 2 weeks after fever subsided ( 0 . 23%; 0 . 00–0 . 57% ) ( p<0 . 0001 and p = 0 . 0001 , respectively ) ( Figure2d ) . Furthermore , when comparing iNKT cells from patients with various severities during febrile phase ( day -1 ) , patients with DHF have significantly higher percentage of activated iNKT cells ( 27 . 40%; 17 . 20–36 . 80% ) when compared to DF ( 3 . 02%; 2 . 18–20 . 33% ) ( p = 0 . 0149 ) ( Figure 2e ) , suggesting that the activation of iNKT cells associated with disease severity . Moreover , iNKT cells were more activated in dengue-infected patients ( DF and DHF ) than in OFI ( 1 . 77%; 0 . 00–7 . 33% ) and healthy controls ( 0 . 00%; 0 . 00–0 . 51% ) ( Figure 2e ) . iNKT cell activation in OFI is higher than healthy controls ( p<0 . 05 ) , possibly due to the heterogeneous non-dengue infectious etiology of OFI group , some of which could also activate iNKT cells . When cells from each patient were analyzed at 3 different time points , the data clearly showed that the percentage of activated iNKT cells were highest during febrile phase , continuously decreased over the course of infection and barely present by 2 weeks after fever subsided in both patients with DF ( Figure 2f ) and DHF ( Figure 2g ) . No correlation between iNKT cell activation and DV viral load was observed ( data not shown ) . Therefore , our results showed that iNKT cells were activated during acute dengue infection and the level of activation associated with dengue disease severity . To study function of the iNKT cells in DV infection , iNKT cells production of various cytokines ( IFN-γ , IL-4 and IL-17 ) were analyzed by intracellular cytokine staining of gated iNKT cells in comparison to isotype controls . Without stimulation , a small amount of IFN-γ and IL-4 could be detected in iNKT cells from some of the acute dengue-infected patients ( Figure 3a–b , 3e–f ) . Previous reports demonstrated that iNKT cells could become anergic or hyporesponsive to α-GalCer stimulation if they were previously activated in vivo [52] , [53] . To further examine the functional properties of the activated iNKT cells from acute DV infected patients , the PBMC were stimulated with α-GalCer ex vivo and intracellular cytokines were evaluated . PBMC from DF and DHF patients during acute dengue infection ( day 0 ) were compared to those 6 months after infection , when the immunological effects of acute DV infection were assumed to return to baseline . The results were then compared with unstimulated condition and with PBMC from OFI and healthy subjects ( Figure 3 ) . As expected , after α-GalCer stimulation , healthy iNKT cells produced large amount of IFN-γ ( Figure 3c ) . In contrast , the capacity to produce IFN-γ of iNKT cells from acute DV infected and OFI patients was reduced ( Figure 3c , Figure S2a ) . At day 0 , after stimulation , the percentage of IFN-γ+ iNKT cells of patients with DF ( 16 . 35%; 14 . 40–24 . 93% ) and DHF ( 11 . 95%; 6 . 77–18 . 30% ) were lower than those of healthy control ( 32 . 1%; 25 . 90–40 . 70% ) ( p = 0 . 002 and p = 0 . 01 , respectively ) ( Figure 3c ) . Therefore , the functional change of iNKT cells is not limited to dengue infection but also occur in other febrile illness , again , this could be due to the heterogeneous infectious etiology of OFI . No significant difference between DF and DHF was observed . The responsiveness to α-GalCer stimulation returned 6 months after fever subsided to the level similar to those of healthy control ( Figure 3d ) . After α-GalCer stimulation , the percentage of IFN-γ+ iNKT cells from day 0 were significantly lower than those from 6 months after fever subsided in both patients with DF ( day 0: 16 . 35%; 14 . 40–24 . 93% vs . month 6: 29 . 20%; 19 . 65–43 . 00% , p = 0 . 002 ) ( Figure 3a ) and DHF groups ( day 0:11 . 95%; 6 . 77–18 . 30% vs . month 6: 25 . 65%; 15 . 35–37 . 23% , p = 0 . 01 ) ( Figure 3b ) . No statistical significant difference was observed when IL-4+ iNKT cells were examined after α-GalCer stimulation ( Figure 3e–h , Figure S2b ) . Interestingly , the iNKT cells cytokine patterns in DF and DHF appears to be different . Acute DF patients have higher IFN-γ/IL-4 ratio compared to DHF ( Figure 3i ) , suggesting that Th1-like response of iNKT cells in acute DV infection may associate with less disease severity . IL-17A was not detectable in iNKT cells in all conditions with the current stimulation protocol ( data not shown ) , perhaps because the kinetics of IL-17 is different from IL-4 and IFN-γ . To further examine the kinetics of functional response of iNKT cells to α-GalCer , additional time points at day -1 and week 2 were studied ( Figure S3 and S4 ) . The responses at these 2 additional time points were not statistically significant different . However , iNKT cells from DHF at 2 weeks appeared to produce more IFN-γ than at day -1 but due to the limited number of sample , statistical test cannot be performed ( Figure S4b ) . Altogether , the IFN-γ response to α-GalCer seems to reduce during acute DV infection and recover by month 6 after acute DV infection but the rate of recovery may differ between patients . Taken together , these findings suggested that iNKT cells from acute dengue infected patients were previously activated in vivo and upon restimulation with α-GalCer ex vivo , they have reduced IFN-γ production . Importantly , skewing toward Th1-like cytokine pattern of iNKT cells during acute DV infection may associate with less clinical severity . Our next question was how iNKT cells get activated during acute DV infection . iNKT cells were known to be activated by cognate recognition of iNKT cell receptor to antigen presented on CD1d . In some circumstances , they can be activated indirectly by cytokines or might require both cognate recognition and cytokine-driven activation [54] . To first investigate if iNKT cells could be activated through the CD1d-dependent pathway , we measured CD1d expression on monocytes from the same patient samples used to study iNKT cells . Monocytes were examined because they are abundant antigen presenting cells in peripheral blood , known to be infected by dengue virus both in vivo and in vitro , and also known to activate iNKT cells in other circumstances . Monocytes were first gated ( Figure 4a ) and the level of CD1d expression on monocytes at different time points was then analyzed in comparison to isotype control in both DF and DHF groups ( Figure 4b ) . Interestingly , the expression of CD1d was highest on monocytes during day -1 and day 0 , in both DF ( median DMFI 16058;13304–18998 ( day -1 ) and 15682; 13820–20191 ( day 0 ) ) and DHF ( 17499; 14987–22505 ( day -1 ) and 17991; 15896–21235 ( day 0 ) ) patients . The level of CD1d expression decreased significantly by 2 weeks after fever subsided in both DF ( 10184; 7962–11852 ) ( p = 0 . 002 ( day -1 vs . 2 weeks ) , p = 0 . 01 ( day 0 vs . 2 weeks ) ) and DHF ( 9645; 8999–12712 ) ( p = 0 . 008 ( day -1 vs . 2 weeks ) , p = 0 . 002 ( day 0 vs . 2 weeks ) ) ( Figure 4c ) to the same level as healthy control ( 10504; 9704–13541 ) ( Figure 4d ) . The similar trend is clearly observed when data from the same patients at 3 different time points were analyzed ( Figure 4e ) . Monocytic CD1d expression at 6 months was similar to those at 2 weeks ( data not shown ) . Furthermore , when comparing between patients with different dengue disease severity , the level of monocyte CD1d expression at day -1 was higher in DHF than in healthy control ( 10504; 9704–13541 ) ( p = 0 . 01 ) , but not significantly higher than that of DF ( p = 0 . 27 ) ( Figure 4d ) . Thus , CD1d expression on monocytes was upregulated in acute DV infection . Moreover , the level of CD1d expression on monocytes positively correlates , although weakly , with the level of iNKT cell activation ( r = 0 . 35 , p<0 . 05 ) . The correlation is stronger when the DHF subgroup was analyzed ( r = 0 . 7 , p = 0 . 002 ) ( Figure S5 ) . These results suggested that CD1d was upregulated in monocytes during acute DV infection . However , future experiments are needed to delineate if iNKT cells were actually activated in a CD1d-dependent manner in DV infection . In general , once iNKT cells get activated , they were known to influence adaptive T cell immune response . To investigate if iNKT cells activation were associated with the activation of conventional T cells in DV infection , the percentage of CD8+ and CD4+ T cells as well as their activation state were evaluated in the PBMC samples that were used for iNKT cells studies . Lymphocytes were pregated based on their characteristic appearance on forward and side scattered dot plot . CD8+ and CD4+ conventional T cells were then identified by the expression of CD8 or CD4 together with CD3 . CD69 in comparison with isotype control was used as activation marker of both CD4+ and CD8+ T cells ( Figure S6a , c ) . Similar to iNKT cell activation , conventional CD8+ T cells were activated during acute phase of dengue infection in both DF and DHF patients ( Figure 5a , b ) . The percentage of CD69+CD8+ conventional T cells at day -1 ( 7 . 62%; 3 . 36–10 . 92 ) was higher than 2 weeks after fever subsided ( 0 . 56%; 0 . 24–1 . 48 ) in patients with DF ( p = 0 . 01 ) ( Figure 5a ) . In patients with DHF , the percentage of CD69+ CD8+ conventional T cells was higher at day -1 ( 10 . 35%; 7 . 99–13 . 08 ) and day 0 ( 2 . 40%; 0 . 52–8 . 71 ) when compared to 2 weeks after fever subsided ( 0 . 30%; 0 . 14–0 . 57 ) ( p<0 . 0001 and p = 0 . 0008 respectively ) ( Figure 5b ) . Furthermore , during febrile phase , patients with DF ( 7 . 62%; 3 . 36–10 . 92 ) and DHF ( 10 . 35%; 7 . 99–13 . 08 ) have significantly higher percentage of activated CD8+ T cells when compared to OFI ( 0 . 76%; 0 . 15–1 . 38 ) , and healthy controls ( 0 . 32%; 0 . 026–0 . 565 ) ( DF vs OFI , p = 0 . 01 , DF vs healthy , p = 0 . 005 , DHF vs OFI , p<0 . 0001 and DHF vs healthy , p = 0 . 0001 respectively ) . At day -1 , the percentage of activated CD8+ T cells of DHF appeared to be higher than DF , but did not reach statistical significance ( Figure 5c ) . This is different from previous reports that showed a higher CD8 activation in DHF compared to DF [55]–[57] , possibly due to the small sample size , high variability of the data and different time point analyzed . When cells from each patient were analyzed at 3 different time points , most of the data showed the percentage of activated CD8+ conventional T cells were highest during febrile phase , continuously decreased over the course of infection and almost absent by 2 weeks after fever subsided in both patients with DF ( Figure 5d ) and DHF ( Figure 5e ) . The activation of CD8+ conventional T cells correlates with iNKT cell activation ( r = 0 . 56 , p<0 . 0100 ) especially in DHF patients ( r = 0 . 69 , p<0 . 0100 ) ( Figure S6b ) , suggesting that iNKT cell activation may associate with the activation of CD8+ conventional T cells especially in DHF patients . At the analyzed time point , CD4+ conventional T cells were also activated during acute DV infection but to a lesser extent than CD8+ T cells and were more prominent in DHF patients ( Figure 5f–j ) . In DHF , but not DF patients , CD4+T cells showed higher activation during day -1 ( 0 . 72%; 0 . 36–1 . 44 ) and day 0 ( 0 . 38%; 0 . 11–0 . 59 ) when compared to 2 weeks afterward ( 0 . 07%; 0 . 03–0 . 15 ) ( p<0 . 0001 , p = 0 . 013 ) ( Figure 5g , j ) . During day -1 , DF and DHF patients showed increased CD4+ T cells activation when compared to healthy controls or OFI ( Figure 5h ) . No significant difference was observed between DF and DHF ( Figure 5h ) , although it appears that only a few DF patients showed increased CD4+ T cell activation ( Figure 5h , i ) . The level of CD4+ T cell activation also weakly correlates with the level of iNKT cells activation ( r = 0 . 41 , p<0 . 01 ) , but the correlation is more prominent in DHF ( r = 0 . 57 , p<0 . 01 ) ( Figure S6d ) .
Our finding is the first to show that human iNKT cells are activated during acute dengue viral infection and the level of activation associates with disease severity . The activation subsided by 2 weeks after fever subsided . Furthermore , the activated iNKT cells from acute DV infected patients produced less IFN-γ in response to subsequent α-GalCer stimulation ex vivo . During acute DV infection , monocytes also upregulated CD1d expression and conventional T cells were activated . The association between the level of iNKT cell activation and the severity of dengue infection in our human data suggests that activated iNKT cells might contribute to the pathogenesis of severe dengue infection . Further investigations are needed to dissect detailed mechanistic involvement of activated iNKT cells in severe dengue disease pathogenesis . It is possible that the activated iNKT cells contribute to immunopathology in severe dengue infection . Alternatively , activated iNKT cells could play a regulatory role that might impede viral clearance resulting in the severe disease . We favor the former hypothesis because our data showed that the activation state of iNKT cells correlates with the activation of conventional T cells known to play pathogenic role in severe disease . In addition , previously published murine data showed that iNKT cell deficient mice suffer less sign of plasma leakage , a cardinal feature of DHF , and survived more than wild type mice [46] . The plasma leakage and death were restored after iNKT cells reconstitution [46] . These data together suggested that iNKT cells might play a detrimental role in dengue virus infection in mice and human . Despite the finding of iNKT cell activation during acute dengue infection , the change in number of iNKT cell in peripheral blood was not observed during the course of infection . It is possible that iNKT cell migrate from intravascular space to affected tissues unexamined as suggested in some animal models [44] . Moreover , some activated iNKT cells might downregulate their iTCR rendering them undetectable by α-GalCer-loaded CD1d tetramer staining [11] . When the functional capacity of iNKT cells from dengue-infected patients was evaluated , these iNKT cells had reduced α-GalCer mediated IFN-γ production . Six months after fever subsided , their IFN-γ production capacity upon α-GalCer stimulation resumed to the level similarly found in healthy control , possibly from a new pool of iNKT cells . The rate of functional recovery varies among patients as seen at 2 weeks after fever subsided . This finding was not surprising as several previous reports consistently showed an unresponsiveness of previously activated iNKT cells to subsequent stimulation , a phenomenon known as iNKT cell anergy [52] , [53] , [58] . Similar to our finding , they observed reduction in IFN-γ , but not IL-4 , in response to subsequent α-GalCer stimulation . Therefore , this finding support that iNKT cells were activated during acute dengue virus infection in vivo , rendering them less responsive to subsequent stimulation ex vivo , while their functional capacity returned 6 months after the fever subsided . Interestingly , iNKT cells from acute DF patients has higher IFN-γ/IL-4 ratio after ex-vivo α-GalCer stimulation than those from acute DHF patients . This finding suggests that cytokines pattern produced by iNKT cells could possibly influence DV disease severity . It would be interesting to know the pattern of cytokine production of iNKT cells in vivo during the actual dengue infection . Unfortunately , we could detect only small amount of intracellular cytokines on iNKT cells from patients without any stimulation , which may be because they secreted most cytokines in vivo or because our detection sensitivity is limited by using cryopreserved PBMC . Further study is warranted to delineate the function of iNKT cells during acute DV infection in vivo . In parallel with iNKT cell activation during acute DV infection , monocytic CD1d surface expression was upregulated . This finding suggests the possible involvement of CD1d on iNKT cell activation through cognate recognition pathway although further experiments are needed to demonstrate how iNKT cells are activated in acute dengue infection . Moreover , CD1d expression on other antigen presenting cells beside monocytes such as dendritic cells may be interesting to examine . Some viruses such as coxakievirus B3 [59] and hepatitis C virus [60] are known to upregulate CD1d expression and activate iNKT cells while others evade iNKT cell recognition by downregulating CD1d , such as Kaposi sarcoma-associated herpes virus [61] , herpes simplex virus type 1 [62] , HIV type 1 [63] , [64] and human papilloma virus [65] . Since viruses do not contain viral lipid antigens , it is postulated that viral infection may alter endogenous lipid presented on CD1d and activate iNKT cells with or without help from cytokines [66] , [67] . Since viruses do not contain viral lipid antigens , altered endogenous lipid might be presented on CD1d [29] . Indeed , recent data suggested alteration of lipid metabolism in DV infected cells but their importance in iNKT cell activation is not yet known [68] . Other possible mechanism to activate iNKT cells , especially cytokine mediated activation , was not evaluated and warrants further study . Cytokines of special interest include , but not limited to , IL-12 , IL-18 , IL-1b and IL-23 . Further investigation is needed to delineate the detail of how dengue virus upregulates CD1d and how exactly iNKT cell activation was achieved in human DV infection . Once iNKT cells are activated , they are known to influence other immune cells both in innate response such as NK cells , dendritic cells and in adaptive T cell and B cell responses [11] , [20] . T cells are very important arm of immune defense against viral infection , but T cell overactivation can lead to immunopathology in dengue infection [69] , [70] . Our results showed the association between iNKT cells activation , T cell activation and disease severity . Consistently , in murine model , mice without iNKT cells had less T cell response and less dengue disease severity [46] . However , whether iNKT cell activation leads to T cells activation in human DV infection is not known and require further study . The possible crosstalk of iNKT cells with other immune cells such as B cells and NK cells in DV infection are also subjects of interest for future study . Secondary dengue infection is associated with higher disease severity . It would be interesting to compare iNKT cell response in primary and secondary dengue infection . However , because Thailand is a hyper endemic area , most of our cohort samples are secondary DV infection . Therefore , primary infection was not evaluated in this current study . In summary , we provide the first evidence that iNKT cells may play a role in human DV infection , one of the most important and expanding global health problems . As neither vaccine nor specific treatment are available for DV infection , and detrimental immune response might cause severe disease rather than protect the host , a better understanding of how immune response are regulated is crucial . We showed here the possible involvement of iNKT cells in human DV infection . Therefore , CD1d and iNKT cells may serve as attractive targets for designing novel strategy to help alleviate suffering from DV infection in the future . | Almost half of the world population is at risk of dengue viral infection . The disease severity varies from mild to a deadly form-which is caused mainly by host overt immune reaction . Earlier studies focused on the disease-causing roles of adaptive immune cells - cells that are highly specific but require time and signal from rapidly activating immune cells to become active . Invariant Natural Killer T ( iNKT ) cells are unique T cells that get activated rapidly and can control later adaptive response by secreting cytokines . They can be activated by lipid loaded on CD1d , an antigen presenting molecule . However , their role in human dengue infection was not known . Here , we studied iNKT cells from dengue infected children and found that they were activated . Importantly , the more severe the disease , the higher level of iNKT cells activation . Their cytokine patterns also differ from those of healthy donors . Moreover , together with iNKT cells activation , the level of CD1d was higher and T cells became active . Therefore , iNKT cells likely play a role in the pathogenesis of human dengue infection . New drugs targeting iNKT cells might help dampen the disease severity before the adaptive immune cells become too active . | [
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"infe... | 2014 | Invariant NKT Cell Response to Dengue Virus Infection in Human |
Babesia , a tick-borne genus of intraerythrocytic parasites , is understudied in humans outside of established high-endemic areas . There is a paucity of data on Babesia in Africa , despite evidence that it is regionally present . A pilot study suggested that Babesia was present in a rural district of Tanzania . A cross-sectional study was conducted July-August 2017: residents in a case hamlet that had clustering of subjects with high signal-to-cut off ( S/CO ) ratios for antibodies against B . microti in the pilot study , and a control hamlet that had lacked significant signal , were evaluated for B . microti . Subjects aged ≥15yrs ( n = 299 ) underwent clinical evaluation and household inspections; 10ml whole blood was drawn for Babesia transcription mediated amplification ( TMA ) , B . microti indirect fluorescent antibody testing ( IFA ) and rapid diagnostic testing ( RDT ) for Plasmodium spp . Subjects aged <15yrs ( n = 266 ) underwent a RDT for Plasmodium and assessment by ELISA for B . microti antibodies . A total of 570 subjects participated ( mean age 22 [<1 to 90yrs] ) of whom 50 . 7% were female and 145 ( 25 . 5% ) subjects were Plasmodium RDT positive ( + ) . In those <15yrs , the median ELISA S/CO was 1 . 11 ( IQR 0 . 80–1 . 48 ) ; the median S/CO in the case ( n = 120 ) and control ( n = 146 ) hamlets was 1 . 19 ( IQR 0 . 81–1 . 48 ) and 1 . 06 ( IQR 0 . 80–1 . 50 ) respectively ( p = 0 . 4 ) . Children ≥5yrs old were more likely to have a higher S/CO ratio than those <5yrs old ( p<0 . 001 ) . One hundred ( 38% ) subjects <15yrs were Plasmodium RDT+ . The median S/CO ratio ( children <15yrs ) did not differ by RDT status ( p = 0 . 15 ) . In subjects ≥15yrs , no molecular test was positive for Babesia , but four subjects ( 1 . 4% ) were IFA reactive ( two each at titers of 128 and 256 ) . The findings offer further support for Babesia in rural Tanzania . However , low prevalence of seroreactivity questions its clinical significance .
Babesia is a ubiquitous [1 , 2] genus of intraerythrocytic , apicomplexan parasites , that is increasingly recognized as posing risk to human health . Over 100 species of Babesia have been shown to infect vertebrate hosts yet only a few are known to infect humans , of which Babesia microti is overwhelmingly representative . Babesia is transmitted principally via the ectoparasitism of ixodid ticks . In the case of B . microti , its principal vector , Ixodes scapularis ( the black-legged or deer tick ) , also transmits Borrelia burgdorferi ( Lyme disease ) , Anaplasma phagocytophilum ( human granulocytic anaplasmosis ) and Borrelia miyomotoi ( relapsing fever ) . Babesiosis , the clinical disease named for infection with any of the Babesia species , is frequently uneventful in the immunocompetent human host following a mild , self-limiting or even subclinical course . Symptoms , when they do occur , are those of mild flu-like illness ( e . g . fever , myalgia , fatigue , headache and chills ) . In the case of uncomplicated babesiosis , infection is treatable with a short course of a combination azithromycin and atovaquone [3] . However , Babesia poses both diagnostic and clinical challenges . First , typical symptoms and signs of babesiosis are non-specific requiring some level of vigilance for a parasite that has historically been neglected . As such those practicing outside of highly endemic areas may lack awareness of Babesia , contributing to delays in diagnosis , with concomitant risk of complicated or severe infection . Second , babesiosis in certain patient subsets , notably those with asplenia , at extremes of age , and/or who are immunocompromised are at high risk for severe infection [3] . Babesia is related to Plasmodium ( malaria ) with which it shares pathologic and clinical features . As in the case of malaria , Babesia-parasitized red blood cells are subject to hemolysis accounting for clinical complications that include hemolytic anemia , cardiorespiratory/renal failure , disseminated intravascular coagulation and even death [3] . Third , Babesia has the ability to establish persistent , asymptomatic infection is some individuals [4] . The mechanism for this is not well understood but , indirectly , poses risk to the blood supply , given that asymptomatic , parasitemic blood donors may unwittingly contribute parasitemic blood to transfusion recipients [5 , 6] . Babesia is transfusion transmissible via red blood cell containing products . With the exception of the United States where regional Babesia screening of blood donors was mandated in 2019 , blood donor screening for Babesia is not in effect elsewhere in the world . Transfusion recipients are at high risk for severe babesiosis given their overrepresentation of risk factors ( e . g . immunosuppression , sickle cell disease etc . ) . Furthermore , severe anemia is the primary indication for red blood cell transfusions rendering transfusion recipients relatively intolerant of Babesia-associated hemolysis , which may account for the high mortality ( ~20% ) reported following transfusion transmitted babesiosis ( TTB ) [6 , 7] . Recognition of risk of TTB in the United States ( US ) has spurred development of new serological and molecular assays , with a view toward blood donor Babesia screening [8–11] . Although the increase in tick-borne and TTB in the US has garnered much attention [12 , 13] , Babesia should be viewed as a global pathogen . Beyond its historical recognition in parts of Europe [14–16] , there is a growing number of reports of human babesiosis from areas where Babesia has not been well publicized such as in South America [17] , Asia [18–21] and Australia [22] . An expanding repertoire of highly sensitive Babesia diagnostic assays affords opportunity for global surveillance for this neglected pathogen . This motivated for a pilot study in Africa [23] where , despite a paucity of Babesia surveillance data in humans , there was plausible evidence that Babesia was present [24–27] . Babesia’s presence in ticks and its role as a significant veterinary pathogen in Africa , is well established [24–26 , 28–30] . Of particular interest , B . microti [25] and B . microti-like parasites [31] have been recovered from non-human primates in Africa . The pilot study , which evaluated dried blood spots from 1–5 yr old children in Kilosa District , Tanzania , using a B . microti ELISA assay , demonstrated clustering of individuals with high signal to cutoff ( S/CO ) ratios in a relatively small number of hamlets and an increase in seroreactivity with age [27] . While suggestive of local exposure , in the absence of confirmatory and ancillary testing , the results were viewed as preliminary . An understanding of Babesia’s role in disease in pastoral African communities is important to guide empiric antimicrobial therapy . Furthermore , malaria is widely endemic in Africa: Babesia is morphologically similar to Plasmodium spp . on microscopy , which could contribute to misdiagnosis and underreporting in those areas where both parasites are encountered , as has been reported , elsewhere [19] . The objective of the Babesia Observational Antibody ( BAOBAB ) study was to determine the prevalence of exposure to Babesia in children age <15 , using a test for antibodies , and to assess active infection as well as past exposure in adults age 15 years and older . We conducted a whole population screen in two communities . If Babesia was present , we sought to gain insight into the risk factors for exposure that might be amenable to intervention .
Ethical approval for the study was obtained from the Tanzanian National Institute for Medical Research and the Institutional Review Board of the Johns Hopkins School of Medicine . Written informed consent was obtained from all participants . In the case of minors , consent was obtained from guardians and additional assent was obtained in the case of children aged 7-17yrs . A cross-sectional study was conducted July-August 2017 in two hamlets in Kilosa District , Tanzania that had participated in the preceding pilot study . The latter was confined to children aged 1–59 months . Residents in a case hamlet ( “119”; Kigobele ) that had clustering of subjects with high signal-to-cut off ( S/Co ) ratios for antibodies against B . microti in the pilot study , and a control hamlet ( “483”; Manungu; Kiduhi village ) that had lacked significant signal , were evaluated for B . microti . In addition to clinical evaluation and household inspections , subjects aged ≥15yrs ( n = 299 ) had 10ml whole blood drawn for evaluation by transcription mediated amplification ( TMA ) for B . microti , B . divergens , B . venatorum and B . duncani , indirect fluorescent antibody testing for B . microti and rapid diagnostic testing ( RDT ) for Plasmodium spp . Those aged <15yrs ( n = 266 ) underwent RDT for Plasmodium and serological assessment with an ELISA for antibodies to B . microti . All residents in the participating hamlets were eligible to participate in the study . A census of each of the houses in the hamlets was conducted prior to sample collection . During the census , a trained field team visited each of the houses and interviewed the head of household . The field team assessed the house for potential risk factors for vector borne illness . These included material composition of the house ( i . e . wall , roof and window construction ) , sleeping conditions ( i . e . number of individuals per room , the presence of bed nets , whether sleeping on animal skins vs . a bed ) and contact with animals . The perimeter of the house was inspected for proximity to grass and/or an animal pen . If the guardian of children living in the house was present , informed consent was sought , and an invitation extended for a follow-up clinical evaluation and sample collection at a central site in the hamlet . The household members presented on a designated day for the clinical evaluation and sample collection . This was conducted under full informed consent from adults or legal guardians ( in the case of children ) . Assent was also obtained from minors ≥7yrs old . Explanation was provided in Kiswahili . Maasai was used in hamlet 483 in select cases . The clinical evaluation included enquiry regarding recent symptoms and signs of babesiosis , recent diagnosis and/or treatment for malaria and ongoing antibiotic or antimalarial therapy at time of evaluation . Vital signs were documented . Procedures differed by subject age . For subjects aged >1yr but <15yrs , a finger stick was performed on each of the participants and dried blood spot ( DBS ) collected ( i . e . filter paper that was blotted with the subject’s blood ) ; testing included a point of care hemoglobin evaluation ( HemoCue , USA ) and rapid diagnostic testing ( RDT ) for malaria ( Paracheck Pf , Orchid Biomedical Systems , Goa , India ) [32] , which were performed in accordance with the manufacturer’s instructions . The DBS were stored refrigerated with a desiccant , pending testing . Subjects ≥15yrs underwent phlebotomy: 2 EDTA tubes were collected ( total 7-10mL whole blood ) . The blood was processed as follows: one of the tubes was aliquoted directly into cryovials as whole blood . The second tube was centrifuged and used to prepare red blood cell and plasma aliquots . All aliquots were processed the day of sampling and frozen ( -18C ) pending shipment to the US where testing was conducted . The samples were maintained frozen until testing was initiated .
A total of 266 of 271 ( 98 . 2% ) of those subjects <15yrs old had DBS available for Babesia evaluation ( Table 2 ) . The signal to cut-off ( S/Co ) ratios increased by age: the median ( Inter Quartile Range [IQR] ) and range were 0 . 94 ( 0 . 72 , 1 . 25 ) in children less than 5 years , and 1 . 27 ( 0 . 94 , 1 . 70 ) in children >5yrs ( p<0 . 001 ) ( Table 2 ) . With the exception of age , there was not a significant association between the S/Co ratio and gender , the presence of fever and malaria status as ascertained by RDT . In those households with ≥2 children with an S/Co ratio >1 . 6 , there was no association between the S/Co ratio and the material composition of the house or proximity of the house within 10m of an animal pen . There was a suggestive association between crop storage in the house and higher S/Co ratio ( Table 3 ) . When comparing those with an S/Co > 1 . 6 vs . those with an S/Co ≤1 . 6 , the only significant association was that of the number of children sleeping in the room ( p = 0 . 02 ) . All of the households with ≥2 children with S/Co ≥1 . 6 lived in houses where crops were stored inside . There was no association with sleeping conditions and room characteristics , including the presence of different domestic animals in the rooms , sleeping on animal skins and the presence of bed nets ( Table 4 ) . A total of 291 subjects ≥15yrs contributed samples that were tested by IFA for antibodies against B . microti , four ( 1 . 4% ) of whom were IFA reactive ( two each at titers of 128 and 256 ) . A further 28 ( 9 . 6% ) were inconclusive . There was a significant association with older age ( p = 0 . 006 ) ; there were no significant associations between IFA positivity and gender , fever or malaria status ( i . e . as ascertained by RDT ) ( Table 5 ) . Two of the IFA positive subjects reported a history of malaria in the preceding 6-months; two did not . No risk factors were significantly associated with antibody status in adults , although there was again a suggestion of increased risk with crops stored inside the house; all of the antibody positive adults had crops stored inside the house ( Table 6 ) . None of the TMA test results were reactive .
Findings from our study suggest that B . microti is present in the two surveyed African communities . However , given the low observed rate of seroreactivity , its clinical impact in these communities is uncertain and potentially low . At least in those aged 15 or older , none had evidence of active parasitemia as reflected by molecular ( TMA ) testing for Babesia infection . The low numbers of seroreactive individuals is a constraint that may have impacted the findings . Larger sample sizes would be needed to ascertain true prevalence of exposure . While none of the postulated risk factors for exposure were statistically significantly associated with antibody positivity , there is a strong suggestion that storing crops , in this case , maize and millet , inside the houses might lead to greater exposure . While plausible that ticks , which have attached themselves to crops or their associated plant debris , could place residents at risk of tick bites and associated Babesia transmission , this needs to be interpreted in the context of multiple negative risk factors . The study also revisits the challenges of investigational study of a neglected pathogen . The study offers further support for the occurrence of Babesia infection in humans in Africa . Evidence for this is as follows: first , there were individuals with high S/Co ratios in the younger age group and there was also an association between seroreactivity ( based on an assigned cutoff ) and age , which is to be expected . We also found four seroreactive cases in the older “adult” age group at modest titers ( 128 and 256 ) ; this rate ( 1 . 4% ) of seroreactivity ( as ascertained by IFA ) is not dissimilar from that in established , high endemic areas such as those in the United States [35] . The absence of molecular reactivity ( where evaluation was restricted to the older age group ) suggests that at the time of the study , there were no active infections . This was not surprising: although a molecular result is a better correlate of active parasitemia , only about 8–20% of seroreactive individuals are expected to have a NAT reactive result [5 , 33 , 36] . Furthermore , this was a surveillance study of local residents rather than targeted assessment of acutely ill individuals . Not unique to this study , correlation between seroreactivity and molecular reactivity is poorly defined [37] . Unlike the preceding pilot study [23] , the seroreactivity–at least in the younger group of subjects- was not associated with RDT positivity for malaria . While the reasons for this difference are not entirely clear , there are several possible explanations . First , the pilot study covered a much broader range of populations ( villages/hamlets ) than the present study . The latter was limited to only two hamlets , whereby differences in the populations may have contributed to the observation ( or lack thereof ) . Second , the relationship between S/Co and malaria RDT result may have been correlative rather than causal ( i . e . perhaps similar risk factors contributed to both results ) , confounding the true causes for each finding in the study populations . Third , stochastic effect cannot be definitively excluded , particularly given the modest number of samples . Other factors that were considered include the specificity of the RDT . The RDT that was used targets histidine-rich protein 2 ( HRP-2 ) , which is specific for P . falciparum . The assay is well established , having been used in multiple studies , both in Tanzania[38–40] as well as regionally[41 , 42] . While sensitivity of the assay is reportedly high ( 90–100% ) , its specificity has been more variable ( 52–99 . 5% ) [38 , 43] . It is uncertain to what extent this impacted the findings . There still remains the possibility of cross-reactivity with other pathogens , including other Babesia species such as B . bigemina and B . bovis [29 , 30] and parasites that have been reported ( e . g . Entopolypoides macaci [44] , Theileria [45] regionally . Independent of whether showing zoonotic potential , it is plausible that exposure to these other parasites can confound the serologic findings for B . microti . This study has limitations . First , the testing approach was not uniform across the study population . We elected to conduct minimally invasive sampling in those aged 15 or under . Consequently , only DBS were available for this group , precluding head to head comparison with the older group of subjects in which formal blood sampling was undertaken . The larger volume in the older age group allowed for IFA and molecular assessment . In hindsight , a better approach might have been to apply the same test ( ELISA ) to all subjects . Second , as described in the preceding pilot study , the B . microti ELISA had not been validated for this population or setting [23]; instead it had been developed for blood donor screening for antibodies against B . microti in the US using plasma or serum samples . In this case , the testing protocol was modified to allow DBS testing . In addition to differences in test performance , the environment imposes its own challenges , whereby the possibility of false positivity and/or cross-reactivity with other local pathogens merits consideration . Similarly , IFA cut offs have not been developed for this our study population; in the US , the CDC recommends a titer of ≥ 256 ( or ≥ 64 in epidemiologically linked blood donors or recipients ) for surveillance [46] . Further , there are no data that compare the actual IFA assay that was used in this study to the ELISA . Nonetheless , during the ELISA validation there was a reported concordance between EIA and IFA of 99 . 34%[8] . Further , in a subsequent study , 91% of IFA-positive clinical babesiosis patients were ELISA positive [33] . The caveat is that the current study did not select for individuals with clinical babesiosis . As such , the expected level of concordance is uncertain . Third , there isn’t a gold standard ( i . e . reference ) test for Babesia . Each assay offers support for or against diagnosis , yet alone fails to address the diagnostic uncertainty . As a neglected pathogen , reference standards are somewhat incomplete and most data pertaining to diversity of human Babesia isolates have been regionally focused ( i . e . in the US ) [47] and may not be applicable to the target location . While the preceding pilot study lend credence to the findings , true prevalence data are lacking . We acknowledge that the positive predictive value of the individual assays in this setting is unknown . As an exploratory endeavor , we tried to compensate for any confounding interference by adjusting cut-offs accordingly . For example , for the interpretation of risk in the context of the ELISA results , a conservative , provisional S/Co ratio of 1 . 6 was applied . The S/Co of 1 . 6 was derived from a previous validation study on U . S . blood donors in which all seroreactive subjects who were also PCR positive exhibited an S/Co > 1 . 6 [33 , 37] . This is not to say that PCR or similar molecular reactivity is a gold standard; rather a higher S/Co ratio reflects a stringent threshold for exposure with or without active parasitemia . In our study , the absence of TMA reactivity offers convincing evidence that none of the subjects in the older group were actively infected with the four species targeted by the Procleix Babesia assay . Fourth , without a complete travel history one cannot be certain that exposure to B . microti occurred outside of the two hamlets . Finally , to echo conclusions from the preceding pilot study , multidisciplinary input , with insight into the local entomology and veterinary input , would help to contextualize the findings by assessing the ecological suitability of the target environment for supporting tick exposure . While zoonotic Babesia spp . have been isolated from ticks in Africa ( e . g . Nigeria ) [28] , B . microti—specifically—has not yet been recovered from regional ticks . As such the putative tick vector is unknown . Furthermore , high homology ( 97 . 9% sequence identity ) between B . microti and E . macaci , could impede the ability of existing nucleic acid or serologic assays to distinguish the two parasites [44] . There is good evidence of regional Babesiosis in domestic and animal populations . This does not necessarily translate to human risk . There is value to surveillance of Babesia in novel populations . This is particularly the case in Africa and other settings where malaria is endemic . Febrile illness in low resource settings is all too frequently treated empirically as malaria , without laboratory confirmation . Such ignores a broad differential diagnosis . In one study in Northern Tanzania , 60 . 7% of subjects who presented with fever were diagnosed with malaria yet only 1 . 6% of cases were ultimately confirmed as having malaria [48] . While empiric treatment likely stems from local resource constraints , specifically a lack of capacity for laboratory investigation [49] , there are fundamental problems with this strategy . Misdiagnosis and treatment delays may have serious if not fatal consequence , while inappropriate antimicrobial therapy also risks treatment failure and development of resistance , broadly detracting from its effectiveness across a range of pathologies . In conclusion , our study further supports the notion that B . microti is encountered locally in Tanzania , at least in two communities in Kilosa , district . The study’s findings raise questions about the clinical significance of Babesia infection ( at least B . microti ) in this setting yet confirms the value of exploratory investigations ( including in Africa ) . Pilot investigation has yielded unexpectedly high prevalence of Babesia in other populations [17] . Where there is active infection , misdiagnosis of babesiosis has serious clinical ramifications that might otherwise be avoided through timely intervention . This further argues for rapid , point of care diagnostic tools to expand surveillance in remote or low-resourced settings . | Babesia , a family of tick-borne parasites , causes babesiosis , a disease that is very similar to malaria . Babesia species are globally ubiquitous yet understudied in humans outside of a few areas of the world , most notably in the United States . There is very little , published information on Babesia in humans in Africa . We conducted a study of two rural communities in Tanzania where earlier findings had suggested Babesia was present . Dedicated study teams visited households in the two communities to collect information about the residents’ health as well as factors that could pose risk of exposure to ticks and other infectious diseases . The residents of the two communities also had samples collected for Babesia evaluation . The test results revealed that a few of the residents had likely been exposed to Babesia in the past but were not actively infected at time of the assessment . The findings provide additional support for Babesia’s presence in human populations in Africa . This is important as Babesia infection can mimic other infections , notably malaria . | [
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"babesiosis",
... | 2019 | The Babesia observational antibody (BAOBAB) study: A cross-sectional evaluation of Babesia in two communities in Kilosa district, Tanzania |
Tsetse flies ( Glossina spp . ) are vectors of parasitic trypanosomes , which cause human ( HAT ) and animal African trypanosomiasis ( AAT ) in sub-Saharan Africa . In Uganda , Glossina fuscipes fuscipes ( Gff ) is the main vector of HAT , where it transmits Gambiense disease in the northwest and Rhodesiense disease in central , southeast and western regions . Endosymbionts can influence transmission efficiency of parasites through their insect vectors via conferring a protective effect against the parasite . It is known that the bacterium Spiroplasma is capable of protecting its Drosophila host from infection with a parasitic nematode . This endosymbiont can also impact its host’s population structure via altering host reproductive traits . Here , we used field collections across 26 different Gff sampling sites in northern and western Uganda to investigate the association of Spiroplasma with geographic origin , seasonal conditions , Gff genetic background and sex , and trypanosome infection status . We also investigated the influence of Spiroplasma on Gff vector competence to trypanosome infections under laboratory conditions . Generalized linear models ( GLM ) showed that Spiroplasma probability was correlated with the geographic origin of Gff host and with the season of collection , with higher prevalence found in flies within the Albert Nile ( 0 . 42 vs 0 . 16 ) and Achwa River ( 0 . 36 vs 0 . 08 ) watersheds and with higher prevalence detected in flies collected in the intermediate than wet season . In contrast , there was no significant correlation of Spiroplasma prevalence with Gff host genetic background or sex once geographic origin was accounted for in generalized linear models . Additionally , we found a potential negative correlation of Spiroplasma with trypanosome infection , with only 2% of Spiroplasma infected flies harboring trypanosome co-infections . We also found that in a laboratory line of Gff , parasitic trypanosomes are less likely to colonize the midgut in individuals that harbor Spiroplasma infection . These results indicate that Spiroplasma infections in tsetse may be maintained by not only maternal but also via horizontal transmission routes , and Spiroplasma infections may also have important effects on trypanosome transmission efficiency of the host tsetse . Potential functional effects of Spiroplasma infection in Gff could have impacts on vector control approaches to reduce trypanosome infections .
Tsetse flies ( Glossina spp . ) are vectors of parasitic African trypanosomes that cause human African trypanosomiasis ( HAT , commonly referred to as sleeping sickness ) and African animal trypanosomiasis ( AAT , also known as Nagana in cattle ) [1–3] . Several major HAT epidemics in sub-Saharan Africa have occurred during the last century , with the most recent one resulting in over half a million deaths in the 1980s [4–7] . An ambitious campaign led by WHO and international partners has now reduced the prevalence of HAT in west Africa [8] to a threshold considered irrelevant for epidemiological considerations , but millions continue to live at risk of contracting HAT in tsetse inhabited areas [9–11] . Despite calls for elimination of HAT by 2030 , there is a lack of effective tools for long-term control of the disease ( e . g . , vaccines and field-ready diagnostic assays ) . Furthermore , the presence of animal reservoirs threatens disease elimination efforts going forward , particularly in East Africa ( reviewed in [12] ) and necessitates the inclusion of vector control applications . Practical interventions [13–15] , as well as mathematical models [16–18] , suggest that vector control can accelerate efforts for reaching the disease elimination phase . Thus , enhancing the vector-control tool box with effective and affordable methods is a desirable goal . Biological approaches that reduce vector reproduction as well as vector competency have emerged as promising means to reduce disease transmission [19] . Variation in the microbiota associated with tsetse flies can influence their pathogen transmission dynamics [20–24] . Several symbiotic microorganisms have been described from laboratory and field populations of tsetse , including the obligate Wigglesworthia glossinidia , commensal Sodalis glossinidius , parasitic Wolbachia and more recently Spiroplasma [25–31] . A survey of Ugandan Gff revealed that all individuals harbored Wigglesworthia , while Sodalis and Wolbachia associations were sporadic [28 , 32 , 33] . Spiroplasma was found in the tsetse species that belong to the Palpalis group ( Gff , G . p . palpalis and G . tachinoides ) , while the tsetse species in the other two subgroups , Morsitans and Fusca , lacked associations with this microbe [31] . The bacterium Spiroplasma confers protection against nematodes , fungi and parasitoid wasps in several insects [34–36] . Spiroplasma also acts as a reproductive parasite that induces a male-killing effect in some arthropod hosts [37–40] . Based on phylogenetic analyses , the Spiroplasma species infecting Gff ( both field-caught individuals and one laboratory line ) is most closely related to the Citri-Chrysopicola-Mirum ( S . insolitum ) clade . Certain members of this clade confer protection against parasitoid wasps , nematodes and fungal pathogens in the fruit fly and aphid hosts [31] . In addition , among the Spiroplasma species within this clade are some that are pathogenic to plants and invertebrates and some that exhibit a male killing phenotype in ladybirds , fruit flies , and some butterfly species they infect ( reviewed in [41] ) . Spiroplasma function ( s ) within the tsetse host remain unknown . In Uganda , Gff is the main vector of HAT , where it transmits the chronic Gambiense disease caused by Trypanosoma brucei gambiense in the northwest and acute Rhodesiense disease caused by T . b . rhodesiense in the center , southeast and west ( reviewed in [42] ) . It is possible that differences in Gff trypanosome susceptibility ( vector competence ) among varying geographic regions could be influenced by Spiroplasma , but patterns of Spiroplasma occurrence remain unexplored . Spiroplasma infection success may be influenced by seasonal fluctuations in host Gff population health ( fitness ) and density . Seasonal changes in the environment can dramatically alter host-endosymbiont dynamics through changes in Gff host physiological status ( e . g . hemolymph lipid levels [43 , 44] ) and tsetse population density [45 , 46] . Collections of Gff in Uganda during different seasons provides the opportunity to test for influence of seasonal fluctuations on Spiroplasma prevalence . Additionally , patterns of Spiroplasma prevalence are likely influenced by Gff host genetic background , either because of vertical transmission that follows host inheritance patterns , or because of lineage-specific coevolutionary dynamics . Gff in Uganda has high genetic structuring at multiple spatial scales , which provides the opportunity to test for influence of Gff genetic background on Spiroplasma . There are three distinct Gff genetic clusters in the north , west and south of the country , and further population structure that separates the northwest from the northeast with ongoing gene flow between them in an admixture zone [47–49] . For this study , we focus our work on the north and west of Uganda in five watersheds . This sampling included four nuclear ( biparentally inherited ) genetic backgrounds: the northwest genetic unit ( NWGU ) , the northeast genetic unit ( NEGU ) , the west genetic unit ( WGU ) and the admixed ( ADMX ) genetic background intermediate to the NWGU and NEGU [47–49] . This sampling also included three mitochondrial ( maternally inherited ) genetic backgrounds: a group of related haplotypes associated with the NWGU known at “haplogroup A” ( mtA ) , a group of related haplotypes associated with the NEGU known at “haplogroup B” ( mtB ) , and a group of related haplotypes associated with the WGU known at “haplogroup C” ( mtC ) [47–49] . In this study , we ( i ) assessed the infection prevalence of Spiroplasma in Gff among five watersheds in northern and western Uganda , ( ii ) tested the effect of seasonal environmental variations , host Gff genetic background and sex , and trypanosome co-infections on Spiroplasma prevalence , and ( iii ) investigated the influence of Spiroplasma infections on Gff trypanosome transmission ability under laboratory conditions . We discuss how our results can elucidate potential functional associations of Spiroplasma with its tsetse host , and the potential applications of this knowledge to disease control .
A total of 1415 Gff individuals collected from northern and western Uganda during the period of 2014–2018 ( pooled for analysis ) across the wet ( April—May and August—October ) , intermediate ( June—July ) , and dry ( December—March ) seasons were assayed for Spiroplasma infection ( S1 Table ) . Flies were collected on public land using biconical traps . Samples included in this study were chosen to represent a wide range of environmental conditions and Gff backgrounds ( Fig 1 ) . The location of each sampling site was placed on a map of Uganda using QGIS v2 . 12 . 1 ( August 2017; http://qgis . osgeo . org ) with free and publicly available data from DIVA-GIS ( August 2017; http://www . diva-gis . org ) . We sampled 11 sites from the Albert Nile watershed ( DUK , AIN , GAN , OSG , LEA , OLO , PAG , NGO , JIA , OKS , and GOR ) , where the majority of Gff belong to the NWGU/mtA genetic background , and a minority belong to the ADMX/mtB genetic background [47–49] . We sampled six sites from the Achwa River watershed ( ORB , BOL , KTC , TUM , CHU , and KIL ) , where Gff belong to a mix of genetic backgrounds including NWGU/mtA , ADMX/mtA , ADMX/mtB , and NEGU/mtB [47–49] . We sampled six sites from the Okole River watershed ( ACA , AKA , OCA , OD , APU , and UWA ) , where Gff hosts belong to a mix of genetic backgrounds including NWGU/mtA , ADMX/mtA , ADMX/mtB , ADMX/mtC , and NEGU/mtB [47–49] . We sampled two sites from the Lake Kyoga watershed ( OCU and AMI ) , where the majority of Gff belong to the NEGU/mtB genetic background , and a minority belong to the ADMX/mtA genetic background [47–49] . Finally , we sampled a single site from the Kafu River watershed ( KAF ) , where the majority of Gff belong to the WGU/mtC genetic background , and a minority belong to the WGU/mtA genetic background [47–49] . To assess the Spiroplasma strain infecting the field-collected samples , we cloned and sequenced Spiroplasma-16S rDNA and rpoB ( RNA polymerase , subunit beta ) from flies from two NGU sampling sites ( GAN and GOR ) . The 16S rDNA touchdown PCR was performed in 20 μL reactions containing 1x GoTaq Green Mastermix ( Promega , USA ) , 0 . 4 μM of each primer SpirRNAF and SpirRNAR ( S2 Table ) and 1 μL of template DNA ( 20-100ng ) . The PCR profile consisted of an initial denaturation for 3 mins . at 94°C , followed by 8 cycles of 1 min . at 94°C , 1 min . at 63°C , and 1 min . at 72 with a reduction in annealing temperature of 1°C/cycle ( 63–56°C ) . This step was followed by 30 cycles of 1 min . at 94°C , 1 min . at 55°C , and 1 min . at 72°C , with a final extension at 72°C for 10 min . Reaction set up for the rpoB-PCR was the same as for 16S rDNA ( S2 Table ) , and the PCR profile consisted of a 3-min . initial denaturation at 94°C , followed by 34 cycles of 90 sec . at 94°C , 90 sec . at 55°C , and 90 sec . at 72°C , with a final extension at 72°C for 10 min . All amplicons were gel purified using the Monarch DNA Gel Extraction Kit ( New England Biolabs , USA ) and cloned into pGEM-T vector ( Promega , USA ) . In total six 16S rDNA and two rpoB clones were sequenced and analysed using the BLASTN algorithm and finally aligned using Spiroplasma glossinidia data from NCBI as reference . To test for potential Spiroplasma strain variation among the different Gff sampling sites , we cloned and sequenced the Multi Locus Sequence Analysis ( MLST ) genes dnaA , fruR , parE and rpoB from two individuals from ACA ( Okole River ) and OKS ( Lake Kyoga ) sampling sites . MLST-PCR reactions were performed with the same reaction set up as described above ( S2 Table ) . The parE touchdown PCR was run as described above for 16S rDNA but with 61°C/52°C annealing temperature . A touchdown PCR approach was also used for the fruR locus with 30 sec steps in each cycle and 60°C/52°C annealing temperature . Cloning and sequencing was performed as described above . All sequences were manually edited using Bioedit v7 . 1 . 9 [50] and aligned with related sequences available at NCBI using MUSCLE [51] . At the time of collection , sex and wing fray information ( all flies were wing fray 2–3 , i . e . 4–8 weeks old ) was recorded for each fly and midguts were dissected and microscopically analyzed for trypanosome infection status . The dissected guts and reproductive parts were stored in 95% ethanol for further analyses . Genomic DNA was extracted from female and male reproductive parts ( RP , n = 1157 ) as well as from whole bodies ( WB , n = 258 ) using DNeasy Blood and Tissue Kit ( Qiagen , Germany ) . We used flies from Pagirinya ( PAG ) for which we had DNA available from both the WB and RP tissues to compare the Spiroplasma infection prevalence to rule out potential DNA source bias in the prevalence results . We noted Spiroplasma infection of 18% in WB versus 17% in RP , which is not significantly different ( Fisher’s P > 0 . 999 ) . Consequently , both tissue datasets were pooled for the final infection prevalence analyses . The final sample set was composed of 893 females and 522 males . Spiroplasma infection prevalence was determined by 16S rDNA touchdown PCR as described above . The presence of Wolbachia was assessed by PCR targeting a single copy membrane protein encoding gene ( Wolbachia Surface Protein gene , wsp ) . The PCR reactions were performed as previously described in [52–54] . All amplified fragments were analysed on 1% agarose gels using Gel Doc EQ quantification analysis software ( Bio-Rad , Image Lab Software Version 4 . 1 ) . We used generalized linear models ( GLM ) to test for the significance of difference in Spiroplasma infection between Wolbachia-infected and uninfected flies . Potential Spiroplasma density differences between individuals and across seasons were tested via quantitative PCR ( qPCR ) using a CFX96 Real-Time PCR Detection System and iTaq Universal SYBR Green Supermix ( Biorad ) . The relative amount of Spiroplasma was calculated with the 2- ( ΔΔCt ) method using primers targeting the Spiroplasma RNA polymerase beta gene ( rpoB ) . Values were normalized against the single copy Glossina Peptidoglycan Recognition Protein-LA gene ( pgrp-la ) . All primer sets are listed in S2 Table . The trypanosome infection status of each sample was assessed by microscopic analysis of dissected guts at the time of sample collection in the field . In addition to the samples typed for a previous study [47] , we sequenced an additional 161 flies for a 491 bp fragment of mtDNA , and genotyped an additional 131 flies at 16 microsatellite loci . To do this , we extracted total genomic DNA from two legs of individual flies using the Qiagen DNeasy Blood & Tissue kit . For mtDNA sequencing , a 491 bp fragment from the cytochrome oxidase I and II gene ( COI , COII ) was amplified as described in [47] . PCR amplicons were run on 1% agarose gels , purified and sequenced at the Yale Keck DNA Sequencing facility . New sequences were combined with existing data [47] for a total data set of 490 sequences ( S1 Table ) . For microsatellite analysis , we genotyped flies at 16 microsatellite loci using methods described in [47] . New genotype calls were combined with existing data [47] for a total data set of 558 genotypes at 16 microsatellite loci ( S1 Table ) . To evaluate the potential association between Spiroplasma infection prevalence and the Gff genetic background , we assigned each individual to a single mtDNA haplogroup based on the phylogenetic relationships among haplotypes , and to a single nuclear genetic background based on clustering analysis of microsatellite genotypes . For mtDNA haplogroup assignment , first evolutionary relationships between the mtDNA haplotypes were assessed by constructing a parsimony-based network using TCS 1 . 21 [55] as implemented in PopART ( [56]; Population Analysis with Reticulate Trees: http://otago . ac . nz ) . These haplotypes were then grouped by phylogenetic relationship following [48] into three haplogroups , each imperfectly associated with the NWGU , NEGU , and WGU . For nuclear genetic background assignment , we used a Bayesian clustering analysis in the program STRUCTURE v2 . 3 . 4 [57] to group individuals based on their microsatellite genotypes . STRUCTURE assigns individuals into a given number of clusters ( K ) to maximize Hardy-Weinberg and linkage equilibrium . The program calculates the posterior probability for a range of K and provides a membership coefficient ( q-value ) of each individual to each cluster . In this analysis , we assessed membership to just three clusters corresponding to the NWGU , NEGU , and WGU . The ADMX does not represent its own cluster , but instead represents a mixed assignment to the NWGU and NEGU . We performed 10 independent runs for K = 3 with a burn-in of 50 . 000 followed by 250 . 000 MCMC steps and summarized results across the 10 independent MCMC runs using the software CLUMPAK [58] . Individual flies were assigned to nuclear genetic units based on q-values . Individuals with q-values > 0 . 8 were assigned to one of the three distinct clusters ( NWGU , NEGU or WGU ) , and individuals with mixed assignment ( q-values ranging from 0 . 2 to 0 . 8 ) to the NWGU and NEGU were assigned as “admixed” ( ADMX ) . Predictive variables considered included watershed of origin , season of collection , Gff host genetic background ( both nuclear and mitochondrial ) , Gff host sex , and trypanosome co-infection . A challenge in this analysis was that correlation between the geographic origin ( specifically watershed ) and environmental conditions , as well as Gff genetic background and trypanosome infection status is well established [47–49 , 59] . We confirmed these correlations among predictive variables and patterns of Spiroplasma infection , we performed a multiple correspondence analysis ( MCA ) . We took two approaches to control for correlation among predictive variables with watershed of origin . First , we fit generalized logistic mixed models ( GLMM ) with the predictive variables of interest ( season , Gff host genetic background , sex , and co-infection ) as fixed effects with and without watershed of origin as the random effect , and tested the improvement of the models with an analysis of variance ( ANOVA ) Chi square test . We followed these tests with more complex combinations of predictive variables using watershed as the random effect . GLMM was performed with the ‘glmer’ function in the R [60] package lme4 [61] and fitted using maximum likelihood . Second , we fit generalized linear models ( GLM ) one watershed at a time for each predictive variable ( season , Gff host nuclear and mtDNA genetic background , sex , and co-infection ) . Direction and significance of the effect of each predictive variable was assessed with Tukey’s contrasts with p-values ( P ) obtained from the z distribution and corrected for multiple comparisons using the unconstrained ( “free” ) adjustment . GLM was performed in R with the multcomp package [62] . Effect of Spiroplasma presence on trypanosome infection outcome was also tested in the laboratory by infecting the Gff colony ( IAEA , Vienna , Austria ) , with bloodstream form Trypanosoma brucei brucei ( RUMP503 ) parasites . Pupae from the colony were sent to Yale , and emerging flies were used for parasite infections . This Gff line has been shown to exhibit a heterogeneous Spiroplasma infection prevalence [31] . Following our established protocols [63 , 64] , teneral ( newly eclosed ) flies were infected by supplementing their first blood meal with 5x106 parasites/ml . All flies that had successfully fed on the infectious blood meal were subsequently maintained on normal blood , which they received every other day . Fourteen days post infection ( dpi ) , the presence of trypanosome infections in the midgut was assessed microscopically plus using a PCR assay . PCR was performed using primers trypalphatubF and trypalphatubR , which target the alpha chain of T . brucei tubulin ( S2 Table ) . The reaction set up and the cycler profile were the same as used for Wolbachia ARM-PCR described above . Spiroplasma presence was assessed in the corresponding reproductive tissue of each fly via PCR assay using the Spiroplasma infection assay described above . We used generalized linear models ( GLM ) to test for the significance of difference in trypanosome infection between Spiroplasma-infected and uninfected flies .
To assess the Spiroplasma strain infecting Gff sampling sites , we employed 16S rDNA and rpoB sequencing analysis . In samples analyzed from the Okole River and Lake Kyoga watersheds , we found a single strain infection ( S1 Fig ) , which belongs to the Citri-Chrysopicola-Mirum clade and which was also previously identified from a Gff colony [31] . We tested for Spiroplasma infection in 1415 Gff individuals ( 894 females and 522 males; S1 Table ) collected from 26 sampling sites spanning five watersheds ( Fig 1 ) . In the northwest region , flies from the Albert Nile watershed ( n = 487 ) had a mean infection rate of 34% ( Fig 1 and S1 Table ) . In the northcentral region , flies from the Achwa River watershed ( n = 234 ) had a mean infection rate of 20% , and the Okole River watershed ( n = 389 ) had a mean infection rate of 5% ( Fig 1 and S1 Table ) . In the northeast region , flies from the Lake Kyoga watershed had relatively low Spiroplasma infection rate , with one of the two sampling sites ( AMI , n = 73 ) having an infection rate of 11% , and the other site ( OCU , n = 90 ) lacking Spiroplasma infection altogether ( Fig 1 and S1 Table ) . In the western region , flies from the Kafu River watershed ( n = 142 ) had an infection rate of 3% ( Fig 1 and S1 Table ) . These results indicate higher Spiroplasma infection in the northwest than in the northeast or west of Uganda , a conclusion that was further supported by tests for association of Spiroplasma with watershed of origin using generalized linear modeling ( see discussion of MDS , GLMM , and GLM results below ) . To assess whether potential differences in Spiroplasma infection density could influence our ability to detect the microorganism in the DNA source , we performed qPCR on individuals from the NEGU ( AMI ) sampled across multiple seasons . We detected varying densities , with the highest Spiroplasma levels observed in the intermediate season ( S2 Fig ) . We assigned Gff host nuclear ( biparentally inherited ) genetic background using STRUCTURE cluster assignments that were based on the microsatellite genotypes . STRUCTURE assignment indicated 195 flies had high ( > 0 . 8 ) membership probability to the NWGU , 94 to the NEGU , and 109 to the WGU ( S1 Table ) . We found 160 flies with mixed assignment , which we considered members of the ADMX genetic background ( S1 Table ) . Flies assigned to the NWGU had a mean Spiroplasma infection rate of 25% , the ADMX genetic background had a mean infection rate of 15% , the NEGU ( n = 94 ) had a mean infection rate of 2% , and the WGU had a mean infection rate of 4% ( Fig 2 and S1 Table ) . Although these results suggest higher Spiroplasma infection in the NWGU and ADMX nuclear genetic backgrounds , this pattern was found to driven by correlation between nuclear genetic background and watershed of origin ( see discussion of MDS , GLMM , and GLM results below ) . We assigned Gff host mitochondrial ( maternally inherited ) genetic background by generating a TCS network of the mtDNA sequences ( n = 490 ) . We identified 29 unique mitochondrial haplotypes that grouped into the three previously described major haplogroups: mtA , mtB and mtC ( Figs 2 and S4 ) [47] . 266 flies were assigned to haplogroup A , 209 to haplogroup B , and 15 to haplogroup C ( S4 Fig ) . Flies assigned to mtA had a mean Spirplasma infection rate of 19% , mtB had a mean infection rate of 10% , and mtC had a mean infection rate of 13% ( Fig 2 and S1 Table ) . Although these results suggest higher Spiroplasma infection in the mtA mitochondrial genetic background , this pattern was found to be driven by correlation between mitochondrial genetic background and watershed of origin ( see discussion of MDS , GLMM , and GLM results below ) . The MCA confirmed that there were strong correlations among predictive variables , especially with watershed of origin ( S3 Fig ) . GLMM indicated that watershed of origin and season of collection ( wet , intermediate and dry ) were the two most important factors influencing Spiroplasma prevalence ( Tables 1 and S3 and S4 ) . GLMM of all predictive variables ( considered one at a time ) were significantly improved by adding watershed as a random effect ( ANOVA P ranging from 2 . 20e-16 to 0 . 0022 , S3 Table ) . Models exploring multiple predictive variables at a time indicated that season of collection was the only variable that positively influenced the fit of the model ( ANOVA P = 3 . 57e-6 , Table 1 ) . Adding random slope or any of the other predictive variables ( nuclear or mtDNA genetic background , sex , or trypanosome co-infection ) did not significantly improve the model ( ANOVA P ranging from 0 . 2870 to 1 . 0 , S4 Table ) . GLM by watershed indicated that flies from the Albert Nile had by far the highest probability of Spiroplasma infection [Pr ( Spiro+ ) = 0 . 32] , followed by flies from the neighboring Achwa River [Pr ( Spiro+ ) = 0 . 22 , Fig 3] . Tukey’s contrasts indicated that the Albert Nile had only somewhat higher Pr ( Spiro+ ) than the Achwa River ( Tukey’s contrast P = 0 . 0015 ) , but that these two watersheds had significantly higher Pr ( Spiro+ ) than any of the other watersheds ( Tukey’s contrasts P ranging from 2 . 00e-16 to 0 . 0002 , Tables 2 and S5 ) . In addition to watershed of origin , season of collection was strongly associated with Spiroplasma infection . The intermediate season had significantly higher probability of Spiroplasma infection than the wet season , which was especially apparent in the Albert Nile [Pr ( Spiro+ ) = 0 . 42 vs 0 . 16 ) ] and Achwa River watersheds [Pr ( Spiro+ ) = 0 . 36 vs 0 . 08] ( Tukey’s contrasts P = 1 . 16E-07 and 5 . 38E-06 , respectively; Table 2 ) . There were no other significant differences in Pr ( Spiro+ ) among seasons in any of the other watersheds ( Table 2 ) . Additionally , none of the other predictive variables ( nuclear or mtDNA genetic background , sex , or trypanosome co-infection ) had significant effects on Pr ( Spiro+ ) when analyzed by watershed ( Tukey’s contrasts P ranging from 0 . 0962 to 1 . 0 , S5 Table ) . Previous analysis of Gff from southern and central regions of Uganda also indicated presence of distinct genetic backgrounds associated with these individuals [47 , 48] as well as the presence of heterogeneous and low-density infections with another endosymbiont , Wolbachia [27 , 31] . To investigate for similar patterns in northern Uganda , we analyzed 106 Gff individuals from the Albert Nile ( NWGU ) and Achwa/Okole River ( ADMX ) watersheds for the presence of Wolbachia infections ( S1 Table ) . Within this set , 92% of flies were not carrying Wolbachia ( 98/106 ) . The remaining infected 8% ( 8/106 ) were all from Achwa river except one sample . Most Wolbachia-infected flies ( 6/8 ) were Spiroplasma-negative , and Wolbachia-negative flies were Spiroplasma-positive and -negative ( S1 Table ) . The generalized mixed models ( GLM ) indicated no significant correlation between the presence of Wolbachia and the probability of Spiroplasma infection ( Tukey’s P = 0 . 78 ) . Patterns of Spiroplasma infection from the field collections , although not significant in the GLMM or GLM , indicated a possible correlation between Spiroplasma and trypanosome co-infections . Of the 243 Spiroplasma infected flies identified in the study , only 2% ( n = 5 ) had trypansome co-infection ( infection rate among the Spiroplasma-negative flies was 10%; n = 115 ) . To test this correlation under more controlled conditions where we could ensure statistical power , we used a laboratory line of Gff with heterogeneous infection of Spiroplasma [30] to complete a trypanosome infection challenge experiment . Microscopic examination and PCR analysis of challenged individuals ( n = 123 ) revealed a negative correlation between the presence of Spiroplasma and trypanosome co-infection , with 18% of individuals co-infected with both microbes ( S+T+; n = 22 ) , 20% infected with only trypanosomes ( S-T+; n = 25 ) , 46% infected with only Spiroplasma ( S+T-; n = 56 ) , and 16% without infection with either microbe ( S-T-; n = 20; Fig 4 and S6 Table ) . The generalized mixed models ( GLM ) indicated a significant negative correlation between the presence of Spiroplasma and the probability of trypanosome coinfection ( Tukey’s P = 0 . 0010 ) .
We found that flies residing in geographically separated watersheds have significantly different Spiroplasma infection prevalences ( Figs 1 and S3 ) . Gff is a riparian species that inhabits low bushes or forests at the margins of rivers , lakes or temporarily flooded scrub land . These water connections may influence dispersal patterns by limiting dispersal between the different watersheds . Limited dispersal would minimize contact among flies from different watersheds . This could suggest that horizontal transfer occurs between flies within the same watersheds , or that there is environmental acquisition of Spiroplasma in Gff . However , it remains to be elucidated whether flies encounter Spiroplasma from the environment or during feeding . Interestingly , although tsetse are strict blood feeders on vertebrate hosts , a recent study has indicated that they are capable of feeding on water with or without sugar when deprived of a blood meal [65] . This feeding behavior would allow Gff to acquire Spiroplasma from the environment , and could account for the strong association of Spiroplasma with watershed of origin , and lack of correlation with other host genetic background . Finally , transfer of Spiroplasma via ectoparasites could account for different infection frequencies . Although there are no ectoparasites described yet , which are associated with tsetse flies , this route of transmission cannot be excluded . In addition to geographic origin , the season of collection was an important factor shaping the Gff-Spiroplasma association in Uganda . We found that the intermediate season ( June—July ) was correlated with higher Spiroplasma infection prevalence than either the wet ( April—May and August—October ) or dry ( December—March ) seasons ( Table 1 and Fig 3 ) . This might be because the environmental conditions during the wet and dry seasons restrict the availability of animal hosts for tsetse blood feeding . This could indicate that the intermediate season represents optimal foraging conditions for Gff . In fact , Spiroplasma survival in Drosophila is dependent on the availability of hemolymph lipids [43 , 44] . Hence , during nutritionally optimal times , maintenance of the symbiont may be less costly for the host than during a period of compromised fitness , and thus higher prevalence and density is observed during these periods [43 , 66] . Other symbionts capable of triggering host phenotypes , such as male-killing , are also affected by host fitness . The persistence of Wolbachia , for example , is negatively affected by host fitness via temperature as well as by other stress factors ( e . g . [66–68] ) . Thus , the more stressful conditions of the dry season may reduce the overall fitness of the fly and consequently the Spiroplasma infection densities . This scenario is supported by our finding of different Spiroplasma densities in flies analyzed across the three sampling seasons ( Figs 2 and S2 ) . Varying Spiroplasma densities can also influence the transmission efficiency of the symbiont from mother to tsetse’s intrauterine progeny . Furthermore , if Spiroplasma is horizontally transferred via the environment , the climatic conditions can also impact the abundance of Spiroplasma for acquisition by Gff . Higher Spiroplasma density in the environment during the intermediate season could facilitate their acquisition by the tsetse host . In support of this theory , free-living bacterial communities that reside in aquatic systems are strongly affected by environmental factors , such as pH [69 , 70] and seasonality [71] . A more recent study has highlighted the significant effect of seasonality-related changes in soil bacterial communities [72] . Hence , the changing environmental conditions that occur between the dry , wet , and intermediate season might impact Spiroplasma density and consequently the infection density . However , seasonality alone cannot explain the differences of the symbiont differences but other parameters such as e . g . temperature variations should be considered . Genetically variable Gff populations residing within the Gambiense and Rhodesiense HAT belts could influence the inheritable microbiota composition , which in turn could have important implications in transmission dynamics and vector control outcomes [73–75] . In that context , we evaluated the potential correlation between host nuclear genetic differences and Spiroplasma infection prevalence across the 26 Gff sampling sites . However , we found that after accounting for watershed of origin in the GLMM model , Spiroplasma infection was not significantly influenced by Gff host nuclear or mitochondrial genetic background ( Figs 2 and 3 and S5 Table ) . Lack of association of with host genetic background provides further support for the idea that Spiroplasma may be acquired by horizontal transfer between flies within the same watersheds , or through contact with other sources of the bacteria in the environment . In Drosophila , Spiroplasma can either coexist with the endosymbiotic Wolbachia without little or no impact on each other [76] , or negatively affect Wolbachia presence . Goto and coworkers showed that the presence of Spiroplasma suppresses Wolbachia infection density in D . melanogaster [77] . Interestingly , while the tsetse species in the Morsitans subgroup , such as G . morsitans , harbor Wolbachia infections , they lack Spiroplasma associations [31] . In contrast , the tsetse species in the Palpalis subgroup , such as Gff and G . palpalis , harbor Spiroplasma infections , but lack Wolbachia associations [31] . Spiroplasma might be negatively affected by the presence of Wolbachia infection in the species within the Morsitans subgroup [31] . As such , the high titer of Wolbachia noted in G . morsitans reproductive organs could suppress the establishment of Spiroplasma infections . Our prior and current studies with distinct Gff populations in Uganda also indicate a potential negative influence for the two endosymbiont infections [28] . Our previous finding reported Wolbachia infections across 18 Gff sampling sites from the Northcentral , West and South of Uganda [28] . In this study we detected 8% Wolbachia infections in samples analyzed from the Achwa River watershed , which is the geographic area with highest Spiroplasma infection prevalence ( S1 Table ) . However , 6/8 Wolbachia-positive samples were negative for Spiroplasma , and hence the idea of reciprocal exclusion of both entities remains a possibility although the GLM did not suggest a significant correlation between the two bacterial entities . We had also noted that the Wolbachia density in the reproductive organs of Gff is unusually low , and that Spiroplasma densities can vary across seasons , thus rendering co-infection detections technically challenging , particularly when using whole body DNA , as was the case with a number of flies analyzed in this study . It also remains to be elucidated if the presence of viral microorganisms plays a role for the infection dynamics of Spiroplasma in Ugandan Gff populations . The salivary gland hypertrophy virus ( SGHV ) , a common virus of Glossina , is inversely correlated with Wolbachia infection prevalence in Gff in Uganda [28] . Hence , the correlation between Spiroplasma and SGHV remains to be tested . Reproductive influences , such as male killing , have been associated with maternally inherited symbionts , including Spiroplasma , where the symbiont drives its own dispersal by selectively killing male embryos in ladybirds , fruit flies and certain butterfly species ( reviewed in [41] ) . As we observed both Spiroplasma-infected males and females and there was also no sex bias in the offspring of the laboratory-reared Gff , this bacterium likely does not confer a male killing trait to Gff . Pairwise comparison suggested a slightly higher infection prevalence in females , but such a slight difference is unlikely to be the result of a male killing phenotype . We also evaluated the potential role of Spiroplasma on tsetse’s immune physiology by measuring the correlation between trypanosome and Spiroplasma infection status . Of the 1415 samples analyzed , we found only five with trypanosome and Spiroplasma co-infections . Although not significant in the GLMM or GLM , this negative results could have been caused by lack of statistical power in the field collected data . To further address the question of a similar protective effect , we performed trypanosome infection experiments using a colonized Gff line that displays heterogeneous Spiroplasma infection prevalence [31] . Our finding that infections with Spiroplasma alone were more frequent than co-infections with Tbb ( 56% vs . 18% , respectively; S4 Table ) indicates a negative correlation between the presence of the symbiont and the parasite , and suggests that both entities negatively impact each other’s fitness . In accordance with investigations in Drosophila [78 , 79] , Spiroplasma infections may confer physiological traits that protect its tsetse host from being colonized by trypanosome infections . In different hosts , Spiroplasma induces a protective effect against nematodes , fungi and parasitoid wasps [35 , 36 , 78] . It remains to be elucidated , whether a potential protection in Gff against parasite infections results from niche competition of both microbes within the host , or by expression of certain Spiroplasma-derived molecules , which block trypanosomes . Alternatively , it has been shown that infections with certain Wolbachia strains confer an immune enhancement phenotype to their Drosophila and mosquito hosts , hence increasing the resistance to other pathogens [80; also reviewed in 81] . Such an immune enhancement , which affect the trypanosome transmission success in Spiroplasma infected Gffs however , is possible but rather unlikely given the low infection frequency of Wolbachia ( 12% ) in the tested flies . The heterogeneous Spiroplasma infection prevalence in the Gff line that we used in the parasite challenge experiment ( Fig 4 ) might result from imperfect maternal transmission to progeny and may similarly be influencing the infection prevalence noted in natural populations . Tsetse are viviparous and the mother supports the development of her progeny in an intrauterine environment . Endosymbiotic Wigglesworthia and Sodalis are maternally acquired by the progeny in female milk secretions during the lactation process , while Wolbachia is transovarially transmitted . Spiroplasma infections in the gonads suggest that this endosymbiont is also transovarially transmitted , although transmission through milk secretions remains to be investigated . While tsetse females remain fecund throughout their entire life ( and can produce 8–10 progeny ) , the transmission of Spiroplasma from mother to her intrauterine progeny however may be more efficient during the early gonotrophic cycles and decrease over the course of female’s reproductive lifespan . Such a scenario could explain why we observed that only 50–60% of colony flies are infected with Spiroplasma . We will further address this question by testing the efficiency of symbiont transmission from mother to each of her offspring in a follow-up study by developing single lines from each pregnant female . Such an imperfect transmission efficiency can also influence the heterogeneous infection prevalence we noted in field populations . In conclusion , the infection prevalence of Spiroplasma in Gff populations in northern Uganda is significantly correlated with different watersheds of origin and seasonal environmental conditions . These associations indicate that seasonal fluctuations and other transmission modes than strictly vertically are drivers of Spiroplasma acquisition in Gff in Uganda . We further demonstrate that colonized Gff are less likely to establish trypanosome parasite infections when carrying Spiroplasma infections , which is of particular interest in the context of alternative vector control approaches to control trypanosome infections . | We investigated the association of symbiotic Spiroplasma with the tsetse fly host Glossina fuscipes fuscipes ( Gff ) to assess if Spiroplasma infections are correlated with Gff genetic background , geography , or season and its interaction with trypanosome parasites . We analyzed distribution and prevalence of Spiroplasma infections across different Gff sampling sites in northern and western Uganda , and found that the symbiont is unevenly distributed and infections have not reached fixation within these sampling sites . We tested for associations with geographic origin of the collections , seasonal environmental conditions at the time of collection , Gff host genetic background and sex , plus trypanosome co-infections . Spiroplasma prevalence was strongly correlated with geographic origin and seasonal environmental conditions . Our parasite infection data suggested a negative correlation of Spiroplasma with trypanosome infection , with only 5 out of 243 flies harboring trypanosome co-infections . We further investigated the influence of Spiroplasma on trypanosome parasite infections in the laboratory . We found that trypanosomes were less likely to establish an infection in Gff individuals that carried Spiroplasma infections . Our results provide new information on host-endosymbiont dynamics in an important human disease vector , and provide evidence that Spiroplasma may confer partial resistance to Gff trypanosome infections . These findings provide preliminary evidence that a symbiont-based control method could be successful in combating tsetse trypanosome transmission to humans and livestock in sub-Saharan Africa . | [
"Abstract",
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"Results",
"Discussion"
] | [
"medicine",
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"genetics",
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"uganda",
"parasitic",
"diseases",
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"wolbachia",
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"infectious"... | 2019 | Spatio-temporal distribution of Spiroplasma infections in the tsetse fly (Glossina fuscipes fuscipes) in northern Uganda |
Monoubiquitination of histone H2B lysine 123 regulates methylation of histone H3 lysine 4 ( H3K4 ) and 79 ( H3K79 ) and the lack of H2B ubiquitination in Saccharomyces cerevisiae coincides with metacaspase-dependent apoptosis . Here , we discovered that loss of H3K4 methylation due to depletion of the methyltransferase Set1p ( or the two COMPASS subunits Spp1p and Bre2p , respectively ) leads to enhanced cell death during chronological aging and increased sensitivity to apoptosis induction . In contrast , loss of H3K79 methylation due to DOT1 disruption only slightly affects yeast survival . SET1 depleted cells accumulate DNA damage and co-disruption of Dot1p , the DNA damage adaptor protein Rad9p , the endonuclease Nuc1p , and the metacaspase Yca1p , respectively , impedes their early death . Furthermore , aged and dying wild-type cells lose H3K4 methylation , whereas depletion of the H3K4 demethylase Jhd2p improves survival , indicating that loss of H3K4 methylation is an important trigger for cell death in S . cerevisiae . Given the evolutionary conservation of H3K4 methylation this likely plays a role in apoptosis regulation in a wide range of organisms .
Apoptosis is the most common form of programmed cell death and plays important roles in the development and cellular homeostasis of all metazoans . Deregulation of apoptosis contributes to the pathogenesis of multiple diseases including autoimmune , neoplastic and neurodegenerative disorders [1] . The budding yeast Saccharomyces cerevisiae has progressively evolved as model to study the mechanisms of apoptotic regulation , as it had become evident that the extent of evolutionary conservation of the apoptotic core machinery makes it a suitable and attractive model system for apoptotic research . S . cerevisiae undergoes apoptosis when treated with various agents including hydrogen peroxide ( H2O2 ) , acetic acid and pheromone ( reviewed in [2] ) . Physiological scenarios that trigger apoptosis in yeast are for example aging and failed mating , and chronological aging is in this respect the to date best-studied scenario [2] , [3] . The chronological lifespan ( CLS ) is defined as the time a yeast cell can survive in a non-dividing , quiescence-like state [4] , [5] . Genetic interventions with key yeast apoptotic regulators , such as Bir1p , Nma111p and Yca1p , have been described that influence the CLS of yeast cells and the appearance of the apoptotic features associated to it [6]–[10] . Particularly , disruption of the yeast metacaspase YCA1 gene delays cell death and the formation of an apoptotic phenotype during chronological aging [8] . The activation of apoptosis results in characteristic biochemical and morphological features outside and inside the cell nucleus [11] with chromatin condensation paralleled by DNA fragmentation being one of the most important nuclear events in cells undergoing apoptosis [12] . The mechanism by which chromosomes reorganize during apoptosis is still poorly understood , but evidence exists that histone modifications contribute critically to the nuclear changes experienced by apoptotic cells . Histone modifications that have been linked to apoptosis are phosphorylation of the histone variant H2A . X at serine 139 ( S139 ) that occurs during the formation of DNA double strand breaks under various conditions , including apoptosis [13] . Phosphorylation of histone H2B at S14 has been associated with chromatin condensation and DNA fragmentation [14]–[16] . This modification is reciprocal and deacetylation of H2B at lysine 15 ( K15 ) is necessary to allow H2BS14 phosphorylation [17] . A similar mechanism appears to exist in yeast . Here deacetylation of H2BK11 , which is characteristic for exponentially growing yeast [18] , is necessary to allow phosphorylation of H2BS10 , an apoptotic mark [19] , [20] . Therefore , the cis-crosstalk between H2B acetylation and phosphorylation appears evolutionary conserved in apoptosis . Phosphorylation of H2A at serine 129 is increasing in yeast cells undergoing H2O2-induced apoptosis and it is paralleled by a decrease in H3 tyrosine 45 phosphorylation [21] , pinpointing to a trans-histone crosstalk related to apoptosis in yeast . An evolutionary conserved trans-histone crosstalk , which thus far has not been linked to apoptosis , is the regulation of H3K4 and H3K79 methylation by H2BK123 ubiquitination [22] . This trans-histone crosstalk has gathered much attention in recent years , since H3K4 and H3K79 methylation have been implicated in many nuclear processes , such as transcription activation and repression , DNA replication , recombination and repair [22] , [23] . The Set1p-containing complex COMPASS acts as H3K4 methyltransferase , and this methyl mark is important for transcriptional activation [24]–[27] as well as silencing at telomeres [27] , [28] and rDNA loci [29]–[31] . Methylation of H3K79 is mediated by the histone methyltransferase Dot1p and is essential for efficient silencing near telomeres , rDNA loci , and the yeast mating type loci [28] . Moreover , H3K79 methylation is critical for proper DNA damage response ( DDR ) [32] , [33] , as it is prerequisite for Rad9p ( 53BP1 ) recruitment [34] . H2B ubiquitination , which is dependent on the ubiquitin conjugase Rad6p and the E3 ligase Bre1p [35]–[37] , has been implicated in DNA repair and DDR [33] , [38] and we have previously shown that lack of H2B ubiquitination causes metacaspase-dependent apoptosis in S . cerevisiae [39] . H2B ubiquitination is furthermore known to render chromatin resistant to nuclease digestion and its absence is consequently causing increased nuclease sensitivity [22] , in keeping with the observed increase in apoptosis . In this study we analyzed whether apoptosis sensitivity of cells that lack H2B ubiquitination is dependent on a lack of H3K4 and/or H3K79 methylation . We show that Δset1 cells are susceptible to Yca1p-dependent apoptosis , whereas DOT1 disruption affects apoptosis to a lesser extent . We moreover found that Dot1p along with the checkpoint kinase Rad9p is critical for cell death of Δset1 cells . Apoptosis sensitivity of Δset1 cells can be rescued by deleting the yeast homolog of endonuclease G , Nuc1p , suggesting that loss of H3K4 methylation in the presence of H3K79 methylation and the kinase Rad9p enhances chromatin accessibility to endonuclease digestion . Wild-type , but not dot1Δ cells , lose H3K4 methylation during chronological aging coinciding with a shorter lifespan , indicating that the loss of H3K4 methylation is an important trigger for apoptotic cell death .
Histone H3K4 methylation is mediated by the methyltransferase Set1p [27] . To test whether a lack of H3K4 methylation predisposes yeast to apoptotic stimuli , we analyzed the apoptosis sensitivity of Δset1 cells . Chronological aging is to date the best-studied physiological scenario of apoptosis induction in yeast and we therefore studied the effect of SET1 disruption on the chronological lifespan of yeast cells ( see Material and Methods ) . We found that Δset1 cells showed an early onset of cell death during chronological aging when compared to wild-type cells ( Figure 1 ) . Almost 100% of Δset1 cells were dead after about 6 days in culture , whereas ∼30% of the wild-type cells were surviving for more than 10 days ( Figure 1A ) . To quantify the difference in life span , we calculated the integral of the survival curve for wild-type and Δset1 cells , which allows to determine the survival differences for the two strains over the time course of the experiment [40] . The survival integral of Δset1 cells ( integral 1 . 2 ) is significantly smaller than the integral for wild-type cells ( integral 4 . 9 ) ( Figure 1B ) . Next , we asked whether the death of SET1 disrupted cells is of apoptotic nature . Apoptosis ( but also necrosis ) is frequently accompanied by an accumulation of reactive oxygen species ( ROS ) , which is an early step in the apoptotic process [41] . Staining with dihydroethidium ( DHE ) was used to visualize accumulation of ROS . DNA fragmentation was detected by using TUNEL staining , and combined Annexin V/propidium iodide ( PI ) staining was used to detect the cell surface exposure of phosphatidylserine , an early apoptotic event . PI staining further allows the discrimination between apoptotic ( PI negative ) and necrotic ( PI positive ) cell death . ROS accumulation was determined after 2 days in culture , when Δset1 cells showed survival of about 35% compared to ∼75% of wild-type cells ( Figure 1A ) , as determined by clonogenicity . At this time point about 70% of Δset1 cells were DHE positive , but only ∼20% of wild-type cells ( Figure 1C and D; Table 1 ) . Consistently , Δset1 cells unlike wild-type cells show apoptotic DNA fragmentation , as determined by TUNEL staining ( Figure 1C ) . Moreover , about 73% of Δset1 cells were stained positive for Annexin V , but negative for PI , compared to about 16% of wild-type cells ( Figure 1C and E ) . Together our data demonstrate that cells lacking set1 have a reduced CLS and their death is predominantly of apoptotic nature . Apoptosis in yeast can occur in a metacaspase-dependent or metacaspase-independent manner [42] . We thus asked whether the metacaspase Yca1p is required for the death of Δset1 cells . Therefore , Δset1Δyca1 double disruptants were generated and their survival was monitored during chronological aging . As shown in Figure 1A and B , deletion of YCA1 in the SET1-deleted background resulted in significantly better survival ( integral 3 . 0 ) when compared to Δset1 cells ( integral 1 . 2 ) . The improved survival of the double mutant is accompanied by a significant reduction of ROS accumulation and phosphatidylserine exposure on the cell membrane ( Figure 1C–E ) . Moreover , unlike Δset1 cells , but similar to Δyca1 cells , Δset1Δyca1 cells did not exhibit apoptotic DNA fragmentation as detected by TUNEL labeling ( Figure 1C ) . Thus , the apoptotic death of Δset1 cells is in part Yca1p-dependent . Histone H2B ubiquitination is not only a prerequisite for H3K4 methylation but also for H3K79 methylation . We next asked whether the lack of Dot1p and H3K79 methylation also influences apoptotic cell death of S . cerevisiae . DOT1 disrupted cells showed better survival during chronological aging when compared to wild-type cells ( Figure 2A and B ) . The effect of dot1 disruption on cell survival is modest , but statistically relevant with survival integrals of 5 . 8 for Δdot1 cells versus 4 . 9 for the wild-type ( Figure 2B ) . Consistently , the Δdot1 strain exhibited less ROS accumulation than wild-type cells , less apoptotic DNA fragmentation as detected by TUNEL labeling , and a slight decrease in the exposure of phosphatidylserine on the cell membrane ( Figure 2C–E; Table 1 ) . To further underline the statistical relevance of the survival advantage of Δdot1 cells as compared to wild-type cells , we normalized the survival of both strains to survival at day 2 to ensure that all yeast cells have reached stationary phase . Again , we found that the difference in cell survival between wild-type and dot1Δ cells is statistically relevant ( Figure S2A and B ) . Together our data suggest that Dot1p in opposite to Set1p may protect against cell death . Next , we asked whether Dot1p promoted cell death depends on Yca1p and generated a Δdot1Δyca1 double mutant to analyze its viability . A better survival of the double mutant as compared to the single mutant cells is expected , if Dot1p and Yca1p act independently . However , Δdot1Δyca1 , Δdot1 and Δyca1 cells exhibited similar viability during chronological aging ( Figure 2A and B ) with similar survival integrals as wild-type cells ( Figure 2B ) and similar ROS accumulation ( Figure 2D; Table 1 ) . Together these data suggest that Dot1p and Yca1p act within the same apoptotic pathway as pro-apoptotic proteins . The above experiments show that Dot1p-mediated H3K79 methylation supports cell death , while Set1p-mediated H3K4 methylation confers apoptosis resistance . Next , we asked if the death of cells lacking H3K4 methylation is dependent on H3K79 methylation and generated a Δset1Δdot1 double mutant , lacking histone H3K4 and K79 methylation . As shown in Figure 3A and B , we observed a significantly improved survival during chronological aging for the Δset1Δdot1 double mutant ( integral 4 . 6 ) as compared to Δset1 cells ( integral 2 . 7 ) , with consistent ROS accumulation of only 47% for Δset1Δdot1 cells compared to 70% of Δset1 cells ( Figure 3C and D; Table 1 ) . These data confirm the pro-death role of Dot1p and suggest that H3K79 methylation is important for cell death of Δset1 cells . Next , we asked whether or not Dot1p is required for Yca1p-dependent cell death of Δset1 cells . We therefore generated a triple mutant Δset1Δdot1Δyca1 strain and analyzed its survival during chronological aging . If Dot1p acts in an Yca1p-independent manner , a better survival of the triple mutant as compared to Δset1Δdot1 cells is expected . This , however , was not the case . The triple mutant Δset1Δdot1Δyca1 showed no better survival as compared to Δset1Δdot1 cells and a similar number of DHE-positive cells ( Figure 3A–D; Table 1 ) . Thus , Dot1p and Yca1p act together in Δset1 provoked cell death . Dot1p and H3K79 methylation has been shown to confer yeast cells with resistance to DNA damaging agents and the loss of such histone modification causes defective DDR by impairing the function of Rad9p [32] , [33] . Rad9p is an adaptor protein required for Rad53p activation [43] , [44] . Interestingly , deletion of the RAD9 gene can partially suppress lethal effects of the apoptotic orc2-1 mutation in the origin recognition complex [45] , suggesting that Rad9p-dependent checkpoint function is required for apoptosis induction in orc2-1 cells . Given that Dot1p is required for Rad9p-dependent checkpoint activation , Δdot1 cells might fail to activate apoptosis as a result of a defective checkpoint function . To test this hypothesis , we analyzed the survival of Δset1Δrad9 cells during chronological aging and found that the disruption of RAD9 in Δset1 cells significantly improved viability ( Figure 4A and B ) . Consistently , DHE-detectable ROS accumulation was reduced in Δset1Δrad9 cells compared to Δset1 cells ( Figure 4C; Table 1 ) . Deletion of RAD9 in a wild-type background does not affect the survival of yeast cells and ROS production , respectively ( Figure 4A–C ) . To test , if set1 depleted cells in fact accumulate DNA damage in a Rad9p-dependent manner , we assayed genome stability of these cells by measuring the mutation frequency in the CAN1 gene . Mutations in the CAN1 gene can be monitored by increased resistance of yeast cells to the toxic amino-acid analogue canavanine and has previously been linked to shorter CLS [46] . We found that SET1 deletion rapidly induced an increase in mutation frequency , which was further increased by a combined deletion of SET1 and RAD9 ( Figure 4D ) , and maintained , but not further increased over time ( Figure 4D ) . Interestingly , RAD9 deletion alone does not coincide with an increased mutation frequency . Together these data indicate that Dot1p is required for apoptosis of Δset1 cells in a Rad9p-dependent manner . To confirm that Dot1p and Rad9p in fact act in the same apoptotic pathway , we tested the apoptosis sensitivity of a Δset1Δrad9Δdot1 triple mutant . Compared to the Δset1Δdot1 and Δset1Δrad9 double mutants , respectively , a decrease in cell death for the triple mutant is expected in the case DOT1 and RAD9 disruption confer apoptosis resistance independent of each other . The Δset1Δrad9Δdot1 triple mutant , however , exhibited similar survival curves , integrals and ROS accumulation as Δset1Δdot1 and Δset1Δrad9 cells ( Figure 4A–C; Table 1 ) . Therefore Dot1p and Rad9p act as pro-apoptotic proteins within the same pathway and the DDR machinery appears to be required for the activation of cell death of aged Δset1 cells . Nuc1p ( EndoG ) is a mitochondrial nuclease that translocates into the nucleus upon apoptosis induction coinciding with DNA fragmentation [47] . As loss of H2B ubiquitination is accompanied by an increased sensitivity to nuclease digestion [22] , we next asked whether the reduced viability and accelerated apoptosis of cells lacking H3K4 methylation is dependent on nuclease activity . As shown in Figure 5 , deletion of NUC1 in Δset1 cells significantly enhanced survival and consequently the survival integrals ( Figure 5 A and B; Table 1 ) . Furthermore , deletion of NUC1 in Δset1 cells diminished ROS production during aging ( Figure 5C and D; Table 1 ) . Consistent with previously published data [47] , aged Δnuc1 cells showed increased cell death compared to wild-type ( Figure 5A and B ) , which likely is of non-apoptotic nature [47] , but accompanied by increased ROS production ( Figure 5C ) . In contrast to nuc1 disruption , deletion of the apoptosis-inducing factor AIF1 , which also exhibits nuclease activity [7] , does not rescue the apoptotic phenotype of Δset1 cells ( Figure S1 ) . The reduced viability of Δset1 cells during chronological aging suggests that loss of H3K4 methylation accompanies cell death of aged wild-type yeast cells . To test this possibility , we carried out Western analysis to monitor H3K4 methylation in wild-type and Δdot1 cells during chronological aging ( Figure 6A ) . A loss of Set1p-mediated H3K4 tri- and dimethylation was observed in aging wild-type cells after 6 days in culture , but not in Δdot1 cells . Dot1p-mediated H3K79 trimethylation remained unaltered in aged wild-type cells ( Figure 6A ) . Quantification of the H3K4me3 and the H3K79me3 levels in wild-type cells normalized to phosphoglycerolkinase ( PGK ) revealed an about 5-fold reduction of H3K4me3 from day 1 to day 6 and 10 , while H3K79me3 levels remain equal ( Figure 6B ) . Similar to aged Δdot1 cells , H3K4 and H3K79 methylation remained unaffected in lymphocytes derived from Hutchison-Gilford progeria syndrome ( HGPS ) patients ( Figure 6C ) . HGPS is a human premature aging disease , predominantly due to mutations in the gene encoding the intermediate filament protein lamin A , and these cells are thought to be in a senescence-like state [48] . Compared to unaffected control cells , cells derived from differently aged HGPS patients ( 5 years old , 9 years and 13 years ) show a similar increase in H3K4me3 and H3K4me2 levels . These data indicate that loss of H3K4 methylation is not a general aging-related event , but rather specific for aged yeast cells undergoing apoptosis . If loss of H3K4 methylation in fact acts as trigger for apoptosis , one would predict that abolishing demethylation of H3K4 protects aging yeast cells from cell death . Demethylation of H3K4 is mediated by the trimethyl demethylase Jhd2p [49] , [50] . To test our hypothesis , we analyzed the viability of JHD2 deletion cells during chronological aging and found that Δjhd2 cells showed a slightly better survival as compared to wild-type cells with larger survival integrals and reduced ROS production ( Figure 6D–G; Table 1 ) . Moreover , the differences in survival of wild-type and Δjhd2 cells are statistically relevant when survival is normalized to day 2 , when all cells have reached the postmitotic stage ( Figure S2C and D ) . A double disruption of JHD2 and DOT1 has no additive effect on improvement of cell survival ( data not shown ) , indicating that Jhd2p and Dot1p act in the same pathway . Consistent with the hypothesis that increased or stable H3K4me3 levels are advantageous for survival , H3K4me3 levels increase in aged Δjhd2 cells from day 1 to day 3 and remain stable until day 10 ( Figure 6A ) . We observed , however , no or undetectable H3K4me2 in jhd2 deleted cells as in Δset1 cells . Similar to wild-type and Δset1 cells , H3K79me3 levels remain unaltered during aging of Δjhd2 cells ( Figure 6A ) . Together , our data strongly support the notion that loss of H3K4 methylation , in particular reduced trimethylation , is the cause for apoptotic death of yeast cells . To further strengthen the notion that loss of H3K4 trimethylation is causing the reduced viability of Δset1 cells during chronological aging , we next analyzed the viability of yeast cells lacking the two COMPASS subunits Spp1p and Bre2p , respectively . Both , Spp1p and Bre2p were previously shown to be required for proper H3K4 trimethylation [51] . Deletion of either SPP1 or BRE2 led to an early onset of cell death during chronological aging , similar to SET1 deleted cells , ( Figure 7A and B; Table 1 ) and to a boosted production of ROS ( Figure 7C and D; Table 1 ) . These data strongly support the notion that loss of H3K4 trimethylation is correlated with an early onset of apoptosis . To furthermore reveal that in fact the lack of H3K4 trimethylation is accounting for the increase in apoptotic cell death , we next tested the consequence of a point mutation in H3K4 , which prevents methylation of H3 at this site , on apoptosis . To do so , we analyzed the viability of the yeast strain H3K4A , which expressses a histone H3 variant containing a lysine-to-alanine substitution at lysine 4 [52] , during chronological aging . We found that these cells showed an early onset of cell death ( Figure 7 E and F ) , similar to Δset1 , Δspp1 , and Δbre2 cells . This increase in cell death of H3K4A cells coincided with enhanced ROS production ( Figure 7 G and H ) . In contrast to H3K4A cells , H3K79A cells that lack methylation at lysine 79 showed an improved survival as compared to wild-type cells ( Figure 7 E and F; Table 1 ) . As for Δdot1 cells ( Figure 2 ) , the effect of the K79A substitution was remote , but statistically relevant ( Figure 7F ) . ROS levels were similar to wild-type cells , albeit a bit increased ( Figure 7 F and G ) . Thus , loss of H3K4 trimethylation directly triggers apoptotic cell death during chronological aging , whereas loss of H3K79 trimethylation moderately improves cell survival . In order to rule out that the limited survival of Δset1 cells during chronological aging is due to acidification of the medium and/or metabolic effects [53] and to demonstrate the importance of H3K4 trimethlyation in apoptosis regulation in more general , we induced apoptosis in Δset1 cells using low concentration of hydrogen peroxide ( H2O2 ) . Whereas about 80% of wild-type and Δyca1 cells were recovered after treatment of cells with 0 . 6 mM H2O2 for 8 hours , less than 40% of set1 cells survived ( Figure 8A ) . The reduced survival of set1 cells coincided with increased ROS production ( Figure 8C and D , Table 1 ) . As during chronological aging , disruption of YCA1 in the Δset1 cells conferred resistance to apoptosis induced by H2O2 ( Figure 8A , C and D , Table 1 ) . Similarly , double disruptants of SET1 and DOT1 , RAD9 , and NUC1 , respectively , were less sensitive to H2O2 , whereas deletion of AIF1 could not rescue the lethal effect of H2O2 on Δset1 cells ( Figure 8B ) . Our data therefore suggest that loss of H3K4 methylation leads to increased apoptosis and sensitizes cells to apoptotic stimuli .
Methylation of histone H3 at lysine 4 and 79 is accomplished by the evolutionary conserved methyltransferases Set1p and Dot1p , respectively [57] , [58] . Methylation of both lysine residues appears to be associated with yeast cell death as loss of H3K4 methylation due to SET1 , SPP1 or BRE2 deletion accelerated apoptosis ( Figure 1 and 7 ) , while disruption of DOT1 and loss of H3K79 methylation delayed death of aged yeast cells ( Figure 2 ) . Similar results were obtained with the respective histone point mutants ( Figure 7 E–H ) , indicating that H3K4 methylation is an anti-apoptotic mark , whereas H3K79 methylation is a pro-apoptotic mark . The loss of SET1 and H3K4 methylation becomes apoptotic only in the presence of Dot1p and H3K79 methylation and can be suppressed by co-disruption of DOT1 ( Figure 3 ) , which is likely linked to the DNA damage checkpoint . H3K79 methylation is important for the recruitment of the checkpoint adaptor protein Rad9p , the S . cerevisiae homolog of 53BP1 , at damaged sites and for subsequent Rad53p phosphorylation to allow accurate DNA repair [32] . SET1 disruptants rapidly accumulate mutations ( Figure 4D ) indicative of genome instability ( see also [56] ) and accelerated DNA damage , which activates the apoptotic machinery after checkpoint activation and failed repair . In the absence of Dot1p and H3K79 methylation , Rad9p recruitment to damaged sites and Rad53p phosphorylation is impaired , the DNA damage checkpoint is not or insufficiently activated , and consequently apoptosis is not activated irrespective to the state of DNA damage . In keeping with this , the co-disruption of RAD9 in Δset1 cells rescued survival ( Figure 4A and B ) , despite the fact that the Δset1Δrad9 cells exhibited a high mutation frequency ( Figure 4D ) . Besides co-disruption of DOT1 and RAD9 , respectively , also co-deletion of YCA1 consequently suppressed the lethality of Δset1 cells , at least in part ( Figure 1 ) . Yca1p is known as yeast metacaspase and numerous cell death scenarios depend on it [2] , [8] . Yca1p likely acts downstream of the DNA damage checkpoint and insufficient DNA repair leads to its activation ( Figure 9 ) . Another executioner of apoptosis in yeast is the endonuclease Nuc1p . Nuc1p can be activated independent of Yca1p and both proteins/pathways converge at the mitochondria [47] . Nuc1p translocates from mitochondria into the nucleus upon activation to degrade chromatin . Changes in chromatin structure due to loss of H3K4 methylation in the absence of Set1p may render yeast cells more sensitive to nuclease activity and consequently NUC1 disruption in the Δset1 background improved cell viability ( Figure 5 ) , in contrast to disruption of AIF1 ( Figure S1 ) , which also exhibits nuclease activity [7] . Together our data presented here therefore suggest that loss of Set1p-mediated H3K4 methylation causes changes in chromatin structure and genomic instability , which activates the Rad9p-mediated DNA damage checkpoint in dependency on H3K79 methylation . Accumulation of DNA damage and insufficient repair in turn leads to an apoptotic response of the cells , which is executed by Yca1p ( in part ) and Nuc1p ( Figure 9 ) . Deletion of Dot1p and the loss of H3K79 methylation blocks activation of the DNA damage checkpoint and subsequent apoptosis . Apoptosis in yeast can be triggered exogenously and endogenously . Known endogenous triggers are , for example , defects in DNA damage response and replication , chromatin condensation , mRNA stability , or N-glycosylation [46] , [59]–[62] . Chronological aging of yeast cells is the best-studied physiological scenario associated with apoptosis in S . cerevisiae and the lifespan of aged yeast cells can be prolonged or shortened in many ways [4] , [63] , [64] . Glucose and nutrients have a strong impact on the CLS of yeast [63] , [65] , whereas endogenous triggers , however , have remained largely unknown . Our data presented here suggest loss of H3K4 methylation as one such endogenous trigger . Wild-type yeast cells lost H3K4 tri- and dimethylation ( Figure 6A ) after 6 days of culturing , which coincided with a significant increase in cell death ( Figure 1A ) . In contrast to that , H3K79 methylation is not altering during chronological aging . Preventing demethylation by either deleting DOT1 ( Figure 6B ) or deleting the trimethyl demethylase Jhd2p ( Figure 6C and D ) delayed against age-induced cell death , indicating that loss of H3K4 methylation is sufficient to drive yeast cells into apoptosis . Particularly , the loss of H3K4 trimethylation seems to promote apoptosis as Δjhd2 cells have low to no H3K4me2 levels ( Figure 6A ) , similar to Δset1 cells . Loss of H3K4me3 is not only triggering apoptosis , but also sensitizes yeast cells to apoptotic stimuli such as exposure to H2O2 ( Figure 8A–D ) , further underlying the importance of this histone modification in apoptosis regulation . H2B ubiquitination is required for H3K4 and H3K79 methylation and it remains to be seen if changes in H2B ubiquitination are the cause for the suppression of H3K4 demethylation upon disruption of DOT1 or if the recruitment of Jhd2p to H3K4 methylation is hindered in the absence of H3K79 methylation . This will be subject of future investigation . Given the strong evolutionary conservation of H3K4 and H3K79 methylation by the Set1/COMPASS complex and Dot1 , respectively , our findings pinpoint to a contribution of a deregulated apoptotic response to the pathology of acute myeloid leukemia ( AML ) . AML is associated with chromosomal translocations involving the MLL gene , the human homolog of Set1p . MLL-associated leukemia are aggressive , characterized by a frustrating therapy outcome , and are DOT1L-dependent [66] . It will be interesting to see how much our findings described here apply to human cells , especially to hematopoietic cells .
BY4742 ( MATα; his3Δ1; leu2Δ0; lys2Δ0; ura3Δ0 ) and its derivatives Δdot1 , Δyca1 , Δrad9 , Δnuc1 , Δjhd2 , Δ aif1 , Δspp1 , and Δbre2 were obtained from Euroscarf . Δset1 was derived from BY4742 , Δset1Δdot1 and Δset1Δdot1Δyca1 were derived from Δdot1 , Δset1Δyca1 and Δdot1Δyca1 were derived from Δyca1 , Δset1Δrad9 and Δset1Δrad9Δdot1 were derived from Δrad9 , Δset1Δnuc1 were derived from Δnuc1 , and Δset1Δaif1 were derived from Δaif1 strains . All derivate strains were constructed according to [67] PCR-based gene deletion . All strains are listed in Table 2 . Survival plating was conducted on YPAD ( 1% yeast extract , 2% peptone , and 2% glucose , 40 mg/ml adenine ) media supplemented with 2% agar . For experiments testing the chronological lifespan , strains were grown in synthetic complete medium ( SC ) with 2% glucose [68] . Transformation of yeast cells was performed by the lithium acetate procedure , as described by [69] . Chronological aging experiments , hydrogen peroxide treatment , and apoptotic tests using DHE-staining and TUNEL-staining were performed as described previously [39] . All chronological aging experiments reported were conducted at least three times , with three replicates for each strain . Integrals of the life span curves were calculated by summing the trapezoids created by the viability time points as described previously [40] . For the calculation of integrals 100% survival was set as 1 . P values were assigned by calculating the variance of integrals between biological replicates and comparing this to the integrals for wild-type cells using a T-test . Cells were viewed using a Leica TCS SP5 and a Zeiss LSM 710 confocal laser scanning microscope . Images were recorded using the microscope system software and processed using Image J and Adobe Photoshop . For quantification of DHE-staining using flow cytometry ( FACS-Aria , BD ) , in each sample 10 . 000 cells were evaluated and processed using BD FACSDiva software . For Annexin V staining the Annexin-V-Fluos staining kit ( Roche , Basel , Switzerland ) was used , following the instructions of the manufacturer . Spontaneous mutation frequency was determined based on the appearance of mutants able to form colonies on agar plates containing 60 mg l−1 L-canavanine sulfate according to [46] . Mutation rates were calculated per 106 living ( colony forming on YPD ) cells . Cell extract were prepared by acid extraction using 10% trichloroacetic acid ( TCA ) according to [70] . In brief , 1 . 5 ml culture were pelleted by centrifugation at 4°C and frozen at −20°C . 150 µl TCA buffer ( 10 mM Tris , pH 8 . 0 , 10% TCA , 25 mM ammonium-acetate , 1 mM EDTA ) were added to the frozen pellet on ice . When thawed , half the volume glass beads were added and samples were vortex 5×1 min with 3 min intervals on ice in between . The cell lysates were then transferred into a fresh , pre-cooled microfuge tube on ice and centrifuged for 10 min at 16 . 000 g at 4°C . The supernatant was discarded , the pellet resuspended in 100 µl resuspension solution ( 0 . 1 M Tris , pH 11 . 0 , 3%SDS ) , and boiled for 5 min . After cooling to room temperature , the samples were spun for 30 sec at 16 . 000 g to pellet the cell debris and 80 µl were transferred into a fresh microfuge . Protein concentrations were determined using the Bio-Rad DC protein assay ( Bio-Rad , Munich , Germany ) and 30 µg of proteins per well were loaded onto a 15% gel . After SDS-PAGE , proteins were transferred to a PVDF membrane and membranes were probed with the following rabbit polyclonal antibodies: anti-histone H3K4me3 ( 1∶1000 dilution; 39915 , Active Motif ) , anti-histone H3K4me2 ( 1∶1000; 39141 , Active Motif ) , anti-histone H3K79me3 ( 1∶1000; ab2621 , Abcam ) , anti-histone H3 ( 1∶500; 9715; Cell Signaling ) , the mouse monoclonal anti-PGK antibody ( 1∶10 . 000; Invitrogen ) and the respective alkaline-phosphatase conjugated secondary antibodies ( 1∶20 . 000; Sigma-Aldrich ) . Membranes were developed using the Western Lightning CDP-Star Chemiluminescence Reagent ( Tropix ) and X-ray films . The films were scanned and processed using Adobe Photoshop . Densitometric quantification was performed from three independent experiments using Image J . Human lymphocyte cell lines were obtained from Coriell Institute ( Coriell Institute , Camden , NJ , USA ) . Cell were grown in suspension in RPMI 1640 medium supplemented with 15% FBS and 2 mM L-glutamine . Cells were cultured at 37°C/5% CO2 . Cells were harvested by centrifugation at 600× g for 5 min . The pelleted cells were washed in PBS , resuspended in lysis buffer containing 50 mM Tris-HCl , pH 7 . 8 , 150 mM NaCl , 1% Nonidet P-40 and protease inhibitor cocktail tablets ( Roche , Basel , Switzerland ) . 30 µg of proteins per well were loaded onto a 15% gel and SDS-PAGE and Western blotting was carried out as described above . | Covalent histone modifications alter chromatin structure and DNA accessibility , which is playing important roles in a wide range of DNA-based processes , such as transcription regulation and DNA repair , but also cell division and apoptosis . Apoptosis is the most common form of programmed cell death and plays important roles in the development and cellular homeostasis of all metazoans . Deregulation of apoptosis contributes to the pathogenesis of multiple diseases including autoimmune , neoplastic and neurodegenerative disorders . The budding yeast Saccharomyces cerevisiae has progressively evolved as model to study the mechanisms of apoptotic regulation , and we study here the role of an evolutionary conserved trans-histone crosstalk , in particular histone methylation , in apoptotic signaling in yeast . We have identified a novel trigger for cell death in yeast and due to the strong evolutionary conservation our findings may apply to human cells and may be of importance for understanding the molecular mechanism underlying a specific subtype of acute leukemia . | [
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] | 2014 | Loss of Histone H3 Methylation at Lysine 4 Triggers Apoptosis in Saccharomyces cerevisiae |
A better knowledge of the flow and pressure distribution in realistic microvascular networks is needed for improving our understanding of neurovascular coupling mechanisms and the related measurement techniques . Here , numerical simulations with discrete tracking of red blood cells ( RBCs ) are performed in three realistic microvascular networks from the mouse cerebral cortex . Our analysis is based on trajectories of individual RBCs and focuses on layer-specific flow phenomena until a cortical depth of 1 mm . The individual RBC trajectories reveal that in the capillary bed RBCs preferentially move in plane . Hence , the capillary flow field shows laminar patterns and a layer-specific analysis is valid . We demonstrate that for RBCs entering the capillary bed close to the cortical surface ( < 400 μm ) the largest pressure drop takes place in the capillaries ( 37% ) , while for deeper regions arterioles are responsible for 61% of the total pressure drop . Further flow characteristics , such as capillary transit time or RBC velocity , also vary significantly over cortical depth . Comparison of purely topological characteristics with flow-based ones shows that a combined interpretation of topology and flow is indispensable . Our results provide evidence that it is crucial to consider layer-specific differences for all investigations related to the flow and pressure distribution in the cortical vasculature . These findings support the hypothesis that for an efficient oxygen up-regulation at least two regulation mechanisms must be playing hand in hand , namely cerebral blood flow increase and microvascular flow homogenization . However , the contribution of both regulation mechanisms to oxygen up-regulation likely varies over depth .
The brain has the ability to locally adapt cerebral blood flow to a locally increased energy demand [1 , 2] . Neuronal activity triggers dilation of vessels which leads to an increased blood flow and therewith to an up-regulation of metabolite and oxygen supply . Additionally , further small-scale regulation is likely to take place [3–5] . However , the detailed vascular mechanisms and the signaling pathways between neurons and vessels are still not fully resolved . One of the difficulties in understanding neurovascular coupling lies in the interaction of the different regulation mechanisms playing at approximately the same time but on different spatial scales . The complex topology of the vasculature as well as the high temporal and spatial resolutions required pose further challenges in performing elucidating measurements in large samples . The most fundamental and most studied regulation mechanism is the increase in blood flow which also is the basis for various measurement techniques such as functional magnetic resonance imaging ( fMRI ) . It is well established that arterioles dilate during neuronal activation and contribute to the up-regulation of blood flow [1 , 6] . However , Hall et al . [3] recently observed that capillaries respond to stimulation earlier than arterioles and they speculate that 84% of the blood flow increase results from dilation of capillaries by pericytes . Thus , there is an ongoing debate about which vessel type is mainly responsible for the increase in blood flow . To answer this question the pressure distribution in cerebral microvascular networks ( MVNs ) is crucial . Indeed , if pure plasma flow is assumed diameter changes at the location of the largest pressure drop will lead to the largest change in flow rate . Yet , in vivo it is extremely challenging to measure blood pressure in MVNs . Commonly used micropipette measurements are limited to vessels close to the cortical surface and are only applicable to vessels with a diameter > 25 μm [7–9] . Furthermore , many measurements at different locations would be needed to compute the pressure drop in different vessel types , which is not feasible in in vivo studies . Hence , numerical simulations are needed to obtain detailed information on the pressure distribution in MVNs . On the smaller scale , the effect of neuronal activation on individual capillaries was investigated in multiple studies [4 , 5 , 10–13] which all agree that red blood cell ( RBC ) velocity and flux increase in the capillary bed with neuronal activity . Additionally , a homogenization of RBC flux in the capillary bed is observed during activation [4 , 5 , 13 , 14] . Jespersen and Østergaard showed that a reduced capillary transit time heterogeneity ( CTH ) is beneficial for the overall oxygen extraction fraction ( OEF ) [15] . Nonetheless , the precise role and impact of the observed phenomena in the up-regulation of oxygen in the brain is still debated . Another challenge in performing in vivo flow measurements in MVNs is the limited penetration depth of the available measurement techniques . Most in vivo studies in cortical MVNs with resolution on the micrometer scale are limited to a few hundreds of micrometers of the cortex and little is known about the flow patterns deep in the grey matter [3 , 4 , 10 , 12 , 13] . This constitutes a major problem , because the neocortex consists of six cortical layers with different neuronal densities and different metabolic demands . Studies on the vasculature showed that vascular densities also vary over cortical depth [16–19] and high-resolution fMRI studies revealed that laminar differences persist in changes in cerebral blood flow ( CBF ) and cerebral blood volume ( CBV ) during activation [20 , 21] . Furthermore , two studies with measurements of flow properties in individual capillaries down to a depth of 600 μm observed depth-dependent changes in RBC velocity [11 , 14] . Hence , laminar differences in flow characteristics seem likely during baseline and activation , but have not been investigated in detail . We simulate blood flow in three realistic microvascular networks from the mouse parietal cortex [19 , 22] . In contrast to previous numerical works in realistic MVNs , which are mostly based on the empirical steady state model derived by Pries et al . [23] , we apply a numerical model which directly tracks individual RBCs . Additionally , we present a new approach for assigning appropriate and realistic boundary conditions at the in- and outflows of MVNs . This work aims to answer questions that are crucial for research on neurovascular coupling and which are extremely difficult to be answered experimentally . We analyze our simulation results with three key questions in mind: ( 1 ) Where does the largest pressure drop take place ? ( 2 ) Are there differences in flow properties over the cortical depth and is it relevant for up-regulation of blood flow ? ( 3 ) How large is the CTH and what can be concluded from the trajectories of RBCs through the capillary bed ?
We studied three MVNs from the mouse parietal cerebral cortex . The networks were acquired with the use of two-photon laser scanning microscopy [19 , 22 , 24] . For details on the data acquisition and the validation of the methods used consult [19 , 22 , 24] and references therein . To properly differentiate between the different vessel types information on the presence of smooth muscle cells and pericytes would be needed [25] . As this information is not available , Blinder et al . [19] classified the vessels based on their morphology , their diameter and the tracking of penetrating trees into: pial arterioles ( PA ) , descending arterioles and arterioles ( DA+A ) , capillaries ( C ) , venules and ascending venules ( V+AV ) and pial venules ( PV ) . The vessel classification is extended by a diameter criterion , which requires that two consecutive vessels have a diameter < 7 . 0 μm until the capillary bed starts . The labeling is further adjusted such that there is no capillary with a diameter > 9 . 0 μm and no arteriole/venule with a diameter < 6 . 0 μm . In general MVN 3 has slightly smaller diameters than MVN 1 and 2 and hence , the minimum arteriole/venule diameter had to be set to 4 . 8 μm in order not to treat most DAs as part of the capillary bed . In the original labeling it is differentiated neither between DAs and As nor between Vs and AVs . Nonetheless , in the course of this work we comment on the impact of introducing this additional classification ( S1 Table ) . Literature data on capillary diameters in rodents is sparse and varies significantly . Table 1 summarizes some of the available measurements of capillary diameters in rodents . As the mean capillary diameter for all MVNs in this study is < 4 . 0 μm the vessel diameters are upscaled slightly . We applied a histogram-based upscaling approach based on a beta distribution with a mean of 4 . 0 μm and a standard deviation of 1 . 0 μm ( Fig 1A ) . The beta distribution is defined in the diameter range [2 . 5 μm , 9 . 0 μm] . Details on the histogram-based upscaling approach are summarized in S1 Fig . In Table 2 several characteristic parameters of the MVNs are summarized . All networks are of cuboid shape with a nearly quadratic surface area and a depth such that most grey matter is contained in it . The simulation procedure is described in more detail in [33] but briefly summarized below . Our results presented in [33] showed that particularly for the flow in the capillary bed it is crucial to consider the impact of RBCs and hence blood is treated as a biphasic fluid . A short analysis on the impact of RBCs on the flow in realistic microvascular networks is presented in S2 Fig . In the numerical representation the tortuous vessels of the MVN are approximated by straight pipes between two bifurcations . The straight pipe is assigned the same length and resistance as its tortuous equivalent . Therewith , we only neglect the effect of diameter changes along individual vessels . The flow in the pipe ij between the nodes i and j is computed by Poiseuille’s law q i j = p i - p j R i j e , ( 1 ) where qij and R i j e are the flow rate and the effective resistance of pipe ij , respectively , pi and pj denote the pressure values at the nodes i and j . The effective resistance R i j e accounts for the presence of RBCs by multiplying the resistance of a circular tube Rij with the relative apparent viscosity μvitro , ij , which is based on the empirical formulation derived by Pries and Secomb [34]: R i j e = μ v i t r o , i j R i j = μ v i t r o , i j 128 μ p l a s m a π d i j 4 L i j , ( 2 ) where μplasma is the plasma viscosity and dij and Lij are the vessel diameter and length , respectively . The relative apparent viscosity μvitro , ij is a function of the tube hematocrit htij and the diameter of the vessel dij: μvitro , ij = f ( htij , dij ) . The complete expression and a justification for this choice is given in S1 Text . RBCs are tracked individually ( discrete simulation ) . According to the Fåhraeus effect the RBC velocity is on average larger than the bulk flow velocity [35] . At divergent capillary bifurcations we assume that the RBCs follow the path of the largest pressure force [36 , 37] , which is equivalent to the path of the largest bulk flow velocity . Another commonly used bifurcation rule states that the RBC moves into the branch with the largest flow rate [38 , 39] . For 91% of all capillary divergent bifurcations in the three MVNs the two bifurcations rules predict the same behaviour ( based on the results of pure plasma simulations ) . Hence , we are confident that the choice of the bifurcation rule , does not greatly affect the overall results . In arteriole divergent bifurcations the RBC motion is more complicated and their separation is described by the phase-separation law introduced by Pries et al . [40] . The RBC tracking is implemented such that an overlapping of RBCs is not possible . For example , at convergent bifurcations RBCs can be blocked temporarily if there is not enough space in the subsequent vessel . As soon as the RBC fits into the next vessel it will proceed . To reduce the computation time and in contrast to the model introduced in [33] the time step Δt is constant and not a function of the next bifurcation event . Hence , per time step multiple bifurcation events take place . The time step is chosen such that for nearly all vessels ( > 99 . 8% ) the following criterion is satisfied: Δ t ≤ L i j v i j , ( 3 ) where Δt is the time step , Lij and vij are the length and the bulk flow velocity of edge ij . For each time step two computation steps are performed . In the first one , which is based on the current distribution of RBCs , the pressure and flow field is calculated . Consecutively , the RBCs are propagated and their distribution is updated . The RBCs are tracked for at least one turn-over time , which is the ratio of the total vascular volume to the sum of all inflows . To minimize the impact of the initial conditions the simulation is run for at least 15 turn-over times before the RBC path is recorded . A major challenge in simulating blood flow in realistic MVNs is the assignment of appropriate boundary conditions . In Fig 1C an exemplary MVN with all its in- and outflow vertices is illustrated . In most numerical studies only the in- and outflow vertices at the pial level are kept to assign pressure boundary conditions . All in- and outflow branches deeper in the cortex are eliminated or no flow boundary conditions are prescribed [41–43] . The results in [42] show that this approach generally underestimates the flow . Hence , we introduce a new approach where the realistic MVN is implanted into a large artificial MVN ( compound network ) . In the center of the artificial network a hole of the size of the realistic network is cut . The realistic network is positioned in the cut-out and connected to the artificial network at the deep in- and outflow vertices . By assuming a constant tube hematocrit the pressure distribution for the compound network can be computed ( steady state simulation without RBC tracking ) . The pressure values obtained from the steady simulation are assigned as boundary conditions to the deep in- and outflow vertices of the realistic microvascular network . The simulation with discrete RBC tracking is only executed in the realistic network . Fig 1C illustrates the steps of the hierarchical boundary condition approach . The artificial network consists of a database of realistic penetrating trees and an artificial capillary bed ( Fig 1C ) . The realistic penetrating vessels have been obtained from the somatosensory cortex of the rat [45] . To account for the differences in size between rat and mouse brain , the arteriole and venule trees have been scaled by the ratio of cortical thicknesses ct:c t m o u s e c t r a t = 0 . 66 [46] . The penetrating trees are arranged as a rhombic lattice based on the observations by Blinder et al . [19] . The artificial capillary bed is constructed from a stacked hexagonal network which represents a simplified mesh structure where every bifurcation has three adjacent edges [47 , 48] . To finish the artificial MVN the ends of the penetrating trees are connected to the closest capillary vertex . Literature data on pressure measurements in pial vessels is very sparse [7–9 , 44] . We fitted a polynomial of degree 3 to the available pressure measurements in pial arterioles ( Fig 1B ) . The pressure in pial venules depends only weakly on the diameter , hence we uniformly set the pressure to 10 mmHg . The tube hematocrit at all inflow edges is set to the physiological value of 0 . 3 . In the studied MVNs the deep in- and outflows were already trimmed and hence , in their original configuration it was not possible to implant and connect the realistic MVNs to the artificial one . In order to create in- and outflows over the depth , we cut off 12 . 5% of the total width on all sides . The average depth of the mouse cortex is 1 . 2 mm [46] . Hence , we trim the MVNs analyzed at a depth of 1 . 2 mm to create in- and outflows at the bottom ( MVN 3 is trimmed at a depth of 0 . 95 mm ) . Simultaneous measurements of flow characteristics in multiple vessels of networks embedded in a tissue volume of > 1 mm3 are very challenging to perform in vivo . Recently , Lee et al . [12] presented a promising approach where optical coherence tomography is used to measure the RBC flux in several capillaries at the same time with a temporal resolution of ∼1 s . Other than that , most in vivo measurements only target a very small subset of vessels and average over several seconds . We validate our simulation setup by comparing our results to two frequently measured flow characteristics: the RBC velocity vRBC and the RBC flow rate qRBC ( Table 3 ) . In our opinion it is essential to compare flow properties for different vessel types . Furthermore , especially in the DAs a good agreement is crucial , because those vessels are the inflow vessels of the downstream capillary bed . Literature values show that the flow in the microvasculature is heterogeneous and fluctuating in time and hence , the range of measured values is large [49] . All in all , our results are in line with the in vivo measurements and we conclude that the assigned boundary conditions and our numerical framework are appropriate . Our data analysis is based on trajectories of individual RBCs through the MVN . We tracked all RBCs entering the MVN at the pial level . RBCs entering the network at the deep in- and outflows can not be analyzed because the history of the RBC pathway is unknown . Yet , we expect that comparable characteristics along the pathway of those RBCs would be observed . A crucial aspect for commenting on the pressure drop in different parts of the microvasculature is the correct labeling of vessel types . As mentioned , for a fully accurate distinction of vessel types the presence of smooth muscle cells and pericytes would have to be considered [25] . However , our labeling is solely based on morphology , topology and diameters and hence is error prone . A correct RBC trajectory flows through the different vessel types in the following order: PA → DA+A → C → V+AV → PV . To make the data analysis robust with respect to labeling errors we allow the RBCs to deviate from the correct path ( PA → DA+A → C → V+AV → PV ) for two subsequent branches , as long as it afterwards proceeds in the correct manner . In the course of this work we comment on the sensitivity of our results with respect to labeling errors ( S3 Fig ) . Only RBC trajectories which flow through the different vessel types in correct order: PA → DA+A → C → V+AV → PV are considered for data analysis . For analyses which only address flow phenomena in the capillary bed , ( PA or DA+A ) → C → ( V+AV or PV ) is also accepted as a correct RBC trajectory . In order to analyze the simulation results with respect to cortical depth we divided the MVN into five analysis layers ( AL ) . We use 200 μm thick slices and limit our analysis to the upper 1000 μm of the cortex . MVN 1 with the five ALs is illustrated in Fig 2A . Unless stated otherwise , all presented results have been averaged over all three MVNs analyzed .
In a first step we analyzed the RBC pathways through the capillary bed . Fig 2B illustrates an exemplary RBC trajectory for each AL . Per MVN there are on average 2811 unique paths leading the RBCs from DA+A to V+AV . Yet , the distribution of the paths from DA+A to V+AV over the five ALs is not homogeneous ( Table 4 ) . The largest number of available paths is found for AL 2 and AL 3 , followed by AL 1 and AL 4 where on average 580 unique paths exist between DA+A to V+AV . With approximately 200 available unique paths AL 5 offers the least possibilities for the RBCs to travel through the capillary bed . The nonhomogeneous distribution of paths through the capillary bed over cortical depth is the first evidence for layer-specific differences in the vasculature , which might as well affect functional properties . Per capillary start point there are on average 5 possible end points and 8 possible paths to reach the V+AV . To comment on the frequency a specific pathway is chosen , the preferred end point and the preferred path are introduced . If a capillary start point has nep end points the relative end point frequency fep is computed by dividing the number of RBCs reaching that end point by the total number of RBCs passing the capillary start point under investigation . A capillary start point has a preferred end point if the largest end point frequency is > 50% and the second largest one is < 30% . The equivalent definition is applied to define a preferred path . 60 . 7% of all capillary start points have a preferred end point and for 53 . 1% of all capillary start points there is a preferred path through the capillary bed . So even if the capillary bed is highly interconnected and offers a multitude of pathways through the capillary bed , the frequency at which different paths are chosen differs significantly . We assume that the nonhomogeneous perfusion in the baseline case enables the vasculature to more effectively alter perfusion during activation , e . g . by increasing the RBC flux through previously less perfused paths . We next investigated whether the existence of the preferred end points emerges from topological characteristics of the MVN . We analyze if the relative frequencies of the available end points correlate with five different trajectory characteristics: For the trajectory characteristics ( 2 ) - ( 5 ) it has to be kept in mind that several paths might be leading from one start to one end point and hence averaging over all the available paths is necessary to obtain a single measure per end point . The trajectory characteristics have been normalized with the maximum value for each start point: t c e p n o r m = t c e p m a x ( T C e p ) , ( 4 ) where tcep is a trajectory characteristic of one path and TCep contains the trajectories characteristics for all end points of one start point . We compute Pearson’s correlation coefficients for the relative end point frequencies and the five normalized trajectory characteristics ( Table 5 ) . The Euclidean distance is a pure topological measure and does not correlate with the relative end point frequencies . All further characteristics are based on the path of the RBCs through the capillary bed and hence not pure topological characteristics but influenced by the flow field . The average path length as well as the average sum of resistances along the path show a very weak negative correlation with the end point frequencies . However , with a correlation coefficient > 0 . 4 the relative end point frequencies correlate more strongly with the average flow rate and RBC velocity . This is plausible , because the average flow rate as well as the average RBC velocity have a direct impact on the distribution of the RBCs . More importantly , this result underlines the importance of a combined analysis of flow field and topology . A purely topological analysis might lead to wrong conclusion because it neglects crucial effects such as the RBC dynamics and the impact of the bifurcation rule . In the next step we study the cortical depth cd of the capillary start points cdC , start and the cortical depth of their capillary end points cdC , end . The Pearson’s correlation coefficient of r = 0 . 86 confirms that cdC , start and the cortical depth of its capillary end points are strongly correlated . The linear fit for cdC , start and cdC , end reads as ( red line in Fig 2C ) : c d C , e n d = 1 . 08 c d C , s t a r t - 0 . 08 . ( 5 ) The y-intercept of −0 . 08 mm shows that the capillary end point is positioned closer to the cortical surface than its capillary start point . It is important to realize that the RBCs tend to move in-plane and no significant movement in the direction of the cortical depth takes place . The in-plane movement of RBCs in the capillary bed is an important result because it implies that at the capillary level there is no significant flow between the different ALs and hence it justifies the approach to analyze flow characteristics with respect to different ALs . This is not only relevant for our simulations , but for all layer-specific analysis , including fMRI or bolus tracking measurements . A further crucial aspect is the robustness of oxygen supply in the brain and the feeding regions of individual DAs . This topic has already been addressed in multiple numerical as well as experimental studies [42 , 54 , 55] . Although our sample size of available DAs and AVs is small we are able to make some observations about the feeding and draining regions of DAs and AVs , respectively . In our study one DA feeds on average 3 . 8 different AVs and one AV is fed on average by 2 . 8 different DAs . Yet , one AV receives on average 72% of all its RBCs from one DA . This implies that every AV has a primary DA by which it is fed . Hence , the tissue around one AV might be very vulnerable to ischemia in case of occlusion of the primary feeding DA , unless significant blood flow reorganization takes place . This is in accordance with the observations of Nishimura et al . [56] , which state that the “penetrating arterioles are a bottleneck in perfusion” . A good understanding of the pressure distribution in MVNs is crucial to interpret the results of in vivo measurements and to derive mechanisms explaining the vasculature’s ability to up-regulate blood flow . Fig 2D and 2E depict the pressure along the path of two exemplary RBCs in MVN 1 . The diameter along the RBC path is illustrated in line with the pressure , because the resistance of a vessel Rij has a strong impact on the pressure drop and R i j ∝ d i j - 4 . In both examples the pressure drop becomes significant as soon as the vessel diameter falls below ∼ 15 μm . After an initial shoulder the slope of the pressure curve remains relatively constant until the RBC reaches the V+AV . The pressure drop tends to increase if the diameter of the vessel decreases . However , the diameter is not the only parameter influencing the pressure drop . Further very important quantities are the topology and connectivity of the vascular network as well as the number of RBCs in each vessel . The pressure along the path of an RBC has been extracted for all RBCs with a correct pathway ( PA → DA+A → C → V+AV → PV ) . To average the pressure curves the normalized path length is introduced: s n o r m = s s t o t , ( 6 ) where stot is the total length of the RBC path through the MVN . The RBCs are grouped based on the cortical depth of their capillary start point . An averaged pressure curve is computed for every AL ( Fig 3A ) . In order to illustrate the total path length for the different ALs , the normalized path length is multiplied with the average total path length for each AL . For all ALs the pressure starts to drop significantly after s ∼ 0 . 5 mm . As the capillary bed starts on average at s ∼ 1 . 3 mm ( depending on the AL ) , the pressure already starts to drop in the arterioles . The shape of the averaged pressure curves for AL 1–3 ( cd < 0 . 6 mm ) is very similar . All three curves have an S-shape with a constant slope in the middle of the path and a flatter slope for the first and the last 0 . 5 mm along the path . Even for AL 4–5 ( cd ≥ 0 . 6 mm ) the shapes of the curves are comparable to the one of AL 1–3 . However , the slope flattens shortly before the start of the capillary bed ( s ∼ 1 . 2 mm ) . This is not seen for the pressure curves of AL 1–3 . The difference between the total path length in AL 1 and AL 5 is 1 . 25 mm . It might seem surprising that the pressure drops continuously and no steeper pressure drop in the capillaries is observed , even though that is where the smallest vessel diameters are found . We assume that this can partly be attributed to averaging over > 1 million RBC pathways , which leads to a smoothing of the originally bumpy curves ( Fig 2D and 2E for comparison ) . The averaged diameter along the path of the RBCs shows a continuous drop in diameter until the capillary bed is reached ( S4 Fig ) . It is smallest at the beginning of the capillary bed and starts to increase for downstream vessels for all ALs . Surprisingly , the pressure drops continuously along the whole path even though the average diameter exhibits strong variations over the path ( S4 Fig ) . This confirms that the pressure drop is not only affected by the diameter , but as aforementioned by the connectivity of the MVN and the distribution of RBCs in the MVN . The location of the largest pressure drop is the ideal region for regulating hemodynamics [3] . Hence , to comment in more detail on the contribution of different vessel types to the total pressure drop the pressure drop per vessel type is computed ( Fig 3D–3F ) . We average the pressure at the inlet vertices of the five different vessel types ( PA , DA+A , C , V+AV , PV ) . Additionally , the averaged path length is computed for each vessel type . As for the previous studies , we calculate averages for every AL based on the cortical depth of the capillary start point . As the sample size of PAs and PVs is very small , the pressure drops are only illustrated for completeness and are not analyzed further . The differences between the three ALs illustrated are striking . Whereas in AL 1 ( cd = 0 − 0 . 2 mm ) the pressure drop in the capillaries is dominant ( 37% ) , in AL 3 ( cd = 0 . 4 − 0 . 6 mm ) and AL 5 ( cd = 0 . 8 − 1 . 0 mm ) the largest pressure drop is found in the DA+A ( AL 3: 51% and AL 5: 61% ) . This reveals that the contribution of the different vessel types to the total pressure drop is highly dependent on the cortical depth of the capillary start point . Furthermore , our results show that total pressure drop in the DA+A correlates with the path length traveled in the DA+A . The total path length increases the deeper the RBC flows into the MVN ( Fig 3D–3F ) . To address the sensitivity to labeling errors we compare the results of the standard labeling to two modified labelings ( S3 Fig ) . For deep ALs the result is very robust ( S3D–S3F Fig ) . A larger sensitivity is found for the labeling of capillaries and arterioles in AL 1 ( S3A–S3C Fig ) . For all investigated scenarios the capillaries play a significant role for the pressure drop in AL 1 . However , if S3A and S3B Fig are compared , it becomes evident that on average 31% of the total pressure drop in the capillary bed takes place in the first capillary branch . Hence , for AL 1 where the pressure gradients are very steep a correct labeling is crucial . Many studies related to neurovascular coupling differentiate between the main branch of the DA and the A branching off ( sometimes called precapillary arterioles ) [57 , 58] . Our results show that for AL 2–5 the pressure drop mainly takes place in the DAs and is very small in the As ( S1 Table ) . For AL 1 the pressure drop in the DAs and As is comparable . Based on the original labeling 16% of all RBCs flow directly from the DAs into the capillary bed . We conclude that already in the main branch of the DAs the pressure starts to drop significantly . All in all , our results show that it is indispensable to account for the pressure drop in the DAs+As . Generalizations on the location of the largest pressure drop in the vasculature are not valid because it needs to be differed based on the cortical depth of the capillary start point . For AL 1–2 the location of the largest pressure drop is the capillary bed and to be more precise mainly the first branches of the capillary bed . For AL 3–5 the pressure drops the most in the DAs+As . The pressure drop in the Cs decreases with increasing cortical depth . Oxygen discharge from the vasculature to tissue is a diffusion driven process which based on common notion mainly takes place in the capillary bed . However , this view has been recently challenged by Sakadžić et al . [58] who state that 50% of the oxygen is extracted from arterioles in the baseline case . Nonetheless , the impact of the heterogeneous flow properties in the capillary bed are crucial to fully understand the oxygen supply of the brain . For example Rasmussen et al . [59] showed that a reduced CTH leads to an increase in OEF . Additionally , our presented results show that significant differences between the ALs persist and hence , the question arises if these differences also affect flow phenomena observed in the capillary bed . We present results for capillary transit time ttC , capillary transit path length tsC and the capillary RBC velocity vRBC , C in different ALs ( Fig 3B ) . All three quantities have an impact on the amount of oxygen which can be discharged from individual RBCs . The mean transit path in the capillary bed is shortest for AL 1 ( ∼0 . 17 mm ) . For all other ALs it is approximately constant tsc ≈ 0 . 3 mm . This agrees well with the observations of Sakadžić et al . [58] which find an average path length of 0 . 34 mm for measurements until a depth of 0 . 45 mm . To the best of our knowledge Kleinfeld et al . [11] and Gutiérrez-Jiménez et al . [14] performed the only measurements of RBC velocity up to a depth of 600 μm [11 , 14] . In both works a slightly decreased RBC velocity over the cortical depth is observed . This agrees well with our results illustrated in Fig 3B . The changes in capillary RBC velocity over depth probably result from the high pressure gradient between DA+A and V+AV close to the surface , which decreases with cortical depth . For AL 1 we obtain an average RBC velocity which is larger than the velocity range stated in literature ( 0 . 4 − 1 . 0 mm s−1 [4 , 10 , 11 , 13 , 51] ) . The capillaries with the large RBC velocities are located very close to the cortical surface ( cdC , start < 75 μm ) and connect DAs with nearby AVs , hence the capillary transit path length is comparably short . The mean capillary transit time on the other hand increases with cortical depth , which is in accordance with the higher capillary RBC velocity vRBC , C close to the cortical surface . For AL 1 the mean capillary transit time is equal to 0 . 07 ± 0 . 14 s and rises to 0 . 52 ± 0 . 51 s for AL 5 . Literature values for capillary transit time are sparse . The most recent and suitable measurements have been done by Gutiérrez-Jiménez et al . [14] which obtain a mean transit time of 0 . 66 ± 0 . 20 s from arterioles to venules . The small capillary transit times close to the cortical surface suggest that the RBCs have less time to discharge oxygen and hence the OEF per RBC is smaller at the cortical surface than deep in the cortex . As the average transit path length tsC is nearly constant over depth , the increased transit time ttC with depth is also reflected in a decrease in RBC velocity vRBC with depth ( Fig 3B ) . The RBC velocity is proportional to the RBC flow rate , which is confirmed by Fig 3C . All in all , our results suggest that the oxygen level in the tissue is largest close to the cortical surface . Due to the large RBC feeding flow in AL 1 and the large RBC velocities , it seems likely that RBCs traveling close to the cortical surface are still highly saturated with oxygen as they reach the venules . As the feeding flow rate decreases for deeper ALs ( Fig 3C ) and the transit time increases , we expect the RBCs leaving the capillary bed at a deeper cortical level to be less saturated with oxygen than the RBCs close to the cortical surface . The scatter plot in Fig 3B confirms the presence of a large CTH in cerebral MVNs . While for the capillary transit path the standard deviation remains constant over cortical depth , it increases for the capillary transit time . Consequently , deeper in the cortex the reduction of CTH might be a more effective mean to increase the OEF than close to the cortical surface . Furthermore , the standard deviation of the capillary transit time and the RBC velocity show opposing trends over cortical depth . Those differences have to be kept in mind for estimations of CTH based on the RBC velocity . In Fig 3C the total number of feeding branches for the five ALs , the sum of the blood flow rate and the sum of the RBC flow rate through those branches is illustrated . While the blood flow and the RBC flow rate show similar trends , namely a lower feeding flow rate for deeper ALs , the number of feeding branches increases until AL 3 and then drops significantly . The number of feeding branches is a topologically based quantity , while the feeding flow rates are flow related quantities . Both results underline once more the complex flow phenomena in MVNs and the necessity to consider the flow field and the vascular topology as one entity .
We simulated blood flow in three realistic MVNs from the mouse parietal cerebral cortex . To our knowledge this is the first numerical work in realistic MVNs where RBCs are tracked individually and the results are directly based on RBC trajectories . As the RBCs are the brain’s oxygen source they are the most fundamental entity of blood for the up-regulation of oxygen and hence should be at the basis of a functional analysis . The focus of our investigations lies on the pressure field in the MVN and on depth specific flow characteristics . Our results show that the location of the maximal pressure drop depends significantly on the cortical depth of the capillary start point . While close to the cortical surface the pressure drop in the capillary bed is dominant , the deeper we dive into the cortex the larger the pressure drop in the DAs+As . This is plausible because based on the vascular topology the distance a RBC travels in the DAs increases for deeper layers and hence a larger pressure drop in DAs+As is to be expected . In Guibert et al . ’s [60] numerical work the pressure drop in different vessel generations is studied in the primate cortex . They show that the pressure drops rapidly over the first vessel generations and then reaches a fairly constant level . Unfortunately , no detailed differentiation between vessel types is presented and differences over depth are neglected , such that a quantitative comparison with our results is difficult . Qualitatively our results agree well with the steep pressure drop early along the path of the RBC . However , we do not observe the pressure plateau in the capillary bed as stated by Guibert et al . [60] but a continuous drop in pressure until the Vs+AVs are reached ( Fig 3A ) . We suppose that the difference results from grouping the capillaries into generations instead of analyzing the pressure drop over the RBC path . Furthermore , a species difference between the primate and rodent cannot be ruled out , which makes a direct comparison even more difficult . Blinder et al . [19] computed the average resistance of the microvasculature in cortical layer IV as well as the average resistance for DAs and AVs from the surface to cortical layer IV . They obtained an average resistance of 0 . 1 , 0 . 4 and 0 . 2P μm3 for the DAs , the capillary bed and the AVs , respectively . If pure plasma flow is assumed , the largest pressure drop would take place in the capillary bed [3] . This disagrees with our observations for AL 3 ( ≙ cortical layer IV ) , where the pressure drop is largest for the DAs+As ( 51% ) ( Fig 3E ) . We assume that those discrepancies result from the fully topological analysis in [19] . For computing the average resistance of the capillary bed 1000 randomly chosen pairs of vertices were used . We suggest that it is more appropriate to base the choice of vertices on actual RBC paths , because topologically connected but not functionally connected vertex pairs might artificially increase the average resistance of the capillary bed . In a recent numerical study by Gould et al . [43] the pressure drop was analyzed along possible paths through the cortical microvasculature . While the focus was on predicting oxygen levels in the brain , one of their main claim is that the “capillary bed offers the largest hemodynamic resistance to the cortical blood supply” . This is partly in contrast to our observations , especially for deeper ALs . Gould et al . applied no flow boundary conditions for the deep in- and outflows that , based on [42] , can lead to an underestimation of flow and thus can impact the resulting pressure field . A more quantitative comparison is however difficult , because values for the pressure drop per vessel type are not provided . Furthermore , whereas two of the analysed networks support their conclusion , it is less obvious for the remaining two . We believe that analyzing the pressure drop over the path length of discrete RBC trajectories is more robust and that a layer specific analysis provides further important information . Consequently , we challenge the hypothesis that the dilation of individual capillaries leads to a flow increase of 84% and therewith would be the ideal location for vascular changes during activation [3] . Based on our results in AL 3–5 the DA+A is the location with the largest pressure drop and hence the most crucial for up-regulating flow . For AL 1–2 the situation is slightly different and vascular changes in the capillary bed and the DA+A could both be effective means to increase the flow rate . However , the number of capillaries is significantly larger than the number of arterioles and hence a well coordinated response of multiple capillaries could compensate for the smaller pressure drop . The impact of the possible regulation scenarios has to be analyzed in future numerical studies . We postulate that different regulation mechanisms are playing at different cortical depths and with different objectives . The dilation of DAs+As seems to be the most relevant mechanisms to increase the flow rate on a large scale , whereas capillary dilation might play a more crucial role for small scale and very localized regulations such as redistribution of RBCs or flow homogenization . On the larger scale Zhao et al . [21] and Goense et al . [20] showed that layer-specific regulation mechanisms have to exist in order to explain the laminar differences in CBV and CBF change during activation . Gutiérrez-Jiménez et al . [14] addressed this topic more locally by measuring RBC velocity and flux in capillaries until a cortical depth of 450 μm during baseline and electrical forepaw stimulation . They show that the RBC velocity and RBC flux do not change homogeneously over depth during activation . This agrees well with our hypothesis that different regulation mechanisms are playing at different depths and that the microvasculature plays a significant role in neurovascular coupling . The question arises whether the layer-specific differences in the pressure drop can be explained by topological characteristics . We address this issue by analyzing differences in RBC pathways , in capillary transit time and transit path lengths and in the feeding of the different layers . Our results show that for AL 2–3 the RBCs have the most options to travel through the capillary bed . These ALs ( 200 − 600 μm ) which overlap with the granular layer IV in the mouse somatosensory cortex also show the largest number of feeding branches ( Fig 3C ) . Furthermore , our findings are in accordance with results obtained in the macaque visual cortex [16] , where the cortical layer IV ( and in particular IVcB ) shows the highest vascular density . A more interconnected microvasculature in AL 2–3 would be beneficial to up-regulate the oxygen supply with a high spatial precision . It seems plausible that the brain has an improved ability to locally up-regulate oxygen in layer IV in the granular cortex , which has the highest neuronal density and metabolic demand . Due to the high neuronal density in cortical layer IV one might assume that the feeding flow rate in this area is largest . Yet , we observe a decrease in feeding blood and RBC flow over cortical depth . While close to the surface the RBC flow is very large and the RBCs as well as the tissue are most likely highly saturated with oxygen , deeper in the cortex a more efficient extraction seems to be crucial to avoid hypoxic tissue regions . This implies that deeper cortical layers might be more vulnerable to disruptions in feeding flow , because the safety margin in RBC flow seems to be significantly lower than close to the cortical surface . Various studies measured the tissue and plasma oxygenation over cortical depth . However , results differ significantly . While Lyons et al . [61] observe an increase in tissue oxygen partial pressure ( PO2 ) until cortical layer IV , Sakadžić et al . [58] and Devor et al . [58 , 61 , 62] report the highest PO2 in cortical layer I . The reason for the discrepancies are not yet resolved , but Lyons et al . suggest it might result from anesthesia effects . A further topological explanation for the results obtained in [61] could be a very coarse capillary grid in AL 1 which impedes the diffusion of oxygen . Based on our simulation results with a large feeding flow rate in AL 1 and comparably short transit times , a high tissue PO2 in AL 1 seems more plausible . However , our hypothesis is solely based on the results of blood flow simulations , which do not account for oxygen discharge from capillaries . Further measurements and simulations with oxygen discharge from capillaries are necessary to properly answer this question . We postulate that RBCs leaving the capillary bed deep in the cortex will be less saturated with oxygen than RBCs close to the surface . This is in line with the observations in [58] . Furthermore , the large feeding flow rates for the ALs close to the cortical surface suggest that up-regulation of flow might be less critical close to the cortical surface , because the level of highly-oxygenated blood supplied is very large and the neuronal energy demand is comparably low and constant . We hypothesize that up-regulation of flow is mainly relevant for deeper ALs to match the metabolic demand of the corresponding neuronal layer . This seems to be in line with the work of Tian et al . [6] who observes that the delay in vascular response to stimulation is smallest for deeper cortical layers . As previously mentioned , in the sensory cortex AL 2–3 overlap with cortical layer IV which has a high neuronal density and a higher and more fluctuating energy demand . One might speculate that the vasculature is designed to primarily support hemodynamic regulation at that depth . Another means to improve the oxygenation of the tissue is an increased OEF . As mentioned above homogenization in RBC flow is beneficial for the oxygen extraction [59] . However , during baseline it is well known that the flow in the microvasculature is very heterogeneous [4 , 10–13] , which is confirmed by our results . We postulate that flow homogenization is more relevant at deeper cortical levels , where the feeding flow rate is lower and the CTH is larger . This agrees with the decreased coefficient of variation of capillary transit times observed for cd > 200 μm due to activation [14] . Consequently , our results support the hypothesis that flow homogenization could be an effective mean to up-regulate the oxygen supply . Even if experimental studies on flow homogenization are currently mainly executed for the upper part of the cortex , we postulate that flow homogenization might be even more effective at deeper cortical levels , where the overall saturation of RBCs is expected to be lower , and hence a very effective discharge of oxygen is required . Based on our results several conclusions can be drawn: ( 1 ) The location of the largest pressure drop is a function of cortical depth and hence its impact on CBF increase is also depth dependent . ( 2 ) Laminar differences exist for all relevant flow characteristics , such as capillary transit time , feeding flow and RBC velocity . ( 3 ) In order to improve the understanding of the flow in MVNs it is crucial to consider the vascular topology and the flow and pressure distribution as one entity . Purely topological analysis might result in spurious interpretations and hence should be avoided . Further experimental and numerical studies will be needed to further investigate layer-specific effects on hemodynamic regulation , because averaging over the whole network might wash out layer-specific effects which are crucial to properly understand neurovascular coupling . | The brain consumes approximately 20% of the total oxygen used by the human body . An efficient and robust energy supply is essential for the brain’s functioning . The brain is able to up-regulate its oxygen supply in the proximity of neuronal activation . However , the details of the underlying vascular regulation mechanisms remain unknown . To improve the understanding of the blood flow patterns in the cortex we perform numerical simulations in realistic microvascular networks . In contrast to experimental measurements , numerical computations offer the advantage that the whole pressure and flow field is available for analysis . It is well established that the cerebral cortex is organized in laminar fashion and indeed our results reveal that the flow field in the capillary bed shows significant layer-specific differences . Those differences must be taken into account in future numerical and experimental works . Furthermore , it seems likely that multiple regulation mechanisms are playing hand in hand and that their impact differs over depth . | [
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"... | 2017 | Depth-dependent flow and pressure characteristics in cortical microvascular networks |
Iron is essential for many cellular processes , but can generate highly toxic hydroxyl radicals in the presence of oxygen . Therefore , intracellular iron accumulation must be tightly regulated , by balancing uptake with storage or export . Iron uptake in Leishmania is mediated by the coordinated action of two plasma membrane proteins , the ferric iron reductase LFR1 and the ferrous iron transporter LIT1 . However , how these parasites regulate their cytosolic iron concentration to prevent toxicity remains unknown . Here we characterize Leishmania Iron Regulator 1 ( LIR1 ) , an iron responsive protein with similarity to membrane transporters of the major facilitator superfamily ( MFS ) and plant nodulin-like proteins . LIR1 localizes on the plasma membrane of L . amazonensis promastigotes and intracellular amastigotes . After heterologous expression in Arabidopsis thaliana , LIR1 decreases the iron content of leaves and worsens the chlorotic phenotype of plants lacking the iron importer IRT1 . Consistent with a role in iron efflux , LIR1 deficiency does not affect iron uptake by L . amazonensis but significantly increases the amount of iron retained intracellularly in the parasites . LIR1 null parasites are more sensitive to iron toxicity and have drastically impaired infectivity , phenotypes that are reversed by LIR1 complementation . We conclude that LIR1 functions as a plasma membrane iron exporter with a critical role in maintaining iron homeostasis and promoting infectivity in L . amazonensis .
Leishmania spp are intracellular protozoan parasites that cause human leishmaniasis , a disease spectrum that can vary from self-healing cutaneous lesions to lethal visceralizing disease . Leishmania is endemic in about 90 countries throughout the world , and has been spreading from rural to urban areas in recent years [1–4] . Currently , an estimated 12 million people are infected with Leishmania and close to 1 billion people may be at risk ( WHO ) [5 , 6] . There is no established vaccine and the treatments available can be highly toxic , expensive and/or of limited effectiveness , making the identification of new drug targets an urgent need . Iron is a critical cofactor for many conserved metabolic pathways in cells . However , free iron can be cytotoxic , because of its ability to generate reactive hydroxyl radicals via the Fenton reaction [7 , 8] . Thus , iron uptake into cells must be balanced with mechanisms for iron sequestration , storage , and/or export . A typical cellular strategy for storage of intracellular iron is the formation of complexes within ferritin , a widely expressed cytosolic protein that binds and releases iron in a controlled fashion [9 , 10] . Iron is also an essential micronutrient for Leishmania , and restriction in iron availability is a demonstrated host defense mechanism against these parasites [11 , 12] . Previous studies showed that iron acquisition in Leishmania is mediated by LIT1 ( Leishmania Iron Transporter 1 ) and LFR1 ( Leishmania Ferric Reductase 1 ) , transmembrane proteins that have homology with plant IRT1 ( iron-regulated transporter 1 ) and plant FRO1 ( ferric oxidoreductase 1 ) , respectively [13 , 14] . LFR1 reduces Fe3+ to Fe2+ , the soluble form of iron that is translocated across the parasite’s plasma membrane by LIT1 . The Leishmania genome also encodes a frataxin-like protein that may function in iron storage inside the mitochondria [15] , but there are no genes encoding cytosolic proteins with similarity to ferritin . This raises an important question: How do these parasites prevent accumulation of free iron in the cytosol to avoid toxicity ? In addition to storage in association with a ferritin-like protein , yeast cells utilize the CCC1 membrane transporter to translocate iron from the cytosol into vacuoles [16] . In plants , sequestration of cytosolic iron in vacuoles is mediated by vacuolar iron transporters ( VITs ) that are homologous to CCC1 [17] . Plants also express nodulin-like membrane proteins , which share sequence similarity with VIT1 and yeast CCC1 transporters [18] . Nodulin-like proteins appear to be involved in the transmembrane transport of iron and other compounds [19] , but their precise functional role in plant iron metabolism remains to be determined . Given that the L . amazonensis ferrous iron importer LIT1 [13] and the ferric iron reductase LFR1 [14] have orthologs in plants [15] , we set out to investigate whether parasite nodulin-like proteins might also be involved in iron homeostasis . In this study we identified and characterized the Leishmania Iron Regulator 1 ( LIR1 ) , a plasma membrane protein with similarity to MFS ( Major Facilitator Superfamily ) membrane transporters [20–22] and that contains a nodulin-like domain . Our results indicate that L . amazonensis LIR1 functions in iron export , revealing a mechanism by which the parasites can avoid toxicity by preventing excess intracellular iron accumulation . In agreement with an important role in iron homeostasis , we also demonstrate that LIR1 is essential for L . amazonensis intracellular replication in macrophages and for the development of pathology in mice .
Analysis of the previously published whole-genome transcriptome profile of L . amazonensis genes modulated by iron deprivation [23] identified LmxM . 21 . 1580 as an iron-responsive gene . This gene , designated Leishmania Iron Regulator 1 ( LIR1 ) ( Genbank ID KY643495 ) , is conserved among all Leishmania species represented in genome databases . Potential orthologs were also found in Crithidia fasciculata ( TriTrypDB CFAC1_130025500 ) , Endotrypanum monterogeii ( TriTrypDB EMOLV88_210023200 ) , Leptomonas pyrrhocoris ( TriTrypDB LpyrH10_14_2060 ) , Leptomonas seymouri ( TriTrypDB Lsey_0232_0200 ) , Trypanosoma cruzi ( TriTrypDB TcCLB . 402857 . 10 ) and Trypanosoma brucei ( TriTrypDB Tb927 . 7 . 5940 ) [24] . LIR1 encodes a 661 amino acid protein with a predicted molecular mass of 73 kDa and 14 putative transmembrane domains ( Fig 1a ) . A 100% confidence alignment of LIR1 with a template for MFS general substrate transporters was obtained through 3D structure modeling using the Phyre2 software [25] ( Fig 1b ) . Conserved domain analysis ( NCBI Conserved Domains Database ) revealed domains similar to plant nodulin-like proteins [18 , 19] ( Bit Score 39 . 63; E-value: 1 . 31e-03 ) and MFS-type small solute membrane transporters [20–22] ( Bit Score 37 . 29; E-value: 9 . 98e-03 ) . Quantification of endogenous LIR1 mRNA revealed upregulation after promastigotes were cultured for 18–24 h in heme-depleted medium ( HD ) , heme-depleted medium containing the iron chelator deferoxamine ( HD+DFO ) or medium depleted in iron using Chelex ( ID ) ( Fig 1c , S1a Fig ) . Conversely , downregulation was observed after 4 days of culture in iron-supplemented medium ( Fig 1c , 1mM FeSO4 ) . No detectable upregulation above the already high levels observed for ectopically expressed LIR1 transcripts was observed after 18 h of culture in iron depleted medium ( HD+DFO ) , but a significant downregulation of ectopically expressed LIR1 transcripts also occurred after 4 days of culture in iron supplemented medium ( S1b Fig ) . However , the unusual polycystronic mode of gene transcription in trypanosomatids [26] does not allow direct transcript-protein extrapolations , because gene expression is regulated largely at the post-transcriptional level [27] . Thus , we used antibodies to quantify ectopically expressed ( GFP-tagged ) LIR1 proteins in L . amazonensis promastigotes exposed to changes in iron availability ( Fig 1d–1f ) . Remarkably , after 18 h of incubation in heme-depleted medium containing the iron chelator DFO ( HD+DFO ) , GFP-LIR1 protein levels were markedly decreased , an opposite effect to what was observed for the mRNA under the same conditions . Conversely , when the parasites were cultured for 4 days in medium supplemented with iron sulfate , there was a dose-dependent increase in the amount of GFP-LIR1 protein detected ( Fig 1d and 1f ) . This effect was specific for GFP-LIR1 , as iron depletion caused much smaller changes and iron supplementation caused no significant changes in ectopically expressed cytosolic EGFP ( Fig 1e and 1f ) . These LIR1 results add to previous evidence indicating a lack of correlation between transcript and protein levels in Leishmania [27] . Considering that LIR1 untranslated regions were not included in the GFP-LIR1 expression constructs , our results suggest the potential existence of mechanisms for iron-dependent regulation of LIR1 expression at the protein turn-over level . However , in the absence of a specific anti-LIR1 antibody ( which is challenging to generate for such a large and multiple membrane spanning domain protein ) , our current results do not rule out other regulatory mechanisms at the level of translation or mRNA stability . Immunofluorescence of L . amazonensis promastigotes ( insect life cycle stages ) expressing the plasmids p-LIR1-3xFlag ( Fig 2a and 2b ) and p-GFP-LIR1 ( Fig 2c ) revealed that both tagged forms of LIR1 ( 3xFlag on the C-terminus or GFP on the N-terminus ) are targeted to the parasite’s plasma membrane . Similar plasma membrane localization was detected in the mammalian intracellular amastigote stages , after mouse bone marrow macrophages ( BMM ) were infected with L . amazonensis expressing p-GFP-LIR1 ( Fig 2d ) or p-LIR1-3xFlag ( Fig 2e ) . The bright fluorescent circular structures observed in intracellular amastigotes , seen with both GFP and 3xFlag tags ( Fig 2d and 2e ) , likely reflect the parasite’s flagellar pocket , a membrane invagination that is continuous with the plasma membrane [28 , 29] . Thus , our findings identify LIR1 as a plasma membrane protein with similarity to MFS transmembrane transporters that is downregulated during iron deprivation and upregulated when the parasites are exposed to excess iron . This increase in protein expression under excess iron and decrease under low iron suggested a role for LIR1 in managing the size of the parasite’s intracellular iron pool . Given the sequence similarity of LIR1 with plant nodulin-like proteins , we investigated the molecular function of LIR1 in a heterologous system by generating transgenic Arabidopsis thaliana plants expressing LIR1 . As observed in L . amazonensis , LIR1-GFP fusion constructs were predominantly targeted to the plasma membrane in A . thaliana tissues , as shown in root cells ( Fig 3a ) and in leaf mesophyll protoplasts ( S2a Fig ) . Remarkably , when the total iron content of leaves in plants expressing LIR1 was quantified by inductively coupled plasma mass spectrometry ( ICP-MS ) , a marked decrease was observed in relation to wild type ( WT ) , reaching levels similar to what is observed in leaves of irt1-/- plants that lack the major iron uptake transporter IRT1 [30 , 31] ( Fig 3b ) . This result directly indicated a function for LIR1 in iron export . WT plants expressing LIR1 did not show the severe growth defect and chlorotic phenotype that is typical of the iron deficient irt1-/- A . thaliana mutants [30 , 31] ( S2b Fig ) , possibly as a result of compensatory mechanisms ( in addition to iron the IRT1 transporter also mediates the uptake of zinc , manganese and cobalt by plant roots [31] ) . To further address this issue and to directly determine whether LIR1 had an impact on the iron-deficiency phenotype of irt1-/- A . thaliana , we generated transgenic irt1-/- plant lines expressing LIR1 . These transgenic plants presented a markedly worsened chlorotic phenotype and had a more severe growth defect , when compared to the irt1-/- line not expressing LIR1 ( Fig 3c , top panels ) . Under normal growth conditions ICP-MS analysis did not detect a statistically significant reduction in the iron content of the irt1-/- lines expressing LIR1 , possibly due to the already critically low iron content of this line . However , when the iron supplement Sequestrene [31] was supplied at 0 . 5 g/L , a marked reduction in iron content was evident in irt1-/- lines expressing LIR1 , when compared to plants not expressing LIR1 ( Fig 3d ) . Confirming the link between these phenotypes and the regulation of iron homeostasis , addition of Sequestrene reversed the chlorotic and growth phenotypes of both strains ( Fig 3c , bottom panels ) . Thus , the results of these heterologous expression experiments in A . thaliana demonstrate a role for LIR1 in reducing the size of the intracellular iron pool by directly promoting iron export across the plasma membrane . To assess the functional role of LIR1 in L . amazonensis we generated heterozygote LIR1/lir1- ( SKO ) and homozygote null lir1-/lir1- ( KO ) clones by transfecting promastigotes with gene deletion constructs , followed by drug selection ( S3a Fig ) . To restore LIR1 expression , the LIR1 ORF sequence was stably integrated into the SSU rRNA locus of the KO mutant , yielding the add-back line lir1-/LIR1 ( AB ) ( S3b Fig ) . Independent SKO , KO and AB clones were isolated and analyzed in parallel . The loss of LIR1 , replacement of both LIR1 alleles and integration of LIR1 into the SSU rRNA locus were confirmed by PCR analysis ( S3c and S3d Fig ) . We directly assessed the role of LIR1 in iron transport by comparing the 55Fe uptake profile of WT and LIR1 KO mutants . Lack of LIR1 expression in the KO strain did not significantly change 55Fe uptake in relation to WT ( Fig 4a ) , reinforcing the conclusion that LIR1 does not function as an iron importer . To examine a potential iron-export phenotype , WT , LIR1 KO and AB cells under iron starvation were pulse-labeled with 55Fe for 90 min and then analyzed after specific chase periods for the amount of 55Fe retained ( Fig 4b ) . While the intracellular amount of 55Fe decreased progressively over time in WT parasites , this was not observed with LIR1 KO parasites , which showed a significant impairment in iron efflux . Importantly , recovery of this phenotype was observed with AB parasites after 24 h of chase , supporting the conclusion that LIR1 promotes iron efflux . We also quantified the total amount of parasite-associated iron by inductively coupled plasma mass spectrometry ( ICP-MS ) before ( promastigotes taken from a late log culture , washed and lysed immediately ) or after 18 h of incubation in fresh growth medium ( which is expected to contain higher iron levels ) . We found that WT Leishmania promastigotes responded to transfer to fresh media by decreasing their intracellular iron content within the 18 h period . Under the same conditions , no decrease in the total iron content of LIR1 KO parasites was observed , suggesting that loss of LIR1 impairs the parasites’ ability to regulate their total intracellular iron levels ( Fig 4c ) . The SKO line showed a decrease in iron content similar to WT , suggesting that one LIR1 allele was sufficient to reduce intracellular iron levels under the assay conditions . A statistically significant difference was not observed between the 0 and 18 h time points with the AB line in this assay ( Fig 4c ) , possibly due to abnormal regulation of the intracellular iron pool of parasites ectopically expressing LIR1 . A failure to fully restore WT phenotypes is a common occurrence when ectopically expressing genes in Leishmania , because expression levels cannot be tightly regulated [32–34] . Interestingly , however , reversal of the KO phenotype was observed with the AB line in 55Fe efflux assays ( Fig 4b ) , suggesting that LIR1 overexpression is still able to restore the dynamics of the cytoplasmic labile iron pool that is readily mobilized by plasma membrane transporters , but may have long term deleterious effects on the total iron content of cells ( detected by ICP-MS ) , which includes iron metabolically complexed to other molecules and stored inside various organelles . Collectively , these results further strengthen the evidence that LIR1 functions as a plasma membrane transporter that promotes iron export . Quantification of in vitro promastigote growth showed that LIR1 deficiency causes a marked delay on the parasites’ ability to initiate replication ( Fig 5a , S4b and S4c Fig ) . KO parasites showed a 3-day growth delay in relation to wild type ( WT ) , while SKO had an intermediate phenotype . Notably , addition of extra iron to the culture media in the form of 0 . 5 mM FeSO4 worsened the growth delay phenotype of the KO , without similarly affecting growth of the SKO and AB lines ( Fig 5b ) . Addition of 1 mM FeSO4 further worsened the KO growth delay , while causing a markedly smaller effect on the WT , SKO and AB lines ( Fig 5c ) . Interestingly , the mutant parasite strains were able to grow at rates similar to the WT strain after the several-day delay periods . This pattern suggests the existence of late-acting mechanisms that allow promastigotes to overcome iron sensitivity and replicate in liquid culture . A similar deleterious effect of iron supplementation on promastigote replication was seen in several independent experiments ( S4a Fig ) . These results suggest that the LIR1 transporter can protect Leishmania promastigotes from the toxic effects of excessive intracellular iron . Many membrane transporters that have iron as a substrate also translocate other transition metals , most commonly manganese and at a lesser extent zinc and copper [35] . In agreement with these findings , increasing the concentration of manganese in the culture medium also worsened the KO line growth delay phenotype without affecting WT promastigotes ( Fig 5d ) . A less pronounced but still detectable inhibitory effect on the replication of KO parasites was observed in the presence of elevated concentrations of zinc ( Fig 5e ) . The toxic effects of excess manganese and zinc on LIR1 KO were , however , significantly less pronounced than what was observed with iron ( Fig 5a–5c ) . In contrast , addition of the non-transition metal magnesium at similar concentrations had no effect on the WT or KO line growth pattern ( Fig 5f ) . Taken together , our results indicate that LIR1 functions as a plasma membrane transition metal transporter that can protect Leishmania from the toxic effects of high concentrations of iron , and of manganese and zinc to a smaller extent . Infection of mouse bone marrow macrophages ( BMM ) revealed that partial LIR1 deficiency ( SKO ) impairs the sustained intracellular replication that is observed with WT L . amazonensis , while complete deficiency ( KO ) leads to no replication and a strong reduction in the number of intracellular parasites over time ( Fig 6a ) . The metacyclic life cycle stages of L . amazonensis used to infect the BMM were purified after selective agglutination of promastigotes with the 3A . 1 mAb antibody [36] and tested in viability assays . These tests showed that LIR1 KO metacyclics were as viable as WT metacyclics prior to macrophage infection ( Fig 6b ) , and there were also no differences in the ability of WT or KO parasites to induce formation of the enlarged parasitophorous vacuoles ( PV ) that are typical of L . amazonensis [37] in macrophages ( Fig 6c ) . Thus , we conclude that the marked inability to survive and replicate intracellularly observed in LIR1 KO parasites is not related to metabolic defects in the metacyclic population used to initiate the infection . Rather , our results indicate the LIR1 expression is required for the parasites to survive and replicate as intracellular amastigotes within macrophage PVs . Strengthening this conclusion , the number of intracellular parasites of the genetically complemented AB line was significantly higher than the KO line at all time points subsequent to the initial 3 h ( Fig 6a ) . Similar results were observed in macrophage infection experiments performed with independent SKO , KO and AB clones ( S5a and S5b Fig ) . To determine the importance of LIR1 for the ability of L . amazonensis to generate cutaneous lesions in vivo , purified metacyclic forms were inoculated into footpads of C57BL/6 mice . As expected , all mice inoculated with WT parasites developed progressive cutaneous lesions within 3–4 weeks ( Fig 6d ) . In contrast , lesion development in mice injected with KO parasites was markedly reduced , with slight footpad swelling detected only between days 49 and 73 ( after which all mice were sacrificed because WT lesions reached the maximum size allowed by our animal welfare protocol ) . Inoculation with SKO and AB parasites led to intermediate-size lesions . Parasite load analysis [38] of cutaneous lesions extracted from the infected mice after 73 days revealed 106-fold less parasites in KO-infected mice and 103-fold less in SKO-infected mice , when compared to WT and AB ( Fig 6e ) . Notably , while lesions from mice infected with parasites lacking one LIR1 allele ( SKO ) showed intermediate parasite loads , full rescue of the WT phenotype was observed in LIR1 complemented parasites ( AB ) . Taken together with the results of our experiments following intracellular replication in macrophages ( Fig 6a , S5a and S5b Fig ) , these findings show that LIR1 deficiency prevents the intracellular replication of the vertebrate amastigote forms , not merely delaying their growth as observed with the insect promastigote stages ( Fig 5 ) . These findings identify LIR1 as a virulence factor that is required for the successful intracellular replication and cutaneous lesion formation in mammalian hosts by L . amazonensis .
Despite advances in our understanding of pathways of iron acquisition and metabolism in Leishmania [13 , 14 , 23 , 39–42] , how these parasites regulate their intracellular labile iron pool to prevent toxicity is still an open question . In this study we clarify this important issue by identifying and characterizing LIR1 , to our knowledge the first plasma membrane protein shown to mediate iron export and prevent intracellular iron accumulation in trypanosomatid parasites . First , we found that LIR1 encodes a predicted multi-pass plasma membrane protein with structural similarity to the MFS group of membrane transporters [20–22] . Second , we showed that expression of LIR1 is regulated by iron , with the protein accumulating in parasites exposed to excess iron and decreasing under iron depletion . Third , when LIR1 is heterologously expressed in Arabidopsis thaliana it is targeted to the plasma membrane and decreases the iron content of plant tissues . Finally , we also showed that LIR1 expression in L . amazonensis regulates the size of the intracellular iron pool , protects the parasites from iron toxicity , and is required for virulence . Collectively , our results indicate that LIR1 encodes a transmembrane MFS-type protein containing a plant-like nodulin domain that promotes iron export in Leishmania . Our results with A . thaliana expressing LIR1 shed light on the potential function of nodulin-like proteins in plants , which were previously linked to mechanisms of iron homeostasis but not directly shown to function as iron exporters [19] . Nodulin-like proteins have significant sequence homology with the plant and yeast vacuolar iron transporters AtVIT1 and ScCCC1 , respectively [18] . CCC1 is a membrane transporter that mediates vacuolar iron storage in yeast , protecting yeast cells from iron accumulation in the cytosol [16] . Here we uncovered a similar function but a different subcellular localization for LIR1 . While CCC1 is localized on the membrane of yeast vacuoles ( lysosome-equivalent organelles ) , LIR1 is predominantly targeted to the plasma membrane of both life cycle stages of the parasites , the insect promastigotes and the intracellular amastigotes responsible for mammalian infection . Taken together with the regulation of LIR1 protein expression by iron levels in the environment , our findings point to the existence in Leishmania of a unique mechanism for managing the intracellular iron pool . Instead of storing iron in the lumen of an intracellular compartment or coupled to cytosolic ferritin , as observed in yeast and other eukaryotes , Leishmania parasites may largely rely on directly exporting cytosolic iron to the extracellular environment through the plasma membrane . Interestingly , the protozoan parasites Plasmodium falciparum and Plasmodium berghei express a VIT1-like iron transporter that also functions as an iron detoxifier [43] , and proteomic studies revealed that Trypanosoma brucei expresses a putative VIT1 protein that is targeted to acidocalciosomes and required for parasite growth [44] . However , prior to our study very little additional information was available about the role that nodulin/VIT-like transporters might play in iron homeostasis in protozoan parasites , and their impact on virulence . The data presented here strongly suggests that the nodulin-like Leishmania protein LIR1 is directly involved in managing the intracellular iron pool and in preventing iron toxicity . Our findings provide , for the first time , an explanation for how Leishmania parasites can maintain iron homeostasis in the absence of ferritin-like cytosolic iron storage proteins . Interestingly , the strongest phenotypes we observed in LIR1-deficient L . amazonensis involved experiments initiated with metacyclic promastigotes , the infective form that is generated inside sand flies and is responsible for transmission of the infection to mammalian hosts . Our results suggest that excessive accumulation of intracellular iron may be particularly deleterious for metacyclic parasites undergoing reprogramming for differentiation into replicative forms . Previous studies from our group showed that iron import in Leishmania is mediated by LIT1 , a plasma membrane ferrous iron transporter [13] . LIT1 transcripts are upregulated in parasites grown in iron depleted media , a response also seen with the plasma membrane proteins LFR1 ( ferric iron reductase ) [14] and LHR1 ( heme transporter ) [45] . Interestingly , although the LIR1 mRNA is also upregulated by iron depletion , the opposite was observed at the protein level . This finding is consistent with recent reports that revealed a markedly low ( only 20–30% ) correlation between mRNA and protein levels in Leishmania , as the parasites underwent gene expression changes triggered by the environment . It is noteworthy that in mammalian cells and other higher eukaryotes , expression of genes involved in iron homeostasis is directly controlled by iron regulatory proteins ( IRPs ) that recognize iron responsive elements ( IRE ) on mRNAs [46 , 47] . In contrast , there is no evidence so far for the presence of IREs in Leishmania mRNAs . Thus , our results contribute to the emerging view that in the absence of a canonical IRE , regulation of iron importers and exporters may be coupled , opening up an interesting new area for future investigation . By identifying LIR1 as the first plasma membrane iron exporter in a trypanosomatid parasite , our findings add a critical missing element to the iron homeostasis machinery of this important group of human pathogens . Given the essential role played by LIR1 in L . amazonensis virulence , its localization on the parasite plasma membrane and the lack of human orthologs , our findings suggest that LIR1 could be a promising target for the future development of therapeutic drugs .
The L . amazonensis IFLA/BR/67/PH8 strain was provided by Dr . David Sacks ( Laboratory of Parasitic Diseases , NIAID , NIH ) . Promastigote forms were cultured in vitro at 26 °C in M199: medium 199 ( Gibco , Invitrogen ) pH 7 . 2 supplemented with 10% heat inactivated fetal bovine serum ( FBS ) , 40 mM Hepes , 0 . 1 mM adenine , 0 . 0001% biotin , 5 μg/ml hemin ( 25 mg/ml in 50% triethanolamine ) , 5 mM L-Glutamine and 5% penicillin-streptomycin . Heme-depleted medium was prepared similarly , omitting hemin addition and replacing regular FBS by heme-depleted FBS . Heme-depleted FBS was generated by treating heat inactivated FBS with 10 mM ascorbic acid for 16 h at room temperature , followed by verification of heme depletion by measuring the optical absorbance at 405 nm [48] , 3 rounds of dialysis in cold phosphate-buffered saline ( PBS ) and filter-sterilization . Iron-depleted FBS and medium were prepared as previously described [23] . Briefly , iron-depleted FBS was prepared treating 100 ml of heme-depleted FBS with 5 g of Chelex for 3–4 h , followed by filtration to remove Chelex and 4 rounds of dialysis in cold PBS . Iron-depleted medium was prepared similarly to regular M199 without addition of hemin and by replacing regular FBS with iron-depleted FBS . The media was stirred with 5 g/100 ml of Chelex for 1 h at room temperature and filter-sterilized . Ca , Cu , Mn , Mg and Zn ions were added back using the values previously determined by ICP-MS [23] . Promastigote growth curves were initiated with parasites taken from cultures in the stationary phase of growth and resuspended at the indicated densities in fresh growth media containing or not the supplemental metal salts . Total RNA was obtained using NucleoSpin RNA kit ( Macherey-Nagel GmbH & Co . KG ) following manufacturers’ instructions . cDNA was synthesized using SuperScript III Reverse Transcriptase ( Invitrogen ) . For a final reaction volume of 20 μl , 1 μg of total RNA mixed with 0 . 5 μg oligo ( dT ) 12-18 and 1 μl of dNTPs 10 mM was denatured at 65 °C for 5 min; after cooling , 1 μl of DTT 0 . 1 M , 4 μl of Buffer 5X and 200 U of Reverse Transcriptase were added to the reaction , followed by incubation at 50 °C for 60 min , inactivation at 70 °C for 15 min , and storage at -20 °C . A negative control containing all reaction components except the enzyme was included and analyzed by real-time PCR to exclude the possibility of DNA contamination in the RNA samples . For real-time PCR , 1/40 of the reverse transcription product was used as a template . The reactions were performed in a C1000 thermocycler fitted with a CFX96 real-time system ( Bio-Rad Laboratories ) with 300 nM of each corresponding primer pair and iQ SYBR Green Supermix ( Bio-Rad ) . The specific primers used were LIR1-RT-F and LIR1-RT-R for L . amazonensis LIR1 , UbH-RT-F and UbH-RT-R for ubiquitin hydrolase ( UbH ) , and EGFP-LIR1-RT-F and EGFP-LIR1-RT-R for ectopically expressed GFP-LIR1 quantification ( S1 Table ) . The PCR reaction consisted of an initial denaturation step of 95 °C for 3 min followed by 40 cycles of 15 s at 95 °C and 30 s at 60 °C . The target gene expression levels were quantified according to a standard curve prepared from a ten-fold serial dilution of a quantified and linearized plasmid containing the DNA segment to be amplified . For protein level determinations , total lysates of L . amazonensis expressing GFP-tagged LIR1 ( plasma membrane ) or EGFP ( cytosol ) were used . Briefly , for detection of GFP-tagged LIR1 , 5x107 parasites were lysed at room temperature in 100 μl of Thorner lysis buffer ( 50 mM Tris-HCl pH 6 . 8 , 8 M urea , 5% SDS , 0 . 1 mM EDTA , 0 . 01% bromophenol blue , 5% β-mercaptoethanol ) . For detection of cytosolic EGFP , 5x107 parasites were lysed in 100 μl of lysis buffer containing 1% Triton , 150 mM NaCl , 50 mM Tris-HCl pH 7 . 6 and a protease inhibitor cocktail ( Roche ) , lysates were clarified at 14 , 000 g for 15 min at 4°C , SDS sample buffer was added to the supernatant and samples were boiled for 5 min . 20 μg of each lysate sample were subjected to Western blot analysis using a rabbit polyclonal anti-GFP ( A-11122 , ThermoFisher Scientific ) and rabbit polyclonal anti-arginase antibodies [34] as loading control . Blots were developed using Clarity Western blot ECL substrate ( Bio-Rad ) and detected with a Fuji LAS-3000 Imaging System and the Image Reader LAS-3000 software ( Fuji ) . Digital quantifications of chemiluminescence were performed using NIH ImageJ 1 . 50i software . To generate parasites expressing LIR1 tagged with triple-Flag ( 3xFlag ) , the gene ORF was amplified using the primers LIR1-Flag-N and ORF-R for N-terminal fusion , and ORF-F and LIR1-Flag-C for C-terminal fusion ( S1 Table ) . The amplicons were purified and cloned into the Leishmania expression vector pXGHyg [49] generating the vectors p-3xFlag-LIR1 and p-LIR1-3xFlag . For generating parasites expressing LIR1 tagged with GFP , the gene ORF was amplified using the primers LIR1-GFP-N-F and LIR1-GFP-N-R for N-terminal fusion , and LIR1-GFP-C-F and LIR1-GFP-C-R for C-terminal ( S1 Table ) . The amplicons were purified and cloned into the BamHI site of the Leishmania expression vectors pXG-GFP2+ and pXG-GFP+ [49] , for GFP fusion at the N- ( p-GFP-LIR1 ) and C- ( p-LIR1-GFP ) terminal respectively . For generating parasites expressing cytosolic EGFP , we utilized the pXG-EGFP plasmid provided by Lucile Maria Floeter-Winter ( University of São Paulo ) as previously described [50] . All constructs were transfected by electroporation [51] . Isolated clones were selected in M199 containing 30 μg/ml Hygromycin for the 3x-Flag tagged constructs , or 20 μg/ml G418 for the GFP-LIR1 and EGFP constructs . The gene deletion constructs were based on the drug resistance cassette donor plasmids pCR-DRC and backbone plasmid pBB-CmR-ccdB ( courtesy of Phillip Yates ) [52] . LIR1 5’ and 3’ UTR flanking cassettes were obtained using the following primers containing SfiI restriction sites: 5’SfiI-A-F , 5’SfiI-B-R , 3’SfiI-C-F and 3’SfiI-D-R ( S1 Table ) . These 5’ and 3’ UTR amplicons were cloned into the backbone plasmid pBB-CmR-ccdB flanking the drug resistance cassettes from pCR-NEO and pCR-BSD . The linearized resulting constructs were transfected by electroporation in 2 independent rounds [51] . Single knockout ( SKO ) clones from the first electroporation round were selected in M199 containing 20 μg/ml Neomycin . Selected SKO clones were subjected to a second electroporation round with a distinct drug resistance cassette and then double knockouts ( KO ) clones were selected in M199 containing 20 μg/ml Neomycin plus 20 μg/ml Blasticidin . To generate complemented cell lines , selected double knockout clones were transfected with the linearized construct pIR1-LIR1 ( AB ) or the plasmid pXG-LIR1 ( AB pXG ) . These constructs were obtained cloning the LIR1 ORF into the pIR1SAT plasmid designed for integration into the SSU rRNA locus [51] or into the pXGHyg plasmid for LIR1 ectopic expression [48] . Add-back clones were selected in M199 containing 20 μg/ml Neomycin , 20 μg/ml Blasticidin and 50 μg/ml Nourseothricin ( AB ) or 30 μg/ml Hygromycin ( AB pX ) . To confirm replacement of the LIR1 ORF by the drug resistance cassettes or integration into the SSU rRNA locus , genomic DNA from the selected clones was extracted using the NucleoSpin Tissue kit ( Macherey-Nagel GmbH & Co . KG ) following manufacturers’ instructions . The resulting DNA samples were used as template in PCR amplification analyses ( S3 Fig ) . Promastigotes were fixed with 4% paraformaldehyde and attached to poly L-lysine coated slides ( multitest 8-well; MP Biomedicals ) . For immunofluorescence of intracellular amastigotes , coverslips with BMM infected as described below were used . The fixed cells were quenched with 50 mM NH4Cl for 1 h and permeabilized with PBS containing 0 . 1% Triton for 15 min , prior to blocking with PBS containing 5% horse serum and 1% bovine serum albumin ( BSA ) for 1 h at room temperature . For 3xFLAG tag detection , mouse anti-FLAG ( F1804 , Sigma ) was used as primary antibody ( 1:500 dilution in PBS-1% BSA ) for 1 h , followed by anti-mouse IgG AlexaFluor 488 ( 1:5000 dilution ) as secondary antibody . For Lamp-1 detection , fixed infected BMM were quenched with 50 mM NH4Cl for 1 h , blocked with PBS containing 3% BSA , permeabilized with PBS containing 0 . 15% saponin for 15 min , followed by incubation with anti-Lamp1 ( 1D4B ) ( Abcam ) diluted 1:100 in PBS followed by anti-rat IgG AlexaFluor 594 ( 1:1000 dilution ) as secondary antibody . All samples were incubated with 1 μg/ml DAPI for nuclear staining . Slides were mounted with ProLong Gold antifade reagent ( Invitrogen ) . Images were acquired through a Deltavision Elite Deconvolution microscope ( GE Healthcare ) and processed using Volocity Suite ( PerkinElmer ) . The LIR1 coding sequence was amplified with the primers ORF-F and ORF-R and cloned into the pCR/8/GW/TOPO vector ( Invitrogen ) . After sequence verification , the fragment was recombined into pEarleyGate 103 [53] to generate a LIR1-GFP fusion construct under the 35S promoter ( a constitutive promoter from Cauliflower Mosaic Virus ) . The construct was introduced into Arabidopsis thaliana wild type ( ecotype Ler ) and irt-1-1 mutants ( ecotype Wassilewskija ) [31] via Agrobacterium by floral dipping [54] . The irt1-1 mutant was kindly provided by Dr . Catherine Curie ( CNRS Montpellier ) . Plants were grown on Metromix soil ( Griffin ) under a 16 h light-8 h dark cycle at 25 °C . When plants were grown in soil , iron was supplied as Sequestrene ( Sequestrene 330 Fe Chelate , Basf ) water solution 0 . 5 g/L , equivalent to about 500 μM Fe-EDDHA ( Sigma Aldrich ) . When plants were grown on media plates , surface sterilized seeds were germinated on half-strength Murashige and Skoog medium containing 0 . 7% ( w/v ) phyto agar ( Research Products International ) . Iron was supplied as 50 μM NaFe-EDTA ( ethylenediaminetetraacetic acid ferric sodium salt , Sigma Aldrich ) in growth media . Mesophyll protoplasts of transgenic plants were prepared as previously described [55] . Imaging of protoplasts and whole roots of transgenic plants was carried out using a Leica SPX5 confocal microscope . The root cell membrane was stained with 10 μg/ml propidium iodide ( PI ) , and the protoplast membrane was stained with 20 μM FM4-64 ( Molecular Probes ) for 5 min . For uptake assays , mid to end-log phase promastigotes were washed once with OptiMEM ( Gibco ) and incubated for 20 min at 26 °C in OptiMEM contaning 50 μM of ascorbic acid to a final concentration of 1 . 25 x 108 parasites/ml . To initiate uptake 1 μM 55FeCl in 1 μM ascorbate ( 55Fe ascorbate ) was added to the cell suspension and samples were incubated at 26 °C or ice for various time intervals . At the end of the incubation period , 400 μl ( 5x107 cells ) were transferred to 1 . 5 ml tubes on ice containing 1 ml of quench buffer ( 0 . 1 M Tris HCl pH 7 . 4 , 0 . 1 M Succinate , 10 mM EDTA ) . The cells were collected , washed twice with quench buffer and once with HBSS , and lysed with 100 μl of 50 mM NaOH followed by addition of 100 μl 50 mM HCl . For efflux assays , mid to end-log phase promastigotes were incubated in heme-depleted medium plus 50 μM deferoxamine ( DFO ) . After 18 h , the cells were washed 3 times with HBSS ( Gibco ) and incubated for 20 min at 26 °C in HBSS containing 50 μM ascorbic acid to a final concentration of 1 . 25 x 108 parasites/ml . To initiate uptake 1 μM 55FeCl in 1 μM ascorbate ( 55Fe ascorbate ) was added to the cell suspension and samples were incubated at 26 °C or ice for 90 min . At the end of the uptake period cells were washed 3 times with cold HBSS . To start the chase period cells were transferred to HBSS containing 50 μM ascorbic acid and 100 μM of “cold” iron ( C6H8O7Fe . H3N—ammonium iron ( III ) citrate ) and incubated at 26 °C or ice for various time intervals . At the end of the incubation period 400 μl ( 5x107 cells ) were transferred to 1 . 5 ml tubes on ice , collected and lysed with 100 μl of 50 mM NaOH followed by addition of 100 μl 50 mM HCl . The radioactivity in the lysates was determined by liquid scintillation counting . 55Fe levels were normalized to the sample protein content , determined using a Pierce BCA protein assay kit ( Thermo Scientific ) . Inductively coupled plasma mass spectrometry ( ICP-MS ) analysis was performed as previously described [56] . Briefly , the concentrations of two Fe isotopes ( 56Fe , 57Fe ) ( μg ) were quantified using a final internal standard concentration of 50 μg/L Ga and normalized per gram of total protein content of digested promastigote cells or plant tissues . 108 L . amazonensis late log promastigotes were digested for 1 h in 100 μl of HNO3 70% . 100 mg of Arabidopsis thaliana leaves were digested with 400 μl of 50% HNO3/50% H2O2 overnight at 50 °C , after drying overnight at 60 °C . Lysates were diluted 10 fold into 1% nitric acid for the analysis . Two isotopes were measured for Fe ( 56Fe , 57Fe ) and Zn ( 64Zn , 66Zn ) . Each sample was subjected to two ( promastigote samples ) or three ( plant samples ) independent injections for the ICP-MS run . Mouse bone marrow macrophages ( BMM ) were prepared from C57BL/6 mice ( Jackson Laboratories ) as previously described [57] . A total of 106 BMMs per well were plated on glass coverslips in 6-well plates and incubated for 24 h at 37 °C 5% CO2 in BMM media: RPMI 1640 containing L-glutamine medium ( Gibco ) supplemented with 20% endotoxin-free FBS ( Gibco ) , 5% penicillin/streptomycin , 132 μg/ml Na pyruvate , 50 ng/ml human macrophage colony-stimulating factor ( M-CSF ) ( PeproTech ) . Infective metacyclic forms were purified from stationary phase promastigote cultures ( second to third day after entering stationary phase ) using the 3A . 1 monoclonal antibody as described [40] . Purified metacyclics were added at a ratio of 3 parasites per macrophage for 3 h at 34 °C . The cells were washed 3 times with PBS and fixed or incubated in BMM media to complete 24 , 48 , 72 and 96 h of infection . Coverslips were fixed in 4% paraformaldehyde and incubated with 1 μg/ml DAPI ( 4’ , 6-diamidino-2-phenylindole ) for 1 h , after permeabilization with 0 . 1% Triton X-100 for 10 min . The number of intracellular parasites was determined by counting the total macrophages and the total intracellular parasites per microscopic field ( Nikon E200 epifluorescence microscope ) . At least 200 host cells , in triplicate , were analyzed for each time point . Cell viability was assessed using AlamarBlue Cell Viability Reagent ( Invitrogen ) following the manufacturers’ instructions . Briefly , 20 μl of AlamarBlue was added to 1 , 2 and 4 x 106 purified metacyclics in 200 μl M199 . After 4 h fluorescence levels were determined using a fluorescence plate reader ( SpectraMax M5 , Molecular Devices ) at 550 nm excitation and 590 nm emission . Six-week-old female C57BL/6 mice ( Jackson Laboratories ) ( n = 5 per group ) were inoculated with 106 purified metacyclics from L . amazonensis WT , LIR1 SKO , KO and add-back ( AB ) in the left hind footpad in a volume of 0 . 05 ml . Lesion progression was monitored once a week by measuring the difference in thickness between the left and right hind footpads with a caliper ( Mitutoyo Corp . , Japan ) . The parasite load in the infected tissue was determined after 10 weeks in the infected tissue collected from footpad lesions of sacrificed mice by limiting dilution [38] . Data were analyzed by an unpaired two-tailed Student’s t test using GraphPad Prism software . The data meet the assumptions of the test . Variance is similar among compared groups . A result was considered significant at a p value < 0 . 05 . P values and the number of times each experiment was repeated are stated in the figure legends . No statistical method was used to predetermine sample size . All animal work was conducted in accordance with the guidelines provided by National Institutes of Health for housing and care of the laboratory animals and performed under protocol # R-14-79 approved by the University of Maryland College Park Institutional Animal Care and Use Committee on January 11 , 2018 . The University of Maryland at College Park is an AAALAC-accredited institution . | Leishmaniasis is a human infectious disease that is endemic in many tropical and subtropical areas of the world . It is caused by transmission of the protozoan parasite Leishmania through bites of infected sand flies . The symptoms of leishmaniasis range from disfiguring skin lesions to potentially deadly visceralizing disease , and close to 1 billion people live in areas that place them at risk of infection . There is no vaccine available and the drugs currently used to treat this disease are highly toxic and/or expensive , with parasite resistance to these drugs also on the rise . Iron is an essential micronutrient for Leishmania , and the parasite’s ability to balance their intracellular iron levels is crucial for their survival and replication inside host cells . Previous studies identified proteins involved in iron uptake that are essential for Leishmania infectivity . In this study we identify LIR1 , a protein that mediates iron export and therefore prevents iron from accumulating to toxic levels inside the parasites . Absence of LIR1 increases the sensitivity of Leishmania to iron toxicity and abolishes parasite infectivity . Given the critical role of LIR1 in iron homeostasis and its importance for parasite virulence , LIR1 is a promising new target for leishmaniasis therapeutic intervention . | [
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"o... | 2018 | A MFS-like plasma membrane transporter required for Leishmania virulence protects the parasites from iron toxicity |
The stringent response is initiated by rapid ( p ) ppGpp synthesis , which leads to a profound reprogramming of gene expression in most bacteria . The stringent phenotype seems to be species specific and may be mediated by fundamentally different molecular mechanisms . In Staphylococcus aureus , ( p ) ppGpp synthesis upon amino acid deprivation is achieved through the synthase domain of the bifunctional enzyme RSH ( RelA/SpoT homolog ) . In several firmicutes , a direct link between stringent response and the CodY regulon was proposed . Wild-type strain HG001 , rshSyn , codY and rshSyn , codY double mutants were analyzed by transcriptome analysis to delineate different consequences of RSH-dependent ( p ) ppGpp synthesis after induction of the stringent response by amino-acid deprivation . Under these conditions genes coding for major components of the protein synthesis machinery and nucleotide metabolism were down-regulated only in rsh positive strains . Genes which became activated upon ( p ) ppGpp induction are mostly regulated indirectly via de-repression of the GTP-responsive repressor CodY . Only seven genes , including those coding for the cytotoxic phenol-soluble modulins ( PSMs ) , were found to be up-regulated via RSH independently of CodY . qtRT-PCR analyses of hallmark genes of the stringent response indicate that an RSH activating stringent condition is induced after uptake of S . aureus in human polymorphonuclear neutrophils ( PMNs ) . The RSH activity in turn is crucial for intracellular expression of psms . Accordingly , rshSyn and rshSyn , codY mutants were less able to survive after phagocytosis similar to psm mutants . Intraphagosomal induction of psmα1-4 and/or psmβ1 , 2 could complement the survival of the rshSyn mutant . Thus , an active RSH synthase is required for intracellular psm expression which contributes to survival after phagocytosis .
In most bacteria , nutrient limitations provoke the so-called stringent response , which is initiated by the rapid synthesis of the alarmones pppGpp and/or ppGpp , here referred to as ( p ) ppGpp . Under stringent conditions , ( p ) ppGpp results in the shut-down of proliferation-related activities , including the transcriptional repression of genes coding for major components of the protein synthesis apparatus ( rRNA , ribosomal proteins and translation factors ) as well as the inhibition of replication [1] , [2] , [3] . Typically genes that are presumed to be important for maintenance and stress-defence are activated under stringent conditions . However , the stringent phenotype resulting from ( p ) ppGpp synthesis seems to be bacteria species specific and may be mediated by fundamentally different molecular mechanisms [3] . The molecular mechanisms leading to the profound reprogramming of the bacterial cellular machinery under stringent conditions were mostly studied in Escherichia coli . Here , ( p ) ppGpp can be synthesized by either one of the two homologous enzymes: RelA and SpoT . The RelA-synthase is activated by sensing uncharged tRNAs that are bound to the ribosome . SpoT is a bifunctional enzyme that not only produces ( p ) ppGpp in response to diverse signals but also contains a ( p ) ppGpp hydrolase domain important for ( p ) ppGpp turnover . In E . coli , ( p ) ppGpp binds , with the help of the DksA protein , directly to the RNA polymerase ( RNAP ) . However , even in this model organism , there is still much debate concerning how ( p ) ppGpp eventually leads to different promoter activities , how ( p ) ppGpp influences the stability of open complex formation at the initial phase of transcription and which of the promoters are indirectly regulated via secondary regulatory circuits such as alternative sigma factors or other transcription factors [1] . In other organisms , such as the gram-positive Bacillus subtilis , ( p ) ppGpp probably does not interact with the RNAP , and no DksA homologue is present . Here ( p ) ppGpp has been proposed to affect promoter activities only indirectly via changes of the intracellular nucleotide pool [4] , [5] , [6] . In this model , the nature of the initiation nucleotide ( iNTP ) determines whether genes are under positive or negative stringent response [4] , [5] , [7] , [8] . ( p ) ppGpp synthesis is usually accompanied by a decrease in intracellular GTP concentration . rRNA promoters in B . subtilis initiate with GTP and a change of this base at position +1 results in a loss of regulation by ( p ) ppGpp and GTP . Furthermore , GTP can act as a co-factor for the repressor CodY , and thus the lower GTP levels imposed by the stringent response result in the de-repression of CodY target genes at least in some firmicutes , e . g . , B . subtilis [9] or Listeria monocytogenes [10] . In most firmicutes , three genes coding for putative ( p ) ppGpp synthases are present . The bifunctional RSH ( RelA/SpoT homologue ) enzymes are typically composed of a C-terminal sensing domain and an N-terminal enzymatic domain with hydrolase and synthase functions . RelQ and RelP ( also named SAS1 and SAS2 , for single small alarmone synthase ) are small proteins with only a putative ( p ) ppGpp synthase domain [11] , [12] . Little is known about the stringent response in the human pathogen Staphylococcus aureus , most likely because of the essentiality of the major ( p ) ppGpp synthase/hydrolase enzyme RSH [13] , [14] . Previously , we have shown that , at least under nutrient rich conditions , mutants defective only in the synthase domain of RSH ( rshSyn ) are not impaired in growth [13] . Furthermore , RSH is the only enzyme responsible for ( p ) ppGpp synthesis in response to amino acid starvation triggered by leucine/valine deprivation or mupirocin treatment . Preliminary characterisation of the rshSyn mutant revealed that part of its phenotype mainly the regulation of genes involved in amino-acid metabolism can be explained by the ( p ) ppGpp induced de-repression of the CodY regulon . CodY of S . aureus was previously shown to be a major regulator of virulence gene expression [15] , [16] . Thus , the CodY regulon seems to be an integral part of the stringent response in S . aureus linking metabolic circuits and virulence . However , whether , and to what extent , other direct or indirect regulatory circuits are involved in RSH mediated stringent response is unclear . A CodY independent contribution of the stringent response to virulence could , so far , not be indicated . However , for many other pathogenic bacteria , a contribution of ( p ) ppGpp to bacterial virulence could be shown [17] . In particular , for many intracellular bacteria , ( p ) ppGpp is essential to survive and replicate in diverse host cells , i . e . , epithelial and endothelial cell types and professional phagocytes . Here , we delineate three ( category I–III ) main consequences of RSH-dependent stringent response in S . aureus . ( I ) : Similar to other organisms , a severe down-regulation of the protein synthesis machinery was observed , and thus , the inhibitory effects of ( p ) ppGpp on gene expression seem to be highly conserved in bacterial species . ( II ) : In contrast , genes that are activated upon ( p ) ppGpp induction are highly species specific . In S . aureus , they are mostly regulated indirectly via the de-repression of CodY . ( III ) : Interestingly , seven genes , including those coding for the toxic phenol-soluble modulins ( PSMs ) , were found to be up-regulated independently of CodY . We demonstrate that a stringent response is induced after uptake of wild-type bacteria in human neutrophils . Moreover , RSH activity is required for psmα1-4 and psmβ1-2 expression in neutrophils which in turn promotes survival after phagocytosis .
S . aureus is able to mount a stringent response upon amino acid starvation , which is characterized by the generation of ( p ) ppGpp [18] , [19] . However , little is known about the impact of ( p ) ppGpp synthesis on global physiological processes in S . aureus . Mupirocin treatment , an antimicrobial agent that inhibits the bacterial isoleucyl tRNA synthetase and therefore mimics isoleucine starvation , results in profound reprogramming of gene expression [20] , [21] . Parts of these effects are mediated by ( p ) ppGpp . However , at least some of them were also observed in an RSH-mutant , which is devoid of ( p ) ppGpp synthesis after mupirocin treatment [13] . Here , we aimed to delineate the impact of ( p ) ppGpp synthesis induced by amino acid starvation on gene expression in S . aureus under defined nutrient limitation rather than after the addition of inhibitors such as mupirocin . Previously we could show that transferring S . aureus into a chemical defined medium ( CDM ) lacking the two branched-chain amino acids leucine and valine results in growth inhibition [13] . A similar experimental setup was chosen here for a further in-depth analysis including transcriptional profiling by microarray: Bacteria were grown to mid-exponential growth phase in complete CDM , filtered and shifted into a medium lacking leucine and valine ( −leu/val ) ( Fig . 1A , open arrow ) . After 30 minutes of incubation in CDM −leu/val the bacteria were harvested for RNA purification ( Fig . 1A , filled arrow ) . At this time all strains showed a slight growth inhibition compared to bacteria grown in complete CDM , which is accompanied by a clear induction of the stringent response indicated by RSH dependent ( p ) ppGpp synthesis and reduction of the GTP pool [13] . The rshSyn mutant showed no accumulation of ( p ) ppGpp under these conditions which indicates that a contribution of the two putative ( p ) ppGpp synthases RelP and RelQ is negligible . To analyze the effects mediated by ( p ) ppGpp synthesis we compared the transcriptional profile of wild-type strain HG001 with that of the rshSyn mutant under the indicated stringent conditions . Previously a close link between the stringent response and the activity of the repressor CodY was demonstrated in different firmicutes [10] , [13] , [22] , [23] . Thus , to delineate which and how many ( p ) ppGpp regulated genes are influenced through CodY we also analyzed the RSH mediated stringent response in codY-negative S . aureus . In accordance to previous results [13] we could confirm by northern blot analysis that under the selected conditions of leucine/valine starvation the wild-type strain showed a significant repression of genes of the translational apparatus , such as rpsB ( ribosomal protein S2 ) , infB ( translation initiation factor B ) and tsf ( translation stable factor ) , whereas no repression occurred in the rshSyn mutant ( data not shown ) . By contrast , typical CodY target genes like brnQ1 coding for an amino acid transporter were induced in the wild-type strain ( Fig . 1B ) . The low expression of brnQ1 in the rshSyn mutant however , could be restored by additional mutation of codY , indicating that the rshSyn mutation affects brnQ1 transcription through CodY ( Fig . 1B ) . To analyze whether this observation is due to a general response to amino acid limitation , we induced serine starvation by addition of serine hydroxamate ( SHX ) . The same transcriptional pattern was observed when compared to conditions of leucine/valine starvation ( −leu/val ) ( Fig . 1B ) . Based on the results of the northern blot hybridizations , we performed microarray analysis of wild-type S . aureus HG001 , rshSyn , codY and rshSyn , codY double mutants after leucine/valine depletion ( Fig . 1A ) . Three major categories ( I–III ) of stringently regulated genes were observed: I ) genes that are negatively regulated by ( p ) ppGpp independent of CodY . II ) genes that are positively influenced by ( p ) ppGpp through CodY de-repression and III ) genes positively influenced by ( p ) ppGpp independent of CodY . Microarray analysis revealed that 102 genes were significantly ( p-value cut-off , 0 . 05 ) down-regulated in the wild-type compared to the rshSyn mutant in the codY positive ( WT<rshSyn ) as well as in the codY negative background ( codY<rshSyn , codY ) ( Fig . 2A , overlap blue Venn diagram ) . This indicates that these genes are negatively regulated by ( p ) ppGpp independent of CodY . Since in total 161 genes were significantly down-regulated in the codY positive background , we also verified the 59 missing genes in the codY negative background . All of these genes appeared also to be down-regulated , although the difference did not reach the significance level . Most of these CodY-independent negatively regulated genes are hallmark genes of the stringent response in other bacteria [24] , [25] , [26] . They are mostly involved in the translation process ( Fig . 2B ) , such as coding for ribosomal proteins ( rps , rpl ) , for translation initiation factor ( infB ) and translation elongation factor ( tuf ) ( Fig . 2C ) . The rRNA processing machinery is also influenced since genes coding for ribonuclease P ( rnpA ) and rimM ( coding for a processing protein ) are repressed in an RSH-dependent manner ( Fig . 2C ) . In addition , genes like DNA helicases ( dnaB , C , D ) , part of the so called “replicon” , are negatively influenced by ( p ) ppGpp , and genes of the recombination/repair system ( ruvAB and dinP ) were also repressed under amino acid starvation due to ( p ) ppGpp ( Fig . 2B , C ) . In accordance with published data from E . coli and B . subtilis [24] , [25] , genes of other physiological processes that are typical for dividing cells ( nucleotide , lipid and coenzyme biosynthesis and transport , inorganic ion transport and protein modification ) are also part of the negative stringent response in S . aureus ( Fig . 2B , C ) . In contrast to B . subtilis [24] , E . coli [25] , or S . pneumoniae [26] , genes involved in cell division and cell wall biosynthesis were not found to be significantly influenced by the stringent response in S . aureus . However , we can not exclude that such genes are affected at later time points . We aimed to obtain a comprehensive overview of genes that are part of the predicted regulatory overlap between stringent response and CodY repression . Under stringent conditions most of the up-regulated genes were expressed only in the codY- positive background ( Fig . 2A ) . An additional introduction of a codY mutation into this analysis ( codY vs . rshSyn , codY ) abrogated the up-regulation of these genes ( Fig . 2C ) . Thus , under amino acid deprivation many genes are de-repressed in the wild-type bacteria ( WT>rshSyn ) through the relief of CodY repression , but stay constitutively repressed via CodY in the rshSyn mutant . These genes are part of the recently described CodY regulon [15] , [16] mainly involved in amino acid metabolism and transport ( Fig . 2B ) . Accordingly , most of them possess CodY binding motifs as described elsewhere [16] and as indicated in Fig . 2C ( three asterisks ) . It was shown previously that CodY represses also several virulence genes in part via inhibition of the quorum sensing system agr . Of note , none of these codY influenced virulence genes were found to be significantly down-regulated in the rshSyn mutants . Next , we investigated if there are genes activated by ( p ) ppGpp with no contribution of CodY . Microarray analysis revealed that only seven genes were expressed significantly lower in the rshSyn mutants in both , a codY-positive ( codY+ ) and codY-negative background ( codY− ) ( Fig . 2A , table 1 ) . One gene coding for a putative ribosome-associated protein Y was described in E . coli to bind to the small ribosomal subunit and to stabilize ribosomes against dissociation when bacteria experience environmental stress [27] . Also traP was expressed significantly lower in the rshSyn mutants . The function of TraP remains unknown since a proposed involvement of this protein in the activation of the agr system was recently disproved [28] , [29] , [30] . Surprisingly , two genes , part of the staphylococcal defence mechanism , coding for β1 and β2 phenol-soluble modulins ( psm β1/β2 ) were transcribed significantly lower in both rshSyn mutants . This result was of special interest because no other obvious virulence gene appeared to be part of the stringent response in S . aureus . The cytolytic activity of β-type PSMs was described to be minor , and their role in virulence is less pronounced compared with α-type PSMs [31] . Since no probes for α-type PSMs are present on the microarray chip , we performed northern blot hybridisation to analyze the RSH-dependent expression of these important molecules ( Fig . 3 ) . To exclude strain specific effects , rshSyn mutants of the prototypic S . aureus strain Newman were also included in the analysis . After leu/val starvation , there is no or very little , α- and β-type psm transcription detectable in the rshSyn mutants of strain HG001 and strain Newman ( Fig . 3A ) in contrast to the wild-type strain , which shows strong induction of both psm classes ( Fig . 3B ) . Introducing full-length rsh chromosomally into the rshSyn mutant strains could restore their deficiencies to induce psms expression ( Fig . 3A ) . An involvement of CodY could be excluded since the rshSyn , codY double mutant shows the same low transcription of psms as the rshSyn single mutant . Queck et al . [32] could show that psm expression is directly regulated via binding of the response regulator AgrA to the psm promoter region . Therefore , we analyzed whether agrA transcription is altered under the conditions tested . No significant transcriptional differences were detectable comparing wild-type strain and the corresponding mutants under leu/val deprivation ( Fig . 3A/B ) . The response regulator AgrA also directly activates the transcription of the divergently transcribed regulatory RNAIII which in turn results in down-stream regulatory effects on several virulence genes . In the microarray analysis , no significant difference in RNAIII or other prototypic RNAIII target genes such as hla or spa were observed . To exclude possible AgrA defects , we screened the mutants for altered haemolytic activity [29] . No haemolytic deficiencies could be detected in the mutant strains ( data not shown ) . Therefore , an AgrA defect in the rshSyn mutants can be excluded . Nonetheless agr mutants exhibit no psm transcriptions under leu/val deprivation ( Fig . 3A ) , supporting that agr activity is still essential for psm expression under stringent conditions . However , RSH dependent induction of psmα1-4 and psmβ1 , 2 under stringent conditions is not mediated by agr activation . Aside from the requirement of functional agr , little is known about psm regulation in S . aureus . The mechanism by which stringent response leads to increased transcription of certain genes is much under debate . In B . subtilis , ( p ) ppGpp does not appear to interact directly with RNA polymerase ( RNAP ) [5] . The nature of the iNTP during transcription was proposed to determine whether genes are under positive or negative stringent response . In this model , positive stringent controlled genes of B . subtilis are characterized by iATP , and these genes are presumably activated because of an increased ATP pool [4] . Previously , the transcriptional starting points of the α- and ß-psms were identified as an adenine ribonucleotide [32] . To analyze whether induction of phenol-soluble modulins in the wild-type strain correlates with an increased ATP pool , the intracellular ATP concentration was measured ( Fig . 4 ) . A significant increase of the intracellular ATP pool was detectable upon amino acid deprivation in all strains . However , no significant difference was found between the strains analyzed ( Fig . 4 ) . Thus , the ATP levels cannot explain the observed differences in psm expression between wild- type and rshSyn mutant . Since α-type PSMs are strongly involved in the survival of S . aureus upon PMN treatment [31] , [33] , we analyzed whether there is an association between phagocytosis and the RSH-dependent stringent response . Comparison of published data revealed that the transcription pattern during neutrophil phagocytosis ( Voyich et al . , 2005 ) is similar to that observed after amino acid starvation and/or mupirocin treatment [13] , [20] , [21] , namely down-regulation of the translational machinery and de-repression of CodY regulated amino acid transporters and biosynthesis genes . Hence , we hypothesized that phagocytosis may induce an RSH-dependent stringent response , similar to the depletion of amino acids . Under these conditions , the ( p ) ppGpp accumulation should result in increased PSMs synthesis . Thus , an rshSyn mutant , unable to transcribe psms , might be more sensitive to phagosomal killing . Indeed , the PMN bactericidal killing assay revealed that the rshSyn mutant is significantly less able to survive after phagocytosis compared to the wild-type strains ( Fig . 5A ) . This effect could be reversed by the introduction of full-length rsh into the chromosome of the rshSyn mutants . A comparison of the two strains ( HG001 and Newman ) with their respective mutant derivatives revealed similar results . Also an assumed contribution of relP and relQ could be excluded , since a relP/Q double mutant showed no decreased survival phenotype compared to the wild-type strain ( data not shown ) . To further analyze whether reduced intracellular psm expression solely accounted for the rshSyn defect in survival , we constructed a psmα1-4 , psmβ1 , 2 double mutant and an agr mutant , known to be defective in psm expression . The phenotype of the psmα , psmβ double mutant and the agr mutant closely resemble that of the rshSyn mutant concerning intracellular survival after phagocytosis ( Fig . 5B ) . Of note , there were no significant differences between the psmα , psmβ double and the rshSyn , psmα , psmβ triple mutant , as well as between the agr single and the rshSyn , agr double mutant , indicating that there are no additive effects of these mutations . We speculate that survival of phagocytosis is mediated by intracellular psm expression mediated by RSH dependent ( p ) ppGpp synthesis . To address this assumption , we used a plasmid , in which psmα1-4 and psmβ1 , 2 were cloned behind a tetracycline inducible promoter , to induce psmα or psmβ expression in the rshSyn mutant after phagosomal uptake . The intracellular induction of psmα and psmβ could significantly complement the reduced survival of the rshSyn mutant ( Fig . 5C ) . Interestingly , the survival of the rshSyn , agr double mutant was not complementable , neither by psmα nor by psmβ expression . We also performed PMN lysis assays by measuring the amount of released lactate dehydrogenase ( LDH ) . Accordingly the mutants which are defective in psms expression were shown to be less toxic compared to the wild type strain ( Fig . 5D ) . These results indicate that the RSH-mediated stringent response in S . aureus plays a major role in survival PMN phagocytosis most probably through regulation of intracellular psm expression . To analyze whether an RSH-dependent stringent response is induced during phagocytosis , we performed quantitative RT-PCRs from bacterial RNA obtained after 60 and 90 minutes of phagocytosis . At this stage , typically all of the bacteria are internalized [34] . We analyzed transcripts of typical genes of each of the three regulatory categories relative to the constitutive gyrB transcript ( Fig . 6 ) . For category I , the transcripts of rpsB , coding for ribosomal protein S2 , and infB , coding for initiation factor 2 were chosen . As expected , the rpsB and infB transcription is significantly lower in the wild-type and complemented strain than in the rshSyn mutants ( rshSyn single and rshSyn , codY double mutant ) ( Fig . 6 ) . In contrast , ilvC transcription ( category II gene ) is significantly higher in the wild-type compared to the rshSyn mutant . Here , comparable to results of the microarray analysis , an additional codY mutation in the rshSyn mutant could restore ilvC transcription . For category III , psmα1-4 and psmβ1 , 2 transcripts were analyzed . The wild- type and the complemented rshSyn strain showed significantly higher transcription compared to rshSyn mutants after incubation for 60 or 90 min with phagocytes . These results are consistent with the assumption that an RSH-mediated stringent response is induced after phagocytosis in wild-type bacteria . Of note , low expression of psms within the PMNs was also observed in the rshSyn , codY double mutant , indicating that intracellular psm regulation occurs independently of CodY . One may speculate that ( p ) ppGpp affect somehow the activity of the response regulator AgrA in the phagolysosomes thereby activating psm expression . Thus , we analyzed the intracellular expression of the prototypic AgrA target transcript RNAIII . However , no significant alteration of RNAIII transcription could be detected in the rshSyn mutants after 60 and 90 minutes of incubation ( Fig . 6 ) . In fact , the rshSyn , codY double mutant showed a slight increase of the RNAIII transcription compared to wild-type strain , which is in line with published data showing that agr transcription is slightly repressed by CodY [15] , [35] . These results indicate that stringent response is induced during phagocytosis which is required for psm expression . The reduced transcription of psmα1-4 in the rshSyn mutant and rshSyn , codY double mutant after phagocytosis is clearly not caused by diminished AgrA activity .
To adapt to changing environmental conditions , bacteria rely on sensory and regulatory systems to modulate complex physiological processes . The stringent response is a highly conserved regulatory mechanism that is provoked by nutrient limitation . It is effective in most bacteria and is mediated by the rapid synthesis of the alarmones ppGpp or pppGpp . Previously , it was shown that , in S . aureus , the RSH enzyme alone is responsible for ( p ) ppGpp accumulation upon amino acid deprivation [13] . Here , we characterized the stringent response of S . aureus in a more comprehensive way . So far , no microarray studies , in which ( p ) ppGpp synthase mutants were compared with wild-type strains under stringent conditions , are available for S . aureus . For other bacteria only a few microarrays of this type were published [24] , [25] , [26] , [36] , [37] . We identified 161 genes that were significantly repressed via RSH . Most of these genes are hallmarks of the stringent response also appearing in other bacteria that have been analyzed . This conserved “core-regulon” mainly encompasses genes of the translational machinery , including initiation and elongation factors . Furthermore , genes coding enzymes of physiological processes used by dividing cells , like biosynthesis and nucleotide transport , are typically under negative stringent response . Thus , negative regulation by ( p ) ppGpp seems to be an evolutionarily conserved mechanism . However , the molecular mechanism by which ( p ) ppGpp leads to the inhibition of these genes remains mostly unclear but seems to be organism dependent [4] , [5] , [38] , [39] . For firmicutes it was proposed that genes starting with an iGTP are repressed due to the lowering of the GTP pool [4] . We have shown previously that also in S . aureus stringent condition lead to lowering of the GTP level [13] . We have mapped the transcriptional start site of two rRNA operons of S . aureus ( data not shown ) and could confirm that the primary promoters initiate with iGTP which is in line with the mechanism proposed by Krasny et al . , 2008 [4] . Induction of the stringent response also leads to the activation of genes proposed to be necessary for survival and maintenance . For E . coli , it was recently shown that most genes that are positively influenced during the stringent response are , depending on the ( p ) ppGpp concentration , either part of the Lrp ( transcriptional regulator ) or RpoS ( alternative sigma factor ) regulon [40] . So far , there is little indication that alternative sigma factors are involved in the stringent response in gram-positive bacteria . Instead in S . aureus , most of the genes that are less expressed in the rshSyn mutant compared with the wild-type strain are part of the previously described CodY regulon [15] , [16] . For these genes , introduction of a codY mutation into the rshSyn mutant leads to an expression pattern that is similar to that of the wild-type strain . Thus , these genes are de-repressed upon the stringent response . An obvious link between the stringent response and CodY is the GTP pool . Amino acid deprivation leads to a lowering of the GTP pool [13] , which in turn may inactivate the CodY repressor . A similar link between the stringent response and CodY was also shown for Listeria monocytogenes [10] and B . subtilis [24] . In contrast , in Streptococci , CodY and the stringent response seem to act independently of each other [23] , [41] . This discrepancy is most likely due to species specific differences in GTP affinity of CodY [42] . In lactococci and streptococci branched-chain amino acids ( e . g . isoleucine ) , act as the only known ligand that mediates the repressive function of CodY . Notably , not all genes of the known CodY regulon seem to be affected under the induced stringent condition , analyzed here . Interestingly , virulence genes like the capsular gene cluster or the agr operon , which were found to be repressed via CodY [15] , [16] , did not appear to be affected during the stringent response . One explanation might be that the deactivation of the CodY repressor in the wild-type strain due to amino acid limitation is not as effective as knocking out the complete codY gene . Alternatively , the different CodY target genes may differ with regard to their sensitivity to CodY activity . One may assume that some of the CodY target genes are still repressed even under low GTP conditions as long as the primary CodY ligand isoleucine is present . This assumption is inline with recent findings that in B . subtilis CodY targets are differentially sensitive to alteration in the GTP pool: the ilv promoters but not the bcaP promoter was derepressed in a mutant not able to synthesize GTP [43] . Only seven genes were positively regulated under the stringent response independently of CodY , including those coding for the cytotoxic phenol-soluble modulins ( PSMs ) . So far psm transcription was shown to be directly activated via the response regulator AgrA [32] . We could show that AgrA is still essential for the stringent controlled psmα1-4 and psmβ1 , 2 transcription , since no psms were detectable in an agr mutant strain . However , the induction appears not to be due to altered agrA activity , since agrA expression was not found to be affected during the stringent response . Also after phagocytosis only psm transcripts but not the Agr effector molecule RNAIII are diminished in the rshSyn mutants . How ( p ) ppGpp regulates the transcription of PSMs remains unknown . Additional regulatory elements upstream of the promoter region of psm genes [32] could possibly take part in the ( p ) ppGpp regulation , presumably mediated by unknown factor ( s ) . In our microarray analysis , no apparent regulatory systems appeared to be affected , and thus , no candidate molecule that may indirectly be involved in ( p ) ppGpp dependent activation could be identified . Small molecules like ( p ) ppGpp or GTP may interact directly with proteins altering their enzymatic activity or binding affinities to DNA similar to the proposed GTP-CodY interaction . One may speculate that such an interaction may also alter the activity of other regulatory molecules such as the transcriptional regulator AgrA ( Fig . 7 ) . Alternatively , it was postulated that under stringent conditions , the iNTP determines the transcription of the gene followed [4] . psm genes were shown to start with an iATP [32] . In B . subtilis , genes starting with iATP were predicted to be up-regulated after amino acid limitation through an increase of the intracellular ATP pool [4] , [7] . However , this increase in ATP is obviously independent of the RSH-dependent ( p ) ppGpp synthesis , since we found a similar increase in the rshSyn mutant which is in line with results obtained in B . subtilis ( Tojo et al . , 2008 ) . Thus , increasing the ATP pool is not sufficient to trigger induction of the PSMs since no enhanced psm transcription was observed in the rshSyn mutant despite a similarly elevated ATP pool than the wild-type and rshSyn complemented strain . Our results indicate , by taking the example of a gene coding for a ribosomal protein S2 ( rpsB ) and initiation factor 2 ( infB ) , that the down-regulation of translational proteins after phagocytosis is mediated via rsh activity ( Fig . 6 ) . Together , with the lower expression of ilvC , psmα1-4 and psmβ1 , 2 in the rshSyn mutants , these findings suggest that the stringent response is induced after phagocytosis ( Fig . 7 ) . This result is supported by the global transcriptional analyses of the S . aureus strains after uptake by professional [34] and non-professional [44] phagocytes . A transcription pattern very similar to those described , was found here especially down-regulation of typical hallmark genes of the stringent response , i . e . , ribosomal proteins and up-regulation of amino acid biosynthesis genes . However , the intracellular signal for an RSH mediated stringent response remains speculative . For S . aureus , so far , only amino acid limitation was shown to induce ( p ) ppGpp synthesis via RSH . We also analyzed other conditions such as glucose starvation as potential signals for RSH dependent ( p ) ppGpp synthesis but found no detectable ( p ) ppGpp accumulation ( data not shown ) . Thus , these findings suggest that amino acid limitation triggers the response within phagocytes . Moreover , in L . monocytogenes , a gram-positive intracellular pathogen , the amino acid limitation sensing RSH was shown to be essential for survival and replication in macrophages [10] . However , this finding is in contradiction to results obtained from gram-negative intracellular pathogens . Here , the authors concluded that no amino acid limitation occurs in infected host cells . This conclusion is based on the finding that RelA , the enzyme solely responsible for accumulation of ( p ) ppGpp upon amino acid limitation in gram-negative bacteria , is not activated [17] , [45] , [46] , [47] , [48] . For these bacteria , the bifunctional ( p ) ppGpp synthase SpoT seems to be more important for adaption to the intracellular environment . It was presumed that balancing the basal levels of ( p ) ppGpp ( due to the hydrolase and synthase activity of SpoT ) is essential for intracellular adaptation [46] . There may be major differences between gram-negative and gram-positive bacteria concerning the mechanisms of signalling and responses to intracellular environments . Interestingly , treatment with azurophilic granule proteins [49] imposed transcriptional changes similar to those of the stringent response . It has to be elucidated whether parts of the reactive oxygen species ( ROS ) in phagolysosomes may be a trigger for the stringent response in S . aureus . The predominant role of S . aureus PSMs in killing human neutrophils was previously shown [31] . The reduced survival of the rshSyn mutant after phagocytosis is probably due to a decreased expression of PSMs within the phagolysosome . No other candidate virulence gene which could potentially account for this observation appeared in our microarray analysis to be down-regulated in the rshSyn mutant . Comparing the survival of an rshSyn mutant to a psmα , psmβ double mutant or an agr mutant reveals a similar low survival rate which is in line with published data [33] . The distinct role of psms expression for survival could be demonstrated by complementation assays of the rshSyn mutant with tetracycline induced psmα1-4 or psmβ1 , 2 . The fact that the reduced survival of an rshSyn , agr double mutant was not complementable by psm expression indicates that probably additional agr dependent factors are needed to survive after phagocytosis . Little is known about the intracellular behaviour of S . aureus . Growing evidence suggests that S . aureus can survive after phagocytosis and persists in neutrophils or macrophages to hide from the immune system , as well as to travel to and infect distant sites in the host [50] , [51] , [52] . However , the importance of single virulence factors contributing to intracellular survival seems to be dependent on the type of host cell and bacterial strains analyzed . For instance , S . aureus can escape from the phagoendosomes of human epithelial and endothelial cells into the cytosol , which is mediated by δ-toxin , β-toxin and ß-PSMs [53] . PSMs may similarly contribute to escape from the more toxic phagolysosomes of neutrophils and thereby allow intracellular survival . Whether they also contribute to a lysis of phagocytes from the inside remains to be shown . This was recently proposed based on observations that PSMs are efficiently inhibited by human serum and therefore lyse neutrophils rather from the inside than from the outside [54] . These authors could also show that psm promoter activity is strongly induced after phagosomal uptake . Moreover there could be an indirect impact of PSMs on the lysis of phagocytes . Previously it could be shown that different clinical isolates of strain USA300 induced a programmed necrosis of PMNs [55] . One may assume that intracellular expressed PSMs thereby could play an important role for this induction . The results we obtained are significantly important for the question how and where PSMs can act as potent cytolytic molecules The data of the current study support the conclusion that in phagolysosomes a stringent response is activated and that the activity of the ( p ) ppGpp synthase RSH is essential for the intracellular induction of psmα1-4 and psmβ1 , 2 expression . These cytolytic peptides in turn are responsible for the ability of S . aureus to survive after phagocytosis ( Fig . 7 ) . The signalling mechanisms leading to the activation of the ( p ) ppGpp synthases as well as the mechanism leading to gene activation through ( p ) ppGpp after phagocytosis is largely unknown and needs further examination .
Strains and plasmids are listed in Table S1 . S . aureus strains were grown in CYPG ( 10 g/l casamino acids , 10 g/l yeast extract , 5 g/l NaCl , 0 . 5% glucose and 0 . 06 M phosphoglycerate ) [56] or in a chemically defined medium ( CDM ) [15] . For strains carrying tetracycline , erythromycin or chloramphenicol resistance genes , antibiotics were used only in precultures at concentration of 5 µg/ml for tetracycline and 10 µg/ml for erythromycin and chloramphenicol , respectively . Bacteria from an overnight culture were diluted to an initial optical density at OD600 of 0 . 05 in 25 ml fresh medium using 100 ml baffled flasks and grown with shaking ( 220 rpm ) at 37°C to the desired growth phase . For down-shift experiments , strains were grown in complete CDM including leucine/valine ( leu/val ) to an OD600 of 0 . 5 . The cultures were filtered over a 0 . 22 µm filter applying vacuum , washed twice with sterile phosphate buffered saline ( PBS ) and bacteria were re-suspended in an equal volume of CDM medium with or without leu/val and grown for another 30 minutes . For serine starvation experiments , bacteria were re-suspended in an equal volume of CDM medium containing serine hydroxamate ( SHX , 1 . 5 mg/ml ) and incubated for 30 minutes . The haemolysis test was performed as described previously [29] . Briefly , bacteria to be tested are streaked at a right angle to RN4220 and the plate was incubated overnight . ß-hemolysin of strain RN4220 and δ-hemolysin of strains to be tested form a zone of clear haemolysis ( synergistic effect ) on blood agar plates . The rshSyn , codY double mutant was obtained by transducing the codY::tet ( K ) mutation into S . aureus strain Newman rshSyn [13] using Φ11 lysates of strains RN4220-21 [15] . Transductants were verified by PCR and PFGE . For complementation the full length rsh gene with a 960 bp upstream region was transduced into strain Newman rshSyn ( Table S1 ) using Φ11 lysates of strain CYL316-199 [13] . The psmα and psmβ mutants were obtained by replacing psmα1-4 with a tetracycline resistance cassette and psmβ1-2 with an erythromycin resistance cassette using a newly developed temperature-sensitive shuttle vector pBASE6 . This vector is based on the previously described pBT2 vector [57] with the additional advantage of counter-selection against the plasmid by inducible expression of S . aureus secY antisense RNA of the pKOR1 vector [58] . Therefore the HindIII-Bst1107I fragment of pBT2 was replaced by the 4 . 875 kb EcoRV-HindIII ( partial digest ) fragment of pKOR1 , containing the tetR/secY regulatory unit . Since some of the restriction sites of the pBT2 multiple cloning site ( MCS ) are also present in the introduced pKOR1 part , the MCS was removed by EcoRI-HindIII digestion . Primers: mcsmod1 ( ATTCCGGAGCTCGGTACCCGGGCTAGCGCGCAGATCTGTCGACGATATCA ) and mcsmod2 ( AGCTTGATATCGTCGACAGATCTGCGCGCTAGCCCGGGTACCGAGCTCCGG ) were mixed in equimolar amounts , heated to 95°C and slowly cooled down to room temperature . This new MCS contains only unique restriction sites and was ligated into the EcoRI-HindIII digested vector , resulting in pBASE6 . For gene replacements , two fragments flanking the pmsα1-4 , psmβ1-2 locus , the tetracycline and erythromycin resistant cassette were amplified and annealed by overlapping PCR to generate the pmsα1-4-tetM and psmβ1 , 2-ermC mutagenesis vectors pCG307 and pCG308 , respectively . The amplicons were cloned into the BglII/SalI restriction sites of pBASE6 . These plasmids were used to mutagenize strain RN4220 as described previously [13] . The obtained psm gene replacement mutant strains ( RN4220-307 and RN4220-308 ) were verified by PCR . In the mutants the whole psmα1-4 operon respectively psmβ1 , 2 operon was replaced by the corresponding resistant cassette . The rshSyn , psmα , psmβ triple mutant was obtained by transducing the psmβ::erm ( C ) and psmα::tet ( M ) mutations into S . aureus strain HG001 rshSyn using lysates of strain RN4220-307 and RN4220-308 . RNA isolation for microarray analysis and northern blot analysis was performed as described previously [59] . Briefly , bacteria were lysed in 1 ml of Trizol reagent ( Invitrogen Life Technologies , Karlsruhe , Germany ) with 0 . 5 ml zirconia-silica beads ( 0 . 1 mm-diameter ) in a high-speed homogenizer ( Savant Instruments , Farmingdale , NY ) . RNA was isolated as described in the instructions provided by the manufacturer of Trizol . RNA isolation after phagocytosis was performed as described in the instructions provided by the manufacturer of the RNA isolation kit ( ExpressArt RNAready , AmpTec ) with the modification adding an inhibitor removal buffer ( high pure viral nucleic acid kit , Roche diagnostics ) in the first step . Then DNA digestion was performed as instructed by the RNA isolation kit . Northern blot analyses were performed as described previously [59] . Digoxigenin-labeled probes for the detection of specific transcripts were generated using a DIG-Labeling PCR Kit following the manufacturer's instructions ( Roche Biochemicals ) . Oligonucleotides were used for probe generation as described previously [13] , [15] , [60] or are listed in Table S2 . Relative quantifications of α-type psms , β-type psms , infB , rpsB , RNAIII and gyrB transcripts were performed using LightCycler instrument ( Roche ) . Briefly , RNA isolated from cultures after phagocytosis ( 60 and 90 min ) was transcribed into complementary DNA using SuperScriptIII Reverse Transcriptase ( Invitrogen ) and 200 ng of random hexamer primers ( Fermentas ) . Complementary DNA was diluted 1∶5 and quantitative real-time PCR was performed using the QuantiFast SYBR Green PCR Kit ( Qiagen ) . A standard curve for each gene was generated using 5-fold serial dilutions of wild-type HG001 cDNA at timepoint 0 h ( oligonucleotides see Table S2 ) . Statistical analysis was performed with the Prism software package ( version 5 . 0; GraphPad ) using the Student t test two-tailed analysis ( p<0 . 05 ) . S . aureus wild type HG001 , isogenic mutants and the complemented strain were grown in CDM to OD600 = 0 . 5 . Cells were shifted to CDM with and without leu/val as described above . Samples for intracellular ATP analysis were harvested 30 min after the shift by fast filtration over a 0 . 22 µm sterility filter applying vacuum . Cells were washed , quenched and nucleotides were extracted as described recently [61] , [62] . The extracts were resuspended in 5 ml of 0 . 1 M Tris-acetate buffer ( pH 7 . 75 ) and stored at −80°C . The detection of ATP was performed by the Enlighten ATP assay system using luciferase and luciferin ( Promega ) . Therefore nucleotide extracts were diluted 1∶100 in Tris-acetate buffer and 10 µl mixed with 90 µl of the ATP assay reagents . Luminescence was measured with a luminescence detection reader ( Infinite M200Pro , Tecan , Austria ) . The standard curve was generated by using known concentrations of ATP . The results of the intracellular ATP measurements represent the mean of 2 biological replicates measured in triplicates . Statistical analysis was performed with the Prism software package ( version 5 . 0; GraphPad ) using the Student t test two-tailed analysis ( p<0 . 05 ) . The microarray was manufactured by in situ synthesis of 60-base-long oligonucleotide probes ( Agilent , Palo Alto , CA ) , selected as previously described [63] . The array covers >98% of all open reading frames ( ORFs ) annotated in strains N315 and Mu50 , MW2 , COL , NCTC8325 and USA300 , and MRSA252 and MSSA476 , as well as Newman , including their respective plasmids . Total RNA was purified from strain HG001 WT , rshSyn mutant , codY mutant and rshSyn , codY double mutant grown in CDM to an OD600 of 0 . 5 . For each strain RNA of three independently grown cultures was analyzed . After additional DNase treatment , the absence of remaining DNA traces was confirmed by quantitative PCR ( SDS 7700; Applied Biosystems , Framingham , MA ) with assays specific for 16S rRNA [15] . Batches of 5 µg of total S . aureus RNA were labeled by Cy3-dCTP using SuperScript II ( Invitrogen , Basel , Switzerland ) following the manufacturer's instructions . Labeled products were then purified onto QiaQuick columns ( Qiagen ) . Purified genomic DNA from the different sequenced strains used for the design of the microarray was extracted ( DNeasy; Qiagen ) , labeled with Cy5 dCTP using the Klenow fragment of DNA polymerase I ( BioPrime , Invitrogen , Carlsbad , CA ) , and used for the normalization process [64] Cy5-labeled DNA ( 500 ng ) and a Cy3-labeled cDNA mixture were diluted in 50 µl of Agilent hybridization buffer and hybridized at a temperature of 60°C for 17 h in a dedicated hybridization oven ( Robbins Scientific , Sunnyvale , CA ) . Slides were washed , dried under nitrogen flow , and scanned ( Agilent , Palo Alto , CA ) using 100% photon multiplier tube power for both wavelengths . Fluorescence intensities were extracted using Feature Extraction software ( version 9; Agilent ) . Local background-subtracted signals were corrected for unequal dye incorporation or unequal load of the labeled product . The algorithm consisted of a rank consistency filter and a curve fit using the default LOWESS ( locally weighted linear regression ) method . Data consisting of three independent biological experiments were expressed as log 10 ratios and analyzed using GeneSpring , version 8 . 0 ( Silicon Genetics , Redwood City , CA ) . A filter was applied to select oligonucleotides mapping ORFs in the Newman genome , yielding approximately 95% coverage . Statistical significance of differentially expressed genes was calculated by analysis of variance [65] using GeneSpring , including the Benjamini and Hochberg false discovery rate correction of 5% ( p value cutoff , 0 . 05 ) and an arbitrary cutoff of twofold for expression ratios . The complete microarray data set has been posted on the Gene Expression Omnibus database ( http://www . ncbi . nlm . nih . gov/geo/ ) under accession number GSE99340 for the platform design and GPL7137 for the original data set . Killing by human neutrophils was performed as described previously [66] . Briefly , bacteria of the logarithmic phase were washed and adjusted in potassium phosphate buffer ( 10 mM K2PO4 ) . Neutrophils were isolated from peripheral blood of healthy volunteers by ficoll/histopaque gradient centrifugation as described previously [67] and resuspended in HBSS-HSA ( hank's balanced salt solution , Sigma , containing 0 . 05% human serum albumin ) . Bacteria were opsonized by addition of pooled human serum ( Sigma ) to a final concentration of 10% . Opsonized bacteria ( 107/ml ) and neutrophils ( 106/ml ) were combined to a volume of 500 µl and samples were shaken at 37°C . For the psm complementation assays , neutrophils and bacteria were preincubated for 30 minutes without anhydrotetracycline ( ATc ) followed by addition of 0 , 1 µg/ml ACT for another 30 minutes . Aliquots were diluted in ice-cold water and vortexed vigorously to disrupt the neutrophils and halt bacterial killing . Appropriate dilutions were plated on tryptic soy agar plates and incubated at 37°C for the following day for enumeration of CFU . The percent of bacterial survival was calculated with the equation CFU+PMN at t60/CFU+PMN at t0 . Statistical analysis was performed with the Prism software package ( version 5 . 0; GraphPad ) using the Student t test two-tailed analysis ( p<0 . 05 ) . Following phagocytosis of S . aureus , lysis of human neutrophils was determined with a standard assay for release of lactate dehydrogenase ( LDH ) as described by the manufacturer ( Cytotoxicity Detection kit; Roche Applied Sciences ) . Statistics were performed with the Prism software package ( version 5 . 0; GraphPad ) using the Student t test two-tailed analysis ( p<0 . 05 ) . | The stringent response is a bacterial response to a multitude of different environmental stress conditions which is characterized by the synthesis of the messenger molecules ( p ) ppGpp . There is now growing evidence that these molecules also play a key role for pathogens to switch between specific phenotypic states within the host . This seems crucial for the adaptation to different microenvironments encountered during infection for instance after uptake by phagocytes . Killing of phagocytes as well as survival within these cells was proposed as major mechanisms for the success of the human pathogen Staphylococcus aureus to spread within the body . In the current study we demonstrate the effect of the stringent response on global gene expression in S . aureus and its impact on intracellular survival in human neutrophils . We reveal that a stringent response is induced after uptake of S . aureus in neutrophils and RSH activity is crucial for intracellular induction of psm expression , coding for cytotoxic phenol-soluble modulins ( PSMs ) . Finally we show that this in turn mediates bacterial survival and escape after phagocytosis . These findings contribute to the understanding of how and where PSMs can act as potent cytolytic molecules and emphasise the importance of ( p ) ppGpp as an intracellular signalling molecule . | [
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] | 2012 | The Stringent Response of Staphylococcus aureus and Its Impact on Survival after Phagocytosis through the Induction of Intracellular PSMs Expression |
In low elevation arid regions throughout the southern United States , Borrelia turicatae is the principal agent of tick-borne relapsing fever . However , endemic foci and the vertebrate hosts involved in the ecology of B . turicatae remain undefined . Experimental infection studies suggest that small and medium sized mammals likely maintain B . turicatae in nature , while the tick vector is a long-lived reservoir . Serum samples from wild caught rodents , raccoons , and wild and domestic canids from 23 counties in Texas were screened for prior exposure to B . turicatae . Serological assays were performed using B . turicatae protein lysates and recombinant Borrelia immunogenic protein A ( rBipA ) , a diagnostic protein that is unique to RF spirochetes and may be a species-specific antigen . Serological responses to B . turicatae were detected from 24 coyotes , one gray fox , two raccoons , and one rodent from six counties in Texas . These studies indicate that wild canids and raccoons were exposed to B . turicatae and are likely involved in the pathogen’s ecology . Additionally , more work should focus on evaluating rodent exposure to B . turicatae and the role of these small mammals in the pathogen’s maintenance in nature .
Tick-borne relapsing fever ( RF ) is primarily caused by spirochetes in the genus Borrelia and the pathogens are transmitted when infected Ornithodoros ticks feed on a competent vertebrate host . In the United States and Mexico , there is an association between Ornithodoros ticks and RF spirochete species where Ornithodoros hermsi , Ornithodoros parkeri , Ornithodoros turicata , and Ornithodoros talaje transmit Borrelia hermsii , Borrelia parkeri , Borrelia turicatae , and Borrelia mazzottii , respectively [1] . Furthermore , these tick species involved in human disease are distributed in varying ecological niches . For example , the ecology of O . hermsi is associated with coniferous forests at elevations above 900 meters throughout the western United States and Canada [2–6] . Ornithodoros parkeri has also been collected in semi-arid regions of the western United States at elevations from sea level to over 2 , 000 meters [7 , 8] . Ornithodoros turicata is found in arid regions of Mexico , the mid- and southwestern United States from California to Texas , and a population exists in Florida [9–11] . The ecology of O . talaje overlaps that of O . turicata and collections have occurred in Mexico and in Texas [1 , 12 , 13] . Of the Ornithodoros species that transmit RF spirochetes , O . turicata and O . talaje are currently the only ones known in Texas , yet there are few records of O . talaje collections and B . mazzottii has not been isolated in the laboratory . The biology of both RF spirochetes and their tick vector have posed challenges in defining the pathogens’ ecology . Ornithodoros species are rapid feeding ticks that reside in cavities including wood crevices , dens , nests , and karst formations [6 , 7 , 9 , 14] . Thus , the vector is rarely found attached on the vertebrate host . Moreover , in the vertebrate host , spirochetes replicate in the blood reaching densities of ~1 x 107 bacteria per ml before being cleared by an antibody mediated response [15] . The pathogens undergo antigenic variation and subsequently repopulate the blood [15] . This dynamic between antigenic variation and the host antibody response can continue for two to three months in a competent host [11 , 16] . The cyclic nature of RF spirochetes within a competent host poses challenges when attempting to directly detect the pathogens in the blood of wild caught animals because there are quiescent periods when the spirochetes are undetectable . Since RF spirochetes induce a robust IgG response [17–19] , serological surveillance is a practical approach toward defining the pathogens’ ecology given the temporal persistence of generated antibodies in the host’s blood . The ecology of B . turicatae is poorly defined and in this current study we utilized a diagnostic antigen , the Borrelia immunogenic protein A ( BipA ) , which has been used to assess canine , rodent , and human exposure to the pathogen [17 , 20] . Aside from the closely related B . parkeri , BipA is highly variable between species of RF spirochetes [20] . Moreover , a BipA homologue has not been identified in other viral , parasitic , or bacterial pathogens [17] . Utilizing this diagnostic antigen , we evaluated the exposure of wild and domestic canids , raccoons , and rodents to B . turicatae . Serum samples were collected from 23 counties in Texas and screened against B . turicatae protein lysates and recombinant BipA ( rBipA ) . Most rodents were also identified to species by morphology and molecular sequencing of the cytochrome B gene . Our findings indicate that Canis latrans ( coyote ) , Urocyon cinereoargenteus ( gray fox ) , Procyon lotor ( raccoon ) , and Peromyscus leucopus ( white-footed mouse ) may be vertebrate hosts for B . turicatae in nature .
Rodent collections were approved by the Institutional Animal Use and Care Committee at Mississippi State University ( IACUC protocol #11–091 ) and Texas Parks and Wildlife ( Scientific Research Permit #SPR-0812-958 ) . Collections of coyotes , gray fox , and raccoon serum samples originally occurred as part of the rabies surveillance program by the Texas Department of State Health Services . Collection of shelter canine serum samples were approved by the University of Texas Health Science Center Animal Welfare Committee ( AWC-07-147 and AWC-03-029 ) . Animal samplings occurred between 2005 and 2018 . Rodents were captured alive using Sherman live traps ( H . B . Sherman Traps , Tallahassee , FL ) . Traps were placed in and around houses , barns , and fields in the late afternoon and baited with dried oats . The following morning traps were collected , and the animals processed . Animals were euthanized by inhalation of isoflurane and exsanguinated by cardiac puncture . A drop of blood was placed on a microscope slide and the presence of spirochetes was evaluated by dark field microscopy . Peripheral blood smears were also made on microscope slides . The remaining blood was centrifuged at 1 , 000 x g and serum separated from the blood clot . Animals were evaluated for argasid ticks . Shelter dogs and wild canids and raccoons were also sampled . Serum samples from stray domestic dogs located in Brownsville , TX were collected , as previously described [21] . Coyote , gray fox , and raccoon serum samples were collected as part of the Texas Department of State Health Services rabies surveillance program . The animals were captured in Tomahawk traps , terminally sampled , and serum samples stored at -20°C . Canids and raccoons were identified to the species level using morphological characteristics . Rodents were identified by morphological characteristics and molecular analysis of the cytB gene . For rodent morphological characteristics , body weights were recorded with Pesola spring scales ( PESOLA SG , Baar , Switzerland ) , gender determined , and body and tail measurements recorded . Photographs of each animal were obtained for future reference . For molecular analysis , a 3-mm tissue biopsy was collected from each animal , stored in 90% ethanol , and DNA extracted using the DNeasy Blood and Tissue kit ( Qiagen Sciences , Inc . , Germantown , MD ) . PCR was performed using forward ( 5’-CCATGAGGACAAATATCCTTCTGAGGG-3’ ) and reverse ( 5’-GCCCTCAGAAGGATATTGTCCTCATGG-3’ ) primers for cytB , and sequencing performed as previously described [19 , 22] . Sequences were assembled into overlapping contiguous DNA segments ( contigs ) using Vector NTI 11 . 0 software ( ThermoFisher Scientific , Waltham , MA ) . Contigs were evaluated using BLASTn on NCBI . Immunoblotting was performed to evaluate seroconversion against B . turicatae protein lysates and rBipA , as previously described [17] . Briefly , protein lysates from 1 x 107 B . turicatae spirochetes and 1 µg of rBipA were loaded into the wells of Mini-PROTEAN TGX precast gels ( Bio-Rad , Hercules , CA ) . Gels were run for 1 . 5 hours and proteins were transferred onto Immobilon PVDF membranes ( Millipore , Billerica , MA ) . Membranes were blocked overnight with Tropix Iblock ( Thermo Fisher Scientific , Waltham , MA ) and then probed for one hour at room temperature with serum samples diluted 1:200 . The secondary molecule was HRP-conjugated protein G ( Thermo Fisher Scientific , Waltham , MA ) for canids and rodents at a 1:4 , 000 dilution . Raccoon serum samples were probed with a goat anti-raccoon IgG-HRP conjugated antibody ( Alpha Diagnostics Intl . Inc . , San Antonio , TX ) at a 1:4 , 000 dilution . The substrate used to detect binding was Amersham ECL Western Blotting Detection Reagent ( GE Healthcare , Buckinghamshire , UK ) . A sample was considered positive for B . turicatae if we detected reactivity to at least five proteins in the B . turicatae protein lysate and rBipA . For visualizing the ecoregions of Texas we obtained a shapefile from the United States Environmental Protection Agency , which included the following 12 ecoregions: Arizona/New Mexico Mountain , Central Great Plains , Chihuahua Deserts , Cross Timbers , East Central Texas Plains , Edwards Plateau , High Plains , South Central Plains , Southern Texas Plains , Southwestern Tablelands , Texas Blackland Prairies , and Western Gulf Coastal Plains [23] . These ecoregions were defined based upon several biotic and abiotic factors such as climate , vegetation , soil type , geology , land use , wildlife , and hydrology [23] . This shapefile was then imported into ArcMap and we overlaid each county where collections occurred in Texas noting the taxa group ( coyote = C , Dog = D , gray fox = GF , raccoons = RA , and rodents = R ) and the number of collections ( Fig 1 ) . Statistical analysis was performed using R 3 . 3 . 1 ( R foundation for Statistical Computing , Vienna , Austria , https://www . R-project . org/ ) . The 95% confidence intervals ( CI ) were determined for each group of samples tested that had at least one positive sample , using the proportions test . A binomial distribution was assumed with determining CI .
One to four field sites were sampled in 23 counties of Texas between 2005 and 2018 . Sites included private property that was accessible through the Texas Ecolab Program and Texas Parks and Wildlife Management Areas . Counties where samples were collected were within the following Texas ecoregions: Central Great Plains , Chihuahuan desert , Cross Timber , East Central Texas Plains , Edwards Plateau , South Central Plains , Southern Texas Plains , Southwestern Tablelands , Texas Blackland Prairies , and Western Gulf Coastal Plains ( Fig 1 ) . A total of 463 canids were sampled and included 185 shelter dogs ( Canis lupus familiaris ) , 220 coyotes ( C . latrans ) and 58 gray foxes ( U . cinereoargenteus ) ( Fig 1 ) . Serum samples were also collected from 25 raccoons ( P . lotor ) and 263 rodents ( Fig 1 ) . Argasid ticks were not detected on the animals . Animals were considered susceptible to infection by B . turicatae based on serological reactivity to at least five bands in B . turicatae protein lysates and rBipA . Assessing serological responses of canids ( Fig 2 ) indicated a total seroprevalence of 5 . 4% ( CI = 3 . 6–8 . 0% ) ( Table 1 ) . None of the 185 shelter dogs that were screened had a detectable antibody response in the diagnostic assay , while 10 . 9% and 1 . 7% ( CI = 7 . 3–16 . 0% and 0 . 09–10 . 5% ) seroprevalence was detected in coyotes and gray fox , respectively . Webb County had the highest number of seropositive coyotes with a total of 10 animals . Presidio and Zapata County each had five seropositive animals , while Dimmit County had four . In the animals exposed to B . turicatae , a gender difference was not detected . In El Paso County , there was a single juvenile male gray fox that was seropositive , resulting in 1 . 7% ( CI = 0 . 7–53 . 3% ) prevalence among gray fox . Species within seven genera of rodents were collected between 2012 and 2015 including Peromyscus maniculatus , Peromyscus leucopus , Chaetodipus hispidus , Sigmodon hispidus , Neotoma albigula , Perognathus , and Dipodomys species . Evaluating serological responses ( Fig 2 ) indicated that 0 . 4% ( CI = 0 . 02–2 . 4% ) were seropositive ( Table 3 ) . Peromyscus leucopus was the only positive animal and originated from Edwards County .
In this study , we began to define the ecology of B . turicatae in Texas by assessing serological responses as an indicator of host competency . While RF spirochete infections can persist for several months in a competent host [11] , the pathogens’ life cycle is recurrent and direct detection of infection can be challenging because of the brevity of time when spirochetes are detectable in the blood . To circumvent this , we indirectly detected exposure to B . turicatae by assessing the vertebrate antibody response . Our findings indicate that wild canids are likely a host for B . turicatae in west Texas . These studies were also the first known serological evaluation of rodents and raccoons to B . turicatae and provided verification that exposure is occurring in this tick-host-pathogen relationship . Rodents and insectivores are known reservoir hosts for at least two species of RF spirochete [3 , 19 , 24 , 25] , but the role of these small mammals in the ecology of B . turicatae is vague . In high elevation regions of the Western United States , sciurid rodents are the primary vertebrate host for B . hermsii , while the pathogens have also been detected in Neotoma macrotis [3 , 24] . In regions of western Africa , Borrelia crocidurae is maintained in Mastomys and Crocidura species [19] . Previous tick transmission studies of B . turicatae to laboratory mice suggest that wild rodents may be susceptible to infection [17 , 26 , 27] , and the identified seropositive P . leucopus from this current study indicated that white-footed mice are a potential competent host . However , we sampled the field site where this animal was collected three more times from 2012 to 2014 and failed to identify other positive rodents . Additional studies are needed to investigate the life cycle of B . turicatae in rodents to determine whether the pathogen attains densities in the animals that will facilitate spirochete acquisition and colonization of the tick vector . There is mounting evidence that canids likely support the maintenance and dissemination of B . turicatae in nature . For example , the competency of domestic canines for B . turicatae was demonstrated as nearly half of the B . turicatae isolates have originated from sick dogs [28] . Moreover , successful infection of B . turicatae to a laboratory dog by tick bite suggested that the spirochetes attained sufficient densities in the blood to infect ticks [17] . In this current report , B . turicatae positive coyote and gray fox serum samples originated from Dimmit , Presidio , Webb , Zapata , and El Paso County , all of which border Mexico . With the broad home range of coyotes , these mammals are likely circulating B . turicatae between the United States and Mexico . Coyotes possess highly organized social systems even in urban settings and are classified as transient or resident based on their territorial range [29 , 30] . Transient coyotes are typically solitary subordinate young adults with a home range of 40 km2 to 395 km2 . Resident coyotes have a home range of 8 km2 to 29 km2 and are part of the larger pack that include breeders , juveniles , and pups [30] . Coyote dens are often found in or around urban settings and with the expansion of these areas in Mexico and the United States , coyotes and humans are commonly in contact [30 , 31] . A knowledge gap in the ecology of B . turicatae is a poor understanding regarding the dissemination of the vector in nature . Ornithodoros turicata are rapid feeders , completing a bloodmeal within five to 60 minutes after attachment [26] . However , it is unclear whether some proportion of ticks remain on the wild vertebrate host after engorgement , either attached or unattached , allowing for increased dissemination . Interestingly , we have collected engorged Carios kelleyi nymphs , which are rapid feeding argasid ticks of bats [9] . This suggests that some argasid species may remain on the vertebrate host for a duration of time after feeding . Population genetic studies are needed to evaluate the genetic diversity between O . turicata populations at different spatial scales collected in the United States , to estimate dissemination patterns of both vector and pathogen . A limitation of our study is the likely circulation of additional uncharacterized RF spirochete species in the southern United States . While BipA is highly divergent between most species of RF spirochete and the recombinant protein can discriminate between B . hermsii and B . turicatae infections [17] , additional work is needed to obtain novel spirochete species circulating in nature . For example , Ornithidoros talaje was recently collected in Texas [1] , and while we failed to detect Borrelia DNA in these the ticks , the circulation of Borrelia mazzottii in the state exists . In 1955 , B . mazzottii was reported to be transmissible by O . talaje ticks that were collected in northern Mexico [12] , but since then reports of the disease have been absent . Recently , RF spirochetes were detected in a blood smear of a sick patient in Sonora , Mexico , but the species was unidentified [32] . Furthermore , Candidatus Borrelia texasensis was initially isolated in medium from an adult ixodid tick , Dermacentor variabilis , which was feeding on a coyote collected in Webb County , Texas [33] . The spirochete was initially cultured and grouped with RF spirochetes , but Lin and colleagues were unable to revive frozen stocks and an isolate does not exist . While it is unclear whether coyotes are a competent host for Candidatus Borrelia texasensis , the findings suggest that the mammals may be exposed to additional species of RF spirochete . We recommend increased surveillance of small and medium sized mammals within metropolitan areas of Texas . San Antonio , Austin , and Dallas , Texas are in the top 11 most populated cities in the United States , are rapidly expanding , and evidence indicates that B . turicatae may be emerging in these areas . In 2017 there was an outbreak of TBRF among conference attendees in Austin , Texas [34] , which is located in Travis County . This outbreak was in a densely populated area of the city and B . turicatae infected ticks were collected from rodent dens at a public park near the conference site . In our current report , there was little overlap between the Texas ecoregions that were sampled for the different vertebrate species ( Table 1 ) , and only three rodents were collected in Travis County . Future studies should focus on small and medium sized vertebrate sampling in regions where B . turicatae is emerging , and investigate host competence for the pathogen . As these studies are conducted , a refined understanding of the vertebrate hosts that support the ecology of B . turicatae will be attained , and surveillance and countermeasures can be implemented to improve public health . | In arid regions of the southern United States and Mexico , tick-borne relapsing fever is primarily caused by Borrelia turicatae . The tick vector , Ornithodoros turicata , feeds indiscriminately on a variety of vertebrates; however , it is unclear which animals are competent hosts for B . turicatae . This study evaluates the exposure of small and medium sized mammals in Texas to B . turicatae and identifies likely hosts for the pathogens . This work will provide insight regarding mammals to target for surveillance to identify endemic foci and to better prevent human exposure . | [
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... | 2018 | Seroprevalence for the tick-borne relapsing fever spirochete Borrelia turicatae among small and medium sized mammals of Texas |
Highly pathogenic avian influenza viruses of the H5N1 subtype continue to threaten agriculture and human health . Here , we use biochemistry and x-ray crystallography to reveal how amino-acid variations in the hemagglutinin ( HA ) protein contribute to the pathogenicity of H5N1 influenza virus in chickens . HA proteins from highly pathogenic ( HP ) A/chicken/Hong Kong/YU562/2001 and moderately pathogenic ( MP ) A/goose/Hong Kong/437-10/1999 isolates of H5N1 were found to be expressed and cleaved in similar amounts , and both proteins had similar receptor-binding properties . However , amino-acid variations at positions 104 and 115 in the vestigial esterase sub-domain of the HA1 receptor-binding domain ( RBD ) were found to modulate the pH of HA activation such that the HP and MP HA proteins are activated for membrane fusion at pH 5 . 7 and 5 . 3 , respectively . In general , an increase in H5N1 pathogenicity in chickens was found to correlate with an increase in the pH of HA activation for mutant and chimeric HA proteins in the observed range of pH 5 . 2 to 6 . 0 . We determined a crystal structure of the MP HA protein at 2 . 50 Å resolution and two structures of HP HA at 2 . 95 and 3 . 10 Å resolution . Residues 104 and 115 that modulate the acid stability of the HA protein are situated at the N- and C-termini of the 110-helix in the vestigial esterase sub-domain , which interacts with the B loop of the HA2 stalk domain . Interactions between the 110-helix and the stalk domain appear to be important in regulating HA protein acid stability , which in turn modulates influenza virus replication and pathogenesis . Overall , an optimal activation pH of the HA protein is found to be necessary for high pathogenicity by H5N1 influenza virus in avian species .
Highly pathogenic avian influenza ( HPAI ) viruses kill up to 100% of infected poultry flocks and may cause high mortality rates when transmitted to humans [1] , [2] . For example , H5N1 influenza viruses have contributed to the deaths of 331 of 565 individuals since 2003 [3] and are endemic in domestic poultry in Egypt and Indonesia [4] . The continued circulation of H5N1 and potential emergence of an H5N1 human pandemic virus remain ever-present threats . The hemagglutinin ( HA ) surface glycoprotein promotes viral entry through its receptor binding and membrane fusion functions [5] , and mutations in HA have been shown to modulate the pathogenicity , host range specificity , transmissibility , and pandemic potential of influenza viruses [1] , [6] , [7] . HA is synthesized as a trimeric HA0 protein that must be activated for membrane fusion by post-translational cleavage into a high-energy HA1/HA2 complex . The multi-basic HA0 cleavage sites of H5 and H7 HPAI viruses are recognized by ubiquitously expressed intracellular proteases , facilitating systemic virus spread and greater pathogenicity [8]–[10] . HA binds to sialic acid-containing receptors on the surfaces of host cells [5] , and the specificity of receptor binding helps determine host range , with avian and human viruses preferentially binding to α ( 2 , 3 ) and α ( 2 , 6 ) sialosides , respectively [11] , [12] . Upon internalization , the virus is exposed to progressively lower pH values until a threshold is reached that triggers HA to undergo irreversible conformational changes that mediate membrane fusion [13] . Mutations that modulate HA acid stability have been associated with the adaptation of influenza viruses to different host species and cell lines [14] , [15] , and HA acid stability has recently been identified as a potential virulence factor [16] . Some influenza viruses contain all of the known genetic elements for high pathogenicity yet are attenuated in vivo . For example , the clade 3 H5N1 isolate A/goose/Hong Kong/437-10/1999 has significantly lower replication and pathogenicity in chickens compared to the closely related isolate A/chicken/Hong Kong/YU562/2001 [17] . The attenuating amino-acid residues have been mapped to the receptor-binding sub-domain and the vestigial esterase sub-domain in the HA1 receptor-binding domain ( RBD ) in the HA protein . However , the HA proteins from both isolates contain markers typical of high pathogenicity including a polybasic cleavage site , identical glycosylation sites , and identical residues in the receptor-binding pocket . The goal of the current study was to determine the molecular mechanism by which the naturally occurring variations in the HA protein modulate H5N1 pathogenicity .
To determine how the HA proteins from the two isolates differ in their biochemical properties , the proteins were expressed in cell culture and compared for expression , cleavage , receptor binding , and activation pH ( Figure 1 , S1 ) . The neuraminidase ( NA ) proteins were co-expressed with the HA proteins because of the known interplay between HA and NA with respect to receptor binding [18] and membrane fusion [16] , [19] , [20] . Western blot and flow cytometric analyses revealed no significant differences in total or cell-surface expression of the two HAs when co-expressed with NA from either isolate ( Figure 1A , B and Figure S1 ) . The ratios of cleaved ( HA1+HA2 ) to uncleaved ( HA0 ) species were also similar for the two HAs ( Figure 1A ) . To investigate potential differences in avian receptor-binding avidity , we quantified the amount of chicken and turkey erythrocytes adsorbed to HA-expressing cells and found no difference ( Figure 1C ) . Overall , these data show that the amino-acid variations in the HA and NA proteins from the MP and HP isolates do not result in substantial differences in HA protein expression , cleavage , or receptor binding . We next compared the activation pH values of the two HA proteins . Flow cytometry was used to measure pH-induced conformational changes by using monoclonal antibodies VN04-09 and VN04-16 that preferentially bind to the prefusion and postfusion forms of the H5N1 HA protein , respectively [19] , [21] . When co-expressed with the homotypic NA partner , conformational changes by MP HA were first observed at pH 5 . 4 , reached a midpoint at pH 5 . 3 , and were complete at pH 5 . 1–5 . 2 depending on the antibody ( Figure 1E ) . In contrast , conformational changes by HP HA were triggered at higher pH ( ∼0 . 4 pH units ) being first observed at pH 5 . 8 , reaching a midpoint at pH 5 . 7 , and being complete at approximately pH 5 . 4 ( Figure 1D ) . Comparing the midpoints of conformational changes , MP HA had a value of pH 5 . 3 whereas HP HA had a value of 5 . 7 , showing that HP HA is less acid stabile than MP HA . To determine the highest pH at which the HA proteins promote membrane fusion , syncytia assays were performed in BHK-21 cells . Consistent with the flow cytometry results , MP HA triggered membrane fusion at pH 5 . 3 when co-expressed with its MP NA partner , and HP HA triggered fusion at pH 5 . 7 when co-expressed with its HP NA partner ( Figure 1F ) . The syncytia assays were repeated using BHK-21 cells infected with the MP 437-10 and HP YU562 viruses . In virus-infected cells , MP HA was activated to cause membrane fusion at pH 5 . 2 , and HP HA promoted membrane fusion at pH 5 . 6 . Therefore , during either infection or transient expression , HP HA was destabilized by 0 . 4 pH units compared to MP HA . We have recently shown that NA enzymatic activity increases the activation pH of the H5N1 HA protein [16] . Therefore , we next investigated whether potential differences in the activities of NA proteins from the HP YU562 and MP 437-10 viruses might affect HA acid stability . We first measured the activities of HP and MP NA when transiently co-expressed with their homotypic HA protein and found that HP NA had significantly more activity than MP NA ( P<0 . 05; unpaired two-tailed t test ) ( Figure 2A ) . Second , we measured the NA activities of HP and MP viruses in vitro and found once again that the HP virus had significantly more NA activity than the MP virus ( P<0 . 01; unpaired two-tailed t test ) ( Figure 2B ) . Third , we measured the pH of activation of the HAs when co-expressed with either the HP or MP NA protein ( Figure 1F ) . MP HA was activated at a higher pH of 5 . 45 when co-expressed with the more active , heterotypic HP NA compared to co-expression with the less active , homotypic MP NA ( pH of 5 . 3 ) . HP HA was activated at a lower pH of 5 . 4 when co-expressed with the less active , heterotypic MP NA compared to co-expression with the more active , homotypic HP NA ( pH of 5 . 7 ) . In summary , we found that the HA protein from the HP YU562 virus was activated at a higher pH than the HA protein from the MP 437-10 virus , and increased NA activity from the HP YU562 virus was associated with a further increase in the pH of HA activation . The HA proteins of MP 437-10 and HP YU562 viruses differ by 7 amino-acid residues in HA1 . Residues 104 and 115 are at the ends of the 110-helix in the vestigial esterase sub-domain of the RBD , 131 and 142 are distal to the receptor-binding pocket in the receptor-binding sub-domain , 216 and 221 are at the interface of receptor-binding sub-domain protomers , and 331 is within the polybasic cleavage site [17] . To identify the residues that are responsible for altering HA acid stability , we introduced mutations into the HP HA that correspond to those found in the MP HA , either individually or in combination . We introduced the mutations into the HP HA , rather than vice versa , because chicken LD50 values for influenza viruses containing analogous mutations were previously made in the background of the 8 gene segments of the HP virus [17] . We then measured the biochemical properties of the mutant HP HA proteins when co-expressed with the homotypic HP NA protein . We initially focused on three chimeric HP HA proteins: rHA1 ( D104N/I115T/E131D/L142H ) , rHA3 ( K216E/S221P ) , and rHA5 ( E331K ) . None of the three chimeric proteins displayed altered levels of expression , cleavage , or receptor-binding avidity of the HP HA protein ( Figure 3 ) . The E331K mutation in the polybasic cleavage site of rHA5 did not affect the HA activation pH ( Figure 3A ) . The mutant HP HA protein containing K216E/S221P mutations ( rHA3 ) was also not responsible for decreasing the pH of activation , but instead had the opposite effect by raising the pH of activation of the HP HA protein to 6 . 0 ( Figure 3A ) due to the presence of the K216E mutation ( Figure S2 ) . The rHA1 chimeric HP HA protein containing 4 mutations ( D104N/I115T/E131D/L142H ) was previously shown to reduce the pathogenicity of HP YU562 virus in chickens [17] , and in this study we found that the rHA1 mutations reduced the activation pH of HP HA from 5 . 7 to 5 . 35 ( Figure 3A ) , a value similar to that of MP HA . To identify the responsible residue ( s ) , we generated HP HA proteins that contained either single ( D104N , I115T , E131D , or L142H ) or double ( D104N/I115T or E131D/L142H ) mutations . A reduced activation pH was only present in the D104N/I115T double mutant , which was triggered at pH 5 . 45 , a value identical to that of the MP HA protein when co-expressed with the HP NA protein ( Figure 3 ) . Therefore , our data suggest that changes at residues 104 and 115 contribute to the difference in the activation pH values of the HP and MP HA proteins . We next compared our measurements of HA activation pH to the values of 50% lethal dose ( LD50 ) in chickens that had been infected with H5N1 viruses containing equivalent HA mutations [17] . An increase in the pH of activation of the HA protein correlated ( R2 = 0 . 82 ) with an increase in pathogenicity , represented as the reciprocal of LD50 ( Figure 4 ) . HP HA and rHA3 ( K216E/S221P ) had relatively high activation pH values of 5 . 7 and 6 . 0 , respectively , and promoted the most pathogenicity in chickens with the lowest LD50 values of 0 . 1 and 0 . 02 log10 EID50/mL , respectively . All of the HAs that had activation pH values less than 5 . 5 promoted reduced pathogenicity in chickens , resulting in LD50 values greater than 0 . 5 log10 EID50/mL . For HP HA , the presence of the more-active HP NA resulted in an activation pH of 5 . 7 and an LD50 value of 0 . 1 EID50/mL , whereas the presence of the less-active MP NA decreased the activation pH to 5 . 4 and lowered the pathogenicity to an LD50 value of 0 . 67 EID50/mL . Conversely for MP HA , the presence of the less-active MP NA resulted in an activation pH of 5 . 3 and an LD50 value of 3 . 7 EID50/mL , whereas the presence of the more-active HP NA increased the activation pH to 5 . 45 and enhanced the pathogenicity to an LD50 value of 1 . 7 EID50/mL . In some cases when switching NA partners , the relationship between HA activation pH and pathogenicity was less pronounced . For example , the HP HA + MP NA combination resulted in an HA activation pH of 5 . 4 and an LD50 value of 0 . 67 EID50/mL while the MP HA + HP NA combination had a slightly higher activation pH of 5 . 45 but was less pathogenic with an LD50 value of 1 . 7 EID50/mL . While a loss of balance between HA's receptor-binding activity and NA's enzymatic activity [18] could potentially cause such a discrepancy when the NA partner is switched , another unidentified mechanism may play a role instead as the presence of either NA resulted in similar receptor-binding avidities for MP and HP HA ( Figure 1C ) . Overall , though , the data reveal a trend in which an increase in the pH of activation of the HA protein is associated with increased pathogenicity in chickens within the observed pH range of 5 . 2 to 6 . 0 . To gain insights into the structural basis for altered HA acid stability , we determined the crystal structures of the prefusion forms of the MP and HP HA proteins ( Table 1 ) . One crystal form of the MP HA protein was obtained at pH 8 . 5 , and two crystal forms of the HP HA protein were obtained at pH 6 . 6 , all above the low pH thresholds for conformational changes for the two proteins . The overall folds of the MP and HP HA proteins ( H5N1 clade 3 ) are very similar to each other ( Figures 5D and S3 ) and to those of the previously determined HA structures from isolates A/Vietnam/1203/04 and A/Vietnam/1194/04 ( H5N1 clade 1 ) [22] , [23] . Of the seven differing residues , 331 is in the polybasic cleavage site and is not present in the cleaved structures , 104 and 115 are within the vestigial esterase sub-domain in the RBD , and 131 , 142 , 216 , and 221 are within the receptor-binding sub-domain in the RBD ( Figure 5B , C ) . An overlay of the RBD , which includes the receptor-binding sub-domain and the vestigial esterase sub-domain , shows that the six varying residues induce no substantial differences in the α-carbon backbone structures of two prefusion HA strains ( Figure 5D ) . The RMSD values ( on α-carbons ) between the RBDs of MP HA and HP HA crystal forms 1 and 2 are 0 . 31 Å and 0 . 27 Å , respectively . The receptor-binding pocket residues had no differences in conformation between the MP and HP HA structures , and mutations at residues 131 and 142 distal to the receptor-binding pocket did not alter the backbone structure ( Figure S4 ) . The most significant differences occur between the two crystal forms of the HP HA protein , specifically , in the B loops of the HA2 stalk domain along with parts of the vestigial esterase sub-domain ( not including the 110-helix ) and the F' fusion sub-domain ( Figures 5C and S5A-C ) . Both crystal forms were grown in identical solutions at pH 6 . 6 , 0 . 9 pH units above its activation pH of 5 . 7 , but display different crystal-packing interactions in the B loop region . The HA2 B loops from H5N1 isolates VN1194 and VN1203 also adopt “in” and “out” forms , respectively ( Figure S5F ) , despite both proteins having identical residues in this region and their crystals being grown at similar pH values of 6 . 5 and 6 . 55 [22] , [23] . VN1203 , which adopts the “out” form in the absence of antibody , adopts the “in” form when bound to antibody [24] , [25] ( Figure S5F ) . Because the various prefusion H5N1 HA proteins adopt either “in” or “out” forms of the B loop in similar conditions and with little apparent structural consequence , the apparently flexible B loop may have little functional relevance in the prefusion conformation of H5N1 HA . Residues 216 and 221 in the receptor-binding sub-domain interact with residues in adjacent monomers across the RBD trimer interface ( Figure 5B ) . In MP HA , E216 makes a hydrogen bond with neighboring RBD backbone amide R212 ( Figure 6B ) , although this hydrogen bond is found only in two of the three E216 residues in the HA trimer . The lack of hydrogen bonding by the third E216 could be biologically relevant , helping to destabilize HA , or could be due to a crystallographic artifact . In HP HA , K216 makes a hydrogen bond with neighboring RBD backbone carbonyl N210 ( Figure 6B ) . We found that a K216E mutation increased the pH of activation of HP HA by 0 . 4 pH units ( Figure S2 ) . However , the presence of an E216 residue did not seem to have a dominant effect in the context of MP HA , which contains six other mutations and has an overall decreased pH of fusion compared to HP HA ( Figure 1 ) . Compared to P221 in MP HA , S221 in HP HA forms a hydrogen bond to the D241 side-chain in an adjacent monomer across the RBD-RBD interface ( Figure 6B ) . While one might have expected that a S221P mutation would destabilize HA by breaking a hydrogen bond and introducing a proline , we found that an S221P mutation had the opposite effect in the background of HP HA , decreasing the activation pH from 5 . 7 to 5 . 5 ( Figure S2A ) . Perhaps the rigidity of a proline at residue 221 stabilizes this region . It has been previously hypothesized for H5N1 and demonstrated for H3N2 ( X31 strain ) that HA stability is regulated by salt bridges across the RBD-RBD interface and that an alteration in HA stability may play a role in influenza virus infectivity [26] . In the present study , the structural and biochemical results on H5N1 mutations at residues 216 and 221 show that alterations in hydrogen-bonding interactions across the RBD-RBD interface also regulate H5N1 HA acid stability ( Figure 6B , S2 ) . The higher activation pH of HP HA compared to MP HA was largely mapped to differences in residues 104 and 115 ( Figure 3A ) , which are located at the N- and C-termini of the 110-helix in the vestigial esterase sub-domain of the RBD ( Figure 5 ) . In the prefusion conformation , the 110-helix in HA1 interacts with the interhelical B loops of two protomers in HA2 ( Figure 6A ) . Most notably , HA1 residues E107 and K109 in the 110-helix form salt bridges with HA2 residues R76 and E69 , respectively . This interaction may stabilize the metastable structure by preventing the B loops from springing out to their coiled-coil form or , alternatively , by stabilizing the RBD head domains to prevent their dissociation from the HA2 stalk after B loop structural changes are initiated by low pH [27] . These salt bridges are clearly important because E107 and K109 are more than 99 . 7% conserved amongst sequenced H5N1 HA proteins , and R76 and E69 are 100% conserved . The structures suggest that the sequence variations at residues 104 and 115 modulate the stability of the 110-helix and , consequently , the interactions between the 110-helix and the stalk domain . We hypothesize that the negatively charged D104 in HP HA forms less favorable interactions with the neighboring L73 at the top of the HA2 coil in the prefusion conformation than does the polar N104 in MP HA ( Figure 6A ) . T115 in MP HA forms a hydrogen bond with the backbone carbonyl oxygen of L111 , thereby capping and stabilizing the C-terminal end of the 110-helix . I115 in the HP HA does not form this hydrogen bond , and the stabilizing capping interaction is therefore absent . Overall , we suggest that the combination of D104N and I115T mutations found in MP HA promotes the stabilization of the 110-helix and thereby stabilizes the prefusion form of the HA protein , lowering its pH of activation and , consequently , attenuating the virus .
The goal of the current study was to understand how amino acid variations in the HA protein contribute to differences in pathogenicity between two H5N1 influenza virus isolates . Our analyses revealed that H5N1 pathogenicity in chickens correlates with the activation pH of the HA protein . Specifically , an increase in the pH of activation of the HA protein from 5 . 3 to 5 . 7 was associated with the greater pathogenicity of the A/chicken/Hong Kong/YU562/2001 isolate in chickens compared to the A/goose/Hong Kong/437-10/1999 isolate . Other factors are largely similar including their prefusion structures , expression levels , cleavage levels , and receptor-binding properties . We have also shown that naturally occurring mutations in the HA proteins of circulating H5N1 influenza viruses have altered the acid stability of the HA protein . Six of the 7 available HA protein sequences from H5N1 viruses sampled in 1999 ( Table 2 ) , including the MP 437-10 isolate , contain the N104 and T115 residues that we found to contribute to a reduced HA activation pH and reduced pathogenicity . In contrast , none of the available 2847 HA protein sequences obtained since 2000 contain the N104/T115 combination , whereas approximately 93% contain the D104/I115 combination found in the HP YU562 isolate that leads to an increased HA activation pH and increased pathogenicity . These epidemiological observations suggest that there has been a negative selection pressure against the N104/T115 combination of residues that are found in the MP virus that has prevented its propagation in avian species , and this may be related to the relatively low pH that is required to trigger membrane fusion . Here , we found that sequence variations in the RBD ( which includes the receptor-binding and vestigial esterase sub-domains ) do not alter the structure of the prefusion RBD but instead modulate the activation pH of the H5N1 HA protein . While such a phenotype may be unexpected , a D112G mutation in the HA2 stalk domain of A/Aichi/68 ( H3N2 ) has also been shown to alter HA acid stability yet involves only the replacement of the Asp sidechain with a water molecule at the mutation site , causing no detectable changes in the backbone or surrounding protein structure in prefusion HA [28] . Further evidence that the RBD forms a stable structure in the prefusion conformation is suggested by the fact that the isolated RBD from A/H1N1/2009 , E . coli-expressed and refolded [29] , has recently been shown to adopt the same fold [30] as the RBD in the intact , prefusion HA ectodomain [31] , [32] . The structures of a mutant H2N2 HA protein ( A/Japan/305/57 ) determined from crystals grown at pH 8 . 1 and 5 . 3 suggest that early structural changes in HA after acid activation include bulging out of the HA2 B loop and distortions in the HA1 vestigial esterase and F' fusion sub-domains ( Figure S5G-I ) [27] . These reversible structural changes were suggested to correspond to an early intermediate of the HA protein after acid activation and may help initiate global HA refolding . We also observed the two forms of the B loop , vestigial esterase sub-domain , and F' fusion sub-domain in the two different crystal forms of the HP A/chicken/Hong Kong/YU562/2001 ( H5N1 ) HA protein ( Figure S5A-C ) , although both H5N1 HA crystals were grown in identical solutions at pH 6 . 6 ( 0 . 9 pH units above its pH of activation ) . While the two HP H5N1 HA structures suggest that the observed differences in the B loops , vestigial esterase sub-domain , and F' fusion sub-domain in the prefusion structures reported here are due to differing crystallographic environments , it is possible that upon low-pH activation the H5N1 HA protein favors the “out” form of the B loop and pivoting of the F' fusion sub-domain similar to that which is observed when the H2 HA protein is exposed to acidic pH [27] . Mutations to amino-acid residues other than 104 and 115 can modulate HA protein activation and influenza virus pathogenicity . For example , in a proof-of-concept study , we recently showed that mutations to conserved residues in the stalk domain ( albeit , mutations that have not been observed in circulating H5N1 viruses ) alter HA acid stability and , as a result , modulate H5N1 replication , pathogenicity , and transmissibility in ducks [16] . In that study , recombinant A/chicken/Vietnam/C58/2004 ( H5N1 , clade 1 ) viruses containing HA proteins activated at pH values of 5 . 6 and 5 . 9 were highly virulent and transmissible in mallards , while those activated at pH values of 5 . 4 and 6 . 3 were avirulent and not transmissible . Taken together , our previous [16] and present data suggest that high levels of H5N1 influenza virus infection and pathogenicity in avian species may be supported by a relatively narrow range of HA protein activation pH values , minimally pH 5 . 6 to 6 . 0 . In general , opposing pressures may limit the activation pH of the HA protein to an optimal range that may shift depending on viral and host factors . A relatively low pH of HA protein activation would be needed to avoid inactivation in the environment or in mildly acidic tissues , whereas the activation pH would still need to be high enough to allow membrane fusion to occur before the virus is trafficked to the lysosome . Circumstantial and direct evidence support this notion . First , the acid stabilities of influenza virus HA proteins range from pH 4 . 6 to 6 . 0 and vary by subtype and host species [33] . Second , the adaptation of H3N2 viruses from eggs to mammalian cells [15] and of H7N3 viruses from ducks to turkeys [14] resulted in HA mutations that altered the acid stability of the HA protein . Third , in the presence of high concentrations of amantadine , a compound that raises endosomal pH , resistant variants of H3N2 , H7N1 , and H7N7 viruses have been selected that have increased HA activation pH values [34]–[37] . In the present work , a higher level of NA enzymatic activity contributed to an increase in the activation pH of the HA protein and was associated with greater virulence by HP YU562 virus compared to MP 437–10 virus . Compared to expression of HA alone , coexpression of NA together with HA has previously been shown to increase the pH of activation of the H5N1 HA protein by 0 . 5 pH units in the absence but not the presence of the NA inhibitor oseltamivir [16] , further demonstrating a link between NA activity and destabilization of the HA protein . The mechanism by which NA enzymatic activity augments HA protein fusogenic activity is unknown; however , cleavage of sialic-acid containing N-linked glycosylation sites on the HA protein may decrease the energy required to trigger HA conformational changes by destabilizing the prefusion form of individual HA trimers . Alternatively , enhanced cleavage of HA glycosylation sites could potentially promote the synchronized activation and refolding of adjacent , interacting HA trimers [38] . Increased NA enzymatic activity could also reduce interference that would occur if HA trimers bound to other HA trimers , NA proteins , glycoproteins , or glycolipids . However , a very large reduction in NA enzymatic activity might be needed to cause such interference in the first place . The importance of glycosylation sites in regulating HA activation and influenza virus replication has been demonstrated previously for A/FPV/Rostock/34 ( H7N1 ) , whose HA protein is destabilized by the removal of glycosylation sites in the stalk domain [39] . Complementation of HA protein fusogenic activity by NA enzymatic activity may depend on influenza virus subtype . For example , NA co-expression resulted in increased membrane fusion by the HA proteins from HPAI H7N4 and human H1N1 influenza viruses [20] , while the addition of exogenous neuraminidase had no effect on membrane fusion mediated by human H2N2 and H3N2 HA proteins but instead led to an increase in receptor-binding activity by HA [40] , [41] . Influenza virus pathogenicity is a polygenic trait that is modulated by a combination of viral and host factors [1] , [6] , [7] . Although an optimal activation pH of the HA protein appears to be necessary for high pathogenicity by H5N1 influenza viruses in avian species , we do not expect it to be sufficient to promote high pathogenicity in the absence of a polybasic cleavage site , host-appropriate receptor-binding specificity , or an efficient polymerase . Moreover , if the optimal activation pH differs between avian and mammalian species , additional studies will be needed to determine whether alterations in HA acid stability may contribute to the pandemic potential of H5N1 influenza viruses .
HA genes from A/goose/Hong Kong/437-10/1999 ( MP ) and A/chicken/Hong Kong/YU562/2001 ( HP ) H5N1 influenza viruses were cloned into pHW2000 , pCAGGS , and pAcGP67B plasmids as described previously [16] , [19] , [22] . Point mutations were introduced by QuickChange mutagenesis ( Stratagene ) . Monolayers of Vero or BHK-21 cells at 70% to 80% confluency in 6-well plates were transiently transfected with pCAGGS HA ( 1 . 0 µg ) and pCAGGS NA ( 0 . 1 µg ) plasmids by using a Lipofectamine Plus expression system ( Invitrogen ) [19] . After 4 hours at 37°C , the transfection medium was replaced with DMEM containing 10% fetal bovine serum ( and 1% glutamine for BHK-21 cells ) , and cells were incubated for 16 h at 37°C . Biochemical analyses were performed as described previously [19] . Briefly , HA proteins were resolved on 4-12% NuPAGE BisTris polyacrylamide-SDS gels ( Invitrogen ) and visualized on a Typhoon 9200 imager ( GE Healthcare , Waukesha , WI ) . HA surface expression was determined by using flow cytometry with the primary monoclonal HA antibody Vn04-02 ( 1∶2000 ) and fluorescein-conjugated , AffiniPure donkey anti-mouse IgG ( H+L , Jackson Immuno Research , West Grove , PA ) secondary antibody . The pH of HA conformational changes ( to 0 . 1 pH resolution ) was determined by using flow cytometry and monoclonal antibodies Vn04-09 and Vn04-16 , which preferentially bind to the prefusion and postfusion HA forms , respectively [21] . To determine the pH of membrane fusion , BHK-21 cell monolayers were transfected with pCAGGS HA and pCAGGS NA plasmids as described above or infected with viruses at an MOI of 3 PFU/cell . At 16 h posttransfection or 6 h postinfection , cells were washed and overlaid with PBS+ ( PBS containing calcium and magnesium at 0 . 1 g/liter ) with the pH adjusted to 0 . 1 resolution with 0 . 1 M citric acid . The pH of fusion was expressed as the highest pH at which syncytium formation was observed . Sixteen hours after transfection , monolayers of Vero cells were washed twice with PBS+ , overlaid with 1% chicken or turkey erythrocytes , and incubated at 37°C for 30 min . Monolayers were then washed 3 times with DMEM ( phenol red-free ) to remove unbound red blood cells and lysed with 1X RBC lysis buffer ( eBioscience ) . The amount of bound erythrocytes was determined by measuring the absorbance of clarified lysate at 415 nm by using a Synergy-2 Multi-mode microplate reader ( BioTek , Winooski , VT ) . NA enzymatic activity was determined by using a fluorescence-based NA assay with methyl umbelliferone N-acetyl neuraminic acid ( MUNANA; Sigma , St Louis , MO ) as a substrate ( final concentration of 100 µM ) [42] . Fluorescence due to release of 4-methylumbelliferone was measured by using a Synergy-2 Multi-mode microplate reader . The enzyme activity of transiently expressed NA was determined as the quantity ( pmol ) of 4-methylumbelliferone sodium salt ( Sigma ) generated during a 30 min incubation at 37°C and was standardized to 0 . 1 mg total protein by using a bicinchoninic acid assay ( Sigma ) . The NA enzyme activity of varying titers of HP and MP viruses was standardized to the relative PFU/mL titers . Purified ectodomains of the HP and MP HA proteins were prepared as described previously [22] using a baculovirus expression system ( BD Biosciences ) and Sf9 insect cells . Secreted HA ectodomains were purified by metal affinity chromatography followed by thrombin digestion of the purification tag . Trypsin was used to cleave HA into the active HA1/HA2 form . HA proteins were further purified by size-exclusion chromatography and concentrated to 1 . 4 mg/mL ( MP HA ) or 3 . 0 mg/mL ( HP HA ) . HA protein crystals were grown by the hanging-drop vapor diffusion method at 18°C . MP HA crystallized in a well solution of 23% PEG 3350 and 0 . 1 M Tris-HCl , pH 8 . 5 . From HP HA , two crystal forms were obtained in the same crystallization conditions ( 1 . 62 M ammonium sulphate , 0 . 1 M sodium cacodylate , pH 6 . 6 ) . Crystals were transferred to a well solution containing 25% glycerol ( MP HA ) or 25% ethylene glycol ( HP HA ) for 1–2 minutes before freezing in liquid nitrogen . Diffraction data were collected at cryogenic temperature at X-ray wavelength 1 . 00 Å from the Southeastern Regional Collaborative Access Team's 22-ID and 22-BM beamlines at the Advanced Photon Source ( Argonne National Laboratory , Chicago , IL ) . Data processing and reduction was completed by using HKL-2000 software [43] . HA ectodomain structures were determined by molecular replacement using the program Phaser [44] . From HP HA crystal form 1 , a solution was obtained by using a single HA protomer from the crystal structure of the HA from H5N1 A/Vietnam/1203/2004 ( PDB entry 2FK0 ) . For MP HA , the HP HA crystal form 1 structure was used as a molecular replacement model . For HP HA crystal form 2 , the best molecular replacement solution was obtained by using a single HA protomer from MP HA's crystal structure . Model building was performed by using Coot [32] followed by iterative rounds of simulated annealing using Phenix [45] and restrained refinement using the CCP4 software suite's REFMAC5 [46] . Refinement was monitored by following the Rfree value calculated for a random subset ( 5% ) of reflections omitted from refinement . The final models were validated by using MolProbity [47] and are numbered according to H3 numbering based on the crystal structure of A/Vietnam/1203/2004 H5 HA ( PDB entry 2FK0 ) . We used the H3 numbering scheme in this manuscript , which differs from the H5 numbering that was used previously [17] . After simulated annealing of HP HA crystal form 2 , the electron density for the region of the stalk domain that is closest to the viral membrane was very poor due to irregular crystal packing within this region . The structural model of HP HA crystal form 2 was guided by B-factors: residues with B-factors higher than 90 were not included in the model . The final model of HP HA crystal form 2 contains HA1 residues 43–312 and HA2 residues 59–101 ( H3 numbering ) . HA protein sequences published between 1996 and 2011 ( as of May 2011 ) were obtained from NCBI's Influenza Virus Resource database ( http://www . ncbi . nlm . nih . gov/genomes/FLU/ ) . Laboratory sequences or sequences that did not cover the amino-acid positions of interest in this study were excluded . Sequences were aligned by using the ClustalW tool included in BioEdit v7 . 0 . 9 [48] . The frequencies of amino-acid residues were calculated for HA1 positions 104 , 107 , 109 , and 115 and HA2 positions 73 , 69 , and 76 ( in H3 numbering ) . | To deliver their genomes into host cells during entry , enveloped viruses contain glycoproteins that bind to cellular receptors and cause fusion of viral and cellular membranes . The influenza virus HA protein is the archetypal viral fusion glycoprotein , promoting entry by undergoing irreversible structural changes that drive membrane merger . HA trimers on the surfaces of infectious influenza virions are trapped in a metastable , high-energy conformation and are triggered to refold and cause membrane fusion after the virus is internalized and exposed to low pH . Here , we provide biochemical and x-ray crystallographic evidence that naturally occurring amino-acid variations at the interface of the vestigial esterase and fusogenic stalk domains alter HA acid stability for highly pathogenic H5N1 influenza , resulting in a shift in the threshold pH required to activate HA protein structural changes that cause membrane fusion . Furthermore , our data reveals that an increased HA activation pH correlates with increased H5N1 virulence in chickens . Overall , the acid stability of the HA protein is identified as a novel virulence factor for emerging H5N1 influenza viruses . A major implication of this work is that the fitness of enveloped viruses may be fine-tuned by mutations that alter the activation energy thresholds of their fusion glycoproteins . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [
"medicine",
"influenza",
"microbiology",
"viral",
"structure",
"membrane",
"proteins",
"protein",
"structure",
"infectious",
"diseases",
"cell",
"membrane",
"cytochemistry",
"proteins",
"biology",
"pathogenesis",
"biochemistry",
"virology",
"viral",
"diseases"
] | 2011 | Acid Stability of the Hemagglutinin Protein Regulates H5N1 Influenza Virus Pathogenicity |
The Pol32 protein is one of the universal subunits of DNA polymerase δ ( Pol δ ) , which is responsible for genome replication in eukaryotic cells . Although the role of Pol32 in DNA repair has been well-characterized , its exact function in genome replication remains obscure as studies in single cell systems have not established an essential role for Pol32 in the process . Here we characterize Pol32 in the context of Drosophila melanogaster development . In the rapidly dividing embryonic cells , loss of Pol32 halts genome replication as it specifically disrupts Pol δ localization to the nucleus . This function of Pol32 in facilitating the nuclear import of Pol δ would be similar to that of accessory subunits of DNA polymerases from mammalian Herpes viruses . In post-embryonic cells , loss of Pol32 reveals mitotic fragile sites in the Drosophila genome , a defect more consistent with Pol32’s role as a polymerase processivity factor . Interestingly , these fragile sites do not favor repetitive sequences in heterochromatin , with the rDNA locus being a striking exception . Our study uncovers a possibly universal function for DNA polymerase ancillary factors and establishes a powerful system for the study of chromosomal fragile sites in a non-mammalian organism .
Genome replication is of paramount importance to life . Although we have ample understanding of the biochemistry of DNA replication at the molecular level , the complexity of replication regulation is much less understood . In particular , the functions of proteins deemed “ancillary factors” are less understood than those of the catalytic components of the DNA replication machinery . The importance of understanding the functions of these factors is highlighted by the remarkable finding that the yeast Pol δ catalytic enzyme can be functionally replaced in vivo by a viral polymerase provided its C-terminal domain retains efficient interactions with ancillary replication factors [1] . Understanding such regulatory roles is also important for improving human health , as while a loss of replication capacity is often lethal , defective regulation might be more compatible with various disease states including cancer . The importance of studying cellular responses to non-lethal perturbation of DNA replication ( or replication stress ) is further emphasized by the results from recent cancer etiological studies suggesting that the majority of pathological mutations likely occurred under normal or near normal DNA replication conditions [2 , 3] . One of the consequences of perturbing replication is the formation of chromosomal fragile sites [reviewed in 4] . These fragile sites appear as visible gaps or constrictions on mitotic chromosomes formed under replication stresses , and can be a source of genome instability by , e . g . , initiating aberrant recombination . Mammalian studies have uncovered detailed features of chromosome fragile sites . Many genomic regions generally considered “hard-to-replicate” , such as repetitive sequences with a tendency to form secondary structures , are more sensitive to replication stress [e . g . 5–7] . Several large genes with complex transcription and replication patterns are common fragile sites in mammals [reviewed in 8 , 9] . The extent to which the features of mammalian fragile sites are conserved through evolution remains unclear , as is the case for common molecular characteristics of fragile sites in yeast [10] . Therefore , more experimental systems are needed for the study of fragile sites to uncover their most fundamentally conserved mechanistic and phenomenological characteristics . DNA polymerase δ is one of the major genome-replicating machineries in eukaryotes . Its subunit composition is highly-conserved from yeast to mammals , including minimally the catalytic subunit PolD , a “structural” subunit of Pol31 and an “ancillary” subunit of Pol32 [for reviews on DNA pol δ , see 11–13] . Although Pol32 is biochemically defined as a processivity factor of Pol δ , ensuring maximal DNA synthesis efficiency of the complex [14–16] , the necessity for Pol32 in genome replication could not be established in multiple organisms . Contrary to pol3 ( S . cerevisiae polD ) or pol31 , deletion of pol32 is not lethal in budding yeast , although pol32 mutants are sensitive to exogenously applied replication stresses [17] . In fission yeast , deletion of cdc27 ( S . pombe pol32 ) is lethal due to defective chromosome segregation but nonetheless does not lead to gross defects in genome replication [18 , 19] . More strikingly , chicken DT40 cells homozygous for a polD3 deletion are viable and exhibit a normal cell cycle profile ( PolD3 and p66 are names given to Pol32 homologs in higher eukaryotes ) [20] . Furthermore , human cells can sustain a significant knockdown of PolD3 level without apparent effects on DNA replication [21 , 22] . However , mouse knockout mutations of polD3 were shown to cause embryonic lethality , and conditional reduction of polD3 in adult B cells and embryonic stem cells caused defects in BrdU incorporation and cell cycle progression [23 , 24] . As no clearly consistent trend is discernible , results from all these studies suggest that a comprehensive understanding of Pol32 needs to involve an analysis of cell type and developmental stage in dissection of its function . A role for Drosophila Pol32 in DNA repair has been previously characterized [25] , and another study revealed that Pol32 is essential for the prevention of chromosome breakage in proliferating cells [26] . Whether Pol32 is required for genome replication has not been investigated in Drosophila . Here we showed that Pol32 is absolutely required for genome replication during the earliest cell cycles , and this function is endowed by Pol32’s ability to facilitate nuclear localization of the Pol δ complex . However , in post-embryonic cells , loss of Pol32 does not block genome replication but instead sensitizes cells to the formation of chromosomal fragile sites . Although a significant portion of the breaks happen in regions enriched with repetitive sequences , these regions are not particularly favored for fragile site formation , with the rDNA locus being the one clear exception .
An important role of Pol32 in DNA double strand break ( DSB ) repair in Drosophila was established using mutant alleles that we generated [25] . What we also observed but did not report in depth at the time , was somatic phenotypes of pol32 homozygotes . Mutant adults express a variable degree of bristle loss or shortening ( S1 Fig ) , and females are sterile while males are fertile . These somatic phenotypes are similar to those reported in a previous study of pol32 in Drosophila [26] . We noticed that pol32 homozygous females lay eggs that do not hatch . We hereafter refer these as pol32-mutant embryos even though they are genotypically heterozygous as they had wild type fathers . To assess embryonic development of pol32-mutants , we DAPI-stained whole-mount embryos and discovered that they were fertilized but that no embryo ( N>1000 ) had more than 8 foci of DAPI-bright material ( Fig 1A ) , indicating that these embryos were arrested very early in development . In Drosophila , the first 13 cell cycles rely solely on maternally supplied protein and RNA molecules . Loss of Pol32 causes maternal effect lethality , which suggests that the presence of maternally deposited Pol32 protein is essential for embryonic development , possibly by ensuring genome replication . We isolated total DNA from 0–2 hr embryos collected from either wild-type or mutant females , digested the two samples with EcoRI , and electrophoretically separated them on an agarose gel . The DNA sample from the mutants revealed a distinct set of four bands , an interesting pattern that is different from the smeary appearance of digested wild-type DNA ( Fig 1B ) . This pattern of EcoRI digestion is consistent with that the DNA extracted from mutants consisting mostly of mitochondrial DNA , based on known sequence of the Drosophila mitochondrial genome [27] . To confirm this hypothesis , we subjected these DNA samples to whole genome sequencing , and found that about 90% of the reads from the mutant sample are mapped to the mitochondrial genome , whereas that number was less than 4% for DNA extracted from the wild-type sample ( Fig 1C ) . We therefore conclude that there is very limited genome replication in pol32-mutant embryos , strongly suggesting that Pol32 is critically required for nuclear replication during early development . We generated an antibody against Drosophila Pol32 . This antibody recognizes a protein band on Western blot from wild-type but not pol32 mutant tissues ( S2A Fig ) confirming its specificity , although the observed size of Pol32 protein is around 65 KD , larger than the predicted size of 47 KD . Interestingly , the mammalian Pol32 homolog PolD3/p66 has an estimated size of 66 KD on an SDS-PAGE gel , also larger than the predicted size of 51 KD [28] , and S . pombe Cdc27 migrates slower than the expected size [15] . The cause for this common behavior of Pol32 proteins is not known . To better understand the developmental regulation of Pol32 , we performed immunostaining on some of the replicating tissues using this antibody . During oogenesis , Pol32 is ubiquitously present in the nucleus . In particular , polyploid nurse cells have abundant Pol32 ( Figs 2A and S2B ) . Pol32 is also present in the nuclear space of the oocyte ( Fig 2A ) , confirming that Pol32 is maternally deposited . Since the pol32 mutant phenotype manifests most strongly during early development , we next focused our study of Pol32 localization on early embryos . During the very first cell cycle when the male and female pronuclei fuse , Pol32 was associated with the parental nuclei as well as the three nuclei that eventually give rise to the polar body ( Figs 2B and 3 ) . Mutant embryos showed no anti-Pol32 signals ( Fig 3 ) , again confirming the specificity of our antibodies . Interestingly , wild-type nuclei with condensed chromosomes lack Pol32 signal , suggesting that Pol32 accumulation is associated with ongoing genome replication ( Fig 2B ) . Consistent with this , Pol32’s nuclear localization is phasic during the later cell cycles in the embryo . Pol32 accumulates in the nucleus during interphase but disperses into the cytoplasm at the onset of mitosis ( Fig 2C ) . We cannot exclude the possibility that some of the Pol32 is degraded during the mitotic program such that the level of Pol32 protein further fluctuates throughout the cell cycle . Since Pol32 is a subunit of the Pol δ enzyme complex , we were interested in the localization of the other subunits . We generated antibodies against PolD and Pol31 , and observed a very similar localization pattern to that of Pol32 in the early embryonic cycles ( S3 Fig ) . Thus , the cellular localization of multiple components of the Pol δ complex is consistent with its molecular role in genome replication . The lack of genome replication in pol32-mutant embryos , produced by pol32 homozygous mothers , is in sharp contrast to the survival of pol32 homozygous animals . We set out to better understand the underlying cause for embryonic lethality by localizing protein factors known to participate in genome replication with antibodies . As pol32-mutant embryos arrest very early in development , we focused our attention on the gonometric first zygotic division at the time when the juxtaposing parental pronuclei and the three polar body nuclei are undergoing replication . As shown in Figs 2B and 3 , Pol32 is abundantly present in those five haploid nuclei . As expected , both PolD and Pol31 are also present ( Fig 3 ) . Remarkably , neither is present at similarly staged nuclei in pol32-mutant embryos ( Fig 3 ) . We first ruled out that this lack of localization was due to the absence of the proteins of interest in the embryos . In the Western blots shown in Fig 4A , both maternal PolD and Pol31 are present at a similar level to those in wild-type embryos . Secondly , we determined that this localization defect induced by the loss of Pol32 is specific to Pol δ as the localization of PCNA , a replication factor interacting with all three subunits of Pol δ in yeast [19 , 29] , was not affected ( Fig 3 ) . Moreover , the localization of the catalytic subunit of DNA polymerase α ( Polα ) , which is required for initiating genome replication [30] , was not affected by the lack of maternal Pol32 either ( Fig 3 ) . Therefore , loss of maternal Pol32 specifically inhibits the nuclear localization of the Pol δ complex . We also investigated the effect of pol32 mutations on PolD location in post-embryonic cells . We have chosen polytene cells in the salivary glands of third instar larvae and cells in the adult ovary for our investigation as PolD is present in these cells under normal conditions ( Fig 5 ) . In pol32 mutants , PolD is also present in the nucleus ( Fig 5 ) , which is expected since pol32 homozygous mutants are viable with largely normal development . Interestingly , PolD is prominently missing from the nucleus of the mutant oocyte ( enlarged image in Fig 5B ) , reminiscent of the situation in early embryos ( Fig 3 ) . This observation further strengthens our conclusion that the nuclear localization of the maternal PolD complex requires Pol32 . To facilitate the identification of specific Pol32 domains required for its function , we set out to investigate the physical interactions among Pol δ subunits by immunoprecipitation ( IP ) using extracts from early embryos . As shown in Fig 4B , we detected interactions between Pol32 and PolD , Pol32 and Pol31 , and PolD and Pol31 , consistent with a hetero-trimeric complex . Interestingly , in the absence of Pol32 , Pol31 remains capable of interacting with PolD ( Fig 4B ) . To identify specific protein interactions that might be responsible for facilitating Pol δ localization we generated point mutations , individually disrupting three known protein domains of Pol32 that interact with other replication factors ( Fig 6A ) . In yeast and mammals , the Pol31-interacting region has been mapped to a winged helix-turn-helix ( wHTH ) domain at the N terminus of Pol32 [31–33]; a Polα-interacting DPIM domain has been mapped to a C-terminal region [34] , and lastly a PCNA-interacting PIP box has been mapped to the C-terminus of Pol32 [19] . We constructed a genomic fragment from the pol32 locus and were able to rescue the phenotypes of the mutants using this gene fragment as a rescuing transgene . Starting with this construct , we introduced small deletions or residue changes to the three domains of interest ( Fig 6A ) , and transformed these constructs individually into a pol32 mutant background and tested the effects on the bristle and fertility phenotypes . As summarized in Fig 6A and shown in S1 Fig , all gene constructions except those disrupting wHTH were able to rescue both defects , while mutations of wHTH failed to rescue either . In embryos produced by females with the wHTH mutations , PolD protein remains at or near its normal level ( Fig 6B ) . These results strongly suggest that the wHTH domain , important for Pol32-Pol31 interaction , is required for Pol32 function in both embryonic and post-embryonic somatic cells . Interestingly , the wHTH-mutated Pol32 protein was produced at a greatly reduced level ( Fig 6B ) , suggesting that the mutant protein is unstable possibly due to its inability to interact with Pol31 . Consistent with this hypothesis , when we reduced Pol31 level in post-embryonic cells with RNAi ( see Materials and Methods ) , we observed a concomitant reduction of the otherwise normal Pol32 protein ( Fig 6C ) . Alternatively , the instability of the wHTH-mutated Pol32 protein could be due to the missing of a few residues critical for its stability , we are currently unable to distinguish between these two hypotheses . As shown previously by Tritto et al . [26] , larval neuroblasts of pol32 mutants exhibit spontaneous chromosome breaks . We confirmed that result using our pol32 alleles . From analyzing mitotic chromosome preparations of mutant nuclei , we discovered that 7 . 7% of the mutant nuclei harbored at least one DSB ( n = 766 ) compared with less than 1% of the wild-type nuclei ( n = 2004 ) . We noticed a seemingly non-random distribution of DSBs on mitotic chromosomes of pol32 mutants . To facilitate the identification of putative “hot spots” for DSB formation , we took advantage of a sensitized background that greatly increases DSB frequency in pol32 mutants . As described in the next section , we discovered a genetic interaction between components of the Pol δ complex with Pol32 . In particular , a heterozygous polD mutation exacerbates the phenotypes of pol32 homozygotes including the frequency of DSB in larval neuroblasts . With this sensitized background , we observed 30 . 6% of the nuclei having at least one DSB ( n = 1375 , Fig 7B ) . We loosely defined genomic regions on the mitotic chromosomes as “centric” and “non-centric” according to prior cytological studies of mitotic chromosomes in Drosophila [e . g . , 35–37] . In brief , the centric domain consists of the centromere constriction , DAPI-bright regions next to the centromere , and the adjacent regions where the sister chromatids remain tightly synapsed . These “centric” regions are generally considered heterochromatin , and the remaining “non-centric” regions are considered gene-rich euchromatin in the genome . Fig 7A shows representative mitotic figures with DSBs in each type of chromatin and on every major chromosome . DSBs of the two different regions were then quantified for each chromosome except the Y or the 4th chromosomes ( Fig 7B; n = 286 for DSB on X; n = 132 for DSB on II; n = 179 for DSB on III ) . We discovered that about 70% of the X chromosomal DSBs could be defined as “centric” . The frequencies are 42% and 54% for chromosomes 2 and 3 respectively . We did not include the Y chromosome in our DSB analyses basing on the rationale that highly condensed heterochromatic regions of the Y chromosome might assume the appearance of DSBs [e . g . , 38] , biasing our quantification . Nevertheless , we did observe mitotic figures showing clearly broken Y chromosomes ( Fig 7Al ) . We did not quantify DSBs on chromosome 4 due to its small size and the consequent difficulty in identifying DSBs cytologically . Therefore , we have established an effective way to generate DSBs induced by replication stress and started to define basic features for them . pol32-mutant adults often express missing , thinning or shortening of large bristles sometimes accompanied by etching of the abdomen ( disruption of the normal abdominal pattern owing to cuticular herniations ) . Some examples are shown in Figs S1 and 8 . This is reminiscent of the classic “bobbed” phenotypes caused by loss of copies of the ribosomal RNA gene ( rDNA ) repeats [39] , and suggesting that the rDNA locus might be experiencing high incidence of instability in pol32-mutant cells . The rDNA loci reside on the X and Y chromosomes in Drosophila . We thus carried out a more focused quantification of X chromosome DSBs . The effect of pol32 on the stability of the rDNA array on the Y chromosome was assayed differently and will be described in a later section . The major components of the X centric region are two large blocks of repetitive sequences: the rDNA locus about 3 Mb in size and the more centromere-proximal 359 satellite about 11 Mb in size . We made fluorescent probes to each region and used them in FISH experiments to categorize DSBs on the X chromosome . We again used the sensitized background of pol32 homozygosity with a heterozygous polD mutation . Out of 332 nuclei with a complete karyotype and FISH signals , we identified 41 breaks in the rDNA locus and 16 DSBs in the 359 repeats . Representative FISH images are shown in Fig 7C . Therefore , under the genetic background in our study , about 1 in 6 ( 57/332 ) larval neuroblasts experienced a DSB at the X peri-centromeric region . Because we could now definitively identify some of the DSB sites using FISH , we were able to further characterize the 286 DSBs that we previously identified on the X chromosome ( Fig 7B ) by comparing the patterns of DAPI and FISH signals . We observed two classes of “centric” DSBs on X . The first class of DSBs lies in the DAPI bright block ( for a representative mitotic figure see Fig 7Af ) . This class accounts for 20 . 6% ( 59/286 ) of all X DSBs . Now FISH analyses clearly show that they happened within the 359 repeats ( Fig 7Cd ) . The second class of DSBs happened in the region right next to the DAPI bright block where the sister chromatids tightly synapse ( Fig 7Ad and 7Ae ) . This class accounts for 49 . 0% ( 140/286 ) of all X DSBs . Our FISH data suggest that most , if not all , of this class of DSBs represent breaks of the rDNA locus ( Fig 7Cb and 7Cc ) . Therefore , almost half of X breaks were at rDNA . In addition to abundant DSBs involving rDNA , we also observed instances in which the broken ends of the rDNA locus joined with other broken ends giving rise to genome rearrangements ( Fig 7Ce ) , and instances in which the rDNA array appears expanded ( Fig 7Cf ) . To further quantify the damage to the rDNA loci and to prove that rDNA instability is not limited to the array on the X chromosome , we made the Y chromosome the sole source of rDNA in pol32 mutants by introducing the pol32 mutation into a C ( 1 ) DX , rDNA0/y+Y10B background . The former chromosome ( compound X ) lacks all rDNA and the latter ( Y ) possesses a well-characterized rDNA array [40] . We extracted genomic DNA from females ( C ( 1 ) DX/Y ) of both pol32 mutants and pol32/+ siblings . The pol32 mutants had 57 . 0% ( ±11 . 4% ) the rDNA copy number as did their heterozygous siblings . This amount ( about 60% of the normal level ) roughly corresponds to the threshold between the extreme-bobbed/bobbed-lethal boundary , suggesting that the surviving pol32 flies have as little rDNA as can sustain development . Despite the overall loss of rDNA , when compared to total rDNA copy number , mutants had 3 . 2 times as many rDNA-resident R1 retrotransposons and 1 . 5 times as many R2 retrotransposons as did their heterozygous siblings . The R1 and R2 elements are generally kept silent in the rDNA arrays [41 , 42] , and we suggest that the preferential loss of rDNA copies uninterrupted by R1 or R2 indicates that the loss due to the pol32 mutations involves active rDNA arrays . Therefore , in a replication compromised background , both of the rDNA loci experience a high rate of instability . Although it is likely that defective replication is the primary cause for the spontaneous DSBs that we observed in the mutants , it is possible that another significant cause is the loss of repair capacity as Pol δ is important in DSB repair [e . g . , 43] . To shed more light onto the primary cause ( s ) , we conducted a genetic interaction study of pol32 with mutations in other replication and DNA repair factors . Our assay was based on the etching of the abdominal region of pol32 adults ( Fig 8A ) . We observed pol32 homozygotes with etched abdomen at a low frequency: 0 . 5% of the adults displayed the phenotype . This was increased to 93 . 7% when a copy of the polD gene was also mutated ( homozygous for pol32 but heterozygous for polD ) , and 51 . 3% when we deleted a copy of the pol31 gene ( homozygous for pol32 but heterozygous for pol31 ) . Interestingly the strength of the genetic interactions between pol32 and pol31 appears proportional to the strength of the heterozygous mutations , as a hypomorphic pol31 mutation ( a homozygous viable mutation with a P element insertion at the 5’UTR of pol31 ) had a weaker enhancing effect ( from 0 . 5% to 10 . 6% ) than a complete deletion of pol31 ( from 0 . 5% to 51 . 3% ) . These results indicate a strong genetic interaction between Pol δ subunits . Using the same assay , we tested mutations in polα , and observed a similar enhancement . Interestingly , when we tested two other factors with important roles in DNA repair , mus309 encoding the Drosophila homolog for the Bloom RecQ helicase [44] and spnA encoding the Drosophila homolog for the Rad51 strand annealing protein [45] , we obtained weaker enhancement of the pol32 phenotype ( Fig 8B ) . Alleles used for mus309 and spnA were previously shown to be strong , if not complete , loss of function alleles [44 , 46] . As shown in the previous section , the strong interaction between pol32 and polD reflects well the frequency of spontaneous DSBs such that the polD mutation also enhances DSB formation frequency in pol32 homozygotes ( Fig 7B ) . Therefore , our cytological and genetic results combined suggest that DSB formation in a pol32 mutant background is largely due to a defect in genomic replication , and less so DSB repair .
We discovered that although Pol32 is not essential for organismal survival , the maternal pool of Pol32 protein is absolutely required for early embryonic development . The early embryonic arrest phenotype is associated with a severe defect in whole genome replication so that as much as 90% of the total embryonic DNA present is of mitochondrial origin . Analysis of our sequencing data did not identify specific regions of the genome that are less represented in mutants , suggesting that the disruption of replication is genome-wide . This is the most severe replication defect ever reported for pol32 mutants in any system . The cessation of replication is associated with a severe disruption of the localization of PolD and Pol31 proteins , the remaining subunits of the polymerase complex . This nuclear localization defect occurs during the earliest zygotic DNA replication , was not the result of protein instability , and is specific to the Pol δ complex . Therefore , Pol32 is required for Pol δ localization during early embryonic development . In post-embryonic cells , however , this requirement is much less stringent . Although pol32-mutant cells show spontaneous DSBs , a consequence of sub-optimal replication function , they are nevertheless proficient in tissue proliferation suggesting that the Pol32-less complex retains substantial function including the ability to enter the nucleus , a proposition supported by our immunostaining results . As we discuss below that there might be redundant mechanisms controlling the nuclear transport of PolD , a systematic approach is therefore required to determine whether Pol32 is at all required for the normal nuclear localization of Pol δ in post-embryonic cells . It is also of great interest to further understand the striking differences displayed between embryonic and post-embryonic cells in response to the loss of Pol32 . We have devised a speculative model for Pol32 functions ( Fig 9 ) . We propose that Pol32 fulfills two separable functions: a factor facilitating the nuclear localization of Pol δ , and a processivity factor for efficient catalytic activity of Pol δ . This proposed dual function of Pol32 is similar to those assigned to viral replication factors from certain mammalian viruses . The genomes of viruses of the Herpesvirdae family , and similar viruses of other mammalian hosts , are replicated by a set of viral factors that include a two-subunit DNA polymerase . In this complex , the polymerase catalytic subunit is accompanied by an ancillary factor , such as the UL42 protein of the HSV-1 virus , UL44 of HCMV , BMRF1 of EBV and ORF59 of KSHV [for a review on viral polymerases see 47] . The ancillary factor greatly increases the processivity of the catalytic enzyme in vitro [e . g . , 48 , 49] , similar to results from studying Pol32 . Interestingly , these viral replication processivity factors also regulate and sometimes control the nuclear import of the polymerase complex [reviewed in 50] . The processivity factors can be classified into two classes in terms of how they participate in the nuclear import of the polymerase complex . In one class , exemplified by UL42 and UL44 , the processivity factor as well as the catalytic subunit harbor functional nuclear localization signals . Each mediates nuclear import of the complex in a redundant fashion [51–53] . In the other class , exemplified by BMRF1 and ORF59 , only the processivity factor has a functional nuclear localization signal ( s ) and is solely responsible for importing the entire complex into the nucleus [54–56] . Therefore , Pol32 is similar to the first class of viral processivity factors , as the Pol δ complex is capable of entering the nucleus without Pol32 in single cell systems such as yeast , chicken cells , cultured mammalian cells , and in post-embryonic cells of mice and flies . The striking exception is early embryonic cells of Drosophila , and possibly mouse , in which Pol32 is vitally required for nuclear import . This might reflect the specialized replication program in early divisions . Interestingly , partial loss of function mutations in other Drosophila replication factors can cause maternal effect embryonic lethality similar to pol32 [e . g . 57] . The viral processivity factor mediates nuclear import via conventional importin-based mechanisms [e . g . , 51 , 52 , 58] . This might also be the case for Pol32 function . It would be even more interesting that the stringent requirement for Pol32 in embryos be based on cell-type specific interaction between Pol32 and the nuclear import machinery . A functional nuclear localization signal ( NLS ) has been identified for human p66 [59] , and we identify a putative NLS in Drosophila Pol32 based on the mammalian finding . We predict that the disruption of this NLS would reproduce the embryonic phenotypes similar to that caused by the current pol32 mutations . The model in Fig 9 also indicates that the processivity function of Pol32 , possibly combined with a defect in Pol δ nuclear import , can explain the appearance of DSBs in mutant somatic cells . There is likely contribution from defects in DNA repair in the mutant as Pol32 is also a subunit of DNA polymerase ζ [11 , 13] , which is essential for DNA repair in Drosophila [25] . Chromosomal fragile sites ( CFS ) , also called Common Fragile Sites , represent genomic regions with the propensity to break under replication stress [for a recent review of CFS see 60] . CFS are best studied in mammalian systems in which “difficult-to-replicate” regions of repetitive sequences capable of forming secondary structures and regions with the likelihood of collisions between replication and transcription machineries are CFSs [reviewed in 61–63] . We established a genetic background in which a cell’s replication efficiency was reduced so that 30% of proliferating cells possess at least one chromosome break . Remarkably , animals of such genetic makeup survive to adulthood . With this abundance of DSBs , we were able to detect some interesting features about the classes of DSB that arose as a result of replication inefficiency . We classified CFS into centric and non-centric classes . The regions that we defined as “centric” fit the general description of heterochromatin on mitotic chromosomes [35 , 37 , 64] . Approximately one-third of the Drosophila genome can be classified as “heterochromatic” [65 , 66] . Yet centric DSBs that we observed account for 55 . 4% of the total DSBs . Therefore , heterochromatic regions in Drosophila seem to have a higher propensity to express CFS . However , an alternative classification of the chromatin state at the rDNA locus could significantly reduce the over-representation of heterochromatic DSBs . Although the rDNA locus in Drosophila is generally considered heterochromatic [65] , it can show different staining patterns from classical heterochromatic regions with dyes commonly used to define heterochromatin [e . g . , 36] . In addition , the rDNA locus , although being repetitive , is one of the most expressed loci in the genome . If we were to take DSBs in rDNA out of consideration as DSBs in heterochromatin , we would reach a new estimate of 28% as heterochromatic DSBs , a number closer to 33% , the estimated heterochromatic proportion of the genome . Therefore , we suggest that the occurrence of DSBs induced by replication stresses does not favor the transcriptionally silent heterochromatic regions . In other words , being repetitive does not necessarily render a region more susceptible to breakage . This proposition is further supported by DSB frequency that we observed for the 359 satellite . The satellite is 11 Mb in size , about 30% of the X chromosome , consisting of tandem repeats of a 359bp element [67] . We observed that only 20 . 6% of the X DSBs happened within the satellite . Even if we were to take rDNA breaks ( 49% of X breaks for about 9% of the size of X ) out of the calculation , the 359 satellite would account for about 35% of the size of the remaining X and 40% of the DSBs on the remaining X . Therefore , our analyses both genome-wide and of the specific 359 satellite locus support our proposition on the lack of a correlation between sequence repetitiveness and CFS expressivity . The rDNA locus is one of the most studied loci for replication induced instability . It has been shown in multiple studies that rDNA is highly sensitive to replication deficiency [e . g . , 68 , 69] . Our study confirmed that this general rule also applies to Drosophila rDNA . In larval neuroblasts under a replication-compromised background , one in eight cells suffers a DSB at rDNA , and half of the DSBs on X happens at rDNA . The likely cause for this high rate of DSB formation is the collision between DNA replication and transcription machineries , which is consistent with our results showing the preferential loss of active rDNA cistrons from the arrays on the Y chromosome . This form of replication stress mechanism has been well studied before [e . g . , 70] . Although we have developed a condition to induce high rates of DSBs in somatic cells , to reveal common features of these fragile sites requires an efficient way to identify the broken region . This is particularly important for DSBs happened in the euchromatic regions . Preferably , a genetic method can be devised to isolate and propagate the chromosomes with the broken end so that further cytological and molecular characterizations of these ends could be carried out . This has been challenging for the mammalian systems since such broken ends are most often lost due to its inability to acquire a functional telomere . In contrast , such isolation is feasible in Drosophila , an organism that naturally lacks the telomerase enzyme and essentially any sequence can be a part of a functional telomere [for a review see 71] . We and others have shown that broken chromosomes can be effectively “healed” in the germline [e . g . , 72 , 73] and an elegant scheme of isolating broken ends of a ring-X chromosome in the germline has been successfully implemented [74] , which will greatly facilitate our future efforts in systematically isolating and characterizing CFS in Drosophila .
Drosophila stocks were raised on cornmeal medium under standard laboratory conditions . The mus309D2 stock was a gift from Dr . Jeff Sekelsky at UNC . Other stocks were obtained from the Bloomington Drosophila stock center and described in FlyBase ( flybase . net ) , with the stock numbers shown below in parentheses: spnA1 ( 3322 ) ; pol31G16501 ( 27423 ) ; pol31 deficiency ( 9142 ) ; polαG13925 ( 31805 ) ; polα deficiency ( 7665 ) ; polDl10 ( 4110 ) ; mus309 deficiency ( 6167 ) ; spnA deficiency ( 2352 ) . The two stocks carrying RNAi hairpins ( Fig 6C ) against pol31 were obtained from Vienna Drosophila Resource Center with the stock numbers of V108565 ( hairpin #1 ) and V13621 ( hairpin #2 ) . They were driven by a tubulin-Gal4 gene . The estimation of rDNA copy numbers was performed as previously described [40 , 42] . Two mutant alleles of pol32 ( L27 and L30 ) were recovered by mobilizing P element P{EPgy2}pol32EY15283 from the 3’ region of pol32 . For pol32L27 , nt15255461 to nt15256304 were deleted ( nt designations are based on FlyBase version FB2018_05 ) with an additional 162bp of filler sequences from the P element . For pol32L30 , nt15255502 to nt15256304 were deleted with an addition of 39bp of P element sequences . These two alleles express identical phenotypes . Since only part of the pol32 coding region was removed in each of the mutant alleles ( along with the entire annotated 3’UTR ) , there is still a possibility that a truncated Pol32 protein with 205 ( L27 ) or 219 ( L30 ) Pol32 residues was produced by the mutant genes even though the truncated protein were undetectable by Western blot analyses . To construct a rescuing transgene for pol32 mutants , a 4kb fragment ( nt15254079 to nt15257317 , FB2018_05 ) was PCR-amplified from wild-type genomic DNA . The DNA was confirmed by sequencing and cloned into pUAST-attB for phiC31-mediated germline transformation of Drosophila [75] . To generate transgenes with various point mutations or domain deletions , site-specific mutagenesis was performed on the pUAST-attB construct with the wild-type pol32 fragment , followed by verification of the mutations by sequencing . Two independent lines for each transgene construct were used to rescue pol32L30 homozygous flies . Embryos ( 0-2h after egg-laying ) from pol32L30 and w1118 females were collected and genomic DNA was extracted by standard methods . A total of 1 . 5μg DNA per sample was used for whole genome sequencing performed by Novogene ( Guangzhou , China ) using the Illumina HiSeq platform . Reads were mapped to the reference genome ( Drosophila melanogaster Release 6 plus ISO1 MT ) . Guinea pig anti-Pol32 antibodies were raised against the full length Pol32 protein purified as a recombinant protein from E . coli , and affinity-purified using the same antigen . The Pol32 antibodies were used at 1:5000 on Western blots and1:1000 in immunostaining experiments . Mouse anti-PolD ( CG5949 ) and anti-Pol31 ( CG12018 ) sera were raised against the first 238 a . a . ( PolD ) and the full-length protein ( Pol31 ) as antigens purified from bacteria , and used at 1:5000 and 1:1000 on Western blots , and1:1000 and 1:100 in immunostaining experiments , respectively . Mouse anti-Polα ( CG6349 ) sera were raised against a recombinant antigen consisting of residues 411–705 , and used at 1:1000 on Western blots and 1:100 in immunostaining experiments . Mouse anti-α-tubulin ( Sigma , DM1A ) was used at 1:10000 on western blots . Mouse anti-PCNA ( Abcam , ab29 ) was used at 1:5000 on Western blots and 1:1000 in immunostaining experiments . Embryos collected every 2 hours were homogenized in IP binding buffer ( PBS supplemented with 0 . 3% Triton X-100 plus protease inhibitor cocktail tablets from Roche ) . An anti-PolD serum ( 5μl ) or a purified anti-Pol32 antibody ( 5μl ) or an anti-Pol31 serum ( 5μl ) was added to the embryonic extracts and incubated for 3h at 4°C . Protein A/G agarose from Santa Cruz ( 20μl for each sample ) was added to the above mixture and incubated for 1h at 4°C . The beads were washed 3 times each with 1ml of IP binding buffer . Bound protein complexes were eluted with SDS sample buffer , and resolved by SDS–PAGE for Western blot analysis . Adult ovaries were dissected in fresh PBS and fixed with freshly diluted 3 . 7% formaldehyde in PBS for 20 min at room temperature . Subsequent immunostaining was performed with a standard protocol . For embryo staining , embryos were collected every 15min and dechorionated with 50% bleach and washed with embryo wash buffer ( 0 . 7% NaCl , 0 . 02%Triton X-100 ) , then fixed with 1:1 freshly diluted 3 . 7% formaldehyde in PBS and heptane . Subsequent immunostaining was performed with a standard protocol . Fluorescent images were taken with an Olympus IX83 confocal microscope . Mitotic chromosome squash of neuroblasts from third instar larvae were prepared following a standard protocol without a colchicine treatment . Chromosome preparations were analyzed with a Zeiss Axio Image A2 microscope . Brains were dissected from wandering third instar larvae and squashed in 45% acetic acid . The slides were fixed in freshly made 4% formaldehyde in PBS for 20 min at room temperature and washed twice with 2×SSC . Slides were dehydrated in 70% ethanol for 10 min twice then in 95% ethanol for 5 min , followed by air drying . Hybridization was performed in 50% formamide , 10% dextran sulfate , 2×SSC , 0 . 5μM of each probe and up to 20μl of dH2O . The slides , covered with a coverslip , were heated to 91°C for 2 min , cooled briefly and incubated in a humid chamber in the dark overnight at room temperature . Post-hybridization washes were done three times in 0 . 1×SSC for 15 min each , and the slides were stained with DAPI ( 0 . 2μg/ml in 2×SSC ) for 5 min , washed briefly in 2×SSC and allowed to air dry . Slides were mounted in Vectashield from Thermo and analyzed with a Zeiss Axio Image A2 microscope . The sequences of fluorescent probes from the 359 satellite and the rDNA IGS were the same as ones used by Jagannathan et al . [76] . | Cancer etiological studies suggest that the majority of pathological mutations occurred under near normal DNA replication conditions , emphasizing the importance of understanding replication regulation under non-lethal conditions . To gain such a better understanding , we investigated the function of Pol32 , a conserved ancillary subunit of the essential DNA polymerase Delta complex , through the development of the fruit fly Drosophila . We uncovered a previously unappreciated function of Pol32 in regulating the nuclear import of the polymerase complex , and this function is developmentally regulated . By utilizing mutations in pol32 and other replication factors , we have started to define basic features of Chromosome Fragile Sites ( CFS ) in Drosophila somatic cells . CFS is a major source of genome instability associated with replication stresses , and has been an important topic of cancer biology . We discovered that CFS formation does not favor genomic regions with repetitive sequences except the highly transcribed locus encoding ribosomal RNA . Our work lays the groundwork for future studies using Drosophila as an alternative system to uncover the most fundamental features of CFS . | [
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"mammali... | 2019 | The processivity factor Pol32 mediates nuclear localization of DNA polymerase delta and prevents chromosomal fragile site formation in Drosophila development |
African trypanosomes are digenetic parasites that undergo part of their developmental cycle in mammals and part in tsetse flies . We established a novel technique to monitor the population dynamics of Trypanosoma brucei throughout its life cycle while minimising the confounding factors of strain differences or variation in fitness . Clones derived from a single trypanosome were tagged with short synthetic DNA sequences in a non-transcribed region of the genome . Infections were initiated with mixtures of tagged parasites and a combination of polymerase chain reaction and deep sequencing were used to monitor the composition of populations throughout the life cycle . This revealed that a minimum of several hundred parasites survived transmission from a tsetse fly to a mouse , or vice versa , and contributed to the infection in the new host . In contrast , the parasites experienced a pronounced bottleneck during differentiation and migration from the midgut to the salivary glands of tsetse . In two cases a single tag accounted for ≥99% of the population in the glands , although minor tags could be also detected . Minor tags were transmitted to mice together with the dominant tag ( s ) , persisted during a chronic infection , and survived transmission to a new insect host . An important outcome of the bottleneck within the tsetse is that rare variants can be amplified in individual flies and disseminated by them . This is compatible with the epidemic population structure of T . brucei , in which clonal expansion of a few genotypes in a region occurs against a background of frequent recombination between strains .
A bottleneck is an event in which the population size of a species is temporarily severely reduced . Bottlenecks can have strong evolutionary effects because limited population sizes can lead to dramatic shifts that favour certain genotypes ( founder effects ) [1] , [2] , [3] and to the stochastic loss of others [4] , with rare genotypes being especially prone to being lost . Many digenetic parasites are presumed to experience bottlenecks because their population sizes are reduced during transmission between their two hosts , but there is little information on the size of such bottlenecks or the impact that this may have on genetic diversity . In addition , parasites may also encounter bottlenecks within a host as they differentiate and migrate from one tissue to another or infect different cell types . The protozoan parasite Trypanosoma brucei brucei causes Nagana in cattle , while its close relatives T . b . rhodesiense and T . b . gambiense cause human sleeping sickness . All three sub-species undergo part of their developmental cycle in their insect vector , the tsetse fly ( Glossina spp . ) , and part in their mammalian host . Within their life cycles , there are several phases where parasite numbers are severely reduced ( shown schematically in Figure 1 ) . When a fly feeds on an infected mammal , the parasites that are taken up reach the midgut together with the blood meal . Depending on the trypanosome density in the mammalian host , the fly may ingest anywhere from a few hundred to several hundred thousand organisms . Many species of tsetse are completely refractory to infection by a particular species of trypanosome ( reviewed in [5] ) . Even when a fly species is susceptible , the number of parasites in the midgut can decrease by three orders of magnitude after 3–5 days [6] ( Figure 1; A ) . Attrition of the parasite population also occurs when an infection is initiated with procyclic forms fed to flies through a silicon membrane [7] indicating that the drop in numbers is not solely due to parasites failing to differentiate . In many flies the infection is eradicated at this point; in flies that sustain an infection , the surviving parasites multiply as procyclic forms and colonise the ectoperitrophic space , reaching densities of up to 5×105 parasites per midgut [6] . To complete the life cycle , trypanosomes must migrate to the salivary glands via the foregut and the proboscis [6] , [8] . In a large proportion of tsetse flies with infected midguts , trypanosomes fail to infect the salivary glands [9] , [10] ( Figure 1; B ) . The factors that promote or hinder colonisation of the salivary glands are not known and it is under debate whether migration is continuous [8] or restricted to a defined period [6] . It has been proposed that only a few trypanosomes undertake this journey and that asymmetrically dividing epimastigotes are the only forms capable of colonising the salivary glands [6] . Two lines of evidence support the notion of a limited founder population in the glands: first , fewer than ten epimastigote forms could be detected in the salivary gland ducts of individual flies [6] and second , in mixed infections with two strains of trypanosomes , each tagged with a different fluorescent protein , colonisation of a gland by only one strain was observed on several occasions [11] , [12] . Epimastigotes in the salivary glands attach to the epithelium and proliferate , giving rise to the mammalian-infective metacyclic forms [13] that are transmitted to a susceptible mammal during a blood meal . It has been estimated that flies can inject up to several thousand trypanosomes when they feed on a new host [14] , [15] , but it is not known how many of these differentiate into bloodstream forms and establish an infection ( Figure 1; C ) . Within the mammalian host , a chronic infection is characterised by repeated waves of parasitaemia ( Figure 1; D ) . These are due to the interplay between three phenomena: the host immune response to the parasite's variant surface glycoprotein ( VSG ) coat , resulting in elimination of the population that expresses this particular variant , outgrowth of minor populations that have switched to a different VSG , and differentiation of proliferating slender bloodstream forms to non-dividing stumpy forms at high parasite densities . Stumpy forms are preadapted for further differentiation in the fly and have a lifespan of only a few days in the mammalian bloodstream [16] . Given the right conditions , trypanosomes can infect their mammalian and insect hosts very efficiently: a single parasite is sufficient to infect a tsetse fly [17] and one bite of an infected fly is sufficient to infect a mammal [18] with a minimal infective dose of one metacyclic trypanosome [19] . This high infectivity implies that trypanosomes can cope with very narrow bottlenecks . If transmission bottlenecks are so small and so frequent , however , trypanosomes might risk a loss of fitness and the accumulation of deleterious mutations [20] . In addition , any acquired mutations ( such as drug resistance ) that are beneficial to the parasite in one host might be lost during transmission through the second host . In the case of endoparasites , the quantification of bottlenecks can be difficult because populations are not easily observed over time . Furthermore , it is not straightforward to distinguish between random and selective population reduction . To resolve these problems we used a novel methodology to monitor the population dynamics of T . b . brucei in tsetse . This was subsequently extended to the rest of the life cycle , including transmission from the fly to the mammalian host and vice versa . Different strains of trypanosomes can vary greatly in their ability to be transmitted by tsetse [21] , [22] . Genetic differences were minimised by tagging the progeny of a single trypanosome with short unique DNA sequences that were integrated into a non-transcribed region of the genome . These tags were subsequently used to identify the different populations by amplifying them by polymerase chain reaction and subjecting them to deep sequencing . This approach has the advantage that it yields quantitative data about the different populations that co-exist , as well as allowing an estimate of the population size after a bottleneck .
Repeated syringe passage of bloodstream forms in rodents or prolonged culture of procyclic forms can reduce infectivity for flies . We therefore used the following protocol ( Figure 2A ) to obtain trypanosomes that were genetically homogeneous and capable of completing the life cycle: procyclic forms of T . b . brucei were cloned and a single clone was transmitted through a fly and a mouse . Bloodstream forms isolated from the mouse were triggered to differentiate to procyclic forms in culture . To generate parasites that were distinguishable from each other , aliquots of the culture were transfected with plasmids containing a unique 40bp tag ( Figure 2B and Table S1 ) . The tag in each plasmid lies upstream of the promoter and should not be transcribed , and therefore not influence the fitness of the parasite . Trypanosome clones ( one for each of eight tags ) were isolated and tested for growth in culture . All grew at similar rates ( Figure S1 ) . Cultures of the eight clones were mixed and used to infect tsetse . Three flies ( A , B , and C ) that were positive for metacyclic forms were selected and allowed to infect mice . Parasites were first detected in the corresponding mice 6 , 7 and 4 days , respectively , after the infective bite . Subsequently , the salivary glands and midguts of the flies were isolated by dissection and DNA was extracted . Tail blood samples were collected from each mouse to monitor the parasitaemia and DNA was prepared from samples in weeks 1 , 2 , 3 and 4 and at the termination of the experiment after 7–10 weeks . Two batches of ten flies were fed on mouse C 18 and 30 days post infection . Midguts were dissected after 10 and 12 days and one positive midgut from each batch was taken for tag analysis ( fly D and fly E in Figure 3 ) . Tags were amplified by PCR , sequenced by 454 massively parallel pyrosequencing and analysed for their frequency and distribution . In total , we identified 30 , 592 sequences , an average of 1330 per sample ( Figure S2 ) . Control experiments confirmed that the barcoded primers did not affect the frequency with which individual sequences were detected ( Figure S2 ) . A common pattern in all three experiments ( Figure 3 ) was the large number of different tags detected in the midgut , many of them at high frequency ( >5% ) . Each midgut contained at least 6 different tags and , taken together , all 8 tags could be detected in the three flies . This demonstrates that the procyclic culture forms used to infect the flies maintained their diversity in the gut lumen . The frequency of individual tags in the salivary glands changed compared to the midgut ( Figure 3 ) . This was most striking in fly A , in which tag 1 was minor ( 0 . 2% ) and tag 6 dominant ( 52% ) in the midgut , whereas in the salivary glands tag 1 was dominant ( 99 . 9% ) and tag 6 undetectable . In fly B , four tags were dominant in the midgut , but only one of these ( tag 2 ) was dominant in the salivary glands . In fly C , the three tags that were dominant in the midgut ( tags 2 , 4 and 6 ) were also dominant in the salivary glands , with tag 6 constituting 74% of the population . In addition , tag 1 , which was present at <1% in the midgut , accounted for 6 . 9% of the parasites in the salivary glands . This analysis demonstrates that tags that are dominant in the midgut are not necessarily so in the salivary glands , and that their relative frequencies can be altered . This is reflected by the diverse correlation coefficients: r2 = 0 . 08 , 0 . 86 and 0 . 25 for flies A , B , and C respectively , and implies that when trypanosomes are equally fit , any of the parasites from the midgut is capable of migrating to the salivary glands and founding the dominant population . At the beginning of the infection in mice , the distribution and frequency of tags was very similar to the parasite populations in the salivary glands of the corresponding tsetse fly . The dominant tags in the salivary glands retained their dominance in mouse A and mouse B from the first sample onwards . In mouse C , tags 2 ( 32% ) , 4 ( 43% ) , and 6 ( 25% ) were present in the first week of infection . Tag 4 was the only dominant tag from the second week onwards and finally the only one detectable after ten weeks . Tag 1 , with a frequency of 6 . 9% in the salivary glands of fly C , became very minor in the following mouse infection and was detected only once after four weeks . The presence of one dominant tag and a few minor tags during mouse infections led to a very uneven distribution of individual tags , which showed up to a thousand-fold variation in frequency within a single sample . This uneven distribution is also reflected in a low Simpson's diversity index [23] during the course of infection in the mice ( Table 1 ) . Based on the parasite density and the frequency with which each tag occurred at the different time points sampled , the parasitaemia of individual populations could be extrapolated from the data ( Figure S3 ) . This revealed that the dominant and minor populations showed similar fluctuations in parasitaemia , although their titres differed by several orders of magnitude . Analysis of the tags present in the midguts of flies D and E , which became infected after feeding on mouse C , revealed two interesting outcomes . First , the tag that was dominant in the mouse remained so in the midgut of both flies ( Figure 3 ) . Second , minor tags in the bloodstream form population were also present . For example tags with frequencies of 0 . 5–3% in the bloodstream form population ( tags 2 , 5 , and 6 ) were detectable in the midgut . Interestingly , tag 3 was detectable in fly E even though it was under the detection limit in all the samples from mouse C . Together , the two flies took up five different tags . This mouse had a parasitaemia of 4 . 9×106 and 7 . 7×106 per ml on days 18 and 30 , respectively . Assuming the flies imbibed approximately 20µl of blood , about 1–1 . 5×105 trypanosomes might reach the midgut of each fly . If approximately 1% survived [6] even very minor tags would be represented by 2–30 individual trypanosomes that could contribute to establishing the midgut infection .
By using tagged trypanosomes originating from a single clone , we have been able to monitor the dynamics of a parasite population throughout the life cycle without the confounding factor of strain differences . This analysis revealed that a major bottleneck in the life cycle occurs during migration of parasites from the midgut to the salivary glands , leading to the establishment of one or a few dominant genotypes in each fly . Minor genotypes constituting <1% of the population could also be detected in the glands , however . These were transmitted to mice together with the dominant genotype ( s ) , and were found to persist during a chronic infection and survive transmission to a new insect vector . The frequency and diversity of tags enabled us to extrapolate the minimum number of parasites transferred between hosts and provide an estimate of the size of the bottleneck ( Figure 4 ) . We estimate that at least 500–1000 trypanosomes must have survived the transfer from mouse C to flies D and E and colonised their midguts . The population structure was similar to that in the mouse blood at the time of the blood meal , indicating that despite the reduction in parasite numbers , transmission from the mammal to the insect does not represent a severe bottleneck . Likewise , the minimum number of trypanosomes that survived the transfer from infected flies and initiated the infection in the 3 mice was estimated by drawing simulation to range from 500–2500 ( Figures 4 and S4 ) . This is similar to the number of metacyclic forms extruded by infected flies [14] , [15] , implying that most of the parasites that are inoculated can contribute to an infection . With the exception of a single major tag that was present in the salivary glands of fly C , parasites isolated from mice during the first week of infection reflected the diversity and distribution of parasites in salivary glands of the infecting fly . A large number of tags were detected during the chronic infections , but their frequency was highly variable . Some tags were detected only once in a total of 6800 sequences obtained from five blood samples ( e . g . tag 1 or tag 8 in mouse B ) . Considering that the parasitaemia never fell below 105 ml−1 , we consider it likely that most tags transmitted by the tsetse were present continuously during mouse infection although they were under the detection limit in individual samples . Antigenic variation must have occurred several times during the course of these infections , since the mice were immunocompetent . Ordered ( hierarchical ) VSG expression is a widely accepted model for antigenic variation [24] , [25] , [26] . Since the tagged trypanosomes derive from a clone , it is possible that they obeyed the same hierarchy , which would result in synchronised VSG expression by trypanosomes with different tags . This is not mandatory , however , as simultaneous expression of several variants is both predicted by the model of Lythgoe et al . [26] and can occur in vivo [27] . In contrast to transmission between hosts , migration from the midgut to the salivary glands of tsetse caused profound changes in relative frequencies of different tags , with up to five tags per experiment changing from dominant to minor , or vice versa . Two flies had a single dominant tag accounting for more than 99% of the population in the glands , while the remaining fly had 4 dominant tags ( one of which accounted for 74% of the population ) . When minor populations from the glands and the corresponding mice were taken into account , all the tags that were found in the midgut were represented , meaning that at least 6 trypanosomes must have reached the salivary glands in each fly . The strong dominance of one tag each in flies A and B , and to a slightly lesser extent in Fly C , could best be explained by waves of migration by very few parasites at a time . Trypanosomes are tightly packed in infected glands and have to compete for space . Early migration might be a more important factor than dominance in the midgut if parasites that arrive first can disperse and colonise the glands more readily than latecomers . This “race for space” would account for the shift in frequencies between the midgut and salivary glands of a single fly and also explain why a single tag can dominate the population while others remain very minor . It would also be compatible with publications that have reported changes in the relative frequencies of two strains of trypanosomes between the midgut and glands , as well as glands colonised by only one of the two strains [11] , [12] . The latter study catalogued whether each of the pair of salivary glands contained one or both strains , thus allowing the minimum number of founder trypanosomes in each fly to be extrapolated from the data . In these experiments the salivary gland infections of approximately two-thirds of the flies could have been established by as few as one or two trypanosomes , while the remaining third would have required at least three or four . It could not be excluded , however , that several trypanosomes of one strain migrated to the same gland , or that very minor populations might have been overlooked . An important outcome of the extreme bottleneck that can occur between the midgut and the salivary glands is that rare variants can be amplified in individual flies and be disseminated by them . If a variant has a selective advantage in mammals , such as altered host range or increased resistance to drugs , this might cause it to become the major species circulating locally [28] , [29] . Such a phenomenon could explain the epidemic population structure of T . brucei documented by MacLeod and coworkers , in which clonal expansion of a few genotypes in a region occurs against a background of frequent recombination between strains [30] . Our data indicate that both mammals and tsetse can readily acquire and transmit more than one genotype in the course of a single blood meal . Mixed genotypes have been detected fairly frequently in field isolates from cattle , humans and tsetse [30] , [31] , [32] , [33] , and it is possible that they might be even more widespread since minor populations would escape detection . Co-infection of susceptible flies with different strains of trypanosomes might affect parasite population dynamics [34] and also increase the chances of genetic exchange [35] , [36] if the parasites develop and migrate in parallel . The approach that we have used here can be extended to study other facets of infection with trypanosomes , for example the population found in the central nervous system during the late stage of sleeping sickness or the parasites causing relapse infections after drug treatment . It can also be applied to the analysis of population dynamics of any other parasite that is amenable to transfection , including other African trypanosomes that do not infect the salivary glands and may therefore show different dynamics in the tsetse fly .
Animal experiments were approved by the local veterinary authorities ( Veterinäramt Basel-Stadt ) in compliance with Swiss federal law ( TSchG ) and cantonal by-laws ( TSchV Basel-Stadt ) . Trypanosoma brucei brucei AnTat 1 . 1 [37] procyclic forms were cloned by the micro-drop method [38] and stabilates were made after 22 days . Tsetse flies ( see below ) were infected with one clone , and the infected salivary glands of one fly were dissected at day 27 and inoculated intraperitoneally into a female NMRI mouse ( RCC , Ittingen , Switzerland ) , which developed a parasitaemia of 108 trypanosomes ml−1 at day 5 post infection . Bloodstream forms , obtained by heart puncture , were triggered to differentiate into procyclic forms in SDM-79 supplemented with 10% foetal bovine serum , 3 mM sodium citrate and cis-aconitate ( CCA ) [39] , and 20mM glycerol at 27°C for 3 days [40] . Procyclic forms were cultured thereafter in the same medium without CCA . Pupae of Glossina morsitans morsitans were obtained from the Institute of Zoology , Bratislava , Slovakia . The flies were maintained at 25°C and 70% relative humidity with 12 hours of light per day . Teneral tsetse flies ( under the age of 72 hours ) were infected with procyclic forms as described previously [22] . Starting twenty days post-infection , tsetse flies were examined for the presence of metacyclic forms in their saliva . Tsetse flies with a mature infection were allowed to feed on NMRI mice 2 to 4 days after the appearance of first metacyclic forms . Subsequently the paired ducts of the salivary glands were extracted from the neck of the tsetse flies . This prevented contamination with midgut forms . The midgut ( including the proventriculus ) was then dissected out of the abdomen . The tissues were dissected on separate slides in a drop of PBS and then transferred to an Eppendorf tube containing 200µl lysis buffer ( see below ) and stored at −20°C prior to DNA extraction . Female NMRI mice ( RCC , Ittingen ) were kept at 22°C , 70% relative humidity and with 12 hours of light per day . To determine the parasitaemia , 10 µl tail blood were mixed with 40 µl 3 . 2% sodium citrate , and 4 µl were uniformly distributed under a 20 mm2 cover slip . For each sample , 10–15 fields were counted . The parasitaemia is given as the number of trypanosomes per ml mouse blood . For analysis of the tags 50 µl of tail blood was processed . The insert from the plasmid pKON [21] , was amplified by PCR using the primers Bgl II-promotor ( ATAGATCTCGAAAACTCTTCGGGA ) and KO 2 ( TATCTAGAGGGCACTGCAGT ) . Bgl II and Xba I sites , respectively , are underlined . The PCR product encompassing the EP1 promoter , the neomycin resistance gene and 19bp of the EP2 3′ untranslated region ( UTR ) was digested with Bgl II and Xba I . The plasmid pLew111 ( http://tryps . rockefeller . edu/ ) was digested with Bgl II and Nhe I to provide the plasmid backbone with the rDNA spacer . The digested PCR product was ligated to the backbone ( Xba I and Nhe I have compatible ends ) . The resulting construct , pIns has a single Bgl II site between the rDNA spacer and the procyclin promoter that was used for the insertion of unique tags ( Figure 2B ) . An oligonucleotide ( ATCACGGCCGGGAGATCT ( N ) 40AGATCTGTGAGACCCATTAAGCTTCC ) containing a variable 40mer flanked by two constant regions with Bgl II sites ( underlined ) , was purchased from Microsynth AG , Balgach , Switzerland . Double-stranded DNA was produced by amplification with the constant flanking sequences: iTag-oligo ( ATCACGGCCGGGAGATCT ) and BIL-4A ( GGAAGCTTAATGGGTCTCAC ) . The PCR product was inserted into pCR2 . 1 TOPO ( Invitrogen , Carlsbad Ca , USA ) according to the manufacturer's protocol and used to transform E . coli XL-1 blue . Purified plasmids were sequenced using standard methods . Eight tags were selected ( Table S1a ) , the fragments released with Bgl II and ligated into pIns to generate the plasmid series piTag1–8 . Transfection was performed with 10µg of each plasmid ( piTag1–8 ) linearised with Not I . Plasmids were electroporated separately into 2 . 5×107 procyclic trypanosomes . Transfection and cloning by limiting dilution were carried out as described elsewhere [40] . G418 ( 25µg ml−1 ) was used to select stable transformants . Samples were resuspended in 200µl lysis buffer ( 100 mM NaCl , 5 mM sodium EDTA , 10 mM tris-HCl , pH 8 ) , supplemented with 20 µl RNAse A ( 1 mg/ml ) and incubated for 1 h at 37°C , followed by the addition of 10µl Pronase ( 20mg/ml ) and incubation for a further 2 h . Genomic DNA was isolated by phenol/chloroform extraction , precipitated with ethanol and resuspended in 50 µl water . Genomic DNA obtained from blood samples was subjected to an additional precipitation using 0 . 5 volumes of 7 . 5M ammonium acetate and 5 volumes ethanol . Nested PCR was performed on 1 µl of each DNA sample . The oligonucleotides rDNAsense/ep2sas2 ( Table S1b ) were used to generate a product of ∼700 bp using the following conditions: 3 min at 96°C , 30 cycles of 1 min 94°C , 1 min 45°C , and 45 sec 72°C , followed by 10 min extension at 72°C . The second PCR performed with 1 µl from the first reaction as template and the fusion primers A and B , these consist of two regions: a template specific region for PCR amplification and a fusion region for 454 sequencing ( Microsynth , Balgach , Switzerland ) . The primers A1–A6 can be distinguished by a variable 6mer barcode that connects the two regions ( Table S1b ) . This barcode was used to allocate samples in the same region on the pyrosequencing plate ( see below ) . The PCR conditions with the primers A and B were: 3 min at 96°C , 30 cycles of 1 min 94°C , 50 sec 52°C and 30 sec 72°C followed by 10 min extension at 72°C , yielding products of 177 bp . 454 picotiter plate pyrosequencing was performed by Microsynth , Balgach , Switzerland , with the Roche Genome Sequencer FLX System as described elsewhere [41] , [42] . Five regions of a picotiter plate were used for this study: one ( I ) for the control DNA and four regions ( II–V ) for the samples ( Figure S2 , panel A ) . For the control sequencing reactions , cultures of individual clones were mixed , genomic DNA extracted , and split into 6 aliquots . DNA from each aliquot was amplified with a different barcoded fusion primer A1–A6 together with the primer B . The samples collected from the flies and mice were amplified with the primers A1/B–A6/B as indicated in Figure 2 . The barcodes were identified with the SFF file program sfffile ( included in the 454 software package ) , allowing one mismatch . The distribution of the tags ( Figure S2 , panel B ) was very similar among all control samples ( two-sided paired T-test; p>0 . 3 for all combinations ) . | African trypanosomes cause human sleeping sickness and Nagana in domestic animals . These parasites undergo part of their life cycle in mammalian hosts and part in their insect host , the tsetse fly , and are transmitted when the fly takes a blood meal . Within the fly , successful transmission involves two steps: colonisation of the midgut , and migration to the salivary glands . Although there are estimates of the number of trypanosomes that a fly can pick up from an infected host or transmit to a new host , it is not known how many parasites actually survive and contribute to an infection . We established a method to track parasites during transmission between individual mammals and flies , as well as in different host tissues . The same method can be applied to other parasites in a wide range of hosts and conditions . We found that a minimum of several hundred trypanosomes survived the transfer between hosts and contributed to a new infection . In contrast , parasites within a fly experienced a bottleneck during migration . An important outcome of this event is that even minor populations can be amplified in the glands of individual flies and disseminated , which could result in the rapid spread of new traits . | [
"Abstract",
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"Results",
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"Methods"
] | [
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] | 2010 | Bottlenecks and the Maintenance of Minor Genotypes during the Life Cycle of Trypanosoma brucei |
The differentiation of self-renewing progenitor cells requires not only the regulation of lineage- and developmental stage–specific genes but also the coordinated adaptation of housekeeping functions from a metabolically active , proliferative state toward quiescence . How metabolic and cell-cycle states are coordinated with the regulation of cell type–specific genes is an important question , because dissociation between differentiation , cell cycle , and metabolic states is a hallmark of cancer . Here , we use a model system to systematically identify key transcriptional regulators of Ikaros-dependent B cell–progenitor differentiation . We find that the coordinated regulation of housekeeping functions and tissue-specific gene expression requires a feedforward circuit whereby Ikaros down-regulates the expression of Myc . Our findings show how coordination between differentiation and housekeeping states can be achieved by interconnected regulators . Similar principles likely coordinate differentiation and housekeeping functions during progenitor cell differentiation in other cell lineages .
Cell proliferation , metabolic state , and differentiation are linked: proliferating progenitor cells exit the cell cycle and adjust their metabolism as they differentiate [1–3] . Mechanistically , this coordination is thought to involve mutual antagonism between cyclin-dependent kinases that promote cell-cycle entry and transcription factors that induce tissue-specific gene expression [1 , 2] . A detailed inventory of differentiation stages is available for mammalian haematopoiesis . In B cell differentiation , discrete stages are defined by CD markers [4] , gene expression profiles [5] ( www . immgen . org ) , transcription factor binding [6–8] , and cell-cycle states [9–11] . A critical step is the transition of proliferating B cell progenitors towards cell-cycle arrest and differentiation . We refer to proliferating B cell progenitors as Fr . C following Hardy’s nomenclature [4]; this stage is also known as the pro-B , pre-B1 , or large pre–B cell stage ( Fig 1A ) . We refer to quiescent , differentiating B cell progenitors as Fr . D following Hardy’s nomenclature [4]; this stage is also known as the pre-B , pre-B2 , or small pre–B cell stage ( Fig 1A ) . Transcriptional regulators of the Ikaros family of zinc finger proteins are up-regulated at this transition [12] and are required for B cell progenitor differentiation in vivo [13–15] . IKZF1 , the gene encoding Ikaros , is recurrently mutated in human B cell progenitor acute lymphoblastic leukemias ( B-ALLs ) with translocations between the IGH locus and the ABL1 proto-oncogene ( BCR-ABL1 ) [16 , 17] . Here , we employ an inducible system in a B cell progenitor line that models the transition from B cell progenitor proliferation toward cell-cycle arrest and differentiation upon the regulated delivery of the transcription factor Ikaros from the cytoplasm into the nucleus [7 , 18] . The availability of this in vitro model , combined with access to primary B cell progenitors for validation experiments , makes B cell progenitor differentiation an attractive system to study progenitor differentiation and the mechanisms that link differentiation with changes in cell cycle and metabolism . To understand the regulatory control of B cell progenitor differentiation , we developed an algorithm that examines the temporal correlation between the expression of transcription factors and their target genes over the course of progenitor differentiation and scores the relative contribution of different transcription factors This approach , which is transferable to other cell-state transitions , highlighted that the Ikaros targets Foxo1 and Myc as high-scoring transcription factors . Perturbation experiments showed that the transcriptional repression of Myc was critical for the coordinated regulation of lineage-specific , cell-cycle , and metabolic genes . Ikaros-mediated repression of Myc connects B cell differentiation to cell-cycle exit and metabolic adaptation . Similar principles may coordinate differentiation and housekeeping functions during progenitor differentiation in other cell lineages .
We controlled the dosage of nuclear Ikaros-ERt2 with temporal precision by the addition of 4-hydroxy-tamoxifen ( 4-OHT ) in the pre–B cell line B3 [7 , 18] . This model is designed to approximate the B cell linker ( BLNK ) -dependent increase of Ikzf3 expression in primary B cell progenitors in response to pre-B cell receptor signaling [12] , and the nuclear translocation of Ikaros recapitulates the majority of gene expression changes that distinguishes proliferating ( Fr . C ) from differentiating ( Fr . D ) B cell progenitors in vivo [7 , 18] . We performed time-resolved RNA sequencing ( RNA-seq ) of 4-OHT-treated B3 cells expressing Ikaros-ERt2 or control vector ( Fig 1B ) at 6 time points after 4-OHT . We combined pairwise comparison between time points by limma [19] with time-course analysis by maSigPro [20] to identify 5 , 865 differentially expressed genes ( S1 Table ) . Pseudotemporal ordering [21] of single cell RNA-seq ( scRNA-seq ) data showed an unbranched path over the experimental differentiation time course ( Fig 1C ) . Gaussian mixture modeling for model-based clustering [22] resolved up- and down-regulated genes , subtrends of immediate and delayed regulation , and 2 nonmonotonic up-down–and down-up–regulated groups ( Fig 1D ) . Functional characterization of these trends by gene set analysis showed that up-regulated genes were enriched in Janus kinase/signal transducers and activators of transcription ( JAK-STAT ) signaling , cell adhesion , and B cell receptor and interleukin signalling , while metabolic functions , RNA metabolism , and ribosome biogenesis were enriched among down-regulated genes . This analysis indicates a clear distinction between induced ( signaling and cell–cell communication ) and repressed ( mainly metabolism-related ) processes during B cell progenitor differentiation ( Fig 1D ) . To ask how well this experimental system models B cell progenitor differentiation in vivo , we compared dynamic gene expression at each time point with static , developmental stage-specific gene expression by primary B cell progenitors [5] . Up to 6 h after 4-OHT-induced nuclear translocation of Ikaros , gene expression correlated positively with the less mature Fr . C and negatively with the more mature Fr . D states in vivo ( Fig 1E ) . The 12 h time point marked a tipping point at which the positive correlation with Fr . C and the negative correlation with Fr . D was lost ( Fig 1E ) . After that , gene expression correlated positively with the more mature Fr . D and negatively with the less mature Fr . C ( Fig 1E ) . Therefore , gene expression in B3 cells showed a transition from an Fr . C-like state to an Fr . D-like state within a 24-h time frame . The experimental system allowed the capture not only of the start and end points but also the dynamics that occurred between them . To examine the ability of this model system to pinpoint Ikaros target genes relevant to human disease , we assembled gene expression profiles of 1 , 404 B-ALL samples with and without IKZF1 mutations ( S1 Fig and associated text ) . Genes that were differentially expressed between Fr . C and Fr . D were preferentially deregulated in IKZF1-mutated B-ALL [23 , 24] , including current and potential therapeutic targets [25–27] and prognostically relevant gene signatures in B-ALL [17 , 28] ( S1 Fig ) . There was significant overlap between differential gene expression in IKZF1-mutated B-ALL and early gene expression changes in B3 cells at 0 to 2 h after Ikaros induction ( Fig 1F , odds ratio = 2 . 53 , adjusted [adj . ] P = 0 . 02 for the 200 top differentially expressed genes ) . Because early gene expression changes are likely direct , this finding indicates that our in vitro system identifies gene expression changes in IKZF1-mutated B-ALL that may result directly from the loss of Ikaros function . To follow up on the down-regulation of genes related to metabolism ( Fig 1D ) , we compared the expression of glycolysis and tricarboxylic acid ( TCA ) cycle genes during B3 cell differentiation in vitro ( Fig 2A and 2B , left ) and B cell progenitor differentiation in vivo ( Fig 2A and 2B , right ) . Key glycolysis and TCA cycle genes were down-regulated in vitro and in vivo ( Fig 2A and 2B; the transition from Fr . C to Fr . D is indicated with a bracket ) . Analysis of Ikaros chromatin immunoprecipitation sequencing ( ChIP-seq ) data [7] showed that numerous core metabolic genes were directly bound by Ikaros , as illustrated by the glucose transporter Slc2a1 and the TCA cycle gene Fh1 ( Fig 2C; see figure legend for a list of Ikaros-bound core metabolic genes ) . In extracellular flux assays , nuclear translocation of Ikaros triggered a pronounced reduction ( 55%–65% ) in extracellular acidification ( ECAR ) as a measure of lactate production ( Fig 2D , left ) . The oxygen consumption rate ( OCR ) was reduced by 45%–50% ( Fig 2D , right ) . This was accompanied by reduced mechanistic target of rapamycin complex 1 ( mTORC1 ) activity , as read out by phosphorylation of S6 ribosomal protein ( S3A Fig ) and the transcriptional up-regulation of autophagy genes ( S3B Fig ) . To validate these findings , we transduced primary Fr . C-like B cell progenitors with Ikaros or Ikzf3 ( Aiolos ) and determined the resulting changes in ECAR and the OCR . Ikaros and Aiolos reduced the ECAR and the OCR of primary B cell progenitors ( Fig 2E ) . In the experiments described above , changes in metabolic gene expression and metabolic activity were induced by the expression of Ikzf1 or Ikzf3 . During B cell progenitor differentiation , Ikzf3 expression is initiated by signaling through the pre-B cell receptor via a pathway that requires BLNK [12] . To determine whether pre-B cell receptor signaling is linked to metabolic regulation , we used an experimental system in which BLNK activity can be inducibly restored in BLNK-deficient B cells by means of a 4-OHT-inducible BLNK-ERt2 fusion protein [29] . As expected , restoration of BLNK activity induced Ikzf3 and repressed Igll1 , a known target of Ikzf1 and Ikzf3 during the the Fr . C to Fr . D transition [12 , 18] ( Fig 2F , top ) . Restoration of BLNK activity led to the repression of the metabolic genes Slc7a5 , Hk2 , and Ldha ( Fig 2F , bottom ) , indicating that pre-B cell receptor signaling controls the expression of metabolic genes in B cell progenitors . These data demonstrate altered metabolic gene expression , reduced glycolytic flux , and a drop in oxygen consumption at the transition of B cell progenitors from proliferation to quiescence in vitro and in vivo . This indicates “reverse” metabolic reprogramming towards a less glycolytic state [30 , 31] . The expression of B cell genes such as Igll1 and Foxo1 was correlated with the expression of housekeeping genes , such as Myc , the metabolic gene Hk2 , and the cell-cycle gene Ccnd2 , not only at the level of cell populations but also in individual cells ( Fig 2G ) . We conclude that the regulation of B cell–specific genes is coordinated with the regulation of housekeeping pathways during B cell progenitor differentiation . B cell progenitor differentiation is marked by the differential expression of numerous transcription factors . To define the key transcription factors and the regulatory pathways involved in this process , we first identified all transcription factor genes that showed a significant and robust ( log2 fold change > 1 . 5 ) change in expression between consecutive time points . We considered transcription factors that were differentially expressed ( adj . P < 0 . 01 ) between Fr . C and Fr . D in vivo ( [5]; www . immgen . org ) . We included transcription factors that showed up-down–or down-up–regulation over the in vitro time course , based on the consideration that genes with nonmonotonic expression may be important for B cell progenitor differentiation even if they were not differentially expressed between the start and the end of the transition . This resulted in a total of 23 candidate transcriptional regulators ( Fig 3A , Table 1 ) . To evaluate the potential importance ( or “weight” ) of transcriptional regulators during cell-state transitions , we developed an approach that numerically integrates the differential expression over time of transcription factors and their target genes , which we refer to as transition weight matrix ( TWM ) . For each transcription factor , we identified potential target genes based on transcription factor ChIP-seq peaks in gene promoters . We then determined the enrichment of transcription factor binding over differentially expressed genes and multiplied this enrichment with the log2 fold change in transcription factor mRNA expression for each time interval . The resulting values were summed over the time series to yield a score for transcription factor expression and target enrichment over time . We next examined to what extent the expression of each transcription factor correlated with mRNA levels of its target genes in a consistent fashion over time , which we term “coherence . ” Coherence between the expression of each transcription factor and its target genes was determined for each time interval and summed over the time series to yield a score for coherence . Finally , the score for transcription factor expression and target enrichment over time was multiplied with the score for coherence to yield a TWM score for each transcription factor . Details of this approach as well as a comprehensive mathematical description are provided in S3 Fig and in the “Methods” section . We validated the TWM approach using the paradigm of T helper 17 ( Th17 ) T-cell differentiation , in which the key transcriptional drivers are known [32 , 33] and high-quality transcription factor ChIP-seq data are available ( S2 Table ) . TWM correctly identified RORC ( TWM score = 0 . 17 ) , the signature transcription factor of Th17 cells , and IRF4 ( TWM score = 0 . 14 ) , which is required for Rorc expression , as transcription factors with the highest TWM score ( Fig 3B ) . c-Maf ( Maf; TWM score = 0 . 14 ) , a transcription factor with an established role in Rorc induction and Th17 differentiation [34] , and Hif1-alpha ( Hif1a; TWM score = 0 . 12 ) , which controls the balance between Th17 and regulatory T ( Treg ) cell differentiation [35 , 36] , also scored highly . Therefore , TWM successfully identified key regulators of Th17 cell differentiation . To apply TWM to B cell progenitor differentiation , we retrieved published ChIP-seq data sets for transcription factors in B cell progenitors . ChIP-seq data for the transcription factors Runx1 , Foxo1 , Myc , Irf4 , Spi1 , and Jund , but ChIP-seq data for Jund did not contain statistically significant peaks by CLCbio Peak Finder [37] . This left Runx1 , Foxo1 , Myc , Irf4 , and Spi1 as potential regulators for which potential target genes could be identified based on promoter-proximal ChIPseq peaks ( Table 1; proximal genes were identified by RGMatch [38] ) . We included EBF1 and Pax5 as key factors of known importance for B cell differentiation and CTCF as a negative control . Runx1 ( TWM score = 1 . 75 ) , Myc ( TWM score = 1 . 20 ) , and Foxo1 ( TWM score = 1 . 14 ) were identified as highly ranked transcription factors ( Fig 3C ) . Runx1 showed transient down-regulation followed by up-regulation . RUNX1 ChIP-seq target genes showed enrichment for differential expression ( P < 0 . 0005 ) and good coherence ( Fig 3C ) . Foxo1 was progressively up-regulated and showed good enrichment for differential expression of its ChIP-seq target genes ( P < 0 . 001 ) . Promoters bound by FOXO1 were mainly up-regulated ( P < 10 × 10−36 ) . Myc was progressively down-regulated and also showed strong enrichment for differential expression of its ChIP-seq target genes ( P < 0 . 001 ) . Promoters bound by Myc were mainly down-regulated ( P < 10 × 10−9 ) . The relevance of FOXO1 and Myc for primary B cell progenitor differentiation is supported by the up-regulation of Foxo1 mRNA and the down-regulation of Myc mRNA during in vivo B cell progenitor differentiation ( Fig 3E ) and direct binding of Ikaros to the Foxo1 and Myc promoters in B cell progenitors ( Fig 3F ) . For cell-state transitions for which sufficient ChIP-seq data are not available , TWM can be implemented based on promoter accessibility and the presence of transcription factor motifs in target gene promoters . We used DNase I hypersensitive sites sequencing ( DNase-seq ) to assess promoter accessibility at each time interval and the presence of transcription factor motifs for all 23 differentially expressed transcription factors ( Table 1 , Fig 3A ) . TWM identified Spib ( TWM score = 2 . 62 ) , Arid5a ( TWM score = 1 . 81 ) , Foxo1 ( TWM score = 1 . 67 ) , and the Myc antagonist Mxd4 ( TWM score = 1 . 58 ) as top-scoring transcription factors ( Table 1 ) . For validation of the TWM results , we focused on Foxo1 and Myc for two reasons . First , Foxo1 and the Myc pathway scored highly in both ChIP-seq and DNase-seq–based TWM approaches . Second , Foxo1 and Myc show monotonic changes in expression ( up- and down-regulation , respectively ) during the B3 cell differentiation time course , which facilitates the analysis of their impact on B cell progenitor differentiation . FOXO1 is essential for B cell development , and its role in the progression from B cell progenitor proliferation to B cell progenitor differentiation ( i . e . , the FR . C to Fr . D transition ) has been characterized in exquisite detail [8 , 9 , 11 , 39] . According to current models , Fr . C cells proliferate in response to interleukin-7 ( IL-7 ) receptor signaling , which inactivates FOXO1 via the phosphatidylinositol 3 kinase/Akt kinase/mechanistic target of rapamycin complex 1 ( PI3K/Akt/mTOR ) axis ( Fig 4Ai ) . Changes in signaling through the IL-7 receptor and/or pre–B cell receptor lead to the post-translational activation and stabilization of FOXO1 protein ( Fig 4Aii ) . FOXO1 then induces the expression of target genes that are critical for B cell progenitor differentiation and include B cell receptor signaling components , the recombinase activating genes Rag1 and Rag2 , and the immunoglobulin light chain loci Igk and Igl ( Fig 4Aiii ) [8 , 9 , 11] . We confirmed that FOXO1 protein expression progressive increased during Ikaros-induced B3 cell differentiation ( Fig 4B ) . Our finding that Foxo1 mRNA increases over the time course of B3 cell differentiation and also between the Fr . C to Fr . D B cell progenitor stages in vivo raise a hitherto unanswered question about the role of FOXO1 , namely , whether the transcriptional up-regulation we have uncovered contributes to the regulation of FOXO1 target genes in B cell progenitor differentiation . This is difficult to address by population RNA-seq data , because FOXO1 target genes were differentially expressed during the Fr . C to Fr . D transition , concomitant with the increase in Foxo1 mRNA ( P < 10−13 , for FOXO1 ChIP-seq targets versus nontargets , chi-squared test ) . To address this conundrum , we interrogated scRNA-seq data . We asked whether Foxo1 mRNA was positively correlated with the expression of FOXO1 target gene transcripts at the single-cell level and to what extent Foxo1 mRNA was a predictor of FOXO1 target gene expression independently of time . FOXO1 target genes were defined either by ChIP-seq peaks in promoters as described above or , alternatively , as FOXO1-dependent genes that were deregulated after genetic deletion of Foxo1 in early lymphoid/B cell progenitor cells [40] . We found significant correlations between Foxo1 mRNA and FOXO1 target gene transcripts when comparing cells with low versus intermediate versus high expression of Foxo1 transcripts ( Fig 4C; see Fig 4D for examples ) . We next used linear models to compute the extent to which the level of each differentially expressed target gene was explained by time after 4-OHT addition , by Foxo1 mRNA level , or a combination of time and Foxo1 mRNA level . Adding Foxo1 mRNA levels to the models significantly increased the fraction of the variance in FOXO1 target gene expression that could be explained by time after 4-OHT addition alone ( Fig 4E ) . The scRNA-seq analysis indicates that the level of Foxo1 mRNA expression correlates with the expression of FOXO1 target genes in the same cells . We next examined the regulatory relationship between Ikaros and Myc during B cell progenitor differentiation . We transduced B3 cells with Myc-ERt2 or control vector ( Fig 5A ) . In an attempt to capture immediate Myc target genes in B3 cells , we isolated chromatin-associated RNA [41] for high-throughput sequencing 30 , 60 , and 180 min after induction with 4-OHT . Analysis over the time series ( as described for Fig 1 ) identified 2 , 809 differentially expressed genes after Myc induction ( adj . P < 0 . 05; 1 , 485 up , 1 , 241 down ) . As a reference , we transduced B3 cells with Ikaros-ERt2 for chromatin-associated RNA-seq as described for Myc-ERt2 . Analysis over the time series identified 1 , 354 differentially expressed genes after Ikaros induction ( adj . P < 0 . 05; 662 up , 692 down ) ( S4 Table and Fig 5B ) . Gene ontology ( GO ) analysis of Ikaros-regulated genes showed enrichment of a spectrum of functional terms dominated by adhesion , differentiation , signaling , kinase activity , phosphorylation , and metabolism ( Fig 5B ) . GO term analysis of Myc-regulated genes showed enrichment mainly of metabolism-related terms within the time frame of these experiments ( Fig 5B ) ; 387 of the 1 , 354 Ikaros-regulated genes identified by sequencing of chromatin-associated RNA were also differentially expressed in response to Myc induction , and thus were responsive to regulatory inputs from Myc as well as Ikaros . GO term analysis of these genes showed predominant enrichment of metabolic genes ( Fig 5B ) , similar to Myc-regulated genes . The remaining 967 Ikaros-regulated genes were not differentially expressed in response to Myc induction . GO term analysis of these genes showed enrichment mainly of adhesion , differentiation , the immune system , signaling , kinase activity and phosphorylation ( Fig 5B ) . Therefore , responsiveness to Myc separated Ikaros target genes broadly into those related to metabolism ( Myc-responsive ) and differentiation ( Myc-unresponsive ) . Ikaros and Aiolos directly bind to the Myc promoter and repress Myc at the transcriptional level [7 , 18 , 42] . Whether repression of Myc is essential for coordinating the regulatory roles of Ikaros and Myc in B cell progenitors is currently unknown , although it has been shown that Myc can override the down-regulation of Ccnd3 ( cyclin D3 ) and the up-regulation of the cell-cycle inhibitor Cdkn1b ( p27 ) by Ikaros and Aiolos [42] . These examples indicate that the regulation of at least some Ikaros target genes requires the repression of Myc . This raises the question of whether the regulation of target genes by Ikaros generally requires the down-regulation of Myc or whether there are classes of Ikaros target genes that do and do not require Myc repression . As an experimental system that removes Myc from the direct control of Ikaros , we simultaneously transduced B3 cells with both Ikaros-ERt2 and Myc-ERt2 and sequenced chromatin-associated RNA as described above . Of the 1 , 354 Ikaros target genes identified by induction of Ikaros-ERt2 alone , 512 differentially expressed also in the presence of Myc ( 240 were up-regulated , and 272 were down-regulated ) . We refer to these Ikaros target genes as “Myc-resistant” ( Fig 6A ) . The remaining 842 Ikaros target genes were only differentially expressed ( adj . P < 0 . 05 ) in response to Ikaros alone ( 422 up , 420 down ) but were not differentially expressed when Myc was expressed alongside Ikaros ( Fig 6A and 6B ) . We refer to these Ikaros target genes as “Myc-sensitive” ( Fig 6A ) . This analysis defined distinct sets of Ikaros target genes that do or do not require the down-regulation of Myc: coexpression of Myc neutralized the impact of Ikaros on Myc-sensitive target genes but not on Myc-resistant target genes ( Fig 6B ) . GO analysis demonstrated that Myc-resistant Ikaros target genes were enriched for functional terms related to signaling , adhesion , differentiation and development , and the immune system ( Fig 6A ) . By contrast , Myc expression did interfere with Ikaros regulation of target genes related to metabolism , proliferation , and mRNA translation ( Fig 6A ) . To ask whether these differences separated B cell–specific from housekeeping genes , we classified Ikaros-regulated genes during B cell progenitor differentiation as B cell specific or ubiquitously expressed . As a measure for how broadly genes are expressed , we used tau-values compiled from mouse Encyclopedia of DNA Elements ( ENCODE ) RNA-seq data across 22 tissues [43] . We assembled a panel of broadly expressed genes with tau-values < 0 . 25 that were expressed > 0 . 5 fragments per kilobase of exon model per million reads mapped ( FPKM ) in B3 cells as well as in spleen ( an organ rich in B cells ) , and a panel of tissue-specific genes with tau-values > 0 . 70 ( also expressed > 0 . 5 FPKM in B3 cells and spleen ) . We found that the distribution of tissue-specific and housekeeping genes was skewed between Myc-sensitive and Myc-resistant Ikaros target genes . Housekeeping genes were enriched among Myc-sensitive Ikaros targets ( P = 0 . 019 , odds ratio = 1 . 64 ) , and B3 tissue-specific genes were depleted among Myc-sensitive genes ( P = 2 . 122 × 10−5 , odds ratio = 0 . 42 ) . Conversely , Myc-resistant Ikaros target genes were enriched for B3-specific genes over housekeeping genes ( P value = 1 . 59× 10−7 , odds ratio = 3 . 57 ) . B3 tissue-specific genes were enriched , and housekeeping genes were depleted among Myc-resistant Ikaros targets ( Fig 6C ) . Validation experiments showed that Myc was able to override Ikaros in the regulation of most glycolysis and glutaminolysis genes ( S4A Fig ) and substantially reduced the impact of Ikaros on ECAR and OCR in metabolic flux assays ( S4B Fig ) . Consistent with data in primary pre–B cells [42] , Myc also prevented Ikaros-imposed cell-cycle exit of B3 cells ( S4C Fig ) . The regulatory relationship between Ikaros and Myc is illustrated by the target genes Igll1 ( dominated by Ikaros ) , Ccnd2 ( dominated by Myc ) , and Slc2a1 ( coregulated by Ikaros and Myc; S4D Fig ) . Analysis of Ikaros ChIP-seq data showed that promoters that were up- or down-regulated by Ikaros irrespective of Myc showed strong enrichment for Ikaros binding ( P < 2 . 2 × 10−16 , odds ratio = 6 . 30 and P < 2 . 2 × 10−16 , odds ratio = 4 . 05 , respectively; Fig 6D ) . Myc-sensitive Ikaros-regulated genes were also significantly enriched for Ikaros binding ( P < 2 . 2 × 10−16 , odds ratio = 5 . 92 for down-regulated and P < 1 . 7 × 10−13 , odds ratio = 2 . 08 for up-regulated genes compared to all expressed genes; Fig 6D ) , suggesting that many promoters may receive regulatory inputs from both Ikaros and Myc . The picture emerging from this analysis is that Ikaros regulates both ubiquitous and tissue-specific genes . Regulation of most ubiquitous genes by Ikaros is broadly sensitive to Myc dosage , whereas regulation of many tissue-specific genes by Ikaros is resistant to Myc dosage . These data are consistent with the existence of a regulatory circuit whereby Ikaros down-regulates Myc , and target gene expression reflects the combined effect of Ikaros expression and Myc down-regulation . The data suggest a model of progenitor cell differentiation in which the regulation of lineage-specific differentiation genes is coordinated with that of housekeeping genes . In B cell progenitor cell differentiation , such coordination is achieved by feedforward regulation of Myc by Ikaros; Fig 6E , left ) . Continued Myc activity interferes with the regulation of housekeeping functions and abolishes the coordinated regulation of housekeeping and lineage-specific differentiation genes ( Fig 6E , right ) . This model is consistent with the known role of Myc as a major regulator of metabolism , the cell cycle , and RNA transcription and translation [44] and provides a framework for how Ikaros-mediated Myc repression contributes to differential gene expression during B cell progenitor differentiation .
To identify transcriptional pathways that drive B cell progenitor differentiation , we developed the TWM algorithm , which identifies coherence between transcription factors downstream of Ikaros induction and their target gene expression over time . This approach pinpointed the transcriptional up-regulation of Foxo1 up-regulation and the repression of Myc as important components of Ikaros-mediated B cell differentiation . FOXO1 target genes are integral to Fr . D , including immunoglobulin light gene rearrangement [8 , 9 , 11] . Previously , several studies have shown that FOXO1 protein is activated and stabilized at the post-translational level during B cell progenitor differentiation [8 , 9 , 11] . Here , we demonstrate that the progressive transcriptional up-regulation of Foxo1 correlates with the expression of FOXO1 target genes at the single cell level . Perturbation experiments will be required to establish the extent to which transcriptional regulation of Foxo1 is a functional contributor to FOXO1 target gene expression during B cell progenitor differentiation . The coordination between proliferation , metabolic state , and differentiation is essential for normal development and homeostasis and has been attributed to antagonism between transcription factors that induce tissue-specific gene expression and cyclin-dependent kinases that promote cell-cycle entry [1–3] . By means of perturbation experiments designed to disrupt feedforward repression of Myc by Ikaros , we demonstrate that the regulation of lineage-specific differentiation genes can be dissociated from that of ubiquitously expressed genes , simply by uncoupling pathways by which Ikaros acts as an inducer of B cell progenitor differentiation from the repression of Myc . Destabilization of one state and implementation of another has been studied extensively in cellular reprogramming [45–47] , and our analysis introduces a similar idea to progenitor cell differentiation . Repression of Myc extinguishes key features of the undifferentiated state , and up-regulation of Ikaros family transcription factors—Foxo1 , and presumably others—promotes a shift to the differentiated state . Consistent with this model , metabolic Myc target genes [48] were mostly repressed ( S5B Fig ) , whereas FOXO1 target genes related to signaling , adhesion , and the immune system were mainly up-regulated ( S5B Fig ) . Reminiscent of the scenario described here , FOXO and Myc control cell proliferation and metabolism in endothelial cells [49] . In B cell progenitors , both Myc and Foxo1 are direct targets of Ikaros , which links the extinction of the Fr . C-like state and establishment of the Fr . D-like state . Integration between cell type–specific and ubiquitous gene expression programs by interconnected regulators may account for other cell-state transitions .
Mouse work was performed according to the Animals ( Scientific Procedures ) Act under the authority of project licence PPL70/7556 issued by the Home Office , United Kingdom . All work with mouse cells was in vitro , and the ARRIVE checklist is not applicable . Cell culture , retroviral transduction , RNA , and protein methods were as described by Ferreirós and colleagues [7] . Isolation of chromatin-associated RNA was done as described by Ma and colleagues [42] . To control for sources of variability , we implemented a scheme that tracks biological batches ( 3 ) , conditions ( Ikaros or control vector ) , time points ( 6 ) , library preparations ( 6 × 6 ) , bar codes , sequencing runs , and flow cell lanes . Each RNA-seq library was split into two ( total of 72 ) to account for variability associated with sequencing . For sequencing , the 72 libraries were distributed across 4 flow cells with 3 libraries per flow cell . Each lane contained different libraries , batches , time points , and conditions . We aimed for 50 million reads per library × 4 sequencing runs , equaling 100 million reads per sample . Strand-specific libraries were sequenced on an Illumina HiSeq 2500 , at 75 nucleotides paired-end . Analysis followed published guidelines [50] using Tophat2 “very-sensitive” mode only allowing a unique best mapping to map sequences to the mm10 reference genome . Trimming was applied to remove Illumina primers and low-quality nucleotides . ht-seq intersection-option was used to assign fragments to genes . We used cqn to correct for GC content and gene-length bias and a nonparametric version of ComBat to correct for RNA-seq library-preparation effects . We identified differential expression by combining limma [19] to identify sharp changes and maSigPro [20] to identify changes over time . In limma , we computed significant differences between Ikaros ( 4-OHT and Ikaros effects ) and control ( 4-OHT effects ) —between consecutive time points and between every time point and 0 h . To compute a final limma-derived P value for each gene , we combined all contrasts using eBayes function of limma and computed the F-statistic , the associated P value , and the adj . P value ( using Benjamini-Hochberg multiple testing correction ) . In maSigPro , we considered 2 conditions ( Ikaros and control ) and identified genes whose trends separated over time . We considered a gene to be differentially expressed if any of the following conditions applied: ( a ) limma FDR < 0 . 001 , ( b ) maSigPro R2 > 90% , or ( c ) limma FDR < 0 . 01 and maSigPro R2 > 60% . We used limma to analyze gene expression array data from www . immgen . org . We used Generally Applicable Gene-set Enrichment [51] to perform gene set analysis over ranked lists of genes [52] and Fisher test to perform gene set analysis over clusters of genes . We used default parameters and defined as significant those gene sets with associated Benjamini-Hochberg adj . P < 0 . 1 . We used gene sets included in the GSKB Bioconductor package [53] . S3 Fig describes the analysis step by step . A mathematical description is given in “Notation . ” Computing log2 fold change per contrast: ∀tfi∈TF , ∀∇j∈∇TestimatelogFCtfi , ∇j Computing aggregated log2 fold change for consecutive contrasts: ∀tfi∈TF , ∀C∇j= ( ∇a , ∇b ) ∈C∇TestimatelogFCtfi , C∇j=logFCtfi , ∇a+logFCtfi , ∇b Computing odds ratios: ∀tf∈TF , ∀∇j∈∇TestimateORtfi , ∇j Computing aggregated log2 fold change for consecutive contrasts ∀tfi∈TF , ∀C∇j= ( ∇a , ∇b ) ∈C∇TestimateORtfi , C∇j=ORtfi , ∇a+ORtfi , ∇b Computing direction for all genes and transcription factors for all contrasts: ∀g∈G , ∀∇j∈∇Testimatesigng , ∇j=sign ( logFCg , ∇j ) ∀tfi∈TF , ∀∇j∈∇Testimatesigntfi , ∇j=sign ( logFCtfi , ∇j ) Computing coherence per transcription factor for each gene and for each consecutive contrast: ∀tfi∈TF , ∀C∇j= ( ∇a , ∇b ) ∈C∇T , ∀g∈G|btfi , g=1∧dei∇a , g=1∧dei∇b , g=1 , computecohg , tfi , C∇j=1ifsigng , ∇a*signg , ∇b*signtfi , ∇a*signtfi , ∇b>00otherwise Computing coherence per transcription factor per consecutive contrast: ∀tfi∈TF , ∀C∇j= ( ∇a , ∇b ) ∈C∇T , ∀g∈G|btfi , g=1compute computecohtfi , C∇j=∑∀g∈G|btfi , g=1cohg , tfi , C∇j#g∈G|btfi , g=1∧dei∇a , g=1∧dei∇b , g=1 Combine log2 fold change and odds ratio measurements: ∀tfi∈TF , combtfi=∑∀C∇j∈C∇logFCtfi , C∇j*ORtfi , C∇j Combine all coherence: ∀tfi∈TF , cohtfi=∏∀C∇j∈C∇cohtfi , C∇j Combine all measurements: ∀tfi∈TF , TWMtfi=combtfi*cohtfi CEL files for 1404 B-ALL patients were obtained from their respective publications [23 , 54–57] . The raw data were normalized together with the Robust Median Average ( RMA ) algorithm , whereas systematic variations across studies were eliminated using ComBat . Differentially expressed genes between Ikaros-mutated and Ikaros wild-type subjects were identified with limma , using surrogate Variable Analysis [58] to account for possible latent confounders . Pathway enrichment analysis was performed using ( a ) mean-rank gene set enrichment [59] on gene sets from the Molecular Signature Database [52] and ( b ) GSEA [52] on Ikaros targets identified by Chip-seq in mouse B3 cells . Enrichment analysis was repeated on the 10 , 111 genes expressed in B3 cells . We analyzed ChIP-seq data for B cell–associated transcription factors ( S3 Table ) . EBF1 , PU . 1 , IRF4 [15] , PAX5 [60] , CTCF [6] , and RUNX1 [61] were from pro–B cells; FOXO1 was from pre–B cells [8]; Myc was from CH12 cells [62]; and Ikaros was from B3 cells [7] . We used Bowtie2 [63] for mapping to the mm10 reference genome . When fastq files were available , we used “end-to-end” and “very-sensitive” parameters , otherwise we used “local” parameter . In all cases , we filtered duplicated reads and any reads with quality scores below 20 . We applied CLCbio Peak Finder tool [37] to identify peaks for each sample using default parameters; we used control libraries when available ( S1 Table ) . We considered peaks with adj . P < 0 . 01 . DNase-seq was performed on 20 to 25 million cells with 3 biological replicates for all time points and conditions . Briefly , cells were harvested and washed with cold 1× PBS . Lysis conditions were optimized to ensure >90% recovery of intact nuclei . Enrichment of DNaseI hypersensitive fragments ( 0–500 bp ) was performed using a low-melt gel size selection protocol . Library preparation was performed and sequenced as 43-bp paired-end NextSeq 500 Illumina reads . DNaseI libraries were sequenced at a minimum depth of 20 million reads per each biological replicate and a total of 200 million per time and condition . DNase-seq reads were trimmed to 36 bp and paired-end mapped to the mm10 reference genome using Bowtie2 [63] with the following options: -v 2 -k 1 -m 1—best–strata . We used Wellington to identify the footprinting sites per time and condition [64] . We used MATCH algorithm from TRANSFAC to predict binding sites ( BSs ) of transcription factor motifs in FP . To minimize the number of false positive BS predictions we defined an FOS-related optimal threshold by using as a gold-standard the ChIP-seq IKZF1 peaks . We identified the optimal level of FOS [64] at which DNase-seq–derived Ikzf1 BS predictions obtained by MATCH were optimally ( minimizing false positives ) predicting CHIP-seq IKZF1 peaks . Proximal genes for ChIP-seq–and DNase-seq–derived peaks were identified with default parameters in RGmatch [38] . We isolated cells using the Fluidigm C1 System . Single-cell C1 runs were completed using the smallest IFC ( 5–10 μm ) . Cells were collected at a concentration of 400 cells/μl in a total of 50 μl . To optimize cell capture rates on the C1 , buoyancy estimates were optimized prior to each run . Single-cell capture efficiency was between 75% and 90% across 8 runs . Each C1 capture site was visually inspected for single-cell capture and cell viability . After visualization , the IFC was loaded with Clontech SMARTer kit lysis , RT , and PCR amplification reagents . After harvesting , cDNA was normalized across all libraries from 0 . 1 to 0 . 3 ng/μl , and libraries were constructed using Illumina’s Nextera XT library prep kit per Fluidigm’s protocol . Constructed libraries were multiplexed and purified using AMPure beads . The final multiplexed single-cell library was analyzed on an Agilent 2100 Bioanalyzer for fragment distribution and quantified using Kapa Biosystem’s universal library quantification kit . The library was normalized to 2 nM and sequenced as 75-bp paired-end dual indexed reads using Illumina’s NextSeq 500 system at a depth of approximately 1 . 0 to 2 . 0 million reads per library . Each Ikaros time point was performed once , with the exception of 18- and 24-h time points , in which 2 C1 runs were required in order to achieve approximately 50 single-cells per time point . We mapped 560 scRNA-seq libraries with Tophat2 [65] to the mouse Ensembl gene annotations and mm10 reference genome . We excluded single-cell libraries with a mapping rate less than 50% and less than 450 , 000 mapped reads; we obtained a total of 324 single cells for all subsequent analysis . Cufflinks [66] version 2 . 2 . 1 was used to quantify expression from single-cell libraries using Cuffquant . Gene expression data for each single-cell library were merged and normalized into a single data matrix using Cuffnorm . Monocle [21] was used to compute pseudotime trajectories , in which cells are ordered by their actual progress in the differentiation course rather than by their experimental time point . We filtered for cells with expression greater than 0 and grouped cells based on quantiles 0 . 33 and 0 . 66 of Foxo1 expression levels ( 3 levels: low , middle , and high ) . Then we did the same for each gene . Using both groupings , we computed a contingency table ( Fig 6C , left panel ) and a P value for each gene and defined genes as significantly regulated and not significantly regulated . We found that significantly regulated genes were enriched in FOXO1 targets ( P = 0 . 05 ) . We repeated the analysis , first by combining low and middle into a single level ( Fig 5C , middle panel , P < 0 . 05 ) and second by combining middle and high into a single level ( Fig 5C , right panel , P < 0 . 07 ) . Finally , we combined all significantly regulated definitions and considered a gene to be Foxo1 regulated if the contingency table analysis was significant for any of the 3 analyses . In this case , significantly regulated genes were enriched in FOXO1 targets ( P < 0 . 001 ) . To quantify and compare the role of time and Foxo1 mRNA levels in FOXO1 targets , we first filtered for cells with expression greater than 0 for each gene pair . Then we computed 2 linear models: in the first one , mRNA gene expression was predicted using time; in the second , mRNA gene expression was predicted using a 6-level grouping of Foxo1 mRNA expression . Finally , for each gene we compared the r2 values derived from each model . Measurement of ECAR and OCR was done using Seahorse XF24 or XF96 extracellular flux analyzers as advised by the manufacturers ( Seahorse Bioscience; North Billerica , MA ) . To assess the impact of Ikaros and Aiolos on ECAR and OCR , primary B cells were transduced with IRES-GFP , Ikzf1-IRES-GFP , or Ikzf3-IRES-GFP; sorted for GFP expression 72 h later; and rested for 3 to 6 h in cultured in the presence of IL-7 . “Immune system” includes the terms “immune , ” “host defense , ” “B cell , ” “T cell , ” “myeloid , ” “lymphocyte , ” “leukocyte , ” and “hematopoiesis . ” “Signaling” includes the terms “signal , ” “signaling , ” “response , ” “stimulus , ” “communication , ” and “activation . ” “Adhesion” includes the terms “adhesion” and “integrin . ” “Differentiation” includes the terms “differentiation” and “development . ” “Metabolism” includes the terms “metabolic , ” “metabolism , ” “biosynthetic , ” “biosynthesis , ” and “catabolic . ” “Translation” includes the terms “translation , ” “ribosome , ” and “ribonuclear . ” “Proliferation” includes the terms “proliferation , ” “chromatid , ” “spindle , ” “mitosis , ” “mitotic , ” “cell cycle , ” “cell division , ” “DNA synthesis , ” and “DNA replication . ” | The human body is made from billions of cells comprizing many specialized cell types . All of these cells ultimately come from a single fertilized oocyte in a process that has two key features: proliferation , which expands cell numbers , and differentiation , which diversifies cell types . Here , we have examined the transition from proliferation to differentiation using B lymphocytes as an example . We find that the transition from proliferation to differentiation involves changes in the expression of genes , which can be categorized into cell-type–specific genes and broadly expressed “housekeeping” genes . The expression of many housekeeping genes is controlled by the gene regulatory factor Myc , whereas the expression of many B lymphocyte–specific genes is controlled by the Ikaros family of gene regulatory proteins . Myc is repressed by Ikaros , which means that changes in housekeeping and tissue-specific gene expression are coordinated during the transition from proliferation to differentiation . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] | [] | 2019 | Feedforward regulation of Myc coordinates lineage-specific with housekeeping gene expression during B cell progenitor cell differentiation |
NMDA ( N-methyl-D-aspartate ) receptors and calcium can exert multiple and very divergent effects within neuronal cells , thereby impacting opposing occurrences such as synaptic plasticity and neuronal degeneration . The neuronal Ca2+ sensor Caldendrin is a postsynaptic density component with high similarity to calmodulin . Jacob , a recently identified Caldendrin binding partner , is a novel protein abundantly expressed in limbic brain and cerebral cortex . Strictly depending upon activation of NMDA-type glutamate receptors , Jacob is recruited to neuronal nuclei , resulting in a rapid stripping of synaptic contacts and in a drastically altered morphology of the dendritic tree . Jacob's nuclear trafficking from distal dendrites crucially requires the classical Importin pathway . Caldendrin binds to Jacob's nuclear localization signal in a Ca2+-dependent manner , thereby controlling Jacob's extranuclear localization by competing with the binding of Importin-α to Jacob's nuclear localization signal . This competition requires sustained synapto-dendritic Ca2+ levels , which presumably cannot be achieved by activation of extrasynaptic NMDA receptors , but are confined to Ca2+ microdomains such as postsynaptic spines . Extrasynaptic NMDA receptors , as opposed to their synaptic counterparts , trigger the cAMP response element-binding protein ( CREB ) shut-off pathway , and cell death . We found that nuclear knockdown of Jacob prevents CREB shut-off after extrasynaptic NMDA receptor activation , whereas its nuclear overexpression induces CREB shut-off without NMDA receptor stimulation . Importantly , nuclear knockdown of Jacob attenuates NMDA-induced loss of synaptic contacts , and neuronal degeneration . This defines a novel mechanism of synapse-to-nucleus communication via a synaptic Ca2+-sensor protein , which links the activity of NMDA receptors to nuclear signalling events involved in modelling synapto-dendritic input and NMDA receptor–induced cellular degeneration .
Ca2+ signals triggered by NMDA-type glutamate receptors can result in long-lasting changes of synaptic input and dendritic cytoarchitecture in phenomena commonly referred to as neuronal plasticity . On the contrary , NMDA receptors are also important players in neurodegenerative processes . Although both aspects require gene expression , our knowledge is still sparse concerning how these fundamental processes are regulated at the molecular level . The Janus face of neuronal NMDA receptor signalling is probably best reflected by the fact that the influx of Ca2+ ions is thought to act as one of the major mediators of synapto-nuclear signalling [1 , 2] and of excitotoxic cell death [3] . Within this scheme , a prevailing idea is the existence of Ca2+ microdomains coupled to the activation of synaptic and extrasynaptic NMDA receptors , and transducing incoming Ca2+ events to different downstream pathways [1–4] . In a series of elegant studies , Hardingham and colleagues [5–7] provided evidence that Ca2+ influx through synaptic NMDA receptors trigger nuclear cAMP response element-binding protein ( CREB ) phosphorylation via an extracellular signal-regulated kinase ( ERK ) -dependent pathway , whereas Ca2+ influx through extrasynaptic NMDA receptors leads via an ERK-independent pathway to a dephosphorylation of CREB termed CREB shut-off . As opposed to the synaptic pathway , the CREB shut-off signal is coupled to neuronal degeneration and cell death [7] . Thus , CREB-regulated gene expression appears to be a shared mechanism for both long-term plasticity and neuronal survival [1–3 , 8–10] . Although Ca2+ exerts its signalling functions via a variety of Ca2+ sensor proteins , pathways that result in a nuclear response to synaptic activity have primarily been based on signalling via calmodulin ( CaM ) [1 , 2] . In its Ca2+-bound state , CaM alters the properties of several other proteins and signalling cascades that have been implicated in diverse neuronal functions [11 , 12] . Whereas it is tacitly assumed that CaM is present in large excess in all cellular compartments , and therefore regulation of CaM signalling largely depends on binding of Ca2+ ions , a variety of additional EF-hand proteins have been identified in neurons , termed neuronal Ca2+ sensor ( NCS ) proteins . These NCS are believed to serve more-specific functions in neurons [13–15] . One of these NCS proteins is Caldendrin ( also termed CaBP1 ) [16 , 17] , a bipartite protein with a unique N-terminal half and a C-terminal half that contains four EF-hand motifs and qualifies Caldendrin as the closest relative of CaM in brain neurons . The second EF-hand is most likely cryptic [16 , 18] . Modelling of the C-terminal segment suggests that Caldendrin displays an altered surface-exposed amino acid residue distribution , especially at EF-hand 2 as compared to CaM [18] . Interestingly , the unique N-terminal half of Caldendrin exhibits no similarity to other known proteins [16] . Moreover , in contrast to the ubiquitously expressed CaM , Caldendrin is only present in a subset of synapses and seems to be exclusively and tightly associated with the somatodendritic cytoskeleton and the postsynaptic density ( PSD ) of mature principal neurons in brain regions with a laminar organization [16 , 19] . To test the hypothesis that Caldendrin might have specific functions in neurons that are distinct from those of CaM , we performed a yeast two-hybrid screen to identify specific interaction partners for the C-terminal half of Caldendrin . This strategy disclosed a novel Caldendrin-binding partner , named Jacob , which exhibits a remarkably restricted expression in cortical and limbic brain regions of mammals . We report that Jacob displays a distribution similar to that of Caldendrin in the PSD , dendritic spines , and dendrites , but in contrast to Caldendrin , is also found in neuronal nuclei . Activation of NMDA receptors induces nuclear trafficking of Jacob that is under the control of Caldendrin and Importin-α . Our data imply that nuclear Jacob participates in the CREB shut-off pathway , which might play a physiological as well as pathophysiological role in the control of dendritic cytoarchitecture , synapse number , and neuronal survival under conditions of increased NMDA receptor activity .
Utilizing yeast two-hybrid screening to identify binding partners for Caldendrin , we obtained eight independent clones of a hitherto uncharacterized gene product , which we termed Jacob . The longest cDNA clone encompassed an open reading frame of 1 , 596 bp encoding a 532–amino acid ( aa ) protein with a calculated molecular weight of 60 kDa ( Figures 1 and S1A ) . Several clones obtained from rat brain cDNA libraries reveal alternatively spliced Jacob transcripts ( Figure S1B ) , giving rise to multiple Jacob isoforms with apparently different molecular weights . Analysis of the primary structure of Jacob revealed a putative N-terminal myristoylation site and several potential phosphorylation sites for protein kinase C ( PKC ) , cAMP-/cGMP-dependent protein kinases , and protein tyrosine kinases ( Figures 1 and S1A ) . In addition , Jacob harbours a well-conserved bipartite nuclear localization signal ( NLS ) . Interestingly , this NLS is part of an incomplete IQ motif ( Figures 1 and S1A ) , a protein–protein interaction region characteristic for CaM binding [20–21] . In situ hybridization experiments revealed a strikingly restricted localization of Jacob transcripts in the limbic brain and cortical areas ( unpublished data ) , showing extensive overlap with Caldendrin mRNA expression ( see [19] ) . In accordance with in situ hybridization data , Jacob immunoreactivity ( IR ) was found predominantly in cortex and limbic brain structures , including the amygdala , the thalamus , and the hippocampus ( Figure 2A ) . At the cellular level , particularly intense immunostaining was observed in the somatodendritic compartment of pyramidal cells in cortex ( Figure 2B and 2C ) and hippocampus , which closely resembles that seen for Caldendrin [16 , 19] . Moreover , both proteins extensively colocalize in hippocampal primary neurons ( Figure S2 ) . At the ultrastructural level , Jacob IR was localized to a subset of asymmetric type I synapses on dendrites of cortical neurons ( Figure 2F–2H ) . Apart from its synaptic localization , intense label was present in patches in dendrites ( Figure 2E ) . In these patches , Jacob IR was mainly concentrated at the cortical cytoskeleton . In contrast to Caldendrin , intense Jacob immunolabelling was also seen in neuronal nuclei ( Figure 2D ) . Patchy IR was found both at the nuclear envelope and in the nuclear matrix . Subcellular fractionation experiments confirmed that Jacob is a synaptic and a nuclear protein . Differential centrifugation of brain protein fractions demonstrated that Jacob IR is associated with particulate fractions , including light and heavy membranes , and is prominently present in synaptosomes , synaptic junctional membranes , and the PSD fraction ( Figure 3A ) . Jacob , like Caldendrin [16] , is tightly associated with the PSD , since extensive Triton X-100 extraction resulted in a further relative enrichment of Jacob IR in the detergent-extracted PSD fraction . Interestingly , immunoblots of the crude nuclear fraction demonstrated the presence of prominent Jacob IR bands in the range of 62–70 kDa , whereas the major bands detected in PSD preparations migrated at 72–80 kDa in SDS-PAGE ( Figure 3A and 3B ) , a difference that most likely reflects posttranslational modification ( s ) . The architecture of the nucleus includes two overlapping nucleic acid–containing structures that are directly associated with the regulation of gene expression: the chromatin and the nuclear matrix . Therefore , we isolated highly pure nuclear matrix , heterochromatin , and euchromatin fractions . Interestingly , after chromatin fractionation , Jacob was found to be exclusively associated with the RNA polymerase II–containing euchromatin ( Figure 3C ) . Moreover , the Jacob-containing protein complexes immunopurified from euchromatin also contained significant amounts of DNA ( Figure 3D ) . In addition , the initial purification of the crude nuclear fraction showed an enrichment of the 62–70 kDa Jacob bands in the nuclear matrix ( D . C . Dieterich and M . R . Kreutz , unpublished data ) . This subcellular localization could be confirmed by subsequent extraction of nuclear protein components , including chromatin from COS-7 cells transfected with a green fluorescent ( GFP ) -Jacob fusion protein ( D . C . Dieterich and M . R . Kreutz , unpublished data ) . These findings suggest that Jacob is highly enriched at active sites of nuclear gene transcription and mRNA processing . Jacob harbours an N-terminal myristoylation consensus motif . Transfection of HEK-293 cells cultivated in the presence of 3H-myristic acid with a wild-type ( WT ) -Jacob-GFP construct , subsequent immunoprecipitation with a monoclonal anti-GFP antibody and immunoblotting revealed incorporation of radioactivity at a band immunoreactive to both a polyclonal GFP antibody ( Figure 3E ) and Jacob antiserum ( unpublished data ) . No incorporation was seen in controls transfected with GFP alone or with a myristoylation mutant , ΔMyr-Jacob-GFP , in which the crucial glycine at position 2 was mutated to alanine ( Figure 3E ) . In contrast to the WT-Jacob-GFP construct , transient transfection of COS-7 cells with the ΔMyr-Jacob-GFP construct led to an exclusive nuclear localization of the mutant protein ( Figure 3F ) . Jacob's primary structure exhibits a well-conserved bipartite NLS between aa 250–265 . To test for the functionality of this NLS , we generated a deletion mutant ( ΔNLS-Jacob-GFP ) lacking the six basic amino acid residues between 247–252 . Transfection of this construct in COS-7 cells resulted in an extranuclear localization of the mutant protein ( Figure 3F ) . Hence , the bipartite NLS seems to be necessary and sufficient for nuclear import of Jacob as the double mutant ΔNLS/ΔMyr-Jacob-GFP is extranuclear in transfected COS-7 cells . To elucidate functional consequences of nuclear versus extranuclear localization of Jacob in terms of structural plasticity , we transfected hippocampal primary neurons with different mutant ( ΔNLS-Jacob-GFP or ΔMyr-Jacob-GFP ) or WT-Jacob constructs . Transfection of these different mutants had drastic effects on cell morphology . WT-Jacob-GFP–transfected neurons as compared to GFP controls exhibited more , but less-complex , dendritic processes ( Figures 4A–4C and S3A ) . This effect was astonishingly rapid and was observed already after 6–12 h post-transfection . In sharp contrast to the WT-Jacob-GFP overexpression phenotype , ΔMyr-Jacob-GFP–transfected cells lost most of their dendritic processes within 12 to 24 h ( Figure 4A–4C ) . In these cells , the construct exclusively accumulated in the nucleus ( Figure 4A ) . Interestingly , the density of synaptic puncta was already reduced before the retraction of dendrites became visible , observed as early as 6 h following transfection ( Figure 4D and 4E ) . No effect on synapse number of WT-Jacob-GFP was seen even 24 h after transfection ( Figure 4E ) . This strongly suggests that the simplification of the postsynaptic receptive units precedes the retraction of the dendrite . The opposite was found after a lentiviral RNA interference ( RNAi ) -based knockdown of the nuclear Jacob isoforms harbouring exon 6 with the NLS ( RNAi-NLS-GFP ) . Quantitative immunoblot analysis and immunostainings showed that viral infection of cortical primary cultures led to a specific reduction of these nuclear Jacob isoforms ( Figure 4F , 4G , and 4I ) . Infected cells showed a slightly increased number of synapses and a more complex dendritic cytoarchitecture ( Figure 4H , 4J , and 4K ) . Similarly , overexpression of ΔNLS-Jacob-GFP caused an increase in the number of dendrites , but had no effects on the number of synapses ( unpublished data ) , providing further evidence that the reduction of synaptic contacts directly correlates with the presence of Jacob in the nucleus . Alternative splicing generates splice isoforms like Δex9-Jacob that contain the NLS but lack large parts of the carboxy-terminus ( Figure S1B ) . We generated a myristoylation-deficient construct of this isoform ( ΔMyr-Δex9-Jacob-GFP ) , which accumulated in the nucleus after transfection of primary neurons , and its overexpression resulted in a comparable reduction of dendritic complexity and synapse number as those seen with ΔMyr-Jacob-GFP ( Figure 4A–4E ) . On the other hand , overexpression of a construct lacking the first 235 amino acids ( C-term-Jacob-GFP ) had no morphological consequences despite the presence of the NLS and its exclusive nuclear localization ( Figures 4E and S3 ) . Taken together , these data provide strong evidence that the reduction of synaptic contacts directly correlates with the presence of Jacob in the nucleus and that the N-terminal half and the NLS are pivotal for Jacob's morphogenetic impact on dendritic architecture . Since the NLS is not only essential , but also sufficient to target Jacob fragments to the nucleus , and the N-terminal half of the protein is crucial and sufficient to elicit the strong pleiomorphic negative effects on neurite and synapse number of nuclear Jacob , we next investigated the Caldendrin binding region in Jacob and vice versa , as well as the functional consequences of Caldendrin binding in more detail . Mapping of binding domains within both proteins was performed using deletion constructs for cotransformation in yeast two-hybrid assays . In Caldendrin , the region containing the first and the second , probably cryptic , EF-hand was found to be essential for Jacob binding ( Figure 5A ) . Strikingly , in Jacob , we could map the Caldendrin binding region to the central α-helical region that harbours the bipartite NLS . Deletion of the first six basic residues of the NLS led to significantly reduced Caldendrin binding ( Figure 5A ) . To substantiate the yeast two-hybrid data , we verified the interaction between Jacob and Caldendrin , employing pull-down assays from brain tissue using a glutathione S-transferase ( GST ) -Caldendrin fusion protein . In this assay , the interaction of Caldendrin and Jacob was found to be Ca2+ dependent inasmuch as 1 μM free Ca2+ in the buffer was required to pull down recombinant Jacob ( Figure 5B ) . Strikingly , CaM did not bind to Jacob at any Ca2+ concentration tested ( Figure 5C ) , and CaM did not compete with GST-Caldendrin for binding to Jacob ( Figure 5D ) . Further evidence for a bona fide interaction of the two proteins was provided by the binding of Jacob to an anti-Caldendrin antibody column and vice versa ( Figure 5E ) . These findings are consistent with the colocalization of Jacob and Caldendrin in dendrites and dendritic spines in hippocampal primary neurons observed by confocal laser scans ( Figure S2B ) . Importantly , the coimmunoprecipitation of Caldendrin from rat brain required the presence of Ca2+ and was not visible after addition of EGTA to the precipitation buffer ( Figure 5F ) . Thus , the interaction of Caldendrin and Jacob in vitro and in vivo is strictly Ca2+ dependent . Three-dimensional modelling substantiated the idea that structural differences in Jacob binding surfaces of Caldendrin and CaM [18] can explain the above findings . In crystallographic structures of CaM-peptide complexes , a helical peptide binds to one or both hydrophobic pockets formed by pairs of either EF-hands 1 and 2 or EF-hands 3 and 4 of CaM . The residues forming the two hydrophobic binding pockets are identical in CaM and Caldendrin . However , the binding affinities for the various peptides are given by the size and shape of the pocket , which has been classified as open , semi-open , or closed [22] . This size is dynamically regulated by the Ca2+ binding states of the EF-hands , which are not rigid structural units , but may function as hinges at low Ca2+ concentration [23] . Indeed , the second EF-hand of Caldendrin is incapable of binding Ca2+ , which in turn results in different binding dynamics at the first hydrophobic pocket compared to CaM . Interestingly , the Jacob sequence does not match any pattern for a typical CaM binding site , but has two incomplete IQ motifs ( residues 237–247 , aisvfRGyaeR , and residues 260–269 , IQrnfRkhlr ) within a central region ( residues 229–272 ) containing the bipartite NLS ( residues 247–266 , PSORTII , [24] ) . Several CaM binding sequences within α-helices have been defined that contain an IQ motif [20–21 , 25] , which was originally suggested to classify Ca2+-independent peptide binding according to the referential CaM/IQ complex . Modelling of the Caldendrin interaction site ( Figure 5G ) suggested that the phenylalanine at position 241 is absolutely essential for the protein interaction , and we therefore generated a point mutation at this position ( substitution of F to E ) . This F241E mutant construct indeed showed no interaction with Caldendrin in yeast ( Figure 5A ) , supporting the assumption that the first part of the central α-helix overlapping with the NLS is the Caldendrin binding region . This α-helical region fits neatly into the hydrophobic pocket generated by EF-hands 1 and 2 and resembles binding to the Ca2+ sensor protein in the manner of an “open” hydrophobic pocket as closely related to the binding of CaMKII to CaM , than the “semi-open” binding in MyosinI/CaM . Moreover , this largely excludes the second incomplete IQ motif as an active binding site for Caldendrin . Accordingly , mutations of residues 260 and 261 , IQ to GG , yielded only minor differences in the binding properties of Jacob to Caldendrin in yeast ( Figure 5A ) . In summary , it is predicted that Caldendrin will bind to comparable structures in the presence of a large excess of CaM , suggesting that the Caldendrin–Jacob interaction has evolved independently of CaM-signalling pathways . Even more interesting , binding of Caldendrin to Jacob can be predicted to reduce or inhibit the accessibility of the NLS . The transport of proteins from the cytosol through the nuclear pore complex into the nucleus depends on the binding of Importins to a specific NLS within the cargo . Within this scheme , Importin-α functions as an adapter molecule by binding both the NLS-bearing protein and Importin-β . Structural modelling suggests that Caldendrin binding will potentially occupy Jacob's NLS , thereby masking this binding site for interaction partners that are likely involved in Jacob's nuclear localization . We tested this hypothesis first by confirming an interaction of Jacob with Importin-α . Coimmunoprecipitation of Importin-α1 from rat cortex indeed suggests a potential in vivo interaction of both proteins ( Figure 5H ) . In pull-down experiments , we found specific binding of myc-his–tagged WT Jacob , but not of the ΔNLS-Jacob mutant to GST-Importin-α1 ( Figure 5I ) . The binding of GST-Importin-α1 was not affected by the presence or absence of Ca2+ ( unpublished data ) . We next investigated whether the binding of Importin-α1 can be competed by equimolar amounts of recombinant Caldendrin . Indeed , these studies revealed a competition between Caldendrin and Importin-α1 for binding to Jacob in the presence of Ca2+ ( Figure 5J ) . Interestingly , no competition was seen in the presence of EGTA , suggesting that elevated Ca2+ levels are needed for Caldendrin to mask the NLS in Jacob . An elegant recent study established a role of the classical Importin-mediated nuclear import for synapse-to-nucleus communication [26] . In this study , translocation of Importin-α1 and -α2 from distal dendrites to the nucleus was observed requiring NMDA receptor activity . Under resting conditions , however , dendritic Importins are largely immobile . Potential cargos associated with this translocation are at present unknown . Since Jacob is localized both to synapses and the nucleus , and harbours a bipartite NLS , which is bound by Importin-α1 and masked in a Ca2+-dependent manner by Caldendrin , we initially tested whether increased NMDA receptor activity will alter the intracellular localization of Jacob . For this purpose , we stimulated hippocampal primary cultures with NMDA for 3 min and quantified for endogenous Jacob the IR fluorescence signal intensity of propidium iodide–counterstained neuronal nuclei . Jacob IR increased significantly in neuronal nuclei within 30 min after NMDA receptor activation , with highest levels after 2 h ( Figure S4A ) . Nuclear Jacob IR returned to control levels within 4 h ( Figure S4A ) . As previously reported [26] , Importin-α1 accumulates in the nucleus in a similar time frame . Interestingly , no recruitment of Caldendrin to the nucleus was observed ( unpublished data ) . Bath application of glutamate led to a significantly increased nuclear accumulation of Jacob IR within a comparable time frame to NMDA receptor activation ( Figure S4B ) . This accumulation could be completely blocked by coincubation of the competitive NMDA receptor antagonist DL-APV ( DL-2-amino-5-phosphonopentanoic acid ) , indicating that activation of NMDA receptors is crucial for glutamate-induced recruitment of Jacob to neuronal nuclei ( Figure S4B ) . To exclude the possibility that stimulation of primary neurons alters the accessibility of the nuclear Jacob antigen to the antibody , we performed quantitative western blot analysis on neuronal nuclei from organotypic hippocampal slice cultures stimulated with the same protocol . These experiments showed a significant increase in intensity of the two major Jacob nuclear isoforms ( 62 kDa/70 kDa ) 2 h after stimulation ( Figure S4C and S4D ) . Moreover , application of anisomycin after NMDA receptor activation did not affect the increase of nuclear Jacob IR , indicating that a recruitment of already existing extranuclear protein underlies the increased Jacob levels in hippocampal nuclei , but not de novo protein synthesis ( Figure S4C and S4D ) . Using quantitative fluorescence time-lapse microscopy of hippocampal primary neurons transfected with WT-Jacob-GFP or the ΔNLS mutant , we found that the presence of the NLS is essential for the nuclear translocation of Jacob . Glutamate stimulation of WT-Jacob-GFP–transfected cultures kept in the presence of anisomycin resulted in an increase of somatic and nuclear GFP fluorescence with a time course comparable to that of the endogenous protein ( Figure 6A–6D ) . The nuclear accumulation of Jacob-GFP , however , was not seen in neurons transfected with the ΔNLS mutant Jacob-GFP construct ( Figure 6E and 6F ) , suggesting that the presence of the binding site for Importin-α1 is a prerequisite for Jacob's nuclear accumulation . Importantly , concomitant to the nuclear accumulation of WT Jacob , the GFP fluorescence decreased in proximal and distal dendrites ( Figure 6C ) , an effect that was absent in ΔNLS-Jacob-GFP–transfected neurons . This indicates that the presence of the NLS and the interaction with Importin-α1 are not only important for the nuclear import , but are also crucial for Jacob's transport from dendrites to the nucleus . To learn more about the role of Caldendrin for the extranuclear retention of Jacob , and to understand the apparently contradictory findings ( i . e . , NMDA receptor activation with subsequent Ca2+ influx leading to Jacob's nuclear import and concomitantly Caldendrin binding preventing this process at high synapto-dendritic Ca2+ levels ) , we analyzed the transport process of Jacob in more detail using confocal laser scan microscopy . A brief depolarization of hippocampal neurons with KCl also induced a translocation of Jacob and Importin-α1 to the nucleus in the presence of anisomycin ( Figure 7A and 7B ) . However , the nuclear accumulation of both proteins was less pronounced than after glutamate receptor stimulation . Importantly , this effect was completely abolished in the presence of the NMDA receptor antagonist DL-APV ( Figure 7A and 7B ) , indicating that raising intracellular Ca2+ levels by other means than NMDA receptor activation is not sufficient to drive Jacob and Importin-α1 into the nucleus . NMDA receptors are situated both at synaptic and extrasynaptic sites [27 , 28] . Bath application of NMDA is considered to affect preferentially , but not exclusively , extrasynaptic NMDA receptors [6 , 7] . To differentiate between these two populations , we indirectly stimulated hippocampal cultures by incubation with the GABAA receptor antagonist bicuculline . The blockade of inhibitory synapses leads to an increased release of glutamate at synaptic sites , and resulted as expected in an increased accumulation of Jacob and Importin-α1 in the nucleus ( Figure 7C and 7D ) . This effect , however , was much less distinct as compared to the bath application of NMDA . A co-incubation with the noncompetitive NMDA receptor antagonist MK-801 attenuated the nuclear accumulation of Jacob and Importin-α1 to levels indistinguishable from control conditions ( Figure 7C and 7D ) . Since MK-801 is an irreversible open channel blocker , we took advantage of this fact to differentiate between synaptic and extrasynaptic NMDA receptors . After washout of the drug following stimulation of synaptic glutamate receptors , we applied NMDA to the bath solution to exclusively activate extrasynaptic NMDA receptors . Interestingly , this regime induced a marked nuclear translocation of Jacob and Importin-α1 that was more prominent than the accumulation after stimulation of synaptic NMDA receptors ( Figure 7E and 7F ) . Synaptic NMDA receptors contain predominantly the NR2A subunit , whereas their extrasynaptic counterparts contain mainly the NR2B subunit [29] . To test the hypothesis that the nuclear translocation of Jacob and Importin-α1 requires activation of NR2B-containing NMDA receptors , we repeated the experiments outlined above in the presence of the NR2B-specific antagonist ifenprodil . Intriguingly , in the presence of ifenprodil , the nuclear import of Jacob and Importin-α1 could be completely blocked after bath application of NMDA ( Figure 7G and 7H ) . These results show that the nuclear import of these two proteins requires signalling via the largely extrasynaptically localized NR2B-containing NMDA receptors . To follow up this hypothesis in more detail , we transfected a GFP-Caldendrin construct into hippocampal primary neurons . Expectedly , overexpression of Caldendrin blocked the increase of endogenous nuclear Jacob IR after synaptic stimulation at day in vitro ( DIV ) 16 , indicating that the interaction with Caldendrin masks the bipartite NLS of Jacob ( Figure 8A and 8B ) . However , after stimulation of extrasynaptic NMDA receptors , overexpression of Caldendrin attenuated Jacob's nuclear import much less efficiently ( Figure 8A and 8B ) . We therefore checked whether RNAi knockdown of Caldendrin ( Figure S5 ) affects the nuclear trafficking of Jacob differentially after synaptic and extrasynaptic NMDA receptor stimulation . We found that the nuclear immunofluorescence for Jacob was significantly increased in cells with reduced Caldendrin levels after enhancing synaptic activity with bicuculline at DIV 16 ( Figure 8C–8E ) , whereas the Caldendrin knockdown had no effect on Jacob's nuclear import after activation of extrasynaptic NMDA receptors . This points to a regulatory function of this protein–protein interaction in nuclear trafficking of Jacob after enhanced synaptic activation that is related to the competitive accessibility of Jacob's NLS for either Caldendrin or Importin-α binding . The predominant Ca2+- and NMDA receptor–activated signalling pathways to the nucleus in neurons funnel through the activation of the transcription factor CREB [1–2] . Previous work has shown that extrasynaptic NMDA receptor activation results in a dephosphorylation of CREB at Ser133 ( pCREB ) that renders it transcriptionally inactive and , therefore , constitutes a CREB shut-off signal [7 , 30] . Because Jacob was most efficiently targeted to neuronal nuclei after extrasynaptic NMDA receptor activation , we next addressed the question of whether the presence or absence of Jacob in the nucleus affects the phosphorylation of CREB at this crucial serine residue . As a first proof of principle , we explored whether nuclear overexpression of the ΔMyr-Jacob-GFP construct significantly reduced the levels of pCREB in hippocampal primary neurons as compared to untransfected or GFP-transfected controls under resting conditions ( Figure 9A and 9B ) . Indeed , infection of cortical primary cultures with a Semliki Forest virus–expressing ΔMyr-Jacob-GFP led to drastically reduced pCREB levels as evidenced by quantitative immunoblotting , whereas total CREB levels were not affected ( Figure 9C and 9D ) . To more rigorously test the hypothesis that Jacob is part of the CREB shut-off signalling pathway , we induced a knockdown of nuclear Jacob using plasmid-based RNAi constructs targeting exon 6–containing isoforms of the protein and subsequently stimulated extrasynaptic NMDA receptors with the protocol outlined above . We found that nuclear knockdown of Jacob completely abolished the reduction of pCREB observed after stimulation of extrasynaptic NMDA receptors ( Figure 9E and 9F ) . These data point to a critical role of Jacob for survival of hippocampal primary neurons after triggering the CREB shut-off pathway . We therefore decided to assess next whether the absence of Jacob in the nucleus enhances neuronal survival after triggering CREB shut-off with the stimulation of extrasynaptic NMDA receptors . To this end , we chose in situ TdT-3′end labelling to visualize DNA fragmentation in hippocampal primary neurons as a measure of apoptotic cell death . Using this assay , we found that the number of neurons showing fragmented DNA after sustained extrasynaptic NMDA receptor activation was clearly reduced under conditions of nuclear knockdown of Jacob as compared to untransfected cells from the same plate or independent GFP-transfected controls from other plates ( Figure 10A and 10B ) . Accordingly , the number of condensed propidium iodide–positive nuclei after nuclear knockdown of Jacob was reduced in the same manner as compared to controls ( Figure 10C and 10D ) . A prominent consequence of bath application of NMDA to primary cultures is the reduction of synaptic contacts within a few hours [34] . Importantly , we found that this reduction requires gene transcription . Coincubation of NMDA with actinomycin-D , an inhibitor of RNA Polymerase II , completely blocked the loss of synaptic contact sites in treated cultures 4 h after stimulation ( Figure 11A and 11C ) . Thus , in line with previous work , loss of synapses appears to be an early event of structural breakdown in cultures treated with bath application of NMDA and requires gene transcription . To further strengthen the point that Jacob is upstream of a transcription-dependent cell death pathway following excessive extrasynaptic NMDA receptor activation , we performed a plasmid-based RNAi knockdown of nuclear Jacob isoforms . Using this approach , we found that the knockdown of Jacob in the nucleus not only prevented CREB shut-off , but also preserved the structural integrity of transfected neurons . As evidenced by immunostainings with the presynaptic marker bassoon quantified 4 h after stimulation , the number of synapses in cultures transfected with RNAi targeting of nuclear Jacob isoforms was essentially the same compared to cultures transfected with a control RNAi vector ( scrRNA-GFP ) . Most importantly , however , after bath application of NMDA , the number of synapses dropped only in cultures transfected with the control vector but not in Jacob RNAi-transfected cultures ( Figure 11B and 11D ) . Thus , the absence of nuclear Jacob prevents not only CREB shut-off and subsequent neuronal degeneration , but also early events of structural disintegration related to loss of synaptic input .
In this study , we identified a novel neuronal protein pathway that is well suited to couple NMDA receptor signalling to the cell nucleus and to trigger long-lasting changes in the cytoarchitecture of dendrites and the number of spine synapses . This novel pathway particularly couples activation of NR2B-containing NMDA receptors to morphogenetic signalling via the nuclear trafficking of Jacob . At resting conditions , Jacob is attached to extranuclear compartments in an either Importin-α bound or unbound state ( see also Figure 12 ) . Ca2+ influx through synaptic and extrasynaptic NMDA receptors is followed by a translocation of Importin-α from synapses and dendrites to the nucleus , and we propose that Importin-α–bound Jacob will be concomitantly recruited to the nucleus . Moreover , the presence of the NLS is essential for Jacob's translocation , indicating that trafficking from dendrites to the nucleus and not only nuclear import already requires the classical Importin pathway . This is reminiscent of previous data showing NMDA receptor-dependent Importin trafficking from dendrites to the nucleus [26] , and establishes Jacob as the first identified cargo of this trafficking event . Accordingly , we always found a tight correlation between Jacob's and Importin-α1 nuclear translocation . Caldendrin binding can mask the bipartite NLS of Jacob in competition with Importin-α and thereby prevent its nuclear trafficking ( Figure 12 ) . However , in contrast to Importin-α binding , this requires high Ca2+ levels and not only NMDA receptor activation ( Figure 12 ) . We propose that Caldendrin will target Jacob to spine synapses after enhanced synaptic activation ( Figure 12 ) . In support of this hypothesis , we could provide evidence that activation of NR2B-containing NMDA receptors , which are mainly located at extrasynaptic sites , is crucial for the nuclear import of Jacob and Importin-α1 . Interestingly , we found that blocking this receptor subtype did attenuate the nuclear accumulation of both proteins after stimulation of synaptic NMDA receptors that contain predominantly , but not exclusively , the NR2A subunit [29–31 , 35–38] . This suggests the intriguing possibility that the nuclear Jacob-Importin pathway is physically coupled to NR2B-containing NMDA receptors and that the presence or absence of Ca2+-bound Caldendrin in the respective synapto-dendritic compartment will decide whether local Jacob shuttles to the nucleus or not . On the basis of the characteristics and consequences of its nuclear import , we found conclusive evidence that Jacob is part of the CREB shut-off pathway . The most prominent nuclear target of neuronal NMDA receptor signalling is the transcription factor CREB [1–2 , 8–9] . Subsequent to its phosphorylation at serine 133 , pCREB triggers gene expression crucially involved in processes of synaptic plasticity and neuronal survival [8–9] . Analysis of this pathway has demonstrated that synaptic NMDA receptors strongly activate CREB-dependent gene expression , whereas extrasynaptic NMDA receptors trigger a CREB shut-off [7] . A most intriguing finding in recent years has been that the antagonistic signalling of extrasynaptic versus synaptic NMDA receptors resembles their opposing actions on the activation of ERK kinase [6 , 39–41] . Activation of synaptic NMDA receptors is coupled to the Ras-ERK pathway and subsequent CREB phosphorylation , whereas extrasynaptic NR2B-containing receptors promote dephosphorylation and inactivation of the Ras-ERK-pathway [6 , 39–41] . One caveat of this scenario , however , is that shutting down Ras-ERK alone cannot explain the shut-off of CREB since other mechanisms , and here prominently nuclear CaMK-IV , should be in principal sufficient to phosphorylate CREB in the absence of ERK activity [8–9] . Thus , the opposing influence of both types of NMDA receptors after bath application of NMDA requires another mechanism that will actively trigger CREB shut-off . Our data suggest that the same conditions that trigger shut-off of CREB and the Ras-ERK pathway drive Jacob into the nucleus . Overexpression of Jacob in the nucleus—without activating these pathways—is sufficient to attenuate CREB phosphorylation , and a nuclear knockdown of Jacob prevents CREB shut-off as well as neuronal cell death after triggering the pathway . Finally , the rapid loss of synaptic contacts , one of the hallmarks of bath application of NMDA in hippocampal primary cultures , was prevented by reducing the amount of nuclear Jacob . Noteworthy in this regard is the observation that CREB shut-off cannot be induced in young cultures ( <DIV 7 ) [30 , 42] , a developmental stage at which Jacob protein levels are very low ( unpublished data ) . We therefore propose that nuclear Jacob is an essential component of CREB shut-off that might be actively involved in rendering CREB in a dephosphorylated state . What is Jacob's physiological role in the nucleus ? In initial experiments , we could not establish a direct binding of Jacob to CREB although both proteins are found in the overlapping fractions after gel filtration of nuclear protein complexes ( unpublished data ) . Therefore , it is conceivable that Jacob is indirectly coupled via CREB-binding proteins to the CREB signalosome . To further support a role in gene expression , we provided substantial evidence that Jacob is highly enriched in two nuclear compartments associated with gene transcription and pre-mRNA processing . Jacob is abundant in euchromatin fractions and therefore present at active sites of gene transcription . The protein harbours long stretches of basic amino acid residues , which are well suited for DNA binding , although no known DNA binding motif was identified in its primary structure . Particularly with regard to the phenotype of its nuclear overexpression that involves a rapid destabilization of synaptic contacts and a retraction of dendrites , and which cannot be explained entirely by CREB shut-off , it is reasonable to assume that Jacob will be part of additional nuclear signalling events . The nature of such signalling events will be obviously related to the circumstances of Jacob's nuclear trafficking . CREB shut-off has been largely assigned so far to pathophysiological insults , including spill-over of glutamate after excessive stimulation or reversal of glutamate transporters in the context of epileptic seizures or brain ischemia [3] . This view , however , probably has to be extended because in recent years , a number of observations raise the possibility that the activation of extrasynaptic NR2B-containing NMDA receptors can occur in a physiological context . It was shown that in several brain regions , sustained synaptic activation causes spillover of synaptically released glutamate to nonsynaptic sites [43–49] . In addition , sustained synaptic activation favours nonsynaptic release of glutamate from astrocytes [50–52] , and it has been suggested that this glia-neuron transmission via extrasynaptic NMDA receptors has profound effects on non–Hebbian types of neuronal plasticity [53] . Moreover it was also claimed that activation of extrasynaptic NMDA receptors might directly induce heterosynaptic long-term depression at certain synapses in close proximity [54] . The evolving concept behind these studies is the idea of homeostatic scaling of synaptic input . Homeostatic plasticity refers to a process by which principal neurons in particular constantly adjust the integration of synaptic input to optimize the contribution of a single synapse with reference to its location in the dendrite and the synchronized activity in a given neuronal network [55 , 56] . A major aspect of homeostatic plasticity is the fact that uncontrolled potentiation of synapses will induce a ceiling effect characterized by epileptic activity and a decoupling of a given neuron from the dynamics of presynaptic input . Homeostatic plasticity reflects the necessity to either remove certain synapses that contribute less efficiently to the optimal activity within a neuronal network or to reduce the level of potentiation of synapses in this network . Jacob's nuclear accumulation and its rapid morphogenetic effects are in favour for a role in the regulation of plasticity-related gene expression related to homeostatic synaptic plasticity . Interestingly , this role includes a stripping of synaptic contacts that precedes the simplification and regression of dendritic processes . It is therefore conceivable that the loss of synapses is the initial trigger for the retraction of dendritic arbors . Moreover , this process is surprisingly rapid , indicating that synapses are actively destabilized . This in turn suggests that Jacob either blocks an essential nuclear signalling event required to prevent the removal of synaptic input or regulates the expression of genes that will actively destabilize synapses . It is likely that the CREB shut-off pathway will be part of this mechanism , but it is unclear whether it is sufficient to trigger solely the course of events following Jacob's nuclear import . A further intriguing aspect of this study is that it provides the first demonstration that an EF-hand CaM-like Ca2+ sensor protein regulates the nuclear localization of a protein by competitive binding to its NLS in a Ca2+-dependent manner . The significance of this novel mechanism of neuronal Ca2+ signalling is further underscored by the fact that binding of Caldendrin is specific in that its ancestor and closest relative in brain , CaM , did not bind to Jacob at any Ca2+ concentration tested . This is of importance since CaM levels are probably more than a magnitude higher in neurons than those of Caldendrin [18] , and Ca2+ binding affinities are comparable between both proteins [57] . Computer modelling based on templates from crystallized structures shows that the outer surface of solvent-exposed amino acids , particularly EF-hand 2 , which seems to be crucial for binding to Jacob , and another recently identified binding partner light chain 3 ( LC3 ) [58] are covered by residues that clearly differ between CaM and Caldendrin [18] . Accordingly , LC3 , a component of the microtubular cytoskeleton , apparently does not bind to CaM [58] . The principal specificity of Caldendrin protein interactions is further supported by the observation that very few mutations occurred in this region during vertebrate development and that none of these mutations affected the solvent-exposed amino acids of EF-hand 2 [18] . Thus , the singularity of the Caldendrin surface is intrinsic and independent from insertions or deletions , and we therefore suggest that this is probably due to adaptations of its surface to a specific localization and function in neurons of higher vertebrates . How could this singularity with respect to other Ca2+ binding proteins relate to Caldendrin's neuronal function ? In contrast to the interaction with Jacob , Caldendrin binding to most of its interaction partners is Ca2+ independent , as already described above for the LC3 interaction [57] . For instance , Ca2+- , CaM- , and ATP-independent interaction of the C-terminal half of Caldendrin/CaBP1 was demonstrated for the inositol trisphosphate receptor ( ( InsP3R ) [59–60] . The functional consequence of Caldendrin binding is a reduction of InsP3-triggered intracellular Ca2+ release [59 , 60] . At the synapse , a Ca2+-independent binding was reported for L-type voltage-dependent CaV1 . 2 Ca2+ channels [61 , 62] . This interaction will probably lead to increased Ca2+ currents following synaptic activation and thereby indirectly via increased synaptic activity could promote Caldendrin's and possibly Jacob's synaptic localization . Low synaptic activity and , hence , low synapto-dendritic Ca2+ levels will instead favour Caldendrin's binding to the InsP3R . It is therefore conceivable that Caldendrin can thereby directly lower Ca2+ levels in dendritic microdomains , and in consequence , negatively regulate its own association with Jacob . Therefore , a switch of binding partners could directly relate to Caldendrin's role in regulating Jacob's nuclear transition . Along these lines , it can be predicted that keeping the delicate balance between Jacob's nuclear and extranuclear localization via Caldendrin binding will provide a powerful regulatory mechanism in the transformation of dendritic Ca2+ signals into morphogenetic signals for the dendritic cytoarchitecture of principal neurons under pathophysiological and probably also under physiological conditions .
Yeast two-hybrid screening was performed as described previously [63] . Library screening was done with a rat brain cDNA library in pACT2 ( Matchmaker-GAL4 Two-Hybrid II; Clontech ) . The bait construct consisted of the entire open reading frame of Caldendrin cloned in frame into the pAS2–1 vector . A total of 3 . 5 × 106 cotransformants were screened , and 108 clones were picked , which turned blue within 6 h in the initial test and after retransformation . Eight of these clones were found to encode a novel protein . Interactions were scored for ß-galactosidase activity by a colony lift assay . Binding activity of different constructs after retransformation was evaluated in three independent experiments . A rat brain hippocampus cDNA Lambda ZAPII library ( Stratagene ) was screened with a cDNA probe encompassing the first 400 bp of Jacob's open reading frame . cDNA labelling , filter hybridization , and subcloning were done using standard procedures [16] . Cloning of full-length murine Jacob was done by reverse transcriptase PCR ( RT-PCR ) from mouse brain with primers encompassing the start and stop codon of rat Jacob . The PCR product was cloned into a TOPO TA vector ( Invitrogen ) and sequenced . A list of the constructs employed in this study is provided in Text S1 . Two peptides ( aa 285–299 and aa 300–314 ) , the GST fusion proteins GST-J1–230 and GST-J253–404 were used to immunize two rabbits and one guinea pig each . Specificity of the antibodies was tested on immunoblots of crude rat brain homogenate by preabsorption of the antibodies with corresponding N-terminal or C-terminal ( J262–532 ) MBP fusion proteins or with affinity-purified antiserum . Immunohistochemistry and immunocytochemistry were performed essentially as described previously [19] ( see Text S1 for more details ) . Details of confocal laser scan microscopy and time-lapse imaging experiments can also be found under Supplementary Materials and Methods in Text S1 . See Supplementary Materials and Methods in Text S1 for details . For RNAi treatment , oligonucleotides with the sense/antisense sequence ( 19–21 bp ) linked by a 9- or 10-bp–long stemloop sequence were obtained from Biomers . Sequences were as follows: nuclear Jacob knockdown ( RNAi-NLS: 5′ AGA ATG ATT CCG CGT CTG TAA 3′/bp 892–912 of the Jacob cDNA ) ; nuclear Jacob scrambled control ( scrRNA: 5′ AGA TAT AGT CGC CGT CTG TAA 3′ ) ; all Jacob isoforms' knockdown ( PAN-Jacob: 5′ TGC TAC TAG TTA CAG TGT AGA 3′/bp 390–410 of the Jacob cDNA ) ; all Jacob isoforms' scrambled control ( 5′ TGA TAG GTC TAT ACG AGT TCA 3′ ) , Caldendrin sRNAi ( 5′ TCC TGG CGG AGA CAG CAG ATA 3′/bp 665–685 of Caldendrin cDNA ) ; and Caldendrin scrambled ( 5′ AGA ATC CTA AGA CAA GTG CAG 3′ ) . Forward and reverse oligos were annealed , phosphorylated , and cloned BamHI , HindIII into the pRNAT-H1 . 1/Neo vector ( Genscript ) for plasmid-based RNAi knockdown . COS-7 cells were cotransfected with Flag-Jacob or Flag-Jacob-Myc/His and the RNAi expression vector . Cells were harvested 2 d after transfection and the samples solubilised for SDS-PAGE . For lentiviral transfections , double-stranded , phosphorylated oligos were cloned BamHI/BglII , HindIII into the pZ-off vector and further subcloned EcoRI , AccI/BstBI into the FUGW H1 ( + ) vector . HEK-293T cells were grown on polyD lysine-coated 10-cm3 plates to 90% confluence and cotransfected with the shRNA-FUGW H1 ( + ) ( 10 μg ) , the VSVg ( 5 μg ) , and Δ8 . 9 ( 7 . 5 μg ) vectors using Lipofectamine 2000 according to the manufacturer to produce competent virus particles . For virus production , cells were grown in Neurobasal medium supplemented with GlutaMAX and B27 at 32 °C and 5% CO2 overnight; the medium was changed and virus harvested 48–60 h after transfection . Sterile-filtered virus was directly added to primary cortical neurons at DIV0 . After 3 wk , cells were either fixed with PFA for immunostaining or harvested and prepared for SDS-PAGE . For the preparation of Semliki Forest particles and infection of primary cortical neurons , pSFV-Helper2 , pSFV-ΔMyr-Jacob-EGFP , or pSFV-EGFP after in vitro transcription were cotransfected into CHO-K1 cells with Lipofectamine2000 ( Invitrogen ) according to the supplier's manual . After 24 and 48 h , the culture medium containing the budded particles was harvested . Viral particles were concentrated by ultracentrifugation through 10% sucrose , the pellet was resolved in Tris-buffered solution overnight at 4 °C . Aliquots of the particles were stored at −80 °C after shock freezing . For infection of primary cortical neurons , the particles were activated by chymotrypsin and further diluted with OptiMEM . High-density cortical cultures were infected at DIV16 and harvested 24 h later . Neurons were homogenized in 20 mM Tris buffer containing protease and phosphatase inhibitors , and solubilised in SDS buffer . The protein concentration was determined by amido black test , and equal amounts were loaded for SDS-PAGE . Statistical analysis was performed with ANOVA and subsequent Bonferroni's Multiple Comparison test . Data are presented as mean ± standard error of the mean ( SEM ) . A level of p < 0 . 05 was considered statistically significant . Details about the computer models can be found under Supplementary Materials and Methods in Text S1 .
The Protein Data Bank ( http://www . pdb . org/pdb/home/home . do ) accession number for the structural model discussed in this paper is 1wdc . | Long-lasting changes in communication between nerve cells require the regulation of gene expression . The influx of calcium ions into the cell , particularly through membrane protein called NMDA receptors , plays a crucial role in this process by determining the type of gene expression induced . NMDA receptors can exert multiple and very divergent effects within neuronal cells by impacting opposing phenomena such as synaptic plasticity and neuronal degeneration . We identified a protein termed Jacob that appears to play a pivotal role in such processes by entering the nucleus in response to NMDA receptor activation and controlling gene expression that governs cell survival and the stability of synaptic cell contacts . Removal of Jacob from the nucleus protects neurons from NMDA receptor–induced cell death and increases phosphorylation of the transcription factor CREB , whereas the opposite occurs after targeting Jacob exclusively to the nucleus . The work defines a novel pathway of synapse-to-nucleus communication involved in modelling synapto-dendritic input and NMDA receptor–induced cellular degeneration . | [
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"neuroscience",
"cell",
"biology"
] | 2008 | Caldendrin–Jacob: A Protein Liaison That Couples NMDA Receptor Signalling to the Nucleus |
In phylogenetically diverse animals , including the basally diverging cnidarians , “determinants” localised within the egg are responsible for directing development of the embryonic body plan . Many such determinants are known to regulate the Wnt signalling pathway , leading to regionalised stabilisation of the transcriptional coregulator β-catenin; however , the only strong molecular candidate for a Wnt-activating determinant identified to date is the ligand Wnt11 in Xenopus . We have identified embryonic “oral–aboral” axis determinants in the cnidarian Clytia hemisphaerica in the form of RNAs encoding two Frizzled family Wnt receptors , localised at opposite poles of the egg . Morpholino-mediated inhibition of translation showed that CheFz1 , localised at the animal pole , activates the canonical Wnt pathway , promotes oral fates including gastrulation , and may also mediate global polarity in the ectoderm . CheFz3 , whose RNA is localised at the egg vegetal cortex , was found to oppose CheFz1 function and to define an aboral territory . Active downregulation mechanisms maintained the reciprocal localisation domains of the two RNAs during early development . Importantly , ectopic expression of either CheFz1 or CheFz3 was able to redirect axis development . These findings identify Frizzled RNAs as axis determinants in Clytia , and have implications for the evolution of embryonic patterning mechanisms , notably that diverse Wnt pathway regulators have been adopted to initiate asymmetric Wnt pathway activation .
The body plan of multicellular animals , generally defined in terms of axes of polarity , planes of symmetry , and germ layer organisation , emerges during early embryogenesis through a series of symmetry-breaking processes acting within and between cells [1] . The initial spatial cues that trigger these processes are frequently provided by maternal “determinants” localised at different sites within the egg . RNAs encoding Bicoid ( transcription factor ) and Nanos ( RNA binding protein ) localised at opposite poles of Drosophila eggs provide classic examples of determinants [2] . In many other species , unidentified determinants are deduced to act as regulators of the canonical Wnt signalling pathway . Activation of this pathway , generally by the binding of Wnt ligands to Frizzled transmembrane receptors , blocks constitutive degradation of the transcriptional coregulator β-catenin by a mechanism involving the cytoplasmic protein Dishevelled and inhibition of the kinase GSK3β [3 , 4] . Localised determinants cause β-catenin stabilisation in a restricted domain around the vegetal pole in early ascidian and sea urchin embryos , promoting endoderm/mesoderm fates , and in domains offset from the vegetal pole in amphibians and fish , promoting the establishment of a dorsal organiser centre [5–8] . A recent study revealed early regionalised stabilisation of β-catenin also in embryos of a cnidarian , the sea anemone Nematostella , indicating that it is an evolutionarily ancient component of early embryonic patterning [9] . The Cnidaria , which include sea anemones , corals , and jellyfish , provide an informative evolutionary perspective for the understanding of core developmental mechanisms because they form a sister group to the more complex three-layered and bilaterally symmetrical animals ( protostomes and deuterostomes ) , and possess a very similar repertoire of regulatory genes [10–13] . Our laboratory model Clytia ( =Phialidium ) hemisphaerica exhibits the typical simplicity of cnidarian organisation in its hydra-like polyp form: two germ layers , called ectoderm and endoderm ( or entoderm ) , and a single opening marking the “oral” end . The defining axis of oral–aboral polarity is first distinguishable at the onset of gastrulation , which proceeds by ingression of presumptive endoderm cells at the future oral pole of a hollow blastula [14] . Gastrulation produces simple polarised “planula” larvae from which polyps later form by metamorphosis . Experimental manipulations in another hydrozoan-group cnidarian , Podocoryne carnea , have shown that determinants responsible for the development of oral fates , including endoderm , and of global polarity properties such as directed swimming , are localised around the animal pole of the egg [15] . The animal pole of the Clytia egg correspondingly gives rise to the oral pole of the planula , although the strong regulative properties of the Clytia embryo make it harder to demonstrate the existence of maternal determinants [16 , 17] . Like the vegetally localised determinants in sea urchins , ascidians , amphibians , and fish , animally localised determinants in cnidarians are predicted to include canonical Wnt pathway activators [11 , 18] , since β-catenin is stabilised in the future oral half of Clytia ( this study ) and Nematostella [9] embryos from as early as the 32-cell stage . Furthermore , Wnt pathway activation appears to promote formation of endoderm in Nematostella embryos and of the “posterior” ( future oral ) pole in Hydractinia [9 , 19] , while in Hydra polyps it is associated with the oral/hypostome organiser region [18 , 20 , 21] . Molecular identification of the maternally localised determinants responsible for regional β-catenin stabilisation in early embryos remains an important goal for developmental biologists . Only in the amphibian Xenopus has a clear candidate been identified , the ligand Wnt11 [22] . The aim of this study was to identify localised maternal determinants responsible for regionalised β-catenin stabilisation in the oral half of the Clytia embryo . We focused on receptor or downstream Wnt pathway components rather than ligands , since in situ hybridisation analysis of Nematostella Wnt gene expression suggests that they play little or no maternal role; ( ubiquitous ) maternal RNA was originally detected for only one of the Wnt gene repertoire ( NvWnt11 ) [23] , and even this has now been put in doubt [18] . We were able to characterise both an animally localised Wnt pathway activating determinant , the receptor CheFz1 , and a related vegetally localised determinant with opposing function , CheFz3 .
Two distinct C . hemisphaerica Frizzled sequences were identified by screening an embryo cDNA library and from searching an expressed sequence tag collection [24] . Both of the Clytia cDNAs identified encode classical Frizzled family receptors containing seven transmembrane segments , a cysteine-rich domain implicated in ligand binding , and a KTXXXW motif essential for the activation of the Wnt–β-catenin pathway [25 , 26] ( Figure 1A ) . Comparison of their sequences with known Frizzled family genes grouped them with Drosophila fz ( vertebrate frizzled 1/2/3/6/7 ) and Drosophila fz3 and fz4 ( vertebrate frizzled 4 , 9 , and10 ) , and they were named CheFz1 and CheFz3 in line with the Drosophila genes ( Figure 1B ) . The Nematostella vectensis genome trace archive also contains Frizzled family sequences in both these groups , as well as in the Drosophila fz2 ( vertebrate 5/8 ) group [18] , indicating that the main frizzled gene subfamilies were founded before the bilaterian-cnidarian divergence . Whole mount in situ hybridization of unfertilised eggs revealed that both CheFz1 and CheFz3 RNAs are present as maternal transcripts and , remarkably , that they are distributed with complementary polarised localisations ( Figure 2 ) . Maternal CheFz1 RNA was found concentrated within the cytoplasm of the half of the egg containing the nucleus ( i . e . , the future oral half of the embryo ) . The predominantly oral localisation of CheFz1 RNA was maintained until the start of gastrulation . At the two- and four-cell stages it remained concentrated in cytoplasmic clouds close to the animally positioned nuclei , and at the eight- and 16-cell stages it became localised to roughly half the blastomeres . In blastulae and early gastrulae , CheFz1 RNA was detected as a gradient , the highest levels coinciding with the gastrulation initiation site . The level of RNA subsequently declined , the low signal detected in late gastrulae and young planula being stronger in the endodermal region . During planula development , CheFz1 RNA levels increased again in the oral endoderm , consistent with the expression of many Wnt genes in Nematostella at equivalent stages [23] . In , medusae and polyps , the low detectable levels of RNA were also concentrated in the endoderm , in line with the distributions of frizzled-1 subfamily RNAs described in Hydractina and Hydra [27 , 28] . The distribution of CheFz3 RNA was entirely opposite to that of CheFz1 RNA during early development . In eggs , it was localised to a domain on the future aboral side of the embryo ( i . e . , opposite the egg nucleus ) , and confined to a thin cortical layer rather than to the cytoplasm . The aboral cortical domain of CheFz3 RNA was inherited by daughter blastomeres during cleavage divisions . CheFz3 RNA was later found to be strongly localised in the aboral half of blastulae and early gastrulae , opposite the gastrulation initiation site . In contrast to CheFz1 RNA , CheFz3RNA remained strongly detectable during gastrulation and larval development , becoming progressively more tightly restricted to the aboral pole of the planula . CheFz3 was selectively expressed in two endodermal regions in medusae: the circular canal , and a band of the manubrium offset from the oral opening , as well as in an equivalent juxta-oral band of the manubrium in polyps . The oral localisation of maternal CheFz1 RNA placed it as a strong candidate for an oral/endoderm determinant acting upstream of β-catenin stabilisation . Functional tests using a morpholino antisense oligonucleotide targeted to the translation initiation site ( CheFz1-Mo ) supported this hypothesis ( Figure 3 ) . To assess Wnt pathway activation we injected eggs before fertilisation with RNA encoding a Podocoryne β-catenin–Venus fusion protein ( see Materials and Methods ) . In controls , β-catenin–Venus was detected in a restricted territory covering approximately half of the embryo from the 16- to 32-cell stage onwards , with a sharp boundary developing by the mid-blastula stage ( Figure 3A ) , as reported in Nematostella with Xenopus and Nematostella β-catenin–GFP fusion proteins [9] . Following CheFz1-Mo injection , β-catenin–Venus was barely detectable at the mid-blastula stage , indicating that active degradation of the protein , normally restricted to the aboral territory , had been promoted in all cells . As in the Nematostella study , we confirmed that the distribution of exogenous fluorescent protein faithfully reflected that of endogenous β-catenin by immunofluoresence of control cleavage-stage embryos with an anti–β-catenin antibody ( unpublished data ) . CheFz1-Mo–injected embryos showed severe reduction in the size of the oral territory of ingressing cells at the onset of gastrulation ( Figure 3B and 3C ) , and consequently a large deficit in the amount of endoderm present at the end of gastrulation period ( Figure 3D ) . Correspondingly , they showed strong down-regulation of the Brachyury gene CheBra , normally expressed prior to gastrulation in a small oral domain corresponding to the site of cell ingression [29] ( E . H . and S . Chevalier , unpublished data; Figure 3E ) . CheFz1-Mo not only inhibited oral CheBra expression and gastrulation , but affected aboral patterning , as demonstrated by expansion of the aboral expression domain of CheFoxQ2a [24] ( Figure 3F ) . A control morpholino containing five nucleotide substitutions ( CheFz1-5mp-Mo ) had no effect on development ( Figure 3D and unpublished data ) . To confirm that CheFz1-Mo specifically blocked translation of the corresponding RNA target sequence , it was co-injected with a reporter RNA in which the CheFz1 5′ UTR target sequence was placed upstream of the β-galactosidase–coding sequence . CheFz1-Mo , but not CheFz1-5mp-Mo , completely abolished β-galactosidase expression ( Figure 4 ) . These results indicate that the receptor CheFz1 acts as a classic positive regulator of the canonical Wnt pathway . Its localisation to the oral side of the early Clytia embryo is thus likely to be a key factor in the asymmetric activation of this pathway , and thereby in defining an oral gene expression territory from which endoderm derives [9 , 15] . In addition to the defects in gastrulation , CheFz1-Mo–injected embryos showed strikingly impaired swimming behaviour , turning slowly on themselves rather than developing directional movement during the early gastrula period . This undirected swimming phenotype led us to suspect that the CheFz1-Mo had interfered with the development of ectodermal polarity . Visualisation of cilia using an antiacetylated tubulin antibody supported this hypothesis; Cilia in CheFz1-Mo–injected embryos were short , curled-up , and lacked the oral–aboral alignment seen in control embryos ( unpublished data ) . This phenotype is reminiscent of that described in vertebrate embryos following interference with a noncanonical Frizzled-mediated response known as planar cell polarity ( PCP ) [30] . Also consistent with interference in PCP , CheFz1-Mo–injected Clytia embryos failed to elongate , a process driven by intercalation of polarised epithelial cells [14] . In vertebrates , interference with PCP likewise disrupts the “convergent extension” movements responsible for embryo elongation during gastrulation [31 , 32] . These indications suggest that the receptor CheFz1 may be required for the development of PCP as well as for canonical Wnt signalling in Clytia . It should be noted that CheFz1-Mo did not completely prevent either gastrulation or polarity development . Although the blastocoel remained mainly empty , some cell ingression was observed , and embryos adopted a pear shape rather than an elongated shape by the end of the normal gastrulation period ( Figure 3D ) . This could be accounted for by incomplete inhibition of translation , by the presence of maternal CheFz1 protein , or to the involvement of independent pathways . In line with its aboral localisation , CheFz3 function was found to oppose that of CheFz1 , repressing canonical Wnt signalling and promoting aboral gene expression ( Figure 3 ) . Thus , embryos injected with the specific morpholino CheFz3-Mo showed β-catenin–Venus stabilisation across the entire embryo ( Figure 3A ) . Correspondingly , cell ingression at gastrulation in CheFz3-Mo–injected embryos was initiated over a much increased area ( 70%–80% of the blastula surface compared with 20%–30% in uninjected siblings; Figure 3B–3D ) , the CheBra expression domain expanded ( Figure 3E ) , and expression of FoxQ2a [24] was abolished ( Figure 3F ) . We conclude that CheFz3 plays an important role in defining an aboral domain during early development . The observation of global β-catenin stabilisation in CheFz3-Mo–injected embryos does not prove that CheFz3 functions directly to downregulate canonical Wnt signalling , because this effect could be due to β-catenin independent downregulation of CheFz1 RNA levels ( see below ) . It should be noted , however , that the aboral localisation of CheFz3 in control embryos at the blastula and gastrula stages is much tighter than the graded oral localisation of CheFz1 ( Figure 2 ) , and matches more closely the sharply demarcated pattern of β-catenin stabilisation ( Figure 3A ) , supporting the hypothesis of direct antagonism at the level of the Wnt pathway . Canonical Wnt pathway activation in many systems invokes a complex system of feedback regulation involving modulation of expression of multiple regulatory components to shape the β-catenin stabilisation domain [3] . In addition to Wnt pathway antagonism , the action of CheFz3 in the aboral domain of the early embryo was found to include strong negative regulation of CheFz1 . A dramatic increase in the CheFz1 RNA level and a massive expansion of its territory was observed following CheFz3-Mo injection ( Figure 5 ) . Reciprocally , CheFz1-Mo promoted greatly increased CheFz3 RNA levels across the embryo , indicating mutual repression between the two genes at the level of new transcription or possibly RNA degradation . Despite the increased levels CheFz1 or CheFz3 RNA levels in these experiments , polarised distributions were still discernable . In particular , levels of CheFz3 RNA around the oral pole were always relatively low ( Figure 5 ) . A simple explanation for the mutual down-regulation between CheFz1 and CheFz3 would be that the level of both RNAs is regulated directly by canonical Wnt pathway activation , CheFz1 positively and CheFz3 negatively . Additional experiments showed that this is unlikely to be the sole explanation . Firstly , co-injection of the two morpholinos together resulted in simultaneous up regulation of both RNAs ( Figure 5 ) , a situation incompatible with opposing regulation by a single pathway . Secondly , treatment with LiCl ( an inhibitor of the negative regulator GSK3β ) to mimic canonical pathway activation [9] resulted in uncoupling of CheFz RNA levels from oral–aboral patterning . Like CheFz3-Mo injection , LiCl treatment caused strong oralisation of the embryo , as indicated by expansion of the gastrulation site ( Figure 6A ) and of the oral CheBra expression domain , and abolition of CheFoxQ2a expression ( compare Figure 6B with Figure 3E and 3F ) . The effects of lithium on the levels of CheFz1 and CheFz3 RNAs were , however , much weaker than the dramatic effects of CheFzMo injection ( compare Figure 6B with Figure 5 ) . LiCl treatment was also unable to reverse the expansion of the CheFz3 RNA domain provoked by CheFz1-Mo ( unpublished data ) . Taken together , these experiments indicate that β-catenin–independent mechanisms , for instance involving secondary secreted inhibitors , participate in the reciprocal downregulation between CheFz3 and CheFz1 . The morpholino loss-of-function experiments described above showed that CheFz1 and CheFz3 proteins are required for oral–aboral patterning in Clytia . To test whether these localised molecules were able to act as determinants to direct formation of the embryonic axis , we relocalised them by injecting synthetic RNA into one blastomere of two-cell stage embryos preinjected with morpholino . The effect of each synthetic RNA was first tested by injection into eggs before fertilisation . Injection of CheFz1RNA into eggs before fertilisation reproducibly caused an oralisation strongly reminiscent of the CheFz3-Mo phenotype , while CheFz3 RNA injection at moderate doses caused a gastrulation block as seen with CheFz1-Mo ( Figure 7A ) . At high doses , CheFz3 RNA had an oralising effect resembling that of CheFz1RNA ( not shown ) , suggesting that CheFz3 has a weak ability to activate the canonical Wnt pathway . A weak Wnt signalling ability has similarly been reported for the related protein Drosophila Fz3 , which attenuates canonical Wnt pathway activation by Fz2 during wing development [33 , 34] . In accordance with a role as an oral fate determinant , CheFz1 RNA injected into one blastomere at the two-cell stage promoted a significant rescue of the CheFz1-Mo–induced gastrulation block . The restored endoderm was composed of descendents of both injected and uninjected blastomeres ( Figure 7B ) , again indicating the involvement of secondary signalling mechanisms . Importantly , mislocalised CheFz1 caused formation of an ectopic pointed oral pole ( arrowed in Figure 7B ) , centred among the progeny of the Fz1RNA-injected blastomere and distinct from the residual endogenous oral pole ( asterisk in Figure 7B ) . Thus , localised CheFz1 is able to direct embryonic axis formation in Clytia . Remarkably , we found that CheFz3 RNA could also redirect polarity development when introduced ectopically into CheFz3-Mo–injected embryos . In this case , ectopic oral poles became positioned opposite a domain of suppressed gastrulation corresponding to the progeny of the RNA-injected blastomere ( Figure 7B ) . Ectopic oral poles were obtained in nine of 12 embryos in the CheFz1 rescue experiments and nine of 21 embryos in CheFz3 rescue experiments , the more variable results with CheFz3 reflecting greater sensitivity of injected blastomeres to RNA dose ( see above ) . Taken together , these RNA misexpression experiments indicate that an asymmetric distribution of either CheFrz1or CheFrz3 can direct polarisation of the Clytia embryo during pregastrula development .
The Frizzled receptors CheFz1 and CheFz3 both fulfilled all the experimental requirements to qualify as maternal localised determinants . First , their RNAs were found to be localised in the egg ( to the future oral and aboral poles ) , and to be inherited by oral- and aboral-fated territories , respectively . Second , loss-of-function experiments by morpholino-mediated translational inhibition showed that CheFz1 is required for oral specific gene expression and CheFz3 for aboral gene expression , and that the two proteins together define a domain of canonical Wnt signalling in the oral half of the embryo . The specificity of the morpholino experiments was confirmed by overexpression experiments , in which injection of CheFz3 RNA injection mimicked CheFz1-Mo and vice versa . Finally , mislocalised RNA of either CheFz1 or CheFz3 was able to restore and redirect axis development in morpholino-injected embryos . Are CheFz1 and CheFz3 the sole localised determinants upstream of canonical Wnt signaling in the Clytia embryo ? They are certainly dominant ones , since overexpression and misexpression experiments demonstrate that all other components necessary to support activation of this pathway are available throughout the embryo . Nevertheless , many Wnt pathway activators and inhibitors upstream or downstream of Frizzled could potentially adopt graded distributions at the RNA and/or protein levels and so contribute to axial patterning in undisturbed embryos , accounting for the residual polarity detected in CheFz1-Mo– , CheFz3-Mo– , and CheFz3 RNA–injected embryos . In Nematostella , none of the Wnt genes repertoired in the genome show detectable maternal RNA [18 , 23] , although low maternal expression of one or more of them cannot be ruled out . The Hydra Wnt gene HyWnt likewise appears not to be expressed maternally [35] . Interestingly , however , a recent study in Hydractinia revealed that RNAs coding for the equivalent Wnt ligand , as well as for the downstream transcriptional activator Tcf , are present maternally and concentrated at the animal pole of the egg [19] . As with CheFz1 RNA , the asymmetric distribution of these two RNAs becomes accentuated as zygotic transcription occurs to produce a strong localisation at the future oral pole of the embryo , suggesting that as in Clytia , active feedback mechanisms are operating to reinforce polarity . Cnidarian eggs may also contain other determinants acting in parallel to the Wnt pathway . In Podocoryne , maternal RNAs coding for Brachyury [29] and for the homeobox transcription factor Cnox4-Pc [36] are localised around the animal pole of the egg , and could potentially participate in directing gastrulation and/or other aspects of oral fate [37] . It will be instructive to test the maternal function of these molecules , and of the variety of Wnt pathway regulators present in cnidarians [18] . The presence of an animally localised canonical Wnt pathway activator in Clytia was predicted from previous work ( see Introduction ) ; however , the involvement of a variant Frizzled protein acting to oppose Wnt pathway activation was unexpected . Our data suggest that the opposing function of CheFz3 involves both direct antagonism of CheFz1-mediated Wnt signalling and indirect mechanisms involving secondary molecules . Direct antagonism of canonical Wnt pathway signalling by Frizzled family proteins has some precedent in other systems: Drosophila Fz3 will attenuate the response of Fz2 to Wnt ligand during wing development [33] , while Caenorhabditis MOM5 appears to antagonise canonical Wnt signalling in the absence of ligand [38] . The antagonistic action of Fz3 and MOM5 is thought to be due to an alteration in the C terminal K-T-xxx-W motif implicated in Dishevelled binding [26] . CheFz3 is phylogenetically related to Dfz3 ( Figure 1B ) and appears similarly to have a weak ability to stimulate canonical Wnt signalling , but does not show an alteration in this motif . It will be interesting to determine the molecular basic of its antagonistic behaviour . Many possible sequence changes could potentially abrogate receptor function and render Frizzled molecules antagonistic , as for instance in the extracellular cysteine-rich domain of mouse Frizzled-1 [39] . It is also possible that noncanonical Wnt signalling through CheFz3 may antagonise canonical CheFz1 signalling , as has been reported for certain Wnt ligands [40 , 41] . Our data include several indications that indirect mechanisms contribute to the negative effect of CheFz3 on canonical Wnt signalling . Most striking was the dramatic effect of morpholino-mediated inhibition of either CheFz1 or CheFz3 RNA translation on RNA levels of the other , which extended well beyond the corresponding RNA domains and was at least partially LiCl insensitive . These observations could be explained by the involvement of downstream-secreted molecules that diffuse away from their sites of production in both oral and aboral territories and act as inhibitors of the opposing fates . Such mechanisms are characteristic of the dynamic regulation systems used frequently during embryonic development to maintain signalling activity gradients , for instance in the vertebrate organiser [42] , and are predicted to provide the basis for the regulative properties typical of cnidarians [43] . Possible candidates as diffusible CheFz1 antagonists produced downstream of CheFz3 are the Dickkopf family proteins , shown to be expressed aborally in the Nematostella embryo and implicated in Wnt antagonism in Hydra polyps [18 , 44 , 45] . “Global” polarity is manifest in hydrozoan embryos and planula larvae by the common orientation of cilia within the ectoderm , responsible for their directed swimming . This global polarity confers certain remarkable properties , as revealed by bisection , grafting , and cell reassociation experiments , in which small pieces of blastula tissue can entrain the polarity of embryos reformed from disaggregated cells [17 , 37] . PCP , a noncanonical Frizzled-mediated process which acts to coordinate polarity of individual cells along a gradient of Frizzled activity [46] , is highly likely to participate in global polarity in hydrozoans . It is becoming increasingly apparent that PCP plays an important role in the coordination of morphogenetic movements during animal development , notably in vertebrate convergent extension [31 , 32 , 47] . In Clytia , CheFz1-Mo injection caused disruption both of cilia alignment and of embryo elongation by convergent extension-like cell intercalation , phenotypes consistent with disruption of PCP . Although such effects could be indirect , and dependent on events downstream of canonical Wnt signalling , it is tempting to speculate that CheFz1 directly mediates both canonical Wnt signalling and PCP , these two pathways acting in parallel to direct regionalised gene expression and global polarity , respectively . This possibility is supported by experiments in Podocoryne , where development of global polarity can be uncoupled experimentally from specification of the endoderm territory at the oral pole [15] . It will be important to analyse the role for PCP in the development of global polarity in hydrozaon embryos by independent means , such as by monitoring the polarised intercellular localisation of Frizzled , Disheveled , Prickle , and Strabismus proteins [18 , 32] . On the basis of its use in cnidarians , regionalised canonical Wnt signalling has been proposed to have had an ancestral role in early embryo patterning in metazoans [9 , 11] . Its primary role appears to be in axial patterning , with Wnt pathway activation and expression of numerous regulators coinciding with the developing oral–aboral axis in diverse cnidarian species [18 , 19] . Ancestral axial patterning may also have involved members of a second group of signalling molecules heavily implicated in bilaterian embryos , the transforming frowth factor β ( TGFβ ) superfamily . A number of TGFβ ligands , antagonists , and downstream regulators have been found to show asymmetric expression patterns in embryos of both anthozoan and hydrozoan cnidarians [48–52] . Intriguingly , expression of many TGFβ pathway regulators is offset from the oral–aboral axis and may reveal a cryptic second embryonic axis , although roles in germ-layer and primary axis formations have also been suggested [49 , 50] . Functional studies are required to understand the significance of these expression patterns . An important unresolved question concerns the relationship between axial patterning and germ layer specification . In Clytia , Podocoryne , and Nematostella , species which gastrulate by invagination and/or unipolar cell ingression from the oral pole [14 , 15 , 53] , definition of the presumptive endoderm territory and of the oral pole are clearly closely linked , and both promoted by Wnt pathway activation . This is not the case in all cnidarians [37] . In Hydractinia , for example , endoderm forms in a nonpolarised fashion from internal cells of solid morula , and GSK3β inhibitor studies indicate that endoderm formation is uncoupled from Wnt pathway–specified axial patterning [19] . We suspect that in Clytia , endodermal fate is determined secondarily within the β-catenin/oral fate territory by a dynamic mechanism involving other signalling pathways , perhaps by TGFβ signalling as hypothesised in Nematostella [50] . Such an indirect role for the Wnt pathway in germ-layer specification would explain why experimental β-catenin stabilisation does not convert all cells to an endodermal fate [9 , 37; this study] . Vestiges of roles for the Wnt signalling pathway in axis specification ( echinoderms , amphibians , and fish ) and germ-layer specification ( echinoderms , ascidians ) can be detected in deuterostomes , but appear to have been largely superceded by other axis and germ-layer specification mechanisms in protostome models . The search for maternal determinants responsible for initiating regionalised canonical Wnt signalling in different animals is far from complete , but existing data suggest that evolutionary conservation does not extend to determinant identity . Apart from the Clytia Frizzled RNAs identified in this study , Xenopus Wnt11 RNA is the only clear example of such a localised determinant . Wnt11 RNA is localised to the vegetal cortex of the Xenopus oocyte , and both RNA and protein become concentrated on the dorsal side of the early embryo [54 , 55] . Maternal Wnt11 is necessary for formation of the dorsal organiser region and promotes dorsalisation [22] . It may , however , not be the sole localised activator of the Wnt pathway in Xenopus: localisation of Dishevelled , GSK3β binding protein ( GBP ) , and even β-catenin itself may also contribute [56–58] . Likewise , Wnt and Tcf RNAs may be involved along with Frizzled RNAs in cnidarians [19; see above] . In zebrafish , maternal determinants that activate Wnt pathway signalling appear to act at the level , or upstream , of Frizzled [59 , 60] , while in sea urchins , the Dishevelled protein adopts a localization appropriate for determinant activity , although other unidentified localised factors contribute to its activation [61] . On current evidence it thus appears that during metazoan evolution , a variety of Wnt pathway regulators have been adopted as maternal determinants . This situation may have been favoured by the existence of efficient systems involving positive and negative feedback mechanisms that provide rapid reinforcement of initially weak gradients of Wnt signalling activity , as demonstrated here in Clytia . Such mechanisms are likely to underlie the remarkable self-organising properties of cnidarians , and have been shown to allow Wnt activity “organising centres” to emerge from nearly uniform cell populations [43] . We can speculate that embryonic polarity specification in the bilaterian/cnidarian ancestor may have relied on consolidation by intercellular signalling systems of weak ( possibly stochastic ) asymmetries in the distribution of one or other Wnt pathway component in the egg or early embryo . As egg size , cleavage patterns , and other features of early development subsequently diversified , the availability of multiple potential cellular mechanisms for the localisation of Wnt pathway-activating proteins or their RNAs within the egg appears to have allowed a wide choice of determinant identity .
CheFz1 was isolated from a Triplex phage cDNA library following PCR using degenerate primers corresponding to conserved regions of metazoan Frizzled genes . The CheFz3 sequence was retrieved from an expressed sequence tag collection [24] . Phylogenetic relationships were determined by maximum likelihood analysis of aligned conserved Frizzled domains using PhyML software ( http://atgc . lirmm . fr/phyml ) . Antisense morpholino oligonucleotides ( GeneTools LLC , http://www . gene-tools . com ) were designed to match the sequence of our clonal Clytia colonies ( CheFz1-Mo: CCGTTCTTGTAAAAACAATTATGTC; CheFz3-Mo: ACGTTAGGCAGCATCACTGCTCCTT ) and microinjected at 0 . 5 mM prior to fertilisation . A mismatch morpholino CheFz1-5mp-Mo ( CCGTTGTTCTAATAAGAATTATCTG ) was used to confirm specificity . To confirm the effects of morpholinos on translation , mRNA encoding β-galactosidase downstream of CheFz1 5′ UTR ( positions −63 to −1 of the start ATG ) was synthesised and injected into eggs with or without morpholino oligonucleotides before fertilisation . Resultant embryos were fixed and stained with X-gal substrate [62] . Gametes were obtained from C . hemisphaerica adult medusae generated from established laboratory colonies as described previously [24] . Embryos were raised in Millipore filtered seawater at 16–18 °C . Microinjection was performed with an Eppendorf “Femtojet” ( injection volumes estimated at 3% of egg or blastomere volume; http://www . eppendorf . com ) . RNAs for microinjection were transcribed from the CheFz1 and CheFz3 cDNA open reading frames using T3 mMessage machine ( Ambion , http://www . ambion . com ) following subcloning into the pRN3 plasmid [63] . In situ hybridisation using DIG-labelled antisense RNA probes was performed as described previously from cDNAs corresponding to CheFoxQ2a [24]; CheBra ( cloned from early embryo cDNA: S . Chevalier and E . H . , unpublished data ) , CheFz1 , and CheFz3 . To visualise cell boundaries and nuclei , embryos were fixed using 4% formaldehyde and stained with 130 nM fluorescent phalloidin and 0 . 4 μM ToPro3 ( both from Molecular Probes , http://probes . invitrogen . com ) , respectively . To monitor activation of the canonical Wnt pathway , eggs were injected prior to fertilisation with 0 . 5 mg/ml RNA coding for full-length Podocoryne carne β-catenin fused to the Venus GFP variant [64] . This was transcribed from a construction in pRN3 , with the Venus sequence placed at the C-terminal end of β-catenin , following a three-codon linker . Embryos were imaged live or after fixation in methanol at −20 °C . Confocal microscopy was performed using a Leica SP2 microscope ( http://www . leica . com ) .
The GenBank ( http://www . ncbi . nim . nih . gov/Genbank ) accession numbers for the structures discussed in this paper are CheFz1 ( DQ869571 ) , CheFz3 ( DQ869572 ) , CheBra ( DQ872898 ) , and β-catenin ( P . carne ) ( DQ869570 ) . N . vectensis frizzled gene sequences were recovered by BLAST from the Joint Genome Institute N . vectensis genome project trace files . | How do different animal body parts form in the correct arrangement during development ? Often , the explanation is provided by “determinant” molecules , prepositioned in the egg cell before it is fertilised . These determinant molecules initiate spatially localized programmes of gene expression , causing the various body parts to form in the appropriate place . Many determinants work by activating the Wnt signalling pathway; however , few concrete examples of determinant molecules have yet been discovered . We have found a new example of such a molecule by studying embryos of a jellyfish called Clytia . This molecule , found on one side of the egg , belongs to the “Frizzled” group of membrane proteins that activate Wnt signalling . Unexpectedly , we also found a second type of Frizzled molecule on the other side of the egg , which has a counterbalancing role in the embryo . Comparison of our findings in Clytia with those in other animals suggests that the molecular mechanisms responsible for body patterning via asymmetric Wnt pathway activation have not been tightly constrained during evolution . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
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] | 2007 | Two Oppositely Localised Frizzled RNAs as Axis Determinants in a Cnidarian Embryo |
Polyclonal Epstein-Barr virus ( EBV ) -infected B cell line ( lymphoblastoid cell lines; LCL ) -stimulated T-cell preparations have been successfully used to treat EBV-positive post-transplant lymphoproliferative disorders ( PTLD ) in transplant recipients , but function and specificity of the CD4+ component are still poorly defined . Here , we assessed the tumor-protective potential of different CD4+ T-cell specificities in a PTLD-SCID mouse model . Injection of different virus-specific CD4+ T-cell clones showed that single specificities were capable of prolonging mouse survival and that the degree of tumor protection directly correlated with recognition of target cells in vitro . Surprisingly , some CD4+ T-cell clones promoted tumor development , suggesting that besides antigen recognition , still elusive functional differences exist among virus-specific T cells . Of several EBV-specific CD4+ T-cell clones tested , those directed against virion antigens proved most tumor-protective . However , enriching these specificities in LCL-stimulated preparations conferred no additional survival benefit . Instead , CD4+ T cells specific for unknown , probably self-antigens were identified as principal antitumoral effectors in LCL-stimulated T-cell lines . These results indicate that virion and still unidentified cellular antigens are crucial targets of the CD4+ T-cell response in this preclinical PTLD-model and that enriching the corresponding T-cell specificities in therapeutic preparations may enhance their clinical efficacy . Moreover , the expression in several EBV-negative B-cell lymphoma cell lines implies that these putative autoantigen ( s ) might also qualify as targets for T-cell-based immunotherapy of virus-negative B cell malignancies .
About 20% of all human cancers are caused by pathogens and of these 80% by viruses [1] . The viral proteins expressed in these tumors represent neo-antigens and potential targets for immunotherapeutic approaches [2] . The oncogenic Epstein-Barr virus ( EBV ) , a member of the gamma-herpes virus family , has been implicated in the pathogenesis of several human malignancies of lymphoid and epithelial origin [3] . Acquired orally , EBV persists lifelong in the human host by establishing latency in B cells but is normally contained as an asymptomatic infection by T-cell surveillance . Consequently , patients with T-cell immunodeficiency are at heightened risk of developing EBV-associated malignancies [3] . In immunosuppressed hematopoietic stem cell transplant ( HSCT ) recipients , such EBV-positive post-transplant lymphoproliferative disorders have been successfully treated by the infusion of polyclonal EBV-specific T-cell preparations that are generated by repeated stimulation of peripheral blood T cells with autologous EBV-infected B cells ( LCL ) in vitro and contain CD8+ and CD4+ T-cell components [4]–[6] . Despite its proven safety and remarkable efficacy , adoptive T-cell therapy still has a limited role in the management of virus-associated complications in transplant recipients , mainly because of the logistical and financial implications that are associated with extensive in vitro T-cell culture , as well as the time required to generate virus-specific T-cell lines when the clinical need is urgent . To expedite the preparation procedure , various protocols have been designed that aim at isolating effector populations directly from stem cell donors , including ex vivo selection of defined EBV antigen-specific T cells with pentamers [7] , or cytokine secretion and capture technology [8] , [9] . Moreover , the recently established repository of cryopreserved virus-specific T-cell lines from healthy seropositive donors provides partially HLA-matched , off-the-shelf products for adoptive transfer [10] . Given the difficulty of generating virus-specific T-cell lines from EBV-naive donors in vitro , recipients of stem cells from cord blood might particularly benefit from such allogeneic effectors [3] , [5] , [6] . Of note , the success of immunotherapy seen in HSCT recipients has not been matched in solid organ transplant ( SOT ) patients , most likely because the continuous immunosuppressive environment limits proliferation and persistence of adoptively transferred cells . Response rates in SOT recipients with refractory PTLD that were treated with autologous or allogeneic LCL-stimulated T-cell preparations were reported to range around 50% [5] , [6] . Importantly , better clinical responses were observed when the infused T cells expressed a broad T-cell receptor repertoire [11] , suggestive of a broadly targeted T-cell response , and when they contained higher proportions of CD4+ T cells [10] , [11] . For unknown reasons , the CD4/CD8 T-cell ratio in LCL-stimulated T-cell lines can vary greatly [12] , [13] . These findings imply that the clinical efficacy of T-cell preparations may be increased by tailoring its cellular composition and , in extension , antigen specificity . However , in contrast to the well-characterized EBV-specific cytotoxic CD8+ T-cell response [3] , [14] , relatively little is known about function and specificity of virus-specific CD4+ T cells . Ex vivo analyses of latent antigen-specific CD4+ T-cell memory has led to the identification of multiple epitopes , and virus carriers usually exhibit memory responses to several epitopes that are derived from more than one antigen [15]–[17] . For the few lytic cycle antigens examined to date , again multiple reactivities were detected per donor [18]–[20] , indicating that the EBV-specific CD4+ T-cell response is broadly distributed across different latent and lytic cycle antigens . A similar pattern of antigen specificity was detected in LCL-stimulated T-cell preparations . Besides viral antigen-specific T cells , these lines also contain CD4+ T cells specific for cellular antigens , whose expression is probably up-regulated by EBV infection [20] , [21] . The remarkable breadth of the virus-specific CD4+ T-cell response and the fact that classical PTLD , like LCL , express all latent antigens of EBV and contain lytically infected cells expressing ∼80 lytic cycle proteins [3] , [22] , raises the question , whether the different CD4+ T-cell specificities are equally tumor-protective or whether some have non-redundant functions in tumor control and , therefore , should be enriched in T-cell preparations for adoptive therapy . Here , we used the well-established PTLD-SCID mouse model [23] , [24] , that permits to assess efficacy of T-cell preparations in a preclinical setting [25] , to comparatively evaluate the tumor-protective potential of different CD4+ T-cell specificities in vivo .
To assess the tumor-protective potential of different T-cell populations in the PTLD-SCID mouse model [24] , [26]–[28] , mice were i . p . injected with 1×107 LCL or 5×107 PBMC from EBV-positive donors and tumor incidence , latency and localization analyzed . After injection of LCL , PTLD-like tumors developed with 100% incidence in three out of four cases ( Figure 1A ) with a latency of 20 to 46 days . Tumors usually developed with slightly delayed kinetics when LCL Z ( - ) of the same donor were injected ( Figure 1B ) . Tumor latency was also extended when reduced numbers of LCL were injected ( Figure 1C ) . Injection of PBMC from EBV-seropositive donors also led to tumor development but with much slower kinetics ( Figure 1B ) . Tumors either formed below the liver and were then often connected with the porta hepatis , or were located at the injection site . Human origin and PTLD-like histology of the tumors was verified by measuring huIgG in mouse serum ( data not shown ) and by immunohistochemical analysis of tumor sections [29] . Although PBMC-induced tumors were more heterogeneous in their cellular composition , all tumors expressed human CD20 and the EBV-proteins EBNA1 and EBNA2 ( Figure 1D ) . To compare the tumor-protective efficacy of CD4+ versus CD8+ T cells in vivo , T-cell lines were generated from several donors by four rounds of in vitro stimulation with autologous LCL and then separated into CD4+ and CD8+ subsets by MACS . Mice that had received 1×107 LCL were i . p . injected on the same day with an equal number of the separated ( n = 4–7 ) , or , as control , the unseparated T cells ( n = 6 ) on the opposite flank . Although T-cell preparations from different donors proved differently effective , mouse survival was consistently prolonged to the same extent by the CD4+ and CD8+ components ( Figure 2A ) , indicating that both T-cell subsets possess similar tumor-protective capacity . Because the single components were not as efficacious as the parental T-cell line , and because T-cell preparations with higher CD4+ numbers had shown better clinical responses [10] , CD4+ and CD8+ T-cell subsets were recombined at different ratios ranging from 0–100% CD4+ T cells , and tested in the same way . None of the combinations , including reconstituted CD4/CD8 ratios of the parental T-cell lines ( group size n = 4 ) , showed enhanced tumor protection ( Figure 2B ) . These results suggested that the T-cell subsets have additive but not synergistic effects on mouse survival and that the comparatively lower tumor-protective effect of the subset combinations might have been due to an impaired fitness or vitality of the T cells following the separation procedure . Given the remarkable breadth of the EBV-specific CD4+ T-cell response , we sought to investigate whether and to which extent single CD4+ T-cell clones were able to delay tumor growth , and whether tumor protection in vivo correlated with target cell recognition and inhibition of proliferation in vitro [19] . To this aim , different latent and lytic cycle antigen-specific CD4+ T-cell clones , that recognize and growth-inhibit unmanipulated LCL to various degrees in vitro [19] , [30] , were injected together with autologous LCL or PBMC and tumor latency analyzed . As shown for the EBNA1- and EBNA3B-specific T-cell clones 1C3 and B9 [30] , T cells that failed to recognize unmanipulated LCL in vitro had no effect on mouse survival ( Figure 3A ) . A possible correlation of in vitro and in vivo effector functions was also suggested by a slight , but statistically not yet significant prolongation of mouse survival by the EBNA3C-specific T-cell clone 3H10 , which moderately recognized LCL in vitro . Consistent with these findings , tumor development was significantly delayed when the BLLF1-specific T-cell clone 1D6 was transferred , which recognized and growth-inhibited LCL very efficiently in vitro [19] ( Figure 3A ) . BLLF1-1D6-treated mice showed a median survival benefit of 9 . 5 days , which is similar to mice that had received tenfold less LCL ( 1×106 ) without T cells ( Figure 1C ) . Moreover , similar results were obtained with this clone in the PBMC-SCID mouse model , but these experiments have not yet reached statistical significance due to the limited availability of large numbers of PBMC from individual donors ( data not shown ) . These results indicated that single CD4+ T-cell specificities can significantly prolong mouse survival and that tumor-protection might correlate with target cell recognition and growth-inhibition in vitro . This notion was further supported by experiments in which 1×107 CFSE-labeled BLLF1-specific or , as a control , EBNA1-specific cells were i . p . injected into animals that had received 1×107 autologous LCL 25 days before and started forming tumors . Both groups of mice were sacrificed 24 , 48 , or 72 hours after T-cell injection and the tumors analyzed by FACS ( Figure 3B ) and immunohistochemistry ( Figure 3C ) for T-cell infiltration . BLLF1- but not EBNA1-specific T cells accumulated in tumors over time . Concomitantly , a reduction in the proportion of human CD20+ cells was observed ( Figure 3B ) . Some BLLF1-specific T cells were even detected in direct contact with BLLF1-positive cells ( Figure 3C ) , lending further support to a potential correlation of T-cell effector functions in vitro and in vivo . However , infusion of the EBNA1-specific clone 3E10 , that failed to recognize unmanipulated LCL in vitro [30] , and the BNRF1-specific T-cell clone 1H7 ( group size n = 10 and n = 4 ) , that efficiently recognized and growth-inhibited LCL in vitro [20] , accelerated tumor development ( Figure 3D ) . When compared to the tumor-protective clone BLLF1-1D6 , these T cells responded to their cognate antigen with similar affinity , secreted similar amounts and patterns of cytokines , and displayed similar cytolytic activity ( Figure S1 in Text S1 ) . These findings suggested that besides target cell recognition and lytic activity , still unknown functional differences among virus-specific CD4+ T cells may impact on antitumoral efficacy . This tumor-promoting effect of some CD4+ T cells notwithstanding , the above described experiments suggested that tumor-protection in vivo correlates with T-cell recognition of target cells in vitro . Since virion antigen-specific CD4+ T cells efficiently recognize LCL in vitro , these results implicated CD4+ T cells specific for structural antigens of the virus as particularly tumor-protective . As demonstrated previously , the frequency of such T-cell specificities is usually low in early passage T-cell lines , but increases with further rounds of stimulation in vitro [20] . Accordingly , later passage LCL-stimulated T-cell lines might exhibit a higher tumor-protective potential . As expected , T cells from the same donor stimulated four or ten times in vitro both recognized autologous LCL in vitro , but responses against virus-pulsed LCL were more pronounced after ten rounds of stimulation . These results indicated that the proportion of T cells with virion antigen specificity had increased ( Figure 4A and Figure S2 in Text S1 ) . When tested in vivo , both T-cell lines prolonged median survival of LCL-injected animals to a similar extent; 50 days in the case of p4 ( n = 13 ) and 46 days in the case of p10 ( n = 13 ) . Thus , despite an increased response against virus-pulsed target cells , later passage T-cell lines were not more efficacious in vivo ( Figure 4B ) . In fact , the tumor-protective potential of these LCL-stimulated T-cell lines seemed to decline with the number of passages , either because extended in vitro culture impaired their antitumoral activity in vivo , as demonstrated for CD8+ T cells [31] , and/or relevant specificities were lost . To investigate the antigen-specificity of protective T-cell lines in more detail , we generated T-cell lines by repeated stimulation with three different stimulator cells , ( i ) LCL cultured in media containing FCS ( LCL-FCS ) , ( ii ) LCL cultured in media containing FCS and acyclovir ( LCL-FCS-ACV ) , and ( iii ) LCL cultured in media containing human serum ( LCL-HS ) instead of FCS . ACV inhibits EBV late lytic gene expression and is used for safety reasons in clinical T-cell stimulation protocols to prevent virus production [32] . As verified in T-cell recognition assays , T-cell lines stimulated with LCL-FCS-ACV were devoid of virion antigen-specific T cells ( Figure S3 in Text S1 ) . LCL-HS were used as stimulators to investigate whether recognition of FCS-derived antigens presented on injected LCL by FCS-specific T cells contributed to tumor protection [13] . Irrespective of the stimulator cells used , all three T-cell lines recognized autologous LCL in vitro , but failed to respond to autologous PBMC pulsed with recombinant EBV latent proteins ( Figure 5A ) . Efficient processing and presentation of peptides derived from these recombinant proteins was confirmed using latent antigen-specific CD4+ T-cell clones ( Figure S4A in Text S1 ) . LCL-FCS and LCL-HS-stimulated T cells potentially recognized EBV lytic cycle antigens and/or autoantigens , whereas LCL-FCS-ACV-stimulated T cells might have been directed against cellular antigens and possibly immediate early and early lytic cycle antigens . Surprisingly , in vivo all three T-cell lines significantly prolonged median mouse survival to approximately 50 days ( group sizes n = 9-12 ) ( Figure 5B ) . Thus , LCL-stimulated T-cell preparations that lacked virion antigen-specific T cells were not compromised in their antitumoral efficacy , indicating that tumor-protection was mediated by T cells specific for non-virion antigens . To further substantiate this notion , 8 mice were co-injected with tumor-inducing cells that are unable to express lytic cycle antigens ( LCL Z ( - ) ) and T cells stimulated with LCL-HS as effectors . Although lytic cycle antigen-specific T cells , including virion antigen-specific T cells , were a priori ineffective in this experimental setting , mouse survival was significantly prolonged with three out of eight animals never developing any tumors ( Figure 5C ) . No human IgG was detected in the serum of these mice ( data not shown ) . Mice in this experiments survived on average for 86 days , compared to 32 days without T cells ( n = 7 ) ( Figure 5C ) . Although this remarkable protective efficacy might have been partly due to the slightly less aggressive nature of LCL Z ( - ) as compared to LCL-induced tumors ( Figure 1B and [33]-[35] ) , these results clearly demonstrated a considerable therapeutic potential of LCL-stimulated T-cell lines independent of EBV latent or lytic cycle antigen recognition . To more directly evaluate the antitumoral efficacy of non-viral antigen-specific T cells in vivo , T-cell lines were generated by stimulation with LCL Z ( - ) or miniLCL , thereby precluding the expansion of T cells that recognize EBV lytic cycle antigens . Following more than 30 rounds of stimulation , these T cells usually expressed one or few Vβ chains , suggesting that these lines were directed against one or few antigens ( data not shown ) . The miniLCL-stimulated T-cell line JM-W3 recognized autologous LCL and LCL Z ( - ) , as well as the HLA-matched EBV-negative Burkitt's lymphoma cell line BL30 . Recognition was not due to alloreactivity , because these T cells failed to recognize the EBV-positive convertants ( BL30-B95 . 8 and BL30-P3HR1 ) . Thus , this T-cell line recognized a differentially expressed cellular antigen ( s ) , but not viral antigens ( Figure 6A and Figure S4C-D in Text S1 ) . In the case of the miniLCL-stimulated T-cell line GB-W3 , reactivity against EBV latent antigens was excluded by assessing recognition of the HLA-matched , EBV-negative Hodgkin's lymphoma cell line L428 that had been pulsed with single recombinant EBV latent antigens ( Figure 6A and Figure S4B in Text S1 ) . Co-injection of 1×107 JM-W3 or GB-W3 T cells together with 1×107 autologous LCL Z ( - ) or miniLCL into SCID mice prolonged median mouse survival from 30 to 36 days in the case of JM-W3 T cells ( group sizes LCL Z ( - ) n = 6; LCL Z ( - ) + T cells n = 4 ) , and from 24 to 29 days in the case of GB-W3 ( group sizes miniLCL n = 4; miniLCL + T cells n = 10 ) , demonstrating that autoantigen-specific T cells were tumor-protective in this preclinical PTLD model ( Figure 6B and Table S1 in Text S1 ) . Similar to virus-specific effectors , these putative autoreactive T cells displayed a differentiated effector/effector-memory Th1 phenotype [36] , [37] ( CD62L− , CCR7− , CD27− , CD28+ , CXCR3+ ) ( Figure 6C ) , that was confirmed by the expression of the cytotoxins granzyme A and B in these T cells ( Figure 6D ) .
The identification of low endogenous CD4+ T-cell numbers as important risk factor for the development of EBV-associated diseases in immunosuppressed patients [38] , and of better clinical responses in patients with PTLD receiving EBV-specific T-cell lines that contained higher proportions of CD4+ T cells [10] , have implied an important role for CD4+ T cells in the control of EBV-driven lymphoproliferation . Thus , elucidating the role of CD4+ T cells in tumor defense may facilitate to generate T-cell preparations with enhanced clinical efficacy and to reduce the logistic complexity of this form of immunotherapy that still precludes its application outside specialized academic centers [3] . The EBV-specific CD4+ T-cell response , albeit one to two orders lower in magnitude , appears to target a much broader set of viral antigens than the corresponding CD8+ T-cell response [6] , [14] , [20] . To investigate whether these numerous CD4+ T-cell specificities are functional redundant or fulfill complementary roles in tumor defense , we assessed their tumor-protective potential in a preclinical PTLD model . In contrast to earlier [39] , but in accordance with recently published data [40] , CD4+ T cells in our LCL-stimulated preparations delayed tumor growth as effectively as the CD8+ components . Contrary to the above mentioned clinical experience , however , antitumoral efficacy was not affected by the CD4/CD8 ratio of the injected T-cell preparations . This functional redundancy implied that both components recognized PTLD-like tumors with similar efficiency . In patients , CD4+ T cells probably also exert indirect “helper” functions that remained undetected in this xenogenic model , where human T cells fail to persist long-term and complex immune networks are unlikely to form . To assess functional differences among virus-specific CD4+ T cells we injected T-cell clones with defined specificities together with autologous LCL or PBMC from EBV-seropositive donors into SCID mice . Unexpectedly , the T-cell clones had divergent effects on mouse survival , ranging from tumor-protective in the case of BLLF1-specific T cells , to ineffective in the case of most latent antigen-specific T cells , to tumor growth-promoting in the case of EBNA1-3E10 and BNRF1-1H7 . The correlation of tumor-protective but not tumor-promoting propensity of T cells in vivo with target cell recognition and inhibition of proliferation in vitro suggested that still unknown phenotypic differences may exist between these populations . Neither the pattern nor the amount of secreted cytokines , including paracrine growth factors like IL-6 that are known to shorten tumor latency in SCID mice [34] , [35] , [41] , differed consistently among tumor-promoting and tumor-protective T cells ( Figure S1 in Text S1 , and data not shown ) . How certain CD4+ T cells promote tumor growth is still unknown , but given the potential clinical implications , warrants further investigation . This dichotomous function of CD4+ T cells may also provide an explanation for the contrasting effects of LCL-stimulated CD4+ T-cell lines on tumor growth in different studies [39] , [40] , and for the baffling observation that tumor development in SCID mice injected with primary B cells from EBV-positive donors depends on the presence of T cells [33] . Unexpectedly , EBNA1-specific CD4+ T cells had no or a tumor growth-promoting effect in vivo . This was surprising because EBNA1 peptide-selected T-cell preparations were successfully used in the clinic to treat PTLD [42] . The reasons for these discrepant results are currently not known . The clinically used T-cell preparations , however , contained CD4+ and CD8+ T-cell components and only about 60% of the adoptively transferred T cells were EBNA1-specific . Therefore , it cannot be excluded that tumor regression was mediated by EBNA1-specific CD8+ T cells and/or T cells with undefined specificities . An important role of CD8+ T cells in the control of PTLD has been implicated by clinical studies using peptide or MHC class I pentamer-selected T-cell preparations [7] , [8] . The infused T cells were predominantly CD8+ and were directed against different viral antigens . Collectively , these studies point towards a redundant function of different latent or lytic antigen-specific T cells in the control of PTLD in stem cell transplant recipients . However , in solid organ transplant recipients , response rates are generally lower ( around 50% ) and positively correlate with the CD4+ T-cell content of the infused T-cell preparations [10] , suggesting that in these patients , CD4+ and CD8+ T cells do not have completely redundant antitumoral functions . Whether virus-specific CD4+ T cells , including those directed against EBNA1 as well as other viral antigens , that had no effect on tumor growth in the SCID mouse model , are of therapeutic importance in this cohort , e . g . by providing help to endogenous immune cells , remains to be determined . The efficient recognition of LCL by virion antigen-specific T cells [19] and the correlation of target cell recognition and prolongation of mouse survival implied that increasing virion antigen-specific CD4+ T cells in T-cell preparations might increase their tumor-protective potential . This notion was supported by immunohistochemical analyses of tumor sections which revealed that approximately 1–3% of the tumor cells expressed BZLF1 ( data not shown ) . A similar percentage of BZLF1-positive cells was detected in the corresponding LCL cultures , suggesting that spontaneous induction of the lytic cycle and expression of lytic cycle antigens was not altered in vivo . However , LCL-stimulated T-cell lines were not more tumor-protective at later than at earlier passage . This was either because ( i ) functionality of the T cells in vivo declined with longer in vitro culture [31] , or ( ii ) tumor-protective T-cell specificities were lost and only partially compensated for by the increase in virion antigen-specific T cells , and/or ( iii ) tumor-promoting T cells were enriched . To further analyze antigen-specificity and antitumoral efficacy of early passage T-cell preparations , we compared the tumor-protective potential of T-cell lines stimulated with LCL that had been cultured under different conditions , including those used in clinical protocols [43] . These experiments revealed that potentially autoantigen-specific , but not FCS-reactive or virus-specific T cells , were the principal effectors against PTLD in early passage LCL-stimulated CD4+ T-cell lines . These T cells prolonged mouse survival as effectively as a virion antigen-specific T-cell clone , implicating these two specificities as critical CD4+ effectors against PTLD in this preclinical model . However , one has to keep in mind that only a limited number of T-cell clones directed against a subset of all viral antigens was included in this analysis . Thus , additional T-cell specificities with protective efficacy may exist . That autoantigen-specific CD4+ T cells are a major component of early passage LCL-stimulated T-cell preparations , has already been demonstrated in earlier studies [20] . Furthermore , when the expansion of lytic cycle antigen-specific T cells was prevented by using LCL Z ( - ) cells as stimulators , the resulting CD4+ T-cell lines targeted cellular but not viral antigens [21] . Although the antigens recognized by these T cells have yet to be defined molecularly , their expression appears to be restricted to transformed B-cell lines and was not detected in primary hematopoietic cells ( Figure S4 in Text S1 ) . In accordance with this , Long et al recently isolated CD4+ T-cell clones from LCL-stimulated lines that recognize cellular antigens expressed in EBV-transformed , but not in mitogen-activated B lymphoblasts [21] . These findings may provide an explanation for the proven clinical safety of LCL-stimulated T-cell preparations [5] , [6] , [44] . In addition , these findings raise the intriguing possibility that EBV-positive lymphomas that fail to express immunodominant antigens of EBV , e . g . Hodgkin's and Burkitt's lymphoma , and even EBV-negative B cell malignancies , might respond to LCL-stimulated T-cell preparations . Circumstantial evidence for a protective role of autoreactive CD4+ T cells has already been obtained in preclinical lymphoma models and lymphoma patients: CD4+ T cells that recognize non-viral antigens can prevent B cell lymphomas in mice transgenic for the EBV latent membrane protein LMP1 [45] , and five of six patients with Hodgkin's-like and Burkitt's-like post-transplant lymphoproliferative disease responded to treatment with allogeneic T-cell preparations , although in some cases the tumor cells did not express the viral antigens recognized by the infused T cells [11] . Moreover , complete remissions were achieved in several patients with LMP2A-positive Hodgkin's lymphoma by the adoptive transfer of autologous LCL-stimulated T-cell lines . Since the infused T cells contained only low amounts of LMP2A-specific CD8+ T cells and their frequencies failed to correlate with clinical responses [5] , [46] , additional and still unknown specificities might have contributed to tumor rejection . Taken together , these results implicate virion and non-viral antigens as important targets of the CD4+ T-cell response against PTLD , and LCL-stimulated T-cell lines , although increasingly replaced by antigen-specific preparations [8] , [9] , [47] , as more potent than previously recognized . Defining the antigens recognized by these non-viral antigen-specific CD4+ T cells and incorporating such specificities in clinically used T-cell preparations may not only increase their antitumoral activity against PTLD , but possibly also against EBV-negative B cell malignancies .
All animal experiments were performed in strict accordance with German animal protection law ( TierSchG ) and approved by the responsible state office Regierung von Oberbayern ( ROB ) under protocol number 55 . 2-1-54-2531-131-07 . The mice were housed and handled in accordance with good animal practice and all efforts were made to minimize suffering as defined by Federation of European Laboratory Animal Science Associations ( FELASA ) and the national animal welfare body Gesellschaft für Versuchstierkunde - Society for Laboratory Animal Science ( GV-SOLAS ) . LCL were established by infection of primary B cells with wild-type ( wt ) -EBV produced by the B95 . 8 marmoset cell line . MiniLCL and LCL Z ( - ) were generated by infection of B cells with the genetically engineered virus mutants miniEBV [48] and ΔBZLF1-EBV [49] that are incapable of lytic replication , as previously described [19] . B cells were obtained from peripheral blood mononuclear cells ( PBMC ) of healthy adult volunteers after informed consent . LCL were cultured as described [20] . In some experiments , FCS was replaced by pooled human serum ( HS ) to avoid the expansion of FCS-reactive T cells . Where indicated , LCL treated with 200 µM acyclovir ( ACV ) ( Hexal ) for at least two weeks were used as T-cell targets . PBMC were repeatedly stimulated with autologous , irradiated ( 80 Gy ) LCL , miniLCL , or LCL Z ( - ) as antigen presenting cells ( APC ) as described [20] . Where indicated , T-cell lines were separated into CD4+ and CD8+ fractions by using αCD4+ and αCD8+ MicroBeads , LS-MACS columns and MidiMACS separator as recommended by the manufacturer ( Miltenyi Biotec ) . Purity of the cells was confirmed by FACS analysis using CD3 , CD4 , and CD8-specific antibodies ( Becton Dickinson ) . Generation and cultivation of CD4+ T-cell clones has been described previously [19] , [30] . Clonality of the T cells was assessed by PCR using Vβ chain-specific primers as described , and T-cell epitopes as well as the restricting HLA-molecules were identified using published methods [13] , [50] . To exclude that prolonged culture caused loss of specificity of the T cells and , consequently , that their anti-tumor effect in vivo would not reflect their initial anti-tumor activity in vitro , antigen-specificity of all clones was verified prior to injection ( data not shown and Fig S4 in Text S1 ) . The T-cell lines were generated by stimulation with autologous LCL or miniLCL . The T-cell lines were 100% CD3+ with varying proportions of CD4+ and CD8+ components . No NK or B cells were detected by FACS . Target cell recognition and lytic activity of all T cells was tested prior to injection ( data not shown ) . Cytokine secretion by the T cells was measured by ELISA ( R&D Systems ) . Plotted data represent the mean plus standard deviation ( SD ) of triplicates . Dendritic cells and PHA blasts were generated as described [51] . Cytolytic activity was measured after 3 h of co-culture of T cells with labeled target cells by quantitating calcein AM ( Invitrogen ) released into the culture supernatant . Virus concentrate was prepared by ultracentrifugation of B95 . 8 cell culture supernatant . Functionality was tested using BLLF1-specific T cells ( Figure S3 in Text S1 ) and viral copy numbers determined by qPCR as described [13] . To assess the antitumoral potential of T cells in vivo , 1×107 LCL ( LCL-SCID mouse model ) or 5×107 PBMC ( PBMC-SCID mouse model ) from EBV-positive donors were injected intraperitoneally ( i . p . ) into 6 to 14-weeks-old C . B . 17-SCID mice ( Taconic ) . 1×107 T cells in PBS , or PBS only , were i . p . injected separately on the same day before down-regulation of HLA class-II on injected LCL occurs [40] , [52] . All cells injected in mice were tested negative for mycoplasma using a commercial detection kit ( Lonza ) . For T-cell tracking experiments , LCL were injected on day 0 and T cells on day 25 . Experimental groups consisting of 4–6 mice were evaluated for tumor growth and survival . Mice were sacrificed when they had ruffled hair , showed food refusal , bulky abdomen or palpable tumors . To verify the presence of human B cells in these mice , human IgG ( huIgG ) -ELISA was performed . 96-well plates were coated with α-human IgG mAb ( 2 . 5 µg/ml; Abcam ) in PBS overnight and then incubated with mouse serum at different dilutions in RPMI-1640 for 1 h . Subsequently , the biotin-labeled detection antibody α-huIgG ( Dianova ) was added for 1 h followed by horseradish-peroxidase ( HRP ) -coupled streptavidin for 20 min . HuIgG was visualized by adding TMB-substrate . Where indicated , T cells were labeled with CFSE according to the guidelines of the manufacturer ( Invitrogen ) . For the FACS-analysis of tumor infiltration by CFSE-labeled T cells , single cell suspensions of tumors were prepared by mechanical disruption and lysis of erythrocytes . For FACS analysis , fluorochrome-conjugated monoclonal antibodies against human CD3 , CD4 , CD8 , CD25 , CD28 , CD57 , CD62L , CXCR3 , CCR4 , CCR6 , CCR7 , CTLA-4 , MHC II , PD-1 ( Becton Dickinson ) , CD20 , CD27 and MHC I ( ImmunoTools ) were used . TIM-3 antibody ( kindly provided by Dr . Kuchroo , Boston ) was visualized using a fluorochrome-conjugated secondary antibody ( Jackson ImmunoResearch laboratories ) . Granzyme A and B stainings were performed on α-CD3-activated T cells . Dead cells were excluded with 7-AAD ( Becton Dickinson ) , cells fixed with paraformaldehyde , permeabilized with saponine and stained for granzyme A and B . FoxP3 staining was performed following the manufactureŕs protocol using the Fix/Perm FoxP3 buffer set ( BioLegend ) . CD4+ cells were stained prior to fixation , CD25+ cells were stained simultaneously with FoxP3 . CD107a antibody ( BioLegend ) was added during T-cell stimulation and surface expression analyzed after 4 h . Flow cytometric analysis was performed in a FACSCalibur flow cytometer and data analyzed with the CellQuest software ( Becton Dickinson ) . Immunohistochemical analyses were performed on cryo-embedded or formalin-fixed , paraffin-embedded ( FFPE ) tumor samples . FFPE-sections of all tumors were stained with hematoxylin and eosin ( H&E ) , or with antibodies against human CD20 , EBNA1 , EBNA2 , BZLF1 , BLLF1 , and FITC ( from Argene , Dako , or kindly provided by Dr . E . Kremmer , Helmholtz Zentrum München ) . For H&E staining , FFPE sections were stained with mayeŕs hematoxylin solution and eosin Y ( both Roth ) . Single stain immunohistochemistry was performed on FFPE sections using the Vectastain ABC Detection System for horseradish peroxidase according to the manufactureŕs protocol ( Vector Laboratories ) . Cryo-embedded sections were used for double-stainings with antibodies against FITC , to detect CFSE-labeled T cells , and BLLF1 , to detect lytically infected tumor cells . In addition to the horseradish peroxidase detection system , the Vectastain ABC Detection System for alkaline phosphatase in combination with the alkaline phosphate substrate kit III ( both from Vectastain ) was used . Mouse survival was analyzed using Kaplan-Meier curves . Significances of the in vivo-experiments were calculated by using the log-rank or the Kruskal-Wallis test . p-values of 0 . 05 or less were considered significant . The statistical analyses were carried out with the GraphPad Prism 5 program . | The γ-herpesvirus Epstein-Barr virus ( EBV ) is associated with several human malignancies , including post-transplant lymphoproliferative disorders ( PTLD ) in immunocompromised patients . The successful treatment of EBV-positive PTLD by the infusion of EBV-specific T-cell lines has provided an important proof of principle for immunotherapy of EBV-associated tumors and for cancer immunotherapy in general . EBV-specific T-cell preparations for clinical application are generated by repeated stimulation with autologous LCL in vitro . These lines contain CD4+ and CD8+ components but the specificity of the infused CD4+ T cells is still poorly defined . Using a mouse model of PTLD , we assessed the antitumoral potential of single virus-specific CD4+ T-cell clones . While T cells specific for a virion antigen of the virus prolonged mouse survival , other virus-specific clones had no effect or , unexpectedly , even promoted tumor growth . Moreover , the principal antitumoral effectors in LCL-stimulated T-cell preparations were CD4+ T cells specific for non-virus antigens . The definition of virion- and potentially autoantigen-specific CD4+ T cells as key effectors against PTLD may contribute to the design of generic and standardized protocols for the generation of T-cell lines with improved clinical efficacy . In addition , the observed tumor-promoting propensity of some CD4+ T cells may have implications for adoptive T-cell therapy in general . | [
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] | 2014 | Virus and Autoantigen-Specific CD4+ T Cells Are Key Effectors in a SCID Mouse Model of EBV-Associated Post-Transplant Lymphoproliferative Disorders |
Several experiments indicate that there exists substantial synaptic-depression at the synapses between olfactory receptor neurons ( ORNs ) and neurons within the drosophila antenna lobe ( AL ) . This synaptic-depression may be partly caused by vesicle-depletion , and partly caused by presynaptic-inhibition due to the activity of inhibitory local neurons within the AL . While it has been proposed that this synaptic-depression contributes to the nonlinear relationship between ORN and projection neuron ( PN ) firing-rates , the precise functional role of synaptic-depression at the ORN synapses is not yet fully understood . In this paper we propose two hypotheses linking the information-coding properties of the fly AL with the network mechanisms responsible for ORNAL synaptic-depression . Our first hypothesis is related to variance coding of ORN firing-rate information — once stimulation to the ORNs is sufficiently high to saturate glomerular responses , further stimulation of the ORNs increases the regularity of PN spiking activity while maintaining PN firing-rates . The second hypothesis proposes a tradeoff between spike-time reliability and coding-capacity governed by the relative contribution of vesicle-depletion and presynaptic-inhibition to ORNAL synaptic-depression . Synaptic-depression caused primarily by vesicle-depletion will give rise to a very reliable system , whereas an equivalent amount of synaptic-depression caused primarily by presynaptic-inhibition will give rise to a less reliable system that is more sensitive to small shifts in odor stimulation . These two hypotheses are substantiated by several small analyzable toy models of the fly AL , as well as a more physiologically realistic large-scale computational model of the fly AL involving glomerular channels .
The early stages of the drosophila olfactory system include a primary sensory structure called the antenna lobe ( AL ) . The AL receives input from olfactory sensory neurons ( ORNs ) at the sensory periphery , and is organized into glomerular clusters , with each cluster corresponding to a specific olfactory receptor class [1]–[5] . Each glomerulus within the AL contains dendrites of local neurons ( LNs ) whose projections are limited to the AL , as well as projection neurons ( PNs ) whose axons extend beyond the AL deeper into the fly brain [6] . The PNs are excitatory , whereas there is evidence that both excitatory local neurons ( LNEs ) and inhibitory local neurons ( LNIs ) exist [7]–[9] . The LNs associated with each glomerulus have local projections , which connect to that glomerulus , as well as lateral projections which connect to other glomeruli [10] . Various experiments indicate that there exists substantial synaptic-depression at the synapses between olfactory receptor neurons ( ORNs ) and neurons within the drosophila antenna lobe ( AL ) ; by ‘synaptic-depression’ , we refer to any mechanism which gives rise to short-term depression of the ORN-induced EPSCs within the AL following an increase in ORN activity . While it has been proposed that this synaptic-depression contributes to the nonlinear relationship between ORN and PN firing-rates , the precise functional role of synaptic-depression at the ORN synapses is not yet fully understood . To investigate the relationship between synaptic-depression and the coding properties of the fly AL , we created and analyzed the dynamics of several models of the fly AL . We have been able to distill two hypotheses linking the information-coding properties of the fly AL with the network mechanisms responsible for ORNAL synaptic-depression . Our first hypothesis is related to the variance coding of ORN firing-rate information — once stimulation to the ORNs is sufficiently high to saturate PN responses within any particular glomerular channel , further stimulation of the ORNs can reduce the amount of fluctuation of the ORNPN input within that channel , thus increasing the regularity of PN spiking activity while maintaining PN firing-rates . Thus , given two different stimuli which saturate the responses of a given glomerulus , it may still be possible to distinguish between these two stimuli solely by using this saturated glomerulus' activity . In order to distinguish these saturated responses , a readout mechanism must be sensitive to higher-order statistics ( such as variance ) in the saturated glomerulus' activity . Our second hypothesis proposes a tradeoff between trial-to-trial reliability and sensitivity governed by the mechanisms responsible for ORNAL synaptic-depression . Within the fly , synaptic-depression may be partly caused by vesicle-depletion , and partly caused by presynaptic-inhibition due to the activity of inhibitory local neurons within the AL [11] , [12] . Our second hypothesis is that synaptic-depression caused primarily by vesicle-depletion will give rise to a very reliable system , whereas an equivalent amount of synaptic-depression caused primarily by presynaptic-inhibition will give rise to a less reliable system that is more sensitive to small shifts in odor stimulation . Using this second hypothesis , one can further postulate that a balance of vesicle-depletion and presynaptic-inhibition within the AL is required in order to optimize the discriminability of the network over short observation-times .
In brief , our computational network model incorporates glomerular channels , each with PNs , LNEs , LNIs and ORNs , in rough accordance with the experimentally observed ratio of ORNs to PNs and LNs [13] . As the real fly AL has glomerular compartments , each of roughly this size [10] , this model is the size of the full AL . Each neuron in this network model is modeled using Hodgkin-Huxley-type equations . The synaptic currents in this network allow neurons to affect other neurons in the same glomerulus , as well as neurons in other glomeruli . The input to this network takes the form of noisy stimulus current to the ORNs , with different ‘odors’ corresponding to different levels of stimulus current to different ORN input channels . Importantly , the model is built to accommodate synaptic-depression of the ORN synapses , allowing for both the mechanisms of presynaptic-inhibition as well as vesicle-depletion . An illustration of the network's connectivity , as well as an abridged list of network parameters , is given in Fig . 1 . We have built this network to respect physiological constraints , and we have tuned this model using several experiments as benchmarks . Here we provide a brief summary of these results . A more detailed description of the model as well as the details regarding the benchmarking are contained in the Methods section . Our goal while benchmarking this model was to ensure that our model produced reasonable statistical features of AL activity during the following odor onset . The reason we focused on matching the statistics of this transient period is that evidence indicates that this period is likely critical for many basic olfactory discrimination and classification tasks [14] , [15] . One of the simplifications we have made in our model is that the input to the ORNs following odor onset is assumed to be a Poisson process with a time-varying rate that is roughly stereotyped across ORN classes ( see Methods ) . While natural odor stimuli are likely temporally complex [16] and even static stimuli generate odor-specific temporal fluctuations at the level of the fly ORNs after several hundred ms [17] , the dynamics of the ORN responses during the first following odor onset seems to be relatively stereotypical , involving either a sharp increase in activity or , more rarely , an inhibitory phase [18] , [19] . Thus , the idealized input to the ORNs we employ in our model is intended to capture these simple features of ORN activity which drive the AL during the first following odor onset . The experimental phenomena we used to benchmark our model ultimately provided three constraints on the connectivity of our model network . First , the convergence ratio of ORNs to PNs must be high , otherwise the PNs do not receive sufficient convergent input to fire quickly after odor onset . Second , the synaptic-depression at the ORN synapses must be sufficient to ensure that PN firing-rates peak earlier than ORN firing-rates ( in response to odor stimulus ) , and that ORNPN input is strong and relatively stable during the first after odor stimulus onset . Finally , the inter-AL connectivity ( governed by the LNLN , PNPN , PNLN , and LNPN connection matrix ) must be sufficiently strong to create PNs which are more broadly responsive than their ORN inputs , yet sufficiently sparse to place the network in a dynamic regime which does not develop spontaneous oscillations ( which are not observed experimentally during the initial transient following odor onset – [17] ) . In addition , to further understand the network mechanisms underlying the two proposed hypotheses , we have designed simpler neuronal network models which distill the relevant phenomena , while allowing for a more comprehensive analysis . The analytical tools we use include the analysis of return-maps for simple network models , as well as the analysis of population-dynamics equations for more complicated network models ( see the sections to follow for more details ) . As evidenced in [20] , [21] , the relationship between ORN firing-rate ( ) and PN firing-rate ( ) for a given glomerulus is often nonlinear , with the PN firing-rate saturating rather quickly as a function of ORN firing-rate . One consequence of this nonlinearity is that , for low , the gain in is high — as varies from 0–50 Hz , can vary from 0–150 Hz or more . Another consequence of the nonlinear relationship is that , for high , the gain in is low — as varies from 100–200 Hz , may remain almost constant . Many have noted that the region of high gain allows for ‘odor separation’ — namely , odors which give rise to similar profiles for a given glomerulus may in turn produce very different profiles within that glomerulus [20] . However , this ‘odor separation’ only works when the odors in question generate which are sufficiently low as to lie in the region of high gain . It is tempting to conclude that if two odors generate which are sufficiently high ( such that the induced lie in the region of low gain ) , then the generated by these odors would be similar , and the odors would not be ‘separated’ . The first hypothesis we propose is that , even if two odors generate which correspond to similar , the dynamics of the glomerulus may still serve to separate these odors . However , in this case the odor separation takes place not in terms of PN firing-rates ( as , indeed , the generated by these two odors may be very similar or identical ) , but rather in terms of higher-order statistics of PN activity . In other words , even though the set of PN firing-rates produced at the plateau of the relationship are similar , we hypothesize that there is in fact a systematic difference in the PN dynamics underlying these similar PN firing-rates . To be more specific , we claim that for values of along the plateau of the relationship , as increases ( and stays roughly the same ) , the synaptic-depression at the ORN synapses continues to increase . One consequence of this increase in synaptic-depression is that , as increases along the plateau of , the number of ORN firing-events increases , but the effect of each ORN firing-event on postsynaptic PNs decreases . Thus , the postsynaptic conductance induced within any PN by the ORNs ( i . e . , the ORN input to the PN ) maintains roughly the same mean , but decreases in variance . When discussing a reduction in the variance of ORN input , we refer specifically to a reduction in the variance across short time-windows of the PN excitatory-conductance due to ORN activity . If the is not very high , then each ORN generates relatively few spikes , each resulting in a large EPSC in the postsynaptic PN . Thus , the ORN input to the PNs will have large fluctuations ( i . e . , the PNs will be ‘fluctuation-driven’ ) . On the other hand , if is very high , then each ORN generates very many spikes , each resulting in a small EPSC within the postsynaptic PN . In this case the PN conductance due to the ORNs will be nearly constant ( and the PNs will be ‘mean-driven’ ) . We further hypothesize that , as increases along the plateau of , the decrease in variance of ORN input to the PNs will correspond to a decrease in the variance of PN spiking activity . Because ( i ) the ORN activity is not deterministic , but rather driven by many independent stochastic molecular binding events [18] , and ( ii ) many ORNs are presynaptic to each PN , the accumulation of ORN firing-events observed by any given PN during any trial of odor presentation is well-approximated by a Poisson process with time-varying rate . Thus , a decrease in the ORN input variance across short time-windows will be associated with a decrease in the ORN input variance across multiple trials ( for the same time-window ) . Thus , one would expect the variance in PN spiking activity mentioned above to decrease both across short time-windows and across multiple trials ( for the same time-window ) . This reduction in variance of PN spiking activity is equivalent to an increase in the regularity of PN spiking activity , which is equivalent to a reduction in the variance of the inter-spike-interval distribution associated with a PN within the given glomerulus . Thus , in summary , our first hypothesis is that the dynamics of a glomerulus can serve to separate ORN inputs in two ways . Not only can similar ORN inputs within the high-gain region of be mapped to significantly different PN firing-rates ( see [20] ) , but ORN inputs within the low-gain region of can give rise to PN activity with differing degrees of regularity , even when the PN firing-rates associated with those ORN inputs are not significantly different . This hypothesis may have significance for odor discrimination , as the variance in PN activity may encode features of the odor even in situations where the ORN input is sufficiently high that PN firing-rates have saturated ( see Discussion ) . It has been hypothesized that one functional role for the AL is to separate similar odors and that the nonlinear gain curve is instrumental in this process . As shown in [11] , the nonlinearity of is influenced strongly by substantial synaptic-depression at the ORN synapses . Thus , it is reasonable to conclude that one functional role of synaptic-depression at the ORN synapses is to enhance the odor separation capabilities of the AL . Within the fly AL there are multiple sources of synaptic-depression at the ORN synapses . Two major mechanisms which contribute to this synaptic-depression are vesicle-depletion and presynaptic-inhibition . While either one of these mechanisms could , in principle , be the major contributing factor to the synaptic-depression observed within the fly AL , it seems as though both of these mechanisms play a substantial role in producing synaptic-depression [11] , [12] . Thus , one is faced with the following natural question: What purpose do these two distinct mechanisms serve within the fly AL ? How would the odor-coding properties of the fly AL change if , say , only one of these mechanisms were responsible for the observed levels of synaptic-depression at the ORN synapses ? Is there some functional advantage gained by having both of these mechanisms at play ? In what follows we introduce a hypothesis which links the underlying nature of synaptic-depression at the ORN synapses to information-coding properties of the AL , such as reliability , sensitivity and discriminability . First we will define these terms , and then we will explain our hypothesis in more detail throughout the rest of this section . sources of noise: There are two sources of ‘noise’ in our network which influence the reliability ( or unreliability ) of the AL's activity across trials . The first is the initial condition of the system ( i . e . , the state of the system at odor onset ) . Different initial conditions will give rise to different dynamic trajectories . The second source of noise is the odor-driven Poisson input to the ORNs in the model . Different trials will give rise to different sequences of ORN spikes . reliability: We define the reliability of the AL as the inverse of the coefficient-of-variation in spike-counts of AL neurons , as measured across trials over a given stimulus-driven time-window . Reliability is high if the spike-counts of the AL neurons are similar from trial-to-trial . Reliability is low if the spike-counts vary significantly from trial to trial . In our analysis we will consider a family of networks with the same mean firing-rate , hence the notion of reliability can be constructed using standard-deviation in spike-counts across trials , rather than coefficient-of-variation . sensitivity: Given two similar stimuli , we can measure the time-averaged firing-rates of the various neurons in the AL , collected over a long time ( e . g . , ) . If the firing-rates induced by these two similar stimuli are nearly identical , we say that the AL is ‘not sensitive’ to the difference between these two stimuli . On the other hand , if the firing-rates induced by these two stimuli are quite different , then we would describe the AL as ‘sensitive’ to the stimulus difference . More specifically , we define sensitivity to be the magnitude of the derivative of the vector of steady-state AL-firing-rates , when considered as a function of the odor input . In this sense , our notion of sensitivity is built around firing-rates , and does not explicitly consider higher order dynamical structure . discriminability: Given an unknown odor from amongst a set of possible known candidates , we can use the AL as a discriminator: by presenting this mystery odor to the AL and measuring PN firing-counts over a time-period , we can attempt to classify the input as one of the possible candidate odors . We define the discriminability of the AL as the accuracy ( i . e . , correct-classification rate ) of this procedure . The discriminability depends strongly on . If is sufficiently long , the discriminability of the AL is related directly to its sensitivity . If is short , then unreliability may come into play and reduce discriminability . As with our definition of sensitivity , our definition of discriminability is built around measurements of firing-rates , and does not take into account higher order dynamic structure . The main thrust of our second hypothesis is that the combination of the mechanisms of vesicle-depletion and presynaptic-inhibition allows the fly AL to balance sensitivity and reliability in such a manner as to maximize the discriminability of AL activity ( with respect to similar ORN inputs ) over short observation times .
The intuition gained in this study may be useful for understanding the coding properties of olfactory systems in other insects , or even in mammals , many of which also exhibit synaptic-depression . In the olfactory system of many other insects , such as the locust and honeybee , the antennal lobe activity is characterized by oscillations which develop soon after the onset of stimulus . These oscillations are thought to be a key feature of the AL-response in these animals [26] , [33] . Since such oscillations do not manifest quickly in the fly [17] , the dynamical regimes studied in this paper are not of this nature . However , we can retune our computational model to produce oscillations by increasing the density of lateral connectivity within the AL ( thus , bringing our model closer in structure to that of [33] ) . The analytical techniques used in this paper may also be useful for studying some of the phenomena associated with such an oscillatory regime . Within certain mammals , such as the mouse , primary olfactory input to the olfactory bulb can be presynaptically inhibited by interneurons [37]–[39] ) . Because the architecture of the mammalian olfactory system is different from that of the fly , the hypotheses investigated in this paper may not directly apply . For example , in the mouse it has been found that inhibitory neurons in the olfactory bulb strongly presynaptically-inhibit the olfactory sensory neurons stimulating their own glomerulus , but not those stimulating other glomeruli [40] , a situation markedly different from the presynaptic-inhibitory network of the fly AL [12] . Thus , as hinted in ( iii′ ) above , one might expect type-A networks to be both more sensitive and more reliable than type-B networks in the mouse . The extra coding power afforded by ‘feedback-induced’ synaptic-depression in this scenario may be necessary for an animal which is forced to sample it's olfactory environment using short observation times ( e . g . , nose-pokes and sniffs ) . This sort of speculation begs for a more detailed investigation of the structural and dynamic mechanisms at work in the mammalian olfactory system .
In this section we describe the point-neuron model we used to investigate the dynamics of the fly AL . This model incorporates glomerular channels , each with PNs , LNEs , LNIs and ORNs , and incorporates presynaptic-inhibition as well as vesicle-depletion ( see Fig . 1 ) . Each PN , LNE , LNI and ORN is modeled using single-compartment Hodgkin-Huxley type kinetics using standard sodium and potassium currents that give rise to fast sodium spikes [22] similar in shape to those observed experimentally [41] . We have tuned the model so that , with a single set of parameters , the model exhibits a dynamic regime that is consistent with a variety of experimentally observed phenomena . We attempted to ensure that the model network architecture is consistent with the literature . For example , motivated by [13] , We chose the inhibitory postsynaptic coupling strengths from LNIsPNs so that the lateral inhibitory IPSC to a PN has both a fast and slow component ( in our model IPSCs incorporate 50% fast ( gabaA type ) and 50% slow ( gabaB type ) inhibition ) . Similarly , we chose the inhibitory postsynaptic coupling strengths from LNIsLNEs and LNIsLNIs to be 100% fast-type . As another example , motivated by [41] , we have chosen LNEPN intra-glomerular coupling to be sparse enough ( 15%-25% ) to align with the fact that direct LNPN connections are rarely observed . Nevertheless , LNEPN inter-glomerular coupling is dense enough that lateral excitatory input is still observed between most pairs of glomeruli [8] , [9] . The lateral excitation between glomeruli is sufficiently strong that , even when ORNs belonging to a particular glomerulus are removed , some PNs and LNs within that glomerulus can still fire after odor presentation . The membrane potential of each ORN is governed by equations of the formwith stimulus current described in a section entitled “Odor Stimulation” below . The membrane potential for each PN , LNE and LNI is governed by equations of the form:The parameters for the passive leak current are , , . Here we describe in detail the idealized model used in the section entitled “A simple cartoon of variance coding” in the main text . This model includes a single conductance-based integrate-and-fire PN , driven by a set of ORNs , each endowed with a simple model of synaptic-depression . Each of the ORNs is modeled as a Poisson process with fixed rate ( ) . The coupling strength between the ORNs and the PN is modulated by a term ( ) , which is intended to model vesicle-depletion at the ORN synapses . As each ORN fires , this term will give rise to synaptic-depression between the ORNs and the PN . The membrane potential and conductance for this single PN obey the following differential equations:where , is the reset potential , is the excitatory reversal potential , and is the conductance time-constant . The voltage evolves continuously until reaches a threshold , at which point the PN fires , and is reset to . The conductance evolves continuously except when an ORN ( say , the ORN ) spikes , at which point jumps . The time is the spiketime of the ORN , and is the coupling strength associated with the ORN at time . If , the synapses between the ORN and the PN are exhausted . If , the synapses between the ORN and the PN are completely refreshed . For this simple model , and the equation for is given by:where is the time-constant associated with vesicle-depletion . The term decays to continuously , except when the ORN fires at some time , at which point jumps by an amount proportional to ( the limit is used since is not technically defined ) . The parameter governs the relative increase in associated with each spike , and hence is bounded between and . The parameters , and are chosen to be consistent with typical point-neuronal models , and the parameter is chosen essentially arbitrarily ( different choices for do not qualitatively change the results ) . As a simple cartoon which illustrates Hypothesis 1 , consider a single PN modeled by a conductance-based integrate-and-fire neuron [22] , driven by a single ORN modeled as a Poisson process ( with firing rate ) . The state variables of the PN are the membrane-potential , the excitatory conductance , and the vesicle-depletion parameter . The equations governing the state of the PN are ( 11 ) where is the leakage conductance , is the reset potential , is the excitatory reversal potential , and is the conductance time-constant . The voltage evolves continuously until reaches a threshold , at which point the PN fires , and is reset to . The conductance decays to continuously except when the ORN fires . The time is the spiketime of the ORN , and is produced by a Poisson process with rate . , The conductance jumps by at time ( the limit is used since is not technically defined ) . The vesicle-depletion parameter decays to continuously with time-constant , except when the ORN fires , at which point jumps by . In this simple model the vesicle-depletion parameter and conductance are both bounded to lie within . As the vesicle-depletion parameter increases , the effect of ORN spikes on the PN conductance decreases . It should be noted that the functional form for the ORNPN synapse — in this case modeled by — is chosen to make the subsequent analysis easier , and is not particularly realistic ( as very small values for imply a very strong ORNPN synapse ) . Nevertheless , the general picture implied by this cartoon holds for more realistic models of vesicle-depletion ( see the section entitled “A simple cartoon of variance coding” in the main text ) . The simple model Eq . 11 can be analyzed by considering the long-time evolution of the PN . For sufficiently small , , and sufficiently large ( with fixed ) , it can be shown [56] that the equilibrium-distribution of ( collected by sampling over a sufficiently long time interval ) is well-approximated by a Gaussian , with mean and standard-deviation given by:It can also be shown that , under these conditions , the equilibrium-distribution of is also well-approximated by a Gaussian , with mean and standard-deviation given by:Using the expression for , the expressions for and can be simplified toThus , for a sufficiently small , as the variance of equilibrium-distribution shrinks to , and the mean remains constant . Thus , as , the long-time conductance-distribution becomes sharply peaked around ; so much so that , for sufficiently large , the PN effectively has a fixed excitatory-conductance and will fire perfectly regularly with a period ofThe excitatory conductance is , in this case , independent of the activity of the PN because the ORN input is only affected by vesicle-depletion , and not by presynaptic-inhibition . Nevertheless , the conclusions we draw from this simple model are quite general , and will hold for more realistic models of synaptic-depression . Note also that synaptic-depression is critical to hypothesis-1 within this model . If were fixed to be ( i . e . , no synaptic-depression of the ORN synapses ) , and were sufficiently large , then the equilibrium-distribution of would be Gaussian with a mean and variance that grow unbounded as . In this section we analyze the model used in the section entitled “A simple analyzable cartoon of the tradeoff between reliability and sensitivity” . To analyze the solutions of Eq . 1 , let's assume for the moment that , and ( i . e . , neuron fires more frequently than neuron ) . If , then and do not affect one another . The steady-state firing-rate of neuron is , and the steady-state firing-rate of neuron is . Let us define and . Since both and are perfect phase-oscillators , and fire perfectly regularly every and time-units ( respectively ) . If there is a difference in ORN inputs to these two neurons ( say , ) , then the difference in firing-rates is . Thus , if , this system is perfectly reliable ( in the sense that the ISI distribution of and the ISI distribution of both have variance ) , and somewhat sensitive to shifts in the input ( in the sense that any difference in input is reflected in the difference of the output firing-rates ) . If , then and affect one another with several consequences: ( i ) the steady-state firing-rates and will be lower than and ( respectively ) , ( ii ) the ISI distributions of and will have nonzero variance , and ( iii ) the difference in steady-state firing-rates will be greater than . Indeed , as increases away from the system becomes less reliable while becoming more sensitive to shifts in the input . More specifically , for a given fixed , the system will settle down to a steady-state dynamics in which neuron fires either or times in between each pair of -firing-events . The steady-state sequence of spike-times is independent of the initial state of the network and , while not generally periodic , can be solved for explicitly . To show why this is true , we consider the return-maps and . We define the return-map as follows: given a spike of neuron ( say , ) , let be the first spike of neuron which occurs after , and let be the first spike of neuron which occurs after — we define . Similarly , given a spike of neuron , let be the first spike of neuron after , and let be the first spike of neuron after — we define . For the return map , we can also define the numbers and as follows: is the number of times fires in between and , and is the number of times fires in between and . Similarly , for the return map , we can define as the number of times fires in between and , and as the number of times fires in between and . See Fig . 14 for an example of these return maps . Recall that , without loss of generality , we have assumed . By considering the return maps and , one can easily show that the maximum and minimum of are and , respectively , and that the maximum and minimum of are and , respectively . Moreover , maps the interval into . Similarly , maps the interval into . It is straightforward to show that the image of under is composed of sub-intervals: ( i ) an interval of length for which , and ( ii ) an interval of length for which . Similarly , the image of under is composed of sub-intervals: ( i ) an interval of length for which , and ( ii ) an interval of length for which . Letting ( 12 ) one can show that the lengths and are given by ( 13 ) For both the sub-maps and the number of extra spikes . These observations allow us to conclude that the steady-state ISI distribution for neuron ( i . e . , ) has a peak of magnitude at , and a peak of magnitude at . Similarly , the steady-state ISI distribution for neuron ( i . e . , ) has a peak of magnitude at , and a peak of at . The steady-state firing-rates associated with these ISI-distributions can be expressed in closed form and directly computed: ( 14 ) Similarly , the means and variances associated with these steady-state ISI-distributions can be expressed in closed form ( see Fig . 5 ) . By considering these expressions for small , one can see that the steady-state return-map consists of segments of length and , corresponding to inter-spike-intervals for neuron of length and , respectively . Thus , has distinct peaks ( at and , respectively ) , and as increases the distance between these two peaks increases . As a consequence , as increases , the variance in increases . In effect , a larger implies that extra spikes from have a larger effect on the of . A similar argument applies to and , and one can also show that , as increase the difference in firing rates also increases ( see Fig . 5 ) . Thus , within this simple network , presynaptic-inhibition between the neurons disrupts their natural regularly-firing behavior , and increases the variance of their ISI distribution ( thus decreasing their reliability ) . In the discussion above , we assumed that . If we assume , we can express the system firing-rate in closed form as a function of , ( simply by replacing with and with in Eqs . 12 , 13 , 14 ) . By requiring the system firing-rate to be constant , we can define implicitly ( as a function of , , and the system firing-rate ) . Thus , we can directly compute the -parameter family of networks which , for fixed , , attain a fixed system firing-rate . As shown in Fig . 5 , this -parameter family of networks does indeed range from type-A networks ( with high and low ) to type-B networks ( with low and high ) . Moreover , as one moves along this -parameter family of networks by increasing ( and decreasing appropriately ) , the variance in and increases , and the sensitivity also increases . In conclusion , this simple network illustrates that presynaptic-inhibition is capable of increasing the variance of the ISI distributions of the neurons within that network ( hence reducing their reliability ) , while at the same time increasing the sensitivity of the neurons' firing-rates to subtle shifts in input . In this section we provide details regarding the analysis in the section entitled “A simple cartoon of optimizing discriminability over short observation-times” . Our goal is to determine from a measurement whether the input to the system is or . Let us denote by and the mean and variance of . As long as is sufficiently large , the estimate can be considered to be drawn from . Thus , as long as is sufficiently large , the measurement can be considered to be drawn from ( since ) . If we attempt to discriminate between the two possible inputs by using a linear-classifier , then the error associated with the best linear-classifier is simply given by the overlap of the distributions and . Because and for this simple scenario , and the variance of these distributions is very similar for ( see Fig . 5 ) , the error is well-approximated bywhere is the difference in the means of and , and is the average variance of and . In this section we describe the point-neuron model used in the section entitled “A population-dynamics approach towards verifying Hypothesis 2 within more general networks” . This model is a stripped down version of the fly AL , consisting of discrete-state LNIs , each driven by a different ORN . We will model each ORN-LNI pair as a discrete-state discrete-time Markov process which is as simple as possible , while still retaining the following features: ( i ) each LNI generates spikes , ( ii ) each ORN input spike contributes to the vesicle-depletion of that ORNLNI synapse , and ( iii ) , each LNI spike gives rise to presynaptic-inhibition of ORNLNI synapses . We will model the ORN-LNI pair using the state-variables , and which represent LNI membrane-potential , ORN vesicle-depletion and ORN presynaptic-inhibition , respectively . At each discrete time , each state variable is either or , thus , at each time , the ORN-LNI pair is in one of states . The input from the ORN to the LNI is modeled as a bernoulli-random-variable , which is with probability ( and otherwise ) . The state-variables undergo transitions of the following form: , , , where ( 15 ) and the function is the logistic functionFor this system and are the typical persistence times of the and states ( respectively ) , and we will assume that . The state is considered a ‘firing’ state for LNI . If , then always equals . If and the LNI does not receive input ( i . e . , ) , then . However , if and , then may transition to the firing state . Given that , the probability of transitioning from to the firing-state is typically , but is lowered if either or . The vesicle-depletion parameter is likely to transition to the state whenever the LNI receives input ( i . e . , ) . The presynaptic-inhibition parameter is likely to transition to the state whenever many other LNIs in the network fire . Note that the connectivity matrix encodes the connectivity of the network , and can be chosen to encode many different network architectures ( e . g . , a densely connected homogeneous network , or a sparsely connected heterogeneous network ) . If is nonzero , then the LNI presynaptically-inhibits the ORN , making it more likely that , and thus less likely that ORN input from the ORN to the LNI will cause the LNI to fire . For this model are the overall strengths of vesicle-depletion and presynaptic-inhibition . As increases , the likelihood of transitioning to the state increases . Similarly , as increases , the likelihood of transitioning to the state increases as long as for some . Ultimately , we will assume that the probability that the neuron will transition from the state = { , , } at time to the state = { , , } at time is given by ( 16 ) Note that is an state-transition matrix which depends on the state of the neuron in the system as long as . This section reviews a diagrammatic approach to analyzing network dynamics , and presents the salient calculations relevant to analyzing ISI-distribution and firing-rate ( which can then be used to analyze reliability and sensitivity , respectively ) . One way to understand the equilibrium dynamics of a network such as Eq . 15 is to first picture the network as a point in phase-space , with the network's current state determined by the collection of parametersat the current time , where we denote by the state of the ORN-LNI pair . As time passes this network will trace out a trajectory in phase-space , and this trajectory will depend on the network's architecture ( i . e . , , , , ) . If one could determine the ‘typical’ phase-trajectories exhibited by this network ( over very long times ) then , in particular , one could determine this network's spike-time reliability . If one could determine how this network's typical trajectories shift as the input changes , then one could determine this network's sensitivity . The typical trajectories of a network can be determined by considering both the evolution-operator of the network , and the frequency with which the network visits each part of phase-space ( i . e . , the network's equilibrium-distribution ) . The full evolution-operator is the probability that the network moves from state to state over one timestep . In this case is an matrix such that each entry has the formThe probability that the network will be in state at time , given that the network was in state at time is ( 17 ) Eq . 17 can be thought of as an integral over all possible paths in state-space connecting to ( i . e . , each path traverses the system-states , , … , in sequence ) . The equilibrium-distribution is an eigenfunction of with eigenvalue — namelyand in this case is an matrix ( i . e . , an -dimensional vector ) . In this discussion we will assume that is unique ( i . e , . only has a single equilibrium-distribution ) . Note that both and are functions of the network's architecture . Given both and , one can determine many properties of the network's equilibrium dynamics . For example , the probability that the neuron fires at any given time ( i . e . , the steady-state firing-rate of the neuron ) is given bywhere is a operator such that , except for states in which , in which case ( i . e . , ) . Similarly , the probability that the neuron fires at times and , without firing at any intermediate times ( denoted by ) is given bywhere is a operator such that . The sensitivity of the network's firing-rates can be calculated via the derivatives . The reliability var of the neuron in the network can be characterized by calculating the variance of ( considered as a distribution with respect to ) . Ideally , one might wish to determine how dynamic sensitivity ( i . e . , ) and reliability ( i . e . , var ) vary as functions of a network's architecture . Unfortunately , the explicit functional dependence of and on architectural parameters ( such as , , , ) cannot be directly determined for most typical networks . However , it is possible to approximate these quantities by considering a weak-coupling expansion of and in terms of . If , then each ORN-LNI pair is independent from the rest of the network , and the full state-evolution operator can be constructed by taking an operator-direct-product of the various , where is the -dimensional state-evolution operator associated with the ORN-LNI pair shown in Eq . 16 ( note that if , then each is independent of all other neurons ) . Similarly , if the full equilibrium-distribution can be constructed by taking the product of the various , where is the -dimensional equilibrium-distribution of the ORN-LNI pair ( note that is the eigenvector of with eigenvalue ) . Both and only depend on and . The sensitivity and reliability for this uncoupled network can be determined simply by computing the sensitivity and reliability for individual ( uncoupled ) ORN-LNI pairs . If is small , then the network's full state-evolution operator is no longer a direct product of the ( and is no longer a product of the ) . Nevertheless , by taking a Taylor-expansion of in terms of ( around ) one can approximate and via a seriesIt can be shown that the -order terms in these series ( corresponding to and ) incorporate subnetworks of the original network spanning up to ORN-LNI pairs [24] , [25] . Specifically , the -order terms capture the equilibrium dynamics of each single ORN-LNI pair in the absence of the rest of the network . The terms capture the first-order corrections associated with a single presynaptic-inhibitory connection of the form . The terms capture both the second-order corrections associated with a single presynaptic-inhibitory connection ( of the form ) , as well as the second-order corrections associated with presynaptic-inhibitory connections ( of the form ) . In the main text ( Fig . 7 ) , we have grouped the -order terms corresponding to only presynaptic-inhibitory connection with the -order terms associated with that connection . For example , when presenting the term associated with the subnetwork , we implicitly include both the -order term proportional to , as well as the -order term proportional to . When presenting the term associated with the subnetwork , we implicitly include both the -order term proportional to , as well as the -order term proportional to . Using the series-expansion for and , one can compute a series-expansion for many quantities of interest ( e . g . , firing rate , autocorrelation , sensitivity or reliability var ) in terms of subnetworks of the original network . One attractive feature of this approach is that the formal series-expansion can be constructed without specifying the connectivity matrix . The terms of the series expansion can then be analyzed to determine which connectivity matrices will give rise to various dynamic phenomena . As an example , the terms and in the series expansion for can be written as:where we use the notation that is equal to the single-neuron operator shown in Eq . 16 , with , and is the derivative of with respect to ( the coupling parameter which appears in ) . We also use the operatorIn the above representation of and , we use to denote an operator-direct-product , and to denote an accumulation of operator-direct-products ( analogous to the use of ‘’ and ‘’ respectively ) . | Understanding the intricacies of sensory processing is a major scientific challenge . In this paper we examine the early stages of the olfactory system of the fruit-fly . Many experiments have revealed a great deal regarding the architecture of this system , including the types of neurons within it , as well as the connections those neurons make amongst one another . In this paper we examine the potential dynamics produced by this neuronal network . Specifically , we construct a computational model of this early olfactory system and study the effects of synaptic-depression within this system . We find that the dynamics and coding properties of this system depend strongly on the strength , and sources of , synaptic-depression . This work has ramifications for understanding the coding properties of other insect olfactory systems , and perhaps even other sensory modalities in other animals . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
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"Methods"
] | [
"computational",
"neuroscience",
"biology",
"neuroscience"
] | 2012 | Functional Roles for Synaptic-Depression within a Model of the Fly Antennal Lobe |
Strongyloidiasis is frequently under diagnosed since many infections remain asymptomatic and conventional diagnostic tests based on parasitological examination are not sufficiently sensitive . Serology is useful but is still only available in reference laboratories . The need for improved diagnostic tests in terms of sensitivity and specificity is clear , particularly in immunocompromised patients or candidates to immunosuppressive treatments . This review aims to evaluate both conventional and novel techniques for the diagnosis of strongyloidiasis as well as available cure markers for this parasitic infection . The search strategy was based on the data-base sources MEDLINE , Cochrane Library Register for systematic review , EmBase , Global Health and LILACS and was limited in the search string to articles published from 1960 to August 2012 and to English , Spanish , French , Portuguese and German languages . Case reports , case series and animal studies were excluded . 2003 potentially relevant citations were selected for retrieval , of which 1649 were selected for review of the abstract . 143 were eligible for final inclusion . Sensitivity of microscopic-based techniques is not good enough , particularly in chronic infections . Furthermore , techniques such as Baermann or agar plate culture are cumbersome and time-consuming and several specimens should be collected on different days to improve the detection rate . Serology is a useful tool but it might overestimate the prevalence of disease due to cross-reactivity with other nematode infections and its difficulty distinguishing recent from past ( and cured ) infections . To evaluate treatment efficacy is still a major concern because direct parasitological methods might overestimate it and the serology has not yet been well evaluated; even if there is a decline in antibody titres after treatment , it is slow and it needs to be done at 6 to 12 months after treatment which can cause a substantial loss to follow-up in a clinical trial .
Strongyloides stercoralis is an intestinal nematode that infects an estimated 30–100 million people worldwide [1] . It is more frequent in areas where hygienic conditions are poor and in areas with a warm and humid climate [2] . Although it generally occurs in subtropical and tropical countries , it might be present in temperate countries with favorable conditions [1] . However , strongyloidiasis can be now diagnosed in non-endemic countries due to the migration flows and travel , being the infection much more common in migrants than in travelers [3] . Risk factors for infection which have identified are HTLV-1 co-infection , malnutrition , chronic obstructive pulmonary disease ( COPD ) , diabetes mellitus ( DM ) , chronic renal failure or breastfeeding [4] , [5] . Due to the ability of the parasite to replicate within the host , it is a chronic condition , with a variety of clinical presentations , from asymptomatic patients who are the majority , to hyperinfection with potentially life-threatening dissemination of larvae in immunocompromised patients . They have been summarized in a several reviews [5] , [6] , [7] Strongyloidiasis is frequently under diagnosed since many infections remain asymptomatic and conventional diagnostic tests based on parasitological examination are not sufficiently sensitive . Serology is useful but is still only available in reference laboratories . The need for improved diagnostic tests in terms of sensitivity and specificity is clear , particularly in immunocompromised patients or candidates to immunosuppressive treatments . This review aims to evaluate both conventional and novel techniques for the diagnosis of strongyloidiasis . The specific objectives are ( i ) To review current parasitological tools for the diagnosis of strongyloidiasis , ( ii ) to review the role of immunodiagnostic tests in strongyloidiasis , ( iii ) to assess the usefulness of molecular diagnosis of S . stercoralis in faecal samples , ( iv ) to evaluate novel diagnostic tools in the diagnosis of the strongyloidiasis and ( v ) to review possible cure markers in the follow-up of patients treated for strongyloidiasis .
The search strategy , available at www . cohemi-project . eu , was based on the data-base sources MEDLINE , Cochrane Library Register for systematic review , EmBase , Global Health and LILACS . Other sources of information were also used such as conference proceedings , abstracts , masters and doctoral theses , correspondence with authors from recently published abstracts , and manuscripts in press . Reference lists of all the articles identified were also examined , and relevant cited references were similarly reviewed . The electronic literature search was updated on August 2012 . The results were limited in the search string to articles published from 1960 to August 2012 and to English , Spanish , French , Portuguese and German languages . The following search terms were used: “Strongyloides” OR “strongyloidiasis” AND “diagnosis” . No restrictions were made with regard to basic study design or data collection ( prospective or retrospective ) . Case reports , case series and animal studies were excluded . The articles were selected in the following way ( see figure 1 ) .
The study selection process is shown in figure 1 . Out of 2003 potentially relevant citations selected for retrieval , 1649 were selected for review of the abstract . Of those , only 296 studies were selected for full-text screening , excluding among them 165 studies and introducing 12 studies whilst reviewing other studies or by other supplementary sources . 143 were eligible for final inclusion .
Strongyloidiasis is a neglected parasitic disease the prevalence of which might be underestimated in many countries and has a particularly importance in immunosuppressed patients because of the risk of hyperinfection . It does not have characteristic clinical features apart from larva currens , although eosinophilia is usually common among infected patients . Stool examination is still considered the primary technique for the detection of S . stercoralis infection . Since direct microscopic examination was first used , many other parasitological methods have been implemented , improving considerably the detection rate of S . stercoralis larvae in faeces . Several specimens should be collected on different days to improve detection rate . However , the sensitivity of microscopic-based techniques might not be good enough , especially in chronic infections where larval output is very low . Furthermore , techniques such as Baermann or APC are cumbersome , time-consuming and are not currently deployed in most laboratories . Serology remains a useful tool both only for epidemiological studies and for the diagnosis of individual cases . However , it might overestimate the prevalence of disease due to cross-reactivity with other nematode infections . Recently , the use of a recombinant antigen ( NIE ) applied to the LIPS technique instead of ELISA has shown a promising reduction of cross-reactivity although more studies are required to confirm this . Another major problem in strongyloidiasis is to evaluate treatment efficacy , since direct parasitological methods might overestimate it and serology has not yet been well evaluated in this context . Although some studies have shown a clear tendency to decline in antibody titer after treatment , a clear cut-off value needs still to be defined . The slow decline means that serological testing needs to be done at 6 to 12 months after treatment which can cause a substantial loss to follow-up in a clinical trial . It is not yet clear as to the dose of ivermectin to eradicate Strongyloides infection , so further efficacy trials must be conducted . The lack of a reliable method to evaluate cure is a major concern in a trial design . Therefore , identification and evaluation of a valid cure marker should be undertaken before conducting these trials . In summary , there is an urgent need of new tools to diagnose strongyloidiasis: efforts are being done to improve specificity of current and new serological methods and their value as a reliable cure marker . Another option is to combine different diagnostic methods as a composite diagnosis to improve sensitivity and specificity for clinical trials , and situations requiring high diagnostic accuracy . In parallel , the development of new biomarkers to evaluate cure of the disease is urgently needed . This research need has been identified by COHEMI network as one of the major gaps in the management of strongyloidiasis . | Strongyloidiasis is a parasitic infection that can occur in any place of the world . It is not easy to diagnose because the conventional tests are not good enough , especially in individuals that do not present any symptoms of the disease . This is of particular importance in immunocompromised patients , because the disease can spread causing a disseminated disease which can be fatal . In this study , authors review both conventional and novel techniques for the diagnosis of strongyloidiasis . Parasitological examinations based on the detection of the parasite in faeces are the most common techniques used until now in the majority of laboratories . However , they have some disadvantages because most of the best techniques are cumbersome and time consuming and several stool samples have to be collected to improve the diagnosis . New techniques such as the serology which is performed through a blood test are becoming available , but they have still some problems; the test sometimes does not accurately differentiate strongyloidiasis from other helminthic diseases . Another major problem in this disease is to evaluate if patient is cured after the treatment . Parasitological methods can fail to detect treatment failure , and serology has not yet been well evaluated in this context . | [
"Abstract",
"Introduction",
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] | [
"medicine",
"infectious",
"diseases",
"public",
"health",
"and",
"epidemiology",
"epidemiology",
"public",
"health"
] | 2013 | The Laboratory Diagnosis and Follow Up of Strongyloidiasis: A Systematic Review |
The hallmark of canonical Wnt signaling is the transcriptional induction of Wnt target genes by the beta-catenin/TCF complex . Several studies have proposed alternative interaction partners for beta-catenin or TCF , but the relevance of potential bifurcations in the distal Wnt pathway remains unclear . Here we study on a genome-wide scale the requirement for Armadillo ( Arm , Drosophila beta-catenin ) and Pangolin ( Pan , Drosophila TCF ) in the Wnt/Wingless ( Wg ) -induced transcriptional response of Drosophila Kc cells . Using somatic genetics , we demonstrate that both Arm and Pan are absolutely required for mediating activation and repression of target genes . Furthermore , by means of STARR-sequencing we identified Wnt/Wg-responsive enhancer elements and found that all responsive enhancers depend on Pan . Together , our results confirm the dogma of canonical Wnt/Wg signaling and argue against the existence of distal pathway branches in this system .
Wnt proteins are highly conserved signaling molecules specifying the fate and behavior of cells in multicellular animals ranging from nematodes to humans [1] . They play crucial roles in embryogenesis , pattern formation and tissue homeostasis during development and in adult life . Therefore it is not surprising that aberrant Wnt signaling has been found to be implicated in many human diseases [2] . Following the identification of Wnt proteins nearly 40 years ago [3–5] genetic and biochemical studies have revealed mechanistic details of how the signaling cascade operates when cells receive a Wnt signal [for review see 6] . As a consequence of Wnt/Wg proteins binding their cognate receptors , beta-catenin is no longer marked for degradation and accumulates in the cytoplasm and nucleus [7–10] . In the prevailing model , TCF is targeted through its DNA binding domain to Wnt-responsive elements ( WREs ) in the promoters or enhancers of target genes [11] and initiates the transcription of Wnt/Wg-responsive genes when complexed with beta-catenin . In the absence of Wnt/Wg ligand , beta-catenin is phosphorylated and degraded while TCF is bound by transcriptional repressors , such as Groucho and Coop [12–15] . In contrast to the well-studied mechanism of gene activation , the mechanisms by which beta-catenin and TCF promote target gene repression are not well understood [16] . Several reports suggest that , in addition to beta-catenin and TCFs , other factors are involved in Wnt-mediated repression , such as Prop1 , Mad or Zic [17–19] . Furthermore it is not clear , in which context alternative [20] or traditional TCF binding sites are used for transcriptional repression [21–23] . A recent study showed that TCF4 is a predominant factor in mediating the Wnt response and for recruiting beta-catenin to DNA [24] , however ongoing research on the Wnt signaling pathway has repeatedly demonstrated that beta-catenin as well as TCF interacts with various other proteins . Yet it remains to be determined , whether alternative transcriptional complexes also regulate the expression of Wnt/Wg target genes . For example , an interaction between beta-catenin and FOXO-transcription factors in mouse and DLD-1 human colon carcinoma cells has been demonstrated resulting in the activation of genes involved in oxidative stress and colon cancer metastasis [25–27] . Furthermore in mouse embryonic stem cells it was shown that beta-catenin forms a complex with Oct4 to promote Oct4-driven transcription and pluripotency [28] . In addition , studies in Xenopus reported an interaction between beta-catenin and Sox17 , promoting expression of Sox17 target genes [29] , and more recently it was suggested that beta-catenin complexes with YAP1 and TBX5 in human cancer cell lines [30] . In addition , alternative binding partners have also been reported for TCF , such as Plakoglobin or Mad [31 , 18] . In this study , we address the question of whether alternative routes exist that bypass beta-catenin or TCF to promote the transcription of Wnt/Wg target genes in Drosophila cells . Using cells that lack either Arm or Pan and functional read-outs ( i . e . RNA-seq and STARR-seq ) , we show that both , Arm and Pan , are absolutely required for target gene activation and repression . Consistent with these findings , we further demonstrate that Wnt/Wg-responsive enhancers also require Pan , arguing against the existence of distal branches in the Wnt signaling pathway .
Next-generation RNA-sequencing ( RNA-seq ) was used to identify and quantify the expression of target genes of the Wnt/Wg signaling pathway in Drosophila Kc167 cells . Cells were treated either with Wg-enriched medium ( referred to as Wingless-conditioned medium , WCM; [32] ) , or control-conditioned medium ( CM ) lacking the Wg ligand . Wg-responsive genes were determined by statistical analysis of gene expression levels in treated samples versus control samples , according to a protocol described in [33] . In order to determine a high confidence set of Wnt/Wg targets , genes had to pass the following selection criteria: exhibit a significantly altered expression profile ( WCM vs CM , p-value ≤ 0 . 0005 ) and an at least two-fold change of expression upon Wg stimulation ( Fig 1A ) . WCM-treatment resulted in the robust induction of 51 genes . Among them we found previously identified Wnt/Wg target genes such as naked cuticle ( nkd ) , CG6234 , frizzled 3 ( fz3 ) and Peroxidasin ( Pxn ) [34–36 , 20] , confirming our quality filters . 40 genes were at least two fold up-regulated ( positive targets ) and 11 genes two fold down-regulated ( negative targets ) ( Fig 1B ) . 7 positive and 5 negative candidate target genes were confirmed by qRT-PCR ( Fig 1C ) . This high confidence set of Wnt/Wg target genes was used to systematically elucidate potential beta-catenin or TCF-independent branches of Wnt/Wg signaling . To investigate whether Arm can be bypassed via alternative branches of the pathway , we generated arm knockout cells using the CRISPR/Cas9 technology as described by Bassett and colleagues [37] . In order to generate Drosophila arm null mutant cells we used sgRNAs targeting two different exons that are present in all transcript variants ( Fig 2A and 2B ) . sgRNA-a1 on the reverse strand targets the translational start site residing in exon 2 . sgRNA-a2 targets a site in the third exon . The presence of CRISPR-induced mutations generated by NHEJ ( non-homologous end joining ) was assessed by sequencing of the PCR products spanning the sgRNA target sites ( see Material and Methods ) . The analysis revealed that most of the alleles had indel mutations at the expected cleavage sites , some of which lead to the deletion of the translational start site or to frameshifts in exon 3 . To generate an arm-/- cell line , we carried out serial dilutions and searched for cell populations that carried previously identified mutations using allele-specific primers as described in [38] . In this way , we isolated an arm null mutant cell line ( named arm-/--AFII7/8 ) which was a homogenous cell population ( see Material and Methods ) carrying a deletion of either one or sixteen nucleotides in the second exon , each of them destroys the START codon ( ATG ) , and a deletion of one nucleotide in the third exon ( Fig 2B ) . Importantly no wild-type alleles were present . These mutations , affecting both arm alleles , result in frameshift mutations introducing a premature termination codon that should trigger nonsense-mediated mRNA decay ( NMD ) [39] ( S1A Fig ) . We confirmed the complete loss of Arm protein in arm-/--AFII7/8 cells by Western blot analysis ( Fig 2C , S1B Fig ) . Next we investigated whether Arm is absolutely required for the Wnt/Wg-driven transcriptional output . To that end arm-/--AFII7/8 cells were treated either with WCM or CM and target gene responses were monitored by RNA-seq . We found that the induction of the positive Wnt/Wg target genes is dependent on Arm , since their expression was not changed in arm null mutant cells . Similarly all negative target genes are no longer repressed in arm-/--AFII7/8 cells ( Fig 3A and 3B ) . These results demonstrate that Arm is absolutely necessary for both , activation and repression of identified Wnt/Wg targets . We confirmed our results with qRT-PCR analysis of 11 candidate targets genes ( S2 Fig ) . From the analysis above , we conclude that Arm is absolutely required for both activation and repression of Wnt/Wg target genes and interpret this as evidence against the existence of an Arm-independent Wnt/Wg signaling transcriptional output . Since several alternative interaction partners for beta-catenin have been proposed for the activation and the repression of genes , such as Sox17 [29] , Oct4 [28] and Prop1 [17] , we next asked whether TCF-independent Wnt/Wg signaling exists . To search for TCF-independent Wnt/Wg signaling , we utilized a similar setup as described above to generate pan null mutant cells . Two distinct sgRNAs were used to target independent loci within the pan gene ( Fig 4A ) . We isolated a population of pan null mutant cells that no longer contain any wild-type allele . Similar to the arm-/--AFII7/8 cells , the selected pan null mutant cells , termed pan-/--AF1AD26 , carry three defined mutations that lead to frameshift mutations . Molecular analysis of the alleles revealed no wild-type allele but a large deletion of approximately 9 kb spanning the two selected CRISPR sites ( Fig 4B ) . In addition , pan-/--AF1AD26 cells also harbor two distinct frameshift mutations in the HMG box , both of which result in premature termination codons ( S3A Fig ) and NMD . Consistent with this qRT-PCR analysis showed a reduction of pan mRNA in knockout cells compared with wild-type cells ( S3B Fig ) . The presence of the three pan mutant alleles suggests that at the pan locus Kc cells are polyploid; segmental polyploidy has been reported for Kc cells [40] . Since no anti-Pan antibodies were available to confirm the absence of functional Pan protein we used the wingful luciferase reporter assay , an artificial built reporter giving a robust and high Wg-response [41] . Consistent with the absence of Pan , in pan-/--AF1AD26 cells the wingful reporter could no longer be induced after WCM-stimulation; responsiveness could be restored by Pan overexpression ( Fig 4C and 4D ) . To answer the question of whether Pan is dispensable for Wnt/Wg-regulated induction of target genes , we treated pan-/--AF1AD26 cells with either WCM or CM and performed RNA-seq . We observed that pan-/--AF1AD26 cells can no longer transduce the Wnt/Wg signal as expression of none of the identified Wnt/Wg targets was altered . Neither positive nor negative Wnt/Wg-target genes significantly changed their expression profile in pan knockout cells after Wg stimulation providing evidence that Pan is indispensable for the activation and repression of Wnt/Wg target genes ( Fig 5A and 5B ) . The lack of a change in the expression of several candidate Wnt/Wg targets was confirmed by qRT-PCR ( S2 Fig ) . Like most major developmental signaling pathways , the Wnt/Wg system uses a “transcriptional switch” mechanism to positively regulate target gene expression [42] . In the absence of Wnt/Wg signaling , the transcription of target genes is repressed by Pan via its interaction with co-repressors such as Groucho or Coop [13 , 15] . Pan turns into an activator when complexed with Arm following pathway activation . It has been shown that loss of Pan function leads to de-repression of the Wg target genes nkd and CG6234 in the Wg OFF state in vivo and in vitro [35 , 43] . To determine whether this mode of action is valid for the entire set of identified Wnt/Wg target genes we compared the gene expression profiles of wild-type and pan-/--AF1AD26 cells in the absence of Wnt/Wg signaling . Interestingly , we found that only a fraction ( 37 . 5% ) of positive target genes were de-repressed in pan null mutant cells ( Fig 5C; fold change ≥ 2; p-value ≤ 0 . 0005 ) ; among them were nkd and CG6234 [35] . We also noted that this set of de-repressed genes is highly induced in the presence of Wg ligand ( Fig 5C ) . In contrast , the absence of Pan had no effect on the basal expression of the other ( the majority ) target genes . However , we also identified some genes exhibiting reduced levels of expression in unstimulated pan knockout cells ( Fig 5C ) , suggesting that Pan might be required for their transcription in the absence of Wnt/Wg signaling . Blauwkamp and colleagues ( 2008 ) proposed this mode of action for Pan in Drosophila Kc cells for several negative target genes , when cells were not exposed to Wnt/Wg [20] . Transcription factors bind to specific signal responsive elements in the promoters or enhancers of target genes in order to regulate their expression [44] . So far we have analyzed in detail the Wnt/Wg-triggered transcriptional output and demonstrated that both , Arm and Pan are absolutely required for the activation and repression of Wnt/Wg target genes in Drosophila cells . However , in order to obtain a more complete understanding of the transcriptional regulation of Wnt/Wg target genes , we carried out Self-transcribing-active-regulatory-region-sequencing ( STARR-seq ) , a genome-wide enhancer activity assay that reveals the identity of DNA sequences that can function as enhancers in a particular cell type [45–46] and in response to external stimuli , such as the insect steroid hormone ecdysone [47] . To identify enhancers whose activity changes in response to the Wnt/Wg signal , we performed STARR-seq under conditions of active Wnt/Wg signaling and under control conditions ( Fig 6A , S4A Fig ) . For technical reasons , we used the Gsk3β-inhibitor CHIR99021 ( CHIR ) –a widely used alternative inducer of Wnt-signaling to stimulate Wg signaling in the STARR-seq experiments [48 , 49] ( see Material and Methods ) , whose activity we compared to WCM by using the wingful reporter ( S5A Fig ) . Furthermore , treatment with CHIR robustly induced expression of known Wg targets in Drosophila cells ( S5B and S5C Fig ) . Activation of the Wnt/Wg signaling pathway led to robust changes in enhancer activities: we identified 185 STARR-seq peaks ( p-value ≤ 0 . 001 ) that were at least 3-fold induced in the CHIR-treated versus control sample , and 348 that were at least 3-fold repressed ( Fig 6B ) . Among the induced peaks , 73 ( 39 . 5% ) were induced more than 5-fold and 32 ( 17 . 2% ) more than 10-fold ( Fig 6C ) . We found several enhancers , which have already been described as WREs in Drosophila Kc cells . For instance we identified two enhancers close to the TSS of nkd ( first intron and 10 kb upstream of TSS ) ( Fig 6D ) , the well-studied WRE 2 . 2 kb upstream of the TSS ( transcription start site ) of Notum , an enhancer 15 . 2 kb upstream of pxb and an element in the 5’ intergenic region 178 bp upstream of Ugt36Bc [50 , 43 , 20] ( S4B Fig ) . We validated activated and repressed STARR-seq enhancers in luciferase reporter assays as described in [47] . Consistent with the STARR-seq results , we found luciferase reporter activities responded as expected to both CHIR treatment and WCM treatment: increased activity for activated enhancers and decreased activities for repressed enhancers ( S4C and S6 Figs ) . Taken together , these results indicate that the activities of STARR-seq detected enhancers are modulated by Wnt/Wg signaling . To further test that the identified enhancers were directly regulated by Pan , we assessed the enrichment of known transcription factor motifs [46] in Wnt/Wg-responsive STARR-seq enhancers in comparison to negative control sequences ( see Material and Methods ) . The known TCF/Pan motif [51] ( Fig 6E ) was strongly enriched in induced enhancers ( 2 . 7-fold enrichment , p-value = 1 . 3x10-8 ) , whereas it was not enriched in constitutive or repressed enhancers ( p-value = 0 . 27 and p-value = 0 . 08 , respectively ) . Using de novo motif discovery ( see Material and Methods ) we found an additional Helper site motif in induced enhancers ( GCCGCC , p-value = 3 . 4x10-14; Fig 6E ) , which is a GC-rich element near TCF/Pan binding sites that is critical for Wnt/Wg target gene activation [52–53 , 11] . To experimentally validate the necessity of the TCF/Pan motif for Wnt/Wg induced enhancers , we tested wild-type and mutated versions of the TCF/Pan motif in 3 enhancers of the odd , how and lbe genes in luciferase assays . While the wild-type enhancers activated luciferase reporters 31- , 11- and 7-fold after Wnt/Wg induction by CHIR treatment , the Pan motif-mutant sequences did not respond to treatment ( <1 . 2-fold induction ) , a substantial and significant difference in each case ( p-value≤0 . 01; Fig 6F ) , indicating that at least these 3 Wnt/Wg-responsive enhancers require the TCF/Pan motif . Given the enrichment of the TCF/Pan motif in the Wnt/Wg-responsive STARR-seq enhancers and the necessity of this motif for enhancer function , we next examined whether Wnt/Wg-responsive enhancers require the Pan protein . We repeated the STARR-seq experiments in pan null mutant cells ( S7A Fig ) and again confirmed our findings for a subset of the enhancers by treatment with WCM ( S6 Fig ) . Consistent with our analysis of target gene expression by RNA-seq , we found that enhancer-induction was overall strongly reduced from 26 . 1-fold the highest induction in wild-type cells to at most 3 . 8-fold in pan null mutant cells and that the vast majority ( 80% ) of Wnt/Wg-induced enhancers no longer responded to pathway activation ( Fig 7A ) . For example , the enhancers in first intron and 10 kb upstream of TSS in the nkd gene locus that were strongly induced in wild-type cells by Wnt/Wg signaling were not any more induced nor detected in pan knockout cells ( p-value>0 . 001 , Fig 7B ) . We confirmed these findings by testing several of the most strongly activated enhancers in luciferase reporter assays . In agreement with the STARR-seq results , enhancers that were strongly activated by Wnt/Wg signaling in wild-type cells did not respond to Wnt/Wg pathway activation in pan knockout cells ( S7B Fig ) . Taken together , these results argue that Pan is required for the activation of Wnt/Wg-responsive enhancers .
According to the generally accepted dogma the canonical Wnt signaling pathway culminates in the transcriptional induction of target genes via the beta-catenin/TCF complex . During the past decade , several alternative configurations of the Wnt pathway have been proposed in which either beta-catenin or TCF is bypassed . A recent study explored the co-occupancy of TCF4 and beta-catenin using ChIP-seq and showed that TCF4 is the major factor in tethering beta-catenin to DNA [24] . However , the study could not exclude the possibility that other putative factors could compensate the lack of TCF or beta-catenin–an aspect that is still poorly understood in the field of Wnt research . In the present study , we investigate whether and , if yes , to which extent a Wnt response can bypass beta-catenin or TCF . To this aim we used somatic cell genetics in Drosophila cultured cells . As a basis for our analysis , we first carried out a systematic and genome-wide study to explore all Wnt/Wg-related transcriptional outputs in this system . We identified a set of 51 genes that are induced upon Wg stimulation . To probe whether their expression requires Arm or Pan , we generated cells lacking one or the other of these factors using the CRISPR/Cas9 technology . Surprisingly , we found that Arm and Pan are both absolutely required for all Wnt/Wg-related transcriptional outputs in this system . As a transcription factor , Pan binds to DNA regulatory elements up- or downstream of the TSS of its target genes . Thus , next we asked , whether these DNA regulatory elements–enhancers/repressors–are dependent on Pan using STARR-seq . Impressively , consistent with our RNA-seq analysis , we found that the induction of Wnt/Wg-responsive enhancer elements fully depends on Pan . In our work we identified eleven down-regulated target genes and showed that knockout of Arm or Pan is sufficient to abrogate their repression . We observed the same effect for repressed enhancers in pan null mutant cells . These findings are in line with a previous study in Drosophila Kc cells [20] , in which it was shown that Pan and Arm are required for the repression of the negative target genes Pxn , Ugt36Bc , Tig and Ugt58Fa [20] . We also found Pxn in our Wnt/Wg target gene set . However , the other genes were less than 2-fold repressed in our system and thus did not pass our selection criteria . This might be due to technical differences in Wnt-pathway stimulation and/or timing . Blauwkamp and colleagues showed also in their study that the negatively regulated targets exhibited lower expression upon Pan reduction in the Wnt OFF state [20] , implicating that Pan normally activates their expression even in the absence of Wg ligand . When analyzing our data , we found that only half of the negative target genes appear to be activated in the Wnt OFF state upon Pan abrogation , the remaining targets did not exhibit a significant change in their expression profile . This suggests that they might be indirect targets or independent of Pan . Furthermore , we found that several repressed enhancers possess neither the traditional TCF/Pan binding motif , nor the previously reported alternative binding site important for repression , indicative for a Pan-dependent indirect regulation of repressed enhancers . It is likely that Pan is tethered to the DNA by other co-factors as it was shown for dpp or CDH1 [21 , 23] . Thus , these Pan-dependent enhancers without any known TCF/Pan binding site provide a good starting point for further molecular studies to gain insight into the still incomplete model of Wnt-mediated repression [16] . In sum our results demonstrate that all Wnt/Wg-related transcriptional output in Drosophila cells requires Arm and Pan and that the induction of Wnt/Wg-responsive enhancers is fully dependent on Pan . Hence , collectively our data argue against the existence of distal branching of the Wnt pathway in this system .
Drosophila Kc167 cell lines were cultured in M3+BYPE medium , supplemented with 5% fetal bovine serum ( FBS ) and 1% penicillin and streptomycin at 25°C . Wg-CM was harvested from S2 tubulin wingless cells . S2 tubulin wingless cells were seeded 24 h prior collecting the supernatant ( 1x106 cells/ml ) by centrifuging the cells at 3500 rpm for 5 min . For the control medium S2 cells were prepared as described above . WCM or CM was added to Kc cells for 24 h to induce Wnt/Wg signaling . To induce the Wnt/Wg signaling pathway with CHIR99021 ( S1263 , Selleckchem ) , 25 μM of the inhibitor was used and added to the medium for 24h . As control DMSO was used . After 24 h of induction , cells were harvested . Cas9 ( 49330 , Addgene ) and empty gRNA vector ( 49410 , Addgene ) were obtained from Addgene . Oligo design and cloning was accomplished after manufacturer’s protocol . CRISPR was performed as described in [37] . Briefly , cells were plated at 2 x 106 cells per well of a 6-well dish and a total of 1 . 7 μg DNA , Cas9 and gRNA in a 1:1 ratio , was co-transfected into each well using Fugene HD ( Promega ) at a 1:2 ratio ( μg:μl ) , following manufacturer’s instructions . Both gene loci were targeted simultaneously using a gRNA and Cas9 with integrated gRNA . Transfections were analyzed after 3 days , and selection was performed in 5 μg/ml Puromycin ( P8833 Sigma ) . The genotype was analyzed using PCR primers spanning the cut site . PCR products were cloned in pGEMT-vector system ( Promega ) and 10–100 clones were analyzed by sequencing . Primers for gRNA cloning and for detection of CRISPR events are available in the S1 Table . Nuclear protein extraction was performed as described in [54] . For Western blot analysis , monoclonal anti-Arm ( 1:500; N2 ( 7A1 ) , DSHB ) and monoclonal anti-alpha-Tubulin ( 1:5000; T5168 , Sigma ) antibodies were used and followed by HRP-anti-mouse IgG ( 705-035-003 , Jackson Immuno Research Laboraties , inc ) . Real-time q-PCR analyses were carried out with SYBR Green Supermix ( BioRad ) on a iCycler iQ real-time OCR detection system ( BioRad ) . For qRT-PCR , total RNA was extracted from 1–2 x 106 cells with NucleoSpin RNA extraction kit from Macherey-Nagel according to the manufacture’s protocol and reverse transcribed with Roche , followed by qRT-PCR . Sequences of the primer pairs used are listed in S1 Table . All pair-end sequencing was performed on an Illumina HiSeq2500 machine at the Genomics Platform of the University of Geneva . For all experiments we compared three independent biological replicates and merged them for the subsequent analysis . All RNA-seq files are available from SRA NCBI database . Submission code: SUB2472808; Study: PRJNA378604 ( Accession Number SRP101692 ) . All deep-sequencing data were mapped to the Drosophila reference genome dm3 using TopHat and analyzed as described in [34] and using thresholds as indicated above . We used GraphPad Prism for all statistical analysis and R for plotting . STARR-seq in Drosophila WT cells and pan knockout cells was performed in two biological replicates as described in [47] . To obtain Wnt-responsive enhancers , cells were treated with 25μM CHIR99021 or DMSO for 24h . Data were analyzed as described in [47] . For Fig 7A fold enrichments were calculated directly over DMSO-treated samples at summits of induced enhancers and p-values indicate significance of the fold change . All STARR-seq files are available at the GEO database ( GEO number GSE96542 ) . For TCF/Pan motif enrichment analysis , we used 200 bp regions around the summit of 185 induced , 348 repressed , 1834 constitutive enhancers , and 987 random sequences that were not detected with STARR-seq but followed the same genomic distribution ( denoted as negative regions ) . Enrichments were calculated as described [46] . De novo motif analysis was done with DREME using negative regions as a background set ( see S2 Table ) . Enhancer candidates were amplified from genomic DNA of Drosophila Kc167 cells ( for primers see S3 Table ) . All candidates were subcloned to either pCR8/GW/TOPO ( Invitrogen ) or pENTR/TOPO ( Invitrogen ) and delivered into the firefly luciferase vector [45] using the Gateway LR Clonase II enzyme mix ( Invitrogen ) . Kc cells ( 1x105 ) were transfected using Fugene HD ( Promega ) with a total of 300 ng of various plasmid combinations ( 1:3 ratio of promoter reporter plasmid to Renilla ) . Luciferase activities were measured 48 h after transfection and after stimulation with either Wg ligand or CHIR99012 using the Dual-Luciferase Reporter Assay System ( Promega ) . Every experiment was repeated at least twice with three replicates in each independent experiment . Enhancers’ sequences used are listed in S3 Table . | Our manuscript addresses the question of whether either of the canonical transduction components , beta-catenin or TCF , can be bypassed when the Wnt pathway is activated . By using somatic cell genetics in Drosophila cells ( via CRISPR/Cas9 editing ) in combination with RNA-seq and STARR-seq ( Self-transcribing-active-regulatory-region-sequencing ) as functional read-outs , we provide firm evidence against the existence of distal branches in the Wnt pathway . | [
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"drosophila... | 2017 | Probing the canonicity of the Wnt/Wingless signaling pathway |
The rising prevalence of arthritogenic alphavirus infections , including chikungunya virus ( CHIKV ) and Ross River virus ( RRV ) , and the lack of antiviral treatments highlight the potential threat of a global alphavirus pandemic . The immune responses underlying alphavirus virulence remain enigmatic . We found that pentraxin 3 ( PTX3 ) was highly expressed in CHIKV and RRV patients during acute disease . Overt expression of PTX3 in CHIKV patients was associated with increased viral load and disease severity . PTX3-deficient ( PTX3-/- ) mice acutely infected with RRV exhibited delayed disease progression and rapid recovery through diminished inflammatory responses and viral replication . Furthermore , binding of the N-terminal domain of PTX3 to RRV facilitated viral entry and replication . Thus , our study demonstrates the pivotal role of PTX3 in shaping alphavirus-triggered immunity and disease and provides new insights into alphavirus pathogenesis .
Arthritogenic alphaviruses including Ross River virus ( RRV ) and chikungunya virus ( CHIKV ) are the causative agents of the widespread arthropod-borne illnesses , Ross River virus disease ( RRVD ) and chikungunya fever ( CHIKF ) respectively [1] . RRV is endemic to Australia , Papua New Guinea and South Pacific islands . An average of ~6 , 000 cases of RRVD endemic to Australia are reported annually [2] , and ~500 , 000 individuals were infected during its first outbreak in Fiji [3] . CHIKV , which is closely related to RRV , has caused large sporadic outbreaks globally , with the largest recorded outbreak of up to 6 . 5 million cases in India [4] . Recently , 470 , 000 suspected and confirmed cases of CHIKF have been reported in the Americas [5] . In both RRVD and CHIKF , clinical symptoms include fever , myalgia , fatigue and maculopapular rash [1 , 6] . Debilitating persistent polyarthritis is the clinical hallmark of alphaviral diseases , often affecting joints in the hands , wrists , elbows , knees and feet , which can persists for months to years post infection [7–9] . In addition , we have recently identified severe pathological bone loss as another characteristic of alphaviral disease which may contribute to the chronic persistent arthralgia [10] . Emerging clinical evidence has demonstrated an increased tendency of CHIKF patients to develop RA [11] , and RRVD patients with pre-existing arthritis such as RA have prolonged rheumatic symptoms after infection [12] . These studies suggested a potential link between alphaviral-induced arthritis and other bone diseases , highlighting alphavirus infection as a possible predisposing risk factor for development of complicated bone disorders [13] . The persistency of debilitating polyarthralgias has a serious impact on quality of life and the economy , with an estimated cost of 34 million euros per year solely in the La Reunion CHIKV outbreak [14] . Symptomatic relief is the only therapeutic option currently available , due partly to a lack of understanding of the immune responses elicited during alphaviral infection . The cellular and humoral arms of innate immunity serve as the first line of host defense against alphaviral invasion . Despite the importance of the innate immune system in the defense against alphaviral infection , increasing evidence of a pathogenic role for innate mediators has also surfaced over the past few years . Excessive production of soluble innate mediators such as interleukin-6 ( IL-6 ) , granulocyte macrophage-colony stimulating factor ( GM-CSF ) , tumor necrosis factor-α ( TNF-α ) , interferon-γ ( IFN- γ ) , macrophage chemoattractant protein-1 ( MCP-1 ) and macrophage migration inhibitory factor ( MIF ) [15–17] contributes to alphaviral disease pathogenesis . Recent evidence that alphavirus-induced diseases can be exacerbated by overt expression of complement factor 3 ( C3 ) [18] and mannose binding lectins ( MBLs ) [19] highlights the significance of the complement cascade in modulating alphaviral disease pathogenesis . Long pentraxin 3 ( PTX3 ) is a pattern recognition molecule which belongs to the humoral arm of innate immunity . PTX3 has a role in all three complement pathways , enhancing the activation , inflammation and cell lysis processes [20] . PTX3 can be secreted by a broad range of cell types including neutrophils [21] , monocytes , macrophages and myeloid DCs [22] in response to inflammatory signals such as TNF and IL-1 [23] . Upon pathogen encounter , the release of PTX3 enables cells of monocyte-macrophage lineage to recognize and opsonize the pathogen , presenting it to activated phagocytic cells of the immune system for elimination [24] . Elevated expression of PTX3 has been implicated in many inflammatory and autoimmune diseases , including pulmonary infection [25] , giant cell arteritis [26] , atherosclerosis [27] and rheumatoid arthritis [28] . Intriguingly , PTX3 is thought to have both protective [29 , 30] and pathogenic functional roles [31] in the immune system . PTX3 has a variety of ligands , including complement components , microbial moieties , extracellular matrix proteins , growth factors and P-selectin [16] . The interaction of PTX3 and P-selectin is involved in the regulation of inflammation and leukocyte recruitment through attenuation of polymorphonuclear leukocyte ( PML , also known as neutrophils ) rolling at sites of inflammation [32] . Consequently , this affects the physiological functions of PMNs in pathogen defense and modulates inflammatory processes . The role of PTX3 in alphavirus-induced diseases has yet to be established . In this study , we identified the crucial involvement of PTX3 during acute alphaviral infections using specimens from CHIKF and RRVD patients . Characterization of PTX3-/- mice and PTX3-overexpressing HEK 293T cells revealed pathological roles of PTX3 in enhancing viral infectivity during acute RRV infection , which was dependent on the binding interaction between RRV and PTX3 . In summary , our data demonstrated the crucial role of PTX3 in modulating alphavirus-induced immune responses and disease manifestation through its N-terminal interaction with the virus particles leading to enhanced viral entry and replication .
Elevated levels of PTX3 have been associated with both protective and pathogenic functions in several inflammatory diseases . To investigate the involvement of PTX3 during acute alphaviral infection , we analyzed PBMCs and serum from CHIKF and RRVD patients for levels of PTX3 using qRT-PCR and ELISA , respectively . Transcriptional expression of PTX3 in PBMCs collected from CHIKF patients was significantly higher compared to controls ( Fig . 1A ) . Further segregation of the CHIKF patient cohort based on viral load ( Fig . 1B ) and disease severity ( Fig . 1C ) [15] revealed significantly higher transcriptional expression of PTX3 in patients with higher viral load and more severe disease . Similarly , ELISA analysis of serum specimens collected from acute RRVD patients revealed significantly higher levels of serum PTX3 compared to healthy controls ( Fig . 1D ) . Taken together , these data indicate that PTX3 is induced as part of the innate immune response during acute alphaviral infection and its expression is associated with viral load and disease severity . To determine the expression of PTX3 during alphaviral disease progression , we utilized an established mouse model of acute RRVD [33] . RRV-infected and mock-infected mice were sacrificed at 2 ( peak viremia phase ) , 5 ( disease onset phase ) , 10 ( peak disease phase ) and 15 ( recovery phase ) days post infection ( dpi ) . The serum , quadricep muscles and ankle joints were harvested for analysis . High levels of serum PTX3 were detected in RRV-infected mice across all time points , particularly at 2 and 10 dpi , in contrast to consistently low levels of PTX3 in serum from mock-infected mice ( Fig . 2A ) . To further investigate PTX3 expression at the sites of inflammation , total RNA was extracted from tissues and analyzed by qRT-PCR . A high level of PTX3 expression was observed at 2 dpi in the ankle joint , with levels declining as the disease progressed . In contrast , quadricep muscles showed peak PTX3 expression at 10 dpi , a time that correlated with the peak of disease ( Fig . 2B ) . IHC was also performed in quadriceps harvested from RRV- and mock-infected mice at 10 dpi ( Fig . 2C ) . Pronounced tissue damage was observed in the striated muscle fibers , which was associated with the presence of inflammatory infiltrates . Increased PTX3 expression was observed in the inflammatory infiltrates of quadricep muscles at peak disease ( Fig . 2C ) . PTX3 is secreted by a vast array of cell types . To identify the source ( s ) of PTX3 production during acute RRV infection , we harvested splenocytes from mock- and RRV-infected mice at 2 dpi for flow cytometry analysis . Total leukocytes ( CD45+ ) demonstrated significant elevation of intracellular PTX3 after RRV infection . Further segregation of the total leukocytes into various cellular subsets revealed PTX3 induction after RRV infection in only 2 subsets of cells—neutrophils ( CD11b+ Ly6Cint ) and inflammatory monocytes ( CD11bhi Ly6Chi ) . No induction of PTX3 was observed in NK cells ( NK1 . 1+ CD3- ) , T cells ( CD3+ CD19- ) and B cells ( CD3- CD19+ ) ( Fig . 2D ) . High expression of PTX3 during inflammatory diseases has been associated with differential effects [34] . To determine the role of PTX3 in RRV disease , PTX3-/- and wild-type ( WT ) C57BL/6 mice were infected with 104 PFU RRV and monitored for the development of RRVD clinical signs for up to 18 dpi . Disease onset in RRV-infected WT mice occurred at 3 dpi , with ruffled fur and very mild hind limb weakness ( clinical score 2 ) , while in PTX3-/- mice disease onset was significantly delayed commencing at 5 dpi . RRV-infected PTX3-/- mice also demonstrated milder disease signs between 2 to 7 dpi , compared to the RRV-infected WT mice ( Fig . 3A ) . In contrast , there was no significant difference in clinical presentation between PTX3-/- and WT mice during peak disease ( from 8 to 10 dpi ) . From 11 dpi , PTX3-/- mice showed faster disease recovery than WT mice and by 15 dpi regained full function of hindlimbs . In contrast , WT mice continued to display signs of hindlimb weakness until 18 dpi . To examine the role of PTX3 in modulating RRV replication in vivo , viral titre was determined in serum , ankle joints and quadricep muscles harvested at 2 and 10 dpi . As seen in Fig . 3B , viral titres in the serum and ankle joints of RRV-infected PTX3-/- mice were significantly reduced compared to WT mice at 2 dpi . There were no significant differences between PTX3-/- and WT mice in viral titres recovered from the quadricep muscles . At 10 dpi , viral titres recovered from the ankle joints of RRV-infected PTX3-/- mice were also lower than in WT mice . Titres in serum and quadricep muscles from both PTX3-/- and WT mice were below the level of detection at this time ( Fig . 3C ) . To confirm these observations , viral load quantification in ankle joints and quadricep muscles were performed using qRT-PCR . Consistent with previous results , higher viral load was detected in the ankle joints of WT mice at 2 and 10 dpi ( S1A Fig . ) , whereas no difference in viral load was detected between RRV-infected WT and PTX3-/- mice in the quadricep muscles ( S1B Fig . ) . Collectively , our data indicate that PTX3 deficiency delays the development of RRV clinical signs in infected mice during early infection and assists in rapid recovery in the latter stages of disease . Additionally , the absence of PTX3 also reduced the level of viremia and viral load in the ankle joints of RRV-infected mice . We next sought to determine the effects of PTX3 on the expression of inflammatory mediators IFN-Ɣ , TNF-α , IL-6 and iNOS in the early and late phases of RRVD . The quadricep muscles were collected from RRV-infected PTX3-/- and WT mice at early ( 2 dpi ) and peak ( 10 dpi ) RRV disease . At 2 dpi , IFN-Ɣ ( Fig . 4A ) , TNF-α ( Fig . 4B ) , IL-6 ( Fig . 4C ) and iNOS ( Fig . 4D ) levels were significantly reduced in RRV-infected PTX3-/- mice . However , at 10 dpi , IFN-Ɣ , TNF-α , IL-6 and iNOS levels were significantly upregulated in RRV-infected PTX3-/- mice compared to WT animals . Collectively , these data demonstrate that the absence of PTX3 results in delayed inflammatory responses in quadricep muscles of RRV-infected mice , as well as enhanced production of these immune mediators in the latter stages of infection . Having demonstrated the effect of PTX3 on the induction of soluble inflammatory mediators during acute RRV infection , we next investigated the effect of PTX3 on leukocyte recruitment during in vivo infection . As shown in Fig . 2C , localized cellular infiltration in quadricep muscles of RRV-infected mice occurs at peak disease ( 10 dpi ) . To examine the effect of PTX3 on cellular recruitment during early RRV infection , mice were inoculated via the peritoneal route with RRV . At 6 hpi , flow cytometry analysis of peritoneal lavages revealed significantly increased numbers of neutrophils and inflammatory monocytes in the peritoneal cavity of RRV-infected PTX3-/- mice compared to WT mice ( Fig . 5A ) . This early influx of neutrophils and inflammatory monocytes coincides with the chemotactic responses observed in the quadricep muscles of PTX3-/- mice . Among the 5 cytokines investigated , CCL2 and MIF were higher in quadriceps of RRV-infected PTX3-/- mice at 2 dpi compared to WT mice , but not during peak disease ( S2A , B Fig . ) . No significant difference in chemotactic responses of CCL3 ( S2C Fig . ) , CXCL1 ( S2D Fig . ) and CXCL2 ( S2E Fig . ) was observed between the PTX3-/- and WT mice at 2 and 10 dpi . To investigate the effects of PTX3 deficiency on cellular infiltrates during peak RRV disease , mice were infected subcutaneously with 104 PFU RRV and the quadricep muscles examined at 10 dpi . Previously we have shown that inflammatory monocytes and NK cells are the major cells recruited into muscles during localized inflammation [35] . As seen in Fig . 5B , the number of inflammatory monocytes was significantly reduced in PTX3-/- mice compared to WT controls . Infiltration of NK cells , however , was not affected by deficiency of PTX3 . Together , these results suggest that acute production of PTX3 dampens early recruitment of neutrophils and inflammatory monocytes , but enhances the egress of inflammatory monocytes in the latter stages of infection . We next determined the direct effect of PTX3 on the RRV infection process using HEK 293T cells overexpressing PTX3 . HEK 293T cells were transiently transfected with a plasmid expressing PTX3 for 20 h and approximately 5 μg/ml of PTX3 could be detected in supernatants using ELISA at this time . In vector-transfected HEK 293T cells , PTX3 could not be detected regardless of RRV infection ( S3 Fig . ) . Overexpression of PTX3 in HEK 293T cells resulted in a significant increase in viral titres recovered from supernatants of RRV-infected cells , compared to cells transfected with control vector , when infected with MOI 0 . 1 , 0 . 5 and 1 ( Fig . 6A , S4A Fig . ) . This data suggests a direct effect of PTX3 in enhancing RRV replication . To support that the presence of PTX3 enhanced viral titres , supernatants from vector- and PTX3-overexpressing HEK 293T cells were harvested at 20 h post transfection and incubated with untransfected HEK 293T cells . In the presence of RRV , untransfected HEK 293T cells treated with supernatant from PTX3-overexpressing HEK 293T cells supported significantly increased virus production compared to cells treated with supernatants from vector-treated control cells ( Fig . 6B ) . These data confirmed that the presence of PTX3 is crucial for enhancing virus production . To confirm that the results of enhanced virus production was due to PTX3 enhancing RRV replication , HEK 293T cells transiently transfected with vector or hPTX3 plasmids were harvested at 20 hour post transfection ( hpt ) ( Fig . 7A ) and subjected to a second round of transfection with RRV T48 plasmid through electroporation . At 3 h and 6 h post RRV transfection , cells were harvested for flow cytometry analysis , which demonstrated a significant increase in virus antigen detected within PTX3- , RRV-transfected HEK 293T cells compared to vector- , RRV-transfected control ( Fig . 7B ) . No virus was detected in the supernatant of these RRV-transfected cells at 3 and 6 hpi ( Fig . 7C ) . To further characterize the effect of PTX3 during alphaviral infection , we examined the potential of PTX3 to directly interact with the virus and enhance viral entry . We quantified the viral load in PTX3-overexpressing HEK 293T cells at early time points following a one-hour virus adsorption step . Typically , alphavirus particles attach to and enter cells during the adsorption phase of infection ( 0 hpi ) , with the replication of alphavirus genome commencing 5 to 6 hpi [36] . Therefore , following an hour of virus adsorption , the detection of viral antigens present at 0 hpi is indicative of binding and entry , and 6 hpi is indicative of the synthesis of new virus particles . Detection of intracellular viral antigens in RRV-infected PTX3-overexpressing HEK 293T cells revealed a significant increase in the number of RRV antigen positive cells at 0 and 6 hpi compared to vector-transfected cells ( Fig . 6C ) , indicating that PTX3 facilitates viral entry . This result was further confirmed with qRT-PCR viral load analysis , which detected increased viral load within PTX3-expressing cells at 0 , 1 , 2 , 4 , 5 and 6 hpi , compared to vector control ( S4B Fig . ) . At 4 hpi , the first round of virus replication was observed when a sudden spike in viral load was detected ( S4B Fig . ) . Interestingly , in conjunction with increased viral entry in the RRV-infected PTX3-overexpressing cells , we also observed a significant increase in intracellular PTX3 expression , compared to the mocked-infected controls ( Fig . 6D , 6E ) . Furthermore , flow cytometry analysis showed up to 90% of RRV+ cells were PTX3+ , suggesting the co-localization of RRV with PTX3 during acute infection ( S5 Fig . ) . Similar results were obtained for CHIKV infection of PTX3-expressing HEK 293T cells . Enhanced viral titres were recovered from the supernatant of PTX3-expressing CHIKV-infected cells when compared to vector controls ( S6A Fig . ) . Further evaluation of CHIKV-infected cells at 0 and 6 hpi demonstrated significant increase in viral entry in PTX3-expressing cells in conjunction with increased intracellular PTX3 expression ( S6B , C Fig . ) . To demonstrate that the effect of PTX3on enhancing RRV entry and replication contributed to the increased level of virus detected in the in vivo studies , we performed RRV infection on primary fibroblasts isolated from tails of PTX3-/- and WT C57BL/6 mice . At 24 hpi , RRV infection of WT fibroblasts resulted in significant up-regulation of PTX3 mRNA expression compared to mock-infected WT fibroblasts ( Fig . 8A ) . Moreover , viral titres in supernatants from WT fibroblasts were significantly enhanced compared to fibroblasts from PTX3-/- mice ( Fig . 8B ) . To further demonstrate the importance of PTX3 in enhancing RRV replication , recombinant mouse PTX3 was pre-incubated with RRV prior to infection of PTX3-/- primary fibroblast cultures . Virus titres recovered from supernatants of PTX3-RRV complex-infected PTX3-/- fibroblasts at 24 hpi were significantly enhanced compared to RRV-infected PTX3-/- fibroblasts ( control ) ( Fig . 8C ) . Furthermore , the effects of PTX3 deficiency on viral entry into primary fibroblasts during the early stages of infection were examined . Consistent with our earlier findings , significantly lower viral load was detected in PTX3-/- primary fibroblasts compared to WT after RRV infection at both 0 and 6 hpi ( Fig . 8D ) . Similarly , RRV infection of WT fibroblasts led to increased PTX3 expression compared to mock-infected controls at 0 and 6 hpi ( Fig . 8E ) . Immunofluorescence staining of the WT fibroblasts also revealed more intense expression of PTX3 , particularly within the cytoplasm , after RRV infection at 0 and 6 hpi ( Fig . 8F ) . Collectively , these data demonstrate that PTX3 promotes viral entry and replication at the early stages of RRV infection ( 0 and 6 hpi ) within host cells . Previous studies have demonstrated that PTX3 binds to a range of microbes , including viruses . For cytomegalovirus [29] and influenza virus [30] , recognition by PTX3 was shown to neutralize virus infectivity . To test whether PTX3 can bind to RRV , a microtitre plate-binding assay was performed . Microtitre wells coated with RRV were incubated with increasing concentrations of recombinant mouse PTX3 ( rmPTX3 ) and RRV-PTX3 binding was determined . As seen in Fig . 9A , PTX3 bound to RRV in a dose-dependent manner . Similarly , a microtitre plate binding assay performed on CHIKV also demonstrated that PTX3 bound to CHIKV dose-dependently ( S6D Fig . ) . Next , we examined whether PTX3 colocalizes with RRV during infection . During RRV infection of PTX3-overexpressing HEK 293T cells , RRV colocalized with PTX3 in the cytoplasm at 24 hpi ( Fig . 9B ) . Similarly , RRV infection of HeLa cells , which are highly permissive to RRV infection and express endogenous PTX3 ( S7A Fig . ) , demonstrated clear evidence of PTX3 colocalization with RRV in the cytoplasm during infection ( S7B Fig . ) . These data show that during acute RRV infection , PTX3 forms a complex with RRV and colocalizes in the cytoplasm of the host cells , which may facilitate viral entry and replication processes . To confirm that the enhanced infectivity observed during acute RRV infection is specific to PTX3 and not to other acute phase immune proteins , a separate experiment was performed using another acute phase protein—MBL . As previously reported , serum MBL expression was significantly elevated in patients suffering from acute RRVD when compared to healthy controls ( Fig . 10A ) [19] . In the acute RRVD mouse model , elevated serum MBL-C was seen at both 2 and 15 dpi ( Fig . 10B ) . Using a microtitre binding assay , a clear dose-dependent binding interaction between RRV and MBL-C was observed ( Fig . 10C ) . Next , we infected C2C12 cells ( Fig . 10D ) with either complexed PTX3-RRV or MBL-RRV in order to identify the specificity of acute phase immune proteins in enhancing RRV infectivity . Enhanced infectivity was observed in cells infected with PTX3-RRV complex at 6 , 12 and 24 hpi; however , no significant difference in infectivity was observed between RRV- or MBL-C-RRV complex-infected cells ( Fig . 10E ) . PTX3 consists of a conserved pentraxin C-terminal domain and a unique N-terminal domain . To determine the functional domain that is crucial for its functionality , we first examined the binding efficiency of recombinant human PTX3 ( rhPTX3 ) N- and C-terminal fragments ( Fig . 11A ) to RRV . Full-length rhPTX3 bound to RRV in a dose-dependent manner ( Fig . 11B ) and the majority of binding activity could be mapped to the N-terminal domain . Removal of the N-terminal domain led to a significant reduction in RRV binding ( Fig . 11C ) . We next compared N- and C-terminal domains of rhPTX3 for their ability to facilitate RRV entry and replication . Briefly , RRV was pre-incubated with full-length rhPTX3 , N-terminal-rhPTX3 , or C-terminal-rhPTX3 and these mixtures were then added to HEK 293T cells . Examination of viral entry at 0 and 6 hpi revealed that N-terminal-rhPTX3 was approximately 30% less efficient in its ability to facilitate RRV entry , compared to full-length-rhPTX3 . In contrast , removal of the N-terminal led to a complete ablation of PTX3-enhanced infection ( Fig . 11D ) . Despite retaining approximately 70% of its ability to facilitate viral entry , infection of cells with RRV-N-terminal-rhPTX3 complex led to a reduced ability to enhance viral replication , compared to full-length rhPTX3 . However , higher viral titre was still recovered from cells infected with RRV-N-terminal-rhPTX3 complex when compared to control infected with only RRV . No difference in viral titre was observed in cells infected with RRV-C-terminal-rhPTX3 complex ( Fig . 11E ) . Taken together , these data indicate that the N-terminal domain of PTX3 is responsible for the binding interaction with RRV and its functionality in facilitating viral entry .
Robust innate immune responses serve as the first line of host defense against alphavirus invasion . However , dysregulation of innate responses can also promote pathogenicity and disease . Consistent with this , we have previously identified overt expression of pro-inflammatory cytokines [37 , 38] and complement components [18] as pathogenic events in alphaviral diseases . In the current study we sought to determine the role of PTX3 , an acute phase protein associated with activation of the complement cascade [39] , in the pathogenesis of alphaviral disease . During the acute phase of alphaviral infection , PTX3 was highly induced in serum and PBMCs of RRVD and CHIKF patients , respectively . Notably , the magnitude of PTX3 induction in CHIKF patients was dependent on viral load and disease severity . Similar observations have been reported for the short pentraxin C-reactive protein ( CRP ) , which is a common laboratory marker for diagnosis of alphaviral infection [40 , 41] . Previously , Chow and colleagues reported that elevated expression of CRP was associated in CHIKF patients with high viral load and severe disease [15] . In addition to elevated PTX3 expression in alphavirus-infected patients , we also report abundant expression of PTX3 in serum and spleen of RRV-infected mice at the early stage of infection . During peak disease , PTX3 expression was also observed within the cellular infiltrates and further characterization identified inflammatory monocytes and neutrophils as the cellular sources of PTX3 during acute RRV infection . These findings indicate PTX3 is induced in response to alphaviral infections in humans and in mice . Elevated serum PTX3 expression has been observed in patients suffering from several arthritic conditions , including rheumatoid arthritis ( 2 . 08 ± 0 . 99 ng/ml ) , psoriatic arthritis ( 1 . 79 ± 0 . 80 ng/ml ) , polymyalgia rheumatic ( 2 . 08 ± 0 . 95 ng/ml ) , ankylosing spondylitis ( 2 . 48 ± 1 . 07 ng/ml ) as well as other diseases such as giant cell arteritis ( 1 . 98 ± 1 . 05 ng/ml ) and systemic lupus erythematosus ( 1 . 03 ± 0 . 84 ng/ml ) [42] . Herein , the strong induction of PTX3 in RRVD ( serum PTX3: 36 . 79 ± 8 . 443 ng/ml ) and CHIKF patients suggests that PTX3 may also be included as a laboratory marker of acute alphaviral infection . Dual roles of PTX3 have been reported in several pathogen-induced inflammatory diseases . Overexpression of PTX3 has protective effector function during bacterial infection with Aspergillus fumigatus [21 , 43] , Pseudomonas aeruginosa [44] and uropathogenic Escherichia coli [45] , as well as viral infections such as murine cytomegalovirus [29] and influenza virus [30] . Nevertheless , PTX3 expression has also been associated with exacerbated inflammatory responses and disease outcomes in intestinal ischemia-reperfusion injury [46] and pulmonary infection with Klebsiella pneumonia [47] . As PTX3 expression was associated with disease severity during acute alphaviral infections , we utilized an established RRVD mouse model [33] to examine the role of PTX3 during alphavirus infection . Deficiency of PTX3 was associated with delayed disease onset . While PTX3-/- mice displayed similar clinical manifestations at peak of disease , these mice recovered more rapidly than WT animals . It has previously been reported that pro-inflammatory cytokines , including IFN-Ɣ , TNF-α and IL-6 , and massive cellular infiltration contribute to inflammatory disease during alphaviral infections [37] . Indeed , delayed IFN-Ɣ , TNF-α and IL-6 responses were observed in quadricep muscles of PTX3-/- mice during the peak of RRVD . In addition , PTX3-/- mice showed diminished infiltration of inflammatory monocytes to the quadricep muscles during peak disease . Indeed , PTX3 has been shown to regulate leukocyte recruitment through interaction with P-selectin , leading to attenuation of cellular recruitment [32] . Using a peritoneal exudate model , we demonstrated increased recruitment of neutrophils and inflammatory monocytes in PTX3-/- mice during early stages of infection . This observation may be associated with early upregulation of CCL2 and MIF , which are crucial for the recruitment of RRV-induced cellular infiltration [17 , 48] during early infection . PTX3 has been shown to bind apoptotic cells promoting deposition of complement components C3 and C1q [49] . Previously , it has been reported that C3 deposition during RRV infection contributes to the destruction of skeletal muscle tissues [18] . Hence , it is likely that the absence of PTX3 in our current study ameliorates complement-induced damage of muscle tissues in RRV-infected mice . Furthermore , we observed higher induction of iNOS in quadricep muscles of PTX3-/- mice at peak RRVD . iNOS expression was recently shown to be pivotal in mediating skeletal muscle regeneration after acute damage [50] . These observations suggest PTX3 plays an immunomodulatory role during alphaviral infection . Moreover , the diminished infiltration of inflammatory monocytes and higher expression of iNOS during peak RRVD may contribute to rapid recovery from disease in the PTX3-/- mice . Collectively , these data identify PTX3 as a pathogenic factor that shapes the progression of alphaviral disease through modulation of RRV-induced immune responses . PTX3 is a pattern recognition molecule that interacts with viruses such as murine cytomegalovirus [29] and influenza virus [30] , through which it can act to inhibit infection of target cells . In our study , in vitro and in vivo approaches were used to demonstrate that PTX3 promotes RRV infection and replication in host cells . Alphaviruses gain entry into host cells through receptor-mediated endocytosis , although the exact cell surface receptors involved remain poorly defined [51] . Herein , we demonstrate that both RRV and CHIKV can bind to PTX3 . RRV and CHIKV infection of PTX3-expressing HEK 293T cells led to enhanced viral entry and replication . In addition , treatment of PTX3-/- primary fibroblasts with rPTX3 also resulted in enhanced viral replication during early RRV infection , likely due to the formation of PTX3-RRV complex which enhances early viral entry events and replication . These data suggest that the extracellular interaction between PTX3 and RRV was involved in facilitating viral entry into host cells . The aggregates formed between RRV and PTX3 may promote more efficient multivalent binding to cell surface receptor/s for RRV , thereby promoting enhanced receptor-mediated endocytosis and viral entry . Alternatively , PTX3 may opsonize RRV and promote its uptake via putative ( at this stage unknown ) cell surface receptors for PTX3 . In addition to demonstrating the potential of PTX3 enhancing RRV entry into cells , we also report that the distribution of intracellular PTX3 was altered during RRV infection . Intracellular PTX3 migrates from perinuclear space to cytoplasm during infection and PTX3 co-localized with RRV in the cytoplasmic space suggests the possibility of intracellular associations between PTX3 and RRV . These interactions may further promote productive viral infection , perhaps by enhancing genomic replication . Indeed , we demonstrated that cells co-transfected with PTX3 and RRV , and harvested prior to the release of new virions had elevated levels of intracellular virus antigen . This result further supports the hypothesis that intracellular associations of PTX3 and RRV may promote viral replication processes . Moreover , the presence of PTX3 was crucial for enhanced viral replication during RRV infection of WT mice and PTX3-overexpressing HEK 293T cells . Together , this study shows that PTX3-RRV interaction gives rise to pathogenic effect , enhancing viral entry and replication , in contrast to previous studies using other viruses such as murine cytomegalovirus [29] and influenza virus [30] , where PTX3 binding was associated with virus neutralization , thereby contributing to a protective host response . PTX3 is a structurally complex multimeric protein , comprising a highly conserved C-terminal domain shared across all members of the pentraxin family and a unique N-terminal domain whose structure is poorly characterized . We showed that the N-terminal domain is crucial for PTX3 binding to RRV and PTX3-mediated enhancement of RRV infection . However , removal of the C-terminal domain did affect the ability of the N-terminal domain of PTX3 to modulate viral replication , resulting in only partial enhancement of viral replication compared to full-length PTX3 . Previous studies have reported the importance of an intact quaternary structure in order for PTX3 to retain its binding and biological efficacies [52] . Therefore , full-length PTX3 with intact quaternary structure would be necessary to retain its biological role of enhancing RRV replication . Taken together , the data presented in this study provides the first evidence of a role for PTX3 in enhancing RRV uptake and replication during early alphaviral infection . PTX3 has previously been associated with protective functions against a number of viruses , including influenza virus [30] , human/murine cytomegalovirus [7] and coronavirus murine hepatitis virus [53] , in contrast to the pathogenic role identified in the current study . Our findings demonstrate a previously undescribed pivotal role of PTX3 in shaping alphaviral disease progression through immunomodulation and facilitating viral infection and replication processes during the acute phase of infection . In conclusion , our findings provide new insight into the role of PTX3 in acute alphaviral infection . The newly identified role of PTX3 in enhancing RRV infection and replication also sheds light on the poorly defined route of alphavirus entry into host cells . Given the diverse functional roles of PTX3 as well as its ability to bind to a variety of immune factors , further study is required to define the exact PTX3-triggered immune pathways induced in alphaviral-induced arthritic diseases . Identification of such pathways will be an important step towards the future development of therapeutic interventions .
Animal experiments were approved by the Animal Ethics Committee of Griffith University ( BDD/01/11/AEC ) . All procedures involving animals conformed to the National Health and Medical Research Council Australian code of practice for the care and use of animals for scientific purposes 8th edition 2013 . CHIKV human PBMC samples were collected from 20 patients that were admitted to the Communicable Disease Centre at Tan Tock Seng Hospital during the 2008 Singapore CHIKF outbreak . All patients were diagnosed with CHIKF and blood were collected at the acute phase ( median of 4 days after illness onset ) of infection [54] , with written informed consent obtained from all participants . The study was approved by the National Healthcare Group’s domain-specific ethics review board ( DSRB Reference No . B/08/026 ) . All RRV human serum samples had been submitted to the Centre for Infectious Diseases and Microbiology Laboratory Services ( CIDMLS ) , Westmead Hospital for diagnostic testing and laboratory investigation of RRV with written and oral informed patient consent . Serum from healthy individuals was provided by Australian Red Cross with written and oral informed consent , approved by Griffith University Human Research Ethics Committee ( BDD/01/12/HREC ) . No new human samples were collected as part of this study . Serum samples were de-identified before being used in the research project . PBMC specimens of 20 patients were classified into viral load ( high viral load , HVL; n = 10 and low viral load , LVL; n = 10 ) and disease severity ( severe illness; n = 10 and mild illness; n = 10 ) groups , as described previously [15] . Briefly , the HVL and LVL groups had mean viral loads of 1 . 31 × 108 PFU/ml and 1 . 95 × 104 PFU/ml respectively , while severe illness were defined as having a temperature of higher than 38 . 5°C , pulse rate more than 100 beats/min or platelet count less than 100 × 109 cells/L . Serum specimens were collected from 21 acute cases of RRV-induced polyarthritis patients in Australia . PBMCs and serum specimens isolated from 10 healthy volunteers were used as controls . All specimens were stored at -80°C until use . Stocks of the WT T48 strain of RRV were generated from the full-length T48 cDNA clone , kindly provided by Richard Kuhn , Purdue University , West Lafayette , IN . The CHIKV variant expressing mCherry ( CHIKV-mCherry ) was constructed using a full-length infectious cDNA clone of the La Reunion CHIKV isolate LR2006-OPY1 as described previously [55] . HEK 293T , HeLa and C2C12 cells were cultured in DMEM supplemented with 10% FBS . Primary fibroblasts were isolated from tails of WT and PTX3-/- mice using a previously described protocol [56] and cultured in DMEM supplemented with 20% FCS . Transient transfection of PTX3 plasmids [57] was performed using Lipofectamine 2000 ( Invitrogen ) following manufacturer’s instructions . Electroporation of RRV T48 infectious plasmid clone [33] was performed using Eppendorf Eporator . Recombinant N-terminal and C-terminal PTX3 proteins were purified as described in [58] . Recombinant mouse and human PTX3 , and mouse MBL-C were purchased from R&D . HEK 293T cells and primary tail fibroblasts were plated at a density of 1 . 0 × 105 per well on 24-well plates overnight , prior to infection with RRV or CHIKV ( MOI 1 ) for 1 h at 37°C in humidified CO2 incubator . Virus overlay was removed and 1 ml of pre-warmed growth medium was added to the monolayer of cells , marking the 0 hour post infection ( hpi ) . Cells were incubated at 37°C in humidified CO2 incubator and were harvested accordingly . All titrations were performed by plaque assay on Vero cells as described previously [59] . Microtiter plates ( Sarstedt ) were coated overnight at 4°C with 0 . 1M carbonate-bicarbonate coating buffer alone or containing either 104 PFU RRV or CHIKV ( UV-inactivated for 30 min ) . Non-specific binding sites were blocked by 5% BSA in PBS for 1 h at room temperature . Recombinant PTX3 or MBL-C binding to virus was performed by incubating recombinant proteins on virus-coated microtitre plate for 2 h at 37°C . Biotin-conjugated anti-PTX3 or anti-MBL-C detection antibody ( R&D ) was added and incubated at room temperature for 2 h . The optical density at 450 nm was read using the streptavidin conjugated to horseradish-peroxidase ( HRP ) substrate ( R&D ) . Total RNA extraction was performed using TRIzol reagent ( Life Technologies ) following manufacturer’s instructions . Quantification of total RNA was measured by NanoDrop 1000 spectrophotometer ( Thermo Scientific ) . Extracted total RNA ( 10 ng/μL ) was reverse-transcribed using an oligo ( dT ) primer and M-MLV reverse transcriptase ( Sigma Aldrich ) according to the manufacturer’s instructions . qRT-PCR was performed using SsoAdvanced Universal SYBR Green Supermix ( BIO-RAD ) in 12 . 5 μl of reaction volume . Reactions were performed using QuantiTect Primer Assay kits ( Qiagen ) and BIO-RAD CFX96 Touch Real-Time PCR Detection System on 96-well plates . Cycler conditions were as follows: ( i ) PCR initial activation step: 95°C for 15 min , 1 cycle and ( ii ) 3-step cycling: 94°C for 15 sec , follow by 55°C for 30 sec and 72°C for 30 sec , 40 cycles . Dissociation curves for each gene were acquired using CFX Manager software to determine specificity of amplified products . The fold change relative to healthy donors/mock samples for each gene was calculated with the ΔΔCt method using Microsoft Excel 2010 . Briefly , ΔΔCt = ΔCt ( patient/infected ) –ΔCt ( healthy donor/mock ) with ΔCt = Ct ( gene-of-interest ) —Ct ( housekeeping gene-GAPDH/HPRT ) . The fold change for each gene is calculated as 2-ΔΔCt . Standard curve was generated using serial dilutions of RRV T48 infectious plasmid DNA as described previously [33] . Quantification of viral load was performed using SsoAdvanced Universal Probes Supermix ( BIO-RAD ) in 12 . 5 μl reaction volume to detect nsP3 region RNA , using specific probe ( 5-ATTAAGAGTGTAGCCATCC-3’ ) and primers ( forward: 5’-CCGTGGCGGGTATTATCAAT-3’; reverse: 5’-AACACTCCCGTCGACAACAGA-3’ ) [60] . Reactions were performed using BIO-RAD CFX96 Touch Real-Time PCR Detection System on 96-well plates . Cycler conditions were as follows: ( i ) PCR initial activation step: 95°C for 3 min , 1 cycle and ( ii ) 2-step cycling: 95°C for 15 sec , followed by 60°C for 45 sec , 45 cycles . Standard curve was plotted and copy numbers of amplified products were interpolated from standard curve using Prism Graphpad software to determine viral load . Transfected HEK 293T cells were seeded on poly-L-lysine-coated coverslips for staining . Cells were fixed with 2% paraformaldehyde ( PFA ) , permeabilized in PBS containing 0 . 1% Triton X-100 , and blocked with 20% goat serum in PBS . Cells were incubated with rat monoclonal anti-PTX3 ( MNB4 , Abcam ) or mouse monoclonal anti-alphavirus ( 3581 , Santa Cruz ) primary antibody in PBS , followed by goat anti-rat AF488 ( Invitrogen ) or goat anti-mouse AF647 ( Invitrogen ) secondary antibody . Cells were washed , mounted , and examined with a confocal laser-scanning microscope ( Fluoview FV 1000 , Olympus ) at 60x magnification . Images were collected and processed using FV1000-ASW software . ELISAs were performed using DuoSet ELISA Development kit ( R&D systems ) following manufacturer’s instructions . To analyze PTX3 intracellular expression , transfected HEK 293T cells were fixed with 2% PFA and permeabilized with 0 . 1% Saponin ( Sigma Aldrich ) in PBS . Indirect intracellular staining was performed with rat anti-PTX3 ( MNB4 , Abcam ) primary antibody , followed by AF488-conjugated anti-rat ( Life Technologies ) secondary antibody . To identify the various cell populations present in splenocytes , peritoneal lavage and quadriceps harvested from mice , cells were first incubated with anti-mouse CD16 / CD32 ( FC block , BD Pharmingen ) and stained with the following antibodies: APC-conjugated anti-mouse GR1 , PE-conjugated anti-mouse F4/80 , FITC-conjugated anti-mouse CD11b , APC-conjugated anti-mouse Ly6c , APC-conjugated anti-mouse CD3 , FITC-conjugated anti-mouse CD19 , PE-conjugated anti-mouse CD45 , or PE-Cy7-conjugated anti-mouse NK1 . 1 ( BD Pharmingen ) . For detection of alphavirus antigens , indirect intracellular staining was performed using mouse monoclonal anti-alphavirus ( 3581 , Santa Cruz ) primary antibody , followed by AF488-conjugated anti-mouse ( Life Technologies ) secondary antibody . Data acquisition was performed using CyanADP ( Beckman Coulter ) , and analysis was done by Kaluza Flow Analysis Software ( Beckman Coulter ) . 6–8 week-old C57BL/6 male and female mice , of equal distribution , were inoculated intraperitoneally with 105 PFU RRV in 500 μl of PBS , to study the early effect of PTX3 deficiency on recruitment of neutrophils and inflammatory monocytes . Peritoneal lavage was harvested at 6 hpi with 5 ml of ice-cold PBS . For the acute RRV mouse model , 21-day-old C57BL/6 male and female mice , of equal distribution , were inoculated subcutaneously in the thorax below the right forelimb with 104 PFU RRV in 50 μl . Mock-infected mice were inoculated with PBS diluent alone . Mice were weighed and scored for disease signs every 24 h . Mice were assessed based on animal strength and hind-leg paralysis , as outlined previously [33] , using the following scale: 0 , no disease signs; 1 , ruffled fur; 2 , very mild hindlimb weakness; 3 , mild hindlimb weakness; 4 , moderate hindlimb weakness; 5 , severe hindlimb weakness , 6 , complete loss of hindlimb function; and 7 , moribund . Mice were euthanized , quadriceps and ankle joints were removed and homogenized using QIAGEN Tissuelyser II then centrifuged at 12 , 000 × g , 5 min , 4°C . Blood was collected via cardiac puncture . Serum was isolated by centrifugation at 12 , 000 × g , 5 min , 4°C . For analysis of infiltrating inflammatory cells by flow cytometry , mice were sacrificed and perfused with PBS at 7 dpi . Quadricep muscles were harvested , weighed , minced , and digested with DMEM containing 20% FBS , 1 mg/ml of collagenase IV ( Roche ) and 1 mg/ml of DNase I ( Roche ) , for 1 h at 37°C . Cells were strained through a 40 μm strainer ( BD Biosciences ) and washed with DMEM containing 20% FBS and viable cells were counted by trypan blue exclusion . For histology , quadricep muscles harvested were fixed in 4% PFA , followed by paraffin-embedding . Five-micrometer sections were prepared . IHC was performed on dewaxed , rehydrated , 5 μm paraffin-embedded tissue sections . Sections were incubated with 20% goat serum ( Gibco ) in 5% BSA/PBS for 20 min . Primary antibody staining was performed using rat anti-mouse PTX3 ( MNB1 , Abcam ) in PBS , incubated overnight , at 4°C , in humidified chamber . Tissue sections were washed in PBS for three times at 5 min intervals . Secondary antibody staining was performed using HRP-conjugated anti-rat IgG2b ( Serotec ) incubated for 30 min , room temperature , in a humidified chamber . Colour was developed with 3 , 3’-diaminobenzidine ( DAB ) Peroxidase Substrate Kit ( Vector Laboratories ) , according to manufacturer’s instructions and counter-stained with hematoxylin ( Vector Laboratories ) . All statistical analyses were performed using Prism 5 . 01 ( Graph-Pad Software ) . Analysis of PTX3 expression profiles in comparison between healthy and RRVD or CHIKF patients , HVL and LVL CHIKF patients’ groups , and severe and mild illness CHIKF patients’ groups was done using Mann-Whitney U test . Comparisons of PTX3 expression among different time points post infection in WT mice , PTX3 expression in mock- and RRV-infected mouse splenocytes , clinical scoring of between PTX3-/- and WT mice , viral replication and viral entry among RRV-infected HEK 293T cells and fibroblasts , were performed using two-way ANOVA with Bonferroni post-test . Comparisons of viral replication and viral entry among RRV- , FL-PTX3 , N-term-PTX3 and C-term-PTX3-RRV infected groups were analyzed using one-way ANOVA with Bonferroni post-test . Analyses of all other experimental groups were performed using student unpaired t-test . P values less than 0 . 05 were considered statistically significant . | Chikungunya virus ( CHIKV ) and Ross River virus ( RRV ) are arthropod-borne viruses associated with massive epidemics affecting millions of people worldwide , causing widespread distribution of alphaviral-induced arthritis . The rising prevalence of alphavirus infections and , critically , the lack of therapeutic treatments warrant urgent attention to elucidate the innate immune responses elicited , which serves as the first line of host defense against alphavirus . Ironically , robust innate immune responses have been associated with both protective and pathogenic outcomes . Here , we identified PTX3 as an innate protein involved in acute CHIKV and RRV infection in humans . Using an established acute RRV disease mouse model , we revealed a pathogenic immunoregulatory role of PTX3 which led to enhanced viral infectivity and prolonged disease . Transient overexpression of PTX3 in a human epithelial cell line identified the importance of PTX3 N-terminus in binding RRV and modulating viral entry and replication . Collectively , our study identified a previously undescribed pathogenic role of PTX3 during virus infection and shed insights into the sophisticated innate immune responses launched against virus invasion . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [] | 2015 | Role of Pentraxin 3 in Shaping Arthritogenic Alphaviral Disease: From Enhanced Viral Replication to Immunomodulation |
Detection of viral nucleic acids plays a critical role in the induction of intracellular host immune defences . However , the temporal recruitment of immune regulators to infecting viral genomes remains poorly defined due to the technical difficulties associated with low genome copy-number detection . Here we utilize 5-Ethynyl-2’-deoxyuridine ( EdU ) labelling of herpes simplex virus 1 ( HSV-1 ) DNA in combination with click chemistry to examine the sequential recruitment of host immune regulators to infecting viral genomes under low multiplicity of infection conditions . Following viral genome entry into the nucleus , PML-nuclear bodies ( PML-NBs ) rapidly entrapped viral DNA ( vDNA ) leading to a block in viral replication in the absence of the viral PML-NB antagonist ICP0 . This pre-existing intrinsic host defence to infection occurred independently of the vDNA pathogen sensor IFI16 ( Interferon Gamma Inducible Protein 16 ) and the induction of interferon stimulated gene ( ISG ) expression , demonstrating that vDNA entry into the nucleus alone is not sufficient to induce a robust innate immune response . Saturation of this pre-existing intrinsic host defence during HSV-1 ICP0-null mutant infection led to the stable recruitment of PML and IFI16 into vDNA complexes associated with ICP4 , and led to the induction of ISG expression . This induced innate immune response occurred in a PML- , IFI16- , and Janus-Associated Kinase ( JAK ) -dependent manner and was restricted by phosphonoacetic acid , demonstrating that vDNA polymerase activity is required for the robust induction of ISG expression during HSV-1 infection . Our data identifies dual roles for PML in the sequential regulation of intrinsic and innate immunity to HSV-1 infection that are dependent on viral genome delivery to the nucleus and the onset of vDNA replication , respectively . These intracellular host defences are counteracted by ICP0 , which targets PML for degradation from the outset of nuclear infection to promote vDNA release from PML-NBs and the onset of HSV-1 lytic replication .
Intrinsic , innate , and adaptive arms of host immunity cooperatively supress the replication and spread of invading viral pathogens . Conferred by constitutively expressed host-cell restriction factors , intrinsic immunity is the first line of intracellular defence against infection ( reviewed in [1–3] ) . In contrast , innate immune defences are upregulated following the activation of Pattern Recognition Receptors ( PRRs ) that detect Pathogen-Associated Molecular Patterns ( PAMPs ) unique to microbial pathogens , including foreign viral nucleic acids . PRR activation induces downstream signalling events that culminate in the expression of antiviral host genes , principally cytokines ( including interferons ) and interferon stimulated gene ( ISG ) products ( reviewed in [4–6] ) . This induced innate immune response confers a broadly refractory antiviral state that limits virus propagation and stimulates adaptive immune responses . Consequently , many viruses have evolved counter measures to antagonize intrinsic and innate immune defences to promote their efficient propagation and transmission to new hosts . A key event in the regulation of intracellular immune defences during herpesvirus infection is the rapid recruitment of constitutively expressed host factors to sites in close proximity to infecting viral genomes upon nuclear entry ( reviewed in [1 , 7] ) . These factors include core constituent proteins of Promyelocytic Leukaemia Nuclear Bodies ( PML-NBs; notably PML , Sp100 , Daxx and ATRX; [8–10] ) , innate immune regulators ( IFI16 , cGAS , and STING; [11–14] ) , DNA Damage Response ( DDR ) proteins ( γH2AX , Mdc1 , 53BP1 , and BRCA1; [15] ) , and core component proteins of the SUMOylation pathway ( SUMO-1 , SUMO-2/3 , PIAS1 , and PIAS4 [16–19] ) . The recruitment of these host factors represents the earliest detectable nuclear responses to infection , and have been linked to the repression of viral gene expression and PRR activation in the regulation of intrinsic and innate immune defences , respectively . The importance of PML-NB constituent proteins and IFI16 in the regulation of intracellular immunity is highlighted by the fact that many viruses have evolved strategies to antagonise these key immune regulators ( reviewed in [1 , 4 , 6 , 20 , 21] ) . One of the first viral proteins to be expressed during Herpes Simplex Virus 1 ( HSV-1 ) infection is ICP0 , a viral RING-finger ubiquitin ligase that promotes the degradation and dispersal of host factors , including PML and IFI16 [11 , 22–31] , away from infecting viral genomes ( reviewed in [7 , 32] ) . This activity inhibits viral genome silencing and the induction of ISG expression , thereby promoting the efficient onset of HSV-1 gene expression and replication . Viral mutants that do not express ICP0 , or carry mutations that impair its ubiquitin ligase activity , are highly susceptible to host-cell restriction at low multiplicities of infection ( MOI ) and are hypersensitive to interferon ( IFN ) treatment [33–38] . The use of such mutants has been critical in defining many aspects relating to the regulation of intrinsic and innate immunity during herpesvirus infection . Studies analysing the recruitment of host immune regulators to infecting viral genomes have typically relied on high MOI conditions due to the technical challenges associated with low genome copy-number detection . A defining hallmark of intrinsic immunity , however , is that this host defence is readily saturated under high MOI conditions due to limiting levels of pre-existing host factors . Thus , much of the mechanistic detail of immune regulator recruitment to infecting HSV-1 genomes has been established using viral mutants at input genome levels that saturate intrinsic host defences . Consequently , the temporal recruitment of intrinsic and innate immune regulators to infecting viral genomes remains poorly defined , specifically under low MOI conditions pertinent to wild-type ( WT ) herpesvirus infections observed in a clinical setting . Here we use fluorophore conjugation by click chemistry to investigate the temporal recruitment of intrinsic and innate immune regulators to 5-Ethynyl-2’-deoxyuridine ( EdU ) labelled HSV-1 genomes under physiologically low MOI conditions ( 0 . 1 to 3 PFU/cell ) . HSV-1 genomes were readily detected in the nucleus within 30 minutes of infection ( post-addition of virus ) and to be stably entrapped within PML-NBs in restrictive cell types prior to PML-NB disruption and genome release by ICP0 . PML-NB entrapment of vDNA occurred independently of the PRR sensor IFI16 and ISG expression , demonstrating that this intrinsic host response does not directly contribute to the induction of innate immunity . Saturation of this host defence during HSV-1 ICP0-null mutant infection led to the stable recruitment of PML and IFI16 into vDNA complexes associated with ICP4 , and the subsequent induction of ISGs . This induced innate immune response occurred in a PML- , IFI16- , and Janus associated kinase ( JAK ) dependent manner , which could be suppressed by the vDNA polymerase inhibitor phosphonoacetic acid ( PAA ) . These data demonstrate that vDNA entry into the nucleus alone under low MOI conditions is not sufficient to stimulate a robust innate immune response to HSV-1 nuclear infection , which only occurs after the onset of vDNA replication . We show that intrinsic and innate arms of intracellular host immunity act sequentially , as inhibition of innate immune signalling could not relieve the intrinsic cellular restriction of an HSV-1 ICP0-null mutant , but instead led to significantly enhanced virus yields under infection conditions that enabled the onset of vDNA replication . Collectively , our data demonstrate that intrinsic and innate arms of host immunity are temporally distinct immune events activated in response to vDNA nuclear entry and the onset of vDNA replication , respectively . Our data identifies distinct roles for PML in the sequential regulation of these intracellular immune defences to HSV-1 infection , findings that are likely to be highly pertinent in the cellular restriction of many nuclear replicating viral pathogens .
Microscopy studies have played pivotal roles in the identification of host factors and signalling pathways that contribute to the intracellular regulation of intrinsic and innate immunity during herpesvirus infection ( reviewed in [1 , 4 , 7 , 32 , 39] ) . However , the detection of viral genomes under low MOI conditions , which do not saturate intrinsic host defences , remains a significant technical challenge . To date , viral genome localization studies have relied on the indirect detection of vDNA through immunolabelling or fluorescent tagging of vDNA binding proteins , for example the viral immediate early ( IE ) transcription factor ICP4 or the early ( E ) single-stranded vDNA binding protein ICP8 [8–10 , 13 , 14 , 40] . The use of vDNA binding proteins limits temporal resolution of host factor recruitment to infecting viral genomes , as genome detection requires the successful expression of viral gene products that may compete with , or displace , host factors bound to vDNA . Consequently , this strategy is suboptimal for the examination of early intrinsic host immune defences that influence the cellular restriction of viral gene expression . While direct vDNA labelling strategies have been employed , most notably fluorescent in situ hybridization ( FISH; [8 , 10] ) , such approaches require harsh denaturing conditions which impair host antigen detection ( [41] , personal communication J . Brown ) , and have not been widely adopted . Recent advances in direct bio-orthogonal nucleic acid labelling , using Ethynyl-tagged deoxynucleotides in combination with fluorescent labelling by click chemistry techniques , have enabled the direct visualization of vDNA during both Adeno- and Herpesvirus infection ( [42–46] ) . We sought to apply this technique by purifying either EdU or EdC labelled HSV-1 virions ( HSV-1EdU or HSV-1EdC , respectively ) and infecting cells at low MOI ( ≤ 3 PFU/cell ) to examine the temporal recruitment of intrinsic and innate immune regulators to input viral genomes following nuclear entry . Successful labelling of vDNA and the purification of high titre WT or ICP0-null mutant HSV-1EdU or HSV-1EdC stocks was achieved by infecting Retinal Pigmented Epithelial ( RPE ) cells ( see Materials and methods; S1A–S1C Fig ) . Notably , many laboratory cell lines were unable to support efficient viral propagation at nucleotide concentrations exceeding 1 μM in an Ethynyl-tag dependent manner ( S1 Table , S1D–S1F Fig ) . As RPE cells were restrictive to HSV-1 ICP0-null mutant replication ( see below ) and sensitive to Ethynyl-tagged deoxynucleotide labelling in the absence of ICP0 ( S1G–S1I Fig ) , we selected the lowest dose of 0 . 5 μM EdU or EdC for genome labelling to enable comparative recruitment studies to input viral genomes in the presence or absence of ICP0 . In vitro genome release assays demonstrated that ≥ 60% of virions contained EdU or EdC labelled viral genomes detectable by click chemistry following partial denaturation of the HSV-1 capsid by 2M guanidine hydrochloride ( GuHCl , Fig 1A–1C , S2 Fig; [47] ) . Particle to plaque forming unit ( PFU ) analysis of virus preparations grown in the presence of EdU demonstrated that HSV-1EdU labelled virions had a roughly equivalent ratio to that of unlabelled control virus preparations ( within 3-fold; S2 Table ) . These data demonstrate that EdU labelling of vDNA was not significantly detrimental to virion production or infectivity under these labelling conditions . A time course of infection of human foreskin fibroblast ( HFt ) cells with WT ( HSV-1EdU ) or ICP0-null ( ΔICP0EdU ) mutant HSV-1 demonstrated that vDNA could be readily detected within the nuclei of infected cells as early as 30 minutes post-infection ( mpi; post-addition of virus ) , with > 70% of nuclei containing at least 1 ( median average of 2 ) HSV-1EdU genome foci by 120 mpi ( Fig 1D , 1F and 1G ) . Signal detection was dependent on both HSV-1 infection and EdU vDNA labelling , demonstrating that fluorescent click signal ( s ) were specific to input EdU labelled vDNA ( Fig 1E ) , with the majority of genome signals ( ≥ 70% ) observed within the nucleus ( Fig 1H ) . Notably , qPCR analysis ( S2 Table ) revealed that the majority of particles ( > 50% ) had yet to release their genomes by 120 mpi ( post-addition of virus ) . As vDNA is undetectable within native capsids ( S2 Fig ) , these data suggest that the process of nuclear infection is still ongoing at 120 mpi . We note that under equivalent MOI conditions , ΔICP0EdU infected cells had a reduced number of vDNA positive nuclei at each time point ( Fig 1F–1H ) , a phenotype that likely reflects the efficiency of ICP0-null mutant EdU vDNA labelling in restrictive RPE cells ( S1G–S1I Fig ) . With the ability to detect input vDNA within the nuclei of infected cells as early as 30 mpi ( post-addition of virus ) , we next assessed the utility of this approach to investigate the recruitment of intrinsic immune factors to infecting WT HSV-1EdU genomes over a short time-course of infection ( 30 to 90 mpi; Fig 2 ) . Using a combination of click chemistry to detect vDNA and immuno-labelling to detect PML-NB intrinsic host factors , PML ( the main scaffolding protein of PML-NBs; [48] ) and Daxx ( a core constituent protein of PML-NBs; [48] ) were observed to stably colocalize with vDNA over the time course of infection ( 30–90 mpi; Fig 2A ) . High-resolution Z-series imaging revealed input vDNA to be encased in PML following nuclear infection ( Fig 2B ) . At 90 mpi , ICP0 could be observed to colocalize with PML-NBs prior to PML degradation and PML-NB disruption ( Fig 2C and 2D; [22 , 25–27] ) . ICP0 localization at multiple PML-NBs demonstrates that vDNA entrapment within any single PML-NB is not sufficient to target ICP0 to that specific body ( Fig 2C ) . Western blotting of infected cell lysates demonstrated that EdU labelling of vDNA was not detrimental to the initiation of IE gene expression ( ICP0 , ICP4 ) or the degradation of PML ( Fig 2D ) . Collectively , these data that demonstrate infecting WT HSV-1 genomes are rapidly encased by PML-NB intrinsic host factors from the outset of nuclear infection prior to the onset of lytic replication . Our data contrast with previous recruitment studies , which have reported PML-NB constituent proteins to localize to sites in close proximity to infecting viral genomes [8–10 , 40] . However , we note that these studies have typically relied on higher MOI conditions ( ≥ 10 PFU/cell; [10] ) , the use of vDNA binding proteins to enable genome detection by proxy , or time points post-infection where vDNA replication proteins are readily detectable . We conclude that PML-NB host factors rapidly entrap viral genomes shortly after nuclear entry prior to the robust onset of viral gene expression ( Fig 2D ) . Asynchronous plaque-edge recruitment studies have shown that PML-NB host factors are independently recruited to infecting viral genomes [49 , 50] in an IFI16-dependent manner [11 , 12 , 14] , where de novo PML-NB like foci are reformed [10] . We therefore assessed the composition of vDNA containing PML-NBs , as well as the localization of the PRR IFI16 , to infecting WT HSV-1EdU or HSV-1EdC genomes ( Fig 3 , S3 Fig ) . High colocalization frequencies ( weighted colocalization coefficients > 0 . 7 ) were observed for all PML-NB component proteins examined ( PML , Daxx , Sp100 , ATRX , and SUMO2/3 ) to infecting viral genomes irrespective of genome label , with equivalent paired colocalization frequencies observed for resident PML-NB proteins in mock-infected cells ( Fig 3A–3D and 3F , S3 Fig ) . These data demonstrate that PML-NBs that contained vDNA were indistinguishable in composition from other PML-NBs within the same infected cell or in mock-infected cells at 90 mpi . Surprisingly , the colocalization frequency between IFI16 and input viral genomes was below coincident threshold levels ( weighted colocalization coefficients < 0 . 2; solid line ) , demonstrating that IFI16 does not stably localize with viral genomes entrapped within PML-NBs at 90 mpi ( Fig 3E and 3F , S3 Fig ) . These data again contrast with published asynchronous plaque-edge recruitment studies that have used vDNA binding proteins for genome detection , which have shown IFI16 and PML to both localize to infecting HSV-1 ICP0-null mutant genomes [11 , 13 , 14] . As ICP0 has been reported to promote the degradation of IFI16 [11 , 28–31] , we examined the recruitment of IFI16 to ΔICP0EdU genomes to investigate the potential effect of ICP0 expression on IFI16 localization to vDNA . No stable localization of IFI16 could be observed to infecting ΔICP0EdU genomes ( S4 Fig ) , demonstrating that a lack of stable IFI16 recruitment to viral genomes was not due to low levels of ICP0 expression at 90 mpi ( Fig 2C ) . We note that IFI16 localization to viral genomes has been reported to be highly dynamic [12 , 14] , which could potentially be inhibited by PML-NB entrapment of vDNA . We therefore investigated the influence of MOI ( 1 , 10 , and 50 PFU/cell ) and time ( 15 or 30 mpi ) on the recruitment of IFI16 and PML to nuclear infecting HSV-1EdU genomes ( S5 Fig ) . While vDNA-IFI16 colocalization could be observed under very high MOI conditions ( 50 PFU/cell; S5A Fig ) , quantitation ( n ≥ 250 genomes ) revealed the frequency of these colocalization events was not significantly altered by MOI or time ( S5B–S5E Fig ) . In contrast , PML colocalization with vDNA was significantly reduced in a MOI dependent manner ( 1–50 PFU/cell ) , indicative of PML-NB saturation by viral genomes or disruption by ICP0 under these high MOI conditions . PML recruitment to vDNA also occurred in a time dependent manner , with a significant increase in colocalization frequency between 15 and 30 mpi ( MOI of 10 PFU/cell ) . As bio-orthogonal nucleic acid labelling is incompatible with live-cell kinetic studies , we conclude that IFI16 does not form a stable association with input vDNA following genome entry into the nucleus . To test if PML-NBs competitively exclude IFI16 from binding vDNA following nuclear entry , we investigated the recruitment of IFI16 and Daxx ( as a positive control; [49] ) to input HSV-1EdU and ΔICP0EdU genomes in cells depleted of PML ( Fig 4 , S6 Fig ) . HFt cells were stably transduced with lentiviral vectors expressing non-targeting control or PML-targeting short hairpin RNAs ( shCtrl and shPML , respectively; [49] ) . qRT-PCR and western blotting confirmed PML depletion without influencing Daxx or IFI16 expression ( Fig 4A and 4B ) . HSV-1EdU or ΔICP0EdU infection of shCtrl cells recapitulated observations made in parental HFt cells ( Fig 3 , S3 Fig , S4 Fig ) , demonstrating that lentiviral transduction , shRNA expression , or puromycin selection did not affect PML-NB entrapment of vDNA or alter IFI16 localization ( Fig 4C–4E ) . PML depletion did not increase the frequency of IFI16 colocalization with vDNA during either HSV-1EdU or ΔICP0EdU infection ( Fig 4D and 4E , S6 Fig ) , demonstrating that PML-NBs do not competitively exclude IFI16 from binding vDNA . In contrast , while Daxx colocalized with vDNA in a subset of PML depleted cells ( Fig 4C , S6A Fig ) , quantitation ( n ≥ 100 genomes ) revealed that the frequency of this colocalization was significantly reduced compared to control cells irrespective of ICP0 expression ( Fig 4E ) . These data contrast with asynchronous plaque-edge recruitment studies , where Daxx recruitment to infecting viral genomes occurs in a PML independent manner under high MOI conditions [49] . We conclude that under infection conditions that do not saturate or disrupt PML-NBs by 90 mpi ( MOI < 10 PFU/cell; S5 Fig ) , Daxx colocalization with vDNA is stabilized by PML at PML-NBs where Daxx is a resident protein ( Figs 2–4 , S3 Fig; [48] ) . Live cell microscopy studies and asynchronous plaque-edge recruitment assays have reported that IFI16 is required for PML and Daxx recruitment to infecting viral genomes [11 , 12 , 14] , although no direct evidence of IFI16 colocalization with vDNA or deposition within PML-NBs was reported to support this hypothesis . We therefore investigated if IFI16 played a role in PML-NB entrapment of vDNA ( Fig 5 ) . HFt cells were stably transduced with lentiviral vectors expressing non-targeting control or IFI16-targeting short hairpin RNAs ( shCtrl and shIFI16 , respectively; [11] ) . qRT-PCR and western blotting confirmed IFI16 depletion without influencing PML or Daxx expression ( Fig 5A and 5B ) . HSV-1EdU infection of shCtrl or shIFI16 cells demonstrated that both PML and Daxx strongly colocalized with vDNA independently of IFI16 ( Fig 5C–5E ) . We conclude that IFI16 does not play an essential role in the entrapment of vDNA within PML-NBs . As we failed to observe any significant recruitment of IFI16 to infecting HSV-1 genomes under a range of infection conditions , our data suggest that the stable recruitment of PML and IFI16 to infecting viral genomes occurs with temporally distinct kinetics . As asynchronous plaque-edge recruitment assays have played a key role in defining the recruitment of IFI16 to infecting HSV-1 genomes [11 , 13 , 14] , we conducted analogous assays to assess the temporal recruitment of PML and IFI16 to both vDNA and ICP4 , an IE vDNA binding protein commonly utilized as a proxy for vDNA in genome recruitment studies [9–11 , 14 , 40] . Viral DNA labelling was achieved by pulse labelling HSV-1 ICP0-null mutant infected cell monolayers at 24 hours post-infection ( hpi ) with 1 μM EdU for 6 h . Under these conditions , DNA replication compartments within the body of a developing plaque were clearly detected ( S7 Fig ) . Cells on the periphery of the plaque-edge were readily observed to contain EdU positive vDNA foci asymmetrically distributed around the nuclear rim prior to ICP4 detection ( Figs 6A , 6C top panels , S7 ) , indicative of input EdU labelled viral genomes that have yet to initiate a productive gene expression programme . The recruitment of PML to infecting viral genomes occurred independently of ICP4 expression , with many genome foci observed to localise in close proximity to PML foci ( Fig 6A and 6B ) . In contrast , IFI16 recruitment only occurred in cells that expressed ICP4 localized to vDNA at the nuclear rim ( ICP4 NR; Fig 6C and 6D , S7 Fig ) . These data support previous asynchronous recruitment studies that have used ICP4 as a proxy for genome detection [11 , 14] and demonstrate that PML and IFI16 are recruited to infecting viral genomes with temporally distinct kinetics , which in the case of IFI16 correlates with the expression and localization of viral gene products with vDNA ( Fig 6D ) . Importantly , these data suggest that vDNA entry into the nucleus alone may not be sufficient to stimulate the induction of an IFI16-dependent innate immune response , but instead require the expression of specific viral gene products or the initiation of vDNA replication . To test this hypothesis , we examined the induction of Mx1 , a well-characterized ISG product [51] , during HSV-1 ICP0-null mutant infection by confocal microscopy . HFt cells were mock treated , stimulated with IFN-β ( as a positive control ) , or infected with ΔICP0EdU at input levels which either restrict or permit the initiation of HSV-1 ICP0-null mutant replication and plaque formation at 24 hpi ( MOI 0 . 1 and 1 . 0 PFU/cell , respectively; Fig 6E ) . vDNA was readily detectible within the nuclei of infected cells under restrictive MOI conditions ( 0 . 1 PFU/cell ) with a frequency close its expected input genome ratio ( Fig 6F ) and copy number ( 1–2 genomes/infected cell; Fig 6G , S2 Table ) . Notably , the number of genomes per infected cell nuclei under permissive conditions ( MOI 1 PFU/cell ) was lower than expected based on our input qPCR analysis ( ~ 25 genomes/cell; Fig 6G , S2 Table ) . These data indicate that under MOI conditions that begin to saturate intrinsic host defences ( ~ 10–20 genome copies/nuclei ) , ΔICP0EdU genome detection is lost following the onset of vDNA replication by 24 hpi . As expected , IFN-β stimulation efficiently induced Mx1 expression 24 h post-treatment ( Fig 6H and 6I ) . In contrast , infection with ICP0-null mutant HSV-1 only stimulated Mx1 expression at genome input levels sufficient to stimulate the onset of viral replication and plaque formation ( MOI 1 . 0 PFU/cell; Fig 6E , 6H and 6I ) . High-resolution Z-series imaging revealed that viral genomes remained stably entrapped within PML-NBs under restrictive MOI conditions ( 0 . 1 PFU/cell ) at 24 hpi ( Fig 6J ) . These data demonstrate that under infection conditions that restrict the initiation of ICP0-null mutant HSV-1 replication , viral genome entry into the nucleus alone is not sufficient to stimulate the induction Mx1 ISG expression . As PML-NB entrapped HSV-1 ICP0-null mutant genomes failed to stimulate the induction of Mx1 expression , we next examined the kinetics of ISG induction during HSV-1 infection under MOI conditions that enabled the onset of viral replication ( MOI 1 PFU/cell; Fig 7 ) . As expected , HSV-1 ICP0-null mutant infection efficiently induced the transcription ( by 8–9 hpi ) and expression ( by 16 hpi ) of three independent ISG products ( Mx1 , ISG15 , and ISG54 ) , a host response that was significantly impaired during WT HSV-1 infection ( Fig 7A–7C ) . Importantly , the induction of ISGs only occurred under infection conditions that enabled the onset of ICP0-null mutant HSV-1 replication and plaque-formation ( ≥ 1 . 0 PFU/cell; Figs 6E and 7D ) . Consistent with our microscopy observations ( Fig 6H and 6I ) , these data demonstrate that saturation of intrinsic host defences is required for the robust induction of ISGs during HSV-1 ICP0-null mutant infection . As IFI16 binds to a range of DNA structures that may be produced during vDNA replication [52] , we next investigated the role of vDNA replication in the induction of ISGs . ISG transcript levels were monitored in the presence of the vDNA replication inhibitors PAA ( phosphonoacetic acid ) and ACG ( acycloguanosine ) , two well-characterized herpesvirus DNA replication inhibitors [53–57] . PAA efficiently inhibited the induction of both Mx1 and ISG15 transcript levels in a dose-dependent manner ( Fig 7E ) , while ACG treatment had only a modest inhibitory effect at concentrations sufficient to restrict HSV-1 plaque formation ( ≥ 50 μM; Fig 7F , S1 Table ) . Inhibition of ISG induction by PAA was virus-specific , as ISG transcript levels were readily induced by IFN-β stimulation in the presence of PAA ( Fig 7G ) . By way of contrast , JAK inhibition by Ruxolitinib ( Ruxo ) effectively blocked ISG induction following IFN-β stimulation ( Fig 7G; [58 , 59] ) , consistent with a key role for JAK in IFN-mediated innate immune signalling [60] . JAK inhibition also effectively blocked ISG induction during HSV-1 ICP0-null mutant infection ( Fig 7H ) . Importantly , this inhibition occurred in the presence 50 μM ACG ( Fig 7I ) , demonstrating that JAK activity is specifically required to induce ISG expression during the initiating cycle ( s ) of HSV-1 ICP0-null mutant vDNA replication by 9 hpi . Together with our microscopy observations ( Fig 6 ) , these data demonstrate that the onset of vDNA replication is required for the robust induction of ISG expression during HSV-1 ICP0-null mutant infection . As the induction of innate immunity during HSV-1 ICP0-null mutant infection was inhibited by Ruxolitinib , we next examined the effect of JAK inhibition on WT and ICP0-null mutant HSV-1 replication ( Fig 8 ) . At a concentration sufficient to inhibit ISG induction ( 5 μM; Fig 7G–7I ) , Ruxolitinib treatment had no effect on the relative plaque formation efficiency ( PFE ) of either WT or ICP0-null mutant HSV-1 ( Fig 8A ) . These data indicate that innate immune signalling and the induction of ISGs does not directly contribute to the cellular restriction and plaque-formation defect of an HSV-1 ICP0-null mutant observed in restrictive cell types ( ≥ 1000 fold; [33 , 35 , 61] ) . In contrast , virus yield assays demonstrated that Ruxolitinib treatment enhanced the levels of ICP0-null mutant , but not WT , HSV-1 propagation ( Fig 8B ) . Thus , under infection conditions that saturate intrinsic host defences and enable the onset of HSV-1 ICP0-null mutant replication ( MOI of ≥ 1 PFU/cell; Fig 6E ) , innate immune defences act to restrict virus propagation . By way of contrast , depletion of IFI16 or PML enhanced both the PFE and virus yield of an HSV-1 ICP0-null mutant ( Fig 8C and 8D; [11 , 49] ) . Importantly , no additional increase in virus yield was observed on Ruxolitinib treatment of IFI16 or PML depleted cells ( Fig 8D ) , indicative of an impaired innate immune response in these cells during HSV-1 ICP0-null mutant infection . Correspondingly , qRT-PCR demonstrated that the induction of ISGs ( Mx1 , ISG15 , ISG54 ) was significantly impaired in both IFI16 or PML depleted cells in response to HSV-1 ICP0-null mutant infection at 9 hpi ( Fig 8E and 8F ) . These data identify a novel role for PML in the induction of ISGs and the regulation of innate immunity during HSV-1 infection . Collectively , our data demonstrate that PML plays dual roles in the temporal regulation of intrinsic and innate immune defences that are dependent on viral genome delivery to the nucleus and the onset of vDNA replication , respectively . As intrinsic and innate immune defences to HSV-1 infection are known to be cell-type dependent [34 , 35 , 62] , we next investigated if there was a correlation between cell line permissiveness to HSV-1 ICP0-null mutant replication and the entrapment of viral genomes by PML-NB host factors ( Fig 9 ) . Relative to permissive osteosarcoma cells ( U2OS , SAOS ) , which do not require ICP0 to stimulate the onset of HSV-1 replication [34] , RPE cells demonstrated equivalent levels of HSV-1 ICP0-null mutant restriction to HFt cells ( ≥ 1000-fold reduction in PFE , Fig 9A ) . Western blot analysis revealed that all these cell lines expressed similar levels of PML , Daxx , and IFI16 ( Fig 9B ) . However , infection with HSV-1EdU demonstrated a significant reduction in the colocalization frequency of PML and Daxx to infecting viral genomes between permissive ( U2OS , SAOS ) and restrictive ( HFt , RPE ) cell-types ( Fig 9C and 9D ) . Importantly , in many instances neither PML nor Daxx was observed to localize with infecting viral genomes in permissive cell types ( Fig 9C , bottom panels ) . Thus , we have identified a correlation between the stable entrapment of vDNA by PML-NBs and the requirement for ICP0 to stimulate the efficient onset of HSV-1 infection in restrictive ( HFt , RPE ) , but not permissive ( U2OS , SAOS ) , cell-types . As U2OS and SAOS cells do not express ATRX ( Fig 9B; [63 , 64] ) , a known core constituent protein of PML-NBs and an intrinsic antiviral regulator to HSV-1 infection [64–66] , we investigated the requirement for ATRX to mediate PML-NB entrapment of vDNA . HFt cells were stably transduced with lentiviral vectors expressing non-targeting control or ATRX-targeting short hairpin RNAs ( shCtrl and shATRX , respectively; [65] ) . qRT-PCR and western blotting confirmed ATRX depletion , which had a modest effect on PML mRNA transcript levels without influencing PML or Daxx expression levels ( Fig 9E and 9F ) . HSV-1EdU infection of shCtrl or shATRX cells demonstrated that depletion of ATRX led to a distinct population of viral genomes with a reduced colocalization frequency with PML ( left-hand dotted box; Fig 9G ) . Notably , low levels of ATRX colocalization were still observed with vDNA in a significant proportion of ATRX depleted cells ( right-hand dotted box; Fig 9G ) . Quantitation ( n ≥ 200 genomes per condition ) revealed that there was a significant difference in PML recruitment to vDNA in ATRX depleted cells ( Fig 9H ) . We conclude that ATRX , either directly or indirectly , contributes to the entrapment of vDNA within PML-NBs following nuclear entry . Finally , we compared restrictive ( HFt , RPE ) and permissive ( U2OS , SAOS; [62] ) cell types to mount an innate immune response to HSV-1 ICP0-null mutant infection under infection conditions that permitted the onset of viral replication ( MOI 1 PFU/cell ) . Surprisingly , qRT-PCR analysis demonstrated that only HFt cells induced ISG ( Mx1 , ISG15 , ISG54 ) expression during HSV-1 ICP0-null mutant infection ( Fig 10A , top panels; [62] ) . This was not due to a defect in IFN pathway signalling , as all four cell-types were responsive to exogenous IFN-β stimulation ( Fig 10A , bottom panels ) . Correspondingly , only HFt cells showed enhanced levels of HSV-1 ICP0-null mutant propagation following JAK inhibition by Ruxolitinib ( Fig 10B ) . We conclude that RPE cells , which are highly restrictive to HSV-1 ICP0-null mutant replication ( Fig 9A ) , are defective in aspects relating to intracellular innate signalling in response to HSV-1 infection . These data support our microscopy observations ( Fig 6 ) and inhibitor studies ( Figs 7 and 8 ) , and collectively demonstrate that intrinsic and innate host immune responses to HSV-1 infection are temporally distinct and functionally separable arms of host immunity . In summary , we show that the temporal recruitment of host immune regulators to infecting viral genomes plays an important role in the sequential regulation of intrinsic and innate immunity during HSV-1 infection . We identify PML-NBs to entrap vDNA shortly after nuclear entry in an ATRX-dependent and IFI16-independent manner . We identify a novel role for PML in the induction of innate immunity in response to HSV-1 infection that correlates with the recruitment of IFI16 into vDNA complexes associated with ICP4 and the onset of vDNA replication . These intracellular host defences are counteracted by ICP0 , which induces the degradation of PML from the outset of infection to release viral genomes entrapped within PML-NBs to stimulate the onset of HSV-1 lytic replication .
A key aspect in the regulation of intracellular host immunity during herpesvirus infection is the rapid recruitment of host immune factors to infecting viral genomes . This nuclear response to infection has been linked to viral genome silencing , as part of a pre-existing intrinsic immune defence , and the activation of innate immune signalling pathways ( reviewed in [1 , 4 , 32] ) . However , the temporal recruitment of these host immune regulators to infecting viral genomes upon vDNA entry into the nucleus has remained poorly defined due to the technical challenges associated with low genome copy-number detection . Microscopy studies have historically relied on the use of viral mutants , high MOI conditions , and vDNA binding proteins to investigate the recruitment of host immune regulators to infecting viral genomes . Whilst informative , such approaches can readily saturate intrinsic host defences that restrict the initiation of viral gene expression due to high input genome loads [35] . Consequently , the temporal sequence of events that influence the sequential regulation of intracellular host immunity upon vDNA entry into the nucleus has remained poorly defined , specifically during WT herpesvirus infections that express a full complement of immune antagonists . Here we quantitatively examine the recruitment of intrinsic and innate immune regulators to infecting WT and ICP0-null mutant HSV-1 genomes under a range of relatively low MOI conditions ( ≤ 3 PFU/cell ) within the first 15–90 mpi ( post-addition of virus ) . We show that PML , the principle scaffolding protein of PML-NBs [48] , plays temporally distinct and functionally separable roles in the regulation of intrinsic and innate immune defences activated in response to HSV-1 infection through the entrapment of viral genomes ( Figs 2 and 6 ) and the induction of ISG expression following the onset of vDNA replication ( Fig 7 ) , respectively . These observations reconcile many longstanding issues within the field as to the importance of PML and PML-NBs during primary herpesvirus infection and the requirement for ICP0 to stimulate the onset of HSV-1 lytic replication , as discussed below . Immuno-FISH experiments conducted by Gerd Maul and colleagues over 20 years ago originally identified that infecting HSV-1 genomes localize in close proximity to PML-NBs under infection conditions that enabled detection of ICP8 [8] , an essential component of the vDNA replication complex [67] . These pioneering observations have stimulated a field of research that has uncovered fundamental roles for many PML-NB associated proteins in the regulation of intracellular host immunity against a range of DNA and RNA viral pathogens ( reviewed in [1 , 20 , 21 , 68] ) . PML-NBs are highly dynamic nuclear sub-domains , with resident proteins ( PML , Sp100 , and Daxx ) in constant exchange with the surrounding nucleoplasm [10] . Correspondingly , asynchronous plaque-edge recruitment assays ( examples of which are shown in Fig 6 , S7 Fig; [9] ) have shown that many PML-NB component proteins re-localize to sites in close proximity to infecting HSV-1 genomes under high MOI conditions , where de novo PML-NB like foci are reformed [10] . These observations have set the paradigm for intrinsic immunity during herpesvirus infection , where pre-existing PML-NB host factors re-localize to infecting viral genomes to mediate the transcriptional repression of viral gene expression [19 , 49 , 50 , 69] . However , recent live-cell microscopy studies have proposed an alternate mechanism , whereby vDNA becomes transiently associated with host factor ( s ) within the nucleoplasm ( notably Daxx and IFI16; [12 , 14] ) prior to deposition at PML-NBs , although no evidence for Daxx or IFI16 colocalization with vDNA or deposition within PML-NBs was reported . Using click chemistry , we demonstrate for the first time that infecting WT and ICP0-null mutant HSV-1 genomes are rapidly entrapped within PML-NBs following nuclear entry ( 30–90 mpi; Figs 2 and 6J ) . While we cannot rule out a recruitment model of genome entrapment , specifically the re-localization of PML-NB host factors that are in immediate proximity to nuclear infecting viral genomes , our data support a deposition model as: ( i ) PML-NBs that contained vDNA were indistinguishable in composition from other PML-NBs within the same infected nucleus or mock-infected cells ( Fig 3A–3D , S3 Fig ) ; ( ii ) Depletion of PML reduced Daxx colocalization with vDNA , indicative of a transient association stabilized by PML at PML-NBs where Daxx is a resident protein ( Fig 4E; [48 , 49] ) ; ( iii ) Depletion of ATRX , a binding partner of Daxx [70] , reduced the frequency of PML colocalization with vDNA in a significant subset of infected cells ( Fig 9E–9H ) . These observations support a deposition model of vDNA entrapment at pre-existing PML-NBs that contain a core complement of PML-NB host factors and implicate the Daxx/ATRX complex in this process , consistent with live-cell microscopy observations [12] . These observations are consistent with co-depletion experiments [19 , 50 , 69] , which have shown PML-NB proteins to act cooperatively to restrict the initiation of HSV-1 ICP0-null mutant replication under low MOI conditions ( ≤ 1 PFU/cell , 6E; < 25 genome copies/cell , S2 Table ) . We therefore provide spatial context to these studies , as repressed viral genomes remain stably entrapped within PML-NBs at 24 hpi ( Fig 6J ) , a host response that is impaired in cell types permissive to HSV-1 ICP0-null mutant replication which lack ATRX ( U2OS , SAOS; Fig 9A–9D; [34 , 63 , 64] ) . Thus , we identify PML-NB entrapment of vDNA as a key intrinsic antiviral host defence to WT herpesvirus nuclear infection , a conclusion consistent with genome localization studies in HSV-1 latently infected cells by immuno-FISH [71–73] . We demonstrate that this intrinsic PML-NB host defence occurs in a range of restrictive cell types relevant to primary HSV-1 infection ( Figs 2 and 9 ) and independently of the induction of ISG expression ( Figs 6H–6J , 7D and 10A ) , demonstrating that this host response does not directly contribute to the sensing of viral nucleic acids that leads to the induction of innate immunity . Our data highlights the importance of ICP0 to promote the onset of WT HSV-1 infection under low MOI conditions [33–35] . ICP0 is known to localize to PML-NBs from the outset of infection in a PML isoform and SUMO-dependent manner [17 , 22 , 74 , 75] , where it targets PML and other SUMO-modified component proteins for ubiquitination and proteasome-dependent degradation [17 , 25–27 , 74 , 75] . As ICP0 does not preferentially localize to PML-NBs that contain vDNA ( Fig 2C ) , our data indicate that these vDNA containing nuclear bodies are likely to be equivalent in their respective PML isoform composition and SUMO modification status at this extremely early stage of nuclear infection . Thus , cell-wide PML-NB disruption through ICP0 mediated degradation of PML ensures viral genome release and the dispersal of associated PML-NB host factors that repress the onset of viral gene expression [19 , 49 , 50 , 66 , 69] . This hypothesis is supported by our depletion experiments that show reduced Daxx localization with vDNA in PML depleted cells ( Fig 4E ) , and accounts for why many PML-NB resident host factors known to restrict HSV-1 ICP0-null mutant replication ( including Daxx , ATRX , and PIAS1 ) are not directly targeted for degradation by ICP0 [19 , 66] . Thus , the correct complement of host factors within pre-existing PML-NBs is likely to play an important role in mediating the cellular restriction of viral gene expression from the outset of nuclear infection . These observations account for why many herpesviruses encode IE gene products that disrupt the structural organization of PML-NBs ( reviewed in [1 , 68] ) , and the respective abilities of these proteins to complement the replication and plaque-forming defect of an HSV-1 ICP0-null mutant in restrictive cell types [76–79] . Our observation that repressed HSV-1 ICP0-null mutant genomes remain stably entrapped within PML-NBs without inducing ISG expression ( Figs 6E–6J and 7D ) has significant implications with respect to host PRR sensing of vDNA and the regulation of innate immunity during herpesvirus infection . The sensing of foreign DNA and the activation of innate immune signalling pathways can occur through multiple pathways and PRRs , including TLR9 , RIG-I , MAVS , AIM2 , DNA-PK , cGAS , and IFI16 ( reviewed in [4–6] ) . Of these , IFI16 has received significant attention due to its role as a vDNA PRR in the induction of ISG expression and type-I IFN production during herpesvirus infection [28 , 29 , 80–84] . Correspondingly , microscopy assays have shown IFI16 to be recruited to infecting HSV-1 genomes in a pyrin domain-dependent manner in association with PML-NB host factors [11 , 12 , 14] . This host response was initially reported to be antagonized by the ubiquitin ligase activity of ICP0 [28 , 29] , although subsequent studies have shown other viral and cellular factors are likely to be involved [11 , 30 , 31] . IFI16 recruitment studies have relied on the use of vDNA binding proteins to enable viral genome detection by proxy , or on extrapolation of altered patterns in IFI16 nuclear localization to infer IFI16-vDNA association in restrictive cell types . Thus , the temporal kinetics of IFI16 recruitment to vDNA and its subsequent association with PML-NB host factors has remained poorly defined , specifically under MOI conditions relevant to WT herpesvirus infections . In contrast to PML-NB host factors , we failed to observe any significant frequency of stable colocalization between IFI16 and vDNA up to 90 mpi ( post-addition of virus; Figs 3 and 5 , S5 Fig ) , even in the absence of PML or ICP0 ( Fig 4E ) . While we cannot exclude the possibility of highly transient IFI16 interactions with vDNA ( S5A Fig; [12 , 14] ) , our data indicates that IFI16 does not play an essential role in the entrapment of viral genomes by PML-NBs ( Fig 5; [11 , 14] ) . Importantly , under infection conditions that do not saturate or antagonize intrinsic PML-NB host defences ( HSV-1 ICP0-null mutant MOI < 1 PFU/cell , Fig 6E; < 25 genome copies/cell , S2 Table ) , we demonstrate vDNA entry into the nucleus alone is not sufficient to stimulate a robust innate immune response ( Figs 6E–6J and 7D ) . Induction of innate immunity only occurred under MOI conditions sufficient to saturate intrinsic host defences leading to the onset of HSV-1 ICP0-null mutant replication and plaque-formation ( MOI ≥ 1 PFU/cell; Figs 6E and 7D ) . Under such conditions , we identified a clear kinetic difference in the stable recruitment of PML and IFI16 to infecting viral genomes , which in the case of IFI16 correlated with the recruitment of ICP4 ( the major IE viral transcription factor ) to vDNA and the onset of viral gene expression ( Fig 6A–6D ) . Thus , we have identified a temporal boundary in the recruitment of intrinsic and innate immune regulators to infecting viral genomes that could represent a shift in host response; from an intrinsic defence centred on the repression of viral gene expression to the induction of innate immune signalling that promotes an antiviral state to restrict virus propagation . This hypothesis is supported by our observation that the induction of innate immunity requires the onset of vDNA replication ( Fig 7E and 7I ) . IFI16 is reported to recognise nucleosome free DNA in a sequence independent manner [85–87] , with high binding affinity for G quadraplex , branched or cruciform DNA structures [52] . Thus , it likely that the recruitment of IFI16 to infecting viral genomes is stabilised following the onset of vDNA replication that produces an abundance of such DNA structures [57] . This hypothesis may account for why PAA , but not ACG , is capable of inhibiting the induction of ISG expression ( Fig 7E and 7F ) . As inactivation of the vDNA polymerase by PAA would be expected to impair the initiation of vDNA replication [53 , 57] , while ACG treatment would lead to the accumulation of stalled vDNA replication products [54] . Thus , we hypothesize that the topology of replicating vDNA is important for the stable recruitment of IFI16 on to vDNA that leads to the induction of ISG expression and type-I IFN production during herpesvirus infection . We note that other viral and cellular factors are likely to contribute to the induction of innate immunity under alternative infection conditions , for example excessively high MOI , UV inactivation , or the use of viral mutants defective in multiple genes , which may deliver or generate PAMPs for PRR detection at different stages of infection . While it is clear that IFI16 plays a key role in the induction of ISG expression during herpesvirus infection , we have also identified an important and novel role for PML in this host response to HSV-1 infection ( Fig 8 ) . Depletion of PML significantly reduced the levels of ISG transcript accumulation observed at 9 hpi during HSV-1 ICP0-null mutant infection ( Fig 8F ) , a time point which proceeds ISG expression ( 16 hpi; Fig 7B ) . Thus , under infection conditions that saturate intrinsic PML-NB host defences during HSV-1 ICP0-null mutant infection ( MOI ≥ 1 PFU/cell , ~ 25 genome copies/cell ) , PML plays a significant role in mediating the induction of ISG transcription . Correspondingly , pharmacological inhibition of JAK signalling by Ruxolitinib [58 , 59] did not enhance HSV-1 ICP0-null mutant propagation in either IFI16 or PML depleted cells ( Fig 8D ) . Collectively , these data demonstrate that PML plays an important role in the induction of innate immunity in response to HSV-1 infection that restricts the propagation of HSV-1 following the successful saturation of PML-NB intrinsic host defences . These observations are consistent with reports highlighting a role for PML to mediate the induction of innate immunity in response to other human herpesviruses [88–90] , and a growing body of literature suggesting that specific PML isoforms play an important role in mediating the transcriptional regulation of cytokine signalling ( reviewed in [91] ) . Notably , PML has been reported to mediate the recruitment of activated STAT1 and 2 , along with HDAC1 and 2 , onto ISG promoters ( ISG54 , CXCL10 ) during human cytomegalovirus ( HCMV ) infection [90] . This host response is antagonized by the HCMV IE gene product IE1 [88 , 90] , a viral protein known to disrupt PML-NBs and to relieve the intrinsic cellular restriction of an HSV-1 ICP0-null mutant [78] . As JAK activity is well known to be required for STAT phosphorylation [60] , these observations are consistent with our inhibitor studies ( Figs 7H , 7I , 8B and 8D ) , which show JAK activity to play an important role in the induction of ISGs during HSV-1 ICP0-null mutant vDNA replication at 9 hpi . Consistent with STAT1 depletion studies [61] , JAK inhibition did not influence the intrinsic restriction of an HSV-1 ICP0-null mutant ( Fig 8A ) . These data contrast with depletion studies , which show a clear cooperative role for PML-NB host factors to restrict the initiation of HSV-1 ICP0-null replication [19 , 50 , 69] . Taken together with our observations in RPE cells ( Figs 9A and 10 ) , which are restrictive to ICP0-null HSV-1 replication but defective in innate immune signalling , these data show that PML plays dual roles in the temporal regulation of both intrinsic and innate immunity in response to HSV-1 infection . Host defences that are counteracted by ICP0 through the degradation of PML and disruption of PML-NBs from the outset of infection . In conclusion , we have shown for the first time that the differential recruitment of host immune regulators to infecting viral genomes plays a fundamental role in the sequential regulation of intrinsic and innate immune defences following HSV-1 nuclear infection . We have identified dual roles for PML in the regulation of these intracellular defences to HSV-1 infection that are dependent on vDNA entry into the nucleus and the onset of vDNA replication , respectively . Our analysis reconciles many long-standing questions as to the importance of PML and PML-NBs in the regulation of intracellular host immunity during HSV-1 infection . Our data highlights the importance of viral antagonists that disrupt PML-NBs to inactivate and evade key intracellular immune defences from the outset of infection , thereby promoting the onset of replication , propagation , and ultimately transmission to new hosts . Moreover , we demonstrate the versatility and sensitivity of bio-orthogonal labelling of viral nucleic acid to investigate the temporal recruitment of host immune regulators to infecting viral genomes during infection .
Primary human foreskin fibroblast cells ( HFs ) were obtained from Thomas Stamminger ( Department of Urology , University of Erlangen; [49] ) and immortalized ( HFt ) by retrovirus transduction to express the catalytic subunit of human telomerase , as previously described [18] . HFt , retinal pigmented epithelial ( RPE-1; ATCC , CRL-4000 ) , Human osteosarcoma ( U2OS and SAOS; ECACC , 92022711 and 89050205 ) , primary human foetal lung fibroblast ( MRC-5; ATCC , CCL-171 ) , and adult human keratinocyte ( HaCat; a gift of F . Rixon , MRC-UoG CVR ) cells were grown in Dulbecco’s Modified Eagle Medium ( DMEM; Life Technologies , 41966 ) . HFt cells were cultured in the presence of 5 μg/ml of Hygromycin ( Invitrogen , 10687–010 ) to maintain hTERT expression . Transduced HFt cells expressing shRNAs were cultured in the presence of Puromycin ( Sigma-Aldrich , P8833; 1 μg/ml or 0 . 5 μg/ml for selection or maintenance , respectively ) . Primary human embryonic lung fibroblast ( HEL 299; ECACC , 87042207 ) cells were maintained in Minimum Essential Medium Eagle ( MEM; Sigma-Aldrich M5650 ) supplemented with 2 mM L-Glutamine ( Life Technologies , 25030–024 ) and 1 mM Sodium Pyruvate ( Life Technologies , 11360–039 ) . Baby hamster kidney fibroblast ( BHK-21 C13; a gift of R . Everett , MRC-UoG CVR ) cells were grown in Glasgow Minimum Essential Medium ( GMEM; Life Technologies , 21710–025 ) supplemented with 10% Tryptose Phosphate Broth ( TPB; Life Technologies , 18050–039 ) . Medium for all cell lines was supplemented with 10% foetal bovine serum ( FBS; Life Technologies , 10270 ) , 100 units/ml penicillin , and 100 μg/ml streptomycin ( Life Technologies , 15140–122 ) . All cell lines were maintained at 37°C in 5% CO2 . 5-Ethynyl-2’-deoxyuridine ( EdU; Sigma-Aldrich , T511285 ) , 5-Ethynyl-2’-deoxycytidine ( EdC; Sigma-Aldrich , T511307 ) , 2’-deoxyruridine ( dU; Sigma-Aldrich , D5412 ) , and Ruxolitinib ( Ruxo; Sellechchem , S1378 ) were prepared in DMSO and used at the indicated concentrations . Acycloguanosine ( ACG , Sigma-Aldrich , A4669 ) , Phosphonoacetic acid ( PAA , Sigma-Aldrich , 284270 ) , and Interferon beta ( IFN-β; Calbiochem , 407318 ) were prepared in Milli-Q H2O and used at the indicated concentrations . Wild-type HSV-1 strain 17syn+ ( HSV-1 ) , its ICP0-null mutant derivative dl1403 ( ΔICP0; [33] ) , and their respective variants that express eYFP . ICP4 [40] were propagated and titrated as described [35] . For EdU labelling of viral genomes , RPE cells were infected with either HSV-1 ( MOI 0 . 001 PFU/cell ) or ΔICP0 ( MOI 0 . 5 PFU/cell ) . At 24 h post-infection ( hpi ) , EdU or EdC was added at a final concentration of 0 . 5 μM , unless otherwise indicated . Fresh EdU/EdC was pulsed into infected cultures at 24 h intervals until extensive cytopathic effect was observed , typically 3 to 4 days post-infection . Supernatants containing labelled cell released virus ( CRV ) were clarified by centrifugation ( 423 xg for 10 min ) and filtered through a 0 . 45 μm sterile filter and pelleted using a Beckman TLA100 Ultracentrifuge ( 33 , 800 xg for 3h at 4°C ) . Virion pellets were resuspended and pooled in 500 μl complete DMEM medium , and titrated in U2OS cells as described [35] . Plasmids encoding short hairpin ( sh ) RNAs against a non-targeted control sequence ( shCtrl; 5’-TTATCGCGCATATCACGCG-3’ ) , PML ( shPML; 5’-AGATGCAGCTGTATCCAAG-3’ ) , ATRX ( shATRX; 5’- CGACAGAAACTAACCCTGTAA-3’ ) , or IFI16 ( shIFI16; 5’-CCACAATCTACGAAATTCA-3’ ) were used to generate lentiviral supernatant stocks for transduction of HFt cells as described [11 , 49 , 65] . Pooled and stably transduced cells were used for experimentation . The following antibodies were used for immunofluorescence or western blotting: Primary rabbit polyclonal: anti-actin ( Sigma-Aldrich , A5060 ) , anti-Daxx ( Upstate , 07–471 ) , anti-ATRX ( Santa Cruz , H300 ) , anti-PML ( Bethyl Laboratories , A301-167A; Jena Biosciences , ABD-030 ) , anti-Sp100 ( GeneTex , GTX131569 ) , anti-SUMO2/3 ( Abcam , ab22654 ) , anti-Mx1 ( Santa Cruz , sc-50509;ProteinTech , 13750-1-AP ) , anti-ISG15 ( ProteinTech , 15981-1-AP ) , and anti-ISG54 ( IFIT2 , proteinTech , 12604-1-AP ) . Primary mouse monoclonal: anti-ICP0 ( 11060 , [92] ) , anti-ICP4 ( 58s , [93] ) , anti-VP5 ( DM165 , [94] ) , anti-SUMO2/3 ( Abcam , ab81371 ) , anti-PML ( abcam , ab96051 ) , anti-IFI16 ( abcam , ab55328; Santa Cruz , sc-8023 ) . Primary antibodies were detected using the following secondary antibodies: DyLight-680 or -800 conjugated anti-rabbit or -mouse ( Thermo; 35568 and SA5-35571 ) , Alexa -488 , -555 , or -647 conjugated anti-rabbit , or -mouse ( Invitrogen; A21206 , A21202 , A31572 , A31570 , A31573 , A31571 ) , HRP conjugated anti-mouse ( Sigma-Aldrich , A4416 ) . Unless otherwise stated , cells were infected with serial dilutions of HSV-1 or ΔICP0 and rocked every 10 min for 1 h prior to overlay with medium supplemented with 2% Human Serum ( HS; MP Biomedicals , 2931149 ) . 24 to 36 hpi , cells were washed twice in PBS ( Sigma-Aldrich , D1408 ) , simultaneously fixed and permeabilized in 1 . 8% formaldehyde ( Sigma-Aldrich , F8775 ) and 0 . 5% NP40 ( BDH , 56009 ) in PBS for 10 min , then washed twice in 0 . 1% Tween in PBS ( PBST ) . Cells were blocked with 5% skimmed milk powder ( SMP; Marvel ) in PBST ( blocking buffer ) for 30 min before incubation with an anti-VP5 monoclonal antibody diluted in blocking buffer for 90 min . Cells were washed three times with PBST , incubated with HRP conjugated anti-mouse IgG diluted in blocking buffer for 60 min , then washed with PBST three times . Plaques were visualized with True Blue peroxidase developing solution ( Insight , 50-78-02 ) according to the manufacturer’s instructions , and washed with Milli-Q H2O prior to plaque counting or imaging using an Axio Observer Z . 1 microscope ( Zeiss ) with differential interference contrast . For plaque formation efficiency ( PFE ) assays , plaque counts are expressed relative to the number of plaques on control HFt or U2OS infected cell monolayers ( as indicated ) at the equivalent dilution of input virus . Results presented as relative fold change ( number of plaques sample/number of plaques sample control ) . Plaque diameters were measured using Zen blue ( Zeiss ) imaging software . Cells were infected with either HSV-1 ( MOI 0 . 001 PFU/cell ) , or ΔICP0 ( MOI 1 or 2 PFU/cell , as indicated ) and rocked every 10 min for 1 h prior to overlay with complete medium containing either 5 μM Ruxolitinib or DMSO as a carrier control . Supernatants containing cell released virus ( CRV ) were collected at the indicated times post-infection . Virus titres were calculated by titration on U2OS cells as described [35] . Equal volumes of virus suspension and polystyrene latex spheres ( Agar Scientific , AGS130-02 ) at a known concentration per ml were mixed in 2 volumes of TNE buffer ( 20 mM Tris [pH 7 . 5] , 0 . 5 M NaCl , and 1 mM EDTA ) . 5 μl of suspension was then added to a glow discharged EM grid ( Agar Scientific , S162-4 ) , allowed to rest for 1 min , washed three times in deionised water , and stained with Ammonium Molybdate ( 2% ( w/v ) pH 7 . 2 ) . Dry grids were examined using a JEM2200 FS electron microscope ( JEOL ) and images captured using an Ultrascan 4000 charge-coupled-device ( CCD ) camera ( Gatan ) . Multiple images ( n ≥ 6 ) per sample were used for virus particle and latex bead enumeration and used to calculate the number of particles per ml of virus stock inoculum . Treated or infected cells were washed twice with PBS . Whole cell lysates were collected in SDS-PAGE loading buffer containing 4 M Urea ( Sigma-Aldrich , U0631 ) and 50 mM Dithiothreitol ( DTT; Sigma-Aldrich , D0632 ) . Proteins were resolved on NuPAGE 4–12% Bis-Tris Protein gels ( Invitrogen , NP0322BOX ) in MES ( Invitrogen; NP0002 ) or MOPS buffer ( Invitrogen , NP0001 ) and transferred onto 0 . 2 μm nitrocellulose membrane ( Amersham , 15249794 ) for 90 min at 30 volts in Novex transfer buffer ( Invitrogen , NP0006-1 ) according to the manufacturer’s instructions . Membranes were blocked in PBS with 5% FBS ( Block ) for a minimum of 1 h at room temperature . Membranes were incubated in primary antibody diluted in Block for a minimum of 1 h , washed three times with PBST for 5 min each , then incubated in secondary antibody diluted in Block for 1 h . Following three 5 min washes in PBST , one 5 min wash in PBS , and one rinse in Milli-Q H2O , membranes were imaged on an Odyssey Infrared Imager ( LiCor ) . The intensity of protein bands was quantified with Odyssey Image Studio Software . Cells were seeded overnight on to 13 mm coverslips prior to treatment or infection at the indicated MOI and time points at 37°C . For click chemistry assays , cells were washed in serum free DMEM prior to overlay in complete medium or fixation . At indicated time points , cells were washed twice in CSK buffer ( 10 mM HEPES , 100 mM NaCl , 300 mM Sucrose , 3 mM MgCl2 , 5 mM EGTA ) , simultaneously fixed and permeabilized in 1 . 8% formaldehyde and 0 . 5% Triton-X100 ( Sigma-Aldrich , T-9284 ) in CSK buffer for 10 min , and washed twice in CSK . Coverslips were then blocked with 2% HS in PBS for 30 min prior to click chemistry followed by immunostaining . Where applicable , EdU-labelled vDNA was detected using the Click-iT Plus EdU Alexa Fluor 555 Imaging Kit ( ThermoFisher scientific , C10638 ) according to the manufacturer’s instructions . For host and viral protein labelling , cells were incubated with primary antibodies diluted in 2% HS in PBS for 60 min , then washed in PBS three times , before incubation with secondary antibodies and DAPI ( Sigma-Aldrich , D9542 ) in 2% HS in PBS for 60 min . Coverslips were then washed in PBS three times , and twice in Milli-Q H2O prior to mounting on Citiflour AF1 ( Agar Scientific , R1320 ) . Coverslips were examined using a Zeiss LSM 880 confocal microscope using the 63x Plan-Apochromat oil immersion lens ( numerical aperture 1 . 4 ) using 405 nm , 488 nm , 543 nm , 594 nm , and 633 nm laser lines . Zen black software ( Zeiss ) was used for image capture , generating cut mask channels , and calculating weighted colocalization coefficients . High-resolution Z-series images were captured under LSM 880 Airy scan deconvolution settings using 1:1:1 capture conditions at 0 . 035 μm intervals . Images were processed using Imaris ( Bitplane ) software to produce rendered 3D image reconstructions and to calculate Pearson colocalization coefficients . Exported images were processed with minimal adjustment using Adobe Photoshop and assembled for presentation using Adobe Illustrator . In vitro virion DNA release assays were conducted as essentially described in [47] . Briefly , 1x108 PFU of virus preparation was diluted in ice-cold TNE buffer in the presence or absence of GuHCl ( 2M final concentration; Sigma-Aldrich , G3272 ) . Samples were incubated on ice for 60 mins prior to the addition of ice-cold Methanol ( final concentration 60% ) . Samples were dried onto poly-D-lysine ( Sigma-Aldrich , P7405 ) treated coverslips for 60–90 mins at 4°C prior to fixation in PBS containing 1 . 8% formaldehyde and 0 . 5% Triton-X100 for 10 mins at RT . Samples were washed twice in PBS and blocked in PBS containing 2% FBS for 10 mins at RT . Samples were processed for click chemistry to detect EdU or EdC labelled vDNA and immuno-stained for VP5 to detect viral capsids ( as described above ) . High-resolution Z-series images were captured under LSM 880 Airy scan deconvolution settings at 0 . 2 μm intervals ( as described above ) and the number of capsids and EdU or EdC labelled viral genomes were quantified in Zen blue ( Zeiss ) from maximum intensity projection images . HFt cells were infected with ΔICP0 EYFP . ICP4 at an MOI of 2 PFU/cell to enable the initiation of viral replication and plaque formation , as previously described [9] . At 24 hpi , infected cell monolayers were pulsed with 1 μM EdU for 6h prior to fixation and immunostaining , as described above . Cells were mock , HSV-1 , or ΔICP0-infected at the indicated MOI , and total RNA collected at 9 hrs post-infection unless otherwise stated . Where applicable , all drug treatments were added at the indicated concentration 1 h after inoculum adsorption . Total RNA was isolated using the RNAeasy Plus Kit ( Qiagen , 74134 ) according to the manufacturer’s instructions . Reverse transcription ( RT ) was performed using the TaqMan Reverse Transcription Reagents kit ( Life Technologies , N8080234 ) with oligo ( dT ) primers . cDNA samples were analyzed in triplicate using TaqMan Fast Universal PCR Master Mix ( Life Technologies , 4352042 ) with the following TaqMan gene specific primer- ( FAM/MGB ) probe mixes ( Life Technologies ) : PML ( assay ID Hs00231241_m1 ) , IFI16 ( assay ID Hs00986757_m1 ) , ATRX ( assay ID HS00997529_m1 ) , Mx1 ( assay ID HS00895608_m1 ) ISG15 ( assay ID HS01921425_s1 ) , ISG54 ( assay ID Hs01922738_s1 ) , or GAPDH ( 4333764F ) on a 7500 Fast Real time PCR system ( Applied Biosystems ) . Relative mRNA levels were determined using the ΔΔCt method , normalized to GAPDH , and expressed relative to indicated treatments . Data presented is from a minimum of two independent biological replicates , each analysed in triplicate ( RQ/RQmin/max ) . Means ( RQ ) and standard deviations ( RQmin/max ) are presented . For input viral genome quantitation , vDNA was extracted from infected HFt cells harvested at 90 mpi . Cells were trypsinised , pelleted by centrifugation ( 500 xg , 10 min ) , washed twice in PBS , and resuspended in PBS containing 1% SDS and 300mM Sodium acetate ( pH 5 . 2 ) . Total DNA was isolated by phenol chloroform extraction and ethanol precipitation , and resuspended in Tris buffer ( 10mM Tris-HCl pH 8 . 5 ) . qPCR was performed using two virus specific ( UL30 and UL36 ) primer-probe sets with distinct fluorophores ( Sigma-Aldrich; S3 Table ) in duplex reactions performed in triplicate per biological replicate . Quantitation was performed against standards of known concentration derived from a purified infectious HSV-1 17syn+ BAC clone ( SR27 DNA , [95]; a kind gift from Andrew Davison MRC-UoG CVR ) . | Intrinsic and innate immunity act to restrict the replication of many clinically important viral pathogens . However , the temporal regulation of these two arms of host immunity during virus infection remains poorly defined . A key aspect in the regulation of these intracellular immune defences during herpesvirus infection is the rapid recruitment of constitutively expressed immune regulators to infecting viral genomes . Here we show that at physiologically low multiplicities of infection , PML-NBs rapidly entrap HSV-1 genomes upon nuclear entry . Saturation of this pre-existing intrinsic host defence led to the stable recruitment of the vDNA pathogen sensor IFI16 to HSV-1 vDNA and the induction of ISG expression , an induced innate immune response dependent on the initiation of vDNA replication . Importantly , both intrinsic and innate arms of host immunity required PML , the principle scaffolding protein of PML-NBs . Our research identifies dual roles for PML in the sequential regulation of intracellular host immunity during HSV-1 infection , and highlights distinct phases in host immune factor recruitment to infecting viral genomes required for the temporal regulation of intracellular host immune defences during herpesvirus infection . | [
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"vi... | 2018 | Distinct temporal roles for the promyelocytic leukaemia (PML) protein in the sequential regulation of intracellular host immunity to HSV-1 infection |
Cryptococcus neoformans is a haploid environmental organism and the major cause of fungal meningoencephalitis in AIDS patients . Fluconazole ( FLC ) , a triazole , is widely used for the maintenance therapy of cryptococcosis . Heteroresistance to FLC , an adaptive mode of azole resistance , was associated with FLC therapy failure cases but the mechanism underlying the resistance was unknown . We used comparative genome hybridization and quantitative real-time PCR in order to show that C . neoformans adapts to high concentrations of FLC by duplication of multiple chromosomes . Formation of disomic chromosomes in response to FLC stress was observed in both serotype A and D strains . Strains that adapted to FLC concentrations higher than their minimal inhibitory concentration ( MIC ) contained disomies of chromosome 1 and stepwise exposure to even higher drug concentrations induced additional duplications of several other specific chromosomes . The number of disomic chromosomes in each resistant strain directly correlated with the concentration of FLC tolerated by each strain . Upon removal of the drug pressure , strains that had adapted to high concentrations of FLC returned to their original level of susceptibility by initially losing the extra copy of chromosome 1 followed by loss of the extra copies of the remaining disomic chromosomes . The duplication of chromosome 1 was closely associated with two of its resident genes: ERG11 , the target of FLC and AFR1 , the major transporter of azoles in C . neoformans . This adaptive mechanism in C . neoformans may play an important role in FLC therapy failure of cryptococcosis leading to relapse during azole maintenance therapy .
Cryptococcus neoformans is the most common cause of fungal meningoencephalitis world-wide . A major predisposing factor is the profound cellular immune defect caused by HIV infection or other underlying conditions . Cryptococcal meningoencephalitis is fatal unless treated and even with the most advanced treatment it is known for its high mortality rates [1] , [2] . Fluconazole ( FLC ) , a triazole antifungal drug , has been the agent most widely used for prophylactic therapy as well as for the long term management of common mycoses such as candidiasis and cryptococcosis owing to its efficacy and safety [3] . Long-term maintenance therapy with azoles creates favorable conditions for the emergence of resistance to the drug and increased azole resistance in vitro has been shown to be predictive of treatment failures and infection relapses [4] . The molecular basis of resistance to azole antifungals has been studied extensively in Saccharomyces cerevisiae and pathogenic Candida species such as C . albicans and C . glabrata which are phylogenetically distant from C . neoformans [5]–[13] . In these fungi , resistance is known to emerge via ( 1 ) increased production of multidrug transporters [14]–[16] , ( 2 ) mutations in ergosterol biosynthetic pathway genes [17] , [18] , ( 3 ) amplification of genomic regions that contain ergosterol biosynthetic pathway genes and transcription factors that positively regulate a subsets of efflux pump genes [19] , [20] and ( 4 ) activation of Hsp90 that may facilitate the cells to respond to drug stress [21] , [22] . In C . neoformans , FLC resistant strains have rarely been reported and the emergence of resistance has most often been documented with clinical outcomes of AIDS patients receiving azole maintenance therapy [23]–[27] . The mechanism of resistance in C . neoformans during maintenance therapy is poorly understood . An intriguing pattern of intrinsic azole resistance termed ‘heteroresistance’ was reported in 1999 among C . neoformans strains isolated from AIDS patients undergoing FLC maintenance therapy [28] and has only recently been characterized further [29] . This phenomenon of heteroresistance has been described as the emergence of a resistant minor subpopulation , within the single colony of a susceptible strain , that can tolerate concentrations of FLC higher than the strain's MIC . The resistant subpopulations can adapt to increasing concentrations of the drug in a stepwise manner . However , this acquired resistance to high concentrations of FLC is lost during repeated passage in drug free media and the clones return to their original level of heteroresistance . The level of heteroresistance to FLC ( LHF ) was defined as the lowest concentration of the azole drug at which resistant subpopulations emerge [29] . All strains of C . neoformans tested in our laboratory thus far have exhibited different LHF regardless of whether they are pre- or post therapy strains and the frequency of resistant subpopulations that emerge at each LHF ranged between 0 . 3 and 10% depending on strains [29] . Purification of a homogeneously sensitive subpopulation was not achieved at each strain's LHF while a homogeneous population of resistant cells could readily be obtained by exposure to FLC concentrations equal to or higher than its initial LHF . This acquired resistance to high concentrations of FLC , however , was lost during repeated passage in drug free media and the clones returned to the original LHF at which only 0 . 3 to 10% of the subpopulations grew . The molecular mechanism involved in this unique pattern of azole resistance remains an enigma . In this paper , we employed a genomic approach to uncover the mechanism by which C . neoformans cells acquire resistance to high concentrations of FLC and then subsequently lose the resistance when the drug stress is removed . We demonstrate that the adaptive resistance to higher concentrations of FLC was achieved by duplications of multiple chromosomes in response to drug pressure . Upon repeated transfer in drug free media , cells with multiple disomic chromosomes lose duplicated copies of the chromosomes sequentially and return to their original levels of drug tolerance . Such genomic fluidity that enables the cells to cope with the drug stress was observed in C . neoformans strains of both serotypes , A and D . Our results provide an explanation as to the mechanism governing the transiently high azole resistance observed in C . neoformans . We propose that this mechanism contributes to the failure of FLC therapy that results in the recurrent infection reported in patients undergoing prolonged azole therapy [28] .
All strains of C . neoformans tested in our laboratory displayed the intrinsic adaptive heteroresistant phenotype to FLC [29] . Since serotype A strains of C . neoformans are the most prevalent of all the four serotypes in clinical settings , we chose the strain H99 , a genome sequenced reference strain of serotype A , to study the mechanism of heteroresistance . Equal numbers of colonies were observed on YPD agar media with or without 16 µg/ml FLC . However , growth of the colonies on 16 µg/ml FLC was slightly slower with heterogeneity in size . On YPD media containing 32 µg/ml FLC , only 0 . 3–0 . 6% of the input cells consistently formed colonies within 72 h . Therefore , the intrinsic level of H99 FLC heteroresistance was determined to be 32 µg/ml [29] . Exposure of these subclones resistant at 32 µg/ml FLC to stepwise increases in FLC concentration generated clones resistant to 64 µg/ml ( strain H99R64 ) and 128 µg/ml ( strain H99R128 ) . Conversely , repeated transfer in drug free media of cells that had adapted to FLC at concentrations >32 µg/ml resulted in their reversal to original levels of heteroresistance . For instance , the H99Rvt16 strain derived from 16 daily transfers of the strain H99R64 in drug-free media displayed a FLC resistance phenotype intermediate between H99R64 and H99 . Its colony size on YPD with 32 µg/ml FLC was larger and its FLC E-test value was higher ( 48 µg/ml ) than the parental H99 strain ( E-test MIC = 24 µg/ml , Figure 1 ) . In contrast , the H99Rvt26 strain similarly derived from 26 daily transfers of the strain H99R64 in drug free media completely reverted back to the parental type . It is possible that the resistant strain H99R64 may express a different set of genes compared to H99 . Thus , we compared the gene expression profiles of H99R64 and H99 using microarray analysis . Of the 6719 detectable genes analyzed , 4149 genes were identified as significant by a mean false discovery rate ( FDR ) of 5% with significance analysis of microarray ( SAM ) as described in Material and Methods . We found 763 genes to be up or down regulated at least 1 . 8-fold in H99R64 compared to H99 . As expected , some of the differentially regulated genes are annotated for drug-related functions such as ABC transporter , multidrug resistance protein and enzymes involved in the ergosterol biosynthetic pathway . More significantly , among the 491 genes observed to be upregulated in H99R64 , 308 ( 63% ) are located on chromosome 1 ( Chr1 ) and 143 ( 29% ) on chromosome 4 ( Chr4 ) , which in collectively comprises 92% of the upregulated genes in H99R64 ( Figure 2A ) . Having a majority of the upregulated genes distinctly clustered in two chromosomes , we suspected some chromosomal anomaly in H99R64 . To examine global genomic changes in H99R64 , we performed comparative genome hybridization ( CGH ) . Interestingly , CGH analysis of the H99R64 strain revealed that the average log2 ratio of hybridization signals for Chr1 and Chr4 was significantly above zero ( 0 . 84 and 0 . 89 , respectively ) across the entire chromosome as shown in Figure 2B . The simplest explanation for this observation was that Chr1 and Chr4 had duplicated in the cells of H99R64 . We also analyzed H99 and H99R64 by flow cytometry and the data suggested that H99R64 is not a diploid strain harboring trisomic Chr1 and Chr4 ( Figure S1 ) . Consequently , the observed overexpression of the genes on Chr1 and Chr4 in cDNA microarray was due to the increase in copy number of the genes on the two chromosomes . To confirm this phenomenon of multiple chromosome duplications revealed by the CGH data , quantitative real time PCR ( qPCR ) of genomic DNA was performed . Four probes representing the four genes at different locations of chromosome 1 that span the left and the right arm ( chr1A , chr1B , chr1C , and chr1D ) were chosen for qPCR using the same genomic DNA used for CGH analysis . qPCR results of each probe on Chr1 were compared to those of the probe on either Chr3 ( chr3A ) or Chr11 ( chr11A ) , which served as unduplicated internal controls . As shown in Figure 2C , the copy number of all tested genes at different locations on Chr1 was close to two fold higher than the genes on Chr3 or Chr11 in H99R64 ( P<0 . 001 ) , while the relative copy number of those genes was close to 1 in H99 . This indicated that H99R64 has two copies for each of the four genes on Chr1 . Similarly , the qPCR results from probes representing two genes on Chr4 ( chr4A and chr4B ) showed the dosage of each gene in H99R64 to be two fold of that in H99 ( Figure 2D; P<0 . 001 ) . These qPCR results corroborated with the CGH data and suggested that chromosomes 1 and 4 in the strain H99R64 were disomic and the disomy of these two chromosomes was associated with resistance at 64 µg/ml FLC . Since the resistant clones can adapt to different levels of FLC concentration , it is possible that the FLC resistance level of each clone positively correlates with the number of disomic chromosomes . To test this hypothesis , we analyzed by CGH array six other H99-derived strains that had adapted to different levels of FLC concentration . First , we tested two of the aforementioned reverted strains , H99Rvt16 and H99Rvt26 , which had resulted from repeated transfer of H99R64 in drug free media for 16 days and 26 days respectively ( Figure 1 ) . CGH data revealed the intermediate revertant H99Rvt16 to be monosomic for Chr1 but still disomic for Chr4 while the complete revertant , H99Rvt26 , contained no disomic chromosomes ( Figure 3A and Figure S2 ) . These results suggested that removal of drug pressure caused a loss of the duplicated copies of chromosomes in the cells starting with that of Chr1 and then eventually return to the wild type status . Second , we performed CGH analysis of the H99R32 and H99R128 strains which were resistant to 32 µg/ml and 128 µg/ml FLC , respectively . CGH plots revealed that only Chr1 was duplicated in H99R32 , while four chromosomes ( Chr1 , 4 , 10 , and 14 ) were duplicated in H99R128 ( Figure 3B and Figure S2 ) . Third , we analyzed strain H99R64L , a clone of H99R64 that was maintained for an additional two weeks on the media with 64 ug/ml FLC . . As was the case with H99R64 , Chr1 and Chr4 were duplicated in H99R64L . Interestingly , Chr10 was also duplicated in H99R64L and the copy number of many genes on Chr14 increased although not quite two-fold compared to that of H99 ( Figure 3B ) . It appears that prolonged incubation of cells at high FLC concentrations results in the emergence of additional disomic chromosomes . CGH results were confirmed by qPCR analysis of a gene chosen from each of the four chromosomes 1 , 4 , 10 and 14 . As shown in Figure 3C , relative copy numbers of each gene against the internal control gene on Chr3 corroborated the CGH analysis . All four genes located on different chromosomes were duplicated in the strain H99R128 while no gene duplication was evident in the complete revertant strain H99Rvt26 ( P<0 . 001 ) . In the strain H99R64L , the gene copy number on Chr10 and Chr14 was close to 2 and 1 . 5 , respectively . Furthermore , chromosome duplication was also verified by quantitative Southern blot analysis using a probe from each of the four affected chromosomes ( Figure S3 and Table S1 ) . Collectively , these data strongly suggested that the number of disomic chromosomes positively correlated with the levels of FLC resistance of the strain and with the duration of exposure to FLC . Since CGH experiments require relatively large amounts of genomic DNA , each strain was allowed to proliferate for many generations on the drug media in order to obtain enough cells . The CGH data , therefore , represents the average status of the whole population grown on the media containing a certain concentration of FLC for many generations . qPCR was performed to examine gene dosages in the small number of individual resistant clones immediately after their emergence on plates containing high concentrations of FLC . This would determine whether gene duplication occurred during the early stages of growth in which resistance was initially observed at the single colony level . We chose 4 different colonies that appeared 4 days after plating naive H99 cells on media with 32 µg/ml FLC . Four independent colonies resistant at 64 and/or 128 µg/ml of the drug ( derived from four different 32 and/or four different 64 µg/ml FLC resistant clones , respectively ) were also isolated and analyzed . The CGH data suggested that the chromosome duplication occurs primarily in Chr1 , 4 , 10 and 14 and thus we focused our colony qPCR analysis only on these four chromosomes , although the duplication event might not be limited to these chromosomes . Interestingly , variations in the gene duplication events on different chromosomes was observed among the independent colonies grown on 32 µg/ml and 128 µg/ml FLC , respectively , but not on 64 µg/ml FLC ( 0 passage in Figure 4A , 4B , and 4C ) . To test whether prolonged drug-exposure would alter the outcome of gene duplication , the same sets of the four clones from each concentration of FLC were streaked on media with the same FLC concentration for 4 and 8 passages . Single colonies were then subjected to qPCR which exposed the tremendous variability in the duplication of genes representing different chromosomes . For example , one clone from 32 µg/ml FLC plate ( clone #2 ) initially had duplication of a gene on Chr1 . After 4 passages , genes on Chr4 and Chr10 were also duplicated in addition to Chr1 and the status of gene duplication in these chromosomes was the same when tested after 8 passages ( Figure 4A ) . Clone #3 from the 32 µg/ml plate , however , appeared to have genes on Chr1 and Chr14 duplicated initially , but the genes on Chr14 did not remain duplicated after longer exposure to the drug . In contrast , clone #4 did not show the gene on Chr1 duplicated until after 4 passages on 32 µg/ml FLC media while gene on Chr4 was duplicated from the beginning and remained duplicated throughout the 8 passages . Generally , a more consistent pattern of gene duplication was observed with independent clones isolated from the plates containing FLC 64 µg/ml compared to those isolated from 32 µg/ml FLC plates ( Figure 4B ) . Fluctuations in the pattern of gene duplication , however , were also obvious among the colonies grown on FLC 128 µg/ml ( Figure 4C ) . These data clearly showed the plasticity of gene duplication patterns at the single colony level , which could not be depicted clearly in CGH data . It is likely that CGH results represent the average status of chromosomes in the whole population and the system is not sensitive enough to allow detection of transient chromosomal duplication events in individual colonies . However , the CGH results of H99R64L apparently revealed the intermediate process of Chr14 duplication in which the gene copy number of Chr14 was 1 . 5 as verified by qPCR using the same batch of DNA ( Figure 3B and 3C ) . Taken together , our data suggested that when C . neoformans was treated with FLC , the process of multiple chromosome duplication may vary among individual cells and the status of chromosome copy number determined by CGH appears to be an average of the whole population from cells grown in the presence of FLC for many generations . It was plausible that formation of disomic chromosomes in association with FLC resistance was due to the presence of certain genes on the duplicated chromosomes which plays crucial role in the survival of cells under the drug stress . Since Chr1 was universally duplicated in the resistant clones , we focused on Chr1 as the first step to determine whether each duplicated chromosome carries genes that confer selective advantage under azole drug stress . Among the annotated genes on Chr1 , AFR1 and ERG11 were the two candidate genes that had already been characterized involving FLC resistance in C . neoformans . AFR1 is an ATP binding cassette ( ABC ) transporter-encoding gene and have shown to play an important role in azole susceptibility [29] , [30] . ERG11 encodes lanosterol-14-α-demethylase , the target of FLC , and increased expression levels of ERG11 is associated with increased FLC resistance in several fungi [15]–[18] . ERG11 , the target of FLC , has been proposed to contribute to isochromosome formation in C . albicans [20] , so we chose it to address its role in Chr1 duplication . If the presence of ERG11 were the main cause of Chr1 duplication , ERG11-containing chromosome would primarily duplicate regardless of the location of the gene . On the other hand , if other genes besides ERG11 were equally or more important for the survival in the presence of FLC , Chr1 would remain duplicated even if ERG11 is relocated from Chr1 to other chromosomes . Since ERG11 is most likely essential , we first inserted an extra copy of ERG11 on Chr3 , which had not duplicated under any level of drug stress and then deleted ERG11 from its native location on Chr1 ( Figure 5 ) . Strain C1345 , which contained two copies of ERG11 – one on Chr1 and the other on Chr3 , exhibited elevated resistance to FLC according to E-test ( Figure 5 ) as well as by growth analysis ( 100% growth at 32 µg/ml and 0 . 1% growth on 64 µg/ml in contrast to 0 . 3–0 . 6% growth at 32 µg/ml and 0 % growth at 64 µg/ml of H99 ) compared to H99 . These data indicate that the extra copy of ERG11 inserted onto Chr3 conferred increased FLC resistance . Since C1345 had two copies of ERG11 mimicking the effect of Chr1 duplication regarding ERG11 copy number , it was of great interest to determine the status of chromosome duplication in C1345 upon exposure to high concentration of FLC . First , qPCR was performed on two independent colonies of C1345 isolated immediately after emerging on the plate containing 32 µg/ml FLC . We detected close to two copies of ERG11 ( chr1A probe ) but only one copy of other genes on Chr1 , Chr3 , and Chr4 suggesting no duplication of chromosomes of C1345 at 32 µg/ml FLC ( Figure 6A ) . This is in contrast to H99 subclones resistant to 32 µg/ml FLC in which Chr1 is duplicated ( Figure 3B and 3C ) . However , qPCR of two C1345 colonies isolated directly from 64 µg/ml of FLC plate showed the existence of three copies of ERG11 ( chr1A probe ) and two copies of both chr1D and chr4A , but only one copy of chr3A ( Figure 6A ) . These data suggested that both Chr1 and Chr4 were duplicated in the C1345 colonies grown in 64 µg/ml of FLC . CGH analysis of the entire cell population harvested from 64 µg/ml FLC ( C1345 R64 ) clearly showed duplication of Chr1 and Chr4 and not Chr3 ( Figure 6B ) . In addition , C1345R128 , the C1345 strain grown on128 µg/ml FLC showed similar chromosome duplication patterns as C1345R64 maintaining duplication of Chr1 and Chr4 . It is intriguing , however , to observe intermediate hybridization signal for Chr3 in C1345R128 ( average log2 ratio of −0 . 035 and 0 . 317 for C1345 R64 and C1345R128 , respectively ) . qPCR using the same DNA showed that the copy number of chr3A probe located on Chr3 was 1 . 22±0 . 06 , confirming the CGH results . This data suggests that a proportion of the cells in the population of C1345R128 strain may have an extra copy of Chr3 . Colony PCR from two independent colonies of C1345R128 supported duplication of the gene on Chr3 ( Figure 6A ) . The second copy of ERG11 resides on Chr3 in C1345R128 which has not been observed to be duplicated in other strains tested so far . These results showed that two copies of ERG11 , one on Chr 1 and the other on Chr3 prevented disomy formation of Chr1 at 32 µml FLC but did not prevent disomy formation of Chr1 and Chr4 at FLC 64 µg/ml , a concentration which is 2-fold higher than the level tolerated by C1345 . Furthermore , Chr1 was preferentially duplicated over Chr3 at high concentrations of FLC when the ERG11 existed on both chromosomes . The ERG11 gene on the Chr1 was subsequently deleted from C1345 leaving only one copy of ERG11 inserted on Chr3 . The FLC resistance levels of three independent transformants ( C1347 , C1348 , and C1350 ) were comparable with H99 ( 100% growth at 16 µg/ml and 0 . 3–0 . 6% growth at 32 µg/ml ) , indicating that translocation of ERG11 from Chr1 to Chr3 did not alter the strain's FLC resistance level . Clones of these three independent transformants grown in 32 µg/ml FLC were subjected to colony qPCR . Noticeably , the copy number of ERG11 ( chr1A probe ) and chr3A were close to two fold , while the copy number of chr1D remained close to one suggesting duplication of Chr3 but not Chr1 ( Figure 6C ) . CGH analysis of C1347R32 , C1348R32 , and C1350R32 showed Chr3 was duplicated in all three strains ( Figure 6D ) . Interestingly , Chr4 was also duplicated in all three strains although colony PCR results suggested duplication of a gene on Chr4 only in C1347R32 and C1348R32 ( Figure 6C and 6D ) . This result was different from H9932R in which only Chr1 duplication was observed at 32 µg/ml FLC ( Figure 3B ) . These data suggested that when only one copy of ERG11 is present in the genome , the ERG11 bearing chromosome is the primary one to be duplicated at 32 µg/ml FLC . However , additional chromosome duplication ( Chr4 ) was required to tolerate the stress exerted by FLC when ERG11 was moved from its native location to Chr3 . Additional CGH was performed using strains derived from C1347 , C1348 , and C1350 resistant to 64 µg/ml FLC ( Figure 6D ) . C1347R64 and C1348R64 displayed disomies of Chr1 , Chr3 and Chr4 while C1350R64 showed duplication only in Chr3 and Chr4 but not in Chr1 . Single colony qPCR of these three strains supported the CGH results although the copy number of chr1D in C1347R64 was only 1 . 32 ( ±0 . 05 ) , suggesting that Chr1 amplification occurred in a certain portion of the clonal population ( Figure 6C ) . These data indicated that when a single copy of ERG11 gene exists in the genome , the chromosome carrying ERG11 is consistently duplicated in all subsequently derived FLC-resistant strains . However , our data also pointed out that ERG11 was not the sole reason for the Chr1 duplication and duplication of other genes on Chr1 and those on Chr4 also appeared to have contributed to the survival of cells at 64 µg/ml FLC . In an attempt to investigate other genes on Chr1 that confer resistance to FLC via chromosome duplication , we investigated AFR1 . Several lines of evidence have indicated that AFR1 plays an important role in FLC resistance . First , AFR1 expression was upregulated in both H99R64 and the H99 strains treated with FLC . Second , deletion of AFR1 resulted in a drastic decrease in FLC resistance in H99 [29] . Third , high expression level of AFR1 resulted in the increased level of FLC resistance [30] . The afr1Δ strain ( C1371 ) was used to determine the possible involvement of AFR1 in Chr1 duplication under FLC stress . If AFR1 were important for duplication of Chr1 , we would not expect Chr1 to be duplicated in afr1Δ strains resistant to FLC . The H99 afr1Δ strain is extremely sensitive to FLC ( MIC 0 . 38 µg/ml ) and its level of heteroresistance was reduced from 32 µg/ml to 1 µg/ml [29] . CGH analysis of the subpopulation resistant at 1 µg/ml FLC ( afr1ΔR1 ) clearly showed that Chr1 was not duplicated in the afr1ΔR1 strain ( Figure 6E ) . Instead , Chr4 and Chr5 were duplicated along with short segmental duplications of Chr9 and Chr10 . Thus , absence of AFR1 on Chr1 not only abrogated Chr1 duplication but also caused whole duplications or segmental duplication in other chromosomes at 1 µg/ml FLC . Such a chromosomal duplication pattern was presumably due to the presence of genes on these duplicated chromosomes which might compensate for the effect of AFR1 deletion from Chr1 in afr1ΔR1 . It is noteworthy that although ERG11 is present on Chr1 in afr1ΔR1 , disomy formation of Chr1 does not occur at 1 µg/ml FLC . However , CGH analysis of the subpopulation resistant at 8 µg/ml ( afr1ΔR8 ) showed that Chr1 was duplicated along with an additional four chromosomes ( Chr 4 , 5 , 6 , and 10; Figure S4 ) . These findings underscore the importance of both ERG11 and AFR1 in the formation of Chr1 disomy under FLC stress . All strains of C . neoformans tested thus far displayed the FLC heteroresistant phenotype [29] . Although different strains displayed heteroresistance at different concentrations of FLC , the stepwise exposure to higher concentrations of FLC allowed the strains to adapt to levels of FLC that are higher than their original MIC . These resistant strains all reverted to the original level of resistance upon removal of drug pressure . To investigate whether chromosome duplication associated with FLC resistance was an H99-specific event , we analyzed a number of matched pairs of naive vs . FLC-adapted resistant isolates in both serotype A and D backgrounds . Consistent with the observation in H99 , FLC-resistant strains derived from both serotype backgrounds contained disomic chromosomes according to CGH analysis ( Figure S5 ) , even though the duplicated chromosomes were not always identical in these strains . These results demonstrated that chromosome duplication associated with FLC resistance is a general mechanism employed by C . neoformans to overcome the stress exerted by FLC .
We report here that C . neoformans consistently forms disomies in multiple chromosomes in response to high level of azole pressure in both serotype A and D strains . Duplicated copies of the disomic chromosomes are lost as the drug pressure is removed . While there can be minor variations in the number of duplicated chromosomes among individual colonies grown on the same FLC media , the number of disomic chromosomes in the population of the overall cultures positively correlates with the adaptation to stepwise increase in FLC concentration . Aneuploidy associated with azole resistance was reported in Candida albicans where a substantially higher frequency of aneuploidy was found among azole resistant strains compared to susceptible strains [19] . In addition , chromosome instability , specific segmental aneuploidy , translocation of chromosomal arms and whole chromosome duplication have been previously reported in Candida species [20] , [31] , [32] . One could argue that the clones with disomy observed in the subpopulation of H99 under FLC stress may comprise a normal population that is selected by the drug rather than the drug induced chromosome amplification . There are three reasons for this argument being unlikely . First , aneuploidy caused by chromosome missegregation occurs once every 5×105 cell divisions in yeast [33] and once every 104 to 105 cell divisions in mammalian cells [34] . The frequency of FLC resistant clones of H99 ( 0 . 3 to 0 . 6% ) that emerged on drug containing media is too high to be the result of spontaneous chromosomal missegregation . Furthermore , the frequency of FLC resistant clones in different strains can be as high as 10% [29] . The frequency at which aneuploidy occurs in C . neoformans under FLC stress , therefore , is several logs higher than the frequency of spontaneous aneuploidy formation in other eukaryotes . Second , H99 is the most widely studied strain of C . neoformans and yet a clone derived from H99 that contains disomic chromosomes in a stress-free environment has never been reported . Third , we observed disomy formation in H99 only when exposed to FLC but not other xenobiotics such as trichostatin A , gliotoxin or rhizoxin ( data not shown ) . Aneuploidy is reported to have multiple effects on cellular physiology and cell division in haploid yeast [35] . Consistent with findings in yeast , disomic chromosomes in C . neoformans result in a proliferative disadvantage as evidenced by the retarded growth rate of H99R64 which harbors extra copies of Chr1 and 4 , and exhibits lower virulence in mice compared to the wild type strain ( Figure S6 ) . Although many fungi undergo chromosome length polymorphisms , chromosomal loss [36] or gain of minichromosomes [37] under different environmental stress , the degree of consistency and reproducibility of genomic fluidity observed in the present work has not been reported in other fungi . Since genetically identical cells of a single C . neoformans colony exposed to a high concentration of FLC can produce small subpopulations that show a marked difference in FLC susceptibility , we can speculate that this variability is linked to stochasticity in gene expression [38] . The genes that govern the capacity to differentiate into heteroresistant subtypes are not known . Although the CGH data show an increase of specific disomic chromosomes when C . neoformans is challenged by increasing drug pressure , minor variations in duplicated chromosomes appear to occur among individual colonies . Such plastic outcomes of duplication events can be advantageous for C . neoformans since it can provide the flexibility required for the cells to respond to various kinds of sudden stress it encounters either in the environment or in the host . The extra copy of a disomic chromosome may have resulted from non-disjunction , which occurs commonly in eukaryotes under different stresses [39] , [40] . In mammalian systems , inhibition of cholesterol biosynthesis by blocking sterol 14 α-demethylase ( ERG11 ortholog ) induces the formation of polyploid cells and mitotic aberrations [41] . Since ergosterol , the counterpart of cholesterol in fungi , is the essential molecule for maintaining membrane integrity , depletion of ergosterol in nuclear and cell membranes due to FLC treatment may jeopardize normal patterns of cytokinesis and enhance the frequency of chromosomal non-disjunction . For example , the spindle pole body ( SPB ) , a fungal equivalent of the centrosome is closely associated with the outer nuclear membrane in C . neoformans [42] . Once integrity of the nuclear membrane is compromised by depletion of ergosterol in FLC treated cells , segregation of the SPB may become irregular and enhance the chromosomal instability during cell division [43] . Gene duplication is known to be one of the key mechanisms which allows fungi to be selected during evolution [44] . Aneuploidy resulting in gene duplication has been reported to be the initial evolutionary change in S . cerevisiae selected in vitro to overcome loss of the myosin II protein which is crucial for normal cytokinesis [45] . In response to drug pressure , disomic chromosomes that contain genes relevant to ergosterol synthesis and drug transport could be beneficial for the survival of C . neoformans . Our hypothesis on the crucial roles of ERG11 and AFR1 in the occurrence of Chr1 duplication in clones resistant to high drug concentrations was borne out . When grown on 32 ug/ml FLC , the drug level at which Chr1 disomy occurs in H99 , the strain with ERG11 translocated from Chr1 to Chr3 showed duplication only in Chr3 but not in Chr1 . However , an extra copy of ERG11 on Chr3 in addition to the native copy on Chr1 was not enough to prevent Chr1 duplication at FLC concentrations higher than 32 µg/ml . This indicated that multiple copies of ERG11 alone can not meet the challenge of very high FLC stress . Similarly , Chr1 was not duplicated when AFR1 was deleted and grown on 1 µg/ml FLC ( the strain's initial heteroresistance level ) . However , Chr4 and Chr5 were duplicated along with short segmental duplications of Chr9 and Chr10 , which most likely compensate for the loss of AFR1 . These findings underscore the important roles of ERG11 and AFR1 in Chr1 duplication under drug stress . Afr1 is related to Snq2 of C . glabrata which is known to function as a transporter for several compounds including FLC [46] . In our test , afr1Δ was also sensitive to cycloheximide and rhizoxin treatment suggesting that AFR1 may function as a transporter for these drugs ( data not shown ) . An ideal experiment to test the hypothesis that duplication of Chr1 causes drug resistance would be to construct a strain in which only Chr1 is duplicated without exposure to azoles and then test the FLC resistance level of the strain . In S . cerevisiae , strains containing duplicated chromosomes could be constructed and the effect of aneuploidy tested [35] . Currently , construction of such strains , however , is technically not feasible in C . neoformans . Duplication of Chr1 has never been observed in H99 prior to the acquisition of FLC resistance . Since the resistance persisted as long as Chr1 disomy remained but was lost simultaneously after prolonged maintenance in drug free media , we are convinced that the two genes contribute to disomy of Chr1 . The C . neoformans genome contains all the genes known to be associated with ergosterol biosynthesis and has twice as many drug-related transporters as S . cerevisiae . These genes are distributed widely among 14 chromosomes and it is possible that some of them play a role in azole tolerance . It remains to be determined whether any other gene and its regulator necessitate duplication of the chromosome on which it resides . C . neoformans strains , regardless of the chronology of isolation either before or after the launch of azole drugs , showed that 0 . 3 to 10% of the subpopulations consistently resisted FLC concentrations higher than their MICs [29] . This number did not vary significantly during repeated tests . Although FLC resistant strains of C . neoformans have been increasingly reported from azole therapy failure cases [24] , [26] , [28] , [29] , [47]–[49] , the number of stable FLC resistant mutants among clinical isolates is rare compared to other pathogenic fungi [15] , [50] . One reason for the rarity in isolating FLC resistant C . neoformans mutants may be that heteroresistance masks mutation . The regular mutation rate is 10−5 to 10−6 and such a low population would be masked by the adaptive heteroresistant population . Our results provide the foundation for a mechanistic understanding of transient high azole resistance to FLC which might occur during prolonged maintenance therapy with azoles .
C . neoformans isolates H99 and NIH376 are serotype A strains; NIH429 is serotype D [29] . Table 1 lists all the H99 derived strains used in this study . Strains were stored in 25% glycerol stocks at −80°C until use and were maintained on YPD ( 1% yeast extract , 2% peptone , 2% glucose ) agar plates at 30°C for routine cultures . Fluconazole ( FLC ) was provided as powder by Pfizer Global Research & Development ( Groton , CT ) . Stock solutions were prepared in dimethyl sulfoxide ( Sigma ) at a concentration of 50 mg/ml . Analysis of FLC heteroresistance was performed by the method described previously [29] . Briefly , cell suspensions ( 1×103 to 4×103 CFU/ml ) in sterile saline were plated on YPD plates containing various concentrations of FLC . Growth was recorded after 72 h incubation at 30°C . Isolates were considered to be heteroresistant when resistant clonal populations were able to grow on a plate containing FLC . Resistant subpopulations were exposed to stepwise increases in FLC concentrations on YPD media . Microarray slides were purchased from the Genome Sequencing Center at Washington University , St Louis . For cDNA arrays , overnight cultures were diluted to OD600 ≅ 0 . 2 and grown in YPD liquid media for 7 hr . RNA was extracted from yeast cells using Trizol ( Invitrogen , Carlsbad , CA ) , and purified with RNeasy MinElute cleanup kit ( Qiagen , Valencia , CA ) . RNA was labeled and hybridized as described previously [51] . Arrays were scanned on a GenePix 4000B scanner and analyzed using GENEPIX PRO 6 . 0 ( Axon Instruments , Foster City , CA ) . Data were further analyzed in mAdb database at http://madb . niaid . nih . gov . Three biological repeats were performed using three independent RNA sets isolated from cells cultured on different days and the dye-reverse hybridizations were performed for all 3 sets . One set of RNA was also subjected to technical repeats . All statistically significant genes were identified by significance analysis of microarray using a mean false discovery rate of less than 5% . Only statistically significant genes were used for data analysis . Although the microarray slides used in this study were printed with 70-mers that are designed to uniquely represent each gene in C . neoformans serotype D , the oligomers were also optimized for homology to genes predicted in the serotype A strain , H99 ( http://genome . wustl . edu/services/microarray/cryptococcus_neoformans ) . Genomic DNA was prepared from C . neoformans strains grown overnight in 10 ml YPD medium as described previously [52] . 5 µg DNA was digested with DpnII ( 10 U/µg DNA , New England Biolabs , Ipswich , USA ) and labeled with dye according to the BioPrime®Array CGH Genomic Labeling System protocol ( Invitrogen Life Technologies , Carlsbad , USA ) . In all CGH experiments , Alexa647 was used to label DNA from the experimental strains and Alexa555 was used to label DNA from the reference control strain ( Invitrogen Life Technologies , Carlsbad , USA ) . Labeled DNA was purified with the purification kit from the same manufacturer and subjected to competitive hybridization with the 70mers microarray . Sample hybridization and data collection were carried out as described above . Data were further analyzed in mAdb database after applying 50th percentile ( Median ) normalization . Two parameters were considered for the CGH experiments . First , we hybridized the slides using H99 genomic DNA as both the experimental and the reference control samples . The scatter plot of the normalized log10 signal intensity of both channels showed tight correlation between two probes attesting to the reliability of the hybridization patterns of H99 genomic DNA to the JEC21-based 70mer slides . Second , we tested the reproducibility between arrays . Data from five independent CGH arrays were obtained from the H99 control set ( H99-Alexa 555 vs . H99-Alexa 647 ) as well as from the H99R64 set ( H99-Alexa 555 vs . H99R64-Alexa 647 ) . The data were highly consistent indicating high reproducibility between the arrays . Therefore , in most CGH studies , only one or two arrays per strain were analyzed . To visualize the CGH array in a chromosomal context , data were imported into Excel format from the mAdb database . CGH data was further normalized by subtracting the average log2 signal ratio of each gene obtained in control experiments ( H99 Alexa647 vs . H99 Alexa555 ) from that of a corresponding gene in the experimental data set to compensate for the dye and background bias . Relative hybridization levels were plotted as a running average over seven ORFs and clipped to the range corresponding to 1–2 copies ( log2 ratio of 0–1 , respectively ) . Each ORF was sorted according to their gene number corresponding to its order along each chromosome ( plotted on the x-axis ) . Although the genomes are largely co-linear between the current genomic assemblies of H99 and JEC21 , there are several apparent inversions and translocations . Due to these alterations , homologous chromosomes between the H99 and JEC21 assemblies have been assigned different numbers for some chromosomes [53] . The chromosomal number assignment of H99 was adopted in our CGH data . Due to the translocation events in Chr3 , Chr4 and Chr11 of H99 , the order of genes on these chromosomes was manually arranged according to its JEC21 counterparts . To quantify the gene copy number on specific chromosomes in wild-type and FLC-resistant strains , quantitative real time PCR ( qPCR ) assays were performed . For confirmation of CGH data , the same genomic DNA from strains used in CGH arrays was used for qPCR assays . For individual colony qPCR , genomic DNA of selected colonies was used . For colony DNA extraction , a single colony was picked with a sterile toothpick , suspended in 40 µl of 10 mM EDTA buffer in a microcentrifuge tube , boiled for 6 min and centrifuged . The supernatant was diluted 1∶10 in TE buffer and 5 µl of diluted DNA template was added to 20 µl of the qPCR mix ( Applied Biosystems , Branchburg , NJ ) . The reaction was performed in an Applied Biosystems 7500 Real-Time PCR System . Each reaction was run in triplicate and the average Ct value was converted to relative amount of DNA using the relative standard curve method . The sequences of the primers and probes used for the qPCR are listed in Table S2 . The genes CNAG_02959 on Chr3 , CNAG_00869 on Chr5 and /or CNAG_07554 on Chr11 were chosen as endogenous controls . For each specific gene , its copy number was obtained by comparing its qPCR value with the endogenous control and expressed as relative gene copy number . ERG11 was cloned by PCR and sequenced . The NAT selectable marker was cloned into the 5′ flanking region of ERG11 and the resulting construct was inserted in the intergenic region between CNAG_03012 and CNAG_03013 on Chr3 which were generated by PCR and sequenced . The final construct was transformed into H99 and the transformant containing a second copy of ERG11 between the intergenic region of CNAG_03012 and CNAG_03013 on Chr3 was screened by PCR and confirmed by Southern blot analysis . Subsequently , the ERG11 gene on Chr1 was deleted with the NEO gene from the clone containing two copies of ERG11 ( C1345 ) by biolistic transformation . An unpaired t test was used for the statistical analysis of qPCR data . A P value of less than 0 . 05 was considered to be significant . | Cryptococcus neoformans is an environmental fungus that causes life threatening brain disease , primarily in AIDS patients . The disease is estimated to claim 700 , 000 lives annually world-wide but most heavily in Africa . Fluconazole ( FLC ) , a fungistatic antifungal drug , is commonly used to treat patients for long term maintenance therapy . Recurrence of cryptococcosis in AIDS patients undergoing FLC maintenance therapy has been increasingly reported . Heteroresistance , an adaptive azole resistance , was associated with FLC therapy failure cases but the mechanism underlying the resistance was unknown . We previously described that C . neoformans strains are innately heteroresistant to FLC; each strain producing a fraction of subpopulation that can tolerate a high concentration of the drug . These resistant subpopulations revert to original phenotype during maintenance in drug free media . Various methods including cDNA microarrays , comparative genome hybridization and quantitative PCR have been applied to uncover the mechanism involved in the adaptation of C . neoformans to high concentrations of FLC and subsequent loss of resistance upon the removal of drug pressure . We discovered that C . neoformans adapts to high concentration of FLC by formation of disomy in multiple chromosomes . The removal of drug pressure results in a sequential loss of the extra chromosomal copies . It is likely that this novel mechanism of adaptation contributes to the failure of FLC therapy for cryptococcosis . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [
"infectious",
"diseases/fungal",
"infections",
"microbiology",
"molecular",
"biology",
"microbiology/medical",
"microbiology",
"infectious",
"diseases/antimicrobials",
"and",
"drug",
"resistance"
] | 2010 | Cryptococcus neoformans Overcomes Stress of Azole Drugs by Formation of Disomy in Specific Multiple Chromosomes |
Current efforts to control human soil-transmitted helminths ( STHs ) involve the periodic mass administration of benzimidazole drugs to school aged children and other at- risk groups . Given that high levels of resistance to these drugs have developed in roundworms of livestock , there is a need to monitor drug efficacy in human STHs . The current study aimed to evaluate an in vitro egg hatch assay for measuring the sensitivity of human hookworms to benzimidazole drugs in an isolated field setting in southern Yunnan province , People's Republic of China . Egg hatch assays were performed with hookworm ( Necator americanus ) eggs extracted from 37 stool samples received from local school-aged children . The mean IC50 was 0 . 10 ug/ml thiabendazole ( 95% CIs: 0 . 09–0 . 12 ug/ml ) . Observation of the eggs immediately prior to assay set-up revealed that a small percentage had embryonated in some samples . Scoring of % embryonation of eggs prior to the assay allowed for corrections to be made to IC50 , IC95 and IC99 values . Examination of the data with and without this correction revealed that the embryonation of a small number of eggs did not affect IC50 values , but did increase IC95 and IC99 values for some samples . This study has highlighted the impact of egg embryonation on the use of benzimidazole drug sensitivity assays for human hookworms in field settings . Given the greater flexibility required in human stool collection procedures compared to livestock studies , we suggest that embryonation of some eggs may be an unavoidable issue in some human studies . Hence , it needs to be measured and accounted for when analysing dose response data , particularly for generation of IC95 and IC99 values . The protocols used in this study and our suggested measures for accounting for egg embryonation should have widespread application in monitoring benzimidazole sensitivity at field sites worldwide .
Periodic mass administration of the benzimidazole drugs albendazole or mebendazole to school-aged children and other at-risk groups is the mainstay of all current programmes to control soil transmitted helminths ( STHs ) in humans [1] . The massive scale and increasing frequency of anthelmintic treatment mean that it is essential to monitor drug-exposed worm populations to ensure that any drug resistance is detected should it emerge . Early detection is a prerequisite for the implementation of mitigation strategies such as drug rotation to ensure that the effectiveness of the few existing anthelmintic drugs is preserved for as long as possible . The detection of anthelmintic drug resistance has been the subject of much attention in the livestock area [2] , [3] . The faecal egg count reduction test ( FECRT ) , in which faecal egg counts are conducted before and after drug treatment to detect any reduced drug efficacy indicative of drug resistance , is the most readily available test that can be adapted for the human field . It is currently being assessed by the WHO as a drug resistance monitoring tool . However , this test suffers from a lack of sensitivity , and its performance depends on pre-treatment egg counts ( infection intensity ) and possibly density dependent fecundity [4] , [5] . In vitro phenotypic assays and molecular biology-based tests have been studied extensively in livestock nematodes . An egg hatch assay has been described for measuring resistance to benzimidazole drugs [2] , [3] , and may therefore be applicable for the detection of benzimidazole resistance in human hookworms , the only common STH to hatch outside the human body . Molecular tests monitoring changes in beta tubulin genotypes have also been proposed [3] , [6] . However , even in certain well–studied livestock parasite species the relationship between benzimidazole drug efficacy and genotype is not fully understood [3] , and the importance of beta tubulin SNPs in benzimidazole sensitivity in human STHs has not yet been demonstrated . Hence , there is a need to develop and utilise phenotypic tests which examine the direct effects of a drug on the free living stages of the human STH in vitro until sensitive molecular tests become available . The use of egg hatch assays for measuring benzimidazole sensitivity in human STHs in field sites has been reported by several groups [7] , [8] . Recently , Kotze et al . [9] described a standardised egg hatch assay for human hookworms in a 96-well plate format using a concentration gradient of thiabendazole embedded in agar . The present study aimed to test this assay format at a field site in the Peoples Republic of China ( P . R . China ) , and to examine logistical and technical issues such as sample collection , handling and storage , egg isolation and test evaluation which may have an impact on the use of the assay in the field .
The present study is an integral part of an on-going project for helminth infection surveillance among schoolchildren implemented by the Yunnan Institute of Parasitic Diseases in collaboration with educational authorities . It focuses on the epidemiology and control of intestinal helminth infections in this province in southwest P . R . China . The project has been approved by the Academic Board ( Ethics Committee ) of the National Institute of Parasitic Diseases , Chinese Center for Disease Control and Prevention in Shanghai , P . R . China . Informed consent to conduct the present study was given by local school authorities who informed the eligible students in the presence of the responsible personnel from the Yunnan Institute of Parasitic Disease . As the children board at the school during the week , and are under the responsibility of the school , this information session was not done in the presence of the parents/guardians . The students were informed about the study aims , procedures and potential risks and benefits , and were alerted to the possibility to withdraw from the study at any time without further obligation . Hence , assent to participate in the study was indicated by subsequent submission of a stool sample . By withdrawing , children did not forfeit their right to anthelminthic treatment at study completion . This procedure , with consent provided by school authorities and by the study subjects through choosing to participate , with no requirement for individual written informed consent , is in line with national and local standards for such studies which are based on diagnosis with no invasive procedures , and was approved by the ethics committee . A single standard dose of albendazole ( 400 mg ) was provided free of charge to all study participants and their classmates after collection of stool samples . Stool samples were collected among students of a primary school located in a suburb of Pu'er city , in southern Yunnan province , P . R . China ( Figure 1 ) . Labeled ( identification number and name ) stool collection containers were handed out to students in the afternoon , and students were advised to keep filled containers shaded and at room temperature . Filled containers were collected the next morning , and transferred to the local branch of the Yunnan Institute of Parasitic Diseases ( YIPD ) , where all subsequent manipulations were performed , within 1 h . In the laboratory and during analyses , only the ID number was used to identify samples; a key linking ID numbers to names was retained by the YIPD . Hookworm eggs were recovered from individual samples rather than pooling faecal samples in order to determine the range of responses in samples from within the same population . The presence of hookworm eggs in the collected samples was determined using the Kato-Katz method [10] . Whenever stool samples could not be processed for egg recovery on the day of collection , about 20 g of stool was suspended in ca . 40 ml water to arrest the development of hookworm eggs ( anaerobic storage ) [11] , and the solution stored at room temperature . The protocol for egg recovery was adapted from Kotze et al . [8] . About 20 g of the hookworm-positive stools , or whatever was available in case the sample was smaller , was mixed with water 1∶2 , homogenized using a spatula and poured through a tea strainer . The runoff was transferred to 45 ml centrifuge tubes . The tubes were topped up with tap water , shaken carefully , and centrifuged in a bench top centrifuge for 2 minutes 30 seconds at 300 g . The supernatant was then poured off , the tube filled with saturated saline solution , and the sediment loosened using a wooden stick . Subsequently , the tube was centrifuged for 2 minutes 30 seconds at 130 g , and then left to stand for 5 minutes . The top 2 cm of the saline solution column were then transferred to a 15 ml tube using a disposable pipette . The 15 ml tube was filled with tap water and centrifuged for 2 minutes 30 seconds at 300 g , and the supernatant carefully removed using a disposable pipette . The tube was filled again with tap water , shaken and centrifuged as before . The supernatant was then removed leaving about 3 ml liquid above the sediment , and the sediment re-suspended . Aliquots of 20 µl of the egg suspension were then placed on a slide and the number of hookworm eggs counted . Based on these counts , the egg concentration was adjusted to approximately 2 eggs per µl egg solution , or the highest possible concentration in cases where fewer eggs than required to achieve the target concentration had been recovered . It was noted after the study had commenced that unusually high numbers of larvae were present in some drug assay plate wells with high drug concentrations . Subsequent observation of egg samples immediately following extraction from faeces revealed that some eggs had embryonated ( embryos visible within the egg shell ) . Hence , from that time onwards the percentage of eggs that had embryonated prior to assay set-up was measured . A subsample of eggs was taken , and each egg was scored as being either embryonated ( that is , with a larval shape visible within the egg ) or not ( that is , in a multicell stage ) . The mean number of eggs in the samples examined for embryonation ( ± SE ) was 70±9 . The number of samples for which embryonation was measured was 36 . Only the egg hatch dose response data from these samples was analysed for the present study . A PCR test designed to discriminate between Necator americanus and Ancylostoma duodenale was performed on a sub-sample of the recovered hookworm eggs conserved in ethanol and analysed according to the protocol published by Zhan et al . [12] . For DNA extraction , the DNEasy blood and tissue kit produced by Qiagen ( Hilden , Germany ) was used according to the manufacturer's protocol . Assay plates were prepared as described by Kotze et al [9] . A stock solution of thiabendazole ( 10 mg/ml ) was prepared in DMSO , and diluted 17 . 2-fold in DMSO to give a solution of 0 . 58 mg/ml , which was then serially-diluted 2-fold to produce a further 9 drug concentrations . Aliquots ( 2 µl ) from this series of dilutions ( starting at 0 . 58 mg/ml ) were added to 96-well microtitre plates , such that each row of the plate comprised a gradient of ten dilutions . The first two wells of each row were utilized as control wells ( i . e . received 2 µl of DMSO only ) , the 3rd well contained the lowest drug concentration , and the 12th well the highest . Each drug concentration was present in all 8 wells within each column of the plate . 200 µl of 2% agar ( Davis Gelatine Co . , powdered agar Grade J ) was dispensed into each well of the plate and allowed to set . Thus , the concentration of thiabendazole across the plate ranged from 0 . 01 to 5 µg/ml ( after addition of 30 µl of egg solution as described below ) . A piece of absorbent cloth soaked in an amphotericin B solution of 2 . 5 µg/ml was placed on top of the plate lids , and each plate was placed into a plastic press-seal bag and stored at 4°C . A box of plates was shipped at room temperature to the field site . The plates were refrigerated on arrival . Aliquots of each egg solution ( 30 µl ) were added to all wells in duplicate rows , or if insufficient egg solution was available , only every second well was loaded . The assay plates were incubated at 28°C for 48 hours before all larvae were killed by addition of 10 µl Lugol's iodine to each well . The number of larvae present in each well was then counted either by direct observation of the well under a dissecting microscope , or if too much debris or fungal/bacterial growth was present , the contents of the well was collected using a disposable pipette and transferred onto a microscope slide . In the latter case , both the empty well and the microscope slide were examined , and all larvae counted . As the use of IC95 and IC99 values has been advocated for livestock nematodes as more sensitive measures of changes in drug response in worm populations than IC50 values ( for example , Coles et al . [3] ) , we examined the data in terms of IC50 , IC95 and IC99 values . For each sample , the mean number of larvae present in the 4 control ( no drug ) wells was calculated . The number of larvae present in each drug well was then expressed as a percentage of the control mean . Data was analysed by non-linear regression using GraphPad Prism software in order to generate IC50 , IC95 and IC99 values , representing the drug concentrations which inhibited egg hatch ( reduced numbers of larvae present in wells ) by 50% , 95% or 99% relative to control wells . Dose response data were analysed before and after the application of a correction for the % embryonation which had been measured prior to assay set-up for each egg sample . This correction was done for each sample of eggs based on the % embryonation measured for that sample . Firstly , the number of eggs embryonated in each sample was expressed as a percentage . The mean number of eggs in the dose response assay control ( no drug ) wells was then corrected by removing the number of larvae that would be expected to have been derived from embryonated eggs added to those assay wells when the assay was established; for example if a mean of 80 eggs were present in control wells for a sample which had been shown to be 15% embryonated prior to assay set-up , then the control mean would become 80− ( 15/100×80 ) = 68 eggs . Similarly , the numbers of larvae present in each drug assay well was also corrected by subtraction of the number of larvae expected to have been derived from embryonated eggs in that specific egg sample ( = 12 in this example ) . The corrected drug assay data point was then expressed as a percentage of the corrected control mean . Corrected and uncorrected dose response data were analysed in two ways: firstly , by pooling the % egg hatch values for all 36 samples at each drug concentration to generate a single dose response for the uncorrected and corrected data sets ( and , hence single IC50 , IC95 and IC99 values for each data set ) ; and , secondly by generating separate dose responses ( and hence , separate IC50 and IC95 values ) for the data derived from each study subject's egg sample .
The PCRs designed to discriminate between N . americanus and A . duodenale indicated the presence of only the former species in the egg samples . This is in agreement with the known predominance of N . americanus in the study population ( Steinman , unpublished data ) . Eggs extracted from 37 faecal samples were examined in egg hatch assays . One of these assays was not included in the subsequent analysis as less than 20 larvae were present in the control ( no drug ) wells of the assay plates at the end of the incubation period . Hence , a total of 36 separate assays were analysed by non-linear regression . The % embryonation measured in all samples prior to assay set-up is illustrated in Figure 2 . The mean % embryonation was 6 . 3% , ranging up to 26% in one sample . The number of samples in which at least one egg had embryonated was 23 out of the 36 . Initially , we pooled the assay data to examine the overall population dose responses using data either corrected for embryonation or uncorrected ( Figure 3 , Table 1 ) . Sigmoidal dose response relationships were apparent ( Figure 3A ) , with the responses for both data sets showing very little difference at either the IC50 or IC95 levels , with overlapping 95% CIs ( Table 1 ) . Both data sets showed a plateauing of the response at the highest drug concentrations ( Figure 3B ) . As a consequence , the uncorrected data set did not decrease to an IC99 level , while the embryonation-corrected data set did decrease to a level which allowed for the calculation of an IC99 ( Figure 3B , Table 1 ) . However , the egg hatch in this latter data set did not reach zero even at the highest thiabendazole concentration of 5 ug/ml . The relationship between egg hatch and drug concentration in egg samples recovered from individual subjects is illustrated with 4 examples in Figure 4 . In each case a plateau was present in the uncorrected data sets , with the % egg hatch at levels of 5–25% at the highest drug concentrations . After correction for embryonation , two effects were apparent: in A and B , the level of the plateau was reduced , but a plateau was still present; in C and D , the plateau was removed , and egg hatch was reduced to zero at the highest concentrations . In all cases the curves showed little change with regard to the IC50 point following correction for embryonation . The variation in IC50 and IC95 values among the different individual faecal samples is illustrated in Figure 5 . IC50 values showed a similar range ( approximately 5-fold ) across both data sets , and mean IC50 values were not significantly different before and after embryonation correction ( paired t-test , P = 0 . 33 ) . A comparison of the IC95 values for the uncorrected and corrected subsets in Figure 5B illustrates the effect of applying the egg embryonation correction in reducing the number of samples for which an IC95 could not be calculated ( that is , IC95>5 ug/ml ) . However , even after the correction an IC95 could not be calculated for two samples . These two outlying IC95 values were derived from samples showing embryonation rates of 14 and 8% .
The present study has generated baseline data for drug sensitivity of human hookworms ( overwhelmingly N . americanus ) in a field setting in southwest P . R . China , and raised a number of important issues if such assays are to be standardized for widespread use . The IC50 for the pooled data ( 0 . 10 ug/ml , 95% CIs 0 . 09–0 . 12 ) was similar to that reported previously for N . americanus in Papua New Guinea by Kotze et al [8] ( 0 . 076 ug/ml ) and in Pemba Island , Zanzibar , by Albonico et al . [7] ( 0 . 079 ug/ml ) , indicating a degree of consistency in IC50 determinations by such assays in quite different field settings . The embryonation of some eggs is an important issue that has not previously been reported . Egg hatch assays in the livestock sphere are performed on eggs isolated from fresh samples ( <3 hours old at the commencement of the egg extraction procedures ) , or , if this is not possible , the faeces is mixed with water and sealed in tubes to generate anaerobic conditions until egg extraction can commence [2] , [11] . Le Jambre [13] compared egg hatch assays using embryonated and unembryonated eggs of Haemonchus contortus . The IC50 was approximately 10–20 fold higher if embryonated eggs had been added to assays than if unembryonated eggs had been used . In the present study , a degree of embryonation was observed and measured in some samples . Significantly though , this did not affect the pooled data IC50 and IC95 values ( from Figure 3 and Table 1 ) , or the mean IC50 values derived from corrected and uncorrected data set from individual study subjects ( Figure 5 ) . The embryonation of some eggs did , however , have a significant effect on some individual dose responses , in particular the IC95 and IC99 values for these samples ( from Figures 4 and 5 ) , as well as the IC99 for the pooled data ( Figure 3B and Table 1 ) . The presence of a small proportion of embryonated eggs manifested itself as a plateau in the dose response curves . This was most likely due to the shorter period of drug exposure prior to hatching for these eggs compared to the majority , hence allowing them to hatch at drug concentrations that would otherwise have been lethal . Although the levels of embryonation observed here ( mean of 6 . 3% ) did not affect the IC50 and IC95 for the pooled data ( as described above ) , the illustration of the impact of the egg embryonation on individual cases in Figure 5 , and its effect on IC99 ( from Table 1 ) , and the data described above from Le Jambre [13] , indicate that it could potentially have significant effects on IC50 , IC95 and IC99 values if it occurred at higher rates and / or in a greater proportion of individual samples than seen in the present study . Hatching of eggs at high drug concentrations could either be indicative of the presence of a small proportion of worms able to resist the effects of the drug , or simply the presence of a degree of egg embryonation in the original sample . Hence , if embryonation was solely responsible for the dose response plateau then the correction we applied to the data may be expected to remove it . While this occurred in some cases ( eg . Figure 4C and D ) , it was not achieved in others ( Figure 4A and B ) , and also did not occur for the pooled data ( from Figure 3B ) . This is likely due to experimental error rather than the presence of a real dose response plateau unrelated to embryonation . Our scoring of samples to obtain a % embryonation figure was based on a single sample of eggs for each faecal preparation ( mean sample size ± SE = 70±9 ) . Hence , this represents at best an estimate of the % embryonation in the samples . If this estimate was too low in a particular sample , its application to the data would not have removed the plateau in the dose response ( as most likely occurred in Figure 4A and B ) . Hence , given the lessons learnt here , we suggest that a greater number of eggs are scored for embryonation at the time of assay set-up than was done for the present study . A sample size of at least 100 eggs may be suitable . It would be clearly desirable to prevent embryonation prior to assay set-up when using egg hatch assays in field studies . However , this is not as easily achieved in human studies as in livestock surveys due to sampling constraints in the former . In the present study , faecal containers were handed out to children in the afternoon , and then collected the next morning . The faeces was then immediately analysed with the Kato-Katz method and , if found hookworm positive , covered with water and mixed well in order to prevent further egg development . Egg extraction then took place from approximately noon till mid-late evening . At this field site it would be difficult to reduce the time between stooling and the mixing of the samples with water in the laboratory since the local children do not stool very often , possibly associated with their low-fibre diet . Hence , it is not possible to only collect stools that had been deposited in the morning if a representative population sample is required . In other field settings , for example Kyrgyzstan [14] , it would be quite easy to ensure the freshness of samples as containers can be given out in schools in the morning and then collected for processing 2–3 hours later . Hence , given this difference in stooling habits in different field settings , it may be difficult to standardise this aspect of the assay across all sites worldwide . We advise that rather than try to standardise on a less desirable but more universal method that could be applied in all sites ( that is , an overnight stooling period along with an acceptance of a degree of embryonation in some cases ) , every effort is made to ensure that samples are as fresh as possible , even if this means that different methods are applied at different field sites . That is , in areas where it is possible , containers should be distributed in the morning and collected again after 2–3 hours for processing . In other cases , an overnight stooling period would need to be accepted . Wherever freshness cannot be guaranteed , the % embryonation should be scored based on a sample of at least 100 eggs at the time of assay set-up , and all egg hatch scores corrected . In areas where fresh stool samples can be accessed , embryonation could be checked in some samples , but not necessarily in all . When stool freshness is assured , confidence can be placed in IC50 , IC95 and IC99 values . Where stool freshness cannot be assured , and % embryonation corrections are required , IC50 values can be regarded with confidence , however , IC95 and IC99 values need to be judged carefully . Where high IC95 and IC99 values are observed , repeat samples could be collected . There was a degree of variability between IC50 and IC95 values over the separate assays . The variability in IC50s from embryonation-corrected assays using different samples of worm eggs amounted to a 5 . 3-fold range . Kotze et al [8] found a 4 . 1-fold range in IC50 values among samples from individual subjects in a Papua New Guinean village . The range for the data of Albonico et al [7] was not reported , but the 95% CIs from that study were similar to those for the pooled data dose response in the present study . The extraction of eggs from stools is a laborious process . In the present study , approximately 15 samples could be processed by 2 people working full-time in the laboratory every day , aided by another 2 technicians who performed the Kato-Katz test . The study of individual faecal samples allowed us to look at the variability across separate assays . However , such a procedure would not be necessary for a more general sensitivity-monitoring exercise . Hence , for such studies , a degree of pooling of faecal samples is recommended . We suggest that an approximately equal weight ( or volume ) of faeces from 5–10 individuals ( depending on study size ) could be pooled . Such a strategy has been applied previously by Albonico et al [7] who pooled faecal samples from groups of 10 children . In conclusion , this study has once again shown that it is possible to measure drug sensitivity using an in vitro assay in a field site with limited laboratory equipment . Difficulties associated with the recovery of hookworm eggs ( most significantly the freshness of the stools ) are not prohibitive , but need to be accounted for during test performance and as part of the data analysis . The protocols used in this study , and our recommendations concerning the pooling of samples and the accounting for egg embryonation , should have widespread application . Although the ability of the egg hatch assay to detect benzimidazole resistance in human hookworms has not been proven ( in the absence of known resistant populations ) , its utility for the detection of benzimidazole resistance in livestock parasites [2] , [3] should generate a degree of confidence that it will also be applicable in the human sphere . There is therefore a need to apply these assays widely in order to obtain baseline data for drug sensitivity in different human hookworm populations so that changes associated with the emergence of drug resistance may be detected , and to compare drug-naïve populations with those already exposed to repeated drug treatments . | With the implementation of mass drug administration programmes for the control of human soil transmitted helminths there is a need to develop drug sensitivity monitoring tools to detect the emergence of resistance . The present study aimed to use an egg hatch assay to measure benzimidazole sensitivity in human hookworms in a field setting in Yunnan province , People's Republic of China , in order to assess whether the assay offered a practical means of monitoring drug sensitivity in human hookworms in such a location . The assay proved able to generate dose response data , which allowed for the drug sensitivity of the hookworms in the local children to be described; the mean IC50 was 0 . 10 ug/ml thiabendazole . The study also found that practical issues associated with stool collection procedures , specifically the embryonation of some eggs during the time elapsing between stool deposition and egg recovery , can have an impact on the drug sensitivity data . We suggest means for data analysis that overcome the impact of egg embryonation on drug dose response data , which should allow for the use of such assays at different field sites worldwide . | [
"Abstract",
"Introduction",
"Materials",
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"Methods",
"Results",
"Discussion"
] | [
"medicine",
"infectious",
"diseases",
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] | 2011 | The Effect of Egg Embryonation on Field-Use of a Hookworm Benzimidazole-Sensitivity Egg Hatch Assay in Yunnan Province, People's Republic of China |
The aberrant expression of the transmembrane protein EpCAM is associated with tumor progression , affecting different cellular processes such as cell–cell adhesion , migration , proliferation , differentiation , signaling , and invasion . However , the in vivo function of EpCAM still remains elusive due to the lack of genetic loss-of-function studies . Here , we describe epcam ( tacstd ) null mutants in zebrafish . Maternal-zygotic mutants display compromised basal protrusive activity and epithelial morphogenesis in cells of the enveloping layer ( EVL ) during epiboly . In partial redundancy with E-cadherin ( Ecad ) , EpCAM made by EVL cells is further required for cell–cell adhesion within the EVL and , possibly , for proper attachment of underlying deep cells to the inner surface of the EVL , thereby also affecting deep cell epiboly movements . During later development , EpCAM per se becomes indispensable for epithelial integrity within the periderm of the skin , secondarily leading to disrupted morphology of the underlying basal epidermis and moderate hyper-proliferation of skin cells . On the molecular level , EVL cells of epcam mutant embryos display reduced levels of membranous Ecad , accompanied by an enrichment of tight junction proteins and a basal extension of apical junction complexes ( AJCs ) . Our data suggest that EpCAM acts as a partner of E-cadherin to control adhesiveness and integrity as well as plasticity and morphogenesis within simple epithelia . In addition , EpCAM is required for the interaction of the epithelia with underlying cell layers .
Like in mammalian gestation embryos , the epidermis of teleost larvae is bi-layered , consisting of an outer enveloping cell layer ( EVL ) , which morphologically and functionally resembles the periderm of mammalian embryos [1] , [2] , and a basal layer of keratinocytes . The function of the mouse periderm is poorly understood , however , recent genetic evidence points to pivotal roles during skin formation and other developmental processes [3] . Furthermore , the zebrafish EVL might serve as a model for other , medically more relevant simple epithelia , such as the epithelial tubules of the developing zebrafish kidney , which during nephron morphogenesis display several crucial cellular features [4] similar to those of the EVL described here . Zebrafish EVL cells segregate from deep cells during blastula stages and cover the embryo during further development [5] , while it remains unclear whether during metamorphosis , when the zebrafish epidermis becomes stratified , they are replaced by cells derived from basal keratinocytes [6] . During gastrulation , EVL cells undergo epiboly movements to progressively spread over the yolk , tightly coordinated with the simultaneous vegetal-wards displacements of deep cells and the yolk syncytial layer ( YSL ) [7]–[9] . Epiboly movements start approximately 4 hours after fertilization ( hpf ) , when only 30% of the yolk cell is covered by the blastoderm ( 30% epiboly ) , and is completed at 10 hpf , when the yolk is entirely surrounded by deep and EVL cells ( 100% epiboly ) . The molecular mechanisms underlying EVL epiboly have just started to be elucidated [10] , whereas the Ca2+-dependent cell adhesion molecule and adherence junction ( AJ ) component E-cadherin ( Ecad; Cdh1 ) has been shown to be specifically required for epiboly of deep cells [11] , [12] . The major force of deep cell epiboly is their polarized intercalative displacement from inner to outer layers . According to one report , Ecad drives these directed intercalations by forming an adhesion gradient within the deep layers themselves [11] , whereas according to another report , it is required for proper attachment of deep cells to the overlying EVL [12] . In addition , the EVL serves as a primary “skin” , constituting a barrier between the embryo proper and the fresh water environment . In contrast to basal keratinocytes , EVL cells are sealed to each other via apical junctional complexes ( AJCs ) , which consist of tight junction ( TJ ) and , possibly , AJ sections [13] . TJ proteins like Tjp/Zo1 and Tjp/Zo3 already accumulate at the lateral/apical sides of EVL membranes during early blastula stages , while loss of Tjp/Zo3 function results in increased surface permeability and compromised osmoregulation [14] . In addition , EVL cells form desmosome-like junctions between each other and with underlying cells [12] , [13] . EpCAM was first described in 1979 as a 40 KDa cell surface cancer-associated antigen [15] , [16] . In addition , it was isolated in several other contexts , which resulted in a plethora of synonyms such as Tacstd1 or Trop1 , recently unified under the name Epithelial cell adhesion molecule ( EpCAM ) or CD326 ( reviewed in [17] , [18] ) . EpCAM is a type I single span transmembrane glycoprotein , with extracellular epidermal growth factor-like ( EGF-like ) and thyroglobulin ( TY ) motifs [17] , [19] , [20] , and an intracellular domain containing an internalization motif and several α-actinin binding sites [19] . In mammals , EpCAM is present on the baso-lateral surface of most developing epithelia [21]–[26] . Expression is usually down-regulated as epithelial cells terminally differentiate . For example , progenitor cells of human skin epithelium express EpCAM , whereas differentiated keratinocytes do not [22] . However , EpCAM levels often rise again during regeneration or neoplastic transformations [18] , [23] , [24] , [27]–[29] . Strikingly , EpCAM is only found in epithelial-derived cancers , i . e . , carcinomas , but not in others , such as sarcomas , melanomas , or lymphomas [30] . Despite exhaustive in vitro studies , the exact roles of EpCAM during tumor progression and the molecular and cellular mechanisms of its functions are not fully understood , with several controversial findings , implicating EpCAM with adhesion , migration , metastasis , proliferation , differentiation , signaling and metabolism ( reviewed in [18] , [31] ) . Whereas according to some data , EpCAM acts as a homophilic cell-cell adhesion molecule with positive effects on cell adhesiveness and negative effects on cell motility and metastasis [26] , [32]–[34] , other data are in line with anti-adhesive and migration-promoting functions of EpCAM . Thus , in the presence of classical cadherins , EpCAM can reduce cell-cell adhesion , possibly by interfering with the interaction between cadherins and the cytoskeleton [20] , [35] . In addition , EpCAM physically interacts with the metastasis-promoting cell surface receptor CD44v4-V7 [36] and the tight junction component Claudin7 [37] , possibly blocking Claudin function during invasion and metastasis of several carcinomas [38] , [39] . Furthermore , EpCAM enhances proliferation rates of carcinoma cells [34] , [40] , presumably mediated via direct nuclear signaling of its proteolytically cleaved intracellular domain EpICD [41] , and via c-Myc and the cell cycle regulators cyclin A and E [42]–[44] . Most of these functional data were obtained in cell or tissue culture systems and via EpCAM overexpression . In contrast , in vivo and loss of function studies are scarce . No EpCAM mouse mutants have been reported so far . In zebrafish , EpCAM ( Tacstd ) mutants were generated via random retroviral insertions , characterized by delayed otolith formation in the developing inner ears [45] . In this study we generate maternal-zygotic zebrafish EpCAM mutants and chimeric embryos , revealing essential roles of EpCAM in the EVL for proper epithelial morphogenesis integrity during epiboly and skin development . Some of these roles are fulfilled in partial or complete redundancy with E-cadherin , whereas for others , EpCAM is absolutely indispensable . The molecular mechanisms underlying these in vivo functions are not completely clear . However , mutant cells display basal extensions of TJs and increased membrane levels of TJ components , coupled with reduced Ecad membrane localization and reduced protrusive basal activity . After skin formation , mutants also display hyper-proliferation of EVL and the underlying epidermal cells , which , however , seems to be a secondary consequence of the epithelial defects . We conclude that EpCAM acts as cell-cell adhesion molecule and a partner of E-cadherin , promoting both epithelial integrity and epithelial morphogenesis .
To identify genes with essential functions during zebrafish skin development , we performed an antibody-based screen on a previously described bank of retroviral insertional mutants [45] , staining larvae at 120 hours post fertilization ( hpf ) for the basal keratinocyte-specific transcription factor ΔNp63 , which is required for epidermal development in both fish and mammals [46]–[51] . The bank contained two mutant alleles of epcam ( ZFIN: tacstd; GenBank accession number NM212175 ) , hi2151 and hi2836 , which were described to have delayed otolith development ( Figure 1A and 1B ) [45] . In the case of hi2836 , the retroviral cassette is inserted upstream from exon 1 of the EpCAM gene , whereas the insertion in hi2151 is within exon 2 , causing a frame shift and premature termination of the protein that removes all annotated functional domains ( Figure 1D and 1E ) . In our assay , both alleles displayed aggregates of basal keratinocytes of undistinguishable strengths ( Figure 1A and 1B; and data not shown ) . Similar aggregates , as well as the characteristic delay in otolith development , were observed in embryos injected with an antisense morpholino oligonucleotide ( MO ) targeting the translational start site of epcam mRNA ( Figure 1C ) . epcam mutants kept under standard conditions ( 28°C ) usually died between day 5 and 7 of development , whereas they were sub-viable when kept under semi-sterile conditions and at lower temperature ( 25°C ) . However , keratinocyte aggregates of survivors remained visible throughout the first three weeks of development , and fish grew more slowly ( Figure S1B , S1C ) . Adult homozygous mutants were fertile and appeared morphologically normal , even in histological studies ( data not shown ) . epcam was previously shown to be expressed in migrating neuromast primordia , otic vesicles and olfactory placodes [52]–[54] . Here , we have extended these analyses with special focus on the skin . Maternally provided epcam mRNA was uniformly distributed in all cells of cleavage and early blastula stage embryos ( Figure 2A ) . After the onset of epiboly , the first of the morphogenetic movements of gastrulation , during which the yolk becomes progressively overgrown by the blastoderm [7] , epcam mRNA was restricted to the enveloping layer ( EVL ) , whereas deep cells had become epcam-negative ( Figure 2B–2D ) . In offspring of homozygous hi2151 or hi2836 mothers and heterozygous fathers , all embryos lacked epcam transcripts at cleavage stages ( compare Figure 2F with Figure 2E ) , whereas at early gastrulation , only 50% ( most likely M−/− , Z−/−; see below ) remained negative , while the other half ( M−/− , Z+/− ) had gained normal EVL expression ( Figure 2G ) . This indicates that zygotic epcam expression starts at blastula stages . In addition , it suggests that the hi2836 and hi2151 mutations cause a transcriptional blockade or mRNA instability , respectively , and that both alleles are null mutations . At 24 and 48 hours post fertilization ( hpf ) , in addition to the previously described epithelial structures ( see above; Figure 2H and 2K ) , we noticed persistent epcam expression in the EVL and expression in the basal epidermis ( Figure 2I and 2J ) , a derivative of the ventral ectoderm which during gastrula and early segmentation stages had been epcam-negative ( Figure 2C ) . This expression persisted throughout the investigated larval stages ( until 120 hpf ) . Also , according to RT-PCR analyses , epcam RNA was present in the skin of adult zebrafish ( data not shown ) . To investigate the subcellular distribution of EpCAM protein , we tried immunostainings with different antibodies against human or mouse EpCAM ( see Materials and Methods ) , however , none of them gave specific signals ( data not shown ) . Therefore , we injected early zebrafish embryos with mRNA encoding full-length zebrafish EpCAM fused to Green fluorescent protein ( GFP ) . The fusion protein was detected at the cell membrane of both EVL and deep cells ( Figure 2L and 2M ) . Early zebrafish development is regulated by a combination of maternal factors ( deposited in the egg during oogenesis ) and zygotic factors generated by the embryo itself . Crossing homozygous or heterozygous epcam mutant females with heterozygous males , we could generate mutants of three different genotypes: M+/− , Z−/− , which still have the maternally supplied epcam gene products , but lack the embryonic contribution ( zygotic effect ) , M−/− , Z+/− , which lack the maternal , but contain embryonic gene products ( maternal effect ) , and M−/− , Z−/− , which lack both the maternal and the embryonic supply ( maternal-zygotic effect; MZ−/− ) . By all means M−/− , Z+/− mutants had wild-type appearance , indicating that zygotic epcam gene products are sufficient for normal development . Nevertheless , defects of MZ−/− embryos were more severe and developed earlier than in zygotic mutants , indicating that maternally supplied gene products can partly take over the role of zygotic epcam: whereas skin aggregates in zygotic mutants only developed during the second day of development ( data not shown ) , in MZ−/− mutants , they were already apparent at mid-segmentation ( 16 hpf; Figure 3A and 3B ) , while later , skin aggregates were larger ( Figure S1A ) , and high numbers of shed skin cells were found floating in the chorion ( starting at approximately 16 hpf; see Figure 3G for 36 hpf ) . At 16 hpf , aggregates often occurred in the tailbud region , where the tail grows out . Here , the skin is most likely exposed to highest mechanical pressure and/or undergoes most dramatic epithelial morphogenesis ( Figure 3B ) . To investigate cell aggregates in greater detail , we took advantage of a transgenic zebrafish line in which EVL cells are labeled by GFP [55] . Our analysis showed that the early skin aggregates in MZ−/− embryos primarily consisted of EVL cells , which had acquired a roundish shape and had piled up on each other . In contrast , p63-positive basal cells underneath the foci seemed unaltered ( Figure 3C–3E ) , and only formed aggregates much later ( see Figure S1A for 48 hpf ) . At these later stages , epcam is expressed both in EVL and basal cells ( see above; Figure 2J ) . To distinguish whether the late aggregation of basal cells is caused by a loss of EpCAM in basal cells themselves , or by its loss in the overlying EVL cells , we generated chimeric embryos , transplanting basal MZ−/− cells into wild-type hosts and vice versa [56] . Strikingly , even largest clones of mutant basal cells were organized normally when present in a wild-type environment ( compare Figure 3I with Figure 3H ) , whereas clones of wild-type basal cells in mutant hosts formed aggregates indistinguishable from those in non-chimeric mutants ( Figure 3J ) . In sum , this indicates that EpCAM from EVL cells is required for proper epithelial organization both within the enveloping layer per se and in the underlying layer of basal keratinocytes . Elevated EpCAM levels in transformed tissues are thought to promote cell proliferation , contributing to carcinoma progression [34] , [40] . To determine proliferation rates in zebrafish epcam mutants , we carried out Bromodeoxyuridine ( BrdU ) incorporation studies in combination with EVL or epidermal-specific markers [56] . During somitogenesis ( 16 hpf ) , when EVL aggregation and cell shedding is already apparent , we could not detect any difference in the number of BrdU labeled cells between mutants and their WT siblings ( Figure 4A and 4B ) . At 24 hpf , proliferation rates in both the EVL and the basal layer of epcam mutants were slightly elevated , while at 48 hpf , this difference only persisted in the EVL , but not in the basal layer ( Figure 4A and 4B ) . Strikingly , aggregates of mutant EVL or basal cells displayed BrdU incorporation rates as in non-affected regions of the skin ( Figure 4C; and data not shown ) . Together , this suggests that cell aggregates in epcam mutants are not due to hyper-proliferation and that , in turn , hyper-proliferation might be a secondary consequence of compromised epithelial integrity . At 24 hpf and later , we also observed increased numbers of leukocytes in the skin of MZepcam mutants ( Video S1 , Video S2; and data not shown ) , similar to the recently described defects in zebrafish mutants lacking the Hepatocyte growth factor activator inhibitor Hai1 [56] , [57] . However , genetic ablation of the myeloid lineage in MZepcam mutants with pu . 1 antisense MOs [58] did not ameliorate the skin defects , ruling out that they are secondary consequences of enhanced skin inflammation ( data not shown ) . In hai1 mutants , skin invasion by innate immune cells might be triggered by the apoptosis of skin cells [56] . However , according to TUNEL stainings , even the skin aggregates of EpCAM mutants only displayed moderately increased numbers of apoptotic cells after 48 hpf ( Figure 4D; data not shown ) , making such a mechanism rather unlikely . To test whether leukocytes are activated as a result of compromised skin barrier and enhanced infection , we compared wild-type and mutant embryos kept under semi-sterile conditions or after incubation in water contaminated with bacteria . Under semi-sterile conditions , wild-type and mutant embryos displayed identical patterns of leukocyte distribution , revealed via leukocyte-specific-plastin ( lcp1 ) [59] , [60] in situ hybridization at 48 hpf ( Figure S2A , S2B ) . However , after bacterial challenge for 2 hours , the skin of epcam mutants contained much more inate immune cells ( Figure S2D ) than in challenged wild-type controls ( Figure S2C ) or un-challenged mutant siblings ( Figure S2B ) . In sum , these data suggest that loss of EpCAM primarily affects epithelial properties of the enveloping cell layer , whereas dysmorphology of the basal layer , hyper-proliferation , apoptosis , infection and inflammation are later or secondary consequences . The EVL-specific defects of MZepcam mutants during segmentations stages prompted us to carry out more thorough analyses of this cell lineage during earlier development . During epiboly , cells throughout the EVL flatten out and increase their apical and basal surfaces [8] , [9] , while marginal EVL cells constrict , involving actin and myosin 2 that is localized in the yolk cytoplasm along the margin of the EVL [10] . In MZepcam mutant embryos , this constriction occurred at positions slightly closer to the animal pole than in wild-type embryos , resulting in an extrusion of the vegetal-most part of the yolk at mid gastrula stages ( Figure 5A and 5B ) and , sometimes , in embryonic death . This suggests that loss of EpCAM might specifically affect the vegetal-wards spreading of the EVL , but not the actin-myosin-dependent constriction of marginal EVL cells . Compromised EVL epiboly as a result of reduced constrictions at the EVL margin has recently been described for embryos after knock-down of msn1 , the zebrafish ortholog of the Drosophila Ste20-like kinase Misshapen that is required for actin/myosin 2 recruitment , or after treatment with the specific myosin 2 inhibitor blebbistatin [10] . In contrast , phalloidin stainings of the actin cytoskeleton revealed normal constrictions of marginal EVL cells in MZepcam mutants ( Figure S3 ) . However , MZepcam mutants did display a significant reduction in yolk coverage by the EVL at late gastrula stages ( 77±4 . 9% ( n = 9 ) versus 89±4 . 7% ( n = 10 ) in wild-type embryos of the same age; Figure 5C , 5D , and 5G ) , and a corresponding reduction in the average surface of individual EVL cells ( Figure 5I , 5J , and 5K ) . Epiboly of deep cells was similarly delayed in MZepcam mutants ( 72±4 . 8% ( n = 9 ) versus 83±3 . 1% ( n = 10 ) in wild type embryos; Figure 5C , 5D , and 5G ) , while the distance between the marginal borders of the EVL and the deep cell layer was as in wild-type embryos ( Figure 5E , 5F , and 5H ) . Furthermore , and most strikingly , whereas the lateral sides of marginal and , to a lower extent , equatorial wild-type EVL cells appeared ruffled , indicating the presence of ( basal; see below ) cellular protrusions , MZepcam mutant cells lacked these ruffles ( Figures 5I and 5J and Figure 6A–6G ) . Ruffles could be at least partly restored by injection of synthetic epcam mRNA into mutant embryos ( Figure 6G–6I ) . However , no rescue was obtained upon epcam re-introduction into single EVL cells ( Figure 6J; n = 0/13 ) , suggesting that EpCAM does not act in a strictly cell-autonomous manner , but is most likely also required in the neighboring cells to allow proper ruffle formation . Together , these data indicate that EpCAM is required for processes of epithelial morphogenesis driving the cell shape changes and spreading of the EVL during zebrafish epiboly . To further investigate the cellular basis of the epithelial defects of MZepcam mutants , we performed immunohistochemistry and transmission electron microscopy ( TEM ) . Consistent with the ruffles visualized via phalloidin stainings ( see above; Figure 5I ) , TEM revealed protrusions at the basal side of wild-type EVL cells ( Figure 7A–7D ) . These protrusions started to form during early gastrulation stages ( Figure 7A ) , increased in length during gastrulation ( Figure 7B–7D ) , and shortened again during segmentation stages ( Figure 7F ) . They were in tight physical contact with the basal side of neighboring EVL cells , and even formed in most marginal EVL regions that are devoid of underlying deep cells ( Figure 7B ) . In agreement with the altered actin pattern ( Figure 5J ) , these basal protrusions were much broader and shorter in MZepcam mutants ( Figure 7E ) . TEM sections further revealed that the closely sealed apical junctional complexes ( AJCs ) of EVL cells were basally extended in MZepcam mutants compared to wild-type controls ( Figure 7G–7M ) . This difference was apparent throughout all investigated developmental stages from mid gastrulation through day 5 of development . However , desmosomes appeared morphologically unaltered ( Figure 7G and 7H; and data not shown ) . In addition , consistent with the basal extension of TJs , immunohistochemistry revealed an increase in the staining intensity for Tight junction protein 1 ( Tjp1/ZO1 ) [61] in the lateral membranes of MZepcam mutant EVL cells ( Figure 8A and 8B ) . Supporting results were obtained in EpCAM gain-of-function studies in madine-darby canine kidney ( MDCK ) cells , which upon transfection with GFP-EpCAM displayed reduced membranous signals for the TJ components Tjp1 and Occludin , whereas desmoplakin stainings appeared unaltered ( Figure S4 ) . However , opposite alterations were observed for Ecad and its cytoplasmic binding partners α- and β-catenin ( Figure 8C–8H ) , all of which displayed reduced membranous staining in MZepcam mutant EVL cells . In addition , perinuclear Ecad staining in the Golgi apparatus ( Figure 8I ) was strongly reduced in mutant cells ( Figure 8D ) compared to wild-type controls ( Figure 8C ) . Together , these data indicate that EpCAM promotes the presence of cadherin-catenin complexes in the basolateral domain of EVL cells , whereas it opposes the presence of TJ proteins . In line with these differential effects , EpCAM was co-localized with Ecad in lateral ( Figure 8J ) as well as basal membranes ( Figure 8M ) of wild-type EVL cells , whereas Tjp1 was localized apical of the EpCAM domain ( Figure 8K and 8L ) , consistent with results obtained in cultured epithelial cells [62] . To investigate whether compromised basal protrusion formation in MZepcam mutants might be caused by this gain of TJPs or loss of E-cadherin , we inactivated zebrafish tjp1–3 [14] , [61] via MO injection , and re-introduced E-cadherin by injecting different mRNAs or plasmid DNAs encoding mouse E-cadherin ( see Materials and Methods ) . However , neither of the treatments led to a significant restoration of ruffle formation ( Figure S5; and data not shown ) , suggesting that the molecular effects of EpCAM might be more complex . Complementing the failed rescue experiments described above , we next analyzed whether the defects of MZepcam mutants get enhanced upon concomitant loss of the ( remaining ) E-cadherin . For this purpose , different amounts of ecad MO were injected into MZepcam mutant embryos . In contrast to epcam , ecad is expressed both in the EVL and in the deep cells . Strong ecad morphants and ecad null mutants display defects during epiboly movements of deep cells ( see Introduction ) , whereas the EVL appeared normal ( Figure 9C and 9G ) . In striking contrast , and unlike uninjected MZepcam controls ( Figure 9B and 9F ) , MZepcam mutants injected with high amounts of ecad MO displayed severely compromised cell-cell adhesion of EVL cells at early gastrula stages ( 5 . 5 hpf; Figure 9H ) , leading to embryo lysis at mid gastrulation ( Figure 9D ) . This effect was strictly layer-autonomous and independent of E-cadherin in the underlying deep layer , as indicated by the disrupted morphology of the EVL in genetic mosaics with a mutant EVL and wild-type deep layers ( Figure 9J ) , but a wild-type morphology in the opposite combination ( Figure 9I ) . This indicates that , while dispensable per se , EpCAM and Ecad together are required for intercellular adhesion within the EVL . As described above , EpCAM and Ecad are not only co-localized at the lateral , but also at the basal membranes of EVL cells , facing the underlying deep cells ( Figure 8M ) . Previous studies have shown that Ecad is primarily required to mediate the anchorage of deep cells to the inner surface of the EVL during radial intercalation processes driving the epiboly of deep cells ( see Introduction ) . To test whether EpCAM from EVL cells might also be involved in this anchorage , we carried out genetic interaction studies , injecting ineffectively low amounts of ecad MO into wild-type or MZepcam mutant embryos . In mid gastrula wild-type embryos ( 80% epiboly stage ) injected with such low amounts of ecad MO , epiboly of deep cells was normal ( Figure 10A; n = 25/25; compare with Figure 5C ) . In contrast , and unlike the very moderate deep cell epiboly defects of un-injected MZepcam mutants ( Figure 5D ) , mutants injected with the same low amounts of ecad MO displayed an arrest of deep cell epiboly at the equator of the embryo ( Figure 10B; n = 27/29 ) , similar to the defects of embryos injected with highest amounts of ecad MO ( data not shown; n = 20/21 ) [10] . Time-lapse recording at early gastrulation stages further revealed crucial differences in the behavior of deep cells . In un-injected embryos or in wild-type embryos injected with low amounts of ecad MO , radially intercalating deep cells remained in the exterior layer of the deep layers , most likely stably attached to the inner surface of the EVL ( Figure 10E and data not shown; n = 6/6; 3 videos ) , whereas in MZepcam mutants injected with low amounts of ecad MO , cells usually moved back into more interior layers of the deep layers ( Figure 10F; n = 4/5; 3 videos ) , similar to the situation after complete knock-down of ecad ( Figure 10G; n = 5/5; 2 videos ) . Interestingly , this effect on deep cell behavior again seemed to primarily depend on EpCAM and Ecad function within the overlying EVL . Thus , in genetic mosaics , deep MZepcam mutant cells injected with low amounts of ecad MO displayed the same epiboly behavior like their wild-type neighbors , which was compromised when the host and the EVL were mutant ( Figure 10C; n = 5/5 ) , but normal when the host and the EVL were wild-type ( Figure 10D; n = 6/6 ) . Together , this suggests that EpCAM from the EVL supports the function of Ecad to drive epiboly of deep cells .
Apart from zebrafish , no EpCAM mutants have been described in any other organism . Two mutant zebrafish alleles were isolated , both of which are most likely EpCAM nulls ( Figure 1 and Figure 2 ) . Maternal-zygotic ( MZ ) mutants lacking both maternally and zygotically supplied epcam gene products display early epiboly and later skin defects , whereas epiboly seems to be normal in zygotic mutants and epcam morphants . The weaker phenotype of zygotic mutants suggests that maternally supplied epcam gene products , either mRNA or protein , are sufficient to drive epiboly . The lack of epiboly defects in epcam morphants further points to maternal EpCAM protein . Translational start site morpholinos as used here target both maternally and zygotically provided mRNA , but not maternal protein , suggesting that the weaker phenotype of epcam morphants compared to MZepcam mutants is due to the presence of maternally provided EpCAM protein . EpCAM-specific antibodies will be required to test this notion . In addition to the epiboly and skin defects that are the focus of this work , epcam zebrafish mutants display compromised otolith formation in the developing inner ears ( Figure 1 and [45] ) . The cellular and molecular basis of this phenotype is unclear , however , similar otolith defects have been described for zebrafish mutants in the tight junction component Claudinj [65] . Another site of prominent zygotic zebrafish epcam expression are the neuromasts of the lateral line ( Figure 2 ) . According to a previous report , loss of EpCAM function by morpholino injection leads to defects in neuromast deposition during the posterior-wards migration of the lateral line primordium [53] . Although nicely in line with the concept of a role of EpCAM during epithelial morphogenesis , our analysis of MZepcam mutants could not confirm this phenotypic trait ( Figure S6 ) . Indeed , Villablanca et al . had to inject highest amounts of morpholinos to obtain the phenotype , suggesting that it might have been an unspecific effect . During gastrulation , epcam is exclusively expressed in cells of the enveloping layer ( EVL; see Introduction ) . Nevertheless , MZepcam mutants display moderate defects during epiboly movements of both the EVL and the underlying deep cell layers ( Figure 5 ) . Our chimeric analyses in combination with E-cadherin inactivation indicate that the deep cell defects are secondary consequences of failed EpCAM function in the EVL , whereas the EVL defects themselves are layer autonomous ( see below ) . During their spreading over the yolk , EVL cells normally change their shape and flatten out along the radial axis to increase their horizontal size . The cellular mechanisms underlying this transition are largely unknown . Here , we show that they involve basal protrusive activity of EVL cells , and that this activity is severely compromised in MZepcam mutants , leading to an overall reduction in the average horizontal size of mutant EVL cells ( Figure 5 ) . Recently , a similar impairment of EVL epiboly has been described for MZpou5f1 mutants . However , in this case , epiboly defects are accompanied by increased , rather than reduced protrusive activity of EVL cells [66] . This indicates that both gain and loss of protrusive activity can compromise epiboly . Future experiments have to address the functional connection between pou5fl and epcam . In MZepcam mutants , the lack of basal activity is accompanied by a basal extension of apical junctional complexes ( AJCs ) ( Figure 7 ) , and by increased levels of TJ components in apico-basal membranes , whereas levels of E-cadherin ( Ecad ) and catenins are reduced ( Figure 8 ) . These effects are consistent with the co-localization of EpCAM and Ecad in the basolateral membranes of wild-type EVL cells , and their exclusion from the apical Tjp1 domain ( Figure 8 ) . Together , this suggests that EpCAM pushes the molecular composition of apico-basal membranes from TJ towards AJ components . In addition to the membrane , mutants displayed reduced perinuclear Ecad staining in the Golgi apparatus , suggesting that EpCAM also affects de novo synthesized Ecad protein . Currently , we cannot distinguish which of the observed phenotypic traits are primary , and which secondary . However , neither knockdown of tjp1–3 nor re-introduction of Ecad led to an alleviation of the mutant phenotype or a restoration of basal protrusions , suggesting that EpCAM might have multiple targets and interaction partners , rather than acting via a single mediator . Generally , protrusion formation is driven by rearrangements of the cortical cytoskeleton that are coordinated with local modulations in cellular adhesiveness [67] . Interestingly , according to our TEM studies , the protrusions of EVL cells primarily attach to the basal membrane of adjacent other EVL cells , rather than to underlying deep cells or extracellular matrix components , while protrusions remain much shorter and broader in MZepcam mutants ( Figure 7 ) . In this light , it is tempting to speculate that the thinning of EVL cells underlying EVL epiboly might be driven by the “crawling” of basal protrusions on the basal surface of adjacent EVL cells , and that EpCAM might be particularly involved in modulating cell-cell adhesiveness and cortical tension in basolateral domains of EVL cells ( Figure 11A and 11B ) . In contrast to cell culture studies identifying EpCAM as a functional antagonist of Ecad [20] , [35] , we found that zebrafish EpCAM and Ecad tightly interact and enhance each other's effects to promote EVL integrity as well as deep cell epiboly . While each of them per se was dispensable for EVL integrity , combined loss of both EpCAM and Ecad led to severe and layer-autonomous EVL disassembly during early gastrulation stages ( Figure 9 ) . This indicates that EpCAM and Ecad play essential , yet redundant roles to mediate proper cell-cell adhesion among EVL cells ( Figure 11D ) . Similarly , partial inactivation of Ecad , which had no effect in a wild-type background , led to a complete arrest of deep cell epiboly in MZepcam mutants ( Figure 10A and 10B ) . Interestingly , also here , the effect depended purely on EpCAM and Ecad function in the EVL ( Figure 10C and 10D ) . On the cellular level , the epiboly arrest was accompanied by a failure of intercalating deep cells to remain in the external deep layer directly underneath the EVL ( Figure 10E–10G ) , pointing to defects in the adhesion between EVL and underlying deep cells , thus , across different layers ( Figure 11C ) [12] . In this light , both the tissue integrity defects caused by loss of EpCAM function in the background of complete ecad inactivation , and the tissue morphogenesis defects caused by loss of EpCAM function in the background of partial ecad inactivation , seem to result from reduced intercellular adhesion . But what are the reasons for the exclusive effects on epiboly , but not EVL-EVL adhesion , in the ecad hypomorphic background ? Differential contributions of Ecad and EpCAM to EVL-EVL versus EVL-deep cell binding could be one factor . EVL-EVL cell adhesion involves apical junctional complexes and desmosomes , and might therefore be less dependent on “free” basolaterally localized EpCAM and Ecad than EVL-deep cell adhesion , which lacks such junctions . Alternatively or in addition , the deep cell epiboly arrest might be due to combined effects on cell adhesiveness and its dynamic regulation . During gastrulation , deep cells undergo massive spatial rearrangements in addition to radial intercalations , one of the driving forces of epiboly . For instance , they simultaneously move from ventrolateral into dorsal regions of the embryo to form the embryonic body axis [67] . Therefore , neighborships between EVL and deep cells need to change rather rapidly . In this light , it is feasible to speculate that EpCAM might also be involved in regulating the dynamic dis- and re-assembly of EVL-deep cell contacts to allow proper morphogenesis . Cadherin contacts can be regulated at multiple levels [68] , and membrane localization of Ecad has recently been shown to be dynamically regulated via endocytosis and recycling during gastrulation movements of deep cells in zebrafish and frog embryos [67] , [69] , [70] . Furthermore , the cytoplasmic domain of EpCAM contains an NPXY internalization motif [19] , which could possibly trigger the concomitant endocytosis of Ecad , comparable to the recently revealed role of the transmembrane protein FLRT3 in Xenopus embryos [70] . In sum , we propose that EpCAM and Ecad play rather similar , and partially redundant roles during zebrafish gastrulation . Furthermore , they seem to mutually influence each other , with a positive effect of EpCAM on membranous Ecad levels and , possibly , Ecad synthesis and recycling . Subject to dynamic regulation , cadherins are well known for their multiple , and seemingly contrary effects , not only promoting cell-cell adhesiveness and tissue integrity , but also cellular plasticity and cellular “grip” during morphogenesis . Similar mechanisms might underlie EpCAM's reported “double face” function also revealed in this work . Future biochemical studies will be necessary to elucidate the molecular basis of the EpCAM – E-cadherin partnership . Since they play largely redundant roles , they do not necessarily have to physically interact at all . They could for instance mediate different modes of adhesion , cadherins in connection with the highly structured actin cytoskeleton and EpCAM more independently of the cytoskeleton [18] , [34] . Consistent with this notion , our immunolocalization studies indicate a salt-and-pepper like distribution of EpCAM and Ecad , rather than complete co-localization in the basolateral membrane of EVL cells ( Figure 8J ) . However , it is interesting to note that in the context of nuclear signaling , complex formation between the intracellular domain of EpCAM and β-catenin has been observed [41] . Furthermore , more indirect mechanisms might be at play , involving adapter or signaling proteins [71] . Similar effects of EpCAM might also account for the later defects in the mutant skin . From mid-segmentation onwards ( 14 hpf ) , the outer EVL , now also called periderm , is juxtaposed against a single layer of basal keratinocytes , which derive from the ventral ectoderm , a subpopulation of deep cells initially located in ventral-animal regions of the pregastrula embryo [5] . Both layers display epcam expression , and both display compromised epithelial integrity in epcam mutants . However , the defects in the periderm are already apparent when the basal layer is still normal ( 16 hpf; Figure 3C–3E ) . This later periderm defects are very similar to those caused by combined loss of EpCAM and E-cadherin during gastrulation . It remains unclear , however , why in contrast to the early stages and despite its maintained expression , E-cadherin fails to compensate for loss of EpCAM after skin formation . Furthermore , consistent with the aforementioned effect of EpCAM from the EVL on epiboly movements of the underlying deep cells , our chimera analyses reveal that defects in the basal layer are due to a non-autonomous effect from the EVL ( Figure 3H and 3I ) . Also , similar to the situation during epiboly , epcam mutants display a persistent basal extension of AJCs in EVL cells during such later stages ( Figure 7J and 7L ) . Although the role of tight junctions in cell adhesion is still disputable , it is generally accepted that their impact compared to adherence junctions and desmosomes is minor [72] , [73] . In this light , and in light of the observed negative effect of the MZepcam mutation on membranous Ecad levels and cell-cell adhesiveness during gastrulation , we assume that the epithelial defects of the mutant periderm are due to reduced , rather than enhanced cell-cell adhesiveness . In addition , defects might be enhanced by reduced epithelial plasticity . Consistent with this notion , initial epithelial lesions in the periderm of epcam mutants were most prominent on the tailbud ( Figure 3B ) and the head , regions that undergo massive morphogenesis and that are exposed to highest mechanical stress . Very similar shedding of skin cells was previously described for hai1 mutants , which display partial epithelial-mesenchymal transitions of basal keratinocytes [56] . However , no mesenchymal-like behavior was observed in time-lapse recordings of basal keratinocytes or EVL cells of epcam mutants ( K . S . and M . H . , unpublished observations ) . In sum , these data suggest that similar to the defects during epiboly , the later skin defects of epcam mutants are due to compromised intercellular adhesion and cellular plasticity of epithelial cells . In light of the reported roles of EpCAM in multiple other cellular processes , such as cell proliferation and cell differentiation , we also investigated whether and when skin cells of MZepcam mutants develop corresponding defects . However , in contrast to other reported zebrafish skin mutants [74] , EVL and basal cells showed normal levels of terminal differentiation markers ( Keratin , ATPases; Figure S7 ) . Also , although EVL and basal cells displayed an up to 50% increase in proliferation , this hyper-proliferation only became apparent several hours after the epithelial defects ( Figure 4B ) . Furthermore , aggregates of both EVL and basal cells displayed similar rates of BrdU incorporation like regions remote of the aggregates ( Figure 4C ) . An interesting side outcome of the BrdU incorporation studies , also confirmed by time-lapse recordings ( K . S . and M . H . , unpublished data ) , was the demonstration that EVL cells divide at all . This had not been shown before . Rather , it was widely believed that the EVL grows by cell shape changes , and that it later sloughs off , being replaced by cells deriving from basal cells [5] . However , our data suggest that the growth of the two larval zebrafish skin layers might involve layer-autonomous , horizontal cell divisions , rather than or in addition to vertical growth/replacement , the typical concept of stratified epithelia . In conclusion , our studies indicate that loss of EpCAM in the developing zebrafish skin primarily leads to compromised epithelial plasticity and adhesiveness , whereas hyper-proliferation is a secondary consequence , possibly due to the loss of contact inhibition . Similarly , the higher susceptibility to bacterial infections and enhanced inflammation of epcam mutants ( Figure S2 , Video S1 , Video S2 ) are most likely secondary consequences of compromised skin integrity . In contrast to embryonic and larval stages , however , we found EpCAM to be largely dispensable after metamorphosis , when the skin has become multi-layered . The reason for this later dispensability remains unclear . Functional redundancy with other genes could be one explanation . In mammals , an EpCAM homologue called Trop2/Tasctd2 exists , which shows approximately 50% sequence identity to EpCAM , and which has most likely evolved via a retrotranspositional event [75] . In contrast , searches of zebrafish databases failed to identify further EpCAM-related sequences [53] ( M . H . and K . S . , unpublished data ) , suggesting that zebrafish epcam is a single gene . Interestingly , adult zebrafish epcam mutants even displayed normal cutaneous wound healing ( K . S . and M . H . , unpublished data ) , indicating that despite its reported elevated expression during epithelial regeneration of the mammalian liver and kidney [24] , [28] , EpCAM is not required for epithelial morphogenesis that takes place during zebrafish skin repair . Future experiments have to reveal whether epcam mutants are less susceptible to epithelial tumor formation , which would reinforce its suitability as a target for anti-carcinoma therapies .
The EpCAM alleles hi2836 and hi2151 were isolated during an insertional mutagenesis screen [76] . Unless noted otherwise , the hi2151 allele was used . hi2151 mutants were obtained from heterozygous ( Z+/− ) or homozygous parents ( MZ−/− ) . The Tg ( krt4: egfp ) gz7 and Tg ( βactin:hras-egfp ) ( allele vu119 ) transgenic lines have been described previously [55] , [77] . The full-length coding region of zebrafish EpCAM cDNA ( GenBank accession number NM_213175 ) was amplified via RT-PCR and cloned into pCRII-TOPO ( Invitrogen ) or upstream of eGFP into pCS2+ plasmid [78] . To generate pCS2-Ecad-HA , the full-length coding region of mouse E-cadherin was amplified and cloned upstream of HA into pCS2+ . For antisense probe synthesis , pCRII-EpCAM was linearized with XbaI and transcribed with SP6 RNA polymerase . For sense RNA synthesis for microinjection , pCS2-EpCAM-eGFP , pCS2-Ecad-HA and pCS2-mCherry ( with farnesylation signal; generous gift from Erez Raz ) were linearized with NotI and transcribed using SP6 Message Machine kit ( Ambion ) ; mGFP mRNA [79] and GM130-GFP mRNA were generated as described [80] . For rescue experiments , EpCAM-eGFP or Ecad-HA mRNA were injected at 150 , 350 ( EpCAM ) or 100 µg/ml ( Ecad ) , respectively ( 1 . 5 nl per embryo ) , pCS2-EpCAM-eGFP , pCDNA3 . 1-Ecad-GFP [81] , pCS2-Ecad-HA , or pL31NU-Ecad-Venus DNA [82] at 350 µg/ml ( EpCAM ) or 100 µg/ml ( Ecad ) , respectively . In situ hybridizations were performed as previously described [83] , using probes for EpCAM and leukocyte-specific-plastin ( lcp1 ) [59] . Whole-mount immunostaining was carried out as described [83] , using fluorescently-labeled secondary antibodies or the Vectastain ABC kit ( Axxora ) for enzymatic detection . Antibodies , dilutions used and sources were as follows: anti-p63 ( 1∶200 , Santa Cruz ) , anti-GFP ( 1∶400 , Invitrogen ) , anti-RFP ( 1∶200; antibodies-online GmbH , ABIN132020 ) , anti-E-cadherin ( 1∶200 , BD Biosciences ) , anti-ZO-1 ( 1∶200 , Zymed ) , Alexa-Fluor-546 goat anti-mouse ( 1∶400 , Invitrogen ) and Alexa-Fluor-488 goat anti-rabbit ( 1∶400 , Invitrogen ) . Tested anti EpCAM antibodies: A-20 ( Santa Cruz ) , 1144 ( Epitomics ) , HO-3 [84] and C-215 [85] . For paraffin sectioning ( 8 or 16 µm ) , stained embryos were dehydrated in ethanol series and clearing in toluene , the specimens were infiltrated with paraffin , embedded , and sectioned . Epidermal cell proliferation was assessed by BrdU incorporation followed by combined anti-p63 and anti-BrdU immunostaining as described [56] . Apoptotic cells were visualized by TUNEL staining using in-situ cell death detection kit ( Roche ) . Phalloidin stainings of cortical actin cytokeleton were carried out with Alexa 488 or Alexa 594 Phalloidin ( 1∶200 , Molecular Probes ) , as described [10] . epcam MO ( 5′- GTGCAGAGACTTTCCGGCCATATTT-3′ ) was obtained from Gene Tools ( Philomath , OR ) and diluted in Danieau's buffer [86] . 1 . 5 nl of a 200 µM MO solution were injected per embryo at the 1 cell stage . The ecad MO was as described [87] . For complete knock-down , 1 . 5 nl of a 200 µM solution was injected , for synergistic enhancement studies , 1 . 5 nl of a 30 µM solution . The tjp1 , tjp2 and tjp3 MOs ( generous gifts from Matthias Köppen and Carl-Philipp Heisenberg; [14] ) were injected alone or together at 50 to 200 µM each ) ; the msn1 MO was as described [10] and injected at 200 µM . Clusters of mGFP-labeled basal keratinocytes were obtained by homotopic transplantation of approximately 50 non-neural ectodermal cells from Tg ( βactin:hras-egfp ) transgenic donor embryos into non-transgenic hosts at 6 hpf . Recipients were fixed at 36 hpf , subjected to anti-GFP and anti-p63 immuno-fluorescence staining , mounted in 1 . 5% low melting agarose and analyzed by confocal microscopy . For localization studies of EpCAM-eGFP on the basal side of EVL cells ( Figure 8 ) , deep cells of mCherry mRNA-injected cells were transplanted at the sphere stage into EpCAM-eGFP mRNA-injected hosts . Embryos were fixed at the 90% epiboly stage for anti-RFP and anti-GFP immunohistochemistry , sectioned , and analyzed via confocal microscopy . To distinguish whether for proper EVL adhesion , EpCAM and Ecad are required in the EVL cells themselves or in underlying deep cells ( Figure 9 ) , chimeric embryos were generated by transplanting deep cells at the sphere stage from mCherry-labelled wild-type or MZepcam donors into unlabelled MZepcam hosts injected with high amounts of ecad MO , or vice versa , followed by fixation at the 90% epiboly stage for anti-Cherry and phalloidin staining . To investigate whether for deep cell epiboly , Epcam and Ecad are required in the deep cells or in the EVL ( Figure 10 ) , cells from mCherry mRNA-injected wild-type or MZepcam mutant donors were transplanted next to cells from mGFP mRNA + low ecad MO-injected MZepcam mutant donors into unlabelled MZepcam hosts or MZepcam hosts injected with low ecad MO . Embryos were fixed at the 90% epiboly stage , and processed via anti-RFP and anti-GFP immunohistochemistry . For time-lapse in vivo imaging , embryos were mounted and recorded at a Zeiss Axiophot with Nomarski optics and a Hamamadzu Orca camera , as previously described [79] . 20-minutes videos were taken at lateral marginal regions , starting at shield stage ( 5 . 5 hpf ) , with 30 sec intervals . For Figure 10 , single images form the time-lapse video recordings were imported into Adobe Photoshop , and single cells were pseudo-colored to aid the presentation [11] . Fluorescent images were taken with a Zeiss Confocal microscope ( LSM510 META ) ; Transmission light microscopy was performed on a Zeiss Axiophot or Leica MZ-8 stereomicroscope . For transmission electron microscopy , wild-type and mutant fish were fixed with 2 . 5% glutaraldehyde in PBS for 30 minutes each at ambient temperature and then on ice . After washing with PBS , the larvae were post-fixed with 1% osmium tetroxide in 100 mM phosphate buffer pH 7 . 2 for 1 hour on ice , washed with H20 , stained with 1% aqueous uranylacetate for 1 hour , dehydrated in a graded series of ethanol and finally embedded in Epon . Ultrathin sections were stained with uranyl acetate and lead citrate and viewed in Philips CM10 electron microscope . | EpCAM is a well-established marker for carcinomas of epithelial origin and a potential target for immunotherapy . In vitro analyses have implicated EpCAM in a plethora of different cellular processes , such as adhesion , motility , proliferation , differentiation , and signaling . Strikingly , depending on the context , EpCAM displayed rather opposite effects , either promoting or attenuating cell–cell adhesion versus cell migration and tissue invasion , a phenomenon described as the “double-face” of EpCAM . However , the in vivo relevance of its different effects remained largely unclear . Here , we present the first genetic analysis of EpCAM function in vivo , based on loss-of-function mutants in the zebrafish . As it is in mammals , zebrafish EpCAM is expressed in simple epithelia . Mutant embryos display defects both in epithelial morphogenesis and in epithelial integrity . Reduced epithelial morphogenesis is accompanied , and possibly caused , by an extension of apical junctional complexes and compromised basal protrusive activity . Furthermore , mutant epithelia display alterations in the relative abundance of adherence junction versus tight junction components . In addition , EpCAM tightly cooperates with E-cadherin and has a previously unrecognized trans effect on the morphogenesis and integrity of underlying cell layers . Cell differentiation and proliferation in EpCAM mutants are not , or only secondarily , affected . During later development and adulthood , EpCAM is largely dispensable , reinforcing its suitability as a target for anti-carcinoma immunotherapy with minimal side effects . | [
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] | 2009 | The Epithelial Cell Adhesion Molecule EpCAM Is Required for Epithelial Morphogenesis and Integrity during Zebrafish Epiboly and Skin Development |
Although misfolding of normal prion protein ( PrPC ) into abnormal conformers ( PrPSc ) is critical for prion disease pathogenesis our current understanding of the underlying molecular pathophysiology is rudimentary . Exploiting an electrophysiology paradigm , herein we report that at least modestly proteinase K ( PK ) -resistant PrPSc ( PrPres ) species are acutely synaptotoxic . Brief exposure to ex vivo PrPSc from two mouse-adapted prion strains ( M1000 and MU02 ) prepared as crude brain homogenates ( cM1000 and cMU02 ) and cell lysates from chronically M1000-infected RK13 cells ( MoRK13-Inf ) caused significant impairment of hippocampal CA1 region long-term potentiation ( LTP ) , with the LTP disruption approximating that reported during the evolution of murine prion disease . Proof of PrPSc ( especially PrPres ) species as the synaptotoxic agent was demonstrated by: significant rescue of LTP following selective immuno-depletion of total PrP from cM1000 ( dM1000 ) ; modestly PK-treated cM1000 ( PK+M1000 ) retaining full synaptotoxicity; and restoration of the LTP impairment when employing reconstituted , PK-eluted , immuno-precipitated M1000 preparations ( PK+IP-M1000 ) . Additional detailed electrophysiological analyses exemplified by impairment of post-tetanic potentiation ( PTP ) suggest possible heightened pre-synaptic vulnerability to the acute synaptotoxicity . This dysfunction correlated with cumulative insufficiency of replenishment of the readily releasable pool ( RRP ) of vesicles during repeated high-frequency stimulation utilised for induction of LTP . Broadly comparable results with LTP and PTP impairment were obtained utilizing hippocampal slices from PrPC knockout ( PrPo/o ) mice , with cM1000 serial dilution assessments revealing similar sensitivity of PrPo/o and wild type ( WT ) slices . Size fractionation chromatography demonstrated that synaptotoxic PrP correlated with PK-resistant species >100kDa , consistent with multimeric PrPSc , with levels of these species >6 ng/ml appearing sufficient to induce synaptic dysfunction . Biochemical analyses of hippocampal slices manifesting acute synaptotoxicity demonstrated reduced levels of multiple key synaptic proteins , albeit with noteworthy differences in PrPo/o slices , while such changes were absent in hippocampi demonstrating rescued LTP through treatment with dM1000 . Our findings offer important new mechanistic insights into the synaptic impairment underlying prion disease , enhancing prospects for development of targeted effective therapies .
Prion diseases constitute a group of transmissible neurodegenerative disorders with the spectrum encompassing several human phenotypes , the most common being Creutzfeldt-Jakob disease ( CJD ) , as well as a number of animal diseases including bovine spongiform encephalopathy ( “mad cow” disease ) and scrapie in sheep [1 , 2] . Regardless of disease phenotype , misfolding of PrPC into disease-associated conformers ( herein collectively designated PrPSc ) , with their subsequent aggregation and accumulation , appears critical to pathogenesis although the precise neurotoxic species and how such species provoke neuronal dysfunction and loss leading to the onset of clinical illness remain unresolved . The precise composition of the infectious unit or “prion” also remains to be determined , although considerable evidence supports that PrPSc is the major , if not exclusive , component ( the “protein only” hypothesis ) [3] . Historically , PrPSc has been considered to be highly protease-resistant ( designated PrPres after protease treatment ) but recent evidence supports the existence of a broader spectrum , including protease-sensitive conformers , which most likely contribute to pathogenesis and may comprise up to 90% of misfolded prion protein in diseased brains [4 , 5] . The primary function of PrPC in the central nervous system remains uncertain although a key role for this glycosylphosphatidylinositol-anchored glycoprotein in synaptic physiology and memory has been described [6] . Aligned to such functions , PrPC has been reported as having a predominant synaptic localisation [7] , with important influences on voltage-gated calcium ( Ca2+ ) [8] and N-methyl-D-aspartate receptor ( NMDAR ) ion channels [9] , as well as LTP [10] . LTP is a use-dependent neurophysiological process , enhancing the strength of synaptic connection , with hippocampal CA1 region LTP directly correlating with episodic memory acquisition [11] . Critical to LTP-type synaptic plasticity and episodic memory generated in the hippocampus are α-amino-3-hydroxy-5-methyl-4-isoxazoleproprionic acid receptor ( AMPAR ) and NMDAR ion channels , as well as metabotropic glutamate receptors with signal transduction mediated through pathways including calcium-regulated phosphorylated extracellular signal–regulated kinase ( pERK ) and phosphorylated cAMP response element binding protein ( pCREB ) , which alter DNA transcription with consequent ultrastructural and receptor changes at synapses [12] . Our group [13] and others [14 , 15] have shown in prion animal models evidence of early selective hippocampal damage , with synapses becoming significantly disrupted and retracted from the mid-incubation period [15–17] . Of particular relevance , selective and progressive impairment of LTP in the CA1 region of the hippocampal stratum radiatum has been demonstrated in vivo in ME7 prion infected mice from 44–70% of the incubation period [14] , with early loss of hippocampal pyramidal neuronal synapses shown to correlate with first evidence of disturbances in hippocampal-dependent behaviour [15] . Additionally , studies have revealed that impairment of LTP coincides with the earliest detection of PrPSc , slightly prior to morphological evidence of synaptic loss or neuropil vacuolation [14 , 18] , indicating that impairment of hippocampal CA1 region LTP is a sensitive indicator of synaptic dysfunction in prion strains that cause early , prominent hippocampal damage and supporting the likelihood that PrPSc is directly synaptotoxic . Somewhat limiting our ability to better understand prion pathogenesis is the relative paucity of tractable , authentic models of acute prion neurotoxicity . Very simple in vitro cell culture models have demonstrated toxic effects of recombinant , soluble , oligomeric PrP enriched in β-sheet content [19] , as well as toxicity from highly “purified” PrPSc and proteinase treated PrPSc extracted from the brains of terminally sick rodents [20 , 21] . An in vivo model of acute neurotoxicity employing stereotaxic injection of recombinant full-length ovine PrP into the hippocampal CA2 region has been reported , with assessment for acute toxicity requiring morphological analysis approximately 24 hours later [22] . In addition , a model utilizing cultured organotypic cerebellar slice explants allowing assessment of factors that interfere with PrPSc replication and abrogate cerebellar granule cell loss has been described [23] , although this model relies entirely on de novo PrPSc propagation to generate neurotoxic species over an extended 5–7 week period . This ex vivo culture model is arguably therefore not ideal for assessing direct acute PrPSc neurotoxicity because PrPSc propagation can closely correlate with deleterious cellular events such as heightened oxidative stress [24] that may also contribute to pathogenesis thereby potentially confounding the delineation of a directly neurotoxic PrPSc species . Of particular interest is a recent study demonstrating that PrPSc species cause retraction and subsequent loss of dendritic spines in cultured hippocampal neurons following several hours of exposure to PrPSc preparations [25] . This study however , reported that the synaptotoxicity required expression of PrPC [25] leaving some uncertainty as to whether the neurotoxic PrPSc species were entirely those directly added to the culture or were different species generated through initial PrPSc propagation from host PrPC . Electrophysiological studies employing techniques to assess LTP are an established method to explore potential acute neurotoxic effects of ex vivo brain material derived from neurodegenerative disorders such as Alzheimer’s disease ( AD ) [26] . Herein we report the use of an electrophysiology paradigm to explore the acute synaptotoxicity of ex vivo prion preparations derived from terminal disease brains briefly superfused onto hippocampal slices . We found that PrPSc ( for convenience hereafter considered as synonymous with PrPres species with at least modest PK resistance ) is directly deleterious to LTP in the hippocampal CA1 region , with the degree of impairment approximating that observed during the natural evolution of prion disease in rodent models and independent of age of mice up to 11 months , with lysates from chronically M1000 prion infected cells ( MoRK13-Inf ) also inducing analogous acute synaptotoxicity . Additional detailed electrophysiological analyses suggested possible heightened pre-synaptic vulnerability to the acute synaptotoxicity , exemplified by impairment of post-tetanic potentiation ( PTP ) and correlating with failure of replenishment of the readily releasable pool ( RRP ) of vesicles during repeated high-frequency stimulation utilised for induction of LTP . Size fractionation chromatography demonstrated that synaptotoxic PrP correlated with PK-resistant species >100kDa , consistent with multimeric PrPSc , with levels of these species >0 . 006 μg/ml appearing sufficient to induce synaptic dysfunction . Biochemical studies confirmed that synaptotoxic PrPSc in WT slices reduces essential proteins required for the induction and maintenance of hippocampal LTP such as pERK , pCREB , synaptophysin and vesicular glutamate transporter 1 ( VGLUT1 ) , as well as the NMDAR NR2A and NR2B subunits and the GluA2 subunit of AMPAR . Importantly , the PrPSc acute impairment of LTP and PTP was largely PrPC independent , albeit with some noteworthy differences in the changes in key synaptic proteins and electrophysiological findings between wild type ( WT ) and Prn-p gene-ablated ( PrPo/o ) hippocampal slices , supporting the likelihood of non-PrPC dependent mechanistic pathways . Dose-response assessments using cM1000 revealed similar sensitivity to synaptic disruption in PrPo/o and WT hippocampal slices . Our findings offer important new pathophysiological insights into the synaptic impairment underlying prion disease , enhancing prospects for development of targeted effective therapies .
All animal handling was in accordance with National Health and Medical Research Council ( NHMRC ) guidelines . All experimental procedures were approved by The Florey Institute of Neuroscience and Mental Health Animal Ethics Committee ( Ethics number: 13–048 ) or the Biochemistry & Molecular Biology , Dental Science , Medicine ( RMH ) , Microbiology & Immunology , and Surgery ( RMH ) Animal Ethics Committee , The University of Melbourne ( Ethics number: 1312997 . 1 ) . To prepare hippocampal slices for multi-electrode array ( MEA ) studies , 12-week-old and 11-month-old WT C57 black 6J ( C57BL/6J ) female mice were used ( Animal Resource Centre , Western Australia ) , as well as 12-week-old female PrP knockout ( PrPo/o ) mice on a C57BL/6J background produced through 10 consecutive back-crossings of C57BL/6JX129/sv mice [27] . Mice were group caged , with 12-hour day-night light cycles and food and water provided ad libitum . Mouse brains were quickly collected following decapitation while under deep anaesthesia induced by isoflurane . 300μm dorsal horizontal brain slices were prepared using a vibratome ( Leica VT1200S ) in ice-cold continuously carboxygenated ( 5% CO2 and 95% O2 ) cutting solution ( 3mM KCl , 25mM NaHCO3 , 1 . 25mM NaH2PO4 , 206mM Sucrose , 10 . 6mM Glucose , 6 mM MgCl2 . 6H2O , 0 . 5mM CaCl2 . 2H2O ) . Approximately three optimal mid-hippocampal slices were collected from each hemisphere for electrophysiology studies . Slices were then allowed to stabilise at 32°C by incubation for one hour in continuously carboxygenated aCSF prior to mounting onto 60MEA200/30iR-Ti-pr-T multi-electrode arrays ( MEA; Multichannel Systems; Germany ) with secure placement achieved using Harp slice grids ( ALA HSG-5B , Multichannel Systems; Germany ) to ensure good contact of the CA1 region with the MEA ( S1A ( 1 ) to S1A ( 3 ) Fig ) . Three slices were simultaneously mounted in separate recording chambers and were independently continuously superfused with carboxygenated aCSF ( S1A ( 3 ) Fig panel i ) . Prior to size exclusion chromatography , brain homogenates were solubilized in Sarkosyl ( w/v in 1xPBS ) , dialysed and filtered . Normal brain homogenates ( ~10% w/v ) were pelleted by 15000xg spin for 10 minutes at 4°C . The supernatant was discarded and the pellet was reconstituted with 4% ( w/v in 1xPBS ) Sarkosyl , incubated at 37°C for 30 minutes , and centrifuged at 10000xg for 10 minutes . The pellet was discarded , and the supernatant was collected and exhaustively dialysed ( using 10kDa cut-off dialysis tubing ) four times in 1x PBS dialysate ( containing no Mg2+ or Ca2+ ) that was ~166 fold greater than the sample volume with each dialysis conducted overnight at 4°C . Parallel to these procedures , ~1% ( w/v ) PK+IP-M1000 was pelleted by 15000xg , and the pellet was resuspended in 4% ( w/v ) Sarkosyl with a volume that was 10-fold less than the initial volume to concentrate the PK+IP-M1000 into ~10% ( w/v ) . Similar procedures were utilized to solubilize ~1% ( w/v ) dM1000 and concentrate to ~10% ( w/v ) . The 10% ( w/v ) solubilized and dialysed preparations were filtered using a 0 . 22-micron filter before ~3mL was injected into a size exclusion chromatography column ( HiPreP 16/60 s-100 ) at a flow rate of 0 . 5mL per min . The protein complexes were eluted in 1x PBS ( containing Mg2+ and Ca2+ ) at 0 . 5mL per min flow rate , wherein the void volume was collected at ~70 minutes after injection followed by continuous collection of 1mL fractions every two minutes for 80 minutes ( ~40 fractions in total ) . The size of proteins or protein complexes fractionated by size exclusion chromatography and eluted into each fraction was determined following size fractionation of the following size exclusion chromatography markers: bovine erythrocyte carbonic anhydrase ( ~29kDa ) , bovine serum albumin ( ~66kDa ) , yeast alcohol dehydrogenase ( ~150kDa ) , sweet potato beta-amylase ( ~200kDa ) , horse spleen apoferritin ( ~443kDa ) , and bovine thyroglobulin ( ~669kDa ) . Fractions 1 ( the void volume ) through 12 were enriched for proteins , protein complexes or protein oligomers and protofibrils with molecular weight above ~100kDa , whereas fractions 15 through 30 were enriched for proteins with molecular weights less than ~100kDa , including monomeric proteins such as PrPC . The levels of prion proteins in each fraction were determined by western blotting , including before and after treatment with 5μg/mL PK for 60 minutes at 37°C . Hippocampal slices ( n = 5 for each treatment condition ) were analysed after dissection of the hippocampus from surrounding tissue , homogenization in lysis buffer ( 50mM Tris-HCl pH 7 . 4 , 150mM NaCl , 0 . 1% ( w/v ) SDS , 0 . 5% ( w/v ) sodium deoxycholate , 1% ( v/v ) NP-40 ) using needles as with whole brain homogenates , methanol precipitation of proteins by adding 5× volumes of ice-cold 100% methanol and incubating at -20°C overnight , followed by centrifugation at ( 20817xg ) at 4°C for one hour . Supernatants were discarded and pellets were resuspended in 50μL lysis buffer and prepared in 4x sample buffer ( NuPAGE LDS , Thermo Fisher Scientific ) with a final concentration of 6% beta-mercaptoethanol . As required , aliquots of 1% brain homogenates ( w/v in aCSF ) of M1000 , MU02 and NBH were also utilised for western blot analysis , including after digestion using 5 or 50μg/ml PK for 60 minutes at 37°C as indicated in the figure legends . The 5μg/ml PK digestion was used for all other PK treatments such as for the PrP-containing preparations used for hippocampal slice treatments ( Fig 2D & 2G ) . In addition , for quantifying levels of PrP in brain homogenates and other preparations used in electrophysiology studies , a serial dilution of recombinant full-length mouse PrP ( rPrP; made as described previously [35] ) of known concentrations ( prepared as described in [36] ) was utilized to generate a standard curve of rPrP through probing by western blotting ( using 8H4 anti-PrP antibody ) and densitometric analysis , which was then used to estimate levels of PrP in the various preparations loaded onto the same gel . Proteins were analysed by PAGE and immunoblotting as described previously [37] . Briefly , samples were resolved on NuPAGE Novex 4–12% Bis-Tris gels ( ThermoFisher Scientific ) , transferred to PVDF membrane ( Millipore ) , blocked in either 5% ( w/v ) skim milk powder ( SkM ) or 3% ( w/v ) bovine serum albumin ( BSA ) , probed with various antibodies ( see S1 Table for a summary of primary and secondary antibodies utilized , their dilutions , as well as blocking conditions/antibody diluents ) , with protein detection using enhanced chemiluminescence ( ECL Prime and Select , Invitrogen ) . Membranes were also stained with Coomassie blue ( and de-stained ) to determine relative total protein levels . All chemiluminescent and digital imaging was carried out using a Fujifilm LAS-3000 Intelligent dark box . Statistical analyses were performed using GraphPad Prism 6 ( USA ) . The PTP and LTP fEPSP data were exported to Excel files ( by LTP Analyzer software from Multichannel Systems ) where they were normalized to average fEPSP recorded over the last five minutes of baseline recording . An unpaired Student t test ( parametric test with Welch’s correction ) was used to compare the average LTP and PTP of the treatment groups , such as NBH controls versus prion containing ( or depleted ) preparations . A paired Student t test ( parametric test ) was used to compare the average ratio of PPF1 and PPF2 . I-O1 and I-O2 were compared using ANOVA with repeated measures . The fEPSP amplitudes of the HFS trains were quantified using PlotDigitizer software and normalized to the baseline fEPSP amplitude . The slope of decline of fEPSP amplitude from pulse 3 to the last pulse in each HFS train was compared between treatment groups by one phase decay exponential function in which the time constant of decay ( Tau = 1/K ) measures the rate of RRP decline in each train . The ratio between pulse 1 ( P1 ) and pulse 2 ( P2 ) of each train was compared between trains within a treatment group by paired Student t test to measure the probability of release per train . Cumulative fEPSP responses of each of the three trains were compared between treatment groups using a linear fit equation ( of the last 4 cumulative fEPSPs/train ) comparing Y-intercepts upon the initial stimulus after extrapolating the linear fit [32 , 33] . Acute synaptotoxicity in the form of LTP and PTP change was calculated as the percentage decrease relative to their appropriate negative controls . The acute synaptotoxicity estimated in the form of PPF ratio was calculated as the percentage of PPF ratio decline in PPF2 relative to PPF1 . Because the PPF ratio is inversely proportional to the Pr , the percentage of PPF ratio decline represents the Pr increase in PPF2 . All data are presented as mean ( m ) ± standard error of mean ( SEM ) . The western blot bands of interest were quantified by densitometry ( Image J ) , after correcting for total protein level and analysed by Student unpaired t test ( parametric test with Welch’s correction ) .
Brains of terminally sick prion infected mice are presumed to contain all pathogenic species responsible for the development of prion diseases . To determine if some of these species are acutely synaptotoxic , independent of de novo propagation of PrPSc given the very short time-frame of the experiments , crude brain homogenates were introduced onto ex vivo mouse hippocampal slices to determine any deleterious effects on LTP . These crude homogenates were derived from WT C57BL/6J mice intracerebrally inoculated with normal brain homogenate ( cNBH ) and terminally ill mice infected with either of two mouse-adapted human prion strains , M1000 ( cM1000 ) [28] and MU02 ( cMU02 ) [29]; Fig 1A , 1D and 1G provide examples of PrPres detection by western blots of brain homogenates pre- and post-PK treatment . The hippocampal CA1 region LTP of 12-week-old WT mice was significantly reduced by 53 ± 9% ( n = 6 ) following five-minute exposure to cM1000 ( Fig 1B & 1C; see S2A Fig ) and by 62 ± 19% ( n = 6 ) following exposure to cMU02 ( Fig 1E & 1F; see S2A Fig ) relative to cNBH . There was no significant difference between the acute synaptotoxicity of cM1000 and cMU02 ( see S2A Fig ) . Further , there was no significant difference in the degree of LTP disruption of cM1000 in slices generated from 11-month-old WT mice ( impaired by 44 ± 7%; n = 7 ) compared with 12-week-old WT mice ( Fig 1H & 1I; see S2A Fig ) . Consistent with the LTP impairment , the I-O2 curve was not significantly enhanced compared to the I-O1 curve following exposure to cM1000 ( in both 12-week-old WT and 11-month-old WT mice ) and cMU02 compared with cNBH ( see S2E and S2F Fig ) . In addition , relative to aCSF technical controls , cNBH negative controls did not affect LTP ( S2B & S2C Fig ) . Propagation of bona fide prions in MoRK13 cell lines that express murine PrPC has been well established through studying M1000 and MU02 ex vivo transmission [29 , 31] . PK-resistant PrPSc detected in these cells ( Fig 1J ) appears a valid biomarker for successful transmission of prions . To determine if these cells also propagate acutely synaptotoxic species similar to cM1000 , whole cell lysates derived from MoRK13-Inf were also briefly superfused onto hippocampal slices from 11-month-old WT mice , with the amount of biochemically detectable PrPSc in MoRK13-Inf lysates balanced to equate that in cM1000 . Similar concentration MoRK13-Un lysates did not affect LTP relative to aCSF controls , demonstrating no background toxicity of the uninfected cell lysates ( see S2D Fig ) . Following brief treatment with MoRK13-Inf lysates , the LTP was significantly impaired by 40 ± 6% ( n = 6 ) ( Fig 1K & 1L ) , with the degree of LTP disruption similar to that obtained from cM1000 ( see S2A Fig ) . Consistent with the LTP impairment , the I-O2 also failed to significantly increase relative to I-O1 following exposure to MoRK13-Inf compared with MoRK13-Un ( see S2H Fig ) . PrPSc species are readily detectable in the brains of terminal prion infected mice [38] and PrPSc species closely correlate with the disruption of neuronal structures including dendritic spines in prion disease in vivo mouse models [16] and a primary neuronal cell culture model [25] . To determine the relationship of PrP species to the acute disruption of LTP following exposure to cM1000 in our electrophysiology assay , total PrP species were selectively immuno-depleted from both cM1000 and cNBH under native conditions using the 03R19 antibody [29] coupled to protein-G conjugated sepharose beads . As shown in Fig 2A , relative to the normal rabbit serum ( NRS ) control , the 03R19 immuno-depletion selectively reduced ~77 ± 12% ( n = 9 ) of PrPC from cNBH ( dNBH ) and ~77 ± 9% total PrP species and 96 ± 4% PrPres from cM1000 ( dM1000 ) . The immuno-depletion did not introduce any synaptotoxicity , wherein dNBH did not affect LTP relative to aCSF controls ( see S3B Fig ) . When hippocampal slices generated from 12-week-old WT mice were treated with dM1000 , LTP was not significantly different to dNBH , and was therefore effectively ‘rescued’ by 74 ± 14% ( n = 8 ) when compared to cM1000 ( Fig 2B & 2C ) , clearly supporting that PrP species in cM1000 are directly responsible for the LTP disruption . In addition , I-O2 became significantly increased relative to I-O1 following exposure to the dM1000 compared with dNBH ( see S3G Fig ) , thus verifying substantial rescue of the synaptic transmission concomitant with the recovery of LTP . Both PK-sensitive and PK-resistant species have been found capable of transmitting prion disease [39] . To determine whether any PK-resistant PrPSc species were directly responsible for the LTP disruption observed with cM1000 , cM1000 was treated with PK prior to superfusion over WT hippocampal slices . The mild PK treatment ( 5μg/ml for one hour at 37°C ) digested ~90% of total protein from cM1000 relative to before the PK treatment but importantly a prominent amount of PK-resistant PrPSc was still evident on western blotting after the PK digestion , demonstrating that the modest PK treatment had considerably enriched for PrPSc ( Fig 2D lower panel; see S3H Fig columns i-ii & S3I Fig ) . The mild PK treatment digested ~80% of total proteins from cNBH including all PrPC relative to before the PK treatment ( Fig 2D upper panel; see S3H Fig columns v-vi & S3I Fig ) . Importantly , this mild PK treatment and possible by-products did not cause any background synaptic impairment when comparing PK+NBH relative to the aCSF technical control ( see S3C Fig ) . Hippocampi derived from 12-week-old WT mice exposed to PK+M1000 demonstrated significant LTP impairment of 48 ± 7% ( n = 8 ) relative to PK+NBH ( Fig 2E & 2F ) . Thus , the LTP disruption of the PK+M1000 was approximately equivalent to that of the cM1000 ( see S2A & S3A Figs ) , indicating that at least modestly PK-resistant PrPSc species are most likely directly responsible for the acute synaptic disruptions caused by cM1000 . This dysfunction correlated with the failure of I-O2 to significantly increase relative to I-O1 after treatment with PK+M1000 ( see S3E Fig ) . To further validate that PrPSc species , in particular PK resistant species , are directly responsible for the acute synaptotoxicity , the total PrP species immuno-precipitated ( IP ) from cM1000 ( IP-M1000 ) and cNBH ( IP-NBH ) ( using the method employed for PrP immuno-depletion ) were eluted from the IP pellets by the same modest PK treatment ( 5μg/ml for one hour at 37°C ) . This PK elution digested ~70% of total proteins from IP-NBH pellets including all PrPC ( Fig 2G upper panel; see S3H Fig columns vii-viii , & S3I Fig ) and ~80% of total proteins from IP-M1000 pellets , leaving substantial levels of PrPSc in the preparations as revealed by western blotting ( Fig 2G lower panel; see S3H Fig columns iii-iv , & S3I Fig ) , effectively enriching the preparations for modestly PK-resistant PrPSc . Following brief exposure of 12-week-old WT hippocampal slices to the PK-eluted IP-M1000 ( PK+IP-M1000 ) , LTP was significantly impaired by 59 ± 5% ( n = 8; Fig 2H & 2I ) . Noteworthy is that the degree of LTP disruption caused by the PrPSc alone from IP pellets was at least as great as that obtained from cM1000 and PK+M1000 ( see S2A & S3A Figs ) , strongly supporting that these species were responsible for the LTP disruption observed with other M1000 preparations . Consistent with the LTP dysfunction , the I-O2 was also prevented by PK+IP-M1000 from becoming significantly enhanced after LTP induction relative to I-O1 ( see S3F Fig ) . Similar to misfolded pathogenic proteins responsible for other neurodegenerative diseases such as amyloid-beta ( Aβ ) in AD and alpha-synuclein in Parkinson’s disease , the neurotoxic species in prion diseases is believed to be soluble multimers or oligomers [40 , 41] . Considerable data supports that PrPSc species accumulate into different size multimers such as oligomers and protofibrils , correlating with the natural evolution of prion disease and the onset of clinical signs in mice [42 , 43] . To determine any correlation between the presence of multimeric PrPSc species in M1000 preparations causing acute synaptic dysfunction ( especially cM1000 , and PK+IP-M1000 ) , PrPSc species in these preparations underwent size exclusion chromatography and analysis by western blotting . For the negative control , PrPC species in cNBH were also fractionated by size exclusion chromatography . Through the use of size exclusion markers with molecular weights of ~400kDa , ~200kDa , ~66kDa and ~29kDa , protein complexes larger than 100kDa , including PrPSc multimers , were eluted in fractions 1 through 12 , whereas protein species smaller than 100kDa , including PrPC , PrPSc monomers and endoproteolytic fragments were eluted in fractions 14 through 40 . Relative to fractions of cNBH where most PrPC species were eluted as monomers ( Fig 3A and 3B ) , the fractions of cM1000 contained mostly multimeric PrPSc species ( Fig 3C upper panel and Fig 3D ) wherein significant levels were at least modestly PK-resistant ( Fig 3C lower panel and Fig 3D ) . Interestingly , fractions of PK+IP-M1000 also contained predominantly at least modestly PK-resistant PrPSc multimers . In contrast , fractions of dM1000 contained significantly reduced levels of the multimeric PrPSc species , especially fractions 5–10 , including at least modestly PK-resistant multimeric PrPSc species ( Fig 3G and 3H ) , which were present at substantial levels in cM1000 ( Fig 3C & 3D ) and PK+IP-M1000 ( Fig 3E & 3F ) . Consequently , the increased levels of multimeric PrPSc species in fractions 5–10 of cM1000 and PK+IP-M1000 which were relatively depleted in dM1000 appear most strongly correlated with the acute impairment of LTP ( Fig 2 ) . Ongoing PrPC expression is required for the sustained propagation of transmissible and neurotoxic PrPSc to cause prion disease [27 , 31] . PrPC has also been described as a receptor for transducing soluble , oligomeric Aβ42 synaptotoxicity [26] . To determine if PrPSc acute hippocampal synaptic disruption requires PrPC expression , the synaptotoxicity of cM1000 was assessed using slices derived from 12-week-old PrPo/o mice . The degree of LTP impairment in these PrPo/o hippocampal slices following exposure to cM1000 , was less marked but broadly comparable to that observed in WT slices ( Fig 6A & 6B; see S5E Fig ) , thereby demonstrating that PrPC expression is not crucial for the acute synaptotoxic mechanisms underlying disruption of LTP by PrPSc . Notably though , in contrast to WT slices treated with cM1000 ( Fig 4A ) , the PPF2 ratio significantly decreased following HFS trains , thereby mirroring what occurred with exposure to cNBH ( Fig 6C; see S5G Fig ) although PTP remained significantly impaired in PrPo/o slices following cM1000 treatment ( Fig 6D; see S5F Fig ) . These findings suggest that any pre-synaptic dysfunction following HFS trains may also be at least partly PrPC independent and that because the Pr was not significantly diminished during LTP expression the mechanisms of any PrPSc pre-synaptic dysfunction in PrPo/o slices are subtly but notably different compared with WT mice . Of further noteworthiness , the LTP , PTP , and PPF ratio in PrPo/o slices treated with cNBH were not affected compared with PrPo/o slices treated with aCSF ( see S5 Fig ) , demonstrating no background synaptotoxicity from crude brain homogenates and importantly , the LTP , PTP , and PPF ratio obtained from PrPo/o and WT slices superfused with aCSF only were not different ( see S5 Fig ) , in keeping with previous reports of no significant effect of the loss of PrPC on the Schäffer collateral pathway synaptic functions in young PrPo/o mice [10] . Given the likely fundamental role PrPC plays in synaptic functions [7 , 9] , it is possible that the molecular components of the pre- and post-synaptic compartments are fundamentally altered to compensate the neuro-developmental absence of PrPC in an attempt to maintain normal synaptic functions , thereby perhaps supporting the possibility of different or distinct mechanisms for any PrPSc acute synaptotoxicity . The disruption of PTP and LTP in PrPo/o hippocampal slices exposed to cM1000 suggested both pre- and post-synaptic impairments , respectively . The Pr during T2 and T3 of the HFS trains showed a normal decline comparable to that observed for cNBH ( Fig 6E ) and similar to what occurred after exposure of WT slices to cM1000 ( Fig 4D ) . Importantly however , the RRP replenishment also appeared impaired in PrPo/o slices similar to that observed in WT slices ( Fig 6G ) leading to a significant reduction in RRP size during T3 ( n = 11; Fig 6H ) , thereby probably disrupting PTP ( n = 11; Fig 6D ) . Unexpectedly , the RRP during T1 was minimally but significantly larger in the PrPo/o slices exposed to cM1000 supporting the possibility of enhanced neurodevelopmental compensation to the absence of PrPC made apparent in such slices upon exposure to PrPSc ( n = 11; Fig 6H ) explaining why a significant impairment of RRP replenishment was not apparent until T3 . Biochemical analysis of the cM1000 treated PrPo/o hippocampi revealed significantly decreased levels of synaptophysin ( Fig 6I & 6J ) akin to what was observed in WT slices ( Fig 5A & 5D ) , further supporting a pre-synaptic component to the PrPSc acute synaptotoxicity in these slices and implying that the disruption of synaptophysin in WT hippocampal slices was probably PrPC independent . In contrast , PrPSc exposure did not affect expression of VGLUT1 ( Fig 6I & 6J ) , once again supporting that pre-synaptic functions in PrPo/o slices are probably less and differentially susceptible to PrPSc acute synaptotoxicity compared with WT slices . Additionally , expression levels of NR2A and NR2B and GluA2 remained unaffected by PrPSc in PrPo/o hippocampi , also supporting the likelihood of different post-synaptic pathophysiological mechanisms of PrPSc acute synaptotoxicity ( Fig 6I & 6J ) and implying that the down-regulation of VGLUT1 , NR2A , NR2B , and GluA2 in WT hippocampal slices is PrPC expression dependent . Nevertheless , importantly both pERK and pCREB were significantly reduced ( Fig 6I & 6J ) in PrPo/o slices , underscoring that although there are likely to be nuanced differences in the pathways sub-serving acute synaptic dysfunction in PrPo/o hippocampi , there appears to be overlap in the final effector pathway of post-synaptic dysfunction similar to WT hippocampi . PSD95 remained unaltered in PrPo/o hippocampi again supporting no net loss of the dendritic compartment associated with this acute synaptotoxicity over the very short time-frames of our experiments ( Fig 6I & 6J ) . Interestingly , Fyn levels were significantly reduced in PrPo/o hippocampi after treatment with cM1000 ( Fig 6I & 6J ) , supporting post-synaptic disruption in PrPo/o slices . To determine if WT and PrPo/o hippocampal slices display similar sensitivity to prion acute synaptotoxicity , the dose-response relationships of LTP and PTP were analysed following exposure to a dilution series of cM1000 including 1% ( w/v ) , 0 . 5% ( w/v; as utilised previously ) , 0 . 25% ( w/v ) and 0 . 1% ( w/v ) . In addition , the approximate level of abnormal or PK-resistant PrPSc in various preparations employed in our electrophysiological studies was determined . The 1% homogenates caused non-specific technical difficulties with electrophysiological testing precluding their use ( S6A Fig ) . In 0 . 5% cM1000 , there was ~0 . 168 ± 0 . 020 μg/mL total PrP including ~0 . 094 ± 0 . 020 μg/mL at least modestly PK-resistant PrPSc ( n = 3; Fig 7A and 7B ) . In 0 . 25% cM1000 ( n = 3 ) , there was ~0 . 066 ± 0 . 003 μg/mL total PrP including ~0 . 026 ± 0 . 002 μg/mL at least modestly PK-resistant PrPSc , while in 0 . 1% cM1000 there was ~0 . 015 ± 0 . 004 μg/mL total PrP with ~0 . 006 ± 0 . 0003 μg/mL at least modestly PK-resistant PrPSc ( n = 3; Fig 7A and 7B ) . For WT hippocampal slices , relative to cNBH controls , the LTP was significantly disrupted in a dose-dependent manner ( p<0 . 0001; One-way ANOVA with Bonferroni correction for multiple comparisons ) wherein non-PK digested 0 . 5% ( n = 6 ) and 0 . 25% ( n = 5 ) cM1000 significantly impaired LTP ( 0 . 5% p<0 . 0001 , impaired by 53 ± 9%; 0 . 25% p = 0 . 0195 , impaired by 30 ± 2% ) , while it was unaffected by the 0 . 1% cM1000 ( n = 5; Fig 7C ) . Similarly , PTP in WT hippocampal slices was significantly impaired in a dose-dependent manner ( p = 0 . 0039; One-way ANOVA with Bonferroni correction for multiple comparisons ) following treatments with the same dilutions of cM1000 wherein both 0 . 5% ( n = 6 ) and 0 . 25% ( n = 5 ) cM1000 were significantly toxic to PTP ( 0 . 5% p = 0 . 0073 , impaired by 30 ± 6%; 0 . 25% p = 0 . 0270 , impaired by 26 ± 7% ) , while 0 . 1% cM1000 did not adversely affect PTP ( n = 5; Fig 7D ) . Hence , these results demonstrated a correlation between the levels of PK-resistant PrPSc and the degree of LTP and PTP dysfunction with a threshold level of at least modestly PK-resistant PrPSc > ~0 . 006 μg/ml being toxic to PTP and although acknowledging a probable non-uniform immuno-depletion across the spectrum of PrP species in dM1000 a level >~0 . 014 μg/ml was toxic to LTP . Levels of at least modestly PK-resistant PrPSc in 0 . 5% PK+M1000 and PK+IP-M1000 that were significantly toxic to LTP and PTP were ~0 . 094 ± 0 . 020 μg/mL ( n = 3 ) and 0 . 057 ± 0 . 013 μg/mL ( n = 3 ) , respectively . For PrPo/o slices relative to cNBH controls , a similar dose-dependent decline in LTP and PTP was observed ( n = 5 each; p = 0 . 0027; One-way ANOVA with Bonferroni correction for multiple comparisons ) . The 0 . 5% cM1000 reduced LTP significantly by 58 ± 8% ( p = 0 . 0003 ) , while 0 . 25% impaired LTP by 48 ± 10% ( p = 0 . 0018 ) ; however , 0 . 1% cM1000 did not significantly disrupt LTP ( Fig 7E ) . Parallel dose-dependent dysfunction was observed with PTP following exposure of PrPo/o hippocampal slices to 0 . 5% , 0 . 25% , and 0 . 1% cM1000 , respectively ( n = 5 each; p = 0 . 0027; One-way ANOVA with Bonferroni correction for multiple comparisons ) . Compared to cNBH controls , both 0 . 5% and 0 . 25% cM1000 significantly disrupted PTP ( 0 . 5% reduced PTP by 32 ± 8% , p = 0 . 0135; 0 . 25% reduced PTP by 39 ± 6% , p = 0 . 0023 ) ; however , 0 . 1% cM1000 was not significantly toxic to PTP ( Fig 7F ) . Overall , the results were similar to those obtained in WT hippocampal slices , thereby implying that the prion acute synaptotoxicity in PrPo/o hippocampal slices reported in this current study was not due to an altered sensitivity .
Herein we report the acute synaptotoxicity of ex vivo , prion-containing preparations and provide important new molecular pathophysiological insights . Utilising a number of experimental approaches , our findings revealed that: ( 1 ) PrPSc ( particularly at least modestly PK-resistant isoforms most likely as multimeric species ) is directly synaptotoxic; ( 2 ) that the acute synaptotoxicity was similar across the two prion strains examined and appears independent of tissue source of prions when balanced for PrPSc levels; ( 3 ) the acute synaptotoxicity is not reliant on hippocampal PrPC expression albeit with noteworthy molecular and electrophysiological differences in the presence or absence of PrPC; and ( 4 ) both pre- and post-synaptic functions are deleteriously affected , with the possibility of enhanced vulnerability of the former compartment . Although previous studies have demonstrated clear correlations between the presence of PrPSc and the onset of neuropathological changes [38] , disruption of LTP at the hippocampal CA1 region of mice inoculated with ME7 [14] and impairment of memory and learning [15] , our studies offer compelling evidence for the direct synpatotoxicity of PrPSc , especially PK-resistant species derived from brains of terminally sick animals . First , we demonstrated that modest PK treatment of ex vivo preparations ( sufficient to digest all PrPC ) did not attenuate the acute synaptotoxicity , with the impairment of LTP similar to that observed with cM1000 . These protease digested preparations demonstrated substantial selective enrichment of PrPSc ( see S3H Fig columns i & ii ) analogous to that recently reported in another model assessing acute PrPSc synaptotoxicity [25] . Next , we demonstrated that immuno-depletion of PrP species from cM1000 substantially and proportionally mitigated the acute synaptotoxicity such that LTP was restored to levels not different to dNBH . Additionally , we demonstrated that the use of reconstituted , PK-eluted , immuno-precipitated PrPSc generated from crude brain preparations achieved full acute synaptotoxicity equivalent to that observed for cM1000 , with additional biochemical characterisation of these preparations once again demonstrating significant selective enrichment of PrPSc ( see S3H Fig columns iii & iv ) . Finally , size fractionation studies revealed that in addition to reducing total PrP species in dM1000 , the spectrum of PK-resistant PrPSc species was altered and the levels of multimeric PrPSc species specifically decreased in dM1000 correlating with the rescue of LTP . Notably , the acute synaptotoxicity of cM1000 and PK+IP-M1000 clearly correlated with elevated levels of multimeric PK-resistant PrPSc species . Our electrophysiology assay demonstrated that brains from terminally ill mice harbouring either M1000 or MU02 prions contain acutely synaptotoxic species . Interestingly , the degree and spectrum of synaptic dysfunction caused by these two different prion strains were indistinguishable , implying that the acute synaptotoxicity may be a generic property of PrPSc species and independent of the specific prion strain; the study of additional prion strains would confirm this speculation . Importantly , the degree of LTP impairment caused by both M1000 and MU02 strains was comparable to that recorded in the hippocampal CA1 region of ME7 scrapie-infected mice between 125 to 160 days post-inoculation [14] , underscoring the biological validity of our findings . In further support of the biological relevance of our findings , the estimated level of misfolded or PK-resistant PrPSc in our 0 . 5% M1000 brain homogenates was ~0 . 094 ± 0 . 020 μg/mL , which despite methodological differences , falls well within the range of modestly ( 10 μg/ml ) PK-resistant PrPSc levels determined by Mays et al . [48] in terminal whole brain homogenates of several prion animal models; however , uncertainty persists as to what precise levels would actually be found localised to synapses . Moreover , our results demonstrated a correlation between the levels of PK-resistant PrPSc and the degree of LTP and PTP dysfunction with a threshold level of at least modestly PK-resistant PrPSc > ~0 . 006 μg/ml appearing toxic to PTP while a level >~0 . 014 μg/ml appears toxic to LTP . A recent study by Fang et al describes retraction and depletion of dendritic spines after 24 hours of exposure to PrPSc preparations [25] . In keeping with the importance of LTP in the generation and maintenance of dendritic spines , our observations may offer insights into the molecular pathogenesis underpinning at least some of the described dendritic spine morphological changes [12 , 49 , 50] . Though it is known that cellular expression is not required for uptake of PrPSc aggregates [51] and in vivo neurons not expressing PrPC develop morphological abnormalities typical of prion disease with continued exposure to PrPSc over many weeks [52] , in noteworthy contrast to this and our electrophysiology studies , Fang et al reported complete dependence on neuronal PrPC expression for toxicity . There are several potential explanations , which from our cM1000 serial dilution studies do not relate to an altered sensitivity of PrPo/o hippocampal slices . Firstly , our model assessed synaptic dysfunction within a period of approximately 45 minutes following exposure to PrPSc containing preparations , whereas the time-frame for assessment in the study of Fang et al was at approximately 24 hours . The importance of ongoing neuronal PrPSc propagation to provide continued PrPSc exposure for effective pathogenesis is exemplified by the reported rapid and complete reversal of morphological , hippocampal CA1 region neurophysiological and behavioural abnormalities shortly after neuronal PrPC expression is abrogated in the setting of established prion infection [53 , 54] . The prompt reversibility of synaptic spine loss has also been reported in relation to AD models employing naturally secreted Aβ oligomers if the toxic species is completely removed [55] . Such observations support that the CNS has evolved powerful compensatory and recuperative mechanisms and it is highly likely that a single brief exposure to a synaptoxin only causes transient dysfunction that probably does not inevitably lead to sustained failure and loss of the synapse , especially if the level of toxin exposure is not extreme . Therefore we speculate in the Fang et al model that an additional approximately 23 hours in the absence of any de novo PrPSc production from endogenous PrPC may have allowed effective activation of neuro-protective or adaptational responses in PrPo/o tissues , including progressive clearance or degradation of exogenous PrPSc , and that persisting neuronal exposure above threshold levels is required to achieve sustained dendritic retraction and pruning when assessing synaptotoxicity over the longer 24 hour period . Secondly , other methodological differences , such as in the techniques for generating ex vivo PrPSc preparations ( eg detergents plus serial ultracentrifugation versus IP plus PK digestion ) , the tissues used for toxicity studies ( primary hippocampal neuronal cultures versus ex vivo hippocampal slices ) and the primary metric for assessing toxicity ( endogenous dendritic spine size/number versus induced LTP amplitudes ) , may collectively contribute to the observed discrepancies . Finally , and notwithstanding the aforementioned neurobiological and technical considerations , although LTP impairment was observed in PrPo/o slices , subtle but potentially important differences were observed in other facets of synaptic function , as well as in changes to key synaptic proteins . Namely , while PTP was also adversely affected by PrPSc preparations in addition to LTP in PrPo/o hippocampi , the PPF ratio showed a normal decline after LTP with VGLUT1 , NR2A , NR2B , GluA2 and procaspase 3 levels unchanged . These discrepancies with WT hippocampi exposed to PrPSc suggest the possibility of PrPC-independent mechanistic pathways contribute to LTP and PTP impairment , which may not have been easily discerned in the setting of PrPC expression and further underscore uncertainty of how such differences may relate to the retraction and loss of dendritic spines over a longer period of 24 hours . The possible impact of age associated with the lack of PrPC expression were important considerations in our studies . Because the absence of PrPC has been reported to be linked with age-dependent impairment of hippocampal synaptic function in 8–15-month old mice [10] , we mitigated this potentially confounding phenomenon by only using hippocampal slices from young PrPo/o mice . Notably , our findings reproduced those previously reported in a number of studies [10 , 56 , 57] with young PrPo/o mice exhibiting hippocampal CA1 synaptic functions congruent with aged-matched WT mice although contrary findings have been reported [58 , 59] , which may partly relate to variations in electrophysiology techniques employed . Also of interest , WT C57BL/6 mice 9–12 months old have been reported to express age-dependent deficits in learning following treatment with neurotoxic Aβ1–42 [60] , thereby suggesting that older WT mice of this age may also be more susceptible to synaptic impairment associated with prion-infected preparations . Our studies however , revealed age-independent disruption of hippocampal synaptic function by cM1000 up to 11 months of age . Synaptic physiology is complex and multi-facted making the achievement of precise understanding of pathophysiological changes through electrophysiological interrogation a considerable challenge . As part of validating the acute synaptotoxicity of PrPSc , our detailed electrophysiological analyses suggest a possible enhanced pre-synaptic vulnerability , exemplified by the impairment of PTP , although contributions to LTP disruption from post-synaptic dysfunction seem likely as discussed below . A technical limitation of our assessments to probe pre-synaptic impairments was the lack of inclusion of specific GABA receptor antagonists . The 20 millisecond inter-stimulus intervals used to determine PPF ratios and the 10 millisecond intervals employed for HFS are very short , making contributions from GABAB receptors quite unlikely but leaves open the possibility that GABAA receptor related inhibitory post-synaptic potentials could have influenced some of the measured synaptic phenomena in ways we have not fully accounted for . Consequently , the absence of GABAA receptor blockade in our experiments utilising fEPSP amplitudes to infer pre-synaptic pathophysiology allows for some potential inaccuracy in the derived measurements of Pr and RRP and precludes our studies from being definitive in this regard . Nevertheless and notwithstanding such caveats , to try to offer an understanding of the basis of the impairment of PTP , our analyses are consistent with impairment of action potential-dependent mechanisms of RRP replenishment , made obvious by the physiological stress imposed by repeated HFS trains used to induce PTP whereby there appeared to be a progressive deterioration of RRP replenishment leading to a significant reduction of RRP size and consequently a reduced PTP . In addition , because the Pr and the depletion rate of RRP during HFS trains appeared normal these could exacerbate the dysfunction of RRP replenishment [61] and the reduction of PTP . Further , this suggestion of pre-synaptic disruption was observed in WT and PrPo/o mice , supporting that PrPC expression appears irrelevant to this dysfunction . The observation that immuno-depletion of total PrP species by ~77% only rescued LTP but not PTP with the ongoing PTP impairment also appearing to be due to deficiency of RRP replenishment leading to a reduction in RRP size , suggests that the modest amount of PK-resistant PrPSc , including multimeric species , remaining after immuno-depletion appears sufficient to cause this disruption although contributions from a non-PrPSc factor cannot be completely excluded . These findings raise the possibility that the mechanisms responsible for RRP replenishment during repeated HFS trains appear highly vulnerable to PrPSc toxicity and more susceptible than LTP . The reduced PTP we observed appears discordant with results reported in a previous in vivo study of the ME7 prion strain in which PTP was reported as unaffected over the mid-incubation period [14] . We believe this apparent discrepancy is methodological in basis given that careful scrutiny of the relevant figure from this report reveals consistently lower amplitude initial PTPs in the prion infected mice similar to what we found . These authors measured PTP at a presumably varying time point during the first minute after HFS ( with the PTP in non-prion infected mice decreasing rapidly after the first stimulation post-HFS ) while we systematically utilised the first response immediately after serial HFS to estimate PTP . The apparent disruption of the PPF ratio following HFS in WT slices is consistent with insufficient Pr during the maintenance of LTP suggesting pre-synaptic impairment following exposure to synaptotoxic PrPSc [62] . Additionally , expression levels of pre-synaptic markers , synaptophysin and VGLUT1 , were consistently decreased in WT hippocampi manifesting disrupted LTP . Although synaptophsyin has been shown to be less important in neurotransmitter release [63] , previous studies have uncovered that synaptophysin is significantly recruited for LTP expression and generally required for synaptic plasticity without involvement in Pr maintenance [64 , 65] . Hence , this reduced level of synaptophysin is somehow directly concomitant with the impairment of LTP , but probably not via diminishing Pr . Noteworthy are previous reports of significantly reduced synaptophysin expression levels in the hippocampi of WT ( C57BL/6 ) mice inoculated with three different prion strains: ME7 , 79A , and 22L [66] . VGLUT1 instead plays substantial roles in the packaging of glutamate into pre-synaptic vesicles and maintaining normal Pr , wherein neurons lacking VGLUT1 have reduced Pr [67] . Therefore , we believe that the reduced expression levels of both synaptophysin and VGLUT1 directly contributed to the disruption of LTP , whereas only the loss of VGLUT1 was probably associated with our postulated impairment of Pr after LTP induction . Unexpectedly , we observed decreased synaptophysin levels but preserved VGLUT1 levels in PrPo/o slices correlating with the normal Pr observed following LTP . This suggests that the loss of VGLUT1 in WT hippocampi was PrPC dependent , whereas the loss of synaptophysin in these hippocampi is PrPC independent . The preservation of the Pr and PPF ratio following HFS in PrPo/o slices exposed to synaptotoxic PrPSc suggests that any pre-synaptic impairment associated with disruption of PTP is a primary pathophysiologic driver of the LTP dysfunction in both WT and PrPo/o slices . Nevertheless , because HFS also cause post-synaptic changes such as receptor activation , new receptor insertion and terminal expansion , which may collectively alter post-synaptic sensitivity to released neurotransmitters [12] , contributions from post-synaptic disruptions are likely in the HFS-dependent synaptic dysfunction such as the impairment of LTP . Variable transient disruption of the baseline during treatments of the hippocampal slices was observed in our study . Although we are not able to offer a definitive explanation for this minor technical issue , possible contributing factors , which are not mutually exclusive and may have occurred in varying combinations , include: i ) slight variation in the temperature of some of the treatments; ii ) slight variation in the pH of some of the treatments or slight pH change during the treatment; iii ) slight variation in the depth of the treatment solution in each MEA recording chamber across experiments; and iv ) minor mouse cohort variation in the sensitivity of hippocampal slices to the treatments . Another issue that could also contribute to variability , particularly in association with the above first three speculations is subtle variation in positioning of the superfusing solution inflow and outflow and the associated flow of solution within the MEA recording chamber . The MEA recording chambers are circular and this shape is known to allow some variation in cross-chamber solution flow as the solution can flow around the circular walls of the chamber rather than inevitably directly across the centre of the chamber; however , despite the occasional transient baseline disruption during treatments , there is no evidence this phenomenon impacted our recordings or results as HFS for elicitation of LTP and PTP was not undertaken until fEPSPs had returned to baseline for at least 5 minutes after the treatment . In addition , the acute synaptotoxic effects of ex vivo PrPSc preparations reported in our study were not linked to or affected by whether the baseline recording was temporarily disrupted ( such as in Fig 1B cM1000 and 2H PK+M1000 ) or not disrupted ( such as in Figures IE cMU02; 1K MoRK13-INF , and 2H PK+IP-M1000 ) . Notwithstanding controversies concerning the exact mechanisms underpinning hippocampal LTP , it is clear that LTP expression involves significant modifications of post-synaptic properties , particularly activation of extant post-synaptic NMDAR and externalization of new AMPAR [12 , 68] . Our study demonstrated reduced expression levels of NR2A- and NR2B-containing NMDAR and GluA2-containing AMPAR in WT hippocampi expressing impaired LTP following exposure to synaptotoxic PrPSc . Although these receptors can be expressed in both pre- and post-synaptic terminals [69 , 70] , their considerable numerical predominance post-synaptically supports that their overall loss was likely to be primarily post-synaptic [71] . NR2A/B-containing NMDAR are essential for hippocampal synaptic function and the expression of CA1 LTP [72]; therefore , their loss supports that the disruption of LTP in WT mice is at least partly dependent on NMDAR disruption . AMPAR also play a critical role in maintaining basal synaptic functions and most importantly in LTP expression , where new AMPAR are inserted into the post-synaptic membrane as part of LTP induction to enhance the function of active synapses and activate silent synapses [73 , 74] . Because the acute PrPSc synaptotoxicity we observed was HFS-dependent , we postulate that the loss of AMPAR was mediated predominantly through silent synapses . Of likely relevance to our findings , parallel losses of NMDAR and AMPAR have been reported in the brains of AD patients [75] directly correlating with Aβ synaptotoxicity [76] . Unlike in WT slices , NR2A/B-containing NMDAR , and GluA2-containing AMPAR remained unaltered in PrPo/o hippocampi following exposure to synpatotoxic PrPSc , implying different mechanisms are responsible for acute PrPSc synaptotoxicity in PrPo/o compared to WT slices . Importantly , this result infers that the disruptions of these receptors in WT mice are probably PrPC dependent with the persistent impairment of LTP in PrPo/o hippocampi suggesting that the alterations of these glutamate receptors are not the sole determinant of PrPSc acute synaptotoxicity . This finding also suggests that PrPo/o mice may have higher innate resistance to PrPSc synaptotoxicity through mechanisms which mitigate acute synaptic dysfunction when studied over longer time frames than we allowed [77 , 78] . Following exposure to PrPSc the key intracellular proteins pERK and pCREB involved in synaptic plasticity were also down-regulated in slices . Of note , both pERK and pCREB levels were significantly rescued following immuno-depletion of PrP , supporting a direct synaptotoxic effect of PrPSc on their function . Offering mechanistic pathway overlap in the disruption of LTP , these key intracellular synaptic proteins were also reduced in PrPo/o slices supporting that PrPC-independent impairment through different mechanisms occurs upstream of ERK and CREB activation . The sustained expression of NR2A and NR2B subunits in PrPo/o slices , while observing persistently reduced pERK and pCREB levels , supports the notion that activation of ERK and CREB during LTP induction and maintenance is likely to be independent of NMDAR activity in hippocampi of PrPo/o mice [79] . Although the activation of NMDAR is known to mediate the influx of Ca2+ during LTP induction , the activation of ERK and CREB has also been demonstrated to be independent of NMDAR activity but dependent on L-type voltage-gated calcium channel ( L-VGCC ) activation . PrPC may be either directly or indirectly involved in Ca2+ influx via neuronal L-VGCCs [8 , 80] , and interact with Fyn to mediate Ca2+ dependent activation of ERK and CREB [81–83] . The absence of PrPC in PrPo/o slices may increase the vulnerability of L-VGCCs to PrPSc disruption compared with WT mice . Phosphorylation of ERK is essential for many synaptic functions such as activation of transcription factor CREB to produce more synaptic proteins . This pathway has been implicated in structural plasticity by which activation mediates formation of new dendritic spines and thereby contributes to LTP expression in ex vivo hippocampi [84] and memory formation in vivo [85] . Hence , the diminished levels of these two-key intracellular post-synaptic markers suggest that the acute PrPSc synaptotoxicity is likely to be associated with impaired production of new synaptic proteins with associated difficulties maintaining some spines and/or producing new spines . Of note , inhibition of ERK activity with MAPK/ERK kinase ( MEK ) inhibitors prevents dendritic spine growth and acutely disrupts LTP induction [68] . Additionally , pERK is directly involved in AMPAR insertion into the post-synaptic membrane following HFS , which is required for both enlarging synapses and activating silent synapses [47 , 68 , 73] . Hence , the reduced activation of pERK might have contributed to the down-regulation of AMPAR in WT mice but supports others factors contributing to this change in PrPo/o slices . Overall , our observations offer new insights into the pathophysiology underlying the acute synaptic dysfunction of prion disease , generally aligning with reported synaptic disruptions demonstrated in other neurodegenerative diseases such as Alzheimer’s , Parkinson’s , and Huntington’s diseases , all of which consist of both pre-synaptic and post-synaptic impairments [86–88] . Our findings suggest an enhanced vulnerability of the pre-synaptic compartment , especially replenishment of the RRP of vesicles , to PrPSc acute synaptotoxicity although post-synaptic impairment is likely to contribute to the disruption of short and/or long-term synaptic plasticity . We have demonstrated that PrPSc derived from terminal disease brains , particularly modestly PK-resistant most likely multimeric species , are important direct synaptotoxins in prion disease , with the likelihood of PrPC-independent pathways contributing to acute PrPSc acute synaptotoxicity . | Misfolding of the normal prion protein ( PrPC ) into disease-associated conformations ( PrPSc ) is the critical initiating step for prion diseases . Similar to other neurodegenerative disorders , progressive failure of brain synapses is considered a primary deleterious event underpinning prion disease evolution . Our current understanding of the underlying mechanisms associated with synaptic failure is rudimentary contributing to difficulties in developing effective treatments . Herein we report the use of an electrophysiology paradigm that allowed us to demonstrate that at least modestly proteinase K ( PK ) -resistant PrPSc species from two mouse-adapted prion strains ( M1000 and MU02 ) are directly synaptotoxic causing significant acute impairment of hippocampal CA1 region long-term potentiation ( LTP ) . Of note , the LTP disruption approximated that reported in prion animal models . Additional detailed analyses provided novel pathophysiological insights suggesting possible heightened pre-synaptic vulnerability to the acute synaptotoxicity through impairment of replenishment of the readily releasable pool of neurotransmitter vesicles , while biochemical analyses demonstrated reduced levels of multiple key pre-and post-synaptic proteins . Broadly similar acute synaptic dysfunction and dose-response susceptibility were observed in slices from mice not expressing PrPC albeit with minor but noteworthy differences in electrophysiological and biochemical findings . Our study offers important new mechanistic insights into the synaptic impairment underlying prion disease , enhancing prospects for development effective therapies . | [
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"neu... | 2018 | Prion acute synaptotoxicity is largely driven by protease-resistant PrPSc species |
Although rabies represents an important public health threat , it is still a neglected disease in Asia and Africa where it causes tens of thousands of deaths annually despite available human and animal vaccines . In the Central African Republic ( CAR ) , an endemic country for rabies , this disease remains poorly investigated . To evaluate the extent of the threat that rabies poses in the CAR , we analyzed data for 2012 from the National Reference Laboratory for Rabies , where laboratory confirmation was performed by immunofluorescence and PCR for both animal and human suspected cases , and data from the only anti-rabies dispensary of the country and only place where post-exposure prophylaxis ( PEP ) is available . Both are located in Bangui , the capital of the CAR . For positive samples , a portion of the N gene was amplified and sequenced to determine the molecular epidemiology of circulating strains . In 2012 , 966 exposed persons visited the anti-rabies dispensary and 632 received a post-exposure rabies vaccination . More than 90% of the exposed persons were from Bangui and its suburbs and almost 60% of them were under 15-years of age . No rabies-related human death was confirmed . Of the 82 samples from suspected rabid dogs tested , 69 were confirmed positive . Most of the rabid dogs were owned although unvaccinated . There was a strong spatiotemporal correlation within Bangui and within the country between reported human exposures and detection of rabid dogs ( P<0 . 001 ) . Phylogenetic analysis indicated that three variants belonging to Africa I and II lineages actively circulated in 2012 . These data indicate that canine rabies was endemic in the CAR in 2012 and had a detrimental impact on human health as shown by the hundreds of exposed persons who received PEP . Implementation of effective public health interventions including mass dog vaccination and improvement of the surveillance and the access to PEP are urgently needed in this country .
Although this fatal disease is preventable since 1884 when Louis Pasteur developed the first vaccine strategy , rabies is still a neglected zoonosis in developing countries where it poses a significant threat to human public health [1] . More than 55 , 000 people die of rabies every year mostly in Asia and Africa [2] . Rabies virus ( RABV ) belongs to the genus Lyssavirus and family Rhabdoviridae . Although all species of mammals are susceptible to rabies virus infection , only a few species are important as reservoirs of infection [3] . The most common route of rabies transmission to humans is the bite of rabid domestic dogs [4] . The WHO considers that canine rabies potentially threatens over three billion people in Asia and Africa [5] . In humans , early clinical features of rabies are nonspecific prodromal symptoms and local neurological symptoms . After an incubation period of variable duration , RABV infects the central nervous system and the clinical presentation of rabies evolves into either encephalitic ( furious ) or paralytic ( dumb ) forms [6] . Rabies is almost always fatal once symptoms appear . However , rabies is a 100% vaccine-preventable disease and vaccination can be used in two situations: to protect those who are at risk of exposure to rabies , i . e . pre-exposure prophylaxis ( PrEP ) , and to prevent the development of clinical rabies after exposure has occurred , i . e . post exposure prophylaxis ( PEP ) . Moreover , mass vaccination of domesticated and wild animals is also possible [7] . With a basic reproductive ratio of less than two , canine rabies is an ideal candidate for worldwide elimination [8] . Consequently , canine rabies elimination is the key towards ultimate reduction of the disease burden in humans , as illustrated in Europe and North America , and mass vaccination of dogs is the most cost-effective way to achieve it [1 , 5] . In many African countries , dog vaccination programs to date have been inadequate and failed to reduce the incidence of canine rabies [9] . However , it has been shown that effective vaccination campaigns reaching a sufficient percentage of the canine population to potentially eliminate disease and prevent future outbreaks are feasible at a cost that is economically and logistically sustainable in developing countries [9 , 10] . For instance , in a study conducted in Tanzania , vaccination of 60–70% of dogs has been sufficient to control dog rabies in the studied area and to significantly reduce demand for human post-exposure rabies treatment [11] . In another study using a model parameterized with routine data on rabid dog and exposed human cases from N’Djaména in Chad , Zinsstag et al . have predicted that a single parenteral rabies mass vaccination of 70% of the dog population would be the most beneficial and cost-effective intervention and would be sufficient to interrupt transmission of rabies to humans for at least six years [12] . This study has also predicted that dog vaccination campaigns combined with human PEP would be more cost-effective compared to human PEP alone beyond a time frame of seven years . In Africa , previous molecular epidemiological studies have shown that at least four clades are circulating [13–15] . In Central Africa , RABV strains belong to the Africa I and Africa II clades [13 , 16] . The Africa I clade is very similar to current Eurasian RABV lineages and is usually grouped into a larger Cosmopolitan clade [14 , 17] . The Africa II clade includes RABV strains that circulate in dogs in several Central and Western African countries [16] . The Central African Republic ( CAR ) is a landlocked country in Central Africa . Its capital is Bangui . It is one of the poorest countries in the world and it has been affected by political instability and internal conflicts for several decades . In the CAR , rabies has been a notifiable disease since April 2009 . The surveillance mainly consists of observation of suspicious animals and brain sample collection by the national veterinary services , and laboratory confirmation by the National Reference Laboratory for Rabies . The national veterinary services operate under the National Agency for Livestock Development ( ANDE ) through an extended network of veterinarians and livestock technicians distributed in 122 sentinel sites across the country . The National Reference Laboratory for Rabies is located at the Institut Pasteur in Bangui . Between August 2006 and December 2008 , 86 animal samples ( 82 of dog origin ) of 101 tested positive for rabies [18] . During the same period , seven human cases were recorded and , biologically confirmation was obtained for three of them [18] . Molecular epidemiological studies have shown the co-circulation in the CAR of strains that belong to Africa I and Africa II clades [13 , 16] . Oscillations in the numbers of rabid dogs have been observed in Bangui with periods of absence or low circulation and then some increases every five years ( manuscript in preparation ) . This pattern might be comparable to the oscillations observed by Hampson et al . in Southern and Eastern Africa [19] . Public strategies for preventing rabies have been very limited in the CAR . Animal vaccination is only at the dog owner's initiative but it is expensive for most people and rarely done . The only serious attempt to control the disease was episodic mass euthanasia of stray dogs in Bangui . In the whole CAR , there is only one anti-rabies dispensary . This dispensary is located at the Institut Pasteur in Bangui and the available post-exposure rabies prophylaxis consists only in vaccination after exposure and is freely available . Administration of immunoglobulin is exceptionally available through some non-governmental organizations ( NGOs ) for some very severe exposures . The persons exposed to suspicious rabid animals are usually referred to the anti-rabies dispensary by the veterinary services , as the first place visited by these persons is often a veterinary clinic . The assessment whether the post-exposure vaccination is needed is usually made by a livestock technician or veterinarian based on the type and circumstances of the exposure . When possible , the veterinary services put the animal under observation and depending on the evolution of the animal health status , they can eventually advise the anti-rabies dispensary to stop the PEP . It is important to note that many persons who have been referred to the anti-rabies dispensary by the veterinary services will never be seen by a medical facility and will then remain unvaccinated . The aim of the present study is to evaluate the extent of the threat that canine rabies represents in the CAR and to determine the dynamics of its causative agent by using data from the National Reference Laboratory for Rabies and the anti-rabies dispensary for the year 2012 .
The CAR had an estimated population of 4 , 487 , 000 inhabitants in 2011 [20] . The country is divided into 16 administrative prefectures . Its capital and most populous city is Bangui with an estimated population of 740 , 000 inhabitants in 2011 [20] . Bangui is divided into eight urban districts and subdivided into 205 neighborhoods ( or quartiers ) . Two conurbations surround Bangui: the cities of Bimbo ( the country's second-largest city ) and Bégoua . Post-mortem samples of brains from dogs with suspicious behaviors were routinely collected by the veterinarians and the livestock technicians of the ANDE through passive surveillance . These samples were provided to the National Reference Laboratory for Rabies at the Institut Pasteur in Bangui for routine rabies diagnosis by direct fluorescent antibody test ( FAT ) and polymerase chain reaction ( PCR ) . Each sample was accompanied by a form with the following information about the suspicious dog: sex , location where the dog was found dead , captured and/or killed , name and address of its owner when identified , circumstances of the capture and/or reason why it was killed , and results of the rabies diagnostic tests . Anonymized data collected between January 1st and December 31st , 2012 were retrospectively reviewed . Owners of dogs suspected of being rabid and persons exposed to these animals were referred to the anti-rabies dispensary located at the Institut Pasteur in Bangui to receive the post-exposure treatment upon a decision by a veterinarian or a livestock technician of the ANDE based on the type ( mainly bites , scratches , and licks ) and circumstances of the exposure ( for instance , attack by the dog without any reason ) . This treatment consists of local treatment of the wound through the cleansing and disinfection of the wound ( a tetanus shot is also often provided ) , followed by a rabies vaccination regimen ( Verorab , a purified vero cell rabies vaccine made by Sanofi Pasteur , Lyon France ) when prescribed . The schedule used was the WHO-approved abbreviated multisite schedule or 2-1-1 regimen [21] . According to this schedule , two doses were given at day 0 ( one in the right arm and one dose in the left arm ) , one dose on day 7 and one dose on day 21 . This schedule induces an early antibody response and is considered effective when post-exposure treatment does not include administration of rabies immunoglobulin [21] . Anonymized data on the rabies exposed humans ( age , gender , and origin ) , exposure ( number and type of wound , depth and sites ) and delay to consult collected between January 1st and December 31st , 2012 were retrospectively reviewed . In addition , data on the rabies vaccination status of the dogs involved , when known , was also collected . This was a non-research national public health surveillance activity approved by the Ministry of Public Health , Population and the Fight against AIDS of the CAR . Approval by institutional review board or written informed consent was not required . Data concerning the exposed humans and/or suspicious dog owners were anonymized before analysis . At the National Reference Laboratory for Rabies , direct FAT was routinely done using an anti-RABV nucleocapsid fluorescent conjugate ( Bio-Rad , USA ) . For diagnostic purposes , PCR was also routinely performed using primers that target a portion of the RNA-dependent RNA polymerase-coding region . Extraction of viral RNA from the original fresh brain samples was done using QIAamp Viral RNA Mini Kit ( Qiagen ) according to the manufacturer’s instructions . To investigate the genetic diversity of RABV circulating in the CAR , we amplified and sequenced a portion of the N gene of 606 nucleotides in length from rabies-positive specimens [22] . The gene of the nucleoprotein has been extensively used for molecular phylogenetic studies because of its relatively conserved variation among reservoir-associated variants and geographic lineages [23] . The date of sampling and location ( city or neighborhood if the city is Bangui ) of the owners of rabid dogs were available for the majority of these sequences . Sequences were then compared with reference sequences from GenBank , and phylogenetic relationships and geographic distribution were determined . Phylogenetic analysis was conducted in MEGA5 [24] . All statistical analysis was performed using STATA version 11 . 1 ( StataCorp , TX ) . Categorical variables were compared by Chi-square or Fisher exact test according to the headcounts , continuous variables where compared with Student t-test or Kruskal-Wallis test when appropriate ( two-sided , significance assigned at P<0 . 05 ) . To analyze the spatiotemporal association between reported human exposures and detection of rabid dogs , each geographic unit ( for Bangui and its suburbs: the eight urban districts and the cities of Bimbo and Bégoua , and for the rest of the country: the prefectures ) by epidemiological week ( i . e . weeks of the year numbered sequentially from one to 52 –week one corresponding to the first complete week of the year ) was considered as a spatiotemporal unit . We performed Spearman rank correlation tests to examine the relationship between the number of reported human exposures ( according to the date of exposure ) and rabid dogs ( according to the date of death ) by spatiotemporal unit . As rabies is a communicable disease , the number of case within a same geographic area is likely to be correlated over time . We used a generalized estimating equations ( GEE ) approach with a Poisson distribution to confirm the significant association between the number of exposed humans ( dependent variable ) and the number of reported dogs ( independent variable ) while taking into account the autocorrelation of data over time . GEE , extension of the generalized linear model , is a population-averaged approach that accounts for the correlation between observations by introducing a working correlation matrix and by using robust variance estimators . The model used has been fully described elsewhere [25] . The correlation matrix can be arbitrarily parameterized , and we choose here a first order autoregressive structure to model the correlation of weekly number of cases in each location . This structure is indicated for time series data when two measurements that are right next to each other in time are pretty correlated , but that as measurements get farther and farther apart they are less correlated . Finally , we took into account the overdispersion of the data by adding an overdispersion scaling parameter in the model [26] .
After only four positive samples by direct FAT in 2011 of seven suspicious samples , the CAR has experienced an important recrudescence of canine rabies in 2012 . Of the 83 samples from suspected rabid animals received by the National Reference Laboratory for Rabies , 82 were from dogs and 69 were tested positive with direct FAT ( Fig 1 and S1 Table ) . The remaining sample was from primate and tested negative . Of these 69 samples , 67 were positive with PCR for diagnostic purposes . Characteristics of the 82 suspected rabid dogs that contributed to the samples panel is summarized in the Table 1 . Most of the dogs were male ( 67 . 3% of the dogs for which the sex was known ) with a known owner ( 68 . 3% ) , originated from Bangui ( 79 . 3% ) and were found aggressive then killed by the owner or by the veterinary services ( 65 . 9% ) . In 2012 , a total of 966 persons visited the anti-rabies dispensary for rabid animals exposure mainly after being prescribed to do it by a veterinarian or a livestock technician of the ANDE ( Fig 1 and S2 Table ) . Of these , 631 received the post-exposure vaccines course ( regimen 2-1-1 ) . The characteristics of these persons are summarized in Table 2 . Briefly , 53 . 8% were male and 57 . 7% of the exposed persons were children under 15 years ( median age = 13 years with inter-quartile range of 8–27 years ) if documented . The main type of exposure was bite by suspicious rabid dogs ( 91 . 7% ) with multiple ( 56 . 0% ) but superficial ( 54 . 2% ) wounds if documented . The vast majority of exposed persons originated from Bangui itself or its suburbs i . e . Bimbo and Bégoua ( 93 . 2% ) . Most of the exposed persons visited the anti-rabies dispensary within a week after exposure ( 74 . 8% ) but 31 persons came only a month or more after exposure . The time delay to visit the anti-rabies dispensary since exposure was significantly associated with the location of the exposed persons , with a mean delay of 6 . 2 days for the exposed persons from Bangui , 9 . 9 days for the persons from Bimbo and Bégoua , and 18 . 1 days for the persons from the other prefectures ( p-value < 0 . 001 ) . Exposed males were older and more likely to have multiple wounds . Children were significantly more likely to be wounded on the face or the trunk but less on the lower limb , while adults were significantly more likely to be bitten on the lower limb ( p-values < 0 . 001 ) ( Table 2 ) . In addition , persons exposed were asked about the rabies vaccination status of the dogs involved in the exposure . Fifty-eight persons declared to have been exposed to a dog vaccinated but only five of them were able to give details as brand name of the vaccine and/or date of vaccination . The Fig 2 summarizes the data on rabies surveillance in the CAR in 2012 . Thirteen dogs were diagnosed as having rabies of 16 samples received from outside of Bangui and its suburbs . They originated from six different prefectures: Lobaye , Ombella M’Poko , Mambéré Kadéï , Ouham Pendé , Kémo and Ouaka ( Fig 2A ) . Most of the persons who were exposed outside of Bangui and its suburbs came from the following prefectures: Ombella M’Poko ( 17 exposures ) , Ouaka ( 12 exposures ) , and Ouham and Mambéré Kadéï ( 10 exposures both ) ( Fig 2B ) . Most of the canine rabies cases that occurred outside of Bangui and its suburbs were confirmed between July and December ( 12 cases of 13 ) . Most of the human exposures that occurred outside of Bangui and its suburbs were reported between June and December with 52 exposures of 64 ( Fig 2C ) . In Bangui and its suburbs , most of the canine rabies cases were from the 4th ( with 13 rabid dogs ) , the 3rd and the 6th districts of Bangui ( with seven reported rabid dogs both ) ( Fig 2D ) . Most of the persons who were exposed in Bangui and its suburbs were from the 4th district ( 216 exposures ) , the 5th district ( 159 exposures ) , and the 3rd and the 8th districts ( 129 and 123 exposures , respectively ) ( Fig 2E ) . Most of the canine rabies cases that occurred in Bangui and its suburbs were confirmed between June and October ( 43 cases of 55 ) while most of the human exposures were reported during the months of June ( 86 cases ) , July ( 95 ) , August ( 118 ) and September ( 138 cases ) ( Fig 2F ) . In the most affected districts , the peak happened in June for the 3rd district ( 20 exposures ) , in August for the 5th and the 8th districts ( 33 and 16 exposures respectively ) , and in September for the 4th district ( 56 exposures ) . These data suggest that the CAR was hit by an epidemic of canine rabies with a peak that happened during the second half of the year 2012 ( Figs 1 and 2 ) . We found a mean number of 0 . 7 ( standard deviation 1 . 4 ) persons exposed when no rabid dog was reported the same week in the same area , against 4 . 3 ( standard deviation 5 . 4 ) persons exposed when at least one rabid dog was reported in the same week in the same area . We found a significant correlation between the number of rabid dogs and the number of persons exposed ( Spearman Rho 0 . 28 , P <0 . 001 ) by spatiotemporal unit ( Fig 3 ) . The correlation was also significant with the number of persons who eventually received PEP ( Spearman Rho 0 . 31 , p-values < 0 . 001 ) . The associations were confirmed when using a model taking into account the temporal autocorrelation ( β = 0 . 80 and p-value < 0 . 001 for the number of persons at risk; and β = 1 . 09 , p-value < 0 . 001 for the number of persons having received post-exposure prophylaxis ) . From the 67 PCR positive rabid dog samples , 62 sequences of the N gene were obtained [GenBank: KF34677 to KF734738] . These sequences were grouped into three variants based on their similarity . The phylogenetic analysis showed that these variants clustered within two clades: Africa I and II ( Fig 4 ) . The Africa I virus isolates described in this study ( seven samples ) are close to viruses isolated in the CAR in 2000 , and in 2003 to 2007 ( identity ≥ 99% ) indicating that regular circulation of this variant , though a minority in 2012 , over the time since 2000 . Among the eight main groups of Africa II RABV , the strains isolated in 2012 from the CAR fell within groups c ( 32 samples ) and e ( 23 samples ) [16] . The Africa II group c isolates are close to viruses isolated from Chad , Ivory Coast , Mauritania , Mali Burkina Faso and Senegal ( identity around 96–97% ) . The Africa II group e viruses are close to viruses isolated in Chad , Niger and Nigeria ( identity ≥ 98% ) . In Bangui , all these three variants were found but the Africa I viruses were a small minority with only three samples . Outside of Bangui , these three variants were found having a specific geographic distribution . The Africa I and Africa II isolates were only found in the west of the CAR while the Africa II group e viruses were only found north-east of Bangui ( Fig 4 ) .
Taken together , these data indicate that canine rabies was endemic in the CAR in 2012 and had an important impact on the human health , as shown by the hundreds of exposed persons who have received PEP . The vaccine coverage of domestic dogs against rabies was very low . Implementation of effective public health interventions including mass dog vaccination but also the improvement of the surveillance and the access to PEP is urgently needed to control rabies in the CAR . | Rabies is a widespread fatal , but preventable , viral disease transmitted from animals to humans . It has been estimated that tens of thousands of people die of rabies annually , mainly in developing countries where rabies is still a neglected disease . In the Central African Republic ( CAR ) , a poor country located at the heart of Africa , rabies is endemic , but its burden remains poorly investigated . Here , we reported a comprehensive analysis of data for 2012 from the Institut Pasteur in Bangui , the capital of the CAR . In 2012 , 966 persons reported exposure to suspicious animals , mainly dogs , and 632 received post-exposure rabies vaccination . Most of these people were from Bangui area and were under 15-years of age . Meanwhile , 82 samples from suspected rabid dogs were tested and 69 were confirmed positive . Most of the rabid dogs were owned although unvaccinated . Positive samples were sequenced and we found that three different variants actively circulated in 2012 . Theses variants clustered with other viruses found in surroundings countries . Our data suggested that canine rabies was endemic in the CAR with a detrimental impact on human health . We conclude that mass vaccination of domestic dogs and the improvement of the surveillance and the access to post-exposure vaccination are urgently needed to control rabies in the CAR . | [
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"rabies... | 2016 | Surveillance of Canine Rabies in the Central African Republic: Impact on Human Health and Molecular Epidemiology |
Staphylococcus aureus contains an autoinducing quorum-sensing system encoded within the agr operon that coordinates expression of virulence genes required for invasive infection . Allelic variation within agr has generated four agr specific groups , agr I–IV , each of which secretes a distinct autoinducing peptide pheromone ( AIP1-4 ) that drives agr signaling . Because agr signaling mediates a phenotypic change in this pathogen from an adherent colonizing phenotype to one associated with considerable tissue injury and invasiveness , we postulated that a significant contribution to host defense against tissue damaging and invasive infections could be provided by innate immune mechanisms that antagonize agr signaling . We determined whether two host defense factors that inhibit AIP1-induced agrI signaling , Nox2 and apolipoprotein B ( apoB ) , also contribute to innate control of AIP3-induced agrIII signaling . We hypothesized that apoB and Nox2 would function differently against AIP3 , which differs from AIP1 in amino acid sequence and length . Here we show that unlike AIP1 , AIP3 is resistant to direct oxidant inactivation by Nox2 characteristic ROS . Rather , the contribution of Nox2 to defense against agrIII signaling is through oxidation of LDL . ApoB in the context of oxLDL , and not LDL , provides optimal host defense against S . aureus agrIII infection by binding the secreted signaling peptide , AIP3 , and preventing expression of the agr-driven virulence factors which mediate invasive infection . ApoB within the context of oxLDL also binds AIP 1-4 and oxLDL antagonizes agr signaling by all four agr alleles . Our results suggest that Nox2-mediated oxidation of LDL facilitates a conformational change in apoB to one sufficient for binding and sequestration of all four AIPs , demonstrating the interdependence of apoB and Nox2 in host defense against agr signaling . These data reveal a novel role for oxLDL in host defense against S . aureus quorum-sensing signaling .
Staphylococcus aureus uses global gene regulation to coordinate gene transcription required for survival within distinct host niches [1]–[10] . One of these global regulators is a four gene operon , agr , that encodes a quorum sensing system that combines secretion of an autoinducing peptide pheromone ( AIP ) with a sensor regulator . Activation of this system upregulates genes for toxins , hemolysins , lytic enzymes , and metabolic pathways that are required for a phenotypic change in this pathogen from an adherent colonizing phenotype to one associated with significant tissue injury and invasiveness [11]–[13] . agr upregulated virulence factors are associated with acute infections particularly at epithelial barriers like the skin and lung [13]–[18] and induce death and dysfunction of phagocytic and epithelial cells responsible for bactericidal clearance [10] , [19]–[23] . Therefore , a significant contribution to host defense against tissue damaging and invasive infections at these sites could be provided by innate immune mechanisms that antagonize agr signaling thus permitting optimal phagocyte and epithelial cell function . While the molecular mechanisms involved in agr sensing and signaling have been extensively studied [11] , the mechanisms by which host innate barriers antagonize agr sensing to control tissue damage and cell injury have not been fully elucidated [24]–[29] . In this regard , we previously reported that both the Nox2 NADPH oxidase and the major structural protein of very low and low density serum lipoproteins ( VLDL , LDL ) , apolipoprotein B ( apoB ) , antagonize AIP dependent activation of its cognate receptor within the agrI allele [24] , [27] . Because three additional agr alleles are represented within the species S . aureus and because all four alleles are associated with significant disease in humans [30] , [31] , we postulated that either or both of these innate immune barriers could be important for antagonism of signaling by other agr types . Each agr allele encodes a unique secreted AIP that differs in amino acid content and length but contains a common thiolactone bond that creates a 5-membered ring essential for biologic function [11] . Importantly , secretion of AIP represents an opportunity for host or environmental control of agr signaling by either direct modification of key amino acids , cleavage of the thiolactone bond , proteolytic degradation , or sequestration to prevent AIP binding to its receptor , AgrC . For AIP1 , reactive oxygen species ( ROS ) generated by the Nox2 NADPH oxidase expressed in phagocytes and other cells directly modify a key C-terminal member of the thiolactone ring , a methionine , to form methionine sulfoxide [27] . While retaining its cyclic structure , this modification is sufficient to render AIP1 biologically inactive . In addition , the large structural protein of serum LDL , apoB , binds directly to cyclic AIP1 , but not its inactive linear form , preventing its activation of its cognate receptor AgrC [24] . Importantly , loss of either Nox2 or apoB in the form of LDL is sufficient to promote agrI-mediated invasive infection beyond epithelial and mucosal barriers . To extend these studies to the other agr alleles , we first focused on the contribution of these two barriers to host antagonism of agrIII signaling . AIP3 is shorter and composed of amino acids that are more resistant to oxidant modification as compared to AIP1 and therefore might be less amenable to control by either apoB or ROS . We hypothesized that Nox2 and apoB within the context of its serum lipoproteins would differ in the molecular mechanism by which they antagonize agrIII signaling and that this difference would impact the susceptibility to invasive infection in mouse models that lack these innate barriers . Here , we show that optimal host innate defense against agrIII-mediated signaling requires binding and sequestration of AIP3 by apoB , not in the form of LDL but in LDL oxidized by Nox2 . Importantly , these studies revealed an important role for oxLDL in binding to and antagonizing signaling by all four agr alleles . In addition , while ROS directly inactivate AIP1 and 4 , they do not affect the biologic function of either AIP 2 or 3 . Thus , the contribution of Nox2 in antagonizing agr signaling for these alleles is primarily through the production of oxLDL . OxLDL-mediated antagonism of agr signaling inhibits agr driven virulence factor expression by all four alleles , providing a mechanistic basis for its importance in preventing invasive S . aureus infection which we demonstrate in a murine agrIII-mediated skin infection model . Therefore , while best studied for its contribution to atherosclerosis , our data reveal a novel role for oxLDL as a host defense effector that controls S . aureus agr-mediated signaling .
Innate immunity controls agrI-mediated invasive S . aureus infection by early extravasation of activated neutrophils and apoB-containing plasma lipoproteins that act to antagonize agrI signaling [24] , [27] . Induction of agr signaling requires AIP cyclized through a 5-membered thiolactone ring . AIP binds and activates AgrC which generates phosphorylated AgrA . Phosphorylated AgrA activates the agr P3 promoter generating the effector molecule RNAIII . ApoB recognizes the cyclic , active form of AIP1 and prevents binding to and signaling through its cognate AgrC receptor [24] . Whereas AIP1 and AIP3 differ in amino acid sequence and in length of the amino terminal tail , they both contain the thiolactone ring ( Fig . 1A ) . We postulated that apoB would antagonize AIP3-dependent activation of AgrC , but that conformational changes of apoB might be required for optimal antagonism of the smaller peptide pheromone of the agrIII strains . In addition to binding the agr P3 promoter , phosphorylated AgrA directly enhances transcription of genes encoding phenol soluble modulin virulence factors ( PSM alpha , PSM beta ) [32]–[34] . ApoB alone significantly inhibited transcription of psmα in clinical isolates USA300 LAC ( agrI ) and USA400 MW2 ( agrIII ) [32] , [35]–[37] , whereas LDL at equivalent apoB concentration did not inhibit psmα transcription in the agrIII strain MW2 ( Fig . S1A ) . The ability of apoB alone to inhibit agrIII-mediated signaling independent of LDL suggests that the conformation of apoB in LDL is not optimal for binding AIP3 . Oxidation of LDL is known to alter the conformation of apoB within the lipoprotein particle [38]–[40] . We predicted that apoB present in oxLDL would significantly antagonize agrIII-mediated signaling compared to LDL . Using strain agrIII MW2 ( [agr::P3-yfp] in which activation of the agr::P3 promoter drives expression of YFP [41] , both apoB alone and oxLDL at equivalent apoB concentration significantly antagonized agr::P3 promoter activation as compared to LDL ( Fig . 1B ) . These results were not due to lipoprotein effects on bacterial viability as demonstrated by the number of colony forming units ( cfus ) . Intriguingly , LDL and oxLDL were equally efficacious in antagonism of AIP1 dependent signaling ( Fig . S1B ) , indicating that apoB within either particle is sufficient to neutralize AIP1 . To confirm that apoB , and not a lipid component of oxLDL was responsible for antagonizing AIP3-mediated signaling , we determined the effects of antibodies against apoB on the ability of apoB and oxLDL to inhibit agrIII-dependent signaling . Pre-treatment of apoB and oxLDL with an antibody specific to a linear peptide within apoB , but not with an isotype control antibody , significantly inhibited apoB-mediated antagonism of agr::P3 promoter activation in this agrIII strain ( Fig . 1C ) . Thus apolipoprotein B is sufficient to antagonize agrIII-dependent signaling and optimal antagonism requires apoB presented in the context of oxLDL rather than LDL . ApoB antagonism of agr type I-mediated virulence entails direct binding to AIP1 [24] , and based on the results of our signaling assays , we predicted that oxLDL would bind AIP3 at significantly higher levels relative to LDL . We analyzed binding of LDL , apoB and oxLDL , at equivalent apoB concentrations to immobilized AIP1 and AIP3 via Surface Plasmon Resonance ( SPR ) . As expected , oxLDL and apoB bound at significantly higher levels to cyclic AIP3 as compared to LDL ( Fig . 1D ) . In contrast , all 3 bound equally to AIP1 ( Fig . S1C ) . These data support our results on the requirement of oxLDL for antagonism of AIP3-dependent signaling , whereas LDL alone was sufficient to antagonize AIP1 signaling . None of the 3 lipoproteins bound significantly to linear AIP3 ( L-AIP3 ) ( data not shown ) , proving that apoB recognition of AIP3 requires the active , cyclic conformation of AIP3 . Furthermore , AIP3 binding by apoB and oxLDL was significantly inhibited by antibody specific to a linear peptide within apoB but not control antibody ( Fig . 1D ) , indicating that apoB is responsible for binding of oxLDL to AIP3 . The ability of the anti-peptide antibody to reverse functional antagonism in the reporter assay and to block AIP3 binding by both apoB and oxLDL , but not LDL , suggests a conformation-dependent AIP3 binding site within apoB that is also present in oxLDL but absent in LDL . Therefore , the mechanism by which oxLDL antagonizes agrIII signaling includes enhanced binding of AIP3 relative to LDL , and this binding is mediated by apoB and not the lipid components of oxLDL . Although AIP expressed from each of the four agr alleles differ in amino acid sequence and length , the peptides share a common five-membered thiolactone bond . To determine whether oxLDL universally binds S . aureus AIPs and antagonizes signaling by each of the four agr alleles , we also measured oxLDL binding to AIP2 and AIP4 ( Figure S1D , E ) by SPR . OxLDL bound immobilized AIP2 and AIP4 , but not the inactive linear peptides , in a dose-dependent manner again illustrating the necessity of the thiolactone bond for apoB-dependent binding . Furthermore , oxLDL antagonized agr::P3 promoter activation by both an agrII ( AH430 – SA502A ) and agrIV ( AH1872 – MN TG ) clinical isolate ( Fig . S1F ) . These data suggest that oxLDL could act as a universal innate inhibitor of agr-signaling mediated by each of the four S . aureus agr alleles . ROS production by the NADPH oxidase Nox2 is essential for control of invasive S . aureus infection [42]–[44] , and facilitates oxidation of LDL [45] , [46] . We postulated that Nox2 would contribute to apoB-mediated control of agrIII S . aureus virulence by oxidation of LDL . If correct , LDL from the serum of Nox2 knockout mice [42] would primarily be in the form of native LDL whereas LDL from the serum of wild-type mice would include oxLDL and would better inhibit agrIII-signaling relative to LDL from Nox2−/− mice . We examined serum from wild-type and Nox2−/− mice for antagonism of agr::P3 promoter activation in the agrIII isolate MW2 and for the presence of LDL and oxLDL . As predicted , serum from wild-type mice , but not from Nox2−/− mice , significantly antagonized agr::P3 promoter ( Fig . 1E ) , and addition of oxLDL , but not LDL , to serum from Nox2−/− mice restored agrIII-antagonism to wild-type levels ( Fig . 1F ) . Relative serum levels of oxLDL and LDL from wild-type and Nox2−/− mice were determined by immunoblot analysis using an antibody against apoB and a monoclonal antibody ( E06 ) which detects epitopes present in oxLDL but absent in LDL [47] , [48] . Serum from wild-type mice had a significantly higher E06/apoB ratio compared to Nox2−/− mice ( Fig . 1G ) , indicating that serum from wild-type mice contains more oxLDL than serum from Nox2−/− mice . Although significantly reduced compared to wild-type mice , serum of Nox2−/− mice had some E06 reactivity , indicating the presence of small amounts of oxLDL resulting from oxidation mechanisms distinct from Nox2 . Interestingly , the amount of E06 positivity in the LDL control fraction reflects a nominal oxidation level in LDL preparations that may vary by preparation , method and storage . This variable level of nominal oxidation likely resulted in the small but significant LDL antagonism of agrIII-signaling observed in some experiments ( Fig . 1B ) . To prove that apoB-containing lipoprotein oxidized by Nox2 is the serum component from wild-type mice responsible for blocking agrIII activation , we measured the ability of LDL purified from the serum of wild-type versus Nox2−/− mice to antagonize agrIII-dependent quorum-sensing signaling . At equivalent protein concentrations , LDL purified from the serum of Nox2−/− mice did not inhibit agr::P3 promoter activation in the agrIII isolate MW2 while LDL from wild-type mice significantly inhibited agrIII signaling ( Fig . 1H ) . There was no significant inhibition of agr::P3 promoter activation in the presence of either Nox2−/− LDL or our human LDL control with minimal EO6 positivity , further demonstrating the requirement for oxLDL in agrIII-antagonism . In addition , purified LDL from wild-type mice had a 30% greater lipid oxidation level compared to LDL from Nox2−/− mice ( Fig . S2A ) . Thus , the ability of serum to control agrIII-signaling in vitro is dictated by the presence of oxLDL within that serum and Nox2 is a major contributor to oxidation of serum LDL . These data indicate that Nox2 contributes to host control of agrIII-mediated quorum sensing in part via oxidation of LDL that induces a conformational change in apoB required for optimal AIP3 binding and sequestration . Virulence factors regulated by agr are essential for invasive skin infection and invasion of bacteria from the host epidermis into the underlying dermis [13] , [16] , [18] , [24] . Having demonstrated that the ability of serum to control agrIII-signaling is attributable to oxLDL , we postulated that the ability of serum to antagonize quorum sensing would predict in vivo susceptibility to agrIII-invasive infection . We used the drug 4APP , which significantly reduces serum apoB levels by inhibition of lipoprotein secretion from the liver , to reduce apoB [49] , [50] in wild-type and Nox2−/− mice prior to infection with the agrIII strain MW2 . Although 4APP treatment decreased serum levels of apoB-containing lipoproteins by 49% compared to buffer controls ( Fig . S2B ) , serum from these mice was as effective as serum from vehicle treated mice in inhibiting agr::P3 promoter activation in MW2 ( Fig . 2A ) suggesting that 4APP treatment alone did not significantly affect levels of oxLDL . To confirm this , we measured lipid oxidation of purified LDL from the 4APP- or buffer control-treated wild-type mice . At equivalent protein concentrations , LDL purified from the 4APP treated wild-type mice had an almost 2-fold greater level of lipid oxidation compared to LDL from vehicle treated wild-type mice ( Fig . S2C ) . Therefore , although the concentration of LDL was reduced by 49% in serum of 4APP treated mice , the overall concentration of oxLDL was not significantly affected , resulting in equivalent serum antagonism of agrIII-signaling . In contrast , serum from Nox2−/− mice , that contains significantly reduced levels of oxLDL compared to wild-type mice ( Fig . 1G ) , was not optimal for inhibition of agr::P3 promoter activation in the agrIII isolate MW2 and serum from 4APP-treated Nox2−/− mice was even less effective ( Fig . 2A ) . This suggests that loss of LDL oxidized by both Nox2 and other mechanisms results in the greatest impairment in agrIII-antagonism . Treatment of wild-type mice with 4APP reduced plasma levels of LDL ( Fig . S2B ) but did not alter the ability of the mice to oxidize LDL still being secreted from the liver ( Fig . S2C ) . Because serum from vehicle and 4APP treated wild-type mice had similar levels of oxLDL and equally antagonized agrIII-signaling in vitro ( Fig . 2A ) , we predicted that 4APP treatment alone would not increase the susceptibility of wild-type mice to invasive MW2 infection . Using an air-pouch model of infection [24] , [27] , [28] , [51]–[54] to determine agrIII-dependent invasion of bacteria from the epidermis into the dermis ( Fig . 2B ) , we infected wild-type mice treated with either 4APP or vehicle with a dose of MW2 that wild-type mice are able to maintain at the epithelial barrier . There was no increased susceptibility of the 4APP treated mice to this dose ( Fig . 2C ) . These results confirmed our in vitro data that the level of oxLDL in these mice was sufficient to prevent agrIII-quorum sensing required for invasive infection . These data demonstrate that whereas reduction of LDL in the serum of Nox2 competent mice is sufficient to increase susceptibility to agr type I S . aureus infection [24] , it does not increase susceptibility to agrIII invasive infection because oxLDL levels are sufficient for protection . Our serum data indicate that in the absence of Nox2 , the resulting reduction of oxLDL significantly impairs apoB-mediated antagonism of agrIII-dependent quorum sensing indicating that apoB within oxLDL is primarily responsible for suppressing agrIII signaling ( Fig . 2A ) . Therefore , we predicted that 4APP treatment of mice lacking Nox2 would significantly increase susceptibility to agrIII-dependent MW2 invasive infection beyond the loss of Nox2 alone . Because Nox2−/− mice are highly susceptible to S . aureus infection due to the critical role of reactive oxidants in host defense against this pathogen [42] , and because we predicted that susceptibility would be further increased following 4APP treatment , a reduced inoculum of MW2 was used in these experiments ( Fig . 2D ) relative to the other infection studies ( Fig . 2C , E ) . As predicted , Nox2 knockout mice treated with 4APP prior to infection with MW2 had significantly increased bacterial invasion into the dermis , morbidity and bacterial burden in the spleen compared to control treated Nox2−/− mice ( Fig . 2D ) . Moreover , Nox2−/− mice treated with 4APP were not more susceptible to infection with an isogenic agr deletion mutant of MW2 ( Δagr ) compared to controls , confirming that the contribution of Nox2 to apoB-mediated host defense is specific to control of agr-mediated pathogenesis . In contrast , infection of Nox2−/− mice with MW2 at an inoculum readily controlled by wild-type mice resulted in significant dermal invasion , morbidity and bacterial burden in the spleen as compared to wild-type mice . In addition , infection with the MW2 agr deletion mutant also resulted in increased dissemination to the spleen ( Fig . 2E ) . Therefore , unlike the agr-specific role of apoB , the protective role of Nox2 is not limited to control of agr-mediated virulence but has broader implications for host antibacterial defense such as contributing to direct killing of bacteria in the spleen [46] , [55]–[57] . These data confirm that apoB-mediated serum antagonism of agrIII-signaling in vitro is a predictor of in vivo susceptibility to S . aureus agrIII-dependent invasive infection . In addition , the increased susceptibility to agrIII-mediated invasive infection following reduction of serum apoB is dependent upon the presence or absence of Nox2 , indicating a novel role for Nox2 in host defense against agrIII-dependent infection by promoting apoB-mediated antagonism of quorum sensing . Whereas reduction of apoB in the context of LDL is not sufficient to increase susceptibility to agrIII-mediated invasive infection , reduction of apoB in the form of oxLDL is sufficient . Quorum-sensing through agr regulates expression of over 100 genes , many of which encode virulence factors necessary for invasive infection [11] , [13] , [58] . To confirm that the role of apoB extends to agrIII-dependent transcription and translation of virulence factors and that this protection was not limited to isolate MW2 , we first determined whether oxLDL inhibited agrIII-dependent transcription by randomly selected MRSA and methicillin sensitive S . aureus ( MSSA ) agrIII clinical isolates . OxLDL significantly inhibited transcription of both the agr effector molecule RNAIII and of a key agr regulated virulence factor , alpha hemolysin ( Hla ) , by both MRSA and MSSA agrIII clinical isolates ( Fig . 3A , B ) . Likewise , oxLDL significantly inhibited production of Hla as determined by functional assay ( Fig . 3C ) . This effect was not due to direct lipoprotein interaction with Hla because neither LDL nor oxLDL reduced the activity of purified Hla ( Fig . S3A ) . Although two of the selected clinical isolates failed to produce the virulence factor staphylococcal lipase , oxLDL again significantly inhibited agrIII-dependent lipase secretion as determined by functional assay of the remaining isolates ( Fig . 3D ) . The decrease in lipase activity was not due to direct inhibition by the lipoproteins ( Fig . S3B ) . These results extend our observations of oxLDL-mediated control of agrIII-signaling and invasive infection to virulence factor expression by current clinical isolates of both MRSA and MSSA indicating that the contribution of oxLDL as a barrier to agrIII infection is not limited to a single genetic background of the pathogen . AIP binding and agr::P3 promoter activation analyses suggest that oxLDL would also inhibit agr-dependent transcription and virulence factor translation by agrI , agrII and agrIV MRSA and MSSA clinical isolates . As predicted , oxLDL antagonized agr-dependent transcription of RNAIII and hla along with production of functional Hla in clinical isolates representing agrI , agrII and agrIV alleles ( Fig . S3C–E ) . Therefore , oxLDL can serve as a universal agr antagonist by inhibiting agr-signaling and virulence factor expression by agrI–IV clinical isolates . Based on published literature and our in vivo data [45] , [46] , [59]–[62] , we postulated that in vitro oxidation of LDL by ROS would be sufficient to promote apoB-mediated antagonism of agrIII-signaling . Previous in vitro studies have shown that isolated neutrophils induce lipid oxidation of LDL [45] , [46] , [63] . Therefore , we first determined the ability of HOCl , a ROS released by activated neutrophils via Nox2 and myeloperoxidase [57] , [64] , to enhance inhibition of agr::P3 promoter activation by LDL in the agrIII isolate MW2 . Exposure of LDL to HOCl significantly increased antagonism of AIP3-induced agr::P3 promoter activation compared to control LDL ( Fig . 4A ) . This effect was dependent upon oxidative modification of LDL because the ROS scavenger N-acetylmethionine ( NAM ) blocked the increase in antagonism . To demonstrate that increased agrIII-antagonism following oxidation of LDL is not limited to a single ROS , we evaluated singlet oxygen for the ability to enhance agrIII antagonism by LDL . Singlet oxygen ( 1O2 ) is a strong oxidizing agent released by activated neutrophils and contributes significantly to neutrophil extracellular trap ( NET ) formation , ozone mediated bacterial killing and ozone formation in atherosclerotic plaques as well as conformational changes of apoB within LDL [38] , [56] , [65] , [66] . In addition , 1O2 induces lipid oxidation of LDL [63] , [67] . As expected , exposure of LDL to 1O2 ( Fig . 4B ) significantly increased the ability of LDL , but not apoB or oxLDL , to antagonize agrIII-signaling and antagonism increased along with the oxidant dose ( Fig . 4C ) . In addition , increased antagonism of agrIII-signaling by 1O2 or HOCl-treated LDL corresponded with a significant increase in LDL lipid oxidation compared to control ( Fig . 4D ) . Therefore , in vitro oxidation of LDL by ROS representative of activated Nox2 is sufficient to significantly increase apoB-mediated antagonism of agrIII-dependent quorum sensing compared to untreated LDL . Extravasation of activated neutrophils to sites of agrI S . aureus infection makes available extracellular ROS that provide defense in part by oxidizing the C-terminal methionine of AIP1 rendering it biologically inactive [27] . Because AIP3 lacks this methionine and the susceptibility of the common AIP thiolactone to oxidative inactivation has not been addressed , we postulated that AIP3 would be resistant to inactivation by ROS relative to AIP1 . At concentrations of HOCl that readily inactivated AIP1 , AIP3 retained biologic function ( Figure 4E ) . At higher HOCl concentrations , there was a partial loss in AIP3 function that most likely resulted from fragmentation of the peptide as mass spectrometry failed to identify AIP3 species with charge to mass ratios suggestive of linearization or addition of oxygen atoms ( data not shown ) . In contrast , mass spectrometry clearly revealed oxidation of the AIP1 methionine residue as was previously reported ( data not shown ) [27] . To further demonstrate the resistance of AIP3 to ROS-mediated inactivation , we assayed singlet oxygen for the ability to inactivate AIP3 . As expected , AIP3 was resistant to inactivation by 1O2 under conditions in which AIP1 signaling decreased rapidly as a function of time ( Fig . 4F ) . These results were not due to changes in bacterial growth resulting from exposure to residual ROS , as the cfus were consistent between both treated and untreated groups ( data not shown ) . Because both AIP1 and AIP3 contain the 5-membered thiolactone ring , these results suggest that this ring is not a target for inactivation under the conditions examined here . To confirm that the AIP thiolactone is not a primary target for oxidative modification , we evaluated the ability of excess ethylthioacetate , a thiolactone mimetic , to protect AIP1 from oxidative loss of function by 1O2 . At 10-fold molar excess , ethylthioacetate did not protect AIP1 from inactivation by 1O2 ( Fig . 4G ) , indicating that the thiolactone does not compete with the AIP1 methionine for oxidative modification and therefore the thiolactone is not a primary target of oxidation . These data demonstrate that these ROS do not provide defense against agrIII-mediated signaling by direct oxidative inactivation of AIP3 but rather through enhancement of apoB-mediated control of agrIII-virulence by oxidative modification of LDL . ROS-mediated inactivation of AIP1 but not AIP3 suggests that methionine is the primary target for oxidative inactivation of AIP . To extend these observations to the role of ROS in oxidative inactivation of other AIPs , we postulated that 1O2 would inactivate AIP4 , which includes a C-terminal methionine residue , but that AIP2 which lacks methionine would be resistant to inactivation . As predicted , exposure of AIP4 to 1O2 significantly inhibited AIP4-induced agr::P3 promoter activation in the agrIV isolate MN TG , whereas AIP2 function remained unchanged ( Fig . S4 ) . These data suggest that in addition to oxidation of LDL , ROS can play an independent role in defense against agrI and agrIV quorum sensing through direct oxidative inactivation of AIP1 and AIP4 . Serum proteins extravasate into inflamed tissues and aid in host defense by providing antibody and complement necessary for opsonization [68] . We predicted that extravasated oxLDL present at the site of infection would also contribute to host defense by antagonizing agrIII invasive infection in vivo . To address this , we first determined relative levels of oxLDL and LDL in lavages of air-pouches of wild-type and Nox2−/− mice 28 hours after infection with MW2 . As expected , oxLDL was present in lavages from wild-type mice who were protected from agrIII invasion , but was largely absent in lavages from Nox2−/− mice which were highly susceptible to MW2 invasion ( Fig . 5A ) . From these results , we predicted that the addition of oxLDL , but not native LDL , to the air-pouch at the time of infection of Nox2−/− mice would inhibit agrIII-signaling . To test this we infected air-pouches of 4APP-treated Nox2−/− mice with agrIII isolate MW2 [agr::P3-yfp] in the presence of oxLDL , LDL or buffer control . Oxidized LDL , but not LDL , introduced into the air-pouch at the time of infection significantly antagonized AIP3-mediated agr::P3 activation in the resulting air-pouch lavage four hours after infection ( Fig . 5B ) . Weight loss is a primary measure of morbidity in this model and mice treated with oxLDL at the time of infection lost significantly less of their total body weight at four and eight hours post-infection compared to controls ( Fig . S5 ) . Thus the presence of oxLDL in the air-pouch at the time of infection significantly inhibited both agr-signaling and morbidity as measured by weight loss . Both the presence of oxLDL in air-pouch lavages from infected wild-type mice and restoration of agrIII antagonism by addition of oxLDL , but not LDL , to the air-pouch of 4APP-treated Nox2−/− mice , indicates that Nox2-mediated apoB control of agrIII-dependent signaling works directly at the site of infection to prevent agr type III-dependent signaling and its pathological consequences .
Host innate immunity is critical for maintaining a defensive barrier against opportunistic pathogens such as Staphylococcus aureus which colonize skin and mucosal surfaces . In order to breach these defensive barriers , S . aureus uses the agr quorum sensing system to coordinate expression of virulence genes needed for invasion and to evade host defensive mechanisms . The fact that most humans are able to limit S . aureus infections to minor ones of skin and skin structures [69] suggests that host factors capable of inhibiting quorum sensing signaling mediated by each of the four agr alleles could contribute to host defense against invasive infection . This antagonism would thus promote host bacterial killing and clearing mechanisms . Here , we extend our knowledge of host inhibition of S . aureus agrI-signaling to host control of quorum-sensing dependent virulence mediated by agrIII . Importantly , our studies into host control of agrIII signaling revealed an important role for the conformation of apoB within lipoprotein particles such that oxLDL was found to be a universal inhibitor of agr signaling in all four agr alleles . We previously reported that both apolipoprotein B , the structural protein of VLDL and LDL , and ROS generated by the phagocyte NADPH oxidase ( Nox2 ) , provide unique barriers against S . aureus agrI-mediated virulence and the loss of either significantly increases susceptibility to invasive infection [24] , [27] . Specifically , Nox2 derived ROS directly inactivate AIP1 by methionine oxidation whereas the apoB component of LDL binds and sequesters AIP1 to prevent agrI-mediated virulence . This current work demonstrates that the roles of apoB and Nox2 in defense against agrIII-mediated infections are interdependent . Unlike AIP1 , AIP3 is resistant to oxidation and direct inactivation by ROS characteristically produced by Nox2 . Instead , the contribution of Nox2 to host innate defense against S . aureus agrIII-dependent quorum sensing is through oxidation of LDL . ApoB in the context of oxLDL , and not LDL , provides optimal host defense against S . aureus agrIII infection by binding the secreted signaling peptide , AIP3 , and preventing expression of the agr-driven virulence factors which mediate invasive infection . Our results suggest that oxidation of LDL facilitates a conformational change in apoB to one required for optimal binding of AIP3 and apoB-mediated defense against agrIII-dependent virulence . Intriguingly , agrI- , agrII- and agrIV-signaling was also antagonized by oxLDL in vitro , suggesting that apoB within oxLDL is sufficient for antagonism of signaling by each of the four agr alleles . Each of the four S . aureus agr alleles are associated with invasive human infections which may range in severity from mild skin and soft tissue infections to severe disease such as osteomyelitis , endocarditis , necrotizing pneumonia and bacteremia [31] . Our data suggest that oxLDL may provide protection against S . aureus infections of any agr type in which agr-signaling contributes to pathogenesis . In contrast , we would predict that oxLDL would play a minimal role in host defense in chronic or device related infections in which agr signaling may be less relevant [70]–[73] . Our data show that LDL and oxLDL are present at the site of infection and prevent quorum-sensing dependent invasion of agrIII S . aureus into the underlying dermis . This suggests that other serum proteins which extravasate to the site of infection may also contribute to defense against agr-mediated signaling . Recently , Surewaard et al [74] described a novel role for VLDL , LDL and HDL in binding and inactivation of phenol soluble modulins ( PSM ) , an important group of agr-regulated S . aureus virulence factors . Among these lipoproteins , HDL was attributed with the highest PSM scavenging activity and , using a wide variety of in vitro assays , demonstrated inhibition of all PSMs investigated . However , unlike our data demonstrating apoB binding and antagonism of AIP1-4 , lipoprotein-mediated inhibition of PSMs was attributed to the lipid and not the protein components of the lipoprotein particles . Another serum component , hemoglobin , also suppresses agr function when released from red blood cells [26] , [75] . Once agr-signaling is initiated and PSMs as well as hemolysins needed to lyse RBCs for release of hemoglobin have begun to be expressed , both lipoprotein-mediated scavenging of PSMs and hemoglobin-mediated suppression of agr-signaling could clearly contribute to prevention of further agr-mediated virulence and invasion of host tissues . Although these additional mechanisms of controlling quorum-sensing dependent S . aureus virulence may contribute in part to our in vivo results , the following factors support the primary role of apoB-mediated control of agr-dependent virulence in our model: 1 ) apoB binds immobilized AIP1-4 and apoB and oxLDL antagonize agr-dependent P3 promoter activation , RNAIII , psmα and hla transcription and Hla production in vitro in both laboratory strains and clinical isolates , 2 ) addition of oxLDL , but not LDL , to MW2 infected air-pouches of LDL-deficient Nox2−/− mice was sufficient to suppress quorum-sensing independent of other lipoproteins and 3 ) compared to untreated mice , 4APP-treated wild-type mice with equivalent oxLDL levels were not more susceptible to MW2 invasive infection , suggesting that oxLDL-mediated control of agrIII-dependent virulence factor expression predominated and offset the need for lipoprotein scavenging of PSMs . Therefore , apoB plays a unique role in inhibition of agr signaling upon initiation of infection . All of these findings highlight the host's multi-tiered innate defense system to combat S . aureus agr-mediated virulence and suggest that conditions which result in decreased lipoprotein levels may contribute on more than one level to host susceptibility to S . aureus invasive infection . Our data comparing oxLDL and LDL binding of AIP1 versus AIP3 demonstrate that whereas oxLDL provides optimal binding and antagonism of AIP3 , both lipoprotein particles are equally efficient at binding AIP1 . Such differences in the ability of apoB-containing lipoprotein particles to bind and antagonize these AIPs may result from multiple factors . One explanation could be that although both peptides contain the conserved thiolactone bond , the length and sequence variation between AIP1 and AIP3 may suggest that each has a unique binding site on apoB . Because oxidation of LDL is known to alter the conformation of apoB within the particle , oxLDL may present apoB in the ideal conformation for binding AIP3 [39] , [40] , [76] , whereas the binding site for AIP1 may be located in a region of apoB not subject to conformational change . The importance of apoB conformation in antagonizing agrIII-virulence is supported by the ability of an apoB-specific antibody to block AIP3 binding by both apoB and oxLDL , but not LDL . Further investigations using antibody blocking and competition binding studies should help to elucidate differences in binding of AIP 1-4 by the different apoB-containing lipoprotein particles and to determine whether there is a single site or multiple sites for AIP binding to apoB . At present however , the specific binding site ( s ) for AIP 1-4 within the three-dimensional structure of this 515 kDa protein and the relevant binding affinities require further investigation . Nox2 activation contributes to phagocyte oxidative responses and in this regard patients with severe sepsis have significantly elevated levels of serum oxLDL suggesting that Nox2 can contribute to oxLDL formation during infection [64] , [77]–[79] . Interestingly , we observed increased oxLDL in the serum of wild-type C57BL/6 mice compared to serum from Nox2−/− mice prior to infection indicating that Nox2-derived ROS contribute to constitutive oxidation of LDL in the circulation . This may be explained in part by expression of Nox2 in other cell types including endothelial cells and adventitial fibroblasts , where it participates in cell cycle regulation and apoptosis [80] . For example , in adventitial fibroblasts , Nox2-derived ROS act in an autocrine and paracrine fashion to mediate angiogenesis and vessel homeostasis [81] , and could contribute to the pre-infection levels of circulating oxLDL seen in wild-type mice . In addition , Kupffer cells within the liver , which are among the first cells to sense endotoxin coming from the gut , could contribute to oxidation of LDL by constitutive release of Nox2-derived ROS in response to endotoxin released by gut microbiota [82] , [83] . Epidermal Langerhans cells might also contribute to constitutive ROS production as they survey the skin for microbes [84]–[86] . Therefore , Nox2 activity in these other cell types may contribute to a basal level of circulating oxLDL , which in turn may play a sentinel role in innate immune defense against both agrI and agrIII-mediated S . aureus invasive infection . Additional roles for both ROS and apoB in innate defense against S . aureus have recently been reported . First , Sun and colleagues demonstrated that oxidation of amino acid Cys199 of AgrA disrupted DNA binding and inhibited agrI-dependent expression of RNAIII and psmα in vitro [87] . This mechanism of oxidation sensing by the agr system is viewed as a bacterial mechanism to counter oxidative stress . However , oxidation of the AgrA disulfide redox switch may also be considered a form of host defense against S . aureus agr-signaling . This mechanism is distinct from ROS-mediated inactivation of AIP or oxidation of LDL as oxidation of either AgrA , AIP1 or LDL in isolation is sufficient to antagonize agr-signaling . Second , apoB and LDL were shown to inhibit LTA-induced cytokine release from immune cells through direct interaction with LTA [88] . Thus , apoB could modulate the host response to S . aureus independent of its role in antagonizing agr-signaling . If this were the primary function of apoB and oxLDL in our current work we would have expected to see a significant role for reduced serum apoB in susceptibility to an agr negative infection in which LTA would be equivalent and we did not . Together , these reports demonstrate multiple distinct and independent roles for both ROS and apoB in both agr-dependent and agr-independent host defense against S . aureus infection . Although to our knowledge this is the first description of oxLDL as an innate defense factor controlling quorum-sensing dependent virulence , oxLDL contributes in other direct and indirect ways to host defense . For example , oxLDL inhibits hepatitis C virus cellular entry in vitro [89] and reduces infection by the malaria parasite Plasmodium falciparum by binding the scavenger receptor SR-BI which is also utilized by the parasite [90] . OxLDL may also indirectly contribute to host antimicrobial defense . Autoantibodies generated against lipid components of oxLDL have demonstrated protection against infection by some strains of Streptococcus pneumoniae and Haemophilus influenzae [91] . However , other bacteria-oxLDL interactions are harmful to the host . For example , certain strains of Helicobacter pylori enhance atherosclerosis by increasing serum oxLDL [92] and the mitogenic activity of Chlamydia pneumonia in vascular smooth muscle cells is enhanced by oxLDL [93] . Although our understanding of the myriad contributions of oxLDL to host antimicrobial defense or microbial pathogenesis is clearly limited , the identification of oxLDL as a barrier against S . aureus agr dependent quorum-sensing by each of the four agr alleles provides new insight into the role of oxLDL in host defense .
Animal work in 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 Animal Welfare Act and US federal law . The protocol was approved by the Institutional Animal Care and Use Committee ( IACUC ) of the Research Service of the New Mexico VA Health Care Service . Synthetic AIPs were synthesized by Biopeptide Co . , Inc ( San Diego , CA ) as described [94] and stored in DMSO at −80°C . Purified human LDL and oxLDL ( Biomedical Technologies Inc . , Stoughton , MA and Kalen Biomedical , Montgomery Village , MD ) and purified apoB ( US Biological , Swampscott , MA ) were assayed for apoB content using a commercially available kit ( ALerCHEK , Inc . , Springvale , Maine ) . The following reagents were obtained as follows: tributyrin , 4-aminopyrazolo- ( 3 , 4-D ) pyrimidine ( 4APP ) , HOCl , Rose Bengal , N-acetymethionine ( NAM ) , ethylthioacetate , ( Sigma-Aldrich , St . Louis , MO ) ; E06 monoclonal Ab ( Avanti Polar Lipids , Alabaster , AL ) ; Rabbit anti-apoB ( Abcam , Cambridge , MA ) ; Goat anti-apoB ( Santa Cruz Biotechnology , Santa Cruz , CA ) ; Goat IgG ( R&D Systems , Minneapolis , MN ) . The bacterial strains used in this study were as follows: AH1677 ( strain agr I LAC [agr:P3-yfp] ) , AH1747 ( strain agr III MW2 [agr:P3-yfp] ) , AH430 ( strain agrII 502a [agr:P3-yfp] ) and AH1872 ( strain agrIV MN TG [agr:P3-yfp] ) were provided by Dr . Alex Horswill ( University of Iowa ) [41]; USA300 strain LAC and USA400 strain MW2 and their agr deletion mutants were provided by Dr . Mike Otto . agrIV clinical isolates ( NRS165 and NRS166 ) were obtained through the Network on Antimicrobial Resistance in Staphylococcus aureus ( NARSA ) program supported under NIAID , NIH Contract No . HHSN272200700055C . Additional clinical MRSA and MSSA isolates were provided by Dr . Larry Massey , New Mexico VAHCS . To generate synchronized early exponential phase , non-fluorescent bacteria , frozen stocks were cultured in Trypticase soy broth ( TSB ) ( Becton Dickinson , Franklin Lakes , NJ ) as described [28] . CFU were determined after washing and sonication to disrupt clumps by plating serial dilutions on blood agar ( Becton Dickinson , Franklin Lakes , NJ ) . Early exponential phase , nonfluorescent reporter bacteria ( 2×107/ml ) were incubated in TSB in polystyrene tubes with shaking ( 200 rpm , 37°C ) for the indicated times with either broth , synthetic AIP , AIP treated with ROS , or antagonists including lipoprotein particles or apoB . After incubation , bacteria were washed by centrifugation at 3000 rpm for 4 min at 4°C in PBS with 0 . 1% Triton X-100 , sonicated , cultured for CFU where indicated , and then fixed with 1% paraformaldehyde containing 25 mM CaCl2 for analysis by flow cytometry ( Accuri C6 , BD Accuri Cytometers , Ann Arbor , MI ) . Promoter activation was demonstrated as fluorescence induction and measured as the mean channel fluorescence ( MCF ) of YFP-positive bacteria . Quantitative RT-PCR was carried out as previously described [24] . Early exponential phase isolates were cultured as described and as indicated in the figure legends . RNA was isolated and purified using the Qiagen RNAprotect Bacteria Reagent and RNeasy Mini Kit ( Qiagen , Valencia , CA ) . cDNA was generated using a high capacity cDNA RT kit with an RNAse inhibitor ( Applied Biosystems , Foster City , CA ) and an Eppendorf Mastercycle thermocycler ( Hamburg , Germany ) . RNAIII was quantified relative to 16S RNA using a probe based assay as described with minor modifications [95] . Briefly , cDNA was quantified using an ABI7300 Real-Time PCR system with Taqman Gene Expression master mix , ROX probe/quencher , and appropriate primer sequences ( Applied Biosystems ) . Each experiment was performed in duplicate and samples assayed in triplicate . The primer-probe sequences used were as follows: psmα forward primer 5′-TATCAAAAGCTTAATCGAACAATTC-3′ , psmα probe 5′-6-FAM-AAAGACCTCCTTTGTTTGTTATGAAATCTTATTTACCAG-BHQ-2-3′ , psmα reverse primer 5′- CCCCTTCAAATAAGATGTTCATATC-3′ , hla forward primer 5′-ACAATTTTAGAGAGCCCAACTGAT-3′ , hla probe 5′-6-FAM-AAAAAGTAGGCTGGAAAGTGATA-BHQ-2-3′ , hla reverse primer 5′-TCCCCAATTTTGATTCACCAT-3′ , RNAIII forward primer 5′-AATTAGCAAGTGAGTAACATTTGCTAGT-3′ , RNAIII probe 5′-6-FAM-AGTTAGTTTCCTTGGACTCAGT-GCTATGTATTTTTCTT-BHQ-2-3′ , RNAIII reverse primer 5′-GATGTTGTTTACGATAGCTTACATGC-3′ , 16S forward primer 5′- TGATCCTGGCTCAGGATGA-3′ , 16S probe 5′-6-FAM-CGCTGGCGGCGTGCCTA-BHQ-2-3′ , 16S reverse primer 5′-TTCGCTCGACTTGCATGTA-3′ . Lipase and alpha hemolysin activity was measured using 0 . 45 µm filtered cultured supernatants from bacterial strains grown overnight as described above in 5 ml TSB with and without 50 nM LDL or oxLDL . Addition of LDL or oxLDL to supernatants from untreated cultures was used as additional controls . Lipase was measured as described using a triglyceride substrate , tributyrin [96] . Alpha hemolysin was measured as described using rabbit erythrocyte lysis [97] . One unit of hemolytic activity was defined as the amount of bacterial supernatant able to liberate half of the total hemoglobin from the erythrocytes . agr typing of clinical isolates was performed using PCR as previously described with minor modifications [98] . In brief , cell pellets from overnight bacterial cultures were suspended in Tris-EDTA buffer ( 10 mM Tris , 1 mM EDTA ) , added to 0 . 1 mm Zirconia beads ( Biospec ) and lysed using a bead beater ( Biospec ) . Following centrifugation , the liquid phase was diluted 50-fold and specific DNA quantified by real-time PCR using an ABI7300 Real-Time PCR system with Taqman Gene Expression master mix , along with agr type specific primers and probes [98] . Each assay included positive control DNA from agr group I isolate LAC , agr group II isolate 502A and agr group III isolate MW2 . Oxidation of AIP or LDL was performed using HOCl or singlet oxygen . HOCl ( Sigma ) was diluted and incubated with AIP or antagonist ( lipoprotein or apoprotein ) at 37°C for 30 min . The HOCl concentration was determined by its absorbance at 292 nm ( pH 12 , ε292 = 350 M−1•cm−1 ) [27] . Reactions were carried out in sterile microfuge tubes in 100 µl volumes and contained 1 µM AIP or 2 µM lipoprotein based on apoB concentration . Residual ROS were scavenged by the addition of 10 mM NAM following HOCl treatment , before addition to the bacterial reporter assay . Singlet oxygen was generated using 10 µM Rose Bengal with or without exposure to 150 W light for 5 min unless otherwise noted [99] , [100] . To control for heat induction , light was applied through a cold water filled 9 . 5 cm filter positioned directly above the samples . Sample volumes and concentrations were identical to those used for the HOCl oxidation assays . A tenfold molar excess of ethylthioacetate relative to AIP1 was used for analysis of thiolactone susceptibility to oxidation . LDL oxidation was assayed using either the LPO Assay kit or by determination of 8-isoprostane levels [101] , [102] using the 8-Isoprostane EIA Kit and 9-Isoprostane Affinity Purification kit ( Cayman Chemical Co , Ann Arbor , MI ) as per the manufacturer's instructions . For determination of 8-isoprostane levels , butylhydroxytoluene was added to LDL samples to 0 . 005% and samples were flash frozen and stored at −80°C until analysis . Immunblot analyses were performed to detect apoB and oxLDL in mouse serum and air-pouch lavages . Samples were loaded onto nitrocellulose membranes , presoaked in Tris Buffered Saline ( TBS ) , using a microfiltration apparatus ( BioRad , Hercules , CA ) . Slots were washed with additional TBS following sample application . Membranes were blocked for 30 min using SuperBlock ( Pierce , Rockford , IL ) , then probed with SuperBlock containing rabbit anti-apoB or E06 anti-oxLDL for 30 min at room temperature ( RT ) . Unbound primary antibody was removed by washing 3× with TBS , 0 . 1% Tween20 ( TBST ) , followed by incubation with the appropriate alkaline phosphatase ( AP ) conjugated secondary antibody also in SuperBlock . After 30 min at 25°C . RT , blots were washed 3× with TBST and 1× with TBS . Blots were developed using nitro-blue tetrazolium and 5-bromo-4-chloro-3′-indolyphosphate ( NBT/BCIP , Pierce ) . Band intensity was quantified using Carestream Molecular Imaging software ( Rochester , NY , USA ) . Surface plasmon resonance was performed using a Biacore ×100 ( Biacore Life Sciences , GE Healthcare ) to analyze the interaction of the analytes ( LDL , apoB and oxLDL ) with immobilized ligand ( AIP ) as previously described [24] . N-terminally biotinylated AIP in both native and linear conformations was immobilized on streptavidin sensor chips ( GE Healthcare , Piscataway , NJ ) according to the manufacturer's protocol . The chips were regenerated with 50 mM NaOH , 1 M NaCl and then washed with immobilization buffer ( 10 mM Hepes , pH 7 . 4 , 150 mM NaCl , 3 mM EDTA ) . Biotinylated AIPs were pulsed onto the chip at a concentration of 1 µM for 420 s at a flow rate of 10 µl/min followed by extensive washing . For binding studies , analytes were applied at 10 nM in running buffer ( 10 mM Hepes , pH 7 . 4 , 250 mM NaCl , 3 mM EDTA ) at a flow rate of 10 µl/min with a contact time of 60 s and a dissociation time of 60 s . Chip platforms were regenerated using a 60 s wash with 0 . 5% SDS followed by 120 s stabilization period . For each experiment specific binding was measured as the RU generated by analyte binding to the test surface minus RU generated by analyte binding to the reference surface ( streptavidin without biotin-AIP ) . The Biacore evaluation software ( ×100 Version 1 . 0 ) was used to analyze the results . All analyses were performed at 25°C . C57BL/6 mice ( 8–12 wk , ≈22–28 g ) from Charles Rivers ( Wilmington , MA ) , and Nox2 knockout mice on the C57BL/6 background ( Nox2−/− ) [42] from Jackson Laboratory ( Bar Harbor , ME ) were gender- and age-matched . Mice receiving 4APP treatment were injected i . p . 48 hours and 24 hours prior to infection with 100 µl of 5 mg/ml 4APP prepared by dissolving in 1 M HCl at 100 mg/ml and diluted to 5 mg/ml in 0 . 025 M phosphate buffer ( pH 8 ) . The solution was adjusted to pH 4 with 7 . 5% NaHCO3 immediately before injection . Total cholesterol levels were determined using a kit ( Thermo Electron , Louisville , CO ) per manufacturer's instructions . 4APP treated mice typically showed a 40–50% reduction in serum cholesterol levels compared to wild-type mice . Cholesterol levels specific to VLDL/LDL were determined using a kit ( BioVision , Mountain view , CA ) according to the manufacturer's protocol . Subcutaneous air pouches were created and infected with early exponential phase bacteria at the indicated dose as previously described [27] , [28] . Twenty-eight hours post infection , the mice were scored for morbidity by the following scale: appearance: 0–4; natural behavior: 0–3; hydration status ( skin pinch test ) : 0–3; provoked behavior: 0–4 . The morbidity score is the sum of the scores in the 4 categories with a maximum of 14 at which point the mice were considered moribund . In addition , weight loss was measured and pouch , lavage and spleen CFU were determined as described [24] , [27] . Basolateral pouch tissue was excised , rinsed in PBS and fixed in 3% paraformaldehye containing 0 . 1 mM CaCl2 and 0 . 1 mM MgCl in PBS . Pouch tissue was then rinsed with PBS and stored in 25% sucrose until freezing . Pouches were frozen in O . C . T . compound using liquid nitrogen . Cryo blocks were stored at −80°C until sectioned . Cryosections ( 10 µm ) were cut onto slides , fixed and permeabilized with acetone at −20°C for 5 minutes , rehydrated with PBS , and blocked overnight with 0 . 5% BSA , 5% normal rabbit serum , 0 . 1% Triton-X-100 in PBS . Slides were incubated for 1 h at 4°C with anti-S . aureus antibody ( GeneTex , San Antonio , TX ) conjugated with Alexafluor 488 ( Molecular Probes/Invitrogen ) . Slides were rinsed and mounted in Prolong Gold Antifade ( Molecular Probes/Invitrogen ) . Images were acquired on a Zeiss LSM 510 confocal microscope . Bacterial density as a measure of tissue invasion into the dermis was quantified from LSM images using Slidebook software ( Intelligent Imaging Innovations , Denver , CO ) . Regions of interest were selected using histiologic criteria for the dermis ( 3000 µm2 ) and the total area and the portion of that area stained for S . aureus quantified in microns2 . Values are displayed as percentage of square microns of staining within the identified area . A minimum of 20 sections were examined for each experimental condition . LDL was isolated from mouse serum basically as previously described [103] , [104] . Specifically , protease inhibitors and antioxidants were immediately added to freshly prepared serum ( Roche Complete Protease Inhibitor Cocktail Tablets , 1 mM EDTA , 1 mM DTT and 20 mM L-ascorbate ) , and the serum and lipoprotein fraction were stored under an argon atmosphere . LDL was separated using gel filtration chromatography at 4°C with a GE Life Sciences ÄTKA FPLC system and two Superose 6 10/300 GL columns in series , using 20 mM HEPES , 250 mM NaCl , 1 mM EDTA buffer at a flow rate of 0 . 3 mL min-1 . Up to 600 µL serum was loaded , 1 mL fractions collected , and the eluent was monitored by the absorbance at 280 nm . The LDL containing fractions were supplemented with protease inhibitors and antioxidants , pooled and concentrated with Amicon Ultra centrifugal filter ( 100 kDa MWCO ) . Immediately before use , LDL was buffer exchanged and concentrated into PBS using centrifugal filters . Total protein concentration was determined using A280 = 1 mg/ml . Data are displayed as the mean ± SEM . In vitro data were analyzed by the Student's t test and the in vivo results by the Mann-Whitney U test for nonparametrics . | Staphylococcus aureus is a common colonizer of humans but can also cause severe , invasive infection . S . aureus uses a secreted peptide-based communication system , agr , to induce production of virulence factors needed for invasive infection . Allelic variation has generated four agr types , agr I–IV , and each secretes a distinct autoinducing peptide ( AIP1-4 ) that differs in amino acid sequence and length . Understanding host factors that prevent signaling by each of the four agr specific groups ( agrI–IV ) could provide opportunities for prevention of infection or therapeutic intervention . We previously demonstrated that apolipoprotein B ( apoB ) , the major structural protein of very low and low density lipoproteins ( VLDL , LDL ) , binds to the secreted agrI peptide , AIP1 , and prevents agr signaling . In addition , the NADPH oxidase Nox2 produces reactive oxygen species which directly modify and inactive AIP1 . Here we examined the role of apoB and Nox2 in defense against agrIII-signaling . We found that apoB in oxidized LDL , but not in native LDL , mediated optimal binding of AIP3 . Also , unlike AIP1 , Nox2 did not directly inactivate AIP3 . Rather Nox2 contributed to defense against agrIII-signaling by oxidizing LDL . Furthermore , we found that oxLDL bound all four AIPs and antagonized agr signaling by each agr allele in vitro . These results expand our understanding of host defense against S . aureus agr signaling . | [
"Abstract",
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] | [
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] | 2013 | Nox2 Modification of LDL Is Essential for Optimal Apolipoprotein B-mediated Control of agr Type III Staphylococcus aureus Quorum-sensing |
In prion diseases , synapse dysfunction , axon retraction and loss of neuronal polarity precede neuronal death . The mechanisms driving such polarization defects , however , remain unclear . Here , we examined the contribution of RhoA-associated coiled-coil containing kinases ( ROCK ) , key players in neuritogenesis , to prion diseases . We found that overactivation of ROCK signaling occurred in neuronal stem cells infected by pathogenic prions ( PrPSc ) and impaired the sprouting of neurites . In reconstructed networks of mature neurons , PrPSc-induced ROCK overactivation provoked synapse disconnection and dendrite/axon degeneration . This overactivation of ROCK also disturbed overall neurotransmitter-associated functions . Importantly , we demonstrated that beyond its impact on neuronal polarity ROCK overactivity favored the production of PrPSc through a ROCK-dependent control of 3-phosphoinositide-dependent kinase 1 ( PDK1 ) activity . In non-infectious conditions , ROCK and PDK1 associated within a complex and ROCK phosphorylated PDK1 , conferring basal activity to PDK1 . In prion-infected neurons , exacerbated ROCK activity increased the pool of PDK1 molecules physically interacting with and phosphorylated by ROCK . ROCK-induced PDK1 overstimulation then canceled the neuroprotective α-cleavage of normal cellular prion protein PrPC by TACE α-secretase , which physiologically precludes PrPSc production . In prion-infected cells , inhibition of ROCK rescued neurite sprouting , preserved neuronal architecture , restored neuronal functions and reduced the amount of PrPSc . In mice challenged with prions , inhibition of ROCK also lowered brain PrPSc accumulation , reduced motor impairment and extended survival . We conclude that ROCK overactivation exerts a double detrimental effect in prion diseases by altering neuronal polarity and triggering PrPSc accumulation . Eventually ROCK emerges as therapeutic target to combat prion diseases .
In neurodegenerative disorders including Transmissible Spongiform Encephalopathies ( TSEs ) , it is now admitted that neuronal death is a late event in the neurodegenerative process preceded by an early loss of neuronal polarity at the root of behavioral and cognitive deficits [1–4] . In TSEs , synapse retraction and progressive axonal degeneration correlate with brain accumulation of the scrapie protein ( PrPSc ) , which is the essential component of infectious prions [5] . PrPSc is an abnormally folded self-propagating isoform of cellular prion protein ( PrPC ) , a physiological cell-surface glycosylphosphatidylinositol ( GPI ) -anchored protein . The neurotoxic effects of PrPSc depend on the neuronal expression of PrPC since the suppression of PrPC in neurons of infected mice , just prior to the clinical phase , hampers PrPSc-induced neuronal loss [6–8] . For instance , prion-associated neurotoxicity relates to subversion of PrPC function ( s ) in neurons following the conversion of PrPC into PrPSc [9–12] . From a physiological point of view , by acting as a signaling and/or a scaffolding molecule , PrPC plays a central role in neuritogenesis able to promote the sprouting , outgrowth and maintenance of neurites [13 , 14] . PrPC involvement in the very initial phase of neuritogenesis is supported by the observation that siRNA-mediated PrPC silencing in 1C11 neuronal stem cells or PC12 cells ( PrPnull-cells ) impairs neurite sprouting accompanying neuronal differentiation [15] . This PrPC role relies on its capacity to control the signaling activity of plasma membrane β1 integrins , the downstream activity of RhoA-associated coiled-coil containing kinases ( ROCK ) and the dynamics of actin microfilaments [15] . In the absence of PrPC , overactivated ROCK reduces the turnover of actin fibers and exerts a dominant negative effect on the sprouting of neurites [15] . In differentiating and mature neurons , PrPC influences neurite outgrowth and maintenance as well as synapse connectivity through its interaction with a set of diverse partners ( N-CAM , STI-1 , laminin γ-1 , mGluR1-5 , α7-nAChR ) depending on the neuronal type [16–21] and the fine-tuning of Rho-GTPase and ROCK activities [14] . Besides , because neuritogenesis is intimately linked to the expression of neuronal functions , ROCK may hence take part to the onset , regulation and integration of neurotransmitter-associated functions . Whether PrPSc-mediated corruption of the functional relationship between PrPC and ROCK accounts for neuronal polarity alterations and abnormal neuronal functions , and contributes to TSEs progression , remains unknown . To address these issues , we mainly exploit the properties of the 1C11 neuroectodermal cell line , which is endowed with the capacity to develop neurites and to acquire all functional properties of serotonergic neurons ( 1C115-HT ) within four days upon appropriate induction [22] , and is chronically infected by mouse-adapted prions derived from scrapie ( 22L ) or a human familial prion disease ( Fukuoka-1 , Fk ) [23] . We previously reported that prion infection disturbs all neurotransmitter-associated functions in prion-infected 1C115-HT neuronal cells and triggers the production of neurotoxins , i . e . oxidative derivatives of serotonin [23] . In this study , we also take advantage of primary cultures of mature cerebellar granule neurons and of a cortico-striatal neuronal network reconstructed on microfluidic chips to assess the impact of prion infection on synapse connectivity and neurite integrity . We show here that prion infection impairs the development of neurites in the 1C11 neuronal stem cell line and triggers synapse disconnection and neurite degeneration in primary cultures of neurons . Defects in neuronal polarity originate from prion-induced overactivation of ROCK activity . Antagonizing ROCK activity rescues neurite sprouting of prion-infected 1C11 cells and protects prion-infected mature neurons from neurite degeneration . The beneficial effect afforded by ROCK inhibition on neuronal polarization is associated with restoration of neurotransmitter-associated functions and decrease of serotonin-derived neurotoxins levels . Importantly , ROCK overactivation contributes to TSEs pathogenesis by stimulating the conversion of PrPC into PrPSc . We recently evidenced that PrPSc formation relates to a defect of cell surface TACE α-secretase neuroprotective activity towards PrPC caused by the overactivation of the 3-phosphoinositide-dependent kinase 1 ( PDK1 ) [24] . We demonstrate here that ROCK interact with and phosphorylate PDK1 leading to PDK1 overactivation in prion-infected cells . Inhibition of ROCK disrupts the ROCK-PDK1 complex , lowers PDK1 activity , rescues TACE activity at the plasma membrane and induces strong reduction of PrPSc level in prion-infected neuronal cells . Finally , inhibiting ROCK in mouse models of prion infection mitigates prion diseases .
When Fk- or 22L-infected 1C11 precursor cells were induced to differentiate towards the serotonergic program , less than 20% of Fk- and 22L-infected cells converted into neuronal-like cells with small , rounded cell bodies and bipolar extensions undistinguishable from uninfected 1C115-HT neuronal cells . The other 80% fraction did not adopt a neural-like morphology and/or presented spindle shaped cell bodies harboring wide and short extensions ( Fig 1A ) . These defects in neuronal polarization recall the impairment of neurite sprouting caused by PrPC silencing in 1C11 progenitors and PC12 cells [15] . We previously showed that PrPC depletion triggers the clustering and overactivation of β1 integrins , which in turn promote overactivation of the RhoA-ROCK-LIMK-cofilin pathway leading to alterations of F-actin architecture and subsequent gain of cell contractility [15] . In line with this , cell surface PrPC immunolabeling under native conditions revealed that more than 90% of Fk-infected cells displayed very little fluorescence , while uninfected 1C11 cells stained brightly and uniformly ( Fig 1B ) . This suggests a thorough conversion of cell surface PrPC into PrPSc and in fine depletion of PrPC molecules normally present at the plasma membrane of infected cells . PrPSc immunolabeling with PrPSc reacting ICSM33 antibody [25] under denatured conditions with guanidine thiocyanate indeed showed a high level of PrPSc in Fk-infected 1C11 cells ( Fig 1B ) . PrPC conversion into PrPSc had no impact on total β1 integrin expression level as assessed by western blotting using the anti-CD29 antibody ( Fig 1C ) . Nevertheless , cell surface immunofluorescence analyses using a β1 integrin antibody ( 9EG7 ) specifically targeting activated β1 integrins revealed that the pool of activated integrins was ~2-fold increased in Fk-infected cells as compared to uninfected 1C11 cells ( Fig 1B ) . In addition , active β1 integrins were evenly distributed and displayed a dot-like staining at the cell periphery of uninfected 1C11 cells , while they clustered and formed elongated patches in Fk-infected 1C11 cells ( Fig 1B ) . As compared to uninfected cells , we measured increases by 2- to 3-fold in RhoA GTPase activity ( Fig 1C ) , the phosphorylation level of LIMK1/2 on Thr505 and Thr508 ( Fig 1B and 1C ) , and the phosphorylation level of cofilin on Ser3 ( Fig 1B and 1C ) in Fk- and 22L-infected 1C11 cells , indicating that prion infection reduces cofilin-associated severing activity towards F-Actin [26–29] . Accordingly , fibrillar actin ( F-actin ) microfilaments were large and disorganized in the cytoplasm of Fk-infected 1C11 cells , while F-actin distributed as thin , parallel stress fibers underneath the cell plasma membrane of uninfected 1C11 precursor cells ( Fig 1B ) . These overall data show that prion infection triggers overactivation of the RhoA-ROCK-LIMK-cofilin signaling pathway , which alters the architecture and turnover of F-actin microfilaments , thereby contributing to neuritogenesis impairment . We next wondered whether inhibiting ROCK activity would counteract prion-induced neuritogenesis defects . When treated with two distinct ROCK inhibitors , namely Y-27632 ( 100 μM ) or dimethylfasudil ( 2 μM ) ( for review see [30–32] and references therein ) , ~90% of Fk- or 22L-infected 1C11 cells induced to differentiate along the serotonergic pathway developed neurites . At the end of the program ( day 4 ) , prion-infected 1C11 cells differentiated in the presence of ROCK inhibitors ( referred to as Rocki-infected 1C115-HT cells ) exhibited neurites that were thin , bipolar and extended from the ovoid cell body as for uninfected 1C115-HT neuronal cells ( S1 Fig and S1 Table ) . The mean neurite length of Rocki-infected 1C115-HT cells was comparable to that of uninfected 1C115-HT cells differentiated in the presence of ROCK inhibitors ( S1 Table ) . Rescued neuritogenesis by Fk-infected 1C11 precursor cells upon ROCK inhibition was associated with decrease to basal level of phospho-cofilin level on Ser 3 ( Fig 2A ) , which restores cofilin severing activity towards F-actin and renders Fk-1C11 precursor cells competent to sprout neurites when induced towards the neuronal program [15] . Beyond the rescue of neuronal polarity , inhibition of ROCK restores the overall neuronal functions , i . e . synthesis , storage , degradation and transport of 5-HT , in Rocki-infected 1C115-HT cells . While the activity of tryptophan hydroxylase ( TPH ) , the 5-HT synthesizing enzyme , in Fk-1C115-HT cells represented 5% of that measured with uninfected 1C115-HT cells , TPH activity increased by 8- to 18-fold in Rocki-Fk-1C115-HT cells treated with Y-27632 or dimethylfasudil , respectively ( Fig 2B ) . Corroborating TPH activity , western blot analysis revealed that the TPH2 enzyme was weakly present in Fk-1C115HT cells compared to uninfected 1C115-HT cells , while TPH2 expression was recovered in Rocki-Fk-1C115-HT cells ( Fig 2B ) . This indicates that PrPSc-induced ROCK overactivation impairs TPH protein synthesis . Using the paroxetine Serotonin Re-uptake Inhibitor ( SRI ) antidepressant to count functional Serotonin Transporter ( SERT ) molecules [33] , we showed that the number of functional SERT proteins was 5- ( Y-27632 ) to 7- ( dimethylfasudil ) fold enhanced in Rocki-Fk-1C115-HT cells as compared to Fk-1C115-HT cells ( where functional SERT level was 10% of that measured with uninfected 1C115-HT cells ) ( Fig 2C ) , indicating that inhibition of ROCK rescues SERT functionality . By contrast with TPH2 enzyme , no significant variation in SERT protein level could be evidenced between Fk-1C115-HT , Rocki-Fk-1C115-HT and uninfected 1C115-HT cells ( Fig 2C ) . This indicates that the impact of prion infection on SERT activity does not relate to modulation of SERT synthesis . Using [3H]-tetrabenazine that selectively binds to the Vesicular Monoamine Transporter ( VMAT ) , we monitored that antagonizing ROCK activity restored 5-HT storage in Rocki-Fk-1C115-HT cells with a tetrabenazine binding value that was 2- ( Y-27632 ) to 2 . 5- ( dimethylfasudil ) fold increased as compared to Fk-infected 1C115-HT cells ( 30% of that measured with uninfected 1C115-HT cells ) ( Fig 2D ) . Restoration of normal serotonergic neuronal functions upon ROCK inhibition was further supported by a 10- ( Y-27632 ) to 15- ( dimethylfasudil ) fold increase of 5-HT content ( Fig 2E ) , decreased levels ( 30 to 40% ) of the 5-hydroxyindolacetic acid ( 5-HIAA ) degradative product of 5-HT ( Fig 2F ) , and deep reduction ( 50 to 70% ) in the intracellular content of serotonin-derived oxidized neurotoxins ( Fig 2G ) . Altogether , these data demonstrate that inhibition of ROCK activity in prion-infected 1C11 cells rescues neuritogenesis and the overall serotonergic-associated functions . To extend our study to mature neurons , we combined the use of primary cultures of mouse cerebellar granule neurons ( CGNs ) and of a reconstructed cortico-striatal neuronal network grown on microfluidic chips [34–36] . CGNs are helpful to probe the effect of prion infection on the axon and dendrites [37 , 38] . The reconstructed cortico-striatal network on microfluidic device offers the possibility to infect cortical neurons in the somato-dendritic side and to monitor the impact of prion infection at distance on synapse connectivity between cortical and striatal neurons . We showed that infection of CGNs with 22L strain triggered neuronal dysfunction as inferred by the fragmentation of axon and dendrites by 11 days post-infection ( dpi ) , using SMI31 and MAP2 as markers of the axon and dendrites , respectively ( Fig 3A ) . Western blot analyses revealed a 2-fold increase in cofilin phosphorylation level in 22L-infected CGNs vs . uninfected CGNs ( Fig 3B ) , indicative of an overactivation of ROCK in infected CGNs . Treatment of 22L-infected CGNs with the ROCK inhibitors Y-27632 ( 100 μM ) or dimethylfasudil ( 2 μM ) at 7 dpi for 4 days exerted a protective effect towards PrPSc-induced neurite degeneration , since ~70 to 90% of treated infected neurons displayed unfragmented dendrites and axon ( Fig 3A ) . Such protective effect of ROCK inhibitors on axon and dendrites of 22L-infected CGNs relates to rescued cofilin activity as shown by cofilin phosphorylation level that returned to basal level upon cell treatment with either Y-27632 or dimethylfasudil ( Fig 3B ) . With reconstructed cortico-striatal networks , we observed that challenging the cortical compartment with 22L strain promoted disconnection and retraction of synapses between cortical and striatal neurons by 11 dpi , as inferred by pre-synaptic cortical v-GLUT1 immunostaining no longer colocalized with post-synaptic striatal dendrite MAP2 staining ( Fig 3C ) . ROCK inhibition with Y-27632 ( 20 μM ) or dimethylfasudil ( 2 μM ) applied in the striatal chamber by 7 dpi for 4 days attenuated PrPSc-induced neuronal disconnection and synapse retraction by ~100% ( Fig 3C ) . As a whole , our data indicate that prion-induced ROCK activation in mature neurons disrupts neuronal polarity and connectivity . Inhibition of ROCK activity protects neurons from prion-induced synapse disconnection and dendrite/axon degeneration . We next investigated whether PrPSc accumulation in prion-infected cells would depend on ROCK overactivity . Inhibition of ROCK with dimethylfasudil ( 2 μM ) or Y-27632 ( 100 μM ) decreased the amount of proteinase K-resistant PrPSc ( PrPres ) by 80 to 90% in either Rocki-Fk-1C115-HT cells ( Fig 4A ) or primary cultures of 22L-infected CGNs ( Fig 4B ) . These observations introduce ROCK overactivation as a novel pathogenic event contributing to the conversion of PrPC into PrPSc . We recently reported that accumulation of PrPSc in prion diseases relates to internalization of TACE α-secretase in caveolin-1 ( Cav-1 ) -enriched microvesicles caused by PDK1 overactivation , which cancels PrPC neuroprotective α-cleavage by TACE [24] . The question was thus to assess whether the reduction of PrPSc level measured upon ROCK inhibition would depend on a control of the PDK1-TACE module by ROCK . Inhibition of ROCK with Y-27632 ( 100 μM , 1h ) promoted translocation of TACE back to the cell surface of Fk-1C115-HT cells ( Fig 4C ) and 22L-infected CGNs ( S2A Fig ) . Detergent-free sucrose gradient membrane fractionation of cell extracts followed by western blotting further revealed that TACE no longer co-distributed with Cav-1 in Fk-1C115-HT cells exposed to Y-27632 , but was found together with the focal adhesion kinase ( FAK ) at the plasma membrane of infected 1C115-HT cells as observed with uninfected 1C115-HT cells ( Fig 4D ) . With Rocki-Fk-1C115-HT cells differentiated for 4 days in the presence of Y-27632 , TACE was at the plasma membrane of both the cell body and neurites with a distribution pattern highly comparable to that of uninfected 1C115-HT cells ( Fig 4E ) . Redirection of TACE to the cell surface of infected cells upon ROCK inhibition rescued TACE-mediated α-cleavage of PrP between residues 111/112 and generated an N-terminal truncated fragment ( that is , membrane C1 ) ( Figs 4F and S2B ) that does not convert into PrPSc [39] . In Fk-1C115-HT cells and 22L-CGNs , the ratio between PrP C1 fragment and full length PrP ( native ) was reduced by approximately 75% as compared to that of uninfected cells ( Figs 4F and S2B ) , thus accounting for conversion of PrPC into PrPSc . In infected cells treated with Y-27632 ( 100 μM ) for 6 h the C1/native ratio was ~2- to 3-fold increased compared to untreated infected cells ( Figs 4F and S2B ) , indicative of restored PrPC α-cleavage . Such an increase in C1/native ratio in the presence of the ROCK inhibitor depends on TACE activity , since inhibition of TACE with TAPI-2 ( 100 μM , 1h ) counteracted the effects of Y-27632 on PrP neuroprotective cleavage ( Figs 4F and S2B ) . Finally , while PDK1 activity was 2- to 3-fold increased in Fk-infected 1C115-HT cells ( Fig 4G ) and 22L-infected CGNs ( S2C Fig ) , ROCK inhibition in Fk-1C115-HT cells or 22L-CGNs with Y-27632 ( 100μM , 1h ) reduced PDK1 activity by ~50 to 70% to basal level measured with uninfected cells ( Figs 4G and S2C ) . Of note , bombardment of Fk-infected 1C115-HT cells with tungsten microprojectiles coated with ROCK-I antibodies [24 , 40] restored basal PDK1 activity , while tungsten microprojectiles coated with ROCK-II antibodies triggered less reduction of PDK1 activity ( ~45% ) ( Fig 4G ) , indicating that ROCK-I overactivity within an infectious context mainly contributes to the overactivation of PDK1 . The rise in PDK1 activity was also counteracted in Rocki-Fk-1C115-HT cells differentiated for 4 days in the presence of Y-27632 ( Fig 4G ) , further demonstrating that the control of PDK1 activity by ROCK-I occurs in polarized cells as well as in non-polarized Fk-1C115-HT cells . These overall data firmly establish that ROCK act as upstream positive regulators of PDK1 activity and contribute to prion-induced neurodegeneration by favoring the production of PrPSc . The acute regulation of PDK1 activity relies on a complex interplay between PDK1 phosphorylation , subcellular localization , binding of regulators and conformational changes ( for review see [41] and references therein ) . To investigate how ROCK-I regulates PDK1 activity , we designed a first set of experiments centered on the interaction between ROCK-I and PDK1 . In uninfected 1C115-HT cells , ROCK-I immunoprecipitation followed by PDK1 western blotting revealed that ROCK-I interacts with PDK1 ( Fig 5A ) . In Fk-infected 1C115-HT cells , the fraction of PDK1 interacting with ROCK-I was ~2-fold increased compared to uninfected cells ( Fig 5A ) . Of note , the level of ROCK-I did not vary between uninfected 1C115-HT and Fk-1C115-HT cells ( Fig 5A ) . The rise in ROCK activity induced by PrPSc thus increases the number of PDK1 molecules recruited by ROCK-I . Exposure of uninfected 1C115-HT or Fk-1C115-HT cells to Y-27632 ( 100 μM ) for 1h dissociated the ROCK-I / PDK1 complex by ~70% and ~90% , respectively ( Fig 5A ) , further indicating that the ROCK-I-kinase activity is necessary for its association with PDK1 . To next probe whether ROCK-I phosphorylates PDK1 , cells treated or not with Y-27632 ( 100 μM , 1h ) were metabolically labeled for 60 min with [32P]-orthophosphate ( 8 . 81 μCi . mL−1 ) and [32P]-labeled PDK1 level was quantified after PDK1 immunoprecipitation and western blotting . In uninfected 1C115-HT cells , PDK1 phosphorylation level was reduced by ~70% in the presence of Y-27632 ( Fig 5B ) , indicating that ROCK-I does phosphorylate PDK1 under physiological conditions . From a mechanistic point of view , autophosphorylation of PDK1 Ser241 is critical but not sufficient to induce PDK1 full activity [42] . Depending on the cell type and signaling pathways converging on PDK1 , additional phosphorylations on Ser , Thr and Tyr residues located in the kinase domain , the pleckstrin-homology ( PH ) domain and in the linker between the kinase and PH domains have already been shown to enhance PDK1 activity in a more or less cooperative manner [41 , 43] . Here , we provide evidence that PDK1 autophosphorylation at Ser241 precedes PDK1 phosphorylation by ROCK-I on yet-to-be identified residues . Indeed , site-directed mutagenesis of PDK1 Ser241 into Ala to mimic a constitutive dephosphorylation ( S241A ) state decreased by ~90% the incorporation of 32P on the S241A PDK1 mutant when transfected into 1C115-HT cells ( Fig 5B ) . Besides , immunoprecipitation experiments showed that ROCK-I did not complex with the S241A PDK1 mutant ( Fig 5A ) . These data establish that autophosphorylation of PDK1 Ser241 is essential for PDK1 interaction with ROCK and further phosphorylation by ROCK . We next examined the phosphorylation status of PDK1 within an infectious context . The level of phosphorylated PDK1 was 2-fold higher in Fk-infected 1C115-HT cells than in uninfected cells ( Fig 5B ) . Such increase in PDK1 phosphorylation level was cancelled upon treatment of Fk-1C115-HT cells with Y-27632 ( 100 μM ) for 1h or in Rocki-Fk-1C115-HT cells left to differentiate for 4 days in the presence of Y-27632 ( Fig 5B ) , indicating that prion-induced ROCK overactivity enhances PDK1 phosphorylation level and that ROCK-induced phosphorylation of PDK1 is independent on the acquisition of neuronal polarity . As a whole , our data reveal that ROCK-I constitutively complexes with and phosphorylates PDK1 in uninfected cells . Autophosphorylation of PDK1 at Ser241 is a prerequisite for PDK1 interaction with ROCK-I and further phosphorylation by ROCK-I . In prion-infected cells , ROCK overactivation augments by 2-fold the pool of PDK1 molecules interacting with and phosphorylated by ROCK-I , which thus enhances PDK1 activity . In adult C57BL/6J mice inoculated with the mouse-adapted scrapie strain 22L via the intracerebellar route [44] and sacrificed at 130 days post infection ( dpi ) just before the symptomatic phase , a marked increase in phosphorylated cofilin immunostaining that matched with PrPSc deposition was observed in the brain of prion-infected mice in both the cerebellar cortex ( CBCX ) and deep cerebellar nuclei ( DCN ) compared to uninfected animals ( SHAM ) ( Fig 6A and 6B ) . Western-blot analyses of cerebellum extracts indicated a ~2 to 3-fold increased level of phosphorylated cofilin in 22L-infected vs . SHAM mice ( Fig 6C ) . Because increased cofilin phosphorylation in the brain of prion-infected mice argues for ROCK overactivity in vivo , we next wondered whether inhibition of ROCK would attenuate prion disease . Y-27632 , known to easily cross the Blood Brain Barrier [30] , was first chronically injected intraperitoneally ( i . p . ) in adult C57BL/6J mice starting 130 days after infection and before the onset of clinical signs ( 140 days ) . We showed that Y-27632 treatment delayed mortality in 22L-infected mice as compared to untreated mice ( 181 . 4 +/- 4 . 7 days versus 166 . 0 +/- 1 . 8 days , n = 10 , P < 0 . 0001 , Fig 6D ) with no overt sign of Y-27632 toxicity . Reduction of phosphorylated cofilin level in post-mortem cerebellum extracts from 22L-infected mice upon Y-27632 treatment indicated ROCK inhibition in brain ( Fig 6C ) . Y-27632 infusion also decreased prion infection-induced impairments in motor function ( Fig 6E ) . While in 22L-infected mice the mean static rod score dropped to 10 by 145 days , in Y-27632-treated infected mice , the mean static rod score never dropped below 10 . In SHAM mice , motor coordination was non-sensitive to Y-27632 treatment . We further showed that the beneficial effect of ROCK inhibition against prion disease correlated with decreased levels of PrPSc . Post-mortem quantifications of proteinase K-resistant PrP revealed a ~30% reduction in PrPres level in the brains of 22L-infected mice infused with Y-27632 compared to untreated infected animals ( Fig 6F ) , indicative of PDK1 down-regulation ( Fig 6G ) , TACE relocation to the plasma membrane ( Fig 6H ) and rescue of PrPC α-cleavage by TACE upon ROCK inhibition in vivo ( Fig 6I ) . Accordingly , while PDK1 activity was ~3-fold enhanced in the brain of 22L-infected mice compared to SHAM mice , PDK1 activity decreased by ~50% in prion-infected mice treated with Y-27632 vs . untreated infected mice ( Fig 6G ) . As for prion-infected 1C115-HT cells and CGNs , reduction of PDK1 activity in the brain of 22L-infected mice infused with Y-27632 originated from disruption of the ROCK-PDK1 complex ( Fig 6J ) . Finally , C57Bl/6J mice inoculated with 22L prions were also intraperitonealy injected with dimethylfasudil following the same procedure as for Y-27632 . ROCK inhibition with dimethylfasudil prolonged the survival time of infected mice compared to untreated mice ( 174 . 8 +/- 4 . 3 days versus 166 . 0 +/- 1 . 8 days , n = 10 , P < 0 . 0001 , S3A Fig ) , reduced phospho-cofilin level in the cerebellum ( S3B Fig ) , counteracted prion-induced motor deficits ( S3C Fig ) , decreased brain PrPSc level by 30% ( S3D Fig ) , as a consequence of dissociation of the ROCK/PDK1 complex ( S3E Fig ) and reduction of PDK1 activity ( S3F Fig ) . Altogether , these data demonstrate that targeting ROCK activity mitigates prion diseases .
Our findings indicate that PrPSc-induced ROCK overactivity contributes to neuronal cell demise at two levels: through ( i ) alterations of neuronal polarity , connectivity and neurotransmitter-associated functions and ( ii ) amplification of the production of neurotoxic PrPSc . ROCK inhibition not only restores neuritogenesis and neurotransmitter-associated functions , but also reduces the production of PrPSc , which thereby lengthens the survival of prion-infected mice ( Fig 7 ) . The rise in ROCK activity in prion-infected cells originates from loss of PrPC regulatory function towards the RhoA-ROCK-LIMK-cofilin pathway [15] upon PrPC conversion into PrPSc . Downstream modifications of F-actin structure and dynamics impair the onset of neurites by differentiating 1C11 neuronal stem cells , disrupt synapse connectivity and provoke neurite degradation in primary neuronal cultures . Our data provide evidence that PrPSc-induced ROCK overactivation exerts a dominant negative effect on neuronal polarity since the sole inhibition of ROCK is sufficient to restore neurite sprouting and protect mature neurons from prion-induced axon and dendrite alterations . The beneficial effect afforded by ROCK inhibition on neuritogenesis and neuronal architecture relates to rescued cofilin-mediated severing of F-actin and improved actin dynamics in prion-infected cells . This however does not exclude that modulation of other signaling effectors known to regulate neuronal outgrowth downstream from ROCK , such as profilin IIa [45] , also partakes to restoration of neuronal morphology upon ROCK inhibition . Our data further show that prion infection of 1C11 neuronal stem cells alters the coupling between cell morphogenesis and the acquisition of neuronal functions . Inhibition of ROCK not only restores neuritogenesis but also rescues the overall neurotransmitter-associated functions . How the inhibition of ROCK permits to restore neuronal functions has however not been deciphered . Neuritogenesis and the onset of neurotransmitter-functions are interconnected events since the actin cytoskeleton directs the transport of specific mRNAs and proteins [46–48] and acts as a scaffold that orchestrates local protein translation [47 , 49 , 50] within axons and dendrites . Of note , all the mRNAs coding for neuronal functions are expressed in 1C11 cells at the stem cell stage but are dormant [51] . Prion infection does not impact on the expression level of these mRNAs ( S4 Fig ) . The drastic reduction of Tryptophan Hydroxylase-2 ( TPH2 ) expression measured in prion-infected 1C115-HT neurons might thus originate from abnormal trafficking of TPH2 mRNA and/or compromised translation . Interestingly , overphosphorylation of the translation initiation factor eiF2α , subsequent decrease of its activity and repression of protein synthesis have been shown to contribute to the progression of prion diseases [52] . Whether rescue of TPH2 protein synthesis upon ROCK inhibition relates to a restoration of eiF2α activity needs further investigation . By contrast with TPH2 , the loss of Serotonin Transporter ( SERT ) functionality within an infectious context does not originate from reduced SERT expression , indicating that PrPSc interferes with the translation of specific mRNAs . Rescue of SERT activity upon ROCK inhibition may alternatively be linked to reduction of the intracellular concentration of serotonin-oxidized neurotoxins that are assumed to poison the SERT protein [23] , corroborating the antioxidant effect of ROCK inhibition [53 , 54] . A major output of this work is the reduction , upon ROCK inhibition , of PrPSc level in prion-infected cells or in the brain of 22L-infected mice . Such reduction in brain PrPSc likely accounts for improved motor function and increased survival of prion-infected animals treated with the ROCK inhibitor . In this work , we decipher how ROCK contributes to the conversion of PrPC into PrPSc . Under physiological conditions ROCK-I acts as positive regulator of PDK1 activity . ROCK-I interacts with and phosphorylates PDK1 . At a mechanistic level , prior autophosphorylation of Ser241 in the kinase domain of PDK1 is necessary to ROCK-I interaction and subsequent PDK1 phosphorylation by ROCK-I , suggesting that PDK1 phosphorylation at Ser241 induces conformational changes unmasking binding site ( s ) for ROCK-I and/or phosphorylatable residues by ROCK-I . Additional phosphorylation of PDK1 by ROCK-I improves the stability of the ROCK-I/PDK1 complex . In prion-infected cells , the rise in ROCK activity increases the pool of PDK1 molecules interacting with and phosphorylated by ROCK-I at the root of the PDK1 activity overboost within an infectious context ( Fig 7 ) . Such ROCK-dependent overstimulation of PDK1 activity in turn cancels plasma membrane TACE neuroprotective α-cleavage of PrPC and thereby favors the production of PrPSc [24] . We previously showed that a rise in Src kinases-PI3K signaling in prion-infected cells also enhanced PDK1 activity [24] , likely as the result of an accelerated PDK1 docking to the plasma membrane by phosphatidylinositol 3 , 4 , 5-trisphosphate and subsequent phosphorylation by Src kinases [41 , 43] . Inhibition of ROCK in prion-infected cells is however sufficient to decrease PDK1 activity up to its basal level as does the sole inhibition of Src kinases or PI3K [24] , thus suggesting that the Src kinases-PI3K and ROCK pathways are both required for overstimulation of PDK1 activity within an infectious context . Inhibition of ROCK has been shown to exert beneficial effects towards other amyloid-based neurodegenerative diseases such as Alzheimer’s ( AD ) [55] or Parkinson’s diseases [56 , 57] . In mouse models with AD-like pathology , decreased levels of neurotoxic amyloid Aβ peptides upon ROCK inhibition have been attributed to disruption of amyloidogenic processing of the amyloid precursor protein APP by the β-secretase BACE [58] . In brain samples from AD subjects as well as in three mouse models with AD-like pathology , PDK1 overactivity was also shown to contribute to the accumulation of Aβ40/42 peptides and the progression of AD by cancelling the non-amyloidogenic processing of APP by TACE [24] . By showing that ROCK overactivation is a novel pathogenic event in TSEs and that ROCK control PDK1 activity , we propose that the beneficial effect afforded by ROCK inhibition against AD also reflects down-regulation of PDK1 activity and rescue of TACE α-secretase activity towards APP . In any case , in the absence of effective medicine , further understanding the functional interplay between ROCK and PDK1 may help to design novel therapeutic strategies for amyloid-based neurodegenerative disorders .
The rat monoclonal CD9 antibody was a kind gift from E . Rubinstein ( Inserm , Villejuif , France ) [59] . The mouse monoclonal SAF32 PrP antibody was from SPI-Bio ( Montigny Le Bretoneux , France ) . The mouse monoclonal ICSM33 PrP antibody was from D-Gen Limited ( London , UK ) . The mouse monoclonal anti-CD29 ( β1 integrin ) antibody was from BD Transduction Laboratories ( Lexington , KY , USA ) . The rat monoclonal 9EG7 anti-activated β1 integrin antibody [60] was from Pharmingen ( San Diego , CA , USA ) . The mouse monoclonal antibody to α-tubulin was from Novus Biologicals ( Littleton , CO , USA ) . The rabbit polyclonal antibody targeting phospho-LIMK1/2 ( pThr505 and pThr508 ) was from AbCam ( Cambridge , MA , USA ) . Rabbit polyclonal antibodies toward LIMK1 and cofilin were from Cell Signaling ( Beverly , MA , USA ) . The rabbit polyclonal anti-phospho-Ser3-cofilin antibody was from Santa Cruz Biotechnology ( SantaCruz , CA , USA ) . The rabbit polyclonal anti-TPH2 antibody was from Genway ( San Diego , CA , USA ) . The rabbit polyclonal anti-SERT antibody was from Chemicon ( Temecula , CA , USA ) . The rabbit polyclonal antibody to MAP2 , the mouse polyclonal antibody to phospho-NFL200 ( SMI31 ) and the guinea pig polyclonal anti-v-GLUT1 antibody were from EMD Millipore ( Darmstadt , Germany ) . Rabbit polyclonal antibody to TACE was purchased from QED Bioscience ( San Diego , CA , USA ) . The rabbit polyclonal antibodies to caveolin-1 ( Cav-1 ) and focal adhesion kinase ( FAK ) were from Transduction laboratories ( Lexington , KY , USA ) and Santa Cruz Biotechnology ( SantaCruz , CA , USA ) , respectively . The rabbit monoclonal ROCK-I and polyclonal ROCK-II and PDK1 antibodies were from Cell Signaling ( Beverly , MA , USA ) . When nonspecified , primary antibodies were used at 0 . 5 μg ml−1 for western blot experiments and at 5 μg ml−1 for immunofluorescence experiments . Adult C57Bl/6J mice were bred and underwent experiments in level-3 biological risk containment , respecting European guidelines for the care and ethical use of laboratory animals ( Directive 2010/63/EU of the European Parliament and of the Council of 22 September 2010 on the protection of animals used for scientific purposes ) . Mice received intracerebral inoculation of the cerebellotropic 22L scrapie strain [44] ( CNRS Strasbourg , France ) . All animal procedures were approved by the Comité Régional d’Ethique en Matière d’Expérimentation Animale de Strasbourg ( France; CEEA35 ref AL/01/01/01/13 ) and the Animal Care and Use Committee at Basel University ( Switzerland ) . Mice were fasted overnight but allowed water ad libitum before the experiment . They were then anesthetized with isoflurane inhalation , and a midline incision was performed to insert into the peritoneum the polyethylene catheter of an osmotic pump ( Alzet , Cupertino , CA , USA ) . Y-27632 , dimethylfasudil or vehicle ( 1% DMSO in sterile normal saline buffer ) was administered at a flow rate of 0 . 25 μL h-1 , which corresponded to 100 μg per mouse per day ( 5 mg kg−1 per day for Y-27632 and 3 mg kg−1 per day for dimethylfasudil ) . Pumps were replaced every 4 weeks . Motor function in 22L-infected mice was assessed by the static rod test [61] . 1C11 cells chronically infected or not by the mouse-adapted 22L or Fukuoka ( Fk ) strains [23] were grown and induced to differentiate along the serotonergic ( 1C115-HT ) pathway [22] . Primary CGNs were isolated from dissociated cerebella of 4- to 5-day-old C57Bl/6J mice and infected by the 22L strain [37 , 38] . “Axon diode” microfluidic chips were designed and fabricated as previously described [34] . Briefly , Polydimethylsiloxane ( Sylgard 184 , PDMS , Dow Corning , Midland , MI , USA ) was mixed with a curing agent ( 9:1 ratio ) and degassed under vacuum . The resulting preparation was poured onto a polyester resin replicate and reticulated at 70°C for 2 h . The elastomeric polymer print was detached and two reservoirs were punched for each macro-channel . The resulting piece was cleaned with isopropanol and dried . The polymer print and a glass cover slip were treated for 200 sec in an air plasma generator ( 98% power , 0 . 6 mBar , Diener Electronic , Ebhausen , Germany ) and bonded together . The chips were then coated with a solution of poly-D-lysine ( 10 μg ml-1 , Sigma; St . Louis , MO , USA ) overnight and washed with PBS before cell seeding . Embryonic cortical and striatal neurons were obtained and cultured as previously described [34 , 35] . Briefly , cortices and ganglionic eminences ( striatal neurons ) were micro-dissected from E14 embryos of C57Bl/6J pregnant mice and digested with papaïn ( 20 U ml-1 in DMEM , Sigma Aldrich ) . Cortices and Striata were mechanically dissociated and neurons were collected by centrifugation . Cells were then re-suspended for plating in DMEM-Glutamax I ( Life Technologies ) supplemented with penicillin and streptomycin ( Life Technologies ) , N2 and B27 supplements ( Life Technologies ) and 5% FBS ( PAA ) . ~105 cortical neurons and ~2 . 4 x 104 striatal neurons were seeded respectively in cortical and striatal compartments , as described before [34] . Microfluidic chips were incubated at 37°C in humid atmosphere with 5% CO2 . The culture medium was renewed every 7 days . Upon time of interest , cells were fixed using a 4% PFA , 4% sucrose solution diluted in PBS and further processed by immuno-cytochemistry with anti MAP2 , α- tubulin and v-GLUT1 antibodies . Immunofluorescent labeling of PrPC , PrPSc , β1 integrins , phospho-LIMK1/2 , phospho-cofilin , TACE , MAP2 , phospho-NFL200 , and v-Glut1 was performed using standard protocols as reported in [15 , 37] . F-actin was stained using TRITC-phalloidin ( Sigma-Aldrich , St . Louis , MO , USA ) as in [15] . Labelings were analyzed using a Leica DMI6000 B microscope ( Wetzlar , Germany ) and subjected to image analysis with AQUA software [62] . Cells were washed in PBS/Ca2+/Mg2+ and incubated for 30 min at 4°C in lysis buffer ( 50 mM Tris-HCl pH 7 . 4 , 150 mM NaCl , 5 mM EDTA , 1% Triton X-100 , 1 mM Na3VO4 and protease inhibitors ( Roche ) ) . After centrifugation of the lysate ( 14 , 000g , 15 min ) , the protein concentration in the supernatant was measured with the bicinchoninic acid method ( Pierce , Rockford , IL , USA ) . For the PNGase assay , protein extracts were incubated with 500 U N-glycosidase F ( PNGase , New England Biolabs , Ipswich , MA , USA ) for 1 h at room temperature . Solubilized proteins ( 20 μg ) were resolved by 10% SDS-PAGE . After transfer , blocked membranes were incubated with SAF61 primary antibody . Bound antibodies were revealed by enhanced chemiluminescence detection ( ECL , Amersham Pharmacia Biotech , Piscataway , NJ , USA ) . To standardize the results , membranes were rehybridized with an anti-α-tubulin antibody . The ratio between the truncated form of PrP ( C1 fragment ) and full-length PrP ( Native ) was evaluated by densitometric analyses using ImageQuant TL software ( GE Healthcare , Little Chalfont , UK ) . Determination of enzymatic functions was conducted on uninfected 1C115-HT cells , Fk-infected 1C115-HT cells and Rocki-Fk-1C115-HT cells . After two washings with cold PBS , cells were scraped and collected down by centrifugation ( 10 , 000g , 3 min , 4°C ) . Tryptophan hydroxylase ( TPH ) activity was measured radioenzymatically as in [23] . Briefly , cell extracts were incubated for 30 min at 37°C in an assay mixture containing 200 mM Na acetate , pH 6 . 1 , 1 mM ferrous sulfate , 2 mM 6-methyl-H4-pterin , 40 mM 2-mercaptoethanol , 20 mM Na phosphate and 100 μM [3H]-L-tryptophan . TPH activity was determined by quantifying the production of [3H]2O in a liquid scintillation counter and expressed as pmol/30 min/mg of cell protein extract . The contents in 5-HT and related metabolites were measured by HPLC combined to electrochemical ( EC ) detection as described in [23] . The presence of vesicular monoamine transporter ( VMAT ) sites was assessed through [3H]-tetrabenazine binding as in [23] . [3H]-paroxetine binding to functional 5-HT transporter ( SERT ) was carried out as in [33] . Prion-infected ( n = 3 ) and control uninfected ( n = 6 ) mice were anaesthetized with ketamine ( 125 mg kg-1 ) and xylazine ( 17 mg kg-1 ) and perfused via cardiac aorta with 4% paraformaldehyde at 130 days after infection . The cerebellum was removed and cryoprotected in sucrose 30% before freezing in isopentane at -80°C . Transverse cryostat sections ( 30 μm-thick ) were cut and submitted floating to classical immuno-peroxidase staining of PrPSc and phosphorylated cofilin using SAF32 ( 1 μg ml−1 ) and anti-phospho-Ser3-cofilin ( 2 μg ml−1; Santa Cruz , CA , USA ) antibodies , respectively . The specificity of PrPSc immunodetection was achieved by denaturing the PrPC by incubation of the sections in proteinase K ( 10 μg ml−1 ) for 10 min at 37°C and subsequently in 3 . 4 M guanidine thiocyanate for 15 min . The PrP- and phospho-Ser3-cofilin-bound antibodies were visualized using biotinylated anti-mouse or anti-rabbit immunoglobulins ( SouthernBiotech , Birmingham , AL , USA ) , respectively , and the Vectastain Elite kit ( Vector Labs , Burlingame , CA , USA ) . ROCK activity was inhibited with dimethylfasudil ( Calbiochem , San Diego , CA , USA ) or Y-27632 ( Tocris Bioscience , Ellisville , MO , USA ) . The amount of proteinase K–resistant PrP ( PrPres ) in infected cell lysates or brain extracts of 22L-infected mice infused or not with Y-27632 or dimethylfasudil were determined using a PrP-specific sandwich ELISA [24 , 63] after proteinase K digestion ( 10 μg ml−1 ) for 1 h at 37°C . TACE was detected by western blot analysis after sucrose gradient membrane fractionation of cell or cerebellar extracts performed under detergent-free conditions to isolate low buoyant fractions enriched in caveolin-1 proteins [24 , 64] . PDK1 activity was measured in cell lysates or cerebellar extracts using a fluorescently labeled PDK1 substrate ( 5FAM-ARKRERTYSFGHHA-COOH , Caliper Life Sciences , Hanover , MD , USA ) as reported in [24 , 64] . The relative amounts of substrate peptide and product phospho-peptide were determined using a Caliper EZ-reader ( Caliper Life Sciences , Hanover , MD , USA ) . ROCK-I or ROCK-II immunosequestration was performed by cell bombardment with tungsten microprojectiles coated with antibody to ROCK-I or ROCK-II [24 , 64] . ROCK-I immunoprecipitation was performed according to standard protocols by using protein A-Sepharose beads ( Amersham Pharmacia Biotech , Picataway , NJ , USA ) coupled to anti-ROCK-I antibody and 100 μg of cell lysates or cerebellar extracts . Immunoprecipitates were analyzed by western blotting using anti-ROCK-I and anti-PDK1 antibodies . [32P]-orthophosphate labeling was performed as in [65] . Briefly , the cell culture medium was removed and cells were thoroughly washed with phosphate-free DMEM to eliminate any residual phosphate-containing medium . [32P]-orthophosphate ( 40 . 7 Gbq mmol-1 , GE Healthcare , Little Chalfont , UK ) was added to the cell culture at a final concentration of 18 . 5 Mbq ml-1 . After 2 h , the labeling medium was removed and the cells were lyzed after extensive washing . Endogenously expressed wild type PDK1 was constitutively repressed in the 1C11 cell system ( PDK1null-cells ) upon cell transfection of a shRNA of the pdk1 gene [24] following the same procedure as in [15] . The mutated S241 PDK1 mutant was built by polymerase chain reaction and eight silent mutations were further introduced into the S241A pdk1 gene sequence corresponding to the siRNA hybridization zone [15] . The mutated S241 pdk1 gene was cloned into the pEBG-2T expression vector [66] . For expression of the S241A PDK1 mutant , PDK1null-cells were transfected with 10 μg of the pEBG-2T construct as in [67] and left to grown for 36 h . Reconstituted cells were then lyzed and assayed for PDK1 expression , PDK1 activity , PDK1 interaction with ROCK-I and PDK1 phosphorylation by ROCK-I after cell metabolic labeling with [32P]-orthophosphate . An analysis of variance of the cell/animal response group was performed using Kaleidagraph software ( Synergy Software , Reading , PA , USA ) . Values are given as means ± s . e . m . Significant responses ( P < 0 . 05 ) are marked by symbols ( # , * , † , ‡ ) and their corresponding P values are provided in figure legends . Survival times were analyzed by Kaplan-Meier survival analysis using a log-rank test for curve comparisons . When non-specified experiments were performed in three to five times in triplicates . | Transmissible Spongiform Encephalopathies ( TSEs ) , commonly named prion diseases , are caused by deposition in the brain of pathogenic prions PrPSc that trigger massive neuronal death . Because of our poor understanding of the mechanisms sustaining prion-induced neurodegeneration , there is to date no effective medicine to combat TSEs . The current study demonstrates that ROCK kinases are overactivated in prion-infected cells and contribute to prion pathogenesis at two levels . First , PrPSc-induced ROCK overactivation affects neuronal polarity with synapse disconnection , axon/dendrite degradation , and disturbs neuronal functions . Second , ROCK overactivity amplifies the production of pathogenic prions . The pharmacological inhibition of ROCK protects diseased neurons from PrPSc toxicity by preserving neuronal architecture and functions and lowering PrPSc level . Inhibition of ROCK in prion-infected mice reduces brain PrPSc levels , improves motor activity and extends lifespan . This study opens up new avenues to design ROCK-based therapeutic strategies to fight TSEs . | [
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] | [] | 2015 | Double-Edge Sword of Sustained ROCK Activation in Prion Diseases through Neuritogenesis Defects and Prion Accumulation |
It is increasingly clear that transcription factors play versatile roles in turning genes “on” or “off” depending on cellular context via the various transcription complexes they form . This poses a major challenge in unraveling combinatorial transcription complex codes . Here we use the powerful genetics of Drosophila combined with microarray and bioinformatics analyses to tackle this challenge . The nuclear adaptor CHIP/LDB is a major developmental regulator capable of forming tissue-specific transcription complexes with various types of transcription factors and cofactors , making it a valuable model to study the intricacies of gene regulation . To date only few CHIP/LDB complexes target genes have been identified , and possible tissue-dependent crosstalk between these complexes has not been rigorously explored . SSDP proteins protect CHIP/LDB complexes from proteasome dependent degradation and are rate-limiting cofactors for these complexes . By using mutations in SSDP , we identified 189 down-stream targets of CHIP/LDB and show that these genes are enriched for the binding sites of APTEROUS ( AP ) and PANNIER ( PNR ) , two well studied transcription factors associated with CHIP/LDB complexes . We performed extensive genetic screens and identified target genes that genetically interact with components of CHIP/LDB complexes in directing the development of the wings ( 28 genes ) and thoracic bristles ( 23 genes ) . Moreover , by in vivo RNAi silencing we uncovered novel roles for two of the target genes , xbp1 and Gs-alpha , in early development of these structures . Taken together , our results suggest that loss of SSDP disrupts the normal balance between the CHIP-AP and the CHIP-PNR transcription complexes , resulting in down-regulation of CHIP-AP target genes and the concomitant up-regulation of CHIP-PNR target genes . Understanding the combinatorial nature of transcription complexes as presented here is crucial to the study of transcription regulation of gene batteries required for development .
The intricate regulation of gene expression in multi-cellular organisms involves an elaborate collaboration between repertoires of cis-regulatory sequences and modular , multi-protein transcription complexes that bind them ( reviewed in [1] ) . Transcription complexes are now viewed as being composed of relatively ubiquitous core elements and a variety of context-dependent cofactors that interact with the core elements to regulate context-specific transcription ( reviewed in [2] ) . An increasing number of such cofactors are being identified and the diverse roles of each transcription complex is thought to depend on the unique combination of associated cofactors ( reviewed in [1]–[3] ) . A prime example for this combination of general and specific factors are complexes formed by transcription factors that interact with cofactors of the CHIP/LDB family . CHIP is a Drosophila gene product that is closely related to the LDB ( alias CLIM or NLI ) proteins that have been well preserved in evolution all the way from Caenorhabditis elegans to man . These multi-adaptor proteins mediate interactions between different classes of transcription factors and additional co-regulators of transcription ( reviewed in [4] ) . One of the best studied CHIP/LDB complexes is the Drosophila CHIP-APTEROUS complex ( Figure 1A ) . APTEROUS ( AP ) is a LIM-homeodomain ( LIM-HD ) transcription factor [5] homologue of mammalian LHX2 and LHX9 [6] . The CHIP-AP complex is composed of a dimer of CHIP molecules [7] , each of which binds one molecule of AP [8] , [9] through a LIM interacting domain ( LID ) [7] , [8] and one molecule of single-stranded DNA-binding protein ( SSDP ) through a CHIP/LDB conserved domain ( LCCD ) [10] . In the fly , this complex triggers a signaling cascade that specifies the dorsal compartment of the wing imaginal disc and serves to define the dorsal/ventral boundary at the adult wing margin ( reviewed in [11] ) . CHIP-AP complex function is negatively regulated by the Drosophila LIM-only ( dLMO ) protein ( Figure 1B ) . dLMO binds CHIP in vitro and competes with AP for binding to CHIP [9] . This cofactor exchange is crucial for the proper function of the CHIP-AP complex during wing imaginal disc development as evident from the analysis of mutant and transgenic flies [7]–[9] , [12]–[15] . An additional level of regulation is introduced by concomitant protein-protein interaction and cofactor exchange with non-LIM transcription factors ( Figure 1C ) . Specifically , CHIP and dLMO form an alternative complex together with a GATA family transcription factor , PANNIER ( PNR ) , and the beta-HLH transcription factors ACHAETE ( AC ) , SCUTE ( SC ) , and DAUGHTERLESS ( DA ) [16] . We refer to this complex as CHIP-PNR . One function of the CHIP-PNR complex is directed toward thoracic macrochaete ( sensory bristles ) differentiation ( Figure 1D ) . The pattern of sensory bristles reflects the distribution of precursor sensory mother cells in the wing imaginal disc . These precursors are specified during the third larval instar and early pupal stages from a restricted group of cells that express ac and sc [17] . The expression of ac and sc , in turn , is regulated in part by the CHIP-PNR complex [16] . In the context of the CHIP-PNR complex , dLMO is a positive regulator [18] , [19] and DNA binding is mediated through the GATA and beta-HLH transcription factors . There is a complex antagonistic relationship between CHIP-PNR and CHIP-AP , as the interaction between CHIP and PNR prevents CHIP from forming the homodimer that is crucial for the function of the CHIP-AP complex . Indeed , the function of the CHIP-PNR complex is antagonized by AP [16] . Like the CHIP/LDB encoding genes themselves , the components , assembly , and function of CHIP/LDB-based complexes appears to be highly conserved [6] , [13] , [20] , [21] . For example , complexes containing SSDP1 , LDB1 and LHX2 or LHX3 ( termed LDB-LHX ) are found in the mouse pituitary cell line alfaT3-1 [22] , and a complex containing LDB1 , GATA-1 , LMO2 , TAL1 and E47 ( termed LDB-GATA ) regulates erythropoiesis in mice [23]-[25] . SSDP proteins play a crucial role in the formation , stability and function of CHIP/LDB-based complexes in flies and mice [10] , [13] . SSDP proteins promote assembly of LDB-LHX and LDB-GATA complexes and contribute to their transcription activity . Moreover , proteasome-mediated turnover of LDB1 , LHX and LMO proteins is inhibited by formation of a complex with SSDP proteins [22] , [26] , [27] . Thus , the functional interaction between LDB and SSDP proteins appears to be independent of the specific composition of LIM or non-LIM proteins within the complex . While the function of CHIP/LDB complexes depends on SSDP , the function of SSDP proteins in turn depends on interaction with CHIP/LDB complexes: both in flies and in mammals SSDP proteins do not contain a nuclear localization signal and have to bind CHIP/LDB in order to enter the nucleus [10] . Thus , SSDP proteins are key components of CHIP/LDB complexes in both functionality and specificity . CHIP/LDB and SSDP are therefore a valuable model for studying the intricacies of transcriptional regulation at the genomic level . Here we address genome-wide effects of Drosophila SSDP on the transcriptional activity of CHIP/LDB-based complexes . Using a combination of microarray analysis and genetic interaction tests we identified novel genes downstream of SSDP that affect the development of wing and thoracic bristle development . Using transcription factor binding site analysis , we were able to show that SSDP makes distinct contributions to the transcriptional activity of the CHIP-AP and the CHIP-PNR complex .
We have conducted a genomic search for putative SSDP target genes using Drosophila microarrays [28] to report expression of 14 , 142 predicted transcripts . Poly-A+ RNA was extracted from third instar larvae ( males only to avoid potentially confounding sex-biased gene expression ) . We used two different heteroallelic combinations of ssdp hypomorphic alleles , ssdpneo48/ssdpBG1663 and ssdp31/ssdpBG1663 , which allow survival up to the pupal stage [13] . We opted to use heteroallelic combinations of ssdp on different genetic backgrounds rather than homozygotes , in order to minimize inadvertent homozygosity for extraneous mutations . The heteroallelic mutant pairs were compared to each of the corresponding single heterozygotes ( Table S1 ) . We identified 189 candidate target genes that were differentially expressed between experimental and control samples ( FDR corrected p<0 . 05; Table S2 ) . Since SSDP is believed to be a positive transcriptional regulator of the CHIP/LDB complex [10] , [13] , we expected most of the target genes to exhibit lower expression in the ssdp mutants compared to the heterozygous controls . Interestingly , only a third of the 189 genes met this expectation ( Table S2 ) . These results might suggest that SSDP has a hitherto unidentified negative transcriptional regulatory effect on certain genes . Alternatively , secondary targets may be negatively regulated by direct targets of SSDP . One way of testing for direct targets of SSDP is to look for enrichment for SSDP binding sites in the upstream regions of the 189 putative target genes . SSDP was first identified due to its ability to bind a single stranded poly-pyrimidine sequence present in the promoter of the chicken alfa-2 ( I ) collagen gene [29] . Our gel shift experiments showed that this binding site is specifically recognized by fly SSDP ( Figure 2 ) . We searched for enrichment for putative SSDP binding sites in the 500 bp upstream region of the 189 candidate genes identified in the microarray work , using two algorithms , PRIMA [30] and DEMON , We found SSDP binding site enrichment upstream the 189 candidate genes ( p = 0 . 037 ) using DEMON . Interestingly , the SSDP binding site was even more significantly enriched ( p = 0 . 02 ) among the genes down-regulated in the mutants , while there was weak significance among the genes up-regulated in the mutants ( p = 0 . 17 ) . This is consistent with the accepted role for SSDP as a positive transcriptional regulator . These data suggest that a significant number of the genes down-regulated in mutants are indeed direct targets of SSDP . In order to determine whether SSDP target genes are also likely CHIP/LDB target genes , we searched the same upstream regions for binding sites of AP and PNR , transcription factors known to function in the CHIP/LDB complex . Binding site matrices for all available insect transcription factors ( including the AP binding site ) were obtained from TransFac [31] , and a matrix of PNR binding sites , not included in TransFac , was constructed [32] . Strikingly , the PRIMA algorithm detected impressive enrichment for both AP ( p = 0 . 04 ) and PNR ( p = 4 . 64E-07 ) binding sites . Enrichment for the latter was also detected by DEMON ( p = 2 . 64E-05 ) . Interestingly , the enrichment for the AP binding site was lost when the down- ( PRIMA: p = 0 . 085 and DEMON: p = 0 . 67 ) and up- regulated ( PRIMA: p = 0 . 33 and DEMON: p = 0 . 21 ) gene groups were analyzed separately . This suggests that both groups harbor genes that are targeted by AP . The enrichment for SSDP and AP binding sites in the genes down-regulated in ssdp mutants is in agreement with SSDP functioning as a positive cofactor of the CHIP-AP complex . In contrast , the PNR binding sites were significantly enriched in the genes up-regulated in the mutants ( PRIMA: p = 2 . 59E-05 and DEMON: p = 6 . 1E-06 ) but not in the genes down-regulated in the mutants ( PRIMA: p = 0 . 085 and DEMON: p = 0 . 27 ) . This suggests that a significant number of the genes up-regulated in ssdp mutants are direct targets of PNR . Given that AP and PNR bind to CHIP competitively during Drosophila thorax formation [16] , we suggest that loss of SSDP disrupts the normal balance to favor CHIP-PNR complex formation . This would result in the down-regulation of CHIP-AP target genes and the simultaneous up-regulation of the CHIP-PNR target genes . Furthermore , up-regulated AP target genes may be regulated by both complexes . For example , AP and PNR are both known to positively regulate the expression of stripe , a key gene regulating development of the wing imaginal disc [33] , [34] . In addition to the expected enrichment for the SSDP , AP and PNR binding sites upstream of the candidate target genes , we found enrichment for several other binding sites in the upstream regions of these genes ( see Table S3 for p-values and binding sites information ) . Whether the function of all of these transcription factors is dependent on , or independent of , SSDP and/or of the CHIP/LDB transcription complexes remains to be determined . However , several of them have already been implicated in CHIP/LDB complex function ( see Discussion ) . The fact that the 189 putative SSDP target genes identified in our microarray experiments are enriched for binding sites of SSDP itself and its known partners in transcription is an independent orthogonal validation of the microarray results . These data encouraged us to ask if these putative targets have a genetic function in developmental events mediated by CHIP/LDB . The analysis of SSDP target genes suggested that they are targeted by both CHIP-AP and CHIP-PNR complexes . To simplify the interpretation of genetic tests , we chose to begin looking for functional interactions between SSDP target genes and the CHIP-AP complex in the wing , where pnr is not expressed [35] . In the wing imaginal disc the CHIP-AP complex is involved in determination of the dorsal compartment . The edge of the CHIP-AP domain is the dorsal/ventral ( D/V ) boundary which will later give rise to the adult wing margin . Subtle disruption of the transcription activity of the CHIP-AP complex causes irregularities in the D/V boundary , which are evident as notches in the adult wing margin [12] , [36] , [37] . Indeed , such disruptions occur in the over-expression allele , DlmoBx which encodes a negative regulator of the CHIP-AP complex . DlmoBx mutants have been previously shown to genetically interact with various ssdp loss-of-function alleles [13] . Thus , the DlmoBx2 allele provides a sensitized background to determine whether SSDP target genes function in D/V boundary formation . An example of the assay is depicted in Figure 3 . Since Dlmo resides on the X chromosome , heterozygous females have a considerably less severe notching than hemizygous males ( Figure 3 ) . The wing notching phenotype displays a characteristic distribution of severities [12] allowing us to delicately determine the extent of genetic interactions by scoring enhancement or suppression of the wing notching phenotype by the Wilcoxon signed-rank test . The DlmoBx2 wing phenotype was subdivided into six severity classes , where Class 1 represents flies with the least severe ( wild type wings ) and Class 6 represents the most severe wing notching . The control distributions were of DlmoBx2/+ females and DlmoBx2/Y males ( Figure 3A and 3B , respectively ) . As expected , when the DlmoBx2 mutation was combined with a heterozygous null mutation of ap , such as apUGO35 ( DlmoBx2/+; apUGO35/+ or DlmoBx2/Y; apUGO35/+ ) , the wing notching phenotype was enhanced , as evidenced by a shift of the distribution towards the more severe phenotypic classes in the double-heterozygous flies . Flies heterozygous for apUGO35 alone ( apUGO35/+ ) had normal wings . As expected due to the lack of pnr expression in this tissue , the pnr loss of function allele , pnrV1 , did not interact genetically with DlmoBx2 in our assay ( Figure S1A and S1B ) . If CHIP-AP transcriptional activity was synergistically reduced by mutations in Dlmo and ap , leading to the down-regulation of target genes of the CHIP-AP complex , then loss of function mutations in the target genes themselves ( i . e . DlmoBx2/+; “target gene−”/+ and DlmoBx2/Y; “target gene−”/+ ) might have a similar effect on the DlmoBx2 wing notching phenotype . This is indeed the case with fringe ( fng ) , a known CHIP-AP target gene in the wing disc [38] , which shows reduced expression in DlmoBx2 mutant larvae dorsal wing pouch cells [9] . Double heterozygotes for DlmoBx2 and fng80 [38] exhibit a more severe wing notching phenotype than DlmoBx2 alone , just as observed for the interaction of DlmoBx2 and apUGO35 ( Figure S1C and S1D ) . Control fng80/+ flies have normal wings . We tested 39 genes from our original set of 189 SSDP candidate target genes in this genetic interaction assay with the DlmoBx2 mutation ( Table 1 ) . These genes had publicly available mutant strains and their differential expression were evenly distributed ( ranging between 0 . 00019 and 0 . 049 FDR-corrected p-values , Figure S2 ) in our array experiments . The mutations used were usually single transposable elements insertions , and where possible two independent mutant strains per gene were tested ( allele-specific interactions are shown in Table S4 ) . Strikingly , twenty eight of these genes ( 72% ) interacted genetically with DlmoBx2 ( Table 1 ) . This is a very high rate of agreement between the microarray results and the genetic interaction assay . In comparison we observed only 30% genetic interaction between DlmoBx2 and a random set of 20 chromosomal deletions . These chromosomal deletions encompass 322 genes that are not included in the 189 SSDP target genes , such that the “background” interaction rate per gene is considerably less than 30% . These results indicate that a large number of the genes identified by the microarray are bona fide SSDP targets and have genetic functions in the CHIP-AP transcription complex pathway during wing development . As expected , most of the interacting target genes ( 25 , i . e . 89% ) enhanced the wing notching phenotype of DlmoBx2 and only three ( 11% ) suppressed it . In comparison , the interactions observed with the random set of deletions always suppressed DlmoBx2 . Thus , loss-of-function mutations in SSDP target genes have a similar effect on DlmoBx2 as loss of function mutations in ap and in its previously known target gene fng . This is consistent with a negative regulatory role for dLMO with respect to the CHIP-AP complex [7]-[9] , [12] , [14] , [15] . SSDP target genes that failed to interact with DlmoBx2 may be targets that are not dose sensitive , interact in different temporal or spatial contexts , or false positives . Genetic interactions between ssdp and Chip or DlmoBx in a double heterozygous state are readily detected in the wing [13] , but analogous genetic interactions between ssdp and loss of function alleles of ap are not . Therefore , to study the interactions between SSDP and CHIP-AP we needed another assay . We therefore explored using the only available dominant allele of ap , apXa , as a sensitized background . This mutant exhibits severe wing notching in a heterozygous state . We examined apXa/+ versus apXa/+; ssdpL7/+ flies , and observed augmentation of wing notching phenotype in the double heterozygous flies ( Figure 4 ) . In a population of apXa/+ flies , two classes of wing notching phenotypes can be distinguished ( Figure 4A , 4B , and 4G ) whereas the apXa/+; ssdpL7/+ flies exhibited three more severe wing notching classes ( Figure 4D–4G ) . The apXa mutant is a gain of function allele [39] , but its exact effect on the activity of the CHIP-AP complex is unknown . Our observation that apXa/+; ssdpL7/+ flies exhibit more severe wing notching than apXa/+ flies suggests that apXa causes reduced activity of the CHIP-AP complex , similar to DlmoBx2 . These results clearly establish a genetic interaction between ssdp and ap , and indicate that apXa is useful for examining genetic interactions between candidate SSDP target genes and ap . We tested seven of the SSDP target genes in the apXa/+ background ( apXa/+; target gene−/+ ) . Mutations in the katanin-60 , CG12163 and Myofilin genes ameliorated the wing notching phenotype of apXa/+ flies , whereas CG11893 and Xbp1 mutations exacerbated wing notching ( CG1518 and Cyp6d4 did not show an overt genetic interaction with apXa ) . These data indicate that both SSDP and SSDP target genes interact with AP and are therefore likely to act in a common pathway . Interestingly , the SSDP target genes enhanced the apXa wing notching less severely than ssdp itself , suggesting that the effect of SSDP is distributed among a large number of SSDP targets . The genetic interactions with DlmoBx2 and apXa demonstrated that the SSDP target genes we identified are likely regulated by the CHIP-AP complex . Next we used genetic interactions to directly test our hypothesis that loss of SSDP disrupts the balance between the CHIP-AP and CHIP-PNR complexes in favor of the latter . To look at this balance between complexes , we examined thoracic bristles where both complexes function [16] . The CHIP-PNR complex positively regulates formation of thoracic sensory bristles via direct binding to the ac/sc enhancer . This CHIP-PNR function should be antagonized by AP since PNR and AP compete for binding of CHIP [16] . Consistent with our hypothesis , that loss of SSDP disrupts the balance between these two complexes , we found that both ssdpL7 and Chipe5 . 5 mutants display duplication of scutellar bristles as heterozygotes ( <30% and <20% penetrance , for ssdpL7/+ and Chipe5 . 5/+ , respectively , data not shown ) , a phenotype similar to gain of function alleles of pnr [35] . Flies heterozygous for pnrVX6 alone have normal number of scutellar bristles . We therefore expected that double heterozygous flies ( ssdpL7/+; pnrVX6/+ ) would exhibit reduced occurrence of scutellar bristle duplications due to the lower levels of pnr . Indeed , duplicated scutellar bristles phenotype was abolished in ssdpL7/+; pnrVX6/+ flies . Thus , reduced levels of pnr rescued the duplicated bristle phenotype of a loss of function ssdp mutant , supporting the antagonistic model for CHIP-PNR and CHIP-AP complex formation . This model predicts that mutations in the SSDP target genes will have a similar phenotypic effect as altering the balance between CHIP-PNR and CHIP-AP complexes . To test this prediction we used the ssdpL7 and Chipe5 . 5 mutations as a sensitized background to screen the SSDP target genes for modifiers of scutellar bristle formation ( ssdpL7/+; target gene−/+ and Chipe5 . 5/+; target gene−/+ ) . Given the opposing roles of the CHIP-AP and CHIP-PNR complexes in this tissue we expected SSDP target genes to either enhance or suppress the duplicated scutellar bristles phenotype of ssdpL7/+ and Chipe5 . 5/+ depending on which of the two complexes regulates that particular SSDP target . Mutations in twenty eight SSDP target genes were tested as double heterozygotes with either ssdpL7 or Chipe5 . 5 ( allele-specific interactions are shown in Table S5 ) . A total of 23 of them were found to interact with either ssdpL7 or Chipe5 . 5 ( Table 1 ) . Fourteen genes ( 52% ) interacted genetically with ssdpL7 and the same number of genes interacted genetically with Chipe5 . 5 . Five genes ( 17 . 8% ) interacted with both . This impressive rate of interaction suggests that SSDP targets are regulated by either or both CHIP complexes . The rate of interaction with CHIP and SSDP mutations in bristles is somewhat lower than what we observed for interaction with DlmoBx2 in the wing . However , this is not surprising as SSDP target genes may be regulated by either AP or PNR or both , which might make bristles more robust to perturbation and thus make it harder to detect genetic interaction in the thoracic bristles compared with the wing , where only AP is present . Among the 23 interacting SSDP target genes , mutations in 12 were found to partially suppress the duplicated scutellar bristle phenotype suggesting that they are positive regulators of scutellar bristle formation ( Table 1 ) . Conversely , mutations in 11 interacting SSDP target genes enhanced the duplicated scutellar bristle phenotype , suggesting that they are negative regulators of bristle formation ( Table 1 ) . Interestingly , ten of the 12 suppressors affected the Chipe5 . 5 bristle phenotype and only five affected the ssdpL7 bristle phenotype ( three genes suppressed both Chipe5 . 5 and ssdpL7 phenotypes ) . In contrast , nine of the enhancers affected the ssdpL7 bristle phenotype while only four enhanced the Chipe5 . 5 phenotype ( two genes enhanced both Chip and ssdp bristle phenotypes ) . Thus , it appears that loss of ssdp has a predominant effect on genes that negatively regulate scutellar bristle formation . This finding is consistent with our microarray and transcription factor binding site enrichment analyses which showed that loss of ssdp function resulted in down regulation of the CHIP-AP target genes , and with the antagonistic effect of AP on bristle formation . In contrast , although CHIP functions as a cofactor for both AP and PNR , the Chipe5 . 5 mutation was more useful than the ssdpL7 mutation for identifying genes that are positive regulators of scutellar bristle formation . The reason for this difference is unknown , but given the complexity evident when comparing the interactions and function of CHIP/LDB complex in just two tissues , it is likely that further complexity remains to be discovered in other contexts . The salient point is that our genetic interaction results demonstrate a clear modularity of the regulation of SSDP target genes by CHIP/LDB complexes in different tissues . Understanding this type of context-dependent component shuffling in transcription complexes will be required for a full understanding of transcriptional networks . Our genetic screens described above tested the ability of heterozygous mutations in SSDP target genes to cause subtle changes in the dominant phenotypes of DlmoBx2 , apXa , ssdpL7 and Chipe5 . 5 in the wing and scutellar bristles , respectively . Next we wished to determine whether the SSDP target genes identified are essential for proper development of these structures . The simplest way is to examine mutations in SSDP target genes in a homozygous state . Unfortunately , those mutations which were homozygous viable did not exhibit any wing or thorax morphological defects . For example , the CG2604EY05974 mutation enhanced the DlmoBx2 wing notching in a double heterozygous state ( Table S4 ) . Yet , in an otherwise wild type background , CG2604EY05974 homozygous flies are viable and do not have any wing or thoracic morphological abnormalities ( not shown ) . It is possible that these genes participate in , but are not essential for , wing and thorax formation , or that the mutations used to test for function were weak hypomorphs . For example , CG2604EY05974/Df ( 3R ) ED5147 exhibit ectopic wing veins ( Figure S3 ) indicating that at least some of the failure to find homozygous mutant phenotypes is due the use of classic hypomorphic mutations . Several of SSDP target gene mutations we used were homozygous lethal prior to adulthood , precluding examination of wing or thorax phenotypes . To avoid difficulties due to pleotyropic affects on viability , we utilized the transgenic GAL4/UAS system for targeted silencing of the SSDP target genes [40] . This approach offered two advantages: First , the UAS-RNAi constructs that were used are gene-specific . Second , expression of the UAS-RNAi can be targeted to a subset of cells depending on the GAL4 driver used while the rest of the cells maintain normal expression of the target gene , thus avoiding lethality . The ap-Gal4 [41] and pnr-Gal4 [35] drivers drive reproducibly high levels of UAS-lacZ transgene expression in cells known to express ap and pnr respectively , within the wing disc . Thus , by combining the transgenic constructs ( ap-Gal4/+; UAS-RNAi-target gene/+ or pnr-Gal4/+; UAS-RNAi-target gene/+ ) we silenced SSDP target genes in either ap- or pnr-expressing cells . We knocked down nine SSDP target genes that interacted with DlmoBx2 , apXa , ssdpL7 and Chipe5 . 5 . Silencing of two of them had profound effects . Silencing of Xbp1 ( a . k . a . CG9415 ) in ap-expressing cells resulted in semi-lethality . Survivors reaching adulthood developed severely disrupted wings which appeared as small amorphic inflated structures , accompanied by marked excess of bristles on the wing and scutum , while the scutellum was not affected ( Figure 5B , 5C , and 5E ) . As expected by the pattern of pnr expression in the adult fly [35] , silencing of Xbp1 in pnr-expressing cells caused a similar excess of bristles that were limited to the mid-line of the scutum while the wings were not affected . Interestingly , no extra bristles were observed on the scutellum , and some of the flies even exhibited a reduced number of scutellar bristles ( Figure 5D ) . These observations indicate that Xbp1 has opposing roles in regulating bristle development in the scutum and scutellum . Silencing of G-salpha60A ( a . k . a . CG2835 ) in ap-expressing cells caused a curled wing phenotype ( Figure 5F ) . In addition , silencing of this gene in pnr-expressing cells reversed the orientation of the posterior pair of scutellar bristles ( Figure 5G ) . It is therefore obvious that these two SSDP target genes are essential for normal wing and thorax development . The remaining seven SSDP target genes tested in this manner exhibited variable effects on the number of scutellar bristles and at very low penetrance . Given the large number of SSDP target genes and the likely robustness that this facilitates , some weak effects are expected . Combinatorial knock down experiments , much like the large set of double heterozyote tests we report here , will be required to piece these genes together into a more developed model . Importantly , like the CHIP-AP and CHIP-PNR complexes themselves , SSDP target genes show context-dependent effects on development .
Our genome-wide expression profiling and bioinformatics analysis of ssdp mutant larvae , combined with genetic screens enabled us to gain insight into the intricate context-dependent transcriptional regulation by CHIP/LDB complexes . We were able to identify 28 putative SSDP target genes that are involved in wing development and 23 putative SSDP target genes that play a role in scutellar bristle formation . Examination of two of these , xbp1 and Gs-alpha60A , suggests novel aspects of developmental regulation such as the involvement of SSDP and CHIP/LDB complexes in ER function and PKA signaling . Furthermore , we showed for the first time that SSDP proteins contribute differentially to transcription activity , and probably to the balance in formation of CHIP-AP and CHIP-PNR complexes . Furthermore we identified potential novel partners of SSDP in regulating transcription of downstream genes during fly development . It stands to reason that an extension of our genetic analysis to mammals and other vertebrates will reveal a host of additional functions of SSDP and CHIP/LDB during the multifaceted process of transcriptional regulation that underlies the development of multicellular organisms .
Unless otherwise stated , flies were grown on a standard medium containing cornmeal , yeast , molasses , and propionic acid at 25°C . The ssdp mutant strains ( i . e ssdpBG1663 , ssdpneo48 and ssdp31 ) used for the microarray experiment were previously described [13] , all three were balanced on TM3-GFP ( FBba0000338 ) . The rev ( ssdpneo48 ) line is a precise excision of the P element inserted in ssdpneo48 . UAS-RNAi lines 18873 , 38686 , 38186 , 24959 , 24959 , 6367 , 40871 , 9026 , 12823 and 15347 were obtained from VDRC [61] . Chromosomal deletions Df ( 2L ) ED49 , Df ( 2L ) ED548 , Df ( 3L ) ED231 , Df ( 3L ) ED4284 , Df ( 2L ) ED1109 , Df ( 2L ) ED299 , Df ( 1 ) ED7067 , Df ( 2R ) ED2222 , Df ( 3R ) ED5156 , Df ( 3L ) ED4528 , Df ( 2L ) ED270 , Df ( 2L ) ED774 , Df ( 2L ) ED746 , Df ( 3R ) ED5187 , Df ( 2L ) ED673 , Df ( 2L ) ED120 , Df ( 1 ) ED6957 , Df ( 2L ) ED19 , Df ( 3R ) ED5657 and Df ( 3R ) ED10257 , were obtained from the DrosDel collection [62] . All other fly stocks were obtained from the Bloomington Drosophila Stock Center ( http://flystocks . bio . indiana . edu ) . Oregon-R flies were used as wild type . RNA handling was performed exactly as described [65] . Briefly , larvae were flash frozen . Total RNA was extracted using Trizol ( Life Technologies , Carlsbad , USA ) , followed by mRNA isolation using an Oligotex poly ( A ) extraction kit ( Qiagen , Valencia , USA ) . RNA concentration was determined using RiboGreen dye ( Molecular Probes , Oak Ridge , USA ) . RNA quality was determined by capillary electrophoresis using the 6000 Nano Assay kit ( Agilent ) . All procedures were carried according to the manufacturer's instructions . All genomic sequences were obtained from the UCSC genome browser ( http://genome . ucsc . edu/ , assembly Apr . 2006 for the D . melanogaster genome ) [70] . The 500 bp upstream of the 189 candidate genes scanned using two algorithms termed PRIMA [30] and DEMON , for identifying enrichment of transcription factors binding sites in a set of co-regulated genes . Both methods require a background set for comparison ( in this case all the annotated genes in Drosophila ) . Analysis for enrichment of GO functions was conducted using the database for annotation , visualization and integrated discovery ( DAVID ) [71] , [72] . Default setting were used and the enrichment cut off was set to p = 0 . 05 after FDR correction . Fly ssdp was PCR amplified , cloned into pZEX plasmid and expressed with a GST tag in E . coli BL-21 . Crude cell extract or purified GST-SSDP fusion protein was used for binding assays . GST-SSDP was purified on a glutathione agarose column ( Sigma G4510 ) . The ssdp single stranded CT oligonucleotide [29] was used as prob . Binding assays were carried out using the DIG Gel shift kit 2nd generation ( Roche , Mannheim , Germany ) according to the manufacturer instruction in a final volume of 20 µl containing labeled DNA ( 150 fmoles ) , 1 µl of poly-L-lysine and 3 µl poly-[d ( I-C ) ] , 140 ng cell extract . For competition experiments 90 or 360 ng of unlabeled probe were added . Following a 20 min incubation at room temperature , the binding reaction products were separated on a native 6% polyacrylamide gel in 0 . 5% TBE ( pH = 8 ) . The gel was contact blotted onto a Hybond-N+ membrane ( Amersham Biosciences ) . The chemiluminescent detection was performed following the manufacturer's instructions ( Roche , Mannheim , Germany ) . The membrane was exposed to X-ray film ( FUJI ) for 15 min at 37°C . | Different cell types in multi-cellular organisms are determined by the repertoire of genes active in each cell . This repertoire , or transcriptome , is established by the coordinated activity of transcription factors and cofactors that form modular transcription complexes . The modular nature of transcription complexes complicates our understanding of how transcription factors shape the transcriptome . CHIP/LDB transcription complexes direct formation of various cell types including blood and nerve cells . CHIP/LDB malfunction leads to developmental defects and cancer . The function of these complexes depends critically on the docking of specific transcription factors and co-factors at a specific time and in a specific cell type , making them outstanding models for intricate transcriptional regulation . Here we demonstrate that loss of SSDP , a key regulatory component of CHIP/LDB transcription complexes , alters transcription of a large group of genes . We used bioinformatics tools and genetic tests to examine the function of additional components of CHIP/LDB transcription complexes and their target genes during the development of specific organs . We demonstrate how differences in the availability of transcription factors in different cells can affect the function and composition of CHIP/LDB transcription complexes . | [
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] | 2010 | Transcriptional Regulation by CHIP/LDB Complexes |
An expanded chemical space is essential for improved identification of small molecules for emerging therapeutic targets . However , the identification of targets for novel compounds is biased towards the synthesis of known scaffolds that bind familiar protein families , limiting the exploration of chemical space . To change this paradigm , we validated a new pipeline that identifies small molecule-protein interactions and works even for compounds lacking similarity to known drugs . Based on differential mRNA profiles in multiple cell types exposed to drugs and in which gene knockdowns ( KD ) were conducted , we showed that drugs induce gene regulatory networks that correlate with those produced after silencing protein-coding genes . Next , we applied supervised machine learning to exploit drug-KD signature correlations and enriched our predictions using an orthogonal structure-based screen . As a proof-of-principle for this regimen , top-10/top-100 target prediction accuracies of 26% and 41% , respectively , were achieved on a validation of set 152 FDA-approved drugs and 3104 potential targets . We then predicted targets for 1680 compounds and validated chemical interactors with four targets that have proven difficult to chemically modulate , including non-covalent inhibitors of HRAS and KRAS . Importantly , drug-target interactions manifest as gene expression correlations between drug treatment and both target gene KD and KD of genes that act up- or down-stream of the target , even for relatively weak binders . These correlations provide new insights on the cellular response of disrupting protein interactions and highlight the complex genetic phenotypes of drug treatment . With further refinement , our pipeline may accelerate the identification and development of novel chemical classes by screening compound-target interactions .
Most research programs focus on a subset of roughly 10% of human proteins , and this bias has a profound effect on drug discovery , as exemplified by studies on protein kinases [1–3] . The origin for this relatively limited exploration of the human interactome and the resulting lack of novel drugs for emerging ‘genomic-era’ targets has been traced back to the availability of small molecular weight probes for only a narrow set of familiar protein families [1] . To break this vicious cycle , a new approach is needed that goes beyond known targets and old scaffolds and benefits from the vast amount of information we possess on gene expression , protein interactions , protein structures , and the genetic basis of disease . The current target-centric paradigm relies on high-throughput in vitro screens of large compound libraries against a single protein [4] . This approach has been effective for kinases , GPCRs , and proteases , but has produced meager yields for new targets such as protein-protein interactions , which require chemotypes absent in most compound libraries [5 , 6] . Moreover , these in vitro biochemical screens often cannot provide any context regarding drug activity in the cell , multi-target effects , or toxicity [7 , 8] . On the other hand , the goal of leveraging new chemistries requires a compound-centric approach that would test compounds directly on thousands of potential targets . In practice , this is undertaken in cell-based phenotypic assays , but it is often unclear how to identify potential molecular targets in these experiments [9–11] . Understanding how cells respond when specific interactions are disrupted is not only essential for target identification but also for developing therapies that might restore perturbed disease networks to their native states . Compound-centric computational approaches are now commonly applied to predict drug—target interactions by leveraging existing data . However , many of these methods extrapolate from known chemistry , structural homology , and/or functionally related compounds , and excel in target prediction only when the query compound is chemically or functionally similar to known drugs [12–17] . Other structure-based methods , such as molecular docking , can evaluate novel chemistries but are limited by the availability of protein structures [18–20] , inadequate scoring functions , and excessive computing times , which render structure-based methods ill-suited for genome-wide virtual screens [21] . More recently , a new paradigm to predict molecular interactions using cellular gene expression profiles has emerged [22–24] . Previous work showed that distinct inhibitors of the same protein target produce similar transcriptional responses [25] . Other studies predicted secondary pathways affected by chemical inhibitors by identifying genes that , when deleted , diminish the transcriptomic signature of drug-treated cells [26] . When target information is lacking for a compound , alternate approaches were needed to map drug-induced differential gene expression networks onto known protein interaction network topologies . Prioritized potential targets could then be identified through highly perturbed subnetworks [27–29] . These studies predicted roughly 20% of known targets within the top 100 ranked genes , but did not predict or validate any previously unknown interactions . The NIH Library of Integrated Cellular Signatures ( LINCS ) project presents an opportunity to leverage gene expression signatures from numerous cellular perturbations to predict drug-target interaction . Specifically , the LINCS L1000 dataset contains cellular mRNA signatures from treatments with over 20 , 000 small molecules and 20 , 000 gene over-expression ( cDNA ) or knockdown ( sh-RNA ) experiments . Based on the hypothesis that drugs which inhibit their target ( s ) should yield similar network-level effects to silencing the target gene ( s ) ( Fig 1a ) , we calculated correlations between the expression signatures of thousands of small molecule treatments and gene knockdowns ( KDs ) in the same cells . We next used the strength of these correlations to rank potential targets for a validation set of 29 FDA-approved drugs tested in the seven most abundant LINCS cell lines . We then evaluated both direct signature correlations between drug treatments and KDs of their potential targets , as well as indirect signature correlations with KDs of proteins up- or down-stream of potential targets . We subsequently combined these correlation features with additional gene annotation , protein interaction and cell-specific features in a supervised learning framework and use Random Forest ( RF ) [30 , 31] to predict each drug’s target . Ultimately , we achieved a top 100 target prediction accuracy of 55% , which we show is due primarily to our novel correlation features . Finally , to filter out false positives and further enrich our predictions , molecular docking evaluated the structural compatibility of the RF-predicted compound—target pairs . This orthogonal analysis significantly improved prediction accuracy on an expanded validation set of 152 FDA-approved drugs , obtaining top-10 and top-100 accuracies of 26% and 41% , respectively , more than double that of aforementioned methods . A receiving operating characteristic ( ROC ) analysis yielded an area under the curve ( AUC ) for top ranked targets of the RF and structural re-ranked predictions of 0 . 77 and 0 . 9 , respectively . We then applied our pipeline to 1680 small molecules profiled in LINCS and experimentally validated seven potential first-in-class inhibitors for disease-relevant targets , namely HRAS , KRAS , CHIP , and PDK1 .
We constructed a validation set of 29 FDA-approved drugs tested in at least seven LINCS cells lines and whose known targets were among 2634 KD genes in the same cell lines . For these drugs , we ranked potential targets using the direct correlation between the drug-induced mRNA expression signature and the KD-induced signatures of potential targets ( Fig 1b and 1c ) . For each cell line , the 2634 KD signatures were sorted by their Pearson correlation with the expression signature of the drug in that cell line . We used each gene’s lowest rank across all cell lines to produce a final ranking of potential targets for the given drug . Using this approach , we predicted known targets in the top 100 potential targets for 8/29 validated compounds ( Table 1 ) . Indirect correlations were evaluated by the fraction of a potential target’s known interaction partners ( cf . BioGrid [32] ) whose KD signatures correlated strongly with the drug-induced signature . Ranking by indirect correlations predicted the known target in the top 100 for 10 of our 29 validation compounds ( Table 1 ) . Interestingly , several of these compounds showed little correlation with the KD of their targets ( Fig 1d and 1e ) , with only 3/10 targets correctly predicted using the direct correlation feature alone . It is well known that expression profiles vary between cell types [33] . Thus , we constructed a cell selection feature to determine the most “active” cell line , defined as the cell line producing the lowest correlation between the drug-induced signature and the control signature . Ranking by direct correlations within the most active cell line for each drug predicted six known targets in the top 100 ( Table 1 ) . However , all six of these targets were already predicted by either direct or indirect correlations , strongly suggesting that scanning for the optimal correlation across all cell lines is a better strategy than trying to identify the most relevant cell type by apparent activity . Next , to incorporate findings of previous studies that suggest that drug treatments often up/down regulate the expression of their target’s interaction partners [27–29] , we constructed two features to report directly on the drug-induced differential expression of potential target interaction partners . These features compute the maximum and the mean differential expression levels of potential interaction partners in the drug-induced expression profile . The lowest rank of each potential target across all cell lines is used in a final ranking . Though neither expression feature produces top 100 accuracies better than those of our correlation features , maximum differential expression identifies three new targets that were not identified using any of the previous features ( Table 1 ) . While each of the features in Table 1 performed better than random , combining them further improved results . Using Leave-One-Out Cross Validation ( LOOCV ) for each drug , logistic regression [31] correctly identified known targets in the top 100 predictions for 11 out of 29 drugs and improved the average known target ranking of all drugs ( Table 1 ) . However , logistic regression assumes that features are independent , which is not the case for our dataset given the complexity and density of cellular protein interaction networks . Hence , we used RF , which is able to learn more sophisticated decision boundaries [34] . Following the same LOOCV procedure , the RF classifier led to much better results than the baseline logistic regression , correctly finding the target in the top 100 for 16 out of 29 drugs ( 55% ) ( Table 1 ) . Without further training , we tested the RF approach on the remaining 123 FDA-approved drugs that had been profiled in 4 , 5 , and 6 different LINCS cell lines , and whose known targets were among 3104 genes knocked down in the same cells . We predicted known targets for 32 drugs ( 26% ) in the top 100 ( S2 Text ) , an encouraging result given the relatively small size of the training set and the expected decline in accuracy as the number of cell lines decreases ( Table 2 ) . Re-training on the full set of 152 drugs and validating with LOOCV allowed us to test two alternative RF models: “on-the-fly” , which learns drug-specific classifiers trained on the set of drugs profiled in the same cell types , and “two-level” , which learns a single classifier trained on experiments from all training drugs ( see Methods ) . The performances of both methods as a function of the number of cell lines profiled are summarized in Table 2 . On-the-fly RF correctly ranked the targets of 8 out of 152 drugs in the top 100 ( 38% ) , with 42 of them in top 50 ( 28% ) . Two-level RF produced better enrichment , correctly predicting targets for 63 drugs in the top 100 ( 41% ) , and for 54 drugs in the top 50 ( 36% ) . To further evaluate model performance , we generated a receiver operating characteristic ( ROC ) curve from the LOOCV predictions of our two-level RF ( S2 Fig ) . In this analysis , the False Positive Rate ( x axis ) is the normalized rank threshold we use to define potential targets from non-targets ( e . g . , top-10 , top-100 ) . The True Positive Rate ( y axis ) is the fraction of compounds for which the known target ranks above the given threshold . Prediction power is measured as the area under the ROC curve ( AUC ) , with AUC = 1 indicating perfect prediction and AUC = 0 . 5 indicating random prediction . Our RF produced an AUC of 0 . 77 while , in sharp contrast , random rankings ( based on 20000 permutations ) leads to only 7% of drugs with targets in the 100 , indicating that both our training/testing and LOOCV results are extremely significant ( S1 Fig ) . It is also noteworthy that the top-100 accuracy of the two-level RF analysis increases to 50% if we only consider drugs treated in 5 or more cell lines . We note that 20% , or 33 , out of the 152 FDA approved training drugs have multiple known targets with KD signatures in the LINCS library ( S1 Table ) . However , only 16 of those had more than one target among the KDs in four or more cell lines . Thus , only a small portion ( 10% ) of the analyzed compounds had multiple known targets that we could potentially predict ( see S2 Table ) , making the analysis of polypharmacological effects difficult . However , for 4 ( out of 16 ) multi-target compounds , our RF model was able to identify more than one target . It is thus possible that drugs in the training set might bind to other targets that could be in our top 100 list . Next , we analyzed in what context our RF analysis was most successful . To this end , we divided the 152 drugs in our training data into “successful” predictions ( the 63 drugs for which the correct target was ranked in the top 100 ) , and “unsuccessful” predictions . We also divided the known targets into those that were correctly predicted and those that were not . We considered several different ways to characterize small molecules including molecular weight , solubility , and hydrophobicity , but none of these seemed to significantly correlate with our “successful” and “unsuccessful” classifications . Next , we used gene ontology to test for enrichment of “successful” and “unsuccessful” targets . Interestingly , we found that “successful” targets were significantly associated with intracellular categories , while the “unsuccessful” targets were mostly associated with transmembrane and extracellular categories ( S3 Table ) . Based on this result we further incorporated this cellular component as a feature in our two-level RF . We encode this feature by assigning 1 to the intracellular genes and -1 to the transmembrane and extracellular ones . We ran the two-level RF with this additional feature included and demonstrated that the cellular component increases the number of top 100 genes to 66 and top 50 genes to 55 . These results demonstrate the possibility of further improving our predictions by incorporating relevant properties of compounds or targets . Fig 1d and 1e show that the gene regulatory effects of TUBA1A inhibition by the drug vinblastine manifest primarily as indirect correlations with KDs of the target’s interaction partners , such as RUVBL1 , rather than via direct correlation with KD of the target . Such cases reflect the intrinsic connectivity of cellular signaling networks , which sometimes produce gene expression correlations that are ambiguous with respect to which of the interacting proteins in the affected pathway is the drug’s actual target . Our pipeline eliminates some of these false positives using an orthogonal structure-based docking scheme that—although limited to targets with known structure—allows us to significantly improve our prediction accuracy . After performing RF classification on the validation set , we mined the Protein Data Bank ( PDB ) [35] to generated structural models of the potential targets for our 63 “hits” . This set represents drugs for which we correctly identified the known target in the top 100 . We selected one or more representative crystal structures for each potential target gene , optimizing for sequence coverage and structural resolution ( see S1 Text ) . We then docked hits to their top 100 potential targets and ranked them using a prospectively validated pipeline [36–39] . On average , crystal structures were available for 69 out of the top 100 potential targets for each compound , and structures of known targets were available for 53 of the 63 hits . In order to avoid redocking into cocrystals , we excluded all crystal structures containing these 53 ligands from our analysis , ensuring that our results would not depend on prior knowledge of interaction partners or binding modes . As shown in Fig 2 , molecular docking scores improved re-ranking of the known target for 40 of the 53 drugs , with a mean and median improvement of 13 and 9 , respectively . Based on genomic data alone , the known target was ranked in the top 10 for 40% of the 63 hits . After structural re-ranking , 65% had their known targets in the top 10 candidates , and this value improved to 75% in the subset of 53 drugs with known target structures . ROC analysis of structurally-refined predictions yielded an AUC of 0 . 90 ( S3 Fig ) . These results demonstrate the power of orthogonal genomic and structural screens and establish that molecular docking can efficiently eliminate false positives in our gene expression-based predictions . After validating our approach on known drug targets , we applied our pipeline to a test set of 1680 small molecules and 3333 gene KDs and predicted several novel interactions . The experimental testing set was chosen based solely on the predicted correlations of the RF model and availability of the assays . We applied our pipeline ( Fig 3 ) in both compound-centric ( target prediction ) and target-centric ( virtual screening ) contexts , in each case producing a final , enriched subset of roughly 10 predictions ( either compounds or targets ) that we tested experimentally . In compound-centric analyses , we performed molecular docking on the available structures of the input compound’s top-100 RF-predicted targets . In target-centric analyses , we ran the RF on our full test set , identified compounds for which the input protein is ranked in the top 100 potential targets , and then docked these candidates into the target . In both applications , we analyzed the final docking score distributions and applied a 50% cutoff threshold to identify highly enriched compound/target hits . Structural analysis further facilitated visual validation of the docking models of predicted hits , thereby minimizing false positives . Because of limitations in available assays for subsequent tests , we analyzed our experimental results within a target-centric approach . According to our validation results , we would expect one hit in about 5 to 6 compounds on targets where crystal structures are available . As outlined below , we chose four targets for this analysis , and it is vital to note that the compounds have not been optimized but represent “crude” hits obtained from the pipeline . Needless to say , significantly improved results could be obtained with chemical optimization , but our efforts simply represent a facile way to isolate these initial hits . Our first application consisted in identifying novel binders of the high-impact and historically “undruggable” RAS-family of oncoproteins . HRAS and KRAS are among the most frequently mutated genes in human cancers [40 , 41] . However , despite the extensive structural data available and tremendous efforts to target them with small-molecule therapeutics , as of yet no RAS-targeting drug candidates have shown success in clinical trials [42–44] . Among the 1680 compounds in our test set , 84 and 156 were predicted ( within the top-100 ) to target KRAS and HRAS , respectively . These compounds produced mRNA perturbation signatures that correlated strongly with KDs of KRAS ( Fig 4a ) , and HRAS ( Fig 4b ) . Of note , differential expression of genes functionally related to K/HRAS , i . e . FGFR4 , FGFR2 , FRS1 , inform on novel regulatory phenotypes responding to both compound inhibition and gene knock out . We docked predicted compounds to our representative structures of KRAS ( PDB ID: 4DSO [42] ) and HRAS ( PDB ID: 4G0N [45] ) ( Fig 4c and 4d ) . RF ranking and docking score distributions were compared to select compounds from our enriched datasets that were both commercially available and moderately priced . Docking models of promising candidates were also examined visually to reject models with unmatched hydrogen bonds [46] and select those that showed suitable mechanisms of action ( see , e . g . , Fig 4c and 4d ) . We purchased six potential HRAS inhibitors and five potential KRAS inhibitors for experimental validation ( S4 Table ) . We sent our compounds to the RAS Biochemistry and Biophysics Group at Leidos Biomedical Research for validation . Their SPR assay measured direct binding of predicted inhibitors to AviTagged HRAS and KRAS . Initial 100 μM screens showed binding response for compounds RS-3906 against HRAS and phloretin against KRAS , and subsequent titrations confirmed binding at μM concentrations ( Fig 4e and 4f ) , comparable to the DCAI positive control [42] . Next , we targeted STUB1 , also known as CHIP ( the carboxy-terminus of Hsc70 interacting protein ) , an E3 ubiquitin ligase that manages the turnover of over 60 cellular substrates [47] . To our knowledge , inhibitors of this ligase—even of low affinity/potency—have not been identified . CHIP interacts with the Hsp70 and Hsp90 molecular chaperones via its TPR motif , which recruits protein substrates and catalyzes their ubiquitination . Thus , treatment with small molecules that inhibit CHIP may prove valuable for pathologies where substrates are prematurely destroyed by the ubiquitin-proteasome system [48] . The screening of the 1680 LINCS small molecules profiled in at least four cell lines predicted 104 compounds with CHIP among the top 100 targets . We docked these molecules to our representative structure of the TPR domain of CHIP ( PDB ID: 2C2L [49] ) , for which we had an available fluorescence polarization ( FP ) assay . The RF ranking and docking score distributions were compared to select compounds highly enriched in one or both scoring metrics . We next visually examined the docking models of top ranking/scoring hits to select those that show suitable mechanisms of action , and purchased six compounds for testing ( S5 Table ) . In parallel , we performed a pharmacophore-based virtual screen of the ZINC database [50] using the ZincPharmer [39] server , followed by the same structural optimization [36–39] performed on the LINCS compounds . We purchased seven of the resulting ZINC compounds for parallel testing ( none of the selected compounds were in the LINCS library ) . Our FP assay measured competition with a natural peptide substrate for the CHIP TPR domain . We found that four ( out of six ) of our LINCS compounds reliably reduced substrate binding ( Fig 5a and 5b ) , while three ( out of seven ) ZINC compounds did so to a modest degree ( S4 Fig ) . The two strongest binders were LINCS compounds 2 . 1 and 2 . 2 . To test if these compounds would inhibit CHIP activity , we utilized a cell-free ubiquitination assay in which purified CHIP polyubiquitinates an Hsc70-derived substrate protein in an ATP dependent manner ( S5a Fig ) . This functional assay verified that 2 . 1 and 2 . 2 prevented substrate ubiquitination and CHIP autoubiquitination ( Fig 5c and 5d , S5b and S5c Fig ) , while ZINC compounds did not ( S5d Fig ) . Compounds 2 . 1 and 2 . 2 also prevented ubiquitination of an alternate substrate that was tested subsequently ( S6 Fig ) . Importantly , the predicted binding modes of these two compounds did not match the pharmacophore model of the TPR-HSP90 interaction [49] , which was used to screen the ZINC database ( S7 Fig ) . The latter emphasizes the power of our approach to identify novel compounds and mechanisms of action to targets without known inhibitors . Contrary to the RAS compounds that were identified based on direct correlations between compound treatments and RAS KDs ( Fig 4a and 4b ) , CHIP hits show almost no direct correlation ( ρ2 . 1 = 0 . 15 , ρ2 . 2 = 0 . 02 ) , but were predicted based on indirect correlations with CHIP interaction partners . This may explain their relatively low potency . Fig 6 shows the correlating differential gene expression profiles for compound 2 . 1 and KDs of the CHIP interaction partners UbcH5 and HSP90 , which , along with CHIP , were also predicted as potential targets by the RF classifier . However , structural screening ruled out these two partners as potential targets because of a lack of favorable binding modes . We next demonstrated a compound-centric application of our pipeline by analyzing Wortmannin , a selective PI3K covalent inhibitor and commonly used cell biological tool . DrugBank [51] lists four known human targets of Wortmannin: PIK3CG , PLK1 , PIK3R1 , and PIK3CA . Of the 100 targets predicted for Wortmannin , the PDB contained structures for 75 , which we used to re-rank these potential targets . Only one known kinase target of Wortmannin , PIK3CA , was detected , and ranked 5th . The human kinase PDPK1 ( PDK1 ) ranked 2nd in our pipeline . Although PDK1 is a downstream signaling partner of the PI3Ks [52] , there is no prior evidence of a direct Wortmannin-PDK1 interaction in the literature . Nevertheless , both the strong direct correlation of wortmannin with the PDK1 KD ( Fig 7a ) , and the native-like binding mode predicted by our pipeline ( Fig 7b ) suggested a possible interaction . We experimentally tested this interaction using an alphascreen PDK1 interaction-displacement assay . Since we predicted that Wortmannin binds to the PH domain of PDK1 ( Fig 7b ) , we measured the effect of increasing Wortmannin concentrations on the interaction of PDK1 with the second messenger PIP3 . We found that Wortmannin specifically increased PDK1-PIP3 interaction , relative to control ( Fig 7c ) . Given that PIP3-mediated recruitment of PDK1 to the membrane is thought to play an important regulatory role in the activity of the enzyme [55 , 56] , a disruptive increase in PDK1-PIP3 interaction following treatment with Wortmannin supports our prediction . For completeness , we compared results for our 63 hits from the validation set to those produced by available structure and ligand-based methods . HTDocking ( HTD ) [57] is a structure-based target prediction method that docks and scores the input compound against a manually curated set of 607 human protein structures . For comparison , in our analysis we were able to extract high-quality domain structures for 1245 ( 40% ) of the 3104 potential gene targets . PharmMapper ( PHM ) [58] is a ligand-based approach that screens the input compound against pharmacophore models generated from publicly available bound drug-target cocrystal structures of 459 human proteins , and then ranks potential targets by the degree to which the input compound matches the binding mode of the cocrystalized ligands . The scope of HTD is limited by the availability of the target structure , while PHM is limited by chemical and structural similarity of active ligands . HTD and PHM rankings for known targets are shown in Table 3 , and complete results are shown in S3 Text . Our combined genomics-structure method outperforms the structure-based HTD server ( average ranking of the known target is 13 for our method vs . 50 for the HTD server ) . This observation suggests that limiting the structural screening to our genomic hits allowed us to predict targets with higher accuracy than docking alone . Results when using the PHM server are on average similar to ours . However , PHM relies on the availability of ligand-bound crystal structures , which in practice makes this class of methods more suitable for drug repurposing than assessing new chemistries or targets . Finally , we emphasize that alternative approaches failed to predict compound interactions with HRAS , KRAS , and CHIP that were verified—albeit with low potency—in our assays . However , a Wortmannin-PDK1 interaction was predicted at the catalytic site by HTD , ranked 540th , and by PHM , ranked 56th . Although we cannot rule out a possible kinase domain interaction , a catalytic activity assay showed that Wortmannin had no measureable effect on the in vitro phosphorylation of the substrate T308tide [54] by the isolated catalytic domain of PDK1 ( Fig 7d ) . Overall , the novel drug-protein interaction pipeline outlined in this study can now be significantly improved—with ever-expanding genomic and proteomic databases—to continue to identify new probe compounds for specific protein targets . Even without further optimization , some of these probes can be used to test new hypotheses , as described above . Through medicinal chemistry , other probes can be in turn be optimized to provide more potent effects in cell and in vitro-based systems .
Delineating the role of small molecules in perturbing cellular interaction networks in normal and disease states is an important step towards identifying new therapeutic targets and chemistries for drug development . To advance toward this goal , we developed a novel target prediction method based on the hypothesis that drugs that inhibit a given protein should have similar network-level effects to silencing the inhibited gene and/or its up- or down-stream partners . Using gene expression profiles from KD and drug treatment experiments in multiple cell types from the LINCS L1000 dataset , we developed several correlation-based features and combined them in a RF model to predict drug-target interactions . Notably , the identified candidates validated our hypothesis that drug treatments and target KDs cause similar disruptions of cellular protein networks . More interestingly—and consistent with our hypothesis—we discovered that these correlations occur for KDs of the drug’s actual protein target ( s ) and/or for genes up- or down-stream of the target ( s ) . We refer to the latter as “indirect correlations” . Several aspects of our approach represent a significant step forward from previous work exploring only expression correlations as a means to predict molecular interactions [59 , 60] . In our case , there are no assumptions about the small molecule or its likely protein target/pathway , and our evaluation of both direct and indirect correlations allow us to screen compounds on a much larger scale and with higher accuracy than previously reported . Furthermore , to our knowledge , this is the first time that pathway connectivity is explicitly considered by indirect correlational effects between drugs and KDs of target interaction partners . Importantly , we have also open-sourced our predictions and methods , providing enriched sets of what will undoubtedly lead to active compounds for hundreds of human targets . In more general terms , our approach presents a new avenue for identifying suitable targets for novel chemistries , accelerating the discovery of chemical probes and potentially new drugs . On a validation set of 152 FDA-approved drugs , we achieve top-100 target prediction accuracy more than double that of previous approaches that use differential expression alone [28 , 29] . Consistent with our underlying hypothesis , the RF results highlight the importance of both direct expression signature correlations between drug treatment and KD of the gene target ( Figs 1c , 4a , 4b and 7a ) and indirect correlations between the drug and the target’s interacting partners ( Figs 1e and 6 ) . Contrary to earlier work [27–29] , our method is capable of predicting potential targets for any compound , even those unrelated to known drugs , and as noted above , our predictions are open source and available for immediate download and testing ( http://sb . cs . cmu . edu/Target2/ ) . These include potential targets for 1680 LINCS small molecules from among over 3000 different human proteins . Unlike most available ligand-based prediction methods [12–17] , the accuracy of our approach does not rely on chemical similarity between compounds in the training/test sets . For instance , our screen against CHIP , a target with no known small molecule inhibitors , delivered four out of six binding compounds , whereas a parallel analysis using a state-of-the-art structure-based virtual screening [36 , 61] yielded even weaker-binding compounds . Moreover , the predicted mechanisms of actions of the more potent LINCS compounds suggest novel interactions that were not prioritized by the ligand-based screen ( S7 Fig ) . In contrast to other machine learning methods , our approach reveals important , human-interpretable insights into perturbation-response properties of cellular networks . Direct and indirect gene expression profile correlations inform on global regulatory responses triggered by small molecule cell treatments ( see , e . g . , Figs 4 , 6 and 7 ) . Namely , our genomic screening not only identifies compounds targeting a given protein , but also highlight related genes that are affected by the chemical modulation of the target . This knowledge is bound to play an important role in the design of polypharmacological therapies . Detailed analyses of our predictions suggest several avenues to improve enrichment . First , we established a clear correlation between the number of cell-types screened and the target prediction accuracy . Second , we identified that a significant source of false positives are indirect correlations that , while important to detect the true target , also tend to predict interacting partners as potential targets . Incorporating compound- or target-specific features are also likely to improve our results . For instance , we noticed that our prediction results were less accurate for extracellular and membrane proteins , and incorporating a cellular localization feature into our RF model increased the number of top-100 hits in our validation set from 63 to 66 . Third , we envision that improved KD databases and transcriptomic profiling databases will emerge , as will more entries and higher resolution structures into the PDB , leading to more effective computational strategies . Nevertheless , we are aware that our pipeline currently suffers from several limitations . For example , since the LINCS data is currently based on 978 landmark genes , any correlations that are not reflected by these genes ( which may be identified when using the full list of 20K genes ) will be lost . Moreover , LINCS has only profiled genes in a small number of cell lines . While we try to account for this limitation with special features , some targets are likely missed because of inactivity in these cell lines . As noted above , we expect to improve on many of these issues when new LINCS data are released as this should include more KDs in more cell lines . A more detailed analyses of polypharmacological effects could also improve predictions , and we are aware that this will likely occur , especially when non-optimized compounds are employed in assays , as reported above . In sum , our method represents a novel application of gene expression data for small molecule—protein interaction prediction , with structural analysis further enriching hits to an unprecedented level in a proteome-scale screen . The success of our proof-of-concept experiments opens the door for a compound-centric drug discovery pipeline that can leverage the relatively small fraction of potentially bioactive compounds that could be of interest for further investigation to become drugs [62] . Interestingly , even relatively weak compounds are able to leave a fingerprint in gene expression correlations . Compared to alternative approaches , our method would be particularly suitable for scanning for targets of newly synthesized scaffolds . We are hopeful that our open source method and predictions might be useful to other labs around the world for identifying new drugs for key proteins involved in various diseases and for better understanding the impact of drug modulation of gene expression . Moreover , our approach represents a new framework for extracting robust correlations from intrinsically noisy gene expression data that reflect the underlying connectivity of the cellular interactome .
All predictions and code are open source and available at the supporting website http://sb . cs . cmu . edu/Target2/ . A full description of the data used in our analysis can be found in the S1 Text . Briefly , from the NIH LINCS library we extracted gene expression perturbations on 978 “landmark genes” from thousands of small molecule treatment and gene KD experiments in various cell lines . We then used ChEMBL [63] , an open large-scale bioactivity database , to identify the LINCS compounds that were FDA approved and had known targets . To construct our validation set we selected the 152 FDA approved compounds that had been tested in at least four distinct LINCS cell lines , and whose known targets were knocked down in the same cell lines . Protein-protein interaction data used in feature construction was extracted from BioGRID [32] and HPRD [64] , both of which contain curated sets of physical and genetic interactions . Protein cellular localization data used in feature construction was obtained from the Gene Ontology database [65] . The notation and symbols that we use in constructing and using the genomic features are described in S6 and S7 Tables . Feature construction is summarized below and is explained in detail in the S1 Text . In order to use molecular docking to enrich our random forest predictions , we needed to generate structural models for the genes profiled in LINCS . The union of our top 100 target predictions for the 1680 small molecules profiled in LINCS in at least four cell lines consisted of 3333 unique human genes . We used a python script ( available on https://github . com/npabon/generate_gene_models ) to mine the PDB for structures of these genes and then select representative crystal structures for each . When multiple structures were available , a representative subset of structures were chosen so as to maximize sequence coverage , minimize structural resolution , and account for structural heterogeneity . Full details of this procedure can be found in the S1 Text . Compounds were docked to representative structures of their predicted targets with smina [37] , using default exhaustiveness and a 6 Å buffer to define the box around each potential binding site . Docked poses across predicted binding sites [66] on a given target were compared and the highest scoring pose of each compound was selected for further analyses [36–39] and comparison to other targets/compounds . Full details on all experimental assays involving HRAS , KRAS , CHIP and PDK1 can be found in S1 Text . | Bioactive compounds often disrupt cellular gene expression in ways that are difficult to predict . While the correlation between a cellular response after treatment with a small molecule and the knockdown of its target protein should be simple to establish , in practice this goal has been difficult to achieve . The main challenges are that data are noisy , drugs are not intended to be active in all cell types , and signals from a bona fide target ( s ) may be obscured by correlations with knockdowns of other proteins in the same pathway ( s ) . Here , we find that a random forest classification model can detect meaningful correlational patterns when gene expression profiles after compound treatment and gene knockdowns in four or more cell lines are compared . When this approach is enriched by a structure-based screen , novel drug-target interactions can be predicted . We then validated new ligand-protein interactions for four difficult targets . Although the initial compounds are not especially potent in vitro , they are capable of disrupting their target pathway in the cell to an extent that generates a significant and characteristic gene expression profile . Collectively , our studies provide insight on cell-level transcriptomic responses to pharmaceutical intervention and the use of these patterns for target identification . In addition , the method provides a novel drug discovery pipeline to test chemistries without a priori knowledge of their target ( s ) . | [
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