Multitrait GWAS to connect disease variants and biological mechanisms.

Genome-wide association studies (GWASs) have uncovered a wealth of associations between common variants and human phenotypes. Here, we present an integrative analysis of GWAS summary statistics from 36 phenotypes to decipher multitrait genetic architecture and its link with biological mechanisms. Our framework incorporates multitrait association mapping along with an investigation of the breakdown of genetic associations into clusters of variants harboring similar multitrait association profiles. Focusing on two subsets of immunity and metabolism phenotypes, we then demonstrate how genetic variants within clusters can be mapped to biological pathways and disease mechanisms. Finally, for the metabolism set, we investigate the link between gene cluster assignment and the success of drug targets in randomized controlled trials.

The oxidative stress response of pathogenic Leptospira is controlled by two peroxide stress regulators which putatively cooperate in controlling virulence.

Pathogenic Leptospira are the causative agents of leptospirosis, the most widespread zoonotic infectious disease. Leptospirosis is a potentially severe and life-threatening emerging disease with highest burden in sub-tropical areas and impoverished populations. Mechanisms allowing pathogenic Leptospira to survive inside a host and induce acute leptospirosis are not fully understood. The ability to resist deadly oxidants produced by the host during infection is pivotal for Leptospira virulence. We have previously shown that genes encoding defenses against oxidants in L. interrogans are repressed by PerRA (encoded by LIMLP_10155), a peroxide stress regulator of the Fur family. In this study, we describe the identification and characterization of another putative PerR-like regulator (LIMLP_05620) in L. interrogans. Protein sequence and phylogenetic analyses indicated that LIMLP_05620 displayed all the canonical PerR amino acid residues and is restricted to pathogenic Leptospira clades. We therefore named this PerR-like regulator PerRB. In L. interrogans, the PerRB regulon is distinct from that of PerRA. While a perRA mutant had a greater tolerance to peroxide, inactivating perRB led to a higher tolerance to superoxide, suggesting that these two regulators have a distinct function in the adaptation of L. interrogans to oxidative stress. The concomitant inactivation of perRA and perRB resulted in a higher tolerance to both peroxide and superoxide and, unlike the single mutants, a double perRAperRB mutant was avirulent. Interestingly, this correlated with major changes in gene and non-coding RNA expression. Notably, several virulence-associated genes (clpB, ligA/B, and lvrAB) were repressed. By obtaining a double mutant in a pathogenic Leptospira strain, our study has uncovered an interplay of two PerRs in the adaptation of Leptospira to oxidative stress with a putative role in virulence and pathogenicity, most likely through the transcriptional control of a complex regulatory network.

SHAMAN: a user-friendly website for metataxonomic analysis from raw reads to statistical analysis.

BACKGROUND: Comparing the composition of microbial communities among groups of interest (e.g., patients vs healthy individuals) is a central aspect in microbiome research. It typically involves sequencing, data processing, statistical analysis and graphical display. Such an analysis is normally obtained by using a set of different applications that require specific expertise for installation, data processing and in some cases, programming skills. RESULTS: Here, we present SHAMAN, an interactive web application we developed in order to facilitate the use of (i) a bioinformatic workflow for metataxonomic analysis, (ii) a reliable statistical modelling and (iii) to provide the largest panel of interactive visualizations among the applications that are currently available. SHAMAN is specifically designed for non-expert users. A strong benefit is to use an integrated version of the different analytic steps underlying a proper metagenomic analysis. The application is freely accessible at http://shaman.pasteur.fr/ , and may also work as a standalone application with a Docker container (aghozlane/shaman), conda and R. The source code is written in R and is available at https://github.com/aghozlane/shaman . Using two different datasets (a mock community sequencing and a published 16S rRNA metagenomic data), we illustrate the strengths of SHAMAN in quickly performing a complete metataxonomic analysis. CONCLUSIONS: With SHAMAN, we aim at providing the scientific community with a platform that simplifies reproducible quantitative analysis of metagenomic data.

Multiple major disease-associated clones of Legionella pneumophila have emerged recently and independently.

Legionella pneumophila is an environmental bacterium and the leading cause of Legionnaires' disease. Just five sequence types (ST), from more than 2000 currently described, cause nearly half of disease cases in northwest Europe. Here, we report the sequence and analyses of 364 L. pneumophila genomes, including 337 from the five disease-associated STs and 27 representative of the species diversity. Phylogenetic analyses revealed that the five STs have independent origins within a highly diverse species. The number of de novo mutations is extremely low with maximum pairwise single-nucleotide polymorphisms (SNPs) ranging from 19 (ST47) to 127 (ST1), which suggests emergences within the last century. Isolates sampled geographically far apart differ by only a few SNPs, demonstrating rapid dissemination. These five STs have been recombining recently, leading to a shared pool of allelic variants potentially contributing to their increased disease propensity. The oldest clone, ST1, has spread globally; between 1940 and 2000, four new clones have emerged in Europe, which show long-distance, rapid dispersal. That a large proportion of clinical cases is caused by recently emerged and internationally dispersed clones, linked by convergent evolution, is surprising for an environmental bacterium traditionally considered to be an opportunistic pathogen. To simultaneously explain recent emergence, rapid spread and increased disease association, we hypothesize that these STs have adapted to new man-made environmental niches, which may be linked by human infection and transmission.

LipL21 lipoprotein binding to peptidoglycan enables Leptospira interrogans to escape NOD1 and NOD2 recognition.

Leptospirosis is a widespread zoonosis, potentially severe in humans, caused by spirochetal bacteria, Leptospira interrogans (L. interrogans). Host defense mechanisms involved in leptospirosis are poorly understood. Recognition of lipopolysaccharide (LPS) and lipoproteins by Toll-Like Receptors (TLR)4 and TLR2 is crucial for clearance of leptospires in mice, yet the role of Nucleotide Oligomerization Domain (NOD)-like receptors (NOD)1 and NOD2, recognizing peptidoglycan (PG) fragments has not previously been examined. Here, we show that pathogenic leptospires escape from NOD1 and NOD2 recognition both in vitro and in vivo, in mice. We found that leptospiral PG is resistant to digestion by certain hydrolases and that a conserved outer membrane lipoprotein of unknown function, LipL21, specific for pathogenic leptospires, is tightly bound to the PG. Leptospiral PG prepared from a mutant not expressing LipL21 (lipl21-) was more readily digested than the parental or complemented strains. Muropeptides released from the PG of the lipl21- mutant, or prepared using a procedure to eliminate the LipL21 protein from the PG of the parental strain, were recognized in vitro by the human NOD1 (hNOD1) and NOD2 (hNOD2) receptors, suggesting that LipL21 protects PG from degradation into muropeptides. LipL21 expressed in E. coli also resulted in impaired PG digestion and NOD signaling. We found that murine NOD1 (mNOD1) did not recognize PG of L. interrogans. This result was confirmed by mass spectrometry showing that leptospiral PG was primarily composed of MurTriDAP, the natural agonist of hNOD1, and contained only trace amounts of the tetra muropeptide, the mNOD1 agonist. Finally, in transgenic mice expressing human NOD1 and deficient for the murine NOD1, we showed enhanced clearance of a lipl21- mutant compared to the complemented strain, or to what was observed in NOD1KO mice, suggesting that LipL21 facilitates escape from immune surveillance in humans. These novel mechanisms allowing L. interrogans to escape recognition by the NOD receptors may be important in circumventing innate host responses.

Impact of lactobacilli on orally acquired listeriosis.

Listeria monocytogenes is a foodborne pathogen that crosses the intestinal barrier and disseminates within the host. Here, we report a unique comprehensive analysis of the impact of two Lactobacillus species, Lactobacillus paracasei CNCM I-3689 and Lactobacillus casei BL23, on L. monocytogenes and orally acquired listeriosis in a gnotobiotic humanized mouse model. We first assessed the effect of treatment with each Lactobacillus on L. monocytogenes counts in host tissues and showed that each decreases L. monocytogenes systemic dissemination in orally inoculated mice. A whole genome intestinal transcriptomic analysis revealed that each Lactobacillus changes expression of a specific subset of genes during infection, with IFN-stimulated genes (ISGs) being the most affected by both lactobacilli. We also examined microRNA (miR) expression and showed that three miRs (miR-192, miR-200b, and miR-215) are repressed during L. monocytogenes infection. Treatment with each Lactobacillus increased miR-192 expression, whereas only L. casei association increased miR-200b and miR-215 expression. Finally, we showed that treatment with each Lactobacillus significantly reshaped the L. monocytogenes transcriptome and up-regulated transcription of L. monocytogenes genes encoding enzymes allowing utilization of intestinal carbon and nitrogen sources in particular genes involved in propanediol and ethanolamine catabolism and cobalamin biosynthesis. Altogether, these data reveal that the modulation of L. monocytogenes infection by treatment with lactobacilli correlates with a decrease in host gene expression, in particular ISGs, miR regulation, and a dramatic reshaping of L. monocytogenes transcriptome.

Revisiting oxygen toxicity: evolution and adaptation to superoxide in a SOD-deficient bacterial pathogen.

Defenses against oxidants are crucial for the virulence of pathogens, with superoxide scavenging enzymes (SOSEs) playing a vital role for most aerobes. However, our knowledge of superoxide adaptation primarily stems from the study of SOSE-encoding bacteria. Here, we investigated the evolution of a naturally SOSE-deficient pathogen ( Leptospira spp.), along with the alternative mechanisms it recruits to combat superoxide stress. We demonstrate that emergence of pathogenic Leptospira correlated with SOD loss, but that a long-lasting adaptation to superoxide remains possible. We reveal that cysteine and leucine biosynthesis are the most induced pathways in response to superoxide and demonstrate the importance of sulfur metabolism in superoxide adaptation in this SOSE-deficient model. We also propose cysteine oxidation as a key mediator of superoxide toxicity in the absence of SOSEs. This study challenges our conventional understanding of the oxygen toxicity theory and proposes a new model of superoxide adaptation through metabolic rewiring in bacteria.

Trait selection strategy in multi-trait GWAS: Boosting SNP discoverability.

Since the first genome-wide association studies (GWASs), thousands of variant-trait associations have been discovered. However, comprehensively mapping the genetic determinant of complex traits through univariate testing can require prohibitive sample sizes. Multi-trait GWAS can circumvent this issue and improve statistical power by leveraging the joint genetic architecture of human phenotypes. Although many methodological hurdles of multi-trait testing have been solved, the strategy to select traits has been overlooked. In this study, we conducted multi-trait GWAS on approximately 20,000 combinations of 72 traits using an omnibus test as implemented in the Joint Analysis of Summary Statistics. We assessed which genetic features of the sets of traits analyzed were associated with an increased detection of variants compared with univariate screening. Several features of the set of traits, including the heritability, the number of traits, and the genetic correlation, drive the multi-trait test gain. Using these features jointly in predictive models captures a large fraction of the power gain of the multi-trait test (Pearson's r between the observed and predicted gain equals 0.43, p < 1.6 × 10-60). Applying an alternative multi-trait approach (Multi-Trait Analysis of GWAS), we identified similar features of interest, but with an overall 70% lower number of new associations. Finally, selecting sets based on our data-driven models systematically outperformed the common strategy of selecting clinically similar traits. This work provides a unique picture of the determinant of multi-trait GWAS statistical power and outlines practical strategies for multi-trait testing.

SynTView - an interactive multi-view genome browser for next-generation comparative microorganism genomics.

BACKGROUND: Dynamic visualisation interfaces are required to explore the multiple microbial genome data now available, especially those obtained by high-throughput sequencing - a.k.a. "Next-Generation Sequencing" (NGS) - technologies; they would also be useful for "standard" annotated genomes whose chromosome organizations may be compared. Although various software systems are available, few offer an optimal combination of feature-rich capabilities, non-static user interfaces and multi-genome data handling. RESULTS: We developed SynTView, a comparative and interactive viewer for microbial genomes, designed to run as either a web-based tool (Flash technology) or a desktop application (AIR environment). The basis of the program is a generic genome browser with sub-maps holding information about genomic objects (annotations). The software is characterised by the presentation of syntenic organisations of microbial genomes and the visualisation of polymorphism data (typically Single Nucleotide Polymorphisms - SNPs) along these genomes; these features are accessible to the user in an integrated way. A variety of specialised views are available and are all dynamically inter-connected (including linear and circular multi-genome representations, dot plots, phylogenetic profiles, SNP density maps, and more). SynTView is not linked to any particular database, allowing the user to plug his own data into the system seamlessly, and use external web services for added functionalities. SynTView has now been used in several genome sequencing projects to help biologists make sense out of huge data sets. CONCLUSIONS: The most important assets of SynTView are: (i) the interactivity due to the Flash technology; (ii) the capabilities for dynamic interaction between many specialised views; and (iii) the flexibility allowing various user data sets to be integrated. It can thus be used to investigate massive amounts of information efficiently at the chromosome level. This innovative approach to data exploration could not be achieved with most existing genome browsers, which are more static and/or do not offer multiple views of multiple genomes. Documentation, tutorials and demonstration sites are available at the URL: http://genopole.pasteur.fr/SynTView.

Comparing methods for constructing and representing human pangenome graphs.

BACKGROUND: As a single reference genome cannot possibly represent all the variation present across human individuals, pangenome graphs have been introduced to incorporate population diversity within a wide range of genomic analyses. Several data structures have been proposed for representing collections of genomes as pangenomes, in particular graphs. RESULTS: In this work, we collect all publicly available high-quality human haplotypes and construct the largest human pangenome graphs to date, incorporating 52 individuals in addition to two synthetic references (CHM13 and GRCh38). We build variation graphs and de Bruijn graphs of this collection using five of the state-of-the-art tools: Bifrost, mdbg, Minigraph, Minigraph-Cactus and pggb. We examine differences in the way each of these tools represents variations between input sequences, both in terms of overall graph structure and representation of specific genetic loci. CONCLUSION: This work sheds light on key differences between pangenome graph representations, informing end-users on how to select the most appropriate graph type for their application.

Yersiniomics, a Multi-Omics Interactive Database for Yersinia Species.

The genus Yersinia includes a large variety of nonpathogenic and life-threatening pathogenic bacteria, which cause a broad spectrum of diseases in humans and animals, such as plague, enteritis, Far East scarlet-like fever (FESLF), and enteric redmouth disease. Like most clinically relevant microorganisms, Yersinia spp. are currently subjected to intense multi-omics investigations whose numbers have increased extensively in recent years, generating massive amounts of data useful for diagnostic and therapeutic developments. The lack of a simple and centralized way to exploit these data led us to design Yersiniomics, a web-based platform allowing straightforward analysis of Yersinia omics data. Yersiniomics contains a curated multi-omics database at its core, gathering 200 genomic, 317 transcriptomic, and 62 proteomic data sets for Yersinia species. It integrates genomic, transcriptomic, and proteomic browsers, a genome viewer, and a heatmap viewer to navigate within genomes and experimental conditions. For streamlined access to structural and functional properties, it directly links each gene to GenBank, the Kyoto Encyclopedia of Genes and Genomes (KEGG), UniProt, InterPro, IntAct, and the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and each experiment to Gene Expression Omnibus (GEO), the European Nucleotide Archive (ENA), or the Proteomics Identifications Database (PRIDE). Yersiniomics provides a powerful tool for microbiologists to assist with investigations ranging from specific gene studies to systems biology studies. IMPORTANCE The expanding genus Yersinia is composed of multiple nonpathogenic species and a few pathogenic species, including the deadly etiologic agent of plague, Yersinia pestis. In 2 decades, the number of genomic, transcriptomic, and proteomic studies on Yersinia grew massively, delivering a wealth of data. We developed Yersiniomics, an interactive web-based platform, to centralize and analyze omics data sets on Yersinia species. The platform allows user-friendly navigation between genomic data, expression data, and experimental conditions. Yersiniomics will be a valuable tool to microbiologists.

Trait selection strategy in multi-trait GWAS: Boosting SNPs discoverability.

Since the first Genome-Wide Association Studies (GWAS), thousands of variant-trait associations have been discovered. However, the sample size required to detect additional variants using standard univariate association screening is increasingly prohibitive. Multi-trait GWAS offers a relevant alternative: it can improve statistical power and lead to new insights about gene function and the joint genetic architecture of human phenotypes. Although many methodological hurdles of multi-trait testing have been discussed, the strategy to select trait, among overwhelming possibilities, has been overlooked. In this study, we conducted extensive multi-trait tests using JASS (Joint Analysis of Summary Statistics) and assessed which genetic features of the analysed sets were associated with an increased detection of variants as compared to univariate screening. Our analyses identified multiple factors associated with the gain in the association detection in multi-trait tests. Together, these factors of the analysed sets are predictive of the gain of the multi-trait test (Pearson's ρ equal to 0.43 between the observed and predicted gain, P < 1.6 × 10-60). Applying an alternative multi-trait approach (MTAG, multi-trait analysis of GWAS), we found that in most scenarios but particularly those with larger numbers of traits, JASS outperformed MTAG. Finally, we benchmark several strategies to select set of traits including the prevalent strategy of selecting clinically similar traits, which systematically underperformed selecting clinically heterogenous traits or selecting sets that issued from our data-driven models. This work provides a unique picture of the determinant of multi-trait GWAS statistical power and outline practical strategies for multi-trait testing.

Climate change and vector-borne diseases: a multi-omics approach of temperature-induced changes in the mosquito.

BACKGROUND: Climate change and globalization contribute to the expansion of mosquito vectors and their associated pathogens. Long spared, temperate regions have had to deal with the emergence of arboviruses traditionally confined to tropical regions. Chikungunya virus (CHIKV) was reported for the first time in Europe in 2007, causing a localized outbreak in Italy, which then recurred repeatedly over the years in other European localities. This raises the question of climate effects, particularly temperature, on the dynamics of vector-borne viruses. The objective of this study is to improve the understanding of the molecular mechanisms set up in the vector in response to temperature. METHODS: We combine three complementary approaches by examining Aedes albopictus mosquito gene expression (transcriptomics), bacterial flora (metagenomics) and CHIKV evolutionary dynamics (genomics) induced by viral infection and temperature changes. RESULTS: We show that temperature alters profoundly mosquito gene expression, bacterial microbiome and viral population diversity. We observe that (i) CHIKV infection upregulated most genes (mainly in immune and stress-related pathways) at 20°C but not at 28°C, (ii) CHIKV infection significantly increased the abundance of Enterobacteriaceae Serratia marcescens at 28°C and (iii) CHIKV evolutionary dynamics were different according to temperature. CONCLUSION: The substantial changes detected in the vectorial system (the vector and its bacterial microbiota, and the arbovirus) lead to temperature-specific adjustments to reach the ultimate goal of arbovirus transmission; at 20°C and 28°C, the Asian tiger mosquito Ae. albopictus was able to transmit CHIKV at the same efficiency. Therefore, CHIKV is likely to continue its expansion in the northern regions and could become a public health problem in more countries than those already affected in Europe.

GenoList: an integrated environment for comparative analysis of microbial genomes.

The multitude of bacterial genome sequences being determined has generated new requirements regarding the development of databases and graphical interfaces: these are needed to organize and retrieve biological information from the comparison of large sets of genomes. GenoList (http://genolist.pasteur.fr/GenoList) is an integrated environment dedicated to querying and analyzing genome data from bacterial species. GenoList inherits from the SubtiList database and web server, the reference data resource for the Bacillus subtilis genome. The data model was extended to hold information about relationships between genomes (e.g. protein families). The web user interface was designed to primarily take into account biologists' needs and modes of operation. Along with standard query and browsing capabilities, comparative genomics facilities are available, including subtractive proteome analysis. One key feature is the integration of the many tools accessible in the environment. As an example, it is straightforward to identify the genes that are specific to a group of bacteria, export them as a tab-separated list, get their protein sequences and run a multiple alignment on a subset of these sequences.

CandidaDB: a multi-genome database for Candida species and related Saccharomycotina.

CandidaDB (http://genodb.pasteur.fr/CandidaDB) was established in 2002 to provide the first genomic database for the human fungal pathogen Candida albicans. The availability of an increasing number of fully or partially completed genome sequences of related fungal species has opened the path for comparative genomics and prompted us to migrate CandidaDB into a multi-genome database. The new version of CandidaDB houses the latest versions of the genomes of C. albicans strains SC5314 and WO-1 along with six genome sequences from species closely related to C. albicans that all belong to the CTG clade of Saccharomycotina-Candida tropicalis, Candida (Clavispora) lusitaniae, Candida (Pichia) guillermondii, Lodderomyces elongisporus, Debaryomyces hansenii, Pichia stipitis-and the reference Saccharomyces cerevisiae genome. CandidaDB includes sequences coding for 54 170 proteins with annotations collected from other databases, enriched with illustrations of structural features and functional domains and data of comparative analyses. In order to take advantage of the integration of multiple genomes in a unique database, new tools using pre-calculated or user-defined comparisons have been implemented that allow rapid access to comparative analysis at the genomic scale.

JASS: command line and web interface for the joint analysis of GWAS results.

Genome-wide association study (GWAS) has been the driving force for identifying association between genetic variants and human phenotypes. Thousands of GWAS summary statistics covering a broad range of human traits and diseases are now publicly available. These GWAS have proven their utility for a range of secondary analyses, including in particular the joint analysis of multiple phenotypes to identify new associated genetic variants. However, although several methods have been proposed, there are very few large-scale applications published so far because of challenges in implementing these methods on real data. Here, we present JASS (Joint Analysis of Summary Statistics), a polyvalent Python package that addresses this need. Our package incorporates recently developed joint tests such as the omnibus approach and various weighted sum of Z-score tests while solving all practical and computational barriers for large-scale multivariate analysis of GWAS summary statistics. This includes data cleaning and harmonization tools, an efficient algorithm for fast derivation of joint statistics, an optimized data management process and a web interface for exploration purposes. Both benchmark analyses and real data applications demonstrated the robustness and strong potential of JASS for the detection of new associated genetic variants. Our package is freely available at https://gitlab.pasteur.fr/statistical-genetics/jass.

Characterization of LE3 and LE4, the only lytic phages known to infect the spirochete Leptospira.

Leptospira is a phylogenetically unique group of bacteria, and includes the causative agents of leptospirosis, the most globally prevalent zoonosis. Bacteriophages in Leptospira are largely unexplored. To date, a genomic sequence is available for only one temperate leptophage called LE1. Here, we sequenced and analysed the first genomes of the lytic phages LE3 and LE4 that can infect the saprophyte Leptospira biflexa using the lipopolysaccharide O-antigen as receptor. Bioinformatics analysis showed that the 48-kb LE3 and LE4 genomes are similar and contain 62% genes whose function cannot be predicted. Mass spectrometry led to the identification of 21 and 23 phage proteins in LE3 and LE4, respectively. However we did not identify significant similarities with other phage genomes. A search for prophages close to LE4 in the Leptospira genomes allowed for the identification of a related plasmid in L. interrogans and a prophage-like region in the draft genome of a clinical isolate of L. mayottensis. Long-read whole genome sequencing of the L. mayottensis revealed that the genome contained a LE4 phage-like circular plasmid. Further isolation and genomic comparison of leptophages should reveal their role in the genetic evolution of Leptospira.

Leishmania Genome Dynamics during Environmental Adaptation Reveal Strain-Specific Differences in Gene Copy Number Variation, Karyotype Instability, and Telomeric Amplification.

Protozoan parasites of the genus Leishmania adapt to environmental change through chromosome and gene copy number variations. Only little is known about external or intrinsic factors that govern Leishmania genomic adaptation. Here, by conducting longitudinal genome analyses of 10 new Leishmania clinical isolates, we uncovered important differences in gene copy number among genetically highly related strains and revealed gain and loss of gene copies as potential drivers of long-term environmental adaptation in the field. In contrast, chromosome rather than gene amplification was associated with short-term environmental adaptation to in vitro culture. Karyotypic solutions were highly reproducible but unique for a given strain, suggesting that chromosome amplification is under positive selection and dependent on species- and strain-specific intrinsic factors. We revealed a progressive increase in read depth towards the chromosome ends for various Leishmania isolates, which may represent a nonclassical mechanism of telomere maintenance that can preserve integrity of chromosome ends during selection for fast in vitro growth. Together our data draw a complex picture of Leishmania genomic adaptation in the field and in culture, which is driven by a combination of intrinsic genetic factors that generate strain-specific phenotypic variations, which are under environmental selection and allow for fitness gain.IMPORTANCE Protozoan parasites of the genus Leishmania cause severe human and veterinary diseases worldwide, termed leishmaniases. A hallmark of Leishmania biology is its capacity to adapt to a variety of unpredictable fluctuations inside its human host, notably pharmacological interventions, thus, causing drug resistance. Here we investigated mechanisms of environmental adaptation using a comparative genomics approach by sequencing 10 new clinical isolates of the L. donovani, L. major, and L. tropica complexes that were sampled across eight distinct geographical regions. Our data provide new evidence that parasites adapt to environmental change in the field and in culture through a combination of chromosome and gene amplification that likely causes phenotypic variation and drives parasite fitness gains in response to environmental constraints. This novel form of gene expression regulation through genomic change compensates for the absence of classical transcriptional control in these early-branching eukaryotes and opens new venues for biomarker discovery.

Listeriomics: an Interactive Web Platform for Systems Biology of Listeria.

As for many model organisms, the amount of Listeria omics data produced has recently increased exponentially. There are now >80 published complete Listeria genomes, around 350 different transcriptomic data sets, and 25 proteomic data sets available. The analysis of these data sets through a systems biology approach and the generation of tools for biologists to browse these various data are a challenge for bioinformaticians. We have developed a web-based platform, named Listeriomics, that integrates different tools for omics data analyses, i.e., (i) an interactive genome viewer to display gene expression arrays, tiling arrays, and sequencing data sets along with proteomics and genomics data sets; (ii) an expression and protein atlas that connects every gene, small RNA, antisense RNA, or protein with the most relevant omics data; (iii) a specific tool for exploring protein conservation through the Listeria phylogenomic tree; and (iv) a coexpression network tool for the discovery of potential new regulations. Our platform integrates all the complete Listeria species genomes, transcriptomes, and proteomes published to date. This website allows navigation among all these data sets with enriched metadata in a user-friendly format and can be used as a central database for systems biology analysis. IMPORTANCE In the last decades, Listeria has become a key model organism for the study of host-pathogen interactions, noncoding RNA regulation, and bacterial adaptation to stress. To study these mechanisms, several genomics, transcriptomics, and proteomics data sets have been produced. We have developed Listeriomics, an interactive web platform to browse and correlate these heterogeneous sources of information. Our website will allow listeriologists and microbiologists to decipher key regulation mechanism by using a systems biology approach.

Species- and Strain-Specific Adaptation of the HSP70 Super Family in Pathogenic Trypanosomatids.

All eukaryotic genomes encode multiple members of the heat shock protein 70 (HSP70) family, which evolved distinctive structural and functional features in response to specific environmental constraints. Phylogenetic analysis of this protein family thus can inform on genetic and molecular mechanisms that drive species-specific environmental adaptation. Here we use the eukaryotic pathogen Leishmania spp. as a model system to investigate the evolution of the HSP70 protein family in an early-branching eukaryote that is prone to gene amplification and adapts to cytotoxic host environments by stress-induced and chaperone-dependent stage differentiation. Combining phylogenetic and comparative analyses of trypanosomatid genomes, draft genome of Paratrypanosoma and recently published genome sequences of 204 L. donovani field isolates, we gained unique insight into the evolutionary dynamics of the Leishmania HSP70 protein family. We provide evidence for (i) significant evolutionary expansion of this protein family in Leishmania through gene amplification and functional specialization of highly conserved canonical HSP70 members, (ii) evolution of trypanosomatid-specific, non-canonical family members that likely gained ATPase-independent functions, and (iii) loss of one atypical HSP70 member in the Trypanosoma genus. Finally, we reveal considerable copy number variation of canonical cytoplasmic HSP70 in highly related L. donovani field isolates, thus identifying this locus as a potential hot spot of environment-genotype interaction. Our data draw a complex picture of the genetic history of HSP70 in trypanosomatids that is driven by the remarkable plasticity of the Leishmania genome to undergo massive intra-chromosomal gene amplification to compensate for the absence of regulated transcriptional control in these parasites.