Expertise

Hub members Have many expertise, covering most of the fields in bioinformatics and biostatistics. You'll find below a non-exhaustive list of these expertise

Search by keywords | Search by organisms

Searched keyword : Human

Related people (6)

Pascal CAMPAGNE

Group : SABER - Hub Core

Initially trained in evolutionary and environmental sciences, I studied population genetics and micro-evolutionary processes in a number of postdoctoral research projects. I recently joined the C3BI-Hub at the Institut Pasteur, where I work on various aspects involving Biostatistics and the analysis of genetic data.


Keywords
Association studiesGenomicsGenotypingBiostatisticsGeneticsEvolutionPopulation genetics
Organisms
BacteriaParasiteHumanInsect or arthropodOther animal
Projects (9)

Etienne KORNOBIS

Group : FUNGEN - Embedded : Epigenetic regulation

After a PhD in Biology in 2011 on population genetics and phylogeography on amazing little amphipods (Crangonyx, Crymostygius) at the University of Reykjavik (Iceland), I pursued my interest in Bioinformatics and Evolutionary Biology in various post-docs in Spain (MNCN Madrid, UB Barcelona). During this time, I investigated transcriptomic landscapes for various non-model species (groups Conus, Junco and Caecilians) using de novo assemblies and participated in the development of TRUFA, a web platform for de novo RNA-seq analysis. In July 2016, I integrated the Revive Consortium and the Epigenetic Regulation unit at Pasteur Institute, where my main focus were transcriptomic and epigenetic analyses on various thematics using short and long reads technologies, with a special interest in alternative splicing events detection. I joined the Bioinformatics and Biostatistics Hub in January 2018. My latest interests are long reads technologies, alternative splicing and achieving reproducibility in Bioinformatics using workflow managers, container technologies and literate programming.


Keywords
Data managementData VisualizationSequence analysisTranscriptomicsWeb developmentGenome analysisProgram developmentExploratory data analysisSofware development and engineeringGeneticsEvolutionRead mappingWorkflow and pipeline developmentPopulation geneticsMotifs and patterns detectionGrid and cloud computing
Organisms
HumanInsect or arthropodOther animalAnopheles gambiae (African malaria mosquito)Mouse
Projects (2)

Rachel LEGENDRE

Group : PLATEFORM - Detached : Biomics

Rachel Legendre is a bioinformatics engineer. She completed her master degree in apprenticeship for two years at INRA in Jouy-en-Josas in the Genetic Animal department. She was involved in a project aiming at the detection and the expression analysis of micro-RNA involved in an equine disease. In 2012, she joined the Genomic, Structure and Translation Team at Paris-Sud (Paris XI) university. She worked principally on Ribosome Profiling data analysis, a new technique that allows to identify the position of the ribosome on the mRNA at the nucleotide level. Since November 2015, she joined the Bioinformatics and Biostatistics HUB at Pasteur Institute and she’s detached to the Biomics Pole in C2RT, where she is in charge of the bioinformatics analyses for transcriptomics and epigenomics projects. She’s also involved in Long Reads (PacBio and Nanopore) developments with other bioinformaticians of Biomics Pole.


Keywords
AlgorithmicsChIP-seqEpigenomicsNon coding RNATranscriptomicsGenome analysisProgram developmentScientific computingSofware development and engineeringIllumina HiSeqRead mappingSequencingWorkflow and pipeline developmentChromatin accessibility assaysPac BioRibosome profiling
Organisms
BacteriaFungiParasiteHumanInsect or arthropodOther animal
Projects (10)

Christophe MALABAT

Group : HEAD - Hub Core

After a PhD in biochemistry of the rapeseed proteins, during which I developed my first automated scripts for handling data processing and analysis, I join Danone research facility center for developing multivariate models for the prediction of milk protein composition using infrared spectrometry.
As I was already developing my own informatics tools, I decided to join the course of informatic for biology of the Institut Pasteur in 2007. At the end of the course I was recruited by the Institute and integrate the unit of “génétique des interactions macromoléculaires” of Alain Jacquier. Within this group, I learn to handle sequencing data and I developed processing and analysis tools using python and R. I also create a genome browser and database system for storing, retrieving and visualizing microarray data. After 8 years within the Alain Jacquier’s lab, I join the Hub of bioinformatics and biostatistics as co-head of the team.


Keywords
ClusteringData managementSequence analysisTranscriptomicsWeb developmentDatabaseGenome analysisProgram developmentScientific computingExploratory data analysisData and text miningIllumina HiSeqRead mappingLIMSIllumina MiSeqHigh Throughput ScreeningMultidimensional data analysisWorkflow and pipeline developmentRibosome profilingMotifs and patterns detection
Organisms

Projects (9)

Violaine SAINT-ANDRÉ

Group : DETACHED - Detached : Labex milieu intérieur

After graduating from Paris VI University with a PhD in Genetics on the “Role of histone protein post-translational modifications in splicing regulation” that I performed in the Epigenetic Regulation unit at the Institut Pasteur, I carried out two post-doctoral experiences. I first worked for three years as a postdoctoral associate of the Whitehead Institute for Biomedical Research/MIT in Cambridge (USA). My main project consisted in the integration of genomic and epigenomic data in order to predict the transcription factors that are potentially at the core of the regulation of the cell-type specific gene expression programs. I then joined the Institut Curie where I deepened my experience in multi-omics data analyses and integration to identify non-coding RNAs involved in cancer progression. I have recently joined the HUB-C3BI of the Institut Pasteur where I am performing high-throughput data integration to better understand biological complexity and contribute to precision medicine development.


Keywords
ATAC-seqChIP-seqEpigenomicsNon coding RNAPathway AnalysisRNA-seqSingle CellSystems BiologyTool DevelopmentTranscriptomicsData integrationGraph theory and analysisCell biology and developmental biology
Organisms
Human
Projects (1)

Related projects (81)

Mapping the cell surface signature of the developing mouse heart

Cell surface protein signatures have been successful to discriminate hematopoietic progenitor populations allowing major advances in understanding blood cell production, to define pathways in hematologic malignancies and to foster new therapeutic approaches. Limited knowledge on the phenotype of cells that participate in heart formation impairs our understanding of progenitors of the cardiac cell lineages and their eventual persistence in the adult organ. As a consequence, therapies to restore heart function after injury have been unsuccessful. A number of membrane proteins have been identified on cardiomyocytes; on cardiac fibroblasts; and on endothelial cells, however a multi-parametric analysis of the phenotype of the different cardiac cell compartments along development is still missing. We combined multi-parametric flow cytometry with transcriptional characterization, based on well-known gene expression patterns, to describe major cardiac cell-subsets. The expression of CD24, CD54, Sca-1 and CD90 allowed defining cardiac populations in the non-hematopoietic and non-endothelial cell fraction by flow cytometry. Transcriptional profiling of the sorted populations enabled the identification of cardiomyocytes, in the CD24+ population, while differential expression of CD54, Sca-1 and CD90 defined four cardiac stromal compartments. The identified subsets exhibited specific distributions in three analyzed regions (atria, auriculo-ventricular junction and ventricles). We have thus identified a panel of surface markers, some of which novel in the cardiac context, that allowed assigning surface signatures to different cellular fractions by their unique transcriptional profiles. This work is the foundation for comprehensive studies on the role of different cell fractions by their unique transcriptional profiles.



Project status : Closed

Characterisation of skeletal muscle stem cell properties in distinct physiological states

Stem cells are defined by their is their capacity for self-renewal and differentiation. Some adult tissues maintain a reservoir of stem cells, that generally reside within specialized microenvironments, known as stem cell niches, that regulate their behaviour. Skeletal muscle stem (satellite) cells are quiescent in homeostatic conditions in adults, and they are activated after muscle injury, when they re-enter the cell cycle, proliferate and differentiate into myoblasts, which will then fuse to form new muscle fibers. Satellite cells express the paired/homeodomain gene Pax7, which plays a critical role in satellite cell maintenance postnatally. Numerous experiments have shown that the skeletal muscle stem cell population is heterogeneous, therefore like many other stem cell systems, characterising the stem cell states is a major objective. In our laboratory, a reversible dormant cell state was identified, correspondent to a Pax7Hi quiescent subpopulation (top 10% of the Pax7-nGFP+ cells isolated from the transgenic mouse model Tg:Pax7-nGFP) with a lower metabolic activity and longer lag for the first cell division compared to Pax7Lo cells [1]. Muscle stem cells that survive for extended periods post-mortem are also dormant, suggesting that this property, in addition to anoxia [2] contributes to their viability. Therefore, different physiological states are associated with distinct cell states of muscle stem cells. Metabolism could play a critical role in dictating whether a cell remains quiescent, proliferates or differentiates. Stem cell metabolic plasticity in homeostasis and differentiation, as well as during cell reprogramming, is well described in different cell systems. However, unanswered questions remain regarding the metabolic regulation of satellite cell biology and skeletal muscle regeneration. In this project, we will investigate the behaviour of muscle stem cells in distinct physiological states, especially post-mortem and aging.



Project status : Closed

Mise a disposition d'un(e) bioinformaticien(ne) du hub pour les analyses bioinformatiques du transcriptome et de l epigenome

La PF Transcriptome et Epigenome développe des projets de séquençage à haut débit (collaboration et service) avec des équipes du Campus. Ceux-ci couvrent l'ensemble des thématiques du campus ainsi qu'une large gamme d'organismes (des virus aux mammifères). La plate-forme exerce des activités de biologie humide (construction des librairies et séquençage) et de biologie sèche (analyse bioinformatiques et statistiques). La personne mise a disposition interagira étroitement avec les autres bioinformaticiens du pôle BioMics et du Hub. Ses activités concerneront notamment: - La participation à la conception et à la mise en place des projets avec les équipes demandeuses, la prise en charge des analyses et le reporting aux utilisateurs - La mise en place d'un workflow d'analyse bioinformatique des données de transcriptome /épigénome en étroite collaboration avec le C3BI, la DSI et les autres bioinformaticiens du pole. Ce workflow permettra le contrôle qualité des données, leur prétraitement, le mapping des séquences sur les génomes/transcriptomes de réference, et le comptage des reads pour les différents éléments de l'annotation - L'adaptation du workflow d'analyse aux questions biologiques et aux organismes étudiés dans le cadre des activités de la PF - L'activité de veille technologique et bibliographique (test et validation de nouveaux outils d'analyse, updates d'outils existants...) - La mise en place et le développement d'outils d'analyse adaptés aux futurs projets de la PF: single cell RNAseq, métatranscriptome, ChIPseq, analyse des isoformes de splicing.. Ceci se fera notamment via la réalisation d'analyses dédiées avec certains utilisateurs. Les outils mis en place et validés dans ce cadre seront ensuite utilisés pour l'ensemble des projets. - L'activité de communication et de formation (participation aux réunions du consortium France Génomique,formation permanente à l' Institut Pasteur… - la participation a d autres projets du Pole BioMics (selon disponibilité) Bernd Jagla, qui était le bioinformaticien de la plateforme a rejoint le Hub au 1er janvier 2016. Rachel Legendre est mise a disposition depuis le 2 novembre 2015 et remplace Bernd Jagla. Je souhaite que Rachel Legendre soit mise à disposition de la plateforme pour une durée d'au moins 2 ans.



Project status : In Progress

A long-term mission for an assigned CIH-embedded bioinformatician to provide bioinformatic support to the CIH community

The Center for Human Immunology (CIH) supports researchers involved in translational research projects by providing access to 16 different cutting edge technologies. Currently, the CIH hosts over 60 scientific projects coming from 8 departments of the Institut Pastuer and 5 external teams. In order to respond to the growing needs of these projects in the area of single cell analysis, the CIH has introduced a significant number of single-cell/single-molecule technologies over the past 2-3 years. These new technologies, such as the Personal Genome Machine (PGM) and Ion Proton sequencers, iSCAN microarray scanner, Nanostring technology for transcriptomics profiling and real-time PCR machine BioMark, give rise to large datasets with high dimensionality. Such trend, in terms of data complexity, is also true for flow cytometry technologies (currently reaching over 20 parameters per cell). The exploration of this data is generally beyond the scope of scientists involved in translational research projects. In order to maximize the research outcomes obtained from the analysis of these rich datasets, and to ensure that the full potential of our technologies can be served to the users of the CIH, we would require a proximity bioinformatics support. A CIH-embedded bioinformatician would: 1) design and implement standard analysis pipelines for each of the data-rich technologies of the CIH; 2) provide regular ‘bioinformatics clinics’ to allow scientists the possibility to customize standard pipelines to their specific needs; 3) run trainings on the ‘R software’ platform and other data analysis tools (such as Qlucore) of interest for the CIH users. The objective would be to empower the users to run exploratory analysis by themselves, and to teach good practices in terms of data management and data analysis.    



Project status : In Progress

secretome analysis of human intestinal cells during shigella invasion



Project status : In Progress

Transcriptional regulation of innate lymphoid cell plasticity versus differentiation

Over the last years, innate lymphoid cells (ILC) have been increasingly investigated. Despite the absence of antigen specific receptors, they belong to the lymphoid lineage and represent important sentinels for tissue homeostasis and inflammation. They contribute to numerous homeostatic and pathophysiological situations via specific cytokine production. ILC are currently divided into three groups based on the expression of specific transcription factors and secretion of cytokines. We focus this study on fetal ILC3 development. We have observed that contrary to lymphocytes, ILC can migrate toward lymphoid organs, tissues and mucosal sites as lymphoid precusors and terminate their developmental program in situ. In the fetal spleen, we observe different stages of ILC3 with precursors that are already RORgt+ but could still give rise to other ILC fate. Hence, these splenic ILC3 precursors were sorted and analyzed by microarrays. The identification of gene expression differences was used to design a single cell transcriptomic assay. The single cell transcriptomic assay is based on this specific selection of primers for transcription factors and cytokine receptors. We evaluate their differential expression in single cells at different stages of their plasticity. The aim is to decipher the progression from an ILC precursor stage to an another in one cell. We are also using the new polaris technology to detect and evaluate at different early timepoints the sequence of molecular events for changing ILC cell fate. In this case, we chose to use the sc RNAseq technology. The single cell transcriptomic will be analyzed and bioinformatic programs will be applied in order to organize the sequential molecular events and to build a hierarchical developmental model in case of ILC cell fate decisions.



Project status : In Progress

Mapping the genomic architecture of human neuroanatomical diversity

Our recent analyses suggest that the genetic determinants of human neuroanatomical diversity are massively polygenic. Like other quantitative traits such as height – but also IQ or ASD risk – neuroanatomical diversity seems to result from the aggregated effect of thousands of frequent variants, each of small effect. GWAS should then require populations of hundreds of thousands of individuals to start to detect the individual variants. GCTA (genomic complex trait analysis) offers an alternative approach to obtain valuable neurogenetic information despite the current impossibility to detect enough individual variants to explaining any substantial part of the variability. We are currently pooling together neuroimaging genomics data from multiple international projects (in particular, IMAGEN, ENIGMA, UK Biobank) to replicate and extend our earlier analyses. We aim to: (1) Compute the amount of variance captured by genome-wide SNPs (SNP-heritability) for the several brain regions: ICV, BV, Hip, Th, Ca, Pa, Pu, Amy and Acc, (2) Compute the matrix of SNP-based genetic correlation among structures, (3) Partition the variance captured by SNPs among structural and functional sets: per chromosome, genic vs non-genic, low/medium/high minor-allele frequency, positive/negative selection, involved or not in neurodevelopment, etc. (4) Compare our results with those obtained using GWAS-based estimations (for example, those used in ENIGMA2). GCTA requires the computation of matrices of genetic relationship among all individuals, and thus, direct access to the genotyping data. Once the matrices are computed, the genotyping data is no longer required, and it is not possible to reconstruct an individual's genome from the matrices. Our analysis of the IMAGEN cohort was based on 1,765 Individuals, which gave us sufficient statistical power (80%) to detect only strong heritabilities (h2~45%), and the estimations had very large standard errors (~20%). A cohort of 4,000 subjects should allow us to decrease the standard error to ~8% (80% power to detect h2=22%), and a cohort of 8,000 subjects should decrease it to ~4% (80% power to detect h2=11%). In this way, we could obtain more accurate estimates, but also detect eventually more subtle effects related to functional genomic partitions.   References Yang et al (2010) Common SNPs explain a large proportion of heritability for human height. Nature Genetics, doi: 10.1038/ng.608 Davies et al (2011) Genome-wide association studies establish that human intelligence is highly heritable and polygenic. Molecular Psychiatry, doi: 10.1038/mp.2011.85 Gaugler et al (2014) Most genetic risk for autism resides with common variation. Nature Genetics, doi: 10.1038/ng.3039 Wood et al (2014) Defining the role of common variation in the genomic and biological architecture of adult human height, doi: 10.1038/ng.3097



Project status : In Progress

JASS: an online tool for the joint analysis of GWAS summary statistics

In recent years, large genome-wide association studies (GWAS) have been successful in identifying thousands of significant genetic associations for multiple traits and diseases1. In the course of this endeavor, sample size has proven to be the key factor for identifying new variants. For example, GWAS of body mass index (BMI), now including up to 350,000 individuals from more than 100 cohorts, have been able to identify genetic variant that explain as low as 0.02% of BMI variance2. While standard approaches for detecting new genetic variants associated with traits and diseases will go on as sample size increases, multivariate analyses have been proposed as an alternative strategy for both improving detection of new variants and exploring the multidimensional components of complex traits and diseases. Intuitively, multivariate analysis can be used to improve detection of variants displaying a pleiotropic effect3 by accumulating moderate evidence of association across multiple traits and diseases. Several recent examples have been published about not only GWAS hit overlap across related traits4, but also of genome-wide shared genetic effect5. Multivariate analyses of GWAS have also proven useful to understand shared genetics between diseases5, and potential causal relationship between phenotypes using Mendelian randomization (MR)6. Importantly, most of existing multivariate methods are based on GWAS summary statistics, while approaches based on individual-level data have been seldom considered because of major practical and ethical issues. In the continuity of ongoing work on multi-phenotype analysis (Aschard et al 20147, Aschard et al 20158), we developed an effective and robust multivariate approach of GWAS summary statistics that addresses the major barriers of existing approaches, i.e. the presence of correlation between studies that would exists when GWAS analyzed share sample9-16. Our approach consists in a robust omnibus multivariate test of GWAS summary statis



Project status : Awaiting Publication

Single cell analysis of HIV-specific CD4+ T cell differentiation



Project status : Awaiting Publication

Genetic profile of patients with dyslexia

Background: Dyslexia is characterized by difficulty with learning to read fluently and with accurate comprehension despite normal intelligence. It affects 5–10% of school-age children. Familial studies repeatedly showed that first-degree relatives of affected individuals have a 30–50% risk of developing the disorder. Twin studies showed that heritability was approximately 50% with a higher concordance rate for monozygotic twins compared to dizygotic twins. Although genetic factors contribute to dyslexia, very little is known on the genes associated with the condition. Preliminary data: Our project consists in the complementary analysis of (i) a cohort of 209 patients with dyslexia, 89 relatives and 95 very well phenotyped controls and (ii) an extended pedigree (Nantaise family) with 12 members diagnosed with dyslexia in three generations. For all the individuals of the project, we genotyped >600K SNPs in order to detect SNP association and copy-number variants (CNVs). For the extended pedigree, we also used linkage analysis and whole genome sequence (WGS). Our preliminary results indicate that a single region on chromosome 7q36 is segregating with dyslexia in the Nantaise family. The region is located within CNTNAP2, a gene previously proposed as a susceptibility gene, but without formal proof of its association. The WGS data of three affected and three unaffected individuals of the pedigree was performed to detect all the variants in the linkage region. Project: We proposed to use this unique resource in France to characterize the genetic profile of patients with dyslexia. We will (i) detect the CNVs present in the patients and (ii) detect the variants in the linkage region.



Project status : In Progress

ModeMood: Modeling Mood Disorders



Project status : Awaiting Publication

Genotype to phenotype analysis of immune responses in chronic inflammatory diseases



Project status : In Progress

DNA encapsulation of human resources for research projects on immune system and inflammatory diseases

Freezing is the most commonly used method for storing DNA extracts. However, that method is non-practical and expensive, since requiring freezers and back-up generators for storage, and specific conditions/reagents for transport. In addition, even when adequate procedures are followed, the frozen extracts integrity might suffer from repeated freeze-thaw cycles or residual microorganism activity. The Institut Pasteur’s ICAReB platform hosts the biological collection related to the CoSImmGEn cohorts (Cohort and Collection to Study the Immune System with its Genetic and Environmental determinants) since 2011 (see related team publication 1). Those cohorts have been designed for providing large, duly annotated, qualified blood-derived bio-resources such as blood peripheral mononuclear cells, DNA and RNA from healthy subjects or cases suffering from diseases such as Hidradenitis Suppurativa to support genetic studies linked to the immune system (see related team publication 2 et 3). To provide over the long term genomic DNA for any kind of future genetic studies searching for immune system etio-pathogenesis, the ICAReB platform has used a newly developed DNAshells® (Imagene) which ensure nondestructive, reliable and long-term stability of DNA at low-cost (Clermont et coll, Biopreserv Biobank, 2014). That technology involves encapsulation of the genomic material such that it can be stored dry at room temperature, in small, watertight, oxidation-proof metal capsules. The first aim of the present project is to determine if SNP genotyping allows the detection of DNA damage during storage in various conditions. The second aim of the project is to demonstrate that encapsulation allows an optimal storage of human blood derived DNA at room temperature.



Project status : Closed

Insight into the Immune System: A bioresource and data-sharing platform to study chronic inflammatory diseases (IsIShare)

Chronic inflammatory systemic diseases (CIDs) are a burden to humans because of life-long debilitating illness, increased mortality and high therapy costs. CIDs’ increasing prevalence in western countries has indeed placed them at the third rank of morbi-mortality causes. Unfortunately, available treatments are poorly targeted and non-curative. That is partly linked to a complex and largely ununderstood pathophysiology. Genetic susceptibility clearly plays a role. Genes linked to the immune system have been identified, but causal genes remain mostly unknown and other factors such as intestinal microbiota have also been implicated. The complexity of CIDs’ pathophysiology suggests that a holistic approach is the most susceptible to help make significant progress. Our project intends to take advantage of recent technical progress and development of informatics tools to set up a transversal approach. High-resolution sequencing technology indeed quickly produces large amounts of accurate data. Besides, new integrative informatics tools allowing storage and integrative analysis of this resulting high amount of data are now available. We intend to set-up a CID’s network allowing the gathering and extensive analysis of data related to immuno-genetic determinants, immune repertoire and microbiota from individuals suffering from one of the three major interlinked CIDs, namely Hidradenitis Suppurativa (HS), Crohn’s disease (CD) and Spondyloarthropathy (SpA) as compared to healthy volunteers.



Project status : Closed

Identification of the mouse and/or rat orthologues of the human gene ANOS1, responsible for the X-chromosome-linked form of Kallmann syndrome



Project status : In Progress

MOODel: Modeling Mood Disorders

Mood disorders such as bipolar and major depressive illnesses are among the most severe psychiatric disorders. They have high prevalence and chronic course, and are associated with significant mental and somatic comorbidities and high personal and societal costs (lost productivity and increased medical expenses). Patients with bipolar disorder (BD), for example, exhibit a reduced lifespan compared with the general population, a finding that cannot only be explained by high suicide risk, reduced access to medical care and lifestyle factors. However, the pathophysiological mechanisms of BD are poorly understood, and patients often have incomplete treatment response. Advanced mathematical approaches such as machine learning techniques are increasingly being used to generate predictions based on complex data, and it has been successfully used to detect a number of clinical outcomes and to predict behaviours. In combination with mobile technologies (e.g. smartphones, wearables) to collect behavioural, physiological and environmental data, these big data predictive approaches may provide a much richer and deeper understanding of phenomenology and pathophysiological mechanisms of mood and bipolar disorders. By taking advantage of the high-standard bioinformatics expertise offered by the C3BI, this multidisciplinary, collaborative project aims to explore how clinical and biological factors, may contribute for better characterizing BD patients as well as to identify predictors of treatment response in BD. Our project also aims to explore how daily behavioural and physiological parameters may influence mood and behaviour in individuals at-risk or suffering from mood disorders.



Project status : In Progress

Exploring immunological mechanisms of human graft-verus-host disease after hematopoietic stem cell transplantation

Hematopoietic stem cell transplantation (HSCT) is a curative treatment for many hematologic malignancies. The main therapeutic benefit derives both from the ability to treat patients with intensive chemotherapy and from a potent graft-versus-leukemia (GVL) effect mediated by donor T lymphocytes. Unfortunately, in some patients, donor T cells also attack host normal tissues, giving rise to graft-versus-host disease (GVHD). GVHD prevalence is between 40-80% depending on patient and transplantation characteristics and GVHD remains the main cause of non-relapse morbidity and mortality. Despite the advances in the field of HSCT and GVHD prophylaxis, disease processes in humans remain poorly understood, and the lack of biomarkers for the early diagnosis and prognosis of GVHD contributes to the high mortality of the disease. The objective of the study is to investigate the cellular and molecular mechanisms involved in the immune reconstitution after transplantation and to explore the mechanisms of acute GVHD. For three independent cohorts of donor-recipient pairs, blood samples were collected from the all the donors before transplantation and for the respective recipients either at GVHD onset or at the Day 30 or Day 90 for recipients that did not develop GVHD. Donors and recipients’ samples were analyzed using different approaches: spectral flow cytometry to investigate the cellular correlates of immune reconstitution after HSCT and of GVHD onset, gene expression analysis by NanoString technology to assess the molecular profile of immune cell populations important for GVHD development (CD4+ T cells, CD8+ T cells, NK cells and monocytes) as well as a metabolomics profiling of serum samples using mass spectrometry.



Project status : Closed

Regulation of HIV replication by cellular DNA topology

HIV-1 replication requires the integration of the viral genome into the cell genome. A viral-encoded enzyme, integrase (IN), performs this critical step of infection and is a promising target for anti-viral therapeutics. If the catalytic properties of INs are well characterized, the mechanisms responsible for their site selectivity are still under investigation. Several cellular proteins, such as the LEDFGF/p75 transcription regulator, the RNA polymerase II machinery, nuclear pore proteins and specific modified histones have been proposed to be involved in IN selectivity at a genomic level. In addition, structural parameters of the target DNA helix (curvature, flexibility and topology) are proposed to regulate IN selectivity at a local level. Our team is studying the role and molecular mechanisms associated with these various parameters (Botbol et al., 2008; Lesbats et al., 2011; Morchikh et al., 2013; Benleulmi et al., 2015; Naughtin et al.,). This project aims to define the role of cellular DNA topology during HIV-1 integration. We will first compare already mapped integration sites and superhelicity profiles and search for possible correlations between these two parameters. We will then modify topoisomerases activity in infected cells and study the consequences on viral replication and integration. Finally, we will study in vitro, the direct effects on integration of two parameters of DNA topology, the twist and writhe of the DNA helix. This project relies on complementary in vivo, in vitro and in silico approaches. Bio-informatics tools are crucial for the correlative and statistical analyses of integration sites and superhelicity maps.



Project status : Declined

Identification of new cellular parameters involved in HIV-1 integration selectivity

HIV-1 replication requires the integration of the viral genome into the cell genome. A viral-encoded enzyme, integrase (IN), performs this critical step of infection and is a promising target for anti-viral therapeutics. If the catalytic properties of INs are well characterized, the mechanisms responsible for their site selectivity are still under investigation. Several cellular proteins, such as the LEDFGF/p75 transcription co-activator, the RNA polymerase II machinery, nuclear pore proteins and specific modified histones have been proposed to be involved in IN selectivity at a genomic level but the underlying molecular mechanisms remain to be demonstrated. In addition, structural parameters of the target DNA helix (curvature, flexibility, topology) are proposed to regulate IN selectivity at a local level. Our aims are to study the role of these different parameters of IN selectivity, using both in vitro and in vivo approaches. In vitro, we will map integration sites on various target DNA substrates (naked DNA or chromatin, minicircles, plasmids with different topologies, transcribed templates) and will test the effect of purified proteins suspected to regulate IN selectivity. In vivo, integration sites will be mapped in cells depleted of these suspected regulators or in cells incubated with drugs targeting enzymes involved in transcription, DNA topology or histone modifications. Integration sites will be mapped using published or “home-made” protocols and the sites will be compared with DNA structural parameters, nucleosome positions, histone modifications or transcriptional parameters (published maps). Bio-informatics tools are crucial for these correlative and statistical analyses of integration sites. Our project relies on complementary in vivo, in vitro and in silico approaches. It should establish molecular and mechanistic rules of HIV-1 integration selectivity that could serve in the development of new antiviral strategies and of safer gene therapy vectors.



Project status : Closed

IgBlast on Galaxy

We would like to be able to use IgBlast on the Galaxy platform. We are studying B cells in adaptive immune response, and are particularly interested in the antibodies termed as broadly neutralizing antibodies (bNAbs). By definition, these antibodies can neutralize most known HIV-1 strains, and are produced by rare infected individuals several years post-infection. We are currently investigating the bNabs immunoglobulin repertoire by focusing our NGS (454 pyrosequencing) analysis on  immunoglobulin sequences (V-domains) from HIV-infected patients who developed bNAbs. As immunoglobulin sequences result from the combinatorial rearrangement of 3 gene segments : V , (D) and J gene segments, we need a specific tool to analyze these sequences. Indentifying the germline genes which are involved in the rearrangment is an essential step. Two main tools are being widely used to analyze Immunoglobulins: IMGT and IgBlast. IgBlast has several advantages; it is based on BLAST (it is then possible for the user to build his own database), open source, can use protein or nucleotide sequences as input, and most of all, IgBlast is already installed on the Institut Pasteur's cluster as well as the germline genes database. As it would be very convenient for us to use the bic cluster and galaxy platform to run our analyzes, we would be grateful if IgBlast could be implemented in the Pasteur Galaxy Platform. In this regard, we are of course fully disposed to help in any ways. We also believe that it would be very useful to people working on immunoglobulin sequences in the immunology department by building specific pipelines. Thank you very much.



Project status : Closed

Regulation of HIV-1 integration selectivity by chromatin

Integration of the viral reverse-transcribed genome into the genome of infected cells is an essential step of retroviral replication and is performed by a viral-encoded enzyme, named integrase (IN). In the case of HIV-1, IN is a new and efficient anti-viral target. The selectivity of this enzyme for its cellular genomic sites is also a major parameter of HIV replication and is regulated by several cellular parameters. One of them is chromatin, and different levels of this nucleoprotein complex are involved in the regulation of IN selectivity. Using in vitro integration assays, established by our team and collaborators, we have studied this regulation at two levels of chromatin architecture: large poly-nucleosome templates (Botbol et al., 2008; Lesbats et al., 2011; Benleulmi et al., 2015; Naughtin et al., 2015) or nucleosome-induced DNA curvature mimicked by DNA minicircles (Pasi et al., 2016). Our present project is to study IN selectivity into mononucleosomes (MN). These MNs will be used as target substrates of integration and the role of MN structure, histone modifications and IN cofactors will be studied. Results obtained in vitro, will be confronted to structural data obtained by molecular modeling and to integration sites observed in infected cells. This project will benefit from our expertise in integration in chromatin templates and a previous collaboration with the C3BI on the analysis of integration sites (Pasi, M., Mornico, D., S. Volant, S., et al., 2016). This project is funded by the ANRS.



Project status : In Progress

Utilize mouse models to study infection by HIV-1

We previously showed that humanized immune system (HIS) mice generated in Balb/c Rag2-/-γc-/- SIRPNOD (BRGS) recipients are susceptible to HIV-1 infection (X4 and R5 isolates) and maintain circulating HIV-1 in the plasma, resulting in a dramatic depletion of human CD4+ T cells. We also characterized features of HIV physiopathology in this model. Human thymocyte subsets developing in the thymus of HIS mice appear phenotypically normal, but in the periphery the T cell repertoire is restricted compared with that of human peripheral blood T cells. This negatively impacts on the ability of HIS mice to generate antigen-specific human immune responses when mice are vaccinated with protein antigens or following infection with lymphotropic viruses such as HIV. One likely explanation for these functional deficiencies involves the fact that human T cells are selected intrathymically by mouse MHC molecules and that naïve T cells in peripheral lymphoid organs interact primarily with mouse DC (as human DC development in HIS mice is limited). As a first line of improvement, we recently generated a novel mouse model by crossing our BRGS mice with the HLA-A*02-HHD class I transgenic mice and the HLA-DRB1*15 class II transgenic mice, resulting in BRGS-A2DR2 mice. Following intra-hepatic injection of these mice with MHC-matched CD34+ stem cells we observed increased engraftment, with faster kinetics. Moreover BRGS-A2DR2 HIS mice have an increased T cell development leading to a more equilibrated B/T and CD4/CD8 phenotype. We showed that BRGS-A2DR2 HIS mice were able to sustain replication of HIV R5 virus as the BRGS hosts. Viremia was similar in a first phase and then lower in a second phase in BRGS-A2DR2 compared to BRGS HIS mice, which could be a consequence of a better quality of the immune response. However, the viremia reached a similar plateau in the last phase. We propose to study the impact of the immune res



Project status : Awaiting Publication

Single cell analysis of HIV-specific CD4+ T cell differentiation



Project status : Awaiting Publication

Study of the early pathogenesis during Lassa fever in cynomolgus monkeys and its correlation with the outcome

Because of their increasing incidence, dramatic severity, lack of treatment or vaccine, complicated diagnosis, misreading of the pathogenesis, and need for a maximum containment, Viral Hemorrhagic Fevers (VHF) constitute a major public health problem. There is therefore an urgent need to further study VHF to understand the pathogenesis of the severe disease and the host responses involved in their control or in the dramatic damages. Among VHF, Lassa fever (LF) is probably the most worrying one because of its endemicity and the large number of cases. LF is caused by the Old-World arenavirus Lassa virus (LASV). It is endemic to West Africa and is responsible for 300,000 cases and 5,000 to 6,000 deaths each year. We propose here to study the pathogenesis of VHF by using LF in cynomolgus monkeys as a paradigm, with a particular emphasis on the very early events. The viral tropism, pathophysiological mechanisms, and immune responses will be studied during the course of infection, including the incubation period. Powerful approaches will be used to (1) identify early biological markers of infection, to be able to confirm infection and isolate patients; (2) determine the viral tropism and dynamics during the course of infection to understand the natural history of virus into its host. (3) characterize the early pathogenic events that lead to the severe hemorrhagic syndrome to fully understand the pathophysiogenesis of VHF and identify new therapeutic targets. (4) identify the immune responses involved in the control of infection or in the fatal outcome, to reveal the involvement of immunopathological mechanisms and help to design a vaccine approach. This ambitious and unprecedented project will allow to develop therapeutic and prophylactic approaches but also to identify early biological markers of infection and improve the early diagnosis to optimize the management of outbreaks in the field and increase the survival rate in patients.



Project status : In Progress