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
Searched keyword : Single Cell
Related people (1)
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.
ATAC-seqChIP-seqEpigenomicsNon coding RNAPathway AnalysisRNA-seqSingle CellSystems BiologyTool DevelopmentTranscriptomicsData integrationGraph theory and analysisCell biology and developmental biology
Related projects (14)
Controlling virus replication by generating a strong CD8+ T cell response against HIV is one of the major goals in the development of an effective HIV vaccine candidate. Indeed, during the chronic phase of infection, HIV-specific CD8+ T cells were shown to have impaired functionality and fail to control viral replication. Understanding the profile of CD8+ T cells able to efficiently tackle HIV is therefore much needed. HIV controllers (HIC) are individuals who control viremia without antiretroviral therapy. CD8+ T cells seems to play a major role in their HIV control. We hypothesized that HIV-specific CD8+ T cells associated with control of infection bear particular transcriptional signature (cell cycle, survival, activation, cytolytic function…) when compared to HIV-specific CD8+ T cells not associated with control of infection sharing the same memory phenotype.
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.
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.
Development and use of statistical programs to analyze RNA-Seq data produced at the Transcriptome & Epigenome Platform
The Transcriptome & Epigenome Platform is dedicated to the development and use of high throughput approaches for transcriptomics and epigenomics studies. The platform is accessible to any research team from the Pasteur Institute (80% of the projects) as well as from outside. It is involved (most often as collaborator) in several projects funded by the ANR, Microbes and Brain, ERANET and by the Pasteur Institute in the framework of the PTR programs. Next Generation Sequencing (NGS) based on the Illumina technology (HiSeq 2000/2500 sequencers) is used to perform RNA-sequencing experiments for which a large amount of data is generated. After a first step involving bioinformatics, specific statistical methods must be used be analyze rigorously the data. These analyses are most often performed by the statistician(s) of the platform. They are also in charge of bibliographical survey activity.
Detection of nucleic acids at the single cell level using microscopy has now reach high throughput levels which promise exciting discoveries concerning the functionning of the genomes. The HSC3D project funded by the CITECH in the Pasteur institute aims at multiplexing nucleic acid detection by Fluorescence In Situ Hybridisation (FISH). This necessitates libraries in the range of tens of thousands of 100mer DNA oligonucleotides which will be synthesised by digital lithography. Several constrains apply to these oligonucleotides which therefore require heavy duty bioinformatics for their design .
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.
Characterization of the specific TCR repertoire preferentially expressed in spontaneously controlled HIV infection
The rare patients who spontaneously control HIV replication in the absence of therapy show signs of a particularly efficient cellular immune response. To identify the molecular determinants underlying this response, we characterized the TCR repertoire directed at the most immunodominant CD4 epitope in HIV-1 capsid, Gag293. HIV Controllers from the ANRS CO21 CODEX cohort showed a highly skewed TCR repertoire characterized by a predominance of the TRAV24 and TRBV2 variable gene families. Controllers shared public clonotypes at higher frequencies than treated patients, suggesting the implication of particular TCRs in HIV control (Benati D. et al., J Clin Invest 2016). We propose to test the generality of these findings by characterizing the TCRs specific for a series of immunodominant HIV Gag and Env epitopes, and comparing the frequencies of public clonotypes in groups of HIV Controllers and treated patients. We will then assay the functions of the most prevalent public clonotypes through lentivector-based TCR transfer, and correlate the panel of T cell functions to TCR affinity and frequency.
HIV infects and depletes CD4+ T cells, leading to a progressive loss of adaptive immune responses and ultimately to AIDS. In addition, HIV preferentially targets HIV-specific CD4+ T cells, resulting in an attrition of the very cells that should orchestrate the antiviral immune response. Due to this preferential depletion, HIV-specific CD4+ T cells are few and remain incompletely characterized. The emergence of single cell technologies opens the opportunity for an in depth analysis of the rare specific CD4+ T cells that persist in the circulation of chronically infected patients. We have sorted single CD4+ T cells specific for the most immunodominant epitope in HIV-1 capsid, using an optimized MHC class II tetramer labeling protocol. We now propose to analyze these single cells by multiplexed real time PCR in a microfluidics device, to define their transcriptional profile. We will analyze the differentiation status of HIV-specific CD4+ T cells in rare patients who naturally control HIV infection and in progressor patients who control HIV replication due to antiretroviral therapy. This project will help define the parameters of an efficient T cell response against HIV, and may provide insights into the type of responses that should be induced by candidate HIV vaccines.
Quantitatively understanding the stochastic dynamics of gene expression requires measurements at the level of single cells. A common approach to follow the expression of genes in single cells and in real time is to make use of fluorescent reporter proteins and to record the cells' fluorescence by microscopy. However, this provides only an indirect readout of the biological processes that are of interest such as the regulation mechanisms at the promoter. A possible way to uncover the unobservable biological processes is to infer the hidden dynamics from the available data through the use of mechanistic models of gene expression. The goal of this project is to develop methods for state estimation and parameter inference for such models and to test these methods on real data.
Invasion of human intestinal epithelial cells by Shigella flexneri is secondary to the delivery of bacterial effectors into the host cell cytoplasm via a type III secretion system (T3SS). By using a beta-lactamase reporter tool we observed that in contrast to the epithelium, human lymphocytes are mainly targeted by injection of T3SS effectors not resulting in subsequent cell invasion (Pinaud et al., 2017). Furthermore, we observed that the targeting process, in form of successful injection of effectors into the host cell, is dependent on glycan-glycan interactions between bacterial and host cell surfaces rendering the targeting process to be dependent on the activation state of the host cell (Belotserkovsky et al., 2018). CyTOF technology is a research tool used for phenotypic analysis of complex cell population allowing for the simultaneous labelling of up to 40 different surface and intracellular marker without issues of compensation as present in regular flow cytometry (van Unen et al., 2016). Using CyTOF technology and the beta-lactamase reporter tool, we will perform a detailed analysis of Shigella targeting in a complex cell population using human lamina propria mononuclear cells (LPMCs), isolated from human colon explants. Analysis will address the question if specific cellular subsets are preferentially targeted in the intestinal environment and if this differs from targeting of peripheral blood mononuclear cells (PBMCs) diverging in their immune phenotypes and cellular activation.
Erythromyeloid progenitors (EMPs) originate from the yolk sac during early mouse development and migrate to the fetal liver via the circulation where they undergo massive expansion and differentiation
Tissue resident stromal cells form the scaffold of all organs. In addition, they provide signals for proper positioning, survival and interaction of a number of other cell types, such as immune cells.
The development of the mammary gland occurs in five distinct phases: embryogenesis, puberty, pregnancy, lactation, and involution. Due to its extraordinary regenerative capacity, the mammary epitheliu
Stromal cells are essential during organ morphogenesis and for the maintenance of tissue homeostasis. In addition, increasing evidence indicates that stromal cells play a role in certain type of chron