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 : Human Immunodeficiency virus (HIV)
Related people (1)
A computer scientist by training, I am applying this knowledge to solve biological problems and am particularly interested in modelling of biological systems, knowledge inference, ontologies and data visualisation.
AlgorithmicsData VisualizationMetabolomicsModelingPathway AnalysisPhylogeneticsSystems BiologyTool DevelopmentDatabaseProgram developmentScientific computingDatabases and ontologiesApplication of mathematics in sciencesSofware development and engineeringData and text miningEvolutionData integrationGraph theory and analysisWorkflow and pipeline developmentDiscrete and numerical optimization
VirusHuman Immunodeficiency virus (HIV)
- Modeling mitochondrial metabolism dormant Cryptococcus neoformans(Benjamin HOMMEL - Molecular Mycology) - Closed
- Measles virus protein C interplay with cellular apoptotic pathways; applications for cancer treatment(Alice MEIGNIÉ - Viral Genomics and Vaccination) - Closed
- Diffusion des mutations de résistance du VIH : modèles et méthodes d’estimation(Olivier GASCUEL - Evolutionary Bioinformatics) - Closed
Related projects (10)
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.
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.
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.
The objective of this study is to evaluate how the different programming of distinct CD4+ T cell subsets affected their susceptibility to HIV infection and the survival of infected cells. Dr. Saez-Cirion's Team evaluates how the metabolic state of CD4+ T cells and the regulation of cellular factors shape the distribution of the HIV reservoir in distinct CD4+ T cell subset. This project uses new technologies and reagents to analyze cells from uninfected donors, and from HIV patients in acute infection, chronic infection and HIV remission.
Les mutations de résistance aux traitements apparaissent sous l’effet de la sélection. Ces mutations sont transmises, les patients pouvant être infectés par des souches déjà résistantes à certains traitements. Ces mutations posent des problèmes considérables en limitant l’arsenal des traitements disponibles, pour les individus comme pour la population sur le long cours. Dans le cas du VIH, nous avons travaillé sur la transmission de ces mutations au sein de la population anglaise, et montré que la majorité de celles-ci étaient transmises par des patients naïfs ignorant leur infection (Mourad et al. AIDS 2015). La méthode employée était souvent ad-hoc et n’utilisait qu’une partie des données disponibles. L’objectif de ce projet est de mettre en place des modèles rigoureux et des méthodes efficaces d’estimation des paramètres (taux de transmission suivant les caractéristiques du donneur, taux de réversion, etc.).
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.
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.
We previously showed that humanized immune system (HIS) mice generated in Balb/c Rag2-/-γc-/- SIRPNOD (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
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.