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Computational Biologist position @ the Imagine single-cell platform
Publish at 18.11.2019
In our lab, we are proposing to combine state of the art single-cell transcriptomic and chromatin accessibility experiments with new powerful computational biology tools, as a novel and an unbiased way to explore the complexity of innate immune response and autoinflammation. The idea is to use the emerging field of transcriptome-based network inference analysis to get a deeper and unbiased understanding of the diversity of the molecular mechanisms behind autoinflammatory diseases.
The fine-tuned analysis and detailed characterization of regulatory networks controlling inflammation will be a major step forward to replace costly life-long immunosuppressive treatments by more definite cures, with hopefully less side effects. It should provide the molecular biology field with a weighted map of potential interactions that can be used to select precisely and prioritize factors to further characterize and decipher the complexity of a particular process, in our case dysregulation of inflammation. In order to make autoinflammatory diseases amenable to network inference, we are proposing to perform RNA sequencing experiments at the single-cell level, where the transcriptome of two different cells is different enough that every cell analyzed can now be considered as an individual sample.
A cell-intrinsic sensor for HIV-1, cGAS, has the potential to activate the type I interferon response to reverse-transcribed viral DNA in DCs, but is not typically engaged owing to a block in reverse transcription mediated by the host dNTP hydrolase SAMHD1. It has been found that HIV-1 infects DCs, if the cells are first exposed to virus-like particles (VLPs) that deliver the protein Vpx (absent in HIV-1 but encoded by SIV and HIV-2). By promoting degradation of SAMHD1, Vpx enables HIV replication in DCs, sensing by cGAS and subsequent type I IFN production.
To characterize the regulatory network controlling host transcriptional responses to HIV-1, in collaboration, with members of Richard Bonneau’s laboratory at the Simons foundation and other colleagues, we have inferred a dynamic computational model that describes the molecular-level regulation of transcriptional responses following HIV-1 infection in human dendritic cells. We used the power of machine learning algorithms (Inferelator ref )combined with the generation of “Big data” (Whole transcriptomic (Bulk RNA-seq) and chromatin accessibility changes (ATAC-seq) to better understand how HIV-1 is sensed by human dendritic cells (DCs) and how this sensing by the innate immune system leads to type I IFN production, DCs maturation and to a potential adaptive immune response against the virus. By integrating genome-wide chromatin accessibility with expression kinetics, we inferred a gene regulatory network that links 542 transcription factors with 21,862 target genes. We observed that an interferon response is required, yet insufficient to drive DC maturation. Among the unexpected TFs predicted to play a role during DC maturation, we validated the role of Retinoic Acid Receptor Alpha (RARA), which acts as a steady state transcriptional repressor of DC maturation. We also identified existing drug agonists of RARA that potentiate DC activation in response to HIV infection.
This network highlights how the innate response depends on the coordinated action of multiple TFs and provides a resource for interrogation of key pathways that regulate HIV replication and innate immunity. (ref paper)
With this dynamic modelization of Transcription factors-genes interaction, we have now a great tool to generate new hypotheses that will then need to be experimentally validated to better understand HIV replication, sensing, type I IFN production and Dendritic cell maturation in response to HIV infection.
DCs express cell surface receptors for HIV-1 entry but are relatively resistant to productive viral replication. They do, however, capture the virus and transfer it to co-cultured T-helper cells, without first being infected, in a process called trans-infection. Taking advantage of this DC to T-cell transfer mechanism, the virus could evade, at least in part, the first line of defense of the immune system in mucosal tissues and establish and amplify infection of CD4+ T cells in lymph nodes, with minimal detection by the immune system.
To better understand this cellular biological process, we have set up and performed an shRNA screen in primary human monocytes derived dendritic cells (MDDCs) to individually knockdown close to 500 genes involved in membrane and vesicular trafficking and compare their efficiency of HIV-1 transfer. We identified several genes and pathways, among which TSPAN7 and DNM2. These two proteins control actin nucleation and stabilization, a process required to maintain HIV-1 on actin-rich dendrites in order to be efficiently transferred toward CD4+ T cells. Beyond these two molecules, this work showed the key role played by actin nucleation in dendritic cells in limiting internalization of HIV-1 and membrane protrusion formation. We also discovered as reported in other biological systems, e.g. the neuronal growth cone, that in MDDCs, opposing forces control the formation and rapid switch between actin-rich dendrites (Actin-nucleation-driven) and blebs (Actomyosin contraction-driven).
Our genetic approach was a first step toward a better understanding of the molecular and cell biological aspects of HIV-1 transmission between DCs and T lymphocytes, which is needed to evaluate the importance of this process in animal models and, eventually, in infected individuals.
-> HIV-1 as a model of study for transfer of pathogens from DCs to T lymphocytes
chef d'équipe
Postdoctoral fellow
Study Engineer
M2 student
PhD student
PhD student
J. Bone Miner. Res. 2020
Fgfr3 Is a Positive Regulator of Osteoblast Expansion and Differentiation Dur...
Front Cell Infect Microbiol
Dendritic Cell Maturation Regulates TSPAN7 Function in HIV-1 Transfer to CD4+...
Biochem. Soc. Trans. 2017
TSPAN7, effector of actin nucleation required for dendritic cell-mediated tra...
Med Sci (Paris) 2016
[Actin nucleation and HIV transfer from dendritic cells to T lymphocytes].
Accélérer la recherche
Computational Biologist position @ the Imagine single-cell platform
Research Acceleration
COVID-19: To uncover a signature of patients at risk of developing a severe form of the disease
26/06/2019
Imagine Institute
The ANR announces the renewal of Imagine Institute’s IHU (University Hospital Institute) status
26/11/2019