Société Française de Bioinformatique

Mots-Clés

multi-omics cell phenotyping extracellular vesicles kidney transplantation data integration

Description

Master 2 or Engineering end-of-study internship in bioinformatics/biostatistics

Clinical and molecular multi-omic data integration to define the B regulatory signature and other humoral signatures during kidney allograft transplantation

Supervisors: Pr. Sophie Limou (sophie.limou@ec-nantes.fr) and Dr Sophie Brouard (sophie.brouard@univ-nantes.fr) + Pr Bertrand Michel (LMJL)
Location: Center for Research in Transplantation and Translational Immunology (CR2TI), UMR1064, CHU de Nantes, 30 bd Jean Monnet, Nantes, France.

Background: Kidney transplanted patients with good long-term renal function exhibit a high frequency of B cells with regulatory properties. These B cells inhibit T cell responses through a granzyme B-dependent mechanism. These cells are also found, in smaller proportions, in the peripheral blood of healthy non-transplanted individuals and likely participate in cellular homeostasis. We have shown that these regulatory B cells can proliferate in vitro while retaining their suppressive properties, which opens important therapeutic possibilities. However, these cells are difficult to functionally characterize due to a lack of consensual extracellular markers on their surface. We previously studied their phenotype under physiological and pathological conditions by scRNAseq. We also showed that their regulatory activity is mediated by the secretion of extracellular vesicles (EVs), and characterized the proteome and miRNome of these EVs.
Objective: Our goal is to integrate these multi-modal molecular data using multi-omic methods to link the content and phenotype of these EVs (proteins, miRNAs) to the phenotype and function of regulatory B cells (mRNA). We will conduct this study by comparing healthy volunteers and kidney transplanted patients in different clinical situations of graft rejection, stability and tolerance, the holy grail in organ transplantation. This project will rely on the comparison of several analytical pipelines for integrating multi-omic data (e.g. WGCNA, RGCCA, mixOmics, MOFA) with the statistical support of the LMJL team (B Michel). A secondary objective is to expand this strategy to an additional multiomic data in kidney humoral rejection (the IMoKiT project).

/!\ Important: The position is suitable for bioinformaticians, or data scientists with an interest for the biomedical field (the biological skills can be acquired during the position).

Application: Please send your CV, a cover letter, and a reference contact to the emails listed above.