Société Française de Bioinformatique

Mots-Clés

single cell RNAsequencing sepsis

Description

Single-cell RNA sequencing of blood antigen-presenting cells in post-septic patients
o Description
Sepsis-induced immunosuppression confers increased susceptibility to secondary pulmonary bacterial infections.
Our main hypothesis, is that Antigen Presenting Cells (APC) subsets are differentially involved in the development and regulation of immune dysfunctions in sepsis. Because of the complexity/multiplicity of APC functions and underlying molecular networks, systems biology approaches are required in order to reach a thorough, systematic and high-resolution characterization of each dendritic cell (DC) and monocyte subset, and optimize the identification of biomarkers and therapeutic targets.
Our objective is to assess high-resolution molecular profiling of sepsis circulating APC subsets using population level and single cell RNAseq.
o Objectives
Cellular composition will be investigated in circulating APCs from septic patients, non-septic patients and healthy donors (n=3 per group). The data are already generated by the host lab. This will be achieved through four specific objectives:
1. Cellular sub-clustering based on differences in marker genes:
We will define which sub-clusters are enriched/reduced following sepsis. Visualization of immune cells sub-clusters associated with the sepsis phenotype.
2. Lineage dedifferentiation trajectory (pseudotime analysis):
Prediction of APC differentiation trajectories with Monocle.
3. Functional enrichment analysis:
DEG and enriched GO functions of upregulated genes in APC sub-clusters.
Pathway activity : AUCell
4. Cell-cell communication analysis:
We will investigate the network of APC interactions using ICELLNET (Vassili Soumelis lab, https://github.com/soumelis-lab/ICELLNET) tool as we already used in a former study (Saichi M, Ladjemi MZ, Korniotis S, et al., Nat Cell Biol. 2021). Dot plots showing ligand-receptor pairs of cytokines (interaction weghts/strenght) between APC sub-clusters will be visualized.