Metabolic imprinting of Th17 cells in disease pathogenesis

Autoimmune diseases affect an estimated 3-9% of the population and cause major personal and socio-economic consequences.

IL-17-producing CD4+ T cells (Th17) are recruited to inflamed tissues and involved in autoimmune pathogenesis but were recently also shown to have homeostatic function in tissues. Preliminary data from the outgoing host indicate that Th17 cells are transcriptionally distinct in different tissues. How tissue Th17 cells acquire such specialized characteristics remains elusive.

Based on recent findings from the lab that a metabolic manipulation affects Th17 cells, we hypothesize that metabolic cues from the target tissue dictate Th17 phenotypes. To address this, we will apply scRNAseq and the host lab developed Compass metabolic flux tool in 9 tissues. Hits from this analysis will undergo a novel screening approach, CHIME, to reveal effects on Th17 function.

In autoimmunity, Th17 cells reside within different tissues before migrating to the inflamed tissue. Identifying a tissue metabolic switch for Th17 cell pathogenicity might thus pave the way for novel treatments. To study this, I will use a mouse model for the autoimmune disease multiple sclerosis (MS) for target validation.

During the return phase, the findings will be set into context of tissue niche immunology and human biology.

In healthy versus inflamed human tissue, spatial RNAseq will directly reveal metabolism related differences in a natural tissue niche context. The project will be performed in a world-renowned Th17 lab.

The fellow brings extensive experience with tissue immune cell extractions and MS mouse models, enabling immediate project progression.

The fellow will then bring back novel techniques and experience (scRNAseq, CHIME) to the return host, where she will acquire skills in human tissue niche immunology and spatial RNAseq.

This project will enhance her expertise, research and transferable skills and allow to build a network to follow her goal of becoming an independent PI.