Study of the Th17 differentiation
Study of the Th17 differentiation
Disciplines
Biology (100%)
Keywords
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Th17,
Network Analysis,
Immunology,
Interleukin-17,
T cells,
Bioinformatics
T helper (Th) cells are central to the adaptive immune response by `instructing` diverse effector cells to perform their tasks. Diverse types of Th cells are known to characteristically influence the overall outcome of an immune response. Until recently, the known Th lineages included the Th1, Th2 and various regulatory, Treg, types which all display a remarkable plasticity, as overexpression of certain transcription factors in fully differentiated Th cells of one type can lead to a `reprogramming` to other Th types. The epigenetic mechanisms involved in Th differentiation include chromatin modification, DNA methylation and self-reinforcing transcriptional networks. Recently, interleukin-17 (IL-17) secreting T cells were shown to constitute a separate Th lineage, termed Th17. This cell type has a strong proinflammatory role and is implicated in autoimmune diseases like arthritis, multiple sclerosis, and systemic lupus erythematosus. The cytokines transforming growth factor-beta (TGF-beta) and IL-6 have been shown to be crucial for Th17 differentiation, while single stimulation with TGF-beta leads to the development of Treg cells. Although several factors important for IL-6/TGF-beta signal transduction were shown to be necessary for the development of Th17 cells, the only true Th17 specific transcription factor identified thus far remains RORgammat. In this project we want to elucidate the general transcriptional network structures underlying Th17 differentiation, to study individual components of these, and to identify novel factors important in this process. We will employ a systems biology approach to address these subjects. The transcriptome of T cells stimulated under Th17 differentiating conditions will be analyzed at multiple timepoints by DNA microarray experiments. These data will be integrated with existing information from databases by various clustering algorithms to infer regulatory interactions. Once we have identified novel factors important for Th17 differentiation, these will be tested by in vitro and in vivo experiments.
- Medical Research Council Centre - 100%
- Universität Salzburg - 10%