Dynamic regulatory network controlling T[subscript H]17 cell differentiation

Despite their importance, the molecular circuits that control the differentiation of naive T cells remain largely unknown. Recent studies that reconstructed regulatory networks in mammalian cells have focused on short-term responses and relied on perturbation-based approaches that cannot be readily applied to primary T cells. Here we combine transcriptional profiling at high temporal resolution, novel computational algorithms, and innovative nanowire-based perturbation tools to systematically derive and experimentally validate a model of the dynamic regulatory network that controls the differentiation of mouse T[subscript H]17 cells, a proinflammatory T-cell subset that has been implicated in the pathogenesis of multiple autoimmune diseases. The T[subscript H]17 transcriptional network consists of two self-reinforcing, but mutually antagonistic, modules, with 12 novel regulators, the coupled action of which may be essential for maintaining the balance between T[subscript H]17 and other CD4[superscript +] T-cell subsets. Our study identifies and validates 39 regulatory factors, embeds them within a comprehensive temporal network and reveals its organizational principles; it also highlights novel drug targets for controlling T[subscript H]17 cell differentiation.National Human Genome Research Institute (U.S.) (1P50HG006193-01)National Institutes of Health (U.S.). Pioneer Award (DP1OD003958-01)Howard Hughes Medical InstituteKlarman Cell Observator