Dynamic regulatory network controlling TH17 cell differentiation
Research output: Contribution to journal › Article › peer-review
Authors
Colleges, School and Institutes
Abstract
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 TH17 cells, a proinflammatory T-cell subset that has been implicated in the pathogenesis of multiple autoimmune diseases. The TH17 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 TH17 and other CD4(+) 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 TH17 cell differentiation.
Details
Original language | English |
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Pages (from-to) | 461-8 |
Number of pages | 8 |
Journal | Nature |
Volume | 496 |
Issue number | 7446 |
Publication status | Published - 25 Apr 2013 |
Keywords
- Animals, Antigens, CD95, Cell Differentiation, Cells, Cultured, DNA, Forkhead Transcription Factors, Gene Knockdown Techniques, Gene Regulatory Networks, Genome, Interferon-gamma, Interleukin-2, Mice, Mice, Inbred C57BL, Nanowires, Neoplasm Proteins, Nuclear Proteins, RNA, Messenger, Reproducibility of Results, Silicon, Th17 Cells, Time Factors, Trans-Activators, Transcription Factors, Transcription, Genetic