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Dynamic regulatory network controlling TH17 cell differentiation.

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.

SUBMITTER: Yosef N

PROVIDER: S-EPMC3637864 | biostudies-literature | 2013 Apr

REPOSITORIES: biostudies-literature

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Dynamic regulatory network controlling TH17 cell differentiation.

Yosef Nir N Shalek Alex K AK Gaublomme Jellert T JT Jin Hulin H Lee Youjin Y Awasthi Amit A Wu Chuan C Karwacz Katarzyna K Xiao Sheng S Jorgolli Marsela M Gennert David D Satija Rahul R Shakya Arvind A Lu Diana Y DY Trombetta John J JJ Pillai Meenu R MR Ratcliffe Peter J PJ Coleman Mathew L ML Bix Mark M Tantin Dean D Park Hongkun H Kuchroo Vijay K VK Regev Aviv A

Nature 20130306 7446

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 de ...[more]

PMID: 23467089

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Project description:Accumulating evidence indicates an important role for microRNA (miRNA)-messenger RNA (mRNA) regulatory networks in human depression. However, the mechanisms by which these networks act are complex and remain poorly understood. We used data mining to identify differentially expressed miRNAs from GSE81152 and GSE152267 datasets, and differentially expressed mRNAs were identified from the Netherlands Study of Depression and Anxiety, the GlaxoSmithKline-High-Throughput Disease-specific target Identification Program, and the Janssen-Brain Resource Company study. We constructed a miRNA-mRNA regulatory network based on differentially expressed mRNAs that intersected with target genes of differentially expressed miRNAs, and then performed bioinformatics analysis of the network. The key candidate genes were assessed in the prefrontal cortex of chronic social defeat stress (CSDS) depression mice by quantitative real-time polymerase chain reaction (qRT-PCR). Three differentially expressed miRNAs were commonly identified across the two datasets, and 119 intersecting differentially expressed mRNAs were identified. A miRNA-mRNA regulatory network including these three key differentially expressed miRNAs and 119 intersecting differentially expressed mRNAs was constructed. Functional analysis of the intersecting differentially expressed mRNAs revealed that an abnormal inflammatory response characterized by disturbed T-helper cell 17 (Th17) differentiation was the primary altered biological function. qRT-PCR validated the decreased expression of Th17 cell differentiation-related genes, including interleukin (IL)17A, IL21, IL22, and IL1β, and the increased expression of retinoic acid receptor-related orphan receptor gamma-t (RORγt) in CSDS mice, which showed significant depressive- and anxiety-like behaviors. This study indicates that an abnormal inflammatory response characterized by disturbed Th17 cell differentiation is the primary altered biological process in major depressive disorder. Our findings indicate possible biomarkers and treatment targets and provide novel clues to understand the pathogenesis of major depressive disorder.

Dataset Information

Dynamic regulatory network controlling TH17 cell differentiation.

Publications

Dynamic regulatory network controlling TH17 cell differentiation.

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