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Adaptive immune responses are tailored to different types of pathogens through differentiation of naive CD4 T cells into functionally distinct subsets of effector T cells (T helper 1 (TH1), TH2, and TH17) defined by expression of the key transcription factors T-bet, GATA3, and RORγt, respectively. Regulatory T (Treg) cells comprise a distinct anti-inflammatory lineage specified by the X-linked transcription factor Foxp3 (refs 2, 3). Paradoxically, some activated Treg cells express the aforementioned effector CD4 T cell transcription factors, which have been suggested to provide Treg cells with enhanced suppressive capacity. Whether expression of these factors in Treg cells-as in effector T cells-is indicative of heterogeneity of functionally discrete and stable differentiation states, or conversely may be readily reversible, is unknown. Here we demonstrate that expression of the TH1-associated transcription factor T-bet in mouse Treg cells, induced at steady state and following infection, gradually becomes highly stable even under non-permissive conditions. Loss of function or elimination of T-bet-expressing Treg cells-but not of T-bet expression in Treg cells-resulted in severe TH1 autoimmunity. Conversely, following depletion of T-bet- Treg cells, the remaining T-bet+ cells specifically inhibited TH1 and CD8 T cell activation consistent with their co-localization with T-bet+ effector T cells. These results suggest that T-bet+ Treg cells have an essential immunosuppressive function and indicate that Treg cell functional heterogeneity is a critical feature of immunological tolerance.
Pubmed ID: 28607488 RIS Download
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Software for single-cell flow cytometry analysis. Its functions include management, display, manipulation, analysis and publication of the data stream produced by flow and mass cytometers.
View all literature mentionsAn Antibody supplier and subset of ThermoFisher Scientific which provides fluorescence reagents for various experiments and methods.
View all literature mentionsSoftware package for differential gene expression analysis based on the negative binomial distribution. Used for analyzing RNA-seq data for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates.
View all literature mentionsMus musculus with name C57BL/6J from IMSR.
View all literature mentionsMus musculus with name B6.129(Cg)-Foxp3tm4(YFP/icre)Ayr/J from IMSR.
View all literature mentionsAllele Detail: Targeted This is a legacy resource.
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