FOXP3型
效应器
关贸总协定3
生物
转录因子
细胞生物学
白细胞介素2受体
细胞毒性T细胞
T细胞
免疫系统
CD8型
免疫学
体外
遗传学
基因
作者
Andrew G. Levine,Alejandra Mendoza,Saskia Hemmers,Bruno Moltedo,Rachel Niec,Michail Schizas,Beatrice Hoyos,Ekaterina V. Putintseva,Ashutosh Chaudhry,Stanislav Dikiy,Sho Fujisawa,Dmitriy M. Chudakov,Piper M. Treuting,Alexander Y. Rudensky
出处
期刊:Nature
[Nature Portfolio]
日期:2017-06-05
卷期号:546 (7658): 421-425
被引量:376
摘要
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.
科研通智能强力驱动
Strongly Powered by AbleSci AI