A defining feature of adaptive immunity is the development of long-lived memory T cells to curtail infection. Recent studies have identified a unique stem-like T-cell subset amongst exhausted CD8-positive T cells in chronic infection1,2,3, but it remains unclear whether CD4-positive T-cell subsets with similar features exist in chronic inflammatory conditions. Amongst helper T cells, TH17 cells have prominent roles in autoimmunity and tissue inflammation and are characterized by inherent plasticity4,5,6,7, although how such plasticity is regulated is poorly understood. Here we demonstrate that TH17 cells in a mouse model of autoimmune disease are functionally and metabolically heterogeneous; they contain a subset with stemness-associated features but lower anabolic metabolism, and a reciprocal subset with higher metabolic activity that supports transdifferentiation into TH1-like cells. These two TH17-cell subsets are defined by selective expression of the transcription factors TCF-1 and T-bet, and by discrete levels of CD27 expression. We also identify signalling via the kinase complex mTORC1 as a central regulator of TH17-cell fate decisions by coordinating metabolic and transcriptional programmes. TH17 cells with disrupted mTORC1 signalling or anabolic metabolism fail to induce autoimmune neuroinflammation or to develop into TH1-like cells, but instead upregulate TCF-1 expression and acquire stemness-associated features. Single-cell RNA sequencing and experimental validation reveal heterogeneity in fate-mapped TH17 cells, and a developmental arrest in the TH1 transdifferentiation trajectory upon loss of mTORC1 activity or metabolic perturbation. Our results establish that the dichotomy of stemness and effector function underlies the heterogeneous TH17 responses and autoimmune pathogenesis, and point to previously unappreciated metabolic control of plasticity in helper T cells.
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Microarray data are available via GEO (https://www.ncbi.nlm.nih.gov/geo/) under accession number GSE107521. ATAC-seq and scRNA-seq data are available via GEO under accession number GSE121599.
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We acknowledge M. Hendren and A. KC for animal work; the Immunology FACS core facility at St Jude Children’s Research Hospital for cell sorting; and N. Chapman and Y. Wang for editing of the manuscript. This work was supported by the National Institutes of Health (NIH; grants AI105887, AI101407, AI131703, CA176624 and NS064599 to H.C.; CA021765 to B.X. and Y.F.) and the National Multiple Sclerosis Society (to H.C.).
P.W.F.K. conceived, designed and performed in vitro and in vivo experiments and bioinformatic analyses, analysed data, and wrote the manuscript. X.C. performed scRNA-seq analysis and developed the latent cellular state analysis (LCA) algorithm. S.A.L., A.A.H. and T.-L.M.N. helped to perform immunological experiments. B.X., Y.C. and Y.F. helped with ATAC-seq analysis. Y.D. and G.N. helped with microarray and scRNA-seq analyses. S.R. performed ChIP assays. W.C., C.R. and J.E. helped with scRNA-seq analyses. K.Y. performed early in vivo studies. P.V. did histopathology analysis. H.C. helped to conceive and design experiments, co-wrote the manuscript, and provided overall direction.
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Cellular & Molecular Immunology (2019)