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PTEN directs developmental and metabolic signaling for innate-like T cell fate and tissue homeostasis

Abstract

Phosphatase and tensin homologue (PTEN) is frequently mutated in human cancer, but its roles in lymphopoiesis and tissue homeostasis remain poorly defined. Here we show that PTEN orchestrates a two-step developmental process linking antigen receptor and IL-23–Stat3 signalling to type-17 innate-like T cell generation. Loss of PTEN leads to pronounced accumulation of mature IL-17-producing innate-like T cells in the thymus. IL-23 is essential for their accumulation, and ablation of IL-23 or IL-17 signalling rectifies the reduced survival of female PTEN-haploinsufficient mice that model human patients with PTEN mutations. Single-cell transcriptome and network analyses revealed the dynamic regulation of PTEN, mTOR and metabolic activities that accompanied type-17 cell programming. Furthermore, deletion of mTORC1 or mTORC2 blocks PTEN loss-driven type-17 cell accumulation, and this is further shaped by the Foxo1 and Stat3 pathways. Collectively, our study establishes developmental and metabolic signalling networks underpinning type-17 cell fate decisions and their functional effects at coordinating PTEN-dependent tissue homeostasis.

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Fig. 1: PTEN deficiency enhances IL-17-producing cells in the thymus and type-17 programming in post-selection DP thymocytes.
Fig. 2: Loss of PTEN enhances IL-23-dependent development of IL-17-producing cells in the thymus, which contributes to the fatality of female PTEN-haploinsufficient mice.
Fig. 3: PTEN-deficient IL-17-producing T cells are heterogenous and less proliferative.
Fig. 4: PTEN plays a cell-intrinsic role for the development of IL-17-producing thymocytes with TCR and transcriptional diversity.
Fig. 5: PTEN interplays with cellular metabolism and depends on mTORC1 and mTORC2 signalling to shape type-17 programming.
Fig. 6: Foxo1 and IL-23–Stat3 signalling reciprocally orchestrate type-17 innate-like cell development.

Data availability

The authors declare that the data supporting the findings of this study are available within the paper and its Supplementary Information. All microarray, scRNA-seq and single-cell TCR-sequencing data described in the manuscript have been deposited in the NCBI GEO database and are accessible through the GEO SuperSeries accession number GSE179512. Public data analysed in this manuscript are also available under the GEO accession codes GSE27241 (ref. 22), GSE15907 (ref. 37) and GSE137350 (ref. 56), or the European Bioinformatics Institute (EMBL-EBI) accession codes E-MTAB-7702 (ref. 38) and E-MTAB-7704 (ref. 38). Publicly available databases used in this study are available at the indicated locations: mSigDB Collections (for Hallmark, CP: Canonical, C5: GO:BP and C7: Immunological databases), http://www.gsea-msigdb.org/gsea/msigdb/collections.jsp; human transcription-factor database, http://humantfs.ccbr.utoronto.ca/; transcription regulator activity database GO:0140110; and mm10 from ENSEMBL GRCm38, https://www.ncbi.nlm.nih.gov/data-hub/genome/GCF_000001635.20/. Source data are provided with this paper. All other data supporting the findings of this study are available from the corresponding authors on reasonable request.

Code availability

Custom R scripts used for the analysis of bulk TCR repertoire data were generated by the authors S.S. and P.G.T. and are available on request.

References

  1. Taylor, H., Laurence, A. D. J. & Uhlig, H. H. The role of PTEN in innate and adaptive immunity. Cold Spring Harb. Perspect. Med. 9, a036996 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Hagenbeek, T. J. & Spits, H. T-cell lymphomas in T-cell-specific Pten-deficient mice originate in the thymus. Leukemia 22, 608–619 (2008).

    Article  CAS  PubMed  Google Scholar 

  3. Liu, X. et al. Distinct roles for PTEN in prevention of T cell lymphoma and autoimmunity in mice. J. Clin. Invest. 120, 2497–2507 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Xue, L., Nolla, H., Suzuki, A., Mak, T. W. & Winoto, A. Normal development is an integral part of tumorigenesis in T cell-specific PTEN-deficient mice. Proc. Natl Acad. Sci. USA 105, 2022–2027 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Hagenbeek, T. J. et al. The loss of PTEN allows TCR αβ lineage thymocytes to bypass IL-7 and pre-TCR-mediated signaling. J. Exp. Med. 200, 883–894 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Suzuki, A. et al. T cell-specific loss of Pten leads to defects in central and peripheral tolerance. Immunity 14, 523–534 (2001).

    Article  CAS  PubMed  Google Scholar 

  7. Di Cristofano, A. et al. Impaired Fas response and autoimmunity in Pten+/− mice. Science 285, 2122–2125 (1999).

    Article  PubMed  Google Scholar 

  8. Yehia, L., Keel, E. & Eng, C. The clinical spectrum of PTEN mutations. Annu. Rev. Med. 71, 103–116 (2020).

    Article  CAS  PubMed  Google Scholar 

  9. Crosby, C. M. & Kronenberg, M. Tissue-specific functions of invariant natural killer T cells. Nat. Rev. Immunol. 18, 559–574 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Provine, N. M. & Klenerman, P. MAIT cells in health and disease. Annu. Rev. Immunol. 38, 203–228 (2020).

    Article  CAS  PubMed  Google Scholar 

  11. Pellicci, D. G., Koay, H. F. & Berzins, S. P. Thymic development of unconventional T cells: how NKT cells, MAIT cells and γδ T cells emerge. Nat. Rev. Immunol. 20, 756–770 (2020).

    Article  CAS  PubMed  Google Scholar 

  12. Li, X., Bechara, R., Zhao, J., McGeachy, M. J. & Gaffen, S. L. IL-17 receptor-based signaling and implications for disease. Nat. Immunol. 20, 1594–1602 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Constantinides, M. G. et al. MAIT cells are imprinted by the microbiota in early life and promote tissue repair. Science 366, eaax6624 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Kjer-Nielsen, L. et al. MR1 presents microbial vitamin B metabolites to MAIT cells. Nature 491, 717–723 (2012).

    Article  CAS  PubMed  Google Scholar 

  15. Legoux, F. et al. Microbial metabolites control the thymic development of mucosal-associated invariant T cells. Science 366, 494–499 (2019).

    Article  CAS  PubMed  Google Scholar 

  16. Ivanov, I. I. et al. The orphan nuclear receptor RORγt directs the differentiation program of proinflammatory IL-17+ T helper cells. Cell 126, 1121–1133 (2006).

    Article  CAS  PubMed  Google Scholar 

  17. Yang, X. O. et al. T helper 17 lineage differentiation is programmed by orphan nuclear receptors RORα and RORγ. Immunity 28, 29–39 (2008).

    Article  CAS  PubMed  Google Scholar 

  18. Veldhoen, M. Interleukin 17 is a chief orchestrator of immunity. Nat. Immunol. 18, 612–621 (2017).

    Article  CAS  PubMed  Google Scholar 

  19. Shi, L. Z. et al. Gfi1–Foxo1 axis controls the fidelity of effector gene expression and developmental maturation of thymocytes. Proc. Natl Acad. Sci. USA 114, E67–E74 (2017).

    Article  CAS  PubMed  Google Scholar 

  20. Swat, W., Dessing, M., von Boehmer, H. & Kisielow, P. CD69 expression during selection and maturation of CD4+8+ thymocytes. Eur. J. Immunol. 23, 739–746 (1993).

    Article  CAS  PubMed  Google Scholar 

  21. Yamashita, I., Nagata, T., Tada, T. & Nakayama, T. CD69 cell surface expression identifies developing thymocytes which audition for T cell antigen receptor-mediated positive selection. Int. Immunol. 5, 1139–1150 (1993).

    Article  CAS  PubMed  Google Scholar 

  22. Huh, J. R. et al. Digoxin and its derivatives suppress TH17 cell differentiation by antagonizing RORγt activity. Nature 472, 486–490 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Tan, H. et al. Integrative proteomics and phosphoproteomics profiling reveals dynamic signaling networks and bioenergetics pathways underlying T cell activation. Immunity 46, 488–503 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Zhang, B. & Horvath, S. A general framework for weighted gene co-expression network analysis. Stat. Appl. Genet. Mol. Biol. https://doi.org/10.2202/1544-6115.1128 (2005).

  25. Boursalian, T. E., Golob, J., Soper, D. M., Cooper, C. J. & Fink, P. J. Continued maturation of thymic emigrants in the periphery. Nat. Immunol. 5, 418–425 (2004).

    Article  CAS  PubMed  Google Scholar 

  26. McCaughtry, T. M., Wilken, M. S. & Hogquist, K. A. Thymic emigration revisited. J. Exp. Med. 204, 2513–2520 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Matloubian, M. et al. Lymphocyte egress from thymus and peripheral lymphoid organs is dependent on S1P receptor 1. Nature 427, 355–360 (2004).

    Article  CAS  PubMed  Google Scholar 

  28. Allende, M. L., Dreier, J. L., Mandala, S. & Proia, R. L. Expression of the sphingosine 1-phosphate receptor, S1P1, on T-cells controls thymic emigration. J. Biol. Chem. 279, 15396–15401 (2004).

    Article  CAS  PubMed  Google Scholar 

  29. Arbones, M. L. et al. Lymphocyte homing and leukocyte rolling and migration are impaired in L-selectin-deficient mice. Immunity 1, 247–260 (1994).

    Article  CAS  PubMed  Google Scholar 

  30. Masopust, D. & Soerens, A. G. Tissue-resident T cells and other resident leukocytes. Annu. Rev. Immunol. 37, 521–546 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Klose, C. S. & Artis, D. Innate lymphoid cells as regulators of immunity, inflammation and tissue homeostasis. Nat. Immunol. 17, 765–774 (2016).

    Article  CAS  PubMed  Google Scholar 

  32. Tuttle, K. D. et al. TCR signal strength controls thymic differentiation of iNKT cell subsets. Nat. Commun. 9, 2650 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  33. Kovalovsky, D. et al. The BTB-zinc finger transcriptional regulator PLZF controls the development of invariant natural killer T cell effector functions. Nat. Immunol. 9, 1055–1064 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Savage, A. K. et al. The transcription factor PLZF directs the effector program of the NKT cell lineage. Immunity 29, 391–403 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Wei, J., Yang, K. & Chi, H. Cutting edge: discrete functions of mTOR signaling in invariant NKT cell development and NKT17 fate decision. J. Immunol. 193, 4297–4301 (2014).

    Article  CAS  PubMed  Google Scholar 

  36. Rahimpour, A. et al. Identification of phenotypically and functionally heterogeneous mouse mucosal-associated invariant T cells using MR1 tetramers. J. Exp. Med. 212, 1095–1108 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Cohen, N. R. et al. Shared and distinct transcriptional programs underlie the hybrid nature of iNKT cells. Nat. Immunol. 14, 90–99 (2013).

    Article  CAS  PubMed  Google Scholar 

  38. Legoux, F. et al. Molecular mechanisms of lineage decisions in metabolite-specific T cells. Nat. Immunol. 20, 1244–1255 (2019).

    Article  CAS  PubMed  Google Scholar 

  39. Wei, J. et al. Autophagy enforces functional integrity of regulatory T cells by coupling environmental cues and metabolic homeostasis. Nat. Immunol. 17, 277–285 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Koay, H. F. et al. A three-stage intrathymic development pathway for the mucosal-associated invariant T cell lineage. Nat. Immunol. 17, 1300–1311 (2016).

    Article  CAS  PubMed  Google Scholar 

  41. Treiner, E. et al. Selection of evolutionarily conserved mucosal-associated invariant T cells by MR1. Nature 422, 164–169 (2003).

    Article  CAS  PubMed  Google Scholar 

  42. Park, S. H., Benlagha, K., Lee, D., Balish, E. & Bendelac, A. Unaltered phenotype, tissue distribution and function of Vα14+ NKT cells in germ-free mice. Eur. J. Immunol. 30, 620–625 (2000).

    Article  CAS  PubMed  Google Scholar 

  43. Bradley, P. & Thomas, P. G. Using T cell receptor repertoires to understand the principles of adaptive immune recognition. Annu. Rev. Immunol. 37, 547–570 (2019).

    Article  CAS  PubMed  Google Scholar 

  44. Wang, G. C., Dash, P., McCullers, J. A., Doherty, P. C. & Thomas, P. G. T cell receptor αβ diversity inversely correlates with pathogen-specific antibody levels in human cytomegalovirus infection. Sci. Transl. Med. 4, 128ra142 (2012).

    Article  Google Scholar 

  45. Ohigashi, I. et al. The thymoproteasome hardwires the TCR repertoire of CD8+ T cells in the cortex independent of negative selection. J. Exp. Med. 218, e20201904 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Ringel, A. E. et al. Obesity shapes metabolism in the tumor microenvironment to suppress anti-tumor immunity. Cell 183, 1848–1866 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Lee, K. et al. Mammalian target of rapamycin protein complex 2 regulates differentiation of Th1 and Th2 cell subsets via distinct signaling pathways. Immunity 32, 743–753 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Huang, H., Long, L., Zhou, P., Chapman, N. M. & Chi, H. mTOR signaling at the crossroads of environmental signals and T-cell fate decisions. Immunol. Rev. 295, 15–38 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Lamming, D. W. et al. Rapamycin-induced insulin resistance is mediated by mTORC2 loss and uncoupled from longevity. Science 335, 1638–1643 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Sarbassov, D. D. et al. Prolonged rapamycin treatment inhibits mTORC2 assembly and Akt/PKB. Mol. Cell 22, 159–168 (2006).

    Article  CAS  PubMed  Google Scholar 

  51. Saravia, J., Chapman, N. M. & Chi, H. Helper T cell differentiation. Cell. Mol. Immunol. 16, 634–643 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Laine, A. et al. Foxo1 is a T cell-intrinsic inhibitor of the RORγt–Th17 program. J. Immunol. 195, 1791–1803 (2015).

    Article  CAS  PubMed  Google Scholar 

  53. Parham, C. et al. A receptor for the heterodimeric cytokine IL-23 is composed of IL-12Rβ1 and a novel cytokine receptor subunit, IL-23R. J. Immunol. 168, 5699–5708 (2002).

    Article  CAS  PubMed  Google Scholar 

  54. Yang, X. O. et al. STAT3 regulates cytokine-mediated generation of inflammatory helper T cells. J. Biol. Chem. 282, 9358–9363 (2007).

    Article  CAS  PubMed  Google Scholar 

  55. Engel, I. et al. Innate-like functions of natural killer T cell subsets result from highly divergent gene programs. Nat. Immunol. 17, 728–739 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Koay, H. F. et al. A divergent transcriptional landscape underpins the development and functional branching of MAIT cells. Sci. Immunol. 4, eaay6039 (2019).

    Article  CAS  PubMed  Google Scholar 

  57. Shrestha, S. et al. Treg cells require the phosphatase PTEN to restrain TH1 and TFH cell responses. Nat. Immunol. 16, 178–187 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Huynh, A. et al. Control of PI(3) kinase in Treg cells maintains homeostasis and lineage stability. Nat. Immunol. 16, 188–196 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Walsh, P. T. et al. PTEN inhibits IL-2 receptor-mediated expansion of CD4+ CD25+ Tregs. J. Clin. Invest. 116, 2521–2531 (2006).

    CAS  PubMed  PubMed Central  Google Scholar 

  60. Zeng, H. et al. mTORC1 and mTORC2 kinase signaling and glucose metabolism drive follicular helper T cell differentiation. Immunity 45, 540–554 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Cheng, M. & Anderson, M. S. Thymic tolerance as a key brake on autoimmunity. Nat. Immunol. 19, 659–664 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Li, H. et al. IL-23 promotes TCR-mediated negative selection of thymocytes through the upregulation of IL-23 receptor and RORγt. Nat. Commun. 5, 4259 (2014).

    Article  CAS  PubMed  Google Scholar 

  63. Tao, H. et al. Differential controls of MAIT cell effector polarization by mTORC1/mTORC2 via integrating cytokine and costimulatory signals. Nat. Commun. 12, 2029 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Chapman, N. M., Boothby, M. R. & Chi, H. Metabolic coordination of T cell quiescence and activation. Nat. Rev. Immunol. 20, 55–70 (2020).

    Article  CAS  PubMed  Google Scholar 

  65. Raynor, J. L. et al. Hippo/Mst signaling coordinates cellular quiescence with terminal maturation in iNKT cell development and fate decisions. J. Exp. Med. 217, e20191157 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Yang, K. et al. Metabolic signaling directs the reciprocal lineage decisions of αβ and γδ T cells. Sci. Immunol. 3, eaas9818 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  67. Prevot, N. et al. Mammalian target of rapamycin complex 2 regulates invariant NKT cell development and function independent of promyelocytic leukemia zinc-finger. J. Immunol. 194, 223–230 (2015).

    Article  CAS  PubMed  Google Scholar 

  68. Shin, J. et al. Mechanistic target of rapamycin complex 1 is critical for invariant natural killer T-cell development and effector function. Proc. Natl Acad. Sci. USA 111, E776–E783 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Zhang, L. et al. Mammalian target of rapamycin complex 1 orchestrates invariant NKT cell differentiation and effector function. J. Immunol. 193, 1759–1765 (2014).

    Article  CAS  PubMed  Google Scholar 

  70. Tao, H., Li, L., Gao, Y., Wang, Z. & Zhong, X. P. Differential control of iNKT cell effector lineage differentiation by the forkhead box protein O1 (Foxo1) transcription factor. Front. Immunol. 10, 2710 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Lee, M. et al. Single-cell RNA sequencing identifies shared differentiation paths of mouse thymic innate T cells. Nat. Commun. 11, 4367 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Burchill, M. A. et al. Linked T cell receptor and cytokine signaling govern the development of the regulatory T cell repertoire. Immunity 28, 112–121 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Lio, C. W. & Hsieh, C. S. A two-step process for thymic regulatory T cell development. Immunity 28, 100–111 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. Yang, K., Neale, G., Green, D. R., He, W. & Chi, H. The tumor suppressor Tsc1 enforces quiescence of naive T cells to promote immune homeostasis and function. Nat. Immunol. 12, 888–897 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Shiota, C., Woo, J. T., Lindner, J., Shelton, K. D. & Magnuson, M. A. Multiallelic disruption of the rictor gene in mice reveals that mTOR complex 2 is essential for fetal growth and viability. Dev. Cell 11, 583–589 (2006).

    Article  CAS  PubMed  Google Scholar 

  76. Cua, D. J. et al. Interleukin-23 rather than interleukin-12 is the critical cytokine for autoimmune inflammation of the brain. Nature 421, 744–748 (2003).

    Article  CAS  PubMed  Google Scholar 

  77. Paik, J. H. FOXOs in the maintenance of vascular homoeostasis. Biochem. Soc. Trans. 34, 731–734 (2006).

    Article  CAS  PubMed  Google Scholar 

  78. Yang, K. et al. Homeostatic control of metabolic and functional fitness of Treg cells by LKB1 signalling. Nature 548, 602–606 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  79. Wang, Y. et al. Tuberous sclerosis 1 (Tsc1)-dependent metabolic checkpoint controls development of dendritic cells. Proc. Natl Acad. Sci. USA 110, E4894–E4903 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Zeng, H. et al. mTORC1 couples immune signals and metabolic programming to establish Treg-cell function. Nature 499, 485–490 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. Hao, Y. et al. Integrated analysis of multimodal single-cell data. Cell 184, 3573–3587.e29 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Stuart, T. et al. Comprehensive integration of single-cell data. Cell 177, 1888–1902 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. McInnes, L., Healy, J. & Melville, J. UMAP: uniform manifold approximation and projection for dimension reduction. Preprint at arXiv https://arxiv.org/abs/1802.03426 (2018).

  84. Lambert, S. A. et al. The human transcription factors. Cell 172, 650–665 (2018).

    Article  CAS  PubMed  Google Scholar 

  85. Ramilowski, J. A. et al. A draft network of ligand-receptor-mediated multicellular signalling in human. Nat. Commun. 6, 7866 (2015).

    Article  CAS  PubMed  Google Scholar 

  86. Borcherding, N., Bormann, N. L. & Kraus, G. scRepertoire: an R-based toolkit for single-cell immune receptor analysis. F1000Research 9, 47 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. Egorov, E. S. et al. Quantitative profiling of immune repertoires for minor lymphocyte counts using unique molecular identifiers. J. Immunol. 194, 6155–6163 (2015).

    Article  CAS  PubMed  Google Scholar 

  88. Shugay, M. et al. Towards error-free profiling of immune repertoires. Nat. Methods 11, 653–655 (2014).

    Article  CAS  PubMed  Google Scholar 

  89. Shugay, M. et al. VDJtools: unifying post-analysis of T cell receptor repertoires. PLoS Comput. Biol. 11, e1004503 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  90. immunarch: an R package for painless bioinformatics analysis of T-cell and B-cell immune repertoires (v. 0.5.5). Zenodo https://doi.org/10.5281/zenodo.3367200 (2019).

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Acknowledgements

The authors acknowledge X. Du and Y. Wang for critical reading or editing of the manuscript, M. Hendren and R. Walton for animal colony maintenance and technical assistance, and the St. Jude Immunology FACS core facility for cell sorting. This work was supported by ALSAC and National Institutes of Health grant nos AI105887, AI131703, AI140761, AI150241, AI150514 and CA253188 (to H.C.), and AI136514 and AI150747 (to P.G.T.). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Author information

Authors and Affiliations

Authors

Contributions

D.B.B. designed, performed and analysed experiments, and wrote the manuscript. N.M.C. designed, performed and analysed experiments, provided insights for bioinformatic analyses, co-wrote the manuscript and provided insights for overall project direction. J.L.R. designed, performed and analysed experiments. C.X., W.S., A.K., W.L., S.A.L., Y.K. and K.Y. designed and performed experiments. S.S. and P.G.T. performed TCR repertoire analysis. H.S., I.R., Y.S., Y.D. and G.N. performed bioinformatic analyses. J.W. provided insights for overall project direction. S.R. contributed to the survival curves and provided technical support. H.C. designed experiments, co-wrote the manuscript and provided overall direction.

Corresponding authors

Correspondence to Kai Yang or Hongbo Chi.

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Competing interests

H.C. is a consultant for Kumquat Biosciences, Inc. P.G.T. is on the scientific advisory board of Immunoscape and Cytoagents, and has consulted for or received personal fees from Mirror Biologics, PACT Pharma, Johnson & Johnson, Pfizer, 10X Genomics, Illumina and Elevate Bio, and has a sponsored research agreement with Elevate Bio. The remaining authors declare no competing interests.

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Nature Cell Biology thanks Keith T. Gagnon, and the other, anonymous reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Characterization of thymic and peripheral IL-17-producing populations in Cd4CrePtenfl/fl mice.

(a) Flow cytometry analysis and quantification of percentages and numbers of CD4CD8 double-negative (DN), CD4+CD8+ double-positive (DP), CD4+ single-positive (CD4SP), and CD8+ SP (CD8SP) thymocytes in 3–6 week-old WT and Cd4CrePtenfl/fl mice (n = 8 mice per group). (b) Quantification of numbers of IFNγ- and IL-4-producing TCRβ+ cells in the thymus from WT and Cd4CrePtenfl/fl mice (n = 12 mice per group for IFNγ+TCRβ+; 6 mice per group for IL-4+TCRb+). (c) Quantification of IL-17A+TCRβ+ cell number in spleen, peripheral lymph nodes (pLN), lung, and liver (n = 6 mice per group for spleen and pLN; 3 mice per group for lung and liver). (d) Flow cytometry analysis of CCR6 and CD127 expression on IL-17A+TCRβ+ thymocytes in WT and Cd4CrePtenfl/fl mice. (e) Flow cytometry analyses of CCR6 versus RORγtGFP expression and CCR6+CD127+ cells among CCR6+RORgtGFP+ thymocytes in Cd4CrePten+/+RORγtGFP and Cd4CrePtenfl/flRORγtGFP mice. Right: quantification of the number of RORgtGFP+CCR6+ thymocytes in Cd4CrePten+/+RORγtGFP and Cd4CrePtenfl/flRORγtGFP mice (n = 3 mice per group). (f) Quantification of numbers of IL-17A+TCRβ+ and CCR6+CD127+TCRβ+ thymocytes in 10–15-day-old WT and Cd4CrePtenfl/fl mice (n = 10 mice per group). (g) Relative Pten mRNA expression in pre-selection and post-selection DP cells from thymus of WT and Cd4CrePtenfl/fl mice (n = 5 mice per group for TCRβCD69 DP cells; 5 WT and 4 Cd4CrePtenfl/fl mice for TCRβ+CD69+ DP cells). (h) Relative Pten mRNA expression in WT pre-selection DP cells stimulated with anti-CD3/CD28 antibodies for 4 h (n = 5 mice per group). (i) Violin plots showing expression of Pten, Rorc, and Il23r in indicated thymocyte populations from WT mice (n = 2 mice). Data are representative of at least two (d,e; flow cytometry panels), or combined from five (a), at least four (b; c, spleen and pLN), three (c, lung and liver), or two (eh) independent experiments. Two-tailed unpaired Student’s t-test (a,b,eh). Data are shown as mean ± s.e.m. (ac,eh). *P < 0.05; **P < 0.01; ***P < 0.001; ns, not significant. Numbers indicate percentages of cells in gates (a,d,e).

Source data

Extended Data Fig. 2 Dispensable role of IL-6 for the generation and thymic-resident features of PTEN-deficient IL-17-producing cells.

(a) Quantification of percentages and numbers of IL-17A+TCRβ+ and CCR6+CD127+TCRβ+ thymocytes (n = 7 WT, 7 Cd4CrePtenfl/fl, 4 Il6–/–, and 8 Cd4CrePtenfl/flIl6–/– mice for frequencies; 6 WT, 6 Cd4CrePtenfl/fl, 2 Il6–/– and 6 Cd4CrePtenfl/flIl6–/– for numbers). (b) Relative number of IL-17A+TCRβ+ thymocytes in indicated 4–6-week-old mice (values were set to WT equal to 1 for normalization) (n = 11 WT, 8 Cd4CrePten+/fl, and 9 Cd4CrePtenfl/fl mice). (c) Percentages of IL-17A+TCRβ+ thymocytes and IL-17A+CD4+Foxp3CD44+ effector/memory T cells in the spleen and mesenteric lymph nodes (mLN) of 5–9-month-old WT and Cd4CrePtenfl/fl mice (n = 8 mice per group for thymus and spleen; 6 mice per group for mLN). (d) Relative number of IL-17A+TCRβ+ thymocytes (n = 5 mice per group for ≤ 20-week-old male mice; 10 mice per group for ≤ 20-week-old female mice and > 20-week-old female mice; 2 mice per group for > 20-week-old male mice). (e,f) Survival curves of male and female WT, Cd4CrePtenfl/fl, and Cd4CrePtenfl/flIl17ra–/– (e; n = 18–111 mice per group; see legend key for details), or male and female WT, Cd4CrePtenfl/fl, and Cd4CrePtenfl/flIl23a–/– mice (f; n = 48–111 mice per group; see legend key for details). WT and Cd4CrePtenfl/fl mice were the same in e and f. (g) Relative number of IL-17A-GFP+TCRβ+ cells (n = 3 mice per group for spleen, peripheral lymph nodes (pLN), and lung; 2 mice per group for liver). (h) Flow cytometry analysis of S1PR1, CD62L, CD69, and CD103 expression. Data are representative of at least three (h), or combined from four (a), at least six (b,d), three (c, thymus and spleen), or two (c, mLN; g) independent experiments. Two-tailed unpaired Student’s t-test (c,d) or log-rank test (e,f). Data are shown as mean ± s.e.m. (ad,g). *P < 0.05; **P < 0.01; ns, not significant. Numbers indicate mean fluorescence intensity (h).

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Extended Data Fig. 3 Cellular and molecular characterization of PTEN-deficient IL-17-producing thymocytes.

(a) Flow cytometry analysis and quantification of percentages of TCRβ+ or TCRγδ+CCR6+CD127+ thymocytes (n = 7 mice per group). (b) Flow cytometry analysis and quantification of percentage of CD3ε+CCR6+CD127+TCRβ+ thymocytes (n = 7 mice per group). (c) Flow cytometry analysis and quantification of relative TCRβ mean fluorescence intensity (MFI) on the indicated thymocyte population from Cd4CrePtenfl/fl mice (n = 3 mice). (d) Flow cytometry analysis of CD1d:PBS57 tetramer staining on IL-17A+TCRβ+ thymocytes. (e) Flow cytometry analysis of IL-17A production among CD44+ thymocytes. (f) Flow cytometry analysis of CD1d:PBS57- and MR1:5-OP-RU-tetramer co-staining on CCR6+CD127+TCRβ+ or IL-17A+TCRβ+ thymocytes (blue, iNKT17; purple, MAIT17; orange, iNKT17MAIT17). (g,h) Enrichment plots showing activity of PTEN gene signature (see Supplementary Table 31) in WT iNKT (g) or WT MAIT (h) compared to CD4SP or CD8SP cells from public microarray datasets37,38. PTEN KO, Cd4CrePtenfl/fl; NES, normalized enrichment score; FDR, false discovery rate. (i) Flow cytometry analysis and quantification of MAIT cell number (n = 9 WT and 10 Cd4CrePtenfl/fl mice). (j) Quantification of percentages and numbers of RORγt+ and T-bet+ MAIT cells (pregated on total MAIT cells) (n = 7 mice per group). (k) Flow cytometry analysis and quantification of percentages of active caspase-3+ thymic iNKT and MAIT cells (n = 5 mice per group). (l) Quantification of percentages of bromodeoxyuridine (BrdU)+ thymic iNKT and MAIT cells (n = 3 mice per group for iNKT cells; 2 mice per group for MAIT cells). (m) Quantification of percentages of Ki67+ iNKT1 (CD1d:PBS57-tetramer+T-bet+PLZFlo) and iNKT2 (CD1d:PBS57-tetramer+PLZFhiRORγt) cells (n = 6 mice per group). Data are representative of at least six (d), two (e), or five (f), or combined from four (a,i,m), six (b,j), three (c), five (k), or two (l) independent experiments. Two-tailed unpaired Student’s t-test (b,c,im). Data are shown as mean ± s.e.m. (ac,im). *P < 0.05; **P < 0.01; ***P < 0.001; ns, not significant. Numbers indicate MFI (c) or percentages of cells in gates or quadrants (df,j,k).

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Extended Data Fig. 4 TCR repertoire, surface molecule, and transcriptome analyses of PTEN-deficient iNKT17MAIT17 thymocytes.

(a) Shannon or Inverse Simpson’s diversity scores of TCR repertoires of indicated cell populations among CCR6+CD127+TCRβ+ thymocytes from Cd4CrePtenfl/fl mice (n = 3 mice). (b) Inverse Simpson’s diversity scores of the TCRα and TCRβ repertoires of sort-purified iNKT17, MAIT17, and iNKT17MAIT17 cells among CCR6+CD127+TCRβ+ thymocytes from Cd4CrePtenfl/fl mice. Each dot corresponds to an individual mouse (n = 4 mice). (c) Relative frequency of TCRα and TCRβ clones in sort-purified iNKT17, MAIT17, and iNKT17MAIT17cells among CCR6+CD127+TCRβ+ thymocytes from Cd4CrePtenfl/fl mice (n = 4 mice). FDR, false discovery rate. (d) Plot depicting differential expression profiles (|log2 FC| > 0.5, FDR < 0.05) in each indicated comparison. Red and blue numbers indicate the numbers of upregulated and downregulated genes in each comparison, respectively. Cells were profiled by scRNA-seq and identified as in Fig. 3e (n = 4 WT and 3 Cd4CrePtenfl/fl mice). (e) Functional enrichment analysis of the differentially expressed (|log2 FC| > 0.5, FDR < 0.05) genes in PTEN-deficient versus WT iNKT17MAIT17 cells (n = 4 WT and 3 Cd4CrePtenfl/fl mice). (f) Flow cytometry analysis and quantification of the numbers of CD4CD8 double-negative (DN), CD4+CD8+ double-positive (DP), CD4+ single-positive (CD4SP), and CD8+ SP (CD8SP) cells among the iNKT17MAIT17 thymocytes (pre-gated on CCR6+CD127+TCRβ+ cells) (n = 9 WT or 10 Cd4CrePtenfl/fl mice). (g) Flow cytometry analysis and quantification of percentages and numbers of PD-1 and PD-1+ cells among the CD4CD8iNKT17MAIT17 thymocytes (pre-gated on CCR6+CD127+TCRβ+ cells) (n = 4 WT or 5 Cd4CrePtenfl/fl mice). Data are combined from two (d), five (f) or three (g) independent experiments. Two-tailed paired Student’s t-test followed by Benjamin–Hochberg method (c; depicted for hyperexpanded TCR clonotypes), right-tailed Fisher’s exact test, (e) or two-tailed unpaired Student’s t-test (f,g). Data are shown as mean ± s.e.m. (f,g). Box plots (d): Box shows median with interquartile range (IQR) of 25% (minima)–75% (maxima); whiskers show 25% quantile ± IQR. **P < 0.01; ***P < 0.001; ns, not significant. Numbers indicate percentages of cells in gates (f,g).

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Extended Data Fig. 5 Metabolic signatures of type-17 innate-like T cell subsets.

(a) Flow cytometry analysis and quantification of TMRM and MitoTracker Deep Red staining of CCR6+CD127+TCRβ+ thymocytes (n = 6 per group for TMRM; 6 WT and 5 Cd4CrePtenfl/fl for MitoTracker Deep Red). Data are relative to the average TMRM or MitoTracker Deep Red mean fluorescence intensity (MFI) in CCR6+CD127+TCRβ+ thymocytes from WT mice. (b) Metabolic signature scores of single cell transcriptomes of PTEN-deficient iNKT17, MAIT17, and iNKT17MAIT17 cells as compared with WT. Cells were profiled by scRNA-seq and identified as in Fig. 3e. Alignment to the left of the dashed line indicates enrichment in PTEN-deficient cells; alignment to the right of the dashed line indicates enrichment in WT cells (n = 3 WT and 4 Cd4CrePtenfl/fl mice). (c) Quantification of numbers of IL-17A+TCRβ+ and CCR6+CD127+TCRβ+ thymocytes in WT and Cd4CrePtenfl/fl mice treated with rapamycin or vehicle (n = 4 WT + vehicle, 4 Cd4CrePtenfl/fl + vehicle, 3 WT + rapamycin, and 4 Cd4CrePtenfl/fl + rapamycin mice for IL-17A+TCRβ+ thymocytes; 4 mice per group for CCR6+CD127+TCRβ+ thymocytes). (d) GSEA of Hallmark pathways upregulated (red) or downregulated (blue) in pre-selection DP cells from Cd4CrePtenfl/fl (PTEN KO) versus WT mice; Cd4CrePtenfl/flRptorfl/fl (PTEN/RAPTOR dKO) versus PTEN KO mice; and Cd4CrePtenfl/flRictorfl/fl (PTEN/RICTOR dKO) versus PTEN KO mice. NES, normalized enrichment score; FDR, false discovery rate. (e,f) Quantification of MitoTracker Deep Red staining of CCR6+CD127+TCRβ+ thymocytes from the indicated mice (e; n = 7 WT, 7 Cd4CrePtenfl/fl, 3 Cd4CreRptorfl/fl and 10 Cd4CrePtenfl/flRptorfl/fl mice; f; n = 11 WT, 8 Cd4CrePtenfl/fl, 2 Cd4CreRictorfl/fl, and 9 Cd4CrePtenfl/flRictorfl/fl mice). (g) Heatmap depicting the expression of Rorc and Il23r in post-selection DP cells from indicated mice (n = 4 WT, 5 Cd4CrePtenfl/fl, 7 Cd4CrePtenfl/flRptorfl/fl and 5 Cd4CrePtenfl/flRictorfl/fl mice). Data are combined from four (a, TMRM; e), three (a, MitoTracker Deep Red), two (c), or five (f) independent experiments. Two-tailed unpaired Student’s t-test (a) or one-way ANOVA with Tukey’s test (c,e,f). Data are shown as mean ± s.e.m. (a,c,e,f). ***P < 0.001. Numbers indicate MFI (a).

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Extended Data Fig. 6 Roles of Foxo1, Stat3 and IL-23 signalling in type-17 innate-like T cell development.

(a) Flow cytometry analysis and quantification of percentage and number of CCR6+CD127+TCRβ+ thymocytes. Lower: flow cytometry analysis and quantification of the relative numbers of indicated subsets among CCR6+CD127+TCRβ+ thymocytes (n = 5 mice per group). (b) Quantification of TMRM and MitoTracker Deep Red staining of CCR6+CD127+TCRβ+ thymocytes (n = 6 WT and 10 Cd4CreFoxo1fl/fl mice). (c) Quantification of percentages of indicated populations among CCR6+CD127+TCRβ+ thymocytes (n = 7 WT and 8 Il23a–/– mice). (d) Quantification of percentages of indicated thymic iNKT subsets (n = 3 WT and 4 Il23a–/– mice for RORγt+PLZFint iNKT17, T-bet+PLZFlo iNKT1, PLZFhiRORγt iNKT2 and IL-4+ iNKT2; 5 WT and 6 Il23a–/– mice for IL-17A+ iNKT17; and 4 WT and 5 Il23a–/– mice for IFNγ+ iNKT1). (e) PTEN orchestrates a two-step thymic programme to regulate the development of type-17 innate-like T cells downstream of TCR and IL-23–IL-23R–Stat3 signalling. Upper: In pre-positive selection DP cells, TCR signals initiate positive selection and downregulate PTEN expression. In post-positive selection DP cells, PTEN restrains RORγt-dependent induction of the type-17 programme that induces IL-23R expression, and restrains Foxo1 activity that inhibits IL-23R expression. Sustained downregulation of PTEN expression at this stage allows for induction of IL-23R expression and IL-23–IL-23R–Stat3 signalling, which promotes the development of type-17 innate-like T cell subsets. Lower left, PTEN inhibits mTOR signalling to restrain metabolic activities and expression of RORγt and IL-23R in DP cells. Lower right, hyperactivation of IL-17RA and IL-23 signalling contributes to the fatality of mice with PTEN haploinsufficiency, a model of human PTEN Hamartoma Tumour Syndrome (PHTS). Data are combined from two (a,b), one (d, transcription factors and IL-4+ iNKT2 cells), four (c), or three (d, IL-17A+ iNKT17 and IFNγ+ iNKT1 cells) independent experiments. Two-tailed unpaired Student’s t-test (ad). Data are shown as mean ± s.e.m. (ad). *P < 0.05; **P < 0.01; ***P < 0.001; ns, not significant. Numbers indicate percentage of cells in gates or quadrants (a).

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Supplementary Tables 1–6.

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Blanco, D.B., Chapman, N.M., Raynor, J.L. et al. PTEN directs developmental and metabolic signaling for innate-like T cell fate and tissue homeostasis. Nat Cell Biol 24, 1642–1654 (2022). https://doi.org/10.1038/s41556-022-01011-w

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