c-MAF-dependent regulatory T cells mediate immunological tolerance to a gut pathobiont

  • Nature volume 554, pages 373377 (15 February 2018)
  • doi:10.1038/nature25500
  • Download Citation
Published online:


Both microbial and host genetic factors contribute to the pathogenesis of autoimmune diseases1,2,3,4. There is accumulating evidence that microbial species that potentiate chronic inflammation, as in inflammatory bowel disease, often also colonize healthy individuals. These microorganisms, including the Helicobacter species, can induce pathogenic T cells and are collectively referred to as pathobionts4,5,6. However, how such T cells are constrained in healthy individuals is not yet understood. Here we report that host tolerance to a potentially pathogenic bacterium, Helicobacter hepaticus, is mediated by the induction of RORγt+FOXP3+ regulatory T (iTreg) cells that selectively restrain pro-inflammatory T helper 17 (TH17) cells and whose function is dependent on the transcription factor c-MAF. Whereas colonization of wild-type mice by H. hepaticus promoted differentiation of RORγt-expressing microorganism-specific iTreg cells in the large intestine, in disease-susceptible IL-10-deficient mice, there was instead expansion of colitogenic TH17 cells. Inactivation of c-MAF in the Treg cell compartment impaired differentiation and function, including IL-10 production, of bacteria-specific iTreg cells, and resulted in the accumulation of H. hepaticus-specific inflammatory TH17 cells and spontaneous colitis. By contrast, RORγt inactivation in Treg cells had only a minor effect on the bacteria-specific Treg and TH17 cell balance, and did not result in inflammation. Our results suggest that pathobiont-dependent inflammatory bowel disease is driven by microbiota-reactive T cells that have escaped this c-MAF-dependent mechanism of iTreg–TH17 homeostasis.

  • Subscribe to Nature for full access:



Additional access options:

Already a subscriber?  Log in  now or  Register  for online access.


Primary accessions

NCBI Reference Sequence

Sequence Read Archive


  1. 1.

    & The gut microbiota shapes intestinal immune responses during health and disease. Nat. Rev. Immunol. 9, 313–323 (2009)

  2. 2.

    , & Interactions between the microbiota and the immune system. Science 336, 1268–1273 (2012)

  3. 3.

    , , & Role of the gut microbiota in immunity and inflammatory disease. Nat. Rev. Immunol. 13, 321–335 (2013)

  4. 4.

    , & Pathobionts of the gastrointestinal microbiota and inflammatory disease. Curr. Opin. Immunol. 23, 473–480 (2011)

  5. 5.

    et al. IL-23 plays a key role in Helicobacter hepaticus-induced T cell-dependent colitis. J. Exp. Med. 203, 2485–2494 (2006)

  6. 6.

    et al. Interleukin-23 drives innate and T cell-mediated intestinal inflammation. J. Exp. Med. 203, 2473–2483 (2006)

  7. 7.

    , & Identification of a CD4+ T cell-stimulating antigen of pathogenic bacteria by expression cloning. J. Exp. Med. 182, 1751–1757 (1995)

  8. 8.

    et al. Focused specificity of intestinal TH17 cells towards commensal bacterial antigens. Nature 510, 152–156 (2014)

  9. 9.

    , , & Visualization of peptide-specific T cell immunity and peripheral tolerance induction in vivo. Immunity 1, 327–339 (1994)

  10. 10.

    et al. Naive CD4+ T cell frequency varies for different epitopes and predicts repertoire diversity and response magnitude. Immunity 27, 203–213 (2007)

  11. 11.

    et al. Individual intestinal symbionts induce a distinct population of RORγ+ regulatory T cells. Science 349, 993–997 (2015)

  12. 12.

    et al. The microbiota regulates type 2 immunity through RORγt+ T cells. Science 349, 989–993 (2015)

  13. 13.

    et al. The alarmin IL-33 promotes regulatory T-cell function in the intestine. Nature 513, 564–568 (2014)

  14. 14.

    et al. Fate mapping of IL-17-producing T cells in inflammatory responses. Nat. Immunol. 12, 255–263 (2011)

  15. 15.

    et al. Acute gastrointestinal infection induces long-lived microbiota-specific T cell responses. Science 337, 1553–1556 (2012)

  16. 16.

    et al. Helicobacter species are potent drivers of colonic T cell responses in homeostasis and inflammation. Sci. Immunol. 2, eaal5068 (2017)

  17. 17.

    et al. Foxp3+ T cells expressing RORγt represent a stable regulatory T-cell effector lineage with enhanced suppressive capacity during intestinal inflammation. Mucosal Immunol. 9, 444–457 (2016)

  18. 18.

    et al. A validated regulatory network for Th17 cell specification. Cell 151, 289–303 (2012)

  19. 19.

    et al. The aryl hydrocarbon receptor interacts with c-Maf to promote the differentiation of type 1 regulatory T cells induced by IL-27. Nat. Immunol. 11, 854–861 (2010)

  20. 20.

    et al. MyD88 signalling in colonic mononuclear phagocytes drives colitis in IL-10-deficient mice. Nat. Commun. 3, 1120 (2012)

  21. 21.

    et al. Specific microbiota direct the differentiation of IL-17-producing T-helper cells in the mucosa of the small intestine. Cell Host Microbe 4, 337–349 (2008)

  22. 22.

    & Abrogation of TGFβ signaling in T cells leads to spontaneous T cell differentiation and autoimmune disease. Immunity 12, 171–181 (2000)

  23. 23.

    et al. CD4+ regulatory T cells control TH17 responses in a Stat3-dependent manner. Science 326, 986–991 (2009)

  24. 24.

    et al. A requisite role for induced regulatory T cells in tolerance based on expanding antigen receptor diversity. Immunity 35, 109–122 (2011)

  25. 25.

    et al. The Toll-like receptor 2 pathway establishes colonization by a commensal of the human microbiota. Science 332, 974–977 (2011)

  26. 26.

    et al. Dietary antigens limit mucosal immunity by inducing regulatory T cells in the small intestine. Science 351, 858–863 (2016)

  27. 27.

    et al. Treg induction by a rationally selected mixture of Clostridia strains from the human microbiota. Nature 500, 232–236 (2013)

  28. 28.

    et al. Regulatory T cell-derived interleukin-10 limits inflammation at environmental interfaces. Immunity 28, 546–558 (2008)

  29. 29.

    et al. The transcription factor c-Maf controls touch receptor development and function. Science 335, 1373–1376 (2012)

  30. 30.

    et al. Cutting edge: IL-23 receptor GFP reporter mice reveal distinct populations of IL-17-producing cells. J. Immunol. 182, 5904–5908 (2009)

  31. 31.

    et al. Paired analysis of TCRα and TCRβ chains at the single-cell level in mice. J. Clin. Invest. 121, 288–295 (2011)

  32. 32.

    et al. IMGT, the international ImMunoGeneTics information system. Nucleic Acids Res. 37, D1006–D1012 (2009)

  33. 33.

    et al. CTLA-4 suppresses the pathogenicity of self antigen-specific T cells by cell-intrinsic and cell-extrinsic mechanisms. Nat. Immunol. 11, 129–135 (2010)

  34. 34.

    et al. Differences in dendritic cells stimulated in vivo by tumors engineered to secrete granulocyte-macrophage colony-stimulating factor or Flt3-ligand. Cancer Res. 60, 3239–3246 (2000)

  35. 35.

    & Prediction of peptide–MHC binding using profiles. Methods Mol. Biol. 409, 185–200 (2007)

  36. 36.

    , , & Cassette vectors directing expression of T cell receptor genes in transgenic mice. J. Immunol. Methods 180, 273–280 (1995)

  37. 37.

    et al. Phenotypic analysis of antigen-specific T lymphocytes. Science 274, 94–96 (1996)

  38. 38.

    et al. T cell transfer model of chronic colitis: concepts, considerations, and tricks of the trade. Am. J. Physiol. Gastrointest. Liver Physiol. 296, G135–G146 (2009)

  39. 39.

    , & Cytotoxic T lymphocyte-associated antigen 4 plays an essential role in the function of CD25+CD4+ regulatory cells that control intestinal inflammation. J. Exp. Med. 192, 295–302 (2000)

  40. 40.

    . et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013)

  41. 41.

    , & featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30, 923–930 (2014)

  42. 42.

    , & Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014)

  43. 43.

    , & Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostatistics 8, 118–127 (2007)

  44. 44.

    R Development Core Team. R: A Language And Environment For Statistical Computing ; (R Foundation for Statistical Computing, Vienna, Austria, 2016)

Download references


We thank S. Y. Kim and the NYU Rodent Genetic Engineering Laboratory (RGEL) for generating TCR transgenic mice, A. Heguy and colleagues at the NYU School of Medicine’s Genome Technology Center (GTC) for preparation of RNA-seq libraries and RNA sequencing, the NIH Tetramer Core Facility for generating MHC class II tetramers, K. Murphy for providing the 58αβ hybridoma line, D. E. Levy for providing the Stat3fl/fl;Cd4cre mice, J. Fox for providing the H. hepaticus strain, P. Dash and P. G. Thomas for advice on single-cell TCR cloning, and J. A. Hall, J. Muller and J. Lafaille for suggestions on the manuscript. The Experimental Pathology Research Laboratory of NYU Medical Center is supported by National Institutes of Health Shared Instrumentation grants S10OD010584-01A1 and S10OD018338-01. The GTC is partially supported by the Cancer Center Support grant P30CA016087 at the Laura and Isaac Perlmutter Cancer Center. This work was supported by the Irvington Institute fellowship program of the Cancer Research Institute (M.X.); the training program in Immunology and Inflammation 5T32AI100853 (M.P.); the Helen and Martin Kimmel Center for Biology and Medicine (D.R.L.); the Colton Center for Autoimmunity (D.R.L.); and National Institutes of Health grant R01DK103358 (R.B. and D.R.L.). D.R.L. is an Investigator of the Howard Hughes Medical Institute.

Author information

Author notes

    • Mo Xu
    •  & Maria Pokrovskii

    These authors contributed equally to this work.


  1. Molecular Pathogenesis Program, The Kimmel Center for Biology and Medicine of the Skirball Institute, New York University School of Medicine, New York, New York 10016, USA.

    • Mo Xu
    • , Maria Pokrovskii
    • , Christy Au
    • , Carolina Galan
    •  & Dan R. Littman
  2. Department of Pathology and Laboratory Medicine, University of Rochester Medical Center, Rochester, New York 14642, USA.

    • Yi Ding
  3. Courant Institute of Mathematical Sciences, Computer Science Department, New York University, New York, New York 10003, USA.

    • Ren Yi
    •  & Richard Bonneau
  4. The Howard Hughes Medical Institute, New York University School of Medicine, New York, New York 10016, USA.

    • Christy Au
    •  & Dan R. Littman
  5. Mucosal Immunology Section, Laboratory of Parasitic Diseases, National Institute of Allergy and Infectious Diseases, NIH, Bethesda, Maryland 20892, USA.

    • Oliver J. Harrison
    •  & Yasmine Belkaid
  6. NIAID Microbiome Program, NIH, Bethesda, Maryland 20892, USA.

    • Yasmine Belkaid
  7. Center for Genomics and Systems Biology, Department of Biology, New York University, New York, New York 10003, USA.

    • Richard Bonneau
  8. Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, New York 10010, USA.

    • Richard Bonneau


  1. Search for Mo Xu in:

  2. Search for Maria Pokrovskii in:

  3. Search for Yi Ding in:

  4. Search for Ren Yi in:

  5. Search for Christy Au in:

  6. Search for Oliver J. Harrison in:

  7. Search for Carolina Galan in:

  8. Search for Yasmine Belkaid in:

  9. Search for Richard Bonneau in:

  10. Search for Dan R. Littman in:


M.X. and M.P. designed and performed all experiments and analysed the data. Y.D. performed blinded histology scoring on colitis sections. C.A. and C.G. assisted with in vivo and in vitro experiments. R.Y. and M.P. performed RNA-seq analysis. O.J.H. and Y.B. analysed the Gata3Treg mouse phenotype. R.B. supervised RNA-seq analysis. M.X., M.P. and D.R.L. wrote the manuscript with input from the co-authors. D.R.L. supervised the research and contributed to experimental design.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Dan R. Littman.

Reviewer Information Nature thanks C. Ohnmacht and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Supplementary information


By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.