Letter | Published:

m6A mRNA methylation controls T cell homeostasis by targeting the IL-7/STAT5/SOCS pathways

Nature volume 548, pages 338342 (17 August 2017) | Download Citation


N6-methyladenosine (m6A) is the most common and abundant messenger RNA modification, modulated by ‘writers’, ‘erasers’ and ‘readers’ of this mark1,2. In vitro data have shown that m6A influences all fundamental aspects of mRNA metabolism, mainly mRNA stability, to determine stem cell fates3,4. However, its in vivo physiological function in mammals and adult mammalian cells is still unknown. Here we show that the deletion of m6A ‘writer’ protein METTL3 in mouse T cells disrupts T cell homeostasis and differentiation. In a lymphopaenic mouse adoptive transfer model, naive Mettl3-deficient T cells failed to undergo homeostatic expansion and remained in the naive state for up to 12 weeks, thereby preventing colitis. Consistent with these observations, the mRNAs of SOCS family genes encoding the STAT signalling inhibitory proteins SOCS1, SOCS3 and CISH were marked by m6A, exhibited slower mRNA decay and showed increased mRNAs and levels of protein expression in Mettl3-deficient naive T cells. This increased SOCS family activity consequently inhibited IL-7-mediated STAT5 activation and T cell homeostatic proliferation and differentiation. We also found that m6A has important roles for inducible degradation of Socs mRNAs in response to IL-7 signalling in order to reprogram naive T cells for proliferation and differentiation. Our study elucidates for the first time, to our knowledge, the in vivo biological role of m6A modification in T-cell-mediated pathogenesis and reveals a novel mechanism of T cell homeostasis and signal-dependent induction of mRNA degradation.

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We thank R. Flynn, R. Jackson, Y. Yang, M. Vesely, R. Paiva, N. Palm and all the other members of the Flavell laboratory for discussions and comments. We thank J. Alderman, C. Lieber, C. Hughes and J. Stein for technical support. H.-B.L. was supported by NIH T32 2T32DK007356. S.Z was supported by a fellowship from Helen Hay Whitney Foundation-Howard Hughes Medical Institute. This work was supported by the Howard Hughes Medical Institute (R.A.F.), NSF Major International Joint Research Program of China - 31420103901 (Z.Y. and R.A.F.) and ‘111’ project (Z.Y.), R01-HG004361 (H.Y.C.), NIH New Innovator Award DP2 HD083992-01 (M.D.S.), and a Searle scholarship (M.D.S.).

Author information

Author notes

    • Hua-Bing Li
    • , Jiyu Tong
    •  & Shu Zhu

    These authors contributed equally to this work.

    • Hua-Bing Li
    • , Zhinan Yin
    •  & Richard A. Flavell

    These authors jointly supervised this work.


  1. Department of Immunobiology, Yale University School of Medicine, New Haven, Connecticut 06520, USA

    • Hua-Bing Li
    • , Jiyu Tong
    • , Shu Zhu
    • , Jun Zhao
    • , Will Bailis
    • , Guangchao Cao
    • , Lina Kroehling
    • , Yuanyuan Chen
    • , Geng Wang
    •  & Richard A. Flavell
  2. The First Affiliated Hospital, Biomedical Translational Research Institute and Guangdong Province Key Laboratory of Molecular Immunology and Antibody Engineering, Jinan University, Guangzhou 510632, China

    • Jiyu Tong
    • , Guangchao Cao
    •  & Zhinan Yin
  3. Center for Dynamic Regulomes, Stanford University, Stanford, California 94305, USA

    • Pedro J. Batista
    • , James P. Broughton
    • , Y. Grace Chen
    •  & Howard Y. Chang
  4. Department of Molecular Biophysics & Biochemistry, Yale University, New Haven, Connecticut 06511, USA

    • Erin E. Duffy
    •  & Matthew D. Simon
  5. Chemical Biology Institute, Yale University, West Haven, Connecticut 06516, USA

    • Erin E. Duffy
    •  & Matthew D. Simon
  6. Department of Pathology, Yale University School of Medicine, New Haven, Connecticut 06520, USA

    • Jun Zhao
    •  & Yuval Kluger
  7. Institute of Surgical Research, Daping Hospital, the Third Military Medical University, Chongqing 400038, China

    • Yuanyuan Chen
  8. Howard Hughes Medical Institute, Chevy Chase, Maryland 20815-6789, USA

    • Richard A. Flavell


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H-B. L. conceived the project. H.-B. L., J. T., S. Z., P.B., E.E.D., W.B., G.C., Y. C., G.W., J.P.B. and Y.G.C. performed the experimental work. J.Z., L.K., M.D.S. and P.B. analysed the RNA-seq, ribo-profiling, s4U-seq and m6A-seq data and performed the statistical analysis. H.Y.C., M.D.S., Y.K., and Z.Y. provided key suggestions. H.-B. L. and R.A.F designed the study, analysed the data and wrote the manuscript. R.A.F. supervised the study.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Hua-Bing Li or Zhinan Yin or Richard A. Flavell.

Reviewer Information Nature thanks F. Fuks, J. H. Hanna 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

PDF files

  1. 1.

    Supplementary information

    This file contains Supplementary Figure 1, the uncropped blots.

  2. 2.

    Reporting Summary

Excel files

  1. 1.

    Supplementary Table 1

    This table contains a list of all the antibodies and reagents used in this study.

  2. 2.

    Supplementary Table 2

    This table contains a list of all the primers used in this study.

  3. 3.

    Supplementary Table 3

    This table contains two lists of up-regulated and down-regulated genes by RNA-Seq of Mettl3 KO and WT Naïve T cells.

  4. 4.

    Supplementary Table 4

    This table contains a list of top 20 up-regulated and down-regulated Ribosome occupancy of Mettl3 KO and WT mRNAs by Ribosome profiling in this study.

  5. 5.

    Supplementary Table 5

    This table contains lists of all the clusters revealed by s4U-Seq of Mettl3 KO and WT naïve T cells in response to IL-7 stimulation over times in this study. Each tab contains one cluster determined by similar time-dependent expression profile changes after IL-7 induction.

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