Tet2 and Tet3 in B cells are required to repress CD86 and prevent autoimmunity

Abstract

A contribution of epigenetic modifications to B cell tolerance has been proposed but not directly tested. Here we report that deficiency of ten–eleven translocation (Tet) DNA demethylase family members Tet2 and Tet3 in B cells led to hyperactivation of B and T cells, autoantibody production and lupus-like disease in mice. Mechanistically, in the absence of Tet2 and Tet3, downregulation of CD86, which normally occurs following chronic exposure of self-reactive B cells to self-antigen, did not take place. The importance of dysregulated CD86 expression in Tet2- and Tet3-deficient B cells was further demonstrated by the restriction, albeit not complete, on aberrant T and B cell activation following anti-CD86 blockade. Tet2- and Tet3-deficient B cells had decreased accumulation of histone deacetylase 1 (HDAC1) and HDAC2 at the Cd86 locus. Thus, our findings suggest that Tet2- and Tet3-mediated chromatin modification participates in repression of CD86 on chronically stimulated self-reactive B cells, which contributes, at least in part, to preventing autoimmunity.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: Spontaneous immune cell activation in bDKO mice.
Fig. 2: Lupus-like autoimmune phenotype in bDKO mice.
Fig. 3: Requirement for T–B interaction in initiation and maintenance of autoimmune inflammation.
Fig. 4: Contribution of dysregulated CD86 expression to induction of autoimmune inflammation.
Fig. 5: A diverse BCR repertoire is required to induce autoimmune inflammation.
Fig. 6: Derepressed CD86 on Tet2- and Tet3-deficient B cells in a peripheral tolerance model.
Fig. 7: Integrative analysis for DNA methylation, HDAC binding and acetylated histones regulated by Tet2 and Tet3.
Fig. 8: Molecular mechanism for CD86 repression by Tet2 and Tet3.

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request. The RNA-seq, WGBS-seq and ChIP–seq data reported in this paper are available under Gene Expression Omnibus accession numbers GSE137914, GSE137621 and GSE137666, respectively. Source data for Figs. 16 and 8 are provided with the paper.

References

  1. 1.

    Pelanda, R. & Torres, R. M. Central B-cell tolerance: where selection begins. Cold Spring Harb. Perspect. Biol. 4, a007146 (2012).

    PubMed  PubMed Central  Google Scholar 

  2. 2.

    Goodnow, C. C., Sprent, J., Fazekas de St Groth, B. & Vinuesa, C. G. Cellular and genetic mechanisms of self tolerance and autoimmunity. Nature 435, 590–597 (2005).

    PubMed  CAS  Google Scholar 

  3. 3.

    Nemazee, D. Mechanisms of central tolerance for B cells. Nat. Rev. Immunol. 17, 281–294 (2017).

    PubMed  PubMed Central  CAS  Google Scholar 

  4. 4.

    Goodnow, C. C. Transgenic mice and analysis of B-cell tolerance. Annu. Rev. Immunol. 10, 489–518 (1992).

    PubMed  CAS  Google Scholar 

  5. 5.

    Cambier, J. C., Gauld, S. B., Merrell, K. T. & Vilen, B. J. B-cell anergy: from transgenic models to naturally occurring anergic B cells? Nat. Rev. Immunol. 7, 633–643 (2007).

    PubMed  PubMed Central  CAS  Google Scholar 

  6. 6.

    Shlomchik, M. J. Sites and stages of autoreactive B cell activation and regulation. Immunity 28, 18–28 (2008).

    PubMed  CAS  Google Scholar 

  7. 7.

    Rawlings, D. J., Metzler, G., Wray-Dutra, M. & Jackson, S. W. Altered B cell signalling in autoimmunity. Nat. Rev. Immunol. 17, 421–436 (2017).

    PubMed  PubMed Central  CAS  Google Scholar 

  8. 8.

    Wu, H. et al. Epigenetic regulation in B-cell maturation and its dysregulation in autoimmunity. Cell. Mol. Immunol. 15, 676–684 (2018).

    PubMed  PubMed Central  CAS  Google Scholar 

  9. 9.

    Alberghini, F., Petrocelli, V., Rahmat, M. & Casola, S. An epigenetic view of B-cell disorders. Immunol. Cell Biol. 93, 253–260 (2015).

    PubMed  CAS  Google Scholar 

  10. 10.

    Richardson, B. DNA methylation and autoimmune disease. Clin. Immunol. 109, 72–79 (2003).

    PubMed  CAS  Google Scholar 

  11. 11.

    Mazzone, R. et al. The emerging role of epigenetics in human autoimmune disorders. Clin. Epigenetics 11, 34 (2019).

    PubMed  PubMed Central  Google Scholar 

  12. 12.

    Pastor, W. A., Aravind, L. & Rao, A. TETonic shift: biological roles of TET proteins in DNA demethylation and transcription. Nat. Rev. Mol. Cell Biol. 14, 341–356 (2013).

    PubMed  PubMed Central  CAS  Google Scholar 

  13. 13.

    Wu, H. & Zhang, Y. Reversing DNA methylation: mechanisms, genomics, and biological functions. Cell 156, 45–68 (2014).

    PubMed  PubMed Central  CAS  Google Scholar 

  14. 14.

    Zhang, Q. et al. Tet2 is required to resolve inflammation by recruiting Hdac2 to specifically repress IL-6. Nature 525, 389–393 (2015).

    PubMed  PubMed Central  CAS  Google Scholar 

  15. 15.

    Xue, S. et al. TET3 inhibits type I IFN production independent of DNA demethylation. Cell Rep. 16, 1096–1105 (2016).

    PubMed  CAS  Google Scholar 

  16. 16.

    Tsagaratou, A., Lio, C. J., Yue, X. & Rao, A. TET methylcytosine oxidases in T cell and B cell development and function. Front. Immunol. 8, 220 (2017).

    PubMed  PubMed Central  Google Scholar 

  17. 17.

    Lio, C. J. & Rao, A. TET enzymes and 5hmC in adaptive and innate immune systems. Front. Immunol. 10, 210 (2019).

    PubMed  PubMed Central  CAS  Google Scholar 

  18. 18.

    Cimmino, L. et al. TET1 is a tumor suppressor of hematopoietic malignancy. Nat. Immunol. 16, 653–662 (2015).

    PubMed  PubMed Central  CAS  Google Scholar 

  19. 19.

    Rickert, R. C., Roes, J. & Rajewsky, K. B lymphocyte-specific, Cre-mediated mutagenesis in mice. Nucleic Acids Res. 25, 1317–1318 (1997).

    PubMed  PubMed Central  CAS  Google Scholar 

  20. 20.

    Lio, C. W. et al. Tet2 and Tet3 cooperate with B-lineage transcription factors to regulate DNA modification and chromatin accessibility. Elife 5, e18290 (2016).

    PubMed  PubMed Central  Google Scholar 

  21. 21.

    Orlanski, S. et al. Tissue-specific DNA demethylation is required for proper B-cell differentiation and function. Proc. Natl Acad. Sci. USA 113, 5018–5023 (2016).

    PubMed  CAS  Google Scholar 

  22. 22.

    Audzevich, T. et al. Pre/pro-B cells generate macrophage populations during homeostasis and inflammation. Proc. Natl Acad. Sci. USA 114, E3954–E3963 (2017).

    PubMed  CAS  Google Scholar 

  23. 23.

    Busslinger, M. Transcriptional control of early B cell development. Annu. Rev. Immunol. 22, 55–79 (2004).

    PubMed  CAS  Google Scholar 

  24. 24.

    Choukrallah, M. A. & Matthias, P. The interplay between chromatin and transcription factor networks during B cell development: who pulls the trigger first? Front. Immunol. 5, 156 (2014).

    PubMed  PubMed Central  Google Scholar 

  25. 25.

    Lu, R., Medina, K. L., Lancki, D. W. & Singh, H. IRF-4,8 orchestrate the pre-B-to-B transition in lymphocyte development. Genes Dev. 17, 1703–1708 (2003).

    PubMed  PubMed Central  CAS  Google Scholar 

  26. 26.

    Allman, D. & Pillai, S. Peripheral B cell subsets. Curr. Opin. Immunol. 20, 149–157 (2008).

    PubMed  PubMed Central  CAS  Google Scholar 

  27. 27.

    Pillai, S. & Cariappa, A. The follicular versus marginal zone B lymphocyte cell fate decision. Nat. Rev. Immunol. 9, 767–777 (2009).

    PubMed  CAS  Google Scholar 

  28. 28.

    Liu, Z. et al. The intracellular domains of Notch1 and Notch2 are functionally equivalent during development and carcinogenesis. Development 142, 2452–2463 (2015).

    PubMed  PubMed Central  CAS  Google Scholar 

  29. 29.

    Luning Prak, E. T., Monestier, M. & Eisenberg, R. A. B cell receptor editing in tolerance and autoimmunity. Ann. N.Y. Acad. Sci. 1217, 96–121 (2011).

    PubMed  PubMed Central  Google Scholar 

  30. 30.

    Victora, G. D. & Nussenzweig, M. C. Germinal centers. Annu. Rev. Immunol. 30, 429–457 (2012).

    PubMed  CAS  Google Scholar 

  31. 31.

    Li, W., Titov, A. A. & Morel, L. An update on lupus animal models. Curr. Opin. Rheumatol. 29, 434–441 (2017).

    PubMed  PubMed Central  Google Scholar 

  32. 32.

    Shlomchik, M. J., Craft, J. E. & Mamula, M. J. From T to B and back again: positive feedback in systemic autoimmune disease. Nat. Rev. Immunol. 1, 147–153 (2001).

    PubMed  CAS  Google Scholar 

  33. 33.

    Cyster, J. G. & Goodnow, C. C. Antigen-induced exclusion from follicles and anergy are separate and complementary processes that influence peripheral B cell fate. Immunity 3, 691–701 (1995).

    PubMed  CAS  Google Scholar 

  34. 34.

    Rathmell, J. C., Fournier, S., Weintraub, B. C., Allison, J. P. & Goodnow, C. C. Repression of B7.2 on self-reactive B cells is essential to prevent proliferation and allow Fas-mediated deletion by CD4+ T cells. J. Exp. Med. 188, 651–659 (1998).

    PubMed  PubMed Central  CAS  Google Scholar 

  35. 35.

    Neighbors, M. et al. Breakpoints in immunoregulation required for Th1 cells to induce diabetes. Eur. J. Immunol. 36, 2315–2323 (2006).

    PubMed  CAS  Google Scholar 

  36. 36.

    Yang, W. et al. Meta-analysis followed by replication identifies loci in or near CDKN1B, TET3, CD80, DRAM1, and ARID5B as associated with systemic lupus erythematosus in Asians. Am. J. Hum. Genet. 92, 41–51 (2013).

    PubMed  PubMed Central  CAS  Google Scholar 

  37. 37.

    Demirci, F. Y. et al. Identification of a new susceptibility locus for systemic lupus erythematosus on chromosome 12 in individuals of European ancestry. Arthritis Rheumatol. 68, 174–183 (2016).

    PubMed  PubMed Central  CAS  Google Scholar 

  38. 38.

    Schwartz, R. H. Costimulation of T lymphocytes: the role of CD28, CTLA-4, and B7/BB1 in interleukin-2 production and immunotherapy. Cell 71, 1065–1068 (1992).

    PubMed  CAS  Google Scholar 

  39. 39.

    Schwartz, R. H. T cell anergy. Annu. Rev. Immunol. 21, 305–334 (2003).

    PubMed  CAS  Google Scholar 

  40. 40.

    Martin-Orozco, N. & Dong, C. Inhibitory costimulation and anti-tumor immunity. Semin. Cancer Biol. 17, 288–298 (2007).

    PubMed  PubMed Central  CAS  Google Scholar 

  41. 41.

    Schoeler, K. et al. TET enzymes control antibody production and shape the mutational landscape in germinal centre B cells. FEBS J. 286, 3566–3581 (2019).

    PubMed  PubMed Central  CAS  Google Scholar 

  42. 42.

    Lio, C.J. et al. TET enzymes augment activation-induced deaminase (AID) expression via 5-hydroxymethylcytosine modifications at the Aicda superenhancer. Sci. Immunol. 4, eaau7523 (2019).

  43. 43.

    Kitamura, D., Roes, J., Kuhn, R. & Rajewsky, K. A B cell-deficient mouse by targeted disruption of the membrane exon of the immunoglobulin µ chain gene. Nature 350, 423–426 (1991).

    PubMed  CAS  Google Scholar 

  44. 44.

    Goodnow, C. C. et al. Altered immunoglobulin expression and functional silencing of self-reactive B lymphocytes in transgenic mice. Nature 334, 676–682 (1988).

    PubMed  CAS  Google Scholar 

  45. 45.

    Hashimoto, K., Joshi, S. K. & Koni, P. A. A conditional null allele of the major histocompatibility IA-β chain gene. Genesis 32, 152–153 (2002).

    PubMed  CAS  Google Scholar 

  46. 46.

    Sakakibara, S. et al. Clonal evolution and antigen recognition of anti-nuclear antibodies in acute systemic lupus erythematosus. Sci. Rep. 7, 16428 (2017).

    PubMed  PubMed Central  Google Scholar 

  47. 47.

    Li, Q. Z. et al. Protein array autoantibody profiles for insights into systemic lupus erythematosus and incomplete lupus syndromes. Clin. Exp. Immunol. 147, 60–70 (2007).

    PubMed  PubMed Central  CAS  Google Scholar 

  48. 48.

    Shinnakasu, R. et al. Regulated selection of germinal-center cells into the memory B cell compartment. Nat. Immunol. 17, 861–869 (2016).

    PubMed  CAS  Google Scholar 

  49. 49.

    Tanaka, S. et al. Trim33 mediates the proinflammatory function of Th17 cells. J. Exp. Med. 215, 1853–1868 (2018).

    PubMed  PubMed Central  CAS  Google Scholar 

  50. 50.

    Miura, F., Enomoto, Y., Dairiki, R. & Ito, T. Amplification-free whole-genome bisulfite sequencing by post-bisulfite adaptor tagging. Nucleic Acids Res. 40, e136 (2012).

    PubMed  PubMed Central  CAS  Google Scholar 

  51. 51.

    Miura, F. et al. Highly efficient single-stranded DNA ligation technique improves low-input whole-genome bisulfite sequencing by post-bisulfite adaptor tagging. Nucleic Acids Res. 47, e85 (2019).

    PubMed  PubMed Central  CAS  Google Scholar 

  52. 52.

    Juhling, F. et al. metilene: fast and sensitive calling of differentially methylated regions from bisulfite sequencing data. Genome Res. 26, 256–262 (2016).

    PubMed  PubMed Central  Google Scholar 

  53. 53.

    Zhu, H. et al. Unexpected characteristics of the IFN-γ reporters in nontransformed T cells. J. Immunol. 167, 855–865 (2001).

    PubMed  CAS  Google Scholar 

  54. 54.

    Ise, W. et al. The transcription factor BATF controls the global regulators of class-switch recombination in both B cells and T cells. Nat. Immunol. 12, 536–543 (2011).

    PubMed  PubMed Central  CAS  Google Scholar 

  55. 55.

    von Boehmer, L. et al. Sequencing and cloning of antigen-specific antibodies from mouse memory B cells. Nat. Protoc. 11, 1908–1923 (2016).

    Google Scholar 

  56. 56.

    Rohatgi, S., Ganju, P. & Sehgal, D. Systematic design and testing of nested (RT–)PCR primers for specific amplification of mouse rearranged/expressed immunoglobulin variable region genes from small number of B cells. J. Immunol. Methods 339, 205–219 (2008).

    PubMed  CAS  Google Scholar 

  57. 57.

    Tiller, T., Busse, C. E. & Wardemann, H. Cloning and expression of murine Ig genes from single B cells. J. Immunol. Methods 350, 183–193 (2009).

    PubMed  CAS  Google Scholar 

  58. 58.

    Brochet, X., Lefranc, M. P. & Giudicelli, V. IMGT/V-QUEST: the highly customized and integrated system for IG and TR standardized V-J and V-D-J sequence analysis. Nucleic Acids Res. 36, W503–508 (2008).

    PubMed  PubMed Central  CAS  Google Scholar 

Download references

Acknowledgements

We thank A.C. Chan (Genentech) for providing the anti-CD20 monoclonal antibody, K. Rajewsky (Max Delbruck Center for Molecular Medicine) for the Cd19-Cre and μMT mice, C.C. Goodnow (Garvan Institute of Medical Research) for MD4 and ML5 mice, A. O’Garra (Francis Crick Institute) for TCR7 TCR-transgenic mice, T. Shimaoka (Tokyo University of Science) for anti-CD4 monoclonal antibody, H. Fukuyama for assistance with the RNA-seq experiment, A. Baba for plasmid DNA construction, C. Kawai for assistance with experiments, K. Tanaka for assistance with the computational analysis, and N. Yakushiji-Kaminatsui and H. Sugishita for assistance with the ChIP–seq experiment and data processing. We appreciate the technical assistance from the Research Support Center at the Kyushu University Graduate School of Medical Sciences. This research was partially supported by the Platform Project for Supporting Drug Discovery and Life Science Research (Basis for Supporting Innovative Drug Discovery and Life Science Research (BINDS)) from AMED under grant no. JP19am0101103 and JP19am0101105. This work is supported by research grants from the Ministry of Education, Culture, Sports, Science and Technology (MEXT) and AMED (Grant-in-Aid for Scientific Research (S) for T.K., AMED under grant no. 19gm6110004h0003 and Grant-in-Aid for Scientific Research (B) for Y.B. and Grant-in-Aid for Scientific Research (C) for S.T.).

Author information

Affiliations

Authors

Contributions

S.T. conceived the project, designed the study, performed experiments, analyzed data, prepared and organized the figures and wrote the manuscript. W.I. designed and performed experiments and analyzed data. T. Inoue contributed to BCR repertoire analysis, and A.I. and K. Fujii assisted with experiments. C.O., Y.S. and S.S. performed pathology experiments. M.K. supported experiments. I.M. performed SNP analysis to verify genetic background. J.S. contributed to the ChIP analysis. M.N. generated the targeting constructs for the mice with loxP-flanked Tet genes. H.K. provided the mice with loxP-flanked Tet genes and wrote the manuscript (Fig. 7). P.A.K. provided the mice with loxP-flanked H2-Ab1. I.R. and Q.-Z.L. performed the autoantibody array. K. Fujiki and R.N. contributed to ChIP–seq experiments. K.S. organized the ChIP–seq experiments. H.A. and F.M. analyzed the WGBS-seq data. T. Ito organized the WGBS-seq experiments. E.K. performed almost all of the secondary bioinformatic analysis related to RNA-seq, WGBS-seq and ChIP–seq experiments. Y.B. designed the study, supported experiments and provided important inputs. T.K. designed the study, supported experiments, provided important inputs and wrote the manuscript.

Corresponding authors

Correspondence to Yoshihiro Baba or Tomohiro Kurosaki.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information L. A. Dempsey was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

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

Extended data

Extended Data Fig. 1 Deletion of Tet genes in B cells.

Schematic diagrams of floxed and deletion alleles of Tet2 and Tet3 genes with primer sets for detection of genomic deletion (Upper panel). Genomic PCR for detection of floxed and deletion alleles with genomic DNA purified from T (TCR-b+) and B (CD19+) cells isolated from Tet2 f/f, Tet3 f/f, CD19 Cre-/- (Cre-, n=4) and Tet2 f/f, Tet3 f/f, CD19 Cre+/- (Cre+, n=4) mice (Lower left panels). mRNA expression of Tet genes in T and B cells isolated from bDKO mice measured by quantitative PCR (Lower right panels). β-actin was used for internal control. Data are mean ± SD.

Extended Data Fig. 2 Spleen and lymph nodes of control and bDKO mice.

Spleen and lymph nodes of 6-week-old control (CD19 Cre+/-) and bDKO mice (Tet2 f/f, Tet3 f/f, CD19 Cre+/-). Data are representative of more than five independent experiments.

Extended Data Fig. 3 Gene expression analysis of control and DKO B cell subsets.

MA plots and enrichment GO terms for differential gene expression (analyzed by DEseq2, FDR<0.1) of B220+ AA4.1+, B220+ AA4.1- CD23+ CD21Int and B220+ AA4.1- CD23- CD21lo B cells isolated, by FACS, from spleen of 4-week-old age matched control and bDKO mice (n=3 each). The fast preranked gene set enrichment analysis (GSEA) was performed by using an algorithm for cumulative GSEA-statistic calculation. The significantly affected pathways were represented as red bars.

Supplementary information

Supplementary Information

Supplementary Figs. 1–6.

Reporting Summary

Supplementary Tables 1–19

Supplementary Table 20

Basic statistics for methylome data.

Source data

Source Data Fig. 1

Statistical source data.

Source Data Fig. 2

Statistical source data.

Source Data Fig. 3

Statistical source data.

Source Data Fig. 4

Statistical source data.

Source Data Fig. 5

Statistical source data.

Source Data Fig. 6

Statistical source data.

Source Data Fig. 8

Statistical source data.

Supplementary Data 1

Statistical source data for Supplementary Fig. 1.

Supplementary Data 2

Statistical source data for Supplementary Fig. 2.

Supplementary Data 3

Statistical source data for Supplementary Fig. 4.

Supplementary Data 4

Statistical source data for Supplementary Fig. 6.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Tanaka, S., Ise, W., Inoue, T. et al. Tet2 and Tet3 in B cells are required to repress CD86 and prevent autoimmunity. Nat Immunol 21, 950–961 (2020). https://doi.org/10.1038/s41590-020-0700-y

Download citation