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Essential role of a ThPOK autoregulatory loop in the maintenance of mature CD4+ T cell identity and function

Nature Immunology volume 22, pages 969–982 (2021)Cite this article

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Abstract

The transcription factor ThPOK (encoded by the Zbtb7b gene) controls homeostasis and differentiation of mature helper T cells, while opposing their differentiation to CD4+ intraepithelial lymphocytes (IELs) in the intestinal mucosa. Thus CD4 IEL differentiation requires ThPOK transcriptional repression via reactivation of the ThPOK transcriptional silencer element (SilThPOK). In the present study, we describe a new autoregulatory loop whereby ThPOK binds to the SilThPOK to maintain its own long-term expression in CD4 T cells. Disruption of this loop in vivo prevents persistent ThPOK expression, leads to genome-wide changes in chromatin accessibility and derepresses the colonic regulatory T (Treg) cell gene expression signature. This promotes selective differentiation of naive CD4 T cells into GITRloPD-1loCD25lo (Triplelo) Treg cells and conversion to CD4+ IELs in the gut, thereby providing dominant protection from colitis. Hence, the ThPOK autoregulatory loop represents a key mechanism to physiologically control ThPOK expression and T cell differentiation in the gut, with potential therapeutic relevance.

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Fig. 1: Genetic mapping of an anti-silencer element in mature CD4 T cells.
Fig. 2: Regulation of anti-silencer by ThPOK binding.
Fig. 3: Loss of anti-silencer destabilizes CD4 T cell phenotype.
Fig. 4: Ablation of anti-silencer leads to deregulation of the CD4 T cell gene expression program.
Fig. 5: Loss of anti-silencer function causes genome-wide change in chromatin accessibility.
Fig. 6: Ablation of anti-silencer promotes differentiation of Triplelo Treg cell subset.
Fig. 7: Anti-silencer-deficient CD4 T cells display anti-colitogenic activity.

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Data availability

All newly generated sequencing data for this study can be accessed at the GEO under accession code GSE168772. All other data that support the findings of this study are available from the corresponding author upon request.

References

  1. Dave, V. P., Allman, D., Keefe, R., Hardy, R. R. & Kappes, D. J. HD mice: a novel mouse mutant with a specific defect in the generation of CD4+ T cells. Proc. Natl Acad. Sci. USA 95, 8187–8192 (1998).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. He, X. et al. The zinc finger transcription factor Th-POK regulates CD4 versus CD8 T-cell lineage commitment. Nature 433, 826–833 (2005).

    Article  CAS  PubMed  Google Scholar 

  3. Keefe, R., Dave, V., Allman, D., Wiest, D. & Kappes, D. J. Regulation of lineage commitment distinct from positive selection. Science 286, 1149–1153 (1999).

    Article  CAS  PubMed  Google Scholar 

  4. Wang, L. et al. The zinc finger transcription factor Zbtb7b represses CD8-lineage gene expression in peripheral CD4+ T cells. Immunity 29, 876–887 (2008).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  5. He, X. et al. CD4-CD8 lineage commitment is regulated by a silencer element at the ThPOK transcription-factor locus. Immunity 28, 346–358 (2008).

    Article  CAS  PubMed  Google Scholar 

  6. Setoguchi, R. et al. Repression of the transcription factor Th-POK by Runx complexes in cytotoxic T cell development. Science 319, 822–825 (2008).

    Article  CAS  PubMed  Google Scholar 

  7. Mookerjee-Basu, J. et al. Functional conservation of a developmental switch in mammals since the Jurassic age. Mol. Biol. Evol. 36, 39–53 (2019).

    Article  CAS  PubMed  Google Scholar 

  8. Vacchio, M. S. et al. A ThPOK-LRF transcriptional node maintains the integrity and effector potential of post-thymic CD4+ T cells. Nat. Immunol. 15, 947–956 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Ciucci, T. et al. The emergence and functional fitness of memory CD4+ T cells require the transcription factor Thpok. Immunity 50, 91–105.e4 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Mucida, D. et al. Transcriptional reprogramming of mature CD4+ helper T cells generates distinct MHC class II–restricted cytotoxic T lymphocytes. Nat. Immunol. 14, 281–289 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Sujino, T. et al. Tissue adaptation of regulatory and intraepithelial CD4+ T cells controls gut inflammation. Science 352, 1581–1586 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Reis, B. S., Rogoz, A., Costa-Pinto, F. A., Taniuchi, I. & Mucida, D. Mutual expression of the transcription factors Runx3 and ThPOK regulates intestinal CD4+ T cell immunity. Nat. Immunol. 14, 271–280 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Fuxman Bass, J. I. et al. Human gene-centered transcription factor networks for enhancers and disease variants. Cell 161, 661–673 (2015).

    Article  CAS  PubMed  Google Scholar 

  14. Reece-Hoyes, J. S. et al. Yeast one-hybrid assays for gene-centered human gene regulatory network mapping. Nat. Methods 8, 1050–1052 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Reece-Hoyes, J. S. et al. Enhanced yeast one-hybrid assays for high-throughput gene-centered regulatory network mapping. Nat. Methods 8, 1059–1064 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Muroi, S. et al. Cascading suppression of transcriptional silencers by ThPOK seals helper T cell fate. Nat. Immunol. 9, 1113–1121 (2008).

    Article  CAS  PubMed  Google Scholar 

  17. 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 

  18. Zhou, W. et al. Single-cell analysis reveals regulatory gene expression dynamics leading to lineage commitment in early T cell development. Cell Syst. 9, 321–337.e9 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Vacchio, M. S. et al. A Thpok-directed transcriptional circuitry promotes Bcl6 and Maf expression to orchestrate T follicular helper differentiation. Immunity 51, 465–478.e6 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Istaces, N. et al. EOMES interacts with RUNX3 and BRG1 to promote innate memory cell formation through epigenetic reprogramming. Nat. Commun. 10, 3306 (2019).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  21. Zhang, J. A., Mortazavi, A., Williams, B. A., Wold, B. J. & Rothenberg, E. V. Dynamic transformations of genome-wide epigenetic marking and transcriptional control establish T cell identity. Cell 149, 467–482 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Zheng, S., Papalexi, E., Butler, A., Stephenson, W. & Satija, R. Molecular transitions in early progenitors during human cord blood hematopoiesis. Mol. Syst. Biol. 14, e8041 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  23. Diao, H. & Pipkin, M. E. Stability and flexibility in chromatin structure and transcription underlies memory CD8 T-cell differentiation. F1000Res. 8, 1278 (2019).

    Article  CAS  Google Scholar 

  24. Chen, H. et al. Single-cell trajectories reconstruction, exploration and mapping of omics data with STREAM. Nat. Commun. 10, 1903 (2019).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  25. Whyte, W. A. et al. Master transcription factors and mediator establish super-enhancers at key cell identity genes. Cell 53, 307–319 (2013).

    Article  CAS  Google Scholar 

  26. Vahedi, G. et al. Super-enhancers delineate disease-associated regulatory nodes in T cells. Nature 520, 558–562 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Khan, A. & Zhang, X. dbSUPER: a database of super-enhancers in mouse and human genome. Nucleic Acids Res. 44, D164–D171 (2016).

    Article  CAS  PubMed  Google Scholar 

  28. Snook, J. P., Kim, C. & Williams, M. A. TCR signal strength controls the differentiation of CD4+ effector and memory T cells. Sci. Immunol. 3, eaas9103 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  29. Carpenter, A. C. et al. Control of regulatory T cell differentiation by the transcription factors Thpok and LRF. J. Immunol. 199, 1716–1728 (2017).

    Article  CAS  PubMed  Google Scholar 

  30. Wyss, L. et al. Affinity for self antigen selects Treg cells with distinct functional properties. Nat. Immunol. 17, 1093–1101 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Miragaia, R. J. et al. Single-cell transcriptomics of regulatory T cells reveals trajectories of tissue adaptation. Immunity 50, 493–504.e7 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Neurath, M., Fuss, I. & Strober, W. TNBS-colitis. Int. Rev. Immunol. 19, 51–62 (2000).

    Article  CAS  PubMed  Google Scholar 

  33. Powrie, F. et al. Inhibition of Th1 responses prevents inflammatory bowel disease in scid mice reconstituted with CD45RBhi CD4+ T cells. Immunity 1, 553–562 (1994).

    Article  CAS  PubMed  Google Scholar 

  34. Larsson, A. J. M. et al. Genomic encoding of transcriptional burst kinetics. Nature 565, 251–254 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Suter, D. M. et al. Mammalian genes are transcribed with widely different bursting kinetics. Science 332, 472–474 (2011).

    Article  CAS  PubMed  Google Scholar 

  36. Chubb, J. R., Trcek, T., Shenoy, S. M. & Singer, R. H. Transcriptional pulsing of a developmental gene. Curr. Biol. 16, 1018–1025 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Raj, A., Peskin, C. S., Tranchina, D., Vargas, D. Y. & Tyagi, S. Stochastic mRNA synthesis in mammalian cells. PLoS Biol. 4, e309 (2006).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  38. De Obaldia, M. E., Bell, J. J. & Bhandoola, A. Early T-cell progenitors are the major granulocyte precursors in the adult mouse thymus. Blood 121, 64–71 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  39. Rothenberg, E. V., Hosokawa, H. & Ungerback, J. Mechanisms of action of hematopoietic transcription factor PU.1 in initiation of T-cell development. Front. Immunol. 10, 228 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Takada, K. & Jameson, S. C. Naive T cell homeostasis: from awareness of space to a sense of place. Nat. Rev. Immunol. 9, 823–832 (2009).

    Article  CAS  PubMed  Google Scholar 

  41. Tu, E. et al. T cell receptor-regulated TGF-β type I receptor expression determines T cell quiescence and activation. Immunity 48, 745–759.e6 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Marshall, N. B. et al. NKG2C/E marks the unique cytotoxic CD4 T cell subset, ThCTL, generated by influenza infection. J. Immunol. 198, 1142–1155 (2017).

    Article  CAS  PubMed  Google Scholar 

  43. Pearce, E. L. et al. Control of effector CD8+ T cell function by the transcription factor eomesodermin. Science 302, 1041–1043 (2003).

    Article  CAS  PubMed  Google Scholar 

  44. Curran, M. A. et al. Systemic 4-1BB activation induces a novel T cell phenotype driven by high expression of eomesodermin. J. Exp. Med. 210, 743–755 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Hirschhorn-Cymerman, D. et al. Induction of tumoricidal function in CD4+ T cells is associated with concomitant memory and terminally differentiated phenotype. J. Exp. Med. 209, 2113–2126 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Qui, H. Z. et al. CD134 plus CD137 dual costimulation induces eomesodermin in CD4 T cells to program cytotoxic Th1 differentiation. J. Immunol. 187, 3555–3564 (2011).

    Article  CAS  PubMed  Google Scholar 

  47. Wagner, D. H. Jr. et al. Expression of CD40 identifies a unique pathogenic T cell population in type 1 diabetes. Proc. Natl Acad. Sci. USA 99, 3782–3787 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Bilate, A. N. et al. T cell receptor is required for differentiation, but not maintenance, of intestinal CD4+ intraepithelial lymphocytes. Immunity 53, 1001–1014.e20 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Waid, D. M., Vaitaitis, G. M. & Wagner, D. H. Jr. Peripheral CD4loCD40+ auto-aggressive T cell expansion during insulin-dependent diabetes mellitus. Eur. J. Immunol. 34, 1488–1497 (2004).

    Article  CAS  PubMed  Google Scholar 

  50. Flamand, L. et al. Activation of CD8+ T lymphocytes through the T cell receptor turns on CD4 gene expression: implications for HIV pathogenesis. Proc. Natl Acad. Sci. USA 95, 3111–3116 (1998).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Buenrostro, J. D., Wu, B., Chang, H. Y. & Greenleaf, W. J. ATAC-seq: a method for assaying chromatin accessibility genome-wide. Curr. Protoc. Mol. Biol. 109, 21.29.1–21.29.9 (2015).

    Article  Google Scholar 

  52. Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Hoffman, M. M. et al. Integrative annotation of chromatin elements from ENCODE data. Nucleic Acids Res. 41, 827–841 (2013).

    Article  CAS  PubMed  Google Scholar 

  54. Quinlan, A. R. BEDTools: the Swiss-army tool for genome feature analysis. Curr. Protoc. Bioinform. 47, 11.12.1–11.12.34 (2014).

    Article  Google Scholar 

  55. Feng, J., Liu, T., Qin, B., Zhang, Y. & Liu, X. S. Identifying ChIP-seq enrichment using MACS. Nat. Protoc. 7, 1728–1740 (2012).

    Article  CAS  PubMed  Google Scholar 

  56. Li, H. & Durbin, R. Fast and accurate long-read alignment with Burrows–Wheeler transform. Bioinformatics 26, 589–595 (2010).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  57. Heinz, S. et al. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol. Cell 38, 576–589 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Anders, S., Pyl, P. T. & Huber, W. HTSeq—a Python framework to work with high-throughput sequencing data. Bioinformatics 31, 166–169 (2015).

    Article  CAS  PubMed  Google Scholar 

  59. Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  60. Huang, D. W., Sherman, B. T. & Lempicki, R. A. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat. Protoc. 4, 44–57 (2009).

    Article  CAS  Google Scholar 

  61. Mucida, D. et al. Reciprocal TH17 and regulatory T cell differentiation mediated by retinoic acid. Science 317, 256–260 (2007).

    Article  CAS  PubMed  Google Scholar 

  62. Antoniou, E. et al. The TNBS-induced colitis animal model: an overview. Ann. Med. Surg. 11, 9–15 (2016).

    Article  Google Scholar 

  63. Hagège, H. et al. Quantitative analysis of chromosome conformation capture assays (3C-qPCR). Nat. Protoc. 2, 1722 (2007).

    Article  PubMed  CAS  Google Scholar 

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Acknowledgements

This work was supported by NIH grants (nos. R01 AI068907 and R01 GM107179 (to D.J.K.), R35 GM122502 (to J.F.B. and A.J.M.W.), R01CA227629 and R01CA218133 (to S.G.) and P30 CA006927 (FCCC Comprehensive Cancer Center Core Grant)). We thank the following core facilities of the Fox Chase Cancer Center for their assistance: Flow Cytometry, Cell Culture, DNA Sequencing, Genomic and Laboratory Animal. We thank D.L. Wiest and G. Rall for critical comments and suggestions on the manuscript.

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Authors and Affiliations

  1. Blood Cell Development and Cancer, Fox Chase Cancer Center, Philadelphia, PA, USA

    Jayati Basu, Jikun Zha, Xiang Hua, Lu Ge, Emmanuelle Nicolas, Philip Czyzewicz & Dietmar J. Kappes

  2. Laboratory of Mucosal Immunology, The Rockefeller University, New York, NY, USA

    Bernardo S. Reis & Daniel Mucida

  3. Biostatistics and Bioinformatics, Fox Chase Cancer Center, Philadelphia, PA, USA

    Suraj Peri

  4. Division of Immunobiology and Center for Systems Immunology, Cincinnati Children’s Hospital 10 Medical Center, Cincinnati, OH, USA

    Kyle Ferchen & H. Leighton Grimes

  5. Cancer Signaling and Epigenetics, Fox Chase Cancer Center, Philadelphia, PA, USA

    Kathy Q. Cai

  6. Cancer Biology, Fox Chase Cancer Center, Philadelphia, PA, USA

    Yinfei Tan

  7. Program in Systems Biology, Program in Molecular Medicine, University of Massachusetts Medical School, Worcester, MA, USA

    Juan I. Fuxman Bass & Albertha J. M. Walhout

  8. Cancer Prevention and Control, Fox Chase Cancer Center, Philadelphia, PA, USA

    Sergei I. Grivennikov

  9. Cedars-Sinai Medical Center, Departments of Medicine and Biomedical Sciences, Samuel Oschin Comprehensive Cancer Institute, Los Angeles, CA, USA

    Sergei I. Grivennikov

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Contributions

J.B. and D.J.K. conceived the project. J.B., B.S.R., S.P., X.H., A.J.M.W., H.L.G., S.G., D.M. and D.J.K. carried out the methodology. J.B., B.S.R., S.P., J.Z., X.H., L.G., K.F., E.N., P.C., K.Q.C., Y.T., J.I.F.B. and D.J.K. performed the investigations. J.B. and D.J.K. wrote the original draft of the manuscript. J.B., A.J.M.W., S.G., D.M. and D.J.K. reviewed and edited the manuscript. D.J.K. acquired the funding. J.B. and D.J.K. were overall supervisors.

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Correspondence to Dietmar J. Kappes.

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Peer review information Nature Immunology thanks Jonathan Kaye and Harinder Singh for their contribution to the peer review of this work. Laurie 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.

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Extended data

Extended Data Fig. 1 Ablation of anti-silencer does not substantially disrupt development of class II-restricted thymocytes.

a, Flow cytometric analysis of CD4, and CD8a expression in total thymocytes (top row), or gated mature (TCRβ + CD69- CD24- CD62L + ) thymocytes of WT mice and homozygous ThPOKΔOB11/ΔOB11 mice, as indicated. A total of 4 animals of each genotype were analyzed over 2 independent experiments. Plots at right indicate % of SP CD4, CD8, and CD4 + 8 + (DP) thymocytes among total thymocytes (top panel), or gated mature thymocytes (as defined in panel a) (n = 4, for each strain). b, RNA was collected from freshly sorted thymocyte subsets, as indicated, before probing for ThPOK expression by qPCR. Data represent 2 technical replicates, each derived from pooled RNA of 3 animals. Data are presented as mean values + /- SEM. Experiment was repeated 3 times. c) Flow cytometric analysis of TCRβ and CD69 expression in total thymocytes (top row), or gated mature thymocytes of β2m-/- ThPOK + /+ and β2m-/- ThPOKΔOB11/ΔOB11 mice, as indicated. Data are representative of 6 animals of each genotype that were analyzed in 3 separate experiments.

Extended Data Fig. 2 Functional analysis of ThPOK binding sites in anti-silencer.

a, EMSA analysis, using the 100 bp OB11 region (lanes 1-4) or EBNA control DNA (lanes 5,6) as probes. Biotinylated probes were incubated with cell extracts from NIH 3T3 cells transfected with empty vector, Fl-ThPOK or EBNA expression constructs, as indicated. In some lanes mutant OB11 probes in which the consensus ThPOK binding sites 1 (lane 4) or 3 (lane 3) are disrupted were added. Experiment was repeated 3 times with similar results. b, Organization of mouse ThPOK gene (top), and diagram of silencer deletion mutants (bottom). Black boxes, blue boxes, arrows, and red boxes indicate exons, enhancers, silencers and promoters, respectively. Deletions within the silencer are indicated by thin black lines. “R” indicates positions of conserved Runx binding sites. c, Flow cytometric analysis of CD4, and CD8a expression in gated TCRβ + PBLs of WT mice and homozygous mutant lines, as designated in panel b. A total of 9 animals of each genotype were analyzed in 3 separate experiments. d, Sequence of WT murine OB11 region (top row) aligned with corresponding human sequence (second row; mismatches between human and mouse are highlighted in yellow), as well as sequences of indicated mutants used in EMSA or for generation of mutant alleles.

Extended Data Fig. 3 Ablation of anti-silencer leads to transient transcription at ThPOK locus.

a, Flow cytometric analysis of GFP expression in gated CD4hi (green), CD4lo/- (orange), DP (CD4 + CD8 + ) (red), or CD8 PBLs (middle) of ThPOKGFP/+ or ThPOKGFP/ΔOB11 mice. Black line indicates MFI of GFP expression by ThPOKGFP/+ CD4 T cells, for comparison (same mice as in Fig. 3c). b, Flow cytometric analysis of GFP expression by gated CD4hi, CD4lo/-, CD4 + CD8 + (DP), and CD8 PBLs from RAG-/- hosts reconstituted with indicated sorted T cell subsets from ThPOKGFP/+ or ThPOKΔOB11.GFP/ΔOB11 mice, as indicated (same mice as in Fig. 3e). c) Surface TCRβ and CD3ε expression of indicated SilΔOB11/ΔOB11 or WT T cell subset after activation.

Extended Data Fig. 4 Genes misregulated upon anti-silencer ablation are often direct targets of ThPOK and Runx3 binding.

a, Heat map displaying relative expression of genes associated with ETP-DN2 transition for indicated ThPOKΔOB11/ΔOB11 and WT T cell subsets. Red indicates increased gene expression levels; blue indicates decreased levels. b, Volcano plots illustrating gene expression differences between individual sorted ThPOKΔOB11/ΔOB11 subsets and WT CD4 T cells (Wald 2-sided test). The grey dots represent genes differentially expressed (adjusted P < 0.05) between samples. Genes with the largest negative or positive standardized mean difference are marked. Note diminished ThPOK (Zbt7b) expression in all samples. c, ThPOK-ChIP and Runx3-Chip profiles and Refseq gene positions across chromosome regions containing Runx3, CD4 and ThPOK (Zbtb7b) genes, as marked. Input is already subtracted for Runx3 peaks. d, Venn diagram indicating intersection between ThPOK and Runx3 ChIP-seq peaks (from WT CD4 and WT CD8 cells, respectively).

Extended Data Fig. 5 Altered chromatin accessibility in ThPOKΔOB11/ΔOB11 CD4lo T cells.

a, Comparison of distribution of RNA-seq reads (top row), ATAC-seq reads (second row, top), genes (second row, bottom), and ThPOK-ChIP seq reads per 100 kb bins across one chromosome (Chr11). b, TF consensus motif enrichment in DACRs selectively open in ThPOKΔOB11/ ΔOB11 CD4lo T cells or WT CD4 T cells, as indicated (Wilcoxon Rank Sum Test with p value adjusted by Benjamini Hochberg method). c, Venn diagram illustrating intersection between super-enhancers from Th cells, thymocytes and proB cells, as indicated.

Extended Data Fig. 6 Effect Anti-silencer element ablation on CD4 T cell proliferation and cytokine gene expression.

a, Bar graph denoting the percentage of cells assigned to each division cycle based on CFSE dilution following stimulation with anti-TCRβ (bottom) or anti-CD3ε/CD28 (top) for 48 h. b, Time course of phospho-ERK expression in response to anti- TCRβ stimulation of indicated WT or OB11 T cell subsets. c, d, Bar graphs illustrating deregulated expression of indicated mRNAs according to qPCR. Sorted OB11 or WT T cell subsets were cultured with anti-TCRβ or anti-CD3ε/CD28 stimulation, or in the absence of stimulation, as indicated. N = 2 (technical replicates, each derived from pooled RNA of 4 animals for each genotype). Experiment was repeated twice. Data are presented as mean values + /- SEM. e, ThPOK-ChIP-seq (for WT CD4 T cells, biological triplicates; pink tracks), and ATAC-seq (for ThPOKΔOB11/ΔOB11 CD4lo T cells or WT CD4 T cells, as indicated, biological duplicates; grey tracks) profiles for gene loci.

Extended Data Fig. 7 Colitis induction in WT and ThPOKΔOB11/ΔOB11 mice.

a–d, Bar graphs depicting the percentage of CD45.1+ (a, c) or CD45.2+ (b, d) cells within each indicated intestinal or splenic population. Data is derived from cotransfer experiment depicted in Fig. 7f. Donor cells were sorted from pooled LN samples of 3 CD45.1+ WT or CD45.2+ ThPOKΔOB11.GFP/ΔOB11 mice. N = 4 (# of host animals reconstituted with each indicated cell combination). The experiment was repeated 3 times. e, Image of whole colons, or stained cross-sections of the indicated mouse strains after colitis induction with TNBS. Experiment was repeated 2 times with similar results. f, Frequency of indicated cell type of OX40ΔThPOK or WT origin at indicated organ site following co-transfer of sorted OX40ΔThPOK or WT CD4 T cells (same experiment as in Fig. 7l–n). N = 3 (WT + Ox40 co transfer), or 2 (WT only), and the experiment was repeated 2 times. Data in panels a-d and f are presented as mean values + /- SEM.

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Basu, J., Reis, B.S., Peri, S. et al. Essential role of a ThPOK autoregulatory loop in the maintenance of mature CD4+ T cell identity and function. Nat Immunol 22, 969–982 (2021). https://doi.org/10.1038/s41590-021-00980-8

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