Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Bcl-6 is the nexus transcription factor of T follicular helper cells via repressor-of-repressor circuits

Nature Immunology volume 21, pages 777–789 (2020)Cite this article

Subjects

Abstract

T follicular helper (TFH) cells are a distinct type of CD4+ T cells that are essential for most antibody and B lymphocyte responses. TFH cell regulation and dysregulation is involved in a range of diseases. Bcl-6 is the lineage-defining transcription factor of TFH cells and its activity is essential for TFH cell differentiation and function. However, how Bcl-6 controls TFH biology has largely remained unclear, at least in part due to the intrinsic challenges of connecting repressors to gene upregulation in complex cell types with multiple possible differentiation fates. Multiple competing models were tested here by a series of experimental approaches to determine that Bcl-6 exhibits negative autoregulation and controls pleiotropic attributes of TFH differentiation and function, including migration, costimulation, inhibitory receptors and cytokines, via multiple repressor-of-repressor gene circuits.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: TFH differentiation is not the default pathway.
Fig. 2: Bcl-6 exhibits direct negative autoregulatory feedback.
Fig. 3: A testable simple circuitry model of TFH differentiation.
Fig. 4: Bcl-6 drives CXCR5 expression via repression of Id2-E2A pathway.
Fig. 5: Integrated analysis of multiple genetic backgrounds and data types.
Fig. 6: Identification of candidate TFs.
Fig. 7: Identification of Runx2, Runx3 and GATA-3 as repressors of TFH genes, acting downstream of Bcl-6.
Fig. 8: Identification of Klf2 as a repressor acting downstream of Bcl-6 regulating major TFH genes.

Similar content being viewed by others

Data availability

RNA-seq and ATAC–seq data were deposited to the Gene Expression Omnibus (GEO) under the GSE140187 super series. Scripts for analysis are available on Github: https://github.com/ScrippsPipkinLab/JYC_DataAnalysis. All other data that support the findings of this study are available from the corresponding author upon request.

References

  1. Crotty, S. T follicular helper cell biology: a decade of discovery and diseases. Immunity 50, 1132–1148 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Vinuesa, C. G., Linterman, M. A., Yu, D. & MacLennan, I. C. M. Follicular helper T cells. Annu. Rev. Immunol. 34, 335–368 (2016).

    Article  CAS  PubMed  Google Scholar 

  3. Johnston, R. J. et al. Bcl6 and Blimp1 are reciprocal and antagonistic regulators of T follicular helper cell differentiation. Science 325, 1006–1010 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Yu, D. et al. The transcriptional repressor Bcl-6 directs T follicular helper cell lineage commitment. Immunity 31, 457–468 (2009).

    Article  CAS  PubMed  Google Scholar 

  5. Nurieva, R. I. et al. Bcl6 mediates the development of T follicular helper cells. Science 325, 1001–1005 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Crotty, S. T follicular helper cell differentiation, function, and roles in disease. Immunity 41, 529–542 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. 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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Kroenke, M. A. et al. Bcl6 and Maf cooperate to instruct human follicular helper CD4 T cell differentiation. J. Immunol. 188, 3734–3744 (2012).

    Article  CAS  PubMed  Google Scholar 

  9. Johnston, R. J., Choi, Y. S., Diamond, J. A., Yang, J. A. & Crotty, S. STAT5 is a potent negative regulator of TFH cell differentiation. J. Exp. Med. 209, 243–250 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Choi, Y. S., Eto, D., Yang, J. A., Lao, C. & Crotty, S. Cutting edge: STAT1 is required for IL-6-mediated Bcl6 induction for early follicular helper cell differentiation. J. Immunol. 190, 3049–3053 (2013).

    Article  CAS  PubMed  Google Scholar 

  11. Wang, H. et al. The transcription factor Foxp1 is a critical negative regulator of the differentiation of follicular helper T cells. Nat. Immunol. 15, 667–675 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Stone, E. L. et al. ICOS coreceptor signaling inactivates the transcription factor FOXO1 to promote Tfh cell differentiation. Immunity 42, 239–251 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Lee, J.-Y. et al. The transcription factor KLF2 restrains CD4+ T follicular helper cell differentiation. Immunity 42, 252–264 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Weber, J. P. et al. ICOS maintains the T follicular helper cell phenotype by down-regulating Krüppel-like factor 2. J. Exp. Med. 212, 217–233 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Krishnamoorthy, V. et al. The IRF4 gene regulatory module functions as a read-write integrator to dynamically coordinate T helper cell fate. Immunity 47, 481–497.e7 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Kim, C. J. et al. The transcription factor Ets1 suppresses T follicular helper type 2 cell differentiation to halt the onset of systemic lupus erythematosus. Immunity 49, 1034–1048.e8 (2018).

    Article  CAS  PubMed  Google Scholar 

  17. Lahmann, A. et al. Bach2 controls T follicular helper cells by direct repression of Bcl-6. J. Immunol. 202, 2229–2239 (2019).

    Article  CAS  PubMed  Google Scholar 

  18. Geng, J. et al. Bach2 negatively regulates T follicular helper cell differentiation and is critical for CD4+T cell memory. J. Immunol. 202, 2991–2998 (2019).

    Article  CAS  PubMed  Google Scholar 

  19. Choi, Y. S. et al. LEF-1 and TCF-1 orchestrate TFH differentiation by regulating differentiation circuits upstream of the transcriptional repressor Bcl6. Nat. Immunol. 16, 980–990 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Xu, L. et al. The transcription factor TCF-1 initiates the differentiation of TFH cells during acute viral infection. Nat. Immunol. 16, 991–999 (2015).

    Article  CAS  PubMed  Google Scholar 

  21. Wu, T. et al. TCF1 is required for the T follicular helper cell response to viral infection. Cell Rep. 12, 2099–2110 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Shaw, L. A. et al. Id2 reinforces TH1 differentiation and inhibits E2A to repress TFH differentiation. Nat. Immunol. 17, 834–843 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Liu, X. et al. Transcription factor achaete-scute homologue 2 initiates follicular T-helper-cell development. Nature 507, 513–518 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Hatzi, K. et al. BCL6 orchestrates Tfh cell differentiation via multiple distinct mechanisms. J. Exp. Med. 212, 539–553 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Liu, X. et al. Genome-wide analysis identifies Bcl6-controlled regulatory networks during T follicular helper cell differentiation. Cell Rep. 14, 1735–1747 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Crotty, S., Johnston, R. J. & Schoenberger, S. P. Effectors and memories: Bcl6 and Blimp1 in T and B lymphocyte differentiation. Nat. Immunol. 11, 114–120 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Crotty, S. Follicular helper CD4 T cells (TFH). Annu. Rev. Immunol. 29, 621–663 (2011).

    Article  CAS  PubMed  Google Scholar 

  28. Nance, J. P. et al. Bcl6 middle domain repressor function is required for T follicular helper cell differentiation and utilizes the corepressor MTA3. Proc. Natl Acad. Sci. USA 112, 13324–13329 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Xie, M. M. et al. Bcl6 promotes follicular helper T-cell differentiation and PD-1 expression in a Blimp1-independent manner in mice. Eur. J. Immunol. 47, 1136–1141 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Mendez, L. M. et al. CtBP is an essential corepressor for BCL6 autoregulation. Mol. Cell. Biol. 28, 2175–2186 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Huynh, K. D. & Bardwell, V. J. The BCL-6 POZ domain and other POZ domains interact with the co-repressors N-CoR and SMRT. Oncogene 17, 2473–2484 (1998).

    Article  CAS  PubMed  Google Scholar 

  32. Bartfeld, D. et al. DNA recognition by the RUNX1 transcription factor is mediated by an allosteric transition in the RUNT domain and by DNA bending. Structure 10, 1395–1407 (2002).

    Article  CAS  PubMed  Google Scholar 

  33. Hiramatsu, Y. et al. c-Maf activates the promoter and enhancer of the IL-21 gene, and TGF-β inhibits c-Maf-induced IL-21 production in CD4+ T cells. J. Leukoc. Biol. 87, 703–712 (2010).

    Article  CAS  PubMed  Google Scholar 

  34. Sahoo, A. et al. Batf is important for IL-4 expression in T follicular helper cells. Nat. Commun. 6, 7997 (2015).

    Article  CAS  PubMed  Google Scholar 

  35. Hatzi, K. et al. A hybrid mechanism of action for BCL6 in B cells defined by formation of functionally distinct complexes at enhancers and promoters. Cell Rep. 4, 578–588 (2013).

    Article  CAS  PubMed  Google Scholar 

  36. Pasqualucci, L. & Dalla Favera, R. Genetics of diffuse large B-cell lymphoma. Blood 131, 2307–2319 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Kusam, S., Toney, L. M., Sato, H. & Dent, A. L. Inhibition of Th2 differentiation and GATA-3 expression by BCL-6. J. Immunol. 170, 2435–2441 (2003).

    Article  CAS  PubMed  Google Scholar 

  38. Kwon, H.-K., Chen, H.-M., Mathis, D. & Benoist, C. Different molecular complexes that mediate transcriptional induction and repression by FoxP3. Nat. Immunol. 486, 549–1248 (2017).

    Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Iwata, S. et al. The transcription factor T-bet limits amplification of type I IFN transcriptome and circuitry in T helper 1 cells. Immunity 46, 983–991.e4 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Vahedi, G. et al. Helper T-cell identity and evolution of differential transcriptomes and epigenomes. Immunol. Rev. 252, 24–40 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  42. Mackay, L. K. et al. Hobit and Blimp1 instruct a universal transcriptional program of tissue residency in lymphocytes. Science 352, 459–463 (2016).

    Article  CAS  PubMed  Google Scholar 

  43. Masson, F. et al. Id2-mediated inhibition of E2A represses memory CD8+ T cell differentiation. J. Immunol. 190, 4585–4594 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Oxenius, A., Bachmann, M. F., Zinkernagel, R. M. & Hengartner, H. Virus‐specific major MHC class II‐restricted TCR‐transgenic mice: effects on humoral and cellular immune responses after viral infection. Eur. J. Immunol. 28, 390–400 (1998).

    Article  CAS  PubMed  Google Scholar 

  45. Kaji, T. et al. Distinct cellular pathways select germline-encoded and somatically mutated antibodies into immunological memory. J. Exp. Med. 209, 2079–2097 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Shapiro-Shelef, M. et al. Blimp-1 is required for the formation of immunoglobulin secreting plasma cells and pre-plasma memory B cells. Immunity 19, 607–620 (2003).

    Article  CAS  PubMed  Google Scholar 

  47. Rutishauser, R. L. et al. Transcriptional repressor Blimp-1 promotes CD8+ T cell terminal differentiation and represses the acquisition of central memory T cell properties. Immunity 31, 296–308 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Wang, D. et al. The transcription factor Runx3 establishes chromatin accessibility of cis-regulatory landscapes that drive memory cytotoxic T lymphocyte formation. Immunity 48, 659–674.e6 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Rosenbauer, F. et al. Lymphoid cell growth and transformation are suppressed by a key regulatory element of the gene encoding PU.1. Nat. Genet. 38, 27–37 (2006).

    Article  CAS  PubMed  Google Scholar 

  50. Montague, T. G., Cruz, J. M., Gagnon, J. A., Church, G. M. & Valen, E. CHOPCHOP: a CRISPR/Cas9 and TALEN web tool for genome editing. Nucleic Acids Res. 42, W401–W407 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Seumois, G. et al. Transcriptional profiling of Th2 cells identifies pathogenic features associated with asthma. J. Immunol. 197, 655–664 (2016).

    Article  CAS  PubMed  Google Scholar 

  52. Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. Series B Stat. Methodol. 57, 289–300 (1995).

    Google Scholar 

  53. Raykov, Y. P., Boukouvalas, A., Baig, F. & Little, M. A. What to do when K-means clustering fails: a simple yet principled alternative algorithm. PLoS ONE 11, e0162259 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  54. Subramanian, A. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA 102, 15545–15550 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Jain, R. et al. Interleukin-23-induced transcription factor Blimp-1 promotes pathogenicity of T helper 17 cells. Immunity 44, 131–142 (2016).

    Article  CAS  PubMed  Google Scholar 

  56. Yu, B. et al. Epigenetic landscapes reveal transcription factors that regulate CD8+ T cell differentiation. Nat. Immunol. 18, 573–582 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. 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 

  58. Pedregosa, F. et al. Scikit-learn: machine learning in Python. J. Mach. Learn. Res. 12, 2825–2830 (2011).

    Google Scholar 

  59. Wingender, E., Schoeps, T., Haubrock, M., Krull, M. & Dönitz, J. TFClass: expanding the classification of human transcription factors to their mammalian orthologs. Nucleic Acids Res. 46, D343–D347 (2018).

    Article  CAS  PubMed  Google Scholar 

  60. Li, Z. et al. Identification of transcription factor binding sites using ATAC-seq. Genome Biol. 20, 45 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  61. Stormo, G. D. Modeling the specificity of protein-DNA interactions. Quant. Biol. 1, 115–130 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Li, F. et al. Ezh2 programs TFH differentiation by integrating phosphorylation-dependent activation of Bcl6 and polycomb-dependent repression of p19Arf. Nat. Commun. 9, 5452 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank C. Kim, L. Boggeman, D. Hinz and C. Dillingham of the La Jolla Insitute for Immunology (LJI) Flow Cytometry Core Facility for cell sorting; J. Greenbaum and A. Sethi of the LJI Bioinformatics core for bioinformatics analysis; G. Seumois and J. Day of the LJI Sequencing core; and K. Jepsen of the University of California San Diego IGM sequencing core for consultation. We thank MaxCyte for generously providing the MaxCyte ATX electroporator and reagents. This work was funded by grants from the US National Institutes of Health (NIH), including the National Institute of Allergy and Infectious Diseases (NIAID) U19 AI109976 and NIAID R01 AI072543, NIH S10 RR027366 (LJI) and internal LJI institutional funds to S.C.

Author information

Authors and Affiliations

  1. Center for Infectious Disease and Vaccine Research, La Jolla Institute for Immunology, La Jolla, CA, USA

    Jinyong Choi, Caterina E. Faliti, Jacquelyn Truong, Meghan Rossi, Simon Bélanger & Shane Crotty

  2. Department of Immunology and Microbiology, The Scripps Research Institute, Jupiter, FL, USA

    Huitian Diao & Matthew E. Pipkin

  3. Division of Biological Sciences, University of California, San Diego, La Jolla, CA, USA

    Bingfei Yu & Ananda W. Goldrath

  4. Department of Medicine, Division of Infectious Diseases and Global Public Health, University of California, San Diego, La Jolla, CA, USA

    Shane Crotty

Authors
  1. Jinyong Choi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Huitian Diao
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Caterina E. Faliti
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jacquelyn Truong
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Meghan Rossi
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Simon Bélanger
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Bingfei Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Ananda W. Goldrath
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Matthew E. Pipkin
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Shane Crotty
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

J.C. designed and performed experiments, analyzed the data and wrote the manuscript. H.D. and M.E.P analyzed ATAC–seq data. C.E.F. developed CRISPR–Cas9-mediated gene deletion experiments. J.T., M.R. and S.B. performed experiments. B.Y. performed PageRank analysis. A.W.G and M.E.P provided advice, reagents and computational analyses. S.C. supervised the project, designed experiments, analyzed data and wrote the manuscript.

Corresponding author

Correspondence to Shane Crotty.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Editor recognition statement 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 TFH differentiation is not the default pathway.

Related to Fig. 1. a, Schematic diagram of a mutually antagonistic relationship of Bcl-6 and Blimp-1. UCSC browser tracks from BCL-6 ChIP–seq and Blimp-1 ChIP–seq were indicated below. b, A null hypothesis of a default TFH differentiation pathway model. c, SMARTA CD4 T cells were transferred to C57BL/6 host mice, followed by immunization of the host mice with KLH-gp61 in alum only, alum + LPS, alum + Poly(I:C), or alum + cGAMP adjuvants, and analyzed 7 days later. Representative flow cytometry of TFH and non-TFH SMARTA cell subsets from draining LNs (dLNs) of KLH-gp61 immunized mice. Two independent experiments were performed; each dot represents one mouse (n = 4). Data are mean ± s.d., unpaired two-tailed Student’s t-test. d, Quantification of results from Fig. 1b. e, Schematic of the SMARTA cell transfer system used for LCMVArm infection. WT, Bcl6f/f, Prdm1f/f, and Bcl6f/fPrdm1f/f CreCD4 SMARTA CD4+ T cells were transferred to C57BL/6 host mice, followed by infection of the host mice with LCMVArm, and analyzed 7 days later. f, Representative flow cytometry of GC-TFH, TFH and non-TFH SMARTA cell subsets from spleens of LCMVArm infected mice in Extended Data Fig. 1c. Three independent experiments were performed; each dot represents one mouse (n = 4). Data are mean ± s.d., unpaired two-tailed Student’s t-test. g, Quantification of results from Extended Data Fig. 1f. h, Representative histology section to define GC, B cell zone, T cell zone, and T-B border. T-B border was defined as ±15 μm region at a boundary line of T cell zone and B cell zone. Scale bar, 200 μm. Related to Fig. 1g. i, Histology of draining LNs at d8 after KLH-gp61 immunization in Fig. 1d. Blue, TCRβ; red, GL7; green, IgD; white, CD45.1 SMARTA. SMARTA cells were presented with large dots for clarity. Scale bar, 200 μm. Related to Fig.1g.

Extended Data Fig. 2 Bcl-6 exhibits direct negative autoregulatory feedback.

Related to Fig. 2. a, Sequence homology at BPS1 locus between various species. The numbers indicate region of mouse chromosome 19 (mm10). b, Schematic diagram of self-inactivating (SIN) vectors. pQdT SIN vector were generated from original pQCXIP SIN vector by removing IRES-PuroR cassette and additional deletion of CCAAT box and TATA box. c, Schematic of the RV+ SMARTA cell transfer system used for LCMVArm infection. SMARTA CD4 T cells transduced with WT Thy1.1-RV or ΔBPS1 Thy1.1-RV were adoptively transferred to C57BL/6 host mice, followed by infection of the host mice with LCMVArm, and analyzed 7 days after infection. Related to Fig. 2a-b and Extended Data Fig. 2d-e. d, TFH and TH1 gates used for Fig. 2b and Extended Data Fig. 2e. e, Chromatogram of DNA sequencing from WT or ΔBPS1 mouse. f, Schematic of the SMARTA cell transfer system used for LCMVArm infection. WT or ΔBPS1 SMARTA CD4 T cells were transferred to C57BL/6 host mice, followed by infection of the host mice with LCMVArm, and analyzed 7 days after infection. Related to Fig. 2c-d. g, Quantification of expression of CXCR5, SLAM, and PSGL1 in Fig. 2d, gated on CXCR5hiSLAMlo TFH or CXCR5loSLAMhi TH1 cells. Two independent experiments were performed; each dot represents one mouse (n = 4). Data are mean ± s.d., unpaired two-tailed Student’s t-test. h, Genome-browser tracks depict BCL-6 or NCOR ChIP–Seq peaks at BCL6 locus from OCI-LY1 cell line. Peak calls indicated below each track.

Extended Data Fig. 3 RNA-seq of TFH and non-TFH populations from multiple genetic backgrounds.

Related to Fig. 3 a, Schematic of the SMARTA cell transfer system used for RNA-seq analysis in KLH-gp61 immunization. Non-TFH (CXCR5loPSGL1hi) populations from WT, Bcl6f/f CreCd4, Prdm1f/f CreCD4, or Bcl6f/fPrdm1f/f CreCd4 SMARTA cells and TFH (CXCR5hiPSGL1lo) populations from WT or Prdm1f/f CreCD4 SMARTA cells were sorted from C57BL/6 host mice given WT, Bcl6f/f, Prdm1f/f, or Bcl6f/fPrdm1f/f CreCD4 SMARTA CD4 T cells, followed by infection of the host mice with KLH-gp61 in alum + cGAMP, and analyzed 8 days later. Naive SMARTA cells were isolated as CD44loCD62LhiCD45.1+ from uninfected mice. Representative flow cytometry of TFH and TH1 subsets from four independent experiments. b, Heatmap of gene expression of curated TFH-associated genes. Scale, row z-score. DKO, Bcl6f/fPrdm1f/f CreCD4. As a first analysis the effect of Bcl6/Prdm1 double-deficiency on the TFH biology, we assessed expression of a broad curated set of TFH-associated genes across all samples from RNA-seq gene expression profiling. Bcl6f/fPrdm1f/fCreCD4 TFH-like cells lost expression of positively TFH-associated genes in comparison to WT TFH cells or Prdm1f/fCreCD4 TFH cells. Conversely, Bcl6f/fPrdm1f/fCreCD4 TH1-like cells had a gene expression profile different from WT TH1 or Bcl6f/fCreCD4 TH1 cells. c, Principal component analysis of differential gene expression from RNA-seq of LCMVArm infection. Principal component analysis provided similar findings as (b), supporting the overall hypothesis that TFH is not a default differentiation pathway of CD4+ T cells and Bcl-6 has important activities beyond inhibition of Prdm1. d, Gene expression changes were clustered by k-means clustering analysis (k=10) of LCMVArm infection. e, Hierarchical clustering analysis of genes upregulated or downregulated in TFH cells relative to their expression in TH1 cells (1.4-fold cut off, Adj. P <0.05) of LCMVArm infection shown in Fig. 3c. Scale, row z-score. f, GSEA of BCL-6 bound genes from human tonsillar GC-TFH compared to Cluster 2 genes (left) or Cluster 3 genes (right) differentially expressed between Bcl6f/fPrdm1f/f TFH-like cells and Prdm1f/f TFH cells. NES, normalized enrichment score; FDR, false discovery rate. g, GSEA of Blimp-1 bound genes from CD8 and TH17 cells in comparison of Cluster 2 and Cluster 3 genes differentially expressed between Bcl6f/fPrdm1f/f TH1-like cells and Bcl6f/f TH1 cells.

Extended Data Fig. 4 Bcl-6 drives CXCR5 expression via repression of Id2-E2A pathway.

Related to Fig. 4 a, Quantification of GC-TFH core signature markers in SMARTA cells from dLNs of KLH-gp61 immunized mice in Fig. 4d. b, Schematic of the SMARTA cell transfer system used for LCMVArm infection. WT, Bcl6f/fPrdm1f/f, or Bcl6f/fPrdm1f/fId2f/f CreCD4 SMARTA CD4 T were transferred to C57BL/6 host mice, followed by infection of the host mice with LCMVArm, and analyzed 7 days later. Related to Fig. 4g and Extended Data Fig. 4c-g. c,e, Representative flow cytometry of TFH and GC-TFH SMARTA cell subsets from spleen of LCMVArm infected mice. Two independent experiments performed; each dot represents one mouse (n = 4). Data are mean ± s.d., unpaired two-tailed Student’s t-test. d, Quantification of expression of CXCR5 in Extended Data Fig. 4c, gated on SMARTA cells. f, Quantification of frequency of CXCR5hiPD1hi GC-TFH cells in Extended Data Fig. 4e, gated on SMARTA cells. g, Quantification of GC-TFH core signature markers in Extended Data Fig. 4e, gated on SMARTA cells.

Extended Data Fig. 5 ATAC–seq of TFH and non-TFH populations from multiple genetic backgrounds.

Related to Fig. 5 a, Representative flow cytometry of naive SMARTA cells (CD44loCD62LhiCD45.1+) used for ATAC–seq analysis. b, Genome-browser tracks depict ATAC–seq chromatin accessibility at Cxcr5 locus. Peak calls indicated below each track. * indicates DEseq2 raw p ≤ 0.05 in comparison between WT TFH and TH1. c, Genome-browser tracks depict ATAC–seq chromatin accessibility at Tbx21 and Gata3 loci. Peak calls indicated below each track. Bcl-6 liftover peaks from human to mouse reference genome are indicated. * and ** indicate DEseq2 raw p-val ≤ 0.05 and ≤ 0.01, respectively, in comparison between WT TFH and TH1. Gene expressions from RNA-seq data of LCMVArm infected mice are graphed. DKO, Bcl6f/fPrdm1f/f CreCD4. d, Genome-browser tracks depict BCL-6 ChIP–Seq peaks at SELPLG locus. Peak calls indicated below the track. e, Representative flow cytometry and quantification of the level of Bcl-6 in RV+ TFH or non-TFH SMARTA cell subsets from spleen of LCMVArm infected mice. SMARTA CD4 T cells transduced with GFP-RV or Bcl6-RV were transferred to C57BL/6 host mice, followed by infection of the host mice with LCMVArm, and analyzed 3 days after infection. Non-TFH: GFP-RV+ and TFH: GFP-RV+ indicate the expression level of endogenous Bcl-6 in each population. Each dot represents one mouse (n = 4). Data are mean ± s.d., unpaired two-tailed Student’s t-test. f, Representative flow cytometry and quantification of GC-TFH and BGC subpopulations from spleen of LCMVArm infected mice. Bcl6f/f CreCD4 SMARTA CD4 T cells transduced with Bcl6-RV or myctagN-Bcl6-RV were transferred to Bcl6f/f CreCD4 host mice, followed by infection of the host mice with LCMVArm, and analyzed 8 days after infection. We validated that an myctagN-Bcl6-RV was functionally comparable with non-tagged Bcl6-RV (Bcl6-RV), based on myctagN-Bcl6-RV rescue of TFH differentiation and B cell help function of Bcl6f/f CreCD4 CD4 T cells in LCMV infected mice. Each dot represents one mouse (n = 4). Data are mean ± s.d.

Extended Data Fig. 6 Identification of candidate TFs.

Related to Fig. 6 a, Heatmap plots representing the frequencies of the most enriched TF motifs in regions in decreased accessibility (relatively less open in first group than second group, DEseq2 raw p-val < 0.05). Scale, motif frequencies (%). Related to Fig. 6b. b, Motif analysis of the center of TF footprint (green bar) in Fig. 6c and Extended Data Fig. 6e from ATAC–seq reads. c, Genome-browser tracks depict ATAC–seq chromatin accessibility and TF occupancy at Icos and Cd200 loci. Peak calls indicated below each track. ** indicates DEseq2 raw p-val ≤ 0.01 in comparison between Bcl6f/fPrdm1f/f CreCD4 TFH-like and Prdm1f/f CreCD4 TFH. d, Gene expression of Klf genes from RNA-seq data of LCMVArm infected mice or KLH-gp61 immunized mice. e, TF footprints derived from ATAC–seq reads over representative TF motifs within accessible ATAC–seq regions. f, Heatmap plots of relative PageRank scores. Scale, row z-score.

Extended Data Fig. 7 CRISPR–Cas9-mediated gene knockdown of SMARTA cells.

Related to Fig. 7 a, Schematic of the CRISPR/Cas9-mediated gene knockdown of SMARTA cell system. Details are in the Method section. b, Representative flow cytometry of RNP transfection from more than four independent experiment; each dot represents one RNP+ group (n = 9). Data are mean ± s.d. Quantification of cell viability and transfection efficiency of RNP+ and RNP- (electroporation without RNP) SMARTA cells. c, Frequency of crRNA+ CD45.1+ SMARTA cells among total CD4 T cells from spleen of LCMVArm infected mice in Fig. 7a. Two independent experiments were performed; each dot represents one crRNA+ group (n = 4). Data are mean ± s.d., unpaired two-tailed Student’s t-test. d,e,f,g, WT or Bcl6f/fPrdm1f/f CreCD4 SMARTA CD4 T cells transfected with crCd8, crGata3, crRunx2, crRunx3, and crKlf2 were transferred to C57BL/6 host mice, followed by infection with LCMVArm (e,f,g) or immunization with KLH-gp61 (d) of the host mice, and analyzed 6-7 days later. crRNA+ SMARTA cells were FACS sorted from spleens (LCMVArm infection) or dLN (KLH-gp61 immunization) of host mice. Gene knockdown efficiencies were measured by flow cytometry (d), mRNA qPCR (e), or Western blot analysis (f,g). shRunx3-RV+ SMARTA cells and pMIG-Klf2-RV+ SMARTA cells were used as positive controls. Two independent experiments were performed; Each dot represents one mouse (n = 5). Data are mean ± s.d., unpaired two-tailed Student’s t-test. Details are in the Method section. h, Schematic of the CRISPR/Cas9-mediated gene knockdown of SMARTA cell system used for testing Gata3 in LCMVArm infection. WT or Bcl6f/fPrdm1f/f CreCD4 SMARTA CD4 T cells transfected with crCd8 or crGata3 were transferred to C57BL/6 host mice, followed by infection of the host mice with LCMVArm, and analyzed 6-7 days later. Related to Fig. 7c and Extended Data Fig. 7i,l,m. i,j,k, Frequency of crRNA+ CD45.1+ SMARTA cells among total CD4 T cells from spleen of LCMVArm infected mice in Fig. 7d and Extended Data Fig. 7h. Two (i) or three (j,k) independent experiments were performed; each dot represents one mouse (n = 4). Data are mean ± s.d., unpaired two-tailed Student’s t-test. l, Representative flow cytometry of TFH SMARTA cell subsets from spleen of LCMVArm infected mice in Extended Data Fig. 7h. Two independent experiments were performed; Each dot represents one mouse (n = 4). Data are mean ± s.d., unpaired two-tailed Student’s t-test. m, Quantification of expression of PSGL1 in Extended Data Fig. 7h, gated on SMARTA cells. CD44lo naive CD4 T cells were used as a negative control.

Extended Data Fig. 8 Identification of Runx2, Runx3 and Gata3 as repressors of TFH genes, acting downstream of Bcl-6.

Related to Fig. 7 a, Schematic of the RV+ SMARTA cell transfer system used for LCMVArm infection. WT SMARTA CD4 T cells transduced with pMIG (GFP-RV+), pMIG-Runx3myc (Runx3-RV+), or pMIG-Runx2myc (Runx2-RV+) were transferred to C57BL/6 host mice, followed by infection of the host mice with LCMVArm, and analyzed 7 days after infection. Related to Fig. 7i-j and Extended Data Fig. 7o-u. b, Total GFP+ RV+ SMARTA cells [RV+ high] were FACS sorted from in vitro culture. Whole cell lysates were analyzed by immunoblotting using anti-myc tag and anti-GAPDH antibodies. Relative Runx expressions are indicated. c, SMARTA CD4 T cells transduced with pMIG (GFP-RV+), pMIG-Runx3myc (Runx3-RV+ [High]), or pMIG-Runx2myc (Runx2-RV+ [High]) were transferred to C57BL/6 host mice, followed by infection of the host mice with LCMVArm, and analyzed 7 days later. Frequency of CD45.1+ SMARTA cells among total CD4 T cells from spleen of LCMVArm infected mice. Two independent experiments were performed; each dot represents one mouse (n = 4). Data are mean ± s.d., unpaired two-tailed Student’s t-test. d, Representative flow cytometry of TFH RV+ [High] SMARTA cell subsets from spleen of LCMVArm infected mice. Quantification of results from left panels. e, Bottom 10% [Low], bottom 10-30% [Med] and remaining 30-100% [High] GFP+ Runx3-RV+ SMARTA cells, and total GFP+ RV+ SMARTA cells were FACS sorted from in vitro culture. Whole cell lysates were analyzed by immunoblotting using anti-Runx3 and anti-GAPDH antibodies. Relative Runx expressions are indicated. f, Bottom 10% GFP+ Runx3-RV+ (Runx3-RV+ [Low]), bottom 30% GFP+ Runx2-RV+ (Runx2-RV+ [Med]), and total GFP+ RV+ (GFP-RV+) SMARTA cells were FACS sorted from in vitro culture. Whole cell lysates were analyzed by immunoblotting using anti-myc tag and anti-GAPDH antibodies. Relative Runx expressions are indicated. g, SMARTA CD4 T cells transduced with pMIG (GFP-RV+), pMIG-Runx3myc (Runx3-RV+ [Low]), or pMIG-Runx2myc (Runx2-RV+ [Med]) were transferred to C57BL/6 host mice, followed by infection of the host mice with LCMVArm, and analyzed 7 days later. Frequency of CD45.1+ SMARTA cells among total CD4 T cells from spleen of LCMVArm infected mice. Two independent experiments were performed; each dot represents one mouse (n = 5). Data are mean ± s.d., unpaired two-tailed Student’s t-test. h, Representative flow cytometry of TFH Runx3-RV+ [Low] and Runx2-RV+ [Med] SMARTA cell subsets from spleen of LCMVArm infected mice. Quantification of results from left panels. h, Representative flow cytometry of TFH Runx3-RV+ [Low] and Runx2-RV+ [Med] SMARTA cell subsets from spleen of LCMVArm infected mice. Quantification of results from left panels.

Extended Data Fig. 9 Identification of Klf2 as a repressor, acting downstream of Bcl-6 regulating major of TFH genes.

Related to Fig. 8 a-c, WT or Bcl6f/fPrdm1f/f CreCd4 SMARTA CD4 T cells transfected with crCd8 or crKlf2 were transferred to C57BL/6 host mice, followed by infection of the host mice with LCMVArm, and analyzed 6-7 days later (n=4-5 mice per group). (a) Frequency of CD45.1+ SMARTA cells among total CD4 T cells from spleen of LCMVArm infected mice. (b) Representative flow cytometry of gp66-restimulated IL-21+ SMARTA cells. Quantification of results from left panels. (c) Quantification of expression of Tcf-1, T-bet, GATA-3, and Maf, gated on SMARTA cells. Three independent experiments were performed; each dot represents one mouse (a, n = 4; b-c, n = 5). Data are mean ± s.d., unpaired two-tailed Student’s t-test. Related to Fig. 8a-c. d, Schematic of the CRISPR/Cas9-mediated gene knockdown of SMARTA cell system used for testing Klf2 in KLH-gp61 immunization. WT or Bcl6f/fPrdm1f/f CreCD4 SMARTA CD4 T cells transfected with crCd8 or crKlf2 were transferred to C57BL/6 host mice, followed by immunization of the host mice with KLH-gp61 and alum + cGAMP, and analyzed 8 days later. Related to Fig. 8d-f. e,g, Genome-browser tracks depict ATAC–seq chromatin accessibility and TF occupancy. Peak calls indicated below each track. * and ** indicate DEseq2 raw p-val ≤ 0.05 and ≤ 0.01, respectively, in comparison between Bcl6f/fPrdm1f/f CreCD4 TFH-like and Prdm1f/f CreCD4 TFH. Gene expression from RNA-seq data of LCMVArm infected mice and KLH-gp61 immunized mice are graphed. f, Genome-browser tracks depict Tcf1 ChIP–Seq peaks at Pdcd1 and IL6ra loci from murine TFH cells. h, Gene expression of Tox and Tox2 from RNA-seq data of LCMVArm infected mice or KLH-gp61 immunized mice. i, Representative flow cytometry of TFH cells, gated on SMARTA cells from spleens of LCMVArm infected mice (n=4 mice per group) in Fig. 8a. Quantification of results from left panels.

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Choi, J., Diao, H., Faliti, C.E. et al. Bcl-6 is the nexus transcription factor of T follicular helper cells via repressor-of-repressor circuits. Nat Immunol 21, 777–789 (2020). https://doi.org/10.1038/s41590-020-0706-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41590-020-0706-5

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing