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PU.1 and BCL11B sequentially cooperate with RUNX1 to anchor mSWI/SNF to poise the T cell effector landscape

Nature Immunology (2024)Cite this article

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Abstract

Adaptive immunity relies on specialized effector functions elicited by lymphocytes, yet how antigen recognition activates appropriate effector responses through nonspecific signaling intermediates is unclear. Here we examined the role of chromatin priming in specifying the functional outputs of effector T cells and found that most of the cis-regulatory landscape active in effector T cells was poised early in development before the expression of the T cell antigen receptor. We identified two principal mechanisms underpinning this poised landscape: the recruitment of the nucleosome remodeler mammalian SWItch/Sucrose Non-Fermentable (mSWI/SNF) by the transcription factors RUNX1 and PU.1 to establish chromatin accessibility at T effector loci; and a ‘relay’ whereby the transcription factor BCL11B succeeded PU.1 to maintain occupancy of the chromatin remodeling complex mSWI/SNF together with RUNX1, after PU.1 silencing during lineage commitment. These mechanisms define modes by which T cells acquire the potential to elicit specialized effector functions early in their ontogeny and underscore the importance of integrating extrinsic cues to the developmentally specified intrinsic program.

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Fig. 1: Chromatin accessibility at many Teff loci is established before TCR expression.
Fig. 2: Early poising of Teff loci is dependent on the mSWI/SNF ATPase SMARCA4.
Fig. 3: RUNX1 partners with mSWI/SNF to poise Teff loci in early T cell development.
Fig. 4: BCL11B maintains chromatin accessibility at SMARCA4-induced Teff loci.
Fig. 5: BCL11B maintains mSWI/SNF occupancy at Teff loci via indirect cooperativity.
Fig. 6: BCL11B and RUNX1 cooperate to maintain mSWI/SNF at Teff loci.
Fig. 7: PU.1 partners with RUNX1 to poise Teff loci at the ETP-DN2a stages.

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Data availability

The original raw ATAC–seq and CUT&RUN data have been deposited with the NCBI Gene Expression Omnibus (GEO) under accession no. GSE234331. Additional GEO accession numbers for the published datasets used in this study include: GSE132531, GSE140187, GSE118112, GSE127768, GSE100738, GSE118189, GSE90958, GSE77695, GSE94039, GSE31233, GSE110305, GSE93755, GSE110020, GSE103953, GSE88967, GSE115744, GSE116204, GSE123198, GSE98412, GSE64409, GSE172358 and GSE40463. Raw immunoblot images from Figs. 5a,b and 6c,d and Extended Data Fig. 8h–k were deposited with Mendeley at https://doi.org/10.17632/zws5pvcyzp.1 and are included in Supplementary Information. All sequencing data were aligned using the mm10 mouse genome assembly.

Code availability

This study did not generate new code.

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Acknowledgements

We thank M. Leid (Oregon State University) for the Bcl11bloxP/loxP mice; P. Liu (NIH/NHGRI) for the Runx1loxP/loxP mice; J. C. Zúñiga-Pflücker (University of Toronto) for the OP9-DL4 cell line; S. Henikoff (Fred Hutchinson Cancer Center) for the protein A-MNase; and C. Chang, B. Shin, V. Cismasiu and D. Avram for the CUT&RUN troubleshooting. We thank S. Smale, A. Weinmann, C. Kadoch and members of the Koh Laboratory for critical reading. We were supported by the following NIH grant nos.: R35-GM138150, 2UL1TR002389-06 and 5UL1TR002389-04 to A.S.K.; CA-163915 to G.R.C.; T32-EB009412b and T32-AI07090 to N.G.; T32-CA009594 to J.M.; and T32-GM139782 to O.B.; by the Howard Hughes Medical Institute (to G.R.C.); and by the Chan Zuckerberg Biohub (to W.J.G.). Fellowship support was provided by The Stamps Scholarship (to A.B.); the University of Chicago Women’s Board (to C.K.); a Stanford Immunology Baker Fellowship and Korea Foundation for Advanced Studies Overseas PhD Scholarship (to Y.K.); the Joint Institute for Metrology in Biology/National Institute of Standards and Technology training program (to B.P.); and the Stanford Genome Training Program (NIH/NHGRI) to S.K. Flow cytometry was supported by the University of Chicago Human Disease and Immune Discovery Facility (research resource identifier (RRID): SCR_022936); the Cytometry and Antibody Technology Facility (RRID: SCR_017760); and the Stanford Shared FACS Facility (NIH grant no. S10RR025518). Genomic sequencing was supported by the University of Chicago Genomics Facility (RRID: SCR_019196), which receives support from a Cancer Center Support Grant (no. P30-CA014599).

Author information

Author notes

  1. These authors contributed equally: Noah Gamble, Alexandra Bradu, Jason A. Caldwell.

Authors and Affiliations

  1. Department of Pathology, University of Chicago, Chicago, IL, USA

    Noah Gamble, Alexandra Bradu, Jason A. Caldwell, Joshua McKeever, Olubusayo Bolonduro, Ebru Ermis, Caroline Kaiser & Andrew S. Koh

  2. Graduate Program in Biophysical Sciences, University of Chicago, Chicago, IL, USA

    Noah Gamble

  3. Committee on Molecular Metabolism and Nutrition, University of Chicago, Chicago, IL, USA

    Joshua McKeever

  4. Committee on Genetics, Genomics, Systems Biology, University of Chicago, Chicago, IL, USA

    Olubusayo Bolonduro

  5. Department of Human Genetics, University of Chicago, Chicago, IL, USA

    Caroline Kaiser

  6. Immunology Program, Stanford University, Stanford, CA, USA

    YeEun Kim

  7. Department of Genetics, Stanford University, Stanford, CA, USA

    YeEun Kim, Benjamin Parks & Sandy Klemm

  8. Department of Computer Science, Stanford University, Stanford, CA, USA

    Benjamin Parks & William J. Greenleaf

  9. Department of Applied Physics, Stanford University, Stanford, CA, USA

    William J. Greenleaf

  10. Chan Zuckerberg Biohub, San Francisco, CA, USA

    William J. Greenleaf

  11. Department of Pathology, Stanford University, Stanford, CA, USA

    Gerald R. Crabtree

  12. Department of Developmental Biology, Stanford University, Stanford, CA, USA

    Gerald R. Crabtree

  13. Institute for Biophysical Dynamics, University of Chicago, Chicago, IL, USA

    Andrew S. Koh

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Contributions

A.S.K. and G.R.C. conceived the study. A.S.K., N.G., A.B., J.A.C., J.M., O.B., E.E., C.K., Y.K. and B.P. conducted the experiments. A.S.K., N.G., A.B. and E.E. performed the bioinformatic analyses. A.S.K. supervised all the experiments and analyses. S.K. and W.J.G. provided resources and conceptual insights. A.S.K. wrote the paper with support from N.G., A.B. and J.A.C. All authors reviewed and provided comments on the paper.

Corresponding author

Correspondence to Andrew S. Koh.

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Competing interests

G.R.C. is a founder and stockholder in Foghorn Therapeutics. W.J.G. is a consultant of and equity holder in 10X Genomics, Guardant Health, Quantapore and Ultima Genomics. W.J.G. is a cofounder of Protillion Biosciences and named on patents describing ATAC–seq. The other authors declare no competing interests.

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Nature Immunology thanks Harinder Singh and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: Ioana Staicu, in collaboration with the Nature Immunology team.

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Extended data

Extended Data Fig. 1 T effector loci reflect the chromatin and transcriptional profiles of major T effector subtypes.

a, Heatmap of Z scores of TPM-normalized RNA-seq reads across the k-means clustered (k = 7) transcriptomes (less genes robustly expressed in BEFF cells) of sorted CD4+CD44+TCRβlo splenic T cells21 18 h post-injection with CD3/CD40 Abs (hereafter CD4+ Teff cd3/cd40), splenic CD19−CD8−TCRβ+CD4+ T cells21 (hereafter CD4+ Tpan), TCM, CD8+ Teff, TRM, TH17CNS, TH17gut, TFH, TH1, TH2 and CD11b−NK-1.1-TCRβ-CD138+Blimp1intMHCIIhi plasmablast cells21 (hereafter PBEFF) (n = 2 each). b, Distribution of genomic displacement of T effector loci (hereafter Teff loci) in relation to the nearest TSS (signed logarithmic scale). c, Heatmap of statistical enrichment (one-sided Fisher’s exact test) of Teff peaks whose nearest gene is in RNA-seq k-means cluster i (horizontal axis) within an ATAC-seq k-means cluster j (vertical axis; see Fig. 1a). d-g, Representative flow cytometry plots illustrating gating strategy for in vivo DN thymocyte FACS. h, Representative distribution (for all ATAC-seq samples) of normalized Tn5 insertions within 2 kb of transcriptional start-sites (TSS). i, Representative genome browser of ATAC-seq in ESC29, HSC11, MPP11, CLP11, ETP, DN2a, DN3, DN4, DP, CD8-SP, naive T cells (hereafter TN), Teff cells and Beff cells at Gzmb (Teff = CD8+ Teff in vitro) and Ifng (Teff = TH1) loci (1 of n = 2 for each). Adjoined bars indicate RNA-seq-determined transcripts-per-million (TPM) in each cell type.

Extended Data Fig. 2 Establishment and maintenance of chromatin accessibility at Teff loci in early T cell development.

a-f, Bar plots representing the fraction of CD8+ Teff-specific (a), CD8+ TRM-specific (b), CD8+ TCM-specific (c), CD4+ TH1-specific (d), CD4+ TH2-specific (e), CD4+ TH17-specific (f) ATAC-seq peaks that became accessible (orange), are maintained accessible from previous stage (blue) or are no longer accessible relative to previous stage (gray) at ESC, HSC, MPP, CLP, ETP, DN2a and DN3 stages. g-l, Corresponding violin plots (boxes represent 25th, 50th and 75th percentiles; whiskers represent median +/- 1.5 interquartile range) representing the number of overlap between each ATAC-seq peak from CD8+ Teff-specific (g), CD8+ TRM-specific (h), CD8+ TCM-specific (i), CD4+ TH1-specific (j), CD4+ TH2-specific (k), CD4+ TH17-specific (l) ATAC-seq profiles, grouped by the developmental windows (ESC, HPC, ETP-DN3 and respective Teff cells) during which the ATAC-seq peak first became accessible.

Extended Data Fig. 3 Chromatin accessibility at Teff loci in early T cell progenitors is not dependent on calcineurin activity.

a, Representative aggregate histograms (1 of n = 2) of ATAC-seq Tn5 insertions in in vitro differentiated FK506-treated (calcineurin inhibitor) vs. DMSO-treated (control) ETP-DN3 thymocytes at Teff loci that first became accessible in ETP-DN3 thymocytes. b, Representative heatmaps (1 of n = 2) of ATAC-seq in in vitro differentiated FK506-treated (calcineurin inhibitor) vs. DMSO-treated (control) ETP-DN3 thymocytes at Teff loci that first become accessible in ETP-DN3 thymocytes.

Extended Data Fig. 4 Enhancer priming mediates early chromatin accessibility at Teff loci.

a, Heatmap of Z scores of TPM-normalized RNA-seq reads across the k-means clustered (k = 10) transcriptomes (less genes robustly expressed in PBEFF cells) of ETP, DN2a, Lin−c-KitintCD25hiCD44hiCD4−CD8− (DN2b), DN3, CD4+ Teff cd3/cd40, CD4+ Tpan, TCM, CD8+ Teff, TRM, TH17CNS, TH17gut, TFH, TH1 and TH2 cells (n = 2 for each). b, Heatmap of Z scores of TSS-normalized ATAC-seq fragments across the k-means clustered (k = 9) Teff loci in ETP, DN2, DN3, TRM, CD8+ Teff in vitro, CD8+ Teff, TCM, TH1, TH2, TH17CNS, TH17gut, TFH cells and BEFF cells (n = 2 each). Labeled columns highlight ATAC-seq peaks whose nearest gene represents a canonical gene reflective of a distinct T effector program. c, Representative aggregate histograms of H3K4me131 (1 of n = 2), H3K4me331 (1 of n = 2), H3K27ac32 (1 of n = 2) or RNA Polymerase II31 (POL II) (1 of n = 2) ChIP-seq or GRO-seq dyads intersecting all Teff loci (blue), Teff loci near active genes in ETP-DN3 cells (blue) and all non-Teff loci (green) in DN2-DN3 thymocytes. d, Representative aggregate histograms of H3K4me131 (1 of n = 2), H3K4me331 (1 of n = 2) ChIP-seq dyads at promoter vs. gene-distal Teff loci in DN2-DN3 thymocytes.

Extended Data Fig. 5 Signal-regulated transcription factors localize to developmentally poised Teff loci in activated Teff cells.

a, Heatmaps and aggregate histograms of JUNB occupancy (ChIP-seq45) in TH1 cells (n = 1), JUNB in TH17 cells40 (1 of n = 2), JUND occupancy (ChIP-seq40) in TH17 cells (n = 1) at Teff loci that contain Jun motifs. b, Heatmap and aggregate histogram of NFκB-p65 occupancy (ChIP-seq43) in in vitro activated Teff cells (1 of n = 2) at Teff loci that contain NFκB-p65 motifs. c, Heatmap and aggregate histogram of NFATc2 occupancy (ChIP-seq41) in CD8 + Teff cells (n = 1) at Teff loci that contain NFATc2 motifs. d, Heatmap and aggregate histogram of BATF occupancy (ChIP-seq39) in TH17 cells (1 of n = 2) at Teff loci that contain BATF motifs. e, Heatmaps and aggregate histograms of STAT1 occupancy (ChIP-seq6) in TH1 cells (n = 1), STAT4 occupancy in TH1 cells (ChIP-seq44) (1 of n = 2), STAT3 occupancy (ChIP-seq42) in CD8 + Teff cells (1 of n = 2) and STAT5 occupancy (ChIP-seq42) in CD8+ Teff cells (1 of n = 2) at Teff loci that contain STAT motifs. For this figure only, Teff loci (rows) in each heatmap were sorted independently and do not correspond to other heatmaps in the group.

Extended Data Fig. 6 Smarca4 deletion inhibits chromatin poising of Teff loci in DN thymocytes.

a, Representative gating strategy for FACS of primary Lin−Sca-1+c-Kit+ hematopoietic progenitors without Cre activity from Smarca4loxP/loxPRosa26CreERT2/nTnG bone marrow cells. b, Representative gating strategy for FACS of ETP-DN3 thymocytes with or without Cre activity from OP9-DL4 in vitro differentiation co-cultures. c, Representative heatmaps of normalized ATAC-seq in in vitro differentiated SMARCA4 WT vs. SMARCA4 cKO ETP (1 of n = 3), DN2a (1 of n = 3) and DN3 (1 of n = 2) thymocytes and BAF155 occupancy (CUT&RUN) in DN2-DN3 thymocytes (1 of n = 3) across SMARCA4-induced Teff loci that first became accessible in ETP, DN2a and DN3 stages (rows). d, Representative aggregate histograms of BAF155 occupancy (CUT&RUN) in DN2-DN3 thymocytes (1 of n = 3) across Teff loci (blue) and Non-Teff loci (red). e, Fraction of transcriptionally active SMARCA4-induced loci in ETP, DN2a, and DN3 thymocytes (n = 2 each). f, Volcano plots of differential gene expression between in vitro differentiated SMARCA4 WT vs. SMARCA4 cKO ETP and DN2-DN3 thymocytes (n = 2 each) across actively transcribed T effector genes. Marginal rugs (blue lines) indicate distribution of values along each axis.

Extended Data Fig. 7 Runx1 perturbation in early T cell development.

a, Representative gating strategy for FACS of ETP-DN3 thymocytes with or without Cre activity from OP9-DL4 in vitro differentiation co-cultures derived from Lin-Sca-1+c-Kithi hematopoietic progenitors of Runx1loxP/loxPRosa26CreERT2/nTnG mice. b-d, Fraction of transcriptionally active RUNX1-induced loci in ETP (b), DN2a (c) and DN3 (d) thymocytes (n= 2). e-g, Volcano plot of differential gene expression between in vitro differentiated RUNX1 WT vs. RUNX1 cKO ETP (e), DN2a (f) and DN3 (g) thymocytes (n = 2) across actively transcribed T effector genes. Marginal rugs (blue lines) indicate distribution of values along each axis.

Extended Data Fig. 8 SMARCA4 and BCL11B cooperate indirectly to promote chromatin accessibility at T effector loci in DN thymocytes.

a, Representative gating strategy for FACS of DN2-DN3 thymocytes from sex-matched littermates of Vav1-iCre+Bcl11bloxP/loxP or Bcl11bloxP/loxP mice. b, Top: Scatter plot depicting the log2 fold-change of normalized ATAC-seq fragments at Teff loci between sorted BCL11B WT vs. BCL11B cKO primary DN2a thymocytes (n = 2; horizontal axis) and in vitro differentiated SMARCA4 WT vs. SMARCA4 cKO DN2a thymocytes (n = 3; vertical axis). SMARCA4-induced Teff loci (Benjamini-Hochberg-corrected FDR < 0.1) peaks highlighted in orange. Number and statistical enrichment of SMARCA4-induced T effector loci (determined by one-sided Fisher’s exact test) within each Cartesian quadrant shown in orange. Bottom: Same as above between sorted BCL11B WT vs. BCL11B cKO DN3 primary thymocytes (n = 2; horizontal axis) and in vitro differentiated SMARCA4 WT vs. SMARCA4 cKO DN3 thymocytes (n = 2; vertical axis). c, Fraction of transcriptionally active jointly SMARCA4-induced BCL11B-induced Teff loci in DN2-DN3 thymocytes (left; n = 2) and of transcriptionally active jointly SMARCA4-induced BCL11B-repressed loci in DN2-DN3 thymocytes (right; n = 2). d, Volcano plots of differential gene expression between sorted BCL11B WT vs. BCL11B cKO ETP-DN3 primary thymocytes (n = 2) across actively transcribed T effector genes. Marginal rugs (blue lines) indicate distribution of values along each axis. e, MA plot depicting the log2 fold-change of normalized ATAC-seq fragments at Teff loci between sorted BCL11B WT vs. BCL11B cKO DN2-DN3 primary thymocytes (n = 2). Statistically significant differentially expressed peaks (Benjamini-Hochberg-corrected FDR < 0.1) are highlighted in orange. f, Representative aggregate histograms of ATAC-seq at jointly SMARCA4-induced BCL11B-induced vs. jointly SMARCA4-induced BCL11B-repressed Teff loci in sorted BCL11B WT primary thymocytes (1 of n = 2). g, Bar plots representing the fraction of jointly SMARCA4-induced BCL11B-induced vs. jointly SMARCA4-induced BCL11B-repressed Teff loci in DN2-DN3 thymocytes that are also accessible in NK cells and ILCs (merged ILC1, ILC2, ILC3)11. h, Reciprocal co-immunoprecipitations of IgG, SMARCA4, BCL11B and PBRM1 (columns) from nuclear extracts (1 mg/mL) of CCRF-CEM human T cell line and immunoblots of co-immunoprecipitating SMARCA4, PBRM1 and BCL11B (rows). (Input sample, immunoprecipitant (IP), flow-through fraction of non-interacting proteins (FT), molecular weight markers (M)). i, Density sedimentation (glycerol gradient; horizontal axis) and immunoblot of SMARCA4, PBRM1 and BCL11B (rows) from nuclear extracts of CCRF-CEM human T cell line. 1 mg total extract loaded onto gradient. j, Density sedimentations (glycerol gradient; horizontal axes) and immunoblots of SMARCA4, PBRM1 and BCL11B (rows) from untreated nuclear extracts (left) and benzonase-treated nuclear extracts (right) of total thymocytes from WT mice. 1 mg total extract loaded onto each gradient. k, Reciprocal co-immunoprecipitations of IgG, SMARCA4, BCL11B and PBRM1 (columns) from high-concentration nuclear extracts (10 mg/mL) of total thymocytes from wild-type mice and immunoblots of co-immunoprecipitating SMARCA4, PBRM1 and BCL11B (rows). (Input sample, immunoprecipitant (IP), flow-through fraction of non-interacting proteins (FT), molecular weight markers (M)). l, Representative aggregate histograms of BAF155 occupancy (CUT&RUN) at jointly SMARCA4-induced, BCL11B-induced (left) vs. jointly SMARCA4-induced, BCL11B-repressed (right) T effector loci in sorted BCL11B WT vs. BCL11B cKO primary DN2-DN3 thymocytes (1 of n = 2). m, Cumulative distribution functions of the log2 fold-change in RUNX1 occupancy (ChIP-seq32) between sorted BCL11B WT and BCL11B cKO primary DN2-DN3 thymocytes at BCL11B-induced, BCL11B-independent and BCL11B-repressed (n = 2) Teff loci. P-values from one-sided Wilcoxon signed-rank tests (using BCL11B-independent distribution as the null) are displayed.

Extended Data Fig. 9 mSWI/SNF-associated RUNX1 complexes are a subset of a heterogeneous pool of RUNX1 complexes in the nucleus.

a, Representative heatmaps of RUNX1 occupancy (ChIP-seq32) (left; 1 of n = 2) and BAF155 occupancy (CUT&RUN) (right; 1 of n = 3) across all RUNX1 ChIP-seq peaks in DN2-DN3 thymocytes partitioned by BAF155 fragment density decile (rows).

Extended Data Fig. 10 Working model of transcription factor relay for specification of T effector potential.

a, Fraction of transcriptionally active jointly SMARCA4-induced, PU.1-induced loci in in vitro differentiated DN2a thymocytes (n = 3). b, Volcano plot of differential gene expression between in vitro differentiated PU.1 WT vs. PU.1 cKO DN2a thymocytes (n = 2) across actively transcribed T effector genes. Marginal rugs (blue lines) indicate distribution of values along each axis. c, Schematic of cooperative transcription factor relay that recruits and maintains mSWI/SNF occupancy at Teff loci to equip thymocytes for T effector potential.

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Supplementary Figs. 1–3 and unprocessed immunoblots.

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Gamble, N., Bradu, A., Caldwell, J.A. et al. PU.1 and BCL11B sequentially cooperate with RUNX1 to anchor mSWI/SNF to poise the T cell effector landscape. Nat Immunol (2024). https://doi.org/10.1038/s41590-024-01807-y

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