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Rapid chromatin repression by Aire provides precise control of immune tolerance

Nature Immunology volume 19, pages 162–172 (2018)Cite this article

Abstract

Aire mediates the expression of tissue-specific antigens in thymic epithelial cells to promote tolerance against self-reactive T lymphocytes. However, the mechanism that allows expression of tissue-specific genes at levels that prevent harm is unknown. Here we show that Brg1 generates accessibility at tissue-specific loci to impose central tolerance. We found that Aire has an intrinsic repressive function that restricts chromatin accessibility and opposes Brg1 across the genome. Aire exerted this repressive influence within minutes after recruitment to chromatin and restrained the amplitude of active transcription. Disease-causing mutations that impair Aire-induced activation also impair the protein’s repressive function, which indicates dual roles for Aire. Together, Brg1 and Aire fine-tune the expression of tissue-specific genes at levels that prevent toxicity yet promote immune tolerance.

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Fig. 1: mTEChi differentiation promotes chromatin accessibility at tissue-specific loci.
Fig. 2: Aire and Brg1 are determinants of an mTEChi-specific chromatin state with opposing influences on accessibility.
Fig. 3: Accessibility at tissue-specific loci is promoted by Brg1 and repressed by Aire.
Fig. 4: Regions that contain NF-κB motifs are highly sensitive to opposing regulation by Aire and Brg1.
Fig. 5: Brg1 imposes immunological tolerance.
Fig. 6: Aire rapidly represses accessibility after recruitment to chromatin.
Fig. 7: Aire recruitment to an active locus restrains transcriptional amplitude.

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Acknowledgements

We are grateful to N. Manley (University of Georgia, Athens, GA, USA) for Foxn1ex9Cre mice; N. Hathaway (University of North Carolina, Chapel Hill, NC, USA), C. Kadoch (Harvard Medical School, Boston, MA, USA), S. Braun (Stanford University, Stanford, CA, USA) and E. Chory (Stanford University, Stanford, CA, USA) for CiA constructs; M. Toribio (Universidad Autónoma de Madrid, Madrid, Spain) and D. Mathis (Harvard Medical School, Boston, MA, USA) for the 4D6 cTEC line; D. Mathis, M. Anderson and S. Denny for insightful comments; Y. Chien, C. Weber, J. Kirkland, L. Wagar and J. Ronan for critical reading of the manuscript; and J. Gardner, P. Chu and R. Li for technical assistance. We thank the Stanford Shared FACS facility and S. Kim for flow cytometry and cell sorting. The Stanford BioX3 cluster was used for computational analyses (NIH S10 grant 1S10RR02664701). This work was supported by the Howard Hughes Medical Institute (to G.R.C.), the NIH (grants CA163915 and NS046789 to G.R.C., P50-HG007735 to H.Y.C. and W.J.G., T32HG000044 to J.D.B., and T32 GM007790 to E.L.M.), the Lymphoma and Leukemia Society (A.S.K.) and the National Library of Medicine (Stanford Biomedical Informatics Training Grant LM-07033 to D.M.M.).

Author information

Authors and Affiliations

  1. Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA

    Andrew S. Koh, Erik L. Miller & Gerald R. Crabtree

  2. Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, CA, USA

    Andrew S. Koh, David M. Moskowitz, William J. Greenleaf, Howard Y. Chang & Gerald R. Crabtree

  3. Howard Hughes Medical Institute, Chevy Chase, MD, USA

    Andrew S. Koh, Erik L. Miller & Gerald R. Crabtree

  4. Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA

    Erik L. Miller, David M. Moskowitz & William J. Greenleaf

  5. Broad Institute of MIT and Harvard, Cambridge, MA, USA

    Jason D. Buenrostro

  6. Harvard Society of Fellows, Harvard University, Cambridge, MA, USA

    Jason D. Buenrostro

  7. Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA, USA

    Jing Wang

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

    William J. Greenleaf

  9. Chan Zuckerburg Biohub, San Francisco, CA, USA

    William J. Greenleaf

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Contributions

A.S.K. and G.R.C. conceived of the study and wrote the paper. A.S.K. planned and performed all experiments and data analysis. A.S.K., E.L.M., J.D.B. and D.M.M. performed ATAC-seq data analysis. J.W. performed kidney capsule transplants. W.J.G. and H.Y.C. provided conceptual insights and advised on data analysis and experimental design.

Corresponding authors

Correspondence to Andrew S. Koh or Gerald R. Crabtree.

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Competing interests

W.J.G. and H.Y.C. are cofounders of Epinomics, Inc. Stanford University has filed a patent on ATAC-seq on which W.J.G. and H.Y.C. are named as inventors.

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Integrated supplementary information

Supplementary Figure 1 mTEChi differentiation promotes major shifts in the chromatin accessibility landscape.

(a) Flow cytometry gating sequence for sorting mTECs. (b) Representative histogram of aggregate Tn5 insertions (blue) and smoothed signal (red) around transcriptional start sites (TSS). (c) Representative distribution of ATAC-seq fragment size exhibiting nucleosomal periodicity. (d) Representative comparison of ATAC-seq fragment density at peaks between biological replicates. (e) Signal enrichment for ATAC-seq libraries, defined by the fold-change between the maximum and minimum signals within the 4 kb region displayed in (b). (f) First principal component (PC) of PCA representing 30.36% of variance separates mTEChi and mTEClo samples. (g) Genomic signal tracks of ATAC-seq fragments at three loci from mTEChi and mTEClo samples. Red arrowheads indicate differentially accessible regions. (h) Representative density plots of ChIP-seq read dyads of indicated factors in embryonic stem cells at ATAC-seq peaks near tissue-specific genes whose accessibilities are induced during mTEChi differentiation. The data shown are from 1 experiment representative of > 20 (a), 16 (b,c), or 4 (d) independent experiments or are from n = 4 (f,g) independent experiments or from pooled data representative of 2 (h) independent experiments.

Supplementary Figure 2 Aire and Brg1 have opposing influences on accessibility.

(a) Representative immunofluorescence stainings of 4-week old thymic sections from indicated genotypes for medullary marker keratin-14 (red) and Aire (green). White scale bar = 10 um. (b) Representative frequencies of TECs in 4-week old thymi from indicated genotypes assessed by flow cytometry. (c) Representative frequencies of mTEChi and mTEClo compartments expressing Aire from 4-week old thymi of indicated mice. (d) CDF plots of indicated accessibility fold-changes at regions classified as differentially accessible in WT vs. Brg1cKO or AireKO mTEChi. P values were determined by Mann-Whitney U-test (two-tailed). (e) Distribution of distances of indicated peak sets to the nearest TSS. (f) Histogram of the distances between indicated peak sets (Fig. 2c) and the nearest TSS. (g) Genomic signal tracks of ATAC-seq fragments at six loci from indicated mTEChi samples (top). ChIP-seq signal tracks from WT mTEChi samples. Red arrowheads indicate differentially accessible regions. (h-j) ATAC-seq analyses on samples generated by Bansal et. al. 2016. (h) First principal component (PC) of PCA separating WT and Aire−/− mTEChi samples. (i) Heatmap of normalized ATAC-seq fragment density at differential peaks (rows). (j) Heatmap of Aire ChIP-seq fragment dyad density at Aire-repressed ATAC-seq peaks. The data shown are from 1 experiment representative of 3 (a), 10 (b,c) or 2 (g) independent experiments or from pooled data representative of 4 (c) or 2 (j) independent experiments or from n = 2 (h,i) independent experiments.

Supplementary Figure 3 Regions in which accessibility is repressed by Aire and induced by Brg1 are enriched for H3K27ac and active topoisomerases.

(a) ChIP-seq fragment dyad density of indicated factors/histones at Aire-induced or Aire-repressed ATAC-seq peaks. (b) Heatmap of ChIP-seq fragment dyad density of indicated factors/histones at Aire-repressed ATAC-seq peaks. (c) ChIP-seq fragment dyad density at Brg1-induced or Brg1-repressed ATAC-seq peaks.  The data shown are from pooled data representative of 2 independent experiments (a-c).

Supplementary Figure 4 Aire is dispensable for induced accessibility at tissue-specific loci during mTEC differentiation.

(a) CDF plot of accessibility fold-changes between AireKO mTEChi and AireKO mTEClo at indicated ATAC-seq peaks differentially accessible or unchanged in WT mTEChi vs. mTEClo. (b) CDF plot of transcriptional fold-changes between AireKO mTEChi and AireKO mTEClo at indicated genes upregulated or unchanged by Aire. (c) CDF plot of accessibility fold-changes between WT mTEChi and AireKO mTEChi at indicated ATAC-seq peaks differentially accessible or unchanged in WT mTEChi vs mTEClo. (d) CDF plot of transcriptional fold-changes between WT mTEChi and AireKO mTEChi at indicated genes upregulated or unchanged by Aire. The data shown are from pooled data representative of 2 independent experiments (a-d). P values determined from Mann-Whitney U-tests (two-tailed) (a-d).

Supplementary Figure 5 Differential enrichment of transcription factor motifs and footprints during mTEC maturation.

(a-c) Change in deviation from expected accessibility signal at ATAC-seq peaks containing known trans-factor motifs (key) between indicated samples. Diamonds represent means, circles represent replicates. (d) NF-kB motifs depicted from analyses in (a-c) and the changes in deviation scores from mTEChi samples of indicated genotypes. Mean +/− s.e.m. (e-p) Differential accessibility footprints in mTEChi vs. mTEClo samples at ATAC-seq peaks containing indicated motifs.  The data shown are n = 2 (a-c, d: Aire-KO or Brg1-cKO samples) or n = 4 (d: WT samples) independent experiments, or from pooled data representative of 4 (e-p) independent experiments. 

Supplementary Figure 6 T cell compartments in Brg1-cKO mice.

(a,b) Frequencies of thymocyte compartments in 4-week old mice from indicated genotypes assessed by flow cytometry Mean +/− s.e.m. n.s., not significant (two-tailed t-tests). (c) Frequency (left) and cellularity (right) of cTEC compartment in 4-week old mice from indicated genotypes. Mean +/− s.e.m. P values determined by two-tailed t-test < 0.001 (***). (d) Cellularity of thymocyte compartments in 4-week old mice from indicated genotypes. Mean +/− s.e.m. P values determined by two-tailed t-test < 0.05 (*), < 0.01 (**). (e) Cellularity of indicated splenic T cell compartments in 4-week old mice from indicated genotypes. Mean +/− s.e.m. P values determined by two-tailed t-test < 0.01 (**). (f) Frequency (left) and celluarity (right) of FoxP3+CD25+ regulatory T cells (Treg) in spleen from 4 week-old mice of indicated genotypes. Mean +/− s.e.m. P values determined by two-tailed t-test < 0.05 (*). (g) Purified CD4+CD25neg Tconv cells were mixed with CD4+CD25+ Treg from WT and Brg1-cKO mice in a criss-cross fashion as indicated, and assayed for proliferation in the presence of irradiated splenocytes and anti-CD3. Mean +/− s.e.m. (h) Histological analyses of indicated tissues from 6 month-old WT or Brg1-cKO mice via H&E and anti-CD3 immunohistochemistry stainings for infiltrating lymphocytes at indicated peripheral tissues. Scale bars for 10x, 60x images = 200 um, 50 um, respectively. The data shown are from 1 experiment representative of 8 (a) or 2 (h) independent experiments or from n = 8 (b–f) or 3 (g) independent experiments.

Supplementary Figure 7 Aire and BAF have divergent influences on accessibility after recruitment to chromatin.

(a) The CiA:Oct4 locus exhibits DNase I sensitivity compared to the inaccessible rhodopsin (Rho) locus. Mean +/− s.e.m. (b) Rapid maximal reduction in DNase I sensitivity after recruitment of Aire to CiA:Oct4 locus via rapamycin. (c) Schematic of CiA recruitment system. (d) Changes in DNase I sensitivity at CiA:Oct4 locus post BAF vs. Aire recruitment. Mean +/− s.e.m. (e) Recruitment of BAF nor Aire to CiA:Oct4 locus activates transcription. (f) The PSMB11 locus exhibits DNase I sensitivity . Mean +/− s.e.m. (g) Schematic of dCas9 recruitment system: Aire fused to MS2 viral domain is targeted by guide RNA with MS2-binding aptamers. (h) Changes in DNase I sensitivity upon dCas9-induced Aire recruitment to PSMB11 locus, compared to changes at locus encoding ribosomal subunit (RPS29). Mean +/− s.e.m. (i) Model of rheostatic chromatin control of ectopic transcription of tissue-specific genes by Aire and Brg1: BAF chromatin remodeling complexes (orange) coordinate with transcription factors (purple) to poise and recruit transcriptional machinery (gold and gray) to tissue-specific loci during mTEC differentiation. Productive elongation of Pol II is inhibited by negative elongation factors, e.g. Nelf. Subsequent Aire expression and targeting brings interacting positive elongation factors (light blue) to release paused Pol II. Aire’s repressive function inhibits chromatin accessibility, reducing the occupancy of BAF, transcription factors and transcriptional machinery (indicated by fading opacity) and restraining amplitude of transcription. The data shown are from n = 6 (a), 1 (b), or 3 (d,f,h) independent experiments or from 1 experiment representative of 4 (e) independent experiments. 

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Koh, A.S., Miller, E.L., Buenrostro, J.D. et al. Rapid chromatin repression by Aire provides precise control of immune tolerance. Nat Immunol 19, 162–172 (2018). https://doi.org/10.1038/s41590-017-0032-8

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