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Dynamic chromatin accessibility licenses STAT5- and STAT6-dependent innate-like function of TH9 cells to promote allergic inflammation

Nature Immunology volume 24, pages 1036–1048 (2023)Cite this article

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A Publisher Correction to this article was published on 11 October 2023

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Abstract

Allergic diseases are a major global health issue. Interleukin (IL)-9-producing helper T (TH9) cells promote allergic inflammation, yet TH9 cell effector functions are incompletely understood because their lineage instability makes them challenging to study. Here we found that resting TH9 cells produced IL-9 independently of T cell receptor (TCR) restimulation, due to STAT5- and STAT6-dependent bystander activation. This mechanism was seen in circulating cells from allergic patients and was restricted to recently activated cells. STAT5-dependent Il9/IL9 regulatory elements underwent remodeling over time, inactivating the locus. A broader ‘allergic TH9’ transcriptomic and epigenomic program was also unstable. In vivo, TH9 cells induced airway inflammation via TCR-independent, STAT-dependent mechanisms. In allergic patients, TH9 cell expansion was associated with responsiveness to JAK inhibitors. These findings suggest that TH9 cell instability is a negative checkpoint on bystander activation that breaks down in allergy and that JAK inhibitors should be considered for allergic patients with TH9 cell expansion.

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Fig. 1: Resting TH9 cells uniquely produce IL-9 independent of TCR restimulation, downstream of paracrine STAT-dependent cytokines.
Fig. 2: IL-2 and IL-4 rapidly induce bystander activation of resting TH9 cells through STAT5 and STAT6.
Fig. 3: STAT-dependent cytokines induce IL9 transcription in recently activated TH9 cells.
Fig. 4: Prolonged resting of TH9 cells reduces accessibility of STAT5-binding sites and type 2 cytokine loci, including critical IL9 enhancers.
Fig. 5: TH9 cells promote TCR-independent airway pathology in vivo.
Fig. 6: STAT-dependent TH9 bystander activation promotes allergic disease and is associated with responsiveness to JAK inhibitors.

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Data availability

Raw and analyzed data are available at the Gene Expression Omnibus under accession no. GSE222910. Source data are provided with this paper.

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Acknowledgements

The authors thank R. Flavell and P. Licona-Limon for generously providing INFER and Klrg1Cre mice. We thank F. Petermann, Y. Baumer and S. Muallem for their thoughtful review of and comments on the manuscript. We acknowledge staff at the NIAID flow core for their assistance with flow sorting and analysis and the NIAMS sequencing core for assistance with sequencing and analysis. We thank J. Reilley and J. Cannons for assistance with sample retrieval. The study was funded by the Intramural Research Programs of NIAID and NIAMS. The relevant grants are ZIA-AI001251 (to D.M.S.), ZIA-AI001202 (to P.A.F.-G.), ZIA-AI001098 (to J.D.M.), ZIA-AI001240 (to P.S.) and ZIC-AR041181 (to F.M.).

Author information

Author notes

  1. These authors contributed equally: Joshua D. Milner, Pamela A. Frischmeyer-Guerrerio, Daniella M. Schwartz.

Authors and Affiliations

  1. Laboratory of Allergic Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA

    Aran Son, McKella Sylvester, Estefania Vazquez, Tamara Haque, Moses M. Kitakule, Pamela A. Frischmeyer-Guerrerio & Daniella M. Schwartz

  2. Office of Science and Technology, National Institute of Arthritis, Musculoskeletal, and Skin Diseases, National Institutes of Health, Bethesda, MD, USA

    Francoise Meylan

  3. Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA

    Julio Gomez-Rodriguez, Zenia Kaul, Kalpana Manthiram, Rama K. Gurram, Jinfang Zhu & Pamela Schwartzberg

  4. TCR Therapeutics, Cambridge, MA, USA

    Julio Gomez-Rodriguez

  5. Division of Rheumatology and Clinical Immunology, University of Pittsburgh, Pittsburgh, PA, USA

    Guido H. Falduto, Chujun Wang & Daniella M. Schwartz

  6. Division of Pediatric Allergy Immunology and Rheumatology, Department of Pediatrics, Columbia University Medical Center, New York, NY, USA

    Moses M. Kitakule & Joshua D. Milner

  7. Pathology Core, Laboratory of Immunogenetics, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA

    Chen-Feng Qi

  8. Embryonic Stem Cell and Transgenic Core, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA

    Jun Cheng

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Contributions

F.M. and J.G.-R. contributed equally to this manuscript. A.S., F.M., J.G.-R., Z.K., M.K., M.S., G.F., C.W., T.H., E.V., J.C., D.M.S. and C.F.Q. performed experiments and analyzed data. K.M. and J.D.M. provided patient samples. R.G. and J.Z. provided proprietary reagents. A.S. and D.M.S. authored the manuscript. J.D.M., P.S., P.F.G. and D.M.S. provided supervision.

Corresponding author

Correspondence to Daniella M. Schwartz.

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Competing interests

J.G.-R. is currently employed by TCR Therapeutics. F.M. has been recruited by AstraZeneca and was very briefly employed by Innovent Biologics. All other authors have no competing interests.

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Nature Immunology thanks Lionel Apetoh, Paula Licona-Limon and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: L. A. Dempsey, in collaboration with the Nature Immunology team. Peer reviewer reports are available.

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Extended data

Extended Data Fig. 1 Corresponds to Fig. 1.

a–e. Naïve CD4+ T cells from HVs were activated for 5 d with αCD3, αCD28, IL-2 and subset-promoting cytokines and antibodies. After 5 d, αCD3/αCD28 were withdrawn, and cells were cultured with IL-2 and subset-promoting cytokines and antibodies. Pooled results show production of IFN-γ (a), n = 9 (Th1, Th2) or 10 (Th9); IL-4 (b), n = 8 (Th1), 9 (Th2), or 4 (Th9); IL-13 (c) n = 8 (Th1), 9 (Th2), or 4 (Th9); IL-9 (d) n = 9 (Th1, Th2), or 10 (Th9); and IL-2 (e) n = 9 (Th1, Th2), or 10 (Th9), with or without PMA and Ionomycin (P/I). *p < 0.05, **p < 0.01, ***p < 0.005, ****p < 0.0001, Wilcoxon. f. Bar graphs show % IL-9 positive cells differentiated to d8 Th9 as above and restimulated with vehicle versus plate-bound αCD3 at escalating doses (0.1, 0.5, 1, 5, 10, 50, 100 μg/mL), or P/I. *p < 0.05, **p < 0.01, ratio paired t-test (n = 3) g–k. Naïve CD4+ T cells from WT C57BL/6 mice were activated for 3 d with αCD3, αCD28, IL-2, and subset-promoting cytokines and antibodies. After 3 d, αCD3/αCD28 were withdrawn, and cells were cultured with IL-2 and subset-promoting cytokines and antibodies. Pooled results show production of IFN-γ (f), n = 6 (Th1, Th2) or 3 (Th9); IL-4 (g), n = 6 (Th1, Th2) or 5 (Th9); IL-13 (h), n = 6 (Th1), 7 (Th2), or 5 (Th9); IL-9 (i), n = 6 (Th1), 7 (Th2), or 10 (Th9); and IL-2 (j), n = 4 (Th1), 5 (Th2), or 3 (Th9), with or without P/I. *p < 0.05, **p < 0.01, ***p < 0.005, ****p < 0.0001, Wilcoxon. l. Bar graphs show % IL-9+ cells of resting (d8) human Th9 cells restimulated with Th9 supernatants and vehicle, αIL-2 (20 μg/mL), αIL-4 (20 μg/mL), or αIL-1β (20 μg/mL). *p < 0.05, **p < 0.01, paired t-test versus Th9 supernatants (n = 3). For all line/bar graphs, error bars show ± s.e.m. Box plots show all data points (min to max, lines at median). All statistical tests are 2-sided.

Source data

Extended Data Fig. 2 Corresponds to Fig. 2.

a. Graph shows % IL-9+ of d8 human Th9 cells restimulated with vehicle (n = 7), IL-1β (n = 3), IL-18 (n = 4), IL-33 (n = 4), IL-36α (n = 7), or IL-36γ (n = 7). b, c. Timelines show experimental design; graphs shows % IL-9+ (n = 6) for human non-restimulated T cells differentiated as in Fig. 1a, with STAT5 inhibitor or STAT6 inhibitor from d0-5 (b) or d5-8 (c). d–f. Bar graph shows concentration (pg/mL, ELISA) of IL-2 (d), IL-4 (e), and IL-9 (f) in supernatants of human in vitro differentiated Th1- or Th9 (d5), or Th2 (d14) cells, after 48 h restimulation. g, h. d8 human Th9 cells were restimulated with escalating doses of IL-2 (b) (2, 20, or 200 ng/mL) or IL-4 (c) (6, 60, or 500 ng/mL). *p < 0.05, paired t-test (n = 3). i, j. Representative flow plots (i) and bar graph (j) show % IL-9+ cells in resting (d4) murine Th9 cells restimulated with IL-2 + IL-4 (n = 10), **p < 0.01, Wilcoxon test. k. Bar graph shows pooled results d8 human Th9 cells restimulated with vehicle (n = 9), IL-6 (n = 3), IL-7 (n = 5), IL-12 (n = 3), IL-21 (n = 3), or TSLP (n = 4). l, m. Bar graphs show pooled (n = 6) mean fluorescence intensity (MFI) of pSTAT5 (l) and pSTAT6 (m) in d8 human IL-9+ and IL-9− Th9 cells restimulated with IL-2, IL-4, or IL-2 + IL-4. *p < 0.05, **p < 0.01, Wilcoxon. n. Bar graphs show pooled (n = 3) % IL-9+ d8 human Th9 cells stimulated with IL-2 and IL-4 in the presence of STAT5 or STAT6 inhibitor. *p < 0.05, paired t-test. For all line/bar graphs, error bars show ± s.e.m. Box plots show all data points (min to max, lines at median). All statistical tests are 2-sided.

Source data

Extended Data Fig. 3 Corresponds to Fig. 3.

a, b. Line graph shows % IL-9+ cells of human Th9 differentiated as in Fig. 1a. Cells were restimulated with vehicle, IL-2, IL-4, or IL-2 + IL-4 (a, n = 5); b. on d5 (n = 14), d8/d11 (n = 17), d15 (n = 16), and d20 (n = 11), cells were restimulated with PMA + ionomycin (P/I) or P/I + IL-2 + IL-4. c, d. Line graph shows % IL-9+ cells of murine Th9 differentiated as in Fig. 1d. Cells were restimulated with vehicle, IL-2, IL-4, or IL-2 + IL-4 (c, n = 4). d. On d3 (n = 12), d4 (n = 11), d5 (n = 9), d6 (n = 3), d7 (n = 3), and d8 (n = 6), cells were restimulated P/I or P/I + IL-2 + IL-4. e, f. Representative flow plots (e) and graphs (f) show % IL-9+ of circulating Th9 cells stimulated with P/I or P/I + IL-2 + IL-4, from HV (n = 5) or atopic patients (AD, n = 14). g. Line graphs shows pooled results (n = 5) for % IL-9+ cells from IL-9 reporter (INFER) mice, sorted on d3 and maintained as in Fig. 1d. Cells were restimulated with vehicle, IL-2 + IL-4, P/I or P/I + IL-2 + IL-4. h. Bar graphs show viability (n = 4) for Th9 cells. For all experiments: *P < 0.05, **P < 0.01, ***P < 0.005, ****P < 0.001, paired t-test. i. Venn diagram shows generation of ‘allergic Th9’ cassette using: HDM-reactive circulating Th9 cells from allergic patients1, Th9 clones from healthy subjects2, pulmonary Th9 cells from IL-9 reporter mice, and in vitro differentiated Th9 cells3. Genes differentially expressed >1 dataset were selected. j. Bar graph shows pathway enrichment scores and FDRs (DAVID) for the ‘allergic Th9’ cassette. k. Scatterplot shows enrichment score (GSEA) and FDR for correlation (Pearson) of STAT1, STAT3, STAT4, STAT5, and STAT6 target genes with murine Il9 expression and human IL9 expression. For all line/bar graphs, error bars show ± s.e.m. Box plots show all data points (min to max, lines at median). All statistical tests are two-sided.

Source data

Extended Data Fig. 4 Corresponds to Fig. 4.

a, b. Genome tracks show poised enhancer (H3K4m1, red), active promoter (H3K4m3, blue), active enhancer (H3K27Ac, purple) marks, and accessibility (ATAC, green) of the murine Th2 (a, Il4−Il13-Rad50-Il5) and Gzmb loci at different time points during Th9 differentiation and resting. c, d. ATAC-seq tracks show the human extended IL9 locus including the promoter (Il9p), downstream enhancer (DS) and upstream enhancers 1–4 (E1-E4), in naïve T cells, Th1 cells (d5), and Th9 cells (d5) (c), and in ex vivo naïve, Th1, Th2, and Th17 cells from ENCODE (d). e, f. Genome tracks show poised enhancer (H3K4m1, red), active promoter (H3K4m3, blue), active enhancer (H3K27Ac, purple) marks, and accessibility (ATAC, green) of the human Th2 (e, IL4-IL13-RAD50-IL5) and GZMB loci at different time points during Th9 differentiation and resting. g. Heatmap shows Pearson correlation of Il9/IL9 expression, ATAC-seq tag density, H3K4me1 tag density, H3K4me3 tag density, and H3K27Ac tag density with those of Il4/IL4, Il13/IL13, Rad50/RAD50, and Il5/IL5.

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Extended Data Fig. 5 Corresponds to Fig. 5.

a–c. Pooled counts of pulmonary CD45+TCRβ+CD4+CD44+IL-13+ cells (a, n = 8, PBS; n = 13, papain), CD45+TCRβ+CD4+CD44+IL-17A+ cells (b, n = 3, PBS; n = 6, papain), and CD45+TCRβ+CD4+CD44+IL-2+ cells (c, n = 8, PBS; n = 13, papain) from mice treated with isotype versus αMHC2 between papain sensitization and challenge. d. Th9 cells were differentiated in the presence of vehicle versus BMS-509744 (Itk inhibitor; 0.5 μM, 1 μM, 1.5 μM) and restimulated with αCD3 + αCD28 (n = 3) e-f. Bar graphs (n = 7) show %IL-9+ (e) of Th9 and %IL-4+ (f) of Th2 cells restimulated with αCD3 + αCD28 and vehicle versus BMS-509744 (0.5 μM, 1 μM), *P < 0.05 paired t-test. g. Design of inducible Itk-deleted mouse. Itkflox/flox were crossed ERT-Cre mice to generate ItkERT mice. h. Representative flow plot and bar graph show %IL-9+ cells of Th9 cells from TAM-treated (Itk-deleted, n = 3) versus TAM-untreated (n = 5) mice, *P < 0.05 Mann–Whitney U-test. i. Timeline shows model of papain-induced airway inflammation with Itk deletion. Mice were treated with vehicle versus tamoxifen between sensitization and challenge. j. Gel shows that injection of tamoxifen results in deletion of WT Itk gene in mice from (i). k–n. Representative periodic acid-Schiff (PAS) stained images (k), pooled histology scores (l, n = 3, PBS; n = 5, papain), pulmonary CD45+TCRβ+CD4+CD44+IL-9+ (Th9) (m, n = 5, PBS; n = 10, papain), and pulmonary CD45+TCRβ+CD4+CD44+IL-13+ (Th2) cell counts (n, n = 3, PBS; n = 5, papain), from Itkf/f treated with vehicle versus tamoxifen as in (i). o–r. Pooled counts of pulmonary CD45+CD4- IL-9+ cells (o, n = 5, PBS; n = 8, papain), CD45+TCRβ+CD4+CD44+IL-13+ cells (Th2) (p, n = 5, PBS; n = 8, papain), CD45+TCRβ+CD4+CD44+IL-17A+ cells (Th17) (q, n = 4, PBS; n = 7, papain), and CD45+TCRβ+CD4+CD44+IL-2+ cells (r n = 4, PBS; n = 7, papain) ILC2-deficient mice treated with isotype versus αMHC2 between papain sensitization and challenge. For all in vivo experiments, *P < 0.05, **P < 0.01, ***P < 0.005, ****P < 0.001, Mann–Whitney U-test. For all line/bar graphs, error bars show ± s.e.m. Box plots show all data points (min to max, lines at median). All statistical tests were two-sided.

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Extended Data Fig. 6 Corresponds to Fig. 6.

a. Timeline shows Th9 adoptive transfer-induced airway inflammation. Ovalbumin (OVA)-specific OT-ii Th9 cells were differentiated in vitro, sorted for IL-9+ cells, and adoptively transferred. Recipient mice were treated with IL-2 and IL-4 intratracheally and intranasally. b. Timeline shows papain-induced airway inflammation with tofacitinib; mice were treated with vehicle versus tofacitinib between sensitization and challenge. c–e. Pooled counts of pulmonary CD45+TCRβ+CD4+CD44+IL-13+ (c), CD45+TCRβ+CD4+CD44+IL-17A+ (d), and CD45+TCRβ+CD4+CD44+IL-2+ cells (e) mice treated with vehicle versus tofacitinib between sensitization and challenge. n = 6 (PBS/PBS), 5 (PBS/tofa), 10 (papain/MC and papain/tofa) f. Timeline shows papain-induced airway inflammation with tofacitinib and αIL-9. Mice were treated as in (b) but also received isotype or αIL-9 every other day. g–k. Pooled counts of pulmonary CD45+TCRβ+CD4+CD44+IL-9+ (g), CD45+TCRβ+CD4+CD44+IL-13+ (h), and live CD45+TCRβ+CD4+CD44+IL-4+ cells (i), representative periodic acid-Schiff (PAS) stained images (j) and pooled histology scores (k) of mice treated as in Extended Data Figure 6f; n = 5 (PBS/isotype/MC), 8 (papain/isotype/MC), and 10 (papain/αIL-9/MC and papain/αIL-9/tofa). For all in vivo experiments, *P < 0.05, **P < 0.01, ***P < 0.005, ****P < 0.001, Mann–Whitney U-test. l-o. Line graphs show expression over 96 h of IL9 (l), STAT5A (m), STAT5B (n), and STAT6 (o), in skin of nickel-allergic patients exposed to nickel over 96 h (n = 7) p. Graph shows normalized enrichment scores and FDR (GSEA) for expression of ‘allergic Th9’ cassette, STAT5-induced genes, and STAT6-induced genes in 7h-nickel-exposed, 48h-nickel-exposed, and 96h-nickel-exposed skin relative to pre-exposed/unexposed skin. For all line/bar graphs, error bars show ± s.e.m. Box plots show all data points (min to max, lines at median). All statistical tests are two-sided.

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Extended Data Fig. 7 Reporting of gating strategy and validation for murine cell studies.

a–f. Representative flow cytometric plots show gating strategies for naïve T cell sorting (a), Th9 sorting for transfer experiments (b), for in vitro differentiated Th9, Th1, and Th2 cells shown in Figs. 1–3 and Extended Data Figs. 1–3(c), for in vivo memory T helper subsets in Figs. 5, 6 and Extended Data Figs. 5, 6(d, e), and for adoptively transferred CD45.1+ Th9 cells analyzed in murine lung 2 days after transfer (f). g. Timeline shows protocol for validation of MHC2 blocking antibody in vivo. Mice were sensitized to ovalbumin (OVA) intraperitoneally on d0 and d7, then challenged on d13 and d14. MHC blocking antibody was administered with each dose of OVA. Bar graphs show results of MHC2 validation experiment. Blockade of MHC2 reduced histology scores, BAL Eosinophil counts, and lung-infiltrating IL-4+ and IL-13+ (Th2) cell counts. *P < 0.05, **P < 0.01, Mann–Whitney U-test. All statistical tests are two-sided.

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Extended Data Fig. 8 Reporting of gating strategy for human cell studies.

Representative flow cytometric plots show gating strategies for naïve T cell sorting (a), gating for in vitro differentiated Th9, Th1, and Th2 cells shown in Figs. 1–3 and Extended Data Figures 1–3 (b), and for ex vivo circulating memory Th9 cells in stimulated PBMC samples (c).

Extended Data Table 1 Th9 cassette genes
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Extended Data Table 2 Public datasets analyzed
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Supplementary information

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Son, A., Meylan, F., Gomez-Rodriguez, J. et al. Dynamic chromatin accessibility licenses STAT5- and STAT6-dependent innate-like function of TH9 cells to promote allergic inflammation. Nat Immunol 24, 1036–1048 (2023). https://doi.org/10.1038/s41590-023-01501-5

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