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.

Homeostatic IL-13 in healthy skin directs dendritic cell differentiation to promote TH2 and inhibit TH17 cell polarization

An Author Correction to this article was published on 13 April 2022

This article has been updated

Abstract

The signals driving the adaptation of type 2 dendritic cells (DC2s) to diverse peripheral environments remain mostly undefined. We show that differentiation of CD11blo migratory DC2s—a DC2 population unique to the dermis—required IL-13 signaling dependent on the transcription factors STAT6 and KLF4, whereas DC2s in lung and small intestine were STAT6-independent. Similarly, human DC2s in skin expressed an IL-4 and IL-13 gene signature that was not found in blood, spleen and lung DCs. In mice, IL-13 was secreted homeostatically by dermal innate lymphoid cells and was independent of microbiota, TSLP or IL-33. In the absence of IL-13 signaling, dermal DC2s were stable in number but remained CD11bhi and showed defective activation in response to allergens, with diminished ability to support the development of IL-4+GATA3+ helper T cells (TH), whereas antifungal IL-17+RORγt+ TH cells were increased. Therefore, homeostatic IL-13 fosters a noninflammatory skin environment that supports allergic sensitization.

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

Access options

Buy article

Get time limited or full article access on ReadCube.

$32.00

All prices are NET prices.

Fig. 1: DC2s display tissue and subset-specific heterogeneity at steady state.
Fig. 2: STAT6-dependent signaling controls CD11blo DC2 differentiation at steady state.
Fig. 3: IL-13 is necessary for the differentiation of dermal CD11blo DC2s in vivo.
Fig. 4: Homeostatic IL-13 is produced by skin innate lymphoid cells irrespective of microbial or alarmin signaling and promotes the differentiation of CD11blo DC2s.
Fig. 5: IL-13 signaling drives the development of CD11blo DC2s in vitro and requires KLF4 expression in DCs.
Fig. 6: IL-13 signaling in DCs is required for optimal IL-4+ and IL-13+ CD4+ T cell responses in skin, but not lung, draining LNs.
Fig. 7: CD11bhi and CD11blo DC2s are differentially activated by allergens and fungal antigens.
Fig. 8: IL-4/IL-13 signature genes are enriched in the transcriptome of DC2s from human skin, but not lung.

Data availability

The authors declare that the data supporting the findings of this study are available within the paper and its supplementary information files or are available from the authors upon reasonable requests. Sequencing data generated for this study including bulk and scRNA-seq data presented in Figs. 1, 2 and Extended Data Fig. 2: raw RNA-seq data as FASTQ files have been deposited in NCBI SRA under bioproject PRJNA668222. IL-13 KO mice are available from G.L.G., MIMR upon request and pending approval of a Material Transfer Agreement. Source data are provided with this paper.

Code availability

All code and associated parameters used for the analysis of bulk and scRNA-seq data as well as the reanalysis of publicly available dataset in Fig. 8 are available at: https://doi.org/10.5281/zenodo.5534993.

Change history

References

  1. Eisenbarth, S. C. Dendritic cell subsets in T cell programming: location dictates function. Nat. Rev. Immunol. 19, 89–103 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Guilliams, M. et al. Unsupervised high-dimensional analysis aligns dendritic cells across tissues and species. Immunity 45, 669–684 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Hilligan, K. & Ronchese, F. Antigen presentation by dendritic cells and their instruction of CD4+ T helper cell responses. Cell Mol. Immunol. 17, 587–599 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Guerin, A. et al. IRF4 haploinsufficiency in a family with Whipple’s disease. eLife 7, e32340 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  5. Alcantara-Hernandez, M. et al. High-dimensional phenotypic mapping of human dendritic cells reveals interindividual variation and tissue specialization. Immunity 47, 1037–1050.e1036 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Heidkamp, G. F. et al. Human lymphoid organ dendritic cell identity is predominantly dictated by ontogeny, not tissue microenvironment. Sci. Immunol. 1, eaai7677 (2016).

    Article  PubMed  Google Scholar 

  7. Sichien, D., Lambrecht, B. N., Guilliams, M. & Scott, C. L. Development of conventional dendritic cells: from common bone marrow progenitors to multiple subsets in peripheral tissues. Mucosal Immunol. 10, 831–844 (2017).

    Article  CAS  PubMed  Google Scholar 

  8. Miller, J. C. et al. Deciphering the transcriptional network of the dendritic cell lineage. Nat. Immunol. 13, 888–899 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Tussiwand, R. et al. Klf4 expression in conventional dendritic cells is required for T helper 2 cell responses. Immunity 42, 916–928 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Henri, S. et al. CD207+ CD103+ dermal dendritic cells cross-present keratinocyte-derived antigens irrespective of the presence of Langerhans cells. J. Exp. Med. 207, 189–206 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. McCormick, S. M. & Heller, N. M. Commentary: IL-4 and IL-13 receptors and signaling. Cytokine 75, 38–50 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Schlitzer, A. et al. Identification of cDC1- and cDC2-committed DC progenitors reveals early lineage priming at the common DC progenitor stage in the bone marrow. Nat. Immunol. 16, 718–728 (2015).

    Article  CAS  PubMed  Google Scholar 

  13. Roediger, B. et al. Cutaneous immunosurveillance and regulation of inflammation by group 2 innate lymphoid cells. Nat. Immunol. 14, 564–573 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Kobayashi, T. et al. Homeostatic control of sebaceous glands by innate lymphoid cells regulates commensal bacteria equilibrium. Cell 176, 982–997 e916 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Ricardo-Gonzalez, R. R. et al. Tissue signals imprint ILC2 identity with anticipatory function. Nat. Immunol. 19, 1093–1099 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Oliphant, C. J. et al. MHCII-mediated dialog between group 2 innate lymphoid cells and CD4(+) T cells potentiates type 2 immunity and promotes parasitic helminth expulsion. Immunity 41, 283–295 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Naik, S. H. et al. Development of plasmacytoid and conventional dendritic cell subtypes from single precursor cells derived in vitro and in vivo. Nat. Immunol. 8, 1217–1226 (2007).

    Article  CAS  PubMed  Google Scholar 

  18. Blecher-Gonen, R. et al. Single-Cell analysis of diverse pathogen responses defines a molecular roadmap for generating antigen-specific immunity. Cell Syst. 8, 109–121 e106 (2019).

    Article  CAS  PubMed  Google Scholar 

  19. Hilligan, K. L. et al. Dermal IRF4+ dendritic cells and monocytes license CD4+ T helper cells to distinct cytokine profiles. Nat. Commun. 11, 5637 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Lamiable, O., Mayer, J. U., Munoz-Erazo, L. & Ronchese, F. Dendritic cells in Th2 immune responses and allergic sensitization. Immunol. Cell Biol. 98, 807–818 (2020).

    Article  CAS  PubMed  Google Scholar 

  21. Connor, L., Tang, S., Camberis, M., Le Gros, G. & Ronchese, F. Helminth-conditioned DC prime CD4+ T cells to IL-4 production in vivo. J. Immunol. 193, 2709–2717 (2014).

    Article  CAS  PubMed  Google Scholar 

  22. Connor, L. M. et al. Th2 responses are primed by skin dendritic cells with distinct transcriptional profiles. J. Exp. Med. 214, 125–142 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Harris, N. L., Peach, R. J. & Ronchese, F. CTLA4-Ig inhibits optimal T helper 2 cell development but not protective immunity or memory response to Nippostrongylus brasiliensis. Eur. J. Immunol. 29, 311–316 (1999).

    Article  CAS  PubMed  Google Scholar 

  24. Pellefigues, C. et al. Toll-like receptor 4, but not neutrophil extracellular traps, promote IFN type I expression to enhance Th2 responses to Nippostrongylus brasiliensis. Front. Immunol. 8, 1575 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Bojang, E., Ghuman, H., Kumwenda, P. & Hall, R. A. Immune sensing of Candida albicans. J. Fungi (Basel) 7, 119 (2021).

    Article  CAS  Google Scholar 

  26. Acharya, M. et al. αv Integrin expression by DCs is required for Th17 cell differentiation and development of experimental autoimmune encephalomyelitis in mice. J. Clin. Invest. 120, 4445–4452 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Melton, A. C. et al. Expression of αvβ8 integrin on dendritic cells regulates Th17 cell development and experimental autoimmune encephalomyelitis in mice. J. Clin. Invest. 120, 4436–4444 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. 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 

  29. Jassal, B. et al. The reactome pathway knowledgebase. Nucleic Acids Res. 48, D498–D503 (2020).

    CAS  PubMed  Google Scholar 

  30. Rojahn, T. B. et al. Single-cell transcriptomics combined with interstitial fluid proteomics defines cell type-specific immune regulation in atopic dermatitis. J Allergy Clin Immunol 146, 1056–1069 (2020).

    Article  CAS  PubMed  Google Scholar 

  31. He, H. et al. Single-cell transcriptome analysis of human skin identifies novel fibroblast subpopulation and enrichment of immune subsets in atopic dermatitis. J. Allergy Clin. Immunol. 145, 1615–1628 (2020).

    Article  CAS  PubMed  Google Scholar 

  32. Teunissen, M. B. M. et al. Composition of innate lymphoid cell subsets in the human skin: enrichment of NCR(+) ILC3 in lesional skin and blood of psoriasis patients. J. Invest Dermatol 134, 2351–2360 (2014).

    Article  CAS  PubMed  Google Scholar 

  33. Strid, J., McLean, W. H. I. & Irvine, A. D. Too much, too little or just enough: a Goldilocks effect for IL-13 and skin barrier regulation? J. Invest. Dermatol. 136, 561–564 (2016).

    Article  CAS  PubMed  Google Scholar 

  34. Laffont, S. et al. Androgen signaling negatively controls group 2 innate lymphoid cells. J. Exp. Med. 214, 1581–1592 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Bielecki, P. et al. Skin-resident innate lymphoid cells converge on a pathogenic effector state. Nature 592, 128–132 (2021).

    CAS  PubMed  PubMed Central  Google Scholar 

  36. Moro, K. et al. Interferon and IL-27 antagonize the function of group 2 innate lymphoid cells and type 2 innate immune responses. Nat. Immunol. 17, 76–86 (2016).

    Article  CAS  PubMed  Google Scholar 

  37. Duerr, C. U. et al. Type I interferon restricts type 2 immunopathology through the regulation of group 2 innate lymphoid cells. Nat. Immunol. 17, 65–75 (2016).

    Article  CAS  PubMed  Google Scholar 

  38. Ronchese, F., Hilligan, K. L. & Mayer, J. U. Dendritic cells and the skin environment. Curr. Opin. Immunol. 64, 56–62 (2020).

    Article  CAS  PubMed  Google Scholar 

  39. Halim, T. Y. et al. Group 2 innate lymphoid cells license dendritic cells to potentiate memory TH2 cell responses. Nat. Immunol. 17, 57–64 (2016).

    Article  CAS  PubMed  Google Scholar 

  40. Halim, T. Y. et al. Group 2 innate lymphoid cells are critical for the initiation of adaptive T helper 2 cell-mediated allergic lung inflammation. Immunity 40, 425–435 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Alpan, O., Bachelder, E., Isil, E., Arnheiter, H. & Matzinger, P. ‘Educated’ dendritic cells act as messengers from memory to naive T helper cells. Nat. Immunol. 5, 615–622 (2004).

    Article  CAS  PubMed  Google Scholar 

  42. Zhou, X. et al. A positive feedback loop reinforces the allergic immune response in human peanut allergy. J. Exp. Med. 218, e20201793 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Harrison, O. J. et al. Commensal-specific T cell plasticity promotes rapid tissue adaptation to injury. Science 363, eaat6280 (2019).

    Article  CAS  PubMed  Google Scholar 

  44. Durai, V. & Murphy, K. M. Functions of murine dendritic cells. Immunity 45, 719–736 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Du Toit, G. et al. Early consumption of peanuts in infancy is associated with a low prevalence of peanut allergy. J. Allergy Clin. Immunol. 122, 984–991 (2008).

    Article  CAS  PubMed  Google Scholar 

  46. Irvine, A. D., McLean, W. H. & Leung, D. Y. Filaggrin mutations associated with skin and allergic diseases. N. Engl. J. Med. 365, 1315–1327 (2011).

    Article  CAS  PubMed  Google Scholar 

  47. McAleer, M. A. & Irvine, A. D. The multifunctional role of filaggrin in allergic skin disease. J. Allergy Clin. Immunol. 131, 280–291 (2013).

    Article  CAS  PubMed  Google Scholar 

  48. Ochiai, S. et al. CD326(lo)CD103(lo)CD11b(lo) dermal dendritic cells are activated by thymic stromal lymphopoietin during contact sensitization in mice. J. Immunol. 193, 2504–2511 (2014).

    Article  CAS  PubMed  Google Scholar 

  49. Ziegler, S. F. Thymic stromal lymphopoietin and allergic disease. J. Allergy Clin. Immunol. 130, 845–852 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Baurecht, H. et al. Genome-wide comparative analysis of atopic dermatitis and psoriasis gives insight into opposing genetic mechanisms. Am. J. Hum. Genet 96, 104–120 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Schindelin, J. et al. Fiji: an open-source platform for biological-image analysis. Nat. Methods 9, 676–682 (2012).

    Article  CAS  PubMed  Google Scholar 

  52. Jones, T. R. et al. CellProfiler Analyst: data exploration and analysis software for complex image-based screens. BMC Bioinf. 9, 482 (2008).

    Article  CAS  Google Scholar 

  53. Schapiro, D. et al. histoCAT: analysis of cell phenotypes and interactions in multiplex image cytometry data. Nat. Methods 14, 873–876 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).

    Article  CAS  PubMed  Google Scholar 

  56. Ewels, P., Magnusson, M., Lundin, S. & Kaller, M. MultiQC: summarize analysis results for multiple tools and samples in a single report. Bioinformatics 32, 3047–3048 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Liao, Y., Smyth, G. K. & Shi, W. The Subread aligner: fast, accurate and scalable read mapping by seed-and-vote. Nucleic Acids Res. 41, e108 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. 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  CAS  PubMed  PubMed Central  Google Scholar 

  59. Conway, J. R., Lex, A. & Gehlenborg, N. UpSetR: an R package for the visualization of intersecting sets and their properties. Bioinformatics 33, 2938–2940 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Matys, V. et al. TRANSFAC and its module TRANSCompel: transcriptional gene regulation in eukaryotes. Nucleic Acids Res. 34, D108–D110 (2006).

    Article  CAS  PubMed  Google Scholar 

  61. Hamada, M., Wijaya, E., Frith, M. C. & Asai, K. Probabilistic alignments with quality scores: an application to short-read mapping toward accurate SNP/indel detection. Bioinformatics 27, 3085–3092 (2011).

    Article  CAS  PubMed  Google Scholar 

  62. Srivastava, A., Malik, L., Smith, T., Sudbery, I. & Patro, R. Alevin efficiently estimates accurate gene abundances from dscRNA-seq data. Genome Biol. 20, 65 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  63. Hao, Y. et al. Integrated analysis of multimodal single-cell data. Cell 184, 3573–3587 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Cao, J. et al. The single-cell transcriptional landscape of mammalian organogenesis. Nature 566, 496–502 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Haniffa, M. et al. Human tissues contain CD141hi cross-presenting dendritic cells with functional homology to mouse CD103+ nonlymphoid dendritic cells. Immunity 37, 60–73 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. McGovern, N. et al. Human fetal dendritic cells promote prenatal T-cell immune suppression through arginase-2. Nature 546, 662–666 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Yu, C. I. et al. Human CD1c+ dendritic cells drive the differentiation of CD103+ CD8+ mucosal effector T cells via the cytokine TGF-beta. Immunity 38, 818–830 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Chen, Y. L. et al. Re-evaluation of human BDCA-2+ DC during acute sterile skin inflammation. J. Exp. Med. 217, jam.20190811 (2020).

    Article  CAS  Google Scholar 

  69. Stuart, T. et al. Comprehensive integration of single-cell data. Cell 177, 1888–1902 e1821 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We wish to thank G. Ogg, Oxford University, for sharing raw data of the scRNA-seq analysis of human skin blisters; P.M. Brunner and V. Vorstandlechner, Medical University of Vienna, for their advice on single-cell QC filtering and data analysis of scRNA-seq data of human skin biopsies and blisters cells; Y. Wang, Google, for developing the Shiny browser for scRNA-seq data and providing debugging help; M. Brewerton, Auckland DHB; A. Livingstone and T. Mosmann, University of Rochester; A. MacDonald, University of Manchester; S. Nutt, Walter and Eliza Hall Institute; and all colleagues at the Malaghan Institute of Medical Research for discussion and suggestions. The MR1 tetramer technology was developed jointly by J. McCluskey, J. Rossjohn and D. Fairlie, and the material was produced by the NIH Tetramer Core Facility as permitted to be distributed by the University of Melbourne, Australia. We also gratefully acknowledge the flow cytometry support of the members of the Hugh Green Cytometry Centre and the expert animal husbandry of the Biomedical Research Unit at the Malaghan Institute. This work was funded by an Independent Research Organization grant from the Health Research Council of New Zealand (HRC) to the Malaghan Institute (18-1003), an HRC Project grant to F.R. (18-510), and the Marjorie Barclay Trust. K.L.H. was supported by a Malaghan Institute Postdoctoral Fellowship and the Intramural Research Program of the NIAID, NIH. M.R.H. was supported by a Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society (grant no. 105644/Z/14/Z), and a Lister Institute of Preventative Medicine Prize. R.G.D. was supported by an EMBO long-term fellowship (ALTF 1209-2019).

Author information

Authors and Affiliations

Authors

Contributions

J.U.M., O.L. and F.R. conceived the study; J.U.M., O.L., K.L.H., J.S.C., R.G.D., J.Y., G.R.W., L.M.-E., K.A.W., E.J.H., S.-C.T., S.C.C., S.V.D. and L.M.C. designed, carried out and analyzed experiments; D.A.E. and S.I.O. carried out bioinformatics analyses, wrote code and visualized results; C.R.M., F.B., A.S., R.T., D.G.O., D.J. and G.L.G. provided essential reagents and/or expertise; O.L., A.S., M.R.H. and F.R. supervised and/or funded research; J.U.M., O.L. and F.R. wrote the original draft; J.U.M., O.L., K.L.H. and F.R. finalized the submission and revision with input from all authors. O.L. and F.R. prepared the final manuscript for publication.

Corresponding author

Correspondence to Franca Ronchese.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature Immunology thanks Michel Gilliet, Daniel Kaplan and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Ioana Visan 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 Gating strategy for DC and DC2 populations in the skin, lung and small intestine of naive mice and their draining lymph nodes.

a, Gating strategy for migratory DC2 subsets in skin, lung and small intestine (SI) dLNs. Generic gating on live single CD3B220Ly6G (Lin) and Ly6C cells was performed for all samples before gating on dLN-specific DC2 subsets. b, Gating strategy for DC2 subsets in skin, lung and SI. Generic gating on live single CD45+CD3B220Ly6G (Lin) and CD64Ly6C cells was performed for all samples before gating on tissue-specific DC2 subsets. c, Numbers of DC2s in the skin, lung and SI dLN of Irf4f/f and Irf4f/f CD11c-Cre mice. Bar graphs show mean ± SEM for 5-8 mice pooled from 2 independent experiments. Each symbol refers to one mouse. P values were determined using a two-tailed Student’s t-test. *P < 0.05; ***P < 0.001; only significant comparisons are indicated.

Source data

Extended Data Fig. 2 Phenotypic and transcriptomic characterization of myeloid and DC2 populations in C57BL/6 and STAT6 KO mice.

a, Gating strategy for DC2 precursors in the bone marrow and skin. b, Representative Opt-SNE visualization of concatenated live single CD45+CD3CD19 myeloid cells from the skin of naive C57BL/6 (C57) and STAT6 KO mice; combined data from both strains are shown in the color image. Opt-SNE was performed on 16648 events (2081 events/mouse, 4 mice per genoype, one experiment) using 12 parameters (XCR1, CD206, CD11b, Ly6c, CD11c, Ly6G, SIRPα, CD326, CD26, CD64, BST2, MHC-II) with default OMIQ settings and a perplexity of 30 with 1000 iterations. Population frequencies are shown in the bar graph. c, Numbers of migratory DC2s in the skin, lung and small intestine (SI) dLNs of naive C57 and STAT6 KO mice. d, Number of migratory DCs in the skin dLN of naive C57 and STAT6 KO mice. e, Relative frequencies (top) and numbers (bottom) of CD11bhi and CD11blo DC2s in the auricular (au), inguinal (i), axillary (ax), brachial (b) and popliteal (p) skin dLNs of naive C57 and STAT6 KO mice. f, Principal component (PC) analyses of all expressed genes in DC2 subsets from the skin, lung and SI dLNs of naive C57 and STAT6 KO mice. Each symbol refers to a biological replicate. g, UpSet plot showing the numbers of unique and shared differentially expressed genes (DEGs, including up- and downregulated genes) in the indicated DC2 subsets from the skin, lung and SI dLNs of STAT6 KO vs. C57 mice. b-e, Bar graphs show mean ± SEM for n=9 (b) n=4-5 (c) n=9-10 (d) n=5-8 (e) mice pooled from 2 independent experiments. Each symbol refers to one mouse. P values were determined using a two-tailed unpaired Student’s t-test. *P < 0.05; ***P < 0.001; only significant comparisons are indicated.

Source data

Extended Data Fig. 3 IL-13 signalling is necessary for the development of CD11blo DC2s in skin.

a, Experimental set-up of mixed wild type and STAT6 KO BM chimeras. The phenotype of skin DC2s from each donor BM is shown in the contour plots, subsets are quantified in the bar graph. b, Schematic of the genomic Il13 locus in wild type and IL-13 KO mice illustrating the deletion of exons 2 and 3. c, Phenotype of skin DC2s in naive mice of the indicated strains. All KO strains were on a C57BL/6 background except for the IL-13Rα1 KO which were on a BALB/c background. d, Relative frequencies of skin DC2 subsets in naive mice of the indicated strains. e,f, Frequencies of CD11blo DC2s (e) and DC2 subsets (f) in DC2 populations from skin, lung and small intestine (SI) dLNs of C57 controls, and IL-13 KO mice treated with either PBS or IL-13 fusion protein (IL-13fp). In (e), C57 controls are representative of several repeats. a,d,e,f, Bar graphs shows mean ± SEM for n=8 (a) n=5-15 (d) n=3-6 (e,f) mice pooled from 2 (a,d,e IL-13 KO, f) or 1 (e, C57 lung and SI dLNs) independent experiments. Each symbol refers to one mouse. P values were determined using two-way ANOVA with Sidak’s (a, lower graphs in d, IL-13 KO in e,f) or Tukey’s (d, top graphs) correction *P < 0.05; ***P < 0.001. Only relevant significant comparisons are indicated.

Source data

Extended Data Fig. 4 Identification of lymphoid cell populations in murine skin.

a, Gating strategy to identify lymphoid cell populations in the ear skin of naive 4C13R reporter mice. To define cells of lymphoid origin, cells were pre-gated on single, live, CD45+, myeloid-lineage negative (CD11bLy6GLy6CCD11c) cells. Il13-DsRed+ cells were gated within each cell population, or in the total CD45+ population as shown in the lower right panel. b, Gating strategy to identify innate lymphoid cells (ILCs) in the skin of naive 4C13R reporter or C57 mice. The Lineage AF4700 gate includes antibodies specific for B220, Ly6G, Ly6C, NK1.1, CD11b, and FCεRIα. A similar gating strategy was used to identify ILCs in lung and small intestine (SI). c, Frequencies of GATA3+, RORyt+, T-bet+ ILCs in the skin, lung and SI of naive C57 mice. Bar graphs show mean ± SEM for 7-8 mice pooled from 2 independent experiments. Each symbol refers to one mouse.

Source data

Extended Data Fig. 5 IL-13 signalling drives the development of CD11blo DC2 in vitro in a dose and time dependent manner.

a, Gating strategy to identify Sirpα+ DC2 in FLT3L bone marrow DC (BMDC) cultures from C57BL/6 (C57) donors. Cultures were untreated or supplemented with 10 ng/ml rIL-13 for the last 72h of culture as indicated. b, Phenotype of Sirpα+ DC2 subsets in FLT3L BMDCs cultures from C57 donors. Cultures were treated with the indicated concentrations of rIL-13 for the last 72h. Frequencies of CD11blo DC2s are shown in the bar graph. c, Phenotype of Sirpα+ DC2 subsets in FLT3L BMDC cultures from C57 donors. Cultures were supplemented with 10 ng/ml rIL-13 at the indicated times before harvest. Frequencies of CD11blo DC2s are shown in the bar graph. d, IL-4Rα and IL-13Rα1 expression on DC2 subsets from the skin dLNs of male Klf4f/f→C57 and Klf4f/f Vav1-iCre→C57 chimeric mice. FMO: fluorescence-minus-one. Histograms show concatenated data from 3 mice. Median fluorescence intensities (MFI) are reported in the bar graphs. e, Representative images of FLT3L BMDC cultures from male C57, IL-4Rα KO and STAT6 KO donors that were set up as controls for the experiments in Figure 5e. Cultures were either unstimulated or treated with 100 ng/ml rIL-13 for 30 minutes before staining. Scale bars correspond to 50 µm. Frequencies of pSTAT6+ cells in the Sirpα+ population are quantified in the bar graph. An average of 2200 Sirpα+ cells/sample were assessed. Each symbol refers to one culture from one of two repeat experiments. b-d, Bar graph shows mean ± SEM for n=4 (b,c) cultures or n=10-11 (d) mice pooled from 2 (b,c) or 3 (d) separate experiments. Each symbol refers to one independently treated culture or one mouse. P values were determined using two-way ANOVA with Sidak’s correction (b,c) or one-way ANOVA with Tukey’s correction (d). **P < 0.01; ***P < 0.001; only significant comparisons are indicated.

Source data

Extended Data Fig. 6 IL-13 signalling in DC2s is required for optimal IL-4+ TH responses in skin-draining lymph node.

a, Experimental set-up of mixed bone marrow (BM) chimeras to compare the antigen-presenting function of C57 and STAT6 KO DCs. b, Phenotype of DC2 populations in the skin dLN of naive C57 and STAT6 KO chimeras. c, Relative frequencies of DC2 subsets from each donor BM in the skin dLN of naive C57 or STAT6 KO mixed BM chimeras. d, Gating strategy to identify cytokine-expressing CD45.1/CD45.2+CD4+ T cells in the skin dLN of Nb-immunized C57 or STAT6 KO mixed BM chimeras. Gating for IL-4+CD4+ T cells is shown; other cytokines were gated in a similar manner. e, Phenotype of DC2 subsets in the skin dLN of naive Il4raf/− and Il4raf/− zDC-Cre mice. f, Gating strategy to identify cytokine-expressing CD4+ T cells in the skin dLN of Nb-immunized Il4raf/− and Il4raf/− zDC-Cre mice. Gating for IL-4+ CD4+ T cells is shown; other cytokines were gated in a similar manner. g, Frequencies of CD44hiCD4+ T cells in the skin dLN of Il4raf/− and Il4raf/− zDC-Cre mice 5 days after intradermal immunization with Mycobacterium smegmatis (Ms), Nippostrongylus brasiliensis L3 larvae (Nb), Candida albicans (Ca) or PBS as a control. h, Gating strategy for AF488+ cells in the skin dLN of Il4raf/− and Il4raf/− zDC-Cre mice 48 hours after intradermal injection of AF488-labeled Nb (Nb-AF488). i, Numbers of AF488+ cells in the skin dLN of Il4raf/− and Il4raf/− zDC-Cre mice 48 hours after intradermal injection of Nb-AF488. j, Numbers of total DCs and monocytes in the skin dLN of Il4raf/− and Il4raf/− zDC-Cre mice 48 hours after intradermal injection of Nb-AF488 or PBS. c,g,i,j, Bar graphs show mean ± SEM for n=7-8 (c) n=6-8 (g) n=7 (i) n=3-9 (j) mice pooled from 2 independent experiments. P values were determined using two-way ANOVA with Sidak’s correction. **P < 0.01; ***P < 0.001; only significant comparisons are indicated. Each symbol refers to one mouse.

Source data

Extended Data Fig. 7 Enrichment of IL-4/IL-13 signature genes in DC2s from healthy human skin.

a, Heatmap showing the expression of GSEA core-enrichment genes of the IL-4 and IL-13 Reactome pathway in cDCs and monocytes from the blood and skin of healthy donors from a published scRNA-seq dataset (Chen et al, 2020). b, UMAP plot showing scRNA-seq subclusters of cells from skin biopsies and suction blisters of healthy donors from the published dataset GSE153760. EC: Endothelial cells, FB 1, FB 2: Fibroblast clusters 1&2, ILC: Innate lymphoid cells, LC: Langerhans cells, LEC: Lymphatic endothelial cells, MC: Mast cells, MEL: Melanocytes, NK: Natural killer cells, KC 1-7: Keratinocyte clusters 1-7, SMC: Smooth muscle cells, Treg cells: Regulatory T cells. c, Feature plots of the UMAP clusters in (b) showing the expression levels of cluster-specific transcripts used for cluster identification. Color intensity represents the level of normalized gene expression. d, Feature plots of the UMAP clusters in (b) showing expression levels of IL4R, IL13RA1, STAT6, KLF4, IL4 and IL13 transcripts. Color intensity represents the level of normalized gene expression.

Supplementary information

Reporting Summary

Supplementary Tables

Supplementary Table 1. Signature genes for Fig. 1g.

Supplementary Table 2

Transcription factor binding site analysis for Fig. 1h.

Supplementary Table 3

DEG list STAT6 KO versus C57BL/6, bulk RNA-seq, for Extended data Fig. 2g.

Supplementary Table 4

Top markers and DEGs for scRNA-seq (Fig. 2f).

Supplementary Table 5

Reactome Pathways Fig. 8a.

Source data

Source Data Fig. 1

Statistical Source Data, Transcription factor binding sites counts.

Source Data Fig. 2

Statistical Source Data.

Source Data Fig. 3

Statistical Source Data.

Source Data Fig. 4

Statistical Source Data.

Source Data Fig. 5

Statistical Source Data.

Source Data Fig. 6

Statistical Source Data.

Source Data Fig. 7

Statistical Source Data.

Source Data Fig. 8

Reactome pathways.

Source Data Extended Data Fig. 1

Statistical Source Data.

Source Data Extended Data Fig. 2

Statistical Source Data.

Source Data Extended Data Fig. 3

Statistical Source Data.

Source Data Extended Data Fig. 4

Statistical Source Data.

Source Data Extended Data Fig. 5

Statistical Source Data.

Source Data Extended Data Fig. 6

Statistical Source Data.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Mayer, J.U., Hilligan, K.L., Chandler, J.S. et al. Homeostatic IL-13 in healthy skin directs dendritic cell differentiation to promote TH2 and inhibit TH17 cell polarization. Nat Immunol 22, 1538–1550 (2021). https://doi.org/10.1038/s41590-021-01067-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41590-021-01067-0

This article is cited by

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