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Regulation of intestinal immunity and tissue repair by enteric glia

Abstract

Tissue maintenance and repair depend on the integrated activity of multiple cell types1. Whereas the contributions of epithelial2,3, immune4,5 and stromal cells6,7 in intestinal tissue integrity are well understood, the role of intrinsic neuroglia networks remains largely unknown. Here we uncover important roles of enteric glial cells (EGCs) in intestinal homeostasis, immunity and tissue repair. We demonstrate that infection of mice with Heligmosomoides polygyrus leads to enteric gliosis and the upregulation of an interferon gamma (IFNγ) gene signature. IFNγ-dependent gene modules were also induced in EGCs from patients with inflammatory bowel disease8. Single-cell transcriptomics analysis of the tunica muscularis showed that glia-specific abrogation of IFNγ signalling leads to tissue-wide activation of pro-inflammatory transcriptional programs. Furthermore, disruption of the IFNγ–EGC signalling axis enhanced the inflammatory and granulomatous response of the tunica muscularis to helminths. Mechanistically, we show that the upregulation of Cxcl10 is an early immediate response of EGCs to IFNγ signalling and provide evidence that this chemokine and the downstream amplification of IFNγ signalling in the tunica muscularis are required for a measured inflammatory response to helminths and resolution of the granulomatous pathology. Our study demonstrates that IFNγ signalling in enteric glia is central to intestinal homeostasis and reveals critical roles of the IFNγ–EGC–CXCL10 axis in immune response and tissue repair after infectious challenge.

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Fig. 1: Inflammatory injury induces IFNγ signature in EGCs.
Fig. 2: IFNγ signalling in EGCs promotes intestinal tissue repair after helminth infection.
Fig. 3: Tissue-wide regulation of immune homeostasis and immune responses in the TM by the IFNγ–EGC signalling axis.
Fig. 4: Early activation of the IFNγ–EGC–Cxcl10 signalling axis regulates tissue repair after helminth infection.

Data availability

The .fastq files, Seurat objects, count matrices and associated meta data are publicly available at the GEO repository under accession number GSE185412 (GSE182708 and GSE182715 for the bulk and scRNA-seq analysis of naive and H. polygyrus-infected EGCs, respectively, and GSE182506 for the scRNA-seq of the naive and H. polygyrus-infected TM of Ifngr2control and Ifngr2ΔEGC mice). All datasets are available to search online (https://biologic.crick.ac.uk/ENS/EGCinflammation). Data for all graphs associated with the scRNA-seq analysis are available at GitHub (https://github.com/michaeldshapiro/RegulationOfIntestinalImmuneHomeostasis).  Source data are provided with this paper.

Code availability

The code used for all scRNA-seq analysis is available at GitHub (https://github.com/michaeldshapiro/RegulationOfIntestinalImmuneHomeostasis).

References

  1. 1.

    Kotas, M. E. & Medzhitov, R. Homeostasis, inflammation, and disease susceptibility. Cell 160, 816–827 (2015).

    CAS  Article  Google Scholar 

  2. 2.

    Turner, J. R. Intestinal mucosal barrier function in health and disease. Nat. Rev. Immunol. 9, 799–809 (2009).

    CAS  Article  Google Scholar 

  3. 3.

    Abreu, M. T. Toll-like receptor signalling in the intestinal epithelium: how bacterial recognition shapes intestinal function. Nat. Rev. Immunol. 10, 131–144 (2010).

    CAS  Article  Google Scholar 

  4. 4.

    Maloy, K. J. & Powrie, F. Intestinal homeostasis and its breakdown in inflammatory bowel disease. Nature 474, 298–306 (2011).

    ADS  CAS  Article  Google Scholar 

  5. 5.

    Klose, C. S. & Artis, D. Innate lymphoid cells as regulators of immunity, inflammation and tissue homeostasis. Nat. Immunol. 17, 765–774 (2016).

    CAS  Article  Google Scholar 

  6. 6.

    Roulis, M. & Flavell, R. A. Fibroblasts and myofibroblasts of the intestinal lamina propria in physiology and disease. Differentiation 92, 116–131 (2016).

    CAS  Article  Google Scholar 

  7. 7.

    Koliaraki, V., Prados, A., Armaka, M. & Kollias, G. The mesenchymal context in inflammation, immunity and cancer. Nat. Immunol. 21, 974–982 (2020).

    CAS  Article  Google Scholar 

  8. 8.

    Kinchen, J. et al. Structural remodeling of the human colonic mesenchyme in inflammatory bowel disease. Cell 175, 372–386 (2018).

    CAS  Article  Google Scholar 

  9. 9.

    Laranjeira, C. et al. Glial cells in the mouse enteric nervous system can undergo neurogenesis in response to injury. J. Clin. Invest. 121, 3412–3424 (2011).

    CAS  Article  Google Scholar 

  10. 10.

    Reynolds, L. A., Filbey, K. J. & Maizels, R. M. Immunity to the model intestinal helminth parasite Heligmosomoides polygyrus. Semin. Immunopathol. 34, 829–846 (2012).

    CAS  Article  Google Scholar 

  11. 11.

    Boesmans, W., Lasrado, R., Vanden Berghe, P. & Pachnis, V. Heterogeneity and phenotypic plasticity of glial cells in the mammalian enteric nervous system. Glia 63, 229–241 (2015).

    Article  Google Scholar 

  12. 12.

    Heanue, T. A. & Pachnis, V. Prospective identification and isolation of enteric nervous system progenitors using Sox2. Stem Cells 29, 128–140 (2011).

    CAS  Article  Google Scholar 

  13. 13.

    Lasrado, R. et al. Lineage-dependent spatial and functional organization of the mammalian enteric nervous system. Science 356, 722–726 (2017).

    ADS  CAS  Article  Google Scholar 

  14. 14.

    Bach, E. A., Aguet, M. & Schreiber, R. D. The IFNγ receptor: a paradigm for cytokine receptor signaling. Annu. Rev. Immunol. 15, 563–591 (1997).

    CAS  Article  Google Scholar 

  15. 15.

    Lee, H. M. et al. IFNγ signaling endows DCs with the capacity to control type I inflammation during parasitic infection through promoting T-bet+ regulatory T cells. PLoS Pathog. 11, e1004635 (2015).

    Article  Google Scholar 

  16. 16.

    Huang, S. et al. Immune response in mice that lack the interferon-γ receptor. Science 259, 1742–1745 (1993).

    ADS  CAS  Article  Google Scholar 

  17. 17.

    Gentile, M. E. et al. NK cell recruitment limits tissue damage during an enteric helminth infection. Mucosal Immunol. 13, 357–370 (2020).

  18. 18.

    Nusse, Y. M. et al. Parasitic helminths induce fetal-like reversion in the intestinal stem cell niche. Nature 559, 109–113 (2018).

    ADS  CAS  Article  Google Scholar 

  19. 19.

    Roulis, M. et al. Paracrine orchestration of intestinal tumorigenesis by a mesenchymal niche. Nature 580, 524–529 (2020).

    ADS  CAS  Article  Google Scholar 

  20. 20.

    Rinkevich, Y. et al. Identification and prospective isolation of a mesothelial precursor lineage giving rise to smooth muscle cells and fibroblasts for mammalian internal organs, and their vasculature. Nat. Cell Biol. 14, 1251–1260 (2012).

    CAS  Article  Google Scholar 

  21. 21.

    Mutsaers, S. E. et al. Mesothelial cells in tissue repair and fibrosis. Front. Pharmacol. 6, 113 (2015).

    Article  Google Scholar 

  22. 22.

    Stetson, D. B. et al. Constitutive cytokine mRNAs mark natural killer (NK) and NK T cells poised for rapid effector function. J. Exp. Med. 198, 1069–1076 (2003).

    CAS  Article  Google Scholar 

  23. 23.

    Dufour, J. H. et al. IFN-γ-inducible protein 10 (IP-10; CXCL10)-deficient mice reveal a role for IP-10 in effector T cell generation and trafficking. J. Immunol. 168, 3195–3204 (2002).

    CAS  Article  Google Scholar 

  24. 24.

    Mills Ko, E. et al. Deletion of astroglial CXCL10 delays clinical onset but does not affect progressive axon loss in a murine autoimmune multiple sclerosis model. J. Neuroinflammation 11, 105 (2014).

    Article  Google Scholar 

  25. 25.

    Ostvik, A. E. et al. Enhanced expression of CXCL10 in inflammatory bowel disease: potential role of mucosal Toll-like receptor 3 stimulation. Inflamm. Bowel Dis. 19, 265–274 (2013).

    Article  Google Scholar 

  26. 26.

    Wang, L. et al. An atlas of genetic variation linking pathogen-induced cellular traits to human disease. Cell Host Microbe 24, 308–323 (2018).

    CAS  Article  Google Scholar 

  27. 27.

    Sasselli, V. et al. Planar cell polarity genes control the connectivity of enteric neurons. J. Clin. Invest. 123, 1763–1772 (2013).

    CAS  Article  Google Scholar 

  28. 28.

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

    CAS  Article  Google Scholar 

  29. 29.

    Tavares, G. et al. Employing an open-source tool to assess astrocyte tridimensional structure. Brain Struct. Funct. 222, 1989–1999 (2017).

    Article  Google Scholar 

  30. 30.

    Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J. 17, 10–12 (2011).

    Article  Google Scholar 

  31. 31.

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

    CAS  Article  Google Scholar 

  32. 32.

    Butler, A., Hoffman, P., Smibert, P., Papalexi, E. & Satija, R. Integrating single-cell transcriptomic data across different conditions, technologies, and species. Nat. Biotechnol. 36, 411–420 (2018).

    CAS  Article  Google Scholar 

  33. 33.

    Su, S. et al. CellBench: R/Bioconductor software for comparing single-cell RNA-seq analysis methods. Bioinformatics 36, 2288–2290 (2020).

  34. 34.

    Finak, G. et al. MAST: a flexible statistical framework for assessing transcriptional changes and characterizing heterogeneity in single-cell RNA sequencing data. Genome Biol. 16, 278 (2015).

    Article  Google Scholar 

  35. 35.

    Reimand, J. et al. g:Profiler—a web server for functional interpretation of gene lists (2016 update). Nucleic Acids Res. 44, W83–W89 (2016).

    CAS  Article  Google Scholar 

  36. 36.

    Sergushichev, A. An algorithm for fast preranked gene set enrichment analysis using cumulative statistic calculation. Preprint at https://doi.org/10.1101/060012 (2016).

  37. 37.

    NCBI Resource Coordinators Database resources of the national center for biotechnology information. Nucleic Acids Res. 46, D8–D13 (2018).

    Article  Google Scholar 

  38. 38.

    R Core Team R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2019).

  39. 39.

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

    CAS  Article  Google Scholar 

  40. 40.

    Wickham, H. ggplot2: Elegant Graphics for Data Analysis. (Springer, 2016).

    Book  Google Scholar 

  41. 41.

    ggsignif: significance brackets for 'ggplot2'. Preprint at https://doi.org/10.31234/osf.io/7awm6 (2019).

  42. 42.

    ggrepel: automatically position non-overlapping text labels with 'ggplot2'. R package version 0.9.1; https://CRAN.R-project.org/package=ggrepel (2020).

  43. 43.

    ggsci: scientific journal and sci-fi themed color palettes for 'ggplot2'. R package version 2.9; https://CRAN.R-project.org/package=ggsci (2018).

Download references

Acknowledgements

We thank staff at the Crick Science Technology Platforms (STPs) for expert support, in particular, the Biological Research Facility (R. Subramaniam, A. Vanderplank, M. Miah, S. Cooper), the Flow Cytometry STP (D. Das, K. Bartolovic), the Advanced Sequencing Facility (R. Goldstone, D. Jackson, A. Edwards, M. Costa) and the Experimental Histopathology Laboratory (E. Nye). We also thank C. Minutti and all members of the Pachnis laboratory for useful advice, discussions and insightful comments on the manuscript. We thank W. Müller for providing the Ifngr2 floxed mice and R. Locksley and A. Luster for giving us permission to use the Yeti and Cxcl10−/− mice, respectively. Ifngr2 This work was supported by the Francis Crick Institute, which receives its core funding from Cancer Research UK (FC001128, FC001159), the UK Medical Research Council (FC001128, FC001159) and the Wellcome Trust (FC001128, FC001159). V.P. acknowledges additional funding from BBSRC (BB/L022974) and the Wellcome Trust (212300/Z/18/Z). B.S. was also funded by the Wellcome Trust (210556/Z/18/Z).

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Authors

Contributions

F.P. and V.P. conceived the study and, together with B.S. and M.S.W., designed the experiments. S.H.C., C.H.C., S.S., M.R., E.-M.A., A.C.B.-F., R.L. and L.J.E. helped with the experiments. S.H.C. performed cell culture of primary EGCs. M.S. and A.L. performed scRNA-seq bioinformatics analysis. S.B. performed bulk RNA-seq bioinformatics analysis. A.C.B.-F., S.S. and B.G.-C. performed immunohistochemistry analysis of the TM. B.G.-C. and C.H.C. designed, performed and analysed immunophenotyping experiments. K.S. designed some of the immunophenotyping experiments. A.S.-B. performed the histopathology examination. V.P. and F.P. wrote the manuscript with help from B.S. and contributions from all of the authors.

Corresponding authors

Correspondence to Fränze Progatzky or Vassilis Pachnis.

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The authors declare no competing interests.

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Peer review information Nature thanks Isaac Chiu and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data figures and tables

Extended Data Fig. 1 Intestinal helminth infection induces ENS injury and gliosis.

(ai) TM preparations (ad, fi) and cross-section (e) from the duodenum of SOX10|tdT mice immunostained for CD45 (a), CD31 (b), PDGFRA (c), C-KIT (d), EPCAM(e), SOX10 (f, h) and HuC/D (f, i). Indicated are cells negative for tdT (empty arrowheads), tdT+ EGCs (asterisks) and neurons (arrowheads). g, h and i show single spectrum images of f. n = 3. (j) Quantification of tdT+ cells expressing SOX10 (EGCs) and HuC/D (neurons) (n = 11 field of views, representative of 3 experiments). (k) Schematic of intestinal cross-section illustrating the organization of the EGC-network and the life-cycle of H. polygyrus. Third-stage H. polygyrus larvae penetrate the duodenum mucosa and settle in the TM, eliciting local tissue damage, inflammation and formation of granulomatous infiltrates. 10 days later they emerge as adult worms into the lumen where they mate and produce eggs. (l, m) Cross-section (l) and whole-mount view (m) of the duodenum of H. polygyrus-infected SOX10|tdT mice (7 d.p.i.). Schematics (top left) show the orientation of the images. Arrowheads point to H. polygyrus settlement sites. n = 4. (n, o, q, r) TM preparations from the duodenum of naive and H. polygyrus-infected (7 dpi n, o; 10 dpi q, r) animals immunostained for GFAP and SOX10 (n, o) and S100 (q, r). n = 5. (p) Quantification (RT-qPCR) of Gfap transcripts in the TM of naive and H. polygyrus-infected mice (7 d.p.i.). n=8 (naive), n = 6 (H. polygyrus). 2 experiments. (su) Quantification of S100+ type III EGC morphology including total process length (s) n = 10, process thickness (t) (n = 10) and Scholl analysis for EGC process branching (u) n = 5. 2 experiments. Two-tailed Mann-Whitney test (p, t), unpaired two-tailed t-test (s), Two-way ANOVA with multiple comparisons (u). Mean ± s.e.m. Scale bars: a-i: 50 μm; l, m, n, o, q, r: 100 μm, insets: 12.5 μm.

Source data

Extended Data Fig. 2 Transcriptomic analysis of H. polygyrus-infected TM.

(a) Experimental design for bulk RNA-seq of EGCs from the TM of naive and H. polygyrus-infected (7 d.p.i.) SOX10|tdT mice. tdT+ and tdT- cell populations of dissociated TM were separated using FACS and subjected to RNA-seq. (b) Sorting strategy for tdT+ EGCs and tdT- non-glia cells. (c, d) Volcano plot showing mean log2-transformed fold change (x-axis) and significance (−log10[Padj]) of differentially expressed genes between tdT- and tdT+ cells from naive mice (c) and in tdT- cells from naive and H. polygyrus-infected animals (d). Coloured dots in (c) indicate genes specific to EGCs (Sox10, Plp1, S100b, Foxd3, Erbb3, Sox2; red), enteric neurons (Ret, Tubb3, Sst, Elavl3, Elavl4; green), immune cells (Ptprc; cyan), interstitial cells of Cajal (Kit; orange), smooth muscle cells (Actg2; pink), fibroblasts (Pdgfra; purple) and in (d) genes specific to type II immune response (Arg1, Retnla, Chil3) and TH2 cytokines (Il13). n = 4. (e) Quantification of IFNγ in the TM of naive and H. polygyrus-infected animals (7 d.p.i.). Mean±SD; n=6. Two-tailed Mann-Whitney test. (f) UMAP of sequenced EGCs from the TM of naive and H. polygyrus infected mice. Cells are colour-coded according to experimental batches. (g) Violin plots showing normalized expression of representative EGC marker genes in EGC1 and EGC2 clusters in Fig. 1g. (h, i) Top 20 up-regulated and top 20 down-regulated genes in EGCs from H. polygyrus-infected mice (h) and in EGC2 relative to EGC1 (i). IFNγ-target genes shown in bold (h). Dot size indicates proportion of expressing cells and fill colour indicates mean normalized, centred and scaled expression level. (j, k) GO terms significantly enriched among the differentially expressed genes in EGC1 and EGC2 clusters shown in Fig. 1g (j) and in hEGC1 and hEGC2 clusters shown in Fig. 1j (k).

Source data

Extended Data Fig. 3 Cell autonomous activation of EGCs by IFNγ.

(a, b) RT-qPCR analysis of Ifngr1 (a) and Ifngr2 (b) transcript levels from spleen cells and FACS-isolated EGCs (tdT+) and non-glia cells (tdT-) from SOX10|tdT mice. n = 3. (c, d) Cultures of FACS-isolated EGCs from SOX10|tdT mice in the absence (c) or presence (d) of IFNγ immunostained for pH3 (green) and labelled with EdU (blue). Scale bars: 100 μm. (e, f) Quantification of pH3+ (e) and EdU+ (f) EGCs (tdT+ cells) in the cultures shown in c and d, respectively. n=8 field of views from each of 3 experiments. (g) RT-qPCR analysis of Ifngr2 transcript levels in muscularis macrophages, fibroblasts, endothelial cells and EGCs FACS-isolated from the TM of Ifngr2control and Ifngr2ΔEGC mice. n = 3. (h) Images of IFNγ-treated (1 h) myenteric plexus preparations from the duodenum of Ifngr2control and Ifngr2ΔEGC mice immunostained for pStat1, SOX10 and HuC/D and counterstained for DAPI. Indicated are pStat1+ EGCs (empty arrowheads), pStat1- EGCs (filled arrowheads). Scale bar = 10 μm. (i) Quantification of pStat1+ muscularis macrophages, fibroblasts, neurons and EGCs in IFNγ-treated (1 h) TM preparations from Ifngr2control and Ifngr2ΔEGC mice. n = 8. (jl) RT-qPCR analysis of Ifngr2, Cxcl10 and Gbp10 transcript levels from rIFNγ treated EGCs isolated from Ifngr2control and Ifngr2ΔEGC mice. n =4. (m) Quantification of Ki67+ EGCs in the TM of H. polygyrus-infected Ifngr2control and Ifngr2ΔEGC mice at 7 d.p.i. (n = 10). (n) Quantification of Ki67+ EGCs in the TM of wild-type and Ifngr1−/− mice (n = 8). 2 experiments (m, n). Two-tailed Mann-Whitney test (e, f, n), unpaired two-tailed t-test (g, i, j, k, l, m). Mean±SEM.

Source data

Extended Data Fig. 4 Characterization of mice with glia-specific deletion of IFNγ signalling.

(a) Quantification of granulomas in the small intestine at 28 d.p.i. (n = 10) and 80 d.p.i. (n = 5) WT and Ifngr1−/− mice (2 experiments). (b) Representative images of H. polygyrus settlement sites in Ifngr2control and Ifngr2ΔEGC gut at 7 d.p.i. Note bleeding in Ifngr2ΔEGC mice (65.2±3.14 versus 31.8±1.56 in Ifngr2control mice). n = 20 animals analysed. (c, d, f) Flow cytometry gating strategy to immunophenotype the TM of naive and H. polygyrus-infected Ifngr2control and Ifngr2ΔEGC mice showing debris exclusion and doublet discrimination, selection of live immune cells (c), followed by gating of myeloid cells (d) or NK-/ T cells (f). (e) Flow cytometry quantification of neutrophils in the TM of naive Ifngr2control and Ifngr2ΔEGC mice. n = 5 (Ifngr2control), n = 6 (Ifngr2ΔEGC). (gi) Flow cytometry quantification of CD4 and γδT cells and NK cells at indicated time-points after H. polygyrus infection within the TM of Ifngr2control and Ifngr2ΔEGC mice. (n = 4, data from 1 experiment). (j) Quantification of worms in the TM at 7 d.p.i. (n = 8) or recovered from the intestinal tract at 28 (n = 11) and 60 d.p.i. (n = 15). Two-way Anova. (k) H. polygyrus egg burden at 14 (ncontrol=15, nΔEGC=16), 28 (n = 11) and 60 d.p.i. (n = 9). Two-tailed Mann-Whitney Test (e), Two-way Anova (a, gk). Mean±SD (a, j, k), Mean±SEM (e, gi).

Source data

Extended Data Fig. 5 Cellular atlas of small intestine TM.

(a) Mean normalized expression of representative marker genes and proportion of expressing cells (indicated by dot size) in the cell clusters shown in (c). Clusters are labelled with post facto annotation based on known markers. (b) Sorting strategy for live TM cells. (c) UMAP of all sequenced cells from small intestine TM. The numbers of clusters in c correspond to the numbers in a. (d) UMAP analysis of integrated scRNA-seq datasets of mesenchymal cells from the lamina propria (GSE142431)19 and the TM (present study; Fig. 3a, b). Annotation of cellular clusters matches those reported by Roulis et al19. on the basis of respective marker genes. Note that cell populations from the TM overlap with those from the lamina propria. (e) Violin plot quantification of Pdgfra expression per single cell highlighting that, similar to those in the lamina propria19, TM fibroblasts are divided into Pdgfrahigh and Pdgfralow cells. (fi) Representative images of cross-section (f) or TM preparations (gi) from the small intestine of SOX10|tdT (f and h), SOX10|YFP (g) and wild type (i) mice immunostained for PDPN to identify mesothelial cells (, arrowhead) and lymphatic endothelial cells (g), VEGFR2 and PDGFRB to identify endothelial cells and pericytes (arrowhead), respectively (h), and CD3 and IBA1 to identify T cells and macrophages, respectively (i). Note the small number of T cells in TM relative to macrophages. Scale bars: 50 μm, insets: 25 μm. Images representative of n = 5 animals analysed.

Extended Data Fig. 6 Glia-specific ablation of IFNγ signalling induces a tissue-wide pro-inflammatory state of TM at steady state and modulates the response to H. polygyrus infection.

(ac) UMAP representation of mesothelial cells (a), fibroblasts (b) and muscularis macrophages (c) from naive Ifngr2control (black) and Ifngr2ΔEGC (orange) mice. (d) RT-qPCR analysis of Lcn2, Il1b, Saa3 and Il6 transcript levels in the TM from naive Ifngr2control and Ifngr2ΔEGC mice. ncontrol = 12, nΔEGC = 11. (e) Representative haematoxylin and eosin stained intestinal cross-sections from naive Ifngr2control and Ifngr2ΔEGC mice. Empty and filled arrowheads in inset highlight reactive mesothelial cells and eosinophils, respectively. Scale bars = 50 μm, insets: 20 μm. Shown also is histology severity score (right) assessing inflammation in the lamina propria and tunica muscularis from naive Ifngr2control and Ifngr2ΔEGC mice. n = 8. 2 experiments. (f) Intestinal paracellular permeability in naive Ifngr2control and Ifngr2ΔEGC mice. ncontrol = 8, nΔEGC = 7 (2 independent experiments). (g) Whole intestinal transit time in naive Ifngr2control and Ifngr2ΔEGC mice. ncontrol = 9, nΔEGC = 8. (h) Fraction of cells per cluster in naive and H. polygyrus-infected Ifngr2control and Ifngr2ΔEGC mice. (i) Violin plot visualization of Ifng expression levels per single cell in indicated cell clusters. (j) Dot plot quantification of expression levels of Ifng vs Cd8a (left panel) and Ifng vs Cd4 (right panel) in the Other lymphoid cells, NK cells, T Cells 1, T Cells 2 and T Cells 3 clusters, indicating that Cd8a T cells are a major source of Ifng in the TM of H. polygyrus-infected mice at 7 dpi. Two-tailed Mann-Whitney test (d, f). Unpaired two-tailed t-test (g). Mean±SEM.

Source data

Extended Data Fig. 7 Activation of the IFNγ–CXCL10 axis in TM precedes type II immune response and promotes tissue repair after helminth infection.

(a, b) RT-qPCR analysis of Il4 and Il13 transcripts in TM (a; nnaive = 8, n3 d.p.i., 7 d.p.i.,10 d.p.i.,14 d.p.i. = 6, n5 d.p.i., 28 d.p.i. = 7, n7 d.p.i. = 9, n21 d.p.i. = 3) and Ifng, Il4, Il13 and Arg1 transcripts in mucosa (b; nnaive,7dpi,10dpi=6, n3dpi,5dpi,14dpi,21dpi,28dpi=3) of small intestine following H. polygyrus infection. 2 experiments. (c, d) qRT-PCR time-course analysis of Gbp6 (c) and Gbp10 (d) transcript levels in TM after H. polygyrus infection. nnaive = 8, n3 d.p.i. ,7 d.p.i., 10 d.p.i., 14 d.p.i. = 6, n5 d.p.i., 28 d.p.i. = 7, n21 d.p.i. = 3. 2 experiments. (e) Flow cytometric quantification of IFNγ-producing cells in the TM of H. polygyrus-infected WT mice (3 d.p.i.). nnaive=7, n3 d.p.i. = 9. 2 experiments. (f) RT-qPCR analysis of Cxcl10 transcripts in TM from H. polygyrus-infected (7 dpi) WT and Ifngr1−/− mice. n = 10. 2 experiments. (g) Quantification of granulomas in the small intestine H. polygyrus-infected (28 d.p.i.) Ifngr1−/− and Cxcl10−/− mice. n = 9. 2 experiments. (h) RT-qPCR analysis of Cxcl10 transcripts from rIFNγ-treated cultures (24 h) of EGCs from Cxcl10control and Cxcl10ΔEGC mice. nControl = 2, nrIFNγ = 3. (i) In situ hybridization for Cxcl10 in IFNγ-treated (1 h) myenteric plexus from the duodenum of Cxcl10control and Cxcl10ΔEGC mice. CXCL10+ EGCs indicated by empty arrowhead. Scale bar = 10 μm. (j) Quantification of CXCL10+ EGCs in IFNγ-treated (1 h) TM preparations from Cxcl10control and Cxcl10ΔEGC mice. ncontrol= 3, nΔEGC = 4. (k) Quantification of CXCL10+ EGCs in the TM of H. polygyrus-infected Cxcl10control and Cxcl10ΔEGC mice (3 d.p.i.). ncontrol = 3, nΔEGC=6. (l, m) Quantification of adult worms (l) and eggs (m) in small intestine from H. polygyrus-infected Cxcl10control and Cxcl10ΔEGC mice (28 d.p.i.). ncontrol = 12, nΔEGC = 13. 2 experiments. (n) Dot plot analysis of Cxcr3 vs Cd8a expression indicating that Cd8+ T cells in TM express Cxcr3. Two-tailed Mann-Whitney test (f, j, k). Kruskal-Wallis test (g). Unpaired two-tailed t-test (e, h). Mean±SEM.

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Progatzky, F., Shapiro, M., Chng, S.H. et al. Regulation of intestinal immunity and tissue repair by enteric glia. Nature 599, 125–130 (2021). https://doi.org/10.1038/s41586-021-04006-z

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