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Feeding-dependent VIP neuron–ILC3 circuit regulates the intestinal barrier

Nature volume 579, pages 575–580 (2020)Cite this article

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Abstract

The intestinal mucosa serves both as a conduit for the uptake of food-derived nutrients and microbiome-derived metabolites, and as a barrier that prevents tissue invasion by microorganisms and tempers inflammatory responses to the myriad contents of the lumen. How the intestine coordinates physiological and immune responses to food consumption to optimize nutrient uptake while maintaining barrier functions remains unclear. Here we show in mice how a gut neuronal signal triggered by food intake is integrated with intestinal antimicrobial and metabolic responses that are controlled by type-3 innate lymphoid cells (ILC3)1,2,3. Food consumption rapidly activates a population of enteric neurons that express vasoactive intestinal peptide (VIP)4. Projections of VIP-producing neurons (VIPergic neurons) in the lamina propria are in close proximity to clusters of ILC3 that selectively express VIP receptor type 2 (VIPR2; also known as VPAC2). Production of interleukin (IL)-22 by ILC3, which is upregulated by the presence of commensal microorganisms such as segmented filamentous bacteria5,6,7, is inhibited upon engagement of VIPR2. As a consequence, levels of antimicrobial peptide derived from epithelial cells are reduced but the expression of lipid-binding proteins and transporters is increased8. During food consumption, the activation of VIPergic neurons thus enhances the growth of segmented filamentous bacteria associated with the epithelium, and increases lipid absorption. Our results reveal a feeding- and circadian-regulated dynamic neuroimmune circuit in the intestine that promotes a trade-off between innate immune protection mediated by IL-22 and the efficiency of nutrient absorption. Modulation of this pathway may therefore be effective for enhancing resistance to enteropathogens2,3,9 and for the treatment of metabolic diseases.

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Fig. 1: Processes of VIPergic enteric neurons are in close proximity to Vipr2-expressing ILC3 within cryptopatches.
Fig. 2: VIPR2-dependent inhibition of CCR6+ ILC3 and epithelial antimicrobial response.
Fig. 3: VIPergic signalling reduces mucosal barrier function.
Fig. 4: Feeding reduces IL-22 production by CCR6+ ILC3 through the activation of VIPergic neurons.
Fig. 5: Feeding-dependent dynamic regulation of commensal bacterial growth through the VIP–VIPR2–IL-22 axis.
Fig. 6: Feeding-dependent regulation of lipid absorption by the VIP–VIPR2–IL-22 axis.

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Data availability

Source Data for Figs. 2–6, Extended Data Figs. 4–10 are provided with the paper. The datasets generated in this study are available from the corresponding author on reasonable request. RNA-seq datasets analysed are publicly available in the Gene Expression Omnibus repository (accession number GSE140502) and 16S sequencing datasets analysed are publicly available at BioProject (accession number PRJNA594406).

References

  1. Constantinides, M. G. Interactions between the microbiota and innate and innate-like lymphocytes. J. Leukoc. Biol. 103, 409–419 (2018).

    Article  CAS  PubMed  Google Scholar 

  2. Sonnenberg, G. F. Regulation of intestinal health and disease by innate lymphoid cells. Int. Immunol. 26, 501–507 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Spits, H. & Cupedo, T. Innate lymphoid cells: emerging insights in development, lineage relationships, and function. Annu. Rev. Immunol. 30, 647–675 (2012).

    Article  CAS  PubMed  Google Scholar 

  4. Chayvialle, J. A., Miyata, M., Rayford, P. L. & Thompson, J. C. Effects of test meal, intragastric nutrients, and intraduodenal bile on plasma concentrations of immunoreactive somatostatin and vasoactive intestinal peptide in dogs. Gastroenterology 79, 844–852 (1980).

    Article  CAS  PubMed  Google Scholar 

  5. Sano, T. et al. An IL-23R/IL-22 circuit regulates epithelial serum amyloid A to promote local effector Th17 responses. Cell 163, 381–393 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Savage, A. K., Liang, H. E. & Locksley, R. M. The development of steady-state activation hubs between adult LTi ILC3s and primed macrophages in small intestine. J. Immunol. 199, 1912–1922 (2017).

    Article  CAS  PubMed  Google Scholar 

  7. Longman, R. S. et al. CX3CR1+ mononuclear phagocytes support colitis-associated innate lymphoid cell production of IL-22. J. Exp. Med. 211, 1571–1583 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Mao, K. et al. Innate and adaptive lymphocytes sequentially shape the gut microbiota and lipid metabolism. Nature 554, 255–259 (2018).

    Article  ADS  CAS  PubMed  Google Scholar 

  9. Zheng, Y. et al. Interleukin-22 mediates early host defense against attaching and effacing bacterial pathogens. Nat. Med. 14, 282–289 (2008).

    Article  CAS  PubMed  Google Scholar 

  10. Ibiza, S. et al. Glial-cell-derived neuroregulators control type 3 innate lymphoid cells and gut defence. Nature 535, 440–443 (2016).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  11. Mortha, A. et al. Microbiota-dependent crosstalk between macrophages and ILC3 promotes intestinal homeostasis. Science 343, 1249288 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  12. Hooper, L. V., Littman, D. R. & Macpherson, A. J. Interactions between the microbiota and the immune system. Science 336, 1268–1273 (2012).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  13. Dudakov, J. A., Hanash, A. M. & van den Brink, M. R. Interleukin-22: immunobiology and pathology. Annu. Rev. Immunol. 33, 747–785 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Eberl, G. et al. An essential function for the nuclear receptor RORγt in the generation of fetal lymphoid tissue inducer cells. Nat. Immunol. 5, 64–73 (2004).

    Article  CAS  PubMed  Google Scholar 

  15. Gury-BenAri M. et al. The spectrum and regulatory landscape of intestinal innate lymphoid cells are shaped by the microbiome. Cell 166,1231–1246 (2016).

    Article  CAS  PubMed  Google Scholar 

  16. Pokrovskii, M. et al. Characterization of transcriptional regulatory networks that promote and restrict identities and functions of intestinal innate lymphoid cells. Immunity 51, 185–197 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Heng, T. S. P. et al. The Immunological Genome Project: networks of gene expression in immune cells. Nat. Immunol. 9, 1091–1094 (2008).

    Article  CAS  PubMed  Google Scholar 

  18. Furness, J. B. The enteric nervous system and neurogastroenterology. Nat. Rev. Gastroenterol. Hepatol. 9, 286–294 (2012).

    Article  CAS  PubMed  Google Scholar 

  19. Muller, P. A. et al. Crosstalk between muscularis macrophages and enteric neurons regulates gastrointestinal motility. Cell 158, 300–313 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Cardoso, V. et al. Neuronal regulation of type 2 innate lymphoid cells via neuromedin U. Nature 549, 277–281 (2017).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  21. Klose, C. S. N. et al. The neuropeptide neuromedin U stimulates innate lymphoid cells and type 2 inflammation. Nature 549, 282–286 (2017).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  22. Margolis, K. G. & Gershon, M. D. Enteric neuronal regulation of intestinal inflammation. Trends Neurosci. 39, 614–624 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Zwarycz, B. et al. IL22 inhibits epithelial stem cell expansion in an ileal organoid model. Cell. Mol. Gastroenterol. Hepatol. 7, 1–17 (2019).

    Article  PubMed  Google Scholar 

  24. Zha, J. M. et al. Interleukin 22 expands transit-amplifying cells while depleting Lgr5+ stem cells via inhibition of Wnt and Notch signaling. Cell. Mol. Gastroenterol. Hepatol. 7, 255–274 (2019).

    Article  PubMed  Google Scholar 

  25. Roth, B. L. DREADDs for neuroscientists. Neuron 89, 683–694 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Conlin, V. S. et al. Vasoactive intestinal peptide ameliorates intestinal barrier disruption associated with Citrobacter rodentium-induced colitis. Am. J. Physiol. Gastrointest. Liver Physiol. 297, G735–G750 (2009).

    Article  ADS  CAS  PubMed  Google Scholar 

  27. Kohsaka, A. et al. High-fat diet disrupts behavioral and molecular circadian rhythms in mice. Cell Metab. 6, 414–421 (2007).

    Article  CAS  PubMed  Google Scholar 

  28. Park, O. et al. In vivo consequences of liver-specific interleukin-22 expression in mice: implications for human liver disease progression. Hepatology 54, 252–261 (2011).

    Article  PubMed  CAS  Google Scholar 

  29. Smith, P. M. et al. The microbial metabolites, short-chain fatty acids, regulate colonic Treg cell homeostasis. Science 341, 569–573 (2013).

    Article  ADS  CAS  PubMed  Google Scholar 

  30. Mullineaux-Sanders, C., Suez, J., Elinav, E. & Frankel, G. Sieving through gut models of colonization resistance. Nat. Microbiol. 3, 132–140 (2018).

    Article  CAS  PubMed  Google Scholar 

  31. McVey Neufeld, K. A., Perez-Burgos, A., Mao, Y. K., Bienenstock, J. & Kunze, W. A. The gut microbiome restores intrinsic and extrinsic nerve function in germ-free mice accompanied by changes in calbindin. Neurogastroenterol. Motil. 27, 627–636 (2015).

    Article  CAS  PubMed  Google Scholar 

  32. McVey Neufeld, K. A., Mao, Y. K., Bienenstock, J., Foster, J. A. & Kunze, W. A. The microbiome is essential for normal gut intrinsic primary afferent neuron excitability in the mouse. Neurogastroenterol. Motil. 25, 183-e88 (2013).

    Article  CAS  PubMed  Google Scholar 

  33. Chayvialle, J. A., Miyata, M., Rayford, P. L. & Thompson, J. C. Release of vasoactive intestinal peptide by distention of the proximal stomach in dogs. Gut 21, 745–749 (1980).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Harmar, A. J. et al. The VPAC2 receptor is essential for circadian function in the mouse suprachiasmatic nuclei. Cell 109, 497–508 (2002).

    Article  CAS  PubMed  Google Scholar 

  35. Nussbaum, J. C. et al. Type 2 innate lymphoid cells control eosinophil homeostasis. Nature 502, 245–248 (2013).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  36. Godinho-Silva, C. et al. Light-entrained and brain-tuned circadian circuits regulate ILC3s and gut homeostasis. Nature 574, 254–258 (2019).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  37. Eberl, G. & Littman, D. R. Thymic origin of intestinal αβ T cells revealed by fate mapping of RORγt+ cells. Science 305, 248–251 (2004).

    Article  ADS  CAS  PubMed  Google Scholar 

  38. Lochner, M. et al. In vivo equilibrium of proinflammatory IL-17+ and regulatory IL-10+ Foxp3+ RORγt+ T cells. J. Exp. Med. 205, 1381–1393 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Wang, H. et al. One-step generation of mice carrying mutations in multiple genes by CRISPR/Cas-mediated genome engineering. Cell 153, 910–918 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  40. Yang, H., Wang, H. & Jaenisch, R. Generating genetically modified mice using CRISPR/Cas-mediated genome engineering. Nat. Protocols 9, 1956–1968 (2014).

    Article  CAS  PubMed  Google Scholar 

  41. Zhang, F. et al. Lacteal junction zippering protects against diet-induced obesity. Science 361, 599–603 (2018).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  42. Bankhead, P. et al. QuPath: open source software for digital pathology image analysis. Sci. Rep. 7, 16878 (2017).

    Article  ADS  PubMed  PubMed Central  CAS  Google Scholar 

  43. Caporaso, J. G. et al. Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME J. 6, 1621–1624 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Bolyen, E. et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat. Biotechnol. 37, 852–857 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Lügering, A. et al. CCR6 identifies lymphoid tissue inducer cells within cryptopatches. Clin. Exp. Immunol. 160, 440–449 (2010).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  46. Reynders, A. et al. Identity, regulation and in vivo function of gut NKp46+RORγt+ and NKp46+RORγt− lymphoid cells. EMBO J. 30, 2934–2947 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank members of the D.R.L. laboratory and J. J. Lafaille’s laboratory for valuable discussion; S. Y. Kim and the NYU Rodent Genetic Engineering Laboratory for generating the mutant mice; C. Loomis and the Experimental Pathology Research Laboratory of New York University Langone Medical Center for histology of small intestine samples; A. Heguy and the Genome Technology Center (GTC) for RNA-seq; F.-X. Liang, J. Sall, C. Petzold and K. Dancel at the Microscopy Laboratory Core for timely preparation of the scanning electron microscopy images; and M. Cammer and Y. Deng for help with optical microscopy. The Microscopy Core and the GTC are partially supported by NYU Cancer Center Support Grant NIH/NCI P30CA016087 at the Laura and Isaac Perlmutter Cancer Center, S10 RR023704-01A1 and NIH S10 ODO019974-01A1. The Experimental Pathology Research Laboratory is supported by NIH Shared Instrumentation grants S10OD010584-01A1 and S10OD018338-01. This study benefited from data assembled by the ImmGen consortium. This work was supported by the Pew Latin American Fellows program (J.T.), the Helen and Martin Kimmel Center for Biology and Medicine (D.R.L.); and NIH grant R01DK103358 (D.R.L.). D.R.L. is an Investigator of the Howard Hughes Medical Institute.

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Authors and Affiliations

  1. Molecular Pathogenesis Program, The Kimmel Center for Biology and Medicine of the Skirball Institute, New York University School of Medicine, New York, NY, USA

    Jhimmy Talbot, Paul Hahn, Lina Kroehling, Henry Nguyen, Dayi Li & Dan R. Littman

  2. Howard Hughes Medical Institute, New York, NY, USA

    Dan R. Littman

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Contributions

J.T. and D.R.L. designed the study and analysed the data. J.T. performed the experiments with assistance from P.H. and D.L., H.N. contributed to the feeding experiments and L.K. performed the bioinformatics analyses. J.T. and D.R.L. wrote the manuscript. D.R.L. supervised the research.

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Correspondence to Dan R. Littman.

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D.R.L. consults and has equity interest in Chemocentryx, Vedanta, and Pfizer Pharmaceuticals. All other authors declare no competing interests.

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Extended data figures and tables

Extended Data Fig. 1 Enrichment of transcripts related to nervous system or neural functions and development in CCR6+ ILC3.

a, Volcano plot of differentially expressed genes between CCR6+ ILC3 and CCR6− ILC3 isolated from the small intestine of C57BL/6 mice (data from GSE11609216). n = 3 independent biological samples. Wald test. Green, genes for neurotransmitter receptors or neuropeptide receptors; blue, genes related to nervous system development or axonal guidance and contact. b, Top 10 Gene Ontology (GO) terms from a comparison between subtypes of ILC3 showing enrichment of transcripts related to neuron differentiation and generation in CCR6+ ILC3 when compared to CCR6− ILC3. A graph-based spectral clustering with seeds algorithm was used for multiple testing correction. Green, genes for neurotransmitter receptors; blue, genes related to nervous system development or axonal guidance and contact. c, Volcano plot of differentially expressed genes between CCR6+ ILC3 (enriched in cryptopatches and ILFs45) and NKp46+ ILC3 (low presence in cryptopatches and ILFs46) (data are from GSE12726717). n = 2 independent biological samples. Wald test.

Extended Data Fig. 2 Cryptopatch-associated enteric neurons are also present in the lamina propria of the large intestine (colon).

a, b, Representative immunofluorescence images of lamina propria neuronal projections of enteric neurons in the large intestine of Rorc(t)eGFP/+ mice. Rpresentative of four cryptopatch or ILF clusters. a, Cluster of ILC3 (GFP+ cells) (green) in close proximity to neuronal projections (β-III-tubulin) (red) of the enteric neurons in the colon lamina propria. b, Cluster of ILC3 (GFP+ cells) (blue) in close proximity to neuronal projections (β-III-tubulin) (red) of VIP+ enteric neurons (green) in the colon lamina propria. Representative of three cryptopatch or ILF clusters.

Extended Data Fig. 3 Neurochemical code of the cryptopatch-associated enteric neurons in the small-intestine lamina propria.

a–c, Representative immunofluorescence images of different subtypes of lamina propria neuronal projections of enteric neurons in the small intestine of Rorc(t)eGFP/+ mice. a, Substance P (green) is not present in neuronal projections (β-III-tubulin) (red) localized inside cryptopatches or ILFs (cluster of GFP+ cells) (blue) in the lamina propria. Representative of 15 cryptopatches or ILFs analysed in the small intestine of 4 Rorc(t)eGFP/+ mice. No colocalization of substance P was observed in any of the cryptopatch-associated neuronal fibres. b, Tyrosine hydroxylase+ neurons (green) are in close proximity but are not represented among neuronal projections (β-III-tubulin) (red) localized inside cryptopatches or ILFs (cluster of GFP+ cells) (blue) in the lamina propria. Representative of 20 cryptopatches or ILFs analysed in the small intestine of 4 Rorc(t)eGFP/+ mice. Tyrosine hydroxylase+ fibres are found in proximity to ILC3 clusters but never intercalate with cryptopatches or ILFs. c, VIP+ (green) neurons (β-III-tubulin) (red) are in close proximity to and interacting with ILC3 (GFP+)(blue) in cryptopatches or ILFs. Representative of 40 cryptopatches or ILFs analysed in the small intestine of 4 Rorc(t)eGFP/+ mice.

Extended Data Fig. 4 VIP agonist inhibits in vitro IL-22 production by CCR6+ ILC3.

a, Vipr2 mRNA expression (relative to Hprt) in different subtypes of RORγt+ intestinal lymphoid cells, including subsets of ILC3, αβ TH17 cells and γδT17 cells. RNA was isolated from CCR6+ ILC3, CCR6− ILC3, TH17 cells (αβ RORγt+ T cells) and γδT17 cells (γδ RORγt+ T cells) sorted from the small intestine of Rorc(t)-GfpTG mice on the basis of the following markers: γδT17 cells (Lin−RORγt–GFP+CD3+TCRγ+), TH17 (Lin−RORγt–GFP+CD3+TCRβ+), CCR6+ ILC3 (Lin−RORγt–GFP+CD3−CCR6+) and CCR6−ILC3 (Lin−RORγt–GFP+CD3−CCR6−). n = 4 mice. ND, not detected. b, FACS plot showing gating strategy for identification and isolation of CCR6+ or CCR6− ILC3 (DAPI−Lin−CD127+CD90.2+). c, d, In vitro activation of VIPR2 alone does not induce cytokine production or activation of CCR6+ ILC3. Representative FACS plots (c) and summary (d) for surface SCA1 expression and intracellular IL-22 expression in small-intestine lamina propria CCR6+ ILC3. n = 3 independent biological samples, representative of 2 independent experiments. Mean + s.e.m., adjusted P value (one-way ANOVA, Bonferroni’s multiple comparisons test). e, In vitro activation of VIPR2 promotes concentration-dependent inhibition of cytokine production by CCR6+ ILC3. Summary for IL-22 and IL-17a intracellular expression in small-intestine lamina propria CCR6+ ILC3 stimulated in vitro for 12 h with IL-23 (300 pg ml−1) with different concentrations of VIP. n = 3 independent biological samples for VIP 10 nM and VIP 10 nM with IL-23; n = 4 independent biological samples for vehicle, VIP 1 nM and VIP 1 nM with IL-23; n = 5 independent biological samples for vehicle with IL-23. Mean + s.e.m., adjusted P value (one-way ANOVA, Bonferroni’s multiple comparisons test). Data are from two independent experiments. f, In vitro activation of VIPR2 does not reduce IL-23-induced SCA1 expression on CCR6+ ILC3. Summary of SCA1 expression in small-intestine lamina propria CCR6+ ILC3 stimulated in vitro for 12 h with IL-23 (100 pg ml−1) with or without the VIPR2 ligands BAY-559837 or VIP. n = 3 independent biological samples, representative of 2 independent experiments. Mean + s.e.m., adjusted P value (one-way ANOVA, Bonferroni’s multiple comparisons test). g, h, In vitro VIPR2 activation does not affect IL-23-induced IL-22 production by CCR6− ILC3. Representative FACS plots (g) and summaries (h) of surface SCA1 expression and intracellular IL-22 expression in small-intestine lamina propria CCR6− ILC3 stimulated in vitro for 12 h with IL-23 (100 pg ml−1) with or without VIPR2 ligand BAY-559837 (1 nM). n = 3 independent biological samples, and from 2 independent experiments. Mean + s.e.m., adjusted P value (one-way ANOVA, Bonferroni’s multiple comparisons test).

Source Data

Extended Data Fig. 5 VIPR2 is required for in vivo inhibition of IL-22 production by CCR6+ ILC3.

a, b, Mixed bone-marrow chimaeras, showing no difference in frequency and ratio of wild-type (Vipr2+/+) to VIPR2-knockout (Vipr2−/−) CCR6+ ILC3 in the ileum of mice receiving an equal number of cells (n = 17 mice, combined from 2 independent experiments; mean ± s.e.m., paired t-test) (a) and VIPR2-dependent inhibition of IL-22 production in wild-type (Vipr2+/+, CD45.1) versus VIPR2-knockout (Vipr2−/−, CD45.2) CCR6+ ILC3 in the ileum of chimeric mice (n = 11 independent biological samples; mean ± s.e.m., paired t-test, from two independent experiments) (b). c–e, Transcriptomic profile showing differences between CCR6+ ILC3 among wild-type (Vipr2+/+) and VIPR2-knockout (Vipr2−/−) cells, isolated from mixed bone-marrow chimaeras. n = 3 independent biological samples per group (Wald test). c, Volcano plot (c) and heat map (d) of selected genes differentially expressed between CCR6+ ILC3 from Vipr2+/+ and Vipr2−/− mice (FDR 5%, log2-transformed fold change > 1, Wald test) (data are from GSE140502). e, Analysis of pathways associated with genes upregulated in Vipr2−/− CCR6+ ILC3 compared to Vipr2+/+ CCR6+ ILC3. f, g, Inactivation of Vipr2 in ILC3 and T cells (Rorc(t)creVipr2fl/fl) does not affect the proportion (f) or number (g) of CCR6+ ILC3 in the mouse ileum. Rorc(t)creVipr2+/+(n = 8 mice) and Rorc(t)creVipr2fl/fl (n = 6 mice). Mean + s.e.m., two-sided t-test. h, i, Frequency of IL-22-producing CCR6+ ILC3 upon inactivation of Vipr2 (Rorc(t)creVipr2fl/fl). Representative FACS plot (h) and summaries (i) indicating frequency of IL-22 production in CCR6+ ILC3 from the ileum of Rorc(t)creVipr2+/+(n = 8) and Rorc(t)creVipr2fl/fl (n = 6) mice. Mean + s.e.m., two-sided t-test. Data are from three independent experiments. j, k, IL-17a production in CCR6+ ILC3 upon inactivation of Vipr2. Representative FACS plot (j) and summaries (k) indicating frequency of IL-22 production in CCR6+ ILC3 from the ileum of Rorc(t)creVipr2+/+(n = ) and Rorc(t)creVipr2fl/fl (n = 3) mice. Data are representative of three independent experiments. Mean + s.e.m., two-sided t-test. l, m, Inactivation of Vipr2 does not affect IL-17a or IL-22 production in CD3+RORγt+ lymphoid cell populations (CD3+RORγt+TCRγ+TCRβ− (γδT17) and CD3+RORγt+TCRγ−TCRβ+ (TH17) cells). Rorc(t)creVipr2+/+(n = 4) and Rorc(t)creVipr2fl/fl (n = 4) mice. Data are representative of two independent experiments. Mean + s.e.m., two-sided t-test. FACS plot (l) and summaries (m) indicating frequency of IL-17 and IL-22. NS, not significant. n, o, Intestinal villi and crypt morphology (H&E-stained) indicating the measurement of villi (red bracket) and crypt (green bracket) lengths. Values represent the average length of 60 structures (villi or crypt) per mouse, in a 10-cm region starting 15 cm from the pylorus. Mean + s.e.m., two-sided t-test. Rorc(t)creVipr2+/+ (n = 4 mice) and Rorc(t)creVipr2fl/fl (n = 3 mice). p, q, Ki67 and haematoxylin staining, revealing increased Ki67+ cells in the crypt region of the small intestine (automated counting). Mean + s.e.m., two-sided t-test, Rorc(t)creVipr2+/+(n = 4 mice) and Rorc(t)creVipr2fl/fl (n = 3 mice).

Source Data

Extended Data Fig. 6 Effect of VIPergic neuronal modulation with DREADDs on IL-22 production by CCR6+ ILC3.

a, b, Vipcre activity in neurons in the gut. Homozygous Vipcre mice were bred to homozygous Rosa26fl-st-fl-tdTomato. a, Distribution of tdTomato+ projections in the small-intestine lamina propria. tdTomato, red; nucleus (DAPI), blue. b, tdTomato+ and tdTomato− neurons present in the small intestine. tdTomato, red; pan-neuronal marker (β-III-tubulin), green. Two distinct β-III-tubulin+tdTomato+ neuronal projections (white arrows) can be observed in a bundle of enteric neurons in the villi. Yellow arrowheads, β-III-tubulin+tdTomato− projection. c, Nuclear FOS localization in VIPergic neurons 2 h after CNO (1 mg kg−1, intraperitoneally) or vehicle treatment of mice expressing the DREADD for activation under the control of Vipcre (VipcrehM3Dqfl/+). FOS–Alexa Fluor (AF)488, red; hM3Dq–HA–AF647, green; nucleus (DAPI), blue. d–f, Effect of chemogenetic modulation of VIPergic neurons on IL-22 production by CCR6+ ILC3 in the small intestine (s.i.) and large intestine. Representative FACS plot (d) and summaries of IL-22 production by CCR6+ ILC3 in mice expressing the DREADD for inhibition (hM4Di) (e) and for activation (hM3Dq) (f). All the mice were treated with CNO (1 mg kg−1, intraperitoneally, twice, 24 h before sample collection). e, n = 6 mice per group. f, VIPcre (n = 6 mice per group) and VipcrehM3Dqcre (n = 5 mice per group). Mean + s.e.m., two-sided t-test. g, h, No difference in the frequencies of IL-17 and IL-22 production by CD3+ RORγt+TCRγ+TCRβ− (γδT17) and CD3+ RORγt +TCRγ−TCRβ+ (TH17) cells after activation of VIPergic neurons. Representative FACS plot (g) and summaries (h). Mean + s.e.m., two-sided t-test. n = 5 mice per group. All the mice were treated with CNO (1 mg kg−1, intraperitoneally, twice, 24 h before sample collection).

Source Data

Extended Data Fig. 7 VIPergic neurons regulate host resistance to enteropathogenic C. rodentium.

a, Normalized Vip mRNA expression in the large intestine (caecum and proximal colon) of C57BL/6 mice at different time points after oral infection with C. rodentium (2 × 109 CFU). Day 0, n = 4 mice; 2, 4 and 9 days after infection: n = 6 mice per group. Mean + s.e.m., one-way ANOVA. b, c, Increased VIP activity in the gastrointestinal tract, but not systemically, in mice infected with C. rodentium. Concentrations of VIP in plasma from the hepatic portal vein (b), which drains the gastrointestinal tract, and peripheral blood (c) of mice at different time points after intragastric administration of vehicle or C. rodentium (2 × 109 CFU). dpi, days post-intragastric infection with C. rodentium. Data shown are pooled from two independent experiments. n = 8 mice per group, two-sided t-test. d, Off-target effects of CNO treatment do not account for mortality observed using activating DREADD during C. rodentium infection. Survival rates for C. rodentium-infected VipIRES-creor VipIRES-crehM3Dqfl-stop-fl/+ mice treated with CNO (1 mg kg−1, daily, 1–4 days post-infection (yellow rectangle)). Vehicle, n = 11 mice; CNO, n = 9 mice. e, f, Infectious burden in faeces of VipIRES-crehM3Dqfl-stop-fl/+ mice (activating DREADD; vehicle, n = 11 mice; CNO, n = 9 mice) (e) and VipIRES-crehM4Difl-stop-fl/+ mice (inhibitory DREADD; vehicle, n = 8 mice; CNO, n = 7 mice) (f). Mice were treated with vehicle or CNO (1 mg kg−1, daily) 1–4 days post-intragastric infection with 2 × 109 CFU (for VipIRES-crehM3Dqfl-stop-fl/+mice) or 4 × 1010 CFU (for VipIRES-crehM4Difl-stop-fl/+ mice). log10(CFU of C. rodentium 9 days post-oral inoculation (9 days post-infection)) is shown. Median, two-tailed Mann–Whitney test. Data are representative of two independent experiments. g, h, Exogenous treatment with recombinant mouse IL-22 (rmIL-22, 250 μg per mouse per day) protects against increase in mortality (g) and bacterial dissemination to the spleen (h) induced by VIPergic activation of VipIRES-crehM3Dqfl-stop-fl/+mice. Mantel Cox test, survival (g); median, two-tailed Mann–Whitney test (h). For visualization in the logarithmic scale in e–g, CFU counts of 0 were attributed a value of 1. i, j, Inactivation of Vipr2 expression in ILC3 (Rorc(t)creVipr2fl/fl) enhances barrier protection after oral infection with the enteropathogen C. rodentium (3 × 1010 CFU) (i). Discrete protection for weight loss in the first nine days after infection. Mean, two-way ANOVA. j, log10(CFU of C. rodentium 9 days post-oral inoculation with 3 × 1010 CFU) is shown. Rorc(t)creVipr2fl/fl mice display reduced amounts of C. rodentium translocation to the spleen and liver, and reduced CFU counts in the faeces. Rorc(t)creVipr2+/+, n = 10 mice; Rorc(t)creVipr2fl/fl, n = 10 mice. Mean ± s.e.m., two-way ANOVA (i) and two-tailed Mann–Whitney test (j).

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Extended Data Fig. 8 Feeding controls intestinal VIP release and IL-22 production by CCR6+ ILC3 via activation of VIPR2.

a, Measurement of concentration of VIP in the ileum reveals higher amounts during the dark phase (feeding period, ZT12–ZT0) than during the light phase (resting period, ZT0–ZT12). n = 3 mice per time point, representative of 2 independent experiments. Mean ± s.e.m. b, Concentrations of VIP in plasma isolated from hepatic portal vein blood of mice fed or fasted for 6 h. Blood samples were collected at two time points, during the light-phase period (ZT6, 12:00) and the dark-phase period (ZT18, 00:00). n = 4 mice per group. Mean + s.e.m., two-sided t-test. Data are from two independent experiments. c, Concentrations of VIP in plasma isolated from the peripheral blood of mice. n = 4 mice per group. Mean + s.e.m. Data are from two independent experiments. Blood samples were collected at the same time point as in b. d, IL-22 expression by CCR6+ ILC3 from the ileum of CD45.1 Vipr2+/+ or CD45.2 Vipr2−/− bone-marrow chimeric mice at 6 h after fasting (fasted, ZT6) and 6 h after feeding (fed, ZT18). n = 7 mice per group, two-sided paired t-test. Data are pooled from two independent experiments. e, Ratio of IL-22-expressing cells, relative to d, among CCR6+ ILC3 from the ileum of CD45.1 Vipr2+/+ and CD45.2 Vipr2−/− bone-marrow chimeric mice at 6 h after fasting (fasted, ZT6) and 6 h after feeding (fed, ZT18). n = 7, ***P < 0.001 (t-test).

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Extended Data Fig. 9 Loss of Vipr2 expression in ILC3 of Rorc(t)creVipr2fl/fl mice affects the growth of epithelium-associated SFB and the composition of ileal and faecal commensal microbiota.

a, Representative scanning electron microscopy images (magnifications of 1,000× (top) and 3,000× (bottom)) showing epithelial-attached SFB in the ileum of mice 12 h after feeding (long filaments) or fasting (short filaments, or stubble) at ZT0. Data are representative of two independent experiments. b, Violin-plot distribution of SFB length at different time points during the day in mice that had been fed for two weeks during the light phase (light-phase-fed mice, ZT0 to ZT12 (red)) or during the dark phase (dark-phase-fed mice, ZT12 to ZT0 (blue)). Measurements of SFB filament length were performed from a minimum of two random fields for each mouse (each dot represents an individual filament). n = 3 mice per group, and bars show mean (one-way ANOVA). Data are from two independent experiments. Blue or red shapes show the distribution of the data. c, Relative amounts (log-transformed) of SFB 16S rRNA measured in the ileal tissue by qPCR, normalized on the basis of host genomic DNA quantity. Mice were fed for two weeks during the light phase or during the dark phase, and the ileal tissue was collected at two time points (ZT0 and ZT12). n = 5 mice per group. Mean + s.e.m., two-sided t-test. d, Weighted Unifrac principal coordinate analysis (PCoA) of 16S rRNA composition in the faecal pellet of mice that had been fed for two weeks during the light phase (circles) or during the dark phase (diamonds) (data are deposited at PRJNA594406). Faecal samples were collected from the same mice at different time points (ZT0 and ZT12). n = 3 mice per group. Dark-phase-fed mice: at ZT0 these mice had been fed for 12 h (red diamond), whereas at ZT12 they had fasted for 12 h (blue diamond). Light-phase-fed mice: at ZT0 these mice had fasted for 12 h (blue circle), whereas at ZT12 they had been fed for 12 h (red circle). e, Phylogenetic profile of the composition of the faecal microbiota associated with feeding or fasting status in the mice from d. f, Weighted Unifrac principal coordinate analysis of 16S rRNA composition in the ileal faecal material from Rorc(t)creVipr2+/+ (n = 3) or Rorc(t)creVipr2fl/fl (n = 3) mice (male, 8 weeks old) that had been fed for two weeks only during the dark phase. Samples were collected at ZT0 (12-h fed). This cohort is composed of 3 pairs of Rorc(t)creVipr2+/+ and Rorc(t)creVipr2fl/fl littermates or cagemates, with each pair housed in different cages. g, Phylogenetic profile of the microbiota composition in the ileal faecal material of Rorc(t)creVipr2+/+ or Rorc(t)creVipr2fl/fl mice after 12 h of feeding. h, Weighted Unifrac principal coordinate analysis of 16S rRNA composition in faecal pellet of the same mice described in f, g (Rorc(t)creVipr2+/+ or Rorc(t)creVipr2fl/fl mice). i, Phylogenetic profile of the microbiota composition in the faecal pellet of Rorc(t)creVipr2+/+ or Rorc(t)creVipr2fl/fl mice after 12 h of feeding. j, Relative amounts (log-transformed) of SFB 16S rRNA measured in the ileal tissue from Rorc(t)creVipr2+/+ (n = 3) or Rorc(t)creVipr2fl/fl (n = 3) mice (male, 8 weeks old) that had been fed for two weeks only during the dark phase. Samples were collected at ZT0 (12-h fed). SFB levels were normalized on the basis of host gDNA levels (Hif1a). This cohort is composed of 3 pairs of Rorc(t)creVipr2+/+ and Rorc(t)creVipr2fl/fl mice. Mice were littermates and cagemates, with each pair housed in different cages. Mean + s.e.m., two-sided Student’s t-test. Data are from two independent experiments.

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Extended Data Fig. 10 Feeding increase the efficiency of triglyceride absorption.

a, b, Plasma 3H CPM (counts per minute) in mice fed or fasted for 12 h during the light phase (ZT0–ZT12) (red and green circles) or during the dark phase (ZT12–ZT0) (blue and black circles) and then gavaged with [3H]triolein and sampled at different times (a); and area under the curve (AUC) during 4 h (b). AUC, area under the curve per ml of plasma. n = 4 mice per group, Mean ± s.e.m., two-way ANOVA (a) and one-way ANOVA (b). Data are from two independent experiments. c, Weight of 10 pairs of Rorc(t)creVipr2+/+ and Rorc(t)creVipr2fl/fl mice under regular chow diet (male, 9 weeks old). Mice were littermates and cagemates. Mean + s.e.m., two-sided t-test. Representative of two independent experiments (males and females). d, Weight difference (per cent) between each Rorc(t)creVipr2fl/fl (n = 10) compared to its paired Rorc(t)creVipr2+/+ littermate and cagemate (n = 10) mice, from c. Mean (box limits represent the minimum and maximum values observed). e, f, Graphical abstract (e) and theoretical model (f) of the observations described in this Article, created using BioRender.

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Supplementary Video 1

3D software reconstruction of Figure 1b showing the small intestine of Rorc(t)EGFP/+ mice with a cluster of intestinal ILC3 (cryptopatch) in close proximity to enteric neurons. Pan-neuronal marker: β3-tubulin+ (red), ILC3: GFP+ (green, respectively).

Supplementary Video 2

3D software reconstruction of Figure 1c from the small intestine of Rorc(t)EGFP/+ mice showing ILC3 in the cryptopatch in close proximity to enteric neurons in the small intestine lamina propria. Pan-neuronal marker: β3-tubulin+ (red), ILC3: GFP+TCRβneg (green, respectively).

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Talbot, J., Hahn, P., Kroehling, L. et al. Feeding-dependent VIP neuron–ILC3 circuit regulates the intestinal barrier. Nature 579, 575–580 (2020). https://doi.org/10.1038/s41586-020-2039-9

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