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The neuropeptide VIP confers anticipatory mucosal immunity by regulating ILC3 activity

Nature Immunology volume 21, pages 168–177 (2020)Cite this article

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A Correction to this article was published on 30 January 2020

Abstract

Group 3 innate lymphoid cell (ILC3)-mediated production of the cytokine interleukin-22 (IL-22) is critical for the maintenance of immune homeostasis in the gastrointestinal tract. Here, we find that the function of ILC3s is not constant across the day, but instead oscillates between active phases and resting phases. Coordinate responsiveness of ILC3s in the intestine depended on the food-induced expression of the neuropeptide vasoactive intestinal peptide (VIP). Intestinal ILC3s had high expression of the G protein-coupled receptor vasoactive intestinal peptide receptor 2 (VIPR2), and activation by VIP markedly enhanced the production of IL-22 and the barrier function of the epithelium. Conversely, deficiency in signaling through VIPR2 led to impaired production of IL-22 by ILC3s and increased susceptibility to inflammation-induced gut injury. Thus, intrinsic cellular rhythms acted in synergy with the cyclic patterns of food intake to drive the production of IL-22 and synchronize protection of the intestinal epithelium through a VIP–VIPR2 pathway in ILC3s.

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Fig. 1: ILC2 and ILC3 activities oscillate during the active and resting phase at steady state in wild-type mice.
Fig. 2: The molecular clock only partially regulates circadian expression of cytokine secretion.
Fig. 3: Food intake regulates the cytokine secretion of enteric ILC2s and ILC3s.
Fig. 4: Intestinal ILC3 subsets express VIPR2 and are located close to VIP-expressing neurons.
Fig. 5: VIP directly regulates IL-22 production by ILC3s.
Fig. 6: VIPR2 signaling regulates IL-22 secretion from ILC3s in vivo.
Fig. 7: VIPR2 signaling is crucial for the regulation of gut integrity in vivo.
Fig. 8: VIPR2−/− ILC3s provide protection from DSS-induced inflammation.

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Data availability

Single-cell RNA–Seq profiling data that support the findings of this study have been deposited in the Gene Expression Omnibus repository with the accession code GSE132273.

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Acknowledgements

We thank M. Camilleri, A. Lin, S. Cree, C. Alvarado and T. Putoczki for expert technical advice and support. We thank S. Wilcox for performing the sequencing, and S. Nutt for critical reading of the manuscript. Financial support for this work was provided by National Health and Medical Research Council (NHMRC) of Australia grants (APP1165443, 1122277 and 1054925 to G.T.B. and C.S.), Cure Cancer and Cancer Australia (APP1163990 to N.J.), The Rebecca L. Cooper Medical Research Foundation (to G.T.B.) and fellowships from the NHMRC (APP1135898 to G.T.B., APP1123000 to C.S. and APP1154970 to G.K.S.). This study was made possible through the Victorian State Government Operational Infrastructure Support Program and the Australian Government NHMRC Independent Research Institute Infrastructure Support Scheme.

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  1. Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia

    Cyril Seillet, Kylie Luong, Julie Tellier, Nicolas Jacquelot, Rui Dong Shen, Peter Hickey, Verena C. Wimmer, Lachlan Whitehead, Kelly Rogers, Gordon K. Smyth, Alexandra L. Garnham, Matthew E. Ritchie & Gabrielle T. Belz

  2. Department of Medical Biology, University of Melbourne, Melbourne, Victoria, Australia

    Cyril Seillet, Kylie Luong, Julie Tellier, Nicolas Jacquelot, Rui Dong Shen, Peter Hickey, Verena C. Wimmer, Lachlan Whitehead, Kelly Rogers, Alexandra L. Garnham, Matthew E. Ritchie & Gabrielle T. Belz

  3. School of Mathematics and Statistics, University of Melbourne, Melbourne, Victoria, Australia

    Gordon K. Smyth

  4. The University of Queensland Diamantina Institute, The University of Queensland, Brisbane, Queensland, Australia

    Gabrielle T. Belz

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Contributions

C.S., K.L., A.L.G., P.H., N.J., J.T., V.C.W. and R.D.S. performed the experiments and data analyses. G.K.S., A.L.G., P.H. and M.E.R. oversaw the bioinformatic analyses. V.C.W., K.R. and L.W. oversaw the imaging analyses. G.T.B. wrote the draft manuscript and coedited it with C.S. and with the help of the other coauthors. G.T.B. and C.S. directed the studies.

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Extended data

Extended Data Fig. 1 Cytokine secretion of ILCs at T4 and T16.

a,b, Frequency of cytokine-producing NK cells, ILC1, ILC2 and ILC3 isolated from the lungs (a) and mesenteric LN (b) at T4 and T16. IFN-γ, TNF-α, IL-5, IL-13, IL-17 and IL-22 production was determined by intracellular cytokine staining in the indicated populations. Individual responses together with mean ± s.e.m. are shown. a,b, n = 7 mice at each time point. Data is shown for one of four similar experiments for the lung analysis and six experiments for the mesenteric LN analysis. a,b, Statistical significance was determined using a two-tailed unpaired Student’s t-test. *P < 0.05; **P < 0.01; NS, not significant.

Extended Data Fig. 2 Enhanced cytokine expression in ILC subsets at T4 and T16.

Geometric mean fluorescence intensity of intracellular IL-5 and IL-22 cytokine production from ILC2 and ILC3, respectively, isolated from the small intestine of naïve C57BL/6 mice at T4 and T16. Shown are individual responses together with mean ± s.e.m. (n = 4 mice per time point) for one of four similar experiments. Statistical significance was determined using a two-tailed unpaired Student’s t-test. *P < 0.05; **P < 0.01.

Extended Data Fig. 3 Cytokine secretion of T lymphocytes at T4 and T16.

a-c, Frequency of indicated cytokine produced by CD4+ T cells and Th17+ cells (CD4+Rorγt+) in the small intestine (a), lungs (b) and mesenteric LN (c) from naïve C57BL/6 mice at T4 and T16. IFN-γ, TNF-α, IL-17 and IL-22 production was determined by intracellular cytokine staining. Individual responses together with mean ± s.e.m. are shown. a-c, n = 7 mice at each time point. Data show one representative of four for the lung analysis, and one of six similar experiments for the small intestine and mesenteric LN analysis. a-c, Statistical significance was determined using a two-tailed unpaired Student’s t-test. *P < 0.05; **P < 0.01; ***P < 0.001; NS, not significant.

Extended Data Fig. 4 Total number of lymphocytes in the small intestine of mixed bone-marrow chimeric mice.

Mixed bone marrow chimeras were generated by reconstituting CD45.1+/+ lethally irradiated recipients with a 1:1 proportion of F1 (CD45.1 × CD45.2, CD45.1+CD45.2+) wild-type and CD45.2+/+ ArntlΔIL−7R bone marrow. Total number of different lymphocyte subsets isolated in the small intestine of mixed bone marrow chimeras are shown. Cells derived from wild-type (CD45.1+CD45.2+) bone marrow are indicated in white and cells from ArntlΔIL−7R (CD45.2+/+) are shown in black. ILC subsets were gated as live lin−(B220−CD19−CD3−) CD45.1+CD45.2+ (wild-type) or CD45.2+/+ (ArntlΔIL−7R) NK1.1+NKp46+ NK cells/ILC1, NK1.1−NKp46−Rorγt−Gata3+ ILC2 and NK1.1−NKp46+/− Rorγt+Gata3− ILC3. Data are representative of three independent experiments and show the mean ± s.e.m. for one experiment (n = 6 mice/experiment). Statistical significance was determined using a two-tailed unpaired Student’s t-test. *P < 0.05; **P < 0.01.

Extended Data Fig. 5 Purification of small intestinal ILC3 from food-restricted mice.

cytometric sorting of lin−(CD3ε−TCRβ−CD19−B220−Gr1−CD11b−) CD45+IL-7Rα+CD90+c-kit+ KLRG1− cells using a BD FACSARIA III (BD Biosciences). a, Representative dot plots show the cell surface markers and gating strategy used to discriminate ILC3 from other ILC subsets. b, Representative analyses of ILC3 purity after cell sorting of 26 independent sorts.

Extended Data Fig. 6 Single cell RNA-sequencing of colon ILC3.

a-c, ILC from colon were sorted and single cells were sequenced using 10× Genomics. a, t-Distributed stochastic neighbour embedding (t-SNE) plots show 7,388 cells (dots) coloured by cluster. b, Level of expression of indicated genes within the t-SNE plots. c, Representative differentially expressed genes (x axis) by cluster (y axis). Dot size represents the fraction of cells within the cluster that express each gene. The colour intensity indicates the z-scaled expression of genes in cells within each cluster. d, Confocal image of a frozen section of the colon of a Rorc(γt)GFP/+ mouse stained for neurons (β3-tubulin III, red), VIP (green), ILC3 (RORγt-GFP+CD3ε−, white) and T cells (CD3ε+, purple). Image is representative of 2 independent experiments with 2 mice per experiment. Scale bar, 100 μm. e, Confocal images of frozen sections of colon from Rorc(γt)GFP/+ mice at T4 (n = 68) and T16 (n = 53) stained for neurons (β3-tubulin, red) and VIP (green). Violin plots show the minima, 25% percentile, median, 75% percentile, and maxima for neuron axons in the colon from two mice with 6–8 sections per timepoint. Representative of two independent experiments (n = 2 mice per condition). Scale bar, 50 μm. e, Statistical significance was determined using a two-tailed unpaired Student’s t-test. ***P < 0.001.

Extended Data Fig. 7 Characterisation of lymphocytes in Vipr2−/−mice.

a, Wild-type and Vipr2−/− mice were fed ad libitum or fasted for 16 h and constitutive expression of IL-22 from CD4+ T cells from the small intestine was determined by flow cytometry following 4 h in vitro culture. Data show the individual responses together with the mean ± s.e.m. pooled from two independent experiments (n = 4 Wild-type mice per experiment/condition and n = 2 Vipr2−/− mice per experiment/condition). b, Enumeration of ILC1, ILC2, total ILC3, CD4+ ILC3, CD4− ILC3, B cells, CD8+ T cells and CD4+ T cells isolated from the small intestine of naïve wild-type and Vipr2−/− mice. Data show the mean ± s.e.m. of one of two similar experiments (n = 8 mice per time point per experiment). a,b, Statistical significance was determined using a two-tailed unpaired Student’s t-test. *P < 0.05; **P < 0.01; NS, not significant.

Extended Data Fig. 8 Untreated Vipr2−/−and wild-type mice maintain weight at steady-state.

a, Weight changes for naive control wild-type and Vipr2−/− mice during the DSS treatment period shown in Fig. 7a. Data show mean ± s.e.m (n = 5 mice/genotype) percent of initial weight for one of two independent experiments with similar results. b, Representative H&E stained sections of the colon from untreated wild-type and Vipr2−/− mice. Scale bar, 200 μm. Images are representative of two independent experiments with similar results. c-e, Quantitative analysis of crypt height (c), epithelium irregularity (d) and inflammatory infiltrate (e) in untreated WT and Vipr2−/− mice. Epithelial length was measured in the distal part of the colon. Overall epithelial irregularity and inflammatory infiltrate was scored from six sections over two different slides per mouse (0 = normal, 1 = minor, 2 = moderate, 3 = severe). Mucosal thickness was measured across 12 randomly selected sites points per mouse. Data show mean ± s.e.m (n = 3 mice/genotype) of one of two independent experiments with similar results. c-e, Statistical significance was determined using a two-tailed unpaired Student’s t-test. *P < 0.05; NS, not significant.

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Seillet, C., Luong, K., Tellier, J. et al. The neuropeptide VIP confers anticipatory mucosal immunity by regulating ILC3 activity. Nat Immunol 21, 168–177 (2020). https://doi.org/10.1038/s41590-019-0567-y

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