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Proline uptake promotes activation of lymphoid tissue inducer cells to maintain gut homeostasis

Nature Metabolism volume 5, pages 1953–1968 (2023)Cite this article

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Abstract

Metabolic regulation is integral to the proper functioning of innate lymphoid cells, yet the underlying mechanisms remain elusive. Here, we show that disruption of exogenous proline uptake, either through dietary restriction or by deficiency of the proline transporter Slc6a7, in lymphoid tissue inducer (LTi) cells, impairs LTi activation and aggravates dextran sodium sulfate-induced colitis in mice. With an integrative transcriptomic and metabolomic analysis, we profile the metabolic characteristics of various innate lymphoid cell subsets and reveal a notable enrichment of proline metabolism in LTi cells. Mechanistically, defective proline uptake diminishes the generation of reactive oxygen species, previously known to facilitate LTi activation. Additionally, LTi cells deficient in Slc6a7 display downregulation of Cebpb and Kdm6b, resulting in compromised transcriptional and epigenetic regulation of interleukin-22. Furthermore, our study uncovers the therapeutic potential of proline supplementation in alleviating colitis. Therefore, these findings shed light on the role of proline in facilitating LTi activation and ultimately contributing to gut homeostasis.

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Fig. 1: Intestinal ILC subsets display distinct metabolic features.
Fig. 2: Exogenous proline facilitates LTi cell activation.
Fig. 3: Slc6a7 deficiency results in diminished LTi cell activation.
Fig. 4: Slc6a7 deficiency in LTi cells exacerbates DSS-induced colitis.
Fig. 5: Slc6a7 promotes LTi cell activation through C/EBPβ.
Fig. 6: JMJD3 cooperates with C/EBPβ to promote LTi cell activation.
Fig. 7: Proline supplementation alleviates DSS-induced colitis.

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Data availability

RNA-seq, CUT&RUN and CUT&Tag data generated in this study have been deposited in the Genome Sequence Archive in National Genomics Data Center, China National Center for Bioinformation/Beijing Institute of Genomics, Chinese Academy of Sciences database under accession code CRA009785. Data access can be requested through the GSA access committee, but any queries can be directed to C.Z. This study did not generate any unique codes. Source data are provided with this paper. All other data can be made available from the authors on reasonable request.

References

  1. Ramos, G. P. & Papadakis, K. A. Mechanisms of disease: inflammatory bowel diseases. Mayo Clin. Proc. 94, 155–165 (2019).

    CAS  PubMed  Google Scholar 

  2. Fiocchi, C. & Iliopoulos, D. Inflammatory bowel disease therapy: beyond the immunome. Front. Immunol. 13, 864762 (2022).

    CAS  PubMed  PubMed Central  Google Scholar 

  3. Danese, S. & Fiocchi, C. Ulcerative colitis. N. Engl. J. Med. 365, 1713–1725 (2011).

    CAS  PubMed  Google Scholar 

  4. Levine, A., Sigall Boneh, R. & Wine, E. Evolving role of diet in the pathogenesis and treatment of inflammatory bowel diseases. Gut 67, 1726–1738 (2018).

    CAS  PubMed  Google Scholar 

  5. Caio, G. et al. Nutritional treatment in Crohn’s disease. Nutrients 13, 1628 (2021).

    CAS  PubMed  PubMed Central  Google Scholar 

  6. O’Moráin, C., Segal, A. W. & Levi, A. J. Elemental diet as primary treatment of acute Crohn’s disease: a controlled trial. Br. Med. J. 288, 1859–1862 (1984).

    Google Scholar 

  7. Teahon, K., Smethurst, P., Pearson, M., Levi, A. J. & Bjarnason, I. The effect of elemental diet on intestinal permeability and inflammation in Crohn’s disease. Gastroenterology 101, 84–89 (1991).

    CAS  PubMed  Google Scholar 

  8. Altomare, R. et al. Enteral nutrition support to treat malnutrition in inflammatory bowel disease. Nutrients 7, 2125–2133 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  9. Spits, H. et al. Innate lymphoid cells–a proposal for uniform nomenclature. Nat. Rev. Immunol. 13, 145–149 (2013).

    CAS  PubMed  Google Scholar 

  10. Fuchs, A. et al. Intraepithelial type 1 innate lymphoid cells are a unique subset of IL-12- and IL-15-responsive IFN-γ-producing cells. Immunity 38, 769–781 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  11. Klose, C. S. N. et al. Differentiation of type 1 ILCs from a common progenitor to all helper-like innate lymphoid cell lineages. Cell 157, 340–356 (2014).

    CAS  PubMed  Google Scholar 

  12. Barlow, J. L. et al. Innate IL-13-producing nuocytes arise during allergic lung inflammation and contribute to airways hyperreactivity. J. Allergy Clin. Immunol. 129, 191–194 (2012).

    CAS  PubMed  Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

  14. Tang, Q. et al. Development of IL-22-producing NK lineage cells from umbilical cord blood hematopoietic stem cells in the absence of secondary lymphoid tissue. Blood 117, 4052–4055 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

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

    PubMed  PubMed Central  Google Scholar 

  16. Kim, H. Y. et al. Interleukin-17-producing innate lymphoid cells and the NLRP3 inflammasome facilitate obesity-associated airway hyperreactivity. Nat. Med. 20, 54–61 (2014).

    CAS  PubMed  Google Scholar 

  17. Klose, C. S. et al. A T-bet gradient controls the fate and function of CCR6−RORγt+ innate lymphoid cells. Nature 494, 261–265 (2013).

    CAS  PubMed  Google Scholar 

  18. Rankin, L. C. et al. Complementarity and redundancy of IL-22-producing innate lymphoid cells. Nat. Immunol. 17, 179–186 (2016).

    CAS  PubMed  Google Scholar 

  19. Constantinides, M. G., McDonald, B. D., Verhoef, P. A. & Bendelac, A. A committed precursor to innate lymphoid cells. Nature 508, 397–401 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  20. Zhong, C. et al. Differential expression of the transcription factor GATA3 specifies lineage and functions of innate lymphoid cells. Immunity 52, 83–95 (2020).

    CAS  PubMed  Google Scholar 

  21. Zhong, C. & Zhu, J. Transcriptional regulators dictate innate lymphoid cell fates. Protein Cell 8, 242–254 (2017).

    PubMed  PubMed Central  Google Scholar 

  22. Wu, D. et al. PD-1 signaling facilitates activation of lymphoid tissue inducer cells by restraining fatty acid oxidation. Nat. Metab. 4, 867–882 (2022).

    CAS  PubMed  Google Scholar 

  23. Lo, B. C. et al. IL-22 preserves gut epithelial integrity and promotes disease remission during chronic salmonella infection. J. Immunol. 202, 956–965 (2019).

    CAS  PubMed  Google Scholar 

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

    CAS  PubMed  Google Scholar 

  25. Keir, M., Yi, Y., Lu, T. & Ghilardi, N. The role of IL-22 in intestinal health and disease. J. Exp. Med. 217, e20192195 (2020).

    PubMed  PubMed Central  Google Scholar 

  26. Bishop, J. L. et al. Lyn activity protects mice from DSS colitis and regulates the production of IL-22 from innate lymphoid cells. Mucosal Immunol. 7, 405–416 (2014).

    CAS  PubMed  Google Scholar 

  27. Shi, Z. et al. A Japanese herbal formula, daikenchuto, alleviates experimental colitis by reshaping microbial profiles and enhancing group 3 innate lymphoid cells. Front Immunol. 13, 903459 (2022).

    CAS  PubMed  PubMed Central  Google Scholar 

  28. Zeng, B. et al. ILC3 function as a double-edged sword in inflammatory bowel diseases. Cell Death Dis. 10, 315 (2019).

    PubMed Central  Google Scholar 

  29. Hughes, T. et al. Interleukin-1β selectively expands and sustains interleukin-22+ immature human natural killer cells in secondary lymphoid tissue. Immunity 32, 803–814 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  30. Guo, X. et al. Induction of innate lymphoid cell-derived interleukin-22 by the transcription factor STAT3 mediates protection against intestinal infection. Immunity 40, 25–39 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  31. Sanos, S. L. et al. RORgammat and commensal microflora are required for the differentiation of mucosal interleukin 22-producing NKp46+ cells. Nat. Immunol. 10, 83–91 (2009).

    CAS  PubMed  Google Scholar 

  32. Qiu, J. et al. The aryl hydrocarbon receptor regulates gut immunity through modulation of innate lymphoid cells. Immunity 36, 92–104 (2012).

    CAS  PubMed  Google Scholar 

  33. Spencer, S. P. et al. Adaptation of innate lymphoid cells to a micronutrient deficiency promotes type 2 barrier immunity. Science 343, 432–437 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  34. Zhong, C. et al. Group 3 innate lymphoid cells continuously require the transcription factor GATA-3 after commitment. Nat. Immunol. 17, 169–178 (2016).

    CAS  PubMed  Google Scholar 

  35. Cella, M. et al. Subsets of ILC3-ILC1-like cells generate a diversity spectrum of innate lymphoid cells in human mucosal tissues. Nat. Immunol. 20, 980–991 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  36. Ebihara, T. et al. Runx3 specifies lineage commitment of innate lymphoid cells. Nat. Immunol. 16, 1124–1133 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  37. Eberl, G. RORγt, a multitask nuclear receptor at mucosal surfaces. Mucosal Immunol. 10, 27–34 (2017).

    CAS  PubMed  Google Scholar 

  38. Di Luccia, B., Gilfillan, S., Cella, M., Colonna, M. & Huang, S. C. ILC3s integrate glycolysis and mitochondrial production of reactive oxygen species to fulfill activation demands. J. Exp. Med. 216, 2231–2241 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  39. Shafqat, S. et al. Human brain-specific L-proline transporter: molecular cloning, functional expression, and chromosomal localization of the gene in human and mouse genomes. Mol. Pharmacol. 48, 219–229 (1995).

    CAS  PubMed  Google Scholar 

  40. Aden, K. et al. Epithelial IL-23R signaling licenses protective IL-22 responses in intestinal inflammation. Cell Rep. 16, 2208–2218 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  41. Yang, F. C., Chiu, P. Y., Chen, Y., Mak, T. W. & Chen, N. J. TREM-1-dependent M1 macrophage polarization restores intestinal epithelium damaged by DSS-induced colitis by activating IL-22-producing innate lymphoid cells. J. Biomed. Sci. 26, 46 (2019).

    PubMed  PubMed Central  Google Scholar 

  42. Donald, S. P. et al. Proline oxidase, encoded by p53-induced gene-6, catalyzes the generation of proline-dependent reactive oxygen species. Cancer Res. 61, 1810–1815 (2001).

    CAS  PubMed  Google Scholar 

  43. Lee, H., Lee, Y. J., Choi, H., Ko, E. H. & Kim, J. W. Reactive oxygen species facilitate adipocyte differentiation by accelerating mitotic clonal expansion. J. Biol. Chem. 284, 10601–10609 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  44. Klose, R. J. & Zhang, Y. Regulation of histone methylation by demethylimination and demethylation. Nat. Rev. Mol. Cell Biol. 8, 307–318 (2007).

    CAS  PubMed  Google Scholar 

  45. Vicario, M., Amat, C., Rivero, M., Moretó, M. & Pelegrí, C. Dietary glutamine affects mucosal functions in rats with mild DSS-induced colitis. J. Nutr. 137, 1931–1937 (2007).

    CAS  PubMed  Google Scholar 

  46. Wang, X. et al. Aberrant gut microbiota alters host metabolome and impacts renal failure in humans and rodents. Gut 69, 2131–2142 (2020).

    CAS  PubMed  Google Scholar 

  47. Notararigo, S. et al. Targeted 1H NMR metabolomics and immunological phenotyping of human fresh blood and serum samples discriminate between healthy individuals and inflammatory bowel disease patients treated with anti-TNF. J. Mol. Med. 99, 1251–1264 (2021).

    CAS  PubMed  Google Scholar 

  48. Bando, J. K., Liang, H. E. & Locksley, R. M. Identification and distribution of developing innate lymphoid cells in the fetal mouse intestine. Nat. Immunol. 16, 153–160 (2015).

    CAS  PubMed  Google Scholar 

  49. Hodge, S. H. et al. Amino acid availability acts as a metabolic rheostat to determine the magnitude of ILC2 responses. J. Exp. Med. 220, e20221073 (2023).

    CAS  PubMed  Google Scholar 

  50. Karagiannis, F. et al. Lipid-droplet formation drives pathogenic group 2 innate lymphoid cells in airway inflammation. Immunity 52, 620–634 (2020).

    CAS  PubMed  Google Scholar 

  51. Li, Q. et al. E3 ligase VHL promotes group 2 innate lymphoid cell maturation and function via glycolysis inhibition and induction of interleukin-33 receptor. Immunity 48, 258–270 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  52. Peng, V. et al. Ornithine decarboxylase supports ILC3 responses in infectious and autoimmune colitis through positive regulation of IL-22 transcription. Proc. Natl Acad. Sci. USA 119, e2214900119 (2022).

    CAS  PubMed  PubMed Central  Google Scholar 

  53. Monticelli, L. A. et al. Arginase 1 is an innate lymphoid-cell-intrinsic metabolic checkpoint controlling type 2 inflammation. Nat. Immunol. 17, 656–665 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  54. Panda, S. K. et al. SLC7A8 is a key amino acids supplier for the metabolic programs that sustain homeostasis and activation of type 2 innate lymphoid cells. Proc. Natl Acad. Sci. USA 119, e2215528119 (2022).

    CAS  PubMed  PubMed Central  Google Scholar 

  55. Surace, L. et al. Dichotomous metabolic networks govern human ILC2 proliferation and function. Nat. Immunol. 22, 1367–1374 (2021).

    CAS  PubMed  PubMed Central  Google Scholar 

  56. Xie, D. et al. Systematic metabolic profiling of mice with dextran sulfate sodium-induced colitis. J. Inflamm. Res 14, 2941–2953 (2021).

    PubMed  PubMed Central  Google Scholar 

  57. Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  58. Zhang, Y. et al. Model-based analysis of ChIP-seq (MACS). Genome Biol. 9, R137 (2008).

    PubMed  PubMed Central  Google Scholar 

  59. Sharma, G. et al. Analysis of 26 amino acids in human plasma by HPLC using AQC as derivatizing agent and its application in metabolic laboratory. Amino Acids 46, 1253–1263 (2014).

    CAS  PubMed  Google Scholar 

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Acknowledgements

We thank members of the Zhong groups for inspiring discussion and all contributions. Additionally, we thank the Mass Spectrometry Core Facility of School of Basic Medicines, Peking University Health Science Center for their support on metabolomic analysis. We thank Y. Deng for help with cell sorting. We acknowledge funding from the National Natural Science Foundation of China (32170896, 31770957 and 91842102), the National Key Research & Development Program of China (2022YFA0806400, 2022YFA1103602) and the Natural Science Foundation of Beijing (18G10645) to C.Z., the Shenzhen Innovation Committee of Science and Technology (JCYJ20220818100401003) to W.J. and the China Postdoctoral Science Foundation (2023T160031) to D.W.

Author information

Author notes

  1. These authors contributed equally: Di Wu, Zongxian Li, Yime Zhang, Yinlian Zhang, Guanqun Ren.

Authors and Affiliations

  1. Institute of Systems Biomedicine, Department of Immunology, NHC Key Laboratory of Medical Immunology (Peking University), Beijing Key Laboratory of Tumor Systems Biology, Peking University Health Science Center, Beijing, China

    Di Wu, Zongxian Li, Yime Zhang, Yinlian Zhang, Guanqun Ren, Yanyu Zeng, Xingyu Zhao, Peng Li, Luni Hu & Chao Zhong

  2. Department of Physiology and Pathophysiology, School of Basic Medical Sciences, Peking University Health Science Center, Beijing, China

    Huiying Liu & Changtao Jiang

  3. State Key Laboratory of Natural and Biomimetic Drugs, Chemical Biology Center, School of Pharmaceutical Sciences, Peking University Health Science Center, Beijing, China

    Weiqiang Guan & Houhua Li

  4. Institute of Systems Biomedicine, Peking University Health Science Center, Beijing, China

    Zhiyuan Hou & Jingjing Gong

  5. Department of Gastroenterology, Peking University Third Hospital, Beijing, China

    Jun Li

  6. Department of Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen, China

    Wenfei Jin

  7. School of Pharmaceutical Sciences, Tsinghua-Peking Center for Life Sciences, Beijing Frontier Research Center for Biological Structure, Tsinghua University, Beijing, China

    Zeping Hu

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Contributions

C.Z. conceived the project. D.W. and Y. Zeng performed sequencing experiments. D.W., Z.L., Yinlian Zhang, X.Z. and P.L. performed animal experiments. Yime Zhang and L.H. helped with bioinformatic analysis. G.R., H. Liu and Z. Hu helped with metabolomic analysis. Z. Hou and J.G. helped with mouse breeding. W.G. helped with the click reaction. J.L., W.J., C.J. and H. Li provided critical suggestions. D.W. wrote the first manuscript draft. C.Z. supervised the project and wrote the manuscript.

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Correspondence to Chao Zhong.

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Nature Metabolism thanks Siyan Cao, Matthew Hepworth and the other, anonymous, reviewer for their contribution to the peer review of this work. Primary Handling Editor: Isabella Samuelson, in collaboration with the Nature Metabolism team.

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Extended data

Extended Data Fig. 1 ILC subsets display distinct metabolic features.

a, Expression of Slc6a7 in intestinal ILC3, ILC2, ILC1 and epithelial cells, as assessed by real-time qPCR and normalized to Hprt (n = 5 per group). b, UMAP visualization of intestinal ILCs (from GSE144687). c, Expression of ILC1, ILC2 and ILC3 master transcription factors Tbx21, Gata3 and Rorc in different ILC clusters. d, UMAP visualization of intestinal ILCs using metabolic pathway associated genes in KEGG. e, Heatmap profiling of top 10 differentially expressed metabolic genes in the three clusters in d. f, Expression of Tbx21, Gata3 and Rorc in the three clusters in d. g, Pie diagram showing the distribution of ILC1, ILC2, and ILC3, as annotated in b, in the three clusters in d. h, Violin plots showing the enrichment of major KEGG metabolic pathways in ILC1, ILC2 and ILC3 using GSVA (n = 548, 3253 or 4418 per group). i, Violin plots showing the enrichment of amino acid metabolism in ILC1, ILC2 and ILC3 using GSVA (n = 548, 3253 or 4418 per group). j, Gating strategy for cell sorting of distinct ILC subsets, including LTi, NKp46+ ILC3 and ILC2. Data were representative of at least three independent experiments (a, j). Data were presented as the mean ± s.e.m (a). For box plots, the three horizontal lines of the box represented the third quartile, median and first quartile, respectively, from top to bottom. The whiskers below and above the box represented maximum and minimum of data no more than 1.5-fold IQR (inter-quartile range) from the hinge (h,i). The statistical significance was determined by two-sided unpaired Mann-Whitney U test (h).

Source data

Extended Data Fig. 2 Proline deficiency does not alter NKp46+ ILC3 and other non-ILC3 immune cells.

a, Comparison of intestinal NK/ILC1, ILC2 and ILC3 in mice fed by normal diet (ND) and proline free diet (PFD) (n = 5 per group; ns; ns; ns). b, Comparison of different ILC3 subgroups, including LTi, NKp46+ ILC3, NKp46−T-bet+ ILC3, NKp46−T-bet−CCR6− ILC3, in mice fed by ND and PFD (n = 5 per group; ns, ns, ns, ns). c-g, Comparison of CD11b+ cells (c), CD11b+Gr-1+ cells (d), T cells (e), CD4+ T cells, Th1, Th17, Treg (f), and B cells (g), in mice fed by ND and PFD (n = 4 per group; ns; ns; ns; ns; ns, ns, ns; ns). h, Flow cytometric analysis of IL-22 production by intestinal ILC3 (live lineage−RORγt+) in mice fed by ND or PFD. Percentages of IL-22+ ILC3 and their IL-22 MFI were calculated in the right (n = 7 per group; **p = 0.0048; **p = 0.0082). i, Flow cytometric analysis of IL-22 production by intestinal NKp46+ ILC3 in mice fed by ND or PFD. Percentages of IL-22+ NKp46+ ILC3 and their IL-22 MFI were calculated in the right (n = 7 per group; ns; ns). j, Flow cytometric analysis of IL-22 production by intestinal NKp46+ ILC3 of Rag2-/- mice fed by ND or PFD. Percentages of IL-22+ NKp46+ ILC3 and their IL-22 MFI were calculated in the right (n = 4 per group; ns; ns). k, The structural formula of proline analog. l, Intestinal LTi, NKp46+ ILC3 and ILC2 cells were sort-purified and cultured in PFM with or without the proline analog for 12 hours and then the cellular proteins incorporating the proline analog were detected by click reaction through adding azide coupled with biotin and PE streptavidin in sequence for reaction. The PE fluorescence intensity was tested by flow cytometry. m, The relative PE fluorescence intensity were calculated and the cells cultured without the proline analog was used as control (n = 4 per group; *p = 0.0339; **p = 0.0072). Data were representative of at least three independent experiments (a-j, l-m). Data were presented as the mean ± s.e.m, and statistical significance was determined by two-sided unpaired t-test (a-j, m). *p < 0.05; **p < 0.01; ns, not significant.

Source data

Extended Data Fig. 3 Slc6a7 deficiency inhibits IL-22 production in LTi rather than NKp46+ ILC3.

a, Lentiviral infection efficiency in LTi. b, Flow cytometric analysis of IL-22 production in LTi infected by scramble shRNA (shScram) or shSlc6a7 lentivirus. Percentages of IL-22+ LTi and their IL-22 MFI were calculated (n = 4 per group; *p = 0.0135; *p = 0.0359). c, Gene targeting strategy for Slc6a7-/- mice. d, UMAP visualization of intestinal immune cells (from GSE124880). e, Assessment of Slc6a7 expression in each immune cell cluster. f, Cell numbers of intestinal NK/ILC1, ILC2 and ILC3 in Slc6a7+/+ and Slc6a7-/- mice (n = 5 per group; ns; ns; ns). g, Cell numbers of the indicated ILC3 subgroups in intestines of Slc6a7+/+ and Slc6a7-/- mice (n = 5 per group; ns, ns, ns, ns). h, Flow cytometric analysis of IL-22 production by intestinal NKp46+ ILC3 in Slc6a7+/+ and Slc6a7-/- mice. Percentages of IL-22+ NKp46+ ILC3 and their IL-22 MFI were calculated (n = 7 per group; ns; ns). i, Flow cytometric analysis of IL-22 production by colonic NKp46+ ILC3 in Slc6a7+/+ and Slc6a7-/- mice on day 7 of DSS-induced colitis. Percentages of IL-22+ NKp46+ ILC3 and their IL-22 MFI were calculated (n = 5 per group; ns; ns). j, Percentages of IL-17A+ and GM-CSF+ colonic LTi in Slc6a7+/+ and Slc6a7-/- mice on day 7 of DSS-induced colitis (n = 6 per group; *p = 0.0313; ns). k, Flow cytometric analysis of IL-22 production by colonic LTi in Slc6a7+/+ and Slc6a7-/- mice on day 4 post C. rodentium infection. Percentages of IL-22+ LTi and their IL-22 MFI were calculated (n = 5 per group; ***p = 0.0004; ns). l, Expression of Il23 and Il1b in colon tissue from Slc6a7+/+ and Slc6a7-/- mice, as assessed by real-time qPCR and normalized to Hprt (n = 4 per group; ns; ns). m, Percentages of IL-22+ NKp46+ ILC3 in wild-type (CD45.1) and Slc6a7-/- (CD45.2) chimerism on day 5 of DSS-induced colitis (n = 5 per group; ns). Data were representative of at least three independent experiments (a-b, f-l) or two independent experiments (m). Data were presented as the mean ± s.e.m, and statistical significance was determined by two-sided unpaired t-test (b, f-l) or two-sided paired t-test (m). *p < 0.05; ***p < 0.001; ns, not significant.

Source data

Extended Data Fig. 4 Impaired exogenous proline uptake and IL-22 production are associated with elevated DSS-induced colitis.

a, Body weight change of Slc6a7-/- mice fed by ND or PFD during DSS-induced colitis (n = 5 per group; ns). b, Colon length of Slc6a7-/- mice fed by ND or PFD on day 7 of DSS-induced colitis (n = 4 per group; ns). c, H&E staining of colon tissues on day 7 of DSS-induced colitis from Slc6a7-/- mice fed by ND or PFD. d, Schematics of colitis induction in wild-type (Slc6a7+/+) or Slc6a7-/- mice administrated with recombinant murine IL-22 (rIL-22) or PBS. e, Body weight change of wild-type (Slc6a7+/+) and Slc6a7-/- mice with the indicated treatment during DSS-induced colitis (n = 4 per group; ns; *p = 0.0164). f, Colon length of wild-type (Slc6a7+/+) and Slc6a7-/- mice on day 7 of DSS-induced colitis with the indicated treatment (n = 4 per group; **p = 0.0083, **p = 0.0053). g, H&E staining of colon tissues from wild-type (Slc6a7+/+) and Slc6a7-/- mice on day 7 of DSS-induced colitis with the indicated treatment. Data were representative of at least three independent experiments (a-c, e−g). Data were presented as the mean ± s.e.m, and statistical significance was determined by two-sided unpaired t-test (b, f) or two-sided paired t-test (a, e). *p < 0.05; **p < 0.01; ns, not significant.

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Extended Data Fig. 5 Transcription factor C/EBPβ facilitates the activation of LTi.

a, Key genes in the enriched GO terms in wild-type (Slc6a7+/+) LTi. b, Key genes in the enriched GO terms in Slc6a7-/- LTi. c, Flow cytometric analysis of IL-22 expression by intestinal LTi after cultured in presence of vehicle (H2O) or NAC for 24 h. Percentages of IL-22+ LTi and their IL-22 MFI were calculated in the right (n = 6 per group; ***p < 0.0001; **p = 0.0034). d, Flow cytometric assessment of ROS content in intestinal LTi of ND and PFD fed mice. Percentages of ROS+ intestinal LTi were calculated in the right (n = 4 per group; **p = 0.0046). e, Comparison of ROS level in LTi cells cultured in presence or absence of proline. Percentages of ROS+ LTi were calculated in the right (n = 5 per group; ***p = 0.0003). f, Comparison of transcription factor expression in wild-type (Slc6a7+/+) and Slc6a7-/- LTi. g, Coexpression network between Cebpb and ILC3 activation related genes based on the single-cell transcriptome of LTi (from GSE144687). h, Evaluation of the Cebpb coexpressed genes in activated or inactivated LTi. i, Assessment of C/EBPβ binding at loci of Cebpb coexpressed genes in intestinal LTi using CUT&RUN assay. j, Flow cytometric analysis of C/EBPβ expression in intestinal LTi from mice fed with H2O or NAC for one week (n = 5 per group; **p = 0.0045). Data were representative of two independent experiments (a-b, f, i) or at least three independent experiments (c-e, j). Data were presented as the mean ± s.e.m, and statistical significance was determined by two-sided unpaired t-test (c-e, j). **p < 0.01; ***p < 0.001.

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Extended Data Fig. 6 JMJD3 promotes LTi activation.

a-d, Comparison of histone acetyltransferases (a), histone deacetylases (b), histone methyltransferases (c) and histone demethylases (d) between wild-type (Slc6a7+/+) and Slc6a7-/- intestinal LTi. e, Flow cytometric analysis of IL-22 expression by intestinal LTi after cultured in the indicated conditions for 24 h. f, Statistical calculation of percentages of IL-22+ LTi and their IL-22 MFI in (e) (n = 5 per group; ***p = 0.0002, ***p = 0.0003, ns; **p = 0.0065, **p = 0.0014, ns). g, Flow cytometric analysis of IL-22 expression by intestinal LTi after cultured with or without succinate for 24 h. h, Statistical calculation of percentages of IL-22+ LTi and their IL-22 MFI in (g) (n = 4 per group; ns; ns). Data were representative of two independent experiments (a-d) or at least three independent experiments (e-h). Data were presented as the mean ± s.e.m, and statistical significance was determined by two-sided unpaired t-test (f, h). **p < 0.01; ***p < 0.001; ns, not significant.

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Extended Data Fig. 7 Exogenous proline promotes gut homeostasis via altering metabolic, transcriptional and epigenetic processes in LTi.

a, LTi resident in the gut specifically express high affinity proline transporter Slc6a7, suggesting an increased exogenous proline uptake. In addition, intracellular synthesis of proline from glutamine is also enhanced as indicated by the upregulation of the related enzymes in LTi. However, free proline content in LTi has displayed a substantial reduction. Given the milder expression of proline degradation enzyme ProDH in LTi, most free proline should be consumed by anabolism. Nevertheless, the additional exogenous proline uptake in LTi through Slc6a7 still enhances its degradation, resulting in increased ROS generation. The proline metabolism in LTi also leads to upregulation of an ROS responsive transcription factor, C/EBPβ, which directly binds to Il22 to promote its transcription. Besides, C/EBPβ also promotes Kdm6b transcription. Its encoding enzyme JMJD3 can reduce H3K27me3 at Il22 locus, and thus cooperatively promotes Il22 expression in LTi. Together, these metabolic, transcriptional and epigenetic changes initiated by exogenous proline optimized LTi activation and their IL-22 production, which finally benefits gut homeostasis through acting on epithelial cells.

Extended Data Fig. 8 The therapeutic effect of proline supplementation on colitis is dependent on ILC3.

a, Expression of proline transporters SLC6A20 and SLC6A7 in human jejunum ILC3 (from GSE126107). HPRT expression is utilized as a reference (n = 3 per group). b, UMAP visualization of intestinal ILC and T cell subsets in IBD patients. Classification in the previous reported study (GSE184291) is utilized. c, Comparison of SLC6A20, CEBPB and KDM6B in CCR6+ ILC3 from inflamed and noninflamed tissues (n = 1279 or 969 per group). The three horizontal lines of the box represented the third quartile, median and first quartile, respectively, from top to bottom. d, Flow cytometric analysis of IL-22 production by colonic NKp46+ ILC3 in wild-type (Slc6a7+/+) and Slc6a7-/- mice supplied with or without additional proline, on day 7 of DSS-induced colitis. e, Percentages of IL-22+ NKp46+ ILC3 and their IL-22 MFI in (d) were calculated (n = 5 per group; ns, ns; ns, ns). f, Body weight change of wild-type (Rorcfl/fl) and RorcKO (Rorcfl/flVavCre) mice during DSS-induced colitis with the indicated treatment (n = 4 per group; ns; *p = 0.0484). g, Colon length of wild-type (Rorcfl/fl) and RorcKO (Rorcfl/flVavCre) mice on day 7 of DSS-induced colitis with the indicated treatment (n = 4 per group; ***p = 0.0005, ns). h, H&E staining of colon tissues of wild-type (Rorcfl/fl) and RorcKO (Rorcfl/flVavCre) mice on day 7 of DSS-induced colitis with the indicated treatment. Data were representative of at least three independent experiments (d-h). Data were presented as the mean ± s.e.m, and statistical significance was determined by two-sided unpaired t-test (e, g) or two-sided paired t-test (f). *p < 0.05; ***p < 0.001; ns, not significant.

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Wu, D., Li, Z., Zhang, Y. et al. Proline uptake promotes activation of lymphoid tissue inducer cells to maintain gut homeostasis. Nat Metab 5, 1953–1968 (2023). https://doi.org/10.1038/s42255-023-00908-6

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