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Inulin fibre promotes microbiota-derived bile acids and type 2 inflammation - Nature.com

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Abstract

Dietary fibres can exert beneficial anti-inflammatory effects through microbially fermented short-chain fatty acid metabolites1,2, although the immunoregulatory roles of most fibre diets and their microbiota-derived metabolites remain poorly defined. Here, using microbial sequencing and untargeted metabolomics, we show that a diet of inulin fibre alters the composition of the mouse microbiota and the levels of microbiota-derived metabolites, notably bile acids. This metabolomic shift is associated with type 2 inflammation in the intestine and lungs, characterized by IL-33 production, activation of group 2 innate lymphoid cells and eosinophilia. Delivery of cholic acid mimics inulin-induced type 2 inflammation, whereas deletion of the bile acid receptor farnesoid X receptor diminishes the effects of inulin. The effects of inulin are microbiota dependent and were reproduced in mice colonized with human-derived microbiota. Furthermore, genetic deletion of a bile-acid-metabolizing enzyme in one bacterial species abolishes the ability of inulin to trigger type 2 inflammation. Finally, we demonstrate that inulin enhances allergen- and helminth-induced type 2 inflammation. Taken together, these data reveal that dietary inulin fibre triggers microbiota-derived cholic acid and type 2 inflammation at barrier surfaces with implications for understanding the pathophysiology of allergic inflammation, tissue protection and host defence.

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Fig. 1: Inulin fibre diet upregulates systemic bile acids and tissue eosinophils.
Fig. 2: Inulin fibre diet-induced eosinophilia requires ILC2s and IL-33.
Fig. 3: Microbiota-derived CA and host FXR mediate inulin fibre diet-triggered type 2 inflammation.
Fig. 4: Inulin-fibre-diet-induced eosinophils promote allergic inflammation and anti-helminth defence.

Data availability

All data necessary to understand and evaluate the conclusions of this paper are provided in the Article and its Source Data and  Supplementary Information. The 16S rRNA-seq data are available at the NCBI Sequence Read Archive under accession number BioProject PRJNA761331. The RNA-seq and spatial transcriptomic data are available at Gene Expression Omnibus (GEO) under accession numbers GSE183443 and GSE183696, respectively. The mouse genome data (NCBI GRCm38/mm10) used for the alignment of RNA-seq data are available under accession number BioProject PRJNA20689. The MS1 and MS2 data for mouse samples analysed in this study are available at the GNPS website (https://massive.ucsd.edu) under MassIVE ID number MSV000086890. Source data are provided with this paper.

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Acknowledgements

We thank the members of the Artis laboratory for discussions and reading the manuscript; A. Alonso and other members of the Epigenomics Core and the Microbiome Core of Weill Cornell Medicine for spatial transcriptomic analyses and RNA-seq; all of the contributing members of the JRI IBD Live Cell Bank consortium, which is supported by the JRI, Jill Roberts Center for IBD, Cure for IBD, the Rosanne H. Silbermann Foundation, the Sanders Family and the Weill Cornell Medicine Division of Pediatric Gastroenterology and Nutrition. The cartoons and illustrations were created using BioRender. The chemical structures were created with ChemDraw. This work was supported by the Crohn’s & Colitis Foundation (851136 to M.A., 901000 to W.Z., 937437 to H.Y.); the Sackler Brain and Spine Institute Research (to C.C.); Thomas C. King Pulmonary Fellowship and Weill Cornell Medicine Fund for the Future (to C.N.P.); the WCM Department of Pediatrics Junior Faculty Pilot Award and The Jill Roberts Center Pilot Award for Research in IBD (to A.M.T.); AGA Research Foundation, WCM-RAPP Initiative, the W. M. Keck Foundation (to C.-J.G.); the Howard Hughes Medical Institute (to F.C.S.); the LEO foundation, CURE for IBD, the Jill Roberts Institute for Research in IBD, the Sanders Family Foundation and Rosanne H. Silbermann Foundation (to D.A.); and the National Institutes of Health (5T32HL134629 to C.N.P., DP2 HD101401-01 to C.-J.G., AI140724 to S.W., KL2 TR002385 to A.F.H., R35 GM131877 to F.C.S., and DK126871, AI151599, AI095466, AI095608, AR070116, AI172027 and DK132244 to D.A.).

Author information

Authors and Affiliations

  1. Jill Roberts Institute for Research in Inflammatory Bowel Disease, Division of Gastroenterology and Hepatology, Joan and Sanford I. Weill Department of Medicine, Weill Cornell Medicine, Cornell University, New York, NY, USA

    Mohammad Arifuzzaman, Ting-Ting Li, Hiroshi Yano, Sreehaas Digumarthi, Wen Zhang, Christopher N. Parkhurst, Sanchita Kashyap, Wen-Bing Jin, Gregory Garbès Putzel, Amy M. Tsou, Coco Chu, Qianru Wei, Alex Grier, Randy Longman, Gregory Sonnenberg, Ellen Scherl, Dana Lukin, Robert Battat, Jasmin Williams, Shaira Khan, Peik Sean Chong, Samah Mozumder, Lance Chou, Wenqing Zhou, Anees Ahmed, Connie Zhong, Ann Joseph, Joseph Gladstone, Samantha Jensen, Chun-Jun Guo & David Artis

  2. Friedman Center for Nutrition and Inflammation, Weill Cornell Medicine, Cornell University, New York, NY, USA

    Mohammad Arifuzzaman, Ting-Ting Li, Hiroshi Yano, Sreehaas Digumarthi, Wen Zhang, Christopher N. Parkhurst, Sanchita Kashyap, Wen-Bing Jin, Gregory Garbès Putzel, Amy M. Tsou, Coco Chu, Qianru Wei, Alex Grier, Randy Longman, Gregory Sonnenberg, Samah Mozumder, Lance Chou, Wenqing Zhou, Anees Ahmed, Connie Zhong, Ann Joseph, Joseph Gladstone, Samantha Jensen, Chun-Jun Guo & David Artis

  3. Department of Microbiology and Immunology, Weill Cornell Medicine, Cornell University, New York, NY, USA

    Mohammad Arifuzzaman, Ting-Ting Li, Hiroshi Yano, Sreehaas Digumarthi, Wen Zhang, Christopher N. Parkhurst, Sanchita Kashyap, Wen-Bing Jin, Gregory Garbès Putzel, Amy M. Tsou, Coco Chu, Qianru Wei, Alex Grier, Randy Longman, Gregory Sonnenberg, Samah Mozumder, Lance Chou, Wenqing Zhou, Anees Ahmed, Connie Zhong, Ann Joseph, Joseph Gladstone, Samantha Jensen, Chun-Jun Guo & David Artis

  4. Boyce Thompson Institute, Department of Chemistry and Chemical Biology, Cornell University, Ithaca, NY, USA

    Tae Hyung Won & Frank C. Schroeder

  5. Gale and Ira Drukier Institute for Children’s Health, Department of Pediatrics, Weill Cornell Medicine, Cornell University, New York, NY, USA

    Andrea F. Heras & Stefan Worgall

  6. Division of Pediatric Gastroenterology, Hepatology and Nutrition, Weill Cornell Medicine, New York, NY, USA

    Amy M. Tsou, Robbyn Sockolow, Thomas Ciecierega, Aliza Solomon, Elaine Barfield, Kimberley Chien & Johanna Ferreira

Authors
  1. Mohammad Arifuzzaman
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  2. Tae Hyung Won
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  4. Hiroshi Yano
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  5. Sreehaas Digumarthi
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  6. Andrea F. Heras
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  7. Wen Zhang
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  8. Christopher N. Parkhurst
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  10. Wen-Bing Jin
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  11. Gregory Garbès Putzel
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  12. Amy M. Tsou
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  13. Coco Chu
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  14. Qianru Wei
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  15. Alex Grier
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  17. Chun-Jun Guo
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  18. Frank C. Schroeder
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  19. David Artis
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Consortia

JRI IBD Live Cell Bank Consortium

  • David Artis
  • , Randy Longman
  • , Gregory Sonnenberg
  • , Ellen Scherl
  • , Robbyn Sockolow
  • , Dana Lukin
  • , Robert Battat
  • , Thomas Ciecierega
  • , Aliza Solomon
  • , Elaine Barfield
  • , Kimberley Chien
  • , Johanna Ferreira
  • , Jasmin Williams
  • , Shaira Khan
  • , Peik Sean Chong
  • , Samah Mozumder
  • , Lance Chou
  • , Wenqing Zhou
  • , Anees Ahmed
  • , Connie Zhong
  • , Ann Joseph
  • , Sanchita Kashyap
  • , Joseph Gladstone
  •  & Samantha Jensen

Contributions

M.A. performed most of the experiments and analysed the data. T.H.W. and F.C.S. conducted untargeted metabolomic data generation and analysis, T.-T.L. and C.-J.G. performed bacterial genome editing and additional LC–quadrupole time-of-flight MS. A.F.H. and S.W. performed lung function measurement. H.Y., S.D., W.Z., C.N.P., S.K., A.M.T., C.C., Q.W. and W.-B.J. helped with various experiments with mice. G.G.P. and A.G. performed RNA-seq data analyses. The members of the JRI IBD Live Cell Bank Consortium contributed to human sample acquisition and processing. M.A. and D.A. conceived the project, analysed data and wrote the manuscript with input from all of the authors.

Corresponding authors

Correspondence to Chun-Jun Guo, Frank C. Schroeder or David Artis.

Ethics declarations

Competing interests

D.A. has contributed to scientific advisory boards at Pfizer, Takeda, FARE and the KRF. F.C.S. is a cofounder of Ascribe Bioscience and Holoclara. The other authors declare no competing interests.

Peer review

Peer review information

Nature thanks Pieter Dorrestein and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data figures and tables

Extended Data Fig. 1 Changes in gut microbiota by inulin fibre diet.

a–d, Mice were fed the control or inulin fibre diets for two weeks (n = 5 mice). Weighted UniFrac PCoA (a) and taxonomic classification (b) of 16S rRNA in stool pellets were shown. For PCoA plot PERMANOVA: F = 12.6, Df = 1, P = 0.008. ‘uncl_d_’ stands for ‘unclassified_domain_’. ‘uncl_d_Bacteria’ matches exactly to mitochondria or chloroplasts, probably from the food. Relative abundance of families or genera increased (c) or decreased (d) by the inulin fibre diet was shown. Data in a–d are representative of three independent experiments. Data are means ± s.e.m. Statistics were calculated by unpaired two-tailed t-test (c,d).

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Extended Data Fig. 2 Changes in systemic metabolome by inulin fibre diet.

a, Chemical structures of major differentially abundant compounds identified in this study. b, Faecal concentration of SCFAs in mice from control and inulin fibre diet groups (n = 5 mice). c, Integration of serum bile acids shown in Fig. 1d (n = 6 mice for control or 7 mice for inulin fibre). Data in b,c are representative of at least two independent experiments. Data are means ± s.e.m. Statistics were calculated by two-way ANOVA with Šidák’s multiple-comparisons test (b) or unpaired two-tailed t-test (c).

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Extended Data Fig. 3 MS analyses of various samples.

a, Table depicting detection level and other parameters for the metabolites analysed. b–c, Coinjection plots (b) or MS/MS spectra (c) for the metabolites analysed. d–g, Relative abundance of conjugated bile acids in serum (n = 8 mice for control or 9 mice for inulin fibre) (d), faecal unconjugated (e) and conjugated bile acids (f) (n = 9 mice for control or 12 mice for inulin fibre), and conjugated and unconjugated bile acids in caecal content (n = 3 mice) (g). Data are representative of (g) or combined (d–f) from two independent experiments. Data are means ± sem. Statistics were calculated by unpaired two-tailed t-test (d–g).

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Extended Data Fig. 4 Gating strategies shown using samples from colon.

a, Gating strategy for eosinophils in bar graphs including Fig. 1e and Tregs in Extended Data Figs. 5a and 7a. CD45+CD11b+SiglecF+ cells were further verified as SSChiCD11c−. b–c, Gating strategies for neutrophils (b) and various other immune cells (c) in Extended Data Fig. 5b.

Extended Data Fig. 5 Effects of inulin fibre diet on immune cells in various tissues.

a,b, Mice were fed control or inulin fibre diet for two weeks (n = 4 mice). Bar graph shows frequencies of FoxP3+ Treg cells (a) and various immunocytes (b) in the colonic lamina propria of control or inulin fibre diet-fed mice. c, Frequency of colonic eosinophils in mice fed control or inulin fibre diet for the indicated periods of time (n = 3 mice for 0.5-, 1-, or 12-week timepoints, n = 5 mice for 2-week timepoint, and n = 4 mice for 6-week timepoint). d, Percentage of eosinophils in various tissue sites from mice administered control or inulin fibre diet for two weeks. mesLN, mesenteric lymph nodes; SI, small intestine. n = 4 for bone marrow, blood, spleen, mesLN, caecum, SI control or skin inulin fibre, n = 3 for SI inulin fibre or skin control. e,f, Mice were fed chow, control diet, or various high fibre diets, and serum levels of CA (e) were measured after two weeks (n = 3 mice for chow, control, or cellulose fibre, and n = 4 mice for inulin or psyllium fibre). Frequency of eosinophils in the colon and lung (f) of mice fed the indicated diets for two weeks (n = 7 mice (colon) or 4 mice (lung) for chow, n = 6 mice for control or inulin fibre, n = 3 mice for cellulose fibre, and n = 7 mice (colon) or 3 mice (lung) for psyllium fibre). Data are representative of (a–d) or combined (e,f) from two independent experiments. Data are means ± s.e.m. Statistics were calculated by unpaired two-tailed t-test (a), two-way ANOVA with Šidák’s (b,d) or Holm–Šidák’s (c) multiple-comparisons test, or one-way ANOVA with Šidák’s multiple-comparisons test (e,f).

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Extended Data Fig. 6 Inulin fibre diet-induced gene and protein expression in various immune and non-immune cells.

a, Mice were fed control or inulin fibre diet for two weeks and ILC2s (CD45+Lin−CD90.2+CD127+KLRG1+) were sorted from colonic lamina propria cells. Heatmap showing level of significance of GO enrichment tests in the colonic ILC2 RNASeq data, as measured by -log10(Pcorrected). Blue, not significant (Pcorrected > 0.01), Red, significant (Pcorrected < 0.01). b,c Gating strategy for bar graphs for IL-5+ cells (including Fig. 2c) (b) and frequency of IL-5-expressing CD4+ T cells (c) in the colonic lamina propria of mice (n = 4 mice). d, Gating strategy for detecting PDGFRα+Sca-1+ (double positive, DP) mesenchymal stromal cells (for bar graphs including Fig. 2f) and double negative (DN) stromal cells in colon and lung tissues. e,f Flow cytometry plots and bar graphs showing IL-33-eGFP expression in epithelial and stromal cell subsets in the colon (e) and lung (f). n = 2 mice (No eGFP) or 3 mice (colon control or inulin fibre) or 4 mice (lung control or inulin fibre). Data in c,e,f, are representative of two independent experiments. Data are means ± s.e.m. Statistics were calculated by unpaired two-tailed t-test (c, f) or one-way ANOVA with Holm–Šidák’s multiple-comparisons test (e).

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Extended Data Fig. 7 Effects of bile acid metabolites on immune and non-immune cells.

a, Frequency of RORγt+ subset of Tregs in the colons of mice administered SCFAs in drinking water, or water alone (control) (n = 4 mice). b, Serum levels of CA in mice provided with regular or CA-supplemented drinking water (control n = 6 mice, CA n = 4 mice). c, Frequency of eosinophils in the lungs of indicated groups (control n = 4 mice, inulin fibre n = 2 mice, CA n = 4 mice). d, Serum levels of CDCA in mice administered 6 mM CDCA in drinking water for two weeks (control n = 6 mice, CDCA n = 3 mice). e, Percentage of IL-5+ ILC2s in single cells from the colons of naïve WT mice in vitro stimulation with or without 50 μM CA (n = 4 mice). f, Gating strategy for detection of human ILCs (for bar graphs including Fig. 3f). g, Top, STRING network visualization of the genes upregulated by the inulin fibre diet (FDR < 10%) in the indicated layers of mouse colon determined by spatial transcriptomic analyses as shown in Fig. 3h. Lines represent protein–protein associations. Connected clusters of less than 3 nodes (genes), as well as all disconnected nodes were excluded. Bottom, a table shows selected significantly enriched KEGG pathways for the genes shown in the STRING network. h, Il33 expression in WT or Nr1h4−/− mice fed control or inulin fibre diet for two weeks (n = 4 mice for WT inulin fibre group and 3 mice for other groups). i, Frequency of eosinophils in the colons and lungs of WT and Nr1h4−/− mice on control or inulin fibre diet (n = 3 mice). j, Il33 levels determined by qRT-PCR in sorted stromal cells cultured for 7 days followed by stimulation for 24 h with media control or 50 μM CA with or without 10 μM DY268 (n = 5 mice). k, Number of IL-5-expressing ILC2s in the colon of bone marrow chimeric mice on indicated diets (For WT→WT, n = 3 mice for control or 4 mice for inulin fibre, For WT→Nr1h4−/−(KO) or KO→WT, n = 4 mice). Data in a–e, h–k are representative of two independent experiments. Data are means ± s.e.m. Statistics were calculated by Mann–Whitney U-test (a), unpaired (b,d) or paired (e, j) two-tailed t-test or one-way (c) or two-way (h,i,k) ANOVA with Fisher’s LSD test.

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Extended Data Fig. 8 Metabolic and immunological parameters in gnotobiotic mice on inulin fibre diet.

a, Schematic diagram for the FMT experiment with human microbiota. b, Taxonomic classification of 16S rRNA genes in faecal suspension from individual human donors or stool pellets collected from representative recipient mice with corresponding human microbiota on control or inulin fibre diet (n = 4 human donors or recipient mice). c–d, Serum CA (c) and tissue eosinophil (d) levels in the diet-fed recipient mice. Each dot represents one animal, and each colour represents one donor. For serum CA levels, n = 15 control mice or 17 inulin fibre mice. For tissue eosinophil levels, n = 14 control mice or 16 inulin fibre mice. e–h, Representative metabolic and immunological parameters of mice colonized with faecal content from one donor two weeks post initiation of the indicated diets (n = 4 mice for control or 5 mice for inulin fibre). Levels of various unconjugated and conjugated bile acid were measured in serum (e) and faeces (f). Il33 expression was measured in the colon (g) and IL-5+ ILC2s in colon and lung (h) two weeks post initiation of the indicated diets. i–j, Single colonies of WT or Δbsh B. ovatus (Bo) strains were cultured in Mega medium with 100 µM taurocholic acid (TCA) for 72 h and then TCA (i) and CA (j) in 100 μl culture supernatants were quantified, n = 3 independent bacterial colonies. k–q, GF mice were monocolonized with WT or Δbsh Bo and fed control or inulin fibre diet. CA and TCA were measured. For serum, n = 10 mice (WT Bo control or Δbsh Bo inulin fibre) or n = 11 mice (WT Bo inulin fibre or Δbsh Bo control). For faeces, n = 6 mice (WT Bo) or n = 8 mice (Δbsh Bo control) or n = 7 mice (Δbsh Bo inulin fibre), and for caecal content, n = 3 mice (WT Bo) or 4 mice (Δbsh Bo) (k–m). Il33 expression in the colon (n), IL-5+ ILC2s in the lung (o), and faecal CFUs (p) were measured (n = 3 mice for WT Bo, n = 4 mice for Δbsh Bo control, n = 3 mice for Δbsh Bo inulin fibre). Expression levels of bsh gene BO_02350 in faecal samples were also quantified (n = 3 mice) (q). Data are representative of (b–j,m–q) or combined (c,d,k,l) from 2-4 independent experiments. Data are means ± s.e.m. Statistics were calculated by unpaired two-tailed t-test (c–j) or two-way ANOVA with Fisher’s LSD test (k–q). The diagram in a was created using BioRender.

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Extended Data Fig. 9 The effects of inulin fibre diet in mice challenged with HDM.

a, Schematic diagram for HDM model of allergic airway inflammation. b–d, Frequency of eosinophils in lung (b) and BALF (c) in naïve (saline) or HDM-challenged mice fed the control or inulin fibre diet (saline n = 2 mice, HDM control diet n = 3 mice for lung or 4 mice for BALF, HDM inulin fibre n = 4 mice). d, Airway hyperresponsiveness in HDM-challenged mice measured as resistance of the respiratory system (Rrs) to increasing doses of methacholine (n = 6 mice). Data are representative of (b–c) or combined (d) from 2 independent experiments. Data are means ± s.e.m. Statistics were calculated by unpaired two-tailed t-test (b–c) or two-way ANOVA with Fisher’s LSD test (d). e,Proposed model. The diagrams in a and e were created using BioRender.

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Extended Data Table 1 Composition of diets used in this study
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Supplementary information

Supplementary Information

Supplementary Figs. 1 and 2 and Supplementary Tables 1 and 2.

Reporting Summary

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Arifuzzaman, M., Won, T.H., Li, TT. et al. Inulin fibre promotes microbiota-derived bile acids and type 2 inflammation. Nature (2022). https://ift.tt/COW2U6t

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