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Microbiota-derived metabolite promotes HDAC3 activity in the gut

Abstract

The coevolution of mammalian hosts and their beneficial commensal microbes has led to development of symbiotic host–microbiota relationships1. Epigenetic machinery permits mammalian cells to integrate environmental signals2; however, how these pathways are fine-tuned by diverse cues from commensal bacteria is not well understood. Here we reveal a highly selective pathway through which microbiota-derived inositol phosphate regulates histone deacetylase 3 (HDAC3) activity in the intestine. Despite the abundant presence of HDAC inhibitors such as butyrate in the intestine, we found that HDAC3 activity was sharply increased in intestinal epithelial cells of microbiota-replete mice compared with germ-free mice. This divergence was reconciled by the finding that commensal bacteria, including Escherichia coli, stimulated HDAC activity through metabolism of phytate and production of inositol-1,4,5-trisphosphate (InsP3). Both intestinal exposure to InsP3 and phytate ingestion promoted recovery following intestinal damage. Of note, InsP3 also induced growth of intestinal organoids derived from human tissue, stimulated HDAC3-dependent proliferation and countered butyrate inhibition of colonic growth. Collectively, these results show that InsP3 is a microbiota-derived metabolite that activates a mammalian histone deacetylase to promote epithelial repair. Thus, HDAC3 represents a convergent epigenetic sensor of distinct metabolites that calibrates host responses to diverse microbial signals.

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Fig. 1: Microbiota calibrate epithelial HDAC3 activity by regulating inositol phosphate.
Fig. 2: Phytate metabolism by commensal bacteria induces HDAC activity in IECs.
Fig. 3: Microbiota-dependent breakdown of phytate improves recovery from intestinal damage.
Fig. 4: Inositol phosphate promotes HDAC3-dependent colonic growth.

Data availability

Global datasets are available in the Gene Expression Omnibus repository under accession numbers GSE50190 and GSE148743. Raw uncropped gel scans with size markers indicated can be found in Supplementary Information. Source data are provided with this paper.

Code availability

Description of scripts used to analyse metagenomic data are provided in the Methods and the scripts are available upon request.

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Acknowledgements

We thank the Way, Qualls and Deshmukh laboratories for useful discussions; CCHMC Veterinary Services, Pathology Research Core, Research Flow Cytometry Core, NMR-based Metabolomics Core, and Confocal Imaging Core for services and technical assistance. This research is supported by the National Institutes of Health (DK114123 and DK116868 to T.A.; DK098231 to L.A.D.; and F32AI147591 to. E.M.E.), Pew Charitable Trust, and a Kenneth Rainin Foundation award to T.A. T.A. holds an Investigator in the Pathogenesis of Infectious Disease Award from the Burroughs Wellcome Fund. This project is supported in part by NIH P30 DK078392 and the CCHMC Trustee Award and Procter Scholar’s Program.

Author information

Authors and Affiliations

Authors

Contributions

S.-e.W., S.H.-H., V.W., E.M.E., J.W. and T.A. designed the studies and analysed the data. S.-e.W. conducted HDAC assays, immunoprecipitations, western blotting, bacterial cultures and colonoid studies. S.H.-H. and V.W. performed ChIP experiments, S.H.-H. conducted qPCR, E.M.E. performed flow cytometry and ELISA analyses, J.W. and S.-e.W. conducted DSS studies, J.W. and L.E. maintained gnotobiotic mice, V.W. analysed recombinant proteins. V.W. and R.K. performed bioinformatic analyses, D.B.H. performed microbiome analyses, and L.A.D. provided patient samples and clinical expertise. T.A., S.H.-H. and S.-e.W. wrote the manuscript. All authors edited the manuscript.

Corresponding author

Correspondence to Theresa Alenghat.

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The authors declare no competing interests.

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Peer review information Nature thanks Matthew Hirschey, Philip Rosenstiel and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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 Butyrate inhibits epithelial HDAC activity in the intestine.

a, IEC HDAC activity of large intestine explant treated with vehicle (n = 3), 10 mM butyrate (n = 3), or 10 mM trichostatin A (TSA; n = 3) for 3 h. ***P = 4.16 × 10–7 (Vehicle vs TSA), ***P = 0.0006 (Vehicle vs Butyrate), **P = 0.0015 (Butyrate vs TSA). b, IEC HDAC activity of GF mice (n = 7) and mice mono-associated with F. prausnitzii (butyrate-producing bacteria) (n = 7). *P = 0.028. c, Bacterial-specific qPCR of faeces for F. prausnitzii, Enterobacteriaceae, and Bacteroides (n = 3/group). d, Western blot of immunoprecipitated HDAC3 from IECs. For gel source data, see Supplementary Fig. 1. e, HDAC activity of immunoprecipitated (IP) HDAC3 from HDAC3FF (n = 3) and HDAC3ΔIEC (n = 3) intestinal epithelium. **P = 0.001. f, HDAC activity of IECs from GF (n = 4), CNV (Vehicle n = 9, TSA n = 6), and HDAC3∆IEC mice (n = 6) −/+ 10 μM TSA. ***P = 5.77 × 10–5 (GF Vehicle vs TSA), ***P = 1.12 × 10–7 (CNV Vehicle vs TSA), ***P = 3.49 × 10–5 (HDAC3∆IEC Vehicle vs TSA), **P = 0.008 (Vehicle GF vs CNV), **P = 0.004 (Vehicle CNV vs HDAC3∆IEC). All graphs are mean of biological replicates ± s.e.m.; unpaired two-tailed t test. Data were independently repeated three (ac) or two (df) times with similar results. *P ≤ 0.05, **P ≤ 0.01, ***P ≤ 0.001.

Source data

Extended Data Fig. 2 HDAC activity and expression in IECs lack sensitivity to multiple bacterial stimuli.

a, HDAC activity of mouse colonoid lysate treated with 1 μg/ml vehicle, butyrate, flagellin, LPS, or Pam3csk4. n = 6/treatment. **P = 0.0008. be, Western blot (b) and qPCR (ce) analyses of HDAC1, HDAC2, and HDAC3 in colonoids following treatment with vehicle (n = 9), butyrate (n = 6), flagellin (n = 6), LPS (n = 6), or Pam3csk4 (n = 6); all at 1 μg/ml for 5 h. For gel source data, see Supplementary Fig. 1. f, g, HDAC activity in IECs harvested from floxed TLR4FF and IEC-specific toll-like receptor 4 knockout (TLR4ΔIEC) mice (f) (n = 3/genotype) or wildtype and Myd88 knockout (Myd88−/−) mice (g) (n = 4/genotype). All graphs are mean of biological replicates ± s.e.m.; unpaired two-tailed t test. Data were independently repeated four (a) or two (bg) times with similar results. **P ≤ 0.01.

Source data

Extended Data Fig. 3 Inositol phosphate-sensitive pathways are upregulated in microbiota-replete mice and InsP3 induces enhanced HDAC3 activity.

a, Principal component analysis of gene expression of inositol phosphate-sensitive pathways in IECs from GF (n = 3) and CNV (n = 3) mice. **P = 0.0046. b, Pathway analysis showing upregulated signalling pathways in IECs from a. c, Gene set enrichment analysis (GSEA) comparing IECs from a to published data enrichment sets obtained from KEGG. *P = 0.05. d, Basal activity (fluorescence units) of 10 nM recombinant HDAC1, HDAC2, and HDAC3/NCoR-deacetylase activation domain (n = 3/group). ***P = 2.19 × 10−5 (vs HDAC1), ***P = 5.48 × 10−7 (vs HDAC2). e, HDAC activity normalized to recombinant basal levels following incubation with vehicle or 1 μM InsP3 (IP3). n = 5/treatment. ***P = 6.61 × 10–5. f, HDAC activity of immunoprecipitated HDAC3 from primary IECs incubated with increasing InsP3 doses. n = 4 (Vehicle, 10 nM, 100 nM), n = 3 (1 μM, 10 μM), *P = 0.040, **P = 0.003. Data in all graphs are mean ± s.e.m.; unpaired two-tailed t test. Data in df were independently repeated three times with similar results. *P ≤ 0.05, **P ≤ 0.01, ***P ≤ 0.001.

Source data

Extended Data Fig. 4 Inositol phosphate induces HDAC enzymatic activity without altering expression in IECs.

a, HDAC activity in mouse colonoids following incubation with increasing doses of InsP3 (IP3) for 5 h (Vehicle: n = 8; 100 nM InsP3: n = 5, *P = 0.0062; 100 μM InsP3: n = 6, *P = 0.0147). b, mRNA expression of Hdac1, Hdac2 and Hdac3 in mouse colonoids following incubation with InsP3 for 5 h at indicated dose (Vehicle: n = 5; InsP3: n = 6/dose). c, Western blot of HDAC1, HDAC2 and HDAC3 in colonoids from a. For gel source data, see Supplementary Fig. 1. All graphs are mean of biological replicates ± s.e.m.; unpaired two-tailed t test. Data were independently repeated three times with similar results. *P ≤ 0.05, **P ≤ 0.01.

Source data

Extended Data Fig. 5 Phytate digestion promotes HDAC activity in IECs.

a, Number of peaks identified by ChIP–sequencing with significantly increased or decreased H3K9Ac enrichment in IECs, relative to IECs harvested from GF mice. n = 2/group; Min to max plots for each comparison (4 per bar); line at median. b, ChIP-seq for H3K9Ac at HDAC3 target genes in primary IECs isolated from GF and E. coli mono-associated mice. Peaks are normalized to reads per million mapped reads. c, InsP3 (IP3) levels in 1010 colony forming units (CFU)/ml cultures of phytaseΔ E. coli (n = 4) versus wildtype E. coli (n = 4) *P = 0.0314. d, HDAC activity of mouse colonoids treated with PBS (n = 8) or phytase-digested phytate (1 mg/ml) (n = 9) for 5 h.**P = 0.0016. e, western blot detection of HDACs in mouse colonoid lysate. For gel source data, see Supplementary Fig. 1. f, HDAC activity with inositol-1,4,5,6-tetrakisphosphate (IP4) doses as indicated. n = 3/group. **P = 0.0052 (1 μM), **P = 0.0018 (100 μM). g, Relative intracellular InsP3 levels of colonoids treated with phytase-digested phytate (1 mg/ml) -/+ 40 μM carbenoxolone. n = 3/treatment. *P = 0.0189. h, CFU measured in stool collected from mice mono-associated with E. coli or phytaseΔ E. coli. n = 3/group. i, Bacterial-specific qPCR of faeces for Enterobacteriaceae, Bacteroides, and Firmicutes. n = 3/group. j, PCR of E. coli phytase gene (appA) in stool from mono-associated mice in (h, i). All graphs, except a, are mean of biological replicates ± s.e.m.; unpaired two-tailed t test. Data were independently repeated two (e, f) or three (c, d, gj) times with similar results. *P ≤ 0.05, **P ≤ 0.01.

Source data

Extended Data Fig. 6 Microbiota-dependent breakdown of dietary phytate improves recovery from intestinal damage.

a, Percentage survival of antibiotic-treated mice exposed to 2.5% DSS while receiving vehicle (n = 8) or 10 μM InsP3 (IP3) (n = 8) via rectal enema as depicted in diagram. *P = 0.0423 Mantel-Cox test; independently repeated two times. b, Abundance of bacterial phytase (E.C.3.1.3.26) DNA sequence in last stool sample collected from non-IBD (n = 27) and ulcerative colitis (UC) (n = 38) patients in Human Microbiome Project27. *P = 0.036; unpaired two-tailed t test. *P ≤ 0.05.

Source data

Extended Data Fig. 7 Microbiota and SCFA composition are not altered in phytate-sensitive DSS protection.

a, b, Shannon diversity index (a) (n = 4/group) and comparison of bacterial communities (b) in stool collected from DSS-treated mice -/+ 2% phytate (n = 4/group). c, Nuclear magnetic resonance identification of short chain fatty acids in intestinal contents from vehicle- and 2% phytate-treated DSS mice, n = 4/group. Graphs (a, c) are mean ± s.e.m.; ns, not significant.

Source data

Extended Data Fig. 8 Phytate decreases pathology caused by intestinal epithelial damage.

a, Frequency of CD45+ intraepithelial leukocytes assessed by flow cytometry (gated on live cells). n = 4/group. *P = 0.0107. b, c, Frequency of TNFα (b) and IFNγ (c) producing CD4+ lamina propria leukocytes from vehicle- and 2% phytate-treated mice during DSS-induced colitis (gated on live, CD45+ CD4+). n = 4/group. **P = 0.0048 (b), *P = 0.0277 (c). d, Relative faecal lipocalin levels measured by ELISA in vehicle (n = 6) or phytate treated (n = 7) mice *P = 0.0484. e, Histological scoring parameters for Fig. 4d. Scores reflect severity of the DSS-induced histological parameters: inflammatory infiltration (1–5), oedema (1–5), and ulceration on a scale ranging from 1 to 5 with 5 being most severe. n = 6/group (inflammatory infiltration: *P = 0.0314; oedema: **P = 0.0075; ulceration: **P = 0.0057). Graphs are mean of biological replicates ± s.e.m.; unpaired two-tailed t test. Data were independently repeated three times with similar results. *P ≤ 0.05, **P ≤ 0.01.

Source data

Extended Data Fig. 9 Inositol trisphosphate counters butyrate-induced inhibition of colonoid growth.

a, b, Growth of colonoids generated from GF mice and treated with vehicle or InsP3 (IP3) (a) (10nM; n = 60 colonoids/treatment; *P = 0.029) or phytate vs phytase-digested phytate (b) (0.2 mg/ml; n = 40 colonoids/treatment; **P = 0.0012). c, Representative images of GF colonoids treated with vehicle or 1mM butyrate, scale bars, 100 μm. d, e, Representative images (d) (red: phalloidin, blue: DAPI), scale bars, 100 μm and growth (e) of colonoids from GF mice treated with vehicle, 5 mM butyrate, or 5 mM butyrate + 50 nM InsP3; n = 30 colonoids/treatment; *P = 0.0409, ***P = 0.0001). All graphs are mean of biological replicates ± s.e.m.; unpaired two-tailed t test. Data were independently repeated two (b) or four (a, ce) times with similar results. *P ≤ 0.05, **P ≤ 0.01, ***P ≤ 0.001.

Source data

Extended Data Fig. 10 Epithelial HDAC3 functions as an intestinal sensor of distinct microbiota-derived metabolites.

Microbiota can generate inhibitory (SCFA) and activating (InsP3) signals through metabolism of dietary fibres and phytate, respectively. Epithelial HDAC3 functions as a central hub for these opposing signals, and likely additional factors, to modulate enzymatic activity and intestinal epithelial homeostasis/repair. Therefore, HDAC3 represents an epigenetic-modifying enzyme that can calibrate intestinal dynamics in response to alterations in diet and/or microbiota.

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This file contains Supplementary Figures 1-2. Supplementary Fig. 1 contains the uncropped data for western blots, and Supplementary Fig. 2 the flow cytometry gating strategy.

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Wu, Se., Hashimoto-Hill, S., Woo, V. et al. Microbiota-derived metabolite promotes HDAC3 activity in the gut. Nature 586, 108–112 (2020). https://doi.org/10.1038/s41586-020-2604-2

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