Gut Microbiota Facilitates Dietary Heme-Induced Epithelial Hyperproliferation by Opening the Mucus Barrier in Colon

Abstract

Colorectal cancer risk is associated with diets high in red meat. Heme, the pigment of red meat, induces cytotoxicity of colonic contents and elicits epithelial damage and compensatory hyperproliferation, leading to hyperplasia. Here we explore the possible causal role of the gut microbiota in heme-induced hyperproliferation. To this end, mice were fed a purified control or heme diet (0.5 μmol/g heme) with or without broad-spectrum antibiotics for 14 d. Heme-induced hyperproliferation was shown to depend on the presence of the gut microbiota, because hyperproliferation was completely eliminated by antibiotics, although heme-induced luminal cytotoxicity was sustained in these mice. Colon mucosa transcriptomics revealed that antibiotics block heme-induced differential expression of oncogenes, tumor suppressors, and cell turnover genes, implying that antibiotic treatment prevented the heme-dependent cytotoxic micelles to reach the epithelium. Our results indicate that this occurs because antibiotics reinforce the mucus barrier by eliminating sulfide-producing bacteria and mucin-degrading bacteria (e.g., Akkermansia). Sulfide potently reduces disulfide bonds and can drive mucin denaturation and microbial access to the mucus layer. This reduction results in formation of trisulfides that can be detected in vitro and in vivo. Therefore, trisulfides can serve as a novel marker of colonic mucolysis and thus as a proxy for mucus barrier reduction. In feces, antibiotics drastically decreased trisulfides but increased mucin polymers that can be lysed by sulfide. We conclude that the gut microbiota is required for heme-induced epithelial hyperproliferation and hyperplasia because of the capacity to reduce mucus barrier function.

Keywords: (tri)sulfides; colorectal cancer; mucolysis; mucus barrier; red meat.

Fig. 1.

(A) Counts of total bacteria, Bacteroidetes, and Firmicutes measured by qPCR. Control bars are set at 100%, and other bars are relative to controls; mean ± SEM (n = 9/group). (B) Bile acid profiles determined by HPLC; mean ± SEM (n = 3/group). Letters indicate significant different groups (P < 0.05), ANOVA with Bonferroni post hoc test. Gly, glycine conjugated; Sec, secondary; Tau, taurine conjugated.

Fig. 2.

(A) Histochemical H&E staining and (B) immunohistochemical Ki67 staining of colon of control and heme-fed mice. (C) Quantification of Ki67-positive cells per crypt, total number of cells per crypt, and labeling index (percentage of proliferative cells per crypt); mean ± SEM (n = 9/group). Letters indicate significant different groups (P < 0.05), ANOVA with Bonferroni post hoc test.

Fig. S1.

(A) Venn diagram showing the numbers of heme and heme plus Abx-specific regulated genes and of overlapping genes (q < 0.01). (B) GSEA showing positive enriched processes. Sources of gene sets are indicated in superscript and represent (1) gene ontology, (2) reactome, and (3) KEGG. Size represents the number of genes in the gene-set and NES is normalized enrichment score, which is the enrichment score for the gene set after it has been normalized to account for variations in gene set size. (C) Ingenuity analysis showing activated or inhibited transcription factors (z-score > 2 and P < 0.05) in both treatments specifically and in overlapping genes.

Fig. 3.

(A) Gene expression of injury markers Birc5, Ier3, Ripk3, and Slpi. (B) immunohistochemical colonic Slpi staining of control and heme-fed mice. (C) Gene expression of mucin genes 1–4 and Galnt 3 and 12. Expression levels of control is set at 1. Expression of other bars is relative to controls; mean ± SEM (n = 4 for C, H, and CA; n = 6 for HA). Letters indicate significant differences (P < 0.05), ANOVA with Bonferroni post hoc test.

Fig. 4.

(A) Bacterial counts of A. muciniphila and SRB determined by qPCR. Controls are set at 100%, and other bars are relative to controls; mean ± SEM (n = 8–9/group). Letters indicate significant different groups (P < 0.05). (B) Rate and extent of S-S bond splitting and synthesis of trisulfide bonds; mean ± SD (n = 3–6/group). *Significant difference with thiol groups (P < 0.05). (C) Reaction scheme by which sulfide splits S-S bonds. (D) Concentrations of sulfides in fecal water; mean ± SEM (n = 8–9/group). (E) Excretion of fecal mucins, expressed as µmoles O-glycan per day (n = 6–9/group). (F) Western blot analysis of fecal mucin with or without DTT as reducing agent and with sulfide. Samples were stained with anti-Muc2 antibody. Each lane represents a pool of n = 9/group. Letters indicate significant different groups (P < 0.05), ANOVA with Bonferroni post hoc test.

Fig. 5.

Proposed mechanism of how microbiota facilitates heme-induced compensatory hyperproliferation. (Upper) Processes when normal microbiota is present (i.e., without Abx) leading to compensatory hyperproliferation. (Lower) How Abx cause the mucus layer to be protective against cytotoxic micelles. R-S-S-R indicates native intra- and intermolecular disulfide bonds in the mucus that can be reduced by H₂S to thiols (R-S-H) and trisulfides (R-S-S-S-R).