Metabolic alterations to the mucosal microbiota in inflammatory bowel disease

Abstract

Background: Inflammation during inflammatory bowel disease may alter nutrient availability to adherent mucosal bacteria and impact their metabolic function. Microbial metabolites may regulate intestinal CD4 T-cell homeostasis. We investigated the relationship between inflammation and microbial function by inferred metagenomics of the mucosal microbiota from colonic pinch biopsies of patients with inflammatory bowel disease.

Methods: Paired pinch biopsy samples of known inflammation states were analyzed from ulcerative colitis (UC) (23), Crohn's disease (CD) (21), and control (24) subjects by 16S ribosomal sequencing, histopathologic assessment, and flow cytometry. PICRUSt was used to generate metagenomic data and derive relative Kyoto Encyclopedia of Genes and Genomes Pathway abundance information. Leukocytes were isolated from paired biopsy samples and analyzed by multicolor flow cytometry. Active inflammation was defined by neutrophil infiltration into the epithelium.

Results: Carriage of metabolic pathways in the mucosal microbiota was relatively stable among patients with inflammatory bowel disease, despite large variations in individual bacterial community structures. However, microbial function was significantly altered in inflamed tissue of UC patients, with a reduction in carbohydrate and nucleotide metabolism in favor of increased lipid and amino acid metabolism. These differences were not observed in samples from CD patients. In CD, microbial lipid, carbohydrate, and amino acid metabolism tightly correlated with the frequency of CD4Foxp3 Tregs, whereas in UC, these pathways correlated with the frequency of CD4IL-22 (TH22) cells.

Conclusions: Metabolic pathways of the mucosal microbiota in CD do not vary as much as UC with inflammation state, indicating a more systemic perturbation of host-bacteria interactions in CD compared with more localized dysfunction in UC.

Figures

Figure 1. Taxonomic and functional diversity of the mucosal microbiota in IBD and healthy patients

(A) Pie charts representing the mean relative abundances of the major (>1%) phyla present in the mucosal microbiota from healthy, UC and CD patients. (B) Scatterplot showing significantly higher relative abundance of the Bacteroidetes phyla in biopsies from CD patients (p

Figure 2. Functional divergence between the mucosal microbiota of inflamed and non-inflamed samples from UC patients

(A) Unsupervised hierarchical clustering analysis of abundance values for KEGG pathways shows distinctive clustering of inflamed (red) and non-inflamed (green) samples. Each column is a separate sample and row is a particular pathway. Blue = less than the mean, Yellow = greater than mean. (B) Principal Component Analysis of KEGG pathways confirms the segregation of inflamed and non-inflamed samples along PC1 and PC2. (C) Supervised comparison identifies differential abundance of specific KEGG pathways using LEfSe (LDA > 3.0). (D) Genes in carbohydrate and nucleotide metabolism pathways are more abundant in non-inflamed normal tissue from UC patients, with a shift towards more abundance in lipid and amino acid metabolism genes for the mucosal microbiota of inflamed tissues. ***P

Figure 3. Limited differences between the mucosal microbiota of inflamed and non-inflamed samples from CD patients

(A) Hierarchical clustering analysis of samples from CD patients shows limited segregation of inflamed (red) and non-inflamed (green) samples. (B) Principal Component Analysis shows limited segregation of inflamed and non-inflamed samples. (C) Supervised comparison identifies only two differentially abundant KEGG pathways using LEfSe (LDA > 2.0). (D) Genes involved in amino acid, lipid and nucleotide metabolism pathways are not significantly different between inflamed and normal tissue of CD patients, but there is a significant increase in the energy metabolism pathway. *P

Figure 4. KEGG metabolic pathways are significantly different in the mucosal microbiota of inflamed tissue from UC and CD patients

(A) UC and CD patient samples with active inflammation cluster distinctly into separate arms. Some samples from healthy patients cluster with UC samples, whereas other healthy samples cluster with CD samples. (B) Principal Component Analysis confirms the segregation of CD and UC inflamed samples, although there is no clear separation from healthy subjects. (C) LEfSe analysis (LDA > 3.0) shows that amino acid and lipid metabolism was more abundant in the mucosal microbiota of inflamed UC samples, whereas carbohydrate, energy and nucleotide metabolism pathways was more abundant in inflamed CD samples.

Figure 5. Correlation of microbial function with the homeostasis of CD4+ effector cells

(A) Representative gating strategy for the FACS analysis of lamina propria mononuclear cells (LPMCs), showing live CD3+ CD4+ lymphocytes with intracellular staining for interleukin (IL)- IL-22 production and Foxp3 expression. (B) Frequency of CD4+Foxp3+Tregs from LPMCs of CD patients in Inflamed (red) and Non-Inflamed (blue) biopsy sites. (C) Linear regression of KEGG pathways (lipid, carbohydrate and amino acid metabolism) with the percentage of CD4+Foxp3+ present in the same biopsy location taken from CD patients. (D) Frequency of CD4+IL-22+ cells of UC patients in Inflamed (red) and Non-Inflamed (blue) biopsy sites. (E) Linear regression of KEGG pathways with the percentage of CD4+IL-22+ cells present in the same biopsy location taken from UC patients.