Spatial variation of the colonic microbiota in patients with ulcerative colitis and control volunteers

Abstract

Objectives: The relevance of spatial composition in the microbial changes associated with UC is unclear. We coupled luminal brush samples, mucosal biopsies and laser capture microdissection with deep sequencing of the gut microbiota to develop an integrated spatial assessment of the microbial community in controls and UC.

Design: A total of 98 samples were sequenced to a mean depth of 31,642 reads from nine individuals, four control volunteers undergoing routine colonoscopy and five patients undergoing surgical colectomy for medically-refractory UC. Samples were retrieved at four colorectal locations, incorporating the luminal microbiota, mucus gel layer and whole mucosal biopsies.

Results: Interpersonal variability accounted for approximately half of the total variance. Surprisingly, within individuals, asymmetric Eigenvector map analysis demonstrated differentiation between the luminal and mucus gel microbiota, in both controls and UC, with no differentiation between colorectal regions. At a taxonomic level, differentiation was evident between both cohorts, as well as between the luminal and mucosal compartments, with a small group of taxa uniquely discriminating the luminal and mucosal microbiota in colitis. There was no correlation between regional inflammation and a breakdown in this spatial differentiation or bacterial diversity.

Conclusions: Our study demonstrates a conserved spatial structure to the colonic microbiota, differentiating the luminal and mucosal communities, within the context of marked interpersonal variability. While elements of this structure overlap between UC and control volunteers, there are differences between the two groups, both in terms of the overall taxonomic composition and how spatial structure is ascribable to distinct taxa.

Keywords: COLONIC BACTERIA; INFLAMMATORY BOWEL DISEASE; INTESTINAL MICROBIOLOGY; ULCERATIVE COLITIS.

Figure 1

Schematic diagram of potential spatial gradients: (A) cross-sectional gradients and (B) longitudinal gradients. (C) Sampling occurred at four colorectal levels (caecum, transverse colon, descending colon and rectum). Three sampling layers were retrieved at each level (luminal, whole mucosal biopsy and mucus gel layer by laser capture microdissection). (D) A diagram of the cross-sectional organisation of samples with representative pictures from each sampling method.

Figure 2

Constrained ordination by canonical analysis of principal coordinates (CAP) using unweighted UniFrac distance of all samples in the cohort (A) demonstrating that interpersonal variability explains the largest proportion of the variance. (B) Percentage of CAP variance described by the constraining variables interpersonal, cross-sectional (luminal vs mucosal), colonic region (caecum, transverse colon, descending colon and rectum) and inflammation.

Figure 3

Modelling of intrapersonal variability by asymmetric Eigenvector maps analysis in the four control volunteers (A) and four out of five patients with UC (C). Values are centred at 0 with white corresponding to negative, black corresponding to positive and the radius of the circle corresponding to the magnitude of the value. The differences in the fitted redundancy analysis values for all luminal and mucus gel samples within an individual compared with brush versus mucus gel samples at matched locations within individuals, in controls (B) and UC (D), demonstrating that luminal samples are more similar to other luminal samples within individuals and mucus gel samples are more similar to mucus gel samples within individuals than luminal and mucus gel samples at each colorectal location. Significance values: *<0.05, ***<0.001.

Figure 4

(A) Results from the Random Forests classifier, demonstrating bacterial families that are most discriminatory between the two cohorts in descending order. Samples are coloured by whether they are significantly increased in controls (blue), UC (red) or not (grey) using the Wilcoxon rank test with a Bonferroni correction for multiple comparisons. (B) Boxplots of the relative abundances of the nine bacterial families that were both discriminatory (with a mean decrease in accuracy of the classifier of greater than 0.01 when removed from the analysis) and significantly different in terms of abundance by the Wilcoxon rank test after a Bonferroni correction.

Figure 5

Luminal versus mucus gel samples in controls and UC. A between-class analysis (BCA) based on a principal component analysis of Hellinger-transformed family-level taxon abundance, comparing the luminal, mucosal and mucus gel microbiota of controls and UC (A). Bacterial families that were discriminatory between the lumen and mucus gel in controls (B) and UC (C) based on the Random Forests classifier and abundance using the Wilcoxon rank test. Lachnospiraceae and Planctomycetaceae were unique to controls, while Porphyromonadaceae, Bifidobacteriaceae, Veillonellaceae, Peptostreptococcaceae and Enterobacteriaceae were unique to UC.