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Randomized Controlled Trial
. 2016 Jun;65(6):954-62.
doi: 10.1136/gutjnl-2015-309184. Epub 2015 Dec 1.

Structural robustness of the gut mucosal microbiota is associated with Crohn's disease remission after surgery

Affiliations
Randomized Controlled Trial

Structural robustness of the gut mucosal microbiota is associated with Crohn's disease remission after surgery

S Mondot et al. Gut. 2016 Jun.

Abstract

Objectives: Preventing postoperative recurrence after ileocolonic resection (ICR) for Crohn's disease (CD) is challenging. Defining the disturbances of the microbial composition and community structure after ICR and their link with early disease recurrence is crucial.

Design: Microbiota composition (fingerprinting and 16S rDNA sequencing) and community structure (correlation networks of bacterial species) were assessed from ileal mucosa sampled in 20 patients undergoing ICR and 6 months later during endoscopy from above (neoterminal ileum) and below (subanastomotic colon) the surgical anastomosis.

Results: ICR had a dramatic effect on gut microbial ecosystem. At surgery, CD mucosa harboured a dysbiotic microbiota with high proportions of α/β Proteobacteria and Bacilli. Six months later, half of the patients had recurrent lesions at ileocolonoscopy and presented higher numbers of Lachnospiraceae. Recurrence of endoscopic lesions was associated with enrichment in Enterococcus durans while patients in remission had increased proportions of Dorea longicatena and Bacteroides plebeius. Structural differences were striking between recurrence and remission microbiota; while the microbiota of patients with CD recurrence exhibited a loose community structure, the microbiota of patients in remission displayed communities that were robustly correlated to each other. Microbiota colonising the neoterminal ileum and subanastomotic colon 6 months after ICR only differed in patients with recurrence.

Conclusions: ICR modifies the gut microbiome. Remission after 6 months was associated with homogenous bacterial distribution around the anastomosis. Community structure and bacterial networks highlight target species, including Faecalibacterium prausnitzii and Ruminococcus gnavus, which may allow precise modulations of the overall microbial ecosystem towards remission pattern.

Keywords: BACTERIAL INTERACTIONS; INFLAMMATORY BOWEL DISEASE; INTESTINAL MICROBIOLOGY; MOLECULAR BIOLOGY; SURGICAL RESECTION.

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Figures

Figure 1
Figure 1
Impact of ileocolonic resection on mucosal microbiota: initial stage compared with 6 months later. Between class analysis (axis 1 and 2) visualising results from the principal component analysis based on the operational taxonomic unit composition in the microbiota of patients before and after surgery (M0 vs M6). Samples were clustered according to remission/recurrence (REM/REC) and sampling times (M0 and M6). Robustness of the clustering result was assessed using a Monte Carlo ranking test. Samples at M0 (REM-0/REC-0) are in blue. Samples at 6 months for patients in remission (REM-6) are in green. Samples at 6 months for patients in recurrence (REC-6) are in red. At M6: sus, neoterminal ileum; sub, subanastomotic colon.
Figure 2
Figure 2
Early bacterial biomarkers of the clinical outcome after ileocolonic resection (ICR). Faecal microbiota from 10 patients was analysed at M0 and 6 months after ICR. (A) Specific bacterial operational taxonomic units (OTUs) that may predict at M0 the clinical outcome following ICR were deciphered applying the LEfSe algorithm. The LEfSe algorithm uses the non-parametric factorial Kruskal–Wallis sum-rank test to detect features with significant differential abundance with respect to the clinical outcome; biological significance is subsequently investigated using a set of pairwise tests using the (unpaired) Wilcoxon rank-sum test. As a last step, LEfSe uses linear discriminant analysis to estimate the effect size of each differentially abundant feature (ie, bacterial OTUs). (B) Boxplot of the distribution (per cent of total reads) of the four OTUs highlighted in the LEfSe analyses in the different patients’ groups. M0 bacterial biomarkers associated with remission at M6 are in green. M0 bacterial biomarkers of future recurrence in patients undergoing ICR are in red. M0, samples at time of surgery; REC, recurrence; REM, remission; LDA, linear discriminant analysis.
Figure 3
Figure 3
Correlation network organisation inferred from the microbiota composition of patients with Crohn's disease in remission and in recurrence 6 months after ileocolonic resection (ICR). (A) and (B) respectively depict the correlation network structures inferred from the microbiota composition of patients in remission or with recurrence 6 months after ICR. Each number relates to operational taxonomic unit (OTU) indexes. OTU phylogeny at phylum level is described by colours filling each OTU dot. Correlation scores are indicated by the colour of the edges linking OTU pairs. Polygons delineate each cluster (C1–C5) identified in the network. (A and B) The red, yellow, green, blue and purple polygons delineate clusters I, II, III, IV and V.
Figure 4
Figure 4
Microbiota recolonisation after ileocolonic resection. Between class analysis (axis 1 and 2) visualising results from the principal component analysis based on the operational taxonomic unit composition in the microbiota of patients 6 months after surgery. Samples were clustered according to remission/recurrence (REM/REC) and location around the anastomosis (sus/sub). Samples of patients in remission are in green (REM-sus and REM-sub). Samples of patients with endoscopic recurrence are in red (REC-sus and REC-sub). sus, neoterminal ileum; sub, subanastomotic colon.

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