Dysbiosis and relapse-related microbiome in inflammatory bowel disease: A shotgun metagenomic approach
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Updated: Oct 9, 2025

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing
Published on: October 15, 2019
Gerard Serrano-Gómez1, Luis Mayorga1, Iñigo Oyarzun1
1Gut Microbiome Lab, Vall d'Hebron Institut de Recerca (VHIR), Vall d'Hebron Hospital Universitari, Vall d'Hebron Barcelona Hospital Campus, Passeig Vall d'Hebron 119-129, 08035 Barcelona, Spain.
Abstract:
Crohn's disease (CD) and ulcerative colitis (UC), the two main forms of inflammatory bowel disease (IBD), affect several million people worldwide. CD and UC are characterized by periods of clinical remission and relapse. Although IBD patients present chronic alterations of the gut microbiome, called dysbiosis, little attention has been devoted to the relapse-related microbiome. To address this gap, we generated shotgun metagenomic data from the stools of two European cohorts-134 Spanish (followed up for one year) and 49 Belgian (followed up for 6 months) subjects-to characterize the microbial taxonomic and metabolic profiles present. To assess the predictive value of microbiome data, we added the taxonomic profiles generated from a previous study of 130 Americans. Our results revealed that CD was more dysbiotic than UC compared to healthy controls (HC) and that strategies for energy extraction and propionate production were different in CD compared to UC and HC. Remarkably, CD and UC relapses were not associated with alpha- or beta-diversity, or with a dysbiotic score. However, CD relapse was linked to alterations at the species and metabolic pathway levels, including those involved in propionate production. The random forest method using taxonomic profiles allowed the prediction of CD vs. non-CD with an AUC = 0.938, UC vs. HC with an AUC = 0.646, and CD relapse vs. remission with an AUC = 0.769. Our study validates previous taxonomic findings, points to different relapse-related growth and defence mechanisms in CD compared to UC and HC and provides biomarkers to discriminate IBD subtypes and predict disease activity.
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