Computational modeling of the gut microbiota reveals putative metabolic mechanisms of recurrent Clostridioides difficile infection.

ABSTRACT: Approximately 30% of patients who have Clostridioides difficile infection (CDI) will suffer at least one incident of reinfection. While the underlying causes of CDI recurrence are poorly understood, interactions between C. difficile and commensal gut bacteria are thought to play an important role. In this study, an in silico pipeline was used to process 16S rRNA gene amplicon sequence data of 225 stool samples from 93 CDI patients into sample-specific models of bacterial community metabolism. Clustered metabolite production rates generated from post-diagnosis samples generated a high Enterobacteriaceae abundance cluster containing disproportionately large numbers of recurrent samples and patients. This cluster was predicted to have significantly reduced capabilities for secondary bile acid

SUBMITTER: Henson MA 

PROVIDER: S-EPMC7932513 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature