Selecting donors for faecal microbiota transplantation in ulcerative colitis

semanticscholar(2020)

引用 1|浏览0
暂无评分
摘要
BackgroundInflammatory bowel disease (IBD) is a set of conditions characterized by non-infectious chronic inflammation of the gastrointestinal tract. These primarily include Crohn’s disease (CD), ulcerative colitis (UC) and indeterminate colitis. Fecal microbiota transplantation (FMT) has proven to be an effective treatment for some patients with active UC. There is currently no procedure allowing to predict the patients’ response and to select the most adequate donor(s).AimInvestigate microbiome characteristics in association with responder/non-responder status and develop selection criteria for donor samples to be used for UC FMT.MethodsAvailable UC longitudinal FMT microbiome data sets were in part combined and reanalyzed, with focus on species level changes in the microbiota, using state-of-the-art 16S analysis routines.ResultsWe predicted antibiotic resistance to be higher in non-responders (p=0.0064). Microbiomes of UC FMT responder donors have higher phylogenetic diversity (p=0.0026) and a higher proportion of facultative anaerobes (p=3.3E-5) as compared to non-responder donors. We predicted succinate and histamine to be increased in non-responder donors and non-responders, respectively. Sialic acid catabolism was also predicted to be increased in non-responder donors. Tryptamine and indole-3-acetaldehyde were predicted to be increased in responder donors.ConclusionsOur findings contribute to the establishment of selection criteria for UC FMT donor samples and composition guidelines for future synthetic microbial communities. Our results suggest that oxidative stress resistant facultative anaerobes are important for the establishment of an anaerobic environment and a successful UC FMT therapy. Several metabolites can be tested for additional optimization or prioritization of stool bank samples for UC FMT. Our results question the usefulness of antibiotics based preparation of the gut, prior to FMT.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要