Abnormal bile acid metabolism is an important feature of gut microbiota and fecal metabolites in patients with slow transit constipation

肠道菌群 胆汁酸 代谢组学 粪便 拟杆菌 脱氧胆酸 代谢物 牛磺酸 胆酸 生物 甘胆酸 内科学 胃肠病学 生理学 微生物学 生物化学 医学 细菌 生物信息学 氨基酸 遗传学
作者
Yadong Fan,Chen Xu,Lulu Xie,Ying Wang,Shan Zhu,Ji‐Ren An,Yuwei Li,Zhikui Tian,Yiqi Yan,Shuang Yu,Haizhao Liu,Beitian Jia,Yiyang Wang,Li Wang,Long Yang,Yuhong Bian
出处
期刊:Frontiers in Cellular and Infection Microbiology [Frontiers Media]
卷期号:12 被引量:8
标识
DOI:10.3389/fcimb.2022.956528
摘要

Destructions in the intestinal ecosystem are implicated with changes in slow transit constipation (STC), which is a kind of intractable constipation characterized by colonic motility disorder. In order to deepen the understanding of the structure of the STC gut microbiota and the relationship between the gut microbiota and fecal metabolites, we first used 16S rRNA amplicon sequencing to evaluate the gut microbiota in 30 STC patients and 30 healthy subjects. The α-diversity of the STC group was changed to a certain degree, and the β-diversity was significantly different, which indicated that the composition of the gut microbiota of STC patients was inconsistent with healthy subjects. Among them, Bacteroides, Parabacteroides, Desulfovibrionaceae, and Ruminiclostridium were significantly upregulated, while Subdoligranulum was significantly downregulated. The metabolomics showed that different metabolites between the STC and the control group were involved in the process of bile acids and lipid metabolism, including taurocholate, taurochenodeoxycholate, taurine, deoxycholic acid, cyclohexylsulfamate, cholic acid, chenodeoxycholate, arachidonic acid, and 4-pyridoxic acid. We found that the colon histomorphology of STC patients was significantly disrupted, and TGR5 and FXR were significantly downregulated. The differences in metabolites were related to changes in the abundance of specific bacteria and patients’ intestinal dysfunction. Analysis of the fecal genomics and metabolomics enabled separation of the STC from controls based on random forest model prediction [STC vs . control (14 gut microbiota and metabolite biomarkers)—Sensitivity: 1, Specificity: 0.877]. This study provided a perspective for the diagnosis and intervention of STC related with abnormal bile acid metabolism.
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