Zhexin Ni1, Shuai Sun1, Yanli Bi1, Jie Ding1, Wen Cheng1, Jin Yu1, Ling Zhou1, Mingqing Li2, Chaoqin Yu1. 1. Department of Gynecology of Traditional Chinese Medicine, Changhai Hospital, Naval Medical University, Shanghai, China. 2. Shanghai Key Laboratory of Female Reproductive Endocrine Related Diseases, Hospital of Obstetrics and Gynecology, Fudan University, Shanghai, China.
Abstract
PROBLEM: Endometriosis (EMS) is a chronic inflammatory disease with unclear pathogenesis. Three studies have uncovered the influence of gut microbiota on mice with EMS, but no study has investigated the characteristics of fecal metabolomics to determine some important clues on EMS. This research aims to uncover the interaction between fecal metabolomics and gut microbiota in EMS mice. METHOD OF STUDY: Female C57BL/6J mice were used to construct the EMS model. Non-target metabolomics was applied to detect the fecal metabolites of EMS mice. The 16s rRNA sequencing was used for clarifying the composition of the gut microbiota. The functional characteristics of gut microbiota were analyzed using the PICRUSt. The receiver operator characteristic curve (ROC) analysis was utilized for determining the potential important differential metabolites, and the Spearman correlation coefficient was applied for expressing the correlation between the important differential metabolites and gut microbiota. RESULTS: A total of 156 named differential metabolites were screened. The diversity and the abundance of gut microbiota in EMS mice decreased. Eleven pathways were involved in the differential metabolites and the functional prediction of gut microbiota, among which the second bile acid biosynthesis and alpha-linolenic acid (ALA) metabolism were the significant enrichment pathways. The increased abundance of chenodeoxycholic and ursodeoxycholic acids and the decreased abundance of ALA and 12,13-EOTrE were found in the feces of EMS mice. CONCLUSION: The abnormal fecal metabolites, which are influenced by dysbacteriosis, may be the characteristics of EMS mice and can be the potential important indices to distinguish the disease.
PROBLEM: Endometriosis (EMS) is a chronic inflammatory disease with unclear pathogenesis. Three studies have uncovered the influence of gut microbiota on mice with EMS, but no study has investigated the characteristics of fecal metabolomics to determine some important clues on EMS. This research aims to uncover the interaction between fecal metabolomics and gut microbiota in EMS mice. METHOD OF STUDY: Female C57BL/6J mice were used to construct the EMS model. Non-target metabolomics was applied to detect the fecal metabolites of EMS mice. The 16s rRNA sequencing was used for clarifying the composition of the gut microbiota. The functional characteristics of gut microbiota were analyzed using the PICRUSt. The receiver operator characteristic curve (ROC) analysis was utilized for determining the potential important differential metabolites, and the Spearman correlation coefficient was applied for expressing the correlation between the important differential metabolites and gut microbiota. RESULTS: A total of 156 named differential metabolites were screened. The diversity and the abundance of gut microbiota in EMS mice decreased. Eleven pathways were involved in the differential metabolites and the functional prediction of gut microbiota, among which the second bile acid biosynthesis and alpha-linolenic acid (ALA) metabolism were the significant enrichment pathways. The increased abundance of chenodeoxycholic and ursodeoxycholic acids and the decreased abundance of ALA and 12,13-EOTrE were found in the feces of EMS mice. CONCLUSION: The abnormal fecal metabolites, which are influenced by dysbacteriosis, may be the characteristics of EMS mice and can be the potential important indices to distinguish the disease.
Authors: Jocelyn M Wessels; Miguel A Domínguez; Nicholas A Leyland; Sanjay K Agarwal; Warren G Foster Journal: Sci Rep Date: 2021-09-23 Impact factor: 4.379
Authors: Sangappa B Chadchan; Pooja Popli; Chandrasekhar R Ambati; Eric Tycksen; Sang Jun Han; Serdar E Bulun; Nagireddy Putluri; Scott W Biest; Ramakrishna Kommagani Journal: Life Sci Alliance Date: 2021-09-30