Literature DB >> 28219800

Variations in gut microbiota and fecal metabolic phenotype associated with depression by 16S rRNA gene sequencing and LC/MS-based metabolomics.

Meng Yu1, Hongmei Jia1, Chao Zhou1, Yong Yang1, Yang Zhao1, Maohua Yang1, Zhongmei Zou2.   

Abstract

As a prevalent, life-threatening and highly recurrent psychiatric illness, depression is characterized by a wide range of pathological changes; however, its etiology remains incompletely understood. Accumulating evidence supports that gut microbiota affects not only gastrointestinal physiology but also central nervous system (CNS) function and behavior through the microbiota-gut-brain axis. To assess the impact of gut microbiota on fecal metabolic phenotype in depressive conditions, an integrated approach of 16S rRNA gene sequencing combined with ultra high-performance liquid chromatography-mass spectrometry (UHPLC-MS) based metabolomics was performed in chronic variable stress (CVS)-induced depression rat model. Interestingly, depression led to significant gut microbiota changes, at the phylum and genus levels in rats treated with CVS compared to controls. The relative abundances of the bacterial genera Marvinbryantia, Corynebacterium, Psychrobacter, Christensenella, Lactobacillus, Peptostreptococcaceae incertae sedis, Anaerovorax, Clostridiales incertae sedis and Coprococcus were significantly decreased, whereas Candidatus Arthromitus and Oscillibacter were markedly increased in model rats compared with normal controls. Meanwhile, distinct changes in fecal metabolic phenotype of depressive rats were also found, including lower levels of amino acids, and fatty acids, and higher amounts of bile acids, hypoxanthine and stercobilins. Moreover, there were substantial associations of perturbed gut microbiota genera with the altered fecal metabolites, especially compounds involved in the metabolism of tryptophan and bile acids. These results showed that the gut microbiota was altered in association with fecal metabolism in depressive conditions. These findings suggest that the 16S rRNA gene sequencing and LC-MS based metabolomics approach can be further applied to assess pathogenesis of depression.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  16S rRNA gene sequencing; Depression; Gut microbiota; LC–MS; Metabolomics

Mesh:

Substances:

Year:  2017        PMID: 28219800     DOI: 10.1016/j.jpba.2017.02.008

Source DB:  PubMed          Journal:  J Pharm Biomed Anal        ISSN: 0731-7085            Impact factor:   3.935


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