Comparative analysis of gut microbiota and fecal metabolome features among multiple depressive animal models

Abstract

Backgrounds: Emerging studies reported that gut microbiota and fecal metabolites take part in major depressive disorder (MDD) pathogenesis. However, the conclusions based on a single depressive animal model seem inconsistent or even controversial.

Methods: Multiple depression rat models, including chronic unpredictable mild stress, chronic restraint stress, social defeat, and learned helplessness, were used. Then, the 16S ribosomal RNA gene sequencing and liquid chromatography-mass spectrometry analysis determined the alteration of gut microbiota and fecal metabolites.

Results: The results of sucrose preference test and forced swimming test suggested that each model successfully established depression-like behavior. A total of 179 discriminative amplicon sequence variants (ASVs) were identified among four models. The overall discriminative ASVs mainly belonged to the family Lachnospiraceae, Muribaculaceae, and Oscillospiraceae. Moreover, the fecal metabolomic analysis identified 468 differential expressed metabolites. Among all the differential metabolites, 11 specific pathways significantly altered, which were mainly belonged to lipid and amino acid metabolism. Finally, co-occurrence network analysis suggested that target differential metabolites were associated with discriminative ASVs mainly assigned to family taxon Lachnospiraceae, Muribaculaceae, and Oscillospiraceae.

Limitations: The heterogeneity of MDD in humans cannot be totally imitated by animal models.

Conclusions: In multiple depression models, the alterations of family Lachnospiraceae, Muribaculaceae, and Oscillospiraceae with the dysbiosis of lipid and amino acid metabolism were gut microbiota and fecal metabolome features. The findings of our research may help us to have a comprehensive understanding of gut microbiota and fecal metabolome in depression.

Keywords: Depression; Fecal metabolite; Gut microbiota; Multiple rat models.