Abstract

Depression is a serious disease that has a significant impact on social functioning. However, the exact causes of depression are still not fully understood. Therefore, it is necessary to explore new pathways leading to depression. In this study, we used 16 S rDNA to examine changes in gut microbiota and predict related pathways in depression-like mice. Additionally, we employed liquid chromatography-mass spectrometry (LC-MS) to identify changes in amino acids and gas chromatography-mass spectrometry (GC-MS) to identify changes in short-chain fatty acids (SCFAs) in fecal samples. We conducted Pearson/Spearman correlation analysis to investigate the associations between changes in amino acids/SCFAs and behavioral outcomes. The 16 S rDNA sequencing revealed significant alterations in gut microbiota at the phylum and genus levels in mice subjected to chronic unpredictable mild stress (CUMS). The relative abundances of Bacteroidetes, Proteobacteria, Bacteroides, and Alloprevotella were increased, while Firmicutes, Verrucomicrobia, Actinobacteria, Lactobacillus, Akkermansia, Lachnospirillum, and Enterobacter were decreased in the CUMS mice. We used PICRUSt software to annotate the kyoto encyclopedia of genes and genomes (KEGG) pathway function related to depression-like behavior in mice. Our analysis identified sixty functional pathways associated with the gut microbiota of mice exhibiting depression-like behavior. In the amino acid concentration analysis, we observed decreased levels of hydroxyproline and tryptophan, and increased levels of alanine in CUMS mice. In the SCFAs concentration assay, we found decreased levels of butyric acid and valeric acid, and increased levels of acetic acid in CUMS mice. Some of these changes were significantly correlated with depressive-like behaviors. Our study contributes to the understanding of the mechanism of the gut-brain axis in the occurrence and development of depression.

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