Gut microbiota has an important role in the immune system, metabolism, and digestion, and has a significant effect on the nervous system. Recent studies have revealed that abnormal gut microbiota induces abnormal behaviors, which may be associated with the hypothalamic–pituitary–adrenal (HPA) axis. Therefore, we investigated the behavioral changes in germ-free (GF) mice by behavioral tests, quantified the basal serum cortisol levels, and examined glucocorticoid receptor pathway genes in hippocampus using microarray analysis followed by real-time PCR validation, to explore the molecular mechanisms by which the gut microbiota influences the host’s behaviors and brain function. Moreover, we quantified the basal serum cortisol levels and validated the differential genes in an Escherichia coli-derived lipopolysaccharide (LPS) treatment mouse model and fecal “depression microbiota” transplantation mouse model by real-time PCR. We found that GF mice showed antianxiety- and antidepressant-like behaviors, whereas E. coli LPS-treated mice showed antidepressant-like behavior, but did not show antianxiety-like behavior. However, “depression microbiota” recipient mice exhibited anxiety- and depressive-like behaviors. In addition, six glucocorticoid receptor pathway genes (Slc22a5, Aqp1, Stat5a, Ampd3, Plekhf1, and Cyb561) were upregulated in GF mice, and of these only two (Stat5a and Ampd3) were upregulated in LPS-treated mice, whereas the shared gene, Stat5a, was downregulated in “depression microbiota” recipient mice. Furthermore, basal serum cortisol levels were decreased in E. coli LPS-treated mice but not in GF mice and “depression microbiota” recipient mice. These results indicated that the gut microbiota may lead to behavioral abnormalities in mice through the downstream pathway of the glucocorticoid receptor. Herein, we proposed a new insight into the molecular mechanisms by which gut microbiota influence depressive-like behavior.
Major depressive disorder (MDD) is a highly prevalent and debilitating mental illness, which is associated with disorder of gut microbiota. However, few studies focusing on detection of the signatures of bacteria in feces of MDD patients using proteomics approach have been carried out. Here, a comparative metaproteomics analysis on the basis of an isobaric tag for relative and absolute quantification coupled with tandem mass spectrometry was carried out to explore the signature of gut microbiota in patients with MDD. Ten patients (age: 18-56 years, five women) who had MDD and a score over 20 on the Hamilton's Depression Scale and 10 healthy controls (age: 24-65 years, five women) group matched for sex, age, and BMI were enrolled. As a result, 279 significantly differentiated bacterial proteins (P<0.05) were detected and used for further bioinformatic analysis. According to phylogenetic analysis, statistically significant differences were observed for four phyla: Bacteroidetes, Proteobacteria, Firmicutes, Actinobacteria (P<0.05, for each). Abundances of 16 bacterial families were significantly different between the MDD and healthy controls (P<0.05). Furthermore, Cluster of Orthologous Groups analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis showed that disordered metabolic pathways of bacterial proteins were mainly involved in glucose metabolism and amino acid metabolism. In conclusion, fecal microbiota signatures were altered significantly in MDD patients. Our findings provide a novel insight into the potential connection between gut microbiota and depression.
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