An Analysis of the Intestinal Microbiome Combined with Metabolomics to Explore the Mechanism of How Jasmine Tea Improves Depression in CUMS-Treated Rats

Abstract

Recently, research has confirmed that jasmine tea may help improve the depressive symptoms that are associated with psychiatric disorders. Our team previously found that jasmine tea improved the depressive-like behavior that is induced by chronic unpredictable mild stress (CUMS) in Sprague Dawley (SD) rats. We hypothesized that the metabolic disorder component of depression may be related to the gut microbiota, which may be reflected in the metabolome in plasma. The influence of jasmine tea on gut microbiota composition and the association with depressive-related indexes were explored. Furthermore, the metabolites in plasma that are related to the gut microbiota were identified. SD rats were treated with control or CUMS and administrated jasmine tea for 8 weeks. The 16S rRNA gene amplicon sequencing was used to analyze the gut microbiota in feces samples, and untargeted metabolomics was used to analyze the metabolites in plasma. The results found that jasmine tea significantly ameliorated the depressive behavior induced by CUMS, significantly improved the neurotransmitter concentration (BDNF and 5-HT), and decreased the pro-inflammation levels (TNF-α and NF-κB). The intervention of jasmine tea also alleviated the dysbiosis caused by CUMS; increased the relative abundance of Bacteroides, Blautia, Clostridium, and Lactobacillus; and decreased Ruminococcus and Butyrivibrio in the CUMS-treated rats. Furthermore, the serum metabolites of the CUMS-treated rats were reversed after the jasmine tea intervention, i.e., 22 were up-regulated and 18 were down-regulated, which may have a close relationship with glycerophospholipid metabolism pathways, glycine serine and threonine metabolism pathways, and nicotinate and nicotinamide metabolism pathways. Finally, there were 30 genera of gut microbiota related to the depressive-related indexes, and 30 metabolites in the plasma had a strong predictive ability for depressive behavior. Potentially, our research implies that the intervention of jasmine tea can ameliorate the depression induced by CUMS via controlling the gut flora and the host's metabolism, which is an innovative approach for the prevention and management of depression.

Keywords: CUMS; gut microbiome; jasmine tea; metabolome.

Figure 1

The schedule of experimental procedures. SPT, sugar preference test; OFT, open-field test; SFT, forced swimming test.

Figure 2

Results of the behavioral tests. (A) Body weight during the experiment. (B) Body weight gain during the experiment. (C) Food intake during the experiment. (D) Sugar preference during the experiment. (E) Immobility time comparison of FST. (F) The comparison of number of inners, outers, and standing in OFT. Con, control; Mod, model; NF, CUMS treated with jasmine tea. SPT, sugar preference test; FST, force swimming test; OFT, open field test. # p < 0.05, ## p < 0.01 versus the control group; * p < 0.05, ** p < 0.01 versus the model group.

Figure 3

The levels of neurotransmitter and inflammation factors among different tissues. (A) 5-HT; (B) BDNF; (C) TNF-α; (D) NF-κB. # p < 0.05, ## p < 0.01, ### p < 0.01 versus the control group; * p < 0.05, ** p < 0.01, *** p < 0.001 versus the model group.

Figure 4

The ameliorations of phenotype in hippocampus and colon of CUMS-induced rats after jasmine tea administration. (A) HE staining of the hippocampus. (B) Nissl staining of the hippocampus. (C) HE staining of the colon. →, the comparison of special structures in the figure.

Figure 5

Gut microbial characteristics of Con, Mod, and NF. (A) Alpha-phylogenetic diversity analysis showed that depressive-like rats induced by CUMS had lower microbial richness in four indexes relative to controls; these indexes had increased when administrated with jasmine tea. (B) Principal component analysis (PCA) revealed that the gut microbiome composition in rats with depressive-like symptoms induced by CUMS was markedly distinct from that of Con, and the intestinal microbial composition of depressive-like induced by CUMS was restored after being treated with jasmine tea. (C) Venn diagram for taxonomy of gut microbes based on genus level. (D) Circus circle diagram of the top 10 relative abundances in intestinal microbial classification based on genus level. (E) The gut microbiota compositions among the experimental groups at the phylum level. (F) The relative abundance of gut microbes at the genus level. # p < 0.05, ## p < 0.01 versus the control group; * p < 0.05, ** p < 0.01, versus the model group.

Figure 6

Linear discriminant analysis effect size (LEfSe) analysis was conducted with a threshold of LDA > 2.0. The results were visualized using a cladogram (A) and a histogram (B) and showed 35 genera responsible for discriminating in Con, Mod, and NF.

Figure 7

Jasmine tea intervention regulated the gut microbiota in CUMS-induced depressive rats. (A) Heatmap of the gut microbiome in genus levels. (B) Phylogenetic tree and heatmap of abundances distribution between groups in phylum level. (C) The comparison of relative abundance of gut microbial community members was conducted at the genus level among three groups. Data represent the mean ± SEM of six rats in each group. # p < 0.05, ## p < 0.01 versus the control group; * p < 0.05, ** p < 0.01 versus the model group.

Figure 8

Associations of gut microbes with neurotransmitters and inflammation factors based on Spearman correlation analysis. (A) The composition of intestinal microorganisms based on the genus level and environmental factors being analyzed through a mapping test. (B) Overreplacement test map of intestinal microorganisms based on generic levels and environmental factors. (C) Visualization of Spearman’s rank correlation in the form of a heatmap of 30 genera and neurotransmitters, with inflammations in colon. * p < 0.05, ** p < 0.01, *** p < 0.001.

Figure 9

Multivariate analysis of metabolic profiles of Con, Mod, and NF. (A–C) The evaluation scatter plots of different groups from the PLS-DA data. (D) Con and Mod pairwise comparison OPLS-DA evaluation scatter plots. (E) Mod and NF pairwise comparison OPLS-DA evaluation scatter plots. (G) Stacked column chart of the percentage of metabolites that play a biological role. (F) Pathway topology enrichment among different treatments.

Figure 10

Associations of gut microbes with neurotransmitters and inflammation factors based on Spearman correlation analysis. * p < 0.05, ** p < 0.01, *** p < 0.001.

Figure 11

Network diagram of associations of gut based on lefse-genus and metabolites based on OPLS-DA.