Microbiome Metabolomic Analysis of the Anxiolytic Effect of Baihe Dihuang Decoction in a Rat Model of Chronic Restraint Stress

Abstract

Purpose: The Baihe Dihuang decoction (BDD) is a representative traditional Chinese medicinal formula that has been used to treat anxiety disorders for thousands of years. This study aimed to reveal mechanisms of anxiolytic effects of BDD with multidimensional omics.

Methods: First, 28-day chronic restraint stress (CRS) was used to create a rat model of anxiety, and the open field test and elevated plus maze were used to assess anxiety-like behavior. Enzyme-linked immunosorbent assay (ELISA), hematoxylin-eosin staining, and immunofluorescence staining were used to evaluate inflammatory response. Besides, 16S rRNA gene sequencing assessed fecal microbiota composition and differential microbiota. Non-targeted metabolomics analysis of feces was performed to determine fecal biomarkers, and targeted metabolomics was used to observe the levels of hippocampus neurotransmitters. Finally, Pearson correlation analysis was used to examine relationships among gut microbiota, fecal metabolites, and neurotransmitters.

Results: BDD significantly improved anxiety-like behaviors in CRS-induced rats and effectively ameliorated hippocampal neuronal damage and abnormal activation of hippocampal microglia. It also had a profound effect on the diversity of microbiota, as evidenced by significant changes in the abundance of 10 potential microbial biomarkers at the genus level. Additionally, BDD led to significant alterations in 18 fecal metabolites and 12 hippocampal neurotransmitters, with the majority of the metabolites implicated in amino acid metabolism pathways such as D-glutamine and D-glutamate, alanine, arginine and proline, and tryptophan metabolism. Furthermore, Pearson analysis showed a strong link among gut microbiota, metabolites, and neurotransmitters during anxiety and BDD treatment.

Conclusion: BDD can effectively improve anxiety-like behaviors by regulating the gut-brain axis, including gut microbiota and metabolite modification, suppression of hippocampal neuronal inflammation, and regulation of neurotransmitters.

Keywords: 16S rRNA; Baihe Dihuang decoction; anxiety; metabolomics; neurotransmitter.

Graphical abstract

Figure 1

BDD improves anxiety behaviors. (A) Anxiety-like behaviors induced by CRS. (B and C) The movement trails of the rats in each group assessed using a video tracking software in the open field test (B) and elevated cross maze test (C). (D and E) Results of open field test were the center distance (D) and central enter times (E). (F and G) Results of elevated plus maze test were the proportion of time keeping the open arm (OT%) (F) and the proportion of entering the open arm (OE%) (G). The immobile times in the forced swimming test (H). Values are expressed as means ± SD. n=6 rats per group. **P<0.01, significant differences compared with the CON group; ^#P<0.05, ^##P<0.01, significant differences compared with the CRS group.

Figure 2

Representative total ion current profiles of BDD in positive (A) and negative (B) ion modes.

Figure 3

BDD reduces inflammatory factors, hippocampal damage, and microglia activation. (A–D) Levels of inflammatory factors in the hippocampus (n=6). (E) Representative HE staining of hippocampal tissue (200×). (F) Representative immunofluorescence staining of IBA1 (red) in the hippocampal tissue (100×). Values are expressed as means ± SD. (n=6). *P<0.05, **P<0.01, significant differences compared with the CON group; ^#P<0.05, ^##P<0.01, significant differences compared with the CRS group.

Figure 4

BDD reverses abnormal diversity of gut microbiota. (A) Alpha diversity analysis of the CON, the CRS, and BDDH groups. (B) Principal coordinate analysis. (C) Non-metric multidimensional scaling analysis of the CON, CRS, and BDDH groups based on the weighted UniFrac distance algorithm. (D) Samples distances heat map on OTU level. n=6 rats per group. **P<0.01, significant differences compared with the CON group; ^##P<0.01, significant differences compared with the CRS group; ns, no significant difference between two groups.

Figure 5

BDD ameliorates the abnormal abundance of potential microbial biomarkers at the phylum level. (A) Average relative abundances at the phylum level in the CON, the CRS, and BDD groups. (B–F) Comparison of relative abundances of potential microbial biomarkers at the phylum level in the CON, CRS, and BDD groups. n=6 rats per group. *P<0.05, **P<0.01, significant differences compared with the CON group; ^##P<0.01, significant differences compared with the CRS group; ns, no significant difference between two groups.

Figure 6

BDD ameliorates the abnormal abundance of potential microbial biomarkers at the genus level. (A) Average relative abundances at the genus level in the CON, the CRS, and BDDH groups. (B–K) Comparison of relative abundances of potential microbial biomarkers at the genus level in the CON, CRS, and BDDH groups. n=6 rats per group. **P<0.01, significant differences compared with the CON group. ^##P<0.01, significant differences compared with the CRS group.

Figure 7

BDD normalizes the disturbed metabolic profiles. (A and B) PCA score plots of fecal samples of rats in different groups in positive (A) mode and negative mode (B). (C and D) OPLS DA score plots fecal samples of rats in different groups in positive mode (C) and negative mode (D). (E and F) OPLS DA model validation plot of fecal samples of rats in different groups in positive mode (E) and negative mode (F). (G and H) The heat map of different metabolites both in positive (G) and in negative ion modes (H). R² and Q² represent the interpretation rate of the model to the matrix and the prediction ability of the model, respectively.

Figure 8

BDD significantly recovers neurotransmitter dysfunction. (A) PCA score plots of neurotransmitters. (B) OPLS DA score plots of neurotransmitters. (C) Heat map of neurotransmitters. (D) Levels of neurotransmitters in the hippocampus. n= 6 rats per group. *P<0.05, **P<0.01, significant differences compared with the CON group; ^#P<0.05, ^##P<0.01, significant differences compared with the CRS group.

Figure 9

Metabolic pathways and network analysis. (A and B) Summary of pathway analysis in fecal (A) and hippocampus (B) samples with MetaboAnalyst. (C) Metabolic network analysis. Red up arrow or red down arrow means that the hippocampal metabolite is significantly increased or decreased compared with the CRS group; green up arrow or green down arrow means that the fecal metabolite is significantly increased or decreased compared with the CRS group.

Figure 10

Correlation analysis between metabolites and microorganisms. Pearson correlation analysis among microbial biomarkers and differential metabolites in fecal samples (A). Pearson correlation analysis among microbial biomarkers and neurotransmitters in the hippocampus (B). The color key represents Pearson’s correlation coefficient. The green color indicates positive correlations, while the red color indicates negative correlations. n=6 rats per group, significance is indicated as *P<0.01.