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. 2023 Mar 27:13:1116277.
doi: 10.3389/fcimb.2023.1116277. eCollection 2023.

Alteration of the gut microbiome and correlated metabolism in a rat model of long-term depression

Yubo Li  1 , Junling Li  2 , Ran Cheng  3 , Haixia Liu  1 , Yukun Zhao  1 , Yanjun Liu  1 , Yanjing Chen  1 , Zhibo Sun  1 , Zhiguang Zhai  1 , Meng Wu  1 , Yupeng Yan  1 , Yuxiu Sun  1 , Zhiguo Zhang  1
Affiliations

Alteration of the gut microbiome and correlated metabolism in a rat model of long-term depression

Yubo Li et al. Front Cell Infect Microbiol. .

Abstract

Objective: This study aims to investigate the composition and function of the gut microbiome in long-term depression using an 8-week chronic unpredictable mild stress (CUMS) rat model.

Materials and methods: Animals were sacrificed after either 4 weeks or 8 weeks under CUMS to mimic long-term depression in humans. The gut microbiome was analyzed to identify potential depression-related gut microbes, and the fecal metabolome was analyzed to detect their functional metabolites. The correlations between altered gut microbes and metabolites in the long-term depression rats were explored. The crucial metabolic pathways related to long-term depression were uncovered through enrichment analysis based on these gut microbes and metabolites.

Results: The microbial composition of long-term depression (8-week CUMS) showed decreased species richness indices and different profiles compared with the control group and the 4-week CUMS group, characterized by disturbance of Alistipes indistinctus, Bacteroides ovatus, and Alistipes senegalensis at the species level. Additionally, long-term depression was associated with disturbances in fecal metabolomics. D-pinitol was the only increased metabolite in the 8-week CUMS group among the top 10 differential metabolites, while the top 3 decreased metabolites in the long-term depression rats included indoxyl sulfate, trimethylaminen-oxide, and 3 alpha,7 alpha-dihydroxy-12-oxocholanoic acid. The disordered fecal metabolomics in the long-term depression rats mainly involved the biosynthesis of pantothenate, CoA, valine, leucine and isoleucine.

Conclusion: Our findings suggest that the gut microbiome may participate in the long-term development of depression, and the mechanism may be related to the regulation of gut metabolism.

Keywords: CUMS; gut microbiome; long-term depression; metabolome; rat.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Experimental Schema and behavioral results. (A) Schedule of experimental procedures. (B) Changes in weight among control, rats under 4-week CUMS, and rats under 8-week CUMS. (C) Changes in sucrose preference among control, rats under 4-week CUMS, and rats under 8-week CUMS. (D) Changes in total distance in the open field test among control, rats under 4-week CUMS, and rats under 8-week CUMS. (E) Changes in times of grid crossing in the open field test among control, rats under 4-week CUMS, and rats under 8-week CUMS.
Figure 2
Figure 2
Characteristics of the gut microbiota in the depression rat model. (A) α-phylogenetic diversity analysis showing that CUMS rats were characterized by lower microbial richness relative to controls. (B) Orthogonal partial least squares discrimination analysis (OPLS-DA) showed that the gut microbial composition of CUMS rats was significantly different from that of the control group. (C) Relative abundance of gut microbes at the species level across samples (CG- normal control group; MG-CUMS group).
Figure 3
Figure 3
Microbial composition in long-term depression and co-occurrence of the species. (A) α-phylogenetic diversity analysis of 4-week CUMS and 8-week CUMS rats. (B) OPLS-DA showed that the gut microbial composition of 8-week CUMS rats was significantly different from that of 4-week CUMS rats. (C) Relative abundance of gut microbes at the species level. (D) Altered species (top 20) in the long-term depression group. (E) Co-occurrence of the species altered in the depression groups at the g and p levels.
Figure 4
Figure 4
Linear discriminant analysis effect size (LEfSe) analysis. Cladogram (A) and histogram (B) illustrating the species responsible for discriminating the rats under 4 weeks of CUMS and 8 weeks of CUMS (n = 10 per group).
Figure 5
Figure 5
Fecal metabolism characteristics of CUMS rats. (A) Volcano plot of differential features between the CUMS group and the control group. (B) Top 10 differential metabolites between the CUMS group and the control group. (C) Volcano plot of differential features between the 8-week CUMS group and the 4-week CUMS group. (D) Top 10 differential metabolites between the 8-week CUMS group and the 4-week CUMS group. (E) KEGG pathways involved in the differential metabolites.
Figure 6
Figure 6
Correlations between gut microbes and fecal metabolites. (A) Heatmap of correlations between gut microbes and fecal metabolites in depression rats; (B) ROC curve of the top 3 representative metabolites related to gut microbes (ID953: N-acetyl-d-glucosamine; ID105: 3-(3-Hydroxyphenyl)propanoic acid; ID186: N-acetyl-d-mannosamine). One asterisk (*) represents a p-value less than 0.05, two asterisks (**) represent a p-value less than 0.01, and three asterisks (***) represent a p-value less than 0.001.
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