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other·endocrinology, preclinical research, biomedical research, animal science·PMC10075032

Characterization of gut microbial and metabolite alterations in faeces of Goto Kakizaki rats using metagenomic and untargeted metabolomic approach

World Journal of Diabetes · 8 authors, 9 centres

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TL;DR

Using metagenomic and untargeted metabolomic analyses on faecal samples from 10 GK (T2DM model) rats and 10 Wistar control rats over 10 weeks, the study found significant shifts in gut microbiota composition and 14 differential metabolic biomarkers associated with fasting blood glucose and insulin resistance. Correlation analyses linked specific microbes and metabolites to glucose homeostasis indicators, and pathway analysis highlighted arginine biosynthesis, primary bile acid biosynthesis, and linoleic acid metabolism as the most altered pathways.

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Ten GK rats and Wistar control rats were observed for 10 weeks. GK rats showed significant differences in weight, fasting blood glucose, insulin levels, HOMA-IR, and HOMA-β compared with controls (P < 0.05, P < 0.01). The model group exhibited significantly decreased abundances of Prevotella sp. CAG:604 and Lactobacillus murinus (P < 0.05) and increased Allobaculum stercoricanis (P < 0.01). Orthogonal partial least squares discriminant analysis separated faecal metabolic profiles between groups, identifying 14 potential metabolic biomarkers. Correlation analyses showed FBG and HOMA-IR were positively correlated with Allobaculum stercoricanis and several metabolites, and negatively correlated with Lactobacillus murinus and specific bile acids (P < 0.05, P < 0.01). Findings suggest disordered gut microbe and metabolite compositions may be associated with diabetic phenotypes in GK rats.

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other

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endocrinology

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ORIGINAL PAPER

PMC10075032

Characterization of gut microbial and metabolite alterations in faeces of Goto Kakizaki rats using metagenomic and untargeted metabolomic approach

World Journal of Diabetes

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ABSTRACT

Abstract BACKGROUND In recent years, the incidence of type 2 diabetes (T2DM) has shown a rapid growth trend. Goto Kakizaki (GK) rats are a valuable model for the study of T2DM and share common glucose metabolism features with human T2DM patients. A series of studies have indicated that T2DM is associated with the gut microbiota composition and gut metabolites. We aimed to systematically characterize the faecal gut microbes and metabolites of GK rats and analyse the relationship between glucose and insulin resistance. AIM To evaluate the gut microbial and metabolite alterations in GK rat faeces based on metagenomics and untargeted metabolomics. METHODS Ten GK rats (model group) and Wistar rats (control group) were observed for 10 wk, and various glucose-related indexes, mainly including weight, fasting blood glucose (FBG) and insulin levels, homeostasis model assessment of insulin resistance (HOMA-IR) and homeostasis model assessment of β cell (HOMA-β) were assessed. The faecal gut microbiota was sequenced by metagenomics, and faecal metabolites were analysed by untargeted metabolomics. Multiple metabolic pathways were evaluated based on the differential metabolites identified, and the correlations between blood glucose and the gut microbiota and metabolites were analysed. RESULTS The model group displayed significant differences in weight, FBG and insulin levels, HOMA-IR and HOMA-β indexes ( P < 0.05, P < 0.01) and a shift in the gut microbiota structure compared with the control group. The results demonstrated significantly decreased abundances of Prevotella sp. CAG:604 and Lactobacillus murinus ( P < 0.05) and a significantly increased abundance of Allobaculum stercoricanis ( P < 0.01) in the model group. A correlation analysis indicated that FBG and HOMA-IR were positively correlated with Allobaculum stercoricanis and negatively correlated with Lactobacillus murinus . An orthogonal partial least squares discriminant analysis suggested that the faecal metabolic profiles differed between the model and control groups. Fourteen potential metabolic biomarkers, including glycochenodeoxycholic acid, uric acid, 13(S)-hydroxyoctadecadienoic acid (HODE), N-acetylaspartate, β-sitostenone, sphinganine, 4-pyridoxic acid, and linoleic acid, were identified. Moreover, FBG and HOMA-IR were found to be positively correlated with glutathione, 13(S)-HODE, uric acid, 4-pyridoxic acid and allantoic acid and ne-gatively correlated with 3-α, 7-α, chenodeoxycholic acid glycine conjugate and 26-trihydroxy-5-β-cholestane ( P < 0.05, P < 0.01). Allobaculum stercoricanis was positively correlated with linoleic acid and sphinganine ( P < 0.01), and 2-methyl-3-hydroxy-5-formylpyridine-4-carboxylate was negatively associated with Prevotella sp. CAG:604 ( P < 0.01). The metabolic pathways showing the largest differences were arginine biosynthesis; primary bile acid biosynthesis; purine metabolism; linoleic acid metabolism; alanine, aspartate and glutamate metabolism; and nitrogen metabolism. CONCLUSION Metagenomics and untargeted metabolomics indicated that disordered compositions of gut microbes and metabolites may be common defects in GK rats. Keywords: Type 2 diabetes mellitus, Gut microbial, Metabolites, Goto-Kakizaki rats, Metagenomics, Untargeted metabolomics

CITATION EXPORT

Jin-Dong Zhao, Min Sun, Yan Li et al.. Characterization of gut microbial and metabolite alterations in faeces of Goto Kakizaki rats using metagenomic and untargeted metabolomic approach. World Journal of Diabetes. (2023). https://doi.org/10.4239/wjd.v14.i3.255

AUTHORS

8 · 9 CENTRES

Jin-Dong Zhao, Min Sun, Yan Li, Chan-Juan Yu, Ruo-Dong Cheng, Si-Hai Wang, Xue Du, Zhao-Hui Fang

1Department of Endocrinology, The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei 230031, Anhui Province, China
2Graduate School, Anhui University of Chinese Medicine, Hefei 230012, Anhui Province, China
3School of Life Sciences, Anhui University, Hefei 230039, Anhui Province, China
4Department of Infectious Disease, The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei 230031, Anhui Province, China
5Department of Endocrinology, The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei 230031, Anhui Province, China
6Department of Endocrinology, The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei 230031, Anhui Province, China
7Department of Endocrinology, The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei 230031, Anhui Province, China
8Department of Endocrinology, The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei 230031, Anhui Province, China
9Department of Endocrinology, The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei 230031, Anhui Province, China. [email protected]