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 sphing...