Berberine (BBR), which is extracted from traditional Chinese herb, is abundant in Coptis chinensis and Berberis vulgaris, with a treatment on type 2 diabetes mellitus (T2DM). However, its oral bioavailability is poor. Therefore, the ability of BBR to regulate gut microbiota and intestinal metabolites might exist. This study aimed to investigate changes in gut microbiota and intestinal metabolites, and to reveal the potential mechanism of BBR. To observe the role of gut microbiota in the treatment of T2DM by BBR, antibiotics intervened gut microbiota was used in this study, and the therapeutic effects of BBR were evaluated. A 16S rRNA gene sequencing approach was utilized to analyze gut microbiota alterations, and UHPLC-QTOF/MS-based untargeted metabolomics analysis of colon contents was used to identity differential intestinal metabolites. Finally, serum aromatic amino acids (AAAs) were absolutely quantified using LC/MS. Inhibition of the blood glucose levels, and improvements in glucose tolerance and serum lipid parameters were observed in the BBR treated group. Type 2 diabetic symptoms in rats in the BA group (treated with antibotics and BBR) were alleviated. However, the therapeutical effects are weaker in the BA group compared with the BBR group, indicating that BBR can be used to treat type 2 diabetic rats immediately, and modulation of gut microbiota is related to the mechanism of BBR in the treatment of T2DM. The community richness and diversity of the gut microbiota were significantly increased by BBR, and the relative abundance of Bacteroidetes was increased in the BBR group, which was accompanied by a decreased relative abundance of Proteobacteria and Verrucomicrobia at the phylum level. At the family level, a probiotic Lactobacillaceae was significantly upregulated not only in the BBR group but also in the BA group and was negatively associated with the risk of T2DM. Metabolomic analysis of colon contents identified 55 differential intestinal metabolites between the BBR group and the model group. AAAs, including tyrosine, tryptophan and phenylalanine, were obviously decreased in the BBR group not only in the colon contents but also in the serum. These results demonstrated that BBR could alleviate symptoms in type 2 diabetic rats by affecting gut microbiota composition and reducing the concentration of AAAs.

Background: Coronary heart disease (CHD) remains highly prevalent and is one of the largest causes of death worldwide. Blood stasis syndrome (BSS) is the main syndrome associated with CHD. However, the underlying biological basis of BSS with CHD is not yet been fully understood. Materials and Methods: We proposed a metabolomics method based on ¹H-NMR and random forest (RF) models to elucidate the underlying biological basis of BSS with CHD. Firstly, 58 cases of CHD patients, including 27 BSS and 31 phlegm syndrome (PS), and 26 volunteers were recruited from Xiangya Hospital affiliated to Central South University. A 1 mL venous blood sample was collected for NMR analysis. Secondly, principal component analysis (PCA), partial least squares discrimination analysis (PLS-DA) and RF was applied to observe the classification of each group, respectively. Finally, RF and multidimensional scaling (MDS) were utilized to discover the plasma potential biomarkers in CHD patients and CHD–BSS patients. Results: The models constructed by RF could visually discriminate BSS from PS in CHD patients. Simultaneously, we obtained 12 characteristic metabolites, including lysine, glutamine, taurine, tyrosine, phenylalanine, histidine, lipid, citrate, choline, lactate, α-glucose, β-glucose related to the CHD patients, and Choline, β-glucose, α-glucose and tyrosine were considered as potential biomarkers of CHD–BSS. Conclusion: The combining of ¹H-NMR profiling with RF models was a useful approach to analyze complex metabolomics data (should be deleted). Choline, β-glucose, α-glucose and tyrosine were considered as potential biomarkers of CHD–BSS.