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Gut microbiota plays a key role in the pathophysiology of type 2 diabetes mellitus (T2D). Mulberry leaf has a hypoglycemic effect, but the potential mechanism is not fully understood. This study aimed to explore the influences and potential mechanisms of mulberry leaf water extract (MLWE) intervention on mice with T2D induced through a high-fat and high-sucrose diet combined with streptozotocin by the combination of fecal metabolomics and gut microbiota analysis. Results showed that MLWE could decrease fasting blood glucose and body weight while ameliorating lipid profiles, insulin resistance, liver inflammation, and the accumulation of lipid droplets in T2D mice. MLWE could reverse the abundances of the phyla Actinobacteria and Bacteroidetes and the ratio of Firmicutes/Bacteroidetes, and increase the abundances of the phyla Cyanobacteria and Epsilonbacteraeota in the feces of T2D mice. The abundances of genera Alloprevotella, Parabacteroides, Muribaculaceae, and Romboutsia in the feces of T2D mice could be reversed, while Oscillatoriales_cyanobacterium and Gastranaerophilales could be reinforced by MLWE supplementation. The levels of nine metabolites in the feces of T2D mice were improved, among which glycine, Phe-Pro, urocanic acid, phylloquinone, and lactate were correlated with Romboutsia and Gastranaerophilales. Taken together, we conclude that MLWE can effectively alleviate T2D by mediating the host-microbial metabolic axis.

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Diabetic nephropathy (DN) is one of the most serious microvascular complications and the leading causes of death in diabetes mellitus (DM). To find biomarkers for prognosing the occurrence and development of DN has significant clinical value for its prevention, diagnosis, and treatment. In this study, a non-targeted cell metabolomics–based ultra-performance liquid chromatography coupled with quadrupole time of flight mass spectrometry and gas chromatography coupled with mass spectrometry was developed and performed the dynamic metabolic profiles of rat renal cells including renal tubular epithelial cells (NRK-52E) and glomerular mesangial cells (HBZY-1) in response to high glucose at time points of 12 h, 24 h, 36 h, and 48 h. Some potential biomarkers were then verified using clinical plasma samples collected from 55 healthy volunteers, 103 DM patients, and 57 DN patients. Statistical methods, such as principal component analysis and partial least squares to latent structure-discriminant analysis were recruited for data analyses. As a result, palmitic acid and linoleic acid (all-cis-9,12) were the potential indicators for the occurrence and development of DN, and valine, leucine, and isoleucine could be used as the prospective biomarkers for DM. In addition, rise and fall of leucine and isoleucine levels in plasma could be used for prognosing DN in DM patients. Through this study, we established a novel non-targeted cell dynamic metabolomics platform and identified potential biomarkers that may be applied for the diagnosis and prognosis of DM and DN.

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