Gut Microbiota Combined with Serum Metabolomics to Investigate the Hypoglycemic Effect of Actinidia arguta Leaves.

Actinidia arguta leaves (AAL) are an excellent source of bioactive components for the food industry and possess many functional properties. However, the hypoglycemic effect and mechanism of AAL remain unclear. The aim of this work was to investigate the potential hypoglycemic effect of AAL and explore its possible mechanism using 16S rRNA sequencing and serum metabolomics in diabetic mice induced by high-fat feeding in combination with streptozotocin injection. A total of 25 flavonoids from AAL were isolated and characterized, and the contents of the extract from the AAL ranged from 0.14 mg/g DW to 8.97 mg/g DW. The compound quercetin (2) had the highest content of 8.97 ± 0.09 mg/g DW, and the compound kaempferol-3-O-(2'-O-D-glucopyl)-ß-D-rutinoside (12) had the lowest content of 0.14 ± 0.01 mg/g DW. In vivo experimental studies showed that AAL reduced blood glucose and cholesterol levels, improved insulin sensitivity, and ameliorated oxidative stress and liver and kidney pathological damage. In addition, gut microbiota analysis found that AAL significantly reduced the F/B ratio, enriched the beneficial bacteria Bacteroides and Bifidobacterium, and inhibited the harmful bacteria Lactobacillus and Desulfovibrio, thereby playing an active role in intestinal imbalance. In addition, metabolomics analysis showed that AAL could improve amino acid metabolism and arachidonic acid metabolism, thereby exerting a hypoglycemic effect. This study confirmed that AAL can alleviate type 2 diabetes mellitus (T2DM) by regulating intestinal flora and interfering with related metabolic pathways, providing a scientific basis for its use as a dietary supplement and for further exploration of the mechanism of AAL against T2DM.

Nontargeted metabolomic analysis of four different parts of Actinidia arguta by UPLC-Q-TOF-MSE.

Actinidia arguta, an edible berry plant with high nutritional values, has been widely used in Asian countries as a food and traditional medicinal herb. The well-recognized health-promoting properties of A. arguta were associated with its bioactive components in its different botanical parts. To rapidly screen and identify chemical components and simultaneously determine the potential metabolites from different parts of A. arguta, UPLC-Q-TOF-MSE coupled with UNIFI platform and multivariate statistical analysis approach was established in this study. As a result, a total of 107 components were identified from the four different parts of A. arguta, in which 31 characteristic chemical markers were discovered among them, including 12, 8, 6, and 5 compounds from the fruits, leaves, roots, and stems, respectively. These results suggested that the combination of UPLC-Q-TOF-MSE and metabolomic analysis is a powerful method to rapidly screen characteristic markers for the quality control of A. arguta.