Integrated Gut Microbiota, Metabolomics, and Network Pharmacology to Investigate the Anti-Alzheimer's Mechanism of Tripterygium Glycoside.

BACKGROUND: Tripterygium glycoside (TG) has been reported to have the effect of ameliorating Alzheimer's disease (AD)-like symptoms in mice model. However, the underlying mechanism is largely unknown. This study aimed to investigate the potential mechanism of TG against AD by integrating metabolomics, 16s rRNA sequencing, network pharmacology, molecular docking, and molecular dynamics simulation. METHODS: Memory and cognitive functions were assessed in mice via the Morris water maze. The pathological changes were assessed using hematoxylin and Nissl's straining. Pathological changes in p-Tau and Aβ(1-42) were assessed using immunohistochemistry, immunofluorescence, ELISA, and Western blotting. 16S rRNA sequencing and metabolomics were performed to analyze alterations in the structure of gut microbiota and hippocampus metabolites. Network pharmacology, molecular docking, and molecular dynamics simulation were performed to determine the putative molecular regulatory mechanism of TG in treating AD. RESULTS: TG significantly could inhibit neuron loss, improved cognitive and memory functions, and significantly reduce the expression of p-Tau and Aβ(1-42.) In addition, 16s rRNA analysis revealed that TG could reverse AD-induced gut microbiota dysbiosis in AD model mice by reducing the abundance of Alistipes. Furthermore, metabolomic analysis revealed that TG may reverse AD-induced metabolic disorders by regulating glycerophospholipid metabolism. And spearman analysis revealed that glycerophospholipids metabolism might closely related to Alistipes. Moreover, network pharmacology, molecular docking, and molecular dynamics simulation analyses indicated that TG might regulate lipid metabolism-related pathways via SRC for the treatment of AD. CONCLUSION: TG may serve as a potential therapeutic drug for preventing AD via the microbiota-gut-brain axis.