Integrated Lipidomics and Network Pharmacology to Reveal the Mechanisms of Swertia mussotii Franch in the Treatment of Liver Fibrosis in Mice

整合脂质组学和网络药理学揭示獐牙菜治疗小鼠肝纤维化的机制

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Abstract

Swertia mussotii Franch (SMF) has been proven to be an effective Chinese herbal medicine (CHM) to treat liver fibrosis. However, the in-depth mechanism remains unclear. In this study, a strategy integrating lipidomics and network pharmacology was developed to reveal the active components, targets, and pathways of SMF against dimethylnitrosamine (DMN)-induced liver fibrosis in mice. Liver lipidomics, based on ultrahigh-performance liquid chromatography (UHPLC) with hybrid quadrupole Orbitrap mass spectrometry (MS), found that 46 lipid metabolites were associated with liver fibrosis, of which 33 were significantly reversed during SMF treatment. The SMF-reversed lipid metabolites were mainly located on triglyceride (TG), diacylglycerol (DG), phosphatidylcholine (PC), and lysophosphatidylcholine (LPC), which were involved in glycerolipid metabolism and glycerophospholipid metabolism. The expressions of pathway-related proteins lysophosphatidylcholine acyltransferase 1 (LPCAT1), phospholipase C (PLC), and diacylglycerol acyltransferase 2 (DGAT2) were further verified, which were in line with the lipidomics results. Network pharmacology combined with Western blot analysis further revealed that SMF could inhibit the expressions of AKT, HIF1α, EGFR, TNF-α, IL-6, and IL-1β to produce an antiliver fibrosis effect through regulating the PI3K-AKT/HIF1/EGFR and TNF signaling pathways, which was associated with lipid metabolism. Importantly, we identified quercetin, 1,2,8-trimethoxyxanthone, 8-hydroxy-1,3-dimethoxyxanthone, 1,2,6-trimethoxy-8-hydroxyxanthone, 1-hydroxy-2,3,5,7-tetramethoxyanthone, and bellidifolin as active compounds of SMF against liver fibrosis. The results provided valuable data and insights for the application of SMF against liver fibrosis and built a good foundation for elucidating the effective compounds of SMF and their potential molecular mechanisms. The work also demonstrated that the combination of lipidomics and network pharmacology was a promising tool to discover the in-depth mechanism of CHM.

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