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    基于质谱的脂质组学研究泽泻醇G对HepG2细胞脂肪累积模型中的脂质代谢的影响

    Investigation of the Effect of Alisol G on Lipid Metabolism in HepG2 Cells Fat Accumulation Model Using Mass Spectrometry Based Lipidomics

      摘要
    • 摘要:
      目的  采用脂质组学探讨泽泻醇G(alisol G，AG)在HepG2细胞脂肪累积模型中改善脂质代谢紊乱的作用机制。
      方法 利用游离脂肪酸(油酸∶棕榈酸=2∶1)构建HepG2细胞脂质累积模型，经AG干预后进行油红O染色，测定细胞内相对脂质含量、甘油三酯(triglyceride，TG)含量、总胆固醇(total cholesterol，TC)含量，采用UPLC-QTOF-MS/MS分析细胞脂质组的变化及脂质代谢通路的影响。通过网络药理学方法预测AG对HepG2细胞脂质代谢影响的作用机制，并用分子对接技术验证AG与关键靶点的结合能力。
      结果 5 µmol·L−1(P<0.05)和10 µmol·L−1(P<0.01) AG显著抑制了游离脂肪酸诱导的HepG2细胞脂肪累积模型中的脂质含量，显著降低了TG、TC水平(P<0.01)。脂质组学分析出16种潜在的差异脂质代谢物，包括甘油磷脂类、鞘脂类和甾醇脂类，主要通过甘油磷脂代谢通路影响HepG2细胞脂肪累积的过程。网络药理学分析得到PPARG、PPARA、ESR1、AKT1、AKT2、PIK3CA等核心靶点，提示这些靶点在AG改善脂质代谢紊乱过程中发挥着关键作用。分子对接结果显示AG与这些关键靶点的最低结合能均−6.0 kcal·mol−1，说明AG与关键靶点的亲和力高，具有较高药物活性。
      结论 AG改善了HepG2细胞脂肪累积模型中的脂肪累积，AG可能通过影响甘油磷脂代谢通路改善脂质代谢紊乱的潜力，主要特征差异脂质代谢物为甘油磷脂类、鞘脂类和甾醇脂类脂质，其机制还可能是通过AKT1、AKT2、PPARG、PPARA等多个核心靶点及PI3K-AKT等多种信号通路，发挥调节脂质代谢紊乱的作用。

       

      Abstract:
      OBJECTIVE To explore the mechanism of Alisol G(AG) in improving lipid metabolism disorder in HepG2 cells fat accumulation model using lipidomics.
      METHODS HepG2 cells fat accumulation model was constructed using free fatty acids(FFA) solution(oleic acid∶palmitic acid=2∶1). After intervention with AG, oil red O staining was performed, and the relative lipid content, triglycerides(TG) content, and total cholesterol(TC) content in the cells were measured, respectively. Ultra-high performance liquid chromatography-quadrupole time of flight-mass spectrometry/mass spectrometry(UPLC-QTOF-MS/MS) techniques was applied to analyze the changes in the cellular lipid composition and the effects of lipid metabolism pathways.The mechanism of the effect of AG on lipid metabolism of HepG2 cells was predicted by network pharmacology, and the binding ability of AG to key targets was verified by molecular docking technology.
      RESULTS 5 µmol·L−1(P<0.05) and 10 µmol·L−1(P<0.01) of AG significantly inhibited the lipid content in the FFA induced HepG2 cells fat accumulation model, and significantly reduced the levels of TG and TC(P<0.01). 16 potential differential lipid metabolites including glycerophospholipids, sphingolipids, and sterols, were identified through Lipidomics analysis, which mainly affect the process of fat accumulation in HepG2 cells through the glycerophospholipid metabolic pathway. Network pharmacologic analysis identified PPARG, PPARA, ESR1, AKT1, AKT2, PIK3CA and other key targets, suggesting that these targets play a key role in the improvement of lipid metabolism disorders by AG. Molecular docking results showed that the lowest binding energy between AG and these key targets was −6.0 kcal·mol−1, indicating that AG has high affinity with key targets and high drug activity.
      CONCLUSION Lipid deposit in the HepG2 cells fat accumulation model was alleviated by AG. AG might have the potential to improve lipid metabolism disorders by affecting the glycerophospholipid metabolism pathway. The main characteristic differential lipid metabolites were glycerophospholipids, sphingolipids, and sterol lipids. The mechanism may also play a role in regulating lipid metabolism disorders through multiple key targets such as AKT1, AKT2, PPARG, PPARA, and various signaling pathways such as PI3K-AKT.

       

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