【摘要】 为揭示炎症细胞模型的极性代谢组特征,该文选择RAW264.7细胞为研究载体,以LPS刺激诱导炎症细胞模型,进行细胞代谢组学的指纹分析。具体方法为:筛选、优化了细胞内极性代谢物的提取方法,建立了利用超高效液相色谱-四极杆飞行时间质谱（UPLC-Q-TOF/MS）进行细胞内代谢组的数据采集方法,采用正交偏最小二乘判别分析（OPLS-DA）进行数据处理,筛选并初步鉴定了17种差异代谢物。结果显示,采用MeOH-CHCl₃-H₂O（8∶1∶1）作为提取溶剂,色谱峰数目较多,细胞内极性代谢物提取效率较高,分析方法的稳定性较好;与正常细胞相比,炎症细胞的蛋白质代谢、糖代谢、核苷酸代谢等代谢通路受到扰动。该研究建立了基于UPLC-Q-TOF/MS的RAW264.7细胞代谢组学指纹分析方法,为揭示细胞炎症机制及抗炎药物机制研究奠定基础。更多还原

【Abstract】 In order to reveal the properties of polar metabolome in inflammatory cells,we selected LPS-induced RAW264.7 inflammatory cell models as the carrier for the research of metabolic fingerprint analysis.In this study,an ultra performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF/MS）-based metabolomics protocol was optimized for the extraction of polar metabolites from RAW264.7 cell line.Then orthogonal partial least squares discriminant analysis（OPLS-DA） was used to process the metabolic data,and finally,a total of 17 metabolites were selected and identified.The results showed that MeOHCHCl₃-H₂O（8∶1∶1） was chosen as the optimal extraction solvent to achieve higher number of chromatographic peaks,with the best relative extraction efficiency and stability.Comparing with the normal cells,the inflammatory cells presented an abnormal metabolism in protein,carbohydrate,nucleotide and phospholipids.In this study,a UPLC-Q-TOF/MS-based metabolomics protocol for the polar metabolites from RAW264.7 cell line was developed,which may provide important information for the study of mechanism of inflammation and the anti-inflammatory drugs.更多还原