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 MeOH-CHCl3-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.
Keywords: inflammatory cells; metabolic fingerprint analysis; metabolomics; orthogonal partial least squares discriminant analysis (OPLS-DA); ultra performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry(UPLC-Q-TOF/MS).
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