J Pharm Biomed Anal 2019 Jul 12;171:171-179. Epub 2019 Apr 12.
School of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, 210023, China; Jiangsu Collaborative Innovation Center of Chinese Medicinal Resources Industrialization, and National and Local Collaborative Engineering Center of Chinese Medicinal Resources Industrialization and Formulae Innovative Medicine, Nanjing University of Chinese Medicine, Nanjing, 210023, China.
Energy synthesis in aerobic organisms relies on two major metabolic pathways, i.e. tricarboxylic acid (TCA) cycle and glycolysis, the metabolites of which are highly affected by many diseases. Cells are the basic unit of the organism and have independent, ordered and self-controlled metabolic systems. Therefore, it is necessary to quantify intracellular metabolites in TCA cycle and glycolysis. In this study, we established a repeatable gas chromatography-tandem mass spectrometry (GC-MS/MS) method with selected reaction monitoring (SRM) mode for simultaneous quantification of several primary metabolites in these two pathways, including glucose, 3-phosphoglycerate, phosphoenolpyruvate (PEP), pyruvate, lactate, citrate, cis-aconitate, isocitrate, α-ketoglutarate, succinate, fumarate and malate. There are many solvents to extract the metabolites in these two pathways, however, which one is more effective still remains unclear. Sample pretreatment was optimized for solvent types and volumes to advance the extraction efficiency of metabolites. 500 μL of 75% methanol-methyl tert-butyl ether (MTBE) was finally selected for the extraction of targeted metabolites in cells due to its highest extraction efficiency. Activated carbon as an effective adsorbent was successfully applied to the removal of endogenous targeted metabolites in cells for getting the analyte-free surrogate matrices. A series of methodological studies verified the validity of this optimized approach which was applied to quantify and compare the targeted metabolites in three common hepatic cells. The developed GC-MS/MS method provided a better way to determine the metabolites of energy metabolism in cellular metabolomics, facilitating the application of targeted quantification metabolomics to precisely discover the metabolic alterations.