Optimization of metabolite extraction of human vein tissue for ultra performance liquid chromatography-mass spectrometry and nuclear magnetic resonance-based untargeted metabolic profiling

Abstract

Human vein tissue is an important matrix to examine when investigating vascular diseases with respect to understanding underlying disease mechanisms. Here, we report the development of an extraction protocol for multi-platform metabolic profiling of human vein tissue. For the first stage of the optimization, two different ratios of methanol/water and 5 organic solvents – namely dichloromethane, chloroform, isopropanol, hexane and methyl tert-butyl ether (MTBE) solutions with methanol – were tested for polar and organic compound extraction, respectively. The extraction output was assessed using ¹H Nuclear Magnetic Resonance (NMR) spectroscopy and a panel of Ultra Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS) methodologies. On the basis of the reproducibility of extraction replicates and metabolic coverage, the optimal aqueous (methanol/water) and organic (MTBE/methanol) solvents identified from the first stage were used in a sequential approach for metabolite extraction, altering the order of solvent-mixture addition. The combination of organic metabolite extraction with MTBE/methanol (3 : 1) followed by extraction of polar compounds with methanol/water (1 : 1) was shown to be the best method for extracting metabolites from human vein tissue in terms of reproducibility and number of signals detected and could be used as a single extraction procedure to serve both NMR and UPLC-MS analyses. Molecular classes such as triacylglycerols, phosphatidylcholines, phosphatidylethanolamines, sphingolipids, purines, and pyrimidines were reproducibly extracted. This study enabled an optimal extraction protocol for robust and more comprehensive metabolome coverage for human vein tissue. Many of the physiological and pathological processes affecting the composition of human vein tissue are common to other tissues and hence the extraction method developed in this study can be generically applied.