Miyagawa Hiromi, Bamba Takeshi
GL Sciences Inc., 237-2 Sayamagahara, Iruma, Saitama 358-0032, Japan.
Research Center for Transomics Medicine, Medical Institute of Bioregulation, Kyusyu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan.
J Biosci Bioeng. 2019 Feb;127(2):160-168. doi: 10.1016/j.jbiosc.2018.07.015. Epub 2018 Oct 11.
The gas chromatography/mass spectrometry (GC/MS)-based metabolomics requires a two-step derivatization procedure consisting of oximation and silylation. However, due to the incomplete derivatization and degeneration of the metabolites, good repeatability is difficult to obtain during the batch derivatization, as the time between completing the derivatization process and GC analysis differs from sample to sample. In this research, we successfully obtained good repeatability for the peak areas of 52 selected metabolites by sequential derivatization and interval injection, in which the oximation and silylation times were maintained at constant values. In addition, the derivatization times and amount of reagents employed were varied to confirm that the optimal derivatization conditions differed for the various metabolites. In conventional batch derivatization, six metabolites, viz. glutamine, glutamic acid, histidine, alanine, asparagine, and tryptophan, exhibited fluctuations in their peak areas. Indeed, we found that for all six metabolites these differences originated from the silylation process, while the variations for glutamine and glutamic acid were related to the oximation process.
基于气相色谱/质谱联用（GC/MS）的代谢组学需要两步衍生化程序，包括肟化和硅烷化。然而，由于代谢物衍生化不完全和降解，在批量衍生化过程中难以获得良好的重复性，因为完成衍生化过程与GC分析之间的时间因样品而异。在本研究中，我们通过顺序衍生化和间隔进样成功获得了52种选定代谢物峰面积的良好重复性，其中肟化和硅烷化时间保持恒定。此外，改变衍生化时间和所用试剂的量，以确认不同代谢物的最佳衍生化条件不同。在传统的批量衍生化中，六种代谢物，即谷氨酰胺、谷氨酸、组氨酸、丙氨酸、天冬酰胺和色氨酸，其峰面积出现波动。实际上，我们发现对于所有六种代谢物，这些差异都源于硅烷化过程，而谷氨酰胺和谷氨酸的变化与肟化过程有关。
