オーラルセッション
- 第3日 6月24日（金） 10:00～10:20 C会場（411，412）
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3C-O1-1000（3P-37） PDF
LC/HRMS/MSとin silico エピメタボライトデータベース (IEMDB) に基づく未知の親水性代謝物の包括的構造推定
Epimetabolites are defined as analogues of known metabolites with different substructures. The rapid development of high-resolution mass spectrometry (HRMS) and some data mining tools has contributed to detecting and identifying a few epimetabolites that could play an important role as biological functions. However, almost all epimetabolites have not been identified because a generally applicable method for the comprehensive annotation of epimetabolites had not been developed. In the present study, we have proposed an advanced methodology for comprehensive structural elucidation of unidentified hydrophilic metabolites by a combination of stable isotope labeling, unified HILIC/AEX/HRMS/MS analysis, data mining techniques, and metabolite annotation using in silico epimetabolite database (IEMDB). In fact, we successfully annotated 444 novel epimetabolite candidates in E. coli. Our method has several advantages over conventional techniques and represents a potentially useful tool for structural elucidation of comprehensive epimetabolites.