化学
质谱法
色谱法
高分辨率
分辨率(逻辑)
代谢组学
鉴定(生物学)
液相色谱-质谱法
人工智能
计算机科学
植物
遥感
生物
地质学
作者
Di Yu,Lina Zhou,Qiuhui Xuan,Lichao Wang,Xinjie Zhao,Xin Lü,Guowang Xu
标识
DOI:10.1021/acs.analchem.7b05471
摘要
Carnitines play important roles in fatty acid oxidation and branched chain amino acid metabolism. The disturbance of acylcarnitines is associated with occurrence and development of many diseases. Comprehensive acylcarnitine identification can greatly benefit their targeted detection, following disease differential diagnosis and possible mechanism study. In this study, we developed a novel strategy to identify as many acylcarnitines as possible based on liquid chromatography–high-resolution mass spectrometry (LC–HRMS). The layer–layer progressive strategy first integrated the initial full scan MS/data-dependent MS/MS monitoring (ddMS2) acquisition and the following parallel reaction monitoring (PRM) to analyze a pooled biological sample. Also 733 possible acylcarnitines were identified containing characteristic high-resolution MS/MS features. Further, accurate mass, retention rules, and HRMS/MS information were used to define subclasses and predict undetected acylcarnitine homologues in each subclass, leading to more acylcarnitines to our newly constructed database. As a result, 758 acylcarnitines were contained in the database, having exact mass, retention time, and MS/MS information, which is the most comprehensive list of acylcarnitines reported to date. Applying this database, 241, 515, and 222 acylcarnitines were rapidly and reliably annotated in human plasma, human urine, and rat liver tissue. This novel strategy enables large-scale identification of acylcarnitines, and a similar method can also be used for identification of other metabolites.
科研通智能强力驱动
Strongly Powered by AbleSci AI