化学
轨道轨道
离子阱
三七
质谱法
碰撞诱导离解
离解(化学)
色谱法
四极离子阱
电喷雾电离
分析化学(期刊)
串联质谱法
有机化学
医学
病理
替代医学
作者
Xiaojian Shi,Wenzhi Yang,Yong Huang,Jinjun Hou,Shi Qiu,Changliang Yao,Zijin Feng,Wenlong Wei,Wanying Wu,De‐an Guo
标识
DOI:10.1016/j.chroma.2018.08.026
摘要
Specific analytical approaches that enable untargeted profiling of modified metabolites are in great need. An untargeted profiling strategy, by integrating in-source collision-induced dissociation (ISCID)-MS1, mass tag-MS2, and neutral loss scan-MS3, is established on a linear ion-trap/Orbitrap mass spectrometer coupled to ultra-high performance liquid chromatography. This strategy is applied to screen malonylginsenosides from three reputable Panax species (P. ginseng, P. quinquefolius, and P. notoginseng). In light of the preferred neutral elimination of CO2 and entire malonyl substituent (C3H2O3) in the negative electrospray ionization mode, a pseudo-neutral loss scan (PNL) method was established by applying ISCID energy 40 V in MS1, mass tag 43.9898 Da oriented CID-MS2 at normalized collision energy (NCE) 30%, and neutral loss 43.9898 Da-triggered high-energy C-trap dissociation-MS3 at NCE 70%. The PNL approach achieved a high coverage of targeted malonylginsenosides but introduced less false positives. It displayed comparable performance to a precursor ions list-driven targeted approach we have reported in the profiling and characterization of malonylginsenosides, but could avoid complex data processing. Totally 178 malonylginsenosides were characterized from the roots, leaves, and flower buds of P. ginseng, P. quinquefolius, and P. notoginseng, and most of them possess potentially new structures. The compositions of malonylginsenosides identified from these three Panax species are similar, and only malonylginsenoside Rb2 and some minor may have potential chemotaxonomic significance. In conclusion, we provide a potent analytical strategy for the direct and efficient screening of modified metabolites, which may have broad applications in the fields of metabolomics, drug metabolism, and natural product research.
科研通智能强力驱动
Strongly Powered by AbleSci AI