不饱和度
化学
质谱法
离子迁移光谱法
串联质谱法
脂类学
臭氧分解
色谱法
双键
三级四极质谱仪
分析化学(期刊)
选择性反应监测
有机化学
生物化学
作者
Berwyck L. J. Poad,Xueyun Zheng,Todd W. Mitchell,Richard Smith,Erin Baker,Stephen J. Blanksby
标识
DOI:10.1021/acs.analchem.7b04091
摘要
One of the most significant challenges in contemporary lipidomics lies in the separation and identification of lipid isomers that differ only in site(s) of unsaturation or geometric configuration of the carbon-carbon double bonds. While analytical separation techniques including ion mobility spectrometry (IMS) and liquid chromatography (LC) can separate isomeric lipids under appropriate conditions, conventional tandem mass spectrometry cannot provide unequivocal identification. To address this challenge, we have implemented ozone-induced dissociation (OzID) in-line with LC, IMS, and high resolution mass spectrometry. Modification of an IMS-capable quadrupole time-of-flight mass spectrometer was undertaken to allow the introduction of ozone into the high-pressure trapping ion funnel region preceding the IMS cell. This enabled the novel LC-OzID-IMS-MS configuration where ozonolysis of ionized lipids occurred rapidly (10 ms) without prior mass-selection. LC-elution time alignment combined with accurate mass and arrival time extraction of ozonolysis products facilitated correlation of precursor and product ions without mass-selection (and associated reductions in duty cycle). Unsaturated lipids across 11 classes were examined using this workflow in both positive and negative ion modalities, and in all cases, the positions of carbon-carbon double bonds were unequivocally assigned based on predictable OzID transitions. Under these conditions, geometric isomers exhibited different IMS arrival time distributions and distinct OzID product ion ratios providing a means for discrimination of cis/trans double bonds in complex lipids. The combination of OzID with multidimensional separations shows significant promise for facile profiling of unsaturation patterns within complex lipidomes including human plasma.
科研通智能强力驱动
Strongly Powered by AbleSci AI