Comprehensive and high-coverage glycerophospholipidomic analysis based on iterative quadrupole time-of-flight mass spectrometry and its application in cerebral ischemia-reperfusion injury.

IF 3.8 2区 化学 Q1 BIOCHEMICAL RESEARCH METHODS
Biqiong Qu, Menghan Feng, Lirong Liu, Shiyu Cong, Shengnan Cai, Tengteng Wang, Yun Qiao, Lixia Shi, Jie Liu, Hongbin Xiao
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Abstract

Glycerophospholipids play important roles in iron-induced lipid peroxidation during cerebral ischemia-reperfusion, making it essential to investigate changes in their varieties and concentrations under these conditions. However, the wide range of glycerophospholipid contents, particularly the low-abundance species in actual biological samples, posed a challenge for comprehensive analysis. In this study, an iterative quadrupole time-of-flight mass spectrometry (Q-ToF-MS/MS) method was established with the aim of comprehensively detecting glycerophospholipids. This method was a data acquisition strategy implemented through iterative analyses. In each iteration, ions detected in previous runs were excluded, allowing low-abundance glycerophospholipids that were missed by the usual analysis to be extensively detected by a simplified operational process. Using this strategy, 254 glycerophospholipids including 157 PCs, 67 PEs, 19 PGs, 9 PIs, 7 PSs and 5 PAs in rat brain samples were identified after four iterations, and the number of glycerophospholipid species increased by 93.9% compared to a single assay, significantly enhancing the coverage of glycerophospholipid detection. Furthermore, the characteristic fragmentation patterns of six glycerophospholipid subclasses were systematically summarized to improve the accuracy of qualitative identification. In addition, these patterns were also used to construct an ion pair database containing 254 glycerophospholipids, enabling targeted multiple reaction monitoring (MRM) analysis under the optimized high-performance liquid chromatography-tandem triple quadrupole mass spectrometry (HPLC-QQQ-MS/MS) conditions. By comparing the changed glycerophospholipids of rat brains from the normal and cerebral ischemia-reperfusion injury groups, 29 glycerophospholipids were recognized as the potential biomarkers for cerebral ischemia-reperfusion injury, among which nine glycerophospholipids were particularly detected by four iterations. Overall, this iterative MS/MS approach extensively expanded the coverage of low-abundance components, and has been proven to be an effective approach in biomarker screening of cerebral ischemia-reperfusion injury.

基于迭代四极杆飞行时间质谱的全面高覆盖率甘油磷脂组学分析及其在脑缺血再灌注损伤中的应用。
甘油磷脂在脑缺血-再灌注期间铁诱导的脂质过氧化中起重要作用,因此研究其种类和浓度在这些条件下的变化是必要的。然而,甘油磷脂含量的大范围,特别是在实际生物样品中的低丰度物种,对综合分析提出了挑战。本研究建立了一种迭代四极杆飞行时间质谱(Q-ToF-MS/MS)方法,目的是全面检测甘油磷脂。该方法是一种通过迭代分析实现的数据采集策略。在每次迭代中,排除之前运行中检测到的离子,允许通过简化的操作流程广泛检测常规分析遗漏的低丰度甘油磷脂。采用该方法,经过4次迭代,共鉴定出大鼠脑样品中的157种pc、67种pe、19种pg、9种pi、7种ps和5种PAs等254种甘油磷脂,比单次检测增加了93.9%,显著提高了甘油磷脂检测的覆盖率。此外,系统总结了6个甘油磷脂亚类的特征破碎模式,以提高定性鉴定的准确性。此外,还利用这些图谱构建了包含254种甘油磷脂的离子对数据库,在优化的高效液相色谱-串联三重四极杆质谱(HPLC-QQQ-MS/MS)条件下实现了靶向多反应监测(MRM)分析。通过比较正常组和脑缺血再灌注损伤组大鼠脑内甘油磷脂的变化,发现29种甘油磷脂可作为脑缺血再灌注损伤的潜在生物标志物,其中9种甘油磷脂通过4次迭代被特异性检测到。总的来说,这种迭代的MS/MS方法广泛地扩展了低丰度成分的覆盖范围,并已被证明是脑缺血再灌注损伤生物标志物筛选的有效方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
8.00
自引率
4.70%
发文量
638
审稿时长
2.1 months
期刊介绍: Analytical and Bioanalytical Chemistry’s mission is the rapid publication of excellent and high-impact research articles on fundamental and applied topics of analytical and bioanalytical measurement science. Its scope is broad, and ranges from novel measurement platforms and their characterization to multidisciplinary approaches that effectively address important scientific problems. The Editors encourage submissions presenting innovative analytical research in concept, instrumentation, methods, and/or applications, including: mass spectrometry, spectroscopy, and electroanalysis; advanced separations; analytical strategies in “-omics” and imaging, bioanalysis, and sampling; miniaturized devices, medical diagnostics, sensors; analytical characterization of nano- and biomaterials; chemometrics and advanced data analysis.
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