Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, Madrid, Spain.
Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, Madrid, Spain; Departamento de Ciencias Médicas Básicas, Facultad de Medicina, Universidad San Pablo-CEU, CEU Universities, Madrid, Spain.
J Lipid Res. 2024 Nov;65(11):100671. doi: 10.1016/j.jlr.2024.100671. Epub 2024 Oct 10.
Liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS)-based methods have become the gold standard methodology for the comprehensive profiling of the human plasma lipidome. However, both the complexity of lipid chemistry and LC-HRMS-associated data pose challenges to the characterization of this biological matrix. In accordance with the current consensus of quality requirements for LC-HRMS lipidomics data, we aimed to characterize the NIST® Standard Reference Material for Human Plasma (SRM 1950) using an LC-ESI(+/-)-MS method compatible with high-throughput lipidome profiling. We generated a highly curated lipid database with increased coverage, quality, and consistency, including additional quality assurance procedures involving adduct formation, within-method m/z evaluation, retention behavior of species within lipid chain isomers, and expert-driven resolution of isomeric and isobaric interferences. As a proof-of-concept, we showed the utility of our in-house LC-MS lipidomic database -consisting of 592 lipid entries- for the fast, comprehensive, and reliable lipidomic profiling of the human plasma from healthy human volunteers. We are confident that the implementation of this robust resource and methodology will have a significant impact by reducing data redundancy and the current delays and bottlenecks in untargeted plasma lipidomic studies.
基于液相色谱与高分辨质谱联用(LC-HRMS)的方法已成为全面分析人血浆脂质组的金标准方法。然而,脂质化学的复杂性和 LC-HRMS 相关数据给这种生物基质的特征描述带来了挑战。根据当前 LC-HRMS 脂质组学数据的质量要求共识,我们旨在使用与高通量脂质组分析兼容的 LC-ESI(+/-)-MS 方法对 NIST®人血浆标准参考物质(SRM 1950)进行特征描述。我们生成了一个高度优化的脂质数据库,具有更高的覆盖度、质量和一致性,包括涉及加合物形成、方法内 m/z 评估、脂质链异构体中物种保留行为以及专家驱动的同异位和同量异位干扰分辨率的额外质量保证程序。作为概念验证,我们展示了我们内部的 LC-MS 脂质组数据库(包含 592 个脂质条目)在快速、全面和可靠地分析健康人类志愿者血浆脂质组方面的实用性。我们相信,实施这一强大的资源和方法将通过减少数据冗余以及目前非靶向性血浆脂质组学研究中的延迟和瓶颈,产生重大影响。