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烷基甘油分析的伪靶向脂质组学方法的开发与应用。

Development and application of a pseudotargeted lipidomics method for alkylglycerol analysis.

机构信息

State Key Laboratory of Food Science and Resources, School of Food Science and Technology, Collaborative Innovation Center of Food Safety and Quality Control in Jiangsu Province, Jiangnan University, Wuxi, China.

Hyproca Nutrition Co., Ltd. Changsha, China; Ausnutria Dairy (China) Co., Ltd, China.

出版信息

Food Chem. 2024 Mar 30;437(Pt 2):137926. doi: 10.1016/j.foodchem.2023.137926. Epub 2023 Nov 7.

Abstract

Alkylglycerols (1-O-alkyl-sn-glycerols) are microscale but critical lipids in foods. Conventional lipidomics analysis often loses sight of alkylglycerol analysis. In this study, we developed a high coverage pseudotargeted lipidomics method for analyzing alkylglycerols. The developed method integrated the advantages of GC-MS and LC-MS to profile alkylglycerol-type ether lipids comprehensively, with the help of a data processing Dart package termed FFIMA (Feature Fragments Information Matching Algorithm). The developed method exhibited competitive superiority to conventional lipidomics, such as wider coverage and higher accuracy. The validated method was assessed by three aquatic products and three milks. A total of 25 alkylglycerols, 107 diacylglycerol ethers, 21 monoacylglycerol ethers, 28 alkylglycerol-type ether phospholipids, and 35 plasmalogens were identified in the six foods. The results demonstrated that this method offers a comprehensive analysis of a wide spectrum of alkylglycerols.

摘要

烷基甘油(1-O-烷基-sn-甘油)是食品中微量但关键的脂质。传统的脂质组学分析往往忽略了烷基甘油分析。在本研究中,我们开发了一种高覆盖率的伪靶向脂质组学方法来分析烷基甘油。该方法集成了 GC-MS 和 LC-MS 的优势,借助一种名为 FFIMA(特征片段信息匹配算法)的数据处理 Dart 包,全面分析烷基甘油型醚脂质。开发的方法与传统脂质组学相比具有竞争优势,例如更广泛的覆盖范围和更高的准确性。该方法通过三种水产品和三种牛奶进行了验证。在这六种食品中总共鉴定出 25 种烷基甘油、107 种二酰基甘油醚、21 种单酰基甘油醚、28 种烷基甘油型醚磷脂和 35 种溶血磷脂。结果表明,该方法可全面分析广泛谱的烷基甘油。

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