通过 DMS shotgun 脂质组学分析哺乳动物脂质组。

Analysis of the Mammalian Lipidome by DMS Shotgun Lipidomics.

机构信息

Department of Biological Chemistry, David Geffen School of Medicine, University of California, Los Angeles, CA, USA.

UCLA Lipidomics Laboratory, Los Angeles, CA, USA.

出版信息

Methods Mol Biol. 2025;2855:357-372. doi: 10.1007/978-1-0716-4116-3_21.

DOI:10.1007/978-1-0716-4116-3_21

PMID:39354318

Abstract

Shotgun Lipidomics is a robust methodology for the characterization of the lipidome of complex biological samples. This assay is among the most quantitative lipidomics methods and is capable of surveying a wide breadth of lipid subclasses, both neutral and polar. The shortfalls of the technique include limitations in lipid species characterization and computationally demanding data analysis requiring isotopic and isobaric overlap correction. Differential Mobility Spectrometry (DMS) has demonstrated its utility in enabling acyl tail characterization within a Shotgun Lipidomics experiment. Here, we present a workflow for DMS Shotgun Lipidomics that measures 1400 possible lipid species. It utilizes the Shotgun Lipidomics Assistant (SLA) application, an open-source application that supervises the data analysis for an expansive Shotgun Lipidomics experiment.

摘要

shotgun 脂质组学是一种强大的方法，用于描述复杂生物样品的脂质组。该测定法是最定量的脂质组学方法之一，能够广泛检测中性和极性脂质亚类。该技术的缺点包括脂质种类特征的局限性以及需要同位素和等压重叠校正的计算要求高的数据分析。差分迁移率光谱法 (DMS) 已证明其在 shotgun 脂质组学实验中能够实现酰基尾部特征化的有效性。在这里，我们提出了一种用于 DMS shotgun 脂质组学的工作流程，该方法可测量 1400 种可能的脂质种类。它利用 shotgun 脂质组学助手 (SLA) 应用程序，这是一个开源应用程序，可监督广泛 shotgun 脂质组学实验的数据分析。