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一种适用于高通量、全面脂质组学的 DMS shotgun 脂质组学工作流程应用程序。

A DMS Shotgun Lipidomics Workflow Application to Facilitate High-Throughput, Comprehensive Lipidomics.

机构信息

Department of Biological Chemistry, University of California, Los Angeles, California 90095, United States.

UCLA Lipidomics Laboratory, University of California, Los Angeles, California 90095, United States.

出版信息

J Am Soc Mass Spectrom. 2021 Nov 3;32(11):2655-2663. doi: 10.1021/jasms.1c00203. Epub 2021 Oct 12.

Abstract

Differential mobility spectrometry (DMS) is highly useful for shotgun lipidomic analysis because it overcomes difficulties in measuring isobaric species within a complex lipid sample and allows for acyl tail characterization of phospholipid species. Despite these advantages, the resulting workflow presents technical challenges, including the need to tune the DMS before every batch to update compensative voltages settings within the method. The Sciex Lipidyzer platform uses a Sciex 5500 QTRAP with a DMS (SelexION), an LC system configured for direction infusion experiments, an extensive set of standards designed for quantitative lipidomics, and a software package (Lipidyzer Workflow Manager) that facilitates the workflow and rapidly analyzes the data. Although the Lipidyzer platform remains very useful for DMS-based shotgun lipidomics, the software is no longer updated for current versions of Analyst and Windows. Furthermore, the software is fixed to a single workflow and cannot take advantage of new lipidomics standards or analyze additional lipid species. To address this multitude of issues, we developed Shotgun Lipidomics Assistant (SLA), a Python-based application that facilitates DMS-based lipidomics workflows. SLA provides the user with flexibility in adding and subtracting lipid and standard MRMs. It can report quantitative lipidomics results from raw data in minutes, comparable to the Lipidyzer software. We show that SLA facilitates an expanded lipidomics analysis that measures over 1450 lipid species across 17 (sub)classes. Lastly, we demonstrate that the SLA performs isotope correction, a feature that was absent from the original software.

摘要

差分迁移谱(DMS)在 shotgun 脂质组学分析中非常有用,因为它克服了在复杂脂质样品中测量等质异位点的困难,并允许对磷脂物种的酰基尾进行特征化。尽管有这些优势,但由此产生的工作流程存在技术挑战,包括需要在每次批量之前对 DMS 进行调谐,以更新方法内的补偿电压设置。Sciex Lipidyzer 平台使用配备 DMS(SelexION)的 Sciex 5500 QTRAP、配置用于定向注入实验的 LC 系统、一套专为定量脂质组学设计的广泛标准以及一个软件包(Lipidyzer Workflow Manager),该软件包可简化工作流程并快速分析数据。尽管 Lipidyzer 平台仍然非常适用于基于 DMS 的 shotgun 脂质组学,但该软件不再针对 Analyst 和 Windows 的当前版本进行更新。此外,该软件固定于单个工作流程,无法利用新的脂质组学标准或分析其他脂质物种。为了解决这些问题,我们开发了 Shotgun Lipidomics Assistant(SLA),这是一个基于 Python 的应用程序,可简化基于 DMS 的脂质组学工作流程。SLA 为用户提供了在添加和减去脂质和标准 MRM 方面的灵活性。它可以在几分钟内从原始数据报告定量脂质组学结果,与 Lipidyzer 软件相当。我们表明,SLA 促进了扩展的脂质组学分析,可测量超过 17 个(亚)类别的 1450 多种脂质物种。最后,我们证明 SLA 执行同位素校正,这是原始软件中缺失的功能。

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