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基于行波离子淌度质谱的代谢组学和脂质组学分析。

Metabolomics and lipidomics using traveling-wave ion mobility mass spectrometry.

机构信息

Center for Biomedicine, European Academy of Bolzano/Bozen, Bolzano, Italy.

Department of Biochemistry and Molecular &Cellular Biology, Georgetown University, Washington, DC, USA.

出版信息

Nat Protoc. 2017 Apr;12(4):797-813. doi: 10.1038/nprot.2017.013. Epub 2017 Mar 16.

Abstract

Metabolomics and lipidomics aim to profile the wide range of metabolites and lipids that are present in biological samples. Recently, ion mobility spectrometry (IMS) has been used to support metabolomics and lipidomics applications to facilitate the separation and the identification of complex mixtures of analytes. IMS is a gas-phase electrophoretic technique that enables the separation of ions in the gas phase according to their charge, shape and size. Occurring within milliseconds, IMS separation is compatible with modern mass spectrometry (MS) operating with microsecond scan speeds. Thus, the time required for acquiring IMS data does not affect the overall run time of traditional liquid chromatography (LC)-MS-based metabolomics and lipidomics experiments. The addition of IMS to conventional LC-MS-based metabolomics and lipidomics workflows has been shown to enhance peak capacity, spectral clarity and fragmentation specificity. Moreover, by enabling determination of a collision cross-section (CCS) value-a parameter related to the shape of ions-IMS can improve the accuracy of metabolite identification. In this protocol, we describe how to integrate traveling-wave ion mobility spectrometry (TWIMS) into traditional LC-MS-based metabolomic and lipidomic workflows. In particular, we describe procedures for the following: tuning and calibrating a SYNAPT High-Definition MS (HDMS) System (Waters) specifically for metabolomics and lipidomics applications; extracting polar metabolites and lipids from brain samples; setting up appropriate chromatographic conditions; acquiring simultaneously m/z, retention time and CCS values for each analyte; processing and analyzing data using dedicated software solutions, such as Progenesis QI (Nonlinear Dynamics); and, finally, performing metabolite and lipid identification using CCS databases and TWIMS-derived fragmentation information.

摘要

代谢组学和脂质组学旨在描绘生物样本中存在的广泛代谢物和脂质。最近,离子淌度谱(IMS)已被用于支持代谢组学和脂质组学应用,以促进复杂混合物分析物的分离和鉴定。IMS 是一种气相电泳技术,可根据离子的电荷、形状和大小在气相中分离离子。IMS 分离在几毫秒内发生,与微秒扫描速度的现代质谱(MS)兼容。因此,获取 IMS 数据所需的时间不会影响传统基于液相色谱(LC)-MS 的代谢组学和脂质组学实验的整体运行时间。将 IMS 添加到传统的基于 LC-MS 的代谢组学和脂质组学工作流程中已被证明可以提高峰容量、光谱清晰度和碎片特异性。此外,通过能够确定碰撞截面(CCS)值——与离子形状相关的参数——IMS 可以提高代谢物鉴定的准确性。在本方案中,我们描述了如何将行波离子淌度谱(TWIMS)集成到传统的基于 LC-MS 的代谢组学和脂质组学工作流程中。特别是,我们描述了以下程序:调整和校准 SYNAPT High-Definition MS(HDMS)系统(Waters),专门用于代谢组学和脂质组学应用;从脑样本中提取极性代谢物和脂质;设置适当的色谱条件;同时获取每个分析物的 m/z、保留时间和 CCS 值;使用专用软件解决方案(如 Progenesis QI(非线性动力学))处理和分析数据;最后,使用 CCS 数据库和 TWIMS 衍生的碎片信息进行代谢物和脂质鉴定。

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