Gas Chromatography-Mass Spectrometry (GC-MS)-Based Metabolomics
Gas Chromatography-Mass Spectrometry (GC-MS)-Based Metabolomics
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DOI：
10.1007/978-1-61737-985-7_11
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发表时间：
2011-01-01
期刊：
影响因子：
--
通讯作者：
Barbas, Coral
中科院分区：
文献类型：
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作者：
Garcia, Antonia;Barbas, Coral
代谢指纹是代谢组学的主要工具，是一种非靶向方法，其中所有可检测的峰（或信号），包括来自未知分析物的峰，都被认为是建立样本分类的依据。经过模式比较，这些信号在响应特定情况下的调查被确定，以获得生物学的洞察力。为此，气相色谱-质谱法（GC-MS）有一个缺点，即只能分析挥发性化合物或衍生化后可挥发的化合物，而衍生化通常需要大量的样品处理。然而，一旦分析集中在低分子量代谢物上，GC-MS是高效、敏感和可重复性好的。此外，它是定量的，其化合物鉴定能力优于其他分离技术，因为GC-MS仪器获得的质谱具有可重复的碎片模式，这允许创建公共数据库。本章描述了利用GC-MS在血浆和尿液中进行代谢指纹（即小分子的综合分析）的成熟方案。还将提供关于后续数据预处理、模式识别和标记物识别的指南。
Metabolic fingerprinting, the main tool in metabolomics, is a non-targeted methodology where all detectable peaks (or signals), including those from unknown analytes, are considered to establish sample classification. After pattern comparison, those signals changing in response to a specific situation under investigation are identified to gain biological insight. For this purpose, gas chromatography-mass spectrometry (GC-MS) has a drawback in that only volatile compounds or compounds that can be made volatile after derivatization can be analysed, and derivatization often requires extensive sample treatment. However, once the analysis is focused on low molecular weight metabolites, GC-MS is highly efficient, sensitive, and reproducible. Moreover, it is quantitative, and its compound identification capabilities are superior to other separation techniques because GC-MS instruments obtain mass spectra with reproducible fragmentation patterns, which allow for the creation of public databases. This chapter describes well-established protocols for metabolic fingerprinting (i.e. the comprehensive analysis of small molecules) in plasma and urine using GC-MS. Guidelines will also be provided regarding subsequent data pre-treatment, pattern recognition, and marker identification.