代谢组学
衍生化
气相色谱-质谱法
化学
色谱法
代谢组
代谢物
质谱法
计算生物学
生物
生物化学
作者
Matthaios-Emmanouil P. Papadimitropoulos,Catherine G. Vasilopoulou,Christoniki Maga‐Nteve,Maria I. Klapa
标识
DOI:10.1007/978-1-4939-7643-0_9
摘要
Untargeted metabolomics refers to the high-throughput analysis of the metabolic state of a biological system (e.g., tissue, biological fluid, cell culture) based on the concentration profile of all measurable free low molecular weight metabolites. Gas chromatography-mass spectrometry (GC-MS), being a highly sensitive and high-throughput analytical platform, has been proven a useful tool for untargeted studies of primary metabolism in a variety of applications. As an omic analysis, GC-MS metabolomics is a multistep procedure; thus, standardization of an untargeted GC-MS metabolomics protocol requires the integrated optimization of pre-analytical, analytical, and computational steps. The main difference of GC-MS metabolomics compared to other metabolomics analytical platforms, including liquid chromatography-MS, is the need for the derivatization of the metabolite extracts into volatile and thermally stable derivatives, the latter being quantified in the metabolic profiles. This analytical step requires special care in the optimization of the untargeted GC-MS metabolomics experimental protocol. Moreover, both the derivatization of the original sample and the compound fragmentation that takes place in GC-MS impose specialized GC-MS metabolomic data identification, quantification, normalization and filtering methods. In this chapter, we describe the integrated protocol of untargeted GC-MS metabolomics with both the analytical and computational steps, focusing on the GC-MS specific parts, and provide details on any sample depending differences.
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