Metabolic Profiling Methods and Protocols
At the intersection of metabolite analysis, metabolic fingerprinting, and metabolomics, the study of metabolic profiling has evolved steadily over the course of time as have the methods and technologies involved in its study. In Metabolic Profiling: Metho
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1. Introduction Gas chromatography coupled to mass spectrometry (GC-MS) has been regarded as the gold standard for analysing many compounds (lipids, drug metabolites, and environmental contaminants), as well as for forensic science. One of the advantages of GC-MS is that identification of detected species is based on both a retention time and a mass spectrum (a compound’s specific fragmentation pattern). Compounds produce reproducible T.O. Metz (ed.), Metabolic Profiling, Methods in Molecular Biology 708, DOI 10.1007/978-1-61737-985-7_11, © Springer Science+Business Media, LLC 2011
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fragmentation patterns when ionized by a fixed electron voltage (usually –70 eV). Thus, the fragmentation spectra obtained by GC-MS are not instrument dependent and allow for the creation of databases and the sharing of data between users, making the technique particularly valuable. In addition, GC-MS allows for quantitative detection of analytes. In classical methods, measuring either a single compound or a set of chemically related substances (such as short chain fatty acids or amino acids), there are clearly established protocols for sample treatment and for quantification using the appropriate standards. In the last few years (1), a new analytical strategy has evolved for obtaining a global view of the metabolic status of an organism. “Metabo(l/n)omics” is an approach capable of generating a comprehensive data set of metabolites. This is not only a new terminology but a new approach to the analytical problem with very different analytical requirements. In an “omics” methodology, the expectation is that the response pattern(s) of numerous analytes, both known and unknown, is reflective of a biological condition, and the comprehensive nature of the data set enables evaluation of systemic response. The broader scope of the analysis forces compromises in method development (e.g. sample extraction, cleanup, derivatization, chromatography) and requires flexibility in accuracy criteria for specific metabolites. On the one hand, GC-MS is far from the ideal of metabolomics; not only is it limited to compounds that either are volatile or can be made volatile through the derivatization process, but also all nonvolatile compounds must be carefully removed from the sample before analysis, which requires demanding sample treatment. However, on the other hand, it is clear that no single analytical platform is capable of detecting the whole set of metabolites in a biological sample. 1 H-NMR, capable of measuring intact samples and, in principle, ideal, is limited by a bias towards analytes with medium to high concentrations. In contrast, GC-MS is highly sensitive and reproducible and permits working with standard libraries for identification of detected species (2); it is widely used, although only a certain subset of compounds will be analysed. This chapter describes and explains guidelines for metabolite fingerprinting of plasma and urine by GC-MS. It gives experimental details on basic steps such as sample collectio
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