ABSTRACT
The aim of metabolomics is the comprehensive and global analysis of the metabolome, which is de ned as all metabolites produced in a cell or organism. The innovative methodology and techniques associated with metabolomics have advanced research on the metabolism of plants, humans, animals, and bacteria. The results of metabolome analysis are expressed as metabolite ngerprint data, which represent the metabolite composition and include unique biomarker characteristics for the samples. Moreover, metabolomics can be used in conjunction with complementary methods such as transcriptomics, proteomics, and other biological studies in multi-omics studies; the biosynthesis of metabolites as regulated by enzymes; and transcription factors that are encoded by genes.1-3
The rst step of metabolomics data collection and analysis involves acquisition of metabolome ngerprints. These are obtained by chemical analysis, performed in order to achieve a metabolite
27.1 General Strategy for Metabolome Analysis ......................................................................... 471 27.2 Metabolomics Data Collection Guidelines ........................................................................... 472
27.2.1 Basics of Sample Preparation ................................................................................... 472 27.2.2 Analyzer Selection for Comprehensive Metabolite Analysis ................................... 472
27.2.2.1 MS .............................................................................................................. 473 27.2.2.2 GC/MS ....................................................................................................... 474 27.2.2.3 LC/MS ....................................................................................................... 475 27.2.2.4 NMR Spectroscopy .................................................................................... 476 27.2.2.5 Other Analyzers ......................................................................................... 477
27.3 Guidelines for Multivariate Analysis of Analytical Chemistry Data ................................... 477 27.3.1 Preprocessing of Chemical Analysis Data ............................................................... 479 27.3.2 Unsupervised Learning ............................................................................................ 479
27.3.2.1 PCA ............................................................................................................ 479 27.3.2.2 SOM ...........................................................................................................480 27.3.2.3 HCA ...........................................................................................................480
