Plant Metabolomics by GC-MS and Differential Analysis
Metabolomics is a new genomics approach that aims at measuring all or a subset of metabolites in the cell. Several approaches to plant metabolomics are currently used in plant research. These include targeted analysis, metabolite profiling, and metabolic fingerprinting. Metabolic fingerprinting, unlike metabolite profiling, does not aim at separating or identifying all the metabolites present in the sample, but rather generates a fingerprint that characterizes a specific metabolic state of the plant system under investigation. This chapter describes the implementation of metabolic fingerprinting approach using gas chromatography coupled to mass spectrometry (GC-MS) and discriminant function analysis combined with genetic algorithm (GA-DFA). This approach enables the identification of specific metabolites that are biologically relevant, and which may go undetected if direct infusion-based fingerprinting approaches were used due to the sample complexity and matrix suppression effects.
Key wordsArabidopsis Plant metabolomics Polar metabolite Extraction Derivatization GC-MS Metabolic fingerprinting Metabolite profiling Targeted analysis Bioinformatics GA-DFA Genetic algorithm Discriminant function analysis
This work was funded by National Science Foundation grant 03122857 as part of the Arabidopsis 2010 Project.
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