Nonbiased Approaches in Metabolomics

In what many consider to be a landmark publication on metabolomics, Fiehn et al. (2000) state it is crucial to perform unbiased (metabolite) analyses in order to define precisely the biochemical function of plant metabolism. The authors argue that for metabolomics/metabolite profiling to become a robust and sensitive method suited to automation, a mature technology such as gas chromatography-mass spectrometry (GC-MS) is required as an analytical technique. The authors go on to describe a simple sample preparation and analysis regime that allowed for the detection and quantification of more than 300 compounds from a single-leaf sample extract. 

Of course, in addition to the requirement for an unbiased extraction methodology, it is imperative that all enzymic activity is quenched throughout the extraction and sample preparation. Typically, this is assumed to be the case when extracting in organic solvents, although numerous enzymes may retain activity in such environments. The physical nature of the samples themselves has an impact upon the efficiency of extraction of metabolites. For example, eukaryotic and prokaryotic samples behave very differently during the several steps of classic sample preparation methods. Even within the eukaryotes alone, there is a vast diversity of cellular structures that would seem to make it imprudent to blindly adopt protocols that were devised for other organisms or tissues. 

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