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J Biomol Tech. 2010 September; 21(3 Suppl): S6.
PMCID: PMC2918200

Managing Complexity - How Many Platforms Do We Need for Metabolomics?

T. Kind, G. Wohlgemuth, M. Palazoglu, D.K. Barupal, and S. Shahbaz
University of California, Davis, Genome Center, Davis, CA, United States



Metabolomics has matured over the past 10 years. By combining different platforms, over 2,000 identified metabolites can be screened. At the UC Davis Genome Center Metabolomics Facility, two laboratories work towards advancing methods and reaching out services, the Fiehn research laboratory and the metabolomics core. We have a combined use of 11 mass spectrometers for which a range of SOPs and quality controls have been developed for (a) primary metabolism, (b) volatile metabolites, (c) lipidomics, (d) secondary metabolites and (e) metabolic polymers. Over 300 studies have been completed over the past 5 years which are stored and disseminated via the SetupX study design database and facilitated by the BinBase mass spectrometry repositories. Lipid identifications by nanoESI-ion trap MS/MS are based on Genedata's MS Refiner software and a novel cross-instrument library, the LipidBLAST tool that stores calculated MS/MS spectra of over 180,000 lipids based on fragmentation patterns of authentic standards. The FiehnLib libraries of over 1,000 primary metabolites authenticate identifications in GC-TOF platforms, in conjunction with BinBase and the Adams volatile MS library. Polymers in biofuel research are assessed by pyrolysis-GC/MS and the MIT-based SpectConnect tool. LC-ion trap, Qtrap and QTOF mass spectrometry are used for determining compounds that are not amenable by one of the above methods, such as cationic metabolites (SAM, betaine, SMM), metabolic active biomarkers (acylcarnitines) and other important metabolic classes (dietary phytochemicals, folates and glucuronides). Despite this progress, metabolomics still faces a number of analytical challenges: the need for accuracy in structural identifications and quantifications, increases in total peak capacities, improved data processing software and the need for standardized database repositories. Current efforts are presented as well as a discussion on experiences in the dual task of ‘research’ and ‘service’ for metabolomic facilities and how to meet outside expectations and financial constraints.

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