Literature DB >> 19320491

High-throughput quantitative metabolomics: workflow for cultivation, quenching, and analysis of yeast in a multiwell format.

Jennifer Christina Ewald1, Stéphanie Heux, Nicola Zamboni.   

Abstract

Metabolomics is a founding pillar of quantitative biology and a valuable tool for studying metabolism and its regulation. Here we present a workflow for metabolomics in microplate format which affords high-throughput and yet quantitative monitoring of primary metabolism in microorganisms and in particular yeast. First, the most critical step of rapid sampling was adapted to a multiplex format by using fritted 96-well plates for cultivation, which ensure fast sample transfer and permit us to use well-established quenching in cold solvents. Second, extensive optimization of large-volume injection on a GC/TOF instrument provided the sensitivity necessary for robust quantification of 30 primary metabolites in 0.6 mg of yeast biomass. The metabolome profiles of baker's yeast cultivated in fritted well plates or in shake flasks were equivalent. Standard deviations of measured metabolites were between 10% and 50% within one plate. As a proof of principle we compared the metabolome of wild-type Saccharomyces cerevisiae and the single-deletion mutant Delta sdh1, which were clearly distinguishable by a 10-fold increase of the intracellular succinate concentration in the mutant. The described workflow allows the production of large amounts of metabolome samples within a day, is compatible with virtually all liquid extraction protocols, and paves the road to quantitative screens.

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Year:  2009        PMID: 19320491     DOI: 10.1021/ac900002u

Source DB:  PubMed          Journal:  Anal Chem        ISSN: 0003-2700            Impact factor:   6.986


  27 in total

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Review 7.  Review of recent developments in GC-MS approaches to metabolomics-based research.

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8.  Metabolomic high-content nuclear magnetic resonance-based drug screening of a kinase inhibitor library.

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9.  MSEA: a web-based tool to identify biologically meaningful patterns in quantitative metabolomic data.

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10.  Tradeoff between enzyme and metabolite efficiency maintains metabolic homeostasis upon perturbations in enzyme capacity.

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