Journal article
High-throughput metabolic state analysis: The missing link in integrated functional genomics of yeasts
The lack of comparable metabolic state assays severely limits understanding the metabolic changes caused by genetic or environmental perturbations. The present study reports the application of a novel derivatization method for metabolome analysis of yeast, coupled to data-mining software that achieve comparable throughput, effort and cost compared with DNA arrays.
Our sample workup method enables simultaneous metabolite measurements throughout central carbon metabolism and amino acid biosynthesis, using a standard GC-MS platform that was optimized for this Purpose. As an implementation proof-of-concept, we assayed metabolite levels in two yeast strains and two different environmental conditions in the context of metabolic pathway reconstruction.
We demonstrate that these differential metabolite level data distinguish among sample types, such as typical metabolic fingerprinting or footprinting. More importantly, we demonstrate that this differential metabolite level data provides insight into specific metabolic pathways and lays the groundwork for integrated transcription-metabolism studies of yeasts.
Language: | English |
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Publisher: | Portland Press Ltd. |
Year: | 2005 |
Pages: | 669-677 |
ISSN: | 14708728 and 02646021 |
Types: | Journal article |
DOI: | 10.1042/BJ20041162 |
AMDIS, automated mass spectra deconvolution and identification system Aerobiosis Amino Acids Anaerobiosis Carboxylic Acids FDA, Fisher discriminant analysis Gene Expression Profiling Genomics MCF, methyl chloroformate Mutation PCA, principal component analysis PPP, pentose phosphate pathway Saccharomyces cerevisiae Sensitivity and Specificity TCA, tricarboxylic acid fingerprint footprint metabolomics redox metabolism yeast