In the field of metabolic engineering and functional genomics, methods for analysis of metabolic fluxes in the cell are attractive as they give an overview of the phenotypic response of the cells at the level of the active metabolic network. This is unlike several other high-throughput experimental techniques, which do not provide information about the integrated response a specific genetic modification has on the cellular function. In this study we have performed phenotypic characterization of several mutants of the yeast Saccharomyces cerevisiae through the use of experiments with (13)C-labelled glucose. Through GC-MS analysis of the (13)C incorporated into the amino acids of cellular proteins, it was possible to obtain quantitative information on the function of the central carbon metabolism in the different mutants. Traditionally, such labelling data have been used to quantify metabolic fluxes through the use of a suitable mathematical model, but here we show that the raw labelling data may also be used directly for phenotypic characterization of different mutant strains. Different glucose derepressed strains investigated employed are the disruption mutants reg1, hxk2, grr1, mig1 and mig1mig2 and the reference strain CEN.PK113-7D. Principal components analysis of the summed fractional labelling data show that deleting the genes HXK2 and GRR1 results in similar phenotype at the fluxome level, with a partial alleviation of glucose repression on the respiratory metabolism. Furthermore, deletion of the genes MIG1, MIG1/MIG2 and REG1 did not result in a significant change in the phenotype at the fluxome level.
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Evidence ID | Analyze ID | Gene/Complex | Systematic Name/Complex Accession | Qualifier | Gene Ontology Term ID | Gene Ontology Term | Aspect | Annotation Extension | Evidence | Method | Source | Assigned On | Reference |
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Evidence ID | Analyze ID | Gene | Gene Systematic Name | Phenotype | Experiment Type | Experiment Type Category | Mutant Information | Strain Background | Chemical | Details | Reference |
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Evidence ID | Analyze ID | Gene | Gene Systematic Name | Disease Ontology Term | Disease Ontology Term ID | Qualifier | Evidence | Method | Source | Assigned On | Reference |
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Evidence ID | Analyze ID | Regulator | Regulator Systematic Name | Target | Target Systematic Name | Direction | Regulation of | Happens During | Regulator Type | Direction | Regulation Of | Happens During | Method | Evidence | Strain Background | Reference |
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Site | Modification | Modifier | Source | Reference |
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Evidence ID | Analyze ID | Interactor | Interactor Systematic Name | Interactor | Interactor Systematic Name | Allele | Assay | Annotation | Action | Phenotype | SGA score | P-value | Source | Reference | Note |
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Evidence ID | Analyze ID | Interactor | Interactor Systematic Name | Interactor | Interactor Systematic Name | Assay | Annotation | Action | Modification | Source | Reference | Note |
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Complement ID | Locus ID | Gene | Species | Gene ID | Strain background | Direction | Details | Source | Reference |
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Evidence ID | Analyze ID | Dataset | Description | Keywords | Number of Conditions | Reference |
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