Tradeoff between enzyme and metabolite efficiency maintains metabolic homeostasis upon perturbations in enzyme capacity
Copyright policy )Tradeoff between enzyme and metabolite efficiency maintains metabolic homeostasis upon perturbations in enzyme capacity
What is the relationship between enzymes and metabolites, the two major constituents of metabolic networks? We propose three alternative relationships between enzyme capacity and metabolite concentration alterations based on a Michaelis–Menten kinetic; that is enzyme capacities, metabolite concentrations, or both could limit the metabolic reaction rates. These relationships imply different correlations between changes in enzyme capacity and metabolite concentration, which we tested by quantifying metabolite, transcript, and enzyme abundances upon local (single‐enzyme modulation) and global ( GCR2 transcription factor mutant) perturbations in Saccharomyces cerevisiae . Our results reveal an inverse relationship between fold‐changes in substrate metabolites and their catalyzing enzymes. These data provide evidence for the hypothesis that reaction rates are jointly limited by enzyme capacity and metabolite concentration. Hence, alteration in one network constituent can be efficiently buffered by converse alterations in the other constituent, implying a passive mechanism to maintain metabolic homeostasis upon perturbations in enzyme capacity.
- KU Leuven Belgium
- ETH Zurich Switzerland
- University of Zurich Switzerland
- Institute for Molecular Systems Biology Switzerland
- Life Science Zurich Switzerland
Medicine (General), design principle, 0601 Biochemistry and Cell Biology, SACCHAROMYCES-CEREVISIAE, PATHWAY, SX00 SystemsX.ch, 2604 Applied Mathematics, 2400 General Immunology and Microbiology, Gene Expression Regulation, Fungal, Homeostasis, Biology (General), Applied Mathematics, TRANSCRIPTIONAL REGULATION, Systems Biology, GLYCOLYTIC GENE-EXPRESSION, metabolomics, Enzymes, Computational Theory and Mathematics, GROWTH, General Agricultural and Biological Sciences, Life Sciences & Biomedicine, Metabolic Networks and Pathways, Information Systems, FLUX, Biochemistry & Molecular Biology, 3101 Biochemistry and cell biology, Saccharomyces cerevisiae Proteins, Bioinformatics, QH301-705.5, 0699 Other Biological Sciences, Down-Regulation, Genetics and Molecular Biology, 1100 General Agricultural and Biological Sciences, Saccharomyces cerevisiae, Models, Biological, Article, R5-920, proteomics, LINEAR TREATMENT, 1300 General Biochemistry, Genetics and Molecular Biology, metabolic network, YEAST, Science & Technology, General Immunology and Microbiology, Gene Expression Profiling, Reproducibility of Results, MASS-SPECTROMETRY, design principle; metabolic network; metabolomics; proteomics; transcriptome, MUTANTS, General Biochemistry, 570 Life sciences; biology, SX16 YeastX, transcriptome, Transcription Factors
Medicine (General), design principle, 0601 Biochemistry and Cell Biology, SACCHAROMYCES-CEREVISIAE, PATHWAY, SX00 SystemsX.ch, 2604 Applied Mathematics, 2400 General Immunology and Microbiology, Gene Expression Regulation, Fungal, Homeostasis, Biology (General), Applied Mathematics, TRANSCRIPTIONAL REGULATION, Systems Biology, GLYCOLYTIC GENE-EXPRESSION, metabolomics, Enzymes, Computational Theory and Mathematics, GROWTH, General Agricultural and Biological Sciences, Life Sciences & Biomedicine, Metabolic Networks and Pathways, Information Systems, FLUX, Biochemistry & Molecular Biology, 3101 Biochemistry and cell biology, Saccharomyces cerevisiae Proteins, Bioinformatics, QH301-705.5, 0699 Other Biological Sciences, Down-Regulation, Genetics and Molecular Biology, 1100 General Agricultural and Biological Sciences, Saccharomyces cerevisiae, Models, Biological, Article, R5-920, proteomics, LINEAR TREATMENT, 1300 General Biochemistry, Genetics and Molecular Biology, metabolic network, YEAST, Science & Technology, General Immunology and Microbiology, Gene Expression Profiling, Reproducibility of Results, MASS-SPECTROMETRY, design principle; metabolic network; metabolomics; proteomics; transcriptome, MUTANTS, General Biochemistry, 570 Life sciences; biology, SX16 YeastX, transcriptome, Transcription Factors
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