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

Sarah‐Maria Fendt, Joerg Martin Buescher, Florian Rudroff, Paola Picotti, Nicola Zamboni, Uwe Sauer

Author Affiliations

  1. Sarah‐Maria Fendt1,2,3,,
  2. Joerg Martin Buescher1,4,,
  3. Florian Rudroff1,
  4. Paola Picotti1,
  5. Nicola Zamboni1,3 and
  6. Uwe Sauer*,1,3
  1. 1 Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
  2. 2 Life Science Zurich PhD Program on Systems Biology of Complex Diseases, Zurich, Switzerland
  3. 3 Competence Center for Systems Physiology and Metabolic Diseases, Zurich, Switzerland
  4. 4 Life Science Zurich PhD Program on Molecular Life Science, Zurich, Switzerland
  1. *Corresponding author. Institute of Molecular Systems Biology, Wolfgang‐Pauli‐Strasse 16, ETH Zurich, Zurich 8093, Switzerland. Tel.: +41 1 633 3672; Fax: +41 44 633 1051; E-mail: sauer{at}
  1. These authors contributed equally to this work

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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.

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Physiological behavior emerges from complex dynamic interactions between transcripts, enzymes, and metabolites, the constituents of metabolism, and its regulatory network (Sauer, 2006). Although large data sets can be generated on all these variables, data integration, in particular across different omics levels, is becoming the key challenge (Stitt and Fernie, 2003; Sauer et al, 2007). In this study, we identify a general relationship between substrates of an enzymatic reaction and enzymatic capacity in central carbon metabolism that allows the prediction of changes in metabolite concentration based on changes in enzyme capacity and vise versa. To elucidate whether general relationships exist between metabolite concentrations and enzyme capacities (i.e. the outcome of enzyme abundance combined with activity), we propose three hypothetical and alternative governing principles. The first hypothesis postulates a minimization of metabolite concentration at a given flux. In this case, no correlation between alterations in metabolite concentrations and enzyme capacities is expected. The second hypothesis postulates a tradeoff between metabolite concentration and enzyme capacity. In this case, a negative correlation between differences in concentrations of substrate metabolites and differences in enzyme capacity is expected. The third hypothesis postulates a minimization of enzyme capacity at a given flux. In this case, we expect a positive correlation between differences in concentrations of product metabolites and differences in enzyme capacity. As hypotheses I–III imply different relationships between enzyme capacities and metabolite concentrations, identification of the prevailing situation in microbial metabolism requires quantitative in vivo metabolite concentration and enzyme capacity data upon moderate changes in enzyme capacity. As a first test, we chose wild type Saccharomyces cerevisiae and an otherwise isogenic mutant with a complete deletion of the transcription factor Gcr2p, an activator of glycolysis (Chambers et al, 1995). This mutant exhibits altered transcript abundances, enzyme activities, and metabolite concentrations within closely connected reactions in glycolysis and in the tricarboxylic acid cycle (Uemura and Fraenkel, 1990, 1999; Sasaki and Uemura, 2005). To quantify the relationship between metabolite concentrations and enzyme capacities, we determined transcript, enzyme, and metabolite abundances in wild type and GCR2 mutant in batch culture on glucose minimal medium. Transcript and enzyme abundances are used as surrogates for enzyme capacities. The most significant correlation was observed for fold‐changes in substrate metabolite concentrations with fold‐changes in enzyme abundance. Not unexpectedly, enzyme abundances were a significantly better approximation for enzyme capacities than transcript abundances. A further improved correlation was achieved by considering all diverging enzymes that react upon a given substrate metabolite simultaneously rather than considering them as a separate reaction (Figure 4). The high correlation between substrate metabolite and enzyme fold‐changes suggests a tradeoff between enzyme capacity and metabolite concentrations in central metabolism. To test the general validity for central carbon metabolism of the above‐identified tradeoff between reaction substrate metabolite concentrations and enzyme abundances, we performed four independent validations: a statistical, a literature based, and two experimental ones. Statistically, we verified that the correlation between substrate metabolites and enzymes could not have been found by chance. On the basis of the literature data, we performed the above correlation analysis with literature data. All available data followed the proposed correlation, thus providing further evidence for the general validity of this relationship. As a more serious challenge of the identified correlation, we designed an experiment where the absolute flux alterations are large and additionally the flux directions are altered. We expected the substrate metabolites to occur at higher concentrations in the mutant than in the wild type. This expectation was fulfilled by the experimental data in all cases, thereby further corroborating the negative correlation between enzyme capacity and metabolite concentrations. So far, our experimental evidence was based on perturbing multiple enzyme abundances through a transcription factor mutant. To ensure that our findings are also valid for single‐reaction perturbations, we modulated individual abundances of the four glycolytic enzymes Pgi1p, Tpi1p, Eno2p, and Cdc19p using strains whose endogenous genomic promotor was replaced by a Tet‐controlled promotor (Mnaimneh et al, 2004) (Figure 7). Thus, we determined intracellular metabolites concentrations during exponential growth in the strains with modulated enzyme abundance. Our above‐identified correlation predicts metabolite concentrations to increase only for the substrate of the such perturbed reaction and all other metabolite concentrations to remain constant. This prediction was verified. We demonstrate here that global or local alterations in enzyme abundance correlate negatively with enzyme reaction substrate concentration at least in central carbon metabolism. This implies a tradeoff between enzyme and metabolite efficiency in metabolic networks. These findings can be interpreted as a passive network mechanism to maintain close‐to‐wild‐type homeostasis of central carbon metabolism upon perturbations that alter the enzyme capacity. The alterations are compensated by converse changes in reaction substrate concentrations, thereby minimizing the difference in metabolic flux that is caused by the alteration.

  • Substrate metabolite concentrations are inversely related to the in vivo capacity of their converting enzymes.

  • Local metabolite responses represent a passive mechanism to achieve metabolic homeostasis upon perturbations in enzyme capacity.

  • Enzyme capacity and metabolite concentration control the metabolic reaction rate.

Mol Syst Biol. 6: 356

  • Received August 19, 2009.
  • Accepted February 9, 2010.
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