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Metabolite concentrations, fluxes and free energies imply efficient enzyme usage

Nature Chemical Biology volume 12, pages 482–489 (2016)Cite this article

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Abstract

In metabolism, available free energy is limited and must be divided across pathway steps to maintain a negative ΔG throughout. For each reaction, ΔG is log proportional both to a concentration ratio (reaction quotient to equilibrium constant) and to a flux ratio (backward to forward flux). Here we use isotope labeling to measure absolute metabolite concentrations and fluxes in Escherichia coli, yeast and a mammalian cell line. We then integrate this information to obtain a unified set of concentrations and ΔG for each organism. In glycolysis, we find that free energy is partitioned so as to mitigate unproductive backward fluxes associated with ΔG near zero. Across metabolism, we observe that absolute metabolite concentrations and ΔG are substantially conserved and that most substrate (but not inhibitor) concentrations exceed the associated enzyme binding site dissociation constant (Km or Ki). The observed conservation of metabolite concentrations is consistent with an evolutionary drive to utilize enzymes efficiently given thermodynamic and osmotic constraints.

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Figure 1: Tracing forward-to-backward flux through TPI.
Figure 2: Metabolic flux distributions in mammalian iBMK cells, yeast and E. coli.
Figure 3: Reaction free energy determined with isotope tracers in mammalian iBMK cells, yeast and E. coli.
Figure 4: Integration of flux and concentration measurements via ΔG.
Figure 5: Conservation of absolute metabolite concentrations.
Figure 6: Comparison of absolute concentrations to enzyme binding site affinities for substrates and for inhibitors.

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Acknowledgements

The authors would like to thank the Gitai, Silhavy, Brynildsen and White labs for strains and cell lines and H. Haraldsdóttir, E. Noor and R. Fleming for their help with Component Contribution method. J. Fan was supported by a Howard Hughes Medical Institute international student research fellowship. Funding was provided by US Department of Energy grant DE-SC0012461, and US National Institutes of Health R01grant 1R01CA163591 and DRC grant 2P30DK019525-37..

Author information

Author notes

  1. Yi-Fan Xu & Daniel Amador-Noguez

    Present address: Present addresses: DuPont Industrial Biosciences, Experimental Station, Wilmington, Delaware, USA (Y.-F.X.),Department of Bacteriology and Great Lake Bioenergy Research Center, University of Wisconsin–Madison, Madison, Wisconsin, USA (D.A.-N.).,

Authors and Affiliations

  1. Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, USA

    Junyoung O Park, Yi-Fan Xu, Daniel Amador-Noguez, Jing Fan & Joshua D Rabinowitz

  2. Department of Chemical and Biological Engineering, Princeton University, Princeton, New Jersey, USA

    Junyoung O Park

  3. Department of Chemistry, Princeton University, Princeton, New Jersey, USA

    Sara A Rubin, Yi-Fan Xu, Jing Fan & Joshua D Rabinowitz

  4. Department of Computer Science, Technion–Israel Institute of Technology, Haifa, Israel

    Tomer Shlomi

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Contributions

J.O.P., S.A.R., Y.-F.X., T.S. and J.D.R. designed the study. J.O.P., S.A.R., Y.-F.X., D.A.-N. and J.F. carried out the experiments. J.O.P. and S.A.R. developed the computational tools. J.O.P., S.A.R. and J.D.R. wrote the paper.

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Correspondence to Joshua D Rabinowitz.

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Supplementary information

Supplementary Text and Figures

Supplementary Results, Supplementary Tables 1–8 and Supplementary Figures 1–4. (PDF 1710 kb)

Supplementary Data Set 1

Steady-state metabolite labeling from various 13C tracers. (XLSX 90 kb)

Supplementary Data Set 2

Comparison of absolute concentrations to enzyme binding site affinities for substrates. (XLSX 120 kb)

Supplementary Data Set 3

Comparison of absolute concentrations to enzyme binding site affinities for inhibitors. (XLSX 34 kb)

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Park, J., Rubin, S., Xu, YF. et al. Metabolite concentrations, fluxes and free energies imply efficient enzyme usage. Nat Chem Biol 12, 482–489 (2016). https://doi.org/10.1038/nchembio.2077

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