We dedicate this work to the memory of Professor Dr Reinhart Heinrich, who pioneered the study of the optimization of metabolic pathways using kinetic mathematical models.
Metabolic states with maximal specific rate carry flux through an elementary flux mode
Article first published online: 12 FEB 2014
© 2014 FEBS
Volume 281, Issue 6, pages 1547–1555, March 2014
How to Cite
Wortel, M. T., Peters, H., Hulshof , J., Teusink, B. and Bruggeman, F. J. (2014), Metabolic states with maximal specific rate carry flux through an elementary flux mode. FEBS Journal, 281: 1547–1555. doi: 10.1111/febs.12722
- Issue published online: 18 MAR 2014
- Article first published online: 12 FEB 2014
- Accepted manuscript online: 25 JAN 2014 03:07AM EST
- Manuscript Accepted: 14 JAN 2014
- Manuscript Revised: 8 JAN 2014
- Manuscript Received: 6 SEP 2013
- NWO-VIDI. Grant Number: 864.11.011
- SP3-People Marie Curie Actions. Grant Numbers: FP7-PEOPLE-2009-RG, 248443
- elementary flux mode;
- flux optimization;
- genome-scale metabolic networks;
- growth rate optimization;
- kinetic model
Specific product formation rates and cellular growth rates are important maximization targets in biotechnology and microbial evolution. Maximization of a specific rate (i.e. a rate expressed per unit biomass amount) requires the expression of particular metabolic pathways at optimal enzyme concentrations. In contrast to the prediction of maximal product yields, any prediction of optimal specific rates at the genome scale is currently computationally intractable, even if the kinetic properties of all enzymes are available. In the present study, we characterize maximal-specific-rate states of metabolic networks of arbitrary size and complexity, including genome-scale kinetic models. We report that optimal states are elementary flux modes, which are minimal metabolic networks operating at a thermodynamically-feasible steady state with one independent flux. Remarkably, elementary flux modes rely only on reaction stoichiometry, yet they function as the optimal states of mathematical models incorporating enzyme kinetics. Our results pave the way for the optimization of genome-scale kinetic models because they offer huge simplifications to overcome the concomitant computational problems.
The mathematical model described here has been submitted to the JWS Online Cellular Systems Modelling Database and can be accessed at http://jjj.mib.ac.uk/database/wortel2/index.html free of charge.
[Database section added 14 May 2014 after original online publication]