Note to users. If you're seeing this message, it means that your browser cannot find this page's style/presentation instructions -- or possibly that you are using a browser that does not support current Web standards. Find out more about why this message is appearing, and what you can do to make your experience of our site the best it can be.
Subscribe

Logo for

Science 336 (6081): 601-604

Copyright © 2012 by the American Association for the Advancement of Science

Multidimensional Optimality of Microbial Metabolism

Robert Schuetz,1 Nicola Zamboni,1 Mattia Zampieri,1 Matthias Heinemann,1,2 Uwe Sauer1,*

Abstract: Although the network topology of metabolism is well known, understanding the principles that govern the distribution of fluxes through metabolism lags behind. Experimentally, these fluxes can be measured by 13C-flux analysis, and there has been a long-standing interest in understanding this functional network operation from an evolutionary perspective. On the basis of 13C-determined fluxes from nine bacteria and multi-objective optimization theory, we show that metabolism operates close to the Pareto-optimal surface of a three-dimensional space defined by competing objectives. Consistent with flux data from evolved Escherichia coli, we propose that flux states evolve under the trade-off between two principles: optimality under one given condition and minimal adjustment between conditions. These principles form the forces by which evolution shapes metabolic fluxes in microorganisms’ environmental context.

1 Institute of Molecular Systems Biology, Eidgenössische Technische Hochschule (ETH) Zurich, Zurich, Switzerland.
2 Molecular Systems Biology, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Groningen, Netherlands.

* To whom correspondence should be addressed. E-mail: sauer{at}ethz.ch

THIS ARTICLE HAS BEEN CITED BY OTHER ARTICLES:
Robust design of microbial strains.
J. Costanza, G. Carapezza, C. Angione, P. Lio, and G. Nicosia (2012)
Bioinformatics 28, 3097-3104
   Abstract »    Full Text »    PDF »
Efficiency in Evolutionary Trade-Offs.
E. Noor and R. Milo (2012)
Science 336, 1114-1115
   Abstract »    Full Text »    PDF »

To Advertise     Find Products

Science Signaling. ISSN 1937-9145 (online), 1945-0877 (print). Pre-2008: Science's STKE. ISSN 1525-8882