title: Multidimensional optimality of microbial metabolism.
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 (13)C-flux analysis, and there has been a long-standing interest in understanding this functional network operation from an evolutionary perspective. On the basis of (13)C-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.
authors.affiliation: Institute of Molecular Systems Biology, Eidgenössische Technische Hochschule Zurich, Zurich, Switzerland.
authors.forename: Robert
authors.initials: R
authors.lastname: Schuetz
authors.forename: Nicola
authors.initials: N
authors.lastname: Zamboni
authors.forename: Mattia
authors.initials: M
authors.lastname: Zampieri
authors.forename: Matthias
authors.initials: M
authors.lastname: Heinemann
authors.forename: Uwe
authors.initials: U
authors.lastname: Sauer
mesh_terms: D000222:Adaptation, Physiological; D000255:Adenosine Triphosphate / Q000378:metabolism; D000332:Aerobiosis; D000465:Algorithms; D001419:Bacteria / Q000254:growth & development / Q000378:metabolism*; D005075:Biological Evolution; D018533:Biomass; D003198:Computer Simulation; D004926:Escherichia coli / Q000235:genetics / Q000254:growth & development / Q000378:metabolism*; D005947:Glucose / Q000378:metabolism; D053858:Metabolic Networks and Pathways; D008954:Models, Biological
chemical_list: D000255:Adenosine Triphosphate; D005947:Glucose