title: Perception and regulatory principles of microbial growth control.
abstract: Fast growth represents an effective strategy for microbial organisms to survive in competitive environments. To accomplish this task, cells must adapt their metabolism to changing nutrient conditions in a way that maximizes their growth rate. However, the regulation of the growth related metabolic pathways can be fundamentally different among microbes. We therefore asked whether growth control by perception of the cell's intracellular metabolic state can give rise to higher growth than by direct perception of extracellular nutrient availability. To answer this question, we created a simplified dynamical computer model of a cellular metabolic network whose regulation was inferred by an optimization approach. We used this model for a competing species experiment, where a species with extracellular nutrient perception competes against one with intracellular nutrient perception by evaluating their respective average growth rate. We found that the intracellular perception is advantageous under situations where the up and down regulation of pathways cannot follow the fast changing nutrient availability in the environment. In this case, optimal regulation ignores any other nutrients except the most preferential ones, in agreement with the phenomenon of catabolite repression in prokaryotes. The corresponding metabolic pathways remain activated, despite environmental fluctuations. Therefore, the cell can take up preferential nutrients as soon as they are available without any prior regulation. As a result species that rely on intracellular perception gain a relevant fitness advantage in fluctuating nutrient environments, which enables survival by outgrowing competitors.
authors.affiliation: Mathematische Modellierung biologischer Systeme, Heinrich-Heine-Universität, Düsseldorf, Germany.
authors.forename: Armin S
authors.initials: AS
authors.lastname: Khonsari
authors.affiliation: Mathematische Modellierung biologischer Systeme, Heinrich-Heine-Universität, Düsseldorf, Germany.
authors.forename: Markus
authors.initials: M
authors.lastname: Kollmann
mesh_terms: D000222:Adaptation, Physiological; D003198:Computer Simulation; D004777:Environment; D004926:Escherichia coli / Q000235:genetics / Q000254:growth & development / Q000378:metabolism; D053858:Metabolic Networks and Pathways; D008954:Models, Biological; D012441:Saccharomyces cerevisiae / Q000235:genetics / Q000254:growth & development / Q000378:metabolism