title: How fast-growing bacteria robustly tune their ribosome concentration to approximate growth-rate maximization.
abstract: Maximization of growth rate is an important fitness strategy for bacteria. Bacteria can achieve this by expressing proteins at optimal concentrations, such that resources are not wasted. This is exemplified for Escherichia coli by the increase of its ribosomal protein-fraction with growth rate, which precisely matches the increased protein synthesis demand. These findings and others have led to the hypothesis that E. coli aims to maximize its growth rate in environments that support growth. However, what kind of regulatory strategy is required for a robust, optimal adjustment of the ribosome concentration to the prevailing condition is still an open question. In the present study, we analyze the ppGpp-controlled mechanism of ribosome expression used by E. coli and show that this mechanism maintains the ribosomes saturated with its substrates. In this manner, overexpression of the highly abundant ribosomal proteins is prevented, and limited resources can be redirected to the synthesis of other growth-promoting enzymes. It turns out that the kinetic conditions for robust, optimal protein-partitioning, which are required for growth rate maximization across conditions, can be achieved with basic biochemical interactions. We show that inactive ribosomes are the most suitable 'signal' for tracking the intracellular nutritional state and for adjusting gene expression accordingly, as small deviations from optimal ribosome concentration cause a huge fractional change in ribosome inactivity. We expect to find this control logic implemented across fast-growing microbial species because growth rate maximization is a common selective pressure, ribosomes are typically highly abundant and thus costly, and the required control can be implemented by a small, simple network.
authors.affiliation: Systems Bioinformatics, VU University, Amsterdam, The Netherlands.
authors.forename: Evert
authors.initials: E
authors.lastname: Bosdriesz
authors.affiliation: Systems Bioinformatics, VU University, Amsterdam, The Netherlands.
authors.forename: Douwe
authors.initials: D
authors.lastname: Molenaar
authors.affiliation: Systems Bioinformatics, VU University, Amsterdam, The Netherlands.
authors.forename: Bas
authors.initials: B
authors.lastname: Teusink
authors.affiliation: Systems Bioinformatics, VU University, Amsterdam, The Netherlands.
authors.forename: Frank J
authors.initials: FJ
authors.lastname: Bruggeman
mesh_terms: D001419:Bacteria / Q000254:growth & development* / Q000378:metabolism*; D004926:Escherichia coli / Q000254:growth & development / Q000378:metabolism; D015964:Gene Expression Regulation, Bacterial / Q000502:physiology; D012270:Ribosomes / Q000378:metabolism*
keywords: growth rate maximization; kinetic model; metabolic regulation; ribosome synthesis; whole-cell model