title: Evolutionary pressures on microbial metabolic strategies in the chemostat.
abstract: Protein expression is shaped by evolutionary processes that tune microbial fitness. The limited biosynthetic capacity of a cell constrains protein expression and forces the cell to carefully manage its protein economy. In a chemostat, the physiology of the cell feeds back on the growth conditions, hindering intuitive understanding of how changes in protein concentration affect fitness. Here, we aim to provide a theoretical framework that addresses the selective pressures and optimal evolutionary-strategies in the chemostat. We show that the optimal enzyme levels are the result of a trade-off between the cost of their production and the benefit of their catalytic function. We also show that deviations from optimal enzyme levels are directly related to selection coefficients. The maximal fitness strategy for an organism in the chemostat is to express a well-defined metabolic subsystem known as an elementary flux mode. Using a coarse-grained, kinetic model of Saccharomyces cerevisiae's metabolism and growth, we illustrate that the dynamics and outcome of evolution in a chemostat can be very counter-intuitive: Strictly-respiring and strictly-fermenting strains can evolve from a common ancestor. This work provides a theoretical framework that relates a kinetic, mechanistic view on metabolism with cellular physiology and evolutionary dynamics in the chemostat.
authors.affiliation: Systems Bioinformatics, VU University, Amsterdam, De Boelelaan 1087, 1081 HV, The Netherlands.
authors.forename: Meike T
authors.initials: MT
authors.lastname: Wortel
authors.affiliation: Systems Bioinformatics, VU University, Amsterdam, De Boelelaan 1087, 1081 HV, The Netherlands.
authors.forename: Evert
authors.initials: E
authors.lastname: Bosdriesz
authors.affiliation: Systems Bioinformatics, VU University, Amsterdam, De Boelelaan 1087, 1081 HV, The Netherlands.
authors.forename: Bas
authors.initials: B
authors.lastname: Teusink
authors.affiliation: Systems Bioinformatics, VU University, Amsterdam, De Boelelaan 1087, 1081 HV, The Netherlands.
authors.forename: Frank J
authors.initials: FJ
authors.lastname: Bruggeman
mesh_terms: D001669:Biochemical Phenomena; D005075:Biological Evolution; D001692:Biological Transport; D018533:Biomass; D019149:Bioreactors; D003198:Computer Simulation; D019143:Evolution, Molecular; D005285:Fermentation; D005947:Glucose / Q000737:chemistry*; D006019:Glycolysis; D008660:Metabolism; D009154:Mutation; D010641:Phenotype; D011487:Protein Conformation; D012441:Saccharomyces cerevisiae / Q000235:genetics* / Q000378:metabolism*; D012641:Selection, Genetic
chemical_list: D005947:Glucose