How Biochemical Constraints of Cellular Growth Shape Evolutionary Adaptations in Metabolism

Abstract

Evolutionary adaptations in metabolic networks are fundamental to evolution of microbial growth. Studies on unneededprotein synthesis indicate reductions in fitness upon nonfunctional protein synthesis, showing that cell growth is limited by constraints acting on cellular protein content. Here, we present a theory for optimal metabolic enzyme activity when cells are selected for maximal growth rate given such growth-limiting biochemical constraints. We show how optimal enzyme levels can be understood to result from an enzyme benefit minus cost optimization. The constraints we consider originate from different biochemical aspects of microbial growth, such as competition for limiting amounts of ribosomes or RNA polymerases, or limitations in available energy. Enzyme benefit is related to its kinetics and its importance for fitness, while enzyme cost expresses to what extent resource consumption reduces fitness through constraint-induced reductions of other enzyme levels. A metabolic fitness landscape is introduced to define the fitness potential of an enzyme. This concept is related to the selection coefficient of the enzyme and can be expressed in terms of its fitness benefit and cost. E NVIRONMENTAL conditions set the selective pressures acting on unicellular organisms. Microbial fitness is often related to growth properties, such as biomass yield, growth rate, or antibiotic resistance. As a large part of the available resources is spent on the synthesis of metabolic machinery, regulation of the levels of metabolic enzymes can have large influences on fitness (Dean 1989; Dong et al. 1995; Dekel and Alon 2005; Stoebel et al. 2008). Selection on growth rate may then direct the evolution of microorganisms to optimal allocation of resources for fitness enhancement (Dekel and Alon 2005; Molenaar et al. 2009). Alternatively, evolution may be directed by metabolic trade-offs (Beardmore et al. 2011; Wenger et al. 2011), which may cause sympatric speciation (Friesen et al. 2004). To improve our understanding of the driving processes of metabolic evolution, the interplay between selective pressures and the biochemistry and organization of metabolic networks must be taken into account.Studies on the growth effects of unneeded-protein expression, sometimes called gratuitous or nonfunctional protein expression, indicate significant reductions in growth rate in batch cultivations of Escherichia coli (Novick and Weiner 1957; Dong et al. 1995; Dekel and Alon 2005; Shachrai et al. 2010) and Zymomonas mobilis (Snoep et al. 1995) and strong selective disadvantages in chemostat cultivations using E. coli (Dean et al. 1986;Dean 1989; Lunzer et al. 2002; Stoebel et al. 2008). In Saccharomyces cerevisiae, a trade-off related to unneeded-protein expression was found (Lang et al. 2009). Dong, Nilsson, and Kurland found that unneeded protein can be expressed up to 30% of the total protein content before E. coli growth halts (Dong et al. 1995). They concluded that growth reduction was caused by competition for protein syn...

Metabolic states with maximal specific rate carry flux through an elementary flux mode

“…Formally, the specific flux (or specific rate), q r , of metabolic reaction r is defined as :where e T denotes the total protein content in the system in gram total protein, and v r is the flux value in mol·h −1 . We note that scaling with total protein content is for some applications more useful (e.g.…”

How fast‐growing bacteria robustly tune their ribosome concentration to approximate growth‐rate maximization

“…Firstly, the growth rate 'cost' of enzyme excess is illustrated by observations that the growth rate decreases upon non-functional protein synthesis. This decrease is often observed to be linear with the non-functional protein fraction [14,7,15], which is predicted by theory [7,16]. However, non-linear protein costs have also been reported [17], possibly as a result of effects related to protein activity rather than production [18].…”

“…However, non-linear protein costs have also been reported [17], possibly as a result of effects related to protein activity rather than production [18]. Secondly, the concentration of each protein should be precisely tuned [16,19]. This has been found for several enzymes in E. coli, [20,21,17,22], Lactococcus lactis [23][24][25] and Saccharomyces cerevisiae [26].…”

Cell responses only partially shape cell-to-cell variations in protein abundances in Escherichia coli chemotaxis

“…5). Limitations such as a finite pool of RNA polymerases and ribosomes in individual cells (27,28) or energetic costs for protein synthesis (29) imposed by the protein synthesis machinery could restrict protein expression. These restrictions are manifested in a reduction in cell growth rate when abundances of nonfunctional proteins are increased in bacterial cells (27,30).…”