Metabolic enzyme cost explains variable trade-offs between microbial growth rate and yield

Abstract

Microbes may maximize the number of daughter cells per time or per amount of nutrients consumed. These two strategies correspond, respectively, to the use of enzyme-efficient or substrate-efficient metabolic pathways. In reality, fast growth is often associated with wasteful, yield-inefficient metabolism, and a general thermodynamic trade-off between growth rate and biomass yield has been proposed to explain this. We studied growth rate/yield trade-offs by using a novel modeling framework, Enzyme-Flux Cost Minimization (EFCM) and by assuming that the growth rate depends directly on the enzyme investment per rate of biomass production. In a comprehensive mathematical model of core metabolism in E. coli, we screened all elementary flux modes leading to cell synthesis, characterized them by the growth rates and yields they provide, and studied the shape of the resulting rate/yield Pareto front. By varying the model parameters, we found that the rate/yield trade-off is not universal, but depends on metabolic kinetics and environmental conditions. A prominent trade-off emerges under oxygen-limited growth, where yield-inefficient pathways support a 2-to-3 times higher growth rate than yield-efficient pathways. EFCM can be widely used to predict optimal metabolic states and growth rates under varying nutrient levels, perturbations of enzyme parameters, and single or multiple gene knockouts.

Life‐history strategy varies with the strength of competition in a food‐limited ungulate population

“…However, other traits influence survival and reproduction and hence carrying capacity, generation time and asymptotic body mass. If we were to extend our size‐structured life‐history models to include other traits such as metabolic rate (Wortel et al ) and energy budgets (Smallegange et al ), we may expect the variance in the scatter around Fig. to decline as we search for multi‐trait structured life‐history strategies.…”

From Escherichia coli mutant 13C labeling data to a core kinetic model: A kinetic model parameterization pipeline

“…Incorporation of kinetic descriptions of transcriptional and translational events into kinetic parameterization procedures would allow for the decoupling of enzyme concentration and elementary kinetic parameters. As an alternative to direct description of protein synthesis events in the cell, protein cost studies have shown that cellular enzyme concentration can be reasonably predicted using kinetic rate expressions for metabolic reactions [95,96]. It may, therefore, be possible to use kinetic rate expressions for enzyme catalyzed reactions directly to characterize changes in enzyme level across conditions rather than kinetic expressions for transcription and translation.…”

Expanding Metabolic Capabilities Using Novel Pathway Designs: Computational Tools and Case Studies

“…Particularly in the context of maximum growth rate prediction of microbial cells, there are theoretical results that support the existence of such optimal rates defined by a single EFM . More recently, enzyme‐flux cost minimization (EFCM) has been proposed to rationally explain the trade‐offs between growth rate and yield(s) based on the ECM framework …”

“…[70,71] More recently, enzyme-flux cost minimization (EFCM) has been proposed to rationally explain the trade-offs between growth rate and yield(s) based on the ECM framework. [72] Application of ECM has been mostly focused on evaluating alternative metabolic pathways fulfilling known biological functions such as carbon assimilation [20] and efficient carbon conversions. [56,57] In both cases, metabolic conditions defined by the allowable metabolite concentrations, as well as pH and ionic strength, played critical roles in determining the most "economical" pathway choice.…”