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

Meike T. Wortel, Elad Noor, Michael Ferris, Frank J. Bruggeman, Wolfram Liebermeister*

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review


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.

Original languageEnglish
Article numbere1006010
JournalPLoS Computational Biology
Issue number2
Publication statusPublished - 16 Feb 2018


This work was funded by the ZonMW Zenith project nr. 40-41009-98-10038 (to MTW), by the Swiss Initiative in Systems Biology ( TPdF fellowship (2014-230) (to EN), and by the German Research Foundation (Ll1676/2-1) (to WL). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. We thank H.-G. Holzhütter, Joost Hulshof, Daan de Groot, Avi Flamholz, Philip van Kuiken, Timo Maarleveld and Bas Teusink for fruitful discussions, and the Lorenz Center of Leiden University for providing a space for developing ideas.

FundersFunder number
Deutsche ForschungsgemeinschaftLl1676/2-1


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