Metabolic enzyme cost explains variable trade-offs between microbial growth rate and yield
Meike T Wortel1,2, Elad Noor3, Michael Ferris4
1Centre for Ecological and Evolutionary Synthesis (CEES), Department of Biosciences, University of Oslo, Oslo, Norway.
Plos Computational Biology
|February 17, 2018
Summary
Microbial growth strategies involve maximizing cell production over time or nutrient use. A trade-off exists between growth rate and biomass yield, influenced by metabolic pathways and environmental conditions.
Area of Science:
- Microbial metabolism
- Systems biology
- Biochemical engineering
Background:
- Microbes balance growth rate versus biomass yield, often exhibiting a trade-off between speed and efficiency.
- Fast growth typically correlates with less efficient, higher-cost metabolism.
- A thermodynamic trade-off between growth rate and biomass yield is a proposed explanation.
Purpose of the Study:
- To investigate the relationship between microbial growth rate and biomass yield.
- To explore the universality of the growth rate/yield trade-off.
- To utilize a novel modeling framework, Enzyme-Flux Cost Minimization (EFCM), for metabolic analysis.
Main Methods:
- Developed and applied the Enzyme-Flux Cost Minimization (EFCM) modeling framework.
- Constructed a comprehensive mathematical model of core metabolism in Escherichia coli.
- Screened all elementary flux modes for cell synthesis to characterize growth rates and yields.
- Analyzed the Pareto front of rate/yield trade-offs under varying conditions.
Main Results:
- The growth rate/yield trade-off is not universal and depends on metabolic kinetics and environmental factors.
- Under oxygen-limited conditions, yield-inefficient pathways yield 2-3 times higher growth rates than yield-efficient pathways.
- The study characterized the Pareto front of achievable growth rates and yields.
Conclusions:
- EFCM provides a powerful tool for predicting optimal metabolic states and growth rates.
- The framework is applicable to diverse scenarios, including varying nutrient levels and genetic perturbations.
- Metabolic efficiency and growth rate optimization are context-dependent, particularly under specific environmental stresses like oxygen limitation.
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