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Quantifying the entropic cost of cellular growth control
Daniele De Martino1, Fabrizio Capuani2, Andrea De Martino2,3
1Institute of Science and Technology Austria, 3400 Klosterneuburg, Austria.
Cellular metabolism regulation minimizes entropy for optimal growth. This study quantifies metabolic regulation costs, revealing growth suppression is as costly as enhancement, impacting cell populations and environments.
Area of Science:
- Systems Biology
- Metabolic Engineering
- Statistical Mechanics
Background:
- Cellular metabolism can be viewed as a physical system's phase space.
- Metabolic regulation aims to reduce system entropy by selecting optimal cellular configurations.
Purpose of the Study:
- Quantify the regulation needed to control cellular growth rate.
- Apply a maximum-entropy approach to metabolic phenotypes.
- Link mean growth rate to minimal metabolic regulation requirements.
Main Methods:
- Utilized a maximum-entropy framework.
- Analyzed metabolic flux patterns using genome-scale models.
- Developed a phase diagram to illustrate regulation costs.
Main Results:
- Demonstrated that growth suppression carries regulatory costs comparable to growth enhancement.
- Provided an interpretation of the inverse temperature parameter (β) in relation to growth dynamics.
- Showed that asymptotic β values depend on environmental carrying capacity, initial colony size, and inoculum sampling distribution.
Conclusions:
- Metabolic regulation is crucial for optimizing cellular growth.
- The cost of regulation is symmetrical for growth enhancement and suppression.
- Environmental and initial conditions significantly influence population-level regulatory dynamics.
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