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Analytic derivation of bacterial growth laws from a simple model of intracellular chemical dynamics
- Source :
- Theory in Biosciences
- Publisher :
- Springer Nature
-
Abstract
- Experiments have found that the growth rate and certain other macroscopic properties of bacterial cells in steady-state cultures depend upon the medium in a surprisingly simple manner; these dependencies are referred to as ‘growth laws’. Here we construct a dynamical model of interacting intracellular populations to understand some of the growth laws. The model has only three population variables: an amino acid pool, a pool of enzymes that transport an external nutrient and produce the amino acids, and ribosomes that catalyze their own and the enzymes’ production from the amino acids. We assume that the cell allocates its resources between the enzyme sector and the ribosomal sector to maximize its growth rate. We show that the empirical growth laws follow from this assumption and derive analytic expressions for the phenomenological parameters in terms of the more basic model parameters. Interestingly, the maximization of the growth rate of the cell as a whole implies that the cell allocates resources to the enzyme and ribosomal sectors in inverse proportion to their respective ‘efficiencies’. The work introduces a mathematical scheme in which the cellular growth rate can be explicitly determined and shows that two large parameters, the number of amino acid residues per enzyme and per ribosome, are useful for making approximations.
- Subjects :
- 0301 basic medicine
Statistics and Probability
Work (thermodynamics)
Population
Bacterial growth
Biology
Bacterial growth laws
Bacterial Physiological Phenomena
Ribosome
Catalysis
03 medical and health sciences
0302 clinical medicine
Chemical dynamics
Growth rate
Amino Acids
education
Ecology, Evolution, Behavior and Systematics
chemistry.chemical_classification
Medicine(all)
education.field_of_study
Original Paper
Bacteria
Growth rate optimization
Applied Mathematics
Maximization
Models, Theoretical
Cellular economy
Chemical Dynamics
Amino acid
Enzymes
030104 developmental biology
chemistry
Nonlinear Dynamics
Law
Mutation
Mathematical modeling
Ribosomes
030217 neurology & neurosurgery
Algorithms
Subjects
Details
- Language :
- English
- ISSN :
- 14317613
- Volume :
- 135
- Issue :
- 3
- Database :
- OpenAIRE
- Journal :
- Theory in Biosciences
- Accession number :
- edsair.doi.dedup.....79ac3e6d2800eede5775cbaed6a30a6c
- Full Text :
- https://doi.org/10.1007/s12064-016-0227-9