Energy allocation theory for bacterial growth control in and out of steady state

被引:0
作者
Cylke, Arianna [1 ]
Serbanescu, Diana [2 ,3 ]
Banerjee, Shiladitya [1 ]
机构
[1] Carnegie Mellon Univ, Dept Phys, Pittsburgh, PA 15213 USA
[2] UCL, Dept Phys & Astron, London WC1E 6BT, England
[3] UCL, Inst Phys Living Syst, London WC1E 6BT, England
来源
PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES | 2024年 / 480卷 / 2300期
基金
美国安德鲁·梅隆基金会;
关键词
bacterial growth; cell morphology; bacterial metabolism; metabolic rate; energy allocation; bacterial physiology; ESCHERICHIA-COLI; GENE-EXPRESSION; SHAPE DYNAMICS; CELL-SHAPE; Z-RING; FTSZ; FORCE; SIZE; EFFICIENCY; PROTEINS;
D O I
10.1098/rspa.2024.0219
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Efficient allocation of energy resources to key physiological functions allows living organisms to grow and thrive in diverse environments and adapt to a wide range of perturbations. To quantitatively understand how unicellular organisms utilize their energy resources in response to changes in growth environment, we introduce a theory of dynamic energy allocation that describes cellular growth dynamics by partitioning metabolizable energy into key physiological functions: growth, division, cell shape regulation, energy storage and loss through dissipation. By optimizing the energy flux for growth, we develop the equations governing the time evolution of cell morphology and growth rate in diverse environments. The resulting model accurately captures experimentally observed dependencies of bacterial cell size on growth rate, superlinear scaling of metabolic rate with cell size and predicts nutrient-dependent trade-offs between energy expended for growth, division and shape maintenance. By calibrating model parameters with experimental data for the model organism Escherichia coli, our model describes bacterial growth control in dynamic conditions, particularly during nutrient shifts and osmotic shocks. Integrating both the mechanical properties of the cell and underlying biochemical regulation, our model predicts the driving factors behind a wide range of observed morphological and growth phenomena with minimal added complexity.
引用
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页数:26
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