Droste Maarten J, Remeijer Maaike, Planqué Robert, Bruggeman Frank J
Department of Mathematics, Amsterdam Center for Dynamics and Computation, Vrije Universiteit Amsterdam, Amsterdam, 1081 HV, The Netherlands.
Systems Biology Lab, A-LIFE, AIMMS, Vrije Universiteit Amsterdam, Amsterdam, 1081 HZ The Netherlands.
J Phys Chem B. 2025 Jun 19;129(24):5923-5936. doi: 10.1021/acs.jpcb.4c08559. Epub 2025 Jun 6.
Thermodynamics dictates that the entropy production rate (EPR) of a steady-state isothermal chemical reaction network rises with reaction rates. Living cells can, in addition, alter reaction rates by changing enzyme concentrations, giving them control over metabolic activities. Here, we ask whether microbial cells can break this relation between EPR and reaction rates by shifting to a metabolism with lower thermodynamic driving force (per unit of biomass) at faster growth. First, we study an example metabolic network to illustrate that maximization of metabolic flux by optimal allocation of resources can indeed lead to selection of a pathway with a lower driving force. This pathway then compensates for the reduction in driving force by relying on fewer enzymes with sufficiently increased concentrations, resulting in a higher flux. Next, we investigate the EPR per unit biomass of microbes that change their catabolic network as a function of their growth rate, using three models for chemostat cultivation of the yeast that are calibrated with experimental data. Although current experimental evidence proved insufficient to give conclusive results, we derive a general criterion to predict when the specific EPR drops after a metabolic switch. We describe the experiments that are required to show that the specific EPR of a microbe can decrease with its growth rate.
热力学表明,稳态等温化学反应网络的熵产生率(EPR)会随着反应速率的增加而升高。此外,活细胞可以通过改变酶的浓度来改变反应速率,从而控制代谢活动。在此,我们要探讨微生物细胞是否能够通过在更快生长速度下转向具有更低热力学驱动力(每单位生物量)的代谢方式,来打破EPR与反应速率之间的这种关系。首先,我们研究一个代谢网络示例,以说明通过资源的最优分配实现代谢通量最大化确实能够导致选择一条具有更低驱动力的途径。然后,这条途径通过依赖更少但浓度充分增加的酶来补偿驱动力的降低,从而实现更高的通量。接下来,我们使用三个根据实验数据校准的酵母恒化器培养模型,研究作为生长速率函数改变其分解代谢网络的微生物每单位生物量的EPR。尽管目前的实验证据不足以得出确凿结果,但我们推导出一个通用标准,以预测代谢转换后比EPR何时会下降。我们描述了为证明微生物的比EPR会随其生长速率降低而需要开展的实验。