Sainz Javier, Pizarro Francisco, Pérez-Correa J Ricardo, Agosin Eduardo
Department of Chemical and Bioprocess Engineering, School of Engineering, Pontificia Universidad Católica de Chile, Casilla 306 Correo 22, Santiago, Chile.
Biotechnol Bioeng. 2003 Mar 30;81(7):818-28. doi: 10.1002/bit.10535.
Much is known about yeast metabolism and the kinetics of industrial batch fermentation processes. In this study, however, we provide the first tool to evaluate the dynamic interaction that exists between them. A stoichiometric model, using wine fermentation as a case study, was constructed to simulate batch cultures of Saccharomyces cerevisiae. Five differential equations describe the evolution of the main metabolites and biomass in the fermentation tank, while a set of underdetermined linear algebraic equations models the pseudo-steady-state microbial metabolism. Specific links between process variables and the reaction rates of metabolic pathways represent microorganism adaptation to environmental changes in the culture. Adaptation requirements to changes in the environment, optimal growth, and homeostasis were set as the physiological objectives. A linear programming routine was used to define optimal metabolic mass flux distribution at each instant throughout the process. The kinetics of the process arise from the dynamic interaction between the environment and metabolic flux distribution. The model assessed the effect of nitrogen starvation and ethanol toxicity in wine fermentation and it was able to simulate fermentation profiles qualitatively, while experimental fermentation yields were reproduced successfully as well.
关于酵母代谢和工业分批发酵过程的动力学，我们已经了解很多。然而，在本研究中，我们提供了首个工具来评估它们之间存在的动态相互作用。以葡萄酒发酵为例，构建了一个化学计量模型来模拟酿酒酵母的分批培养。五个微分方程描述了发酵罐中主要代谢物和生物质的演变，而一组欠定线性代数方程对伪稳态微生物代谢进行建模。过程变量与代谢途径反应速率之间的特定联系代表了微生物对培养环境变化的适应。将对环境变化、最佳生长和稳态的适应要求设定为生理目标。使用线性规划程序来定义整个过程中每个时刻的最佳代谢质量通量分布。该过程的动力学源于环境与代谢通量分布之间的动态相互作用。该模型评估了葡萄酒发酵中氮饥饿和乙醇毒性的影响，它能够定性地模拟发酵过程，同时也成功地再现了实验发酵产量。
