Sonnleitner B, Käppeli O
Department for Biotechnology, Swiss Federal Institute of Technology, 8093 Zürich, Switzerland.
Biotechnol Bioeng. 1986 Jun;28(6):927-37. doi: 10.1002/bit.260280620.
A novel mechanistic model for the growth of baker's yeast on glucoseis presented. It is based on the fact that glucose degradation proceeds via two pathways under conditions of aerobic ethanol formation. Part is metabolized oxidatively and part reductively, with ethanol being the end product of reductive energy metabolism. The corresponding metabolic state is designated oxidoreductive. Ethanol can be used oxidatively only. Maximum rates of oxidative glucose and ethanol degradation are governed by the respiratory capacity of the cells. The model is formulated by using the stoichiometric growth equations for pure oxidative and reductive (fermentative) glucose and ethanol metabolism. Together with the experimentally determinable yield coefficients (Y(X/S)) for the respective metabolic pathways, the resulting equation system is sufficiently determined. The superiority of the presented model over hitherto published ones is based on two essential novelities. (1) The model was developed on experimentally easily accessible parameters only. (2) For the modeling of aerobic ethanol formation, the substrate flow was split into two simultaneously operating (i.e., in parallel) metabolic pathways that exhibit different but constant energy-generating efficiencies (respiration and fermentation) and consequently different and constant biomass yields (Y(X/S)). The model allows the prediction of experimental data without parameter adaption in a biologically dubious manner.
提出了一种关于面包酵母在葡萄糖上生长的新型机理模型。该模型基于这样一个事实:在有氧乙醇形成的条件下,葡萄糖降解通过两条途径进行。一部分通过氧化代谢,一部分通过还原代谢,乙醇是还原能量代谢的终产物。相应的代谢状态被称为氧化还原状态。乙醇只能被氧化利用。氧化葡萄糖和乙醇降解的最大速率受细胞呼吸能力的控制。该模型通过使用纯氧化和还原(发酵)葡萄糖及乙醇代谢的化学计量生长方程来构建。结合各代谢途径实验可测定的产率系数(Y(X/S)),所得方程组得到了充分确定。所提出的模型相对于迄今已发表的模型的优势基于两个重要的新颖之处。(1)该模型仅基于实验上易于获取的参数开发。(2)对于有氧乙醇形成的建模,底物流被分为两条同时运行(即并行)的代谢途径,这两条途径具有不同但恒定的能量产生效率(呼吸和发酵),因此具有不同且恒定的生物量产率(Y(X/S))。该模型能够在不进行生物学上可疑的参数调整的情况下预测实验数据。