Metabolic control analysis of glycerol synthesis in Saccharomyces cerevisiae
Metabolic control analysis of glycerol synthesis in Saccharomyces cerevisiae
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DOI：
10.1128/aem.68.9.4448-4456.2002
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发表时间：
2002-09-01
影响因子：
4.4
通讯作者：
Prior, BA
中科院分区：
文献类型：
--
作者：
Cronwright, GR;Rohwer, JM;Prior, BA
甘油是酿酒酵母发酵乙醇的主要副产物，对葡萄酒、啤酒和乙醇生产具有重要意义。为了更清楚地了解和量化甘油合成途径参数对酿酒酵母甘油通量的影响程度，构建了甘油合成途径的动力学模型。动力学参数是从已公布的数值中收集的。实验测定了最大酶活力和胞内效应物浓度。通过将甘油产率的实验结果与模型计算的甘油产率进行比较，验证了模型的有效性。模型计算值与独立实验值吻合较好。该模型还模拟了甘油合成速率在不同生长阶段的变化。由该模型计算的代谢控制分析值表明，NAD+依赖的3-磷酸甘油脱氢酶催化的反应的通量控制系数(C-v1(J))约为0.85，并通过该途径进行大部分通量控制。参数代谢物的响应系数表明，通过该途径的通量对二羟丙酮磷酸浓度的响应最快(R-Dhap(J)=0.48~0.69)，其次是ATP浓度(R-ATP(J)=-0.21~-0.50)。有趣的是，该途径对NADH浓度的反应很弱(R-NADH(J)=0.03~0.08)。该模型表明，通过该途径增加通量的最佳策略不是单独增加酶活性、底物浓度或辅酶浓度，而是同时增加所有这些参数。
Glycerol, a major by-product of ethanol fermentation by Saccharomyces cerevisiae, is of significant importance to the wine, beer, and ethanol production industries. To gain a clearer understanding of and to quantify the extent to which parameters of the pathway affect glycerol flux in S. cerevisiae, a kinetic model of the glycerol synthesis pathway has been constructed. Kinetic parameters were collected from published values. Maximal enzyme activities and intracellular effector concentrations were determined experimentally. The model was validated by comparing experimental results on the rate of glycerol production to the rate calculated by the model. Values calculated by the model agreed well with those measured in independent experiments. The model also mimics the changes in the rate of glycerol synthesis at different phases of growth. Metabolic control analysis values calculated by the model indicate that the NAD+-dependent glycerol 3-phosphate dehydrogenase-catalyzed reaction has a flux control coefficient (C-v1(J)) of approximately 0.85 and exercises the majority of the control of flux through the pathway. Response coefficients of parameter metabolites indicate that flux through the pathway is most responsive to dihydroxyacetone phosphate concentration (R-DHAP(J) = 0.48 to 0.69), followed by ATP concentration (R-ATP(J) = -0.21 to -0.50). Interestingly, the pathway responds weakly to NADH concentration (R-NADH(J) = 0.03 to 0.08). The model indicates that the best strategy to increase flux through the pathway is not to increase enzyme activity, substrate concentration, or coenzyme concentration alone but to increase all of these parameters in conjunction with each other.