The purpose of this work is to illustrate the relationship between genotype and phenotype in the complex cellular network of saccharomyces cerevisiae. As a structure-oriented method, using elementary flux mode(EFM) an...The purpose of this work is to illustrate the relationship between genotype and phenotype in the complex cellular network of saccharomyces cerevisiae. As a structure-oriented method, using elementary flux mode(EFM) analysis can obtain its popularity in analysis of the robustness of the central metabolism, as well as network function of some organisms. However, this method has not been widely used for modeling gene deletion phenotype. By enumerating all the metabolic pathways, the EFM analysis presented herein can be used to identify the functional features and predict the growth phenotype of the S.cerevisiae. In comparison with the flux balance analysis(FBA), the performance of EFM analysis was superior to FBA in prediction of gene deletion phenotype. EFM analysis is demonstrated to be an effective tool for bridging the gap between metabolic network and growth phenotype.展开更多
Elementary flux mode （EFM） analysis was used in the metabolic analysis of central carbon metabolism in Saccharomyces cerevisiae based on constructed cellular network. Calculated from the metabolic model, the ethanol...Elementary flux mode （EFM） analysis was used in the metabolic analysis of central carbon metabolism in Saccharomyces cerevisiae based on constructed cellular network. Calculated from the metabolic model, the ethanol-producing pathway No. 37 furthest converts the substrate into ethanol among the 78 elementary flux modes. The in silico metabolic phenotypes predicted based on this analysis fit well with the fermentation performance of the engineered strains, KAM3 and KAMll, which confirmed that EFM analysis is valid to direct the construction of Saccharomyces cerevisiae engineered strains, to increase the ethanol yield.展开更多
以基因工程强化微藻三酰甘油(TAG)积累是实现微藻生物柴油应用化的途径之一。为进行有效的基因工程操作,研究分析了微藻代谢网络,以找出其中对TAG合成重要的反应。构建了异养及自养条件下小球藻产TAG过程核心代谢网络。采用改进CASOP(Co...以基因工程强化微藻三酰甘油(TAG)积累是实现微藻生物柴油应用化的途径之一。为进行有效的基因工程操作,研究分析了微藻代谢网络,以找出其中对TAG合成重要的反应。构建了异养及自养条件下小球藻产TAG过程核心代谢网络。采用改进CASOP(Computational approach for strain optimization aiming at high productivity)法分析网络中各反应的重要度。结果表明,主要的关键反应包括脂肪酸和TAG的合成反应以及提供NADPH的反应,特别是将NADH转化为NADPH的反应。此外,分析结果也部分解释了环境压力对TAG积累的作用。展开更多
文摘The purpose of this work is to illustrate the relationship between genotype and phenotype in the complex cellular network of saccharomyces cerevisiae. As a structure-oriented method, using elementary flux mode(EFM) analysis can obtain its popularity in analysis of the robustness of the central metabolism, as well as network function of some organisms. However, this method has not been widely used for modeling gene deletion phenotype. By enumerating all the metabolic pathways, the EFM analysis presented herein can be used to identify the functional features and predict the growth phenotype of the S.cerevisiae. In comparison with the flux balance analysis(FBA), the performance of EFM analysis was superior to FBA in prediction of gene deletion phenotype. EFM analysis is demonstrated to be an effective tool for bridging the gap between metabolic network and growth phenotype.
基金Supported by the National Natural Science Foundation of China （No.2002AA647040）
文摘Elementary flux mode （EFM） analysis was used in the metabolic analysis of central carbon metabolism in Saccharomyces cerevisiae based on constructed cellular network. Calculated from the metabolic model, the ethanol-producing pathway No. 37 furthest converts the substrate into ethanol among the 78 elementary flux modes. The in silico metabolic phenotypes predicted based on this analysis fit well with the fermentation performance of the engineered strains, KAM3 and KAMll, which confirmed that EFM analysis is valid to direct the construction of Saccharomyces cerevisiae engineered strains, to increase the ethanol yield.
文摘以基因工程强化微藻三酰甘油(TAG)积累是实现微藻生物柴油应用化的途径之一。为进行有效的基因工程操作,研究分析了微藻代谢网络,以找出其中对TAG合成重要的反应。构建了异养及自养条件下小球藻产TAG过程核心代谢网络。采用改进CASOP(Computational approach for strain optimization aiming at high productivity)法分析网络中各反应的重要度。结果表明,主要的关键反应包括脂肪酸和TAG的合成反应以及提供NADPH的反应,特别是将NADH转化为NADPH的反应。此外,分析结果也部分解释了环境压力对TAG积累的作用。
