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Analysis and optimization of C3 photosynthetic carbon metabolism

机译:C 3 光合碳代谢的分析与优化

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摘要

We have studied the C 3 photosynthetic carbon metabolism centering our investigation on the following four design principles. (1) Optimization of the photosynthetic rate by modifying the partitioning of resources between the different enzymes of the C 3 photosynthetic carbon metabolism using a constant amount of protein-nitrogen. (2) Identify sensitive and less sensitive enzymes of the studied model. (3) Maximize photosynthetic productivity rate through the choice of robust enzyme concentrations using a new precise definition of robustness. (4) Modeling photosynthetic carbon metabolism as a multi-objective problem of two competing biological selection pressures: light-saturated photosynthetic rate versus total protein-nitrogen requirement. Using the designed single-objective optimization algorithms, PAO and A-CMA-ES, we have obtained an increase in photosynthetic productivity of the 135% from 15.486 μmol m -2 s -1 to 36.382 μmol m -2 s -1 , and improving the previous best-found photosynthetic productivity value (27.261 μmol m -2 s -1 , 76% of enhancement). Optimized enzyme concentrations express a maximal local robustness (100%) and a high global robustness (97.2%), satisfactory properties for a possible "in vitro" manufacturing of the optimized pathway. Morris sensitivity analysis shows that 11 enzymes over 23 are high sensitive enzymes, i.e., the most influential enzymes of the carbon metabolism model. Finally, we have obtained the tradeoff between the maximization of the leaf CO 2 uptake rate and the minimization of the total protein-nitrogen concentration. This trade-off search has been carried out for the three ciconcentrations referring to the estimate of CO 2 concentration in the atmosphere characteristic of 25 million years ago, nowadays and in 2100 a.C. Remarkably, the three Pareto frontiers identify the highest photosynthetic productivity rates together with the fewest protein-nitrogen usage. © 2010 IEEE.
机译:我们围绕以下四个设计原理进行了研究,从而研究了C 3光合碳代谢。 (1)通过使用恒定量的蛋白质氮来修改C 3光合碳代谢的不同酶之间的资源分配,从而优化光合速率。 (2)确定研究模型的敏感和较不敏感的酶。 (3)通过使用新的稳健性精确定义来选择稳健的酶浓度,从而最大化光合生产率。 (4)将光合碳代谢建模为两个竞争的生物选择压力的多目标问题:光饱和光合速率与总蛋白质氮需求。使用设计的单目标优化算法PAO和A-CMA-ES,我们将光合作用的生产率从15.486μmolm -2 s -1增加到了36.382μmolm -2 s -1,提高了135%,并提高了以前的最佳光合作用生产力值(27.261μmolm -2 s -1,增强的76%)。优化的酶浓度表现出最大的局部鲁棒性(100%)和高的全局鲁棒性(97.2%),这是优化路径可能“体外”制造的令人满意的特性。莫里斯敏感性分析表明,超过23种的11种酶是高敏感性酶,即碳代谢模型中影响最大的酶。最后,我们获得了最大的叶片CO 2吸收率与最小的总蛋白氮​​浓度之间的权衡。这种权衡的搜索是针对三个ccentcents进行的,参考了2500万年前,今天和2100 a.C大气特征中的CO 2浓度估计值。值得注意的是,这三个帕累托前沿确定了最高的光合作用生产率和最少的蛋白质氮使用量。 ©2010 IEEE。

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