Predicting the plant cell response in complex environmental conditions is a challenge in plant biology. Here we developed a resource allocation model of cellular and molecular scale for the leaf photosynthetic cell of Arabidopsis thaliana, based on the Resource Balance Analysis (RBA) constraint-based modeling framework. The RBA model contains the metabolic network and the major macromolecular processes involved in the plant cell growth and survival and localized in cellular compartments. We simulated the model for varying environmental conditions of temperature, irradiance, partial pressure of CO2 and O2, and compared RBA predictions to known resource distributions and quantitative phenotypic traits such as the relative growth rate, the C:N ratio, and finally to the empirical characteristics of CO2 fixation given by the well-established Farquhar model. In comparison to other standard constraint-based modeling methods like Flux Balance Analysis, the RBA model makes accurate quantitative predictions without the need for empirical constraints. Altogether, we show that RBA significantly improves the autonomous prediction of plant cell phenotypes in complex environmental conditions, and provides mechanistic links between the genotype and the phenotype of the plant cell.

中文翻译：

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用于植物细胞表型自主预测的资源分配建模


预测植物细胞在复杂环境条件下的反应是植物生物学的一项挑战。在这里，我们基于资源平衡分析 （RBA） 基于约束的建模框架，为拟南芥叶片光合细胞开发了细胞和分子尺度的资源分配模型。RBA 模型包含代谢网络和参与植物细胞生长和存活的主要大分子过程，并位于细胞区室中。我们模拟了温度、辐照度、CO2 和 O2 分压等不同环境条件的模型，并将 RBA 预测与已知的资源分布和定量表型特征（如相对增长率、C：N 比）进行比较，最后与成熟的 Farquhar 模型给出的 CO2 固定的经验特征进行了比较。与磁通平衡分析等其他基于约束的标准建模方法相比，RBA 模型无需经验约束即可做出准确的定量预测。总而言之，我们表明 RBA 显着改善了复杂环境条件下植物细胞表型的自主预测，并在基因型和植物细胞表型之间提供了机制联系。