Cells can sense changes in their extracellular environment and subsequently adapt their biomass composition. Nutrient abundance defines the capability of the cell to produce biomass components. Under nutrient-limited conditions, resource allocation dramatically shifts to carbon-rich molecules. Here, we used dynamic biomass composition data to predict changes in growth and reaction flux distributions using the available genome-scale metabolic models of five eukaryotic organisms (three heterotrophs and two phototrophs). We identified temporal profiles of metabolic fluxes that indicate long-term trends in pathway and organelle function in response to nitrogen depletion. Surprisingly, our calculations of model sensitivity and biosynthetic cost showed that free energy of biomass metabolites is the main driver of biosynthetic cost and not molecular weight, thus explaining the high costs of arginine and histidine. We demonstrated how metabolic models can accurately predict the complexity of interwoven mechanisms in response to stress over the course of growth.

中文翻译：

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动态资源分配驱动真核生物在氮饥饿下生长。

细胞可以感知其细胞外环境的变化，并随后适应其生物量组成。营养丰富度定义了细胞产生生物质成分的能力。在营养有限的条件下，资源分配急剧转移到富含碳的分子上。在这里，我们使用动态生物量组成数据，使用五个真核生物（三个异养生物和两个光养生物）的可用基因组规模代谢模型来预测生长和反应通量分布的变化。我们确定了代谢通量的时间概况，表明响应氮耗竭的途径和细胞器功能的长期趋势。出奇，我们对模型敏感性和生物合成成本的计算表明，生物质代谢产物的自由能是生物合成成本的主要驱动力，而不是分子量，从而解释了精氨酸和组氨酸的高成本。我们证明了代谢模型如何准确预测交联机制的复杂性，以响应生长过程中的压力。