Whole-cell modeling in yeast predicts compartment-specific proteome constraints that drive metabolic strategies
Whole-cell modeling in yeast predicts compartment-specific proteome constraints that drive metabolic strategies
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酵母的全细胞建模预测了驱动代谢策略的区室特异性蛋白质组限制
DOI：
10.1101/2021.06.11.448029
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发表时间：
2021
期刊：
影响因子：
--
通讯作者：
Elsemman I
中科院分区：
文献类型：
--
作者：
Elsemman I
当条件发生变化时，单细胞生物会重新调整它们的新陈代谢，以维持细胞的维持和细胞的生长。这种重新布线可以被理解为在蜂窝约束下的资源重新分配。真核细胞含有代谢活跃的细胞器，如线粒体，竞争胞质空间和资源，相关的细胞约束的性质仍有待确定的细胞。在这里，我们提出了一个全面的代谢模型的酵母细胞，基于其完整的代谢反应网络扩展与蛋白质合成和降解反应。该模型预测代谢通量和相应的蛋白质表达，通过限制特定的隔室蛋白质池和最大化的增长率。将模型预测与定量实验数据进行比较表明，在葡萄糖限制下，线粒体约束限制了乙醇形成开始时的生长-称为Crabtree效应。然而，在糖过量的情况下，对总胞质体积的限制决定了溢流代谢。因此，我们的综合模型确定了条件依赖性和特定于隔室的限制，可以解释生长速率优化的代谢策略和蛋白质表达谱，为理解真核细胞的代谢适应提供了一个框架。
When conditions change, unicellular organisms rewire their metabolism to sustain cell maintenance and cellular growth. Such rewiring may be understood as resource re-allocation under cellular constraints. Eukaryal cells contain metabolically active organelles such as mitochondria, competing for cytosolic space and resources, and the nature of the relevant cellular constraints remain to be determined for such cells. Here, we present a comprehensive metabolic model of the yeast cell, based on its full metabolic reaction network extended with protein synthesis and degradation reactions. The model predicts metabolic fluxes and corresponding protein expression by constraining compartment-specific protein pools and maximising growth rate. Comparing model predictions with quantitative experimental data suggests that under glucose limitation, a mitochondrial constraint limits growth at the onset of ethanol formation—known as the Crabtree effect. Under sugar excess, however, a constraint on total cytosolic volume dictates overflow metabolism. Our comprehensive model thus identifies condition-dependent and compartment-specific constraints that can explain metabolic strategies and protein expression profiles from growth rate optimisation, providing a framework to understand metabolic adaptation in eukaryal cells.
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影响因子：
3.2
作者：
Teusink, B;Diderich, JA;Walsh, MC
通讯作者：
Walsh, MC
DOI：
10.1073/pnas.90.17.8068
发表时间：
1993-09-01
影响因子：
11.1
作者：
JENSEN, PR;MICHELSEN, O;WESTERHOFF, HV
通讯作者：
WESTERHOFF, HV
影响因子：
9.9
作者：
Zhuang, Kai;Vemuri, Goutham N.;Mahadevan, Radhakrishnan
通讯作者：
Mahadevan, Radhakrishnan
影响因子：
4.3
作者：
Adadi R;Volkmer B;Milo R;Heinemann M;Shlomi T
通讯作者：
Shlomi T
DOI：
10.1073/pnas.0707476104
发表时间：
2007-10-02
影响因子：
11.1
作者：
Daran-Lapujade, Pascale;Rossell, Sergio;Bakker, Barbara M.
通讯作者：
Bakker, Barbara M.