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A yield-cost tradeoff governs Escherichia coli's decision between fermentation and respiration in carbon-limited growth.
npj Systems Biology and Applications ( IF 3.5 ) Pub Date : 2019-05-01 , DOI: 10.1038/s41540-019-0093-4
Matteo Mori 1 , Enzo Marinari 2, 3 , Andrea De Martino 4, 5
Affiliation  

Living cells react to changes in growth conditions by re-shaping their proteome. This accounts for different stress-response strategies, both specific (i.e., aimed at increasing the availability of stress-mitigating proteins) and systemic (such as large-scale changes in the use of metabolic pathways aimed at a more efficient exploitation of resources). Proteome re-allocation can, however, imply significant biosynthetic costs. Whether and how such costs impact the growth performance are largely open problems. Focusing on carbon-limited E. coli growth, we integrate genome-scale modeling and proteomic data to address these questions at quantitative level. After deriving a simple formula linking growth rate, carbon intake, and biosynthetic costs, we show that optimal growth results from the tradeoff between yield maximization and protein burden minimization. Empirical data confirm that E. coli growth is indeed close to Pareto-optimal over a broad range of growth rates. Moreover, we establish that, while most of the intaken carbon is diverted into biomass precursors, the efficiency of ATP synthesis is the key driver of the yield-cost tradeoff. These findings provide a quantitative perspective on carbon overflow, the origin of growth laws and the multidimensional optimality of E. coli metabolism.

中文翻译:


在碳限制生长中,产量与成本的权衡决定了大肠杆菌在发酵和呼吸之间的决定。



活细胞通过重塑蛋白质组来对生长条件的变化做出反应。这解释了不同的应激反应策略,既有特定的(即,旨在增加缓解应激蛋白质的可用性),也有系统的(例如,为了更有效地利用资源而大规模改变代谢途径的使用)。然而,蛋白质组的重新分配可能意味着巨大的生物合成成本。这些成本是否以及如何影响增长绩效在很大程度上是一个悬而未决的问题。我们专注于碳限制的大肠杆菌生长,整合基因组规模建模和蛋白质组数据,以在定量水平上解决这些问题。在推导出一个将生长速率、碳摄入量和生物合成成本联系起来的简单公式后,我们表明最佳生长是产量最大化和蛋白质负担最小化之间权衡的结果。经验数据证实,大肠杆菌的生长在广泛的增长率范围内确实接近帕累托最优。此外,我们确定,虽然大部分摄入的碳被转化为生物质前体,但 ATP 合成的效率是产量与成本权衡的关键驱动因素。这些发现为碳溢出、生长规律的起源和大肠杆菌代谢的多维最优性提供了定量视角。
更新日期:2019-05-01
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