Department of Biology, Stanford University, Stanford, United States.
Elife. 2023 Mar 10;12:e84878. doi: 10.7554/eLife.84878.
Effective coordination of cellular processes is critical to ensure the competitive growth of microbial organisms. Pivotal to this coordination is the appropriate partitioning of cellular resources between protein synthesis via translation and the metabolism needed to sustain it. Here, we extend a low-dimensional allocation model to describe the dynamic regulation of this resource partitioning. At the core of this regulation is the optimal coordination of metabolic and translational fluxes, mechanistically achieved via the perception of charged- and uncharged-tRNA turnover. An extensive comparison with ≈ 60 data sets from establishes this regulatory mechanism's biological veracity and demonstrates that a remarkably wide range of growth phenomena in and out of steady state can be predicted with quantitative accuracy. This predictive power, achieved with only a few biological parameters, cements the preeminent importance of optimal flux regulation across conditions and establishes low-dimensional allocation models as an ideal physiological framework to interrogate the dynamics of growth, competition, and adaptation in complex and ever-changing environments.
有效的细胞过程协调对于确保微生物的竞争生长至关重要。这种协调的关键是在蛋白质合成(通过翻译)和维持所需的代谢之间适当分配细胞资源。在这里,我们扩展了一个低维分配模型来描述这种资源分配的动态调节。这种调节的核心是通过感知 charged-tRNA 和 uncharged-tRNA 周转来实现代谢和翻译通量的最佳协调。与来自 ≈ 60 个数据集的广泛比较证实了这种调节机制的生物学真实性,并表明可以以定量精度预测稳态内外的各种生长现象。这种预测能力仅用几个生物学参数即可实现,这证明了在不同条件下进行最优通量调节的至关重要性,并确立了低维分配模型作为一种理想的生理框架,可用于研究复杂和不断变化的环境中生长、竞争和适应的动态。