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A global resource allocation strategy governs growth transition kinetics of Escherichia coli

机译：全球资源分配策略控制大肠杆菌的生长过渡动力学

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摘要

A grand challenge of systems biology is to predict the kinetic responses of living systems to perturbations starting from the underlying molecular interactions. Changes in the nutrient environment have long been used to study regulation and adaptation phenomena in microorganisms(1-3) and they remain a topic of active investigation(4-11). Although much is known about the molecular interactions that govern the regulation of key metabolic processes in response to applied perturbations(12-17), they are insufficiently quantified for predictive bottom-up modelling. Here we develop a top-down approach, expanding the recently established coarse-grained proteome allocation models(15,18-20) from steady-state growth into the kinetic regime. Using only qualitative knowledge of the underlying regulatory processes and imposing the condition of flux balance, we derive a quantitative model of bacterial growth transitions that is independent of inaccessible kinetic parameters. The resulting flux-controlled regulation model accurately predicts the time course of gene expression and biomass accumulation in response to carbon upshifts and downshifts (for example, diauxic shifts) without adjustable parameters. As predicted by the model and validated by quantitative proteomics, cells exhibit suboptimal recovery kinetics in response to nutrient shifts owing to a rigid strategy of protein synthesis allocation, which is not directed towards alleviating specific metabolic bottlenecks. Our approach does not rely on kinetic parameters, and therefore points to a theoretical framework for describing a broad range of such kinetic processes without detailed knowledge of the underlying biochemical reactions.
机译：系统生物学的一个巨大挑战是从基本的分子相互作用开始，预测生命系统对扰动的动力学响应。营养环境的变化长期以来一直用于研究微生物的调节和适应现象（1-3），它​​们仍然是积极研究的主题（4-11）。尽管人们对响应于所施加扰动的关键代谢过程的调控所涉及的分子相互作用知之甚少（12-17），但是对于预测性自下而上的建模，它们的量化还不够。在这里，我们开发了一种自上而下的方法，将最近建立的粗粒蛋白质组分配模型（15,18-20）从稳态增长扩展到动力学机制。仅使用基本调节过程的定性知识并施加通量平衡的条件，我们得出了细菌生长转变的定量模型，该模型独立于不可获取的动力学参数。生成的通量控制调节模型可准确预测基因表达和生物量积累的时间过程，以响应无可调整参数的碳上移和下移（例如双峰移动）。正如该模型所预测并通过定量蛋白质组学验证的那样，由于蛋白质合成分配的严格策略（并非旨在缓解特定的代谢瓶颈），细胞对营养物的迁移表现出次佳的恢复动力学。我们的方法不依赖于动力学参数，因此在没有详细了解潜在生化反应的情况下，指向了用于描述此类动力学过程的理论框架。

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  • 来源
    《Nature》 |2017年第7678期|119-123|共5页
  • 作者

    Erickson David W.; Schink Severin J.; Patsalo Vadim; Williamson James R.; Gerland Ulrich; Hwa Terence;

  • 作者单位

    Univ Calif San Diego, Dept Phys, La Jolla, CA 92093 USA;

    Univ Calif San Diego, Dept Phys, La Jolla, CA 92093 USA|Tech Univ Munich, Phys Dept, Phys Complex Biosyst, D-85748 Garching, Germany;

    Scripps Res Inst, Dept Chem, Skaggs Inst Chem Biol, Dept Integrat Struct & Computat Biol, La Jolla, CA 92037 USA;

    Scripps Res Inst, Dept Chem, Skaggs Inst Chem Biol, Dept Integrat Struct & Computat Biol, La Jolla, CA 92037 USA;

    Tech Univ Munich, Phys Dept, Phys Complex Biosyst, D-85748 Garching, Germany;

    Univ Calif San Diego, Dept Phys, La Jolla, CA 92093 USA;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
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