Limits and Trade-offs of Feedback Control

描述(申请人提供)：负反馈控制对于使生物系统对内部和外部扰动保持稳定是必不可少的。它被用来调节从体温到基因表达的一切，它的失败会导致一系列人类疾病。但我们对生物学中的反馈的理解是不完整和不连贯的。大多数系统的理论方法是基于确定性动力学的，不太适合微观细胞事件，很少有系统允许对给定细胞中单个分子的数量进行准确的实验测量。以前的工作过于集中于每个系统的细节，以至于忽略了一般指导原则，这反过来又使详细分析变得困难。我们建议通过开发新的数学方法和系统地将我们的新的实验分子计数分析应用于简单的模型系统来解决这些问题。我们的初步理论证明了对抑制细胞系统波动的负反馈能力的硬限制，以及减少一种类型的变化反而放大另一种类型的变化的总体挫折权衡。它还提出了使这些问题最小化的创造性机制，值得注意的是，我们现在已经在生物学中找到了这些例子。我们建议通过将统计物理和控制理论的中心概念集成到一个新的相干框架中来扩展个别定理，该框架使得关于强非线性和奇异系统的精确定量描述成为可能。这一理论还被用来激励、设计和解释两个系统的定量实验，这两个系统提高了大肠杆菌的毒力和耐药性。我们专注于细菌质粒的复制控制，其中噪音抑制是必不可少的。质粒的无与伦比的易操纵性使我们能够系统地改变控制回路的性质，并严格测试一般定理。我们将把这些结果与应力反应西格玛系数rpos的结果进行比较，我们认为负反馈可能反而会增强变异。与公共健康相关：我们的研究将有助于为有效研究生物学中的随机性奠定基础：它来自哪里，它是如何控制的，物理学对生物系统如何抑制噪音设定了什么限制，以及生物系统利用这些限制中明显的漏洞的创造性方式。我们相信，这将揭示新的原则，有助于我们了解生物系统是如何进化的，以及它们在健康和疾病中如何发挥作用，特别是在促进细菌耐药性和毒力的系统中。

DESCRIPTION (provided by applicant): Negative feedback control is essential to make biological systems stable to internal and external perturbations. It is used to regulate everything from body temperature to gene expression, and its failure causes a range of human disorders. But our understanding of feedback in biology is incomplete and incoherent. Most systematic theoretical approaches are based on deterministic kinetics, poorly suited for microscopic cellular events, and few systems allow accurate experimental measurements of the numbers of individual molecules in a given cell. Prior work focused so closely on the details of each system that general guiding principles have been overlooked, in turn making detailed analysis difficult. We propose to address these problems by developing new mathematical approaches and systematically applying our novel experimental molecule counting assays to simple model systems. Our preliminary theory demonstrates hard limits on the ability of negative feedback to suppress fluctuations in cellular systems, and general frustration trade-offs where reducing one type of variation instead amplifies another. It also suggests creative mechanisms that minimize these problems, and remarkably enough, we have now found examples of these in biology. We propose to extend the individual theorems by integrating central concepts from statistical physics and control theory into a novel coherent framework that makes it possible to make exact quantitative statements about strongly nonlinear and exotic systems. The theory is also used to motivate, design and interpret quantitative experiments for two systems that promote virulence and drug resistance in Escherichia coli. We focus on replication control of bacterial plasmids, where noise suppression is essential. The unmatched tractability of plasmids allows us to systematically vary control loop properties and rigorously test the general theorems. We will compare these results with those for stress response sigma factor RpoS, where we believe negative feedback may instead enhance variation. PUBLIC HEALTH RELEVANCE: Our studies will help lay the groundwork for effective studies of randomness in biology: where it comes from, how it is controlled, what limits physics sets on how biological systems suppress noise, and the creative ways that biological systems exploit apparent loopholes in those limits. We believe this will expose new principles that will help us understand how biological systems evolved, and how they function in health and disease particularly in systems that promote drug resistance and virulence in bacteria.