Limits and trade-offs of feedback control

反馈控制的限制和权衡

• 批准号: 9291476
• 负责人: Johan Paulsson
• 金额: $ 35.26万
• 依托单位: HARVARD MEDICAL SCHOOL
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-04-01 至 2019-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9291476
• 关键词: Address; Affect; Bacteria; Behavior; Biochemical; Biological Assay; Biological Models; Biological Process; Biology; Biotechnology; Cells; Cessation of life; Complex; Concentration measurement; Control Groups; Disease; Disease Outbreaks; Drops; Drug resistance; Engineering; Failure; Feedback; Gene Cluster; Gene Expression; Goals; Grant; Health; Home environment; Horizontal Gene Transfer; Hospitals; Human; Human body; Individual; Industry; Intuition; Knowledge; Libraries; Mathematics; Measures; Medical; Methods; Microfluidic Microchips; Modeling; Modification; Molecular; Molecular Biology; Noise; Pharmaceutical Preparations; Phenotype; Plasmids; Positioning Attribute; Process; Property; Queuing Theory; Reaction; Research Personnel; Resolution; Scheme; Signaling Molecule; Source; System; Temperature; Testing; Time; Work; base; biological systems; chemical reaction; chromosome replication; design; experimental analysis; inhibitor/antagonist; insight; mathematical methods; mathematical theory; mutant; novel; public health relevance; replicator; theories; tool

 DESCRIPTION (provided by applicant): Negative feedback control is essential to make biological systems stable to internal and external perturbations, just as homes need thermostats to maintain a fixed room temperature. In cells feedback is used to regulate everything from gene expression to chromosome replication, and its failure causes a range of human disorders. But our understanding of feedback in biology is very incomplete. Most theoretical approaches use mathematical frameworks that are poorly suited to describe cells because they ignore a main source of perturbations: chemical reactions involve molecules in low numbers and since each individual reaction is probabilistic, fluctuations in concentrations arise spontaneously. Unlike human-designed systems, where the control systems (e.g. thermostats) are fundamentally different from what they control (temperature fluctuations), the control systems in cells are similar to the processes they control. This makes it very difficult for cells to suppress perturbations, and also makes it very difficult for researchers to analyze the control system design. Experimentally, very few systems allow both accurate measurements of concentrations in single cells and systematic modifications of the control system to analyze how they affect the system. Analyses can also focus so closely on the specific details of one specific system that general guiding principles are overlooked or misinterpreted. We propose to address these problems by developing new mathematical approaches and systematically applying our novel experimental assays to simple model systems, bacterial plasmids. Our preliminary theory demonstrates hard limits on the ability of negative feedback to suppress fluctuations in cells. It also suggests creative and counter-intuitive mechanisms that minimize these problems. Remarkably enough, we have found examples of these in plasmid gene clusters that we know are under strong selection to suppress noise. In addition to the usefulness of these systems to understand feedback control, bacterial plasmids are also very relevant medically, since they cause the majority of drug resistance cases in hospitals, a problem that leads to millions of serious illnesses and tens of thousands of deaths annually in the US alone. They are also key tools for the biotechnology industry, where the fluctuation suppression properties we study are a significant nuisance. The unmatched experimental tractability of plasmids allows us to systematically vary control properties and rigorously test the mathematical descriptions experimentally, leading to a deeper understanding of feedback mechanisms and also an increase in useful knowledge about plasmid behavior.

 描述（由适用提供）：负反馈控制对于使生物系统稳定在内部和外部扰动中至关重要，就像房屋需要恒温器以保持固定的室温一样。在细胞中，反馈用于调节从基因表达到染色体复制的所有内容，其失败会导致一系列人类疾病。但是，我们对生物学反馈的理解非常不完整。大多数理论方法都使用数学框架来描述细胞的数学框架，因为它们忽略了扰动的主要来源：化学反应涉及分子数量少，并且由于每个单独的反应都是概率概率的，因此浓度的波动是在赞助的。与人类设计的系统不同，控制系统（例如恒温器）与其控制（温度波动）根本不同，细胞中的控制系统与它们控制的过程相似。这使得细胞很难抑制扰动，并且也使研究人员很难分析控制系统设计。在实验上，很少有系统允许对单个细胞中的浓度进行准确的测量以及控制系统的系统修饰，以分析它们如何影响系统。分析也可以紧密关注一个特定系统的特定细节，以至于一般指导原则被忽略或错过了。我们建议通过开发新的数学方法来解决这些问题，并系统地将我们的新实验评估应用于简单模型系统，细菌质粒。我们的初步理论证明了负反馈抑制细胞波动的能力的严格限制。它还提出了使这些问题最小化的创造性和违反直觉机制。值得注意的是，我们已经在质粒基因簇中发现了这些例子，我们知道这些示例正在强烈选择以抑制噪声。除了这些系统了解反馈控制的有用性外，细菌质粒在医学上也非常相关，因为它们在医院中引起了大多数耐药性病例，这一问题会导致数百万个严重疾病和仅在美国每年在美国每年数以万计的死亡。它们也是生物技术行业的关键工具，在该行业中，我们研究的波动抑制属性是一个重要的滋扰。质粒的无与伦比的实验障碍使我们能够系统地改变控制属性并严格地测试数学描述，从而更深入地了解反馈机制，并增加对质粒行为的有用知识的增加。