Dynamics, Control, and Design of Bacteriophage T7

描述(申请人提供)：由自然系统编码的设计有时通过进化进行优化，以提供解决(I)个人发展和(Ii)在许多环境和进化中持续生存所带来的物理问题的解决方案。然而，我们的自然系统模型，在分子和细胞尺度上，主要是描述性的。我们的模型通常概括了流程中涉及的部分、流程发生的时间和地点，以及流程如何工作。由于系统可能以特定方式设计的原因造成的约束通常会缺失。我们还经常缺乏描述系统随时间变化的物理状态的精确实验数据，并且，当我们试图对系统的动态行为进行建模时，会使用基于细胞内部硬球稀薄气体近似的建模框架。毫不奇怪，随着我们的模型的规模和复杂性的增加，它们在帮助我们预测分子和细胞系统的新扰动导致的行为方面的效用是有限的。 为多组分分子和细胞系统的动态行为建立模型的最佳实用基础是什么？我们能不能通过探索为什么自然生物系统可能是按我们发现的那样设计的，来更好地约束我们的自然生物系统模型？我们的实验是否对自然遗传系统中编码的信息产生了足够的理解，以至于我们现在应该能够预测它们的行为？我们可以用定义更好、更容易建模、交互和预测的工程代理来取代自然生命系统吗？ 为了在这些问题上取得进展，我们计划利用一个特性相对较好的自然生物系统--噬菌体T7。具体地说，我们建议：(1)基于我们目前对影响噬菌体基因表达的遗传元件的了解，设计和构建一个合成的噬菌体T7基因组；(2)通过表征合成基因组相对于原始‘野生型1分离物’的行为，测试我们的模型中T7基因组上编码的部分；(3)通过测试T7基因表达的早期和中期的反馈控制被用来在一系列不确定的细胞环境中调节表达资源的分配的假设，来约束我们的模型。

DESCRIPTION (provided by applicant): The designs encoded by natural systems are sometimes optimized by evolution to provide solutions to the physical problems posed by both (i) individual development and (ii) continued viability across many environments and evolution. However, our models of natural systems, at the molecular and cellular scales, are largely descriptive. Our models typically recapitulate what parts are involved in a process, when and where a process occurs, and how the process works. Constraints due to why a system might be designed in a particular way are typically missing. We also often lack precise experimental data describing the physical state of our system over time and, when we attempt to model the dynamic behavior of the system, make use of a modeling framework that is based on a hard-sphere dilute gas approximation for the inside of a cell. Not surprisingly, as our models increase in size and complexity, their utility in helping us to predict the behavior that results from novel perturbations to molecular and cellular systems is limited. What is the best practical foundation on which to ground models for the dynamic behavior of many- component molecular and cellular systems? Can we better constrain our models of natural biological systems by exploring why the systems might be designed as we find them? Do our experiments produce enough understanding of the information encoded in natural genetic systems such that we should now expect to be able to predict their behavior? Could we replace natural living systems with engineered surrogates that are better defined and easier to model, interact with, and predict? To make progress on these questions we plan to work with a relatively well-characterized natural biological system, bacteriophage T7. Specifically, we propose to: (1) Design and construct a synthetic bacteriophage T7 genome that is based on our current understanding of the genetic elements that contribute to phage gene expression, (2) Test our models for the parts encoded on the T7 genome by characterizing the behavior of our synthetic genome relative to the behavior of the original 'wild-type1 isolate, (3) Constrain our models for how the parts of T7 produce a functioning whole by testing the hypothesis that feedback control during early and middle T7 gene expression is used to tune the allocation of expression resources across a range of uncertain cellular environments.