Dynamics, Control, and Design of Bacteriophage T7

噬菌体 T7 的动力学、控制和设计

• 批准号: 7390745
• 负责人: DREW ENDY
• 金额: $ 20.93万
• 依托单位: MASSACHUSETTS INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-04-01 至 2009-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7390745
• 关键词: Bacteriophage T7; Bacteriophages; Behavior; Biological; Cells; Data; Development; Engineering; Environment; Evolution; Feedback; Foundations; Gases; Gene Expression; Genetic; Genome; Individual; Modeling; Molecular; Organism; Process; Range; Relative (related person); Research Personnel; Resources; Solutions; System; Testing; Time; Work; base; design; design and construction; genetic element; novel; physical state; programs; research study; size

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.

描述（由申请人提供）：自然系统编码的设计有时会通过进化来优化，以提供（i）个人发展和（ii）在许多环境和进化中持续可行性所带来的物理问题的解决方案。但是，我们在分子和细胞尺度上的天然系统模型在很大程度上是描述性的。我们的模型通常会概括过程中涉及哪些部分，过程何时何地以及过程的工作方式。由于为什么通常会以特定方式设计系统，因此限制通常丢失。我们通常还缺乏随着时间的推移描述系统物理状态的精确实验数据，并且当我们尝试建模系统的动态行为时，请使用基于细胞内部的硬球稀释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新型扰动对分子和细胞系统产生的行为方面的效用受到限制。 为多组分分子和细胞系统的动态行为扎根的最佳实用基础是什么？我们能否通过探索为什么在我们发现的过程中设计系统来更好地限制天然生物系统的模型？我们的实验是否对自然遗传系统中编码的信息产生足够的了解，以便我们现在应该期望能够预测其行为？我们能否用工程化的替代物代替自然生活系统，这些替代物的定义更好，更易于建模，与之互动和预测？ 为了在这些问题上取得进展，我们计划与相对良好的自然生物系统（噬菌体T7）合作。具体而言，我们提出：（1）设计和构建一个合成菌株T7基因组，基于我们对有助于噬菌体基因表达的遗传元素的当前理解，（2）测试我们的模型，用于在T7基因组上编码的部分，通过表征我们的合成基因组的行为，相对于原始'wild-type的行为来表征我们的合成基因组的行为。检验以下假设：在早期和中间T7基因表达过程中的反馈控制用于调整一系列不确定的细胞环境中表达资源的分配。