M13 Phage: A Model System for Complex Control of Multicomponent Processes in Biology

自然进化的系统通常包含复杂的嵌套控制机制，涉及协调和竞争的生物分子相互作用，转化为无数的表型和行为。生物学中的一个重大挑战是在分子水平上理解遗传编码指令如何转化为生命系统中观察到的行为。然而，用于定量研究生物过程的复杂控制的易处理的模型系统通常是缺乏的，但会促进对生物学控制的理解，并转化为用于在设计的生物系统中设计复杂控制架构的工具，如其他模型系统所具有的。该项目的重点是提高一个简单的生物系统，噬菌体M13的定量分子水平的理解。噬菌体，感染细菌的病毒，一直是分子生物学发展的核心。 作为理解分子现象的模型系统，噬菌体系统仍然处于纳米材料和纳米医学研究的最前沿，并通过噬菌体展示作为药物和材料发现的重要组分生成技术。 PI将开发控制噬菌体系统行为的分子相互作用的详细模型，这将提供定量的见解，以实现合成生物学，纳米技术，生物制造和医学的应用。 PI将使用交互式平台让K-12学生参与计算系统生物学项目，将本科生融入研究，并培训学生，从而为下一代跨学科科学家和工程师的准备做出贡献。在先前工作的基础上，包括模拟M13生长，整合了50年的实验观察，这个项目的目标是评估M13生命周期中的嵌套反馈控制回路，并填补M13生物学定量理解的空白。本项目的第一个目标是定量研究M13蛋白质-蛋白质和蛋白质-DNA相互作用，这些相互作用控制着噬菌体DNA复制和系统水平对DNA复制程序修改的响应。第二个目标涉及鉴定和定量蛋白质-RNA相互作用，其调节噬菌体蛋白质产生的时间和程度。 在此目标下，将研究修饰蛋白质-RNA控制机制的系统水平效应。该项目的最终目标是将实验结果整合到仿真模型中。 这一目标将侧重于用目标1和目标2的新定量数据增强模型，并通过将系统级实验的结果与预测进行比较来评估目前的理解状况。需要重复的理论完善和实验测试循环来构建M13噬菌体的工程设计循环。这项提议将大大提高对M13生物学的定量理解，并为设计和生产高度改性的粒子提供基础设施。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Naturally evolved systems often contain complex nested control mechanisms involving coordinated and competing biomolecular interactions that translate into a myriad of phenotypes and behaviors. One of the grand challenges in biology is the development of a molecular level understanding of how genetically-encoded instructions are converted into the behaviors observed in living systems. However, tractable model systems for quantitatively investigating the complex control of biological processes are generally lacking but would advance the understanding of control in biology and translate, as other model systems have, into tools for engineering complex control architectures in designed biological systems. The focus of this project is on improving the quantitative molecular level understanding of a simple biological system, bacteriophage M13. Bacteriophages, viruses that infect bacteria, have been central to the development of molecular biology. As model systems for understanding molecular phenomena, phage systems remain at the forefront of research in nanomaterials and nanomedicine and act as important component-generating technologies for drug and material discovery through phage display. The PI will develop a detailed model of the molecular interactions that govern the behavior of phage systems, which will provide quantitative insight to enable applications in synthetic biology, nanotechnology, bio-manufacturing and medicine. The PI will use interactive platforms to engage K-12 students in computational systems biology projects, integrate undergraduates in research, and train students thus contributing to the preparation of the next generation of interdisciplinary scientists and engineers.Building on previous work involving a simulation of M13 growth that integrates 50 years of experimental observations, the goals of this project are to evaluate the nested feedback control loops in the M13 life cycle and fill in gaps in the quantitative understanding of M13 biology. The first objective of the current project involves quantification of the poorly-understood M13 protein-protein and protein-DNA interactions that govern phage DNA replication and the system level response to modifications of the DNA replication program. The second objective involves the identification and quantification of the protein-RNA interactions that regulate the timing and extent of phage protein production. Within this aim the system level effects of modifying the protein-RNA control mechanisms will be investigated. The final objective of the project is to integrate the results of the experiments into the simulation model. This aim will focus on augmenting the model with new quantitative data from Aims 1 and 2, and evaluating the present state of understanding by comparing the results of the system level experiments to predictions. Repeated cycles of theoretical refinement and experimental testing are required to build an engineering design cycle for M13 phage. This proposal will result in a greatly improved quantitative understanding of M13 biology and an infrastructure for the design and production of highly modified particles.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.