Collaborative Research: Developing a multi-scale understanding of microtubule dynamic instability

在广泛的生物体中，大多数细胞都包含一个称为细胞骨架的动态子结构，这是一个基于蛋白质的聚合物和相关蛋白质的网络，在细胞运动、DNA分割和内部细胞组织中具有基础作用。许多细胞骨架聚合物的一个关键方面是，它们需要以ATP(或GTP)形式的化学能来维持聚合状态。这种能量的利用使细胞骨架细丝能够做功，对内部和外部信号做出动态反应，并进行自我组织。这项工作的主要目标是使用实验和计算建模相结合的方法来开发一个改进的理论框架，以了解和预测这些动态细胞骨架聚合物在不同尺度上的行为。更具体地说，这项拟议的工作旨在确定聚合物亚单位的生化特性(包括它们燃烧ATP或GTP的速率)如何与单个细丝的行为以及细丝群体的整体行为相关。此外，该项目还研究了细丝结合蛋白如何共同作用来调节细丝的动态。虽然这项工作是基础科学，但它在纳米技术和合成生物学方面具有实际应用的潜力。通过这个项目，研究生和本科生将接受计算建模和实验生物学的跨学科培训。高中教师和学生也将参与研究过程。通过这个项目制作的免费开放源码软件和教程将帮助各级学生和研究人员对动态聚合物系统有一个直观的了解。从技术角度来看，该项目有四个具体目标，其中大部分集中在一种被称为微管的细胞骨架细丝上。单个微管表现出一种称为动态不稳定的戏剧性行为，在这种行为中，它们在延长的增长期和解聚期之间随机交替。(1)第一个项目的目标是通过将微管的行为与其尖端的亚单位水平结构相关联来开发和测试微管动态不稳定性中的转变机制的假说。该方法将利用与先前建立的微管动力学详细计算模型、用于识别微管行为并对其进行统计分类的新数据分析工具以及在高时间和空间分辨率下获得的实验数据相结合的工作。(2)第二个目标是建立对亚基的生物化学特性(动力学速率常数)、细丝的行为(例如，动态不稳定、跑动)和聚合物系统的属性(例如，临界浓度、稳态)之间的关系的预测性理解。该方法将结合使用计算建模(使用目标1中使用的模型的变体进行)和对微管蛋白的细菌近亲PhuZ的实验(之所以选择，是因为这种蛋白质的野生型和改变版本可以在细菌中表达并在体外进行表征)。(3)第三个目标是使用实验和计算模型的组合来测试一组假设，这些假设是关于一组被称为TIPS(微管加末端跟踪蛋白)的细丝结合蛋白如何协同工作来调节微管行为。(4)最终目标是为目标1至3中使用的我们的软件和相关分析工具创建广泛的分发包。这些包将包括面向研究和教学社区的软件。虽然我们的研究重点是微管，但由此产生的对聚合细丝系统的多尺度理解应该更广泛地应用于稳态(能源利用)聚合物，包括肌动蛋白、细丝和通过生物技术产生的聚合物。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Most cells in a wide range of organisms contain a dynamic substructure called the cytoskeleton, a network of protein-based polymers and associated proteins that has fundamental roles in cell movement, DNA partitioning, and internal cell organization. A key aspect of many cytoskeletal polymers is that they require chemical energy in the form of ATP (or GTP) to maintain a polymerized state. The harnessing of this energy allows the cytoskeletal filaments to do work, respond dynamically to internal and external signals, and self-organize. The major goal of the work in this project is to use a combination of experiments and computational modeling to develop an improved theoretical framework for understanding and predicting the behaviors of these dynamic cytoskeletal polymers as observed at different scales. More specifically, the proposed work sets out to establish how the biochemical properties of the polymer subunits (including the rate at which they burn ATP or GTP) relate to the behaviors of the individual filaments and to the overall behaviors of populations of filaments. In addition, the project studies how filament binding proteins work together to regulate filament dynamics. While this work is basic science, it has the potential to have practical applications in nanotechnology and synthetic biology. Through this project, graduate students and undergraduates will receive interdisciplinary training in both computational modeling and experimental biology. High school teachers and students will also be engaged in the research process. Freely available, open-source software and tutorials produced through this project will help students and researchers at all levels gain an intuitive understanding of dynamic polymer systems. From a technical perspective, the project has four specific goals, most of which focus on a type of cytoskeletal filaments known as microtubules. Individual microtubules exhibit a dramatic behavior known as dynamic instability, in which they stochastically alternate between extended periods of growth and depolymerization. (1) The first project goal is to develop and test hypotheses for the mechanisms of the transitions in microtubule dynamic instability by relating the behaviors of the filaments to the subunit-level structure of their tips. The approach will utilize a combination of work with a previously established detailed computational model of microtubule dynamics, a novel data analysis tool for identifying and statistically categorizing the microtubule behaviors, and experimental data acquired at high temporal and spatial resolutions. (2) The second goal is to establish a predictive understanding of the relationships between the biochemical characteristics of the subunits (kinetic rate constants), the behaviors of the filaments (e.g., dynamic instability, treadmilling) and the attributes of the polymer systems (e.g., critical concentrations, steady states). The approach will utilize a combination of computational modeling (performed with variants of the model used in Goal 1) and experiments with a bacterial relative of tubulin called PhuZ (chosen because wildtype and altered versions of this protein can be expressed in bacteria and characterized in vitro). (3) The third goal is to use a combination of experiments and computational models to test a set of hypotheses for how a group of filament binding proteins known as +TIPs (microtubule plus-end tracking proteins) work together to regulate microtubule behavior. (4) The final goal is to create for broad distribution packages of our software and associated analysis tools used in Goals 1 to 3. These packages will include software targeted at both the research and teaching communities. While the focus of our studies is on microtubules, the resulting multi-scale understanding of polymerizing filament systems should apply to steady-state (energy-utilizing) polymers more generally, including actin, bacterial filaments, and polymers created through biotechnology.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.