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.
