Collaborative Research: Characterizing Two Cell Polarity Processes Using Uncertainty Quantification to Analyze Complex Models and Data

Ohio State University, The, Columbus OH

Investigators

Abstract

The goal of this project, jointly funded by the Division of Mathematical Sciences Mathematical Biology Program and Division of Molecular and Cellular Biosciences Cellular Dynamics and Function Program, is to obtain a more detailed understanding of how cells "polarize" to generate different shapes. Specifically, how do cells rearrange themselves to go from a symmetric object like a round egg cell into an asymmetric object like a nerve cell? Experiments will be performed on budding yeast which can switch from a sphere to an asymmetric projection shape by localizing components to one end, a process termed cell polarization. Examples of polarization include immune cell activation, tumor cell metastasis, and yeast infections in which yeast cells invade human tissue by polarized cell growth. Fungal infections are increasing in prevalence in the U.S. Insights can help researchers discover treatments to halt the invasive growth of yeast infections. The research will investigate the spatial distribution of cellular proteins during polarization using a combination of mathematical modeling and microscopy imaging. Experimental data can be compared to computer simulation data to confirm the models and adjust the model parameters. An important methodological advance will be replacing the model, which can take significant time to run, with a simpler polynomial surrogate model which can be calculated very quickly resulting in a dramatic computational speed-up. Through this process one obtains models that can reproduce and predict the behavior of polarizing cells. In addition, the research will be integrated with outreach activities training graduate, undergraduate, and high school students on how to perform quantitative microscopy experiments and simulate mathematical models. Cell polarity and morphology define the form and function of individual and groups of cells. A systems biology approach will delve into this subject at a more quantitative level moving beyond arrow diagrams to characterize the spatial dynamics of cell polarity. The investigation will take advantage of the experimental tractability of budding yeast to characterize two classic cell polarity morphologies: the bud and the mating projection. More specifically, the investigation will use microscopy to visualize the spatial dynamics of polarization proteins and process the images into quantitative data. In parallel, a collection of mathematical models of budding and mating projection growth will be constructed based on biological hypotheses. Methodologically, one of the grand challenges of systems biology is to estimate the models/parameters using large datasets. Bayesian inference will be used to select the best models and estimate the parameters based on the experimental data. A central concept in this proposal will be applying techniques from uncertainty quantification (UQ) that replace model evaluations in the Monte Carlo method with a surrogate polynomial function, resulting in a dramatic speed-up of the uncertainty analysis. The combined result will be a systematic investigation of cell polarity leading to model predictions that will be tested by experiments converting one cellular morphology into the other. In addition, the proposed study of improved surrogate model calculation will further accelerate the uncertainty analysis of complex models. 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.