Experimentally informed bottom-up model of yeast polarity suggests how single cells respond to chemical gradients
type: CreativeWork
description: How do single cells—like neutrophils, amoebae, neurons, yeast, etc.—grow or move in a directed fashion in response to spatial chemical gradients? To address this question, we used the mating response in the budding yeast, Saccharomyces cerevisiae, as a biological model. To mate, pairs of yeast cells orient their cell fronts toward each other and fuse. Each cell relies on a pheromone gradient established by its partner to orient correctly. The ability for cells to resolve gradients is striking, because each cell is only ~5 μm wide and is thought to be operating in complex and noisy environments. Interestingly, mating pairs of cells often start out not facing each other. When this happens, the front of each cell—defined by a patch of cortical polarity proteins—undergoes a series of erratic and random movements along the cell cortex till it ‘finds’ the mating partner’s patch. We sought to understand how polarity patches in misaligned cells find each other. To this end, we first characterized patch movement in cells by the distribution of their step-lengths and turning angles and analyzed a bottom-up model of the polarity patch’s dynamics. The final version of our model combines 11 reaction-diffusion equations representing polarity protein dynamics with a stochastic module representing vesicle trafficking on a plane with periodic boundary conditions. We found that the model could not quantitatively reproduce step-length and turning angle distributions, which suggested that some mechanisms driving patch movement may not be present in the model. Incorpo-rating biologically inspired features into the model—such as focused vesicle delivery, sudden fluctuations in vesicle delivery rates, and the presence of polarity inhibitors on vesicles—allowed us to quantitatively match the in vivo polarity patch’s behavior. We then introduced a pathway, which connects pheromone sensing to polarity, to see how the model behaved when exposed to pheromone gradients. Concurrently, we analyze…
abstract: How do single cells—like neutrophils, amoebae, neurons, yeast, etc.—grow or move in a directed fashion in response to spatial chemical gradients? To address this question, we used the mating response in the budding yeast, Saccharomyces cerevisiae, as a biological model. To mate, pairs of yeast cells orient their cell fronts toward each other and fuse. Each cell relies on a pheromone gradient established by its partner to orient correctly. The ability for cells to resolve gradients is striking, because each cell is only ~5 μm wide and is thought to be operating in complex and noisy environments. Interestingly, mating pairs of cells often start out not facing each other. When this happens, the front of each cell—defined by a patch of cortical polarity proteins—undergoes a series of erratic and random movements along the cell cortex till it ‘finds’ the mating partner’s patch. We sought to understand how polarity patches in misaligned cells find each other. To this end, we first characterized patch movement in cells by the distribution of their step-lengths and turning angles and analyzed a bottom-up model of the polarity patch’s dynamics. The final version of our model combines 11 reaction-diffusion equations representing polarity protein dynamics with a stochastic module representing vesicle trafficking on a plane with periodic boundary conditions. We found that the model could not quantitatively reproduce step-length and turning angle distributions, which suggested that some mechanisms driving patch movement may not be present in the model. Incorpo-rating biologically inspired features into the model—such as focused vesicle delivery, sudden fluctuations in vesicle delivery rates, and the presence of polarity inhibitors on vesicles—allowed us to quantitatively match the in vivo polarity patch’s behavior. We then introduced a pathway, which connects pheromone sensing to polarity, to see how the model behaved when exposed to pheromone gradients. Concurrently, we analyze…
author: Ghose, Debraj
keywords: Cellular biology, Biophysics, Computational physics, chemotaxis, chemotropism, gradient, polarity, reaction-diffusion, yeast
date published: 2021
date modified: 2026-07-24T02:07:07Z
provider: Duke University
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Duke University

PropertyValue
property ID: Handle
value: https://hdl.handle.net/10161/23131