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PLoS Comput Biol

Title:		Spatial stochastic dynamics enable robust cell polarization
Author(s):		Lawson MJ; Drawert B; Khammash M; Petzold L; Yi TM;
Address:		"Department of BioMolecular Science and Engineering, University of California, Santa Barbara, California, United States of America"
Journal Title:		PLoS Comput Biol
Year:		2013
Volume:		20130725
Issue:		7
Page Number:		e1003139 -
DOI:		10.1371/journal.pcbi.1003139
ISSN/ISBN:		1553-7358 (Electronic) 1553-734X (Print) 1553-734X (Linking)
Abstract:		"Although cell polarity is an essential feature of living cells, it is far from being well-understood. Using a combination of computational modeling and biological experiments we closely examine an important prototype of cell polarity: the pheromone-induced formation of the yeast polarisome. Focusing on the role of noise and spatial heterogeneity, we develop and investigate two mechanistic spatial models of polarisome formation, one deterministic and the other stochastic, and compare the contrasting predictions of these two models against experimental phenotypes of wild-type and mutant cells. We find that the stochastic model can more robustly reproduce two fundamental characteristics observed in wild-type cells: a highly polarized phenotype via a mechanism that we refer to as spatial stochastic amplification, and the ability of the polarisome to track a moving pheromone input. Moreover, we find that only the stochastic model can simultaneously reproduce these characteristics of the wild-type phenotype and the multi-polarisome phenotype of a deletion mutant of the scaffolding protein Spa2. Significantly, our analysis also demonstrates that higher levels of stochastic noise results in increased robustness of polarization to parameter variation. Furthermore, our work suggests a novel role for a polarisome protein in the stabilization of actin cables. These findings elucidate the intricate role of spatial stochastic effects in cell polarity, giving support to a cellular model where noise and spatial heterogeneity combine to achieve robust biological function"
Keywords:		"*Cell Polarity *Models, Biological *Stochastic Processes;"
Notes:		"MedlineLawson, Michael J Drawert, Brian Khammash, Mustafa Petzold, Linda Yi, Tau-Mu eng R01 EB014877/EB/NIBIB NIH HHS/ R01-EB014877-01/EB/NIBIB NIH HHS/ Research Support, N.I.H., Extramural Research Support, U.S. Gov't, Non-P.H.S. 2013/08/13 PLoS Comput Biol. 2013; 9(7):e1003139. doi: 10.1371/journal.pcbi.1003139. Epub 2013 Jul 25"