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PLoS Comput Biol


Title:A Predictive Model for Yeast Cell Polarization in Pheromone Gradients
Author(s):Muller N; Piel M; Calvez V; Voituriez R; Goncalves-Sa J; Guo CL; Jiang X; Murray A; Meunier N;
Address:"MAP5, CNRS UMR 8145, Universite Paris Descartes, Paris, France. Institut Curie, CNRS UMR 144, Paris, France. Unite de Mathematiques Pures et Appliquees, CNRS UMR 5669 and equipe-projet INRIA NUMED, Ecole Normale Superieure de Lyon, Lyon, France. Laboratoire Jean Perrin and Laboratoire de Physique Theorique de la Matiere Condensee, UMR 7600 CNRS /UPMC, Paris, France. Molecular and Cell Biology and FAS Center for Systems Biology, Harvard University, Cambridge, Massachusetts, United States of America. Institute of Physics, Academia Sinica, Taiwan. Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts, United States of America. CAS Key Laboratory for Biological Effects of Nanomaterials and Nanosafety, National Center for Nanoscience and Technology, Beijing, People's Republic of China"
Journal Title:PLoS Comput Biol
Year:2016
Volume:20160414
Issue:4
Page Number:e1004795 -
DOI: 10.1371/journal.pcbi.1004795
ISSN/ISBN:1553-7358 (Electronic) 1553-734X (Print) 1553-734X (Linking)
Abstract:"Budding yeast cells exist in two mating types, a and alpha, which use peptide pheromones to communicate with each other during mating. Mating depends on the ability of cells to polarize up pheromone gradients, but cells also respond to spatially uniform fields of pheromone by polarizing along a single axis. We used quantitative measurements of the response of a cells to alpha-factor to produce a predictive model of yeast polarization towards a pheromone gradient. We found that cells make a sharp transition between budding cycles and mating induced polarization and that they detect pheromone gradients accurately only over a narrow range of pheromone concentrations corresponding to this transition. We fit all the parameters of the mathematical model by using quantitative data on spontaneous polarization in uniform pheromone concentration. Once these parameters have been computed, and without any further fit, our model quantitatively predicts the yeast cell response to pheromone gradient providing an important step toward understanding how cells communicate with each other"
Keywords:"Cell Polarity/physiology Computational Biology *Models, Biological Pheromones/physiology Quorum Sensing/physiology Saccharomyces cerevisiae/*physiology Saccharomyces cerevisiae Proteins/physiology Signal Transduction;"
Notes:"MedlineMuller, Nicolas Piel, Matthieu Calvez, Vincent Voituriez, Raphael Goncalves-Sa, Joana Guo, Chin-Lin Jiang, Xingyu Murray, Andrew Meunier, Nicolas eng P50 GM068763/GM/NIGMS NIH HHS/ Research Support, Non-U.S. Gov't 2016/04/15 PLoS Comput Biol. 2016 Apr 14; 12(4):e1004795. doi: 10.1371/journal.pcbi.1004795. eCollection 2016 Apr"

 
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Citation: El-Sayed AM 2024. The Pherobase: Database of Pheromones and Semiochemicals. <http://www.pherobase.com>.
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