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PLoS Comput Biol. 2016 Apr 14;12(4):e1004795. doi: 10.1371/journal.pcbi.1004795. eCollection 2016 Apr.

A Predictive Model for Yeast Cell Polarization in Pheromone Gradients.

Author information

1
MAP5, CNRS UMR 8145, Université Paris Descartes, Paris, France.
2
Institut Curie, CNRS UMR 144, Paris, France.
3
Unité de Mathématiques Pures et Appliquées, CNRS UMR 5669 and équipe-projet INRIA NUMED, École Normale Supérieure de Lyon, Lyon, France.
4
Laboratoire Jean Perrin and Laboratoire de Physique Théorique de la Matière Condensée, UMR 7600 CNRS /UPMC, Paris, France.
5
Molecular and Cell Biology and FAS Center for Systems Biology, Harvard University, Cambridge, Massachusetts, United States of America.
6
Institute of Physics, Academia Sinica, Taiwan.
7
Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts, United States of America.
8
CAS Key Laboratory for Biological Effects of Nanomaterials and Nanosafety, National Center for Nanoscience and Technology, Beijing, People's Republic of China.

Abstract

Budding yeast cells exist in two mating types, a and α, 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 α-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.

PMID:
27077831
PMCID:
PMC4831791
DOI:
10.1371/journal.pcbi.1004795
[Indexed for MEDLINE]
Free PMC Article

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