Open Access Open Badges Research article

Modeling mutant phenotypes and oscillatory dynamics in the Saccharomyces cerevisiae cAMP-PKA pathway

Kevin Gonzales13, Ömür Kayıkçı23, David G Schaeffer13 and Paul M Magwene23*

Author Affiliations

1 Department of Mathematics, Duke University, Durham, NC 27708, USA

2 Department of Biology, Duke University, Durham, NC 27708, USA

3 IGSP Center for Systems Biology, Duke University, Durham, NC 27708, USA

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BMC Systems Biology 2013, 7:40  doi:10.1186/1752-0509-7-40

Published: 17 May 2013


Background The cyclic AMP-Protein Kinase A (cAMP-PKA) pathway is an evolutionarily conserved signal transduction mechanism that regulates cellular growth and differentiation in animals and fungi. We present a mathematical model that recapitulates the short-term and long-term dynamics of this pathway in the budding yeast, Saccharomyces cerevisiae. Our model is aimed at recapitulating the dynamics of cAMP signaling for wild-type cells as well as single (pde1Δ and pde2Δ) and double (pde1Δpde2Δ) phosphodiesterase mutants.

Results Our model focuses on PKA-mediated negative feedback on the activity of phosphodiesterases and the Ras branch of the cAMP-PKA pathway. We show that both of these types of negative feedback are required to reproduce the wild-type signaling behavior that occurs on both short and long time scales, as well as the the observed responses of phosphodiesterase mutants. A novel feature of our model is that, for a wide range of parameters, it predicts that intracellular cAMP concentrations should exhibit decaying oscillatory dynamics in their approach to steady state following glucose stimulation. Experimental measurements of cAMP levels in two genetic backgrounds of S. cerevisiae confirmed the presence of decaying cAMP oscillations as predicted by the model.

Conclusions Our model of the cAMP-PKA pathway provides new insights into how yeast respond to alterations in their nutrient environment. Because the model has both predictive and explanatory power it will serve as a foundation for future mathematical and experimental studies of this important signaling network.

Yeast; Signal transduction; Second messenger; Genetic variation