Models and analysis of yeast mating response : tools for model building, from documentation to time-dependent stimulation

Abstract

Molecular signaling systems allow cells to sense and respond to environmental stimuli. Quantitative modeling can be a valuable tool for evaluating and extending our understanding of signaling systems. In particular, studies of the mating pheromone response system in yeast (Saccharomyces cerevisiae) have revealed many protein families and regulatory motifs also found in higher eukaryotes. This thesis develops several computational and experimental approaches that facilitate characterization of cellular signaling systems, and tests these approaches using yeast mating response as a model. Limitations in the current approach to building models of molecular systems were addressed first. For example, published computational models are often difficult to evaluate and extend because researchers rarely make available the information and assumptions generated throughout model building. I developed tools that facilitate model construction, evaluation, and extension. I used these tools to develop the YeastPheromoneModel (YPM) information repository, in which construction of an exhaustive model of the yeast mating system is documented (http://www.YeastPheromoneModel.org). Next, motivated by an ability to rapidly make many derivative models from the YPM repository and by carefully measured abundances of mating system proteins, I analyzed a model of the mating system mitogen activated protein kinase cascade. I found that varying the abundance of the scaffold protein Ste5, but not the abundances of other proteins, is expected to result in a quantitative tradeoff between total system output and dynamic range. Thus, the abundance of scaffold proteins in signaling systems may generally be under selective pressure to support specific quantitative system behavior.

(cont.) Finally, because traditional methods for characterizing signaling systems can be slow and tedious, I postulated that time-dependent stimulation of signaling systems might increase the richness and value of data derived from individual experiments. To do this, I devised a custom microfluidic device to expose yeast cells to pheromone in a time-dependent manner. I also developed computational approaches to investigate the use of time-dependent stimulation to characterize receptor and G protein response dynamics. I found that, at least for the receptor/G protein portion of the mating system, time-dependent stimulation does not appear to offer significant gains for constraining kinetic parameters relative to traditional step-response experiments.