Phosphorylation can rapidly and reversibly modulate numerous properties of proteins including their conformation, enzymatic activity, molecular interactions, subcellular localization and surface charge. In organisms as diverse as mammals, invertebrates and yeast, researchers have used mass spectrometry based proteomics to identify thousands of sites of phosphorylation on proteins in cell signaling pathways. Some sites of phosphorylation serve as molecular switches that activate an enzyme, determine a protein’s subcellular localization, or target a protein for degradation. The roles of these types of sites are relatively straightforward to elucidate with qualitative assays since point mutants that cannot be phosphorylated either phenocopy null mutants or produce constitutive activity. However, there are many uncharacterized phosphorylation sites. We BEZ235 hypothesized that many of these sites exert quantitative regulatory roles in signaling pathways, the effects of which would only be revealed with quantitative assays in the context of the specific stimulus about which they convey information. We therefore developed a systematic and general approach to prioritize the study of individual phosphorylation events and their potential quantitative functions in signaling networks. We focused on the pheromone response system in the budding yeast Saccharomyces cerevisiae 
�C a well-developed system for studying eukaryotic cell signaling. In this system we can sensitively and accurately quantify pathway input, signal flow and pathway output in vivo in single cells. In the nucleus, Fus3 phosphorylates the functionally redundant transcription repressors Dig1 and Dig2, as well as the transcription activator Ste12 to induce pheromone responsive gene expression. Upon stimulation with pheromone, precise quantitative information about the amount of receptor occupied at the cell surface reaches the nucleus within minutes. Here, we mined mass spectrometry based proteomics data to identify phosphorylation sites with no known function on components of the pheromone pathway. We then prioritized for further examination phosphopeptides that contained conserved consensus sequences in regions of system proteins that contained no known or predicted structural domains. Finally we combined mutations, quantitative single-cell experiments and computational modeling to define novel quantitative roles for six phosphorylation events on three pathway proteins in regulating pheromone signaling. While more detailed and mechanistic computational models of the pathway have been published before, the simple models used here are course-grained in order to be generic and broadly VE-822 applicable. We found that mutation of three of the six sites decreases system output, mutation of two other sites increases system output, and mutation of the final site removes a negative feedback loop that conditionally diminishes system output when signal is low. We believe that a similar combination of approaches will allow researchers to characterize functional roles for phosphorylation events that contribute to the dynamic quantitative regulation of many signaling systems. To explore how phosphorylation of S400 and T525 regulate pheromone signaling, we developed a simple mathematical model of the pheromone pathway.