Saccharomyces cerevisiae, or Baker's yeast, has served as the model eukaryotic cell. Its genome, composed of 16 chromosomes totaling 12.2Mbp, was the first published for a eukaryote [1]. Current estimates suggest that there are 6913 open reading frames (ORFs) in the S. cerevisiae genome, of which 4304 are annotated [2]. Genome-scale reconstructions of the metabolic and regulatory networks of S. cerevisiae have previously been completed, accounting for approximately 17% and 10% of the ORFs, respectively [3, 4].

Recent studies show that the reconstruction of a signaling network can elucidate its functional specificity and generate hypothetical strategies for engineering signaling pathways aimed at practical applications including drug target identification [5, 6]. In this work, we present a draft of the genome-scale reconstruction of the model S. cerevisiae signaling network, consisting of more than 320 reactions involving approximately 120 genes, or about 2% of the annotated ORFs within the genome [2]. This work covers a comprehensive range of reconstruction procedures, from inferring causality relationships between chemical entities to incorporating stoichiometric detail accounting for more than 60 literature sources contributing primary experimental data such as yeast-two-hybrid and mass spectrometry. All four known MAP kinase signaling families, namely pheromone signaling, osmolarity response, cell wall integrity, and filamentous growth, are captured. Particular attention is placed upon the target of rapamycin (Tor) pathway, which regulates yeast growth according to nutrient availability [7].

We also discuss the computational issues associated with the reconstruction and suggest an algorithmic framework to address them. High-throughput data such as protein-protein interaction maps have a significant number of false-positives, and the available evidence and data are not necessarily reliable enough to incorporate into a model. A Bayesian statistics-based approach is suggested to utilize such data in a systematic fashion.

Ultimately, this reconstruction compactly represents the current set of hypotheses for the function and composition of the S. cerevisiae signaling network that serve as a starting point for future work.

References:

1. Goffeau, A., et al. (1996) Life with 6000 genes. Science 274, 546, 563-547

2. Christie, K.R., et al. (2004) Saccharomyces Genome Database (SGD) provides tools to identify and analyze sequences from Saccharomyces cerevisiae and related sequences from other organisms. Nucleic Acids Res 32, D311-314

3. Duarte, N.C., et al. (2004) Reconstruction and validation of Saccharomyces cerevisiae iND750, a fully compartmentalized genome-scale metabolic model. Genome Res 14, 1298-1309

4. Herrgard, M.J., et al. (2006) Integrated analysis of regulatory and metabolic networks reveals novel regulatory mechanisms in Saccharomyces cerevisiae. Genome Res

5. Papin, J.A., and Palsson, B.O. (2004) Topological analysis of mass-balanced signaling networks: a framework to obtain network properties including crosstalk. J Theor Biol 227, 283-297

6. Dasika, M.S. (2005) Optimization-based strategies for the systematic analysis and therapeutic disruption of signal transduction networks. AIChE Annual Meeting 2005, paper 379d

7. Powers, T., et al. (2004) Yeast TOR signaling: a mechanism for metabolic regulation. Curr Top Microbiol Immunol 279, 39-51