Genetic interaction network of the Saccharomyces cerevisiae type 1 phosphatase Glc7

<p>Abstract</p> <p>Background</p> <p>Protein kinases and phosphatases regulate protein phosphorylation, a critical means of modulating protein function, stability and localization. The identification of functional networks for protein phosphatases has been slow due to their redundant nature and the lack of large-scale analyses. We hypothesized that a genome-scale analysis of genetic interactions using the Synthetic Genetic Array could reveal protein phosphatase functional networks. We apply this approach to the conserved type 1 protein phosphatase Glc7, which regulates numerous cellular processes in budding yeast.</p> <p>Results</p> <p>We created a novel <it>glc7 </it>catalytic mutant (<it>glc7-E101Q</it>). Phenotypic analysis indicates that this novel allele exhibits slow growth and defects in glucose metabolism but normal cell cycle progression and chromosome segregation. This suggests that <it>glc7-E101Q </it>is a hypomorphic <it>glc7 </it>mutant. Synthetic Genetic Array analysis of <it>glc7-E101Q </it>revealed a broad network of 245 synthetic sick/lethal interactions reflecting that many processes are required when Glc7 function is compromised such as histone modification, chromosome segregation and cytokinesis, nutrient sensing and DNA damage. In addition, mitochondrial activity and inheritance and lipid metabolism were identified as new processes involved in buffering Glc7 function. An interaction network among 95 genes genetically interacting with <it>GLC7 </it>was constructed by integration of genetic and physical interaction data. The obtained network has a modular architecture, and the interconnection among the modules reflects the cooperation of the processes buffering Glc7 function.</p> <p>Conclusion</p> <p>We found 245 genes required for the normal growth of the <it>glc7-E101Q </it>mutant. Functional grouping of these genes and analysis of their physical and genetic interaction patterns bring new information on Glc7-regulated processes.</p

Glc7-E101Q is a novel tool for integrated genomic and proteomic analysis of PP1Glc7 phosphatase functional networks in Saccharomyces cerevisiae

Reversible phosphorylation is a major mechanism for regulating the activity, localization and stability of proteins required for vital cellular processes such as glucose metabolism, gene expression, establishment of polarity, mitosis and cytokinesis. Phospho-regulation is driven by the activities of kinases and phosphatases. Together, these enzymes account for &sim;3% of eukaryotic genomes and it is estimated that 30% of the eukaryotic proteome is composed of phospho-proteins. Protein kinases (PKs) have been studied extensively, however relatively little is known regarding the signaling networks of protein phosphatases (PPases). The identification of PPase functional networks has been slow due to the redundant nature of the majority of PPases, the complexity of their substrate recognition in vivo, and the lack of large-scale analyses that would facilitate network analysis. We hypothesized that large-scale analysis of genetic interactions using the Synthetic Genetic Array (SGA) and proteomic analyses using 2D-PAGE Difference Gel Electrophoresis (DiGE) could reveal PPase functional networks. Here, we apply this approach to the essential and conserved PP1 PPase Glc7 as it regulates numerous cellular processes in budding yeast. For this study, we created a glc7 hypomorphic mutant (glc7-E101Q) suited for both SGA and DiGE analyses. SGA analysis of glc7-E101Q revealed a broad network of 147 synthetic sick/lethal (SSL) and 178 synthetic rescue (SR) interactions. DiGE comparison of the glc7-E101Q proteome relative to wild-type at medium-resolution (&sim;1000 proteins) revealed alterations in 39 proteins that changed as a consequence of both the mutation and growth conditions. One of the proteins identified in this analysis was Eno1, a non-essential enolase that is mis-regulated in the presence of glucose and identified a SR mutation in the glc7-E101Q SGA. Subsequent phenotypic analysis suggests a novel, non-metabolic role for Eno1 in the Glc7 interaction network. Our results reveal that parallel analysis, using SGA and DIGE, can reveal novel functions and networks that a single analysis may not detect