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 ∼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 (∼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.
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:QMM.101656 |
| Date | January 2007 |
| Creators | Szapiel, Nicolas. |
| Publisher | McGill University |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | English |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Format | application/pdf |
| Coverage | Master of Science (Department of Biology.) |
| Rights | © Nicolas Szapiel, 2007 |
| Relation | alephsysno: 002611929, proquestno: AAIMR32793, Theses scanned by UMI/ProQuest. |
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