Generation of a functional network around a single kinase highlights its involvement in unsuspected biological processes

Abstract

Bioinformatics is the application of computational techniques to the field of biology. Computational techniques can be used to analyze large quantities of compiled data. The budding yeast, Saccharomyces cerevisiae, has vast biological databases that are regularly curated and easily accessible, making it an ideal system for bioinformatic analysis (Dwight 2004). In this study we constructed a ‘panoramic\u27 gene-centered network around the SPorulation-Specific gene, SPS1 (Percival-Smith and Segall 1986). Sporulation is the process by which diploid Saccharomyces cerevisiae cells survive during times of nutritional starvation. Upon induction of sporulation, meiosis occurs and is followed by de novo formation of environmentally resistant spore walls (Neiman 2011). In cells lacking SPS1, meiosis proceeds normally, but there are defects during spore morphogenesis (Friesen et al. 1994). In order to elucidate the mechanism(s) of action of SPS1, we used a number of bioinformatic applications to integrate the massive datasets that exist for the model organism with in-house generated mass spectrometry data for the protein Sps1. Using these methods we were able to functionally cluster the majority of the proteins that interact with Sps1. By doing so we generated an Sps1-centered functional network that we believe captures aspects of Sps1 function during different stages of the yeast life-cycle; the analysis of which suggested a novel role of vacuolar involvement with Sps1. We argue this type of bioinformatic analysis can be used to examine biological data independent of gene, model system, technique or assay