Genetic variation, created by duplication events recombination and point mutations serves as the raw material for natural selection to act upon during the evolution of species. To fully understand biological systems we must understand the evolutionary process and how this variation is translated into changes in phenotypes that have a measurable impact on fitness. Genome research and comparative genomics in particular have been crucial to study genome evolution, to identify functional DNA elements and has led us to ever more sophisticated models of transcriptional gene regulation. More recently, progress in mass-spectrometry is unveiling a complex world of post-transcriptional regulation and is challenging our current view of signaling systems. Thousands of different post-translational modification (PTM) sites are now routinely identified per study and the list of different types of abundant PTMs is growing (e.g. phosphorylation, acetylation, ubiquitylation, sumoylation, etc). These technological developments raise a problem of functional characterization, an issue this proposal aims to address. UCSF provides an ideal environment to conduct this research with a vibrant and collaborative spirit and an excellent Mass-Spectrometry facility containing last-generation MS instrumentation. Since arriving at UCSF, with the support of a HFSP fellowship, I have collaborated with this facility to perform a cross-species MS study of protein phosphorylation. This initial study revealed that the regulation by protein phosphorylation can diverge quickly during evolution although it is not yet clear to what extent these changes have a functional consequence. This work underscores the importance of cross-species studies and the crucial need to develop formal models of protein regulatory networks. We should make use of the lessons learned from genome research and applied them to the study of post- transcriptional regulatory networks. With this in mind, the main objectives of this proposal are to 1) use a comparative proteomics approach to catalog and identify functionally important PTMs;2) to develop predictors that can classify PTMs according to their function and 3) create models of these regulatory networks for different species. Besides improving our understanding signaling and of the evolutionary dynamics of cellular interaction networks, lessons learned from these model organisms will then be applied to the study of human genetic variation.
Understanding the evolutionary process is a fundamental problem in biological research. This project focuses specifically on the study of if the important post-transcriptional regulatory networks that regulate protein function inside the cell. These networks will be compared across different fungi allowing us for the first time to understand how these networks change during evolution. Studying how changes at the level of DNA result in a phenotypic difference with impact on fitness will help us understand why some specific mutations result in disease and why different species react differently to different drugs or environmental conditions.