Project 171487

Genes and gene products are regulated at multiple levels. Post-translational regulation by protein phosphorylation is of central importance in all cellular and developmental processes, in which protein kinases occupy key roles in signal partition, integration and transmission. The phosphorylation of proteins regulates their activity, localization, stability and interactions with other proteins. Perturbations of these regulatory mechanisms are implicated in numerous genetic diseases such as cancer. The human genome contains hundreds of related protein kinases and hundreds of thousands of potential phosphorylation sites, however, only a small fraction of these are phosphorylated, and this in a time- and localization-dependent manner by specific protein kinases. There is therefore a strong need to determine how these protein kinases can specify distinct cellular responses, what the molecular determinants of their specificity are and how mutations affect their regulating functions at the network and cellular levels. We will use an evolutionary systems-biology approach to dissect the organization of signaling pathways of key protein kinases and the mechanisms by which specificity is achieved. We will use the budding yeast as a model system, as it offers powerful molecular biology and genomics tools and since the number of protein kinases and associated factors has expanded in its recent evolutionary history. A functional dissection of paralogs (within species) and orthologs (between species) will allow to determine how new kinase-substrate interactions have been created and lost following these expansions, how the corresponding pathways have concomitantly been reorganized and thus how specificities of signaling pathways is encoded at the molecular level. This project will help answer questions such as how mutations can reroute signaling networks, as it is the case for several human diseases, and how network complexity evolves by the addition of regulatory proteins.

using evolutionary comparative systems biology to define functional relationships in eukaryotic cellular signaling networks