My first postdoctoral project has just appeared online in PLoS Biology. It is about the evolution of phosphoregulation in yeast species. This analysis follows from a previous work I had done during my PhD on the evolution of protein-protein interactions after gene duplication (paper / blog post). One of the conclusions from that previous work was that interactions of lower specificity, such as those mediated by short peptides, would be more prone to change. In fact, one of the protein domains that we found associated with high rates of change of protein-protein interactions was the kinase domain.
Given that the substrate specificity of a kinase is usually determined by a few key amino-acids surrounding the target phosphosite it is easy to image how kinase-substrate interactions can be easily created and destroyed with few mutations. It is also well known that these phosphorylation events can have important functional consequences. We therefore postulated that changes in phosphorylation are an important source of phenotypic diversity.
To test this, we collected by mass-spectrometry in vivo phosphorylation sites for 3 yeast species (S. cerevisiae, C. albicans and S. pombe). These were compared in order to estimate the rate of change of kinase-substrate interactions. Since changes in gene expression are generally regarded as one of the main sources of phenotypic diversity we compared these estimates with similar calculations for the rate of change of transcription factor (TF) interactions to promoters. Depending on how we define a divergence of phosphorylation we estimate that kinase-substrate interactions change either at similar rates or at most 2 orders of magnitude slower than TF-promoter interactions.
Although these changes in kinase-substrate interactions appear to be fast, groups of functionally related proteins tend to maintain the same levels of phosphorylation across broad time scales. We could identify a few functional groups and protein complexes with a significant divergence in phosphorylation and we tried to predict the most likely kinases responsible for these changes.
Finally we compiled recently published genetic interaction data for S. pombe (from Assen Roguev's work) and for S. cerevisiae (from Dorothea Fiedler's work) in addition to some novel genetic data produced for this work. We used this information to study the relative conservation of genetic interactions for protein kinases and transcription factors. We observed that both proteins kinases and TFs show a lower than average conservation of genetic interactions.
We think these observations strongly support the initial hypothesis that divergence in kinase-substrate interactions contributes significantly to phenotypic diversity.
Technology opening doors
For me personally it really feels like I was in the right place at the right time. Many of the experimental methods we used are still under heavy development but I was lucky to be very literally next door to the right people. I had the chance to collaborate with Jonathan Trinidad who works for the UCSF Mass Spectrometry Facility directed by Alma Burlingame. I also arrived at a time when the Krogan lab, more specifically Assen Roguev (twitter feed), has been working to develop genetic interaction assays for S. pombe (Roguev A 2007). As we describe in the introduction, these technological developments really allow us to map out the functional and physical interactions of a cell at an incredible rate. What I am hoping for is that soon they are seen in much the same light as genome sequencing. We can and should be using these tools to study, simultaneously, groups of species and not just the same usual model organisms that diverged from each other more than 1 billion years ago.
Evolution of signalling
There are many more protein interactions that are determined by short linear peptide motifs (Neduva PLoS Bio 2005). A large fraction of these determine protein post-translational modifications and are crucial for signal transduction systems. For the next couple of years I will try to continue to study the evolution of signal transduction systems. There are certainly many experimental and computational challenges to address. I am particularly interested in looking at the co-regulation by combinations of post-translational modifications and their co-evolution. I will do my best to share some of that work as it happens here in the blog.