Reply: On the evolution of protein length and phosphorylation sites

Lars just pointed out in a blog post that the average protein length of a group of proteins is a strong predictor of average number of phosphorylation sites. Although this is intuitive this is something that I honestly had not fully considered. As Lars mentions this has potential implications for some of the calculations in our recently published study on the evolution of phosphorylation in yeast species.

One potential concern relates to figure 1a. We found that, although protein phosphorylation appears to diverge quickly, there is a high conservation of the relative number of phosphosites per protein for different GO groups. Lars suggests that, at least in part, this could be due to relative differences in average protein size for these different groups that in turn is highly conserved across species.

To test this hypothesis more directly I tried to correct for differences in the average protein size of different functional groups by calculating the average number of phosphorylation sites per amino-acid, instead of psites per protein. These values were then corrected for the average number of phosphorylation sites per AA in the proteome.

As before, there is still a high cross-species correlation for the average number of psites per amino-acid for different GO groups. The correlations are only somewhat smaller than before. The individual correlation coefficients among the three species changed from: S. cerevisiae versus C. albicans – R~0.90 to 0.80; S. cerevisiae versus S. pombe – R~0.91 to 0.84; S. pombe versus C. albicans – R~0.88 to 0.83. It would seem that differences in protein length explains only a small part of the observed correlations. Results in figure 1b are also not qualitative affected by this normalization suggesting that observed differences are not due to potential changes in the average size of proteins. In fact the number of amino acids per GO group is almost perfectly correlated across species.

Another potential concern relates to the sequence based prediction of phosphorylation. As explained in the methods, one of the two approaches used to predict if a protein was phosphorylated was the sum over multiple phosphorylation site predictors for the same sequence. Given the correlation shown by Lars, could it be that, at least for one of the methods, we are mostly predicting the average protein size ? To test this I normalized the phosphorylation prediction for each S. cerevisiae protein by their length. I re-tested the predictive power of this normalized value using ROC curves and the known phosphoproteins of S. cerevisiae as postives. The AROC values changed from 0.73 to 0.68. This shows that the phosphorylation propensity is not just predicting protein size although, as expected from Lars' blog post, size alone is actually a decent predictor for phosphorylation (AROC=0.66). The normalized phosphorylation propensity does not correlate with the protein size (CC~0.05) suggesting that there might ways to improve the predictors we used.

Nature or method bias ?
Are larger proteins more likely to be phosphorylated in a cell or are they more likely to be detected in a mass-spec experiment ? It is likely that what we are observing is a combination of both effects but it would be nice to know how much of this observed correlation is due to potential MS bias. I am open to suggestions for potential tests.
This is also important for what I am planning to work on next. A while ago I had noticed that prediction of phosphorylation propensity could also predict ubiquitination and vice-versa. It is possible that they are mostly related by protein size. I will try to look at this in future posts.

Comparative analysis of phosphoproteins in yeast species

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.

HFSP fellows meeting (Tokyo 2009)

I spent last week in Japan attending the fellows meeting of the Human Frontier Science Program. I was fortunate enough to get a postdoc fellowship from HFSP to support my current interest in the evolution of signalling systems. The meeting took place in Tokyo and brought together people from all sorts of different fields and at different stages of their careers. This program funds postdocs but also provides funding to young investigators setting up their labs and for teams of PIs working on interdisciplinary projects.

This year marks the 20th anniversary of the program that also coincides with a period of change in leadership. Ernst-Ludwig Winnacker, current Secretary General of the European Research Council, will take over the role of Secretary General of the HFSP organization from Torsten Wiesel. Also, Akito Arima will replace Masao Ito as the president of HFSPO (press release). Probably because of this the meeting had plenty of political moments and speeches. Thankfully most of the people involved in this organization appear to be very lighthearted so these moments were not a burden.

The curse of specialization ? 

A core focus of HFSP is to fund interdisciplinary projects that involve people from different areas or that help researchers change significantly their field of research. There was some time for discussions about the future of the organization as well as the future of "systems biology". For me personally, these debates helped to crystallized many of my own doubts. I am a biochemist but spent 90% of my PhD doing computational work. At this point I feel very much like a jack of all trades and master of none. In my previous work I have mostly hit walls due to lack of data so I plan to spend the next few years leaning a lot more about experimental work. Still, it is hard to be sure of what is best for the future. How much should I sacrifice in productivity to learn new skills ? Is it best to work as a specialist in interdisciplinary teams or be trained as an interdisciplinary person (Eddy SR, PloS Comp Bio 2005) ?

The broad scope of HFSP was well reflected in the topics presented in the meeting (PDF of program). There were many interesting talks, like the keynote by Takao Hensch about "How experience shapes the brain", in particular during the very early stages of life. He showed amazing work about "windows of opportunity" in learning and how these can be manipulated genetically or pharmacologically. Still, when I was looking around in the poster session I could not help but feel a bit of lack of interest since most of the topics were outside my previous work experience. This brings me back to the topic of specialization. Isn't it upsetting that we have to specialize so ? I don't think I can read and enjoy more than a third of a typical issue of Nature. This is for me the curse of specialization, it focuses not only your skills but your interests and curiosity.


Tokyo/Kyoto

Aside from the science, this was my first trip to Japan. I really liked it and hope to come back one day with more time to explore. I loved the temples, gardens, food, colors and all the differences.