Friday, June 17, 2016

Group member profile - Romain Studer

Next up on this series of group member profiles is Romain Studer (blog, scholar profile, twitter), a postdoc in the group that is very interested in protein evolution combining sequence and structural information.

What was the path the brought you to the group? Where are you from and what did you work on before arriving in the group?

My main interest in biology is the study of proteins in a broad diversity of organisms. My PhD work, as well as my postdoctoral research, was focused on protein evolution, at the primary sequence level and at the tertiary structure level.

I did my undergraduate studies and PhD work at University of Lausanne, Switzerland. My undergraduate studies were focused on immunology and biochemistry, with a dash of bioinformatics.  My PhD research, with Prof. Marc Robinson-Rechavi, was more on evolution and mainly focused on the comparison between paralogs (i.e. genes that diverged after a duplication event) and orthologs (i.e. genes that diverged after a speciation event). Positive selection can be used as a mechanism to fix advantageous mutations between paralogs, as well as between orthologous genes. The conclusion of my analyses was threefold: (1) positive selection affects diverse phylogenetic branches and diverse gene categories during vertebrate evolution; (2) positive selection concerns only a small proportion of sites (1%-5%); and (3) whole genome duplication had no detectable impact on the prevalence of this positive selection (Studer RA et al. 2008, Studer RA et al 2010).

After my PhD, I stayed a few months in Lausanne to work with Prof. Bernard C. Rossier to explore the evolution of sodium pumps and channels, involved in the regulation of blood pressure. I found that the sequential emergence of the different subunits of these proteins could be directly linked to the emergence of multicellularity in animals (Studer RA et al. 2011; Rossier BC et al. 2015).

In 2010, I then obtained two successive fellowship grants from the SNSF to move to UK. I worked in the group of Prof. Christine Orengo, where I have explored in more details the influence of structure on protein evolution. I contributed to the evolutionary aspect of the CATH database, a classification of protein domains. I also explored the evolution of RubisCO, the enzyme responsible for photosynthesis. I reconstructed the ancestral 3D structures of RubisCO and estimated the stability effect (ΔΔG) of mutations during evolution. The essential conclusion of this work was that mutations providing an increase in catalytic rate tend to be destabilising, but are rapidly followed by stabilising mutations during the course of evolution (Studer et al 2014).

My SNSF funding finished by the end of Summer 2013 and I then started to work as a senior postdoctoral fellow with Pedro Beltrao at the European Bioinformatics Institute (EMBL-EBI).

What are you currently working on? 

My current project is to estimate the level of conservation of posttranslational modifications (PTMs) in proteins, in particular phosphorylation. Phosphorylation is an important mechanism to quickly regulate protein function. Combining phylogenomics methods and experimental phosphoproteomics data, I am evaluating the replacement rate of phosphorylated residues during the evolution of multiple yeast species. I found that (1) most phosphosites are quite recent, (2) ancient phosphosites are very likely to be important for function and (3) motif preference have diverged across species.

What are some of the areas of research that excite you right now?

One interesting field is the application of experimental analyses on ancestral characters, such ancestral amino acid mutations, phosphorylation state or whole ancestral proteins. Evolutionary frameworks allow the prediction of ancestral sequences with good accuracy. Such sequences can then be modelled in 3D structure by homology modelling, or can be even resurrected in vitro by protein synthesis. These ancient proteins can be submitted to the same analysis as their modern counterpart and explore the difference over the time. This framework has the potential to reveal important properties.