Cellular consequences of genetic variation
[COVID-19 - During this period our group is devoting some resources to help in the study of the SARS-CoV-2 virus. If you are working on this and are looking to coordinate efforts or require assistance in data analysis, please get in touch]
Our group studies how cellular functions have diverged during evolution as well as how they are altered in disease. We study the molecular sources of phenotypic novelties, exploring how DNA changes are propagated through molecular structures and interaction networks to give rise to phenotypic variability.
We use post-translational modifications (PTMs) data from mass-spectrometry experiments to study the evolutionary dynamics and functional importance of post-translational regulatory networks. We aim to reconstruct the ancestral states of PTM regulatory networks in order to understand how some of the wondrous cellular functions that exist today were like in their primitive forms. For this we develop approaches to infer the history of protein modifications; the determinants of specificity for PTM regulators; and the ways protein function is controlled by PTMs.
We are also increasingly interested in understanding how these regulatory systems make decisions in present day species and how they are re-wired in the context of disease (e.g. cancer or infection). We have assembled a collection of conditional phosphoproteomic experiments (phosphate.com) that we have used to study human kinase regulation and the space of signalling states of cells. We are now studying how genetic variation seen in cancer cells changes their signalling state with an aim to understand context dependent cellular vulnerabilities to drugs.
Beyond PTM regulatory networks we are broadly interested in studying why different individuals or species diverge in their response to drugs, other environmental perturbations or additional genetic changes. For this purpose we are developing a general propose framework to predict the molecular consequences of DNA changes (www.mutfunc.com) and using these to guide genotype-phenotype associations.
Ochoa D, et al. The functional landscape of the human phosphoproteome Nature Biotechnology 2019 09 Dec
Strumillo MJ, et al. Conserved phosphorylation hotspots in eukaryotic protein domain families. Nature Comm. 2019 10, 1977
Wagih O et al. A resource of variant effect predictions of single nucleotide variants in model organisms. Mol Sys Bio 2018 14, e8430
Galardini M et al. Phenotype inference in an Escherichia coli strain panel. eLife 2017;6:e31035
Gonçalves E, et al. Widespread Post-transcriptional Attenuation of Genomic Copy-Number Variation in Cancer. Cell Syst. 2017 Oct 25;5(4):386-398.e4.
Studer RA, et al. Evolution of protein phosphorylation across 18 fungal species Science 2016 Vol. 354, Issue 6309, pp. 229-232
- Recent lab preprints
- Viéitez, Busby, et al. "Towards a systematic map of the functional role of protein phosphorylation"
- COVID-19 preprints [Colaborations and group papers]