Biology subjects

Petursson, B.

Publications and source records attributed to Petursson, B..

3 recordsLinked to original sources

bioRxiv2022

Data-driven extraction of human kinase-substrate relationships from omics datasets

Phosphorylation forms an important part of the signalling system that cells use for decision making and regulation of processes such as cell division and differentiation. To date, a large portion of identified phosphosites are not known to be targeted by any kinase. At the same time around 30% of kinases have no known target. This knowledge gap stresses the need to make large scale, data-driven computational predictions. In this study, we have created a machine learning-based model to derive a probabilistic kinase-substrate network from omics datasets. Our methodology displays improved performance compared to other state-of-the-art kinase-substrate prediction methods, and provides predictions for more kinases. Importantly, it better captures new experimentally-identified kinase-substrate relationships. It can therefore allow the improved prioritisation of kinase-substrate pairs for illuminating the dark human cell signalling space. Our model is integrated into a web server, SELPHI2.0, to allow unbiased analysis of phosphoproteomics data, facilitating the design of downstream experiments to uncover mechanisms of signal transduction across conditions and cellular contexts.

bioinformatics↗

bioRxiv2021

Pan-Cancer landscape of protein activities identifies drivers of signalling dysregulation and patient survival

Genetic alterations in cancer cells trigger oncogenic transformation, a process largely mediated by the dysregulation of kinase and transcription factor (TF) activities. While the mutational profiles of thousands of tumours has been extensively characterized, the measurements of protein activities has been technically limited until recently. We compiled public data of matched genomics and (phospho)proteomics measurements for 1,110 tumours and 77 cell lines that we used to estimate activity changes in 218 kinases and 292 TFs. Kinase activities are, on average, not strongly determined by protein abundance but rather by their phosphorylation state while the reverse is more common for TFs. Co-regulation of kinase and TF activities reflects previously known regulatory relationships and allows us to dissect genetic drivers of signalling changes in cancer. Loss-of-function mutation is not often associated with dysregulation of downstream targets, suggesting frequent compensatory mechanisms. Finally, we identified the activities most differentially regulated in cancer subtypes and showed how these can be linked to differences in patient survival. Our results provide broad insights into dysregulation of protein activities in cancer and their contribution to disease severity.

cancer biology↗

bioRxiv2019

Proteome-wide inference of protein kinase regulatory circuits

Complex networks of regulatory relationships between protein kinases comprise a major component of intracellular signaling. Although many kinase-kinase regulatory relationships have been described in detail, these are biased towards well-studied kinases while the majority of possible relationships remains unexplored. Here, we implement data-driven, unbiased methods to predict human kinase-kinase regulatory relationships and whether they have activating or inhibiting effects. We incorporate high-throughput data, kinase specificity profiles, and structural information to produce our predictions. The results successfully recapitulate previously annotated regulatory relationships and can reconstruct known signaling pathways from the ground up. The full network of predictions is relatively sparse, with the vast majority of relationships assigned low probabilities. However, it nevertheless suggests denser modes of inter-kinase regulation than normally considered in intracellular signaling research.

systems biology↗