Elucidating the in vivo phosphorylation dynamics of the ERK MAP kinase using quantitative proteomics data and Bayesian model selection.

Molecular BioSystems
Tina ToniMichael P H Stumpf

Abstract

Ever since reversible protein phosphorylation was discovered, it has been clear that it plays a key role in the regulation of cellular processes. Proteins often undergo double phosphorylation, which can occur through two possible mechanisms: distributive or processive. Which phosphorylation mechanism is chosen for a particular cellular regulation bears biological significance, and it is therefore in our interest to understand these mechanisms. In this paper we study dynamics of the MEK/ERK phosphorylation. We employ a model selection algorithm based on approximate Bayesian computation to elucidate phosphorylation dynamics from quantitative time course data obtained from PC12 cells in vivo. The algorithm infers the posterior distribution over four proposed models for phosphorylation and dephosphorylation dynamics, and this distribution indicates the amount of support given to each model. We evaluate the robustness of our inferential framework by systematically exploring different ways of parameterizing the models and for different prior specifications. The models with the highest inferred posterior probability are the two models employing distributive dephosphorylation, whereas we are unable to choose decisively between the proc...Continue Reading

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Citations

May 10, 2013·The Journal of Chemical Physics·Angelique AleMichael P H Stumpf
Apr 13, 2013·Current Opinion in Biotechnology·Paul KirkMichael P H Stumpf
Apr 18, 2016·Current Opinion in Biotechnology·Tim Heinemann, Andreas Raue
Mar 12, 2016·PLoS Computational Biology·Andreas Milias-ArgeitisJohn Lygeros
Oct 22, 2020·Journal of the Royal Society, Interface·Michael P H Stumpf

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