Modeling Kinase Translocation Reporter Behavior to Understand ERK Signaling Kinetics

Abstract

Kinase Translocation Reporters (KTRs) measure single-cell signal transduction dynamics to study the signaling cascades that control proliferation, differentiation, division, and apoptosis. A classic example is the RAS/ERK signaling pathway, which converts extracellular stimuli into gene expression and is abnormally activated in diseases such as cancer. A fluorescently-tagged ERK KTR biosensor can be used to elucidate the relationships between specific patterns and durations of ERK activation and their corresponding downstream effects. However, while KTRs are widely used to report on live-cell ERK activity states and dynamics, these biosensors are highly sensitive and suffer from a narrow dynamic range, limiting the levels of ERK activity that can be accurately detected. This work uses computational modeling to predict how changes to the KTR biosensor design might alter properties like its dynamic range and to better understand the effects of sequence modifications on kinase biosensors. The behavior of the kinase translocation reporter in response to ERK levels was modeled using principles of mass action kinetics and multi-compartment modeling. Sensitivity analyses and parameter modulation suggest that reducing ERK binding at the KTR docking site, increasing KTR phosphorylation, and increasing importin binding at the nuclear localization site would best decrease KTR sensitivity.