Poster

Elucidating Mechanisms Underlying Experimentally Induced Changes in the Zebrafish Circadian Clock

eSMB2020 eSMB2020 2:30 - 3:30pm EDT, Monday - Wednesday
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Vojtech Kumpost

Karlsruhe Institute of Technology
"Elucidating Mechanisms Underlying Experimentally Induced Changes in the Zebrafish Circadian Clock"
Zebrafish embryonic cell lines are a unique experimental model of the circadian regulation in vertebrates. They can be directly paced by external light stimuli and the oscillatory dynamics of gene expression can be monitored by luciferase reporter assays. These assays are designed to convert transcriptional activation to bioluminescence with an excellent time resolution and obvious changes in the measured waveforms can be observed as a result of light stimuli, gene knockouts or drug treatment. Here, we aim to utilize mathematical modeling to clarify how those changes in the recorded data correspond to the specific cellular mechanisms that generate them. We start with a simplified ODE Kim-Forger model proposed for the mammalian clock. This model consists of three state variables connected in a single negative feedback loop, which represents the core mechanism of the circadian clock mechanism. The model is further adjusted to correspond to the specifics of the zebrafish circadian regulatory system. Next, we validate the proposed model on a previously published data set with a variety of light-pacing regimes. In our further work, we will use stochastic modeling to account for molecular noise on the single-cell level that affects the observed dynamics of the recorded cell population. Finally, we plan to quantify the effect of a variety of drug treatments by fitting the model parameters to the drug-treated cell cultures and exploring the parameter space that can explain such variations. Our work represents a novel approach to studying bioluminescence recordings of zebrafish embryonic cell lines and aims to better quantify the observed differences due to drug treatments.
eSMB2020
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Virtual conference of the Society for Mathematical Biology, 2020.