Interpretation of Cellular Imaging and AQP4 Quantification Data in a Single Cell Simulator
AbstractThe goal of the present study is to integrate different datasets in cell biology to derive additional quantitative information about a gene or protein of interest within a single cell using computational simulations. We propose a novel prototype cell simulator as a quantitative tool to integrate datasets including dynamic information about transcript and protein levels and the spatial information on protein trafficking in a complex cellular geometry. In order to represent the stochastic nature of transcription and gene expression, our cell simulator uses event-based stochastic simulations to capture transcription, translation, and dynamic trafficking events. In a reconstructed cellular geometry, a realistic microtubule structure is generated with a novel growth algorithm for simulating vesicular transport and trafficking events. In a case study, we investigate the change in quantitative expression levels of a water channel-aquaporin 4-in a single astrocyte cell, upon pharmacological treatment. Gillespie based discrete time approximation method results in stochastic fluctuation of mRNA and protein levels. In addition, we compute the dynamic trafficking of aquaporin-4 on microtubules in this reconstructed astrocyte. Computational predictions are validated with experimental data. The demonstrated cell simulator facilitates the analysis and prediction of protein expression dynamics.
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Kim, S.B.; Hsu, Y.; Linninger, A.A. Interpretation of Cellular Imaging and AQP4 Quantification Data in a Single Cell Simulator. Processes 2014, 2, 218-237.
Kim SB, Hsu Y, Linninger AA. Interpretation of Cellular Imaging and AQP4 Quantification Data in a Single Cell Simulator. Processes. 2014; 2(1):218-237.Chicago/Turabian Style
Kim, Seon B.; Hsu, Ying; Linninger, Andreas A. 2014. "Interpretation of Cellular Imaging and AQP4 Quantification Data in a Single Cell Simulator." Processes 2, no. 1: 218-237.