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Interpretation of Cellular Imaging and AQP4 Quantification Data in a Single Cell Simulator

Laboratory for Product and Process Design, Department of Bioengineering, University of Illinois at Chicago, 851 South Morgan St. 218 SEO, Chicago, IL 60607, USA
Author to whom correspondence should be addressed.
Processes 2014, 2(1), 218-237;
Received: 22 July 2013 / Revised: 21 January 2014 / Accepted: 22 January 2014 / Published: 4 March 2014
(This article belongs to the Special Issue Feature Papers)
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The 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. View Full-Text
Keywords: stochastic simulation; aquaporin 4; cell molecular simulator; systems biology stochastic simulation; aquaporin 4; cell molecular simulator; systems biology

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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.

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