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Processes 2014, 2(1), 218-237; doi:10.3390/pr2010218

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
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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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Abstract

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
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

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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