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  Challenges of Integrating Stochastic Dynamics and Cryo-Electron Tomograms in Whole-Cell Simulations

Earnest, T. M., Watanabe, R., Stone, J. E., Mahamid, J., Baumeister, W., Villa, E., et al. (2017). Challenges of Integrating Stochastic Dynamics and Cryo-Electron Tomograms in Whole-Cell Simulations. The Journal of Physical Chemistry B, 121(15), 3871-3881. doi:10.1021/acs.jpcb.7b00672.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-002D-537D-7 Version Permalink: http://hdl.handle.net/11858/00-001M-0000-002D-537E-5
Genre: Journal Article

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 Creators:
Earnest, Tyler M.1, Author
Watanabe, Reika1, Author
Stone, John E.1, Author
Mahamid, Julia2, Author              
Baumeister, Wolfgang2, Author              
Villa, Elizabeth1, Author
Luthey-Schulten, Zaida1, Author
Affiliations:
1external, ou_persistent22              
2Baumeister, Wolfgang / Molecular Structural Biology, Max Planck Institute of Biochemistry, Max Planck Society, ou_1565142              

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Free keywords: NUCLEAR-PORE COMPLEX; DNA-BINDING SITES; RIBOSOME BIOGENESIS; YEAST-CELLS; DIFFUSION; MEMBRANE; TIME; VISUALIZATION; CHROMATIN; EXPORTChemistry;
 Abstract: Cryo-electron tomography (cryo-ET) has rapidly emerged as a powerful tool to investigate the internal, three-dimensional spatial organization of the cell. In parallel, the GPU-based technology to perform spatially resolved stochastic simulations of whole cells has arisen, allowing the simulation of complex biochemical networks over cell cycle time scales using data taken from -omics, single molecule experiments, and in vitro kinetics. By using real cell geometry derived from cryo-ET data, we have the opportunity to imbue these highly detailed structural data-frozen in time-with realistic biochemical dynamics and investigate how cell structure affects the behavior of the embedded chemical reaction network. Here we present two examples to illustrate the challenges and techniques involved in integrating structural data into stochastic simulations. First, a tomographic reconstruction of Saccharomyces cerevisiae is used to construct the geometry of an entire cell through which a simple stochastic model of an inducible genetic switch is studied. Second, a tomogram of the nuclear periphery in a HeLa cell is converted to the simulation geometry through which we study the effects of cellular substructure on the stochastic dynamics of gene repression. These simple chemical models allow us to illustrate how to build whole-cell simulations using cryo-ET derived geometry and the challenges involved in such a process.

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Language(s): eng - English
 Dates: 2017-03-142017
 Publication Status: Published in print
 Pages: 11
 Publishing info: -
 Table of Contents: -
 Rev. Method: -
 Identifiers: ISI: 000400039500063
DOI: 10.1021/acs.jpcb.7b00672
 Degree: -

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Title: The Journal of Physical Chemistry B
  Other : J. Phys. Chem. B
Source Genre: Journal
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Publ. Info: Washington, D.C. : American Chemical Society
Pages: - Volume / Issue: 121 (15) Sequence Number: - Start / End Page: 3871 - 3881 Identifier: ISSN: 1520-6106
CoNE: /journals/resource/1000000000293370_1