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Multi-scale Method Development for Cell Simulations and Cell Simulations of a Genetically Minimal Cell

Zaida Luthey-Schulten, University of Illinois at Urbana-Champaign

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Aaron Hoskins Department of Biochemistry, University of Wisconsin, Madison, WI, USA Thomas Kuhlman Department of Physics, Center for the Physics of Living Cells; University of Illinois, Urbana, IL, USA Team members Tyler M. Earnest Postdoctoral Researcher, National Center for Supercomputing Applications, Department of Chemistry, University of Illinois, Urbana, IL, USA. Zhaleh Ghaemi Postdoctoral Researcher, Department of Chemistry, University of Illinois, Urbana, IL, USA. Michael J. Hallock


Whole-cell models allow the synthesis of the vast body of experimental knowledge and physical/biochemical models into a unified computational description. Our software, Lattice Microbes (LM), is capable of simulating a stochastic, spatially resolved description of a cell through hour time scales. Here, we propose to extend a recent model of ribosome biogenesis in a growing Escherichia coli cell to include the expression of genes coding for central metabolism, allowing the computational cell to interact with its environment through the uptake and secretion of metabolites. We will include the effect of molecular crowding on the transport of biomolecules by modifying LM to account for excluded volume interactions during diffusion, which will be applied to the interactions between ribosomes and used to include the physical bacterial genome in the simulation domain. In parallel, we will begin the first whole-cell model of the assembly of the spliceosome in the eukaryote Saccharomyces cerevisiae. To perform these simulations, a high-performance computing environment featuring GPU-based accelerators is necessary.