Abstract

Co-authors: Michael J. Hallock (University of Illinois at Urbana-Champaign), Joseph R. Peterson (University of Illinois at Urbana-Champaign), John A. Cole (University of Illinois at Urbana-Champaign), Tyler M. Earnest (University of Illinois at Urbana-Champaign), John E. Stone (University of Illinois at Urbana-Champaign)

High-performance computing now allows integration of data from cryoelectron tomography, super resolution imaging, various –omics, and systems biology reaction studies into coherent computational models of cells and cellular processes functioning under in vivo conditions. Here we analyze the stochastic reaction-diffusion dynamics of ribosome biogenesis in slow growing bacterial cells undergoing DNA replication and probe the metabolic reprogramming that occurs within dense colonies of Escherichia coli cells over periods of hours. Using our GPU -based Lattice Microbe software, the some 1300 reactions and 250 species involved in transcription, translation and ribosome assembly are described in terms of reaction-diffusion master equations and simulated over a cell cycle of two hours. The ribosome biogenesis simulations account for DNA replication that takes place within the cell cycle, and the results are compared to super resolution imaging results. In the case of the c ell colony simulations, reaction-diffusion kinetics of the surrounding medium are coupled with the cellular metabolic networks to demonstrate how small colonies of interacting bacterial cells differentially respond to the competition for resources according to their position in the colony. The predicted metabolic reprogramming has been observed experimentally. Finally we will report on the progress we have achieved to date and how supercomputers will provide us a window into cellular dynamics within bacterial and eukaryotic cells.