Computational modeling of synthetic microbial biofilms

Timothy J Rudge, Paul J Steiner, Andrew Phillips, Jim Haseloff
Department of Plant Sciences, University of Cambridge, Cambridge, UK
ACS Synthetic Biology, 2012


   title={Computational modeling of synthetic microbial biofilms},

   author={Rudge, T.J. and Steiner, P.J. and Phillips, A. and Haseloff, J.},

   journal={ACS Synthetic Biology},

   year={2012}publisher={ACS Publications}


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Microbial biofilms are complex, self-organized communities of bacteria, which employ physiological cooperation and spatial organization to increase both their metabolic efficiency and their resistance to changes in their local environment. These properties make biofilms an attractive target for engineering, particularly for the production of chemicals such as pharmaceutical ingredients or biofuels, with the potential to significantly improve yields and lower maintenance costs. Biofilms are also a major cause of persistent infection, and a better understanding of their organization could lead to new strategies for their disruption. In spite of this potential, the design of synthetic biofilms remains a major challenge, due to the complex interplay between transcriptional regulation, inter-cellular signaling and cell biophysics. Computational modeling could help to address this challenge by predicting the behavior of synthetic biofilms prior to their construction, however multi-scale modeling has so far not been achieved for realistic cell numbers. This paper presents a computational method for modeling synthetic microbial biofilms, which combines three-dimensional biophysical models of individual cells with models of genetic regulation and inter-cellular signaling. The method is implemented as a software tool (CellModeller), which uses parallel Graphics Processing Unit architectures to scale to more than 30,000 cells – typical of a 100 micron diameter colony – in 30 minutes of computation time.
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