Modeling bacterial growth patterns in the presence of antibiotic

With recent growth in systems biology research there has been a significant increase in complex systems modeling research relating to biological systems. Multi-drug resistant (MDR) organisms are a threat not only as hospital-acquired infections, but also now as community-acquired infections. Multilocus sequence typing (MLST) can genetically characterize clones of several bacterial pathogens, allowing the tracking of hypervirulent/ antibiotic resistant lineages and the extent of acquisition and horizontal movement of the resistance genes by Feil, E.J., et al, (2004). This paper describes the initial research using an agent based cellular automata approach to model the complex sub-cellular processes in bacteria growth. Rules derived from a biological background simulate the growth of bacteria under a number of conditions including the presence of antibiotic. Altering the level of antibiotic in the bacteria environment and effects on the growth curves was explored and verified. Bacterial survival under a number of conditions (pH, temperature, nutrient concentration) emergent growth patterns and collective behaviour were also studied. A case study using the parameters reflecting the bacterium Escherichia coli was simulated and the results were validated. The software provides an in silico laboratory where bacteria can be grown under a variety of rules and conditions thereby learning the underlying mechanisms of behaviour at a local level, which collectively generate the global behaviour of interest