Virginia Covo1, Luis Miguel Medina1, Martha Josefina Vives2, and Andres Fernando Gonzalez Barrios1. (1) Chemical Engineering, Centro de Diseño de Productos y Procesos, Universidad de los Andes, Carrera 1a este No. 19 A 40 7° piso, Bogotá, Colombia, (2) Microbiology, Centro de investigación en Microbiología (CIMIC), Universidad de los Andes, Cra 1E No 18A-10 . Bloque J, Bogotá, Colombia
Discovering that the expression of some phenotypes is regulated by quorum sensing (QS) has broadened the knowledge on the mechanism that several bacteria use for the environmental response for their benefit. Such is the case of
Pseudomonas aeruginosa, bacteria that are responsible for the development of biofilms as a result of this communication system. Biofilms are sessile communities encountered in many environments and are responsible for the resistance towards antibiotics. It has reported that there exist certain compounds that are able to interrupt this communication system (quorum quenching), and it results in the expression or suppression of certain genes.
This study centers its attention on 4-nitropyridine-n-oxide (4-NPO) that has already been proven to interrupt P. aeruginosa quorum sensing system (Rasmussen et al. 2005). Simulated annealing algorithm was used in order to find a distribution of optimum concentrations of the quencher considering its stochastic behavior modeled by the Gillespie algorithm and minimizing LasR/3O-C12-HSL complex. Distribution of the optimum concentrations was found to behave normally as expected based on the results regarding the distribution of the population at different time points.
On the other hand, optimum concentrations obtained were corroborated by evaluating P. aeruginosa biofilm formation capability which has been reported to be significantly controlled by the QS system (Hentzer et al. 2002). Mean optimal concentration was predicted to be 2500 µM while biofilm formation was reduced 75% when adding 2000µM 4-NPO. This approach demonstrates the useful role for stochastic model regarding dose optimization.