(94f) Genome Scale Modeling of Pseudomonas Aeruginosa in a Microbial Air-Cathode Single Chamber Fuel Cell

Microbial fuel cells (MFC) represent nowadays a significant alternative energy source for low power demand devices such as medical implants or biosensors. Its advantage is based on the fact that it is possible to obtain energy from organic substrates at low cost. Nevertheless, there exist several technological limitations that do not permit to expand its applications such as the development of efficient electrodes or the selection of suitable microorganisms. In order to obtain a better understanding of the performance and the effects of the metabolism on the cell we propose a 2D air-cathode single chamber microbial fuel cell model in COMSOL®. This model accounts for the effects of metabolites diffusion in the chamber. In order to consider for the metabolism state of the cell we coupled this model with a genomic scale model of Pseudomonas aeruginosa based on flux balance analysis (FBA) as a lineal programming model implemented in Xpress MP. We built an objective function composed by the biomass flux of the cell and the electron shuttle flux in order to make both fluxes positive; by maximizing this function we could predict time profiles of the power density and these profiles were then validated in a 30 ml fuel cell with glucose as a substrate. Finally, in silico knockouts were carried out to determine genes deletion candidates to increase the electron shuttles such as pyocianin and phenazine. The in silico model predicted maximum potentials of 0.135V that were consistent to the ones obtained in the experimental cell.