Genetic Algorithmic Optimization of PHB Production by a Mixed Culture in an Optimally Dispersed Fed-batch Bioreactor

Poly-β-hydroxybutyrate (PHB) is an energy-storage polymer whose properties are similar to those of chemical polymers such as polyethylene and polypropylene. Moreover, PHB is biodegradable, absorbed by human tissues and less energy-consuming than synthetic polymers. Although Ralstonia eutropha is widely used to synthesize PHB, it is inefficient in utilizing glucose and similar sugars. Therefore a co-culture of R. eutropha and Lactobacillus delbrueckii is preferred since the latter can convert glucose to lactate, which R. eutropha can metabolize easily. Tohyama et al. [24] maximized PHB production in a well-mixed fed-batch bioreactor with glucose and (NH4)2SO4 as the primary substrates. Since production-scale bioreactors often deviate from ideal laboratory-scale reactors, a large bioreactor was simulated by means of a dispersion model with the kinetics determined by Tohyama et al. [24] and dispersion set at an optimum Peclet number of 20 [32]. The time-dependent feed rates of the two substrates were determined through a genetic algorithm (GA) to maximize PHB production. This bioreactor produced 22.2% more PHB per liter and 12.8% more cell mass than achieved by Tohyama et al. [24]. These results, and similar observations with other fermentations, indicate the feasibility of enhancing the efficiency of large nonideal bioreactors through GA optimizations.