A Computational Approach to Incorporate Metabolite Inhibition in the Growth Kinetics of Indigenous Bacterial Strain Bacillus subtilis MN372379 in the Treatment of Wastewater Containing Congo Red Dye

A rigorous knowledge of the bacterial growth kinetics is essential for the scaling-up and optimization of biodegradation process conditions in a bioreactor. Although a great deal of literature is available on the modeling of bacterial growth kinetics considering the inhibition at high substrate-loading, the inhibition caused by toxic metabolic byproducts was not accounted in the bacterial growth kinetics. This work primarily aimed at developing a parametric bacterial growth model to account for metabolite inhibition, indicated by a decelerating log-phase growth, which was rarely discussed in the previous studies. An efficient azo-dye degrading bacterium (Bacillus subtilis MN372379) was isolated from the sludge-waste nearby a carpet-dyeing unit. The isolated bacterial strain was used to decolorize the simulated wastewater containing Congo red dye. This study proposed a computational approach to calculate specific bacterial growth rate time-averaged over the entire sigmoidal log phase (including the decelerating phase) for incorporating the effect of metabolite-inhibition, in contrast to the conventional studies where only the initial part (accelerating) of log phase was considered. The nature of metabolite inhibition was also determined and found to be non-competitive. Next, the computed time-averaged specific bacterial growth rate was incorporated into three substrate inhibition models to account for both, the metabolite and substrate inhibitions, and subsequently their kinetic parameters were also determined. Finally, the initial dye concentration and inoculum size were optimized to yield maximum dye utilization rate. This study paves the way for predicting bacterial growth kinetic with improved accuracy to enable a better optimization of bioreactors at the industrial scale.