Statistical modelling and optimization of protease production by an autochthonous Bacillus aryabhattai Ab15-ES: A response surface methodology approach

In this study, response surface methodology (RSM) was employed for the optimization of bioprocess parameters for enhanced extracellular protease production by a native Bacillus aryabhattai Ab15-ES. Preliminary screening of various nutritional parameters by one factor at-a-time approach revealed that maltose and beef extract were the best carbon and nitrogen sources, respectively, that considerably influenced the enzyme production. The quadratic model of RSM for protease production was significant (p < 0.0001, R2 = 0.9880) with an approximately 99.9% correlation with observed response, thus confirming the validity of the model. Under the optimum fermentation conditions of maltose (12.35 g/L), beef extract (5.30 g/L), inoculum volume (2.5%, v/v), initial pH (7.8) and incubation temperature (40 °C), maximum protease production of 247.84 U/mL was obtained, and this was found to be 4.4-fold higher than protease yield recorded in the unoptimized medium. Findings from this study demonstrate the applicability of the predicted optimum conditions for large-scale protease production by Bacillus aryabhattai Ab15-ES for various biotechnological applications.