Response surface methodological approach for optimizing the enzyme activity and enzymatically mediated bioprecipitation of heavy metals by alkaline phosphatase

Abstract

This study investigates using an alkaline phosphatase enzyme isolated from Bacillus cereus to decontaminate heavy metals. The experiments were performed with several process parameters, including substrate concentration, pH, and temperature. To optimize the best experimental conditions, they were estimated by using a central composite experimental design combined with response surface methodology (RSM). Variables were concentration of substrate ((p-NPP 14 to 17 mM), pH 8 to 10.5, and temperature (35 to 45^oC). Statistical analysis of variance (ANOVA) was performed to classify the competence of the developed model and revealed a good understanding between the experimental data and the proposed model. The highest enzymatic activity 25.73 units/ml was identified by the RSM with the following optimal set of parameters: concentration of substrate 15.5 mM, pH 9.25, and temperature 34oC. The accuracy of the predicted model optimum parameters was confirmed by experimenting under the same parameters. It was found that the experimental enzyme activity efficiency under optimum conditions was very close (less than a 3% error) to the model-predicted value. The removal efficiency of each heavy metal was found to be in the following order: Hg >Pb>As.