Statistical design of experiments for optimization of arsenate reductase production by Kocuria palustris (RJB-6) and immobilization parameters in polymer beads

Abstract

Detection and bioremediation of arsenic by bacterial strains are of immense importance. The enzyme arsenate reductase produced by microbes plays an important role for both. The enzyme, however, is not produced commercially. This study presents statistical optimization of operational parameters for the enhancement of arsenate reductase production by an arsenic tolerant bacterium Kocuria palustris (RJB-6). Plackett–Burman and response surface methodology (RSM) were applied to screen the significant variables and determine the interactive effect of the factors influencing enzyme production. The highest arsenate reductase activity of 31.86 U mL⁻¹ was obtained under optimized conditions (pH 5.0; seed age 24 h; substrate concentration 150 μM) compared to that obtained under common process parameters (12.89 U mL⁻¹). A K_m value of 6.36 mM and V_max of 6250 μmol per min per mg protein were achieved from an enzyme kinetics study. EDAX analysis confirmed cytoplasmic accumulation of arsenic by RJB-6. RSM was applied to evaluate the effect of various formulations of the selected polymeric matrices for the immobilization of the enzyme. Maximum enzyme activity was obtained with a combination of alginate, chitosan, and glutaraldehyde at 3%, 0.75% and 0.75% respectively. The immobilized enzyme retained its activity following 15 cycles of reuse and had storage stability of up to 30 days at 4 °C. This ensured the potential application of the enzyme in large-scale remediation and detection of arsenic in a cost-effective and environment friendly way.