A statistical approach to the optimization of cold‐adapted amylase production by Exiguobacterium sp. SH3

Abstract

AbstractCold‐adapted enzymes produced by psychrotrophic organisms are interesting from both molecular and biotechnological viewpoints. The enzymes show superior catalytic activity than their mesophilic and thermophilic counterparts at room temperature. Therefore, the enzymes seem interesting for applications where high catalytic activity at ambient temperature is required. In this study, the production of cold‐adapted amylase by Exiguobacterium sp. SH3 was optimized and modeled. In the first step, single factor experiments using shake flask cultures were conducted for primary optimization. These experiments resulted in the improvement of amylase production up to 180 U/mL. In the next step, the Plackett–Burman design was used to identify significant factors affecting the amylase production. Starch concentration, tryptone concentration, and temperature were selected as significant factors; while time, shaking, yeast extract, pH, MnCl2, CaCl2, MgCl2, and KH2PO4 were not significant in this step. Finally, the response surface methodology based on central composite design (CCD) was used for further optimization and modeling of the significant factors. The optimization efforts resulted in the maximum amylase production of 730 U/mL, which was four times higher than that achieved by the single‐factor optimization experiments.