Statistical optimization of l-leucine amino peptidase production from Streptomyces gedanensis IFO 13427 under submerged fermentation using response surface methodology

Abstract

Response surface methodology (RSM) employing the central composite design (CCD) was used to optimize the fermentation medium for the production of l-leucine amino peptidase (LAP) from Streptomyces gedanensis IFO13427 under submerged fermentation. The design was employed by selecting substrate concentration, NaCl concentration and initial pH as model factors by ‘one variable at a time’ experiment. A second-order quadratic model and response surface method showed that the optimum conditions (soy bean 0.3%, NaCl, 0.03 M, and initial pH 7) resulted in the improvement of LAP production (25.69 IU/ml) as compared to the initial level (12.17 ± 0.23 IU/ml) after 72 h of fermentation, whereas its value predicted by the quadratic model was 24.56 IU/ml. Analysis of variance (ANOVA) showed a high coefficient of determination (R2) value of 0.9799, ensuring a satisfactory adjustment of the quadratic model with the experimental data. This is first report on LAP production by S. gedanensis using statistical experimental design and response surface methodology in submerged fermentation.