Statistical optimization of a multivariate fermentation process for enhancing antibiotic activity of Streptomyces sp. CS392

Abstract

Antibiotic activity against various gram positive bacteria including Staphylococcus aureus and Enterococcus was ascertained from a soil-isolated microbial strain Streptomyces sp. CS392. The antibiotic activity of the strain was maximized by using a dual-stage, multivariate statistical optimization framework based on the response surface methodology considering a lab-scale fermentation process. Multiple nutrient constituents of the fermentation broth were jointly optimized in the first stage, while the fermentation culture conditions were optimized in the subsequent stage. Based on the empirical models derived from the dual-stage statistical optimization framework, 39.79 % of cumulative enhancement in the antibiotic activity was obtained (analytically) at the concurrent optimal settings (Optimal nutrient composition for the first stage of optimization: 29.82 glucose, 7.6 peptone, 4.678 MgCl₂ and 0.5005 g/l casamino acid; and optimal fermentation condition for the second stage of optimization: incubation period 47.55 h; incubation temperature 29.15 °C; and pH 8.36). The analytically depicted enhancement in the antibiotic activity was validated experimentally.