Optimization of fermentation medium and conditions for enhancing valinomycin production by Streptomyces sp. ZJUT-IFE-354.

Valinomycin is a cyclodepsipeptide antibiotic with a broad spectrum of biological activities, such as antiviral, antitumor, and antifungal activities. However, the low yield of valinomycin often limits its applications in medicine, agriculture, and industry. In our previous report, Streptomyces sp. ZJUT-IFE-354 was identified as a high-yielding strain of valinomycin. In this study, Plackett-Burman design (PBD) and response surface methodology (RSM) were used to optimize components of medium. The optimal medium contained 31 g/L glucose, 22 g/L soybean meal, and 1.6 g/L K2HPO4·3H2O, which could generate 262.47 ± 4.28 mg/L of valinomycin. Then, the culture conditions were optimized by a one-factor-at-a-time (OFAT) approach. The optimal conditions for the strain included a seed age of 24 h, an inoculum size of 8% (v/v), an incubation temperature of 28 °C, an initial pH of 7.2, an elicitor of 0.1% Bacillus cereus feeding at 24 h cultivation, and the feeding of 0.6% L-valine at 36 h cultivation. The final valinomycin production increased to 457.23 ± 9.52 mg/L, which was the highest yield ever reported. It highlights that RSM and OFAT may be efficient methods to enhance valinomycin production by Streptomyces sp. ZJUT-IFE-354.

Application of an integrated statistical design for optimization of culture condition for ammonium removal by Nitrosomonas europaea.

Statistical methodology was applied to the optimization of the ammonium oxidation by Nitrosomonas europaea for biomass concentration (C(B)), nitrite yield (Y(N)) and ammonium removal (R(A)). Initial screening by Plackett-Burman design was performed to select major variables out of nineteen factors, among which NH4Cl concentration (C(N)), trace element solution (TES), agitation speed (AS), and fermentation time (T) were found to have significant effects. Path of steepest ascent and response surface methodology was applied to optimize the levels of the selected factors. Finally, multi-objective optimization was used to obtain optimal condition by compromise of the three desirable objectives through a combination of weighted coefficient method coupled with entropy measurement methodology. These models enabled us to identify the optimum operation conditions (C(N)= 84.1 mM; TES = 0.74 ml; AS= 100 rpm and T = 78 h), under which C(B)= 3.386×10(8) cells/ml; Y(N)= 1.98 mg/mg and R(A) = 97.76% were simultaneously obtained. The optimized conditions were shown to be feasible through verification tests.