Statistical medium optimization to increase rhamnolipid production by Pseudomonas aeruginosa sp MB2

BACKGROUND: We aimed to provide an appropriate production medium using statistical optimization method that could significantly improve rhamnolipid production. METHODS: A two-stage optimization strategy, on the basis of statistical experimental designs, was applied to improve production of rhamnolipid by an indigenous Pseudomonas aeruginosa (P. Aeruginosa) isolate. For screening bioprocess factors significantly affected rhamnolipid production, the two-level Plackett-Burman design was employed. RESULTS: Among eleven variables attempts; yeast extract, NH4NO3 and (NH4)(2)HPO4 were opted based on their high significant influence on rhamnolipid production. These variables were then selected and run separately for glucose and sunflower oil by employing the three-level Box-Behnken design. A polynomial model was produced to establish a mutual relation between the three variables and rhamnolipid production. Optimum combination of chief components of medium for rhamnolipid production assessed from non-linear optimization algorithm of MINITAB Response Surface Optimizer function was as follows: yeast extract 3 (NH4)(2)HPO4 1 and NH4NO3 3 g/L for glucose, and: yeast extract 2.59, (NH4)(2)HPO4 1 and NH4NO3 3 g/L for sunflower oil. The forecasted optimum ingredients for rhamnolipid production were 1.253 g/L and 0.877 g/L for sunflower oil and glucose, which were 2.064 and 1.44 times more than the basal medium for sunflower oil and glucose, respectively. CONCLUSIONS: The statistical method provided rapid identification and integration of important medium factors for P. aeruginosa sp. MB2, resulting in high rhamnolipid production.