Investigation of antimicrobial activity and statistical optimization of Bacillus subtilis SPB1 biosurfactant production in solid-state fermentation.

During the last years, several applications of biosurfactants with medical purposes have been reported. Biosurfactants are considered relevant molecules for applications in combating many diseases. However, their use is currently extremely limited due to their high cost in relation to that of chemical surfactants. Use of inexpensive substrates can drastically decrease its production cost. Here, twelve solid substrates were screened for the production of Bacillus subtilis SPB1 biosurfactant and the maximum yield was found with millet. A Plackett-Burman design was then used to evaluate the effects of five variables (temperature, moisture, initial pH, inoculum age, and inoculum size). Statistical analyses showed that temperature, inoculum age, and moisture content had significantly positive effect on SPB1 biosurfactant production. Their values were further optimized using a central composite design and a response surface methodology. The optimal conditions of temperature, inoculum age, and moisture content obtained under the conditions of study were 37°C, 14 h, and 88%, respectively. The evaluation of the antimicrobial activity of this compound was carried out against 11 bacteria and 8 fungi. The results demonstrated that this biosurfactant exhibited an important antimicrobial activity against microorganisms with multidrug-resistant profiles. Its activity was very effective against Staphylococcus aureus, Staphylococcus xylosus, Enterococcus faecalis, Klebsiella pneumonia, and so forth.

Optimization of the Nutritional Parameters for Enhanced Production of B. subtilis SPB1 Biosurfactant in Submerged Culture Using Response Surface Methodology.

Nutritional requirements can contribute considerably to the production cost and the bioprocess economics. Media optimisation using response surface methodology is one of the used methods to ameliorate the bioprocess economics. In the present study, biosurfactant production by Bacillus subtilis SPB1 was effectively enhanced by response surface methodology. A Plackett-Burman-based statistical screening procedure was adopted to determine the most important factor affecting lipopeptide production. Eleven variables are screened and results show that glucose, K(2)HPO(4), and urea concentrations influence the most biosurfactant production. A Central Composite Design was conducted to optimize the three selected factors. Statistical analyses of the data of model fitting were done by using NemrodW. Results show a maximum predicted biosurfactant concentration of 2.93 (±0.32) g/L when using 15 g/L glucose, 6 g/L urea, and 1 g/L K(2)HPO(4). The predicted value is approximately 1.65 much higher than the original production determined by the conventional one-factor-at-a-time optimization method.