Response Surface Methodology for the Optimization of Proteases Production by a Novel Egyptian Isolate Bacillus amyloliquefaciens 35s

Abstract

Aims: The present work aimed to optimize proteases production by Bacillus amyloliquefaciens 35s using the response surface methodology (RSM). Study Design: Variables affecting proteases production were screened using a Plackett–Burman design. Face Centered Central Composite Design (FCCCD) of RSM was adopted for the augmentation of total proteases production assessed at three coded levels (–1, 0, +1). All obtained data were analyzed by ANOVA with post hoc multiple comparison analysis performed using Tukey’s HSD. Place and Duration of Study: Department of Agricultural Microbiology, Faculty of Agriculture, Ain Shams University, between March 2014 and September 2014. Methodology: Bacillus amyloliquefaciens 35s was used for proteases production. Modified TGY (Tryptone gluscose yeast extarct) medium was the basal medium. Impacts of nutritional factors (carbon and nitrogen and mineral salts) were studied using Plackett-Burman design with fold over augmenting method. “Design Expert ® 8.0.7.1” Stat-Ease was used to analyze the experimental Original Research Article Nassar et al.; BMRJ, 6(5):255-269, 2015; Article no.BMRJ.2015.078 256 Plackett–Burman design. Temperature, pH and agitation rate (using shake flask) were optimized statistically by the factorial FCCCD of the RSM. Validation of statistical model of physical factors was done by carrying out the experiment at optimum conditions of the process parameters as determined from the model. Optimum conditions obtained through RSM in terms of FCCCD were examined and verified in a 5 L bench top continuous stirred tank bioreactor and production process was scaled-up in a batch process with controlled and non-controlled pH. Fermented medium was centrifuged to collect cells and determination of biomass and protease concentration. Results: Among the significant media components, peptone and starch showed to have significant effects on the response as for protease production, with confidence level > 98% and were further optimized using FCCCD. Conditions promoted proteases production were different from those enhanced cell growth. Physical parameters indicated that production of proteases by Bacillus amyloliquefaciens is non-growth dependent. Maximum proteases production predicted (992.12 u/ml) was observed near the mid-point (0) values (concentrations) of both peptone (10 g/l) and starch (10 g/l) and the experimental value 935 u/ml was very close to the predicted value validating the model. The final proteases production in the bioreactor reached 1530 u/ml obtained within 12-14 h at 0.6 vvm aeration and 120 rpm of agitation speed. Conclusion: Instead of conventional method of one variable at time approach, Response Surface Methodology, as statistical approach, showed to be adequate and efficient to optimize protease production by Bacillus amyloliquefaciens.