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Response Surface Methodology for the Optimizationof Proteases Production by a Novel Egyptian IsolateBacillus amyloliquefaciens 35s

机译:响应面方法优化新型埃及分离株蛋白酶的解淀粉芽孢杆菌35s

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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 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.
机译:目的:本研究旨在使用响应表面方法(RSM)优化解淀粉芽孢杆菌35s的蛋白酶生产。研究设计:使用Plackett-Burman设计筛选影响蛋白酶生产的变量。采用RSM的面心中央复合设计(FCCCD)来增加三种编码水平(–1、0,+ 1)评估的总蛋白酶产量。所有获得的数据均通过ANOVA进行分析,并使用Tukey HSD进行事后多重比较分析。研究的地点和持续时间:艾因汉姆斯大学农学院农业微生物学系,2014年3月至2014年9月。方法:解淀粉芽孢杆菌35s用于生产蛋白酶。改良的TGY(色氨酸葡糖酵母提取物)培养基是基础培养基。采用Plackett-Burman设计和倍增法研究了营养因素(碳,氮和矿物质盐)的影响。 “设计专家? 8.0.7.1英寸Stat-Ease用于分析实验性的Plackett-Burman设计。通过RSM的阶乘FCCCD对温度,pH和搅拌速率(使用摇瓶)进行统计优化。物理因素统计模型的验证是通过在由模型确定的最佳工艺参数条件下进行实验来完成的。在5 L台式连续搅拌罐式生物反应器中检查并验证了通过RSM获得的关于FCCCD的最佳条件,并在具有受控和非受控pH的间歇过程中扩大了生产过程。结果:在重要的培养基成分中,蛋白ept和淀粉对蛋白酶的反应具有显着影响,置信度> 98%,并进行了进一步优化使用FCCCD。促进蛋白酶产生的条件与增强细胞生长的条件不同。物理参数表明解淀粉芽孢杆菌产生的蛋白酶是非生长依赖性的。在蛋白p(10 g / l)和淀粉(10 g / l)的中点(0)值(浓度)附近观察到最大预测的蛋白酶产量(992.12 u / ml),实验值为935 u / ml。非常接近验证模型的预测值。在生物反应器中,最终蛋白酶的产量在0.6 vvm曝气和120 rpm搅拌速度下于12-14小时内达到1530 u / ml。结论:代替时变法的一种常规方法,即响应面法,作为统计方法,证明足以和有效地优化解淀粉芽孢杆菌的蛋白酶生产。

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