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Bioprocess development for production of alkaline protease by bacillus pseudofirmus Mn6 through statistical experimental designs

机译:通过统计实验设计开发假细菌芽孢杆菌Mn6生产碱性蛋白酶的生物工艺

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摘要

A sequential optimization strategy, based on statistical experimental designs, is employed to enhance the production of alkaline protease by a Bacillus pseudofirmus local isolate. To screen the bioprocess parameters significantly influencing the alkaline protease activity, a 2-level Plackett-Burman design was applied. Among 15 variables tested, the pH, peptone, and incubation time were selected based on their high positive significant effect on the protease activity. A near-optimum medium formulation was then obtained that increased the protease yield by more than 5-fold. Thereafter, the response surface methodology (RSM) was adopted to acquire the best process conditions among the selected variables, where a 3-level Box-Behnken design was utilized to create a polynomial quadratic model correlating the relationship between the three variables and the protease activity. The optimal combination of the major medium constituents for alkaline protease production, evaluated using the nonlinear optimization algorithm of EXCEL-Solver, was as follows: pH of 9.5, 2% peptone, and incubation time of 60 h. The predicted optimum alkaline protease activity was 3,213 U/ml/min, which was 6.4 times the activity with the basal medium.
机译:基于统计实验设计的顺序优化策略可用于增强假单胞杆菌局部分离株碱性蛋白酶的产生。为了筛选显着影响碱性蛋白酶活性的生物过程参数,应用了2级Plackett-Burman设计。在测试的15个变量中,根据其对蛋白酶活性的高正显着影响来选择pH,蛋白ept和孵育时间。然后获得了接近最佳的培养基配方,该配方将蛋白酶的产量提高了5倍以上。此后,采用响应面方法(RSM)来获得所选变量中的最佳工艺条件,其中采用三级Box-Behnken设计来创建多项式二次模型,该模型将三个变量与蛋白酶活性之间的关系相关联。使用EXCEL-Solver的非线性优化算法评估的用于碱性蛋白酶生产的主要培养基成分的最佳组合如下:pH值为9.5,蛋白ept为2%,孵育时间为60 h。预测的最佳碱性蛋白酶活性为3,213 U / ml / min,是基础培养基活性的6.4倍。

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