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Physical optimization of thermostable alkaline protease by E. coli BL21 (DE3) plyss harboring 50a protease gene using response surface methodology

机译:使用响应面方法通过带有50a蛋白酶基因的大肠杆菌BL21(DE3)层对热稳定碱性蛋白酶的物理优化

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摘要

Physical optimization is important for enzyme production by fermentation process. In general, fermentation process at optimal condition increases the expression and production level of enzyme to many times in comparison with their natural production. This study was focused on the optimization of the physical factors that influenced the thermostable alkaline protease production. The induction and incubation time were studied using conventional method while the other three factors which are incubation temperature, initial pH of medium and agitation speed were optimized by response surface methodology (RSM). The interaction effects among these factors were explained using response plot and the model adequacy was satisfactory as the coefficient of determination (R²) was 96.48%. The enhancement of thermostable protease from 197.83 U/ml to 325.89 U/ml was achieved using both conventional and statistical approach of response surface methodology (RSM). This present study proved that physical optimization significantly affects the protease production and the optimum physical condition obtained may applied in large scale process.
机译:物理优化对于通过发酵过程生产酶至关重要。通常,在最佳条件下的发酵过程与其天然产生的酶相比,其表达和生产水平提高了许多倍。这项研究的重点是影响热稳定碱性蛋白酶生产的物理因素的优化。采用常规方法研究了诱导时间和孵育时间,采用响应面法(RSM)优化了孵育温度,培养基初始pH和搅拌速度等三个因素。使用响应图解释了这些因素之间的相互作用,并且模型的确定性令人满意,因为测定系数(R²)为96.48%。使用响应面方法(RSM)的常规方法和统计方法均可实现将热稳定蛋白酶从197.83 U / ml提高到325.89 U / ml。本研究证明,物理优化会显着影响蛋白酶的生产,并且所获得的最佳物理条件可应用于大规模过程。

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