• 主题
高级搜索  >
历史搜索 清空历史
首页> 美国卫生研究院文献>Scientific Reports >Response Surface Methodology-Genetic Algorithm Based Medium Optimization Purification and Characterization of Cholesterol Oxidase from Streptomyces rimosus
【2h】

Response Surface Methodology-Genetic Algorithm Based Medium Optimization Purification and Characterization of Cholesterol Oxidase from Streptomyces rimosus

机译：基于响应面方法-遗传算法的中链Streptomyces rimosus胆固醇氧化酶的培养基优化纯化和表征

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务，本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文，但由于OA文献来源多样且变更频繁，仍可能出现获取不到、文献不完整或与标题不符等情况，如果获取不到我们将提供退款服务。请知悉。
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

The applicability of the statistical tools coupled with artificial intelligence techniques was tested to optimize the critical medium components for the production of extracellular cholesterol oxidase (COD; an enzyme of commercial interest) from Streptomyces rimosus MTCC 10792. The initial medium component screening was performed using Placket-Burman design with yeast extract, dextrose, starch and ammonium carbonate as significant factors. Response surface methodology (RSM) was attempted to develop a statistical model with a significant coefficient of determination (R2 = 0.89847), followed by model optimization using Genetic Algorithm (GA). RSM-GA based optimization approach predicted that the combination of yeast extract, dextrose, starch and ammonium carbonate at concentrations 0.99, 0.8, 0.1, and 0.05 g/100 ml respectively, has resulted in 3.6 folds increase in COD production (5.41 U/ml) in comparison with the un-optimized medium (1.5 U/ml). COD was purified 10.34 folds having specific activity of 12.37 U/mg with molecular mass of 54 kDa. The enzyme was stable at pH 7.0 and 40 °C temperature. The apparent Michaelis constant (Km) and Vmax values of COD were 0.043 mM and 2.21 μmol/min/mg, respectively. This is the first communication reporting RSM-GA based medium optimization, purification and characterization of COD by S. rimosus isolated from the forest soil of eastern India.
机译：测试了统计工具与人工智能技术相结合的适用性，以优化用于从线状链霉菌MTCC 10792生产细胞外胆固醇氧化酶（COD；商业上感兴趣的酶）的关键培养基成分。使用Placket进行了初始培养基成分筛选-Burman设计，其中酵母提取物，葡萄糖，淀粉和碳酸铵是重要因素。尝试使用响应面方法（RSM）建立具有显着确定系数（R 2 = 0.89847）的统计模型，然后使用遗传算法（GA）进行模型优化。基于RSM-GA的优化方法预测，分别以0.99、0.8、0.1和0.05微克/ 100微升的浓度混合酵母提取物，葡萄糖，淀粉和碳酸铵，可使COD产量增加3.6倍（5.41 U / ml ）与未优化的培养基（1.5 U / ml）相比。纯化的COD为10.34倍，比活为12.37 U / mg，分子量为54 kDa。该酶在pH 7.0和40°C的温度下稳定。 COD的表观米氏常数（Km）和Vmax分别为0.043 mM和2.21μmol/ min / mg。这是首次报道基于RSM-GA的培养基，该培养基从印度东部的森林土壤中分离出的金边链球菌对COD进行了优化，纯化和表征。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号