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细脚拟青霉RCEF4339原生质体制备工艺优化 被引量:1

Optimization of protoplast preparation conditions of Paceilomyces tenuipes RCEF4339
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摘要 采用多种化学计量学方法优化并建立细脚拟青霉RCEF4339最优原生质体制备工艺。首先,采用单因素优化策略筛选得到细脚拟青霉原生质体制备的最适酶为溶壁酶、其浓度为2 mg/mL、酶解温度32℃、酶解时间3 h、pH 7.0、渗透压稳定剂0.9 mol/L KCl。其次,应用Plackett-Burman设计试验筛选得到影响原生质体生成量的关键因素(酶解时间、pH值和酶解温度)。最后,通过Box-Behnken设计试验对3个关键因素进一步优化。建立多元二次回归模型拟合Box-Behnken设计试验结果,并采用响应面法考察各因素间的交互作用。与此同时,进一步建立神经网络模型,并通过遗传算法寻优,经过上述优化过程获得了细脚拟青霉的最适原生质体制备工艺:渗透压稳定剂为0.9 mol/L的KCl缓冲液,溶壁酶酶解浓度2 mg/mL,酶解时间为3.4 h,酶解温度为28.0℃,pH值为6.0。按照该最优条件制备细脚拟青霉原生质体,其原生质体生成量为4.398 2×10~7个/mL,而原生质体再生率为31.25%,表明采用化学计量学方法优化细脚拟青霉原生质体制备工艺是可行的。 Paecilomyces tenuipes,one of the commonly used Chinese medicinal fungi,possesses various biological activities. However,the yield of active constituents in P. tenuipes is low. Therefore,it is urgent to screen high-production strain. Protoplast is an important material which has been widely used in filamentous fungi breeding. In this study,a sequential statistical approach was applied to optimize the protoplast preparation conditions from P. tenuipes RCEF4339. Based on single-factor optimization strategy,the optimal condition was obtained as hydrolysis by 2 mg/mL lyticase at 32 ℃ and pH 7 for 3 h,wherein using 0. 9 mol/L KCl was used for stabilization of osmotic pressure. Then,key factors( enzymatic hydrolysis time,enzymatic hydrolysis temperature and pH) were identified by Plackett-Burman design. Finally,the suitable values of three key factors were further optimized by Box-Behnken design. A multiple quadratic regression model was established for fitting the results of Box-Behnken design experiment.Response surface methodology was employed to investigate the mutual effects between candidate factors and response value. Artificial neural network-genetic algorithm were further used to model and optimize the experimental results obtained from Box-Behnken design experiment. The optimum conditions of protoplast preparation of P. tenuipes were hydrolysis by 2 mg/mL lyticase at 28 ℃,pH 6. 0 for 3. 7 h,wherein 0. 9 mol/L KCl was used for stabilization of osmotic pressure. The mean amount of protoplast reached 4. 398 2 × 10~7/mL. The rate of protoplast regeneration was 31. 25%. The experimental results showed that this method was reliable.
作者 杜林娜 魏东旭 李秀兰 姚宇 DU Lin-na ,WEI Dong-xu, LI Xiu-lan,YAO Yu(College of Life Science, Jilin Agricultural University, Changchun 130118, Chin)
出处 《食品与发酵工业》 CAS CSCD 北大核心 2018年第7期69-75,共7页 Food and Fermentation Industries
基金 吉林农业大学科研启动基金(2015014) 吉林省教育厅"十三五"科学技术研究项目吉教科合字(2016180) 2016大学生创新计划项目(201610193042) 吉林省科技厅优秀青年人才基金项目(20170520035JH)
关键词 细脚拟青霉 原生质体 响应面法 神经网络 遗传算法 Paecilomyces tenuipes protoplast response surface methodology artificial neural network genetic al-gorithms
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