响应面法优化S-腺苷蛋氨酸发酵培养基的研究  

Optimization of mediam for S-adenosylmethionine by response surface method

作　　者：张渝杰[1] 詹良静[1] 张新宜[1] 王欣荣[1] 

机构地区：[1]中国医药集团总公司四川抗菌素工业研究所,成都610052

出　　处：《中国抗生素杂志》2013年第4期255-260,共6页Chinese Journal of Antibiotics

基　　金："重大新药创制"科技重大专项;"国药集团技术创新产学研联盟建设"2011ZX09401-403

摘　　要：目的采用响应面法对酿酒酵母菌发酵生产S-腺苷蛋氨酸(SAM)的培养基进行优化,提高S-腺苷蛋氨酸发酵单位。方法采用Plackett-Burman设计和响应面法进行培养基优化,对8个因素进行了筛选,结果表明:酵母粉,葡萄糖,丝氨酸的浓度对S-腺苷蛋氨酸产量的影响最大。通过最陡爬坡试验及Box-Behnken设计对3个显著因素进行寻优,并利用Design-Expert软件对实验数据进行二次回归分析。结果结果显示酵母粉、葡萄糖和丝氨酸的最佳浓度分别为39.5、73.4和6g/L。经过3次试验所测得的数据8402.6、8600.0和8357.9mg/L。与预测结果基本一致。结论模型预测值与实际值吻合度比较高,模型具有显著性,比优化前提高了53%。Objective The medium was optimized for fermentation ofS. cerevisiae by response surface method to enhance the concentration of S-adenosylmethionine. Methods The component of medium for fermentation of S-adenosylmenthionine was optimized by Plackett-Burman design and response surface method. A Plackett-Burman design was used to evaluate the influence of eight factors. Results showed that the concentration of yeast extract, glucose, serine played important roles in influencing the content of S-adenosylmethionine. Then, the path of steepest ascent and the Box-Behnken design were adopted for further optimization,and the optimum concentration levels and the relationships among these factors was found out by quadratic regression model equation with Design-Expert statistic methods. Results The optimized concentrations of yeast extract, glucose, serine were 39.5, 73.4 and 6g/L. The adenosylmethionine yields obtained by three verification tests were 8402.6,8600.0 and 8357.9 mg/L,which was basically consistent with that expected. Conclusion Indicates that the model predicted and actual values of the degree of matching is relatively high, the model was significant. And the concentration of Adenosylmethionine was increased by 53% compared with the previous condition.

关 键 词：响应面法 酿酒酵母 S-腺苷蛋氨酸 发酵 培养基 

分 类 号：TQ464.7[化学工程—制药化工]