响应面法优化头孢菌素C发酵条件
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摘要
目的研究顶头孢霉发酵制备头孢菌素C的过程,确定关键影响因素,优化发酵条件,提高发酵水平。方法采用Plackett-Burman方法对影响头孢菌素C发酵水平的11个因素进行考察,评估各因素的影响程度,筛查影响发酵水平的关键因素,再采用响应面方法建立这些因素与发酵水平间的数学模型,为发酵条件的优化提供指导。结果 Plackett-Burman实验发现,金枪鱼浸膏浓度和蛋氨酸浓度是对头孢菌素C发酵产量影响最显著的2个因素,经响应面方法优化后头孢菌素C的产量从32.59g/L提高到了35.99g/L,提高了10.4%。结论合适浓度的金枪鱼浸膏和蛋氨酸可提高头孢菌素C发酵产量,通过统计优化方法,可有效提高头孢菌素C发酵水平。
Objective To study the cephalosporin C fermentation by Cephalosporium acremonium, ascertain the key factors, and improve the production level through condition optimization. Methods The PlackettBurman design was applied to evaluate the influence of related factors and screen the key factors critical to the yield. The response surface methodology was used to construct one statistic model of how these key elements impact the cephalosporin C yield in order to guide the fermentation condition optimization. Results Of eleven factors investigated, tuna extract and DL-methionine concentration were identified as the critical factors. Based on the mathematical model between the two factors and the fermentation yield of cephalosporin C established by the response surface methodology, an optimal fermentation condition was obtained and the yield of cephalosporin C increased 10.3% from 32.589 to 35.946 g/L. Conclusion The suitable concentration of tuna extract and methionine can improve the fermentation yield of cephalosporin C. With the help of statistical optimization methods, cephalosporin C fermentation yield was enhanced effectively.
Objective To study the cephalosporin C fermentation by Cephalosporium acremonium, ascertain the key factors, and improve the production level through condition optimization. Methods The PlackettBurman design was applied to evaluate the influence of related factors and screen the key factors critical to the yield. The response surface methodology was used to construct one statistic model of how these key elements impact the cephalosporin C yield in order to guide the fermentation condition optimization. Results Of eleven factors investigated, tuna extract and DL-methionine concentration were identified as the critical factors. Based on the mathematical model between the two factors and the fermentation yield of cephalosporin C established by the response surface methodology, an optimal fermentation condition was obtained and the yield of cephalosporin C increased 10.3% from 32.589 to 35.946 g/L. Conclusion The suitable concentration of tuna extract and methionine can improve the fermentation yield of cephalosporin C. With the help of statistical optimization methods, cephalosporin C fermentation yield was enhanced effectively.
引文
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[12]梅乐和,胡升,徐静,等.纳豆枯草杆菌的筛选和纳豆激酶发酵条件优化[J].浙江大学学报(工学版),2004,38(10):1355-1360.
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[14]Vasiee A,Behbahani B A,Yazdi F T,et al.Optimization of the production conditions of the lipase produced by Bacillus cereus from rice flour through Plackett-Burman Design(PBD)and response surface methodology(RSM)[J].Microb Pathog,2016,101:36-43.
[15]Korayem A S,Abde A A,Zaki M M,et al.Optimization of biosurfactant production by Streptomyces isolated from Egyptian arid soil using Plackett-Burman design[J].Ann Agric Sci,2015,60(2):209-217.
[16]Lotfy W A.The utilization of beet molasses as a novel carbon source for cephalosporin C production by Acremonium chrysogenum:Optimization of process parameters through statistical experimental designs[J].Bioresour Technol,2007,98(18):3491-3498.
[17]郑杰.试验设计与数据分析[M].广州:华南理工大学出版社,2016:188-209.
[18]刘振学,王力,等.实验设计与数据处理[M].北京:化学工业出版社,2016:82-88.
[19]李英英.头孢菌素C高产菌株高通量筛选及低场核磁在发酵过程中油含量检测的应用[D].上海:华东理工大学,2017:2-6.
[2]薛雨,陈宇瑛.头孢菌素类抗生素的最新研究进展[J].中国抗生素杂志,2011,36(2):86-92.
[3]You J,Bao Q Z.Study on genetic engineering of Acremonium chrysogenum the cephalosporin C producer[J].Synth Systems Biotechnol,2016,1(1):143-149.
[4]Luo H Z,Zhang J S,Yuan G Q,et al.Performance improvement of cephalosporin C fermentation by Acremonium chrysogenum with DO-Stat based strategy of co-feeding soybean oil and glucose[J].Proc Biochem,2013,48(12):1822-1830.
[5]Jobanputra A H,Vasait R D.Cephalosporin C acylase from Pseudomonas species:Production and enhancement of its activity by optimization of process parameters[J].Biocat Agric Biotechnol,2015,4(4):465-470.
[6]郭元昕,李景森,储炬,等.豆油对头孢菌素C发酵影响的初步研究[J].中国抗生素杂志,2010,35(1):747-750.
[7]桑美纳,袁国强,李红飞,等.不同补料控制方式发酵生产头孢菌素C的性能比较[J].微生物学通报,2011,38(9):1321-1330.
[8]徐洪利,赵斐,左良成,等.响应面法优化头孢菌素C摇瓶发酵培养基[J].中国抗生素杂志,2014,39(4):253-255.
[9]Duan S B,Yuan G Q,Zhao Y L.Enhanced cephalosporin C production with a combinational ammonium sulfate and DO-Stat based soybean oil feeding strategy[J].Biochem Engineer J,2012,61(15):1-10.
[10]Hamid M.Production of cephalosporin C from Acremonium chrysogenum and optimization of fermentation parameters[J].J Biotechnol,2010,150:374.
[11]李宁慧.头孢菌素C高产顶头孢霉的选育和发酵条件优化[M].杭州:浙江大学,2011:37-48.
[12]梅乐和,胡升,徐静,等.纳豆枯草杆菌的筛选和纳豆激酶发酵条件优化[J].浙江大学学报(工学版),2004,38(10):1355-1360.
[13]Jia,B,Jin Z H,Mei L H.Medium optimization based on statistical methodologies for pristinamycins production by Streptomyces pristinaespiralis[J].Appl Biochem Biotechnol,2007,144(2):133-143.
[14]Vasiee A,Behbahani B A,Yazdi F T,et al.Optimization of the production conditions of the lipase produced by Bacillus cereus from rice flour through Plackett-Burman Design(PBD)and response surface methodology(RSM)[J].Microb Pathog,2016,101:36-43.
[15]Korayem A S,Abde A A,Zaki M M,et al.Optimization of biosurfactant production by Streptomyces isolated from Egyptian arid soil using Plackett-Burman design[J].Ann Agric Sci,2015,60(2):209-217.
[16]Lotfy W A.The utilization of beet molasses as a novel carbon source for cephalosporin C production by Acremonium chrysogenum:Optimization of process parameters through statistical experimental designs[J].Bioresour Technol,2007,98(18):3491-3498.
[17]郑杰.试验设计与数据分析[M].广州:华南理工大学出版社,2016:188-209.
[18]刘振学,王力,等.实验设计与数据处理[M].北京:化学工业出版社,2016:82-88.
[19]李英英.头孢菌素C高产菌株高通量筛选及低场核磁在发酵过程中油含量检测的应用[D].上海:华东理工大学,2017:2-6.