摘要: |
采用响应面法对1株高产琼胶酶的南极海冰菌Pseudoalteromonassp. NJ21的发酵条件进行优化。首先分别以温度、pH、不同碳源、不同氮源、不同金属离子作为唯一变量进行单因素实验, 筛选出对酶活有显著影响的单因素取值范围; 参考单因素实验结果, 采用Plackett-Burman实验设计筛选出影响酶活主要因素, 再利用Box-Behnken设计及响应面分析法进行回归分析以确定最佳发酵条件。结果表明, D-甘露糖、蛋白胨、CaCl2和培养温度与酶活存在着显著的相关性, 通过求解回归方程得到Pseudoalteromonassp. NJ21的最佳培养基组成为D-甘露糖5.52g/L; 蛋白胨7.4g/L; CaCl25.84mmol/L; 最佳发酵温度为15℃; 优化后发酵液中琼胶酶酶活由3.5U/mL提高到25.76U/mL, 比优化前提高了6.36倍。 |
关键词: 南极菌Pseudoalteromonassp. NJ21 琼胶酶 优化 响应面法 |
DOI:10.11693/hyhz201306031 |
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基金项目:海洋公益性行业科研专项经费, 201105027 号; 山东省中青年科学家科研奖励基金, DS2010HZ001 号; 国家海洋局一所基本科研业务费专项基金, GY02-2011G17 号。 |
附件 |
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OPTIMIZATION OF FERMENTATION CONDITIONS OF AN AGARASE- PRODUCING ANTARCTIC BACTERIUM PSEUDOALTEROMONASsp. NJ21 BY RESPONSE SURFACE METHODOLOGY |
XU Yuan1, LI Yu-Quan1, LI Jiang2, SHA Yu-Jie2, ZHANG Qu2
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1.College of Animal Science and Technology, Agriculture University of Qingdao;2.Key Lab of Marine Bioactivity Substance, The First Institute of Oceanography, State Oceanic Administration
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Abstract: |
To study the optimal culture medium and fermentation conditions of an agarase-produced Antarctic bacterium Pseudoalteromonassp. NJ21, we applied response surface methodology to optimize systematically the fermentation medium and the conditions. First, the range of single factors (temperature, pH, carbon sources, nitrogen sources, metal ions, and inoculum) were selected by single test. Second, three important factors on agarase activity were identified in Plackett-Burman design as D-mannose, strontium chloride, and calcium chloride. We also adopted Box-Behnken design and
response surface analysis to further investigate the mutual interaction of the variables and obtain optimal values at maximum agarase activity. The optimal conditions included culture medium composition of D-mannose at 5.52g/L + Peptone at 7.4g/L + CaCl2at 5.84mmol/L and fermentation temperature at 15℃, under which the agarase activity of the fermentation broth was improved to from 3.5 to 25.76U/mL, a 6.36-fold increase. |
Key words: Antarctic bacterium Pseudoalteromonassp. NJ21 agarase optimization response surface methodology |