降尿酸菌株培养基优化

doi:10.11924/j.issn.1000-6850.casb2025-0650

摘要/Abstract

摘要：

旨在提高副干酪乳杆菌的菌体含量，为高尿酸血症的预防或治疗提供技术支持。通过单因素试验及响应面分析法，对副干酪乳杆菌的培养基进行了优化，在初步筛选出最佳碳源、氮源、缓冲盐、营养因子后，设计并实施了Box-Behnken响应面试验。试验结果表明，成功构建了一个以副干酪乳杆菌OD₆₀₀为响应值的多元二次回归方程，经模型分析，最终确定的副干酪乳杆菌最佳培养基为：可溶性淀粉35.1 g/L、酵母膏45.6 g/L、磷酸氢二钠7.3 g/L、白萝卜汁82.8 g/L。采用优化后的培养基进行培养，副干酪乳杆菌的活菌数为6.16×10⁹cfu/mL，显著优于优化前的水平，增长了3.2倍。

关键词: 单因素试验, 响应面试验, 副干酪乳杆菌, Box-Behnken, 优化, 最佳, 培养基, 活菌数

Abstract:

This study aimed to enhance the biomass content of Lactobacillus paracasei and provide technical support for its application in the prevention or treatment of hyperuricemia. The culture medium for Lactobacillus paracasei was optimized through single-factor and response surface methodology (RSM) experiments. Based on the screening of carbon sources, nitrogen sources, buffer salts, and nutritional factors via single-factor experiments, a Box-Behnken response surface design was employed. The results showed that a multiple quadratic regression model was established with OD₆₀₀ of Lactobacillus paracasei as the response value. Analysis of the model indicated that the optimal culture medium composition for Lactobacillus paracasei was as follows: soluble starch 35.1 g/L, yeast extract 45.6 g/L, disodium hydrogen phosphate 7.3 g/L, and white radish juice 82.8 g/L. After optimization, the viable count of Lactobacillus paracasei cultured in the optimized medium reached 6.16×10⁹ cfu/mL, which was 3.2 times higher than before optimization.

Key words: single-factor experiment, response surface methodology, Lactobacillus paracasei, Box-Behnken, optimization, optimal, culture medium, viable count

中图分类号:

S-3农业科学研究、试验

潘冬梅, 刘振学, 杨传伦, 苏士岗, 潘云霞, 刘结磊, 王旭亮, 马娜娜, 蔡倩倩. 降尿酸菌株培养基优化[J]. 中国农学通报, 2026, 42(17): 42-48.

PAN Dongmei, LIU Zhenxue, YANG Chuanlun, SU Shigang, PAN Yunxia, LIU Jielei, WANG Xuliang, MA Nana, CAI Qianqian. Optimization of Culture Medium for Uric Acid-reducing Bacterial Strain[J]. Chinese Agricultural Science Bulletin, 2026, 42(17): 42-48.

图/表 12

参考文献 25

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方差来源	平方和	自由度	均方	F值	P值	显著性
模型	2.86	14	0.20	24.27	<0.0001	极显著
A	0.38	1	0.38	44.71	<0.0001	极显著
B	0.42	1	0.42	49.46	<0.0001	极显著
C	0.085	1	0.085	10.05	0.0068	极显著
D	0.093	1	0.093	11.03	0.0050	极显著
AB	0.050	1	0.050	5.91	0.0290	显著
AC	3.192E-003	1	3.192E-003	0.38	0.5477	不显著
AD	0.015	1	0.015	1.73	0.2100	不显著
BC	0.014	1	0.014	1.63	0.2228	不显著
BD	0.024	1	0.024	2.89	0.1110	不显著
CD	0.052	1	0.052	6.24	0.0256	显著
A²	0.56	1	0.56	66.69	<0.0001	极显著
B²	0.65	1	0.65	77.53	<0.0001	极显著
C²	0.49	1	0.49	58.72	<0.0001	极显著
D²	0.96	1	0.96	114.72	<0.0001	极显著
残差	0.12	14	8.409E-003	—	—	—
失拟项	0.10	10	0.010	2.60	0.1854	不显著
纯误差	0.016	4	3.929E-003	—	—	—
总离差	2.98	28	—	—	—	—

方差来源	平方和	自由度	均方	F值	P值	显著性
模型	2.86	14	0.20	24.27	<0.0001	极显著
A	0.38	1	0.38	44.71	<0.0001	极显著
B	0.42	1	0.42	49.46	<0.0001	极显著
C	0.085	1	0.085	10.05	0.0068	极显著
D	0.093	1	0.093	11.03	0.0050	极显著
AB	0.050	1	0.050	5.91	0.0290	显著
AC	3.192E-003	1	3.192E-003	0.38	0.5477	不显著
AD	0.015	1	0.015	1.73	0.2100	不显著
BC	0.014	1	0.014	1.63	0.2228	不显著
BD	0.024	1	0.024	2.89	0.1110	不显著
CD	0.052	1	0.052	6.24	0.0256	显著
A²	0.56	1	0.56	66.69	<0.0001	极显著
B²	0.65	1	0.65	77.53	<0.0001	极显著
C²	0.49	1	0.49	58.72	<0.0001	极显著
D²	0.96	1	0.96	114.72	<0.0001	极显著
残差	0.12	14	8.409E-003	—	—	—
失拟项	0.10	10	0.010	2.60	0.1854	不显著
纯误差	0.016	4	3.929E-003	—	—	—
总离差	2.98	28	—	—	—	—