食品科学 ›› 2020, Vol. 41 ›› Issue (22): 140-147.doi: 10.7506/spkx1002-6630-20190916-182

• 生物工程 • 上一篇    下一篇

Nisin、ɛ-聚赖氨酸、pH值对虾源枯草芽孢杆菌生长/非生长界面模型构建与评价

郭全友,刘玲,李保国,杨絮,姜朝军   

  1. (1.中国水产科学研究院东海水产研究所,上海 200090;2.上海理工大学医疗器械与食品学院,上海 200093)
  • 出版日期:2020-11-25 发布日期:2020-11-26
  • 基金资助:
    中国水产科学研究院基本科研业务费资助项目(2020TD68);国家自然科学基金面上项目(31871872)

Modelling and Evaluating Growth/No-growth Interface of Bacillus subtilis Isolated from Penaeus vannamei Affected by Nisin, ɛ-Polylysine and pH

GUO Quanyou, LIU Ling, LI Baoguo, YANG Xu, JIANG Chaojun   

  1. (1. East China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Shanghai 200090, China; 2. School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China)
  • Online:2020-11-25 Published:2020-11-26

摘要: 以分离自熟制南美白对虾的虾源枯草芽孢杆菌为对象,探究乳酸链球菌肽(Nisin)、?-聚赖氨酸(?-polylysine,?-PL)和pH值对枯草芽孢杆菌的抑制效应,采用简单Logistic及多项式Logistic方程构建其生长/非生长界面模型,并对模型进行验证,比较分析抑菌因子间的协同或拮抗效应。结果表明,建立简单Logistic模型与多项式Logistic模型的R2-Nagelkerke值分别为0.79和0.91;Hosmer-Lemeshow测试分别为χ2=2.00、P=0.981(简单Logistic模型)和χ2=0.76、P=1(多项式Logistic模型),说明两种模型均能很好描述Nisin、?-PL、pH值及其交互作用下枯草芽孢杆菌生长/非生长情况(P<0.05),且多项式Logistic模型能更好预测枯草芽孢杆菌的生长概率。此外,Nisin、?-PL、pH值及其交互作用对虾源枯草芽孢杆菌生长/非生长界面影响显著(P<0.05)。随Nisin及?-PL质量浓度增加或pH值降低,生长区域逐渐减小,非生长区域逐渐扩大,枯草芽孢杆菌的生长受到抑制,当Nisin质量浓度增加,枯草芽孢杆菌的生长/非生长界限向更高?-PL质量浓度、更低pH值方向移动。无论第3种因子质量浓度为何值,当Nisin质量浓度为60、100、140、180 μg/mL时,枯草芽孢杆菌在pH值分别为4.0、4.25、4.5、5.0时表现为不生长。?-PL质量浓度为60、100、140、180 μg/mL时,枯草芽孢杆菌pH值为4.0、4.5、4.75、5.25时生长概率均为0。当pH<5.0时,枯草芽孢杆菌的生长受到较强抑制,此时pH值是影响枯草芽孢杆菌生长/非生长界限的主要因素。通过构建枯草芽孢杆菌生长/非生长概率模型,为定量描述水产品抑菌效应和风险评价提供一种有效手段。

关键词: 枯草芽孢杆菌;生长/非生长模型;Nisin;?-聚赖氨酸;抑菌效应;pH值

Abstract: The inactivation characteristics of nisin, ?-polylysine (?-PL) and pH on Bacillus subtilis isolated from vacuum packed cooked Penaeus vannamei were studied. Growth/no-growth interface models were fitted using simple Logistic and polynomial Logistic equations and validated, and the synergistic or antagonistic effects between the antibacterial factors were comparatively analyzed. The results showed that the R2-Nagelkerke values of the simple Logistic and the polynomial Logistic models were 0.79 and 0.91, respectively; the Hosmer-Lemeshow test showed χ2 of 2.00 and 0.76, and P of 0.981 and 1 for the simple and polynomial Logistic models, respectively, indicating that both models can well describe the growth/no-growth of B. subtilis under the influence of nisin, ?-PL, pH and their interactions, and that the polynomial Logistic model can better predict the probability of growth of the spores of B. subtilis. In addition, nisin, ?-polylysine, pH and their interactions had significant effects on the growth/no-growth interface of B. subtilis isolated from shrimp (P < 0.05). With increasing the concentration of nisin and ?-PL or decreasing the pH, the growth area gradually decreased, while the no-growth area gradually expanded, and the growth of B. subtilis was inhibited. As the nisin concentration increased, the growth/no-growth limit of B. subtilis shifted in the direction of higher ?-PL concentration and lower pH. Regardless of the concentration of ?-PL, when the nisin concentration was 60, 100, 140 or 180 μg/mL, B. subtilis showed no growth at pH values of 4.0, 4.25, 4.5, and 5.0. When the ?-PL concentration was 60, 100, 140 or 180 μg/mL, the growth probability of B. subtilis was zero at pH values of 4.0, 4.5, 4.75, and 5.25. At pH < 5.0, the growth of B. subtilis was strongly inhibited, and pH below 5.0 was a major factor affecting the growth/no-growth of B. subtilis. The growth/no-growth model predicting growth probability of B. subtilis can provide an effective means for quantitatively describing microbial inhibition on aquatic products and for microbial risk assessment.

Key words: Bacillus subtilis; growth/no-growth model; nisin; ?-polylysine; bacteriostatic effect; pH

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