食品科学 ›› 2018, Vol. 39 ›› Issue (23): 1-6.doi: 10.7506/spkx1002-6630-201823001

• 基础研究 •    下一篇

低温条件下即食虾中单增李斯特菌与副溶血性弧菌共存分子预测模型的建立

牛 犇1,穆丽丽1,张昭寰1,刘海泉1,2,3,4,潘迎捷1,2,3,赵 勇1,2,3,*   

  1. 1.上海海洋大学食品学院,上海 201306;2.农业部水产品贮藏保鲜质量安全风险评估实验室,上海 201306;3.上海水产品加工及贮藏工程技术研究中心,上海 201306;4.上海海洋大学食品热加工工程技术研究中心,上海 201306
  • 出版日期:2018-12-15 发布日期:2018-12-17
  • 基金资助:
    国家自然科学基金面上项目(31571917;31671779);上海市科技兴农推广项目(沪农科推字2017第4-4号20170404;沪农科攻字2015第4-8号20150408);上海市教育委员会科研创新计划资助项目(2017-01-07-00-10-E00056)

Development of Predictive Models Based on qPCR for the Growth of Listeria monocytogenes and Vibrio parahaemolyticus Coexisting on Cooked Shrimps Stored at Low Temperatures

NIU Ben1, MU Lili1, ZHANG Zhaohuan1, LIU Haiquan1,2,3,4, PAN Yingjie1,2,3, ZHAO Yong1,2,3,*   

  1. 1. College of Food Science and Technology, Shanghai Ocean University, Shanghai 201306, China; 2. Laboratory of Quality and Safety Risk Assessment for Aquatic Product on Storage and Preservation (Shanghai), Ministry of Agriculture, Shanghai 201306, China; 3. Shanghai Engineering Research Center of Aquatic-Product Processing and Preservation, Shanghai 201306, China; 4. Engineering Research Center of Food Thermal-Processing Technology, Shanghai Ocean University, Shanghai 201306, China
  • Online:2018-12-15 Published:2018-12-17

摘要: 本研究旨在应用实时荧光定量聚合酶链式反应(quantitative real-time polymerase chain reaction,qPCR)技术描述即食虾中的单增李斯特菌与副溶血性弧菌的生长行为,构建混菌模式下的分子预测模型。将单增李斯特菌与副溶血性弧菌等量((5.0±0.5)(lg(CFU/g)))混合接种于即食虾中,置于低温环境(4 ℃和10 ℃)下培养,并利用qPCR定量检测单增李斯特菌与副溶血性弧菌数量的动态变化。运用生长模型(修正Gompertz、Logistic、Baranyi)和失活模型(Log-linear、Weibull)分别拟合两株菌的生长和失活趋势。结果表明:低温条件下,修正Gompertz、Logistic和Baranyi模型均可成功拟合单增李斯特菌的生长曲线,其决定系数(R2)均大于0.98。对于副溶血性弧菌,在4 ℃条件下,Log-linear和Weibull模型能够清晰地描述其失活情况,R2分别为0.950和0.945;而10 ℃条件下,2 个失活模型均难以描述其行为变化,R2仅为0.784和0.775。本研究运用分子生物学技术描述即食虾中两种致病菌混合培养的菌量变化,探究混菌模式下微生物的生长失活情况,为分子预测模型的进一步研究提供了新的思路。

关键词: 混菌, 实时荧光定量聚合酶链式反应, 分子预测模型, 副溶血性弧菌, 单增李斯特菌, 即食虾

Abstract: The aim of this study was to develop predictive models based on quantitative real-time polymerase chain reaction (qPCR) for describing the growth of Listeria monocytogenes and Vibrio parahaemolyticus co-cultured on cooked shrimps. The strains were inoculated at the same level ((5.0 ± 0.5) (lg(CFU/g))) and cultured at low temperatures (4 and 10 ℃), and then the dynamic changes in microbial load were detected by qPCR. Three growth curve models, modified Gompertz, Logistic and Baranyi were fitted for each of the strains as well as two inactivation curve models, Log-linear and Weibull. The results showed that the modified Gompertz, Logistic and Baranyi models could successfully describe the growth curve of L. monocytogenes at low temperatures, with a coefficient of determination (R2) greater than 0.98. The inactivation of V. parahaemolyticus at 4 ℃ could be clearly described by the Log-linear and Weibull models, with R2 of 0.950 and 0.945, respectively; however, the inactivation models failed to describe the behavior changes at 10 ℃, with R2 of only 0.784 and 0.775, respectively. The results from this study provide a new clue for growth modelling of food-borne pathogens based on molecular biological techniques.

Key words: mixed bacteria, quantitative real-time polymerase chain reaction, predictive models, Listeria monocytogenes, Vibrio parahaemolyticus, cooked shrimp

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