Laboratory of Food Quality Control and Hygiene, Department of Food Science and Human Nutrition, Agricultural University of Athens, Athens, Greece.
Food Microbiol. 2013 Dec;36(2):395-405. doi: 10.1016/j.fm.2013.06.020. Epub 2013 Jul 16.
Listeria monocytogenes poses a serious threat to public health, and the majority of cases of human listeriosis are associated with contaminated food. Reliable microbiological testing is needed for effective pathogen control by food industry and competent authorities. The aims of this work were to estimate the prevalence and concentration of L. monocytogenes in minced pork meat by the application of a Bayesian modeling approach, and also to determine the performance of three culture media commonly used for detecting L. monocytogenes in foods from a deterministic and stochastic perspective. Samples (n = 100) collected from local markets were tested for L. monocytogenes using in parallel the PALCAM, ALOA and RAPID'L.mono selective media according to ISO 11290-1:1996 and 11290-2:1998 methods. Presence of the pathogen was confirmed by conducting biochemical and molecular tests. Independent experiments (n = 10) for model validation purposes were performed. Performance attributes were calculated from the presence-absence microbiological test results by combining the results obtained from the culture media and confirmative tests. Dirichlet distribution, the multivariate expression of a Beta distribution, was used to analyze the performance data from a stochastic perspective. No L. monocytogenes was enumerated by direct-plating (<10 CFU/g), though the pathogen was detected in 22% of the samples. L. monocytogenes concentration was estimated at 14-17 CFU/kg. Validation showed good agreement between observed and predicted prevalence (error = -2.17%). The results showed that all media were best at ruling in L. monocytogenes presence than ruling it out. Sensitivity and specificity varied depending on the culture-dependent method. None of the culture media was perfect in detecting L. monocytogenes in minced pork meat alone. The use of at least two culture media in parallel enhanced the efficiency of L. monocytogenes detection. Bayesian modeling may reduce the time needed to draw conclusions regarding L. monocytogenes presence and the uncertainty of the results obtained. Furthermore, the problem of observing zero counts may be overcome by applying Bayesian analysis, making the determination of a test performance feasible.
单增李斯特菌对公共卫生构成严重威胁，大多数人类李斯特菌病病例与污染食物有关。食品行业和主管部门需要进行可靠的微生物检测，以有效控制病原体。本工作的目的是应用贝叶斯建模方法估计碎猪肉中单增李斯特菌的流行率和浓度，并从确定性和随机性的角度确定三种常用食品中单增李斯特菌检测培养基的性能。根据 ISO 11290-1:1996 和 11290-2:1998 方法，使用 PALCAM、ALOA 和 RAPID'L.mono 选择性培养基同时平行测试从当地市场采集的 100 个样本中是否存在李斯特菌。通过进行生化和分子测试来确认病原体的存在。为了验证模型的目的，进行了独立的实验（n = 10）。从存在-不存在微生物测试结果中计算性能属性，将从培养基和确认测试中获得的结果结合起来。从随机角度分析性能数据使用 Dirichlet 分布，即 Beta 分布的多元表达。没有通过直接平板计数（<10 CFU/g）计数到单增李斯特菌，但在 22%的样本中检测到该病原体。估计单增李斯特菌浓度为 14-17 CFU/kg。验证表明，观察到的和预测的流行率之间存在良好的一致性（误差=-2.17%）。结果表明，所有培养基在判断李斯特菌存在方面都优于判断其不存在。灵敏度和特异性取决于依赖培养的方法。单独使用任何一种培养基都无法完美检测碎猪肉中的单增李斯特菌。平行使用至少两种培养基可提高李斯特菌检测效率。贝叶斯建模可以减少得出有关单增李斯特菌存在的结论所需的时间和结果的不确定性。此外，通过应用贝叶斯分析，可以克服观察到零计数的问题，从而使测试性能的确定成为可能。
