建筑饮用水系统中嗜肺军团菌的定量分析:比较 qPCR 和基于培养的检测方法的荟萃分析

Émile Sylvestre, William J. Rhoads, Timothy R. Julian, Frederik Hammes
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引用次数: 0

摘要

定量聚合酶链式反应 (qPCR) 提供了一种快速、自动化和潜在的现场方法,用于定量检测建筑饮用水系统中的嗜肺病毒,补充并有可能取代传统的基于培养的技术。然而,qPCR 在评估人类健康风险方面的应用却很复杂,因为它容易高估风险,因为它检测到的基因组拷贝与有活力的传染性细菌并不相符。本研究探讨了通过 qPCR 和基于培养的方法获得的嗜肺病毒测量值之间的关系,旨在了解和确定相关健康风险所需的 qPCR 与培养浓度比。我们建立了泊松对数正态比率模型和随机效应荟萃分析,以分析不同地点内和不同地点间 qPCR 与培养物比率的差异。我们的研究结果表明,这些比率通常从 1:1 到 100:1 不等,所有地点的预测比率都接近 1:1。因此,采用默认的 1:1 转换系数似乎是必要的,这是一种谨慎的方法,可将 qPCR 浓度转换为可培养浓度,用于相关健康风险模型,例如通过定量微生物风险评估 (QMRA) 框架。在这种方法过于保守的情况下,有针对性的采样和活力 qPCR 的应用可提高基于 qPCR 的 QMRA 的准确性。将 qPCR 和基于培养的方法标准化,并报告影响嗜肺菌培养能力的特定地点环境因素,将有助于更好地理解这两种方法之间的关系。本文介绍的比率模型使我们超越了简单的相关性分析,有助于研究这两种方法在时间和空间上的异质性。这项分析是 QMRA 与分子生物学结合的一个进步,因为这里针对嗜肺菌展示的框架适用于环境中监测到的其他病原体。
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Quantification of Legionella pneumophila in building potable water systems: a meta-analysis comparing qPCR and culture-based detection methods
Quantitative polymerase chain reaction (qPCR) offers a rapid, automated, and potentially on-site method for quantifying L. pneumophila in building potable water systems, complementing and potentially replacing traditional culture-based techniques. However, the application of qPCR in assessing human health risks is complicated by its tendency to overestimate such risks due to the detection of genomic copies that do not correspond to viable, infectious bacteria. This study examines the relationship between L. pneumophila measurements obtained via qPCR and culture-based methods, aiming to understand and establish qPCR-to-culture concentration ratios needed to inform associated health risks. We developed a Poisson lognormal ratio model and a random-effects meta-analysis to analyze variations in qPCR-to-culture ratios within and across sites. Our findings indicate these ratios typically vary from 1:1 to 100:1, with ratios close to 1:1 predicted at all sites. Consequently, adopting a default 1:1 conversion factor appears necessary as a cautious approach to convert qPCR concentrations to culturable concentrations for use in models of associated health risks, for example, through quantitative microbial risk assessment (QMRA) frameworks. Where this approach may be too conservative, targeted sampling and the applications of viability-qPCR could improve the accuracy of qPCR-based QMRA. Standardizing qPCR and culture-based methods and reporting site-specific environmental factors that affect the culturability of L. pneumophila would improve the understanding of the relationship between the two methods. The ratio model introduced here shifts us beyond simple correlation analyses, facilitating investigations of temporal and spatial heterogeneities in the relationship. This analysis is a step forward in the integration of QMRA and molecular biology, as the framework demonstrated here for L. pneumphila is applicable to other pathogens monitored in the environment.
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