Émile Sylvestre, William J. Rhoads, Timothy R. Julian, Frederik Hammes
{"title":"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","authors":"Émile Sylvestre, William J. Rhoads, Timothy R. Julian, Frederik Hammes","doi":"10.1101/2024.05.02.24306716","DOIUrl":null,"url":null,"abstract":"Quantitative polymerase chain reaction (qPCR) offers a rapid, automated, and potentially on-site method for quantifying <em>L. pneumophila</em> 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 <em>L. pneumophila</em> 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 <em>L. pneumophila</em> 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 <em>L. pneumphila</em> is applicable to other pathogens monitored in the environment.","PeriodicalId":501555,"journal":{"name":"medRxiv - Occupational and Environmental Health","volume":"29 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Quantification of Legionella pneumophila in building potable water systems: a meta-analysis comparing qPCR and culture-based detection methods\",\"authors\":\"Émile Sylvestre, William J. Rhoads, Timothy R. Julian, Frederik Hammes\",\"doi\":\"10.1101/2024.05.02.24306716\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Quantitative polymerase chain reaction (qPCR) offers a rapid, automated, and potentially on-site method for quantifying <em>L. pneumophila</em> 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 <em>L. pneumophila</em> 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 <em>L. pneumophila</em> 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 <em>L. pneumphila</em> is applicable to other pathogens monitored in the environment.\",\"PeriodicalId\":501555,\"journal\":{\"name\":\"medRxiv - Occupational and Environmental Health\",\"volume\":\"29 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-05-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"medRxiv - Occupational and Environmental Health\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1101/2024.05.02.24306716\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"medRxiv - Occupational and Environmental Health","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2024.05.02.24306716","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.