André Vinicius Costa Ribeiro, Camille Ferreira Mannarino, Shênia Patrícia Corrêa Novo, Tatiana Prado, André Lermontov, Bruna Barbosa de Paula, Tulio Machado Fumian, Marize Pereira Miagostovich
{"title":"Assessment of crAssphage as a biological variable for SARS-CoV-2 data normalization in wastewater surveillance.","authors":"André Vinicius Costa Ribeiro, Camille Ferreira Mannarino, Shênia Patrícia Corrêa Novo, Tatiana Prado, André Lermontov, Bruna Barbosa de Paula, Tulio Machado Fumian, Marize Pereira Miagostovich","doi":"10.1093/jambio/lxae177","DOIUrl":null,"url":null,"abstract":"<p><strong>Aims: </strong>This study aimed to assess the use of cross-assembled phage (crAssphage) as an endogenous control employing a multivariate normalization analysis and its application as a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) data normalizer.</p><p><strong>Methods and results: </strong>A total of 188 twelve-hour composite raw sewage samples were obtained from eight wastewater treatment plants (WWTP) during a 1-year monitoring period. Employing the N1 and N2 target regions, SARS-CoV-2 RNA was detected in 94% (177) and 90% (170) of the samples, respectively, with a global median of 5 log10 genomic copies per liter (GC l-1). CrAssphage was detected in 100% of the samples, ranging from 8.29 to 10.43 log10 GC l-1, with a median of 9.46 ± 0.40 log10 GC l-1, presenting both spatial and temporal variabilities.</p><p><strong>Conclusions: </strong>Although SARS-CoV-2 data normalization employing crAssphage revealed a correlation with clinical cases occurring during the study period, crAssphage normalization by the flow per capita per day of each WWTP increased this correlation, corroborating the importance of normalizing wastewater surveillance data in disease trend monitoring.</p>","PeriodicalId":15036,"journal":{"name":"Journal of Applied Microbiology","volume":" ","pages":""},"PeriodicalIF":3.2000,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Applied Microbiology","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1093/jambio/lxae177","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOTECHNOLOGY & APPLIED MICROBIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Aims: This study aimed to assess the use of cross-assembled phage (crAssphage) as an endogenous control employing a multivariate normalization analysis and its application as a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) data normalizer.
Methods and results: A total of 188 twelve-hour composite raw sewage samples were obtained from eight wastewater treatment plants (WWTP) during a 1-year monitoring period. Employing the N1 and N2 target regions, SARS-CoV-2 RNA was detected in 94% (177) and 90% (170) of the samples, respectively, with a global median of 5 log10 genomic copies per liter (GC l-1). CrAssphage was detected in 100% of the samples, ranging from 8.29 to 10.43 log10 GC l-1, with a median of 9.46 ± 0.40 log10 GC l-1, presenting both spatial and temporal variabilities.
Conclusions: Although SARS-CoV-2 data normalization employing crAssphage revealed a correlation with clinical cases occurring during the study period, crAssphage normalization by the flow per capita per day of each WWTP increased this correlation, corroborating the importance of normalizing wastewater surveillance data in disease trend monitoring.
期刊介绍:
Journal of & Letters in Applied Microbiology are two of the flagship research journals of the Society for Applied Microbiology (SfAM). For more than 75 years they have been publishing top quality research and reviews in the broad field of applied microbiology. The journals are provided to all SfAM members as well as having a global online readership totalling more than 500,000 downloads per year in more than 200 countries. Submitting authors can expect fast decision and publication times, averaging 33 days to first decision and 34 days from acceptance to online publication. There are no page charges.