Real-time evaluation of signal accuracy in wastewater surveillance of pathogens with high rates of mutation
Authors: Thakali Ocean , Mercier Élisabeth , Eid Walaa , Wellman Martin , Brasset-Gorny Julia , Overton Alyssa K. , Knapp Jennifer J. , Manuel Douglas , Charles Trevor C. , Goodridge Lawrence , Arts Eric J. , Poon Art F. Y. , Brown R. Stephen , Graber Tyson E. , Delatolla Robert , DeGroot Christopher T. ,   Ontario Wastewater Surveillance Consortium, Adebiyi Adebowale , Advani Matthew , Agboola Simininuoluwa , Andino Dania , Aqeel Hussain , Badlani Yash , Bitter Lena Carolin , Bragg Leslie , Breadner Patrick , Bulir David , Chan Ronny , Channa Babneet , Charles Trevor , Chen JinJin , Corchis-Scott Ryland , Cranney Matthew , D’Aoust Patrick M. , Dang Hoang , Danna Nora , Dawe Rachel , de Melo Tomas , Desaulniers Jean-Paul , Dhiyebi Hadi , Donovan Justin , Edwards Elizabeth , Ellmen Isaac , Farah Joud Abu , Farahbakhsh Farnaz , Fuzzen Meghan , Garant Tim , Geng Qiudi , Gedge Ashley , Gere Alice , Gibson Richard , Gilbride Kimberly , Goitom Eyerusalem , Gong Qinyuan , Habash Marc , Hamilton Amanda , Haskell Blake , Hayat Samina , Hegazy Nada , Ho Hannifer , Hungwe Yemurayi , Ikert Heather , Islam Golam , Joseph Dilan , Khan Ismail , Kibbee Richard , Kirkwood Andrea , Knapp Jennifer , Knockleby James , Kwon Su-Hyun , Kyle Christopher , Lawal Opeyemi U. , Lomheim Line , McKay Robert Michael , Menon Ria , Miller Zach , Mloszewska Aleksandra M. , Mohammadiankia Ataollah , Naik Shiv , Nash Delaney , Ng Anthony , Olabode Abayomi , Örmeci Banu , Oswald Claire , Overton Alyssa , Pabon Gabriela Jimenez , Paramananthasivam Vinthiya , Pardy Jessica , Parreira Valeria R. , Payne Sarah Jane , Peng Hui , Pisharody Lakshmi , Prasla Samran , Precious Melinda , Rizvi Fozia , Santilli Matthew , Sarvi Hooman , Servos Mark , Siemon Dan , Simmons Denina , Sing-Judge Carly , Srikanthan Nivetha , Stephenson Sean , Sun Jianxian , Susilawati Endang , Tehrani Amir , Wan Shen , Wellman Martin , Williams Katie , Yang Ivy , Ybazeta Gustavo , Zeeb Eli 
Published: February 2024

AbstractWastewater surveillance of coronavirus disease 2019 (COVID-19) commonly applies reverse transcription-quantitative polymerase chain reaction (RT-qPCR) to quantify severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA concentrations in wastewater over time. In most applications worldwide, maximal sensitivity and specificity of RT-qPCR has been achieved, in part, by monitoring two or more genomic loci of SARS-CoV-2. In Ontario, Canada, the provincial Wastewater Surveillance Initiative reports the average copies of the CDC N1 and N2 loci normalized to the fecal biomarker pepper mild mottle virus. In November 2021, the emergence of the Omicron variant of concern, harboring a C28311T mutation within the CDC N1 probe region, challenged the accuracy of the consensus between the RT-qPCR measurements of the N1 and N2 loci of SARS-CoV-2. In this study, we developed and applied a novel real-time dual loci quality assurance and control framework based on the relative difference between the loci measurements to the City of Ottawa dataset to identify a loss of sensitivity of the N1 assay in the period from July 10, 2022 to January 31, 2023. Further analysis via sequencing and allele-specific RT-qPCR revealed a high proportion of mutations C28312T and A28330G during the study period, both in the City of Ottawa and across the province. It is hypothesized that nucleotide mutations in the probe region, especially A28330G, led to inefficient annealing, resulting in reduction in sensitivity and accuracy of the N1 assay. This study highlights the importance of implementing quality assurance and control criteria to continually evaluate, in near real-time, the accuracy of the signal produced in wastewater surveillance applications that rely on detection of pathogens whose genomes undergo high rates of mutation.