Quantitative SARS-CoV-2 Alpha Variant B.1.1.7 Tracking in Wastewater by Allele-Specific RT-qPCR

Wei Lin Lee; Maxim Imakaev; Federica Armas; Kyle A. McElroy; Xiaoqiong Gu; Claire Duvallet; Franciscus Chandra; Hongjie Chen; Mats Leifels; Samuel Mendola; Róisín Floyd-O'sullivan; Morgan M. Powell; Shane T. Wilson; Karl L.J. Berge; Claire Y.J. Lim; Fuqing Wu; Amy Xiao; Katya Moniz; Newsha Ghaeli; Mariana Matus; Janelle Thompson; Eric J. Alm

doi:10.1021/acs.estlett.1c00375

Quantitative SARS-CoV-2 Alpha Variant B.1.1.7 Tracking in Wastewater by Allele-Specific RT-qPCR

Wei Lin Lee, Maxim Imakaev, Federica Armas, Kyle A. McElroy, Xiaoqiong Gu, Claire Duvallet, Franciscus Chandra, Hongjie Chen, Mats Leifels, Samuel Mendola, Róisín Floyd-O'sullivan, Morgan M. Powell, Shane T. Wilson, Karl L.J. Berge, Claire Y.J. Lim, Fuqing Wu, Amy Xiao, Katya Moniz, Newsha Ghaeli, Mariana MatusJanelle Thompson^*, Eric J. Alm^*

^*Corresponding author for this work

Research output: Journal article (peer-reviewed) › Journal article

64 Citations (Scopus)

Abstract

The critical need for surveillance of SARS-CoV-2 variants of concern has prompted the development of methods that can track variants in wastewater. Here, we develop and present an open-source method based on allele-specific RT-qPCR (AS RT-qPCR) that detects and quantifies the B.1.1.7 variant, targeting spike protein mutations at three independent genomic loci that are highly predictive of B.1.1.7 (HV69/70del, Y144del, and A570D). Our assays can reliably detect and quantify low levels of B.1.1.7 with low cross-reactivity, and at variant proportions down to 1% in a background of mixed SARS-CoV-2. Applying our method to wastewater samples from the United States, we track the occurrence of B.1.1.7 over time in 19 communities. AS RT-qPCR results align with clinical trends, and summation of B.1.1.7 and wild-Type sequences quantified by our assays matches SARS-CoV-2 levels indicated by the U.S. CDC N1 and N2 assays. This work paves the way for AS RT-qPCR as a method for rapid inexpensive surveillance of SARS-CoV-2 variants in wastewater.

Original language	English
Pages (from-to)	675-682
Number of pages	8
Journal	Environmental Science and Technology Letters
Volume	8
Issue number	8
DOIs	https://doi.org/10.1021/acs.estlett.1c00375
Publication status	Published - 10 Aug 2021
Externally published	Yes

ASJC Scopus subject areas

Environmental Chemistry
Ecology
Water Science and Technology
Waste Management and Disposal
Pollution
Health, Toxicology and Mutagenesis

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10.1021/acs.estlett.1c00375

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Lee, W. L., Imakaev, M., Armas, F., McElroy, K. A., Gu, X., Duvallet, C., Chandra, F., Chen, H., Leifels, M., Mendola, S., Floyd-O'sullivan, R., Powell, M. M., Wilson, S. T., Berge, K. L. J., Lim, C. Y. J., Wu, F., Xiao, A., Moniz, K., Ghaeli, N., ... Alm, E. J. (2021). Quantitative SARS-CoV-2 Alpha Variant B.1.1.7 Tracking in Wastewater by Allele-Specific RT-qPCR. Environmental Science and Technology Letters, 8(8), 675-682. https://doi.org/10.1021/acs.estlett.1c00375

@article{ff731e5110e441efb9d9486bf7387f9f,

title = "Quantitative SARS-CoV-2 Alpha Variant B.1.1.7 Tracking in Wastewater by Allele-Specific RT-qPCR",

abstract = "The critical need for surveillance of SARS-CoV-2 variants of concern has prompted the development of methods that can track variants in wastewater. Here, we develop and present an open-source method based on allele-specific RT-qPCR (AS RT-qPCR) that detects and quantifies the B.1.1.7 variant, targeting spike protein mutations at three independent genomic loci that are highly predictive of B.1.1.7 (HV69/70del, Y144del, and A570D). Our assays can reliably detect and quantify low levels of B.1.1.7 with low cross-reactivity, and at variant proportions down to 1% in a background of mixed SARS-CoV-2. Applying our method to wastewater samples from the United States, we track the occurrence of B.1.1.7 over time in 19 communities. AS RT-qPCR results align with clinical trends, and summation of B.1.1.7 and wild-Type sequences quantified by our assays matches SARS-CoV-2 levels indicated by the U.S. CDC N1 and N2 assays. This work paves the way for AS RT-qPCR as a method for rapid inexpensive surveillance of SARS-CoV-2 variants in wastewater.",

author = "Lee, {Wei Lin} and Maxim Imakaev and Federica Armas and McElroy, {Kyle A.} and Xiaoqiong Gu and Claire Duvallet and Franciscus Chandra and Hongjie Chen and Mats Leifels and Samuel Mendola and R{\'o}is{\'i}n Floyd-O'sullivan and Powell, {Morgan M.} and Wilson, {Shane T.} and Berge, {Karl L.J.} and Lim, {Claire Y.J.} and Fuqing Wu and Amy Xiao and Katya Moniz and Newsha Ghaeli and Mariana Matus and Janelle Thompson and Alm, {Eric J.}",

note = "Publisher Copyright: {\textcopyright} ",

year = "2021",

month = aug,

day = "10",

doi = "10.1021/acs.estlett.1c00375",

language = "English",

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Lee, WL, Imakaev, M, Armas, F, McElroy, KA, Gu, X, Duvallet, C, Chandra, F, Chen, H, Leifels, M, Mendola, S, Floyd-O'sullivan, R, Powell, MM, Wilson, ST, Berge, KLJ, Lim, CYJ, Wu, F, Xiao, A, Moniz, K, Ghaeli, N, Matus, M, Thompson, J & Alm, EJ 2021, 'Quantitative SARS-CoV-2 Alpha Variant B.1.1.7 Tracking in Wastewater by Allele-Specific RT-qPCR', Environmental Science and Technology Letters, vol. 8, no. 8, pp. 675-682. https://doi.org/10.1021/acs.estlett.1c00375

TY - JOUR

T1 - Quantitative SARS-CoV-2 Alpha Variant B.1.1.7 Tracking in Wastewater by Allele-Specific RT-qPCR

AU - Lee, Wei Lin

AU - Imakaev, Maxim

AU - Armas, Federica

AU - McElroy, Kyle A.

AU - Gu, Xiaoqiong

AU - Duvallet, Claire

AU - Chandra, Franciscus

AU - Chen, Hongjie

AU - Leifels, Mats

AU - Mendola, Samuel

AU - Floyd-O'sullivan, Róisín

AU - Powell, Morgan M.

AU - Wilson, Shane T.

AU - Berge, Karl L.J.

AU - Lim, Claire Y.J.

AU - Wu, Fuqing

AU - Xiao, Amy

AU - Moniz, Katya

AU - Ghaeli, Newsha

AU - Matus, Mariana

AU - Thompson, Janelle

AU - Alm, Eric J.

PY - 2021/8/10

Y1 - 2021/8/10

N2 - The critical need for surveillance of SARS-CoV-2 variants of concern has prompted the development of methods that can track variants in wastewater. Here, we develop and present an open-source method based on allele-specific RT-qPCR (AS RT-qPCR) that detects and quantifies the B.1.1.7 variant, targeting spike protein mutations at three independent genomic loci that are highly predictive of B.1.1.7 (HV69/70del, Y144del, and A570D). Our assays can reliably detect and quantify low levels of B.1.1.7 with low cross-reactivity, and at variant proportions down to 1% in a background of mixed SARS-CoV-2. Applying our method to wastewater samples from the United States, we track the occurrence of B.1.1.7 over time in 19 communities. AS RT-qPCR results align with clinical trends, and summation of B.1.1.7 and wild-Type sequences quantified by our assays matches SARS-CoV-2 levels indicated by the U.S. CDC N1 and N2 assays. This work paves the way for AS RT-qPCR as a method for rapid inexpensive surveillance of SARS-CoV-2 variants in wastewater.

AB - The critical need for surveillance of SARS-CoV-2 variants of concern has prompted the development of methods that can track variants in wastewater. Here, we develop and present an open-source method based on allele-specific RT-qPCR (AS RT-qPCR) that detects and quantifies the B.1.1.7 variant, targeting spike protein mutations at three independent genomic loci that are highly predictive of B.1.1.7 (HV69/70del, Y144del, and A570D). Our assays can reliably detect and quantify low levels of B.1.1.7 with low cross-reactivity, and at variant proportions down to 1% in a background of mixed SARS-CoV-2. Applying our method to wastewater samples from the United States, we track the occurrence of B.1.1.7 over time in 19 communities. AS RT-qPCR results align with clinical trends, and summation of B.1.1.7 and wild-Type sequences quantified by our assays matches SARS-CoV-2 levels indicated by the U.S. CDC N1 and N2 assays. This work paves the way for AS RT-qPCR as a method for rapid inexpensive surveillance of SARS-CoV-2 variants in wastewater.

UR - http://www.scopus.com/inward/record.url?scp=85111508893&partnerID=8YFLogxK

U2 - 10.1021/acs.estlett.1c00375

DO - 10.1021/acs.estlett.1c00375

M3 - Journal article

AN - SCOPUS:85111508893

SN - 2328-8930

VL - 8

SP - 675

EP - 682

JO - Environmental Science and Technology Letters

JF - Environmental Science and Technology Letters

IS - 8

ER -

Quantitative SARS-CoV-2 Alpha Variant B.1.1.7 Tracking in Wastewater by Allele-Specific RT-qPCR

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