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

69 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

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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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",

volume = "8",

pages = "675--682",

journal = "Environmental Science and Technology Letters",

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publisher = "American Chemical Society",

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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 - https://www.scopus.com/pages/publications/85111508893

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

Abstract

ASJC Scopus subject areas

UN SDGs

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