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

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

33 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 languageEnglish
Pages (from-to)675-682
Number of pages8
JournalEnvironmental Science and Technology Letters
Volume8
Issue number8
DOIs
Publication statusPublished - 10 Aug 2021
Externally publishedYes

ASJC Scopus subject areas

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

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