Quantitative SARS-CoV-2 Alpha Variant B.1.1.7 Tracking in Wastewater by Allele-Specific RT-qPCR
Author(s)
Lee, Wei Lin; Imakaev, Maxim; Armas, Federica; McElroy, Kyle A.; Gu, Xiaoqiong; Duvallet, Claire; Chandra, Franciscus; Chen, Hongjie; Leifels, Mats; Mendola, Samuel; Floyd-O’Sullivan, Róisín; Powell, Morgan M.; Wilson, Shane T.; Berge, Karl L. J.; Lim, Claire Y. J.; Wu, Fuqing; Xiao, Amy; Moniz, Katya H; Ghaeli, Newsha; Matus, Mariana; Thompson, Janelle; Alm, Eric J.; ... Show more Show less
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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.
Date issued
2021-07Department
Massachusetts Institute of Technology. Center for Microbiome Informatics and Therapeutics; Massachusetts Institute of Technology. Department of Biological Engineering; Singapore-MIT Alliance in Research and Technology (SMART)Journal
Environmental Science & Technology Letters
Publisher
American Chemical Society (ACS)
Citation
Lee, Wei Lin et al. "Quantitative SARS-CoV-2 Alpha Variant B.1.1.7 Tracking in Wastewater by Allele-Specific RT-qPCR." Environmental Science & Technology Letters (July 2021): dx.doi.org/10.1021/acs.estlett.1c00375. © 2021 The Authors
Version: Final published version
ISSN
2328-8930
2328-8930