Quantitative SARS-CoV-2 alpha variant B.1.1.7 tracking in wastewater by allele-specific RT-qPCR

• Main Authors: 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, Ghaeli, Newsha, Matus, Mariana, Thompson, Janelle R., Alm, Eric J.
• Other Authors: Asian School of the Environment
• Format: Article
• Language: English
• Published: 2022
• Subjects: Engineering::Environmental engineering; DNA; Amplification
• Online Access: https://hdl.handle.net/10356/159844
• Institution: Nanyang Technological University

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.