Innovative New Way To Detect the SARS-CoV-2 Alpha Variant in Wastewater

SMART AMR researchers Wei Lin Lee (left), Xiaoqiong Gu (center), and Federica Armas evaluate a 384-well plate set up for variant detection assays. Credit: Photo Courtesy of SMART

SMART researchers have developed an innovative method to detect and quantify the concern B.1.1.7 (Alpha) variant through wastewater epidemiology.

Researchers from the Antimicrobial Resistance (AMR) interdisciplinary research group of the Singapore-MIT Alliance for Research and Technology (SMART), MIT’s Singapore research firm, together with collaborators from Biobot Analytics, Nanyang Technological University (NTU) and MIT, have successfully developed a innovative, open-source molecular detection method that can detect and quantify the B.1.1.7 (Alpha) variant of SARS-CoV-2. The breakthrough paves the way for rapid, low-cost monitoring of other SARS-CoV-2 variants in wastewater.

As the world continues to struggle and contain Covid-19, the recent identification of SARS-CoV-2 variants with higher transmissibility and increased severity has made developing convenient methods for variant tracking essential. Currently, among the identified variants are the B.1.17 (Alpha) variant first identified in the UK and the B.1.617.2 (Delta) variant first detected in India.

SMART AMR researchers Franciscus Chandra (left) and Hongjie Chen (right) evaluate wastewater samples used to validate the variant test. Credit: Photo Courtesy of SMART

Wastewater monitoring has emerged as a critical public health tool to monitor the SARS-CoV-2 pandemic safely and efficiently in a non-intrusive manner, providing additional information that enables health authorities to obtain actionable information at the community level . Recently, viral fragments of SARS-CoV-2 were detected in residential areas in Singapore through a proactive wastewater monitoring program. This information, in addition to surveillance testing, enabled the Singapore Ministry of Health to respond quickly, isolating and testing swabs as part of precautionary measures.

However, detecting variants through wastewater monitoring is less common due to challenges in existing technology. The next generation of sequencing for wastewater monitoring is time consuming and expensive. Tests also lack the sensitivity needed to detect low variant abundances in diluted and mixed wastewater samples due to inconsistent and/or low sequence coverage.

The method developed by the researchers is uniquely tailored to address these challenges and extends the utility of wastewater monitoring beyond testing for SARS-CoV-2, toward tracking the spread of SARS-CoV-2. variants of care.

Wei Lin Lee, research scientist at SMART AMR and lead author of the paper, adds: “This is especially important in countries battling SARS-CoV-2 variants. Wastewater monitoring will help to find out the true share and distribution of the variants in the local communities. Our method is sensitive enough to detect variants in highly diluted SARS-CoV-2 concentrations typically seen in wastewater samples, and provides reliable results even for samples containing multiple SARS-CoV-2 lines.”

Led by Janelle Thompson, associate professor of NTU, and Eric Alm, MIT professor and principal investigator of SMART AMR, the team’s study, “Quantitative SARS-CoV-2 Alpha variant B.1.1.7 Tracking in wastewater by allelic- specific RT-qPCR” is published in Environmental Science & Technology Letters. The study explains the innovative, open-source molecular detection method based on allele-specific RT-qPCR that detects and quantifies the B.1.1.7 (Alpha) variant. The test developed, tested and validated in wastewater samples in 19 communities in the United States, is able to reliably detect and quantify low levels of the B.1.1.7 (Alpha) variant with low cross-reactivity and at variant ratios up to 1 percent on a background of mixed SARS-CoV-2 viruses.

SMART AMR researchers Karl Berge (left) and Claire Lim set up variant detection assays on a 384-well plate. Credit: Photo Courtesy of SMART

The method targets spike protein mutations that are highly predictive of the B.1.1.7 (Alpha) variant and can be implemented using commercially available RT-qPCR protocols. Unlike commercially available products that use proprietary primers and probes for wastewater monitoring, the document describes the open source method and its development that can be freely used by other organizations and research institutes for their work on wastewater monitoring of SARS-CoV-2 and its variants. .

The Singapore research team’s breakthrough is currently being used by Biobot Analytics, an MIT startup and global leader in wastewater epidemiology headquartered in Cambridge, Massachusetts, for states and cities across the United States. Using the method, Biobot Analytics can accept and analyze wastewater samples for the B.1.1.7 (Alpha) variant and plans to add additional variants to the analysis as the methods are developed. For example, the SMART AMR team is currently developing specific tests that can detect and quantify the B.1.617.2 (Delta) variant, which was recently identified as a variant of concern by the World Health Organization.

“Using the team’s innovative methodology, we have been able to track the B.1.1.7 (Alpha) variant in the US local population, enabling leaders to learn about Covid-19 trends in their communities and make them informed recommendations and changes in controls,” said Mariana Matus PhD ’18, CEO and co-founder of Biobot Analytics.

“This method can be quickly adapted to detect new variants of concern beyond B.1.1.7,” added Alm of MIT. “Our partnership with Biobot Analytics has translated our research into the real-world impacts off Singapore’s shores, aiding in the detection of Covid-19 and its variants, serving as an early warning system and guiding policy makers in detecting infection clusters. and considering appropriate public health measures.”

Reference: “Quantitative SARS-CoV-2 Alpha Variant B.1.1.7 Tracking in Wastewater by Allele-Specific RT-qPCR” by 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 LJ Berge, Claire YJ Lim, Fuqing Wu, Amy Xiao, Katya Moniz, Newsha Ghaeli, Mariana Matus , Janelle Thompson and Eric J. Alm, July 18, 2021, Environmental Science & Technology Letters.
DOI: 10.1021/acs.estlett.1c00375

The research is conducted by SMART and supported by the National Research Foundation (NRF) Singapore as part of its Campus for Research Excellence And Technological Enterprise (CREATE) program.

SMART was founded in 2007 by MIT in partnership with the National Research Foundation of Singapore (NRF). SMART is the first entity in CREATE developed by NRF. SMART serves as an intellectual and innovation center for research interactions between MIT and Singapore and conducts pioneering research projects in areas of interest to both Singapore and MIT. SMART currently consists of an Innovation Center and five IRGs: AMR, Critical Analytics for Manufacturing Personalized-Medicine, Disruptive and Sustainable Technologies for Agricultural Precision, Future Urban Mobility and Low Energy Electronic Systems.

The interdisciplinary research group AMR is a translational research and entrepreneurship program addressing the growing threat of antimicrobial resistance. Leveraging talent and convergent technologies in Singapore and MIT, AMR aims to develop multiple innovative and disruptive approaches to identify, respond to and treat drug-resistant microbial infections. Through strong scientific and clinical collaborations, the goal is to provide transformative, holistic solutions for Singapore and the world.