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Updated: Jul 6, 2025
Quantification and Whole Genome Characterization of SARS-CoV-2 RNA in Wastewater and Air Samples
Published on: June 30, 2023
Spike-Seq: An amplicon-based high-throughput sequencing approach for the sensitive detection and characterization of
Panagiotis G Adamopoulos1, Marios A Diamantopoulos1, Michaela A Boti1
1Department of Biochemistry and Molecular Biology, Faculty of Biology, National and Kapodistrian University of Athens, Athens, Greece.
Abstract:
Ever since the outbreak of COVID-19 disease in Wuhan, China, different variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been identified. Wastewater-based epidemiology (WBE), an approach that has been successfully applied in numerous case studies worldwide, offers a cost-effective and rapid way for monitoring trends of SARS-Cov-2 in the community level without selection bias. Despite being a gold-standard procedure, WBE is a challenging approach due to the sample instability and the moderate efficiency of SARS-CoV-2 concentration in wastewater. In the present study, we introduce Spike-Seq, a custom amplicon-based approach for the S gene sequencing of SARS-CoV-2 in wastewater samples, which enables not only the accurate identification of the existing Spike-related genetic markers, but also the estimation of their frequency in the investigated samples. The implementation of Spike-Seq involves the combination of nested PCR-based assays that efficiently amplify the entire nucleotide sequence of the S gene and next-generation sequencing, which enables the variant detection and the estimation of their frequency. In the framework of the current work, Spike-Seq was performed to investigate the mutational profile of SARS-CoV-2 in samples from the Wastewater Treatment Plant (WWTP) of Athens, Greece, which originated from multiple timepoints, ranging from March 2021 until July 2022. Our findings demonstrate that Spike-Seq efficiently detected major genetic markers of B.1.1.7 (Alpha), B.1.617.2 (Delta) as well as B.1.1.529 (Omicron) variants in wastewater samples and provided their frequency levels, showing similar variant distributions with the published clinical data from the National Public Health organization. The presented approach can prove to be a useful tool for the detection of SARS-CoV-2 in challenging wastewater samples and the identification of the existing genetic variants of S gene.
