Novel dPCR-Based Approach for SARS-CoV-2 Variant Detection and Monitoring in Wastewater: A Multi-State Comparison with Clinical Genotyping and GISAID Sequencing Data

Abstract Wastewater testing has emerged as an effective tool for monitoring levels of SARS-CoV-2 infection in sewered communities. As of July 2024, PCR-based methods continue to be the most widely used methods in wastewater surveillance (1–3). Data from PCR-based wastewater testing is usually available to public health authorities in near real time, typically within 5 to 7 days after waste enters the sewer (4,5). Unfortunately, while these methods can accurately detect and quantify SARS-CoV-2, they are not usually used to differentiate between the multitude of variants, including variants that are classified as Variants of High Consequence (VOHC) and Variants of Concern (VOC) (6). Currently, to identify these variants, the extracted nucleic acids must be analyzed using resource-intensive sequencing-based methods. Moreover, not every lab has access to sequencing technology, so availability of equipment and expertise is also a roadblock besides These costly and time-consuming sequencing methods, while informative, diminish some of the early warning benefits provided by wastewater surveillance. Moreover, not every lab has access to sequencing technology, creating additional barriers due to the availability of equipment and expertise. In response to these analytical shortcomings, we developed and assessed an alternative approach for variant monitoring in wastewater using customizable dPCR-based genotyping assays. This approach is an expansion from a previously described method for analyzing clinical samples utilizing customizable qPCR-based genotyping. Relative to sequencing, this approach is cost-effective, fast, and easily implemented. We combined the dPCR-based wastewater genotyping approach along with the well-established Nanotrap Ⓡ Particles virus concentration method as part of a wastewater processing protocol to perform SARS-CoV-2 genotyping in five wastewater testing labs across multiple regions in the United States. The results for the wastewater genotyping approach are displayed on a public-facing dashboard alongside clinical genotyping results and GISAID data (see https://tracker.rosalind.bio ). Despite conducting genotyping on fewer wastewater samples than clinical samples, our approach effectively detected signals of emerging variants and trends in SARS-CoV-2 variants within the community, similar to clinical analyses. For instance, in Georgia, the rapid rise and dominance of the Unknown and BA.2.86*/JN* variants in early 2024 were consistently observed in wastewater samples and closely matched trends in the GISAID clinical sequencing database. Similarly, the EG.5* and FL* variants showed elevated signals in wastewater before clinical detection, highlighting the early warning potential of wastewater testing. Detailed analysis of multiple datasets from various states revealed consistency in the rise and fall of variants across wastewater genotyping, clinical genotyping, and GISAID data. This consistency demonstrates that the prevalence of variants in wastewater closely matches that in clinical settings, underscoring the capability of wastewater-based surveillance to provide extended monitoring of circulating variants, often preceding clinical detections by several weeks. We further assessed the wastewater genotyping approach by calculating positive percent agreement for detection of four variants (JN, EG.5, FL, and XBB) between the genotyping results and whole genome sequencing results for a set of 129 matched samples that were analyzed using both methods. The agreement ranged between 54% agreement for FL to 97% agreement for JN, with an average of 76% agreement across all samples for all four variants. Additionally, we estimate that collecting and analyzing data using the dPCR genotyping method is significantly less expensive and time-consuming compared to next-generation sequencing. Labs that outsource next-generation sequencing face much higher costs and longer delays. Transitioning to multiplex dPCR for variant detection could further reduce both cost and turnaround time. Finally, we discuss the challenges and lessons learned in the development, validation, and implementation of dPCR-based wastewater genotyping. These findings support the use of wastewater-based surveillance as a complementary approach to clinical surveillance, offering a broader and more inclusive picture of variant prevalence and transmission in the community.