Large-scale wastewater surveillance can be used to help communities monitor infection dynamics for SARS-CoV-2. Wide-spread implementation of wastewater surveillance has been stymied by lack of a robust, high-throughput viral concentration method. In this webinar, researchers from University of California San Diego will discuss an automated method using affinity-capture magnetic hydrogel particles, followed by RNA extraction, RT-qPCR and sequencing. All steps from concentration to RT-qPCR plating are performed hands-free and conducted by liquid-handling robots, enabling the processing of 96 raw sewage samples in just 4.5 hours (concentration to RT-qPCR detection/quantification), effectively reducing the processing time by at least 20-fold. The high-throughput method has higher recovery efficiencies than conventionally used methods for viral wastewater concentration and can enable the processing of over 100 wastewater samples in a day. Using the high-throughput pipeline, samples from the influent stream of the primary wastewater treatment plant of San Diego County (serving 2.3 million residents) were processed for a period of 13 weeks. Wastewater estimates of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral genome copies in raw untreated wastewater correlated strongly with clinically reported cases by the county, and when used alongside past reported case numbers and temporal information in an autoregressive integrated moving average model, enabled prediction of new reported cases up to 3 weeks in advance. On campus, the high-throughput method has been used to process over 9,500 samples from 121 samplers covering 350 buildings. The sensitivity of the high-throughput protocol was shown to detect 1 asymptomatic individual in a building of 415 residents. To date, nearly 85% of the individual cases on the UCSD campus have been preceded by positive wastewater samples. Extracted RNA samples from this high-throughput method can be used for genome sequencing, which will prove invaluable as there is a growing need to keep track of emerging variants.

 

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