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COPMAN: A Novel High-throughput and Highly Sensitive Method to Detect Viral Nucleic Acids Including SARS-CoV-2 RNA in Wastewater

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Date 2022 Sep 26
PMID 36162583
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Abstract

During the coronavirus disease 2019 (COVID-19) pandemic, wastewater-based epidemiology (WBE) attracted attention as an objective and comprehensive indicator of community infection that does not require individual inspection. Although several severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) detection methods from wastewater have been developed, there are obstacles to their social implementation. In this study, we developed the COPMAN (Coagulation and Proteolysis method using Magnetic beads for detection of Nucleic acids in wastewater), an automatable method that can concentrate and detect multiple types of viruses from a limited volume (∼10 mL) of wastewater. The COPMAN consists of a high basicity polyaluminum chloride (PAC) coagulation process, magnetic bead-based RNA purification, and RT-preamplification, followed by qPCR. A series of enzymes exhibiting a high tolerance to PCR inhibitors derived from wastewater was identified and employed in the molecular detection steps in the COPMAN. We compared the detectability of viral RNA from 10-mL samples of virus-spiked (heat-inactivated SARS-CoV-2 and intact RSV) or unspiked wastewater by the COPMAN and other methods (PEG-qPCR, UF-qPCR, and EPISENS-S). The COPMAN was the most efficient for detecting spiked viruses from wastewater, detecting the highest level of pepper mild mottle virus (PMMoV), a typical intrinsic virus in human stool, from wastewater samples. The COPMAN also successfully detected indigenous SARS-CoV-2 RNA from 12 samples of wastewater at concentrations of 2.2 × 10 to 5.4 × 10 copies/L, during initial stages of an infection wave in the right and the left bank of the Sagami River in Japan (0.65 to 11.45 daily reported cases per 100,000 people). These results indicate that the COPMAN is suitable for detection of multiple pathogens from small volume of wastewater in automated stations.

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