Abstract
Wastewater monitoring is rapidly expanding to provide surveillance for a growing number of epidemic and endemic pathogens. To provide early warning and support rapid response to a novel virus through wastewater surveillance, it would be ideal to understand in advance which concentration and extraction methods are likely to be effective for dPCR-based methods, depending on virus characteristics. In this study, we spiked wastewater samples with eight human respiratory viruses and processed them with four commercial methods that concentrate and/or extract nucleic acids from both liquid and solid fractions (Promega, Nanotrap, InnovaPrep), or only the solid fraction of wastewater (Solids). Our findings provide encouraging evidence that all four concentration/extraction methods combined with dPCR could detect an emerging virus in wastewater, although they differed in sensitivity. The pattern of recovery efficiency for adenoviruses, coronaviruses, and influenza A viruses was consistent across methods, while distinct patterns were observed for coxsackieviruses. Promega produced higher median recovery efficiencies based on dPCR for all viruses except for coxsackieviruses, even though it had the highest dPCR inhibition. We suggest caution in applying Nanotrap to new targets, based on the low recovery of coxsackievirus B5 compared to the other viruses. We also quantified the endogenous indicators PMMoV and Carjivirus (formerly crAssphage), illustrating how normalization could either improve or worsen the comparison of virus concentrations measured by different methods. These findings can guide the selection of concentration and extraction methods for wastewater monitoring based on the properties of target viruses, thus enhancing pandemic preparedness.
Synopsis Statement Benchmarking scalable concentration and extraction methods on respiratory viruses with diverse properties facilitates the rapid application of wastewater-based surveillance to emerging viruses.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
Add myself (Audrey LiWen Wang) as a first-author to the "Author list".