Validation of prototype virus inactivation from seven virus families of pandemic potential with a novel low-cost, field-deployable RNA extraction and storage method

The Centers for Research in Emerging Infectious Diseases (CREID) was established to enhance pandemic preparedness by studying emerging/reemerging pathogens, especially in resource-limited regions. To overcome infrastructure challenges, a low-cost, field-deployable method for extracting total nucleic acids is essential, eliminating reliance on expensive equipment, power, and cold chain systems used in traditional extraction techniques. To address this challenge, we developed an RNA extraction and storage method (RNAES) that meets these criteria. Herein, we report RNAES inactivation efficacy against nine prototype viruses (Middle Eastern respiratory syndrome coronavirus, Japanese encephalitis virus, West Nile virus, Hantaan virus, measles virus, Heartland virus, enterovirus A71, chikungunya virus, and Western equine encephalitis virus) representing seven pandemic potential virus families. We compare the RNAES method to the Qiagen QIAamp kit across various viral loads and field sample types. The presence of infectious virus in RNA samples was quantified using plaque assays. Successful inactivation of viruses was demonstrated for six enveloped virus families spiked into matrices routinely collected at field sites. The seventh family tested (Picornaviridae) was not completely inactivated, likely due to non-enveloped viruses being differentially susceptible to the lysis chemistry of the RNAES kit. The commercial comparator inactivated all viruses tested. Specialized biosafety facilities, specific detailed permits, and comprehensive logistics are required to ensure safety when handling and shipping potentially infectious samples. Inactivating pathogens at the point of collection reduces risks and simplifies sample transfer for critical outbreak research. Confidently ensuring that an isolated nucleic acid sample is non-infectious using RNAES will enable safer, and more efficient downstream analysis.