Optimization of environmental air sampling for viral metagenomics in a cave-roosting bat assemblage

Abstract Background Environmental air sampling holds significant potential as a tool for viral surveillance. Its use in agricultural and indoor settings has demonstrated its feasibility and effectiveness but despite this, it has rarely been used in wildlife settings. Methods To enable future applications, we optimized key parameters in air sampling methodology using a cave-roosting bat assemblage as a model system. We systematically investigated the impact of sampling conditions (flow rate, sampling duration, and sampling location/deployment time) and post-sampling treatments (DNA/RNA Shield ratios and secondary filtration) on three viral metrics – total mammalian virus abundance, mammalian RNA virus abundance, and Shannon diversity index – generated from next-generation sequencing data. Results We first showed that air sampling can recover broad viral diversity, including alphacoronaviruses and betacoronaviruses. The sampling conditions for maximizing viral metrics were larger air sample volumes (≥24,000 liters) and sampling inside the cave while the bats were roosting, as opposed to at the cave entrance during emergence. Post-sampling treatments had limited impact on viral metrics, but their application may vary depending on the objectives of the study. Conclusion This work provides a proof-of-concept for applying air sampling for wildlife viral surveillance in a cave-roosting bat assemblage and identifies key sampling parameters.