Livestock aggregated samples for monitoring viruses infecting animals and potentially zoonotic viral pathogens

Abstract

Active surveillance of livestock pathogens is essential to prevent animal health losses and zoonotic spillover. This study evaluted aggregated environmental sampling as a non-invasive approach for monitoring swine- and cattle-associated viruses across farms and slaughterhouses, bridging the gap between agricultural biosecurity and public health. Over eleven months, 105 samples, including swine slurry, cattle manure, farm air, and slaughterhouse wastewater, were collected and analyzed using pathogen-specific (RT) qPCR and targeted viral metagenomics.

Seasonal and sample patterns were evident, with higher detection of rotavirus A (RoV-A) and bovine coronavirus (BCoV) in slurry and wastewater during winter, and porcine reproductive and respiratory syndrome virus (PRRSV), porcine epidemic diarrhea virus (PEDV) and transmissible gastroenteritis virus (TGEV) sporadicly in slaughterhouse wastewater. Farm slurry or manure were optimal for enteric viruses such as RoV-A or hepatitis E virus (HEV), and farm air proved valuable for respiratory viruses like BCoV.

Targeted sequencing identified a broader viral community, revealing up to 80% of total detected viral species in slaughterhouse wastewater alone. Frequent detection of porcine bocavirus, circoviruses and astrovirus, alongside zoonotic viruses such as HEV and porcine bufavirus (PBuV), underscored the environmental transmission risk at the human-animal interface. Sequencing also uncovered viruses of unclear pathogenicity, including kobuvirus and copiparvovirus, underscoring the complexity of the livestock virome and the potential for emerging viral threats. Slaughterhouse wastewater consistently captured the highest viral richness, integrating inputs from multiple farms and regions, while farm air samples yielded lower diversity but detected respiratory (astrovirus, caliciviruses) and persistent viruses (papillomaviruses, polyomaviruses). Aggregated sampling proved particularly efficient in swine systems, while cattle surveillance may require adapted strategies due to lower stocking densities and greater ventilation.

This work demonstrates the novelty and value of aggregated environmental samples, collected at different points in the production chain, as strategic One Health sentinels. This scalable, practical approach supports early warning and control of animal and zoonotic diseases, directly contributing to One Health surveillance.