One health viral metagenomics for pathogen surveillance: robust mNGS workflows for viral detection and genome recovery from swab and tissue specimens

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Abstract Background Metagenomic next-generation sequencing (mNGS) is an untargeted approach that enables detection of pathogens directly from samples without prior knowledge of their genetic sequences. In the context of pandemic preparedness and One Health surveillance, there is a pressing need for robust viral mNGS workflows that perform reliably across diverse hosts sample types and pre-analytical conditions. Results The study evaluated two shotgun mNGS workflows, one for swabs and one for complex tissue matrices, using a reference repository of clinical and post-mortem samples. The panel comprised swabs and tissue samples positive for 18 DNA and RNA viruses (including 12 species) from nine host species and nine anatomical sites, encompassing a range of transport media, storage temperatures and processing timelines. Quality control metrics were embedded throughout nucleic acid extraction, library preparation and sequencing to monitor performance and support interpretation. Overall, 88.9% of 18 DNA and RNA viruses previously detected by PCR were identified, including from samples with low nucleic acid concentrations (< 1 ng/µl) and variable integrity and purity. The workflows identified viral co-infections that had not been detected by prior targeted testing, as well as Phocid herpesvirus 7 (PHV7) for which no complete reference genome was initially available. Conclusions These results demonstrate the feasibility and robustness of the swab and tissue mNGS workflows for virus identification across a range of complex clinical specimens supporting their use in investigations of suspected viral diseases of unknown aetiology and is currently being evaluated for early detection of emerging viral threats at the animal-human interface.

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