Evidence map›Paper›PMID 42215894›Full record

ArticleBMC microbiology2026

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

Tristan Russell, Elisa Formiconi, Alison Murphy, Jimmy Hortion, Máire McElroy, Mícheál Casey, Laura Garza Cuartero, John F Mee, Hanne Jahns, Christine Kelly and 4 more

Abstract read
In one paragraph

Article in BMC microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Tristan RussellUCD Centre for Experimental Pathogen Host Research (CEPHR), University College Dublin, Dublin, D04 E1W1, Ireland.
Elisa FormiconiUCD Centre for Experimental Pathogen Host Research (CEPHR), University College Dublin, Dublin, D04 E1W1, Ireland.
Alison MurphyUCD Conway Institute, University College Dublin, Dublin, D04 E1W1, Ireland.
Jimmy HortionUCD Centre for Experimental Pathogen Host Research (CEPHR), University College Dublin, Dublin, D04 E1W1, Ireland.
Máire McElroyDepartment of Agriculture, Food, and the Marine Laboratories, Backweston, Celbridge, Kildare, W23 VW2C, Ireland.
Mícheál CaseyRegional Veterinary Laboratories (RVL) Division, Department of Agriculture, Food and the Marine, Agriculture House, Backweston, Dublin, T12 XD51, Ireland.
Laura Garza CuarteroDepartment of Agriculture, Food, and the Marine Laboratories, Backweston, Celbridge, Kildare, W23 VW2C, Ireland.
John F MeeTeagasc, Moorepark Research Centre, Animal and Bioscience Research Department, Fermoy, P61 P302, Ireland.
Hanne JahnsUCD School of Veterinary Medicine, University College Dublin, Dublin 4, D04 W6F6, Ireland.
Christine KellyUCD Centre for Experimental Pathogen Host Research (CEPHR), University College Dublin, Dublin, D04 E1W1, Ireland.
Joanne ByrneUCD Centre for Experimental Pathogen Host Research (CEPHR), University College Dublin, Dublin, D04 E1W1, Ireland.
Eoin R FeeneyUCD Centre for Experimental Pathogen Host Research (CEPHR), University College Dublin, Dublin, D04 E1W1, Ireland.
Patrick Wg MallonUCD Centre for Experimental Pathogen Host Research (CEPHR), University College Dublin, Dublin, D04 E1W1, Ireland.
Virginie W GautierUCD Centre for Experimental Pathogen Host Research (CEPHR), University College Dublin, Dublin, D04 E1W1, Ireland. virginie.gautier@ucd.ie.

Funding

European Commission 101132970, EU4H-2022-DGA-MS-IBA3
6 · The paper itself

Abstract

backgroundMetagenomic 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.

resultsThe 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.

conclusionsThese 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.

Indexed as

Genome, ViralHigh-Throughput Nucleotide SequencingMetagenomicsVirus DiseasesVirusesAnimalsDNA VirusesHumansRNA VirusesSpecimen HandlingWorkflowDisease SurveillancePandemic PreparednessVirus Discovery

Identifiers

PMID42215894
PMCPMC13435701

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.