ArticleNature communications2026
Environmental metagenomics enhances detection of circulating viruses from live poultry markets in Cambodia.
Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- metaWEPP: leveraging biobank-scale intra-species phylogenies for near-haplotype resolution in metagenomic analysis.NAR genomics and bioinformatics · 2026Article
- Empowering One Health with metagenomics.One health outlook · 2026Review
- Optimization of environmental air sampling for viral metagenomics in a cave-roosting bat assemblage.One health outlook · 2026Article
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20 authors.
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Abstract
Environmental surveillance has emerged as a pivotal strategy for early detection of pathogens that pose a threat to humans. In Asia, live-bird markets (LBMs) are key human-animal interfaces for zoonotic virus transmission. Traditional sampling strategies are time-consuming, expensive and carry significant biosafety risks. Here, we assess the performance of metagenomics on environmental samples (ES) versus traditional poultry swabs for detecting viral pathogens in two Cambodian LBMs between January 2022 and April 2023. ES, including air (n = 35), cage swabs (n = 17), carcass wash water (n = 17) and drinking water (n = 9) are collected alongside oropharyngeal and cloacal swabs from chickens (n = 30) and ducks (n = 29). ES is sensitive in detecting 40 viruses from pathogen families including Orthomyxoviridae and Coronaviridae. Air samples capture the greatest diversity of poultry viruses. Viral contigs from ES show high sequence identity to poultry swab contigs when aligned to the same gene. We show ES outperforms poultry samples in detecting the highly pathogenic influenza A/H5N1, including clades 2.3.4.4b and 2.3.2.1c, which are found in the environment but are missed by poultry swabs. Our findings show metagenomics on ES replicates traditional surveillance, offering broader coverage and improved pathogen detection. This approach could be pivotal for mitigating zoonotic spillover and enhancing pandemic preparedness.
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