Evidence map›Paper›PMID 36175536›Full record

ArticleScientific reports2022

Establishing farm dust as a useful viral metagenomic surveillance matrix.

Kirsty T T Kwok, Myrna M T de Rooij, Aniek B Messink, Inge M Wouters, Lidwien A M Smit, Matthew Cotten, Dick J J Heederik, Marion P G Koopmans, My V T Phan

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.9field-weighted citation impact, top 12% of its field
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

14 citing papers in PubMed, 21 citations in OpenAlex.

  1. Article
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  3. Shotgun metagenomics on indoor air for surveillance of respiratory, enteric, and skin viruses in a Belgian daycare setting, January to December 2022.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2025
    Article
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  5. Microbial genomics: a potential toolkit for forensic investigations.Forensic science, medicine, and pathology · 2025
    Review
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  9. Article
  10. Review
  11. Article
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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

9 authors at 3 institutions in 2 countries.

Kirsty T T KwokDepartment of Viroscience, Erasmus Medical Center, Rotterdam, The Netherlands. Kirsty.Kwok@glasgow.ac.uk.
Myrna M T de RooijInstitute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, The Netherlands.
Aniek B MessinkInstitute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, The Netherlands.
Inge M WoutersInstitute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, The Netherlands.
Lidwien A M SmitInstitute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, The Netherlands.
Matthew CottenDepartment of Viroscience, Erasmus Medical Center, Rotterdam, The Netherlands.
Dick J J HeederikInstitute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, The Netherlands.
Marion P G KoopmansDepartment of Viroscience, Erasmus Medical Center, Rotterdam, The Netherlands.
My V T PhanDepartment of Viroscience, Erasmus Medical Center, Rotterdam, The Netherlands. my.phan@lshtm.ac.uk.
Utrecht University · NLErasmus MC · NLLondon School of Hygiene & Tropical Medicine · GB

Funding

Marie Curie 799417Medical Research Council MC_UU_12014/12Wellcome TrustWellcome Trust 220977/Z/20/Z
6 · The paper itself

Abstract

Farm animals may harbor viral pathogens, some with zoonotic potential which can possibly cause severe clinical outcomes in animals and humans. Documenting the viral content of dust may provide information on the potential sources and movement of viruses. Here, we describe a dust sequencing strategy that provides detailed viral sequence characterization from farm dust samples and use this method to document the virus communities from chicken farm dust samples and paired feces collected from the same broiler farms in the Netherlands. From the sequencing data, Parvoviridae and Picornaviridae were the most frequently found virus families, detected in 85-100% of all fecal and dust samples with a large genomic diversity identified from the Picornaviridae. Sequences from the Caliciviridae and Astroviridae familes were also obtained. This study provides a unique characterization of virus communities in farmed chickens and paired farm dust samples and our sequencing methodology enabled the recovery of viral genome sequences from farm dust, providing important tracking details for virus movement between livestock animals and their farm environment. This study serves as a proof of concept supporting dust sampling to be used in viral metagenomic surveillance.

Indexed as

ChickensDustAnimalsFarmsHumansMetagenomeMetagenomicsDust

Identifiers

PMID36175536
PMCPMC9521564
OpenAlexW4297998187

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.