Evidence map›Paper›PMID 39033279›Full record

ArticleBMC genomics2024

A cross-sectional comparison of gut metagenomes between dairy workers and community controls.

Pauline Trinh, Sarah Teichman, Marilyn C Roberts, Peter M Rabinowitz, Amy D Willis

Abstract readComparative Study
In one paragraph

Article in BMC genomics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Pauline TrinhDepartment of Biostatistics, University of Washington, Seattle, USA.
Sarah TeichmanDepartment of Statistics, University of Washington, Seattle, USA.
Marilyn C RobertsDepartment of Environmental and Occupational Health Sciences, University of Washington, Seattle, USA.
Peter M RabinowitzDepartment of Environmental and Occupational Health Sciences, University of Washington, Seattle, USA.
Amy D WillisDepartment of Biostatistics, University of Washington, Seattle, USA. adwillis@uw.edu.

Funding

Biostatistics, Epidemiologic & Bioinformatic Training in Environmental HealthT32ES015459 · NIEHS · UNIVERSITY OF WASHINGTON · PI June T. Spector · 2009 to 2026
$10.6M
Statistical methods to enhance reproducible microbiome discoveryR35GM133420 · NIGMS · UNIVERSITY OF WASHINGTON · PI Amy D Willis · 2019 to 2026
$2.8M
Statistical pangenomics to study the effects of zoonotic exposure on the gut microbiomeR21AI168679 · NIAID · UNIVERSITY OF WASHINGTON · PI WILLIS, AMY D · 2022 to 2023
$428k
NIAID NIH HHS R21 AI168679NIEHS NIH HHS T32 ES015459NIGMS NIH HHS R35 GM133420
6 · The paper itself

Abstract

backgroundAs a nexus of routine antibiotic use and zoonotic pathogen presence, the livestock farming environment is a potential hotspot for the emergence of zoonotic diseases and antibiotic resistant bacteria. Livestock can further facilitate disease transmission by serving as intermediary hosts for pathogens before a spillover event. In light of this, we aimed to characterize the microbiomes and resistomes of dairy workers, whose exposure to the livestock farming environment places them at risk for facilitating community transmission of antibiotic resistant genes and emerging zoonotic diseases.

resultsUsing shotgun sequencing, we investigated differences in the taxonomy, diversity and gene presence of 10 dairy farm workers and 6 community controls' gut metagenomes, contextualizing these samples with additional publicly available gut metagenomes. We found no significant differences in the prevalence of resistance genes, virulence factors, or taxonomic composition between the two groups. The lack of statistical significance may be attributed, in part, to the limited sample size of our study or the potential similarities in exposures between the dairy workers and community controls. We did, however, observe patterns warranting further investigation including greater abundance of tetracycline resistance genes and prevalence of cephamycin resistance genes as well as lower average gene diversity (even after accounting for differential sequencing depth) in dairy workers' metagenomes. We also found evidence of commensal organism association with tetracycline resistance genes in both groups (including Faecalibacterium prausnitzii, Ligilactobacillus animalis, and Simiaoa sunii).

conclusionsThis study highlights the utility of shotgun metagenomics in examining the microbiomes and resistomes of livestock workers, focusing on a cohort of dairy workers in the United States. While our study revealed no statistically significant differences between groups in taxonomy, diversity and gene presence, we observed patterns in antibiotic resistance gene abundance and prevalence that align with findings from previous studies of livestock workers in China and Europe. Our results lay the groundwork for future research involving larger cohorts of dairy and non-dairy workers to better understand the impact of occupational exposure to livestock farming on the microbiomes and resistomes of workers.

Indexed as

Gastrointestinal MicrobiomeMetagenomeAdultAnimalsBacteriaCross-Sectional StudiesDairyingDrug Resistance, BacterialFarmersFemaleHumansMaleMetagenomicsMiddle AgedAntibiotic resistanceLivestock farmingMicrobiomeShotgun metagenomicsVirulence factors

Identifiers

PMID39033279
PMCPMC11626760

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Registered trials

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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.