Evidence map›Paper›PMID 41803939›Full record

ArticleAnimal microbiome2026

Longitudinal source-sink dynamics of fecal litter and farm indoor environmental resistomes in broiler chicken and Cherry Valley ducks.

Peter Fauszt, Maja Mikolas, Peter David, Zsombor Szoke, Njomza Gashi, Emese Szilagyi-Tolnai, Endre Szilágyi, Maria Magdolna Szarvas, Monika Eva Fazekas, Andrea Kun-Nemes and 7 more

Abstract read
In one paragraph

Article in Animal microbiome, 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
–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

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

17 authors.

Peter FausztComplex Systems and Microbiome-innovations Centre, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, Debrecen, Hungary.
Maja MikolasComplex Systems and Microbiome-innovations Centre, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, Debrecen, Hungary.
Peter DavidComplex Systems and Microbiome-innovations Centre, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, Debrecen, Hungary.
Zsombor SzokeComplex Systems and Microbiome-innovations Centre, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, Debrecen, Hungary.
Njomza GashiComplex Systems and Microbiome-innovations Centre, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, Debrecen, Hungary.
Emese Szilagyi-TolnaiComplex Systems and Microbiome-innovations Centre, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, Debrecen, Hungary.
Endre SzilágyiComplex Systems and Microbiome-innovations Centre, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, Debrecen, Hungary.
Maria Magdolna SzarvasComplex Systems and Microbiome-innovations Centre, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, Debrecen, Hungary.
Monika Eva FazekasComplex Systems and Microbiome-innovations Centre, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, Debrecen, Hungary.
Andrea Kun-NemesComplex Systems and Microbiome-innovations Centre, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, Debrecen, Hungary.
Aniko StagelHungarian National Blood Transfusion Service Nucleic Acid Testing Laboratory, Budapest, Hungary.
Ferenc GalComplex Systems and Microbiome-innovations Centre, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, Debrecen, Hungary.
Levente CzeglediDepartment of Animal Husbandry, Faculty of Agricultural and Food Sciences and Environmental Management, Institute of Animal Science, Biotechnology and Nature Conservation, University of Debrecen, Debrecen, Hungary.
Sandor BiroDepartment of Human Genetics, Faculty of Medicine, University of Debrecen, Debrecen, Hungary.
Laszlo StundlFaculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, Debrecen, Hungary.
Judit RemenyikComplex Systems and Microbiome-innovations Centre, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, Debrecen, Hungary.
Melinda PaholcsekComplex Systems and Microbiome-innovations Centre, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, Debrecen, Hungary. paholcsek.melinda@agr.unideb.hu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAntimicrobial resistance is a major One Health threat, and intensive poultry systems function as amplifiers. Although broilers and ducks are reared under similarly controlled conditions, their microecologies diverge. Integrated, longitudinal source-sink analyses quantifying overlap and directional flux between host-associated and environmental resistomes remain scarce. A two-year (2022–2024), longitudinal, commercial-scale comparison was undertaken across 15 stocking cycles under harmonized husbandry in Ross 308 broiler and Cherry Valley duck. Parallel shotgun metagenomics profiled fecal litter and farm indoor environments across standardized production, with daily monitoring in one complete cycle per system; in total, 96 pooled samples were sequenced to quantify cross-compartment overlaps.

resultsAntibiotic resistance gene (ARG) reservoir dominance proved to be system-specific, duck systems were environment-centric, whereas broiler systems were fecal litter-centric. Although overall ARG diversity was similar between systems (broiler 2,542; duck 2,494 types), ducks exhibited greater compartmental divergence, with ~ 2.6-fold more environment-unique ARGs than paired fecal litter and 1.15-fold higher environmental richness than broilers. Compartment coupling also differed: broilers showed tighter host-environment overlap, while ducks were more partitioned. A shared environmental ARG pool (57.5%) indicated substantial cross-system exchange potential. Temporally, shared ARGs accumulated across the grow-out and peaked pre-depopulation. The distribution of significant ARG carrier species revealed asymmetric host-environment coupling: overlap across compartments was 66.67% in broilers versus 45.45% in ducks, notably. The impact of antimicrobial use was nuanced: short, targeted courses were associated with lower aaAMR burden overall Collectively, the recurrent detection of clinically consequential carriers (P. aeruginosa, E. coli, A. baumannii, S. aureus, K. pneumoniae, S. maltophilia, toxigenic Clostridium spp.) underscored One Health risks of zoonotic spillover and food-chain contamination.

conclusionReservoir behavior in intensive poultry systems should be treated as system-specific, and matrix-targeted, with biofilm and humidity management prioritized in duck operations, and litter/manure control emphasized in broilers. The finisher-depopulation window emerges as a critical intervention point, warranting intensified mitigation clean-out. Finally, mitigation should extend beyond individual farms to transport crates, vehicles, shared equipment, and supply chains.

Indexed as

Antimicrobial resistanceBroilerDuckFarm environmentMicrobiome

Identifiers

PMID41803939
PMCPMC13085657

What Socratic 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 Socratic graph.