ArticleAnimal microbiome2025
Microbial exchange at the wildlife-livestock interface: insights into microbial composition, antimicrobial resistance and virulence factor gene dynamics in grassland ecosystems.
Article in Animal microbiome, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 5 papers.
What it found
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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.
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.
Who cites it
5 citing papers in PubMed.
- Article
- How do anthropogenic changes affect wildlife microbiomes?PLoS biology · 2026Article
- The Wildlife-Livestock Interface as a Bidirectional Pathway for the Spread of ESBL-ProducingAnimals : an open access journal from MDPI · 2026Review
- Molecular diversity and phylogenetic characterization of theVeterinary world · 2026Article
- Effects of Age, Sex, and Social Network on Antibiotic Resistance Genes in the Gut Microbiome of Tibetan Macaques (Ecology and evolution · 2026Article
Corrections and comments
- Erratum issued
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The transmission of antimicrobial resistance genes (ARGs) and virulence factors (VFs) between wildlife and livestock is an emerging concern for animal and human health, especially in shared ecosystems. ARGs enhance bacterial survival against antibiotics, while VFs contribute to infection processes, and the microbiome composition influences host health. Understanding microbial exchange at the wildlife-livestock interface is essential for assessing risks to both animal and human health. This study addresses the gap in knowledge by investigating the microbial composition, ARGs, and VFs in fecal matter from livestock (Bos taurus, Ovis aries) and wildlife (Microtus arvalis) cohabiting grassland pastures. Sampling was conducted within the DFG Biodiversity Exploratories, which provides valuable and extensive long-term ecological datasets and enables the study of diverse environmental parameters. Using metagenomic sequencing and 16 S rRNA amplicon analysis, we compared bacterial diversity, antimicrobial resistance profiles, and virulence gene presence across the three host species. Metagenomic analysis revealed host-specific differences in bacterial community composition. Livestock samples exhibited higher microbial diversity than those from M. arvalis, likely due to greater environmental exposure and management practices. The most common VFs in livestock were associated with immune modulation, whereas motility-related VFs were prevalent in M. arvalis. ARG profiles differed among hosts, suggesting rare events rather due to environmental acquisition than direct transmission between the hosts. The limited numbers of ARGs and VFs shared between the species indicate that horizontal gene transfer events between wildlife and livestock are infrequent. Notably, M. arvalis harbored diverse ARGs, including resistance to tetracycline and vancomycin, which were likely acquired from the environment rather than from direct livestock contact. These findings highlight the significant role of environmental reservoirs in shaping microbial communities and the spread of resistance. This research underscores the need for enhanced surveillance and ecosystem management strategies to mitigate the risk associated with antimicrobial resistance and the potential impacts on both animal and human health.
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Registered trials
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.