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Record W4411428744 · doi:10.1186/s42523-025-00432-w

Genomic characterization of antimicrobial resistance and mobile genetic elements in swine gut bacteria isolated from a Canadian research farm

2025· article· en· W4411428744 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAnimal Microbiome · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsMcMaster UniversityPopulation Health Research InstituteUniversity of GuelphUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMobile genetic elementsBiologyResistomeMetagenomicsMicrobiomeAntibiotic resistanceGut floraGenomeGeneticsGeneBacteriaImmunology

Abstract

fetched live from OpenAlex

INTRODUCTION: The widespread use of antimicrobials in the livestock industry has raised global concerns regarding the emergence and spread of antimicrobial resistance genes (ARGs). Comprehensive databases of ARGs specific to different farm animal species can greatly improve the surveillance of ARGs within the agri-food sector and beyond. In particular, defining the association of ARGs with mobile genetic elements (MGEs)-the primary agents responsible for the spread and acquisition of resistant phenotypes among bacterial populations-could help assess the transmissibility potential of clinically relevant ARGs. Recognizing the gut microbiota as a vast reservoir of ARGs, we aimed to generate a representative isolate collection and genome database of the swine gut microbiome, enabling high-resolution characterization of ARGs in relation to bacterial host range and their association with MGEs. RESULTS: We generated a biobank of bacteria from different sections of the gastrointestinal tracts of four clinically healthy pigs housed at a research farm in Ontario, Canada. The culturing was performed under anaerobic conditions using both selective and general enrichment media to ensure the capture of a diverse range of bacterial families within the swine gut microbiota. We sequenced the genomes of 129 unique isolates encompassing 44 genera and 25 distinct families of the swine gut microbiome. Approximately 85.3% (110 isolates) contained one or more ARGs, with a total of 246 ARGs identified across 38 resistance gene families. Tetracycline and macrolide resistance genes were the most prevalent across different lineages of the swine gut microbiota. Additionally, we observed a wide range of MGEs, including integrative conjugative elements, plasmids, and phages, frequently associated with ARGs, indicating that the swine gut ecosystem is conducive to the horizontal transfer of ARGs. High-throughput alignment of the identified ARG-MGE complexes to large-scale metagenomics datasets of the swine gut microbiome suggests the presence of highly prevalent and conserved resistome sequences across diverse pig populations. CONCLUSION: Our findings reveal a highly diverse and relatively conserved reservoir of ARGs and MGEs within the gut microbiome of pigs. A deeper understanding of the microbial host range and potential transmissibility of prevalent ARGs in the swine microbiome can inform development of targeted antimicrobial resistance surveillance and disease control programs.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.716
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.279
Teacher spread0.265 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it