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Record W4402541682 · doi:10.1093/jas/skae234.763

PSLBII-27 Investigating the emergence of antimicrobial resistance in <i>Mycoplasma bovis</i> from feedlot cattle

2024· article· en· W4402541682 on OpenAlexaffabout
Sara Andrés-Lasheras, Rahat Zaheer, Antonio C. Ruzzini, Murray Jelinski, Tim A. McAllister

Bibliographic record

VenueJournal of Animal Science · 2024
Typearticle
Languageen
FieldImmunology and Microbiology
TopicMicrobial infections and disease research
Canadian institutionsUniversity of SaskatchewanAgriculture and Agri-Food Canada
Fundersnot available
KeywordsFeedlotBiologyAntimicrobialAntibiotic resistanceMycoplasmaVeterinary medicineTylosinResistance (ecology)Animal scienceMicrobiologyAntibioticsAgronomyMedicine

Abstract

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Abstract Bovine respiratory disease (BRD) is the most significant disease affecting feedlot cattle in North America. Mycoplasma bovis is among the main BRD pathogenic bacteria. Infection control of M. bovis is hampered by a lack of effective vaccines and increasing antimicrobial resistance (AMR). Integrative and conjugative elements (ICEs) have been documented as a mechanism of horizontal gene transfer (HGT) in mycoplasmas. Mycoplasma ICEs (MICE) do not carry AMR genes but have been associated with the HGT of genes that confer AMR through point mutations. Hence, there is a need to gain a better understanding of the role of MICE in M. bovis AMR. Randomly selected M. bovis isolates (n = 54) collected from Western Canadian feedlot cattle (AB and SK) underwent whole-genome sequencing by short-reads (Illumina), with a subset (n = 6) selected based on AMR and ICE profiles for Oxford Nanopore long-read sequencing. Sequences were screened for the presence of MICE. MICE circularization (cMICE) is the first step of conjugation, and an in-house collection of 472 M. bovis field isolates (feedlot cattle just from AB) was screened by PCR for the presence of cMICE as a proxy for conjugation capabilities. Environmental conditions that could impact cMICE quantity, including growth phase, temperature, cell density, pH, starvation, UV light, CO2 concentration, and sub-inhibitory concentrations of mitomycin C were investigated by qPCR, followed by growth of M. bovis isolates under the most favorable conditions identified for cMICE-detection and screening by a high throughput qPCR method that eliminated the need for DNA extraction. Nineteen different mating pairs were carried out and 4 different environmental factors were tested for their possible impact on conjugation occurrence (incubation time, incubation volume, conjugation parent proportions, atmosphere). All isolates carried MICEs with 23/54 having a structure/sequence comparable to previously described functional MICE in mycoplasma, 43/54 possessing non-functional ICE, and 23 having >1 ICE. The presence of more than one MICE/genome suggests a lack of MICE (entry) exclusion systems in M. bovis, a trait that may promote the flow of genetic information among M. bovis isolates including AMR. Even though some factors including growth phase (early stationary phase) and pH (9.0) generated greater levels (≥1.5 fold) of cMICE, none of the examined parameters were statistically significant. However, as early stationary growth phase generated the greatest cMICE quantity (2.3 fold), M. bovis isolates were cMICE-screened at this growth stage for the expeditious identification of M. bovis conjugation candidates. A total of 25.7% M. bovis were cMICE-positive. Of 19 mating pairs tested, transconjugants were recovered from only 2 different mating pairs, possibly reflective of the need for further optimization of conjugation conditions.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.023
GPT teacher head0.300
Teacher spread0.277 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2024
Admission routes2
Has abstractyes

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