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Record W2888213194 · doi:10.2134/jeq2018.04.0139

Antimicrobial‐Resistant <i>E. coli</i> from Surface Waters in Southwest Ontario Dairy Farms

2018· article· en· W2888213194 on OpenAlexafffundabout
Gurleen Taggar, Muhammad Attiq Rehman, Xianhua Yin, Dion Lepp, Kim Ziebell, Patrick Handyside, Patrick Boerlin, Moussa S. Diarra

Bibliographic record

VenueJournal of Environmental Quality · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsPublic Health Agency of CanadaUniversity of GuelphAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food Canada
KeywordsEscherichia coliAntimicrobialBiologyAntibiotic resistanceCephalosporinMicrobiologyPlasmidMultiple drug resistanceSerotypeBacteriaBiotechnologyVeterinary medicineAntibioticsGeneGenetics

Abstract

fetched live from OpenAlex

Untreated surface waters can be contaminated with a variety of bacteria, including Escherichia coli, some of which can be pathogenic for both humans and animals. Therefore, such waters need to be treated before their use in dairy operations to mitigate risks to dairy cow health and milk safety. To understand the molecular ecology of E. coli, this study aimed to assess antimicrobial resistance (AMR) in E. coli recovered from untreated surface water sources of dairy farms. Untreated surface water samples (n = 240) from 15 dairy farms were collected and processed to isolate E. coli. A total of 234 E. coli isolates were obtained and further characterized for their serotypes and antimicrobial susceptibility. Of the 234 isolates, 71.4% were pan‐susceptible, 23.5% were resistant to one or two antimicrobial classes, and 5.1% were resistant to three or more antimicrobial classes. Whole genome sequence analysis of 11 selected multidrug‐resistant isolates revealed AMR genes including blaCMY‐2 and blaCTX‐M‐1 that confer resistance to the critically important extended‐spectrum cephalosporins, as well as a variety of plasmids (mainly of the IncF replicon type) and class 1 integrons. Phylogenetic and comparative genome analysis revealed a genetic relationship between some of the sequenced E. coli and Shiga toxin‐producing E. coli O157:H7 (STEC), which warrants further investigation. This study shows that untreated surface water sources contain antimicrobial‐resistant E. coli, which may serve as a reservoir of AMR that could be disseminated through horizontal gene transfer. This is another reason why effective water treatment before usage should be routinely done on dairy farm operations. Core Ideas Surface water is a valuable input for livestock production. Untreated surface water can be a source of antimicrobial‐resistant bacteria. Multidrug‐resistant E. coli strains may facilitate spread of antimicrobial resistance (AMR). Whole genome sequencing provides insight into the molecular ecology of E. coli from surface water. This highlights the need to implement efficient water treatment units for dairy farms.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.196
Threshold uncertainty score0.394

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.000
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 head0.012
GPT teacher head0.244
Teacher spread0.232 · 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

Citations10
Published2018
Admission routes3
Has abstractyes

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