MétaCan
Menu
Back to cohort
Record W4389301585 · doi:10.3389/fsybi.2023.1301879

Influence of three different manure treatments on antimicrobial resistance genes and mobile genetic elements

2023· article· en· W4389301585 on OpenAlexafffund
Daniel Flores-Orozco, David B. Levin, Ayush Kumar, Richard Sparling, Nazim Çiçek

Bibliographic record

VenueFrontiers in Synthetic Biology · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMobile genetic elementsManureBiologyAntibiotic resistanceBiotechnologyMetagenomicsAntimicrobialFood scienceAgronomyMicrobiologyAntibioticsGeneGeneticsPlasmid

Abstract

fetched live from OpenAlex

There is a growing concern about the potential dissemination of antimicrobial resistance into agricultural fields due to the application of manure as crop fertilizer. While reducing the usage of antibiotics in livestock production stands as the first alternative to prevent this problem, there is evidence that this may not be enough to eliminate antimicrobial resistance elements already present in manure microbiomes. This study employed a metagenomic approach to investigate the impact of common manure treatments, including aerobic storage, mesophilic anaerobic digestion (MAD), and solid-liquid separation, on the presence and abundance of antimicrobial resistance genes (ARGs), bactericides, and heavy metal resistance genes (BacMet), and mobile genetic elements (MGEs) in manure from three different farms, including one operating in an antibiotic-free environment. The results indicated that MAD was the best method to reduce the numbers of ARGs, BacMet, and MGEs, achieving reduction rates greater than 40%, 89%, and 68%, respectively. Manure storage significantly reduced BacMet levels (over 30%) and MGEs (28%) but had no significant effect on total ARG levels. Solids recovered through solid-liquid separation exhibited elevated levels of ARGs, BacMet, and MGEs, while the liquid fraction displayed levels similar to untreated manures. Correlation and co-occurrence modeling analyses indicated that changes in microbial communities, particularly fluctuations in aerobic and facultative communities belonging to Bacillota, Actinomycetota, and Pseudomonadota phyla, played a significant role in driving changes in ARGs, BacMet, and MGEs. The results also showed the presence of toxin-antitoxin and transposon systems near different ARGs. Overall, the results confirmed that genes conferring resistance to various antimicrobials and MGE capable of mobilizing them are widely spread in dairy farms; that even under the absence of antibiotics, the use of heavy metals and disinfectants may promote the maintenance of ARGs and MGEs, and; that treatment such as anaerobic digestion could reduce the risk of the spread of antimicrobial resistance.

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 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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.090
Threshold uncertainty score0.558

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.256
Teacher spread0.243 · 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 teacher head, 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

Citations4
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueFrontiers in Synthetic BiologySame topicPharmaceutical and Antibiotic Environmental ImpactsFrench-language works237,207