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Record W2790171019 · doi:10.1128/aem.00109-18

Long-Term Exposure of Agricultural Soil to Veterinary Antibiotics Changes the Population Structure of Symbiotic Nitrogen-Fixing Rhizobacteria Occupying Nodules of Soybeans (Glycine max)

2018· article· en· W2790171019 on OpenAlexafffund
Cécile Revellin, Alain Hartmann, Sébastien Solanas, Edward Topp

Bibliographic record

VenueApplied and Environmental Microbiology · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLegume Nitrogen Fixing Symbiosis
Canadian institutionsAgriculture and Agri-Food CanadaWestern University
FundersAgriculture and Agri-Food CanadaGovernment of Canada
KeywordsBiologyBradyrhizobiumAntibioticsNitrogen fixationPopulationAgronomyVeterinary medicineRoot nodule16S ribosomal RNAAnimal scienceBacteriaMicrobiology

Abstract

fetched live from OpenAlex

ABSTRACT Antibiotics are entrained in agricultural soil through the application of manures from medicated animals. In the present study, a series of small field plots was established in 1999 that receive annual spring applications of a mixture of tylosin, sulfamethazine, and chlortetracycline at concentrations ranging from 0.1 to 10 mg · kg −1 soil. These antibiotics are commonly used in commercial swine production. The field plots were cropped continuously for soybeans, and in 2012, after 14 annual antibiotic applications, the nodules from soybean roots were sampled and the occupying bradyrhizobia were characterized. Nodules and isolates were serotyped, and isolates were distinguished using 16S rRNA gene and 16S to 23S rRNA gene intergenic spacer region sequencing, multilocus sequence typing, and RSα fingerprinting. Treatment with the antibiotic mixture skewed the population of bradyrhizobia dominating the nodule occupancy, with a significantly larger proportion of Bradyrhizobium liaoningense organisms even at the lowest dose of 0.1 mg · kg −1 soil. Likewise, all doses of antibiotics altered the distribution of RSα fingerprint types. Bradyrhizobia were phenotypically evaluated for their sensitivity to the antibiotics, and there was no association between in situ treatment and a decreased sensitivity to the drugs. Overall, long-term exposure to the antibiotic mixture altered the composition of bradyrhizobial populations occupying nitrogen-fixing nodules, apparently through an indirect effect not associated with the sensitivity to the drugs. Further work evaluating agronomic impacts is warranted. IMPORTANCE Antibiotics are entrained in agricultural soil through the application of animal or human waste or by irrigation with reused wastewater. Soybeans obtain nitrogen through symbiotic nitrogen fixation. Here, we evaluated the impact of 14 annual exposures to antibiotics commonly used in swine production on the distribution of bradyrhizobia occupying nitrogen-fixing nodules on soybean roots in a long-term field experiment. By means of various sequencing and genomic fingerprinting techniques, the repeated exposure to a mixture of tylosin, sulfamethazine, and chlortetracycline each at a nominal soil concentration of 0.1 mg · kg −1 soil was found to modify the diversity and identity of bradyrhizobia occupying the nodules. Nodule occupancy was not associated with the level of sensitivity to the antibiotics, indicating that the observed effects were not due to the direct toxicity of the antibiotics on bradyrhizobia. Altogether, these results indicate the potential for long-term impacts of antibiotics on this agronomically important symbiosis.

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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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 head0.008
GPT teacher head0.188
Teacher spread0.180 · 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

Citations23
Published2018
Admission routes2
Has abstractyes

Explore more

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