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Record W2970283910 · doi:10.1186/s12866-019-1548-x

Comparative diversity of microbiomes and Resistomes in beef feedlots, downstream environments and urban sewage influent

2019· article· en· W2970283910 on OpenAlex
Rahat Zaheer, Steven M. Lakin, Rodrigo Ortega Polo, Shaun R. Cook, Francis J. Larney, Paul S. Morley, Calvin W. Booker, Sherry J. Hannon, Gary Van Domselaar, Ron Read, Tim A. McAllister

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

VenueBMC Microbiology · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsUniversity of CalgaryPublic Health Agency of CanadaAlberta Health ServicesAlberta Ministry of Agriculture and ForestryAgriculture Food and Rural DevelopmentAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food CanadaBeef Cattle Research CouncilMcGill UniversityAustralian GovernmentGénome QuébecNational Institutes of HealthGovernment of Canada
KeywordsResistomeMetagenomicsBiologyMicrobiomeSewageAntibiotic resistanceFirmicutesTetracyclineVeterinary medicineMicrobiologyAntibioticsIntegronBacteriaEnvironmental scienceEnvironmental engineeringBioinformatics

Abstract

fetched live from OpenAlex

BACKGROUND: Comparative knowledge of microbiomes and resistomes across environmental interfaces between animal production systems and urban settings is lacking. In this study, we executed a comparative analysis of the microbiota and resistomes of metagenomes from cattle feces, catch basin water, manured agricultural soil and urban sewage. RESULTS: Metagenomic DNA from composite fecal samples (FC; n = 12) collected from penned cattle at four feedlots in Alberta, Canada, along with water from adjacent catchment basins (CB; n = 13), soil (n = 4) from fields in the vicinity of one of the feedlots and urban sewage influent (SI; n = 6) from two municipalities were subjected to Illumina HiSeq2000 sequencing. Firmicutes exhibited the highest prevalence (40%) in FC, whereas Proteobacteria were most abundant in CB (64%), soil (60%) and SI (83%). Among sample types, SI had the highest diversity of antimicrobial resistance (AMR), and metal and biocide resistance (MBR) classes (13 & 15) followed by FC (10 & 8), CB (8 & 4), and soil (6 & 1). The highest antimicrobial resistant (AMR) gene (ARG) abundance was harboured by FC, whereas soil samples had a very small, but unique resistome which did not overlap with FC & CB resistomes. In the beef production system, tetracycline resistance predominated followed by macrolide resistance. The SI resistome harboured β-lactam, macrolide, tetracycline, aminoglycoside, fluoroquinolone and fosfomycin resistance determinants. Metal and biocide resistance accounted for 26% of the SI resistome with a predominance of mercury resistance. CONCLUSIONS: This study demonstrates an increasing divergence in the nature of the microbiome and resistome as the distance from the feedlot increases. Consistent with antimicrobial use, tetracycline and macrolide resistance genes were predominant in the beef production system. One of the feedlots contributed both conventional (raised with antibiotics) and natural (raised without antibiotics) pens samples. Although natural pen samples exhibited a microbiota composition that was similar to samples from conventional pens, their resistome was less complex. Similarly, the SI resistome was indicative of drug classes used in humans and the greater abundance of mercury resistance may be associated with contamination of municipal water with household and industrial products.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.387
Threshold uncertainty score0.579

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 science0.0000.001
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 head0.018
GPT teacher head0.246
Teacher spread0.228 · 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