Evidence map›Paper›PMID 31555225›Full record

ArticleFrontiers in microbiology2019

Characterization of the Microbial Resistome in Conventional and "Raised Without Antibiotics" Beef and Dairy Production Systems.

Pablo Rovira, Tim McAllister, Steven M Lakin, Shaun R Cook, Enrique Doster, Noelle R Noyes, Maggie D Weinroth, Xiang Yang, Jennifer K Parker, Christina Boucher and 4 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in microbiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers.

0numbers the graph read from it
0cells of the map it votes in
50citing papers in PubMed
4.0field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

50 citing papers in PubMed, 101 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors at 9 institutions in 2 countries.

Pablo RoviraDepartment of Animal Sciences, College of Agricultural Sciences, Colorado State University, Fort Collins, CO, United States.
Tim McAllisterLethbridge Research and Development Centre, Agriculture and Agri-Food Canada, Lethbridge, AB, Canada.
Steven M LakinDepartment of Microbiology, Immunology and Pathology, College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins, CO, United States.
Shaun R CookAlberta Agriculture and Forestry, Lethbridge, AB, Canada.
Enrique DosterDepartment of Microbiology, Immunology and Pathology, College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins, CO, United States.
Noelle R NoyesVeterinary Population Medicine Department, University of Minnesota, St. Paul, MN, United States.
Maggie D WeinrothDepartment of Animal Sciences, College of Agricultural Sciences, Colorado State University, Fort Collins, CO, United States.
Xiang YangDepartment of Animal Sciences, University of California, Davis, Davis, CA, United States.
Jennifer K ParkerDepartment of Molecular Biosciences, University of Texas, Austin, TX, United States.
Christina BoucherDepartment of Computer and Information Science and Engineering, University of Florida, Gainesville, FL, United States.
Calvin W BookerFeedlot Health Management Services, Ltd., Okotoks, AB, Canada.
Dale R WoernerDepartment of Animal and Food Sciences, College of Agricultural Sciences & Natural Resources, Texas Tech University, Lubbock, TX, United States.
Keith E BelkDepartment of Animal Sciences, College of Agricultural Sciences, Colorado State University, Fort Collins, CO, United States.
Paul S MorleyVERO - Veterinary Education, Research, and Outreach Program, Texas A&M University and West Texas A&M University, Canyon, TX, United States.
Colorado State University · USAgriculture and Agri-Food Canada · CAAlberta Health Services · CATexas Tech University · USThe University of Texas at Austin · USUniversity of California, Davis · USUniversity of Florida · USUniversity of Minnesota · USWest Texas A&M University · US

Funding

Veterinary Pre-Doctoral Research Scholars ProgramT32OD012201 · OD · COLORADO STATE UNIVERSITY · PI VANDEWOUDE, SUE · 2013 to 2019
$795k
NIH HHS T32 OD012201
6 · The paper itself

Abstract

Metagenomic investigations have the potential to provide unprecedented insights into microbial ecologies, such as those relating to antimicrobial resistance (AMR). We characterized the microbial resistome in livestock operations raising cattle conventionally (CONV) or without antibiotic exposures (RWA) using shotgun metagenomics. Samples of feces, wastewater from catchment basins, and soil where wastewater was applied were collected from CONV and RWA feedlot and dairy farms. After DNA extraction and sequencing, shotgun metagenomic reads were aligned to reference databases for identification of bacteria (Kraken) and antibiotic resistance genes (ARGs) accessions (MEGARes). Differences in microbial resistomes were found across farms with different production practices (CONV vs. RWA), types of cattle (beef vs. dairy), and types of sample (feces vs. wastewater vs. soil). Feces had the greatest number of ARGs per sample (mean = 118 and 79 in CONV and RWA, respectively), with tetracycline efflux pumps, macrolide phosphotransferases, and aminoglycoside nucleotidyltransferases mechanisms of resistance more abundant in CONV than in RWA feces. Tetracycline and macrolide-lincosamide-streptogramin classes of resistance were more abundant in feedlot cattle than in dairy cow feces, whereas the β-lactam class was more abundant in dairy cow feces. Lack of congruence between ARGs and microbial communities (procrustes analysis) suggested that other factors (e.g., location of farms, cattle source, management practices, diet, horizontal ARGs transfer, and co-selection of resistance), in addition to antimicrobial use, could have impacted resistome profiles. For that reason, we could not establish a cause-effect relationship between antimicrobial use and AMR, although ARGs in feces and effluents were associated with drug classes used to treat animals according to farms' records (tetracyclines and macrolides in feedlots, β-lactams in dairies), whereas ARGs in soil were dominated by multidrug resistance. Characterization of the "resistance potential" of animal-derived and environmental samples is the first step toward incorporating metagenomic approaches into AMR surveillance in agricultural systems. Further research is needed to assess the public-health risk associated with different microbial resistomes.

Indexed as

antibiotic resistancecattlemetagenomicsmicrobiomeresistome

Identifiers

PMID31555225
PMCPMC6736999
OpenAlexW2966978688

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.