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, Calvin W. Booker, Dale R. Woerner, Keith E. Belk, Paul S. Morley

Research output: Contribution to journalArticlepeer-review

36 Scopus citations


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.

Original languageEnglish (US)
Article number1980
JournalFrontiers in Microbiology
StatePublished - Sep 4 2019

Bibliographical note

Funding Information:
We gratefully acknowledge the feedlot and dairy farms operators for allowing us access to their facilities. Special thanks to Dr. Sherry Hannon and Courtney Stamm (Feedlot Health Management Services), and Shaun R. Cook for facilitating sample collection and processing in Canada. Thanks are also extended to personal at Feedlot Health Management Services and Lethbridge Research and Development Centre for assistance during collection and handling of samples. Funding. This research was supported by the United States Department of Agriculture National Institute of Food in Agriculture (USDA NIFA) awards 2015-68003-23048 awarded to Principal Investigators PM and KB (Microbial Ecology Group, Colorado State University, Fort Collins, CO, United States). Work at Lethbridge was supported by the Genomics Research and Development Initiative of Agriculture and Agri-Food Canada and Beef Cluster funding.

Publisher Copyright:
© Copyright © 2019 Rovira, McAllister, Lakin, Cook, Doster, Noyes, Weinroth, Yang, Parker, Boucher, Booker, Woerner, Belk and Morley.


  • antibiotic resistance
  • cattle
  • metagenomics
  • microbiome
  • resistome


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