Characterization of the resistome in manure, soil and wastewater from dairy and beef production systems

Noelle R. Noyes, Xiang Yang, Lyndsey M. Linke, Roberta J. Magnuson, Shaun R. Cook, Rahat Zaheer, Hua Yang, Dale R. Woerner, Ifigenia Geornaras, Jessica A. McArt, Sheryl P. Gow, Jaime Ruiz, Kenneth L. Jones, Christina A. Boucher, Tim A. McAllister, Keith E. Belk, Paul S. Morley

Research output: Contribution to journalArticlepeer-review

45 Scopus citations

Abstract

It has been proposed that livestock production effluents such as wastewater, airborne dust and manure increase the density of antimicrobial resistant bacteria and genes in the environment. The public health risk posed by this proposed outcome has been difficult to quantify using traditional microbiological approaches. We utilized shotgun metagenomics to provide a first description of the resistome of North American dairy and beef production effluents, and identify factors that significantly impact this resistome. We identified 34 mechanisms of antimicrobial drug resistance within 34 soil, manure and wastewater samples from feedlot, ranch and dairy operations. The majority of resistance-associated sequences found in all samples belonged to tetracycline resistance mechanisms. We found that the ranch samples contained significantly fewer resistance mechanisms than dairy and feedlot samples, and that the resistome of dairy operations differed significantly from that of feedlots. The resistome in soil, manure and wastewater differed, suggesting that management of these effluents should be tailored appropriately. By providing a baseline of the cattle production waste resistome, this study represents a solid foundation for future efforts to characterize and quantify the public health risk posed by livestock effluents.

Original languageEnglish (US)
Article number24645
JournalScientific reports
Volume6
DOIs
StatePublished - Apr 20 2016

Bibliographical note

Funding Information:
The authors thank all of the livestock operations that allowed us access to their facilities to obtain samples. The authors also acknowledge Erin Petrilli and the Colorado State University Next Generation Sequencing Core for their assistance. This project was supported by a grant from the Colorado State University Infectious Disease Supercluster. N.N. was supported by NIH T32OD012201.

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