Metagenomic characterization of the effect of feed additives on the gut microbiome and antibiotic resistome of feedlot cattle

Milton Thomas, Megan Webb, Sudeep Ghimire, Amanda Blair, Kenneth Olson, Gavin John Fenske, Alex Thomas Fonder, Jane Christopher-Hennings, Derek Brake, Joy Scaria

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39 Scopus citations

Abstract

In North America, antibiotic feed additives such as monensin and tylosin are added to the finishing diets of feedlot cattle to counter the ill-effects of feeding diets with rapidly digestible carbohydrates. While these feed additives have been proven to improve feed efficiency and reduce liver abscess incidence, how these products impact the gastrointestinal microbiota is not completely understood. In this study, we analyzed the impact of providing antibiotic feed additives to feedlot cattle using metagenome sequencing of treated and control animals. Our results indicate that use of antibiotic feed additives does not produce discernable changes at the phylum level. However, treated cattle had reduced abundance of gram-positive bacteria at the genus level. The abundance of Ruminococcus, Erysipelotrichaceae and Lachnospiraceae in the gut of treated steers was reduced. Functional analysis of the data indicates that there was only minimal impact due to the treatment in the rumen. Genes involved in detoxification were significantly increased in the rumen of AB steers. But the relative abundance of these genes was < 0.3%. However, our results did not show any correlation between the presence of antimicrobial resistance genes in the gut microbiota and the administration of antibiotic feed additives.

Original languageEnglish (US)
Article number12257
JournalScientific reports
Volume7
Issue number1
DOIs
StatePublished - Dec 1 2017

Bibliographical note

Funding Information:
This work was supported in part by the USDA National Institute of Food and Agriculture, Hatch projects SD00H532-14 and SD00R540-15, and South Dakota Beef Industry Council grant awarded to JS. The funding agencies had no role in study design, data collection, and interpretation, or the decision to submit the work for publication.

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