A sampling and metagenomic sequencing-based methodology for monitoring antimicrobial resistance in swine herds

J Antimicrob Chemother. 2017 Feb;72(2):385-392. doi: 10.1093/jac/dkw415. Epub 2016 Nov 8.


Objectives: Reliable methods for monitoring antimicrobial resistance (AMR) in livestock and other reservoirs are essential to understand the trends, transmission and importance of agricultural resistance. Quantification of AMR is mostly done using culture-based techniques, but metagenomic read mapping shows promise for quantitative resistance monitoring.

Methods: We evaluated the ability of: (i) MIC determination for Escherichia coli; (ii) cfu counting of E. coli; (iii) cfu counting of aerobic bacteria; and (iv) metagenomic shotgun sequencing to predict expected tetracycline resistance based on known antimicrobial consumption in 10 Danish integrated slaughter pig herds. In addition, we evaluated whether fresh or manure floor samples constitute suitable proxies for intestinal sampling, using cfu counting, qPCR and metagenomic shotgun sequencing.

Results: Metagenomic read-mapping outperformed cultivation-based techniques in terms of predicting expected tetracycline resistance based on antimicrobial consumption. Our metagenomic approach had sufficient resolution to detect antimicrobial-induced changes to individual resistance gene abundances. Pen floor manure samples were found to represent rectal samples well when analysed using metagenomics, as they contain the same DNA with the exception of a few contaminating taxa that proliferate in the extraintestinal environment.

Conclusions: We present a workflow, from sampling to interpretation, showing how resistance monitoring can be carried out in swine herds using a metagenomic approach. We propose metagenomic sequencing should be part of routine livestock resistance monitoring programmes and potentially of integrated One Health monitoring in all reservoirs.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Bacteria / drug effects*
  • Bacteria / genetics*
  • Colony Count, Microbial
  • Denmark
  • Environmental Microbiology
  • Epidemiological Monitoring
  • Feces / microbiology*
  • Metagenomics / methods*
  • Microbial Sensitivity Tests
  • Real-Time Polymerase Chain Reaction
  • Swine / microbiology*
  • Tetracycline Resistance*