Literature DB >> 28115502

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

Patrick Munk1, Vibe Dalhoff Andersen1, Leonardo de Knegt1, Marie Stengaard Jensen1, Berith Elkær Knudsen1, Oksana Lukjancenko1, Hanne Mordhorst1, Julie Clasen2, Yvonne Agersø1, Anders Folkesson2, Sünje Johanna Pamp1, Håkan Vigre1, Frank Møller Aarestrup3.   

Abstract

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.
© The Author 2016. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy.

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Year:  2016        PMID: 28115502     DOI: 10.1093/jac/dkw415

Source DB:  PubMed          Journal:  J Antimicrob Chemother        ISSN: 0305-7453            Impact factor:   5.790


  29 in total

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2.  Dissecting microbial communities and resistomes for interconnected humans, soil, and livestock.

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3.  Widespread stop-codon recoding in bacteriophages may regulate translation of lytic genes.

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Journal:  Nat Microbiol       Date:  2022-05-26       Impact factor: 30.964

Review 4.  Sequencing-based methods and resources to study antimicrobial resistance.

Authors:  Manish Boolchandani; Alaric W D'Souza; Gautam Dantas
Journal:  Nat Rev Genet       Date:  2019-06       Impact factor: 53.242

5.  The impact of sequencing depth on the inferred taxonomic composition and AMR gene content of metagenomic samples.

Authors:  H Soon Gweon; Liam P Shaw; Jeremy Swann; Nicola De Maio; Manal AbuOun; Rene Niehus; Alasdair T M Hubbard; Mike J Bowes; Mark J Bailey; Tim E A Peto; Sarah J Hoosdally; A Sarah Walker; Robert P Sebra; Derrick W Crook; Muna F Anjum; Daniel S Read; Nicole Stoesser
Journal:  Environ Microbiome       Date:  2019-10-24

6.  The association between measurements of antimicrobial use and resistance in the faeces microbiota of finisher batches.

Authors:  V D Andersen; L V DE Knegt; P Munk; M S Jensen; Y Agersø; F M Aarestrup; H Vigre
Journal:  Epidemiol Infect       Date:  2017-06-27       Impact factor: 4.434

7.  Validation of the register-based lifetime antimicrobial usage measurement for finisher batches based on comparison with recorded antimicrobial usage at farm level.

Authors:  V D Andersen; P Munk; L V de Knegt; M S Jensen; F M Aarestrup; H Vigre
Journal:  Epidemiol Infect       Date:  2018-02-07       Impact factor: 4.434

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

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10.  The In-Feed Antibiotic Carbadox Induces Phage Gene Transcription in the Swine Gut Microbiome.

Authors:  Timothy A Johnson; Torey Looft; Andrew J Severin; Darrell O Bayles; Daniel J Nasko; K Eric Wommack; Adina Howe; Heather K Allen
Journal:  mBio       Date:  2017-08-08       Impact factor: 7.867

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