1887

Abstract

Enterobacterales from livestock are potentially important reservoirs for antimicrobial resistance (AMR) to pass through the food chain to humans, thereby increasing the AMR burden and affecting our ability to tackle infections. In this study 168 isolates from four genera of the order , primarily , were purified from livestock (cattle, pigs and sheep) faeces from 14 farms in the United Kingdom. Their genomes were resolved using long- and short-read sequencing to analyse AMR genes and their genetic context, as well as to explore the relationship between AMR burden and on-farm antimicrobial usage (AMU), in the three months prior to sampling. Although isolates were genomically diverse, phylogenetic analysis using a core-genome SNP tree indicated pig isolates to generally be distinct from sheep isolates, with cattle isolates being intermediates. Approximately 28 % of isolates harboured AMR genes, with the greatest proportion detected in pigs, followed by cattle then sheep; pig isolates also harboured the highest number of AMR genes per isolate. Although 90 % of sequenced isolates harboured diverse plasmids, only 11 % of plasmids (=58 out of 522) identified contained AMR genes, with 91 % of AMR plasmids being from pig, 9 % from cattle and none from sheep isolates; these results indicated that pigs were a principle reservoir of AMR genes harboured by plasmids and likely to be involved in their horizontal transfer. Significant associations were observed between AMU (mg kg) and AMR. As both the total and the numbers of different antimicrobial classes used on-farm increased, the risk of multi-drug resistance (MDR) in isolates rose. However, even when AMU on pig farms was comparatively low, pig isolates had increased likelihood of being MDR; harbouring relatively more resistances than those from other livestock species. Therefore, our results indicate that AMR prevalence in livestock is not only influenced by recent AMU on-farm but also livestock-related factors, which can influence the AMR burden in these reservoirs and its plasmid mediated transmission.

Funding
This study was supported by the:
  • National Institute for Health Research Health Protection Research Unit (NIHR HPRU) in Healthcare Associated Infections and Antimicrobial Resistance at the University of Oxford in partnership with Public Health England (PHE) (Award NIHR200915)
    • Principle Award Recipient: DerrickW Crook
  • Antimicrobial Resistance Cross-council Initiative (Award NE/N019989/1)
    • Principle Award Recipient: DerrickW Crook
  • This is an open-access article distributed under the terms of the Creative Commons Attribution License. This article was made open access via a Publish and Read agreement between the Microbiology Society and the corresponding author’s institution.
Loading

Article metrics loading...

/content/journal/mgen/10.1099/mgen.0.000630
2021-10-05
2024-05-04
Loading full text...

Full text loading...

/deliver/fulltext/mgen/7/10/mgen000630.html?itemId=/content/journal/mgen/10.1099/mgen.0.000630&mimeType=html&fmt=ahah

References

  1. World Health Organisation World Health Organization Antimicrobial Resistance: Global Report on Surveillance Geneva, Switzerland: WHO; 2014
    [Google Scholar]
  2. O’Neill J. The review of antimicrobial resistance; 2016 https://amr-review.org
  3. AbuOun M, O’Connor HM, Stubberfield EJ, Nunez-Garcia J, Sayers E et al. Characterizing antimicrobial resistant Escherichia coli and associated risk factors in a cross-sectional study of pig farms in Great Britain. Front Microbiol 2020; 11:861 [View Article] [PubMed]
    [Google Scholar]
  4. Chantziaras I, Boyen F, Callens B, Dewulf J. Correlation between veterinary antimicrobial use and antimicrobial resistance in food-producing animals: a report on seven countries. J Antimicrob Chemother 2014; 69:827–834 [View Article] [PubMed]
    [Google Scholar]
  5. UK-VARSS UK Veterinary Antibiotic Resistance and Sales Surveillance Report (UK-VARSS 2017) New Haw, Addlestone: Veterinary Medicines Directorate2018;
    [Google Scholar]
  6. UK-VARSS UK Veterinary Antibiotic Resistance and Sales Surveillance Report (UK-VARSS 2018) New Haw, Addlestone: Veterinary Medicines Directorate2019;
    [Google Scholar]
  7. Kirchner M, Lemma F, Randall L, Anjum MF. Loop-mediated isothermal amplification for extended spectrum beta-lactamase gene detection in poultry carcase. Vet Rec 2017; 181:119 [View Article] [PubMed]
    [Google Scholar]
  8. Anjum MF, Choudhary S, Morrison V, Snow LC, Mafura M et al. Identifying antimicrobial resistance genes of human clinical relevance within Salmonella isolated from food animals in Great Britain. J Antimicrob Chemother 2011; 66:550–559 [View Article] [PubMed]
    [Google Scholar]
  9. Card R, Vaughan K, Bagnall M, Spiropoulos J, Cooley W et al. Virulence Characterisation of Salmonella enterica Isolates of Differing Antimicrobial Resistance Recovered from UK Livestock and Imported Meat Samples. Front Microbiol 2016; 7:640 [View Article] [PubMed]
    [Google Scholar]
  10. Duggett NA, Sayers E, AbuOun M, Ellis RJ, Nunez-Garcia J et al. Occurrence and characterization of mcr-1-harbouring Escherichia coli isolated from pigs in Great Britain from 2013 to 2015. J Antimicrob Chemother 2017; 72:691–695 [View Article] [PubMed]
    [Google Scholar]
  11. Randall LP, Lemma F, Rogers JP, Cheney TE, Powell LF et al. Prevalence of extended-spectrum-beta-lactamase-producing Escherichia coli from pigs at slaughter in the UK in 2013. J Antimicrob Chemother 2014; 69:2947–2950 [View Article] [PubMed]
    [Google Scholar]
  12. Szmolka A, Anjum MF, La Ragione RM, Kaszanyitzky EJ, Nagy B. Microarray based comparative genotyping of gentamicin resistant Escherichia coli strains from food animals and humans. Vet Microbiol 2012; 156:110–118 [View Article] [PubMed]
    [Google Scholar]
  13. Hopkins KL, Batchelor MJ, Anjum M, Davies RH, Threlfall EJ. Comparison of antimicrobial resistance genes in nontyphoidal salmonellae of serotypes enteritidis, hadar, and virchow from humans and food-producing animals in England and wales. Microb Drug Resist 2007; 13:281–288 [View Article] [PubMed]
    [Google Scholar]
  14. Munk P, Knudsen BE, Lukjancenko O, Duarte ASR, Van Gompel L et al. Abundance and diversity of the faecal resistome in slaughter pigs and broilers in nine European countries. Nat Microbiol 2018; 3:898–908 [View Article] [PubMed]
    [Google Scholar]
  15. Frost LS, Leplae R, Summers AO, Toussaint A. Mobile genetic elements: the agents of open source evolution. Nat Rev Microbiol 2005; 3:722–732 [View Article] [PubMed]
    [Google Scholar]
  16. Carattoli A. Resistance plasmid families in Enterobacteriaceae. Antimicrob Agents Chemother 2009; 53:2227–2238 [View Article] [PubMed]
    [Google Scholar]
  17. Shintani M, Sanchez ZK, Kimbara K. Genomics of microbial plasmids: classification and identification based on replication and transfer systems and host taxonomy. Front Microbiol 2015; 6:242 [View Article] [PubMed]
    [Google Scholar]
  18. Day MJ, Rodriguez I, van Essen-Zandbergen A, Dierikx C, Kadlec K et al. Diversity of STs, plasmids and ESBL genes among Escherichia coli from humans, animals and food in Germany, the Netherlands and the UK. J Antimicrob Chemother 2016; 71:1178–1182 [View Article] [PubMed]
    [Google Scholar]
  19. Rozwandowicz M, Brouwer MSM, Fischer J, Wagenaar JA, Gonzalez-Zorn B. Plasmids carrying antimicrobial resistance genes in Enterobacteriaceae. J Antimicrob Chemother 2018; 73:1121–1137 [View Article] [PubMed]
    [Google Scholar]
  20. Duggett N, AbuOun M, Randall L, Horton R, Lemma F. The importance of using whole genome sequencing and extended spectrum beta-lactamase selective media when monitoring antimicrobial resistance. Sci Rep 2020; 10:19880 [View Article] [PubMed]
    [Google Scholar]
  21. Livestock Demographic Data Group (Pig) Livestock demographic data group: pig population report. Weybridge: Animal and Plant Health Agency; 2017
  22. Livestock Demographic Data Group (Cattle) Livestock demographic data group: cattle population report. Weybridge 2017. Report No.: CP16/17: 2017
  23. Livestock Demographic Data Group (Sheep) Livestock demographic data group: sheep population report. Weybridge: Animal and Plant Health Agency 2018. Report No.: SP17/18; 2018
  24. Edwards KJ, Logan JM, Langham S, Swift C, Gharbia SE. Utility of real-time amplification of selected 16S rRNA gene sequences as a tool for detection and identification of microbial signatures directly from clinical samples. J Med Microbiol 2012; 61:645–652 [View Article] [PubMed]
    [Google Scholar]
  25. Shaw LP, Chau KK, Kavanagh J, AbuOun M, Stubberfield E et al. Niche and local geography shape the pangenome of wastewater- and livestock-associated Enterobacteriaceae. bioRxiv 2020
    [Google Scholar]
  26. De Maio N, Shaw LP, Hubbard A, George S, Sanderson ND. Comparison of long-read sequencing technologies in the hybrid assembly of complex bacterial genomes. Microb Genom 2019; 5: [View Article] [PubMed]
    [Google Scholar]
  27. Wood DE, Salzberg SL. Kraken: ultrafast metagenomic sequence classification using exact alignments. Genome Biol 2014; 15:R46 [View Article] [PubMed]
    [Google Scholar]
  28. Wick RR, Judd LM, Gorrie CL, Holt KE. Unicycler: Resolving bacterial genome assemblies from short and long sequencing reads. PLoS Comput Biol 2017; 13:e1005595 [View Article] [PubMed]
    [Google Scholar]
  29. Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics 2014; 30:2068–2069 [View Article] [PubMed]
    [Google Scholar]
  30. Beghain J, Bridier-Nahmias A, Le Nagard H, Denamur E, Clermont O. ClermonTyping: an easy-to-use and accurate in silico method for Escherichia genus strain phylotyping. Microb Genom 2018; 4: [View Article] [PubMed]
    [Google Scholar]
  31. Wirth T, Falush D, Lan R, Colles F, Mensa P. Sex and virulence in Escherichia coli: an evolutionary perspective. Mol Microbiol 2006; 60:1136–1151 [View Article] [PubMed]
    [Google Scholar]
  32. Inouye M, Dashnow H, Raven LA, Schultz MB, Pope BJ. SRST2: Rapid genomic surveillance for public health and hospital microbiology labs. Genome Med 2014; 6:90 [View Article] [PubMed]
    [Google Scholar]
  33. Larsen MV, Cosentino S, Rasmussen S, Friis C, Hasman H. Multilocus sequence typing of total-genome-sequenced bacteria. J Clin Microbiol 2012; 50:1355–1361 [View Article] [PubMed]
    [Google Scholar]
  34. Jolley KA, Bray JE, Maiden MCJ. Open-access bacterial population genomics: BIGSdb software, the PubMLST.org website and their applications. Wellcome Open Res 2018; 3:124 [View Article] [PubMed]
    [Google Scholar]
  35. Didelot X, Falush D. Inference of bacterial microevolution using multilocus sequence data. Genetics 2007; 175:1251–1266 [View Article] [PubMed]
    [Google Scholar]
  36. Letunic I, Bork P. Interactive Tree Of Life (iTOL): an online tool for phylogenetic tree display and annotation. Bioinformatics 2007; 23:127–128 [View Article] [PubMed]
    [Google Scholar]
  37. Carattoli A, Zankari E, Garcia-Fernandez A, Voldby Larsen M, Lund O. In silico detection and typing of plasmids using PlasmidFinder and plasmid multilocus sequence typing. Antimicrob Agents Chemother 2014; 58:3895–3903 [View Article] [PubMed]
    [Google Scholar]
  38. Anjum MF, Duggett NA, AbuOun M, Randall L, Nunez-Garcia J. Colistin resistance in Salmonella and Escherichia coli isolates from a pig farm in Great Britain. J Antimicrob Chemother 2016; 71:2306–2313 [View Article] [PubMed]
    [Google Scholar]
  39. Stubberfield E, AbuOun M, Sayers E, O’Connor HM, Card RM et al. Use of whole genome sequencing of commensal Escherichia coli in pigs for antimicrobial resistance surveillance, United Kingdom, 2018. Euro Surveill 2019; 24:50
    [Google Scholar]
  40. Sullivan MJ, Petty NK, Beatson SA. Easyfig: a genome comparison visualizer. Bioinformatics 2011; 27:1009–1010 [View Article] [PubMed]
    [Google Scholar]
  41. Pierce NT, Irber L, Reiter T, Brooks P, Brown CT. Large-scale sequence comparisons with sourmash. F1000Res 2019; 8:1006 [View Article] [PubMed]
    [Google Scholar]
  42. Laczny CC, Galata V, Plum A, Posch AE, Keller A. Assessing the heterogeneity of in silico plasmid predictions based on whole-genome-sequenced clinical isolates. Brief Bioinform 2019; 20:857–865 [View Article] [PubMed]
    [Google Scholar]
  43. Robertson J, Nash JHE. MOB-suite: software tools for clustering, reconstruction and typing of plasmids from draft assemblies. Microb Genom 2018; 4: [View Article] [PubMed]
    [Google Scholar]
  44. Page AJ, Cummins CA, Hunt M, Wong VK, Reuter S. Roary: rapid large-scale prokaryote pan genome analysis. Bioinformatics 2015; 31:3691–3693 [View Article] [PubMed]
    [Google Scholar]
  45. National Office of Animal Health NOAH Compendium; 2017 http://www.noahcompendium.co.uk/datasheets
  46. Manges AR, Geum HM, Guo A, Edens TJ, Fibke CD. Global extraintestinal pathogenic Escherichia coli (ExPEC) lineages. Clin Microbiol Rev 2019; 32: [View Article] [PubMed]
    [Google Scholar]
  47. Pop-Vicas A, Opal SM. The clinical impact of multidrug-resistant Gram-negative bacilli in the management of septic shock. Virulence 2014; 5:206–212 [View Article] [PubMed]
    [Google Scholar]
  48. Wuthrich D, Brilhante M, Hausherr A, Becker J, Meylan M et al. A novel trimethoprim resistance gene, dfrA36, characterized from Escherichia coli from calves. mSphere 2019; 4:
    [Google Scholar]
  49. Tyson GH, Li C, Hsu CH, Bodeis-Jones S, McDermott PF. Diverse fluoroquinolone resistance plasmids from retail meat E. coli in the United States. Front Microbiol 2019; 10:2826 [View Article] [PubMed]
    [Google Scholar]
  50. EFSA and ECDC The European Union summary report on antimicrobial resistance in zoonotic and indicator bacteria from humans, animals and food in 2017 in: EFSA (European Food Safety Authority) and ECDC (European Centre for Disease Prevention and Control), editor. EFSA Journal 20175598–5876
    [Google Scholar]
  51. Decano AG, Ludden C, Feltwell T, Judge K, Parkhill J et al. Complete assembly of Escherichia coli sequence type 131 genomes using long reads demonstrates antibiotic resistance gene variation within diverse plasmid and chromosomal contexts. mSphere 2019; 4: [View Article] [PubMed]
    [Google Scholar]
  52. Reid CJ, Roy Chowdhury P, Djordjevic SP. Tn6026 and Tn6029 are found in complex resistance regions mobilised by diverse plasmids and chromosomal islands in multiple antibiotic resistant Enterobacteriaceae. Plasmid 2015; 80:127–137 [View Article] [PubMed]
    [Google Scholar]
  53. Roy Chowdhury P, McKinnon J, Liu M, Djordjevic SP. Multidrug resistant uropathogenic Escherichia coli ST405 with a novel, composite IS26 transposon in a unique chromosomal location. Front Microbiol 2018; 9:3212 [View Article] [PubMed]
    [Google Scholar]
  54. Matlock W, Chau K, AbuOun M, Stubberfield E, Barker L et al. Genomic network analysis of an environmental and livestock IncF plasmid populations. ISME J 2021 [View Article]
    [Google Scholar]
  55. Monnet DL, Lopez-Lozano JM, Campillos P, Burgos A, Yague A. Making sense of antimicrobial use and resistance surveillance data: application of ARIMA and transfer function models. Clin Microbiol Infect 2001; 7:29–36 [View Article] [PubMed]
    [Google Scholar]
  56. Moller JK. Antimicrobial usage and microbial resistance in a university hospital during a seven-year period. J Antimicrob Chemother 1989; 24:983–992 [View Article] [PubMed]
    [Google Scholar]
  57. European Medicines Agency Sales of veterinary antimicrobial agents in 31 European countries in 2017 (ESVAC Report. In European Surveillance of Veterinary Antimicrobial Consumption 2019
    [Google Scholar]
http://instance.metastore.ingenta.com/content/journal/mgen/10.1099/mgen.0.000630
Loading
/content/journal/mgen/10.1099/mgen.0.000630
Loading

Data & Media loading...

Supplements

Loading data from figshare Loading data from figshare
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error