1887

Abstract

Antimicrobial resistance (AMR) has become a critical threat to public health worldwide. The use of antimicrobials in food and livestock agriculture, including the production of poultry, is thought to contribute to the dissemination of antibiotic resistant bacteria (ARB) and the genes and plasmids that confer the resistant phenotype (ARG). However, the relative contribution of each of these processes to the emergence of resistant pathogens in poultry production and their potential role in the transmission of resistant pathogens in human infections, requires a deeper understanding of the dynamics of ARB and ARG in food production and the factors involved in the increased risk of transmission.

Funding
This study was supported by the:
  • Ontario Veterinary College, University of Guelph
    • Principle Award Recipient: BenjaminM Hetman
  • Genome Canada
    • Principle Award Recipient: NotApplicable
  • This is an open-access article distributed under the terms of the Creative Commons Attribution License.
Loading

Article metrics loading...

/content/journal/mgen/10.1099/mgen.0.000891
2022-11-23
2024-06-25
Loading full text...

Full text loading...

/deliver/fulltext/mgen/8/11/mgen000891.html?itemId=/content/journal/mgen/10.1099/mgen.0.000891&mimeType=html&fmt=ahah

References

  1. O’Neill J. Tackling drug-resistant infections globally: final report and recommendations; 2016 http://amr-review.org accessed 12 March 2021
  2. Topp E. Agriculture and Agri-Food Canada’s research program on antimicrobial resistance. Can Commun Dis Rep 2017; 43:224–227 [View Article] [PubMed]
    [Google Scholar]
  3. Thanner S, Drissner D, Walsh F. Antimicrobial Resistance in Agriculture. mBio 2016; 7:e02227–15 [View Article] [PubMed]
    [Google Scholar]
  4. Carattoli A. Resistance plasmid families in Enterobacteriaceae. Antimicrob Agents Chemother 2009; 53:2227–2238 [View Article] [PubMed]
    [Google Scholar]
  5. Marquez-Ortiz RA, Haggerty L, Olarte N, Duarte C, Garza-Ramos U et al. Genomic Epidemiology of NDM-1-Encoding Plasmids in Latin American Clinical Isolates Reveals Insights into the Evolution of Multidrug Resistance. Genome Biol Evol 2017; 9:1725–1741 [View Article] [PubMed]
    [Google Scholar]
  6. Woodford N, Turton JF, Livermore DM. Multiresistant Gram-negative bacteria: the role of high-risk clones in the dissemination of antibiotic resistance. FEMS Microbiol Rev 2011; 35:736–755 [View Article] [PubMed]
    [Google Scholar]
  7. Wetterstrand KA. DNA sequencing costs: data from the NHGRI large-scale genome sequencing program; 2019 https://www.genome.gov/about-genomics/fact-sheets/Sequencing-Human-Genome-cost accessed 13 April 2021
  8. Rumore J, Tschetter L, Kearney A, Kandar R, McCormick R et al. Evaluation of whole-genome sequencing for outbreak detection of Verotoxigenic Escherichia coli O157:H7 from the Canadian perspective. BMC Genomics 2018; 19:870 [View Article] [PubMed]
    [Google Scholar]
  9. Nadon C, Van Walle I, Gerner-Smidt P, Campos J, Chinen I et al. PulseNet International: Vision for the implementation of whole genome sequencing (WGS) for global food-borne disease surveillance. Euro Surveill 2017; 22:307–316 [View Article] [PubMed]
    [Google Scholar]
  10. Ronholm J, Nasheri N, Petronella N, Pagotto F. Navigating Microbiological Food Safety in the Era of Whole-Genome Sequencing. Clin Microbiol Rev 2016; 29:837–857 [View Article] [PubMed]
    [Google Scholar]
  11. Silva M, Machado MP, Silva DN, Rossi M, Moran-Gilad J et al. chewBBACA: A complete suite for gene-by-gene schema creation and strain identification. Microb Genom 2018; 4: [View Article] [PubMed]
    [Google Scholar]
  12. Zhou Z, Alikhan N-F, Sergeant MJ, Luhmann N, Vaz C et al. GrapeTree: visualization of core genomic relationships among 100,000 bacterial pathogens. Genome Res 2018; 28:1395–1404 [View Article] [PubMed]
    [Google Scholar]
  13. McArthur AG, Waglechner N, Nizam F, Yan A, Azad MA et al. The comprehensive antibiotic resistance database. Antimicrob Agents Chemother 2013; 57:3348–3357 [View Article] [PubMed]
    [Google Scholar]
  14. Clausen PTLC, Zankari E, Aarestrup FM, Lund O. Benchmarking of methods for identification of antimicrobial resistance genes in bacterial whole genome data. J Antimicrob Chemother 2016; 71:2484–2488 [View Article] [PubMed]
    [Google Scholar]
  15. Hunt M, Mather AE, Sánchez-Busó L, Page AJ, Parkhill J et al. ARIBA: rapid antimicrobial resistance genotyping directly from sequencing reads. Microb Genom 2017; 3:e000131 [View Article] [PubMed]
    [Google Scholar]
  16. Dohoo I, Martin W, Stryhn H. Methods in Epidemiologic Research Prince Edward Island, Canada: VER, Inc; 2012
    [Google Scholar]
  17. Public Health Agency of Canada National Enteric Surveillance Program (NESP),Annual Report; 2016 http://publications.gc.ca/collections/collection_2018/aspc-phac/HP37-15-2016-eng.pdf
  18. Canadian Integrated Program for Antimicrobial Resistance Surveillance (CIPARS): Annual Report; 2016 https://publications.gc.ca/collections/collection_2018/aspc-phac/HP2-4-2016-eng.pdf accessed 4 June 2021
  19. Dutil L, Irwin R, Finley R, Ng LK, Avery B et al. Ceftiofur resistance in Salmonella enterica serovar Heidelberg from chicken meat and humans, Canada. Emerg Infect Dis 2010; 16:148–54
    [Google Scholar]
  20. Edirmanasinghe R, Finley R, Parmley EJ, Avery BP, Carson C et al. A whole-genome sequencing approach to study cefoxitin-resistant salmonella enterica serovar heidelberg isolates from various sources. Antimicrob Agents Chemother 2017; 61:e01919-16 [View Article]
    [Google Scholar]
  21. Bekal S, Berry C, Reimer AR, Van Domselaar G, Beaudry G et al. Usefulness of High-Quality Core Genome Single-Nucleotide Variant Analysis for Subtyping the Highly Clonal and the Most Prevalent Salmonella enterica Serovar Heidelberg Clone in the Context of Outbreak Investigations. J Clin Microbiol 2016; 54:289–295 [View Article] [PubMed]
    [Google Scholar]
  22. Canadian Integrated Program for Antimicrobial Resistance Surveillance (CIPARS): Annual Report; 2013 http://publications.gc.ca/collections/collection_2015/aspc-phac/HP2-4-2013-1-eng.pdf accessed 1 January 2021
  23. National microbiological baseline study in broiler chicken December 2012- December 2013; 2016 https://inspection.canada.ca/DAM/DAM-food-aliments/STAGING/text-texte/chem_testing_report_2012-2013_broiler_chicken_1471382238248_eng.pdf accessed 5 July 2021
  24. Huber L, Agunos A, Gow SP, Carson CA, Van Boeckel TP. Reduction in antimicrobial use and resistance to Salmonella, Campylobacter, and Escherichia coli in Broiler Chickens, Canada, 2013-2019. Emerg Infect Dis 2021; 27:2434–2444 [View Article]
    [Google Scholar]
  25. Hetman B. Bioinformatic analysis and STATA code and dataset for analysis of S. Heidelberg in Ontario 2013 Epub ahead of printOctober18 2021 [View Article]
    [Google Scholar]
  26. Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol 2012; 19:455–477 [View Article] [PubMed]
    [Google Scholar]
  27. Zankari E, Hasman H, Cosentino S, Vestergaard M, Rasmussen S et al. Identification of acquired antimicrobial resistance genes. J Antimicrob Chemother 2012; 67:2640–2644 [View Article] [PubMed]
    [Google Scholar]
  28. Robertson J, Nash JHE. MOB-suite: software tools for clustering, reconstruction and typing of plasmids from draft assemblies. Microb Genom 2018; 4:1–7 [View Article] [PubMed]
    [Google Scholar]
  29. Ondov BD, Treangen TJ, Melsted P, Mallonee AB, Bergman NH et al. Mash: fast genome and metagenome distance estimation using MinHash. Genome Biol 2016; 17:132 [View Article]
    [Google Scholar]
  30. Hunt M, Silva ND, Otto TD, Parkhill J, Keane JA et al. Circlator: automated circularization of genome assemblies using long sequencing reads. Genome Biol 2015; 16:294 [View Article]
    [Google Scholar]
  31. Treangen TJ, Ondov BD, Koren S, Phillippy AM. The Harvest suite for rapid core-genome alignment and visualization of thousands of intraspecific microbial genomes. Genome Biol 2014; 15:11 [View Article] [PubMed]
    [Google Scholar]
  32. van Belkum A, Tassios PT, Dijkshoorn L, Haeggman S, Cookson B et al. Guidelines for the validation and application of typing methods for use in bacterial epidemiology. Clin Microbiol Infect 2007; 13 Suppl 3:1–46 [View Article] [PubMed]
    [Google Scholar]
  33. Labbé G, Ziebell K, Bekal S, Macdonald KA, Parmley EJ et al. Complete Genome Sequences of 17 Canadian Isolates of Salmonella enterica subsp. enterica Serovar Heidelberg from Human, Animal, and Food Sources. Genome Announc 2016; 4:16–17 [View Article] [PubMed]
    [Google Scholar]
  34. Usongo V, Berry C, Yousfi K, Doualla-Bell F, Labbé G et al. Impact of the choice of reference genome on the ability of the core genome SNV methodology to distinguish strains of Salmonella enterica serovar Heidelberg. PLoS One 2018; 13:e0192233 [View Article]
    [Google Scholar]
  35. Bruen TC, Philippe H, Bryant D. A simple and robust statistical test for detecting the presence of recombination. Genetics 2006; 172:2665–2681 [View Article] [PubMed]
    [Google Scholar]
  36. Simpson EH. Measurement of Diversity. Nature 1949; 163:688 [View Article]
    [Google Scholar]
  37. Hunter PR, Gaston MA. Numerical index of the discriminatory ability of typing systems: an application of Simpson’s index of diversity. J Clin Microbiol 1988; 26:2465–2466 [View Article] [PubMed]
    [Google Scholar]
  38. Pearl DL, Louie M, Chui L, Doré K, Grimsrud KM et al. The use of randomization tests to assess the degree of similarity in PFGE patterns of E. coli O157 isolates from known outbreaks and statistical space-time clusters. Epidemiol Infect 2007; 135:100–109 [View Article] [PubMed]
    [Google Scholar]
  39. StataCorp Stata Statistical Software: Release 14 College Station, TX: StataCorp LP; 2015
    [Google Scholar]
  40. Pearl DL. Making the most of clustered data in laboratory animal research using multi-level models. ILAR J 2014; 55:486–492 [View Article] [PubMed]
    [Google Scholar]
  41. Miller EA, Elnekave E, Flores-Figueroa C, Johnson A, Kearney A et al. Emergence of a novel salmonella enterica serotype reading clonal group is linked to its expansion in commercial Turkey production, resulting in unanticipated Human illness in North America. mSphere 2020; 5:e00056-20 [View Article]
    [Google Scholar]
  42. Wallace RL, Bulach DM, Jennison AV, Valcanis M, McLure A et al. Molecular characterization of Campylobacter spp. recovered from beef, chicken, lamb and pork products at retail in Australia. PLoS One 2020; 15:e0236889 [View Article]
    [Google Scholar]
  43. Alikhan NF, Zhou Z, Sergeant MJ, Achtman M. A genomic overview of the population structure of Salmonella. PLoS Genet 2018; 14:e1007261 [View Article]
    [Google Scholar]
  44. de Been M, Pinholt M, Top J, Bletz S, Mellmann A et al. Core Genome Multilocus Sequence Typing Scheme for High- Resolution Typing of Enterococcus faecium. J Clin Microbiol 2015; 53:3788–3797 [View Article] [PubMed]
    [Google Scholar]
  45. Pearce ME, Alikhan N-F, Dallman TJ, Zhou Z, Grant K et al. Comparative analysis of core genome MLST and SNP typing within a European Salmonella serovar Enteritidis outbreak. Int J Food Microbiol 2018; 274:1–11 [View Article] [PubMed]
    [Google Scholar]
  46. Rehman MA, Yin X, Persaud-Lachhman MG, Diarra MS. First Detection of a Fosfomycin Resistance Gene, fosA7, in Salmonella enterica Serovar Heidelberg Isolated from Broiler Chickens. Antimicrob Agents Chemother 2017; 61:1–6 [View Article] [PubMed]
    [Google Scholar]
  47. Zhanel GG, Walkty AJ, Karlowsky JA. Fosfomycin: A First-Line Oral Therapy for Acute Uncomplicated Cystitis. Can J Infect Dis Med Microbiol 2016; 2016:2082693 [View Article] [PubMed]
    [Google Scholar]
  48. Pérez DS, Tapia MO, Soraci AL. Fosfomycin: Uses and potentialities in veterinary medicine. Open Vet J 2014; 4:26–43 [PubMed]
    [Google Scholar]
  49. Falagas ME, Vouloumanou EK, Samonis G, Vardakas KZ. Fosfomycin. Clin Microbiol Rev 2016; 29:321–347 [View Article] [PubMed]
    [Google Scholar]
  50. Barlow M, Hall BG. Origin and evolution of the AmpC beta-lactamases of Citrobacter freundii. Antimicrob Agents Chemother 2002; 46:1190–1198 [View Article]
    [Google Scholar]
  51. Oladeinde A, Cook K, Orlek A, Zock G, Herrington K et al. Hotspot mutations and ColE1 plasmids contribute to the fitness of Salmonella Heidelberg in poultry litter. PLoS ONE 2018; 13:1–36 [View Article] [PubMed]
    [Google Scholar]
http://instance.metastore.ingenta.com/content/journal/mgen/10.1099/mgen.0.000891
Loading
/content/journal/mgen/10.1099/mgen.0.000891
Loading

Data & Media loading...

Supplements

Supplementary material 1

EXCEL
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