Research Open Access
Like 0



Surveillance of commensal , a possible reservoir of antimicrobial resistance (AMR) genes, is important as they pose a risk to human and animal health. Most surveillance activities rely on phenotypic characterisation, but whole genome sequencing (WGS) presents an alternative.


In this retrospective study, we tested 515 isolated from pigs to evaluate the use of WGS to predict resistance phenotype.


Minimum inhibitory concentration (MIC) was determined for nine antimicrobials of clinical and veterinary importance. Deviation from wild-type, fully-susceptible MIC was assessed using European Committee on Antimicrobial Susceptibility Testing (EUCAST) epidemiological cut-off (ECOFF) values. Presence of AMR genes and mutations were determined using APHA SeqFinder. Statistical two-by-two table analysis and Cohen’s kappa (k) test were applied to assess genotype and phenotype concordance.


Overall, correlation of WGS with susceptibility to the nine antimicrobials was 98.9% for test specificity, and 97.5% for the positive predictive value of a test. The overall kappa score (k = 0.914) indicated AMR gene presence was highly predictive of reduced susceptibility and showed excellent correlation with MIC. However, there was variation for each antimicrobial; five showed excellent correlation; four very good and one moderate. Suggested ECOFF adjustments increased concordance between genotypic data and kappa values for four antimicrobials.


WGS is a powerful tool for accurately predicting AMR that can be used for national surveillance purposes. Additionally, it can detect resistance genes from a wider panel of antimicrobials whose phenotypes are currently not monitored but may be of importance in the future.


Article metrics loading...

Loading full text...

Full text loading...



  1. Anjum MF. Screening methods for the detection of antimicrobial resistance genes present in bacterial isolates and the microbiota. Future Microbiol. 2015;10(3):317-20.  https://doi.org/10.2217/fmb.15.2  PMID: 25812454 
  2. Partridge SR, Kwong SM, Firth N, Jensen SO. Mobile Genetic Elements Associated with Antimicrobial Resistance. Clin Microbiol Rev. 2018;31(4):e00088-17.  https://doi.org/10.1128/CMR.00088-17  PMID: 30068738 
  3. Punina NV, Makridakis NM, Remnev MA, Topunov AF. Whole-genome sequencing targets drug-resistant bacterial infections. Hum Genomics. 2015;9(1):19.  https://doi.org/10.1186/s40246-015-0037-z  PMID: 26243131 
  4. European Commission (EC). Commission Implementing Decision 2013/652/EU of 12 November 2013 on the monitoring and reporting of antimicrobial resistance in zonotic and commensal bacteria. L 303/26. 14 Nov 2013. Available from: https://op.europa.eu/en/publication-detail/-/publication/83e1934f-4d39-11e3-ae03-01aa75ed71a1/language-enhttps://publications.europa.eu
  5. European Food Safety Authority (EFSA)/European Centre for Disease Prevention and Control (ECDC).The European Union summary report on antimicrobial resistance in zoonotic and indicator bacteria from humans, animals and food in 2015. EFSA J. 2017;15(2):4694.
  6. Ellington MJ, Ekelund O, Aarestrup FM, Canton R, Doumith M, Giske C, et al. The role of whole genome sequencing in antimicrobial susceptibility testing of bacteria: report from the EUCAST Subcommittee. Clin Microbiol Infect. 2017;23(1):2-22.  https://doi.org/10.1016/j.cmi.2016.11.012  PMID: 27890457 
  7. Duggett NA, Sayers E, AbuOun M, Ellis RJ, Nunez-Garcia J, Randall L, 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(3):691-5.  https://doi.org/10.1093/jac/dkw477  PMID: 27999032 
  8. McArthur AG, Waglechner N, Nizam F, Yan A, Azad MA, Baylay AJ, et al. The comprehensive antibiotic resistance database. Antimicrob Agents Chemother. 2013;57(7):3348-57.  https://doi.org/10.1128/AAC.00419-13  PMID: 23650175 
  9. Zankari E, Hasman H, Cosentino S, Vestergaard M, Rasmussen S, Lund O, et al. Identification of acquired antimicrobial resistance genes. J Antimicrob Chemother. 2012;67(11):2640-4.  https://doi.org/10.1093/jac/dks261  PMID: 22782487 
  10. Do Nascimento V, Day MR, Doumith M, Hopkins KL, Woodford N, Godbole G, et al. Comparison of phenotypic and WGS-derived antimicrobial resistance profiles of enteroaggregative Escherichia coli isolated from cases of diarrhoeal disease in England, 2015-16. J Antimicrob Chemother. 2017;72(12):3288-97.  https://doi.org/10.1093/jac/dkx301  PMID: 28961934 
  11. Moran RA, Anantham S, Holt KE, Hall RM. Prediction of antibiotic resistance from antibiotic resistance genes detected in antibiotic-resistant commensal Escherichia coli using PCR or WGS. J Antimicrob Chemother. 2017;72(3):700-4.  https://doi.org/10.1093/jac/dkw511  PMID: 28039273 
  12. Stoesser N, Batty EM, Eyre DW, Morgan M, Wyllie DH, Del Ojo Elias C, et al. Predicting antimicrobial susceptibilities for Escherichia coli and Klebsiella pneumoniae isolates using whole genomic sequence data. J Antimicrob Chemother. 2013;68(10):2234-44.  https://doi.org/10.1093/jac/dkt180  PMID: 23722448 
  13. Tyson GH, McDermott PF, Li C, Chen Y, Tadesse DA, Mukherjee S, et al. WGS accurately predicts antimicrobial resistance in Escherichia coli. J Antimicrob Chemother. 2015;70(10):2763-9.  https://doi.org/10.1093/jac/dkv186  PMID: 26142410 
  14. Zankari E, Hasman H, Kaas RS, Seyfarth AM, Agersø Y, Lund O, et al. Genotyping using whole-genome sequencing is a realistic alternative to surveillance based on phenotypic antimicrobial susceptibility testing. J Antimicrob Chemother. 2013;68(4):771-7.  https://doi.org/10.1093/jac/dks496  PMID: 23233485 
  15. AbuOun M, Stubberfield EJ, Duggett NA, Kirchner M, Dormer L, Nunez-Garcia J, et al. mcr-1 and mcr-2 variant genes identified in Moraxella species isolated from pigs in Great Britain from 2014 to 2015. J Antimicrob Chemother. 2017;72(10):2745-9.  https://doi.org/10.1093/jac/dkx286  PMID: 29091227 
  16. Andrews JM. Determination of minimum inhibitory concentrations. J Antimicrob Chemother. 2001;48(Suppl 1):5-16.  https://doi.org/10.1093/jac/48.suppl_1.5  PMID: 11420333 
  17. World Health Organization (WHO). Critically Important Antimicrobials for Human Medicine, 5th revision. Geneva: WHO; 2017. Available from: https://www.who.int/foodsafety/publications/antimicrobials-fifth/en/
  18. European Committee on Antimicrobial Susceptibility Testing (EUCAST). Antimicrobial wild type distribution of microorganisms. Basel; EUCAST. [Accessed 2018]. Available from: htts://mic.eucast.org/Eucast2/.
  19. Brown DF, Wootton M, Howe RA. Antimicrobial susceptibility testing breakpoints and methods from BSAC to EUCAST. J Antimicrob Chemother. 2016;71(1):3-5.  https://doi.org/10.1093/jac/dkv287  PMID: 26377864 
  20. Danish Integrated Antimicrobial Resistance Monitoring and Research Programme (DANMAP). DANMAP 2004 - Use of antimicrobial agents and occurrence of antimicrobial resistance in bacteria from food animals, foods and humans in Denmark. Søborg: DANMAP; July 2005. Available from: https://www.danmap.org/-/media/arkiv/projekt-sites/danmap/danmap-reports/danmap_2004.pdf?la=en
  21. Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M, Kulikov AS, et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol. 2012;19(5):455-77.  https://doi.org/10.1089/cmb.2012.0021  PMID: 22506599 
  22. Card R, Zhang J, Das P, Cook C, Woodford N, Anjum MF. Evaluation of an expanded microarray for detecting antibiotic resistance genes in a broad range of gram-negative bacterial pathogens. Antimicrob Agents Chemother. 2013;57(1):458-65.  https://doi.org/10.1128/AAC.01223-12  PMID: 23129055 
  23. Mackinnon A. A spreadsheet for the calculation of comprehensive statistics for the assessment of diagnostic tests and inter-rater agreement. Comput Biol Med. 2000;30(3):127-34.  https://doi.org/10.1016/S0010-4825(00)00006-8  PMID: 10758228 
  24. McHugh ML. Interrater reliability: the kappa statistic. Biochem Med (Zagreb). 2012;22(3):276-82.  https://doi.org/10.11613/BM.2012.031  PMID: 23092060 
  25. Lin CF, Hsu SK, Chen CH, Huang JR, Lo HH. Genotypic detection and molecular epidemiology of extended-spectrum beta-lactamase-producing Escherichia coli and Klebsiella pneumoniae in a regional hospital in central Taiwan. J Med Microbiol. 2010;59(Pt 6):665-71.  https://doi.org/10.1099/jmm.0.015818-0  PMID: 20150317 
  26. Figueiredo R, Card RM, Nunez-Garcia J, Mendonça N, da Silva GJ, Anjum MF. Multidrug-Resistant Salmonella enterica Isolated from Food Animal and Foodstuff May Also Be Less Susceptible to Heavy Metals. Foodborne Pathog Dis. 2019;16(3):166-72.  https://doi.org/10.1089/fpd.2017.2418  PMID: 30480469 
  27. Bryan A, Shapir N, Sadowsky MJ. Frequency and distribution of tetracycline resistance genes in genetically diverse, nonselected, and nonclinical Escherichia coli strains isolated from diverse human and animal sources. Appl Environ Microbiol. 2004;70(4):2503-7.  https://doi.org/10.1128/AEM.70.4.2503-2507.2004  PMID: 15066850 
  28. Rayamajhi N, Cha SB, Kang ML, Lee SI, Lee HS, Yoo HS. Inter- and intraspecies plasmid-mediated transfer of florfenicol resistance in Enterobacteriaceae isolates from swine. Appl Environ Microbiol. 2009;75(17):5700-3.  https://doi.org/10.1128/AEM.02816-08  PMID: 19592530 
  29. Singer RS, Patterson SK, Meier AE, Gibson JK, Lee HL, Maddox CW. Relationship between phenotypic and genotypic florfenicol resistance in Escherichia coli. Antimicrob Agents Chemother. 2004;48(10):4047-9.  https://doi.org/10.1128/AAC.48.10.4047-4049.2004  PMID: 15388477 
  30. European Agency for the Evaluation of Medicinal Products (EMEA). Committee For Veterinary Medicinal Products. Trimethoprim. Summary Report (2). London; EMEA: 1997. Available from: https://www.ema.europa.eu/en/documents/mrl-report/trimethoprim-summary-report-2-committee-veterinary-medicinal-products_en.pdf
  31. Huovinen P. Resistance to trimethoprim-sulfamethoxazole. Clin Infect Dis. 2001;32(11):1608-14.  https://doi.org/10.1086/320532  PMID: 11340533 
  32. Maneewannakul K, Levy SB. Identification for mar mutants among quinolone-resistant clinical isolates of Escherichia coli. Antimicrob Agents Chemother. 1996;40(7):1695-8.  https://doi.org/10.1128/AAC.40.7.1695  PMID: 8807064 
  33. Speer BS, Shoemaker NB, Salyers AA. Bacterial resistance to tetracycline: mechanisms, transfer, and clinical significance. Clin Microbiol Rev. 1992;5(4):387-99.  https://doi.org/10.1128/CMR.5.4.387  PMID: 1423217 
  34. 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(4):281-8.  https://doi.org/10.1089/mdr.2007.779  PMID: 18184054 
  35. Card RM, Stubberfield E, Rogers J, Nunez-Garcia J, Ellis RJ, AbuOun M, et al. Identification of a New Antimicrobial Resistance Gene Provides Fresh Insights Into Pleuromutilin Resistance in Brachyspira hyodysenteriae, Aetiological Agent of Swine Dysentery. Front Microbiol. 2018;9:1183.  https://doi.org/10.3389/fmicb.2018.01183  PMID: 29971045 
  36. Duggett NA, Randall LP, Horton RA, Lemma F, Kirchner M, Nunez-Garcia J, et al. Molecular epidemiology of isolates with multiple mcr plasmids from a pig farm in Great Britain: the effects of colistin withdrawal in the short and long term. J Antimicrob Chemother. 2018;73(11):3025-33.  https://doi.org/10.1093/jac/dky292  PMID: 30124905 
  37. Turnidge J, Paterson DL. Setting and revising antibacterial susceptibility breakpoints. Clin Microbiol Rev. 2007;20(3):391-408.  https://doi.org/10.1128/CMR.00047-06  PMID: 17630331 

Data & Media loading...

Supplementary data

Submit comment
Comment moderation successfully completed
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