Skip to content
1887

Journal of Medical Microbiology logo Journal of Medical Microbiology

Volume 74, Issue 3

Evaluation of whole-genome sequencing protocols for detection of antimicrobial resistance, virulence factors and mobile genetic elements in antimicrobial-resistant bacteria Open Access

Abstract

Antimicrobial resistance (AMR) poses a critical threat to global health, underscoring the need for rapid and accurate diagnostic tools. Methicillin-resistant (MRSA) and extended-spectrum beta-lactamase (ESBL)-producing (ESBL-Kp) are listed among the World Health Organization’s priority pathogens.

A rapid nanopore-based protocol can accurately and efficiently detect AMR genes, virulence factors (VFs) and mobile genetic elements (MGEs) in MRSA and ESBL-Kp, offering performance comparable to or superior to traditional sequencing methods.

Evaluate whole-genome sequencing (WGS) protocols for detecting AMR genes, VFs and MGEs in MRSA and ESBL-Kp, to identify the most accurate and efficient tool for pathogen profiling.

Five distinct WGS protocols, including a rapid nanopore-based protocol (ONT20h) and four slower sequencing methods, were evaluated for their effectiveness in detecting genetic markers. The protocols' performances were compared across AMR genes, VFs and MGEs. Additionally, phenotypic antimicrobial susceptibility testing was performed to assess concordance with the genomic findings.

Compared to four slower sequencing protocols, the rapid nanopore-based protocol (ONT20h) demonstrated comparable or superior performance in AMR gene detection and equivalent VF identification. Although MGE detection varied among protocols, ONT20h showed a high level of agreement with phenotypic antimicrobial susceptibility testing.

The findings highlight the potential of rapid WGS as a valuable tool for clinical microbiology, enabling timely implementation of infection control measures and informed therapeutic decisions. However, further studies are required to optimize the clinical application of this technology, considering costs, availability of bioinformatics tools and quality of reference databases.

  • Received:
  • Accepted:
  • Published Online:
Keyword(s): antibiotic resistance , bacteria , diagnosis , genome analysis , genotypic method and whole-genome sequencing
Funding
This study was supported by the:
  • Norwegian Surveillance Programme for Antimicrobial Resistance (NORM) and strategic funding from Akershus University Hospital (Award 268902)
    • Principal Award Recipient: HegeVangstein Aamot
© 2025 The Authors
  • This is an open-access article distributed under the terms of the Creative Commons Attribution License. The Microbiology Society waived the open access fees for this article.
Loading

Article metrics loading...

/content/journal/jmm/10.1099/jmm.0.001990
2025-03-19
2026-02-09

Metrics

Loading full text...

Full text loading...

/deliver/fulltext/jmm/74/3/jmm001990.html?itemId=/content/journal/jmm/10.1099/jmm.0.001990&mimeType=html&fmt=ahah

References

  1. GBD 2021 Antimicrobial Resistance Collaborators Global burden of bacterial antimicrobial resistance 1990–2021: a systematic analysis with forecasts to 2050. Lancet 2024; 404:1199–1226 [View Article]
     [Google Scholar]
  2. Turner NA, Sharma-Kuinkel BK, Maskarinec SA, Eichenberger EM, Shah PP et al. Methicillin-resistant Staphylococcus aureus: an overview of basic and clinical research. Nat Rev Microbiol 2019; 17:203–218 [View Article] [PubMed]
     [Google Scholar]
  3. Jiang J-H, Cameron DR, Nethercott C, Aires-de-Sousa M, Peleg AY. Virulence attributes of successful methicillin-resistant Staphylococcus aureus lineages. Clin Microbiol Rev 2023; 36:e0014822 [View Article] [PubMed]
     [Google Scholar]
  4. Gauba A, Rahman KM. Evaluation of antibiotic resistance mechanisms in gram-negative bacteria. Antibiotics 2023; 12:1590 [View Article] [PubMed]
     [Google Scholar]
  5. Dong N, Yang X, Chan EW-C, Zhang R, Chen S. Klebsiella species: taxonomy, hypervirulence and multidrug resistance. eBioMedicine 2022; 79:103998 [View Article] [PubMed]
     [Google Scholar]
  6. Weinmaier T, Conzemius R, Bergman Y, Lewis S, Jacobs EB et al. Validation and application of long-read whole-genome sequencing for antimicrobial resistance gene detection and antimicrobial susceptibility testing. Antimicrob Agents Chemother 2023; 67:e0107222 [View Article] [PubMed]
     [Google Scholar]
  7. Bianconi I, Aschbacher R, Pagani E. Current uses and future perspectives of genomic technologies in clinical microbiology. Antibiotics 2023; 12:1580 [View Article] [PubMed]
     [Google Scholar]
  8. Ferreira FA, Helmersen K, Visnovska T, Jørgensen SB, Aamot HV. Rapid nanopore-based DNA sequencing protocol of antibiotic-resistant bacteria for use in surveillance and outbreak investigation. Microb Genom 2021; 7:000557 [View Article] [PubMed]
     [Google Scholar]
  9. Kolmogorov M, Yuan J, Lin Y, Pevzner PA. Assembly of long, error-prone reads using repeat graphs. Nat Biotechnol 2019; 37:540–546 [View Article] [PubMed]
     [Google Scholar]
  10. Koren S, Walenz BP, Berlin K, Miller JR, Bergman NH et al. Canu: scalable and accurate long-read assembly via adaptive k-mer weighting and repeat separation. Genome Res 2017; 27:722–736 [View Article] [PubMed]
     [Google Scholar]
  11. 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]
  12. Mikheenko A, Prjibelski A, Saveliev V, Antipov D, Gurevich A. Versatile genome assembly evaluation with QUAST-LG. Bioinformatics 2018; 34:i142–i150 [View Article] [PubMed]
     [Google Scholar]
  13. Bortolaia V, Kaas RS, Ruppe E, Roberts MC, Schwarz S et al. ResFinder 4.0 for predictions of phenotypes from genotypes. J Antimicrob Chemother 2020; 75:3491–3500 [View Article] [PubMed]
     [Google Scholar]
  14. Alcock BP, Raphenya AR, Lau TTY, Tsang KK, Bouchard M et al. CARD 2020: antibiotic resistome surveillance with the comprehensive antibiotic resistance database. Nucleic Acids Res 2020; 48:D517–D525 [View Article] [PubMed]
     [Google Scholar]
  15. Malberg Tetzschner AM, Johnson JR, Johnston BD, Lund O, Scheutz F. In silico genotyping of Escherichia coli isolates for extraintestinal virulence genes by use of whole-genome sequencing data. J Clin Microbiol 2020; 58:e01269-20 [View Article] [PubMed]
     [Google Scholar]
  16. Carattoli A, Zankari E, García-Fernández A, Voldby Larsen M, Lund O et al. 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]
  17. Johansson MHK, Bortolaia V, Tansirichaiya S, Aarestrup FM, Roberts AP et al. Detection of mobile genetic elements associated with antibiotic resistance in Salmonella enterica using a newly developed web tool: MobileElementFinder. J Antimicrob Chemother 2021; 76:101–109 [View Article] [PubMed]
     [Google Scholar]
  18. Chen L, Yang J, Yu J, Yao Z, Sun L et al. VFDB: a reference database for bacterial virulence factors. Nucleic Acids Res 2005; 33:D325–8 [View Article] [PubMed]
     [Google Scholar]
  19. EUCAST Breakpoint tables for interpretation of MICs and zone diameters, Version 14.0; 2024 https://www.eucast.org/clinical_breakpoints/ accessed 20 June 2024
  20. Safar HA, Alatar F, Nasser K, Al-Ajmi R, Alfouzan W et al. The impact of applying various de novo assembly and correction tools on the identification of genome characterization, drug resistance, and virulence factors of clinical isolates using ONT sequencing. BMC Biotechnol 2023; 23:26 [View Article] [PubMed]
     [Google Scholar]
  21. Schiavone A, Pugliese N, Samarelli R, Cumbo C, Minervini CF et al. Factors affecting the quality of bacterial genome assemblies by Canu after nanopore sequencing. Appl Sci 2022; 12:3110 [View Article]
     [Google Scholar]
  22. Lee JY, Kong M, Oh J, Lim J, Chung SH et al. Comparative evaluation of nanopore polishing tools for microbial genome assembly and polishing strategies for downstream analysis. Sci Rep 2021; 11:20740 [View Article]
     [Google Scholar]
  23. Goldstein S, Beka L, Graf J, Klassen JL. Evaluation of strategies for the assembly of diverse bacterial genomes using MinION long-read sequencing. BMC Genom 2019; 20:23 [View Article] [PubMed]
     [Google Scholar]
  24. Juraschek K, Borowiak M, Tausch SH, Malorny B, Käsbohrer A et al. Outcome of different sequencing and assembly approaches on the detection of plasmids and localization of antimicrobial resistance genes in commensal Escherichia coli. Microorganisms 2021; 9:598 [View Article] [PubMed]
     [Google Scholar]
  25. Conzemius R, Bergman Y, Májek P, Beisken S, Lewis S et al. Automated antimicrobial susceptibility testing and antimicrobial resistance genotyping using Illumina and Oxford Nanopore Technologies sequencing data among Enterobacteriaceae. Front Microbiol 2022; 13:973605 [View Article] [PubMed]
     [Google Scholar]
  26. Ellington MJ, Ekelund O, Aarestrup FM, Canton R, Doumith M et al. The role of whole genome sequencing in antimicrobial susceptibility testing of bacteria: report from the EUCAST subcommittee. Clin Microbiol Infect 2017; 23:2–22 [View Article] [PubMed]
     [Google Scholar]
  27. Del Rio A, Puci M, Muresu N, Sechi I, Saderi L et al. Comparison of genotypic and phenotypic antimicrobial profile in carbapenemases producing Klebsiella pneumoniae. Acta Biomed 2023; 94:e2023201 [View Article] [PubMed]
     [Google Scholar]
  28. Mutschler E, Roloff T, Neves A, Vangstein Aamot H, Rodriguez-Sanchez B et al. ESCMID study group for epidemiological markers (ESGEM), and ESCMID study group for genomic and molecular diagnostics (ESGMD). Towards unified reporting of genome sequencing results in clinical microbiology. PeerJ 2024; 12:e17673 [View Article]
     [Google Scholar]
  29. Doyle RM, O’Sullivan DM, Aller SD, Bruchmann S, Clark T et al. Discordant bioinformatic predictions of antimicrobial resistance from whole-genome sequencing data of bacterial isolates: an inter-laboratory study. Microb Genom 2020; 6:e000335 [View Article] [PubMed]
     [Google Scholar]
  30. Sherry NL, Horan KA, Ballard SA, Gonҫalves da Silva A, Gorrie CL et al. An ISO-certified genomics workflow for identification and surveillance of antimicrobial resistance. Nat Commun 2023; 14:60 [View Article] [PubMed]
     [Google Scholar]
/content/journal/jmm/10.1099/jmm.0.001990
Loading
Evaluation of whole-genome sequencing protocols for detection of antimicrobial resistance, virulence factors and mobile genetic elements in antimicrobial-resistant bacteria
J. Med. Microbiol. 74, 001990 (2025); https://doi.org/10.1099/jmm.0.001990
/content/journal/jmm/10.1099/jmm.0.001990
/content/journal/jmm/10.1099/jmm.0.001990
Loading

Data & Media loading...

Supplements

Supplementary material 1

PDF

Most cited Most Cited RSS feed

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