1887

Abstract

Outbreak investigations are essential to control and prevent the dissemination of pathogens. This study developed and validated a complete analysis protocol for faster and more accurate surveillance and outbreak investigations of antibiotic-resistant microbes based on Oxford Nanopore Technologies (ONT) DNA whole-genome sequencing. The protocol was developed using 42 methicillin-resistant (MRSA) isolates identified from former well-characterized outbreaks. The validation of the protocol was performed using Illumina technology (MiSeq, Illumina). Additionally, a real-time outbreak investigation of six clinical isolates was conducted to test the ONT-based protocol. The suggested protocol includes: (1) a 20 h sequencing run; (2) identification of the sequence type (ST); (3) genome assembly; (4) polishing of the draft genomes; and (5) phylogenetic analysis based on SNPs. After the sequencing run, it was possible to identify the ST in 2 h (20 min per isolate). Assemblies were achieved after 4 h (40 min per isolate) while the polishing was carried out in 7 min per isolate (42 min in total). The phylogenetic analysis took 0.6 h to confirm an outbreak. Overall, the developed protocol was able to at least discard an outbreak in 27 h (mean) after the bacterial identification and less than 33 h to confirm it. All these estimated times were calculated considering the average time for six MRSA isolates per sequencing run. During the real-time outbreak investigation, the protocol was able to identify two outbreaks in less than 31 h. The suggested protocol enables identification of outbreaks in early stages using a portable and low-cost device along with a streamlined downstream analysis, therefore having the potential to be incorporated in routine surveillance analysis workflows. In addition, further analysis may include identification of virulence and antibiotic resistance genes for improved pathogen characterization.

Funding
This study was supported by the:
  • Norwegian Surveillance Program for Antimicrobial Resistance (NORM)
    • Principle Award Recipient: HegeVangstein Aamot
  • Akershus Universitetssykehus (Award 268902)
    • Principle Award Recipient: HegeVangstein Aamot
  • This is an open-access article distributed under the terms of the Creative Commons Attribution NonCommercial License.
Loading

Article metrics loading...

/content/journal/mgen/10.1099/mgen.0.000557
2021-04-22
2022-01-21
Loading full text...

Full text loading...

/deliver/fulltext/mgen/7/4/mgen000557.html?itemId=/content/journal/mgen/10.1099/mgen.0.000557&mimeType=html&fmt=ahah

References

  1. Quainoo S, Coolen JPM, van Hijum SAFT, Huynen MA, Melchers WJG et al. Whole-genome sequencing of bacterial pathogens: the future of nosocomial outbreak analysis. Clin Microbiol Rev 2017; 30:1015–1063 [View Article][PubMed]
    [Google Scholar]
  2. Fossum Moen AE, Holberg-Petersen M, Andresen LL, Blomfeldt A. Spa typing alone is not sufficient to demonstrate endemic establishment of meticillin-resistant Staphylococcus aureus in a low-prevalence country. J Hosp Infect 2014; 88:72–77 [View Article][PubMed]
    [Google Scholar]
  3. Blomfeldt A, Hasan AA, Aamot HV. Can MLVA differentiate among endemic-like MRSA isolates with identical Spa-Type in a low-prevalence region?. PLoS One 2016; 11:e0148772 [View Article][PubMed]
    [Google Scholar]
  4. Blomfeldt A, Larssen KW, Moghen A, Haugum K, Steen TW et al. Bengal Bay clone ST772-MRSA-V outbreak: conserved clone causes investigation challenges. J Hosp Infect 2017; 95:253–258 [View Article][PubMed]
    [Google Scholar]
  5. Ahrenfeldt J, Skaarup C, Hasman H, Pedersen AG, Aarestrup FM et al. Bacterial whole genome-based phylogeny: construction of a new benchmarking dataset and assessment of some existing methods. BMC Genomics 2017; 18:1–13 [View Article]
    [Google Scholar]
  6. Rossen JWA, Friedrich AW, Moran-Gilad J. ESCMID Study Group for Genomic and Molecular Diagnostics (ESGMD Practical issues in implementing whole-genome-sequencing in routine diagnostic microbiology. Clin Microbiol Infect 2018; 24:355–360 [View Article][PubMed]
    [Google Scholar]
  7. Berry M I, Melendrez MC, Bishop-Lilly KA, Rutvisuttinunt W, Pollett S et al. Next generation sequencing and bioinformatics methodologies for infectious disease research and public health: approaches, applications, and considerations for development of laboratory capacity. J Infect Dis 2019; 221:S292–307
    [Google Scholar]
  8. Quick J, Loman NJ, Duraffour S, Simpson JT, Severi E et al. Real-time, portable genome sequencing for Ebola surveillance . Nature 2016; 530:228–232 [View Article][PubMed]
    [Google Scholar]
  9. Schmidt K, Mwaigwisya S, Crossman LC, Doumith M, Munroe D et al. Identification of bacterial pathogens and antimicrobial resistance directly from clinical urines by nanopore-based metagenomic sequencing. J Antimicrob Chemother 2017; 72:104–114 [View Article][PubMed]
    [Google Scholar]
  10. Golparian D, Donà V, Sánchez-Busó L, Foerster S, Harris S et al. Antimicrobial resistance prediction and phylogenetic analysis of Neisseria gonorrhoeae isolates using the Oxford nanopore MinION sequencer. Sci Rep 2018; 8:17596 [View Article][PubMed]
    [Google Scholar]
  11. Payne M, Octavia S, Luu LDW, Sotomayor-Castillo C, Wang Q et al. Enhancing genomics-based outbreak detection of endemic Salmonellaenterica serovar Typhimurium using dynamic thresholds. Microb Genom 2019 04 Nov 2019 [View Article][PubMed]
    [Google Scholar]
  12. WHO Who publishes list of bacteria for which new antibiotics are urgently needed. Available from. https://www.who.int/news/item/27-02-2017-who-publishes-list-of-bacteria-for-which-new-antibiotics-are-urgently-needed 2 Dec 2020
  13. Lee AS, de Lencastre H, Garau J, Kluytmans J, Malhotra-Kumar S et al. Methicillin-resistant Staphylococcus aureus. Nat Rev Dis Primers 2018; 4:1–23 [View Article]
    [Google Scholar]
  14. Cassini A, Högberg LD, Plachouras D, Quattrocchi A, Hoxha A et al. Attributable deaths and disability-adjusted life-years caused by infections with antibiotic-resistant bacteria in the EU and the European economic area in 2015: a population-level modelling analysis. Lancet Infect Dis 2019; 19:56–66 [View Article][PubMed]
    [Google Scholar]
  15. Blomfeldt A, Larssen KW, Moghen A, Gabrielsen C, Elstrøm P et al. Emerging multidrug-resistant Bengal Bay clone ST772-MRSA-V in Norway: molecular epidemiology 2004-2014. Eur J Clin Microbiol Infect Dis 2017; 36:1911–1921 [View Article][PubMed]
    [Google Scholar]
  16. Di Ruscio F, Guzzetta G, Bjørnholt JV, Leegaard TM, Moen AEF et al. Quantifying the transmission dynamics of MRSA in the community and healthcare settings in a low-prevalence country. Proc Natl Acad Sci U S A 2019; 116:14599–14605 [View Article]
    [Google Scholar]
  17. Page AJ, Keane JA. Rapid multi-locus sequence typing direct from uncorrected long reads using Krocus . PeerJ 2018; 6:e5233 [View Article][PubMed]
    [Google Scholar]
  18. 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]
  19. Wick RR, Schultz MB, Zobel J, Holt KE. Bandage: interactive visualization of de novo genome assemblies: Fig. 1. Bioinformatics 2015; 31:3350–3352 [View Article]
    [Google Scholar]
  20. Oxford Nanopore Technologies Medaka. Available from. https://nanoporetech.github.io/medaka/ 2 Dec 2020
  21. Bertels F, Silander OK, Pachkov M, Rainey PB, van Nimwegen E. Automated reconstruction of whole-genome phylogenies from short-sequence reads. Mol Biol Evol 2014; 31:1077–1088 [View Article][PubMed]
    [Google Scholar]
  22. Rambaut, A FigTree. Available from. https://github.com/rambaut/figtree 2 Dec 2020
  23. Geneious Geneious prime. Available from. https://www.geneious.com/prime 2 Dec 2020
  24. Noone JC, Stegger M, Lilje B, Stavem K, Helmersen K et al. Molecular characteristics of Staphylococcus aureus associated prosthetic joint infections after hip fractures treated with hemiarthroplasty: a retrospective genome-wide association study. Sci Rep 2020; 10:16553 [View Article][PubMed]
    [Google Scholar]
  25. Babraham Bioinformatics FastQC. Available from. https://www.bioinformatics.babraham.ac.uk/projects/fastqc/ 2 Dec 2020
  26. Larsen MV, Cosentino S, Rasmussen S, Friis C, Hasman H et al. Multilocus sequence typing of total-genome-sequenced bacteria. J Clin Microbiol 2012; 50:1355–1361 [View Article][PubMed]
    [Google Scholar]
  27. Seemann T Snippy. Available from. https://github.com/tseemann/snippy 2 Dec 2020
  28. Croucher NJ, Page AJ, Connor TR, Delaney AJ, Keane JA et al. Rapid phylogenetic analysis of large samples of recombinant bacterial whole genome sequences using Gubbins. Nucleic Acids Res 2015; 43:e15 [View Article][PubMed]
    [Google Scholar]
  29. Yu G. Using ggtree to visualize data on Tree-Like structures. Curr Protoc Bioinformatics 2020; 69:e96 [View Article][PubMed]
    [Google Scholar]
  30. Fossum AE, Bukholm G. Increased incidence of methicillin-resistant Staphylococcus aureus ST80, novel ST125 and SCCmecIV in the south-eastern part of Norway during a 12-year period. Clin Microbiol Infect 2006; 12:627–633 [View Article][PubMed]
    [Google Scholar]
  31. Schouls LM, Spalburg EC, van Luit M, Huijsdens XW, Pluister GN et al. Multiple-Locus variable number tandem repeat analysis of Staphylococcus aureus: comparison with pulsed-field gel electrophoresis and spa-typing. PLoS One 2009; 4:e5082 [View Article][PubMed]
    [Google Scholar]
  32. Cunningham SA, Chia N, Jeraldo PR, Quest DJ, Johnson JA et al. Comparison of whole-genome sequencing methods for analysis of three methicillin-resistant Staphylococcus aureus outbreaks. J Clin Microbiol 2017; 55:1946–1953 [View Article][PubMed]
    [Google Scholar]
  33. Bartels MD, Petersen A, Worning P, Nielsen JB, Larner-Svensson H et al. Comparing whole-genome sequencing with Sanger sequencing for spa typing of methicillin-resistant Staphylococcus aureus. J Clin Microbiol 2014; 52:4305–4308 [View Article][PubMed]
    [Google Scholar]
  34. Wick RR, Holt KE. Benchmarking of long-read assemblers for prokaryote whole genome sequencing. F1000Res 2019; 8:2138 [View Article][PubMed]
    [Google Scholar]
  35. Kaas RS, Leekitcharoenphon P, Aarestrup FM, Lund O. Solving the problem of comparing whole bacterial genomes across different sequencing platforms. PLoS One 2014; 9:e104984 [View Article][PubMed]
    [Google Scholar]
  36. Greig DR, Jenkins C, Gharbia S, Dallman TJ. Comparison of single-nucleotide variants identified by illumina and Oxford nanopore technologies in the context of a potential outbreak of Shiga toxin–producing Escherichia coli. Gigascience 2019; 8:1–12 [View Article]
    [Google Scholar]
  37. Salazar AN, Nobrega FL, Anyansi C, Aparicio-Maldonado C, Costa AR et al. An educational guide for nanopore sequencing in the classroom. PLoS Comput Biol 2020; 16:e1007314 [View Article][PubMed]
    [Google Scholar]
http://instance.metastore.ingenta.com/content/journal/mgen/10.1099/mgen.0.000557
Loading
/content/journal/mgen/10.1099/mgen.0.000557
Loading

Data & Media loading...

Supplements

Supplementary material 1

PDF

Supplementary material 2

EXCEL

Most cited this month 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