1887

Abstract

Over the last 35 years in the UK, the burden of Shiga toxin-producing (STEC) O157:H7 infection has, during different periods of time, been associated with five different sub-lineages (1983–1995, Ia, I/IIa and I/IIb; 1996–2014, Ic; and 2015–2018, IIb). The acquisition of a -encoding bacteriophage by these five sub-lineages appears to have coincided with their respective emergences. The Oxford Nanopore Technologies (ONT) system was used to sequence, characterize and compare the -encoding prophages harboured by each sub-lineage to investigate the integration of this key virulence factor. The -encoding prophages from each of the lineages causing clinical disease in the UK were all different, including the two UK sub-lineages (Ia and I/IIa) circulating concurrently and causing severe disease in the early 1980s. Comparisons between the encoding prophage in sub-lineages I/IIb and IIb revealed similarity to the prophage commonly found to encode , and the same site of bacteriophage integration () as -encoding prophage. These data suggest independent acquisition of previously unobserved -encoding phage is more likely to have contributed to the emergence of STEC O157:H7 sub-lineages in the UK than intra-UK lineage to lineage phage transmission. In contrast, the -encoding prophage showed a high level of similarity across lineages and time, consistent with the model of being present in the common ancestor to extant STEC O157:H7 and maintained by vertical inheritance in the majority of the population. Studying the nature of the -encoding bacteriophage contributes to our understanding of the emergence of highly pathogenic strains of STEC O157:H7.

Funding
This study was supported by the:
  • Biotechnology and Biological Sciences Research Council
    • Principle Award Recipient: Daniel A Yara
  • National Institute for Health Research (Award 109524)
    • Principle Award Recipient: Timothy J Dallman
  • National Institute for Health Research (Award 109524)
    • Principle Award Recipient: Claire Jenkins
  • This is an open-access article distributed under the terms of the Creative Commons Attribution License.
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2020-02-25
2024-03-29
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References

  1. Tarr PI, Gordon CA, Chandler WL. Shiga-toxin-producing Escherichia coli and haemolytic uraemic syndrome. The Lancet 2005; 365:1073–1086 [View Article]
    [Google Scholar]
  2. Taylor CM, White RH, Winterborn MH, Rowe B. Haemolytic-uraemic syndrome: clinical experience of an outbreak in the West Midlands. BMJ 1986; 292:1513–1516 [View Article]
    [Google Scholar]
  3. Khakhria R, Duck D, Lior H. Extended phage-typing scheme for Escherichia coli 0157:H7. Epidemiol Infect 1990; 105:511–520 [View Article]
    [Google Scholar]
  4. Dallman TJ, Byrne L, Ashton PM, Cowley LA, Perry NT et al. Whole-genome sequencing for national surveillance of Shiga toxin-producing Escherichia coli O157. Clin Infect Dis 2015; 61:305–312 [View Article]
    [Google Scholar]
  5. Dallman TJ, Ashton PM, Byrne L, Perry NT, Petrovska L et al. Applying phylogenomics to understand the emergence of Shiga-toxin-producing Escherichia coli O157:H7 strains causing severe human disease in the UK. Microb Genom 2015; 1:e000029 [View Article]
    [Google Scholar]
  6. Persson S, Olsen KEP, Ethelberg S, Scheutz F. Subtyping method for Escherichia coli Shiga toxin (verocytotoxin) 2 variants and correlations to clinical manifestations. J Clin Microbiol 2007; 45:2020–2024 [View Article]
    [Google Scholar]
  7. Fitzgerald SF, Beckett AE, Palarea-Albaladejo J, McAteer S, Shaaban S et al. Shiga toxin sub-type 2a increases the efficiency of Escherichia coli O157 transmission between animals and restricts epithelial regeneration in bovine enteroids. PLoS Pathog 2019; 15:e1008003 [View Article]
    [Google Scholar]
  8. Ogura Y, Mondal SI, Islam MR, Mako T, Arisawa K et al. The Shiga toxin 2 production level in enterohemorrhagic Escherichia coli O157:H7 is correlated with the subtypes of toxin-encoding phage. Sci Rep 2015; 16:16663
    [Google Scholar]
  9. Adams NL, Byrne L, Smith GA, Elson R, Harris JP et al. Shiga toxin-producing Escherichia coli O157, England and Wales, 1983–2012. Emerg Infect Dis 2016; 22:590–597 [View Article]
    [Google Scholar]
  10. Byrne L, Dallman TJ, Adams N, Mikhail AFW, McCarthy N et al. Highly pathogenic clone of Shiga toxin-producing Escherichia coli O157:H7, England and Wales. Emerg Infect Dis 2018; 24:2303–2308 [View Article]
    [Google Scholar]
  11. Launders N, Locking ME, Hanson M, Willshaw G, Charlett A et al. A large great Britain-wide outbreak of STEC O157 phage type 8 linked to handling of raw leeks and potatoes. Epidemiol Infect 2016; 144:171–181 [View Article]
    [Google Scholar]
  12. Cowley LA, Dallman TJ, Fitzgerald S, Irvine N, Rooney PJ et al. Short-term evolution of Shiga toxin-producing Escherichia coli O157:H7 between two food-borne outbreaks. Microb Genom 2016; 2:e000084 [View Article]
    [Google Scholar]
  13. Jenkins C, Dallman TJ, Launders N, Willis C, Byrne L et al. Public health investigation of two outbreaks of Shiga toxin-producing Escherichia coli O157 associated with consumption of watercress. Appl Environ Microbiol 2015; 81:3946–3952 [View Article]
    [Google Scholar]
  14. Riley LW, Remis RS, Helgerson SD, McGee HB, Wells JG et al. Hemorrhagic colitis associated with a rare Escherichia coli serotype. N Engl J Med 1983; 308:681–685 [View Article]
    [Google Scholar]
  15. Uhlich GA, Sinclair JR, Warren NG, Chmielecki WA, Fratamico P. Characterization of Shiga toxin-producing Escherichia coli isolates associated with two multistate food-borne outbreaks that occurred in 2006. Appl Environ Microbiol 2008; 74:1268–1272 [View Article]
    [Google Scholar]
  16. Michino H, Araki K, Minami S, Takaya S, Sakai N et al. Massive outbreak of Escherichia coli O157: H7 infection in schoolchildren in Sakai City, Japan, associated with consumption of white radish sprouts. Am J Epidemiol 1999; 150:787–796 [View Article]
    [Google Scholar]
  17. Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 2014; 30:2114–2120 [View Article]
    [Google Scholar]
  18. Wick RR, Judd LM, Holt KE. Deepbinner: demultiplexing barcoded Oxford Nanopore reads with deep convolutional neural networks. PLoS Comput Biol 2018; 14:e1006583 [View Article]
    [Google Scholar]
  19. De Coster W, D’Hert S, Schultz DT, Cruts M, Van Broeckhoven C. NanoPack: visualizing and processing long-read sequencing data. Bioinformatics 2018; 34:2666–2669 [View Article]
    [Google Scholar]
  20. Wick RR. Porechop 2017 https://github.com/rrwick/Porechop
  21. Wick RR. Filtlong 2017 https://github.com/rrwick/Filtlong
  22. 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]
    [Google Scholar]
  23. 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]
    [Google Scholar]
  24. 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]
    [Google Scholar]
  25. Loman NJ, Quick J, Simpson JT. A complete bacterial genome assembled de novo using only nanopore sequencing data. Nat Methods 2015; 12:733–735 [View Article]
    [Google Scholar]
  26. Walker BJ, Abeel T, Shea T, Priest M, Abouelliel A et al. Pilon: an integrated tool for comprehensive microbial variant detection and genome assembly improvement. PLoS One 2014; 9:e112963 [View Article]
    [Google Scholar]
  27. Li H, Durbin R. Fast and accurate long-read alignment with Burrows–Wheeler transform. Bioinformatics 2010; 26:589–595 [View Article]
    [Google Scholar]
  28. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 2009; 25:2078–2079
    [Google Scholar]
  29. Vaser R, Sović I, Nagarajan N, Šikić M. Fast and accurate de novo genome assembly from long uncorrected reads. Genome Res 2017; 27:737–746 [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. Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics 2014; 30:2068–2069 [View Article]
    [Google Scholar]
  32. Arndt D, Grant JR, Marcu A, Sajed T, Pon A et al. PHASTER: a better, faster version of the PHAST phage search tool. Nucleic Acids Res 2016; 44:W16–W21 [View Article]
    [Google Scholar]
  33. Shaaban S, Cowley LA, McAteer SP, Jenkins C, Dallman TJ et al. Evolution of a zoonotic pathogen: investigating prophage diversity in enterohaemorrhagic Escherichia coli O157 by long-read sequencing. Microb Gen 2016; 2:e000096 [View Article]
    [Google Scholar]
  34. 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]
  35. Rambaut A, Drummond AJ. FigTree 2018 https://github.com/rambaut/figtree
  36. Dallman T, Ashton P, Schafer U, Jironkin A, Painset A et al. SnapperDB: a database solution for routine sequencing analysis of bacterial isolates. Bioinformatics 2018; 34:3028–3029 [View Article]
    [Google Scholar]
  37. 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]
    [Google Scholar]
  38. Stamatakis A. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 2014; 30:1312–1313 [View Article]
    [Google Scholar]
  39. Sullivan MJ, Petty NK, Beatson SA. Easyfig: a genome comparison visualizer. Bioinformatics 2011; 27:1009–1010 [View Article]
    [Google Scholar]
  40. Schutz K, Cowley LA, Shaaban S, Carroll A, McNamara E et al. Evolutionary context of non-sorbitol-fermenting Shiga toxin-producing Escherichia coli O55:H7. Emerg Infect Dis 2017; 23:1966–1973 [View Article]
    [Google Scholar]
  41. Scotland SM, Willshaw GA, Smith HR, Rowe B. Properties of strains of Escherichia coli belonging to serogroup O 157 with special reference to production of Vero cytotoxins VTl and VT2. Epidemiol Infect 1987; 99:613–624 [View Article]
    [Google Scholar]
  42. Mikhail AFW, Jenkins C, Dallman TJ, Inns T, Douglas A et al. An outbreak of Shiga toxin-producing Escherichia coli O157:H7 associated with contaminated salad leaves: epidemiological, genomic and food trace back investigations. Epidemiol Infect 2018; 146:187–196 [View Article]
    [Google Scholar]
  43. Gobin M, Hawker J, Cleary P, Inns T, Gardiner D et al. National outbreak of Shiga toxin-producing Escherichia coli O157:H7 linked to mixed salad leaves, United Kingdom, 2016. Euro Surveill 2018; 23:17-00197 [View Article]
    [Google Scholar]
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