Skip to content
1887

Microbial Genomics logo Microbial Genomics

Volume 9, Issue 5

Evaluation of core genome and whole genome multilocus sequence typing schemes for and outbreak detection in the USA Open Access

Abstract

is a leading causing of bacterial foodborne and zoonotic illnesses in the USA. Pulsed-field gene electrophoresis (PFGE) and 7-gene multilocus sequence typing (MLST) have been historically used to differentiate sporadic from outbreak isolates. Whole genome sequencing (WGS) has been shown to provide superior resolution and concordance with epidemiological data when compared with PFGE and 7-gene MLST during outbreak investigations. In this study, we evaluated epidemiological concordance for high-quality SNP (hqSNP), core genome (cg)MLST and whole genome (wg)MLST to cluster or differentiate outbreak-associated and sporadic and isolates. Phylogenetic hqSNP, cgMLST and wgMLST analyses were also compared using Baker’s gamma index (BGI) and cophenetic correlation coefficients. Pairwise distances comparing all three analysis methods were compared using linear regression models. Our results showed that 68/73 sporadic and isolates were differentiated from outbreak-associated isolates using all three methods. There was a high correlation between cgMLST and wgMLST analyses of the isolates; the BGI, cophenetic correlation coefficient, linear regression model and Pearson correlation coefficients were >0.90. The correlation was sometimes lower comparing hqSNP analysis to the MLST-based methods; the linear regression model and Pearson correlation coefficients were between 0.60 and 0.86, and the BGI and cophenetic correlation coefficient were between 0.63 and 0.86 for some outbreak isolates. We demonstrated that and isolates clustered in concordance with epidemiological data using WGS-based analysis methods. Discrepancies between allele and SNP-based approaches may reflect the differences between how genomic variation (SNPs and indels) are captured between the two methods. Since cgMLST examines allele differences in genes that are common in most isolates being compared, it is well suited to surveillance: searching large genomic databases for similar isolates is easily and efficiently done using allelic profiles. On the other hand, use of an hqSNP approach is much more computer intensive and not scalable to large sets of genomes. If further resolution between potential outbreak isolates is needed, wgMLST or hqSNP analysis can be used.

  • Received:
  • Accepted:
  • Published Online:
Keyword(s): Campylobacter , cgMLST , hqSNP , outbreak and wgMLST
© Microbiology Society
  • 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.0.001012
2023-05-03
2025-05-16
Loading full text...

Full text loading...

/deliver/fulltext/mgen/9/5/mgen001012.html?itemId=/content/journal/mgen/10.1099/mgen.0.001012&mimeType=html&fmt=ahah

References

  1. Collier SA, Deng L, Adam EA, Benedict KM, Beshearse EM et al. Estimate of burden and direct healthcare cost of infectious waterborne disease in the United States. Emerg Infect Dis 2021; 27:140–149 [View Article] [PubMed]
     [Google Scholar]
  2. Kirkpatrick BD, Tribble DR. Update on human Campylobacter jejuni infections. Curr Opin Gastroenterol 2011; 27:1–7 [View Article] [PubMed]
     [Google Scholar]
  3. Allos BM. Campylobacter jejuni infections: update on emerging issues and trends. Clin Infect Dis 2001; 32:1201–1206 [View Article] [PubMed]
     [Google Scholar]
  4. Butzler J-P. Campylobacter, from obscurity to celebrity. Clin Microbiol Infect 2004; 10:868–876 [View Article] [PubMed]
     [Google Scholar]
  5. Smith JL, Bayles D. Postinfectious irritable bowel syndrome: a long-term consequence of bacterial gastroenteritis. J Food Prot 2007; 70:1762–1769 [View Article] [PubMed]
     [Google Scholar]
  6. Humphrey T, O’Brien S, Madsen M. Campylobacters as zoonotic pathogens: a food production perspective. Int J Food Microbiol 2007; 117:237–257 [View Article] [PubMed]
     [Google Scholar]
  7. Gardner TJ, Fitzgerald C, Xavier C, Klein R, Pruckler J et al. Outbreak of campylobacteriosis associated with consumption of raw peas. Clin Infect Dis 2011; 53:26–32 [View Article] [PubMed]
     [Google Scholar]
  8. Kwan PSL, Xavier C, Santovenia M, Pruckler J, Stroika S et al. Multilocus sequence typing confirms wild birds as the source of a Campylobacter outbreak associated with the consumption of raw peas. Appl Environ Microbiol 2014; 80:4540–4546 [View Article] [PubMed]
     [Google Scholar]
  9. Fernandes AM, Balasegaram S, Willis C, Wimalarathna HML, Maiden MC et al. Partial failure of milk pasteurization as a risk for the transmission of Campylobacter from cattle to humans. Clin Infect Dis 2015; 61:903–909 [View Article] [PubMed]
     [Google Scholar]
  10. Davis KR, Dunn AC, Burnett C, McCullough L, Dimond M et al. Campylobacter jejuni infections associated with raw milk consumption--utah, 2014. MMWR Morb Mortal Wkly Rep 2016; 65:301–305 [View Article] [PubMed]
     [Google Scholar]
  11. Moffat C, Appuhamy R, Andrew W, Wynn S, Roberts J et al. An assessment of risk posed by a Campylobacter-positive puppy living in an Australian residential aged-care facility. WPSAR 2014; 5:1–6 [View Article] [PubMed]
     [Google Scholar]
  12. Acke E. Campylobacteriosis in dogs and cats: a review. N Z Vet J 2018; 66:221–228 [View Article] [PubMed]
     [Google Scholar]
  13. Montgomery MP, Robertson S, Koski L, Salehi E, Stevenson LM et al. Multidrug-resistant Campylobacter jejuni outbreak linked to puppy exposure - United States, 2016-2018. MMWR Morb Mortal Wkly Rep 2018; 67:1032–1035 [View Article] [PubMed]
     [Google Scholar]
  14. Joseph LA, Francois Watkins LK, Chen J, Tagg KA, Bennett C et al. Comparison of molecular subtyping and antimicrobial resistance detection methods used in a large multistate outbreak of extensively drug-resistant Campylobacter jejuni infections linked to pet store puppies. J Clin Microbiol 2020; 58:e00771–20 [View Article] [PubMed]
     [Google Scholar]
  15. Dingle KE, Colles FM, Wareing DR, Ure R, Fox AJ et al. Multilocus sequence typing system for Campylobacter jejuni. J Clin Microbiol 2001; 39:14–23 [View Article] [PubMed]
     [Google Scholar]
  16. Parsons BN, Cody AJ, Porter CJ, Stavisky JH, Smith JL et al. Typing of Campylobacter jejuni isolates from dogs by use of multilocus sequence typing and pulsed-field gel electrophoresis. J Clin Microbiol 2009; 47:3466–3471 [View Article] [PubMed]
     [Google Scholar]
  17. Taboada EN, Clark CG, Sproston EL, Carrillo CD. Current methods for molecular typing of Campylobacter species. J Microbiol Methods 2013; 95:24–31 [View Article] [PubMed]
     [Google Scholar]
  18. Kovanen SM, Kivistö RI, Rossi M, Schott T, Kärkkäinen U-M et al. Multilocus sequence typing (MLST) and whole-genome MLST of Campylobacter jejuni isolates from human infections in three districts during a seasonal peak in Finland. J Clin Microbiol 2014; 52:4147–4154 [View Article] [PubMed]
     [Google Scholar]
  19. Carleton HA, Gerner-Smidt P. Whole-genome sequencing is taking over foodborne disease surveillance. Microbe Magazine 2016; 11:311–317 [View Article]
     [Google Scholar]
  20. Llarena A-K, Taboada E, Rossi M. Whole-genome sequencing in epidemiology of Campylobacter jejuni infections. J Clin Microbiol 2017; 55:1269–1275 [View Article] [PubMed]
     [Google Scholar]
  21. Oakeson KF, Wagner JM, Rohrwasser A, Atkinson-Dunn R. Whole-genome sequencing and bioinformatic analysis of isolates from foodborne illness outbreaks of Campylobacter jejuni and Salmonella enterica. J Clin Microbiol 2018; 56:1–11 [View Article] [PubMed]
     [Google Scholar]
  22. Ribot EM, Fitzgerald C, Kubota K, Swaminathan B, Barrett TJ. Rapid pulsed-field gel electrophoresis protocol for subtyping of Campylobacter jejuni. J Clin Microbiol 2001; 39:1889–1894 [View Article] [PubMed]
     [Google Scholar]
  23. Kovac J, Bakker H den, Carroll LM, Wiedmann M. Precision food safety: a systems approach to food safety facilitated by genomics tools. TrAC Trends in Analytical Chemistry 2017; 96:52–61 [View Article]
     [Google Scholar]
  24. Cody AJ, McCarthy ND, Jansen van Rensburg M, Isinkaye T, Bentley SD et al. Real-time genomic epidemiological evaluation of human Campylobacter isolates by use of whole-genome multilocus sequence typing. J Clin Microbiol 2013; 51:2526–2534 [View Article] [PubMed]
     [Google Scholar]
  25. Cody AJ, Bray JE, Jolley KA, McCarthy ND, Maiden MCJ. Core genome multilocus sequence typing scheme for stable, comparative analyses of Campylobacter jejuni and C. coli human disease isolates. J Clin Microbiol 2017; 55:2086–2097 [View Article] [PubMed]
     [Google Scholar]
  26. Vincent C, Usongo V, Berry C, Tremblay DM, Moineau S et al. Comparison of advanced whole genome sequence-based methods to distinguish strains of Salmonella enterica serovar Heidelberg involved in foodborne outbreaks in Québec. Food Microbiol 2018; 73:99–110 [View Article] [PubMed]
     [Google Scholar]
  27. 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]
  28. Pearce ME, Alikhan NF, 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]
  29. 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] [PubMed]
     [Google Scholar]
  30. Tolar B, Joseph LA, Schroeder MN, Stroika S, Ribot EM et al. An overview of PulseNet USA databases. Foodborne Pathog Dis 2019; 16:457–462 [View Article] [PubMed]
     [Google Scholar]
  31. Waldram A, Dolan G, Ashton PM, Jenkins C, Dallman TJ. Epidemiological analysis of Salmonella clusters identified by whole genome sequencing, England and Wales 2014. Food Microbiol 2018; 71:39–45 [View Article] [PubMed]
     [Google Scholar]
  32. Holmes A, Allison L, Ward M, Dallman TJ, Clark R et al. Utility of whole-genome sequencing of Escherichia coli O157 for outbreak detection and epidemiological surveillance. J Clin Microbiol 2015; 53:3565–3573 [View Article] [PubMed]
     [Google Scholar]
  33. Moura A, Criscuolo A, Pouseele H, Maury MM, Leclercq A et al. Whole genome-based population biology and epidemiological surveillance of Listeria monocytogenes. Nat Microbiol 2016; 2:16185 [View Article] [PubMed]
     [Google Scholar]
  34. Gerner-Smidt P, Besser J, Concepción-Acevedo J, Folster JP, Huffman J et al. Whole genome sequencing: bridging one-health surveillance of foodborne diseases. Front Public Health 2019; 7:172 [View Article] [PubMed]
     [Google Scholar]
  35. Chattaway MA, Dallman TJ, Larkin L, Nair S, McCormick J et al. The transformation of reference microbiology methods and surveillance for Salmonella with the use of whole genome sequencing in England and Wales. Front Public Health 2019; 7:317 [View Article] [PubMed]
     [Google Scholar]
  36. Katz LS, Griswold T, Williams-Newkirk AJ, Wagner D, Petkau A et al. A comparative analysis of the Lyve-SET phylogenomics pipeline for genomic epidemiology of foodborne pathogens. Front Microbiol 2017; 8:375 [View Article] [PubMed]
     [Google Scholar]
  37. Jackson KA, Stroika S, Katz LS, Beal J, Brandt E et al. Use of whole genome sequencing and patient interviews to link a case of sporadic listeriosis to consumption of prepackaged lettuce. J Food Prot 2016; 79:806–809 [View Article] [PubMed]
     [Google Scholar]
  38. 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; 22:1–12 [View Article] [PubMed]
     [Google Scholar]
  39. Besser J, Carleton HA, Gerner-Smidt P, Lindsey RL, Trees E. Next-generation sequencing technologies and their application to the study and control of bacterial infections. Clin Microbiol Infect 2018; 24:335–341 [View Article] [PubMed]
     [Google Scholar]
  40. Gerner-Smidt P, Hise K, Kincaid J, Hunter S, Rolando S et al. PulseNet USA: a five-year update. Foodborne Pathog Dis 2006; 3:9–19 [View Article] [PubMed]
     [Google Scholar]
  41. Wickham H. ggplot2: Elegant Graphics for Data Analysis, Springer-Verlag New York; 2016 https://ggplot2.tidyverse.org
  42. Letunic I, Bork P. Interactive Tree Of Life (iTOL) v5: an online tool for phylogenetic tree display and annotation. Nucleic Acids Res 2021; 49:W293–W296 [View Article] [PubMed]
     [Google Scholar]
  43. Baker FB. Stability of two hierarchical grouping techniques case I: sensitivity to data errors. J Am Stat Assoc 1974; 69:440–445 [View Article]
     [Google Scholar]
  44. Saraçli S, Doğan N, Doğan İ. Comparison of hierarchical cluster analysis methods by cophenetic correlation. J Inequal Appl 2013; 2013:1–8 [View Article]
     [Google Scholar]
  45. Mourkas E, Yahara K, Bayliss SC, Calland JK, Johansson H et al. Host ecology regulates interspecies recombination in bacteria of the genus Campylobacter. Elife 2022; 11:e73552 [View Article] [PubMed]
     [Google Scholar]
  46. Golz JC, Stingl K. Natural competence and horizontal gene transfer in Campylobacter. Curr Top Microbiol Immunol 2021; 431:265–292 [View Article] [PubMed]
     [Google Scholar]
  47. Marasini D, Fakhr MK. Exploring PFGE for detecting large plasmids in Campylobacter jejuni and Campylobacter coli isolated from various retail meats. Pathogens 2014; 3:833–844 [View Article] [PubMed]
     [Google Scholar]
  48. Marasini D, Karki AB, Bryant JM, Sheaff RJ, Fakhr MK. Molecular characterization of megaplasmids encoding the type VI secretion system in Campylobacter jejuni isolated from chicken livers and gizzards. Sci Rep 2020; 10:12514 [View Article] [PubMed]
     [Google Scholar]
  49. Gencay YE, Sørensen MCH, Wenzel CQ, Szymanski CM, Brøndsted L. Phase variable expression of a single phage receptor in Campylobacter jejuni NCTC12662 influences sensitivity toward several diverse CPS-dependent phages. Front Microbiol 2018; 9:82 [View Article] [PubMed]
     [Google Scholar]
  50. Owens J, Barton MD, Heuzenroeder MW. The isolation and characterization of Campylobacter jejuni bacteriophages from free range and indoor poultry. Vet Microbiol 2013; 162:144–150 [View Article] [PubMed]
     [Google Scholar]
  51. Sørensen MCH, Gencay YE, Birk T, Baldvinsson SB, Jäckel C et al. Primary isolation strain determines both phage type and receptors recognised by Campylobacter jejuni bacteriophages. PLoS One 2015; 10:e0116287 [View Article] [PubMed]
     [Google Scholar]
  52. Nennig M, Llarena A-K, Herold M, Mossong J, Penny C et al. Investigating major recurring Campylobacter jejuni lineages in Luxembourg using four core or whole genome sequencing typing schemes. Front Cell Infect Microbiol 2020; 10:608020 [View Article] [PubMed]
     [Google Scholar]
/content/journal/mgen/10.1099/mgen.0.001012
Loading
Evaluation of core genome and whole genome multilocus sequence typing schemes for Campylobacter jejuni and Campylobacter coli outbreak detection in the USA
M Gen 9, 001012 (2023); https://doi.org/10.1099/mgen.0.001012
/content/journal/mgen/10.1099/mgen.0.001012
/content/journal/mgen/10.1099/mgen.0.001012
Loading

Data & Media loading...

Supplements

Supplementary material 1

PDF

Supplementary material 2

ARCHIVE

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