1887

Abstract

serovar Enteritidis is a major cause of foodborne infections and outbreaks in humans. Effective surveillance and timely outbreak detection are essential for public health control. Multilevel genome typing (MGT) with multiple levels of resolution has been previously demonstrated as a promising tool for this purpose. In this study, we developed MGT with nine levels for . Enteritidis and characterised the genomic epidemiology of . Enteritidis in detail. We examined 26 670 publicly available . Enteritidis genome sequences from isolates spanning 101 years from 86 countries to reveal their spatial and temporal distributions. Using the lower resolution MGT levels, globally prevalent and regionally restricted sequence types (STs) were identified; avian associated MGT4-STs were found that were common in human cases in the USA; temporal trends were observed in the UK with MGT5-STs from 2014 to 2018 revealing both long lived endemic STs and the rapid expansion of new STs. Using MGT3 to MGT6, we identified multidrug resistance (MDR) associated STs at various MGT levels, which improves precision of detection and global tracking of MDR clones. We also found that the majority of the global . Enteritidis population fell within two predominant lineages, which had significantly different propensity of causing large scale outbreaks. An online open MGT database has been established for unified international surveillance of . Enteritidis. We demonstrated that MGT provides a flexible and high-resolution genome typing tool for . Enteritidis surveillance and outbreak detection.

Funding
This study was supported by the:
  • project grant from the National Health and Medical Research Council of Australia (Award 1129713)
    • Principle Award Recipient: NotApplicable
  • 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.0.000605
2021-07-22
2024-04-19
Loading full text...

Full text loading...

/deliver/fulltext/mgen/7/7/mgen000605.html?itemId=/content/journal/mgen/10.1099/mgen.0.000605&mimeType=html&fmt=ahah

References

  1. Dewey-Mattia D, Manikonda K, Hall AJ, Wise ME, Crowe SJ. Surveillance for foodborne disease outbreaks - United States, 2009-2015. MMWR Surveill Summ 2018; 67:1–11 [View Article] [PubMed]
    [Google Scholar]
  2. European Centre for Disease Prevention and Control Salmonellosis. In ECDC. Annual epidemiological report for 2017 Stockholm: ECDC; 2020
    [Google Scholar]
  3. Pijnacker R, Dallman TJ, Tijsma ASL, Hawkins G, Larkin L et al. An international outbreak of Salmonella enterica serotype Enteritidis linked to eggs from Poland: a microbiological and epidemiological study. Lancet Infect Dis 2019; 19:778–786 [View Article] [PubMed]
    [Google Scholar]
  4. Snyder TR, Boktor SW, M’Ikanatha NM. Salmonellosis outbreaks by food vehicle, serotype, season, and geographical location, United States, 1998 to 2015. J Food Prot 2019; 82:1191–1199 [View Article] [PubMed]
    [Google Scholar]
  5. Feasey NA, Hadfield J, Keddy KH, Dallman TJ, Jacobs J et al. Distinct Salmonella Enteritidis lineages associated with enterocolitis in high-income settings and invasive disease in low-income settings. Nat Genet, Article 2016; 48:1211–1217
    [Google Scholar]
  6. Mohan A, Munusamy C, Tan YC, Muthuvelu S, Hashim R et al. Invasive Salmonella infections among children in Bintulu, Sarawak, Malaysian Borneo: a 6-year retrospective review. BMC Infect Dis 2019; 19:330 [View Article] [PubMed]
    [Google Scholar]
  7. Thung TY, Mahyudin NA, Basri DF, Wan Mohamed Radzi CWJ, Nakaguchi Y et al. Prevalence and antibiotic resistance of Salmonella Enteritidis and Salmonella Typhimurium in raw chicken meat at retail markets in Malaysia. Poult Sci 2016; 95:1888–1893 [View Article] [PubMed]
    [Google Scholar]
  8. Akullian A, Montgomery JM, John-Stewart G, Miller SI, Hayden HS et al. Multi-drug resistant non-typhoidal Salmonella associated with invasive disease in western Kenya. PLoS Negl Trop Dis 2018; 12:e0006156 [View Article] [PubMed]
    [Google Scholar]
  9. Parn T, Dahl V, Lienemann T, Perevoscikovs J, De Jong B. Multi-country outbreak of Salmonella enteritidis infection linked to the international ice hockey tournament. Epidemiol Infect 2017; 145:2221–2230 [View Article] [PubMed]
    [Google Scholar]
  10. Deng X, Desai PT, den Bakker HC, Mikoleit M, Tolar B et al. Genomic epidemiology of Salmonella enterica serotype Enteritidis based on population structure of prevalent lineages. Emerg Infect Dis 2014; 20:1481–1489 [View Article] [PubMed]
    [Google Scholar]
  11. Graham RMA, Hiley L, Rathnayake IU, Jennison AV. Comparative genomics identifies distinct lineages of S. PLoS One 2018; 13:e0191042 [View Article] [PubMed]
    [Google Scholar]
  12. Achtman M, Wain J, Weill FX, Nair S, Zhou Z et al. Multilocus sequence typing as a replacement for serotyping in Salmonella enterica. PLoS Pathog 2012; 8:e1002776 [View Article] [PubMed]
    [Google Scholar]
  13. Alikhan NF, Zhou Z, Sergeant MJ, Achtman M. A genomic overview of the population structure of Salmonella. PLoS Genet 2018; 14:e1007261 [View Article] [PubMed]
    [Google Scholar]
  14. Zhou Z, Alikhan NF, Mohamed K, Fan Y, Agama Study G et al. The EnteroBase user’s guide, with case studies on Salmonella transmissions, Yersinia pestis phylogeny, and Escherichia core genomic diversity. Genome Res 2020; 30:138–152
    [Google Scholar]
  15. Ashton P, Nair S, Peters T, Tewolde R, Day M et al. Revolutionising public health reference microbiology using whole genome sequencing: Salmonella as an exemplar. bioRxiv 2015033225
    [Google Scholar]
  16. Zhou Z, Charlesworth J, Achtman M. HierCC: A multi-level clustering scheme for population assignments based on core genome MLST. Bioinformatics 2021
    [Google Scholar]
  17. Zhang S, Li S, Gu W, den Bakker H, Boxrud D et al. Zoonotic source attribution of Salmonella enterica serotype Typhimurium using genomic surveillance data, United States. Emerg Infect Dis 2019; 25:82–91 [View Article] [PubMed]
    [Google Scholar]
  18. Deng X, Shariat N, Driebe EM, Roe CC, Tolar B et al. Comparative analysis of subtyping methods against a whole-genome-sequencing standard for Salmonella enterica serotype Enteritidis. J Clin Microbiol 2015; 53:212–218 [View Article] [PubMed]
    [Google Scholar]
  19. Hormansdorfer S, Messelhausser U, Rampp A, Schonberger K, Dallman T et al. Re-evaluation of a 2014 multi-country European outbreak of Salmonella Enteritidis phage type 14b using recent epidemiological and molecular data. Euro Surveill 2017; 22:17–00196
    [Google Scholar]
  20. Payne M, Kaur S, Wang Q, Hennessy D, Luo L et al. Multilevel genome typing: Genomics-guided scalable resolution typing of microbial pathogens. Euro Surveill 2020; 25:1900519 [View Article]
    [Google Scholar]
  21. Gurevich A, Saveliev V, Vyahhi N, Tesler G. QUAST: quality assessment tool for genome assemblies. Bioinformatics 2013; 29:1072–1075 [View Article] [PubMed]
    [Google Scholar]
  22. Robertson J, Yoshida C, Kruczkiewicz P, Nadon C, Nichani A et al. Comprehensive assessment of the quality of Salmonella whole genome sequence data available in public sequence databases using the Salmonella In silico Typing Resource (SISTR). Microb Genom 2018; 4:
    [Google Scholar]
  23. Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 2014; 30:2114–2120 [View Article] [PubMed]
    [Google Scholar]
  24. Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol 2012; 19:455–477 [View Article] [PubMed]
    [Google Scholar]
  25. Souvorov A, Agarwala R, Lipman DJ. SKESA: strategic k-mer extension for scrupulous assemblies. Genome Biol 2018; 19:153 [View Article] [PubMed]
    [Google Scholar]
  26. Wood DE, Salzberg SL. Kraken: ultrafast metagenomic sequence classification using exact alignments. Genome Biol 2014; 15:R46 [View Article] [PubMed]
    [Google Scholar]
  27. Zhang S, Yin Y, Jones MB, Zhang Z, Deatherage Kaiser BL et al. Salmonella serotype determination utilizing high-throughput genome sequencing data. J Clin Microbiol 2015; 53:1685–1692 [View Article] [PubMed]
    [Google Scholar]
  28. Yoshida CE, Kruczkiewicz P, Laing CR, Lingohr EJ, Gannon VP et al. The Salmonella in silico Typing Resource (SISTR): An open web-accessible tool for rapidly typing and subtyping Draft Salmonella genome assemblies. PLoS One 2016; 11:e0147101 [View Article] [PubMed]
    [Google Scholar]
  29. Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics 2014; 30:2068–2069 [View Article] [PubMed]
    [Google Scholar]
  30. Kroger C, Dillon SC, Cameron AD, Papenfort K, Sivasankaran SK et al. The transcriptional landscape and small rnas of Salmonella enterica serovar Typhimurium. Proc Natl Acad Sci U S A 2012; 109:1277–1286
    [Google Scholar]
  31. Tableau (version. 9.1) J Med Libr Assoc 2016; 104:182–183 [View Article]
    [Google Scholar]
  32. Zankari E, Hasman H, Cosentino S, Vestergaard M, Rasmussen S et al. Identification of acquired antimicrobial resistance genes. J Antimicrob Chemother 2012; 67:2640–2644 [View Article] [PubMed]
    [Google Scholar]
  33. Carattoli A, Zankari E, Garcia-Fernandez 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]
  34. Treangen TJ, Ondov BD, Koren S, Phillippy AM. The Harvest suite for rapid core-genome alignment and visualization of thousands of intraspecific microbial genomes. Genome Biol 2014; 15:524 [View Article]
    [Google Scholar]
  35. Price MN, Dehal PS, Arkin AP. FastTree 2--approximately maximum-likelihood trees for large alignments. PloS one 2010; 5:e9490 [View Article] [PubMed]
    [Google Scholar]
  36. 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]
  37. Hu D, Liu B, Wang L, Reeves PR. Living trees: High-quality reproducible and reusable construction of bacterial phylogenetic trees. Mol Biol Evol 2020; 37:563–575 [View Article] [PubMed]
    [Google Scholar]
  38. Suchard MA, Lemey P, Baele G, Ayres DL, Drummond AJ et al. Bayesian phylogenetic and phylodynamic data integration using BEAST 1.10. Virus Evol 2018; 4:vey016 [View Article] [PubMed]
    [Google Scholar]
  39. Rambaut A, Drummond AJ, Xie D, Baele G, Suchard MA. Posterior summarization in bayesian phylogenetics using Tracer 1.7. Syst Biol 2018; 67:901–904 [View Article] [PubMed]
    [Google Scholar]
  40. Chen L, Yang J, Yu J, Yao Z, Sun L et al. VFDB: A reference database for bacterial virulence factors. Nucleic Acids Res 2005; 33:325–328
    [Google Scholar]
  41. Mansour MN, Yaghi J, El Khoury A, Felten A, Mistou MY et al. Prediction of Salmonella serovars isolated from clinical and food matrices in Lebanon and genomic-based investigation focusing on Enteritidis serovar. Int J Food Microbiol 2020; 333:108831 [View Article] [PubMed]
    [Google Scholar]
  42. Kendall MG. A new measure of rank correlation. Biometrika 1938; 30:81–93 [View Article]
    [Google Scholar]
  43. Feil EJ. Small change: keeping pace with microevolution. Nat Rev Microbiol 2004; 2:483–495 [View Article] [PubMed]
    [Google Scholar]
  44. Lawson B, Franklinos LHV, Rodriguez-Ramos Fernandez J, Wend-Hansen C, Nair S et al. Salmonella Enteritidis ST183: emerging and endemic biotypes affecting western European hedgehogs (Erinaceus europaeus) and people in Great Britain. Sci Rep 2018; 8:2449
    [Google Scholar]
  45. Kanagarajah S, Waldram A, Dolan G, Jenkins C, Ashton PM et al. Whole genome sequencing reveals an outbreak of Salmonella Enteritidis associated with reptile feeder mice in the United Kingdom, 2012-2015. Food Microbiol 2018; 71:32–38 [View Article] [PubMed]
    [Google Scholar]
  46. Payne M, Octavia S, LDW L, Sotomayor-Castillo C, Wang Q et al. Enhancing genomics-based outbreak detection of endemic Salmonella enterica serovar Typhimurium using dynamic thresholds. Microb Genom 2019
    [Google Scholar]
  47. 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 Pub Health 2019; 7:317
    [Google Scholar]
  48. Inns T, Lane C, Peters T, Dallman T, Chatt C et al. A multi-country Salmonella Enteritidis phage type 14b outbreak associated with eggs from a German producer: “near real-time” application of whole genome sequencing and food chain investigations, United Kingdom, May to September 2014. Euro Surveill 2015; 20:21098 [View Article]
    [Google Scholar]
  49. Inns T, Ashton P, Herrera-Leon S, Lighthill J, Foulkes S et al. Prospective use of whole genome sequencing (WGS) detected a multi-country outbreak of Salmonella Enteritidis. Epidemiol Infect 2017; 145:289–298 [View Article]
    [Google Scholar]
  50. Guiney DG, Fierer J. The role of the SPV genes in Salmonella pathogenesis. Front microbiol 2011; 2:129 [View Article] [PubMed]
    [Google Scholar]
  51. Zhang X, He L, Zhang C, Yu C, Yang Y et al. The impact of Ssek2 deletion on Salmonella enterica serovar typhimurium virulence in vivo and in vitro. BMC Microbiol 2019; 19:182 [View Article]
    [Google Scholar]
  52. Dallman T, Inns T, Jombart T, Ashton P, Loman N et al. Phylogenetic structure of European Salmonella enteritidis outbreak correlates with national and international Egg Distribution network. Microb Genom 2016; 2:e000070 [View Article]
    [Google Scholar]
  53. Nichols M, Stevenson L, Whitlock L, Pabilonia K, Robyn M et al. Preventing human Salmonella infections resulting from live poultry contact through interventions at retail stores. J Agric Saf Health 2018; 24:155–166 [View Article] [PubMed]
    [Google Scholar]
  54. Fu S, Octavia S, Tanaka MM, Sintchenko V, Lan R. Defining the core genome of Salmonella enterica SEROVAR typhimurium for genomic surveillance and epidemiological typing. J Clin Microbiol 2015; 53:2530–2538 [View Article] [PubMed]
    [Google Scholar]
  55. Taylor AJ, Lappi V, Wolfgang WJ, Lapierre P, Palumbo MJ et al. Characterization of foodborne outbreaks of Salmonella enterica SEROVAR enteritidis with whole-genome sequencing single nucleotide polymorphism-based analysis for surveillance and outbreak detection. J Clin Microbiol 2015; 53:3334–3340 [View Article] [PubMed]
    [Google Scholar]
  56. Vidovic S, An R, Rendahl A. Molecular and physiological characterization of fluoroquinolone-highly resistant Salmonella enteritidis strains. Front Microbiol 2019; 10:729 [View Article] [PubMed]
    [Google Scholar]
  57. Kaldhone PR, Carlton A, Aljahdali N, Khajanchi BK, Sanad YM et al. Evaluation of incompatibility Group i1 (inci1) plasmid-containing Salmonella enterica and assessment of the plasmids in bacteriocin production and biofilm development. Front Vet Sci 2019; 6:298 [View Article] [PubMed]
    [Google Scholar]
  58. Zhou X, Li M, Xu L, Shi C, Shi X. Characterization of antibiotic resistance genes, plasmids, biofilm formation, and in vitro invasion capacity of Salmonella enteritidis isolates from children with gastroenteritis. Microb Drug Resist 2019; 25:1191–1198 [View Article] [PubMed]
    [Google Scholar]
  59. Aldrich C, Hartman H, Feasey N, Chattaway MA, Dekker D et al. Emergence of phylogenetically diverse and fluoroquinolone resistant Salmonella Enteritidis as a cause of invasive nontyphoidal Salmonella disease in Ghana. PLoS Negl Trop Dis 2019; 13:e0007485 [View Article] [PubMed]
    [Google Scholar]
  60. Smalla K, Heuer H, Gotz A, Niemeyer D, Krogerrecklenfort E et al. Exogenous isolation of antibiotic resistance plasmids from piggery manure slurries reveals a high prevalence and diversity of IncQ-like plasmids. Appl Environ Microbiol 2000; 66:4854–4862 [View Article] [PubMed]
    [Google Scholar]
  61. Castellanos LR, van der Graaf-van Bloois L, Donado-Godoy P, Leon M, Clavijo V et al. Genomic characterization of Extended-Spectrum Cephalosporin-Resistant Salmonella enterica in the colombian poultry chain. Front Microbiol 2018; 9:2431 [View Article] [PubMed]
    [Google Scholar]
  62. Mastrorilli E, Pietrucci D, Barco L, Ammendola S, Petrin S et al. A comparative genomic analysis provides novel insights into the ecological success of the monophasic Salmonella Serovar 4,[5],12:i. Front Microbiol 2018; 9:715 [View Article] [PubMed]
    [Google Scholar]
  63. Wong MH, Kan B, Chan EW, Yan M, Chen S. IncI1 plasmids carrying various blaCTX-M genes contribute to ceftriaxone resistance in Salmonella enterica serovar enteritidis in China. Antimicrob Agents Chemother 2016; 60:982–989 [View Article] [PubMed]
    [Google Scholar]
  64. Garcia-Fernandez A, Chiaretto G, Bertini A, Villa L, Fortini D et al. Multilocus sequence typing of IncI1 plasmids carrying extended-spectrum beta-lactamases in Escherichia coli and Salmonella of human and animal origin. J Antimicrob Chemother 2008; 61:1229–1233 [View Article] [PubMed]
    [Google Scholar]
  65. Kameyama M, Chuma T, Yokoi T, Yabata J, Tominaga K et al. Emergence of Salmonella enterica serovar infantis harboring IncI1 plasmid with bla(CTX-M-14) in a broiler farm in Japan. J Vet Med Sci 2012; 74:1213–1216 [View Article] [PubMed]
    [Google Scholar]
  66. Pulford CV, Perez-Sepulveda BM, Canals R, Bevington JA, Bengtsson RJ et al. Stepwise evolution of Salmonella Typhimurium ST313 causing bloodstream infection in Africa. Nat Microbiol 2021; 6:327–338 [View Article] [PubMed]
    [Google Scholar]
  67. Silva CA, Blondel CJ, Quezada CP, Porwollik S, Andrews-Polymenis HL et al. Infection of mice by Salmonella enterica serovar Enteritidis involves additional genes that are absent in the genome of serovar Typhimurium. Infect Immun 2012; 80:839–849 [View Article] [PubMed]
    [Google Scholar]
http://instance.metastore.ingenta.com/content/journal/mgen/10.1099/mgen.0.000605
Loading
/content/journal/mgen/10.1099/mgen.0.000605
Loading

Data & Media loading...

Supplements

Supplementary material 1

PDF

Supplementary material 2

EXCEL

Supplementary material 3

EXCEL
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