1887
Research article Open Access
Like 0

Abstract

Background and aim

The trend in reported case counts of invasive (), a potentially severe food-borne disease, has been increasing since 2008. In 2015, 2,224 cases were reported in the European Union/European Economic Area (EU/EEA). We aimed to validate the microbiological and epidemiological aspects of an envisaged EU/EEA-wide surveillance system enhanced by routine whole genome sequencing (WGS). WGS and core genome multilocus sequence typing (cgMLST) were performed on isolates from 2,726 cases from 27 EU/EEA countries from 2010–15. Quality controls for contamination, mixed cultures and sequence quality classified nearly all isolates with a minimum average coverage of the genome of 55x as acceptable for analysis. Assessment of the cgMLST variation between six different pipelines revealed slightly less variation associated with assembly-based analysis compared to reads-based analysis. Epidemiological concordance, based on 152 isolates from 19 confirmed outbreaks and a cluster cutoff of seven allelic differences, was good (sensitivity > 95% for two cgMLST schemes of 1,748 and 1,701 loci each; PPV 58‒68%). The proportion of sporadic cases was slightly below 50%. Of remaining isolates, around one third were in clusters involving more than one country, often spanning several years. Detection of multi-country clusters was on average several months earlier when pooling the data at EU/EEA level, compared with first detection at national level. : These findings provide a good basis for comprehensive EU/EEA-wide, WGS-enhanced surveillance of listeriosis. Time limits should not be used for hypothesis generation during outbreak investigations, but should be for analytical studies.

Loading

Article metrics loading...

/content/10.2807/1560-7917.ES.2018.23.33.1700798
2018-08-16
2018-09-21
http://instance.metastore.ingenta.com/content/10.2807/1560-7917.ES.2018.23.33.1700798
Loading
Loading full text...

Full text loading...

/deliver/fulltext/eurosurveillance/23/33/eurosurv-23-33-2.html?itemId=/content/10.2807/1560-7917.ES.2018.23.33.1700798&mimeType=html&fmt=ahah

References

  1. de Noordhout CM, Devleesschauwer B, Angulo FJ, Verbeke G, Haagsma J, Kirk M, et al. The global burden of listeriosis: a systematic review and meta-analysis. Lancet Infect Dis. 2014;14(11):1073-82.  https://doi.org/10.1016/S1473-3099(14)70870-9  PMID: 25241232 
  2. Charlier C, Perrodeau É, Leclercq A, Cazenave B, Pilmis B, Henry B, et al. MONALISA study group. Clinical features and prognostic factors of listeriosis: the MONALISA national prospective cohort study. Lancet Infect Dis. 2017;17(5):510-9.  https://doi.org/10.1016/S1473-3099(16)30521-7  PMID: 28139432 
  3. Lamont RF, Sobel J, Mazaki-Tovi S, Kusanovic JP, Vaisbuch E, Kim SK, et al. Listeriosis in human pregnancy: a systematic review. J Perinat Med. 2011;39(3):227-36.  https://doi.org/10.1515/jpm.2011.035  PMID: 21517700 
  4. European Centre for Disease Prevention and Control (ECDC). Surveillance Atlas of Infectious Diseases. Stockholm: ECDC. [Accessed: 10 Mar 2016]. Available from: http://atlas.ecdc.europa.eu
  5. Goulet V, King LA, Vaillant V, de Valk H. What is the incubation period for listeriosis? BMC Infect Dis. 2013;13(1):11.  https://doi.org/10.1186/1471-2334-13-11  PMID: 23305174 
  6. Lundén J, Autio T, Markkula A, Hellström S, Korkeala H. Adaptive and cross-adaptive responses of persistent and non-persistent Listeria monocytogenes strains to disinfectants. Int J Food Microbiol. 2003;82(3):265-72.  https://doi.org/10.1016/S0168-1605(02)00312-4  PMID: 12593929 
  7. Keto-Timonen R, Tolvanen R, Lundén J, Korkeala H. An 8-year surveillance of the diversity and persistence of Listeria monocytogenes in a chilled food processing plant analyzed by amplified fragment length polymorphism. J Food Prot. 2007;70(8):1866-73.  https://doi.org/10.4315/0362-028X-70.8.1866  PMID: 17803143 
  8. Gerner-Smidt P, Hise K, Kincaid J, Hunter S, Rolando S, Hyytiä-Trees E, et al. Pulsenet Taskforce. PulseNet USA: a five-year update. Foodborne Pathog Dis. 2006;3(1):9-19.  https://doi.org/10.1089/fpd.2006.3.9  PMID: 16602975 
  9. Jackson BR, Tarr C, Strain E, Jackson KA, Conrad A, Carleton H, et al. Implementation of Nationwide Real-time Whole-genome Sequencing to Enhance Listeriosis Outbreak Detection and Investigation. Clin Infect Dis. 2016;63(3):380-6.  https://doi.org/10.1093/cid/ciw242  PMID: 27090985 
  10. Moura A, Criscuolo A, Pouseele H, Maury MM, Leclercq A, Tarr C, et al. Whole genome-based population biology and epidemiological surveillance of Listeria monocytogenes. Nat Microbiol. 2016;2(2):16185.  https://doi.org/10.1038/nmicrobiol.2016.185  PMID: 27723724 
  11. Moura A, Tourdjman M, Leclercq A, Hamelin E, Laurent E, Fredriksen N, et al. Real-Time Whole-Genome Sequencing for Surveillance of Listeria monocytogenes, France. Emerg Infect Dis. 2017;23(9):1462-70.  https://doi.org/10.3201/eid2309.170336  PMID: 28643628 
  12. European Centre for Disease Prevention and Control (ECDC). ECDC roadmap for integration of molecular and genomic typing into European-level surveillance and epidemic preparedness – Version 2.1, 2016-2019. Stockholm: ECDC; 2016. Available from: http://ecdc.europa.eu/en/publications/Publications/molecular-typing-EU-surveillance-epidemic-preparedness-2016-19-roadmap.pdf
  13. van Belkum A, Tassios PT, Dijkshoorn L, Haeggman S, Cookson B, Fry NK, et al. European Society of Clinical Microbiology and Infectious Diseases (ESCMID) Study Group on Epidemiological Markers (ESGEM). Guidelines for the validation and application of typing methods for use in bacterial epidemiology. Clin Microbiol Infect. 2007;13(Suppl 3):1-46.  https://doi.org/10.1111/j.1469-0691.2007.01786.x  PMID: 17716294 
  14. Mellmann A, Harmsen D, Cummings CA, Zentz EB, Leopold SR, Rico A, et al. Prospective genomic characterization of the German enterohemorrhagic Escherichia coli O104:H4 outbreak by rapid next generation sequencing technology. PLoS One. 2011;6(7):e22751.  https://doi.org/10.1371/journal.pone.0022751  PMID: 21799941 
  15. Maiden MC, Jansen van Rensburg MJ, Bray JE, Earle SG, Ford SA, Jolley KA, et al. MLST revisited: the gene-by-gene approach to bacterial genomics. Nat Rev Microbiol. 2013;11(10):728-36.  https://doi.org/10.1038/nrmicro3093  PMID: 23979428 
  16. European Centre for Disease Prevention and Control (ECDC). Expert Opinion on the introduction of next-generation typing methods for food- and waterborne diseases in the EU and EEA. Stockholm: ECDC; 2015. Available from: https://ecdc.europa.eu/en/publications-data/expert-opinion-introduction-next-generation-typing-methods-food-and-waterborne
  17. Nadon C, Van Walle I, Gerner-Smidt P, Campos J, Chinen I, Concepcion-Acevedo J, et al. FWD-NEXT Expert Panel. PulseNet International: Vision for the implementation of whole genome sequencing (WGS) for global food-borne disease surveillance. Euro Surveill. 2017;22(23):30544.  https://doi.org/10.2807/1560-7917.ES.2017.22.23.30544  PMID: 28662764 
  18. Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30(15):2114-20.  https://doi.org/10.1093/bioinformatics/btu170  PMID: 24695404 
  19. Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M, Kulikov AS, et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol. 2012;19(5):455-77.  https://doi.org/10.1089/cmb.2012.0021  PMID: 22506599 
  20. Zerbino DR, Birney E. Velvet: algorithms for de novo short read assembly using de Bruijn graphs. Genome Res. 2008;18(5):821-9.  https://doi.org/10.1101/gr.074492.107  PMID: 18349386 
  21. Li H, Durbin R. Fast and accurate long-read alignment with Burrows-Wheeler transform. Bioinformatics. 2010;26(5):589-95.  https://doi.org/10.1093/bioinformatics/btp698  PMID: 20080505 
  22. Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods. 2012;9(4):357-9.  https://doi.org/10.1038/nmeth.1923  PMID: 22388286 
  23. Ruppitsch W, Pietzka A, Prior K, Bletz S, Fernandez HL, Allerberger F, et al. Defining and evaluating a core genome multilocus sequence typing scheme for whole-genome sequence-based typing of Listeria monocytogenes. J Clin Microbiol. 2015;53(9):2869-76.  https://doi.org/10.1128/JCM.01193-15  PMID: 26135865 
  24. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol. 1990;215(3):403-10.  https://doi.org/10.1016/S0022-2836(05)80360-2  PMID: 2231712 
  25. Maury MM, Tsai YH, Charlier C, Touchon M, Chenal-Francisque V, Leclercq A, et al. Uncovering Listeria monocytogenes hypervirulence by harnessing its biodiversity. Nat Genet. 2016;48(3):308-13.  https://doi.org/10.1038/ng.3501  PMID: 26829754 
  26. Holch A, Webb K, Lukjancenko O, Ussery D, Rosenthal BM, Gram L. Genome sequencing identifies two nearly unchanged strains of persistent Listeria monocytogenes isolated at two different fish processing plants sampled 6 years apart. Appl Environ Microbiol. 2013;79(9):2944-51.  https://doi.org/10.1128/AEM.03715-12  PMID: 23435887 
  27. Schmid D, Allerberger F, Huhulescu S, Pietzka A, Amar C, Kleta S, et al. Whole genome sequencing as a tool to investigate a cluster of seven cases of listeriosis in Austria and Germany, 2011-2013. Clin Microbiol Infect. 2014;20(5):431-6.  https://doi.org/10.1111/1469-0691.12638  PMID: 24698214 
  28. Stasiewicz MJ, Oliver HF, Wiedmann M, den Bakker HC. Whole-Genome Sequencing Allows for Improved Identification of Persistent Listeria monocytogenes in Food-Associated Environments. Appl Environ Microbiol. 2015;81(17):6024-37.  https://doi.org/10.1128/AEM.01049-15  PMID: 26116683 
  29. Orsi RH, Borowsky ML, Lauer P, Young SK, Nusbaum C, Galagan JE, et al. Short-term genome evolution of Listeria monocytogenes in a non-controlled environment. BMC Genomics. 2008;9(1):539.  https://doi.org/10.1186/1471-2164-9-539  PMID: 19014550 
  30. Gillesberg Lassen S, Ethelberg S, Björkman JT, Jensen T, Sørensen G, Kvistholm Jensen A, et al. Two listeria outbreaks caused by smoked fish consumption-using whole-genome sequencing for outbreak investigations. Clin Microbiol Infect. 2016;22(7):620-4.  https://doi.org/10.1016/j.cmi.2016.04.017  PMID: 27145209 
  31. European Collaborative Projects (Euroreference). The ECDC-EFSA molecular typing database for European Union public health protection. Europe: Euroreference; 2017;2:4-12.Available from: https://euroreference.anses.fr/sites/default/files/17%2003%20ED%20ER%2002%201_RIZZI.pdf
  32. Field N, Cohen T, Struelens MJ, Palm D, Cookson B, Glynn JR, et al. Strengthening the Reporting of Molecular Epidemiology for Infectious Diseases (STROME-ID): an extension of the STROBE statement. Lancet Infect Dis. 2014;14(4):341-52.  https://doi.org/10.1016/S1473-3099(13)70324-4  PMID: 24631223 
  33. EFSA BIOHAZ Panel (EFSA Panel on Biological Hazards), Ricci A, Allende A, Bolton D, Chemaly M, Davies R, et al. Scientific opinion on the Listeria monocytogenes contamination of ready-to-eat foods and the risk for human health in the EU. EFSA Journal 2018;16(1):5134. Available from: https://efsa.onlinelibrary.wiley.com/doi/abs/10.2903/j.efsa.2018.5134
/content/10.2807/1560-7917.ES.2018.23.33.1700798
Loading

Data & Media loading...

Comment has been disabled for this content
Submit comment
Close
Comment moderation successfully completed
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