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PulseNet International is a global network dedicated to laboratory-based surveillance for food-borne diseases. The network comprises the national and regional laboratory networks of Africa, Asia Pacific, Canada, Europe, Latin America and the Caribbean, the Middle East, and the United States. The PulseNet International vision is the standardised use of whole genome sequencing (WGS) to identify and subtype food-borne bacterial pathogens worldwide, replacing traditional methods to strengthen preparedness and response, reduce global social and economic disease burden, and save lives. To meet the needs of real-time surveillance, the PulseNet International network will standardise subtyping via WGS using whole genome multilocus sequence typing (wgMLST), which delivers sufficiently high resolution and epidemiological concordance, plus unambiguous nomenclature for the purposes of surveillance. Standardised protocols, validation studies, quality control programmes, database and nomenclature development, and training should support the implementation and decentralisation of WGS. Ideally, WGS data collected for surveillance purposes should be publicly available, in real time where possible, respecting data protection policies. WGS data are suitable for surveillance and outbreak purposes and for answering scientific questions pertaining to source attribution, antimicrobial resistance, transmission patterns, and virulence, which will further enable the protection and improvement of public health with respect to food-borne disease.


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  1. World Health Organization (WHO). WHO estimates of the global burden of foodborne diseases. Technical report. Geneva: WHO. [Accessed 16 Dec 2016]. Available from: http://www.who.int/foodsafety/publications/foodborne_disease/fergreport/en/
  2. Swaminathan B, Gerner-Smidt P, Ng L-K, Lukinmaa S, Kam K-M, Rolando S, et al. Building PulseNet International: an interconnected system of laboratory networks to facilitate timely public health recognition and response to foodborne disease outbreaks and emerging foodborne diseases. Foodborne Pathog Dis. 2006;3(1):36-50.  https://doi.org/10.1089/fpd.2006.3.36  PMID: 16602978 
  3. Nadon CA, Trees E, Ng LK, Møller Nielsen E, Reimer A, Maxwell N, et al. Development and application of MLVA methods as a tool for inter-laboratory surveillance. Euro Surveill. 2013;18(35):20565.  https://doi.org/10.2807/1560-7917.ES2013.18.35.20565  PMID: 24008231 
  4. Barrett TJ, Gerner-Smidt P, Swaminathan B. Interpretation of pulsed-field gel electrophoresis patterns in foodborne disease investigations and surveillance. Foodborne Pathog Dis. 2006;3(1):20-31.  https://doi.org/10.1089/fpd.2006.3.20  PMID: 16602976 
  5. Rumore JL, Tschetter L, Nadon C. The Impact of Multilocus Variable-Number Tandem-Repeat Analysis on PulseNet Canada Escherichia coli O157:H7 Laboratory Surveillance and Outbreak Support, 2008-2012. Foodborne Pathog Dis. 2016;13(5):255-61.  https://doi.org/10.1089/fpd.2015.2066  PMID: 26990274 
  6. Pichel M, Brengi SP, Cooper KLF, Ribot EM, Al-Busaidy S, Araya P, et al. . Standardization and international multicenter validation of a PulseNet pulsed-field gel electrophoresis protocol for subtyping Shigella flexneri isolates. Foodborne Pathog Dis. 2012;9(5):418-24.  https://doi.org/10.1089/fpd.2011.1067  PMID: 22506731 
  7. Aarestrup FM, Brown EW, Detter C, Gerner-Smidt P, Gilmour MW, Harmsen D, et al. Integrating genome-based informatics to modernize global disease monitoring, information sharing, and response. Emerg Infect Dis. 2012;18(11):e1.  https://doi.org/10.3201/eid1811.120453  PMID: 23092707 
  8. Carleton HA, Gerner-smidt P. Whole-Genome Sequencing Is Taking over Foodborne Disease Surveillance. Microbe Mag. 2016;11(7):311-7. Available from: http://www.asmscience.org/content/journal/microbe/10.1128/microbe.11.311.1
  9. Dallman T, Inns T, Jombart T, Ashton P, Loman N, Chatt C, et al. Phylogenetic structure of European Salmonella Enteritidis outbreak correlates with national and international egg distribution network. Microb Genom. 2016;2(8):e000070.  https://doi.org/10.1099/mgen.0.000070  PMID: 28348865 
  10. 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 
  11. Holmes A, Allison L, Ward M, Dallman TJ, Clark R, Fawkes A, et al. Utility of whole-genome sequencing of Escherichia coli O157 for outbreak detection and epidemiological surveillance. J Clin Microbiol. 2015;53(11):3565-73.  https://doi.org/10.1128/JCM.01066-15  PMID: 26354815 
  12. Mossong J, Decruyenaere F, Moris G, Ragimbeau C, Olinger CM, Johler S, et al. Investigation of a staphylococcal food poisoning outbreak combining case-control, traditional typing and whole genome sequencing methods, Luxembourg, June 2014. Euro Surveill. 2015;20(45):30059.  https://doi.org/10.2807/1560-7917.ES.2015.20.45.30059  PMID: 26608881 
  13. Butcher H, Elson R, Chattaway MA, Featherstone CA, Willis C, Jorgensen F, et al. Whole genome sequencing improved case ascertainment in an outbreak of Shiga toxin-producing Escherichia coli O157 associated with raw drinking milk. Epidemiol Infect. 2016;144(13):2812-23.  https://doi.org/10.1017/S0950268816000509  PMID: 27338677 
  14. Joensen KG, Scheutz F, Lund O, Hasman H, Kaas RS, Nielsen EM, et al. Real-time whole-genome sequencing for routine typing, surveillance, and outbreak detection of verotoxigenic Escherichia coli. J Clin Microbiol. 2014;52(5):1501-10.  https://doi.org/10.1128/JCM.03617-13  PMID: 24574290 
  15. The INFOSAN Activity Report 2014/2015. Geneva: World Health Organization. [Accessed 16 Dec 2016]. Available from: http://www.who.int/foodsafety/publications/infosan_activity2014-15/en/
  16. Mardis ER. Next-generation sequencing platforms. Annu Rev Anal Chem (Palo Alto, Calif). 2013;6(1):287-303.  https://doi.org/10.1146/annurev-anchem-062012-092628  PMID: 23560931 
  17. Xavier BB, Sabirova J, Pieter M, Hernalsteens J-P, de Greve H, Goossens H, et al. Employing whole genome mapping for optimal de novo assembly of bacterial genomes. BMC Res Notes. 2014;7(1):484.  https://doi.org/10.1186/1756-0500-7-484  PMID: 25077983 
  18. Gardner SN, Hall BG. When whole-genome alignments just won’t work: kSNP v2 software for alignment-free SNP discovery and phylogenetics of hundreds of microbial genomes. PLoS One. 2013;8(12):e81760.  https://doi.org/10.1371/journal.pone.0081760  PMID: 24349125 
  19. 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 
  20. Wasyl D, El Sedawy A, Lukinmaa S. PulseNet Europe - international molecular subtyping network for food-borne disease surveillance. Med Weter. 2008;64(2):123-6.
  21. European Centre for Disease Control and Prevention (ECDC). Expert Opinion on the introduction of next-generation typing methods for food- and waterborne diseases in the EU and EEA Stockholm: ECDC; 2014. [Accessed Dec 2016]. Available from: http://ecdc.europa.eu/en/publications/Publications/food-and-waterborne-diseases-next-generation-typing-methods.pdf
  22. Marakeby H, Badr E, Torkey H, Song Y, Leman S, Monteil CL, et al. A system to automatically classify and name any individual genome-sequenced organism independently of current biological classification and nomenclature. PLoS One. 2014;9(2):e89142.  https://doi.org/10.1371/journal.pone.0089142  PMID: 24586551 
  23. 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;2:16185.  https://doi.org/10.1038/nmicrobiol.2016.185  PMID: 27723724 
  24. Sheppard SK, Jolley KA, Maiden MC. A Gene-By-Gene Approach to Bacterial Population Genomics: Whole Genome MLST of Campylobacter. Genes (Basel). 2012;3(2):261-77.  https://doi.org/10.3390/genes3020261  PMID: 24704917 
  25. World Health Organization (WHO). One Health. Geneva: WHO; April 2017. Available from: http://www.who.int/features/qa/one-health/en/
  26. Shendure J, Ji H. Next-generation DNA sequencing. Nat Biotechnol. 2008;26(10):1135-45.  https://doi.org/10.1038/nbt1486  PMID: 18846087 
  27. Olsen RJ, Long SW, Musser JM. Bacterial genomics in infectious disease and the clinical pathology laboratory. Arch Pathol Lab Med. 2012;136(11):1414-22.  https://doi.org/10.5858/arpa.2012-0025-RA  PMID: 22439809 
  28. Food and Agriculture Organization (FAO). Application of whole genome sequencing in food safety management. Rome: FAO; 2016. [Accessed 28 Aug 2016]. Available from: http://www.fao.org/documents/card/en/c/61e44b34-b328-4239-b59c-a9e926e327b4/
  29. Allard MW, Strain E, Melka D, Bunning K, Musser SM, Brown EW, et al. Practical Value of Food Pathogen Traceability through Building a Whole-Genome Sequencing Network and Database. J Clin Microbiol. 2016;54(8):1975-83.  https://doi.org/10.1128/JCM.00081-16  PMID: 27008877 
  30. 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 
  31. Scharff RL, Besser J, Sharp DJ, Jones TF, Peter G-S, Hedberg CW. An Economic Evaluation of PulseNet: A Network for Foodborne Disease Surveillance. Am J Prev Med. 2016;50(5) Suppl 1;S66-73.  https://doi.org/10.1016/j.amepre.2015.09.018  PMID: 26993535 

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