Se ha denunciado esta presentación.
Utilizamos tu perfil de LinkedIn y tus datos de actividad para personalizar los anuncios y mostrarte publicidad más relevante. Puedes cambiar tus preferencias de publicidad en cualquier momento.

Whole Genome Sequencing (WGS): How significant is it for food safety?

2.179 visualizaciones

Publicado el

Presentation on the Technical Paper developed by FAO in collaboration with WHO. Presentation from the Technical Meeting on the impact of Whole Genome Sequencing (WGS) on food safety management -23-25 May 2016, Rome, Italy.

© FAO:

Publicado en: Educación
  • Inicia sesión para ver los comentarios

  • Sé el primero en recomendar esto

Whole Genome Sequencing (WGS): How significant is it for food safety?

  1. 1. Whole Genome Sequencing: How significant is it for food safety? Technical Meeting on the impact of Whole Genome Sequencing on food safety management within a One Health framework GMI9 23 May 2016 Celine Nadon, PhD Public Health Agency of Canada
  2. 2. The Paper Expert Workshop, December 2015, Rome Frank Møller Aarestrup (Chair, Denmark) Marc Allard (USA) John Besser (USA) Sabah Bidawid (Canada) Tim Dallman (UK) Stephanie Defibaugh-Chávez (USA) John N. Kiiru (Kenya) Ana Maria Maquieira (Uruguay) Paula Mussio (Uruguay) Celine Nadon (Vice-Chair, Canada) Eva Møller Nielsen (Denmark) Sophie Roussel (France)
  3. 3. Outline Background Examples BenePits & Drawbacks Regulatory challenge Resource Considerations Discussion Conclusions & Summary Why WGS for food safety? Technical Paper sec.on 2 Real-life applicaEons Technical Paper Sec.on 3 Technical Paper Sec.on 4 Applying WGS within regulatory frameworks Technical Paper Sec.on 5 Countries with limited capacity & resources Technical Paper Sec.on 6 One Health and needed global acEons Technical Paper Sec.on 7
  4. 4. Background 600 000 000 WHO, 2015 420 000 foodborne illnesses deaths 31 major food safety hazards
  5. 5. Background WGS will impact food safety worldwide DISEASE SURVEILLANCE FOOD INSPECTION OUTBREAK INVESTIGATION ATTRIBUTION FOOD TECHNOLOGY Centre Image: Smithsonian InsEtuEon
  6. 6. Background test$1$ test$2$ test$3$ test$4$ test$5$ purpose$1$$ purpose$2$$ purpose$3$$ purpose$4$ purpose$5$ $ $ lab$1$ lab$2$ lab$3$ lab$4$ lab$5$ Courtesy of Aleisha Reimer
  7. 7. Background Sample collection Bacterial Growth DNA Extraction Fragment SequencingRaw Sequence Reads Prep DNA Library DATA
  8. 8. Background Laboratory subtyping methods affect outbreak detection and response Adapted from John Besser, 2006
  9. 9. Background of food safety problems from imprecise or incorrect product implicaEons IdentiPication, mitigation and prevention Reduced economic losses and waste food security
  10. 10. Examples WGS is already being used for food safety what can we learn?
  11. 11. Examples Available at HIGHER RESOLUTION Listeriosis outbreak, United States 2014
  12. 12. Examples PFGE CLUSTER 1 PFGE CLUSTER 2 PFGE CLUSTER 3 Seasonal food product Seasonal food product & other* WGS CLUSTER WGS CLUSTER Seasonal food product Seasonal food product not outbreak-associated *ready-to-eat food product commonly associated with L. monocytogenes Adapted from Besser, 2015 HIGHER RESOLUTION Listeriosis outbreak, United States 2014
  13. 13. Examples WGS CLUSTER WGS CLUSTER Seasonal food product not outbreak-associated Confirmed hypothesis quickly Added strength to evidence Resolved ambiguous lab-epi data Accelerated response due to data sharing Fueled research for prevenEon What did WGS do? HIGHER RESOLUTION Listeriosis outbreak, United States 2014
  14. 14. Examples REDEFINED “SPORADIC” Listeriosis cases, Denmark 2014-2015 TOTAL CASES 5-YEAR MOVING AVERAGE Sporadic case: any illnesses below expected levels?
  15. 15. Examples REDEFINED “SPORADIC” Listeriosis cases, Denmark 2014-2015 10 cases over 24 months WGS CLUSTER Environmental samples from Company X, supplier to Supermarket
  16. 16. Examples REDEFINED “SPORADIC” Listeriosis cases, Denmark 2014-2015 WGS CLUSTER Detected and confirmed source of illnesses that would have otherwise been “sporadic” What did WGS do? Enabled strong evidence from environmental and food sampling Delineated outbreaks caused by the same product type from different companies
  17. 17. Examples UNCOVERED ROOT CAUSE Salmonella EnteriEdis, UK 2014 EnteriEdis phagetype 14b Inns et al – Eurosurveillance 2015 Associated with ea^ng at restaurants
  18. 18. Examples UNCOVERED ROOT CAUSE Salmonella EnteriEdis, UK 2014 Inns et al – Eurosurveillance 2015 Restaurant associa^on was just the beginning: WGS showed •  Outbreaks at different restaurants were linked •  Egg distribuEon network correlated with distribuEon of cases •  Traceback of eggs to single supplier in another country, and linked to cases outside of UK
  19. 19. Examples UNCOVERED ROOT CAUSE Salmonella EnteriEdis, UK 2014 Revealed the epidemiology behind the outbreak What did WGS do? IdenEfied true source – rather than implicaEng restaurant business only, as the interface with the consumer Enabled targeted intervenEon further upstream in food producEon Demonstrated benefits of global WGS sharing
  20. 20. Examples MOTIVATE ACTION Kenyan Experience Vibrio Salmonella Campylobacter E. coli
  21. 21. Examples MOTIVATE ACTION Kenyan Experience Demonstrates value of mapping disease hotspots, idenEfying high risk foods, revising treatment What did WGS do? Increases consideraEon to investments in food safety Fuels interest in regulatory intervenEons, food tesEng, AMR Illuminates need for advocacy
  22. 22. Examples Why were these applications successful? •  FuncEoning naEonal food control system •  Inter-sectoral infrastructure & networks (including laboratory) •  Adequate volume of isolates (cost effecEve) •  Ability to isolate pathogens from all matrices •  Technical support: laboratory, bioinformaEcs •  Sufficient data storage and connecEvity •  InformaEcs capacity and infrastructure
  23. 23. BenePits Image: Chris Rinke, available at UNIVERSALITY STRENGTH TO EVIDENCE
  24. 24. Drawbacks Image: Chris Rinke, available at SURVEILLANCE REQUIRED
  25. 25. Global Data Sharing Improves food safety sciences Efficient use of resources Enables trend analysis & rapid response MiEgates health, social, economic impacts InequiEes in capacity & resources Data ownership & metadata access Accountability & transparency ValidaEon, standards & quality Fear of being “scooped” Technical trade barriers Privacy law
  26. 26. Regulatory Challenge GUIDELINES AND BEST PRACTICES ROLE OF WGS IN EXISTING STREAMS OF EVIDENCE DATA ACCESS & TRANSPARENCY Developed countries: Factors to consider for using WGS in regulatory decisions need to be sorted out legal issues trade impacts quality control training communication sustainability continuous improvement
  27. 27. Regulatory Challenge ASSESS AND SENSITIZE Developing countries: (YES) (NO) STRENGTHEN NATIONAL FOOD SAFETY DEVELOP AND EDUCATE TRANSITION & FUND Prepare policy makers, and assess: is your country’s infrastructure ready for WGS? Build/enhance human health surveillance, food monitoring/testing, laboratories. Decision-making guidance, rationale, cost- benefit, leverage other countries’ experiences. Educate & train. Establish stakeholder engagement. Implement national coordination mechanisms. Harmonize SOPs. Sensitize. Sustainable funding.
  28. 28. Resource Considerations PERCEPTION “WGS is too advanced and too difficult to implement” “WGS is the perfect soluEon to all our problems”
  29. 29. Resource Considerations Feasibility Assessment quesEons for fact-based answers PRIORITIES Is food safety high priority? Are many people affected? Are industry, trade and economy affected? Will WGS help with the priority pathogens? PREREQUISITES NaEonal food safety policy and integrated food control system in place? FuncEonal naEonal health surveillance, with naEonal clinical reporEng and databases? FuncEonal naEonal food monitoring and tesEng? READINESS Where is the appropriate place for naEonal coordinaEon? How will the system work? Can other resources be leveraged, e.g. WHO, FAO, PulseNet InternaEonal, Global Microbial IdenEfier?
  30. 30. One Health Image: Nagasaki University WGS can help bridge inter-sectoral approaches through a truly global common dataset
  32. 32. Conclusion Countries with existing effective food safety & health systems well posiEoned for adopEng WGS Others may need to develop or strengthen the basics Pirst competent authoriEes, labs, food monitoring, human health surveillance WGS will become standard methodology in food safety Expected to be beneficial for all countries, with some challenges remaining Greater role for international organizations Neutral and transparent brokers? WGS will not supplant epidemiology and basic good practices WGS alone will not fix lacking or broken systems Global sustained commitment and collaboration Ensure technology advances do not contribute to further inequiEes
  33. 33. Acknowledgements Masami Takeuchi (FAO, Document Development Coordinator) Markus Lipp (FAO), Renata Clarke (FAO) Document Peer-Reviewers: Saoud Al Habsi (Oman), Genevieve Baah-Mante (Ghana), Chris Braden (USA), Josefina Campos (ArgenEna), Isabel Chinen (ArgenEna), Almueda C. David (Philippines), Joanne Edge (UK), Mariam Eid (Lebanon), Dina El-Khishin (Egypt), Jeff Farber (Canada), Agaba Friday (Uganda), Peter Gerner-Smidt (USA), Morag Graham (Canada), Kai Man Kam (China), Karen Keddy (South Africa), Ernesto Liebana (EFSA), Virachnee Lohachoompol (Thailand), Kinley Pelden (Bhutan), Jennifer Ronholm (Canada), Jorgen Shlundt (Denmark), MarEn Wiedmann (USA), Seyoum Wolde (Ethiopia), and Mayren Zamora (Mexico) Vanessa Jones, Sarah Cahill (FAO), Amy Louise Cawthorne (WHO), Gwenalaelle Dauphin (FAO), Francisco Lopez (FAO) Editing and Technical Contributions: