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Choosing the Right Tool for the Job Handyman, Expert or DIY? Jacob Moran-Gilad, MD MPH ESCAIDE 2015 Eurosurveillance Seminar, 12 Nov 2015 Choosing the right tool? first let s define the Job! Local / hospital Emergency situation Type


  1. Choosing the Right Tool for the Job – Handyman, Expert or DIY? Jacob Moran-Gilad, MD MPH ESCAIDE 2015 – Eurosurveillance Seminar, 12 Nov 2015

  2. Choosing the right tool? first let ’ s define the Job! Local / hospital Emergency situation Type of organism NRC Diversity / typeability ‘ One-off ’ / ad hoc International Routine task Type of sample Type of setting Microbiologist Outbreak investigation Epidemiologist Population study Clinician Research

  3. What makes a Bacterial Typing Tool ‘ Right ’ ? • Typeability & Discriminatory power • Reproducibility & Stability over time • Cost effectiveness • Ease of adoption and use, Speed • Agreed nomenclature, harmonised results • Portability and accessibility • Scalability • Amenable to QC/QA

  4. Where does typing take place? All over!

  5. Shall we refine the question? Choosing the Right (Bioinformatics) Tool for the Job?!

  6. What ’ s between typing and mobile phones?

  7. Microbiological challenges - Legionella pneumophila • A significant cause of waterborne infections • Explosive outbreaks, a ‘ celebrity ’ disease • Difficult to control, highly regulated • Heavy reliance on traditional methods • Clinical diagnostic challenges • Cluster investigation challenges • International networking paramount • Need to ‘ personalise ’ risk assessment

  8. Evolution of Lp typing – mAbs C. Luck JMM 1995

  9. Evolution of Lp typing - RAPD N.S. Bansal & F. McDonell JCM 1997

  10. Evolution of Lp typing - AFLP N.K. Fry et al., CMI 2005

  11. Evolution of Lp typing - PFGE H. Zhou et al., AEM 2010

  12. Evolution of Lp typing – The ‘ EWGLI ’ SBT ST1 7 genes flaA, pilE, asd, mip, mompS, proA, neuA J. Moran-Gilad et al., CMI 2013

  13. Evolution of Lp typing – MLVA-8 C. Pourcel et al., JCM 2007

  14. Evolution of Lp typing – Spoligotyping Ginevra et al. JCM 2012

  15. Microbiological challenges - Acinetobacter spp. • A significant cause of healthcare-associated infections worldwide • High morbidity and mortality • Difficult-to-treat – MDR / XDR / PR • Various syndromes; unpredictable clinical course • Traditional micro methods – limited • Complex hospital epidemiology • Suboptimal typing schemes

  16. Evolution of Ab typing – rep-PCR 100 20 30 40 50 60 70 80 90 1882 1963 4598 193 Other 4871 1590 822 pattern 4620 4488 19606 377 s 406 1831 1832 1257 1893 1302 1329 172 Rep- 4555 4523 439 PCR 1576 661 1982 4570 Pattern 1278 1378 1869 1311 3 359 1818 1858 Rep- 1404 1445 1958 PCR 586 849 292 Pattern 446 59 320 230 Rep- 2 504 5657 5897 5780 PCR 108 5587 5510 Pattern 217 1985 559 647 1 409 Other 534 42 4663 patters 5862 6029

  17. Evolution of Ab typing - AFLP L. Dijkshoorn et al., JCM 1996

  18. Evolution of Ab typing - PFGE H. Seifert et al., JCM 2005

  19. Evolution of Ab typing - MLVA J. Turton et al., EJCMID 2009

  20. Evolution of Ab typing – MLST (Oxford) S.G. Bartual et al., JCM 2005

  21. Evolution of Ab typing – MLST (Pasteur) A. DiPopolo et al., CMI 2011

  22. Evolution of Ab typing – 3LT (Poor man ’ s MLST) J. Turton et al., CMI 2007

  23. Evolution of Ab typing – MLST comparison

  24. Evolution of Ab typing – ‘ Tower of Babylon ’ R. Zarrilli et al. IJAA 2013

  25. Evolution of typing - NGS S. Shokralla et al. Molecular Ecology 2012

  26. NGS - a Disruptive Technology Bioinformatics, IT Sample NGS Processing infrastructure Platforms

  27. NGS Application in Public Health Micro

  28. Contribution of Eurosurveillance to the body of knowledge on WGS typing

  29. NGS Application for LD Investigation - England S. Reuter et al. BMJ Open 2013

  30. NGS Application for LD Investigation – Australia R.M.A Graham et al. Epidemiol Infect 2014

  31. NGS Application for LD Investigation - Canada S. Levesque et al. PLOS One 2014

  32. NGS Application for Ab investigation T. Lewis et al. J Hosp Infect 2010

  33. NGS Application for Ab investigation S.J. Salipante et al. JCM 2015

  34. NGS Application in Public Health Micro

  35. Current cgMLST Schemes

  36. Development of cgMLST scheme for Lp J. Moran-Gilad et al. Eurosurv 2015

  37. Development of cgMLST scheme for Lp J. Moran-Gilad et al. Eurosurv 2015

  38. Development of cgMLST scheme for Lp J. Moran-Gilad et al. Eurosurv 2015

  39. Development of cgMLST scheme for Lp J. Moran-Gilad et al. Eurosurv 2015

  40. Development of cgMLST scheme for Lp C 1,518 / 1,623 core genes used H J. Moran-Gilad et al. Eurosurv 2015

  41. cgMLST changes our understanding of epi Triple Lp (including double ST1) infection stemming from cold 282-1 (ST1) water system feeding the filtrator H and aerosolised via humidifier 286-1 (ST1) 286-2 (ST93) 283/285 (ST1) C O N 286-1 (ST1) 283/285 (ST1) 283/285 286-2 (ST93) 284 (ST1) (ST1) J. Moran-Gilad et al. Eurosurv 2015

  42. Acinetobacter baumannii cgMLST M. Silva et al. ECCMID 2015

  43. Diagnostic hierarchy in the era of NGS is driven by bioinformatics C&C Expert Handyman DIY

  44. Expert DIY Handyman J. Moran-Gilad et al. BMC ID 2015

  45. Current Public Health Challenges for Choosing the Right (Bioinformatics) Tools • Adoption of cgMLST schemes as a standard tool and making them publicly available and widely implemented • Continuously optimise cgMLST schemes ( refined core genome, backward compatibility , setting thresholds for interpretability ) • Build capacity for add-on SNP-based analyses for enhanced resolution (micro-evolution, tree directionality) • Ensure quality , validation and harmonisation of WGS typing (create nomenclature, proficiency testing, reference materials) • IT Infrastructure , data integration , genome repositories • Human resource - Cloning of bioinformaticians?

  46. The ESGLI NGS WG

  47. Future Challenges for Developing the Right Tools • Transferable pipelines to support routine NGS implementation globally – diffuse from Experts to DIY ’ s • Metagenomic FW&E microbiology • Metagenomic clinical sample analysis • Exploit BIG data, machine learning, cloud computing for real time global genomic epidemiology • Embrace, develop and train ‘ Public Health Informatics ’ as an allied discipline

  48. THANK YOU Prof. Jacob Moran-Gilad giladko@post.bgu.ac.il

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