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Whole genome microbiology for Salmonella public health microbiology

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My talk at #ASMNGS 2015

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Whole genome microbiology for Salmonella public health microbiology

  1. 1. Revolutionising Public Health Reference Microbiology Using Whole Genome Sequencing: A Case Study with Salmonella Philip Ashton Bioinformatician, Gastrointestinal Bacteria Reference Unit
  2. 2. 2 Salmonella WGS for Public Health PHE are using WGS as the routine test for Salmonella reference microbiology. All Salmonella isolates are being sequenced. No routine serotyping.
  3. 3. Why? How? What? Salmonella WGS for Public Health3
  4. 4. 4 Salmonella WGS for Public Health Why do we want to implement WGS for Salmonella reference micro?
  5. 5. 5 Salmonella WGS for Public Health > 38000 cases of Salmonella gastroenteritis in the UK per year, of which > 11000 report to their GP. Tam et al, 2011, Gut gut.2011.238386 Typhoidal Salmonella as well. 77 deaths in UK 2008, FSA Foodborne Disease Strategy
  6. 6. 6 Salmonella WGS for Public Health Tom Innes & PT14b OCT ‘protecting and improving the nation’s health’.
  7. 7. 7 Salmonella WGS for Public Health Previous typing method - serotyping Satheesh Nair
  8. 8. 8 Salmonella WGS for Public Health David Powell
  9. 9. 9 Salmonella WGS for Public Health PHE Salmonella surveillance data - http://bit.ly/1CdEOe0
  10. 10. 10 Salmonella WGS for Public Health PHE Salmonella surveillance data - http://bit.ly/1CdEOe0
  11. 11. Salmonella is a major public health issue. Existing typing/subtyping has limited phylogenetic insight. Need higher resolution typing methods (WGS) for monitoring trends and detecting outbreaks. Unique opportunity for global data sharing 11 Summary – why WGS? Salmonella WGS for Public Health
  12. 12. 12 Salmonella WGS for Public Health How will WGS based Salmonella reference microbiology work?
  13. 13. WGS implementation at PHE 2011- 2015 2 MiSeq machines 2 HiSeq 2500 high-throughput machines Capacity > 3,000 genomes per week + PHE investment in WGS: financial, laboratory, bioinformatics, data handling, staff training = Salmonella WGS for Public Health13
  14. 14. Identification / Mixed – kmer gateway K-mer Gateway 14 Acetobacter Acinetobacter Actinomyces Aeromonas Aggregatibacter Bacillus Bacteroides Bartonella Bifidobacterium Bordetella Borrelia Brucella Burkholderia Campylobacter Chlamydia Chlamydophila Clostridium Corynebacterium Desulfovibrio Enterobacter Enterococcus Escherichia Francisella Fusobacterium Gardnerella Gordonia Haemophilus Helicobacter Klebsiella Lactobacillus Legionella Leptospira Leuconostoc Listeria Morganella Mycobacterium Mycoplasma Neisseria Nocardia Paenibacillus Prevotella Propionibacterium Pseudomonas Rhizobium Rhodococcus Rickettsia Salmonella Shewanella Shigella Staphylococcus Streptococcus Streptomyces Treponema Ureaplasma Vibrio Yersinia Off all the k-mers of length 18 in each reference genome what percentage are in our sequencing reads? Can be used to identify cross species contamination. Salmonella WGS for Public Health 99.7% accurate subspeciation
  15. 15. 15 Salmonella WGS for Public Health Serotype inferred via MLST Satheesh Nair Achtman et al., 2012
  16. 16. MLST to infer serotype 16 Method Short Read Sequence Typing ST (and eburst group) Serotype Result Inouye et al., 2012 6887 strains with WGS and pheno 6616 (96%) results matched Salmonella WGS for Public Health 2 serotypes – 1 ST/EBG Lab error No ST/serotype lookup
  17. 17. Novel Sequence Types 17 Salmonella WGS for Public Health SISTR/SeqSero
  18. 18. 18 Salmonella WGS for Public Health Challenges: • Many different eburst groups (of STs) – have to be analysed separately • Hundreds of strains a week • Rapid, hands-off analysis Solution – SnapperDB: Most common serotypes – SNP typing Sample FASTQs (with ST) EBG 1 - Typhimuriumdb db db db db EBG 4 - Enteritidis EBG 13 - Typhi EBG 3 - Newport EBG 11 – Paratyphi A … 30 mins - parallel 5 min – 1 hour
  19. 19. 19 Salmonella WGS for Public Health What will be the output of WGS for Salmonella reference micro?
  20. 20. • Example of use in outbreak – PT14b • Strain characterisation – antibiotic resistance profile • Future perspectives 20 Salmonella WGS for Public Health
  21. 21. Salmonella NGS at PHE Salmonella Enteritidis Phage Type 14b International outbreak Tom Inns/PT14b Outbreak Control Team – Inns et al., Eurosurveillance, 2015
  22. 22. 22 Salmonella WGS for Public Health 0.02 * * * OUTBREAK 4 OUTBREAK 2 * OUTBREAK 3 OUTBREAK 3 OUTBREAK 2 OUTBREAK 3 OUTBREAK 5 * OUTBREAK 2 OUTBREAK 3 OUTBREAK 3 OUTBREAK 1 OUTBREAK 4 * * * OUTBREAK 3 OUTBREAK 3 OUTBREAK 3 OUTBREAK 1 * OUTBREAK 4 OUTBREAK 3 OUTBREAK 3 OUTBREAK 3 * * OUTBREAK 1 OUTBREAK 2 OUTBREAK 1 OUTBREAK 4 * OUTBREAK 1 OUTBREAK 3 OUTBREAK 4 OUTBREAK 2 OUTBREAK 4 * OUTBREAK 3 OUTBREAK 3 OUTBREAK 1 OUTBREAK 3 OUTBREAK 3 OUTBREAK 5 * OUTBREAK 3 OUTBREAK 3 OUTBREAK 1 OUTBREAK 4 OUTBREAK 3 OUTBREAK 2 * OUTBREAK 2 OUTBREAK 3 OUTBREAK 2 OUTBREAK 4 * OUTBREAK 3 * * OUTBREAK 3 * OUTBREAK 3 OUTBREAK 3 * * OUTBREAK 3 OUTBREAK 3 OUTBREAK 3 OUTBREAK 4 OUTBREAK 3 OUTBREAK 3 OUTBREAK 2 OUTBREAK 2 OUTBREAK 3 * OUTBREAK 2 OUTBREAK 5 * OUTBREAK 2 * * OUTBREAK 1 OUTBREAK 1 OUTBREAK 3 OUTBREAK 2 * OUTBREAK 2 OUTBREAK 1 OUTBREAK 3 * OUTBREAK 2 * OUTBREAK 2 OUTBREAK 1 * OUTBREAK 3 * OUTBREAK 1 * * OUTBREAK 1 OUTBREAK 3 OUTBREAK 3 * * OUTBREAK 3 OUTBREAK 3 * OUTBREAK 1 OUTBREAK 3 * OUTBREAK 4 * OUTBREAK 3 OUTBREAK 3 OUTBREAK 1 * OUTBREAK 4 * OUTBREAK 3 * OUTBREAK 3 * OUTBREAK 3 * * * OUTBREAK 1 OUTBREAK 2 OUTBREAK 3 OUTBREAK 3 OUTBREAK 2 * OUTBREAK 4 OUTBREAK 1 * OUTBREAK 1 * * * OUTBREAK 3 * * * OUTBREAK 2 * OUTBREAK 3 OUTBREAK 3 OUTBREAK 3 OUTBREAK 3 * * OUTBREAK 4 * OUTBREAK 3 OUTBREAK 3 OUTBREAK 3 OUTBREAK 1 OUTBREAK 3 OUTBREAK 1 OUTBREAK 4 * OUTBREAK 5 OUTBREAK 1 OUTBREAK 3 * OUTBREAK 4 * * * * OUTBREAK 1 OUTBREAK 3 OUTBREAK 3 OUTBREAK 4 OUTBREAK 2 OUTBREAK 2 * * * OUTBREAK 3 OUTBREAK 3 OUTBREAK 3 OUTBREAK 3 * OUTBREAK 3 * OUTBREAK 4 * * OUTBREAK 5 OUTBREAK 4 * * OUTBREAK 2 * OUTBREAK 3 * OUTBREAK 2 * OUTBREAK 2 OUTBREAK 4 OUTBREAK 4 OUTBREAK 5 * OUTBREAK 5 OUTBREAK 3 * OUTBREAK 4 OUTBREAK 1 * OUTBREAK 4 OUTBREAK 4 OUTBREAK 1 * * * OUTBREAK 5 OUTBREAK 2 * OUTBREAK 1 * * OUTBREAK 3 OUTBREAK 1 OUTBREAK 3 OUTBREAK 3 OUTBREAK 3 * OUTBREAK 3 * * OUTBREAK 1 OUTBREAK 1 * * OUTBREAK 1 * * OUTBREAK 1 OUTBREAK 4 * * OUTBREAK 3 OUTBREAK 4 * * * * OUTBREAK 2 * * OUTBREAK 4 OUTBREAK 3 * * OUTBREAK 1 OUTBREAK 1 * * OUTBREAK 4 OUTBREAK 3 * OUTBREAK 4 OUTBREAK 3 * OUTBREAK 3 OUTBREAK 4 OUTBREAK 2 OUTBREAK 1 * * OUTBREAK 4 * * OUTBREAK 4 OUTBREAK 4 OUTBREAK 4 OUTBREAK 1 OUTBREAK 3 * OUTBREAK 1 OUTBREAK 1 * * * OUTBREAK 2 * * OUTBREAK 3 OUTBREAK 2 * * OUTBREAK 3 OUTBREAK 1 OUTBREAK 4 * * OUTBREAK 2 OUTBREAK 2 * OUTBREAK 3 OUTBREAK 3 OUTBREAK 3 OUTBREAK 2 * * * OUTBREAK 1 OUTBREAK 3 * OUTBREAK 3 * OUTBREAK 4 OUTBREAK 5 OUTBREAK 1 OUTBREAK 1 * * * * OUTBREAK 3 OUTBREAK 3 OUTBREAK 1 * * OUTBREAK 3 * OUTBREAK 4 OUTBREAK 1 OUTBREAK 2 OUTBREAK 3 * OUTBREAK 3 OUTBREAK 1 OUTBREAK 3 * * * OUTBREAK 4 OUTBREAK 1 OUTBREAK 1 OUTBREAK 1 OUTBREAK 3 * OUTBREAK 4 OUTBREAK 4 OUTBREAK 3 OUTBREAK 1 * * * OUTBREAK 3 * * * OUTBREAK 2 * OUTBREAK 4 OUTBREAK 1 81094_H14372077201-1 OUTBREAK 2 OUTBREAK 2 OUTBREAK 3 * * OUTBREAK 1 OUTBREAK 2 * OUTBREAK 3 OUTBREAK 3 * OUTBREAK 3 OUTBREAK 3 OUTBREAK 2 OUTBREAK 1 * OUTBREAK 2 OUTBREAK 3 * OUTBREAK 3 OUTBREAK 3 OUTBREAK 3 OUTBREAK 1 OUTBREAK 4 OUTBREAK 3 * OUTBREAK 1 OUTBREAK 3 * * * * OUTBREAK 4 OUTBREAK 3 * OUTBREAK 1 * * OUTBREAK 3 OUTBREAK 4 * * OUTBREAK 3 * * OUTBREAK 1 * * OUTBREAK 1 OUTBREAK 2 OUTBREAK 4 OUTBREAK 4 OUTBREAK 2 OUTBREAK 3 OUTBREAK 1 * OUTBREAK 3 OUTBREAK 3 OUTBREAK 3 OUTBREAK 2 * OUTBREAK 1 OUTBREAK 3 OUTBREAK 3 OUTBREAK 2 0.02 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * ** * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * ** * * * * * * * * * * * * ** * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * Hospital – W.Mids Kebab Grill - London Chinese Restaurant - Wessex Chinese Restaurant - Cheshire Chinese Restaurant - Lancashire Tim Dallman, Tom Inns, Thibaut Jombart
  23. 23. Hierarchical clustering and Geography 23 Alison Waldram & Gayle Dolan
  24. 24. 24 Phenotype S Phenotype R Error% Genotype S Genotype R Genotype R Genotype S CHL 580 2 39 3 0.78 SUL 466 1 149 8 1.40 TET 467 3 151 3 0.93 TMP 562 3 57 2 0.78 AMP 484 5 134 1 0.93 CTX/CAZ 618 1 5 0 0.16 CPR 619 1 4 0 0.16 FOX 612 0 7 5 0.78 CIP 478 4 138 4 1.25 NAL 485 2 127 10 1.87 GEN 608 1 14 1 0.31 TOB 613 2 8 1 0.47 AMK 622 0 1 1 0.16 STR 486 18 119 1 2.96 7700 43 953 40 0.95 AMS: Genotype vs phenotype Major errors Very major errors Michel Doumith/Martin Day Validation : 642 Salmonella strains Resistance : 57.5 % susceptible 24.7 % multi-resistant (> 2 classes) Salmonella WGS for Public Health
  25. 25. Future perspectives 25 Salmonella WGS for Public Health • Move from MLST to kmer/phylogenetic placement for sorting before SNP analysis, especially for Enteritidis. • MinION sequencing: • Outbreak investigation (Quick, Ashton et al., Genome Biology, 2015, v16, p114), • Solving complex + interesting regions of the genome (Ashton, Nair et al., Nature Biotech, 2015, v33, p296) • Live streaming of sequencing data – google ‘Loman labs’ • National (One Health) and international (GenomeTrakr) real-time collaborations
  26. 26. Summary • WGS is a single test – multiple assays • Better quality information than existing tests • Evolutionary and phylogentic insight Salmonella WGS for Public Health26
  27. 27. Acknowledgements 27 Salmonella WGS for Public Health Microbiology Elizabeth de Pinna, Tansy Peters, Satheesh Nair, Martin Day, Anna Lewis, Tim Dallman, Kathie Grant and other staff in the Salmonella lab Epidemiology Alison Waldram (FETP), Richard Elson, Chris Lane, Tom Inns Genomic Services Unit Cath Arnold and team Bioinformatics Unit Jonathon Green, Anthony Underwood, Rediat Tewolde, et al.

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