Sequencing and Beyond?
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The document discusses the strengths, weaknesses, opportunities, and threats (SWOT) of using whole genome sequencing (WGS) for surveillance and diagnostics of zoonotic bacteria. It provides a case study of using WGS to track the nosocomial transmission of Pseudomonas aeruginosa between patients and the hospital water supply. WGS was able to identify transmission routes and microevolution of the bacteria with single nucleotide resolution. However, challenges include the need for robust and standardized analysis methods as well as experimental design considerations. Overall, WGS provides opportunities for improved outbreak tracking, classification, and diagnostics if its strengths are leveraged and weaknesses addressed.
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Sequencing and Beyond?
- 1. Sequencing and Beyond? Risks and SWOT for sequencing-led surveillance and diagnostics of zoonotic bacteria Leighton Pritchard1;2;3 1Information and Computational Sciences, 2Centre for Human and Animal Pathogens in the Environment, 3Dundee Eector Consortium, The James Hutton Institute, Invergowrie, Dundee, Scotland, DD2 5DA
- 2. Acceptable Use Policy Recording of this talk, taking photos, discussing the content using email, Twitter, blogs, etc. is permitted (and encouraged), providing distraction to others is minimised. This presentation will be available on SlideShare.
- 3. Table of Contents SWOT analysis Case Study Nosocomial P.aeruginosa acquisition Strengths Weaknesses Opportunities Threats Acknowledgements Without Whom. . .
- 4. What is SWOT? A generic structured planning/categorisation method Identify the objective, and identify internal and external factors that can help or harm reaching that objective. Strengths: characteristics of sequencing approaches that may be helpful Weaknesses: characteristics of sequencing approaches that might be harmful Opportunities: external elements that could be helpful Threats: external elements that may be harmful Its purpose is to guide strategies that might help achieve objectives.
- 6. Table of Contents SWOT analysis Case Study Nosocomial P.aeruginosa acquisition Strengths Weaknesses Opportunities Threats Acknowledgements Without Whom. . .
- 7. P.aeruginosa nosocomial acquisitiona a Quick et al. (2014) BMJ Open 4: e006278. doi:10.1136/bmjopen-2014-006278 Motivation Nosocomial water transmission of P.aeruginosa an urgent concern
- 8. P.aeruginosa nosocomial acquisitiona a Quick et al. (2014) BMJ Open 4: e006278. doi:10.1136/bmjopen-2014-006278 Motivation Nosocomial water transmission of P.aeruginosa an urgent concern Setup Burns patients (30) screened for P.aeruginosa on admission Samples taken from patients and environment All P.aeruginosa isolates (141) WGS sequenced
- 9. P.aeruginosa nosocomial acquisitiona a Quick et al. (2014) BMJ Open 4: e006278. doi:10.1136/bmjopen-2014-006278 Motivation Nosocomial water transmission of P.aeruginosa an urgent concern Setup Burns patients (30) screened for P.aeruginosa on admission Samples taken from patients and environment All P.aeruginosa isolates (141) WGS sequenced Outcome Clustering of isolates by room and outlet Three patient isolates identical to water isolates from same room Bio
- 10. lm from thermostatic mixer valve a possible source
- 11. P.aeruginosa nosocomial acquisitiona a Quick et al. (2014) BMJ Open 4: e006278. doi:10.1136/bmjopen-2014-006278
- 12. P.aeruginosa nosocomial acquisitiona a Quick et al. (2014) BMJ Open 4: e006278. doi:10.1136/bmjopen-2014-006278 Methods Illumina MiSeq WGS of 141 isolates Metagenomic sequencing of bio
- 13. lm Simulated sequencing of 55 published P. aeruginosa BWA mapping against PAO1 reference genome SNPs called with SAMtools VarScan ML reconstruction with FastTree De novo assembly with Velvet for MLST prediction Sequences and bioinformatic methods shared online: http://www.github.com/joshquick/snp calling scripts
- 14. P.aeruginosa nosocomial acquisitiona a Quick et al. (2014) BMJ Open 4: e006278. doi:10.1136/bmjopen-2014-006278
- 15. P.aeruginosa nosocomial acquisitiona a Quick et al. (2014) BMJ Open 4: e006278. doi:10.1136/bmjopen-2014-006278
- 16. P.aeruginosa nosocomial acquisitiona a Quick et al. (2014) BMJ Open 4: e006278. doi:10.1136/bmjopen-2014-006278 Strengths A P. aeruginosa source could be tracked by WGS Insights into transmission: water to patient a likely route Sensitivity - identi
- 18. P.aeruginosa nosocomial acquisitiona a Quick et al. (2014) BMJ Open 4: e006278. doi:10.1136/bmjopen-2014-006278 Strengths A P. aeruginosa source could be tracked by WGS Insights into transmission: water to patient a likely route Sensitivity - identi
- 19. es microevolution Limitations Small sample size: 5/30 patients infected, gave 55/141 isolates Not clear that causal inferences are general 300-day sampling, not real-time crisis analysis Good existing reference genome set for this bacterium Sequencing cost: $8k; Sta cost: $15k; (infrastructure $?)
- 20. Table of Contents SWOT analysis Case Study Nosocomial P.aeruginosa acquisition Strengths Weaknesses Opportunities Threats Acknowledgements Without Whom. . .
- 21. Strength: Illumina Illumina sequencing is a stable, widespread technology Low price: $50 per WGS bacterial genome Robust software for assembly/mapping Single assay pipeline for multiple species Promise of (near) real-time genotyping and surveillance
- 22. Strength: Nature of information (Almost) complete genome sequence information with WGS Extremely sensitive: whole-genomes at single SNP/indel resolution Enables tracing of microevolution Data is digital, and in
- 23. nitely sharable Reference repositories for data: ENA/SNA, NCBI etc. Can build on public sequence data
- 24. Strength: Active RD area Technology is still moving forward: good things will get better Nanopore promises cheap, long reads Assembly/SNP calling tools can improve New techniques, technologies, software, : : : Active
- 25. elds attract bright people
- 26. Table of Contents SWOT analysis Case Study Nosocomial P.aeruginosa acquisition Strengths Weaknesses Opportunities Threats Acknowledgements Without Whom. . .
- 27. Weakness: New technologies New technologies may not be robust or reliable Readily available only in more developed nations; in labs, not farms/factories? New sequencing technologies still to be proven (Nanopore) Lack of plug-and-play analysis solutions: requires statistical/computing/biological expertise Plethora of assembly/mapping tools: results and quality vary Stability of results/analysis
- 28. Weakness: Nature of information Data integrity, availability critical for success Siloing of data (no public submission) can happen Inaccurate or incorrect reference/public data Inadequate, incorrect or absent metadata (new ontologies?) Unstable results between software/technology versions Reproducibility of analyses Genome sequence does not generally predict phenotype
- 29. Weakness: Experimental design Technology does not replace a well-designed experiment Temptation to collect data
- 30. rst, ask scienti
- 31. c question later Identi
- 32. cation of appropriate metadata (or not) Sample deeply enough for sucient power (or not) WGS vs metagenomics colonies vs communities whole genomes vs identi
- 33. able fragments evolution vs composition
- 34. Table of Contents SWOT analysis Case Study Nosocomial P.aeruginosa acquisition Strengths Weaknesses Opportunities Threats Acknowledgements Without Whom. . .
- 35. Opportunities: Existing resources Existing resources oer opportunities for cataloguing and classi
- 36. cation Large, expanding isolate collections (Fera, etc.) Local isolate collections Large, expanding reference databases (ENA/SRA, NCBI, etc.) Consortia with similar interests (e.g. GMI)
- 38. er No need to reinvent the wheel : : : http://www.globalmicrobialidenti
- 39. er.org/
- 40. Classi
- 41. cation/diagnostics Comprehensive sequence data could be highly in uential High-resolution tracing of outbreaks/contamination/transfer Combine with system-scale understanding of transport/trade
- 42. Classi
- 43. cation/diagnostics Comprehensive sequence data could be highly in uential High-resolution tracing of outbreaks/contamination/transfer Combine with system-scale understanding of transport/trade Pangenome-based view of bacteria Improved taxonomic (and phenotypic?) classi
- 44. cation High-resolution long-term epidemiological records Improved cheap, quick, prospective/sentinel/early diagnostic tools
- 45. E.coli classi
- 46. cation Brunei20070942_contigs Muenster20063091_contigs Senftenberg20070885_contigs Lys142_contigs Lys175_contigs Lys130_contigs Lys170_contigs Lys126_contigs Lys167_contigs Lys176_contigs Lys169_contigs Lys50_contigs X5038_contigs Lys131_contigs Lys171_contigs Lys111_contigs Lys107_contigs Lys114_contigs Lys16_contigs Lys22_contigs Lys65_contigs Lys56_contigs Lys113_contigs Lys109_contigs Lys77_contigs Lys102_contigs Lys100_contigs Lys92_contigs Lys94_contigs Lys80_contigs Lys64_contigs Lys82_contigs AW3_contigs X5008_contigs AW4_contigs AW1_contigs Lys118_contigs Lys138_contigs Lys121_contigs Lys122_contigs Lys177_contigs Lys155_contigs Lys165_contigs Lys163_contigs Lys160_contigs Lys161_contigs Lys172_contigs Lys144_contigs Lys135_contigs Lys146_contigs Lys123_contigs Lys124_contigs Lys150_contigs Lys140_contigs Lys157_contigs Lys173_contigs Lys156_contigs Lys158_contigs Lys159_contigs Lys162_contigs Lys5_contigs X5084_contigs X5042_contigs Lys110_contigs Lys136_contigs Lys54_contigs Lys1_contigs Lys6_contigs Lys112_contigs X5012_contigs Lys30_contigs Lys25_contigs Lys43_contigs Lys37_contigs Lys40_contigs Lys151_contigs Lys31_contigs Lys27_contigs Lys42_contigs Lys51_contigs Lys33_contigs Lys46_contigs Lys38_contigs Lys89_contigs Lys23_contigs Lys115_contigs Lys108_contigs Lys104_contigs DSM10973_contigs Lys125_contigs Lys105_contigs Lys17_contigs Lys128_contigs Lys66_contigs Lys73_contigs Lys15_contigs Lys91_contigs DSM8698_contigs DSM8695_contigs Lys74_contigs Lys61_contigs Lys9_contigs Lys153_contigs Lys84_contigs Lys93_contigs Lys72_contigs Lys62_contigs Lys21_contigs Lys59_contigs Lys63_contigs Lys83_contigs Lys19_contigs Lys4_contigs AW13_contigs Lys45_contigs Lys28_contigs Lys53_contigs Lys52_contigs Lys34_contigs Lys36_contigs Lys24_contigs Lys35_contigs Lys68_contigs Lys106_contigs Lys88_contigs Lys97_contigs Lys76_contigs Lys134_contigs Lys58_contigs Lys71_contigs Lys81_contigs Lys129_contigs Lys120_contigs Lys145_contigs Lys137_contigs Lys127_contigs Lys152_contigs Lys101_contigs Lys98_contigs Lys70_contigs Lys133_contigs Lys47_contigs Lys75_contigs Lys48_contigs Lys148_contigs Lys139_contigs Lys141_contigs Lys164_contigs Lys149_contigs Lys147_contigs Lys60_contigs Lys79_contigs Lys168_contigs Lys18_contigs Lys87_contigs Lys96_contigs Lys7_contigs Lys154_contigs Lys117_contigs Lys119_contigs Lys178_contigs Lys116_contigs Lys86_contigs Lys90_contigs Lys41_contigs Lys13_contigs Lys85_contigs X5002_contigs Lys12_contigs Lys39_contigs Lys14_contigs Lys55_contigs Lys29_contigs Lys99_contigs X5035_contigs Lys8_contigs Lys3_contigs X5034_contigs X5088_contigs Lys20_contigs Lys78_contigs Lys11_contigs Lys11_contigs Lys78_contigs Lys20_contigs 5088_contigs 5034_contigs Lys3_contigs Lys8_contigs 5035_contigs Lys99_contigs Lys29_contigs Lys55_contigs Lys14_contigs Lys39_contigs Lys12_contigs 5002_contigs Lys85_contigs Lys13_contigs Lys41_contigs Lys90_contigs Lys86_contigs Lys116_contigs Lys178_contigs Lys119_contigs Lys117_contigs Lys154_contigs Lys7_contigs Lys96_contigs Lys87_contigs Lys18_contigs Lys168_contigs Lys79_contigs Lys60_contigs Lys147_contigs Lys149_contigs Lys164_contigs Lys141_contigs Lys139_contigs Lys148_contigs Lys48_contigs Lys75_contigs Lys47_contigs Lys133_contigs Lys70_contigs Lys98_contigs Lys101_contigs Lys152_contigs Lys127_contigs Lys137_contigs Lys145_contigs Lys120_contigs Lys129_contigs Lys81_contigs Lys71_contigs Lys58_contigs Lys134_contigs Lys76_contigs Lys97_contigs Lys88_contigs Lys106_contigs Lys68_contigs Lys35_contigs Lys24_contigs Lys36_contigs Lys34_contigs Lys52_contigs Lys53_contigs Lys28_contigs Lys45_contigs AW13_contigs Lys4_contigs Lys19_contigs Lys83_contigs Lys63_contigs Lys59_contigs Lys21_contigs Lys62_contigs Lys72_contigs Lys93_contigs Lys84_contigs Lys153_contigs Lys9_contigs Lys61_contigs Lys74_contigs DSM8695_contigs DSM8698_contigs Lys91_contigs Lys15_contigs Lys73_contigs Lys66_contigs Lys128_contigs Lys17_contigs Lys105_contigs Lys125_contigs DSM10973_contigs Lys104_contigs Lys108_contigs Lys115_contigs Lys23_contigs Lys89_contigs Lys38_contigs Lys46_contigs Lys33_contigs Lys51_contigs Lys42_contigs Lys27_contigs Lys31_contigs Lys151_contigs Lys40_contigs Lys37_contigs Lys43_contigs Lys25_contigs Lys30_contigs 5012_contigs Lys112_contigs Lys6_contigs Lys1_contigs Lys54_contigs Lys136_contigs Lys110_contigs 5042_contigs 5084_contigs Lys5_contigs Lys162_contigs Lys159_contigs Lys158_contigs Lys156_contigs Lys173_contigs Lys157_contigs Lys140_contigs Lys150_contigs Lys124_contigs Lys123_contigs Lys146_contigs Lys135_contigs Lys144_contigs Lys172_contigs Lys161_contigs Lys160_contigs Lys163_contigs Lys165_contigs Lys155_contigs Lys177_contigs Lys122_contigs Lys121_contigs Lys138_contigs Lys118_contigs AW1_contigs AW4_contigs 5008_contigs AW3_contigs Lys82_contigs Lys64_contigs Lys80_contigs Lys94_contigs Lys92_contigs Lys100_contigs Lys102_contigs Lys77_contigs Lys109_contigs Lys113_contigs Lys56_contigs 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- 47. Dickeya classi
- 48. cationa a van der Wolf et al. (2014) IJSEM 64: 768-774. doi:10.1099/ijs.0.052944-0
- 49. Pangenome description Core genes are present in all isolates of a group
- 50. Pangenome description Horizontal lines are Dickeya isolate genomes Coloured links are core genes Gaps are accessory genes
- 51. Pangenome description Accessory genes only occur in some members of a group
- 53. Diagnostics design targets o-targets classication V IV III II I genomes Start with correctly-classi
- 54. ed reference set of genomes
- 55. Diagnostics design targets o-targets classication V IV III II I genomes Design diagnostic tools for all genomes, e.g. qPCR primer sets
- 56. Diagnostics design targets V IV III II I genomes I II III IV V Predict speci
- 57. city of tools in silico
- 58. Diagnostics design Validate against known, unseen examples Successful at species level in Dickeya1, sub-serotype level in E. coli 2 targets classication o-targets V IV III II I primer sets validation gels I II III IV V III IV V +ve -ve III IV V +ve -ve III IV V +ve -ve III IV V +ve -ve II V I III 1 Pritchard et al. (2013) Plant Path. 62: 587-596. doi:10.1111/j.1365-3059.2012.02678.x 2 Pritchard et al. (2012) PLoS One 7: e34498. doi:10.1371/journal.pone.0034498
- 59. Diagnostics design Distinguish at species level in Dickeya3, sub-serotype level in E. coli 4 3 Pritchard et al. (2013) Plant Path. 62: 587-596. doi:10.1111/j.1365-3059.2012.02678.x 4 Pritchard et al. (2012) PLoS One 7: e34498. doi:10.1371/journal.pone.0034498
- 60. Table of Contents SWOT analysis Case Study Nosocomial P.aeruginosa acquisition Strengths Weaknesses Opportunities Threats Acknowledgements Without Whom. . .
- 61. Threats: Funding Central and communal resources might not be supported,
- 62. nancially Whose responsibility is it? How to ensure funding continuity? Centralisation vs federation/distribution
- 63. Threats: Data Management Having lots of data brings its own problems Do analyses scale from 10s to 100s to 1000s to 10000s of sequences? (Where do we do the computing?) Metadata/data accuracy and provenance Data standards (minimum information) Common analytical standards Timely collection/generation/release in a crisis
- 64. Scaling Moving from 30 genome to 1000 genome pairwise comparisons New algorithms, storage and visualisation tools required
- 65. Threats: Data Legalities Who owns what? Who owns public data? (and who owns the results of analysis?) Legal/
- 66. nancial implications of identi
- 67. able association, such as pathogen with location (e.g. an identi
- 68. able farm or factory)? Will all data be released - siloing? national security? trade sensitivity?
- 69. Threats: Skills Managing and analysing data requires speci
- 70. c skills New algorithms and techniques for scale New visualisation and other software tools Tools/interfaces for usability Data curators are extremely important! Is there a skills shortage? Industry better-paid? Old guard may not appreciate these needs [employer] isn't interested in an equation as an academic exercise. You [: : :] might want to do some [computing] thing that's [...] special, but we're not interested.
- 71. Table of Contents SWOT analysis Case Study Nosocomial P.aeruginosa acquisition Strengths Weaknesses Opportunities Threats Acknowledgements Without Whom. . .
- 72. Acknowledgements James Hutton Institute Nicola Holden Fiona Brennan Sonia Humphris Ian Toth Emma Campbell University of Aberdeen Ken Forbes Norval Strachan SASA Gerry Saddler FERA Valerie Bertrand John Elphinstone Neil Parkinson University of Munster Martina Bielaszewska Helge Karch GitHub Benjamin Leopold Michael Robeson
- 73. Licence: CC-BY-SA By: Leighton Pritchard This presentation is licensed under the Creative Commons Attribution ShareAlike license https://creativecommons.org/licenses/by-sa/4.0/