Veterinary Public Health - Whole genome sequencing sink or ... ¢  Whole genome sequencing ... Lesley

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  • Whole genome sequencing –

    sink or swim… opportunities and challenges for veterinarians

    working in veterinary public health

    Lesley Larkin Public Health England

    12 October 2019

  • Overview

    1. Introduction

    • Public Health England

    • Whole genome

    sequencing

    2. How we are using

    WGS – examples

    3. Impact, challenges and

    opportunities for

    veterinarians working

    in public health

    4. Key conclusions

    Source: google images

  • Introduction – Public Health England

    Infectious disease surveillance and

    control:

    ➢ Reference microbiology services

    ➢ FW&E laboratory services

    ➢ National epidemiology team in London

    ➢ Regional teams – epidemiologists and

    Health Protection Teams

    Functions:

    ✓ National and regional surveillance for

    infectious diseases

    ✓ Outbreak detection and investigation

    (PHE lead)

    ✓ Research and production of guidance

  • Introduction - whole genome sequencing

    • PHE processes and analyses

    approximately 1,000 bacterial

    genome sequences each week.

    • Routine sequencing and use for

    surveillance purposes:

    – Mycobacteria

    – Salmonella

    – Listeria

    – Shigatoxin producing E. coli

    – Campylobacter

    etc

  • Assessing genetic similarity between

    genomes

    • Bacteria DNA broken down into fragments and markers

    attached (short read sequencing)

    • Short reads lined up against a reference genome and

    variants compared between strains

    • A SNP or single nucleotide polymorphism is a one

    base difference in the bacteria’s DNA compared to a

    reference genome A G T C G C G T A T G T C T G A C C C

    A G T C G C A T G T A T

    C G C G T A T A T G A C C C

    A G T C G C G A T G A C C C

    G T A T G T A

    T C G C G T G T A T G A

    A G T C G C G A T G A C

    G C G T A T

    T G T A T

    C G T A T G

    Reference genome

    Isolate genome pieces

    Single nucleotide polymorphism (SNP)

  • Two matching SNP addresses indicate that the isolates are ‘~genetically identical’

    5 SNP level corresponds to typical outbreak diversity

    SNP threshold 250 100 50 25 10 5 0

    Isolate 1 1 2 18 158 199 222 243

    Isolate 2 1 2 18 158 199 222 243

    Isolate 3 1 2 18 158 199 222 100

    Isolate 4 1 2 3 178 200 245 289

    The ‘SNP address’

    SNP address indicates how closely related genetically an

    isolate is to other isolates in the database

  • Phylogeny Trees

    To fully assess the genetic relationship between

    isolates in a cluster needs a phylogeny tree.

    Salmonella NGS at PHE

    Maximum likelihood phylogeny Minimum spanning tree

  • 5 SNPs clusters → likely to be

    epidemiologically linked/ share a

    common exposure

    0 SNPs clusters → strongest

    evidence of being part of an outbreak

    with a common exposure or with a

    direct person-to-person transmission

    Outbreak detection with WGS

  • t50= 276

    • US Shell Eggs

    • PT8/PT13a

    • Recent Emergence in EU

    • Invasive?

    • MDR

    • “Global Epidemic”

    • PT4, PT1, PT14B

    • Reduced susceptibility to

    ciprofloxacin

    • Peak in early 90’s – 20k

    isolates a year in England!

    Salmonella Enteritidis

    Population Structure

    Acknowledgements: Tim Dallman and Hassan Hartman

  • Travel associated

    Salmonella Enteritidis

    Acknowledgements: Tim Dallman and Hassan Hartman

  • Key points

    • WGS is a highly discriminatory typing method – comparing the genomes of the bacteria

    • Provides phylogenetic information → genetic diversity, wider phylogenetic context, MRCA etc

    • The 5-SNP threshold corresponds to typical outbreak diversity.

    → = same ‘source of contamination’ (≠ same vehicle of infection)

    • WGS is still only a microbiological typing technique – and the results must be interpreted carefully.

    • Microbiological (WGS) results + epidemiology → outbreak detection/investigation/management

  • Outbreak

    investigation

    examples…

    Gary Larson, google images

  • Whole genome sequencing…

    • The unparalleled sensitivity this method provides over previous phenotypic methods, combined with epidemiological data, provides greater power to:

    1. Detect and define outbreaks more easily

    2. Collect better evidence for trace back, identifying vehicle and source → greater confidence in source attribution

    3. Assess/monitor effectiveness of control measures

    4. Improve our understanding of pathogen populations and infection transmission routes

  • Example 1: Outbreak detection,

    case ascertainment and

    increased strength of association

    in investigations

    Salmonella Enteritidis PT8/t5:2684

  • ‘High definition’ case ascertainment

    Cluster of Salmonella Enteritidis cases 5-SNP

    1.2.3.18.2190.2684.%

    • 31 cases reported May to September 2016, nationally

    distributed, no travel reported

    • 76% children

  • Increased strength of associations

    Outcome of case interviews = 7/9 cases bought items from

    East/Central European delicatessen shops: ➢ 5/9 cases (56%) consumed sausages

    ➢ 5/9 (56%) consumed cold sliced pork/ham

    But also – ‘name ontology analysis’…

    http://worldnames.publicprofiler.org/Main.aspx and http://onomap.org/

    http://worldnames.publicprofiler.org/Main.aspx http://onomap.org/

  • Key points

    1. Improved ability to detect outbreaks, especially clusters of

    cases that are:

    • small

    • geographically dispersed

    • a common serovar/PT combinations

    2. High resolution strain discrimination:

    • More accurate case definition and case ascertainment

    • Link cases that have had an exposure to a ‘common

    source of contamination’ with much greater accuracy →

    find commonality between cases more easily –

    time/person/place and reported exposures (higher odds

    ratios)

    3. Time to outbreak resolution ~ faster using WGS.

  • Example 2: Source attribution

    Salmonella Typhimurium DT104/ t5:459

    Acknowledgements t5:459 IMT

  • S. Typhimurium t5:459

    ➢ 5-SNP cluster 60.11.15.16.458.459.%

    ➢ First investigated by local teams in 2016, national

    investigation 2017

    ➢ 179 cases reported Aug 2014 - Sept 2018

    ➢ Two ‘temporal events’

  • S. Typhimurium DT104/t5:459

    ➢Phylogenetic analysis → ‘common

    strain’, related to DT104 seen to

    date in England and Wales

    ➢Mostly urban population, many

    reporting eating halal meat and

    shopping at halal butchers

    ➢Hypothesis = epidemiology +

    phylogeny ≈ consumption UK

    produced meat

  • 2017 cases

  • 2017 cases

    2014-16 cases

  • 2017 cases

    2015-16 cases

    Farms

  • Overall…

    • Multiple food vehicles of infection through multiple

    supply chains likely involved!

    • Seasonal factors in livestock movements and

    husbandry driving seasonal pattern?

    • Amplification in specific supply chains - likely that a

    combination of pre and post slaughter factors were

    increasing total risk and driving transmission.

    • Total number livestock farms identified with outbreak

    strain 2014 – 2018 = 32/57

    • Likely that persistently circulating on farms →

    environmental contamination and perpetration via

    animal movements…

  • How to handle this?

    • Scale of contamination and timelines → very

    difficult to decide on risk management actions to

    take.

    • Livestock movement data for the initial 9 positive

    farms → identified a further 73 premises in the

    network (January 2015 – June 2017) and 26,389

    animal movements (sheep, cattle, pigs and goats)

    Presentation title - edit in Header and Footer

  • How to handle this?

    • Feasible and proportionate

    control options?

    ✓ Enhanced surveillance on

    livestock in the affected region

    ✓ Farm visits, sampling and expert

    advice on control.

    ✓ Identification of linked catering

    /retail premises and

    slaughterhouses for hygiene

    inspections/enhanced hygiene

    measures

    Presentation title - edit in Header and Footer

  • Monitoring controls

    28

    Three week moving average number of cases of

    Salmonella Typhimurium RDNC/t5:3225 by report

    date and week July 2017 – August 2019 (n= 365 cases)

    ➢ Controls applied at 6 farms and 9 slaughterhouses and

    proactive press releases with co