whole genome microbiology for salmonella public health microbiology

Revolutionising Public Health Reference Microbiology Using Whole Genome Sequencing: A Case Study with SalmonellaPhilip AshtonBioinformatician, Gastrointestinal Bacteria Reference Unit

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.

Why?How?What?

Salmonella WGS for Public Health3


Why do we want to implement WGS for Salmonella

reference micro?


> 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


Tom Innes & PT14b OCT

‘protecting and improving the nation’s

health’.


Previous typing method - serotyping

Satheesh Nair


David Powell


PHE Salmonella surveillance data - http://bit.ly/1CdEOe0

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


How will WGS based Salmonella reference microbiology work?

WGS implementation at PHE2011- 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

=


Identification / Mixed – kmer gateway

K-mer Gateway

14

AcetobacterAcinetobacterActinomycesAeromonasAggregatibacterBacillusBacteroidesBartonellaBifidobacteriumBordetellaBorreliaBrucellaBurkholderiaCampylobacterChlamydiaChlamydophilaClostridiumCorynebacteriumDesulfovibrioEnterobacterEnterococcusEscherichiaFrancisellaFusobacteriumGardnerellaGordoniaHaemophilusHelicobacter

KlebsiellaLactobacillusLegionellaLeptospiraLeuconostocListeriaMorganellaMycobacteriumMycoplasmaNeisseriaNocardiaPaenibacillusPrevotellaPropionibacteriumPseudomonasRhizobiumRhodococcusRickettsiaSalmonellaShewanellaShigellaStaphylococcusStreptococcusStreptomycesTreponemaUreaplasmaVibrioYersinia

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.


99.7% accurate subspeciation


Serotype inferred via MLST

Satheesh NairAchtman et al., 2012

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


2 serotypes – 1 ST/EBGLab errorNo ST/serotype lookup

Novel Sequence Types


SISTR/SeqSero


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

SampleFASTQs(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

Tomorrow – pipeline se

ssion


What will be the output of WGS for Salmonella

reference micro?

• Example of use in outbreak – PT14b• Strain characterisation – antibiotic

resistance profile• Future perspectives


Salmonella NGS at PHE

Salmonella Enteritidis Phage Type 14b

International outbreak

Tom Inns/PT14b Outbreak Control Team – Inns et al., Eurosurveillance, 2015


Tim Dallman, Tom Inns, Thibaut Jombart

Hierarchical clustering and Geography

23

Alison Waldram & Gayle Dolan

24

Phenotype S Phenotype R Error%Genotype S Genotype R Genotype R Genotype S

CHL 580 2 39 3 0.78SUL 466 1 149 8 1.40TET 467 3 151 3 0.93TMP 562 3 57 2 0.78AMP 484 5 134 1 0.93CTX/CAZ 618 1 5 0 0.16CPR 619 1 4 0 0.16FOX 612 0 7 5 0.78CIP 478 4 138 4 1.25NAL 485 2 127 10 1.87GEN 608 1 14 1 0.31TOB 613 2 8 1 0.47AMK 622 0 1 1 0.16STR 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 strainsResistance : 57.5 % susceptible 24.7 % multi-resistant (> 2 classes)


Future perspectives


• 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

Summary• WGS is a single test – multiple assays• Better quality information than existing

tests• Evolutionary and phylogentic insight


Acknowledgements


MicrobiologyElizabeth de Pinna, Tansy Peters, Satheesh Nair, Martin Day, Anna Lewis, Tim Dallman, Kathie Grant and other staff in the Salmonella lab

EpidemiologyAlison Waldram (FETP), Richard Elson, Chris Lane, Tom Inns

Genomic Services Unit Cath Arnold and team

Bioinformatics UnitJonathon Green, Anthony Underwood, Rediat Tewolde, et al.

whole genome microbiology for salmonella public health microbiology

Science