Added value of Salmonella genomics in outbreak investigations

Dr Qinning Wang

CIDM-Public Health, Pathology West-ICPMR

Major outbreaks due to Salmonella serovars other than

STM between 2015-2016

Serovar Notified Possible source Outbreak

S. Saintpaul Dec. 2015 Food related Multi-jurisdictional

S. Mbandaka Early 2016 Food related NSW

S. Bareilly Early 2016 Contaminated sushi NSW

S. Hvittingfoss June 2016 Rockmelon Multi-jurisdictional

2014 2015 2016 up to Aug

Rank No. (%) Rank No. (%) Rank No. (%)

S. Saintpaul 8 53 (1.2) 3 138 (3.6) 4 120 (4.0)

S. Mbandaka 18 30 (0.7) 35 14 (0.4) 14 36 (1.2)

S. Bareilly 13 42 (0.9) 15 44 (1.2) 9 56 (1.9)

S. Hvittingfoss 34 12 (0.3) 30 17 (0.4) 6 81 (2.7)

Total 4434 3814 3027

Changes in the impact of difference serovars

(NSW ERL data)

WGS investigation of the outbreaks

• Sequencing platform:

NextSeq500, Nextera XT library prep kit (Illumina)

• Selection of isolates:

included isolates collected during the epidemic periods together

with isolates from possible food/environmental sources and

backgrounds

• DNA extraction

single colony, pure culture, automated extraction system (Perkin

Elmer), RNase A treatment, QC

Sequencing workflow and data analysis

DNA

QC

Library prep

QC

Flowcell

Raw data (Basespace, Illumina)

QC (FastQC: quality check, GC content, etc.)

Reads

trimming

(FASTQ-Toolkit: adapter/quality trimming, length

filtering, down-sampling)

(NextSeq500, Illumina)

Mapping

reads to ref

De novo

assembly

Web-based

server Nullarbor

SNP calling, phylogenetic tree

(CLC Genomic

Workbench)

(Selection of Ref,

Coverage analysis

(contig check)

Serovar ID, MLST, antibiotic resistance, core

SNP, cgMLST, Minimum spanning tree etc.

Report

01-16-025-4615-B34

80-15-315-4697-B43

80-15-254-2933-B41

80-16-020-4338-B33

80-16-053-5203-B21

80-15-254-3004-B40

80-15-351-4409-B44

80-15-261-1767-B45

80-16-029-4490-B46

80-16-022-4248-B30

80-16-033-5065-B24

80-16-027-4514-B23

80-16-051-2473-B28

80-16-022-4313-B11

80-16-029-4491-B47

80-16-030-2500-B31

80-16-039-5105-B1

80-16-077-4808-B15

80-14-344-4587-B39

80-14-153-4895-B37

80-14-153-4897-B38

80-16-036-4634-B16

80-16-016-2298-B7

80-16-050-4651-B20

80-16-104-4797-B36

80-15-315-4696-B42

80-16-013-4293-B9

80-16-019-4845-B10

80-16-021-4385-B5

80-16-018-4711-B8

80-16-029-4485-B12

80-16-034-4917-B13

80-16-025-4842-B14

80-16-037-2359-B17

80-16-020-4336-B18

80-15-020-4484-B3

80-16-030-2497-B26

80-16-063-5108-B27

80-16-029-4509-B32

80-16-014-4386-B6

80-14-227-4738-B2

Reference

80-15-341-5131-B4

80-16-057-4481-B29

80-16-023-2397-B25

80-16-050-4612-B19

0.2

80-16-020-4336-B18

80-16-053-5203-B21

80-16-013-4293-B9

80-16-018-4711-B8

80-16-020-4338-B33

80-16-014-4386-B6

80-16-016-2298-B7

80-16-019-4845-B10

80-16-036-4634-B16

80-16-051-2473-B28

80-16-021-4385-B5

80-16-029-4490-B46

80-16-029-4491-B47

80-16-077-4808-B15

80-16-027-4514-B23

80-16-029-4509-B32

80-16-039-5105-B1

80-15-254-2933-B41

80-16-022-4248-B30

80-16-025-4842-B14

80-16-022-4313-B11

80-15-261-1767-B45

80-16-029-4485-B12

80-15-254-3004-B40

80-16-030-2500-B31

80-16-037-2359-B17

01-16-025-4615-B34

80-16-030-2497-B26

80-16-033-5065-B24

80-16-034-4917-B13

80-15-315-4696-B42

80-15-315-4697-B43

80-15-020-4484-B3

80-15-351-4409-B44

80-16-050-4651-B20

80-14-153-4897-B38

80-14-153-4895-B37

80-14-344-4587-B39

80-16-104-4797-B36

80-16-063-5108-B27

80-14-227-4738-B2

80-15-341-5131-B4

reference

80-16-057-4481-B29

80-16-023-2397-B25

80-16-050-4612-B19

0.2

The reference genome

mapping based SNP

tree of S. Bareilly

isolates

Denovo assembly based

SNP tree of S. Bareilly

isolates

S. Bareilly cgMLST profile and allele distances

Details of the 38

isolates cluster

38 isolates cluster

AA

C

C

BB

Food/environmental sample

• A rare seen serovar

• Isolated from human, animal and environmental sources in

northern Queensland

• Previous multi-state outbreak was reported in Australia in

2005, no food vehicle identified (Oxenford, et al 2005)

• Recent outbreak involves cases from NSW, SA, WA, VIC

and QLD

• 128 isolates and WGS sequence data from human and food

samples were subject to WGS investigation

S. Hvitiingfoss outbreak investigation

S. Hvittingfoss SNP maximum likelihood tree

by mapping reads to an assembled local

isolates (128 isolates in total)

Cluster I

C1

C2

Re-generation of the tree by

exclusion of outliers

S. Hvittingfoss SNP distance matrix

S. Hvittingfoss whole genome

sequence cgMLST profile

OC 1

C 2

Re-generation of the

MST from C1 cluster

C 1

Includes 11 food/

environmental

isolates

S. Hvittingfoss cgMLST comparison of

Australian and international isolates

S. Saintpaul multijurisdictional

outbreak NSW isolates (2015-

2016) cgMLST profile

S. Mbandaka outbreak cgMLST profile NSW, 2016(Highlighted in yellow: food/environmental isolates)

OC

Report

Sent to OzFoodNet and Public Health for the integrated epidemiological analysis

• Generate complete public health microbiology reports from sequenced isolates

(Reads to report)

• Variants calling

• Species identification: k-mer analysis against known genome database (Kraken)

• MLST, Resistome

• Core genome SNPs

• Draw tree (Maximum likelihood)

• SNP distance matrix

• Pan genome

• Report : Table of isolates, yield, coverage, species, MLST, SNP distance matrix

Nullarbor pipeline

(Developed by Torsten Seemann from MDU)

https://github.com/tseemann/nullarbor

2016-12974

QLDSH2

QLDSH4

SA15

QLDSH10

QLDSH3

QLDSH6

QLDSH8

QLDSH9

SA16

2016-13536

QLDSH1

H20

H19

QLDSH7

QLDSH12

2016-11136

H35

2016-11149

H18

SA17

SA5

H5

SA14

H43

SA13

2016-14214

QLDSH5

QLDSH11

H7

2016-13030

2016-13909

2016-09557

2016-11450

Reference

H36

QLDSH14

WA7

WA5

WA8

H17

2016-15951

QLDSH13

WA2

H2

2016-16164

H29

SA1

SA10

SA8

SA11

H1

H10

H11

H12

H13

H14

H15

H16

H21

H22

H23

H24

H25

H26

H27

H28

H3

H31

H38

H39

H4

H40

H41

H44

H6

H8

H9

SA12

SA2

SA3

SA4

SA6

SA7

SA9

WA1

WA3

WA4

WA6 Example of a report generated by Nullarbor

SerovarNo. isolates sequenced OC

Food/environmental isolates

Food source

identified Outbreak Scope

S. Saintpaul 157 118 3 from SA by MDU Yes, by MDUNSW, SA, QLD, VIC, NT, WA, ACT

by MDU (~400 isolates)

S. Bareilly 45 27 11 Yes NSW

S. Mbandaka 46 19 7 Possibly NSW

S. Hvittingfoss 128 80 11 Yes NSW, SA, WA, QLD, VIC

WGS summary

Conclusions

• The added value of high-resolution and high-throughput capacity of

WGS was demonstrated through the outbreak investigations

• WGS enabled isolates clustered into groupings that would be

problematic when relying on epidemiology or serotyping alone

• Multiple approaches to the comparison of bacterial genomes helped

to validate analytic pipelines

• Sequence data analysis turnaround time would be improved by well

designed and validated analytic pipelines

• Proper report format needs to be further developed for easy

interpretation by Public Health and epidemiological professionals

19

Acknowledgements

NSW ERL/CIDM-PH

Vitali Sintchenko

Peter Howard

Agnieszka Wiklendt

Cristina Sotomayor

WGS lab staff

NSW Communicable Diseases Branch, Health

Protection

OzFoodNet

NSW Food Authority

Microbiological Diagnostic Unit

Public Health Laboratory, University of

Melbourne

PathWest, WA

Queensland Health Forensic & Scientific

Services

SA Pathology