Perspectives from CanadaCanadian Food Inspection AgencyPublic Health Agency of Canada

Health Canada

Sabah Bidawid, PhDChief, Microbiology Research DivisionFood Directorate, Bureau of Microbial HazardsHealth Canada

Celine Nadon, PhDChief, Enteric Diseases

National Microbiology LaboratoryPublic Health Agency of Canada

2

FOOD SAFETY IN CANADA

3

Federal food safety responsibilities are shared

PRODUCTION PROCESSING/DISTRIBUTION/RETAIL/FOOD SERVICE CONSUMERS

On-farm Food Safety Programs

Policy &Standards

Monitoring/ Early Warning

Education &Outreach

Inspection &Enforcement

Public Health Surveillance

AGRICULTURE & AGRIFOOD CANADA

•Contributes to research and development of on-farm food safety programs

HEALTH CANADA

•Establishes food safety policy and standards

•Conducts health risk assessments

• Informs Canadians about potential risk to their health

•Safety of veterinary drugs and pesticides

• Research vis-a-vis policy development

CANADIAN FOOD INSPECTION AGENCY

•Design and delivery of federal food inspection programs

•Monitors industry’s compliance with Acts and regulations

•Undertakes enforcement action as necessary

PUBLIC HEALTH AGENCY OF CANADA

•Public health surveillance

•Leads outbreak investigations with P/T public health officials

HEALTH CANADA

CFIA

PHAC

AAFC

4

IMPLEMENTATION OF WGS – REGULATORY/INSPECTION

Outbreakinvestigation

Monitoring program

Isolated colony WGS Bioinformatics Report of analysis

Health Risk

Assessment

RegulatoryAction

(e.g., recall)

Map readsAssembly

Identification

Typing/Signature sequencesVirulence profile

Quality metricsDesired outcomes:

• Comprehensive analysis

• Definitive identification

• Risk profiling

• Timely interventions

Canadian Food Inspection Agency

Approximately 12,500 food

samples analyzed annually for

compliance and investigation

Fresh Produce – 10%

Imported and Manufactured

Foods – 4%

2014-2015

SAMPLED PRODUCTS

5

IMPLEMENTATION OF WGS - POLICY

NO

YES

YES

STRONG EVIDENCE

PFGE ANALYSIS PHAC/

HC/CFIA Link cases to food Section B

STRONG EVIDENCE

NO

NO

HRA HC Section E

Appendix E

NO

RISK ASSIGNED

TO FOOD HC Section F

CHECK GMPs

and HACCP CFIA

RISK MANAGEMENT ACTION

CFIA Section G

GMP, HACCP, QA, Investigation Check additional products

LEGEND

STRONG EVIDENCE

NO

YES

NEXT

BACK AND FORTH

YES

CONTINUE

SURVEILLANCE PHAC/CFIA

Continue epidemiological

investigation

NO MORE

LEADS

CLOSED

UNSOLVED

TRACEBACK/TRACEFORWARD

Products identified in distribution CFIA Section D

YES

STRONG EVIDENCE

EPIDEMIOLOGICAL

ANALYSIS PHAC (# cases, demographics, clinical presentation,

food history/exposures) Section C

YES

CONTINUE PHAC

SURVEILLANCE

NO

CASES OF ILLNESS (food, # of cases, history, etc.) PHAC Section C

FOOD SAMPLE (in-situ; for

pathogen ID) CFIA* Section A

ISOLATE MATCH PHAC (link between cases)

Section B

6

IMPLEMENTATION OF WGS - POLICY

7

IMPLEMENTATION OF WGS - POLICY

“While PFGE and MLVA are the gold standard subtyping methods for

foodborne bacterial pathogens, newer methods are being developed

for genetic profiling, including whole genome sequencing. This

research and development is done to ensure that the best

technology and most current science are available for foodborne

disease investigations and with the application of validated

interpretation criteria and assessment of weight of evidence. When

new tests are applied during outbreak investigations for this purpose,

they are applied in parallel to the primary tests and are carefully

interpreted on a case-by-case basis.”

8

IMPLEMENTATION OF WGS POLICY:

Foodborne Pathogens

• Canada is in the process of incorporating information from WGS

into Health Risk Assessments and Epidemiological Surveillance

– WGS is being performed on, Bacteria, Viruses, and Parasites from

Clinical, Environmental, and Food Sources

– WGS data: currently used to monitor trends in emerging

pathogens, AMR, to identify novel virulence factors, and as an

parallel/alternative to traditional analyses like MLST and serotyping

– HC is also working on Quality Assurance and Best Practices

Standards Guidelines for sequence analysis (Pightling et al., 2015;

2014).

– Working toward using WGS to support the development of policy/

standards/compliance.

9

IMPLEMENTATION OF WGS:

SURVEILLANCE & OUTBREAKS

PulseNet Canada

Genomic

Epidemiology

Roadmap

Aleisha Reimer with contributions

from Drs Celine Nadon, Morag

Graham, and PulseNet Canada

members

October 16, 2013

Based on existing PulseNet Canada

model

De-centralized sequencing and

analysis

Parallel, centralized storage & analysis of

national data sets

Continued NML support in reference

testing, training, certification &

proficiency

Continued method development,

refinement, and KT

10

IMPLEMENTATION OF WGS: SURVEILLANCE & OUTBREAKS

WGS initiated by

NML or member

and permission

granted by member

laboratory

Sequencing

performed by NML

Sequencing performed by

member laboratory, but part

of a multijurisdictional

cluster/outbreak

Member uploads raw

sequence to NML database

Multi-jurisdictional

bioinformatics analysis

performed by NMLMember can

download raw

sequences

Results & interpretations

are verified with the

submitting laboratories for

consensus

NML provides results

interpretations to PHAC

managers & epidemiologists,

OICC, and international

partners (as determined in

previous step).

Information Flow:

Whole Genome Sequencing

Challenges: - Comfort level among partners on

appropriate use of data

- IP and isolate ownership: national

agreements to enable meta-data

sharing

- Paradigm shift about what should

be publicly available

Mitigations:- Transparency

- Rigorous communications protocols

- Trust building

- MOU

11

BIOINFORMATICS AND IT INFRASTRUCTURE

NML

IRIDA

BioNumerics

HPC

AB

BC

SK

MB

ON

QCNL

NB

NS

PEI

NU

NT

Hub and Spoke Model

- High speed connections from FPT

partners to NML

- IRIDA and BioNumerics used for

data storage, management,

surveillance, analysis

- Centralised IT and bioinformatics

experts

- Intent – common platform for

federal partners

12

CFIA

BIOINFORMATICS

HUB

NML

BIOINFORMATICS

HUB

Public Health Lab WGS Capacity

Food Lab WGS Capacity

13

STANDARDS AND HARMONIZATION

International standards for Bioinformatics and Genomics for public health and

regulatory activities - currently under way. Government of Canada active in:

• Global Coalition for Regulatory Science Research Working Group on Bioinformatics

- developing Best Practices for bioinformatics for food regulatory application

• Global Microbial Identifier international consortium developing standards for

genomic epidemiology

• PulseNet International harmonization and standards for surveillance and outbreak

response

• International Standards Organization Technical Committee (ISO/TC 34/SC

9/WG25) – QA standards for genomics in food testing

• IRIDA platform incorporates ontologies, public APIs, data provenance, and a

flexible QA/QC system for WGS-based analyses

Approach: Harmonized, non-prescriptive

standards and best practices

14

EDUCATION

NEED GOAL APPROACH TO DATE…

Lab capacity – data

analysis specialists to

perform genomic

analyses and

interpretation “frontline”

Knowledge of how

to interpret genomic

information by

partner laboratories

Hub and Spoke:

Expert computational

resources that

cascade skills to wider

users (hub); lab staff

receive training

appropriate to their

role (spokes)

Technical bioinformatics

workshops; genomics

wet lab training; practice

(repeated outbreak

analyses)

Stakeholders with

comfort &understanding

of the added value &

benefits offered by

WGS

Stakeholder fluency

in genomics-based

evidence

HUB & SPOKE model;

different audience than

for operational training

Educational webinars,

multi-jurisdictional task

groups, annual

meetings, briefing

notes, white papers

Knowledge translation activities critically important, tailored for audience

15

CASE STUDIES

Organism Case or Outbreak Details (putative/confirmed vehicle)

L. monocytogenes Collaboration with USA (lettuce product)

L. monocytogenes Collaboration with USA (RTE meat product)

Salmonella Thompson National laboratory investigation to support outbreak

response in a single province (suspected chicken

products)

E. coli O157:H7 Large outbreak in a single province (pork products)

L. monocytogenes Ongoing cluster of common PFGE pattern

L. monocytogenes Collaboration with USA (caramel apples)

S. Enteritidis Collaboration with USA (bean sprouts)

Selected Investigations Supported Prospectively by

WGS, PulseNet Canada, 2014

Usefulness of WGS application to outbreaks in 2014:

- Increased resolution; ability to rule in/out matching PFGE patterns

- Provided confirmation of PFGE/MLVA findings

- Grouped unrelated PFGE patterns – large clusters that otherwise may have been missed

- Facilitated development of data sharing protocols for use in real time as well as

knowledge translation to lab and epi partners

16

CASE STUDIES

In Canada, WGS is routinely applied during cluster investigation or

outbreak response in parallel to PFGE/MLVA. General findings:

WGS CONFIRMS MOLECULAR

RESULTSWGS PROVIDES ADDITIONAL

INFORMATION

Example: beef-associated E.

coli O157:H7 outbreak (2012)

PFGE & MLVA used for case

definition; WGS in parallel gave

same results

Example: Canadian cases - US

outbreak of listeriosis

associated with caramel apples

Canada had 2 PFGE matches

One case reported apple

exposure, one did not

WGS confirmed that the case

with no exposure was not

outbreak-related, despite the

PFGE match

Only

molecular

results

“officially”

used

17

CASE STUDIES

WGS CONFIRMS MOLECULAR

RESULTS

Example: beef-associated E.

coli O157:H7 outbreak (2012)Example: Canadian cases - US

outbreak of listeriosis associated

with caramel apples

WGS used in parallel with

established molecular tests

enables database building &

increases knowledge transfer

activities while providing the

“comfort” of the gold standard

Independent analyses using two

pipelines (US and Canada) were

in agreement, thus increased

confidence in WGS results of a

higher resolution than PFGE

In Canada, WGS is routinely applied during cluster investigation or

outbreak response in parallel to PFGE/MLVA. General findings:

WGS PROVIDES ADDITIONAL

INFORMATION

18

SUMMARY

Status: government-wide tiered approach; mostly in parallel with traditional tests so far

Implementation challenges: what happens when funding is insufficient? When volumes are low? How long until traditional tests are phased out? What will

new interpretation criteria look like?

Primary issues present in Canada: standardization/harmonization, IT and bioinformatics

infrastructure, data integration, sharing, and KT

19

Co-Authors

Canadian Food

Inspection Agency (CFIA)

- Burton Blais

Health Canada (HC)

- Sabah Bidawid

- Franco Pagotto

- Nicholas Petronella

- Jennifer Ronholm

- Jennifer Holtzman

Public Health Agency

of Canada (PHAC)

- Celine Nadon

- Morag Graham

- John Nash

- Aleisha Reimer

- Gary Van Domselaar

20

Additional Materials

- Discussion points on FAO questions

- GMO perspective on use of genomics

21

INSIGHTS

Is WGS considered beneficial for food safety management in Canada?

What could be the drawbacks?

• Benefits

– Harmonize methodology (decrease lab to lab variability) – one test fits all approach

– Highly informative tests results (identification, characterization, risk assessment)

– Third party evaluation of results

– Cost effective and timely

• Drawbacks

– Still need an isolate

– Possible decline of culture collections

– Comparison to legacy data

What are the necessary conditions /infrastructure to employ WGS

technology for food safety management in Canada?

• Sequencing capacity

• High Capacity Storage and Data analysis

• Bioinformatics support in the form of tools, expertise, & databases

• Interpretation criteria/policy for data use

• Governance for sharing

If in the future this will be used for food safety management, what are

the key prerequisite activities?

• Database construction

• Validation experiments

22

INSIGHTS

What agencies are/should be involved to make good results? How they are

(can be) working together on this topic? Are there any important stakeholders

(industry/company or academia/research) who should be involved?

• Health Canada (HC); Public Health Agency of Canada (PHAC); Canadian Food

Inspection Agency (CFIA).

• Provincial and territorial public health

• Food Industry

What could be the real challenges (overall and specific) in when actually

using WGS for food safety management?

• Sharing (databases, sequencing data, tools, results of validation experiments etc.)

• Food Industry outpacing regulatory and compliance agencies (CIFA, PHAC, HC)

• Predictive accuracy (e.g. predicting phenotype)

What roles do you expect/wish that international organisations would play

on this topic?

• Standardization/harmonization (not prescriptive though)

• Database

23

Capacity building for pre-market assessment of genetically

modified organisms

• Mandated activity (Division 28 of the Food and Drug Regulations)

– molecular characterization, nutritional composition, chemical safety

number of DNA insertion sites in the genome, presence of complete or partial

copies, intact insert, absence of plasmid backbone

• Companies typically provide data generated by classical molecular biology

methods (Southern blot, PCR, Sanger sequencing), however there is interest from

industry to provide regulators with molecular characterization data generated

using WGS

• Approach

– Consultation with experts and stakeholders (CFIA lead, March 2015)

– Draft internal guidance by GoC expert working group (Health Canada lead,

Nov. 2015)

– External guidance will be developed by GoC working group (2016)