WGS 101: The Rationale, Mechanics, and Impact of

WGS for Food Safety

Eric W. Brown, Ph.D., FAAM Director, Division of Microbiology

Office of Regulatory Science

Center for Food Safety and Applied Nutrition,

US Food and Drug Administration

TO: The IRAC Workgroup

Patriots Plaza 3

FSIS Bldg.

March 16, 2017

What is Whole Genome Sequencing?

A genome is an organism’s complete set of DNA,

including all of its genes. Each genome contains all of the

information needed to build and maintain that organism.

A bacterial genome is generally smaller and less

variant in size between species when compared with

Genomes of animals and single cell eukaryotes.

Bacterial genomes can range in size from about 130 kb

to over 14 Mb.

What’s a Genome?

What’s a Bacterial Genome?

4

“Whole Genome Sequencing Is The Biggest Thing To

Happen To Food Microbiology Since

Pasteur Showed Us How To Culture Pathogens…”

Dr. Jorgen Schlundt

Exec Director and Founder

The Global Microbial Identifier

biocomicals.blogspot.com

WGS (aka NGS/MPS/SHOTGUN SEQ) is fast becoming a common and widespread

approach in microbiology and is impacting food safety in ways we never could

have imagined!

What’s

WGS?

WGS is a laboratory

process that

determines the

complete DNA

sequence of an

organism’s genome

at a single time.

NGS High-Resolution Typing for

1. Infectious Disease

2. Hospital Acquired Infections

3. Foodborne Outbreaks

What’s WGS?

WGS is a laboratory process that determines the complete

DNA sequence of an organism’s genome at a single time.

8

A high-throughput sequencing method that

parallelizes the sequencing process,

producing millions of sequences at once.

Over the past six years, “Next-Generation”

sequencing technologies have made

accessible data capable of answering

questions fundamental to our understanding

of life and the factors that govern human

health. The combination of the vast increase

in data generated, coupled with plummeting

costs required to generate these data, has

rendered this technology a tractable, general

purpose tool for a variety of applications.

Next-Generation Sequencing

Next-Generation Sequencers

Illumina MiSeq

454 GS Junior

Illumina HiSeq

Ion Torrent PGM

Illumina NextSeq

PacBio RS

454 GS FLX

Is WGS a viable solution?

• Cost

• Increasing ease of operation

• Database longevity

• Comparable times to conventional pipelines

• Sample prep – Identical for all pathogens

• Cost savings – Resistance, subtyping, virulence

factors, more…

• New applications – tracking, regulatory/compliance

actions, historical trends, more…

$0

$500

$1,000

$1,500

$2,000

$2,500

$3,000

$3,500

2007 2008 2009 2010 2011 2012 2013

Cost per bacterial genome

Illumina

Miseq

454

$70/genome

in 2014

$50/genome

in 2016 w/

Illumina NextSeq Technology

Background: CFSAN SNP Pipeline

http://www.ibbl.lu/wp-content/uploads/2012/07/SNPs.jpg

Reference

Food or

Environmental

Isolate

Single Nucleotide Polymorphism

Background: CFSAN SNP Pipeline

Forensics Analysis for Humans

• FBI CODIS: 13 Short Tandem Repeat (STR) loci

• 6-21 alleles for each loci

• Allele frequencies studied in U.S. Caucasian, African American, and Hispanic populations

Image from http://www.dna.gov/dna-databases/codis

Background: CFSAN SNP Pipeline

Mapping/Aligning (66+) SNP Detection (16+)

Samtools

SOAPsnp

GATK

SNVer

VarScan

SHORE

SMALT

MaCH

IMPUTE2

CLC Bio QualitySNPng DNABaser SNPdetector

FreeBayes

SolSNP

DNAStar Bowtie2 VarScan

Phylogenetic Tree

A phylogenetic tree, also known as a phylogeny, is a diagram

that depicts the lines of evolutionary descent of different species,

organisms, or genes from a common ancestor.

Pedigree vs Phylogeny

Microbial Forensic Analysis

Ou et al. 1992 Science

• Local Controls

(LC)

– Two HIV clinics

within 90 miles of

dental practice

• 35 LCs analyzed

• Sequenced

680bp of gp120

gene

Daubert standard 1. Empirical testing: whether the theory or technique is falsifiable,

refutable, and/or testable.

2. Whether it has been subjected to peer review and publication.

–Specific/Target Studies for pathogen have been published. Multiple software

packages for mapping and calling SNPs.

3. The known or potential error rate.

–Well characterized at read level, less so for cluster analysis.

4. The existence and maintenance of standards and controls

concerning its operation.

–Proficiency testing efforts through Global Microbial Identifier and also FDA

GenomeTrakr network. ISO and CEN workgroups

5. The degree to which the theory and technique is generally

accepted by a relevant scientific community.

–Acceptance facilitated by open database (NCBI/SRA).

Example: L. mono in sprouts

clinical

FDA00008247

Intralaboratory Sequencing

Study Sources of variation between isolates

1. Biological variation

2. Laboratory Handling, Passaging

3. Sequencing error (454 vs Illumina vs Solid)

4. Assembly (Newbler vs Celera)

5. Annotation (PGAAP vs RAST)

Salmonella Montevideo replicates

– 4 colonies from same plate

– 4 runs from same colony

– 4 serial passages

Intralaboratory Sequencing Study

Isolate Description PeakDepth Contigs N50 Bases

315996572 Pistachio 29 61 226927 4650467

315731156 Pistachio 20 54 248886 4652384

IA_2009159199 Clinical 12 115 99285 4644811

IA_2010008282 Lunch Meat 14 91 135215 4646326

IA_2010008283 Lunch Meat 11 178 81429 4640232

IA_2010008284 Lunch Meat 13 139 88743 4644780

IA_2010008285 Lunch Meat 16 51 248902 4650034

IA_2010008286 Lunch Meat 18 60 225458 4653767

IA_2010008287 Lunch Meat 12 79 172435 4646949

IA_2010008282 Colony 1 16 76 135129 4649477

IA_2010008282 Colony 2 18 54 216022 4650773

IA_2010008282 Colony 3 19 248 168430 4650742

IA_2010008282 Colony 4 Rep 1 18 56 225458 4650579

IA_2010008282 Colony 4 Rep 2 16 54 352671 4651518

IA_2010008282 Colony 4 Rep 3 12 278 33279 4635334

IA_2010008282 Colony 4 Rep 4 16 187 51085 4648528

IA_2010008282 Passage 1 15 357 29972 4658141

IA_2010008282 Passage 2 14 187 51782 4652212

IA_2010008282 Passage 3 12 570 17534 4632779

IA_2010008282 Passage 4 13 262 42418 4653143

Intralaboratory Sequencing

Study Position Description Position Description

204781 Missing after MUSCLE 1806153 Homopolymer (6 T/A)

255578 Homopolymer (8 T/A) 2087876 Missing after MUSCLE

355131 Missing after MUSCLE 2354057 Homopolymer (6 T/A)

756435 Homopolymer (9 C/G) 2545225 Missing after MUSCLE

1070504 SNP in Gap 3193883 Homopolymer (7 T/A)

1097814 Homopolymer (9 T/A) 3823524 Good

1179704 Homopolymer (7 T/A) 4257557 Homopolymer (8 T/A)

1205130 Good 4545198 SNP in Gap

1368882 Missing after MUSCLE 4545878 Duplicated in other Salmonella – Elongation Factor Tu

1642240 Missing after MUSCLE 4546413 SNP in Gap

1693620 Homopolymer (6 T/A) 4548105 23S rRNA

1713322 Missing after MUSCLE

Intralaboratory Sequencing Study

Position 1205130

Intralaboratory Sequencing Study

3.0E-4

Colony 4 Rep 4

Passage 1

IA_2010008282

Colony 1

Passage 3

Colony 2

315731156 (Pistachios)

IA_2010008283

Colony 4 Rep 3

IA_2010008286

Passage 2

Colony 4 Rep 1

Colony 4 Rep 2

IA_2010008287

Colony 3

IA_2009159199

IA_2010008285

315996572 (Pistachios)

IA_2010008284

Passage 4

Data Set

12024 nucleotides (24*501)

22 SNPs in pistachios

2 SNPs in lunch meat

Tree Construction

Garli ML, HKY

The Rationale for WGS and other ‘Omics in FDA’s Food Safety

Programs

Some perspective on the food supply

• Tracking and Tracing of food pathogens

• Almost 200,000 registered food facilities (2/14)

– 81,574 Domestic and 115,753 Foreign

• More than 300 ports of entry

• More than 130,000 importers and more than 11 million import lines/yr

• In the US there are more than 2 million farms

http://www.nextgenerationfood.com/news/risky-food-list/

The 10 Riskiest Foods (circa 2009)

NGS

Biomarker Assays

SNP Discovery

Outbreak response

Microarray Targets

MLVA and CRISPR

loci

Next-Generation

Sequencing (NGS)

provides support

for other

technologies and

fosters novel

targets and assay

design for rapid

diagnostics.

2009

Don’t eat the salamae

Rejected by Science

2010

FOODBORNE OUTBREAK INVESTIGATION:

WGS analysis of foodborne salmonellae case study

This investigation focused on

Salmonella Montevideo samples

associated with red and black pepper

used in the production of Italian-style

spiced meats in a New England

processing facility. This manufacturer

was implicated in a major salmonellosis

outbreak that affected more than 272

people in 44 states and the District of

Columbia.

15-20x shot gun sequencing

35 pure culture isolates

from patients, foods and

Environmental samples.

Concatenate 40 variable genes for

Phylogenetic analysis

IN or OUT?

This from 1859, Darwin's, On the Origin of Species

“It is obvious that the Galapagos

Islands would be likely to receive colonists, whether by occasional

means of transport or by formerly continuous land, from America;

and the Cape de Verde Islands from Africa; and that such colonists

would be liable to modification;—the principle of inheritance still

betraying their original birthplace"

In WGS, we now have the potential to discern those birthplaces…

Time

mutation

recombination

deletion/insertion

A B

C D E

F

M H G

I K J L

I II III Strain

lineage:

Time

mutation

recombination

deletion/insertion

A B

C D E

F

M H G

I K J L

I II III Strain

lineage:

Time

mutatio

n recombination

deletion/insertion

A B

C D E

F

M H G

I K J L

I II III Strain

lineage: X

X

X

X

X

X

X

X

S. Bareilly CFSAN000189

Real

World

DNA

Fragments

Whole-Genome

Sequencing

I

II

III

PFGE-SpeI

JIXS18.0001

PFGE-BlnI

JIXA26.0012

PFGE-XbaI

JIXX01.0011

During the S. Montevideo outbreak, all isolates

were indistinguishable by 1st, 2nd, and third

enzyme PFGE.

40 genes vary within an S. Montevideo outbreak while

unique SNPs and a 100kb insertion separates a CA isolate

from the outbreak

• WGS is high resolution

3-5 million data points are collected for each isolate

• WGS analyses are statistically robust

Unlike PFGE patterns, WGS data can be analyzed in its evolutionary

context. Accurate and stable genetic changes within pathogen genomes

enable us to pin point specific common sources of outbreak strains

(farms, processing plants, food types, and geographic regions).

Source Tracking is Key Application:

moving from PFGE to WGS has been no less

impactful than the move from backyard

telescopes to the Hubble in terms

of resolution in differentiating foodborne

outbreaks.

PFGE transition to WGS

DNA Forensics…

Genome sequence is agnostic.

One biological assay could work

on all pathogen species

To be immediately useful all we

need is the genome and a little

metadata.

A Pathogen Genome Is The Fingerprint

Functional prediction can be

developed and refined more slowly

from this base.

S. Braenderup

Outbreak Investigation Timelines

Outbreak Investigation Timeline

Epidemiology Investigation

Regulatory Investigation

Questionnaires

Laboratory results

Patient interviews

Inspection

Sample collection

Laboratory results

Recall time

WGS Impact @ FDA

What does the WGS information tell us?

Environmental sampling combined with WGS can help point to root cause

of the contamination

42

Field 1

Field 2

Processing facility

Scenario 1 (pass through)

Field 1

Field 2

Processing facility

Scenario 2 (harborage and persistence)

Listeria monocytogenes in Fish Plant

4 isolates from Apr.

5 isolates from Feb.

10 isolates from Jun.

5 isolates from Aug.

4 clinical isolates

Montevideo black and red pepper

Senftenberg black and red pepper

Enteritidis shell/liquid eggs

Heidelberg ground turkey

Heidelberg chicken broilers

Heidelberg chicken livers

Enteritidis custard

Bareilly tuna scrape

Tennessee peanut butter/peanut butter paste

Typhimurium peanut butter

Braenderup peanut butter/nut butter

Tennessee cilantro

Agona dry cereal

Agona papaya

Newport tomatoes

Newport environmental

Kentucky - Cerro dairy/dairy farms

Anatum spices/pepper flakes

Javiana cantaloupes

Saintpaul hot peppers

4,5,12: i –

Javiana/Newport Cucumbers

Montevideo Pistachios

Hartford Chia powder

Mbandaka Tahini Sesame paste

Braenderup Mangoes

Poona Cucumbers

Lmono cantaloupes

Lmono queso cheese

Lmono potato salad

Lmono artisanal cheeses

Lmono avocados

Lmono ricotta

Lmono celery/chix salad

Lmono smoked fish

Lmono other herbs

Lmono peaches

Lmono hot peppers

Lmono tofu

Lmono sprouts

Lmono ice cream

Cronobacter infant formula

V para oysters

EcO157:H7 lettuce

STEC beef

STEC flour

FDA WGS Application to Actual

Food Contamination Events

Applications of WGS for One

Microbiological Workflow Delimiting scope and traceback of food

contamination events (Track-N-Trace)

Quality control for FDA testing and surveillance

(enhanced confidence against type 1 and 2 error)

Preventive control monitoring for compliance

standards

ID, geno/pheno typing schemes (AST,Serotyping,

VP) (CVM,CDRH,CFSAN) – risk assessment and

adaptive change in Salmonella and Listeria

National and International WGS Initiatives

What Can WGS Tell Us?

1. Are bacteria found in food/environmental

samples a “match” to clinical isolates? –Match may not imply causation, contaminated ingredient

2. Endemic contamination in a facility –Bacteria isolated are identical over time, before and after cleanup efforts

3. Source of contamination –Database contains isolates from different countries, regions, states

4. Anti-Microbial Resistance, Virulence,

Pathogenicity

Salmonella reveals extensive

phylogeographic structure

Romaine #1

Pistachio #3

Pistachio #2

Pistachio #1

Weather as a Modern Global Infrastructure

Citizens and Government All See the Power and Limits of Science

Why Develop a WGS Based Network?

• Tracking and Tracing of food pathogens • Insufficient resolution of current tools

-matching clinical to environmental

• Faster identification of the food involved in the outbreak

• Limited number of investigators vs. facilities and import lines

• Global travel

• Global food supply

Importance of a Balanced Approach

Clinical

Samples

Food and

Environmental

Samples

Maximum

WGS Benefit

What is GenomeTrakr

• First distributed network of laboratories that utilize whole genome

sequencing for pathogen identification

• Network was established by FDA in 2011 and is growing rapidly. Now

includes CDC, FSIS and dozens of collaborating institutions both

nationally and around the world.

• Open access data curation is provided by the National Center for

Biotechnology Information (NCBI)

• Partner with CDC and PulseNet for human real-time surveillance

• Partner with FSIS/USDA to better cover the food supply

• Partner with international organizations to expand use worldwide

7

58 Participating Laboratories

WGS and Beyond: Metagenomics,

Epigenetics, and DNA Modifications as

Biomarkers

Non Enrich

Enriched Firmicutes Proteobacteria

Enriched Firmicutes

Enrichment Methods: Are some firmicutes actively inhibiting Salmonella In vitro? How can we minimize enrichment of Firmicutes in UPB to better culture our target organism: Salmonella

Lm enrichment (BAM) – characterized every 4 hours to describe genomic coverage of Lm

and describe co-enriching microbiota

METAGENOMICS

TOWARDS A CULTURE INDEPENDENT FOOD TESTING PROGRAM

Genomes from different hours of enrichment (H20, H36, & H40) cluster

with WGS of pure isolates from ice cream listeriosis outbreak

H 20

H 36, 40

quasiMetaGenomic Sequencing…

I

Detection

(species)

II

Identification

(serotype)

III

Traceback

(subtype)

Is a pathogen

there?

What kind of

pathogen is it?

Is it part of the

outbreak?

Next-Generation Sequencing

Investigating Food Contamination Events with OMICS Approaches

Next-Generation Sequencing

Better understanding of adaptive change in Salmonella and Lm may provide

more accurate risk assessment as well as enhanced preventive control

measures on the farm and in the processing plant.

Functional Assays for SNPs

Salmonella 4.7 Mb

E. Coli 4.6 Mb

Listeria 3 Mb

Campylobacter 2 Mb

Bacterial Genomes

SeqSero Salmonella Serotyping by Whole Genome Sequencing

•Reads (paired-end & interleaved)

•Reads (paired-end)

•Reads (single-end)

•Genome Assembly

*The following formats are supported for raw reads input: .fastq.gz(preferred), .fastq

and .sra.

Please select your input file:

*The following formats are supported for raw reads

input: .fastq.gz(preferred), .fastq and .sra.

Please select the first reads file:

Please select the second reads file:

*The following formats are supported for raw reads input: .fastq.gz(preferred), .fastq

and .sra.

Please select your input file:

*The FASTA format is supported for genome assembly input.

Please select your input file:

http://www.denglab.info/

From WGS to Antibiotic Resistance Genotype

DNA from

Single colony

Sequencing

With Illumina Miseq

Assembly

CLC Genomics

Workbench

Local Blast AR

Gene Database

BLAST ®

Sequences alignment

gyrA gene

23S rRNA gene

Acquired AR genes

AR Genotype

Point mutations related

to AR

aac(3)-IIa, aadA1,

aph(3')-Ia

catA1, tetO …

S. Bareilly CFSAN000189

new genomic island

arsenic resistance operon

about 40 kb

Salmonella Bareilly from Tuna

68

Name Minimum Maximum Length Direction product

toxinCDS 43,465 43,788 324 forward toxin

antitoxinCDS 43,124 43,444 321 forward antitoxin

transcriptionalregulatorCDS 38,480 39,184 705 forward transcriptionalregulator

fattyacidtransporterCDS 36,027 37,214 1,188 forward fattyacidtransporter

mechanosensitiveionchannelproteinMscSCDS 34,410 35,996 1,587 forward mechanosensitiveionchannelproteinMscS

alkylsulfataseCDS 32,360 34,267 1,908 forward alkylsulfatase

histidinephosphataseCDS 30,833 31,447 615 reverse histidinephosphatase

transcriptionalregulatorCDS 28,266 28,532 267 reverse transcriptionalregulatormagnesiumtransporterCDS 24,110 24,766 657 forward magnesiumtransporter

fimbrialusherproteinCDS 20,181 22,691 2,511 reverse fimbrialusherprotein

fimbrialchaperoneproteinStdCCDS 19,404 20,129 726 reverse fimbrialchaperoneproteinStdC

PositiveregulatorGrlACDS 17,713 18,189 477 reverse PositiveregulatorGrlA

transcriptionalregulatorCDS 16,860 17,720 861 reverse transcriptionalregulator

membraneproteinCDS 14,535 15,275 741 reverse membraneprotein

ArsRfamilytranscriptionalregulatorCDS 13,772 14,101 330 reverse ArsRfamilytranscriptionalregulator

NADPH-dependentFMNreductaseCDS 13,057 13,770 714 reverse NADPH-dependentFMNreductase

RNApolymerasesigma70CDS 12,503 13,048 546 reverse RNApolymerasesigma70

arsenicresistanceoperonrepressorCDS 12,065 12,427 363 reverse arsenicresistanceoperonrepressor

arsenictransporterATPaseCDS 10,287 12,044 1,758 reverse arsenictransporterATPase

ModEfamilytranscriptionalregulatorCDS 9,845 10,213 369 forward ModEfamilytranscriptionalregulator

arsenatereductaseCDS 8,388 8,819 432 forward arsenatereductase

arylsulfataseCDS 7,086 8,375 1,290 forward arylsulfatase

arsenictransporterATPaseCDS 5,287 7,038 1,752 forward arsenictransporterATPase

arsenicresistanceoperonrepressorCDS 4,907 5,269 363 forward arsenicresistanceoperonrepressor

arsenicresistanceoperonrepressorCDS 4,506 4,859 354 forward arsenicresistanceoperonrepressor

nucleotidyltransferaseCDS 2,538 4,313 1,776 forward nucleotidyltransferase

integraseCDS 1 1,194 1,194 forward integrase

New Genomic Island

GOAL = <5 years have first 25 mapped and rapid detection assay developed

Adaptations of particular interest to food safety specialists:

(1) Thermal tolerance

(2) Dessication resistance

(3) Osmotic/Ionic tolerance

(4) Quat resistance

(5) Chlorine resistance

(6) Biofilm persistence

(7) Surface adherence

(8) Antibiotic resistance

(9) Antimicrobial resistance

(10) Ecological fitness

(11) Heavy metal resistance

(12) Metabolic persistence

(13) Enhanced hydrophobic fitness

(14) Produce invasiveness

(15) Flower invasiveness

(16) Root system invasiveness

(17) Acid resistance

(18) Surface water fitness

(19) In vivo plant migratory fitness

(20) Soil fitness

(21) Capsaicin resistance

(22) Swarming

(23) Trans-ovarian poultry colonization

(24) Fecal persistence (poultry)

(25) Yolk content invasion

(26) Multidrug resistance

(27) External amoeba harborage

(28) Internal amoeba harborage

(29) Acyl-homoserine lactone (AHL)

(30) KatE stationary-phase catalase

(31) In vivo migratory fitness

(32) RDAR phenotype

(33) The ‘Weltevreden’ type

(34) Persistence within the tomato**

Species Resistance

Virulence Subtype

Serotype Adaptations

ONE MICROBIOLOGICAL WORKFLOW: ONE MICROBIOLOGICAL TOOL BOX

All AT YOUR FINGERTIPS

IN THE NOT SO DISTANT FUTURE…..

71

Summary WGS is now routine in FDA’s outbreak response and compliance/surveillance activities.

Internally (across our agency), and in collaboration with FSIS and CDC, WGS has

now been deployed and benefitted the traceability of numerous foodborne

contamination events.

WGS can be used to inform traceback investigations and delimit the scope of food

contamination events unlike ever before – not just a regulatory tool - numerous

offshoot applications exist (i.e., supply chain management, quality assurance,

process evaluation, etc.)

Genome sequences are portable and instantly cross-compatible. One technology

approach irrelevant of organism.

Have to balance the need for increased number of well characterized environmental

(food, water, facility, etc.) sequences with the need for extensive clinical isolates

WGS, unlike PFGE, is more than a surveillance tool. It provides information on AMR,

Virulence, serotype, and other critical factors in one assay, including historical

reference to pathogen emergence.

WGS-based typing approaches are supplanting current microbiological methods (i.e.,

phage typing – serotyping, PFGE, etc.) AND WILL YIELD ONE MICROBIOLOGICAL

WORKFLOW VERY SOON.

WGS Supports The Food Safety and

Modernization Act

WGS compliments rapid testing methods with environmental monitoring for

repeat positives and problems w/ resident pathogens.

WGS provides an integrated food safety surveillance system with the

potential to connect federal food safety resources with state and municipal

surveillance efforts and the food production and testing industry directly.

WGS also permits international capacity building through integration of

foreign food safety entities into the GT network as well through interntional

outreach and education efforts in the deployment and use of WGS in the

traceability of foodborne pathogens.

The GT Food and Environmental Network represents a national genomic

food shield that should be managed and funded as a national asset at the

highest levels of the agency.

Transparency of open GT data gives industry full access to:

~ Genome data made public in real-time

~ Public software and analysis tools readily available to industry for

viewing of results

Program Chairs: Dag Harmsen (Univ. Münster, DE), Marc Allard and Eric Brown (both FDA, US)

ASM Conference Committee Liaison: Gary Procop (Cleveland Clinic Foundation, US)

ASM Conferences Program Manager: Lisa Nalker (Washington DC, US)

Twitter: #ASMNGS

2nd ASM Conference on Rapid Applied Microbial Next-Generation Sequencing

and Bioinformatic Pipelines October 8–11, 2017 | Washington, DC

Acknowledgements

• FDA

• Center for Food Safety and Applied Nutrition

• Center for Veterinary Medicine

• Office of Regulatory Affairs

• National Institutes of Health

• National Center for Biotechnology Information

• State Health and University Labs

• Alaska

• Arizona

• California

• Florida

• Hawaii

• Maryland

• Minnesota

• New Mexico

• New York

• South Dakota

• Texas

• Virginia

• Washington

• USDA/FSIS

• Eastern Laboratory

• CDC

• Enteric Diseases Laboratory

• INEI-ANLIS “Carolos Malbran Institute,”

Argentina

• Centre for Food Safety, University College

Dublin, Ireland

• Food Environmental Research Agency,

UK

• Public Health England, UK

• WHO

• Illumina

• Pac Bio

• CLC Bio

• Other independent collaborators