WGS 101: The Rationale, Mechanics, and Impact of WGS for...
Transcript of WGS 101: The Rationale, Mechanics, and Impact of WGS for...
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?
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“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.
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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
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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
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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
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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…..
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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