1.
Added Value of Open data sharing
using examples from GenomeTrakr
Marc W. Allard, PhD
Senior Biomedical Research
Services Officer
Division of Microbiology
FAO/GMI Seminar, May. 24, 2016

2.
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
…Numerous other taxa
FDA WGS Application to Actual Food
Contamination Events

3.
Example 2: Hot Peppers
L. monocytogenes found on finished product
samples in 2014 and through environmental
sampling in 2015:
– Did contamination originate on peppers, or during
manufacturing process? Was roasting/steaming
controlling for Listeria?
– Contamination originating from agricultural/farm
environments is generally diverse, we would expect
to see multiple clones.
– Extremely low level of genetic diversity observed
using WGS suggests contamination coming from
facility.

4.
Example 2: Hot Peppers
L. monocytogenes
from 2014 and 2015 are
virtually identical by WGS,
contamination originated
from same source

5.
Example 1: Smoked Fish
L. monocytogenes strains found on finished smoked
fish
– Was fish contaminated before smoking, or was it
contaminated during the production process?
– WGS was used to analyze Listeria
monocytogenes isolate from environment and
from product.
– Multiple clones found, likely that incoming fish
was contaminated and additional contamination
occurred during processing.

6.
Example 1: Smoked Fish
Product Isolates from
Clone A match Lm found on
product from another
manufacturer, likely
contaminated ingredient
Product isolates from
Clone B match Lm
from facility, likely
contaminated
during manufacturing

7.
7
Why is environmental sampling important.
1)The GenomeTrakr database relies on a reference set of
isolates from known foods and known geographic localities.
2)A match of an unknown clinical to a known food or known
geographic location provides an investigational clue for
sourcetracking where the contamination has occurred.
3)Knowledge of where a contaminant is coming from allows
industry to fix the problem based on scientific evidence. This
is research supporting preventative controls.
4)If the root cause of the problem is left unresolved then it is
likely to occur again at a later date.

8.
Phylogenetic analysis of 35 isolates show ingredient source tracking
2009

9.
Salmonella reveals extensive
phylogeographic structure
Romaine #1
Pistachio #3
Pistachio #2
Pistachio #1

10.
<=5 SNPs
20-25 SNPs
SW
INDIA
WGS Cpmparative genomics can also pinpoint sources on a
global scale.

11.
WGS Supports Preventive Controls
 Microbial WGS compliments rapid testing methods
 Permits deep dive to solve persistent/complex problems in a
facility or on a farm
 Comparison of internal WGS results to public database of
food/environmental isolates
 Environmental Monitoring
 Repeat positives, problem w/ resident pathogen?
 Are positives from Zones 2-4 contaminating Zone 1 and/or finished
product?
 Transparency of open 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

12.
Listeria WGS for Food Safety
• 1) Resident Pathogens
• Does a firm/facility have an issue with a
resident pathogen(s)? Does
environmental testing find the same
isolate(s) over time?
• 2) Preventive Controls
• Are isolate(s) from the facility
contaminating finished and/or intermediate
product?

13.
Inspections of High-Risk
Facilities

14.
L. mono in Sprouts

15.
L. mono in Sprouts

16.
Interpretation
SNP Distance
How close are the isolates? No single threshold for all
species/types: rough, conservative guides
1. Inclusion: <=20 SNPs match, virtually identical
2. Inconclusive: 20-100 SNPs
3. Exclusion: > 100 SNPs exclude
Bootstrapping
Do the isolates form a unique cluster w/ >= 95%
support? Is the cluster distinct from other isolates in the
tree?
16

17.
Facility #3, Ice Cream

18.
SNPs - Year to Year, 10
facilities
Facility Product Year to Year
2 Hot Peppers 21
5 RTE Beans 6
6 RTE Meals 8
7 RTE Meals 11
8 RTE Meals >1000
11 Seafood >1000
12 Seafood 4
15 Soft Cheese 8
16 Soft Cheese >1000
17 Soy Sauce 6

19.
Facility #2, Peppers

20.
Facility #17, Soy Sauce

21.
Applications of WGS in the
Food Safety Environment
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

22.
Conclusions
• Resident Pathogens – Over half of facilities
polyclonal, but clones persist year to year
• Not new – TX facility1988 isolates match
2000 outbreak
• Inclusion – 20 SNPs is probably conservative,
more data needed to develop probabilities/odds-
ratios
• Inspections – Most facilities on a 3 to 5 year
cycle, problematic facilities more often, more
data on the way with statistical inferences