is increasingly important because people now regularly consume
ingredients and foods that were sourced from other countries.
Having lots of contributors who are submitting sequences for
isolates collected from many different products and environments
helps to increase the food and environmental strain diversity in
the database and provides a platform for global collaboration of
foodborne pathogen surveillance.
The raw WGS data and daily analyses are publically available
at www.ncbi.nlm.nih.gov/pathogens. As of August 2017, the five
foodborne pathogens under surveillance within Genome Trakr
are: Salmonella enterica, Listeria monocytogenes, Escherichia coli/
Shigella, Campylobacter jejuni, and Vibrio parahaemolyticus.
To date, the Salmonella collection is the largest, with over 80,000
sequences, while the Vibrio parahaemolyticus collection, the newest
collection, has about 1,000 sequences. Each morning, FDA scientists
mine data from this site, looking at submissions and following up on
items of interest. In 2016, the FDA took over 200 regulatory actions
based on data derived from Genome Trakr.
This is how the FDA typically uses the data. A sequence from
an isolate taken during a routine FDA inspection and submitted to
the database might “match” a set of clinical isolate sequences. This
would prompt the FDA to start an inquiry, which might lead to a
follow-up inspection and more sampling at the location from which
the environmental isolate was originally collected, in an effort to
determine if there is causal link between processing facility and the
illness. If a link were established, appropriate regulatory action would
In another example, a non-FDA user of the database might be
curious about tracking a current outbreak. This user could search
the database for words related to the outbreak (ex. papaya, sprouts,
ice cream, or flour) to find clusters (groups of closely related strains),
metadata, and raw sequence data associated with the outbreak or
event of interest.
Genome Trakr data can also be monitored for emerging antibiotic
resistance (AMR) genes. Alongside the cluster results, a panel of
AMR genotypes is predicted for each genome, so a user can track the
incidence of a particular resistance gene across the database or be
alerted when new patterns emerge.
The examples given here are just a few applications of the
Genome Trakr database. Genome Trakr is a great model of a federally
funded program whose initial small investment is returning ten-fold
in ways we could never predict at the onset.
—Ruth Timme, Ph.D., Research Microbiologist and
Genome Trakr Data Coordinator,
Food and Drug Administration (FDA)
Co-Authors: Eric Stevens, Marc Allard, Eric Brown, FDA
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