to applying WGS in food safety management. These factors include but are not lim-
• Development of harmonized guidelines on good practices for WGS data collec-
tion, sequencing quality, and validated analysis
• Validation of methodologies used for data mining and analysis before critical de-
cisions are made based on WGS data
• Ensuring access to global WGS data
To incorporate WGS within a regulatory framework, several key peripheral issues
need to be addressed:
• Legal issues: There may be issues around liability and accountability that are
legally binding in respect of WGS data use in a food safety regulatory framework.
Legal aspects in relation to methodologies used, as well as the need for harmonized and accredited typing methods, may also arise. However, augmenting good
practices in food safety management with the use of WGS data is likely to provide strong justification for regulatory actions.
• Proficiency testing: Transparent validation and certification are common needs
for all new methods, including WGS.
• Training/education: Regulators need to be trained to increase their skills and
capacities in WGS technologies and management of WGS data to use them in
the decision-making process.
• Sustainability: While it is likely that WGS will play an increasingly important
role in food issues, including outbreaks and trade, there should be plans to ensure that sufficient resources are allocated to food safety programs to allow Good
Laboratory Practices in the context of performance.
• Continuous improvement: Newer ways of enhancing WGS may improve the
depth of investigations into pathogen behavior and its correlation with food safety issues. Food safety programs should therefore be regularly reviewed to ensure
essential improvements can be incorporated into their systems.
Promoting Widespread Adoption across the Food Industry
Industry is encouraged to adopt these WGS methods for such applications as
root-cause analysis and understanding when preventive controls are failing at a company. Moreover, as WGS helps pinpoint previously unknown sources of contamination, this knowledge will be used to update Good Agricultural Practices as well as
Good Manufacturing Practices (GMPs). Based on new WGS revelations, FDA is
designing targeted guidance to help manufacturers avoid future pathogen contamination along the farm-to-fork continuum. 7
FDA is expanding its outreach to industry, which performs the vast majority of
food safety monitoring compared with the public sector. Some industry leaders (e.g.,
Mars, DuPont, Nestlé, General Mills, and Conagra) are beginning to implement
WGS in their own food safety monitoring efforts using genomic technologies. There
are many applications in the area of food quality and standardization that would
immediately benefit from the use of these technologies. Food manufacturers could
use the highly discriminatory data provided by WGS to track the source of pathogen
contaminations to a supplier of ingredients or to a specific environmental niche in
the manufacturing environment. The data could be used to allow manufacturers to
efficiently detect and correct problems, which is consistent with most modern food
safety system concepts (GMPs and Hazard Analysis and Critical Control Points) as
well as with Food Safety Modernization Act requirements.
ferred through the Internet to be available and of benefit to the global community.
• Data handling: Many laboratories
do not have access to well-trained bio-informaticians locally and thus cannot
fully take advantage of WGS with their
own data analyses. One solution may be
access to knowledge networks and software/online platforms or through partnership with experienced groups that
could help with initial genome studies.
• Interpretation of WGS data: Even
with access to basic bioinformatics/
genomics software/online platforms,
the interpretation of the data, especially
in combination with epidemiological
information, may not be easy. Training
the microbiologists performing the sequencing, as well as the end-users of the
data, is a critical part of implementing
• Sustainability: If local and socioeconomic benefits are not well-demonstrated and communicated, WGS may not
• Trust: Not only is there an issue
around the legal ownership of publicly
available WGS data and applicable privacy laws, but there also are concerns on
the part of data producers, generators,
and collectors about the ultimate use of
their data, possibly due to lack of trust.
• Need for basic epidemiology, surveillance, and food monitoring/testing
infrastructure: If there are no isolates to
analyze, then implementation of WGS
technology has limited usefulness and is
not a cost-effective investment.
It is evident that considerable progress has been made in WGS methodology and that it will eventually replace
most existing strain-characterization and
subtyping tools. However, it remains
challenging for some to use WGS-generated data for decision making in a
regulatory framework. Therefore, various factors need to be considered when
making informed decisions with respect
“The U.S. Food and Drug Administration (FDA) has created an open-source
WGS network of state, federal, international, and commercial partners.”
(continued on page 54)