Tag Archives: pathogens

Dr. Douglass Marshall, Chief Scientific Officer – Eurofins Microbiology Laboratories
Food Genomics

Part II: Logistics of GenomeTrakr

By Douglas Marshall, Ph.D., Gregory Siragusa, Ph.D.
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Dr. Douglass Marshall, Chief Scientific Officer – Eurofins Microbiology Laboratories

Last month in Food Genomics we asked FDA scientists Drs. Marc Allard and Eric Brown to help the readers of Food Safety Tech understand the process used by GenomeTrakr. In part two we cover some logistical and more general questions.

Greg Siragusa/Douglas Marshall: Why should a food producer or processor submit its own pathogen isolates to GenomeTrakr? Are there any legal liabilities incurred by doing so?

Eric Brown/Marc Allard: The database is available publicly for any outside laboratory to be able to rapidly compare their new WGS data to all of the data in the database. The data is all publicly available so food industry members should carefully consider the strengths and weaknesses of sharing data. The main reason for sharing data is that if any matches arise then this would be immediately known for an investigation and corrective action. With knowledge, companies can better understand their risk and exposure to occasional contamination events.

Siragusa/Marshall: Are there private third-party providers who will perform the same method of sequence analysis for private companies that GenomeTrakr uses in the FDA?

Brown/Allard: Yes, as all of the FDA methods of data collection and analysis are fully transparent and publicly available, any expert third-party provider could easily set up and reproduce the GenomeTrakr methods. Third-party support may be an excellent mechanism for food industry partners that wish to examine the pathogens they have found connected to their products but do not wish to maintain an active WGS laboratory. An internet and reference search will uncover these private third-party providers, as this is a growing market with a diversity of services provided. The FDA works closely with the Institute for Food Safety and Health (IFSH) to share information that may be valuable to their industry partners.

Siragusa/Marshall: Will the FDA perform analysis of isolates for private parties and the sequence not made publicly available?

Brown/Allard: No. While we will sequence relevant strains from many different sources, as a matter of protocol we will submit all of these data to the GenomeTrakr database. That is, currently, the FDA sequences and uploads all available genomic strain data. All data are made publicly available through the GenomeTrakr and NCBI pathogen detection website. The metadata describing each isolate only includes species, date, state location and a general food description which could include the type of food (e.g., an egg) and/or the type of sample (e.g., environmental swab, surface water, sediment, etc.) as well as production date, pH, fat content and water activity. No trade or industry brand names are made publicly available, and the location is ambiguous down to the state level to allow for anonymity of specific farm names or processing centers. An example of metadata in the GenomeTrakr database might include Salmonella, from Washington State in spinach from 2015.

Siragusa/Marshall: Is the CDC tied into GenomeTrakr and if so, how?

Brown/Allard: CDC labels their clinical WGS data as PulseNet with the data uploaded to the NCBI Pathogen Detection website. USDA FSIS also uploads the isolates that they have collected and sequenced from foods that they regulate. All of this WGS data is housed in a centralized repository at NCBI Pathogen Detection website where NCBI conducts rapid analysis for QA/QC. The NCBI posts a daily tree for all species that recently have been uploaded. This way all of the data collected by these federal laboratories and their state and international partners are made publicly available for direct comparison. Numerous other international and academic laboratories also provide data to the NCBI centralized database. When isolates cluster together and appear to be closely related, the FDA works with CDC and USDA FSIS through the normal channels. The great benefit of combining food, environmental and clinical isolate genomes in a common database cannot be overstated.

Siragusa/Marshall: In the event of an outbreak, is it possible to obtain WGS’s from using a shotgun metagenome (a microbial and organismic profile obtain by sequencing all of the DNA in a sample, not just bacterial analysis of an enrichment thereby precluding isolation? (Refer to glossary; see Table 1)

Brown/Allard: Yes, preliminary research has documented the potential to obtain WGS data from cultural enrichments, saving the time it takes for full pure culture isolation, which potentially could provide time savings of two to five days depending on the pathogen. Having well characterized draft genomes such as those in the GenomeTrakr database will support rapid characterization from metagenomes after cultural enrichment. A future goal for the FDA is to transform and expand GenomeTrakr into metaGenomeTrakr to support either pure culture or enriched shotgun metagenomic samples.

Siragusa/Marshall: Is there any way that associated metadata tied to a strain (and hence its sequence) can be unmasked through legal action?

Brown/Allard: FDA protects confidential metadata collected during inspection just as it has always done with PFGE data. WGS data is protected at the same level as other types of subtyping information.

Siragusa/Marshall: Is the GenomeTrakr database associated with the GMI (Global Microbial Identifier)?

Brown/Allard: The GMI is a consortium of like-minded public health scientists who wish to collaborate to create a harmonized global system of DNA genome databases that is publicly available to promote a one-health approach. The GenomeTrakr is one of the databases that make up this larger effort that includes some data from members of the GMI.

Siragusa/Marshall: This column is meant to keep food safety professionals abreast of the latest knowledge, technology and uses of genomics for food safety and quality. Tell us your vision of how or which changes in technology (sequencing chemistry, bioinformatics, etc.) will be coming down the pike and how it might impact GenomeTrakr?

Brown/Allard: New technology has been constantly improving in WGS and in sequencing for the last 20 years, and there is no sign of this slowing down. Improvements continue to accrue in chemistry, equipment and software analysis. Likely future improvements will include more turnkey solutions for WGS from sample to report. This includes both DNA extraction and library preparation for sequencing, as well as data analysis pipelines (the system of analyzing the actual sequence data) that provide rapid, accurate and simple language results. Smaller mobile WGS devices are starting to show feasibility that would bring the lab to the samples and decrease the time to an answer (See: https://nanoporetech.com/products/minion) Metagenomics approaches appear to be maturing so that technology improvements are moving this out of a research phase and into direct applications. Currently MISeq (a commonly used workhorse nucleic acid sequencer made by the Illumina Co.) outputs are on the order of 300 base pair read lengths of nucleotides (i.e. A’s, T’s. C’s G’s), long read sequencing technologies, upwards of 1,500 base pairs may make analysis much easier so that more assembled and completed finished genomes are available in the databases. Cloud-based solutions of data analysis pipelines may provide simple solutions, giving wider access to rapid, validated data analysis and results. FDA researchers are working on all of these aspects of improvements in WGS technology as well as expanding the network to more global partners.

Siragusa/Marshall: Sequences deposited into GenBank (as part of GenomeTrakr) are accessible to anyone anywhere. Does this essentially usher in a whole new chapter in food microbiology especially at the pre-harvest level?

Brown/Allard: Yes, having well characterized reference genomes provided by GenomeTrakr partners will support microbial ecology and metagenomics studies. Metagenomics or microbiomes describing which species are present and what they may be doing in the ecology is providing new knowledge in all aspects of the farm to fork continuum. As the costs for these services decrease, we are seeing an increase in use to answer questions that have been impossible or extremely difficult in the past.

Siragusa/Marshall: GenomeTrakr is not a project per se; rather it is a program. How is it funded and will it continue on stable fiscal footing for the foreseeable future?

Brown/Allard: GenomeTrakr started as a research project in the Office of Regulatory Science in CFSAN, but much of this data collection is no longer research. Today, and for some time in the future, WGS at the FDA is collected as fully validated regulatory data to support outbreak and compliance investigations. As such, the FDA is in transition of moving WGS into a phase for more stable regulatory support. Research and development for future applications and technology exploration will always be a part of the FDA portfolio, although typically at lower funding levels than the regulatory offices. Public health funding is generally protected as everyone wants safe food.

Siragusa/Marshall: Are there any restrictions of isolate source? For instance, can isolates from poultry flocks or even wild birds be deposited?

Brown/Allard: The GenomeTrakr and NCBI pathogen detection databases are open to the public and thus there are no restrictions as long as the minimal metadata and QA and QC metrics are met. Current GenomeTrakr WGS foodborne pathogen data includes samples from both poultry and wild birds, as well as turtles, snakes and frogs. Members interested in what is in the database can go to the NCBI Pathogen Detection website and filter on simple words like avian, bird, gull, chicken, wheat, avocado, etc. An example is as follows for a snake.

Siragusa/Marshall: If a company deposits an isolate, will it have access to the GenomeTrakr derived sequence exclusively or at least initially for some period before that information becomes public?

Brown/Allard: No, currently the FDA does not hold WGS data. All data collected by the FDA is uploaded and released publicly at the GenomeTrakr bioprojects and at NCBI pathogen detection website with no delays. If companies wish to hold data then they need to look to third-party solutions for their needs. The reason that GenomeTrakr has been so successful is due to the real-time nature of the released information and that it is globally available.

Read on to page two below.

Gregory Siragusa, Eurofins
Food Genomics

GenomeTrakr: What Do You Know and What Should You Know?

By Gregory Siragusa, Douglas Marshall, Ph.D.
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Gregory Siragusa, Eurofins

This month we are happy to welcome our guest co-authors and interviewees Eric Brown, Ph.D. and Marc Allard, Ph.D. of CFSAN as we explore the FDA’s GenomeTrakr program in a two-part Food Genomics column. Many of our readers have heard of GenomeTrakr, but are likely to have several questions regarding its core purpose and how it will impact food producers and processors in the United States and globally. In Part I we explore some technical aspects of the topic followed by Part II dealing with practical questions.

Part I: The basics of GenomeTrakr

Greg Siragusa/Doug Marshall: Thank you Dr. Allard and Dr. Brown for joining us in our monthly series, Food Genomics, to inform our readers about GenomeTrakr. Will you begin by telling us about yourselves and your team?

Eric Brown/Marc Allard: Hello, I am Eric, the director of the Division of Microbiology at the U.S. Food and Drug Administration at the Center for Food Safety and Applied Nutrition. Our team is made up of two branches, one that specializes in developing and validating methods for getting foodborne pathogens out of many different food matrices and the other branch conducts numerous tests to subtype and characterized foodborne pathogens. The GenomeTrakr program is in the subtyping branch as Whole Genome Sequencing (WGS) is the ultimate genomic subtyping tool for characterizing a foodborne pathogen at the DNA level.

Hello, my name is Marc, I am a senior biomedical research services officer and a senior advisor in Eric’s division. We are part of the group that conceived, evaluated and deployed the GenomeTrakr database and network.

Siragusa/Marshall: Drs. Allard and Brown, imagine yourself with a group of food safety professionals ranging from vice president for food safety to director, manager and technologists. Would you please give us the ‘elevator speech’ on GenomeTrakr?

Brown/Allard: GenomeTrakr is the first of its kind distributed network for rapidly characterizing bacterial foodborne pathogens using whole genome sequences (WGS). This genomic data can help FDA with many applications, including trace-back to determine the root cause of an outbreak as well providing one work-flow for rapidly characterizing all of the pathogens for which the agency has responsibility. These same methods are also very helpful for antimicrobial resistance monitoring and characterization.

Siragusa/Marshall: From the FDA website, GenomeTrakr is described as “a distributed network of labs to utilize whole genome sequencing for pathogen identification.” We of course have very time-proven methods of microbial identification and subtyping, so why do we need GenomeTrakr for identification and subtyping of microorganisms?

Brown/Allard: If all you want to know is species identification then you are correct, there are existing methods to do this. For some applications you need full characterization through subtyping (i.e., Below the level of species to the actual strain) with WGS. WGS of pathogens provides all of the genetic information about an organism as well as any mobile elements such as phages and plasmids that may be associated with these foodborne pathogens. The GenomeTrakr network and database compiles a large amount of new genetic or DNA sequence data to more fully characterize foodborne pathogens.

GenomeTrakr and WGS are a means to track bacteria based on knowing the sequence of all DNA that comprises that specific bacterium’s genome. It can be called the “ultimate identifier” in that it will show relationships at a very deep level of accuracy.

Siragusa/Marshall: Is it an accurate statement that GenomeTrakr can be considered the new iteration of PulseNet and Pulse field gel electrophoresis (PFGE)? Will PulseNet and PFGE disappear, or will PulseNet and GenomeTrkr merge into a single entity?

Brown/Allard: PulseNet is a network of public health labs run by the CDC, with USDA and FDA as active participants. The network is alive and well and will continue subtyping pathogens for public health. The current and historical subtyping tool used by PulseNet for more than 20 years is PFGE. It is expected that CDC, USDA and FDA’s PFGE data collection will be replaced by WGS data and methods. That transformation has already begun. GenomeTrakr is a network of public health labs run by the FDA to support FDA public health and regulatory activities using WGS methods. Starting in 2012, this network is relatively new and is focused currently on using WGS for trace back to support outbreak investigations and FDA regulatory actions. CDC PulseNet has used WGS data on Listeria and collects draft genomes (i.e., unfinished versions of a final genome are used for quicker assembly) of other foodborne pathogens as well, and USDA’s FSIS has used WGS for the pathogens found on the foods that they regulate. All of the data from GenomeTrakr and Pulsenet are shared at the NCBI Pathogen Detection website (see Figure 1).

Sequences, GenomeTrakr
Figure 1

Siragusa/Marshall: Does an organism have to be classified to the species level before submitting to GenomeTrakr?

Brown/Allard: Yes, species-level identification is part of the minimal metadata (all of the descriptors related to a sample such as geographic origin, lot number, sources, ingredients etc.) required to deposit data in the GenomeTrakr database. This allows initial QA/QC metrics to determine if the new genome is labeled properly.

Siragusa/Marshall: After an isolate is identified to the species level, would you describe to the reader what the basic process is going from an isolated and speciated bacterial colony on an agar plate to a usable whole genome sequence deposited in the GenomeTrakr database?

Brown/Allard: The FDA has a branch of scientists who specialize in ways to isolate foodborne pathogens from food. The detailed methods used ultimately end up in the Bacteriological Analytical Manual (BAM) of approved and validated methods. Once a pathogen is in pure culture then DNA is extracted from the bacterial cells. The DNA is then put into a DNA sequencing library, which modifies the DNA to properly attach and run sequencing reactions depending on the specific sequencing vendor used. The sequence data is downloaded from the sequencing equipment and then uploaded to the National Center for Biotechnology Information (NCBI) Pathogen Detection website. The database is publicly open to allow anyone with foodborne pathogens to upload their data and compare their sequences to what is available in the database.

Siragusa/Marshall: Suppose a specific sequence type of a foodborne bacterial pathogen is found and identified from a processing plant but that the plant has never had a positive assay result for that pathogen in any of its history of product production and ultimate consumption. If an outbreak occurred somewhere in the world and that same specific sequence type were identified as the causative agent, would a company be in anyway liable? Could one even make an association between the two isolates with the same sequence type isolated at great distances from open another?

Brown/Allard: The genetic evidence from WGS supports the hypothesis that the two isolates shared a recent common ancestor. If, for example, the isolate from the processing plant and the outbreak sample where genetically identical across the entire genome, the prediction is that the two samples are connected in some way that is currently not understood. The genetic matches guide the FDA and help point investigations to study the possible connections. This might include additional inspection of the processing plant as well as linking this to the typical epidemiological exposure data. Sometimes due to the indirect nature of how pathogens circulate through the farm to fork continuum and the complex methods of trade, no connection is made. More commonly, these investigative leads from genetic matches help the FDA establish direct links between the two bacterial isolates through a shared ingredient, shared processing, distribution or packaging process. The genetic information and cluster helps the FDA discover new ways that the pathogens are moving from farm to fork. We are unaware of any example where identical genomes somehow independently arose and were unrelated. This is counter to molecular evolutionary theory anyway. Genetic identity equals genetic relatedness and the closer two isolates are genetically to each other, the more recent that they shared a common ancestor. With regard to liability, this is a topic beyond the scope of our group, but genomic data does not by itself prove a direct linkage and that is why additional investigations must follow any close matches.

Siragusa/Marshall: We know that SNPs (Single Nucleotide Polymorphisms or single base pair differences in the same location in a genome) are commonly used to distinguish clonality of bacteria with highly similar genomes. Are there criteria used by GenomeTrakr bioinformaticists that are set to help define what is similar, different or the same?

Brown/Allard: As the database grows with more examples of diverse serotypes or kinds of foodborne pathogens, the FDA WGS group is observing common patterns that can be used as guidance to define what is same or different. For example, closely related for Salmonella and E. coli are usually in the five or fewer SNPs, and closely related for Listeria is 20 or fewer SNPs using the current FDA validated bioinformatics pipeline. These values are not set in stone but should be considered more like guidance for what FDA and GenomeTrakr have observed already from earlier case studies that have already been collected and examined. Often, a greater number (e.g., 21-50) of SNP differences have been observed between strains isolated in some outbreaks. Any close match might support or direct an outbreak investigation if there is evidence that suggests that a particular outbreak looks most closely like an early case from a specific geographic location. WGS data helps investigators focus their efforts toward and international verses domestic exposure or possible country of origin. Even more divergent WGS linkages, when SNPs are greater than 50-100, often connect to different foods or different geographic locations that would lead investigators away from the source of an outbreak as the data provides both inclusivity as well as exclusivity.

When two strains have more than 50–100 SNPs, different food or geographic sources of those strains can be incorrectly linked resulting in investigators pursuing an incorrect source.

Siragusa/Marshall: Can SNPs be identified from different agar-plate clones of the same strain (i.e., Different colonies on the same plate)?

Brown/Allard: Since understanding the natural genetic variation present in foodborne pathogens is the basis to understanding relatedness, the FDA conducted validation experiments on growing then sequencing colonies from the same plate, colonies from frozen inocula, thawing and plating, as well as running the same DNAs on different instruments and with different sequencing technicians. The FDA’s work with Salmonella enterica Montevideo sequencing as well as ongoing proficiency testing among laboratories shows that the same isolate most often has no differences, although some samples have 1-2 SNP differences. Genetic differences observed in isolates collected by FDA inspectors all related to a common outbreak generally have more genetic differences, and this appears to be dependent on the nature of the facility and the length of time that the foodborne pathogen has been resident in the facility and the selective pressure to which the pathogen was exposed to in a range from 0–5 SNPs different.

Siragusa/Marshall: Regarding the use of WGS to track strains in a particular processing plant, is it possible that within that closed microenvironment that strains will evolve sufficiently so that it becomes unique to that source?

Brown/Allard: Yes, we have discovered multiple examples of strains that have evolved in a unique way that they appear to be specific to that source. Hospitals use the same practice to understand hospital-acquired infections and the routes of transmission within a hospitals intensive care unit or surgery. Food industry laboratories as well as FDA investigators could use WGS data in a similar way to determine the root cause of the contamination by combining WGS data with inspection and surveillance. The FDA Office of Compliance uses WGS as one piece of evidence to ask the question: Have we seen this pathogen before?

Siragusa/Marshall: The number of sequences in the GenomeTrakr database is approaching 120,000 (~4,000 per month are added). Are the sequences in the GenomeTrakr database all generated by GenomeTrakr Network labs?

Brown/Allard: The sequences labeled as GenomeTrakr isolates at the NCBI biosample and bioproject databases are the WGS efforts supported by the U.S. FDA and USDA FSIS. GenomeTrakr is a label identifying the FDA, USDA FSIS and collaborative partner’s efforts to sequence food and environmental isolates. Additional laboratories, independent and beyond formal membership in the GT network, upload WGS data to the NCBI pathogen detection website of which GenomeTrakr is one part. CDC shares WGS data on primarily clinical PulseNet isolates and USDA FSIS shares WGS foodborne pathogens for foods that they regulate. Numerous international public health laboratories also upload WGS data to NCBI. The NCBI pathogen detection website includes all publicly released WGS data for the species that they are analyzing, and this might include additional research or public health data. The point of contact for who submitted the data is listed in the biosample data sheet, an example of which can be seen here.

Siragusa/Marshall: Once sequences are deposited into the GenomeTrakr database, are they also part of GenBank?

Brown/Allard: The majority of the GenomeTrakr database is part of the NCBI SRA (sequence read archive) database, which is a less finished version of the data in GenBank. GenBank data is assembled and annotated, which takes more time and analysis to complete. Once automated software is optimized and validated, NCBI likely will place all of the GenomeTrakr data into GenBank. Currently, only the published WGS data from GenomeTrakr is available in GenBank. All of the GenomeTrakr data is available in SRA both at GenomeTrakr bioprojects and in the NCBI pathogen detection website.

Readers, look for the Part II of this column where we continue our exploration with Drs. Brown and Allard and ask some general questions about the logistics surrounding GenomeTrakr. As always, please contact either Greg Siragusa or Doug Marshall with comments, questions or ideas for future Food Genomics columns.

About the Interviewees

Marc W. Allard, Ph.D.

Marc Allard, FDAMarc Allard, Ph.D. is a senior biomedical research services officer specializing in both phylogenetic analysis as well as the biochemical laboratory methods that generate the genetic information in the GenomeTrakr database, which is part of the NCBI Pathogen Detection website. Allard joined the Division of Microbiology in FDA’s Office of Regulatory Science in 2008 where he uses Whole Genome Sequencing of foodborne pathogens to identify and characterize outbreaks of bacterial strains, particularly Salmonella, E. coli, and Listeria. He obtained a B.A. from the University of Vermont, an M.S. from Texas A&M University and his Ph.D. in biology in from Harvard University. Allard was the Louis Weintraub Associate Professor of Biology at George Washington University for 14 years from 1994 to 2008. He is a Fellow of the American Academy of Microbiology.

Eric W. Brown, Ph.D.

Eric Brown, FDAEric W. Brown, Ph.D. currently serves as director of the Division of Microbiology in the Office of Regulatory Science. He oversees a group of 50 researchers and support scientists engaged in a multi-parameter research program to develop and apply microbiological and molecular genetic strategies for detecting, identifying, and differentiating bacterial foodborne pathogens such as Salmonella and shiga-toxin producing E. coli. Brown received his Ph.D. in microbial genetics from The Genetics Program in the Department of Biological Sciences at The George Washington University. He has conducted research in microbial evolution and microbial ecology as a research fellow in the National Cancer Institute, the U.S. Department of Agriculture, and as a tenure-track Professor of Microbiology at Loyola University of Chicago. Brown came to the Food and Drug Administration in 1999 and has since carried out numerous experiments relating to the detection, identification, and discrimination of foodborne pathogens.

Recall

Agroson’s Recalls Nearly 2500 Boxes of Maradol Papayas

By Food Safety Tech Staff
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Recall

Agroson’s LLC is taking precautionary measures and has recalled 2483 boxes of Maradol Papaya Cavi Brand over Salmonella concerns. The papayas were grown and packed by Carica de Campeche—and other brands that have bought from this farm tested positive for Salmonella. Although no illnesses have been reported, the company initial the recall after FDA notified it about these other brands testing positive.

The papayas (carton codes 3044, 3045 and 3050) were distributed to wholesalers in New York, New Jersey and Connecticut between July 16 and July 19, and were sold until July 31, 2017.

Freshtex Produce of Alamo, TX also announced a voluntary recall of its “Valery” brand Maradol Papayas grown and packed by Carica de Campeche.

Following one death, Grande Produce recalled its Caribeña brand Maradol papayas more than a week ago.

Papaya recall, Salmonella

One Death, Grande Produce Issues Voluntary Recall of Caribeña Papayas

By Food Safety Tech Staff
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Papaya recall, Salmonella
Papaya recall, Salmonella
Grande Produce has recalled papayas with the brand name Caribeña labeled on cartons.

One person has died (New York City), 12 people have been hospitalized and a total of 47 people have been infected with a strain of Salmonella Kiambu, according to the CDC. Epidemiological and lab evidence points to yellow Maradol papayas as the “likely” culprit of this multistate outbreak.

Thus far, one brand has been linked to the outbreak, Grande Produce, which has recalled its Caribeña brand Maradol papayas distributed between July 10 and July 19, 2017. The CDC will announce other brands once more information is available. During its investigation, an illness cluster was identified in Maryland.

Grande Produce, a distribution center located in Maryland, has stopped importing papayas from its grower and “is taking all precautionary measures to ensure the safety of its imported produce”, according to a company announcement on FDA’s website. According to Grande Produce, environmental microbial testing of its facilities has, to date, tested negative for Salmonella. “Specific sources of what health officials now believe may be two separate Salmonella outbreaks have not yet been determined,” the announcement states.

Recall

325,000 Pounds of Meat Lard Products Recalled due to Processing Deviation

By Food Safety Tech Staff
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Recall

On Friday the USDA announced a large recall of 325,000 pounds of meat and poultry fat and lard products by Supreme Cuisine. The Class I recall is due to a processing deviation that could cause bacterial pathogens to grow and survive in the products. The duck, beef and pork fat and lard products, which have a one-year shelf life, were produced and packaged from June 1, 2016 through May 8, 2017.

The issue was uncovered after Supreme Cuisine received a consumer complaint of a loose lid. There have been no confirmed reports of adverse reactions due to consumption of the products, and consumers are being urged to discard any of these products.

FSIS is providing a full list of the recalled products here on its website.

Sequencing pattern, pathogens

Build Stronger Food Safety Programs With Next-Generation Sequencing

By Akhila Vasan, Mahni Ghorashi
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Sequencing pattern, pathogens

According to a survey by retail consulting firm Daymon Worldwide, 50% of today’s consumers are more concerned about food safety and quality than they were five years ago. Their concerns are not unfounded. Recalls are on the rise, and consumer health is put at risk by undetected cases of food adulteration and contamination.

While consumers are concerned about the quality of the food they eat, buy and sell, the brands responsible for making and selling these products also face serious consequences if their food safety programs don’t safeguard against devastating recalls.

A key cause of recalls, food fraud, or the deliberate and intentional substitution, addition, tampering or misrepresentation of food, food ingredients or food packaging, continues to be an issue for the food safety industry. According to PricewaterhouseCoopers, food fraud is estimated to be a $10–15 billion a year problem.

Some of the more notorious examples include wood shavings in Parmesan cheese, the 2013 horsemeat scandal in the United Kingdom, and Oceana’s landmark 2013 study, which revealed that a whopping 33% of seafood sold in the United States is mislabeled. While international organizations like Interpol have stepped up to tackle food fraud, which is exacerbated by the complexity of globalization, academics estimate that 4% of all food is adulterated in some way.

High-profile outbreaks due to undetected pathogens are also a serious risk for consumers and the food industry alike. The United States’ economy alone loses about $55 billion each year due to food illnesses. The World Health Organization estimates that nearly 1 in 10 people become ill every year from eating contaminated food. In 2016 alone, several high-profile outbreaks rocked the industry, harming consumers and brands alike. From the E. coli O26 outbreak at Chipotle to Salmonella in live poultry to Hepatitis A in raw scallops to the Listeria monocytogenes outbreak at Blue Bell ice cream, the food industry has dealt with many challenges on this front.

What’s Being Done?

Both food fraud and undetected contamination can cause massive, expensive and damaging recalls for brands. Each recall can cost a brand about $10 million in direct costs, and that doesn’t include the cost of brand damage and lost sales.

Frustratingly, more recalls due to food fraud and contamination are happening at a time when regulation and policy is stronger than ever. As the global food system evolves, regulatory agencies around the world are fine-tuning or overhauling their food safety systems, taking a more preventive approach.

At the core of these changes is HACCP, the long implemented and well-understood method of evaluating and controlling food safety hazards. In the United States, while HACCP is still used in some sectors, the move to FSMA is apparent in others. In many ways, 2017 is dubbed the year of FSMA compliance.

There is also the Global Food Safety Initiative (GFSI), a private industry conformance standard for certification, which was established proactively by industry to improve food safety throughout the supply chain. It is important to note that all regulatory drivers, be they public or private, work together to ensure the common goal of delivering safe food for consumers. However, more is needed to ensure that nothing slips through the food safety programs.

Now, bolstered by regulatory efforts, advancements in technology make it easier than ever to update food safety programs to better safeguard against food safety risks and recalls and to explore what’s next in food.

Powering the Food Safety Programs of Tomorrow

Today, food safety programs are being bolstered by new technologies as well, including genomic sequencing techniques like NGS. NGS, which stands for next-generation sequencing, is an automated DNA sequencing technology that generates and analyzes millions of sequences per run, allowing researchers to sequence, re-sequence and compare data at a rate previously not possible.

The traditional methods of polymerase chain reaction (PCR) are quickly being replaced by faster and more accurate solutions. The benefit of NGS over PCR is that PCR is targeted, meaning you have to know what you’re looking for. It is also conducted one target at a time, meaning that each target you wish to test requires a separate run. This is costly and does not scale.

Next-generation sequencing, by contrast, is universal. A single test exposes all potential threats, both expected and unexpected. From bacteria and fungi to the precise composition of ingredients in a given sample, a single NGS test guarantees that hazards cannot slip through your supply chain.  In the not-too-distant future, the cost and speed of NGS will meet and then quickly surpass legacy technologies; you can expect the technology to be adopted with increasing speed the moment it becomes price-competitive with PCR.

Applications of NGS

Even today’s NGS technologies are deployment-ready for applications including food safety and supplier verification. With the bottom line protected, food brands are also able to leverage NGS to build the food chain of tomorrow, and focus funding and resources on research and development.

Safety Testing. Advances in NGS allow retailers and manufacturers to securely identify specific pathogens down to the strain level, test environmental samples, verify authenticity and ultimately reduce the risk of outbreaks or counterfeit incidents.

Compared to legacy PCR methods, brands leveraging NGS are able to test for multiple pathogens with a single test, at a lower cost and higher accuracy. This universality is key to protecting brands against all pathogens, not just the ones for which they know to look.

Supplier Verification. NGS technologies can be used to combat economically motivated food fraud and mislabeling, and verify supplier claims. Undeclared allergens are the number one reason for recalls.

As a result of FSMA, the FDA now requires food facilities to implement preventative controls to avoid food fraud, which today occurs in up to 10% of all food types. Traditional PCR-based tests cannot distinguish between closely related species and have high false-positive rates. NGS offers high-resolution, scalable testing so that you can verify suppliers and authenticate product claims, mitigating risk at every level.

R&D. NGS-based metagenomics analysis can be used in R&D and new product development to build the next-generation of health foods and nutritional products, as well as to perform competitive benchmarking and formulation consistency monitoring.

As the consumer takes more and more control over what goes into their food, brands have the opportunity to differentiate not only on transparency, but on personalization, novel approaches and better consistency.

A Brighter Future for Food Safety

With advances in genomic techniques and analysis, we are now better than ever equipped to safeguard against food safety risks, protect brands from having to issue costly recalls, and even explore the next frontier for food. As the technology gets better, faster and cheaper, we are going to experience a tectonic shift in the way we manage our food safety programs and supply chains at large.

We will be discussing this topic, “Building Stronger Food Safety Programs through Next-Generation Sequencing”, during a live conversation on June 7, 2017 at 2:00 pm ET. Microbiologists, testing personnel, food industry management, and anyone interested in how to leverage these new technologies to fortify their food safety programs will learn how NGS is going to transform the future of food safety.

Reduce Foodborne Illness Causing Microorganisms through a Structured Food Safety Plan

By James Cook
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In 2011 three U.S. government agencies, the CDC, the FDA and the USDA’s Food Safety Inspection Service (FSIS) created the Interagency Food Safety Analytics Collaboration (IFSAC). The development of IFSAC allowed these agencies to combine their federal food safety efforts. The initial focus was to identify those foods and prioritize pathogens that were the most important sources of foodborne illnesses.

The priority pathogens are Salmonella, E. coli O157:H7, Listeria monocytogenes and Campylobacter. To research the most important product sources, the three agencies collaborated on the development of better data collection and developed methods for estimating the sources of foodborne illnesses. Some of this research was to evaluate whether the regulatory requirements already in effect were reducing the foodborne pathogens in a specific product matrix. The collection, sharing and use of this data is an important part of the collaboration. For example, when the FDA is in a facility for routine audit or targeted enforcement, they will generally take environmental swabs and samples of air, water and materials, as appropriate, which are then tested for the targeted pathogens. If a pathogen is found, then serotyping and pulsed-field gel electrophoresis (PFGE) fingerprinting is performed, and this is compared to the information in the database concerning outbreaks and illnesses. This data collection enables the agencies to more quickly react to pinpoint the source of foodborne illnesses and thereby reduce the number of foodborne illnesses.

The IFSAC strategic plan for 2017 to 2021 will enhance the collection of data. The industry must be prepared for more environmental and material sampling. Enhancement of data collection by both agencies can be seen through the FSIS notices and directives, and through the guidance information being produced by the FDA for FSMA. Some examples are the raw pork products exploratory sampling project and the FDA draft guidance for the control of Listeria monocytogenes in ready-to-eat foods.

Starting May 1 2017, the next phase of the raw pork products exploratory sampling project will begin. Samples will be collected and tested for Salmonella, Shiga-toxin producing E. coli (STECs), aerobic plate count and generic E. coli. In the previous phase, the FSIS analyzed 1200 samples for Salmonella for which results are published in their quarterly reports. This is part of the USDA FSIS Salmonella action plan published December 4, 2013 in an effort to establish pathogen reduction standards. In order to achieve any objective, establishing baseline data is essential in any program. Once the baseline data is established and the objective is determined, which in this situation is the Health People 2020 goal of reducing human illness from Salmonella by 25%, one can determine by assessment of the programs and data what interventions will need to take place.

The FDA has revised its draft guidance for the control of Listeria monocytogenes in ready-to-eat food, as per the requirement in 21 CFR 117 Current Good Manufacturing Practice, Hazard Analysis and Risk-Based Preventive Controls for Human Foods, which is one of the seven core FSMA regulations. Ready-to-eat foods that are exposed to the environment prior to packaging and have no Listeria monocytogenes control measure that significantly reduces the pathogen’s presence, will be required to perform testing of the environment and, if necessary, testing of the raw and finished materials. Implementing this guidance document helps the suppliers of these items to cover many sections of this FSMA regulation.

The purpose of any environmental program is to verify the effectiveness of control programs such as cleaning and sanitizing, and personnel hygiene, and to identify those locations in a facility where there are issues. Corrective actions to eliminate or reduce those problems can then be implemented. Environmental programs that never find any problems are poorly designed. The FDA has stated in its guidance that finding Listeria species is expected. They also recommend that instead of sampling after cleaning and/or sanitation, the sampling program be designed to look for contamination in the worst-case scenario by sampling several hours into production, and preferably, just before clean up. The suggestion on this type of sampling is to hold and test the product being produced and to perform some validated rapid test methodology in order to determine whether or not action must be taken. If the presence of a pathogen is confirmed, it is not always necessary to dispose of a product, as some materials can be further processed to eliminate it.

With this environmental and product/material testing data collected, it is possible to perform a trends analysis. This will help to improve sanitation conditions, the performance of both programs and personnel, and identity the need for corrective actions. The main points to this program are the data collection and then the use of this data to reduce the incidence of foodborne illness. Repeated problems require intervention and resolution. Changes in programs or training may be necessary, if they are shown to be the root cause of the problem. If a specific issue is discovered to be a supply source problem, then the determination of a suppliers’ program is the appropriate avenue to resolve that issue. Generally, this will mean performing an audit of the suppliers program or reviewing the audit, not just the certificate, and establishing whether they have a structured program to reduce or eliminate these pathogens.

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High processing pas

HPP: Achieve High Standards of Food Safety Without Compromising Food Quality

By Mark Duffy
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High processing pas

As food companies analyze and modify their production processes to ensure FSMA compliance, many are finding that traditional food processing technologies aren’t ideally suiting their needs. Conventional pasteurization technologies like heat pasteurization have been relied on to protect the safety of the food supply over the years, but they aren’t without their downsides. For example, sometimes they negatively impact the flavor, texture, nutrients and color of food products. Additionally, many traditional food processing methods require chemical additives to be integrated to preserve quality and taste. In a market where consumers are more frequently appreciating, if not demanding, cleaner labels with simple ingredients, these solutions are often becoming less attractive options for some companies.

This new demand for a higher level of food safety combined with an emphasis on food quality has led some producers of refrigerated foods to turn to an increasingly popular alternative: High pressure processing.

How HPP Works

High pressure processing, or HPP, is an effective technique that uses pressure rather than heat or chemicals to disable pathogens in food. After packaging, food products composed of some degree of water activity (Aw) are placed into a machine that applies incredibly intense water pressure to food—sometimes as much as 87,000 psi.

High pressure processing
How high pressure processing works. Graphic courtesy of Universal Pasteurization & Universal Cold Storage

This process interrupts the cellular function of the microorganisms both on the surface and deep within the food and can serve as a critical control point (CCP) in a HACCP program. Research studies on a wide range of refrigerated food products and categories confirm that HPP technology inactivates vegetative bacteria like Listeria monocytogenes, Salmonella, E. coli 0157:H7, and Campylobacter as well as yeasts and molds. Additionally, because pressure is applied after the food is packaged, HPP drastically reduces any chance of recontamination.

Besides its food safety benefits, HPP offers food producers added benefits over traditional methods. Because the pressure inactivates spoilage organisms along with pathogens, many foods see a substantial increase in shelf life after undergoing HPP, sometimes even twice as long. Processors use this shelf-life extension to increase their distribution reach and reduce food waste.

In a recent survey, 57% of respondents in the food and beverage industry characterized their companies’ use of HPP as substantial or growing. Survey respondents also scored HPP’s ability to make food safer by eliminating pathogens above a 4 on a 5-point scale, one of the highest of any food processing technology.

However, HPP isn’t right for every product. It isn’t effective on some enzymes and bacterial spores, like Clostridium botulinum. Producers need to tap into other techniques to address concerns not affected by HPP. The process also requires foods to be packaged in fairly flexible packaging to allow for an even application of pressure. Glass bottles or particularly hard plastics will not be suitable.

HPP can also be daunting to implement for some companies. Purchasing an HPP machine is a major investment, typically seven-figures, without factoring in specific facility requirements or staffing needs. In the same survey of food and beverage producers, the most commonly cited concerns had nothing to do with the efficacy or value of the technology, but rather with the cost of purchasing and staffing the equipment.

For businesses that don’t want to make that kind of capital expenditure commitment but want to take advantage of high pressure processing, HPP outsourcing providers offer a more affordable solution. These companies own and operate HPP machines on behalf of clients. That way, food brands don’t have to purchase expensive HPP machines and regularly maintain their own equipment.

Is HPP right for you? The answer and the nuances are highly variable, but HPP is a fast-growing food preservation technology offering many benefits, including food safety benefits, across a broad product spectrum.

Listeria

How One Company Eliminated Listeria Using Chlorine Dioxide Gas

By Kevin Lorcheim
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Listeria

The previous article discussed the various decontamination options available to eliminate Listeria. It was explained why the physical properties of gaseous chlorine dioxide make it so effective. This article focuses on one company’s use of chlorine dioxide gas decontamination for both contamination response and for preventive control.

The summer of 2015 saw multiple ice cream manufacturers affected by Listeria monocytogenes. The ice cream facility detailed in this article never had a supply outage, but ceased production for a short amount of time in order to investigate and correct their contamination. After a plant-wide review of procedures, workflows, equipment design and product testing, multiple corrective actions were put into place to eliminate Listeria from the facility and help prevent it from returning. One such corrective action was to decontaminate the production area and cold storage rooms using chlorine dioxide gas. This process took place after the rest of the corrective actions, so as to decontaminate the entire facility immediately before production was set to resume.

Responsive Decontamination

The initial decontamination was in response to the Listeria monocytogenes found at various locations throughout the facility. A food safety investigation and microbiological review took place to find the source of the contamination within the facility in order to create a corrective action plan in place. Listeria was found in a number of locations including the dairy brick flooring that ran throughout the production area. A decision was made to replace the flooring, among other equipment upgrades and procedural changes in order to provide a safer food manufacturing environment once production resumed. Once the lengthy repair and upgrade list was completed, the chlorine dioxide gas decontamination was initiated.

The facility in question was approximately 620,000 cubic feet in volume, spanning multiple rooms as well as a tank alley located on a different floor. The timeline to complete the decontamination was 2.5 days. The first half-day consisted of safety training, a plant orientation tour, a meeting with plant supervisors, and the unpacking of equipment. The second day involved the setup of all equipment, which included chlorine dioxide gas generators, air distribution blowers, and a chlorine dioxide gas concentration monitor. Gas injection tubing was run from the chlorine dioxide gas generators throughout the facility to approximately 30 locations within the production area. The injection points were selected to aid its natural gaseous distribution by placing them apart from one another. Gas sample tubing was run to various points throughout the facility in locations away from the injection locations to sample gas concentrations furthest away from injection points where concentrations would be higher. Sample locations were also placed in locations known to be positive for Listeria monocytogenes to provide a more complete record of treatment for those locations. In total, 14 sample locations were selected between plant supervisors and the decontamination team. Throughout the entire decontamination, the gas concentration monitor would be used to continuously pull samples from those locations to monitor the concentration of chlorine dioxide gas and ensure that the proper dosage is reached.

As a final means of process control, 61 biological indicators were brought to validate that the decontamination process was effective at achieving a 6-log sporicidal reduction. 60 would be placed at various challenging locations within the facility, while one would be randomly selected to act as a positive control that would not be exposed to chlorine dioxide gas. Biological indicators provide a reliable method to validate decontamination, as they are produced in a laboratory to be highly consistent and contain more than a million bacterial spores impregnated on a paper substrate and wrapped in a Tyvek pouch. Bacterial spores are considered to be the hardest microorganism to kill, so validating that the process was able to kill all million spores on the biological indicator in effect also proves the process was able to eliminate Listeria from surfaces. The biological indicators were placed at locations known to be positive for Listeria, as well as other hard-to-reach locations such as the interior of production equipment, underneath equipment and inside some piping systems.

In order to prepare the facility for decontamination, all doors, air handling systems, and penetrations into the space were sealed off to keep the gas within the production area. After a safety sweep for personnel, the decontamination was performed to eliminate Listeria from all locations within the production area.

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Peas, UV light

Controlling and Mitigating Pathogens Throughout Production

By Troy Smith
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Peas, UV light
Sampling
Product sampling

As the enforcement of rules, regulations and inspections get underway at food production facilities, we are faced with maintaining production rates while looking for infinitesimal pathogens and cleaning to non-detectible levels. This clearly sets demand on the plant for new and creative methods to control and mitigate pathogens pre-production, during production and post production.

As this occurs, the term clean takes on new meaning: What is clean, and how clean is clean? Swab and plate counts are now critically important. What method is used at the plant, who is testing, what sampling procedure is used, and how do we use the results? As we look at the process from start to finish, we must keep several key questions in mind: What are harboring points in the process, and what are the touch-point considerations to the product? Let’s review the overall processing progression through the factory (see Figure 1).

Figure 1.
Figure 1. The progression of processing of a food product through a facility.

Now consider micro pathogen contamination to the product, as we look deeper in the process for contamination or critical control points as used in successful HACCP plans. Consider contamination and how it may travel or contact food product. It is understood through study and research of both pathogens and plant operations that contamination may be introduced to the plant by the front door, back door, pallet, product, or by a person. In many cases, each of these considerations leads to uncontrolled environments that create uncontrolled measurements throughout, which lead to cleaning procedures based on time rather than science. This is certainly not to say that creating a preventive maintenance schedule based on a calendar is a bad thing. Rather, the message is to consider a deeper look at the pathogens and how they live and replicate. From the regulatory and control measures this should be a clear message of what food-to-pathogen considerations should be taken at the plant level as well as measurement methods and acceptable levels (which is not an easy answer, as each product and environment can change this answer). A good example to consider is public schools and children. Health organizations work to help the schooling system understand what immunizations children should have based on the current health risk tolerance levels. In food production, the consideration is similar in an everchanging environment. As we see contamination levels change the methods, techniques and solutions to proper food production must account for the pathogens of concern.

Contamination, Risk tolerance, Opportunity for Growth

Contamination, risk tolerance, and opportunity for growth are the considerations when looking at a plant design or a plant modification. Modification to modernization should be a top-of-mind critical quality control measure. If there are a few things we know, it is how to produce food at high rates of speed, measure and value production rates, and delays or failures can be measured by equipment and personnel performance. In the case of quality control, we must review, comprehend, and protect process risk. From a management or non-technical viewpoint, quality control can be very difficult to understand. When discussing pathogens, our concerns are not visible to the human eye—we are beyond a dirty surface, weare looking at risk tolerance based on pathogen growth in logarithmic measurement. When combining quality control and production, the measurement control and mitigation measures complement the effort. The use of quality control is expected and should coordinate with production to ensure the product is produced at the expected quality level.