Ingenuity Pathway Analysis (IPA)

Contributed by Poyin Chen

Scientific research is slowly but surely moving away from one gene-one organism focus. We now understand that individual genes are only a small part of a whole, just as a single organism is only a small part of a large, diverse community. The constant improvement in –omics technologies is creating a large influx of genomic, transcriptomic, and metabolomic data on community interactions.

With this influx comes the problem of how to make sense of these data in a biologically coherent manner. While knowing how one gene or one metabolite is changing in response to different treatments used to be satisfactory, knowing how this change is impacting up and downstream pathways is much more impactful and relevant in today’s research environment. Ingenuity Pathway Analysis (IPA), a software provided by Qiagen, draws together all known (published) knowledge on pathways in the human model. IPA is curated with all known pathways in humans, such as metabolic, inflammatory, and disease pathways.

What I find exciting is that IPA allows for simultaneous analysis of transcriptomic and metabolomics data sets. With this feature, I will be able to visualize infectious disease networks and their associated molecules to ascertain the impact of bacterial infections and preventative treatments on the host. Changes in gene expression levels may not always equate to an equivalent change in small molecules in the cell. Using IPA as as the interface between my transcriptomic and metabolomic data sets will help to further make sense of the puzzle that is life.

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Forensic Science and Microbiome

Contributed by Ning Chin

Forensic science is the use of science to settle a legal argument. In criminal cases, a forensic technique is used to definitively identify the victim and the perpetrator. Deoxyribonucleic acid (DNA) that is present in most human cells and biological fluid has individualizing characteristics that allow forensic scientists to identify the person that left the DNA. DNA fingerprinting is currently widely accepted in court and is considered the gold standard in forensic science because it is highly polymorphic and thus has a high degree of individualization. The court also accepts animal DNA evidence. Unknown animal blood and tissue samples are tested to screen for endangered wildlife to track down poachers. DNA of pets can also serve as evidence of association between the suspect, the victim, the evidence, and the crime scene.

One of the most important aspects of forensic science is context. While human DNA is great at providing information regarding the identity of a person, other evidence are often needed to prove that the suspect has ill intent. Bacterial DNA might prove to be useful in these situations. Bacterial DNA has gained significant attention because next-generation sequencing has made sequencing bacterial DNA more accessible. Traditionally, scientists used culture-based methods to grow and observe bacteria on different media, but that lacks the predictive value of single organism analysis. In contrast, sequencing bacterial DNA yields genomic information to provide community structure and specific genomic information about the entire bacterial population of a specific location. In environmental samples this molecular bacterial fingerprint is definitive for specific location. This is also true of specific metabolically linked human parameters, such as obesity. Several researchers have demonstrated that every individual has a unique skin microbiome that can be used as an identification method to connect an item to its user. Researchers also showed that bacteria can be used to determine the cause of death and time of death. Bacteria can also be used to predict the source of body fluids, which is especially important in sexual assault cases. Collectively these studies suggest that measuring each bacterial species in a bacterial community can be very helpful in forensic science.

 

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The Importance of Small Molecules in Biological Systems

Contributed by Narine Arabyan

Metabolomics is a newly blooming and rapidly expanding field that combines the sciences of biology, chemistry, mathematics, and computer technology. Metabolomics is the study of metabolites or small molecules inside the cells and biological systems. This provides a unique chemical fingerprints that specific cellular processes leave behind, producing a snapshot for a certain point in time. A complete or global metabolic profiles and their comparative analysis can be obtained. However, the major limitation profiling these metabolites is the analysis and identification of these compounds. Hence, to analyze such details in a biological system requires robust platforms. Separation techniques (GC and LC) are used along with detection techniques (MS and NMR) to help metabolic profiling. Hyphenated techniques such as GC-MS, LC-MS, LC-NMR, and others are now being used for high-resolution.

Metabolomics is expanding at a fast speed along with the enhancement of technology. This provides large applications in life sciences. The importance of metabolomics has been identified in food sciences to help check the quality, taste, and nutritional value of food and drinks; in pharmaceutical industry to help identify new compounds which can be used to develop new drugs; in infectious diseases to help identify unique metabolites that can be used as biomarkers to identify diseases; in cancer to identify early stages of cancer to provide better and more effective treatment; and in agriculture to investigate how plants respond to different environmental conditions.

There are many programs and databases that help to analyze data and to identify compounds. I like to use MetaboAnalyst 3.0 (http://www.metaboanalyst.ca/) to perform analysis of metabolomic data. This program has many different functional modules for different purposes, such as: Statistical analysis, Enrichment analysis, Pathway analysis, Time series analysis, Power analysis, Biomarker analysis, Integrated pathway analysis, and other utilities. For more details please see the three references.

 

References:

Xia, J., Sinelnikov, I., Han, B., and Wishart, D.S. (2015) MetaboAnalyst 3.0 – making metabolomics more meaningful. Nucl. Acids Res. (DOI: 10.1093/nar/gkv380).

Xia, J., Mandal, R., Sinelnikov, I., Broadhurst, D., and Wishart, D.S. (2012) MetaboAnalyst 2.0 – a comprehensive server for metabolomic data analysis. Nucl. Acids Res. 40, W127-W133.

Xia, J., Psychogios, N., Young, N. and Wishart, D.S. (2009) MetaboAnalyst: a web server for metabolomic data analysis and interpretation. Nucl. Acids Res. 37, W652-660.

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California has set the strictest antibiotics standards

Contributed by Nguyet Kong

California Governor Jerry Brown signed a bill that set the strictest antibiotics standards in the United States for the use with livestock production from chickens to cows. This bill will go into effect in 2018, so livestock production farmers have time to adjust to the new requirement. The new law bans it use of growth promoters to make the animals fatter, so the California Department of Food and Agriculture tracks the information on drug sales and usage, drug resistant bacteria, and livestock management practices.

California being known for their leadership in public health and environmental issues comes from the overuse of drugs that is contributing to life threatening infections from drug resistant bacteria that are called “superbugs.” Animals can carry harmful bacteria in their gut, so when antibiotics are given to the animals the antibiotics kill most of the bacteria in their gut and only resistant bacteria survive and grow. The resistant bacteria can be spread via multiple routes such as animal products, produce through contaminated water or soil, prepared food through contaminated surfaces and the environment when animals poop. People can get sick with resistant infections from contaminated food and the environment so take precaution to prevent food poisoning. The US Center for Disease Control and Prevention (CDC) estimates that 2 million people in the country are infected with drug resistant bacteria each year and at least 20,000 cases lead to death. Some infections are mild illnesses and some are deadly. About 1 in 5 resistant infections are caused by germs from food and animals. Be aware and understand about antibiotic resistance and food safety to protect yourself and your family from those infections.

For more information, please visit

http://www.nrdc.org/media/2015/151009.asp

http://www.cdc.gov/foodsafety/index.html

http://www.cdc.gov/ncezid/dfwed/factsheets.html

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Avian Influenza Breakouts in Southern China during the Winter Season

Contributed by Carol Huang

On January 14th, 2016, the Health and Family Planning Commission of Guangdong Province, China, has reported an additional two human cases of avian influenza A (H7N9). Human infection with H7N9 flu virus, however, causes serious respiratory symptoms and can lead to death – the most common symptom is severe pneumonia. Other symptoms include fever, cough that produces sputum, wheeze (whistling sound during breathing, a sign of breathing problems), headache, myalgia (muscle pain/aches), and general malaise. The Mainland health authorities have reported a total of 680 human cases of avian influenza A (H7N9) since 2013.

On Jan. 13th, 2016, an H5N1 avian influenza case was reported in Sichuan province, China. The 42-year-old patient presented with fever and other symptoms in late December and was hospitalized and is currently in extreme critical condition. Almost all cases of H5N1 infection in people have been associated with close contact with infected live or dead birds, or H5N1-contaminated environments. The virus does not infect humans easily, and spread from person to person appears to be unusual. There is no evidence that the disease can be spread to people through properly prepared and thoroughly cooked food.

On January 8th, 2016, the Health and Family Planning Commission of Guangdong Province has reported a 3rd case of H5N6 avian influenza case in Shenzhen City and Zhaoqing City involving a 25-year-old Shenzhen man. The Mainland health authorities have reported a total of seven human cases of avian influenza A (H5N6) since 2014.

Avian influenza is caused by those influenza viruses that mainly affect birds and poultry, such as chickens or ducks. Clinical presentation of avian influenza in humans includes eye infection (conjunctivitis), flu-like symptoms (e.g. fever, cough, sore throat, muscle aches) or severe respiratory illness (e.g. chest infection). The incubation period ranges from 7 to 10 days. The more virulent forms can result in respiratory failure, multi-organ failure and even death. People primarily become infected with avian influenza through close contact with infected birds and poultry (live or dead) or their droppings. Human-to-human transmission is inefficient.

Poultry, especially chicken is an important dish on the table during the Lunar New Year season in Asian countries, who celebrate Lunar New Year. It is considered to bring luck to people. For preparation of big market needs, farmers would increase poultry production in the early winter season. Unfortunately, most breakouts occur in winter season.

To be alert, do not visit poultry markets, farms, or have contact with poultry in infected regions.

http://outbreaknewstoday.com

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Alli’s QuickStart Genomics User Guide: How To Get On The Bus!

Contributed by Allison Weis

The big scary world of genomics, when first entering, can be overwhelming to say the least. But with a deep breath and these tools, you’ll soon be whizzing down ATG Avenue with the other polymerases. First, if you’ve received sequence data, you need an assembler! We use Abyss in the Weimer lab, but there are a few other good options for bacterial assembly. A5, or Andrew and Aaron’s Awesome Assembly Pipeline, is a popular one that you can reference here: (http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0042304). SPAdes is another good assembler out there and some consider it the best for bacterial assemblies. If you aren’t familiar with command line commandeering – check out using CLC or the Geneious assembler.  Once you have your genome assembled, you need to annotate the thing! That’s right… you need to figure out what genes are present and where they live on the chromosome. We use the program Prokka because it’s a great pipeline already set up and incorporates several different layers of annotations which you can read about here: http://www.vicbioinformatics.com/software.shtml.  Execute it on the command line and you’ll have a bacterial genome done in ~3 minutes! Now that you have an annotated genome, you can run it through the genomic aligner named Mauve http://darlinglab.org/mauve/mauve.html. If you have a closed genome this is easy – if a draft genome you need to align the contigs to a reference first. But it’s not too hard and soon you’ll have beautiful comparative visualizations of your genomes! Super cool! Mummer is a popular tool of doing pairwise comparisons from one genome to the next and comparisons can be by nucleotides or by protein comparisons.  Genome to Genome distance calculation tools have been developed here http://ggdc.dsmz.de/distcalc2.php and will give you a distance matrix with which you can build a phylogenetic tree.  Now comes the interesting part: asking questions of your genomes.  Want to know about the Antibiotic resistance genes in your genomes? Try running them through this database http://arpcard.mcmaster.ca/?q=CARD/tools/RGI. To begin analyzing your genomes for classic virulence factors give this database a try http://www.mgc.ac.cn/cgi-bin/VFs/vfs.cgi?VFID=VF0053#VF0053.  Happy hunting!

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100k Genome Project named in GenomeWeb Article

Outbreak Tracking, Infectious Disease Diagnostics Becoming Key Applications for NGS

Dec 28, 2015

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NEW YORK (GenomeWeb) – In 2011, experts predicted that within five to 10 years, clinical microbiology labs would routinely sequence microbial genomes on a next-generation sequencing instrument, and that it would cost less than €100 ($109) to generate a complete bacterial genome.

Four years later, those predictions are starting to bear fruit.

 “NGS is becoming more and more routine in clinical microbiology labs,” Ted Pak, a graduate student in Andrew Kasarkis’ lab at the Icahn School of Medicine at Mount Sinai, told GenomeWeb. His lab recently sequenced serial isolates of a patient with Stenotrophomonas maltophilia infection in order to determine whether the hospital’s recent uptick in infections was an outbreak or separate transmission events.

NGS offers a level of granularity that other technologies, like PCR or traditional strain typing methods like pulsed-field gel electrophoresis, do not. It is more comprehensive than PCR, able to analyze not just known genomic sites but the entire genome. And it has a much higher resolution than pulsed-field gel electrophoresis, which cannot say whether two hospital patients infected with the same bug acquired their infections separately, or whether their infections are related — a key difference that can impact measures the hospital takes to control the spread of infection.

In the US, there are a number of signs that point to the adoption of the technology within hospitals. The US Centers for Disease Control and Prevention, for example, has set aside $2.3 million in fiscal year 2016 to roll out NGS and bioinformatics technologies for the detection of infectious disease outbreaks in certain states.

The CDC has also been actively involved in a number of research projects. For instance, it collaborated with the Translational Genomics Research Institute to sequence multidrug resistant Klebsiella pneumoniae strains that produce carbapenemase enzyme, which confers resistance to the antibiotic carbapenem. These so-called KPC-producing organisms are fortunately still rare, although Brandi Limbago, deputy director of the CDC’s Division of Healthcare and Quality Promotion’s Clinical and Environmental Microbiology Branch, previously referred to them as “nightmare bacteria.” By focusing efforts to study the mechanism by which they’ve acquired drug resistance now, the hope is to stem the spread of these strains before they become problematic.

The CDC is also involved with a large-scale project to sequence the genomes of 100,000 foodborne pathogens. The University of California, Davis is spearheading the 100K Genomes Project in order to build up a public database of genomes to help identify genes associated with antibiotic resistance, persistence, and pathogenesis, as well as genes that provide information about the strain’s location, serotype, and its associated host.

The National Institutes of Health is also playing a significant role. Its interest in using the technology to sequence pathogens responsible for infections and hospital outbreaks was piqued in 2012, when NIH researchers used NGS to figure out how 18 patients at the NIH Clinical Center became infected with drug-resistant K. pneumoniae. Comparing the genomes from all 18 patients helped determine a likely transmission route in which the first patient transmitted the bacteria to other patients on two different occasions. The sequencing results were even able to determine that transmission occurred from two different parts of her body.

Now, NIH researchers are testing whole-genome and amplicon sequencing-based protocols to diagnose microbial infections. Initially, they plan to test the methods on discarded portions of 250 samples that have received standard testing in the clinical microbiology lab in order to evaluate the utility of NGS for infectious disease diagnostics in the context of a routine hospital clinical microbiology lab, Karen Frank, chief of the microbiology service at the NIH Clinical Center, told GenomeWeb.

“Initial results are very promising,” she said in an email, and the team has now progressed to testing primary specimens. Nonetheless, she said, there are still a number of challenges for integrating NGS into clinical microbiology labs, including the “expertise required for data analysis and interpretation, the absence of commercially available push-button diagnostic systems, and regulatory issues relating to validation, quality control, reporting to the medical record, and genetic privacy.”

Modern microbiology

Across the Atlantic, researchers and public health officials in the UK are taking a systematic approach to moving NGS into clinical microbiology labs. For the last several years, members of the UK Clinical Research Collaboration have been sequencing pathogen genomes to build up genomic databases of various bugs. Recently, a group led by the University of Cambridge published a database of over 1,000 methicillin-resistant Staphylococcus aureusgenomes. The genomes came from 46 laboratories that had submitted clinical isolates to the British Society for Antimicrobial Chemotherapy. The database can now be used as a resource for future surveillance and outbreak investigations of MRSA, the authors wrote.

Aside from MRSA, the research team is building up databases of other pathogens, including vancomycin-resistant StreptococciSharon Peacock, a clinical microbiology professor at the University of Cambridge, previously told GenomeWeb.

Other researchers within the Modernising Medical Microbiology group at the University of Oxford are working on developing an NGS-based test for Mycobacterium tuberculosis. The group published a validation of the test in The Lancet this month, demonstrating that it was accurate, faster than traditional testing methods, and would cost about 7 percent less than current diagnostic tests.

Public Health England is now conducting a feasibility study on 2,000 samples to see if the test can be implemented in routine diagnostics, and the Modernising Medical Microbiology team is working on developing NGS-based tests for Escherichia coli and S. aureus.

Real-time tracking

Last summer, researchers put NGS technology to the ultimate test, deploying it in the midst of an ongoing outbreak of a rapidly spreading pathogen in mostly rural areas of Western Africa without major medical laboratory infrastructure.

In the midst of the Ebola outbreak, researchers with the Liberian Institute for Biomedical Research and the US Army Medical Research of Infectious Diseases (USAMRIID) set up a genome sequencing laboratory to help manage outbreaks of the virus.

Earlier this month, the team published whole-genome sequencing results of 140 Ebola isolates collected during the second wave of the outbreak in Liberia. The data indicated that most Liberian infections came from an isolate from Sierra Leone. The researchers also noted that the results suggested the second wave of the outbreak may have been different from the first wave, which began in March 2014, but fizzled out much more quickly than the second wave that began in May 2014.

Understanding the origin of an outbreak and how it spreads is important for figuring out how to manage and stem transmission, and could help better manage future outbreaks.

Some groups are pushing to implement newer nanopore sequencing technology that could generate whole-genome sequence data faster and in the field. Two groups from Europe and the US took the USB stick-sized MinIon from Oxford Nanopore Technologies to Guinea and Liberia to sequence Ebola isolates. Joshua Quick, a graduate student in Nick Loman’s lab at the University of Birmingham, set up three MinIon devices, a PCR machine, and four laptops at a Guinean hospital with no lab equipment aside from a refrigerator, freezer, and a back-up generator. Quick was able to generate Ebola sequence data from samples shipped in from sites just a few hours north of the hospital, and analyzed over a dozen samples in a couple of weeks.

Challenges

Despite the progress made this year, a number of challenges remain. First, although the MinIon is especially promising for tracking outbreaks in resource-poor areas in real time, the technology is still new and needs further validation before it can be routinely used.

Perhaps a more crucial hurdle will be to ensure that the vast amounts of pathogen sequence data are publicly available, according to Andrew Kasarskis, co-director of the Icahn Institute for Genomics and Multiscale Biology at Mount Sinai Hospital. His team is now sequencing clinical isolates of Clostridium difficile infections in attempt to develop a workflow for tracking infection in the hospital.

One problem with clinical data is that it is proprietary and often contains sensitive patient information, he said. But, if the hospitals and research groups work in isolation, the real insights into how pathogens spread and get transmitted, what types of antibiotic resistance elements are becoming more common, and detecting the start of an outbreak early will not be possible, he said.

For instance, if a patient with carbapenem-resistant Enterobacteriaceae was previously hospitalized in one state, but then a patient a different state becomes sick with the same strain, “you can say you’ve imported the bug from here to there,” he said. “But if those groups  keep their data siloed, you wouldn’t know.”

Aside from data sharing, another challenge will be managing the sheer amount of data that is produced. Hospitals and clinical microbiology labs will “have to get used to the generation, storage, and interpretation of all that data,” Kasarskis said. “It’s not simple.”

These challenges are starting to be overcome though, Kasarskis said, as more and more clinical microbiology labs start testing NGS protocols. He predicted that such testing will be done both in large centralized laboratories as well as in hospitals.

Pak added that although PCR is a promising technology for rapid diagnostics, it “won’t give you as much information as sequencing.”

click here to go to GenomeWeb

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Norovirus

Contributed by Poyin Chen

California is currently experiencing an outbreak of Norovirus. This nasty little virus, also known as the winter vomiting disease, infects via contact with infected surfaces or people and wreaks havoc on the digestive system. Norovirus infections result in gastroenteritis as well as fever and body aches, but the infection is self limiting and usually clears up on its own in a few days.

Despite being resolved in a matter of days, Norovirus infections, as well as all other GI infections, leave a lasting impact on the microscopic communities within the gut. During the initial stages of the infection when the GI flood gates are open, everything is forcefully expelled from the GI tract. This mass exodus includes the established gut microbiome, resulting in a severe decrease in the total numbers of microbes in the GI tract. Reestablishment of the gut microbiome community diversity is a process that will take months and will not return to the preexisting community structure before infection.

While we can go back to the same dietary habits (and life as we know it) within a week of contracting a Norovirus infection, the dramatic and lasting changes to our gut microbiomes means that the metabolic profile of our gut will take time to rebuild [1]. Losing whole genera of bacteria means losing all of the metabolic capabilities these genera provided [2]. Many of these bacteria are able to break down molecules that we otherwise would not be able to digest on our own. Oligosaccharides that cannot be broken down by our digestive enzymes will remain intact throughout its passage through our gut.

Thankfully, the ubiquitous nature of bacteria means that ingesting bacteria on a daily, if not hourly basis is unavoidable. I, myself, like to help diversify my gut microbiome by giving my dog extra kisses and licking chocolate off of my fingers. Hey, it couldn’t hurt, right?*

*Disclaimer: It probably could hurt. That may have been how I got sick in the first place but I love my dog and my chocolate too much to stop.

References

  1. David LA, Materna AC, Friedman J, Campos-Baptista MI, Blackburn MC, Perrotta A, Erdman SE, Alm EJ: Host lifestyle affects human microbiota on daily timescales. Genome Biol 2014, 15:R89.
  2. Tremaroli V, Backhed F: Functional interactions between the gut microbiota and host metabolism. Nature 2012, 489:242-249.

 

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Happy New Year !!

Contributed by Robin Jones

It’s New Year’s Eve! As a child I couldn’t wait to see if I could stay awake long enough to celebrate the turning of the clock from 11:59 pm to 12:00 am. I would always have 1 party popper left over from the 4th of July that I could pull the string on should I make it to midnight. But what usually occurred was that I would pull it the following morning when I awoke on the couch. As a teen, I never had to try to stay awake, for midnight was a part of my normal waking hours. Now, as an adult, I find the struggle to stay awake until midnight to be as challenging as when I was a child. The only difference now is that I go to bed knowing that the New Year will happen regardless if I am awake to herald it in (and I can never remember to save a party popper).

There is something wonderful about the New Year though. Many of us find a new drive within ourselves to be kinder, to be more gentle with others. Maybe we get the urge to finally plan those vacations we get too busy to take. We look at spa memberships and run to town to buy those workout clothes that began hitting the shelves on December 26th.   Maybe we decide to buckle down and take financial strides to pay off a mortgage, a car, or a loan that has hung over our heads. Whatever it is, it seems we make some resolution or another. Maybe the thought that we can make change within ourselves or our environment gives us hope?  I am reminded of how vivid Y2K is in my memory.  It seems as though it was just a couple of years ago but tonight it will be 16 years since that moment. Life is moving at warp speed! I personally am working to slow my world down, to enjoy more quiet moments and take life from a rabbits pace to somewhere between a turtle and a lazy house cat.

I have always been intrigued at how people view, celebrate, and welcome in the New Year. I came across an interesting story in Business Insider this morning about the strange and unusual ways people celebrate the New Year ( http://www.businessinsider.com/new-years-rituals-around-the-world-2014-12 ) Whether it is eating beans on New Year’s Eve – to bring luck, or burning effigies of your enemies at midnight, if it’s eating up to 12 meals that night, or hiding mistletoe under your pillow to attract a husband. Which ever way that  you and your culture celebrate, I wish you the happiest of New Year’s. I hope in 2016 you will be healthy and happy, prosperous and blessed. If you are a resolution maker, I wish you the best to stick them out and look back in a year’s time and see that you have reaped the fruits of those efforts. If you need encouragement seek me out, hopefully I will be the one moving really slow in a fast paced world!

Happy New Year!

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Regulation with WGS – The Wild West has Returned

Contributed by Bart Weimer Ph.D.

WGS is becoming the method of choice for food safety outbreak and surveillance. The US CDC, US FDA, and the EU CDC (ECDC) have all announced that they will transition from pervious typing methods and only use WGS in the coming year.  The announcement of these agencies will have a dramatic impact on the food industry and their ability to monitor the food chain with well-accepted methods http://www.foodqualitynews.com/Lab-Technology/WGS-cost-and-time-comparable-to-current-typing-methods).

It is clear that approved methods are missing outbreaks and leave doubt as to the identity of isolated pathogens. This is also boiling over into the clinical detection realm. Use of NGS is also moving full steam ahead into metagenomics; however, use of classical bioinformatic tools are not providing much success to accurately and robustly detect pathogens that may result in regulatory or actionable information from metagenomes.

This transition now has enough steam to carry WGS and metagenomics into the coming years for food chain management. The only questions are how fast, how much information is needed to manage/detect/ID pathogens, and how will industry implement a tool that is not in use today, except on a very small scale?

Recently Deng et al. (2014; PMID: 25147968) demonstrated that WGS delineated identical ID’s based on PFGE. This enabled a post hoc epidemiological investigation that linked seawater isolates to new linages responsible for human disease. This finding coupled with the mountain of evidence that WGS provides will be undeniable for those who contribute pathogens into the human environment – whether that is food, soil, or the clinic. The time has arrived that WGS is democratized and all need to have the capability to conduct this work in their own grasp. WGS moved from the bench in 2012 to government implementation in 2015 – that is an incredibly short transition with the speed increasing. Use of real time sequencing, represented by Oxford Nanopore (but others are coming), this speed of big data in microbiology is upon the food industry.

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