Tag Archives: detection

Can a smartphone stop a norovirus outbreak?

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Rebecca Trager of Chemistry World reports U.S. researchers have created a handheld detection system that is sensitive enough to catch just a few particles of norovirus.

University of Arizona biomedical engineer Jeong-Yeol Yoon and his team have created a highly sensitive portable detection system capable of spotting norovirus at levels that can make people sick. The work was presented the American Chemical Society’s national meeting in San Diego, California on 27 August.

As few as 10 norovirus particles can cause vomiting and diarrhoea in humans and the virus is extremely contagious so early detection is vital to prevent outbreaks. However, the virus does not grow in laboratory cultures and current detection methods rely on specialised and time-consuming PCR (polymerase chain reaction) techniques.

Yoon’s research team previously developed a smartphone-based device that measured light-scattering from norovirus-bound polystyrene beads in a paper microfluidic chip. It has now improved the device’s detection limit by changing to a fluorescence-based method.

‘I looked at Amazon.com and saw that they sell a lot of these smartphone attachments – smartphone microscope attachments – that turn your phone turns into a microscope, and by adding a couple of other components, I could convert the smartphone-based microscope into a fluorescence microscope,’ Yoon explains.

The setup uses a microscope accessory with a separate light source and two optical filters. He and colleagues also designed a 3D printed case to house the components.

To test a sample, it is first added to the paper microfluidic chip, followed by a suspension of fluorescent beads labelled with norovirus antibodies. After three to five minutes, the antibodies bind to any norovirus particles in the sample, creating aggregates of the fluorescent beads that spread out along the channels of the chip. The resulting increase in fluorescence intensity around each norovirus particle can be detected by taking a picture of the chip with the smartphone’s camera.

An app that the team has also developed then analyses the picture to calculate the sample’s norovirus concentration from the pixel count in the image. So far, the lowest detection limit corresponded to about 5 or 6 norovirus particles per sample, Yoon says. He estimates that the material costs of this system, aside from the cell phone and app development costs, are about $200.

Cat’s in the cream, NZ

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About 15 years ago, some Aussie researchers, using motion-activated video cameras, found that however well-behaved cats were during the day, as soon as everyone went to sleep, it was party time, and the cats were everywhere.

In a story about how needles get into food and diagnosed – there’s been lotsa cases in Australia and NZ of late – the fun part is how New Zealand ERS scientists use their food forensics lab to track things down and in one case it was, again, cats (and happy 26th to this kid, who always loved — and sometimes tortured — her cats).

One complaint involving hair came from a milk company, which was continually finding ginger hairs in its on-line filter.

“We identified it as coming from a cat, so you get this image of the cat waiting until night time and jumping into the vat,” said scientist Darren Saunders.

“Literally, the cat that got the cream.”

Putting food-safety detection in the hands of consumers

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I always thought the MIT Media Lab would be the coolest place to work.

I have no idea whether this gadget will work, but it has coolnest factor.

MIT Media Lab researchers have developed a wireless system that leverages the cheap RFID tags already on hundreds of billions of products to sense potential food contamination—with no hardware modifications needed. With the simple, scalable system, the researchers hope to bring food-safety detection to the general public.

Food safety incidents have made headlines around the globe for causing illness and death nearly every year for the past two decades. Back in 2008, for instance, 50,000 babies in China were hospitalized after eating infant formula adulterated with melamine, an organic compound used to make plastics, which is toxic in high concentrations. And this April, more than 100 people in Indonesia died from drinking alcohol contaminated, in part, with methanol, a toxic alcohol commonly used to dilute liquor for sale in black markets around the world.

The researchers’ system, called RFIQ, includes a reader that senses minute changes in wireless signals emitted from RFID tags when the signals interact with food. For this study they focused on baby formula and alcohol, but in the future, consumers might have their own reader and software to conduct food-safety sensing before buying virtually any product. Systems could also be implemented in supermarket back rooms or in smart fridges to continuously ping an RFID tag to automatically detect food spoilage, the researchers say.

The technology hinges on the fact that certain changes in the signals emitted from an RFID tag correspond to levels of certain contaminants within that product. A machine-learning model “learns” those correlations and, given a new material, can predict if the material is pure or tainted, and at what concentration. In experiments, the system detected baby formula laced with melamine with 96 percent accuracy, and alcohol diluted with methanol with 97 percent accuracy.

“In recent years, there have been so many hazards related to food and drinks we could have avoided if we all had tools to sense food quality and safety ourselves,” says Fadel Adib, an assistant professor at the Media Lab who is co-author on a paper describing the system, which is being presented at the ACM Workshop on Hot Topics in Networks. “We want to democratize food quality and safety, and bring it to the hands of everyone.”

The paper’s co-authors include: postdoc and first author Unsoo Ha, postdoc Yunfei Ma, visiting researcher Zexuan Zhong, and electrical engineering and computer science graduate student Tzu-Ming Hsu.

Other sensors have also been developed for detecting chemicals or spoilage in food. But those are highly specialized systems, where the sensor is coated with chemicals and trained to detect specific contaminations. The Media Lab researchers instead aim for broader sensing. “We’ve moved this detection purely to the computation side, where you’re going to use the same very cheap sensor for products as varied as alcohol and baby formula,” Adib says.

RFID tags are stickers with tiny, ultra-high-frequency antennas. They come on food products and other items, and each costs around three to five cents. Traditionally, a wireless device called a reader pings the tag, which powers up and emits a unique signal containing information about the product it’s stuck to.

The researchers’ system leverages the fact that, when RFID tags power up, the small electromagnetic waves they emit travel into and are distorted by the molecules and ions of the contents in the container. This process is known as “weak coupling.” Essentially, if the material’s property changes, so do the signal properties.

A simple example of feature distortion is with a container of air versus water. If a container is empty, the RFID will always respond at around 950 megahertz. If it’s filled with water, the water absorbs some of the frequency, and its main response is around only 720 megahertz. Feature distortions get far more fine-grained with different materials and different contaminants. “That kind of information can be used to classify materials … [and] show different characteristics between impure and pure materials,” Ha says.

In the researchers’ system, a reader emits a wireless signal that powers the RFID tag on a food container. Electromagnetic waves penetrate the material inside the container and return to the reader with distorted amplitude (strength of signal) and phase (angle).

When the reader extracts the signal features, it sends those data to a machine-learning model on a separate computer. In training, the researchers tell the model which feature changes correspond to pure or impure materials. For this study, they used pure alcohol and alcohol tainted with 25, 50, 75, and 100 percent methanol; baby formula was adulterated with a varied percentage of melamine, from 0 to 30 percent.

“Then, the model will automatically learn which frequencies are most impacted by this type of impurity at this level of percentage,” Adib says. “Once we get a new sample, say, 20 percent methanol, the model extracts [the features] and weights them, and tells you, ‘I think with high accuracy that this is alcohol with 20 percent methanol.’”

The system’s concept derives from a technique called radio frequency spectroscopy, which excites a material with electromagnetic waves over a wide frequency and measures the various interactions to determine the material’s makeup.

But there was one major challenge in adapting this technique for the system: RFID tags only power up at a very tight bandwidth wavering around 950 megahertz. Extracting signals in that limited bandwidth wouldn’t net any useful information.

The researchers built on a sensing technique they developed earlier, called two-frequency excitation, which sends two frequencies—one for activation, and one for sensing—to measure hundreds more frequencies. The reader sends a signal at around 950 megahertz to power the RFID tag. When it activates, the reader sends another frequency that sweeps a range of frequencies from around 400 to 800 megahertz. It detects the feature changes across all these frequencies and feeds them to the reader.

“Given this response, it’s almost as if we have transformed cheap RFIDs into tiny radio frequency spectroscopes,” Adib says.

Because the shape of the container and other environmental aspects can affect the signal, the researchers are currently working on ensuring the system can account for those variables. They are also seeking to expand the system’s capabilities to detect many different contaminants in many different materials.

“We want to generalize to any environment,” Adib says. “That requires us to be very robust, because you want to learn to extract the right signals and to eliminate the impact of the environment from what’s inside the material.”

Does chlorine make pathogens harder to detect in fresh produce?

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The microbiological safety of fresh produce is monitored almost exclusively by culture-based detection methods. However, bacterial foodborne pathogens are known to enter a viable-but-nonculturable (VBNC) state in response to environmental stresses such as chlorine, which is commonly used for fresh produce decontamination.

Here, complete VBNC induction of green fluorescent protein-tagged Listeria monocytogenes and Salmonella enterica serovar Thompson was achieved by exposure to 12 and 3 ppm chlorine, respectively. The pathogens were subjected to chlorine washing following incubation on spinach leaves. Culture data revealed that total viable L. monocytogenes and Salmonella Thompson populations became VBNC by 50 and 100 ppm chlorine, respectively, while enumeration by direct viable counting found that chlorine caused a <1-log reduction in viability. The pathogenicity of chlorine-induced VBNC L. monocytogenes and Salmonella Thompson was assessed by using Caenorhabditis elegans. Ingestion of VBNC pathogens by C. elegans resulted in a significant life span reduction (P = 0.0064 and P < 0.0001), and no significant difference between the life span reductions caused by the VBNC and culturable L. monocytogenes treatments was observed. L. monocytogenes was visualized beyond the nematode intestinal lumen, indicating resuscitation and cell invasion. These data emphasize the risk that VBNC food-borne pathogens could pose to public health should they continue to go undetected.

IMPORTANCE Many bacteria are known to enter a viable-but-nonculturable (VBNC) state in response to environmental stresses. VBNC cells cannot be detected by standard laboratory culture techniques, presenting a problem for the food industry, which uses these techniques to detect pathogen contaminants. This study found that chlorine, a sanitizer commonly used for fresh produce, induces a VBNC state in the foodborne pathogens Listeria monocytogenes and Salmonella enterica. It was also found that chlorine is ineffective at killing total populations of the pathogens. A life span reduction was observed in Caenorhabditis elegans that ingested these VBNC pathogens, with VBNC L. monocytogenes as infectious as its culturable counterpart. These data show that VBNC foodborne pathogens can both be generated and avoid detection by industrial practices while potentially retaining the ability to cause disease.

Viable-but-nonculturable listeria monocytogenes and Salmonella enterica serovar Thompson induced by chlorine stress remain infectious

17 April 2018

American Society for Microbiology, vol. 9 no. 2

Callum J. Highmorea, Jennifer C. Warnera*,  Steve D. Rothwellb, Sandra A. Wilksa, C. William Keevila

doi: 10.1128/mBio.00540-18

http://mbio.asm.org/content/9/2/e00540-18

Seek and ye shall find: Sapovirus sickens 650 in Sweden, 2016

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A foodborne outbreak of gastroenteritis with more than 650 suspected cases occurred in April 2016 in Sollentuna, Sweden. It originated in a school kitchen serving a total of 2,700 meals daily.

Initial microbiological testing (for Campylobacter, Salmonella, Shigella, Yersinia, Giardia, Cryptosporidium, Entamoeba histolytica, adeno-, astro-, noro-, rota- and sapovirus) of stool samples from 15 symptomatic cases was negative, despite a clinical presentation suggestive of calicivirus.

Analyses of the findings from both the Sollentuna municipality environmental team and a web-based questionnaire suggested that the source of the outbreak was the salad buffet served on 20 April, although no specific food item could be identified.

Subsequent electron microscopic examination of stool samples followed by whole genome sequencing revealed a variant of sapovirus genogroup V. The virus was not detected using standard PCR screening. This paper describes the epidemiological outbreak investigation and findings leading to the discovery.

Investigation of a foodborne outbreak of gastroenteritis in a school canteen revealed a variant of sapovirus  genogroup V not detected by standard PCR, sollentuna, Sweden, 2016

Eurosurveillance, vol 22, issue 22, 01 June 2017, M Hergens, J Nederby Öhd, E Alm , HH Askling, S Helgesson, M Insulander, N Lagerqvist, B Svenungsson, M Tihane, T Tolfvenstam, P Follin,

http://dx.doi.org/10.2807/1560-7917.ES.2017.22.22.30543

http://www.eurosurveillance.org/ViewArticle.aspx?ArticleId=22808

 

Expediting detection of pathogens in food supply

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Angelo Gaitas, a research assistant professor at Florida International University’s Electrical and Computer Engineering Department, along with Gwangseong Kim, a research scientist, are commercializing a device that reduces the screening process of foods to just a few hours at the same cost as current devices.

FIU says that if you have ever suffered from food poisoning, you will appreciate why it is so important to inspect food before it reaches the consumer. Food producers have to check for bacteria and signs of contamination before they are able to ship out any perishable food. Some common bacteria that can lead to foodborne illnesses include E.coli, salmonella and listeria. In fact, according to the Centers for Disease Control, each year, one in six Americans gets sick by consuming contaminated foods or beverages, that is forty-eight million people, out of whom 128,000 are hospitalized.

Typically, the inspection process, which involves putting samples in a solution and placing it in an incubator to see if bacteria grows, takes anywhere from 18 hours to several days. The reason is that it takes time for bacteria to grow at detectable levels. Current detection techniques are limited – you may need about 1,000 to a million bacteria present, depending on the technique, in a small volume before bacteria can be successfully detected. To reach that level, it takes time.

With this new device, food producers are able to run the whole solution through a smaller container inside the incubator oven. Antibodies in the device capture the target bacteria. This procedure allows bacteria to be concentrated in a smaller volume enabling same day detection.

“We are focused on helping food producers reduce storage cost and get fresher food to consumers,” Gaitas says. “We are addressing a major and well documented need in a very large market. There are about 1.2 billion food tests conducted worldwide and about 220 million tests in the United States.”

By shortening the detection time by one day, the team believes that the device can save the food industry billions. For example, meat producers, as a collective industry, could save up to $3 billion in storage costs by shortening the detection to one day. This device can also be used to expedite the detection of bloodborne illnesses such as sepsis and viral infections; however, currently the commercial focus is on food due to the lower barriers to entry.

Gaitas formed a company, Kytaro Inc – an FIU startup – which spent the last few years creating and testing the device and publishing the results in scientific journals. Besides Gaitas and Kim, the company has been employing FIU undergraduates.

FIU notes that this April, with the support of Henry Artigues of the Office of Research and Economic Development and Shekhar Bhansali, chair of the Electrical and Computer Engineering Department, Kytaro was recognized as one of “40 Best University Startups 2017” at the University Startups Conference and Demo Day in Washington, D.C. About 200 startups applied to the national competition.

Men who stare at goats – and use spinach as bomb detectors

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A team of scientists from the Massachusetts Institute of Technology (MIT) embedded carbon nanotubes in spinach leaves which emitted a signal when they detected nitroaromatics — a chemical compound used in landmines and other explosives.

spinach-bomb-detectionThrough the nanotubes, which are one ten-thousandth the diameter of a human hair, the plant can detect the chemicals through the air and groundwater.

Researchers also applied a solution of nanoparticles to the underside of the leaves and placed sensors into a leaf layer (known as the mesophyll) where most photosynthesis takes place.

To read the signals the plants give off, researchers shine a laser on the leaves which prompts the carbon nanotubes to emit a near-infrared fluorescent light.

That light is picked up by using an infrared camera connected to a Raspberry Pi, a credit-card-sized computer, similar to the computer used in a smartphone.

The Raspberry Pi then sends an email to the phone, alerting the owner to the presence and size of an explosive.

By engineering these plants to act as chemical sensors, scientists can perform monitoring tasks in public spaces and identify potential terrorism threats at mass-attended events, said Michael Strano, professor of chemical engineering at MIT.

“They could also be used on the periphery of a chemical plant and even fracking sites.”

Plants are ideal for this purpose as they have extensive root networks to monitor groundwater, are self-repairing, and are naturally adaptive to where they exist.

“If you think of taking your iPhone or a piece of electronics outside and having it adapt to the temperature changes, it’s actually an engineering challenge,” said Professor Strano.

men-who-stare-at-goats“We look at the plant for a great starting point for technology.

“It’s amazing it hasn’t been explored for this purpose.”

The researchers can pick up the warning signal from about one metre away, but are working to increase that distance.

As well as spinach, researchers used rocket and watercress as chemical sensors, choosing to use plants that were commonly available.

“We wanted to show that these techniques work with plants found in the wild or a nursery, rather than using genetically-engineered plants,” Professor Strano said.

By using plants that already exist in the wild, the need to create new organisms which may have problems surviving is eliminated.

A.I. might prevent the next E. coli outbreak

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Tonya Riley of Inverse reports that artificial intelligence is already well on its way to being the future of food service, but what if it could also do things like prevent foodborne illnesses, such as E. coli?

cow-poop2Researchers at University of Edinburgh say they’ve designed  software to do just that. The A.I. compares the genetic signatures of E. coli samples that have caused infection in humans to bacterial samples from humans and animals. The technology will allow researchers to identify deadly strains of E. coli before the threat becomes an outbreak.

“Our findings indicate that the most dangerous E. coli O157 strains may in fact be very rare in the cattle reservoir, which is reassuring,” University of Edinburgh Professor David Gally said in a press release. “The study highlights the potential of machine learning approaches for identifying these strains early.”

E.coli strains can normally live in human and animal guts without complications, but strains like E.coli O157 can cause infection. The strain is much more deadly in humans than in cattle, where the bacteria serves to collect toxins that need disposed. The team predicts that the O157 strain is present in about 10 percent of cattle.

Advancements in cellular engineering will make it easier for researchers to detect bacteria that is harmful to humans, but let’s not forget E. coli isn’t all bad. Air Force researchers have shown that the bacteria may be key to controlling robots through biological means.

Researchers plan on using the software on test samples of other animal-borne toxins, such as salmonella in order to identify strains with the potential to cause human disease.

Food fraud detection: Chinese team develops new method for rapid authentication of edible oils and screening of gutter oils

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The Food Safety and Technology Research Centre under the Department of Applied Biology and Chemical Technology of The Hong Kong Polytechnic University (PolyU) has developed a new method for rapid authentication of edible oils and screening of gutter oils. Authentication of edible oils has been a long-term issue in food safety, and becomes particularly important with the emergence and widespread use of gutter oils in recent years. However, the conventional analytical approach for edible oils is not only labor intensive and time consuming, but also fails to provide a versatile solution for screening of gutter oils. By setting up a simple analytical protocol and a spectral library of edible oils, the new approach is able to determine the authenticity of a labeled edible oil sample and hence screened gutter oils within five minutes.

1-polyudevelopThe conventional approach for edible oil authentication involves labor-intensive and time-consuming sample pretreatment and the subsequent chromatographic separation to separate complex sample mixture before mass spectrometric detection, a commonly used technology for identification and quantitation of chemical compounds. The whole process takes a few hours to analyze one sample. On the other hand, identification of gutter oils mainly involves detection of certain food residue markers or toxic and carcinogenic chemicals in the sample. However, due to the vast diversity of gutter oils, and the fact that target compounds could be removed by processing, a universal strategy to screen gutter oils is not available at present.

PolyU researchers have developed a simplified method for direct analysis of edible oils using matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). In the new MALDI-MS approach, only simple sample preparation, automatic data acquisition and simple data processing are involved. High quality and highly reproducible MALDI-MS spectra results can be obtained using this method, and a preliminary spectral database of labeled edible oils available in the market has been set up. Since different types of edible oils have different MALDI-MS spectral patterns, the authenticity of an edible oil sample can then be determined within five minutes by comparing its MALDI-MS spectrum with those of its labeled oil in the established database. Since this method is capable of authenticating edible oils, it also enables a rapid screening of gutter oils, given fraudulent mislabeling is a common feature of gutter oils.

The related paper has been recently published on Analytica Chimica Acta, a leading journal in Analytical Chemistry. The research team will establish a more complete MALDI spectral library of various edible oils in the coming two years, and improve the library searching technique. In addition, more testing of edible oil samples with different MALDI-MS equipment will be carried out to further validate the new approach.

The Eyes have it? Iowa researchers study retinal scans as early detection method for mad cow disease

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New research from Iowa State University shows that a fatal neurological disease in cows can be detected earlier by examining the animal’s retinas.

mad.cows.mother's.milkBovine spongiform encephalopathy (BSE), known more commonly as mad cow disease, is an untreatable neurodegenerative disorder caused by misfolded brain proteins known as prions. Classic BSE incubates for years before producers or veterinarians notice symptoms, usually discovered when the animal can no longer stand on its own.

But Heather Greenlee, an associate professor of biomedical sciences in Iowa State’s College of Veterinary Medicine, said studying the retinas of cattle can identify infected animals up to 11 months before they show signs of illness.

“The retina is part of the central nervous system,” Greenlee said. “Essentially, it’s the part of the brain closest to the outside world, and we know the retina is changed in animals that have prion diseases.”

In collaboration with Justin Greenlee’s group at the U.S. Department of Agriculture’s National Animal Disease Center, she recently published findings in the peer-reviewed academic journal PLOS ONE. She began studying how the retina relates to prion diseases in 2006, and the experiments that led to her most recent publication began in 2010.

The experiments utilize electroretinography and optical coherence tomography, noninvasive technologies commonly used to assess the retina. Greenlee said cows infected with BSE showed marked changes in retinal function and thickness.

The results have implications for food safety, and Greenlee said the screening methods used in her research could be adopted for animals tagged for import or export as a means of identifying BSE sooner than conventional methods.

Greenlee said she’s also looking at how similar diseases in other species affect the retina. For instance, she’s conducting experiments to find out if retinal tissue may be a valid means of surveillance for chronic wasting disease in deer.

She said she isn’t ready to publish her results, but the data gathered so far looks promising.

The research also may contribute to faster diagnosis of Alzheimer’s disease and Parkinson’s disease in humans, both of which are caused by proteins folding incorrectly.

“Our goal is to develop our understanding of the retina to monitor disease progression and to move diagnoses up earlier,” Greenlee said. “We think this research has the potential to improve diagnosis for a range of species and a range of diseases.”