New tools could catch disease outbreaks earlier - or predict them
Every year, the villages which lie in the so-called ‘Nipah belt’— which stretches along the western border between Bangladesh and India, brace themselves for the latest outbreak. For since 1998, when Nipah virus—a form of hemorrhagic fever most common in Bangladesh—first spilled over into humans, it has been a grim annual visitor to the people of this region.
With a 70 percent fatality rate, no vaccine, and no known treatments, Nipah virus has been dubbed in the Western world as ‘the worst disease no one has ever heard of.’ Currently, outbreaks tend to be relatively contained because it is not very transmissible. The virus circulates throughout Asia in fruit eating bats, and only tends to be passed on to people who consume contaminated date palm sap, a sweet drink which is harvested across Bangladesh.
But as SARS-CoV-2 has shown the world, this can quickly change.
“Nipah virus is among what virologists call ‘the Big 10,’ along with things like Lassa fever and Crimean Congo hemorrhagic fever,” says Noam Ross, a disease ecologist at New York-based non-profit EcoHealth Alliance. “These are pretty dangerous viruses from a lethality perspective, which don’t currently have the capacity to spread into broader human populations. But that can evolve, and you could very well see a variant emerge that has human-human transmission capability.”
That’s not an overstatement. Surveys suggest that mammals harbour about 40,000 viruses, with roughly a quarter capable of infecting humans. The vast majority never get a chance to do so because we don’t encounter them, but climate change can alter that. Recent studies have found that as animals relocate to new habitats due to shifting environmental conditions, the coming decades will bring around 300,000 first encounters between species which normally don’t interact, especially in tropical Africa and southeast Asia. All these interactions will make it far more likely for hitherto unknown viruses to cross paths with humans.
That’s why for the last 16 years, EcoHealth Alliance has been conducting ongoing viral surveillance projects across Bangladesh. The goal is to understand why Nipah is so much more prevalent in the western part of the country, compared to the east, and keep a watchful eye out for new Nipah strains as well as other dangerous pathogens like Ebola.
"There are a lot of different infectious agents that are sensitive to climate change that don't have these sorts of software tools being developed for them," says Cat Lippi, medical geography researcher at the University of Florida.
Until very recently this kind of work has been hampered by the limitations of viral surveillance technology. The PREDICT project, a $200 million initiative funded by the United States Agency for International Development, which conducted surveillance across the Amazon Basin, Congo Basin and extensive parts of South and Southeast Asia, relied upon so-called nucleic acid assays which enabled scientists to search for the genetic material of viruses in animal samples.
However, the project came under criticism for being highly inefficient. “That approach requires a big sampling effort, because of the rarity of individual infections,” says Ross. “Any particular animal may be infected for a couple of weeks, maybe once or twice in its lifetime. So if you sample thousands and thousands of animals, you'll eventually get one that has an Ebola virus infection right now.”
Ross explains that there is now far more interest in serological sampling—the scientific term for the process of drawing blood for antibody testing. By searching for the presence of antibodies in the blood of humans and animals, scientists have a greater chance of detecting viruses which started circulating recently.
Despite the controversy surrounding EcoHealth Alliance’s involvement in so-called gain of function research—experiments that study whether viruses might mutate into deadlier strains—the organization’s separate efforts to stay one step ahead of pathogen evolution are key to stopping the next pandemic.
“Having really cheap and fast surveillance is really important,” says Ross. “Particularly in a place where there's persistent, low level, moderate infections that potentially have the ability to develop into more epidemic or pandemic situations. It means there’s a pathway that something more dangerous can come through."
Scientists are searching for the presence of antibodies in the blood of humans and animals in hopes to detect viruses that recently started circulating.
EcoHealth Alliance
In Bangladesh, EcoHealth Alliance is attempting to do this using a newer serological technology known as a multiplex Luminex assay, which tests samples against a panel of known antibodies against many different viruses. It collects what Ross describes as a ‘footprint of information,’ which allows scientists to tell whether the sample contains the presence of a known pathogen or something completely different and needs to be investigated further.
By using this technology to sample human and animal populations across the country, they hope to gain an idea of whether there are any novel Nipah virus variants or strains from the same family, as well as other deadly viral families like Ebola.
This is just one of several novel tools being used for viral discovery in surveillance projects around the globe. Multiple research groups are taking PREDICT’s approach of looking for novel viruses in animals in various hotspots. They collect environmental DNA—mucus, faeces or shed skin left behind in soil, sediment or water—which can then be genetically sequenced.
Five years ago, this would have been a painstaking work requiring bringing collected samples back to labs. Today, thanks to the vast amounts of money spent on new technologies during COVID-19, researchers now have portable sequencing tools they can take out into the field.
Christopher Jerde, a researcher at the UC Santa Barbara Marine Science Institute, points to the Oxford Nanopore MinION sequencer as one example. “I tried one of the early versions of it four years ago, and it was miserable,” he says. “But they’ve really improved, and what we’re going to be able to do in the next five to ten years will be amazing. Instead of having to carefully transport samples back to the lab, we're going to have cigar box-shaped sequencers that we take into the field, plug into a laptop, and do the whole sequencing of an organism.”
In the past, viral surveillance has had to be very targeted and focused on known families of viruses, potentially missing new, previously unknown zoonotic pathogens. Jerde says that the rise of portable sequencers will lead to what he describes as “true surveillance.”
“Before, this was just too complex,” he says. “It had to be very focused, for example, looking for SARS-type viruses. Now we’re able to say, ‘Tell us all the viruses that are here?’ And this will give us true surveillance – we’ll be able to see the diversity of all the pathogens which are in these spots and have an understanding of which ones are coming into the population and causing damage.”
But being able to discover more viruses also comes with certain challenges. Some scientists fear that the speed of viral discovery will soon outpace the human capacity to analyze them all and assess the threat that they pose to us.
“I think we're already there,” says Jason Ladner, assistant professor at Northern Arizona University’s Pathogen and Microbiome Institute. “If you look at all the papers on the expanding RNA virus sphere, there are all of these deposited partial or complete viral sequences in groups that we just don't know anything really about yet.” Bats, for example, carry a myriad of viruses, whose ability to infect human cells we understand very poorly.
Cultivating these viruses under laboratory conditions and testing them on organoids— miniature, simplified versions of organs created from stem cells—can help with these assessments, but it is a slow and painstaking work. One hope is that in the future, machine learning could help automate this process. The new SpillOver Viral Risk Ranking platform aims to assess the risk level of a given virus based on 31 different metrics, while other computer models have tried to do the same based on the similarity of a virus’s genomic sequence to known zoonotic threats.
However, Ladner says that these types of comparisons are still overly simplistic. For one thing, scientists are still only aware of a few hundred zoonotic viruses, which is a very limited data sample for accurately assessing a novel pathogen. Instead, he says that there is a need for virologists to develop models which can determine viral compatibility with human cells, based on genomic data.
“One thing which is really useful, but can be challenging to do, is understand the cell surface receptors that a given virus might use,” he says. “Understanding whether a virus is likely to be able to use proteins on the surface of human cells to gain entry can be very informative.”
As the Earth’s climate heats up, scientists also need to better model the so-called vector borne diseases such as dengue, Zika, chikungunya and yellow fever. Transmitted by the Aedes mosquito residing in humid climates, these blights currently disproportionally affect people in low-income nations. But predictions suggest that as the planet warms and the pests find new homes, an estimated one billion people who currently don’t encounter them might be threatened by their bites by 2080. “When it comes to mosquito-borne diseases we have to worry about shifts in suitable habitat,” says Cat Lippi, a medical geography researcher at the University of Florida. “As climate patterns change on these big scales, we expect to see shifts in where people will be at risk for contracting these diseases.”
Public health practitioners and government decision-makers need tools to make climate-informed decisions about the evolving threat of different infectious diseases. Some projects are already underway. An ongoing collaboration between the Catalan Institution for Research and Advanced Studies and researchers in Brazil and Peru is utilizing drones and weather stations to collect data on how mosquitoes change their breeding patterns in response to climate shifts. This information will then be fed into computer algorithms to predict the impact of mosquito-borne illnesses on different regions.
The team at the Catalan Institution for Research and Advanced Studies is using drones and weather stations to collect data on how mosquito breeding patterns change due to climate shifts.
Gabriel Carrasco
Lippi says that similar models are urgently needed to predict how changing climate patterns affect respiratory, foodborne, waterborne and soilborne illnesses. The UK-based Wellcome Trust has allocated significant assets to fund such projects, which should allow scientists to monitor the impact of climate on a much broader range of infections. “There are a lot of different infectious agents that are sensitive to climate change that don't have these sorts of software tools being developed for them,” she says.
COVID-19’s havoc boosted funding for infectious disease research, but as its threats begin to fade from policymakers’ focus, the money may dry up. Meanwhile, scientists warn that another major infectious disease outbreak is inevitable, potentially within the next decade, so combing the planet for pathogens is vital. “Surveillance is ultimately a really boring thing that a lot of people don't want to put money into, until we have a wide scale pandemic,” Jerde says, but that vigilance is key to thwarting the next deadly horror. “It takes a lot of patience and perseverance to keep looking.”
This article originally appeared in One Health/One Planet, a single-issue magazine that explores how climate change and other environmental shifts are increasing vulnerabilities to infectious diseases by land and by sea. The magazine probes how scientists are making progress with leaders in other fields toward solutions that embrace diverse perspectives and the interconnectedness of all lifeforms and the planet.
In different countries' national dietary guidelines, red meats (beef, pork, and lamb) are often confined to a very small corner. Swedish officials, for example, advise the population to "eat less red and processed meat". Experts in Greece recommend consuming no more than four servings of red meat — not per week, but per month.
"Humans 100% rely on the microbes to digest this food."
Yet somehow, the matter is far from settled. Quibbles over the scientific evidence emerge on a regular basis — as in a recent BMJ article titled, "No need to cut red meat, say new guidelines." News headlines lately have declared that limiting red meat may be "bad advice," while carnivore diet enthusiasts boast about the weight loss and good health they've achieved on an all-meat diet. The wildly successful plant-based burgers? To them, a gimmick. The burger wars are on.
Nutrition science would seem the best place to look for answers on the health effects of specific foods. And on one hand, the science is rather clear: in large populations, people who eat more red meat tend to have more health problems, including cardiovascular disease, colorectal cancer, and other conditions. But this sort of correlational evidence fails to settle the matter once and for all; many who look closely at these studies cite methodological shortcomings and a low certainty of evidence.
Some scientists, meanwhile, are trying to cut through the noise by increasing their focus on the mechanisms: exactly how red meat is digested and the step-by-step of how this affects human health. And curiously, as these lines of evidence emerge, several of them center around gut microbes as active participants in red meat's ultimate effects on human health.
Dr. Stanley Hazen, researcher and medical director of preventive cardiology at Cleveland Clinic, was one of the first to zero in on gut microorganisms as possible contributors to the health effects of red meat. In looking for chemical compounds in the blood that could predict the future development of cardiovascular disease, his lab identified a molecule called trimethylamine-N-oxide (TMAO). Little by little, he and his colleagues began to gather both human and animal evidence that TMAO played a role in causing heart disease.
Naturally, they tried to figure out where the TMAO came from. Hazen says, "We found that animal products, and especially red meat, were a dietary source that, [along with] gut microbes, would generate this product that leads to heart disease development." They observed that the gut microbes were essential for making TMAO out of dietary compounds (like red meat) that contained its precursor, trimethylamine (TMA).
So in linking red meat to cardiovascular disease through TMAO, the surprising conclusion, says Hazen, was that, "Without a doubt, [the microbes] are the most important aspect of the whole pathway."
"I think it's just a matter of time [before] we will have therapeutic interventions that actually target our gut microbes, just like the way we take drugs that lower cholesterol levels."
Other researchers have taken an interest in different red-meat-associated health problems, like colorectal cancer and the inflammation that accompanies it. This was the mechanistic link tackled by the lab of professor Karsten Zengler of the UC San Diego Departments of Pediatrics and Bioengineering—and it also led straight back to the gut microbes.
Zengler and colleagues recently published a paper in Nature Microbiology that focused on the effects of a red meat carbohydrate (or sugar) called Neu5Gc.
He explains, "If you eat animal proteins in your diet… the bound sugars in your diet are cleaved off in your gut and they get recycled. Your own cells will not recognize between the foreign sugars and your own sugars, because they look almost identical." The unsuspecting human cells then take up these foreign sugars — spurring antibody production and creating inflammation.
Zengler showed, however, that gut bacteria use enzymes to cleave off the sugar during digestion, stopping the inflammation and rendering the sugar harmless. "There's no enzyme in the human body that can cleave this [sugar] off. Humans 100% rely on the microbes to digest this food," he says.
Both researchers are quick to caution that the health effects of diet are complex. Other work indicates, for example, that while intake of red meat can affect TMAO levels, so can intake of fish and seafood. But these new lines of evidence could help explain why some people, ironically, seem to be in perfect health despite eating a lot of red meat: their ideal frequency of meat consumption may depend on their existing community of gut microbes.
"It helps explain what accounts for inter-person variability," Hazen says.
These emerging mechanisms reinforce overall why it's prudent to limit red meat, just as the nutritional guidelines advised in the first place. But both Hazen and Zengler predict that interventions to buffer the effects of too many ribeyes may be just around the corner.
Zengler says, "Our idea is that you basically can help your own digestive system detoxify these inflammatory compounds in meat, if you continue eating red meat or you want to eat a high amount of red meat." A possibly strategy, he says, is to use specific pre- or probiotics to cultivate an inflammation-reducing gut microbial community.
Hazen foresees the emergence of drugs that act not on the human, but on the human's gut microorganisms. "I think it's just a matter of time [before] we will have therapeutic interventions that actually target our gut microbes, just like the way we take drugs that lower cholesterol levels."
He adds, "It's a matter of 'stay tuned', I think."
New Device Can Detect Peanut Allergens on a Plate in 30 Seconds
People with life-threatening allergies live in constant fear of coming into contact with deadly allergens. Researchers estimate that about 32 million Americans have food allergies, with the most severe being milk, egg, peanut, tree nuts, wheat, soy, fish, and shellfish.
"It is important to understand that just several years ago, this would not have been possible."
Every three minutes, a food allergy reaction sends someone to the emergency room, and 200,000 people in the U.S. require emergency medical care each year for allergic reactions, according to Food Allergy Research and Education.
But what if there was a way you could easily detect if something you were about to eat contains any harmful allergens? Thanks to Israeli scientists, this will soon be the case — at least for peanuts. The team has been working to develop a handheld device called Allerguard, which analyzes the vapors in your meal and can detect allergens in 30 seconds.
Leapsmag spoke with the founder and CTO of Allerguard, Guy Ayal, about the groundbreaking technology, how it works, and when it will be available to purchase.
What prompted you to create this device? Do you have a personal connection with severe food allergies?
Guy Ayal: My eldest daughter's best friend suffers from a severe food allergy, and I experienced first-hand the effect it has on the person and their immediate surroundings. Most notable for me was the effect on the quality of life – the experience of living in constant fear. Everything we do at Allerguard is basically to alleviate some of that fear.
How exactly does the device work?
The device is built on two main pillars. The first is the nano-chemical stage, in which we developed specially attuned nanoparticles that selectively adhere only to the specific molecules that we are looking for. Those molecules, once bound to the nanoparticles, induce a change in their electrical behavior, which is measured and analyzed by the second main pillar -- highly advanced machine learning algorithms, which can surmise which molecules were collected, and thus whether or not peanuts (or in the future, other allergens) were detected.
It is important to understand that just several years ago, this would not have been possible, because both the nano-chemistry, and especially the entire world of machine learning, big data, and what is commonly known as AI only started to exist in the '90s, and reached applicability for handheld devices only in the past few years.
Where are you at in the development process and when will the device be available to consumers?
We have concluded the proof of concept and proof of capability phase, when we demonstrated successful detection of the minimal known clinical amount that may cause the slightest effect in the most severely allergic person – less than 1 mg of peanut (actually it is 0.7 mg). Over the next 18 months will be productization, qualification, and validation of our device, which should be ready to market in the latter half of 2021. The sensor will be available in the U.S., and after a year in Europe and Canada.
The Allerguard was made possible through recent advances in machine learning, big data, and AI.
(Courtesy)
How much will it cost?
Our target price is about $200 for the device, with a disposable SenseCard that will run for at least a full day and cost about $1. That card is for a specific allergen and will work for multiple scans in a day, not just one time.
[At a later stage, the company will have sensors for other allergens like tree nuts, eggs, and milk, and they'll develop a multi-SenseCard that works for a few allergens at once.]
Are there any other devices on the market that do something similar to Allerguard?
No other devices are even close to supplying the level of service that we promise. All known methods for allergen detection rely on sampling of the food, which is a viable solution for homogenous foodstuffs, such as a factory testing their raw ingredients, but not for something as heterogenous as an actual dish – especially not for solid allergens such as peanuts, treenuts, or sesame.
If there is a single peanut in your plate, and you sample from anywhere on that plate which is not where that peanut is located, you will find that your sample is perfectly clean – because it is. But the dish is not. That dish is a death trap for an allergic person. Allerguard is the only suggested solution that could indeed detect that peanut, no matter where in that plate it is hiding.
Anything else readers should know?
Our first-generation product will be for peanuts only. You have to understand, we are still a start-up company, and if we don't concentrate our limited resources to one specific goal, we will not be able to achieve anything at all. Once we are ready to market our first device, the peanut detector, we will be able to start the R&D for the 2nd product, which will be for another allergen – most likely tree nuts and/or sesame, but that will probably be in debate until we actually start it.