Body-on-a-chip, prime editing, and gut microbes all are poised to make a big impact in 2020.
1. Happening Now: Body-on-a-Chip Technology Is Enabling Safer Drug Trials and Better Cancer Research
Researchers have increasingly used the technology known as "lab-on-a-chip" or "organ-on-a-chip" to test the effects of pharmaceuticals, toxins, and chemicals on humans. Rather than testing on animals, which raises ethical concerns and can sometimes be inaccurate, and human-based clinical trials, which can be expensive and difficult to iterate, scientists turn to tiny, micro-engineered chips—about the size of a thumb drive.
It's possible that doctors could one day take individual cell samples and create personalized treatments, testing out any medications on the chip.
The chips are lined with living samples of human cells, which mimic the physiology and mechanical forces experienced by cells inside the human body, down to blood flow and breathing motions; the functions of organs ranging from kidneys and lungs to skin, eyes, and the blood-brain barrier.
A more recent—and potentially even more useful—development takes organ-on-a-chip technology to the next level by integrating several chips into a "body-on-a-chip." Since human organs don't work in isolation, seeing how they all react—and interact—once a foreign element has been introduced can be crucial to understanding how a certain treatment will or won't perform. Dr. Shyni Varghese, a MEDx investigator at the Duke University School of Medicine, is one of the researchers working with these systems in order to gain a more nuanced understanding of how multiple different organs react to the same stimuli.
Her lab is working on "tumor-on-a-chip" models, which can not only show the progression and treatment of cancer, but also model how other organs would react to immunotherapy and other drugs. "The effect of drugs on different organs can be tested to identify potential side effects," Varghese says. In addition, these models can help the researchers figure out how cancers grow and spread, as well as how to effectively encourage immune cells to move in and attack a tumor.
One body-on-a-chip used by Dr. Varghese's lab tracks the interactions of five organs—brain, heart, liver, muscle, and bone.
As their research progresses, Varghese and her team are looking for ways to maintain the long-term function of the engineered organs. In addition, she notes that this kind of research is not just useful for generalized testing; "organ-on-chip technologies allow patient-specific analyses, which can be used towards a fundamental understanding of disease progression," Varghese says. It's possible that doctors could one day take individual cell samples and create personalized treatments, testing out any medications on the chip for safety, efficacy, and potential side effects before writing a prescription.
2. Happening Soon: Prime Editing Will Have the Power to "Find and Replace" Disease-Causing Genes
Biochemist David Liu made industry-wide news last fall when he and his lab at MIT's Broad Institute, led by Andrew Anzalone, published a paper on prime editing: a new, more focused technology for editing genes. Prime editing is a descendant of the CRISPR-Cas9 system that researchers have been working with for years, and a cousin to Liu's previous innovation—base editing, which can make a limited number of changes to a single DNA letter at a time.
By contrast, prime editing has the potential to make much larger insertions and deletions; it also doesn't require the tweaked cells to divide in order to write the changes into the DNA, which could make it especially suitable for central nervous system diseases, like Parkinson's.
Crucially, the prime editing technique has a much higher efficiency rate than the older CRISPR system, and a much lower incidence of accidental insertions or deletions, which can make dangerous changes for a patient.
It also has a very broad potential range: according to Liu, 89% of the pathogenic mutations that have been collected in ClinVar (a public archive of human variations) could, in principle, be treated with prime editing—although he is careful to note that correcting a single genetic mutation may not be sufficient to fully treat a genetic disease.
Figuring out just how prime editing can be used most effectively and safely will be a long process, but it's already underway. The same day that Liu and his team posted their paper, they also made the basic prime editing constructs available for researchers around the world through Addgene, a plasmid repository, so that others in the scientific community can test out the technique for themselves. It might be years before human patients will see the results, and in the meantime, significant bioethical questions remain about the limits and sociological effects of such a powerful gene-editing tool. But in the long fight against genetic diseases, it's a huge step forward.
3. Happening When We Fund It: Focusing on Microbiome Health Could Help Us Tackle Social Inequality—And Vice Versa
The past decade has seen a growing awareness of the major role that the microbiome, the microbes present in our digestive tract, play in human health. Having a less-healthy microbiome is correlated with health risks like diabetes and depression, and interventions that target gut health, ranging from kombucha to fecal transplants, have cropped up with increasing frequency.
New research from the University of Maine's Dr. Suzanne Ishaq takes an even broader view, arguing that low-income and disadvantaged populations are less likely to have healthy, diverse gut bacteria, and that increasing access to beneficial microorganisms is an important juncture of social justice and public health.
"Basically, allowing people to lead healthy lives allows them to access and recruit microbes."
"Typically, having a more diverse bacterial community is associated with health, and having fewer different species is associated with illness and may leave you open to infection from bacteria that are good at exploiting opportunities," Ishaq says.
Having a healthy biome doesn't mean meeting one fixed ratio of gut bacteria, since different combinations of microbes can generate roughly similar results when they work in concert. Generally, "good" microbes are the ones that break down fiber and create the byproducts that we use for energy, or ones like lactic acid bacteria that work to make microbials and keep other bacteria in check. The microbial universe in your gut is chaotic, Ishaq says. "Microbes in your gut interact with each other, with you, with your food, or maybe they don't interact at all and pass right through you." Overall, it's tricky to name specific microbial communities that will make or break someone's health.
There are important corollaries between environment and biome health, though, which Ishaq points out: Living in urban environments reduces microbial exposure, and losing the microorganisms that humans typically source from soil and plants can reduce our adaptive immunity and ability to fight off conditions like allergies and asthma. Access to green space within cities can counteract those effects, but in the U.S. that access varies along income, education, and racial lines. Likewise, lower-income communities are more likely to live in food deserts or areas where the cheapest, most convenient food options are monotonous and low in fiber, further reducing microbial diversity.
Ishaq also suggests other areas that would benefit from further study, like the correlation between paid family leave, breastfeeding, and gut microbiota. There are technical and ethical challenges to direct experimentation with human populations—but that's not what Ishaq sees as the main impediment to future research.
"The biggest roadblock is money, and the solution is also money," she says. "Basically, allowing people to lead healthy lives allows them to access and recruit microbes."
That means investment in things we already understand to improve public health, like better education and healthcare, green space, and nutritious food. It also means funding ambitious, interdisciplinary research that will investigate the connections between urban infrastructure, housing policy, social equity, and the millions of microbes keeping us company day in and day out.
Avalanche rescue dogs train to find and dig out people buried in snow slides
By the time he is three, Lume, like Huckleberry, will be a fully trained avy pup and will join seven other avy dogs on Breckenridge ski patrol team. Some of the team members, both human and canine, are also certified to work with Colorado Rapid Avalanche Deployment, a coordinated response team that works with the Summit County Sheriff’s office for avalanche emergencies outside of the ski slopes’ boundaries.
There have been 19 avalanche deaths in the U.S. this season, according to avalanche.org, which tracks slides; eight in Colorado. During the entirety of last season there were 17. Avalanche season runs from November through June, but avalanches can occur year-round.
High tech and high stakes
Complementing avy dogs’ ability to smell people buried in a slide, avalanche detection, rescue and recovery is becoming increasingly high tech. There are transceivers, signal locators, ground scanners and drones, which are considered “games changers” by many in avalanche rescue and recovery
For a person buried in an avalanche, the chance of survival plummets after 20 minutes, so every moment counts.
A drone can provide thermal imaging of objects caught in a slide; what looks like a rock from far away might be a human with a heat signature. Transceivers, also known as beacons, send a signal from an avalanche victim to a companion. Signal locators, like RECCO reflectors which are often sewn directly into gear, can echo back a radar signal sent by a detector; most ski resorts have RECCO detector units.
Research suggests that Ground Penetrating Radar (GPR), an electromagnetic tool used by geophysicists to pull images from inside the ground, could be used to locate an avalanche victim. A new study from the Department of Energy’s Sandia National Laboratories suggests that a computer program developed to pinpoint the source of a chemical or biological terrorist attack could also be used to find someone submerged in an avalanche. The search algorithm allows for small robots (described as cockroach-sized) to “swarm” a search area. Researchers say that this distributed optimization algorithm can help find avalanche victims four times faster than current search mechanisms. For a person buried in an avalanche, the chance of survival plummets after 20 minutes, so every moment counts.
An avy dog in training is picking up scent
Sarah McLear
While rescue gear has been evolving, predicting when a slab will fall remains an emerging science — kind of where weather forecasting science was in the 1980s. Avalanche forecasting still relies on documenting avalanches by going out and looking,” says Ethan Greene, director of the Colorado Avalanche Information Center (CAIC). “So if there's a big snowstorm, and as you might remember, most avalanches happened during snowstorms, we could have 10,000 avalanches that release and we document 50,” says Greene. “Avalanche forecasting is essentially pattern recognition,” he adds--and understanding the layering structure of snow.
However, determining where the hazards lie can be tricky. While a dense layer of snow over a softer, weaker layer may be a recipe for an avalanche, there’s so much variability in snowpack that no one formula can predict the trigger. Further, observing and measuring snow at a single point may not be representative of all nearby slopes. Finally, there’s not enough historical data to help avalanche scientists create better prediction models.
That, however, may be changing.
Last year, an international group of researchers created computer simulations of snow cover using 16 years of meteorological data to forecast avalanche hazards, publishing their research in Cold Regions Science and Technology. They believe their models, which categorize different kinds of avalanches, can support forecasting and determine whether the avalanche is natural (caused by temperature changes, wind, additional snowfall) or artificial (triggered by a human or animal).
With smell receptors ranging from 800 million for an average dog, to 4 billion for scent hounds, canines remain key to finding people caught in slides.
With data from two sites in British Columbia and one in Switzerland, researchers built computer simulations of five different avalanche types. “In terms of real time avalanche forecasting, this has potential to fill in a lot of data gaps, where we don't have field observations of what the snow looks like,” says Simon Horton, a postdoctoral fellow with the Simon Fraser University Centre for Natural Hazards Research and a forecaster with Avalanche Canada, who participated in the study. While complex models that simulate snowpack layers have been around for a few decades, they weren’t easy to apply until recently. “It's been difficult to find out how to apply that to actual decision-making and improving safety,” says Horton. If you can derive avalanche problem types from simulated snowpack properties, he says, you’ll learn “a lot about how you want to manage that risk.”
The five categories include “new snow,” which is unstable and slides down the slope, “wet snow,” when rain or heat makes it liquidly, as well as “wind-drifted snow,” “persistent weak layers” and “old snow.” “That's when there's some type of deeply buried weak layer in the snow that releases without any real change in the weather,” Horton explains. “These ones tend to cause the most accidents.” One step by a person on that structurally weak layer of snow will cause a slide. Horton is hopeful that computer simulations of avalanche types can be used by scientists in different snow climates to help predict hazard levels.
Greene is doubtful. “If you have six slopes that are lined up next to each other, and you're going to try to predict which one avalanches and the exact dimensions and what time, that's going to be really hard to do. And I think it's going to be a long time before we're able to do that,” says Greene.
What both researchers do agree on, though, is that what avalanche prediction really needs is better imagery through satellite detection. “Just being able to count the number of avalanches that are out there will have a huge impact on what we do,” Greene says. “[Satellites] will change what we do, dramatically.” In a 2022 paper, scientists at the University of Aberdeen in England used satellites to study two deadly Himalayan avalanches. The imaging helped them determine that sediment from a 2016 ice avalanche plus subsequent snow avalanches contributed to the 2021 avalanche that caused a flash flood, killing over 200 people. The researchers say that understanding the avalanches characteristics through satellite imagery can inform them how one such event increases the magnitude of another in the same area.
Avy dogs trainers hide in dug-out holes in the snow, teaching the dogs to find buried victims
Sarah McLear
Lifesaving combo: human tech and Mother Nature’s gear
Even as avalanche forecasting evolves, dogs with their built-in rescue mechanisms will remain invaluable. With smell receptors ranging from 800 million for an average dog, to 4 billion for scent hounds, canines remain key to finding people caught in slides. (Humans in comparison, have a meager 12 million.) A new study published in the Journal of Neuroscience revealed that in dogs smell and vision are connected in the brain, which has not been found in other animals. “They can detect the smell of their owner's fingerprints on a glass slide six weeks after they touched it,” says Nicholas Dodman, professor emeritus at Cummings School of Veterinary Medicine at Tufts University. “And they can track from a boat where a box filled with meat was buried in the water, 100 feet below,” says Dodman, who is also co-founder and president of the Center for Canine Behavior Studies.
Another recent study from Queens College in Belfast, United Kingdom, further confirms that dogs can smell when humans are stressed. They can also detect the smell of a person’s breath and the smell of the skin cells of a deceased person.
The emerging avalanche-predicting human-made tech and the incredible nature-made tech of dogs’ olfactory talents is the lifesaving “equipment” that Leffler believes in. Even when human-made technology develops further, it will be most efficient when used together with the millions of dogs’ smell receptors, Leffler believes. “It is a combination of technology and the avalanche dog that will always be effective in finding an avalanche victim.”
