Eight Big Medical and Science Trends to Watch in 2021
The world as we know it has forever changed. With a greater focus on science and technology than before, experts in the biotech and life sciences spaces are grappling with what comes next as SARS-CoV-2, the coronavirus that causes the COVID-19 illness, has spread and mutated across the world.
Even with vaccines being distributed, so much still remains unknown.
Jared Auclair, Technical Supervisor for the Northeastern University's Life Science Testing Center in Burlington, Massachusetts, guides a COVID testing lab that cranks out thousands of coronavirus test results per day. His lab is also focused on monitoring the quality of new cell and gene therapy products coming to the market.
Here are trends Auclair and other experts are watching in 2021.
Better Diagnostic Testing for COVID
Expect improvements in COVID diagnostic testing and the ability to test at home.
There are currently three types of coronavirus tests. The molecular test—also known as the RT-PCR test, detects the virus's genetic material, and is highly accurate, but it can take days to receive results. There are also antibody tests, done through a blood draw, designed to test whether you've had COVID in the past. Finally, there's the quick antigen test that isn't as accurate as the PCR test, but can identify if people are going to infect others.
Last month, Lucira Health secured the U.S. FDA Emergency Use Authorization for the first prescription molecular diagnostic test for COVID-19 that can be performed at home. On December 15th, the Ellume Covid-19 Home Test received authorization as the first over-the-counter COVID-19 diagnostic antigen test that can be done at home without a prescription. The test uses a nasal swab that is connected to a smartphone app and returns results in 15-20 minutes. Similarly, the BinaxNOW COVID-19 Ag Card Home Test received authorization on Dec. 16 for its 15-minute antigen test that can be used within the first seven days of onset of COIVD-19 symptoms.
Home testing has the possibility to impact the pandemic pretty drastically, Auclair says, but there are other considerations: the type and timing of test that is administered, how expensive is the test (and if it is financially feasible for the general public) and the ability of a home test taker to accurately administer the test.
"The vaccine roll-out will not eliminate the need for testing until late 2021 or early 2022."
Ideally, everyone would frequently get tested, but that would mean the cost of a single home test—which is expected to be around $30 or more—would need to be much cheaper, more in the $5 range.
Auclair expects "innovations in the diagnostic space to explode" with the need for more accurate, inexpensive, quicker COVID tests. Auclair foresees innovations to be at first focused on COVID point-of-care testing, but he expects improvements within diagnostic testing for other types of viruses and diseases too.
"We still need more testing to get the pandemic under control, likely over the next 12 months," Auclair says. "The vaccine roll-out will not eliminate the need for testing until late 2021 or early 2022."
Rise of mRNA-based Vaccines and Therapies
A year ago, vaccines weren't being talked about like they are today.
"But clearly vaccines are the talk of the town," Auclair says. "The reason we got a vaccine so fast was there was so much money thrown at it."
A vaccine can take more than 10 years to fully develop, according to the World Economic Forum. Prior to the new COVID vaccines, which were remarkably developed and tested in under a year, the fastest vaccine ever made was for mumps -- and it took four years.
"Normally you have to produce a protein. This is typically done in eggs. It takes forever," says Catherine Dulac, a neuroscientist and developmental biologist at Harvard University who won the 2021 Breakthrough Prize in Life Sciences. "But an mRNA vaccine just enabled [us] to skip all sorts of steps [compared with burdensome conventional manufacturing] and go directly to a product that can be injected into people."
Non-traditional medicines based on genetic research are in their infancy. With mRNA-based vaccines hitting the market for the first time, look for more vaccines to be developed for whatever viruses we don't currently have vaccines for, like dengue virus and Ebola, Auclair says.
"There's a whole bunch of things that could be explored now that haven't been thought about in the past," Auclair says. "It could really be a game changer."
Vaccine Innovation over the last 140 years.
Max Roser/Our World in Data (Creative Commons license)
Advancements in Cell and Gene Therapies
CRISPR, a type of gene editing, is going to be huge in 2021, especially after the Nobel Prize in Chemistry was awarded to Emmanuelle Charpentier and Jennifer Doudna in October for pioneering the technology.
Right now, CRISPR isn't completely precise and can cause deletions or rearrangements of DNA.
"It's definitely not there yet, but over the next year it's going to get a lot closer and you're going to have a lot of momentum in this space," Auclair says. "CRISPR is one of the technologies I'm most excited about and 2021 is the year for it."
Gene therapies are typically used on rare genetic diseases. They work by replacing the faulty dysfunctional genes with corrected DNA codes.
"Cell and gene therapies are really where the field is going," Auclair says. "There is so much opportunity....For the first time in our life, in our existence as a species, we may actually be able to cure disease by using [techniques] like gene editing, where you cut in and out of pieces of DNA that caused a disease and put in healthy DNA," Auclair says.
For example, Spinal Muscular Atrophy is a rare genetic disorder that leads to muscle weakness, paralysis and death in children by age two. As of last year, afflicted children can take a gene therapy drug called Zolgensma that targets the missing or nonworking SMN1 gene with a new copy.
Another recent breakthrough uses gene editing for sickle cell disease. Victoria Gray, a mom from Mississippi who was exclusively followed by NPR, was the first person in the United States to be successfully treated for the genetic disorder with the help of CRISPR. She has continued to improve since her landmark treatment on July 2, 2019 and her once-debilitating pain has greatly eased.
"This is really a life-changer for me," she told NPR. "It's magnificent."
"You are going to see bigger leaps in gene therapies."
Look out also for improvements in cell therapies, but on a much lesser scale.
Cell therapies remove immune cells from a person or use cells from a donor. The cells are modified or cultured in lab, multiplied by the millions and then injected back into patients. These include stem cell therapies as well as CAR-T cell therapies, which are typically therapies of last resort and used in cancers like leukemia, Auclair says.
"You are going to see bigger leaps in gene therapies," Auclair says. "It's being heavily researched and we understand more about how to do gene therapies. Cell therapies will lie behind it a bit because they are so much more difficult to work with right now."
More Monoclonal Antibody Therapies
Look for more customized drugs to personalize medicine even more in the biotechnology space.
In 2019, the FDA anticipated receiving more than 200 Investigational New Drug (IND) applications in 2020. But with COVID, the number of INDs skyrocketed to 6,954 applications for the 2020 fiscal year, which ended September 30, 2020, according to the FDA's online tracker. Look for antibody therapies to play a bigger role.
Monoclonal antibodies are lab-grown proteins that mimic or enhance the immune system's response to fight off pathogens, like viruses, and they've been used to treat cancer. Now they are being used to treat patients with COVID-19.
President Donald Trump received a monoclonal antibody cocktail, called REGEN-COV2, which later received FDA emergency use authorization.
A newer type of monoclonal antibody therapy is Antibody-Drug Conjugates, also called ADCs. It's something we're going to be hearing a lot about in 2021, Auclair says.
"Antibody-Drug Conjugates is a monoclonal antibody with a chemical, we consider it a chemical warhead on it," Auclair says. "The monoclonal antibody binds to a specific antigen in your body or protein and delivers a chemical to that location and kills the infected cell."
Moving Beyond Male-Centric Lab Testing
Scientific testing for biology has, until recently, focused on testing males. Dulac, a Howard Hughes Medical Investigator and professor of molecular and cellular biology at Harvard University, challenged that idea to find brain circuitry behind sex-specific behaviors.
"For the longest time, until now, all the model systems in biology, are male," Dulac says. "The idea is if you do testing on males, you don't need to do testing on females."
Clinical models are done in male animals, as well as fundamental research. Because biological research is always done on male models, Dulac says the outcomes and understanding in biology is geared towards understanding male biology.
"All the drugs currently on the market and diagnoses of diseases are biased towards the understanding of male biology," Dulac says. "The diagnostics of diseases is way weaker in women than men."
That means the treatment isn't necessarily as good for women as men, she says, including what is known and understood about pain medication.
"So pain medication doesn't work well in women," Dulac says. "It works way better in men. It's true for almost all diseases that I know. Why? because you have a science that is dominated by males."
Although some in the scientific community challenge that females are not interesting or too complicated with their hormonal variations, Dulac says that's simply not true.
"There's absolutely no reason to decide 50% of life forms are interesting and the other 50% are not interesting. What about looking at both?" says Dulac, who was awarded the $3 million Breakthrough Prize in Life Sciences in September for connecting specific neural mechanisms to male and female parenting behaviors.
Disease Research on Single Cells
To better understand how diseases manifest in the body's cell and tissues, many researchers are looking at single-cell biology. Cells are the most fundamental building blocks of life. Much still needs to be learned.
"A remarkable development this year is the massive use of analysis of gene expression and chromosomal regulation at the single-cell level," Dulac says.
Much is focused on the Human Cell Atlas (HCA), a global initiative to map all cells in healthy humans and to better identify which genes associated with diseases are active in a person's body. Most estimates put the number of cells around 30 trillion.
Dulac points to work being conducted by the Cell Census Network (BICCN) Brain Initiative, an initiative by the National Institutes of Health to come up with an atlas of cell types in mouse, human and non-human primate brains, and the Chan Zuckerberg Initiative's funding of single-cell biology projects, including those focused on single-cell analysis of inflammation.
"Our body and our brain are made of a large number of cell types," Dulac says. "The ability to explore and identify differences in gene expression and regulation in massively multiplex ways by analyzing millions of cells is extraordinarily important."
Converting Plastics into Food
Yep, you heard it right, plastics may eventually be turned into food. The Defense Advanced Research Projects Agency, better known as DARPA, is funding a project—formally titled "Production of Macronutrients from Thermally Oxo-Degraded Wastes"—and asking researchers how to do this.
"When I first heard about this challenge, I thought it was absolutely absurd," says Dr. Robert Brown, director of the Bioeconomy Institute at Iowa State University and the project's principal investigator, who is working with other research partners at the University of Delaware, Sandia National Laboratories, and the American Institute of Chemical Engineering (AIChE)/RAPID Institute.
But then Brown realized plastics will slowly start oxidizing—taking in oxygen—and microorganisms can then consume it. The oxidation process at room temperature is extremely slow, however, which makes plastics essentially not biodegradable, Brown says.
That changes when heat is applied at brick pizza oven-like temperatures around 900-degrees Fahrenheit. The high temperatures get compounds to oxidize rapidly. Plastics are synthetic polymers made from petroleum—large molecules formed by linking many molecules together in a chain. Heated, these polymers will melt and crack into smaller molecules, causing them to vaporize in a process called devolatilization. Air is then used to cause oxidation in plastics and produce oxygenated compounds—fatty acids and alcohols—that microorganisms will eat and grow into single-cell proteins that can be used as an ingredient or substitute in protein-rich foods.
"The caveat is the microorganisms must be food-safe, something that we can consume," Brown says. "Like supplemental or nutritional yeast, like we use to brew beer and to make bread or is used in Australia to make Vegemite."
What do the microorganisms look like? For any home beer brewers, it's the "gunky looking stuff you'd find at the bottom after the fermentation process," Brown says. "That's cellular biomass. Like corn grown in the field, yeast or other microorganisms like bacteria can be harvested as macro-nutrients."
Brown says DARPA's ReSource program has challenged all the project researchers to find ways for microorganisms to consume any plastics found in the waste stream coming out of a military expeditionary force, including all the packaging of food and supplies. Then the researchers aim to remake the plastic waste into products soldiers can use, including food. The project is in the first of three phases.
"We are talking about polyethylene, polypropylene, like PET plastics used in water bottles and converting that into macronutrients that are food," says Brown.
Renewed Focus on Climate Change
The Union of Concerned Scientists say carbon dioxide levels are higher today than any point in at least 800,000 years.
"Climate science is so important for all of humankind. It is critical because the quality of life of humans on the planet depends on it."
Look for technology to help locate large-scale emitters of carbon dioxide, including sensors on satellites and artificial intelligence to optimize energy usage, especially in data centers.
Other technologies focus on alleviating the root cause of climate change: emissions of heat-trapping gasses that mainly come from burning fossil fuels.
Direct air carbon capture, an emerging effort to capture carbon dioxide directly from ambient air, could play a role.
The technology is in the early stages of development and still highly uncertain, says Peter Frumhoff, director of science and policy at Union of Concerned Scientists. "There are a lot of questions about how to do that at sufficiently low costs...and how to scale it up so you can get carbon dioxide stored in the right way," he says, and it can be very energy intensive.
One of the oldest solutions is planting new forests, or restoring old ones, which can help convert carbon dioxide into oxygen through photosynthesis. Hence the Trillion Trees Initiative launched by the World Economic Forum. Trees are only part of the solution, because planting trees isn't enough on its own, Frumhoff says. That's especially true, since 2020 was the year that human-made, artificial stuff now outweighs all life on earth.
More research is also going into artificial photosynthesis for solar fuels. The U.S. Department of Energy awarded $100 million in 2020 to two entities that are conducting research. Look also for improvements in battery storage capacity to help electric vehicles, as well as back-up power sources for solar and wind power, Frumhoff says.
Another method to combat climate change is solar geoengineering, also called solar radiation management, which reflects sunlight back to space. The idea stems from a volcanic eruption in 1991 that released a tremendous amount of sulfate aerosol particles into the stratosphere, reflecting the sunlight away from Earth. The planet cooled by a half degree for nearly a year, Frumhoff says. However, he acknowledges, "there's a lot of things we don't know about the potential impacts and risks" involved in this controversial approach.
Whatever the approach, scientific solutions to climate change are attracting renewed attention. Under President Trump, the White House Office of Science and Technology Policy didn't have an acting director for almost two years. Expect that to change when President-elect Joe Biden takes office.
"Climate science is so important for all of humankind," Dulac says. "It is critical because the quality of life of humans on the planet depends on it."
Massive benefits of AI come with environmental and human costs. Can AI itself be part of the solution?
The recent explosion of generative artificial intelligence tools like ChatGPT and Dall-E enabled anyone with internet access to harness AI’s power for enhanced productivity, creativity, and problem-solving. With their ever-improving capabilities and expanding user base, these tools proved useful across disciplines, from the creative to the scientific.
But beneath the technological wonders of human-like conversation and creative expression lies a dirty secret—an alarming environmental and human cost. AI has an immense carbon footprint. Systems like ChatGPT take months to train in high-powered data centers, which demand huge amounts of electricity, much of which is still generated with fossil fuels, as well as water for cooling. “One of the reasons why Open AI needs investments [to the tune of] $10 billion from Microsoft is because they need to pay for all of that computation,” says Kentaro Toyama, a computer scientist at the University of Michigan. There’s also an ecological toll from mining rare minerals required for hardware and infrastructure. This environmental exploitation pollutes land, triggers natural disasters and causes large-scale human displacement. Finally, for data labeling needed to train and correct AI algorithms, the Big Data industry employs cheap and exploitative labor, often from the Global South.
Generative AI tools are based on large language models (LLMs), with most well-known being various versions of GPT. LLMs can perform natural language processing, including translating, summarizing and answering questions. They use artificial neural networks, called deep learning or machine learning. Inspired by the human brain, neural networks are made of millions of artificial neurons. “The basic principles of neural networks were known even in the 1950s and 1960s,” Toyama says, “but it’s only now, with the tremendous amount of compute power that we have, as well as huge amounts of data, that it’s become possible to train generative AI models.”
Though there aren’t any official figures about the power consumption or emissions from data centers, experts estimate that they use one percent of global electricity—more than entire countries.
In recent months, much attention has gone to the transformative benefits of these technologies. But it’s important to consider that these remarkable advances may come at a price.
AI’s carbon footprint
In their latest annual report, 2023 Landscape: Confronting Tech Power, the AI Now Institute, an independent policy research entity focusing on the concentration of power in the tech industry, says: “The constant push for scale in artificial intelligence has led Big Tech firms to develop hugely energy-intensive computational models that optimize for ‘accuracy’—through increasingly large datasets and computationally intensive model training—over more efficient and sustainable alternatives.”
Though there aren’t any official figures about the power consumption or emissions from data centers, experts estimate that they use one percent of global electricity—more than entire countries. In 2019, Emma Strubell, then a graduate researcher at the University of Massachusetts Amherst, estimated that training a single LLM resulted in over 280,000 kg in CO2 emissions—an equivalent of driving almost 1.2 million km in a gas-powered car. A couple of years later, David Patterson, a computer scientist from the University of California Berkeley, and colleagues, estimated GPT-3’s carbon footprint at over 550,000 kg of CO2 In 2022, the tech company Hugging Face, estimated the carbon footprint of its own language model, BLOOM, as 25,000 kg in CO2 emissions. (BLOOM’s footprint is lower because Hugging Face uses renewable energy, but it doubled when other life-cycle processes like hardware manufacturing and use were added.)
Luckily, despite the growing size and numbers of data centers, their increasing energy demands and emissions have not kept pace proportionately—thanks to renewable energy sources and energy-efficient hardware.
But emissions don’t tell the full story.
AI’s hidden human cost
“If historical colonialism annexed territories, their resources, and the bodies that worked on them, data colonialism’s power grab is both simpler and deeper: the capture and control of human life itself through appropriating the data that can be extracted from it for profit.” So write Nick Couldry and Ulises Mejias, authors of the book The Costs of Connection.
The energy requirements, hardware manufacture and the cheap human labor behind AI systems disproportionately affect marginalized communities.
Technologies we use daily inexorably gather our data. “Human experience, potentially every layer and aspect of it, is becoming the target of profitable extraction,” Couldry and Meijas say. This feeds data capitalism, the economic model built on the extraction and commodification of data. While we are being dispossessed of our data, Big Tech commodifies it for their own benefit. This results in consolidation of power structures that reinforce existing race, gender, class and other inequalities.
“The political economy around tech and tech companies, and the development in advances in AI contribute to massive displacement and pollution, and significantly changes the built environment,” says technologist and activist Yeshi Milner, who founded Data For Black Lives (D4BL) to create measurable change in Black people’s lives using data. The energy requirements, hardware manufacture and the cheap human labor behind AI systems disproportionately affect marginalized communities.
AI’s recent explosive growth spiked the demand for manual, behind-the-scenes tasks, creating an industry described by Mary Gray and Siddharth Suri as “ghost work” in their book. This invisible human workforce that lies behind the “magic” of AI, is overworked and underpaid, and very often based in the Global South. For example, workers in Kenya who made less than $2 an hour, were the behind the mechanism that trained ChatGPT to properly talk about violence, hate speech and sexual abuse. And, according to an article in Analytics India Magazine, in some cases these workers may not have been paid at all, a case for wage theft. An exposé by the Washington Post describes “digital sweatshops” in the Philippines, where thousands of workers experience low wages, delays in payment, and wage theft by Remotasks, a platform owned by Scale AI, a $7 billion dollar American startup. Rights groups and labor researchers have flagged Scale AI as one company that flouts basic labor standards for workers abroad.
It is possible to draw a parallel with chattel slavery—the most significant economic event that continues to shape the modern world—to see the business structures that allow for the massive exploitation of people, Milner says. Back then, people got chocolate, sugar, cotton; today, they get generative AI tools. “What’s invisible through distance—because [tech companies] also control what we see—is the massive exploitation,” Milner says.
“At Data for Black Lives, we are less concerned with whether AI will become human…[W]e’re more concerned with the growing power of AI to decide who’s human and who’s not,” Milner says. As a decision-making force, AI becomes a “justifying factor for policies, practices, rules that not just reinforce, but are currently turning the clock back generations years on people’s civil and human rights.”
Ironically, AI plays an important role in mitigating its own harms—by plowing through mountains of data about weather changes, extreme weather events and human displacement.
Nuria Oliver, a computer scientist, and co-founder and vice-president of the European Laboratory of Learning and Intelligent Systems (ELLIS), says that instead of focusing on the hypothetical existential risks of today’s AI, we should talk about its real, tangible risks.
“Because AI is a transverse discipline that you can apply to any field [from education, journalism, medicine, to transportation and energy], it has a transformative power…and an exponential impact,” she says.
AI's accountability
“At the core of what we were arguing about data capitalism [is] a call to action to abolish Big Data,” says Milner. “Not to abolish data itself, but the power structures that concentrate [its] power in the hands of very few actors.”
A comprehensive AI Act currently negotiated in the European Parliament aims to rein Big Tech in. It plans to introduce a rating of AI tools based on the harms caused to humans, while being as technology-neutral as possible. That sets standards for safe, transparent, traceable, non-discriminatory, and environmentally friendly AI systems, overseen by people, not automation. The regulations also ask for transparency in the content used to train generative AIs, particularly with copyrighted data, and also disclosing that the content is AI-generated. “This European regulation is setting the example for other regions and countries in the world,” Oliver says. But, she adds, such transparencies are hard to achieve.
Google, for example, recently updated its privacy policy to say that anything on the public internet will be used as training data. “Obviously, technology companies have to respond to their economic interests, so their decisions are not necessarily going to be the best for society and for the environment,” Oliver says. “And that’s why we need strong research institutions and civil society institutions to push for actions.” ELLIS also advocates for data centers to be built in locations where the energy can be produced sustainably.
Ironically, AI plays an important role in mitigating its own harms—by plowing through mountains of data about weather changes, extreme weather events and human displacement. “The only way to make sense of this data is using machine learning methods,” Oliver says.
Milner believes that the best way to expose AI-caused systemic inequalities is through people's stories. “In these last five years, so much of our work [at D4BL] has been creating new datasets, new data tools, bringing the data to life. To show the harms but also to continue to reclaim it as a tool for social change and for political change.” This change, she adds, will depend on whose hands it is in.
DNA gathered from animal poop helps protect wildlife
On the savannah near the Botswana-Zimbabwe border, elephants grazed contentedly. Nearby, postdoctoral researcher Alida de Flamingh watched and waited. As the herd moved away, she went into action, collecting samples of elephant dung that she and other wildlife conservationists would study in the months to come. She pulled on gloves, took a swab, and ran it all over the still-warm, round blob of elephant poop.
Sequencing DNA from fecal matter is a safe, non-invasive way to track and ultimately help protect over 42,000 species currently threatened by extinction. Scientists are using this DNA to gain insights into wildlife health, genetic diversity and even the broader environment. Applied to elephants, chimpanzees, toucans and other species, it helps scientists determine the genetic diversity of groups and linkages with other groups. Such analysis can show changes in rates of inbreeding. Populations with greater genetic diversity adapt better to changes and environmental stressors than those with less diversity, thus reducing their risks of extinction, explains de Flamingh, a postdoctoral researcher at the University of Illinois Urbana-Champaign.
Analyzing fecal DNA also reveals information about an animal’s diet and health, and even nearby flora that is eaten. That information gives scientists broader insights into the ecosystem, and the findings are informing conservation initiatives. Examples include restoring or maintaining genetic connections among groups, ensuring access to certain foraging areas or increasing diversity in captive breeding programs.
Approximately 27 percent of mammals and 28 percent of all assessed species are close to dying out. The IUCN Red List of threatened species, simply called the Red List, is the world’s most comprehensive record of animals’ risk of extinction status. The more information scientists gather, the better their chances of reducing those risks. In Africa, populations of vertebrates declined 69 percent between 1970 and 2022, according to the World Wildlife Fund (WWF).
“We put on sterile gloves and use a sterile swab to collect wet mucus and materials from the outside of the dung ball,” says Alida de Flamingh, a postdoctoral researcher at the University of Illinois Urbana-Champaign.
“When people talk about species, they often talk about ecosystems, but they often overlook genetic diversity,” says Christina Hvilsom, senior geneticist at the Copenhagen Zoo. “It’s easy to count (individuals) to assess whether the population size is increasing or decreasing, but diversity isn’t something we can see with our bare eyes. Yet, it’s actually the foundation for the species and populations.” DNA analysis can provide this critical information.
Assessing elephants’ health
“Africa’s elephant populations are facing unprecedented threats,” says de Flamingh, the postdoc, who has studied them since 2009. Challenges include ivory poaching, habitat destruction and smaller, more fragmented habitats that result in smaller mating pools with less genetic diversity. Additionally, de Flamingh studies the microbial communities living on and in elephants – their microbiomes – looking for parasites or dangerous microbes.
Approximately 415,000 elephants inhabit Africa today, but de Flamingh says the number would be four times higher without these challenges. The IUCN Red List reports African savannah elephants are endangered and African forest elephants are critically endangered. Elephants support ecosystem biodiversity by clearing paths that help other species travel. Their very footprints create small puddles that can host smaller organisms such as tadpoles. Elephants are often described as ecosystems’ engineers, so if they disappear, the rest of the ecosystem will suffer too.
There’s a process to collecting elephant feces. “We put on sterile gloves (which we change for each sample) and use a sterile swab to collect wet mucus and materials from the outside of the dung ball,” says de Flamingh. They rub a sample about the size of a U.S. quarter onto a paper card embedded with DNA preservation technology. Each card is air dried and stored in a packet of desiccant to prevent mold growth. This way, samples can be stored at room temperature indefinitely without the DNA degrading.
Earlier methods required collecting dung in bags, which needed either refrigeration or the addition of preservatives, or the riskier alternative of tranquilizing the animals before approaching them to draw blood samples. The ability to collect and sequence the DNA made things much easier and safer.
“Our research provides a way to assess elephant health without having to physically interact with elephants,” de Flamingh emphasizes. “We also keep track of the GPS coordinates of each sample so that we can create a map of the sampling locations,” she adds. That helps researchers correlate elephants’ health with geographic areas and their conditions.
Although de Flamingh works with elephants in the wild, the contributions of zoos in the United States and collaborations in South Africa (notably the late Professor Rudi van Aarde and the Conservation Ecology Research Unit at the University of Pretoria) were key in studying this method to ensure it worked, she points out.
Protecting chimpanzees
Genetic work with chimpanzees began about a decade ago. Hvilsom and her group at the Copenhagen Zoo analyzed DNA from nearly 1,000 fecal samples collected between 2003 and 2018 by a team of international researchers. The goal was to assess the status of the West African subspecies, which is critically endangered after rapid population declines. Of the four subspecies of chimpanzees, the West African subspecies is considered the most at-risk.
In total, the WWF estimates the numbers of chimpanzees inhabiting Africa’s forests and savannah woodlands at between 173,000 and 300,000. Poaching, disease and human-caused changes to their lands are their major risks.
By analyzing genetics obtained from fecal samples, Hvilsom estimated the chimpanzees’ population, ascertained their family relationships and mapped their migration routes.
“One of the threats is mining near the Nimba Mountains in Guinea,” a stronghold for the West African subspecies, Hvilsom says. The Nimba Mountains are a UNESCO World Heritage Site, but they are rich in iron ore, which is used to make the steel that is vital to the Asian construction boom. As she and colleagues wrote in a recent paper, “Many extractive industries are currently developing projects in chimpanzee habitat.”
Analyzing DNA allows researchers to identify individual chimpanzees more accurately than simply observing them, she says. Normally, field researchers would install cameras and manually inspect each picture to determine how many chimpanzees were in an area. But, Hvilsom says, “That’s very tricky. Chimpanzees move a lot and are fast, so it’s difficult to get clear pictures. Often, they find and destroy the cameras. Also, they live in large areas, so you need a lot of cameras.”
By analyzing genetics obtained from fecal samples, Hvilsom estimated the chimpanzees’ population, ascertained their family relationships and mapped their migration routes based upon DNA comparisons with other chimpanzee groups. The mining companies and builders are using this information to locate future roads where they won’t disrupt migration – a more effective solution than trying to build artificial corridors for wildlife.
“The current route cuts off communities of chimpanzees,” Hvilsom elaborates. That effectively prevents young adult chimps from joining other groups when the time comes, eventually reducing the currently-high levels of genetic diversity.
“The mining company helped pay for the genetics work,” Hvilsom says, “as part of its obligation to assess and monitor biodiversity and the effect of the mining in the area.”
Of 50 toucan subspecies, 11 are threatened or near-threatened with extinction because of deforestation and poaching.
Identifying toucan families
Feces aren't the only substance researchers draw DNA samples from. Jeffrey Coleman, a Ph.D. candidate at the University of Texas at Austin relies on blood tests for studying the genetic diversity of toucans---birds species native to Central America and nearby regions. They live in the jungles, where they hop among branches, snip fruit from trees, toss it in the air and catch it with their large beaks. “Toucans are beautiful, charismatic birds that are really important to the ecosystem,” says Coleman.
Of their 50 subspecies, 11 are threatened or near-threatened with extinction because of deforestation and poaching. “When people see these aesthetically pleasing birds, they’re motivated to care about conservation practices,” he points out.
Coleman works with the Dallas World Aquarium and its partner zoos to analyze DNA from blood draws, using it to identify which toucans are related and how closely. His goal is to use science to improve the genetic diversity among toucan offspring.
Specifically, he’s looking at sections of the genome of captive birds in which the nucleotides repeat multiple times, such as AGATAGATAGAT. Called microsatellites, these consecutively-repeating sections can be passed from parents to children, helping scientists identify parent-child and sibling-sibling relationships. “That allows you to make strategic decisions about how to pair (captive) individuals for mating...to avoid inbreeding,” Coleman says.
Jeffrey Coleman is studying the microsatellites inside the toucan genomes.
Courtesy Jeffrey Coleman
The alternative is to use a type of analysis that looks for a single DNA building block – a nucleotide – that differs in a given sequence. Called single nucleotide polymorphisms (SNPs, pronounced “snips”), they are very common and very accurate. Coleman says they are better than microsatellites for some uses. But scientists have already developed a large body of microsatellite data from multiple species, so microsatellites can shed more insights on relations.
Regardless of whether conservation programs use SNPs or microsatellites to guide captive breeding efforts, the goal is to help them build genetically diverse populations that eventually may supplement endangered populations in the wild. “The hope is that the ecosystem will be stable enough and that the populations (once reintroduced into the wild) will be able to survive and thrive,” says Coleman. History knows some good examples of captive breeding success.
The California condor, which had a total population of 27 in 1987, when the last wild birds were captured, is one of them. A captive breeding program boosted their numbers to 561 by the end of 2022. Of those, 347 of those are in the wild, according to the National Park Service.
Conservationists hope that their work on animals’ genetic diversity will help preserve and restore endangered species in captivity and the wild. DNA analysis is crucial to both types of efforts. The ability to apply genome sequencing to wildlife conservation brings a new level of accuracy that helps protect species and gives fresh insights that observation alone can’t provide.
“A lot of species are threatened,” Coleman says. “I hope this research will be a resource people can use to get more information on longer-term genealogies and different populations.”