Anti-Aging Pioneer Aubrey de Grey: “People in Middle Age Now Have a Fair Chance”
Kira Peikoff was the editor-in-chief of Leaps.org from 2017 to 2021. As a journalist, her work has appeared in The New York Times, Newsweek, Nautilus, Popular Mechanics, The New York Academy of Sciences, and other outlets. She is also the author of four suspense novels that explore controversial issues arising from scientific innovation: Living Proof, No Time to Die, Die Again Tomorrow, and Mother Knows Best. Peikoff holds a B.A. in Journalism from New York University and an M.S. in Bioethics from Columbia University. She lives in New Jersey with her husband and two young sons. Follow her on Twitter @KiraPeikoff.
Aging is not a mystery, says famed researcher Dr. Aubrey de Grey, perhaps the world's foremost advocate of the provocative view that medical technology will one day allow humans to control the aging process and live healthily into our hundreds—or even thousands.
"The cultural attitudes toward all of this are going to be completely turned upside down by sufficiently promising results in the lab, in mice."
He likens aging to a car wearing down over time; as the body operates normally, it accumulates damage which can be tolerated for a while, but eventually sends us into steep decline. The most promising way to escape this biological reality, he says, is to repair the damage as needed with precise scientific tools.
The bad news is that doing this groundbreaking research takes a long time and a lot of money, which has not always been readily available, in part due to a cultural phenomenon he terms "the pro-aging trance." Cultural attitudes have long been fatalistic about the inevitability of aging; many people balk at the seemingly implausible prospect of indefinite longevity.
But the good news for de Grey—and those who are cheering him on—is that his view is becoming less radical these days. Both the academic and private sectors are racing to tackle aging; his own SENS Research Foundation, for one, has spun out into five different companies. Defeating aging, he says, "is not just a future industry; it's an industry now that will be both profitable and extremely good for your health."
De Grey sat down with Editor-in-Chief Kira Peikoff at the World Stem Cell Summit in Miami to give LeapsMag the latest scoop on his work. Here is an edited and condensed version of our conversation.
Since your book Ending Aging was published a decade ago, scientific breakthroughs in stem cell research, genome editing, and other fields have taken the world by storm. Which of these have most affected your research?
They have all affected it a lot in one way, and hardly at all in another way. They have speeded it up--facilitated short cuts, ways to get where we're already trying to go. What they have not done is identified any fundamental changes to the overall strategy. In the book, we described the seven major types of damage, and particular ways of going about fixing each of them, and that hasn't changed.
"Repair at the microscopic level, one would be able to expect to do without surgery, just by injecting the right kind of stem cells."
Has any breakthrough specifically made the biggest impact?
It's not just the obvious things, like iPS (induced pluripotent stem cells) and CRISPR (a precise tool for editing genes). It's also the more esoteric things that applied specifically to certain of our areas, but most people don't really know about them. For example, the identification of how to control something called co-translational mitochondrial protein import.
How much of the future of anti-aging treatments will involve regeneration of old tissue, or wholesale growth of new organs?
The more large-scale ones, regenerating whole new organs, are probably only going to play a role in the short-term and will be phased out relatively rapidly, simply because, in order to be useful, one has to employ surgery, which is really invasive. We'll want to try to get around that, but it seems quite likely that in the very early stages, the techniques we have for repairing things at the molecular and cellular level in situ will be insufficiently comprehensive, and so we will need to do the more sledgehammer approach of building a whole new organ and sticking it in.
Every time you are in a position where you're replacing an organ, you have the option, in principle, of repairing the organ, without replacing it. And repair at the microscopic level, one would be able to expect to do without surgery, just by injecting the right kind of stem cells or whatever. That would be something one would expect to be able to apply to someone much closer to death's door and much more safely in general, and probably much more cheaply. One would expect that subsequent generations of these therapies would move in that direction.
Your foundation is working on an initiative requiring $50 million in funding—
Well, if we had $50 million per year in funding, we could go about three times faster than we are on $5 million per year.
And you're looking at a 2021 timeframe to start human trials?
That's approximate. Remember, because we accumulate in the body so many different types of damage, that means we have many different types of therapy to repair that damage. And of course, each of those types has to be developed independently. It's very much a divide and conquer therapy. The therapies interact with each other to some extent; the repair of one type of damage may slow down the creation of another type of damage, but still that's how it's going to be.
And some of these therapies are much easier to implement than others. The easier components of what we need to do are already in clinical trials—stem cell therapies especially, and immunotherapy against amyloid in the brain, for example. Even in phase III clinical trials in some cases. So when I talk about a timeframe like 2021, or early 20s shall we say, I'm really talking about the most difficult components.
What recent strides are you most excited about?
Looking back over the past couple of years, I'm particularly proud of the successes we've had in the very most difficult areas. If you go through the 7 components of SENS, there are two that have absolutely been stuck in a rut and have gotten nowhere for 15 to 20 years, and we basically fixed that in both cases. We published two years ago in Science magazine that essentially showed a way forward against the stiffening of the extracellular matrix, which is responsible for things like wrinkles and hypertension. And then a year ago, we published a real breakthrough paper with regard to placing copies of the mitochondria DNA in the nuclear DNA modified in such a way that they still work, which is an idea that had been around for 30 years; everyone had given up on it, some a long time ago, and we basically revived it.
A slide presented by Aubrey de Grey, referencing his collaboration with Mike West at AgeX, showing the 7 types of damage that he believes must be repaired to end aging.
(Courtesy Kira Peikoff)
That's exciting. What do you think are the biggest barriers to defeating aging today: the technological challenges, the regulatory framework, the cost, or the cultural attitude of the "pro-aging" trance?
One can't really address those independently of each other. The technological side is one thing; it's hard, but we know where we're going, we've got a plan. The other ones are very intertwined with each other. A lot of people are inclined to say, the regulatory hurdle will be completely insurmountable, plus people don't recognize aging as a disease, so it's going to be a complete nonstarter. I think that's nonsense. And the reason is because the cultural attitudes toward all of this are going to be completely turned upside down before we have to worry about the regulatory hurdles. In other words, they're going to be turned upside down by sufficiently promising results in the lab, in mice. Once we get to be able to rejuvenate actually old mice really well so they live substantially longer than they otherwise would have done, in a healthy state, everyone's going to know about it and everyone's going to demand – it's not going to be possible to get re-elected unless you have a manifesto commitment to turn the FDA completely upside down and make sure this happens without any kind of regulatory obstacle.
I've been struggling away all these years trying to bring little bits of money in the door, and the reason I have is because of the skepticism as to regards whether this could actually work, combined with the pro-aging trance, which is a product of the skepticism – people not wanting to get their hopes up, so finding excuses about aging being a blessing in disguise, so they don't have to think about it. All of that will literally disintegrate pretty much overnight when we have the right kind of sufficiently impressive progress in the lab. Therefore, the availability of money will also [open up]. It's already cracking: we're already seeing the beginnings of the actual rejuvenation biotechnology industry that I've been talking about with a twinkle in my eye for some years.
"For humans, a 50-50 chance would be twenty years at this point, and there's a 10 percent chance that we won't get there for a hundred years."
Why do you think the culture is starting to shift?
There's no one thing yet. There will be that tipping point I mentioned, perhaps five years from now when we get a real breakthrough, decisive results in mice that make it simply impossible to carry on being fatalistic about all this. Prior to that, what we're already seeing is the impact of sheer old-school repeat advertising—me going out there, banging away and saying the same fucking thing again and again, and nobody saying anything that persuasively knocks me down. … And it's also the fact that we are making incremental amounts of progress, not just ourselves, but the scientific community generally. It has become incrementally more plausible that what I say might be true.
I'm sure you hate getting the timeline question, but if we're five years away from this breakthrough in mice, it's hard to resist asking—how far is that in terms of a human cure?
When I give any kind of timeframes, the only real care I have to take is to emphasize the variance. In this case I think we have got a 50-50 chance of getting to that tipping point in mice within five years from now, certainly it could be 10 or 15 years if we get unlucky. Similarly, for humans, a 50-50 chance would be twenty years at this point, and there's a 10 percent chance that we won't get there for a hundred years.
"I don't get people coming to me saying, well I don't think medicine for the elderly should be done because if it worked it would be a bad thing. People like to ignore this contradiction."
What would you tell skeptical people are the biggest benefits of a very long-lived population?
Any question about the longevity of people is the wrong question. Because the longevity that people fixate about so much will only ever occur as a side effect of health. However long ago you were born or however recently, if you're sick, you're likely to die fairly soon unless we can stop you being sick. Whereas if you're healthy, you're not. So if we do as well as we think we can do in terms of keeping people healthy and youthful however long ago they were born, then the side effect in terms of longevity and life expectancy is likely to be very large. But it's still a side effect, so the way that people actually ought to be—in fact have a requirement to be—thinking, is about whether they want people to be healthy.
Now I don't get people coming to me saying, well I don't think medicine for the elderly should be done because if it worked it would be a bad thing. People like to ignore this contradiction, they like to sweep it under the carpet and say, oh yeah, aging is totally a good thing.
People will never actually admit to the fact that what they are fundamentally saying is medicine for the elderly, if it actually works, would be bad, but still that is what they are saying.
Shifting gears a bit, I'm curious to find out which other radical visionaries in science and tech today you most admire?
Fair question. One is Mike West. I have the great privilege that I now work for him part-time with Age X. I have looked up to him very much for the past ten years, because what he did over the past 20 years starting with Geron is unimaginable today. He was working in an environment where I would not have dreamt of the possibility of getting any private money, any actual investment, in something that far out, that far ahead of its time, and he did it, again and again. It's insane what he managed to do.
What about someone like Elon Musk?
Sure, he's another one. He is totally impervious to the caution and criticism and conservatism that pervades humanity, and he's getting on making these bloody self-driving cars, space tourism, and so on, making them happen. He's thinking just the way I'm thinking really.
"You can just choose how frequently and how thoroughly you repair the damage. And you can make a different choice next time."
You famously said ten years ago that you think the first person to live to 1000 is already alive. Do you think that's still the case?
Definitely, yeah. I can't see how it could not be. Again, it's a probabilistic thing. I said there's at least a 10 percent chance that we won't get to what I call Longevity Escape Velocity for 100 years and if that's true, then the statement about 1000 years being alive already is not going to be the case. But for sure, I believe that the beneficiaries of what we may as well call SENS 1.0, the point where we get to LEV, those people are exceptionally unlikely ever to suffer from any kind of ill health correlated with their age. Because we will never fall below Longevity Escape Velocity once we attain it.
Could someone who was just born today expect—
I would say people in middle age now have a fair chance. Remember – a 50/50 chance of getting to LEV within 20 years, and when you get there, you don't just stay at biologically 70 or 80, you are rejuvenated back to biologically 30 or 40 and you stay there, so your risk of death each year is not related to how long ago you were born, it's the same as a young adult. Today, that's less than 1 in 1000 per year, and that number is going to go down as we get self-driving cars and all that, so actually 1000 is a very conservative number.
So you would be able to choose what age you wanted to go back to?
Oh sure, of course, it's just like a car. What you're doing is you're repairing damage, and the damage is still being created by the body's metabolism, so you can just choose how frequently and how thoroughly you repair the damage. And you can make a different choice next time.
What would be your perfect age?
I have no idea. That's something I don't have an opinion about, because I could change it whenever I like.
Kira Peikoff was the editor-in-chief of Leaps.org from 2017 to 2021. As a journalist, her work has appeared in The New York Times, Newsweek, Nautilus, Popular Mechanics, The New York Academy of Sciences, and other outlets. She is also the author of four suspense novels that explore controversial issues arising from scientific innovation: Living Proof, No Time to Die, Die Again Tomorrow, and Mother Knows Best. Peikoff holds a B.A. in Journalism from New York University and an M.S. in Bioethics from Columbia University. She lives in New Jersey with her husband and two young sons. Follow her on Twitter @KiraPeikoff.
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.”