With Lab-Grown Chicken Nuggets, Dumplings, and Burgers, Futuristic Foods Aim to Seem Familiar
Sandhya Sriram is at the forefront of the expanding lab-grown meat industry in more ways than one.
"[Lab-grown meat] is kind of a brave new world for a lot of people, and food isn't something people like being brave about."
She's the CEO and co-founder of one of fewer than 30 companies that is even in this game in the first place. Her Singapore-based company, Shiok Meats, is the only one to pop up in Southeast Asia. And it's the only company in the world that's attempting to grow crustaceans in a lab, starting with shrimp. This spring, the company debuted a prototype of its shrimp, and completed a seed funding round of $4.6 million.
Yet despite all of these wins, Sriram's own mother won't try the company's shrimp. She's a staunch, lifelong vegetarian, adhering to a strict definition of what that means.
"[Lab-grown meat] is kind of a brave new world for a lot of people, and food isn't something people like being brave about. It's really a rather hard-wired thing," says Kate Krueger, the research director at New Harvest, a non-profit accelerator for cellular agriculture (the umbrella field that studies how to grow animal products in the lab, including meat, dairy, and eggs).
It's so hard-wired, in fact, that trends in food inform our species' origin story. In 2017, a group of paleoanthropologists caused an upset when they unearthed fossils in present day Morocco showing that our earliest human ancestors lived much further north and 100,000 years earlier than expected -- the remains date back 300,000 years. But the excavation not only included bones and tools, it also painted a clear picture of the prevailing menu at the time: The oldest humans were apparently chomping on tons of gazelle, as well as wildebeest and zebra when they could find them, plus the occasional seasonal ostrich egg.
These were people with a diet shaped by available resources, but also by the ability to cook in the first place. In his book Catching Fire: How Cooking Made Us Human, Harvard primatologist Richard Wrangam writes that the very thing that allowed for the evolution of Homo sapiens was the ability to transform raw ingredients into edible nutrients through cooking.
Today, our behavior and feelings around food are the product of local climate, crops, animal populations, and tools, but also religion, tradition, and superstition. So what happens when you add science to the mix? Turns out, we still trend toward the familiar. The innovations in lab-grown meat that are picking up the most steam are foods like burgers, not meat chips, and salmon, not salmon-cod-tilapia hybrids. It's not for lack of imagination, it's because the industry's practitioners know that a lifetime of food memories is a hard thing to contend with. So far, the nascent lab-grown meat industry is not so much disrupting as being shaped by the oldest culture we have.
Not a single piece of lab-grown meat is commercially available to consumers yet, and already so much ink has been spilled debating if it's really meat, if it's kosher, if it's vegetarian, if it's ethical, if it's sustainable. But whether or not the industry succeeds and sticks around is almost moot -- watching these conversations and innovations unfold serves as a mirror reflecting back who we are, what concerns us, and what we aspire to.
The More Things Change, the More They Stay the Same
The building blocks for making lab-grown meat right now are remarkably similar, no matter what type of animal protein a company is aiming to produce.
First, a small biopsy, about the size of a sesame seed, is taken from a single animal. Then, the muscle cells are isolated and added to a nutrient-dense culture in a bioreactor -- the same tool used to make beer -- where the cells can multiply, grow, and form muscle tissue. This tissue can then be mixed with additives like nutrients, seasonings, binders, and sometimes colors to form a food product. Whether a company is attempting to make chicken, fish, beef, shrimp, or any other animal protein in a lab, the basic steps remain similar. Cells from various animals do behave differently, though, and each company has its own proprietary techniques and tools. Some, for example, use fetal calf serum as their cell culture, while others, aiming for a more vegan approach, eschew it.
"New gadgets feel safest when they remind us of other objects that we already know."
According to Mark Post, who made the first lab-grown hamburger at Maastricht University in the Netherlands in 2013, the cells of just one cow can give way to 175 million four-ounce burgers. By today's available burger-making methods, you'd need to slaughter 440,000 cows for the same result. The projected difference in the purely material efficiency between the two systems is staggering. The environmental impact is hard to predict, though. Some companies claim that their lab-grown meat requires 99 percent less land and 96 percent less water than traditional farming methods -- and that rearing fewer cows, specifically, would reduce methane emissions -- but the energy cost of running a lab-grown-meat production facility at an industrial scale, especially as compared to small-scale, pasture-raised farming, could be problematic. It's difficult to truly measure any of this in a burgeoning industry.
At this point, growing something like an intact shrimp tail or a marbled steak in a lab is still a Holy Grail. It would require reproducing the complex musculo-skeletal and vascular structure of meat, not just the cellular basis, and no one's successfully done it yet. Until then, many companies working on lab-grown meat are perfecting mince. Each new company's demo of a prototype food feels distinctly regional, though: At the Disruption in Food and Sustainability Summit in March, Shiok (which is pronounced "shook," and is Singaporean slang for "very tasty and delicious") first shared a prototype of its shrimp as an ingredient in siu-mai, a dumpling of Chinese origin and a fixture at dim sum. JUST, a company based in the U.S., produced a demo chicken nugget.
As Jean Anthelme Brillat-Savarin, the 17th century founder of the gastronomic essay, famously said, "Show me what you eat, and I'll tell you who you are."
For many of these companies, the baseline animal protein they are trying to innovate also feels tied to place and culture: When meat comes from a bioreactor, not a farm, the world's largest exporter of seafood could be a landlocked region, and beef could be "reared" in a bayou, yet the handful of lab-grown fish companies, like Finless Foods and BlueNalu, hug the American coasts; VOW, based in Australia, started making lab-grown kangaroo meat in August; and of course the world's first lab-grown shrimp is in Singapore.
"In the U.S., shrimps are either seen in shrimp cocktail, shrimp sushi, and so on, but [in Singapore] we have everything from shrimp paste to shrimp oil," Sriram says. "It's used in noodles and rice, as flavoring in cup noodles, and in biscuits and crackers as well. It's seen in every form, shape, and size. It just made sense for us to go after a protein that was widely used."
It's tempting to assume that innovating on pillars of cultural significance might be easier if the focus were on a whole new kind of food to begin with, not your popular dim sum items or fast food offerings. But it's proving to be quite the opposite.
"That could have been one direction where [researchers] just said, 'Look, it's really hard to reproduce raw ground beef. Why don't we just make something completely new, like meat chips?'" says Mike Lee, co-founder and co-CEO of Alpha Food Labs, which works on food innovation more broadly. "While that strategy's interesting, I think we've got so many new things to explain to people that I don't know if you want to also explain this new format of food that you've never, ever seen before."
We've seen this same cautious approach to change before in other ways that relate to cooking. Perhaps the most obvious example is the kitchen range. As Bee Wilson writes in her book Consider the Fork: A History of How We Cook and Eat, in the 1880s, convincing ardent coal-range users to switch to newfangled gas was a hard sell. To win them over, inventor William Sugg designed a range that used gas, but aesthetically looked like the coal ones already in fashion at the time -- and which in some visual ways harkened even further back to the days of open-hearth cooking. Over time, gas range designs moved further away from those of the past, but the initial jump was only made possible through familiarity. There's a cleverness to meeting people where they are.
"New gadgets feel safest when they remind us of other objects that we already know," writes Wilson. "It is far harder to accept a technology that is entirely new."
Maybe someday we won't want anything other than meat chips, but not today.
Measuring Success
A 2018 Gallup poll shows that in the U.S., rates of true vegetarianism and veganism have been stagnant for as long as they've been measured. When the poll began in 1999, six percent of Americans were vegetarian, a number that remained steady until 2012, when the number dropped one point. As of 2018, it remained at five percent.
In 2012, when Gallup first measured the percentage of vegans, the rate was two percent. By 2018 it had gone up just one point, to three percent. Increasing awareness of animal welfare, health, and environmental concerns don't seem to be incentive enough to convince Americans, en masse, to completely slam the door on a food culture characterized in many ways by its emphasis on traditional meat consumption.
"A lot of consumers get over the ick factor when you tell them that most of the food that you're eating right now has entered the lab at some point."
Wilson writes that "experimenting with new foods has always been a dangerous business. In the wild, trying out some tempting new berries might lead to death. A lingering sense of this danger may make us risk-averse in the kitchen."
That might be one psychologically deep-seated reason that Americans are so resistant to ditch meat altogether. But a middle ground is emerging with a rise in flexitarianism, which aims to reduce reliance on traditional animal products. "Americans are eager to include alternatives to animal products in their diets, but are not willing to give up animal products completely," the same 2018 Gallup poll reported. This may represent the best opportunity for lab-grown meat to wedge itself into the culture.
Quantitatively predicting a population's willingness to try a lab-grown version of its favorite protein is proving a hard thing to measure, however, because it's still science fiction to a regular consumer. Measuring popular opinion of something that doesn't really exist yet is a dubious pastime.
In 2015, University of Wisconsin School of Public Health researchers Linnea Laestadius and Mark Caldwell conducted a study using online comments on articles about lab-grown meat to suss out public response to the food. The results showed a mostly negative attitude, but that was only two years into a field that is six years old today. Already public opinion may have shifted.
Shiok Meat's Sriram and her co-founder Ka Yi Ling have used online surveys to get a sense of the landscape, but they also take a more direct approach sometimes. Every time they give a public talk about their company and their shrimp, they poll their audience before and after the talk, using the question, "How many of you are willing to try, and pay, to eat lab-grown meat?"
They consistently find that the percentage of people willing to try goes up from 50 to 90 percent after hearing their talk, which includes information about the downsides of traditional shrimp farming (for one thing, many shrimp are raised in sewage, and peeled and deveined by slaves) and a bit of information about how lab-grown animal protein is being made now. I saw this pan out myself when Ling spoke at a New Harvest conference in Cambridge, Massachusetts in July.
"A lot of consumers get over the ick factor when you tell them that most of the food that you're eating right now has entered the lab at some point," Sriram says. "We're not going to grow our meat in the lab always. It's in the lab right now, because we're in R&D. Once we go into manufacturing ... it's going to be a food manufacturing facility, where a lot of food comes from."
The downside of the University of Wisconsin's and Shiok Meat's approach to capturing public opinion is that they each look at self-selecting groups: Online commenters are often fueled by a need to complain, and it's likely that anyone attending a talk by the co-founders of a lab-grown meat company already has some level of open-mindedness.
So Sriram says that she and Ling are also using another method to assess the landscape, and it's somewhere in the middle. They've been watching public responses to the closest available product to lab-grown meat that's on the market: Impossible Burger. As a 100 percent plant-based burger, it's not quite the same, but this bleedable, searable patty is still very much the product of science and laboratory work. Its remarkable similarity to beef is courtesy of yeast that have been genetically engineered to contain DNA from soy plant roots, which produce a protein called heme as they multiply. This heme is a plant-derived protein that can look and act like the heme found in animal muscle.
So far, the sciencey underpinnings of the burger don't seem to be turning people off. In just four years, it's already found its place within other American food icons. It's readily available everywhere from nationwide Burger Kings to Boston's Warren Tavern, which has been in operation since 1780, is one of the oldest pubs in America, and is even named after the man who sent Paul Revere on his midnight ride. Some people have already grown so attached to the Impossible Burger that they will actually walk out of a restaurant that's out of stock. Demand for the burger is outpacing production.
"Even though [Impossible] doesn't consider their product cellular agriculture, it's part of a spectrum of innovation," Krueger says. "There are novel proteins that you're not going to find in your average food, and there's some cool tech there. So to me, that does show a lot of willingness on people's part to think about trying something new."
The message for those working on animal-based lab-grown meat is clear: People will accept innovation on their favorite food if it tastes good enough and evokes the same emotional connection as the real deal.
"How people talk about lab-grown meat now, it's still a conversation about science, not about culture and emotion," Lee says. But he's confident that the conversation will start to shift in that direction if the companies doing this work can nail the flavor memory, above all.
And then proving how much power flavor lords over us, we quickly derail into a conversation about Doritos, which he calls "maniacally delicious." The chips carry no health value whatsoever and are a native product of food engineering and manufacturing — just watch how hard it is for Bon Appetit associate food editor Claire Saffitz to try and recreate them in the magazine's test kitchen — yet devotees remain unfazed and crunch on.
"It's funny because it shows you that people don't ask questions about how [some foods] are made, so why are they asking so many questions about how lab-grown meat is made?" Lee asks.
For all the hype around Impossible Burger, there are still controversies and hand-wringing around lab-grown meat. Some people are grossed out by the idea, some people are confused, and if you're the U.S. Cattlemen's Association (USCA), you're territorial. Last year, the group sent a petition to the USDA to "exclude products not derived directly from animals raised and slaughtered from the definition of 'beef' and meat.'"
"I think we are probably three or four big food safety scares away from everyone, especially younger generations, embracing lab-grown meat as like, 'Science is good; nature is dirty, and can kill you.'"
"I have this working hypothesis that if you look at the nation in 50-year spurts, we revolve back and forth between artisanal, all-natural food that's unadulterated and pure, and food that's empowered by science," Lee says. "Maybe we've only had one lap around the track on that, but I think we are probably three or four big food safety scares away from everyone, especially younger generations, embracing lab-grown meat as like, 'Science is good; nature is dirty, and can kill you.'"
Food culture goes beyond just the ingredients we know and love — it's also about how we interact with them, produce them, and expect them to taste and feel when we bite down. We accept a margin of difference among a fast food burger, a backyard burger from the grill, and a gourmet burger. Maybe someday we'll accept the difference between a burger created by killing a cow and a burger created by biopsying one.
Looking to the Future
Every time we engage with food, "we are enacting a ritual that binds us to the place we live and to those in our family, both living and dead," Wilson writes in Consider the Fork. "Such things are not easily shrugged off. Every time a new cooking technology has been introduced, however useful … it has been greeted in some quarters with hostility and protestations that the old ways were better and safer."
This is why it might be hard for a vegetarian mother to try her daughter's lab-grown shrimp, no matter how ethically it was produced or how awe-inspiring the invention is. Yet food cultures can and do change. "They're not these static things," says Benjamin Wurgaft, a historian whose book Meat Planet: Artificial Flesh and the Future of Food comes out this month. "The real tension seems to be between slow change and fast change."
In fact, the very definition of the word "meat" has never exclusively meant what the USCA wants it to mean. Before the 12th century, when it first appeared in Old English as "mete," it wasn't very specific at all and could be used to describe anything from "nourishment," to "food item," to "fodder," to "sustenance." By the 13th century it had been narrowed down to mean "flesh of warm-blooded animals killed and used as food." And yet the British mincemeat pie lives on as a sweet Christmas treat full of -- to the surprise of many non-Brits -- spiced, dried fruit. Since 1901, we've also used this word with ease as a general term for anything that's substantive -- as in, "the meat of the matter." There is room for yet more definitions to pile on.
"The conversation [about lab-ground meat] has changed remarkably in the last six years," Wurgaft says. "It has become a conversation about whether or not specific companies will bring a product to market, and that's a really different conversation than asking, 'Should we produce meat in the lab?'"
As part of the field research for his book, Wurgaft visited the Rijksmuseum Boerhaave, a Dutch museum that specializes in the history of science and medicine. It was 2015, and he was there to see an exhibit on the future of food. Just two years earlier, Mark Post had made that first lab-grown hamburger about a two-and-a-half hour drive south of the museum. When Wurgaft arrived, he found the novel invention, which Post had donated to the museum, already preserved and served up on a dinner plate, the whole outfit protected by plexiglass.
"They put this in the exhibit as if it were already part of the historical records, which to a historian looked really weird," Wurgaft says. "It looked like somebody taking the most recent supercomputer and putting it in a museum exhibit saying, 'This is the supercomputer that changed everything,' as if you were already 100 years in the future, looking back."
It seemed to symbolize an effort to codify a lab-grown hamburger as a matter of Dutch pride, perhaps someday occupying a place in people's hearts right next to the stroopwafel.
"Who's to say that we couldn't get a whole school of how to cook with lab-grown meat?"
Lee likes to imagine that part of the legacy of lab-grown meat, if it succeeds, will be to inspire entirely new fads in cooking -- a step beyond ones like the crab-filled avocado of the 1960s or the pesto of the 1980s in the U.S.
"[Lab-grown meat] is inherently going to be a different quality than anything we've done with an animal," he says. "Look at every cut [of meat] on the sphere today -- each requires a slightly different cooking method to optimize the flavor of that cut. Who's to say that we couldn't get a whole school of how to cook with lab-grown meat?"
At this point, most of us have no way of trying lab-grown meat. It remains exclusively available through sometimes gimmicky demos reserved for investors and the media. But Wurgaft says the stories we tell about this innovation, the articles we write, the films we make, and yes, even the museum exhibits we curate, all hold as much cultural significance as the product itself might someday.
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.”