Can You Trust Your Gut for Food Advice?
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.
I recently got on the scale to weigh myself, thinking I've got to eat better. With so many trendy diets today claiming to improve health, from Keto to Paleo to Whole30, it can be confusing to figure out what we should and shouldn't eat for optimal nutrition.
A number of companies are now selling the concept of "personalized" nutrition based on the genetic makeup of your individual gut bugs.
My next thought was: I've got to lose a few pounds.
Consider a weird factoid: In addition to my fat, skin, bone and muscle, I'm carrying around two or three pounds of straight-up bacteria. Like you, I am the host to trillions of micro-organisms that live in my gut and are collectively known as my microbiome. An explosion of research has occurred in the last decade to try to understand exactly how these microbial populations, which are unique to each of us, may influence our overall health and potentially even our brains and behavior.
Lots of mysteries still remain, but it is established that these "bugs" are crucial to keeping our body running smoothly, performing functions like stimulating the immune system, synthesizing important vitamins, and aiding digestion. The field of microbiome science is evolving rapidly, and a number of companies are now selling the concept of "personalized" nutrition based on the genetic makeup of your individual gut bugs. The two leading players are Viome and DayTwo, but the landscape includes the newly launched startup Onegevity Health and others like Thryve, which offers customized probiotic supplements in addition to dietary recommendations.
The idea has immediate appeal – if science could tell you exactly what to make for lunch and what to avoid, you could forget about the fad diets and go with your own bespoke food pyramid. Wondering if the promise might be too good to be true, I decided to perform my own experiment.
Last fall, I sent the identical fecal sample to both Viome (I paid $425, but the price has since dropped to $299) and DayTwo ($349). A couple of months later, both reports finally arrived, and I eagerly opened each app to compare their recommendations.
First, I examined my results from Viome, which was founded in 2016 in Cupertino, Calif., and declares without irony on its website that "conflicting food advice is now obsolete."
I learned I have "average" metabolic fitness and "average" inflammatory activity in my gut, which are scores that the company defines based on a proprietary algorithm. But I have "low" microbial richness, with only 62 active species of bacteria identified in my sample, compared with the mean of 157 in their test population. I also received a list of the specific species in my gut, with names like Lactococcus and Romboutsia.
But none of it meant anything to me without actionable food advice, so I clicked through to the Recommendations page and found a list of My Superfoods (cranberry, garlic, kale, salmon, turmeric, watermelon, and bone broth) and My Foods to Avoid (chickpeas, kombucha, lentils, and rice noodles). There was also a searchable database of many foods that had been categorized for me, like "bell pepper; minimize" and "beef; enjoy."
"I just don't think sufficient data is yet available to make reliable personalized dietary recommendations based on one's microbiome."
Next, I looked at my results from DayTwo, which was founded in 2015 from research out of the Weizmann Institute of Science in Israel, and whose pitch to consumers is, "Blood sugar made easy. The algorithm diet personalized to you."
This app had some notable differences. There was no result about my metabolic fitness, microbial richness, or list of the species in my sample. There was also no list of superfoods or foods to avoid. Instead, the app encouraged me to build a meal by searching for foods in their database and combining them in beneficial ways for my blood sugar. Two slices of whole wheat bread received a score of 2.7 out of 10 ("Avoid"), but if combined with one cup of large curd cottage cheese, the score improved to 6.8 ("Limit"), and if I added two hard-boiled eggs, the score went up to 7.5 ("Good").
Perusing my list of foods with "Excellent" scores, I noticed some troubling conflicts with the other app. Lentils, which had been a no-no according to Viome, received high marks from DayTwo. Ditto for Kombucha. My purported superfood of cranberry received low marks. Almonds got an almost perfect score (9.7) while Viome told me to minimize them. I found similarly contradictory advice for foods I regularly eat, including navel oranges, peanuts, pork, and beets.
Contradictory dietary guidance that Kira Peikoff received from Viome (left) and DayTwo from an identical sample.
To be sure, there was some overlap. Both apps agreed on rice noodles (bad), chickpeas (bad), honey (bad), carrots (good), and avocado (good), among other foods.
But still, I was left scratching my head. Which set of recommendations should I trust, if either? And what did my results mean for the accuracy of this nascent field?
I called a couple of experts to find out.
"I have worked on the microbiome and nutrition for the last 20 years and I would be absolutely incapable of finding you evidence in the scientific literature that lentils have a detrimental effect based on the microbiome," said Dr. Jens Walter, an Associate Professor and chair for Nutrition, Microbes, and Gastrointestinal Health at the University of Alberta. "I just don't think sufficient data is yet available to make reliable personalized dietary recommendations based on one's microbiome. And even if they would have proprietary algorithms, at least one of them is not doing it right."
There is definite potential for personalized nutrition based on the microbiome, he said, but first, predictive models must be built and standardized, then linked to clinical endpoints, and tested in a large sample of healthy volunteers in order to enable extrapolations for the general population.
"It is mindboggling what you would need to do to make this work," he observed. "There are probably hundreds of relevant dietary compounds, then the microbiome has at least a hundred relevant species with a hundred or more relevant genes each, then you'd have to put all this together with relevant clinical outcomes. And there's a hundred-fold variation in that information between individuals."
However, Walter did acknowledge that the companies might be basing their algorithms on proprietary data that could potentially connect all the dots. I reached out to them to find out.
Amir Golan, the Chief Commercial Officer of DayTwo, told me, "It's important to emphasize this is a prediction, as the microbiome field is in a very early stage of research." But he added, "I believe we are the only company that has very solid science published in top journals and we can bring very actionable evidence and benefit to our uses."
He was referring to pioneering work out of the Weizmann Institute that was published in 2015 in the journal Cell, which logged the glycemic responses of 800 people in response to nearly 50,000 meals; adding information about the subjects' microbiomes enabled more accurate glycemic response predictions. Since then, Golan said, additional trials have been conducted, most recently with the Mayo Clinic, to duplicate the results, and other studies are ongoing whose results have not yet been published.
He also pointed out that the microbiome was merely one component that goes into building a client's profile, in addition to medical records, including blood glucose levels. (I provided my HbA1c levels, a measure of average blood sugar over the previous several months.)
"We are not saying we want to improve your gut microbiome. We provide a dynamic tool to help guide what you should eat to control your blood sugar and think about combinations," he said. "If you eat one thing, or with another, it will affect you in a different way."
Viome acknowledged that the two companies are taking very different approaches.
"DayTwo is primarily focused on the glycemic response," Naveen Jain, the CEO, told me. "If you can only eat butter for rest of your life, you will have no glycemic response but will probably die of a heart attack." He laughed. "Whereas we came from very different angle – what is happening inside the gut at a microbial level? When you eat food like spinach, how will that be metabolized in the gut? Will it produce the nutrients you need or cause inflammation?"
He said his team studied 1000 people who were on continuous glucose monitoring and fed them 45,000 meals, then built a proprietary data prediction model, looking at which microbes existed and how they actively broke down the food.
Jain pointed out that DayTwo sequences the DNA of the microbes, while Viome sequences the RNA – the active expression of DNA. That difference, in his opinion, is key to making accurate predictions.
"DNA is extremely stable, so when you eat any food and measure the DNA [in a fecal sample], you get all these false positives--you get DNA from plant food and meat, and you have no idea if those organisms are dead and simply transient, or actually exist. With RNA, you see what is actually alive in the gut."
More contradictory food advice from Viome (left) and DayTwo.
Note that controversy exists over how it is possible with a fecal sample to effectively measure RNA, which degrades within minutes, though Jain said that his company has the technology to keep RNA stable for fourteen days.
Viome's approach, Jain maintains, is 90 percent accurate, based on as-yet unpublished data; a patent was filed just last week. DayTwo's approach is 66 percent accurate according to the latest published research.
Natasha Haskey, a registered dietician and doctoral student conducting research in the field of microbiome science and nutrition, is skeptical of both companies. "We can make broad statements, like eat more fruits and vegetables and fiber, but when it comes to specific foods, the science is just not there yet," she said. "I think there is a future, and we will be doing that someday, but not yet. Maybe we will be closer in ten years."
Professor Walter wholeheartedly agrees with Haskey, and suggested that if people want to eat a gut-healthy diet, they should focus on beneficial oils, fruits and vegetables, fish, a variety of whole grains, poultry and beans, and limit red meat and cheese, as well as avoid processed meats.
"These services are far over the tips of their science skis," Arthur Caplan, the founding head of New York University's Division of Medical Ethics, said in an email. "We simply don't know enough about the gut microbiome, its fluctuations and variability from person to person to support general [direct-to-consumer] testing. This is simply premature. We need standards for accuracy, specificity, and sensitivity, plus mandatory competent counseling for all such testing. They don't exist. Neither should DTC testing—yet."
Meanwhile, it's time for lunch. I close out my Viome and DayTwo apps and head to the kitchen to prepare a peanut butter sandwich. My gut tells me I'll be just fine.
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.”