Six Questions about the Kids' COVID Vaccine, Answered by an Infectious Disease Doctor
I enthusiastically support the vaccination against COVID for children aged 5-11 years old. As an infectious disease doctor who took care of hundreds of COVID-19 patients over the past 20 months, I have seen the immediate and long-term consequences of COVID-19 on patients – and on their families. As a father of two daughters, I have lived through the fear and anxiety of protecting my kids at all cost from the scourges of the pandemic and worried constantly about bringing the virus home from work.
It is imperative that we vaccinate as many children in the community as possible. There are several reasons why. First children do get sick from COVID-19. Over the course of the pandemic in the U.S, more than 2 million children aged 5-11 have become infected, more than 8000 have been hospitalized, and more than 100 have died, making COVID one of the top 10 causes of pediatric deaths in this age group over the past year. Children are also susceptible to chronic consequences of COVID such as long COVID and multisystem inflammatory syndrome in children (MIS-C). Most studies demonstrate that 10-30% of children will develop chronic symptoms following COVID-19. These include complaints of brain fog, fatigue, trouble breathing, fever, headache, muscle and joint pains, abdominal pain, mood swings and even psychiatric disorders. Symptoms typically last from 4-8 weeks in children, with some reporting symptoms that persist for many months.
Second, children are increasingly recognized as vectors who can bring infection into the house, potentially transmitting infection to vulnerable household members. Finally, we have all seen the mayhem that results when one child in the classroom becomes infected with COVID and the other students get sent home to quarantine – across the U.S., more than 2000 schools have been affected this way.
We now have an extraordinarily effective vaccine with more than 90 percent efficacy at preventing symptomatic infection. Vaccinating children will boost our countrywide vaccination rate which is trailing many countries after an early start. Nevertheless, there are still many questions and concerns that parents have as the vaccine gets rolled out. I will address six of them here.
"Novel Vaccine Technology"
Even though this is a relatively new vaccine, the technology is not new. Scientists had worked on mRNA vaccines for decades prior to the COVID mRNA vaccine breakthrough. Furthermore, experience with the Pfizer COVID vaccine is rapidly growing. By now it has been more than a year and a half since the Pfizer trials began in March 2020, and more than 7 billion doses have already been administered globally, including in 13.7 million adolescents in the U.S. alone.
"Will This Vaccine Alter My Child's DNA?"
No. This is not how mRNA works. DNA is present in the cell's nucleus. The mRNA only stays in the outside cytoplasm, gets destroyed and never enters the inner sanctum of the nucleus. Furthermore, for the mRNA to be ever integrated into DNA, it requires a special enzyme called reverse transcriptase which humans don't have. Proteins (that look like the spike proteins on SARS-CoV-2) are made directly from this mRNA message without involvement of our DNA at any time. Pieces of spike proteins get displayed on the outside of our cells and our body makes protective antibodies that then protects us handily against the future real virus if it were ever to enter our (or our children's) bodies. Our children's DNA or genes can never be affected by an mRNA vaccine.
"Lack of Info on Long-Term Side Effects"
Unlike medications that are taken daily or periodically and can build up over time, the mRNA in the Pfizer vaccine is evanescent. It literally is just the messenger (that is what the "m" in mRNA stands for) and the messenger quickly disappears. mRNA is extremely fragile and easily inactivated – that's why we need to encase it in a special fatty bubble and store the vaccines at extremely cold temperatures. Our cells break down and destroy the mRNA within a few days after receiving the instructions to make the virus spike proteins. The presence of these fragments of the virus (note this is not "live" virus) prompts our immune system to generate protective antibodies to the real thing. Our bodies break down mRNA all the time in normal cellular processes – this is nothing new.
What the transience of the delivery system means is that most of the effects of the mRNA vaccines are expected to be more immediate (sore arm, redness at the site, fever, chills etc.), with no long-term side effects anticipated. A severe allergic response has been reported to occur in some generally within the first 15 minutes, is very rare, and everyone gets observed for that as part of standard vaccine administration. Even with the very uncommon complication of myocarditis (inflammation of the heart muscle) and pericarditis (inflammation of the lining of the heart) seen primarily in young men under the age of 30 following mRNA vaccines, these typically happen within days to 2 weeks and many return to work or school in days. In the 70-year history of pediatric (and adult vaccines), dangerous complications happen in the first two months. There have been millions of adolescents as young as 12 years and thousands in the initial trial of children aged 5-11 who have already received the vaccine and are well beyond the two-month period of observation. There is no biological reason to believe that younger children will have a different long-term side effect profile compared to adolescents or adults.
"Small Sample Size in Kids and the Trial Design"
Although the Pfizer trial in children aged 5-11 was relatively small, it was big enough to give us statistical confidence in assessing safety and efficacy outcomes. Scientists spend a lot of time determining the right sample size of a study during the design phase. On one hand, you want to conduct the study efficiently so that resources are used in a cost-effective way and that you get a timely answer, especially in a fast-moving pandemic. On the other hand, you want to make sure you have enough sample size so that you can answer the question confidently as to whether the intervention works and whether there are adverse effects. The more profound the effect size of the intervention (in this case the vaccine), the fewer the numbers of children needed in the trials.
Statistics help investigators determine whether the results seen would have appeared by chance or not. In this case, the effect was real and impressive. Over 3,000 children around the world have received the vaccines through the trials alone with no serious side effects detected. The first press release reported that the immune response in children aged 5-11 was similar (at one-third the vaccine dose) to the response in the comparator group aged 16-25 years old. Extrapolating clinical efficacy results from immune response measurements ("immunobridging" study) would already have been acceptable if this was the only data. This is a standard trial design for many pediatric vaccines. Vaccines are first tested in the lab, followed by animals then adults. Only when deemed safe in adults and various regulatory bodies have signed off, do the pediatric vaccine trials commence.
Because children's immune systems and bodies are in a constant state of development, the vaccines must be right-sized. Investigators typically conduct "age de-escalation" studies in various age groups. The lowest dose is first tried so see if that is effective, then the dose is increased gradually as needed. Immune response is the easiest, safest and most efficient way to test the efficacy of pediatric vaccines. This is a typical size and design of a childhood vaccine seeking regulatory approval. There is no reason to think that the clinical efficacy would be any different in children vs. adults for a given antibody response, given the experience already in the remainder of the population, including older children and adolescents. Although this was primarily designed as an "immunobridging" study, the initial immunologic response data was followed by real clinical outcomes in this population. Reporting on the outcomes of 2,268 children in the randomized controlled trial, the vaccine was 90.7% effective at preventing symptomatic infection.
"Fear of Myocarditis"
Myocarditis (inflammation of the heart muscle) and pericarditis (inflammation of the lining of the heart) have been associated with receipt of the mRNA vaccines, particularly among male adolescents and young adults, typically within a few days after receiving the second dose. But this is very rare. For every million vaccine recipients, you would expect 41 cases in males, and 4 cases in females aged 12-29 years-old. The risk in older age groups is substantially lower. It is important to recognize that the risk of myocarditis associated with COVID is substantially higher. Patients present with new chest pain, shortness of breath, or palpitations after receiving an mRNA vaccine (more common after the second dose). But outcomes are good if associated with the vaccine. Most respond well to treatment and resolve symptoms within a week. There have been no deaths associated with vaccine-associated myocarditis.
In contrast, COVID-associated myocarditis has been associated with more severe cases as well as other complications including chronic symptoms of long COVID. The risk of myocarditis is likely related to vaccine dose, so the fact that one-third the dose of the vaccine will be used in the 5-11 year-olds is expected to correspond to a lower risk of myocarditis. At the lower dose given to younger kids, there has been a lower incidence of adverse effects reported compared to older children and adults who received the full dose. In addition, baseline rates of myocarditis not associated with vaccination are much lower in children ages 5-11 years than in older children, so the same may hold true for vaccine-associated myocarditis cases. This is because myocarditis is associated with sex hormones (particularly testosterone) that surge during puberty. In support of this, the incidence of vaccine-associated myocarditis is lower in 12–15-year-old boys, compared to those who were older than 16 years old. There were no cases of myocarditis reported in the experience to date of 5–11-year-old children in the trials, although the trial was too small to pick up on such a rare effect.
"Optimal Dose Spacing Interval: Longer Than 3 Weeks?"
There is a biologic basis for increasing the interval between vaccine doses in general. Priming the immune system with the first shot and then waiting gives the second shot a better chance of prompting a secondary immune reaction that results in a more durable response (with more T cell driven immune memory). One study from the U.K. showed that the antibody response in people over 80 was more than 3 times higher if they delayed the second dose to after 12 weeks for the Pfizer vaccine instead of the 3 weeks studied in trials. In a study of 503 British health care workers, there were twice as many neutralizing antibodies produced in a longer interval group (6-14 weeks) versus a shorter interval group (3-4 weeks) between doses. However, the safety and efficacy with longer intervals has not been evaluated in the pediatric or other COVID vaccine trials.
In the U.S., the C.D.C. reported that 88 percent of counties are at a "high" or "substantial" level of community transmission. Also, Europe is already experiencing a winter surge of infections that may predict more U.S. winter cases as international travel reopens. During a time of high community virus burden with a highly transmissible Delta variant, relying on one dose of vaccine for several more weeks until the second may leave many more susceptible to infection while waiting. One study from England showed that one dose of the Pfizer vaccine was only 33% protective against symptomatic Delta infection in contrast to 50% for the Alpha variant in adults. There has been no corollary information in children but we would expect less protection in general from one vaccine dose vs. two. This is a particularly important issue with the upcoming holiday season when an increased number of families will travel. Some countries such as the U.K. and Norway have proceeded with only offering older than 12 year-olds one dose of vaccine rather than two, but this was before the current European surge which may change the risk-benefit calculus. There are no plans to only offer one vaccine dose in the U.S. at this time. However a lower dose of the vaccine will likely be studied in the future for adolescents aged 12-15.
For parents worried about the potential risk of adverse effects of two doses of vaccines in their children, it is reasonable to wait 6-12 weeks for the second shot but it all depends on your risk-benefit calculus. There is biological plausibility to pursue this strategy. Although there is no pediatric-specific data to draw from, a longer interval may lengthen immune memory and potentially decrease the risk of myocarditis, particularly in boys. There may only be partial benefit in eliciting protective antibodies after one vaccine dose but only 2-4% of children are hospitalized with COVID once infected, with risk of severe illness increasing if they have comorbidities.
There are also some data indicating that 40% of children have already been exposed to infection naturally and may not need further protection after one shot. However, this percentage is likely a large overestimation given the way the data was collected. Using antibody tests to ascertain previous infection in children may be problematic for several reasons: uncertainty regarding duration of protection, variability in symptoms in children with most having very mild symptoms, and the lack of standardization of antibody tests in general. Overall, if the child has medical comorbidities such as diabetes, parents are planning to travel with their children, if local epidemiology shows increasing cases, and if there are elderly or immunocompromised individuals in the household, I would vaccinate children with two doses as per the original recommended schedule.
Bottom line: Given the time of the year and circulating Delta, I would probably stick with the recommended 3-week interval between doses for now for most children. But if parents choose a longer interval between the first and second dose for their children, I wouldn't worry too much about it. Better to be vaccinated - even if slowly, over time -- than not at all.
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.”