Indigenous wisdom plus honeypot ants could provide new antibiotics
Lina Zeldovich has written about science, medicine and technology for Popular Science, Smithsonian, National Geographic, Scientific American, Reader’s Digest, the New York Times and other major national and international publications. A Columbia J-School alumna, she has won several awards for her stories, including the ASJA Crisis Coverage Award for Covid reporting, and has been a contributing editor at Nautilus Magazine. In 2021, Zeldovich released her first book, The Other Dark Matter, published by the University of Chicago Press, about the science and business of turning waste into wealth and health. You can find her on http://linazeldovich.com/ and @linazeldovich.
For generations, the Indigenous Tjupan people of Australia enjoyed the sweet treat of honey made by honeypot ants. As a favorite pastime, entire families would go searching for the underground colonies, first spotting a worker ant and then tracing it to its home. The ants, which belong to the species called Camponotus inflatus, usually build their subterranean homes near the mulga trees, Acacia aneura. Having traced an ant to its tree, it would be the women who carefully dug a pit next to a colony, cautious not to destroy the entire structure. Once the ant chambers were exposed, the women would harvest a small amount to avoid devastating the colony’s stocks—and the family would share the treat.
The Tjupan people also knew that the honey had antimicrobial properties. “You could use it for a sore throat,” says Danny Ulrich, a member of the Tjupan nation. “You could also use it topically, on cuts and things like that.”
These hunts have become rarer, as many of the Tjupan people have moved away and, up until now, the exact antimicrobial properties of the ant honey remained unknown. But recently, scientists Andrew Dong and Kenya Fernandes from the University of Sydney, joined Ulrich, who runs the Honeypot Ants tours in Kalgoorlie, a city in Western Australia, on a honey-gathering expedition. Afterwards, they ran a series of experiments analyzing the honey’s antimicrobial activity—and confirmed that the Indigenous wisdom was true. The honey was effective against Staphylococcus aureus, a common pathogen responsible for sore throats, skin infections like boils and sores, and also sepsis, which can result in death. Moreover, the honey also worked against two species of fungi, Cryptococcus and Aspergillus, which can be pathogenic to humans, especially those with suppressed immune systems.
In the era of growing antibiotic resistance and the rising threat of pathogenic fungi, these findings may help scientists identify and make new antimicrobial compounds. “Natural products have been honed over thousands and millions of years by nature and evolution,” says Fernandes. “And some of them have complex and intricate properties that make them really important as potential new antibiotics. “
In an era of growing resistance to antibiotics and new threats of fungi infections, the latest findings about honeypot ants are helping scientists identify new antimicrobial drugs.
Danny Ulrich
Bee honey is also known for its antimicrobial properties, but bees produce it very differently than the ants. Bees collect nectar from flowers, which they regurgitate at the hive and pack into the hexagonal honeycombs they build for storage. As they do so, they also add into the mix an enzyme called glucose oxidase produced by their glands. The enzyme converts atmospheric oxygen into hydrogen peroxide, a reactive molecule that destroys bacteria and acts as a natural preservative. After the bees pack the honey into the honeycombs, they fan it with their wings to evaporate the water. Once a honeycomb is full, the bees put a beeswax cover on it, where it stays well-preserved thanks to the enzymatic action, until the bees need it.
Less is known about the chemistry of ants’ honey-making. Similarly to bees, they collect nectar. They also collect the sweet sap of the mulga tree. Additionally, they also “milk” the aphids—small sap-sucking insects that live on the tree. When ants tickle the aphids with their antennae, the latter release a sweet substance, which the former also transfer to their colonies. That’s where the honey management difference becomes really pronounced. The ants don’t build any kind of structures to store their honey. Instead, they store it in themselves.
The workers feed their harvest to their fellow ants called repletes, stuffing them up to the point that their swollen bellies outgrow the ants themselves, looking like amber-colored honeypots—hence the name. Because of their size, repletes don’t move, but hang down from the chamber’s ceiling, acting as living feedstocks. When food becomes scarce, they regurgitate their reserves to their colony’s brethren. It’s not clear whether the repletes die afterwards or can be restuffed again. “That's a good question,” Dong says. “After they've been stretched, they can't really return to exactly the same shape.”
These replete ants are the “treat” the Tjupan women dug for. Once they saw the round-belly ants inside the chambers, they would reach in carefully and get a few scoops of them. “You see a lot of honeypot ants just hanging on the roof of the little openings,” says Ulrich’s mother, Edie Ulrich. The women would share the ants with family members who would eat them one by one. “They're very delicate,” shares Edie Ulrich—you have to take them out carefully, so they don’t accidentally pop and become a wasted resource. “Because you’d lose all this precious honey.”
Dong stumbled upon the honeypot ants phenomenon because he was interested in Indigenous foods and went on Ulrich’s tour. He quickly became fascinated with the insects and their role in the Indigenous culture. “The honeypot ants are culturally revered by the Indigenous people,” he says. Eventually he decided to test out the honey’s medicinal qualities.
The researchers were surprised to see that even the smallest, eight percent concentration of honey was able to arrest the growth of S. aureus.
To do this, the two scientists first diluted the ant honey with water. “We used something called doubling dilutions, which means that we made 32 percent dilutions, and then we halve that to 16 percent and then we half that to eight percent,” explains Fernandes. The goal was to obtain as much results as possible with the meager honey they had. “We had very, very little of the honeypot ant honey so we wanted to maximize the spectrum of results we can get without wasting too much of the sample.”
After that, the researchers grew different microbes inside a nutrient rich broth. They added the broth to the different honey dilutions and incubated the mixes for a day or two at the temperature favorable to the germs’ growth. If the resulting solution turned turbid, it was a sign that the bugs proliferated. If it stayed clear, it meant that the honey destroyed them. The researchers were surprised to see that even the smallest, eight percent concentration of honey was able to arrest the growth of S. aureus. “It was really quite amazing,” Fernandes says. “Eight milliliters of honey in 92 milliliters of water is a really tiny amount of honey compared to the amount of water.”
Similar to bee honey, the ants’ honey exhibited some peroxide antimicrobial activity, researchers found, but given how little peroxide was in the solution, they think the honey also kills germs by a different mechanism. “When we measured, we found that [the solution] did have some hydrogen peroxide, but it didn't have as much of it as we would expect based on how active it was,” Fernandes says. “Whether this hydrogen peroxide also comes from glucose oxidase or whether it's produced by another source, we don't really know,” she adds. The research team does have some hypotheses about the identity of this other germ-killing agent. “We think it is most likely some kind of antimicrobial peptide that is actually coming from the ant itself.”
The honey also has a very strong activity against the two types of fungi, Cryptococcus and Aspergillus. Both fungi are associated with trees and decaying leaves, as well as in the soils where ants live, so the insects likely have evolved some natural defense compounds, which end up inside the honey.
It wouldn’t be the first time when modern medicines take their origin from the natural world or from the indigenous people’s knowledge. The bark of the cinchona tree native to South America contains quinine, a substance that treats malaria. The Indigenous people of the Andes used the bark to quell fever and chills for generations, and when Europeans began to fall ill with malaria in the Amazon rainforest, they learned to use that medicine from the Andean people.
The wonder drug aspirin similarly takes its origin from a bark of a tree—in this case a willow.
Even some anticancer compounds originated from nature. A chemotherapy drug called Paclitaxel, was originally extracted from the Pacific yew trees, Taxus brevifolia. The samples of the Pacific yew bark were first collected in 1962 by researchers from the United States Department of Agriculture who were looking for natural compounds that might have anti-tumor activity. In December 1992, the FDA approved Paclitaxel (brand name Taxol) for the treatment of ovarian cancer and two years later for breast cancer.
In the era when the world is struggling to find new medicines fast enough to subvert a fungal or bacterial pandemic, these discoveries can pave the way to new therapeutics. “I think it's really important to listen to indigenous cultures and to take their knowledge because they have been using these sources for a really, really long time,” Fernandes says. Now we know it works, so science can elucidate the molecular mechanisms behind it, she adds. “And maybe it can even provide a lead for us to develop some kind of new treatments in the future.”
Lina Zeldovich has written about science, medicine and technology for Popular Science, Smithsonian, National Geographic, Scientific American, Reader’s Digest, the New York Times and other major national and international publications. A Columbia J-School alumna, she has won several awards for her stories, including the ASJA Crisis Coverage Award for Covid reporting, and has been a contributing editor at Nautilus Magazine. In 2021, Zeldovich released her first book, The Other Dark Matter, published by the University of Chicago Press, about the science and business of turning waste into wealth and health. You can find her on http://linazeldovich.com/ and @linazeldovich.
Researchers probe extreme gene therapy for severe alcoholism
Story by Freethink
A single shot — a gene therapy injected into the brain — dramatically reduced alcohol consumption in monkeys that previously drank heavily. If the therapy is safe and effective in people, it might one day be a permanent treatment for alcoholism for people with no other options.
The challenge: Alcohol use disorder (AUD) means a person has trouble controlling their alcohol consumption, even when it is negatively affecting their life, job, or health.
In the U.S., more than 10 percent of people over the age of 12 are estimated to have AUD, and while medications, counseling, or sheer willpower can help some stop drinking, staying sober can be a huge struggle — an estimated 40-60 percent of people relapse at least once.
A team of U.S. researchers suspected that an in-development gene therapy for Parkinson’s disease might work as a dopamine-replenishing treatment for alcoholism, too.
According to the CDC, more than 140,000 Americans are dying each year from alcohol-related causes, and the rate of deaths has been rising for years, especially during the pandemic.
The idea: For occasional drinkers, alcohol causes the brain to release more dopamine, a chemical that makes you feel good. Chronic alcohol use, however, causes the brain to produce, and process, less dopamine, and this persistent dopamine deficit has been linked to alcohol relapse.
There is currently no way to reverse the changes in the brain brought about by AUD, but a team of U.S. researchers suspected that an in-development gene therapy for Parkinson’s disease might work as a dopamine-replenishing treatment for alcoholism, too.
To find out, they tested it in heavy-drinking monkeys — and the animals’ alcohol consumption dropped by 90% over the course of a year.
How it works: The treatment centers on the protein GDNF (“glial cell line-derived neurotrophic factor”), which supports the survival of certain neurons, including ones linked to dopamine.
For the new study, a harmless virus was used to deliver the gene that codes for GDNF into the brains of four monkeys that, when they had the option, drank heavily — the amount of ethanol-infused water they consumed would be equivalent to a person having nine drinks per day.
“We targeted the cell bodies that produce dopamine with this gene to increase dopamine synthesis, thereby replenishing or restoring what chronic drinking has taken away,” said co-lead researcher Kathleen Grant.
To serve as controls, another four heavy-drinking monkeys underwent the same procedure, but with a saline solution delivered instead of the gene therapy.
The results: All of the monkeys had their access to alcohol removed for two months following the surgery. When it was then reintroduced for four weeks, the heavy drinkers consumed 50 percent less compared to the control group.
When the researchers examined the monkeys’ brains at the end of the study, they were able to confirm that dopamine levels had been replenished in the treated animals, but remained low in the controls.
The researchers then took the alcohol away for another four weeks, before giving it back for four. They repeated this cycle for a year, and by the end of it, the treated monkeys’ consumption had fallen by more than 90 percent compared to the controls.
“Drinking went down to almost zero,” said Grant. “For months on end, these animals would choose to drink water and just avoid drinking alcohol altogether. They decreased their drinking to the point that it was so low we didn’t record a blood-alcohol level.”
When the researchers examined the monkeys’ brains at the end of the study, they were able to confirm that dopamine levels had been replenished in the treated animals, but remained low in the controls.
Looking ahead: Dopamine is involved in a lot more than addiction, so more research is needed to not only see if the results translate to people but whether the gene therapy leads to any unwanted changes to mood or behavior.
Because the therapy requires invasive brain surgery and is likely irreversible, it’s unlikely to ever become a common treatment for alcoholism — but it could one day be the only thing standing between people with severe AUD and death.
“[The treatment] would be most appropriate for people who have already shown that all our normal therapeutic approaches do not work for them,” said Grant. “They are likely to create severe harm or kill themselves or others due to their drinking.”
This article originally appeared on Freethink, home of the brightest minds and biggest ideas of all time.
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.