A surprising weapon in the fight against food poisoning
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.
Every year, one in seven people in America comes down with a foodborne illness, typically caused by a bacterial pathogen, including E.Coli, listeria, salmonella, or campylobacter. That adds up to 48 million people, of which 120,000 are hospitalized and 3000 die, according to the Centers for Disease Control. And the variety of foods that can be contaminated with bacterial pathogens is growing too. In the 20th century, E.Coli and listeria lurked primarily within meat. Now they find their way into lettuce, spinach, and other leafy greens, causing periodic consumer scares and product recalls. Onions are the most recent suspected culprit of a nationwide salmonella outbreak.
Some of these incidents are almost inevitable because of how Mother Nature works, explains Divya Jaroni, associate professor of animal and food sciences at Oklahoma State University. These common foodborne pathogens come from the cattle's intestines when the animals shed them in their manure—and then they get washed into rivers and lakes, especially in heavy rains. When this water is later used to irrigate produce farms, the bugs end up on salad greens. Plus, many small farms do both—herd cattle and grow produce.
"Unfortunately for us, these pathogens are part of the microflora of the cows' intestinal tract," Jaroni says. "Some farmers may have an acre or two of cattle pastures, and an acre of a produce farm nearby, so it's easy for this water to contaminate the crops."
Food producers and packagers fight bacteria by potent chemicals, with chlorine being the go-to disinfectant. Cattle carcasses, for example, are typically washed by chlorine solutions as the animals' intestines are removed. Leafy greens are bathed in water with added chlorine solutions. However, because the same "bath" can be used for multiple veggie batches and chlorine evaporates over time, the later rounds may not kill all of the bacteria, sparing some. The natural and organic producers avoid chlorine, substituting it with lactic acid, a more holistic sanitizer, but even with all these efforts, some pathogens survive, sickening consumers and causing food recalls. As we farm more animals and grow more produce, while also striving to use fewer chemicals and more organic growing methods, it will be harder to control bacteria's spread.
"It took us a long time to convince the FDA phages were safe and efficient alternatives. But we had worked with them to gather all the data they needed, and the FDA was very supportive in the end."
Luckily, bacteria have their own killers. Called bacteriophages, or phages for short, they are viruses that prey on bacteria only. Under the electron microscope, they look like fantasy spaceships, with oblong bodies, spider-like legs and long tails. Much smaller than a bacterium, phages pierce the microbes' cells with their tails, sneak in and begin multiplying inside, eventually bursting the microbes open—and then proceed to infect more of them.
The best part is that these phages are harmless to humans. Moreover, recent research finds that millions of phages dwell on us and in us—in our nose, throat, skin and gut, protecting us from bacterial infections as part of our healthy microbiome. A recent study suggested that we absorb about 30 billion phages into our bodies on a daily basis. Now, ingeniously, they are starting to be deployed as anti-microbial agents in the food industry.
A Maryland-based phage research company called Intralytix is doing just that. Founded by Alexander Sulakvelidze, a microbiologist and epidemiologist who came to the United States from Tbilisi, the capital of Georgia, Intralytix makes and sells five different FDA-approved phage cocktails that work against some of the most notorious food pathogens: ListShield for Listeria, SalmoFresh for Salmonella, ShigaShield for Shigella, another foodborne bug, and EcoShield for E.coli, including the infamous strain that caused the Jack in the Box outbreak in 1993 that killed four children and sickened 732 people across four states. Last year, the FDA granted its approval to yet another Intralytix phage for managing Campylobacter contamination, named CampyShield. "We call it safety by nature," Sulakvelidze says.
Intralytix grows phages inside massive 1500-liter fermenters, feeding them bacterial "fodder."
Photo credit: Living Radiant Photography
Phage preparations are relatively straightforward to make. In nature, phages thrive in any body of water where bacteria live too, including rivers, lakes and bays. "I can dip a bucket into the Chesapeake Bay, and it will be full of all kinds of phages," Sulakvelidze says. "Sewage is another great place to look for specific phages of interest, because it's teeming with all sorts of bacteria—and therefore the viruses that prey on them."
In lab settings, Intralytix grows phages inside massive 1500-liter fermenters, feeding them bacterial "fodder." Once phages multiply enough, they are harvested, dispensed into containers and shipped to food producers who have adopted this disinfecting practice into their preparation process. Typically, it's done by computer-controlled sprayer systems that disperse mist-like phage preparations onto the food.
Unlike chemicals like chlorine or antibiotics, which kill a wide spectrum of bacteria, phages are more specialized, each feeding on specific microbial species. A phage that targets salmonella will not prey on listeria and vice versa. So food producers may sometimes use a combo of different phage preparations. Intralytix is continuously researching and testing new phages. With a contract from the National Institutes of Health, Intralytix is expanding its automated high-throughput robot that tests which phages work best against which bacteria, speeding up the development of the new phage cocktails.
Phages have other "talents." In her recent study, Jaroni found that phages have the ability to destroy bacterial biofilms—colonies of microorganisms that tend to grow on surfaces of the food processing equipment, surrounding themselves with protective coating that even very harsh chemicals can't crack.
"Phages are very clever," Jaroni says. "They produce enzymes that target the biofilms, and once they break through, they can reach the bacteria."
Convincing the FDA that phages were safe to use on food products was no easy feat, Sulakvelidze says. In his home country of Georgia, phages have been used as antimicrobial remedies for over a century, but the FDA was leery of using viruses as food safety agents. "It took us a long time to convince the FDA phages were safe and efficient alternatives," Sulakvelidze says. "But we had worked with them to gather all the data they needed, and the FDA was very supportive in the end."
The agency had granted Intralytix its first approval in 2006, and over the past 10 years, the company's sales increased by over 15-fold. "We currently sell to about 40 companies and are in discussions with several other large food producers," Sulakvelidze says. One indicator that the industry now understands and appreciates the science of phages was that his company was ranked as Top Food Safety Provider in 2021 by Food and Beverage Technology Review, he adds. Notably, phage sprays are kosher, halal and organic-certified.
Intralytix's phage cocktails to safeguard food from bacteria are approved for consumers in addition to food producers, but currently the company sells to food producers only. Selling retail requires different packaging like easy-to-use spray bottles and different marketing that would inform people about phages' antimicrobial qualities. But ultimately, giving people the ability to remove pathogens from their food with probiotic phage sprays is the goal, Sulakvelidze says.
It's not the company's only goal. Now Intralytix is going a step further, investigating phages' probiotic and therapeutic abilities. Because phages are highly specialized in the bacteria they target, they can be used to treat infections caused by specific pathogens while leaving the beneficial species of our microbiome intact. In an ongoing clinical trial with Mount Sinai, Intralytix is now investigating a potential phage treatment against a certain type of E. coli for patients with Crohn's disease, and is about to start another clinical trial for treating bacterial dysentery.
"Now that we have proved that phages are safe and effective against foodborne bacteria," Sulakvelidze says, "we are going to demonstrate their potential in therapeutic applications."
This article was first published by Leaps.org on October 27, 2021.
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.