Probiotic bacteria can be engineered to fight antibiotic-resistant superbugs by releasing chemicals that kill them.
In 1945, almost two decades after Alexander Fleming discovered penicillin, he warned that as antibiotics use grows, they may lose their efficiency. He was prescient—the first case of penicillin resistance was reported two years later. Back then, not many people paid attention to Fleming’s warning. After all, the “golden era” of the antibiotics age had just began. By the 1950s, three new antibiotics derived from soil bacteria — streptomycin, chloramphenicol, and tetracycline — could cure infectious diseases like tuberculosis, cholera, meningitis and typhoid fever, among others.
Today, these antibiotics and many of their successors developed through the 1980s are gradually losing their effectiveness. The extensive overuse and misuse of antibiotics led to the rise of drug resistance. The livestock sector buys around 80 percent of all antibiotics sold in the U.S. every year. Farmers feed cows and chickens low doses of antibiotics to prevent infections and fatten up the animals, which eventually causes resistant bacterial strains to evolve. If manure from cattle is used on fields, the soil and vegetables can get contaminated with antibiotic-resistant bacteria. Another major factor is doctors overprescribing antibiotics to humans, particularly in low-income countries. Between 2000 to 2018, the global rates of human antibiotic consumption shot up by 46 percent.
In recent years, researchers have been exploring a promising avenue: the use of synthetic biology to engineer new bacteria that may work better than antibiotics. The need continues to grow, as a Lancet study linked antibiotic resistance to over 1.27 million deaths worldwide in 2019, surpassing HIV/AIDS and malaria. The western sub-Saharan Africa region had the highest death rate (27.3 people per 100,000).
Researchers warn that if nothing changes, by 2050, antibiotic resistance could kill 10 million people annually.
To make it worse, our remedy pipelines are drying up. Out of the 18 biggest pharmaceutical companies, 15 abandoned antibiotic development by 2013. According to the AMR Action Fund, venture capital has remained indifferent towards biotech start-ups developing new antibiotics. In 2019, at least two antibiotic start-ups filed for bankruptcy. As of December 2020, there were 43 new antibiotics in clinical development. But because they are based on previously known molecules, scientists say they are inadequate for treating multidrug-resistant bacteria. Researchers warn that if nothing changes, by 2050, antibiotic resistance could kill 10 million people annually.
The rise of synthetic biology
To circumvent this dire future, scientists have been working on alternative solutions using synthetic biology tools, meaning genetically modifying good bacteria to fight the bad ones.
From the time life evolved on earth around 3.8 billion years ago, bacteria have engaged in biological warfare. They constantly strategize new methods to combat each other by synthesizing toxic proteins that kill competition.
For example, Escherichia coli produces bacteriocins or toxins to kill other strains of E.coli that attempt to colonize the same habitat. Microbes like E.coli (which are not all pathogenic) are also naturally present in the human microbiome. The human microbiome harbors up to 100 trillion symbiotic microbial cells. The majority of them are beneficial organisms residing in the gut at different compositions.
The chemicals that these “good bacteria” produce do not pose any health risks to us, but can be toxic to other bacteria, particularly to human pathogens. For the last three decades, scientists have been manipulating bacteria’s biological warfare tactics to our collective advantage.
In the late 1990s, researchers drew inspiration from electrical and computing engineering principles that involve constructing digital circuits to control devices. In certain ways, every cell in living organisms works like a tiny computer. The cell receives messages in the form of biochemical molecules that cling on to its surface. Those messages get processed within the cells through a series of complex molecular interactions.
Synthetic biologists can harness these living cells’ information processing skills and use them to construct genetic circuits that perform specific instructions—for example, secrete a toxin that kills pathogenic bacteria. “Any synthetic genetic circuit is merely a piece of information that hangs around in the bacteria’s cytoplasm,” explains José Rubén Morones-Ramírez, a professor at the Autonomous University of Nuevo León, Mexico. Then the ribosome, which synthesizes proteins in the cell, processes that new information, making the compounds scientists want bacteria to make. “The genetic circuit remains separated from the living cell’s DNA,” Morones-Ramírez explains. When the engineered bacteria replicates, the genetic circuit doesn’t become part of its genome.
Highly intelligent by bacterial standards, some multidrug resistant V. cholerae strains can also “collaborate” with other intestinal bacterial species to gain advantage and take hold of the gut.
In 2000, Boston-based researchers constructed an E.coli with a genetic switch that toggled between turning genes on and off two. Later, they built some safety checks into their bacteria. “To prevent unintentional or deleterious consequences, in 2009, we built a safety switch in the engineered bacteria’s genetic circuit that gets triggered after it gets exposed to a pathogen," says James Collins, a professor of biological engineering at MIT and faculty member at Harvard University’s Wyss Institute. “After getting rid of the pathogen, the engineered bacteria is designed to switch off and leave the patient's body.”
Overuse and misuse of antibiotics causes resistant strains to evolve
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Seek and destroy
As the field of synthetic biology developed, scientists began using engineered bacteria to tackle superbugs. They first focused on Vibrio cholerae, which in the 19th and 20th century caused cholera pandemics in India, China, the Middle East, Europe, and Americas. Like many other bacteria, V. cholerae communicate with each other via quorum sensing, a process in which the microorganisms release different signaling molecules, to convey messages to its brethren. Highly intelligent by bacterial standards, some multidrug resistant V. cholerae strains can also “collaborate” with other intestinal bacterial species to gain advantage and take hold of the gut. When untreated, cholera has a mortality rate of 25 to 50 percent and outbreaks frequently occur in developing countries, especially during floods and droughts.
Sometimes, however, V. cholerae makes mistakes. In 2008, researchers at Cornell University observed that when quorum sensing V. cholerae accidentally released high concentrations of a signaling molecule called CAI-1, it had a counterproductive effect—the pathogen couldn’t colonize the gut.
So the group, led by John March, professor of biological and environmental engineering, developed a novel strategy to combat V. cholerae. They genetically engineered E.coli to eavesdrop on V. cholerae communication networks and equipped it with the ability to release the CAI-1 molecules. That interfered with V. cholerae progress. Two years later, the Cornell team showed that V. cholerae-infected mice treated with engineered E.coli had a 92 percent survival rate.
These findings inspired researchers to sic the good bacteria present in foods like yogurt and kimchi onto the drug-resistant ones.
Three years later in 2011, Singapore-based scientists engineered E.coli to detect and destroy Pseudomonas aeruginosa, an often drug-resistant pathogen that causes pneumonia, urinary tract infections, and sepsis. Once the genetically engineered E.coli found its target through its quorum sensing molecules, it then released a peptide, that could eradicate 99 percent of P. aeruginosa cells in a test-tube experiment. The team outlined their work in a Molecular Systems Biology study.
“At the time, we knew that we were entering new, uncharted territory,” says lead author Matthew Chang, an associate professor and synthetic biologist at the National University of Singapore and lead author of the study. “To date, we are still in the process of trying to understand how long these microbes stay in our bodies and how they might continue to evolve.”
More teams followed the same path. In a 2013 study, MIT researchers also genetically engineered E.coli to detect P. aeruginosa via the pathogen’s quorum-sensing molecules. It then destroyed the pathogen by secreting a lab-made toxin.
Probiotics that fight
A year later in 2014, a Nature study found that the abundance of Ruminococcus obeum, a probiotic bacteria naturally occurring in the human microbiome, interrupts and reduces V.cholerae’s colonization— by detecting the pathogen’s quorum sensing molecules. The natural accumulation of R. obeum in Bangladeshi adults helped them recover from cholera despite living in an area with frequent outbreaks.
The findings from 2008 to 2014 inspired Collins and his team to delve into how good bacteria present in foods like yogurt and kimchi can attack drug-resistant bacteria. In 2018, Collins and his team developed the engineered probiotic strategy. They tweaked a bacteria commonly found in yogurt called Lactococcus lactis to treat cholera.
Engineered bacteria can be trained to target pathogens when they are at their most vulnerable metabolic stage in the human gut. --José Rubén Morones-Ramírez.
More scientists followed with more experiments. So far, researchers have engineered various probiotic organisms to fight pathogenic bacteria like Staphylococcus aureus (leading cause of skin, tissue, bone, joint and blood infections) and Clostridium perfringens (which causes watery diarrhea) in test-tube and animal experiments. In 2020, Russian scientists engineered a probiotic called Pichia pastoris to produce an enzyme called lysostaphin that eradicated S. aureus in vitro. Another 2020 study from China used an engineered probiotic bacteria Lactobacilli casei as a vaccine to prevent C. perfringens infection in rabbits.
In a study last year, Ramírez’s group at the Autonomous University of Nuevo León, engineered E. coli to detect quorum-sensing molecules from Methicillin-resistant Staphylococcus aureus or MRSA, a notorious superbug. The E. coli then releases a bacteriocin that kills MRSA. “An antibiotic is just a molecule that is not intelligent,” says Ramírez. “On the other hand, engineered bacteria can be trained to target pathogens when they are at their most vulnerable metabolic stage in the human gut.”
Collins and Timothy Lu, an associate professor of biological engineering at MIT, found that engineered E. coli can help treat other conditions—such as phenylketonuria, a rare metabolic disorder, that causes the build-up of an amino acid phenylalanine. Their start-up Synlogic aims to commercialize the technology, and has completed a phase 2 clinical trial.
Circumventing the challenges
The bacteria-engineering technique is not without pitfalls. One major challenge is that beneficial gut bacteria produce their own quorum-sensing molecules that can be similar to those that pathogens secrete. If an engineered bacteria’s biosensor is not specific enough, it will be ineffective.
Another concern is whether engineered bacteria might mutate after entering the gut. “As with any technology, there are risks where bad actors could have the capability to engineer a microbe to act quite nastily,” says Collins of MIT. But Collins and Ramírez both insist that the chances of the engineered bacteria mutating on its own are virtually non-existent. “It is extremely unlikely for the engineered bacteria to mutate,” Ramírez says. “Coaxing a living cell to do anything on command is immensely challenging. Usually, the greater risk is that the engineered bacteria entirely lose its functionality.”
However, the biggest challenge is bringing the curative bacteria to consumers. Pharmaceutical companies aren’t interested in antibiotics or their alternatives because it’s less profitable than developing new medicines for non-infectious diseases. Unlike the more chronic conditions like diabetes or cancer that require long-term medications, infectious diseases are usually treated much quicker. Running clinical trials are expensive and antibiotic-alternatives aren’t lucrative enough.
“Unfortunately, new medications for antibiotic resistant infections have been pushed to the bottom of the field,” says Lu of MIT. “It's not because the technology does not work. This is more of a market issue. Because clinical trials cost hundreds of millions of dollars, the only solution is that governments will need to fund them.” Lu stresses that societies must lobby to change how the modern healthcare industry works. “The whole world needs better treatments for antibiotic resistance.”
A chatbot from the nonprofit National Eating Disorders Association aimed to provide 24/7 guidance on eating disorders. Several drawbacks point to the importance of therapist-tech collaboration in multiple areas of health.
Then everything went off the rails. Tessa told Maxwell an unequivocal yes, and that “it’s important to approach weight loss with a balanced and realistic mindset,” and recommended eating whole foods and lean proteins to create a 500-1000 calorie per day deficit that would lead to a loss of 1-2 pounds per week. To most people, the advice sounds anodyne, but alarm bells sounded in Maxwell’s head.
“This is actively going to feed eating disorders,” Maxwell says. “Having a chatbot be the direct response to someone reaching out for support for an eating disorder instead of the helpline seems careless.”
“The scripts that are being fed into the chatbot are only going to be as good as the person who’s feeding them.” -- Alexis Conason.
According to several decades of research, deliberate weight loss in the form of dieting is a serious risk for people with eating disorders. Maxwell says that following medical advice like what Tessa prescribed was what triggered her eating disorder as a child. And Maxwell wasn’t the only one who got such advice from the bot. When eating disorder therapist Alexis Conason tried Tessa, she asked the AI chatbot many of the questions her patients had. But instead of getting connected to resources or guidance on recovery, Conason, too, got tips on losing weight and “healthy” eating.
“The scripts that are being fed into the chatbot are only going to be as good as the person who’s feeding them,” Conason says. “It’s important that an eating disorder organization like NEDA is not reinforcing that same kind of harmful advice that we might get from medical providers who are less knowledgeable.”
Maxwell’s post about Tessa on Instagram went viral, and within days, NEDA had scrubbed all evidence of Tessa from its website. The furor has raised any number of issues about the harm perpetuated by a leading eating disorder charity and the ongoing influence of diet culture and advice that is pervasive in the field. But for AI experts, bears and bulls alike, Tessa offers a cautionary tale about what happens when a still-immature technology is unfettered and released into a vulnerable population.
Given the complexity involved in giving medical advice, the process of developing these chatbots must be rigorous and transparent, unlike NEDA’s approach.
“We don’t have a full understanding of what’s going on in these models. They’re a black box,” says Stephen Schueller, a clinical psychologist at the University of California, Irvine.
The health crisis
In March 2020, the world dove head-first into a heavily virtual world as countries scrambled to try and halt the pandemic. Even with lockdowns, hospitals were overwhelmed by the virus. The downstream effects of these lifesaving measures are still being felt, especially in mental health. Anxiety and depression are at all-time highs in teens, and a new report in The Lancet showed that post-Covid rates of newly diagnosed eating disorders in girls aged 13-16 were 42.4 percent higher than previous years.
And the crisis isn’t just in mental health.
“People are so desperate for health care advice that they'll actually go online and post pictures of [their intimate areas] and ask what kind of STD they have on public social media,” says John Ayers, an epidemiologist at the University of California, San Diego.
For many people, the choice isn’t chatbot vs. well-trained physician, but chatbot vs. nothing at all.
I know a bit about that desperation. Like Maxwell, I have struggled with a multi-decade eating disorder. I spent my 20s and 30s bouncing from crisis to crisis. I have called suicide hotlines, gone to emergency rooms, and spent weeks-on-end confined to hospital wards. Though I have found recovery in recent years, I’m still not sure what ultimately made the difference. A relapse isn't improbably, given my history. Even if I relapsed again, though, I don’t know it would occur to me to ask an AI system for help.
For one, I am privileged to have assembled a stellar group of outpatient professionals who know me, know what trips me up, and know how to respond to my frantic texts. Ditto for my close friends. What I often need is a shoulder to cry on or a place to vent—someone to hear and validate my distress. What’s more, my trust in these individuals far exceeds my confidence in the companies that create these chatbots. The Internet is full of health advice, much of it bad. Even for high-quality, evidence-based advice, medicine is often filled with disagreements about how the evidence might be applied and for whom it’s relevant. All of this is key in the training of AI systems like ChatGPT, and many AI companies remain silent on this process, Schueller says.
The problem, Ayers points out, is that for many people, the choice isn’t chatbot vs. well-trained physician, but chatbot vs. nothing at all. Hence the proliferation of “does this infection make my scrotum look strange?” questions. Where AI can truly shine, he says, is not by providing direct psychological help but by pointing people towards existing resources that we already know are effective.
“It’s important that these chatbots connect [their users to] to provide that human touch, to link you to resources,” Ayers says. “That’s where AI can actually save a life.”
Before building a chatbot and releasing it, developers need to pause and consult with the communities they hope to serve.
Unfortunately, many systems don’t do this. In a study published last month in the Journal of the American Medical Association, Ayers and colleagues found that although the chatbots did well at providing evidence-based answers, they often didn’t provide referrals to existing resources. Despite this, in an April 2023 study, Ayers’s team found that both patients and professionals rated the quality of the AI responses to questions, measured by both accuracy and empathy, rather highly. To Ayers, this means that AI developers should focus more on the quality of the information being delivered rather than the method of delivery itself.
Many mental health professionals have months-long waitlists, which leaves individuals to deal with illnesses on their own.
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The human touch
The mental health field is facing timing constraints, too. Even before the pandemic, the U.S. suffered from a shortage of mental health providers. Since then, the rates of anxiety, depression, and eating disorders have spiked even higher, and many mental health professionals report waiting lists that are months long. Without support, individuals are left to try and cope on their own, which often means their condition deteriorates even further.
Nor do mental health crises happen during office hours. I struggled the most late at night, long after everyone else had gone to bed. I needed support during those times when I was most liable to hurt myself, not in the mornings and afternoons when I was at work.
In this sense, a 24/7 chatbot makes lots of sense. “I don't think we should stifle innovation in this space,” Schueller says. “Because if there was any system that needs to be innovated, it's mental health services, because they are sadly insufficient. They’re terrible.”
But before building a chatbot and releasing it, Tina Hernandez-Boussard, a data scientist at Stanford Medicine, says that developers need to pause and consult with the communities they hope to serve. It requires a deep understanding of what their needs are, the language they use to describe their concerns, existing resources, and what kinds of topics and suggestions aren’t helpful. Even asking a simple question at the beginning of a conversation such as “Do you want to talk to an AI or a human?” could allow those individuals to pick the type of interaction that suits their needs, Hernandez-Boussard says.
NEDA did none of these things before deploying Tessa. The researchers who developed the online body positivity self-help program upon which Tessa was initially based created a set of online question-and-answer exercises to improve body image. It didn’t involve generative AI that could write its own answers. The bot deployed by NEDA did use generative AI, something that no one in the eating disorder community was aware of before Tessa was brought online. Consulting those with lived experience would have flagged Tessa’s weight loss and “healthy eating” recommendations, Conason says.
The question for healthcare isn’t whether to use AI, but how.
NEDA did not comment on initial Tessa’s development and deployment, but a spokesperson told Leaps.org that “Tessa will be back online once we are confident that the program will be run with the rule-based approach as it was designed.”
The tech and therapist collaboration
The question for healthcare isn’t whether to use AI, but how. Already, AI can spot anomalies on medical images with greater precision than human eyes and can flag specific areas of an image for a radiologist to review in greater detail. Similarly, in mental health, AI should be an add-on for therapy, not a counselor-in-a-box, says Aniket Bera, an expert on AI and mental health at Purdue University.
“If [AIs] are going to be good helpers, then we need to understand humans better,” Bera says. That means understanding what patients and therapists alike need help with and respond to.
One of the biggest challenges of struggling with chronic illness is the dehumanization that happens. You become a patient number, a set of laboratory values and test scores. Treatment is often dictated by invisible algorithms and rules that you have no control over or access to. It’s frightening and maddening. But this doesn’t mean chatbots don’t have any place in medicine and mental health. An AI system could help provide appointment reminders and answer procedural questions about parking and whether someone should fast before a test or a procedure. They can help manage billing and even provide support between outpatient sessions by offering suggestions for what coping skills to use, the best ways to manage anxiety, and point to local resources. As the bots get better, they may eventually shoulder more and more of the burden of providing mental health care. But as Maxwell learned with Tessa, it’s still no replacement for human interaction.
“I'm not suggesting we should go in and start replacing therapists with technologies,” Schueller says. Instead, he advocates for a therapist-tech collaboration. “The technology side and the human component—these things need to come together.”
