Probiotic bacteria can be engineered to fight antibiotic-resistant superbugs by releasing chemicals that kill them.
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
Adobe Stock
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 recent study in The Lancet Oncology showed that AI found 20 percent more cancers on mammogram screens than radiologists alone.
Published in The Lancet Oncology, the study analyzed the scans of 80,000 Swedish women with a moderate hereditary risk of breast cancer who had undergone a mammogram between April 2021 and July 2022. Half of these scans were read by AI and then a radiologist to double-check the findings. The second group of scans was read by two researchers without the help of AI. (Currently, the standard of care across Europe is to have two radiologists analyze a scan before diagnosing a patient with breast cancer.)
The study showed that the AI group detected cancer in 6 out of every 1,000 scans, while the radiologists detected cancer in 5 per 1,000 scans. In other words, AI found 20 percent more cancers than the highly-trained radiologists.
Scientists have been using MRI images (like the ones pictured here) to train artificial intelligence to detect cancers earlier and with more accuracy. Here, MIT's AI system, MIRAI, looks for patterns in a patient's mammograms to detect breast cancer earlier than ever before. news.mit.edu
But even though the AI was better able to pinpoint cancer on an image, it doesn’t mean radiologists will soon be out of a job. Dr. Laura Heacock, a breast radiologist at NYU, said in an interview with CNN that radiologists do much more than simply screening mammograms, and that even well-trained technology can make errors. “These tools work best when paired with highly-trained radiologists who make the final call on your mammogram. Think of it as a tool like a stethoscope for a cardiologist.”
AI is still an emerging technology, but more and more doctors are using them to detect different cancers. For example, researchers at MIT have developed a program called MIRAI, which looks at patterns in patient mammograms across a series of scans and uses an algorithm to model a patient's risk of developing breast cancer over time. The program was "trained" with more than 200,000 breast imaging scans from Massachusetts General Hospital and has been tested on over 100,000 women in different hospitals across the world. According to MIT, MIRAI "has been shown to be more accurate in predicting the risk for developing breast cancer in the short term (over a 3-year period) compared to traditional tools." It has also been able to detect breast cancer up to five years before a patient receives a diagnosis.
The challenges for cancer-detecting AI tools now is not just accuracy. AI tools are also being challenged to perform consistently well across different ages, races, and breast density profiles, particularly given the increased risks that different women face. For example, Black women are 42 percent more likely than white women to die from breast cancer, despite having nearly the same rates of breast cancer as white women. Recently, an FDA-approved AI device for screening breast cancer has come under fire for wrongly detecting cancer in Black patients significantly more often than white patients.
As AI technology improves, radiologists will be able to accurately scan a more diverse set of patients at a larger volume than ever before, potentially saving more lives than ever.
