In March, researchers published a review that lists which organic chemicals match up with certain diseases and biomarkers in the skin, saliva and urine. It’s an important step in creating a robot nose that can reliably detect diseases.
All diseases alter the organic compounds found in the body and their odors. Volatolomics is an emerging branch of chemistry that uses the smell of gases emitted by breath, urine, blood, stool, tears or sweat to diagnose disease. When someone is sick, the normal biochemical process is disrupted, and this alters the makeup of the gas, including a change in odor.
“These metabolites show a snapshot of what’s going on with the body,” says Cristina Davis, a biomedical engineer and associate vice chancellor of Interdisciplinary Research and Strategic Initiatives at the University of California, Davis. This opens the door to diagnosing conditions even before symptoms are present. It’s possible to detect a sweet, fruity smell in the breath of someone with diabetes, for example.
Hippocrates may have been the first to note that people with certain diseases give off an odor but dogs provided the proof of concept. Scientists have published countless studies in which dogs or other high-performing smellers like rodents have identified people with cancer, lung disease or other conditions by smell alone. The brain region that analyzes smells is proportionally about 40 times greater in dogs than in people. The noses of rodents are even more powerful.
Take prostate cancer, which is notoriously difficult to detect accurately with standard medical testing. After sniffing a tiny urine sample, trained dogs were able to pick out prostate cancer in study subjects more than 96 percent of the time, and earlier than a physician could in some cases.
But using dogs as bio-detectors is not practical. It is labor-intensive, complicated and expensive to train dogs to bark or lie down when they smell a certain VOC, explains Bruce Kimball, a chemical ecologist at the Monell Chemical Senses Center in Philadelphia. Kimball has trained ferrets to scratch a box when they smell a specific VOC so he knows. The lab animal must be taught to distinguish the VOC from background odors and trained anew for each disease scent.
In the lab of chemical ecologist Bruce Kimball, ferrets were trained to scratch a box when they identified avian flu in mallard ducks.
Glen J. Golden
There are some human super-smellers among us. In 2019, Joy Milne of Scotland proved she could unerringly identify people with Parkinson’s disease from a musky scent emitted from their skin. Clinical testing showed that she could distinguish the odor of Parkinson’s on a worn t-shirt before clinical symptoms even appeared.
Hossam Haick, a professor at Technion-Israel Institute of Technology, maintains that volatolomics is the future of medicine. Misdiagnosis and late detection are huge problems in health care, he says. “A precise and early diagnosis is the starting point of all clinical activities.” Further, this science has the potential to eliminate costly invasive testing or imaging studies and improve outcomes through earlier treatment.
The Nose Knows a Lot
“Volatolomics is not a fringe theory. There is science behind it,” Davis stresses. Every VOC has its own fingerprint, and a method called gas chromatography-mass spectrometry (GCMS) uses highly sensitive instruments to separate the molecules of these VOCs to determine their structures. But GCMS can’t discern the telltale patterns of particular diseases, and other technologies to analyze biomarkers have been limited.
We have technology that can see, hear and sense touch but scientists don’t have a handle yet on how smell works. The ability goes beyond picking out a single scent in someone’s breath or blood sample. It’s the totality of the smell—not the smell of a single chemical— which defines a disease. The dog’s brain is able to infer something when they smell a VOC that eludes human analysis so far.
Odor is a complex ecosystem and analyzing a VOC is compounded by other scents in the environment, says Kimball. A person’s diet and use of tobacco or alcohol also will affect the breath. Even fluctuations in humidity and temperature can contaminate a sample.
If successful, a sophisticated AI network can imitate how the dog brain recognizes patterns in smells. Early versions of robot noses have already been developed.
With today’s advances in data mining, AI and machine learning, scientists are trying to create mechanical devices that can draw on algorithms based on GCMS readings and data about diseases that dogs have sniffed out. If successful, a sophisticated AI network can imitate how the dog brain recognizes patterns in smells.
In March, Nano Research published a comprehensive review of volatolomics in health care authored by Haick and seven colleagues. The intent was to bridge gaps in the field for scientists trying to connect the biomarkers and sensor technology needed to develop a robot nose. This paper serves as a reference manual for the field that lists which VOCs are associated with what disease and the biomarkers in skin, saliva, breath, and urine.
Weiwei Wu, one of the co-authors and a professor at Xidian University in China, explains that creating a robotic nose requires the expertise of chemists, computer scientists, electrical engineers, material scientists, and clinicians. These researchers use different terms and methodologies and most have not collaborated before with the other disciplines. “The electrical engineers know the device but they don’t know as much about the biomarkers they need to detect,” Wu offers as an example.
This review is significant, Wu continues, because it can facilitate progress in the field by providing experts in all the disciplines with the basic knowledge needed to create an effective robot nose for diagnostic use. The paper also includes a systematic summary of the research methodology of volatolomics.
Once scientists build a stronger database of VOCs, they can program a device to identify critical patterns of specified diseases on a reliable basis. On a machine learning model, the algorithms automatically get better at diagnosing with each use. Wu envisions further tweaks in the next few years to make the devices smaller and consume less power.
A Whiff of the Future
Early versions of robot noses have already been developed. Some of them use chemical sensors to pick up smells in the breath or other body emission molecules. That data is sent through an electrical signal to a computer network for interpretation and possible linkage to a disease.
This electronic nose, or e-nose, has been successful in small pilot studies at labs around the world. At Ben-Gurion University in Israel, researchers detected breast cancer with electronic gas sensors with 95% accuracy, a higher sensitivity than mammograms. Other robot noses, called p-noses, use photons instead of electrical signals.
The mechanical noses being developed tap different methodologies and analytic techniques which makes it hard to compare them. Plus, the devices are intended for varying uses. One team, for example, is working on an e-nose that can be waved over a plate to screen for the presence of a particular allergen when you’re dining out.
A robot nose could be used as a real-time diagnostic tool in clinical practice. Kimball is working on one such tool that can distinguish between a viral and bacterial infection. This would enable physicians to determine whether an antibiotic prescription is appropriate without waiting for a lab result.
Davis is refining a hand-held device that identifies COVID-19 through a simple breath test. She sees the tool being used at crowded airports, sports stadiums and concert venues where PCR or rapid antigen testing is impractical. Background air samples are collected from the space so that those signals can be removed from the human breath measurement. “[The sensor tool] has the same accuracy as the rapid antigen test kits but exhaled breath is easier to collect,” she notes.
The NaNose, also known as the SniffPhone, uses tiny sensors boosted by AI to distinguish Alzheimer's, Crohn's disease, the early stages of several cancers, and other diseases with 84 to 98 percent accuracy.
Hossam Haick
Haick named his team’s robot nose, “NaNose,” since it is based on nanotechnology; the prototype is called the SniffPhone. Using tiny sensors boosted by AI, it can distinguish 23 diseases in human subjects with 84 to 98 percent accuracy. This includes early stages of several cancers, Alzheimer’s, tuberculosis and Crohn’s disease. His team has been raising the accuracy level by combining biomarker signals from both breath and skin, for example. The goal is to achieve 99.9 percent accuracy consistently so no other diagnostic tests would be needed before treating the patient. Plus, it will be affordable, he says.
Kimball predicts we’ll be seeing these diagnostic tools in the next decade. “The physician would narrow down what [the diagnosis] might be and then get the correct tool,” he says. Others are envisioning one device that can screen for multiple diseases by programming the software, which would be updated regularly with new findings.
Larger volatolomics studies must be conducted before these e-noses are ready for clinical use, however. Experts also need to learn how to establish normal reference ranges for e-nose readings to support clinicians using the tool.
“Taking successful prototypes from the lab to industry is the challenge,” says Haick, ticking off issues like reproducibility, mass production and regulation. But volatolomics researchers are unanimous in believing the future of health care is so close they can smell it.
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 Lancetstudy 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, whichin 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. choleraestrains 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 byJohn March, professor of biological and environmental engineering, developed a novel strategy to combat V. cholerae. They genetically engineered E.coli toeavesdrop 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 oftendrug-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. obeumin Bangladeshi adults helped them recover from cholera despite living in an area with frequent outbreaks.
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.
These findings inspired researchers to sic the good bacteria present in foods like yogurt and kimchi onto the drug-resistant ones. 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.”
Today's podcast guest, Dr. Renee Wegrzyn, directs ARPA-H, a new agency formed last year to spearhead health innovations. Time will tell if ARPA-H will produce advances on the level of its fellow agency, DARPA.
Listen on Apple | Listen on Spotify | Listen on Stitcher | Listen on Amazon | Listen on Google
How will the agency figure out which projects to take on, especially with so many patient advocates for different diseases demanding moonshot funding for rapid progress?
I talked with Dr. Wegrzyn about the opportunities and challenges, what lessons ARPA-H is borrowing from Operation Warp Speed, how she decided on the first ARPA-H project that was announced recently, why a separate agency was needed instead of reforming HHS and the National Institutes of Health to be better at innovation, and how ARPA-H will make progress on disease prevention in addition to treatments for cancer, Alzheimer’s and diabetes, among many other health priorities.
Dr. Wegrzyn’s resume leaves no doubt of her suitability for this role. She was a program manager at DARPA where she focused on applying gene editing and synthetic biology to the goal of improving biosecurity. For her work there, she received the Superior Public Service Medal and, in case that wasn’t enough ARPA experience, she also worked at another ARPA that leads advanced projects in intelligence, called I-ARPA. Before that, she ran technical teams in the private sector working on gene therapies and disease diagnostics, among other areas. She has been a vice president of business development at Gingko Bioworks and headed innovation at Concentric by Gingko. Her training and education includes a PhD and undergraduate degree in applied biology from the Georgia Institute of Technology and she did her postdoc as an Alexander von Humboldt Fellow in Heidelberg, Germany.
Dr. Wegrzyn told me that she’s “in the hot seat.” The pressure is on for ARPA-H especially after the need and potential for health innovation was spot lit by the pandemic and the unprecedented speed of vaccine development. We'll soon find out if ARPA-H can produce gamechangers in health that are equivalent to DARPA’s creation of the internet.
Show links:
ARPA-H - https://arpa-h.gov/
Dr. Wegrzyn profile - https://arpa-h.gov/people/renee-wegrzyn/
Dr. Wegrzyn Twitter - https://twitter.com/rwegrzyn?lang=en
President Biden Announces Dr. Wegrzyn's appointment - https://www.whitehouse.gov/briefing-room/statement...
Leaps.org coverage of ARPA-H - https://leaps.org/arpa/
ARPA-H program for joints to heal themselves - https://arpa-h.gov/news/nitro/ -
ARPA-H virtual talent search - https://arpa-h.gov/news/aco-talent-search/
Dr. Renee Wegrzyn was appointed director of ARPA-H last October.