A future app may help you avoid getting the flu by informing you of your local risk on a given day.
Applied mathematician Sara del Valle works at the U.S.'s foremost nuclear weapons lab: Los Alamos. Once colloquially called Atomic City, it's a hidden place 45 minutes into the mountains northwest of Santa Fe. Here, engineers developed the first atomic bomb.
Like AccuWeather, an app for disease prediction could help people alter their behavior to live better lives.
Today, Los Alamos still a small science town, though no longer a secret, nor in the business of building new bombs. Instead, it's tasked with, among other things, keeping the stockpile of nuclear weapons safe and stable: not exploding when they're not supposed to (yes, please) and exploding if someone presses that red button (please, no).
Del Valle, though, doesn't work on any of that. Los Alamos is also interested in other kinds of booms—like the explosion of a contagious disease that could take down a city. Predicting (and, ideally, preventing) such epidemics is del Valle's passion. She hopes to develop an app that's like AccuWeather for germs: It would tell you your chance of getting the flu, or dengue or Zika, in your city on a given day. And like AccuWeather, it could help people alter their behavior to live better lives, whether that means staying home on a snowy morning or washing their hands on a sickness-heavy commute.
Sara del Valle of Los Alamos is working to predict and prevent epidemics using data and machine learning.
Since the beginning of del Valle's career, she's been driven by one thing: using data and predictions to help people behave practically around pathogens. As a kid, she'd always been good at math, but when she found out she could use it to capture the tentacular spread of disease, and not just manipulate abstractions, she was hooked.
When she made her way to Los Alamos, she started looking at what people were doing during outbreaks. Using social media like Twitter, Google search data, and Wikipedia, the team started to sift for trends. Were people talking about hygiene, like hand-washing? Or about being sick? Were they Googling information about mosquitoes? Searching Wikipedia for symptoms? And how did those things correlate with the spread of disease?
It was a new, faster way to think about how pathogens propagate in the real world. Usually, there's a 10- to 14-day lag in the U.S. between when doctors tap numbers into spreadsheets and when that information becomes public. By then, the world has moved on, and so has the disease—to other villages, other victims.
"We found there was a correlation between actual flu incidents in a community and the number of searches online and the number of tweets online," says del Valle. That was when she first let herself dream about a real-time forecast, not a 10-days-later backcast. Del Valle's group—computer scientists, mathematicians, statisticians, economists, public health professionals, epidemiologists, satellite analysis experts—has continued to work on the problem ever since their first Twitter parsing, in 2011.
They've had their share of outbreaks to track. Looking back at the 2009 swine flu pandemic, they saw people buying face masks and paying attention to the cleanliness of their hands. "People were talking about whether or not they needed to cancel their vacation," she says, and also whether pork products—which have nothing to do with swine flu—were safe to buy.
At the latest meeting with all the prediction groups, del Valle's flu models took first and second place.
They watched internet conversations during the measles outbreak in California. "There's a lot of online discussion about anti-vax sentiment, and people trying to convince people to vaccinate children and vice versa," she says.
Today, they work on predicting the spread of Zika, Chikungunya, and dengue fever, as well as the plain old flu. And according to the CDC, that latter effort is going well.
Since 2015, the CDC has run the Epidemic Prediction Initiative, a competition in which teams like de Valle's submit weekly predictions of how raging the flu will be in particular locations, along with other ailments occasionally. Michael Johannson is co-founder and leader of the program, which began with the Dengue Forecasting Project. Its goal, he says, was to predict when dengue cases would blow up, when previously an area just had a low-level baseline of sick people. "You'll get this massive epidemic where all of a sudden, instead of 3,000 to 4,000 cases, you have 20,000 cases," he says. "They kind of come out of nowhere."
But the "kind of" is key: The outbreaks surely come out of somewhere and, if scientists applied research and data the right way, they could forecast the upswing and perhaps dodge a bomb before it hit big-time. Questions about how big, when, and where are also key to the flu.
A big part of these projects is the CDC giving the right researchers access to the right information, and the structure to both forecast useful public-health outcomes and to compare how well the models are doing. The extra information has been great for the Los Alamos effort. "We don't have to call departments and beg for data," says del Valle.
When data isn't available, "proxies"—things like symptom searches, tweets about empty offices, satellite images showing a green, wet, mosquito-friendly landscape—are helpful: You don't have to rely on anyone's health department.
At the latest meeting with all the prediction groups, del Valle's flu models took first and second place. But del Valle wants more than weekly numbers on a government website; she wants that weather-app-inspired fortune-teller, incorporating the many diseases you could get today, standing right where you are. "That's our dream," she says.
This plot shows the the correlations between the online data stream, from Wikipedia, and various infectious diseases in different countries. The results of del Valle's predictive models are shown in brown, while the actual number of cases or illness rates are shown in blue.
(Courtesy del Valle)
The goal isn't to turn you into a germophobic agoraphobe. It's to make you more aware when you do go out. "If you know it's going to rain today, you're more likely to bring an umbrella," del Valle says. "When you go on vacation, you always look at the weather and make sure you bring the appropriate clothing. If you do the same thing for diseases, you think, 'There's Zika spreading in Sao Paulo, so maybe I should bring even more mosquito repellent and bring more long sleeves and pants.'"
They're not there yet (don't hold your breath, but do stop touching your mouth). She estimates it's at least a decade away, but advances in machine learning could accelerate that hypothetical timeline. "We're doing baby steps," says del Valle, starting with the flu in the U.S., dengue in Brazil, and other efforts in Colombia, Ecuador, and Canada. "Going from there to forecasting all diseases around the globe is a long way," she says.
But even AccuWeather started small: One man began predicting weather for a utility company, then helping ski resorts optimize their snowmaking. His influence snowballed, and now private forecasting apps, including AccuWeather's, populate phones across the planet. The company's progression hasn't been without controversy—privacy incursions, inaccuracy of long-term forecasts, fights with the government—but it has continued, for better and for worse.
Disease apps, perhaps spun out of a small, unlikely team at a nuclear-weapons lab, could grow and breed in a similar way. And both the controversies and public-health benefits that may someday spin out of them lie in the future, impossible to predict with certainty.
Researchers are looking to engineer chocolate with less oil, which could reduce some of its detriments to health.
Building a 3D tongue
The team began by building a 3D tongue to analyze the physical process by which chocolate breaks down inside the mouth.
As part of the effort, reported earlier this year in the scientific journal ACS Applied Materials and Interfaces, the team studied a large variety of human tongues with the intention to build an “average” 3D model, says Soltanahmadi, a lubrication scientist. When it comes to edible substances, lubrication science looks at how food feels in the mouth and can help design foods that taste better and have more satisfying texture or health benefits.
There are variations in how people enjoy chocolate; some chew it while others “lick it” inside their mouths.
Tongue impressions from human participants studied using optical imaging helped the team build a tongue with key characteristics. “Our tongue is not a smooth muscle, it’s got some texture, it has got some roughness,” Soltanahmadi says. From those images, the team came up with a digital design of an average tongue and, using 3D printed molds, built a “mimic tongue.” They also added elastomers—such as silicone or polyurethane—to mimic the roughness, the texture and the mechanical properties of a real tongue. “Wettability" was another key component of the 3D tongue, Soltanahmadi says, referring to whether a surface mixes with water (hydrophilic) or, in the case of oil, resists it (hydrophobic).
Notably, the resulting artificial 3D-tongues looked nothing like the human version, but they were good mimics. The scientists also created “testing kits” that produced data on various physical parameters. One such parameter was viscosity, the measure of how gooey a food or liquid is — honey is more viscous compared to water, for example. Another was tribology, which defines how slippery something is — high fat yogurt is more slippery than low fat yogurt; milk can be more slippery than water. The researchers then mixed chocolate with artificial saliva and spread it on the 3D tongue to measure the tribology and the viscosity. From there they were able to study what happens inside the mouth when we eat chocolate.
The team focused on the stages of lubrication and the location of the fat in the chocolate, a process that has rarely been researched.
The artificial 3D-tongues look nothing like human tongues, but they function well enough to do the job.
Courtesy Anwesha Sarkar and University of Leeds
The oral processing of chocolate
We process food in our mouths in several stages, Soltanahmadi says. And there is variation in these stages depending on the type of food. So, the oral processing of a piece of meat would be different from, say, the processing of jelly or popcorn.
There are variations with chocolate, in particular; some people chew it while others use their tongues to explore it (within their mouths), Soltanahmadi explains. “Usually, from a consumer perspective, what we find is that if you have a luxury kind of a chocolate, then people tend to start with licking the chocolate rather than chewing it.” The researchers used a luxury brand of dark chocolate and focused on the process of licking rather than chewing.
As solid cocoa particles and fat are released, the emulsion envelops the tongue and coats the palette creating a smooth feeling of chocolate all over the mouth. That tactile sensation is part of the chocolate’s hedonistic appeal we crave.
Understanding the make-up of the chocolate was also an important step in the study. “Chocolate is a composite material. So, it has cocoa butter, which is oil, it has some particles in it, which is cocoa solid, and it has sugars," Soltanahmadi says. "Dark chocolate has less oil, for example, and less sugar in it, most of the time."
The researchers determined that the oral processing of chocolate begins as soon as it enters a person’s mouth; it starts melting upon exposure to one’s body temperature, even before the tongue starts moving, Soltanahmadi says. Then, lubrication begins. “[Saliva] mixes with the oily chocolate and it makes an emulsion." An emulsion is a fluid with a watery (or aqueous) phase and an oily phase. As chocolate breaks down in the mouth, that solid piece turns into a smooth emulsion with a fatty film. “The oil from the chocolate becomes droplets in a continuous aqueous phase,” says Soltanahmadi. In other words, as solid cocoa particles and fat are released, the emulsion envelops the tongue and coats the palette, creating a smooth feeling of chocolate all over the mouth. That tactile sensation is part of the chocolate’s hedonistic appeal we crave, says Soltanahmadi.
Finding the sweet spot
After determining how chocolate is orally processed, the research team wanted to find the exact sweet spot of the breakdown of solid cocoa particles and fat as they are released into the mouth. They determined that the epicurean pleasure comes only from the chocolate's outer layer of fat; the secondary fatty layers inside the chocolate don’t add to the sensation. It was this final discovery that helped the team determine that it might be possible to produce healthier chocolate that would contain less oil, says Soltanahmadi. And therefore, less fat.
Rongjia Tao, a physicist at Temple University in Philadelphia, thinks the Leeds study and the concept behind it is “very interesting.” Tao, himself, did a study in 2016 and found he could reduce fat in milk chocolate by 20 percent. He believes that the Leeds researchers’ discovery about the first layer of fat being more important for taste than the other layer can inform future chocolate manufacturing. “As a scientist I consider this significant and an important starting point,” he says.
Chocolate is rich in polyphenols, naturally occurring compounds also found in fruits and vegetables, such as grapes, apples and berries. Research found that plant polyphenols can protect against cancer, diabetes and osteoporosis as well as cardiovascular ad neurodegenerative diseases.
Not everyone thinks it’s a good idea, such as chef Michael Antonorsi, founder and owner of Chuao Chocolatier, one of the leading chocolate makers in the U.S. First, he says, “cacao fat is definitely a good fat.” Second, he’s not thrilled that science is trying to interfere with nature. “Every time we've tried to intervene and change nature, we get things out of balance,” says Antonorsi. “There’s a reason cacao is botanically known as food of the gods. The botanical name is the Theobroma cacao: Theobroma in ancient Greek, Theo is God and Brahma is food. So it's a food of the gods,” Antonorsi explains. He’s doubtful that a chocolate made only with a top layer of fat will produce the same epicurean satisfaction. “You're not going to achieve the same sensation because that surface fat is going to dissipate and there is no fat from behind coming to take over,” he says.
Without layers of fat, Antonorsi fears the deeply satisfying experiential part of savoring chocolate will be lost. The University of Leeds team, however, thinks that it may be possible to make chocolate healthier - when consumed in limited amounts - without sacrificing its taste. They believe the concept of less fatty but no less slick chocolate will resonate with at least some chocolate-makers and consumers, too.
Chocolate already contains some healthful compounds. Its cocoa particles have “loads of health benefits,” says Soltanahmadi. Dark chocolate usually has more cocoa than milk chocolate. Some experts recommend that dark chocolate should contain at least 70 percent cocoa in order for it to offer some health benefit. Research has shown that the cocoa in chocolate is rich in polyphenols, naturally occurring compounds also found in fruits and vegetables, such as grapes, apples and berries. Research has shown that consuming plant polyphenols can be protective against cancer, diabetes and osteoporosis as well as cardiovascular and neurodegenerative diseases.
“So keeping the healthy part of it and reducing the oily part of it, which is not healthy, but is giving you that indulgence of it … that was the final aim,” Soltanahmadi says. He adds that the team has been approached by individuals in the chocolate industry about their research. “Everyone wants to have a healthy chocolate, which at the same time tastes brilliant and gives you that self-indulging experience.”
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.”