Researchers are looking to engineer chocolate with less oil, which could reduce some of its detriments to health.
Creamy milk with velvety texture. Dark with sprinkles of sea salt. Crunchy hazelnut-studded chunks. Chocolate is a treat that appeals to billions of people worldwide, no matter the age. And it’s not only the taste, but the feel of a chocolate morsel slowly melting in our mouths—the smoothness and slipperiness—that’s part of the overwhelming satisfaction. Why is it so enjoyable?
That’s what an interdisciplinary research team of chocolate lovers from the University of Leeds School of Food Science and Nutrition and School of Mechanical Engineering in the U.K. resolved to study in 2021. They wanted to know, “What is making chocolate that desirable?” says Siavash Soltanahmadi, one of the lead authors of a new study about chocolates hedonistic quality.
Besides addressing the researchers’ general curiosity, their answers might help chocolate manufacturers make the delicacy even more enjoyable and potentially healthier. After all, chocolate is a billion-dollar industry. Revenue from chocolate sales, whether milk or dark, is forecasted to grow 13 percent by 2027 in the U.K. In the U.S., chocolate and candy sales increased by 11 percent from 2020 to 2021, on track to reach $44.9 billion by 2026. Figuring out how chocolate affects the human palate could up the ante even more.
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.”
Basecamp Research is using portable labs like this one to gather samples from ecosystems around the world.
Clark works for Basecamp Research, a biotech company headquartered in London, and his job is to collect samples from ecosystems around the world. By extracting DNA from soil, water, plants, microbes and other organisms, Basecamp is building an extensive database of the Earth’s proteins. While DNA itself isn’t a protein, the information stored in DNA is used to create proteins, so extracting, sequencing, and annotating DNA allows for the discovery of unique protein sequences.
Using what they’re finding in the middle of the Atlantic and beyond, Basecamp’s detailed database is constantly growing. The outputs could be essential for cleaning up the damage done by toxic chemicals and finding alternatives to these chemicals.
Catalysts for change
Proteins provide structure and function in all living organisms. Some of these functional proteins are enzymes, which quite literally make things happen.
“Industrial chemistry is heavily polluting, especially the chemistry done in pharmaceutical drug development. Biocatalysis is providing advantages, both to make more complex drugs and to be more sustainable, reducing the pollution and toxicity of conventional chemistry," says Ahir Pushpanath, who heads partnerships for Basecamp.
“Enzymes are perfectly evolved catalysts,” says Ahir Pushpanath, a partnerships lead at Basecamp. ”Enzymes are essentially just a polymer, and polymers are made up of amino acids, which are nature’s building blocks.” He suggests thinking about it like Legos — if you have a bunch of Lego pieces and use them to build a structure that performs a function, “that’s basically how an enzyme works. In nature, these monuments have evolved to do life’s chemistry. If we didn’t have enzymes, we wouldn’t be alive.”
In our own bodies, enzymes catalyze everything from vision to digesting food to regrowing muscles, and these same types of enzymes are necessary in the pharmaceutical, agrochemical and fine chemical industries. But industrial conditions differ from those inside our bodies. So, when scientists need certain chemical reactions to create a particular product or substance, they make their own catalysts in their labs — generally through the use of petroleum and heavy metals.
These petrochemicals are effective and cost-efficient, but they’re wasteful and often hazardous. With growing concerns around sustainability and long-term public health, it's essential to find alternative solutions to toxic chemicals. “Industrial chemistry is heavily polluting, especially the chemistry done in pharmaceutical drug development,” Pushpanath says.
Basecamp is trying to replace lab-created catalysts with enzymes found in the wild. This concept is called biocatalysis, and in theory, all scientists have to do is find the right enzymes for their specific need. Yet, historically, researchers have struggled to find enzymes to replace petrochemicals. When they can’t identify a suitable match, they turn to what Pushpanath describes as “long, iterative, resource-intensive, directed evolution” in the laboratory to coax a protein into industrial adaptation. But the latest scientific advances have enabled these discoveries in nature instead.
Marlon Clark, a research scientist at Basecamp Research, looks for novel biochemistries in the Azores.
Glen Gowers
Enzyme hunters
Whether it’s Clark and a colleague setting off on an expedition, or a local, on-the-ground partner gathering and processing samples, there’s a lot to be learned from each collection. “Microbial genomes contain complete sets of information that define an organism — much like how letters are a code allowing us to form words, sentences, pages, and books that contain complex but digestible knowledge,” Clark says. He thinks of the environmental samples as biological libraries, filled with thousands of species, strains, and sequence variants. “It’s our job to glean genetic information from these samples.”
“We can actually dream up new proteins using generative AI," Pushpanath says.
Basecamp researchers manage this feat by sequencing the DNA and then assembling the information into a comprehensible structure. “We’re building the ‘stories’ of the biota,” Clark says. The more varied the samples, the more valuable insights his team gains into the characteristics of different organisms and their interactions with the environment. Sequencing allows scientists to examine the order of nucleotides — the organic molecules that form DNA — to identify genetic makeups and find changes within genomes. The process used to be too expensive, but the cost of sequencing has dropped from $10,000 a decade ago to as low as $100. Notably, biocatalysis isn’t a new concept — there have been waves of interest in using natural enzymes in catalysis for over a century, Pushpanath says. “But the technology just wasn’t there to make it cost effective,” he explains. “Sequencing has been the biggest boon.”
AI is probably the second biggest boon.
“We can actually dream up new proteins using generative AI,” Pushpanath says, which means that biocataylsis now has real potential to scale.
Glen Gowers, the co-founder of Basecamp, compares the company’s AI approach to that of social networks and streaming services. Consider how these platforms suggest connecting with the friends of your friends, or how watching one comedy film from the 1990s leads to a suggestion of three more.
“They’re thinking about data as networks of relationships as opposed to lists of items,” says Gowers. “By doing the same, we’re able to link the metadata of the proteins — by their relationships to each other, the environments in which they’re found, the way those proteins might look similar in sequence and structure, their surrounding genome context — really, this just comes down to creating a searchable network of proteins.”
On an Azores island, this volcanic opening may harbor organisms that can help scientists identify enzymes for biocatalysis to replace toxic chemicals.
Emma Bolton
Uwe Bornscheuer, professor at the Institute of Biochemistry at the University of Greifswald, and co-founder of Enzymicals, another biocatalysis company, says that the development of machine learning is a critical component of this work. “It’s a very hot topic, because the challenge in protein engineering is to predict which mutation at which position in the protein will make an enzyme suitable for certain applications,” Bornscheuer explains. These predictions are difficult for humans to make at all, let alone quickly. “It is clear that machine learning is a key technology.”
Benefiting from nature’s bounty
Biodiversity commonly refers to plants and animals, but the term extends to all life, including microbial life, and some regions of the world are more biodiverse than others. Building relationships with global partners is another key element to Basecamp’s success. Doing so in accordance with the access and benefit sharing principles set forth by the Nagoya Protocol — an international agreement that seeks to ensure the benefits of using genetic resources are distributed in a fair and equitable way — is part of the company's ethos. “There's a lot of potential for us, and there’s a lot of potential for our partners to have exactly the same impact in building and discovering commercially relevant proteins and biochemistries from nature,” Clark says.
Bornscheuer points out that Basecamp is not the first company of its kind. A former San Diego company called Diversa went public in 2000 with similar work. “At that time, the Nagoya Protocol was not around, but Diversa also wanted to ensure that if a certain enzyme or microorganism from Costa Rica, for example, were used in an industrial process, then people in Costa Rica would somehow profit from this.”
An eventual merger turned Diversa into Verenium Corporation, which is now a part of the chemical producer BASF, but it laid important groundwork for modern companies like Basecamp to continue to scale with today’s technologies.
“To collect natural diversity is the key to identifying new catalysts for use in new applications,” Bornscheuer says. “Natural diversity is immense, and over the past 20 years we have gained the advantages that sequencing is no longer a cost or time factor.”
This has allowed Basecamp to rapidly grow its database, outperforming Universal Protein Resource or UniProt, which is the public repository of protein sequences most commonly used by researchers. Basecamp’s database is three times larger, totaling about 900 million sequences. (UniProt isn’t compliant with the Nagoya Protocol, because, as a public database, it doesn’t provide traceability of protein sequences. Some scientists, however, argue that Nagoya compliance hinders progress.)
“Eventually, this work will reduce chemical processes. We’ll have cleaner processes, more sustainable processes," says Uwe Bornscheuer, a professor at the University of Greifswald.
With so much information available, Basecamp’s AI has been trained on “the true dictionary of protein sequence life,” Pushpanath says, which makes it possible to design sequences for particular applications. “Through deep learning approaches, we’re able to find protein sequences directly from our database, without the need for further laboratory-directed evolution.”
Recently, a major chemical company was searching for a specific transaminase — an enzyme that catalyzes a transfer of amino groups. “They had already spent a year-and-a-half and nearly two million dollars to evolve a public-database enzyme, and still had not reached their goal,” Pushpanath says. “We used our AI approaches on our novel database to yield 10 candidates within a week, which, when validated by the client, achieved the desired target even better than their best-evolved candidate.”
Basecamp’s other huge potential is in bioremediation, where natural enzymes can help to undo the damage caused by toxic chemicals. “Biocatalysis impacts both sides,” says Gowers. “It reduces the usage of chemicals to make products, and at the same time, where contamination sites do exist from chemical spills, enzymes are also there to kind of mop those up.”
So far, Basecamp's round-the-world sampling has covered 50 percent of the 14 major biomes, or regions of the planet that can be distinguished by their flora, fauna, and climate, as defined by the World Wildlife Fund. The other half remains to be catalogued — a key milestone for understanding our planet’s protein diversity, Pushpanath notes.
There’s still a long road ahead to fully replace petrochemicals with natural enzymes, but biocatalysis is on an upward trajectory. "Eventually, this work will reduce chemical processes,” Bornscheuer says. “We’ll have cleaner processes, more sustainable processes.”
In an initial study, Canary analyzed speech recordings with AI and identified early stage Alzheimer’s with 96 percent accuracy.
Arnold was diagnosed sooner than many others. It's important to find out early, when interventions can make the most difference. One promising avenue is looking at how people talk. Research has shown that Alzheimer’s affects a part of the brain that controls speech, resulting in small changes before people show other signs of the disease.
Now, Canary Speech, a company based in Utah, is using AI to examine elements like the pitch of a person’s voice and their pauses. In an initial study, Canary analyzed speech recordings with AI and identified early stage Alzheimer’s with 96 percent accuracy.
Developing the AI model
Canary Speech’s CEO, Henry O’Connell, met cofounder Jeff Adams about 40 years before they started the company. Back when they first crossed paths, they were both living in Bethesda, Maryland; O’Connell was a research fellow at the National Institutes of Health studying rare neurological diseases, while Adams was working to decode spy messages. Later on, Adams would specialize in building mathematical models to analyze speech and sound as a team leader in developing Amazon's Alexa.
It wasn't until 2015 that they decided to make use of the fit between their backgrounds. ““We established Canary Speech in 2017 to build a product that could be used in multiple languages in clinical environments,” O'Connell says.
The need is growing. About 55 million people worldwide currently live with Alzheimer’s, a number that is expected to double by 2050. Some scientists think the disease results from a buildup of plaque in the brain. It causes mild memory loss at first and, over time, this issue get worse while other symptoms, such as disorientation and hallucinations, can develop. Treatment to manage the disease is more effective in the earlier stages, but detection is difficult since mild symptoms are often attributed to the normal aging process.
O’Connell and Adams specialize in the complex ways that Alzheimer’s effects how people speak. Using AI, their mathematical model analyzes 15 million data points every minute, focusing on certain features of speech such as pitch, pauses and elongation of words. It also pays attention to how the vibrations of vocal cords change in different stages of the disease.
To create their model, the team used a type of machine learning called deep neural nets, which looks at multiple layers of data - in this case, the multiple features of a person’s speech patterns.
“Deep neural nets allow us to look at much, much larger data sets built out of millions of elements,” O’Connell explained. “Through machine learning and AI, we’ve identified features that are very sensitive to an Alzheimer’s patient versus [people without the disease] and also very sensitive to mild cognitive impairment, early stage and moderate Alzheimer's.” Based on their learnings, Canary is able to classify the disease stage very quickly, O’Connell said.
“When we’re listening to sublanguage elements, we’re really analyzing the direct result of changes in the brain in the physical body,” O’Connell said. “The brain controls your vocal cords: how fast they vibrate, the expansion of them, the contraction.” These factors, along with where people put their tongues when talking, function subconsciously and result in subtle changes in the sounds of speech.
Further testing is needed
In an initial trial, Canary analyzed speech recordings from phone calls to a large U.S. health insurer. They looked at the audio recordings of 651 policyholders who had early stage Alzheimer’s and 1018 who did not have the condition, aiming for a representative sample of age, gender and race. They used this data to create their first diagnostic model and found that it was 96 percent accurate in identifying Alzheimer’s.
Christian Herff, an assistant professor of neuroscience at Maastricht University in the Netherlands, praised this approach while adding that further testing is needed to assess its effectiveness.
“I think the general idea of identifying increased risk for cognitive impairment based on speech characteristics is very feasible, particularly when change in a user’s voice is monitored, for example, by recording speech every year,” Herff said. He noted that this can only be a first indication, not a full diagnosis. The accuracy still needs to be validated in studies that follows individuals over a period of time, he said.
Toby Walsh, a professor of artificial intelligence at the University of New South Wales, also thinks Canary’s tool has potential but highlights that Canary could diagnose some people who don’t really have the disease. “This is an interesting and promising application of AI,” he said, “but these tools need to be used carefully. Imagine the anxiety of being misdiagnosed with Alzheimer’s.”
As with many other AI tools, privacy and bias are additional issues to monitor closely, Walsh said.
Other languages
A related issue is that not everyone is fluent in English. Mahnaz Arvaneh, a senior lecturer in automatic control and systems engineering at the University of Sheffield, said this could be a blind spot.
“The system may not be very accurate for those who have English as their second language as their speaking patterns would be different, and any issue might be because of language deficiency rather than cognitive issues,” Arvaneh said.
The team is expanding to multiple languages starting with Japanese and Spanish. The elements of the model that make up the algorithm are very similar, but they need to be validated and retrained in a different language, which will require access to more data.
Recently, Canary analyzed the phone calls of 233 Japanese patients who had mild cognitive impairment and 704 healthy people. Using an English model they were able to identify the Japanese patients who had mild cognitive impairment with 78 percent accuracy. They also developed a model in Japanese that was 45 percent accurate, and they’re continuing to train it with more data.
The future
Canary is using their model to look at other diseases like Huntington’s and Parkinson’s. They’re also collaborating with pharmaceuticals to validate potential therapies for Alzheimer’s. By looking at speech patterns over time, Canary can get an indication of how well these drugs are working.
Dave Arnold and his wife dance at his nephew’s wedding in Rochester, New York, ten years ago, before his Alzheimer's diagnosis.
Dave Arnold
Ultimately, they want to integrate their tool into everyday life. “We want it to be used in a smartphone, or a teleconference call so that individuals could be examined in their home,” O’Connell said. “We could follow them over time and work with clinical teams and hospitals to improve the evaluation of patients and contribute towards an accurate diagnosis.”
Arnold, the patient with early stage Alzheimer’s, sees great promise. “The process of getting a diagnosis is already filled with so much anxiety,” he said. “Anything that can be done to make it easier and less stressful would be a good thing, as long as it’s proven accurate.”