'Periodic table' for AI methods aims to drive innovation

Eslam Abdelaleem led the work as an Emory graduate student. The day of the final breakthrough, the AI health tracker on his watch recorded his racing heart as three hours of cycling. "That's how it interpretated the level of excitement I was feeling," Abdelaleem says. (Photo by Barbara Conner)

Artificial intelligence is increasingly used to integrate and analyze multiple types of data formats, such as text, images, audio and video. One challenge slowing advances in multimodal AI, however, is the process of choosing the algorithmic method best aligned to the specific task an AI system needs to perform. 

Scientists have developed a unified view of AI methods aimed at systemizing this process. The Journal of Machine Learning Research published the new framework for deriving algorithms, developed by physicists at Emory University. 

“We found that many of today’s most successful AI methods boil down to a single, simple idea — compress multiple kinds of data just enough to keep the pieces that truly predict what you need,” says Ilya Nemenman, Emory professor of physics and senior author of the paper. “This gives us a kind of ‘periodic table’ of AI methods. Different methods fall into different cells, based on which information a method’s loss function retains or discards.”

Read the full story here.

Electric charge connects jumping worm to prey

A tiny worm that leaps high into the air — up to 25 times its body length — to attach to flying insects uses static electricity to perform this astounding feat, scientists have found. The journal PNAS published the work on the nematode Steinernema carpocapsae, a parasitic roundworm, led by researchers at Emory University and the University of California, Berkeley. 

“We’ve identified the electrostatic mechanism this worm uses to hit its target, and we’ve shown the importance of this mechanism for the worm’s survival,” says co-author Justin Burton, an Emory professor of physics whose lab led the mathematical analyses of laboratory experiments. “Higher voltage, combined with a tiny breath of wind, greatly boosts the odds of a jumping worm connecting to a flying insect.” 

“You might expect to find big discoveries in big animals, but the tiny ones also hold a lot of interesting secrets,” adds Victor Ortega-Jiménez, co-lead author and assistant professor of biomechanics at the University of California, Berkeley. He conducted the experiments, including the use of highspeed microscopy techniques to film the parasitic worm — whose length is about the diameter of a needle point — as it leaped onto electrically charged fruit flies. 

The researchers showed how a charge of a few hundred volts, similar to that generated by an insect’s wings beating the air, initiates an opposite charge in the worm, creating an attractive force. They identified electrostatic induction as the charging mechanism driving this process.

Read the full story here.

AI reveals new physics in dusty plasma

Physicists used a machine-learning method to identify surprising new twists on the non-reciprocal forces governing a many-body system.

The journal PNAS published the findings by experimental and theoretical physicists at Emory University, based on a neural network model and data from laboratory experiments on dusty plasma — ionized gas containing suspended dust particles. 

The work is one of the relatively few instances of using AI not as a data processing or predictive tool, but to discover new physical laws governing the natural world.

"We showed that we can us AI to discover new physics," says Justin Burton, an Emory professor of experimental physics and senior co-author of the paper. "Our AI method is not a black box: we understand how and why it works. The framework it provides is also universal. It could potentially be applied to other many-body systems to open to new routes to discovery."

Read the full story here.

New AI tool set to speed quest for advanced superconductors

Xu Chen, an Emory PhD student of theoretical chemistry, is first author of the paper. He says the team was inspired by the image-recognition training used for self-driving cars to create a powerful machine-learning framework.

Using artificial intelligence shortens the time to identify complex quantum phases in materials from months to minutes, finds a new study published in Newton. The breakthrough could significantly speed up research into quantum materials, particularly low-dimensional superconductors. 

The study was led by theorists at Emory University and experimentalists at Yale University. Senior authors include Fang Liu and Yao Wang, assistant professors in Emory’s Department of Chemistry, and Yu He, assistant professor in Yale’s Department of Applied Physics. 

The team applied machine-learning techniques to detect clear spectral signals that indicate phase transitions in quantum materials — systems where electrons are strongly entangled. These materials are notoriously difficult to model with traditional physics because of their unpredictable fluctuations. 

“Our method gives a fast and accurate snapshot of a very complex phase transition, at virtually no cost,” says Xu Chen, the study’s first author and an Emory PhD student in chemistry. “We hope this can dramatically speed up discoveries in the field of superconductivity.” 

One of the challenges in applying machine learning to quantum materials is the lack of sufficient high-quality experimental data needed to train models. To overcome this, the researchers used high-throughput simulations to generate large amounts of data. They then combined these simulation results with just a small amount of experimental data to create a powerful and efficient machine-learning framework.

Read more about the discovery.

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A new clue to how multicellular life may have evolved

The idea for the work came from watching the filter feeding of stentors — trumpet-shaped, single-celled giants that float near the surface of ponds. (Getty Images)

Life emerged on Earth some 3.8 billion years ago. The “primordial soup theory” proposes that chemicals floating in pools of water, in the presence of sunlight and electrical discharge, spontaneously formed organic molecules. These building blocks of life underwent chemical reactions, likely driven by RNA, eventually leading to the formation of single cells. 

But what sparked single cells to assemble into more complex, multicellular life forms? 

Nature Physics published a new insight about a possible driver of this key step in evolution — the fluid dynamics of cooperative feeding. 

“So much work on the origins of multicellular life focuses on chemistry,” says Shashank Shekhar, lead author of the study and assistant professor of physics at Emory University. “We wanted to investigate the role of physical forces in the process.” 

Shekhar got the idea while watching the filter feeding of stentors — trumpet-shaped, single-celled giants that float near the surface of ponds. Through microscope video, he captured the fluid dynamics of a stentor in a liquid-filled lab dish as the organism sucked in particles suspended in the liquid. He also recorded the fluid dynamics of pairs and groups of stentors clumped together and feeding. 

The videos revealed a world similar to how Van Gogh saw the night sky, swirling with stars. 

“The project started with beautiful images of the fluid flows,” Shekhar says. “Only later did we realize the evolutionary significance of this behavior.”

Read the full story by clicking here.

Celebrating Valentine's Day and science

Emory biophysicists Jennifer Rieser and Gordon Berman enjoy a hike in Aspen following a summer conference.

Jennifer Rieser, assistant professor of physics, and Gordon Berman, associate professor of biology, connected at Cornell University in 2006. They are fascinated by the biophysics of animal behaviors, tackling esoteric questions such as variations in how organisms move. 

“We both noticed each other,” Berman recalls of their first meeting. Berman was already working on his PhD, studying the biodynamics of insect flight, when Rieser attended a recruitment weekend for graduate students. 

“I reached out to him afterwards to learn more about what it’s like at Cornell,” Rieser says. 

Berman didn’t discourage her. She was enrolled that fall, and, by Christmas, Berman informed his mother he had a girlfriend. 

They married in 2010. Their eventual move to Atlanta was a homecoming for Rieser, who grew up in nearby Lawrenceville, while Berman is from Michigan. 

During the COVID-19 lockdown they shared a Midtown loft, teaching online on opposite sides of the space, sometimes simultaneously. “And we didn’t get tired of each other,” Berman says. “We survived that test.” 

They now live just a few blocks from campus with daughter, Naomi, who is two-and-a-half, and dogs Escher and Kona. 

Berman focuses more on theoretical and computational methods, while Rieser takes an experimental approach to the locomotion of everything from snakes to ants. They often run their research by one another to get feedback from their complementary strengths. 

They manage to combine work and play, traveling together following conferences or summer teaching gigs that took them to Brazil, Italy and Germany. And they enjoy cooking and eating nice meals. 

“I tend to bake things,” Rieser says. 

“She’s more a creature of precision,” Berman explains. “Her signature dish is a chocolate babka, a very decadent bread.” 

"He’s more of an improvisational chef,” Rieser says. 

“Give me a cabinet of ingredients and a couple of adjectives,” Berman says, “and I can make you a bespoke, likely unrepeatable cocktail.”

Read more stories of Emory scientific power couples.

Atlanta Science Festival returns to inspire discovery for all ages

A middle-school student experiences an Emory chemistry lab during a recent community outreach event. 

The Atlanta Science Festival returns March 9 to 23, inviting curious kids and adults to explore all things science, technology, engineering and mathematics (STEM). Experts in these fields — including many members of the Emory community — will serve as educational guides for more than 150 interactive events. 

“The Atlanta Science Festival aims to bring the community together through their shared love of science,” says Meisa Salaita, co-founder and co-executive director of Science ATL, the engineers of the festival. “Through these events, we hope to inspire and empower the next generation to pursue their dreams.” 

Participants can take a crash course on the basics of AI, create an herbarium of medicinal plants, go into the field with researchers studying microplastic pollution in a stream, take a behind-the-scenes tour of the latest advances in healthcare technology and even get a taste of the physics of cheese making. 

Now in its 11th year, the Atlanta Science Festival was co-founded by Emory, Georgia Tech and the Metro Atlanta Chamber. 

“We have grown into a mainstay of Atlanta,” says Salaita, noting that many of the events fill up quickly. “The festival is something that people look forward to every spring.” 

 Click here for highlights of this year's festival with an Emory connection.

New tool to analyze blood platelets holds major medical potential

Graphic image shows a blood clot forming in an artery. The white, spikey platelets are amid red and white blood cells. Activated platelets use their spkes like "arms" to grip onto one another and to stringy chains of proteins in the blood called fibrin, forming clumps that also bind up red and white blood cells.

By Carol Clark

A novel technique to test platelet function within a person’s blood sample is faster, easier and more precise than methods currently in use, an experimental study shows. 

Nature Biomedical Engineering published the research, led by scientists at Emory University. The researchers demonstrated the proof-of-concept for the technique, which provides the first detailed look at the molecular forces generated by activated platelets in patient blood samples. 

The study results show that the technology holds the potential to assess the effects of antiplatelet drugs on individuals and to gain a clearer picture of bleeding risks for patients undergoing cardiopulmonary bypass surgery. 

The technique requires only about a drop of blood to run tests, compared to the tablespoon needed for current assays. This ultrasensitivity may make the technology a valuable tool for the diagnosis of babies suffering from rare, congenital platelet disorders. 

The breakthrough is based on synthetic-DNA tension probes developed more than a decade ago in the laboratory of Khalid Salaita, professor in Emory’s Department of Chemistry and in the Wallace H. Coulter Department of Biomedical Engineering at Emory and Georgia Tech. 

‘A scientist’s dream’ 

The tension probes can detect cellular forces on the magnitude of just a few piconewtons, or about a billion times less than the weight of a paper clip. The researchers found a way to amplify the signal of the probes by tapping the power of an enzyme known as CRISPR-associated 12a. The mechanical signal is then detected using a plate-reader, a tool already routinely used in clinical testing. 

“This project started out of basic curiosity,” says Salaita, co-corresponding author. “We wanted to know whether we could measure the tiniest forces exerted by cells. It’s exciting that we are now building on this basic curiosity to develop diagnostic tools to help patients. It’s a scientist’s dream.” 

First author of the paper is Yuxin Duan, an American Heart Association postdoctoral fellow in the Salaita lab. 

Roman Sniecinski, a professor in Emory School of Medicine’s Department of Anesthesiology and a leading expert in the field of perioperative coagulation, is co-corresponding author of the paper.

“Platelet function in general is important and yet the current tools that we have to measure it are relatively primitive,” Sniecinski says. “This new technique offers an easier, faster and cheaper way to measure platelet function, while also providing us with key information that we didn’t have before.” 

Co-authors include: Fania Szlam, a senior associate in the Sniecinski lab; Yuesong Hu, a graduate student in the Salaita lab; Renhao Li, a professor in Emory School of Medicine’s Department of Pediatrics, Hematology/Oncology; Wenchun Chen, a postdoctoral fellow in Emory School of Medicine; and Yonggang Ke, an associate professor in the Coulter Department of Biomedical Engineering at Emory and Georgia Tech. 

The importance of platelets 

Platelets are colorless, disc-shaped blood-cell fragments whose job is to bind at the site of an injured blood vessel to stop the bleeding. In some cases, however, platelets may not function optimally. When platelets are weak, or less active than optimal, the blood may not clot properly leading to uncontrolled bleeding. But if platelets are “hyperactive” they may become too sticky and cause spontaneous blood clots that can lead to heart attack or stroke. 

Regulating platelet function is especially critical to people at higher risk for some conditions. Antiplatelet drugs, such as clopidogrel, ticagrelor and even aspirin, are among the most commonly prescribed medications in the United States. In some patients, however, these drugs may not work well and adjustments in doses or changing to another drug might better help prevent heart attacks. 

During cardiac surgery, platelet function becomes even more dysregulated. The operating-room team must perform a balancing act of making blood not clot during cardiopulmonary bypass, then using procoagulant interventions, including transfusions of platelets, to stop the bleeding when the surgical procedure is finished. This can be difficult because the use of the cardiopulmonary bypass machine can stress and weaken blood platelets. 

“For decades, people have written in the scientific literature about this problem of platelet dysfunction during cardiac surgery,” Sniecinski says, “but it’s really difficult to measure it with the tools that we’ve been using. And since we haven’t been able to measure platelet function well, that’s made it difficult to study it in effective ways.” 

‘A small part of the picture’ 

Aggregometry is a standard tool currently used to assess platelet function. It measures the speed and degree at which platelets in a blood sample clump together, or aggregate. 

“This data provides only a small part of the picture of platelet function and it’s not the most interesting part,” Sniecinski says. 

When a platelet gets activated, he explains, it changes its morphology and grows tiny pseudo “arms.” Platelets use these arms to grip onto chains of proteins in the blood called fibrinogen to form clots. 

“Aggregometry tells you that platelets are clumping together,” Sniecinski says. “But it doesn’t tell you about their level of activation — the amount of force they’re using to hold on to other coagulation proteins, as well as each other.” 

Amplifying the signal 

The Salaita lab is a leader in visualizing and measuring the mechanical forces applied by cells using tension probes made from synthetic strands of double-stranded DNA tethered to a surface. 

The double-strands of DNA can be programmed to bind to platelet cells. When the cells bind and apply force to the anchored DNA, the DNA splits into two strands, leaving one strand stuck to the surface. The resulting physical tug is converted into a fluorescent signal. 

A major challenge to reading this signal, however, is that these physical tugs are faint, fleeting and infrequent. They require a microscope to detect them. 

During the COVID-19 pandemic , the enzyme CRISPR 12a, or Cas12a, came to the fore as a diagnostic tool for SARS-CoV-2 virus. Bacteria use Cas12a to defend against phages, or viruses that attack bacteria. The Cas12a enzyme can be loaded with single-stranded “guide” RNA that is programmed to bind to a complementary single-stranded DNA. The enzyme then reacts to the single-stranded DNA by destroying other single-stranded DNA surrounding it. 

The Salaita lab decided to combine Cas12a with its tension probes to see if the enzyme would amplify the signal for the mechanical forces exerted by blood platelets. The lab developed what it calls the Mechano-Cas12a Assisted Tension Sensor, or MCATS. 

“It worked like gangbusters,” Salaita says. 

“Cas12a is quiet and inactive if it doesn’t see its target,” he explains. “But as soon as it sees a specific single-strand DNA, it goes bananas and starts destroying any single-stranded DNA it comes across. This activation generates a massive fluorescence signal output.” 

MCATS is precise and ultrasensitive, able to measure cellular traction forces generated by as few as 2,000 platelets within a sample. And the resulting signal is robust enough to measure via a conventional fluorometer — a tool commonly used in routine blood tests. 

MCATS also works with a plate reader, an instrument designed to handle dozens of samples simultaneously, for the kind of high-throughput readout needed to conduct research. 

Testing its clinical potential 

To test the efficacy of MCATS at measuring the activity of platelet function, the researchers drew blood samples from healthy volunteer donors. They first validated that the MCATS response was sensitive to the mechanical forces of platelets. 

They next added to the healthy blood samples different antiplatelet drugs, ranging from over-the-counter aspirin to a panel of different prescription medications. The MCATS results showed that the antiplatelet therapies reduced the mechanical activity of platelets by an amount similar to the reduction observed in aggregometry. 

The researchers also received permission to take blood samples for investigation from seven patients pre- and post-cardiopulmonary bypass surgery. The results showed that the MCATS readings for the platelet activity of each individual patient’s sample correlated to their likelihood to need platelet transfusions to minimize bleeding after surgery. 

The researchers are now enrolling participants in a prospective study to further explore MCATS as a diagnostic tool. People diagnosed with a platelet disorder will have their blood samples tested pre- and post-treatment to assess how well a therapy is working. 

“The bottom line is that MCATS is a whole new way to measure platelet function using a really tiny sample,” Sniecinski says. “It’s telling us something specific that we haven’t been able to measure before and that can give us a new way to understand what’s going on with platelet dysfunction and the best methods for controlling it.” 

“Blood work up gives you a basic readout of your health based on data like platelet count and metabolic concentrations,” Salaita adds. “Now we’re adding information about the mechanics of platelets. That’s like getting a whole new dial on your dashboard for monitoring your health.” 

Work on the current paper was funded by the National Institutes of Health, the National Science Foundation and the American Heart Association.

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'Firefly' imaging method zooms in on 'the forces within us'

New methods reveal the biomechanics of blood clotting

Math trio makes new points about size of the smallest triangle

"It's a very rich area, to study tiny, small-scale shapes and uncover what the math hidden there can tell us," says Emory mathematician Cosmin Pohoata.

By Carol Clark

Think of a square dotted with points. Now imagine the smallest triangle that could be made by connecting three of those points. That’s the Heilbronn triangle problem in a nutshell. 

“The problem is very easy to state and can sound frivolous,” says Cosmin Pohoata, a theoretical mathematician and Emory assistant professor of mathematics “When I have conversations with non-math friends, they often ask me why we should study problems like this. The beauty of them is that they are often more complex than they seem. They can have unexpected connections that open new doors for understanding all sorts of phenomena.” 

 

Pohoata and two MIT graduate students, Alex Cohen and Dimitrii Zakharov, recently opened some of those new doors. They completed a new proof for the Heilbronn triangle problem that shows that the smallest triangle in a confined space is much smaller than was previously realized, breaking a record that stood for 40 years. 

 

Their proof, available online, is submitted to the Journal of the American Mathematical Society and is already making waves in the math world. 

“I think it’s a stunning result,” Anthony Carbery, a mathematician at the University of Edinburgh, told Qanta Magazine. And Thomas Bloom of the University of Oxford told Qanta that he expects the new proof to “prompt a renaissance” of progress on the triangle problem. 

 

“What makes the proof special to me,” Pohoata says, “is the way that we connected the triangle problem to different areas of math. In particular, harmonic analysis, the study of how waves interact with one another and projection theory, or the behavior of fractals under projections.” 

A graphic representation of the Heilbronn triangle problem.

The making of a mathematician 

Pohoata loved math from the time he was a small child growing up in Romania. He cites an elementary school teacher, who encouraged his love for numbers and patterns, as one key influence. 

In middle school he began competing in International Mathematical Olympiads (IMO). Romania is the original home of the IMO, which dates back to 1959, making it the oldest of the International Science Olympiads. Today more than 100 countries compete in the annual event. 

“I thought I knew a lot about math because the problems in class had been so easy for me,” Pohoata recalls. “When I started competing in the Olympiads, I began to realize how little I knew and how much math was out there to learn.” 

He began to think about math as a career. “It’s quite fun to get to think about problems that interest you,” he says. 

Pohoata attended Princeton as an undergraduate, got his PhD at the California Institute of Technology and taught at Yale before joining Emory this fall. 

Patterns in points and lines 

As a theoretical mathematician, Pohoata focuses his research on three specialized fields: Discrete geometry, additive number theory and extremal combinatorics. 

Extremal combinatorics examines how large or small finite objects such as graphs can be, if placed under certain restrictions. For centuries, it seemed like an esoteric endeavor. 

“The breadcrumbs to extremal combinatorics trace back to ancient Greece,” Pohoata says, “but the field didn’t really come alive until the late 20th century with the rise of computers and the internet. Graphs are at the heart of many things to do with computer science and the internet.” 

Facebook “friend” networks, for example, are large collections of data that are essentially graphs. “You can think of people in the world as points on paper and then draw arrows connecting the ones who are friends,” Pohoata explains. “Then you can look at basic questions underlying these structures. If you have at least seven points do you always have triangles? When do you see a big cluster of connected vertices? Are there areas of the world that are less connected than others?” 

Real-life problems, like how to make algorithms run faster, fuel interest in studying problems about graphs and related areas. 

“As a theorist, I’m driven simply by the math behind shapes and the beauty of them,” Pohoata says, “but I do get excited when I hear that some math breakthrough has been used in a cool way to help with a practical problem.” 

The human side of math 

“I wasn’t interested in the history of math when I first started out,” Pohoata says. “Why learn the progression of results if you have the latest result?” 

But when he taught an introductory course to number theory, it forced him to look more closely at the history of the greats and trace the chronology of events. “I started realizing that you can get many new ideas by following the progress of the past rather than just focusing on the latest thing,” he says. “And I personally learn better when I follow the story of the people in the history of math. You feel the math differently, too, when you put yourself in someone else’s shoes.” 

Pohoata’s interest in the Heilbronn triangle problem inspired him to delve deeper into the work of Klaus Roth, a German-British mathematician who won math’s highest honor, the Fields Medal. “Roth does elegant math that has inspired a lot of activity,” Pohoata says. 

In 1951, Roth developed a strategy for finding the smallest possible triangle within the parameters of the Heilbronn triangle problem, or its so-called “upper bound.” Austrian mathematician Wolfgang Schmidt pushed the upper bound further in a paper published in 1972. That inspired Roth to jump back into the game. Roth further improved the result by Schmidt, just a few months after Schmidt’s breakthrough. 

A tiny problem 

“Roth and Schmidt had a kind of rivalry to see who could come up with the best recipe to find even smaller triangles,” Pohoata says. “They were writing beautiful papers, improving on each other’s work. I learned a lot by studying them.” 

In 1980, a trio of mathematicians — Komlos, Pintz and Szemeredi — pushed the envelope even further, finding a new upper bound to the Heilbronn triangle problem. 

While the problem in its simplest form can be thought of as dots and lines drawn on paper, the mathematicians are working with triangles far too tiny to be “seen” without special tools. 

“You can think of these triangles as microscopic,” Pohoata says. “We’re talking about billions of points crammed within a confined space.” 

Just as scientists keep making improvements in microscopy to get an ever more detailed view of the tiniest parts of a living system or of distant galaxies imperceptible to human eyes on Earth, theoretical mathematicians create tools to get closer and sharper views of the math underlying the universe and everything in it. 

Making connections 

Pohoata had pondered the Heilbronn triangle problem for several months with Zakharov. He met Cohen last year in a chance encounter at MIT, where he had traveled to give a presentation. 

“When math people get together, they like to talk about recent problems on their minds,” he says. “We were excited to learn that we were taking similar approaches to the Heilbronn triangle problem. And that we were all stuck in the same place.” 

The trio decided to join forces. Unlike many of their math heroes of the past, who communicated across distances by letter, they exchanged ideas in real time through Zoom and the Discord instant-messaging platform. 

“Math research is becoming more of a social experience as the world has become more connected,” Pohoata says. “Technology facilitates collaboration.” 

Rather than a single, euphoric eureka moment, he describes the process of creating their 40-page proof as a series of smaller insights. “There are many moving pieces to this proof and each one had to come together,” Pohoata explains. “There was a lot of going back and forth to get all the pieces to fit. You can think of it like putting together a really complex Lego structure.” 

Ultimately, their breakthrough revealed new connections between the Heilbronn triangle problem and other areas of mathematics, including harmonic analysis and fractals — figures that are similar and keep repeating one another at smaller and smaller scales. 

Pohoata and his two MIT colleagues are continuing to work on explaining this web of connections in more detail. “It’s a very rich area, to study tiny, small-scale shapes and uncover what the math hidden there can tell us,” Pohoata says. “What makes math fascinating is that it’s the language for how things work in the world.” 

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NIH funds Emory center to advance cellular mechanics

"We are catalyzing the process of spreading our technology so that studying biomechanics becomes common and routine in biology," says Khalid Salaita, Emory professor of chemistry and director of the new Center for Molecular Mechanobiology.

By Carol Clark

The National Institutes of Health (NIH) awarded Emory University $5.6 million to establish a national center to advance pioneering technology for cellular mechanics. The center is directed by Khalid Salaita, Emory professor of chemistry, whose lab developed the first sensors for detecting cell-receptor forces at the molecular level. 

“We’ve been working on our molecular-force probes for more than a decade,” Salaita says. “We’ve demonstrated that these probes can be used to visualize, measure and map cellular forces down to the level of piconewtons. The center allows us to get this technology into the hands of end users — researchers in the biomedical sciences.” 

The Center for Molecular Mechanobiology encompasses labs from seven leading research institutions including: Children’s Hospital of Philadelphia, Dana-Farber Cancer Institute, Emory, Georgia Tech, Memorial Sloan Kettering, University of Utah and Vanderbilt University. 

The center members will use the molecular-force probes to investigate the biomechanics of processes such as the clotting of blood cells, the response of immune cells to an infection and the migration of cancer cells. Better understanding these processes may lead to the development of new treatments and therapies for a range of diseases and disorders. 

In addition to supplying the technology, the center will train researchers to use the molecular-force probes and help adapt the technology to answer specific biomedical research questions. 

“Working directly with the research community will help us to further refine and optimize the technology,” Salaita says. “We envision that measuring cellular forces will soon become part of the standard repertoire of biochemical techniques that scientists use to study living systems.” 

The center’s associate directors are Yonggan Ke (associate professor in the Wallace H. Coulter Department of Biomedical Engineering at Emory and Georgia Tech) and Alexa Mattheyses (associate professor in the Department of Cell Developmental and Integrative Biology at the University of Alabama). 

The five-year award from the National Institute of General Medical Sciences is part of the NIH Biomedical Technology Optimization and Dissemination Centers program. The goal is to optimize and disseminate state-of-the-art, late-stage biomedical technologies. 

The first detailed view of mechanical forces

The Salaita lab works at the intersection of chemistry, biology and the physical sciences. It uses the building blocks of nature — nucleic acids — to create synthetic micro motors and probes for investigating fundamental questions of biology. 

The molecular-force probes, developed by the Salaita lab in 2011, provide the first detailed view of the mechanical forces on the surface of a cell. The technology can detect mechanical forces as fleeting as the blink of an eye and as faint as piconewtons — about one billionth the weight of a paperclip. 

The probes are made from strands of synthetic DNA tagged with fluorescence so that they function like molecular beacons, shining when they sense force. The technique is noninvasive, does not modify the cell and can be done with a standard fluorescence microscope. 

In 2014, the lab used the new method to demonstrate how adherent cells — the kind that form the architecture of all multicellular organisms — mechanically sense their environments, migrate and stick to things. 

In 2016, the molecular-force probes provided the first direct evidence for the mechanical forces of T cells, the security guards of the immune system. The lab’s experiments on T cells drawn from mice showed how they use a kind of mechanical “handshake” to test whether a cell they encounter is a friend or a foe. 

In 2017, the lab shined its molecular beacons on platelets, the cells in the blood whose job is to stop bleeding by sticking together to form clots and plug up a wound. That work revealed the key molecular forces on platelets that trigger the clotting process. 

In 2020, the lab and its collaborators combined advances in optical imaging with the molecular-force probes to capture forces at a resolution of 25 nanometers — far shorter than the length of a light wave. “That resolution is akin to being on the moon and seeing the ripples caused by raindrops hitting the surface of a lake on the Earth,” Salaita said at the time. 

Key technological goals 

The Center for Molecular Mechanobiology will build on this foundational work of the Salaita lab. It will focus on three key technological development goals:

• Optimizing the highest-resolution technique of the molecular-force probes so that it can be applied to a range of research questions. 

• Tagging cells based on their force level in order to use force as a marker to barcode cells and their receptors. The idea is to classify the mechanics of individual cells and then link these classifications to gene-expression levels to study the cause-and-effect relationships. 

• Amplifying the molecular-force signals to better understand the role of even the weakest forces involved in cellular mechanics, including those involved in the immune response. 

Researchers from throughout the country will come to the Center for Molecular Mechanobiology to receive hands-on training in the molecular-force probes and then return to their home labs to become ambassadors for the technology. 

“We’ll be adding a whole other layer of information for researchers working on everything from designing vaccines to cancer immunotherapy agents,” Salaita says. 

Decades ago, he points out, complicated techniques such as crystallography, PCR and mass spectrometry were not frequently used but have since become routine workhorses in the biomedical sciences. 

“We are catalyzing the process of spreading our technology so that studying biomechanics also becomes common and routine in biology,” Salaita says. “Molecular forces are a missing piece to understanding the way biology works.” 

Related: 

‘Firefly’ imaging method makes cellular forces visible

Chemists reveal the force within you

T cells use ‘handshakes’ to sort friends from foes

New methods reveal the mechanics of blood clotting

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Physicists open new path to exotic form of superconductivity

"Everything we learn about the world has potential applications," says Emory physicist Luiz Santos, senior author of the paper.

By Carol Clark

Physicists have identified a mechanism for the formation of oscillating superconductivity known as pair-density waves. Physical Review Letters published the discovery, which provides new insight into an unconventional superconductive state seen in certain materials, including high-temperature superconductors. 

“We discovered that structures known as Van Hove singularities can produce modulating, oscillating states of superconductivity,” says Luiz Santos, assistant professor of physics at Emory University and senior author of the study. “Our work provides a new theoretical framework for understanding the emergence of this behavior, a phenomenon that is not well understood.” 

First author of the study is Pedro Castro, an Emory physics graduate student. Co-authors include Daniel Shaffer, a postdoctoral fellow in the Santos group, and Yi-Ming Wu from Stanford University. 

The work was funded by the U.S. Department of Energy’s Office of Basic Energy Sciences. 

The puzzle of superconductivity 

Santos is a theorist who specializes in condensed matter physics. He studies the interactions of quantum materials — tiny things such as atoms, photons and electrons — that don’t behave according to the laws of classical physics. 

Superconductivity, or the ability of certain materials to conduct electricity without energy loss when cooled to a super-low temperature, is one example of intriguing quantum behavior. The phenomenon was discovered in 1911 when Dutch physicist Heike Kamerlingh Onnes showed that mercury lost its electrical resistance when cooled to 4 Kelvin or minus 371 degrees Fahrenheit. That’s about the temperature of Uranus, the coldest planet in the solar system. 

It took scientists until 1957 to come up with an explanation for how and why superconductivity occurs. At normal temperatures, electrons roam more or less independently. They bump into other particles, causing them to shift speed and direction and dissipate energy. At low temperatures, however, electrons can organize into a new state of matter. 

“They form pairs that are bound together into a collective state that behaves like a single entity,” Santos explains. “You can think of them like soldiers in an army. If they are moving in isolation they are easier to deflect. But when they are marching together in lockstep it’s much harder to destabilize them. This collective state carries current in a robust way.” 

A holy grail of physics 

Superconductivity holds huge potential. In theory, it could allow for electric current to move through wires without heating them up, or losing energy. These wires could then carry far more electricity, far more efficiently. 

“One of the holy grails of physics is room-temperature superconductivity that is practical enough for everyday-living applications,” Santos says. “That breakthrough could change the shape of civilization.”

Many physicists and engineers are working on this frontline to revolutionize how electricity gets transferred. 

Meanwhile, superconductivity has already found applications. Superconducting coils power electromagnets used in magnetic resonance imaging (MRI) machines for medical diagnostics. A handful of magnetic levitation trains are now operating in the world, built on superconducting magnets that are 10 times stronger than ordinary electromagnets. The magnets repel each other when the matching poles face each other, generating a magnetic field capable of levitating and propelling a train. 

The Large Hadron Collider, a particle accelerator that scientists are using to research the fundamental structure of the universe, is another example of technology that runs through superconductivity. 

Superconductivity continues to be discovered in more materials, including many that are superconductive at higher temperatures.  

An accidental discovery 

One focus of Santos’ research is how interactions between electrons can lead to forms of superconductivity that cannot be explained by the 1957 description of superconductivity. An example of this so-called exotic phenomenon is oscillating superconductivity, when the paired electrons dance in waves, changing amplitude. 

In an unrelated project, Santos asked Castro to investigate specific properties of Van Hove singularities, structures where many electronic states become close in energy. Castro’s project revealed that the singularities appeared to have the right kind of physics to seed oscillating superconductivity. 

That sparked Santos and his collaborators to delve deeper. They uncovered a mechanism that would allow these dancing-wave states of superconductivity to arise from Van Hove singularities. 

“As theoretical physicists, we want to be able to predict and classify behavior to understand how nature works,” Santos says. “Then we can start to ask questions with technological relevance.” 

Some high-temperature superconductors — which function at temperatures about three times as cold as a household freezer — have this dancing-wave behavior. 

The discovery of how this behavior can emerge from Van Hove singularities provides a foundation for experimentalists to explore the realm of possibilities it presents. 

“I doubt that Kamerlingh Onnes was thinking about levitation or particle accelerators when he discovered superconductivity,” Santos says. “But everything we learn about the world has potential applications.” 

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Merck Prize boosts work on air sensor for pandemic pathogens

"There is a need for viral-detecting devices for public indoor air spaces as we enter an era when pandemics will likely become more common," says Emory chemist Khalid Salaita.

Merck KGaA, Darmstadt, Germany, awarded its 2023 Future Insight Prize to Khalid Salaita, professor of chemistry at Emory University. The award comes with $540,000 to fund the next phase of research into an air sensor that can continuously monitor indoor spaces for pathogens that can cause pandemics. 

“I’m extremely thankful to receive the Future Insight Prize as this enables us to continue our path toward an early-warning system for emerging threats,” Salaita says. “Our research sets the stage for fully automated detection of airborne pathogens without human intervention or sample processing.” 

The Merck Future Insight Prize recognizes groundbreaking ideas to solve some of the world’s most pressing challenges in health, nutrition and energy. 

The Salaita lab’s sensor, a rolling micro-motor called “Rolosense,” holds the potential to help mitigate, or even prevent, a pandemic. 

Read the full story here.

Biophysicists reveal how three proteins interact to fine-tune cellular movement

Graduate student Heidi Ulrichs created this cartoon to illustrate previous theories that three enzymes could not all "dance" together on the end of an actin filament. The filament (in blue) is shown with the enzymes, in pink, gold and green, engaged in a kind of "sibling rivalry." The Emory physicists discovered that, in fact, the three enzymes could simultaneously work together on the end of an actin filament.
 

By Carol Clark

A single human cell teems with as many 100,000 different proteins. Actin is one of the most abundant and essential of them all. This protein forms into filaments that help make up the skeleton of cells, giving them shape. And as the actin filaments elongate, they work like muscles, pushing against the inner membrane of a cell to move it forward. 

Three other proteins are known to drive the activities of actin. One class of protein assembles individual actin molecules into actin filaments, another causes the filaments to stop growing and a third disassembles filaments. 

Biophysicists at Emory University, however, have discovered an even more complex and nuanced view of how these three proteins together influence actin dynamics. Nature Communications published the findings, showing how these proteins sometimes shift from solo or duet acts to perform as a trio, allowing them to fine-tune the activity of actin filaments. 

The discovery opens another window onto the dynamics of cellular movement, which is key to processes ranging from stem-cell differentiation and wound healing to the development of diseases such as cancer. 

“We found that while these three proteins do one thing when working on their own, they do a completely different thing when the other two proteins join them,” says Shashank Shekhar, Emory assistant professor of physics and cell biology, and senior author of the study. “It gets really complex, very fast.” 

“No one had looked at all of these proteins interacting at once on actin,” adds Heidi Ulrichs, co-first author of the study and an Emory PhD candidate in biochemistry, cell and developmental biology. “Our paper is the first report of all three of them occupying the same barbed end of an actin filament.” 

Ulrichs worked closely on the project with Ignas Gaska, a postdoctoral fellow in the Shekkhar lab who is co-first author of the paper. 

Building on previous research 

Research into how proteins act individually on actin is relatively well-characterized. 

A polymerase protein, such as formin, drives elongation of actin. Formin positions itself at the end of an actin filament, grabs onto free-floating actin molecules and stacks them up one by one to keep growing the end. 

Depolymerase proteins, such as twinfilin, are another class of proteins that influence actin. Twinfilin works like a lint roller, binding to the end of a filament and peeling away one molecule at a time. Twinfilin can repeat the process to disassemble the actin filament entirely. 

Proteins known as cappers can stop the elongation and disassembling of the filaments. A capper attaches to the end of an actin filament and covers it like a hat, blocking activity by the other proteins. 

This knowledge was built up by isolating one protein at a time to study how it influences actin. More recent studies have also shown simultaneous interactions between twinfilin and capping proteins. 

A new approach using advanced technology 

For the current study, the researchers wanted to explore whether formin, twinfilin and the capping protein could all three act simultaneously on actin. 

“An actin filament end is really tiny, just five nanometers across,” Shekhar explains. “One thought was that there just isn’t enough real estate available for three proteins to work on a single actin filament at once.” 

The Shekhar lab is one of only a handful in the world using the highly specialized technique of microfluidics-assisted total internal reflection fluorescence microscopy (mf-TIRF) to study how the actin cytoskeleton remodels itself. 

Cells are packed with thousands of proteins moving around, performing different functions, making it impossible to track all of them. Researchers must isolate the proteins of interest and study them outside of a cellular system, by introducing them to a microfluidic system on a microscope slide. 

The mf-TIRF technology allows the Shekhar Lab to attach fluorescent orbs to single protein molecules so that researchers can better observe what these molecules are doing through a microscope. 

In experiments, the researchers tagged molecules of actin, formin, twinfilin and the capping protein with four different colors that emitted fluorescent light. They then introduced actin to the microfluidic system and added the other proteins one at a time. 

Establishing a new paradigm 

The results startled them. 

When twinfilin, the protein that breaks apart an actin filament, was added in the presence of both formin and the capping protein, twinfilin actually worked to speed up the process of filament elongation. 

“That’s counterintuitive, which is cool,” Ulrichs says. “Doing science you get surprised all the time.” 

Twinfilin alone could not join formin on the end of the actin filament. However, when the capping protein was also present, all three could simultaneously work together on the tiny surface of the actin filament. 

Shekhar compares the effects of all three proteins working together to a knob that allows for more precise control of a process. 

“Our findings establish a new paradigm in which the three proteins work in concert to fine-tune how fast or slowly actin filaments are formed,” he says. The dynamics of how the three proteins interact with actin is fundamental to teasing apart the complex mysteries of how cells function normally and what happens when something goes wrong. 

“We’re building up knowledge, step by step, study by study, on the dynamics of what’s happening inside of a cell,” Ulrichs says. 

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How protein assemblies drive cell movement 

'Firefly' imaging zooms in on the forces within us

As the worm turns: New twists in behavioral association theories

The researchers conducted experiments on C. elegans, a roundworm with just 300 neurons, that offers a simple laboratory model for studying how an animal learns.

By Carol Clark

Physicists have developed a dynamical model of animal behavior that may explain some mysteries surrounding associative learning going back to Pavlov’s dogs. The Proceedings of the National Academy of Sciences (PNAS) published the findings, based on experiments on a common laboratory organism, the roundworm C. elegans. 

“We showed how learned associations are not mediated by just the strength of an association, but by multiple, nearly independent pathways — at least in the worms,” says Ilya Nemenman, an Emory professor of physics and biology whose lab led the theoretical analyses for the paper. “We expect that similar results will hold for larger animals as well, including maybe in humans.” 

“Our model is dynamical and multi-dimensional,” adds William Ryu, an associate professor of physics at the Donnelly Centre at the University of Toronto, whose lab led the experimental work. “It explains why this example of associative learning is not as simple as forming a single positive memory. Instead, it’s a continuous interplay between positive and negative associations that are happening at the same time.” 

First author of the paper is Ahmed Roman, who worked on the project as an Emory graduate student and is now a postdoctoral fellow at the Broad Institute. Konstaintine Palanski, a former graduate student at the University of Toronto, is also an author. 

The conditioned reflex

More than 100 years ago, Ivan Pavlov discovered the “conditioned reflex” in animals through his experiments on dogs. For example, after a dog was trained to associate a sound with the subsequent arrival of food, the dog would start to salivate when it heard the sound, even before the food appeared. 

About 70 years later, psychologists built on Pavlov’s insights to develop the Rescorla-Wagner model of classical conditioning. This mathematical model describes conditioned associations by their time-dependent strength. That strength increases when the conditioned stimulus (in Pavlov dog’s case the sound) can be used by the animal to decrease the surprise in the arrival of the unconditioned response (the food). 

Such insights helped set the stage for modern theories of reinforcement learning in animals, which in turn enabled reinforcement learning algorithms in artificial intelligence systems. But many mysteries remain, including some related to Pavlov’s original experiments. 

After Pavlov trained dogs to associate the sound of a bell with food he would then repeatedly expose them to the bell without food. During the first few trials without food, the dogs continued to salivate when the bell rang. If the trials continued long enough, the dogs “unlearned” and stopped salivating in response to the bell. The association was said to be “extinguished.” 

Pavlov discovered, however, that if he waited a while and then retested the dogs, they would once again salivate in response to the bell, even if no food was present. Neither Pavlov nor more recent associative-learning theories could accurately explain or mathematically model this spontaneous recovery of an extinguished association. 

Teasing out the puzzle

Researchers have explored such mysteries through experiments with C. elegans. The one-millimeter roundworm only has about 1,000 cells and 300 of them are neurons. That simplicity provides scientists with a simple system to test how the animal learns. At the same time, C. elegans’ neural circuitry is just complicated enough to connect some of the insights gained from studying its behavior to more complex systems. 

Earlier experiments have established that C. elegans can be trained to prefer a cooler or warmer temperature by conditioning it at a certain temperature with food. In a typical experiment, the worms are placed in a petri dish with a gradient of temperatures but no food. Those trained to prefer a cooler temperature will move to the cooler side of the dish, while the worms trained to prefer a warmer temperature go to the warmer side. 

But what exactly do these result mean? Some believe that the worms crawl toward a particular temperature in expectation of food. Others argue that the worms simply become habituated to that temperature, so they prefer to hang out there even without a food reward. 

The puzzle could not be resolved due to a major limitation of many of these experiments — the lengthy amount of time it takes for a worm to traverse a nine-centimeter petri dish in search of the preferred temperature. 

Measuring how learning changes over time

Nemenman and Ryu sought to overcome this limitation. They wanted to develop a practical way to precisely measure the dynamics of learning, or how learning changes over time. 

Ryu’s lab used a microfluidic device to shrink the experimental model of nine-centimeter petri dishes into four-millimeter droplets. The researchers could rapidly run experiments on hundreds of worms, each worm encased within its individual droplet. 

“We could observe in real time how a worm moved across a linear gradient of temperatures,” Ryu says. “Instead of waiting for it to crawl for 30 minutes or an hour, we could much more quickly see which side of the droplet, the cold side or the warm side, that the worm preferred. And we could also follow how its preferences changed with time.” 

Their experiments confirmed that if a worm is trained to associate food with a cooler temperature it will move to the cooler side of the droplet. Over time, however, with no food present, this memory preference seemingly decays. 

“We found that suddenly the worms wanted to spend more time on the warm side of the droplet,” Ryu says. “That’s surprising because why would the worms develop a different preference and even avoidance of the temperature they had come to associate with food?” 

Eventually the worm begins moving back and forth between the cooler and warmer temperatures. The researchers hypothesized that the worm does not simply forget the positive memory of food associated with cooler temperatures but instead starts to negatively associate the cooler side with no food. That spurs it to head for the warmer side. Then as more time passes, it begins to form a negative association of no food with the warmer temperature, which combined with the residual positive association to the cold, makes it migrate back to the cooler one. 

“The worm is always learning, all the time,” Ryu explains. “There is an interplay between the drive of a positive association and a negative association that causes it to start oscillating between cold and warm.” 

'It's like when you lose your keys'

Nemenman’s team developed theoretical equations to describe the interactions over time between the two independent variables — the positive, or excitatory, association that drives a worm toward one temperature and the negative, or inhibitory, association that drives it away from that temperature. 

“The side that the worm gravitates toward depends on when exactly you take the measurements,” Nemenman explains. “It’s like when you lose your keys you may check the desk where you usually keep them first. If you don’t see them there right away, you run around different places looking for them. If you still don’t find them, you go back to the original desk figuring you just didn’t look hard enough.” 

The researchers repeated the experiments under different conditions. They trained the worms at different starting temperatures and starved them for different durations before testing their temperature preference, and the worms’ behaviors were correctly predicted by the equations. 

They also tested their hypothesis by genetically modifying the worms, knocking out the insulin-like signaling pathway known to serve as a negative association pathway. 

“We perturbed the biology in specific ways and when we ran the experiments, the worm’s behavior changed as predicted by our theoretical model,” Nemenman says. “That gives us more confidence that the model reflects the underlying biology of learning, at least in C. elegans.” 

The researchers hope that others will test their model in studies of larger animals across species. 

“Our model provides an alternative quantitative model of learning that is multi-dimensional,” Ryu says. “It explains results that are difficult, or in some cases impossible, for other theories of classical conditioning to explain.” 

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Machine learning used to understand and predict dynamics of worm behavior

Emory physicists to study airborne microbes, funded by $1.2 million Keck Award

The Keck Foundation awarded Emory physicists Minsu Kim, left, and Justin Burton $1.2 million to explore how microbes adapt to living in the Earth's atmosphere and the broader role that these organisms may play in the planet's ecosystem.

By Carol Clark

Microbes have an incredible ability to thrive in different environments. Extensive research has shown the vital roles that these invisible organisms play in the ecosystems of marine and soil environments. But the atmosphere is another important habitat. 

Growing evidence shows that microbes in the Earth’s atmosphere can affect rainfall, land fertilization and food production. Little is known, however, about how these tiny life forms adapt to living in air and the even broader role that airborne microbes may play in the planet’s ecosystem. 

The W.M. Keck Foundation awarded Emory University physicists Justin Burton and Minsu Kim $1.2 million to explore these mysteries. In a collaboration with the University of Oregon, the researchers will use the funds to pioneer new methods for mechanistic studies of the physiology, metabolism, ecology and evolution of airborne microbes. 

The Emory project will create new tools to conduct never-before-done studies of how microbes adapt to living in air. “We’ve developed a prototype acoustic levitation system that opens the door for air-culturing microbes in a well-controlled laboratory environment for the first time,” says Burton, associate professor of physics. 

The Burton lab specializes in studying the fluid dynamics of natural phenomena, from the molecular to the geographical scale. 

The Kim lab specializes in using advanced biophysical techniques to characterize microbes from the molecular to cellular level. 

“We are helping to take the field of air biology into a new era,” says Kim, associate professor of physics. “Most research into microbe ecology has focused on microbes from marine and soil environments. We’re expanding the possibilities for investigating atmospheric microbes.” 

The Emory researchers will collaborate with additional principal investigators on the Keck Award project: Earth scientist Joshua Méndez Harper, a former postdoctoral fellow in the Burton lab now at the University of Oregon, and Josef Dufek, professor of Earth sciences at the University of Oregon. 

Wind-blown dust circulates globally, emitted by volcanic eruptions, wildfires and dust storms. These airborne particles can carry minerals and other nutrients across long distances. Desert dust from the Sahara, for example, is an important source of phosphorous for the Amazon rain forest. It is also well-known that microbes — including viruses, fungi and bacteria — hitchhike on atmospheric dust. 

Perhaps the most striking example of how atmospheric microbes can impact the environment is the so-called rain-making bacterium Pseudomonas syringae that has been isolated from clouds. Research shows that this bacterium may play a role in the precipitation cycle by producing an enzyme that catalyzes ice formation. 

Key impediments to further studying such atmospheric phenomena are sampling and culturing microbes in the air. The Keck-funded project will develop an airborne-culturing method using acoustic levitators, each about the size of a microwave oven, that simulate atmospheric conditions. The levitators will work by creating standing waves of sound, just like a musical instrument, but at a frequency well outside of the range of human hearing. These high-intensity sound waves create high pressure that is capable of suspending particles in air that are as dense as copper. 

Initially, the project will focus on studying bacteria, believed to make up more than 50% of atmospheric microbes. The controlled, laboratory conditions of the levitators will allow the researchers to home in on how different species of bacteria adapt to living in the harsh conditions found in the atmosphere, such as extreme temperature shifts, high humidity and solar radiation. 

The bacterial species studied will include some that the researchers collect from the atmosphere through balloon experiments. Team members at the University of Oregon will release a series of small, ultralight balloons. They will float on easterly winds across the country at altitudes between five and six kilometers, which is comparable to those of Saharan dust clouds and wildfire plumes. Each balloon will house sterile titanium booms affixed with tiny sponges to trap microbes within their pores. 

Balloon positions and sensor data — including temperature, pressure, humidity and dust concentration — will be transmitted continuously using amateur radio bands. As the balloons fly over Georgia, descent will be controlled using parachutes. GPS beacons will be enabled upon landing, allowing the researchers to pinpoint and recover the balloons. 

The methods developed in the lab, and the resulting data, will be open source. Scientists around the world can build on the work and continue to push the boundaries in the field of air biology. 

“The award from the Keck Foundation is giving us the freedom to strike out in bold new scientific directions,” Burton says. 

Based in Los Angeles, the W.M. Keck Foundation was established in 1954 by the late W.M. Keck, founder of the Superior Oil Company. The foundation’s grant making is focused primarily on pioneering efforts in the areas of medical research and science and engineering. The foundation also supports undergraduate education and maintains a Southern California Grant Program that provides support for the Lost Angeles community, with a special emphasis on children and youth. For more information, visit www.wmkeck.org. 

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Physicist seeks ultimate formula for fun

Justin and Afeira Burton encase their son Jonah in a giant bubble while their dog Boba Fetch looks on.

By day, Justin Burton is an Emory associate professor of physics, conducing high-level research on fluid dynamics and granular materials. Evenings and weekends, however, he turns into a comic-book version of a scientist. Not a mad scientist, tough. More like a glad scientist.

Read more about his alter ego, Dr. Bubbles, here.

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Chronic COVID infections source of variants of concern, study shows

An electron microscopic image shows an isolate from the first U.S. case of COVID-19, caused by SARS-CoV-2. The virus has since evolved into five variants of concern.  "If we want to stay a step ahead of this virus, we need to be more actively identifying and surveilling people with chronic infections," says Emory graduate Mahan Ghafari, first author of a new study on how the virus evolves. (CDC)

By Carol Clark

The coronavirus variants of concern are emerging from chronic, long-term COVID infections in people who may be immune comprised and unable to clear the virus, a new study strongly suggests. Frontiers in Virology published the findings by scientists at Emory University and the University of Oxford. 

“Rather than evolving from transmission chains of acute COVID infections in hundreds of millions of people, our results show that the variants of concern come from rare cases when someone may have an active infection for months,” says Daniel Weissman, a corresponding author and Emory professor of biology and physics focused on quantitative evolutionary theory. 

“A key take-home message is that it is important to find these individuals who are chronically infected and provide support for them to recover,” adds Mahan Ghafari, first author of the paper and a postdoctoral researcher at the University of Oxford. “In many cases they may be asymptomatic and not even realize that they are infected with COVID although they are actively shedding the virus.” 

Ghafari graduated from Emory in 2018 with a masters in physics. 

Additional authors of the paper include Aris Katzourakis, a professor of evolution and genomics at the University of Oxford; Qihan Liu, an Emory graduate student in physics; and Emory undergraduate Arushi Dhillon. 

Random mutations

Viruses like SARS-CoV-2 continuously evolve due to occasional mutations in the genetic code that may occur when they replicate. “When a virus copies itself, it doesn’t always make perfect copies,” Weissman explains. 

Usually, such random mutations do not benefit the virus or raise the concerns of scientists monitoring these changes. Occasionally, however, the mutations result in a variant of the virus that may make it more transmissible, more difficult to detect and treat, and even more lethal. 

The World Health Organization defines a SARS-CoV-2 variant of concern as one that is more likely to cause infections even in those who are vaccinated or in those who were previously infected. 

“During the first few months of the pandemic, it didn’t look like the coronavirus was going to adapt into a variant of concern,” Weissman says. “But then, boom, boom, boom! Not only did the coronavirus evolve into VOCs, it did it three times in quick succession in late 2020.” 

The WHO dubbed these first three variants of concern alpha, beta and gamma. 

Mysteries surrounding VOCs

Why had all three of these VOCs emerged at roughly the same time and apparently in three far-flung areas of the world? 

Another mystery was why large clusters of mutations occurred in the VOCs. “A key element that distinguished these VOCs from other lineages of virus that were circulating is that each of them has a vastly elevated number of mutations,” Ghafari notes. “That’s a major distinction point in evolutionary terms.” 

At least some of the mutations from the VOC had been detected in chronic cases of COVID, leading to the hypothesis that these long-term cases may be the source of the VOCs. The other main theory was that VOCs were emerging from sustained transmission of acute infections in areas of the world with poor genomic surveillance of the virus. 

Ghafari, Weissman and their collaborators were among the first teams to methodically test these theories surrounding the emergence of the alpha, beta and gamma VOCs. 

The researchers built a mechanistic, theoretical model to study the problem, using existing data and software they developed. 

The resulting model rules out the theory that the VOCs emerged from sustained transmission of acute infections and fully supports the theory that each variant evolved within a single individual with a chronic infection. 

The model shows how multiple mutations were needed, each of which may have been either neutral or slightly advantageous to viral fitness. In this way, a variant eventually acquires a constellation of mutations that allow it to become more transmissible. 

Model explains delta and omicron emergence

Although the current paper drew from data for the alpha, beta and gamma variants, the resulting theoretical model also explains the later independent emergence of the delta and omicron VOCs. Delta emerged in India in late 2020, rapidly sweeping through that country and spreading around the world. Delta subsided after omicron, which is not a descendent of the delta variant, emerged in South Africa in late 2021. Omicron quickly became the dominant global VOC. 

The researchers have made their model and software publicly available for others to study the evolution of SARS-CoV-2 variants. 

“Ideally, we’d like to eventually be able to quantify the timing at which new variants might emerge in the future,” Weissman says. “That has huge implications from a public health perspective.” 

Studies have shown that some immune-compromised people, such as those taking medication for other chronic disorders, have carried active COVID infections for a year or even longer. It’s critical to identify these people, the researchers stress, not only to help them get treated for COVID, but also to conduct genomic surveillance of the SARS-CoV-2 viruses that they carry. 

“Who knows what variant could be boiling up next from a chronically infected individual?” Ghafari says. “Our study shows that from an evolutionary point of view, we can expect something completely different from the previous VOCs. If we want to stay a step ahead of this virus, we need to be more actively identifying and surveilling people with chronic infections.” 

The work was funded by the National Science Foundation, the Simons Foundation, the Sloan Foundation, the Biotechnology and Biological Science Research Council and the European Research Council. 

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Viral sequencing can reveal how SARS-CoV-2 spreads and evolves 

Emory physicist Daniel Weissman awarded 2021 Sloan Research Fellowship

Chemists crack complete quantum nature of water

"Now that we have a good template for understanding how water molecules interact among themselves, we have a basis to deepen our understanding of the role of water in biochemical processes essential to life," says Joel Bowman,  Emory professor of theoretical chemistry.

Chemists have produced the first full quantum mechanical model of water — one of the key ingredients of life. The Journal of Physical Chemistry Letters published the breakthrough, which used machine learning to develop a model that gives a detailed, accurate description for how large groups of water molecules interact with one another. 

“We believe we have found the missing piece to a complete, microscopic understanding of water,” says Joel Bowman, professor of theoretical chemistry at Emory University and senior author of the study. “It appears that we now have all that we need to know to describe water molecules under any conditions, including ice, liquid or vapor over a range of temperature and pressure.” 

The researchers developed free, open-source software for the model, which they dubbed “q-AQUA.” The q-AQUA software provides a universal tool for studying water. 

“We anticipate researchers using it for everything from predicting whether an exoplanet may have water to deepening our understanding of the role of water in cellular function,” Bowman says. 

Read more about the discovery here. 

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