“Our work provides a proof-of-concept showing a path to a single-step method that could be used to identify and measure nucleic acids and proteins,” says Paul Rothemund (BS ’94), a visiting associate at Caltech in computing and mathematical sciences, and computation and neural systems.

A paper describing the work recently appeared in the journal Proceedings of the National Academy of Sciences. The lead authors of the paper are former Caltech postdoctoral scholar Byoung-jin Jeon and current graduate student Matteo M. Guareschi, who completed the work in Rothemund’s lab.

In 2006, Rothemund published the first paper on DNA origami, a technique that provides simple yet exquisite control over the design of molecular structures at the nanoscale using nothing more than DNA.

Essentially DNA origami enables long strands of DNA to fold, through self-assembly, into any desired shape. (In the 2006 paper, Rothemund famously used the technique to create miniature DNA smiley faces measuring 100 nanometers across and 2 nanometers thick). Researchers begin with a long strand of DNA, the scaffold, in solution. Because the nucleotide bases that make up DNA bind in a known way (adenine binds to thymine, and guanine binds to cytosine), the scientists can add hundreds of short sequences of complementary DNA knowing they will bind to the scaffold on either end at known locations. Those short, added pieces of DNA fold the scaffold and give it shape, acting as “staples” that hold the structure together. The technique can then be used to create shapes ranging from a map of North and South America to nanoscale transistors.

In the new work, Rothemund and his colleagues used DNA origami to create a lilypad-like structure — a flat, circular surface about 100 nanometers in diameter, tethered by a DNA linker to a gold electrode. Both the lilypad and the electrode have short DNA strands available to bind with an analyte, a molecule of interest in solution — whether that be a molecule of DNA, a protein, or an antibody. When the analyte binds to those short strands, the lilypad gets pulled down to the gold surface, bringing 70 reporter molecules on the lilypad (which indicate that the targeted molecule is present) into contact with the gold surface. These reporters are redox reactive molecules, meaning they can easily lose electrons during a reaction. So, when they get sufficiently close to an electrode, an electric current can be observed. A stronger current indicates that more of the molecule of interest is present.

Previously, a similar approach to making biosensors was developed using a single DNA strand rather than a DNA origami structure. That earlier work was led by Kevin W. Plaxco (PhD ’94) of UC Santa Barbara, who is also an author of the current paper.

Caltech’s Guareschi points out that the new lilypad origami is large compared to a single DNA strand. “That means it can fit 70 reporters on a single molecule and keep them away from the surface before binding. Then when the analyte is bound and the lilypad reaches the electrode, there is a large signal gain, making the change easy to detect,” Guareschi says.

The relatively large size of the lilypad origami also means that the system can readily accommodate and detect larger molecules, such as large proteins. In the new paper, the team showed that the two short DNA strands on the lilypad and the gold surface could be used as adapters, making it a sensor for proteins rather than for DNA. In the work, the researchers added the vitamin biotin to those short DNA strands to turn the system into a sensor for the protein streptavidin. Then they added a DNA aptamer, a DNA strand that can bind to a specific protein; in this case, they used an aptamer that binds to a protein called platelet-derived growth factor BB (PDGF-BB), which could be used to help diagnose diseases such as cirrhosis and inflammatory bowel disease.

“We just add these simple molecules to the system, and it’s ready to sense something different,” Guareschi says. “It’s large enough to accommodate whatever you throw at it — that could be aptamers, nanobodies, fragments of antibodies — and it doesn’t need to be completely redesigned every time.”

The researchers also show that the sensor can be reused several times, with new adapters added each round for different detections. Although the performance slightly degrades over time, the current system could be reused at least four times.

In the future, the team hopes the system might also be useful for proteomics — studies that determine what proteins are in a sample and at what concentrations. “You could have multiple sensors at the same time with different analytes, and then you could do a wash, switch the analytes, and remeasure. And you could do that several times,” Guareschi says. “Within a few hours, you could measure hundreds of proteins using a single system.”

Additional authors of the paper, “Modular DNA origami-based electrochemical detection of DNA and proteins,” are Jaimie M. Stewart of UCLA; Emily Wu and Ashwin Gopinath of MIT, Netzahualcóyotl Arroyo-Currás of Johns Hopkins University School of Medicine, Philippe Dauphin-Ducharme of the Université de Sherbrooke in Canada; and Philip S. Lukeman of St. John’s University in New York.

The team used fabrication equipment at the Kavli Nanoscience Institute at Caltech. The work was supported by the Army Research Office, the Office of Naval Research, the National Science Foundation, and the Life Sciences Research Foundation supported by Merck Research Laboratories.

While not as deep and complex as a Super Bowl half-time show, the bees’ moves, known as the “waggle” dance, convey very specific food foraging instructions to their nestmates. The direction the dancer moves explains to other bees which way to go, and the duration of the waggle dance, or the “run,” shows how far to go. Once other bees have been convinced to follow the directions, they are “recruited.” After receiving the instructions, these recruits leave the hive to find the food their sisters were so excited about.

Unfortunately, many of these recruited bees do not always successfully find the food they set out in search of. Margaret Couvillon, associate professor in the Department of Entomology in the College of Agriculture and Life Sciences, and her former Ph.D. student Laura McHenry wanted to find out why.

Trying to understand why waggle dances fail

Honeybees have had millions of years to perfect the waggle dance, so it may be surprising to learn that it doesn’t often work. Even though it was first described by scientists over 80 years ago, there is still a lot about the waggle dance that we don’t understand.

Couvillon has learned several interesting patterns related to this form of communication. One such observation was that bees have consistent, unique ways of dancing, meaning each bee has its own “style” that it adds to the communication. Could the success of the waggle dance be related to this uniqueness? Would bees that communicated similarly yield more successful recruits? Or is there some other factor at play? This study reveals the waggle to be a diverse form of communication that helps improve the likelihood that one bee can tell another where food can be found. The findings were recently published in Current Biology.

“Although the waggle dance itself is fascinating, my lab has additionally been intrigued about waggle dance miscommunication, or the hows and whys behind the failure of the dance recruitment,” Couvillon said.

To answer these questions, the Couvillon Lab devised an experiment utilizing clear-walled hives, video cameras, and a method of tagging bees so they could be tracked as individuals when they foraged and danced. Each hive included foragers who had been taught the location of an artificial food source. These trained foragers performed a waggle dance to teach others where this food was, effectively training a new set of recruits. If successful in locating the food, these recruits returned to teach other bees what they learned. Couvillon and her team hypothesized that bees with similar dance styles would more often successfully teach others how to find the food and communication that differed between bees would be less successful.

Whenever a new, tagged bee was observed at the food source, video of the hive was reviewed to determine which dancer had recruited that successful forager. This pattern of data collection allowed the researchers to track the dance the bees used, with each bee learning where the food was located from a slightly different telling. These successful dances were then compiled, and the run of each dance was measured and compared to the earlier dances. The pattern that emerged was not what the researchers expected.

The power of individuality

Based on the data from these dances, Couvillon and McHenry found that similar dance communication did not actually result in the most successful foraging, which was their original hypothesis. Dances that had a longer run, effectively telling the recruits to overshoot the food source, were more successful than dances describing similar, more accurate, distances. This pattern suggested that the “overshooting” instructions may have led to additional opportunities to find the food, once on the way past the food source and again on the way back to the hive. They theorized that the foragers having a second chance to find the food source increased the chance that they find it at all.

What does this mean for understanding the honeybee waggle dance? One takeaway is the importance of these unique communication styles, where individual dance mannerisms enhance communication success. If every bee communicated the same, the likelihood of foragers reaching the food would decrease as compared to having a diverse set of styles.

This study adds effective dance moves to the list of known benefits of individuality, showing that a diverse set of communication skills helps improve the likelihood that one bee can tell another where food can be found, all through dance.

“We’ve known for a while that behavioral and genetic diversity benefit honeybees, allowing for superior thermoregulation, disease resistance, growth, and foraging,” said Couvillon. “Now we have also seen that diverse communication enhances recruitment success.”

Called the Electronic Bee-Veterinarian, or EBV, the technology uses low-cost heat sensors and forecasting models to predict when hive temperatures may reach dangerous levels. The system provides remote beekeepers with early warnings, allowing them to take preventive action before their colonies collapse during extreme hot or cold weather or when the bees cannot regulate their hive temperature because of disease, pesticide exposure, food shortages, or other stressors.

“We convert the temperature to a factor that we are calling the health factor, which gives an estimate of how strong the bees are on a scale from zero to one,” said Shamima Hossain, a Ph.D. student in computer science at UCR and lead author of a paper explaining the technology.

This simplified metric — with a score of ‘one’ meaning the bees are at full strength — allows beekeepers unfamiliar with the underlying model to assess hive health quickly.

Boris Baer, a UCR professor of entomology, believes the technology could revolutionize beekeeping, which is essential to vast sectors of global agriculture. Honeybees pollinate more than 80 crops and contribute an estimated $29 billion annually to U.S. agriculture. Yet bee populations have declined due to various factors, including habitat loss, pesticide exposure, parasites, and climate change.

“Over the last year, the U.S. lost over 55% of its honeybee colonies,” Baer said, citing data from Project Apis m., which monitors beehive losses throughout the U.S. “We are experiencing a major collapse of bee populations, and that is extremely worrying because about one-third of what we eat depends on bees.”

Beekeepers now rely on their own judgment and manual inspections to detect problems, often leading to delayed interventions. With EBV, they can get real-time insights and predict conditions days in advance, significantly reducing labor costs, said Baer, who collaborated with Hossain and other scientists at UCR’s Bourns College of Engineering.

“People have dreamed of these sensors for a very long time,” Baer said. “What I like here is that this system is fully integrated into the hive setup that beekeepers already use.”

Temperature fluctuations are among the first responses to any kind of threats to a hive’s health. Honeybees maintain a precise internal hive temperature between 33 and 36 degrees Celsius (91.4-96.8°F), a requirement for proper brood development and colony survival, Baer said.

The EBV method is based on thermal diffusion equations and control theory, making its predictions interpretable to both scientists and beekeepers, Hossain said. The model uses temperature data collected from low-cost sensors installed inside the hive, feeding that information into an algorithm that predicts hive conditions several days in advance.

In tests conducted at UCR’s apiary, the EBV method analyzed data from 10 hives during initial development and later expanded to 25 hives. The technology has already proven its effectiveness, detecting conditions that required beekeeper intervention.

“When I looked at the dashboard and saw the health factor dropped below an empirical threshold, I contacted our apiary manager,” Hossain recalled. “When we went to check the hive, we found that there was actually something wrong, and they were able to take action to manage the situation.” Hyoseung Kim, an associate professor of electrical and computer engineering at UCR, explained that keeping costs low — under $50 per hive — is a high priority.

“There are commercial sensors available, but they are too expensive,” Kim said. “We decided to create a very cheap device using off-the-shelf components so that beekeepers can afford it.”

The research team is already working on the next phase, which is to develop automated hive climate controls that can be installed on hives and respond to EBV’s predictions, adjusting hive temperatures automatically.

“Right now, we can only issue warnings,” Hossain said. “But in the next phase, we are working on designing a system that can automatically heat or cool the hive when needed.”

The title of Hossain’s paper is “Principled Mining, Forecasting and Monitoring of Honeybee Time Series with EBV+” In addition to Hossain, Baer and Kim, the co-authors are Christos Faloutsos, professor of computer science at Carnegie Mellon University, and Vassilis Tsotras, professor of computer science and engineering at UCR.

All the authors are with UCR’s Center for Integrative Bee Research, one of the largest pollinator health research hubs in the nation.