“This technology could have a big role to play in how we detect things in the environment,” says Chris Scholin, a molecular biologist and president and CEO of the Monterey Bay Aquarium Research Institute. The tool could also be useful in clinical diagnostics, he adds, although it has several competing technologies already in wide use.
Genetic tests are nothing new. Most of these technologies rely on measuring light absorption or emission from probe molecules tailored to latch onto the target gene. But to produce a signal large enough to detect, most of the technologies rely on amplifying techniques such as polymerase chain reaction to produce many copies of the target before trying to detect them, adding to the cost and time of the tests.
Researchers have devised a variety of more sensitive technologies. “But previous sensors have not been able to detect a wide range of target molecules,” from very low to very high abundance, says Jennifer Dionne, an applied physicist at Stanford University.
In hopes of getting around these problems, Dionne and her colleagues turned to an optical detection approach that relies on metasurfaces, arrays of tiny silicon boxes—each roughly 500 nanometers high, 600 nanometers long, and 160 nanometers wide—that focus near-infrared light on their top surface. This focusing makes it easy for a simple optical microscope to detect the shift in the wavelength of light coming from each silicon block, which varies depending on what molecules sit on top.
 |
| A rapid screen detects gene fragments tethered to arrays of silicon boxes, each just 500 nanometers tall and 600 nanometers across. |
To test the idea, the researchers tethered single-stranded gene fragments 22 nucleotides long to the silicon boxes and immersed the array in a buffer solution. When they added the complementary DNA strands to the solution, the strands quickly bound to the tethered ones, shifting the wavelength of light emitted from the surface of each box. Dionne and her colleagues report that their setup could detect the presence of as few as 4000 copies of target genes per microliter, a result they published in Nature Communications.
That’s a concentration typically present in a nasal sample from a person infected with SARS-CoV-2. So the technique could allow doctors to detect viral infections without first having to amplify the genetic material from a patient, Dionne says. Perhaps as important, she notes, an array can be designed to reveal how much target DNA has bound, making it possible to detect in minutes not just whether a particular virus is present, but how intense the infection is. Such information could help doctors tailor their treatments. Current tests can also do this, but they normally take several hours to amplify the genetic material and quantify the results.
Scholin argues that the technology could find more immediate widespread use in tracking molecules outside the lab or doctor’s office. For example, environmental scientists currently use genetic probes to detect toxic algae in waterways. But this normally requires added processing steps to amplify target genes and then test for their abundance, which can take hours, if not days, of lab work.
In that situation, the new technique’s speed could be a game changer, Scholin says. Another enticing option, he says, is to tether antibodies on top of the silicon boxes. This might allow researchers to directly grab the corresponding antigen, whether a toxin or a protein marker of disease. He hopes to use the Stanford team’s detectors to see whether they can detect microbial toxins in the water directly on the fly. “That would have a real impact on people, ecology, and wildlife,” he says.
Dionne and her colleagues have formed a company called Pumpkinseed Bio to commercialize their new detectors, specifically aimed at detecting minute levels of proteins and other molecules that can’t readily be amplified to make them easier to detect. And because only a small number of silicon blocks would be needed to spot individual target molecules, researchers should be able to craft arrays to track a multitude of disease biomarkers simultaneously. “We hope to look at many disease states at the same time,” says Jack Hu, a former graduate student in Dionne’s lab and head of the new startup. “That’s the vision.”