‘Shadow Waveguide’ Casts Complex Acoustic Patterns to Control Particles
New approach to ‘acoustic tweezers’ could help push past limitations for cell and tissue engineering applications
Tony Jun Huang and colleagues have developed a platform that uses sound waves to sort viruses from other compounds in a liquid.
From the American Chemical Society
Developing antiviral therapeutics and vaccines requires close study of the viruses that cause disease. But how can these small germs be isolated from complex biological samples like saliva? Researchers in ACS Nano describe a platform that uses sound waves as acoustic tweezers to sort viruses from other compounds in a liquid. In demonstrations, the method quickly and accurately separates viruses from large and small particles in human saliva samples.
Isolating, identifying and genetically sequencing a virus provides important information to scientists about how it causes disease and how to develop effective therapeutics. Current methods for separating viruses from other particles in biological samples include time-consuming ultracentrifugation and cell culture procedures. To speed up and simplify the process, Luke Lee and Tony Jun Huang looked to acoustofluidics: A technology that uses sound waves to sort particles by size in a liquid. They chose a specific type of sound wave, called a Bessel beam, because it can be tuned to sort specific nanosized particles, and multiple waves remain tightly focused over long distances — like a pair of tweezers.
“With its high separation resolution, high yield, high purity, and high biocompatibility, our BEST technology is an extremely powerful tool for rapidly and efficiently isolating viruses,” said Huang, the William Bevan Distinguished Professor of Mechanical Engineering and Materials Science at Duke University. “It has the potential to play an important role in the development of next-generation viral diagnostics, therapeutics and vaccines.”
The Bessel beam excitation separation technology (BEST) platform that Lee, Huang and colleagues developed consists of a rectangular chip with a sample-loading inlet at one end and separate virus and waste outlets at the other end. Two acoustic Bessel beams were applied across the chip, perpendicular to the sample flow. By tuning the beams’ wavelengths, the system sorted particles of different sizes:
The team tested the BEST platform on human saliva samples loaded with SARS-CoV-2. Liquid collected from the chip’s virus outlet contained 90% of viral genetic material, while liquid from the waste outlet contained no viral genetic material, showing that the platform successfully isolated the virus. The researchers confirmed the results with electron microscopy, finding viruses only in liquid sampled from the virus outlet. Although BEST cannot yet separate waste particles from viruses that are smaller than 50 nm, such as parvoviruses, the researchers are working to broaden the technology’s range to enable its use in developing new therapeutic targets for numerous viral diseases.
The authors acknowledge funding from the National Institutes of Health, National Science Foundation (NSF) and NSF Graduate Research Fellowship Program.
Some authors have competing financial interests in Ascent Bio-Nano Technologies Inc., to commercialize technologies involving acoustofluidics and acoustic tweezers, and equity in Liquid Diagnostics.
This research was supported by the National Institutes of Health (U18TR003778, UH3TR002978, R01GM132603, R01GM141055, R01GM135486, R21CA283665, R21DE034146), the National Science Foundation Graduate Research Fellowship Program (2139754), and the National Science Foundation (CMMI-2104295).
CITATION: “Acoustofluidic Virus Isolation via Bessel Beam Excitation Separation TechnologyClick to copy article link.” Jianping Xia, Zeyu Wang, Ryan Becker, Feng Li, Fang Wei, Shujie Yang, Joseph Rich, Ke Li, Joseph Rufo, Jiao Qian, Kaichun Yang, Chuyi Chen, Yuyang Gu, Ruoyu Zhong, Patty J. Lee, David T. W. Wong, Luke P. Lee, Tony Jun Huang. ACS Nano, 2024, 18, 33, 22596–22607. DOI: 10.1021/acsnano.4c09692
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