Ordinarily, when biological samples are being tested to see which (if any) viruses are present, it can take up to several days to get results. An inexpensive new tool, however, is claimed to capture and identify viruses within minutes.
Developed by scientists at Pennsylvania State University and New York University, the handheld VIRRION device is just a few centimeters in width. By contrast, traditional virus-identification equipment is large, costly, and lab-based.
The prototype tool incorporates a vertically-aligned “forest” of carbon nanotubes, to which gold nanoparticles have been added. The diameter of those tubes, and thus the size of the spaces between them, can be tweaked in the manufacturing process. Doing so allows the nanotube forests to trap individual virus molecules of specific sizes, when liquid biological samples are passed through different versions of the device.
Once the viruses are captured, a technique known as Raman spectroscopy is used to identify them. Putting it very basically, this process involves subjecting a sample to laser light in order to excite its molecules, and then monitoring the manner in which those vibrating molecules scatter the light.
The gold nanoparticles enhance the Raman signal, which is analyzed via machine-learning algorithms that were “trained” on the signals of known virus molecules. This essentially means that VIRRION simply matches up the received signal to one that it’s got on file.
It is hoped that once the technology is developed further, it could be utilized onsite in doctors’ offices and remotely-located healthcare facilities, or by farmers checking crops and livestock for disease.
“We synthesized a gradient of aligned carbon nanotube forest arrays to capture different viruses according to their size and detect them in-situ using Raman spectroscopy,” says Asst. Prof. Ying-Ting Yeh. “We designed and assembled a portable platform that enriches virus particles from several milliliters of clinical samples in a couple of minutes.”
Portable device quickly and cheaply identifies viruses [New Atlas]