Korean researchers improve pathogen and contaminant identification

The light scattering pattern from a single bacterium, L. casei. | Courtesy of the Korea Advanced Institute of Scinece and Technology
Researchers at the Korea Institute of Science and Technology (KAIST) in Daejeon, South Korea, have discovered a new technique that could expedite the identification process of pathogens and contaminants, the Optical Society (OSA) announced Monday.

The research was also published in the OSA's Optics Express scientific journal. Researchers at KAIST bounced light in the form of a laser off of bacterial samples while under the microscope. Doing so created an image that computer software is able to analyze and identify based on known bacteria. The identification process is similar to the way facial recognition works in security software.

"Employing laser holographic techniques, we achieved rapid and label-free identification of bacterial species at the single bacterium level with a single-shot measurement," Physicist and KAIST Team Lead YongKeun Park said. "This means the present method can be utilized as a prescreening test for point-of-care bacterial diagnosis for various applications including medicine and food hygiene."

If the technique proves to be effective in clinical trials, this technique could potentially replace the many days it takes to grow patient cultures in a lab. This method remains more popular as other genetic-based tests are often very costly, especially for hospitals in rural or less economically stable regions.

According to the OSA, speeding up the identification process would allow hospitals to use more specific treatments in cases of hospital-acquired infections rather than using broad spectrum antibiotics during the identification process.

Park states that they have created a portable device that can be attached to a microscope that is able to measure the light information from samples.

Organizations in this story

Korea Institute of Science and Technology Seongbuk-gu, Seoul, South Korea Seoul,

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