UNIST Develops Method to Identify Infection-Causing Bacteria with 99% Accuracy in 3 Hours

Developed FISH Diagnostic Technology Using Two PNA Molecules
Distinguishes Escherichia coli, Pseudomonas aeruginosa, and Others with 99% Accuracy... Published in Biosensors and Bioelectronics

A diagnostic technology capable of identifying the causative bacteria of an infection with nearly 100% accuracy within three hours has been developed.

This technology is much faster and more accurate than bacterial culture or PCR analysis, raising expectations that it could lower mortality rates for diseases where the golden time for administering antibiotics is critical, such as sepsis.

A team of professors?Kim Hajin, Kwon Taejun, and Kang Juhun?from the Department of Biomedical Engineering at UNIST announced on the 12th that they have developed a FISH diagnostic technology using a synthetic molecule called PNA as a probe.

Professor Hajin Kim (left) and Dr. Sungho Kim (first author). Provided by UNIST

The FISH technology is based on reading fluorescent signals generated when probe molecules bind to specific gene sequences of bacteria.

The newly developed FISH technology utilizes two PNA molecules simultaneously. The research team analyzed the genome sequences of 20,000 bacterial species and designed PNA sequences to bind only to ribosomal RNA of specific species. Compared to conventional DNA-based probes, PNA has higher sensitivity to sequence mismatches and superior ability to penetrate bacterial cell walls.

Additionally, because both PNA molecules must bind to the target site for a signal to occur, the method significantly reduces crosstalk caused by probes binding to incorrect sites. This approach not only improves accuracy in detecting individual bacterial infections but also in situations where multiple bacterial species are mixed.

In experiments detecting seven types of bacteria?including Escherichia coli, Pseudomonas aeruginosa, and Staphylococcus aureus?from individual samples, the technology demonstrated over 99% detection accuracy for all except Staphylococcus aureus.

Staphylococcus aureus was detected with 96.3% accuracy. The performance was also verified in mixed-bacteria scenarios. When Enterococcus and Escherichia coli were tested together, both bacteria were detected with over 99% accuracy.

The technology using two PNA molecules is based on the Forster Resonance Energy Transfer (FRET) phenomenon. When two PNA molecules are in close proximity, energy is transferred from one molecule to the other, and the resulting fluorescence emitted by the energy-receiving molecule is measured.

Operating principle and detection accuracy of the developed diagnostic technology.

Professor Kim Hajin expressed hope that “this will aid in the diagnosis of infectious diseases requiring immediate antibiotic treatment?such as sepsis, urinary tract infections, and pneumonia?and help reduce unnecessary antibiotic use.” The research team added that they plan to explore clinical applications through additional experiments using blood samples collected from actual patients.

This research was conducted with Kim Sungho and Hyun Hwi of UNIST as co-first authors, and was supported by the National Research Foundation of Korea, the Institute for Basic Science (IBS), the Korea National Institute of Health, and UNIST.

The results were published in the international journal Biosensors and Bioelectronics on March 1.

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