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Microfluidic system can quickly and accurately identify bacteria, including antibiotic-resistant strains

A tiny droplet: A giant leap in bacteria detection
Schematic and photo of the ALM-SERS system. This system can sequentially collect eight SERS spectra in a single sample droplet, which can be used to discriminate bacteria with subtle difference. Credit: National Taiwan University

Scientists at National Taiwan University have developed a new microfluidic system that can detect subtle chemical fingerprints from bacteria—helping to identify even antibiotic-resistant strains. This technology could help physicians quickly and accurately diagnose infections in hospitals. The study is in Biosensors and Bioelectronics.

Accurate and fast identification of bacteria is vital for prescribing the right antibiotics, especially with the rising threat of drug-resistant infections. Traditional diagnostic methods often require time-consuming culture steps, delaying treatment and increasing the risk to patients.

Researchers at National Taiwan University (NTU) have developed a new tool that integrates microfluidics and optical sensing techniques, enabling highly detailed chemical analysis of bacterial secretions in a fast and minimally invasive way.

This system consists of air-liquid microfluidics with a surface-enhanced Raman spectroscopy-based substrate, called ALM-SERS, that captures the chemical signals of tiny molecules that bacteria naturally release. These molecules include purine derivatives, which vary subtly between different bacterial species and strains.

However, identifying these differences is not easy—some molecules bind more strongly to detection surfaces than others, masking signals from weaker ones. The team overcame this challenge with a clever design: their device moves microdroplets containing the bacterial secretions across a series of microwells.

Each well selectively absorbs different molecules based on their binding strength, producing a sequence of spectral fingerprints that together offer a much clearer picture of the sample.

By analyzing the patterns across all eight wells using advanced data processing techniques like (PCA) and support vector machines (SVM), the researchers could distinguish between closely related bacterial strains, even when they had identical species but different antibiotic resistance profiles. In tests on both lab and real-world clinical samples, this system achieved remarkably accurate results.

This innovation opens the door to faster, more precise diagnostics in hospitals, with potential applications in , , and environmental monitoring.

"This chip doesn't just take a single snapshot—it reads a whole movie of molecular adsorption," says Prof. Nien-Tsu Huang. "That makes it possible to spot tiny metabolic differences between superbugs and ordinary in real time, offering a faster path to targeted treatments."

More information: Chi-Yao Ku et al, Air-liquid microfluidics-integrated surface-enhanced Raman spectroscopy for selective molecular adsorption and detection to achieve bacterial discrimination, Biosensors and Bioelectronics (2025).

Journal information: Biosensors and Bioelectronics

Citation: Microfluidic system can quickly and accurately identify bacteria, including antibiotic-resistant strains (2025, June 25) retrieved 27 June 2025 from /news/2025-06-microfluidic-quickly-accurately-bacteria-antibiotic.html
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