| Jun 25, 2025 |
Microfluidic system detects subtle chemical fingerprints from bacteriaScientists developed a new microfluidic system that can detect subtle chemical fingerprints from bacteria - helping identify even antibiotic-resistant strains. This technology could help physicians quickly and accurately diagnose infections in hospitals.(Nanowerk News) 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 (Biosensors and Bioelectronics, "Air-liquid microfluidics-integrated surface-enhanced Raman spectroscopy for selective molecular adsorption and detection to achieve bacterial discrimination"). |
| This system consists of an air-liquid microfluidics with surface-enhanced Raman spectroscopy-based substrate, or called ALM-SERS, 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. |
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| 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. (Image: National Taiwan University) (click on image to enlarge) |
| By analyzing the patterns across all eight wells using advanced data processing techniques like principal component analysis (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 diagnostic in hospitals, with potential applications in drug development, food safety, 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 bacteria in real time, offering a faster path to targeted treatments.” |
| Source: National Taiwan University (Note: Content may be edited for style and length) |
