Nanoplasmonic SERS on fidget spinner for digital bacterial identification.

利用纳米等离子体表面增强拉曼光谱技术在指尖陀螺上进行数字细菌识别

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作者:Karmacharya Mamata, Michael Issac, Han Jiyun, Clarissa Elizabeth Maria, Gulenko Oleksandra, Kumar Sumit, Cho Yoon-Kyoung
Raman spectroscopy offers non-destructive and highly sensitive molecular insights into bacterial species, making it a valuable tool for detection, identification, and antibiotic susceptibility testing. However, achieving clinically relevant accuracy, quantitative data, and reproducibility remains challenging due to the dominance of bulk signals and the uncontrollable heterogeneity of analytes. In this study, we introduce an innovative diagnostic tool: a plasmonic fidget spinner (P-FS) incorporating a nitrocellulose membrane integrated with a metallic feature, referred to as a nanoplasmonic-enhanced matrix, designed for simultaneous bacterial filtration and detection. We developed a method to fabricate a plasmonic array patterned nitrocellulose membrane using photolithography, which is then integrated with a customized fidget spinner. Testing the P-FS device with various bacterial species (E. coli 25922, S. aureus 25923, E. coli MG1655, Lactobacillus brevis, and S. mutans 3065) demonstrated successful identification based on their unique Raman fingerprints. The bacterial interface with regions within the plasmonic array, where the electromagnetic field is most intensely concentrated-called nanoplasmonic hotspots-on the P-FS significantly enhances sensitivity, enabling more precise detection. SERS intensity mappings from the Raman spectrometer are transformed into digital signals using a threshold-based approach to identify and quantify bacterial distribution. Given the P-FS's ability to enhance vibrational signatures and its scalable fabrication under routine conditions, we anticipate that nanoplasmonic-enhanced Raman spectroscopy-utilizing nanostructures made from metals (specifically gold and silver) deposited onto a nitrocellulose membrane to amplify Raman scattering signals-will become the preferred technology for reliable and ultrasensitive detection of various analytes, including those crucial to human health, with strong potential for transitioning from laboratory research to clinical applications.

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