Abstract
Rapidly and accurately detecting multiple bacteria through existing on-site detection methods remains a challenge. Here, we first propose a lateral flow immunoassay (LFA) based on three-dimensional (3D) multi-hotspot membrane-like (ML) tag, which enables ultrasensitive, simultaneous, and quantitative detection of multiple pathogens through surface-enhanced Raman scattering (SERS) encoding. The 3D ML SERS tag (named MoDAu@Ag) achieves superior colorimetric/SERS activities and a large reactive interface by loading two layers of Au@Ag nanoparticles onto 2D MoS2 nanosheets and precisely regulating the nanogaps through self-assembly with polyethyleneimine (PEI). The functionalization of MoDAu@Ag tags is achieved by filling three Raman molecules into PEI-nanogaps and directly modifying antibodies through electrostatic adsorption, overcoming the decline in material stability caused by traditional chemical synthesis methods. By implementing a testing line containing mixed antibodies, the MoDAu@Ag-based SERS-LFA enables rapid qualitative (colorimetric) and quantitative (SERS) detection of different pathogens through visual color signal evaluation and characteristic Raman signal measurement within a single detection area. The developed SERS-encoding LFA can simultaneously and accurately detect Pseudomonas aeruginosa, Salmonella typhimurium, and Escherichia coli O157:H7, with a remarkably low detection limits of 30–40 cells/mL and maintaining a quantitative linear relationship across four orders of magnitude. Furthermore, the robust practicality of our methodology is validated through comprehensive testing of diverse real-world samples, demonstrating its great potential for real-time, on-site pathogen detection applications.
| Original language | English |
|---|---|
| Article number | 163223 |
| Journal | Chemical Engineering Journal |
| Volume | 514 |
| DOIs | |
| Publication status | Published - 15 Jun 2025 |
| Externally published | Yes |
Keywords
- 3D membrane-like tag
- Bacteria
- Lateral flow immunoassay
- Multiplex detection
- SERS encoding
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