Rapid enrichment and SERS differentiation of various bacteria in skin interstitial fluid by 4-MPBA-AuNPs-functionalized hydrogel microneedles

Bacterial infection is a major threat to global public health, and can cause serious diseases such as bacterial skin infection and foodborne diseases. It is essential to develop a new method to rapidly diagnose clinical multiple bacterial infections and monitor food microbial contamination in production sites in real-time. In this work, we developed a 4-mercaptophenylboronic acid gold nanoparticles (4-MPBA-AuNPs)-functionalized hydrogel microneedle (MPBA-MN) for bacteria detection in skin interstitial fluid. MPBA-MN could conveniently capture and enrich a variety of bacteria within 5 min. Surface enhanced Raman spectroscopy (SERS) detection was then performed and combined with machine learning technology to distinguish and identify a variety of bacteria. Overall, the capture efficiency of this method exceeded 50%. In the concentration range of 1×10⁷ to 1×10¹⁰ colony-forming units/mL (CFU/mL), the corresponding SERS intensity showed a certain linear relationship with the bacterial concentration. Using rank forest-based machine learning, bacteria were effectively distinguished with an accuracy of 97.87%. In addition, the harmless disposal of used microneedles by photothermal ablation was convenient, environmentally friendly and inexpensive. This technique provided a potential method for rapid and real-time diagnosis of multiple clinical bacterial infections and for monitoring microbial contamination of food in production sites.