Plasmon-Mediated Peroxidase-like Activity on an Asymmetric Nanotube Architecture for Rapid Visual Detection of Bacteria.

Abstract

Rapid and sensitive detection of bacteria from a complex real media remains a challenge. Herein, we report a visual bacterial sensing assay with excellent specificity, anti-interference ability, and sensitivity based on a surface plasmon resonance (SPR)-enhanced peroxidase (POD) mimetic. The POD mimetic based on Pt nanoparticles (NPs) asymmetrically decorated on Au/TiO2 magnetic nanotubes (Au/Pt/MTNTs) is designed by combining the intrinsic photocatalytic activity of TiO2 and the limited transport depth of light. It is revealed that the localized surface plasmon resonance (LSPR) effect of the asymmetric nanotubes is more effective in facilitating the generation of hot electrons, which are subsequently transferred to Pt and MTNTs, thus greatly promoting the catalytic performance. Using Staphylococcus aureus (S.aureus) as a model of Gram-positive bacteria, the dependence of the colorimetric reaction on the active sites of the POD mimetic is used for the sensing of target bacteria. Owing to the specific recognition between S.aureus and peptide, the fluorescein isothiocyanate (FITC) labeled peptide probes are captured by S.aureus and removed from the Au/Pt/MTNTs, leading to the recovery of POD-like activity and fluorescence emission of S.aureus. Particularly, benefiting from the Au-SPR effect and the magnetic feature of the Au/Pt/MTNTs, the recovery of catalytic activity induced an improved colorimetric assay with a wider linear response for S.aureus qualification and a detection limit of four cells, as well as satisfactory selectivity and feasibility for application in real samples. The plasmon-enhanced POD activity would provide a simple-yet-effective approach to achieve a colorimetric bioassay with high efficiency and sensitivity. This asymmetric design can also be utilized to engineer nanozymes in colorimetric assays for the specific detection of biotoxins, biomarkers, and cancer cells.