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Using a silver-enhanced microarray sandwich structure to improve SERS sensitivity for protein detection
Authors:Xuefang Gu  Yuerong Yan  Guoqing Jiang  Jason Adkins  Jian Shi  Guomin Jiang  Shu Tian
Institution:1. School of Chemistry and Chemical Engineering, Nantong University, Nantong, 226007, China
2. Department of science and technology, Jiaozuo Teachers College, Jiaozuo, 454000, China
3. Institute of Chemical Power Sources, Soochow University, Suzhou, 215006, China
Abstract:A simple and sensitive method, based on surface-enhanced Raman scattering (SERS), for immunoassay and label-free protein detection is reported. A series of bowl-shaped silver cavity arrays were fabricated by electrodeposition using a self-assembled polystyrene spheres template. The reflection spectra of these cavity arrays were recorded as a function of film thickness, and then correlated with SERS enhancement using sodium thiophenolate as the probe molecule. The results reveal that SERS enhancement can be maximized when the frequency of both the incident laser and the Raman scattering approach the frequency of the localized surface plasmon resonance. The optimized array was then used as the bottom layer of a silver nanoparticle–protein–bowl-shaped silver cavity array sandwich. The second layer of silver was introduced by the interactions between the proteins in the middle layer of the sandwich architecture and silver nanoparticles. Human IgG bound to the surface of this microcavity array can retain its recognition function. With the Raman reporter molecules labeled on the antibody, a detection limit down to 0.1 ng mL?1 for human IgG is easily achieved. Furthermore, the SERS spectra of label-free proteins (catalase, cytochrome C, avidin and lysozyme) from the assembled sandwich have excellent reproducibility and high quality. The results reveal that the proposed approach has potential for use in qualitative and quantitative detection of biomolecules.
Schematic diagram of sandwich structure for labelled and label-free protein detection.
Keywords:
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