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Protein Quantification and Imaging by Surface‐Enhanced Raman Spectroscopy and Similarity Analysis
Author(s) -
Shin Hyunku,
Oh Seunghyun,
Kang Daehyeon,
Choi Yeonho
Publication year - 2020
Publication title -
advanced science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.388
H-Index - 100
ISSN - 2198-3844
DOI - 10.1002/advs.201903638
Subject(s) - surface enhanced raman spectroscopy , colloidal gold , detection limit , immunoassay , raman spectroscopy , chemistry , protein detection , target protein , substrate (aquarium) , chromatography , materials science , nanoparticle , nanotechnology , raman scattering , antibody , biochemistry , biology , physics , gene , optics , immunology , ecology
Protein quantification techniques such as immunoassays have been improved considerably, but they have several limitations, including time‐consuming procedures, low sensitivity, and extrinsic detection. Because direct surface‐enhanced Raman spectroscopy (SERS) can detect intrinsic signals of proteins, it can be used as an effective detection method. However, owing to the complexity and reliability of SERS signals, SERS is rarely adopted for quantification without a purified target protein. This study reports an efficient and effective direct SERS‐based immunoassay (SERSIA) technique for protein quantification and imaging. SERSIA relies on the uniform coating of gold nanoparticles (GNPs) on a target‐protein‐immobilized substrate by simple centrifugation. As centrifugation induces close contact between the GNPs and target proteins, the intrinsic signals of the target protein can be detected. For quantification, the protein levels in a cell lysate are estimated using similarity analysis between antibody‐only and protein‐conjugated samples. This method reliably estimates the protein level at a sub‐picomolar detection limit. Furthermore, this method enables quantitative imaging of immobilized protein at a micrometer range. Because this technique is fast, sensitive, and requires only one type of antibody, this approach can be a useful method to detect proteins in biological samples.

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