Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Protein Quantification and Imaging by Surface-Enhanced Raman Spectroscopy and Similarity Analysis

Authors
Shin, HyunkuOh, SeunghyunKang, DaehyeonChoi, Yeonho
Issue Date
Jun-2020
Publisher
WILEY
Keywords
plasmonics; protein imaging; protein quantification; similarity analysis; surface-enhanced Raman spectroscopy
Citation
ADVANCED SCIENCE, v.7, no.11
Indexed
SCIE
SCOPUS
Journal Title
ADVANCED SCIENCE
Volume
7
Number
11
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/55539
DOI
10.1002/advs.201903638
ISSN
2198-3844
Abstract
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.
Files in This Item
There are no files associated with this item.
Appears in
Collections
Graduate School > Department of Bioengineering > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Choi, Yeon ho photo

Choi, Yeon ho
Department of Bioengineering
Read more

Altmetrics

Total Views & Downloads

BROWSE