Molecular Imprinting-Based SERS Detection Strategy for the Large-Size Protein Quantitation and Curbing Non-Specific Recognition

doi:10.1021/acs.analchem.4c00541

	Molecular Imprinting-Based SERS Detection Strategy for the Large-Size Protein Quantitation and Curbing Non-Specific Recognition
	Chen, Xuan 1,2; Ostovan, Abbas 1; Arabi, Maryam1 ; Wang, Yunqing1 ; Chen, Lingxin1,3 ; Li, Jinhua1,2,3
发表期刊	ANALYTICAL CHEMISTRY
ISSN	0003-2700
	2024-04-12
卷号	96 期号:16 页码:6417-6425
DOI	10.1021/acs.analchem.4c00541
通讯作者	Arabi, Maryam(m.arabi@yic.ac.cn) ; Li, Jinhua(jhli@yic.ac.cn)
英文摘要	Molecular imprinting-based surface-enhanced Raman scattering (MI-SERS) sensors have shown remarkable potential from an academic standpoint. However, their practical applications, especially in the detection of large-size protein (>= 10 nm), face challenges due to the lack of versatile sensing strategies and nonspecific fouling of matrix species. Herein, we propose a Raman reporter inspector mechanism (RRIM) implemented on a protein-imprinted polydopamine (PDA) layer coated on the SERS active substrate. In the RRIM, after large-size protein recognition, the permeability of the PDA imprinted cavities undergoes changes that are scrutinized by Raman reporter molecules. Target proteins can specifically bind and fully occupy the imprinted cavities, whereas matrix species cannot. Then, Raman reporter molecules with suitable size are introduced to serve as both inspectors of the recognition status and inducers of the SERS signal, which can only penetrate through the vacant and nonspecifically filled cavities. Consequently, changes in the SERS signal exclusively originate from the specific binding of target proteins, while the nonspecific recognition of matrix species is curbed. The RRIM enables reproducible quantitation of the large-size cyanobacteria-specific protein model (>= 10 nm), phycocyanin, at the level down to 2.6 x 10-3 mu g L-1. Finally, the practical applicability of the RRIM is confirmed by accurately analyzing crude urban waterway samples over 21 min without any pretreatment.
资助机构	National Natural Science Foundation of China ; National Nature Science Foundation of China ; Shandong Provincial Natural Science Foundation of China ; Taishan Scholar Project Special Funding
收录类别	SCI
语种	英语
研究领域[WOS]	Chemistry
WOS记录号	WOS:001203965500001
引用统计	被引频次：4[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.yic.ac.cn/handle/133337/35305
专题	中国科学院海岸带环境过程与生态修复重点实验室中国科学院海岸带环境过程与生态修复重点实验室_海岸带环境工程技术研究与发展中心
通讯作者	Arabi, Maryam; Li, Jinhua
作者单位	1.Chinese Acad Sci, Yantai Inst Coastal Zone Res, Shandong Res Ctr Coastal Environm Engn & Technol, CAS Key Lab Coastal Environm Proc & Ecol Remediat,, Yantai 264003, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.Qingdao Marine Sci & Technol Ctr, Lab Marine Biol & Biotechnol, Qingdao 266237, Peoples R China
推荐引用方式 GB/T 7714	Chen, Xuan,Ostovan, Abbas,Arabi, Maryam,et al. Molecular Imprinting-Based SERS Detection Strategy for the Large-Size Protein Quantitation and Curbing Non-Specific Recognition[J]. ANALYTICAL CHEMISTRY,2024,96(16):6417-6425.
APA	Chen, Xuan,Ostovan, Abbas,Arabi, Maryam,Wang, Yunqing,Chen, Lingxin,&Li, Jinhua.(2024).Molecular Imprinting-Based SERS Detection Strategy for the Large-Size Protein Quantitation and Curbing Non-Specific Recognition.ANALYTICAL CHEMISTRY,96(16),6417-6425.
MLA	Chen, Xuan,et al."Molecular Imprinting-Based SERS Detection Strategy for the Large-Size Protein Quantitation and Curbing Non-Specific Recognition".ANALYTICAL CHEMISTRY 96.16(2024):6417-6425.