Issue 1, 2020

A surface-enhanced electrochemiluminescence sensor based on Au-SiO2 core–shell nanocomposites doped with Ru(bpy)32+ for the ultrasensitive detection of prostate-specific antigen in human serum

Abstract

This study reports a surface-enhanced electrochemiluminescence (SEECL) sensor for the ultrasensitive detection of prostate-specific antigen (PSA) in human serum. First, we prepared the Au-SiO2 core–shell nanocomposites doped with Ru(bpy)32+ (Au@SiO2-Ru) as the ECL signal generation and amplification element of the SEECL sensor. Ru(bpy)32+ could emit ECL under the excitation of an electrochemical reaction, and generate the local surface plasmon resonance (LSPR) electromagnetic field from the gold nanoparticle (AuNP) core. The produced LSPR then effectively enhanced the ECL signals. This sensing strategy was utilized for the detection of PSA, which can be absorbed on the electrode surface by the reaction between PSA and monoclonal antibodies. When polyclonal antibody-modified Au@SiO2-Ru was added, the PSA-double-antibody sandwich structure was formed on the electrode surface and thus, the Au@SiO2-Ru were quantitatively immobilized on the electrode surface. The results show that this kind of SEECL sensor has good selectivity toward PSA. Notably, the minimum detection concentration reached 7 × 10−7 ng mL−1 under the optimum experimental conditions, which is much better than most of the previously reported approaches for the detection of PSA in serum.

Graphical abstract: A surface-enhanced electrochemiluminescence sensor based on Au-SiO2 core–shell nanocomposites doped with Ru(bpy)32+ for the ultrasensitive detection of prostate-specific antigen in human serum

Article information

Article type
Paper
Submitted
28 sept. 2019
Accepted
05 nov. 2019
First published
06 nov. 2019

Analyst, 2020,145, 132-138

A surface-enhanced electrochemiluminescence sensor based on Au-SiO2 core–shell nanocomposites doped with Ru(bpy)32+ for the ultrasensitive detection of prostate-specific antigen in human serum

D. Wang, J. Zhou, L. Guo, B. Qiu and Z. Lin, Analyst, 2020, 145, 132 DOI: 10.1039/C9AN01935A

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