Issue 22, 2017

A universal and enzyme-free immunoassay platform for biomarker detection based on gold nanoparticle enumeration with a dark-field microscope

Abstract

Developing an enzyme-free, non-amplification strategy for biomarker detection with universality and easy implementation is of central importance in clinical diagnosis and therapeutic monitoring. Herein, we report for the first time a universal and enzyme-free magnetic bead-based sandwich-format immunoassay platform for biomarker detection by combining secondary antibody functionalized AuNPs and automatic AuNP counting readout. For the prostate specific antigen (PSA), the detection limit is found to be 1 ng mL−1, and the spike recoveries (n = 3) with 10% fetal bovine serum are 113.5% for 2 ng mL−1 and 107.7% for 10 ng mL−1. The assay also presents reasonable repeatability as indicated by the coefficient of variance of 13.1% with 5 measurements in 60 days. This strategy has been successfully applied to the determination of carcinoembryonic antigen (CEA) and alpha-fetoprotein (AFP), demonstrating the universality of this strategy. Our proposed non-amplification platform presents sensitivity comparable to that of the enzyme-linked immunosorbent assay (ELISA) with better repeatability; and more importantly, our method has better simplicity than most of the amplification-based methods, and thus is more suitable for routine analysis. The highlights of our work suggest that it is a promising method and would be potentially an alternative for ELISA in laboratories where routine analyses are intensively performed.

Graphical abstract: A universal and enzyme-free immunoassay platform for biomarker detection based on gold nanoparticle enumeration with a dark-field microscope

Supplementary files

Article information

Article type
Communication
Submitted
08 Sep 2017
Accepted
18 Sep 2017
First published
26 Sep 2017

Analyst, 2017,142, 4201-4205

A universal and enzyme-free immunoassay platform for biomarker detection based on gold nanoparticle enumeration with a dark-field microscope

X. Wu, T. Li, G. Tao, R. Lin, X. Pei, F. Liu and N. Li, Analyst, 2017, 142, 4201 DOI: 10.1039/C7AN01495C

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