Issue 5, 2016

Improvement of enzyme-linked immunosorbent assay for the multicolor detection of biomarkers

Abstract

An enzyme-linked immunosorbent assay that is dependent on enzyme amplification has dominated the current field of protein detection; however, limited multiple detection ability and susceptible enzymatic reactions, and low sensitivity may severely hinder its application. Here, we report a new signal amplification scheme based on allochroic molecule modified carboxyl graphene oxide (cGO), which can be used to develop a multicolor immunoassay named as allochroic-cGO linked immunosorbent assay (ALISA). Thanks to high adsorption levels and a wide selection of allochroic molecules, the simultaneous colorimetric detection of diagnostic biomarkers at a picogram level can be successfully achieved for the first time. In addition, the color change triggered by acidic or basic water can provide a simple, rapid, stable and economical signal output, further meeting the growing biodetection requirements. Moreover, with the help of ALISA, we demonstrate that the combined detection of three tumor biomarkers, including carcino-embryonic antigen, neuron-specific enolase, and cytokeratin-19 fragment, is more valuable for differentiating lung cancer patients than the detection of a single biomarker, further manifesting the superiority of ALISA. All in all, this straightforward approach not only opens up new prospects for multicolor immunoassays, but also has great potential for applications in resource-constrained settings.

Graphical abstract: Improvement of enzyme-linked immunosorbent assay for the multicolor detection of biomarkers

Supplementary files

Article information

Article type
Edge Article
Submitted
09 Nov 2015
Accepted
03 Feb 2016
First published
03 Feb 2016
This article is Open Access

All publication charges for this article have been paid for by the Royal Society of Chemistry
Creative Commons BY-NC license

Chem. Sci., 2016,7, 3011-3016

Improvement of enzyme-linked immunosorbent assay for the multicolor detection of biomarkers

C. Li, Y. Yang, D. Wu, T. Li, Y. Yin and G. Li, Chem. Sci., 2016, 7, 3011 DOI: 10.1039/C5SC04256A

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