Issue 15, 2023

Electrochemical detection of SARS-CoV-2 based on copper nanoflower-triggered in situ growth of electroactive polymers

Abstract

SARS-CoV-2, the pathogen of COVID-19, has introduced massive confirmed cases and millions of deaths worldwide, which poses a serious public health threat. For the early diagnosis of COVID-19, we have constructed an electrochemical biosensor-combined magnetic separation system with copper nanoflower-triggered cascade signal amplification strategy. In the proposed system, magnetic beads were utilized to fabricate the recognition element for capturing the conserved sequence of SARS-CoV-2. As the copper ions source, oligonucleotides modified copper nanoflowers with special layered structure provide numerous catalysts for click chemistry reaction. When target sequence RdRP_SARSr-P2 appears, copper nanoflowers will be bound with magnetic beads, thus prompting the Cu(I)-catalyzed azide–alkyne cycloaddition reaction through the connection of the SARS-CoV-2 conserved sequence. Then, a large number of signal molecules FMMA can be grafted onto the modified electrode surface by electrochemically mediated atom-transfer radical polymerization to amplify the signal for the quantitative analysis of SARS-CoV-2. Under optimal conditions, a linear range from 0.1 to 103 nM with a detection limit of 33.83 pM is obtained. It provides a powerful tool for the diagnosis of COVID-19, which further benefits the early monitoring of other explosive infectious diseases effectively, thus guaranteeing public health safety.

Graphical abstract: Electrochemical detection of SARS-CoV-2 based on copper nanoflower-triggered in situ growth of electroactive polymers

Supplementary files

Article information

Article type
Paper
Submitted
05 May 2023
Accepted
27 Jun 2023
First published
29 Jun 2023

Analyst, 2023,148, 3659-3665

Electrochemical detection of SARS-CoV-2 based on copper nanoflower-triggered in situ growth of electroactive polymers

J. Lu, X. Zhou, Y. Li, M. Yu, S. Fu, Z. Qu, Y. Li, J. Miao and Y. Xu, Analyst, 2023, 148, 3659 DOI: 10.1039/D3AN00716B

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