Issue 16, 2014

Detection of polynucleotide kinase activity by using a gold electrode modified with magnetic microspheres coated with titanium dioxide nanoparticles and a DNA dendrimer

Abstract

In this paper, we have designed a signal amplified method for the electrochemical determination of polynucleotide kinase activity. It is based on (a) the peroxidase-like activity of magnetite microspheres (MNPs), (b) the specific recognition capabilities of titanium dioxide (TiO2) with the phosphate groups of the capture probe and (c) the DNA dendrimer structure for signal amplification. MNPs coated with TiO2 (TMNPs) were prepared and characterized by scanning electron microscopy (SEM) and Fourier transform infrared (FTIR) spectroscopy. TMNP–DNA dendrimers were formed by the hybridization of captured nucleic acids with a link probe. Cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) were carried out to study the electrocatalytic process. The formation of the TMNP–DNA dendrimer structures was related to the phosphorylated capture probe and further to the activity of polynucleotide kinase, which was the base of the polynucleotide kinase detection. The TMNP–DNA dendrimer based biosensor showed sensitive detection of polynucleotide kinase with a satisfying result; a low detection of 0.003 U mL−1 and wide linear range of 0.01 to 30 U mL−1 were achieved. Additionally, the present TMNP–DNA dendrimer based biosensor also demonstrated excellent selectivity, stability and reproducibility.

Graphical abstract: Detection of polynucleotide kinase activity by using a gold electrode modified with magnetic microspheres coated with titanium dioxide nanoparticles and a DNA dendrimer

Supplementary files

Article information

Article type
Paper
Submitted
18 Mar 2014
Accepted
11 Apr 2014
First published
11 Apr 2014

Analyst, 2014,139, 3895-3900

Detection of polynucleotide kinase activity by using a gold electrode modified with magnetic microspheres coated with titanium dioxide nanoparticles and a DNA dendrimer

G. Wang, L. Chen, X. He, Y. Zhu and X. Zhang, Analyst, 2014, 139, 3895 DOI: 10.1039/C4AN00499J

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