An alternative strategy for the label‐free electrochemical detection of DNA hypermethylation using a microelectrode array as an oligodinucleotide (ODN) detector is presented. It relies on the oligonucleotide dependent electrostatic affinity interaction firstly with unmethylated ODN and then follow‐up with methylated DNA. The methylated cytosine status is quantified by monitoring the relative change in the exchange current at the ODN‐detector before and after the bisulfite treated DNA samples. This novel aproach displays unique advantages such as small working volumes of the analytes, low damage to DNA samples, easy integration of oligonucleides on the detector and signal evaluation.
Direct and efficient label-free voltammetric detection of Glutathione S-Transferase Pi 1 (GSTP1) hypermethylation is reported using a custom developed 16-channel Microelectrode Array chip. The microelectrode array chip is used in a dipstick configuration allowing detection of DNA hybridization in a solution volume of only 0.35 mL. Platinum microelectrode disks (n = 16) 30 µm in diameter have been modified with a polypyrrole bilayer before any contact with the oligonucleotides. The attachment of the 15-mer Probe DNA to the bilayer is random but controlled by the presence of aliphatic tether groups allowing it to form a bidentate complex with the probe DNA. The voltammetric detection procedure of methylated GSTP1-specific target DNA is combined with bisulfite treatment of target DNA. Changes at the interface of the modified microelectrodes in an array configuration are used to record simultaneously cyclic voltammetry on all of the devices. The detection of the hybridization is evaluated statistically for a event by comparing the changes in recorded cyclic voltammograms before and after exposure to the Target DNA. All cyclic voltammograms of the methylated target show a greater percentage change than those with the non-methylated target exposure and show a greater change in cyclic voltammogram area after methylated target exposure. We observe an average percentage difference of 25.6% ± 4.9 with a variation of 19.1%. These results demonstrate that the fast sensing strategy possesses sensitivity and good specificity. Furthermore, this technology can potentially support rapid, accurate diagnosis and risk assessment of patients with prostate cancer.
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