Issue 17, 2014

Electrochemical detection of leukemia oncogenes using enzyme-loaded carbon nanotube labels

Abstract

We describe an ultrasensitive electrochemical nucleic acid assay amplified by carbon nanotubes (CNTs)-based labels for the detection of human acute lymphocytic leukemia (ALL)-related p185 BCR-ABL fusion transcript. The carboxylated CNTs were functionalized with horseradish peroxidase (HRP) molecules and target-specific detection probes (DP) via diimide-activated amidation and used to label and amplify the target hybridization signal. The activity of captured HRP was monitored by square-wave voltammetry measuring the electroactive enzymatic product in the presence of 2-aminophenol and hydrogen peroxide substrate solution. The signal-amplified assay achieved a detection limit of 83 fM (5 × 10−18 mol in 60 μL) targets oligonucleotides and has a 4-order-wide dynamic range of target concentration. The resulting assay allowed robust discrimination between the perfect match and a three-base mismatch sequence. When exposed to the full-length (491 bp) DNA oncogene, the approach demonstrated a detection limit of 1 × 10−16 mol in 60 μL, corresponding to approximately 33 pg of the target gene. The high sensitivity and specificity of the assay enabled a PCR-free detection of target transcripts in as little as 65 ng of mRNA extracted from positive ALL cell lines SUP-B15 in comparison to those obtained from negative cell line HL-60. The approach enables a simple, low-cost and ultrasensitive electrochemical nucleic acid detection in portable devices, point-of-care and early disease diagnostic applications.

Graphical abstract: Electrochemical detection of leukemia oncogenes using enzyme-loaded carbon nanotube labels

Article information

Article type
Paper
Submitted
10 Jun 2013
Accepted
19 May 2014
First published
20 May 2014

Analyst, 2014,139, 4223-4230

Author version available

Electrochemical detection of leukemia oncogenes using enzyme-loaded carbon nanotube labels

A. Lee, D. Du, B. Chen, C. Heng, T. Lim and Y. Lin, Analyst, 2014, 139, 4223 DOI: 10.1039/C3AN01156A

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