Issue 21, 2017, Issue in Progress

Rapid detection of blaNDM-1 in multidrug-resistant organisms using a novel electrochemical biosensor

Abstract

Traditional detection methods of multidrug-resistant organisms (MDROs) include phenotype-based screening for carbapenem-hydrolyzing enzymes, such as the paper disk diffusion assay, the broth trace dilution assay, a modified Hodge assay, and sequencing analysis. In the present study, a novel electrochemical biosensor was successfully constructed, and highly specific locked nucleic acid (LNA) probes were used for the marker-free, direct, and rapid detection of the drug-resistance gene blaNDM-1 in MDROs in complex clinical specimens. The highly specific LNA probes were designed for the direct and fast detection of blaNDM-1 DNA in clinical bacterial specimens without requiring culturing or amplification. The linearity range was 10 pg L−1 to 100 μg L−1, and the limit of detection was as low as 1 pg L−1. The mean coefficient of variation values of intra-day and inter-day reproducibility were 3.93% and 5.96%, respectively. The time for biosensor incubation and scanning detection was as short as 30 min. In addition, the immunity of the electrochemical biosensor against interference was excellent. In the present study, highly specific LNA probes, fast detection, and the simultaneous acquisition and analysis of data were combined to create a novel marker-free direct detector of bacterial drug-resistance genes, which is crucial for the fast diagnosis of multidrug-resistant organisms and holds promise for the fast accurate detection of other drug-resistant bacteria.

Graphical abstract: Rapid detection of blaNDM-1 in multidrug-resistant organisms using a novel electrochemical biosensor

Article information

Article type
Paper
Submitted
08 Dec 2016
Accepted
16 Feb 2017
First published
22 Feb 2017
This article is Open Access
Creative Commons BY-NC license

RSC Adv., 2017,7, 12576-12585

Rapid detection of blaNDM-1 in multidrug-resistant organisms using a novel electrochemical biosensor

L. Zhang, J. Wang, F. Liu, Y. Xiong, Z. Liu, D. Jiang, Y. Li, D. Tu, Y. Wang and X. Pu, RSC Adv., 2017, 7, 12576 DOI: 10.1039/C6RA27916C

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