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Anal Chem. 2017 Mar 7;89(5):3108-3115. doi: 10.1021/acs.analchem.6b04871. Epub 2017 Feb 10.

Universal Dynamic DNA Assembly-Programmed Surface Hybridization Effect for Single-Step, Reusable, and Amplified Electrochemical Nucleic Acid Biosensing.

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Key Laboratory of Sensor Analysis of Tumor Marker, Ministry of Education, College of Chemistry and Molecular Engineering, Qingdao University of Science and Technology , No. 53, Rd. Zhengzhou, Qingdao, Shandong 266042, China.


The traditional sensitive electrochemical biosensors are commonly confronted with the cumbersome interface operation and washing procedures and the inclusion of extra exogenous reagents, which impose the challenge on the detection simplicity, reliability, and reusability. Herein, we present the proof-of-principle of a unique biosensor architecture based on dynamic DNA assembly programmed surface hybridization, which confers the single-step, reusable, and enzyme-free amplified electrochemical nucleic acid analysis. To demonstrate the fabrication universality three dynamic DNA assembly strategies including DNA-fueled target recycling, catalytic hairpin DNA assembly, and hybridization chain reaction were flexibly harnessed to convey the homogeneous target recognition and amplification events into various DNA scaffolds for the autonomous proximity-based surface hybridization. The current biosensor architecture features generalizability, simplicity, low cost, high sensitivity, and specificity over the traditional nucleic acid-related amplified biosensors. The lowest detection limit of 50 aM toward target DNA could be achieved by hybridization chain reaction-programmed surface hybridization. The reliable working ability for both homogeneous solution and heterogeneous inteface facilitates the target analysis with a robust reliability and reproducibility, also making it to be readily extended for the integration with the kinds of detecting platforms. Thus, it may hold great potential for the biosensor fabrication served for the point-of-care applications in resource constrained regions.

[Indexed for MEDLINE]

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