Ultrasensitive non enzymatic multiple immunosensor for tumor markers detection by coupling DNA hybridization chain reaction with intercalated molecules

Publication date: 15 April 2017
Source:Biosensors and Bioelectronics, Volume 90
Author(s): Jinjin Guo, Junchun Wang, Junjun Zhang, Wenjuan Zhang, Yuzhong Zhang
In this study, we tried coupling the small signal molecules that could intercalate into DNA double helix with hybridization chain reaction (HCR) technique to fabricate a multiple immunosensor. Doxorubicin hydrochloride (DXH) and methylene blue (MB) were used as signal molecules and alpha-fetoprotein (AFP) and carcinoembryonic antigen (CEA) were selected as model biomarkers. The immunosensor mainly consists of three parts as follows: First, two different primary antibodies (Ab1) immobilized on the surface of gold nanoparticles (Au NPs); Second, secondary antibodies (Ab2) conjugated with DNA primer; Third, long DNA concatemers from HCR were used as a carrier to intercalate amounts of signal molecules (DXH or MB). A sandwich immunocomplex was formed among primary antibodies, target biomarkers and secondary antibodies conjugated with DNA primer via specific recognition reaction. Afterwards, DNA concatemers intercalating amounts of DXH or MB were linked to DNA primer via DNA hybridization. Square wave voltammetry (SWV) was employed to record the response signals from electroactive molecules DXH and MB, and two distinguishable signals were obtained, which peak potentials were at about −0.30V (corresponding to MB) and −0.70V (corresponding to DXH, both vs SCE), respectively. The signal intensities of MB and DXH were linearly related to the logarithm of biomarkers concentration in the range of 0.05pgmL⁻¹–25ngmL⁻¹, and the limit of detection were 0.03pgmL⁻¹ for CEA and 0.02pgmL⁻¹ for AFP (at S/N=3), respectively. Furthermore, the immunosensor exhibited a sensitive electrochemical response to biomarkers in human serum samples and the results obtained were in accordance with reference method, indicating the immunosensor can be applied to real sample analysis in clinic diagnosis.



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