Semi-analytical dynamic modeling of DNA surface-hybridization via AC Electro-kinetic steering

Abstract

The change in electrical property (capacitance) upon hybridization of the desired ssDNA to a capture probe has been proposed as a promising technology platform in biomedical research and practice. An appropriate mathematical model is needed for understanding and optimizing the process occurring at the electrode/electrolyte interface. It is also informative for examining the forces generated by the AC electric fields on the DNA molecules as well as the suspending buffer solution in the experimental pool. Here, we provide the development, formulation and validation of a semi-analytical model of DNA hybridization with deoxynucleotide molecules chemically tethered to a solid gold electrode. The parameters of the proposed model have been estimated using available experimental data. We demonstrate that the detection limit and specificity of our surface-based genosensor are not only dependent on the probe/target binding affinity, but also on the Self-Assembled Monolayer (SAM) density and on the interfacial electric field. The label-free Electrochemical Impedance Spectroscopy (EIS)-based oligonucleotide biosensor with integrated DC-biased can achieve rapid hybridization, high selectivity and sensitive detection for DNA target samples. SIGNIFICANCEDNA hybridization, wherein strands of DNA form duplex through noncovalent, sequence-specific interactions, is one of the most fundamental processes in biology. Fast and reliable determination of miniature amounts of DNA plays important role in clinical forensic and pharmaceutical applications. Thus, developing a better understanding of the kinetic and dynamic properties of DNA hybridization will help in the elucidation of all mechanisms involved in numerous biochemical processes. Moreover, because DNA hybridization has been widely adapted in biotechnology, its study is invaluable to the development of a range of commercially important processes. To achieve optimal sensitivity with minimum sample size and rapid hybridization, ability to predict the kinetics of hybridization based on the characteristics of the strands is crucial, and hence a computer aided numerical model for the design and optimization of a DNA biosensor has been implemented.