Development Of An Optical Surface Plasmon Resonance Biosensor Based On A Laser Line Generator

The surface plasmon resonance(SPR) biosensor based on laser line generator is designed to meet the requirements for portable bioanalyzers, which is used in field with high sensitivity, high performance and low cost. The biosensor based on surface plasmon resonance plays an vital role in food safety, toxic moleculars detection, the environmental protection and so on. Compared to the traditional analysis method, the kinetic analysis of biomolecular interaction using this SPR biosensor has a great significance to monitor the response rate and affinity of biomolecular interaction in analyzing the protein function, drug discover, genomics and proteomics research. Non-destructive and real-time monitoring the association and dissociation between antigens and antibodies can be performed by using optical surface plasmon resonance (SPR) biosensor technology. This technology provides a quantitative analysis that is carried out rapidly with label-free high-throughput detection using the binding curves of antigens-antibodies. Consequently, the kinetic parameters of interaction between antigens and antibodies can be obtained, so this technology is the best way to research the interaction of biomoleculars.This thesis presents a novel design method of optical surface plasmon resonance biosensor in which a laser line generator was used as a light source of the biosensor. The construction and photoelectricity detecting principle and experiment of the optical biosensor based on linear laser were introduced. A series experiments were designed to validate the performance of the optical biosensor using HBsAg, HBsAb and different volume fraction ethanol and also to construct the resonance response curves. We also developed the kinetic analysis method of biomolecular interaction. As a biosensor for use in monitoring the response curves of biomolecular interaction, it is based on a laser line generator and composed of a microflow cell, a clamp and a photoelectronic conversion device. There are three channels in the microflow cell, so the bioanalyzer can perform nearly simultaneously SPR measurements up to three channels or set reference channels. The curves and evaluates kinetic parameters are constructed using the microprocessor chip PIC16F876A, and a semiconductor temperature-control chip is embedded inside. The temperature is controlled by a PID regulated module algorithm, and the temperature signal come from the microprossor are output to the upper computer through the USB interface. The thesis suggests, under appropriate assumptions, an optimal analysis fitting method-the least squares fitting derived for measuring biomolecular interaction parameters, and the centroid algorithm for calculating the resonance dip position of reflected spectra for a decrease in signal to noise ratio. The moving average filter, polynomial fitting and the centroid algorithm used for calculating the resonance dips are described in detail. The experiments were designed to validate the performance of the optical biosensor using different volume fraction ethanol 13%, 14%, 16%, 17%, 18%, 19%, respectively. It is shown that the fitting algorithm is insensitive to optical power and surrounded factors correlated noise/drift. In the certain range of volume fraction ethanol, there is a linear relation existed between the concentration of ethanol and optical response dip corresponsing to the resonance pixels position. The correlation coefficient is -0.9852 and the sensitivity is 959.60 (resonance pixels position per volume fraction ethanol).Generally, the kinetic model of biomolecular interaction is a very complicated nonlinear function, in which the kinetic parameters are difficult obtained if the common numerical method was used for solving differential equation. This thesis proposes a novel method to evaluate the kinetic parameters of biomolecular interaction which combined the Newton Iteration Method and the Least Squares Method. First, the Pseudo First Order kinetic model of biomolecular interaction was established. Then the data of molecular interaction of HBsAg and HBsAb was obtained by biosensor. Finally, we used the optical SPR bioanalyzer software which was written by ourselves to make nonlinear curve fitting for analyzing the association and dissociation parameters. The R-squared value as high as 0.99229 and 0.99593 are obtained within the optimized operating range, respectively and a curve excellently fitting to the experimental data is given with an associated rate constant ka of 6.969×105 ml·g-1·s-1 and a dissociate rate constant kd of 0.00073 s-1 .