A biomolecule compatible electrical model of microimpedance affinity biosensor for sensitivity improvement in cell detection

Microimpedance affinity biosensors using interdigitated electrodes are being extensively employed for label free and rapid detection of bacteria molecules. To improve the sensitivity of such sensors, it is required to maximize the antibody immobilization and bacteria captured for an applied input concentration through proper quantification and also optimize the electrode geometry to achieve maximum signal to noise ratio. In this paper, a biomolecule compatible electrical model has been developed which quantifies the number of immobilized antibody and captured bacteria by simple calculations from impedance spectroscopy results which are comparable to the accuracy obtained by conventional time consuming and sometimes expensive biochemical methods and can also estimate the electrode impedance associated with each biomolecule. The model has been applied for the detection of Escherichia coli K12 bacteria by antibody–antigen binding method on gold electrodes with PBS as the background solution. The quantitative estimation of the actual number of antibody immobilized and bacteria captured for input concentration of 103 and 106 CFU/ml on the gold surface in this case has been matched with the conventional optical density methods and radioactive labeling method respectively. A quantitative relationship between the geometrical parameters and the output signal has been deduced after extracting the electrode impedance for each biomolecule and the effects of transducer geometry on the sensitivity of this biosensor have been matched with recently reported experimental results for the same system. Thus the proposed model enables quantitative estimation of the antibody immobilized and bacteria captured and quantitative prediction of the optimum geometry for maximum sensitivity eliminating the need for trial and error experimentation. This will lead to a rapid and cost effective method for performance enhancement of microimpedance biosensors with different topologies.