Abstract

In this research, we have developed biosensors to detect beta human chorionic gonadotropin (beta-HCG) which is a hormone widely used to test for pregnancy and also serves as a biomarker for risk assessment of certain types of cancers. The biosensor methodology is based on extended gate design of electrical double layer (EDL) gated field effect transistor (FET). In this study, we fabricated a sensor array chip and functionalized the gold electrode surface with antibodies to capture the antigen, beta-HCG. Each sensor in the sensor array chip consists of two gold electrodes, one connected to the gate voltage supply and the other connected to the gate terminal of the FET, which is located on isolated PCB such that the test solution does not directly contact the transistor active region. A hand-held sensor measurement unit is fabricated which can apply the biasing voltages, measurement the resulting drain current signal and display the output results in LCD monitor. Fluorescence measurement technique is used to confirm and analyze the surface functionalization with antibodies to beta-HCG. The relation between beta-HCG antigen concentration and electrical signal is established by testing the sensor array chips using the hand-held device. The test samples are prepared by diluting purified stock proteins in 1X PBS, as it simulates the physiological conditions of human urine. Using our FET biosensor, we can directly detect beta-HCG in high ionic strength media like 1X PBS, without performing additional sample processing. Most pregnancy tests have a sensitivity of 25–50 IU/l (1.5-3 ng/ml), based on immunochromatography which is the most widely technique for detection of beta-HCG. Using our sensor methodology, we can obtain a sensor response curve with a dynamic range of antigen concentration between 0.03 to 30 ng/ml. As the antigen concentration approximately approaches 10 ng/ml, the current gain value is nearly saturated. The result shows that when beta-HCG antigen concentration increases, current gain value decreases. This sensing methodology can facilitate quantitative detection of beta-HCG in physiological conditions, whereas the current commercially available assays provide only qualitative test results. The sensor demonstrates a very wide dynamic range of detection, with a very low detection limit, which shows the potential of our sensor to detect pregnancies in very early stages. Furthermore, this sensor platform can enable the use of beta-HCG for risk stratification of cancers as well. The sensor can be batch produced and does not use additional labels/reagents or sample pre-processing techniques, which can greatly enhance the cost-effectiveness, comparable to the current commercialized beta-HCG assays.

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