The overall goal of this NIH R21 research proposal is to develop two versions of a high-throughput plasmonic diagnostic assay for the detection of analytes from complex mixtures. The proposed diagnostic platforms are based on our recent finding that the local surface plasmon resonance (LSPR) behavior of metal nanoparticles (NPs) is extraordinarily sensitive to their distance from a metal film. Drastic changes in both the color and the polarization of the scattered light from the NPs above metal films can be detected upon subtle, Engstrom-scale changes in separation distance;we call this effect the """"""""nanoparticle-film (NPF) plasmon ruler"""""""". We hypothesize that the NPF plasmon ruler can be used to quantify the concentration of analytes from the distance between the NP and film. The first objective of this proposal is to exploit this plasmon ruler effect to develop two new detection modalities for clinical diagnostics in which binding of the analyte by receptor-functionalized NPs will be optically transduced and amplified via large changes in the color and polarization of the scattered light from the NPs when the analyte-bound NPs are either directly adsorbed on a metal film (direct assay) or bind to capture antibodies that are immobilized on the metal film (sandwich assay). The second objective of this proposal is to develop an optical detection system that consists of a conventional red-green-blue (RGB) digital camera and a multivariate statistical image processing algorithm for rapid, high-throughput, and portable detection. The proposed research will have significant biomedical impact, because it will lead to the development of a generic nanotechnology platform for the ultra-sensitive detection of clinical analytes.
The proposed research is clinically significant, because it will lead to the development of a new nanotechnology platform for the ultra-sensitive detection of clinical analytes. The greatest impact of this research will be the development of easy-to-use, disposable nano-biosensors for detection of clinical analytes for point-of-care (POC) clinical diagnostics where cost-effective and time-efficient detection is important.
