PubMed2006
Due to the ability to detect multiple parameters simultaneously, protein microarrays have found widespread applications from basic biological research to diagnosis of diseases. Generally, readout of protein microarrays is performed by fluorescence detection using either dye-labeled detector antibodies or direct labeling of the target proteins. We developed a method for the label-free detection and quantification of proteins based on time-gated, wide-field, camera-based UV fluorescence lifetime imaging microscopy to gain lifetime information from each pixel of a sensitive CCD camera. The method relies on differences in the native fluorescence lifetime of proteins and takes advantage of binding-induced lifetime changes for the unequivocal detection and quantification of target proteins. Since fitting of the fluorescence decay for every pixel in an image using a classical exponential decay model is time-consuming and unstable at very low fluorescence intensities, we used a new, very robust and fast alternative method to generate UV fluorescence lifetime images by calculating the average lifetime of the decay for each pixel in the image stack using a model-free average decay time algorithm.To validate the method, we demonstrate the detection and quantification of p53 antibodies, a tumor marker in cancer diagnosis. Using tryptophan-containing capture peptides, we achieved a detection sensitivity for monoclonal antibodies down to the picomolar concentration range. The obtained affinity constant, Ka, of (1.4 +/- 0.6) x 10(9) M(-1), represents a typical value for antigen/antibody binding and is in agreement with values determined by traditional binding assays.