Sensing and imaging of hyaluronidase activity using a long-lived fluorophore

Date

2016-05-01

Authors

Chib, Rahul

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Abstract

This dissertation explores the synthesis, characterization and biomedical applications of a fluorescent probe for sensing and imaging of hyaluronidase activity. The enzyme hyaluronidase is overexpressed in various cancer including bladder cancer, prostate cancer, melanoma, head and neck carcinoma etc. Fluorescence-based sensing and imaging have tremendous applications in biomedical sciences. A fluorescent probe specific to a disease biomarker can help in the diagnosis and treatment of various diseases like cancer. Fluorescence emission in the red region of the electromagnetic spectrum provides the best optical window for sensing and imaging, as the contribution of autofluorescence decreases in this region. To distinguish the signal from the fluorophore and autofluorescence, efforts have been focused on developing red-emitting fluorophores, preferentially with a long fluorescence lifetime (significantly longer than autofluorescence). This improves signal-to-noise ratio and opens the possibility for time-gated detection. However, the commercially available red fluorophores have a very short fluorescence lifetime. The groups of currently developed triangulenium fluorophores like Azadioxatriangulenium (ADOTA), which emits in the orange/red region with a long fluorescence lifetime and high quantum yield presents great opportunities for sensing and imaging applications. The goal of this study was to characterize the photophysical properties of Azadioxatriangulenium (ADOTA) fluorophore and explore its properties for biomedical sensing and imaging. A sensor for the enzyme hyaluronidase was developed by using ADOTA fluorophore. This sensor was developed by heavy labeling of hyaluronic acid with ADOTA fluorophore. Results from these studies show the applications of ADOTA in fluorescence-based sensing, as a contrast agent in fluorescence-lifetime imaging microscopy (FLIM), and its application in time-gated detection for background-free cellular imaging.

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