In recent years, semiconductor quantum dots (QDs) have arisen as a new class of fluorescent probes that possess unique optical and electronic properties well-suited for single-molecule imaging of dynamic live cell processes. Nonetheless, the large size of conventional QD-ligand constructs has precluded their widespread use in single-molecule studies, especially on cell interiors. A typical QD-ligand construct can range upwards of 35 nm in diameter, well exceeding the size threshold for cytosolic diffusion and posing steric hindrance to binding cell receptors. The objective of this research is to develop tagging strategies that allow QD-ligand conjugates to specifically bind their target proteins while maintaining a small overall construct size. To achieve this objective, we utilize the HaloTag protein (HTP) available from Promega Corporation, which reacts readily with a HaloTag ligand (HTL) to form a covalent bond. When HaloTag ligands are conjugated to size-minimized multidentate polymer coated QDs, compact QD-ligand constructs less than 15 nm in diameter can be produced. These quantum dot-HaloTag ligand (QD-HTL) conjugates can then be used to covalently bind and track cellular receptors genetically fused to the HaloTag protein. In this study, size-minimized quantum dot-HaloTag ligand conjugates are synthesized and evaluated for their ability to bind specifically to purified and cellular HTP. The effect of QD-HTL surface modifications on different types of specific and nonspecific cellular binding are systematically investigated. Finally, these QD-HTL conjugates are utilized for single-molecule imaging of dynamic live cell processes. Our results show that size-minimized QD-HTLs exhibit great promise as novel imaging probes for live cell imaging, allowing researchers to visualize cellular protein dynamics in remarkable detail.
Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/52150 |
Date | 27 August 2014 |
Creators | Wen, Mary Mei |
Contributors | Nie, Shuming |
Publisher | Georgia Institute of Technology |
Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
Language | en_US |
Detected Language | English |
Type | Dissertation |
Format | application/pdf |
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