Semiconductor quantum dots (QDs) have emerged as a new class of fluorescent probes and labeling agents for biological samples. QDs are bright, highly photostable and allow simultaneous excitation of multiple emissions. Owing to these properties, QDs hold exceptional promise in enabling intracellular biochemical studies and diagnosis with unprecedented sensitivity and accuracy. However, use of QD probes inside living cells remains a challenge due to difficulties in delivery of nanoparticles without causing aggregation and imaging single nanoparticles inside living cells. In this dissertation, a systematic approach to deliver, image and locate single QDs inside living cells is presented and the properties of molecular motor protein driven QD transport are studied. First, spectroscopic and imaging methods capable of differentiating single nanoparticles from the aggregates were developed. These technologies were validated by differentiating surface protein expression on viral particles and by enabling rapid counting of single biomolecules. Second, controlled delivery of single QDs into living cells is demonstrated. A surprising finding is that single QDs associate non-specifically with the dynein motor protein complex and are transported to the microtubule organizing center. Accurate localization and tracking of QDs inside cell cytoplasm revealed multiple dynein motor protein attachment resulting in increased velocity of the QDs. Further, spectrin molecule which is known to recruit dynein motor protein complex to phospholipid micelles was found to associate with the QDs. These results may serve as a benchmark for developing new QD surface coatings suitable for intracellular applications. Since, nanoparticles are similar in size to viral pathogens; better understanding of nanoparticle-cell interactions should also help engineer nanoparticle models to study virus-host cell interactions. (Contains AVI format multimedia files)
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/19798 |
| Date | 09 November 2006 |
| Creators | Agrawal, Amit |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Detected Language | English |
| Type | Dissertation |
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