Thesis: Ph. D., Massachusetts Institute of Technology, Computational and Systems Biology Program, 2016. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 82-85). / Whether at the level of a single protein, or in the cytoplasm as a whole, the diffusive mobility of proteins plays a key role in biological function. To measure protein diffusion in cells, researchers have developed multiple fluorescence microscopy methods, and have tested them rigorously. However, using these methods for precise measurement of diffusion coefficients requires expertise that can be a barrier to broad utilization of these methods. Here, we report on a new method we have developed, which we name Photo-converted Intensity Profile Expansion (PIPE). It is a simple and intuitive technique that works on commercial imaging systems and requires little expertise. PIPE works by pulsing photo-convertible fluorescent proteins, generating a peaked fluorescence signal at the pulsed region, and analyzing the spatial expansion of the signal as diffusion spreads it out. The width of the expanding signal is directly related to the protein ensemble mean-square displacement, from which the diffusion coefficient of the ensemble is calculated. In the main part of the thesis, we demonstrate the success of PIPE in measuring accurate diffusion coefficients in silico, in vitro and in vivo. We then broaden the discussion, and challenge the assumption that the Fickian diffusion equation is the most appropriate model for describing protein motion in the cytoplasm. Since the cytoplasm is crowded with obstacles that trap proteins for a wide range of times, the motion of those proteins may be more accurately described by models of anomalous diffusion. To contribute to the ongoing debate about anomalous diffusion, we show how PIPE can be used to measure the degree of diffusion anomality by examining the temporal scaling of the mean-square displacement. Whether for measuring normal or anomalous diffusion, we suggest that the simplicity and user-friendliness of PIPE could make it a useful tool in molecular and cell biology. / by Rotem Gura Sadovsky. / Ph. D.
| Identifer | oai:union.ndltd.org:MIT/oai:dspace.mit.edu:1721.1/104576 |
| Date | January 2016 |
| Creators | Gura Sadovsky, Rotem |
| Contributors | Jeremy L. England., Massachusetts Institute of Technology. Computational and Systems Biology Program., Massachusetts Institute of Technology. Computational and Systems Biology Program. |
| Publisher | Massachusetts Institute of Technology |
| Source Sets | M.I.T. Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | 85 pages, application/pdf |
| Rights | M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission., http://dspace.mit.edu/handle/1721.1/7582 |
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