dc.contributor.advisor | Mehmet Fatih Yanik. | en_US |
dc.contributor.author | Gilleland, Cody Lee | en_US |
dc.contributor.other | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. | en_US |
dc.date.accessioned | 2015-01-05T20:02:34Z | |
dc.date.available | 2015-01-05T20:02:34Z | |
dc.date.copyright | 2014 | en_US |
dc.date.issued | 2014 | en_US |
dc.identifier.uri | http://hdl.handle.net/1721.1/92654 | |
dc.description | Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2014. | en_US |
dc.description | Cataloged from PDF version of thesis. | en_US |
dc.description | Includes bibliographical references (pages 143-150). | en_US |
dc.description.abstract | Caenorhabditis elegans (C. elegans) is a widely studied model organism due to their fully mapped neural network of 302 neurons and amenable genetics. Their small size and short life cycle allows for rapid studies to be conducted; however, after decades of use the manual methods of manipulation have remained relatively unchanged. This thesis details the development of largely automated, high-throughput, optical, robotic, and microfluidic technologies for laser neurosurgery screening and transgenesis in C. elegans. Discovery of molecular mechanisms and chemical compounds that enhance neuronal regeneration can lead to development of therapeutics to combat nervous system injuries and neurodegenerative diseases. By combining high-throughput microfluidics and femtosecond laser microsurgery, we demonstrate for the first time large-scale in vivo screens for identification of compounds that affect neurite regeneration. We performed over ten thousand microsurgeries at single-axon precision in the nematode C. elegans at a rate of 20 seconds per animal. Following surgeries, we exposed the animals to a hand-curated library of approximately one hundred small-molecules and identified chemicals that significantly alter neurite regeneration. In particular, we found that the PKC kinase inhibitor staurosporine strongly modulates regeneration in a concentration- and neuronal type-specific manner. Two structurally unrelated PKC inhibitors produce similar effects. We further show that regeneration is significantly enhanced by the PKC activator prostratin. Microinjection is an essential and widely used method for C. elegans transgenesis. Traditional injections have remained low-throughput for decades due to the laborious nature of the manual procedure which prohibit large-scale transgenesis screening. This thesis details the development of the C. elegans Automated Micro-Injection (CAMI) system for high-throughput microinjection which could be broadly useful for analysis of gene function through insertion of CRISPR/Cas9, cDNA or RNAi vectors in future applications. Using the standard roller phenotype the transformation efficiency in creating transgenic lines is comparable to manual injections. We demonstrate the utility of the system by deep-phenotyping a subset of 6 mutants backgrounds selected from the million mutant project. We introduced 12 fluorescent reporters to label 38 neurons in each genetic background in order to search for defects in development. | en_US |
dc.description.statementofresponsibility | by Cody Lee Gilleland. | en_US |
dc.format.extent | 152 pages | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Massachusetts Institute of Technology | en_US |
dc.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. | en_US |
dc.rights.uri | http://dspace.mit.edu/handle/1721.1/7582 | en_US |
dc.subject | Electrical Engineering and Computer Science. | en_US |
dc.title | Large-scale transgenesis and nerve regeneration in C. elegans | en_US |
dc.type | Thesis | en_US |
dc.description.degree | Ph. D. | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science | |
dc.identifier.oclc | 898134950 | en_US |