Methods to study protein folding and evolution in vivo

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Chemistry, 2018.

Bibliographic Details
Main Author: Moore, Christopher Lawrence
Other Authors: Matthew D. Shoulders.
Format: Thesis
Language:eng
Published: Massachusetts Institute of Technology 2018
Subjects:
Online Access:http://hdl.handle.net/1721.1/118273
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author Moore, Christopher Lawrence
author2 Matthew D. Shoulders.
author_facet Matthew D. Shoulders.
Moore, Christopher Lawrence
author_sort Moore, Christopher Lawrence
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spelling mit-1721.1/1182732019-04-10T07:50:28Z Methods to study protein folding and evolution in vivo Moore, Christopher Lawrence Matthew D. Shoulders. Massachusetts Institute of Technology. Department of Chemistry. Massachusetts Institute of Technology. Department of Chemistry. Chemistry. Thesis: Ph. D., Massachusetts Institute of Technology, Department of Chemistry, 2018. Cataloged from PDF version of thesis. Includes bibliographical references. Living systems have developed complex gene networks consisting of chaperones and quality control factors which maintain protein homeostasis (proteostasis) by actively monitoring protein folding processes in an organelle-specific and dealing with protein misfolding in a stress-responsive manner. While we know that these "proteostasis networks" are capable of influencing protein folding, we lack molecular details regarding how particular components of proteostasis networks work in concert to deal with protein misfolding. Unfortunately, this gap in knowledge also prevents us from understanding the consequences of proteostasis regulation on higher order biological processes, such as the impact chaperone and quality control factors have on protein evolution. Furthermore, we are not able to comment on how dysfunctional proteostasis networks contribute to prominent disease states, including neurodegeneration, cancer, and even pathogenic infections. Thus, an overarching interest in the Shoulders lab at MIT is to fill the aforementioned knowledge gaps by studying how living metazoan systems handle protein folding problems. The lack of available methods for controlling the activity of proteostasis network components has significantly limited the study of proteostasis in metazoans. In this thesis, I present work that has focused on addressing the limitation in chemical biology tools for studying proteostasis by developing chemical genetic methods tune the level of proteostasis components. Similarly, the inability to conveniently explore protein folding and fitness landscapes on the laboratory timescale has hindered the study of evolution in higher eukaryotes. Thus, my later work sought to overcome this limitation by creating new evolution platforms. Though the inspiration for my work stemmed from a desire to study proteostasis and evolution in metazoans, the methods I developed have allowed other scientists to overcome technical limitations in their own work and progressed the study of many other biological processes beyond proteostasis. by Christopher Lawrence Moore. Ph. D. 2018-09-28T20:59:43Z 2018-09-28T20:59:43Z 2018 2018 Thesis http://hdl.handle.net/1721.1/118273 1054191699 eng MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. http://dspace.mit.edu/handle/1721.1/7582 194 pages application/pdf Massachusetts Institute of Technology
spellingShingle Chemistry.
Moore, Christopher Lawrence
Methods to study protein folding and evolution in vivo
title Methods to study protein folding and evolution in vivo
title_full Methods to study protein folding and evolution in vivo
title_fullStr Methods to study protein folding and evolution in vivo
title_full_unstemmed Methods to study protein folding and evolution in vivo
title_short Methods to study protein folding and evolution in vivo
title_sort methods to study protein folding and evolution in vivo
topic Chemistry.
url http://hdl.handle.net/1721.1/118273
work_keys_str_mv AT moorechristopherlawrence methodstostudyproteinfoldingandevolutioninvivo