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dc.contributor.advisorGerald R. Fink.en_US
dc.contributor.authorNewby, Gregory A. (Gregory Arthur)en_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Biology.en_US
dc.date.accessioned2017-09-15T15:28:32Z
dc.date.available2017-09-15T15:28:32Z
dc.date.copyright2017en_US
dc.date.issued2017en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/111310
dc.descriptionThesis: Ph. D., Massachusetts Institute of Technology, Department of Biology, 2017.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references.en_US
dc.description.abstractProteins mediate every cellular process. In order for life to exist, each protein must be finely tuned to carry out its function at the proper time and place. Because the environment is dynamic and often unpredictable, the regulation of proteins must be responsive to environmental stimuli. Mutations, age, and severe or repeated insults can decrease the quality of protein regulation, leading to disease. The study of protein regulation and its dysfunction in disease are of vital importance. Regulatory and disease phenomena involving protein assembly or aggregation are common but currently understudied on account of their intractability with existing techniques. In order to equip scientists with better tools to tackle these difficult phenomena, my collaborators Ahmad Khalil and Szilvia Kiriakov (Boston University) and I developed the yTRAP platform (standing for: yeast transcriptional reporters of aggregating proteins). yTRAP couples the activity of a synthetic transcriptional activator to a protein's solubility. It enables sensitive measurement of a protein's state within a eukaryotic cellular context, preserving complex interactions that may be lost using in vitro techniques. yTRAP can be measured in high throughput to enable large studies, screens, and selections on aggregation phenomena. The reporter output is modular and can be customized to desired purposes and measurement modalities. Using a fluorescent output, the signal from yTRAP is readily quantifiable. The combination of these desirable properties enables many kinds of previously-impossible studies. Furthermore, because of its exquisite sensitivity, yTRAP can be used to broadly screen for protein perturbation beyond the context of aggregation. For example, it can report on alterations in protein localization, binding partners, or degradation. I applied yTRAP to track yeast prions, which have previously been difficult to study due to a lack of simple and reliable reporters. Prions are protein-based elements of inheritance that have profound implications for the evolution of single-celled organisms. I first utilized yTRAP to identify factors that faithfully switch prion states on and off, thus proving that prion states can be deterministically regulated. I used these factors to create new cellular tools out of prions: 1) a memory device that records elevated temperatures experienced by a yeast population, and 2) an anti-prion drive that eliminates prions from mating partners and progeny. Separately, I conducted an ecological study into the yeast prion [SW*]. I found that [SWI*] confers a 'pioneering' cellular program that encourages migration and diverse mating partners. Loss of the prion confers a protective 'settled' cellular program with growth and survivability advantages. yTRAP greatly facilitated this study through reliable tracking of the prion state. Prion-like phenomena are now ripe for study with yTRAP.en_US
dc.description.statementofresponsibilityby Gregory A. Newby.en_US
dc.format.extent163 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT 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.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectBiology.en_US
dc.titleA genetic platform for the study of protein perturbation and prion-based inheritanceen_US
dc.typeThesisen_US
dc.description.degreePh. D.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Biology
dc.identifier.oclc1003284610en_US


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