Quantitative analysis of apoptotic decisions in single cells and cell populations

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Biology, 2007.

Bibliographic Details
Main Author: Albeck, John G
Other Authors: Peter K. Sorger.
Format: Thesis
Language:eng
Published: Massachusetts Institute of Technology 2007
Subjects:
Online Access:http://hdl.handle.net/1721.1/38589
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author Albeck, John G
author2 Peter K. Sorger.
author_facet Peter K. Sorger.
Albeck, John G
author_sort Albeck, John G
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description Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Biology, 2007.
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spelling mit-1721.1/385892019-04-09T18:10:26Z Quantitative analysis of apoptotic decisions in single cells and cell populations Albeck, John G Peter K. Sorger. Massachusetts Institute of Technology. Dept. of Bioogy. Massachusetts Institute of Technology. Dept. of Bioogy. Bioogy. Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Biology, 2007. Includes bibliographical references. Apoptosis is a form of programmed cell death that is essential for the elimination of damaged or unneeded cells in multicellular organisms. Inactivation of apoptotic cell death is a necessary step in the development of cancer, while hypersensitivity to apoptosis is a factor in degenerative diseases. Many of the molecular components controlling apoptosis have been identified, including the central effectors of apoptosis, a family of proteases known as caspases that efficiently dismantle the cell when active. While many of the molecular details of apoptotic regulators are now understood, a major challenge is to integrate this information to understand quantitatively how sensitivity to apoptosis and the kinetics of death are determined, in both single cells and populations of cells. We have approached this problem with a combined experimental and computational approach. Using single-cell observations, genetic and pharmacological perturbations, and mechanistic mathematical modeling, we have dissected the mechanism by which cells make a binary decision between survival and apoptosis. We identified conditions under which the apoptotic decision system fails, allowing cells to survive with caspase-induced damage that may result in damage to the genome and oncogenesis. (cont.) We further used live-cell imaging to identify and characterize a kinetic threshold at which slow and variable upstream signals are converted into rapid and discrete downstream caspase activation. Lastly, we examined the integration of multiple pro-and apoptotic signal transduction pathways by constructing a principal component-based model that linked apoptotic phenotypes to a compendium of signaling measurements. This approach enabled the identification of the molecular signals most important in determining the level of apoptosis across a population of cells. Together, our findings provide insight into the molecular and kinetic mechanisms by which cells integrate diverse molecular signals to make a discrete cell fate decision. by John G. Albeck. Ph.D. 2007-08-29T20:31:49Z 2007-08-29T20:31:49Z 2007 2007 Thesis http://hdl.handle.net/1721.1/38589 156823553 eng 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 2 v. (287 leaves) application/pdf Massachusetts Institute of Technology
spellingShingle Bioogy.
Albeck, John G
Quantitative analysis of apoptotic decisions in single cells and cell populations
title Quantitative analysis of apoptotic decisions in single cells and cell populations
title_full Quantitative analysis of apoptotic decisions in single cells and cell populations
title_fullStr Quantitative analysis of apoptotic decisions in single cells and cell populations
title_full_unstemmed Quantitative analysis of apoptotic decisions in single cells and cell populations
title_short Quantitative analysis of apoptotic decisions in single cells and cell populations
title_sort quantitative analysis of apoptotic decisions in single cells and cell populations
topic Bioogy.
url http://hdl.handle.net/1721.1/38589
work_keys_str_mv AT albeckjohng quantitativeanalysisofapoptoticdecisionsinsinglecellsandcellpopulations