Quantitative analysis of apoptotic decisions in single cells and cell populations

• Main Author: Albeck, John G
• Other Authors: Peter K. Sorger.
• Format: Others
• Language: English
• Published: Massachusetts Institute of Technology 2007
• Subjects: Bioogy.
• Online Access: http://hdl.handle.net/1721.1/38589

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.