Ph.D. Defense by Mei Zhan
Date: November 7, 2014
Time: 3:00 pm
Location: BME (Whitaker) 1214
Hang Lu, Ph.D. (Georgia Institute of Technology) - Thesis Advisor
Queelim Ch'ng, Ph.D. (MRC Centre for Developmental Neurobiology, Kings College London)
Robert Butera, Ph.D. (Georgia Institute of Technology)
Philip J. Santangelo, Ph.D. (Georgia Institute of Technology)
Harold Kim, Ph.D. (Georgia Institute of Technology)
Patrick McGrath, Ph.D. (Georgia Institute of Technology)
New Toolsets to Understand Environmental Sensation and Variability in the Aging Process
Aging is a complex process by which a combination of environmental, genetic and stochastic factors generate whole-system changes that modify organ and tissue function and alter physiological processes. Over the last few decades, many genetic and environmental modulators of aging have been found to be highly conserved between humans and a diverse group of model organisms. Yet, an integrative understanding of how these environmental and genetic variables interact over time in a whole organism to modulate the systemic changes involved in aging is lacking. The goal of this thesis project is to advance a systems perspective of aging by providing the experimental tools and conceptual framework for dissecting the regulatory connection between environmental inputs, molecular outputs and long term aging phenotypes in C. elegans, an experimentally tractable multi-cellular model for aging.
Specifically, this work advances the quantitative imaging toolsets available to biologists by developing and refining microfluidic, hardware, computer vision, and software integration tools for high-throughput, high-content imaging of C. elegans. As a result of these technological advances, new roles for the TGF-beta and serotonin signalling pathways in encoding environmental food signals to influence longevity were uncovered and quantitatively characterized. Moreover, this work develops and integrates new microfluidic technologies with off-chip support systems to establish a platform for long-term tracking of the health and longevity trajectories of large numbers of individual C. elegans. The capabilities of this platform have the potential to address many important questions in aging including addressing environmental determinants of aging, the sources of inter-individual variability, the time course of aging-related declines and the effects of interventional strategies to improve health outcomes. Together, the toolsets for quantitative imaging and the long-term culture platform permit the large-scale investigation of both the internal state and long-term behavioral and health outputs of an important multicellular model organism for aging.