Sleep is a vital process thought to provide a restorative function and is one of the most conserved behaviors in the animal kingdom. Inadequate sleep has been shown to have negative health implications, yet the molecular mechanisms that underlie the sleep process are not well understood. The fruit fly, Drosophila melanogaster, is a genetically tractable model organism with homology to mammalian sleep regulation that can be used to collect a vast amount of experimental data that may associate with the underlying mechanism of sleep and its impact on health. Mathematical modeling of these data can advanced our understanding of sleep-wake dynamics, identify previously unknown influences on the process, and can be used to generate testable hypotheses. Ultimately, by combining the power of Drosophila genetics with mathematical modeling, a better understanding of sleep and wake transition dynamics and how they relate to the biological mechanism that underlies sleep and the aging process can be achieved and possibly inform our understanding of human sleep. The proposed research aims to (1) develop an algorithm that can predict long- and short-lived flies and determine whether molecular mechanisms associated with aging correlate with the predicted short- and long-lived flies, (2) apply novel time series algorithms to characterize the evolution of sleep transitions over the lifetime of a fly, and (3) use a physiological model to determine critical variables and determine links between sleep structure and aging outcomes in Drosophila. Our preliminary data indicate that features derived from sleep architecture in flies over their entire lifespan and are significantly associated with survival time. A significant correlation between sleep architecture and lifespan persists even when data is limited to the first 30 days of a fly's lifespan. Moreover, when data is limited to only the first 30 days of data, there is a significant correlation between sleep architecture and lifespan. We will determine whether flies predicted to be short- or long-lived have differences in markers of aging and whether inducing sleep in these flies helps ameliorate these changes.
The second aim focuses on describing an equivalent of Process S in the fly by searching for cyclical behavior associated sleep-wake patterns in circadian rhythm mutant flies. These models have the potential to provide valuable insight into the molecular mechanisms that govern sleep.
The third aim will employ the physiologically motivated model to ?reverse engineer? sleep parameter estimates in individual flies that can be correlated with health and biochemical changes associated with aging. These estimates will be valuable in gaining an insight into the mechanism that governs the build-up and dissipation of sleep debt and other sleep mechanisms in Drosophila, where standard model building techniques used in mammalian species are not practical. Results from all three aims will provide a better toolkit to address the molecular link between observed sleep parameters and health outcomes.
Increased sleep fragmentation and insufficient sleep are associated with adverse health and cognitive outcomes in humans and the reasons for this are unclear. This work will develop sophisticated statistical models to characterize Drosophila sleep and correlate changes in sleep features with lifespan and molecular marker of aging. This work will shed light on the genetic and molecular links between inadequate sleep and adverse consequences that can be applied to our knowledge of the importance of human sleep.