Masters Theses

Keywords and Phrases

Lifespan; Modeling; Sleep


”Adequate sleep is associated with an individual’s health. Too little sleep is associated with many health problems, including cardiovascular disease, obesity, and a general increase in all-cause mortality. Yet the molecular changes that link poor sleep and changes in health are still not well understood. Individuals have a unique daily need for sleep, and deviations from the animal’s regular sleeping patterns can be indicative of, or result in, underlying changes in its health. Therefore, we hypothesize that changes in the sleep architecture in Drosophila melanogaster reflect changes in the fly’s health.

We determined sleep architecture in wild-type male flies over their entire lifespan. We converted activity into sleep and wake-bout parameters and determined the best multiple linear regression model that described lifespan. Variables describing sleep stability can predict the actual lifespan with an adjusted R2 of 0.42. We then re-calculated the model using sleep data to predict lifespan by approximately midlife. The animals were separated into cohorts consisting of short-lived and long-lived flies, giving us the opportunity to study their underlying molecular differences.

Short-lived flies have significantly increased Amylase mRNA expression in the heads, a biomarker for sleepiness. Moreover, long-lived flies had significantly increased levels of the endogenous antioxidant glutathione (GSH) in their bodies when compared to their short-lived counterparts. There were increased levels of polyubiquitinated proteins in our short-lived samples, which is often observed in older animals. Our results indicate that sleep architecture can be used to separate biological aging in flies in a non-invasive manner to study the molecular changes that occur with an individual’s sleep patterns”--Abstract, page iii.


Thimgan, Matthew S.

Committee Member(s)

Olbricht, Gayla R.
Hou, Chen


Biological Sciences

Degree Name

M.S. in Applied and Environmental Biology


The author would like to thank NIH for funding this project.


Missouri University of Science and Technology

Publication Date

Spring 2019


viii, 48 pages

Note about bibliography

Includes bibliographic references (pages 40-44).


© 2019 Joshua Randall Lisse, All rights reserved.

Document Type

Thesis - Open Access

File Type




Thesis Number

T 12033

Electronic OCLC #