Aging is a fundamental question in biology, yet its mechanism remains elusive despite decades of research. Using mathematical approaches coupled with laboratory experiments, this study will illustrate the basic principles of cellular aging and shed new light on how dietary restriction extends lifespan. Using a novel mathematical model that demonstrates how aging in yeast cells emerges and what genes and their interactions are involved, the close-connection between cellular aging and the robustness of the gene interactions involved will be examined. Given the lack of adequate methods to evaluate changes in genes and their interactions involved in cellular aging, this novel mathematical approach for data analysis could transform what we know about how cells age. Coupled to this research, the educational component of the project will provide cross-disciplinary training to minority students and cultivate their interests in quantitative biology through integrating research with teaching, a student Chapter for the Society of Industrial and Applied Mathematics, tutorial workshops, and broad dissemination of educational materials. Additionally, a new Systems Biology course will contribute to a new Bioinformatics and Systems Biology minor at Spelman College. Research tutorials will be uploaded to YouTube, open research projects will be uploaded to GitHub, and an open research blog will be developed and maintained. In summary, this project will provide training to minority undergraduates in mathematics, computing, and systems biology at a historically black college for women.

The overarching goal of this project will focus on aging from the perspective of gene networks through an integrated research and teaching approach. Cellular aging will be addressed using the budding yeast, a single-cell organism as a model system. The current knowledge on cellular aging lacks coherence, and a major logical gap exists between molecular pathways of aging and population characteristics of aging. Hundreds of yeast genes are known to influence lifespan, but paradoxically, not a single gene can be claimed as a direct cause of aging. Different and even opposite pathways have been observed when experiments are performed in different ways. Despite the complexity of aging, the lifespan of many species can be extended by dietary restriction. This seemingly complicated picture and the evolutionarily conserved lifespan extension effect of dietary restriction will be addressed by the core idea of the study, that cellular aging is an emergent property of stochastic gene networks. A probabilistic gene network model for cellular aging will be used to illustrate the conserved lifespan extension mechanism of dietary restriction in the model organism of Saccharomyces cerevisiae, and study how the organization and dynamics of the yeast gene networks will influence the aging process. The first objective is to test a hypothesis that dietary restriction extends lifespan by improving reliability of gene interaction through analyzing lifespan data of hundreds of yeast mutants. The second objective is to further develop the theoretical foundation of the network model for cellular aging.

Agency
National Science Foundation (NSF)
Institute
Division of Molecular and Cellular Biosciences (MCB)
Application #
1720215
Program Officer
Anthony Garza
Project Start
Project End
Budget Start
2016-08-01
Budget End
2022-03-31
Support Year
Fiscal Year
2017
Total Cost
$529,308
Indirect Cost
Name
University of Tennessee Chattanooga
Department
Type
DUNS #
City
Chattanooga
State
TN
Country
United States
Zip Code
37403