Aging is a complex process affected by genetic, environmental and stochastic factors. How these factors interact is not fully understood. Our long term goal is to define the relationships between genetic pathways, environmental inputs and stochastic factors that contribute to aging, and build models that predict the aging outcomes of individuals based on their genetic markup, past experiences, and readouts from biomarkers.
The aims of this proposed project are to determine how transcriptional noises in environmental responses translate to heterogeneity in lifespan and aging in C. elegans, and to define environmental and genetic factors that contribute to these sources of noise. To achieve these aims, we will develop new automated microscopy systems capable of collecting the data necessary for our analysis. The central hypothesis is that noises in environment-related transcriptional responses can lead to heterogeneity in aging, and through feedback and feed-forward processes, these noises are either buffered or amplified, resulting in variation in the aging process. First we will analyze transcriptional noises in pathways affecting lifespan, dissecting it into components that can be attributed to various sources;we will also determine how each source of noise is affected by food and temperature. Because the genes tested communicate with each other in the nervous system, we will next determine how the communication process affects noise in this signaling network. Finally, we will determine whether noises in gene activity lead to variability in lifespan and other age-related declines. This proposal is innovative for several reasons. First, it combines molecular genetics and engineering to solve a fundamental problem in aging. Second, it provides a new framework to analyze transcriptional noise and feedback mechanisms in multicellular animals in vivo, to uncover how these processes ultimately affect aging in different environments. Lastly, it creates new automated platforms for high-throughput quantitative imaging to accelerate research. Our approach exploits the key advantages of the C. elegans model by integrating analysis of gene expression, signaling, behavior and physiology in the intact animal. This work is significant because it will provide new insights into how transcriptional noise arises in intercellular signaling pathways that affect lifespan, and uncover relationships between genetic pathways, environmental inputs, transcriptional noise and aging.

Public Health Relevance

Aging is an important and active area of research linking genes and environments to the degeneration of functions. It has direct applications to many human diseases such as neurodegeneration and muscle function declination.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Research Project (R01)
Project #
5R01AG035317-03
Application #
8120460
Study Section
Special Emphasis Panel (ZAG1-ZIJ-5 (A1))
Program Officer
Guo, Max
Project Start
2009-09-30
Project End
2013-08-31
Budget Start
2011-09-01
Budget End
2013-08-31
Support Year
3
Fiscal Year
2011
Total Cost
$270,700
Indirect Cost
Name
Georgia Institute of Technology
Department
Engineering (All Types)
Type
Schools of Engineering
DUNS #
097394084
City
Atlanta
State
GA
Country
United States
Zip Code
30332
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Entchev, Eugeni V; Patel, Dhaval S; Zhan, Mei et al. (2015) A gene-expression-based neural code for food abundance that modulates lifespan. Elife 4:e06259
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