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Systems and methods for molecular dissection of socio-environmental effects on aging

社会环境对衰老影响的分子剖析系统和方法

基本信息

批准号：
10686251
负责人：
SCOTT PLETCHER
金额：
$ 30.53万
依托单位：
UNIVERSITY OF MICHIGAN AT ANN ARBOR
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-09-01 至 2024-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10686251
关键词：
Acute Affect Afferent Neurons Age Aging Animal Behavior Animals Assessment tool Behavior Behavior Control Behavior monitoring Behavioral Biogenic Amines Biological Biological Markers Biological Models Cognitive aging Collaborations Computer software Coupled Data Analyses Diet Dissection Drosophila genus Drosophila melanogaster Ensure Environment Environmental Exposure Environmental Risk Factor Exhibits Exposure to Fatty acid glycerol esters Food Foundations Frequencies Future Gene Expression Genes Genetic Goals Health Human Individual Influentials Intervention Investigation Knowledge Laboratories Learning Life Light Link Long-Term Effects Longevity Longitudinal Studies Measurement Measures Mediating Methods Molecular Motivation Movement Neurologic Neurons Neuropeptides Nutrient Organism Pathway interactions Pattern Phase Physiological Research Resistance Rewards Scientist Series Shapes Social Behavior Social Conditions Social Environment Social Interaction Stress Structure System Technology Temperature Testing Time Uncertainty Work adverse outcome age related design dietary restriction experience feeding fly genetic manipulation healthy aging high dimensionality innovation invention lipid metabolism metabolome metabolomics middle age mortality multidimensional data neural circuit neurotransmission new technology resilience response sex sleep pattern social social factors technology validation tool treatment group

项目摘要

Project Summary Despite extensive research on the relationship between early-life social and physical environmental exposures, and consequent effects on aging, little is understood about the mechanisms that link social interactions and aging. The work proposed here provides technological, conceptual, and analytical innovations to fill this gap. The R61 phase of our proposal will build on our existing technologies, which precisely measure how groups of the fruit fly, Drosophila melanogaster, interact with each other as well as with their surroundings, to accommodate long-term, longitudinal studies of aging individuals. Key components of our system will include: (i) our DTrack video tracking system, which provides detailed and near-continuous quantification of changes in movement, exploration, and social interactions, and (ii) our FLIC system, which measures each fly’s interactions with food every 50ms and allows us to analyze the fine structure of feeding activities in real time. These behavioral monitoring systems will interface with external Smart control modules that provide programmable open- and closed-loop control of environmental variables, such as temperature and light, and that will be coupled to genetic systems for acute manipulation of gene expression and neuron activity in response to specific behaviors. During the R61 phase, we will also develop experimental and statistical tools to analyze high-dimensional -omic profiles, which will be used to identify molecular mechanisms that shape and are shaped by social interactions and aging. A series of Goals and Milestones will ensure that this new technology supports the requirements for long term husbandry and that it is robust, reliable, and effective for detecting reasonable differences in behavioral profiles among individuals and groups of individuals. The R33 component of our proposal will use these tools to provide the first detailed characterization of age-dependent socio-environment interactions in an influential model system for aging research, and we will evaluate their association with mechanisms of slowed aging. Importantly, our research will also begin dissecting the mechanisms underlying how aging modulates social interactions and how these interactions modulate aging. We will accomplish this by exploiting our ability to dynamically stimulate and inhibit individual neurons in live, behaving animals to identify the molecular mechanisms through which behavioral interactions influence lifespan and to evaluate behavioral and molecular interventions that reverse the deleterious consequences of adverse social conditions. Measures of resilience in metabolome profiles will enable us to link relationships between social interactions and aging to specific functional cellular pathways. The technology and experimental paradigms that we develop will push the limits of behavioral monitoring and analysis in any organism, will offer the first glimpses of mechanisms through which behavioral interactions influence aging in Drosophila, and will provide a foundation for future investigation in other species, including humans.

项目总结