Emergent properties of signaling network degradation that mediate homeostatic failure during aging
Emergent properties of signaling network degradation that mediate homeostatic failure during aging
批准号:
9927555
负责人:
MATT KAEBERLEIN
金额:
$54.89万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-08-01 至 2022-05-31
关键词:
AgeAgingBiological AssayCatalogsCell physiologyCellsCellular StressComputer ModelsData SetDependenceDiseaseEngineeringEnvironmentEventExposure toFailureGene DeletionGoalsHealthHomeostasisHumanIndividualKnowledgeLibrariesLongevityMapsMass Spectrum AnalysisMeasurementMeasuresMediatingMicrofluidicsModelingMolecularOrganismPenetrancePerformancePhosphorylationPhosphorylation SitePhosphotransferasesPopulationPrevalenceProcessPropertyProtein KinaseProteinsProteomicsReporterResearchResolutionSaccharomycetalesSeriesSignal PathwaySignal TransductionStressStructureSystemSystems BiologyTimeVertebral columnWorkYeastsacute stressage relatedagedbasebiological systemsdesignenvironmental changeexperienceexperimental studyfrailtyfunctional declinegenetic manipulationhealthspanimproved functioninginsightmicrofluidic technologymiddle agemortality riskmutantnetwork modelsphosphoproteomicspredictive testsingle cell proteins
中文摘要
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英文摘要
PROJECT SUMMARY
Loss of homeostatic capacity is a fundamental and defining property of aged organisms from yeast to humans.
The global protein kinase-substrate network forms an essential backbone of the homeostatic signaling network
(HSN) that allows cells to respond appropriately to a dynamic environment and cellular needs. We propose
that aging can be modeled as a series of changes to the HSN that directly impinge on core cellular functions.
The overarching goal of this proposal is to model the HSN in yeast, and to understand the mechanisms by
which degradation of the HSN results in functional declines and increasing risk of mortality with age. To
accomplish this goal we will use a combination of global and targeted mass spectrometry approaches to map
at high resolution the kinases and substrates that comprise the HSN. We will then expose aging yeast to
perturbations, and measure changes in signaling using phosphoproteomics. Finally, we will combine these
population level analyses with single-cell microfluidics measurements in order to define the penetrance and
temporal dynamics of key components of the network (kinases and substrates) and reporters of cellular
functions that are most prone to degradation throughout aging. This approach will allow us to determine, for
the first time, the extent to which individual cells experience distinct aging trajectories. We will use this
information to develop models for network degradation with age and to predict key components of the network
prone to failure, which could potentially be strengthened to build a more robust network. We will test these
predicted improvements by engineering them within yeast strains and assessing whether the strains indeed
maintain important network structures with age, keep cellular functions of their youthful state, and, perhaps,
live longer.
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