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Aging Cell. 2016 Feb;15(1):4-13. doi: 10.1111/acel.12424. Epub 2015 Nov 29.

Using measures of single-cell physiology and physiological state to understand organismic aging.

Author information

1
Division of Basic Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
2
Department of Molecular Biology and Biochemistry, Rutgers, The State University of New Jersey, Piscataway, NJ, USA.

Abstract

Genetically identical organisms in homogeneous environments have different lifespans and healthspans. These differences are often attributed to stochastic events, such as mutations and 'epimutations', changes in DNA methylation and chromatin that change gene function and expression. But work in the last 10 years has revealed differences in lifespan- and health-related phenotypes that are not caused by lasting changes in DNA or identified by modifications to DNA or chromatin. This work has demonstrated persistent differences in single-cell and whole-organism physiological states operationally defined by values of reporter gene signals in living cells. While some single-cell states, for example, responses to oxygen deprivation, were defined previously, others, such as a generally heightened ability to make proteins, were, revealed by direct experiment only recently, and are not well understood. Here, we review technical progress that promises to greatly increase the number of these measurable single-cell physiological variables and measureable states. We discuss concepts that facilitate use of single-cell measurements to provide insight into physiological states and state transitions. We assert that researchers will use this information to relate cell level physiological readouts to whole-organism outcomes, to stratify aging populations into groups based on different physiologies, to define biomarkers predictive of outcomes, and to shed light on the molecular processes that bring about different individual physiologies. For these reasons, quantitative study of single-cell physiological variables and state transitions should provide a valuable complement to genetic and molecular explanations of how organisms age.

KEYWORDS:

aging; chance; physiology; quantitative microscopy; reporter genes; single-cell; stochastic

PMID:
26616110
PMCID:
PMC4717262
DOI:
10.1111/acel.12424
[Indexed for MEDLINE]
Free PMC Article

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