The Temporal Scaling of Caenorhabditis Elegans Ageing
Authors
Affiliations
The process of ageing makes death increasingly likely, involving a random aspect that produces a wide distribution of lifespan even in homogeneous populations. The study of this stochastic behaviour may link molecular mechanisms to the ageing process that determines lifespan. Here, by collecting high-precision mortality statistics from large populations, we observe that interventions as diverse as changes in diet, temperature, exposure to oxidative stress, and disruption of genes including the heat shock factor hsf-1, the hypoxia-inducible factor hif-1, and the insulin/IGF-1 pathway components daf-2, age-1, and daf-16 all alter lifespan distributions by an apparent stretching or shrinking of time. To produce such temporal scaling, each intervention must alter to the same extent throughout adult life all physiological determinants of the risk of death. Organismic ageing in Caenorhabditis elegans therefore appears to involve aspects of physiology that respond in concert to a diverse set of interventions. In this way, temporal scaling identifies a novel state variable, r(t), that governs the risk of death and whose average decay dynamics involves a single effective rate constant of ageing, kr. Interventions that produce temporal scaling influence lifespan exclusively by altering kr. Such interventions, when applied transiently even in early adulthood, temporarily alter kr with an attendant transient increase or decrease in the rate of change in r and a permanent effect on remaining lifespan. The existence of an organismal ageing dynamics that is invariant across genetic and environmental contexts provides the basis for a new, quantitative framework for evaluating the manner and extent to which specific molecular processes contribute to the aspect of ageing that determines lifespan.
Demographics of co-ageing complex systems: from infected worms to chess games.
Eskin C, Vural D R Soc Open Sci. 2024; 11(11):240932.
PMID: 39539505 PMC: 11557240. DOI: 10.1098/rsos.240932.
The Power of a Complex Systems Perspective to Elucidate Aging.
Cohen A, Olde Rikkert M J Gerontol A Biol Sci Med Sci. 2024; 79(10).
PMID: 39352172 PMC: 11443544. DOI: 10.1093/gerona/glae210.
Transcriptional drift in aging cells: A global decontroller.
Matsuzaki T, Weistuch C, de Graff A, Dill K, Balazsi G Proc Natl Acad Sci U S A. 2024; 121(30):e2401830121.
PMID: 39012826 PMC: 11287169. DOI: 10.1073/pnas.2401830121.
The egg-counter: a novel microfluidic platform for characterization of egg-laying.
Banse S, Jarrett C, Robinson K, Blue B, Shaw E, Phillips P Lab Chip. 2024; 24(11):2975-2986.
PMID: 38738514 PMC: 11131562. DOI: 10.1039/d3lc01073b.
Exploring Patterns of Human Mortality and Aging: A Reliability Theory Viewpoint.
Gavrilov L, Gavrilova N Biochemistry (Mosc). 2024; 89(2):341-355.
PMID: 38622100 PMC: 11090256. DOI: 10.1134/S0006297924020123.