Blind cave salamanders age very slowly: A new member of Methuselah's Bestiary

Metabolomic Changes Are Predictive of Aging in Laying Hens

Aging in vertebrates is an extremely complex process that is still poorly understood. One confining factor to studying vertebrate aging is the lack of appropriate models. The laying hen is a good model to study vertebrate aging, as it can be maintained under standard housing conditions, its breeds are genetically well defined and it exhibits significant aging phenotypes at around 18 months of age. Furthermore, laying hens are maintained in a challenging realistic environment and possess a fully functional immune system. Here we used, for the first time, metabolomic profiling of laying hens' blood for identifying biomarkers of aging. Random forest classifier was used to quantify the quality of the markers and found that the markers can predict the correct age group of individuals with 90% accuracy. Animals under time-restricted feeding, a condition known to increase health span, appeared younger under the markers, indicating that the aging biomarkers can also predict the effectiveness of environmental treatments. Additionally, we found that noise, defined as the ratio between the standard deviation and the mean, is an exceptionally robust and universal biomarker of aging, as metabolomic noise increases significantly with age in laying hens, humans, and mice. Our study suggests the laying hen as a useful model to study aging in vertebrates and establishes metabolomic noise as a novel, universal biomarker of aging.

Effects of extrinsic mortality on the evolution of aging: a stochastic modeling approach

The evolutionary theories of aging are useful for gaining insights into the complex mechanisms underlying senescence. Classical theories argue that high levels of extrinsic mortality should select for the evolution of shorter lifespans and earlier peak fertility. Non-classical theories, in contrast, posit that an increase in extrinsic mortality could select for the evolution of longer lifespans. Although numerous studies support the classical paradigm, recent data challenge classical predictions, finding that high extrinsic mortality can select for the evolution of longer lifespans. To further elucidate the role of extrinsic mortality in the evolution of aging, we implemented a stochastic, agent-based, computational model. We used a simulated annealing optimization approach to predict which model parameters predispose populations to evolve longer or shorter lifespans in response to increased levels of predation. We report that longer lifespans evolved in the presence of rising predation if the cost of mating is relatively high and if energy is available in excess. Conversely, we found that dramatically shorter lifespans evolved when mating costs were relatively low and food was relatively scarce. We also analyzed the effects of increased predation on various parameters related to density dependence and energy allocation. Longer and shorter lifespans were accompanied by increased and decreased investments of energy into somatic maintenance, respectively. Similarly, earlier and later maturation ages were accompanied by increased and decreased energetic investments into early fecundity, respectively. Higher predation significantly decreased the total population size, enlarged the shared resource pool, and redistributed energy reserves for mature individuals. These results both corroborate and refine classical predictions, demonstrating a population-level trade-off between longevity and fecundity and identifying conditions that produce both classical and non-classical lifespan effects.