Deep Learning of Cellular Metabolic Flux Distributions Predicts Lifespan.

ABSTRACT: It is a common observation that individuals within a species age at different rates. Variation in both genetics and environmental interaction are generally thought responsible. Surprisingly, even genetically identical organisms cultured under environmentally homogeneous conditions age at different rates, implying a more fundamental cause of aging. Here we have examined the basis for lifespan variance in haploid, single-celled yeast of Saccharomyces cerevisiae. The probabilistic nature of metabolism means metabolites often, but not always, follow the same route through the metabolic network. We speculate redundancy in metabolic pathway choice is sufficient to explain lifespan variance. To interrogate the reaction flux space of S. cerevisiae we used a model of its intermediary

SUBMITTER: Hilsabeck TAU 

PROVIDER: S-EPMC11623549 | biostudies-literature | 2025 May

REPOSITORIES: biostudies-literature