bioRxiv · 10.1101/696682
A Competitive-Aging Method for Quantitative Genetic Analysis of the Chronological Lifespan of Saccharomyces cerevisiae
Abstract
The chronological lifespan of budding yeast is a model of aging and age-related diseases. This paradigm has recently allowed genome-wide screening of genetic factors underlying post-mitotic viability in a simple unicellular system, which underscores its potential to provide a comprehensive view of the aging process. However, results from different large-scale studies show little overlap and typically lack quantitative resolution to derive interactions among different aging factors. We previously introduced a sensitive, parallelizable approach to measure the chronological-lifespan effects of gene deletions based on the competitive aging of fluorescence-labeled strains. Here, we present a thorough description of the method, including an improved multiple-regression model to estimate the association between death rates and fluorescent signals, which accounts for possible differences in growth rate and experimental batch effects. We illustrate the experimental procedure--from data acquisition to calculation of relative survivorship--for ten deletion strains with known lifespan phenotypes, which is achieved with high technical replicability. We apply our method to screen for gene-drug interactions in an array of yeast deletion strains, which reveals a functional link between protein glycosylation and lifespan extension by metformin. Competitive-aging screening coupled to multiple-regression modeling provides a powerful, straight-forward way to identify aging factors in yeast and their interactions with pharmacological interventions.
Source connections
Explore related subjects
Keep this discovery
Explore connections, maps & timelines
Avelar-Rivas, J. A., Mungiua-Figueroa, M., Juarez-Reyes, A., Garay, E., Campos, S. E., Shoresh, N., DeLuna, A.. 2019-07-11. A Competitive-Aging Method for Quantitative Genetic Analysis of the Chronological Lifespan of Saccharomyces cerevisiae. https://doi.org/10.1101/696682
Cite the original work for its findings. Save a collection to share your selection of sources.