An Optimized Competitive-Aging Method Reveals Gene-Drug Interactions Underlying the Chronological Lifespan of Saccharomyces cerevisiae

• Published in: Frontiers in genetics Vol. 11; p. 468
• Main Authors: Avelar-Rivas, J Abraham, Munguía-Figueroa, Michelle, Juárez-Reyes, Alejandro, Garay, Erika, Campos, Sergio E, Shoresh, Noam, DeLuna, Alexander
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 14.05.2020
• Subjects: gene-drug interactions; genetic analysis; Genetics; high-throughput screening; post-mitotic aging; Saccharomyces cerevisiae; gene-drug interactions; genetic analysis; post-mitotic aging; Saccharomyces cerevisiae; high-throughput screening
• ISSN: 1664-8021; 1664-8021
• DOI: 10.3389/fgene.2020.00468

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.