Background:

Age-related diseases such as cancer, cardiovascular and neurodegenerative diseases pose a major burden to our quality of life and healthcare systems. However, even if we eradicated all cancers today, life expectancy in developed countries would only increase by three years due to other age-related diseases arising instead. Therefore, it is essential to understand the genetic pathways that modulate lifespan directly. Lifespan is an exceptionally diverse phenotype under selection, yet the underlying evolutionary mechanisms remain elusive. Many principles of cellular lifespan have been uncovered by studying the finite lifespan of the single-celled budding yeast Saccharomyces cerevisiae. Moreover, yeast studies have revealed numerous genetic and chemical interventions that extended lifespan in yeast and showed analogous outcomes in multi-cellular eukaryotes like nematodes, fruit flies, and mammals. These findings indicate the broad conservation of the ancient genetic pathways able to modulate lifespan across different species, which we will systematically map in this project.

Project:

Experimental evolution offers an unbiased approach to select for the fittest among thousands of genotypes competing under intrinsic (genetic) and extrinsic (environmental) conditions. It thereby resembles a biological gradient ascent algorithm on the fitness landscape. Experimental evolution has been utilized to construct genotype-phenotype-fitness (GPF) maps for diverse selection conditions by evolving isogenic barcoded yeast libraries and tracking lineages using barcode sequencing, however, a GPF map for yeast lifespan is missing. Creating a comprehensive GPF map for yeast lifespan will elevate our molecular understanding and ability to predict how different genotypes modulate the lifespan phenotype. To assess the conservation of the identified genetic variants that extended yeast lifespan and variants extending lifespan in nematodes, fruit flies, and mammals documented in the literature, the variants will be introduced into human cell lines mimicking age-related diseases by parallel genome editing. We will sort this collection of human cells carrying different lifespan variants for curative variants using image–enabled cell sorting. Yeast lifespan variants effective against age-related diseases in human cell culture will be tested for their impact on the organismal lifespan of short-lived turquoise killifish. Creating a GPF map for yeast lifespan and assessing its conservation to humans and killifish will provide unprecedented insights into the evolution of lifespan over approximately 1 billion years of eukaryotic evolution, deepen our understanding of lifespan at molecular resolution and potentially reveal therapies against age-related diseases.

This project is supported by a Bridging Excellence Fellowship, awarded to Stefan Bassler. 

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