Periodic Reporting for period 1 - EvolAge (Experimental Evolution of Aging: the genetic link between lifespan, nutrient sensing and fat metabolism)
Reporting period: 2017-01-01 to 2018-12-31
Both diet and reproduction have a major impact on aging in a wide range of animal species, including humans, but how exactly these factors are linked to each other is still largely unknown. Recent studies suggested that the link between diet, reproduction and aging is controlled by genes related to fat metabolism and nutrient sensing. Indeed, lipids are an important source of energy storage required for growth, reproduction and survival. Most of the knowledge on the genetic link between lifespan, nutrient sensing and fat metabolism has been obtained through studies using transgenes or mutants, but studies on experimentally evolved lines of fruit flies also support this idea: selection for a longer lifespan is often correlated with an increased starvation resistance and a higher fat content. The natural genetic variants responsible for aging and correlated responses in fat metabolism are still unknown, however. By studying populations of fruit flies (Drosophila melanogaster) that evolved an extended lifespan, we aimed to (1) identify natural genetic variants involved in the evolution of longevity, (2) to study the link between lifespan and fat metabolism in the evolved populations, and (3) to confirm candidate genes involved in lifespan and/or metabolism by functional testing.
In this project, we have studied a unique set of 24 experimentally evolved (EE) populations of fruit flies that adapted their lifespan in response to selection on postponed reproduction and/or adaptation to a poor larval diet. We have analysed the genomes of these populations to identify loci that diverged in response to one or both selective regimes. Overall, our analyses did not indicate an overrepresentation of candidate genes involved in lipid metabolism or nutrient sensing, or other known "aging" genes. This suggests that naturally occurring variants involved in longevity evolution are distinct from variants identified through classical mutant screens. However, there was a significant overlap of our candidates with those identified in other independent longevity EE studies, which may indicate the presence of preferred targets of selection for the evolution of lifespan. In parallel, we have characterized fat metabolism of the EE lines, by measuring fat content and starvation resistance. These experiments indicated a strong effect of age on both fat content and starvation resistance, but only modest differentiation in response to the two selective regimes. This finding supports the results of our genomic analyses, and again suggests a limited role for nutrient sensing or metabolic pathways in the evolution of lifespan in these EE lines. We then performed in-depth functional genetic tests on two of our candidate genes, and SNPs therein: the LAMMER protein kinase Doa and the nuclear hormone receptor Eip75B. By doing RNAi and association experiments, we confirmed that both genes play a role in lifespan, as well as reproduction, and we identified the most likely candidate SNP responsible for this effect. These findings provide novel insights into how aging evolves in concert with other life history phenotypes.
As part of this project, a review on the effects of dietary amino acids on lifespan and reproduction was published in Current Opinion in Insect Science. The results have been presented at five international conferences and at ten seminars.
As part of this project, a review on the effects of dietary amino acids on lifespan and reproduction was published in Current Opinion in Insect Science. The results have been presented at five international conferences and at ten seminars.
It has become increasingly clear that naturally occurring variants involved in longevity evolution are distinct from "aging" or "metabolic" genes identified through classical mutant screens. Our approach has provided a powerful method for discovering and confirming novel loci involved in the evolution of lifespan and life history. This information may contribute the first stepping-stones to identifying new biomarkers for aging or targets for drug treatment.