Quantitative and Molecular Genetic Analyses of Mutations Increasing Drosophila Life Span

Understanding the genetic and environmental factors that affect variation in life span and senescence is of major interest for human health and evolutionary biology. Multiple mechanisms affect longevity, many of which are conserved across species, but the genetic networks underlying each mechanism and cross-talk between networks are unknown. We report the results of a screen for mutations affecting Drosophila life span. One third of the 1,332 homozygous P–element insertion lines assessed had quantitative effects on life span; mutations reducing life span were twice as common as mutations increasing life span. We confirmed 58 mutations with increased longevity, only one of which is in a gene previously associated with life span. The effects of the mutations increasing life span were highly sex-specific, with a trend towards opposite effects in males and females. Mutations in the same gene were associated with both increased and decreased life span, depending on the location and orientation of the P–element insertion, and genetic background. We observed substantial—and sex-specific—epistasis among a sample of ten mutations with increased life span. All mutations increasing life span had at least one deleterious pleiotropic effect on stress resistance or general health, with different patterns of pleiotropy for males and females. Whole-genome transcript profiles of seven of the mutant lines and the wild type revealed 4,488 differentially expressed transcripts, 553 of which were common to four or more of the mutant lines, which include genes previously associated with life span and novel genes implicated by this study. Therefore longevity has a large mutational target size; genes affecting life span have variable allelic effects; alleles affecting life span exhibit antagonistic pleiotropy and form epistatic networks; and sex-specific mutational effects are ubiquitous. Comparison of transcript profiles of long-lived mutations and the control line reveals a transcriptional signature of increased life span

C. elegans maximum velocity correlates with healthspan and is maintained in worms with an insulin receptor mutation

Ageing is marked by physical decline. Caenorhabditis elegans is a valuable model for identifying genetic regulatory mechanisms of ageing and longevity. Here we report a simple method to assess C. elegans' maximum physical ability based on the worms' maximum movement velocity. We show maximum velocity declines with age, correlates well with longevity, accurately reports movement ability and, if measured in mid-adulthood, is predictive of maximal lifespan. Contrary to recent findings, we observe that maximum velocity of worm with mutations in daf-2(e1370) insulin/IGF-1 signalling scales with lifespan. Because of increased odorant receptor expression, daf-2(e1370) mutants prefer food over exploration, causing previous on-food motility assays to underestimate movement ability and, thus, worm health. Finally, a disease-burden analysis of published data reveals that the daf-2(e1370) mutation improves quality of life, and therefore combines lifespan extension with various signs of an increased healthspan

Reliability and variability of sleep and activity as biomarkers of ageing in Drosophila

There are currently no reliable biomarkers of ageing. A biomarker should indicate biological age, that is, the amount of an animal's total lifespan it has lived and, therefore, the amount of time it has remaining. Some potential biomarkers cannot be validated as their measurement involves harm or death of the animal, such that its ultimate lifespan cannot be determined. A non-destructive biomarker would allow us to test molecular markers potentially involved directly in the ageing process, to monitor the effectiveness of therapeutic interventions to delay ageing, and provide a useful measure of general health of the organism. In the model organism Drosophila, various behavioural phenotypes change directionally with age, but we do not know whether they predict lifespan. Here we measure activity and sleep parameters in 64 wild type male flies from two recently wild-caught populations over the course of their natural lives, and determine whether such measures may predict biological age and ultimate lifespan. Indices of sleep fragmentation and circadian rhythm were the best predictors of lifespan, though population differences were evident. However, when used to predict a biological age of 50 % lifespan elapsed our best behavioural measure was slightly less accurate and less precise compared with using chronological age as predictor

Opposed growth factor signals control protein degradation in muscles of Caenorhabditis elegans

In addition to contractile function, muscle provides a metabolic buffer by degrading protein in times of organismal need. Protein is also degraded during adaptive muscle remodeling upon exercise, but extreme degradation in diverse clinical conditions can compromise function(s) and threaten life. Here, we show how two independent signals interact to control protein degradation. In striated muscles of Caenorhabditis elegans, reduction of insulin-like signaling via DAF-2 insulin/IGF receptor or its intramuscular effector PtdIns-3-kinase (PI3K) causes unexpected activation of MAP kinase (MAPK), consequent activation of pre-existing systems for protein degradation, and progressive impairment of mobility. Degradation is prevented by mutations that increase signal downstream of PI3K or by disruption of autocrine signal from fibroblast growth factor (FGF) via the FGF receptor and its effectors in the Ras–MAPK pathway. Thus, the activity of constitutive protein degradation systems in normal muscle is minimized by a balance between directly interacting signaling pathways, implying that physiological, pathological, or therapeutic alteration of this balance may contribute to muscle remodeling or wasting

Lifespan Versus Healthspan

International audienceLifespan is a measure of duration, not of content, and it does not provide the same information as biological markers of ageing. Therefore, one cannot rely on lifespan to infer conclusions about ageing. For example, two centenarians can die in very contrasted physiological states: as bedridden for years or during jogging. Healthspan can be measured in animal models by relying on behaviour, resistance to stress, and so on. Biogerontologists working with animal models tend to privilege the measurement of lifespan rather than that of healthspan when the animal lives for a short time (e.g. Caenorhabditis elegans, Drosophila melanogaster) because measuring lifespan is easy and studying, say, behaviour, is more difficult. Conversely, biogerontologists privilege healthspan when the animal model lives for years (e.g. rodents, non-human primates), because measuring lifespan can be out of reach. In any case, biogerontologists should try to observe both lifespan and indicators of health, whenever it is possible, and not conclude that ageing is delayed when they have simply observed longer lifespans