Affiliations: 1) Center for Research and Interdisciplinarity (CRI), Inserm U1284, Université de Paris, 75006 Paris, France.; 2) Plateforme Protéomique/Spectrométrie de masse, Institut Jacques-Monod, 75013, Paris, France.; 3) Metabolomics platform, Institute Gustave Roussy, 94 805 Villejuif, France; 4) ARTbio bioinformatic analysis platform, Institute of Biology Paris Seine, Sorbonne Université, F-75005, Paris, France.; 5) Sorbonne Université, 75006, Paris, France
Keywords: i. lifespan; k. next-generation sequencing
Ageing is a process affecting a broad range of living organisms. In humans and multiple model organisms, it is characterized by an age-dependent decrease in functional efficiency and increased vulnerability to death. The classical approach for studying ageing involves comparing individuals of different chronological ages. Even if deregulation in certain pathways and mechanisms have been identified as associated with ageing, the so-called hallmarks of ageing, a comprehensive picture of the process is still missing. We believe that the inability to look at the physiological age of individuals -at the moment of sampling- rather than their chronological age is an important limiting factor in ageing research.
In 2012, Rera and collaborators described a new age-dependent and death-related phenotype in Drosophila melanogaster. By looking at a physiological increase in the intestinal permeability to a blue food dye, they were able to identify individuals committed to death in a few days. Interestingly, these individuals, called “Smurfs”, are the only ones, among a population, to exhibit various age-related changes and high-risk of impending death whatever their chronological age; Smurfness has been therefore hypothesized to be a good proxy to follow physiological age of single individuals.
We are here presenting our work on the characterization of the Smurf transcriptome using D. melanogaster. Through whole-body RNA-sequencing on Smurf and age-matched non-Smurf flies of different chronological ages, we demonstrate that Smurfs carry a stereotypical transcriptional signature independently of their age. Strikingly, this signature mostly overlaps the previously described transcriptional signature of ageing. By studying concomitantly time-related changes and smurf-related changes in gene expression, we were able to identify genes moving through time but not necessarily associated to the physiological collapse of the organism and death. Those results confirm that not only Smurfs are a valid model to look at the physiological age of D.melanogaster, but are a powerful tool for deconvolving the changes related to physiological and chronological time. In conclusion, they highlight the importance of considering smurfness when designing ageing studies.