Smurfness-based two-phase model of ageing helps deconvolve the ageing transcriptional signature

Abstract

Ageing is a common feature of living organisms, showing shared molecular features called hallmarks of ageing. Usually they are quantified in groups of individuals as a function of their chronological age (time passed since birth) and display continuous and progressive changes. Such approaches are based on the assumption that individuals taken at a given chronological age are biological replicates. However, even in genetically homogeneous and synchronised populations individuals do die at different chronological ages. This highlights the difference between chronological age and biological age, the latter being defined by the actual mortality risk of the organism, reflecting its physiology. The Smurf assay, previously described by Rera and colleagues, allows the identification of individuals at higher risk of death from natural causes amongst a population of a given chronological age. We found that the categorization of individuals as Smurf or non-Smurf, permits to distinguish transcriptional changes associated with either chronological or biological age. We show that transcriptional heterogeneity increases with chronological age, while four out of the six currently defined transcriptional hallmarks of ageing are associated with the biological age of individuals, i.e. their Smurf state. In conclusion, we demonstrate that studying properties of ageing by applying the Smurf classification allows us to differentiate the effect of time from the effect of a physiological response triggering an end-of-life switch (i.e. Smurf phase). More specifically, we show that the ability to isolate a pre-death phase of life in vivo enables us not only to study late life mechanisms preceding death, but also investigate early physiological changes triggering such phase. This allowed the identification of novel pro-longevity genetic interventions. We anticipate that the use of the evolutionary conserved Smurf phenotype in ageing studies will allow significant advances in our comprehension of the underlying mechanisms of ageing.

Markers and mechanisms of death in Drosophila

“…They found that only 22% of males and 34% of females exhibited Smurf phenotype prior to or at death. Therefore, whereas Rera and coworkers recently stated that their data "unequivocally show that every female Drosophila dies as a Smurf" (Zane et al, 2023), that conclusion is not consistent with the results from multiple other groups. Finally, Regan et al reported that Smurf phenotype is completely absent throughout the life span of males of the wDah strain, and is present only at very low frequencies in males of the w[1118] strain (Regan et al, 2016).…”

“…These early time points are before significant death of the cohort begins, and therefore before any significant expression of the Smurf phenotype is expected to occur. However, certain studies have suggested that increased expression of innate immune response genes with age, including increased expression of the Drosomycin-GFP reporter, is largely due to flies undergoing the Smurf phenotype (Rera et al, 2012;Martins et al, 2018;Zane et al, 2023). Here, fluorescence imaging experiments were conducted to further demonstrate that increased immune reporter expression during aging occurs independent of the Smurf phenotype.…”

A scenario for an evolutionary selection of ageing

“…More importantly, our model suggests a central role of ageing in evolution, as the mathematical constraint we show is likely to apply to any function affecting fertility and homeostasis. Could this broader application of constraints be responsible for the stereotyped gene expression changes - reminiscent of the so-called hallmarks of ageing - we recently described in Smurfs (Zane et al, 2023)? Although this model helps us to see the conditions under which ageing is an evolutionarily adaptive force, it is still a toy model.…”

“…In flies, the Smurf phase is characterized by multiple physiological marks of ageing such as the high risk of impending death, loss of energy stores, systemic inflammation, reduced motility (Rera et al, 2012), and reduced fertility (Rera et al, 2018). More generally, the transcriptional hallmarks (Frenk and Houseley, 2018) usually associated with ageing are mostly observed in the latter phase (Zane et al, 2023). To summarize, this phenotype allows for the identification of two successive and necessary phases of life with all the age-related changes occurring in the last.…”

Ageing as a two-phase process: theoretical framework

“…This phenotype distinguishes a first phase (in which the risk of reaching the point of transition increases with time) from a second phase, where individuals show the long-described properties of ageing. Notably, differentiating between Smurf and non-Smurf individuals within an ageing population allows for the deconvolution of the "ageing transcriptome" into its chronological and biological components (Zane et al, 2023). Thus, our conception of ageing better accounts for biological disposition and heterogeneity of a population.…”