Caractérisation des changements d’expression génétique associés au phénotype Smurf lié à l’âge chez Drosophila melanogaster

Le vieillissement est caractérisé par une diminution de l'efficacité fonctionnelle et un risque accru de décès. Même si la dérégulation de certaines voies et de certains mécanismes a été identifiée, il manque encore une image complète du processus. Les études menées pour comprendre les changements liés au vieillissement sont souvent réalisées au niveau de la population, en supposant que les individus à un moment donné dans une population synchrone sont homogènes. Bien que cette hypothèse simplifie la réalité, elle est souvent utilisée pour des raisons pratiques. En 2012, un phénotype dépendant de l'âge et lié à la mort chez la drosophile a été décrit. En observant une augmentation physiologique de la perméabilité intestinale à un colorant alimentaire bleu, des individus voués à la mort en quelques jours (Smurfs) sont identifié. Les Smurfs sont les seuls dans une population à présenter divers changements liés aux vieillissement et un risque élevé de mort imminente, indépendamment de leur âge. On a donc émis l'hypothèse que “Smurfness’” était un bon indicateur pour suivre l'âge physiologique d'individus individuels. Grâce à l'analyse RNA-Seq sur des mouches Smurfs et non-Smurfs, j'ai démontré que les Smurfs portent une signature transcriptionnelle stéréotypée indépendamment de leur âge, qui recouvre principalement ce qui a été décrit jusqu'à présent comme vieillissement. En étudiant concomitamment les changements liés au temps et ceux liés aux Smurfs dans l'expression des gènes, j'ai identifié des processus affectés par le temps mais pas nécessairement associés à la mort. Enfin, j'ai montré comment de nouveaux gènes de longévité peuvent être identifiés en utilisant ce modèle.Ageing is characterized by a decrease in functional efficiency and an increased risk of death. Even if deregulation in certain pathways and mechanisms have been identified (hallmarks of ageing), a comprehensive picture of the process is still missing. Studies conducted to understand ageing changes are mostly performed at a population level, assuming individuals at a given moment in a synchronous population to be homogenous. Although this assumption simplifies reality, it is often used for practical reasons. Indeed, it is still difficult to have non-invasive biomarkers to follow individual ageing in a research context. In 2012, a new age-dependent and death-related phenotype in Drosophila melanogaster was described. By looking at a physiological increase in the intestinal permeability to a blue food dye, they identified individuals committed to death within a few days (Smurfs). Smurfs are the only ones in a population to exhibit various age-related changes and high risk of impending death, independently of their age. Smurfness has been therefore hypothesized to be a good proxy to follow physiological age of single individuals. Through RNA-Seq on Smurf and age-matched non-Smurf flies of different ages, I demonstrated that Smurfs carry a stereotypical transcriptional signature independently of their age, mostly overlapping with what described so far as ageing. By studying concomitantly time-related changes and Smurf-related changes in gene expression, I also identified processes affected by time but not necessarily associated with the physiological collapse of the organism and death. Finally, I showed how new longevity genes can be identified by using this model

Ageing as a Two-Phase Process: Development of a new Theoretical Framework

International audienceHuman ageing, along with the ageing of conventional model organisms, is frequently depicted as a continuous and progressive decline of biological capabilities. Additionally, it is assumed that the risk of mortality increases exponentially during this process. However, it is pivotal to acknowledge that not all organisms experience ageing identically and that our understanding of the phenomenon is coloured by human-centric views. Ageing is multifaceted and influences a diverse range of species in varying ways. For instance, certain organisms undergo swift declines post-reproduction, while others exhibit almost insubstantial changes throughout their existence. This vast array renders the classification of universally applicable "ageing attributes" a daunting task. It is nonetheless essential to also recognize that not all ageing features are organism-specific. The existence of these common attributes has paved the way for identifying the "hallmarks of ageing". These hallmarks are processes that are intertwined with age, amplified during accelerated ageing, and manipulations of which can potentially modulate or even reverse the ageing process. Yet, a glaring observation is that individuals within a single population age at varying rates.. To address this variation, demographers have coined the term 'frailty'. Concurrently, scientific advancements have ushered in the era of molecular clocks. These innovations enable a distinction between an individual's chronological age (time since birth) and biological age (physiological status and corresponding mortality risk). Rera and colleagues, in 2011, unveiled the "Smurf" phenotype in Drosophila, delineating an age-linked escalation in intestinal permeability that presages imminent mortality. This phenotype not only acts as a predictor of natural death but also identifies individuals exhibiting heightened inflammation, energy-store depletion, and compromised motility, among other age-induced traits. Subsequent studies have revealed the Smurf phenotype's presence in organisms like nematodes, zebrafish, and mice, invariably acting as a death precursor. A compelling study by Zane et al. demonstrated that the transcriptional hallmarks of ageing predominantly impact Smurf individuals, with time primarily influencing transcriptional irregularities. Collectively, these findings have steered our conception of ageing towards a framework where ageing is not a linear and continuous progression. Instead, a lifespan is marked by two distinct, necessary phases, discernible in vivo across diverse organisms, courtesy of the Smurf phenotype. This framework additionally includes a mathematical enunciation of longevity trends based on three experimentally measurable parameters, coupled with an analysis of the transcriptome in flies, contingent on both their chronological and biological ages. Moreover, it facilitates a fresh perspective on the evolution of ageing as a function. In this present article, we aim to delineate and explore the foundational principles of this innovative framework, emphasising its potential to reshape our understanding of ageing, challenge its conventional definitions, and recalibrate our comprehension of its evolutionary trajectory

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

International audienceAgeing is characterised at the molecular level by six transcriptional ‘hallmarks of ageing’, that are commonly described as progressively affected as time passes. By contrast, the ‘Smurf’ assay separates high‐and‐constant‐mortality risk individuals from healthy, zero‐mortality risk individuals, based on increased intestinal permeability. Performing whole body total RNA sequencing, we found that Smurfness distinguishes transcriptional changes associated with chronological age from those associated with biological age. We show that transcriptional heterogeneity increases with chronological age in non‐Smurf individuals preceding the other five hallmarks of ageing that are specifically associated with the Smurf state. Using this approach, we also devise targeted pro‐longevity genetic interventions delaying entry in the Smurf state. We anticipate that increased attention to the evolutionary conserved Smurf phenotype will bring about significant advances in our understanding of the mechanisms of ageing

Transcriptional Characterization of Stage I Epithelial Ovarian Cancer: A Multicentric Study

Stage I epithelial ovarian cancer (EOC) represents about 10% of all EOCs. It is characterized by a complex histopathological and molecular heterogeneity, and it is composed of five main histological subtypes (mucinous, endometrioid, clear cell and high, and low grade serous), which have peculiar genetic, molecular, and clinical characteristics. As it occurs less frequently than advanced-stage EOC, its molecular features have not been thoroughly investigated. In this study, using in silico approaches and gene expression data, on a multicentric cohort composed of 208 snap-frozen tumor biopsies, we explored the subtype-specific molecular alterations that regulate tumor aggressiveness in stage I EOC. We found that single genes rather than pathways are responsible for histotype specificities and that a cAMP-PKA-CREB1 signaling axis seems to play a central role in histotype differentiation. Moreover, our results indicate that immune response seems to be, at least in part, involved in histotype differences, as a higher immune-reactive behavior of serous and mucinous samples was observed with respect to other histotypes