Biology subjects

Rera, M.

Publications and source records attributed to Rera, M..

10 recordsLinked to original sources

bioRxiv2026

Dynamics of the end-of-life phase explained by the saturating removal model

End of life is characterized by a phase of rapid physiological decline and high morbidity, phenotypically observed as the "Smurf" phase in Drosophila, metabolic end-of-life dysregulation in mice, and end-stage frailty in humans. Existing two-phase aging models often conceptualize this end-of-life phase as a discrete biological state. Here, we demonstrate that a continuous stochastic model of damage accumulation, the saturating removal (SR) model, captures these multi-species morbidity dynamics. By defining the end-of-life phase as a stochastic crossing of a sub-lethal damage threshold, the SR model accurately reproduces empirical end-of-life dynamics across flies, mice, and humans. The model predicts a surprising temporary reduction in hazard shortly after entering the end-of-life phase consistent with empirical data in all three organisms. It also correctly predicts a shortening twilight phenomenon where the mean duration of the end-of-life phase decreases the later its onset. We conclude that end-of-life dynamics are consistent with universal features of a driver of aging crossing a threshold for end-of-life morbidity and then a threshold for death.

systems biology↗

bioRxiv2026

Acute Smurf mortality and inter-phase dependence in Drosophila and mice identified through comprehensive modelling and statistical analysis of two-phase ageing

Ageing is traditionally conceived as a continuous process of progressive physiological decline. However, recent evidence across species suggests that ageing may instead proceed through distinct phases. Using state-of-the-art statistical methods, we develop a rigorous analysis of longitudinal survival data from 1,159 individually tracked female Drosophila melanogaster. This data-driven analysis leads us to introduce a new parametric model of transition rates within the two-phase ageing framework. Flies were monitored using the Smurf assay, which detects increased intestinal permeability through leakage of an ingested blue dye, and is a strong biological marker of ageing. The Smurf phenotype identifies a sharp transition from a non-Smurf state to a Smurf state that precedes death. Our results yield three key findings. First, the Smurf transition rate follows a Gompertz-Makeham law, increasing exponentially with age. Second, contrary to previous constant-rate assumptions, newly transitioned Smurf flies exhibit remarkably high mortality - approximately 40% die within 24 hours - followed by an exponential decline in death rate that stabilises to a lower constant baseline. Third, we identified a mild but statistically significant negative dependence between time spent non-Smurf and subsequent Smurf lifespan. Our best-fit model captures a potential bimodal nature of mortality curves using simple, biologically interpretable functions. Validation using data from two mouse strains confirms the broader applicability of this framework. These results establish a quantitative foundation for the two-phase ageing paradigm and highlight a critical period of vulnerability immediately following the physiological transition to frailty.

systems biology↗

bioRxiv2025

ProteoCast: a web server to predict, validate, and interpret missense variant effects

Understanding how mutations affect protein function remains critical yet challenging, particularly for variants in clinical databases lacking experimental characterisation and for intrinsically disordered regions. Current computational approaches often operate as black boxes, providing predictions without sufficient transparency or quality assessment of the underlying data. Here we present ProteoCast, a user-friendly web server that predicts variant effects through evolutionary constraint analysis and structural context integration. ProteoCast provides a three-tier variant classification (impactful, mild, neutral) to help prioritise mutations for clinical interpretation and experimental validation. It incorporates multiple sequence alignment quality controls to ensure prediction reliability and flag positions with insufficient evolutionary information. Beyond single-variant classification, ProteoCast employs a novel segmentation approach based on mutational sensitivity to identify functional linear peptides in disordered regions. Interactive visualisations guide users through results interpretation, from variant-level predictions to protein-wide functional landscapes. Evaluation on 63,000 ClinVar variants demonstrates 77% sensitivity and 87% specificity for pathogenicity prediction, with performance maintained across species (85% accuracy on Drosophila lethal mutations). ProteoCast successfully identifies twice as many functional motifs in intrinsically disordered regions compared to conservation-based phylogenetic methods. Predictions can be tuned to specific conformations, such as bound forms in protein complexes, for improved accuracy and interpretability. With its transparent, unsupervised methodology and computational efficiency (minutes per protein), ProteoCast democratises access to variant effect prediction and functional site discovery for the broader research community. The web server is freely available at: https://proteocast.ijm.fr/. HighlightsO_LIProteoCast web server democratises variant effect prediction through a fast, transparent platform combining evolutionary analysis and structural context C_LIO_LIThree-tier variant classification enables prioritisation for clinical interpretation and genome editing experiments C_LIO_LINovel mutational sensitivity segmentation approach identifies functional peptides in disordered regions C_LIO_LIInteractive visualisations and input alignment quality controls guide interpretation C_LI

bioinformatics↗

bioRxiv2025

"Smurf Mice": revolutionising our understanding of age-related and end-of-life animal physiology

Living animals reach their end-of-life through a stereotypic set of fascinating but poorly understood processes. The discovery, first in flies and later in nematodes and zebrafish, of the "Smurf phenotype" is a central tool for picking this complex "lock of biology", that one of ageing. Using the Smurfs, we have shown an evolutionarily conserved end-of-life transition across Drosophilids, nematodes and zebrafish. This tool has been key to identify the discontinuous nature of ageing and predict impending death from natural causes as well as from environmental stresses. This phenotype allowed us to discover that ageing is made up of two successive phases : a first phase where individuals are healthy and have no risk of mortality, but show an age-dependent and increasing risk of entering a second phase, characterized by the so-called hallmarks of ageing and a high risk of death. Here, we test whether these two consecutive phases of ageing separated by the Smurf transition are a conserved feature of ageing in the mammals using Mus musculus as a model. We performed a longitudinal longevity study using both males and females from two different mouse genetic backgrounds and by integrating physiological, metabolic and molecular measurements with the life history of approximately 150 mice. We show the existence of a phenotypic signature typical of the last phase of life, observable at any chronological age. Validating the two-phase ageing model in a mammalian organism allows better characterized the high risk of imminent death and would extend its implications to a broader range of species for ageing research.

physiology↗

bioRxiv2025

Proteome-wide prediction of the Functional Impact of Missense Variants with ProteoCast

Dissecting the functional impact of genetic mutations is essential to advancing our understanding of genotype-phenotype relationships and identifying therapeutic targets. Despite progress in sequencing and genome editing technologies, proteome-wide mutation effect prediction remains challenging. Here we show that evolutionary information alone enables accurate prediction of mutation effects across entire proteomes. ProteoCast is a scalable and interpretable computational method that leverages protein sequence conservation to classify genetic variants and identify functionally important protein sites. We apply ProteoCast to the complete Drosophila melanogaster proteome (22,000 isoforms, 300 million mutations) and validate it against nearly 400,000 natural and experimental variants. It correctly classifies 85% of known lethal mutations as functionally impactful versus 13-18% of population variants. ProteoCast-guided genome editing experiments confirm these predictions. Moreover, ProteoCast successfully identifies functionally important protein modification sites and binding motifs. ProteoCast provides a publicly available resource and deployable pipeline for studying gene function and mutations in any organism.

evolutionary biology↗

bioRxiv2022

Alignment-based protein mutational landscape prediction: doing more with less

The wealth of genomic data has boosted the development of computational methods predicting the phenotypic outcomes of missense variants. The most accurate ones exploit multiple sequence alignments, which can be costly to generate. Recent efforts for democratizing protein structure prediction have overcome this bottleneck by leveraging the fast homology search of MMseqs2. Here, we show the usefulness of this strategy for mutational outcome prediction through a large-scale assessment of 1.5M missense variants across 72 protein families. Our study demonstrates the feasibility of producing alignment-based mutational landscape predictions that are both high-quality and compute-efficient for entire proteomes. We provide the community with the whole human proteome mutational landscape and simplified access to our predictive pipeline. Significant statementUnderstanding the implications of DNA alterations, particularly missense variants, on our health is paramount. This study introduces a faster and more efficient approach to predict these effects, harnessing vast genomic data resources. The speed-up is possible by establishing that resource-saving multiple sequence alignments suffice even as input to a method fitting few parameters given the alignment. Our results opens the door to discovering how tiny changes in our genes can impact our health. They provide valuable insights into the genotype-phenotype relationship that could lead to new treatments for genetic diseases.

bioinformatics↗

bioRxiv2022

Drosophilid cuticle pigmentation impacts body temperature

Cuticle pigmentation has been clearly demonstrated to impact body temperature for several relatively large species of insects, but it was questioned for small insects. Here we used a thermal camera to assess the impact of drosophilid cuticle pigmentation on body temperature when individuals are exposed to light. We compared mutants of large effects within species (Drosophila melanogaster ebony and yellow mutants). Then we analyzed the impact of naturally occurring pigmentation variation within species complexes (Drosophila americana/Drosophila novamexicana and Drosophila yakuba/Drosophila santomea). Finally we analyzed lines of D. melanogaster with moderate differences in pigmentation. We found significant differences in temperatures for each of the four pairs we analyzed. The temperature differences appeared to be proportional to the differently pigmented area: between Drosophila melanogaster ebony and yellow mutants or between Drosophila americana and Drosophila novamexicana, for which the whole body is differently pigmented, the difference in temperatures was around 0.6{degrees}C {+/-}0.2{degrees}C. By contrast, between D. yakuba and D. santomea or between Drosophila melanogaster Dark and Pale lines, for which only the posterior abdomen is differentially pigmented, we detected a temperature difference of about 0.14{degrees}C {+/-}0.10{degrees}C. This demonstrates that cuticle pigmentation has ecological implications in drosophilids regarding adaptation to environmental temperature.

evolutionary biology↗

bioRxiv2022

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

Ageing 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. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=150 HEIGHT=200 SRC="FIGDIR/small/517330v5_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@37b39org.highwire.dtl.DTLVardef@8ef8f0org.highwire.dtl.DTLVardef@797299org.highwire.dtl.DTLVardef@1529b0d_HPS_FORMAT_FIGEXP M_FIG The two-phase model of ageing allows to study separately the effect of chronological and physiological age. (A) Classic approaches for studying ageing tend to consider it as a black box affecting all individuals progressively from birth to death. Instead, the Smurf phenotype shows that life can be divided into two consecutive phases separated by an abrupt transition. (B) All individuals undergo this transition at a different moment in their life, prior to death. This allows us to switch from population based approaches, comparing bulks of age-matched individuals through time, to individuals-centred approaches relying on direct access to their transition status. (C) Such paradigm shift shows that hallmarks of ageing long thought to progressively change with age are actually mostly affected in a growing proportion of Smurfs, allowing for the identification of the chain of events accompanying ageing and death from natural causes. (D) By studying the behaviour of the ageing transcriptome as a function of chronological age and Smurfness separately, we demonstrate that the progressively changing transcriptional ageing signature, as described in Frenk & Houseley (2018), is in fact the convolution changes accompanying chronological age signature (increased transcriptional noise) and changes associated with Smurfness (or biological age) signature (increased stress response and inflammation, decreased expression of ribosomal and mitochondrial genes). We also identified a hallmark partially associated with only old Smurfs (ATH5), suggesting that chronological age can affect, late in life, the Smurf response. C_FIG

systems biology↗

bioRxiv2022

TRANSCRIPTOMIC SIGNATURES OF TELOMERASE-DEPENDENT AND -INDEPENDENT AGEING, IN THE ZEBRAFISH GUT AND BRAIN

Decreased telomerase expression, telomere shortening, senescence-associated markers and inflammation have all been independently observed in the ageing brain and associated with disease. However, causality between limited telomerase expression and brain senescence and neuro-inflammation in the natural ageing setting is yet to be established. Here, we address these questions using the zebrafish as an ageing model which. Akin to humans, zebrafish display premature ageing and death in the absence of telomerase and where telomere shortening is a driver of cellular senescence. Our work shows for the first time that telomerase deficiency (tert-/-) accelerates key hallmarks of ageing identified in the Wild Type (WT) zebrafish brain at transcriptional, cellular, tissue and functional levels. We show that telomerase depletion accelerates ageing-associated transcriptomic changes associated with dysregulation of stress response and immune genes. These are accompanied by accelerated in situ accumulation of senescence-associated markers and inflammation in the aged brain. Importantly, In vivo, these changes correlate with increased blood-brain barrier permeability and increased anxiety-like behaviour. Of note, the acceleration of senescence-associated markers in the absence of tert occurs not only in the expected proliferative areas but also in non-proliferative ones, where it is unlikely due to telomere-dependent replicative exhaustion, suggesting that non-canonical roles of telomerase may be involved. Together, our work suggests that telomerase has a protective role in the zebrafish brain against the accumulation of senescence and neuro-inflammation and is required for blood-brain barrier integrity. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=88 SRC="FIGDIR/small/493215v4_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@12d3171org.highwire.dtl.DTLVardef@8f45eorg.highwire.dtl.DTLVardef@1e37580org.highwire.dtl.DTLVardef@372777_HPS_FORMAT_FIGEXP M_FIG Graphical Abstract Telomerase depletion accelerates markers of ageing in the zebrafish brain, ranging from dysregulated immune and stress ageing transcriptomic hallmarks to in situ accumulation of senescence-associated markers and inflammation, dysfunction of the blood-brain barrier and increased anxiety behaviour. C_FIG

genomics↗

bioRxiv2022

Positive selection of senescence through increased evolvability: ageing is not a by-product of evolution.

Signs of ageing become apparent only late in life, after organismal development is finalized. Ageing, most notably, decreases an individuals fitness. As such, it is most commonly perceived as a non-adaptive force of evolution and considered a by-product of natural selection. Building upon the evolutionarily conserved age-related Smurf phenotype, we propose a simple mathematical life-history trait model in which an organism is characterized by two core abilities: reproduction and homeostasis. Through the simulation of this model, we observe 1) the convergence of fertilitys end with the onset of senescence, 2) the relative success of ageing populations, as compared to non-ageing populations, and 3) the enhanced evolvability (i.e. the generation of genetic variability) of ageing populations. In addition, we formally demonstrate the mathematical convergence observed in 1). We thus theorize that mechanisms that link the timing of fertility and ageing have been selected and fixed over evolutionary history, which, in turn, explains why ageing populations are more evolvable and therefore more successful. Broadly speaking, our work suggests that ageing is an adaptive force of evolution.

evolutionary biology↗