Biology subjects

Cansell, C.

Publications and source records attributed to Cansell, C..

4 recordsLinked to original sources

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

Computational detection, characterization, and clustering of microglial cells in a mouse model of fat-induced postprandial hypothalamic inflammation

Obesity is associated with brain inflammation, glial reactivity, and immune cells infiltration. Studies in rodents have shown that glial reactivity occurs within 24 hour of high-fat diet (HFD) consumption, long before obesity development, and takes place mainly in the hypothalamus (HT), a crucial brain structure for controlling body weight. Understanding more precisely the kinetics of glial activation of two major brain cells (astrocytes and microglia) and their impact on eating behavior could prevent obesity and offer new prospects for therapeutic treatments. To understand the mechanisms pertaining to obesity-related neuroinflammation, we developed a fully automated algorithm, NutriMorph. Although some algorithms were developed in the past decade to detect and segment cells, they are highly specific, not fully automatic, and do not provide the desired morphological analysis. Our algorithm cope with these issues and performs the analysis of cells images (here, microglia of the hypothalamic arcuate nucleus), and the morphological clustering of these cells through statistical analysis and machine learning. Using the k-Means algorithm, it clusters the microglia of the control condition (healthy mice) and the different states of neuroinflammation induced by high-fat diets (obese mice) into subpopulations. This paper is an extension and re-analysis of a first published paper showing that microglial reactivity can already be seen after few hours of high-fat diet (Cansell et al., 2021). Thanks to NutriMorph algorithm, we unravel the presence of different hypothalamic microglial subpopulations (based on morphology) subject to proportion changes in response to already few hours of high-fat diet in mice.

neuroscience↗

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↗

bioRxiv2019

Fat food exacerbates post-prandial hypothalamic inflammation involving GFAP+ cells and microglia

In humans, obesity was associated with brain inflammation and glial cell proliferation. Studies in rodents showed that glial cell proliferation occurs within 24 hours of high-fat diet (HFD) consumption, before obesity development. This proliferation was mainly observed in the hypothalamus (HT), a crucial brain structure for controlling body weight. Therefore, we sought to characterize the post-prandial HT inflammatory response to 1-3-6 hours exposure to a standard diet and HFD. HFD exposure increased gene expression of astrocyte and microglial marker (GFAP and Iba1) compare to standard treated mice and induced morphological modifications of microglial cells in HT. This remodeling was associated with higher expression of inflammatory genes and differential activation of hypothalamic neuropeptides involved in energy balance regulation. DREADD and PLX5622 technologies, used to modulate GFAP-positive or microglial cells activity respectively, showed that both glial cell types are involved in hypothalamic post-prandial inflammation, but in a different time frame and with a diet specificity Thus, an exacerbated post-prandial inflammation in brain might predispose individuals to obesity and needs to be characterized to address this worldwide crisis.

neuroscience↗