The crustacean Armadillidium vulgare (Latreille, 1804) (Isopoda: Oniscoidea), a new promising model for the study of cellular senescence

Abstract

Senescence, the decline of physiological parameters with increasing age, is a quasi-ubiquitous phenomenon in the living world. The observed patterns of senescence, however, can markedly differ across species and populations, between sexes, and even among individuals. To identify the drivers of this variation in senescence, experimental approaches are essential and involve the development of tools and new study models. Current knowledge of the senescence process is mostly based on studies on vertebrates and the main information about senescence in invertebrates is mostly limited to model organisms such as Caenorhabditis elegans or Drosophila melanogaster. In this context, we tested whether biomarkers of vertebrate ageing could be used to study senescence in a new invertebrate model: the common woodlouse Armadillidium vulgare (Latreille, 1804). More specifically, we looked for the effect of age in woodlouse on three well-established physiological biomarkers of ageing in vertebrates: immune cells (cell size, density, and viability), β-galactosidase activity, and the gene expression of telomerase reverse transcriptase (TERT), an essential subunit of telomerase protein. We found that the size of immune cells was higher in older individuals, whereas their density and viability decreased, and that the β-galactosidase activity increased with age, whereas the TERT gene expression decreased. These findings demonstrate that woodlouse displays age-related changes in biomarkers of vertebrate senescence, with different patterns depending on gender. The tools used in studies of vertebrate senescence can thus be successfully used in studies of senescence of invertebrates such as the woodlouse. The application of commonly used tools to new biological models offers a promising approach to assess the diversity of senescence patterns across the tree of life.

Immune priming depends on age, sex and Wolbachia in the interaction between Armadillidium vulgare and Salmonella

“…Survival abilities to the second infection decline in old w − females compared to young ones of same priming treatment, but this decline was not observed for w − males: old males survived as well as young males comparing the same priming treatment. In A. vulgare , we know that genders display same changes in phenoloxidase activity and haemocyte concentrations with ageing and are therefore both affected by cellular senescence (Depeux et al., 2020; Sicard et al., 2010). However, Depeux et al.…”

“…However, Depeux et al. (2020) showed that females have higher β‐galactosidase activity and lower immune cell viability than males, suggesting that females are physiologically more senescent than males of the same age. The “accelerated” senescence of females could be the consequence of a reproductive evolutionary cost, females allocating more physiological resources in reproduction through ageing than males (Bonduriansky et al., 2008; Lawniczak et al., 2007; Sheldon & Verhulst, 1996; Thiel, 2003; Vinogradov, 1998).…”

“…Terrestrial isopods are appropriate organisms to investigate this question. Compared to dipterian models, these crustaceans have a long lifespan (natural populations display 13% of two‐year‐old individuals; Pitelka & Paris, 1962; Warburg et al., 1984), especially suitable for ageing effects’ study (Depeux et al., 2020; Pitelka & Paris, 1962). Age and gender induce variations in their immune parameters (Depeux et al., 2020; Pigeault et al., 2014; Sicard et al., 2010) and several species harbour the maternally transmitted endosymbiont Wolbachia (Bouchon et al., 1998; Cordaux et al., 2012).…”

Deleterious effects of thermal and water stresses on life history and physiology: a case study on woodlouse

“…for the groups CT, HT, CM, and LM) for measuring the level of our set of physiological traits (i.e. immune cells parameters and β-galactosidase activity) developed in Depeux et al (2020a).…”

“…For survival data, the effect size was the hazard ratio, calculated as the exponential of the regression parameter (Collett 2003). When the selected model did not include the effect of the stress, we took the model with the variable stress as fixed factor to obtain a size effect as made in Depeux et al 2020a. All statistical analyses and representations of results were performed using the software R 4.2.1 (R core Team 2022).…”