Biology subjects

Riquier, S.

Publications and source records attributed to Riquier, S..

3 recordsLinked to original sources

bioRxiv2025

Defying expectations: sex-biased telomere dynamics and extended lifespan in the tropical bat species, Molossus molossus.

Telomeres are key biomarkers of cellular ageing, yet their dynamics remain poorly studied in tropical and short-lived bat species. Here, we present the first investigation of telomere length across age in Molossus molossus, a tropical bat historically categorised as the shortest-lived bat on record. Through a multi-year mark-recapture study in Gamboa, Panama, we sampled 492 individuals (n = 317 females, 175 males) and documented a female M. molossus surviving to at least 13 years of age, more than doubling the previously reported maximum lifespan of 5.6 years. Across the population, relative telomere length (rTL) showed no overall significant decline with age. No evidence was found for sex-specific rates of telomere attrition. Rather these results suggest that males and females follow parallel age-related telomere trajectories, with any sex differences primarily reflecting differences in mean telomere length rather than ageing dynamics. Overall, the findings here challenge previous assumptions about the lifespan and ageing biology of M. molossus. They demonstrate that telomere maintenance is not limited to temperate bats, show that sex differences in telomere biology are subtle and species-specific, and reinforce the value of long-term field studies for understanding ageing processes in the wild.

molecular biology↗

bioRxiv2024

Limited Cell-Autonomous Anticancer Mechanisms in Long-Lived Bats

Bats are remarkably long-lived for their size with many species living more than 20-40 years, suggesting that they possess efficient anti-aging and anti-cancer defenses. Here we investigated requirements for malignant transformation in primary bat fibroblasts in four bat species - little brown bat (Myotis lucifugus), big brown bat (Eptesicus fuscus), cave nectar bat (Eonycteris spelaea) and Jamaican fruit bat (Artibeus jamaicensis) - spanning the bat evolutionary tree and including the longest-lived genera. We show that bat fibroblasts do not undergo replicative senescence and express active telomerase. Bat cells displayed attenuated stress induced premature senescence with a dampened secretory phenotype. Unexpectedly, we discovered that bat cells could be readily transformed by only two oncogenic perturbations or "hits": inactivation of either p53 or pRb and activation of oncogenic RASV12. This was surprising because other long-lived mammalian species require up to five hits for malignant transformation. Additionally, bat fibroblasts exhibited increased p53 and MDM2 transcript levels, and elevated p53-dependent apoptosis. The little brown bat showed a genomic duplication of the p53 gene. We hypothesize that bats evolved enhanced p53 activity through gene duplications and transcriptional upregulation as an additional anti-cancer strategy, similar to elephants. In summary, active telomerase and the small number of oncogenic hits sufficient to malignantly transform bat cells suggest that in vivo bats rely heavily on non-cell autonomous mechanisms of tumor suppression.

cell biology↗

bioRxiv2021

Kmerator Suite: design of specific k-mer signatures andautomatic metadata discovery in large RNA-Seq datasets.

The huge body of publicly available RNA-seq libraries is a treasure of functional information allowing to quantify the expression of known or novel transcripts in tissues. However, transcript quantification commonly relies on alignment methods requiring a lot of computational resources and processing time, which does not scale easily to large datasets. K-mer decomposition constitutes a new way to process RNA-seq data for the identification of transcriptional signatures, as k-mers can be used to quantify accurately gene expression in a less resource-consuming way. We present the Kmerator Suite, a set of three tools designed to extract specific k-mer signatures, quantify these k-mers into RNA-seq datasets and quickly visualize large datasets characteristics. The core tool, Kmerator, produces specific k-mers for 97% of human genes, enabling the measure of gene expression with high accuracy in simulated datasets. KmerExploR, a direct application of Kmerator, uses a set of predictor genes specific k-mers to infer metadata including library protocol, sample features or contaminations from RNA-seq datasets. KmerExploR results are visualised through a user-friendly interface. Moreover, we demonstrate that the Kmerator Suite can be used for advanced queries targeting known or new biomarkers such as mutations, gene fusions or long non coding-RNAs for human health applications.

bioinformatics↗