Biology subjects

Lira, M.

Publications and source records attributed to Lira, M..

3 recordsLinked to original sources

bioRxiv2021

Necroptosis inhibition counteracts axonal degeneration, cognitive decline and key hallmarks of aging, promoting brain rejuvenation.

Age is the main risk factor for the development of neurodegenerative diseases. In the aged brain, axonal degeneration is an early pathological event, preceding neuronal dysfunction, and cognitive disabilities in humans, primates, rodents, and invertebrates. Necroptosis mediates degeneration of injured axons, but whether necroptosis triggers neurodegeneration and cognitive impairment along aging is unknown. Here we show that the loss of the necroptotic effector Mlkl was sufficient to delay age-associated axonal degeneration and neuroinflammation, protecting against decreased synaptic transmission and memory decline in aged mice. Moreover, short-term pharmacologic inhibition of necroptosis in aged mice reverted structural and functional hippocampal impairment, both at the electrophysiological and behavioral level. Finally, a quantitative proteomic analysis revealed that necroptosis inhibition leads to an overall improvement of the aged hippocampal proteome, including a subclass of molecular biofunctions associated with brain rejuvenation, such as long-term potentiation and synaptic plasticity. Our results demonstrate that necroptosis contributes to the age-dependent brain degeneration, disturbing hippocampal neuronal connectivity, and cognitive function. Therefore, necroptosis inhibition constitutes a potential geroprotective strategy to treat age-related disabilities associated with memory impairment and cognitive decline.

neuroscience↗

bioRxiv2020

Additive and non-additive epigenetic signatures of hybridisation between fish species with different mating systems

Hybridisation is a major source of evolutionary innovation. However, several prezygotic and postzygotic factors influence its likelihood and evolutionary outcomes. Differences in mating systems can have a major effect on the extent and direction of hybridisation and introgression. In plants, epigenetic mechanisms help to stabilize hybrid genomes and contribute to reproductive isolation, but the relationship between genetic and epigenetic changes in animal hybrids is unclear. We analysed the extent of a unique case of natural hybridisation between two genetically distant mangrove killifish species with different mating systems, Kryptolebias hermaphroditus (self-fertilising) and K. ocellatus (outcrossing), and the methylation patterns of their hybrids. Hybridisation rate between the species ranged between 14% and 26%. Although co-existing parental species displayed highly distinct genetic (microsatellites and SNPs) and methylation patterns (37,000 differentially methylated cytosines), our results indicate that F1 hybrids are viable and able to backcross with parental species. Hybrids had predominantly intermediate methylation patterns (88.5% of the sites) suggesting additive effects, as expected from hybridisation between genetically distant species. Differentially methylated cytosines between hybrids and both parental species (5,800) suggest that introgressive hybridisation may play a role in generating novel genetic and epigenetic variation which could lead to species diversification. We also found a small percentage of non-additive epigenetic effects which might act as an evolutionary bet-hedging strategy and increase fitness under environmental change.

evolutionary biology↗

bioRxiv2017

TNER: A Novel Bayesian Background Error Suppression Method for Mutation Detection in Circulating Tumor DNA

The use of ultra-deep, next generation sequencing of circulating tumor DNA (ctDNA) holds great promise for early detection of cancer as well as a tool for monitoring disease progression and therapeutic responses. However, the low abundance of ctDNA in the bloodstream coupled with technical errors introduced during library construction and sequencing complicates mutation detection. To achieve high accuracy of variant calling via better distinguishing low frequency ctDNA mutations from background errors, we introduce TNER (Tri-Nucleotide Error Reducer), a novel background error suppression method that provides a robust estimation of background noise to reduce sequencing errors. It significantly enhances the specificity for downstream ctDNA mutation detection without sacrificing sensitivity. Results on both simulated and real healthy subjects data demonstrate that the proposed algorithm consistently outperforms a current, state of the art, position-specific error polishing model, particularly when the sample size of healthy subjects is small. TNER is publicly available at https://github.com/ctDNA/TNER.

bioinformatics↗