Biology subjects

Vignes, M.

Publications and source records attributed to Vignes, M..

6 recordsLinked to original sources

bioRxiv2026

Neurobiological alterations and autism-like phenotype in mice following regulatory-limit exposure to fungicides in drinking water

Neurodevelopmental conditions, including attention deficit hyperactivity disorder (ADHD) and autism spectrum disorders (ASD), have increased markedly over recent decades. This rise parallels the widespread use of agrochemicals, suggesting a contribution of environmental exposures. We hypothesize that pesticide residues may disrupt brain development and promote neurodevelopmental disorders. Here, we test whether concentrations permitted in drinking water affect brain development using a maternal exposure model in wild-type mice. Exposure to a fungicide mixture at 0.3 g/L, below the current European regulatory limit of 0.5 g/L, impairs corticogenesis and is associated with alterations in synaptic function and glutamatergic signaling. Offspring exhibit delays in sensory development, reduced social interactions, and increased stereotyped behaviors. We identify the adenosine A2A receptor as a molecular target of anilinopyrimidine fungicides. Together, these findings indicate that low-dose exposure to this fungicide mixture can induce an autism spectrum-like phenotype in the offspring.

neuroscience↗

bioRxiv2024

Evaluation of protein intake and protein quality in New Zealand vegans

Dietary protein provides indispensable amino acids (IAAs) that the body cannot synthesise. Past assessments of total protein intake from vegan populations in western, developed countries were found to be low but not necessarily below daily requirements. However, plant-sourced proteins generally have lower quantities of digestible IAAs as compared to animal-sourced proteins. Simply accounting for protein intake without considering AA profile and digestibility could overestimate protein adequacy among vegans. This study quantified protein intake and quality, as compared to reference intake values among 193 NZ vegans using a four-day food diary. Protein and IAA composition of all foods were derived from New Zealand FoodFiles and the United States Department of Agriculture and adjusted for True Ileal Digestibility (TID). Mean protein intakes for males and females were 0.99 and 0.81 g/kg /day, respectively with 78.8% of males and 74.5% of females meeting the Estimated Average Requirement for protein. Plant-sourced proteins provided 52.9 mg of leucine and 35.7 mg of lysine per gram of protein and were below the reference scoring patterns (leucine: 59mg/g, lysine: 45mg/g). When adjusted to individual body weight, average IAA intakes were above daily requirements, but lysine just met requirements at 31.2 mg/kg of body weight/day (reference: 30 mg/kg/day). Upon TID adjustment, the percentage of vegans meeting adequacy for protein and IAA decreased and only approximately 50% of the cohort could meet lysine and leucine requirements. Hence, lysine and leucine were the most limiting IAAs in the vegan cohorts diet. Legumes and pulses contributed most to overall protein and lysine intake. An increased proportion of legumes and pulses can potentially increase these intakes but must be considered in the context of the whole diet. AA composition and digestibility are important aspects of protein quality when assessing protein adequacy and is of particular importance in restrictive diets.

physiology↗

bioRxiv2024

Neuroprotection by chronic administration of Fluoroethylnormemantine (FENM) in mouse models of Alzheimer's disease

BackgroundFluoroethylnormemantine (FENM), a new Memantine (MEM) derivative, prevented amyloid-{beta}[25-35] peptide (A{beta}25-35)-induced neurotoxicity in mice, a pharmacological model of Alzheimers disease (AD) with high predictive value for drug discovery. Here, as drug infusion is likely to better reflect drug bioavailability due to the interspecies pharmacokinetics variation, we analyzed the efficacy of FENM after chronic subcutaneous (SC) infusion, in comparison with IP injections in two AD mouse models, A{beta}25-35 -injected mice and the transgenic APP /PSEN1{partial}E9 (APP/PS1) line. MethodsIn A{beta}25-35-treated mice, FENM was infused at 0.03-0.3 mg/kg/day during one week after A{beta}25-35 injection. For comparison, FENM and MEM were administered IP daily at 0.03-0.3 mg/kg. In 10-month-old APP/PS1 mice, FENM was administered during four weeks by daily IP injections at 0.3 mg/kg or chronic SC infusion at 0.1 mg/kg/day. Memory deficits, spatial working memory and recognition memory, were analysed. Markers of neuroinflammation, apoptosis, oxidative stress, and amyloid burden in APP/PS1 mice, were quantified. Markers of synaptic plasticity such as PSD-95 and GluN2A/B/D subunits expression in hippocampus homogenates or synaptosomes were quantified in A{beta}25-35-treated mice and synaptic long-term potentiation (LTP) in hippocampal slices was analysed in APP/PS1 mice. ResultsDeficits in spontaneous alternation and object recognition in A{beta}25-35 mice were prevented by infused FENM at all doses tested. Similar effects were observed with the daily FENM or MEM treatments. Animals infused with 0.1 mg/kg/day FENM showed prevention of A{beta}25-35-induced neuroinflammation, oxidative stress and apoptosis. FENM infusion restored A{beta}25-35-induced alterations in synaptosomal PSD-95, GluN2A and P-GluN2B levels. GluN2D levels were unchanged whatever the treatment. In APP/PS1 mice, FENM infused or administered IP alleviated spontaneous alternation deficits, neuroinflammation, increases in A{beta}1-40/A{beta}1-42 and hippocampal LTP alteration. ConclusionThese data confirmed the neuroprotective potential of FENM in the pharmacological A{beta}25-35 and transgenic APP/PS1 mouse models of AD, with a superiority to MEM, and showed that the drug can be efficiently infused chronically.

pharmacology and toxicology↗

bioRxiv2024

MOTL: enhancing multi-omics matrix factorization with transfer learning

Joint matrix factorization is popular for extracting lower dimensional representations of multi-omics data but loses effectiveness with limited samples. Addressing this limitation, we introduce MOTL (Multi-Omics Transfer Learning), a framework that enhances MOFA (Multi-Omics Factor Analysis) by inferring latent factors for small multi-omics target datasets with respect to those inferred from a large heterogeneous learning dataset. We evaluated MOTL by designing simulated and real data protocols and demonstrated that MOTL improves the factorization of limited-sample multi-omics datasets when compared to factorization without transfer learning. When applied to actual glioblastoma samples, MOTL enhanced delineation of cancer status and subtype.

bioinformatics↗

bioRxiv2023

Visual integration of GWAS and differential expression results with the hidecan R package

SummaryWe present hidecan, an R package for generating visualisations that summarise the results of one or more genome-wide association studies and differential expression analyses, as well as manually curated candidate genes, e.g. extracted from the literature. Availability and ImplementationThe hidecan package is implemented in R and is publicly available on the CRAN repository (https://CRAN.R-project.org/package=hidecan) and on GitHub (https://github.com/PlantandFoodResearch/hidecan). A description of the package, as well as a detailed tutorial are available at https://plantandfoodresearch.github.io/hidecan/. Contactolivia.angelin-bonnet@plantandfood.co.nz. Supplementary informationSupplementary data are available.

genetics↗

bioRxiv2020

A Multi-Objective Genetic Algorithm to Find Active Modules in Multiplex Biological Networks

The identification of subnetworks of interest - or active modules - by integrating biological networks with molecular profiles is a key resource to inform on the processes perturbed in different cellular conditions. We here propose MOGAMUN, a Multi-Objective Genetic Algorithm to identify active modules in multiplex biological networks. MOGAMUN optimizes both the density of interactions and the scores of the nodes (e.g., their differential expression). We compare MOGAMUN with state-of-the-art methods, representative of different algorithms dedicated to the identification of active modules in single networks. MOGAMUN identifies dense and high-scoring modules that are also easier to interpret. In addition, to our knowledge, MOGAMUN is the first method able to use multiplex networks. Multiplex networks are composed of different layers of physical and functional relationships between genes and proteins. Each layer is associated to its own meaning, topology, and biases; the multiplex framework allows exploiting this diversity of biological networks. We applied MOGAMUN to identify cellular processes perturbed in Facio-Scapulo-Humeral muscular Dystrophy, by integrating RNA-seq expression data with a multiplex biological network. We identified different active modules of interest, thereby providing new angles for investigating the pathomechanisms of this disease. AvailabilityMOGAMUN is available at https://github.com/elvanov/MOGAMUN. Contactelva.novoa@inserm.fr, anais.baudot@univ-amu.fr

systems biology↗