Biology subjects

Legrand, C.

Publications and source records attributed to Legrand, C..

6 recordsLinked to original sources

bioRxiv2026

Forest edge effects on termites in a neotropical rainforest

Termites are dominant arthropods in tropical forests, where they play a major role in organic matter decomposition. However, their activity may be reduced by habitat degradation, to which soil-dwelling species are especially sensitive. Nowadays, one of the major threats affecting tropical forests is fragmentation, through two concurring effects: a reduction in area of the forested zones, and an increase in the length of forest edges. These effects are hard to disentangle. In this study, we took advantage of a powerline clearing to evaluate edge effects on the termite fauna of an otherwise continuous rainforest in French Guiana. No edge effect was detected 100--300 m into the interior. Soil feeders were not significantly less present at the forest edge although they have an allegedly thinner skeleton and a need for moist and soft soil. Finally, no increase in beta diversity near the edge was found either. Overall, it seems that termites are resilient insects against forest edges as long as the fragment size stays large enough. However, a 3-fold larger presence of an opportunistic and pest species (Heterotermes tenuis) was found at the forest edge. We hypothesize that H. tenuis good adaptability and dispersibility may have allowed it to quickly colonize and dominate this new environment before more cryptic species, as it has been shown for ants.

ecology↗

bioRxiv2023

Orthogonal outlier detection and dimension estimation for improved MDS embedding of biological datasets

Conventional dimensionality reduction methods like Multidimensional Scaling (MDS) are sensitive to the presence of orthogonal outliers, leading to significant defects in the embedding. We introduce a robust MDS method, called DeCOr-MDS (Detection and Correction of Orthogonal outliers using MDS), based on the geometry and statistics of simplices formed by data points, that allows to detect orthogonal outliers and subsequently reduce dimensionality. We validate our methods using synthetic datasets, and further show how it can be applied to a variety of large real biological datasets, including cancer image cell data and human microbiome project data.

bioinformatics↗

bioRxiv2021

Time-resolved, integrated analysis of clonal genome evolution in parthenogenetic animals and in cancer

Clonal genome evolution is a key aspect for parthenogenetic species and cancer. While many studies describe precise landscapes of clonal evolution in cancer, few determine the underlying evolutionary parameters from molecular data, and even fewer integrate theory with data. We derived theoretical results linking mutation rate, time, expansion dynamics, and clinical parameters. We then inferred time-resolved estimates of evolutionary parameters from mutation accumulation, mutational signatures and selection. Using this framework, we traced the speciation of the clonally evolving marbled crayfish population to a time window between 1986 and 1990, which is consistent with biological records. We also used our framework to analyze a published dataset of glioblastoma samples, which identified tumor expansion patterns, cell survival at resection, and selective forces as important factors for tumor development. In conclusion, our framework allowed a time-resolved, integrated analysis of key parameters in clonally evolving genomes, and provided novel insights into the evolutionary age of marbled crayfish and the progression of glioblastoma.

evolutionary biology↗

bioRxiv2020

Translational adaptation to heat stress is mediated by 5-methylcytosine RNA modification in Caenorhabditis elegans

Methylation of carbon-5 of cytosines (m5C) is a post-transcriptional nucleotide modification of RNA found in all kingdoms of life. While individual m5C-methyltransferases have been studied, the impact of the global cytosine-5 methylome on development, homeostasis and stress remains unknown. Here, using Caenorhabditis elegans, we generated the first organism devoid of m5C in RNA, demonstrating that this modification is non-essential. We determined the localisation and enzymatic specificity of m5C sites in RNA in vivo and showed that animals devoid of m5C are sensitive to temperature stress. At the molecular level, we showed that loss of m5C specifically impacts decoding of leucine and proline thus reducing the translation efficiency of transcripts enriched in these amino acids. Finally, we found translation of leucine UUG codons to be the most strongly affected upon heat shock, suggesting a role of m5C tRNA wobble methylation in the adaptation to heat stress.

genetics↗

bioRxiv2019

The α1 subunit of the Na,K-ATPase acts upstream of PI(4,5)P2 facilitating unconventional secretion of Fibroblast Growth Factor 2 from tumor cells

Fibroblast Growth Factor 2 (FGF2) is a tumor cell survival factor that is exported from cells by an unconventional secretory pathway. This process is based on direct translocation of FGF2 across the plasma membrane. FGF2 membrane translocation depends on PI(4,5)P2-induced formation of membrane-inserted FGF2 oligomers followed by extracellular trapping of FGF2 at the outer leaflet mediated by cell surface heparan sulfate proteoglycans. Beyond the well-characterized core mechanism of FGF2 membrane translocation, the Na,K-ATPase has been proposed to play a so far unknown role in unconventional secretion of FGF2. Here, we define a direct physical interaction of FGF2 with a subdomain of the cytoplasmic part of the 1 subunit of the Na,K-ATPase. Employing NMR spectroscopy and molecular dynamics simulations, we identified two lysine residues on the molecular surface of FGF2 that are shown to be essential for its interaction with 1. In intact cells, the corresponding lysine-to-glutamate variants of FGF2 were characterized by inefficient secretion and reduced recruitment to the inner plasma membrane leaflet as shown by single molecule TIRF microscopy. Our findings suggest that 1 acts upstream of PI(4,5)P2 facilitating efficient membrane translocation of FGF2 to the cell surface of tumor cells.

biochemistry↗

bioRxiv2017

Statistically robust methylation calling for whole-transcriptome bisulfite sequencing reveals distinct methylation patterns for mouse RNAs

Cytosine-5 RNA methylation plays an important role in several biologically and pathologically relevant processes. However, owing to methodological limitations, the transcriptome-wide distribution of this mark has remained largely unknown. We previously established RNA bisulfite sequencing as a method for the analysis of RNA cytosine-5 methylation patterns at single-base resolution. More recently, next-generation sequencing has provided opportunities to establish transcriptome-wide maps of this modification. Here we present a computational approach that integrates tailored filtering and data-driven statistical modeling to eliminate many of the artifacts that are known to be associated with bisulfite sequencing. Using RNAs from mouse embryonic stem cells we performed a comprehensive methylation analysis of mouse tRNAs, rRNAs and mRNAs. Our approach identified all known methylation marks in tRNA and two previously unknown but evolutionary conserved marks in 28S rRNA. In addition, mRNAs were found to be very sparsely methylated or not methylated at all. Finally, the tRNA-specific activity of the DNMT2 methyltransferase could be resolved at single-base resolution, which provided important further validation. Our approach can be used to profile cytosine-5 RNA methylation patterns in many experimental contexts and will be important for understanding the function of cytosine-5 RNA methylation in RNA biology and in human disease.

bioinformatics↗