Biology subjects

Faure, L.

Publications and source records attributed to Faure, L..

12 recordsLinked to original sources

bioRxiv2026

Early avoidance of human-dominated landscapes by juvenile Alpine golden eagles

O_LIThe expanding human footprint drives profound transformations in species, including not only morphological trait loss but also behavioural trait extinction. In contrast to behavioural trait extinction, which entails a reduction in genetic variability, behavioural plasticity maintains behavioural trait diversity and the associated genetic variability required for evolutionary adaptation. Yet, while behavioural plasticity shaping non-human capacity to coexist with humans has evolved under past, human-modified, environmental conditions, few studies have examined whether species retain a level of behavioural plasticity after past interactions with humans. C_LIO_LIUsing data from 64 juveniles golden eagles (Aquila chrysaetos) from a population demographically recovering after centuries of persecution, yet still restricted to less human-dominated alpine massifs, we tested whether human avoidance is innate or learned through experience during dispersal or parental influences during the pre-dispersal period. We performed a Principal Component Analysis (PCA) on landscape features used during the pre-dispersal and the first fifteen weeks of the dispersal phase, and used Mahalanobis distance as an indicator for quantifying changes in individual spatial behaviour over time. C_LIO_LIThe lower frequency of use of human-dominated landscape features, compared with the more sparsely populated mid- and high-elevation landscape features, resulted from individuals consistent use of similar landscape features across the pre-dispersal and dispersal periods. Avoidance of humans was therefore better explained by a learning or imprinting process prior to dispersal, which predisposed individuals to use landscape features similar to those experienced during pre-dispersal, rather than by learning during dispersal, or by an innate avoidance. C_LIO_LIImprinting on natal habitat features corroborates the observed limited range expansion of the alpine population beyond the massif borders. Differences among European populations in range recolonisation suggest contrasting histories of persecution, which may have left varying degrees of behavioural plasticity across populations. C_LIO_LIAs a guide for future conservation priorities, these findings underscore the need to reconstruct past conditions and/or to document contemporary animal behaviour in order to build a library of behaviours that can be used in the future to track behavioural changes. C_LI

animal behavior and cognition↗

bioRxiv2025

Cell Cycle Arrest of a "Zippering" Epithelial Cell Cluster Shapes the Face and is Disrupted in Craniofacial Disorders

Facial features identify individuals, but the mechanisms shaping the human face remain elusive. Orofacial clefting (OFC), the most common craniofacial abnormality, results from failed fusion of the facial prominences that is in part caused by persistence of the cephalic epithelium. Here we uncover the identity, behaviors, and molecular blueprints of a novel craniofacial epithelial population, the Zippering Lambda (ZL), which mediates prominence fusion and is characterized by cell cycle arrest in mouse and human embryos. Remarkably, cell cycle is unleashed in the ZL of Pbx1/2 and p63 mutant mice with OFC. Intersection of ZL-enriched genes with human OFC whole-genome sequencing datasets identifies ZFHX3 variants in affected individuals and cephalic epithelial Zfhx3 deletion causes murine OFC. ZFHX3 and PBX1 genetically interact and synergistically regulate cell cycle inhibitor genes within a complex in embryonic faces. Collectively, we deconstruct new mechanisms that pattern the face, connecting cell cycle arrest to developmental tissue fusion.

developmental biology↗

bioRxiv2023

SOX2+ sustentacular cells are stem cells of the postnatal adrenal medulla

Renewal of the catecholamine-secreting chromaffin cell population of the adrenal medulla is necessary for physiological homeostasis throughout life. Definitive evidence for the presence or absence of an adrenomedullary stem cell has been enigmatic. In this work, we demonstrate that a subset of sustentacular cells endowed with a support role, are in fact adrenomedullary stem cells. Through genetic tracing and comprehensive transcriptomic data of the mouse adrenal medulla, we show that cells expressing Sox2/SOX2 specialise as a unique postnatal population from embryonic Schwann Cell Precursors and are also present in the normal adult human adrenal medulla. Postnatal SOX2+ cells give rise to chromaffin cells of both the adrenaline and noradrenaline lineages in vivo and in vitro. We reveal that SOX2+ stem cells have a second, paracrine role in maintaining adrenal chromaffin cell homeostasis, where they promote proliferation through paracrine secretion of WNT6. This work identifies SOX2+ cells as a true stem cell for catecholamine-secreting chromaffin cells.

developmental biology↗

bioRxiv2023

Gaining proficiency in flight transforms energy landscapes during ontogeny

The heterogeneity of the physical environment determines the cost of transport for animals, shaping their energy landscape. Animals respond to this energy landscape by adjusting their distribution and movement to maximize gains and reduce costs. Much of our knowledge about energy landscape dynamics focuses on factors external to the animal, particularly the spatio-temporal variations of the environment. However, an animals internal state can significantly impact its ability to perceive and utilize available energy, creating a distinction between the "fundamental" and the "realized" energy landscapes. Here we show that the realized energy landscape varies along the ontogenetic axis. Locomotor and cognitive capabilities of individuals change over time, especially during the early life stages. We investigate the development of the realized energy landscape in the Central European Alpine population of the golden eagle Aquila chrysaetos, a large predator that requires negotiating the atmospheric environment to achieve energy-efficient soaring flight. We quantified weekly energy landscapes using environmental features for 55 juvenile golden eagles, demonstrating that energetic costs of traversing the landscape decreased with age. Consequently, the potentially flyable area within the Alpine region increased 2,170-fold during their first three years of independence. Our work contributes to a predictive understanding of animal movement by presenting ontogeny as a mechanism shaping the realized energy landscape.

animal behavior and cognition↗

bioRxiv2022

scFates: a scalable python package for advanced pseudotime and bifurcation analysis from single cell data

scFates provides an extensive toolset for analysis of dynamic trajectories comprising tree learning, feature association testing, branch differential expression and with a focus on cell biasing and fate splits at the level of bifurcations. It is meant to be fully integrated into scanpy ecosystem for seamless analysis of trajectories from single cell data of various modalities (e.g. RNA, ATAC). Availability and implementationscFates is released as open-source software under the BSD 3-Clause "New" License and is available from the Python Package Index at https://pypi.org/project/scFates/. The source code is available on Github at https://github.com/LouisFaure/scFates/ Supplementary informationA supplementary document is provided with a complete explanation of the underlying statistics, and two figures showing examples of analysis.

bioinformatics↗

bioRxiv2022

Developmental heterogeneity of embryonic neuroendocrine chromaffin cells and their maturation dynamics

During embryonic development, nerve-associated Schwann cell precursors (SCPs) give rise to chromaffin cells of the adrenal gland via the "bridge" transient stage, according to recent functional experiments and single cell transcriptomics data from humans and mice. However, currently existing data do not resolve the finest heterogeneity of developing chromaffin populations. Here we took advantage of deep SmartSeq2 transcriptomics sequencing to expand our collection of individual cells from developing murine sympatho-adrenal anlage and uncover the microheterogeneity of embryonic chromaffin cells and corresponding developmental paths. After improving our atlas of sympatho-adrenal development and performing experimental validations, we discovered that SCPs in the local nerve show high degree of microheterogeneity corresponding to early biases towards either Schwann or chromaffin terminal fates. Furthermore, we found that a post-"bridge" population of developing chromaffin cells gives rise to persisting immature chromaffin cells and the two terminal populations (adrenergic and noradrenergic) via diverging differentiation paths. Taken together, we provide a thorough identification of novel markers of adrenergic and noradrenergic populations in developing adrenal glands and report novel differentiation micro-paths leading to them.

developmental biology↗

bioRxiv2022

Artificial Metabolic Networks: enabling neural computation with metabolic networks

Constraint-based metabolic models have been used for decades to predict the phenotype of microorganisms in different environments. However, quantitative predictions are limited unless labor-intensive measurements of media uptake fluxes are performed. We show how hybrid neural-mechanistic models can serve as an architecture for machine learning providing a way to improve phenotype predictions. We illustrate our hybrid models with growth rate predictions of Escherichia coli and Pseudomonas putida grown in different media and with phenotype predictions of gene knocked-out Escherichia coli mutants. Our neural-mechanistic models systematically outperform constraint-based models and require training set sizes orders of magnitude smaller than classical machine learning methods. Our hybrid approach opens a doorway to enhancing constraint-based modeling: instead of constraining mechanistic models with additional experimental measurements, our hybrid models grasp the power of machine learning while fulfilling mechanistic constrains, thus saving time and resources in typical systems biology or biological engineering projects.

systems biology↗

bioRxiv2021

A versatile active learning workflow for optimization of genetic and metabolic networks

The study, engineering and application of biological networks require practical and efficient approaches. Current optimization efforts of these systems are often limited by wet lab labor and cost, as well as the lack of convenient, easily adoptable computational tools. Aimed at democratization and standardization, we describe METIS, a modular and versatile active machine learning workflow with a simple online interface for the optimization of biological target functions with minimal experimental datasets. We demonstrate our workflow for various applications, from simple to complex gene circuits and metabolic networks, including several cell-free transcription and translation systems, a LacI-based multi-level controller and a 27-variable synthetic CO2-fixation cycle (CETCH cycle). Using METIS, we could improve above systems between one and two orders of magnitude compared to their original setup with minimal experimental efforts. For the CETCH cycle, we explored the combinatorial space of [~]1025 conditions with only 1,000 experiments to yield the most efficient CO2-fixation cascade described to date. Beyond optimization, our workflow also quantifies the relative importance of individual factors to the performance of a system. This allows to identify so far unknown interactions and bottlenecks in complex systems, which paves the way for their hypothesis-driven improvement, which we demonstrate for the LacI multi-level controller that we were able to improve by 34-fold after having identified resource competition as limiting factor. Overall, our workflow opens the way for convenient optimization and prototyping of genetic and metabolic networks with customizable adjustments according to user experience, experimental setup, and laboratory facilities.

synthetic biology↗

bioRxiv2021

Two different cell-cycle processes determine the timing of cell division in Escherichia coli

Cells must control the cell cycle to ensure that key processes are brought to completion. In Escherichia coli, it is controversial whether cell division is tied to chromosome replication or to a replication-independent inter-division process. A recent model suggests instead that both processes may limit cell division with comparable odds in single cells. Here, we tested this possibility experimentally by monitoring single-cell division and replication over multiple generations at slow growth. We then perturbed cell width, causing an increase of the time between replication termination and division. As a consequence, replication became decreasingly limiting for cell division, while correlations between birth and division and between subsequent replication-initiation events were maintained. Our experiments support the hypothesis that both chromosome replication and a replication-independent inter-division process can limit cell division: the two processes have balanced contributions in non-perturbed cells, while our width perturbations increase the odds of the replication-independent process being limiting.

systems biology↗

bioRxiv2020

Galaxy-SynBioCAD: Synthetic Biology Design Automation tools in Galaxy workflows

Many computer-aided design tools are available for synthetic biology and metabolic engineering. Yet, these tools can be difficult to apprehend, sometimes requiring a level of expertise that limits their use by a wider community. Furthermore, some of the tools, although complementary, rely on different input and output formats and cannot communicate with one another. Scientific workflows address these shortcomings while offering a novel design strategy. Among the workflow systems available, Galaxy is a web-based platform for performing findable and accessible data analyses for all scientists regardless of their informatics expertise, along with interoperable and reproducible computations regardless of the particular platform that is being used. Here, we introduce the Galaxy-SynBioCADa portal, the first Galaxy toolshed for synthetic biology and metabolic engineering. It allows one to easily create workflows or use those already developed by the community. The portal is a growing community effort where developers can add new tools and users can evaluate the tools performing design for their specific projects. The tools and workflows currently shared on the Galaxy-SynBioCAD portal cover an end-to-end metabolic pathway design process from the selection of strain and target to the calculation of DNA parts to be assembled to build libraries of strains to be engineered to produce the target. Standard formats are used throughout to enforce the compatibility of the tools. These include SBML for strain and pathway and SBOL for genetic layouts. The portal has been benchmarked on 81 literature pathways, overall, we find we have a 65% (and 88%) success rate in retrieving the literature pathways among the top 10 (50) pathways predicted and generated by the workflows.

bioengineering↗

bioRxiv2019

Prototypical pacemaker neurons are immunocompetent cells

Pacemaker neurons exert control over neuronal circuit function by their intrinsic ability to generate rhythmic bursts of action potential. Recent work has identified rhythmic gut contractions in human, mice and hydra to be dependent on both neurons and the resident microbiota. However, little is known about the evolutionary origin of these neurons and their interaction with microbes. In this study, we identified and functionally characterized prototypical ANO/SCN/TRPM ion channel expressing pacemaker cells in the basal metazoan Hydra by using a combination of single-cell transcriptomics, immunochemistry, and functional experiments. Unexpectedly, these prototypical pacemaker neurons express a rich set of immune-related genes mediating their interaction with the microbial environment. Functional experiments validated a model of the evolutionary emergence of pacemaker cells as neurons using components of innate immunity to interact with the microbial environment and ion channels to generate rhythmic contractions.

developmental biology↗

bioRxiv2019

Feedback regulation of BMP signaling by C. elegans cuticle collagens

Cellular responsiveness to environmental cues, including changes in extracellular matrix (ECM), is critical for normal processes such as development and wound healing, but can go awry, as in oncogenesis and fibrosis. One type of molecular pathway allowing this responsiveness is the bone morphogenetic protein (BMP) signaling pathway. Due to their broad and potent functions, BMPs and their signaling pathways are highly regulated at multiple levels. In Caenorhabditis elegans, the BMP ligand DBL-1 is a major regulator of body size. We have previously shown that DBL-1/BMP signaling determines body size through transcriptional regulation of cuticle collagen genes. We have now obtained evidence of feedback regulation of DBL-1/BMP by collagen genes. We analyzed four DBL-1-regulated collagen genes that affect body size. Here we show that inactivation of any one of these cuticle collagen genes reduces DBL-1/BMP signaling, as measured by a Smad activity reporter. Furthermore, we find that depletion of these collagens reduces GFP::DBL-1 fluorescence, and acts unexpectedly at the level of dbl-1 transcription. We therefore conclude that cuticle, a type of ECM, impinges on DBL-1/BMP expression and signaling. In contrast to other characterized examples, however, the feedback regulation of DBL-1/BMP signaling by collagens is likely to be contact-independent, due to the physical separation of the cuticle from DBL-1-expressing cells in the ventral nerve cord. Our results provide an entry point into a novel mechanism of regulation of BMP signaling, with broader implications for mechanical regulation of gene expression in general.

developmental biology↗