Biology subjects

de Buyl, S.

Publications and source records attributed to de Buyl, S..

6 recordsLinked to original sources

bioRxiv2025

Development and characterisation of pNarsenic: a naringenin-inducible biosensor for arsenic in Escherichia coli

Whole-cell biosensors detecting the heavy metal arsenic have been widely studied for their potential in environmental monitoring. And while inducible biosensors have been shown to be an effective tool to tune the operational range, a thoroughly characterised inducible biosensor is currently lacking. Here, we present an Escherichia coli biosensor for arsenic in which the transcription factor gene arsR is inducible by naringenin, a plant-derived secondary metabolite. Increasing naringenin concentrations reduced the basal output while increasing both the dynamic range and sensing threshold of the biosensor dose-response curves, but the operational ranges appeared constrained by a fixed upper limit. Comparison with a previously published phenomenological model revealed good overall agreement between experimental data and model predictions, except for the behaviour of the maximum output and threshold. This work expands the biosensor toolbox with a profoundly characterised arsenic biosensor and raises a potential practical limit to dose-response curve engineering by tuning transcription factor expression alone. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=104 SRC="FIGDIR/small/678503v1_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@c15051org.highwire.dtl.DTLVardef@180214forg.highwire.dtl.DTLVardef@10afa84org.highwire.dtl.DTLVardef@1c51bba_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2024

Optimizing information transmission in neural induction constrains cell surface contacts of ascidian embryos

The onset of neural induction in the anterior ectoderm of ascidian embryos is regulated at the extracellular level by FGF signaling molecules, which control the acquisition of neural fate through the activation of the ERK pathway. Among the anterior ectoderm cells exposed to FGF, only a fraction will acquire neural fate. The selection of neural precursors depends on the quasi-invariant geometry of the embryo, which imposes upon each ectoderm cell a precise area of cell surface contact with underlying FGF-expressing (mesendoderm) cells. Here, we investigate information transmission between FGF and activated ERK and how this depends on the geometry of the system. Optimizing information transmission with the constraint that the total FGF-emitting surface area is restricted, as in the embryo, we find that the surface contacts with FGF that maximize information transmission are close to those observed experimentally. This information optimal solution is compatible with the anterior ectoderm cells having different areas of cell surface exposure to FGF, allowing the embryo to use cell surface areas as a regulatory mechanism for differentiating the outcome of cells that sense a constant FGF concentration.

biophysics↗

bioRxiv2023

The sliding motility of the bacilliform virions of Influenza A Viruses

Influenza A virus (IAV) infection relies on the action of the hemagglutinin (HA) and neuraminidase (NA) membrane proteins. The HA ligands anchor the IAV virion to the cells surface by binding the sialic acid (SA) present on the hosts receptors while NA is an enzyme capable of cleaving the SA from the extracellular environment. It is believed that the activity of NA ligands increases the motility of the virions favoring the propagation of the infection. In this work, we develop a numerical framework to study the dynamics of a virion moving across the cell surface for timescales much bigger than the typical ligand-receptor reaction times. We find that the rates controlling the ligand-receptor reactions and the maximal distance at which a pair of ligand-receptor molecules can interact greatly affect the motility of the virions. We also report on how different ways of organizing the two types of ligands on the virions surface result in different types of motion that we rationalize using general principles. In particular, we show how the emerging motility of the virion is less sensitive to the rate controlling the enzymatic activity when NA ligands are clustered. These results help to assess how variations in the biochemical properties of the ligand-receptor interactions (as observed across different IAV subtypes) affect the dynamics of the virions at the cell surface.

biophysics↗

bioRxiv2022

Model of neural induction in the ascidian embryo

How cell specification can be controlled in a reproducible manner is a fundamental question in development biology. In ascidians, a group of marine invertebrate chordates, geometry plays a key role in achieving this control. Here, we use mathematical modeling to demonstrate that geometry dictates the neural-epidermal cell fate choice in the 32-cell stage ascidian embryo by a two-step process involving first the modulation of ERK signaling and second, the expression of the neural marker gene, Otx. The model describes signal transduction by the ERK pathway that is stimulated by FGF and repressed by ephrin, and ERK-mediated control of Otx gene expression, which involves both an activator and an inhibitor of transcription. Considering the measured area of cell surface contacts with FGF- or ephrin-expressing cells as inputs, the solutions of the model reproduce the experimental observations about ERK activation and Otx expression in the different cells under normal and perturbed conditions. Sensitivity analyses and computations of Hill coefficients allow to quantify the robustness of the specification mechanism controlled by cell surface area and to identify the respective role played by each signaling input. Simulations also predict in which conditions the dual control of gene expression by an activator and an inhibitor that are both under the control of ERK can induce a robust ON/OFF control of neural fate induction. Author summaryThe development of a single cell zygote into a multicellular embryo occurs thanks to the combination of cell division and cell specification. The latter process corresponds to the progressive acquisition by the embryonic cells of their final physiological and functional characteristics, which rely on well-defined signaling-controlled genetic programs. The origin of the great robustness of cell specification remains poorly understood. Here, we address this question in the framework of the embryonic neural fate induction in ascidians, which are marine invertebrates. At the 32-cells stage, four cells identified by their precise location in the embryo adopt neural fate. On the basis of experimental observations, we develop a mathematical model that predicts that the choice between the neural or epidermal fate is controlled by the cell surface areas of the cells in contact with two antagonistic signals, FGF and ephrin. Our findings provide a computational confirmation of the major role played by the geometry of the embryo in controlling cell lineage acquisition during ascidian development.

developmental biology↗

bioRxiv2021

Heavy-tailed abundance distributions from stochastic Lotka-Volterra models

Microbial communities found in nature are composed of many rare species and few abundant ones, as reflected by their heavy-tailed abundance distributions. How a large number of species can coexist in those complex communities and why they are dominated by rare species is still not fully understood. We show how heavy-tailed distributions arise as an emergent property from large communities with many interacting species in population-level models. To do so we rely on stochastic logistic and generalized Lotka-Volterra models for which we introduce a global maximal capacity. This maximal capacity accounts for the fact that communities are limited by available resources and space. In a parallel ad-hoc approach, we obtain heavy-tailed abundance distributions from non-interacting models through specific distributions of the parameters. We expect both mechanisms, interactions between many species and specific parameter distributions, to be relevant to explain the observed heavy tails.

ecology↗

bioRxiv2020

Stochastic logistic models reproduce experimental time series of microbial communities

We analyze properties of experimental microbial time series, from plankton and the human microbiome, and investigate whether stochastic generalized Lotka-Volterra models could reproduce those properties. We show that the noise term should be large and that it is a linear function of the species abundance, while the strength of the self-interactions should vary over multiple orders of magnitude. We stress the fact that all the observed stochastic properties can be obtained from a logistic model, i.e. without interactions, even the niche character of the experimental time series. Linear noise is associated with growth rate stochasticity, which is related to changes in the environment. This suggests that fluctuations in the sparsely sampled experimental time series are caused by extrinsic sources.

systems biology↗