Biology subjects

Riviere, M.

Publications and source records attributed to Riviere, M..

7 recordsLinked to original sources

bioRxiv2026

Dynamic membrane organization coordinates protein-O-mannosylation and proteostasis in mycobacteria.

Integral membrane enzymes operate within molecular environments, yet how these are organized remains poorly understood. Using M. smegmatis as a mycobacterial model, we define the membrane environment of the protein O-mannosyltransferase MtPMT through stratified interactomics combining affinity purification-mass spectrometry under four stringencies with a persistence score. This approach resolves a persistent membrane-associated core of 108 proteins from more transient layers, revealing a hierarchically organized landscape enriched in Sec protein translocation, protein biogenesis and envelope proteostasis machineries. Reciprocal affinity purification and in vivo FRET identify YajC and FtsH as neighbors of MtPMT, while structural modelling supports integration within a Sec-associated assembly. Genetic disruption of factors reduces O-mannosylation activity, demonstrating dependence on platform integrity. The MtPMT-associated network is remodelled during growth, indicating an adaptive system. Loss of POM compromises envelope permeability and stress resilience, linking O-mannosylation to fitness. Together, our results establish protein O-mannosylation as an integrated component of a dynamic membrane platform coordinating secretion, membrane protein biogenesis and proteostasis. Our findings support a model in which mycobacterial membranes contain specialized domains dynamically modulated by physiological state.

cell biology↗

bioRxiv2026

Nonlinear distributed sensing of light patterns leads to perceptual distortions in plants

Many organisms lack centralized sensory-processing systems, navigating complex environments through local integration of spatially distributed stimuli (e.g., chemotaxis of cells, bacteria, or growing neurons). Here we propose the first general physical and geometric framework to describe how such distributed sensing translates into integrated directional responses. We study plants, multicellular decentralized systems that grow towards light (phototropism), which can come from multiple directions and at different intensities. We develop a model in which light is sensed locally on the shoot circumference, transduced nonlinearly, and integrated vectorially; the model is informed and validated by unilateral and bilateral lighting, and out-of-plane illumination experiments on sunflower seedlings. We show that seedlings respond to the vectorial sum of transduced signals rather than to the physical sum of incident light, which can create systematic deviations between maximal physical illumination and growth direction, akin to optical illusions. This framework further predicts that symmetrical, opposing cues cancel each other out, which we validate experimentally using a weaker symmetry-breaking light source.

plant biology↗

bioRxiv2023

A quantitative model for spatio-temporal dynamics of root gravitropism

Plant organs adapt their morphology according to environmental signals through growth-driven processes called tropisms. While much effort has been directed in the development of mathematical models describing the tropic dynamics of aerial organs, these cannot provide a good description of roots due to intrinsic physiological differences. Here we present a mathematical model informed by gravitropic experiments on Arabidopsis thaliana roots, assuming a sub-apical growth profile and apical sensing. The model quantitatively recovers the full spatio-temporal dynamics observed in experiments. An analytical solution of the model enables us to evaluate the gravitropic and proprioceptive sensitivities of roots, while also allowing us to corroborate the requirement of proprioception in describing root dynamics. Lastly, we find that the dynamics are analogous to a damped harmonic oscillator, providing intuition regarding the source of the observed oscillatory behavior. In all, the model not only provides a quantitative description of root tropic dynamics, but also provides a mathematical framework for the future investigation of roots in complex media.

plant biology↗

bioRxiv2023

Revealing how memory shapes time-dependent computational processes in plant tropisms

Mounting evidence suggests that plants engage complex computational processes to quantify and integrate sensory information over time, enabling remarkable adaptive growth strategies. However, quantitative understanding of these computational processes is limited. We report experiments probing the dependence of gravitropic responses of wheat coleoptiles on previous stimuli. First, building on a mathematical model that identifies this dependence as a form of memory, or a filter, we use experimental observations to reveal the mathematical principles of how coleoptiles integrate multiple stimuli over time. Next, we perform two-stimulus experiments, informed by model predictions, to reveal fundamental computational processes. We quantitatively show that coleoptiles respond not only to sums but also to differences between stimuli over different timescales, constituting first evidence that plants can compare stimuli - crucial for search and regulation processes. These timescales also coincide with oscillations observed in gravitropic responses of wheat coleoptiles, suggesting shoots may combine memory and movement in order to enhance posture control and sensing capabilities.

plant biology↗

bioRxiv2022

Spatiotemporal growth pattern during plant nutation implies fast dynamics for cell wall mechanics and chemistry: a multiscale study in Averrhoa carambola

Nutation is the most striking and ubiquitous example of the rhythmic nature of plant development. Although there is a consensus that this wide oscillatory motion is driven by growth, its internal mechanisms have not been fully elucidated yet. In this work, we study the specific case of nutation in compound leaves in the archetypal Averrhoa carambola plant. We quantify the macroscopic growth kinematics with time lapse imaging, image analysis and kinematics modeling. We further characterize the mechanical and chemical properties of the cell wall with atomic force microscopy and immunolabelling. Our data first reveal that the differential growth driving nutation is localized and peaks where the average growth drops. We then show this specific spatiotemporal growth profile is compatible with local contraction events. At the cell wall level, differential growth is further colocalized with an asymmetry of the cell wall elastic modulus, and with an asymmetric distribution of homogalacturonans (HG). Our results not only back up the hypothesis of HG being involved in plant growth, but also build up on it by suggesting a dynamic nature for this process. Significance StatementNutation is an oscillatory motion displayed by many organs of growing plants. Most works on nutation focus on its relation to external stimuli attempting to explain its origins. By contrast, its internal physiological mechanisms remain to be fully explored. Here we propose an experimental and multiscale characterization of undisturbed nutation. We determine the macroscopic growth profile and show it is compatible with cell expansion but also local contractions in the tissues. At the microscopic level, we reveal that both the rigidity and composition of the cell wall are asymmetrically distributed where nutation occurs. The combination of results on both scales brings contributions to the understanding of interplay between global movement, local growth, cell wall mechanics and cell wall biochemistry.

biophysics↗

bioRxiv2020

Prediction of regional wildfire activity with a probabilistic Bayesian framework

O_LIModelling wildfire activity is crucial for informing science-based risk management and understanding fire-prone ecosystem functioning worldwide. Models also help to disentangle the relative roles of different factors, to understand wildfire predictability or to provide insights into specific events. C_LIO_LIHere, we develop a two-component Bayesian hierarchically-structured probabilistic model of daily fire activity, which are modelled as the outcome of a marked point process in which individual fires are the points (occurrence component) and the fire sizes are the marks (size component). The space-time Poisson model for occurrence is adjusted to gridded fire counts using the integrated nested Laplace approximation (INLA) combined with the Stochastic Partial Differential Equation (SPDE) approach. The size model is based on piecewise-estimated Pareto and Generalized-Pareto distributions, also adjusted with INLA. The Fire Weather Index (FWI) and Forest Area are the main explanatory variables. Seasonal and spatial residuals as well as a post-2003 effect are included to improve the consistency of the relationship between climate and fire occurrence, in accordance with parsimonious criteria. C_LIO_LIA set of 1000 simulations of the posterior model of fire activity is evaluated at various temporal and spatial scales in Mediterranean France. The number of escaped fires ([≥]1ha) across the region can be coarsely reproduced at the daily scale, and is more accurately predicted on a weekly basis or longer. The regional weekly total number of larger fires (10 to 100 ha) can be predicted as well, but the accuracy decays with size, as the model uncertainty increases with event rareness. Local predictions of fire numbers or burnt areas likewise require a longer aggregation period to maintain model accuracy. C_LIO_LIRegarding the year 2003 -which was characterized by an extreme burnt area in France associated with a heat wave-, the estimation of the number of escaped fires was consistent with observations, but the model systematically underrepresents larger fires and burnt areas, which suggests that the FWI does not consistently rate the danger of large fire occurrence during heat waves. C_LIO_LIOur study sheds new light on the stochastic processes underlying fire hazard, and is promising for predicting and projecting future fire hazard in the context of climate change. C_LI

bioengineering↗

bioRxiv2020

Hook Shape of Growing Leaves Results from an Active Regulation

The rachis of most growing compound leaves observed in nature exhibit a stereotyped hook shape. In this study, we focus on the canonical case of Averrhoa carambola. Combining kinematics and mechanical investigation, we characterize this hook shape and shed light on its establishment and maintenance. We show quantitatively that the hook shape is a conserved bent zone propagating at constant velocity and constant distance from the apex throughout development. A simple mechanical test first reveals non-zero spontaneous curvature profiles for the growing leaves, indicating that the hook shape is actively regulated. It then evidences the robust spatial organization of growth, curvature, rigidity and lignification and their interplay. Regulation processes appear to be specifically localized: in particular, differential growth occurs where the elongation rate drops. Finally, impairing the graviception of the leaf on a clinostat led to reduced hook curvatures but not to its loss. Altogether our results suggest a role for proprioception in the regulation of the apical hook, likely mediated via mechanical strain.

plant biology↗