arXiv subjects

Florence Chapeland-Leclerc

Publications and source records attributed to Florence Chapeland-Leclerc.

3 recordsLinked to original sources

arXiv2026

Direct Evidence of Apex-Hypha Interactions During Vegetative Growth of Fungal Thallus via Comprehensive Network and Trajectory Extraction

The mycelium of a filamentous fungus is a growing, branching network of numerous entangled hyphae exhibiting polarised apical growth. Expansion occurs during the vegetative phase from a single ascospore, driven by the need to explore and occupy surrounding space-limiting competitors, enhancing nutrient uptake, and promoting spore dispersal. Radial, rapid, and rectilinear growth combined with frequent branching appears adaptive. However, passive growth without interactions or feedback may produce suboptimal networks, as neither local density nor potential connectivity is considered. Reorientations of the apex near existing hyphae suggest apex-hypha feedback. Yet, the diversity of behaviours, spontaneous fluctuations, and limited apical trajectories studied leave open the question of active regulation. To investigate possible apex-hypha interactions, we analyse a dataset of Podospora anserina thallus growth by reconstructing all apical trajectories post-branching and fitting them with a classical Langevin model that incorporates potential interactions. Comparing isolated and non-isolated hyphae trajectories allows to identify a clear signature of interaction composed of abrupt deceleration and reorientation. This work opens the path towards a systematic exploration of hyphal interactions.

q-bio.QM↗

arXiv2024

Full Identification of a Growing and Branching Network's Spatio-Temporal Structures

Experimentally monitoring the kinematics of branching network growth is a tricky task, given the complexity of the structures generated in three dimensions. One option is to drive the network in such a way as to obtain two-dimensional growth, enabling a collection of independent images to be obtained. The density of the network generates ambiguous structures, such as overlaps and meetings, which hinder the reconstruction of the chronology of connections. In this paper, we propose a general method for global network reconstruction. Each network connection is defined by a unique label, enabling it to be tracked in time and space. In this work, we distinguish between lateral and apical branches on the one hand, and extremities on the other. Finally, we reconstruct the network after identifying and eliminating overlaps. This method is then applied to the model filamentous fungus Podospora anserina to reconstruct its growing thallus. We derive criteria for differentiating between apical and lateral branches. We find that the outer ring is favorably composed of apical branches, while densification within the network comes from lateral branches. From this, we derive the specific dynamics of each of the two types. Finally, in the absence of any latency phase during growth initiation, we can reconstruct a time based on the equality of apical and lateral branching collections. This makes it possible to directly compare the growth dynamics of different thalli.

physics.bio-ph↗

arXiv2022

Prediction and experimental evidence of the optimisation of the angular branching process in the thallus growth of Podospora anserina

Based upon apical growth and hyphal branching, the two main processes that drive the growth pattern of a fungal network, we propose here a two-dimensions simulation based on a binary-tree modelling allowing us to extract the main characteristics of a generic thallus growth. In particular, we showed that, in a homogeneous environment, the fungal growth can be optimized for exploration and exploitation of its surroundings with a specific angular distribution of apical branching. Two complementary methods of extracting angle values have been used to confront the result of the simulation with experimental data obtained from the thallus growth of the saprophytic filamentous fungus Podospora anserina. Finally, we propose here a validated model that, while being computationally low-cost, is powerful enough to test quickly multiple conditions and constraints. It will allow in future works to deepen the characterization of the growth dynamic of fungal network, in addition to laboratory experiments, that could be sometimes expensive, tedious or of limited scope.

q-bio.QM↗