Biology subjects

Lallouette, J.

Publications and source records attributed to Lallouette, J..

4 recordsLinked to original sources

bioRxiv2026

Competing calcium sensors orchestrate various patterns of synaptic transmission

Neurotransmission critically depends on both timing and efficacy, enabling neurons to encode information with highly accuracy in millisecond timescales. While synapses often express multiple calcium sensors, such as synaptotagmin-1 (syt1) and synaptotagmin-7 (syt7), the quantitative mechanisms by which these sensors regulate synchronous release (SR) and asynchronous release (AR) remain unresolved. We develop a biophysically detailed stochastic model of a presynaptic bouton that incorporates the distinct calcium-binding kinetics of syt1 and syt7 to dissect their roles in shaping synaptic release. We demonstrate how a rich repertoire of SR and AR patterns is influenced by calcium channel distribution, sensor quantity, the external calcium concentration and buffer properties. Importantly, the interplay between syt1 and syt7-- through their distinct calcium affinities and exocytotic kinetics -- constitutes a core mechanism for neural transmission. These findings establish calcium partitioning as a core mechanism driving the diverse release patterns of syt1 and syt7, accommodating even more complex multi-sensor environments.

neuroscience↗

bioRxiv2023

Hybrid vesicle and reaction-diffusion modeling with STEPS

Vesicles carry out many essential functions within cells through the processes of endocytosis, exocytosis, and passive and active transport. This includes transporting and delivering molecules between different parts of the cell, and storing and releasing neurotransmitters in neurons. To date, computational simulation of these key biological players has been rather limited and has not advanced at the same pace as other aspects of cell modeling. As computational power advances and researchers want to add new realism to their models an important advance in the field of computational biology is to simulate vesicles in a realistic yet efficient manner. We describe a general vesicle modeling tool that has been designed for wide application to a variety of cell models, implemented within our voxel-based approach to modeling reaction-diffusion processes in realistic mesh reconstructions of cell tissue in our software STEPS. The implementation is validated in an extensive test suite, parallel performance demonstrated in a realistic synaptic bouton model, and example models are visualized in a Blender extension module.

systems biology↗

bioRxiv2022

STEPS 4.0: Fast and memory-efficient molecular simulations of neurons at the nanoscale

AO_SCPLOWBSTRACTC_SCPLOWRecent advances in computational neuroscience have demonstrated the usefulness and importance of stochastic, spatial reaction-diffusion simulations. However, ever increasing model complexity renders traditional serial solvers, as well as naive parallel implementations, inadequate. This paper introduces a new generation of the STochastic Engine for Pathway Simulation (STEPS) project, denominated STEPS 4.0, and its core components which have been designed for improved scalability, performance, and memory efficiency. STEPS 4.0 aims to enable novel scientific studies of macroscopic systems such as whole cells while capturing their nanoscale details. This class of models is out of reach for serial solvers due to the vast quantity of computation in such detailed models, and also out of reach for naive parallel solvers due to the large memory footprint. Based on a distributed mesh solution, we introduce a new parallel stochastic reaction-diffusion solver and a deterministic membrane potential solver in STEPS 4.0. The distributed mesh, together with improved data layout and algorithm designs, significantly reduces the memory footprint of parallel simulations in STEPS 4.0. This enables massively parallel simulations on modern HPC clusters and overcomes the limitations of the previous parallel STEPS implementation. Current and future improvements to the solver are not sustainable without proper software engineering practices. For this reason, we also give an overview of how the STEPS codebase and the development environment have been updated to follow modern software development practices. We benchmark performance improvement and memory footprint on three published models with different complexities, from a simple spatial stochastic reaction-diffusion model, to a more complex one that is coupled to a deterministic membrane potential solver to simulate the calcium burst activity of a Purkinje neuron. Simulation results of these models suggest that the new solution dramatically reduces the per-core memory consumption by more than a factor of 30, while maintaining similar or better performance and scalability.

neuroscience↗

bioRxiv2018

Astrocyte networks and intercellular calcium propagation

Astrocytes organize in complex networks through connections by gap junction channels that are regulated by extra- and intracellular signals. Calcium signals generated in individual cells, can propagate across these networks in the form of intercellular calcium waves, mediated by diffusion of second messengers molecules such as inositol 1,4,5-trisphosphate. The mechanisms underpinning the large variety of spatiotemporal patterns of propagation of astrocytic calcium waves however remain a matter of investigation. In the last decade, awareness has grown on the morphological diversity of astrocytes as well as their connections in networks, which seem dependent on the brain area, developmental stage, and the ultrastructure of the associated neuropile. It is speculated that this diversity underpins an equal functional variety but the current experimental techniques are limited in supporting this hypothesis because they do not allow to resolve the exact connectivity of astrocyte networks in the brain. With this aim we present a general framework to model intercellular calcium wave propagation in astrocyte networks and use it to specifically investigate how different network topologies could influence shape, frequency and propagation of these waves.

neuroscience↗