Encoding neuronal shape in the stochastic dynamics of branching processes
Abstract
Cell shape critically influences function, yet how complex and reproducible morphologies emerge from stochastic cellular dynamics remains unclear. Here, we investigate dendritic morphogenesis of two classes of Drosophila mechanosensory neurons with contrasting architectures, combining in vivo live imaging, quantitative analysis, cytoskeletal perturbations, and computational modeling. We show that despite sharing similar local stochastic branching rules, the two classes exhibit divergent growth dynamics that cannot be explained by standard, diffusive growth models. This discrepancy arises because Class I neurons display subdiffusive branch dynamics over long timescales, unlike Class IV. Based on these findings, we develop a minimal model with only four parameters that separates shortand long-term branch behaviors, and successfully recapitulates growth dynamics and final morphologies in both classes. Cytoskeletal perturbations reveal a functional separation between actin, which drives short-term exploratory branch fluctuations and arbor expansion, and microtubules, which tune long-term branch diffusivity and determine class-specific morphology. Together, these results establish a parsimonious, generalizable framework linking local cytoskeletal regulation to global neuronal architecture and reveal how stochastic dynamics encode reproducible cell shapes.
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BibTeX
@misc{perrin2026encoding,
title = {{Encoding neuronal shape in the stochastic dynamics of branching processes}},
author = {Marc-Eric Perrin and Maximilien Courgeon and Elise da Silva and Jean-Marc Philippe and Jean-François Rupprecht and Claire Bertet and Thomas Lecuit},
howpublished = {HAL},
year = {2026},
month = jun,
doi = {10.64898/2026.06.05.729577},
url = {https://hal.science/hal-05800093v1},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Encoding neuronal shape in the stochastic dynamics of branching processes
AU - Marc-Eric Perrin
AU - Maximilien Courgeon
AU - Elise da Silva
AU - Jean-Marc Philippe
AU - Jean-François Rupprecht
AU - Claire Bertet
AU - Thomas Lecuit
PY - 2026
DA - 2026/06/05
PB - HAL
DO - 10.64898/2026.06.05.729577
UR - https://hal.science/hal-05800093v1
AB - Cell shape critically influences function, yet how complex and reproducible morphologies emerge from stochastic cellular dynamics remains unclear. Here, we investigate dendritic morphogenesis of two classes of Drosophila mechanosensory neurons with contrasting architectures, combining in vivo live imaging, quantitative analysis, cytoskeletal perturbations, and computational modeling. We show that despite sharing similar local stochastic branching rules, the two classes exhibit divergent growth dynamics that cannot be explained by standard, diffusive growth models. This discrepancy arises because Class I neurons display subdiffusive branch dynamics over long timescales, unlike Class IV. Based on these findings, we develop a minimal model with only four parameters that separates shortand long-term branch behaviors, and successfully recapitulates growth dynamics and final morphologies in both classes. Cytoskeletal perturbations reveal a functional separation between actin, which drives short-term exploratory branch fluctuations and arbor expansion, and microtubules, which tune long-term branch diffusivity and determine class-specific morphology. Together, these results establish a parsimonious, generalizable framework linking local cytoskeletal regulation to global neuronal architecture and reveal how stochastic dynamics encode reproducible cell shapes.
ER -