Speaker
Description
We develop mathematical models to study the role of mechanical forces in determining plant cell and tissue polarity. Our focus lies on SOSEKI proteins (SOKs) that distribute anisotropically along the cell membrane. Recent work suggests that SOKs are mechanosensitive \cite{p}, creating a potential connection between mechanics and plant cell polarity essential to plant organ development.
The deeply conserved SOKs share a homologous domain with Dishevelled, an animal protein involved in Planar Cell Polarity (PCP) \cite{p}, the polarization of epithelial tissue normal to the apical-basal axis. Despite fundamental differences between the mechanism of PCP and SOKs, mathematical models of PCP (e.g., \cite{s}) are a useful starting point for our research. Many models of PCP consist of three interacting components: (1) a cell-autonomous tendency to polarize, (2) information exchange between adjacent cells, and (3) a mechanism communicating tissue-wide directional information to individual cells. Although the molecular mechanism will differ, we expect animal PCP mechanisms may share conceptual similarities with plant models.
We present first results of our multicellular SOK-model implemented in the vertex-based 2D plant tissue modelling framework VirtualLeaf \cite{vl}. We study how this model explains tissue polarity and present first results of the effect of mechanics.
Bibliography
@incollection{vl,
address = {New York, NY},
title = {Modeling {Plant} {Tissue} {Development} {Using} {VirtualLeaf}},
isbn = {978-1-0716-1816-5},
url = {https://doi.org/10.1007/978-1-0716-1816-5_9},
doi = {10.1007/978-1-0716-1816-5_9},
abstract = {Cell-based computational modeling and simulation are becoming invaluable tools in analyzing plant development. In a cell-based simulation model, the inputs are behaviors and dynamics of individual cells and the rules describing responses to signals from adjacent cells. The outputs are the growing tissues, shapes, and cell-differentiation patterns that emerge from the local, chemical, and biomechanical cell-cell interactions. In this updated and extended version of our previous chapter on VirtualLeaf (Merks and Guravage, Methods in Molecular Biology 959, 333–352), we present a step-by-step, practical tutorial for building cell-based simulations of plant development and for analyzing the influence of parameters on simulation outcomes by systematically changing the values of the parameters and analyzing each outcome. We show how to build a model of a growing tissue, a reaction–diffusion system on a growing domain, and an auxin transport model. Moreover, in addition to the previous publication, we demonstrate how to run a Turing system on a regular, rectangular lattice, and how to run parameter sweeps. The aim of VirtualLeaf is to make computational modeling more accessible to experimental plant biologists with relatively little computational background.},
booktitle = {Plant {Systems} {Biology}: {Methods} and {Protocols}},
publisher = {Springer New York},
author = {Antonovici, Claudiu-Cristi and Peerdeman, Guacimo Y. and Wolff, Harold B. and Merks, Roeland M. H.},
editor = {Lucas, Mikaël},
year = {2022},
pages = {165--198},
}
@misc{p,
title = {Mechanics and growth coordination define {SOSEKI}-based polarity fields},
copyright = {© 2025, Posted by openRxiv. This pre-print is available under a Creative Commons License (Attribution-NonCommercial-NoDerivs 4.0 International), CC BY-NC-ND 4.0, as described at http://creativecommons.org/licenses/by-nc-nd/4.0/},
url = {https://www.biorxiv.org/content/10.1101/2025.11.26.690761v2},
doi = {10.1101/2025.11.26.690761},
abstract = {The formation of organs requires the coordinated growth of cells and tissues relative to the main body axes. Plant growth is typically anisotropic and mechanically coupled through contiguous cell walls, yet how these physical patterns link to cell and tissue polarity remains unclear. Here, we use SOSEKI (SOK) proteins—previously thought to report global polarity fields—as markers to dissect how polarity arises during lateral root (LR) organogenesis. Live imaging revealed that SOK polarisation does not follow a uniform global field but instead responds to local differences in growth and mechanical state between neighbouring tissues. SOKs accumulate at interfaces separating domains of distinct growth behaviour and dissipate under compressive stress. After perturbing tissue interfaces or the mechanical continuity of the tissue, the coherence of the polarity was disrupted, indicating that stable axis establishment requires mechanical coupling across the cell wall network. Our results suggest that SOK polarisation is mechanoresponsive, linking tissue mechanics to polarity and axis establishment.},
language = {en},
urldate = {2026-02-26},
publisher = {bioRxiv},
author = {Piepers, Marcel and Reyes-Hernández, Blanca Jazmin and Ramos, João R. D. and Bölke, Neva and Schütz, Laura and Song, Changzheng and Primc, Anamarija and Bald, Lotte and Merks, Roeland MH and Weijers, Dolf and Maizel, Alexis},
month = nov,
year = {2025},
note = {ISSN: 2692-8205
Pages: 2025.11.26.690761
Section: New Results},
file = {Full Text PDF:C\:\Users\leide\Zotero\storage\4GM8H7C3\Piepers et al. - 2025 - Mechanics and growth coordination define SOSEKI-based polarity fields.pdf:application/pdf},
}
@article{s,
title = {Modelling and {Analysis} of {Planar} {Cell} {Polarity}},
volume = {72},
issn = {1522-9602},
url = {https://doi.org/10.1007/s11538-009-9464-0},
doi = {10.1007/s11538-009-9464-0},
abstract = {Planar cell polarity (PCP) occurs in the epithelia of many animals and can lead to the alignment of hairs, bristles, and feathers. Here, we present two approaches to modelling this phenomenon. The aim is to discover the basic mechanisms that drive PCP, while keeping the models mathematically tractable. We present a feedback and diffusion model, in which adjacent cell sides of neighbouring cells are coupled by a negative feedback loop and diffusion acts within the cell. This approach can give rise to polarity, but also to period two patterns. Polarisation arises via an instability provided a sufficiently strong feedback and sufficiently weak diffusion. Moreover, we discuss a conservative model in which proteins within a cell are redistributed depending on the amount of proteins in the neighbouring cells, coupled with intracellular diffusion. In this case, polarity can arise from weakly polarised initial conditions or via a wave provided the diffusion is weak enough. Both models can overcome small anomalies in the initial conditions. Furthermore, the range of the effects of groups of cells with different properties than the surrounding cells depends on the strength of the initial global cue and the intracellular diffusion.},
language = {en},
number = {3},
urldate = {2026-02-19},
journal = {Bulletin of Mathematical Biology},
author = {Schamberg, S. and Houston, P. and Monk, N. A. M. and Owen, M. R.},
month = apr,
year = {2010},
keywords = {Drosophila, Frizzled, Reaction–diffusion equations},
pages = {645--680},
file = {Full Text PDF:C\:\Users\leide\Zotero\storage\FPQBD83M\Schamberg et al. - 2010 - Modelling and Analysis of Planar Cell Polarity.pdf:application/pdf},
}
