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Kinematic Analysis of Cell Division and Expansion: Quantifying the Cellular Basis of Growth and Sampling Developmental Zones in Zea mays Leaves
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A plant cell division algorithm based on cell biomechanics and ellipse-fitting.

Metadel K Abera, Pieter Verboven, Thijs Defraeye

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    This study introduces a new algorithm for plant cell division, simulating both symmetric and asymmetric cell division with simultaneous cell wall growth. The model accurately represents biological variability and tissue development in silico.

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    Area of Science:

    • Computational biology
    • Plant science
    • Cell biology

    Background:

    • Cell division models are crucial for understanding cellular patterns.
    • Existing models often simplify cell division to symmetric cases with isotropic growth, neglecting simultaneous cell wall mechanics.
    • This limits their accuracy in representing complex biological processes.

    Purpose of the Study:

    • To present a generic algorithm for simulating plant cell division.
    • To incorporate both symmetric and asymmetric cell division with isotropic and anisotropic growth.
    • To simulate actual cell wall growth simultaneously with mechanical processes.

    Main Methods:

    • Modeling cells as thin-walled structures under turgor pressure, with walls as linear elastic elements.
    • Developing a system of differential equations for cell vertex dynamics and cell wall growth.
    • Utilizing an ellipse-fitting algorithm to determine division plane orientation and incorporating biological variability.
    • Comparing model outputs with existing experimental data.

    Main Results:

    • Successfully implemented a generic plant cell division algorithm capable of handling symmetric and asymmetric divisions with isotropic and anisotropic growth.
    • Demonstrated the importance of ellipse-fitting for introducing biological variability in cell division patterns.
    • Formulated and solved a differential equation for cell wall resting length, enabling simultaneous simulation of growth and mechanics.

    Conclusions:

    • The developed algorithm can generate diverse plant tissues with varied topological and geometrical properties.
    • This model offers significant potential for in silico investigations of plant cell division and growth dynamics.
    • The simultaneous simulation of mechanics and actual growth enhances the biological realism of the model.