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Plant cell walls are versatile materials that can adopt a wide range of mechanical properties through controlled deposition of cellulose fibrils. Wall integrity requires a sufficiently homogeneous fibril distribution to cope effectively with wall stresses. Additionally, specific conditions, such as the negative pressure in water transporting xylem vessels, may require more complex wall patterns, e.g., bands in protoxylem. The orientation and patterning of cellulose fibrils is guided by dynamic cortical microtubules. New microtubules are predominantly nucleated from parent microtubules causing positive feedback on local microtubule density with the potential to yield highly inhomogeneous patterns. Inhomogeneity indeed appears in all current cortical array simulations that include microtubule-based nucleation, suggesting that plant cells must possess an as-yet unknown balancing mechanism to prevent it. Here, in a combined simulation and experimental approach, we show that the naturally limited local recruitment of nucleation complexes to microtubules can counter the positive feedback, whereas local tubulin depletion cannot. We observe that nucleation complexes are preferentially inserted at microtubules. By incorporating our experimental findings in stochastic simulations, we find that the spatial behaviour of nucleation complexes delicately balances the positive feedback, such that differences in local microtubule dynamics – as in developing protoxylem – can quickly turn a homogeneous array into a patterned one. Our results provide insight into how the plant cytoskeleton is wired to meet diverse mechanical requirements and greatly increase the predictive power of computational cell biology studies.Significance statementThe plant cortical microtubule array is an established model system for self-organisation, with a rich history of complementary experiments, computer simulations, and analytical theory. Understanding how array homogeneity is maintained given that new microtubules nucleate from existing microtubules has been a major hurdle for using mechanistic (simulation) models to predict future wall structures. We overcome this hurdle with detailed observations of the nucleation process from which we derive a more “natural” nucleation algorithm. With this algorithm, we enable various new lines of quantitative, mechanistic research into how cells dynamically control their cell wall properties. At a mechanistic level, moreover, this work relates to the theory on cluster coexistence in Turing-like continuum models and demonstrates its relevance for discrete stochastic entities. |
