A CLASP-modulated cell edge barrier mechanism drives cell-wide cortical microtubule organization in Arabidopsis
Bibliographic record
Abstract
It is well known that the parallel order of microtubules in the plant cell cortex defines the direction of cell expansion, yet it remains unclear how microtubule orientation is controlled, especially on a cell-wide basis. Here we show through 4D imaging and computational modelling that plant cell polyhedral geometry provides spatial input that determines array orientation and heterogeneity. Microtubules depolymerize when encountering sharp cell edges head-on, whereas those oriented parallel to those sharp edges remain. Edge-induced microtubule depolymerization, however, is overcome by the microtubule-associated protein CLASP, which accumulates at specific cell edges, enables microtubule growth around sharp edges and promotes formation of microtubule bundles that span adjacent cell faces. By computationally modelling dynamic 'microtubules on a cube' with edges differentially permissive to microtubule passage, we show that the CLASP-edge complex is a 'tuneable' microtubule organizer, with the inherent flexibility to generate the numerous cortical array patterns observed in nature. How microtubules are organized correctly in plant cells is not well understood. Ambroseet al. use 4D imaging and computer modelling to show that sharp cell edges induce microtubule depolymerization and that the microtubule-associated protein CLASP mitigates this process to modulate array organization.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".