Exploring Microtubule-Dependent Cellulose-Synthase-Complex Movement with High Precision Particle Tracking
Bibliographic record
Abstract
Cellulose synthesis at the plasma membrane is a critical process in plant growth and development. The displacement of cellulose synthase complexes (CSCs) by the rigid cellulose polymers they produce is a measure of enzyme activity. Connections between cortical microtubules and CSCs have been identified but it remains unclear how these affect CSC displacement speed. In this study, we applied a high throughput automated particle tracking method using near-total internal reflection fluorescence microscopy to measure the speed of CSCs. We found CSC speeds did not vary according to their proximity to microtubules, and that inhibiting microtubule polymerization could have opposite effects on CSC speed, depending on the nature of inhibition. While CSC speed increased in the temperature-sensitive mor1-1 mutant, it decreased after treatment with the drug oryzalin. Moreover, introducing the mor1-1 mutation into the CesA1 mutant any1 increased CSC speed, suggesting that microtubule dynamics affect CSC speed by a mechanism other than Cellulose Synthase A (CesA) catalytic activity. CSC speed varied widely in a range of mutants with reduced growth anisotropy, indicating that the relationship between CSC speed and anisotropy is complex. We conclude that microtubules affect CSC speed by finely tuned mechanisms that are independent of their physical association with CSCs.
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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 | 0.001 |
| 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".