The GTP-tubulin cap is not the determinant of microtubule end stability in cells
Bibliographic record
Abstract
Microtubules are dynamic cytoskeletal polymers essential for cell division, motility, and intracellular transport. Microtubule dynamics are characterized by dynamic instability-the ability of individual microtubules to switch between phases of growth and shrinkage. Dynamic instability can be explained by the GTP-cap model, suggesting that a "cap" of GTP-tubulin subunits at the growing microtubule end has a stabilizing effect, protecting against microtubule catastrophe-the switch from growth to shrinkage. Although the GTP-cap is thought to protect the growing microtubule end, whether the GTP-cap size affects microtubule stability in cells is not known. Notably, microtubule end-binding proteins, EBs, recognize the nucleotide state of tubulin and display comet-like localization at growing microtubule ends, which can be used as a proxy for the GTP-cap. Here, we employ high spatiotemporal resolution imaging to compare the relationship between EB comet size and microtubule dynamics in interphase LLC-PK1 cells to that measured in vitro. Our data reveal that the GTP-cap size in cells scales with the microtubule growth rate in the same way as in vitro. However, we find that microtubule ends in cells can withstand transition to catastrophe even after the EB comet is lost. Thus, our findings suggest that the presence of the GTP-cap is not the determinant of microtubule end stability in cells.
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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 | 0.001 | 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".