Competition for microtubule lattice spacing between a microtubule expander and compactor
Bibliographic record
Abstract
Microtubules exist in expanded and compacted states, as defined by the lattice spacing of αβ-tubulin dimers. Changes in lattice spacing has been linked to factors such as GTP-hydrolysis, the binding of microtubule-associated proteins (MAPs), the tubulin code, and microtubule bending. These diverse factors exert opposing molecular driving forces on the microtubule lattice that push lattice spacing towards expanded or compacted states. To better understand how these opposing forces are reconciled, we developed in vitro and cell-based model systems for the competition between a microtubule expander (paclitaxel) and a microtubule compactor (Doublecortin, or DCX). Using an in vitro reconstitution approach, we show that paclitaxel expands microtubules cooperatively. In cells, high concentrations of paclitaxel cause DCX to relocalize to compacted lattices found at concave bends. When the concentration of DCX is increased, however, we find that DCX re-compacts the previously expanded microtubules in vitro. Consistently, high expression levels of DCX prevent its relocalization in paclitaxel treated cells. When the competition between paclitaxel and DCX is “balanced”, we observe a complex phenotype: DCX simultaneously localized to both long, straight clusters and concave bends, while other regions on the microtubule network remained DCX-free. We conclude that multiple lattice spacings can coexist in cells. Our results indicate that competition for microtubule lattice spacing is a critical aspect of microtubule physiology.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".