Spatial cues and not spindle pole maturation drive the asymmetry of astral microtubules between new and preexisting spindle poles
Bibliographic record
Abstract
In many asymmetrically dividing cells, the microtubule-organizing centers (MTOCs; mammalian centrosome and yeast spindle pole body [SPB]) nucleate more astral microtubules on one of the two spindle poles than the other. This differential activity generally correlates with the age of MTOCs and contributes to orienting the mitotic spindle within the cell. The asymmetry might result from the two MTOCs being in distinctive maturation states. We investigated this model in budding yeast. Using fluorophores with different maturation kinetics to label the outer plaque components of the SPB, we found that the Cnm67 protein is mobile, whereas Spc72 is not. However, these two proteins were rapidly as abundant on both SPBs, indicating that SPBs mature more rapidly than anticipated. Superresolution microscopy confirmed this finding for Spc72 and for the γ-tubulin complex. Moreover, astral microtubule number and length correlated with the subcellular localization of SPBs rather than their age. Kar9-dependent orientation of the spindle drove the differential activity of the SPBs in astral microtubule organization rather than intrinsic differences between the spindle poles. Together, our data establish that Kar9 and spatial cues, rather than the kinetics of SPB maturation, control the asymmetry of astral microtubule organization between the preexisting and new SPBs.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".