Microtubule-dependent orchestration of centriole amplification in brain multiciliated cells
Bibliographic record
Abstract
Abstract Centriole number must be restricted to two in cycling cells to avoid pathological cell divisions. Multiciliated cells (MCC), however, need to produce a hundred or more centrioles to nucleate the same number of motile cilia required for fluid flow circulation. These centrioles are produced by highjacking cell cycle and centriole duplication programs. However, how the MCC progenitor handles such a massive number of centrioles to finally organize them in an apical basal body patch is unclear. Here, using new cellular models and high-resolution imaging techniques, we identify the microtubule network as the bandleader, and show how it orchestrates the process in space and in time. Organized by the pre-existing centrosome at the start of amplification, microtubules build a nest of centriolar components from which procentrioles emerge. When amplification is over, the centrosome’s dominance is lost as new centrioles mature and become microtubule nucleators. Microtubules then drag all the centrioles to the nuclear membrane, assist their isotropic perinuclear disengagement and their subsequent collective apical migration. These results reveal that in brain MCC as in cycling cells, the same dynamics - from the centrosome to the cell pole via the nucleus-exists, is the result of a reflexive link between microtubules and the progressive maturation of new centrioles, and participates in the organized reshaping of the entire cytoplasm. On the other hand, new elements described in this work such as microtubule-driven organization of a nest, identification of a spatio-temporal progression of centriole growth and microtubule-assisted disengagement, may shed new light on the centriole duplication program.
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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".