Cytokinetic diversity in mammalian cells is revealed by the characterization of endogenous anillin, Ect2 and RhoA
Bibliographic record
Abstract
Cytokinesis is required to physically separate the daughter cells at the end of mitosis. This crucial process requires the assembly and ingression of an actomyosin ring, which must occur with high fidelity to avoid aneuploidy and cell fate changes. Most of our knowledge of mammalian cytokinesis was generated using over-expressed transgenes in HeLa cells. Over-expression can introduce artefacts, while HeLa are cancerous human cells that have lost their epithelial identity, and the mechanisms controlling cytokinesis in these cells could be vastly different from other cell types. Here, we tagged endogenous anillin, Ect2 and RhoA with mNeonGreen and characterized their localization during cytokinesis for the first time in live human cells. Comparing anillin localization in multiple cell types revealed cytokinetic diversity with differences in the duration and symmetry of ring closure, and the timing of cortical recruitment. Our findings show that the breadth of anillin correlates with the rate of ring closure, and support models where cell size or ploidy affects the cortical organization, and intrinsic mechanisms control the symmetry of ring closure. This work highlights the need to study cytokinesis in more diverse cell types, which will be facilitated by the reagents generated for this study.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".