Cellularization in chytrid fungi uses distinct mechanisms from conventional cytokinesis and cellularization in animals and yeast
Bibliographic record
Abstract
Chytrid fungi provide a model for studying foam-like cellularization, where nuclei that are dispersed throughout the cytoplasm are synchronously compartmentalized into daughter cells. This organization poses geometric challenges not faced by cells undergoing conventional cytokinesis or Drosophila monolayer cellularization, where nuclei are organized in linear or planar arrangements with ready access to the plasma membrane. We use the chytrid Spizellomyces punctatus to show that chytrid cellularization begins with migration of nuclei and their attached centrosomes to the plasma membrane, where centrosome-associated vesicles mark sites of membrane invagination. These vesicles then extend inward, resulting in tubular furrows that branch and merge to create a honeycomb of polyhedral membrane compartments-a cellularization foam-each with a nucleus and cilium. Using inhibitors and laser ablation, we show that tensile forces produced by actomyosin networks drive aphrogenesis (foam generation), while microtubules are important for foam patterning and ciliogenesis but are not essential for cellularization. Finally, we suggest that chytrids may have incorporated ancestral mechanisms associated with ciliogenesis to coordinate the association of internal nuclei with membrane furrows to solve the unique geometric challenges associated with aphrogenic cellularization.
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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".