Myosin 2 drives actin contractility in fast-crawling species outside of the amorphean lineage
Bibliographic record
Abstract
Myosin 2-dependent actin contractility drives essential cell functions, including fast-crawling motility in animal cells, Dictyostelium amoebae, and other species from the Amorphea lineage. Whether and how species outside this single eukaryotic group can generate contractile actin networks has been largely unexplored. We demonstrate that Naegleria, an amoeba from the Heterolobosea-an evolutionarily distant eukaryotic lineage that includes cells that are among the fastest known crawling eukaryotes-expresses three distinct myosin 2 homologs. Using functional assays and immunofluorescence, we show that these myosin 2 proteins bind cellular actin networks and that these networks generate ATP-dependent contractility. By identifying additional myosin 2 homologs in dozens of additional heterolobosean amoebae (but not obligate flagellates), we find a widespread correlation within this group between crawling behavior and contractile actin networks. This correlation includes the amoeba Vahlkampfia avara, which we demonstrate can crawl at speeds exceeding 180 μm/min and has contractile actin networks and myosin 2 homologs. These findings show that myosin 2-driven contractility exists beyond Amorphea and is associated with diverse, fast-crawling cell types. Expanding the taxonomic breadth of actin network contractility impacts our basic understanding of cell motility, evolutionary biology, and the fundamental biology of human pathogens that rely on fast cell migration.
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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) | 0.000 | 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".