Regulation of the actin cytoskeleton by the Ndel1-Tara complex is critical for cell migration
Bibliographic record
Abstract
Nuclear distribution element-like 1 (Ndel1) plays pivotal roles in diverse biological processes and is implicated in the pathogenesis of multiple neurodevelopmental disorders. Ndel1 function by regulating microtubules and intermediate filaments; however, its functional link with the actin cytoskeleton is largely unknown. Here, we show that Ndel1 interacts with TRIO-associated repeat on actin (Tara), an actin-bundling protein, to regulate cell movement. In vitro wound healing and Boyden chamber assays revealed that Ndel1- or Tara-deficient cells were defective in cell migration. Moreover, Tara overexpression induced the accumulation of Ndel1 at the cell periphery and resulted in prominent co-localization with F-actin. This redistribution of Ndel1 was abolished by deletion of the Ndel1-interacting domain of Tara, suggesting that the altered peripheral localization of Ndel1 requires a physical interaction with Tara. Furthermore, co-expression of Ndel1 and Tara in SH-SY5Y cells caused a synergistic increase in F-actin levels and filopodia formation, suggesting that Tara facilitates cell movement by sequestering Ndel1 at peripheral structures to regulate actin remodeling. Thus, we demonstrated that Ndel1 interacts with Tara to regulate cell movement. These findings reveal a novel role of the Ndel1-Tara complex in actin reorganization during cell movement.
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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 | 0.001 |
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".