The NIMA-family kinase, Nek1 affects the stability of centrosomes and ciliogenesis
Bibliographic record
Abstract
BACKGROUND: Mutations in Nek1 (NIMA-Related Kinase 1) are causal in the murine models of polycystic kidney disease kat and kat2J. The Neks are known as cell cycle kinases, but recent work in protists has revealed that in addition to roles in the regulation of cell cycle progression, some Neks also regulate cilia. In most cells, cilia are disassembled prior to mitosis and are regenerated after cytokinesis. We propose that Neks participate in the coordination of ciliogenesis with cell cycle progression. Mammalian Nek1 is a candidate for this activity because renal cysts form in response to dysfunctional ciliary signalling. RESULTS: Here we report that over-expression of full-length mNek1 inhibited ciliogenesis without disrupting centrosomes in the murine renal epithelial cell line IMCD3. In contrast, over-expression of the kinase domain with its associated basic region, but without the acidic domain, caused loss of centrosomes. As expected, these cells also failed to grow cilia. Both defective ciliogenesis in response to too much mNek1 and disassembly of centrosomes in response to expression of the kinase lacking the presumptive regulatory domain was abrogated by kinase-inactivating mutations or by removal of the coiled-coil domain. We observed that kinase-inactive, C-terminal truncations of mNek1 retaining the coiled-coil domain localized to the cilium, and we define a ciliary targeting region within the coiled-coil domain. CONCLUSION: Based on our data, we propose that Nek1 plays a role in centrosome integrity, affecting both ciliogenesis and centrosome stability.
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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".