Nocodazole-Induced Expression and Phosphorylation of Anillin and Other Mitotic Proteins Are Decreased in DNA-Dependent Protein Kinase Catalytic Subunit-Deficient Cells and Rescued by Inhibition of the Anaphase-Promoting Complex/Cyclosome with proTAME but Not Apcin
Bibliographic record
Abstract
The DNA-dependent protein kinase catalytic subunit (DNA-PKcs) has well-established roles in DNA double-strand break repair, and recently, nonrepair functions have also been reported. To better understand its cellular functions, we deleted DNA-PKcs from HeLa and A549 cells using CRISPR/Cas9. The resulting cells were radiation sensitive, had reduced expression of ataxia-telangiectasia mutated (ATM), and exhibited multiple mitotic defects. Mechanistically, nocodazole-induced upregulation of cyclin B1, anillin, and securin was decreased in DNA-PKcs-deficient cells, as were phosphorylation of Aurora A on threonine 288, phosphorylation of Polo-like kinase 1 (PLK1) on threonine 210, and phosphorylation of targeting protein for Xenopus Klp2 (TPX2) on serine 121. Moreover, reduced nocodazole-induced expression of anillin, securin, and cyclin B1 and phosphorylation of PLK1, Aurora A, and TPX2 were rescued by inhibition of the anaphase-promoting complex/cyclosome (APC/C) by proTAME, which prevents binding of the APC/C-activating proteins Cdc20 and Cdh1 to the APC/C. Altogether, our studies suggest that loss of DNA-PKcs prevents inactivation of the APC/C in nocodazole-treated cells.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".