Noncanonical functions of Ku may underlie essentiality in human cells
Bibliographic record
Abstract
The Ku70/80 heterodimer is a key player in non-homologous end-joining DNA repair but is involved in other cellular functions like telomere regulation and maintenance, in which Ku's role is not fully characterized. It was previously reported that knockout of Ku80 in a human cell line results in lethality, but the underlying cause of Ku essentiality in human cells has yet to be fully explored. Here, we established conditional Ku70 knockout cells using CRISPR/Cas9 editing to study the essentiality of Ku70 function. While we observed loss of cell viability upon Ku depletion, we did not detect significant changes in telomere length, nor did we record lethal levels of DNA damage upon loss of Ku. Analysis of global proteome changes following Ku70 depletion revealed dysregulations of several cellular pathways including cell cycle/mitosis, RNA related processes, and translation/ribosome biogenesis. Our study suggests that the driving cause of loss of cell viability in Ku70 knockouts is not linked to the functions of Ku in DNA repair or at telomeres. Moreover, our data shows that loss of Ku affects multiple cellular processes and pathways and suggests that Ku plays critical roles in cellular processes beyond DNA repair and telomere maintenance to maintain cell viability.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".