Ku suppresses RNA-mediated innate immune responses in human cells to accommodate primate-specific Alu expansion
Bibliographic record
Abstract
Summary Ku70 and Ku80 form Ku, a ring-shaped protein that initiates the non-homologous end-joining (NHEJ) DNA repair pathway. 1 Specifically, Ku binds to double-stranded DNA (dsDNA) ends and recruits other NHEJ factors ( e.g. , DNA-PKcs and LIG4). While Ku binds to double-stranded RNA (dsRNA) 2 and traps mutated-DNA-PKcs on ribosomal RNA in vivo, 3,4 the physiological significance of Ku-dsRNA interactions in otherwise wild-type cells remains elusive. Intriguingly, while dispensable for murine development, 5,6 Ku is essential in human cells. 7 Despite similar genome sizes, human cells express ∼100-fold more Ku than mouse cells, implying functions beyond NHEJ, possibly through a dose-sensitive interaction with dsRNA, which is ∼100 times weaker than with dsDNA. 2,8 While investigating the essentiality of Ku in human cells, we found that depletion of Ku - unlike LIG4 - induces profound interferon (IFN) and NF-kB responses reliant on the dsRNA-sensor MDA5/RIG-I and adaptor MAVS. Prolonged Ku-degradation also activates other dsRNA-sensors, e.g. PKR that suppresses protein translation, and OAS/RNaseL that cleaves rRNAs and eventually induces growth arrest and cell death. MAVS, RIG-I, or MDA5 knockouts suppressed IFN signaling and, together with PKR knockouts, partially rescued Ku-depleted human cells. Ku-irCLIP analyses revealed that Ku binds to diverse dsRNA, predominantly stem-loops in primate-specific Alu elements 9 at anti-sense orientation in introns and 3’-UTRs. Ku expression rose sharply in higher primates tightly correlating with Alu-expansion (r = 0.94/0.95). Together, our study identified a vital role of Ku in accommodating Alu-expansion in primates by mitigating a dsRNA-induced innate immune response, explaining the rise of Ku levels and its essentiality in human 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) | 0.000 | 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".