Inhibition of CHK2 dependent DNA damage response suppresses Zika virus infection through a STING dependent mechanism
Bibliographic record
Abstract
ABSTRACT Zika virus (ZIKV) is a mosquito-borne flavivirus that causes neurological disorders and microcephaly. Recent research has shown that ZIKV causes cell cycle arrest and DNA damage response in neuronal progenitor cells that potentially leads to congenital neurodevelopmental defects. However, the specific role of regulators that control DNA damage response to ZIKV infection and the related mechanisms remain largely unknown. Here through both in vitro and in vivo studies, we observe that ZIKV induces DNA damage response in both human cell line and mouse embryo. When CHK2 dependent DNA damage response pathway is inhibited by a small molecule inhibitor or genetic deletion, ZIKV production is reduced and the embryonic developmental defects are rescued. Furthermore, we demonstrate that in ZIKV infected Chk2-/- mice, the reduced viral load correlates with elevated antiviral innate immune response which is found to be dependent on the STING signaling pathway. Collectively, our study reveals a specific role of CHK2 for ZIKV infection and pathogenesis, demonstrating a mechanism that inhibition of the CHK2 axis suppresses ZIKV infection through the STING-dependent antiviral pathway, thus providing a new therapeutic strategy against ZIKV. These findings also suggest the intriguing possibility that ZIKV evolved to orchestrate DNA damage response factors to create a beneficial environment for its infection in the host 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".