Reviewer #2 (Public Review): SARS-CoV-2 NSP13 interacts with TEAD to suppress Hippo-YAP signaling
Bibliographic record
Abstract
The Hippo pathway is critical to organ development, homeostasis, and regeneration, facilitated by YAP/TEAD-mediated gene expression. Although emerging studies report Hippo-YAP dysfunction after viral infection, it is largely unknown in the context of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Here, we analyzed RNA sequencing data from SARS-CoV-2 infected human lung samples and induced pluripotent stem cell–derived cardiomyocytes (iPSC-CMs), and observed a decrease in YAP target gene expression. In screening SARS-CoV-2 nonstructural proteins, we found that nonstructural protein 13 (NSP13), a conserved coronavirus helicase, inhibited YAP transcriptional activity independent of the upstream Hippo kinases LATS1/2. Consistently, introducing NSP13 into cardiomyocytes suppressed active YAP (YAP5SA) in vivo. Subsequent investigations on NSP13 mutants indicated that NSP13 helicase activity is crucial for suppressing YAP transactivation. Mechanistically, TEAD4 serves as a platform for recruiting NSP13 and YAP. NSP13 inactivates the YAP/TEAD4 transcription complex through its interacting proteins, such as transcription termination factor 2 (TTF2). These discoveries reveal a novel YAP/TEAD regulatory mechanism orchestrated by TEAD4, which provides molecular insights of Hippo-YAP regulation after SARS-CoV-2 infection.
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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 | 0.023 | 0.112 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.020 | 0.007 |
| Insufficient payload (model declined to judge) | 0.095 | 0.047 |
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".