Human Stimulator of Interferon Genes Promotes Rhinovirus C Replication in Mouse Cells In Vitro and In Vivo
Bibliographic record
Abstract
Rhinovirus C (RV-C) infects airway epithelial cells and is an important cause of acute respiratory disease in humans. To interrogate the mechanisms of RV-C-mediated disease, animal models are essential. Towards this, RV-C infection was recently reported in wild-type (WT) mice, yet, titers were not sustained. Therefore, the requirements for RV-C infection in mice remain unclear. Notably, prior work has implicated human cadherin-related family member 3 (CDHR3) and stimulator of interferon genes (STING) as essential host factors for virus uptake and replication, respectively. Here, we report that even though human (h) and murine (m) CDHR3 orthologs have similar tissue distribution, amino acid sequence homology is limited. Further, while RV-C can replicate in mouse lung epithelial type 1 (LET1) cells and produce infectious virus, we observed a significant increase in the frequency and intensity of dsRNA-positive cells following hSTING expression. Based on these findings, we sought to assess the impact of hCDHR3 and hSTING on RV-C infection in mice in vivo. Thus, we developed hCDHR3 transgenic mice, and utilized adeno-associated virus (AAV) to deliver hSTING to the murine airways. Subsequent challenge of these mice with RV-C15 revealed significantly higher titers 24 h post-infection in mice expressing both hCDHR3 and hSTING-compared to either WT mice, or mice with hCDHR3 or hSTING alone, indicating more efficient infection. Ultimately, this mouse model can be further engineered to establish a robust in vivo model, recapitulating viral dynamics and disease.
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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 | 0.001 | 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 | 0.001 |
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".