Induction of antiviral gene expression by cyclosporine A, but not inhibition of cyclophilin A or B, contributes to its restriction of human coronavirus 229E infection in a lung epithelial cell line
Bibliographic record
Abstract
The development of antivirals with an extended spectrum of activity is an attractive possibility to protect against future emerging coronaviruses (CoVs). Cyclosporine A (CsA), a clinically approved immunosuppressive drug, has established antiviral activity against diverse unrelated viruses, including several CoVs. However, its antiviral mechanisms of action against CoV infection have remained elusive, precluding the rational design of non-immunosuppressive derivatives with improved antiviral activities. In this study, we evaluated the mechanisms of CsA against HCoV-229E infection in a human lung epithelial cell line. We demonstrate that the antiviral activity of CsA against HCoV-229E is independent of classical CsA target proteins, cyclophilin A or B, which are not required host factors for HCoV-229E in A549 cells. Instead, CsA treatment induces expression of antiviral genes in a manner dependent on interferon regulatory factor 1, but independent of classical interferon responses, which contributes to its inhibitory effect against HCoV-229E infection. Our results also point to a role for the HCoV-229E nucleoprotein in antagonizing activation of type I interferon, but we show that CsA treatment does not affect evasion of innate immune signalling pathways by HCoV-229E. Overall, our findings further the understanding of the antiviral mechanisms of CsA against CoV infection and highlight a novel immunomodulatory strategy to inhibit CoV infection that may inform future drug development efforts.
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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 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".