Activation of cGAS-STING suppresses coxsackievirus replication via interferon-dependent signaling
Bibliographic record
Abstract
Coxsackievirus B3 (CVB3) is a non-enveloped, single-stranded, positive RNA virus known for its role in provoking inflammatory diseases that affect the heart, pancreas, and brain, leading to conditions such as myocarditis, pancreatitis, and meningitis. Currently, there are no FDA-approved drugs treating CVB3 infection; therefore, identifying potential molecular targets for antiviral drug development is imperative. In this study, we examined the possibility of activating the cyclic GMP-AMP (cGAMP) synthase (cGAS)-stimulator of interferon genes (STING) pathway, a cytosolic DNA-sensing pathway that triggers a type-I interferon (IFN) response, in inhibiting CVB3 infection. We found that activation of the cGAS-STING pathway through the application of cGAS (poly dA:dT and herring testes DNA) or STING agonists (2'3'-cGAMP and diamidobenzimidazole), or the overexpression of STING, significantly suppresses CVB3 replication. Conversely, gene-silencing of STING enhances viral replication. Mechanistically, we demonstrated that cGAS-STING activation combats CVB3 infection by inducing IFN response. Notably, we discovered that knockdown of IFN-α/β receptor, a key membrane receptor in type-I IFN signaling, or inhibition of the downstream JAK1/2 signaling with ruxolitinib, mitigates the effects of STING activation, resulting in increased viral protein production. Furthermore, we investigated the interplay between CVB3 and the cGAS-STING pathway. We showed that CVB3 does not trigger cGAS-STING activation; instead, it antagonizes STING and the downstream TBK1 activation induced by cGAMP. In summary, our results provide insights into the interaction of an RNA virus and the DNA-sensing pathway, highlighting the potential for agonist activation of the cGAS-STING pathway in the development of anti-CVB3 drugs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".