Dynasore enhances the formation of mitochondrial antiviral signalling aggregates and endocytosis‐independent <scp>NF</scp>‐κ<scp>B</scp> activation
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Dynasore has been used extensively as an inhibitor of clathrin-mediated endocytosis. While studying the role of endocytosis in LPS-induced signalling events, we discovered that dynasore itself induced activation of NF-κB, independently of its effects on endocytosis and without involving the Toll-like receptor 4 signalling pathways. The purpose of this study was to characterize this novel effect and to explore the underlying mechanism of action. EXPERIMENTAL APPROACH: We utilized gel electrophoresis, microscopy, gene knockdown and luciferase-based promoter activity to evaluate the effect of dynasore on cell signalling pathways and to delineate the mechanisms involved in its effects, KEY RESULTS: Dynasore activated the NF-κB and IFN-β pathways by activating mitochondrial antiviral signalling protein (MAVS). We showed that MAVS is activated by NOX/Rac and forms high molecular weight aggregates, similar to that observed in response to viral infection. We also demonstrated that dynasore-induced activation of JNK occurs downstream of MAVS and is required for activation of NF-κB and IFN-β. CONCLUSION AND IMPLICATIONS: These findings demonstrate a novel effect of dynasore on cell signalling. We describe a novel Rac1-, ROS- and MAVS-mediated signalling cascade through which dynasore dramatically activates NF-κB, mimicking the viral induction of this key inflammatory signalling pathway. Our results call attention to the need for a broader interpretation of results when dynasore is used in its traditional fashion as an inhibitor of clathrin-mediated endocytosis. These results suggest the intriguing possibility that dynasore or one of its analogues might be of value as an antiviral therapeutic strategy or vaccine adjuvant.
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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) | 0.001 | 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".