Ebola Zaire Virus Blocks Type I Interferon Production by Exploiting the Host SUMO Modification Machinery
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Ebola Zaire virus is highly pathogenic for humans, with case fatality rates approaching 90% in large outbreaks in Africa. The virus replicates in macrophages and dendritic cells (DCs), suppressing production of type I interferons (IFNs) while inducing the release of large quantities of proinflammatory cytokines. Although the viral VP35 protein has been shown to inhibit IFN responses, the mechanism by which it blocks IFN production has not been fully elucidated. We expressed VP35 from a mouse-adapted variant of Ebola Zaire virus in murine DCs by retroviral gene transfer, and tested for IFN transcription upon Newcastle Disease virus (NDV) infection and toll-like receptor signaling. We found that VP35 inhibited IFN transcription in DCs following these stimuli by disabling the activity of IRF7, a transcription factor required for IFN transcription. By yeast two-hybrid screens and coimmunoprecipitation assays, we found that VP35 interacted with IRF7, Ubc9 and PIAS1. The latter two are the host SUMO E2 enzyme and E3 ligase, respectively. VP35, while not itself a SUMO ligase, increased PIAS1-mediated SUMOylation of IRF7, and repressed Ifn transcription. In contrast, VP35 did not interfere with the activation of NF-kappaB, which is required for induction of many proinflammatory cytokines. Our findings indicate that Ebola Zaire virus exploits the cellular SUMOylation machinery for its advantage and help to explain how the virus overcomes host innate defenses, causing rapidly overwhelming infection to produce a syndrome resembling fulminant septic shock.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it