Epstein-Barr Virus Interferes with the Amplification of IFNα Secretion by Activating Suppressor of Cytokine Signaling 3 in Primary Human Monocytes
Bibliographic record
Abstract
BACKGROUND: Epstein-Barr virus is recognized to cause lymphoproliferative disorders and is also associated with cancer. Evidence suggests that monocytes are likely to be involved in EBV pathogenesis, especially due to a number of cellular functions altered in EBV-infected monocytes, a process that may affect efficient host defense. Because type I interferons (IFNs) are crucial mediators of host defense against viruses, we investigated the effect of EBV infection on the IFNalpha pathway in primary human monocytes. METHODOLOGY/PRINCIPAL FINDINGS: Infection of monocytes with EBV induced IFNalpha secretion but inhibited the positive feedback loop for the amplification of IFNalpha. We showed that EBV infection induced the expression of suppressor of cytokine signaling 3 (SOCS3) and, to a lesser extent, SOCS1, two proteins known to interfere with the amplification of IFNalpha secretion mediated by the JAK/STAT signal transduction pathway. EBV infection correlated with a blockage in the activation of JAK/STAT pathway members and affected the level of phosphorylated IFN regulatory factor 7 (IRF7). Depletion of SOCS3, but not SOCS1, by small interfering RNA (siRNA) abrogated the inhibitory effect of EBV on JAK/STAT pathway activation and significantly restored IFNalpha secretion. Finally, transfection of monocytes with the viral protein Zta caused the upregulation of SOCS3, an event that could not be recapitulated with mutated Zta. CONCLUSIONS/SIGNIFICANCE: We propose that EBV protein Zta activates SOCS3 protein as an immune escape mechanism that both suppresses optimal IFNalpha secretion by human monocytes and favors a state of type I IFN irresponsiveness in these cells. This immunomodulatory effect is important to better understand the aspects of the immune response to EBV.
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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 | 0.001 |
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".