Antagonism of Type I Interferon Responses by New World Hantaviruses
Bibliographic record
Abstract
Evasion of interferon (IFN)-mediated antiviral signaling is a common defense strategy for pathogenic RNA viruses. To date, research on IFN antagonism by hantaviruses is limited and has focused on only a subset of the numerous recognized hantavirus species. The host IFN response has two phases, an initiation phase, resulting in the induction of alpha/beta IFN (IFN-α/β), and an amplification phase, whereby IFN-α/β signals through the Jak/STAT pathway, resulting in the establishment of the cellular antiviral state. We examined interactions between these critical host responses and the New World hantaviruses. We observed delayed cellular responses in both Andes virus (ANDV)- and Sin Nombre virus (SNV)-infected A549 and Huh7-TLR3 cells. We found that IFN-β induction is inhibited by coexpression of ANDV nucleocapsid protein (NP) and glycoprotein precursor (GPC) and is robustly inhibited by SNV GPC alone. Downstream amplification by Jak/STAT signaling is also inhibited by SNV GPC and by either NP or GPC of ANDV. Therefore, ANDV- and SNV-encoded proteins have the potential for inhibiting both IFN-β induction and signaling, with SNV exhibiting the more potent antagonism ability. Herein we identify ANDV NP, a previously unrecognized inhibitor of Jak/STAT signaling, and show that IFN antagonism by ANDV relies on expression of both the glycoproteins and NP, whereas the glycoproteins appear to be sufficient for antagonism by SNV. These data suggest that IFN antagonism strategies by hantaviruses are quite variable, even between species with similar disease phenotypes, and may help to better elucidate species-specific pathogenesis.
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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) | 0.000 | 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 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".