Bat-specific adaptations in interferon signaling and GBP1 contribute to enhanced antiviral capacity
Bibliographic record
Abstract
Bats are reservoirs of emerging zoonotic viruses that may cause severe disease in humans and agricultural animals. However, it is poorly understood how bats can tolerate diverse viral infections. Here, we characterized type I interferon response pathways in kidney cell lines derived from two divergent bat species, Pteropus alecto and Eptesicus fuscus, identifying distinct mechanisms underlying their enhanced control of viral infection. We demonstrate the critical roles of STAT1/STAT2 in IFNβ signaling, along with species-specific adaptations that contribute towards a steady and ready antiviral state. Unlike in humans, bat IFNβ signaling processes resist the immune antagonistic properties of MERS-CoV which further explains the ability of bats to tolerate coronavirus infections. Transcriptomic analysis on interferon stimulated cell lines identified canonical and non-canonical interferon stimulated genes including two differentially expressed genes, IFIT1 and GBP1, that exhibit enhanced antiviral activity against a wide range of viruses, including the bat-derived Eptesipoxvirus. We have identified a functional (AV1) motif within E. fuscus GBP1 that restricts Eptesipoxvirus replication. Ultimately, our work provides important insights into the evolution of enhanced interferon-mediated antiviral responses in bats, contributing to their ability to resist viral diseases. Bats harbor diverse viruses but it’s less clear how they tolerate infection. Here, by characterizing innate immune responses in bat cells the authors show that IFN-beta signaling resists antagonistic activity by viruses and identify interferon stimulated genes with enhanced antiviral activity.
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How this classification was reachedexpand
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 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".