Alternative splicing expands the antiviral IFITM repertoire in Chinese rufous horseshoe bats
Bibliographic record
Abstract
Species-specific interferon responses are shaped by the virus-host arms race. The human interferon-induced transmembrane protein (IFITM) family consists of three antiviral IFITM genes that arose by gene duplication. These genes restrict virus entry and are key players in antiviral interferon responses. The unique IFITM repertoires in different species influence their resistance to viral infections, but the role of IFITMs in shaping the enhanced antiviral immunity of reservoir bat species is unclear. Here, we identified an IFITM gene in Chinese rufous horseshoe bat, a natural host of severe acute respiratory syndrome (SARS)-related coronaviruses, that is alternatively spliced to produce two IFITM isoforms in native cells as shown by transcriptomics. These bat IFITMs have conserved structures in vitro as demonstrated by circular dichroism spectroscopy, yet they exhibit distinct antiviral specificities against influenza A virus, Nipah virus and coronaviruses including SARS-CoV, SARS-CoV-2 and MERS-CoV. In parallel with human IFITM1-3, bat IFITM isoforms localize to distinct sites of virus entry which influences their antiviral potency. Further bioinformatic analysis of IFITM repertoires in 206 mammals reveals that alternative splicing is a recurring strategy for IFITM diversification, albeit less widely adopted than gene duplication. These findings demonstrate that alternative splicing is a key strategy for evolutionary diversification in the IFITM family. Our study also highlights an example of convergent evolution where species-specific selection pressures led to expansion of the IFITM family through multiple means, underscoring the importance of IFITM diversity as a component of innate immunity.
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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".