Predator-prey transmission of a gammaherpesvirus from Asian badgers (Meles leucurus) to endangered Amur tigers (Panthera tigris altaica)
Bibliographic record
Abstract
We sought to identify herpesviruses in wild Amur tigers (Panthera tigris altaica) of the Russian Far East in and near the Sikhote-Alin Biosphere Zapovednik protected area. We used multiple herpesvirus consensus PCRs targeting the glycoprotein B and DNA polymerase genes followed by DNA sequencing to test blood samples collected over a 22-year period. We found identical herpesvirus sequences in 3 of 41 tigers by consensus PCR and 8 of 41 tigers (19.5%) using a virus-specific PCR. Persistent infection was demonstrated in a tiger that remained virus DNA-positive in three blood samples over a 2.5-year period. Surprisingly, the viral DNA sequence present in tigers had 98.8% identity to mustelid gammaherpesvirus 1 (MusGHV1) commonly found in European badgers (Meles meles), which do not range to the Russian Far East. We then tested 69 blood samples from 11 other carnivore species collected in this region and found that 81.0% (17/21) of Asian badgers (Meles leucurus), but no other species, had MusGHV1 sequences with 99.8-100% identity to those found in tigers. Interaction between Amur tigers and Asian badgers is supported by previous studies demonstrating that badgers are a common prey species for tigers in this region. Taken together, these results are consistent with the interpretation that a strain of MusGHV1 common in Asian badgers was transmitted via predator-prey interactions to Amur tigers. While gammaherpesviruses are generally thought to exhibit strong host species-specificity, our results present an example of cross-species transmission and one of the first examples, to our knowledge, of gammaherpesvirus predator-prey transmission. In addition, we identified novel gammaherpesviruses in sable (Martes zibellina), Asiatic black bear (Ursus thibetanus), and brown bear (Ursus arctos).
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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 | 0.001 | 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".