Evaluation of bat adenoviruses suggests co-evolution and host roosting behaviour as drivers for diversity
Bibliographic record
Abstract
Adenoviruses (AdVs) are diverse pathogens of humans and animals, with several dozen bat AdVs already identified. Considering that over 100 human AdVs are known, and the huge diversity of bat species, many bat AdVs likely remain undiscovered. To learn more about AdV prevalence, diversity and evolution, we sampled and tested bats in Cameroon using several PCR assays for viral and host DNA. AdV DNA was detected in 14 % of the 671 sampled animals belonging to 37 different bat species. There was a correlation between species roosting in larger groups and AdV DNA detection. The detected AdV DNA belonged to between 28 and 44 different, mostly previously unknown, mastadenovirus species. The novel isolates are phylogenetically diverse and while some cluster with known viruses, others appear to form divergent new clusters. The phylogenetic tree of novel and previously known bat AdVs does not mirror that of the various host species, but does contain structures consistent with a degree of virus-host co-evolution. Given that closely related isolates were found in different host species, it seems likely that at least some bat AdVs have jumped species barriers, probably in the more recent past; however, the tree is also consistent with such events having taken place throughout bat AdV evolution. AdV diversity was highest in bat species roosting in large groups. The study significantly increased the diversity of AdVs known to be harboured by bats, and suggests that host behaviours, such as roosting size, may be what limits some AdVs to one species rather than an inability of AdVs to infect other related hosts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".