Using a Novel Partitivirus in Pseudogymnoascus destructans to Understand the Epidemiology of White-Nose Syndrome
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
White-nose syndrome is one of the most lethal wildlife diseases, killing over 5 million North American bats since it was first reported in 2006. The causal agent of the disease is a psychrophilic filamentous fungus, Pseudogymnoascus destructans. The fungus is widely distributed in North America and Europe and has recently been found in some parts of Asia, but interestingly, no mass mortality is observed in European or Asian bats. Here we report a novel double-stranded RNA virus found in North American isolates of the fungus and show that the virus can be used as a tool to study the epidemiology of White-nose syndrome. The virus, termed Pseudogymnoascus destructans partitivirus-pa, contains 2 genomic segments, dsRNA 1 and dsRNA 2 of 1.76 kbp and 1.59 kbp respectively, each possessing a single open reading frame, and forms isometric particles approximately 30 nm in diameter, characteristic of the genus Gammapartitivirus in the family Partitiviridae. Phylogenetic analysis revealed that the virus is closely related to Penicillium stoloniferum virus S. We were able to cure P. destructans of the virus by treating fungal cultures with polyethylene glycol. Examination of 62 isolates of P. destructans including 35 from United States, 10 from Canada and 17 from Europe showed virus infection only in North American isolates of the fungus. Bayesian phylogenetic analysis using nucleotide sequences of the viral coat protein geographically clustered North American isolates indicating fungal spread followed by local adaptation of P. destructans in different regions of the United States and Canada. This is the first demonstration that a mycovirus potentially can be used to study fungal disease epidemiology.
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.
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 | 0.001 |
| 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 it