Mycobiome of the Bat White Nose Syndrome Affected Caves and Mines Reveals Diversity of Fungi and Local Adaptation by the Fungal Pathogen Pseudogymnoascus (Geomyces) destructans
Bibliographic record
Abstract
Current investigations of bat White Nose Syndrome (WNS) and the causative fungus Pseudogymnoascus (Geomyces) destructans (Pd) are intensely focused on the reasons for the appearance of the disease in the Northeast and its rapid spread in the US and Canada. Urgent steps are still needed for the mitigation or control of Pd to save bats. We hypothesized that a focus on fungal community would advance the understanding of ecology and ecosystem processes that are crucial in the disease transmission cycle. This study was conducted in 2010-2011 in New York and Vermont using 90 samples from four mines and two caves situated within the epicenter of WNS. We used culture-dependent (CD) and culture-independent (CI) methods to catalogue all fungi ('mycobiome'). CD methods included fungal isolations followed by phenotypic and molecular identifications. CI methods included amplification of DNA extracted from environmental samples with universal fungal primers followed by cloning and sequencing. CD methods yielded 675 fungal isolates and CI method yielded 594 fungal environmental nucleic acid sequences (FENAS). The core mycobiome of WNS comprised of 136 operational taxonomic units (OTUs) recovered in culture and 248 OTUs recovered in clone libraries. The fungal community was diverse across the sites, although a subgroup of dominant cosmopolitan fungi was present. The frequent recovery of Pd (18% of samples positive by culture) even in the presence of dominant, cosmopolitan fungal genera suggests some level of local adaptation in WNS-afflicted habitats, while the extensive distribution of Pd (48% of samples positive by real-time PCR) suggests an active reservoir of the pathogen at these sites. These findings underscore the need for integrated disease control measures that target both bats and Pd in the hibernacula for the control of WNS.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".