Culturing and direct DNA extraction find different fungi from the same ericoid mycorrhizal roots
Bibliographic record
Abstract
• This study compares DNA and culture-based detection of fungi from 15 ericoid mycorrhizal roots of salal (Gaultheria shallon), from Vancouver Island, BC Canada. • From the 15 roots, we PCR amplified fungal DNAs and analyzed 156 clones that included the internal transcribed spacer two (ITS2). From 150 different subsections of the same roots, we cultured fungi and analyzed their ITS2 DNAs by RFLP patterns or sequencing. We mapped the original position of each root section and recorded fungi detected in each. • Phylogenetically, most cloned DNAs clustered among Sebacina spp. (Sebacinaceae, Basidiomycota). Capronia sp. and Hymenoscyphus erica (Ascomycota) predominated among the cultured fungi and formed intracellular hyphal coils in resynthesis experiments with salal. • We illustrate patterns of fungal diversity at the scale of individual roots and compare cloned and cultured fungi from each root. Indicating a systematic culturing detection bias, Sebacina DNAs predominated in 10 of the 15 roots yet Sebacina spp. never grew from cultures from the same roots or from among the > 200 ericoid mycorrhizal fungi previously cultured from different roots from the same site.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".