A novel application of RNase H2-dependent quantitative PCR for detection and quantification of Grosmannia clavigera, a mountain pine beetle fungal symbiont, in environmental samples
Bibliographic record
Abstract
Mountain pine beetle (Dendroctonus ponderosae Hopkins; MPB) is an economically and ecologically important pest of pine species in western North America. Mountain pine beetles form complex multipartite relationships with microbial partners, including the ophiostomoid fungi Grosmannia clavigera (Robinson-Jeffrey and Davidson) Zipfel, de Beer and Wingfield, Ophiostoma montium (Rumbold) von Arx, Grosmannia aurea (Robinson-Jeffrey and Davidson) Zipfel, de Beer and Wingfield, Leptographium longiclavatum (Lee, Kim, and Breuil) and Leptographium terebrantis (Barras and Perry). These fungi are vectored by MPB to new pine hosts, where the fungi overcome host defenses to grow into the sapwood. A tree's relative susceptibility to these fungi is conventionally assessed by measuring lesions that develop in response to fungal inoculation. However, these lesions represent a symptom of infection, representing both fungal growth and tree defense capacity. In order to more objectively assess fungal virulence and host tree susceptibility in studies of host-pathogen interactions, a reliable, consistent, sensitive method is required to accurately identify and quantify MPB-associated fungal symbionts in planta. We have adapted RNase H2-dependent PCR, a technique originally designed for rare allele discrimination, to develop a novel RNase H2-dependent quantitative PCR (rh-qPCR) assay that shows greater specificity and sensitivity than previously published PCR-based methods to quantify MPB fungal symbionts in pine xylem and MPB whole beetles. Two sets of assay probes were designed: one that amplifies a broad range of ophiostomoid species, and a second that amplifies G. clavigera but not other MPB-associated ophiostomoid species. Using these primers to quantify G. clavigera in pine stems, we provide evidence that lesion length does not accurately reflect the extent of fungal colonization along the stem nor the quantity of fungal growth within this colonized portion of stem. The sensitivity, specificity, reproducibility, cost effectiveness and high-throughput potential of the rh-qPCR assay makes the technology suitable for identification and quantification of a wide array of pathogenic and beneficial microbes that form associations with plants and other organisms, even when the microbial partner is present in low abundance.
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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 | 0.000 |
| 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 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".