A specialized <scp>ABC</scp> efflux transporter <scp>G</scp>c<scp>ABC</scp>‐<scp>G</scp>1 confers monoterpene resistance to <i><scp>G</scp>rosmannia clavigera</i>, a bark beetle‐associated fungal pathogen of pine trees
Bibliographic record
Abstract
Grosmannia clavigera is a bark beetle-vectored pine pathogen in the mountain pine beetle epidemic in western North America. Grosmannia clavigera colonizes pines despite the trees' massive oleoresin terpenoid defences. We are using a functional genomics approach to identify G. clavigera's mechanisms of adaptation to pine defences. We annotated the ABC transporters in the G. clavigera genome and generated RNA-seq transcriptomes from G. clavigera grown with a range of terpenes. We functionally characterized GcABC-G1, a pleiotropic drug resistance (PDR) transporter that was highly induced by terpenes, using qRT-PCR, gene knock-out and heterologous expression in yeast. Deleting GcABC-G1 increased G. clavigera's sensitivity to monoterpenes and delayed development of symptoms in inoculated young lodgepole pine trees. Heterologous expression of GcABC-G1 in yeast increased tolerance to monoterpenes. G. clavigera but not the deletion mutant, can use (+)-limonene as a carbon source. Phylogenetic analysis placed GcABC-G1 outside the ascomycete PDR transporter clades. G. clavigera appears to have evolved two mechanisms to survive and grow when exposed to monoterpenes: GcABC-G1 controls monoterpene levels within the fungal cells and G. clavigera uses monoterpenes as a carbon source. This work has implications for understanding adaptation to host defences in an important forest insect-fungal system, and potentially for metabolic engineering of terpenoid production in yeast.
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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 | 0.000 |
| 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) | 0.001 | 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".