Fungal adaptation to plant defences through convergent assembly of metabolic modules
Bibliographic record
Abstract
The ongoing diversification of plant defence compounds exerts dynamic selection pressures on the microorganisms that colonize plant tissues. Evolutionary processes that generate resistance towards these compounds increase microbial fitness by giving access to plant resources and increasing pathogen virulence. These processes entail sequence-based mechanisms that result in adaptive gene functions, and combinatorial mechanisms that result in novel syntheses of existing gene functions. However, the priority and interactions among these processes in adaptive resistance remain poorly understood. Using a combination of molecular genetic and computational approaches, we investigated the contributions of sequence-based and combinatorial processes to the evolution of fungal metabolic gene clusters encoding stilbene cleavage oxygenases (SCOs), which catalyse the degradation of biphenolic plant defence compounds known as stilbenes into monophenolic molecules. We present phylogenetic evidence of convergent assembly among three distinct types of SCO gene clusters containing alternate combinations of phenolic catabolism. Multiple evolutionary transitions between different cluster types suggest recurrent selection for distinct gene assemblages. By comparison, we found that the substrate specificities of heterologously expressed SCO enzymes encoded in different clusters types were all limited to stilbenes and related molecules with a 4'-OH group, and differed modestly in substrate range and activity under the experimental conditions. Together, this work suggests a primary role for genome structural rearrangement, and the importance of enzyme modularity, in promoting fungal metabolic adaptation to plant defence chemistry.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".