Differential regulation and production of secondary metabolites among isolates of the fungal wheat pathogen <i>Zymoseptoria tritici</i>
Bibliographic record
Abstract
Summary The genome of the wheat pathogenic fungus, Zymoseptoria tritici, represents extensive presence-absence variation in gene content. Here, we addressed variation in biosynthetic gene clusters (BGCs) content and biochemical profiles among three isolates. We analysed secondary metabolite properties based on genome, transcriptome and metabolome data. The isolates represent highly distinct genome architecture, but harbor similar repertoire of BGCs. Expression profiles for most BGCs show comparable patterns of regulation among the isolates, suggesting a conserved “biochemical infection program”. For all three isolates, we observed a strong up-regulation of an abscisic acid (ABA) gene cluster during biotrophic host colonization, indicating that Z. tritici potentially interfere with host defenses by the biosynthesis of this phytohormone. Further, during in vitro growth the isolates show similar metabolomes congruent with the predicted BGC content. We assessed if secondary metabolite production is regulated by histone methylation using a mutant impaired in formation of facultative heterochromatin (H3K27me3). In contrast to other ascomycete fungi, chromatin modifications play a less prominent role in regulation of secondary metabolites. In summary, we show that Z. tritici has a conserved program of secondary metabolite production contrasting the immense variation in effector expression, some of these metabolites might play a key role during host colonization. Originality-Significance Statement Zymoseptoria tritici is one of the most devastating pathogens of wheat. So far the molecular determinants of virulence and their regulation are poorly understood. Previous studies have focused on proteinasous virulence factors and their extensive diversity. In this study, we focus on secondary metabolites produced by Z. tritici . Using a comparative framework, we here characterize core and non-core metabolites produced by Z. tritici by combining genome, transcriptome and metabolome datasets. Our findings indicate highly conserved biochemical profiles contrasting genetic and phenotypic diversity of the field isolates investigated here. This discovery has relevance for future crop protection strategies.
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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".