Cataloging proteins putatively secreted during the biotrophy-necrotrophy transition of the anthracnose pathogen<i>Colletotrichum truncatum</i>
Bibliographic record
Abstract
Hemibiotrophic phytopathogenic fungi cause devastating diseases in agronomically important crops. These fungal pathogens exploit a stealth bi-phasic infection strategy to colonize host plants. Their morphological and nutritional transition from biotrophy (characterized by voluminous intracellular primary hyphae) to necrotrophy (characterized by thin secondary hyphae) known as the biotrophy-necrotrophy switch (hemibiotrophy) is critical in symptom and disease development. To establish successful hemibiotrophic parasitism, pathogens likely secrete suites of proteins at the switch that constitute the biotrophy-necrotrophy switch secretome. To catalogue such proteins, a directional cDNA library was constructed from mRNA isolated from infected Lens culinaris leaflet tissues displaying the switch of Colletotrichum truncatum, and 5000 expressed sequence tags (ESTs) were generated. Four potential groups (hydrolytic enzymes, cell envelope-associated proteins [CEAPs], candidate effectors and proteins with diverse functions) were identified from pathogen-derived ESTs. Expression profiling of transcripts encoding CEAPs and candidate effectors in an infection time-course revealed that the majority of these transcripts were expressed or induced during the necrotrophic phase and repressed during the biotrophic phase of in planta colonization, indicating the massive accumulation of proteins at the switch. Taken together, our data suggest that the hemibiotrophic mode of fungal proliferation entails complex interactions of a pathogen with its host wherein the pathogen requires live host cells prior to switching to the necrotrophic phase. The microbial proteins employed during pathogenesis are likely to have defined roles at specific stages of pathogenesis.
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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 | 0.001 |
| 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 | 0.001 |
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".