Proteomic analysis of the phytopathogenic soilborne fungus <i>Verticillium dahliae</i> reveals differential protein expression in isolates that differ in aggressiveness
Bibliographic record
Abstract
Verticillium dahliae is a soilborne fungus that causes a vascular wilt disease of plants and losses in a broad range of economically important crops worldwide. In this study, we compared the proteomes of highly (Vd1396-9) and weakly (Vs06-14) aggressive isolates of V. dahliae to identify protein factors that may contribute to pathogenicity. Twenty-five protein spots were consistently observed as differential in the proteome profiles of the two isolates. The protein sequences in the spots were identified by LC-ESI-MS/MS and MASCOT database searches. Some of the identified sequences shared homology with fungal proteins that have roles in stress response, colonization, melanin biosynthesis, microsclerotia formation, antibiotic resistance, and fungal penetration. These are important functions for infection of the host and survival of the pathogen in soil. One protein found only in the highly aggressive isolate was identified as isochorismatase hydrolase, a potential plant-defense suppressor. This enzyme may inhibit the production of salicylic acid, which is important for plant defense response signaling. Other sequences corresponding to potential pathogenicity factors were identified in the highly aggressive isolate. This work indicates that, in combination with functional genomics, proteomics-based analyses can provide additional insights into pathogenesis and potential management strategies for this disease.
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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) | 0.000 | 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".