Proximity‐dependent biotinylation identifies a suite of candidate effector proteins from <i>Fusarium graminearum</i>
Bibliographic record
Abstract
Fusarium graminearum is a fungal pathogen that causes Fusarium head blight in cereal crops. The identification of proteins secreted from pathogens to overcome plant defenses and cause disease, collectively known as effectors, can reveal the etiology of a disease process. Proximity-dependent biotin identification (BioID) was used to identify potential effector proteins secreted in planta by F. graminearum during the infection of Arabidopsis. Mass spectrometry analysis of streptavidin affinity-purified proteins revealed over 300 proteins from F. graminearum, of which 62 were candidate effector proteins (CEPs). An independent analysis of secreted proteins from axenic cultures of F. graminearum showed a 42% overlap with CEPs, thereby assuring confidence in the BioID methodology. The analysis also revealed that 19 out of 62 CEPs (approx. 30%) had been previously characterized with virulence function in fungi. The functional characterization of additional CEPs was undertaken through deletion analysis by the CRISPR/Cas9 method, and by overexpression into Triticum aestivum (wheat) leaves by the Ustilago hordei delivery system. Deletion studies of 12 CEPs confirmed the effector function of three previously characterized CEPs and validated the function of another four CEPs on wheat inflorescence or vegetative tissues. Lastly, overexpression in wheat showed that all seven CEPs enhanced resistance against the bacterial pathogen Pseudomonas syringae DC3000.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".