Reverse Genetic Analyses of Hydrophobins in Sclerotinia sclerotiorum Revealed Their Diverse Roles in Development, Environmental Survival, and Virulence
Bibliographic record
Abstract
Sclerotinia sclerotiorum is a notorious soilborne fungal pathogen that causes white mold in a wide range of host plants, leading to globally significant yield loss in many crops. Hydrophobins (HPs) are small, secreted proteins unique to filamentous fungi, with diverse roles in fungal biology. However, their functions in S. sclerotiorum remain poorly understood. Here, we systematically investigated the roles of three HP genes, SsHP1, SsHP2, and SsHP3, through reverse genetic analyses. By analyzing their deletion mutant phenotypes, we demonstrate that class I HP (SsHP1) is specifically required for proper sclerotia development, whereas class II HPs (SsHP2 and SsHP3) are essential for compound appressoria functionality. All three HPs contribute to fungal surface hydrophobicity, cell wall integrity, and stress tolerance. Using mycelial fusion, we generated double mutants lacking both class II HPs, which exhibited more severe defects in appressoria development, virulence, cell wall integrity, and stress adaptation, indicating their partially redundant roles. SsHP2 is required for both host penetration and post-penetration virulence, whereas SsHP3 mainly affects host penetration, revealing their overlapping yet distinct contributions to pathogenic development. Although all HP mutants formed normal apothecia and asci, they released significantly fewer ascospores, suggesting that HPs are dispensable for sexual morphogenesis but crucial for the biophysical process of ascospore dispersal. Furthermore, carbohydrate analyses uncovered that these HPs affect cell wall composition, more broadly influencing stress adaptation and virulence. Taken together, our study reveals both conserved and divergent roles of HPs across fungi and highlight their multifaceted contributions to S. sclerotiorum biology, offering new perspectives for disease management.
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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".