Comprehensive identification of lysine 2‐hydroxyisobutyrylated proteins in <i>Ustilaginoidea virens</i> reveals the involvement of lysine 2‐hydroxyisobutyrylation in fungal virulence
Bibliographic record
Abstract
Abstract Lysine 2‐hydroxyisobutyrylation (K hib ) is a newly identified post‐translational modification (PTM) that plays important roles in transcription and cell proliferation in eukaryotes. However, its function remains unknown in phytopathogenic fungi. Here, we performed a comprehensive assessment of K hib in the rice false smut fungus Ustilaginoidea virens , using Tandem Mass Tag (TMT)‐based quantitative proteomics approach. A total of 3 426 K hib sites were identified in 977 proteins, suggesting that K hib is a common and complex PTM in U. virens . Our data demonstrated that the 2‐hydroxyisobutyrylated proteins are involved in diverse biological processes. Network analysis of the modified proteins revealed a highly interconnected protein network that included many well‐studied virulence factors. We confirmed that the Zn‐binding reduced potassium dependency3‐type histone deacetylase (UvRpd3) is a major enzyme that removes 2‐hydroxyisobutyrylation and acetylation in U. virens . Notably, mutations of K hib sites in the mitogen‐activated protein kinase (MAPK) UvSlt2 significantly reduced fungal virulence and decreased the enzymatic activity of UvSlt2. Molecular dynamics simulations demonstrated that 2‐hydroxyisobutyrylation in UvSlt2 increased the hydrophobic solvent‐accessible surface area and thereby affected binding between the UvSlt2 enzyme and its substrates. Our findings thus establish K hib as a major post‐translational modification in U. virens and point to an important role for K hib in the virulence of this phytopathogenic fungus.
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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".