Proteomic analysis of the metabolic adaptation of the biocontrol agent Pseudozyma flocculosa leading to glycolipid production
Bibliographic record
Abstract
The yeast-like epiphytic fungus Pseudozyma flocculosa is known to antagonize powdery mildew fungi through proliferation on colonies presumably preceded by the release of an antifungal glycolipid (flocculosin). In culture conditions, P. flocculosa can be induced to produce or not flocculosin through manipulation of the culture medium nutrients. In order to characterize and understand the metabolic changes in P. flocculosa linked to glycolipid production, we conducted a 2-DE proteomic analysis and compared the proteomic profile of P. flocculosa growing under conditions favoring the development of the fungus (control) or conducive to flocculosin synthesis (stress). A large number of protein spots (771) were detected in protein extracts of the control treatment compared to only 435 matched protein spots in extracts of the stress cultures, which clearly suggests an important metabolic reorganization in slow-growing cells producing flocculosin. From the latter treatment, we were able to identify 21 protein spots that were either specific to the treatment or up-regulated significantly (2-fold increase). All of them were identified based on similarity between predicted ORF of the newly sequenced genome of P. flocculosa with Ustilago maydis' available annotated sequences. These proteins were associated with the carbon and fatty acid metabolism, and also with the filamentous change of the fungus leading to flocculosin production. This first look into the proteome of P. flocculosa suggests that flocculosin synthesis is elicited in response to specific stress or limiting conditions.
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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".