β-(1 → 3)-Glucanolytic Yeasts from Brazilian Grape Microbiota: Production and Characterization of β-Glucanolytic Enzymes by <i>Aureobasidium pullulans</i> 1WA1 Cultivated on Fungal Mycelium
Bibliographic record
Abstract
A total of 95 yeast strains were isolated from the microbiota of different grapes collected at vineyards in southern Brazil. The yeasts were screened for β-(1 → 3)-glucanases using a newly developed zymogram method that relies upon the appearance of clearance zones around growing colonies cultured on agar–botryosphaeran medium and also by submerged fermentation on nutrient medium containing botryosphaeran, a (1 → 3),(1 → 6)-β-d-glucan. Among 14 β-(1 → 3)-glucanase-positive yeasts identified, four strains produced the highest β-glucanolytic activities and were evaluated for enzyme production on cellobiose, botryosphaeran, and mycelial biomass from Botryosphaeria rhodina (MAMB-05). Yeast strain 1WA1 produced the highest β-(1 → 3)-glucanase and β-glucosidase activities and was identified by molecular characterization as Aureobasidium pullulans. The physicochemical properties of the crude β-glucanolytic enzyme preparation were characterized, and the preparation was used to hydrolyze several β-d-glucans (laminarin, botryosphaeran, lasiodiplodan, pustulan, and curdlan). The production and physicochemical properties of the β-glucanolytic preparation enable its potential applications in wine enology and production of prebiotics through hydrolysis of β-d-glucans.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".