Differential Proteomic Analysis of Secreted Proteins from Cutinase-producing Bacillus sp. SB-007
Bibliographic record
Abstract
Bacillus sp. SB-007 was isolated from pea leaves harvested from the southwestern parts of South Korea through screening on a minimal medium containing 0.2% purified cutin for its ability to induce the cutinase production. However, no cutinase was produced when it was grown in a minimal medium containing 0.2% glucose. A proteomic approach was applied to separate and characterize these differentially secreted proteins. The expression level of 83 extracellular proteins of the cutinase-producing Bacillus sp. strain SB-007 incubated in a cutinase-induced medium increased significantly as compared with that cultured in a non cutinase-induced medium containing glucose. The extracellular proteome of Bacillus sp. SB-007 includes proteins from different functional classes, such as enzymes for the degradation of various macromolecules, proteins involved in energy metabolism, sporulation, transport/binding proteins and lipoproteins, stress inducible proteins, several cellular molecule biosynthetic pathways and catabolism, and some proteins with an as yet unknown function. In addition, the two protein spots showed little similarities with the known lipolytic enzymes in the database. These secreted proteome analysis results are expected to be useful in improving the Bacillus strains for the production of industrial cutinases.
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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".