Discovery and Characterization of a New Cold-Active Protease From an Extremophilic Bacterium via Comparative Genome Analysis and in vitro Expression
Bibliographic record
Abstract
Following a screening of Antarctic glacier forefield-bacteria for novel cold-active enzymes, a psychrophilic strain Psychrobacter sp. 94-6PB was selected for further characterization of enzymatic activities. The strain produced lipases and proteases in the temperature range of 4-18ºC. The coding sequence of an extracellular serine-protease was then identified via comparative analysis across Psychrobacter sp. genomes, PCR-amplified in our strain 94-6PB and expressed in the heterologous host E. coli. The purified enzyme (80-kDa) resulted to be a cold-active alkaline protease, performing best at temperatures of 20-30ºC and pH 7-9. It was stable in presence of common inhibitors (β mercaptoethanol (β-ME), dithiothreitol (DTT), urea, phenylmethylsulfonyl fluoride (PMSF) and ethylenediaminetetraacetic acid (EDTA)) and compatible with detergents and surfactants (Tween 20, Tween 80, hydrogen peroxide and Triton X-100). Because of these properties, the P94-6PB protease may be suitable for use in a new generation of laundry products for cold washing. Furthermore, we assessed the microdiversity of this enzyme in Psychrobacter organisms from different cold habitats and found several gene clusters that correlated with specific ecological niches. We then discussed the role of habitat specialization in shaping the biodiversity of proteins and enzymes and anticipate far-reaching implications for the search of novel variants of biotechnological products.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".