Novel Psychrophiles and Exopolymers from Permafrost Thaw Lake Sediments
Bibliographic record
Abstract
Thermokarst lakes are one of the most abundant types of microbial ecosystems in the circumpolar North. These shallow basins are formed by the thawing and collapse of ice-rich permafrost, with subsequent filling by snow and ice melt. Until now, permafrost thaw lakes have received little attention for isolation of microorganisms by culture-based analysis. The discovery of novel psychrophiles and their biomolecules makes these extreme environments suitable sources for the isolation of new strains, including for potential biotechnological applications. In this study, samples of bottom sediments were collected from three permafrost thaw lakes in subarctic Québec, Canada. Their diverse microbial communities were characterized by 16S rRNA gene amplicon analysis, and subsamples were cultured for the isolation of bacterial strains. Phenotypic and genetic characterization of the isolates revealed affinities to the genera Pseudomonas, Paenibacillus, Acinetobacter,Staphylococcus and Sphingomonas. The isolates were then evaluated for their production of extracellular enzymes and exopolymers. Enzymes of potential biotechnological interest included α and β-glucosidase, α and β-maltosidase, β-xylosidase and cellobiohydrolase. One isolate, Pseudomonas extremaustralis strain 2ASCA, also showed the capability to produce, in the loosely bound cell fraction, a levan-type polysaccharide with a yield of 613 mg/L of culture, suggesting its suitability as a candidate for eco-sustainable alternatives to commercial polymers.
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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 | 0.001 | 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".