Culturable bacterial pool from aged petroleum-contaminated soil: identification of oil-eating Bacillus strains
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Information gleaned from soil microbiota may provide access to new economically important species. Here, we describe the isolation, identification, and genetic diversity of high-density bacterial populations isolated from aged oil-contaminated soil. Twenty different morphotypes were identified in populations present at densities of up to 107 cells g−1 soil, encompassing seven bacterial genera based on 16S rRNA sequencing. Six isolates of the genus Bacillus were identified, three of which appear to consume oil. The genetic clusters defined by the DNA fingerprinting analysis suggest that there is a close relationship between these oil-eating Bacillus species. Isolates able to grow using crude oil as a carbon source were biochemically characterized and found to exhibit high lipolytic activity in liquid medium and to produce alkaline-stable biosurfactants. Fluorescence spectroscopy analysis of the cell-free extract from the oil-eating Bacillus sp. strain MO.04b showed an increase in the relative fluorescence intensity of low-molecular-mass aromatics concomitantly with an increase in the protein content, suggesting the transformation of aromatic hydrocarbons to the liquid phase in response to biodegradation. The approach adopted in this study suggests a low diversity of the high-density bacterial population colonizing an aged oil-contaminated soil and may prove useful in selecting bacterial isolates for bioremediation studies and biotechnological applications such as biosurfactant production.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.004 | 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 it