Selective biostimulation of cold‐ and salt‐tolerant hydrocarbon‐degrading <i>Dietzia maris</i> in petroleum‐contaminated sub‐Arctic soils with high salinity
Bibliographic record
Abstract
Abstract BACKGROUND The dual tolerance of hydrocarbon‐degrading bacteria to low temperatures and salinity has not been extensively reported. This study identifies cold‐ and salt‐tolerant hydrocarbon degraders obtained from petroleum‐contaminated sub‐Arctic soils, with the objective of stimulating target populations and assessing hydrocarbon biodegradation in soils abruptly impacted by salinity. RESULTS Halotolerant Dietzia and Arthrobacter bacteria were isolated from the soils. Dietzia maris strain NWWC4 can grow in the absence and presence of NaCl (≤12.5% w/v), adheres to hydrocarbons, and produces biosurfactant. The nutrient conditions preferred by strain NWWC4 were characterized to stimulate halotolerant hydrocarbon degraders related to strain NWWC4. In soil‐slurry microcosms with the selected nutrient, Terminal Restriction Fragment Length Polymorphism indicated the dominance of alkB ‐gene‐harboring NWWC4 relatives. Radiolabeled 14 C‐hexadecane mineralization in high‐salinity soil‐slurry microcosms (29 ± 0.33% 14 CO 2 production) was strikingly comparable with that in non‐saline conditions (35 ± 0.84% 14 CO 2 production). In nutrient‐amended, Arctic‐diesel‐spiked soil microcosms subjected to dual stresses (10 °C and 5% NaCl, w/v), hydrocarbon removal in the diesel range (C10–C21) was 21 ± 8% after 18 days and was comparable with the removal achieved under non‐saline conditions (37 ± 6% removal). CONCLUSION This study reports the unique versatility of cold‐adapted and salt‐tolerant Dietzia maris capable of degrading hydrocarbons in highly saline and non‐saline conditions. © 2017 Society of Chemical Industry
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How this classification was reachedexpand
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 teacher head, 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".