Characterization of Hydrocarbon-Degrading Microbial Populations in Contaminated and Pristine Alpine Soils
Bibliographic record
Abstract
Biodegradation of petroleum hydrocarbons in cold environments, including Alpine soils, is a result of indigenous cold-adapted microorganisms able to degrade these contaminants. In the present study, the prevalence of seven genotypes involved in the degradation of n-alkanes (Pseudomonas putida GPo1 alkB; Acinetobacter spp. alkM; Rhodococcus spp. alkB1, and Rhodococcus spp. alkB2), aromatic hydrocarbons (P. putida xylE), and polycyclic aromatic hydrocarbons (P. putida ndoB and Mycobacterium sp. strain PYR-1 nidA) was determined in 12 oil-contaminated (428 to 30,644 mg of total petroleum hydrocarbons [TPH]/kg of soil) and 8 pristine Alpine soils from Tyrol (Austria) by PCR hybridization analyses of total soil community DNA, using oligonucleotide primers and DNA probes specific for each genotype. The soils investigated were also analyzed for various physical, chemical, and microbiological parameters, and statistical correlations between all parameters were determined. Genotypes containing genes from gram-negative bacteria (P. putida alkB, xylE, and ndoB and Acinetobacter alkM) were detected to a significantly higher percentage in the contaminated (50 to 75%) than in the pristine (0 to 12.5%) soils, indicating that these organisms had been enriched in soils following contamination. There was a highly significant positive correlation (P < 0.001) between the level of contamination and the number of genotypes containing genes from P. putida and Acinetobacter sp. but no significant correlation between the TPH content and the number of genotypes containing genes from gram-positive bacteria (Rhodococcus alkB1 and alkB2 and Mycobacterium nidA). These genotypes were detected at a high frequency in both contaminated (41.7 to 75%) and pristine (37.5 to 50%) soils, indicating that they are already present in substantial numbers before a contamination event. No correlation was found between the prevalence of hydrocarbon-degradative genotypes and biological activities (respiration, fluorescein diacetate hydrolysis, lipase activity) or numbers of culturable hydrocarbon-degrading soil microorganisms; there also was no correlation between the numbers of hydrocarbon degraders and the contamination level. The measured biological activities showed significant positive correlation with each other, with the organic matter content, and partially with the TPH content and a significant negative correlation with the soil dry-mass content (P < 0.05 to 0.001).
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".