Genomic Diversity of Two Hydrocarbon-Degrading and Plant Growth-Promoting Pseudomonas Species Isolated from the Oil Field of Bóbrka (Poland)
Bibliographic record
Abstract
Hydrocarbon-degrading bacteria are important resources for use in phytoremediation applications. Yet, for many hydrocarbonoclastic strains the genetic information regarding pollutant degradation and detoxification has not been thoroughly revealed. In this study, hydrocarbon-degrading bacteria were isolated from a long-term oil-polluted soil in Bóbrka, Poland. Pseudomonas spp. was the most dominant species. Of all 69 isolated strains tested in the laboratory using qualitative biochemical assays, 61% showed the capability to use diesel as sole carbon source, 33% could produce indole, 19% produced siderophores, 36% produced organic acids, and 54% were capable of producing 1-aminocyclopropane-1-carboxylate (ACC)-deaminase. From all morphologically and genetically different strains, two representative Pseudomonas spp., strain VI4.1 and VI4T1, were selected for genome sequencing. Genomic analyses indicated the presence of the full naphthalene dioxygenase operon (plasmid and chromosomal), of genes involved in the degradation of BTEX compounds (Benzene, Toluene, Ethylbenzene, Xylene) and alkanes (alkB gene) as well as the anthranilate degradation pathway (strain VI4T1) and terephthalate dioxygenase protein (strain VI4.1). Proton transfer reaction time-of-flight mass spectrometry (PTR-TOF-MS) analyses confirmed naphthalene and BTEX degradation within seven days. Motility, resistance to abiotic stresses, high and low temperatures, low pH, and salinity were confirmed at the genetic level and experimentally verified. The presence of multiple degradative and plant growth promotion genes, together with the in vitro experimental evidence, indicates the high value of these two strains and their potential use for sustainable site clean-up.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".