Bacterial Endophytes Isolated from Plants in Natural Oil Seep Soils with Chronic Hydrocarbon Contamination
Bibliographic record
Abstract
The bacterial endophytic communities of four plants growing abundantly in soils highly contaminated by hydrocarbons were analyzed through culturable and culture-independent means. Given their tolerance to the high levels of petroleum contamination at our study site, we sought evidence that Achillea millefolium, Solidago canadensis, Trifolium aureum, and Dactylis glomerata support high levels of hydrocarbon degrading endophytes. A total of 190 isolates were isolated from four plant species. The isolates were identified by partial 16S rDNA sequence analysis, with class Actinobacteria as the dominant group in all species except S. canadensis, which was dominated by Gammaproteobacteria. Microbacterium foliorum and Plantibacter flavus were present in all the plants, with M. foliorum showing predominance in D. glomerata and both endophytic bacterial species dominated T. aureum. More than 50% of the isolates demonstrated degradative capabilities for octanol, toluene, naphthalene, kerosene, or motor oil based on sole carbon source growth screens involving the reduction of tetrazolium dye. P. flavus isolates from all the sampled plants showed growth on all the petroleum hydrocarbons (PHCs) substrates tested. Mineralization of toluene and naphthalene was confirmed using gas-chromatography. 16S based terminal restriction fragment length polymorphism analysis revealed significant differences between the endophytic bacterial communities showing them to be plant host specific at this site. To our knowledge, this is the first account of the degradation potential of bacterial endophytes in these commonly occurring pioneer plants that were not previously known as phytoremediating plants.
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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 | 0.000 | 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".