Endophytic Bacterial Community Structure and Function of Herbaceous Plants From Petroleum Hydrocarbon Contaminated and Non-contaminated Sites
Bibliographic record
Abstract
Bacterial endophytes (BEs) are non-pathogenic residents of healthy plant tissues that can confer benefits to plants. Many Bacterial endophytes have been shown to contribute to plant growth and health, alleviation of plant stress and to in-planta contaminant-degradation. This study examined the endophytic bacterial communities of plants growing abundantly in a heavily hydrocarbon contaminated site, and compared them to those found in the same species at a non-contaminated. We used culture- dependent and independent methods to characterize the community structure, hydrocarbon degrading capabilities, and plant growth promoting traits of cultivable endophytes isolated from Achillea millefolium, Solidago canadensis and Daucus carota plants from these two areas. Culture- dependent and independent analyses revealed class Gammaproteobacteria predominated in all the plants regardless of the presence of petroleum hydrocarbon, with Pantoea spp. as largely dominant. It was interesting to note a >50% taxonomic overlap (genus level) of 16s rRNA high throughput amplicon sequences with cultivable endophytes. PERMANOVA analysis of TRFLP fragments revealed significant structural differences between endophytic bacterial communities from hydrocarbon-contaminated and non-contaminated soils - however, there was no marked difference in their functional capabilities of bacterial endophytes. Pantoea spp. demonstrated plant beneficial characteristics, such as, P solubilization, indole-3-acetic acid production and presence of 1-aminocyclopropane-1-carboxylate deaminase. Our findings reveal that functional capabilities of bacterial isolates being examined were not influenced by the presence of contamination; and that the stem endosphere supports predominant BEs that were consistent throughout plant hosts and sites.
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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 | 0.000 |
| 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".