Bacterial endophytes of plants used for soil reclamation
Bibliographic record
Abstract
Microorganisms that colonize the plant rhizosphere and root tissues may provide host plants with nutrients, stimulate growth and increase tolerance to abiotic stress. These plant-microbe associations are also being investigated to assist land reclamation in Alberta's oil sands. However, these newly reconstructed landscapes may be limited by several factors that include low soil nutrient levels, reduced microbial activity and the presence of residual hydrocarbons. This study was designed to assess the bacterial root microbiome of plants growing in oil sands reclamation covers and investigate the potential use of bacterial endophytes in phytoremediation. Soil microbial community structure in these areas was mainly driven by soil total and organic carbon, NH4+ and organic matter. In addition, an assessment of the bacterial root microbiome associated with sweet clover (Melilotus albus) and barley (Hordeum vulgare) strongly suggests that plants have the ability to select for certain soil bacterial consortia. Sweet clover plants were more selective and mainly associated with Sinorhizobium and Rhizobium, whereas Acholeplasma was unique to barley. Furthermore, genera such as Pseudomonas and Pantoea were able to successfully colonize both plants. However, due to the presence of residual hydrocarbons in these areas, plants may rely on association with hydrocarbon degrading endophytes. Therefore, an assessment of unculturable endophytic communities revealed that sweet clover had higher CYP153 gene copy numbers when compared to barley. In addition, a total of 42 endophytic bacteria isolates tested positive for hydrocarbon degrading genes and were further investigated for their application as inoculants. Based on overall growth promoting effects, sweet clover plants and four different bacterial strains were selected for phytoremediation experiments. Despite plant growth inhibition caused by diesel fuel toxicity, an overall higher plant biomass was observed in inoculated plants. However, only at high diesel concentrations did bacterial inoculants enhanced soil hydrocarbon degradation.\n\nIn conclusion, bacterial species associated with plants growing in reclamation covers were mainly driven by plant factors and this microbiome harbors endophytes that can be potentially used in phytoremediation. In particular, bacterial endophytes such as Pantoea and Pseudomonas species in association with sweet clover plants were shown to successfully reduce petroleum hydrocarbons in soil.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.001 | 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".