The quantitation of Bradyrhizobium japonicum communities and the isolation of bacteriocin-producing Bradyrhizobium strains from Manitoban soil
Bibliographic record
Abstract
Bradyrhizobium japonicum is a Gram negative α-proteobacteria capable of reducing atmospheric nitrogen to ammonia while in a symbiotic relationship with soybean. This symbiosis manifests itself as nodules formed on the roots of soybean plants. A well-nodulated plant can derive all the nitrogen necessary for growth from this association. One problem that is often encountered is not having sufficient numbers of the correct strains of rhizobia present as the seed is germinating which prevent effective nodules to develop in a timely manner. Currently, the quantification of Bradyrhizobium in soil relies heavily on culture-based assays which are time-consuming, labour-intensive, and lacks the ability to differentiate between strains of B. japonicum. In this study, we developed a rapid and sensitive real-time qPCR based assay for the quantification of B. japonicum. This assay is able to differentiate between strains of B. japonicum. Using this assay, we showed the differences in the composition of B. japonicum community in fields utilizing narrow (15 inches) and wide (30 inches) row spacing. We showed that the composition of B. japonicum community in soil is affected by the population density of host plants. We also isolated B. japonicum strain FN1 in Manitoba. FN1 produces substances with bacteriocin-like characteristics that inhibit the growth of multiple other strains of Bradyrhizobium. In this study, we were able to identify a gene that is responsible for the production of the bacteriocin-like substance that inhibits the growth of the strain SR-16. Furthermore, we showed that the ability of FN1 to produce bacteriocin-like substance provide a competitive advantage for nodule occupancy over SR-16. This is the first study in B. japonicum that shows that the ability to produce bacteriocin-like substance is related to the competitiveness for nodule occupancy.
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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) | 0.001 | 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 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".