Isolation and identification of soil bacteria growing at the expense of arbuscular mycorrhizal fungi
Bibliographic record
Abstract
Soil-microorganism symbioses are of fundamental importance for plant adaptation to the environment. Research in microbial ecology has revealed that some soil bacteria are associated with arbuscular mycorrhizal fungi (AMF). However, these interactions may be much more complex than originally thought. To assess the type of bacteria associated with AMF, we initially isolated spores of Glomus irregulare from an Agrostis stolonifera rhizosphere. The spores were washed with sterile water and plated onto G. irregulare mycelium growing in vitro in a root-free compartment of bicompartmented Petri dishes. We hypothesized that this system should select for bacteria closely associated with the fungus because the only nutrients available to the bacteria were those derived from the hyphae. Twenty-nine bacterial colonies growing on the AMF hyphae were subcultured and identified using 16S rRNA gene sequences. All bacterial isolates showed high sequence identity to Bacillus cereus, Bacillus megaterium, Bacillus simplex, Kocuria rhizophila, Microbacterium ginsengisoli, Sphingomonas sp. and Variovorax paradoxus. We also assessed bacterial diversity on the surface of spores by PCR-denaturating gradient gel electrophoresis. Finally, we used live cellular imaging to show that the bacteria isolated can grow on the surface of hyphae with different growing patterns in contrast to Escherichia coli as a control.
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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".