Distribution of antimicrobial lipopeptides in Bacillus and Pseudomonas spp., two genera with antagonistic effects against plant pathogens
Bibliographic record
Abstract
Suppressive soils, composts, and compost teas have previously shown inhibitory effects against plant disease.A major reason for this suppressiveness has been their beneficial microbial populations.The present study was carried out to investigate the inhibitory activity of forty bacteria isolated from these three sources against the mycelial growth of six plant pathogens.Thirty-eight isolates inhibited at least one of the pathogens whereas sixteen of the isolates inhibited all the pathogens (36% average inhibition).Crude lipopeptides extracts were precipitated from bacterial liquid cultures.All tested lipopeptide samples inhibited the mycelial growth or conidial germination of at least one of the pathogens.Known antimicrobial lipopeptides in selected samples were identified by LC-MS.Results showed that all Bacillus and Bacillus-related spp.produced one or more lipopeptides from the fengycin, iturin, and surfactin families.In addition, certain Pseudomonas spp.produced lipopeptides from the amphisin and putisolvin families.
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".