Simultaneous profiling of seed‐associated bacteria and fungi reveals antagonistic interactions between microorganisms within a shared epiphytic microbiome on <i><scp>T</scp>riticum</i> and <i><scp>B</scp>rassica</i> seeds
Bibliographic record
Abstract
In order to address the hypothesis that seeds from ecologically and geographically diverse plants harbor characteristic epiphytic microbiota, we characterized the bacterial and fungal microbiota associated with Triticum and Brassica seed surfaces. The total microbial complement was determined by amplification and sequencing of a fragment of chaperonin 60 (cpn60). Specific microorganisms were quantified by qPCR. Bacteria and fungi corresponding to operational taxonomic units (OTU) that were identified in the sequencing study were isolated and their interactions examined. A total of 5477 OTU were observed from seed washes. Neither total epiphytic bacterial load nor community richness/evenness was significantly different between the seed types; 578 OTU were shared among all samples at a variety of abundances. Hierarchical clustering revealed that 203 were significantly different in abundance on Triticum seeds compared with Brassica. Microorganisms isolated from seeds showed 99-100% identity between the cpn60 sequences of the isolates and the OTU sequences from this shared microbiome. Bacterial strains identified as Pantoea agglomerans had antagonistic properties toward one of the fungal isolates (Alternaria sp.), providing a possible explanation for their reciprocal abundances on both Triticum and Brassica seeds. cpn60 enabled the simultaneous profiling of bacterial and fungal microbiota and revealed a core seed-associated microbiota shared between diverse plant genera.
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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 | 0.000 | 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) | 0.000 | 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".