The expanding antimicrobial diversity of the genus Pantoea
Bibliographic record
Abstract
With the rise of antimicrobial resistance, there is high demand for novel antimicrobials to combat multi-drug resistant pathogens. The bacterial genus Pantoea produces a diversity of antimicrobial natural products effective against a wide range of bacterial and fungal targets. These antimicrobials are synthesized by specialized biosynthetic gene clusters that have unique distributions across Pantoea as well as several other genera outside of the Erwiniaceae. Phylogenetic and genomic evidence shows that these clusters can mobilize within and between species and potentially between genera. Pantoea antimicrobials belong to unique structural classes with diverse mechanisms of action, but despite their potential in antagonizing a wide variety of plant, human, and animal pathogens, little is known about many of these metabolites and how they function. This review will explore the known antimicrobials produced by Pantoea: agglomerins, andrimid, D-alanylgriseoluteic acid, dapdiamide, herbicolins, pantocins, and the various Pantoea Natural Products (PNPs). It will include information on the structure of each compound, their genetic basis, biosynthesis, mechanism of action, spectrum of activity, and distribution, highlighting the significance of Pantoea antimicrobials as potential therapeutics and for applications in biocontrol.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".