Quantitative evaluation of the host-colonizing capabilities of the enteric bacterium Pantoea using plant and insect hosts
Bibliographic record
Abstract
The genus Pantoea is a highly diverse group comprising free-living, and both pathogenic and non-pathogenic host-associating species. Pathogenic isolates have been found to infect insects, plants and humans, yet it is unclear whether these isolates have similar pathogenic potential to the free-living environmental populations. Using MLSA of six housekeeping genes, we evaluated the phylogenetic relationships among 115 environmental and clinical (human) isolates representing 11 Pantoea species. An overlay of the location of isolation onto the resulting tree revealed that clinical and environmental isolates are interspersed, and do not form distinctive groups. We then conducted quantitative growth assays of our isolates using maize, onion and fruit flies as hosts. Notably, most clinical isolates were able to grow in both plant hosts often comparably or even better than the environmental isolates. There were no obvious growth or host colonization patterns that could distinguish those isolates with clinical potential. Growth of an isolate in one host could not be predicted based on its performance in another host, nor could host growth be predicted by phylogeny or source of isolation. This work demonstrates that the host-colonizing capabilities of all Pantoea species groups is unpredictable, indicating a broader host range and pathogenic potential than currently assumed.
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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 | 0.001 |
| 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".