Activation of metabolic and stress responses during subtoxic expression of the type I toxin hok in Erwinia amylovora
Bibliographic record
Abstract
BACKGROUND: Toxin-antitoxin (TA) systems, abundant in prokaryotes, are composed of a toxin gene and its cognate antitoxin. Several toxins are implied to affect the physiological state and stress tolerance of bacteria in a population. We previously identified a chromosomally encoded hok-sok type I TA system in Erwinia amylovora, the causative agent of fire blight disease on pome fruit trees. A high-level induction of the hok gene was lethal to E. amylovora cells through unknown mechanisms. The molecular targets or regulatory roles of Hok were unknown. RESULTS: Here, we examined the physiological and transcriptomic changes of Erwinia amylovora cells expressing hok at subtoxic levels that were confirmed to confer no cell death, and at toxic levels that resulted in killing of cells. In both conditions, hok caused membrane rupture and collapse of the proton motive force in a subpopulation of E. amylovora cells. We demonstrated that induction of hok resulted in upregulation of ATP biosynthesis genes, and caused leakage of ATP from cells only at toxic levels. We showed that overexpression of the phage shock protein gene pspA largely reversed the cell death phenotype caused by high levels of hok induction. We also showed that induction of hok at a subtoxic level rendered a greater proportion of stationary phase E. amylovora cells tolerant to the antibiotic streptomycin. CONCLUSIONS: We characterized the molecular mechanism of toxicity by high-level of hok induction and demonstrated that low-level expression of hok primes the stress responses of E. amylovora against further membrane and antibiotic stressors.
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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 | 0.001 |
| 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".