Clinical stringent response activation promotes conjugal transfer of staphylococcal resistance plasmids
Bibliographic record
Abstract
ABSTRACT Conjugative transfer of plasmids represents a major route through which antibiotic resistance genes are spread. In the case of the prevalent and deadly pathogen Staphylococcus aureus , >90% of clinical isolates carry at least one plasmid. While plasmid-encoded mechanisms ( e.g. plasmid copy number) can influence conjugation frequency, host factors and environmental stimuli can also affect transmission. In particular, stress responses like the stringent response have been associated with increased movement of mobile genetic elements. We have previously shown that clinical mutations in the stringent response controller, Rel, lead to elevated levels of the alarmones (p)ppGpp and antibiotic tolerance in S. aureus . Here, we report that stringent response activation in these strains promotes the conjugal transfer of diverse staphylococcal resistance plasmids. We observed that clinical Rel mutations promote donation, but not receipt, of plasmids from the three families of staphylococcal plasmid and a mobilisable plasmid. This increased conjugation frequency could also be induced by chemical induction of the stringent response by mupirocin. Intriguingly, detailed experimental analysis revealed that the effect of elevated (p)ppGpp on plasmid donation was not due to CodY derepression, SOS response induction, increased plasmid copy number or increased expression of conjugation machinery genes. Further, transcriptomic analysis failed to identify any other putative plasmid- or host-derived mechanisms to explain this observation. Further investigations are required to explore the mechanistic link between the stringent response and conjugation, given the pervasive transcriptional and post-translational effects of (p)ppGpp. Overall, the association between Rel mutation and increased plasmid donation is alarming, especially as Rel mutations are being increasingly identified among clinical isolates.
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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) | 0.003 | 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".