Trehalose-deficient <i>Acinetobacter baumannii</i> exhibits reduced virulence by losing capsular polysaccharide and altering membrane integrity
Bibliographic record
Abstract
Acinetobacter baumannii has become a leading cause of bacterial nosocomial infections, in part, due to its ability to resist desiccation, disinfection and antibiotics. Several factors contribute to the tenacity and virulence of this pathogen, including production of a broad range of surface glycoconjugates, secretory systems and efflux pumps. We became interested in examining the importance of trehalose in A. baumannii after comparing intact bacterial cells by high-resolution magic angle spinning nuclear magnetic resonance and by noting high levels of this disaccharide, obscuring all other resonances in the spectrum. Since this was observed under normal growth conditions, we speculated that trehalose must serve additional functions beyond osmolyte homeostasis. Using the virulent isolate A. baumannii AB5075 and mutants in the trehalose synthesis pathway, osmoregulatory trehalose synthesis proteins A and B (△otsA and △otsB), we found that the trehalose-deficient △otsA showed increased sensitivity to desiccation, colistin, serum complement and peripheral blood mononuclear cells, while trehalose-6-phosphate producing △otsB behaved similar to the wild-type. The △otsA mutant also demonstrated increased membrane permeability and loss of capsular polysaccharide. These findings demonstrate that trehalose deficiency leads to loss of virulence in A. baumannii AB5075.
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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) | 0.001 | 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".