Genetic mutations in adaptive evolution of growth-independent vancomycin-tolerant <i>Staphylococcus aureus</i>
Bibliographic record
Abstract
BACKGROUND: Antibiotic tolerance allows bacteria to overcome antibiotic treatment transiently and potentially accelerates the emergence of resistance. However, our understanding of antibiotic tolerance at the genetic level during adaptive evolution of Staphylococcus aureus remains incomplete. We sought to identify the mutated genes and verify the role of these genes in the formation of vancomycin tolerance in S. aureus. METHODS: Vancomycin-susceptible S. aureus strain Newman was used to induce vancomycin-tolerant isolates in vitro by cyclic exposure under a high concentration of vancomycin (20× MIC). WGS and Sanger sequencing were performed to identify the genetic mutations. The function of mutated genes in vancomycin-tolerant isolates were verified by gene complementation. Other phenotypes of vancomycin-tolerant isolates were also determined, including mutation frequency, autolysis, lysostaphin susceptibility, cell wall thickness and cross-tolerance. RESULTS: A series of vancomycin-tolerant S. aureus (VTSA) strains were isolated and 18 mutated genes were identified by WGS. Among these genes, pbp4, htrA, stp1, pth and NWMN_1068 were confirmed to play roles in VTSA formation. Mutation of mutL promoted the emergence of VTSA. All VTSA showed no changes in growth phenotype. Instead, they exhibited reduced autolysis, decreased lysostaphin susceptibility and thickened cell walls. In addition, all VTSA strains were cross-tolerant to antibiotics targeting cell wall synthesis but not to quinolones and lipopeptides. CONCLUSIONS: Our results demonstrate that genetic mutations are responsible for emergence of phenotypic tolerance and formation of vancomycin tolerance may lie in cell wall changes in S. aureus.
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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".