Inducible Resistance to β-Lactams in Oxacillin-Susceptible mecA1-Positive Staphylococcus sciuri Isolated From Retail Pork
Bibliographic record
Abstract
Most isolated strains of Staphylococcus sciuri contain mecA1 , the evolutionary origin of mecA , but are sensitive to β-lactams (OS-MRSS, oxacillin-susceptible mecA1 -positive S. sciuri ). In order to improve the efficacy of antibiotic treatment, it is important to clarify whether the resistance of OS-MRSS to β-lactams is an inducible phenotype. In this study, three OS-MRSS strains with oxacillin MIC = 1 μg/ml were isolated from 29 retail pork samples. The resistance of OS-MRSS to β-lactams (MIC > 256 μg/ml) was found to be induced by oxacillin, and the induced resistance was observed to remain stable within a certain period of time. Interestingly, the induced β-lactam resistance was not caused by mecA1 , heterogeneous resistance, or any genetic mutation, but mainly due to increased wall teichoic acid (WTA) synthesis that thickened the cell wall. The induced strains also showed slower growth rate, as well as decreased adhesion ability and biofilm thickness. These phenotypes were found to be achieved through altered gene expression in associated pathways, such as the citrate cycle and pentose phosphate pathway. The results challenge the traditional antibiotic sensitivity test. In the presence of β-lactam antibiotics, OS-MRSS that was initially sensitive to β-lactams was observed to gradually develop β-lactam resistance in several days. This often-neglected phenomenon in antibiotic sensitivity tests requires further research attention.
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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".