Cloning, Sequencing, and Characterization of the SdeAB Multidrug Efflux Pump of <i>Serratia marcescens</i>
Bibliographic record
Abstract
Serratia marcescens is an important nosocomial agent known for causing various infections in immunocompromised individuals. Resistance of this organism to a broad spectrum of antibiotics makes the treatment of infections very difficult. This study was undertaken to identify multidrug resistance efflux pumps in S. marcescens. Three mutant strains of S. marcescens were isolated in vitro by the serial passaging of a wild-type strain in culture medium supplemented with ciprofloxacin, norfloxacin, or ofloxacin. Fluoroquinolone accumulation assays were performed to detect the presence of a proton gradient-dependent efflux mechanism. Two of the mutant strains were found to be effluxing norfloxacin, ciprofloxacin, and ofloxacin, while the third was found to efflux only ofloxacin. A genomic library of S. marcescens wild-type strain UOC-67 was constructed and screened for RND pump-encoding genes by using DNA probes for two putative RND pump-encoding genes. Two different loci were identified: sdeAB, encoding an MFP and an RND pump, and sdeCDE, encoding an MFP and two different RND pumps. Northern blot analysis revealed overexpression of sdeB in two mutant strains effluxing fluoroquinolones. Analysis of the sdeAB and sdeCDE loci in Escherichia coli strain AG102MB, deficient in the RND pump (AcrB), revealed that gene products of sdeAB are responsible for the efflux of a diverse range of substrates that includes ciprofloxacin, norfloxacin, ofloxacin, chloramphenicol, sodium dodecyl sulfate, ethidium bromide, and n-hexane, while those of sdeCDE did not result in any change in susceptibilities to any of these agents.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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 | 0.001 |
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".