Gene expression analysis of the SdeAB multidrug efflux pump in antibiotic-resistant clinical isolates of Serratia marcescens
Bibliographic record
Abstract
PURPOSE: Many isolates of Serratia marcescens, a well-known opportunistic pathogen, can be multidrug resistant. Fluoroquinolones are among the most important groups of antibiotics used for treatment of these organisms. However, fluoroquinolone resistance among S. marcescens isolates is fast increasing. Drug extrusion through efflux pumps like SdeAB/ HasF is one of the major mechanisms of resistance to fluoroquinolones. This study was carried out to analyze, through gene expression analysis of sdeB, the relative contribution of this mechanism toward fluoroquinolone resistance in clinical isolates of Serratia. MATERIALS AND METHODS: Total RNA from 45 clinical isolates of S. marcescens was isolated. Quantitative real-time RT PCR was performed on the extracted RNA to study the gene expression of sdeB and was normalized to the sdeB expression in the standard strain of S. marcescens. RESULTS: Of the 45 isolates analyzed, sdeB expression was found to be elevated in 20 isolates (44%). Of these 20 isolates, eight (40%) were fully resistant to at least one of the fluoroquinolones studied. Conversely, of the 20 isolates that over-expressed sdeB, 12 (60%) were fully sensitive to all fluoroquinolones tested. CONCLUSIONS: Drug efflux pumps are an important means of fluoroquinolone resistance among clinically important species of Serratia. The expression of these pumps can be up-regulated in the presence of antibiotics and have the potential for changing the phenotype from sensitive to resistant, thus contributing to therapeutic failures.
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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".