The lack of OmpF, but not OmpC, contributes to increased antibiotic resistance in Serratia marcescens
Bibliographic record
Abstract
The environmental organism Serratia marcescens is one of the primary causes of numerous nosocomial outbreaks and opportunistic infections. Multi-drug resistance is now a common feature among S. marcescens clinical isolates, complicating the efficacy of treatment. Recent reports have attributed antibiotic resistance to altered porin expression as well as perturbation of the intrinsic AmpC beta-lactamase production pathway. In this study, we aimed to genetically correlate the absence of OmpF and OmpC classical porins with increased antibiotic resistance. In generating isogenic porin mutant strains, we avoided incorporating additional resistance through the use of antibiotic cassettes in gene replacement and adopted an alternative strategy in creating clean unmarked mutant strains. We found that lack of OmpF, but not OmpC, significantly increased antibiotic MIC values to the beta-lactam drugs such as ampicillin and cefoxitin as well as to nitrofurantoin. Furthermore, we found that cefoxitin did not induce intrinsic AmpC beta-lactamase production, indicating that the increased MIC values were a result of reduced permeability of cefoxitin due to the lack of OmpF. Genetic deletion of both ompF and ompC did not compromise the integrity of the bacterial cell envelope in optimal growth conditions, suggesting that other outer-membrane porins may function in a compensatory role to facilitate nutrient uptake and cell envelope integrity. Taken together, to our knowledge this is the first study that genetically correlates increased antibiotic resistance with altered porin expression in S. marcescens.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".