The intrinsic resistome of<i>Pseudomonas aeruginosa</i>to β-lactams
Bibliographic record
Abstract
Pseudomonas aeruginosa is a relevant opportunistic pathogen particularly problematic due to its low intrinsic susceptibility to antibiotics. Intrinsic resistance has been traditionally attributed to the low permeability of cellular envelopes together with the presence of chromosomally-encoded detoxification systems such as multidrug efflux pumps or antibiotic inactivating enzymes. However, some recently published articles indicate that several other elements can contribute to the phenotype of intrinsic resistance of bacterial pathogens. In a recently published article, we explored the chromosomally-encoded determinants that contribute to the phenotype of susceptibility of P. aeruginosa to ceftazidime, imipenem and carbapenem. Using a comprehensive library of transposon-tagged insertion mutants, we found 37 loci in the chromosome of P. aeruginosa that contributed to its intrinsic resistance, because mutants in these loci were more susceptible to antibiotics than their parental strain. 41 further loci could potentially be involved in the acquisition of resistance, because mutants in these loci were less susceptible than their wild-type counterpart. These results indicate that the intrinsic resistome of P. aeruginosa involves several elements, belonging to different functional families and cannot be considered as a specific mechanism of adaptation to the recent usage of antibiotics as therapeutic agents. In the current article, we summarize the findings of the paper and discuss their implications for understanding the evolution of antibiotic resistance and for defining novel targets for the search of new antimicrobials. Finally, the validity of recent theories on the mechanisms of action of antibiotics is discussed taken into consideration the results of our paper and other recently published works on the mechanisms of intrinsic resistance to antibiotics of P. aeruginosa.
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 | 0.001 | 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".