Non-genetic mechanisms communicating antibiotic resistance: rethinking strategies for antimicrobial drug design
Bibliographic record
Abstract
INTRODUCTION: Infections by multidrug-resistant bacteria are of great concern worldwide. In many cases, resistance is not due to the presence of specific antibiotic-modifying enzymes, but rather associated with a general impermeability of the bacterial cell envelope. The molecular bases of this intrinsic resistance are not completely understood. Moreover, horizontal gene transfers cannot solely explain the spread of intrinsic resistance among bacterial strains. AREAS COVERED: This review focuses on the increased intrinsic antibiotic resistance mediated by small molecules. These small molecules can either be secreted from bacterial cells of the same or different species (e.g., indole, polyamines, ammonia, and the Pseudomonas quinolone signal) or be present in the bacterial cell milieu, whether in the environment, such as indole acetic acid and other plant hormones, or in human tissues and body fluids, such as polyamines. These molecules are metabolic byproducts that act as infochemicals and modulate bacterial responses toward antibiotics leading to increasing or decreasing resistance levels. EXPERT OPINION: The non-genetic mechanisms of antibiotic response modulation and communication discussed in this review should reorient our thinking of the mechanisms of intrinsic resistance to antibiotics and its spread across bacterial cell populations. The identification of chemical signals mediating increased intrinsic antibiotic resistance will expose novel critical targets for the development of new antimicrobial strategies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".