<i>De novo</i> evolution of antibiotic resistance to Oct-TriA <sub>1</sub>
Bibliographic record
Abstract
Abstract The rise of antimicrobial resistance as a global health concern has led to a strong interest in compounds able to inhibit the growth of bacteria without detectable levels of resistance evolution. A number of these compounds have been reported in recent years, including the tridecaptins, a small family of lipopeptides typified by the synthetic analogue octyl-tridecaptin A 1 . Hypothesizing that prior reports of negligible resistance evolution have been due in part to limitations in the laboratory evolution systems used, we have attempted to select for resistant mutants using a soft agar gradient evolution (SAGE) system developed by our lab. Following optimization of the media conditions by incorporation of the anti-synaeresis agent xanthan gum into the agar matrix, we successfully evolved high-level resistance to both octyl-tridecaptin A 1 as well as the challenging lipopeptide antibiotic polymyxin B. Decreased tridecaptin susceptibility was linked to mutations in outer membrane proteins ompC , lptD and mlaA , with the effect of these genes confirmed through a mix of allelic replacement and knockout studies. Overall, this work demonstrates the robust evolutionary potential of bacteria, even in the face of challenging antimicrobial 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 | 0.000 |
| 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 | 0.001 |
| 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".