Triclosan Can Select for an AdeIJK-Overexpressing Mutant of Acinetobacter baumannii ATCC 17978 That Displays Reduced Susceptibility to Multiple Antibiotics
Bibliographic record
Abstract
In order to determine if triclosan can select for mutants of Acinetobacter baumannii ATCC 17978 that display reduced susceptibilities to antibiotics, we isolated a triclosan-resistant mutant, A. baumannii AB042, by serial passaging of A. baumannii ATCC 17978 in growth medium supplemented with triclosan. The antimicrobial susceptibility of AB042 was analyzed by the 2-fold serial dilution method. Expression of five different resistance-nodulation-division (RND) pump-encoding genes (adeB, adeG, adeJ, A1S_2818, and A1S_3217), two outer membrane porin-encoding genes (carO and oprD), and the MATE family pump-encoding gene abeM was analyzed using quantitative reverse transcriptase (qRT) PCR. A. baumannii AB042 exhibited elevated resistance to multiple antibiotics, including piperacillin-tazobactam, doxycycline, moxifloxacin, ceftriaxone, cefepime, meropenem, doripenem, ertapenem, ciprofloxacin, aztreonam, tigecycline, and trimethoprim-sulfamethoxazole, in addition to triclosan. Genome sequencing of A. baumannii AB042 revealed a (116)G→V mutation in fabI, the gene encoding the target enzyme for triclosan. Expression analysis of efflux pumps showed overexpression of the AdeIJK pump, and sequencing of adeN, the gene that encodes the repressor of the adeIJK operon, revealed a 73-bp deletion which would cause a premature termination of translation, resulting in an inactive truncated AdeN protein. This work shows that triclosan can select for mutants of A. baumannii that display reduced susceptibilities to multiple antibiotics from chemically distinct classes in addition to triclosan resistance. This multidrug resistance can be explained by the overexpression of the AdeIJK efflux pump.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 | 0.001 |
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".