Genetic determinants of increased sodium hypochlorite and ciprofloxacin susceptibility in <i>Pseudomonas aeruginosa</i> PA14 biofilms
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Reactive chlorine species (RCS) like sodium hypochlorite (NaOCl) are potent oxidizing agents and widely used biocides in surface disinfection, water treatment, and biofilm elimination. Moreover, RCS are also produced by the human immune system to kill invading pathogens. However, bacteria have developed mechanisms to survive the damage caused by RCS. Using the comprehensive Pseudomonas aeruginosa PA14 transposon mutant library in a genetic screen, we identified a total of 28 P. aeruginosa PA14 mutants whose biofilms showed increased susceptibility to NaOCl in comparison to PA14 WT biofilms. Of these, ten PA14 mutants with a disrupted apaH, PA0793, acsA, PA1506, PA1547, PA3728, yajC, queA, PA3869, or PA14_32840 gene presented a 4-fold increase in NaOCl susceptibility compared to wild-type biofilms. While none of these mutants showed a defect in biofilm formation or attenuated susceptibility of biofilms toward the oxidant hydrogen peroxide (H2O2), all but PA14_32840 also exhibited a 2–4-fold increase in susceptibility toward the antibiotic ciprofloxacin. Further analyses revealed attenuated levels of intracellular ROS and catalase activity only for the apaH and PA1547 mutant, providing insights into the oxidative stress response in P. aeruginosa biofilms. The findings of this paper highlight the complexity of biofilm resistance and the intricate interplay between different mechanisms to survive oxidative stress. Understanding resistance strategies adopted by biofilms is crucial for developing more effective ways to fight resistant bacteria, ultimately contributing to better management of bacterial growth and resistance in clinical and environmental settings.
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.
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 | 0.000 | 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 it