Extracellular DNA Chelates Cations and Induces Antibiotic Resistance in Pseudomonas aeruginosa Biofilms
Bibliographic record
Abstract
Biofilms are surface-adhered bacterial communities encased in an extracellular matrix composed of DNA, bacterial polysaccharides and proteins, which are up to 1000-fold more antibiotic resistant than planktonic cultures. To date, extracellular DNA has been shown to function as a structural support to maintain Pseudomonas aeruginosa biofilm architecture. Here we show that DNA is a multifaceted component of P. aeruginosa biofilms. At physiologically relevant concentrations, extracellular DNA has antimicrobial activity, causing cell lysis by chelating cations that stabilize lipopolysaccharide (LPS) and the outer membrane (OM). DNA-mediated killing occurred within minutes, as a result of perturbation of both the outer and inner membrane (IM) and the release of cytoplasmic contents, including genomic DNA. Sub-inhibitory concentrations of DNA created a cation-limited environment that resulted in induction of the PhoPQ- and PmrAB-regulated cationic antimicrobial peptide resistance operon PA3552-PA3559 in P. aeruginosa. Furthermore, DNA-induced expression of this operon resulted in up to 2560-fold increased resistance to cationic antimicrobial peptides and 640-fold increased resistance to aminoglycosides, but had no effect on beta-lactam and fluoroquinolone resistance. Thus, the presence of extracellular DNA in the biofilm matrix contributes to cation gradients, genomic DNA release and inducible antibiotic resistance. DNA-rich environments, including biofilms and other infection sites like the CF lung, are likely the in vivo environments where extracellular pathogens such as P. aeruginosa encounter cation limitation.
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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 | 0.000 |
| 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".