Nitric oxide donor sodium nitroprusside serves as a source of iron supporting <i>Pseudomonas aeruginosa</i> growth and biofilm formation
Bibliographic record
Abstract
ABSTRACT Biofilm dispersal agents, like nitric oxide (NO), restore antimicrobial effectiveness against biofilm infections by inducing bacteria to shift from a biofilm to a planktonic state, thereby overcoming the antimicrobial tolerance typically associated with biofilms. Sodium nitroprusside (SNP) is a widely used NO donor for investigating the molecular mechanisms underlying NO-mediated biofilm dispersal in the nosocomial pathogen Pseudomonas aeruginosa . However, the biofilm effects of SNP are variable depending on the in vitro experimental conditions, with some studies reporting enhanced growth in both planktonic and biofilm forms instead of dispersal. These discrepancies suggest that SNP affects P. aeruginosa biofilm-residing cells beyond the release of NO. In this study, we compared SNP with another NO donor, Spermine NONOate, to systematically contrast their effects on biofilm and planktonic cultures of P. aeruginosa . We found that SNP, but not Spermine NONOate, increased the biomass of P. aeruginosa biofilms in microplate cultures. This effect was also observed when biofilm cultures were supplemented with iron. Additionally, supplementation with SNP rescued the planktonic growth of P. aeruginosa in iron-depleted media similarly to FeSO₄, suggesting that SNP may serve as an iron source. Our findings indicate that the use of SNP as an NO donor in biofilm dispersal may be compromised by its role in promoting both biofilm and planktonic growth through its iron center. Our study cautions investigators using SNP for studying NO-mediated biofilm dispersal. IMPORTANCE Research into biofilm dispersal agent nitric oxide (NO) holds promise for treating biofilm-associated infections. Sodium nitroprusside (SNP), an NO donor widely used in antibiofilm research, has been shown in this study to enhance cell growth and biofilm formation in Pseudomonas aeruginosa by acting as a source of iron. Our results suggest that SNP functions both as an NO and an iron donor, with its iron-releasing properties playing a more dominant role in promoting biofilm growth in closed culture systems. This study underscores the dual but conflicting roles of SNP in biofilm growth, which caution its future development as an NO-based therapeutic strategy for biofilm-associated infections.
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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".