A comprehensive proteomics analysis of the response of <i>Pseudomonas aeruginosa</i> to nanoceria cytotoxicity
Bibliographic record
Abstract
The increased commercial use and spread of nanoceria raises concerns about the risks associated with its effects on living organisms. Although Pseudomonas aeruginosa may be ubiquitous in nature, it is largely found in locations closely linked with human activity. P. aeruginosa san ai was used as a model organism for a deeper understanding of the interaction between biomolecules of the bacteria with this intriguing nanomaterial. A comprehensive proteomics approach along with analysis of altered respiration and production of targeted/specific secondary metabolites was conducted to study the response of P. aeruginosa san ai to nanoceria. Quantitative proteomics found that proteins associated with redox homeostasis, biosynthesis of amino acids, and lipid catabolism were upregulated. Proteins from outer cellular structures were downregulated, including transporters responsible for peptides, sugars, amino acids and polyamines, and the crucial TolB protein of the Tol-Pal system, required for the structural formation of the outer membrane layer. In accordance with the altered redox homeostasis proteins, an increased amount of pyocyanin, a key redox shuttle, and the upregulation of the siderophore, pyoverdine, responsible for iron homeostasis, were found. Production of extracellular molecules, e.g. pyocyanin, pyoverdine, exopolysaccharides, lipase, and alkaline protease, was significantly increased in P. aeruginosa san ai exposed to nanoceria. Overall, nanoceria at sublethal concentrations induces profound metabolic changes in P. aeruginosa san ai and provokes increased secretion of extracellular virulence factors, revealing the powerful influence this nanomaterial has on the vital functions of the microorganism.
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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".