Proteomic analysis of <i>Pseudomonas aeruginosa</i> grown under magnesium limitation
Bibliographic record
Abstract
In this study, large-scale qualitative and quantitative proteomic technology was applied to the analysis of the opportunistic bacterial pathogen Pseudomonas aeruginosa grown under magnesium limitation, an environmental condition previously shown to induce expression of various virulence factors. For quantitative analysis, whole cell and membrane proteins were differentially labeled with isotope-coded affinity tag (ICAT) reagents and ICAT reagent-labeled peptides were separated by two-dimensional chromatography prior to analysis by electrospray ionization-tandem mass spectrometry (ESI-MS/MS) in an ion trap mass spectrometer (ITMS). To increase the number of protein identifications, gas-phase fractionation (GPF) in the m/z dimension was employed for analysis of ICAT peptides derived from whole cell extracts. The experiments confirmed expression of 1331 P. aeruginosa proteins of which 145 were differentially expressed upon limitation of magnesium. A number of conserved Gram-negative magnesium stress-response proteins involved in bacterial virulence were among the most abundant proteins induced in low magnesium. Comparative ICAT analysis of membrane versus whole cell protein indicated that growth of P. aeruginosa in low magnesium resulted in altered subcellular compartmentalization of large enzyme complexes such as ribosomes. This result was confirmed by 2-D PAGE analysis of P. aeruginosa outer membrane proteins. This study shows that large-scale quantitative proteomic technology can be successfully applied to the analysis of whole bacteria and to the discovery of functionally relevant biologic phenotypes.
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How this classification was reachedexpand
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 | 0.002 |
| Bibliometrics | 0.000 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".