Metabolic profiling of <i>Staphylococcus aureus</i> cultivated under aerobic and anaerobic conditions with <sup>1</sup>H NMR-based nontargeted analysis
Bibliographic record
Abstract
Staphylococcus aureus is a major pathogen in the medical area and food-producing sector. Detailed analyses of its basic cell physiology will help comprehensively understand this pathogen, which will be useful for developing novel diagnostic and treatment tools. Oxygen is one of the most crucial growth-limiting factors for S. aureus. In this study, to characterize and distinguish metabolic profiles of S. aureus cultivated under aerobic and anaerobic conditions, nontargeted analyses of both types of cultures were carried out using (1)H nuclear magnetic resonance spectroscopy. Fifty compounds were identified by Chenomx software. Characteristics of metabolic profiles were achieved by using principal components analysis. During aerobic growth, S. aureus mainly consumed glucose, alanine, arginine, glycine, isoleucine, leucine, phenylalanine, and acetate. Meanwhile, it accumulated 17 metabolites, mainly 2-oxoglutarate, isobutyrate, isovalerate, succinate, and ethanol. Under anaerobic condition, S. aureus mainly consumed glucose, arginine, and threonine. Meanwhile, it accumulated 13 metabolites, mainly ethanol, lactate, and ornithine. The representative metabolites that could most significantly differentiate metabolic profiles of S. aureus were isobutyrate, isovalerate, and succinate in aerobic cultivation; and lactate, ethanol, and ornithine in anaerobic cultivation. Among these metabolites, isobutyrate and ornithine were present only in aerobic and anaerobic culture, respectively.
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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) | 0.000 | 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 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".