Comparative study on nutrient depletion-induced lipidome adaptations in Staphylococcus haemolyticus and Staphylococcus epidermidis
Bibliographic record
Abstract
Staphylococcus species are emerging opportunistic pathogens that cause outbreaks of hospital and community-acquired infections. Some of these bacteria such as methicillin-resistant Staphylococcus aureus (MRSA) are difficult to treat due to their resistance to multiple antibiotics. We carried out a comparative study on the lipidome adaptations in response to starvation in the two most common coagulase-negative Staphylococcus species: a S. epidermidis strain sensitive to ampicillin and erythromycin and a S. haemolyticus strain resistant to both. The predominant fatty acid composition in glycerolipids was (17:0-15:0) in both bacteria. During the exponential phase, the two bacterial lipidomes were similar. Both were dominated by diacylglycerol (DAG), phosphatidylglycerol (PG), lysyl-phosphatidylglycerol (Lysyl-PG) and Diglucosyl-diacylglycerol (DGDG). Alanyl-PG was detected in small amounts in both bacterial lipids. N-succinyl-lysyl-PG was detected only in S. haemolyticus, while lysyl-DAG only in S. epidermidis. As the two bacteria entered stationary phase, both lipidomes became essentially nitrogen-free. Both bacteria accumulated large amounts of free fatty acids. Strikingly, the lipidome of S. epidermidis became dominated by cardiolipin (CL), while that of S. haemolyticus was simplified to DGDG and PG. The S. epidermidis strain also produced acyl-phosphatidylglycerol (APG) in the stationary phase.
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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".