Modulation of Staphylococcus aureus gene expression during proliferation in platelet concentrates with focus on virulence and platelet functionality
Bibliographic record
Abstract
Staphylococcus aureus is a well-documented bacterial contaminant in platelet concentrates (PCs), a blood component used to treat patients with platelet deficiencies. This bacterium can evade routine PC culture screening and cause septic transfusion reactions. Here, we investigated the gene expression modulation within the PC niche versus trypticase soy media (TSB) of S. aureus CBS2016-05, a strain isolated from a septic reaction, in comparison to PS/BAC/317/16/W, a strain identified during PC screening. RNA-seq analysis revealed upregulation of the capsule biosynthesis operon (capA-H), surface adhesion factors (sasADF), clumping factor A (clfA), protein A (spa), and anaerobic metabolism genes (pflAB, nrdDG) in CBS2016-05 when grown in PCs versus TSB, implying its enhanced pathogenicity in this milieu, in contrast to the PS/BAC/317/16/W strain. Furthermore, we investigated the impact of S. aureus CBS2016-05 on platelet functionality in spiked PCs versus non-spiked PC units. Flow cytometry analyses revealed a significant decrease in glycoprotein (GP) IIb (CD41) and GPIbα (CD42b) expression, alongside increased P-selectin (CD62P) and phosphatidylserine (annexin V) expression in spiked PCs compared to non-spiked PCs (p = 0.01). Moreover, spiked PCs exhibited a drastic reduction in MitoTrack Red FM and Calcein AM positive platelets (87.3% vs. 29.4%, p = 0.0001 and 95.4% vs. 24.7%, p = 0.0001) in a bacterial cell density manner. These results indicated that S. aureus CBS2016-05 triggers platelet activation and apoptosis, and compromises mitochondrial functionality and platelet viability, in contaminated PCs. Furthermore, this study enhanced our understanding of the effects of platelet-bacteria interactions in the unique PC niche, highlighting S. aureus increased pathogenicity and deleterious effect on platelet functionality in a strain specific manner. Our novel insights serve as a platform to improve PC transfusion safety.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".