Comparative Proteomics Analyses Reveal a Potential Biomarker for the Detection of Vancomycin-Intermediate <i>Staphylococcus aureus</i> Strains
Bibliographic record
Abstract
Vancomycin-intermediate Staphylococcus aureus (VISA) strains tend to develop during glycopeptide treatment of infections caused by methicillin-resistant S. aureus (MRSA). Rapid and effective detection methods for VISA strains are lacking, and mechanisms of resistance are unclear. Here, global comparative proteomic approaches have been used to identify potential biomarkers of intermediate vancomycin resistance. With the use of high-resolution two-dimensional gels and iTRAQ mass tagging, numerous proteins were found to be differentially expressed between clinical MRSA and VISA isolates of the same multilocus sequence type. One of these, the predicted lytic transglycosylase SAV2095 (SceD-like protein), was selected for further study based on both its high level of induction in Mu50 and its predicted role in modeling the cell wall, which is the target of vancomycin. Relative SAV2095 mRNA expression levels were compared between 25 MRSA and VISA/heterogeneous VISA clinical isolates by real-time RT-PCR. The SAV2095 mRNA was significantly induced in all VISA isolates relative to all MRSA strains ( p < 0.001), and significant induction of SAV2095 was also seen for several potential heterogeneous VISA strains that appear vancomycin-sensitive by standard minimum inhibitory concentration-determining methods. Furthermore, strains selected in vitro for increasing levels of resistance from four unrelated clinical MRSA isolates displayed concomitant increases in levels of SAV2095 expression. Together, these results suggest that SAV2095 expression level could serve as a molecular diagnostic marker for the rapid detection of VISA.
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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".