Multiplex Real-Time PCR for Rapid Staphylococcal Cassette Chromosome <i>mec</i> Typing
Bibliographic record
Abstract
Rapid identification and typing of methicillin (meticillin)-resistant Staphylococcus aureus (MRSA) is important for understanding the molecular epidemiology and evolution of MRSA and offers many advantages for controlling transmission in both health care and community settings. We developed a rapid molecular beacon real-time PCR (MB-PCR) assay for staphylococcal cassette chromosome mec (SCCmec) typing. The design of this system is based on the established definition of SCCmec types, namely, the combination of the mec class complex with the ccr allotype. The assay consists of two multiplex panels, the combination of which results in two targets (mec class, ccr) for each SCCmec type. MB-PCR panel I targets mecA, ccrB2, mecI, and the DeltamecR1-IS1272 junction (mec class B); it can definitively identify SCCmec types II and IV. MB-PCR panel II detects ccrC, ccrB1, ccrB3, ccrB4, and the DeltamecR1-IS431 junction (mec class C2) and is therefore capable of identifying SCCmec types I, III, V, and VI in combination with panel I. The method can also detect the recently described novel SCCmec type VIII (ccrAB4 with mec class A). Our assay demonstrated 100% concordance when applied to 162 MRSA strains previously characterized by traditional SCCmec typing schemes. Four geographically and temporally diverse S. aureus collections were also successfully classified by our assay, along with 1,683 clinical isolates comprising both hospital- and community-associated MRSA and methicillin-susceptible S. aureus strains. As many as 96 isolates can be classified easily within 3 to 4 h, including DNA isolation, PCR cycling, and analysis. The assay is rapid, robust, sensitive, and cost-effective, allowing for high-throughput SCCmec typing of MRSA isolates.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".