Differentiation of Staphylococcus spp. by high-resolution melting analysis
Bibliographic record
Abstract
High-resolution melting analysis (HRMA) is a fast (post-PCR) high-throughput method to scan for sequence variations in a target gene. The aim of this study was to test the potential of HRMA to distinguish particular bacterial species of the Staphylococcus genus even when using a broad-range PCR within the 16S rRNA gene where sequence differences are minimal. Genomic DNA samples isolated from 12 reference staphylococcal strains (Staphylococcus aureus, Staphylococcus capitis, Staphylococcus caprae, Staphylococcus epidermidis, Staphylococcus haemolyticus, Staphylococcus hominis, Staphylococcus intermedius, Staphylococcus saprophyticus, Staphylococcus sciuri, Staphylococcus simulans, Staphylococcus warneri, and Staphylococcus xylosus) were subjected to a real-time PCR amplification of the 16S rRNA gene in the presence of fluorescent dye EvaGreen™, followed by HRMA. Melting profiles were used as molecular fingerprints for bacterial species differentiation. HRMA of S. saprophyticus and S. xylosus resulted in undistinguishable profiles because of their identical sequences in the analyzed 16S rRNA region. The remaining reference strains were fully differentiated either directly or via high-resolution plots obtained by heteroduplex formation between coamplified PCR products of the tested staphylococcal strain and phylogenetically unrelated strain.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 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".