Suspension Bead Array of the Single-Stranded Multiplex Polymerase Chain Reaction Amplicons for Enhanced Identification and Quantification of Multiple Pathogens
Bibliographic record
Abstract
Rapid identification of single and multiple infectious agents is vital in clinical settings and during biothreat attack. This study assesses the assay of single-stranded multiplex polymerase chain reaction (PCR) amplicons by suspension bead array (SSMP-SBA) for multiple pathogens identification in a single-tube reaction. A 15-plex assay for identification of 11 highly infectious pathogens was developed to evaluate the performance of SSMP-SBA. Pathogen-specific amplicons were obtained by sequential amplification of genomic DNAs using gene-specific primers tagged with artificial unique sequences and unique primers of which the reverse primer was modified by biotin and phosphorothioate. The SSMP products generated by T7 exonuclease-mediated DNA hydrolysis were hybridized to 15 sets of beads coupled with gene-specific and control oligonucleotide probes for pathogen identification and quantification by flow cytometry. This method was validated via assessment of 57 reference strains and one clinical bacterial isolate. All 11 pathogens can be detected by the 15-plex SSMP-SBA assay, and this design significantly enhanced the signal-to-noise ratio and improved the assay performance. This assay achieves similar sensitivity to our in-house real-time PCR system with the limit of detection equivalent to 5-100 genome copies and a linear dynamic range crossing three to five logs. In the validation assay, a 100% accuracy rate was achieved when the pathogens were among the target species. Notably, the species of pathogens were accurately identified from the samples with multiple infections. SSMP-SBA presents superior performance with multiplexing capability in a single-tube reaction and provides a new approach for detection and species identification of multiple pathogen infections.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".