Optimization of duplex real-time PCR with melting-curve analysis for detecting the microsporidian parasites <i>Nosema apis</i> and <i>Nosema ceranae</i> in <i>Apis mellifera</i>
Bibliographic record
Abstract
Abstract Honey bees, Apis mellifera (L.) (Hymenoptera: Apidae), are parasitized by the microsporidians Nosema apis (Zander) and Nosema ceranae (Fries). Molecular techniques are commonly used to differentiate between these parasites because light microscopy is inadequate. Our objectives were to (i) adapt the previously published duplex polymerase chain reaction (PCR) targeting the 16S rRNA gene of N. apis (321APIS-FOR, 321APIS-REV) and N. ceranae (218MITOC-FOR, 218MITOC-REV) using qualitative real-time PCR assay with SYBR® Green I dye (R-T PCR) and DNA melting-curve analysis, and (ii) determine whether the two Nosema species can be detected simultaneously in honey bees. Total spore counts and purified total genomic DNA were obtained from 37 bee samples (19 individual workers and 18 pooled samples of 15 workers) collected in Nova Scotia, Prince Edward Island, and Newfoundland, Canada. Overall, the prevalence of Nosema species was 86.5% (32/37 samples of bee DNA), based on conventional PCR and the optimized R-T PCR assay. The melting-curve analysis showed three groups of curve profiles that could determine the prevalence of N. apis, N. ceranae, and co-infection (21.9%, 56.2%, and 21.9%, respectively). The duplex R-T PCR assay was efficient, specific, and more sensitive than duplex conventional PCR because co-infection was identified in 5.4% (n = 2) more samples. Sequencing of R-T PCR products confirmed the results of the melting-curve analysis. Duplex R-T PCR with melting-curve analysis is a sensitive and rapid method of detecting N. apis, N. ceranae, and co-infection in honey bees.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".