Development and evaluation of quadruplex droplet digital PCR assay for rapid detection of molecular markers associated with macrocyclic lactone resistance and susceptibility in Dirofilaria immitis
Bibliographic record
Abstract
Due to climate change and human interventions, there has been an increase in D. immitis infections, underscoring the necessity for monitoring the spread and extent of resistance. In our prior research, we introduced a rapid test utilizing four predominant SNP markers at loci 15709 (SNP1), 30575 (SNP2), 21554 (SNP3), and 9400 (SNP7) linked to ML resistance. Our findings highlighted SNP1 and SNP2 as potent predictive markers, offering suitability for the rapid detection and monitoring of drug resistance. Therefore, we developed a cost-effective test using droplet digital PCR (ddPCR) technology to perform a quadruplex assay to assess alternate allele frequency. Our assay can identify both SNP1 and SNP2 wildtype and mutant targets in a single sample. We tested the performance of our 4-plex assay on 8 laboratory-maintained isolates, including Missouri (MO), Berkeley, JYD-34, Metairie-2014, Yazoo-2013, GA-2, GA-3, and Big Head, and further validated the sensitivity using clinical isolates from the United States. Our assay demonstrated consistent results compared to the standard MiSeq sequencing and ddPCR duplex assay. Notably, we showcased the utility of ddPCR for direct genotyping of D. immitis infected whole blood from two well-characterized isolates, MO and JYD-34. This approach streamlined the assay workflow and lowered costs, thus enhancing affordability for larger genotyping studies.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".