A Rapid and Highly Sensitive CRISPR Assay Utilizing Cas12a Orthologs for the Detection of Novel Duck Reovirus
Bibliographic record
Abstract
Abstract The novel duck reovirus (NDRV) disease presents a significant threat to the poultry industry due to the absence of effective therapeutic measures. As a result, there is an urgent need to develop innovative rapid diagnostic methods for early virus detection. In this study, we developed a Rapid Visual CRISPR Assay to detect the NDRV S3 gene using novel Cas12a orthologs. Specifically, we compared the performance of two candidates, Gs12-16 and Gs12-18, in detecting the NDRV S3 gene to identify a highly sensitive and efficient CRISPR-based diagnostic method. Our results demonstrated that both Gs12-16 and Gs12-18 exhibited strong cis - and trans -cleavage activities for classical “TTTV” protospacer adjacent motif (PAM)-containing targets in vitro , although they required different reaction temperatures. Notably, Gs12-18 showed relatively higher activity for dsDNA targets compared to Gs12-16, indicating that Gs12-18 is more suitable for CRISPR-based nucleic acid detection applications. To leverage these properties, we integrated Gs12-18 with loop-mediated isothermal amplification (LAMP) technology to establish a LAMP-CRISPR/Gs12-18-mediated method for detecting the NDRV S3 gene. This approach enables highly sensitive and visually detectable on-site identification of the NDRV S3 gene, achieving a sensitivity of 38 copies per reaction. Our LAMP-CRISPR/Gs12-18-based method can be utilized for highly sensitive detection of NDRV nucleic acids.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".