Development of Rapid Isothermal Amplification Assays for Detection of<i>Phytophthora</i>spp. in Plant Tissue
Bibliographic record
Abstract
Several isothermal amplification techniques recently have been developed that are tolerant of inhibitors present in many plant extracts, which can reduce the need for obtaining purified DNA for running diagnostic assays. One such commercially available technique that has similarities with real-time polymerase chain reaction (PCR) for designing primers and a labeled probe is recombinase polymerase amplification (RPA). This technology was used to develop two simple and rapid approaches for detection of Phytophthora spp.: one genus-specific assay multiplexed with a plant internal control and the other species-specific assays for Phytophthora ramorum and P. kernoviae. All assays were tested for sensitivity (ranging from 3 ng to 1 fg of DNA) and specificity using DNA extracted from more than 136 Phytophthora taxa, 21 Pythium spp., 1 Phytopythium sp., and a wide range of plant species. The lower limit of linear detection using purified DNA was 200 to 300 fg of DNA in all pathogen RPA assays. Six different extraction buffers were tested for use during plant tissue maceration and the assays were validated in the field by collecting 222 symptomatic plant samples from over 50 different hosts. Only 56 samples were culture positive for Phytophthora spp. whereas 91 were positive using the Phytophthora genus-specific RPA test and a TaqMan real-time PCR assay. A technique for the generation of sequencing templates from positive RPA amplifications to confirm species identification was also developed. These RPA assays have added benefits over traditional technologies because they are rapid (results can be obtained in as little as 15 min), do not require DNA extraction or extensive training to complete, use less expensive portable equipment than PCR-based assays, and are significantly more specific than current immunologically based methods. This should provide a rapid, field-deployable capability for pathogen detection that will facilitate point-of-sample collection processing, thereby reducing the time necessary for accurate diagnostics and making management decisions.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".