Propidium Monoazide Improves Quantification of Resting Spores of <i>Plasmodiophora brassicae</i> with qPCR
Bibliographic record
Abstract
Plasmodiophora brassicae, which causes clubroot of Brassica crops, persists in soil as long-lived resting spores. Quantitative polymerase chain reaction (qPCR) analysis is often used to quantify resting spores but does not distinguish between DNA of viable and nonviable spores. The impact of pretreating spores with propidium monoazide (PMA), which inhibits amplification of DNA from nonviable microorganisms, was assessed in several experiments. Spore suspensions from immature and mature clubs were heat treated; then, PMA-PCR analyses and bioassays were performed to assess spore viability. Prior to heat treatment, assessments comparing PMA-PCR to qPCR for mature spores were similar, indicating that most of these spores were viable. However, only a small proportion (<26%) of immature spores were amplified in PMA-PCR. Bioassays demonstrated that clubroot severity was much higher in plants inoculated with mature spores than with immature spores. Heat treatment produced little or no change in estimates of mature spores from qPCR but spore estimates from PMA-PCR and clubroot severity in bioassays were both substantially reduced. Estimates of spore concentration with PMA-PCR were less consistent for immature spores. To facilitate use of PMA-PCR on infested soil, a protocol for extracting spores from soil was developed that provided higher extraction efficiency than the standard methods.
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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 | 0.003 |
| 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 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".