Quantification of endophyte Serendipita indica in Brassica napus roots by qPCR
Bibliographic record
Abstract
Context The fungal endophyte Serendipita indica enhances plant growth and plant resistance to biotic and abiotic stresses. Inoculum concentration greatly impacts the endophyte–plant interaction from mutualism to antagonism. Aims and methods We used both microscopy and qPCR to examine the effect of inoculum concentrations on the extent (%) and density of Brassica napus L. root colonisation by S. indica. B. napus seeds were inoculated with the fungus at five different inoculum concentrations (1–10% w/w basis). Key results Standard curves were constructed using the mean threshold cycle (Ct) and serially diluted gDNA ranging between 4.14 × 102 and 2.65 × 105 colony forming units (CFU). The result indicated a linear relationship between Ct and the log of input DNA. Variation in inoculum concentration significantly affected the root colonisation density by the fungus shown by qPCR. However, the percent root colonisation (PRC) measure was not affected and remained the same across all the treatments. Conclusions Our findings show that the qPCR assay developed will determine the colonisation density whereas PRC gives a measure of the incidence of infected roots. Also, we suggest that the optimum quantity of inoculum is a key factor for a successful interaction that impacts the plant–S. indica interaction. Implications To our knowledge, this is the first study that quantitative qPCR has been used to investigate the correlation between inoculum quantities and the corresponding density of root colonisation in S. indica.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".