Monitoring toxigenic <i>Microcystis</i> strains in the Missisquoi bay, Quebec, by PCR targeting multiple toxic gene loci
Why this work is in the frame
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Bibliographic record
Abstract
The increasing incidence of mixed assemblages of toxic and nontoxic cyanobacterial blooms in Quebec's freshwater bodies over the last decade, coupled with inherent inadequacies of current monitoring approaches, warrants development of sensitive and reliable tools for assessing the toxigenic potential of these water blooms. In this study, we applied three independent polymerase chain reaction (PCR) assays that simultaneously target the microcystin synthetase (mcy) genes A, E, and G to rapidly and reliably detect and quantify potentially toxic Microcystis genotypes in the Missisquoi bay, Quebec, Canada. Linear regressions of quantitative PCR threshold cycles (Ct ) against the logarithm of their respective Microcystis cell number equivalents resulted in highly significant linear curves with coefficients of determination (R(2) ) greater than 0.99 (p < 0.0001, n = 6) and reaction efficiencies of 91.0, 95.8, and 92.7%, respectively, for the mcyA, mcyE, and mcyG-based quantitative real-time PCR (qPCR) assays. The three assays successfully estimated potential microcystin-producing Microcystis genotypes from all field samples. The proportions of MicrocystismcyA, mcyE, and mcyG genotypes to total Microcystis cell counts showed substantial spatial variability ranging between 1.7-21.6%, 1.9-11.2%, and 2.2-22.6%, respectively. Correlation of microscopically determined total Microcystis counts to qPCR-based MicrocystismcyA, mcyE, or mcyG cell number equivalents resulted in highly significant associations with R(2) > 0.90. Thus, PCR-based assays targeting the mcyA, mcyG, and/or mcyE genes can serve as powerful screening tools for rapid and sensitive estimation of microcystin-producing Microcystis genotypes in freshwater water bodies.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it