Molecular Characterization of Toxic Cyanobacteria in North American and East African Lakes
Bibliographic record
Abstract
Toxic cyanobacterial blooms constitute a threat to the safety and ecological quality of aquatic environments worldwide. Cyclic hepatotoxin, especially microcystin, is the most widely occurring of the cyanotoxins. The aim of this study was to identify the cyanobacterial genotypes present including how many toxic genotypes were present in two North American lakes and one African Lake. All three lakes are prone to cyanobacterial blooms and were sampled in 2005 and 2006: Lake Ontario (Bay of Quinte, Canada), Lake Erie (Maumee Bay, Canada) and Lake Victoria (Nyanza Gulf, Kenya). The cyanobacterial genotypic community was assessed using DNA based analyses of the hypervariable V3 region of the 16S rRNA gene. In addition, the aminotransferase (AMT) domain in modules mcyE and ndaF of the microcystin and nodularin gene cluster respectively was used to detect the presence of hepatotoxic genotypes. Denaturing gradient gel electrophoresis (DGGE) results from this study suggested that hepatotoxin producers were present in all study sites sampled and were most likely members of the genus Microcystis. This study was the first to report the potential for microcystin production in the in-shore and off-shore open lake of Nyanza Gulf in Kenya. A seasonal study of the Bay of Quinte and Maumee Bay showed differences in the cyanobacterial genotypic community from early to late summer. In addition, the cyanobacterial genotypic community from the Bay of Quinte differed from 2005 to 2006 and quantification of the North American samples revealed an increase in cyanobacterial cells from early to late summer. The Bay of Quinte saw relatively no change in hepatotoxic cells from early to late summer but in Maumee Bay hepatotoxic cells increased from undetectable in early summer to dominating the cyanobacterial community by late summer. This study demonstrated the use of DGGE and qPCR of the 16S rRNA-V3 and AMT gene region in monitoring the cyanobacterial community of waterbodies susceptible to toxic cyanobacterial blooms.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".