Genetic Diversity and Anatoxin Profiles of Freshwater Benthic Cyanobacteria From Nova Scotia (Canada)
Bibliographic record
Abstract
Some mat-forming cyanobacteria produce harmful cyanotoxins, yet benthic species remain understudied compared to planktonic counterparts. This study assesses the diversity, distribution and toxin production of mat-forming cyanobacteria across lentic and lotic systems in Nova Scotia, Canada. We documented greater cyanobacterial species richness in lentic environments, with six dominant species distributed into two major Microcoleus clades, five of which represent putative novel taxa. Two Microcoleus species with the genetic repertoire to produce anatoxins were prevalent. One has been previously reported in Canada, while the second represents a novel species found exclusively in an environment impacted by discharge from a water treatment plant. We observed variability in the gene clusters responsible for the biosynthesis of anatoxin-a and associated analogues (ATXs), including the discovery of a novel anaG variant with a ~ 1.7 kb insertion in a Microcoleus strain dominating homoanatoxin-producing mats. This extended anaG, encoding a polyketide synthase with an additional methyltransferase domain, coexists with shorter variants, leading to the production of a mixture of ATXs. These findings highlight the genetic diversity of benthic cyanobacteria in freshwater environments, with Microcoleus as the primary contributor to the production of ATXs in both lentic and lotic systems, underscoring their potential to produce harmful toxins.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".