Mass-Spectrometry and Genomic Approaches to Investigating Cyanopeptides in Environmental Samples and Cultured Microcystis
Bibliographic record
Abstract
Cyanobacterial blooms pose a significant threat to freshwater ecosystems in Canada, a problem that is predicted to worsen with climate change.A major concern during blooms is the production of cyanopeptides, a diverse group of biologically active secondary metabolites.Beyond the well studied class of microcystins, advancements in analytical techniques have allowed for the identification of hundreds of other cyanopeptides including cyanopeptolins, microginins, anabaenopeptins, aeruginosins, microviridins, and cyanobactins.Although it remains unclear why cyanobacteria produce such a large and diverse array of cyanopeptides, one of the primary predictors of microcystin production has been identified as the cellular growth rate.In this thesis, I investigated the effects of altering growth rates on the production of multiple classes of cyanopeptides.Two Microcystis aeruginosa strains (CPCC 300, CPCC 464), differing in their chemical profiles, were grown as semi-continuous batch cultures to compare congener composition and total concentrations between maximum growth (µmax) and a 10% per day dilution rate.There was no significant difference in the production and composition of cyanopeptides (considering both total concentrations and cellular quotas) between growth rates within either strain.Using similar techniques of high-resolution tandem mass spectrometry, combined with global natural products social molecular networking (GNPS), I then characterized the cyanopeptide profile from a dynamic Microcystis bloom in Missisquoi Bay, Lake Champlain, both in water and air, in late summer.Among the 151 cyanopeptides detected, cyanopeptolins were found to be the most abundant and chemically diverse class of cyanopeptides, similar to what was found in the cultured strains.Cyanopeptide biosynthesis genes quantified using digital droplet PCR were highly correlated with the chemical concentrations of major groups of cyanopeptides in water (microcystins, cyanopeptolins, anabaenopeptins).Cyanopeptides and cyanobacterial genes were not consistently detected in the air samples, despite high concentrations found in the water.Thesis Conclusions ......
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".