<i>Expression of</i> Microcystis <i>biosynthetic gene clusters in natural populations suggests temporally dynamic synthesis of novel and known secondary metabolites in western Lake Erie</i>
Bibliographic record
Abstract
Summary Microcystis spp. produces diverse secondary metabolites within freshwater cyanoHABs around the world. In addition to the biosynthetic gene clusters (BGCs) encoding known compounds, Microcystis genomes harbor numerous BGCs of unknown function, indicating its poorly understood chemical repertoire. While recent studies show that Microcystis produces several metabolites in the lab and field, little work has focused on analyzing the abundance and expression of its broader suite of BGCs during cyanoHAB events. Here, we use metagenomic and metatranscriptomic approaches to track the relative abundance of Microcystis BGCs and their transcripts throughout the 2014 western Lake Erie cyanoHAB. Results indicate the presence of several transcriptionally active BGCs that are predicted to synthesize both known and novel secondary metabolites. The abundance and expression of these BGCs shifted throughout the bloom, with transcript abundance levels correlating with temperature, nitrate and phosphorus concentrations, and the abundance of co-occurring predatory and competitive eukaryotic microorganisms, suggesting the importance of both abiotic and biotic controls in regulating expression. This work highlights the need for understanding the chemical ecology and potential risks to human and environmental health posed by secondary metabolites that are produced but unmonitored, as well as the potential discovery of pharmaceutical compounds from cyanoHAB-derived BGCs. Originality-Statement of Significance Microcystis spp . dominate cyanobacterial harmful algal blooms (cyanoHABs) worldwide and pose significant threats to water quality through the production of numerous secondary metabolites, many of which are toxic. While the toxicity and biochemistry of microcystins and several other compounds have been well studied, the broader suite of secondary metabolites produced by Microcystis remains poorly understood, leaving gaps in our understanding of their impacts on ecology, human and ecosystem health, or potential pharmaceutical application. In this study, we use metagenomic and transcriptomic datasets to examine the diversity of genes encoding synthesis of secondary metabolites in natural Microcystis populations and assess their patterns of transcription in the context of biotic and abiotic conditions in western Lake Erie cyanoHABs. Our results reveal the presence of a large diversity of both known gene clusters that encode toxic secondary metabolites as well as novel ones that encode cryptic compounds. This research highlights the need for targeted studies of the secondary metabolite diversity in western Lake Erie, a vital freshwater source to the United States and Canada.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".