Metagenomics reveals spatial variation in cyanobacterial composition, function, and biosynthetic potential in the Winam Gulf, Lake Victoria, Kenya
Bibliographic record
Abstract
ABSTRACT The Winam Gulf in the Kenyan region of Lake Victoria experiences prolific, year-round cyanobacterial harmful algal blooms (cyanoHABs) which pose threats to human, livestock, and ecosystem health. To our knowledge, there is limited molecular research on the gulf’s cyanoHABs, and thus, the strategies employed for survival and proliferation by toxigenic cyanobacteria in this region remain largely unexplored. Here, we used metagenomics to analyze the Winam Gulf’s cyanobacterial composition, function, and biosynthetic potential. Dolichospermum was the dominant bloom-forming cyanobacterium, co-occurring with Microcystis at most sites. Microcystis and Planktothrix were more abundant in shallow and turbid sites. Metagenome-assembled genomes (MAGs) of Dolichospermum harbored nitrogen fixation genes, suggesting diazotrophy as a potential mechanism supporting the proliferation of Dolichospermum in the nitrogen-limited gulf. Over 300 biosynthetic gene clusters (BGCs) putatively encoding the synthesis of toxins and other secondary metabolites were identified across the gulf, even at sites where there were no visible cyanoHAB events. Almost all BGCs identified had no known synthesis product, indicating a diverse and novel biosynthetic repertoire capable of synthesizing harmful or potentially therapeutic metabolites. Microcystis MAGs contained mcy genes encoding the synthesis of hepatotoxic microcystins which are a concern for drinking water safety. These findings illustrate the spatial variation of bloom-forming cyanobacteria in the Winam Gulf and their available strategies to dominate different ecological niches. This study underscores the need for further use of genomic techniques to elucidate the dynamics and mitigate the potentially harmful effects of cyanoHABs and their associated toxins on human, environmental, and economic health. IMPORTANCE The Winam Gulf (Kenya) is a vital resource that experiences prolific cyanobacterial harmful algal blooms (cyanoHABs). Bloom-forming cyanobacteria produce cyanotoxins, threatening human and environmental health, recreation, and fishing. However, cyanotoxin production in the gulf has not been linked to a specific type of cyanobacteria. We used DNA sequencing of whole microbial communities to track the species of cyanobacteria present across the gulf and investigate the genes responsible for synthesis of known and novel toxins. Our results reveal Dolichospermum as the main bloom-forming cyanobacteria in the gulf, often co-occurring with high abundance of toxigenic Microcystis. Over 300 unique gene clusters were found, with most predicted to encode the synthesis of uncharacterized molecules. These results provide initial insights into the diverse biosynthetic potential encoded by cyanobacteria in the Winam Gulf and underscore the need to further elucidate and investigate the effects of known and novel molecules produced in cyanoHABs in this region.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".