Analysis of bacterioplankton genes in an impaired Great Lakes harbour reveals seasonal metabolic shifts and a previously undetected cyanobacterium
Bibliographic record
Abstract
Hamilton Harbour is an impaired embayment of Lake Ontario that experiences seasonal algal blooms despite decades of remedial efforts. To study the harbour’s cyanobacterial and heterotrophic bacterial communities, we extracted and sequenced community DNA from surface water samples collected biweekly from different sites during summer and fall. Assembled contigs were annotated at the phylum level, and Cyanobacteria were further characterized at order and species levels. Actinobacteria were most abundant in early summer, while Cyanobacteria were dominant in mid-summer. Microcystis aeruginosa and Limnoraphis robusta were most abundant throughout the sampling period, expanding the documented diversity of Cyanobacteria in Hamilton Harbour. Functional annotations were performed using the MG-RAST pipeline and SEED database, revealing that genes for photosynthesis, nitrogen metabolism, and aromatic compound metabolism varied in relative abundances over the season, while phosphorus metabolism was consistent, suggesting that these genes remained essential despite fluctuating environmental conditions and community succession. We observed seasonal shifts from anoxygenic to oxygenic phototrophy, and from ammonia assimilation to nitrogen fixation, coupled with decreasing heterotrophic bacteria and increasing Cyanobacteria relative abundances. Our data contribute important insights into bacterial taxa and functional potentials in Hamilton Harbour, revealing seasonal and spatial dynamics that can be used to inform ongoing remediation efforts.
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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) | 0.000 | 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".