Cell-associated viral community composition and its functional potential in a dimictic lake on the Canadian Shield
Bibliographic record
Abstract
Abstract The Turkey Lake Watershed (TLW), located in Northern Ontario, forms a cascading lake system that ultimately drains into Lake Superior. Historically, the TLW has served as a key research site for studies on acid rain and climate change. Despite its long-standing ecological importance, investigations into its microbial communities remain limited, and to date, no studies have explicitly examined the viral component of this watershed. A major obstacle to such research is the challenge of obtaining sufficient viral biomass from remote locations like the TLW for downstream sequencing and analysis. To address this, we focused on viral signatures associated with microbial cells, which require less biomass at the time of collection. Using this approach, we conducted a seasonal metagenomic survey of Big Turkey Lake (BTL)—one of the primary lakes within the TLW—from summer 2018 to winter 2020. Our study characterized the diversity and composition of cell-associated viral communities, predicted potential host relationships, and identified auxiliary metabolic genes (AMGs) to better understand the functional roles of these viruses. The results revealed a dynamic viral community that varied across seasons. Most viral contigs were classified within the class Caudoviricetes , while members of the Phycodnaviridae emerged as important non-bacteriophage contributors to the viral assemblage. We also reconstructed six draft viral metagenome-assembled genomes (vMAGs), ranging in size from 11 to 45 kbp, all identified as Caudoviricetes , with two being potential temperate phages, and a third containing ribosomal genes. Notably, AMGs associated with lipid metabolism were detected exclusively in a winter sample, suggesting a potential season- or niche-specific role for these genes in BTL, while AMGs related to phosphorus acquisition were present in all samples. Together, these findings provide the first insight into the viral ecology of the TLW and establish a foundation for future studies investigating the roles of viruses in shaping the microbial dynamics in this important habitat.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 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".