Deciphering the dynamics of Cyanobacteria-Phage in a natural lake: Insights from a decade-long investigation
Bibliographic record
Abstract
ABSTRACT Phages – viruses that infect bacteria – are often seen as key players in bacterial community dynamics and the ecosystem services those communities support. However, much of our understanding of phage-bacteria interactions comes from in vitro studies, which provide limited insights into how these interactions occur in natural environments. In this study, we used cyanobacterial blooms as a model microbial community to evaluate the potential role of phages in driving cyanobacterial populations. These blooms are characterized by massive and usually rapid accumulation of cyanobacterial biomass and occur worldwide, threatening aquatic systems. The frequency and intensity of cyanobacterial blooms are increasing over time, likely due to human activities, and, until now, the role of predators like phages has remained unclear. We used a deep amplicon sequencing approach targeting the g20 capsid gene to profile the cyanophage community in eutrophic Lake Champlain over time, comparing their dynamics and diversity with bacterial communities and examining their associations. We evaluated whether phages simply followed bacterial dynamics, with limited impact on bacterial composition, or instead whether they played an active role in drving bacterial community structure. We found that phages exhibited similar dynamics to their potential bacterial hosts and shared environmental niches. However, we also observed strong differences specific to the phage community, such as inter-annual variation and an increase in Shannon diversity over time. Phage-bacteria and phage-cyanobacteria co-variance uncovered potential interactions that resulted in strongly modular networks. However, while the network structure remained modular, the composition of the modules differed significantly between environmental and temporal conditions. Lastly, viral phylogeny partially explained phage-bacteria co-variance, but only for a small proportion of bacterial ASVs. Our results indicate that phage-bacterial interactions are partly genetically structured and vary within modules across environmental conditions.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".