Seasonal Patterns of Viromes in Urban Aquatic Environments of Manitoba
Bibliographic record
Abstract
ABSTRACT Although wastewater and treatment plants harbor many pathogenic organisms’ traditional methods that monitor the microbial quality of wastewater have not changed since the early 1900s and often disregard the presence of other types of significant waterborne pathogens such as viruses. Using advanced technology, our study aims to characterize the taxonomy, functional profiling and seasonal patterns of viral DNA and RNA community structures using metagenomics and quantitative-PCR, for the purpose of establishing the virome distribution in aquatic environment’s receiving wastewater discharge. Environmental water samples were collected at 11 locations in Winnipeg, Manitoba along the Red and Assiniboine Rivers during the Spring, Summer and Fall 2021. Samples were filtered and underwent skimmed milk flocculation for viral concentration. The taxonomic classification of DNA viruses identified from the RefSeq database (available from MG-RAST) and Kraken 2 Viral Genome database were predominately DNA bacteriophages ( Myoviridae, Podoviridae and Siphoviridae ) which accounted for approximately 90% of each aquatic sample location along the Red and Assiniboine Rivers. Phage related functionalities such as phage tail fiber proteins, phage replication, and phage packaging machinery accounted for 40% of each aquatic samples collected which possibly correspond to the DNA phages that were previously identified. RNA phages such as Cystoviridae and Leviviridae were identified to a lesser extent accounting for approximately 3 % of each aquatic sample collected, while other viruses such as Virgaviridae, Retroviridae, Picobirnaviridae and Partiviridae accounted for 7%–100% of aquatic samples. The functionalities of RNA viruses were primarily related to metabolic pathways such as potassium homeostasis, respiratory complexes and sialic acid metabolism, essential for RNA viruses to survive in their host. IMPORTANCE Municipal wastewater effluents discharged into the Red and Assiniboine Rivers of Winnipeg, Manitoba relies on traditional methods that monitor the microbial quality of wastewater focus solely on the detection of fecal bacteria, which are not necessarily good indicators of viruses or other pathogens. There is also a lack of current wastewater system effluent regulations at the federal and provincial level. Furthermore, previous literature has shown that when viral DNA and RNA sequences are blasted against current genomic databases, approximately 50 % of the viral reads are classified as unknown. The significance of our research in characterizing the virome distribution in aquatic environments addresses a knowledge gap in the current effluent guidelines and a need for regulatory practices. In the long run, fecal indicator bacteria combined with the detection of enteric viruses, may complement assessment of water quality in effluents discharged into rivers.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| 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".