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Article
Evelien Adriaenssens
Quadram Institute Bioscience
Corresponding Author
ORCiD: https://orcid.org/0000-0003-4826-5406
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This work is licensed under a CC BY 4.0 License. Read Full License
The discharge of wastewater-derived viruses in aquatic environments impacts catchment-scale virome composition and is a potential hazard to human health. Here, we used viromic analysis of RNA and DNA virus-like particle preparations to track virus communities entering and leaving wastewater treatment plants and the connecting river catchment system and estuary. We found substantial viral diversity and geographically distinct virus communities associated with different wastewater treatment plants. River and estuarine water bodies harboured more diverse viral communities in downstream locations, influenced by tidal movement and proximity to wastewater treatment plants. Shellfish and beach sand were enriched in viral communities when compared with the surrounding water, acting as entrapment matrices for virus particles. We reconstructed >40,000 partial viral genomes into 10,149 species-level groups, dominated by dsDNA and (+)ssRNA bacteriophages (Caudovirales and Leviviridae). We identified 73 (partial) genomes comprising six families that could pose a risk to human health; Astroviridae, Caliciviridae (sapovirus), Picornaviridae (cocksackievirus), Reoviridae (rotavirus), Parvoviridae and Circoviridae. Based on the pattern of viral incidence, we observe that wastewater-derived viral genetic material is commonly deposited in the environment, but due to fragemented nature of these viral genomes, the risk to human health is low, and is more likely driven by community transmission, with wastewater-derived viruses subject to cycles of dilution, enrichment and virion degradation influenced by local geography, weather events and tidal effects. Our data illustrate the utility of viromic analyses for wastewater- and environment-based epidemiology, and we present a conceptual model for the circulation of viruses in a freshwater catchment.
Keywords
wastewater, virus, treatment, environmental epidemiology, freshwater catchment
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The full text of this article is available to read as a PDF.
There is NO Competing Interest.
This is a list of supplementary files associated with this preprint. Click to download.
- FigS1.png
Extended Data Figure 1 | Differential patterns of abundance of each viral genome (UViG) along the wastewater impacted Conwy river and coastal zone, including positive and negative controls. Anvi’o - mean coverage per contig (split). Each row is a sequencing library, coloured by its sample type (green = sediment; orange = mussels; blue = river/estuary water; red = wastewater, grey = controls). Each column (leaf in top dendrogram) is a contig or a split of a contig (in cases where contigs were larger than 11 kb). The height of the bar in each row is the log mean coverage across the contig or contig split length. The contigs are clustered (top dendrogram) according to their sequence composition and differential coverage using Euclidean distance and Ward linkage. Based on this clustering, we identified 13 categories of UViGs, indicated by shades of grey in the dendrogram and numbered at the bottom of the plot. The bottom row represents the taxonomy assigned by Kaiju (using its viral database) to the predicted genes in each contig. Contigs without assigned taxonomy are depicted in grey, dsDNA bacteriophages in shades of blue, other dsDNA viruses in shades of green, ssDNA viruses in shades of yellow, RNA (ds, (+)ss, (-)ss) in shades of purple/red. The right hand panels the number of single nucleotide variants (SNVs) found after read mapping (0-20,640) and the total number of reads mapped to contigs (0-13,757,048).
- FigS2.png
Extended Data Figure 2 | Number of UViGs detected per environment and classified into family-level taxonomic groups. The cut-off for detection was 10 TPM summed per environment, a) wastewater, b) river and estuary river water, c) mussel digestive tissue, d) beach sediment.
- FigS3final.jpg
Extended Data Figure 3 | UViG genome comparison with closest relative in sequence database. The figures were generated with Easyfig, displaying annotated ORFs as arrows and tBLASTx-based pairwise genome identity in shades of grey. a) UViG GI_NODE_9 compared with astrovirus MLB1; b) UViGs LI_NODE_9 and LI_NODE_11 compared with each other and the sapoviruses GII.5 Nashville9387 and GII.2 Nashville9331, respectively; c) partial UViGs GI_NODE_118 and GI_NODE_86 compared with human coxsackieviruses A19 strain 8663 and A22 strain 43913, respectively.
- FigS4final.jpg
Extended Data Figure 4 | Anvi’o read mapping inspection panel for UViG LI_NODE_9, a predicted sapovirus. The genome was detected at low coverage in beach sediment RNA libraries (RNA_SBb, RNA_SBa), shellfish libraries (RNA_DS1, RNA_DP1) and one river water library (RNA_SW5b). It was detected at high coverage in the wastewater libraries RNA_GI, RNA_LE and RNA_LI, with the RNA_GI mapping showing the presence of multiple single nucleotide variants, indicating that a different strain was present in the Ganol wastewater treatment plant than in the Llanrwst plant.
- TableS1final.jpg
Extended Data Table 1: Summary of sample distribution in the Conwy water catchment.
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A new preprint design is coming!
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This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Article
Evelien Adriaenssens
Quadram Institute Bioscience
Corresponding Author
ORCiD: https://orcid.org/0000-0003-4826-5406
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
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View the published article at Water Research.
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Posted 15 Sep, 2020
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View the published article at Water Research.
The discharge of wastewater-derived viruses in aquatic environments impacts catchment-scale virome composition and is a potential hazard to human health. Here, we used viromic analysis of RNA and DNA virus-like particle preparations to track virus communities entering and leaving wastewater treatment plants and the connecting river catchment system and estuary. We found substantial viral diversity and geographically distinct virus communities associated with different wastewater treatment plants. River and estuarine water bodies harboured more diverse viral communities in downstream locations, influenced by tidal movement and proximity to wastewater treatment plants. Shellfish and beach sand were enriched in viral communities when compared with the surrounding water, acting as entrapment matrices for virus particles. We reconstructed >40,000 partial viral genomes into 10,149 species-level groups, dominated by dsDNA and (+)ssRNA bacteriophages (Caudovirales and Leviviridae). We identified 73 (partial) genomes comprising six families that could pose a risk to human health; Astroviridae, Caliciviridae (sapovirus), Picornaviridae (cocksackievirus), Reoviridae (rotavirus), Parvoviridae and Circoviridae. Based on the pattern of viral incidence, we observe that wastewater-derived viral genetic material is commonly deposited in the environment, but due to fragemented nature of these viral genomes, the risk to human health is low, and is more likely driven by community transmission, with wastewater-derived viruses subject to cycles of dilution, enrichment and virion degradation influenced by local geography, weather events and tidal effects. Our data illustrate the utility of viromic analyses for wastewater- and environment-based epidemiology, and we present a conceptual model for the circulation of viruses in a freshwater catchment.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
The full text of this article is available to read as a PDF.
There is NO Competing Interest.
This is a list of supplementary files associated with this preprint. Click to download.
- FigS1.png
Extended Data Figure 1 | Differential patterns of abundance of each viral genome (UViG) along the wastewater impacted Conwy river and coastal zone, including positive and negative controls. Anvi’o - mean coverage per contig (split). Each row is a sequencing library, coloured by its sample type (green = sediment; orange = mussels; blue = river/estuary water; red = wastewater, grey = controls). Each column (leaf in top dendrogram) is a contig or a split of a contig (in cases where contigs were larger than 11 kb). The height of the bar in each row is the log mean coverage across the contig or contig split length. The contigs are clustered (top dendrogram) according to their sequence composition and differential coverage using Euclidean distance and Ward linkage. Based on this clustering, we identified 13 categories of UViGs, indicated by shades of grey in the dendrogram and numbered at the bottom of the plot. The bottom row represents the taxonomy assigned by Kaiju (using its viral database) to the predicted genes in each contig. Contigs without assigned taxonomy are depicted in grey, dsDNA bacteriophages in shades of blue, other dsDNA viruses in shades of green, ssDNA viruses in shades of yellow, RNA (ds, (+)ss, (-)ss) in shades of purple/red. The right hand panels the number of single nucleotide variants (SNVs) found after read mapping (0-20,640) and the total number of reads mapped to contigs (0-13,757,048).
- FigS2.png
Extended Data Figure 2 | Number of UViGs detected per environment and classified into family-level taxonomic groups. The cut-off for detection was 10 TPM summed per environment, a) wastewater, b) river and estuary river water, c) mussel digestive tissue, d) beach sediment.
- FigS3final.jpg
Extended Data Figure 3 | UViG genome comparison with closest relative in sequence database. The figures were generated with Easyfig, displaying annotated ORFs as arrows and tBLASTx-based pairwise genome identity in shades of grey. a) UViG GI_NODE_9 compared with astrovirus MLB1; b) UViGs LI_NODE_9 and LI_NODE_11 compared with each other and the sapoviruses GII.5 Nashville9387 and GII.2 Nashville9331, respectively; c) partial UViGs GI_NODE_118 and GI_NODE_86 compared with human coxsackieviruses A19 strain 8663 and A22 strain 43913, respectively.
- FigS4final.jpg
Extended Data Figure 4 | Anvi’o read mapping inspection panel for UViG LI_NODE_9, a predicted sapovirus. The genome was detected at low coverage in beach sediment RNA libraries (RNA_SBb, RNA_SBa), shellfish libraries (RNA_DS1, RNA_DP1) and one river water library (RNA_SW5b). It was detected at high coverage in the wastewater libraries RNA_GI, RNA_LE and RNA_LI, with the RNA_GI mapping showing the presence of multiple single nucleotide variants, indicating that a different strain was present in the Ganol wastewater treatment plant than in the Llanrwst plant.
- TableS1final.jpg
Extended Data Table 1: Summary of sample distribution in the Conwy water catchment.
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