| Literature DB >> 32967111 |
Sergio Guajardo-Leiva1, Jonás Chnaiderman2, Aldo Gaggero2, Beatriz Díez1,3.
Abstract
Sewage-associated viruses can cause several human and animal diseases, such as gastroenteritis, hepatitis, and respiratory infections. Therefore, their detection in wastewater can reflect current infections within the source population. To date, no viral study has been performed using the sewage of any large South American city. In this study, we used viral metagenomics to obtain a single sample snapshot of the RNA virosphere in the wastewater from Santiago de Chile, the seventh largest city in the Americas. Despite the overrepresentation of dsRNA viruses, our results show that Santiago's sewage RNA virosphere was composed mostly of unknown sequences (88%), while known viral sequences were dominated by viruses that infect bacteria (60%), invertebrates (37%) and humans (2.4%). Interestingly, we discovered three novel genogroups within the Picobirnaviridae family that can fill major gaps in this taxa's evolutionary history. We also demonstrated the dominance of emerging Rotavirus genotypes, such as G8 and G6, that have displaced other classical genotypes, which is consistent with recent clinical reports. This study supports the usefulness of sewage viral metagenomics for public health surveillance. Moreover, it demonstrates the need to monitor the viral component during the wastewater treatment and recycling process, where this virome can constitute a reservoir of human pathogens.Entities:
Keywords: Picobirnavirus; Rotavirus; sewage RNA virosphere; viral metagenomics; wastewater
Mesh:
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Year: 2020 PMID: 32967111 PMCID: PMC7551614 DOI: 10.3390/v12091050
Source DB: PubMed Journal: Viruses ISSN: 1999-4915 Impact factor: 5.048
Figure 1Map of el Trebal Wastewater Treatment Plant location in Santiago de Chile. El Trebal wastewater treatment plant (WWTP) is indicated by a white-star red baloon.
Figure 2Relative abundances of predicted protein sequences in Trebal viral RNA metagenome, classified by LCA algorithm trough local alignment to NCBI nr database. (A) Domain level, and (B) Family level for sequences classified as Virus in A. (C) Putative host for sequences classified as Virus in A. Sequences were normalized by protein length.
Figure 3Hierarchical clustering analysis of 2266 RNA-dependent RNA polymerase (RdRP) predicted protein sequences from Trebal and NCBI RefSeq database based on Bray–Curtis amino acid distance (k = 2). Dendrogram was divided in 12 main cluster based on the “unrooted” dendrogram. Pie charts represent the frequency of sequences in each cluster classified by the putative host trough LCA algorithm. Bar charts represent the source (NCBI or Trebal) from which sequences were retrieved inside each cluster.
Figure 4Maximum Likelihood phylogenetic reconstruction of 31 RNA-dependent RNA polymerase (RdRP) predicted proteins from Picobirnaviridae family. Node numbers indicate ultra-fast bootstrap values. RdRP sequence of White clover cryptic virus 1 was used as an outgroup and appeared in grey letters. The sequences characterized in the present study are reported in red letters. Scale bar: 0.5 aminoacid substitution per site.
Figure 5Relative abundances of Human Rotavirus species and genotypes inferred from Pfam annotated VP4, VP6, and VP7 genes and classified by local alignment (BLASTn) to NCBI nt database. Sequences were normalized by gene length. (A) Relative abundance of Human Rotavirus species based on VP6. (B) Relative abundance of Human Rotavirus G types based on VP7. (C) Relative abundance of Human Rotavirus P types based on VP4.