Metavirome Sequencing to Evaluate Norovirus Diversity in Sewage and Related Bioaccumulated Oysters.

Sofia Strubbia ; Julien Schaeffer ; Bas B Oude Munnink ; Alban Besnard ; My VT Phan ORCID logo ; David F Nieuwenhuijse ; Miranda de Graaf ; Claudia ME Schapendonk ; Candice Wacrenier ; Matthew Cotten ORCID logo ; +2 more... Marion PG Koopmans ; Françoise S Le Guyader ; (2019) Metavirome Sequencing to Evaluate Norovirus Diversity in Sewage and Related Bioaccumulated Oysters. Frontiers in Microbiology, 10 (OCT). 2394-. ISSN 1664-302X DOI: 10.3389/fmicb.2019.02394
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Metagenomic sequencing is a promising method to determine the virus diversity in environmental samples such as sewage or shellfish. However, to identify the short RNA genomes of human enteric viruses among the large diversity of nucleic acids present in such complex matrices, method optimization is still needed. This work presents methodological developments focused on norovirus, a small ssRNA non-enveloped virus known as the major cause of human gastroenteritis worldwide and frequently present in human excreta and sewage. Different elution protocols were applied and Illumina MiSeq technology were used to study norovirus diversity. A double approach, agnostic deep sequencing and a capture-based approach (VirCapSeq-VERT) was used to identify norovirus in environmental samples. Family-specific viral contigs were classified and sorted by SLIM and final norovirus contigs were genotyped using the online Norovirus genotyping tool v2.0. From sewage samples, 14 norovirus genogroup I sequences were identified of which six were complete genomes. For norovirus genogroup II, nine sequences were identified and three of them comprised more than half of the genome. In oyster samples bioaccumulated with these sewage samples, only the use of an enrichment step during library preparation allowed successful identification of nine different sequences of norovirus genogroup I and four for genogroup II (>500 bp). This study demonstrates the importance of method development to increase virus recovery, and the interest of a capture-based approach to be able to identify viruses present at low concentrations.


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