Human and Animal RNA Virus Diversity Detected by Metagenomics in Cameroonian Clams

Many recent pandemics have been recognized as zoonotic viral diseases. While their origins remain frequently unknown, environmental contamination may play an important role in emergence. Thus, being able to describe the viral diversity in environmental samples contributes to understand the key issues in zoonotic transmission. This work describes the use of a metagenomic approach to assess the diversity of eukaryotic RNA viruses in river clams and identify sequences from human or potentially zoonotic viruses. Clam samples collected over 2years were first screened for the presence of norovirus to verify human contamination. Selected samples were analyzed using metagenomics, including a capture of sequences from viral families infecting vertebrates (VirCapSeq-VERT) before Illumina NovaSeq sequencing. The bioinformatics analysis included pooling of data from triplicates, quality filtering, elimination of bacterial and host sequences, and a deduplication step before de novo assembly. After taxonomic assignment, the viral fraction represented 0.8-15% of reads with most sequences (68-87%) remaining un-assigned. Yet, several mammalian RNA viruses were identified. Contigs identified as belonging to the Astroviridae were the most abundant, with some nearly complete genomes of bastrovirus identified. Picobirnaviridae sequences were related to strains infecting bats, and few others to strains infecting humans or other hosts. Hepeviridae sequences were mostly related to strains detected in sponge samples but also strains from swine samples. For Caliciviridae and Picornaviridae, most of identified sequences were related to strains infecting bats, with few sequences close to human norovirus, picornavirus, and genogroup V hepatitis A virus. Despite a need to improve the sensitivity of our method, this study describes a large diversity of RNA virus sequences from clam samples. To describe all viral contaminants in this type of food, and being able to identify the host infected by viral sequences detected, may help to understand some zoonotic transmission events and alert health authorities of possible emergence.