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

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          Abstract

          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.

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          Fast gapped-read alignment with Bowtie 2.

          As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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            BLAST+: architecture and applications

            Background Sequence similarity searching is a very important bioinformatics task. While Basic Local Alignment Search Tool (BLAST) outperforms exact methods through its use of heuristics, the speed of the current BLAST software is suboptimal for very long queries or database sequences. There are also some shortcomings in the user-interface of the current command-line applications. Results We describe features and improvements of rewritten BLAST software and introduce new command-line applications. Long query sequences are broken into chunks for processing, in some cases leading to dramatically shorter run times. For long database sequences, it is possible to retrieve only the relevant parts of the sequence, reducing CPU time and memory usage for searches of short queries against databases of contigs or chromosomes. The program can now retrieve masking information for database sequences from the BLAST databases. A new modular software library can now access subject sequence data from arbitrary data sources. We introduce several new features, including strategy files that allow a user to save and reuse their favorite set of options. The strategy files can be uploaded to and downloaded from the NCBI BLAST web site. Conclusion The new BLAST command-line applications, compared to the current BLAST tools, demonstrate substantial speed improvements for long queries as well as chromosome length database sequences. We have also improved the user interface of the command-line applications.
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              Fast and sensitive protein alignment using DIAMOND.

              The alignment of sequencing reads against a protein reference database is a major computational bottleneck in metagenomics and data-intensive evolutionary projects. Although recent tools offer improved performance over the gold standard BLASTX, they exhibit only a modest speedup or low sensitivity. We introduce DIAMOND, an open-source algorithm based on double indexing that is 20,000 times faster than BLASTX on short reads and has a similar degree of sensitivity.
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                Author and article information

                Contributors
                Journal
                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                1664-302X
                30 November 2021
                2021
                : 12
                : 770385
                Affiliations
                [1] 1Laboratoire de Microbiologie, LSEM/SG2M, Ifremer , Nantes, France
                [2] 2Département de Microbiologie, Université de Yaoundé I , Yaoundé, Cameroon
                [3] 3Centre de Recherche en Alimentation et Nutrition, IMPM , Yaoundé, Cameroon
                Author notes

                Edited by: Erna Geessien Kroon, Federal University of Minas Gerais, Brazil

                Reviewed by: Jemma Geoghegan, University of Otago, New Zealand; Jesus L. Romalde, University of Santiago de Compostela, Spain

                *Correspondence: Françoise S. Le Guyader, soizick.le.guyader@ 123456ifremer.fr

                This article was submitted to Virology, a section of the journal Frontiers in Microbiology

                Article
                10.3389/fmicb.2021.770385
                8669915
                34917052
                6ab9042d-e6ff-4428-886a-0435a6864fe1
                Copyright © 2021 Bonny, Schaeffer, Besnard, Desdouits, Essia Ngang and Le Guyader.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 03 September 2021
                : 18 October 2021
                Page count
                Figures: 6, Tables: 7, Equations: 0, References: 45, Pages: 15, Words: 9306
                Funding
                Funded by: VEO European
                Award ID: SC1-2019-874735
                Funded by: Ministry of Scientific Research and Innovation of Cameroon
                Categories
                Microbiology
                Original Research

                Microbiology & Virology
                shellfish,metagenomics,human enteric viruses,mammal viruses,zoonosis
                Microbiology & Virology
                shellfish, metagenomics, human enteric viruses, mammal viruses, zoonosis

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