Virus Bioinformatics 2022

A special issue of Viruses (ISSN 1999-4915). This special issue belongs to the section "General Virology".

Deadline for manuscript submissions: closed (30 April 2022) | Viewed by 60679

Special Issue Editors

The European Virus Bioinformatics Center, Friedrich Schiller University Jena, Jena, Germany
Interests: computational metabolomics and mass spectrometry; algorithms in bioinformatics; virus bioinformatics
Special Issues, Collections and Topics in MDPI journals
CSIC - Instituto de Agroquimica y Tecnologia de los Alimentos (IATA), Valencia, Spain
Interests: sewage; food microbiology; fermentation; molecular biology; sanger sequencing; microbial molecular biology
Special Issues, Collections and Topics in MDPI journals
Instituto de Agroquímica y Tecnología de Alimentos (IATA), Spanish National Research Council (CSIC), Valencia, Spain
Interests: food safety; enteric viruses; molecular biology; norovirus; hepatitis A and E viruses; environmental and food virology; epidemiology
Special Issues, Collections and Topics in MDPI journals
Environmental Virology and Food Safety Lab (VISAFELab), Department of Preservation and Food Safety Technologies, IATA-CSIC, Av. Agustín Escardino 7, 46980 Valencia, Spain
Interests: emerging viruses; molecular techniques; food safety
Special Issues, Collections and Topics in MDPI journals
Unidad Mixta Infección y Salud Pública, Universitat de ValEncia, Valencia, Spain
Interests: molecular evolutionary epidemiology of different pathogens, mainly RNA viruses, such as hepatitis C virus (HCV) and human immunodeficiency virus (HIV), and bacteria, such as Legionella pneumophila, Treponema pallidum, Neisseria gonorrhoeae, Pseudomonas aeruginosa and Klebsiella pneumoniae
Special Issues, Collections and Topics in MDPI journals
The European Virus Bioinformatics Center, Friedrich Schiller University, Jena, Germany
Interests: high throughput sequencing analysis; bioinformatic analysis and system biology of viruses; comparative genomics; identification and annotation of non-coding RNAs; coevolution of proteins and RNAs; algorithmic bioinformatics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue is published alongside the International Virus Bioinformatics Meeting 2022 (ViBioM 2022) taking place in spring 2022 in Valencia, Spain.

This Special Issue will present articles covering computational approaches in virology, and we welcome any contribution within this cross-disciplinary field. Sub-topics may include (but are not limited to): systems virology, virus–host interactions, viral infections and immunology, virus evolution and classification, epidemiology and surveillance, viral metagenomics and ecology, and clinical bioinformatics.

We welcome original research articles and review papers dealing with the recent advancements and current understanding of computational technologies aspects of virology.

We encourage you to publish your work in this Special Issue and present it at ViBioM 2022. However, this is not an obligation for publication.

All papers should be submitted online at https://www.mdpi.com/journal/viruses. Please select the correct Special Issue when submitting your paper to Viruses.

Dr. Franziska Hufsky
Dr. Alba Pérez-Cataluña
Dr. Walter Randazzo
Dr. Gloria Sánchez Moragas
Prof. Dr. Fernando González-Candelas
Prof. Dr. Manja Marz
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Viruses is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • virus bioinformatics
  • software
  • viral metagenomics and ecology
  • virus–host interactions
  • viral diversity and evolution
  • virus identification

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Published Papers (12 papers)

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Research

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16 pages, 2602 KiB  
Article
Investigating the Human Host—ssRNA Virus Interaction Landscape Using the SMEAGOL Toolbox
by Avantika Lal, Mariana Galvao Ferrarini and Andreas J. Gruber
Viruses 2022, 14(7), 1436; https://doi.org/10.3390/v14071436 - 29 Jun 2022
Cited by 2 | Viewed by 1933
Abstract
Viruses have evolved numerous mechanisms to exploit the molecular machinery of their host cells, including the broad spectrum of host RNA-binding proteins (RBPs). However, the RBP interactomes of most viruses are largely unknown. To shed light on the interaction landscape of RNA viruses [...] Read more.
Viruses have evolved numerous mechanisms to exploit the molecular machinery of their host cells, including the broad spectrum of host RNA-binding proteins (RBPs). However, the RBP interactomes of most viruses are largely unknown. To shed light on the interaction landscape of RNA viruses with human host cell RBPs, we have analysed 197 single-stranded RNA (ssRNA) viral genome sequences and found that the majority of ssRNA virus genomes are significantly enriched or depleted in motifs for specific human RBPs, suggesting selection pressure on these interactions. To facilitate tailored investigations and the analysis of genomes sequenced in future, we have released our methodology as a fast and user-friendly computational toolbox named SMEAGOL. Our resources will contribute to future studies of specific ssRNA virus—host cell interactions and support the identification of antiviral drug targets. Full article
(This article belongs to the Special Issue Virus Bioinformatics 2022)
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20 pages, 4269 KiB  
Article
Potential Autoimmunity Resulting from Molecular Mimicry between SARS-CoV-2 Spike and Human Proteins
by Janelle Nunez-Castilla, Vitalii Stebliankin, Prabin Baral, Christian A. Balbin, Masrur Sobhan, Trevor Cickovski, Ananda Mohan Mondal, Giri Narasimhan, Prem Chapagain, Kalai Mathee and Jessica Siltberg-Liberles
Viruses 2022, 14(7), 1415; https://doi.org/10.3390/v14071415 - 28 Jun 2022
Cited by 33 | Viewed by 16678
Abstract
Molecular mimicry between viral antigens and host proteins can produce cross-reacting antibodies leading to autoimmunity. The coronavirus SARS-CoV-2 causes COVID-19, a disease curiously resulting in varied symptoms and outcomes, ranging from asymptomatic to fatal. Autoimmunity due to cross-reacting antibodies resulting from molecular mimicry [...] Read more.
Molecular mimicry between viral antigens and host proteins can produce cross-reacting antibodies leading to autoimmunity. The coronavirus SARS-CoV-2 causes COVID-19, a disease curiously resulting in varied symptoms and outcomes, ranging from asymptomatic to fatal. Autoimmunity due to cross-reacting antibodies resulting from molecular mimicry between viral antigens and host proteins may provide an explanation. Thus, we computationally investigated molecular mimicry between SARS-CoV-2 Spike and known epitopes. We discovered molecular mimicry hotspots in Spike and highlight two examples with tentative high autoimmune potential and implications for understanding COVID-19 complications. We show that a TQLPP motif in Spike and thrombopoietin shares similar antibody binding properties. Antibodies cross-reacting with thrombopoietin may induce thrombocytopenia, a condition observed in COVID-19 patients. Another motif, ELDKY, is shared in multiple human proteins, such as PRKG1 involved in platelet activation and calcium regulation, and tropomyosin, which is linked to cardiac disease. Antibodies cross-reacting with PRKG1 and tropomyosin may cause known COVID-19 complications such as blood-clotting disorders and cardiac disease, respectively. Our findings illuminate COVID-19 pathogenesis and highlight the importance of considering autoimmune potential when developing therapeutic interventions to reduce adverse reactions. Full article
(This article belongs to the Special Issue Virus Bioinformatics 2022)
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13 pages, 1816 KiB  
Article
Identification of Phage Receptor-Binding Protein Sequences with Hidden Markov Models and an Extreme Gradient Boosting Classifier
by Dimitri Boeckaerts, Michiel Stock, Bernard De Baets and Yves Briers
Viruses 2022, 14(6), 1329; https://doi.org/10.3390/v14061329 - 17 Jun 2022
Cited by 10 | Viewed by 3983
Abstract
Receptor-binding proteins (RBPs) of bacteriophages initiate the infection of their corresponding bacterial host and act as the primary determinant for host specificity. The ever-increasing amount of sequence data enables the development of predictive models for the automated identification of RBP sequences. However, the [...] Read more.
Receptor-binding proteins (RBPs) of bacteriophages initiate the infection of their corresponding bacterial host and act as the primary determinant for host specificity. The ever-increasing amount of sequence data enables the development of predictive models for the automated identification of RBP sequences. However, the development of such models is challenged by the inconsistent or missing annotation of many phage proteins. Recently developed tools have started to bridge this gap but are not specifically focused on RBP sequences, for which many different annotations are available. We have developed two parallel approaches to alleviate the complex identification of RBP sequences in phage genomic data. The first combines known RBP-related hidden Markov models (HMMs) from the Pfam database with custom-built HMMs to identify phage RBPs based on protein domains. The second approach consists of training an extreme gradient boosting classifier that can accurately discriminate between RBPs and other phage proteins. We explained how these complementary approaches can reinforce each other in identifying RBP sequences. In addition, we benchmarked our methods against the recently developed PhANNs tool. Our best performing model reached a precision-recall area-under-the-curve of 93.8% and outperformed PhANNs on an independent test set, reaching an F1-score of 84.0% compared to 69.8%. Full article
(This article belongs to the Special Issue Virus Bioinformatics 2022)
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13 pages, 1842 KiB  
Article
CAVES: A Novel Tool for Comparative Analysis of Variant Epitope Sequences
by Katherine Li, Connor Lowey, Paul Sandstrom and Hezhao Ji
Viruses 2022, 14(6), 1152; https://doi.org/10.3390/v14061152 - 26 May 2022
Viewed by 1694
Abstract
In silico methods for immune epitope prediction have become essential for vaccine and therapeutic design, but manual intra-species comparison of putative epitopes remains challenging and subject to human error. Created initially for analyzing SARS-CoV-2 variants of concern, comparative analysis of variant epitope sequences [...] Read more.
In silico methods for immune epitope prediction have become essential for vaccine and therapeutic design, but manual intra-species comparison of putative epitopes remains challenging and subject to human error. Created initially for analyzing SARS-CoV-2 variants of concern, comparative analysis of variant epitope sequences (CAVES) is a novel tool designed to carry out rapid comparative analyses of epitopes amongst closely related pathogens, substantially reducing the required time and user workload. CAVES applies a two-level analysis approach. The Level-one (L1) analysis compares two epitope prediction files, and the Level-two (L2) analysis incorporates search results from the IEDB database of experimentally confirmed epitopes. Both L1 and L2 analyses sort epitopes into categories of exact matches, partial matches, or novel epitopes based on the degree to which they match with peptides from the compared file. Furthermore, CAVES uses positional sequence data to improve its accuracy and speed, taking only a fraction of the time required by manual analyses and minimizing human error. CAVES is widely applicable for evolutionary analyses and antigenic comparisons of any closely related pathogen species. CAVES is open-source software that runs through a graphical user interface on Windows operating systems, making it widely accessible regardless of coding expertise. The CAVES source code and test dataset presented here are publicly available on the CAVES GitHub page. Full article
(This article belongs to the Special Issue Virus Bioinformatics 2022)
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18 pages, 1158 KiB  
Article
DVGfinder: A Metasearch Tool for Identifying Defective Viral Genomes in RNA-Seq Data
by Maria J. Olmo-Uceda, Juan C. Muñoz-Sánchez, Wilberth Lasso-Giraldo, Vicente Arnau, Wladimiro Díaz-Villanueva and Santiago F. Elena
Viruses 2022, 14(5), 1114; https://doi.org/10.3390/v14051114 - 23 May 2022
Cited by 7 | Viewed by 3121
Abstract
The generation of different types of defective viral genomes (DVG) is an unavoidable consequence of the error-prone replication of RNA viruses. In recent years, a particular class of DVGs, those containing long deletions or genome rearrangements, has gain interest due to their potential [...] Read more.
The generation of different types of defective viral genomes (DVG) is an unavoidable consequence of the error-prone replication of RNA viruses. In recent years, a particular class of DVGs, those containing long deletions or genome rearrangements, has gain interest due to their potential therapeutic and biotechnological applications. Identifying such DVGs in high-throughput sequencing (HTS) data has become an interesting computational problem. Several algorithms have been proposed to accomplish this goal, though all incur false positives, a problem of practical interest if such DVGs have to be synthetized and tested in the laboratory. We present a metasearch tool, DVGfinder, that wraps the two most commonly used DVG search algorithms in a single workflow for the identification of the DVGs in HTS data. DVGfinder processes the results of ViReMa-a and DI-tector and uses a gradient boosting classifier machine learning algorithm to reduce the number of false-positive events. The program also generates output files in user-friendly HTML format, which can help users to explore the DVGs identified in the sample. We evaluated the performance of DVGfinder compared to the two search algorithms used separately and found that it slightly improves sensitivities for low-coverage synthetic HTS data and DI-tector precision for high-coverage samples. The metasearch program also showed higher sensitivity on a real sample for which a set of copy-backs were previously validated. Full article
(This article belongs to the Special Issue Virus Bioinformatics 2022)
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11 pages, 2975 KiB  
Article
ViralFlow: A Versatile Automated Workflow for SARS-CoV-2 Genome Assembly, Lineage Assignment, Mutations and Intrahost Variant Detection
by Filipe Zimmer Dezordi, Antonio Marinho da Silva Neto, Túlio de Lima Campos, Pedro Miguel Carneiro Jeronimo, Cleber Furtado Aksenen, Suzana Porto Almeida, Gabriel Luz Wallau and on behalf of the Fiocruz COVID-19 Genomic Surveillance Network
Viruses 2022, 14(2), 217; https://doi.org/10.3390/v14020217 - 23 Jan 2022
Cited by 27 | Viewed by 6371
Abstract
The COVID-19 pandemic is driven by Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) that emerged in 2019 and quickly spread worldwide. Genomic surveillance has become the gold standard methodology used to monitor and study this fast-spreading virus and its constantly emerging lineages. The [...] Read more.
The COVID-19 pandemic is driven by Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) that emerged in 2019 and quickly spread worldwide. Genomic surveillance has become the gold standard methodology used to monitor and study this fast-spreading virus and its constantly emerging lineages. The current deluge of SARS-CoV-2 genomic data generated worldwide has put additional pressure on the urgent need for streamlined bioinformatics workflows. Here, we describe a workflow developed by our group to process and analyze large-scale SARS-CoV-2 Illumina amplicon sequencing data. This workflow automates all steps of SARS-CoV-2 reference-based genomic analysis: data processing, genome assembly, PANGO lineage assignment, mutation analysis and the screening of intrahost variants. The pipeline is capable of processing a batch of around 100 samples in less than half an hour on a personal laptop or in less than five minutes on a server with 50 threads. The workflow presented here is available through Docker or Singularity images, allowing for implementation on laptops for small-scale analyses or on high processing capacity servers or clusters. Moreover, the low requirements for memory and CPU cores and the standardized results provided by ViralFlow highlight it as a versatile tool for SARS-CoV-2 genomic analysis. Full article
(This article belongs to the Special Issue Virus Bioinformatics 2022)
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19 pages, 3245 KiB  
Article
Exploring the Diversity of the Human Blood Virome
by María Cebriá-Mendoza, María A. Bracho, Cristina Arbona, Luís Larrea, Wladimiro Díaz, Rafael Sanjuán and José M. Cuevas
Viruses 2021, 13(11), 2322; https://doi.org/10.3390/v13112322 - 21 Nov 2021
Cited by 15 | Viewed by 3208
Abstract
Metagenomics is greatly improving our ability to discover new viruses, as well as their possible associations with disease. However, metagenomics has also changed our understanding of viruses in general. The vast expansion of currently known viral diversity has revealed a large fraction of [...] Read more.
Metagenomics is greatly improving our ability to discover new viruses, as well as their possible associations with disease. However, metagenomics has also changed our understanding of viruses in general. The vast expansion of currently known viral diversity has revealed a large fraction of non-pathogenic viruses, and offers a new perspective in which viruses function as important components of many ecosystems. In this vein, studies of the human blood virome are often motivated by the search for new viral diseases, especially those associated with blood transfusions. However, these studies have revealed the common presence of apparently non-pathogenic viruses in blood, particularly human anelloviruses and, to a lower extent, human pegiviruses (HPgV). To shed light on the diversity of the human blood virome, we subjected pooled plasma samples from 587 healthy donors in Spain to a viral enrichment protocol, followed by massive parallel sequencing. This showed that anelloviruses were clearly the major component of the blood virome and showed remarkable diversity. In total, we assembled 332 complete or near-complete anellovirus genomes, 50 of which could be considered new species. HPgV was much less frequent, but we, nevertheless, recovered 17 different isolates that we subsequently used for characterizing the diversity of this virus. In-depth investigation of the human blood virome should help to elucidate the ecology of these viruses, and to unveil potentially associated diseases. Full article
(This article belongs to the Special Issue Virus Bioinformatics 2022)
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11 pages, 1729 KiB  
Article
Rise and Fall of SARS-CoV-2 Lineage A.27 in Germany
by Sébastien Calvignac-Spencer, Matthias Budt, Matthew Huska, Hugues Richard, Luca Leipold, Linus Grabenhenrich, Torsten Semmler, Max von Kleist, Stefan Kröger, Thorsten Wolff and Martin Hölzer
Viruses 2021, 13(8), 1491; https://doi.org/10.3390/v13081491 - 29 Jul 2021
Cited by 7 | Viewed by 3771
Abstract
Here, we report on the increasing frequency of the SARS-CoV-2 lineage A.27 in Germany during the first months of 2021. Genomic surveillance identified 710 A.27 genomes in Germany as of 2 May 2021, with a vast majority identified in laboratories from a single [...] Read more.
Here, we report on the increasing frequency of the SARS-CoV-2 lineage A.27 in Germany during the first months of 2021. Genomic surveillance identified 710 A.27 genomes in Germany as of 2 May 2021, with a vast majority identified in laboratories from a single German state (Baden-Wuerttemberg, n = 572; 80.5%). Baden-Wuerttemberg is located near the border with France, from where most A.27 sequences were entered into public databases until May 2021. The first appearance of this lineage based on sequencing in a laboratory in Baden-Wuerttemberg can be dated to early January ’21. From then on, the relative abundance of A.27 increased until the end of February but has since declined—meanwhile, the abundance of B.1.1.7 increased in the region. The A.27 lineage shows a mutational pattern typical of VOIs/VOCs, including an accumulation of amino acid substitutions in the Spike glycoprotein. Among those, L18F, L452R and N501Y are located in the epitope regions of the N-terminal- (NTD) or receptor binding domain (RBD) and have been suggested to result in immune escape and higher transmissibility. In addition, A.27 does not show the D614G mutation typical for all VOIs/VOCs from the B lineage. Overall, A.27 should continue to be monitored nationally and internationally, even though the observed trend in Germany was initially displaced by B.1.1.7 (Alpha), while now B.1.617.2 (Delta) is on the rise. Full article
(This article belongs to the Special Issue Virus Bioinformatics 2022)
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Review

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24 pages, 1250 KiB  
Review
Detection of Ancient Viruses and Long-Term Viral Evolution
by Luca Nishimura, Naoko Fujito, Ryota Sugimoto and Ituro Inoue
Viruses 2022, 14(6), 1336; https://doi.org/10.3390/v14061336 - 18 Jun 2022
Cited by 7 | Viewed by 4838
Abstract
The COVID-19 outbreak has reminded us of the importance of viral evolutionary studies as regards comprehending complex viral evolution and preventing future pandemics. A unique approach to understanding viral evolution is the use of ancient viral genomes. Ancient viruses are detectable in various [...] Read more.
The COVID-19 outbreak has reminded us of the importance of viral evolutionary studies as regards comprehending complex viral evolution and preventing future pandemics. A unique approach to understanding viral evolution is the use of ancient viral genomes. Ancient viruses are detectable in various archaeological remains, including ancient people’s skeletons and mummified tissues. Those specimens have preserved ancient viral DNA and RNA, which have been vigorously analyzed in the last few decades thanks to the development of sequencing technologies. Reconstructed ancient pathogenic viral genomes have been utilized to estimate the past pandemics of pathogenic viruses within the ancient human population and long-term evolutionary events. Recent studies revealed the existence of non-pathogenic viral genomes in ancient people’s bodies. These ancient non-pathogenic viruses might be informative for inferring their relationships with ancient people’s diets and lifestyles. Here, we reviewed the past and ongoing studies on ancient pathogenic and non-pathogenic viruses and the usage of ancient viral genomes to understand their long-term viral evolution. Full article
(This article belongs to the Special Issue Virus Bioinformatics 2022)
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Other

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12 pages, 1356 KiB  
Technical Note
PIMGAVir and Vir-MinION: Two Viral Metagenomic Pipelines for Complete Baseline Analysis of 2nd and 3rd Generation Data
by Emilio Mastriani, Kathrina Mae Bienes, Gary Wong and Nicolas Berthet
Viruses 2022, 14(6), 1260; https://doi.org/10.3390/v14061260 - 10 Jun 2022
Cited by 3 | Viewed by 2673
Abstract
The taxonomic classification of viral sequences is frequently used for the rapid identification of pathogens, which is a key point for when a viral outbreak occurs. Both Oxford Nanopore Technologies (ONT) MinION and the Illumina (NGS) technology provide efficient methods to detect viral [...] Read more.
The taxonomic classification of viral sequences is frequently used for the rapid identification of pathogens, which is a key point for when a viral outbreak occurs. Both Oxford Nanopore Technologies (ONT) MinION and the Illumina (NGS) technology provide efficient methods to detect viral pathogens. Despite the availability of many strategies and software, matching them can be a very tedious and time-consuming task. As a result, we developed PIMGAVir and Vir-MinION, two metagenomics pipelines that automatically provide the user with a complete baseline analysis. The PIMGAVir and Vir-MinION pipelines work on 2nd and 3rd generation data, respectively, and provide the user with a taxonomic classification of the reads through three strategies: assembly-based, read-based, and clustering-based. The pipelines supply the scientist with comprehensive results in graphical and textual format for future analyses. Finally, the pipelines equip the user with a stand-alone platform with dedicated and various viral databases, which is a requirement for working in field conditions without internet connection. Full article
(This article belongs to the Special Issue Virus Bioinformatics 2022)
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23 pages, 2911 KiB  
Conference Report
The International Virus Bioinformatics Meeting 2022
by Franziska Hufsky, Denis Beslic, Dimitri Boeckaerts, Sebastian Duchene, Enrique González-Tortuero, Andreas J. Gruber, Jiarong Guo, Daan Jansen, John Juma, Kunaphas Kongkitimanon, Antoni Luque, Muriel Ritsch, Gabriel Lencioni Lovate, Luca Nishimura, Célia Pas, Esteban Domingo, Emma Hodcroft, Philippe Lemey, Matthew B. Sullivan, Friedemann Weber, Fernando González-Candelas, Sarah Krautwurst, Alba Pérez-Cataluña, Walter Randazzo, Gloria Sánchez and Manja Marzadd Show full author list remove Hide full author list
Viruses 2022, 14(5), 973; https://doi.org/10.3390/v14050973 - 05 May 2022
Cited by 3 | Viewed by 3282
Abstract
The International Virus Bioinformatics Meeting 2022 took place online, on 23–25 March 2022, and has attracted about 380 participants from all over the world. The goal of the meeting was to provide a meaningful and interactive scientific environment to promote discussion and collaboration [...] Read more.
The International Virus Bioinformatics Meeting 2022 took place online, on 23–25 March 2022, and has attracted about 380 participants from all over the world. The goal of the meeting was to provide a meaningful and interactive scientific environment to promote discussion and collaboration and to inspire and suggest new research directions and questions. The participants created a highly interactive scientific environment even without physical face-to-face interactions. This meeting is a focal point to gain an insight into the state-of-the-art of the virus bioinformatics research landscape and to interact with researchers in the forefront as well as aspiring young scientists. The meeting featured eight invited and 18 contributed talks in eight sessions on three days, as well as 52 posters, which were presented during three virtual poster sessions. The main topics were: SARS-CoV-2, viral emergence and surveillance, virus–host interactions, viral sequence analysis, virus identification and annotation, phages, and viral diversity. This report summarizes the main research findings and highlights presented at the meeting. Full article
(This article belongs to the Special Issue Virus Bioinformatics 2022)
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15 pages, 797 KiB  
Protocol
LABRADOR—A Computational Workflow for Virus Detection in High-Throughput Sequencing Data
by Izabela Fabiańska, Stefan Borutzki, Benjamin Richter, Hon Q. Tran, Andreas Neubert and Dietmar Mayer
Viruses 2021, 13(12), 2541; https://doi.org/10.3390/v13122541 - 18 Dec 2021
Cited by 1 | Viewed by 3364
Abstract
High-throughput sequencing (HTS) allows detection of known and unknown viruses in samples of broad origin. This makes HTS a perfect technology to determine whether or not the biological products, such as vaccines are free from the adventitious agents, which could support or replace [...] Read more.
High-throughput sequencing (HTS) allows detection of known and unknown viruses in samples of broad origin. This makes HTS a perfect technology to determine whether or not the biological products, such as vaccines are free from the adventitious agents, which could support or replace extensive testing using various in vitro and in vivo assays. Due to bioinformatics complexities, there is a need for standardized and reliable methods to manage HTS generated data in this field. Thus, we developed LABRADOR—an analysis pipeline for adventitious virus detection. The pipeline consists of several third-party programs and is divided into two major parts: (i) direct reads classification based on the comparison of characteristic profiles between reads and sequences deposited in the database supported with alignment of to the best matching reference sequence and (ii) de novo assembly of contigs and their classification on nucleotide and amino acid levels. To meet the requirements published in guidelines for biologicals’ safety we generated a custom nucleotide database with viral sequences. We tested our pipeline on publicly available HTS datasets and showed that LABRADOR can reliably detect viruses in mixtures of model viruses, vaccines and clinical samples. Full article
(This article belongs to the Special Issue Virus Bioinformatics 2022)
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