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Viruses
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Virus Bioinformatics 2020
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Virus Bioinformatics 2020

A special issue of Viruses (ISSN 1999-4915).

Deadline for manuscript submissions: closed (31 October 2020) | Viewed by 65078

Special Issue Editors

Prof. Dr. Manja Marz

E-Mail Website
Guest Editor
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
Prof. Dr. Bashar Ibrahim

E-Mail Website
Guest Editor
1. College of Arts & Sciences, Mathematics & Natural Science Department, Gulf University for Science and Technology, Hawally, Kuwait
2. Institute of Bioinformatics, Friedrich Schiller University Jena, Jena, Germany
3. The European Virus Bioinformatics Center, Jena, Germany
Interests: mathematical and computational systems biology; multiscale and unconventional modelling, simulation, and analysis of complex systems
Special Issues, Collections and Topics in MDPI journals
Dr. Franziska Hufsky

E-Mail Website
Guest Editor
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
Prof. Dr. Ronald Dijkman

E-Mail Website
Guest Editor
Institut für Virologie und Immunologie, Universität Bern, Bern, Switzerland
Interests: microbiology; immunology; virology; influenza viruses; zoonoses
Dr. Alban Ramette

E-Mail Website
Guest Editor
Institute for Infectious Diseases (IFIK), University of Bern, Bern, Switzerland
Interests: microbiology; epidemiology; biostatistics; microbial ecology; bioinformatics
Special Issues, Collections and Topics in MDPI journals
Dr. Jenna Kelly

E-Mail Website
Guest Editor
Institut für Virologie und Immunologie, Universität Bern, Bern, Switzerland
Interests: emerging viruses; zoonosis; bioinformatics; host pathogen dynamics; single cell sequencing; next generation sequencing

Special Issue Information

Dear Colleagues,

This Special Issue is related to the 4th International Virus Bioinformatics Meeting (former Annual Meeting of the European Virus Bioinformatics Center) taking place from 05–06 March 2020 at the Eventforum in Bern, Switzerland.

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

The Special Issue is open to all researchers working on the boundaries between bioinformatics and virology.

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

All papers should be submitted online at https://0-www-mdpi-com.brum.beds.ac.uk/journal/viruses. Please select the correct Special Issue when submitting your paper to Viruses.

Prof. Dr. Manja Marz
PD Dr. habil. Bashar Ibrahim
Dr. Franziska Hufsky
Prof. Dr. Ronald Dijkman
Dr. Alban Ramette
Dr. Jenna Kelly
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

  • systems virology
  • virus-host interactions
  • virus classification and evolution
  • epidemiology and surveillance
  • viral metagenomics and ecology
  • clinical bioinformatics

Related Special Issues

Published Papers (15 papers)

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Research

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7 pages, 2522 KiB  
Article
viromeBrowser: A Shiny App for Browsing Virome Sequencing Analysis Results
by David F. Nieuwenhuijse, Bas B. Oude Munnink and Marion P. G. Koopmans
Viruses 2021, 13(3), 437; https://0-doi-org.brum.beds.ac.uk/10.3390/v13030437 - 09 Mar 2021
Cited by 1 | Viewed by 2781
Abstract
Experiments in which complex virome sequencing data is generated remain difficult to explore and unpack for scientists without a background in data science. The processing of raw sequencing data by high throughput sequencing workflows usually results in contigs in FASTA format coupled to [...] Read more.
Experiments in which complex virome sequencing data is generated remain difficult to explore and unpack for scientists without a background in data science. The processing of raw sequencing data by high throughput sequencing workflows usually results in contigs in FASTA format coupled to an annotation file linking the contigs to a reference sequence or taxonomic identifier. The next step is to compare the virome of different samples based on the metadata of the experimental setup and extract sequences of interest that can be used in subsequent analyses. The viromeBrowser is an application written in the opensource R shiny framework that was developed in collaboration with end-users and is focused on three common data analysis steps. First, the application allows interactive filtering of annotations by default or custom quality thresholds. Next, multiple samples can be visualized to facilitate comparison of contig annotations based on sample specific metadata values. Last, the application makes it easy for users to extract sequences of interest in FASTA format. With the interactive features in the viromeBrowser we aim to enable scientists without a data science background to compare and extract annotation data and sequences from virome sequencing analysis results. Full article
(This article belongs to the Special Issue Virus Bioinformatics 2020)
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20 pages, 3812 KiB  
Article
Characterization of a Novel Mitovirus of the Sand Fly Lutzomyia longipalpis Using Genomic and Virus–Host Interaction Signatures
by Paula Fonseca, Flavia Ferreira, Felipe da Silva, Liliane Santana Oliveira, João Trindade Marques, Aristóteles Goes-Neto, Eric Aguiar and Arthur Gruber
Viruses 2021, 13(1), 9; https://0-doi-org.brum.beds.ac.uk/10.3390/v13010009 - 23 Dec 2020
Cited by 19 | Viewed by 3448
Abstract
Hematophagous insects act as the major reservoirs of infectious agents due to their intimate contact with a large variety of vertebrate hosts. Lutzomyia longipalpis is the main vector of Leishmania chagasi in the New World, but its role as a host of viruses [...] Read more.
Hematophagous insects act as the major reservoirs of infectious agents due to their intimate contact with a large variety of vertebrate hosts. Lutzomyia longipalpis is the main vector of Leishmania chagasi in the New World, but its role as a host of viruses is poorly understood. In this work, Lu. longipalpis RNA libraries were subjected to progressive assembly using viral profile HMMs as seeds. A sequence phylogenetically related to fungal viruses of the genus Mitovirus was identified and this novel virus was named Lul-MV-1. The 2697-base genome presents a single gene coding for an RNA-directed RNA polymerase with an organellar genetic code. To determine the possible host of Lul-MV-1, we analyzed the molecular characteristics of the viral genome. Dinucleotide composition and codon usage showed profiles similar to mitochondrial DNA of invertebrate hosts. Also, the virus-derived small RNA profile was consistent with the activation of the siRNA pathway, with size distribution and 5′ base enrichment analogous to those observed in viruses of sand flies, reinforcing Lu. longipalpis as a putative host. Finally, RT-PCR of different insect pools and sequences of public Lu. longipalpis RNA libraries confirmed the high prevalence of Lul-MV-1. This is the first report of a mitovirus infecting an insect host. Full article
(This article belongs to the Special Issue Virus Bioinformatics 2020)
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18 pages, 697 KiB  
Article
Structure and Hierarchy of SARS-CoV-2 Infection Dynamics Models Revealed by Reaction Network Analysis
by Stephan Peter, Peter Dittrich and Bashar Ibrahim
Viruses 2021, 13(1), 14; https://0-doi-org.brum.beds.ac.uk/10.3390/v13010014 - 23 Dec 2020
Cited by 14 | Viewed by 2797
Abstract
This work provides a mathematical technique for analyzing and comparing infection dynamics models with respect to their potential long-term behavior, resulting in a hierarchy integrating all models. We apply our technique to coupled ordinary and partial differential equation models of SARS-CoV-2 infection dynamics [...] Read more.
This work provides a mathematical technique for analyzing and comparing infection dynamics models with respect to their potential long-term behavior, resulting in a hierarchy integrating all models. We apply our technique to coupled ordinary and partial differential equation models of SARS-CoV-2 infection dynamics operating on different scales, that is, within a single organism and between several hosts. The structure of a model is assessed by the theory of chemical organizations, not requiring quantitative kinetic information. We present the Hasse diagrams of organizations for the twelve virus models analyzed within this study. For comparing models, each organization is characterized by the types of species it contains. For this, each species is mapped to one out of four types, representing uninfected, infected, immune system, and bacterial species, respectively. Subsequently, we can integrate these results with those of our former work on Influenza-A virus resulting in a single joint hierarchy of 24 models. It appears that the SARS-CoV-2 models are simpler with respect to their long term behavior and thus display a simpler hierarchy with little dependencies compared to the Influenza-A models. Our results can support further development towards more complex SARS-CoV-2 models targeting the higher levels of the hierarchy. Full article
(This article belongs to the Special Issue Virus Bioinformatics 2020)
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11 pages, 9056 KiB  
Article
Natural Selection Plays an Important Role in Shaping the Codon Usage of Structural Genes of the Viruses Belonging to the Coronaviridae Family
by Dimpal A. Nyayanit, Pragya D. Yadav, Rutuja Kharde and Sarah Cherian
Viruses 2021, 13(1), 3; https://0-doi-org.brum.beds.ac.uk/10.3390/v13010003 - 22 Dec 2020
Cited by 13 | Viewed by 2932
Abstract
Viruses belonging to the Coronaviridae family have a single-stranded positive-sense RNA with a poly-A tail. The genome has a length of ~29.9 kbps, which encodes for genes that are essential for cell survival and replication. Different evolutionary constraints constantly influence the codon usage [...] Read more.
Viruses belonging to the Coronaviridae family have a single-stranded positive-sense RNA with a poly-A tail. The genome has a length of ~29.9 kbps, which encodes for genes that are essential for cell survival and replication. Different evolutionary constraints constantly influence the codon usage bias (CUB) of different genes. A virus optimizes its codon usage to fit the host environment on which it savors. This study is a comprehensive analysis of the CUB for the different genes encoded by viruses of the Coronaviridae family. Different methods including relative synonymous codon usage (RSCU), an Effective number of codons (ENc), parity plot 2, and Neutrality plot, were adopted to analyze the factors responsible for the genetic evolution of the Coronaviridae family. Base composition and RSCU analyses demonstrated the presence of A-ended and U-ended codons being preferred in the 3rd codon position and are suggestive of mutational selection. The lesser ENc value for the spike ‘S’ gene suggests a higher bias in the codon usage of this gene compared to the other structural genes. Parity plot 2 and neutrality plot analyses demonstrate the role and the extent of mutational and natural selection towards the codon usage pattern. It was observed that the structural genes of the Coronaviridae family analyzed in this study were at the least under 84% influence of natural selection, implying a major role of natural selection in shaping the codon usage. Full article
(This article belongs to the Special Issue Virus Bioinformatics 2020)
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15 pages, 2506 KiB  
Article
Characterization and Diversity of 243 Complete Human Papillomavirus Genomes in Cervical Swabs Using Next Generation Sequencing
by Ardashel Latsuzbaia, Anke Wienecke-Baldacchino, Jessica Tapp, Marc Arbyn, Irma Karabegović, Zigui Chen, Marc Fischer, Friedrich Mühlschlegel, Steven Weyers, Pascale Pesch and Joël Mossong
Viruses 2020, 12(12), 1437; https://0-doi-org.brum.beds.ac.uk/10.3390/v12121437 - 14 Dec 2020
Cited by 11 | Viewed by 4226
Abstract
In recent years, next generation sequencing (NGS) technology has been widely used for the discovery of novel human papillomavirus (HPV) genotypes, variant characterization and genotyping. Here, we compared the analytical performance of NGS with a commercial PCR-based assay (Anyplex II HPV28) in cervical [...] Read more.
In recent years, next generation sequencing (NGS) technology has been widely used for the discovery of novel human papillomavirus (HPV) genotypes, variant characterization and genotyping. Here, we compared the analytical performance of NGS with a commercial PCR-based assay (Anyplex II HPV28) in cervical samples of 744 women. Overall, HPV positivity was 50.2% by the Anyplex and 45.5% by the NGS. With the NGS, we detected 25 genotypes covered by Anyplex and 41 additional genotypes. Agreement between the two methods for HPV positivity was 80.8% (kappa = 0.616) and 84.8% (kappa = 0.652) for 28 HPV genotypes and 14 high-risk genotypes, respectively. We recovered and characterized 243 complete HPV genomes from 153 samples spanning 40 different genotypes. According to phylogenetic analysis and pairwise distance, we identified novel lineages and sublineages of four high-risk and 16 low-risk genotypes. In total, 17 novel lineages and 14 novel sublineages were proposed, including novel lineages of HPV45, HPV52, HPV66 and a novel sublineage of HPV59. Our study provides important genomic insights on HPV types and lineages, where few complete genomes were publicly available. Full article
(This article belongs to the Special Issue Virus Bioinformatics 2020)
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17 pages, 2120 KiB  
Article
NCBI’s Virus Discovery Codeathon: Building “FIVE” —The Federated Index of Viral Experiments API Index
by Joan Martí-Carreras, Alejandro Rafael Gener, Sierra D. Miller, Anderson F. Brito, Christiam E. Camacho, Ryan Connor, Ward Deboutte, Cody Glickman, David M. Kristensen, Wynn K. Meyer, Sejal Modha, Alexis L. Norris, Surya Saha, Anna K. Belford, Evan Biederstedt, James Rodney Brister, Jan P. Buchmann, Nicholas P. Cooley, Robert A. Edwards, Kiran Javkar, Michael Muchow, Harihara Subrahmaniam Muralidharan, Charles Pepe-Ranney, Nidhi Shah, Migun Shakya, Michael J. Tisza, Benjamin J. Tully, Bert Vanmechelen, Valerie C. Virta, JL Weissman, Vadim Zalunin, Alexandre Efremov and Ben Busbyadd Show full author list remove Hide full author list
Viruses 2020, 12(12), 1424; https://0-doi-org.brum.beds.ac.uk/10.3390/v12121424 - 10 Dec 2020
Cited by 3 | Viewed by 4535
Abstract
Viruses represent important test cases for data federation due to their genome size and the rapid increase in sequence data in publicly available databases. However, some consequences of previously decentralized (unfederated) data are lack of consensus or comparisons between feature annotations. Unifying or [...] Read more.
Viruses represent important test cases for data federation due to their genome size and the rapid increase in sequence data in publicly available databases. However, some consequences of previously decentralized (unfederated) data are lack of consensus or comparisons between feature annotations. Unifying or displaying alternative annotations should be a priority both for communities with robust entry representation and for nascent communities with burgeoning data sources. To this end, during this three-day continuation of the Virus Hunting Toolkit codeathon series (VHT-2), a new integrated and federated viral index was elaborated. This Federated Index of Viral Experiments (FIVE) integrates pre-existing and novel functional and taxonomy annotations and virus–host pairings. Variability in the context of viral genomic diversity is often overlooked in virus databases. As a proof-of-concept, FIVE was the first attempt to include viral genome variation for HIV, the most well-studied human pathogen, through viral genome diversity graphs. As per the publication of this manuscript, FIVE is the first implementation of a virus-specific federated index of such scope. FIVE is coded in BigQuery for optimal access of large quantities of data and is publicly accessible. Many projects of database or index federation fail to provide easier alternatives to access or query information. To this end, a Python API query system was developed to enhance the accessibility of FIVE. Full article
(This article belongs to the Special Issue Virus Bioinformatics 2020)
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11 pages, 411 KiB  
Communication
Determining the Suitability of MinION’s Direct RNA and DNA Amplicon Sequencing for Viral Subtype Identification
by Deborah M. Leigh, Christopher Schefer and Carolina Cornejo
Viruses 2020, 12(8), 801; https://0-doi-org.brum.beds.ac.uk/10.3390/v12080801 - 25 Jul 2020
Cited by 11 | Viewed by 3046
Abstract
The MinION sequencer is increasingly being used for the detection and outbreak surveillance of pathogens due to its rapid throughput. For RNA viruses, MinION’s new direct RNA sequencing is the next significant development. Direct RNA sequencing studies are currently limited and comparisons of [...] Read more.
The MinION sequencer is increasingly being used for the detection and outbreak surveillance of pathogens due to its rapid throughput. For RNA viruses, MinION’s new direct RNA sequencing is the next significant development. Direct RNA sequencing studies are currently limited and comparisons of its diagnostic performance relative to different DNA sequencing approaches are lacking as a result. We sought to address this gap and sequenced six subtypes from the mycovirus CHV-1 using MinION’s direct RNA sequencing and DNA sequencing based on a targeted viral amplicon. Reads from both techniques could correctly identify viral presence and species using BLAST, though direct RNA reads were more frequently misassigned to closely related CHV species. De novo consensus sequences were error prone but suitable for viral species identification. However, subtype identification was less accurate from both reads and consensus sequences. This is due to the high sequencing error rate and the limited sequence divergence between some CHV-1 subtypes. Importantly, neither RNA nor amplicon sequencing reads could be used to obtain reliable intra-host variants. Overall, both sequencing techniques were suitable for virus detection, though limitations are present due to the error rate of MinION reads. Full article
(This article belongs to the Special Issue Virus Bioinformatics 2020)
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21 pages, 5573 KiB  
Article
Covid-19 Transmission Trajectories–Monitoring the Pandemic in the Worldwide Context
by Henry Loeffler-Wirth, Maria Schmidt and Hans Binder
Viruses 2020, 12(7), 777; https://0-doi-org.brum.beds.ac.uk/10.3390/v12070777 - 20 Jul 2020
Cited by 22 | Viewed by 5043
Abstract
The Covid-19 pandemic is developing worldwide with common dynamics but also with marked differences between regions and countries. These are not completely understood, but presumably, provide a clue to find ways to mitigate epidemics until strategies leading to its eradication become available. We [...] Read more.
The Covid-19 pandemic is developing worldwide with common dynamics but also with marked differences between regions and countries. These are not completely understood, but presumably, provide a clue to find ways to mitigate epidemics until strategies leading to its eradication become available. We describe an iteractive monitoring tool available in the internet. It enables inspection of the dynamic state of the epidemic in 187 countries using trajectories that visualize the transmission and removal rates of the epidemic and in this way bridge epi-curve tracking with modelling approaches. Examples were provided which characterize state of epidemic in different regions of the world in terms of fast and slow growing and decaying regimes and estimate associated rate factors. The basic spread of the disease is associated with transmission between two individuals every two-three days on the average. Non-pharmaceutical interventions decrease this value to up to ten days, whereas ‘complete lock down’ measures are required to stop the epidemic. Comparison of trajectories revealed marked differences between the countries regarding efficiency of measures taken against the epidemic. Trajectories also reveal marked country-specific recovery and death rate dynamics. The results presented refer to the pandemic state in May to July 2020 and can serve as ‘working instruction’ for timely monitoring using the interactive monitoring tool as a sort of ‘seismometer’ for the evaluation of the state of epidemic, e.g., the possible effect of measures taken in both, lock-down and lock-up directions. Comparison of trajectories between countries and regions will support developing hypotheses and models to better understand regional differences of dynamics of Covid-19. Full article
(This article belongs to the Special Issue Virus Bioinformatics 2020)
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29 pages, 12613 KiB  
Article
Deploying Machine and Deep Learning Models for Efficient Data-Augmented Detection of COVID-19 Infections
by Ahmed Sedik, Abdullah M Iliyasu, Basma Abd El-Rahiem, Mohammed E. Abdel Samea, Asmaa Abdel-Raheem, Mohamed Hammad, Jialiang Peng, Fathi E. Abd El-Samie and Ahmed A. Abd El-Latif
Viruses 2020, 12(7), 769; https://0-doi-org.brum.beds.ac.uk/10.3390/v12070769 - 16 Jul 2020
Cited by 146 | Viewed by 8735
Abstract
This generation faces existential threats because of the global assault of the novel Corona virus 2019 (i.e., COVID-19). With more than thirteen million infected and nearly 600000 fatalities in 188 countries/regions, COVID-19 is the worst calamity since the World War II. These misfortunes [...] Read more.
This generation faces existential threats because of the global assault of the novel Corona virus 2019 (i.e., COVID-19). With more than thirteen million infected and nearly 600000 fatalities in 188 countries/regions, COVID-19 is the worst calamity since the World War II. These misfortunes are traced to various reasons, including late detection of latent or asymptomatic carriers, migration, and inadequate isolation of infected people. This makes detection, containment, and mitigation global priorities to contain exposure via quarantine, lockdowns, work/stay at home, and social distancing that are focused on “flattening the curve”. While medical and healthcare givers are at the frontline in the battle against COVID-19, it is a crusade for all of humanity. Meanwhile, machine and deep learning models have been revolutionary across numerous domains and applications whose potency have been exploited to birth numerous state-of-the-art technologies utilised in disease detection, diagnoses, and treatment. Despite these potentials, machine and, particularly, deep learning models are data sensitive, because their effectiveness depends on availability and reliability of data. The unavailability of such data hinders efforts of engineers and computer scientists to fully contribute to the ongoing assault against COVID-19. Faced with a calamity on one side and absence of reliable data on the other, this study presents two data-augmentation models to enhance learnability of the Convolutional Neural Network (CNN) and the Convolutional Long Short-Term Memory (ConvLSTM)-based deep learning models (DADLMs) and, by doing so, boost the accuracy of COVID-19 detection. Experimental results reveal improvement in terms of accuracy of detection, logarithmic loss, and testing time relative to DLMs devoid of such data augmentation. Furthermore, average increases of 4% to 11% in COVID-19 detection accuracy are reported in favour of the proposed data-augmented deep learning models relative to the machine learning techniques. Therefore, the proposed algorithm is effective in performing a rapid and consistent Corona virus diagnosis that is primarily aimed at assisting clinicians in making accurate identification of the virus. Full article
(This article belongs to the Special Issue Virus Bioinformatics 2020)
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12 pages, 1845 KiB  
Article
Synonymous Dinucleotide Usage: A Codon-Aware Metric for Quantifying Dinucleotide Representation in Viruses
by Spyros Lytras and Joseph Hughes
Viruses 2020, 12(4), 462; https://0-doi-org.brum.beds.ac.uk/10.3390/v12040462 - 20 Apr 2020
Cited by 10 | Viewed by 4269
Abstract
Distinct patterns of dinucleotide representation, such as CpG and UpA suppression, are characteristic of certain viral genomes. Recent research has uncovered vertebrate immune mechanisms that select against specific dinucleotides in targeted viruses. This evidence highlights the importance of systematically examining the dinucleotide composition [...] Read more.
Distinct patterns of dinucleotide representation, such as CpG and UpA suppression, are characteristic of certain viral genomes. Recent research has uncovered vertebrate immune mechanisms that select against specific dinucleotides in targeted viruses. This evidence highlights the importance of systematically examining the dinucleotide composition of viral genomes. We have developed a novel metric, called synonymous dinucleotide usage (SDU), for quantifying dinucleotide representation in coding sequences. Our method compares the abundance of a given dinucleotide to the null hypothesis of equal synonymous codon usage in the sequence. We present a Python3 package, DinuQ, for calculating SDU and other relevant metrics. We have applied this method on two sets of invertebrate- and vertebrate-specific flaviviruses and rhabdoviruses. The SDU shows that the vertebrate viruses exhibit consistently greater under-representation of CpG dinucleotides in all three codon positions in both datasets. In comparison to existing metrics for dinucleotide quantification, the SDU allows for a statistical interpretation of its values by comparing it to a null expectation based on the codon table. Here we apply the method to viruses, but coding sequences of other living organisms can be analysed in the same way. Full article
(This article belongs to the Special Issue Virus Bioinformatics 2020)
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22 pages, 4748 KiB  
Article
The In Silico Prediction of Hotspot Residues that Contribute to the Structural Stability of Subunit Interfaces of a Picornavirus Capsid
by Nicole Upfold, Caroline Ross, Özlem Tastan Bishop and Caroline Knox
Viruses 2020, 12(4), 387; https://0-doi-org.brum.beds.ac.uk/10.3390/v12040387 - 31 Mar 2020
Cited by 2 | Viewed by 3598
Abstract
The assembly of picornavirus capsids proceeds through the stepwise oligomerization of capsid protein subunits and depends on interactions between critical residues known as hotspots. Few studies have described the identification of hotspot residues at the protein subunit interfaces of the picornavirus capsid, some [...] Read more.
The assembly of picornavirus capsids proceeds through the stepwise oligomerization of capsid protein subunits and depends on interactions between critical residues known as hotspots. Few studies have described the identification of hotspot residues at the protein subunit interfaces of the picornavirus capsid, some of which could represent novel drug targets. Using a combination of accessible web servers for hotspot prediction, we performed a comprehensive bioinformatic analysis of the hotspot residues at the intraprotomer, interprotomer and interpentamer interfaces of the Theiler’s murine encephalomyelitis virus (TMEV) capsid. Significantly, many of the predicted hotspot residues were found to be conserved in representative viruses from different genera, suggesting that the molecular determinants of capsid assembly are conserved across the family. The analysis presented here can be applied to any icosahedral structure and provides a platform for in vitro mutagenesis studies to further investigate the significance of these hotspots in critical stages of the virus life cycle with a view to identify potential targets for antiviral drug design. Full article
(This article belongs to the Special Issue Virus Bioinformatics 2020)
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18 pages, 973 KiB  
Article
Rapid, Unbiased PRRSV Strain Detection Using MinION Direct RNA Sequencing and Bioinformatics Tools
by Shaoyuan Tan, Cheryl M.T. Dvorak and Michael P. Murtaugh
Viruses 2019, 11(12), 1132; https://0-doi-org.brum.beds.ac.uk/10.3390/v11121132 - 07 Dec 2019
Cited by 20 | Viewed by 5356
Abstract
Prompt detection and effective control of porcine reproductive and respiratory syndrome virus (PRRSV) during outbreaks is important given its immense adverse impact on the swine industry. However, the diagnostic process can be challenging due to the high genetic diversity and high mutation rate [...] Read more.
Prompt detection and effective control of porcine reproductive and respiratory syndrome virus (PRRSV) during outbreaks is important given its immense adverse impact on the swine industry. However, the diagnostic process can be challenging due to the high genetic diversity and high mutation rate of PRRSV. A diagnostic method that can provide more detailed genetic information about pathogens is urgently needed. In this study, we evaluated the ability of Oxford Nanopore MinION direct RNA sequencing to generate a PRRSV whole genome sequence and detect and discriminate virus at the strain-level. A nearly full length PRRSV genome was successfully generated from raw sequence reads, achieving an accuracy of 96% after consensus genome generation. Direct RNA sequencing reliably detected the PRRSV strain present with an accuracy of 99.9% using as few as 5 raw sequencing reads and successfully differentiated multiple co-infecting strains present in a sample. In addition, PRRSV strain information was obtained from clinical samples containing 104 to 106 viral copies or more within 6 hours of sequencing. Overall, direct viral RNA sequencing followed by bioinformatic analysis proves to be a promising approach for identification of the viral strain or strains involved in clinical infections, allowing for more precise prevention and control strategies during PRRSV outbreaks. Full article
(This article belongs to the Special Issue Virus Bioinformatics 2020)
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Review

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26 pages, 2930 KiB  
Review
Advances in the Bioinformatics Knowledge of mRNA Polyadenylation in Baculovirus Genes
by Iván Gabriel Peros, Carolina Susana Cerrudo, Marcela Gabriela Pilloff, Mariano Nicolás Belaich, Mario Enrique Lozano and Pablo Daniel Ghiringhelli
Viruses 2020, 12(12), 1395; https://0-doi-org.brum.beds.ac.uk/10.3390/v12121395 - 06 Dec 2020
Viewed by 3698
Abstract
Baculoviruses are a group of insect viruses with large circular dsDNA genomes exploited in numerous biotechnological applications, such as the biological control of agricultural pests, the expression of recombinant proteins or the gene delivery of therapeutic sequences in mammals, among others. Their genomes [...] Read more.
Baculoviruses are a group of insect viruses with large circular dsDNA genomes exploited in numerous biotechnological applications, such as the biological control of agricultural pests, the expression of recombinant proteins or the gene delivery of therapeutic sequences in mammals, among others. Their genomes encode between 80 and 200 proteins, of which 38 are shared by all reported species. Thanks to multi-omic studies, there is remarkable information about the baculoviral proteome and the temporality in the virus gene expression. This allows some functional elements of the genome to be very well described, such as promoters and open reading frames. However, less information is available about the transcription termination signals and, consequently, there are still imprecisions about what are the limits of the transcriptional units present in the baculovirus genomes and how is the processing of the 3′ end of viral mRNA. Regarding to this, in this review we provide an update about the characteristics of DNA signals involved in this process and we contribute to their correct prediction through an exhaustive analysis that involves bibliography information, data mining, RNA structure and a comprehensive study of the core gene 3′ ends from 180 baculovirus genomes. Full article
(This article belongs to the Special Issue Virus Bioinformatics 2020)
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Other

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20 pages, 12076 KiB  
Commentary
ITN—VIROINF: Understanding (Harmful) Virus-Host Interactions by Linking Virology and Bioinformatics
by Winfried Goettsch, Niko Beerenwinkel, Li Deng, Lars Dölken, Bas E. Dutilh, Florian Erhard, Lars Kaderali, Max von Kleist, Roland Marquet, Jelle Matthijnssens, Shawna McCallin, Dino McMahon, Thomas Rattei, Ronald P. Van Rij, David L. Robertson, Martin Schwemmle, Noam Stern-Ginossar and Manja Marz
Viruses 2021, 13(5), 766; https://0-doi-org.brum.beds.ac.uk/10.3390/v13050766 - 27 Apr 2021
Cited by 5 | Viewed by 4223
Abstract
Many recent studies highlight the fundamental importance of viruses. Besides their important role as human and animal pathogens, their beneficial, commensal or harmful functions are poorly understood. By developing and applying tailored bioinformatical tools in important virological models, the Marie Skłodowska-Curie Initiative International [...] Read more.
Many recent studies highlight the fundamental importance of viruses. Besides their important role as human and animal pathogens, their beneficial, commensal or harmful functions are poorly understood. By developing and applying tailored bioinformatical tools in important virological models, the Marie Skłodowska-Curie Initiative International Training Network VIROINF will provide a better understanding of viruses and the interaction with their hosts. This will open the door to validate methods of improving viral growth, morphogenesis and development, as well as to control strategies against unwanted microorganisms. The key feature of VIROINF is its interdisciplinary nature, which brings together virologists and bioinformaticians to achieve common goals. Full article
(This article belongs to the Special Issue Virus Bioinformatics 2020)
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20 pages, 4040 KiB  
Conference Report
The International Virus Bioinformatics Meeting 2020
by Franziska Hufsky, Niko Beerenwinkel, Irmtraud M. Meyer, Simon Roux, Georgia May Cook, Cormac M. Kinsella, Kevin Lamkiewicz, Mike Marquet, David F. Nieuwenhuijse, Ingrida Olendraite, Sofia Paraskevopoulou, Francesca Young, Ronald Dijkman, Bashar Ibrahim, Jenna Kelly, Philippe Le Mercier, Manja Marz, Alban Ramette and Volker Thiel
Viruses 2020, 12(12), 1398; https://0-doi-org.brum.beds.ac.uk/10.3390/v12121398 - 06 Dec 2020
Cited by 4 | Viewed by 4219
Abstract
The International Virus Bioinformatics Meeting 2020 was originally planned to take place in Bern, Switzerland, in March 2020. However, the COVID-19 pandemic put a spoke in the wheel of almost all conferences to be held in 2020. After moving the conference to 8–9 [...] Read more.
The International Virus Bioinformatics Meeting 2020 was originally planned to take place in Bern, Switzerland, in March 2020. However, the COVID-19 pandemic put a spoke in the wheel of almost all conferences to be held in 2020. After moving the conference to 8–9 October 2020, we got hit by the second wave and finally decided at short notice to go fully online. On the other hand, the pandemic has made us even more aware of the importance of accelerating research in viral bioinformatics. Advances in bioinformatics have led to improved approaches to investigate viral infections and outbreaks. The International Virus Bioinformatics Meeting 2020 has attracted approximately 120 experts in virology and bioinformatics from all over the world to join the two-day virtual meeting. Despite concerns being raised that virtual meetings lack possibilities for face-to-face discussion, the participants from this small community created a highly interactive scientific environment, engaging in lively and inspiring discussions and suggesting new research directions and questions. The meeting featured five invited and twelve contributed talks, on the four main topics: (1) proteome and RNAome of RNA viruses, (2) viral metagenomics and ecology, (3) virus evolution and classification and (4) viral infections and immunology. Further, the meeting featured 20 oral poster presentations, all of which focused on specific areas of virus bioinformatics. This report summarizes the main research findings and highlights presented at the meeting. Full article
(This article belongs to the Special Issue Virus Bioinformatics 2020)
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