Minireview Trna Splicing in Archaea and Eukaryotes
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2020 Taxonomic Update for Phylum Negarnaviricota (Riboviria: Orthornavirae), Including the Large Orders Bunyavirales and Mononegavirales
Archives of Virology https://doi.org/10.1007/s00705-020-04731-2 VIROLOGY DIVISION NEWS 2020 taxonomic update for phylum Negarnaviricota (Riboviria: Orthornavirae), including the large orders Bunyavirales and Mononegavirales Jens H. Kuhn1 · Scott Adkins2 · Daniela Alioto3 · Sergey V. Alkhovsky4 · Gaya K. Amarasinghe5 · Simon J. Anthony6,7 · Tatjana Avšič‑Županc8 · María A. Ayllón9,10 · Justin Bahl11 · Anne Balkema‑Buschmann12 · Matthew J. Ballinger13 · Tomáš Bartonička14 · Christopher Basler15 · Sina Bavari16 · Martin Beer17 · Dennis A. Bente18 · Éric Bergeron19 · Brian H. Bird20 · Carol Blair21 · Kim R. Blasdell22 · Steven B. Bradfute23 · Rachel Breyta24 · Thomas Briese25 · Paul A. Brown26 · Ursula J. Buchholz27 · Michael J. Buchmeier28 · Alexander Bukreyev18,29 · Felicity Burt30 · Nihal Buzkan31 · Charles H. Calisher32 · Mengji Cao33,34 · Inmaculada Casas35 · John Chamberlain36 · Kartik Chandran37 · Rémi N. Charrel38 · Biao Chen39 · Michela Chiumenti40 · Il‑Ryong Choi41 · J. Christopher S. Clegg42 · Ian Crozier43 · John V. da Graça44 · Elena Dal Bó45 · Alberto M. R. Dávila46 · Juan Carlos de la Torre47 · Xavier de Lamballerie38 · Rik L. de Swart48 · Patrick L. Di Bello49 · Nicholas Di Paola50 · Francesco Di Serio40 · Ralf G. Dietzgen51 · Michele Digiaro52 · Valerian V. Dolja53 · Olga Dolnik54 · Michael A. Drebot55 · Jan Felix Drexler56 · Ralf Dürrwald57 · Lucie Dufkova58 · William G. Dundon59 · W. Paul Duprex60 · John M. Dye50 · Andrew J. Easton61 · Hideki Ebihara62 · Toufc Elbeaino63 · Koray Ergünay64 · Jorlan Fernandes195 · Anthony R. Fooks65 · Pierre B. H. Formenty66 · Leonie F. Forth17 · Ron A. M. Fouchier48 · Juliana Freitas‑Astúa67 · Selma Gago‑Zachert68,69 · George Fú Gāo70 · María Laura García71 · Adolfo García‑Sastre72 · Aura R. Garrison50 · Aiah Gbakima73 · Tracey Goldstein74 · Jean‑Paul J. Gonzalez75,76 · Anthony Grifths77 · Martin H. Groschup12 · Stephan Günther78 · Alexandro Guterres195 · Roy A. -
The LUCA and Its Complex Virome in Another Recent Synthesis, We Examined the Origins of the Replication and Structural Mart Krupovic , Valerian V
PERSPECTIVES archaea that form several distinct, seemingly unrelated groups16–18. The LUCA and its complex virome In another recent synthesis, we examined the origins of the replication and structural Mart Krupovic , Valerian V. Dolja and Eugene V. Koonin modules of viruses and posited a ‘chimeric’ scenario of virus evolution19. Under this Abstract | The last universal cellular ancestor (LUCA) is the most recent population model, the replication machineries of each of of organisms from which all cellular life on Earth descends. The reconstruction of the four realms derive from the primordial the genome and phenotype of the LUCA is a major challenge in evolutionary pool of genetic elements, whereas the major biology. Given that all life forms are associated with viruses and/or other mobile virion structural proteins were acquired genetic elements, there is no doubt that the LUCA was a host to viruses. Here, by from cellular hosts at different stages of evolution giving rise to bona fide viruses. projecting back in time using the extant distribution of viruses across the two In this Perspective article, we combine primary domains of life, bacteria and archaea, and tracing the evolutionary this recent work with observations on the histories of some key virus genes, we attempt a reconstruction of the LUCA virome. host ranges of viruses in each of the four Even a conservative version of this reconstruction suggests a remarkably complex realms, along with deeper reconstructions virome that already included the main groups of extant viruses of bacteria and of virus evolution, to tentatively infer archaea. We further present evidence of extensive virus evolution antedating the the composition of the virome of the last universal cellular ancestor (LUCA; also LUCA. -
Rapid Protein Sequence Evolution Via Compensatory Frameshift Is Widespread in RNA Virus Genomes
Park and Hahn BMC Bioinformatics (2021) 22:251 https://doi.org/10.1186/s12859-021-04182-9 RESEARCH Open Access Rapid protein sequence evolution via compensatory frameshift is widespread in RNA virus genomes Dongbin Park and Yoonsoo Hahn* *Correspondence: [email protected] Abstract Department of Life Science, Background: RNA viruses possess remarkable evolutionary versatility driven by the Chung-Ang University, Seoul 06794, South Korea high mutability of their genomes. Frameshifting nucleotide insertions or deletions (indels), which cause the premature termination of proteins, are frequently observed in the coding sequences of various viral genomes. When a secondary indel occurs near the primary indel site, the open reading frame can be restored to produce functional proteins, a phenomenon known as the compensatory frameshift. Results: In this study, we systematically analyzed publicly available viral genome sequences and identifed compensatory frameshift events in hundreds of viral protein- coding sequences. Compensatory frameshift events resulted in large-scale amino acid diferences between the compensatory frameshift form and the wild type even though their nucleotide sequences were almost identical. Phylogenetic analyses revealed that the evolutionary distance between proteins with and without a compensatory frameshift were signifcantly overestimated because amino acid mismatches caused by compensatory frameshifts were counted as substitutions. Further, this could cause compensatory frameshift forms to branch in diferent locations in the protein and nucleotide trees, which may obscure the correct interpretation of phylogenetic rela- tionships between variant viruses. Conclusions: Our results imply that the compensatory frameshift is one of the mecha- nisms driving the rapid protein evolution of RNA viruses and potentially assisting their host-range expansion and adaptation. -
Viral Metagenomics in the Clinical Realm: Lessons Learned from a Swiss-Wide Ring Trial
G C A T T A C G G C A T genes Article Viral Metagenomics in the Clinical Realm: Lessons Learned from a Swiss-Wide Ring Trial 1, 2, 2 2, Thomas Junier *, Michael Huber * , Stefan Schmutz , Verena Kufner y, 2, 3, 3, 4, Osvaldo Zagordi y, Stefan Neuenschwander y, Alban Ramette y , Jakub Kubacki y , 4, 5, 6, 6, Claudia Bachofen y, Weihong Qi y, Florian Laubscher y, Samuel Cordey y , 6, 7, 8 1,9 8, Laurent Kaiser y, Christian Beuret y, Valérie Barbié , Jacques Fellay and Aitana Lebrand * 1 Global Health Institute, Swiss Federal Institute of Technology (ETH Lausanne) & SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland 2 Institute of Medical Virology, University of Zurich, 8057 Zurich, Switzerland 3 Institute for Infectious Diseases, University of Bern, 3001 Bern, Switzerland 4 Institute of Virology, VetSuisse Faculty, University of Zurich, 8057 Zurich, Switzerland 5 Functional Genomics Center Zurich, Swiss Federal Institute of Technology (ETH Zurich) & University of Zurich, 8057 Zurich, Switzerland 6 Laboratory of Virology, University Hospitals of Geneva, 1205 Geneva, Switzerland; University of Geneva Medical School, 1206 Geneva, Switzerland 7 Biology Department, Spiez Laboratory, 3700 Spiez, Switzerland 8 Clinical Bioinformatics, SIB Swiss Institute of Bioinformatics, 1202 Geneva, Switzerland 9 Precision Medicine Unit, Lausanne University Hospital and University of Lausanne, 1010 Lausanne, Switzerland * Correspondence: [email protected] (T.J.); [email protected] (M.H.); [email protected] (A.L.) These authors contributed equally. y Received: 30 July 2019; Accepted: 24 August 2019; Published: 28 August 2019 Abstract: Shotgun metagenomics using next generation sequencing (NGS) is a promising technique to analyze both DNA and RNA microbial material from patient samples. -
Virology Is That the Study of Viruses ? Submicroscopic, Parasitic Particles
Current research in Virology & Retrovirology 2021, Vol.4, Issue 3 Editorial Bahman Khalilidehkordi Shahrekord University of Medical Sciences, Iran mobile genetic elements of cells (such as transposons, Editorial retrotransposons or plasmids) that became encapsulated in protein capsids, acquired the power to “break free” from Virology is that the study of viruses – submicroscopic, the host cell and infect other cells. Of particular interest parasitic particles of genetic material contained during a here is mimivirus, a huge virus that infects amoebae and protein coat – and virus-like agents. It focuses on the sub- encodes much of the molecular machinery traditionally sequent aspects of viruses: their structure, classification associated with bacteria. Two possibilities are that it’s a and evolution, their ways to infect and exploit host cells for simplified version of a parasitic prokaryote or it originated copy , their interaction with host organism physiology and as an easier virus that acquired genes from its host. The immunity, the diseases they cause, the techniques to iso- evolution of viruses, which frequently occurs together with late and culture them, and their use in research and ther- the evolution of their hosts, is studied within the field of apy. Virology is a subfield of microbiology.Structure and viral evolution. While viruses reproduce and evolve, they’re classification of Virus: A major branch of virology is virus doing not engage in metabolism, don’t move, and depend classification. Viruses are often classified consistent with on variety cell for copy . The often-debated question of the host cell they infect: animal viruses, plant viruses, fun- whether or not they’re alive or not could also be a matter gal viruses, and bacteriophages (viruses infecting bacte- of definition that does not affect the biological reality of vi- ria, which include the foremost complex viruses). -
BIOL 399 Special Topics Virology (PDF)
Course and Code Virology Biology 399 Class time: 3:00-3:50 pm, MWF Location: Room 128 Name of Faculty: Dr. Mark S. Davis Contact details: [email protected] Office hours: TBA Course Description Virology is a relatively new discipline in the realm of science. Viruses have been recognized as the causative agents of epidemics from the beginning of human history through early written records or archeological data. In addition, rudimentary vaccinations have occurred for almost one thousand years. However, it is only recently (relatively speaking) that the virus particle and its composition have been identified and studied. Virology, the study of viruses, includes many facets including viral replication, structure, interactions with hosts, evolution/history, epidemiology, and the diseases caused by the agent. This field is vast and any course must be selective in the coverage of the subject. This course is designed for the upper level science major with a background in microbiology and/or genetics. The course objectives are the following: Introduce the students to general viral structure and replication, viral immunology, viral therapy, and the major diseases caused by various viral families. Credit Hour Policy Statement This class meets the federal credit hour policy of: □ Standard lecture – e.g. 1 hour of class with an expected 2 hours of additional student work outside of class each week for approximately 15 weeks for each hour of credit, or a total of 45-75 hours for each credit. □ Other academic activities – e.g. 2 hours of laboratory, studio, or similar activities with an expected 1 hour of additional student work each week for approximately 15 weeks for each hour of credit, or a total of 45-75 hours for each credit. -
Virtual Screening of Anti-HIV1 Compounds Against SARS-Cov-2
www.nature.com/scientificreports OPEN Virtual screening of anti‑HIV1 compounds against SARS‑CoV‑2: machine learning modeling, chemoinformatics and molecular dynamics simulation based analysis Mahesha Nand1,6, Priyanka Maiti 2,6*, Tushar Joshi3, Subhash Chandra4*, Veena Pande3, Jagdish Chandra Kuniyal2 & Muthannan Andavar Ramakrishnan5* COVID‑19 caused by the SARS‑CoV‑2 is a current global challenge and urgent discovery of potential drugs to combat this pandemic is a need of the hour. 3‑chymotrypsin‑like cysteine protease (3CLpro) enzyme is the vital molecular target against the SARS‑CoV‑2. Therefore, in the present study, 1528 anti‑HIV1compounds were screened by sequence alignment between 3CLpro of SARS‑CoV‑2 and avian infectious bronchitis virus (avian coronavirus) followed by machine learning predictive model, drug‑likeness screening and molecular docking, which resulted in 41 screened compounds. These 41 compounds were re‑screened by deep learning model constructed considering the IC50 values of known inhibitors which resulted in 22 hit compounds. Further, screening was done by structural activity relationship mapping which resulted in two structural clefts. Thereafter, functional group analysis was also done, where cluster 2 showed the presence of several essential functional groups having pharmacological importance. In the fnal stage, Cluster 2 compounds were re‑docked with four diferent PDB structures of 3CLpro, and their depth interaction profle was analyzed followed by molecular dynamics simulation at 100 ns. Conclusively, 2 out of 1528 compounds were screened as potential hits against 3CLpro which could be further treated as an excellent drug against SARS‑CoV‑2. Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is the causative agent of the COVID-19. -
Coronavirus: Detailed Taxonomy
Coronavirus: Detailed taxonomy Coronaviruses are in the realm: Riboviria; phylum: Incertae sedis; and order: Nidovirales. The Coronaviridae family gets its name, in part, because the virus surface is surrounded by a ring of projections that appear like a solar corona when viewed through an electron microscope. Taxonomically, the main Coronaviridae subfamily – Orthocoronavirinae – is subdivided into alpha (formerly referred to as type 1 or phylogroup 1), beta (formerly referred to as type 2 or phylogroup 2), delta, and gamma coronavirus genera. Using molecular clock analysis, investigators have estimated the most common ancestor of all coronaviruses appeared in about 8,100 BC, and those of alphacoronavirus, betacoronavirus, gammacoronavirus, and deltacoronavirus appeared in approximately 2,400 BC, 3,300 BC, 2,800 BC, and 3,000 BC, respectively. These investigators posit that bats and birds are ideal hosts for the coronavirus gene source, bats for alphacoronavirus and betacoronavirus, and birds for gammacoronavirus and deltacoronavirus. Coronaviruses are usually associated with enteric or respiratory diseases in their hosts, although hepatic, neurologic, and other organ systems may be affected with certain coronaviruses. Genomic and amino acid sequence phylogenetic trees do not offer clear lines of demarcation among corona virus genus, lineage (subgroup), host, and organ system affected by disease, so information is provided below in rough descending order of the phylogenetic length of the reported genome. Subgroup/ Genus Lineage Abbreviation -
A Tool for Hierarchical Clustering, Core Gene Detection and Annotation of (Prokaryotic) Viruses Cristina Moraru
bioRxiv preprint doi: https://doi.org/10.1101/2021.06.14.448304; this version posted June 14, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. VirClust – a tool for hierarchical clustering, core gene detection and annotation of (prokaryotic) viruses Cristina Moraru Institute for Chemistry and Biology of the Marine Environment, Carl-von-Ossietzky –Str. 9 -11, D-26111 Oldenburg, Germany; [email protected] Abstract Recent years have seen major changes in the classification criteria and taxonomy of viruses. The current classification scheme, also called “megataxonomy of viruses”, recognizes five different viral realms, defined based on the presence of viral hallmark genes. Within the realms, viruses are classified into hierarchical taxons, ideally defined by their shared genes. Therefore, there is currently a need for virus classification tools based on such shared genes / proteins. Here, VirClust is presented – a novel tool capable of performing i) hierarchical clustering of viruses based on intergenomic distances calculated from their protein cluster content, ii) identification of core proteins and iii) annotation of viral proteins. VirClust groups proteins into clusters both based on BLASTP sequence similarity, which identifies more related proteins, and also based on hidden markow models (HMM), which identifies more distantly related proteins. Furthermore, VirClust provides an integrated visualization of the hierarchical clustering tree and of the distribution of the protein content, which allows the identification of the genomic features responsible for the respective clustering. By using different intergenomic distances, the hierarchical trees produced by VirClust can be split into viral genome clusters of different taxonomic ranks. -
Rhabdoviridae.Pdf
1 Rhabdoviridae Taxonomy Realm- Ribovira Kingdom- Orthornavirae Phylum- Negarnaviricota Subphylum-Haploviricotina Class- Monjiviricetes Order- Mononegaviriales Family- Rhabdoviridae Genus- Lyssavirus Genus-Ephemerovirus Rhabdoviridae: The family Derivation of names Rhabdoviridae: from rhabdos (Greek) meaning rod, referring to virion morphology. Member taxa Vertebrate host Lyssavirus Novirhabdovirus Perhabdovirus Sprivivirus Tupavirus Vertebrate host, arthropod vector Prepared by Dr. Vandana Gupta Page 1 2 Curiovirus Ephemerovirus Hapavirus Ledantevirus Sripuvirus Tibrovirus Vesiculovirus Invertebrate host Almendravirus Alphanemrhavirus Caligrhavirus Sigmavirus Plant host Cytorhabdovirus Dichorhavirus Nucleorhabdovirus Varicosavirus The family Rhabdoviridae includes 20 genera and 144 species of viruses with negative-sense, single-stranded RNA genomes of approximately 10–16 kb. Virions are typically enveloped with bullet-shaped or bacilliform morphology but non-enveloped filamentous virions have also been reported. The genomes are usually (but not always) single RNA molecules with partially complementary termini. Almost all rhabdovirus genomes have 5 genes encoding the structural proteins (N, P, M, G and L); however, many rhabdovirus genomes encode other proteins in additional genes or in alternative open reading frames (ORFs) within the structural protein genes. The family is ecologically diverse with members infecting plants or animals including mammals, birds, reptiles or fish. Rhabdoviruses are also detected in invertebrates, -
Structure Unveils Relationships Between RNA Virus Polymerases
viruses Article Structure Unveils Relationships between RNA Virus Polymerases Heli A. M. Mönttinen † , Janne J. Ravantti * and Minna M. Poranen * Molecular and Integrative Biosciences Research Programme, Faculty of Biological and Environmental Sciences, University of Helsinki, Viikki Biocenter 1, P.O. Box 56 (Viikinkaari 9), 00014 Helsinki, Finland; heli.monttinen@helsinki.fi * Correspondence: janne.ravantti@helsinki.fi (J.J.R.); minna.poranen@helsinki.fi (M.M.P.); Tel.: +358-2941-59110 (M.M.P.) † Present address: Institute of Biotechnology, Helsinki Institute of Life Sciences (HiLIFE), University of Helsinki, Viikki Biocenter 2, P.O. Box 56 (Viikinkaari 5), 00014 Helsinki, Finland. Abstract: RNA viruses are the fastest evolving known biological entities. Consequently, the sequence similarity between homologous viral proteins disappears quickly, limiting the usability of traditional sequence-based phylogenetic methods in the reconstruction of relationships and evolutionary history among RNA viruses. Protein structures, however, typically evolve more slowly than sequences, and structural similarity can still be evident, when no sequence similarity can be detected. Here, we used an automated structural comparison method, homologous structure finder, for comprehensive comparisons of viral RNA-dependent RNA polymerases (RdRps). We identified a common structural core of 231 residues for all the structurally characterized viral RdRps, covering segmented and non-segmented negative-sense, positive-sense, and double-stranded RNA viruses infecting both prokaryotic and eukaryotic hosts. The grouping and branching of the viral RdRps in the structure- based phylogenetic tree follow their functional differentiation. The RdRps using protein primer, RNA primer, or self-priming mechanisms have evolved independently of each other, and the RdRps cluster into two large branches based on the used transcription mechanism. -
Superimposition of Viral Protein Structures: a Means to Decipher the Phylogenies of Viruses
viruses Review Superimposition of Viral Protein Structures: A Means to Decipher the Phylogenies of Viruses Janne J. Ravantti 1 , Ane Martinez-Castillo 2 and Nicola G.A. Abrescia 2,3,4,* 1 Molecular and Integrative Biosciences Research Programme, Faculty of Biological and Environmental Sciences, University of Helsinki, FI-00014 Helsinki, Finland; Janne.Ravantti@helsinki.fi 2 Center for Cooperative Research in Biosciences (CIC bioGUNE), Basque Research and Technology Alliance (BRTA), Bizkaia Technology Park, 48160 Derio, Spain; [email protected] 3 IKERBASQUE, Basque Foundation for Science, 48013 Bilbao, Spain 4 Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Instituto de Salud Carlos III, 28029 Madrid, Spain * Correspondence: [email protected]; Tel.: +34-946572502 Received: 10 September 2020; Accepted: 2 October 2020; Published: 9 October 2020 Abstract: Superimposition of protein structures is key in unravelling structural homology across proteins whose sequence similarity is lost. Structural comparison provides insights into protein function and evolution. Here, we review some of the original findings and thoughts that have led to the current established structure-based phylogeny of viruses: starting from the original observation that the major capsid proteins of plant and animal viruses possess similar folds, to the idea that each virus has an innate “self”. This latter idea fueled the conceptualization of the PRD1-adenovirus lineage whose members possess a major capsid protein (innate “self”) with a double jelly roll fold. Based on this approach, long-range viral evolutionary relationships can be detected allowing the virosphere to be classified in four structure-based lineages. However, this process is not without its challenges or limitations.