Academia.eduAcademia.edu

Outline

Title
Abstract
Introduction
Materials and Methods
Results
Discussion
References

Bacterial Virus Ontology; Coordinating across Databases

Profile image of Sylvain PouxSylvain Poux

Viruses

https://doi.org/10.3390/V9060126
visibility

…

description

17 pages

link

1 file

Abstract

Bacterial viruses, also called bacteriophages, display a great genetic diversity and utilize unique processes for infecting and reproducing within a host cell. All these processes were investigated and indexed in the ViralZone knowledge base. To facilitate standardizing data, a simple ontology of viral life-cycle terms was developed to provide a common vocabulary for annotating data sets. New terminology was developed to address unique viral replication cycle processes, and existing terminology was modified and adapted. Classically, the viral life-cycle is described by schematic pictures. Using this ontology, it can be represented by a combination of successive events: entry, latency, transcription/replication, host-virus interactions and virus release. Each of these parts is broken down into discrete steps. For example enterobacteria phage lambda entry is broken down in: viral attachment to host adhesion receptor, viral attachment to host entry receptor, viral genome ejection and viral genome circularization. To demonstrate the utility of a standard ontology for virus biology, this work was completed by annotating virus data in the ViralZone, UniProtKB and Gene Ontology databases.

Related papers

Coordinating virus research: The Virus Infectious Disease Ontology
John Beverley

PLOS ONE, 2024

The COVID-19 pandemic prompted immense work on the investigation of the SARS-CoV-2 virus. Rapid, accurate, and consistent interpretation of generated data is thereby of fundamental concern. Ontologies-structured, controlled, vocabularies-are designed to support consistency of interpretation, and thereby to prevent the development of data silos. This paper describes how ontologies are serving this purpose in the COVID-19 research domain, by following principles of the Open Biological and Biomedical Ontology (OBO) Foundry and by reusing existing ontologies such as the Infectious Disease Ontology (IDO) Core, which provides terminological content common to investigations of all infectious diseases. We report here on the development of an IDO extension, the Virus Infectious Disease Ontology (VIDO), a reference ontology covering viral infectious diseases. We motivate term and definition choices, showcase reuse of terms from existing OBO ontologies, illustrate how ontological decisions were motivated by relevant life science research, and connect VIDO to the Coronavirus Infectious Disease Ontology (CIDO). We next use terms from these ontologies to annotate selections from life science research on SARS-CoV-2, highlighting how ontologies employing a common upper-level vocabulary may be seamlessly interwoven. Finally, we outline future work, including bacteria and fungus infectious disease reference ontologies currently under development, then cite uses of VIDO and CIDO in host-pathogen data analytics, electronic health record annotation, and ontology conflict-resolution projects.

View PDFchevron_right
PhiGO, a phage ontology associated with the ACLAME database
Gipsi Lima Mendez

Research in Microbiology, 2007

As is the case for other genomes and metagenomes, complete nucleotide sequences of bacteriophages and archaeviruses have become increasingly numerous and require robust annotation tools. We present here the first version of a phage ontology, PhiGO, which should contribute to more informational annotation of gene products in phage and prophage sequences. PhiGO uses the Gene Ontology schema, the de facto standard for describing knowledge about gene products across many databases.

View PDFchevron_right
ViralZone: recent updates to the virus knowledge resource
Ioannis Xenarios

Nucleic Acids Research, 2013

ViralZone (http://viralzone.expasy.org) is a knowledge repository that allows users to learn about viruses including their virion structure, replication cycle and host-virus interactions. The information is divided into viral fact sheets that describe virion shape, molecular biology and epidemiology for each viral genus, with links to the corresponding annotated proteomes of UniProtKB. Each viral genus page contains detailed illustrations, text and PubMed references. This new update provides a linked view of viral molecular biology through 133 new viral ontology pages that describe common steps of viral replication cycles shared by several viral genera. This viral cell-cycle ontology is also represented in UniProtKB in the form of annotated keywords. In this way, users can navigate from the description of a replication-cycle event, to the viral genus concerned, and the associated UniProtKB protein records.

View PDFchevron_right
Coordinating Coronavirus Research: The COVID-19 Infectious Disease Ontology
Regina Hurley

2020

The COVID-19 pandemic prompted immense investigation of the SARS-CoV-2 virus. Rapidly, accurately, and easily interpreting generated data is of fundamental concern. Ontologies – structured, controlled, vocabularies – support interoperability, and prevent the development of data silos which undermine interoperability. The Open Biological and Biomedical Ontology Foundry serves to ensure ontologies remain interoperable through adherence by its members to core ontology design principles. For example, the Infectious Disease Ontology (IDO) Core includes terminological content common to investigations of all infectious diseases. Ontologies covering more specific infectious diseases, in turn, extend from IDO Core, such as the Coronavirus Infectious Disease Ontology (CIDO). The growing list of virus specific IDO extensions has motivated construction of a reference ontology covering content common to viral infectious disease investigations: the Virus Infectious Disease Ontology (VIDO). Additi...

View PDFchevron_right
Why ontology matters? Understanding COVID19 pandemic
Miguel Guerrero Fernandez

Academia Letters, 2022

An old disease: common cold. An old virus: coronavirus. A new event: COVID-19 disease by "new coronavirus" (SARS-CoV-2) that creates a globalized pandemic with media and social networks driving uncontrollably alarm… We are immersed in the third/fourth wave of COVID-19 pandemic and, at present time, there are two different kind of vaccines un use: mRNA vs. viral-vector. Understanding this two different but related events requires to know what kind of ontological entities are viruses. An infective virus is essentially a biopolymer composite of (A) polynucleotide-RNA/DNA genome plus (B) polypeptide capsid. This distinction is important because: by routine (A) is detected with PCR genetic tests and (B) with immunologic antibodies diagnostic technologies; and the base to understand the innovative mRNA vaccines versus classic viral vector and/or attenuated virus vaccines. Virus are chemical biopolymers that can be classified as complex and adaptive dynamic systems (CADS). RNA and DNA polynucleotides are integrated in planet Earth evolution since origin of life some three billion years ago, but to be a living organism is more than a dynamic replicating and adapting structure. There are other kinds infectious biopolymers i.e. prion proteins (mad cows disease), but in contrast of virus, infectious proteins are not CADS. The basic units of life is the cell (another CADS) and not only compounded biopolymers like polypeptides or polynucleotides chains. Cells are far more structured that viruses because they integer units of information (DNA genes) with complex metabolic pathways for processing of matter and energy, this latter function not available to viruses. The virome-the total viral populations now existing-must be integrated in the earth's biosphere ecosystems evolution (because of its obligatory cell parasite status), but its classification in families/species can not be easily adapted from our biological extant categories.

View PDFchevron_right
Virus Ontology: Thing, Being, Process, or Information?
Nicolae Sfetcu

MultiMedia Publishing, 2020

The study of viruses raises pressing conceptual and philosophical questions about their nature, their classification, and their place in the biological world. A major set of problems concerns the individuality and diachronic identity of a virus: what is the virus, the viral particle (virion) or the entire viral cycle? The correct identification of the virus has significant ontological consequences, also related to the place and time when biological entities begin and end. DOI: 10.13140/RG.2.2.35874.66241

View PDFchevron_right
The Infectious Disease Ontology in the Age of COVID-19
John Beverley

2020

Background: Effective response to public health emergencies, such as we are now experiencing with COVID-19, requires data sharing across multiple disciplines and data systems. Ontologies offer a powerful data sharing tool, and this holds especially for those ontologies built on the design principles of the Open Biomedical Ontologies Foundry. These principles are exemplified by the Infectious Disease Ontology (IDO), a suite of interoperable ontology modules aiming to provide coverage of all aspects of the infectious disease domain. At its center is IDO Core, a disease- and pathogen-neutral ontology covering just those types of entities and relations that are relevant to infectious diseases generally. IDO Core is extended by disease and pathogen-specific ontology modules.Results: To assist the integration and analysis of COVID-19 data, and viral infectious disease data more generally, we have recently developed three new IDO extensions: IDO Virus (VIDO); the Coronavirus Infectious Dis...

View PDFchevron_right
Ontology of the Virus
PLAMEN N . NIKOLOV, PhD

International Journal For Multidisciplinary Research, 2024

The paper describes the mutual correlation between the complex systems and the simple ones through the prism of the micro based entities like viruses. The carbon based biochemical beings in their capacity of complex systems are in a constant coexistence with viruses representing the simplest biological system, which unintendedly may destroy their host. On the other hand, the digital viruses also operate in an environment, where they can spread causing the same consequences for the complex system they use as a host. The article explicitly shows what are the similarities between the two entities, which can cause the same ontological outcomes, although they belong to different evolutionary paradigms.

View PDFchevron_right
OntoRepliCov: an Ontology-Based Approach for Modeling the SARS-CoV-2 Replication Process
Lina Soualmia

Procedia Computer Science, 2021

Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre-including this research content-immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

View PDFchevron_right
Combining Devs and Semantic Technologies for Modeling the SARS-CoV-2 Replication Machinery
Lina Soualmia

2021 Annual Modeling and Simulation Conference (ANNSIM), 2021

The search for inhibitors of SARS-CoV-2 viral replication depends on the understanding of the events taking place at different molecular levels during the viral infection. The macro-molecular level focuses on the interactions among viral and host proteins, while the micro-molecular level focuses on the different biochemical modifications that occur to one or more amino acids on proteins. A hybrid approach for modeling the SARS-CoV-2 viral replication in the micro-and macro-molecular levels is presented in this paper. The proposed approach combines two domains which complement one another, ontology engineering and discrete event system specification (DEVS) modeling.In this approach, biological knowledge at the micro-level of the viral system is capitalized and inferred by ontological models, while the dynamic behavior of SARS-CoV-2 molecular mechanisms and their different state changes in time are modeled by DEVS models. We illustrate the proposed approach through the modeling and simulation of the ribosome, a key molecule of the host cell that all viruses compete for, including the SARS-CoV-2.

View PDFchevron_right

References (76)

  1. Hershey, A.D.; Chase, M. Independent functions of viral protein and nucleic acid in growth of bacteriophage. J. Gen. Physiol. 1952, 36, 39-56. [CrossRef] [PubMed]
  2. Haq, I.U.; Chaudhry, W.N.; Akhtar, M.N.; Andleeb, S.; Qadri, I. Bacteriophages and their implications on future biotechnology: A review. Virol. J. 2012, 9, 9. [CrossRef] [PubMed]
  3. Henry, M.; Debarbieux, L. Tools from viruses: Bacteriophage successes and beyond. Virology 2012, 434, 151-161. [CrossRef] [PubMed]
  4. Sharan, S.K.; Thomason, L.C.; Kuznetsov, S.G.; Court, D.L. Recombineering: A homologous recombination- based method of genetic engineering. Nat. Protoc. 2009, 4, 206-223. [CrossRef] [PubMed]
  5. Cisek, A.A.; D ąbrowska, I.; Gregorczyk, K.P.; Wy żewski, Z. Phage Therapy in Bacterial Infections Treatment: One Hundred Years after the Discovery of Bacteriophages. Curr. Microbiol. 2017, 74, 277-283. [CrossRef] [PubMed] Viruses 2017, 9, 126 15 of 17
  6. Drulis-Kawa, Z.; Majkowska-Skrobek, G.; Maciejewska, B.; Delattre, A.-S.; Lavigne, R. Learning from bacteriophages-advantages and limitations of phage and phage-encoded protein applications. Curr. Protein Pept. Sci. 2012, 13, 699-722. [CrossRef] [PubMed]
  7. Snyder, J.C.; Bolduc, B.; Young, M.J. 40 Years of archaeal virology: Expanding viral diversity. Virology 2015, 479-480, 369-378. [CrossRef] [PubMed]
  8. Mann, N.H. The third age of phage. PLoS Biol. 2005, 3, e182. [CrossRef] [PubMed]
  9. Wagner, P.L.; Waldor, M.K. Bacteriophage control of bacterial virulence. Infect. Immun. 2002, 70, 3985-3993. [CrossRef] [PubMed]
  10. Jover, L.F.; Effler, T.C.; Buchan, A.; Wilhelm, S.W.; Weitz, J.S. The elemental composition of virus particles: Implications for marine biogeochemical cycles. Nat. Rev. Microbiol. 2014, 12, 519-528. [CrossRef] [PubMed]
  11. Rodriguez-Valera, F.; Martin-Cuadrado, A.-B.; Rodriguez-Brito, B.; Pasić, L.; Thingstad, T.F.; Rohwer, F.; Mira, A. Explaining microbial population genomics through phage predation. Nat. Rev. Microbiol. 2009, 7, 828-836. [CrossRef] [PubMed]
  12. Nelson, D. Phage taxonomy: We agree to disagree. J. Bacteriol. 2004, 186, 7029-7031. [CrossRef] [PubMed]
  13. Hulo, C.; de Castro, E.; Masson, P.; Bougueleret, L.; Bairoch, A.; Xenarios, I.; Le Mercier, P. ViralZone: A knowledge resource to understand virus diversity. Nucleic Acids Res. 2011, 39, 576-582. [CrossRef] [PubMed]
  14. UniProt Consortium. UniProt: A hub for protein information. Nucleic Acids Res. 2015, 43, 204-212.
  15. Ashburner, M.; Ball, C.A.; Blake, J.A.; Botstein, D.; Butler, H.; Cherry, J.M.; Davis, A.P.; Dolinski, K.; Dwight, S.S.; Eppig, J.T.; et al. Gene ontology: Tool for the unification of biology. Nat. Genet. 2000, 25, 25-29. [CrossRef] [PubMed]
  16. Gene Ontology Consortium. The Gene Ontology in 2010: Extensions and refinements. Nucleic Acids Res. 2010, 38, D331-D335.
  17. Masson, P.; Hulo, C.; de Castro, E.; Foulger, R.; Poux, S.; Bridge, A.; Lomax, J.; Bougueleret, L.; Xenarios, I.; Le Mercier, P. An integrated ontology resource to explore and study host-virus relationships. PLoS ONE 2014, 9, e108075. [CrossRef] [PubMed]
  18. Calendar, R. The Bacteriophages, 2th ed.; Oxford University Press: Oxford, UK, 2006.
  19. Toussaint, A.; Lima-Mendez, G.; Leplae, R. PhiGO, a phage ontology associated with the ACLAME database. Res. Microbiol. 2007, 158, 567-571. [CrossRef] [PubMed]
  20. Leiman, P.G.; Shneider, M.M. Contractile tail machines of bacteriophages. Adv. Exp. Med. Biol. 2012, 726, 93-114. [PubMed]
  21. Casjens, S.R.; Molineux, I.J. Short noncontractile tail machines: Adsorption and DNA delivery by podoviruses. Adv. Exp. Med. Biol. 2012, 726, 143-179. [PubMed]
  22. Davidson, A.R.; Cardarelli, L.; Pell, L.G.; Radford, D.R.; Maxwell, K.L. Long noncontractile tail machines of bacteriophages. Adv. Exp. Med. Biol. 2012, 726, 115-142. [PubMed]
  23. Büttner, C.R.; Wu, Y.; Maxwell, K.L.; Davidson, A.R. Baseplate assembly of phage Mu: Defining the conserved core components of contractile-tailed phages and related bacterial systems. Proc. Natl. Acad. Sci. USA 2016, 113, 10174-10179. [CrossRef] [PubMed]
  24. Taylor, N.M.I.; Prokhorov, N.S.; Guerrero-Ferreira, R.C.; Shneider, M.M.; Browning, C.; Goldie, K.N.; Stahlberg, H.; Leiman, P.G. Structure of the T4 baseplate and its function in triggering sheath contraction. Nature 2016, 533, 346-352. [CrossRef] [PubMed]
  25. Holland, S.J.; Sanz, C.; Perham, R.N. Identification and specificity of pilus adsorption proteins of filamentous bacteriophages infecting Pseudomonas aeruginosa. Virology 2006, 345, 540-548. [CrossRef] [PubMed]
  26. Choi, Y.; Shin, H.; Lee, J.-H.; Ryu, S. Identification and characterization of a novel flagellum-dependent Salmonella-infecting bacteriophage, iEPS5. Appl. Environ. Microbiol. 2013, 79, 4829-4837. [CrossRef] [PubMed]
  27. Grahn, A.M.; Daugelavicius, R.; Bamford, D.H. Sequential model of phage PRD1 DNA delivery: Active involvement of the viral membrane. Mol. Microbiol. 2002, 46, 1199-1209. [CrossRef] [PubMed]
  28. Rakonjac, J.; Bennett, N.J.; Spagnuolo, J.; Gagic, D.; Russel, M. Filamentous bacteriophage: Biology, phage display and nanotechnology applications. Curr. Issues Mol. Biol. 2011, 13, 51-76. [PubMed]
  29. Puspurs, A.H.; Trun, N.J.; Reeve, J.N. Bacteriophage Mu DNA circularizes following infection of Escherichia coli. EMBO J. 1983, 2, 345-352. [PubMed]
  30. Mardanov, A.V.; Ravin, N.V. Conversion of linear DNA with hairpin telomeres into a circular molecule in the course of phage N15 lytic replication. J. Mol. Biol. 2009, 391, 261-268. [CrossRef] [PubMed]
  31. Roldan, L.A.; Baker, T.A. Differential role of the Mu B protein in phage Mu integration vs. replication: Mechanistic insights into two transposition pathways. Mol. Microbiol. 2001, 40, 141-155. [CrossRef] [PubMed]
  32. Farruggio, A.P.; Chavez, C.L.; Mikell, C.L.; Calos, M.P. Efficient reversal of phiC31 integrase recombination in mammalian cells. Biotechnol. J. 2012, 7, 1332-1336. [CrossRef] [PubMed]
  33. Pope, W.H.; Bowman, C.A.; Russell, D.A.; Jacobs-Sera, D.; Asai, D.J.; Cresawn, S.G.; Jacobs, W.R.; Hendrix, R.W.; Lawrence, J.G.; Hatfull, G.F. Whole genome comparison of a large collection of mycobacteriophages reveals a continuum of phage genetic diversity. eLife 2015, 4, e06416. [CrossRef] [PubMed]
  34. Labrie, S.J.; Samson, J.E.; Moineau, S. Bacteriophage resistance mechanisms. Nat. Rev. Microbiol. 2010, 8, 317-327. [CrossRef] [PubMed]
  35. Samson, J.E.; Magadán, A.H.; Sabri, M.; Moineau, S. Revenge of the phages: Defeating bacterial defences. Nat. Rev. Microbiol. 2013, 11, 675-687. [CrossRef] [PubMed]
  36. Roberts, R.J. Restriction and modification enzymes and their recognition sequences. Nucleic Acids Res. 1981, 9, 167-204. [CrossRef]
  37. Studier, F.W. Gene 0.3 of bacteriophage T7 acts to overcome the DNA restriction system of the host. J. Mol. Biol. 1975, 94, 283-295. [CrossRef]
  38. Berkner, K.L.; Folk, W.R. The effects of substituted pyrimidines in DNAs on cleavage by sequence-specific endonucleases. J. Biol. Chem. 1979, 254, 2551-2560. [PubMed]
  39. Dillingham, M.S.; Kowalczykowski, S.C. RecBCD enzyme and the repair of double-stranded DNA breaks. Microbiol. Mol. Biol. Rev. 2008, 72, 642-671. [CrossRef] [PubMed]
  40. Lipinska, B.; Rao, A.S.; Bolten, B.M.; Balakrishnan, R.; Goldberg, E.B. Cloning and identification of bacteriophage T4 gene 2 product Gp2 and action of Gp2 on infecting DNA in vivo. J. Bacteriol. 1989, 171, 488-497. [CrossRef] [PubMed]
  41. Murphy, K.C. The lambda Gam protein inhibits RecBCD binding to dsDNA ends. J. Mol. Biol. 2007, 371, 19-24. [CrossRef] [PubMed]
  42. Chopin, M.-C.; Chopin, A.; Bidnenko, E. Phage abortive infection in lactococci: Variations on a theme. Curr. Opin. Microbiol. 2005, 8, 473-479. [CrossRef] [PubMed]
  43. Otsuka, Y.; Yonesaki, T. Dmd of bacteriophage T4 functions as an antitoxin against Escherichia coli LsoA and RnlA toxins. Mol. Microbiol. 2012, 83, 669-681. [CrossRef] [PubMed]
  44. Barrangou, R.; Marraffini, L.A. CRISPR-Cas systems: Prokaryotes upgrade to adaptive immunity. Mol. Cell 2014, 54, 234-244. [CrossRef] [PubMed]
  45. Bondy-Denomy, J.; Pawluk, A.; Maxwell, K.L.; Davidson, A.R. Bacteriophage genes that inactivate the CRISPR/Cas bacterial immune system. Nature 2013, 493, 429-432. [CrossRef] [PubMed]
  46. Seed, K.D.; Lazinski, D.W.; Calderwood, S.B.; Camilli, A. A bacteriophage encodes its own CRISPR/Cas adaptive response to evade host innate immunity. Nature 2013, 494, 489-491. [CrossRef] [PubMed]
  47. Bae, B.; Davis, E.; Brown, D.; Campbell, E.A.; Wigneshweraraj, S.; Darst, S.A. Phage T7 Gp2 inhibition of Escherichia coli RNA polymerase involves misappropriation of σ70 domain 1.1. Proc. Natl. Acad. Sci. USA 2013, 110, 19772-19777. [CrossRef] [PubMed]
  48. Souther, A.; Bruner, R.; Elliott, J. Degradation of Escherichia coli chromosome after infection by bacteriophage T4: Role of bacteriophage gene D2a. J. Virol. 1972, 10, 979-984. [PubMed]
  49. Powell, I.B.; Tulloch, D.L.; Hillier, A.J.; Davidson, B.E. Phage DNA synthesis and host DNA degradation in the life cycle of Lactococcus lactis bacteriophage c6A. J. Gen. Microbiol. 1992, 138, 945-950. [CrossRef] [PubMed]
  50. Yano, S.T.; Rothman-Denes, L.B. A phage-encoded inhibitor of Escherichia coli DNA replication targets the DNA polymerase clamp loader. Mol. Microbiol. 2011, 79, 1325-1338. [CrossRef] [PubMed]
  51. Belley, A.; Callejo, M.; Arhin, F.; Dehbi, M.; Fadhil, I.; Liu, J.; McKay, G.; Srikumar, R.; Bauda, P.; Bergeron, D.; et al. Competition of bacteriophage polypeptides with native replicase proteins for binding to the DNA sliding clamp reveals a novel mechanism for DNA replication arrest in Staphylococcus aureus. Mol. Microbiol. 2006, 62, 1132-1143. [CrossRef] [PubMed]
  52. Bondy-Denomy, J.; Qian, J.; Westra, E.R.; Buckling, A.; Guttman, D.S.; Davidson, A.R.; Maxwell, K.L. Prophages mediate defense against phage infection through diverse mechanisms. ISME J. 2016, 10, 2854-2866. [CrossRef] [PubMed]
  53. Berngruber, T.W.; Weissing, F.J.; Gandon, S. Inhibition of superinfection and the evolution of viral latency. J. Virol. 2010, 84, 10200-10208. [CrossRef] [PubMed] Viruses 2017, 9, 126
  54. Braun, V.; Killmann, H.; Herrmann, C. Inactivation of FhuA at the cell surface of Escherichia coli K-12 by a phage T5 lipoprotein at the periplasmic face of the outer membrane. J. Bacteriol. 1994, 176, 4710-4717. [CrossRef] [PubMed]
  55. Lu, M.J.; Henning, U. Superinfection exclusion by T-even-type coliphages. Trends Microbiol. 1994, 2, 137-139.
  56. Abedon, S.T.; Lejeune, J.T. Why bacteriophage encode exotoxins and other virulence factors. Evol. Bioinform. Online 2007, 1, 97-110. [PubMed]
  57. Boyd, E.F.; Brüssow, H. Common themes among bacteriophage-encoded virulence factors and diversity among the bacteriophages involved. Trends Microbiol. 2002, 10, 521-529. [CrossRef]
  58. Mann, N.H.; Clokie, M.R.J.; Millard, A.; Cook, A.; Wilson, W.H.; Wheatley, P.J.; Letarov, A.; Krisch, H.M. The genome of S-PM2, a "photosynthetic" T4-type bacteriophage that infects marine Synechococcus strains. J. Bacteriol. 2005, 187, 3188-3200. [CrossRef] [PubMed]
  59. Maluf, N.K.; Gaussier, H.; Bogner, E.; Feiss, M.; Catalano, C.E. Assembly of bacteriophage lambda terminase into a viral DNA maturation and packaging machine. Biochemistry 2006, 45, 15259-15268. [CrossRef] [PubMed]
  60. Zhang, Z.; Kottadiel, V.I.; Vafabakhsh, R.; Dai, L.; Chemla, Y.R.; Ha, T.; Rao, V.B. A promiscuous DNA packaging machine from bacteriophage T4. PLoS Biol. 2011, 9, e1000592. [CrossRef] [PubMed]
  61. Narajczyk, M.; Bara ńska, S.; Wegrzyn, A.; Wegrzyn, G. Switch from theta to sigma replication of bacteriophage lambda DNA: Factors involved in the process and a model for its regulation. Mol. Genet. Genom. 2007, 278, 65-74. [CrossRef] [PubMed]
  62. Salas, M.; Holguera, I.; Redrejo-Rodríguez, M.; de Vega, M. DNA-binding proteins essential for protein-primed bacteriophage Φ29 DNA replication. Front. Mol. Biosci. 2016, 3, 37. [CrossRef] [PubMed]
  63. Hulo, C.; Masson, P.; Le Mercier, P.; Toussaint, A. A structured annotation frame for the transposable phages: A new proposed family "Saltoviridae" within the Caudovirales. Virology 2015, 477, 155-163. [CrossRef] [PubMed]
  64. Shapiro, J.A. Molecular model for the transposition and replication of bacteriophage Mu and other transposable elements. Proc. Natl. Acad. Sci. USA 1979, 76, 1933-1937. [CrossRef] [PubMed]
  65. Lundström, K.H.; Bamford, D.H.; Palva, E.T.; Lounatmaa, K. Lipid-containing bacteriophage PR4: Structure and life cycle. J. Gen. Virol. 1979, 43, 583-592. [CrossRef] [PubMed]
  66. Johnson, M.D.; Mindich, L. Plasmid-directed assembly of the lipid-containing membrane of bacteriophage phi 6. J. Bacteriol. 1994, 176, 4124-4132. [CrossRef] [PubMed]
  67. Young, R. Phage lysis: Three steps, three choices, one outcome. J. Microbiol. Seoul Korea 2014, 52, 243-258. [CrossRef] [PubMed]
  68. Young, R. Phage lysis: Do we have the hole story yet? Curr. Opin. Microbiol. 2013, 16, 790-797. [CrossRef] [PubMed]
  69. Zheng, Y.; Struck, D.K.; Young, R. Purification and functional characterization of phiX174 lysis protein E. Biochemistry 2009, 48, 4999-5006. [CrossRef] [PubMed]
  70. Karnik, S.; Billeter, M. The lysis function of RNA bacteriophage Qbeta is mediated by the maturation (A2) protein. EMBO J. 1983, 2, 1521-1526. [PubMed]
  71. Marvin, D.A.; Symmons, M.F.; Straus, S.K. Structure and assembly of filamentous bacteriophages. Prog. Biophys. Mol. Biol. 2014, 114, 80-122. [CrossRef] [PubMed]
  72. Poddar, S.K.; Cadden, S.P.; Das, J.; Maniloff, J. Heterogeneous progeny viruses are produced by a budding enveloped phage. Intervirology 1985, 23, 208-221. [CrossRef] [PubMed]
  73. Burge, S.; Kelly, E.; Lonsdale, D.; Mutowo-Muellenet, P.; McAnulla, C.; Mitchell, A.; Sangrador-Vegas, A.; Yong, S.-Y.; Mulder, N.; Hunter, S. Manual GO annotation of predictive protein signatures: The InterPro approach to GO curation. Database J. Biol. Databases Curation 2012, 2012. [CrossRef] [PubMed]
  74. Pedruzzi, I.; Rivoire, C.; Auchincloss, A.H.; Coudert, E.; Keller, G.; de Castro, E.; Baratin, D.; Cuche, B.A.; Bougueleret, L.; Poux, S.; et al. HAMAP in 2015: Updates to the protein family classification and annotation system. Nucleic Acids Res. 2015, 43, D1064-D1070. [CrossRef] [PubMed]
  75. Delattre, H.; Souiai, O.; Fagoonee, K.; Guerois, R.; Petit, M.-A. Phagonaute: A web-based interface for phage synteny browsing and protein function prediction. Virology 2016, 496, 42-50. [CrossRef] [PubMed]
  76. Category: CACAO-GONUTS. Available online: https://gowiki.tamu.edu/wiki/index.php/Category: CACAO (accessed on 16 May 2017).

Related papers

The ins and outs of eukaryotic viruses: Knowledge base and ontology of a viral infection
Sylvain Poux

PloS one, 2017

Viruses are genetically diverse, infect a wide range of tissues and host cells and follow unique processes for replicating themselves. All these processes were investigated and indexed in ViralZone knowledge base. To facilitate standardizing data, a simple ontology of viral life-cycle terms was developed to provide a common vocabulary for annotating data sets. New terminology was developed to address unique viral replication cycle processes, and existing terminology was modified and adapted. The virus life-cycle is classically described by schematic pictures. Using this ontology, it can be represented by a combination of successive terms: "entry", "latency", "transcription", "replication" and "exit". Each of these parts is broken down into discrete steps. For example Zika virus "entry" is broken down in successive steps: "Attachment", "Apoptotic mimicry", "Viral endocytosis/ macropinocytosis", ...

View PDFchevron_right
An integrated ontology resource to explore and study host-virus relationships
Lydie Bougueleret, Ioannis Xenarios, Sylvain Poux

PloS one, 2014

Our growing knowledge of viruses reveals how these pathogens manage to evade innate host defenses. A global scheme emerges in which many viruses usurp key cellular defense mechanisms and often inhibit the same components of antiviral signaling. To accurately describe these processes, we have generated a comprehensive dictionary for eukaryotic host-virus interactions. This controlled vocabulary has been detailed in 57 ViralZone resource web pages which contain a global description of all molecular processes. In order to annotate viral gene products with this vocabulary, an ontology has been built in a hierarchy of UniProt Knowledgebase (UniProtKB) keyword terms and corresponding Gene Ontology (GO) terms have been developed in parallel. The results are 65 UniProtKB keywords related to 57 GO terms, which have been used in 14,390 manual annotations; 908,723 automatic annotations and propagated to an estimation of 922,941 GO annotations. ViralZone pages, UniProtKB keywords and GO terms p...

View PDFchevron_right
Understanding animal viruses using the Gene Ontology
Shane C Burgess

Trends in Microbiology, 2009

View PDFchevron_right
HBVO: Human Biological Viruses Ontology
Kashif Raffat

2012

Biological viruses have recently received a lot of attention especially in sub continent due to some spectacular effects of infections like bird flu, dengue and swine flu. This problem generated a requirement to classify these viruses in some formal form. Therefore, we are proposing an ontology for Human Biological Viruses Ontology (HBVO) that covers all the viruses that belongs to human. The proposed ontology is developed by using the principles of Open Biological Ontologies and will be available in the format of OBO. It can be viewed by using OBO-Edit. To develop HBVO we used the taxonomy developed by the International Committee on Taxonomy of Viruses.

View PDFchevron_right
Towards the development of Biological Viruses Community Ontology (BVCO)
Kashif Raffat

This century is said to be the century of biological and information sciences due to the number of researches conducted in this field. The viruses (biological and non-biological) received a lot of attention in all over the world due to its massive effect on different living communities. Viruses like bird flu, dengue and late blight of potato had its drastic impact on human, animal and plant communities. All these problems generated a need to classify these virus communities in some formal form. Ontology plays a vital role in classification of different biological information in a controlled and appropriate manner. Therefore, Biological Viruses Community Ontology (BVCO) is proposed which will cover virus communities exist in different species. Viruses are part of different viral communities according to its host like vertebrate, invertebrate, plant and unicellular organism. The proposed ontology is developed by using the principles of Open Biomedical Ontology (OBO) and will be available in the format of OBO. It can be explore by using OBO-Edit or any other OBO supported browser. To develop BVCO we used the taxonomy of viruses developed by the International Committee on Taxonomy of Viruses (ICTV).

View PDFchevron_right

Cited by

Prion-Like Domains in Phagobiota
Victor Tetz

Frontiers in Microbiology

Prions are molecules characterized by self-propagation, which can undergo a conformational switch leading to the creation of new prions. Prion proteins have originally been associated with the development of mammalian pathologies; however, recently they have been shown to contribute to the environmental adaptation in a variety of prokaryotic and eukaryotic organisms. Bacteriophages are widespread and represent the important regulators of microbiota homeostasis and have been shown to be diverse across various bacterial families. Here, we examined whether bacteriophages contain prion-like proteins and whether these prion-like protein domains are involved in the regulation of homeostasis. We used a computational algorithm, prion-like amino acid composition, to detect prion-like domains in 370,617 publicly available bacteriophage protein sequences, which resulted in the identification of 5040 putative prions. We analyzed a set of these prion-like proteins, and observed regularities in their distribution across different phage families, associated with their interactions with the bacterial host cells. We found that prion-like domains could be found across all phages of various groups of bacteria and archaea. The results obtained in this study indicate that bacteriophage prion-like proteins are predominantly involved in the interactions between bacteriophages and bacterial cell, such as those associated with the attachment and penetration of bacteriophage in the cell, and the release of the phage progeny. These data allow the identification of phage prion-like proteins as novel regulators of the interactions between bacteriophages and bacterial cells.

View PDFchevron_right
580 California St., Suite 400
San Francisco, CA, 94104
© 2025 Academia. All rights reserved