Статті в журналах: "Virus interactions"

1

Strebel, Klaus. "Virus–host interactions." AIDS 17, Supplement 4 (2003): S25—S34. http://dx.doi.org/10.1097/00002030-200317004-00003.

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2

Stebbing, Justin, and Brian Gazzard. "Virus host interactions." Obstetrician & Gynaecologist 5, no. 2 (April 2003): 103–6. http://dx.doi.org/10.1576/toag.5.2.103.

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3

Calderwood, Michael A., Kavitha Venkatesan, Li Xing, Michael R. Chase, Alexei Vazquez, Amy M. Holthaus, Alexandra E. Ewence, et al. "Epstein–Barr virus and virus human protein interaction maps." Proceedings of the National Academy of Sciences 104, no. 18 (April 19, 2007): 7606–11. http://dx.doi.org/10.1073/pnas.0702332104.

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A comprehensive mapping of interactions among Epstein–Barr virus (EBV) proteins and interactions of EBV proteins with human proteins should provide specific hypotheses and a broad perspective on EBV strategies for replication and persistence. Interactions of EBV proteins with each other and with human proteins were assessed by using a stringent high-throughput yeast two-hybrid system. Overall, 43 interactions between EBV proteins and 173 interactions between EBV and human proteins were identified. EBV–EBV and EBV–human protein interaction, or “interactome” maps provided a framework for hypotheses of protein function. For example, LF2, an EBV protein of unknown function interacted with the EBV immediate early R transactivator (Rta) and was found to inhibit Rta transactivation. From a broader perspective, EBV genes can be divided into two evolutionary classes, “core” genes, which are conserved across all herpesviruses and subfamily specific, or “noncore” genes. Our EBV–EBV interactome map is enriched for interactions among proteins in the same evolutionary class. Furthermore, human proteins targeted by EBV proteins were enriched for highly connected or “hub” proteins and for proteins with relatively short paths to all other proteins in the human interactome network. Targeting of hubs might be an efficient mechanism for EBV reorganization of cellular processes.

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4

Roy, Urmi. "Host–Virus Interactions in Japanese Encephalitis Virus." Zoonotic Diseases 2, no. 3 (August 5, 2022): 117–25. http://dx.doi.org/10.3390/zoonoticdis2030012.

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Japanese encephalitis (JE) is a mosquito-borne zoonotic disease that causes severe brain inflammation. The JE virus envelope protein domain III (JEV-ED3) plays a critical role in activating receptor binding and membrane fusion. This communication briefly describes, in a computational approach, how structural changes within the JEV-ED3 mutant epitopes suppress their antibody neutralization function. The simulated results demonstrate that mutant Ser40Lys acts as an antibody neutralization escape while Asp41Arg may play the role of an escape mutant. Additionally, an examination of the double mutants on JEV-ED3 suggests that these mutants may qualify as stronger neutralizing escape agents than their single variants. The structural analysis of this work helps to identify the proper antiviral target sequences and specific monoclonal antibodies for the JEV-ED3 escape mutants.

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5

Pawlotsky, J. M. "Hepatitis C virus infection: virus/host interactions." Journal of Viral Hepatitis 5, s1 (September 1998): 3–8. http://dx.doi.org/10.1046/j.1365-2893.1998.0050s1003.x.

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6

Segredo-Otero, Ernesto, and Rafael Sanjuán. "Cooperative Virus-Virus Interactions: An Evolutionary Perspective." BioDesign Research 2022 (October 3, 2022): 1–13. http://dx.doi.org/10.34133/2022/9819272.

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Despite extensive evidence of virus-virus interactions, not much is known about their biological significance. Importantly, virus-virus interactions could have evolved as a form of cooperation or simply be a by-product of other processes. Here, we review and discuss different types of virus-virus interactions from the point of view of social evolution, which provides a well-established framework for interpreting the fitness costs and benefits of such traits. We also classify interactions according to their mechanisms of action and speculate on their evolutionary implications. As in any other biological system, the evolutionary stability of viral cooperation critically requires cheaters to be excluded from cooperative interactions. We discuss how cheater viruses exploit cooperative traits and how viral populations are able to counteract this maladaptive process.

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7

DaPalma, T., B. P. Doonan, N. M. Trager, and L. M. Kasman. "A systematic approach to virus–virus interactions." Virus Research 149, no. 1 (April 2010): 1–9. http://dx.doi.org/10.1016/j.virusres.2010.01.002.

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8

Cook, Helen, Nadezhda Doncheva, Damian Szklarczyk, Christian von Mering, and Lars Jensen. "Viruses.STRING: A Virus-Host Protein-Protein Interaction Database." Viruses 10, no. 10 (September 23, 2018): 519. http://dx.doi.org/10.3390/v10100519.

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As viruses continue to pose risks to global health, having a better understanding of virus–host protein–protein interactions aids in the development of treatments and vaccines. Here, we introduce Viruses.STRING, a protein–protein interaction database specifically catering to virus–virus and virus–host interactions. This database combines evidence from experimental and text-mining channels to provide combined probabilities for interactions between viral and host proteins. The database contains 177,425 interactions between 239 viruses and 319 hosts. The database is publicly available at viruses.string-db.org, and the interaction data can also be accessed through the latest version of the Cytoscape STRING app.

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9

Hoenen, Thomas, and Allison Groseth. "Virus–Host Cell Interactions." Cells 11, no. 5 (February 25, 2022): 804. http://dx.doi.org/10.3390/cells11050804.

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10

Coffey, Lark, Anna-Bella Failloux, and Scott Weaver. "Chikungunya Virus–Vector Interactions." Viruses 6, no. 11 (November 24, 2014): 4628–63. http://dx.doi.org/10.3390/v6114628.

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11

Harty, Ronald N., Anthony P. Schmitt, Fadila Bouamr, Carolina B. Lopez, and Claude Krummenacher. "Virus Budding/Host Interactions." Advances in Virology 2011 (2011): 1–2. http://dx.doi.org/10.1155/2011/963192.

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12

Haverkos, H. W., Z. Amsel, and D. P. Drotman. "Adverse Virus-Drug Interactions." Clinical Infectious Diseases 13, no. 4 (July 1, 1991): 697–704. http://dx.doi.org/10.1093/clinids/13.4.697.

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13

Zaitlin, M., and R. Hull. "Plant Virus-Host Interactions." Annual Review of Plant Physiology 38, no. 1 (June 1987): 291–315. http://dx.doi.org/10.1146/annurev.pp.38.060187.001451.

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14

Halstead, Scott B. "Dengue Virus–Mosquito Interactions." Annual Review of Entomology 53, no. 1 (January 2008): 273–91. http://dx.doi.org/10.1146/annurev.ento.53.103106.093326.

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15

Air, Gillian M. "Influenza virus–glycan interactions." Current Opinion in Virology 7 (August 2014): 128–33. http://dx.doi.org/10.1016/j.coviro.2014.06.004.

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16

Oldstone, M. B. A. "Virus-lymphoid cell interactions." Proceedings of the National Academy of Sciences 93, no. 23 (November 12, 1996): 12756–58. http://dx.doi.org/10.1073/pnas.93.23.12756.

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17

Perdiguero, Beatriz, and Rafael Blasco. "Interaction between Vaccinia Virus Extracellular Virus Envelope A33 and B5 Glycoproteins." Journal of Virology 80, no. 17 (September 1, 2006): 8763–77. http://dx.doi.org/10.1128/jvi.00598-06.

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ABSTRACT The extracellular form of vaccinia virus acquires its outer envelope by wrapping with cytoplasmic membranes that contain at least seven virus-encoded proteins, of which four are glycoproteins. We searched for interactions between the vaccinia virus A33 glycoprotein and proteins A34, A36, B5, F12, and F13. First, when myc epitope-tagged A33 was expressed in combination with other envelope proteins, A33 colocalized with B5 and A36, suggesting that direct A33-B5 and A33-A36 interactions occur in the absence of infection. A recombinant vaccinia virus (vA33Rmyc) was constructed by introduction of the myc-tagged A33 version (A33myc) into A33-deficient vaccinia virus. A33myc partially restored plaque formation and colocalized with enveloped virions in infected cells. Coimmunoprecipitation experiments with extracts of vA33Rmyc-infected cells confirmed the existence of a physical association of A33 with A36 and B5. Of these, the A33-B5 interaction is a novel finding, whereas the interaction between A33 and A36 has been previously characterized. A collection of vaccinia viruses expressing mutated versions of the B5 protein was used to investigate the domain(s) of B5 required for interaction with A33. Both the cytoplasmic domain and most of the extracellular domain, but not the transmembrane domain, of the B5 protein were dispensable for binding to A33. Mutations in the extracellular portions of B5 and A33 that enhance extracellular virus release did not affect the interaction between the two. In contrast, substituting the B5 transmembrane domain with that of the vesicular stomatitis virus G glycoprotein prevented the association with A33. Immunofluorescence experiments on virus mutants indicated that B5 is required for efficient targeting of A33 into enveloped virions. These results point to the transmembrane domain of B5 as the major determinant of the A33-B5 interaction and demonstrate that protein-protein interactions are crucial in determining the composition of the virus envelope.

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18

Van Vliet, Kim, Mohamed R. Mohamed, Leiliang Zhang, Nancy Yaneth Villa, Steven J. Werden, Jia Liu, and Grant McFadden. "Poxvirus Proteomics and Virus-Host Protein Interactions." Microbiology and Molecular Biology Reviews 73, no. 4 (December 2009): 730–49. http://dx.doi.org/10.1128/mmbr.00026-09.

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SUMMARY Studies of the functional proteins encoded by the poxvirus genome provide information about the composition of the virus as well as individual virus-virus protein and virus-host protein interactions, which provides insight into viral pathogenesis and drug discovery. Widely used proteomic techniques to identify and characterize specific protein-protein interactions include yeast two-hybrid studies and coimmunoprecipitations. Recently, various mass spectrometry techniques have been employed to identify viral protein components of larger complexes. These methods, combined with structural studies, can provide new information about the putative functions of viral proteins as well as insights into virus-host interaction dynamics. For viral proteins of unknown function, identification of either viral or host binding partners provides clues about their putative function. In this review, we discuss poxvirus proteomics, including the use of proteomic methodologies to identify viral components and virus-host protein interactions. High-throughput global protein expression studies using protein chip technology as well as new methods for validating putative protein-protein interactions are also discussed.

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19

Guidotti, Luca G., Masanori Isogawa, and Francis V. Chisari. "Host–virus interactions in hepatitis B virus infection." Current Opinion in Immunology 36 (October 2015): 61–66. http://dx.doi.org/10.1016/j.coi.2015.06.016.

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20

Trinh, Jimmy Tri, and Lanying Zeng. "Virus interactions: cooperation or competition?" Future Microbiology 12, no. 7 (June 2017): 561–64. http://dx.doi.org/10.2217/fmb-2017-0048.

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21

Lang, G., W. Howell, and D. Ophardt. "SWEET CHERRY ROOTSTOCK/VIRUS INTERACTIONS." Acta Horticulturae, no. 468 (July 1998): 307–14. http://dx.doi.org/10.17660/actahortic.1998.468.36.

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22

Yang, Meng, Asigul Ismayil, and Yule Liu. "Autophagy in Plant-Virus Interactions." Annual Review of Virology 7, no. 1 (September 29, 2020): 403–19. http://dx.doi.org/10.1146/annurev-virology-010220-054709.

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Autophagy is a conserved vacuole/lysosome-mediated degradation pathway for clearing and recycling cellular components including cytosol, macromolecules, and dysfunctional organelles. In recent years, autophagy has emerged to play important roles in plant-pathogen interactions. It acts as an antiviral defense mechanism in plants. Moreover, increasing evidence shows that plant viruses can manipulate, hijack, or even exploit the autophagy pathway to promote pathogenesis, demonstrating the pivotal role of autophagy in the evolutionary arms race between hosts and viruses. In this review, we discuss recent findings about the antiviral and proviral roles of autophagy in plant-virus interactions.

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23

Jameson, Paula E., and Sean F. Clarke. "Hormone-Virus Interactions in Plants." Critical Reviews in Plant Sciences 21, no. 3 (May 2002): 205–28. http://dx.doi.org/10.1080/0735-260291044241.

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24

Vassilaki, Niki, and Efseveia Frakolaki. "Virus–host interactions under hypoxia." Microbes and Infection 19, no. 3 (March 2017): 193–203. http://dx.doi.org/10.1016/j.micinf.2016.10.004.

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25

Milazzo, Laura, and Spinello Antinori. "Hepatitis virus and HIV interactions." Lancet Infectious Diseases 14, no. 11 (November 2014): 1025–27. http://dx.doi.org/10.1016/s1473-3099(14)70853-9.

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26

Lozach, Pierre-Yves. "Early Virus–Host Cell Interactions." Journal of Molecular Biology 430, no. 17 (August 2018): 2555–56. http://dx.doi.org/10.1016/j.jmb.2018.06.049.

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27

Gavala, Monica L., Hiba Bashir, and James E. Gern. "Virus/Allergen Interactions in Asthma." Current Allergy and Asthma Reports 13, no. 3 (March 10, 2013): 298–307. http://dx.doi.org/10.1007/s11882-013-0344-1.

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28

Weaver, Scott C., and Anne E. Simon. "Editorial overview: Virus–vector interactions." Current Opinion in Virology 15 (December 2015): iv—vi. http://dx.doi.org/10.1016/j.coviro.2015.11.001.

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29

Kramer, Laura D. "Complexity of virus–vector interactions." Current Opinion in Virology 21 (December 2016): 81–86. http://dx.doi.org/10.1016/j.coviro.2016.08.008.

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30

Rico-Hesse, Rebecca. "Editorial Overview: Virus–vector interactions." Current Opinion in Virology 21 (December 2016): v—vi. http://dx.doi.org/10.1016/j.coviro.2016.11.003.

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31

Klagge, I. M., and S. Schneider-Schaulies. "Virus interactions with dendritic cells." Journal of General Virology 80, no. 4 (April 1, 1999): 823–33. http://dx.doi.org/10.1099/0022-1317-80-4-823.

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32

Ploegh, Hidde. "VIRUS INTERACTIONS WITH IMMUNE SYSTEM." JAIDS: Journal of Acquired Immune Deficiency Syndromes 21, no. 1 (May 1999): A7. http://dx.doi.org/10.1097/00126334-199905010-00014.

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33

Young, John A. T. "Avian leukosis virus‐receptor interactions." Avian Pathology 27, sup1 (April 1998): S21—S25. http://dx.doi.org/10.1080/03079459808419289.

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34

Kamitani, Mari, Atsushi J. Nagano, Mie N. Honjo, and Hiroshi Kudoh. "RNA-Seq reveals virus–virus and virus–plant interactions in nature." FEMS Microbiology Ecology 92, no. 11 (August 21, 2016): fiw176. http://dx.doi.org/10.1093/femsec/fiw176.

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35

Jayawardena, Nadishka, John T. Poirier, Laura N. Burga, and Mihnea Bostina. "Virus–Receptor Interactions and Virus Neutralization: Insights for Oncolytic Virus Development." Oncolytic Virotherapy Volume 9 (March 2020): 1–15. http://dx.doi.org/10.2147/ov.s186337.

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36

Llabrés, Mercè, and Gabriel Valiente. "Alignment of virus-host protein-protein interaction networks by integer linear programming: SARS-CoV-2." PLOS ONE 15, no. 12 (December 7, 2020): e0236304. http://dx.doi.org/10.1371/journal.pone.0236304.

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Motivation Beside socio-economic issues, coronavirus pandemic COVID-19, the infectious disease caused by the newly discovered coronavirus SARS-CoV-2, has caused a deep impact in the scientific community, that has considerably increased its effort to discover the infection strategies of the new virus. Among the extensive and crucial research that has been carried out in the last months, the analysis of the virus-host relationship plays an important role in drug discovery. Virus-host protein-protein interactions are the active agents in virus replication, and the analysis of virus-host protein-protein interaction networks is fundamental to the study of the virus-host relationship. Results We have adapted and implemented a recent integer linear programming model for protein-protein interaction network alignment to virus-host networks, and obtained a consensus alignment of the SARS-CoV-1 and SARS-CoV-2 virus-host protein-protein interaction networks. Despite the lack of shared human proteins in these virus-host networks, and the low number of preserved virus-host interactions, the consensus alignment revealed aligned human proteins that share a function related to viral infection, as well as human proteins of high functional similarity that interact with SARS-CoV-1 and SARS-CoV-2 proteins, whose alignment would preserve these virus-host interactions.

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37

Füzik, Tibor, Růžena Píchalová, Florian K. M. Schur, Karolína Strohalmová, Ivana Křížová, Romana Hadravová, Michaela Rumlová, John A. G. Briggs, Pavel Ulbrich, and Tomáš Ruml. "Nucleic Acid Binding by Mason-Pfizer Monkey Virus CA Promotes Virus Assembly and Genome Packaging." Journal of Virology 90, no. 9 (February 24, 2016): 4593–603. http://dx.doi.org/10.1128/jvi.03197-15.

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ABSTRACTThe Gag polyprotein of retroviruses drives immature virus assembly by forming hexameric protein lattices. The assembly is primarily mediated by protein-protein interactions between capsid (CA) domains and by interactions between nucleocapsid (NC) domains and RNA. Specific interactions between NC and the viral RNA are required for genome packaging. Previously reported cryoelectron microscopy analysis of immature Mason-Pfizer monkey virus (M-PMV) particles suggested that a basic region (residues RKK) in CA may serve as an additional binding site for nucleic acids. Here, we have introduced mutations into the RKK region in both bacterial and proviral M-PMV vectors and have assessed their impact on M-PMV assembly, structure, RNA binding, budding/release, nuclear trafficking, and infectivity usingin vitroandin vivosystems. Our data indicate that the RKK region binds and structures nucleic acid that serves to promote virus particle assembly in the cytoplasm. Moreover, the RKK region appears to be important for recruitment of viral genomic RNA into Gag particles, and this function could be linked to changes in nuclear trafficking. Together these observations suggest that in M-PMV, direct interactions between CA and nucleic acid play important functions in the late stages of the viral life cycle.IMPORTANCEAssembly of retrovirus particles is driven by the Gag polyprotein, which can self-assemble to form virus particles and interact with RNA to recruit the viral genome into the particles. Generally, the capsid domains of Gag contribute to essential protein-protein interactions during assembly, while the nucleocapsid domain interacts with RNA. The interactions between the nucleocapsid domain and RNA are important both for identifying the genome and for self-assembly of Gag molecules. Here, we show that a region of basic residues in the capsid protein of the betaretrovirus Mason-Pfizer monkey virus (M-PMV) contributes to interaction of Gag with nucleic acid. This interaction appears to provide a critical scaffolding function that promotes assembly of virus particles in the cytoplasm. It is also crucial for packaging the viral genome and thus for infectivity. These data indicate that, surprisingly, interactions between the capsid domain and RNA play an important role in the assembly of M-PMV.

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38

Hamel, Rodolphe, Florian Liégeois, Sineewanlaya Wichit, Julien Pompon, Fodé Diop, Loïc Talignani, Frédéric Thomas, Philippe Desprès, Hans Yssel, and Dorothée Missé. "Zika virus: epidemiology, clinical features and host-virus interactions." Microbes and Infection 18, no. 7-8 (July 2016): 441–49. http://dx.doi.org/10.1016/j.micinf.2016.03.009.

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39

Arvin, A. "Varicella-zoster virus: molecular virology and virus–host interactions." Current Opinion in Microbiology 4, no. 4 (August 1, 2001): 442–49. http://dx.doi.org/10.1016/s1369-5274(00)00233-2.

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40

Zhang, QiYa, and Jian-Fang Gui. "Virus genomes and virus-host interactions in aquaculture animals." Science China Life Sciences 58, no. 2 (January 15, 2015): 156–69. http://dx.doi.org/10.1007/s11427-015-4802-y.

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41

Matthew A., Gonda, Luther D. Gene, Fong Steven E., and Tobin Gregory J. "Bovine immunodeficiency virus: molecular biology and virus-host interactions." Virus Research 32, no. 2 (May 1994): 155–81. http://dx.doi.org/10.1016/0168-1702(94)90040-x.

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42

Shirvani-Dastgerdi, Elham. "Molecular interactions between hepatitis B virus and delta virus." World Journal of Virology 4, no. 2 (2015): 36. http://dx.doi.org/10.5501/wjv.v4.i2.36.

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43

Jayawardena, Nadishka, Laura N. Burga, John T. Poirier, and Mihnea Bostina. "Virus–Receptor Interactions: Structural Insights For Oncolytic Virus Development." Oncolytic Virotherapy Volume 8 (October 2019): 39–56. http://dx.doi.org/10.2147/ov.s218494.

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44

Frisque, RJ, LH Kilpatrick, and ST Tyagarajan. "JC virus early proteins: Contributions to virus-host interactions." Journal of Neurovirology 10, s2 (January 2004): 21. http://dx.doi.org/10.1080/13550280490469653.

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45

Landers, V. Douglas, Daniel W. Wilkey, Michael L. Merchant, Thomas C. Mitchell, and Kevin J. Sokoloski. "The Alphaviral Capsid Protein Inhibits IRAK1-Dependent TLR Signaling." Viruses 13, no. 3 (February 27, 2021): 377. http://dx.doi.org/10.3390/v13030377.

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Alphaviruses are arthropod-borne RNA viruses which can cause either mild to severe febrile arthritis which may persist for months, or encephalitis which can lead to death or lifelong cognitive impairments. The non-assembly molecular role(s), functions, and protein–protein interactions of the alphavirus capsid proteins have been largely overlooked. Here we detail the use of a BioID2 biotin ligase system to identify the protein–protein interactions of the Sindbis virus capsid protein. These efforts led to the discovery of a series of novel host–pathogen interactions, including the identification of an interaction between the alphaviral capsid protein and the host IRAK1 protein. Importantly, this capsid–IRAK1 interaction is conserved across multiple alphavirus species, including arthritogenic alphaviruses SINV, Ross River virus, and Chikungunya virus; and encephalitic alphaviruses Eastern Equine Encephalitis virus, and Venezuelan Equine Encephalitis virus. The impact of the capsid–IRAK1 interaction was evaluated using a robust set of cellular model systems, leading to the realization that the alphaviral capsid protein specifically inhibits IRAK1-dependent signaling. This inhibition represents a means by which alphaviruses may evade innate immune detection and activation prior to viral gene expression. Altogether, these data identify novel capsid protein–protein interactions, establish the capsid–IRAK1 interaction as a common alphavirus host–pathogen interface, and delineate the molecular consequences of the capsid–IRAK1 interaction on IRAK1-dependent signaling.

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46

Ali, Nida Fatima, Rehan Zafar Paracha, and Muhammad Tahir. "In silico evaluation of molecular virus–virus interactions taking place between Cotton leaf curl Kokhran virus- Burewala strain and Tomato leaf curl New Delhi virus." PeerJ 9 (October 19, 2021): e12018. http://dx.doi.org/10.7717/peerj.12018.

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Background Cotton leaf curl disease (CLCuD) is a disease of cotton caused by begomoviruses, leading to a drastic loss in the annual yield of the crop. Pakistan has suffered two epidemics of this disease leading to the loss of billions in annual exports. The speculation that a third epidemic of CLCuD may result as consequence of the frequent occurrence of Tomato leaf curl New Delhi virus (ToLCNDV) and Cotton leaf curl Kokhran Virus-Burewala Strain (CLCuKoV-Bu) in CLCuD infected samples, demand that the interactions taking between the two viruses be properly evaluated. This study is designed to assess virus-virus interactions at the molecular level and determine the type of co-infection taking place. Methods Based on the amino acid sequences of the gene products of both CLCuKoV-Bu and ToLCNDV, protein structures were generated using different software, i.e., MODELLER, I-TASSER, QUARKS, LOMETS and RAPTORX. A consensus model for each protein was selected after model quality assessment using ERRAT, QMEANDisCo, PROCHECK Z-Score and Ramachandran plot analysis. The active and passive residues in the protein structures were identified using the CPORT server. Protein–Protein Docking was done using the HADDOCK webserver, and 169 Protein–Protein Interaction (PPIs) were performed between the proteins of the two viruses. The docked complexes were submitted to the PRODIGY server to identify the interacting residues between the complexes. The strongest interactions were determined based on the HADDOCK Score, Desolvation energy, Van der Waals Energy, Restraint Violation Energy, Electrostatic Energy, Buried Surface Area and Restraint Violation Energy, Binding Affinity and Dissociation constant (Kd). A total of 50 ns Molecular Dynamic simulations were performed on complexes that exhibited the strongest affinity in order to validate the stability of the complexes, and to remove any steric hindrances that may exist within the structures. Results Our results indicate significant interactions taking place between the proteins of the two viruses. Out of all the interactions, the strongest were observed between the Replication Initiation protein (Rep) of CLCuKoV-Bu with the Movement protein (MP), Nuclear Shuttle Protein (NSP) of ToLCNDV (DNA-B), while the weakest were seen between the Replication Enhancer protein (REn) of CLCuKoV-Bu with the REn protein of ToLCNDV. The residues identified to be taking a part in interaction belonged to domains having a pivotal role in the viral life cycle and pathogenicity. It maybe deduced that the two viruses exhibit antagonistic behavior towards each other, and the type of infection may be categorised as a type of Super Infection Exclusion (SIE) or homologous interference. However, further experimentation, in the form of transient expression analysis, is needed to confirm the nature of these interactions and increase our understanding of the direct interactions taking place between two viruses.

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Le Mercier, Mariethoz, Lascano-Maillard, Bonnardel, Imberty, Ricard-Blum, and Lisacek. "A Bioinformatics View of Glycan–Virus Interactions." Viruses 11, no. 4 (April 23, 2019): 374. http://dx.doi.org/10.3390/v11040374.

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Evidence of the mediation of glycan molecules in the interaction between viruses and their hosts is accumulating and is now partially reflected in several online databases. Bioinformatics provides convenient and efficient means of searching, visualizing, comparing, and sometimes predicting, interactions in numerous and diverse molecular biology applications related to the -omics fields. As viromics is gaining momentum, bioinformatics support is increasingly needed. We propose a survey of the current resources for searching, visualizing, comparing, and possibly predicting host–virus interactions that integrate the presence and role of glycans. To the best of our knowledge, we have mapped the specialized and general-purpose databases with the appropriate focus. With an illustration of their potential usage, we also discuss the strong and weak points of the current bioinformatics landscape in the context of understanding viral infection and the immune response to it.

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Rodamilans, Bernardo, Adrián Valli, and Juan Antonio García. "Molecular Plant-Plum Pox Virus Interactions." Molecular Plant-Microbe Interactions® 33, no. 1 (January 2020): 6–17. http://dx.doi.org/10.1094/mpmi-07-19-0189-fi.

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Plum pox virus, the agent that causes sharka disease, is among the most important plant viral pathogens, affecting Prunus trees across the globe. The fabric of interactions that the virus is able to establish with the plant regulates its life cycle, including RNA uncoating, translation, replication, virion assembly, and movement. In addition, plant-virus interactions are strongly conditioned by host specificities, which determine infection outcomes, including resistance. This review attempts to summarize the latest knowledge regarding Plum pox virus–host interactions, giving a comprehensive overview of their relevance for viral infection and plant survival, including the latest advances in genetic engineering of resistant species.

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Chen, Qian, and Taiyun Wei. "Cell Biology During Infection of Plant Viruses in Insect Vectors and Plant Hosts." Molecular Plant-Microbe Interactions® 33, no. 1 (January 2020): 18–25. http://dx.doi.org/10.1094/mpmi-07-19-0184-cr.

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Plant viruses typically cause severe pathogenicity in plants, even resulting in the death of plants. Many pathogenic plant viruses are transmitted in a persistent manner via insect vectors. Interestingly, unlike in the plant hosts, persistent viruses are either nonpathogenic or show limited pathogenicity in their insect vectors, while taking advantage of the cellular machinery of insect vectors for completing their life cycles. This review discusses why persistent plant viruses are nonpathogenic or have limited pathogenicity to their insect vectors while being pathogenic to plants hosts. Current advances in cell biology of virus–insect vector interactions are summarized, including virus-induced inclusion bodies, changes of insect cellular ultrastructure, and immune response of insects to the viruses, especially autophagy and apoptosis. The corresponding findings of virus-plant interactions are compared. An integrated view of the balance strategy achieved by the interaction between viral attack and the immune response of insect is presented. Finally, we outline progress gaps between virus-insect and virus-plant interactions, thus highlighting the contributions of cultured cells to the cell biology of virus-insect interactions. Furthermore, future prospects of studying the cell biology of virus-vector interactions are presented.

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DeBlasio, Stacy L., Juan D. Chavez, Mariko M. Alexander, John Ramsey, Jimmy K. Eng, Jaclyn Mahoney, Stewart M. Gray, James E. Bruce, and Michelle Cilia. "Visualization of Host-Polerovirus Interaction Topologies Using Protein Interaction Reporter Technology." Journal of Virology 90, no. 4 (December 9, 2015): 1973–87. http://dx.doi.org/10.1128/jvi.01706-15.

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ABSTRACTDemonstrating direct interactions between host and virus proteins during infection is a major goal and challenge for the field of virology. Most protein interactions are not binary or easily amenable to structural determination. Using infectious preparations of a polerovirus (Potato leafroll virus[PLRV]) and protein interaction reporter (PIR), a revolutionary technology that couples a mass spectrometric-cleavable chemical cross-linker with high-resolution mass spectrometry, we provide the first report of a host-pathogen protein interaction network that includes data-derived, topological features for every cross-linked site that was identified. We show that PLRV virions have hot spots of protein interaction and multifunctional surface topologies, revealing how these plant viruses maximize their use of binding interfaces. Modeling data, guided by cross-linking constraints, suggest asymmetric packing of the major capsid protein in the virion, which supports previous epitope mapping studies. Protein interaction topologies are conserved with other species in theLuteoviridaeand with unrelated viruses in theHerpesviridaeandAdenoviridae. Functional analysis of three PLRV-interacting host proteinsin plantausing a reverse-genetics approach revealed a complex, molecular tug-of-war between host and virus. Structural mimicry and diversifying selection—hallmarks of host-pathogen interactions—were identified within host and viral binding interfaces predicted by our models. These results illuminate the functional diversity of the PLRV-host protein interaction network and demonstrate the usefulness of PIR technology for precision mapping of functional host-pathogen protein interaction topologies.IMPORTANCEThe exterior shape of a plant virus and its interacting host and insect vector proteins determine whether a virus will be transmitted by an insect or infect a specific host. Gaining this information is difficult and requires years of experimentation. We used protein interaction reporter (PIR) technology to illustrate how viruses exploit host proteins during plant infection. PIR technology enabled our team to precisely describe the sites of functional virus-virus, virus-host, and host-host protein interactions using a mass spectrometry analysis that takes just a few hours. Applications of PIR technology in host-pathogen interactions will enable researchers studying recalcitrant pathogens, such as animal pathogens where host proteins are incorporated directly into the infectious agents, to investigate how proteins interact during infection and transmission as well as develop new tools for interdiction and therapy.

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