Investigating RNA-RNA interactions through computational and biophysical analysis

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dc.contributor.authorMrozowich, Tyler
dc.contributor.authorPark, Sean M.
dc.contributor.authorWaldl, Maria
dc.contributor.authorHenrickson, Amy
dc.contributor.authorTersteeg, Scott
dc.contributor.authorNelson, Corey R.
dc.contributor.authorDe Klerk, Anneke
dc.contributor.authorDemeler, Borries
dc.contributor.authorHofacker, Ivo L.
dc.contributor.authorWolfinger, MIchael T.
dc.contributor.authorPatel, Trushar R.
dc.date.accessioned2024-07-11T17:56:24Z
dc.date.available2024-07-11T17:56:24Z
dc.date.issued2023
dc.descriptionOpen access article. Creative Commons Attribution-NonCommercial 4.0 International license (CC BY-NC 4.0) applies
dc.description.abstractNumerous viruses utilize essential long-range RNA–RNA genome interactions, specifically flaviviruses. Using Japanese encephalitis virus (JEV) as a model system, we computationally predicted and then biophysically validated and characterized its long-range RNA–RNA genomic interaction. Using multiple RNA computation assessment programs, we determine the primary RNA–RNA interacting site among JEV isolates and numerous related viruses. Following in vitro transcription of RNA, we provide, for the first time, characterization of an RNA–RNA interaction using size-exclusion chromatography coupled with multi-angle light scattering and analytical ultracentrifugation. Next, we demonstrate that the 5′ and 3′ terminal regions of JEV interact with nM affinity using microscale thermophoresis, and this affinity is significantly reduced when the conserved cyclization sequence is not present. Furthermore, we perform computational kinetic analyses validating the cyclization sequence as the primary driver of this RNA–RNA interaction. Finally, we examined the 3D structure of the interaction using small-angle X-ray scattering, revealing a flexible yet stable interaction. This pathway can be adapted and utilized to study various viral and human long-non-coding RNA–RNA interactions and determine their binding affinities, a critical pharmacological property of designing potential therapeutics.
dc.description.peer-reviewYes
dc.identifier.citationMrozowich, T., Park, S. M., Waldl, M., Henrickson, A., Tersteeg, S., Nelson, C. R., De Klerk, A., Demeler, B., Hofacker, I. L., Wolfinger, M. T., & Patel, T. R. (2023). Investigating RNA-RNA interactions through computational and biophysical analysis. Nucleic Acids Research, 51(9), 4588-4601.https://doi.org/10.1093/nar/gkad223
dc.identifier.urihttps://hdl.handle.net/10133/6812
dc.language.isoen
dc.publisherOxford University Press
dc.publisher.departmentDepartment of Chemistry and Biochemistry
dc.publisher.facultyArts and Science
dc.publisher.institutionUniversity of Lethbridge
dc.publisher.institutionUniversity of Vienna
dc.publisher.institutionUniversity of Montana
dc.publisher.institutionRNA Forecast e.U.
dc.publisher.institutionUniversity of Alberta
dc.publisher.institutionUniversity of Calgary
dc.publisher.urlhttps://doi.org/10.1093/nar/gkad223
dc.subjectRNA-RNA genome interactions
dc.subjectJapanese encephalitis virus
dc.subjectLight scattering
dc.subjectAnalytical ultracentrifugation
dc.subjectNon-coding RNA
dc.subjectInteraction analysis
dc.subject.lcshRNA
dc.subject.lcshJapanese B encephalitis
dc.subject.lcshLight--Scattering
dc.titleInvestigating RNA-RNA interactions through computational and biophysical analysis
dc.typeArticle
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