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dc.contributor.authorKnodel, Markus M.
dc.contributor.authorNägel, Arne
dc.contributor.authorReiter, Sebastian
dc.contributor.authorVogel, Andreas
dc.contributor.authorTargett-Adams, Paul
dc.contributor.authorMcLauchlan, John
dc.contributor.authorHerrmann, Eva
dc.contributor.authorWittum, Gabriel
dc.date.accessioned2018-01-15T06:10:41Z
dc.date.available2018-01-15T06:10:41Z
dc.date.issued2018-01-08
dc.identifier.citationKnodel M, Nägel A, Reiter S, Vogel A, Targett-Adams P, et al. (2018) Quantitative Analysis of Hepatitis C NS5A Viral Protein Dynamics on the ER Surface. Viruses 10: 28. Available: http://dx.doi.org/10.3390/v10010028.
dc.identifier.issn1999-4915
dc.identifier.doi10.3390/v10010028
dc.identifier.urihttp://hdl.handle.net/10754/626765
dc.description.abstractExploring biophysical properties of virus-encoded components and their requirement for virus replication is an exciting new area of interdisciplinary virological research. To date, spatial resolution has only rarely been analyzed in computational/biophysical descriptions of virus replication dynamics. However, it is widely acknowledged that intracellular spatial dependence is a crucial component of virus life cycles. The hepatitis C virus-encoded NS5A protein is an endoplasmatic reticulum (ER)-anchored viral protein and an essential component of the virus replication machinery. Therefore, we simulate NS5A dynamics on realistic reconstructed, curved ER surfaces by means of surface partial differential equations (sPDE) upon unstructured grids. We match the in silico NS5A diffusion constant such that the NS5A sPDE simulation data reproduce experimental NS5A fluorescence recovery after photobleaching (FRAP) time series data. This parameter estimation yields the NS5A diffusion constant. Such parameters are needed for spatial models of HCV dynamics, which we are developing in parallel but remain qualitative at this stage. Thus, our present study likely provides the first quantitative biophysical description of the movement of a viral component. Our spatio-temporal resolved ansatz paves new ways for understanding intricate spatial-defined processes central to specfic aspects of virus life cycles.
dc.description.sponsorshipWe thank Konstantinos Xylouris (G-CSC) for very fruitful discussions on the evaluation of the simulation results, Martin Rupp (G-CSC) for very friendly technical support with respect to the implementation of the solvers, Ranjita Dutta-Roy (Karolinska Institute, Stockholm, Sweden) for profound explanations of FRAP experimental setup and data analysis, Stefan Groote (University of Tartu, Estonia) for proof reading the manuscript and very helpful hints, Tobias Denninger (Heidelberg, Germany) for very stimulating discussions about spatial resolution within computational biophysics, Alfio Grillo (Politecnico di Torino, Italy) and Jürgen Vollmer (MPI Göttingen, Germany) for very stimulating discussions about the subject, and Wouter van Beerendonk (Huygens SVI, Netherlands) for his very friendly support in Huygens usage, backgrounds, and licensing. The HLRS Stuttgart is acknowledged for the supplied computing time on the Hermit and Hornet super computers [90], and Michael Lampe for very friendly technical support on the G-CSC cesari cluster. The authors acknowledge the Goethe Universität Frankfurt for general support and computational resources and the Politecnico di Torino for general support. This work has been supported in part by the “Fondazione Cassa di Risparmio di Torino” (Italy), through the “La Ricerca dei Talenti” (HR Excellence in Research) programme. The Authors wish to express their sincere thanks to the anonymous Referees for their thorough and critical reviews of our work.
dc.publisherMDPI AG
dc.relation.urlhttp://www.mdpi.com/1999-4915/10/1/28
dc.rightsThis is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectcomputational virology
dc.subjecthepatitis C virus (HCV)
dc.subjectviral dynamics
dc.subjectwithin-host viral modelling
dc.subjectparameter estimation
dc.subject3D spatio-temporal resolved mathematical models
dc.subjectrealistic geometries
dc.subject(surface) partial differential equations
dc.subjectFinite Volumes
dc.subjectmassively parallel multigrid solvers
dc.titleQuantitative Analysis of Hepatitis C NS5A Viral Protein Dynamics on the ER Surface
dc.typeArticle
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentApplied Mathematics and Computational Science Program
dc.contributor.departmentExtreme Computing Research Center
dc.identifier.journalViruses
dc.eprint.versionPublisher's Version/PDF
dc.contributor.institutionGoethe Center for Scientific Computing (G-CSC), Goethe Universität Frankfurt, Kettenhofweg 139, 60325 Frankfurt am Main, Germany
dc.contributor.institutionRuhr-Universität Bochum, High Performance Computing in the Engineering Sciences, Universitätsstrasse 150, 44801 Bochum, Germany
dc.contributor.institutionMedivir AB, Department of Biology, Huddinge 141 22, Sweden
dc.contributor.institutionMRC-University of Glasgow Centre for Virus Research, 464 Bearsden Road, Glasgow G61 1QH, UK
dc.contributor.institutionDepartment of Medicine, Institute for Biostatistics and Mathematic Modeling, Goethe Universität Frankfurt, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany
kaust.personWittum, Gabriel
refterms.dateFOA2018-06-13T21:01:43Z


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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
Except where otherwise noted, this item's license is described as This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).