Quantitative Analysis of Hepatitis C NS5A Viral Protein Dynamics on the ER Surface
1
Goethe Center for Scientific Computing (G-CSC), Goethe Universität Frankfurt, Kettenhofweg 139, 60325 Frankfurt am Main, Germany
2
Ruhr-Universität Bochum, High Performance Computing in the Engineering Sciences, Universitätsstrasse 150, 44801 Bochum, Germany
3
Medivir AB, Department of Biology, Huddinge 141 22, Sweden
4
MRC-University of Glasgow Centre for Virus Research, 464 Bearsden Road, Glasgow G61 1QH, UK
5
Department of Medicine, Institute for Biostatistics and Mathematic Modeling, Goethe Universität Frankfurt, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany
6
Applied Mathematics and Computational Science, Computer, Electrical and Mathematical Science and Engineering Division, King Abdullah University of Science and Technology, KAUST, Thuwal 23955, Saudi Arabia
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Viruses 2018, 10(1), 28; https://doi.org/10.3390/v10010028
Received: 8 November 2017 / Revised: 2 January 2018 / Accepted: 4 January 2018 / Published: 8 January 2018
(This article belongs to the Special Issue Mathematical Modeling of Viral Infections)
Exploring 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.
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Keywords:
computational virology; hepatitis C virus (HCV); viral dynamics; within-host viral modelling; parameter estimation; 3D spatio-temporal resolved mathematical models; realistic geometries; (surface) partial differential equations; Finite Volumes; massively parallel multigrid solvers
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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
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MDPI and ACS Style
Knodel, M.M.; Nägel, A.; Reiter, S.; Vogel, A.; Targett-Adams, P.; McLauchlan, J.; Herrmann, E.; Wittum, G. Quantitative Analysis of Hepatitis C NS5A Viral Protein Dynamics on the ER Surface. Viruses 2018, 10, 28. https://doi.org/10.3390/v10010028
AMA Style
Knodel MM, Nägel A, Reiter S, Vogel A, Targett-Adams P, McLauchlan J, Herrmann E, Wittum G. Quantitative Analysis of Hepatitis C NS5A Viral Protein Dynamics on the ER Surface. Viruses. 2018; 10(1):28. https://doi.org/10.3390/v10010028
Chicago/Turabian StyleKnodel, Markus M.; Nägel, Arne; Reiter, Sebastian; Vogel, Andreas; Targett-Adams, Paul; McLauchlan, John; Herrmann, Eva; Wittum, Gabriel. 2018. "Quantitative Analysis of Hepatitis C NS5A Viral Protein Dynamics on the ER Surface" Viruses 10, no. 1: 28. https://doi.org/10.3390/v10010028
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