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Advanced Hepatitis C Virus Replication PDE Models within a Realistic Intracellular Geometric Environment

Author

Listed:
  • Markus M. Knodel

    (Department of Mathematics, Chair of Applied Mathematics 1, Friedrich-Alexander-Universität Erlangen-Nürnberg, Cauerstr. 11, 91058 Erlangen, Germany
    Affiliation 5 was affiliation of M.M.K until March 2018. The major part of this study was performed at the G-CSC.)

  • Paul Targett-Adams

    (Medivir AB, Department of Biology, 141 22 Huddinge, Sweden)

  • Alfio Grillo

    (Dipartimento di Scienze Matematiche (DISMA) “G.L. Lagrange”, Politecnico di Torino, Corso Duca degli Abruzzi, 24, 10129 Torino (TO), Italy)

  • Eva Herrmann

    (Department of Medicine, Institute for Biostatistics and Mathematic Modeling, Goethe Universität Frankfurt, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany
    These authors contributed equally to this work.)

  • Gabriel Wittum

    (Goethe Center for Scientific Computing (G-CSC), Goethe Universität Frankfurt, Kettenhofweg 139, 60325 Frankfurt am Main, Germany
    Applied Mathematics and Computational Science, King Abdullah University of Science and Technology (KAUST), 23955-6900 Thuwal, Saudi Arabia
    These authors contributed equally to this work.)

Abstract

The hepatitis C virus (HCV) RNA replication cycle is a dynamic intracellular process occurring in three-dimensional space (3D), which is difficult both to capture experimentally and to visualize conceptually. HCV-generated replication factories are housed within virus-induced intracellular structures termed membranous webs (MW), which are derived from the Endoplasmatic Reticulum (ER). Recently, we published 3D spatiotemporal resolved diffusion–reaction models of the HCV RNA replication cycle by means of surface partial differential equation (sPDE) descriptions. We distinguished between the basic components of the HCV RNA replication cycle, namely HCV RNA, non-structural viral proteins (NSPs), and a host factor. In particular, we evaluated the sPDE models upon realistic reconstructed intracellular compartments (ER/MW). In this paper, we propose a significant extension of the model based upon two additional parameters: different aggregate states of HCV RNA and NSPs, and population dynamics inspired diffusion and reaction coefficients instead of multilinear ones. The combination of both aspects enables realistic modeling of viral replication at all scales. Specifically, we describe a replication complex state consisting of HCV RNA together with a defined amount of NSPs. As a result of the combination of spatial resolution and different aggregate states, the new model mimics a cis requirement for HCV RNA replication. We used heuristic parameters for our simulations, which were run only on a subsection of the ER. Nevertheless, this was sufficient to allow the fitting of core aspects of virus reproduction, at least qualitatively. Our findings should help stimulate new model approaches and experimental directions for virology.

Suggested Citation

  • Markus M. Knodel & Paul Targett-Adams & Alfio Grillo & Eva Herrmann & Gabriel Wittum, 2019. "Advanced Hepatitis C Virus Replication PDE Models within a Realistic Intracellular Geometric Environment," IJERPH, MDPI, vol. 16(3), pages 1-53, February.
  • Handle: RePEc:gam:jijerp:v:16:y:2019:i:3:p:513-:d:205076
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    References listed on IDEAS

    as
    1. Libin Rong & Jeremie Guedj & Harel Dahari & Daniel J Coffield Jr & Micha Levi & Patrick Smith & Alan S Perelson, 2013. "Analysis of Hepatitis C Virus Decline during Treatment with the Protease Inhibitor Danoprevir Using a Multiscale Model," PLOS Computational Biology, Public Library of Science, vol. 9(3), pages 1-12, March.
    2. Timothy L. Tellinghuisen & Joseph Marcotrigiano & Charles M. Rice, 2005. "Structure of the zinc-binding domain of an essential component of the hepatitis C virus replicase," Nature, Nature, vol. 435(7040), pages 374-379, May.
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    Cited by:

    1. Antonio López-Quílez, 2019. "Spatio-Temporal Analysis of Infectious Diseases," IJERPH, MDPI, vol. 16(4), pages 1-2, February.

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