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      Replication Vesicles are Load- and Choke-Points in the Hepatitis C Virus Lifecycle

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          Abstract

          Hepatitis C virus (HCV) infection develops into chronicity in 80% of all patients, characterized by persistent low-level replication. To understand how the virus establishes its tightly controlled intracellular RNA replication cycle, we developed the first detailed mathematical model of the initial dynamic phase of the intracellular HCV RNA replication. We therefore quantitatively measured viral RNA and protein translation upon synchronous delivery of viral genomes to host cells, and thoroughly validated the model using additional, independent experiments. Model analysis was used to predict the efficacy of different classes of inhibitors and identified sensitive substeps of replication that could be targeted by current and future therapeutics. A protective replication compartment proved to be essential for sustained RNA replication, balancing translation versus replication and thus effectively limiting RNA amplification. The model predicts that host factors involved in the formation of this compartment determine cellular permissiveness to HCV replication. In gene expression profiling, we identified several key processes potentially determining cellular HCV replication efficiency.

          Author Summary

          Hepatitis C is a severe disease and a prime cause for liver transplantation. Up to 3% of the world's population are chronically infected with its causative agent, the Hepatitis C virus (HCV). This capacity to establish long (decades) lasting persistent infection sets HCV apart from other plus-strand RNA viruses typically causing acute, self-limiting infections. A prerequisite for its capacity to persist is HCV's complex and tightly regulated intracellular replication strategy. In this study, we therefore wanted to develop a comprehensive understanding of the molecular processes governing HCV RNA replication in order to pinpoint the most vulnerable substeps in the viral life cycle. For that purpose, we used a combination of biological experiments and mathematical modeling. Using the model to study HCV's replication strategy, we recognized diverse but crucial roles for the membraneous replication compartment of HCV in regulating RNA amplification. We further predict the existence of an essential limiting host factor (or function) required for establishing active RNA replication and thereby determining cellular permissiveness for HCV. Our model also proved valuable to understand and predict the effects of pharmacological inhibitors of HCV and might be a solid basis for the development of similar models for other plus-strand RNA viruses.

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          Most cited references76

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          A methodology for performing global uncertainty and sensitivity analysis in systems biology.

          Accuracy of results from mathematical and computer models of biological systems is often complicated by the presence of uncertainties in experimental data that are used to estimate parameter values. Current mathematical modeling approaches typically use either single-parameter or local sensitivity analyses. However, these methods do not accurately assess uncertainty and sensitivity in the system as, by default, they hold all other parameters fixed at baseline values. Using techniques described within we demonstrate how a multi-dimensional parameter space can be studied globally so all uncertainties can be identified. Further, uncertainty and sensitivity analysis techniques can help to identify and ultimately control uncertainties. In this work we develop methods for applying existing analytical tools to perform analyses on a variety of mathematical and computer models. We compare two specific types of global sensitivity analysis indexes that have proven to be among the most robust and efficient. Through familiar and new examples of mathematical and computer models, we provide a complete methodology for performing these analyses, in both deterministic and stochastic settings, and propose novel techniques to handle problems encountered during these types of analyses.
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            Interferons and viruses: an interplay between induction, signalling, antiviral responses and virus countermeasures.

            The interferon (IFN) system is an extremely powerful antiviral response that is capable of controlling most, if not all, virus infections in the absence of adaptive immunity. However, viruses can still replicate and cause disease in vivo, because they have some strategy for at least partially circumventing the IFN response. We reviewed this topic in 2000 [Goodbourn, S., Didcock, L. & Randall, R. E. (2000). J Gen Virol 81, 2341-2364] but, since then, a great deal has been discovered about the molecular mechanisms of the IFN response and how different viruses circumvent it. This information is of fundamental interest, but may also have practical application in the design and manufacture of attenuated virus vaccines and the development of novel antiviral drugs. In the first part of this review, we describe how viruses activate the IFN system, how IFNs induce transcription of their target genes and the mechanism of action of IFN-induced proteins with antiviral action. In the second part, we describe how viruses circumvent the IFN response. Here, we reflect upon possible consequences for both the virus and host of the different strategies that viruses have evolved and discuss whether certain viruses have exploited the IFN response to modulate their life cycle (e.g. to establish and maintain persistent/latent infections), whether perturbation of the IFN response by persistent infections can lead to chronic disease, and the importance of the IFN system as a species barrier to virus infections. Lastly, we briefly describe applied aspects that arise from an increase in our knowledge in this area, including vaccine design and manufacture, the development of novel antiviral drugs and the use of IFN-sensitive oncolytic viruses in the treatment of cancer.
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              Composition and Three-Dimensional Architecture of the Dengue Virus Replication and Assembly Sites

              Summary Positive-strand RNA viruses are known to rearrange cellular membranes to facilitate viral genome replication. The biogenesis and three-dimensional organization of these membranes and the link between replication and virus assembly sites is not fully clear. Using electron microscopy, we find Dengue virus (DENV)-induced vesicles, convoluted membranes, and virus particles to be endoplasmic reticulum (ER)-derived, and we detect double-stranded RNA, a presumed marker of RNA replication, inside virus-induced vesicles. Electron tomography (ET) shows DENV-induced membrane structures to be part of one ER-derived network. Furthermore, ET reveals vesicle pores that could enable release of newly synthesized viral RNA and reveals budding of DENV particles on ER membranes directly apposed to vesicle pores. Thus, DENV modifies ER membrane structure to promote replication and efficient encapsidation of the genome into progeny virus. This architecture of DENV replication and assembly sites could explain the coordination of distinct steps of the flavivirus replication cycle.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Pathog
                PLoS Pathog
                plos
                plospath
                PLoS Pathogens
                Public Library of Science (San Francisco, USA )
                1553-7366
                1553-7374
                August 2013
                August 2013
                22 August 2013
                : 9
                : 8
                : e1003561
                Affiliations
                [1 ]Heidelberg University, Medical Faculty, Department of Infectious Diseases, Molecular Virology, Heidelberg, Germany
                [2 ]Technische Universität Dresden, Institute for Medical Informatics and Biometry, Dresden, Germany
                [3 ]Heidelberg University, ViroQuant Research Group Modeling, BioQuant BQ26, Heidelberg, Germany
                [4 ]Heidelberg University, Interdisciplinary Center for Scientific Computing (IWR), Simulation and Optimization Group, Heidelberg, Germany
                [5 ]University Hospital of Essen, Department of Gastroenterology and Hepatology, Essen, Germany
                University of Texas at Austin, United States of America
                Author notes

                The authors have declared that no competing interests exist.

                Conceived and designed the experiments: MB LK. Performed the experiments: MB CMH MT VL RB. Analyzed the data: NS DC MS SML JPS MB LK. Wrote the paper: NS MB VL LK. Developed the models: NS MB LK. Performed multiple shooting optimization and analysis: SML JPS.

                [¤]

                Current address: Department of Obstetrics and Gynaecology, University of Cambridge Clinical School, The Rosie Hospital, Cambridge, United Kingdom.

                Article
                PPATHOGENS-D-13-00009
                10.1371/journal.ppat.1003561
                3749965
                23990783
                d4423c64-a6b6-4add-8dc1-68774c67a522
                Copyright @ 2013

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 21 December 2012
                : 2 July 2013
                Page count
                Pages: 21
                Funding
                The authors acknowledge funding from the German Ministry for Education and Research (BMBF), grant 0313923 (ForSys/ViroQuant), the European Union's Seventh Framework Program (FP7/2007–2013), grant 267429 (SysPatho), and the Helmholtz Alliance on Systems Biology (SBCancer). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology
                Computational Biology
                Systems Biology
                Theoretical Biology
                Medicine
                Infectious Diseases
                Viral Diseases
                Hepatitis
                Hepatitis C

                Infectious disease & Microbiology
                Infectious disease & Microbiology

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