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Elucidating the dynamics of influenza virus replication by mathematical modeling

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Heldt,  F. S.
Bioprocess Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

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Frensing,  Timo
Bioprocess Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

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Reichl,  Udo
Otto-von-Guericke-Universität Magdeburg;
Bioprocess Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

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Citation

Heldt, F. S., Frensing, T., & Reichl, U. (2012). Elucidating the dynamics of influenza virus replication by mathematical modeling. Poster presented at 22nd Annual Meeting of the Society for Virology, Essen, Germany.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0013-892B-0
Abstract
Influenza viruses transcribe and replicate their negative-sense RNA genome inside the nucleus of host cells via three viral RNA species. These RNAs are regulated in a quantitative and temporal manner such that each species shows distinct dynamics during infection. The molecular mechanisms behind this regulation have received much attention in the past. However, so far the wealth of available data could not be integrated into a consistent description of the viral life cycle. We developed a mathematical model of influenza virus infection on the single cell level to gain a quantitative understanding of virus replication. It encompasses key steps from virus entry to the release of progeny virions and focuses in particular on the regulation of viral RNA synthesis. We find that two control mechanisms are essential and sufficient for the model to capture a variety of published experimental data: (I) the early control of virus replication by a recently proposed mechanism in which viral proteins stabilize replicative intermediates (cRNA); (II) the nuclear export of genome copies (vRNA) at later stages which may directly cause the previously described shutdown of positive-strand RNA synthesis. Simulations also suggest that the transport of viral precursors or budding may limit virion release as viral proteins and genomes accumulate in the cytoplasm toward the end of infection. Thus, modeling provides a valuable tool to gain a systems-level understanding of influenza virus replication.