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Multiscale Modeling of Influenza A Virus Infection Supports the Development of Direct-Acting Antivirals

Influenza A viruses are respiratory pathogens that cause seasonal epidemics with up to 500,000 deaths each year. Yet there are currently only two classes of antivirals licensed for treatment and drug-resistant strains are on the rise. A major challenge for the discovery of new anti-influenza agents...

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Autores principales: Heldt, Frank S., Frensing, Timo, Pflugmacher, Antje, Gröpler, Robin, Peschel, Britta, Reichl, Udo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3836700/
https://www.ncbi.nlm.nih.gov/pubmed/24278009
http://dx.doi.org/10.1371/journal.pcbi.1003372
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author Heldt, Frank S.
Frensing, Timo
Pflugmacher, Antje
Gröpler, Robin
Peschel, Britta
Reichl, Udo
author_facet Heldt, Frank S.
Frensing, Timo
Pflugmacher, Antje
Gröpler, Robin
Peschel, Britta
Reichl, Udo
author_sort Heldt, Frank S.
collection PubMed
description Influenza A viruses are respiratory pathogens that cause seasonal epidemics with up to 500,000 deaths each year. Yet there are currently only two classes of antivirals licensed for treatment and drug-resistant strains are on the rise. A major challenge for the discovery of new anti-influenza agents is the identification of drug targets that efficiently interfere with viral replication. To support this step, we developed a multiscale model of influenza A virus infection which comprises both the intracellular level where the virus synthesizes its proteins, replicates its genome, and assembles new virions and the extracellular level where it spreads to new host cells. This integrated modeling approach recapitulates a wide range of experimental data across both scales including the time course of all three viral RNA species inside an infected cell and the infection dynamics in a cell population. It also allowed us to systematically study how interfering with specific steps of the viral life cycle affects virus production. We find that inhibitors of viral transcription, replication, protein synthesis, nuclear export, and assembly/release are most effective in decreasing virus titers whereas targeting virus entry primarily delays infection. In addition, our results suggest that for some antivirals therapy success strongly depends on the lifespan of infected cells and, thus, on the dynamics of virus-induced apoptosis or the host's immune response. Hence, the proposed model provides a systems-level understanding of influenza A virus infection and therapy as well as an ideal platform to include further levels of complexity toward a comprehensive description of infectious diseases.
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spelling pubmed-38367002013-11-25 Multiscale Modeling of Influenza A Virus Infection Supports the Development of Direct-Acting Antivirals Heldt, Frank S. Frensing, Timo Pflugmacher, Antje Gröpler, Robin Peschel, Britta Reichl, Udo PLoS Comput Biol Research Article Influenza A viruses are respiratory pathogens that cause seasonal epidemics with up to 500,000 deaths each year. Yet there are currently only two classes of antivirals licensed for treatment and drug-resistant strains are on the rise. A major challenge for the discovery of new anti-influenza agents is the identification of drug targets that efficiently interfere with viral replication. To support this step, we developed a multiscale model of influenza A virus infection which comprises both the intracellular level where the virus synthesizes its proteins, replicates its genome, and assembles new virions and the extracellular level where it spreads to new host cells. This integrated modeling approach recapitulates a wide range of experimental data across both scales including the time course of all three viral RNA species inside an infected cell and the infection dynamics in a cell population. It also allowed us to systematically study how interfering with specific steps of the viral life cycle affects virus production. We find that inhibitors of viral transcription, replication, protein synthesis, nuclear export, and assembly/release are most effective in decreasing virus titers whereas targeting virus entry primarily delays infection. In addition, our results suggest that for some antivirals therapy success strongly depends on the lifespan of infected cells and, thus, on the dynamics of virus-induced apoptosis or the host's immune response. Hence, the proposed model provides a systems-level understanding of influenza A virus infection and therapy as well as an ideal platform to include further levels of complexity toward a comprehensive description of infectious diseases. Public Library of Science 2013-11-21 /pmc/articles/PMC3836700/ /pubmed/24278009 http://dx.doi.org/10.1371/journal.pcbi.1003372 Text en © 2013 Heldt et al http://creativecommons.org/licenses/by/4.0/ 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 properly credited.
spellingShingle Research Article
Heldt, Frank S.
Frensing, Timo
Pflugmacher, Antje
Gröpler, Robin
Peschel, Britta
Reichl, Udo
Multiscale Modeling of Influenza A Virus Infection Supports the Development of Direct-Acting Antivirals
title Multiscale Modeling of Influenza A Virus Infection Supports the Development of Direct-Acting Antivirals
title_full Multiscale Modeling of Influenza A Virus Infection Supports the Development of Direct-Acting Antivirals
title_fullStr Multiscale Modeling of Influenza A Virus Infection Supports the Development of Direct-Acting Antivirals
title_full_unstemmed Multiscale Modeling of Influenza A Virus Infection Supports the Development of Direct-Acting Antivirals
title_short Multiscale Modeling of Influenza A Virus Infection Supports the Development of Direct-Acting Antivirals
title_sort multiscale modeling of influenza a virus infection supports the development of direct-acting antivirals
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3836700/
https://www.ncbi.nlm.nih.gov/pubmed/24278009
http://dx.doi.org/10.1371/journal.pcbi.1003372
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