Cargando…
Multiscale modeling of influenza A virus replication in cell cultures predicts infection dynamics for highly different infection conditions
Influenza A viruses (IAV) are commonly used to infect animal cell cultures for research purposes and vaccine production. Their replication is influenced strongly by the multiplicity of infection (MOI), which ranges over several orders of magnitude depending on the respective application. So far, mat...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6396949/ https://www.ncbi.nlm.nih.gov/pubmed/30779733 http://dx.doi.org/10.1371/journal.pcbi.1006819 |
_version_ | 1783399348840693760 |
---|---|
author | Rüdiger, Daniel Kupke, Sascha Young Laske, Tanja Zmora, Pawel Reichl, Udo |
author_facet | Rüdiger, Daniel Kupke, Sascha Young Laske, Tanja Zmora, Pawel Reichl, Udo |
author_sort | Rüdiger, Daniel |
collection | PubMed |
description | Influenza A viruses (IAV) are commonly used to infect animal cell cultures for research purposes and vaccine production. Their replication is influenced strongly by the multiplicity of infection (MOI), which ranges over several orders of magnitude depending on the respective application. So far, mathematical models of IAV replication have paid little attention to the impact of the MOI on infection dynamics and virus yields. To address this issue, we extended an existing model of IAV replication in adherent MDCK cells with kinetics that explicitly consider the time point of cell infection. This modification does not only enable the fitting of high MOI measurements, but also the successful prediction of viral release dynamics of low MOI experiments using the same set of parameters. Furthermore, this model allows the investigation of defective interfering particle (DIP) propagation in different MOI regimes. The key difference between high and low MOI conditions is the percentage of infectious virions among the total virus particle release. Simulation studies show that DIP interference at a high MOI is determined exclusively by the DIP content of the seed virus while, in low MOI conditions, it is predominantly controlled by the de novo generation of DIPs. Overall, the extended model provides an ideal framework for the prediction and optimization of cell culture-derived IAV manufacturing and the production of DIPs for therapeutic use. |
format | Online Article Text |
id | pubmed-6396949 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-63969492019-03-09 Multiscale modeling of influenza A virus replication in cell cultures predicts infection dynamics for highly different infection conditions Rüdiger, Daniel Kupke, Sascha Young Laske, Tanja Zmora, Pawel Reichl, Udo PLoS Comput Biol Research Article Influenza A viruses (IAV) are commonly used to infect animal cell cultures for research purposes and vaccine production. Their replication is influenced strongly by the multiplicity of infection (MOI), which ranges over several orders of magnitude depending on the respective application. So far, mathematical models of IAV replication have paid little attention to the impact of the MOI on infection dynamics and virus yields. To address this issue, we extended an existing model of IAV replication in adherent MDCK cells with kinetics that explicitly consider the time point of cell infection. This modification does not only enable the fitting of high MOI measurements, but also the successful prediction of viral release dynamics of low MOI experiments using the same set of parameters. Furthermore, this model allows the investigation of defective interfering particle (DIP) propagation in different MOI regimes. The key difference between high and low MOI conditions is the percentage of infectious virions among the total virus particle release. Simulation studies show that DIP interference at a high MOI is determined exclusively by the DIP content of the seed virus while, in low MOI conditions, it is predominantly controlled by the de novo generation of DIPs. Overall, the extended model provides an ideal framework for the prediction and optimization of cell culture-derived IAV manufacturing and the production of DIPs for therapeutic use. Public Library of Science 2019-02-19 /pmc/articles/PMC6396949/ /pubmed/30779733 http://dx.doi.org/10.1371/journal.pcbi.1006819 Text en © 2019 Rüdiger 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 (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Rüdiger, Daniel Kupke, Sascha Young Laske, Tanja Zmora, Pawel Reichl, Udo Multiscale modeling of influenza A virus replication in cell cultures predicts infection dynamics for highly different infection conditions |
title | Multiscale modeling of influenza A virus replication in cell cultures predicts infection dynamics for highly different infection conditions |
title_full | Multiscale modeling of influenza A virus replication in cell cultures predicts infection dynamics for highly different infection conditions |
title_fullStr | Multiscale modeling of influenza A virus replication in cell cultures predicts infection dynamics for highly different infection conditions |
title_full_unstemmed | Multiscale modeling of influenza A virus replication in cell cultures predicts infection dynamics for highly different infection conditions |
title_short | Multiscale modeling of influenza A virus replication in cell cultures predicts infection dynamics for highly different infection conditions |
title_sort | multiscale modeling of influenza a virus replication in cell cultures predicts infection dynamics for highly different infection conditions |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6396949/ https://www.ncbi.nlm.nih.gov/pubmed/30779733 http://dx.doi.org/10.1371/journal.pcbi.1006819 |
work_keys_str_mv | AT rudigerdaniel multiscalemodelingofinfluenzaavirusreplicationincellculturespredictsinfectiondynamicsforhighlydifferentinfectionconditions AT kupkesaschayoung multiscalemodelingofinfluenzaavirusreplicationincellculturespredictsinfectiondynamicsforhighlydifferentinfectionconditions AT lasketanja multiscalemodelingofinfluenzaavirusreplicationincellculturespredictsinfectiondynamicsforhighlydifferentinfectionconditions AT zmorapawel multiscalemodelingofinfluenzaavirusreplicationincellculturespredictsinfectiondynamicsforhighlydifferentinfectionconditions AT reichludo multiscalemodelingofinfluenzaavirusreplicationincellculturespredictsinfectiondynamicsforhighlydifferentinfectionconditions |