Multicellular spatial model of RNA virus replication and interferon responses reveals factors controlling plaque growth dynamics.

Respiratory viruses present major public health challenges, as evidenced by the 1918 Spanish Flu, the 1957 H2N2, 1968 H3N2, and 2009 H1N1 influenza pandemics, and the ongoing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. Severe RNA virus respiratory infections often correlat...

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Main Authors: Josua O Aponte-Serrano, Jordan J A Weaver, T J Sego, James A Glazier, Jason E Shoemaker
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2021-10-01
Series:PLoS Computational Biology
Online Access:https://doi.org/10.1371/journal.pcbi.1008874
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author Josua O Aponte-Serrano
Jordan J A Weaver
T J Sego
James A Glazier
Jason E Shoemaker
author_facet Josua O Aponte-Serrano
Jordan J A Weaver
T J Sego
James A Glazier
Jason E Shoemaker
author_sort Josua O Aponte-Serrano
collection DOAJ
description Respiratory viruses present major public health challenges, as evidenced by the 1918 Spanish Flu, the 1957 H2N2, 1968 H3N2, and 2009 H1N1 influenza pandemics, and the ongoing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. Severe RNA virus respiratory infections often correlate with high viral load and excessive inflammation. Understanding the dynamics of the innate immune response and its manifestations at the cell and tissue levels is vital to understanding the mechanisms of immunopathology and to developing strain-independent treatments. Here, we present a novel spatialized multicellular computational model of RNA virus infection and the type-I interferon-mediated antiviral response that it induces within lung epithelial cells. The model is built using the CompuCell3D multicellular simulation environment and is parameterized using data from influenza virus-infected cell cultures. Consistent with experimental observations, it exhibits either linear radial growth of viral plaques or arrested plaque growth depending on the local concentration of type I interferons. The model suggests that modifying the activity of signaling molecules in the JAK/STAT pathway or altering the ratio of the diffusion lengths of interferon and virus in the cell culture could lead to plaque growth arrest. The dependence of plaque growth arrest on diffusion lengths highlights the importance of developing validated spatial models of cytokine signaling and the need for in vitro measurement of these diffusion coefficients. Sensitivity analyses under conditions leading to continuous or arrested plaque growth found that plaque growth is more sensitive to variations of most parameters and more likely to have identifiable model parameters when conditions lead to plaque arrest. This result suggests that cytokine assay measurements may be most informative under conditions leading to arrested plaque growth. The model is easy to extend to include SARS-CoV-2-specific mechanisms or to use as a component in models linking epithelial cell signaling to systemic immune models.
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spelling doaj.art-665229f699cf4d378040ea345b385a8a2022-12-21T18:46:48ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582021-10-011710e100887410.1371/journal.pcbi.1008874Multicellular spatial model of RNA virus replication and interferon responses reveals factors controlling plaque growth dynamics.Josua O Aponte-SerranoJordan J A WeaverT J SegoJames A GlazierJason E ShoemakerRespiratory viruses present major public health challenges, as evidenced by the 1918 Spanish Flu, the 1957 H2N2, 1968 H3N2, and 2009 H1N1 influenza pandemics, and the ongoing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. Severe RNA virus respiratory infections often correlate with high viral load and excessive inflammation. Understanding the dynamics of the innate immune response and its manifestations at the cell and tissue levels is vital to understanding the mechanisms of immunopathology and to developing strain-independent treatments. Here, we present a novel spatialized multicellular computational model of RNA virus infection and the type-I interferon-mediated antiviral response that it induces within lung epithelial cells. The model is built using the CompuCell3D multicellular simulation environment and is parameterized using data from influenza virus-infected cell cultures. Consistent with experimental observations, it exhibits either linear radial growth of viral plaques or arrested plaque growth depending on the local concentration of type I interferons. The model suggests that modifying the activity of signaling molecules in the JAK/STAT pathway or altering the ratio of the diffusion lengths of interferon and virus in the cell culture could lead to plaque growth arrest. The dependence of plaque growth arrest on diffusion lengths highlights the importance of developing validated spatial models of cytokine signaling and the need for in vitro measurement of these diffusion coefficients. Sensitivity analyses under conditions leading to continuous or arrested plaque growth found that plaque growth is more sensitive to variations of most parameters and more likely to have identifiable model parameters when conditions lead to plaque arrest. This result suggests that cytokine assay measurements may be most informative under conditions leading to arrested plaque growth. The model is easy to extend to include SARS-CoV-2-specific mechanisms or to use as a component in models linking epithelial cell signaling to systemic immune models.https://doi.org/10.1371/journal.pcbi.1008874
spellingShingle Josua O Aponte-Serrano
Jordan J A Weaver
T J Sego
James A Glazier
Jason E Shoemaker
Multicellular spatial model of RNA virus replication and interferon responses reveals factors controlling plaque growth dynamics.
PLoS Computational Biology
title Multicellular spatial model of RNA virus replication and interferon responses reveals factors controlling plaque growth dynamics.
title_full Multicellular spatial model of RNA virus replication and interferon responses reveals factors controlling plaque growth dynamics.
title_fullStr Multicellular spatial model of RNA virus replication and interferon responses reveals factors controlling plaque growth dynamics.
title_full_unstemmed Multicellular spatial model of RNA virus replication and interferon responses reveals factors controlling plaque growth dynamics.
title_short Multicellular spatial model of RNA virus replication and interferon responses reveals factors controlling plaque growth dynamics.
title_sort multicellular spatial model of rna virus replication and interferon responses reveals factors controlling plaque growth dynamics
url https://doi.org/10.1371/journal.pcbi.1008874
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