Stochastic model of vesicular stomatitis virus replication reveals mutational effects on virion production
We present the first complete stochastic model of vesicular stomatitis virus (VSV) intracellular replication. Previous models developed to capture VSV's intracellular replication have either been ODE-based or have not represented the complete replicative cycle, limiting our ability to understan...
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description | We present the first complete stochastic model of vesicular stomatitis virus (VSV) intracellular replication. Previous models developed to capture VSV's intracellular replication have either been ODE-based or have not represented the complete replicative cycle, limiting our ability to understand the impact of the stochastic nature of early cellular infections on virion production between cells and how these dynamics change in response to mutations. Our model accurately predicts changes in mean virion production in gene-shuffled VSV variants and can capture the distribution of the number of viruses produced. This model has allowed us to enhance our understanding of intercellular variability in virion production, which appears to be influenced by the duration of the early phase of infection, and variation between variants, arising from balancing the time the genome spends in the active state, the speed of incorporating new genomes into virions, and the production of viral components. Being a stochastic model, we can also assess other effects of mutations beyond just the mean number of virions produced, including the probability of aborted infections and the standard deviation of the number of virions produced. Our model provides a biologically interpretable framework for studying the stochastic nature of VSV replication, shedding light on the mechanisms underlying variation in virion production. In the future, this model could enable the design of more complex viral phenotypes when attenuating VSV, moving beyond solely considering the mean number of virions produced. |
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Previous models developed to capture VSV's intracellular replication have either been ODE-based or have not represented the complete replicative cycle, limiting our ability to understand the impact of the stochastic nature of early cellular infections on virion production between cells and how these dynamics change in response to mutations. Our model accurately predicts changes in mean virion production in gene-shuffled VSV variants and can capture the distribution of the number of viruses produced. This model has allowed us to enhance our understanding of intercellular variability in virion production, which appears to be influenced by the duration of the early phase of infection, and variation between variants, arising from balancing the time the genome spends in the active state, the speed of incorporating new genomes into virions, and the production of viral components. Being a stochastic model, we can also assess other effects of mutations beyond just the mean number of virions produced, including the probability of aborted infections and the standard deviation of the number of virions produced. Our model provides a biologically interpretable framework for studying the stochastic nature of VSV replication, shedding light on the mechanisms underlying variation in virion production. In the future, this model could enable the design of more complex viral phenotypes when attenuating VSV, moving beyond solely considering the mean number of virions produced.</description><identifier>ISSN: 1553-7358</identifier><identifier>ISSN: 1553-734X</identifier><identifier>EISSN: 1553-7358</identifier><identifier>DOI: 10.1371/journal.pcbi.1011373</identifier><identifier>PMID: 38324583</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Algorithms ; Biology and Life Sciences ; Genes ; Genomes ; Infections ; Intracellular ; Medicine and Health Sciences ; Mutation ; Ordinary differential equations ; Parameter estimation ; Phenotypes ; Physical Sciences ; Proteins ; Replication ; Respiratory syncytial virus ; Simulation ; Stochastic models ; Stochasticity ; Stomatitis ; Virions ; Viruses</subject><ispartof>PLoS computational biology, 2024-02, Vol.20 (2), p.e1011373-e1011373</ispartof><rights>Copyright: © 2024 King et al. 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.</rights><rights>2024 King et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2024 King et al 2024 King et al</rights><rights>2024 King et al. 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Previous models developed to capture VSV's intracellular replication have either been ODE-based or have not represented the complete replicative cycle, limiting our ability to understand the impact of the stochastic nature of early cellular infections on virion production between cells and how these dynamics change in response to mutations. Our model accurately predicts changes in mean virion production in gene-shuffled VSV variants and can capture the distribution of the number of viruses produced. This model has allowed us to enhance our understanding of intercellular variability in virion production, which appears to be influenced by the duration of the early phase of infection, and variation between variants, arising from balancing the time the genome spends in the active state, the speed of incorporating new genomes into virions, and the production of viral components. Being a stochastic model, we can also assess other effects of mutations beyond just the mean number of virions produced, including the probability of aborted infections and the standard deviation of the number of virions produced. Our model provides a biologically interpretable framework for studying the stochastic nature of VSV replication, shedding light on the mechanisms underlying variation in virion production. 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Biol</addtitle><date>2024-02-01</date><risdate>2024</risdate><volume>20</volume><issue>2</issue><spage>e1011373</spage><epage>e1011373</epage><pages>e1011373-e1011373</pages><issn>1553-7358</issn><issn>1553-734X</issn><eissn>1553-7358</eissn><abstract>We present the first complete stochastic model of vesicular stomatitis virus (VSV) intracellular replication. 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Being a stochastic model, we can also assess other effects of mutations beyond just the mean number of virions produced, including the probability of aborted infections and the standard deviation of the number of virions produced. Our model provides a biologically interpretable framework for studying the stochastic nature of VSV replication, shedding light on the mechanisms underlying variation in virion production. In the future, this model could enable the design of more complex viral phenotypes when attenuating VSV, moving beyond solely considering the mean number of virions produced.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>38324583</pmid><doi>10.1371/journal.pcbi.1011373</doi><orcidid>https://orcid.org/0000-0001-5863-9876</orcidid><orcidid>https://orcid.org/0000-0001-7649-6127</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Biology and Life Sciences Genes Genomes Infections Intracellular Medicine and Health Sciences Mutation Ordinary differential equations Parameter estimation Phenotypes Physical Sciences Proteins Replication Respiratory syncytial virus Simulation Stochastic models Stochasticity Stomatitis Virions Viruses |
title | Stochastic model of vesicular stomatitis virus replication reveals mutational effects on virion production |
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