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Viral Infection Spreading in Cell Culture with Intracellular Regulation

Author

Listed:
  • Nikolay Bessonov

    (Institute of Problems of Mechanical Engineering, Russian Academy of Sciences, 199178 Saint Petersburg, Russia)

  • Gennady Bocharov

    (Marchuk Institute of Numerical Mathematics, Russian Academy of Sciences (INM RAS), 119333 Moscow, Russia
    Moscow Center of Fundamental and Applied Mathematics at INM RAS, 119333 Moscow, Russia
    Institute of Computer Science and Mathematical Modelling, Sechenov First Moscow State Medical University, 119991 Moscow, Russia)

  • Anastasiia Mozokhina

    (S.M. Nikolsky Mathematical Institute, Peoples’ Friendship University of Russia, 6 Miklukho-Maklaya St, 117198 Moscow, Russia)

  • Vitaly Volpert

    (S.M. Nikolsky Mathematical Institute, Peoples’ Friendship University of Russia, 6 Miklukho-Maklaya St, 117198 Moscow, Russia
    Institut Camille Jordan, UMR 5208 CNRS, University Lyon 1, 69622 Villeurbanne, France)

Abstract

Virus plaque assays are conventionally used for the assessment of viral infections, including their virulence, and vaccine efficacy. These experiments can be modeled with reaction–diffusion equations, allowing the estimation of the speed of infection spread (related to virus virulence) and viral load (related to virus infectivity). In this work, we develop a multiscale model of infection progression that combines macroscopic characterization of virus plaque growth in cell culture with a reference model of intracellular virus replication. We determine the infection spreading speed and viral load in a model for the extracellular dynamics and the kinetics of the abundance of intracellular viral genomes and proteins. In particular, the spatial infection spreading speed increases if the rate of virus entry into the target cell increases, while the viral load can either increase or decrease depending on other model parameters. The reduction in the model under a quasi-steady state assumption for some intracellular reactions allows us to derive a family of reduced models and to compare the reference model with the previous model for the concentration of uninfected cells, infected cells, and total virus concentration. Overall, the combination of different scales in reaction–diffusion models opens up new perspectives on virus plaque growth models and their applications.

Suggested Citation

  • Nikolay Bessonov & Gennady Bocharov & Anastasiia Mozokhina & Vitaly Volpert, 2023. "Viral Infection Spreading in Cell Culture with Intracellular Regulation," Mathematics, MDPI, vol. 11(6), pages 1-23, March.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:6:p:1526-:d:1103271
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    References listed on IDEAS

    as
    1. Ignacio A Rodriguez-Brenes & Andrew Hofacre & Hung Fan & Dominik Wodarz, 2017. "Complex Dynamics of Virus Spread from Low Infection Multiplicities: Implications for the Spread of Oncolytic Viruses," PLOS Computational Biology, Public Library of Science, vol. 13(1), pages 1-19, January.
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    Cited by:

    1. Anastasia Mozokhina & Latifa Ait Mahiout & Vitaly Volpert, 2023. "Modeling of Viral Infection with Inflammation," Mathematics, MDPI, vol. 11(19), pages 1-15, September.

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