A modular framework for multiscale, multicellular, spatiotemporal modeling of acute primary viral infection and immune response in epithelial tissues and its application to drug therapy timing and effectiveness

Simulations of tissue-specific effects of primary acute viral infections like COVID-19 are essential for understanding disease outcomes and optimizing therapies. Such simulations need to support continuous updating in response to rapid advances in understanding of infection mechanisms, and parallel...

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Bibliographic Details
Published in:PLoS computational biology 2020-12, Vol.16 (12), p.e1008451-e1008451
Main Authors: Sego, T J, Aponte-Serrano, Josua O, Ferrari Gianlupi, Juliano, Heaps, Samuel R, Breithaupt, Kira, Brusch, Lutz, Crawshaw, Jessica, Osborne, James M, Quardokus, Ellen M, Plemper, Richard K, Glazier, James A
Format: Article
Language:English
Subjects:
Analysis
Antiviral Agents - therapeutic use
Biology and Life Sciences
Chemotherapy
Computational biology
Computational Biology - methods
Computer Simulation
Coronaviruses
COVID-19
COVID-19 - immunology
Disease resistance
Drug therapy
Epithelium
Epithelium - immunology
Epithelium - virology
Genomes
Hepacivirus - immunology
Hepatitis C - drug therapy
Hepatitis C - immunology
Humans
Immune response
Immune system
Infections
Innate immunity
Interferon
Internalization
Leukocytes (neutrophilic)
Macrophages
Medicine and Health Sciences
Methods
Models, Immunological
Natural killer cells
Packaging
Phagocytosis
Physiological aspects
Replication
SARS-CoV-2 - immunology
Tissues
Viral infections
Virus Diseases - drug therapy
Virus Diseases - immunology
Viruses
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Summary:Simulations of tissue-specific effects of primary acute viral infections like COVID-19 are essential for understanding disease outcomes and optimizing therapies. Such simulations need to support continuous updating in response to rapid advances in understanding of infection mechanisms, and parallel development of components by multiple groups. We present an open-source platform for multiscale spatiotemporal simulation of an epithelial tissue, viral infection, cellular immune response and tissue damage, specifically designed to be modular and extensible to support continuous updating and parallel development. The base simulation of a simplified patch of epithelial tissue and immune response exhibits distinct patterns of infection dynamics from widespread infection, to recurrence, to clearance. Slower viral internalization and faster immune-cell recruitment slow infection and promote containment. Because antiviral drugs can have side effects and show reduced clinical effectiveness when given later during infection, we studied the effects on progression of treatment potency and time-of-first treatment after infection. In simulations, even a low potency therapy with a drug which reduces the replication rate of viral RNA greatly decreases the total tissue damage and virus burden when given near the beginning of infection. Many combinations of dosage and treatment time lead to stochastic outcomes, with some simulation replicas showing clearance or control (treatment success), while others show rapid infection of all epithelial cells (treatment failure). Thus, while a high potency therapy usually is less effective when given later, treatments at late times are occasionally effective. We illustrate how to extend the platform to model specific virus types (e.g., hepatitis C) and add additional cellular mechanisms (tissue recovery and variable cell susceptibility to infection), using our software modules and publicly-available software repository.
ISSN:1553-7358
1553-734X
1553-7358
DOI:10.1371/journal.pcbi.1008451