Kinetic Modeling of Virus Growth in Cells
Abstract
SUMMARY: When a virus infects a host cell, it hijacks the biosynthetic capacity of the cell to produce virus progeny, a process that may take less than an hour or more than a week. The overall time required for a virus to reproduce depends collectively on the rates of multiple steps in the infection process, including initial binding of the virus particle to the surface of the cell, virus internalization and release of the viral genome within the cell, decoding of the genome to make viral proteins, replication of the genome, assembly of progeny virus particles, and release of these particles into the extracellular environment. For a large number of virus types, much has been learned about the molecular mechanisms and rates of the various steps. However, in only relatively few cases during the last 50 years has an attempt been made—using mathematical modeling—to account for how the different steps contribute to the overall timing and productivity of the infection cycle in a cell. Here we review the initial case studies, which include studies of the one-step growth behavior of viruses that infect bacteria (Qβ, T7, and M13), human immunodeficiency virus, influenza A virus, poliovirus, vesicular stomatitis virus, baculovirus, hepatitis B and C viruses, and herpes simplex virus. Further, we consider how such models enable one to explore how cellular resources are utilized and how antiviral strategies might be designed to resist escape. Finally, we highlight challenges and opportunities at the frontiers of cell-level modeling of virus infections.
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No unified mechanistic framework currently captures AdV, AAV, and LV processes within the same HEK293 host using a consistent mathematical structure that allows cross platform parameterization with minimal structural modification.
“Despite these contributions, no unified mechanistic framework currently captures AdV, AAV, and LV processes within the same HEK293 host using a consistent mathematical structure that allows cross platform parameterization with minimal structural modification [21, 22].”
From Mechanistic model for HEK293 viral vector processes and its application in a digital shadow framework (2026) · cites this paper as [22]
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Kuchemüller, K. B., Austerjost, J., Machleid, R., Roßkamp, A., Niemann, J., & McCready, C. (2026) · Bioprocess and Biosystems Engineering · doi:10.1007/s00449-026-03362-2
- Authors
- Yin, J., & Redovich, J.
- Affiliations
- Department of Chemical and Biological Engineering, Wisconsin Institute for Discovery, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Venue
- Microbiology and Molecular Biology Reviews
- Publisher
- American Society for Microbiology
- Published
- 2018-06
- Volume
- 82
- Issue
- 2
- ISSN
- 1092-2172
- 1098-5557
- Cited by
- 66
- References
- 3
- Language
- en
- Funders
- Texas-Wisconsin Modeling and Control Consortium
- Merck Research Laboratories
- HHS | National Institutes of Health (AI077296, AI071197, AI091646, AI104317, T32-GM08349, T32-HG002760)
- National Science Foundation (BES-0087939, BES-0331337, BES-9896067, EF0313214, EIA-0130874, EIA-0331337)
- Wisconsin Alumni Research Foundation
- University of Wisconsin-Madison
- DOD | United States Navy | Office of Naval Research (N00014-98-1-0226)
- HHS | NIH | U.S. National Library of Medicine (T15LM007359)
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