Uncovering Virus Replication: a Stochastic Model

The primary motivation of this work is to gain insights into viral replication inside the host cell. The organism for this study is Influenza A, which is the sixth most common cause of death in the United States (20,000 people/year). Additionally, influenza epidemics continue to be severe in terms of lives and expenses (medical costs and lost work days). We created a stochastic model of Influenza A infection through a population of MDCK cells. Our work combines a set of equations previously described (1). The base model takes into account cell replication and natural cell death, as well as viral decay due to process conditions. We then added an expression describing the virus incubation period, to account for the time during which the infected cells produce no virus. The stochastic model was originally based on (2) and the algorithm was further modified with ideas and data structures from (3). The model was written in C++ and all the data analysis was done in MatLab. The model is validated by comparing model predictions with experimental data. We observe an excellent correlation between model and experiments. In the future, we will use the model to analyze which steps have the greatest effect on virus yield.

1) Mohler, L, et al Mathematical Model of Influenza A Virus Production in Large-Scale Microcarrier Culture. Biotechnol Bioeng 2005 Apr 5, 90(1):46-58. 2) Gillespie, D. T., Exact Stochastic Simulation of Coupled Chemical Reactions. J. Phys. Chem. 1977, 81:2340-61. 3)Gibson M.A. and Burke J. Efficient Exact Stochastic Simulation of Chemical Systems with Many Species and Many Channels. J. Phys. Chem. A, 2000. 104 (9):1876 -89.