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Mathematical Modeling of Hepatitis C Virus Replication
At present, 170 million people are infected with Hepatitis C Virus, which is about 3 % of the world population. Currently available treatment is successful in only 50 % of treated patients. Further development of the treatment strategies requires a profound quantitative understanding of the viral lifecycle. This remains a major challenge, however, by combining the experimental and modeling approaches it has become possible to understand it quantitatively. In this thesis, we develop a mathematical model to investigate the intracellular dynamics of HCV replication. In this model, two processes, the translation of viral proteins and the replication of viral genomes are considered. This model is established by using ordinary differential equations. The established model is then calibrated by using the time course data representing the viral plus-, minus-strand RNA and the polyprotein dynamics and the steady state data reflecting the ratios among the plus-, minus-strand RNA and the non-structural proteins. Subsequently, the model is validated using the independent measurements highlighting the replication deficient and synthesis inhibited HCV RNA dynamics. Furthermore, the model is used to analyze the observed difference in HCV RNA replication in the clonal Huh-7 cell lines. We demonstrate that this difference can be explained by the differential expression of the cellular host factor which involves in the replication of viral genomes. Using the model, a role of replication vesicles with respect to viral dynamics is analyzed. A sensitivity analysis is performed on the model parameters to reveal the crucial steps in the viral replication. This analysis shows that the processes in the replication vesicles are the most crucial for HCV replication. Finally, an identifiability analysis is performed to check whether the model parameters are sufficiently estimated from the measured data.
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500 Naturwissenschaften und Mathematik
500 Natural sciences and mathematics