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Intracellular Stochastic Modelling of Influenza A Virus and DIP Replication
- Publication Year :
- 2018
-
Abstract
- Defective interfering particles (DIPs) are mutated versions of viruses that are characterized by carrying internal deletions in their genome. These deletions are introduced randomly during virus replication and the truncated genomes interfere with the propagation of their standard virus (STV) leading to reduced infectious virus titers. Therefore, DIPs were recently proposed to be used for antiviral therapy which increased the demand for a reliable production process and a better understanding of the interference mechanism. The infection dynamics were analysed by a deterministic modelling approach, however, the impact of stochastic effects introduced by cell-to-cell variability, different coinfection scenarios and an independent genome segment replication remain largely elusive. Hence, we developed a stochastic model of influenza A virus and DIP replication which considers the influence of these random effects on STV and DIP release. We found that the viral nucleoprotein (NP), which is essential for encapsidation of the naked viral RNA (vRNA), is strongly affected by fluctuations and three distinct sub-populations emerged in our model. Furthermore, simulations performed with one DIP and one STV infecting the cell resulted in mostly non-productive simulations, mainly caused by failures during the endocytosis of particles and by the random degradation of vRNAs. Moreover, the optimal DIP production was achieved when STV enters nucleus first and the DIP entry is delayed between 1.5 and 3 hours. Lastly, we demonstrate that the implementation of a two-step packaging process, which separates the formation of genome complexes and the assembly of all required proteins for release, is crucial to achieve a substantial DIP advantage over STV production. Overall, our simulations suggest that a combination of various random effects influences the replication of STVs and DIPs inducing a broad distribution of progeny particle release. The stochastic model developed in this thesis provides an ideal basis for the analysis of these effects and their impact on DIP interference and production.
Details
- Language :
- English
- Database :
- OpenAIRE
- Accession number :
- edsair.od......1437..a5f82ca7739c3b644044926124de3790