Tissue-like in vitro models to study antiviral mechanisms of influenza defective interfering particles

Motivation

Defective interfering particles (DIPs) resemble conventional influenza A virus (IAV) particles, but contain internal deletions or point mutations in one or more of their eight viral genome segments. DIPs can only replicate in a co-infection with infectious standard virus (STV), where they inhibit replication and packaging of STV. Furthermore, DIP infection induces an antiviral state by stimulating innate immunity and are therefore considered promising candidates for antiviral therapy. In this project, we want to investigate various DIP/STV co-infection scenarios in tissue-like in vitro models representing key properties of the human pharynx, the site of initial virus infection.

Figure 1: Overview of the project: in vitro models of the pharynx will be established. For various DIP/STV co-infection scenarios, we will investigate the spatial and temporal spread of virus infection to infer the optimal dosing and timing of DIP administration. Additionally, the role of the innate immune response and its contribution to the antiviral activity will be characterized. The generated data will be used to establish a mathematical model that allows for in silico experiments, predictions and experimental hypotheses testing. Created with BioRender. — Figure 1: Overview of the project: *in vitro* models of the pharynx will be established. For various DIP/STV co-infection scenarios, we will investigate the spatial and temporal spread of virus infection to infer the optimal dosing and timing of DIP administration. Additionally, the role of the innate immune response and its contribution to the antiviral activity will be characterized. The generated data will be used to establish a mathematical model that allows for *in silico* experiments, predictions and experimental hypotheses testing. Created with BioRender.

Figure 1: Overview of the project: *in vitro* models of the pharynx will be established. For various DIP/STV co-infection scenarios, we will investigate the spatial and temporal spread of virus infection to infer the optimal dosing and timing of DIP administration. Additionally, the role of the innate immune response and its contribution to the antiviral activity will be characterized. The generated data will be used to establish a mathematical model that allows for *in silico* experiments, predictions and experimental hypotheses testing. Created with BioRender.

Aim of the project

First, we will establish a cell culture model to study the spatial and temporal DIP/STV spread for different co-infection scenarios. In addition, the optimal ratio of DIP/STV, as well as the ideal timing of administration will be determined. In a second setting, we will try to better characterize how DIP replication interferes with the provision of viral resources for STV replication and investigate details of the stimulation of the innate immune response. Thereby, we want to reveal the extent of which both contribute to the antiviral effect of DIPs. Based on the results obtained, a mathematical model will be established that will be calibrated to the experimental data obtained from the in vitro experiments. The model is then used to describe and predict the outcome of co-infection scenarios, and for setting up new hypotheses that will be validated by subsequent in vitro experiments.

Outlook

Overall, we expect our studies will help to improve our understanding of DIP/STV co-infections in tissues and to assess optimal dosing to support the initiation of safety studies and clinical trials towards the use of this new class of antivirals in humans.

References

Rüdiger, D.; Pelz, L.; Hein, M. D.; Kupke, S. Y.; Reichl, U.: Multiscale model of defective interfering particle replication for influenza A virus infection in animal cell culture. PLoS Computational Biology 17, e1009357 (2021)

MPG.PuRe

DOI

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