Mathematical models of influenza A virus infection : multiplicity of infection and its impact on co-infection and virus production

Abstract

Influenza A viruses (IAV) are pathogens that infect up to 20% of the human population in seasonal epidemics inducing a contagious respiratory disease, which can lead to more than half a million deaths each year. Besides their annual impact on public health and the economy, the outbreak of major pandemics like the “Spanish flu” caused by emerging virus strains may threaten millions of lives. For the development and improvement of prevention and treatment strategies for IAV infections, it is critical to understand the exact mechanisms during virus infection and spreading on the cellular, human and global level. In this thesis, we aim to establish mathematical models of IAV infection that can describe and predict virus replication and spreading dynamics in a wide range of infection conditions relevant for vaccine production. In particular, we focus on the impact of the number of infecting virus particles per cell, i.e., the multiplicity of infection (MOI), and the impact of defective interfering particles (DIPs) on the infection dynamics. These two factors strongly influence virus yields during cell culture-based vaccine production. In addition, DIPs show great promise for antiviral application. In the first part of this thesis, we develop a mathematical multiscale model of IAV infection in animal cell culture that closely captures replication and propagation dynamics on the intracellular and cell population level for high MOI infections. Using the same model parameters, the model was able to reproduce infectious and total virus titers in low MOI conditions. The key difference between high and low MOI conditions was the percentage of infectious virions among the total virus particles released. Furthermore, we find that the time until cells are detected as apoptotic after IAV infection is normally distributed, which can be described closely using a logistic function for the rate of apoptosis. Overall, the multiscale model of IAV infection provides an ideal framework for the prediction and optimization of IAV manufacturing in animal cell culture. Cell culture-derived DIPs, which cannot replicate on their own, are considered for antiviral therapy, because they can inhibit IAV production during co-infection and enhance the innate immune response in the host. The second part of this work covers a mathematical multiscale model of IAV and DIP co-infection that reproduces intracellular and cell population dynamics closely for a wide range of infection conditions. To describe these different scenarios of competition between the two types of virus particles with a single set of parameters, various regulatory mechanisms of viral ribonucleic acid (RNA) synthesis had to be considered. We observe a reduction of the levels of viral messenger RNAs (vmRNAs) related to proteins of the viral polymerase. Furthermore, we find that the accumulation of vmRNA in cells infected only by a specific DIP, which cannot produce the viral polymerase required for replication, can be described by incorporating the primary transcription of vmRNA mediated solely by the parental viral polymerase bound to the viral genome. Additionally, the levels of viral genomic RNA (vRNA) can only be captured if the ratio between the MOI and the number of DIPs per cell, i.e., the multiplicity of DIPs (MODIP), is considered during intracellular virus replication. Overall, the co-infection model supports a comprehensive understanding of the interactions between IAVs and DIPs during co-infection and enables the prediction and optimization of DIP production for therapeutic use. In the last part of this thesis, we use the two developed multiscale models for simulation studies and model prediction. Simulations performed with the model of IAV infection suggest that for high MOIs the infection is driven only by multiple-hit infections of the seed virus. In low MOI conditions, infections are induced almost exclusively by progeny virus particles shifting from single- to multiple-hit infections over time. The model of IAV and DIP co-infection predicts that the concentration of DIPs should be at least 104 times higher than that of regular IAV particles to prevent the spread of an infection. Furthermore, model simulations suggest a nearly equimolar concentration of IAVs and DIPs as the optimal initial conditions for cell culture-derived production of DIPs for antiviral therapy. Taken together, the multiscale models developed in this thesis provide a systems-level understanding of IAV infection dynamics and how this dynamics is impacted by the initially provided MOI and MODIP. These detailed mathematical models successfully describe infection dynamics on the intracellular and cell population level for a wide range of conditions using a single set of parameters and enable meaningful model predictions. Such models, thus, support the fight against influenza and could facilitate a deeper understanding of infection processes for other virus species, in particular regarding the impact of the MOI and potential interactions with DIPs.