Quantification and Integration of the Multi-scale Effects of Defective Interfering Particles on Virus Infections

Quantification and Integration of the Multi-scale Effects of Defective Interfering Particles on Virus Infections
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Release: 2014
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Defective interfering particles (DIPs) are virus mutants that lack essential genes for growth, but able to divert the viral proteins produced by an infectious virus, and thus, interfere with infectious virus production. The accumulating evidence about their presence in nature and the increasing interest in DIP-based vaccine formulations highlight the need for an accurate understanding of the effect of DIPs on virus growth at intracellular and cell-to-cell spread scale. To analyze the multi-scale effects of DIPs, we first tracked the intracellular growth of a recombinant vesicular stomatitis virus (VSV) in individual cells using fluorescence microscopy and quantified the effects of DIPs on intracellular virus production kinetics. Through a metric scoring the dose-dependent effects of DIPs in cells and their cell-to-cell variations, we identified two-fold higher degree of interference by DIPs in isolated cells than that in single cells within a population. Quantification of infection spread behavior revealed an induction in the diversity of spread patterns with increasing DIP input. Through a cellular automata model driven by the measured virus growth kinetics in individual cells, we found that the intracellular scale effects of DIPs and cell-to-cell variations play a major role in the formation of the diverse interfered spread patterns. Using the developed framework the DIP-induced interference was compared to the interference by a recombinant defective viral mutant that only lacks virus assembly proteins. Our findings suggested that during the DIP co-infections the competition at replication stage interferes mainly with the early growth delaying and reducing the intracellular virus activity, and thus decreasing extracellular virus production, which is further diminished by the competition at virus assembly stage. Despite this reduction in virus production, we observed that the enrichment of DIPs are limited by the growth of infectious virus suggesting the dependency of DIPs on infectious virus at all scales of virus infections. Overall, the insight provided by this work can guide future studies of the viral infectious disease progression in the presence of DIPs, while the developed framework sets a platform to investigate other microbial infections under the effects of different interfering substances, such as antiviral or antibacterial drugs and vaccines.

Kinetics of Vesicular Stomatitis Virus MRNA and Genomes During Infection

Kinetics of Vesicular Stomatitis Virus MRNA and Genomes During Infection
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Release: 2013
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Viruses can be attributed to many devastating human diseases. In this thesis I present quantitative methods and analysis of infections of vesicular stomatitis virus (VSV) in cell culture environments. The work presented here reveals new information about VSV infection and suggests future directions for quantitative study of viral infections. Quantitative data collection and analysis in Chapter 2 reveal that the mRNA production rate is dependent only on viral genomes, suggesting that viral polymerases are in excess. This work suggests that VSV is able to establish a robust infection in multiple cellular environments. In Chapter 3 I present a large scale simulation and simulation environment developed to predict the outcome of infections of multiple strains of VSV in cell culture. The simulation reveals that viral genome replication is limited by the presence of the nucleocapsid protein, the catalyst for genome replication. Finally, in Chapter 4 I present quantitative analysis of VSV populations using RNA sequencing. This work shows that RNA sequencing is an unbiased tool that can be used to detect, identify, and quantify defective interfering particles in a virus population. Together this work shows that quantitative analysis of biological systems can reveal new biology. Quantitative techniques are necessary for developing predictive models of viral infections, which will lead to the rational design of anti-viral treatments.