(535b) Toward a Quantitative and Predictive Model of Growth for An RNA Virus

Viral infections are the cause of many human diseases such as the common cold, AIDS and even some cancers. In order to fight and prevent virally caused diseases we must understand the viral replication process. Our approach is to use kinetic models based on known viral mechanisms to predict viral growth. A model that can predict virus growth can be used to design virus systems to generate vaccines, to suggest anti-viral strategies, and to engineer viruses that selectively kill cancerous cells while avoiding healthy tissue. The viral system we use is the well studied vesicular stomatitis virus (VSV). VSV has a negative sense RNA genome which encodes five viral proteins. Upon introduction of the viral genome into the cell, the viral polymerase begins transcribing the five genes sequentially with a measureable attenuation at each gene junction. The attenuation leads to viral gene expression control from a single promoter, with the genes closer to the promoter being expressed higher than the next gene in the sequence. As the mRNAs accumulate and are translated, the viral polymerase is transformed from a transcriptase to a replicase by interaction with produced viral proteins. The replicase generates full length anti-genome which is not translated but used as a template to produce more viral genomes. The genomes associate with viral proteins and produce infectious viral particles.

While the general mechanisms of the VSV replication cycle are well studied, the relative rates of the processes are unknown. In order to determine some of the unknown rates we have developed an assay to measure absolute numbers per cell of viral mRNAs, genomes and anti-genomes during the infection process. The kinetic data for viral RNA is used with a previously published model to predict kinetic parameters. In order to provide a rich data set for parameter estimation and model refinement, the initial condition of the viral infection was varied from a low virus to cell ratio to a high virus to cell ratio. A low virus to cell ratio represents the initiation of infection in an organism, while a high ratio represents the conditions that would be seen in an infection spreading through tissue. Interestingly, while the published model was able to predict viral growth it underestimated the levels of viral RNA by orders of magnitude. These results suggest unknown and important mechanisms in the viral infection process which must be included in the predictive model. This research will lead to development of a true predictive model of VSV growth which can be extended to other virus systems for the design of vaccines, anti-viral strategies, and anti-cancer strategies.