Experimentally guided models reveal replication principles that shape the mutation distribution of RNA viruses

• Main Authors: Michael B Schulte, Jeremy A Draghi, Joshua B Plotkin, Raul Andino
• Format: Article
• Language: English
• Published: eLife Sciences Publications Ltd 2015-01-01
• Series: eLife
• Subjects: stochastic mathematical modeling; population structure; virus replication; RNA replication
• Online Access: https://elifesciences.org/articles/03753

Life history theory posits that the sequence and timing of events in an organism's lifespan are fine-tuned by evolution to maximize the production of viable offspring. In a virus, a life history strategy is largely manifested in its replication mode. Here, we develop a stochastic mathematical model to infer the replication mode shaping the structure and mutation distribution of a poliovirus population in an intact single infected cell. We measure production of RNA and poliovirus particles through the infection cycle, and use these data to infer the parameters of our model. We find that on average the viral progeny produced from each cell are approximately five generations removed from the infecting virus. Multiple generations within a single cell infection provide opportunities for significant accumulation of mutations per viral genome and for intracellular selection.