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

Abstract

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.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jan 30, 2015
Source ID
10.7554/elife.03753

Entities

People

  • Jeremy A. Draghi
  • Joshua B. Plotkin
  • Michael B Schulte
  • Raul Andino

Organizations

  • Army Research Office
  • Burroughs Wellcome Fund
  • David and Lucile Packard Foundation
  • Defense Advanced Research Projects Agency
  • National Institute of Allergy and Infectious Diseases
  • United States Department of the Interior
  • University of California
  • University of Pennsylvania

Tags

Fields of Study

  • Biology

Readers

  • Computational Modeling and Simulation
  • Microbial Pathology
  • Molecular Genetics

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference