Within-host antigenic selection of influenza A virus dominates over stochasticity but is limited by fitness tradeoffs and timing of the immune response
Raghunathan, V.; Leyson, C. M.; Gaddy, M.; Ortiz, L.; Vargas-Maldonado, N.; Wrammert, J.; Bazykin, G. A.; Weissman, D.; VanInsberghe, D.; Lowen, A. C.
Show abstract
Despite antigenic evolution at the global scale, positive selection of influenza virus antigenic variants is not readily observed within hosts. Here, we tested the extent to which fitness tradeoffs, the timing of immune pressure, and stochastic effects impede antigenic selection within pre-immune hosts. We used genetically barcoded influenza A/Texas/50/2012 (H3N2) viruses (Tx/12) in a guinea pig model to probe these dynamics. Positive selection of an antigenic variant was reliant on a high strength of immune pressure acting early in infection. However, when fitness tradeoffs of the antigenic change were lessened, a lower strength and later introduction of immune pressure favored the antigenic variant. In all conditions, barcode dynamics revealed moderate stochastic effects. Our results suggest that stochastic evolution does not impede selection during acute influenza virus infection. The rarity of antigenic escape may instead stem from low mutational supply, fitness tradeoffs, and the intrinsic delay between infection and antibody recall.
Matching journals
The top 5 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Genetic drift acts strongly on within-host influenza virus populations during acute infection but does not act alone 96%
- Immune Pressure is Key to Understanding Observed Patterns of Respiratory Virus Evolution in Prolonged Infections 96%
- Single capsid mutations modulating phage adsorption, persistence, and plaque morphology shape evolutionary trajectories in {Phi}X174 94%
Similar papers in this journal
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.