RT Journal Article SR Electronic T1 Tuning the course of evolution on the biophysical fitness landscape of an RNA virus JF bioRxiv FD Cold Spring Harbor Laboratory SP 090258 DO 10.1101/090258 A1 Assaf Rotem A1 Adrian W.R. Serohijos A1 Connie B. Chang A1 Joshua T. Wolfe A1 Audrey E. Fischer A1 Thomas S. Mehoke A1 Huidan Zhang A1 Ye Tao A1 W. Lloyd Ung A1 Jeong-Mo Choi A1 Abimbola O. Kolawole A1 Stephan A. Koehler A1 Susan Wu A1 Peter M. Thielen A1 Naiwen Cui A1 Plamen A. Demirev A1 Nicholas S. Giacobbi A1 Timothy R. Julian A1 Kellogg Schwab A1 Jeffrey S. Lin A1 Thomas J. Smith A1 James M. Pipas A1 Christiane E. Wobus A1 Andrew B. Feldman A1 David A. Weitz A1 Eugene I. Shakhnovich YR 2016 UL http://biorxiv.org/content/early/2016/11/28/090258.abstract AB Predicting viral evolution remains a major challenge with profound implications for public health. Viral evolutionary pathways are determined by the fitness landscape, which maps viral genotype to fitness. However, a quantitative description of the landscape and the evolutionary forces on it remain elusive. Here, we apply a biophysical fitness model based on capsid folding stability and antibody binding affinity to predict the evolutionary pathway of norovirus escaping a neutralizing antibody. The model is validated by experimental evolution in bulk culture and in a drop-based microfluidics device, the “Evolution Chip”, which propagates millions of independent viral sub-populations. We demonstrate that along the axis of binding affinity, selection for escape variants and drift due to random mutations have the same direction. However, along folding stability, selection and drift are opposing forces whose balance is tuned by viral population size. Our results demonstrate that predictable epistatic tradeoffs shape viral evolution.