Clonal interference and changing selective pressures shape the escape of SARS-CoV-2 from hundreds of antibodies
SARS-CoV-2 rapidly evolves to evade human immunity. While the viruss overall resistance to human polyclonal antibody responses has steadily increased over time, the dynamics by which it escaped individual monoclonal antibodies within these responses have not been thoroughly explored. Recently, a series of studies by Cao et al. [1, 2, 3] used deep mutational scanning (DMS) to identify which mutations allow the Wuhan-Hu-1 receptor-binding domain to escape binding by individual antibodies, doing so for thousands of antibodies. Here, we sought to use these data to retrospectively examine the evolutionary dynamics of escape from a set of 1,603 antibodies. For each antibody, we used the DMS data to predict an antibody-escape score for each of thousands of globally circulating viral sequences from the first 3.5 years of the pandemic, and then computed an escape trajectory that quantifies how the populations average escape score changed over time. We use pseudovirus neutralization data from Cao et al. and Wang et al. [4] to validate common patterns in escape trajectories. While some trajectories increase monotonically over time, others show large fluctuations as a result of clade-displacement events that reduce the frequency of antibody-escape mutations in the viral population. Fitness effects of mutations estimated from natural sequences suggest that the mutations are displaced due to clonal interference. Further, these estimates suggest that the order in which escape mutations arose is shaped by changing selective pressures. Overall, this work helps describe how SARS-CoV-2 evaded the individual components of a polyclonal immune response in nature, and suggests that evasion occurred via complex evolutionary dynamics.