PT  - JOURNAL ARTICLE
AU  - Le Yan
AU  - Richard A. Neher
AU  - Boris I. Shraiman
TI  - Phylodynamics of rapidly adapting pathogens: extinction and speciation of a Red Queen
AID  - 10.1101/455444
DP  - 2018 Jan 01
TA  - bioRxiv
PG  - 455444
4099  - http://biorxiv.org/content/early/2018/10/29/455444.short
4100  - http://biorxiv.org/content/early/2018/10/29/455444.full
AB  - Rapidly evolving pathogens like influenza viruses can persist by accumulating antigenic novelty fast enough to evade the adaptive immunity of the host population, yet without continuous accumulation of genetic diversity. This dynamical state is often compared to the Red Queen evolving as fast as it can just to maintain its foothold in the host population: Accumulation of antigenic novelty is balanced by the build-up of host immunity. Such Red Queen States (RQS) of continuous adaptation in large rapidly mutating populations are well understood in terms of Traveling Wave (TW) theories of population genetics. Here we shall make explicit the mapping of the established Multi-strain Susceptible-Infected-Recovered (SIR) model onto the TW theory and demonstrate that a pathogen can persist in RQS if cross-immunity is long-ranged and its population size is large populations allowing for rapid adaptation. We then investigate the stability of this state focusing on the rate of extinction and the rate of “speciation” defined as antigenic divergence of viral strains beyond the range of cross-inhibition. RQS states are transient, but in a certain range of evolutionary parameters can exist for the time long compared to the typical time to the most recent common ancestor (TMRCA). In this range the steady TW is unstable and the antigenic advance of the lead strains relative to the typical co-circulating viruses tends to oscillate. This results in large fluctuations in prevalence that facilitate extinction. We shall demonstrate that the rate of TW fission into antigenically uncoupled viral populations is related to fluctuations of TMRCA and construct a “phase diagram” identifying different regimes of viral phylodynamics as a function of evolutionary parameters.