Speaker
Igor Rouzine
Description
To escape immune recognition in previously infected hosts, viruses
evolve genetically in immunologically important regions. The host’s
immune system responds by generating new memory cells recognizing
the mutated viral strains. Despite recent advances in data collection
and analysis, it remains conceptually unclear how epidemiology,
immune response, and evolutionary factors interact to produce the
observed speed of evolution and the incidence of infection. Here we
establish a general and simple relationship between long-term cross-
immunity, genetic diversity, speed of evolution, and incidence. We
develop an analytic method fusing the standard epidemiological
susceptible-infected-recovered approach and the modern virus
evolution theory. The model includes the factors of strain selection due
to immune memory cells, random genetic drift, and clonal interference
effects.
We predict that the distribution of recovered individuals in memory
serotypes creates a moving fitness landscape for the circulating strains
which drives antigenic escape. The fitness slope (effective selection
coefficient) is proportional to the reproductive number in the absence
of immunity R0 and inversely proportional to the cross-immunity
distance a, defined as the genetic distance of a virus strain from a
previously infecting strain conferring 50% decrease in infection
probability. Analysis predicts that the evolution rate increases linearly
with the fitness slope and logarithmically with the genomic mutation
rate and the host population size.
Fitting our analytic model to data obtained for influenza A H3N2 and
H1N1, we predict the annual infection incidence within a previously
estimated range, (4-7)%, and the antigenic mutation rate of Ub = (5 −
8) 10−4 per transmission event per genome. Our prediction of the
cross- immunity distance of a = (14 − 15) aminoacid substitutions
agrees with independent data for equine influenza. Importantly, we
demonstrate that variation in basic reproduction ratio R0 is mostly
responsible for the variation among strains, and explain the observed
inverse correlation between the substitution rate and the time to the
most recent common ancestor.
Primary author
Igor Rouzine
