For viruses, ecology shapes the speed of evolutionary change

Polio virus (picornavirus)

Particles of polio virus, an RNA virus. Image from Flickr/Sanofi Pasteur

Molecular ecologists are interested in understanding what patterns in genetic variation across and among populations can tell us about the ecology of the living things we study. But a paper published in the latest issue of The American Naturalist demonstrates that this relationship between ecology and genetic variation can operate on a deeper level than we may usually think about—it suggests that the rate at which some viruses evolve may be determined not by natural selection imposed by their hosts, but by simple population dynamics.
The paper’s authors, a team of collaborators from Duke University, the Centers for Disease Control, North Carolina State University, and the National Institutes of Health, were motivated by a weird pattern in the biology of RNA viruses. Viruses based on RNA, as opposed to DNA, generally have very high mutation rates—in part because the process of replicating RNA is more error-prone than DNA replication. But there’s also tremendous variation in the substitution rate between different RNA viruses, even between populations of closely related viruses.
The authors hypothesize that this variation in rates of evolutionary change—beyond what’s accounted for by the errors of RNA replication and the strength of selection acting on viruses under continual pressure to evade their hosts’ immune responses—may be explained by the population dynamics of viruses spreading within hosts, and then among hosts. To test that idea, they built interlinked models of viral infection at those two different levels.
The first model tracks the spread of viral particles through a population of cells within an individual host. As in many such models, the infection proceeds through several stages: a slow initial spread, which accelerates as the viral load within the host increases, then tails off as the virus runs out of naive cells to infect. Along with those dynamics, the within-host model keeps track of how many rounds of viral replication had occurred as the viral population grew. These replication events are the points at which errors in RNA copying can occur. And it turns out that the rate of new replication events—which determines the rate of mutations—peaks while the virus is in that phase of accelerating population growth, then falls off as the infection reaches an internal equilibrium.
The second model, then, tracks the spread of infection through a population of hosts. Similarly to the first, this model keeps track of the average time that each infected host individual had been infected—which translates into the phase of within-host viral population growth. This connection allowed the authors to describe the relationship between the rate of an infection’s spread through the host population to the age of individual hosts’ viral infections—to the rate of mutation in the population of viruses within each host.
The dynamics of this second model follow two scenarios. In the first case, an epidemic, an infection is spreading through a population of previously uninfected hosts—and it spreads rapidly enough that infections tend to be passed from one host to the other during the growth phase of their within-host dynamics. In this scenario, the viral substitution rate stays high as the infection spreads.
In the second case, an endemic infection, the virus is at equilibrium within the host population, infecting new individuals about as fast as new hosts are born. Under these conditions, the virus tends to be transmitted by hosts whose viral populations are past the initial growth phase—so the viral substitution rate across the host population is quite a bit lower.
This pattern of rapid substitution rates in epidemic infections and slower substitution rates in stable, endemic infections, has been observed in empirical studies of evolutionary change in different RNA viruses. A recent study of rabies in bats, which I linked to above, found that rabies viruses infecting bats from the tropics have substantially higher substitution rates than rabies infecting bats from temperate latitudes. That might be consistent with infections spreading more rapidly through denser tropical populations.
The authors apply their model to the estimated differences in substitution rate between endemic and epidemic viral populations in a handful of empirical cases, and find that, for the most part, the model implies plausible rates of infection spread given the observed substitution rates. So it does look as though these purely ecological dynamics of within-host viral population growth and among-host transmission rates can explain some of the variation in substitution rates in RNA viruses—even before we add the effects of natural selection to the mix.
It’s an interesting illustration, I think, of the importance of considering non-equilibrium conditions in evolutionary ecology, even in molecular studies—because the living world is not necessarily in equilibrium.
Hanada, K., Y. Suzuki, and T. Gojobori. 2004. A large variation in the rates of synonymous substitution for RNA viruses and its relationship to a diversity of viral infection and transmission modes. Molecular Biology and Evolution 21:1074–80. doi: 10.1093/molbev/msh109.
Scholle, S. O., R. J. F. Ypma, A. L. Lloyd, and K. Koelle. 2013. Viral substitution rate variation can arise from the interplay between within-host and epidemiological dynamics. The American Naturalist 182:494–513. doi: 10.1086/672000.
Streicker, D. G., P. Lemey, A. Velasco-Villa, and C. E. Rupprecht. 2012. Rates of viral evolution are linked to host geography in bat rabies. PLoS Pathogens 8:e1002720. doi: 10.1371/journal.ppat.1002720.

About Jeremy Yoder

Jeremy B. Yoder is an Associate Professor of Biology at California State University Northridge, studying the evolution and coevolution of interacting species, especially mutualists. He is a collaborator with the Joshua Tree Genome Project and the Queer in STEM study of LGBTQ experiences in scientific careers. He has written for the website of Scientific American, the LA Review of Books, the Chronicle of Higher Education, The Awl, and Slate.
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