No abstract

During the past decade or so, there has been a substantial body of work to dissect arboviral evolution and to develop models of adaptation during host switching. Regardless of what species serve as host or vectors, and of the geographic distribution and the mechanisms of replication, arboviruses tend to have slow evolutionary rates in nature. The hypothesis that this is the result of replication in the disparate environments provided by host and vector did not receive solid experimental support in any of the many viral species tested. Instead, it seems that from the virus’s point of view, either the two environments are sufficiently similar or one of the environments so dominates viral evolution that there is tolerance for suboptimal adaptation to the other environment. Replication in alternating environments has an unexpected cost in that there is decreased genetic variance that translates into a compromised adaptability for bypassed environments. Arboviruses under strong and continuous positive selection may have unusual patterns of genomic changes, with few or no mutations accumulated in the consensus sequence or with dN/dS values typically consistent with random drift in DNA-based organisms.

The amount and nature of preexisting variation in a population of RNA viruses is an important determinant of the virus's ability to adapt rapidly to a changed environment. However, direct quantification of this preexisting variation may be cumbersome, because potentially beneficial alleles are typically rare, and isolation of a large number of subclones is required. Here, we propose a simpler method. We infer the initial population structure of vesicular stomatitis virus (VSV) by fitting a mathematical model of asexual evolution to an extensive set of measurements of VSV fitness dynamics under various conditions, including new and previously published data. The inferred variation of fitness in the initial population agrees very well with the results of direct experiments with subclone fitness quantification. From the same procedure, we also estimate the mean fitness effect of beneficial mutations (selection coefficient s), the percentage of sites in the genome that are under moderate positive or negative selection, and the percentage of sites where beneficial mutations may potentially occur. For VSV strain MARM U evolving in BHK-21 cells, the three parameters have values of 0.39, 9%, and 0.06%, respectively. The method can be generalized and applied easily to other rapidly evolving microbes, including both asexual microorganisms and those with recombination.

No abstract