Models of RNA virus evolution and their roles in vaccine design

Ojosnegros, Samuel; Beerenwinkel, Niko

The application of statistical genetics and phylogenetics methods to influenza sequence data has not only improved our understanding of the evolutionary dynamics and the epidemiology of the virus, but it has also become an integral part of the yearly vaccine design cycle. However, the successful case of influenza does not seem to provide a practical model for HIV. One reason for this discrepancy might be the evolutionary dynamics of HIV which are strikingly different from those of influenza. Rather than the drift-and-shift pattern of influenza evolution which generates only a small amount of genetic diversity around the successful trunk lineage, HIV tends to spread out from an ancestor in a radial fashion and to generate much more variation. The worldwide diversity of influenza sequences in any given year appears to be comparable to the diversity of HIV sequences found within a single infected individual at one time point [62] . Thus, an HIV vaccine must stimulate a very broad reactive immune response against a large set of diverse viral strains and the genetic makeup of these sequences is much more difficult to predict from the currently circulating strains as compared to influenza. It is for these and possibly other reasons that the same bioinformatics-assisted vaccine design approach that is established for influenza, has not been equally successful for HIV to date. In the following sections, we will discuss extensions of the models discussed above as well as complementary mathematical and computational approaches that might be of help in search for an HIV vaccine in the future.