Models of RNA virus evolution and their roles in vaccine design

Abstract

Viruses are fast evolving pathogens that continuously adapt to the highly variable environments they live and reproduce in. Strategies devoted to inhibit virus replication and to control their spread among hosts need to cope with these extremely heterogeneous populations and with their potential to avoid medical interventions. Computational techniques such as phylogenetic methods have broadened our picture of viral evolution both in time and space, and mathematical modeling has contributed substantially to our progress in unraveling the dynamics of virus replication, fitness, and virulence. Integration of multiple computational and mathematical approaches with experimental data can help to predict the behavior of viral pathogens and to anticipate their escape dynamics. This piece of information plays a critical role in some aspects of vaccine development, such as viral strain selection for vaccinations or rational attenuation of viruses. Here we review several aspects of viral evolution that can be addressed quantitatively, and we discuss computational methods that have the potential to improve vaccine design.

Evidence for genetic variation in Natterer’s bats (Myotis nattereri) across three regions in Germany but no evidence for co-variation with their associated astroviruses

“…Thus, it is unlikely that individual bats directly transmit a certain virus haplotype between the three geographic regions analyzed (NRW, BY and MV). Since viruses have a considerably higher mutation rate [73] compared to the bat host, mutations in the virus sequences do occur within much shorter time scales than mutation in the bats’ genome [74, 75]. As bats need to transmit the astroviruses directly, the movement of viruses across the landscape should mirror the movement of the bats and hence occur successively over large distances following the stepping stone model of the host.…”

“…In contrast to higher Eukaryotes such as the bat host, RNA viruses are subject to higher selective pressures and combined with a high mutation rate allow continuous and rapid adaptation to changing environmental conditions [73, 76, 77]. Coupled with large population sizes, virus evolution can thus already be observed within very short time scales of weeks to months [74, 75]. The frequent fluctuations in the prevalence of viral populations (e.g.…”

Analyses of Brucella Pathogenesis, Host Immunity, and Vaccine Targets using Systems Biology and Bioinformatics

“…To promote vaccine development, the author’s laboratory has developed Vaxign 2 , the first web-based vaccine design program based on reverse vaccinology (Xiang and He, 2009; He and Xiang, 2010; He et al, 2010b). Predicted features in the Vaxign pipeline include protein subcellular location, transmembrane helices, adhesin probability, sequence conservation among genomes of pathogenic strains, exclusion of sequences in non-pathogenic strains, exclusion of proteins shared in host spp.…”

“…(Xiang and He, 2009; He and Xiang, 2010). An O-sialoglycoprotein endopeptidase was predicted to be a secreted Brucella protein.…”

“…Among the final 14 proteins are two known Brucella protective antigens (Omp25 and Omp31-1), two flagellar hook proteins FlgE and FlgK, one porin protein Omp2b, two TonB-dependent receptor proteins. Omp2b and Omp31-1 are absent from the genome of B. ovis , a Brucella species non-pathogenic to human (He and Xiang, 2010). The feasibility of using these Brucella proteins for development of a safe and effective human vaccine deserves further investigation.…”