Two-stepping through time: mammals and viruses

Abstract

Recent studies have identified ancient virus genomes preserved as fossils within diverse animal genomes. These fossils have led to the revelation that a broad range of mammalian virus families are older and more ubiquitous than previously appreciated. Long-term interactions between viruses and their hosts often develop into genetic arms races where both parties continually jockey for evolutionary dominance. It is difficult to imagine how mammalian hosts have kept pace in the evolutionary race against rapidly evolving viruses over large expanses of time, given their much slower evolutionary rates. However, recent data has begun to reveal the evolutionary strategy of slowly-evolving hosts. We review these data and suggest a modified arms race model where the evolutionary possibilities of viruses are relatively constrained. Such a model could allow more accurate forecasting of virus evolution.

Figure 1. Evolutionary arms races involve interacting host and virus proteins

(a) A schematic of the HIV/SIV lifecycle is shown, illustrating some of the instances where virus proteins (V, red) are known to interact with host proteins (H, blue). In some cases these interactions involve host cofactors (squares and cell surface receptors) that are hijacked by the virus for replication. Hosts also encode antiviral restriction factors (pie shapes) that inhibit viral replication through various mechanisms. For instance, TRIM5α interferes with capsid cores, APOBEC3G hypermutates viral genomes, and tetherin inhibits with virus budding. (b) The cellular receptor, CD4, is used to illustrate a hypothetical arms race scenario. Interaction of the viral spike glycoprotein with CD4 results in virus entry into the cell. Over time, any mutation in CD4 that reduces the strength of this interaction will be preferred by natural selection acting on the host population. Selective pressure will then be placed on the virus population for a mutation in the glycoprotein that re-establishes interaction with CD4. This back-and-forth interplay will result in the rapid fixation of mutations that alter both protein sequences.

Figure 2. Arms races play out in populations

The circles represent populations of hosts, with the circle sizes representing the relative frequencies of different alleles of a single host gene. The spread of a virus (arrows) through this population of hosts is illustrated. Overlapping regions represent heterozygous hosts and non-overlapping regions represent homozygous hosts. (a) In this schematic, the effect of polymorphism in a cofactor gene is illustrated, where the effect on susceptibility would be predicted to be semi-dominant (similar to the CCR5Δ32 mutation discussed in the text). Allele A encodes a cofactor that can be exploited by the virus, while allele B encodes a cofactor variant that is resistant to viral exploitation. The virus will be able to replicate in both A/A and A/B individuals, although presumably less well in A/B heterozygotes. Eventually, allele frequencies in the host population will shift due to the partial protection afforded by the A/B genotype. As allele B becomes more common, there will be selective pressure on the virus to better utilize the B cofactor (blue arrows). A new resistant allele, C, might also emerge or pre-exist in the host population. (b) In this schematic, the effect of polymorphism in a restriction factor gene is illustrated, where allelic versions that restrict a virus are predicted to have a dominant influence on susceptibility to infection. The major allele, A, encodes a restriction factor that is inactive against a circulating virus population. Allele B encodes a restriction factor that is effective against this virus. When allele B is rare, all carriers are assumed to be heterozygous. Because A/B individuals are protected from infection, allele frequencies shift such that allele B is now more common, giving rise to B/B homozygotes. The diminished reservoir of A/A homozygotes places pressure on the virus to ‘escape’ (blue arrows) restriction by the B restriction factor. A new allele with potency against the virus, C, might also emerge or pre-exist in the host population.

Figure 3. Primate restriction factor genes are rapidly evolving

The distribution shows dN/dS values previously determined for 13,454 human-chimpanzee orthologous gene pairs [44]. Adaptive, gain-of-function mutations commonly arise from point mutations that change an amino acid in the encoded protein. When genes are experiencing sequential rounds of positive selection for new adaptations, as in the arms race scenario, they will retain a higher proportion of non-synonymous mutations (dN) than synonymous mutations (dS) in the domains critical for governing the physical interaction. Domains under positive selection will thus accumulate a characteristic signature of dN/dS > 1. dN/dS values for three primate retroviral restriction factor genes are indicated on this distribution. As expected, restriction factor genes such as TRIM5 and APOBEC3G have some of the highest dN/dS values in the human genome [18, 38]. While it is known that codons within tetherin are evolving under positive selection [–21], a full length gene analysis reveals a much lower dN/dS value (dN/dS ~ 0.3). Tetherin is either under less intense selective pressure for adaptation than APOBEC3G and TRIM5, or is more constrained by its other cellular roles. Both tetherin and TRIM5α are known to function in host roles other than retroviral restriction [75, 76]. Additional evolutionary constraint comes from the other host proteins with which restriction factors must interact in order to execute restriction [14, 56].

Figure 4. The cyclic arms race: a game of rock-paper-scissors?

(a) Molecular evidence for the rock-paper-scissors model. For each restriction factor, a key residue known to alter specificity for retroviral targets is illustrated, and the amino acid (aa) encoded at that position is reported for a panel of primate sequences available on Genbank. In two cases, SNPs have been noted at these positions, so multiple amino acids are listed. Amino acid coordinates refer to the human protein except in tetherin (*), where amino acid 17 is the chimpanzee coordinate, since amino acids 14–18 are deleted in the human sequence. Abbreviations: nd, not determined; del, deletion; W, tryptophan; L, leucine; C, cysteine; R, arginine; Q, glutamine; P, proline; K, lysine; D, aspartic acid. (b) The illustration shows the physical interaction between a host restriction factor protein (square) and a virus protein (circle). In the rock-paper-scissors model, both the host and the virus have only a small number of biochemical variants with which to compete (3 in this example), because of the many constraints placed on each. These variants are symbolized by different colors. When colors are matched, the host restriction factor successfully inhibits viral infection. However, escape by the virus is also possible. The host population will then respond through selection for an adaptive mutation that re-establishes interaction. The virus might resample previous states (gray circle) that will now be resistant in the context of the new host genotype (orange square).