Immune responses in mammals are highly coordinated processes involving multiple systems that sense infection, activate antiviral and antimicrobial responses, and trigger adaptive immunity. The evolutionary history of several such systems has been analysed in detail, and below we describe the most recent findings.

Innate immune receptors. The mammalian immune system is endowed with a repertoire of molecular sensors called pattern-recognition receptors (PRRs). These molecules detect pathogen-associated molecular patterns (PAMPs) and initiate a downstream signalling cascade that culminates in the production of cytokines and antimicrobial factors. The main families of PRRs include TLRs, NOD-like receptors (NLRs), RIG-like receptors (RLRs) and AIM2-like receptors (ALRs). In the host–pathogen arms race, these molecules represent one of the foremost detection–defence systems; consistently, several studies have reported adaptive evolution at genes encoding mammalian PRRs.

Analyses in primates, rodents and representative mammalian species indicate that positive selection shaped nucleotide diversity at most TLRs, with the strongest pressure acting on TLR4 (Refs 35,48,49). Similarly to TLR4 (Fig. 1), several positively selected sites in other TLRs are located in PAMP-binding regions, raising questions as to whether species-specific host–pathogen co-evolution is occurring, and how these sequence changes translate into differential PAMP recognition. In fact, as mentioned above for LPS, species-specific differences in ligand binding by TLRs seem to be common and potentially affect the overall immune response to specific pathogens50. Integration of evolutionary, immunological and genetic studies will be instrumental in the future for medical applications, especially in light of the proposed use of TLR ligands as vaccine adjuvants, a step that may require tailoring to distinct species50.

Compared with TLRs, mammalian ALRs are much less conserved and more dynamic, with distinct species carrying different sets of functional genes (ranging from 13 in mice to none in some bats)37,51. As a consequence, analysis of several mammals indicated that, with the exception of absent in melanoma 2 (AIM2), which is non-functional in several species, no unequivocal orthologues can be inferred for the remaining ALR genes. This prevents the application of standard codon-based tests across the entire mammalian phylogeny, although closely related species can be analysed. Thus, interferon-γ-inducible protein 16 (IFI16) and AIM2 were shown to have evolved under positive selection in primates. Positively selected sites were observed to mainly localize near to regions or domains involved in DNA binding and protein–protein interaction, suggesting modulation of substrate specificity or genetic conflicts with viral inhibitors52. Positive selection was also described for the three mammalian RLRs (retinoic acid-inducible gene I (RIGI; also known as DDX58), melanoma differentiation-associated 5 (MDA5; also known as IFIH1) and LGP2 (also known as DHX58)), the primate NLR family apoptosis inhibitory protein (NAIP) and rodent Naip2 genes53,54. Indeed, as is the case for ALRs, rodents have multiple NAIP paralogues that show widespread evidence of inter-locus recombination. This led to the application of a dN/dS sliding window approach: the Naip2 sites evolving with dN/dS >1 were found to be located in the bacterial ligand domain54.

Antiviral effectors and restriction factors. Studies on antiviral restriction factors have been extensive because these molecules represent obvious targets in host–pathogen arms races. Specifically, genetic conflicts between host restriction factors and viral components often play out in terms of binding-seeking dynamics (the host factor adapts to bind the viral component) and binding-avoidance dynamics (the virus counter-adapts to avoid binding and restriction by the host factors). The evolutionary history of antiviral restriction factors has been comprehensively reviewed elsewhere55,56,57, and we only highlight a few recent developments here.

The first restriction factor to be identified was the product of the mouse gene Friend virus susceptibility 1 (Fv1), a protein that protects against murine leukaemia virus (MLV) infection58. The origin and evolution of FV1 is extremely interesting: early sequence analysis revealed that it derives from the gag gene of an ancient endogenous retrovirus that is not directly related to MLV58. Thus, FV1 exemplifies a paradoxical twist of the arms race scenario whereby a viral gene is co-opted by the host to serve an antiviral function (this is not the only instance, see Ref. 59). Recent results showed that the Fv1 gene was inserted into the mouse genome between 4 million and 7 million years ago, long before the appearance of MLV. Thus, the selective pressure exerted by other viruses must have maintained FV1 function and driven its evolution60. Indeed, analysis of FV1 from wild-type mice indicates that different Fv1 products can recognize and block multiple genera of retroviruses (for example, equine infectious anaemia virus and feline foamy virus), and a number of positively selected sites in the carboxy-terminal region of FV1 are directly involved in restriction specificity60. Thus, in a similar way to TRIM5, FV1 was identified for its ability to restrict an extant virus, but its evolution was driven by different waves of retroviral species, some of which are likely to be extinct.

Other restriction factors that have been the topic of recent investigation are encoded by two paralogous genes, myxovirus resistance 1 (MX1; also known as MxA) and MX2 (also known as MxB). The protein products of the two genes display high sequence identity but different antiviral specificity. MX1 has broad activity against RNA and DNA viruses. Recently, Mitchell and collaborators61 showed the potential of evolutionary analyses to generate experimentally testable hypotheses on the nature of genetic changes that affect species-specific susceptibility to infection. The authors applied an evolution-guided approach and identified a cluster of positively selected residues in an unstructured surface-exposed MX1 loop (loop 4), which confers antiviral specificity; genetic variation in loop 4 is a major determinant of MX1 antiviral activity against Thogoto and avian influenza A viruses, and replacements at a single positively selected site alter the ability of MX1 to restrict these pathogens61.

More recently, the selection pattern at the MX2 gene, which encodes an antiretroviral effector62, was shown to parallel that of MX1, with most selected sites located in loop 4 (Ref. 63). In MX2, sites selected in the primate lineage were detected outside loop 4, and MX1 also showed evidence of selection in other domains61,63; these sites are promising candidates for being additional determinants of antiviral activity.

Antigen presentation, T cell activation and immunoglobulin G receptors. Antigen presentation and the ensuing T cell activation are central processes in mammalian cell-mediated immune response (Fig. 3). Therefore, a convenient strategy for pathogens to elude immune surveillance is to hijack the molecular pathways responsible for these processes64,65. In line with the arms race scenario, there is evidence of positive selection at several mammalian genes involved in antigen presentation and the regulation of T cell activation66,67 (Fig. 3). The pathogen-driven mechanisms underlying evolution at these genes are likely to be manifold. One mechanism is genetic conflict with a pathogen-encoded component, evidence of which can be seen in the protein CD86. Positively selected sites in the transmembrane and juxtamembrane region of CD86 interact with MIR2 (Fig. 3), a Kaposi sarcoma-associated herpesvirus (KSHV) protein that downmodulates CD86 expression67,68. A second mechanism is the use of cell-surface molecules as viral receptors: some adenovirus strains, for example, have been reported to exploit CD80 and CD86 for cellular attachment69,70. A third mechanism is the broadening or tuning of the host's ability to process and present pathogen-derived components. For example, a positively selected site in the carbohydrate-recognition domain of CD207 (also known as langerin; a Birbeck granule molecule) affects an amino acid position that is directly involved in the binding of pathogen-derived glycoconjugates71.

Figure 3: Genes involved in antigen processing and presentation and T cell regulation are common targets of positive selection in mammals. All pathway components are designated using official gene names (excluding the major histocompatibility complex (MHC) and T cell receptor (TCR)) and are highlighted in red if they are targets of positive selection in mammals or primates25,66,67. The molecular components of different antigen processing and presentation pathways are shown (details from Refs 107,108) to provide a general overview of the extent of positive selection and to highlight the function of positively selected genes, as most of their protein products directly interact with the antigen. Thus, the figure is not meant to show all molecules involved in the process or to convey mechanistic insights. Also, some genes may show tissue-specific expression or may be induced under specific circumstances: their products are nonetheless included for the sake of completeness. As for T cell regulatory molecules, the representation does not reflect the stoichiometry of binding (for example, CD28 functions as a dimer). Notably, the same molecule may be expressed by different populations of T cells, although here each molecule is shown on one T cell type only (to avoid redundancy). The dashed arrows and '?' indicate steps that lack clear molecular definition or are only inferred. The orange circles, and red and blue shapes at the bottom of the figure represent proteolytic fragments. B2M, β2-microglobulin; BLMH, bleomycin hydrolase; CALR, calreticulin; CD40LG, CD40 ligand; CTLA4, cytotoxic T lymphocyte protein 4; CTS, cathepsin; CYB, cytochrome b; ERAP, endoplasmic reticulum aminopeptidase; HAVCR2, hepatitis A virus cellular receptor 2; HLA-DM, major histocompatibility complex, class II, DM; ICOS, inducible T cell co-stimulator; ICOSLG, ICOS ligand; IFI30, interferon-γ-inducible protein 30; iNKT, invariant natural killer T; iTCR, invariant TCR; LGMN, legumain; LNPEP, leucyl-cystinyl aminopeptidase; NCF, neutrophil cytosol factor; NPEPPS, puromycin-sensitive aminopeptidase (also known as PSA); NRD1, nardilysin; PDCD1, programmed cell death 1; PDCD1LG2, programmed cell death 1 ligand 2; PDIA3, protein disulfide-isomerase A3; ROS, reactive oxygen species; TAP, antigen peptide transporter; TAPBP, TAP-binding protein (also known as tapasin); THOP1, thimet oligopeptidase 1; TPP2, tripeptidyl-peptidase 2. PowerPoint slide Full size image

These mechanisms are not mutually exclusive. For example, a plethora of viral pathogens (such as herpes simplex virus 1, human papillomavirus, HIV-1 and KSHV) interfere with CD1D trafficking and recycling72,73. As a consequence, the cytoplasmic and transmembrane regions of CD1D display positively selected sites, one of which is within a primate-specific trafficking signal. Additional positively selected sites are located in the CD1D extracellular region and flank the T cell receptor interaction surface and the lipid-binding pocket, which suggests that they exert an effect on antigen-binding specificity67.

Finally, we draw attention to one of the few attempts at assessing the part that helminth infections have played as selective pressures for mammals and at integrating epidemiological information into molecular evolutionary approaches. Machado and co-workers74 found evidence of positive selection at the mammalian gene Fc fragment of IgG, low affinity IIIb, receptor (FCGR3B), which is expressed by eosinophils and is involved in the binding of immunoglobulin G (IgG)-coated parasites. Notably, the authors also tested a specific hypothesis whereby mammalian lineages hosting a wider range of helminth species should show stronger evidence of selection compared with other species (this was accomplished by running the phylogenetic analysis by maximum likelihood (PAML) branch-site models with helminth-rich lineages as foreground branches74; Box 3). Their hypothesis was verified, providing a plausible explanation for the evolutionary pattern at FCGR3B and suggesting that similar approaches may be used to detect other mammalian genes involved in genetic conflicts with helminth parasites.