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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Future Microbiol. Author manuscript; available in PMC May 30, 2012.
Published in final edited form as:
PMCID: PMC3363998
Uncovering the interplay between CD8, CD4 and antibody responses to complex pathogens
Magdalini Moutaftsi, David C Tscharke, Kerrie Vaughan, David M Koelle, Lawrence Stern, Mauricio Calvo-Calle, Francis Ennis, Masanori Terajima, Gerd Sutter, Shane Crotty, Ingo Drexler, Genoveffa Franchini, Jon W Yewdell, Steven R Head, Janice Blum, Bjoern Peters, and Alex Sette
Magdalini Moutaftsi, Vaccine Discovery, La Jolla Institute for Allergy & Immunology, La Jolla, CA, USA;
Author for correspondence: Infectious Disease Research Institute, 1124 Columbia Street, Suite 400, Seattle, WA 98104, USA, Tel.: +1 206 330 2519, Fax: +1 206 381 3678, mmoutaftsi/at/
Vaccinia virus (VACV) was used as the vaccine strain to eradicate smallpox. VACV is still administered to healthcare workers or researchers who are at risk of contracting the virus, and to military personnel. Thus, VACV represents a weapon against outbreaks, both natural (e.g., monkeypox) or man-made (bioterror). This virus is also used as a vector for experimental vaccine development (cancer/infectious disease). As a prototypic poxvirus, VACV is a model system for studying host–pathogen interactions. Until recently, little was known about the targets of host immune responses, which was likely owing to VACVs large genome (>200 open reading frames). However, the last few years have witnessed an explosion of data, and VACV has quickly become a useful model to study adaptive immune responses. This review summarizes and highlights key findings based on identification of VACV antigens targeted by the immune system (CD4, CD8 and antibodies) and the complex interplay between responses.
Keywords: adaptive immunity, epitopes, immunodominant, protection, vaccinia virus
Amongst the viruses of relevance to human health, members of the poxvirus family have some of the largest viral genomes (ranging from 130 to 300 kb), with as many as 260 open reading frames (ORFs). All poxviruses replicate exclusively in the cytoplasm of their hosts and have an enveloped viral particle that carries the single, linear dsDNA genome. In general, the genes located in the center of the genome are relatively conserved among poxviruses and have essential molecular functions for replication and survival. By contrast, terminally located genes are more variable and encode proteins that interfere with the host response to infection (virulence factors) and determine host-range restriction [1].
The poxviruses that infect vertebrate hosts comprise eight genera and, of these, the orthopox genus has the best-known members and also those most relevant to human health. The most prominent is variola virus (VARV), the causative agent of smallpox, and vaccinia virus (VACV), the vaccine used to prevent and eradicate this once dreaded disease. With smallpox conquered in the 1980s, attention was focused on the use of recombinant VACV as a vector for protein expression in the study of cancer and infectious disease vaccines [2]. A variety of strains of VACV have been used for these studies. The high rates of severe adverse events associated with the traditional smallpox vaccine led to the development of attenuated strains, exemplified by modified vaccinia virus Ankara (MVA). MVA was generated by extensive passaging of VACV Ankara on chicken embryo fibroblasts, resulting in the loss of several genes compared with the parental genome and loss of the ability to replicate in most mammalian cells, including primary human cells [3]. By contrast to the extreme attenuation of MVA, the most commonly used VACV strain for laboratory experiments, namely Western Reserve (WR), is amongst the most virulent of strains, having been selected by serial passage in suckling mouse brain. Smallpox vaccine strains such as Dryvax, ACAM2000 (a clone from Dryvax) and Lister are less pathogenic than WR in animal models [4,5], but remain fully replicating viruses and are associated with unacceptably high rates of adverse events in vaccines [6,7].
In the past few years, the threat of accidental or intentional release of VARV, as well as concerns about the emergence of zoonotic poxviruses such as monkeypox, which can also cause fatal disease in humans, has intensified interest in studying VACV. In this context, VACV serves not only as a vaccine, but as a surrogate model of virulent poxvirus infection in humans owing to the high sequence similarity with VARV (~90% identical) [8]. VACV expresses approximately 200 genes that have classically been divided into early (0–1.5 h), intermediate (1–3 h), early/late and late (>3 h) classes, but recent data suggests that early genes can be subdivided into two groups, the earliest being called immediate-early [1,9]. In general, VACV transcription proceeds in three phases [1]:
  • The immediate-early- and early-expressed proteins include enzymes and factors needed for DNA replication, intermediate gene expression and host defense modulators (virulence factors);
  • In the intermediate phase mainly trans-activating factors for late gene transcription are expressed;
  • The late genes encode for major membrane and core proteins that are contained within the viral particle (virion).
Immunization with VACV confers protection against smallpox owing to a multispecific humoral and cellular immune response. Both antibody and T-cell immunity remain detectable for decades following VACV immunization [1015]. The general consensus is that cellular and humoral immunity are both key for poxvirus clearance [16,17], while humoral immunity is key in conferring protection from reinfection.
Vaccinia virus gene expression at both RNA and protein levels has been intensely investigated [1]. Methods commonly utilized for transcriptional analyses of VACV genes include northern blot [18], 5′-end extension analysis [19] and RNA protection assays [20]. There are several advantages of these methods – in particular, their high sensitivity of detection. On the other hand, these methods tend to be very labor-intensive and therefore impractical for measuring large sets of genes.
Until recently, experimental results on expression kinetics were available for only about two thirds of the annotated ORFs in the VACV WR genome. A study based on canonical promoter motifs, performed by Lefkowitz and colleagues, predicted the kinetic expression for as many as 46 additional ORFs [201]. Predictions were not possible for another 23 ORFs lacking prototypic promoter sequences. Despite this wealth of data in the literature, the experimental settings and methodologies used were highly diverse, making comparisons between the studies difficult. For example, some ORFs, such as I3L [21,22], D5R [23,24] and A36R [25,26], have been denoted as early/late because different studies have suggested different temporal ORF expression.
More recently, the availability of microarray technology has offered an opportunity to experimentally address, in a comprehensive and systematic fashion, the levels and kinetics of VACV ORF transcription [9]. This analysis yielded, for the first time, a complete map of VACV gene expression, including experimental expression data for 69 ORFs that had not been previously characterized. To group expression profiles as a function of time postinfection in an unbiased manner, a hierarchical clustering analysis based on relative expression levels was performed. It was found that segregation into four clusters provided the most reproducible grouping of genes. Most strikingly, we found a clear division of early gene expression into two previously unreported discrete clusters, which we denoted as immediate-early and early genes. More than half of these genes were of unknown function. The largest fraction of the immediate-early genes with known functions was associated with immune evasion/virulence. The early class was the largest by number, containing 73 genes. A late class of 60 genes was also clearly identified. Finally, an early/late class of 26 genes exhibited onset of transcription typical of early genes, but with sustained expression at late times, similar to the late genes (Figure 1A).
Figure 1
Figure 1
Kinetic and functional categories of vaccinia virus antigens either contained within vaccinia virus genome and virion or targeted by adaptive immunity: CD8 and CD4/antibody target different sets of viral antigens
At the protein level, immunohistochemistry [27] and western blot [28] approaches have been used to analyze the expression of many VACV-derived proteins. Alternatively, when specific antibodies are unavailable, viruses containing genes linked with a protein tag (e.g., GFP) can be generated, which makes protein detection possible [26,29,30]. These approaches are highly specific and sensitive, and immunohistochemical analysis can, in addition, provide information on the cellular location of the proteins studied. However, neither a panel of antibodies specific for all VACV ORFs, nor and a systematic comparison of all ORFs at the protein level, is currently available.
Several independent studies examined the composition of the VACV virion by using mass spectrometry analysis, resulting in the identification of a total of 93 VACV proteins [3133]. The majority of the proteins were membrane proteins, structural/core proteins and proteins involved in regulating transcription. Interestingly, several host proteins associated with vaccinia virus intracellular mature virion particles (C22L, E3L and N1L) were also identified. A subset of 51 proteins was identified by all three studies. In terms of relative abundance within the virion [31,32], the majority of the most abundant proteins are core proteins (F17R, A4L, A3L, A10L, A27L, A14L, D8L, H3L and A13L) and only one is a transcription protein (L4R).
With these data one can examine the correlation between protein abundance in the virion and mRNA expression levels. Specifically, we compared the average relative abundance, as described by Chung et al. [31] and Resch et al. [32], with average mRNA expression levels for each ORF identified in the microarray analysis [9]. Of the 21 (top 10% of all ORFs) most abundant proteins in the virion (Supplementary Table 1, see online toc/fmb/5/2), five viral proteins (H5R, A10L, A13L, A17L and F17R) were also found within the top 21 (10%) expressed ORFs mRNAs at the 4 or 24 h time point.
These results emphasize how the highest-ranking ORFs, in terms of mRNA levels, do not necessarily correspond to the highest-ranking proteins in terms of expression within virions. Several investigators have previously reported a similar lack of correlation [34], and attributed this result to differences in RNA transcription rates and protein stability. This finding is of relevance in the analysis of the antigen targets of CD8, CD4 and antibody responses, described in the present review, as discussed in more detail in the following sections.
The past few years have witnessed a quantum leap in our understanding of the molecular targets of adaptive immune responses against poxviruses. More than 40 papers defining the targets of immune responses in mice and humans have been published in the last 5 years, and additional papers are forthcoming [3576]. A broad picture has started to emerge that defines which protein antigens are targeted by CD8+ and CD4+ T cells and antibody (Ab) responses and their interconnection with mRNA and protein expression, as described in more detail in the following sections [9,3133,77]. For CD8+ T cells, in most cases, the minimal peptide that is immunogenic and the restriction element have been defined (Supplementary table 2A) [41,46,47,50,5254,5862,66,67,7175]. In the case of class II epitopes, a number of studies have defined targets of immune responses [40,49,51,56,57,68,70]. In some cases, while the protein antigens recognized by immune responses were identified, the exact epitopes and their restriction were not mapped (Supplementary Table 3B). However, many class II restricted CD4+ epitopes derived from poxviruses have been identified and mapped (Supplementary Table 3A) [40,49,51,56,57,68].
The large size of many poxvirus genomes has precluded a systematic search of all potential epitopes using comprehensive series of overlapping peptides and blood samples from exposed donors (or HLA-transgenic mice), an approach used successfully in characterization of CD8 and CD4 epitopes from viruses with smaller genomes, such as HIV [7880] and influenza [81]. Instead, some poxvirus investigators have relied on bioinformatic prediction tools to reduce the number of potential epitopes to be tested [8,56,57], or have limited their studies to particular proteins already known or suspected to be immunogenic [68]. Whole-genome expression library studies of the human T-cell response to vaccinia proteins have appeared, but these generally have not included fine mapping at the epitope level [49,51]. A different approach has been used in a few studies, in which mass spectrometry was employed to identify peptide antigens naturally processed and loaded onto MHC proteins in poxvirus-infected cells [68].
The Immune Epitope Database and Analysis Resource (IEDB) [8286,202] is an online freely accessible resource that catalogs immune epitope data relating to infectious diseases and allergies and, in the future, transplant antigens and autoimmunity. Meta-analyses of epitope data were recently performed for influenza A [87], mycobacteria [88,89], anthrax/botulinum toxins [90] and Plasmodium [91]. Herein, we present a similar analysis of poxvirus-derived epitopes. We utilized the IEDB, which has inventoried all immune epitope data found in the scientific literature, and then reviewed the original papers.
According to the data assembled in the IEDB, 246 distinct epitopes restricted by MHC class I and 61 distinct epitopes restricted by class II have been identified following viral infection (data following DNA vaccination were not included). By contrast, only nine different antibody epitopes have been mapped (Table 1). In terms of the hosts of the immune responses from which the epitopes were defined, a total of 145 class I epitopes were identified in humans and/or HLA-transgenic mice (six were recognized by both human and transgenic mice) and 103 epitopes were identified in nontransgenic mice (two were recognized by both transgenic and wild-type mice) (Supplementary Table 2A). Regarding the MHC class II epitopes, a total of 43 were identified in humans and 18 in mice (Supplementary Table 3A). Of the nine antibody epitopes, five were identified in mice and four were unknown, as the host utilized to raise the monoclonal antibodies was not described in the relevant publication (Table 2). Most, if not all, defined epitopes were derived from VACV and, accordingly, in the analysis described herein we have focused on VACV epitopes. It should be noted that there are sequence differences between VACV strains and, while mouse work has been done largely with the WR strain, mapping in humans is based on Dryvax immunization. We estimate that less than 10% of mapped epitopes differ between these strains. Having said this, there is also evidence that, even if an epitope is conserved in two strains, its immunogenicity is not guaranteed [74].
Table 1
Table 1
Defined poxvirus epitopes*.
Table 2
Table 2
Vaccinia virus-specific B-cell epitopes as described in the literature.
Initially, CD8+ T-cell epitopes were identified for the purpose of tracking T-cell responses following immunization and to evaluate new and/or safer smallpox vaccines. Owing to the high prevalence of HLA-A*0201 in donor cohort populations, these studies were focused on the identification of HLA-A2-specific epitopes by selecting and testing peptides based on HLA-A*0201 binding motifs, leading to the identification of six unique HLA-A*0201 restricted epitopes [3,67,72].
However, while these studies shed some light on the VACV CD8+ T-cell response, they covered only a fraction of the VACV genome. Several approaches were used to identify the complete CD8+ T-cell response against VACV. More elaborate studies identified a total of 16 epitopes in humans using polypeptide fragments from a library of VACV genomic DNA to screen cloned and bulk VACV-specific CD8+ T cells [50]. A series of studies compared the epitope prediction approach with expression library approaches. Initial studies utilizing an expression library approach to study CD8+ T-cell epitopes from VACV WR in the H-2b mouse model led to the identification of five different epitopes that accounted for approximately 40% of the response [74]. A subsequent study in the same system, using the bioinformatic approach, identified 49 different epitopes, including the five epitopes identified with the expression library approach, which account for approximately 95% of the total response to VACV infection in vivo, as judged by comparing the fraction of CD8+ T-cells derived from VACV-infected mice that recognized in vitro either a pool of the 49 epitopes or VACV-infected antigen-presenting cells (APCs) [58]. Similar results were obtained in the H-2d system [60,75]. Furthermore, independent studies by Mathew et al. and Cornberg et al. identified three more unique mouse epitopes restricted by Db and Kd molecules [41,53], resulting in a total of 103 unique murine CD8+ T-cell epitopes.
Based on these results, the epitopes restricted by human HLA molecules were investigated further. More than 6000 peptides from putative vaccinia ORFs predicted to bind the common molecules of the HLA-A1, -A2, -A3, -A24, -B7, and -B44 supertypes were screened with peripheral blood mononuclear cells of 31 vaccinees. A total of 49 epitopes derived from 35 different VACV antigens were identified [59]. These antigens were expressed predominantly early during infection, although some late antigens were also recognized. This finding may be a result of limited viral gene expression (mostly early genes) in APCs (and lymphocytes), as VACV infection of dendritic cells is abortive [9295], suggesting that recognition of early VACV antigens maybe be an effect of direct priming. Most epitopes were conserved in the genomes of VACV strains WR and MVA as well as VARV, supporting their potential use in vaccine and diagnostic applications. Screening this peptide panel for cytotoxic T lymphocytes from VACV-infected HLA transgenic mice, we identified 14 HLA-A*0201-, four HLA-A*1101- and three HLA-B*0702-restricted epitopes from over 20 distinct proteins [62], further enhancing the number of HLA-restricted epitopes available for study.
Several independent studies identified another nine HLA-A*0201 epitopes [46,61,66,71], as well as two HLA-B7 epitopes [71], by using different binding prediction algorithms and testing human donors. Also, mass spectrometry has been used to identify VACV-derived peptides from among the pool of peptides eluted from MHC class I molecules isolated from VACV-infected B-lymphoblastoid cell lines. In an early study, a single VACV-derived peptide bound to HLA-A*0201 was identified, but no immunological characterization was described [46]. A recent study by another group used a novel stable-isotope tagging strategy to identify VACV-derived peptides, and described a total of 12 HLA-A*0201-bound naturally processed VACV peptides, including the one found earlier, and three HLA-B*0702-bound VACV peptides [48]. All 12 HLA-A*0201 peptides, including seven that had not been previously described, were demonstrated to be recognized by vaccinated donors and, thus, represent bonafide CD8+ T-cell epitopes.
In summary, these studies show that the CD8+ T-cell response to VACV is broad and diverse, rather than focused on a few antigenic targets.
Parallel studies have investigated the mechanisms that determine which epitopes within an antigen are recognized by class I responses [37]. A comprehensive analysis of 18 viral proteins recognized by CD8+ T cells demonstrated that approximately 1/40 of all possible 9- and 10-mer peptides were high-affinity HLA-A*0201 binders. Peptide immunization and T-cell recognition data from 90 peptides indicated that approximately half of the HLA binding peptides could elicit T-cell responses, and that 1/7 of immunogenic peptides are generated by natural processing. Based on these results, it has been estimated that VACV encodes approximately 150 HLA-A*0201 dominant and sub-dominant epitopes. However, only 15 are actually recognized following VACV infection of HLA transgenic mice. Thus, additional factors restrict the epitope repertoire by a factor of at least ten.
Do differences in expression of different VACV ORFs influence immunodominance? If different patterns and magnitude of ORF expression or transcription influence immunogenicity and immunodominance, these influences would not be expected to depend on the MHC type expressed in the infected host. Accordingly, we defined as immunoprevalent those antigens that were frequently recognized (prevalent) in the context of different MHC molecules, haplotypes or even different species. A recently published analysis of nearly 200 CD8+ T-cell epitopes from H-2d, H-2b and HLA-transgenic mice, as well as humans, revealed that CD8+ T-cell epitopes are not randomly distributed across the VACV proteome [60]. Ten different VACV antigens were described as immunoprevalent, which is defined as being recognized in the context of three or more different MHC class I molecules. By contrast, a set of different antigens was recognized infrequently or not at all.
This analysis is repeated here, encompassing all data from the 20 studies available to date that mapped VACV-specific CD8+ T-cell epitopes (to the best of our knowledge) (Supplementary Table 2A) and further compiled the antigens and the frequency of CD8+ T-cell responses (Supplementary Table 2B). To date, a total of 114 antigens (~50% of the total ORFs) have been shown to be recognized by CD8+ T cells. Once again, it is apparent that this is a nonrandom distribution, with many antigens not being recognized and others being immunoprevalent or frequently recognized across different MHC types, loci and even species. The top 23 (~10% of all ORFs) VACV antigens that represent the most prevalent are listed in Table 3, and are associated with more than three MHC restrictions.
Table 3
Table 3
Prevalent Ag* recognized by CD8 T cells.
Thus, specific features of the VACV antigens, distinct from the characteristics of the epitopes contained within them, also contribute to rendering them more or less immunogenic. In general, prevalent CD8+ T-cell responses preferentially recognize antigens that are expressed early during the viral lifecycle, although some virus late proteins are also recognized (82.6 vs 13%; Figure 1A). This prevalence is surprising because the established paradigm for VACV has been that late genes are poorly immunogenic for CD8+ T cells [96]. The representation of recognized antigens within each functional category did not differ significantly from their representation within the viral genome. However, proteins regulating the viral life cycle seem to be recognized slightly more, and structural proteins slightly less frequently, as compared with their representation in the viral genome (Figure 1B). These data are in agreement with previously published results [34,58,59,62].
Fewer studies have been conducted to identify the targets of VACV-specific CD4+ T cells. In the murine system (C57Bl/6), using a random peptide library of 2146 different peptides, a total of 14 CD4+ T-cell epitopes were identified [57]. Subsequent screening of five selected VACV proteins (B5, A4, A27, B2 and A33), with overlapping peptides covering the entirety of each protein, led to the identification of four more CD4+ T-cell epitopes restricted by H-2b [65].
Several studies in humans have started to highlight a number of antigens and antigenic regions that are targeted by human HLA class II restricted responses [40,49,51,56,68,70]. In some cases the restriction was defined, and the epitope was mapped to a discrete peptide, while in other cases the epitopes were mapped to relatively large antigenic regions, and/or the exact HLA restriction was left undefined.
Tang et al. screened vaccinees for responses to four VACV proteins known to induce protective antibody responses in animals (B5R, A27L, A33R and L1R), and used overlapping peptides to identify three distinct CD4+ T-cell epitopes within A27L [70]. Mistra-Kaulik et al. and Calvo-Calle et al. used an HLA-DR1 binding prediction algorithm covering the complete MVA genome to identify 25 additional CD4+ T-cell epitopes recognized by VACV vaccinated or infected donors [40,56]. The epitopes derived predominantly, but not exclusively, from proteins present in the virion. Seven of the epitopes were shown to be restricted by HLA-DRB1*0101, with the remainder presented by other HLA-DRB gene products [40].
Mass spectrometry of naturally processed peptides eluted from VACV-infected cells has been used to identify CD4+ T-cell epitopes. Three HLA-DRB1*0101 bound peptides, including one novel epitope, were characterized by Strug et al. [68]. As with the CD8+ T-cell epitopes, each of the eluted peptides was shown to represent an actual T-cell epitope recognized by CD4+ T cells from VACV-exposed donors.
Expression libraries have also been used to characterize the targets of the CD4+ T-cell response to VACV. Initial studies by Koelle’s group examined VACV-reactive CD4+ in vitro T-cell lines with VACV protein fragments expressed from a genomic library, and a panel of membrane proteins [49]. CD4+ T cells from three vaccinees reacted with 44 separate antigenic regions in 35 vaccinia proteins, with eight to 20 proteins being recognized per person. The expression of protein in virions was strongly associated with CD4+ antigenicity, as was the case for the bioinformatic studies. A subsequent study [51] used a whole-proteome approach to study 180 predicted ORFs in 11 vaccinees. The most frequently recognized ORFs were present in virions, including A3L and A10L (core proteins), WR148/A25L, H3L (a membrane protein), D13L (a membrane scaffold protein) and L4R (a nucleic acid-binding protein). Serum immunoglobulin G profiling demonstrated a diverse response directed to membrane and nonmembrane antigens. These seminal results are consistent with the general assumption that abundantly expressed structural proteins are immunodominant for CD4+ T cells.
A compilation of all antigens recognized in humans and mice on the basis of the data from several published reports [40,49,51,56,57,65,68,70] is summarized in Supplementary Table 3B and demonstrated that a total of 133 antigens are recognized by CD4+ T cells. This illustrates that the CD4+ T-cell response against VACV is directed against a large number of viral proteins. The top 21 antigens (approximately 10% of all ORFs), were recognized by more than 40% of all tested donors (Table 4). Analysis of their structural and functional characteristics revealed a significant preference for late antigens (Figure 1A), as well as structural proteins, compared with their representation in the viral genome (Figure 1B). This is in contrast to CD8+ T-cell responses as described previously (early, regulatory proteins) and highlights fundamental differences in immune responses of CD4+ and CD8+ T-cell responses to complex pathogens.
Table 4
Table 4
Top 21 antigens (>40% of tested donors) recognized by CD4 T cells.
The human Ab response to the smallpox vaccine is highly diverse and redundant [39]. Owing to the large size and existence of two distinct virion surface forms, antibody responses target numerous VACV antigens. These have been comprehensively identified using protein microarrays [42,45] and primary vaccinated donors [44]. Supplementary Table 4 lists all targets of Ab responses identified by all published studies to date. Several studies focusing on selected viral proteins (B5R, A33R, A56R, A27L, H3L and L1R) screened large cohorts of vaccinated donors and confirmed their importance as targets of the Ab responses [55,63,64]. While there is significant variability in the profile of targets recognized, a subset of 19 antigens is frequently recognized both in donors receiving primary immunizations and in those receiving boost immunizations [39,44,45]. These antigens are listed in Table 5 and were recognized by more than 20% of tested donors. Not surprisingly, Ab responses recognize mainly late-expressed viral genes and structural proteins (Figure 1A & B), most likely because they target virions, the main components of which are core proteins [3133].
Table 5
Table 5
Top 19 antigens (>20% of tested donors) recognized by B cells.
This list includes the six antigens known to be targets of neutralizing or protective Abs described in more detail in the following sections. Ab-mediated protection is thought to occur both by neutralizing the initial virus inoculum and by limiting the spread of virus particles within the host after infection is initiated [97]. Presence on the surface of the virion is a prerequisite for being a neutralizing Ab target. There are five known neutralizing Ab targets: L1R, H3L, A27L, D8L and B5R [97]. Interestingly, antibodies against the A33R surface protein are protective, but not neutralizing [97,98]. Abs to these antigens are very frequently observed in vaccinated humans, but the antigens are not present on the virion surface and do not seem to contribute to protective immunity. Studying such antigens would be of interest, since their frequent recognition makes them good candidates for diagnostics. There are additional surface proteins, for which it is yet unclear whether they are neutralizing and/or protective Ab targets. Also included in Table 5 is A56R, which is a target of Ab responses in smallpox vaccine-immunized mice and humans [42,44]. However, immunization against A56R was not protective [98], in contrast to immunization against B5R and A33R [98]. Finally, the A14L antigen is also of note; this is an abundant surface protein [31] that has only 14 amino acids exposed as a loop between two transmembrane domains [99]. It has been identified as an antigenic target in vaccinated humans [39,44], and we have shown that IgG responses to A14L correlate with neutralizing Ab levels in vaccinees [39]. Despite the wealth of information available regarding the targets of Ab responses, little is known about the actual epitopes recognized, which are listed in Table 2. This is most likely owing to the fact the most B cell epitopes may not be linear and can encompass secondary and tertiary structures and, therefore, are more difficult to identify.
As described in the previous sections, a substantial body of knowledge is now available relating to the antigens and epitopes recognized by CD4, CD8 and Ab responses. Based on this knowledge, we started to examine whether any significant correlation existed between the types of antigens recognized by the various arms of adaptive immune responses and expression patterns.
In the case of CD8+ T-cell responses, we detected the most significant correlation between antigens containing epitopes and mRNA levels at the relatively early 4 h time point. A mean mRNA expression ranking (MER) was calculated by taking the average of individual mRNA rankings for each ORF, as reported by Assarsson et al. [9]. Hence, a low number corresponding to high expression levels (e.g., a ranking of ten corresponds to the tenth highest expression level). The MER of the 23 most prevalently recognized ORFs was significantly higher (MER = 80) compared with the remaining antigenic ORFs (MER = 99) or nonantigenic for CD8+ (MER = 126) (Figure 2A). At 24 h, the correlation was less pronounced, with MERs of 95, 93 and 126 for the prevalent, recognized and nonantigenic groups, respectively. Performing a similar analysis by correlating antigenicity with median ranking of the protein abundance in the virion, as detected by the proteomic analysis, we found that the MER of CD8+ T-cell responses did not vary significantly between prevalent (MER = 145), recognized (MER = 128) and nonantigenic (MER = 145) ORFs. No correlation was observed between CD8+ T-cell targets and abundance in virions, as determined by proteomic analysis. These data are in agreement with the finding that, in general, early proteins that are not found in virions are the best source of CD8+ T-cell epitopes [57].
Figure 2
Figure 2
Vaccinia virus mRNA early expression pattern correlates with CD8 T-cell responses, whereas late expression correlates with CD4 and antibody responses
By contrast, a similar analysis with the ORFs recognized by CD4+ T cells revealed a different pattern. Median mRNA expression levels at 4 h of the top 21 protein antigens recognized by CD4+ T cells (MER = 112) [57,65] did not differ from the remaining antigenic proteins recognized by CD4+ T cells (MER = 107) or nonantigenic ORFs (MER = 112). By contrast, a good correlation was detected with mRNA levels at the 24 h time point, with a MER of 74 for the most prominent CD4 antigens, 103 for the remaining CD4 antigens and 117 for the non-CD4 antigenic ORFs (Figure 2B). CD4 responses also demonstrated a similarly high correlation with protein abundance in the virion, with the top 21 ORFs recognized by CD4+ T-cell responses being associated with a much lower ranking (MER = 71) compared with remaining (MER = 109) or nonantigenic (MER = 145) ORFs. Again, the analysis based on expression and virion protein levels was in broad agreement with that done using previously published data on the function and timing of VACV gene expression [9]. Specifically, CD4+ T cells tend to recognize structural proteins that are expressed later during infection.
The ORFs recognized by Ab were associated with a pattern similar to that for CD4+ T cells. The mRNA rankings of ORFs encoding proteins recognized by Ab responses [39] demonstrated little correlation at the 4 h time point (shown in Figure 2C). Specifically, mRNAs encoding these antigens were expressed at 4 h at levels (MER = 117) comparable to the remaining (MER = 98) or nonantigenic ORFs (MER = 107). By contrast, a good correlation was detected with mRNA levels at the 24 h time point with a MER of 73 for the most prominent CD4 antigens, 102 for the remaining CD4 antigens, and 117 for the nonantigenic CD4 ORFs (Figure 2B). Ab responses also demonstrated a rather dramatic correlation with virion protein abundance, with the top 19 ORFs being associated with a high ranking (MER = 44) compared with either the remaining (MER = 107) or nonantigenic (MER = 145) ones.
In conclusion, we found that the general pattern of VACV antigens recognized by CD4+ and CD8+ T-cell responses is different. CD8+ T-cell responses correlate with early mRNA levels of the specific antigens recognized and not protein levels in virions. By contrast, the antigens recognized by CD4+ T cells and Ab tend to correspond to antigens whose mRNAs are expressed at late time points, and also with antigens expressed in high amounts in viral particles [57].
At the same time as the above studies were done, an analysis of the potential correlation between Abs and CD4+ T-cell responses was carried out. A simple model of CD4+ T-cell–B-cell linkage would predict that T cells could deliver help to B cells specific for any protein antigen present in the viral particle. Unexpectedly, in a recent study, analysis of the Ab and CD4+ T-cell response specificities to VACV revealed that many of the CD4+ T-cell responses identified in an unbiased screen were specific for proteins that were also targets of Ab responses, consistent with a deterministic linkage (p < 0.001) [65].
This linkage was demonstrated by direct peptide immunizations with CD4+ VACV epitopes. Mice vaccinated with a VACV-specific CD4+ T-cell epitope (I1L21–35), demonstrated a tenfold increase in the total anti-VACV Ab response as measured by a standard VACV ELISA. Unexpectedly, virus-neutralizing Ab titers were unimproved in VACV-infected mice preimmunized with IlL21–35 when compared with unprimed mice. While I1L is a viral virion core protein and, therefore, not itself a neutralizing Ab target, I1L–specific CD4+ T cells were expected to provide intermolecular help to all B cells specific for VACV viral particle proteins and, thereby, boost neutralizing Ab titers. Surprisingly, when serum samples were probed for the detailed antigen specificities of the Ab response using VACV protein microarrays, we found the increased Ab response was exclusively against I1L and not other VACV. These data led us to the conclusion that purified CD4+ T cells specific for a given antigen (I1L, for example), only provided help for Ab responses to that same antigen. In contrast to the standard model, these data indicate that individual proteins are the primary unit of immunological recognition for VACV and suggest that while CD4+ and CD8+ T-cell responses recognize different antigens, CD4+ and Ab responses tend to recognize the same structures.
This data led to a revision of the classic model of antigenic bridge in cognate recognition, at least in the case of VACV. It was also demonstrated that the knowledge of the serological targets of VACV responses could be used to predict CD4+ reactivity. Specifically, four of five antigens predicted to have CD4+ T-cell epitopes on the basis of recognition by serum from VACV infected mice were indeed found to have these epitopes. By contrast, of two antigens not recognized by antibody, neither was found to have a CD4+ T-cell epitope [65], demonstrating that knowledge of the serological response can be used to support CD4+ T-cell epitope identification.
The identification of a large array of different VACV-derived CD8+ T-cell epitopes offered a unique opportunity to systematically analyze the correlation between protective efficacy and variables such as kinetics of expression and function of viral proteins, binding affinity to MHC molecules, immunogenicity and viral antigen processing/presentation. In a recent study, 49 different H-2b restricted epitopes were tested for their ability to protect peptide-immunized C57Bl/6 mice from lethal intranasal challenge with VACV [100]. The epitopes varied greatly in their ability to confer protection, ranging from complete protection with minimal disease to no protection at all (Table 6). The function or kinetics of the viral antigen expression did not correlate with protective efficacy. However, binding affinity partially predicted protection efficacy and ultimately epitope immunogenicity and recognition of infected cells offered the best correlation. Thus, while antigen expression, both at the mRNA and protein levels, greatly influence the antigenic focus of the immune response, the intrinsic protective capacity of each epitope is directly dependent on its MHC binding affinity, the efficiency of its generation by antigen processing, and the number of T cells that can recognize it in the naive repertoire. To date, no protective capacity has been associated with reported CD4+ T cell or antibody epitopes.
Table 6
Table 6
Protection efficacy of CD8+ epitopes
Owing to the rapid progress in knowledge in the last few years, VACV has become a useful model to study adaptive immune responses against complex pathogens, both in murine systems and in humans. This review summarizes and highlights key findings based on identification of VACV antigens targeted by the immune system (CD4, CD8 and Ab) and the complex interplay between these responses. More specifically, recent studies provided a first complete inventory of the mRNA expression patterns, and proteomic studies provided data relating to expression at the protein level. In parallel, additional studies provided an inventory of the epitopes recognized by CD8 and CD4 T cells, and protein array studies also mapped the antigens recognized by antibody responses. The data in the VACV system have started to shed light on the mechanisms that determine which antigen(s) will be targeted by immune responses. CD8 responses, on the one hand, and CD4/Ab responses, on the other hand, tend to recognize different antigens associated with discrete characteristics, both at the functional and expression kinetic level. While CD8 responses focus on early antigens, CD4 and Ab responses focus on late and structural proteins. When this data was correlated with the mRNA and proteomic data, it was found that CD8+ T-cell responses correlate with early mRNA levels and not protein levels in virions. By contrast, the antigens recognized by CD4+ T cells and Ab tend to correspond to antigens whose mRNAs are expressed at late time points, and also with antigens expressed in high amounts in viral particles. While the mechanisms underlying this apparent dichotomy have not been elucidated, it is likely that direct priming of CD8 responses by infected cells might contribute to the effect, especially since dendritic cells are thought to be only abortively infected [9295] and, thereby, are likely to best present early antigens. Conversely, the recognition of late and structural antigens by CD4 and Ab responses might reflect antigen uptake and presentation by noninfected APCs. Finally, VACV and poxviruses in general are known to express many systems for evasion of immune responses [101], including those that affect antigen presentation pathways [102], and it is possible that these may play a role in shaping the spectrum of T cell and antibody epitopes recognized.
These studies illustrate that immune responses to complex pathogens are highly diverse, broad and multispecific, and that a narrow immunodominance with responses directed against only one or a few epitopes does not exist. Indeed, a recent study of lymphocytic choriomeningitis virus infection in inbred mice [103] has also suggested that the narrowness of immunodominance has been overestimated. Having said this, at least for CD8+ T cells, some epitopes are far more immunogenic than others. The CD8+ T-cell immunodominance hierarchies found in two strains of inbred mice after intraperitoneal VACV infection look superficially similar, with both having one dominant epitope that accounts for around 25% of the antiviral response [58,60]. There is also evidence that immunization route can sharpen this inequity between epitopes: in C57Bl/6 mice cells that recognize the most dominant epitope increase in proportion to around 50% of all anti-VACV CD8+ T cells if mice are immunized by a dermal route [74]. Recent work carried out with VACV and lymphocytic choriomeningitis virus has also started to outline two different paths that shape immunodominance hierachies and select the determinants of immune responses. Within a particular antigen, the choice of the epitope(s) that will be recognized is dictated by, in decreasing order of importance, MHC binding, ease of cellular processing and T-cell receptor repertoire [37]. Nevertheless, complex cellular regulatory events, such as immunodomination, might further decrease the epitopes actually recognized, but direct evidence for this in the case of VACV has not yet been found [104].
Of practical relevance, the targets of CD8, CD4 and Ab responses could be, to a certain extent, retrospectively predicted by a combination of tiling array and proteomic analysis. As our knowledge grows, it might be reflected in an increase in predictive accuracy. It is possible that, in the not so distant future, we may be able to combine algorithms predicting which antigens have a high likelihood of being recognized by adaptive responses with algorithms capable of predicting, within a given antigen, which particular epitopes (particularly in the cases of CD8 and CD4) might be recognized and induce protective immunity. In the end, this would translate in an unprecedented accuracy in the prediction of the targets of immune responses to complex pathogens.
While these hypotheses are reasonable, it still remains to be investigated how occasional CD8 responses against late antigens, and CD4 responses against early antigens, are primed and develop, perhaps because of cross-priming of CD8 responses [105108], and direct priming by infected APCs of CD4 responses. Furthermore, if the pathways that lead to priming of CD4 and CD8 responses are largely nonoverlapping, it will be important to clarify how these patterns intersect, and how CD4 help is effectively provided to CD8 T cells. Another issue relating to the intersection between different effector pathways is the deterministic linkage between Ab responses and CD4 responses. Thus far, several possible mechanisms have been proposed and are currently under investigation. The fundamental components of this proposed linkage include antigen presentation to B cells in the underlying follicles by professional APCs bridging the subcapslar sinus, followed by the interaction of B cells with CD4+ T cells at the T/B cell boundary [65]. Taken together, these data suggest that a revision of the classic model of antigenic bridge (direct presentation) might be in order, at least for certain antigenic systems.
In conclusion, the VACV system continues to expand in sophistication. While many important questions remain unanswered and will provide challenges for future research, the detailed knowledge of the nature of the targets of immune responses provided an invaluable tool for researchers to continue to expand our knowledge of the mechanisms at the root of adaptive responses against complex pathogens.
The extensive map of immune epitope reactivity for poxviruses, including the VACV, makes this one of the most well-understood model systems to study human and murine immune responses. Findings from these studies will initially greatly increase our basic understanding of the immunobiology of complex host–virus interactions, including a clearer understanding of antigen selection and effector cell interplay. This knowledge can then be utilized for further development of safe and efficacious vaccines, tailored toward different target populations, and in the development of more sophisticated poxvirus vectors as transgene delivery systems.
Executive summary
  • Due to the rapid progress in knowledge in the last few years, vaccinia virus (VACV) has become a useful model to study adaptive immune responses against complex pathogens, both in murine systems and in humans.
  • Studies have shown that immune responses to VACV are highly diverse, broad and multispecific; narrow immunodominance does not exist.
  • The data in the VACV system has started to shed light on the mechanisms that determine which antigen(s) will be targeted by immune responses.
  • CD8 and CD4/antibody (Ab) responses tend to recognize different antigens associated with discrete characteristics, both at the functional and expression kinetic level – CD8 recognize early antigens; CD4 and Abs recognize later antigens.
  • VACV, and poxviruses in general, are known to express many systems for evasion of immune responses, including those that affect antigen presentation pathways. Thus, it is possible that these may play a role in shaping the spectrum of T cell and antibody epitopes recognized.
  • It is as yet unclear as to how CD8 responses against late antigens, and CD4 responses against early antigens, are primed and develop; perhaps due to cross-priming of CD8 responses and direct priming by infected antigen-presenting cells of CD4 responses.
  • Another issue relating to the intersection between different effector pathways is the deterministic linkage between Ab responses and CD4 responses – characterizing these relationships should be a future priority.
  • In the future, antigenic targets of CD8, CD4 and antibody responses may be retrospectively predicted by a combination of tiling array and proteomic analysis; as our knowledge grows, so too should the predictive accuracy of these tools.
  • It is possible to combine computational algorithms predicting which antigens have a high likelihood of being recognized by adaptive responses with algorithms capable of predicting which epitopes might be recognized and induce protective immunity.
Supplementary Material
The authors gratefully acknowledge the helpful contributions of the following subject matter experts: Lichen Jing, Jay Greenbaum, Erika Assarsson, Carla Oseroff, John Sidney, Michael Croft, Shahram Salek-Ardakani and Howard Grey.
Financial & competing interests disclosure
The La Jolla Institute of Allergy and Immunology (LIAI) VACV work is supported by NIH/NIAID, contract number: N01-AI-40024 and the Immune Epitope Database (IEDB) work is supoorted by NIH/ NIAID, contract number: HHSN2662004000 0 6C. This research also is partially supported by NIH AI-067496 and the Poxvirus T-cell Vaccine Discovery Consortium of the Bill and Melinda Gates Foundation Cooperative AIDS Vaccine Discovery program (author DMK). The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.
No writing assistance was utilized in the production of this manuscript.
Contributor Information
Magdalini Moutaftsi, Vaccine Discovery, La Jolla Institute for Allergy & Immunology, La Jolla, CA, USA.
David C Tscharke, Laboratory of Viral Diseases, National Institute of Allergy & Infectious Diseases, Bethesda, MD, USA.
Kerrie Vaughan, Vaccine Discovery, La Jolla Institute for Allergy & Immunology, La Jolla CA, USA.
David M Koelle, Department of Medicine, University of Washington, Seattle, WA, USA.
Lawrence Stern, Department of Pathology, University of Massachusetts Medical School, Worcester, MA, USA.
Mauricio Calvo-Calle, Department of Pathology, University of Massachusetts Medical School, Worcester, MA, USA.
Francis Ennis, Center for Infectious Disease & Vaccine Research, University of Massachusetts Medical School, Worcester, MA, USA.
Masanori Terajima, Center for Infectious Disease & Vaccine Research, University of Massachusetts Medical School, Worcester, MA, USA.
Gerd Sutter, Department of Virology, Paul-Ehrlich-Institut, Munich, Germany.
Shane Crotty, Vaccine Discovery, La Jolla Institute for Allergy & Immunology, La Jolla CA, USA.
Ingo Drexler, Institute of Virology, Technische Universitat, Munich, Germany.
Genoveffa Franchini, Animal Models & Retroviral Vaccines Section, National Cancer Institute, Bethesda, MD, USA.
Jon W Yewdell, Laboratory of Viral Diseases, National Institute of Allergy & Infectious Diseases, Bethesda, MD, USA.
Steven R Head, DNA Array Core Facility, The Scripps Research Institute, La Jolla, CA, USA.
Janice Blum, Department of Microbiology & Immunology, School of Medicine, Indiana University, Indianapolis, IN, USA.
Bjoern Peters, Vaccine Discovery, La Jolla Institute for Allergy & Immunology, La Jolla CA, USA.
Alex Sette, Vaccine Discovery, La Jolla Institute for Allergy & Immunology, La Jolla CA, USA.
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