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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Parasite Immunol. Author manuscript; available in PMC 2012 April 16.
Published in final edited form as:
PMCID: PMC3327129
NIHMSID: NIHMS240384

Meta-analysis of immune epitope data for all Plasmodia: overview and applications for malarial immunobiology and vaccine-related issues

Summary

We present a comprehensive meta-analysis of more than 500 references, describing nearly 5000 unique B cell and T cell epitopes derived from the Plasmodium genus, and detailing thousands of immunological assays. This is the first inventory of epitope data related to malaria-specific immunology, plasmodial pathogenesis, and vaccine performance. The survey included host and pathogen species distribution of epitopes, the number of antibody vs. CD4+ and CD8+ T cell epitopes, the genomic distribution of recognized epitopes, variance among epitopes from different parasite strains, and the characterization of protective epitopes and of epitopes associated with parasite evasion of the host immune response. The results identify knowledge gaps and areas for further investigation. This information has relevance to issues, such as the identification of epitopes and antigens associated with protective immunity, the design and development of candidate malaria vaccines, and characterization of immune response to strain polymorphisms.

Keywords: malaria, epitope, Plasmodium, vaccine

Malaria, the Immune Epitope Database (IEDB) and Meta-Analysis

Human malaria is a mosquito-borne disease caused by protozoa of the Plasmodium species (Plasmodium falciparum, P. vivax, P. ovale and P. malariae), of these, P. falciparum is responsible for the most significant morbidity and mortality in humans. Each year, this parasite is responsible for more than 200 million infections, which result in nearly 1 million deaths globally (1). Those most vulnerable for severe and complicated malaria and death are children under the age of five, pregnant women (primigravidae) and immunocompromised individuals, such as those with HIV/AIDS (2,3).

Immunity to malaria is slow to develop and often incomplete (4,5). While anti-disease immunity does exist in endemic areas as a result of repeated infections, memory and protection appear to be short-lived in the absence of continuous parasite exposure. The increase in drug and insecticide resistant strains of P. falciparum renders standard anti-malaria drugs increasingly ineffective against falciparum malaria in disparate geographical regions (6,7). This phenomenon further heightens the sense of urgency for the development of a malaria vaccine, and also emphasizes that parasite variation (mutants within a strain) should be considered in the design of malaria vaccine candidates.

The Plasmodium parasite has a large genome encoding approximately 5300 proteins (8) and a complex multi-stage life cycle. The complexity of the plasmodial life cycle presents both challenges and opportunities for vaccine design. On one hand, this complexity presents many potential target antigens to incorporate into different prophylactic or therapeutic modalities. Indeed, candidate vaccines have targeted all life cycle stages (sporozoite, liver, blood and sexual stage), a number of which are currently in clinical trials (911). However, with the exception of RTS,S (12), candidate vaccines to date have been not completely efficacious (13) and the recent field trials of promising recombinant protein vaccines (11,14,15) suggest that current understanding and vaccine development strategies may be suboptimal. It is also thought that different immune mechanisms target different stages of the parasite life cycle (1619), adding an additional challenge to vaccine development.

Malaria vaccine development may therefore benefit from a combined approach to assessing malarial immunobiology. Both traditional and bioinformatic approaches can enhance our current vaccine efforts and understanding of pathogenesis. Indeed, several bioinformatic resources incorporate information related to malaria and Plasmodium species (20). Among these, the Immune Epitope Database and Analysis Resource (IEDB) provides scientists with a comprehensive repository of immune epitope data and associated analysis tools <www.immuneepitope.org>. The data in the IEDB, which is captured from the peer-reviewed literature (PubMed), is updated quarterly. The database contains antibody and T cell data from human, non-human primate and rodent hosts, and targets epitopes derived from a broad range of organisms, including infectious (bacteria, viruses, fungi, parasites), as well as non-infectious (allergy, autoimmunity, transplant/alloantigen) agents. The database has been designed to capture the immunological and experimental details associated with each epitope.

To enhance the utility of the IEDB for scientific community, we have initiated meta-analyses of all epitope data related to pathogens of interest. To date, the IEDB has completed meta-analyses for several high-profile pathogens – influenza A, Mycobacterium (TB and related species) and Anthrax/Botulinum toxins (2123). These analyses provide a comprehensive inventory of pathogen-specific epitope data, while at the same time, identify knowledge gaps and highlight potential areas for further research. We report here a comprehensive analysis of all malaria immune epitope data as of 31 March 2008. Our literature queries were designed to retrieve all relevant data from the published literature, including all B cell and T cell data, covering all host systems for the pathogen of interest. However, occasionally our queries do miss papers. We encourage the scientific community to help us correct any oversight, by the contacting us through ‘Support’/‘Provide Feedback’ function of the IEDB webpage.

The Nature of Plasmodium Epitopes

A total of 4497 epitopes (unique molecular structures) were retrieved by our search of epitope data related to the Plasmodium genus. Here, an epitope is defined as any structure (peptidic or non-peptidic) interacting with a B cell or T cell receptor, and the term unique molecular structure reference to the total number of non-redundant structures. This total includes 1566 structures associated with positive data (referred hereafter as ‘epitopes’) and 2337 molecular structures only associated with negative data (immunologically un-reactive). The curation of negative data is relevant, as it provides for the identification of non-epitopic (non-immunogenic/antigenic) regions. Overall, the large number of Plasmodium epitopes described in the literature and curated in the IEDB, reflects the intense immunological investigation of the field decades, starting mostly in the late-1980s and early 1990s.

To date, all reported plasmodial epitopes are peptidic in nature. While some epitopes have been derived from well-known lipoproteins, the defined epitope itself is strictly peptidic. Surprisingly, no carbohydrate epitopes have been reported to date. While genomic analysis suggests that Plasmodium species generally lack certain machinery necessary for complex post-translation glycosylation (N- and O-linked) (24), other studies have confirmed the existence of protein glycosylation, albeit at low levels (25). Thus the lack of carbohydrate epitopes is likely a reflection of the difficulty in identifying epitopes of complex biochemical nature, and not necessarily a reflection of lack of a functional role in parasite pathogenesis. Therefore, the role of these moieties has yet to be fully elucidated. To date, the only well-documented plasmodial carbohydrate modification pathway is that of the glycosyl-phosphatidylinositol (GPI) anchors. These modifications are essential for parasite survival and affect such functionally important proteins as CSP, MSP-1, MSP-2, p71 and the 55 kDa merozoite rhoptry antigens (25). Determinants derived from these molecules maybe of interest for future epitope analysis. A vaccine targeting the malaria glycosylphosphatidylinositol toxin has indeed been proposed to prevent severe malaria (26).

Phenotype of Defined T Cell Epitopes

A total of 892 T cell epitopes have been reported for all species within the Plasmodium genus. The CD4+ vs. CD8+ phenotype of most of these (more than 500) was undefined by the authors. However, the effector cell phenotype can in many cases be inferred from the assay used. Accordingly we enumerated CD4+/class II vs. CD8+/class I epitopes as 686 and 157, respectively. The remaining T cell epitopes remained as unassigned. Thus, reported CD4+/class II epitopes out-numbered CD8+/class I epitopes by a ratio of more than 4 to 1. While it is possible to conclude that this apparent disparity may have biologic significance (27), it is more likely that the higher number of CD4+ T cell epitopes may simply reflect the technical ease of certain assays (for example, lymphoproliferation vs. cytotoxicity), or reflect the focus of the scientific investigations performed to date. It is our assessment that the over abundance of CD4+/class II vs. CD8+/class I data is a result of experimental bias, and that this tells us that more work defining CD8+ epitopes is warranted. Indeed, evidence from the literature suggests that both CD4+ and CD8+ T cells contribute to malaria immunity, and CD4+ and CD8+ T cell epitopes often map to similar regions and in many cases overlap (2830).

MHC Restriction of Epitopes

Epitope-specific T cell responses were further characterized in terms of their MHC class restriction (Table S1 in Supporting Information). However, the vast majority of studies focused on only a few haplotypes. In humans, both class I (HLA-A, B) and class II (HLA-DR, DP, DQ) data were present, including certain MHC alleles (HLA-B35, DRB1*1302 and DQB1*1501) that have been associated with protection from severe disease in certain human populations (31,32). However, the majority of defined restrictions were mediated by HLA-A2 or other frequent alleles. This distribution mirrors a general bias in definition of HLA epitopes present in all epitope-related literature. These results suggest that epitopes recognized in the context of a more diverse set of HLA molecules need to be defined, especially for those alleles expressed by populations in malaria-endemic regions. This will be required to support evaluation of vaccines in field studies targeting populations of diverse ethnicities. In mice there a slightly greater array of MHC was tested; however, most responses were either restricted by the H-2d-restricted alleles for class I and H-2d or H-2b-restricted alleles for class II. This bias is reflective of the MHC alleles expressed in the murine strains most frequently utilized in experimental studies.

The Nature of B Cell Epitopes

While it is generally considered that antibody responses against conformational epitopes on Plasmodium antigens are important in anti-malaria immunity, the vast majority of epitopes defined in the literature are actually linear. Of the 896 antibody epitopes captured within the IEDB, only 20 are conformational in nature. This is likely a reflection of the difficulty in defining these epitope types for complex pathogens. Indeed, a large fraction of conformational epitopes defined to date are derived from simpler pathogens, such as viruses, using escape mutants selected by specific antibodies, and this approach is not readily feasible in the case of Plasmodium. It is also possible that the nature of the parasite's genome may contribute to the difficulty in defining non-linear epitopes. Indeed, approximately 40% of the plasmodial genome is enriched in intrinsically unstructured proteins, which are either entirely disordered or disordered in large segments (33). We believe that defining Plasmodium derived discontinuous epitopes will by an important area for future investigation, which will also benefit from high throughput definition of antibody antigen 3D structures, data which to date represents only a tint fraction of the B cell epitope data.

Another important point to consider is that the vast majority of B cell epitope identification comes from the analysis of linear, overlapping peptides using the ELISA technique. This aspect of B cell epitope identification is universal, and not unique to Plasmodium species; indeed, we have found this phenomenon in all meta-analyses performed to date. While efficient and standardized, ELISAs cannot discriminate between low and high affinity binding, and cannot therefore, fully characterize the structural relationship of overlapping peptides, preventing the identification of residues potentially involved in larger conformational determinants. Therefore the B cell epitope data from the literature reflects a bias towards linear epitopes. The IEDB can, and does capture NMR and X-ray structures when these data are reported. However, these data are seldom reported.

The isotype of antibodies recognizing the various epitopes has also been captured in the IEDB, whenever this information was available in the published reports. This issue is relevant in the case of blood stage immunity, since IgG1 and IgG3 in humans (34), as well as IgG2a and IgG2b in mice (35) have been associated with protective immunity. Not surprisingly, we found that the majority of epitope reactivity was defined for total IgG (364), however, IgG1(75), IgG2 (3), IgG2a (6), IgG2b (18), IgG3 (12), IgG4 (1), and IgM (50) isotypes were also described. It was somewhat surprising, though, that IgE epitopes were not reported, given the putative role of this isotype in the control of parasitic infections. A role for this isotype has been implicated in malarial infection (3638).

Interestingly, we also found that more than 200 plasmodial epitopes (c. 14%) are recognized by both B and T cells. And indeed, a survey of the literature shows that certain antigenic determinants have been reported as being recognized by both arms of the immune system in the course of plasmodial infection (3945), including the tandem repeat regions of certain surface proteins (NANP of CSP and EENV of RESA). However, it is also true that many epitopes are identified as 15–20-mer peptides, and that these same peptides are often found to be reactive in both ELISA and proliferation assays (two different epitopes nested within the same peptide). Moreover, many of the well-known plasmodial antigens were first identified by the characterization of humoral immunity; these antigens were then subsequently studied for the identification of T cell epitopes. Thus the phenomenon is likely to result from a combination of biological and experimental factors.

Plasmodium Species and Strain Distribution

Epitope data has been captured from a total of 12 different species within the Plasmodium genus. This includes data from Plasmodium species that represent three of the four known human pathogens (P. falciparum; Pf, P. vivax; Pv and P. malariae, those used in rodent models (P. berghei, P. yoelii and P. chabaudi), as well as those specific to non-human primate models (P. cynomolgi, P. simiovale, P. knowlesi, P. simium, P. brasilianum, P. fragile and P. reichenowi). Table 1 enumerates epitope distribution among all reported Plasmodium species and strains (a separation according to effector phenotype is also provided). The vast majority of epitopes were described for P. falciparum (1373 epitopes records representing some 15 different strains), followed distantly by P. vivax (152 records representing the 2 major strains). For non-human primates 14 epitopes are derived from P. knowlesi and 8 epitopes derived from the six remaining species for which epitope data was reported. For rodent species, the greatest number (89) of epitopes is derived from P. yoelii; followed by P. berghei (53) and then P. chabaudi (44). No epitopes have been reported to date for P. ovale, which has been identified as a fourth species involved in human malaria, and P. vinckei, which is common rodent malaria parasite. Overall, the relative ratio of defined epitopes (nearly 10 : 1 for Pv compared to Pv) reflects, as expected the priority in which the different Plasmodium species have been targeted by immunological investigations.

Table 1
Plasmodium species and strain distribution. Immune epitope distribution among Plasmodium species and strains is given according to three categories: human pathogens (4), species associated with non-human primate models (6) and species associated with ...

Genomic Distribution of Defined Epitopes

To date, epitopes have been reported from antigens expressed in one or more of all major life cycle stages of the plasmodial parasite (150 total unique proteins). Table 2a shows the distribution of antigens associated with each life stage of P. falciparum: the pre-erythrocytic (sporozoite/liver), erythrocytic/asexual (blood) and transmission/sexual (mosquito) stage. Also shown in this table is the number of epitopes reported for each antigen. Not surprisingly, the majority of reported epitopes come from surface antigens expressed during the pre-erythrocytic and erythrocytic stages. Thus far, the majority of epitopes have been defined from circumsporozoite protein (CSP), liver stage antigen 1 (LSA-1), merozoite surface proteins (MSP-1 and MSP-2), sporozoite surface protein 2 (SSP2/TRAP), ring-infected erythrocyte surface antigen (RESA), rhoptry associated protein 1 (RAP-1), apical membrane antigen (AMA-1) and the erythrocyte binding antigen (EBA-175). Epitopes from proteins expressed during the sexual stage have also been reported: ookinete surface protein (P25), gametocyte-specific surface protein (Pfs230), antigen Pfg27/25, 11-1 polyprotein, chitinase, multidrug resistance protein (MRP), sexual stage and sporozoite surface antigen and antigen QF122. Table 2b shows results for P. vivax; a significantly smaller distribution of epitopes and antigens currently exist for this species which reflects the fact that most research efforts to date have focused on P. falciparum rather than P. vivax.

Table 2
Epitope mapping by plasmodial life cycle stage. Epitopes have been reported from antigens expressed in all three life cycle stages of the plasmodial parasite (150 total unique proteins): 2a) shows the distribution of antigens associated with each life ...

It is important to note that the prominence of a given antigen in the epitope data can be attributed to historical and/or experimental factors rather than a true reflection of immunodominance. For example, a large number of epitopes have been defined for CSP and MSP-1, but this does not mean that these are necessarily the only or the most immunodominant proteins. Recent reports in the literature have supported an immunodominant and protective role of CSP (46). However, CSP was the first of the malarial proteins to be cloned, and as a result, significant efforts have been devoted to analysis and reagent development specific for this protein. This point is particularly relevant in the context of past difficulties in generating recombinant Plasmodium antigens for a broader characterization of reactivity of malarial proteins (4749) (Dr Lee, personal communication).

Genome-wide searches for correlates of immunity for vaccine development and sequence comparisons for identifying diagnostic candidates may be of significant interest to those in the malaria community. However, thus far epitopes have been described for only a small fraction of the more than 5000 predicted open reading frames (ORFs) for Plasmodium species, and many investigators are therefore cautious due to the low yield of actionable data from genomic analyses. Controversy currently exists in the malaria community as to the relative value of expending resource and time on the identification of new antigens using this data vs. focusing on the optimization of delivery systems for existing promising candidates (i.e. CSP, MSP-1, and AMA-1). Nevertheless, because it is likely that protective immunity results from the summation of immune responses against multiple antigens/epitopes, genomic data will no doubt play a critical future role in understanding pathogenesis and immunobiology of malaria.

The data reported in the IEDB and analysed herein was also interpreted in a broader context, taking advantage of other database applications, synergistic in scope with the IEDB. To this end, we can coalesce genomic, proteomic and gene expression data (transcriptome), data available in the Plasmodium Genome Resource (PlasmoDB) (50) with the output from our epitope analysis (data not shown). All reported epitopes can thus be aligned to specific expression time points (life cycle stages) and assigned function to the derivative antigens (both at the gene and protein level). Here we can assign both terms associated with gene function (so-called GO terms), as well as terms relevant for identifying roles in pathogenesis. Currently, PlasmoDB houses the complete genome of P. falciparum 3D7, including complete gene expression data. In this way, individual epitopes can be correlated with genes as they are expressed during the process of infection and potentially extrapolate for related species/strains. Ultimately, it is our goal to provide links between the IEDB and PlasmoDB. In the future it may be possible to chart the number of new epitopes discovered per year and determine whether the rate of epitope discovery has increased with the volume of genomic data.

Epitope Reactivity Associated With Different Parasite Life Cycle Stages

We evaluated the relationship between epitope reactivity and life cycle stage. For this, we considered all records in which the immunogen, was the epitope and the antigen used to test reactivity was the whole organism of a specified stage (i.e. sporozoite, schizont, or merozoite) (Table 3a). We also considered records in which the immunogen was the whole organism of a specified stage and the antigen was the epitope (Table 3b). This sort of analysis has implications for identifying epitopes and/or antigens for use in vaccines, as well as diagnostics.

Table 3
Epitope reactivity according to life cycle stage. The relationship between identified epitopes and each of the three plasmodial life cycle stages in terms of demonstrated immune reactivity is presented. (a) All records in which the immunogen, or immunizing ...

A total of 35 epitopes (c. 70% B cell and 30% T cell) were found to generate reactivity specific to sporozoites, 21 to schizonts (all B cell), 18 to merozoites (all B cell), 2 to gametocytes, 2 to schizonts and trophozoites (all B cell), 1 to schizonts and gametocytes (all B cell) and 1 to schizonts and merozoites (all B cell). This includes all Plasmodium species (Table 3a). Some epitopes (shown in bold) were found to generate responses to more than one life cycle stage. As expected, no common epitope reactivity was observed when the whole organism was used as immunogen (Table 3b) for any host species, consistent with the known genetic restriction of protective immunity against malaria. This data may help identify potential targets for incorporation into candidate vaccines or for evaluation of the immunogenicity of candidate whole organism vaccines. Currently, only one epitope (CSP NANP) has been reported that, when used to immunize humans, generated immunity against the whole organism (sporozoites). However, more than 700 different epitopes are recognized by humans following natural infection/exposure to plasmodia (data not shown). These epitopes are derived from more than 40 different sporozoite, liver and/or blood stage (asexual and sexual forms) antigens.

Host Distribution of The Epitope Reactivities

Epitopes were most frequently defined using human hosts (940), followed by murine hosts (689). Smaller numbers of epitopes were defined in non-human primates, as well as in rabbits, rats, guinea pigs and goats (Table 4; a separation according to effector phenotype is also provided). While the majority of epitope identification in humans focused on T cell reactivity, the reverse was true in mice.

Table 4
Host species distribution. The distribution of epitopes (all Plasmodium species) according to the host species in which they were defined is reported. Epitope data are presented for human hosts, murine hosts, including 22 different inbred, transgenic ...

For human epitopes we found a broad distribution of populations from which the data was derived, consistent with the universal nature of the problem of malaria (Table 5; a separation according to effector phenotype is also provided). To date, epitope data has been reported from many countries in which malaria has been defined as problematic including Africa, Central and South America, Asia, as well as N. America and Europe (where many experimental vaccine studies are conducted); from areas of high, medium and low malaria endemicity (hyper-endemic, holoendemic, mesoendemic, etc.) and from subjects of all age groups lsqb;adults, children, infants and neonatesrsqb;. The greatest number of epitopes has been reported from populations within the African continent (633), followed distantly by Indonesia (150), and North America (135), South America (101), Australia (57), Europe (41), Asia (30) and Central America (3) reflecting the relative focus of research efforts. In only a few instances was the geographical assignment of epitopes more generally ascribed to ‘non-endemic region’ or ‘endemic region’ (16).

Table 5
Summary of human epitope data by geographic region. Epitope data are reported for populations from most, if not all, countries in which malaria has been defined as problematic. These include: all parts of Africa, Central and South America, numerous parts ...

As shown in Table 4, in non-human primate models, epitopes were most frequently defined in Aotus monkeys (mostly B cell epitopes in this species) (60), followed by chimpanzees (18), squirrel monkeys (12) and rhesus macaques (7), reflecting that Aotus monkeys are considered good models of P. falciparum and P. vivax blood stage immunity/vaccination (51) and rhesus macaques are considered good models for T cell-mediated immunity. Increased availability of epitope data for NHP species would facilitate the evaluation of candidate vaccines in these models and provide greater understanding of malarial and immunobiology. Only a few epitopes were defined in other NHP species (M. fascicularis, Saki monkeys, Howler monkeys and Red-handed tamarins).

Prominent among rodent models of malaria were those utilizing standard inbred mouse strains, such as BALB/c (365) and C57BL (211) (> 80% of total; data not shown), which are regarded as established models of malaria infection/immunity (P. chabaudi and P. yoelii) or cerebral malaria (P. berghei ANKA) (5254). Outbred mice were more rarely used to define malarial epitopes. Epitopes defined in BALB/c and C57BL mice include those from P. falciparum, P. vivax, P. berghei, P. yoelii, and P. chabaudi. Epitopes have also been defined in rats (P. falciparum and P. berghei), and New Zealand White rabbits (P. falciparum, P. berghei, P. yoelii and P. knowlesi).

Epitope Data Associated With Different Clinical Stages of Malarial Disease

Disease severity and outcome are influenced by a combination of host and parasite-specific factors. Severe clinical disease is more frequently seen in children, the elderly and in those whose immune system has been compromised either by co-infection, pregnancy or malnutrition. Similarly, length of exposure/endemicity of the affected population is associated with disease susceptibility or resistance. To this end, fields within the IEDB have been specifically designed for the capture of patient histories, including age, gender, MHC type, ethnicity/geographical location, disease state/stage, the manner in which the immunogen was encountered (natural exposure/immunization), timing of sample collection relative to episode and parasitaemia level (if provided). This information can then be used to probe for different patterns of epitope recognition between individuals with active disease and those who recovered uneventfully from infection.

Table 6a shows the distribution of reported epitope reactivities according to five defined malarial disease states (see Table S2 in Supporting Information for definitions): healthy-exposed individuals from endemic areas [exposed, no symptoms at time of sampling] (474), uncomplicated falciparum malaria [423], subjects from endemic areas with no clinical histories [exposure-unknown] (192; Pf and Pv combined), uncomplicated vivax malaria (77), healthy-exposed individuals from non-endemic areas [experimentally immunized volunteers/travellers] (34) and severe/complicated falciparum malaria (5). When possible, disease states were further categorized by the stage of disease: acute (parasitaemia; symptomatic at sampling), post (past malaria; clinically immune; convalescent), or unknown (parasitaemic, but no clinical signs/asymptomatic; includes infants (chord blood) of mothers with placental malaria). Table 6b lists all epitopes distinctly identifiable by disease stage (acute or post). Here, only epitopes that were empirically tested for reactivity in both stages are presented.

Table 6
Epitope distribution in malaria disease states. Epitope defined in human populations can be further enumerated according to reported disease states. (a) shows the distribution of reported epitope reactivities according to 5 defined malarial disease states ...

The distribution of epitopes by age of disease shows, not surprisingly, that the vast majority of epitopes were defined for uncomplicated falciparum malaria in adults (273), followed by children and adults combined (120), children (20), pregnant women (13), infants (11) and neonates (4). For uncomplicated vivax malaria 60 epitopes were defined in adults and 33 were described in groups containing adults and children. Of the five epitopes defined for severe/complicated falciparum malaria, four were defined in adults and one in a child. Given the prevalence of severe disease in children, additional epitope identification would be desirable in this group. Finally, the largest number of epitopes was defined in exposed-healthy (asymptomatic) adults (348), followed by adults and children combined (65) and pregnant women (7) from endemic regions.

Recognition profiles were different in non/low-exposure individuals (children < 10 years and naïve travellers), and these were distinguishable from individuals characterized by high-exposure. This finding may be consistent with the reports indicating that rates of malaria in adults are lower in areas of high endemicity, whereas in areas of low exposure/endemicity, there are higher rates of malarial disease (55,56).

Lacking is a better definition of whether recognition of certain epitopes/antigens is associated with different malarial disease states: severe/complicated malaria, cerebral malaria, pregnancy-associated malaria (PAM)/placental malaria and co-infection (HIV/HBV). Epitopes defined during Plasmodium species co-infection is also lacking. Due to the importance of these data for our overall understanding of immunological distinction between mild and severe malaria, further investigation is warranted in this area.

Protective Epitopes and Epitopes Associated With Protective Responses

The IEDB information details natural and experimental exposure/infection and identifies epitopes putatively associated with protective responses. We first searched for protective epitopes, defined as those utilized as isolated molecular structures to immunize and confer protection. Protection was most often defined in vivo as reduction in parasitaemia or as sterile protection (pre-erythrocytic stage). According to this definition and available data, no epitopes defined in humans have been associated with protection from infection and/or disease. This is not surprising as human studies utilizing direct immunization with defined epitopes have been limited.

In rodents, however, more than 30 epitopes (B cell and T cell) have been associated with protection following direct immunization with the epitope itself (Tables 7 and and8).8). These epitopes were mainly derived from P. berghei and P. yoelii (lethal and non-lethal strains), and come from a narrow range of antigenic proteins (CSP, MSP-1, HEP17, EXP-1 and ribosomal phosphoprotein). Interestingly, one protective epitope was defined for P. falciparum 3D7 using an outbred mouse strain. Protective epitopes were also defined for Norway brown rats and New Zealand White rabbits. While slightly more B cell epitopes were reported than T cell epitopes, we found that both B cell and T cell epitopes were associated with protection from disease in these models, as expected based on current knowledge of mechanisms of protective immunity against malaria (2830). The majority of reported protective epitopes were derived from CSP reflecting the fact that this is an extensively studied model protein.

Table 7
Protective T cell epitopes defined in Non-human models (in vivo)
Table 8
Protective B cell epitopes defined in Non-human models (in vivo)

We have also considered two additional classes of epitopes. First, epitopes that are associated with assays linked to protection or neutralization in vitro, such as neutralization, growth inhibition assays (GIA) or antibody dependent cellular inhibition (ADCI), inhibition of sporozoite invasion assay (ISI) or inhibition of liver stage development assay (ILSDA) or CTL. As a further category, epitopes associated with protection in the context of multiple epitope specificities directed against a whole malaria antigen or the whole organism (for example irradiated sporozoites) were also considered (Tables 9 and and10).10). More than 60 B and T cell epitopes that have been identified using humans immunized with sporozoites, and these were derived from CSP, LSA-1, CRA, EXP-1 and TRAP/SSP2. Of those with defined HLA restriction, the majority were DR, followed distantly by A2 and B8.

Table 9
Epitopes associated with protective responses as defined in vitro. Epitopes associated with assays linked to protection in vitro are listed according to sequence, assay type and host species. Assays that demonstrate correlates of protection in vitro broadly ...
Table 10
Reactivity of humans immunized with irradiate sporozoites to epitopes. Reactivities against multiple epitope specificities defined in humans following immunization with whole malarial antigen (irradiated sporozoites) are presented. The data include both ...

It is of interest to determine if any epitopes identified as protective in non-human models (in vivo) were common to those found to be associated with protective responses (in vitro functional assays) in humans, and then ascertain what type of immune responses were measured. Of the protective epitopes identified in non-human models, 10 were common to those identified as being associated with protective responses in vitro (Table 9; in bold) determined most frequently in vitro using neutralization or inhibition assays (such as, ADCI) for antibody-mediated protection, as well as cytotoxicity and inhibition of growth assays for T cell-mediated protection.

Summary of Key Findings

Herein we present a meta-analysis of epitope data related to the Plasmodium genus. We anticipate that this analysis will help establish a broader picture of malaria-related epitope data with relevance for the identification of epitopes and antigens associated with protective immunity, assisting in vaccine design and development, and for the characterization of immune response to Plasmodium variant strains. The results of this analysis are also relevant for the identification of knowledge gaps and areas of further investigation in the field.

More than 1500 different epitope structures are described in the literature. About half are T cell epitopes, and CD4 epitopes out-number CD8 epitopes 4 : 1. This may be a reflection of predominance of CD4+ T helper cell activity in both the blood and liver stages. However, more work defining CD8+ epitopes is warranted particularly since CD8+ T cells are primary effectors of pre-erythrocytic (sporozoite/liver) stage immunity. At the level of MHC restriction, we found low HLA diversity. Most defined epitopes are associated with alleles abundant in Caucasians populations, underscoring the need for the identification of epitopes recognized by a more diverse set of HLA molecules. Likewise for B cell epitopes, a striking experimental bias exists in the favour of definition of linear vs. discontinuous epitopes. We believe that defining Plasmodium-specific discontinuous epitopes will be an important area for future investigation, which will also benefit from high throughput definition of antibody antigen 3D structures.

Looking at the Plasmodium species distribution for human pathogens, the vast majority of epitopes were described for P. falciparum, followed distantly by P. vivax, while in rodents as expected P. yoelii and P berghei constituted the majority of entries. Epitope identification studies may be desirable in several additional Plasmodium species, and in those associated with non-human primates in particular to better correlate mechanisms of immunity and pathogenesis between animal models and human disease. In addition, further epitope identification in P. knowlesi may be of significant interest, given the recent association of this species with human fatality (5759).

Despite the fairly broad distribution of epitopes among malarial proteins, we note that only a small fraction of the more than 5000 predicted ORFs for Plasmodium species have been associated with defined epitopes. It is likely that these results reflect experimental bias rather that an extreme form of immunodominance in responses, as it is well-known that Plasmodium specific responses are broad and multi-specific. Thus, genome-wide searches for correlates of immunity for vaccine development and sequence comparisons for identifying diagnostic candidates may be of significant interest to those in the malaria research community.

Assessing how many epitopes are associated with reactivity to different life cycle stages has implications for identifying target epitopes and/or antigens for use in vaccines. Epitopes have been reported from antigens expressed in all three life cycle stages of the plasmodial parasite (150 total unique proteins), consistent with the long recognized fact that different life stages can be targeted by immune responses. In terms of function of the recognized proteins, the preponderance of reported epitopes was derived from antigens that are expressed at the parasite surface, during the sporozoite stage and/or the asexual erythrocytic stage of the infection. This seems to be true regardless of effector cell (antibody or T cell), and highlights the need for epitope identification in a more diverse set of plasmodial antigens.

The distribution of the hosts from which the epitopes are derived is relevant for malaria vaccine and diagnostic development. Epitopes were most frequently defined using human hosts, followed by murine hosts. In humans to date, epitope data has been reported for populations from most, if not all, countries in which malaria has been defined as problematic and from subjects of all age groups [adults, children, infants and neonates]. However lacking from the human epitope data is a better definition of epitopes associated with different malarial disease states. Further investigation is highly desirable and strongly recommended.

Because fields within the IEDB have been specifically designed for the capture of patient histories, it should be possible in the future to use this information to probe for different patterns of epitope recognition. However, the current data for malaria is not yet comprehensive enough to allow for this analysis, even though interesting trends were noted, and might be confirmed as additional reports are published and included in the IEDB.

While identification of protective epitopes (those that when used as immunogen provide protection against infection/disease) was fairly broad in animal models, no protective epitopes have been defined for humans, However, epitopes recognized in the course of natural infection represent targets for inclusion into epitope-based vaccines. Likewise, analysis of epitopic responses associated with differential activities in in vitro assays, taken as surrogates of protection, will be of significant interest.

One of the most promising applications of the IEDB is for human data relating to clinical trials evaluating the immunogenicity, safety and protective efficacy of different antigens and vaccine formulations. In this application, the IEDB could thus assist the process of vaccine development and testing. The data currently available in the epitope literature is somewhat limited and therefore does not reflect the large number of vaccine trials conducted to date. However, in the last few years a resurgence of interest and activity in malaria research has brought together several different scientific groups, basic scientists, clinical investigators, health organizations and funding agencies. It is possible to speculate that in the future, more data would become available relating to the immunogenicity and efficacy of different vaccine candidates. The paradigm, database structure, curation and analysis strategies developed for the purpose of the present analysis could be easily applied to hosting and curation of detailed immunological data that could be queried at any level of granularity.

Ultimately, it will be interesting to repeat this analysis in 3–5 years to evaluate the growth of epitope data for Plasmodium species, to assess to what extent knowledge gaps have been addressed, and further, to access how such growth correlates with the growth of genomic data. Moreover, tools available on the IEDB webpage, such as ‘Homology Mapping’ and ‘Epitope Conservancy Analysis,’ could be employed for further analysis to assess such things as the potential impact of variants (polymorphism) on Plasmodium immunity and/or to perform cluster analysis to further refine epitope analysis.

Supplementary Material

Acknowledgments

Authors gratefully acknowledge the contributions of Alison Deckhut, Lee Hall and Tonu Wali in the reviewing of initial query material for the analysis. Authors thank the Eukaryotic Pathogens Database (EuPathDB) team, and in particular Dr Gregory Grant, for supplying various proteome, expression, localization, and polymorphism data sets available through PlasmoDB that were used in the meta-analysis. The La Jolla Institute of Allergy and Immunology team is supported by NIH/NIAID, contract number: HHSN26620040006C, under the Immune Epitope Database and Analysis Program. Dr Denise Doolan is supported in part by a Pfizer Australia Research Fellowship.

Footnotes

Please note: Wiley-Blackwell are not responsible for the content or functionality of any supporting materials supplied by the authors. Any queries (other than missing material) should be directed to the corresponding author for the article.

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