Predicted Strain Coverage of a New Meningococcal Multicomponent Vaccine (4CMenB) in Spain: Analysis of the Differences with Other European Countries

Background

A novel meningococcal multicomponent vaccine, 4CMenB (Bexsero^®), has been approved in Europe, Canada, Australia and US. The potential impact of 4CMenB on strain coverage is being estimated by using Meningococcal Antigen Typing System (MATS), an ELISA assay which measures vaccine antigen expression and diversity in each strain. Here we show the genetic characterization and the 4CMenB potential coverage of Spanish invasive strains (collected during one epidemiological year) compared to other European countries and discuss the potential reasons for the lower estimate of coverage in Spain.

Material and Methods

A panel of 300 strains, a representative sample of all serogroup B Neisseria meningitidis notified cases in Spain from 2009 to 2010, was characterized by multilocus sequence typing (MLST) and FetA variable region determination. 4CMenB vaccine antigens, PorA, factor H binding protein (fHbp), Neisseria Heparin Binding Antigen (NHBA) and Neisserial adhesin A (NadA) were molecularly typed by sequencing. PorA coverage was assigned to strain with VR2 = 4. The levels of expression and cross-reactivity of fHbp, NHBA and NadA were analyzed using MATS ELISA.

Findings

Global estimated strain coverage by MATS was 68.67% (95% CI: 47.77–84.59%), with 51.33%, 15.33% and 2% of strains covered by one, two and three vaccine antigens, respectively. The predicted strain coverage by individual antigens was: 42% NHBA, 36.33% fHbp, 8.33% PorA and 1.33% NadA. Coverage within the most prevalent clonal complexes (cc) was 70.37% for cc 269, 30.19% for cc 213 and 95.83% for cc 32.

Conclusions

Clonal complexes (cc) distribution accounts for variations in strain coverage, so that country-by-country investigations of strain coverage and cc prevalence are important. Because the cc distribution could also vary over time, which in turn could lead to changes in strain coverage, continuous detailed surveillance and monitoring of vaccine antigens expression is needed in those countries where the multicomponent vaccine is introduced. This is really important in countries like Spain where most of the strains are predicted to be covered by only one vaccine antigen and the chance for escape mutants to emerge with vaccine use is higher. Based on the observed data, cc213 should receive special attention as it is associated with low predicted strain coverage, and has recently emerged in Spain.     

Comprehensive Sieve Analysis of Breakthrough HIV-1 Sequences in the RV144 Vaccine Efficacy Trial

The RV144 clinical trial showed the partial efficacy of a vaccine regimen with an estimated vaccine efficacy (VE) of 31% for protecting low-risk Thai volunteers against acquisition of HIV-1. The impact of vaccine-induced immune responses can be investigated through sieve analysis of HIV-1 breakthrough infections (infected vaccine and placebo recipients). A V1/V2-targeted comparison of the genomes of HIV-1 breakthrough viruses identified two V2 amino acid sites that differed between the vaccine and placebo groups. Here we extended the V1/V2 analysis to the entire HIV-1 genome using an array of methods based on individual sites, k-mers and genes/proteins. We identified 56 amino acid sites or “signatures” and 119 k-mers that differed between the vaccine and placebo groups. Of those, 19 sites and 38 k-mers were located in the regions comprising the RV144 vaccine (Env-gp120, Gag, and Pro). The nine signature sites in Env-gp120 were significantly enriched for known antibody-associated sites (p = 0.0021). In particular, site 317 in the third variable loop (V3) overlapped with a hotspot of antibody recognition, and sites 369 and 424 were linked to CD4 binding site neutralization. The identified signature sites significantly covaried with other sites across the genome (mean = 32.1) more than did non-signature sites (mean = 0.9) (p < 0.0001), suggesting functional and/or structural relevance of the signature sites. Since signature sites were not preferentially restricted to the vaccine immunogens and because most of the associations were insignificant following correction for multiple testing, we predict that few of the genetic differences are strongly linked to the RV144 vaccine-induced immune pressure. In addition to presenting results of the first complete-genome analysis of the breakthrough infections in the RV144 trial, this work describes a set of statistical methods and tools applicable to analysis of breakthrough infection genomes in general vaccine efficacy trials for diverse pathogens.     

Polyvalent vaccines for optimal coverage of potential T-cell epitopes in global HIV-1 variants

HIV-1/AIDS vaccines must address the extreme diversity of HIV-1. We have designed new polyvalent vaccine antigens comprised of sets of 'mosaic' proteins, assembled from fragments of natural sequences via a computational optimization method. Mosaic proteins resemble natural proteins, and a mosaic set maximizes the coverage of potential T-cell epitopes (peptides of nine amino acids) for a viral population. We found that coverage of viral diversity using mosaics was greatly increased compared to coverage by natural-sequence vaccine candidates, for both variable and conserved proteins; for conserved HIV-1 proteins, global coverage may be feasible. For example, four mosaic proteins perfectly matched 74% of 9-amino-acid potential epitopes in global Gag sequences; 87% of potential epitopes matched at least 8 of 9 positions. In contrast, a single natural Gag protein covered only 37% (9 of 9) and 67% (8 of 9). Mosaics provide diversity coverage comparable to that afforded by thousands of separate peptides, but, because the fragments of natural proteins are compressed into a small number of native-like proteins, they are tractable for vaccines.     

A computational approach for identification of epitopes in dengue virus envelope protein: a step towards designing a universal dengue vaccine targeting endemic regions

A major problem in designing vaccine for the dengue virus has been the high antigenic variability in the envelope protein of different virus strains. In this study, a computational approach was adopted to identify a multi-epitope vaccine candidate against dengue virus that may be suitable for large populations in the dengue-endemic regions. Different bioinformatics tools were exploited that helped the identification of a conserved immunological hot-spot in the dengue envelope protein. The tools also rendered the prediction of immunogenicity and population coverage to the proposed 'in silico' vaccine candidate against dengue. A peptide region, spanning 19 amino acids, was identified in the envelope protein which found to be conserved in all four types of dengue viruses. Ten proteasomal cleavage sites were identified within the 19-mer conserved peptide sequence and a total of 8 overlapping putative cytotoxic T cell (CTL) epitopes were identified. The immunogenicity of these epitopes was evaluated in terms of their binding affinities to and dissociation half-time from respective human leukocyte antigen (HLA) molecules. The HLA allele frequencies were studied among populations in the dengue endemic regions and compared with respect to HLA restriction patterns of the overlapping epitopes. The cumulative population coverage for these epitopes as vaccine candidates was high ranging from approximately 80% to 92%. Structural analysis suggested that a 9-mer epitope fitted well into the peptide-binding groove of HLA-A*0201. In conclusion, the 19-mer epitope cluster was shown to have the potential for use as a vaccine candidate against dengue.     

Vaccines to combat river blindness: expression,selection and formulation of vaccines against infection with Onchocerca volvulus in a mouse model

Human onchocerciasis is a neglected tropical disease caused by Onchocerca volvulus and an important cause of blindness and chronic disability in the developing world. Although mass drug administration of ivermectin has had a profound effect on control of the disease, additional tools are critically needed including the need for a vaccine against onchocerciasis. The objectives of the present study were to: (i) select antigens with known vaccine pedigrees as components of a vaccine; (ii) produce the selected vaccine antigens under controlled conditions, using two expression systems and in one laboratory and (iii) evaluate their vaccine efficacy using a single immunisation protocol in mice. In addition, we tested the hypothesis that joining protective antigens as a fusion protein or in combination, into a multivalent vaccine, would improve the ability of the vaccine to induce protective immunity. Out of eight vaccine candidates tested in this study, Ov-103, Ov-RAL-2 and Ov-CPI-2M were shown to reproducibly induce protective immunity when administered individually, as fusion proteins or in combination. Although there was no increase in the level of protective immunity induced by combining the antigens into one vaccine, these antigens remain strong candidates for inclusion in a vaccine to control onchocerciasis in humans.     

Estimating the total genome length of a metagenomic sample using k-mers

Background

Metagenomic sequencing is a powerful technology for studying the mixture of microbes or the microbiomes on human and in the environment. One basic task of analyzing metagenomic data is to identify the component genomes in the community. This task is challenging due to the complexity of microbiome composition, limited availability of known reference genomes, and usually insufficient sequencing coverage.

Results

As an initial step toward understanding the complete composition of a metagenomic sample, we studied the problem of estimating the total length of all distinct component genomes in a metagenomic sample. We showed that this problem can be solved by estimating the total number of distinct k-mers in all the metagenomic sequencing data. We proposed a method for this estimation based on the sequencing coverage distribution of observed k-mers, and introduced a k-mer redundancy index (KRI) to fill in the gap between the count of distinct k-mers and the total genome length. We showed the effectiveness of the proposed method on a set of carefully designed simulation data corresponding to multiple situations of true metagenomic data. Results on real data indicate that the uncaptured genomic information can vary dramatically across metagenomic samples, with the potential to mislead downstream analyses.

Conclusions

We proposed the question of how long the total genome length of all different species in a microbial community is and introduced a method to answer it.

     

Identification and validation of T-cell epitopes in outer membrane protein (OMP) of Salmonella typhi

This study aims to design epitope-based peptides for the utility of vaccine development by targeting outer membrane protein F (Omp F), because two available licensed vaccines, live oral Ty21a and injectable polysaccharide, are 50% to 80% protective with a higher rate of side effects. Conventional vaccines take longer time for development and have less differentiation power between vaccinated and infected cells. On the other hand, Peptide-based vaccines present few advantages over other vaccines, such as stability of peptide, ease to manufacture, better storage, avoidance of infectious agents during manufacture, and different molecules can be linked with peptides to enhance their immunogenicity. Omp F is highly conserved and facilitates attachment and fusion of Salmonella typhi with host cells. Using various databases and tools, immune parameters of conserved sequences from Omp F of different isolates of Salmonella typhi were tested to predict probable epitopes. Binding analysis of the peptides with MHC molecules, epitopes conservancy, population coverage, and linear B cell epitope prediction were analyzed. Among all those predicted peptides, ESYTDMAPY epitope interacted with six MHC alleles and it shows highest amount of interaction compared to others. The cumulative population coverage for these epitopes as vaccine candidates was approximately 70%. Structural analysis suggested that epitope ESYTDMAPY fitted well into the epitope-binding groove of HLA-C*12:03, as this HLA molecule was common which interact with each and every predicted epitopes. So, this potential epitope may be linked with other molecules to enhance its immunogenicity and used for vaccine development.     

Identification and characterization of merozoite surface protein 1 epitope

Malaria is an important tropical infection which urgently requires intervention of an effective vaccine. Antigenic variations of the parasite and allelic diversity of the host are main problems in the development of an effective malaria vaccine. Cytotoxic T lymphocytes (CTL) directed against Plasmodium falciparum­derived antigens are shown to play an important role for the protection against malaria. The merozoite surface protein 1 (MSP1) is expressed in all the four life-cycle stages of Plasmodium falciparum and did not find any sequence similarity to human and mouse reference proteins. MSP1 is a known target of the immune response and a single CTL epitope binding to the HLA­A*0201 is available for merozoite form. Here, we report the results from the computational characterization of MSP1, precursor (1720 residue) and screening of highest scoring potential CTL epitopes for 1712 overlapping peptides binding to thirty four HLA class­I alleles and twelve HLA class­I supertypes (5 HLA­A and 7 HLA­B) using bioinformatics tools. Supertypes are the clustered groups of HLA class­I molecules, representing a sets of molecules that share largely overlapping peptide binding specificity. The prediction results for MSP1 as adhesin and adhesin-like in terms of probability is 1.0. Results also show that MSP1 has orthologs to other related species as well as having non allergenicity and single transmembrane properties demonstrating its suitability as a vaccine candidate. The predicted peptides are expected to be useful in the design of multi-epitope vaccines without compromising the human population coverage.     

Immunoproteomics of Helicobacter pylori infection and relation to gastric disease

The Gram negative bacterium Helicobacter pylori is a human pathogen which infects the gastric mucosa and causes an inflammatory process leading to gastritis, ulceration and cancer. A systematic, proteome based approach was chosen to detect candidate antigens of H. pylori for diagnosis, therapy and vaccine development and to investigate potential associations between specific immune responses and manifestations of disease. Sera from patients with active H. pylori infection (n = 24), a control group with unrelated gastric disorders (n = 12) and from patients with gastric cancer (n = 6) were collected and analyzed for the reactivity against proteins of the strain HP 26695 separated by two-dimensional electrophoresis. Overall, 310 antigenic protein species were recognized by H. pylori positive sera representing about 17% of all spots separated. Out of the 32 antigens most frequently recognized by H. pylori positive sera, nine were newly identified and 23 were confirmed from other studies. Three newly identified antigens which belong to the 150 most abundant protein species of H. pylori, were specifically recognized by H. pylori positive sera: the predicted coding region HP0231, serine protease HtrA (HP1019) and Cag3 (HP0522). Other antigens were recognized differently by sera from gastritis and ulcer patients, which may identify them as candidate indicators for clinical manifestations. The data from these immunoproteomic analyses are added to our public database (http://www.mpiib-berlin.mpg.de/2D-PAGE). This platform enables one to compile many protein profiles and to integrate data from other studies, an approach which will greatly assist the search for more immunogenic proteins for diagnostic assays and vaccine design.     

Assessment of cathepsin D and L-like proteinases of poultry red mite, Dermanyssus gallinae (De Geer), as potential vaccine antigens

Vaccination is a feasible strategy for controlling the haematophagous poultry red mite Dermanyssus gallinae. A cDNA library enriched for genes upregulated after feeding was created to identify potential vaccine antigens. From this library, a gene (Dg-CatD-1) encoding a 383 amino acid protein (Dg-CatD-1) with homology to cathepsin D lysosomal aspartyl proteinases was identified as a potential vaccine candidate. A second gene (Dg-CatL-1) encoding a 341 amino acid protein (Dg-CatL-1) with homology to cathepsin L cysteine proteinases was also selected for further study. IgY obtained from naturally infested hens failed to detect Dg-CatD-1 suggesting that it is a concealed antigen. Conversely, Dg-CatL-1 was detected by IgY derived from natural-infestation, indicating that infested hens are exposed to Dg-CatL-1. Mortality rates 120 h after mites had been fed anti-Dg-CatD-1 were significantly higher than those fed control IgY (PF<0·01). In a survival analysis, fitting a proportional hazards model to the time of death of mites, anti-Dg-CatD-1 and anti-Dg-CatL-1 IgY had 4·42 and 2·13 times higher risks of dying compared with controls (PF<0·05). Dg-CatD-1 and L-1 both have potential as vaccine antigens as part of a multi-component vaccine and have the potential to be improved as vaccine antigens using alternative expression systems.     

Targeting unique tumor antigens and modulating the cytokine environment may improve immunotherapy for tumors with immune escape mechanisms

Cytotoxic T-cell responses to shared tumor antigens have been characterized for several tumor types, and the MHC-associated peptides that comprise these antigens have been defined at a molecular level. These provide new tools to determine whether immune responses can be generated with these tumor antigens, and there are data to suggest that such immune responses can be generated. However, it is also clear that tumor cells can evade immune responses directed against some shared antigens, by downregulating expression of MHC or of the antigenic protein(s), as well as by more active methods such as secretion of immunosuppressive cytokines. Awareness of these mechanisms of immune escape will help to direct development of the next generation of tumor vaccines. Targeting unique antigens and modulating the cytokine environment likely will be critical to comprehensive vaccine systems in the future. Received: 20 March 1999 / Accepted: 3 May 1999     

These Are Not the K-mers You Are Looking For: Efficient Online K-mer Counting Using a Probabilistic Data Structure

K-mer abundance analysis is widely used for many purposes in nucleotide sequence analysis, including data preprocessing for de novo assembly, repeat detection, and sequencing coverage estimation. We present the khmer software package for fast and memory efficient online counting of k-mers in sequencing data sets. Unlike previous methods based on data structures such as hash tables, suffix arrays, and trie structures, khmer relies entirely on a simple probabilistic data structure, a Count-Min Sketch. The Count-Min Sketch permits online updating and retrieval of k-mer counts in memory which is necessary to support online k-mer analysis algorithms. On sparse data sets this data structure is considerably more memory efficient than any exact data structure. In exchange, the use of a Count-Min Sketch introduces a systematic overcount for k-mers; moreover, only the counts, and not the k-mers, are stored. Here we analyze the speed, the memory usage, and the miscount rate of khmer for generating k-mer frequency distributions and retrieving k-mer counts for individual k-mers. We also compare the performance of khmer to several other k-mer counting packages, including Tallymer, Jellyfish, BFCounter, DSK, KMC, Turtle and KAnalyze. Finally, we examine the effectiveness of profiling sequencing error, k-mer abundance trimming, and digital normalization of reads in the context of high khmer false positive rates. khmer is implemented in C++ wrapped in a Python interface, offers a tested and robust API, and is freely available under the BSD license at github.com/ged-lab/khmer.     

Immunization effect of recombinant P27/30 protein expressed in Escherichia coli against the hard tick Haemaphysalis longicornis (Acari: Ixodidae) in rabbits

We investigated the induction of resistance to Haemaphysalis longicornis infestation in rabbits that had been immunized with recombinant H. longicornis P27/30 protein. The success of immunological control methods is dependent upon the use of potential key antigens as tick vaccine candidates. Previously, we cloned a gene encoding 27 kDa and 30 kDa proteins (P27/30) of H. longicornis, and identified P27/30 as a troponin I-like protein. In this study, rabbits that were immunized with recombinant P27/30 expressed in Escherichia coli showed the statistically significant longer feeding duration for larval and adult ticks (P<0.05), low engorgement rates in larval ticks (64.4%), and an apparent reduction in egg weights, which suggest that H. longicornis P27/30 protein is a potential candidate antigen for a tick vaccine. These results demonstrated that the recombinant P27/30 protein might be a useful vaccine candidate antigen for biological control of H. longicornis.     

Biotechnology and vaccines: application of functional genomics to Neisseria meningitidis and other bacterial pathogens

Since its introduction, vaccinology has been very effective in preventing infectious diseases. However, in several cases, the conventional approach to identify protective antigens, based on biochemical, immunological and microbiological methods, has failed to deliver successful vaccine candidates against major bacterial pathogens. The recent development of powerful biotechnological tools applied to genome-based approaches has revolutionized vaccine development, biological research and clinical diagnostics. The availability of a genome provides an inclusive virtual catalogue of all the potential antigens from which it is possible to select the molecules that are likely to be more effective. Here, we describe the use of "reverse vaccinology", which has been successful in the identification of potential vaccines candidates against Neisseria meningitidis serogroup B and review the use of functional genomics approaches as DNA microarrays, proteomics and comparative genome analysis for the identification of virulence factors and novel vaccine candidates. In addition, we describe the potential of these powerful technologies in understanding the pathogenesis of various bacteria.     

Identification of glycosylated regions in pneumococcal PspA conjugated to serotype 6B capsular polysaccharide

Conjugate vaccines are being widely used since their introduction. Nowadays the interest in these vaccines is still growing and new antigens and conjugate chemistry are being studied and developed. Pneumococcal surface protein A (PspA) is one of the most studied pneumococcal antigens and is an important vaccine candidate. One approach to broaden the conjugate vaccine coverage could be the conjugation of the polysaccharide to a pneumococcal protein such as PspA. Previous results have shown that conjugated recombinant fragment of PspA (rPspA) not only maintained but also in some conjugates improved the induction of protective antibodies raised against the protein carrier. We describe here a characterization study to identify the domains of Streptococcus pneumoniae recombinant PspA (rPspA), from family 1 clade 1 and family 2 clade 3, involved in the conjugation with serotype 6B capsular polysaccharide.     

基于响应面分析方法的钩端螺旋体三联属特异性蛋白抗原原核表达条件的优化

脂蛋白LipL32和LipL21及穿膜蛋白OMPL1是问号钩端螺旋体(简称钩体)属特异性表面抗原,可作为通用型钩体基因工程疫苗抗原.[目的]在我们的研究中,为了获得使得重组人工融合基因lipL32/1-lipL21-ompL1/2获得较高的表达水平,我们优化了重组宿主大肠杆菌的表达条件.[方法]我们采用了基于中心复合设计(CCD)的响应面分析方法(RSM).影响重组大肠杆菌生长的主要因素包pH、诱导剂IPTG浓度、诱导前培养实践、诱导时间以及诱导温度.响应面分析方法可以从这些因素中找到适合目的蛋白表达的最优表达条件.[结果]我们的结果显示在pH7.9、0.20mmol/LIPTG、诱导前培养时间2.5 h、诱导时间5.83 h、诱导后温度31℃条件下,可获得目的重组蛋白37.78 mg/L的最大表达量.[结论]实验结果表明采用基于中心复合设计的响应面分析方法能够较吹靥岣吣康牟锏牟?利用统计方法不但可以减少试验的次数,而且还能够从影响蛋白的因素中找出最重要的影响因素,因此该方法不仅对重组蛋白表达条件的优化有用,而且是一种很好的筛选方法.     

Liposome-polycation-DNA (LPD) particle as a carrier and adjuvant for protein-based vaccines: Therapeutic effect against cervical cancer

With the successful identification of many tumor-specific antigens, tumor-associated antigens, and the potential of using unfractioned tumor cell derivatives as tumor antigens, a system and/or adjuvant that can deliver these antigens and help them to induce strong and effective anti-tumor immune responses is greatly needed. Previously, we reported that a MHC class I-restricted peptide epitope derived from human papillomavirus (HPV) 16 E7 protein, when incorporated into a clinically proven safe LPD (liposome-polycation-DNA) particle, was able to effectively eradicate tumors established in mice. Cervical cancer is the second most common cancer among women worldwide. HPV infection is clearly linked to this cancer. Vaccines based on the early (E) gene products of HPV could be effective in controlling it. However, besides the fact that epitope vaccines have many limitations particularly, concerning the diverse HLAs in humans, the use of the epitope as an antigen prevented us from fully characterizing the immune responses induced by the LPD as a vaccine carrier and/or adjuvant in previous studies. In the present study, by using the HPV 16 E7 protein as an antigen, we first showed that LPD, as a vaccine carrier and adjuvant induced strong and robust immune responses, both cellular and antibody. We then showed that immunization with LPD particles incorporated with either the wild type HPV 16 E7 protein or a potentially safer mutant induced strong immune responses that caused complete regressions of a model cervical cancer tumor established in murines. LPD could be a potent vaccine carrier and/or adjuvant for many antigens.     

DNA motif elucidation using belief propagation

Protein-binding microarray (PBM) is a high-throughout platform that can measure the DNA-binding preference of a protein in a comprehensive and unbiased manner. A typical PBM experiment can measure binding signal intensities of a protein to all the possible DNA k-mers (k = 8 ∼10); such comprehensive binding affinity data usually need to be reduced and represented as motif models before they can be further analyzed and applied. Since proteins can often bind to DNA in multiple modes, one of the major challenges is to decompose the comprehensive affinity data into multimodal motif representations. Here, we describe a new algorithm that uses Hidden Markov Models (HMMs) and can derive precise and multimodal motifs using belief propagations. We describe an HMM-based approach using belief propagations (kmerHMM), which accepts and preprocesses PBM probe raw data into median-binding intensities of individual k-mers. The k-mers are ranked and aligned for training an HMM as the underlying motif representation. Multiple motifs are then extracted from the HMM using belief propagations. Comparisons of kmerHMM with other leading methods on several data sets demonstrated its effectiveness and uniqueness. Especially, it achieved the best performance on more than half of the data sets. In addition, the multiple binding modes derived by kmerHMM are biologically meaningful and will be useful in interpreting other genome-wide data such as those generated from ChIP-seq. The executables and source codes are available at the authors’ websites: e.g. http://www.cs.toronto.edu/∼wkc/kmerHMM.     

The nature and prospects for gut membrane proteins as vaccine candidates for Haemonchus contortus and other ruminant trichostrongyloids

Substantial progress has been made in the last decade in identifying several antigens from Haemonchus contortus which, in their native form, stimulate useful levels of protective immunity (70-95% reductions in faecal egg output) in the ovine host. Much work has focussed on proteins/protein complexes expressed on the surface of the worm gut which are exposed to the blood meal, and, hence, antibody ingested with it. The antigens generally, but not in all cases, show protease activity and antibody is thought to mediate protective immunity by blocking the activity of enzymes involved in digestion within the worm. This review summarises the protective efficacy, as well as the biochemical and molecular properties, of the principal candidate antigens which are expressed in the gut of these parasites. Of course, such antigens will have to be expressed as recombinant proteins to be sufficiently cost-effective for use in a commercial vaccine and the current status of recombinant antigen expression is discussed with particular reference to conformation and glycosylation. There is a need for continued antigen definition even in the confines of gut antigens and potential targets can be selected from the rapidly expanding genome/EST datasets on the basis of predicted functional homology. Gene knockout technologies such as RNA interference have the potential to provide high throughput, rapid and inexpensive methods to define whether the protein product of a particular gene would be a suitable vaccine candidate.