A combined immuno-informatics and structure-based modeling approach for prediction of T cell epitopes of secretory proteins of Mycobacterium tuberculosis

The role of immunoinformatics in the development of T-cell peptide-based vaccines against Mycobacterium tuberculosis

INTRODUCTION

Tuberculosis (TB) is a major health problem worldwide. The BCG, the only authorized vaccine to fight TB, shows a variable protection in the adult population highlighting the need of a new vaccine. Immunoinformatics offers a variety of tools that can predict immunogenic T-cell peptides of Mycobacterium tuberculosis (Mtb) that can be used to create a new vaccine. Immunoinformatics has made possible the identification of immunogenic T-cell peptides of Mtb that have been tested in vitro showing a potential for using these molecules as part of a new TB vaccine.

AREAS COVERED

This review summarizes the most common immunoinformatics tools to identify immunogenic T-cell peptides and presents a compilation about research studies that have identified T-cell peptides of Mtb by using immunoinformatics. Also, it is provided a summary of the TB vaccines undergoing clinical trials.

EXPERT OPINION

In the next few years, the field of peptide-based vaccines will keep growing along with the development of more efficient and sophisticated immunoinformatic tools to identify immunogenic peptides with a greater accuracy.

Recent progress in the design of DNA vaccines against tuberculosis

Current tuberculosis (TB) vaccines have some disadvantages and many efforts have been undertaken to produce effective TB vaccines. As a result of their advantages, DNA vaccines are promising future vaccine candidates. This review focuses on the design and delivery of novel DNA-based vaccines against TB.

Prediction of Epitope-Based Peptide Vaccine Against the Chikungunya Virus by Immuno-informatics Approach

BACKGROUND

Chikungunya is an arthropod-borne viral disease characterized by abrupt onset of fever frequently accompanied by joint pain, which has been identified in over 60 countries in Africa, the Americas, Asia, and Europe.

METHODS

Regardless of the availability of molecular knowledge of this virus, no definite vaccine or other remedial agents have been developed yet. In the present study, a combination of B-cell and T-cell epitope predictions, followed by molecular docking simulation approach has been carried out to design a potential epitope-based peptide vaccine, which can trigger a critical immune response against the viral infections.

RESULTS

A total of 52 sequences of E1 glycoprotein from the previously reported isolates of Chikungunya outbreaks were retrieved and examined through in silico methods to identify a potential B-cell and T-cell epitope. From the two separate epitope prediction servers, five potential B-cell epitopes were selected, among them "NTQLSEAHVEKS" was found highly conserved across strains and manifests high antigenicity with surface accessibility, flexibility, and hydrophilicity. Similarly, two highly conserved, non-allergenic, non-cytotoxic putative T-cell epitopes having maximum population coverage were screened to bind with the HLA-C 12*03 molecule. Molecular docking simulation revealed potential T-cell based epitope "KTEFASAYR" as a vaccine candidate for this virus.

CONCLUSION

A combination of these B-cell and T-cell epitope-based vaccine can open up a new skyline with broader therapeutic application against Chikungunya virus with further experimental and clinical investigation.

Immunogenicity of late stage specific peptide antigens of Mycobacterium tuberculosis

Global burden of latent TB infection comprises one-third of the world population. Identifying potential Mycobacterium tuberculosis (Mtb) latency associated antigens that can generate protective immunity against the pathogen is crucial for designing an effective TB vaccine. Usually the immune system responds to a small number of amino acids as MHC Class I or Class II peptides. The precision to trigger epitope specific protective T-cell immune response could therefore be achieved with synthetic peptide-based subunit vaccine. In the present study we have considered an immunoinformatic approach using available softwares (ProPred, IEDB, NETMHC, BIMAS, Vaxijen2.0) and docking and visualizing softwares (CABSDOCK, HEX, Pymol, Discovery Studio) to select 10 peptides as latency antigens from 4 proteins (Rv2626, Rv2627, Rv2628, and Rv2032) of DosR regulon of Mtb. As Intracellular IFN-γ secreted by T cells is the most essential cytokine in Th1 mediated protective immunity, these peptides were verified as potential immunogenic epitopes in Peripheral Blood Mononuclear Cells (PBMCs) of 10 healthy contacts of TB patients (HTB) and 10 Category I Pulmonary TB patients (PTB).The antigen-specific CD4 and CD8 T cells expressing intracellular IFN-γ were analyzed using monoclonal antibodies in all subjects by multi-parameter flow cytometry. Both, PTB and HTB individuals responded to DosR peptides by showing increased frequency of IFN-γ⁺CD4 and IFN-γ⁺CD8 T cells. The T-cell responses were significantly higher in PTB patients in comparision to the HTB individuals. Additionally, our synthetic peptides and pools showed higher frequencies of IFN-γ⁺CD4 and IFN-γ⁺CD8 T cells than the peptides of Ag85B. This pilot study can be taken up further in larger sample size which may support the untapped opportunity of designing Mtb DosR inclusive peptide based post-exposure subunit vaccine.

In silico-based vaccine design against Ebola virus glycoprotein

Ebola virus (EBOV) is one of the lethal viruses, causing more than 24 epidemic outbreaks to date. Despite having available molecular knowledge of this virus, no definite vaccine or other remedial agents have been developed yet for the management and avoidance of EBOV infections in humans. Disclosing this, the present study described an epitope-based peptide vaccine against EBOV, using a combination of B-cell and T-cell epitope predictions, followed by molecular docking and molecular dynamics simulation approach. Here, protein sequences of all glycoproteins of EBOV were collected and examined via in silico methods to determine the most immunogenic protein. From the identified antigenic protein, the peptide region ranging from 186 to 220 and the sequence HKEGAFFLY from the positions of 154-162 were considered the most potential B-cell and T-cell epitopes, correspondingly. Moreover, this peptide (HKEGAFFLY) interacted with HLA-A*32:15 with the highest binding energy and stability, and also a good conservancy of 83.85% with maximum population coverage. The results imply that the designed epitopes could manifest vigorous enduring defensive immunity against EBOV.

Exploring functional membrane microdomains in bacteria: an overview

Recent studies show that internal organization of bacterial cells is more complex than previously appreciated. A clear example of this is the assembly of the nanoscale membrane platforms termed functional membrane microdomains. The lipid composition of these regions differs from that of the surrounding membrane; these domains confine a set of proteins involved in specific cellular processes such as protease secretion and signal transduction. It is currently thought that functional membrane microdomains act as oligomerization platforms and promote efficient oligomerization of interacting protein partners in bacterial membranes. In this review, we highlight the most noteworthy achievements, challenges and controversies of this emerging research field over the past five years.

Immunoproteomic identification of MbovP579, a promising diagnostic biomarker for serological detection of Mycoplasma bovis infection

A lack of knowledge regarding the antigenic properties of Mycoplasma bovis proteins prevents the effective control of bovine infections using immunological approaches. In this study, we detected and characterized a specific and sensitive M. bovis diagnostic biomarker. After M. bovis total proteins and membrane fractions were separated with two dimensional gel electrophoresis, proteins reacting with antiserawere detected using MALDI-TOF MS. Thirty-nine proteins were identified, 32 of which were previously unreported. Among them, immunoinformatics predicted eight antigens, encoded by Mbov_0106, 0116, 0126, 0212, 0275, 0579, 0739, and 0789, to have high immunological value. These genes were expressed in E. coli after mutagenesis of UGA to UGG using overlap extension PCR. A lipoprotein, MbovP579, encoded by a functionally unknown gene, was a sensitive and specific antigen for detection of antibodies in sera from both M. bovis-infected and vaccinated cattle. The specificity of MbovP579 was confirmed by its lack of cross-reactivity with other mycoplasmas, including Mycoplasma agalactiae. An iELISA based on rMbovP579 detected seroconversion 7 days post-infection (dpi). The ELISA had sensitivity of 90.2% (95% CI: 83.7%, 94.3%) and a specificity of 97.8% (95% CI: 88.7%, 99.6%) with clinical samples. Additional comparative studies showed that both diagnostic and analytic sensitivities of the ELISA were higher than those of a commercially available kit (p<0.01). We have thus detected and characterized the novel antigen, MbovP579, and established an rMbovP579-based ELISA as a highly sensitive and specific method for the early diagnosis of M. bovis infection.

Sequence conservation analysis and in silico human leukocyte antigen-peptide binding predictions for the Mtb72F and M72 tuberculosis candidate vaccine antigens

Background

Requisites for an efficacious tuberculosis (TB) vaccine are a minimal genomic diversity among infectious Mycobacterium tuberculosis strains for the selected antigen, and the capability to induce robust T-cell responses in the majority of human populations. A tool in the identification of putative T-cell epitopes is in silico prediction of major histocompatibility complex (MHC)-peptide binding. Candidate TB vaccine antigen Mtb72F and its successor M72 are recombinant fusion proteins derived from Mtb32A and Mtb39A (encoded by Rv0125 and Rv1196, respectively). Adjuvanted Mtb72F and M72 candidate vaccines were shown to induce CD4⁺ T-cell responses in European, US, African and Asian populations.

Methods

Sequence conservation of Mtb32A, Mtb39A, Mtb72F and M72 among 46 strains (prevalent Mycobacterium strains causing human TB disease, and H37Ra) was assessed by multiple alignments using ClustalX. For Mtb32A, Mtb39A and Mtb72F, 15-mer human leukocyte antigen (HLA)-class II-binding peptides were predicted for 158 DRB1 alleles prevailing in populations with high TB burden, 6 DRB3/4/5, 8 DQ and 6 DP alleles, using NetMHCII-pan-3.0. Results for 3 DRB1 alleles were compared with previously published allele-matched in vitro binding data. Additional analyses were done for M72. Nonameric MHC class I-binding peptides in Mtb72F were predicted for three alleles representative of class I supertypes A02, A03 and B07, using seven prediction algorithms.

Results

Sequence identity among strains was ≥98 % for each protein. Residue changes in Mtb39A comprised primarily single residue or nucleotide insertions and/or deletions in repeat regions, and were observed in 67 % of strains. For Mtb72F, 156 DRB1, 6 DRB3/4/5, 7 DQ and 5 DP alleles were predicted to contain at least one MHC class II-binding peptide, and class I-binding peptides were predicted for each HLA-A/B allele. Comparison of predicted MHC-II-binding peptides with experimental data indicated that the algorithm’s sensitivity and specificity were variable among alleles.

Conclusions

The sequences from which Mtb72F and M72 are derived are highly conserved among representative Mycobacterium strains. Predicted putative T-cell epitopes in M72 and/or Mtb72F covered a wide array of HLA alleles. In silico binding predictions for class I- and II-binding putative epitopes can be complemented with biochemical verification of HLA binding capacity, processing and immunogenicity of the predicted peptides.

Electronic supplementary material

The online version of this article (doi:10.1186/s12865-015-0119-7) contains supplementary material, which is available to authorized users.

Proteome-wide B and T cell epitope repertoires in outer membrane proteins of Mycobacterium avium subsp. paratuberculosis have vaccine and diagnostic relevance: a holistic approach

Mycobacterium avium subsp. paratuberculosis (MAP) is an etiological agent of chronic inflammation of the intestine among ruminants and humans. Currently, there are no effective vaccines and sensitive diagnostic tests available for its control and detection. For this, it is of paramount importance to identify the MAP antigens, which may be immunologically recognized by the host immune system. To address this challenge, we performed identification of the immunogenic epitopes in the MAP outer membrane proteins (OMPs). We have previously identified 57 MAP proteins as OMPs [Rana A, Rub A, Akhter Y. 2014. Molecular BioSystems, 10:2329-2337] and have evaluated them for the epitope selection and analysis employing a computational approach. Thirty-five MAP OMPs are reported with nine-mer peptides showing high binding affinity to major histocompatibility complex (MHC) class I molecules and 28 MAP OMPs with 15-mer peptides of high binding affinity for MHC class II molecules. The presence of MHC binding epitopes indicates the potential cell-mediated immune response inducing capacity of these MAP OMPs in infected host. To further investigate the humoral response inducing properties of OMPs of MAP, we report potential B cell epitopes based on the sequences of peptide antigens and their molecular structures. We also report 10 proteins having epitopes for both B and T cells representing potential candidates which may invoke both humoral and cellular immune responses in the host. These findings will greatly accelerate and expedite the formulation of effective and cost-efficient vaccines and diagnostic tests against MAP infection.

Antigens for CD4 and CD8 T cells in tuberculosis

Tuberculosis (TB), caused by infection with Mycobacterium tuberculosis (MTB), represents an important cause of morbidity and mortality worldwide for which an improved vaccine and immunodiagnostics are urgently needed. CD4(+) and CD8(+) T cells play an important role in host defense to TB. Definition of the antigens recognized by these T cells is critical for improved understanding of the immunobiology of TB and for development of vaccines and diagnostics. Herein, the antigens and epitopes recognized by classically HLA class I- and II-restricted CD4(+) and CD8(+) T cells in humans infected with MTB are reviewed. Immunodominant antigens and epitopes have been defined using approaches targeting particular TB proteins or classes of proteins and by genome-wide discovery approaches. Antigens and epitopes recognized by classically restricted CD4(+) and CD8(+) T cells show extensive breadth and diversity in MTB-infected humans.

In silico identification of epitopes in Mycobacterium avium subsp. paratuberculosis proteins that were upregulated under stress conditions

Johne's disease in ruminants is caused by Mycobacterium avium subsp. paratuberculosis. Diagnosis of M. avium subsp. paratuberculosis infection is difficult, especially in the early stages. To date, ideal antigen candidates are not available for efficient immunization or immunodiagnosis. This study reports the in silico selection and subsequent analysis of epitopes of M. avium subsp. paratuberculosis proteins that were found to be upregulated under stress conditions as a means to identify immunogenic candidate proteins. Previous studies have reported differential regulation of proteins when M. avium subsp. paratuberculosis is exposed to stressors which induce a response similar to dormancy. Dormancy may be involved in evading host defense mechanisms, and the host may also mount an immune response against these proteins. Twenty-five M. avium subsp. paratuberculosis proteins that were previously identified as being upregulated under in vitro stress conditions were analyzed for B and T cell epitopes by use of the prediction tools at the Immune Epitope Database and Analysis Resource. Major histocompatibility complex class I T cell epitopes were predicted using an artificial neural network method, and class II T cell epitopes were predicted using the consensus method. Conformational B cell epitopes were predicted from the relevant three-dimensional structure template for each protein. Based on the greatest number of predicted epitopes, eight proteins (MAP2698c [encoded by desA2], MAP2312c [encoded by fadE19], MAP3651c [encoded by fadE3_2], MAP2872c [encoded by fabG5_2], MAP3523c [encoded by oxcA], MAP0187c [encoded by sodA], and the hypothetical proteins MAP3567 and MAP1168c) were identified as potential candidates for study of antibody- and cell-mediated immune responses within infected hosts.

In silico identification of potential antigenic proteins and promiscuous CTL epitopes in Mycobacterium tuberculosis

Cell-mediated immunity is critical for the control of Mycobacterium tuberculosis infection. We hypothesized that those proteins of M. tuberculosis (MTB) that do not have homologs in humans as well as human gut flora, would mount a good antigenic response in man, and employed a bioinformatics approach to identify MTB antigens capable of inducing a robust cell-mediated immune response in humans. In the first step we identified 624 MTB proteins that had no homologs in humans. Comparison of this set of proteins with the proteome of 77 different microbes that comprise the human gut flora narrowed down the list to 180 proteins unique to MTB. Twenty nine of the 180 proteins are known to be associated with dormancy. Since dormancy associated proteins are known to harbor CTL epitopes, we selected four representative unique proteins and subjected them to epitope analysis using ProPred1. Nineteen novel promiscuous epitopes were identified in the four proteins. Population coverage for 7 of the 19 shortlisted epitopes including Rv3852 (58-KPAEAPVSL, 112-VPLIVAVTL, 118-VTLSLLALL and 123-LALLLIRQL), Rv2706c (66-RPLSGVSFL) Rv3466 (8- RIVEVFDAL and 38-RSLERLECL) was >74%. These novel promiscuous epitopes are conserved in other virulent MTB strains, and can therefore be further investigated for their immunological relevance and usefulness as vaccine candidates.

Genome-based in silico identification of new Mycobacterium tuberculosis antigens activating polyfunctional CD8+ T cells in human tuberculosis

Although CD8(+) T cells help control Mycobacterium tuberculosis infection, their M. tuberculosis Ag repertoire, in vivo frequency, and functionality in human tuberculosis (TB) remains largely undefined. We have performed genome-based bioinformatics searches to identify new M. tuberculosis epitopes presented by major HLA class I supertypes A2, A3, and B7 (covering 80% of the human population). A total of 432 M. tuberculosis peptides predicted to bind to HLA-A*0201, HLA-A*0301, and HLA-B*0702 (representing the above supertypes) were synthesized and HLA-binding affinities determined. Peptide-specific CD8(+) T cell proliferation assays (CFSE dilution) in 41 M. tuberculosis-responsive donors identified 70 new M. tuberculosis epitopes. Using HLA/peptide tetramers for the 18 most prominently recognized HLA-A*0201-binding M. tuberculosis peptides, recognition by cured TB patients' CD8(+) T cells was validated for all 18 epitopes. Intracellular cytokine staining for IFN-γ, IL-2, and TNF-α revealed mono-, dual-, as well as triple-positive CD8(+) T cells, indicating these M. tuberculosis peptide-specific CD8(+) T cells were (poly)functional. Moreover, these T cells were primed during natural infection, because they were absent from M. tuberculosis-noninfected individuals. Control CMV peptide/HLA-A*0201 tetramers stained CD8(+) T cells in M. tuberculosis-infected and noninfected individuals equally, whereas Ebola peptide/HLA-A*0201 tetramers were negative. In conclusion, the M. tuberculosis-epitope/Ag repertoire for human CD8(+) T cells is much broader than hitherto suspected, and the newly identified M. tuberculosis Ags are recognized by (poly)functional CD8(+) T cells during control of infection. These results impact on TB-vaccine design and biomarker identification.

Computational analysis of cysteine proteases (Clan CA, Family Cl) of Leishmania major to find potential epitopic regions

Leishmania is associated with a broad spectrum of diseases, ranging from simple cutaneous to invasive visceral leishmaniasis. Here, the sequences of ten cysteine proteases of types A, B and C of Leishmania major were obtained from GeneDB database. Prediction of MHC class I epitopes of these cysteine proteases was performed by NetCTL program version 1.2. In addition, by using BcePred server, different structural properties of the proteins were predicted to find out their potential B cell epitopes. According to this computational analysis, nine regions were predicted as B cell epitopes. The results provide useful information for designing peptide-based vaccines.

In silico analysis of chimeric espA, eae and tir fragments of Escherichia coli O157:H7 for oral immunogenic applications

Background

In silico techniques are highly suited for both the discovery of new and development of existing vaccines. Enterohemorrhagic Escherichia coli O157:H7 (EHEC) exhibits a pattern of localized adherence to host cells, with the formation of microcolonies, and induces a specific histopathological lesion (attaching/effacing). The genes encoding the products responsible for this phenotype are clustered on a 35-kb pathogenicity island. Among these proteins, Intimin, Tir, and EspA, which are expressed by attaching-effacing genes, are responsible for the attachment to epithelial cell that leads to lesions.

Results

We designed synthetic genes encoding the carboxy-terminal fragment of Intimin, the middle region of Tir and the carboxy-terminal part of EspA. These multi genes were synthesized with codon optimization for a plant host and were fused together by the application of four repeats of five hydrophobic amino acids as linkers. The structure of the synthetic construct gene, its mRNA and deduced protein and their stabilities were analyzed by bioinformatic software. Furthermore, the immunogenicity of this multimeric recombinant protein consisting of three different domains was predicted.

Conclusion

a structural model for a chimeric gene from LEE antigenic determinants of EHEC is presented. It may define accessibility, solubility and immunogenecity.

Analysis of predicted CD8+ T cell epitopes from proteins encoded by the specific RD regions of Mycobacterium tuberculosis for vaccine development and specific diagnosis

A number of regions designated as RD1-RD16 (region of difference) and encompassing 129 open reading frames have been identified between Mycobacterium tuberculosis and Mycobacterium bovis on the one hand and Bacillus Calmette-Guérin on the other. Identification of T cell epitopes from this set of proteins may serve to define candidate antigens with potentials in specific diagnosis and development of new vaccines against TB. All possible nonameric peptide sequences from proteins of these M. tuberculosis specific regions were analyzed in silico for the ability to bind to 33 alleles of class I HLA. These results reveal that of all RD proteins, a significant number of these peptides are predicted to be high-affinity HLA binders (T (1/2) >or= 100 min), irrespective of the length of the protein, and 67% of the peptides predicted to bind are mono-allelic in their binding. Pathogen peptides that could behave as self- or partially self-peptides in the host were eliminated using a comparative study with the human proteome, thus the number of peptides for analysis was reduced. The predicted epitopes can be tested experimentally for their inclusion in a potential vaccine against tuberculosis and specific diagnosis.

Whole genome identification of Mycobacterium tuberculosis vaccine candidates by comprehensive data mining and bioinformatic analyses

Background

Mycobacterium tuberculosis, the causative agent of tuberculosis (TB), infects ~8 million annually culminating in ~2 million deaths. Moreover, about one third of the population is latently infected, 10% of which develop disease during lifetime. Current approved prophylactic TB vaccines (BCG and derivatives thereof) are of variable efficiency in adult protection against pulmonary TB (0%–80%), and directed essentially against early phase infection.

Methods

A genome-scale dataset was constructed by analyzing published data of: (1) global gene expression studies under conditions which simulate intra-macrophage stress, dormancy, persistence and/or reactivation; (2) cellular and humoral immunity, and vaccine potential. This information was compiled along with revised annotation/bioinformatic characterization of selected gene products and in silico mapping of T-cell epitopes. Protocols for scoring, ranking and prioritization of the antigens were developed and applied.

Results

Cross-matching of literature and in silico-derived data, in conjunction with the prioritization scheme and biological rationale, allowed for selection of 189 putative vaccine candidates from the entire genome. Within the 189 set, the relative distribution of antigens in 3 functional categories differs significantly from their distribution in the whole genome, with reduction in the Conserved hypothetical category (due to improved annotation) and enrichment in Lipid and in Virulence categories. Other prominent representatives in the 189 set are the PE/PPE proteins; iron sequestration, nitroreductases and proteases, all within the Intermediary metabolism and respiration category; ESX secretion systems, resuscitation promoting factors and lipoproteins, all within the Cell wall category. Application of a ranking scheme based on qualitative and quantitative scores, resulted in a list of 45 best-scoring antigens, of which: 74% belong to the dormancy/reactivation/resuscitation classes; 30% belong to the Cell wall category; 13% are classical vaccine candidates; 9% are categorized Conserved hypotheticals, all potentially very potent T-cell antigens.

Conclusion

The comprehensive literature and in silico-based analyses allowed for the selection of a repertoire of 189 vaccine candidates, out of the whole-genome 3989 ORF products. This repertoire, which was ranked to generate a list of 45 top-hits antigens, is a platform for selection of genes covering all stages of M. tuberculosis infection, to be incorporated in rBCG or subunit-based vaccines.

Computer-aided biotechnology: from immuno-informatics to reverse vaccinology

Genome sequences from many organisms, including humans, have been completed, and high-throughput analyses have produced burgeoning volumes of 'omics' data. Bioinformatics is crucial for the management and analysis of such data and is increasingly used to accelerate progress in a wide variety of large-scale and object-specific functional analyses. Refined algorithms enable biotechnologists to follow 'computer-aided strategies' based on experiments driven by high-confidence predictions. In order to address compound problems, current efforts in immuno-informatics and reverse vaccinology are aimed at developing and tuning integrative approaches and user-friendly, automated bioinformatics environments. This will herald a move to 'computer-aided biotechnology': smart projects in which time-consuming and expensive large-scale experimental approaches are progressively replaced by prediction-driven investigations.

Computational analysis of proteome of H5N1 avian influenza virus to define T cell epitopes with vaccine potential

The existing vaccines against influenza are based on the generation of neutralizing antibody primarily directed against surface proteins - hemagglutinin and neuraminidase. In this work, we have computationally defined conserved T cell epitopes of proteins of influenza virus H5N1 to help in the design of a vaccine with haplotype specificity for a target population. The peptides from the proteome of H5N1 virus which are predicted to bind to different HLAs, do not show similarity with peptides of human proteome and are also identified to be generated by proteolytic cleavage. These peptides could be made use of in the design of either a DNA vaccine or a subunit vaccine against influenza.

Comparative in silico analysis of two vaccine candidates for group A streptococcus predicts that they both may have similar safety profiles

BACKGROUND

Concerns of immune cross-reactivity, between epitopes of the group A streptococcal (GAS) M-proteins and host proteins have hindered the progress of an effective GAS vaccine. An ideal M-protein based subunit vaccine should not elicit heart tissue cross-reactive antibody responses and should not activate M-protein specific CD4+ T-cells. In the current study we used a bioinformatic and immunoinformatic approach to assess the safety of J8 and J14, chimeric vaccine constructs containing a GAS derived M-protein epitope embedded in flanking GCN4 region. We demonstrate that at the primary amino acid level J8 and J14 show very little homology to human proteins. ProPred, RANKPEP and HLABIND algorithms failed to predict significant binding between the M-protein specific regions of J8 and J14 and class II binding alleles. A single peptide was predicted to bind to HLA class I allele B_2705. This data was supported by cellular proliferation assays demonstrating few peripheral blood mononuclear cells (PBMCs) from donors respond to J8 and J14. Reassuringly, there was no correlation between proliferation to these peptides, and proliferation to host proteins. This data suggests that J8 and J14 are unlikely to induce cross-reactive immune responses, and will be safe for use in humans.

Expression profiling in granulomatous lung disease

Granulomatous lung diseases, such as sarcoidosis, hypersensitivity pneumonitis, Wegener's granulomatosis, and chronic beryllium disease, along with granulomatous diseases of known infectious etiologies, such as tuberculosis, are major causes of morbidity and mortality throughout the world. Clinical manifestations of these diseases are highly heterogeneous, and the determinants of disease susceptibility and clinical course (e.g., resolution vs. chronic, progressive fibrosis) are largely unknown. The underlying pathogenic mechanisms of these diseases also remain poorly understood. Within this context, these diseases have been approached using genomic and proteomic technologies to allow us to identify patterns of gene/protein expression that track with clinical disease or to identify new pathways involved in disease pathogenesis. The results from these initial studies highlight the potential for these "-omics" approaches to reveal novel insights into the pathogenesis of granulomatous lung disease and provide new tools to improve diagnosis, clinical classification, course prediction, and response to therapy. Realizing this potential will require collaboration among multidisciplinary groups with expertise in the respective technologies, bioinformatics, and clinical medicine for these complex diseases.