ProPred analysis and experimental evaluation of promiscuous T-cell epitopes of three major secreted antigens of Mycobacterium tuberculosis

Selection of vaccine-candidate peptides from Mycobacterium avium subsp. paratuberculosis by in silico prediction, in vitro T-cell line proliferation, and in vivo immunogenicity

Mycobacterium avium subspecies paratuberculosis (MAP) is a global concern in modern livestock production worldwide. The available vaccines against paratuberculosis do not offer optimal protection and interfere with the diagnosis of bovine tuberculosis. The aim of this study was to identify immunogenic MAP-specific peptides that do not interfere with the diagnosis of bovine tuberculosis. Initially, 119 peptides were selected by either (1) identifying unique MAP peptides that were predicted to bind to bovine major histocompatibility complex class II (MHC-predicted peptides) or (2) selecting hydrophobic peptides unique to MAP within proteins previously shown to be immunogenic (hydrophobic peptides). Subsequent testing of peptide-specific CD4+ T-cell lines from MAP-infected, adult goats vaccinated with peptides in cationic liposome adjuvant pointed to 23 peptides as being most immunogenic. These peptides were included in a second vaccine trial where three groups of eight healthy goat kids were vaccinated with 14 MHC-predicted peptides, nine hydrophobic peptides, or no peptides in o/w emulsion adjuvant. The majority of the MHC-predicted (93%) and hydrophobic peptides (67%) induced interferon-gamma (IFN-γ) responses in at least one animal. Similarly, 86% of the MHC-predicted and 89% of the hydrophobic peptides induced antibody responses in at least one goat. The immunization of eight healthy heifers with all 119 peptides formulated in emulsion adjuvant identified more peptides as immunogenic, as peptide specific IFN-γ and antibody responses in at least one heifer was found toward 84% and 24% of the peptides, respectively. No peptide-induced reactivity was found with commercial ELISAs for detecting antibodies against Mycobacterium bovis or MAP or when performing tuberculin skin testing for bovine tuberculosis. The vaccinated animals experienced adverse reactions at the injection site; thus, it is recommend that future studies make improvements to the vaccine formulation. In conclusion, immunogenic MAP-specific peptides that appeared promising for use in a vaccine against paratuberculosis without interfering with surveillance and trade tests for bovine tuberculosis were identified by in silico analysis and ex vivo generation of CD4+ T-cell lines and validated by the immunization of goats and cattle. Future studies should test different peptide combinations in challenge trials to determine their protective effect and identify the most MHC-promiscuous vaccine candidates.

RPEMHC: improved prediction of MHC-peptide binding affinity by a deep learning approach based on residue-residue pair encoding

MOTIVATION

Binding of peptides to major histocompatibility complex (MHC) molecules plays a crucial role in triggering T cell recognition mechanisms essential for immune response. Accurate prediction of MHC-peptide binding is vital for the development of cancer therapeutic vaccines. While recent deep learning-based methods have achieved significant performance in predicting MHC-peptide binding affinity, most of them separately encode MHC molecules and peptides as inputs, potentially overlooking critical interaction information between the two.

RESULTS

In this work, we propose RPEMHC, a new deep learning approach based on residue-residue pair encoding to predict the binding affinity between peptides and MHC, which encode an MHC molecule and a peptide as a residue-residue pair map. We evaluate the performance of RPEMHC on various MHC-II-related datasets for MHC-peptide binding prediction, demonstrating that RPEMHC achieves better or comparable performance against other state-of-the-art baselines. Moreover, we further construct experiments on MHC-I-related datasets, and experimental results demonstrate that our method can work on both two MHC classes. These extensive validations have manifested that RPEMHC is an effective tool for studying MHC-peptide interactions and can potentially facilitate the vaccine development.

AVAILABILITY

The source code of the method along with trained models is freely available at https://github.com/lennylv/RPEMHC.

TN strain proteome mediated therapeutic target mapping and multi-epitopic peptide-based vaccine development for Mycobacterium leprae

Leprosy is a significant universal health problem that is remarkably still a concern in developing countries due to infection frequency. New therapeutic molecules and next-generation vaccines are urgently needed to accelerate the leprosy-free world. In this direction, the present study was performed using two routes: proteome-mediated therapeutic target identification and mapping as well as multi-epitopic peptide-based novel vaccine development using state of the art of computational biology for the TN strain of M. leprae. The TN strain was selected from 65 Mycobacterium strains, and TN strain proteome mediated 83 therapeutic protein targets were mapped and characterized according to subcellular localization. Also, drug molecules were mapped with respect to protein targets localization. The Druggability potential of proteins was also evaluated. For multi-epitope peptide-based vaccine development, the four common types of B and T cell epitopes were identified (SLFQSHNRK, VVGIGQHAA, MMHRSPRTR, LGVDQTQPV) and combined with the suitable peptide linker. The vaccine component had an acceptable protective antigenic score (0.9751). The molecular docking of vaccine components with TLR4/MD2 complex exhibited a low ACE value (-244.12) which signifies the proper binding between the two molecules. The estimated free Gibbs binding energy ensured accurate protein-protein interactions (-112.46 kcal/mol). The vaccine was evaluated through adaptive immunity stimulation as well as immune interactions. The molecular dynamic simulation was carried out by using CHARMM topology-based parameters to minimize the docked complex. Subsequently, the Normal Mode Analysis in the internal coordinates showed a low eigen-value (1.3982892e-05), which also signifies the stability of molecular docking. Finally, the vaccine components were adopted for reverse transcription and codon optimization in E. coli strain K12 for the pGEX-4T1 vector, which supports in silico cloning of the vaccine components against the pathogen. The study directs the experimental study for therapeutics molecules discovery and vaccine candidate development with higher reliability.

Peptide-Based Vaccines for Tuberculosis

Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis. As a result of the coronavirus disease 2019 (COVID-19) pandemic, the global TB mortality rate in 2020 is rising, making TB prevention and control more challenging. Vaccination has been considered the best approach to reduce the TB burden. Unfortunately, BCG, the only TB vaccine currently approved for use, offers some protection against childhood TB but is less effective in adults. Therefore, it is urgent to develop new TB vaccines that are more effective than BCG. Accumulating data indicated that peptides or epitopes play essential roles in bridging innate and adaptive immunity and triggering adaptive immunity. Furthermore, innovations in bioinformatics, immunoinformatics, synthetic technologies, new materials, and transgenic animal models have put wings on the research of peptide-based vaccines for TB. Hence, this review seeks to give an overview of current tools that can be used to design a peptide-based vaccine, the research status of peptide-based vaccines for TB, protein-based bacterial vaccine delivery systems, and animal models for the peptide-based vaccines. These explorations will provide approaches and strategies for developing safer and more effective peptide-based vaccines and contribute to achieving the WHO's End TB Strategy.

Evaluation and Designing of Epitopic-Peptide Vaccine Against Bunyamwera orthobunyavirus Using M-Polyprotein Target Sequences

Bunyamwera orthobunyavirus and its serogroup can cause several diseases in humans, cattle, ruminants, and birds. The viral M-polyprotein helps the virus to enter the host body. Therefore, this protein might serve as a potential vaccine target against Bunyamwera orthobunyavirus. The present study applied the immunoinformatics technique to design an epitopic vaccine component that could protect against Bunyamwera infection. Phylogenetic analysis revealed the presence of conserved patterns of M-polyprotein within the viral serogroup. Three epitopes common for both B-cell and T-cell were identified, i.e., YQPTELTRS, YKAHDKEET, and ILGTGTPKF merged with a specific linker peptide to construct an active vaccine component. The low atomic contact energy value of docking complex between human TLR4 (TLR4/MD2 complex) and vaccine construct confirms the elevated protein–protein binding interaction. Molecular dynamic simulation and normal mode analysis illustrate the docking complex’s stability, especially by the higher Eigenvalue. In silico cloning of the vaccine construct was applied to amplify the desired vaccine component. Structural allocation of both the vaccine and epitopes also show the efficacy of the developed vaccine. Hence, the computational research design outcomes support that the peptide-based vaccine construction is a crucial drive target to limit the infection of Bunyamwera orthobunyavirus to an extent.

Immunological Characterization of Proteins Expressed by Genes Located in Mycobacterium tuberculosis-Specific Genomic Regions Encoding the ESAT6-like Proteins

The 6 kDa early secreted antigen target (ESAT6) is a low molecular weight and highly immunogenic protein of Mycobacterium tuberculosis with relevance in the diagnosis of tuberculosis and subunit vaccine development. The gene encoding the ESAT6 protein is located in the M. tuberculosis-specific genomic region known as the region of difference (RD)1. There are 11 M. tuberculosis-specific RDs absent in all of the vaccine strains of BCG, and three of them (RD1, RD7, and RD9) encode immunodominant proteins. Each of these RDs has genes for a pair of ESAT6-like proteins. The immunological characterizations of all the possible proteins encoded by genes in RD1, RD7 and RD9 have shown that, besides ESAT-6 like proteins, several other proteins are major antigens useful for the development of subunit vaccines to substitute or supplement BCG. Furthermore, some of these proteins may replace the purified protein derivative of M. tuberculosis in the specific diagnosis of tuberculosis by using interferon-gamma release assays and/or tuberculin-type skin tests. At least three subunit vaccine candidates containing ESAT6-like proteins as antigen components of multimeric proteins have shown efficacy in phase 1 and phase II clinical trials in humans.

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.

Computational approaches in epitope design using DNA binding proteins as vaccine candidate in Mycobacterium tuberculosis

Mycobacterium tuberculosis (Mtb) is a successful pathogen in the history of mankind. A high rate of mortality and morbidity raises the need for vaccine development. Mechanism of pathogenesis, survival strategy and virulence determinant are needed to be explored well for this pathogen. The involvement of DNA binding proteins in the regulation of virulence genes, transcription, DNA replication, repair make them more significant. In present work, we have identified 1453 DNA binding proteins (DBPs) in the 4173 genes of Mtb through the DNABIND tool and they were subjected for further screening by incorporating different bioinformatics tools. The eighteen DBPs were selected for the B-cell epitope prediction by using ABCpred server. Moreover, the B-cell epitope bearing the antigenic and non- allergenic property were selected for T-cell epitope prediction using ProPredI, and ProPred server. Finally, DGIGSAVSV (Rv1088), IRALPSSRH (Rv3923c), LTISPIANS (Rv3235), VQPSGKGGL (Rv2871) VPRPGPRPG (Rv2731) and VGQKINPHG (Rv0707) were identified as T-cell epitopes. The structural modelling of these epitopes and DBPs was performed to ensure the localization of these epitopes on the respective proteins. The interaction studies of these epitopes with human HLA confirmed their validation to be used as potential vaccine candidates. Collectively, these results revealed that the DBPs- Rv2731, Rv3235, Rv1088, Rv0707, Rv3923c and Rv2871 are the most appropriate vaccine candidates. In our knowledge, it is the first report of using the DBPs of Mtb for epitope prediction. Significantly, this study also provides evidence to be useful for designing a peptide-based vaccine against tuberculosis.

Designing and evaluation of an antibody-targeted chimeric recombinant vaccine encoding Shigella flexneri outer membrane antigens

Shigellosis is one of the most common diseases found in the developing countries, especially those countries that are prone flood. The causative agent for this disease is the Shigella species. This organism is one of the third most common enteropathogens responsible for childhood diarrhea. Since Shigella can survive gastric acidity and is an intracellular pathogen, it becomes difficult to treat. Also, uncontrolled use of antibiotics has led to development of resistant strains which poses a threat to public health. Therefore, there is a need for long term control of Shigella infection which can be achieved by designing a proper and effective vaccine. In this study, emphasis was made on designing a candidate that could elicit both B-cell and T-cell immune response. Hence B- and T-cell epitopes of outer membrane channel protein (OM) and putative lipoprotein (PL) from S. flexneri 2a were computationally predicted using immunoinformatics approach and a chimeric construct (chimeric-OP) containing the immunogenic epitopes selected from OM and PL was designed, cloned and expressed in E. coli system. The immunogenicity of the recombinant chimeric-OP was assessed using Shigella antigen infected rabbit antibody. The result showed that the chimeric-OP was a synthetic peptide candidate suitable for the development of vaccine and immunodiagnostics against Shigella infection.

Epitope-Based Vaccine Designing of Nocardia asteroides Targeting the Virulence Factor Mce-Family Protein by Immunoinformatics Approach

Nocardia asteroides is the main causative agent responsible for nocardiosis disease in immunocompromised patient viz. Acquired Immunodeficiency Syndrome (AIDS), malignancy, diabetic, organ recipient and genetic disorders. The virulence factor and outer membrane protein pertains immense contribution towards the designing of epitopic vaccine and limiting the robust outbreak of diseases. While epitopic based vaccine element carrying B and T cell epitope along with adjuvant is highly immunoprophylactic in nature. Present research equips immunoinformatics to figure out the suitable epitopes for effective vaccine designing. The selected epitopes VLGSSVQTA, VNIELKPEF and VVPSNLFAV amino acids sequence are identified by HLA-DRB alleles of both MHC class (MHC-I and II) molecules. Simultaneously, these also accessible to B-cell, confirmed through the ABCPred server. Antigenic property expression is validated by the Vaxijen antigenic prediction web portal. Molecular docking between the epitopes and T cell receptor delta chain authenticate the accurate interaction between epitope and receptor with significantly low binding energy. Easy access of epitopes to immune system also be concluded as transmembrane nature of the protein verified by using of TMHMM server. Appropriate structural identity of the virulence factor Mce-family protein generated through Phyre2 server and subsequently validated by ProSA and PROCHECK program suite. The structural configuration of theses epitopes also shaped using DISTILL web server. Both the structure of epitopes and protein will contribute a significant step in designing of epitopic vaccine against N. asteroides. Therefore, such immunoinformatics based computational drive definitely provides a conspicuous impel towards the development of epitopic vaccine as a promising remedy of nocardiosis.

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.

The Utility of Supertype Clustering in Prediction for Class II MHC-Peptide Binding

MOTIVATION

Extensive efforts have been devoted to understanding the antigenic peptides binding to MHC class I and II molecules since they play a fundamental role in controlling immune responses and due their involvement in vaccination, transplantation, and autoimmunity. The genes coding for the MHC molecules are highly polymorphic, and it is difficult to build computational models for MHC molecules with few know binders. On the other hand, previous studies demonstrated that some MHC molecules share overlapping peptide binding repertoires and attempted to group them into supertypes. Herein, we present a framework of the utility of supertype clustering to gain more information about the data to improve the prediction accuracy of class II MHC-peptide binding.

RESULTS

We developed a new method, called superMHC, for class II MHC-peptide binding prediction, including three MHC isotypes of HLA-DR, HLA-DP, and HLA-DQ, by using supertype clustering in conjunction with RLS regression. The supertypes were identified by using a novel repertoire dissimilarity index to quantify the difference in MHC binding specificities. The superMHC method achieves the state-of-the-art performance and is demonstrated to predict binding affinities to a series of MHC molecules with few binders accurately. These results have implications for understanding receptor-ligand interactions involved in MHC-peptide binding.

Improved methods for predicting peptide binding affinity to MHC class II molecules

Major histocompatibility complex class II (MHC-II) molecules are expressed on the surface of professional antigen-presenting cells where they display peptides to T helper cells, which orchestrate the onset and outcome of many host immune responses. Understanding which peptides will be presented by the MHC-II molecule is therefore important for understanding the activation of T helper cells and can be used to identify T-cell epitopes. We here present updated versions of two MHC-II-peptide binding affinity prediction methods, NetMHCII and NetMHCIIpan. These were constructed using an extended data set of quantitative MHC-peptide binding affinity data obtained from the Immune Epitope Database covering HLA-DR, HLA-DQ, HLA-DP and H-2 mouse molecules. We show that training with this extended data set improved the performance for peptide binding predictions for both methods. Both methods are publicly available at www.cbs.dtu.dk/services/NetMHCII-2.3 and www.cbs.dtu.dk/services/NetMHCIIpan-3.2.

In Silico Tools and Databases for Designing Peptide-Based Vaccine and Drugs

The prolonged conventional approaches of drug screening and vaccine designing prerequisite patience, vigorous effort, outrageous cost as well as additional manpower. Screening and experimentally validating thousands of molecules for a specific therapeutic property never proved to be an easy task. Similarly, traditional way of vaccination includes administration of either whole or attenuated pathogen, which raises toxicity and safety issues. Emergence of sequencing and recombinant DNA technology led to the epitope-based advanced vaccination concept, i.e., small peptides (epitope) can stimulate specific immune response. Advent of bioinformatics proved to be an adjunct in vaccine and drug designing. Genomic study of pathogens aid to identify and analyze the protective epitope. A number of in silico tools have been developed to design immunotherapy as well as peptide-based drugs in the last two decades. These tools proved to be a catalyst in drug and vaccine designing. This review solicits therapeutic peptide databases as well as in silico tools developed for designing peptide-based vaccine and drugs.

Proteome-scale identification of Leishmania infantum for novel vaccine candidates: A hierarchical subtractive approach

Vaccines are one of the most significant achievements in medical science. However, vaccine design is still challenging at all stages. The selection of antigenic peptides as vaccine candidates is the first and most important step for vaccine design. Experimental selection of antigenic peptides for the design of vaccines is a time-consuming, labor-intensive and expensive procedure. More recently, in the light of computer-aided biotechnology and reverse vaccinology, the precise selection of antigenic peptides and rational vaccine design against many pathogens have developed. In this study, the whole proteome of Leishmania infantum was analyzed using a pipeline of algorithms. From the set of 8045 proteins of L. infantum, sixteen novel antigenic proteins were derived using a hierarchical proteome subtractive analysis. These novel vaccine targets can be utilized as top candidates for designing the new prophylactic or therapeutic vaccines against visceral leishmaniasis. Significantly, all the sixteen novel vaccine candidates are non-allergen antigenic proteins that have not been used for the design of vaccines against visceral leishmaniasis until now.

A Platform for Designing Genome-Based Personalized Immunotherapy or Vaccine against Cancer

Due to advancement in sequencing technology, genomes of thousands of cancer tissues or cell-lines have been sequenced. Identification of cancer-specific epitopes or neoepitopes from cancer genomes is one of the major challenges in the field of immunotherapy or vaccine development. This paper describes a platform Cancertope, developed for designing genome-based immunotherapy or vaccine against a cancer cell. Broadly, the integrated resources on this platform are apportioned into three precise sections. First section explains a cancer-specific database of neoepitopes generated from genome of 905 cancer cell lines. This database harbors wide range of epitopes (e.g., B-cell, CD8+ T-cell, HLA class I, HLA class II) against 60 cancer-specific vaccine antigens. Second section describes a partially personalized module developed for predicting potential neoepitopes against a user-specific cancer genome. Finally, we describe a fully personalized module developed for identification of neoepitopes from genomes of cancerous and healthy cells of a cancer-patient. In order to assist the scientific community, wide range of tools are incorporated in this platform that includes screening of epitopes against human reference proteome (http://www.imtech.res.in/raghava/cancertope/).

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.

T-cell antigens of Mycobacterium immunogenum, an etiological agent of occupational hypersensitivity pneumonitis

The T lymphocyte-mediated immune lung disease hypersensitivity pneumonitis (HP) in machinists is poorly understood for disease mechanisms and diagnosis due in part to lack of information on causative T-cell antigens of the etiological agent Mycobacterium immunogenum (MI). Therefore, overall objective of the current study was to identify T-cell reactive antigens of this recently recognized pathogen. In this direction, purified recombinant form of five of the seroreactive proteins (reported in our initial study), including three cell wall-associated (arbitrarily designated as antigens A through C) and two secretory (AgD & AgE), were examined for their potential to activate antigen-presenting cells (APCs) viz. alveolar macrophages and human monocyte-derived dendritic cells (DCs) and for T-cell reactivity. All five proteins strongly activated APCs by inducing inflammatory cytokines (TNF-α, IL-6 & IL-1α) and nitric oxide (NO), albeit to a varying extent (AgE≥AgD>AgB≥AgA≥AgC), implying their differential potential for activation of APCs. However, only two of the five proteins (AgA, AgD) showed significant T-cell response (T lymphocyte proliferation and IFN-γ secretion) when tested using sensitized T-cells from MI-induced HP mouse model. These antigens also activated the human naïve CD4(+) T cells in presence of autologous DCs as measured using ELISPOT for IFN-γ. Immuno-informatic analysis predicted that the identified T-cell antigens (AgA and AgD) bind more number of class I and class II HLA alleles as compared with the reference immuno-dominant antigens ESAT-6 and CFP-10 from the tuberculous mycobacterial species M. tuberculosis. Predicted human population coverage for the epitopes of AgA (90.87%) and AgD (88.09%) was also higher as compared to those for the reference antigens ESAT-6 (82.42%) and CFP-10 (80.21%). These two antigens were further predicted to be highly immunogenic for class I peptide MHC (pMHC) complex as compared to the reference antigens. Collectively, our results imply that AgA and AgD are T-cell antigens with a high HLA binding frequency as well as population coverage for HLA alleles. This first report on T-cell antigens and epitopes of M. immunogenum is significant as it is expected to open up avenues for understanding pathogenesis mechanisms and developing T-cell-based immunodiagnostic tools for this poorly investigated occupational lung disease.

Immunoprotective responses of T helper type 1 stimulatory protein-S-adenosyl-L-homocysteine hydrolase against experimental visceral leishmaniasis

It is well known that a patient in clinical remission of visceral leishmaniasis (VL) remains immune to reinfection, which provides a rationale for the feasibility of a vaccine against this deadly disease. In earlier studies, observation of significant cellular responses in treated Leishmania patients as well as in hamsters against leishmanial antigens from different fractions led to its further proteomic characterization, wherein S-adenosyl-L-homocysteine hydrolase (AdoHcy) was identified as a helper type 1 (Th1) stimulatory protein. The present study includes immunological characterization of this protein, its cellular responses [lymphoproliferation, nitric oxide (NO) production and cytokine responses] in treated Leishmania-infected hamsters and patients as well as prophylactic efficacy against Leishmania challenge in hamsters and the immune responses generated thereof. Significantly higher cellular responses were noticed against recombinant L. donovani S-adenosyl-L-homocysteine hydrolase (rLdAdoHcy) compared to soluble L. donovani antigen in treated samples. Moreover, stimulation of peripheral blood mononuclear cells with rLdAdoHcy up-regulated the levels of interferon (IFN)-γ, interleukin (IL)-12 and down-regulated IL-10. Furthermore, vaccination with rLdAdoHcy generated perceptible delayed-type hypersensitivity response and exerted considerably good prophylactic efficacy (∼70% inhibition) against L. donovani challenge. The efficacy was confirmed by the increased expression levels of inducible NO synthase and Th1-type cytokines, IFN-γ and IL-12 and down-regulation of IL-4, IL-10 and transforming growth factor (TGF)-β. The results indicate the potentiality of rLdAdoHcy protein as a suitable vaccine candidate against VL.

Major histocompatibility complex linked databases and prediction tools for designing vaccines

Presently, the major histocompatibility complex (MHC) is receiving considerable interest owing to its remarkable role in antigen presentation and vaccine design. The specific databases and prediction approaches related to MHC sequences, structures and binding/nonbinding peptides have been aggressively developed in the past two decades with their own benchmarks and standards. Before using these databases and prediction tools, it is important to analyze why and how the tools are constructed along with their strengths and limitations. The current review presents insights into web-based immunological bioinformatics resources that include searchable databases of MHC sequences, epitopes and prediction tools that are linked to MHC based vaccine design, including population coverage analysis. In T cell epitope forecasts, MHC class I binding predictions are very accurate for most of the identified MHC alleles. However, these predictions could be further improved by integrating proteasome cleavage (in conjugation with transporter associated with antigen processing (TAP) binding) prediction, as well as T cell receptor binding prediction. On the other hand, MHC class II restricted epitope predictions display relatively low accuracy compared to MHC class I. To date, pan-specific tools have been developed, which not only deliver significantly improved predictions in terms of accuracy, but also in terms of the coverage of MHC alleles and supertypes. In addition, structural modeling and simulation systems for peptide-MHC complexes enable the molecular-level investigation of immune processes. Finally, epitope prediction tools, and their assessments and guidelines, have been presented to immunologist for the design of novel vaccine and diagnostics.

In silico epitope analysis of unique and membrane associated proteins from Mycobacterium avium subsp. paratuberculosis for immunogenicity and vaccine evaluation

Mycobacterium avium subsp. paratuberculosis (MAP) is the etiologic agent of paratuberculosis disease affecting ruminants worldwide. The aim of this study was to identify potential candidate antigens and epitopes by bio and immuno-informatic tools which could be later evaluated as vaccines and/or diagnosis. 110 protein sequences were selected from MAP K-10 genome database: 48 classified as putative enzymes involved in surface polysaccharide and lipopolysaccharide synthesis, as membrane associated and secreted proteins, 32 as conserved membrane proteins, and 30 as absent from other mycobacterial genomes. These 110 proteins were preliminary screened for Major Histocompatibility Complex (MHC) class II affinity and promiscuity using ProPred program. In addition, subcellular localization and host protein homology was analyzed. From these analyses, 23 MAP proteins were selected for a more accurate inmunoinformatic analysis (i.e. T cell and B cell epitopes analysis) and for homology with mycobacterial proteins. Finally, eleven MAP proteins were identified as potential candidates for further immunogenic evaluation: six proteins (MAP0228c, MAP1239c, MAP2232, MAP3080, MAP3131 and MAP3890) were identified as presenting potential T cell epitopes, while 5 selected proteins (MAP0232c, MAP1240c, MAP1738, MAP2239 and MAP3641c) harbored a large numbers of epitopes predicted to induce both cell- and antibody-mediated immune responses. Moreover, immunogenicity of selected epitopes from MAP1239c were evaluated in IFN-γ release assay. In summary, eleven M. avium subsp. paratuberculosis proteins were identified by in silico analysis and need to be further evaluated for their immunodiagnostic and vaccine potential in field and mice model.

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.

Characterization of a cross-reactive, immunodominant and HLA-promiscuous epitope of Mycobacterium tuberculosis-specific major antigenic protein PPE68

PPE68 (Rv3873), a major antignic protein encoded by Mycobacteriun tuberculosis-specific genomic region of difference (RD)1, is a strong stimulator of peripheral blood mononuclear cells (PBMCs) obtained from tuberculosis patients and Mycobacterium bovis bacillus Calmette Guerin (BCG)-vaccianted healthy subjects in T helper (Th)1 cell assays, i.e. antigen-induced proliferation and interferon-gamma (IFN-γ) secretion. To confirm the antigen-specific recognition of PPE68 by T cells in IFN-γ assays, antigen-induced human T-cell lines were established from PBMCs of M. Bovis BCG-vaccinated and HLA-heterogeneous healthy subjects and tested with peptide pools of RD1 proteins. The results showed that PPE68 was recognized by antigen-specific T-cell lines from HLA-heteregeneous subjects. To further identify the immunodominant and HLA-promiscuous Th1-1 cell epitopes present in PPE68, 24 synthetic peptides covering the sequence of PPE68 were indivdually analyzed for HLA-DR binding prediction analysis and tested with PBMCs from M. bovis BCG-vaccinated and HLA-heterogeuous healthy subjects in IFN-γ assays. The results identified the peptide P9, i.e. aa 121-VLTATNFFGINTIPIALTEMDYFIR-145, as an immunodominant and HLA-DR promiscuous peptide of PPE68. Furthermore, by using deletion peptides, the immunodominant and HLA-DR promiscuous core sequence was mapped to aa 127-FFGINTIPIA-136. Interestingly, the core sequence is present in several PPE proteins of M. tuberculosis, and conserved in all sequenced strains/species of M. tuberculosis and M. tuberculosis complex, and several other pathogenic mycobacterial species, including M. leprae and M. avium-intracellulalae complex. These results suggest that the peptide aa 121-145 may be exploited as a peptide-based vaccine candidate against tuberculosis and other mycobacterial diseases.

From genome screening to creation of vaccine against Trypanosoma cruzi by use of immunoinformatics

Chagas disease is caused by the protozoan parasite Trypanosoma cruzi, and activation of CD8(+) T cells is crucial for a protective immune response. Therefore, the identification of antigens with major histocompatibility complex class I epitopes is a crucial step for vaccine development against T. cruzi. Our aim was to identify novel antigens and epitopes by immunoinformatics analysis of the parasite proteome (12 969 proteins) and to validate their immunotherapeutic potential in infected mice. We identified 172 predicted epitopes, using NetMHC and RANKPEP. The corresponding protein sequences were reanalyzed to generate a consensus prediction, and 26 epitopes were selected for in vivo validation. The interferon γ (IFN-γ) recall response of splenocytes from T. cruzi-infected mice confirmed that 10 of 26 epitopes (38%) induced IFN-γ production. The immunotherapeutic potential of a mixture of all 10 peptides was evaluated in infected mice. The therapeutic vaccine was able to control T. cruzi infection, as evidenced by reduced parasitemia, cardiac tissue inflammation, and parasite burden and increased survival. These findings illustrate the benefits of this approach for the rapid development of a vaccine against pathogens with large genomes. The identified peptides and the proteins from which they are derived are excellent candidates for the development of a vaccine against T. cruzi.

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.

Novel approaches in polyepitope T-cell vaccine development against HIV-1

RV144 clinical trial was modestly effective in preventing HIV infection. New alternative approaches are needed to design improved HIV-1 vaccines and their delivery strategies. One of these approaches is construction of synthetic polyepitope HIV-1 immunogen using protective T- and B-cell epitopes that can induce broadly neutralizing antibodies and responses of cytotoxic (CD8(+) CTL) and helpers (CD4(+) Th) T-lymphocytes. This approach seems to be promising for designing of new generation of vaccines against HIV-1, enables in theory to cope with HIV-1 antigenic variability, focuses immune responses on protective determinants and enables to exclude from the vaccine compound that can induce autoantibodies or antibodies enhancing HIV-1 infectivity. Herein, the authors will focus on construction and rational design of polyepitope T-cell HIV-1 immunogens and their delivery, including: advantages and disadvantages of existing T-cell epitope prediction methods; features of organization of polyepitope immunogens, which can generate high-level CD8(+) and CD4(+) T-lymphocyte responses; the strategies to optimize efficient processing, presentation and immunogenicity of polyepitope constructs; original software to design polyepitope immunogens; and delivery vectors as well as mucosal strategies of vaccination. This new knowledge may bring us a one step closer to developing an effective T-cell vaccine against HIV-1, other chronic viral infections and cancer.

Structure-guided deimmunization of therapeutic proteins

Therapeutic proteins continue to yield revolutionary new treatments for a growing spectrum of human disease, but the development of these powerful drugs requires solving a unique set of challenges. For instance, it is increasingly apparent that mitigating potential anti-therapeutic immune responses, driven by molecular recognition of a therapeutic protein's peptide fragments, may be best accomplished early in the drug development process. One may eliminate immunogenic peptide fragments by mutating the cognate amino acid sequences, but deimmunizing mutations are constrained by the need for a folded, stable, and functional protein structure. These two concerns may be competing, as the mutations that are best at reducing immunogenicity often involve amino acids that are substantially different physicochemically. We develop a novel approach, called EpiSweep, that simultaneously optimizes both concerns. Our algorithm identifies sets of mutations making such Pareto optimal trade-offs between structure and immunogenicity, embodied by a molecular mechanics energy function and a T-cell epitope predictor, respectively. EpiSweep integrates structure-based protein design, sequence-based protein deimmunization, and algorithms for finding the Pareto frontier of a design space. While structure-based protein design is NP-hard, we employ integer programming techniques that are efficient in practice. Furthermore, EpiSweep only invokes the optimizer once per identified Pareto optimal design. We show that EpiSweep designs of regions of the therapeutics erythropoietin and staphylokinase are predicted to outperform previous experimental efforts. We also demonstrate EpiSweep's capacity for deimmunization of the entire proteins, case analyses involving dozens of predicted epitopes, and tens of thousands of unique side-chain interactions. Ultimately, Epi-Sweep is a powerful protein design tool that guides the protein engineer toward the most promising immunotolerant biotherapeutic candidates.

Cellular immune responses to recombinant Mycobacterium bovis BCG constructs expressing major antigens of region of difference 1 of Mycobacterium tuberculosis

Besides being the most widely used vaccine directed against tuberculosis (TB) worldwide, Mycobacterium bovis BCG is also the most controversial vaccine in current use. Its protective efficacy varies widely in different parts of the world. One approach to improving the current BCG vaccine might be to produce recombinant BCG strains that express major antigens encoded by genes that are present in the M. tuberculosis-specific region of difference 1 (RD1), such as pe35, cfp10, and esat6. In this study, pe35, cfp10, and esat6 genes were cloned into shuttle plasmid pDE22 to generate the recombinant plasmids PDE22-PE35, PDE22-CFP10, and PDE22-ESAT6, which were electroporated into BCG to generate recombinant BCGs (rBCGs). The cellular immune responses (antigen-induced proliferation and secretion of selected T helper 1 [Th1], Th2, and anti-inflammatory cytokines, i.e., gamma interferon [IFN-γ], interleukin 5 [IL-5], and IL-10, respectively) that are specific to the proteins of cloned genes were studied by using spleen cells from mice immunized with native BCGs and rBCGs and synthetic peptides covering the protein sequence of the cloned genes. The results showed that the spleen cells did not secrete IL-5, whereas IL-10 was secreted in response to peptides of all three proteins from mice immunized with rBCGs only, suggesting expression of the cloned genes and in vivo priming of spleen cells to the expressed proteins. However, in Th1 cell assays that correlate with protective cellular immune responses, i.e., antigen-induced proliferation and IFN-γ secretion, only mice immunized with rBCG-pDE22-PE35 yielded positive responses to the peptides of PE35. These results suggest that rBCG-PDE22-PE35 is the only one of the three vaccines used in this work that is worthy of consideration as a new vaccine candidate against TB.

Computational approaches to identify common subunit vaccine candidates against bacterial meningitis

Bacterial meningitis, an infection of the membranes (meninges) and cerebrospinal fluid (CSF) surrounding the brain and spinal cord, is a major cause of death and disability all over the world. From perinatal period to adult, four common organisms responsible for most of the bacterial meningitis are Streptococcus pneumonia, Neisseria meningitidis, Haemophilus influenza and Staphylococcus aureus. As the disease is caused by more organisms, currently available vaccines for bacterial meningitis are specific and restricted to some of the serogroups or serotypes of each bacterium. In an effort to design common vaccine against bacterial meningitis, proteomes of the four pathogens were compared to extract seven common surface exposed ABC transporter proteins. Pro-Pred server was used to investigate the seven surface exposed proteins for promiscuous T-cell epitopes prediction. Predicted 22 T-cell epitopes were validated through published positive control, SYFPEITHI and immune epitope database to reduce the epitope dataset into seven. T-cell epitope 162-FMILPIFNV-170 of spermidine/putrescine ABC transporter permease (potH) protein was conserved across the four selected pathogens of bacterial meningitis. Hence, structural analysis was extended for epitope 162-FMILPIFNV-170. Crystal structures of HLA-DRB alleles were retrieved and structure of potH was modeled using Prime v3.0 for structural analysis. Computational docking of HLA-DRB alleles and epitope 162-FMILPIFNV-170 of potH was performed using Glide v5.7. RMSD and RMSF of simulation studies were analyzed by Desmond v3.2. The docking and simulation results revealed that the HLA-DRB-epitope complex was stable with interaction repressive function of HLA. Thus, the epitope would be ideal candidate for T-cell driven subunit vaccine design against bacterial meningitis.

Structure-based redesign of proteins for minimal T-cell epitope content

The protein universe displays a wealth of therapeutically relevant activities, but T-cell driven immune responses to non-"self" biological agents present a major impediment to harnessing the full diversity of these molecular functions. Mutagenic T-cell epitope deletion seeks to mitigate the immune response, but can typically address only a small number of epitopes. Here, we pursue a "bottom-up" approach that redesigns an entire protein to remain native-like but contain few if any immunogenic epitopes. We do so by extending the Rosetta flexible-backbone protein design software with an epitope scoring mechanism and appropriate constraints. The method is benchmarked with a diverse panel of proteins and applied to three targets of therapeutic interest. We show that the deimmunized designs indeed have minimal predicted epitope content and are native-like in terms of various quality measures, and moreover that they display levels of native sequence recovery comparable to those of non-deimmunized designs.

Optimization of multimeric human papillomavirus L2 vaccines

We sought to define the protective epitopes within the amino terminus of human papillomavirus (HPV) type 16 minor capsid protein L2. Passive transfer of mice with rabbit antisera to HPV16 L2 peptides 17–36, 32–51 and 65–81 provided significant protection against vaginal HPV16 challenge, whereas antisera to 47–66, 108–120 or 373–392 did not. Vaccination with L1 virus-like particles induces a high titer, but generally type-restricted neutralizing antibody response. Conversely, vaccination with L2 11–88, especially multimers thereof, induces antibodies that neutralize a broad range of papillomavirus types, albeit at lower titers than for L1 VLP. With the intent of enhancing the immunogenicity and the breadth of protection by focusing the immune response to the key protective epitopes, we designed L2 fusion proteins consisting of residues ∼11–88 of eight divergent mucosal HPV types 6, 16, 18, 31, 39, 51, 56, 73 (11–88×8) or residues ∼13–47 of fifteen HPV types (13–47×15). The 11–88×8 was significantly more immunogenic than 13–47×15 in Balb/c mice regardless of the adjuvant used, suggesting the value of including the 65–81 protective epitope in the vaccine. Since the L2 47–66 peptide antiserum failed to elicit significant protection, we generated an 11–88×8 construct deleted for this region in each subunit (11–88×8Δ). Mice were vaccinated with 11–88×8 and 11–88×8Δ to determine if deletion of this non-protective epitope enhanced the neutralizing antibody response. However, 11–88×8Δ was significantly less immunogenic than 11–88×8, and even the addition of a known T helper epitope, PADRE, to the construct (11–88×8ΔPADRE) failed to recover the immunogenicity of 11–88×8 in C57BL/6 mice, suggesting that while L2 47–66 is not a critical protective or T helper epitope, it nevertheless contributes to the immunogenicity of the L2 11–88×8 multimer vaccine.

Identification of Candidate Vaccine Antigens In Silico

The identification of immunogenic whole-protein antigens is fundamental to the successful discovery of candidate subunit vaccines and their rapid, effective, and efficient transformation into clinically useful, commercially successful vaccine formulations. In the wider context of the experimental discovery of vaccine antigens, with particular reference to reverse vaccinology, this chapter adumbrates the principal computational approaches currently deployed in the hunt for novel antigens: genome-level prediction of antigens, antigen identification through the use of protein sequence alignment-based approaches, antigen detection through the use of subcellular location prediction, and the use of alignment-independent approaches to antigen discovery. Reference is also made to the recent emergence of various expert systems for protein antigen identification.

In silico analysis and experimental validation of Mycobacterium tuberculosis -specific proteins and peptides of Mycobacterium tuberculosis for immunological diagnosis and vaccine development

Comparative analyses of the Mycobacterium tuberculosis genome with the genomes of other mycobacteria have led to the identification of several genomic regions of difference (RDs) between M. tuberculosis and M. bovis BCG. The identification of immunodominant and HLA-promiscuous antigens and peptides encoded by these RDs could be useful for diagnosis and the development of new vaccines against tuberculosis. The analysis of RD proteins and peptides by in silico methods (using computational programs to predict major and HLA-promiscuous antigenic proteins and peptides) and experimental validations (using peripheral blood mononuclear cells and sera from tuberculosis patients and BCG-vaccinated healthy subjects to assess antigen-specific cellular and humoral immune responses in vitro) identified several major antigens and peptides. To evaluate the in vivo potentials, the genes of immunodominant antigens were cloned and expressed in DNA vaccine vectors. Immunizations of experimental animals with the recombinant constructs induced antigen-specific cellular responses. Further experiments showed that each of these proteins had several T and B cell epitopes scattered throughout their sequence, which confirmed their strong immunogenicity. In conclusion, the bioinformatics-based in silico identification of promiscuous antigens and peptides of M. tuberculosis is a useful approach to identify new candidates important for diagnosis and vaccine applications.

Bioinformatic and empirical analysis of novel hypoxia-inducible targets of the human antituberculosis T cell response

We analyzed whole genome-based transcriptional profiles of Mycobacterium tuberculosis subjected to prolonged hypoxia to guide the discovery of novel potential Ags, by a combined bioinformatic and empirical approach. We analyzed the fold induction of the 100 most highly induced genes at 7 d of hypoxia, as well as transcript abundance, peptide-binding prediction (ProPred) adjusted for population-specific MHC class II allele frequency, and by literature search. Twenty-six candidate genes were selected by this bioinformatic approach and evaluated empirically using IFN-γ and IL-2 ELISPOT using immunodominant Ags (Acr-1, CFP-10, ESAT-6) as references. Twenty-three of twenty-six proteins induced an IFN-γ response in PBMCs of persons with active or latent tuberculosis. Five novel immunodominant proteins-Rv1957, Rv1954c, Rv1955, Rv2022c, and Rv1471-were identified that induced responses similar to CFP-10 and ESAT-6 in both magnitude and frequency. IL-2 responses were of lower magnitude than were those of IFN-γ. Only moderate evidence of infection stage-specific recognition of Ags was observed. Reconciliation of bioinformatic and empirical hierarchies of immunodominance revealed that Ags could be predicted, providing transcriptomic data were combined with peptide-binding prediction adjusted by population-specific MHC class II allele frequency.

Design and analysis of immune-evading enzymes for ADEPT therapy

The unparalleled specificity and activity of therapeutic proteins has reshaped many aspects of modern clinical practice, and aggressive development of new protein drugs promises a continued revolution in disease therapy. As a result of their biological origins, however, therapeutic proteins present unique design challenges for the biomolecular engineer. For example, protein drugs are subject to immune surveillance within the patient's body; this anti-drug immune response can compromise therapeutic efficacy and even threaten patient safety. Thus, there is a growing demand for broadly applicable protein deimmunization strategies. We have recently developed optimization algorithms that integrate computational prediction of T-cell epitopes and bioinformatics-based assessment of the structural and functional consequences of epitope-deleting mutations. Here, we describe the first experimental validation of our deimmunization algorithms using Enterobacter cloacae P99 β-lactamase, a component of antibody-directed enzyme prodrug cancer therapies. Compared with wild-type or a previously deimmunized variant, our computationally optimized sequences exhibited significantly less in vitro binding to human type II major histocompatibility complex immune molecules. At the same time, our globally optimal design exhibited wild-type catalytic proficiency. We conclude that our deimmunization algorithms guide the protein engineer towards promising immunoevasive candidates and thereby have the potential to streamline biotherapeutic development.

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.

Cellular immune responses in mice induced by M. tuberculosis PE35-DNA vaccine construct

The PE35 (Rv3872) gene of Mycobacterium tuberculosis is present in the region of difference (RD) one that is deleted in all vaccine strains of Mycobacterium bovis bacillus Calmette Guerin. The aim of this study was to clone PE35 DNA into a DNA vaccine plasmid with CMV promoter and interleukin-2 secretory signal and evaluate the recombinant plasmid for induction of antigen-specific cellular responses in mice. DNA corresponding to PE35 was PCR amplified from the genomic DNA of M. tuberculosis H(37) Rv, cloned into pGEMT-Easy vector and sub-cloned into the DNA vaccine vector pUMVC6. BALB/c mice were immunized with recombinant pUMVC6/PE35 and spleen cells were tested for T-helper (Th)1-type (antigen-induced proliferation and secretion of IFN-γ) and Th2-type (IL-5), and anti-inflammatory (IL-10) cytokine responses to pure recombinant PE35 protein and its synthetic peptides. Mice immunized with the recombinant plasmid DNA (pUMVC6/PE35) showed positive Th1-type cellular responses to pure PE35, but not to an irrelevant antigen, i.e. PPE68 (Rv3873). However, the vaccine construct did not induce antigen-specific Th2-type (IL-5) or anti-inflammatory (IL-10) reactivity to PE35. Testing with synthetic peptides showed that Th1-type cells recognizing various epitopes of PE35 were induced in mice immunized with pUMVC6/PE35 DNA. These results suggest that pUMVC6/PE35 may be useful as a safer vaccine candidate against TB.

Optimization of therapeutic proteins to delete T-cell epitopes while maintaining beneficial residue interactions

Exogenous enzymes, signaling peptides, and other classes of nonhuman proteins represent a potentially massive but largely untapped pool of biotherapeutic agents. Adapting a foreign protein for therapeutic use poses numerous design challenges. We focus here on one significant problem: modifying the protein to mitigate the immune response mounted against "non-self" proteins, while not adversely affecting the protein's stability or therapeutic activity. In order to propose such variants suitable for experimental evaluation, this paper develops a computational method to select sets of mutations predicted to delete immunogenic T-cell epitopes, as evaluated by a 9-mer potential, while simultaneously maintaining important residues and residue interactions, as evaluated by one- and two-body potentials. While this design problem is NP-hard, we develop an integer programming approach that works very well in practice. We demonstrate the effectiveness of our approach by developing plans for biotherapeutic proteins that, in previous studies, have been partially deimmunized via extensive experimental characterization and modification of limited segments. In contrast, our global optimization technique considers an entire protein and accounts for all residues, residue interactions, and epitopes in proposing candidates worth subjecting to experimental evaluation.

Comparative evaluation of MPT83 (Rv2873) for T helper-1 cell reactivity and identification of HLA-promiscuous peptides in Mycobacterium bovis BCG-vaccinated healthy subjects

MPT83 (Rv2873), a surface lipoprotein excreted in the culture of Mycobacterium tuberculosis, is immunoreactive in antibody assays in humans and animals and provides protection as a combined DNA vaccine in mice and cattle. This study was undertaken to determine the reactivity of MPT83 in T helper 1 (Th1)-cell assays, i.e., antigen-induced proliferation and gamma interferon (IFN-γ) secretion, using peripheral blood mononuclear cells (PBMCs) obtained from Mycobacterium bovis bacillus Calmette-Guérin (BCG)-vaccinated and/or M. tuberculosis-infected healthy subjects. PBMCs were tested with complex mycobacterial antigens and pools of synthetic peptides corresponding to MPT63, MPT83, MPB70, LppX, PPE68, CFP10, and ESAT-6. The results showed that MPT83 is among the strongest Th1 cell antigens of M. tuberculosis, and it was recognized equally strongly by BCG-vaccinated and by BCG-vaccinated and M. tuberculosis-infected healthy subjects. Furthermore, HLA heterogeneity of the responding donors suggested that MPT83 was presented to Th1 cells by several HLA-DR molecules. The analysis of the mature MPT83 sequence (amino acids [aa] 1 to 220) and its 14 overlapping synthetic peptides for binding prediction to HLA class II molecules and actual recognition of the peptides by PBMCs from HLA-DR-typed subjects in antigen-induced proliferation and IFN-γ assays suggested that Th1 cell epitopes were scattered throughout the sequence of MPT83. In addition, the HLA-promiscuous nature of at least three peptides, i.e., P11 (aa 151 to 175), P12 (aa 166 to 190), and P14 (aa 196 to 220), was suggested by HLA-DR binding predictions and recognition by HLA-DR heterogeneous donors in Th1 cell assays. These results support the inclusion of MPT83 in an antigen cocktail to develop a new antituberculosis vaccine.

Cytokines in response to proteins predicted in genomic regions of difference of Mycobacterium tuberculosis

Cellular immune responses are responsible for both protection and pathogenesis in tuberculosis, and are mediated/regulated by a complex network of pro-inflammatory, T helper (Th) type 1 and type 2 cytokines. In this study, the secretion of pro-inflammatory cytokines tumor necrosis factor-alpha (TNF-α), interleukin (IL)-6, IL-8 and IL-1β; Th1 cytokines interferon-gamma (IFN-γ), IL-2 and tumor necrosis factor-beta (TNF-β); and Th2 cytokines IL-4, IL-5 and IL-10 by the peripheral blood mononuclear cells (PBMCs) of pulmonary tuberculosis patients was studied. PBMCs were cultured in vitro in the absence and presence of complex mycobacterial antigens and peptides corresponding to 11 regions of difference (RD) of Mycobacterium tuberculosis that are deleted/absent in all vaccine strains of Mycobacterium bovis bacillus Calmette-Guérin (BCG). The culture supernatants were tested for secreted cytokines by FlowCytomix assay. PBMCs from the majority of patients (53-100%) spontaneously secreted detectable concentrations of all cytokines tested, except for IL2 (29%) and IL-10 (41%). The profiles of proinflammatory cytokines were largely similar for various complex antigens or RD peptides. However, with respect to Th1 and Th2 cytokines, the antigens could be divided into three groups; the first with Th1-bias (culture filtrate of M. tuberculosis, RD1, RD5, RD7, RD9 and RD10), the second with Th2-bias (whole cells and cell walls of M. tuberculosis, RD12, RD13 and RD15), and the third without Th1/Th2-bias (M. bovis BCG, RD4, RD6 and RD11). Complex mycobacterial antigens and RD proteins with Th1- and Th2-biases may have roles in protection and pathogenesis of tuberculosis, respectively.

Molecular cloning, expression, purification and immunological characterization of three low-molecular weight proteins encoded by genes in genomic regions of difference of mycobacterium tuberculosis

The aim of this study was to clone, express and purify three major antigenic proteins, i.e. Rv3874, Rv3875 and Rv3619c, encoded by genes located in regions of difference of Mycobacterium tuberculosis and characterize them for immunogenicity in rabbits. The respective genes were amplified using gene-specific primers and genomic DNA of M. tuberculosis by polymerase chain reaction. The amplified DNA were cloned into pGEM-T Easy and subcloned into pGES-TH-1 vector for high-level expression in Escherichia coli and efficient purification. The results showed that the three fusion proteins, i.e. glutathione-S-transferase (GST)-Rv3874, GST-Rv3875 and GST-Rv3619c, were expressed at high levels and were purified (free of the GST fusion partner) to homogeneity using glutathione-Sepharose and Ni-NTA agarose affinity matrix after cleavage of the column-bound fusion proteins by thrombin protease. The purified recombinant Rv3874, Rv3875 and Rv3619c proteins were immunogenic and induced antigen-specific antibodies in rabbits. Testing of the rabbit sera with overlapping synthetic peptides showed that the antibodies were induced to several epitopes that were scattered throughout the sequence of each protein. These results show immunogenicity of all the proteins for inducing antigen-specific antibodies in rabbits and demonstrate the usefulness of pGES-TH-1 vector for obtaining purified recombinant proteins of M. tuberculosis for immunological characterization.

Identification of HLA-DR4-restricted T-cell epitope on MPT51 protein, a major secreted protein derived from Mycobacterium tuberculosis using MPT51 overlapping peptides screening and DNA vaccination

We identified a novel HLA-DR4-restricted CD4+ T-cell epitope on a secreted antigen of Mycobacterium tuberculosis, MPT51, in 004149-MM HLA-DR4-transgenic mice which express HLA-DRB1*0401, but not murine MHC class II molecules. The mice were immunized with plasmid DNA encoding MPT51 using gene gun and interferon (IFN)-gamma production from the immune splenocytes was analyzed. In response to overlapping synthetic peptides covering the mature MPT51 sequence, only one peptide, p191-210, stimulated the splenocytes to produce IFN-gamma. Further analysis using flow cytometry and computer-assisted algorithm, ProPred, narrowed down the region of CD4+ T-cell epitope to p191-202. The CD4+ T-cell epitope would be feasible for vaccine design against tuberculosis as well as for analysis of MPT51-specific T-cells in M. tuberculosis infection.

MHC class II epitope predictive algorithms

SUMMARY

Major histocompatibility complex class II (MHC-II) molecules sample peptides from the extracellular space, allowing the immune system to detect the presence of foreign microbes from this compartment. To be able to predict the immune response to given pathogens, a number of methods have been developed to predict peptide-MHC binding. However, few methods other than the pioneering TEPITOPE/ProPred method have been developed for MHC-II. Despite recent progress in method development, the predictive performance for MHC-II remains significantly lower than what can be obtained for MHC-I. One reason for this is that the MHC-II molecule is open at both ends allowing binding of peptides extending out of the groove. The binding core of MHC-II-bound peptides is therefore not known a priori and the binding motif is hence not readily discernible. Recent progress has been obtained by including the flanking residues in the predictions. All attempts to make ab initio predictions based on protein structure have failed to reach predictive performances similar to those that can be obtained by data-driven methods. Thousands of different MHC-II alleles exist in humans. Recently developed pan-specific methods have been able to make reasonably accurate predictions for alleles that were not included in the training data. These methods can be used to define supertypes (clusters) of MHC-II alleles where alleles within each supertype have similar binding specificities. Furthermore, the pan-specific methods have been used to make a graphical atlas such as the MHCMotifviewer, which allows for visual comparison of specificities of different alleles.