Modeling the MHC class I pathway by combining predictions of proteasomal cleavage, TAP transport and MHC class I binding

Intranasal Multiepitope PD-L1-siRNA-Based Nanovaccine: The Next-Gen COVID-19 Immunotherapy

The first approved vaccines for human use against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are nanotechnology-based. Although they are modular, rapidly produced, and can reduce disease severity, the currently available vaccines are restricted in preventing infection, stressing the global demand for novel preventive vaccine technologies. Bearing this in mind, we set out to develop a flexible nanovaccine platform for nasal administration to induce mucosal immunity, which is fundamental for optimal protection against respiratory virus infection. The next-generation multiepitope nanovaccines co-deliver immunogenic peptides, selected by an immunoinformatic workflow, along with adjuvants and regulators of the PD-L1 expression. As a case study, we focused on SARS-CoV-2 peptides as relevant antigens to validate the approach. This platform can evoke both local and systemic cellular- and humoral-specific responses against SARS-CoV-2. This led to the secretion of immunoglobulin A (IgA), capable of neutralizing SARS-CoV-2, including variants of concern, following a heterologous immunization strategy. Considering the limitations of the required cold chain distribution for current nanotechnology-based vaccines, it is shown that the lyophilized nanovaccine is stable for long-term at room temperature and retains its in vivo efficacy upon reconstitution. This makes it particularly relevant for developing countries and offers a modular system adaptable to future viral threats.

Next-generation IEDB tools: a platform for epitope prediction and analysis

The Next-Generation (NG) IEDB Tools website (https://nextgen-tools.iedb.org) provides users with a redesigned interface to many of the algorithms for epitope prediction and analysis that were originally released on the legacy IEDB Tools website. The initial release focuses on consolidation of all tools related to HLA class I epitopes (MHC binding, elution, immunogenicity, and processing), making all of these predictions accessible from a single application and allowing for their simultaneous execution with minimal user inputs. Additionally, the PEPMatch tool for identifying highly similar epitopes in a set of curated proteomes, as well as a tool for epitope clustering, are available on the site. The NG Tools site allows users to build data pipelines by sending the output of one tool as input for the next. Over the next several years, all pre-existing IEDB Tools, and any newly developed tools, will be integrated into this new site. Here we describe the philosophy behind the redesign and demonstrate the utility and productivity enhancements that are enabled by the new interface.

An immuno-informatics approach for annotation of hypothetical proteins and multi-epitope vaccine designed against the Mpox virus

A worrying new outbreak of Monkeypox (Mpox) in humans is caused by the Mpox virus (MpoxV). The pathogen has roughly 28 hypothetical proteins of unknown structure, function, and pathogenicity. Using reliable bioinformatics tools, we attempted to analyze the MpoxV genome, identify the role of hypothetical proteins (HPs), and design a potential candidate vaccine. Out of 28, we identified seven hypothetical proteins using multi-server validation with high confidence for the occurrence of conserved domains. Their physical, chemical, and functional characterizations, including molecular weight, theoretical isoelectric point, 3D structures, GRAVY value, subcellular localization, functional motifs, antigenicity, and virulence factors, were performed. We predicted possible cytotoxic T cell (CTL), helper T cell (HTL) and linear and conformational B cell epitopes, which were combined in a 219 amino acid multiepitope vaccine with human β defensin as a linker. This multi-epitopic vaccine was structurally modelled and docked with toll-like receptor-3 (TLR-3). The dynamical stability of the vaccine-TLR-3 docked complexes exhibited stable interactions based on RMSD and RMSF tests. Additionally, the modelled vaccine was cloned in-silico in an E. coli host to check the appropriate expression of the final vaccine built. Our results might conform to an immunogenic and safe vaccine, which would require further experimental validation.Communicated by Ramaswamy H. Sarma.

Cytomegalovirus UL44 protein induces a potent T-cell immune response in mice

Due to the severity of CMV infection in immunocompromised individuals the development of a vaccine has been declared a priority. However, despite the efforts made there is no yet a vaccine available for clinical use. We designed an approach to identify new CMV antigens able to inducing a broad immune response that could be used in future vaccine formulations. We have used serum samples from 28 kidney transplant recipients, with a previously acquired CMV-specific immune response to identify viral proteins that were recognized by the antibodies present in the patient serum samples by Western blot. A band of approximately 45 kDa, identified as UL44, was detected by most serum samples. UL44 immunogenicity was tested in BALB/c mice that received three doses of the UL44-pcDNA DNA vaccine. UL44 elicited both, a strong antibody response and CMV-specific cellular response. Using bioinformatic analysis we demonstrated that UL44 is a highly conserved protein and contains epitopes that are able to activate CD8 lymphocytes of the most common HLA alleles in the world population. We constructed a UL44 ORF deletion mutant virus that produced no viral progeny, suggesting that UL44 is an essential viral protein. In addition, other authors have demonstrated that UL44 is one of the most abundant viral proteins after infection and have suggested an essential role of UL44 in viral replication. Altogether, our data suggests that UL44 is a potent antigen, and favored by its abundance, it may be a good candidate to include in a vaccine formulation.

In silico designing of novel epitope-based peptide vaccines against HIV-1

The HIV-1 virus has been regarded as a catastrophe for human well-being. The global incidence of HIV-1-infected individuals is increasing. Hence, development of effective immunostimulatory molecules has recently attracted an increasing attention in the field of vaccine design against HIV-1 infection. In this study, we explored the impacts of CD40L and IFN-γ as immunostimulatory adjuvants for our candidate HIV-1 Nef vaccine in human and mouse using immunoinformatics analyses. Overall, 18 IFN-γ-based vaccine constructs (9 constructs in human and 9 constructs in mouse), and 18 CD40L-based vaccine constructs (9 constructs in human and 9 constructs in mouse) were designed. To find immunogenic epitopes, important characteristics of each component (e.g., MHC-I and MHC-II binding, and peptide-MHC-I/MHC-II molecular docking) were determined. Then, the selected epitopes were applied to create multiepitope constructs. Finally, the physicochemical properties, linear and discontinuous B cell epitopes, and molecular interaction between the 3D structure of each construct and CD40, IFN-γ receptor or toll-like receptors (TLRs) were predicted. Our data showed that the full-length CD40L and IFN-γ linked to the N-terminal region of Nef were capable of inducing more effective immune response than multiepitope vaccine constructs. Moreover, molecular docking of the non-allergenic full-length- and epitope-based CD40L and IFN-γ constructs to their cognate receptors, CD40 and IFN-γ receptors, and TLRs 4 and 5 in mouse were more potent than in human. Generally, these findings suggest that the full forms of these adjuvants could be more efficient for improvement of HIV-1 Nef vaccine candidate compared to the designed multiepitope-based constructs.

FASTMAP-a flexible and scalable immunopeptidomics pipeline for HLA- and antigen-specific T-cell epitope mapping based on artificial antigen-presenting cells

The study of peptide repertoires presented by major histocompatibility complex (MHC) molecules and the identification of potential T-cell epitopes contribute to a multitude of immunopeptidome-based treatment approaches. Epitope mapping is essential for the development of promising epitope-based approaches in vaccination as well as for innovative therapeutics for autoimmune diseases, infectious diseases, and cancer. It also plays a critical role in the immunogenicity assessment of protein therapeutics with regard to safety and efficacy concerns. The main challenge emerges from the highly polymorphic nature of the human leukocyte antigen (HLA) molecules leading to the requirement of a peptide mapping strategy for a single HLA allele. As many autoimmune diseases are linked to at least one specific antigen, we established FASTMAP, an innovative strategy to transiently co-transfect a single HLA allele combined with a disease-specific antigen into a human cell line. This approach allows the specific identification of HLA-bound peptides using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Using FASTMAP, we found a comparable spectrum of endogenous peptides presented by the most frequently expressed HLA alleles in the world's population compared to what has been described in literature. To ensure a reliable peptide mapping workflow, we combined the HLA alleles with well-known human model antigens like coagulation factor VIII, acetylcholine receptor subunit alpha, protein structures of the SARS-CoV-2 virus, and myelin basic protein. Using these model antigens, we have been able to identify a broad range of peptides that are in line with already published and in silico predicted T-cell epitopes of the specific HLA/model antigen combination. The transient co-expression of a single affinity-tagged MHC molecule combined with a disease-specific antigen in a human cell line in our FASTMAP pipeline provides the opportunity to identify potential T-cell epitopes/endogenously processed MHC-bound peptides in a very cost-effective, fast, and customizable system with high-throughput potential.

Dual T cell receptor/chimeric antigen receptor engineered NK-92 cells targeting the HPV16 E6 oncoprotein and the tumor-associated antigen L1CAM exhibit enhanced cytotoxicity and specificity against tumor cells

The human papillomavirus type 16 (HPV16) causes a large fraction of genital and oropharyngeal carcinomas. To maintain the transformed state, the tumor cells must continuously synthesize the E6 and E7 viral oncoproteins, which makes them tumor-specific antigens. Indeed, specific T cell responses against them have been well documented and CD8+ T cells engineered to express T cell receptors (TCRs) that recognize epitopes of E6 or E7 have been tested in clinical studies with promising results, yet with limited clinical success. Using CD8+ T cells from peripheral blood of healthy donors, we have identified two novel TCRs reactive to an unexplored E618-26 epitope. These TCRs showed limited standalone cytotoxicity against E618-26-HLA-A*02:01-presenting tumor cells. However, a single-signaling domain chimeric antigen receptor (ssdCAR) targeting L1CAM, a cell adhesion protein frequently overexpressed in HPV16-induced cancer, prompted a synergistic effect that significantly enhanced the cytotoxic capacity of NK-92/CD3/CD8 cells armored with both TCR and ssdCAR when both receptors simultaneously engaged their respective targets, as shown by live microscopy of 2-D and 3-D co-cultures. Thus, virus-specific TCRs from the CD8+ T cell repertoire of healthy donors can be combined with a suitable ssdCAR to enhance the cytotoxic capacity of the effector cells and, indirectly, their specificity.

Self-assembled peptide/polymer hybrid nanoplatform for cancer immunostimulating therapies

Integrating peptide epitopes in self-assembling materials is a successful strategy to obtain nanovaccines with high antigen density and improved efficacy. In this study, self-assembling peptides containing MAGE-A3/PADRE epitopes were designed to generate functional therapeutic nanovaccines. To achieve higher stability, peptide/polymer hybrid nanoparticles were formulated by controlled self-assembly of the engineered peptides. The nanoparticles showed good biocompatibility to both human red blood- and dendritic cells. Incubation of the nanoparticles with immature dendritic cells triggered immune effects that ultimately activated CD8 + cells. The antigen-specific and IgG antibody responses of healthy C57BL/6 mice vaccinated with the nanoparticles were analyzed. The in vivo results indicate a specific response to the nanovaccines, mainly mediated through a cellular pathway. This research indicates that the immunogenicity of peptide epitope vaccines can be effectively enhanced by developing self-assembled peptide-polymer hybrid nanostructures.

Immunoinformatics Approach to Design a Chimeric CD70-Peptide Vaccine against Renal Cell Carcinoma

Renal cell carcinoma (RCC) accounts for the majority of cancer-related deaths worldwide. Overexpression of CD70 has been linked to advanced stages of RCC. Therefore, this study aims to develop a multiepitope vaccine targeting the overexpressed CD70 using immunoinformatics techniques. In this investigation, in silico multiepitope vaccines were constructed by linking specific CD70 protein epitopes for helper T lymphocytes and CD8+ T lymphocytes. To enhance immunogenicity, sequences of cell-penetrating peptide (CPP), penetratin (pAntp), along with the entire sequence of tumor necrosis factor-α (TNF-α), were attached to the N-terminal and C-terminal of the CD70 epitopes. Computational assessments were performed on these chimeric vaccines for antigenicity, allergenicity, peptide toxicity, population coverage, and physicochemical properties. Furthermore, refined 3D constructs were subjected to a range of analyses, encompassing structural B-cell epitope prediction and molecular docking. The chosen vaccine construct underwent diverse assessments such as molecular dynamics simulation, immune response simulation, and in silico cloning. All vaccines comprised antigenic, nontoxic, and nonallergenic epitopes, ensuring extensive global population coverage. The vaccine constructs demonstrated favorable physicochemical characteristics. The binding affinity of chimeric vaccines to the TNF receptor remained relatively stable, influenced by the alignment of vaccine components. Molecular docking and dynamics analyses predicted stable interactions between CD70-CPP-TNF and the TNF receptor, indicating potential efficacy. In silico codon optimization and cloning of the vaccine nucleic acid sequence were accomplished using the pET28a plasmid. Furthermore, this vaccine displayed the capacity to modulate humoral and cellular immune responses. Overall, the results suggest therapeutic potential for the chimeric CD70-CPP-TNF vaccine against RCC. However, validation through in vitro and in vivo experiments is necessary. This trial is registered with NCT04696731 and NCT04046445.

Immunoinformatics-guided approach for designing a pan-proteome multi-epitope subunit vaccine against African swine fever virus

Despite being identified over a hundred years ago, there is still no commercially available vaccine for the highly contagious and deadly African swine fever virus (ASFV). This study used immunoinformatics for the rapid and inexpensive designing of a safe and effective multi-epitope subunit vaccine for ASFV. A total of 18,858 proteins from 100 well-annotated ASFV proteomes were screened using various computational tools to identify potential epitopes, or peptides capable of triggering an immune response in swine. Proteins from genotypes I and II were prioritized for their involvement in the recent global ASFV outbreaks. The screened epitopes exhibited promising qualities that positioned them as effective components of the ASFV vaccine. They demonstrated antigenicity, immunogenicity, and cytokine-inducing properties indicating their ability to induce potent immune responses. They have strong binding affinities to multiple swine allele receptors suggesting a high likelihood of yielding more amplified responses. Moreover, they were non-allergenic and non-toxic, a crucial prerequisite for ensuring safety and minimizing any potential adverse effects when the vaccine is processed within the host. Integrated with an immunogenic 50S ribosomal protein adjuvant and linkers, the epitopes formed a 364-amino acid multi-epitope subunit vaccine. The ASFV vaccine construct exhibited notable immunogenicity in immune simulation and molecular docking analyses, and stable profiles in secondary and tertiary structure assessments. Moreover, this study designed an optimized codon for efficient translation of the ASFV vaccine construct into the Escherichia coli K-12 expression system using the pET28a(+) vector. Overall, both sequence and structural evaluations suggested the potential of the ASFV vaccine construct as a candidate for controlling and eradicating outbreaks caused by the pathogen.

Reverse vaccinology and immunoinformatics approach to design a chimeric epitope vaccine against Orientia tsutsugamushi

Scrub typhus is a vector-borne infectious disease caused by Orientia tsutsugamushi and it is reportedly associated with up to 20 % of hospitalized cases of febrile illnesses. The major challenge of vaccine development is the lack of identified antigens that can induce both heterotypic and homotypic immunity including the production of antibodies, cytotoxic T lymphocyte, and helper T lymphocytes. We employed a comprehensive immunoinformatic prediction algorithm to identify immunogenic epitopes of the 56-kDa type-specific cell membrane surface antigen and surface cell antigen A of O. tsutsugamushi to select potential candidates for developing vaccines and diagnostic assays. We identified 35 linear and 29 continuous immunogenic B-cell epitopes and 51 and 27 strong-binding T-cell epitopes of major histocompatibility complex class I and class II molecules, respectively, in the conserved and variable regions of the 56-kDa type-specific surface antigen. The predicted B- and T-cell epitopes were used to develop immunogenic multi-epitope candidate vaccines and showed to elicit a broad-range of immune protection. A stable interactions between the multi-epitope vaccines and the host fibronectin protein were observed using docking and simulation methods. Molecular dynamics simulation studies demonstrated that the multi-epitope vaccine constructs and fibronectin docked models were stable during simulation time. Furthermore, the multi-epitope vaccine exhibited properties such as antigenicity, non-allergenicity and ability to induce interferon gamma production and had strong associations with their respective human leukocyte antigen alleles of world-wide population coverage. A correlation of immune simulations and the in-silico predicted immunogenic potential of multi-epitope vaccines implicate for further investigations to accelerate designing of epitope-based vaccine candidates and chimeric antigens for development of serological diagnostic assays for scrub typhus.

In Silico Tools for Predicting Novel Epitopes

Identifying antigens within a pathogen is a critical task to develop effective vaccines and diagnostic methods, as well as understanding the evolution and adaptation to host immune responses. Historically, antigenicity was studied with experiments that evaluate the immune response against selected fragments of pathogens. Using this approach, the scientific community has gathered abundant information regarding which pathogenic fragments are immunogenic. The systematic collection of this data has enabled unraveling many of the fundamental rules underlying the properties defining epitopes and immunogenicity, and has resulted in the creation of a large panel of immunologically relevant predictive (in silico) tools. The development and application of such tools have proven to accelerate the identification of novel epitopes within biomedical applications reducing experimental costs. This chapter introduces some basic concepts about MHC presentation, T cell and B cell epitopes, the experimental efforts to determine those, and focuses on state-of-the-art methods for epitope prediction, highlighting their strengths and limitations, and catering instructions for their rational use.

In-silico development of multi-epitope subunit vaccine against lymphatic filariasis

The World Health Organization in 2022 reported that more than 863 million people in 50 countries are at risk of developing lymphatic filariasis (LF), a disease caused by parasitic infection. Immune responses to parasites suggest that the development of a prophylactic vaccine against LF is possible. Using a reverse vaccinology approach, the current study identified Trehalose-6-phosphatase (TPP) as a potential vaccine candidate among 15 reported vaccine antigens for B. malayi. High-ranking B and T-cell epitopes in the Trehalose-6-phosphatase (TPP) were shortlisted using online servers for subsequent analysis. We selected these peptides to construct a vaccine model using I-TASSER and GalaxyRefine server. The vaccine construct showed favorable physicochemical properties, high antigenicity, no allergenicity, no toxicity, and high stability. Structural validation using the Ramachandran plot showed that 98% of the residues were in favorable or mostly allowed regions. Molecular docking and simulation showed a strong binding affinity and stability of the subunit vaccine with toll-like receptor 4 (TLR4). Furthermore, the subunit vaccine showed a strong IgG/IgM response, with the disappearance of the antigen. We propose that our vaccine construct should be further evaluated using cellular and animal models to develop a vaccine that is safe and effective against LF.Communicated by Ramaswamy H. Sarma.

Utilizing immunogenomic approaches to prioritize targetable neoantigens for personalized cancer immunotherapy

Advancements in sequencing technologies and bioinformatics algorithms have expanded our ability to identify tumor-specific somatic mutation-derived antigens (neoantigens). While recent studies have shown neoantigens to be compelling targets for cancer immunotherapy due to their foreign nature and high immunogenicity, the need for increasingly accurate and cost-effective approaches to rapidly identify neoantigens remains a challenging task, but essential for successful cancer immunotherapy. Currently, gene expression analysis and algorithms for variant calling can be used to generate lists of mutational profiles across patients, but more care is needed to curate these lists and prioritize the candidate neoantigens most capable of inducing an immune response. A growing amount of evidence suggests that only a handful of somatic mutations predicted by mutational profiling approaches act as immunogenic neoantigens. Hence, unbiased screening of all candidate neoantigens predicted by Whole Genome Sequencing/Whole Exome Sequencing may be necessary to more comprehensively access the full spectrum of immunogenic neoepitopes. Once putative cancer neoantigens are identified, one of the largest bottlenecks in translating these neoantigens into actionable targets for cell-based therapies is identifying the cognate T cell receptors (TCRs) capable of recognizing these neoantigens. While many TCR-directed screening and validation assays have utilized bulk samples in the past, there has been a recent surge in the number of single-cell assays that provide a more granular understanding of the factors governing TCR-pMHC interactions. The goal of this review is to provide an overview of existing strategies to identify candidate neoantigens using genomics-based approaches and methods for assessing neoantigen immunogenicity. Additionally, applications, prospects, and limitations of some of the current single-cell technologies will be discussed. Finally, we will briefly summarize some of the recent models that have been used to predict TCR antigen specificity and analyze the TCR receptor repertoire.

Characterization of exclusively non-commensal Neisseria gonorrhoeae pangenome to prioritize globally conserved and thermodynamically stable vaccine candidates using immune-molecular dynamic simulations

Neisseria gonorrhoeae (Ngo) has emerged as a global threat leading to one of the most common sexually transmitted diseases in the world. It has also become one of the leading antimicrobial resistant organisms, resulting in fewer treatment options and an increased morbidity. Therefore, in recent years, there has been an increased focus on the development of new treatments and preventive strategies to combat its infection. In this study, we have combined the most conserved epitopes from the completely assembled strains of Ngo to develop a universal and a thermodynamically stable vaccine candidate. For our vaccine design, the epitopes were selected for their high immunogenicity, non-allergenicity and non-cytotoxicity, making them the ideal candidates for vaccine development. For the screening process, several reverse vaccinology tools were employed to rigorously extract non-homologous and immunogenic epitopes from the selected proteins. Consequently, a total number of 3 B-cell epitopes and 6 T-cell epitopes were selected and joined by multiple immune-modulating adjuvants and linkers to generate a promiscuous immune response. Additionally, the stability and flexible nature of the vaccine construct was confirmed using various molecular dynamic simulation tools. Overall, the vaccine candidate showed promising binding affinity to various HLA alleles and TLR receptors; however, further studies are needed to assess its efficacy in-vivo. In this way, we have designed a multi-subunit vaccine candidate to potentially combat and control the spread of N. gonorrhoeae.

Immunotherapy of cytomegalovirus infection by low-dose adoptive transfer of antiviral CD8 T cells relies on substantial post-transfer expansion of central memory cells but not effector-memory cells

Cytomegaloviruses (CMVs) are host species-specific in their replication. It is a hallmark of all CMVs that productive primary infection is controlled by concerted innate and adaptive immune responses in the immunocompetent host. As a result, the infection usually passes without overt clinical symptoms and develops into latent infection, referred to as "latency". During latency, the virus is maintained in a non-replicative state from which it can reactivate to productive infection under conditions of waning immune surveillance. In contrast, infection of an immunocompromised host causes CMV disease with viral multiple-organ histopathology resulting in organ failure. Primary or reactivated CMV infection of hematopoietic cell transplantation (HCT) recipients in a "window of risk" between therapeutic hemato-ablative leukemia therapy and immune system reconstitution remains a clinical challenge. Studies in the mouse model of experimental HCT and infection with murine CMV (mCMV), followed by clinical trials in HCT patients with human CMV (hCMV) reactivation, have revealed a protective function of virus-specific CD8 T cells upon adoptive cell transfer (AT). Memory CD8 T cells derived from latently infected hosts are a favored source for immunotherapy by AT. Strikingly low numbers of these cells were found to prevent CMV disease, suggesting either an immediate effector function of few transferred cells or a clonal expansion generating high numbers of effector cells. In the murine model, the memory population consists of resting central memory T cells (TCM), as well as of conventional effector-memory T cells (cTEM) and inflationary effector-memory T cells (iTEM). iTEM increase in numbers over time in the latently infected host, a phenomenon known as 'memory inflation' (MI). They thus appeared to be a promising source for use in immunotherapy. However, we show here that iTEM contribute little to the control of infection after AT, which relies almost entirely on superior proliferative potential of TCM.

Novel "GaEl Antigenic Patches" Identified by a "Reverse Epitomics" Approach to Design Multipatch Vaccines against NIPAH Infection, a Silent Threat to Global Human Health

Nipah virus (NiV) is a zoonotic virus that causes lethal encephalitis and respiratory disease with the symptom of endothelial cell-cell fusion. Several NiV outbreaks have been reported since 1999 with nearly annual occurrences in Bangladesh. The outbreaks had high mortality rates ranging from 40 to 90%. No specific vaccine has yet been reported against NiV. Recently, several vaccine candidates and different designs of vaccines composed of epitopes against NiV were proposed. Most of the vaccines target single protein or protein complex subunits of the pathogen. The multiepitope vaccines proposed also cover a largely limited number of epitopes, and hence, their efficiency is still uncertain. To address the urgent need for a specific and effective vaccine against NiV infection, in the present study, we have utilized the "reverse epitomics" approach ("overlapping-epitope-clusters-to-patches" method) to identify "antigenic patches" (Ag-Patches) and utilize them as immunogenic composition for multipatch vaccine (MPV) design. The designed MPVs were analyzed for immunologically crucial parameters, physiochemical properties, and interaction with Toll-like receptor 3 ectodomain. In total, 30 CTL (cytotoxic T lymphocyte) and 27 HTL (helper T lymphocyte) antigenic patches were identified from the entire NiV proteome based on the clusters of overlapping epitopes. These identified Ag-Patches cover a total of discrete 362 CTL and 414 HTL epitopes from the entire proteome of NiV. The antigenic patches were utilized as immunogenic composition for the design of two CTL and two HTL multipatch vaccines. The 57 antigenic patches utilized here cover 776 overlapping epitopes targeting 52 different HLA class I and II alleles, providing a global ethnically distributed human population coverage of 99.71%. Such large number of epitope coverage resulting in large human population coverage cannot be reached with single-protein/subunit or multiepitope based vaccines. The reported antigenic patches also provide potential immunogenic composition for early detection diagnostic kits for NiV infection. Further, all the MPVs and Toll-like receptor ectodomain complexes show a stable nature of molecular interaction with numerous hydrogen bonds, salt bridges, and nonbounded contact formation and acceptable root mean square deviation and fluctuation. The cDNA analysis shows a favorable large-scale expression of the MPV constructs in a human cell line. By utilizing the novel "reverse epitomics" approach, highly immunogenic novel "GaEl antigenic patches" (GaEl Ag-Patches), a synonym term for "antigenic patches", were identified and utilized as immunogenic composition to design four MPVs against NiV. We conclude that the novel multipatch vaccines are potential candidates to combat NiV, with greater effectiveness, high specificity, and large human population coverage worldwide.

Preclinical proof of concept of a tetravalent lentiviral T-cell vaccine against dengue viruses

Dengue virus (DENV) is responsible for approximately 100 million cases of dengue fever annually, including severe forms such as hemorrhagic dengue and dengue shock syndrome. Despite intensive vaccine research and development spanning several decades, a universally accepted and approved vaccine against dengue fever has not yet been developed. The major challenge associated with the development of such a vaccine is that it should induce simultaneous and equal protection against the four DENV serotypes, because past infection with one serotype may greatly increase the severity of secondary infection with a distinct serotype, a phenomenon known as antibody-dependent enhancement (ADE). Using a lentiviral vector platform that is particularly suitable for the induction of cellular immune responses, we designed a tetravalent T-cell vaccine candidate against DENV ("LV-DEN"). This vaccine candidate has a strong CD8+ T-cell immunogenicity against the targeted non-structural DENV proteins, without inducing antibody response against surface antigens. Evaluation of its protective potential in the preclinical flavivirus infection model, i.e., mice knockout for the receptor to the type I IFN, demonstrated its significant protective effect against four distinct DENV serotypes, based on reduced weight loss, viremia, and viral loads in peripheral organs of the challenged mice. These results provide proof of concept for the use of lentiviral vectors for the development of efficient polyvalent T-cell vaccine candidates against all DENV serotypes.

Immunoinformatics studies of heat shock proteins 27 and 70: Development of potent therapeutic vaccine constructs against human papillomavirus-related cancers

Heat shock proteins (HSPs) improve cross-presentation of linked tumor antigens, thus they can be exploited in therapeutic vaccine design. Herein, in silico analyses of different vaccine constructs were performed based on human papillomavirus (HPV)-16 E7 protein linked to Homo sapiens/Mus musculus Hsp27 or Hsp70 in multiepitope and whole sequence forms. Then, computational comparison between different orientations of Hsp/E7 was carried out in both forms. Finally, molecular docking was performed between the designed constructs and signaling (TLRs) or endocytic (CD14, LOX-1 and SREC-1) receptors. Our data represented the high-ranked T-cell epitopes and the potential B-cell epitopes of Homo sapiens/Mus musculus Hsp27 and Hsp70. Moreover, molecular docking showed that whole sequence of Hsp27 had better interaction with all receptors than whole sequence of Hsp70 suggesting likely stronger stimulation of innate and adaptive immunity. All designed Homo sapiens/Mus musculus Hsp27/E7 constructs had better docking scores with the endocytic receptors especially SREC-1 than all designed Homo sapiens/Mus musculus Hsp70/E7 constructs in both orientations. Generally, the multiepitope-/whole sequence-based Homo sapiens/Mus musculus Hsp27-E7 fusion constructs showed more conservancy and immunogenicity than other designed constructs. These fusion constructs were non-allergenic, non-toxic and stable suggesting them as promising vaccine candidates against HPV-related cancers.

Identification of Bacterial Strains and Development of anmRNA-Based Vaccine to Combat Antibiotic Resistance in Staphylococcus aureus via In Vitro and In Silico Approaches

The emergence of antibiotic-resistant microorganisms is a significant concern in global health. Antibiotic resistance is attributed to various virulent factors and genetic elements. This study investigated the virulence factors of Staphylococcus aureus to create an mRNA-based vaccine that could help prevent antibiotic resistance. Distinct strains of the bacteria were selected for molecular identification of virulence genes, such as spa, fmhA, lukD, and hla-D, which were performed utilizing PCR techniques. DNA extraction from samples of Staphylococcus aureus was conducted using the Cetyl Trimethyl Ammonium Bromide (CTAB) method, which was confirmed and visualized using a gel doc; 16S rRNA was utilized to identify the bacterial strains, and primers of spa, lukD, fmhA, and hla-D genes were employed to identify the specific genes. Sequencing was carried out at Applied Bioscience International (ABI) in Malaysia. Phylogenetic analysis and alignment of the strains were subsequently constructed. We also performed an in silico analysis of the spa, fmhA, lukD, and hla-D genes to generate an antigen-specific vaccine. The virulence genes were translated into proteins, and a chimera was created using various linkers. The mRNA vaccine candidate was produced utilizing 18 epitopes, linkers, and an adjuvant, known as RpfE, to target the immune system. Testing determined that this design covered 90% of the population conservancy. An in silico immunological vaccine simulation was conducted to verify the hypothesis, including validating and predicting secondary and tertiary structures and molecular dynamics simulations to evaluate the vaccine’s long-term viability. This vaccine design may be further evaluated through in vivo and in vitro testing to assess its efficacy.

Immunoinformatics aided approach for predicting potent cytotoxic T cell epitopes of respiratory syncytial virus

Respiratory syncytial virus (RSV) is an infectious viral pathogen that causing serious respiratory infection in adults and neonates. The only approved therapies for RSV are the monoclonal antibodies palivizumab and its derivative motavizumab. Both treatments are expensive and require a hospital setting for administration. A vaccine represents a safe, effective and cheaper alternative for preventing RSV infection. In silico prediction methods have proven to be valuable in speeding up the process of vaccine design. In this study, reverse vaccinology methods were used to predict the cytotoxic T lymphocytes (CTL) epitopes from the entire proteome of RSV strain A. From amongst 3402 predicted binders to 12 high frequency alleles from the Immune Epitope Database (IEDB), 567 had positive processing scores while 327 epitopes were predicted to be immunogenic. A thorough examination of the 327 epitopes for possible antigenicity, allergenicity and toxicity resulted in 95 epitopes with desirable properties. A BLASTp analysis revealed 94 unique and non-homologous epitopes that were subjected to molecular docking across the 12 high frequency alleles. The final dataset of 70 epitopes contained 13 experimentally proven and 57 unique epitopes from a total of 11 RSV proteins. From our findings on selected T-cell-specific RSV antigen epitopes, notably the four epitopes confirmed to exhibit stable binding by molecular dynamics. The prediction pipeline used in this study represents an effective way to screen the immunogenic epitopes from other pathogens.Communicated by Ramaswamy H. Sarma.

Contemplating immunopeptidomes to better predict them

The identification of T-cell epitopes is key for a complete molecular understanding of immune recognition mechanisms in infectious diseases, autoimmunity and cancer. T-cell epitopes further provide targets for personalized vaccines and T-cell therapy, with several therapeutic applications in cancer immunotherapy and elsewhere. T-cell epitopes consist of short peptides displayed on Major Histocompatibility Complex (MHC) molecules. The recent advances in mass spectrometry (MS) based technologies to profile the ensemble of peptides displayed on MHC molecules - the so-called immunopeptidome - had a major impact on our understanding of antigen presentation and MHC ligands. On the one hand, these techniques enabled researchers to directly identify hundreds of thousands of peptides presented on MHC molecules, including some that elicited T-cell recognition. On the other hand, the data collected in these experiments revealed fundamental properties of antigen presentation pathways and significantly improved our ability to predict naturally presented MHC ligands and T-cell epitopes across the wide spectrum of MHC alleles found in human and other organisms. Here we review recent computational developments to analyze experimentally determined immunopeptidomes and harness these data to improve our understanding of antigen presentation and MHC binding specificities, as well as our ability to predict MHC ligands. We further discuss the strengths and limitations of the latest approaches to move beyond predictions of antigen presentation and tackle the challenges of predicting TCR recognition and immunogenicity.

Exploring the structural basis to develop efficient multi-epitope vaccines displaying interaction with HLA and TAP and TLR3 molecules to prevent NIPAH infection, a global threat to human health

Nipah virus (NiV) is an emerging zoonotic virus that caused several serious outbreaks in the south asian region with high mortality rates ranging from 40 to 90% since 2001. NiV infection causes lethal encephalitis and respiratory disease with the symptom of endothelial cell-cell fusion. No specific and effective vaccine has yet been reported against NiV. To address the urgent need for a specific and effective vaccine against NiV infection, in the present study, we have designed two Multi-Epitope Vaccines (MEVs) composed of 33 Cytotoxic T lymphocyte (CTL) epitopes and 38 Helper T lymphocyte (HTL) epitopes. Out of those CTL and HTL combined 71 epitopes, 61 novel epitopes targeting nine different NiV proteins were not used before for vaccine design. Codon optimization for the cDNA of both the designed MEVs might ensure high expression potential in the human cell line as stable proteins. Both MEVs carry potential B cell linear epitope overlapping regions, B cell discontinuous epitopes as well as IFN-γ inducing epitopes. Additional criteria such as sequence consensus amongst CTL, HTL and B Cell epitopes was implemented for the design of final constructs constituting MEVs. Hence, the designed MEVs carry the potential to elicit cell-mediated as well as humoral immune response. Selected overlapping CTL and HTL epitopes were validated for their stable molecular interactions with HLA class I and II alleles and in case of CTL epitopes with human Transporter Associated with antigen Processing (TAP) cavity. The structure based epitope cross validation for interaction with TAP cavity was used as another criteria choosing final epitopes for NiV MEVs. Finally, human Beta-defensin 2 and Beta-defensin 3 were used as adjuvants to enhance the immune response of both the MEVs. Molecular dynamics simulation studies of MEVs-TLR3 ectodomain (Human Toll-Like Receptor 3) complex indicated the stable molecular interaction. We conclude that the MEVs designed and in silico validated here could be highly potential vaccine candidates to combat NiV infections, with great effectiveness, high specificity and large human population coverage worldwide.

Designing of cytotoxic T lymphocyte-based multi-epitope vaccine against SARS-CoV2: a reverse vaccinology approach

SARS-CoV2 is a single-stranded RNA virus, gaining much attention after it out broke in China in December 2019. The virus rapidly spread to several countries around the world and caused severe respiratory illness to humans. Since the outbreak, researchers around the world have devoted maximum resources and effort to develop a potent vaccine that would offer protection to uninfected individuals against SARS-CoV2. Reverse vaccinology is a relatively new approach that thrives faster in vaccine research. In this study, we constructed Cytotoxic T Lymphocytes (CTL)-based multi-epitope vaccine using hybrid epitope prediction methods. A total of 121 immunogenic CTL epitopes were screened by various sequence-based prediction methods and docked with their respective HLA alleles using the AutoDock Vina v1.1.2. In all, 17 epitopes were selected based on their binding affinity, followed by the construction of multi-epitope vaccine by placing the appropriate linkers between the epitopes and tuberculosis heparin-binding hemagglutinin (HBHA) adjuvant. The final vaccine construct was modeled by the I-TASSER server and the best model was further validated by ERRAT, ProSA, and PROCHECK servers. Furthermore, the molecular interaction of the constructed vaccine with TLR4 was assessed by ClusPro 2.0 and PROtein binDIng enerGY prediction (PRODIGY) server. The immune simulation analysis confirms that the constructed vaccine was capable of inducing long-lasting memory T helper (Th) and CTL responses. Finally, the nucleotide sequence was codon-optimized by the JCAT tool and cloned into the pET21a (+) vector. The current results reveal that the candidate vaccine is capable of provoking robust CTL response against the SARS-CoV2.Communicated by Ramaswamy H. Sarma.

In silico design of epitope-based peptide vaccine against non-typhoidal Salmonella through immunoinformatic approaches

Non-typhoidal Salmonella (NTS) is one of the leading bacterial causes of many invasive human infections with a high antibiotic resistance profile. With this concern, the current study aimed to design an effective epitope-based peptide vaccine against NTS species as a successive and substitutive protective measure of invasive NTS disease. To design rationally, the current study considered a comprehensive in silico workflow combination of both immunoinformatics and molecular modeling approaches, including molecular docking and molecular dynamics (MD) simulation. We identified the two most promising T cell epitopes KVLYGIFAI and YGIFAITAL, and three B cell epitopes AAPVQVGEAAGS, TGGGDGSNT, and TGGGDGSNTGTTTT, in the outer membrane of NTS. Using these epitopes, a multiepitope vaccine was subsequently constructed along with appropriate adjuvant and linkers, which showed a good binding affinity and stability with toll-like receptor 2 (TLR2) in both molecular docking and MD simulation. Furthermore, in silico immune simulation described a strong immune response with a high number of antibodies, interferon-γ, and activated B and T cells. This study collectively suggests that predicted vaccine constructs could be considered potential vaccine candidates against common NTS species.Communicated by Ramaswamy H. Sarma.

Structural analysis of PpSP15 and PsSP9 sand fly salivary proteins designed with a self-cleavable linker as a live vaccine candidate against cutaneous leishmaniasis

Background

Leishmania parasites are deposited in the host through sand fly bites along with sand fly saliva. Therefore, salivary proteins are promising vaccine candidates for controlling leishmaniasis. Herein, two immunogenic salivary proteins, PpSP15 from Phlebotomus papatasi and PsSP9 from Phlebotomus sergenti, were selected as vaccine candidates to be delivered by live Leishmania tarentolae as vector. The stepwise in silico protocol advantaged in this study for multi-protein design in L. tarentolae is then described in detail.

Methods

All possible combinations of two salivary proteins, PpSP15 and PsSP9, with or without T2A peptide were designed at the mRNA and protein levels. Then, the best combination for the vaccine candidate was selected based on mRNA and protein stability along with peptide analysis.

Results

At the mRNA level, the most favored secondary structure was PpSP15-T2A-PsSP9. At the protein level, the refined three-dimensional models of all combinations were structurally valid; however, local quality estimation showed that the PpSp15-T2A-PsSP9 fusion had higher stability for each amino acid position, with low root-mean-square deviation (RMSD), compared with the original proteins. In silico evaluation confirmed the PpSP15-T2A-PsSP9 combination as a good Th1-polarizing candidate in terms of high IFN-γ production and low IL-10/TGF-β ratio in response to three consecutive immunizations. Potential protein expression was then confirmed by Western blotting.

Conclusions

The approach presented herein is among the first studies to have privileged protein homology modeling along with mRNA analysis for logical live vaccine design-coding multi-proteins.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13071-022-05437-x.

Vaccination-based immunotherapy to target profibrotic cells in liver and lung

Fibrosis is the final path of nearly every form of chronic disease, regardless of the pathogenesis. Upon chronic injury, activated, fibrogenic fibroblasts deposit excess extracellular matrix, and severe tissue fibrosis can occur in virtually any organ. However, antifibrotic therapies that target fibrogenic cells, while sparing homeostatic fibroblasts in healthy tissues, are limited. We tested whether specific immunization against endogenous proteins, strongly expressed in fibrogenic cells but highly restricted in quiescent fibroblasts, can elicit an antigen-specific cytotoxic T cell response to ameliorate organ fibrosis. In silico epitope prediction revealed that activation of the genes Adam12 and Gli1 in profibrotic cells and the resulting "self-peptides" can be exploited for T cell vaccines to ablate fibrogenic cells. We demonstrate the efficacy of a vaccination approach to mount CD8⁺ T cell responses that reduce fibroblasts and fibrosis in the liver and lungs in mice. These results provide proof of principle for vaccination-based immunotherapies to treat fibrosis.

Evaluating complete surface-associated and secretory proteome of Leishmania donovani for discovering novel vaccines and diagnostic targets

The protozoa Leishmania donovani causes visceral leishmaniasis (kala-azar), the third most common vector-borne disease. The visceral organs, particularly the spleen, liver, and bone marrow, are affected by the disease. The lack of effective treatment regimens makes curing and eradicating the disease difficult. The availability of complete L. donovani genome/proteome data allows for the development of specific and efficient vaccine candidates using the reverse vaccinology method, while utilizing the unique sequential and structural features of potential antigenic proteins to induce protective T cell and B cell responses. Such shortlisted candidates may then be tested quickly for their efficacy in the laboratory and later in clinical settings. These antigens will also be useful for designing antigen-based next-generation sero-diagnostic assays. L. donovani's cell surface-associated proteins and secretory proteins are among the first interacting entities to be exposed to the host immune machinery. As a result, potential antigenic epitope peptides derived from these proteins could serve as competent vaccine components. We used a stepwise filtering-based in silico approach to identify the entire surface-associated and secretory proteome of L. donovani, which may provide rationally selected most exposed antigenic proteins. Our study identified 12 glycosylphosphatidylinositol-anchored proteins, 45 transmembrane helix-containing proteins, and 73 secretory proteins as potent antigens unique to L. donovani. In addition, we used immunoinformatics to identify B and T cell epitopes in them. Out of the shortlisted surface-associated and secretory proteome, 66 protein targets were found to have the most potential overlapping B cell and T cell epitopes (linear and conformational; MHC class I and MHC class II).

Refining the DC-targeting vaccination for preventing emerging infectious diseases

The development of safe, long-term, effective vaccines is still a challenge for many infectious diseases. Thus, the search of new vaccine strategies and production platforms that allow rapidly and effectively responding against emerging or reemerging pathogens has become a priority in the last years. Targeting the antigens directly to dendritic cells (DCs) has emerged as a new approach to enhance the immune response after vaccination. This strategy is based on the fusion of the antigens of choice to monoclonal antibodies directed against specific DC surface receptors such as CD40. Since time is essential, in silico approaches are of high interest to select the most immunogenic and conserved epitopes to improve the T- and B-cells responses. The purpose of this review is to present the advances in DC vaccination, with special focus on DC targeting vaccines and epitope mapping strategies and provide a new framework for improving vaccine responses against infectious diseases.

Experimental Study of Potential CD8+ Trivalent Synthetic Peptides for Liver Cancer Vaccine Development Using Sprague Dawley Rat Models

Background. Liver cancer (LC) is the most devastating disease affecting a large set of populations in the world. The mortality due to LC is escalating, indicating the lack of effective therapeutic options. Immunotherapeutic agents may play an important role against cancer cells. As immune cells, especially T lymphocytes, which are part of cancer immunology, the design of vaccine candidates for cytotoxic T lymphocytes may be an effective strategy for curing liver cancer. Results. In our study, based on an immunoinformatics approach, we predicted potential T cell epitopes of MHC class I molecules using integrated steps of data retrieval, screening of antigenic proteins, functional analysis, peptide synthesis, and experimental in vivo investigations. We predicted the binding affinity of epitopes LLECADDRADLAKY, VSEHRIQDKDGLFY, and EYILSLEELVNGMY of LC membrane-bounded extracellular proteins including butyrophilin-like protein-2 (BTNL2), glypican-3 (GPC3), and serum albumin (ALB), respectively, with MHC class I molecules (allele: HLA-A $\ast$ 01:01). These T cell epitopes rely on the level of their binding energy and antigenic properties. We designed and constructed a trivalent immunogenic model by conjugating these epitopes with linkers to activate cytotoxic T cells. For validation, the nonspecific hematological assays showed a significant rise in the count of white blood cells ( $5\times {10}^9/\text{l}$ ), lymphocytes ( $13\times {10}^9/\text{l}$ ), and granulocytes ( $5\times {10}^9/\text{l}$ ) compared to the control after administration of trivalent peptides. Specific immunoassays including granzyme B and IgG ELISA exhibited the significant concentration of these effector molecules in blood serum, indicating the activity of cytotoxic T cells. Granzyme concentration increased to 1050 pg/ml at the second booster dose compared to the control (95 pg/ml), while the concentration of IgG raised to 6 g/l compared to the control (2 g/l). Conclusion. We concluded that a potential therapeutic trivalent vaccine can activate and modulate the immune system to cure liver cancer on the basis of significant outcomes of specific and nonspecific assays.

CAD v1.0: Cancer Antigens Database Platform for Cancer Antigen Algorithm Development and Information Exploration

Cancer vaccines have gradually attracted attention for their tremendous preclinical and clinical performance. With the development of next-generation sequencing technologies and related algorithms, pipelines based on sequencing and machine learning methods have become mainstream in cancer antigen prediction; of particular focus are neoantigens, mutation peptides that only exist in tumor cells that lack central tolerance and have fewer side effects. The rapid prediction and filtering of neoantigen peptides are crucial to the development of neoantigen-based cancer vaccines. However, due to the lack of verified neoantigen datasets and insufficient research on the properties of neoantigens, neoantigen prediction algorithms still need to be improved. Here, we recruited verified cancer antigen peptides and collected as much relevant peptide information as possible. Then, we discussed the role of each dataset for algorithm improvement in cancer antigen research, especially neoantigen prediction. A platform, Cancer Antigens Database (CAD, http://cad.bio-it.cn/), was designed to facilitate users to perform a complete exploration of cancer antigens online.

The Importance of Being Presented: Target Validation by Immunopeptidomics for Epitope-Specific Immunotherapies

Presentation of tumor-specific or tumor-associated peptides by HLA class I molecules to CD8⁺ T cells is the foundation of epitope-centric cancer immunotherapies. While often in silico HLA binding predictions or in vitro immunogenicity assays are utilized to select candidates, mass spectrometry-based immunopeptidomics is currently the only method providing a direct proof of actual cell surface presentation. Despite much progress in the last decade, identification of such HLA-presented peptides remains challenging. Here we review typical workflows and current developments in the field of immunopeptidomics, highlight the challenges which remain to be solved and emphasize the importance of direct target validation for clinical immunotherapy development.

A Vaccine Construction against COVID-19-Associated Mucormycosis Contrived with Immunoinformatics-Based Scavenging of Potential Mucoralean Epitopes

Mucormycosis is a group of infections, caused by multiple fungal species, which affect many human organs and is lethal in immunocompromised patients. During the COVID-19 pandemic, the current wave of mucormycosis is a challenge to medical professionals as its effects are multiplied because of the severity of COVID-19 infection. The variant of concern, Omicron, has been linked to fatal mucormycosis infections in the US and Asia. Consequently, current postdiagnostic treatments of mucormycosis have been rendered unsatisfactory. In this hour of need, a preinfection cure is needed that may prevent lethal infections in immunocompromised individuals. This study proposes a potential vaccine construct targeting mucor and rhizopus species responsible for mucormycosis infections, providing immunoprotection to immunocompromised patients. The vaccine construct, with an antigenicity score of 0.75 covering, on average, 92-98% of the world population, was designed using an immunoinformatics approach. Molecular interactions with major histocompatibility complex-1 (MHC-I), Toll-like receptors-2 (TLR2), and glucose-regulated protein 78 (GRP78), with scores of -896.0, -948.4, and -925.0, respectively, demonstrated its potential to bind with the human immune receptors. It elicited a strong predicted innate and adaptive immune response in the form of helper T (Th) cells, cytotoxic T (TC) cells, B cells, natural killer (NK) cells, and macrophages. The vaccine cloned in the pBR322 vector showed positive amplification, further solidifying its stability and potential. The proposed construct holds a promising approach as the first step towards an antimucormycosis vaccine and may contribute to minimizing postdiagnostic burdens and failures.

Computationally validated SARS-CoV-2 CTL and HTL Multi-Patch vaccines, designed by reverse epitomics approach, show potential to cover large ethnically distributed human population worldwide

The SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) is responsible for the COVID-19 outbreak. The highly contagious COVID-19 disease has spread to 216 countries in less than six months. Though several vaccine candidates are being claimed, an effective vaccine is yet to come. A novel reverse epitomics approach, 'overlapping-epitope-clusters-to-patches' method is utilized to identify the antigenic regions from the SARS-CoV-2 proteome. These antigenic regions are named as 'Ag-Patch or Ag-Patches', for Antigenic Patch or Patches. The identification of Ag-Patches is based on the clusters of overlapping epitopes rising from SARS-CoV-2 proteins. Further, we have utilized the identified Ag-Patches to design Multi-Patch Vaccines (MPVs), proposing a novel method for the vaccine design. The designed MPVs were analyzed for immunologically crucial parameters, physiochemical properties and cDNA constructs. We identified 73 CTL (Cytotoxic T-Lymphocyte) and 49 HTL (Helper T-Lymphocyte) novel Ag-Patches from the proteome of SARS-CoV-2. The identified Ag-Patches utilized to design MPVs cover 768 overlapping epitopes targeting 55 different HLA alleles leading to 99.98% of world human population coverage. The MPVs and Toll-Like Receptor ectodomain complex shows stable complex formation tendency. Further, the cDNA analysis favors high expression of the MPVs constructs in a human cell line. We identified highly immunogenic novel Ag-Patches from the entire proteome of SARS CoV-2 by a novel reverse epitomics approach and utilized them to design MPVs. We conclude that the novel MPVs could be a highly potential novel approach to combat SARS-CoV-2, with greater effectiveness, high specificity and large human population coverage worldwide. Communicated by Ramaswamy H. Sarma.

Identification of a Potential mRNA-based Vaccine Candidate against the SARS-CoV-2 Spike Glycoprotein: A Reverse Vaccinology Approach

The emergence of the novel coronavirus (SARS-CoV-2) in December 2019 has generated a devastating global consequence which makes the development of a rapidly deployable, effective and safe vaccine candidate an imminent global health priority. The design of most vaccine candidates has been directed at the induction of antibody responses against the trimeric spike glycoprotein of SARS-CoV-2, a class I fusion protein that aids ACE2 (angiotensin-converting enzyme 2) receptor binding. A variety of formulations and vaccinology approaches are being pursued for targeting the spike glycoprotein, including simian and human replication-defective adenoviral vaccines, subunit protein vaccines, nucleic acid vaccines and whole-inactivated SARS-CoV-2. Here, we directed a reverse vaccinology approach towards the design of a nucleic acid (mRNA-based) vaccine candidate. The "YLQPRTFLL" peptide sequence (position 269-277) which was predicted to be a B cell epitope and likewise a strong binder of the HLA*A-0201 was selected for the design of the vaccine candidate, having satisfied series of antigenicity assessments. Through the codon optimization protocol, the nucleotide sequence for the vaccine candidate design was generated and targeted at the human toll-like receptor 7 (TLR7). Bioinformatics analyses showed that the sequence "UACCUGCAGCCGCGUACCUUCCUGCUG" exhibited a strong affinity and likewise was bound to a stable cavity in the TLR7 pocket. This study is therefore expected to contribute to the research efforts directed at securing definitive preventive measures against the SARS-CoV-2 infection.

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.

Screening of potential antigens from whole proteome and development of multi-epitope vaccine against Rhizopus delemar using immunoinformatics approaches

Mucormycosis is a deadly fungal disease mainly caused by Rhizopus oryzae (strain 99-880), also known as Rhizopus delemar. Previously, mucormycosis occurs in immunocompromised patients of diabetes mellitus, cancer, organ transplant, etc. But there was a drastic increase in mucormycosis cases in the ongoing COVID-19 pandemic. Despite several available therapies and antifungal treatments, the mortality rate of mucormycosis is about more than 50%. Currently, there is no vaccine available in the market for mucormycosis that urgently needs to develop a potential vaccine against mucormycosis with high efficacy. In the present study, we have screened 4 genome-derived predicted antigens (GDPA) through sequential filtration of the whole proteome of R. delemar using different benchmarked bioinformatics tools. These 4 GDPA along with 4 randomly selected experimentally reported antigens (ERA) were sourced for prediction of B- and T- cell epitopes and utilized in designing of two potential multi-epitope vaccine candidates which can induce both innate and adaptive immunity against R. delemar. Besides these, comparative immune simulation studies and in silico cloning were performed using L. lactis as an expression system for their possible uses as oral vaccines. This is the first multi-epitope vaccine designed against R. delemar through systematic pipelined reverse vaccinology and immunoinformatic approaches. Although the wet-lab based experimental validation of designed vaccines is required before testing in the preclinical model, the current study will significantly help in reducing the cost of experimentation as well as improving the efficacy of vaccine therapy against mucormycosis and other pathogenic diseases.Communicated by Ramaswamy H. Sarma.

A vaccine built from potential immunogenic pieces derived from the SARS-CoV-2 spike glycoprotein: A computational approximation

Coronavirus Disease 2019 (COVID-19) represents a new global threat demanding a multidisciplinary effort to fight its etiological agent—severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this regard, immunoinformatics may aid to predict prominent immunogenic regions from critical SARS-CoV-2 structural proteins, such as the spike (S) glycoprotein, for their use in prophylactic or therapeutic interventions against this highly pathogenic betacoronavirus. Accordingly, in this study, an integrated immunoinformatics approach was applied to identify cytotoxic T cell (CTC), T helper cell (THC), and Linear B cell (BC) epitopes from the S glycoprotein in an attempt to design a high-quality multi-epitope vaccine. The best CTC, THC, and BC epitopes showed high viral antigenicity and lack of allergenic or toxic residues, as well as CTC and THC epitopes showed suitable interactions with HLA class I (HLA-I) and HLA class II (HLA-II) molecules, respectively. Remarkably, SARS-CoV-2 receptor-binding domain (RBD) and its receptor-binding motif (RBM) harbour several potential epitopes. The structure prediction, refinement, and validation data indicate that the multi-epitope vaccine has an appropriate conformation and stability. Four conformational epitopes and an efficient binding between Toll-like receptor 4 (TLR4) and the vaccine model were observed. Importantly, the population coverage analysis showed that the multi-epitope vaccine could be used globally. Notably, computer-based simulations suggest that the vaccine model has a robust potential to evoke and maximize both immune effector responses and immunological memory to SARS-CoV-2. Further research is needed to accomplish with the mandatory international guidelines for human vaccine formulations.

Searching Epitope-Based Vaccines Using Bioinformatics Studies

Epitope-based vaccines is one of the most recent methodologies applied in bioinformatics studies. This strategy consists of identifying regions of the protein (peptides or epitopes) which show antigen properties capable of stimulating the immune system against proteins from virus, bacteria, fungi, etc. This chapter describes a general procedure to identify epitopes to be used as epitope vaccine using bioinformatics methods including primary protein sequence analyses, epitope predictor, docking, and molecular dynamics simulations for the selection of T- and B-cell epitopes.

Design of Personalized Neoantigen RNA Vaccines Against Cancer Based on Next-Generation Sequencing Data

The good clinical results of immune checkpoint inhibitors (ICIs) in recent cancer therapy and the success of RNA vaccines against SARS-nCoV2 have provided important lessons to the scientific community. On the one hand, the efficacy of ICI depends on the number and immunogenicity of tumor neoantigens (TNAs) which unfortunately are not abundantly expressed in many cancer subtypes. On the other hand, novel RNA vaccines have significantly improved both the stability and immunogenicity of mRNA and its efficient delivery, this way overcoming past technique limitations and also allowing a quick vaccine development at the same time. These two facts together have triggered a resurgence of therapeutic cancer vaccines which can be designed to include individual TNAs and be synthesized in a timeframe short enough to be suitable for the tailored treatment of a given cancer patient.In this chapter, we explain the pipeline for the synthesis of TNA-carrying RNA vaccines which encompasses several steps such as individual tumor next-generation sequencing (NGS), selection of immunogenic TNAs, nucleic acid synthesis, drug delivery systems, and immunogenicity assessment, all of each step comprising different alternatives and variations which will be discussed.

Vaccines Targeting Numerous Coronavirus Antigens, Ensuring Broader Global Population Coverage: Multi-epitope and Multi-patch Vaccines

Coronaviruses are causative agents of different zoonosis including SARS, MERS, or COVID-19 in humans. The high transmission rate of coronaviruses, the time-consuming development of efficient anti-infectives and vaccines, the possible evolutionary adaptation of the virus to conventional vaccines, and the challenge to cover broad human population worldwide are the major reasons that made it challenging to avoid coronaviruses outbreaks. Although, a plethora of different approaches are being followed to design and develop vaccines against coronaviruses, most of them target subunits, full-length single, or only a very limited number of proteins. Vaccine targeting multiple proteins or even the entire proteome of the coronavirus is yet to come. In the present chapter, we will be discussing multi-epitope vaccine (MEV) and multi-patch vaccine (MPV) approaches to design and develop efficient and sustainably successful strategies against coronaviruses. MEV and MPV utilize highly conserved, potentially immunogenic epitopes and antigenic patches, respectively, and hence they have the potential to target large number of coronavirus proteins or even its entire proteome, allowing us to combat the challenge of its evolutionary adaptation. In addition, the large number of human leukocyte antigen (HLA) alleles targeted by the chosen specific epitopes enables MEV and MPV to cover broader global population.

Designing of a Chimeric Vaccine Using EIS (Rv2416c) Protein Against Mycobacterium tuberculosis H37Rv: an Immunoinformatics Approach

Mycobacterium tuberculosis (Mtb) is a respiratory pathogen that causes tuberculosis (TB). There are a large number of proteins that are involved in the pathogenesis of TB. Stimulating the immune response against TB is very important to clear the pathogens from host. In the present study, an immunoinformatics conduit is used for designing an epitope based chimeric vaccine against TB. Enhanced intracellular survival (EIS) protein from Mtb is used for designing the chimeric vaccine. One B cell epitope, 8 cytotoxic T lymphocyte (CTL), and 6 helper T lymphocyte (HTL) epitopes were predicted based on the MHC allele binding, immunogenicity, antigenicity, allergenicity, toxicity and IFN epitopes. The selected epitopes were used for chimeric vaccine designing. Furthermore, 3D structure elucidation, structural refinement and validation of the designed chimeric vaccine were carried out. The 3D structure was used for protein-protein docking studies with Toll-like receptor 4 (TLR-4), followed by molecular dynamic simulation (MDS) and the interaction between the chimeric vaccine and TLR-4 complex was verified.

Immunoinformatics mapping of potential epitopes in SARS-CoV-2 structural proteins

All approved coronavirus disease 2019 (COVID-19) vaccines in current use are safe, effective, and reduce the risk of severe illness. Although data on the immunological presentation of patients with COVID-19 is limited, increasing experimental evidence supports the significant contribution of B and T cells towards the resolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Despite the availability of several COVID-19 vaccines with high efficacy, more effective vaccines are still needed to protect against the new variants of SARS-CoV-2. Employing a comprehensive immunoinformatic prediction algorithm and leveraging the genetic closeness with SARS-CoV, we have predicted potential immune epitopes in the structural proteins of SARS-CoV-2. The S and N proteins of SARS-CoV-2 and SARS-CoVs are main targets of antibody detection and have motivated us to design four multi-epitope vaccines which were based on our predicted B- and T-cell epitopes of SARS-CoV-2 structural proteins. The cardinal epitopes selected for the vaccine constructs are predicted to possess antigenic, non-allergenic, and cytokine-inducing properties. Additionally, some of the predicted epitopes have been experimentally validated in published papers. Furthermore, we used the C-ImmSim server to predict effective immune responses induced by the epitope-based vaccines. Taken together, the immune epitopes predicted in this study provide a platform for future experimental validations which may facilitate the development of effective vaccine candidates and epitope-based serological diagnostic assays.

Development of synthetic antigen vaccines for COVID-19

The current pandemic called COVID-19 caused by the SARS-CoV-2 virus brought the need for the search for fast alternatives to both control and fight the SARS-CoV-2 infection. Therefore, a race for a vaccine against COVID-19 took place, and some vaccines have been approved for emergency use in several countries in a record time. Ongoing prophylactic research has sought faster, safer, and precise alternatives by redirecting knowledge of other vaccines, and/or the development of new strategies using available tools, mainly in the areas of genomics and bioinformatics. The current review highlights the development of synthetic antigen vaccines, focusing on the usage of bioinformatics tools for the selection and construction of antigens on the different vaccine constructions under development, as well as strategies to optimize vaccines for COVID-19.

CAMAP: Artificial neural networks unveil the role of codon arrangement in modulating MHC-I peptides presentation

MHC-I associated peptides (MAPs) play a central role in the elimination of virus-infected and neoplastic cells by CD8 T cells. However, accurately predicting the MAP repertoire remains difficult, because only a fraction of the transcriptome generates MAPs. In this study, we investigated whether codon arrangement (usage and placement) regulates MAP biogenesis. We developed an artificial neural network called Codon Arrangement MAP Predictor (CAMAP), predicting MAP presentation solely from mRNA sequences flanking the MAP-coding codons (MCCs), while excluding the MCC per se. CAMAP predictions were significantly more accurate when using original codon sequences than shuffled codon sequences which reflect amino acid usage. Furthermore, predictions were independent of mRNA expression and MAP binding affinity to MHC-I molecules and applied to several cell types and species. Combining MAP ligand scores, transcript expression level and CAMAP scores was particularly useful to increase MAP prediction accuracy. Using an in vitro assay, we showed that varying the synonymous codons in the regions flanking the MCCs (without changing the amino acid sequence) resulted in significant modulation of MAP presentation at the cell surface. Taken together, our results demonstrate the role of codon arrangement in the regulation of MAP presentation and support integration of both translational and post-translational events in predictive algorithms to ameliorate modeling of the immunopeptidome.

MHC-I associated peptides (MAPs) are small fragments of intracellular proteins presented at the surface of cells and used by the immune system to detect and eliminate cancerous or virus-infected cells. While it is theoretically possible to predict which portions of the intracellular proteins will be naturally processed by the cells to ultimately reach the surface, current methodologies have prohibitively high false discovery rates. Here we introduce an artificial neural network called Codon Arrangement MAP Predictor (CAMAP) which integrates information from mRNA-to-protein translation to other factors regulating MAP biogenesis (e.g. MAP ligand score and transcript expression levels) to improve MAP prediction accuracy. While most MAP predictive approaches focus on MAP sequences per se, CAMAP’s novelty is to analyze the MAP-flanking mRNA sequences, thereby providing completely independent information for MAP prediction. We show on several datasets that the integration of CAMAP scores with other known factors involved in MAP presentation (i.e. MAP ligand score and mRNA expression) significantly improves MAP prediction accuracy, and further validate CAMAP learned features using an in-vitro assay. These findings may have major implications for the design of vaccines against cancers and viruses, and in times of pandemics could accelerate the identification of relevant MAPs of viral origins.

Immunogenic T cell epitopes of SARS-CoV-2 are recognized by circulating memory and naïve CD8 T cells of unexposed individuals

Background

Recent studies have provided evidence of T cell reactivity to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in significant numbers of non-infected individuals, which has been attributed to cross-reactive CD4 memory T cells from previous exposure to seasonal coronaviruses. Less evidence of cross-reactive memory CD8 T cells has been documented to date.

Methods

We used the NetCTLPan neural network of the Epitope Database and Analysis Resource to select a series of 27 HLA-A*02:01 epitopes derived from the proteome of SARS-CoV-2. Their binding capacity was assessed by a HLA-A*02:01 stabilization assay and by quantifying their binding to HLA-A*02:01 monomers for the generation of tetramers. Their ability to stimulate and induce expansion of SARS-CoV-2 reactive CD8 T cells was measured by flow cytometry. The TCR repertoire of COVID convalescent and healthy unexposed donors was analysed using the MIRA database.

Findings

The HLA-A*02:01 epitopes tested were able to stabilise HLA molecules and induce activation of CD8 T cells of healthy unexposed donors. Our results, based on specific tetramer binding, provide evidence supporting the presence of frequent cross-reactive CD8 T cells to SARS-CoV-2 antigens in non-exposed individuals. Interestingly, the reactive cells were distributed into naïve, memory and effector subsets.

Interpretation

Our data are consistent with a significant proportion of the reactive CD8 T clones belonging to the public shared repertoire, readily available in absence of previous contact with closely related coronaviruses. Furthermore, we demonstrate the immunogenic capacity of long peptides carrying T cell epitopes, which can serve to isolate virus-specific T cell receptors among the ample repertoire of healthy unexposed subjects and could have application in COVID-19 immunotherapy. Limitations of our study are that it concentrated on one MHC I allele (HLA-A*02:01) and the low numbers of samples and epitopes tested.

Antigen processing and presentation in cancer immunotherapy

Background

Knowledge about and identification of T cell tumor antigens may inform the development of T cell receptor-engineered adoptive cell transfer or personalized cancer vaccine immunotherapy. Here, we review antigen processing and presentation and discuss limitations in tumor antigen prediction approaches.

Methods

Original articles covering antigen processing and presentation, epitope discovery, and in silico T cell epitope prediction were reviewed.

Results

Natural processing and presentation of antigens is a complex process that involves proteasomal proteolysis of parental proteins, transportation of digested peptides into the endoplasmic reticulum, loading of peptides onto major histocompatibility complex (MHC) class I molecules, and shuttling of peptide:MHC complexes to the cell surface. A number of T cell tumor antigens have been experimentally validated in patients with cancer. Assessment of predicted MHC class I binding and total score for these validated T cell antigens demonstrated a wide range of values, with nearly one-third of validated antigens carrying an IC₅₀ of greater than 500 nM.

Conclusions

Antigen processing and presentation is a complex, multistep process. In silico epitope prediction techniques can be a useful tool, but comprehensive experimental testing and validation on a patient-by-patient basis may be required to reliably identify T cell tumor antigens.

Glycopeptidomics Analysis of a Cell Line Model Revealing Pathogenesis and Potential Marker Molecules for the Early Diagnosis of Gastric MALT Lymphoma

Background & Aims

Gastric mucosa-associated lymphoma (GML) is a mature B cell tumor related to Helicobacter pylori (H.pylori) infection. The clinical manifestations of GML are not specific, so GML is often misdiagnosed, leading to excessive treatment. The pathogenesis of H.pylori-induced GML is not well understood and there are no molecular markers for early GML diagnosis.

Methods

Glycopeptidomics analyses of host cell lines (a BCG823 cell line, C823) and C823 cells infected by H. pylori isolated from patients with GML (GMALT823), gastritis (GAT823), gastric ulcer (GAU823) and gastric cancer (GAC823) were carried out to clarify the host reaction mechanism against GML and to identify potential molecular criteria for the early diagnosis of GML.

Results

Thirty-three samples were analyzed and approximately 2000 proteins, 200 glycoproteins and 500 glycopeptides were detected in each sample. O-glycans were the dominant glycoforms in GMALT823 cells only. Four specific glycoforms in GMALT823 cells and 2 specific glycoforms in C823 and GMALT823 cells were identified. Eight specific glycopeptides from 7 glycoproteins were found in GMALT823 cells; of these glycopeptides, 6 and 3 specific glycopeptides had high affinity for T cell epitopes and have conformational B cell epitopes, respectively.

Conclusion

The predominant glycoforms of host cells infected by MALT H. pylori isolates differ from others, and the glycoproteins, glycosylation sites and glycoforms might be closely related to the formation of GML, which provides new insights into the pathogenic mechanisms of H. pylori infection and suggests molecular indicators for the early diagnosis of GML.

In-silico design of envelope based multi-epitope vaccine candidate against Kyasanur forest disease virus

Kyasanur forest disease virus (KFDV) causing tick-borne hemorrhagic fever which was earlier endemic to western Ghats, southern India, it is now encroaching into new geographic regions, but there is no approved medicine or effective vaccine against this deadly disease. In this study, we did in-silico design of multi-epitope subunit vaccine for KFDV. B-cell and T-cell epitopes were predicted from conserved regions of KFDV envelope protein and two vaccine candidates (VC1 and VC2) were constructed, those were found to be non-allergic and possess good antigenic properties, also gives cross-protection against Alkhurma hemorrhagic fever virus. The 3D structures of vaccine candidates were built and validated. Docking analysis of vaccine candidates with toll-like receptor-2 (TLR-2) by Cluspro and PatchDock revealed strong affinity between VC1 and TLR2. Ligplot tool was identified the intermolecular hydrogen bonds between vaccine candidates and TLR-2, iMOD server confirmed the stability of the docking complexes. JCAT sever ensured cloning efficiency of both vaccine constructs and in-silico cloning into pET30a (+) vector by SnapGene showed successful translation of epitope region. IMMSIM server was identified increased immunological responses. Finally, multi-epitope vaccine candidates were designed and validated their efficiency, it may pave the way for up-coming vaccine and diagnostic kit development.

Genomic profiling of solid tumors harboring BRD4-NUT and response to immune checkpoint inhibitors

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NUT carcinoma is a rare but aggressive solid tumor that can be diagnosed by presence of the BRD4-NUT fusion.

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This series presents 31 cases of solid tumors that harbor BRD4-NUT but often carry other diagnoses such NSCLC—NOS and NSCLC-SCC.

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Despite lack of PD-L1 expression and a low tumor mutational burden, two index cases responded to either nivolumab or atezolizumab+chemotherapy with partial response or better with 4–5 month duration of response.

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The unexpected response to checkpoint inhibitors could be explained by a very high affinity of the fusion peptide at the junction of BRD4 and NUT to the MHC complex as recently suggested for an exceptional response to an immune checkpoint inhibitor in a fusion bearing low TMB, low PD-L1 expression head and neck carcinoma.

Background

The translocation t(15:19) produces the oncogenic BRD4-NUT fusion which is pathognomonic for NUT carcinoma (NC), which is a rare, but extremely aggressive solid tumor. Comprehensive genomic profiling (CGP) by hybrid-capture based next generation sequencing of 186+ genes of a cohort of advanced cancer cases with a variety of initial diagnoses harboring BRD4-NUT may shed further insight into the biology of these tumors and possible options for targeted treatment.

Case presentation

Thirty-one solid tumor cases harboring a BRD4-NUT translocation are described, with only 16% initially diagnosed as NC and the remainder carrying other diagnoses, most commonly NSCLC—NOS (22%) and lung squamous cell carcinoma (NSCLC-SCC) (16%). The cohort was all microsatellite stable and harbored a low Tumor Mutational Burden (TMB, mean 1.7 mut/mb, range 0–4). In two index cases, patients treated with immune checkpoint inhibitors (ICPI) had unexpected partial or better responses of varying duration. Notably, four cases – including the two index cases - were negative for PD-L1 expression. Neo-antigen prediction for BRD4-NUT and then affinity modeling of the peptide-MHC (pMHC) complex for an assessable index case predicted very high affinity binding, both on a ranked (99.9%) and absolute (33 nM) basis.

Conclusions

CGP identifies BRD4-NUT fusions in advanced solid tumors which carry a broad range of initial diagnoses and which should be re-diagnosed as NC per guidelines. A hypothesized mechanism underlying responses to ICPI in the low TMB, PD-L1 negative index cases is the predicted high affinity of the BRD4-NUT fusion peptide to MHC complexes. Further study of pMHC affinity and response to immune checkpoint inhibitors in patients with NC harboring BRD4-NUT is needed to validate this therapeutic hypothesis.