SYFPEITHI: database for MHC ligands and peptide motifs

CrossDome: an interactive R package to predict cross-reactivity risk using immunopeptidomics databases

T-cell-based immunotherapies hold tremendous potential in the fight against cancer, thanks to their capacity to specifically targeting diseased cells. Nevertheless, this potential has been tempered with safety concerns regarding the possible recognition of unknown off-targets displayed by healthy cells. In a notorious example, engineered T-cells specific to MAGEA3 (EVDPIGHLY) also recognized a TITIN-derived peptide (ESDPIVAQY) expressed by cardiac cells, inducing lethal damage in melanoma patients. Such off-target toxicity has been related to T-cell cross-reactivity induced by molecular mimicry. In this context, there is growing interest in developing the means to avoid off-target toxicity, and to provide safer immunotherapy products. To this end, we present CrossDome, a multi-omics suite to predict the off-target toxicity risk of T-cell-based immunotherapies. Our suite provides two alternative protocols, i) a peptide-centered prediction, or ii) a TCR-centered prediction. As proof-of-principle, we evaluate our approach using 16 well-known cross-reactivity cases involving cancer-associated antigens. With CrossDome, the TITIN-derived peptide was predicted at the 99+ percentile rank among 36,000 scored candidates (p-value < 0.001). In addition, off-targets for all the 16 known cases were predicted within the top ranges of relatedness score on a Monte Carlo simulation with over 5 million putative peptide pairs, allowing us to determine a cut-off p-value for off-target toxicity risk. We also implemented a penalty system based on TCR hotspots, named contact map (CM). This TCR-centered approach improved upon the peptide-centered prediction on the MAGEA3-TITIN screening (e.g., from 27th to 6th, out of 36,000 ranked peptides). Next, we used an extended dataset of experimentally-determined cross-reactive peptides to evaluate alternative CrossDome protocols. The level of enrichment of validated cases among top 50 best-scored peptides was 63% for the peptide-centered protocol, and up to 82% for the TCR-centered protocol. Finally, we performed functional characterization of top ranking candidates, by integrating expression data, HLA binding, and immunogenicity predictions. CrossDome was designed as an R package for easy integration with antigen discovery pipelines, and an interactive web interface for users without coding experience. CrossDome is under active development, and it is available at https://github.com/AntunesLab/crossdome.

ASP-2/Trans-sialidase chimeric protein induces robust protective immunity in experimental models of Chagas' disease

Immunization with the Amastigote Surface Protein-2 (ASP-2) and Trans-sialidase (TS) antigens either in the form of recombinant protein, encoded in plasmids or human adenovirus 5 (hAd5) confers robust protection against various lineages of Trypanosoma cruzi. Herein we generated a chimeric protein containing the most immunogenic regions for T and B cells from TS and ASP-2 (TRASP) and evaluated its immunogenicity in comparison with our standard protocol of heterologous prime-boost using plasmids and hAd5. Mice immunized with TRASP protein associated to Poly-ICLC (Hiltonol) were highly resistant to challenge with T. cruzi, showing a large decrease in tissue parasitism, parasitemia and no lethality. This protection lasted for at least 3 months after the last boost of immunization, being equivalent to the protection induced by DNA/hAd5 protocol. TRASP induced high levels of T. cruzi-specific antibodies and IFNγ-producing T cells and protection was primarily mediated by CD8⁺ T cells and IFN-γ. We also evaluated the toxicity, immunogenicity, and efficacy of TRASP and DNA/hAd5 formulations in dogs. Mild collateral effects were detected at the site of vaccine inoculation. While the chimeric protein associated with Poly-ICLC induced high levels of antibodies and CD4⁺ T cell responses, the DNA/hAd5 induced no antibodies, but a strong CD8⁺ T cell response. Immunization with either vaccine protected dogs against challenge with T. cruzi. Despite the similar efficacy, we conclude that moving ahead with TRASP together with Hiltonol is advantageous over the DNA/hAd5 vaccine due to pre-existing immunity to the adenovirus vector, as well as the cost-benefit for development and large-scale production.

The biogenesis of the immunopeptidome

The immunopeptidome is the repertoire of peptides bound and presented by the MHC class I, class II, and non-classical molecules. The peptides are produced by the degradation of most cellular proteins, and in some cases, peptides are produced from extracellular proteins taken up by the cells. This review attempts to first describe some of its known and well-accepted concepts, and next, raise some questions about a few of the established dogmas in this field: The production of novel peptides by splicing is questioned, suggesting here that spliced peptides are extremely rare, if existent at all. The degree of the contribution to the immunopeptidome by degradation of cellular protein by the proteasome is doubted, therefore this review attempts to explain why it is likely that this contribution to the immunopeptidome is possibly overstated. The contribution of defective ribosome products (DRiPs) and non-canonical peptides to the immunopeptidome is noted and methods are suggested to quantify them. In addition, the common misconception that the MHC class II peptidome is mostly derived from extracellular proteins is noted, and corrected. It is stressed that the confirmation of sequence assignments of non-canonical and spliced peptides should rely on targeted mass spectrometry using spiking-in of heavy isotope-labeled peptides. Finally, the new methodologies and modern instrumentation currently available for high throughput kinetics and quantitative immunopeptidomics are described. These advanced methods open up new possibilities for utilizing the big data generated and taking a fresh look at the established dogmas and reevaluating them critically.

Microbial peptides activate tumour-infiltrating lymphocytes in glioblastoma

Microbial organisms have key roles in numerous physiological processes in the human body and have recently been shown to modify the response to immune checkpoint inhibitors1,2. Here we aim to address the role of microbial organisms and their potential role in immune reactivity against glioblastoma. We demonstrate that HLA molecules of both glioblastoma tissues and tumour cell lines present bacteria-specific peptides. This finding prompted us to examine whether tumour-infiltrating lymphocytes (TILs) recognize tumour-derived bacterial peptides. Bacterial peptides eluted from HLA class II molecules are recognized by TILs, albeit very weakly. Using an unbiased antigen discovery approach to probe the specificity of a TIL CD4+ T cell clone, we show that it recognizes a broad spectrum of peptides from pathogenic bacteria, commensal gut microbiota and also glioblastoma-related tumour antigens. These peptides were also strongly stimulatory for bulk TILs and peripheral blood memory cells, which then respond to tumour-derived target peptides. Our data hint at how bacterial pathogens and bacterial gut microbiota can be involved in specific immune recognition of tumour antigens. The unbiased identification of microbial target antigens for TILs holds promise for future personalized tumour vaccination approaches.

Molecular mimicry and cancer vaccine development

BACKGROUND

The development of cancer immunotherapeutic strategies relies on the identification and validation of optimal target tumor antigens, which should be tumor-specific as well as able to elicit a swift and potent anti-tumor immune response. The vast majority of such strategies are based on tumor associated antigens (TAAs) which are shared wild type cellular self-epitopes highly expressed on tumor cells. Indeed, TAAs can be used to develop off-the-shelf cancer vaccines appropriate to all patients affected by the same malignancy. However, given that they may be also presented by HLAs on the surface of non-malignant cells, they may be possibly affected by immunological tolerance or elicit autoimmune responses.

MAIN BODY

In order to overcome such limitations, analogue peptides with improved antigenicity and immunogenicity able to elicit a cross-reactive T cell response are needed. To this aim, non-self-antigens derived from microorganisms (MoAs) may be of great benefit.

Spheromers reveal robust T cell responses to the Pfizer/BioNTech vaccine and attenuated peripheral CD8+ T cell responses post SARS-CoV-2 infection

T cells are a critical component of the response to SARS-CoV-2, but their kinetics after infection and vaccination are insufficiently understood. Using "spheromer" peptide-MHC multimer reagents, we analyzed healthy subjects receiving two doses of the Pfizer/BioNTech BNT162b2 vaccine. Vaccination resulted in robust spike-specific T cell responses for the dominant CD4+ (HLA-DRB1∗15:01/S191) and CD8+ (HLA-A∗02/S691) T cell epitopes. Antigen-specific CD4+ and CD8+ T cell responses were asynchronous, with the peak CD4+ T cell responses occurring 1 week post the second vaccination (boost), whereas CD8+ T cells peaked 2 weeks later. These peripheral T cell responses were elevated compared with COVID-19 patients. We also found that previous SARS-CoV-2 infection resulted in decreased CD8+ T cell activation and expansion, suggesting that previous infection can influence the T cell response to vaccination.

Precision Neoantigen Discovery Using Large-Scale Immunopeptidomes and Composite Modeling of MHC Peptide Presentation

Major histocompatibility complex (MHC)-bound peptides that originate from tumor-specific genetic alterations, known as neoantigens, are an important class of anticancer therapeutic targets. Accurately predicting peptide presentation by MHC complexes is a key aspect of discovering therapeutically relevant neoantigens. Technological improvements in mass spectrometry-based immunopeptidomics and advanced modeling techniques have vastly improved MHC presentation prediction over the past 2 decades. However, improvement in the accuracy of prediction algorithms is needed for clinical applications like the development of personalized cancer vaccines, the discovery of biomarkers for response to immunotherapies, and the quantification of autoimmune risk in gene therapies. Toward this end, we generated allele-specific immunopeptidomics data using 25 monoallelic cell lines and created Systematic Human Leukocyte Antigen (HLA) Epitope Ranking Pan Algorithm (SHERPA), a pan-allelic MHC-peptide algorithm for predicting MHC-peptide binding and presentation. In contrast to previously published large-scale monoallelic data, we used an HLA-null K562 parental cell line and a stable transfection of HLA allele to better emulate native presentation. Our dataset includes five previously unprofiled alleles that expand MHC diversity in the training data and extend allelic coverage in underprofiled populations. To improve generalizability, SHERPA systematically integrates 128 monoallelic and 384 multiallelic samples with publicly available immunoproteomics data and binding assay data. Using this dataset, we developed two features that empirically estimate the propensities of genes and specific regions within gene bodies to engender immunopeptides to represent antigen processing. Using a composite model constructed with gradient boosting decision trees, multiallelic deconvolution, and 2.15 million peptides encompassing 167 alleles, we achieved a 1.44-fold improvement of positive predictive value compared with existing tools when evaluated on independent monoallelic datasets and a 1.17-fold improvement when evaluating on tumor samples. With a high degree of accuracy, SHERPA has the potential to enable precision neoantigen discovery for future clinical applications.

Cysteine carboxyethylation generates neoantigens to induce HLA-restricted autoimmunity

Autoimmune diseases such as ankylosing spondylitis (AS) can be driven by emerging neoantigens that disrupt immune tolerance. Here, we developed a workflow to profile posttranslational modifications involved in neoantigen formation. Using mass spectrometry, we identified a panel of cysteine residues differentially modified by carboxyethylation that required 3-hydroxypropionic acid to generate neoantigens in patients with AS. The lysosomal degradation of integrin αIIb [ITGA2B (CD41)] carboxyethylated at Cys96 (ITGA2B-ceC96) generated carboxyethylated peptides that were presented by HLA-DRB1*04 to stimulate CD4⁺ T cell responses and induce autoantibody production. Immunization of HLA-DR4 transgenic mice with the ITGA2B-ceC96 peptide promoted colitis and vertebral bone erosion. Thus, metabolite-induced cysteine carboxyethylation can give rise to pathogenic neoantigens that lead to autoreactive CD4⁺ T cell responses and autoantibody production in autoimmune diseases.

In silico designing of a novel polyvalent multi-subunit peptide vaccine leveraging cross-immunity against human visceral and cutaneous leishmaniasis: an immunoinformatics-based approach

CONTEXT

Leishmaniasis is a group of vector-borne infectious diseases caused by over 20 pathogenic Leishmania species that are endemic in many tropical and subtropical countries. The emergence of drug-resistant strains, the adverse side effects of anti-Leishmania drugs, and the absence of a preventative vaccination strategy threaten the sensitive population. Recently, many groups of researchers have exploited the field of reverse vaccinology to develop vaccines, focusing chiefly on inducing immunity against either visceral or cutaneous leishmaniasis.

METHODS

This present work involves retrieving twelve experimentally validated leishmanial antigenic protein sequences from the UniProt database, followed by their antigenicity profiling employing ANTIGENpro and Vaxijen 2.0 servers. MHC-binding epitopes for the same were predicted using both NetCTL 1.2 and SYFPEITHI servers, while epitopes for B cell were computed using ABCpred and BepiPred 2.0 servers. The screened epitopes with significantly higher scores were utilized for designing the vaccine construct with appropriate linkers and natural adjuvant. The secondary and tertiary structures of the synthetic peptide were determined by conditional random fields, shallow neural networks, and profile-profile threading alignment with iterative structure assembly simulations, respectively. The 3-D vaccine model was validated through CASP10-tested refinement and the MolProbity web server. Molecular docking and multi-scale normal mode analysis simulation were performed to analyze the best vaccine-TLR complex. Finally, computational immune simulation findings revealed promising cellular and humoral immune responses, suggesting that the engineered chimeric peptide is a potential broad-spectrum vaccine against visceral and cutaneous leishmaniasis.

A Synthetic SARS-CoV-2-Derived T-Cell and B-Cell Peptide Cocktail Elicits Full Protection against Lethal Omicron BA.1 Infection in H11-K18-hACE2 Mice

Emerging variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been developing the capacity for immune evasion and resistance to existing vaccines and drugs. To address this, development of vaccines against coronavirus disease 2019 (COVID-19) has focused on universality, strong T cell immunity, and rapid production. Synthetic peptide vaccines, which are inexpensive and quick to produce, show low toxicity, and can be selected from the conserved SARS-CoV-2 proteome, are promising candidates. In this study, we evaluated the effectiveness of a synthetic peptide cocktail containing three murine CD4+ T-cell epitopes from the SARS-CoV-2 nonspike proteome and one B-cell epitope from the Omicron BA.1 receptor-binding domain (RBD), along with aluminum phosphate (Al) adjuvant and 5' cytosine-phosphate-guanine 3' oligodeoxynucleotide (CpG-ODN) adjuvant in mice. The peptide cocktail induced good Th1-biased T-cell responses and effective neutralizing-antibody titers against the Omicron BA.1 variant. Additionally, H11-K18-hACE2 transgenic mice were fully protected against lethal challenge with the BA.1 strain, with a 100% survival rate and reduced pulmonary viral load and pathological lesions. Subcutaneous administration was found to be the superior route for synthetic peptide vaccine delivery. Our findings demonstrate the effectiveness of the peptide cocktail in mice, suggesting the feasibility of synthetic peptide vaccines for humans. IMPORTANCE Current vaccines based on production of neutralizing antibodies fail to prevent the infection and transmission of SARS-CoV-2 Omicron and its subvariants. Understanding the critical factors and avoiding the disadvantages of vaccine strategies are essential for developing a safe and effective COVID-19 vaccine, which would include a more effective and durable cellular response, minimal effects of viral mutations, rapid production against emerging variants, and good safety. Peptide-based vaccines are an excellent alternative because they are inexpensive, quick to produce, and very safe. In addition, human leukocyte antigen T-cell epitopes could be targeted at robust T-cell immunity and selected in the conserved region of the SARS-CoV-2 variants. Our study showed that a synthetic SARS-CoV-2-derived peptide cocktail induced full protection against lethal infection with Omicron BA.1 in H11-K18-hACE2 mice for the first time. This could have implications for the development of effective COVID-19 peptide vaccines for humans.

Artificial intelligence in cancer immunotherapy: Applications in neoantigen recognition, antibody design and immunotherapy response prediction

Cancer immunotherapy is a method of controlling and eliminating tumors by reactivating the body's cancer-immunity cycle and restoring its antitumor immune response. The increased availability of data, combined with advancements in high-performance computing and innovative artificial intelligence (AI) technology, has resulted in a rise in the use of AI in oncology research. State-of-the-art AI models for functional classification and prediction in immunotherapy research are increasingly used to support laboratory-based experiments. This review offers a glimpse of the current AI applications in immunotherapy, including neoantigen recognition, antibody design, and prediction of immunotherapy response. Advancing in this direction will result in more robust predictive models for developing better targets, drugs, and treatments, and these advancements will eventually make their way into the clinical setting, pushing AI forward in the field of precision oncology.

Recent trends in next generation immunoinformatics harnessed for universal coronavirus vaccine design

The ongoing pandemic of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has globally devastated public health, the economies of many countries and quality of life universally. The recent emergence of immune-escaped variants and scenario of vaccinated individuals being infected has raised the global concerns about the effectiveness of the current available vaccines in transmission control and disease prevention. Given the high rate mutation of SARS-CoV-2, an efficacious vaccine targeting against multiple variants that contains virus-specific epitopes is desperately needed. An immunoinformatics approach is gaining traction in vaccine design and development due to the significant reduction in time and cost of immunogenicity studies and increasing reliability of the generated results. It can underpin the development of novel therapeutic methods and accelerate the design and production of peptide vaccines for infectious diseases. Structural proteins, particularly spike protein (S), along with other proteins have been studied intensively as promising coronavirus vaccine targets. Numbers of promising online immunological databases, tools and web servers have widely been employed for the design and development of next generation COVID-19 vaccines. This review highlights the role of immunoinformatics in identifying immunogenic peptides as potential vaccine targets, involving databases, and prediction and characterization of epitopes which can be harnessed for designing future coronavirus vaccines.

Viral T-cell epitopes - Identification, characterization and clinical application

T-cell immunity, mediated by CD4⁺ and CD8⁺ T cells, represents a cornerstone in the control of viral infections. Virus-derived T-cell epitopes are represented by human leukocyte antigen (HLA)-presented viral peptides on the surface of virus-infected cells. They are the prerequisite for the recognition of infected cells by T cells. Knowledge of viral T-cell epitopes provides on the one hand a diagnostic tool to decipher protective T-cell immune responses in the human population and on the other hand various prophylactic and therapeutic options including vaccination approaches and the transfer of virus-specific T cells. Such approaches have already been proven to be effective against various viral infections, particularly in immunocompromised patients lacking sufficient humoral, antibody-based immune response. This review provides an overview on the state of the art as well as current studies regarding the identification and characterization of viral T-cell epitopes and approaches of clinical application. In the first chapter in silico prediction tools and direct, mass spectrometry-based identification of viral T-cell epitopes is compared. The second chapter provides an overview of commonly used assays for further characterization of T-cell responses and phenotypes. The final chapter presents an overview of clinical application of viral T-cell epitopes with a focus on human immunodeficiency virus (HIV), human cytomegalovirus (HCMV) and severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), being representatives of relevant viruses.

The HLA ligandome of oropharyngeal squamous cell carcinomas reveals shared tumour-exclusive peptides for semi-personalised vaccination

BACKGROUND

The immune peptidome of OPSCC has not previously been studied. Cancer-antigen specific vaccination may improve clinical outcome and efficacy of immune checkpoint inhibitors such as PD1/PD-L1 antibodies.

METHODS

Mapping of the OPSCC HLA ligandome was performed by mass spectrometry (MS) based analysis of naturally presented HLA ligands isolated from tumour tissue samples (n = 40) using immunoaffinity purification. The cohort included 22 HPV-positive (primarily HPV-16) and 18 HPV-negative samples. A benign reference dataset comprised of the HLA ligandomes of benign haematological and tissue datasets was used to identify tumour-associated antigens.

RESULTS

MS analysis led to the identification of naturally HLA-presented peptides in OPSCC tumour tissue. In total, 22,769 peptides from 9485 source proteins were detected on HLA class I. For HLA class II, 15,203 peptides from 4634 source proteins were discovered. By comparative profiling against the benign HLA ligandomic datasets, 29 OPSCC-associated HLA class I ligands covering 11 different HLA allotypes and nine HLA class II ligands were selected to create a peptide warehouse.

CONCLUSION

Tumour-associated peptides are HLA-presented on the cell surfaces of OPSCCs. The established warehouse of OPSCC-associated peptides can be used for downstream immunogenicity testing and peptide-based immunotherapy in (semi)personalised strategies.

MHC2AffyPred: A machine-learning approach to estimate affinity of MHC class II peptides based on structural interaction fingerprints

Understanding how MHC class II (MHC-II) binding peptides with differing lengths exhibit specific interaction at the core and extended sites within the large MHC-II pocket is a very important aspect of immunological research for designing peptides. Certain efforts were made to generate peptide conformations amenable for MHC-II binding and calculate the binding energy of such complex formation but not directed toward developing a relationship between the peptide conformation in MHC-II structures and the binding affinity (BA) (IC₅₀ ). We present here a machine-learning approach to calculate the BA of the peptides within the MHC-II pocket for HLA-DRA1, HLA-DRB1, HLA-DP, and HLA-DQ allotypes. Instead of generating ensembles of peptide conformations conventionally, the biased mode of conformations was created by considering the peptides in the crystal structures of pMHC-II complexes as the templates, followed by site-directed peptide docking. The structural interaction fingerprints generated from such docked pMHC-II structures along with the Moran autocorrelation descriptors were trained using a random forest regressor specific to each MHC-II peptide lengths (9-19). The entire workflow is automated using Linux shell and Perl scripts to promote the utilization of MHC2AffyPred program to any characterized MHC-II allotypes and is made for free access at https://github.com/SiddhiJani/MHC2AffyPred. The MHC2AffyPred attained better performance (correlation coefficient [CC] of .612-.898) than MHCII3D (.03-.594) and NetMHCIIpan-3.2 (.289-.692) programs in the HLA-DRA1, HLA-DRB1 types. Similarly, the MHC2AffyPred program achieved CC between .91 and .98 for HLA-DP and HLA-DQ peptides (13-mer to 17-mer). Further, a case study on MHC-II binding 15-mer peptides of severe acute respiratory syndrome coronavirus-2 showed very close competency in computing the IC₅₀ values compared to the sequence-based NetMHCIIpan v3.2 and v4.0 programs with a correlation of .998 and .570, respectively.

Targeting Driver Oncogenes and Other Public Neoantigens Using T Cell Receptor-Based Cellular Therapy

T cell reactivity to tumor-specific neoantigens can drive endogenous and therapeutically induced antitumor immunity. However, most tumor-specific neoantigens are unique to each patient (private) and targeting them requires personalized therapy. A smaller subset of neoantigens includes epitopes that span recurrent mutation hotspots, translocations, or gene fusions in oncogenic drivers and tumor suppressors, as well as epitopes that arise from viral oncogenic proteins. Such antigens are likely to be shared across patients (public), uniformly expressed within a tumor, and required for cancer cell survival and fitness. Although a limited number of these public neoantigens are naturally immunogenic, recent studies affirm their clinical utility. In this review, we highlight efforts to target mutant KRAS, mutant p53, and epitopes derived from oncogenic viruses using T cells engineered with off-the-shelf T cell receptors. We also discuss the challenges and strategies to achieving more effective T cell therapies, particularly in the context of solid tumors.

Physical-Chemical Regulation of Membrane Receptors Dynamics in Viral Invasion and Immune Defense

Mechanical cues dynamically regulate membrane receptors functions to trigger various physiological and pathological processes from viral invasion to immune defense. These cues mainly include various types of dynamic mechanical forces and the spatial confinement of plasma membrane. However, the molecular mechanisms of how they couple with biochemical cues in regulating membrane receptors functions still remain mysterious. Here, we review recent advances in methodologies of single-molecule biomechanical techniques and in novel biomechanical regulatory mechanisms of critical ligand recognition of viral and immune receptors including SARS-CoV-2 spike protein, T cell receptor (TCR) and other co-stimulatory immune receptors. Furthermore, we provide our perspectives of the general principle of how force-dependent kinetics determine the dynamic functions of membrane receptors and of biomechanical-mechanism-driven SARS-CoV-2 neutralizing antibody design and TCR engineering for T-cell-based therapies.

Current Update on Rotavirus in-Silico Multiepitope Vaccine Design

Rotavirus gastroenteritis is one of the leading causes of pediatric morbidity and mortality worldwide in infants and under-five populations. The World Health Organization (WHO) recommended global incorporation of the rotavirus vaccine in national immunization programs to alleviate the burden of the disease. Implementation of the rotavirus vaccination in certain regions of the world brought about a significant and consistent reduction of rotavirus-associated hospitalizations. However, the efficacy of licensed vaccines remains suboptimal in low-income countries where the incidences of rotavirus gastroenteritis continue to happen unabated. The problem of low efficacy of currently licensed oral rotavirus vaccines in low-income countries necessitates continuous exploration, design, and development of new rotavirus vaccines. Traditional vaccine development is a complex, expensive, labor-intensive, and time-consuming process. Reverse vaccinology essentially utilizes the genome and proteome information on pathogens and has opened new avenues for in-silico multiepitope vaccine design for a plethora of pathogens, promising time reduction in the complete vaccine development pipeline by complementing the traditional vaccinology approach. A substantial number of reviews on licensed rotavirus vaccines and those under evaluation are already available in the literature. However, a collective account of rotavirus in-silico vaccines is lacking in the literature, and such an account may further fuel the interest of researchers to use reverse vaccinology to expedite the vaccine development process. Therefore, the main focus of this review is to summarize the research endeavors undertaken for the design and development of rotavirus vaccines by the reverse vaccinology approach utilizing the tools of immunoinformatics.

Challenges in neoantigen-directed therapeutics

A fundamental prerequisite for the efficacy of cancer immunotherapy is the presence of functional, antigen-specific T cells within the tumor. Neoantigen-directed therapy is a promising strategy that aims at targeting the host's immune response against tumor-specific antigens, thereby eradicating cancer cells. Initial forays have been made in clinical environments utilizing vaccines and adoptive cell therapy; however, many challenges lie ahead. We provide an in-depth overview of the current state of the field with an emphasis on in silico neoantigen discovery and the clinical aspects that need to be addressed to unlock the full potential of this therapy.

Trypanosoma cruzi-specific CD8+ T cells and other immunological hallmarks in chronic Chagas cardiomyopathy: Two decades of research

Trypanosoma cruzi, the causal agent of Chagas disease, has coexisted with humans for thousands of years. Therefore, the parasite has developed several mechanisms of antigenic variability that has allowed it to live inside the cells and evade the host immune response. Since T. cruzi displays an intracellular cycle-stage, our research team focused on providing insights into the CD8+ T cells immune response in chronic Chagas cardiomyopathy. We began our work in the 2000s studying parasite antigens that induce natural immune responses such as the KMP11 protein and TcTLE, its N-terminal derived peptide. Different approaches allowed us to reveal TcTLE peptide as a promiscuous CD8+ T cell epitope, able of inducing multifunctional cellular immune responses and eliciting a humoral response capable of decreasing parasite movement and infective capacity. Next, we demonstrated that as the disease progresses, total CD8+ T cells display a dysfunctional state characterized by a prolonged hyper-activation state along with an increase of inhibitory receptors (2B4, CD160, PD-1, TIM-3, CTLA-4) expression, an increase of specific terminal effector T cells (TTE), a decrease of proliferative capacity, a decrease of stem cell memory (TSCM) frequency, and a decrease of CD28 and CD3ζ expression. Thus, parasite-specific CD8+ T cells undergo clonal exhaustion, distinguished by an increase in late-differentiated cells, a mono-functional response, and enhanced expression of inhibitory receptors. Finally, it was found that anti-parasitic treatment induces an improved CD8+ T cell response in asymptomatic individuals, and a mouse animal model led us to establish a correlation between the quality of the CD8+ T cell responses and the outcome of chronic infection. In the future, using OMICs strategies, the identification of the specific cellular signals involved in disease progression will provide an invaluable resource for discovering new biomarkers of progression or new vaccine and immunotherapy strategies. Also, the inclusion of the TcTLE peptide in the rational design of epitope-based vaccines, the development of immunotherapy strategies using TSCM or the blocking of inhibitory receptors, and the use of the CD8+ T cell response quality to follow treatments, immunotherapies or vaccines, all are alternatives than could be explored in the fight against Chagas disease.

Targeting the EGFR in cancer cells by fusion protein consisting of arazyme and third loop of TGF-alpha: an in silico study

The anticancer effects of arazyme, a bacterial metalloprotease, have been revealed in previous studies. Because of the overexpression of epidermal growth factor receptor (EGFR) in tumor cells, targeting this receptor is one of the approaches to cancer therapy. In the present study, we designed fusion protein by using a non-mitogenic binding sequence of TGFα, arazyme, and a suitable linker. The I-TASSER and Robetta web servers were employed to predict the territory structures of the Arazyme-linker-TGFαL3, and TGFαL3-linker-Arazyme. Then, models were validated by using PROCHECK, ERRAT, ProSA, and MolProbity web servers. After docking to EGFR, Arazyme-linker-TGFαL3 showed a higher binding affinity and was selected to be optimized through 100 ns Molecular dynamic (MD) simulation. Next, the stability of ligand-bound receptor was examined utilizing MD simulation for 100 ns. Furthermore, the binding free energy calculation and free energy decomposition were carried out employing MM-PBSA and MM-GBSA methods, respectively. The root mean square deviation and fluctuation (RMSD, RMSF), the radius of gyration, H-bond, and binding free energy analysis revealed the stability of the complex during simulation time. Finally, linear and conformational epitopes of B cells, as well as MHC class I and MHC class II were predicted by using different web servers. Meanwhile, the potential B cell and T cell epitopes were identified throughout arazyme protein sequence. Collectively, this study suggests a novel chimera protein candidate prevent cancer cells potentially by inducing an immune response and inhibiting cell proliferation. Communicated by Ramaswamy H. Sarma.

The Intracellular Proteome as a Source for Novel Targets in CAR-T and T-Cell Engagers-Based Immunotherapy

The impressive clinical success of cancer immunotherapy has motivated the continued search for new targets that may serve to guide potent effector functions in an attempt to efficiently kill malignant cells. The intracellular proteome is an interesting source for such new targets, such as neo-antigens and others, with growing interest in their application for cell-based immunotherapies. These intracellular-derived targets are peptides presented by MHC class I molecules on the cell surface of malignant cells. These disease-specific class I HLA-peptide complexes can be targeted by specific TCRs or by antibodies that mimic TCR-specificity, termed TCR-like (TCRL) antibodies. Adoptive cell transfer of TCR engineered T cells and T-cell-receptor-like based CAR-T cells, targeted against a peptide-MHC of interest, are currently tested as cancer therapeutic agents in pre-clinical and clinical trials, along with soluble TCR- and TCRL-based agents, such as immunotoxins and bi-specific T cell engagers. Targeting the intracellular proteome using TCRL- and TCR-based molecules shows promising results in cancer immunotherapy, as exemplified by the success of the anti-gp100/HLA-A2 TCR-based T cell engager, recently approved by the FDA for the treatment of unresectable or metastatic uveal melanoma. This review is focused on the selection and isolation processes of TCR- and TCRL-based targeting moieties, with a spotlight on pre-clinical and clinical studies, examining peptide-MHC targeting agents in cancer immunotherapy.

Vaccination with Designed Neopeptides Induces Intratumoral, Cross-reactive CD4+ T-cell Responses in Glioblastoma

PURPOSE

The low mutational load of some cancers is considered one reason for the difficulty to develop effective tumor vaccines. To overcome this problem, we developed a strategy to design neopeptides through single amino acid mutations to enhance their immunogenicity.

EXPERIMENTAL DESIGN

Exome and RNA sequencing as well as in silico HLA-binding predictions to autologous HLA molecules were used to identify candidate neopeptides. Subsequently, in silico HLA-anchor placements were used to deduce putative T-cell receptor (TCR) contacts of peptides. Single amino acids of TCR contacting residues were then mutated by amino acid replacements. Overall, 175 peptides were synthesized and sets of 25 each containing both peptides designed to bind to HLA class I and II molecules applied in the vaccination. Upon development of a tumor recurrence, the tumor-infiltrating lymphocytes (TIL) were characterized in detail both at the bulk and clonal level.

RESULTS

The immune response of peripheral blood T cells to vaccine peptides, including natural peptides and designed neopeptides, gradually increased with repetitive vaccination, but remained low. In contrast, at the time of tumor recurrence, CD8+ TILs and CD4+ TILs responded to 45% and 100%, respectively, of the vaccine peptides. Furthermore, TIL-derived CD4+ T-cell clones showed strong responses and tumor cell lysis not only against the designed neopeptide but also against the unmutated natural peptides of the tumor.

CONCLUSIONS

Turning tumor self-peptides into foreign antigens by introduction of designed mutations is a promising strategy to induce strong intratumoral CD4+ T-cell responses in a cold tumor like glioblastoma.

What do cancer-specific T cells 'see'?

Complex cellular interactions between the immune system and cancer can impact tumour development, growth, and progression. T cells play a key role in these interactions; however, the challenge for T cells is to recognize tumour antigens whilst minimizing cross-reactivity with antigens associated with healthy tissue. Some tumour cells, including those associated with viral infections, have clear, tumour-specific antigens that can be targeted by T cells. A high mutational burden can lead to increased numbers of mutational neoantigens that allow very specific immune responses to be generated but also allow escape variants to develop. Other cancer indications and those with low mutational burden are less easily distinguished from normal tissue. Recent studies have suggested that cancer-associated alterations in tumour cell biology including changes in post-translational modification (PTM) patterns may also lead to novel antigens that can be directly recognized by T cells. The PTM-derived antigens provide tumour-specific T-cell responses that both escape central tolerance and avoid the necessity for individualized therapies. PTM-specific CD4 T-cell responses have shown tumour therapy in murine models and highlight the importance of CD4 T cells as well as CD8 T cells in reversing the immunosuppressive tumour microenvironment. Understanding which cancer-specific antigens can be recognized by T cells and the way that immune tolerance and the tumour microenvironment shape immune responses to cancer is vital for the future development of cancer therapies.

SARS-CoV-2 Omicron (BA.1 and BA.2) specific novel CD8+ and CD4+ T cell epitopes targeting spike protein

The Omicron (BA.1/B.1.1.529) variant of SARS-CoV-2 harbors an alarming 37 mutations on its spike protein, reducing the efficacy of current COVID-19 vaccines. In this study, we identified CD8+ and CD4+ T cell epitopes from SARS-CoV-2 S protein mutants. To identify the highest quality CD8 and CD4 epitopes from the Omicron variant, we selected epitopes with a high binding affinity towards both MHC I and MHC II molecules. We applied other clinical checkpoint predictors, including immunogenicity, antigenicity, allergenicity, instability and toxicity. Subsequently, we found eight Omicron (BA.1/B.1.1.529) specific CD8+ and eleven CD4+ T cell epitopes with a world population coverage of 76.16% and 97.46%, respectively. Additionally, we identified common epitopes across Omicron BA.1 and BA.2 lineages that target mutations critical to SARS-CoV-2 virulence. Further, we identified common epitopes across B.1.1.529 and other circulating SARS-CoV-2 variants, such as B.1.617.2 (Delta). We predicted CD8 epitopes' binding affinity to murine MHC alleles to test the vaccine candidates in preclinical models. The CD8 epitopes were further validated using our previously developed software tool PCOptim. We then modeled the three-dimensional structures of our top CD8 epitopes to investigate the binding interaction between peptide-MHC and peptide-MHC-TCR complexes. Notably, our identified epitopes are targeting the mutations on the RNA-binding domain and the fusion sites of S protein. This could potentially eliminate viral infections and form long-term immune responses compared to relatively short-lived mRNA vaccines and maximize the efficacy of vaccine candidates against the current pandemic and potential future variants.

BRAFV600E and BRAF-WT Specific Antitumor Immunity in Papillary Thyroid Cancer

One feature of papillary thyroid cancer (PTC) is the frequently present somatic BRAF^V600E mutation. PTCs are also characterized by a lymphocytic infiltration, which may correlate with an improved clinical outcome. The objective of the study was the characterization of BRAF^V600E specific anti-immunity in PTC patients and correlation analyses with the clinical outcome. Fourteen HLA A2 positive PTC patients were included into the study of whom tumor tissue samples were also available. Of those, 8 PTC patients revealed a somatic BRAF^V600E mutation. All PTC patients were also MHC class II typed. Tetramer analyses for detection of MHC class I and MHC class II-restricted, BRAF^V600E epitope-specific T cells using unstimulated and peptide-stimulated T cells were performed; correlation analyses between MHC phenotypes, T cell immunity, and the clinical course were performed. In regard to unstimulated T cells, a significantly higher amount of BRAF^V600E epitope specific T cells was detected compared to a control tetramer. Importantly, after overnight peptide stimulation a significantly higher number of BRAF^V600E positive and BRAF WT epitope-specific T cells could be seen. In regard to the clinical course, however, no significant differences were seen, neither in the context of the initial tumor size, nor in the context of lymph node metastases or peripheral metastastic spread. In conclusion, we clearly demonstrated a BRAF-specific tumor immunity in PTC-patients which is, however, independent of a BRAF^V600E status of the PTC patients.

Neoantigen-specific TCR-T cell-based immunotherapy for acute myeloid leukemia

Neoantigens derived from non-synonymous somatic mutations are restricted to malignant cells and are thus considered ideal targets for T cell receptor (TCR)-based immunotherapy. Adoptive transfer of T cells bearing neoantigen-specific TCRs exhibits the ability to preferentially target tumor cells while remaining harmless to normal cells. High-avidity TCRs specific for neoantigens expressed on AML cells have been identified in vitro and verified using xenograft mouse models. Preclinical studies of these neoantigen-specific TCR-T cells are underway and offer great promise as safe and effective therapies. Additionally, TCR-based immunotherapies targeting tumor-associated antigens are used in early-phase clinical trials for the treatment of AML and show encouraging anti-leukemic effects. These clinical experiences support the application of TCR-T cells that are specifically designed to recognize neoantigens. In this review, we will provide a detailed profile of verified neoantigens in AML, describe the strategies to identify neoantigen-specific TCRs, and discuss the potential of neoantigen-specific T-cell-based immunotherapy in AML.

An Attention Based Bidirectional LSTM Method to Predict the Binding of TCR and Epitope

The T-cell epitope prediction has always been a long-term challenge in immunoinformatics and bioinformatics. Studying the specific recognition between T-cell receptor (TCR) and peptide-major histocompatibility complex (p-MHC) complexes can help us better understand the immune mechanism, it's also make a signification contribution in developing vaccines and targeted drugs. Meanwhile, more advanced methods are needed for distinguishing TCRs binding from different epitopes. In this paper, we introduce a hybrid model composed of bidirectional long short-term memory networks (BiLSTM), attention and convolutional neural networks (CNN) that can identified the binding of TCRs to epitopes. The BiLSTM can more completely extract amino acid forward and backward information in the sequence, and attention mechanism can focus on amino acids at certain positions from complex sequences to capture the most important feature, then CNN was used to further extract salient features to predict the binding of TCR-epitope. In McPAS dataset, the AUC value (the area under ROC curve) of naive TCR-epitope binding is 0.974 and specific TCR-epitope binding is 0.887. The model has achieved better prediction results than other existing models (TCRGP, ERGO, NetTCR), and some experiments are used to analyze the advantages of our model. The algorithm is available at https://github.com/bijingshu/BiAttCNN.git.

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.

Tumor microenvironment: barrier or opportunity towards effective cancer therapy

Tumor microenvironment (TME) is a specialized ecosystem of host components, designed by tumor cells for successful development and metastasis of tumor. With the advent of 3D culture and advanced bioinformatic methodologies, it is now possible to study TME’s individual components and their interplay at higher resolution. Deeper understanding of the immune cell’s diversity, stromal constituents, repertoire profiling, neoantigen prediction of TMEs has provided the opportunity to explore the spatial and temporal regulation of immune therapeutic interventions. The variation of TME composition among patients plays an important role in determining responders and non-responders towards cancer immunotherapy. Therefore, there could be a possibility of reprogramming of TME components to overcome the widely prevailing issue of immunotherapeutic resistance. The focus of the present review is to understand the complexity of TME and comprehending future perspective of its components as potential therapeutic targets. The later part of the review describes the sophisticated 3D models emerging as valuable means to study TME components and an extensive account of advanced bioinformatic tools to profile TME components and predict neoantigens. Overall, this review provides a comprehensive account of the current knowledge available to target TME.

The Autophagy Receptor TAX1BP1 (T6BP) improves antigen presentation by MHC-II molecules

CD4⁺ T lymphocytes play a major role in the establishment and maintenance of immunity. They are activated by antigenic peptides derived from extracellular or newly synthesized (endogenous) proteins presented by the MHC-II molecules. The pathways leading to endogenous MHC-II presentation remain poorly characterized. We demonstrate here that the autophagy receptor, T6BP, influences both autophagy-dependent and -independent endogenous presentation of HIV- and HCMV-derived peptides. By studying the immunopeptidome of MHC-II molecules, we show that T6BP affects both the quantity and quality of peptides presented. T6BP silencing induces the mislocalization of the MHC-II-loading compartments and rapid degradation of the invariant chain (CD74) without altering the expression and internalization kinetics of MHC-II molecules. Defining the interactome of T6BP, we identify calnexin as a T6BP partner. We show that the calnexin cytosolic tail is required for this interaction. Remarkably, calnexin silencing replicates the functional consequences of T6BP silencing: decreased CD4⁺ T cell activation and exacerbated CD74 degradation. Altogether, we unravel T6BP as a key player of the MHC-II-restricted endogenous presentation pathway, and we propose one potential mechanism of action.

A novel vaccine based on SARS-CoV-2 CD4+ and CD8+ T cell conserved epitopes from variants Alpha to Omicron

COVID-19 caused, as of September, 1rst, 2022, 599,825,400 confirmed cases, including 6,469,458 deaths. Currently used vaccines reduced severity and mortality but not virus transmission or reinfection by different strains. They are based on the Spike protein of the Wuhan reference virus, which although highly antigenic suffered many mutations in SARS-CoV-2 variants, escaping vaccine-generated immune responses. Multiepitope vaccines based on 100% conserved epitopes of multiple proteins of all SARS-CoV-2 variants, rather than a single highly mutating antigen, could offer more long-lasting protection. In this study, a multiepitope multivariant vaccine was designed using immunoinformatics and in silico approaches. It is composed of highly promiscuous and strong HLA binding CD4+ and CD8+ T cell epitopes of the S, M, N, E, ORF1ab, ORF 6 and ORF8 proteins. Based on the analysis of one genome per WHO clade, the epitopes were 100% conserved among the Wuhan-Hu1, Alpha, Beta, Gamma, Delta, Omicron, Mµ, Zeta, Lambda and R1 variants. An extended epitope-conservancy analysis performed using GISAID metadata of 3,630,666 SARS-CoV-2 genomes of these variants and the additional genomes of the Epsilon, Lota, Theta, Eta, Kappa and GH490 R clades, confirmed the high conservancy of the epitopes. All but one of the CD4 peptides showed a level of conservation greater than 97% among all genomes. All but one of the CD8 epitopes showed a level of conservation greater than 96% among all genomes, with the vast majority greater than 99%. A multiepitope and multivariant recombinant vaccine was designed and it was stable, mildly hydrophobic and non-toxic. The vaccine has good molecular docking with TLR4 and promoted, without adjuvant, strong B and Th1 memory immune responses and secretion of high levels of IL-2, IFN-γ, lower levels of IL-12, TGF-β and IL-10, and no IL-6. Experimental in vivo studies should validate the vaccine's further use as preventive tool with cross-protective properties.

Arginase-2-specific cytotoxic T cells specifically recognize functional regulatory T cells

Background

High expression of the metabolic enzyme arginase-2 (ARG2) by cancer cells, regulatory immune cells, or cells of the tumor stroma can reduce the availability of arginine (L-Arg) in the tumor microenvironment (TME). Depletion of L-Arg has detrimental consequences for T cells and leads to T-cell dysfunction and suppression of anticancer immune responses. Previous work from our group has demonstrated the presence of proinflammatory ARG2-specific CD4 T cells that inhibited tumor growth in murine models on activation with ARG2-derived peptides. In this study, we investigated the natural occurrence of ARG2-specific CD8 T cells in both healthy donors (HDs) and patients with cancer, along with their immunomodulatory capabilities in the context of the TME.

Materials and methods

A library of 15 major histocompatibility complex (MHC) class I-restricted ARG2-derived peptides were screened in HD peripheral blood mononuclear cells using interferon gamma (IFN-γ) ELISPOT. ARG2-specific CD8 T-cell responses were identified using intracellular cytokine staining and ARG2-specific CD8 T-cell cultures were established by enrichment and rapid expansion following in vitro peptide stimulation. The reactivity of the cultures toward ARG2-expressing cells, including cancer cell lines and activated regulatory T cells (Tregs), was assessed using IFN-γ ELISPOT and a chromium release assay. The Treg signature was validated based on proliferation suppression assays, flow cytometry and quantitative reverse transcription PCR (RT-qPCR). In addition, vaccinations with ARG2-derived epitopes were performed in the murine Pan02 tumor model, and induction of ARG2-specific T-cell responses was evaluated with IFN-γ ELISPOT. RNAseq and subsequent GO-term and ImmuCC analysis was performed on the tumor tissue.

Results

We describe the existence of ARG2-specific CD8⁺ T cells and demonstrate these CD8⁺ T-cell responses in both HDs and patients with cancer. ARG2-specific T cells recognize and react to an ARG2-derived peptide presented in the context of HLA-B8 and exert their cytotoxic function against cancer cells with endogenous ARG2 expression. We demonstrate that ARG2-specific T cells can specifically recognize and react to activated Tregs with high ARG2 expression. Finally, we observe tumor growth suppression and antitumorigenic immunomodulation following ARG2 vaccination in an in vivo setting.

Conclusion

These findings highlight the ability of ARG2-specific T cells to modulate the immunosuppressive TME and suggest that ARG2-based immunomodulatory vaccines may be an interesting option for cancer immunotherapy.

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).

SILVI, an open-source pipeline for T-cell epitope selection

High-throughput screening of available genomic data and identification of potential antigenic candidates have promoted the development of epitope-based vaccines and therapeutics. Several immunoinformatic tools are available to predict potential epitopes and other immunogenicity-related features, yet it is still challenging and time-consuming to compare and integrate results from different algorithms. We developed the R script SILVI (short for: from in silico to in vivo), to assist in the selection of the potentially most immunogenic T-cell epitopes from Human Leukocyte Antigen (HLA)-binding prediction data. SILVI merges and compares data from available HLA-binding prediction servers, and integrates additional relevant information of predicted epitopes, namely BLASTp alignments with host proteins and physical-chemical properties. The two default criteria applied by SILVI and additional filtering allow the fast selection of the most conserved, promiscuous, strong binding T-cell epitopes. Users may adapt the script at their discretion as it is written in open-source R language. To demonstrate the workflow and present selection options, SILVI was used to integrate HLA-binding prediction results of three example proteins, from viral, bacterial and parasitic microorganisms, containing validated epitopes included in the Immune Epitope Database (IEDB), plus the Human Papillomavirus (HPV) proteome. Applying different filters on predicted IC50, hydrophobicity and mismatches with host proteins allows to significantly reduce the epitope lists with favourable sensitivity and specificity to select immunogenic epitopes. We contemplate SILVI will assist T-cell epitope selections and can be continuously refined in a community-driven manner, helping the improvement and design of peptide-based vaccines or immunotherapies. SILVI development version is available at: github.com/JoanaPissarra/SILVI2020 and https://doi.org/10.5281/zenodo.6865909.

Differential ion mobility mass spectrometry in immunopeptidomics identifies neoantigens carrying colorectal cancer driver mutations

Understanding the properties of human leukocyte antigen (HLA) peptides (immunopeptides) is essential for precision cancer medicine, while the direct identification of immunopeptides from small biopsies of clinical tissues by mass spectrometry (MS) is still confronted with technical challenges. Here, to overcome these hindrances, high-field asymmetric waveform ion mobility spectrometry (FAIMS) is introduced to conduct differential ion mobility (DIM)-MS by seamless gas-phase fractionation optimal for scarce samples. By established DIM-MS for immunopeptidomics analysis, on average, 42.9 mg of normal and tumor colorectal tissues from identical patients (n = 17) were analyzed, and on average 4921 immunopeptides were identified. Among these 44,815 unique immunopeptides, two neoantigens, KRAS-G12V and CPPED1-R228Q, were identified. These neoantigens were confirmed by synthetic peptides through targeted MS in parallel reaction monitoring (PRM) mode. Comparison of the tissue-based personal immunopeptidome revealed tumor-specific processing of immunopeptides. Since the direct identification of neoantigens from tumor tissues suggested that more potential neoantigens have yet to be identified, we screened cell lines with known oncogenic KRAS mutations and identified 2 more neoantigens that carry KRAS-G12V. These results indicated that the established FAIMS-assisted DIM-MS is effective in the identification of immunopeptides and potential recurrent neoantigens directly from scarce samples such as clinical tissues.

Viral informatics: bioinformatics-based solution for managing viral infections

Several new viral infections have emerged in the human population and establishing as global pandemics. With advancements in translation research, the scientific community has developed potential therapeutics to eradicate or control certain viral infections, such as smallpox and polio, responsible for billions of disabilities and deaths in the past. Unfortunately, some viral infections, such as dengue virus (DENV) and human immunodeficiency virus-1 (HIV-1), are still prevailing due to a lack of specific therapeutics, while new pathogenic viral strains or variants are emerging because of high genetic recombination or cross-species transmission. Consequently, to combat the emerging viral infections, bioinformatics-based potential strategies have been developed for viral characterization and developing new effective therapeutics for their eradication or management. This review attempts to provide a single platform for the available wide range of bioinformatics-based approaches, including bioinformatics methods for the identification and management of emerging or evolved viral strains, genome analysis concerning the pathogenicity and epidemiological analysis, computational methods for designing the viral therapeutics, and consolidated information in the form of databases against the known pathogenic viruses. This enriched review of the generally applicable viral informatics approaches aims to provide an overview of available resources capable of carrying out the desired task and may be utilized to expand additional strategies to improve the quality of translation viral informatics research.

Combined treatment with epigenetic agents enhances anti-tumor activity of MAGE-D4 peptide-specific T cells by upregulating the MAGE-D4 expression in glioma

Objective

The study evaluated the efficacy of combined epigenetic drugs of decitabine (DAC), valproic acid (VPA), and trichostatin A (TSA) on immunotherapy against glioma.

Methods

The expression and prognosis of MAGE-D4 in glioma were analyzed online, and the expression of MAGE-D4 and HLA-A2 in glioma induced by epigenetic drugs was detected by qRT-PCR, Western blot, and flow cytometry. The methylation status of the MAGE-D4 promoter was determined by pyrosequencing. An HLA-A2 restricted MAGE-D4 peptide was predicted and synthesized. An affinity assay and a peptide/HLA complex stability assay were performed to determine the affinity between peptide and HLA. CCK8 assay, CFSE assay, ELISA and ELISPOT were performed to detect the function of MAGE-D4 peptide-specific T cells. Flow cytometry, ELISA, and cytotoxicity assays were used to detect the cytotoxicity effect of MAGE-D4 peptide-specific T cells combined with epigenetic drugs against glioma in vitro. Finally, the glioma-loaded mouse model was applied to test the inhibitory effect of specific T cells on gliomas in vivo.

Results

MAGE-D4 was highly expressed in glioma and correlated with poor prognosis. Glioma cells could be induced to express MAGE-D4 and HLA-A2 by epigenetic drugs. MAGE-D4-associated peptides were found that induce DCs to stimulate the highest T-cell activities of proliferation, IL-2 excretion, and IFN-γ secretion. MAGE-D4 peptide-specific T cells treated with TSA only or combining TSA and DAC had the most cytotoxicity effect, and its cytotoxicity effect on glioma cells decreased significantly after HLA blocking. In vivo experiments also confirmed that MAGE-D4-specific T cells inhibit TSA-treated glioma.

Conclusion

MAGE-D4 is highly expressed in glioma and correlated with the prognosis of glioma. The novel MAGE-D4 peptide identified was capable of inducing MAGE-D4-specific T cells that can effectively inhibit glioma growth, and the epigenetic drug application can enhance this inhibition.

CAF08 adjuvant enables single dose protection against respiratory syncytial virus infection in murine newborns

Respiratory syncytial virus is a leading cause of morbidity and mortality in children, due in part to their distinct immune system, characterized by impaired induction of Th 1 immunity. Here we show application of cationic adjuvant formulation CAF08, a liposomal vaccine formulation tailored to induce Th 1 immunity in early life via synergistic engagement of Toll-like Receptor 7/8 and the C-type lectin receptor Mincle. We apply quantitative phosphoproteomics to human dendritic cells and reveal a role for Protein Kinase C-δ for enhanced Th1 cytokine production in neonatal dendritic cells and identify signaling events resulting in antigen cross-presentation. In a murine in vivo model a single immunization at birth with CAF08-adjuvanted RSV pre-fusion antigen protects newborn mice from RSV infection by induction of antigen-specific CD8+ T-cells and Th1 cells. Overall, we describe a pediatric adjuvant formulation and characterize its mechanism of action providing a promising avenue for development of early life vaccines against RSV and other respiratory viral pathogens.

A comprehensive analysis of the IEDB MHC class-I automated benchmark

In 2014, the Immune Epitope Database automated benchmark was created to compare the performance of the MHC class I binding predictors. However, this is not a straightforward process due to the different and non-standardized outputs of the methods. Additionally, some methods are more restrictive regarding the HLA alleles and epitope sizes for which they predict binding affinities, while others are more comprehensive. To address how these problems impacted the ranking of the predictors, we developed an approach to assess the reliability of different metrics. We found that using percentile-ranked results improved the stability of the ranks and allowed the predictors to be reliably ranked despite not being evaluated on the same data. We also found that given the rate new data are incorporated into the benchmark, a new method must wait for at least 4 years to be ranked against the pre-existing methods. The best-performing tools with statistically indistinguishable scores in this benchmark were NetMHCcons, NetMHCpan4.0, ANN3.4, NetMHCpan3.0 and NetMHCpan2.8. The results of this study will be used to improve the evaluation and display of benchmark performance. We highly encourage anyone working on MHC binding predictions to participate in this benchmark to get an unbiased evaluation of their predictors.

In silico design of multi-epitope-based peptide vaccine against SARS-CoV-2 using its spike protein

SARS-CoV-2 has been efficient in ensuring that many countries are brought to a standstill. With repercussions ranging from rampant mortality, fear, paranoia, and economic recession, the virus has brought together countries to look at possible therapeutic countermeasures. With prophylactic interventions possibly months away from being particularly effective, a slew of measures and possibilities concerning the design of vaccines are being worked upon. We attempted a structure-based approach utilizing a combination of epitope prediction servers and Molecular dynamic (MD) simulations to develop a multi-epitope-based subunit vaccine that involves the two subunits of the spike glycoprotein of SARS-CoV-2 (S1 and S2) coupled with a substantially effective chimeric adjuvant to create stable vaccine constructs. The designed constructs were evaluated based on their docking with Toll-Like Receptor (TLR) 4. Our findings provide an epitope-based peptide fragment that can be a potential candidate for the development of a vaccine against SARS-CoV-2. Recent experimental studies based on determining immunodominant regions across the spike glycoprotein of SARS-CoV-2 indicate the presence of the predicted epitopes included in this study.Communicated by Ramaswamy H. Sarma.

Mapping immunogenic epitopes of an adhesin-like protein from Methanobrevibacter ruminantium M1 and comparison of empirical data with in silico prediction methods

In silico prediction of epitopes is a potentially time-saving alternative to experimental epitope identification but is often subject to misidentification of epitopes and may not be useful for proteins from archaeal microorganisms. In this study, we mapped B- and T-cell epitopes of a model antigen from the methanogen Methanobrevibacter ruminantium M1, the Big_1 domain (AdLP-D1, amino acids 19-198) of an adhesin-like protein. A series of 17 overlapping 20-mer peptides was selected to cover the Big_1 domain. Peptide-specific antibodies were produced in mice and measured by ELISA, while an in vitro splenocyte re-stimulation assay determined specific T-cell responses. Overall, five peptides of the 17 peptides were shown to be major immunogenic epitopes of AdLP-D1. These immunogenic regions were examined for their localization in a homology-based model of AdLP-D1. Validated epitopes were found in the outside region of the protein, with loop like secondary structures reflecting their flexibility. The empirical data were compared with epitope predictions made by programmes based on a range of algorithms. In general, the epitopes identified by in silico predictions were not comparable to those determined empirically.

Designing of multi-epitope chimeric vaccine using immunoinformatic platform by targeting oncogenic strain HPV 16 and 18 against cervical cancer

Cervical cancer is the most common gynaecological cancer and reaches an alarming stage. HPVs are considered the main causative agents for cervical cancer and other sexually transmitted infections across the globe. Currently, three prophylactic vaccines are available against HPV infections with no therapeutic values. Due to a lack of effective therapeutic and prophylactic measures, the HPV infection is spreading in an uncontrolled manner. Next-generation of vaccine is needed to have both prophylactic and therapeutic values against HPV. Here first time we have designed a multi-epitope chimeric vaccine using the most oncogenic strain HPV 16 and HPV 18 through an immunoinformatic approach. In this study, we have used the L1, E5, E6 and E7 oncoproteins from both HPV 16 and HPV 18 strains for epitope prediction. Our recombinant chimeric vaccine construct consists, selected helper and cytotoxic T cell epitopes. Our computational analysis suggests that this chimeric construct is highly stable, non-toxic and also capable of inducing both cell-mediated and humoral immune responses. Furthermore, in silico cloning of the multi-epitope chimeric vaccine construct was done and the stabilization of the vaccine construct is validated with molecular dynamics simulation studies. Finally, our results indicated that our construct could be used for an effective prophylactic and therapeutic vaccine against HPV.

Prediction of Major Histocompatibility Complex Binding with Bilateral and Variable Long Short Term Memory Networks

Simple Summary

Major histocompatibility complex molecules are of significant biological and clinical importance due to their utility in immunotherapy. The prediction of potential MHC binding peptides can estimate a T-cell immune response. The variable length of existing MHC binding peptides creates difficulty for MHC binding prediction algorithms. Thus, we utilized a bilateral and variable long-short term memory neural network to address this specific problem and developed a novel MHC binding prediction tool.

Abstract

As an important part of immune surveillance, major histocompatibility complex (MHC) is a set of proteins that recognize foreign molecules. Computational prediction methods for MHC binding peptides have been developed. However, existing methods share the limitation of fixed peptide sequence length, which necessitates the training of models by peptide length or prediction with a length reduction technique. Using a bidirectional long short-term memory neural network, we constructed BVMHC, an MHC class I and II binding prediction tool that is independent of peptide length. The performance of BVMHC was compared to seven MHC class I prediction tools and three MHC class II prediction tools using eight performance criteria independently. BVMHC attained the best performance in three of the eight criteria for MHC class I, and the best performance in four of the eight criteria for MHC class II, including accuracy and AUC. Furthermore, models for non-human species were also trained using the same strategy and made available for applications in mice, chimpanzees, macaques, and rats. BVMHC is composed of a series of peptide length independent MHC class I and II binding predictors. Models from this study have been implemented in an online web portal for easy access and use.

Antigen Presentation in the Lung

The lungs are constantly exposed to environmental and infectious agents such as dust, viruses, fungi, and bacteria that invade the lungs upon breathing. The lungs are equipped with an immune defense mechanism that involves a wide variety of immunological cells to eliminate these agents. Various types of dendritic cells (DCs) and macrophages (MACs) function as professional antigen-presenting cells (APCs) that engulf pathogens through endocytosis or phagocytosis and degrade proteins derived from them into peptide fragments. During this process, DCs and MACs present the peptides on their major histocompatibility complex class I (MHC-I) or MHC-II protein complex to naïve CD8⁺ or CD4⁺ T cells, respectively. In addition to these cells, recent evidence supports that antigen-specific effector and memory T cells are activated by other lung cells such as endothelial cells, epithelial cells, and monocytes through antigen presentation. In this review, we summarize the molecular mechanisms of antigen presentation by APCs in the lungs and their contribution to immune response.

SARS-CoV-2 Omicron Variant is Expected to Retain Most of the Spike Protein Specific Dominant T-Cell Epitopes Presented by COVID-19 Vaccines - Worldwide, 2021

What is already known about this topic?

The newly emerged variant of Omicron, which carries many of the mutations found in other variants of concern (VOCs), as well as a great number of new mutations that may enhance its immune escape, has spread rapidly around the world. This has raised public concern about the effectiveness of the current coronavirus disease 2019 (COVID-19) vaccine.

What is added by this report?

In this study, different bioinformatic softwares were applied to predict the dominant Omicron spike (S) protein cytotoxic T lymphocyte (CTL) and T helper (Th) epitopes in representative world population and Chinese population. Compared to the original severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) S protein, limited mutations were identified within the dominant CTL and Th epitopes in Omicron variant.

What are the implications for public health practice?

The results of this study suggested that the current COVID-19 vaccine-induced T-cell immunity may still provide significant protection against Omicron variant infection in fully vaccinated individuals.

IDO Vaccine Ablates Immune-Suppressive Myeloid Populations and Enhances Antitumor Effects Independent of Tumor Cell IDO Status

The immunosuppressive tumor microenvironment (TME) does not allow generation and expansion of antitumor effector cells. One of the potent immunosuppressive factors present in the TME is the indoleamine-pyrrole 2,3-dioxygenase (IDO) enzyme, produced mainly by cancer cells and suppressive immune cells of myeloid origin. In fact, IDO+ myeloid-derived suppressor cells (MDSC) and dendritic cells (DC) tend to be more suppressive than their IDO- counterparts. Hence, therapeutic approaches that would target the IDO+ cells in the TME, while sparing the antigen-presenting functions of IDO- myeloid populations, are needed. Using an IDO-specific peptide vaccine (IDO vaccine), we explored the possibility of generating effector cells against IDO and non-IDO tumor-derived antigens. For this, IDO-secreting (B16F10 melanoma) and non-IDO-secreting (TC-1) mouse tumor models were employed. We showed that the IDO vaccine significantly reduced tumor growth and enhanced survival of mice in both the tumor models, which associated with a robust induction of IDO-specific effector cells in the TME. The IDO vaccine significantly enhanced the antitumor efficacy of non-IDO tumor antigen-specific vaccines, leading to an increase in the number of total and antigen-specific activated CD8+ T cells (IFNγ+ and granzyme B+). Treatment with the IDO vaccine significantly reduced the numbers of IDO+ MDSCs and DCs, and immunosuppressive regulatory T cells in both tumor models, resulting in enhanced therapeutic ratios. Together, we showed that vaccination against IDO is a promising therapeutic option for both IDO-producing and non-IDO-producing tumors. The IDO vaccine selectively ablates the IDO+ compartment in the TME, leading to a significant enhancement of the immune responses against other tumor antigen-specific vaccines.

The Use of Molecular Dynamics Simulation Method to Quantitatively Evaluate the Affinity between HBV Antigen T Cell Epitope Peptides and HLA-A Molecules

Chronic hepatitis B virus (HBV), a potentially life-threatening liver disease, makes people vulnerable to serious diseases such as cancer. T lymphocytes play a crucial role in clearing HBV virus, while the pathway depends on the strong binding of T cell epitope peptide and HLA. However, the experimental identification of HLA-restricted HBV antigenic peptides is extremely time-consuming. In this study, we provide a novel prediction strategy based on structure to assess the affinity between the HBV antigenic peptide and HLA molecule. We used residue scanning, peptide docking and molecular dynamics methods to obtain the molecular docking model of HBV peptide and HLA, and then adopted the MM-GBSA method to calculate the binding affinity of the HBV peptide–HLA complex. Overall, we collected 59 structures of HLA-A from Protein Data Bank, and finally obtained 352 numerical affinity results to figure out the optimal bind choice between the HLA-A molecules and 45 HBV T cell epitope peptides. The results were highly consistent with the qualitative affinity level determined by the competitive peptide binding assay, which confirmed that our affinity prediction process based on an HLA structure is accurate and also proved that the homologous modeling strategy for HLA-A molecules in this study was reliable. Hence, our work highlights an effective way by which to predict and screen for HLA-peptide binding that would improve the treatment of HBV infection.