Structure of a SARS coronavirus-derived peptide bound to the human major histocompatibility complex class I molecule HLA-B*1501

The rigidity of a structural bridge on HLA-I binding groove explains its differential outcome in cancer immune response

The tremendous success of immune checkpoint blockade (ICB) therapy has raised the great demand for the development of predictive biomarkers. A recent cancer genomic study suggested that human leukocyte antigen (HLA)-B*44:02 and HLA-B*15:01 alleles may act as potential biomarkers for ICB therapies, however, the underlying molecular mechanisms remain largely elusive. Here, we investigated the molecular origins of differential responses to ICB therapies for four representative HLA alleles: HLA-B*44:02, HLA-B*15:01, HLA-B*07:02, and HLA-B*53:01, using extensive all-atom molecular dynamics simulations. We first demonstrated that the relatively more rigid peptide-binding groove of HLA-B*15:01, than those in the other three HLA alleles, may result in challenges in its recognition with T-cell receptors. Specifically, the "bridge" structure in HLA-B*15:01 is stabilized through both intramolecular electrostatic interactions between the HLA residues and intermolecular interactions between the HLA and the antigenic peptide. These observations were further confirmed by in silico mutagenesis studies, as well as simulations of several other HLA-B*15:01-peptide complexes. By contrast, the "bridge" structure is either completely absent in HLA-B*44:02 or easily perturbed in HLA-B*07:02 and HLA-B*53:01. Our findings provide detailed structural and mechanistic insights into how HLA genotype influences ICB responses and may have important implications for developing immune markers.

Unveiling the functional epitopes of cobra venom cytotoxin by immunoinformatics and epitope-omic analyses

Approximate 70% of cobra venom is composed of cytotoxin (CTX), which is responsible for the dermonecrotic symptoms of cobra envenomation. However, CTX is generally low in immunogenicity, and the antivenom is ineffective in attenuating its in vivo toxicity. Furthermore, little is known about its epitope properties for empirical antivenom therapy. This study aimed to determine the epitope sequences of CTX using the immunoinformatic analyses and epitope-omics profiling. A conserved CTX was used in this study to determine its T-cell and B-cell epitope sequences using immunoinformatic tools and molecular docking simulation with different Human Leukocyte Antigens (HLAs). The potential T-cell and B-cell epitopes were 'KLVPLFY,' 'CPAGKNLCY,' 'MFMVSTPTK,' and 'DVCPKNSLL.' Molecular docking simulations disclosed that the HLA-B62 supertype exhibited the greatest binding affinity towards cobra venom cytotoxin. The namely L7, G18, K19, N20, M25, K33, V43, C44, K46, N47, and S48 of CTX exhibited prominent intermolecular interactions with HLA-B62. The multi-enzymatic-limited-digestion/liquid chromatography-mass spectrometry (MELD/LC-MS) also revealed three potential epitope sequences as 'LVPLFYK,' 'MFMVS,' and 'TVPVKR'. From different epitope mapping approaches, we concluded four potential epitope sites of CTX as 'KLVPLFYK', 'AGKNL', 'MFMVSTPKVPV' and 'DVCPKNSLL'. Site-directed mutagenesis of these epitopes confirmed their locations at the functional loops of CTX. These epitope sequences are crucial to CTX's structural folding and cytotoxicity. The results concluded the epitopes that resided within the functional loops constituted potential targets to fabricate synthetic epitopes for CTX-targeted antivenom production.

Landscape and selection of vaccine epitopes in SARS-CoV-2

BACKGROUND

Early in the pandemic, we designed a SARS-CoV-2 peptide vaccine containing epitope regions optimized for concurrent B cell, CD4+ T cell, and CD8+ T cell stimulation. The rationale for this design was to drive both humoral and cellular immunity with high specificity while avoiding undesired effects such as antibody-dependent enhancement (ADE).

METHODS

We explored the set of computationally predicted SARS-CoV-2 HLA-I and HLA-II ligands, examining protein source, concurrent human/murine coverage, and population coverage. Beyond MHC affinity, T cell vaccine candidates were further refined by predicted immunogenicity, sequence conservation, source protein abundance, and coverage of high frequency HLA alleles. B cell epitope regions were chosen from linear epitope mapping studies of convalescent patient serum, followed by filtering for surface accessibility, sequence conservation, spatial localization near functional domains of the spike glycoprotein, and avoidance of glycosylation sites.

RESULTS

From 58 initial candidates, three B cell epitope regions were identified. From 3730 (MHC-I) and 5045 (MHC-II) candidate ligands, 292 CD8+ and 284 CD4+ T cell epitopes were identified. By combining these B cell and T cell analyses, as well as a manufacturability heuristic, we proposed a set of 22 SARS-CoV-2 vaccine peptides for use in subsequent murine studies. We curated a dataset of ~ 1000 observed T cell epitopes from convalescent COVID-19 patients across eight studies, showing 8/15 recurrent epitope regions to overlap with at least one of our candidate peptides. Of the 22 candidate vaccine peptides, 16 (n = 10 T cell epitope optimized; n = 6 B cell epitope optimized) were manually selected to decrease their degree of sequence overlap and then synthesized. The immunogenicity of the synthesized vaccine peptides was validated using ELISpot and ELISA following murine vaccination. Strong T cell responses were observed in 7/10 T cell epitope optimized peptides following vaccination. Humoral responses were deficient, likely due to the unrestricted conformational space inhabited by linear vaccine peptides.

CONCLUSIONS

Overall, we find our selection process and vaccine formulation to be appropriate for identifying T cell epitopes and eliciting T cell responses against those epitopes. Further studies are needed to optimize prediction and induction of B cell responses, as well as study the protective capacity of predicted T and B cell epitopes.

Frequency of HLA alleles among COVID-19 infected patients: Preliminary data from Saudi Arabia

HLA polymorphism is one of the genetic factors that may be associated with variations in susceptibility to COVID-19 infection. In this study, the frequency of HLA alleles among Saudi patients infected with COVID-19 was examined. The association with infection susceptibility and mortality was evaluated. This study included 135 Saudi COVID-19-infected patients (106 recovered and 29 died) who were admitted to hospitals because of their symptoms, and 135 healthy controls. HLA class I (A, B, C) and class II (DRB1, DQB1) genotyping was performed using the molecular method (PCR-rSSO). In this study, there was a significant increase in the frequency of HLA-A*01, B*56 and C*01 among infected patients compared to the control group (12.1% vs. 5.2%, p = 0.004, 3.7% vs. 0%, p = 0.006, 4.4% vs. 1.5%, p = 0.042, respectively). Moreover, there was a significant increase in the frequency of HLA-A*03 and C*06 among fatal patients compared to infected patients (13.8% vs. 5.7%, p = 0.036, 32.8% vs. 17.5%, p = 0.011, respectively). In terms of HLA class II, HLA-DRB1*04 was significantly higher in the control group compared to infected patients (27.4% vs. 16.3%, p = 0.002), while HLA-DRB1*08 was significantly higher in the infected group compared to the control (4.8% vs. 0.7%, p = 0.004). After statistical correction of the p value, A*01, B*56, DRB1*04 and DRB1*08 remained statistically significant (p_c = 0.04, p_c = 0.03, p_c = 0.014 and p_c = 0.028). This initial data suggested that individual HLA genotypes might play a role in determining susceptibility to COVID-19 infection and infection outcome. However, examining a larger sample size from different populations is required to determine a powerful association for clinical application.

Leveraging on the genomics and immunopathology of SARS-CoV-2 for vaccines development: prospects and challenges

The incidence and case-fatality rates (CFRs) of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection, the etiological agent for Coronavirus Disease 2019 (COVID-19), have been rising unabated. Even though the entire world has been implementing infection prevention and control measures, the pandemic continues to spread. It has been widely accepted that preventive vaccination strategies are the public health measures for countering this pandemic. This study critically reviews the latest scientific advancement in genomics, replication pattern, pathogenesis, and immunopathology of SARS-CoV-2 infection and how these concepts could be used in the development of vaccines. We also offer a detailed discussion on the anticipated potency, efficacy, safety, and pharmaco-economic issues that are and will be associated with candidate COVID-19 vaccines.

Immunoinformatic identification of B cell and T cell epitopes in the SARS-CoV-2 proteome

A novel coronavirus (SARS-CoV-2) emerged from China in late 2019 and rapidly spread across the globe, infecting millions of people and generating societal disruption on a level not seen since the 1918 influenza pandemic. A safe and effective vaccine is desperately needed to prevent the continued spread of SARS-CoV-2; yet, rational vaccine design efforts are currently hampered by the lack of knowledge regarding viral epitopes targeted during an immune response, and the need for more in-depth knowledge on betacoronavirus immunology. To that end, we developed a computational workflow using a series of open-source algorithms and webtools to analyze the proteome of SARS-CoV-2 and identify putative T cell and B cell epitopes. Utilizing a set of stringent selection criteria to filter peptide epitopes, we identified 41 T cell epitopes (5 HLA class I, 36 HLA class II) and 6 B cell epitopes that could serve as promising targets for peptide-based vaccine development against this emerging global pathogen. To our knowledge, this is the first study to comprehensively analyze all 10 (structural, non-structural and accessory) proteins from SARS-CoV-2 using predictive algorithms to identify potential targets for vaccine development.

Landscape and Selection of Vaccine Epitopes in SARS-CoV-2

There is an urgent need for a vaccine with efficacy against SARS-CoV-2. We hypothesize that peptide vaccines containing epitope regions optimized for concurrent B cell, CD4+ T cell, and CD8+ T cell stimulation would drive both humoral and cellular immunity with high specificity, potentially avoiding undesired effects such as antibody-dependent enhancement (ADE). Additionally, such vaccines can be rapidly manufactured in a distributed manner. In this study, we combine computational prediction of T cell epitopes, recently published B cell epitope mapping studies, and epitope accessibility to select candidate peptide vaccines for SARS-CoV-2. We begin with an exploration of the space of possible T cell epitopes in SARS-CoV-2 with interrogation of predicted HLA-I and HLA-II ligands, overlap between predicted ligands, protein source, as well as concurrent human/murine coverage. Beyond MHC affinity, T cell vaccine candidates were further refined by predicted immunogenicity, viral source protein abundance, sequence conservation, coverage of high frequency HLA alleles and co-localization of CD4+ and CD8+ T cell epitopes. B cell epitope regions were chosen from linear epitope mapping studies of convalescent patient serum, followed by filtering to select regions with surface accessibility, high sequence conservation, spatial localization near functional domains of the spike glycoprotein, and avoidance of glycosylation sites. From 58 initial candidates, three B cell epitope regions were identified. By combining these B cell and T cell analyses, as well as a manufacturability heuristic, we propose a set of SARS-CoV-2 vaccine peptides for use in subsequent murine studies and clinical trials.

A Recurrent Mutation in Anaplastic Lymphoma Kinase with Distinct Neoepitope Conformations

The identification of recurrent human leukocyte antigen (HLA) neoepitopes driving T cell responses against tumors poses a significant bottleneck in the development of approaches for precision cancer therapeutics. Here, we employ a bioinformatics method, Prediction of T Cell Epitopes for Cancer Therapy, to analyze sequencing data from neuroblastoma patients and identify a recurrent anaplastic lymphoma kinase mutation (ALK R1275Q) that leads to two high affinity neoepitopes when expressed in complex with common HLA alleles. Analysis of the X-ray structures of the two peptides bound to HLA-B*15:01 reveals drastically different conformations with measurable changes in the stability of the protein complexes, while the self-epitope is excluded from binding due to steric hindrance in the MHC groove. To evaluate the range of HLA alleles that could display the ALK neoepitopes, we used structure-based Rosetta comparative modeling calculations, which accurately predict several additional high affinity interactions and compare our results with commonly used prediction tools. Subsequent determination of the X-ray structure of an HLA-A*01:01 bound neoepitope validates atomic features seen in our Rosetta models with respect to key residues relevant for MHC stability and T cell receptor recognition. Finally, MHC tetramer staining of peripheral blood mononuclear cells from HLA-matched donors shows that the two neoepitopes are recognized by CD8+ T cells. This work provides a rational approach toward high-throughput identification and further optimization of putative neoantigen/HLA targets with desired recognition features for cancer immunotherapy.

T-cell immunity of SARS-CoV: Implications for vaccine development against MERS-CoV

Over 12 years have elapsed since severe acute respiratory syndrome (SARS) triggered the first global alert for coronavirus infections. Virus transmission in humans was quickly halted by public health measures and human infections of SARS coronavirus (SARS-CoV) have not been observed since. However, other coronaviruses still pose a continuous threat to human health, as exemplified by the recent emergence of Middle East respiratory syndrome (MERS) in humans. The work on SARS-CoV widens our knowledge on the epidemiology, pathophysiology and immunology of coronaviruses and may shed light on MERS coronavirus (MERS-CoV). It has been confirmed that T-cell immunity plays an important role in recovery from SARS-CoV infection. Herein, we summarize T-cell immunological studies of SARS-CoV and discuss the potential cross-reactivity of the SARS-CoV-specific immunity against MERS-CoV, which may provide useful recommendations for the development of broad-spectrum vaccines against coronavirus infections.

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T-cell epitopes identified throughout the SARS-CoV proteome may act as candidates for vaccine development.

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Both SARS-CoV and MERS-CoV-recovered donors have had long-lasting memory T-cell immunity.

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The structures of HLA/SARS-CoV-epitopes illuminate the molecular bases of cellular immunogenicity.

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Potential cross-T-cell immune reactivities of SARS-CoV and MERS-CoV benefit vaccine development.

Applications of omics approaches to the development of microbiological risk assessment using RNA virus dose-response models as a case study

T e in the amount of ‘omics’ data available and in our ability to interpret those data. The aim of this paper was to consider how omics techniques can be used to improve and refine microbiological risk assessment, using dose–response models for RNA viruses, with particular reference to norovirus through the oral route as the case study. The dose–response model for initial infection in the gastrointestinal tract is broken down into the component steps at the molecular level and the feasibility of assigning probabilities to each step assessed. The molecular mechanisms are not sufficiently well understood at present to enable quantitative estimation of probabilities on the basis of omics data. At present, the great strength of gene sequence data appears to be in giving information on the distribution and proportion of susceptible genotypes (for example due to the presence of the appropriate pathogen‐binding receptor) in the host population rather than in predicting specificities from the amino acid sequences concurrently obtained. The nature of the mutant spectrum in RNA viruses greatly complicates the application of omics approaches to the development of mechanistic dose–response models and prevents prediction of risks of disease progression (given infection has occurred) at the level of the individual host. However, molecular markers in the host and virus may enable more broad predictions to be made about the consequences of exposure in a population. In an alternative approach, comparing the results of deep sequencing of RNA viruses in the faeces/vomitus from donor humans with those from their infected recipients may enable direct estimates of the average probability of infection per virion to be made.