Binding affinities of 438 HLA proteins to complete proteomes of seven pandemic viruses and distributions of strongest and weakest HLA peptide binders in populations worldwide.

We report detailed peptide-binding affinities between 438 HLA Class I and Class II proteins and complete proteomes of seven pandemic human viruses, including coronaviruses, influenza viruses and HIV-1. We contrast these affinities with HLA allele frequencies across hundreds of human populations worldwide. Statistical modelling shows that peptide-binding affinities classified into four distinct categories depend on the HLA locus but that the type of virus is only a weak predictor, except in the case of HIV-1. Among the strong HLA binders (IC50 ≤ 50), we uncovered 16 alleles (the top ones being A*02:02, B*15:03 and DRB1*01:02) binding more than 1% of peptides derived from all viruses, 9 (top ones including HLA-A*68:01, B*15:25, C*03:02 and DRB1*07:01) binding all viruses except HIV-1, and 15 (top ones A*02:01 and C*14:02) only binding coronaviruses. The frequencies of strongest and weakest HLA peptide binders differ significantly among populations from different geographic regions. In particular, Indigenous peoples of America show both higher frequencies of strongest and lower frequencies of weakest HLA binders. As many HLA proteins are found to be strong binders of peptides derived from distinct viral families, and are hence promiscuous (or generalist), we discuss this result in relation to possible signatures of natural selection on HLA promiscuous alleles due to past pathogenic infections. Our findings are highly relevant for both evolutionary genetics and the development of vaccine therapies. However they should not lead to forget that individual resistance and vulnerability to diseases go beyond the sole HLA allelic affinity and depend on multiple, complex and often unknown biological, environmental and other variables.

Generation of SARS-CoV-2 S1 Spike Glycoprotein Putative Antigenic Epitopes in Vitro by Intracellular Aminopeptidases.

Presentation of antigenic peptides by MHCI is central to cellular immune responses against viral pathogens. While adaptive immune responses versus SARS-CoV-2 can be of critical importance to both recovery and vaccine efficacy, how protein antigens from this pathogen are processed to generate antigenic peptides is largely unknown. Here, we analyzed the proteolytic processing of overlapping precursor peptides spanning the entire sequence of the S1 spike glycoprotein of SARS-CoV-2, by three key enzymes that generate antigenic peptides, aminopeptidases ERAP1, ERAP2, and IRAP. All enzymes generated shorter peptides with sequences suitable for binding onto HLA alleles, but with distinct specificity fingerprints. ERAP1 was the most efficient in generating peptides 8-11 residues long, the optimal length for HLA binding, while IRAP was the least efficient. The combination of ERAP1 with ERAP2 greatly limited the variability of peptide sequences produced. Less than 7% of computationally predicted epitopes were found to be produced experimentally, suggesting that aminopeptidase processing may constitute a significant filter to epitope presentation. These experimentally generated putative epitopes could be prioritized for SARS-CoV-2 immunogenicity studies and vaccine design. We furthermore propose that this in vitro trimming approach could constitute a general filtering method to enhance the prediction robustness for viral antigenic epitopes.

Design of an epitope-based peptide vaccine against the SARS-CoV-2: a vaccine-informatics approach.

The recurrent and recent global outbreak of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has turned into a global concern which has infected more than 42 million people all over the globe, and this number is increasing in hours. Unfortunately, no vaccine or specific treatment is available, which makes it more deadly. A vaccine-informatics approach has shown significant breakthrough in peptide-based epitope mapping and opens the new horizon in vaccine development. In this study, we have identified a total of 15 antigenic peptides [including thymus cells (T-cells) and bone marrow or bursa-derived cells] in the surface glycoprotein (SG) of SARS-CoV-2 which is nontoxic and nonallergenic in nature, nonallergenic, highly antigenic and non-mutated in other SARS-CoV-2 virus strains. The population coverage analysis has found that cluster of differentiation 4 (CD4+) T-cell peptides showed higher cumulative population coverage over cluster of differentiation 8 (CD8+) peptides in the 16 different geographical regions of the world. We identified 12 peptides ((LTDEMIAQY, WTAGAAAYY, WMESEFRVY, IRASANLAA, FGAISSVLN, VKQLSSNFG, FAMQMAYRF, FGAGAALQI, YGFQPTNGVGYQ, LPDPSKPSKR, QTQTNSPRRARS and VITPGTNTSN) that are $80\hbox{--} 90\%$ identical with experimentally determined epitopes of SARS-CoV, and this will likely be beneficial for a quick progression of the vaccine design. Moreover, docking analysis suggested that the identified peptides are tightly bound in the groove of human leukocyte antigen molecules which can induce the T-cell response. Overall, this study allows us to determine potent peptide antigen targets in the SG on intuitive grounds, which opens up a new horizon in the coronavirus disease (COVID-19) research. However, this study needs experimental validation by in vitro and in vivo.

Integrin Activation Enables Sensitive Detection of Functional CD4+ and CD8+ T Cells: Application to Characterize SARS-CoV-2 Immunity.

We have previously shown that conformational change in the ß2-integrin is a very early activation marker that can be detected with fluorescent multimers of its ligand intercellular adhesion molecule (ICAM)-1 for rapid assessment of antigen-specific CD8+ T cells. In this study, we describe a modified protocol of this assay for sensitive detection of functional antigen-specific CD4+ T cells using a monoclonal antibody (clone m24 Ab) specific for the open, high-affinity conformation of the ß2-integrin. The kinetics of ß2-integrin activation was different on CD4+ and CD8+ T cells (several hours vs. few minutes, respectively); however, m24 Ab readily stained both cell types 4-6 h after antigen stimulation. With this protocol, we were able to monitor ex vivo effector and memory CD4+ and CD8+ T cells specific for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), cytomegalovirus (CMV), Epstein-Barr virus (EBV), and hepatitis B virus (HBV) in whole blood or cryopreserved peripheral blood mononuclear cells (PBMCs) of infected or vaccinated individuals. By costaining ß2-integrin with m24 and CD154 Abs, we assessed extremely low frequencies of polyfunctional CD4+ T cell responses. The novel assay used in this study allows very sensitive and simultaneous screening of both CD4+ and CD8+ T cell reactivities, with versatile applicability in clinical and vaccination studies.

Design of novel multiepitope constructs-based peptide vaccine against the structural S, N and M proteins of human COVID-19 using immunoinformatics analysis.

The causative agent of severe acute respiratory syndrome (SARS) reported by the Chinese Center for Disease Control (China CDC) has been identified as a novel Betacoronavirus (SARS-CoV-2). A computational approach was adopted to identify multiepitope vaccine candidates against SARS-CoV-2 based on S, N and M proteins being able to elicit both humoral and cellular immune responses. In this study, the sequence of the virus was obtained from NCBI database and analyzed with in silico tools such as NetMHCpan, IEDB, BepiPred, NetCTL, Tap transport/proteasomal cleavage, Pa3P, GalexyPepDock, I-TASSER, Ellipro and ClusPro. To identify the most immunodominant regions, after analysis of population coverage and epitope conservancy, we proposed three different constructs based on linear B-cell, CTL and HTL epitopes. The 3D structure of constructs was assessed to find discontinuous B-cell epitopes. Among CTL predicted epitopes, S257-265, S603-611 and S360-368, and among HTL predicted epitopes, N167-181, S313-330 and S1110-1126 had better MHC binding rank. We found one putative CTL epitope, S360-368 related to receptor-binding domain (RBD) region for S protein. The predicted epitopes were non-allergen and showed a high quality of proteasomal cleavage and Tap transport efficiency and 100% conservancy within four different clades of SARS-CoV-2. For CTL and HTL epitopes, the highest population coverage of the world's population was calculated for S27-37 with 86.27% and for S196-231, S303-323, S313-330, S1009-1030 and N328-349 with 90.33%, respectively. We identified overall 10 discontinuous B-cell epitopes for three multiepitope constructs. All three constructs showed strong interactions with TLRs 2, 3 and 4 supporting the hypothesis of SARS-CoV-2 susceptibility to TLRs 2, 3 and 4 like other Coronaviridae families. These data demonstrated that the novel designed multiepitope constructs can contribute to develop SARS-CoV-2 peptide vaccine candidates. The in vivo studies are underway using several vaccination strategies.

Designing a multi-epitope peptide based vaccine against SARS-CoV-2.

COVID-19 pandemic has resulted in 16,114,449 cases with 646,641 deaths from the 217 countries, or territories as on July 27th 2020. Due to multifaceted issues and challenges in the implementation of the safety and preventive measures, inconsistent coordination between societies-governments and most importantly lack of specific vaccine to SARS-CoV-2, the spread of the virus that initially emerged at Wuhan is still uprising after taking a heavy toll on human life. In the present study, we mapped immunogenic epitopes present on the four structural proteins of SARS-CoV-2 and we designed a multi-epitope peptide based vaccine that, demonstrated a high immunogenic response with a vast application on world's human population. On codon optimization and in-silico cloning, we found that candidate vaccine showed high expression in E. coli and immune simulation resulted in inducing a high level of both B-cell and T-cell mediated immunity. The results predicted that exposure of vaccine by administrating three injections significantly subsidized the antigen growth in the system. The proposed candidate vaccine found promising by yielding desired results and hence, should be validated by practical experimentations for its functioning and efficacy to neutralize SARS-CoV-2.

3CL hydrolase-based multiepitope peptide vaccine against SARS-CoV-2 using immunoinformatics.

The present study provides the first multiepitope vaccine construct using the 3CL hydrolase protein of SARS-CoV-2. The coronavirus 3CL hydrolase (Mpro) enzyme is essential for proteolytic maturation of the virus. This study was based on immunoinformatics and structural vaccinology strategies. The design of the multiepitope vaccine was built using helper T-cell and cytotoxic T-cell epitopes from the 3CL hydrolase protein along with an adjuvant to enhance immune response; these are joined to each other by short peptide linkers. The vaccine also carries potential B-cell linear epitope regions, B-cell discontinuous epitopes, and interferon-γ-inducing epitopes. Epitopes of the constructed multiepitope vaccine were found to be antigenic, nonallergic, nontoxic, and covering large human populations worldwide. The vaccine construct was modeled, validated, and refined by different programs to achieve a high-quality three-dimensional structure. The resulting high-quality model was applied for conformational B-cell epitope selection and docking analyses with toll-like receptor-3 for understanding the capability of the vaccine to elicit an immune response. In silico cloning and codon adaptation were also performed with the pET-19b plasmid vector. The designed multiepitope peptide vaccine may prompt the development of a vaccine to control SARS-CoV-2 infection.

Sequence-based prediction of SARS-CoV-2 vaccine targets using a mass spectrometry-based bioinformatics predictor identifies immunogenic T cell epitopes.

BACKGROUND: The ongoing COVID-19 pandemic has created an urgency to identify novel vaccine targets for protective immunity against SARS-CoV-2. Early reports identify protective roles for both humoral and cell-mediated immunity for SARS-CoV-2. METHODS: We leveraged our bioinformatics binding prediction tools for human leukocyte antigen (HLA)-I and HLA-II alleles that were developed using mass spectrometry-based profiling of individual HLA-I and HLA-II alleles to predict peptide binding to diverse allele sets. We applied these binding predictors to viral genomes from the Coronaviridae family and specifically focused on T cell epitopes from SARS-CoV-2 proteins. We assayed a subset of these epitopes in a T cell induction assay for their ability to elicit CD8+ T cell responses. RESULTS: We first validated HLA-I and HLA-II predictions on Coronaviridae family epitopes deposited in the Virus Pathogen Database and Analysis Resource (ViPR) database. We then utilized our HLA-I and HLA-II predictors to identify 11,897 HLA-I and 8046 HLA-II candidate peptides which were highly ranked for binding across 13 open reading frames (ORFs) of SARS-CoV-2. These peptides are predicted to provide over 99% allele coverage for the US, European, and Asian populations. From our SARS-CoV-2-predicted peptide-HLA-I allele pairs, 374 pairs identically matched what was previously reported in the ViPR database, originating from other coronaviruses with identical sequences. Of these pairs, 333 (89%) had a positive HLA binding assay result, reinforcing the validity of our predictions. We then demonstrated that a subset of these highly predicted epitopes were immunogenic based on their recognition by specific CD8+ T cells in healthy human donor peripheral blood mononuclear cells (PBMCs). Finally, we characterized the expression of SARS-CoV-2 proteins in virally infected cells to prioritize those which could be potential targets for T cell immunity. CONCLUSIONS: Using our bioinformatics platform, we identify multiple putative epitopes that are potential targets for CD4+ and CD8+ T cells, whose HLA binding properties cover nearly the entire population. We also confirm that our binding predictors can predict epitopes eliciting CD8+ T cell responses from multiple SARS-CoV-2 proteins. Protein expression and population HLA allele coverage, combined with the ability to identify T cell epitopes, should be considered in SARS-CoV-2 vaccine design strategies and immune monitoring.

Designing Multi-Epitope Vaccines to Combat Emerging Coronavirus Disease 2019 (COVID-19) by Employing Immuno-Informatics Approach.

A recent pandemic caused by a single-stranded RNA virus, COVID-19, initially discovered in China, is now spreading globally. This poses a serious threat that needs to be addressed immediately. Genome analysis of SARS-CoV-2 has revealed its close relation to SARS-coronavirus along with few changes in its spike protein. The spike protein aids in receptor binding and viral entry within the host and therefore represents a potential target for vaccine and therapeutic development. In the current study, the spike protein of SARS-CoV-2 was explored for potential immunogenic epitopes to design multi-epitope vaccine constructs. The S1 and S2 domains of spike proteins were analyzed, and two vaccine constructs were prioritized with T-cell and B-cell epitopes. We adapted a comprehensive predictive framework to provide novel insights into immunogenic epitopes of spike proteins, which can further be evaluated as potential vaccine candidates against COVID-19. Prioritized epitopes were then modeled using linkers and adjuvants, and respective 3D models were constructed to evaluate their physiochemical properties and their possible interactions with ACE2, HLA Superfamily alleles, TLR2, and TLR4.

Understanding the B and T cell epitopes of spike protein of severe acute respiratory syndrome coronavirus-2: A computational way to predict the immunogens.

The 2019 novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) outbreak has caused a large number of deaths, with thousands of confirmed cases worldwide. The present study followed computational approaches to identify B- and T-cell epitopes for the spike (S) glycoprotein of SARS-CoV-2 by its interactions with the human leukocyte antigen alleles. We identified 24 peptide stretches on the SARS-CoV-2 S protein that are well conserved among the reported strains. The S protein structure further validated the presence of predicted peptides on the surface, of which 20 are surface exposed and predicted to have reasonable epitope binding efficiency. The work could be useful for understanding the immunodominant regions in the surface protein of SARS-CoV-2 and could potentially help in designing some peptide-based diagnostics. Also, identified T-cell epitopes might be considered for incorporation in vaccine designs.