Functional studies of HLA and its role in SARS-CoV-2: Stimulating T cell response and vaccine development.

In the biological immune process, the major histocompatibility complex (MHC) plays an indispensable role in the expression of HLA molecules in the human body when viral infection activates the T-cell response to remove the virus. Since the first case of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in 2019, how to address and prevent SARS-CoV-2 has become a common problem facing all mankind. The T-cell immune response activated by MHC peptides is a way to construct a defense line and reduce the transmission and harm of the virus. Presentation of SARS-CoV-2 antigen is associated with different types of HLA phenotypes, and different HLA phenotypes induce different immune responses. The prediction of SARS-CoV-2 mutation information and the design of vaccines based on HLAs can effectively activate autoimmunity and cope with virus mutations, which can provide some references for the prevention and treatment of SARS-CoV-2.

CRESSP: a comprehensive pipeline for prediction of immunopathogenic SARS-CoV-2 epitopes using structural properties of proteins.

The development of autoimmune diseases following SARS-CoV-2 infection, including multisystem inflammatory syndrome, has been reported, and several mechanisms have been suggested, including molecular mimicry. We developed a scalable, comparative immunoinformatics pipeline called cross-reactive-epitope-search-using-structural-properties-of-proteins (CRESSP) to identify cross-reactive epitopes between a collection of SARS-CoV-2 proteomes and the human proteome using the structural properties of the proteins. Overall, by searching 4 911 245 proteins from 196 352 SARS-CoV-2 genomes, we identified 133 and 648 human proteins harboring potential cross-reactive B-cell and CD8+ T-cell epitopes, respectively. To demonstrate the robustness of our pipeline, we predicted the cross-reactive epitopes of coronavirus spike proteins, which were recognized by known cross-neutralizing antibodies. Using single-cell expression data, we identified PARP14 as a potential target of intermolecular epitope spreading between the virus and human proteins. Finally, we developed a web application (https://ahs2202.github.io/3M/) to interactively visualize our results. We also made our pipeline available as an open-source CRESSP package (https://pypi.org/project/cressp/), which can analyze any two proteomes of interest to identify potentially cross-reactive epitopes between the proteomes. Overall, our immunoinformatic resources provide a foundation for the investigation of molecular mimicry in the pathogenesis of autoimmune and chronic inflammatory diseases following COVID-19.

In Translation: FcRn across the Therapeutic Spectrum.

As an essential modulator of IgG disposition, the neonatal Fc receptor (FcRn) governs the pharmacokinetics and functions many therapeutic modalities. In this review, we thoroughly reexamine the hitherto elucidated biological and thermodynamic properties of FcRn to provide context for our assessment of more recent advances, which covers antigen-binding fragment (Fab) determinants of FcRn affinity, transgenic preclinical models, and FcRn targeting as an immune-complex (IC)-clearing strategy. We further comment on therapeutic antibodies authorized for treating SARS-CoV-2 (bamlanivimab, casirivimab, and imdevimab) and evaluate their potential to saturate FcRn-mediated recycling. Finally, we discuss modeling and simulation studies that probe the quantitative relationship between in vivo IgG persistence and in vitro FcRn binding, emphasizing the importance of endosomal transit parameters.

Can molecular mimicry explain the cytokine storm of SARS-CoV-2?: An in silico approach.

PARP14 and PARP9 play a key role in macrophage immune regulation. SARS-CoV-2 is an emerging viral disease that triggers hyper-inflammation known as a cytokine storm. In this study, using in silico tools, we hypothesize about the immunological phenomena of molecular mimicry between SARS-CoV-2 Nsp3 and the human PARP14 and PARP9. The results showed an epitope of SARS-CoV-2 Nsp3 protein that contains consensus sequences for both human PARP14 and PARP9 that are antigens for MHC Classes 1 and 2, which can potentially induce an immune response against human PARP14 and PARP9; while its depletion causes a hyper-inflammatory state in SARS-CoV-2 patients.

A novel and efficient approach to high-throughput production of HLA-E/peptide monomer for T-cell epitope screening.

Over the past two decades, there has been a great interest in the study of HLA-E-restricted αß T cells during bacterial and viral infections, including recently SARS-CoV-2 infection. Phenotyping of these specific HLA-E-restricted T cells requires new tools such as tetramers for rapid cell staining or sorting, as well as for the identification of new peptides capable to bind to the HLA-E pocket. To this aim, we have developed an optimal photosensitive peptide to generate stable HLA-E/pUV complexes allowing high-throughput production of new HLA-E/peptide complexes by peptide exchange. We characterized the UV exchange by ELISA and improved the peptide exchange readout using size exclusion chromatography. This novel approach for complex quantification is indeed very important to perform tetramerization of MHC/peptide complexes with the high quality required for detection of specific T cells. Our approach allows the rapid screening of peptides capable of binding to the non-classical human HLA-E allele, paving the way for the development of new therapeutic approaches based on the detection of HLA-E-restricted T cells.

Nonameric Peptide Orchestrates Signal Transduction in the Activating HLA-E/NKG2C/CD94 Immune Complex as Revealed by All-Atom Simulations.

The innate immune system's natural killer (NK) cells exert their cytolytic function against a variety of pathological challenges, including tumors and virally infected cells. Their activation depends on net signaling mediated via inhibitory and activating receptors that interact with specific ligands displayed on the surfaces of target cells. The CD94/NKG2C heterodimer is one of the NK activating receptors and performs its function by interacting with the trimeric ligand comprised of the HLA-E/ß2m/nonameric peptide complex. Here, simulations of the all-atom multi-microsecond molecular dynamics in five immune complexes provide atomistic insights into the receptor-ligand molecular recognition, as well as the molecular events that facilitate the NK cell activation. We identify NKG2C, the HLA-Eα2 domain, and the nonameric peptide as the key elements involved in the molecular machinery of signal transduction via an intertwined hydrogen bond network. Overall, the study addresses the complex intricacies that are necessary to understand the mechanisms of the innate immune system.

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.

Total predicted MHC-I epitope load is inversely associated with population mortality from SARS-CoV-2.

Polymorphisms in MHC-I protein sequences across human populations significantly affect viral peptide binding capacity, and thus alter T cell immunity to infection. In the present study, we assess the relationship between observed SARS-CoV-2 population mortality and the predicted viral binding capacities of 52 common MHC-I alleles. Potential SARS-CoV-2 MHC-I peptides are identified using a consensus MHC-I binding and presentation prediction algorithm called EnsembleMHC. Starting with nearly 3.5 million candidates, we resolve a few hundred highly probable MHC-I peptides. By weighing individual MHC allele-specific SARS-CoV-2 binding capacity with population frequency in 23 countries, we discover a strong inverse correlation between predicted population SARS-CoV-2 peptide binding capacity and mortality rate. Our computations reveal that peptides derived from the structural proteins of the virus produce a stronger association with observed mortality rate, highlighting the importance of S, N, M, and E proteins in driving productive immune responses.

Exploring the out of sight antigens of SARS-CoV-2 to design a candidate multi-epitope vaccine by utilizing immunoinformatics approaches.

SARS-CoV-2 causes a severe respiratory disease called COVID-19. Currently, global health is facing its devastating outbreak. However, there is no vaccine available against this virus up to now. In this study, a novel multi-epitope vaccine against SARS-CoV-2 was designed to provoke both innate and adaptive immune responses. The immunodominant regions of six non-structural proteins (nsp7, nsp8, nsp9, nsp10, nsp12 and nsp14) of SARS-CoV-2 were selected by multiple immunoinformatic tools to provoke T cell immune response. Also, immunodominant fragment of the functional region of SARS-CoV-2 spike (400-510 residues) protein was selected for inducing neutralizing antibodies production. The selected regions' sequences were connected to each other by furin-sensitive linker (RVRR). Moreover, the functional region of ß-defensin as a well-known agonist for the TLR-4/MD complex was added at the N-terminus of the vaccine using (EAAAK)3 linker. Also, a CD4 + T-helper epitope, PADRE, was used at the C-terminal of the vaccine by GPGPG and A(EAAAK)2A linkers to form the final vaccine construct. The physicochemical properties, allergenicity, antigenicity, functionality and population coverage of the final vaccine construct were analyzed. The final vaccine construct was an immunogenic, non-allergen and unfunctional protein which contained multiple CD8 + and CD4 + overlapping epitopes, IFN-γ inducing epitopes, linear and conformational B cell epitopes. It could form stable and significant interactions with TLR-4/MD according to molecular docking and dynamics simulations. Global population coverage of the vaccine for HLA-I and II were estimated 96.2% and 97.1%, respectively. At last, the final vaccine construct was reverse translated to design the DNA vaccine. Although the designed vaccine exhibited high efficacy in silico, further experimental validation is necessary.

Estimating the Binding of Sars-CoV-2 Peptides to HLA Class I in Human Subpopulations Using Artificial Neural Networks.

Epidemiological studies show that SARS-CoV-2 infection leads to severe symptoms only in a fraction of patients, but the determinants of individual susceptibility to the virus are still unknown. The major histocompatibility complex (MHC) class I exposes viral peptides in all nucleated cells and is involved in the susceptibility to many human diseases. Here, we use artificial neural networks to analyze the binding of SARS-CoV-2 peptides with polymorphic human MHC class I molecules. In this way, we identify two sets of haplotypes present in specific human populations: the first displays weak binding with SARS-CoV-2 peptides, while the second shows strong binding and T cell propensity. Our work offers a useful support to identify the individual susceptibility to COVID-19 and illustrates a mechanism underlying variations in the immune response to SARS-CoV-2. A record of this paper's transparent peer review process is included in the Supplemental Information.

Computationally Optimized SARS-CoV-2 MHC Class I and II Vaccine Formulations Predicted to Target Human Haplotype Distributions.

We present a combinatorial machine learning method to evaluate and optimize peptide vaccine formulations for SARS-CoV-2. Our approach optimizes the presentation likelihood of a diverse set of vaccine peptides conditioned on a target human-population HLA haplotype distribution and expected epitope drift. Our proposed SARS-CoV-2 MHC class I vaccine formulations provide 93.21% predicted population coverage with at least five vaccine peptide-HLA average hits per person (≥ 1 peptide: 99.91%) with all vaccine peptides perfectly conserved across 4,690 geographically sampled SARS-CoV-2 genomes. Our proposed MHC class II vaccine formulations provide 97.21% predicted coverage with at least five vaccine peptide-HLA average hits per person with all peptides having an observed mutation probability of ≤ 0.001. We provide an open-source implementation of our design methods (OptiVax), vaccine evaluation tool (EvalVax), as well as the data used in our design efforts here: https://github.com/gifford-lab/optivax.

Bioinformatic prediction of potential T cell epitopes for SARS-Cov-2.

To control and prevent the current COVID-19 pandemic, the development of novel vaccines is an emergent issue. In addition, we need to develop tools that can measure/monitor T-cell and B-cell responses to know how our immune system is responding to this deleterious virus. However, little information is currently available about the immune target epitopes of novel coronavirus (SARS-CoV-2) to induce host immune responses. Through a comprehensive bioinformatic screening of potential epitopes derived from the SARS-CoV-2 sequences for HLAs commonly present in the Japanese population, we identified 2013 and 1399 possible peptide epitopes that are likely to have the high affinity (<0.5%- and 2%-rank, respectively) to HLA class I and II molecules, respectively, that may induce CD8+ and CD4+ T-cell responses. These epitopes distributed across the structural (spike, envelope, membrane, and nucleocapsid proteins) and the nonstructural proteins (proteins corresponding to six open reading frames); however, we found several regions where high-affinity epitopes were significantly enriched. By comparing the sequences of these predicted T cell epitopes to the other coronaviruses, we identified 781 HLA-class I and 418 HLA-class II epitopes that have high homologies to SARS-CoV. To further select commonly-available epitopes that would be applicable to larger populations, we calculated population coverages based on the allele frequencies of HLA molecules, and found 2 HLA-class I epitopes covering 83.8% of the Japanese population. The findings in the current study provide us valuable information to design widely-available vaccine epitopes against SARS-CoV-2 and also provide the useful information for monitoring T-cell responses.

Development of epitope-based peptide vaccine against novel coronavirus 2019 (SARS-COV-2): Immunoinformatics approach.

Recently, a novel coronavirus (SARS-COV-2) emerged which is responsible for the recent outbreak in Wuhan, China. Genetically, it is closely related to SARS-CoV and MERS-CoV. The situation is getting worse and worse, therefore, there is an urgent need for designing a suitable peptide vaccine component against the SARS-COV-2. Here, we characterized spike glycoprotein to obtain immunogenic epitopes. Next, we chose 13 Major Histocompatibility Complex-(MHC) I and 3 MHC-II epitopes, having antigenic properties. These epitopes are usually linked to specific linkers to build vaccine components and molecularly dock on toll-like receptor-5 to get binding affinity. Therefore, to provide a fast immunogenic profile of these epitopes, we performed immunoinformatics analysis so that the rapid development of the vaccine might bring this disastrous situation to the end earlier.