Association of HLA Class I Genotype with Mortality in Patients with Diabetes Mellitus and COVID-19.

Numerous studies showed that diabetes mellitus (DM) increases the risk of death from COVID-19 by five times. It is generally accepted that the high lethality of COVID-19 against the background of DM is due to the main complications of this disease: micro- and macroangiopathies, as well as heart and kidney failure. In addition, it was shown that acute respiratory viral infection increases the production of interferon gamma, increases muscle resistance to insulin, and modulates the activity of effector CD8+ T cells. The ability of CD8+ T cells to recognize SARS-CoV-2-infected cells depends not only on humoral factors but also on individual genetic characteristics, including the individual set of major histocompatibility complex class I (MHC-I) molecules. In this study, the relationship of the MHC-I genotype of patients with DM aged less than 60 years with the outcome of COVID-19 was studied using a sample of 222 patients. It was shown that lethal outcomes of COVID-19 in patients with DM are associated with the low affinity of the interaction of an individual set of MHC-I molecules with SARS-CoV-2 peptides.

Inhibition of major histocompatibility complex-I antigen presentation by sarbecovirus ORF7a proteins.

Viruses employ a variety of strategies to escape or counteract immune responses, including depletion of cell surface major histocompatibility complex class I (MHC-I), that would ordinarily present viral peptides to CD8+ cytotoxic T cells. As part of a screen to elucidate biological activities associated with individual severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) viral proteins, we found that ORF7a reduced cell surface MHC-I levels by approximately fivefold. Nevertheless, in cells infected with SARS-CoV-2, surface MHC-I levels were reduced even in the absence of ORF7a, suggesting additional mechanisms of MHC-I down-regulation. ORF7a proteins from a sample of sarbecoviruses varied in their ability to induce MHC-I down-regulation and, unlike SARS-CoV-2, the ORF7a protein from SARS-CoV lacked MHC-I downregulating activity. A single amino acid at position 59 (T/F) that is variable among sarbecovirus ORF7a proteins governed the difference in MHC-I downregulating activity. SARS-CoV-2 ORF7a physically associated with the MHC-I heavy chain and inhibited the presentation of expressed antigen to CD8+ T cells. Specifically, ORF7a prevented the assembly of the MHC-I peptide loading complex and caused retention of MHC-I in the endoplasmic reticulum. The differential ability of ORF7a proteins to function in this way might affect sarbecovirus dissemination and persistence in human populations, particularly those with infection- or vaccine-elicited immunity.

Relationship of Covid-19 Severity with SARS-CoV-2 NS8 Protein Mutations Depending on Virus Strain.

In mid-2021, the Delta strain of SARS-CoV-2 caused the third wave of the COVID-19 pandemic. Huge efforts have been devoted to studying the effect of its mutations on the effectiveness of neutralizing antibodies. Much less attention was paid to the individual features of the presentation of its peptides by molecules of the major histocompatibility complex class I (MCHC-I). In this study, the correlation of the HLA-I genotype of patients under the age of 60 years with the severity of COVID-19 caused by the two most common variants of the SARS-CoV-2 Delta strain in the summer of 2021: AY.122 and B.1.617.2 was studied. Analysis of the severity of the course of COVID-19 revealed a more severe course of the disease caused by the AY.122 variant. Comparison of the mutation profile of the two most common variants of the Delta strain showed that that the G8R mutation in the NS8 protein makes the greatest contribution to the ability of MHC-I to present viral peptides. Given that the NS8 protein is able to suppress the maturation of MHC-I molecules, the appearance of a mutation in one of its immunogenic epitopes could make a significant contribution to the prevalence of the AY.122 variant in the Russian population.

HLA-A*01:01 allele diminishing in COVID-19 patients population associated with non-structural epitope abundance in CD8+ T-cell repertoire.

In mid-2021, the SARS-CoV-2 Delta variant caused the third wave of the COVID-19 pandemic in several countries worldwide. The pivotal studies were aimed at studying changes in the efficiency of neutralizing antibodies to the spike protein. However, much less attention was paid to the T-cell response and the presentation of virus peptides by MHC-I molecules. In this study, we compared the features of the HLA-I genotype in symptomatic patients with COVID-19 in the first and third waves of the pandemic. As a result, we could identify the diminishing of carriers of the HLA-A*01:01 allele in the third wave and demonstrate the unique properties of this allele. Thus, HLA-A*01:01-binding immunoprevalent epitopes are mostly derived from ORF1ab. A set of epitopes from ORF1ab was tested, and their high immunogenicity was confirmed. Moreover, analysis of the results of single-cell phenotyping of T-cells in recovered patients showed that the predominant phenotype in HLA-A*01:01 carriers is central memory T-cells. The predominance of T-lymphocytes of this phenotype may contribute to forming long-term T-cell immunity in carriers of this allele. Our results can be the basis for highly effective vaccines based on ORF1ab peptides.

Engineering of a Multi-Epitope Subunit Vaccine Against SASRS-CoV-2 Through the Viroinformatic Approach

The COVID-19 outbreak has infected millions of people worldwide, but no vaccine has been discovered to combat it efficiently. This research aims to design a multi-epitope vaccine using highly efficient B- and T-cell epitopes from the SARS-CoV-2 Surabaya isolate through a viroinformatic approach. First, the putative epitopes were linked together to develop tertiary structures and then docked with toll-like receptor 4 (TLR-4) that demonstrated a robust interaction with a low eigenvalue of 4.816138 e¡06. Furthermore, the structure's high immunogenic response was observed and successfully cloned into the expression vector pET28a (þ). This implies that the designed vaccine can prove effective in combating SARS-CoV-2. © 2022 University of Kerbala.

Identification of a promiscuous conserved CTL epitope within the SARS-CoV-2 spike protein.

ABSTRACTThe COVID-19 disease caused by infection with SARS-CoV-2 and its variants is devastating to the global public health and economy. To date, over a hundred COVID-19 vaccines are known to be under development, and the few that have been approved to fight the disease are using the spike protein as the primary target antigen. Although virus-neutralizing epitopes are mainly located within the RBD of the spike protein, the presence of T cell epitopes, particularly the CTL epitopes that are likely to be needed for killing infected cells, has received comparatively little attention. This study predicted several potential T cell epitopes with web-based analytic tools and narrowed them down from several potential MHC-I and MHC-II epitopes by ELIspot and cytolytic assays to a conserved MHC-I epitope. The epitope is highly conserved in current viral variants and compatible with a presentation by most HLA alleles worldwide. In conclusion, we identified a CTL epitope suitable for evaluating the CD8+ T cell-mediated cellular response and potentially for addition into future COVID-19 vaccine candidates to maximize CTL responses against SARS-CoV-2.

Structure-Based Modeling of SARS-CoV-2 Peptide/HLA-A02 Antigens.

SARS-CoV-2-specific CD4 and CD8 T cells have been shown to be present in individuals with acute, mild, and asymptomatic Coronavirus disease (COVID-19). Toward the development of diagnostic and therapeutic tools to fight COVID-19, it is important to predict and characterize T cell epitopes expressed by SARS-CoV-2. Here, we use RosettaMHC, a comparative modeling approach which leverages existing structures of peptide/MHC complexes available in the Protein Data Bank, to derive accurate 3D models for putative SARS-CoV-2 CD8 epitopes. We outline an application of our method to model 8-10 residue epitopic peptides predicted to bind to the common allele HLA-A*02:01, and we make our models publicly available through an online database (https://rosettamhc.chemistry.ucsc.edu). We further compare electrostatic surfaces with models of homologous peptide/HLA-A*02:01 complexes from human common cold coronavirus strains to identify epitopes which may be recognized by a shared pool of cross-reactive TCRs. As more detailed studies on antigen-specific T cell recognition become available, RosettaMHC models can be used to understand the link between peptide/HLA complex structure and surface chemistry with immunogenicity, in the context of SARS-CoV-2 infection.

Towards Determining the Epitopes of the Structural Proteins of SARS-CoV-2.

COVID-19 caused by SARS-CoV-2, an RNA coronavirus has impacted the health and economy of all the countries. The virus has wide host adaptability and causes severe diseases in humans and animals. The major structural proteins of SARS-CoV-2 include spike (S), envelop (E), membrane (M), and nucleocapsid (N). The current vaccines are based on the S protein. The emergence of variants of SARS-CoV-2 has renewed interest in the use of additional structural proteins for the development of diagnostics and vaccines. Knowledge of B cell epitopes and MHC-I binding regions of the structural proteins of SARS-CoV-2 is essential in the development of effective diagnostics and therapies. This chapter provides information on the epitopes of the structural proteins of SARS-CoV-2.

Population-Predicted MHC Class II Epitope Presentation of SARS-CoV-2 Structural Proteins Correlates to the Case Fatality Rates of COVID-19 in Different Countries.

We observed substantial differences in predicted Major Histocompatibility Complex II (MHCII) epitope presentation of SARS-CoV-2 proteins for different populations but only minor differences in predicted MHCI epitope presentation. A comparison of this predicted epitope MHC-coverage revealed for the early phase of infection spread (till day 15 after reaching 128 observed infection cases) highly significant negative correlations with the case fatality rate. Specifically, this was observed in different populations for MHC class II presentation of the viral spike protein (p-value: 0.0733 for linear regression), the envelope protein (p-value: 0.023), and the membrane protein (p-value: 0.00053), indicating that the high case fatality rates of COVID-19 observed in some countries seem to be related with poor MHC class II presentation and hence weak adaptive immune response against these viral envelope proteins. Our results highlight the general importance of the SARS-CoV-2 structural proteins in immunological control in early infection spread looking at a global census in various countries and taking case fatality rate into account. Other factors such as health system and control measures become more important after the early spread. Our study should encourage further studies on MHCII alleles as potential risk factors in COVID-19 including assessment of local populations and specific allele distributions.

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.

Prediction of putative epitope-based vaccine against all corona virus strains for the Chinese population: Approach toward development of vaccine.

Currently, the whole world is facing the coronavirus disease-19 pandemic. As of now, approximately 0.15 million people around the globe are infected with the novel coronavirus. In the last decade, two strains of the coronavirus family, severe acute respiratory syndrome-related coronavirus and Middle East respiratory syndrome coronavirus, also resulted in epidemics in south Asian and the Middle Eastern countries with high mortality rate. This scenario demands the development of a putative vaccine which may provide immunity against all current and new evolving coronavirus strains. In this study, we designed an epitope-based vaccine using an immunoinformatic approach. This vaccine may protect against all coronavirus strains. The vaccine is developed by considering the geographical distribution of coronavirus strains and host genetics (Chinese population). Nine experimentally validated epitopes sequences from coronavirus strains were used to derive the variants considering the conservancy in all strains. Further, the binding affinities of all derived variants were checked with most abundant human leukocyte antigen alleles in the Chinese population. Three major histocompatibility complex (MHC) Class I epitopes from spike glycoprotein and nucleoprotein showed sufficient binding while one MHC Class II epitope from spike glycoprotein was found to be an effective binder. A cocktail of these epitopes gave more than 95% population coverage in the Chinese population. Moreover, molecular dynamics simulation supported the aforementioned predictions. Further, in vivo studies are needed to confirm the immunogenic potential of these vaccines.