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

Development of mRNA nano-vaccines for COVID-19 prevention and its biochemical interactions with various disease conditions and age groups

This review has focused on the development of mRNA nano-vaccine and the biochemical interactions of anti-COVID-19 mRNA vaccines with various disease conditions and age groups. It studied five major groups of individuals with different disease conditions and ages, including allergic background, infarction background, adolescent, and adult (youngsters), pregnant women, and elderly. All five groups had been reported to have background-related adverse effects. Allergic background individuals were observed to have higher chances of experiencing allergic reactions and even anaphylaxis. Individuals with an infarction background had a higher risk of vaccine-induced diseases, e.g. pneumonitis and interstitial lung diseases. Pregnant women were seen to suffer from obstetric and gynecological adverse effects after receiving vaccinations. However, interestingly, the elderly individuals (> 65 years old) had experienced milder and less frequent adverse effects compared to the adolescent (<19 and >9 years old) and young adulthood (19-39 years old), or middle adulthood (40-59 years old) age groups, while middle to late adolescent (14-17 years old) was the riskiest age group to vaccine-induced cardiovascular manifestations.

Influence of polymorphic variations of IFNL, HLA, and IL-6 genes in severe cases of COVID-19

The administration of vaccination doses to the global population has led to a decrease in the incidence of COVID-19. However, the clinical picture developed by infected individuals remains extremely concerning due to the great variability in the severity of cases even in vaccinated individuals. The clinical progression of the pathology is characterized by various influential factors such as sex, age group, comorbidities, and the genetics of the individual. The immune response to viral infections can be strongly influenced by the genetics of individuals; nucleotide variations called single-nucleotide polymorphisms (SNPs) in structures involved in the innate and adaptive immune response such as interferon (IFN)-λ, human leukocyte antigen (HLA), and interleukin (IL)-6 are frequently associated with pathological progression. In this study, we conducted a review of the main SNPs of these structures that are associated with severity in COVID-19. Searches were conducted on some platforms of the National Center for Biotechnology and Information (NCBI), and 102 studies were selected for full reading according to the inclusion criteria. IFNs showed a strong association with antiviral function, specifically, IFN-λ3 (IL-28B) demonstrated genetic variants commonly related to clinical progression in various pathologies. For COVID-19, rs12979860 and rs1298275 presented frequently described unfavorable genotypes for pathological conditions of hepatitis C and hepatocellular carcinoma. The high genetic variability of HLA was reported in the studies as a crucial factor relevant to the late immune response, mainly due to its ability to recognize antigens, with the HLA-B*46:01 SNP being associated with susceptibility to COVID-19. For IL-6, rs1554606 showed a strong relationship with the clinical progression of COVID-19. In addition, rs2069837 was identified with possible host protection relationships when linked to this infection.

COVID-19: Attacks Immune Cells and Interferences With Antigen Presentation Through MHC-Like Decoy System

The high mortality of coronavirus disease 2019 is related to poor antigen presentation and lymphopenia. Cytomegalovirus and the herpes family encode a series of major histocompatibility complex (MHC)-like molecules required for targeted immune responses to achieve immune escape. In this present study, domain search results showed that many proteins of the severe acute respiratory syndrome coronavirus 2 virus had MHC-like domains, which were similar to decoys for the human immune system. MHC-like structures could bind to MHC receptors of immune cells (such as CD4 + T-cell, CD8 + T-cell, and natural killer-cell), interfering with antigen presentation. Then the oxygen free radicals generated by E protein destroyed immune cells after MHC-like of S protein could bind to them. Mutations in the MHC-like region of the viral proteins such as S promoted weaker immune resistance and more robust transmission. S 127-194 were the primary reason for the robust transmission of delta variants. The S 144-162 regulated the formation of S trimer. The mutations of RdRP: G671S and N: D63G of delta variant caused high viral load. S 62-80 of alpha, beta, lambda variants were the important factor for fast-spreading. S 616-676 and 1014-1114 were causes of high mortality for gamma variants infections. These sites were in the MHC-like structure regions.

Systems biology models to identify the influence of SARS-CoV-2 infections to the progression of human autoimmune diseases

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been circulating since 2019, and its global dominance is rising. Evidences suggest the respiratory illness SARS-CoV-2 has a sensitive affect on causing organ damage and other complications to the patients with autoimmune diseases (AD), posing a significant risk factor. The genetic interrelationships and molecular appearances between SARS-CoV-2 and AD are yet unknown. We carried out the transcriptomic analytical framework to delve into the SARS-CoV-2 impacts on AD progression. We analyzed both gene expression microarray and RNA-Seq datasets from SARS-CoV-2 and AD affected tissues. With neighborhood-based benchmarks and multilevel network topology, we obtained dysfunctional signaling and ontological pathways, gene disease (diseasesome) association network and protein-protein interaction network (PPIN), uncovered essential shared infection recurrence connectivities with biological insights underlying between SARS-CoV-2 and AD. We found a total of 77, 21, 9, 54 common DEGs for SARS-CoV-2 and inflammatory bowel disorder (IBD), SARS-CoV-2 and rheumatoid arthritis (RA), SARS-CoV-2 and systemic lupus erythematosus (SLE) and SARS-CoV-2 and type 1 diabetes (T1D). The enclosure of these common DEGs with bimolecular networks revealed 10 hub proteins (FYN, VEGFA, CTNNB1, KDR, STAT1, B2M, CD3G, ITGAV, TGFB3). Drugs such as amlodipine besylate, vorinostat, methylprednisolone, and disulfiram have been identified as a common ground between SARS-CoV-2 and AD from drug repurposing investigation which will stimulate the optimal selection of medications in the battle against this ongoing pandemic triggered by COVID-19.

Allelic variation in class I HLA determines CD8+ T cell repertoire shape and cross-reactive memory responses to SARS-CoV-2

Effective presentation of antigens by HLA class I molecules to CD8⁺ T cells is required for viral elimination and generation of long-term immunological memory. In this study, we applied a single-cell, multi-omic technology to generate a unified ex vivo characterization of the CD8⁺ T cell response to SARS-CoV-2 across 4 major HLA class I alleles. We found that HLA genotype conditions key features of epitope specificity, TCR α/β sequence diversity, and the utilization of pre-existing SARS-CoV-2 reactive memory T cell pools. Single-cell transcriptomics revealed functionally diverse T cell phenotypes of SARS-CoV-2-reactive T cells, associated with both disease stage and epitope specificity. Our results show that HLA variations significantly influence the CD8⁺ T cell repertoire shape and utilization of immune recall upon SARS-CoV-2 infection.

GeneTrail: A Framework for the Analysis of High-Throughput Profiles

Experimental high-throughput techniques, like next-generation sequencing or microarrays, are nowadays routinely applied to create detailed molecular profiles of cells. In general, these platforms generate high-dimensional and noisy data sets. For their analysis, powerful bioinformatics tools are required to gain novel insights into the biological processes under investigation. Here, we present an overview of the GeneTrail tool suite that offers rich functionality for the analysis and visualization of (epi-)genomic, transcriptomic, miRNomic, and proteomic profiles. Our framework enables the analysis of standard bulk, time-series, and single-cell measurements and includes various state-of-the-art methods to identify potentially deregulated biological processes and to detect driving factors within those deregulated processes. We highlight the capabilities of our web service with an analysis of a single-cell COVID-19 data set that demonstrates its potential for uncovering complex molecular mechanisms. GeneTrail can be accessed freely and without login requirements at http://genetrail.bioinf.uni-sb.de.

Distribution of HLA-DRB1 alleles in BRICS countries with a high tuberculosis burden: a systematic review and meta-analysis

INTRODUCTION

Tuberculosis (TB) is the leading cause of death worldwide caused by a single infectious disease agent. Brazil, Russia, India, China, and South Africa (BRICS) account for more than half of the world's TB cases. Bacillus Calmette-Guérin (BCG) remains the only vaccine available despite its variable efficacy. Promising antigen-based vaccines have been proposed as prophylactic and/or immunotherapeutic approaches to boost BCG vaccination. Relevant antigens must interact with the range of human leukocyte antigen (HLA) molecules present in target populations; yet this information is currently not available.

METHODS

MEDLINE and EMBASE were systematically searched for articles published during 2013-2020 to measure the allelic frequencies of HLA-DRB1 in the BRICS.

RESULTS

In total, 67 articles involving 3,207,861 healthy individuals were included in the meta-analysis. HLA-DRB1 alleles *03, *04, *07, *11, *13, and *15 were consistently identified at high frequencies across the BRICS, with a combined estimated frequency varying from 52% to 80%. HLA-DRB1 alleles *01, *08, *09, *10, *12, and *14 were found to be relevant in only one or two BRICS populations.

CONCLUSIONS

By combining these alleles, it is possible to ensure at least 80% coverage throughout the BRICS populations.