Prediction of Conserved HLA Class I and Class II Epitopes from SARS-CoV-2 Licensed Vaccines Supports T-Cell Cross-Protection against SARS-CoV-1

Conservation of HLA Spike Protein Epitopes Supports T Cell Cross-Protection in SARS-CoV-2 Vaccinated Individuals against the Potentially Zoonotic Coronavirus Khosta-2

Heterologous vaccines, which induce immunity against several related pathogens, can be a very useful and rapid way to deal with new pandemics. In this study, the potential impact of licensed COVID-19 vaccines on cytotoxic and helper cell immune responses against Khosta-2, a novel sarbecovirus that productively infects human cells, was analyzed for the 567 and 41 most common HLA class I and II alleles, respectively. Computational predictions indicated that most of these 608 alleles, covering more than 90% of the human population, contain sufficient fully conserved T-cell epitopes between the Khosta-2 and SARS-CoV-2 spike-in proteins. Ninety percent of these fully conserved peptides for class I and 93% for class II HLA molecules were verified as epitopes recognized by CD8+ or CD4+ T lymphocytes, respectively. These results show a very high correlation between bioinformatic prediction and experimental assays, which strongly validates this study. This immunoinformatics analysis allowed a broader assessment of the alleles that recognize these peptides, a global approach at the population level that is not possible with experimental assays. In summary, these findings suggest that both cytotoxic and helper cell immune protection elicited by currently licensed COVID-19 vaccines should be effective against Khosta-2 virus infection. Finally, by being rapidly adaptable to future coronavirus pandemics, this study has potential public health implications.

Could SARS-CoV-1 Vaccines in the Pipeline Have Contributed to Fighting the COVID-19 Pandemic? Lessons for the Next Coronavirus Plague

SARS-CoV-2 caused the devastating COVID-19 pandemic, which, to date, has resulted in more than 800 million confirmed cases and 7 million deaths worldwide. The rapid development and distribution (at least in high-income countries) of various vaccines prevented these overwhelming numbers of infections and deaths from being much higher. But would it have been possible to develop a prophylaxis against this pandemic more quickly? Since SARS-CoV-2 belongs to the subgenus sarbecovirus, with its highly homologous SARS-CoV-1, we propose here that while SARS-CoV-2-specific vaccines are being developed, phase II clinical trials of specific SARS-CoV-1 vaccines, which have been in the pipeline since the early 20th century, could have been conducted to test a highly probable cross-protection between SARS-CoV-1 and SARS-CoV-2.

A Synthetic SARS-CoV-2-Derived T-Cell and B-Cell Peptide Cocktail Elicits Full Protection against Lethal Omicron BA.1 Infection in H11-K18-hACE2 Mice

Emerging variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been developing the capacity for immune evasion and resistance to existing vaccines and drugs. To address this, development of vaccines against coronavirus disease 2019 (COVID-19) has focused on universality, strong T cell immunity, and rapid production. Synthetic peptide vaccines, which are inexpensive and quick to produce, show low toxicity, and can be selected from the conserved SARS-CoV-2 proteome, are promising candidates. In this study, we evaluated the effectiveness of a synthetic peptide cocktail containing three murine CD4+ T-cell epitopes from the SARS-CoV-2 nonspike proteome and one B-cell epitope from the Omicron BA.1 receptor-binding domain (RBD), along with aluminum phosphate (Al) adjuvant and 5' cytosine-phosphate-guanine 3' oligodeoxynucleotide (CpG-ODN) adjuvant in mice. The peptide cocktail induced good Th1-biased T-cell responses and effective neutralizing-antibody titers against the Omicron BA.1 variant. Additionally, H11-K18-hACE2 transgenic mice were fully protected against lethal challenge with the BA.1 strain, with a 100% survival rate and reduced pulmonary viral load and pathological lesions. Subcutaneous administration was found to be the superior route for synthetic peptide vaccine delivery. Our findings demonstrate the effectiveness of the peptide cocktail in mice, suggesting the feasibility of synthetic peptide vaccines for humans. IMPORTANCE Current vaccines based on production of neutralizing antibodies fail to prevent the infection and transmission of SARS-CoV-2 Omicron and its subvariants. Understanding the critical factors and avoiding the disadvantages of vaccine strategies are essential for developing a safe and effective COVID-19 vaccine, which would include a more effective and durable cellular response, minimal effects of viral mutations, rapid production against emerging variants, and good safety. Peptide-based vaccines are an excellent alternative because they are inexpensive, quick to produce, and very safe. In addition, human leukocyte antigen T-cell epitopes could be targeted at robust T-cell immunity and selected in the conserved region of the SARS-CoV-2 variants. Our study showed that a synthetic SARS-CoV-2-derived peptide cocktail induced full protection against lethal infection with Omicron BA.1 in H11-K18-hACE2 mice for the first time. This could have implications for the development of effective COVID-19 peptide vaccines for humans.

ELUCNN for explainable COVID-19 diagnosis

COVID-19 is a positive-sense single-stranded RNA virus caused by a strain of coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Several noteworthy variants of SARS-CoV-2 were declared by WHO as Alpha, Beta, Gamma, Delta, and Omicron. Till 13/Dec/2022, it has caused 6.65 million death tolls, and over 649 million confirmed positive cases. Based on the convolutional neural network (CNN), this study first proposes a ten-layer CNN as the backbone model. Then, the exponential linear unit (ELU) is introduced to replace ReLU, and the traditional convolutional block is now transformed into conv-ELU. Finally, an ELU-based CNN (ELUCNN) model is proposed for COVID-19 diagnosis. Besides, the MDA strategy is used to enhance the size of the training set. We develop a mobile app integrating ELUCNN, and this web app is run on a client-server modeled structure. Ten runs of the tenfold cross-validation experiment show our model yields a sensitivity of 94.41 ± 0.98 , a specificity of 94.84 ± 1.21 , an accuracy of 94.62 ± 0.96 , and an F1 score of 94.61 ± 0.95 . The ELUCNN model and mobile app are effective in COVID-19 diagnosis and give better results than 14 state-of-the-art COVID-19 diagnosis models concerning accuracy.