Latest updates on SARS-CoV-2 genomic characterization, drug, and vaccine development; a comprehensive bioinformatics review

Efficacy of Inactivated Bivalent SARS-CoV-2 Vaccines Targeting Ancestral Strain (ERAGEM), Delta, and Omicron Variants

BACKGROUND/OBJECTIVES

The rapid evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to the emergence of variants with enhanced transmissibility and immune evasion, challenging existing vaccines. This study aimed to evaluate the immunogenicity and protective efficacy of inactivated bivalent vaccine formulations incorporating the ancestral SARS-CoV-2 strain (ERAGEM) with either Delta or Omicron (BA.5) variants.

METHODS

Bivalent vaccine formulations were prepared using beta-propiolactone-inactivated SARS-CoV-2 antigens and administered to K18-hACE2 transgenic mice. Following prime and booster immunizations, neutralizing antibody titers and viral loads were assessed through ELISA, microneutralization assays, and quantitative PCR. Mice were challenged with the respective variants, and the survival rates, temperature, and body weight changes were monitored for 21 days.

RESULTS

Both vaccine formulations elicited significant increases in neutralizing antibody titers post-booster immunization. The ERAGEM + Delta group demonstrated geometric mean titers (GMTs) of 6938.1 and 4935.0 for the ancestral and Delta variants, respectively, while the ERAGEM + Omicron (BA.5) group achieved GMTs of 16,280.7 and 24,215.9 for the ancestral and Omicron (BA.5) variants. Complete survival (100%) was observed in all the vaccinated groups post-challenge, with no detectable viral titers in the lungs and substantial reductions in the nasal turbinate viral loads compared to the unvaccinated controls.

CONCLUSIONS

The bivalent inactivated vaccines demonstrated strong immunogenicity and complete protection against severe disease in preclinical models. These findings indicate the potential of bivalent vaccine strategies in addressing antigenic diversity and preparing for future pandemics caused by rapidly evolving pathogens.

Bioinformatics and molecular biology tools for diagnosis, prevention, treatment and prognosis of COVID-19

Since December 2019, a new form of Severe Acute Respiratory Syndrome (SARS) has emerged worldwide, caused by SARS coronavirus 2 (SARS-CoV-2). This disease was called COVID-19 and was declared a pandemic by the World Health Organization in March 2020. Symptoms can vary from a common cold to severe pneumonia, hypoxemia, respiratory distress, and death. During this period of world stress, the medical and scientific community were able to acquire information and generate scientific data at unprecedented speed, to better understand the disease and facilitate vaccines and therapeutics development. Notably, bioinformatics tools were instrumental in decoding the viral genome and identifying critical targets for COVID-19 diagnosis and therapeutics. Through the integration of omics data, bioinformatics has also improved our understanding of disease pathogenesis and virus-host interactions, facilitating the development of targeted treatments and vaccines. Furthermore, molecular biology techniques have accelerated the design of sensitive diagnostic tests and the characterization of immune responses, paving the way for precision medicine approaches in treating COVID-19. Our analysis highlights the indispensable contributions of bioinformatics and molecular biology to the global effort against COVID-19. In this review, we aim to revise the COVID-19 features, diagnostic, prevention, treatment options, and how molecular biology, modern bioinformatic tools, and collaborations have helped combat this pandemic. An integrative literature review was performed, searching articles on several sites, including PUBMED and Google Scholar indexed in referenced databases, prioritizing articles from the last 3 years. The lessons learned from this COVID-19 pandemic will place the world in a much better position to respond to future pandemics.

State of the art in epitope mapping and opportunities in COVID-19

The understanding of any disease calls for studying specific biological structures called epitopes. One important tool recently drawing attention and proving efficiency in both diagnosis and vaccine development is epitope mapping. Several techniques have been developed with the urge to provide precise epitope mapping for use in designing sensitive diagnostic tools and developing rpitope-based vaccines (EBVs) as well as therapeutics. In this review, we will discuss the state of the art in epitope mapping with a special emphasis on accomplishments and opportunities in combating COVID-19. These comprise SARS-CoV-2 variant analysis versus the currently available immune-based diagnostic tools and vaccines, immunological profile-based patient stratification, and finally, exploring novel epitope targets for potential prophylactic, therapeutic or diagnostic agents for COVID-19.

Bioinformatics analysis of the potential regulatory mechanisms of renal fibrosis and the screening and identification of factors related to human renal fibrosis

Background

This paper aimed to identify the key genes and potential mechanisms of renal fibrosis, and provide methods of evaluation and new ideas for the early diagnosis and treatment of renal fibrosis.

Methods

The GSE102515 dataset was searched from the Gene Expression Omnibus (GEO) database was searched, the differential genes were screened out, and the down-regulated and up-regulated genes were identified. Enrichment analysis of differential genes in the development of renal fibrosis was carried out using the DAVID database, differential genes were analyzed using the STRING database, and Cytoscape software was used for visual processing.

Results

Eighteen up-regulated genes and ten down-regulated genes were screened. Differential genes are mainly involved in the integrin-mediated signaling pathway and mitotic sister chromatid binding, etc. We found that the molecular functions (MFs) of the differential genes are phospholipid binding and regulatory region DNA binding, etc. Moreover, the cellular components (CCs) of the differential genes are mainly related to low-density lipoprotein (LDL) particles and nuclei. Screening revealed that ADM, ARRB1, AVPR2, CCR1, MTNR1A, PTH, and S1PR2 were core genes in the interaction network of renal fibrosis risk-related proteins.

Conclusions

In this study, the differential genes in the occurrence of renal fibrosis were screened out via dataset analysis. It was found that ADM, ARRB1, AVPR2, CCR1, MTNR1A, PTH, and S1PR2 may be important participants in the development of renal fibrosis, which provides analytical support for the identification of valuable markers of renal fibrosis.

A mathematical model for human-to-human transmission of COVID-19: a case study for Turkey's data

In this study, a mathematical model for simulating the human-to-human transmission of the novel coronavirus disease (COVID-19) is presented for Turkey's data. For this purpose, the total population is classified into eight epidemiological compartments, including the super-spreaders. The local stability and sensitivity analysis in terms of the model parameters are discussed, and the basic reproduction number, R₀, is derived. The system of nonlinear ordinary differential equations is solved by using the Galerkin finite element method in the FEniCS environment. Furthermore, to guide the interested reader in reproducing the results and/or performing their own simulations, a sample solver is provided. Numerical simulations show that the proposed model is quite convenient for Turkey's data when used with appropriate parameters.