SARS-CoV-2 spike protein displays sequence similarities with paramyxovirus surface proteins; a bioinformatics study

Evolutionary and Phylogenetic Dynamics of SARS-CoV-2 Variants: A Genetic Comparative Study of Taiyuan and Wuhan Cities of China

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a positive-sense, single-stranded RNA genome-containing virus which has infected millions of people all over the world. The virus has been mutating rapidly enough, resulting in the emergence of new variants and sub-variants which have reportedly been spread from Wuhan city in China, the epicenter of the virus, to the rest of China and all over the world. The occurrence of mutations in the viral genome, especially in the viral spike protein region, has resulted in the evolution of multiple variants and sub-variants which gives the virus the benefit of host immune evasion and thus renders modern-day vaccines and therapeutics ineffective. Therefore, there is a continuous need to study the genetic characteristics and evolutionary dynamics of the SARS-CoV-2 variants. Hence, in this study, a total of 832 complete genomes of SARS-CoV-2 variants from the cities of Taiyuan and Wuhan in China was genetically characterized and their phylogenetic and evolutionary dynamics studied using phylogenetics, genetic similarity, and phylogenetic network analyses. This study shows that the four most prevalent lineages in Taiyuan and Wuhan are as follows: the Omicron lineages EG.5.1.1, followed by HK.3, FY.3, and XBB.1.16 (Pangolin classification), and clades 23F (EG.5.1), followed by 23H (HK.3), 22F (XBB), and 23D (XBB.1.9) (Nextclade classification), and lineage B followed by the Omicron FY.3, lineage A, and Omicron FL.2.3 (Pangolin classification), and the clades 19A, followed by 22F (XBB), 23F (EG.5.1), and 23H (HK.3) (Nextclade classification), respectively. Furthermore, our genetic similarity analysis show that the SARS-CoV-2 clade 19A-B.4 from Wuhan (name starting with 412981) has the least genetic similarity of about 95.5% in the spike region of the genome as compared to the query sequence of Omicron XBB.2.3.2 from Taiyuan (name starting with 18495234), followed by the Omicron FR.1.4 from Taiyuan (name starting with 18495199) with ~97.2% similarity and Omicron DY.3 (name starting with 17485740) with ~97.9% similarity. The rest of the variants showed ≥98% similarity with the query sequence of Omicron XBB.2.3.2 from Taiyuan (name starting with 18495234). In addition, our recombination analysis results show that the SARS-CoV-2 variants have three statistically significant recombinant events which could have possibly resulted in the emergence of Omicron XBB.1.16 (recombination event 3), FY.3 (recombination event 5), and FL.2.4 (recombination event 7), suggesting some very important information regarding viral evolution. Also, our phylogenetic tree and network analyses show that there are a total of 14 clusters and more than 10,000 mutations which may have probably resulted in the emergence of cluster-I, followed by 47 mutations resulting in the emergence of cluster-II and so on. The clustering of the viral variants of both cities reveals significant information regarding the phylodynamics of the virus among them. The results of our temporal phylogenetic analysis suggest that the variants of Taiyuan have likely emerged as independent variants separate from the variants of Wuhan. This study, to the best of our knowledge, is the first ever genetic comparative study between Taiyuan and Wuhan cities in China. This study will help us better understand the virus and cope with the emergence and spread of new variants at a local as well as an international level, and keep the public health authorities informed for them to make better decisions in designing new viral vaccines and therapeutics. It will also help the outbreak investigators to better examine any future outbreak.

The Influence of Cross-Reactive T Cells in COVID-19

Memory T cells form from the adaptive immune response to historic infections or vaccinations. Some memory T cells have the potential to recognise unrelated pathogens like severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and generate cross-reactive immune responses. Notably, such T cell cross-reactivity has been observed between SARS-CoV-2 and other human coronaviruses. T cell cross-reactivity has also been observed between SARS-CoV-2 variants from unrelated microbes and unrelated vaccinations against influenza A, tuberculosis and measles, mumps and rubella. Extensive research and debate is underway to understand the mechanism and role of T cell cross-reactivity and how it relates to Coronavirus disease 2019 (COVID-19) outcomes. Here, we review the evidence for the ability of pre-existing memory T cells to cross-react with SARS-CoV-2. We discuss the latest findings on the impact of T cell cross-reactivity and the extent to which it can cross-protect from COVID-19.

Targets and cross-reactivity of human T cell recognition of common cold coronaviruses

The coronavirus (CoV) family includes several viruses infecting humans, highlighting the importance of exploring pan-CoV vaccine strategies to provide broad adaptive immune protection. We analyze T cell reactivity against representative Alpha (NL63) and Beta (OC43) common cold CoVs (CCCs) in pre-pandemic samples. S, N, M, and nsp3 antigens are immunodominant, as shown for severe acute respiratory syndrome 2 (SARS2), while nsp2 and nsp12 are Alpha or Beta specific. We further identify 78 OC43- and 87 NL63-specific epitopes, and, for a subset of those, we assess the T cell capability to cross-recognize sequences from representative viruses belonging to AlphaCoV, sarbecoCoV, and Beta-non-sarbecoCoV groups. We find T cell cross-reactivity within the Alpha and Beta groups, in 89% of the instances associated with sequence conservation >67%. However, despite conservation, limited cross-reactivity is observed for sarbecoCoV, indicating that previous CoV exposure is a contributing factor in determining cross-reactivity. Overall, these results provide critical insights in developing future pan-CoV vaccines.

The impact of pre-existing cross-reactive immunity on SARS-CoV-2 infection and vaccine responses

Pre-existing cross-reactive immune responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) proteins in infection-naive subjects have been described by several studies. In particular, regions of high homology between SARS-CoV-2 and common cold coronaviruses have been highlighted as a likely source of this cross-reactivity. However, the role of such cross-reactive responses in the outcome of SARS-CoV-2 infection and vaccination is currently unclear. Here, we review evidence regarding the impact of pre-existing humoral and T cell immune responses to outcomes of SARS-CoV-2 infection and vaccination. Furthermore, we discuss the importance of conserved coronavirus epitopes for the rational design of pan-coronavirus vaccines and consider cross-reactivity of immune responses to ancestral SARS-CoV-2 and SARS-CoV-2 variants, as well as their impact on COVID-19 vaccination.

Targets and cross-reactivity of human T cell recognition of Common Cold Coronaviruses

The Coronavirus (CoV) family includes a variety of viruses able to infect humans. Endemic CoVs that can cause common cold belong to the alphaCoV and betaCoV genera, with the betaCoV genus also containing subgenera with zoonotic and pandemic concern, including sarbecoCoV (SARS-CoV and SARS-CoV-2) and merbecoCoV (MERS-CoV). It is therefore warranted to explore pan-CoV vaccine concepts, to provide adaptive immune protection against new potential CoV outbreaks, particularly in the context of betaCoV sub lineages. To explore the feasibility of eliciting CD4 + T cell responses widely cross-recognizing different CoVs, we utilized samples collected pre-pandemic to systematically analyze T cell reactivity against representative alpha (NL63) and beta (OC43) common cold CoVs (CCC). Similar to previous findings on SARS-CoV-2, the S, N, M, and nsp3 antigens were immunodominant for both viruses while nsp2 and nsp12 were immunodominant for NL63 and OC43, respectively. We next performed a comprehensive T cell epitope screen, identifying 78 OC43 and 87 NL63-specific epitopes. For a selected subset of 18 epitopes, we experimentally assessed the T cell capability to cross-recognize sequences from representative viruses belonging to alphaCoV, sarbecoCoV, and beta-non-sarbecoCoV groups. We found general conservation within the alpha and beta groups, with cross-reactivity experimentally detected in 89% of the instances associated with sequence conservation of >67%. However, despite sequence conservation, limited cross-reactivity was observed in the case of sarbecoCoV (50% of instances), indicating that previous CoV exposure to viruses phylogenetically closer to this subgenera is a contributing factor in determining cross-reactivity. Overall, these results provided critical insights in the development of future pan-CoV vaccines.

Sequence Similarity Network Analysis Provides Insight into the Temporal and Geographical Distribution of Mutations in SARS-CoV-2 Spike Protein

Severe acute respiratory syndrome-related coronavirus (SARS-CoV-2), which still infects hundreds of thousands of people globally each day despite various countermeasures, has been mutating rapidly. Mutations in the spike (S) protein seem to play a vital role in viral stability, transmission, and adaptability. Therefore, to control the spread of the virus, it is important to gain insight into the evolution and transmission of the S protein. This study deals with the temporal and geographical distribution of mutant S proteins from sequences gathered across the US over a period of 19 months in 2020 and 2021. The S protein sequences are studied using two approaches: (i) multiple sequence alignment is used to identify prominent mutations and highly mutable regions and (ii) sequence similarity networks are subsequently employed to gain further insight and study mutation profiles of concerning variants across the defined time periods and states. Additionally, we tracked the variants using visualizations on geographical maps. The visualizations produced using the Directed Weighted All Nearest Neighbors (DiWANN) networks and maps provided insights into the transmission of the virus that reflect well the statistics reported for the time periods studied. We found that the networks created using DiWANN are superior to commonly used approximate distance networks created using BLAST bitscores. The study offers a richer computational approach to analyze the transmission profile of the prominent S protein mutations in SARS-CoV-2 and can be extended to other proteins and viruses.

Identification, propagation and molecular characterization of SARS-CoV-2 delta variant isolated from Egyptian COVID-19 patients

The recently emerging coronavirus, severe acute respiratory syndrome coronavirus 2, (SARS-CoV-2) is the causative agent of the Coronavirus disease 2019 (COVID-19) pandemic. Since its discovery in the city of Wahan, China, SARS-CoV-2 has spread rapidly to invade all countries. In addition to its rapid transmission rate, it is characterized by high genetic mutation rates. The aim of this study is to provide an effective method for the isolation and propagation of SARS-CoV-2 in cell lines without any induction of genetic variations. In this study, we isolated SARS-CoV-2 from oro-nasopharyngeal swabs collected from Egyptian patients who were clinically diagnosed with COVID-19. Molecular identification of SARS-CoV-2 was performed by Real-Time Quantitative Reverse Transcription PCR (RT-qPCR). The isolated virus was propagated on Vero E6 cells without applying serial viral passages to avoid any variation of the viral genome. The replication and propagation were confirmed by the results of both RT-qPCR and the cytopathic effect (CPE). Moreover, SARS-CoV-2 was completely inactivated chemically using beta-propiolactone (βPL). Whole genome sequencing (WGS) of the propagated virus was performed in order to investigate mutational patterns. The genome sequences recovered in 2020 (n = 18) were similar to the reference strain, Wuhan-Hu-1, and were clustered as clade 20A. However, the genomic sequences recovered in 2021 (n = 2) were clustered as clade 21J. These two sequences are considered the first Delta (B.1.617.2) variants detected in Egypt. This study provides a reference for researchers in Egypt to isolate and propagate SARS-CoV-2 easily and efficiently. Furthermore, the prevalence of the SARS-CoV-2 delta variant in Egypt necessitates continuous monitoring of the efficacy of the applied treatment protocol and the effectiveness of current vaccines against such variants of concern (VOC).