A database resource and online analysis tools for coronaviruses on a historical and global scale

Applying the digital data and the bioinformatics tools in SARS-CoV-2 research

Bioinformatics has been playing a crucial role in the scientific progress to fight against the pandemic of the coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The advances in novel algorithms, mega data technology, artificial intelligence and deep learning assisted the development of novel bioinformatics tools to analyze daily increasing SARS-CoV-2 data in the past years. These tools were applied in genomic analyses, evolutionary tracking, epidemiological analyses, protein structure interpretation, studies in virus-host interaction and clinical performance. To promote the in-silico analysis in the future, we conducted a review which summarized the databases, web services and software applied in SARS-CoV-2 research. Those digital resources applied in SARS-CoV-2 research may also potentially contribute to the research in other coronavirus and non-coronavirus viruses.

The NSP4 T492I mutation increases SARS-CoV-2 infectivity by altering non-structural protein cleavage

The historically dominant SARS-CoV-2 Delta variant and the currently dominant Omicron variants carry a T492I substitution within the non-structural protein 4 (NSP4). Based on in silico analyses, we hypothesized that the T492I mutation increases viral transmissibility and adaptability, which we confirmed with competition experiments in hamster and human airway tissue culture models. Furthermore, we showed that the T492I mutation increases the replication capacity and infectiveness of the virus and improves its ability to evade host immune responses. Mechanistically, the T492I mutation increases the cleavage efficiency of the viral main protease NSP5 by enhancing enzyme-substrate binding, which increases production of nearly all non-structural proteins processed by NSP5. Importantly, the T492I mutation suppresses viral-RNA-associated chemokine production in monocytic macrophages, which may contribute to the attenuated pathogenicity of Omicron variants. Our results highlight the importance of NSP4 adaptation in the evolutionary dynamics of SARS-CoV-2.

COVID-19 Vaccines: Computational tools and Development

The 2019 coronavirus outbreak, also known as COVID-19, poses a serious threat to global health and has already had widespread, devastating effects around the world. Scientists have been working tirelessly to develop vaccines to stop the virus from spreading as much as possible, as its cure has not yet been found. As of December 2022, 651,918,402 cases and 6,656,601 deaths had been reported. Globally, over 13 billion doses of vaccine have been administered, representing 64.45% of the world's population that has received the vaccine. To expedite the vaccine development process, computational tools have been utilized. This paper aims to analyze some computational tools that aid vaccine development by presenting positive evidence for proving the efficacy of these vaccines to suppress the spread of the virus and for the use of computational tools in the development of vaccines for emerging diseases.

Conserved recombination patterns across coronavirus subgenera

Recombination contributes to the genetic diversity found in coronaviruses and is known to be a prominent mechanism whereby they evolve. It is apparent, both from controlled experiments and in genome sequences sampled from nature, that patterns of recombination in coronaviruses are non-random and that this is likely attributable to a combination of sequence features that favour the occurrence of recombination break points at specific genomic sites, and selection disfavouring the survival of recombinants within which favourable intra-genome interactions have been disrupted. Here we leverage available whole-genome sequence data for six coronavirus subgenera to identify specific patterns of recombination that are conserved between multiple subgenera and then identify the likely factors that underlie these conserved patterns. Specifically, we confirm the non-randomness of recombination break points across all six tested coronavirus subgenera, locate conserved recombination hot- and cold-spots, and determine that the locations of transcriptional regulatory sequences are likely major determinants of conserved recombination break-point hotspot locations. We find that while the locations of recombination break points are not uniformly associated with degrees of nucleotide sequence conservation, they display significant tendencies in multiple coronavirus subgenera to occur in low guanine-cytosine content genome regions, in non-coding regions, at the edges of genes, and at sites within the Spike gene that are predicted to be minimally disruptive of Spike protein folding. While it is apparent that sequence features such as transcriptional regulatory sequences are likely major determinants of where the template-switching events that yield recombination break points most commonly occur, it is evident that selection against misfolded recombinant proteins also strongly impacts observable recombination break-point distributions in coronavirus genomes sampled from nature.

Nucleocapsid mutations R203K/G204R increase the infectivity, fitness, and virulence of SARS-CoV-2

Previous work found that the co-occurring mutations R203K/G204R on the SARS-CoV-2 nucleocapsid (N) protein are increasing in frequency among emerging variants of concern or interest. Through a combination of in silico analyses, this study demonstrates that R203K/G204R are adaptive, while large-scale phylogenetic analyses indicate that R203K/G204R associate with the emergence of the high-transmissibility SARS-CoV-2 lineage B.1.1.7. Competition experiments suggest that the 203K/204R variants possess a replication advantage over the preceding R203/G204 variants, possibly related to ribonucleocapsid (RNP) assembly. Moreover, the 203K/204R virus shows increased infectivity in human lung cells and hamsters. Accordingly, we observe a positive association between increased COVID-19 severity and sample frequency of 203K/204R. Our work suggests that the 203K/204R mutations contribute to the increased transmission and virulence of select SARS-CoV-2 variants. In addition to mutations in the spike protein, mutations in the nucleocapsid protein are important for viral spreading during the pandemic.

Web resources facilitate drug discovery in treatment of COVID-19

The infectious disease Coronavirus 2019 (COVID-19) continues to cause a global pandemic and, thus, the need for effective therapeutics remains urgent. Global research targeting COVID-19 treatments has produced numerous therapy-related data and established data repositories. However, these data are disseminated throughout the literature and web resources, which could lead to a reduction in the levels of their use. In this review, we introduce resource repositories for the development of COVID-19 therapeutics, from the genome and proteome to antiviral drugs, vaccines, and monoclonal antibodies. We briefly describe the data and usage, and how they advance research for therapies. Finally, we discuss the opportunities and challenges to preventing the pandemic from developing further.

Next-Generation Bioinformatics Approaches and Resources for Coronavirus Vaccine Discovery and Development-A Perspective Review

COVID-19 is a contagious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). To fight this pandemic, which has caused a massive death toll around the globe, researchers are putting efforts into developing an effective vaccine against the pathogen. As genome sequencing projects for several coronavirus strains have been completed, a detailed investigation of the functions of the proteins and their 3D structures has gained increasing attention. These high throughput data are a valuable resource for accelerating the emerging field of immuno-informatics, which is primarily aimed toward the identification of potential antigenic epitopes in viral proteins that can be targeted for the development of a vaccine construct eliciting a high immune response. Bioinformatics platforms and various computational tools and databases are also essential for the identification of promising vaccine targets making the best use of genomic resources, for further experimental validation. The present review focuses on the various stages of the vaccine development process and the vaccines available for COVID-19. Additionally, recent advances in genomic platforms and publicly available bioinformatics resources in coronavirus vaccine discovery together with related immunoinformatics databases and advances in technology are discussed.

Integrative web-based analysis of omics data for study of drugs against SARS-CoV-2

Research on drugs against SARS-CoV-2 (cause of COVID-19) has been one of the major world concerns at present. There have been abundant research data and findings in this field. The interference of drugs on gene expression in cell lines, drug-target, protein-virus receptor networks, and immune cell infiltration of the host may provide useful information for anti-SARS-CoV-2 drug research. To simplify the complex bioinformatics analysis and facilitate the evaluation of the latest research data, we developed OmiczViz ( http://medcode.link/omicsviz ), a web tool that has integrated drug-cell line interference data, virus-host protein-protein interactions, and drug-target interactions. To demonstrate the usages of OmiczViz, we analyzed the gene expression data from cell lines treated with chloroquine and ruxolitinib, the drug-target protein networks of 48 anti-coronavirus drugs and drugs bound with ACE2, and the profiles of immune cell infiltration between different COVID-19 patient groups. Our research shows that chloroquine had a regulatory role of the immune response in renal cell line but not in lung cell line. The anti-coronavirus drug-target network analysis suggested that antihistamine of promethaziney and dietary supplement of Zinc might be beneficial when used jointly with antiviral drugs. The immune infiltration analysis indicated that both the COVID-19 patients admitted to the ICU and the elderly with infection showed immune exhaustion status, yet with different molecular mechanisms. The interactive graphic interface of OmiczViz also makes it easier to analyze newly discovered and user-uploaded data, leading to an in-depth understanding of existing findings and an expansion of existing knowledge of SARS-CoV-2. Collectively, OmicsViz is web program that promotes the research on medical agents against SARS-CoV-2 and supports the evaluation of the latest research findings.

Structural and Drug Screening Analysis of the Non-structural Proteins of Severe Acute Respiratory Syndrome Coronavirus 2 Virus Extracted From Indian Coronavirus Disease 2019 Patients

The novel coronavirus 2 (nCoV2) outbreaks took place in December 2019 in Wuhan City, Hubei Province, China. It continued to spread worldwide in an unprecedented manner, bringing the whole world to a lockdown and causing severe loss of life and economic stability. The coronavirus disease 2019 (COVID-19) pandemic has also affected India, infecting more than 10 million till 31st December 2020 and resulting in more than a hundred thousand deaths. In the absence of an effective vaccine, it is imperative to understand the phenotypic outcome of the genetic variants and subsequently the mode of action of its proteins with respect to human proteins and other bio-molecules. Availability of a large number of genomic and mutational data extracted from the nCoV2 virus infecting Indian patients in a public repository provided an opportunity to understand and analyze the specific variations of the virus in India and their impact in broader perspectives. Non-structural proteins (NSPs) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) virus play a major role in its survival as well as virulence power. Here, we provide a detailed overview of the SARS-CoV2 NSPs including primary and secondary structural information, mutational frequency of the Indian and Wuhan variants, phylogenetic profiles, three-dimensional (3D) structural perspectives using homology modeling and molecular dynamics analyses for wild-type and selected variants, host-interactome analysis and viral-host protein complexes, and in silico drug screening with known antivirals and other drugs against the SARS-CoV2 NSPs isolated from the variants found within Indian patients across various regions of the country. All this information is categorized in the form of a database named, Database of NSPs of India specific Novel Coronavirus (DbNSP InC), which is freely available at http://www.hpppi.iicb.res.in/covid19/index.php.

Rapid Spread of Mutant Alleles in Worldwide SARS-CoV-2 Strains Revealed by Genome-Wide Single Nucleotide Polymorphism and Variation Analysis

The novel coronavirus (SARS-CoV-2) has become a pandemic and is threatening human health globally. Here, we report nine newly evolved SARS-CoV-2 single nucleotide polymorphism (SNP) alleles those underwent a rapid increase (seven cases) or decrease (two cases) in their frequency for 30-80% in the initial four months, which are further confirmed by intrahost single nucleotide variation analysis using raw sequence data including 8,217 samples. The nine SNPs are mostly (8/9) located in the coding region and are mainly (6/9) nonsynonymous substitutions. The nine SNPs show a complete linkage in SNP pairs and belong to three different linkage groups, named LG_1 to LG_3. Analyses in population genetics show signatures of adaptive selection toward the mutants in LG_1, but no signal of selection for LG_2. Population genetic analysis results on LG_3 show geological differentiation. Analyses on geographic COVID-19 cases and published clinical data provide evidence that the mutants in LG_1 and LG_3 benefit virus replication and those in LG_1 have a positive correlation with the disease severity in COVID-19-infected patients. The mutants in LG_2 show a bias toward mildness of the disease based on available public clinical data. Our findings may be instructive for epidemiological surveys and disease control of COVID-19 in the future.

Genomic recombination events may reveal the evolution of coronavirus and the origin of SARS-CoV-2

To trace the evolution of coronaviruses and reveal the possible origin of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes the coronavirus disease 2019 (COVID-19), we collected and thoroughly analyzed 29,452 publicly available coronavirus genomes, including 26,312 genomes of SARS-CoV-2 strains. We observed coronavirus recombination events among different hosts including 3 independent recombination events with statistical significance between some isolates from humans, bats and pangolins. Consistent with previous records, we also detected putative recombination between strains similar or related to Bat-CoV-RaTG13 and Pangolin-CoV-2019. The putative recombination region is located inside the receptor-binding domain (RBD) of the spike glycoprotein (S protein), which may represent the origin of SARS-CoV-2. Population genetic analyses provide estimates suggesting that the putative introduced DNA within the RBD is undergoing directional evolution. This may result in the adaptation of the virus to hosts. Unsurprisingly, we found that the putative recombination region in S protein was highly diverse among strains from bats. Bats harbor numerous coronavirus subclades that frequently participate in recombination events with human coronavirus. Therefore, bats may provide a pool of genetic diversity for the origin of SARS-CoV-2.