SARS-CoV genome polymorphism: a bioinformatics study

Substitution spectra of SARS-CoV-2 genome from Pakistan reveals insights into the evolution of variants across the pandemic

Changing morbidity and mortality due to COVID-19 across the pandemic has been linked with factors such as the emergence of SARS-CoV-2 variants and vaccination. Mutations in the Spike glycoprotein enhanced viral transmission and virulence. We investigated whether SARS-CoV-2 mutation rates and entropy were associated COVID-19 in Pakistan, before and after the introduction of vaccinations. We analyzed 1,705 SARS-CoV-2 genomes using the Augur phylogenetic pipeline. Substitution rates and entropy across the genome, and in the Spike glycoprotein were compared between 2020, 2021 and 2022 (as periods A, B and C). Mortality was greatest in B whilst cases were highest during C. In period A, G clades were predominant, and substitution rate was 5.25 × 10-4 per site per year. In B, Delta variants dominated, and substitution rates increased to 9.74 × 10-4. In C, Omicron variants led to substitution rates of 5.02 × 10-4. Genome-wide entropy was the highest during B particularly, at Spike E484K and K417N. During C, genome-wide mutations increased whilst entropy was reduced. Enhanced SARS-CoV-2 genome substitution rates were associated with a period when more virulent SARS-CoV-2 variants were prevalent. Reduced substitution rates and stabilization of genome entropy was subsequently evident when vaccinations were introduced. Whole genome entropy analysis can help predict virus evolution to guide public health interventions.

Viral informatics: bioinformatics-based solution for managing viral infections

Several new viral infections have emerged in the human population and establishing as global pandemics. With advancements in translation research, the scientific community has developed potential therapeutics to eradicate or control certain viral infections, such as smallpox and polio, responsible for billions of disabilities and deaths in the past. Unfortunately, some viral infections, such as dengue virus (DENV) and human immunodeficiency virus-1 (HIV-1), are still prevailing due to a lack of specific therapeutics, while new pathogenic viral strains or variants are emerging because of high genetic recombination or cross-species transmission. Consequently, to combat the emerging viral infections, bioinformatics-based potential strategies have been developed for viral characterization and developing new effective therapeutics for their eradication or management. This review attempts to provide a single platform for the available wide range of bioinformatics-based approaches, including bioinformatics methods for the identification and management of emerging or evolved viral strains, genome analysis concerning the pathogenicity and epidemiological analysis, computational methods for designing the viral therapeutics, and consolidated information in the form of databases against the known pathogenic viruses. This enriched review of the generally applicable viral informatics approaches aims to provide an overview of available resources capable of carrying out the desired task and may be utilized to expand additional strategies to improve the quality of translation viral informatics research.

Evolutionary Dynamics of Indels in SARS-CoV-2 Spike Glycoprotein

SARS-CoV-2, responsible for the current COVID-19 pandemic that claimed over 5.0 million lives, belongs to a class of enveloped viruses that undergo quick evolutionary adjustments under selection pressure. Numerous variants have emerged in SARS-CoV-2, posing a serious challenge to the global vaccination effort and COVID-19 management. The evolutionary dynamics of this virus are only beginning to be explored. In this work, we have analysed 1.79 million spike glycoprotein sequences of SARS-CoV-2 and found that the virus is fine-tuning the spike with numerous amino acid insertions and deletions (indels). Indels seem to have a selective advantage as the proportions of sequences with indels steadily increased over time, currently at over 89%, with similar trends across countries/variants. There were as many as 420 unique indel positions and 447 unique combinations of indels. Despite their high frequency, indels resulted in only minimal alteration of N-glycosylation sites, including both gain and loss. As indels and point mutations are positively correlated and sequences with indels have significantly more point mutations, they have implications in the evolutionary dynamics of the SARS-CoV-2 spike glycoprotein.

Evolutionary trajectory of SARS-CoV-2 and emerging variants

The emergence of a novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and more recently, the independent evolution of multiple SARS-CoV-2 variants has generated renewed interest in virus evolution and cross-species transmission. While all known human coronaviruses (HCoVs) are speculated to have originated in animals, very little is known about their evolutionary history and factors that enable some CoVs to co-exist with humans as low pathogenic and endemic infections (HCoV-229E, HCoV-NL63, HCoV-OC43, HCoV-HKU1), while others, such as SARS-CoV, MERS-CoV and SARS-CoV-2 have evolved to cause severe disease. In this review, we highlight the origins of all known HCoVs and map positively selected for mutations within HCoV proteins to discuss the evolutionary trajectory of SARS-CoV-2. Furthermore, we discuss emerging mutations within SARS-CoV-2 and variants of concern (VOC), along with highlighting the demonstrated or speculated impact of these mutations on virus transmission, pathogenicity, and neutralization by natural or vaccine-mediated immunity.

An Educational Bioinformatics Project to Improve Genome Annotation

Scientific advancement is hindered without proper genome annotation because biologists lack a complete understanding of cellular protein functions. In bacterial cells, hypothetical proteins (HPs) are open reading frames with unknown functions. HPs result from either an outdated database or insufficient experimental evidence (i.e., indeterminate annotation). While automated annotation reviews help keep genome annotation up to date, often manual reviews are needed to verify proper annotation. Students can provide the manual review necessary to improve genome annotation. This paper outlines an innovative classroom project that determines if HPs have outdated or indeterminate annotation. The Hypothetical Protein Characterization Project uses multiple well-documented, freely available, web-based, bioinformatics resources that analyze an amino acid sequence to (1) detect sequence similarities to other proteins, (2) identify domains, (3) predict tertiary structure including active site characterization and potential binding ligands, and (4) determine cellular location. Enough evidence can be generated from these analyses to support re-annotation of HPs or prioritize HPs for experimental examinations such as structural determination via X-ray crystallography. Additionally, this paper details several approaches for selecting HPs to characterize using the Hypothetical Protein Characterization Project. These approaches include student- and instructor-directed random selection, selection using differential gene expression from mRNA expression data, and selection based on phylogenetic relations. This paper also provides additional resources to support instructional use of the Hypothetical Protein Characterization Project, such as example assignment instructions with grading rubrics, links to training videos in YouTube, and several step-by-step example projects to demonstrate and interpret the range of achievable results that students might encounter. Educational use of the Hypothetical Protein Characterization Project provides students with an opportunity to learn and apply knowledge of bioinformatic programs to address scientific questions. The project is highly customizable in that HP selection and analysis can be specifically formulated based on the scope and purpose of each student's investigations. Programs used for HP analysis can be easily adapted to course learning objectives. The project can be used in both online and in-seat instruction for a wide variety of undergraduate and graduate classes as well as undergraduate capstone, honor's, and experiential learning projects.

The phylogenetic relationship within SARS-CoV-2s: An expanding basal clade

The COVID-19 pandemic is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) whose origin is still shed in mystery. In this study, we developed a method to search the basal SARS-CoV-2 clade among collected SARS-CoV-2 genome sequences. We first identified the mutation sites in the SARS-CoV-2 whole genome sequence alignment. Then by the pairwise comparison of the numbers of mutation sites among all SARS-CoV-2s, the least mutated clade was identified, which is the basal clade under parsimony principle. In our first analysis, we used 168 SARS-CoV-2 sequences (GISAID dataset till 2020/03/04) to identify the basal clade which contains 33 identical viral sequences from seven countries. To our surprise, in our second analysis with 367 SARS-CoV-2 sequences (GISAID dataset till 2020/03/17), the basal clade has 51 viral sequences, 18 more sequences added. The much larger NCBI dataset shows that this clade has expanded with 85 unique sequences by 2020/04/04. The expanding basal clade tells a chilling fact that the least mutated SARS-CoV-2 sequence was replicating and spreading for at least four months. It is known that coronaviruses have the RNA proofreading capability to ensure their genome replication fidelity. Interestingly, we found that the SARS-CoV-2 without its nonstructural proteins 13 to 16 (Nsp13-Nsp16) exhibits an unusually high mutation rate. Our result suggests that SARS-CoV-2 has an unprecedented RNA proofreading capability which can intactly preserve its genome even after a long period of transmission. Our selection analyses also indicate that the positive selection event enabling SARS-CoV-2 to cross species and adapt to human hosts might have been achieved before its outbreak.

Synthetic reconstruction of zoonotic and early human severe acute respiratory syndrome coronavirus isolates that produce fatal disease in aged mice

The severe acute respiratory syndrome (SARS) epidemic was characterized by high mortality rates in the elderly. The molecular mechanisms that govern enhanced susceptibility of elderly populations are not known, and robust animal models are needed that recapitulate the increased pathogenic phenotype noted with increasing age. Using synthetic biology and reverse genetics, we describe the construction of a panel of isogenic SARS coronavirus (SARS-CoV) strains bearing variant spike glycoproteins that are representative of zoonotic strains found in palm civets and raccoon dogs, as well as isolates spanning the early, middle, and late phases of the SARS-CoV epidemic. The recombinant viruses replicated efficiently in cell culture and demonstrated variable sensitivities to neutralization with antibodies. The human but not the zoonotic variants replicated efficiently in human airway epithelial cultures, supporting earlier hypotheses that zoonotic isolates are less pathogenic in humans but can evolve into highly pathogenic strains. All viruses replicated efficiently, but none produced clinical disease or death in young animals. In contrast, severe clinical disease, diffuse alveolar damage, hyaline membrane formation, alveolitis, and death were noted in 12-month-old mice inoculated with the palm civet HC/SZ/61/03 strain or early-human-phase GZ02 variants but not with related middle- and late-phase epidemic or raccoon dog strains. This panel of SARS-CoV recombinants bearing zoonotic and human epidemic spike glycoproteins will provide heterologous challenge models for testing vaccine efficacy against zoonotic reintroductions as well as provide the appropriate model system for elucidating the complex virus-host interactions that contribute to more-severe and fatal SARS-CoV disease and acute respiratory distress in the elderly.