ABSTRACT
The Global Evaluation of SARS-CoV-2/hCoV-19 Sequences 2 (GESS v2 https://shiny.ph.iu.edu/GESS_v2/) is an updated version of GESS, which has offered a handy query platform to analyze single-nucleotide variants (SNVs) on millions of high coverages and high-quality severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) complete genomes provided by the Global Initiative on Sharing Avian Influenza Data (GISAID). Including the tools in the first version, the GESS v2 is embedded with new functions, which allow users to search SNVs, given the viral nucleotide or amino acid sequence. The GESS v2 helps users to identify SNVs or SARS-CoV-2 lineages enriched in countries of user's interest and show the migration path of a selected lineage on a world map during specific time periods chosen by the users. In addition, the GESS v2 can recognize the dynamic variations of newly emerging SNVs in each month to help users monitor SNVs, which will potentially become dominant soon. More importantly, multiple sets of analyzed results about SNVs can be downloaded directly from the GESS v2 by which users can conduct their own independent research. With these significant updates, the GESS v2 will continue to serve as a public open platform for researchers to explore SARS-CoV-2 evolutionary patterns from the perspectives of the prevalence and impact of SNVs.
ABSTRACT
By analyzing newly collected SARS-CoV-2 genomes and comparing them with our previous study about SARS-CoV-2 single nucleotide variants (SNVs) before June 2020, we found that the SNV clustering had changed remarkably since June 2020. Apart from that the group of SNVs became dominant, which is represented by two nonsynonymous mutations A23403G (S:D614G) and C14408T (ORF1ab:P4715L), a few emerging groups of SNVs were recognized with sharply increased monthly incidence ratios of up to 70% in November 2020. Further investigation revealed sets of SNVs specific to patients' ages and/or gender, or strongly associated with mortality. Our logistic regression model explored features contributing to mortality status, including three critical SNVs, G25088T(S:V1176F), T27484C (ORF7a:L31L), and T25A (upstream of ORF1ab), ages above 40 years old, and the male gender. The protein structure analysis indicated that the emerging subgroups of nonsynonymous SNVs and the mortality-related ones were located on the protein surface area. The clashes in protein structure introduced by these mutations might in turn affect the viral pathogenesis through the alteration of protein conformation, leading to a difference in transmission and virulence. Particularly, we explored the fact that nonsynonymous SNVs tended to occur in intrinsic disordered regions of Spike and ORF1ab to significantly increase hydrophobicity, suggesting a potential role in the change of protein folding related to immune evasion.
Subject(s)
COVID-19/mortality , Genome, Viral/genetics , Polymorphism, Single Nucleotide/genetics , SARS-CoV-2/genetics , SARS-CoV-2/pathogenicity , Adult , Aged , Aged, 80 and over , COVID-19/pathology , Female , Humans , Male , Middle Aged , Mutation , Polyproteins/genetics , Spike Glycoprotein, Coronavirus/genetics , Viral Proteins/genetics , Virulence/genetics , Young AdultABSTRACT
Front Cover Caption: The cover image is based on the Research Article Updated SARS-CoV-2 single nucleotide variants and mortality association by Shuyi Fang et al., https://doi.org/10.1002/jmv.27191.
ABSTRACT
Antiviral drugs (AvDs) are the primary resource in the global battle against viruses, including the recent fight against corona virus disease 2019 (COVID-19). Most AvDs require multiple medications, and their use frequently leads to drug resistance, since they have poor oral bioavailability and low efficacy due to their low solubility/low permeability. Characterizing the in vivo metabolism and pharmacokinetic characteristics of AvDs may help to solve the problems associated with AvDs and enhance their efficacy. In this review of AvDs, we systematically investigated their structure-based metabolic reactions and related enzymes, their cellular pharmacology, and the effects of metabolism on AvD pharmacodynamics and pharmacokinetics. We further assessed how delivery systems achieve better metabolism and pharmacology of AvDs. This review suggests that suitable nanosystems may help to achieve better pharmacological activity and pharmacokinetic behavior of AvDs by altering drug metabolism through the utilization of advanced nanotechnology and appropriate administration routes. Notably, such AvDs as ribavirin, remdesivir, favipiravir, chloroquine, lopinavir and ritonavir have been confirmed to bind to the severe acute respiratory syndrome-like coronavirus (SARS-CoV-2) receptor and thus may represent anti-COVID-19 treatments. Elucidating the metabolic and pharmacokinetic characteristics of AvDs may help pharmacologists to identify new formulations with high bioavailability and efficacy and help physicians to better treat virus-related diseases, including COVID-19.
Subject(s)
Antiviral Agents/administration & dosage , Antiviral Agents/pharmacokinetics , COVID-19/metabolism , Drug Delivery Systems , SARS-CoV-2/drug effects , Antiviral Agents/metabolism , Antiviral Agents/pharmacology , Humans , COVID-19 Drug TreatmentABSTRACT
The COVID-19 outbreak has become a global emergency since December 2019. Analysis of SARS-CoV-2 sequences can uncover single nucleotide variants (SNVs) and corresponding evolution patterns. The Global Evaluation of SARS-CoV-2/hCoV-19 Sequences (GESS, https://wan-bioinfo.shinyapps.io/GESS/) is a resource to provide comprehensive analysis results based on tens of thousands of high-coverage and high-quality SARS-CoV-2 complete genomes. The database allows user to browse, search and download SNVs at any individual or multiple SARS-CoV-2 genomic positions, or within a chosen genomic region or protein, or in certain country/area of interest. GESS reveals geographical distributions of SNVs around the world and across the states of USA, while exhibiting time-dependent patterns for SNV occurrences which reflect development of SARS-CoV-2 genomes. For each month, the top 100 SNVs that were firstly identified world-widely can be retrieved. GESS also explores SNVs occurring simultaneously with specific SNVs of user's interests. Furthermore, the database can be of great help to calibrate mutation rates and identify conserved genome regions. Taken together, GESS is a powerful resource and tool to monitor SARS-CoV-2 migration and evolution according to featured genomic variations. It provides potential directive information for prevalence prediction, related public health policy making, and vaccine designs.
Subject(s)
COVID-19/prevention & control , Computational Biology/methods , Databases, Genetic , Genome, Viral/genetics , Genomics/methods , SARS-CoV-2/genetics , Algorithms , COVID-19/epidemiology , COVID-19/virology , Disease Outbreaks , Global Health , Humans , Internet , Mutation Rate , Polymorphism, Single Nucleotide , Population Dynamics , SARS-CoV-2/metabolism , SARS-CoV-2/physiology , Viral Proteins/genetics , Viral Proteins/metabolismABSTRACT
Four signature groups of frequently occurred single-nucleotide variants (SNVs) were identified in over twenty-eight thousand high-quality and high-coverage SARS-CoV-2 complete genome sequences, representing different viral strains. Some SNVs predominated but were mutually exclusively presented in patients from different countries and areas. These major SNV signatures exhibited distinguishable evolution patterns over time. A few hundred patients were detected with multiple viral strain-representing mutations simultaneously, which may stand for possible co-infection or potential homogenous recombination of SARS-CoV-2 in environment or within the viral host. Interestingly nucleotide substitutions among SARS-CoV-2 genomes tended to switch between bat RaTG13 coronavirus sequence and Wuhan-Hu-1 genome, indicating the higher genetic instability or tolerance of mutations on those sites or suggesting that major viral strains might exist between Wuhan-Hu-1 and RaTG13 coronavirus.
ABSTRACT
Four signature groups of frequently occurred single-nucleotide variants (SNVs) were identified in over twenty-eight thousand high-quality and high-coverage SARS-CoV-2 complete genome sequences, representing different viral strains. Some SNVs predominated but were mutually exclusively presented in patients from different countries and areas. These major SNV signatures exhibited distinguishable evolution patterns over time. A few hundred patients were detected with multiple viral strain-representing mutations simultaneously, which may stand for possible co-infection or potential homogenous recombination of SARS-CoV-2 in environment or within the viral host. Interestingly nucleotide substitutions among SARS-CoV-2 genomes tended to switch between bat RaTG13 coronavirus sequence and Wuhan-Hu-1 genome, indicating the higher genetic instability or tolerance of mutations on those sites or suggesting that major viral strains might exist between Wuhan-Hu-1 and RaTG13 coronavirus.