Therapeutics to tackle Omicron outbreak.

Tweetable abstract In this commentary, the authors have focused on the mutational impact of the Omicron variant on the current therapeutics to manage #COVID19.

Computational repurposing approach for targeting the critical spike mutations in B.1.617.2 (delta), AY.1 (delta plus) and C.37 (lambda) SARS-CoV-2 variants using exhaustive structure-based virtual screening, molecular dynamic simulations and MM-PBSA methods.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the contagious coronavirus disease 2019 (COVID-19) which was first identified in Wuhan, China, in December 2019. Around the world, many researchers focused their research on identifying inhibitors against the druggable SARS-CoV-2 targets. The reported genomic mutations have a direct effect on the receptor-binding domain (RBD), which interacts with host angiotensin-converting enzyme 2 (ACE-2) for viral cell entry. These mutations, some of which are variants of concern (VOC), lead to increased morbidity and mortality rates. The newest variants including B.1.617.2 (Delta), AY.1 (Delta plus), and C.37 (Lambda) were considered in this study. Thus, an exhaustive structure-based virtual screening of a ligand library (in which FDA approved drugs are also present) using the drug-likeness screening, molecular docking, ADMET profiling was performed followed by molecular dynamics (MD) simulation, and Molecular Mechanics-Poisson Boltzmann Surface Area (MM-PBSA) calculation to identify compounds or drugs can be repurposed for inhibiting the wild type, Delta, Delta plus and Lambda variants of RBD of the spike protein. Based on the virtual screening steps, two FDA approved drugs, Atovaquone (atv) and Praziquantel (prz), were selected and repurposed as the best candidates of SARS-CoV-2 RBD inhibitors. Molecular docking results display that both atv and prz contribute in different interaction with binding site residues (Gln493, Asn501 and Gly502 in the hydrogen bond formation, Phe490 and Tyr505 in the π- π stacking and Tyr449, Ser494, and Phe497 in the vdW interactions) in the wild type, Delta, Delta plus and Lambda variants of RBD of the spike protein. MD simulations revealed that among the eight studied complexes, the wild type-atv and Delta-prz complexes have the most structural stability over the simulation time. Furthermore, MM-PBSA calculation showed that in the atv containing complexes, highest binding affinity is related to the wild type-atv complex and in the prz containing complexes, it is related to the Delta-prz complex. The validation of docking results was done by comparing with experimental data (heparin in complex with wild type and Delta variants). Also, comparison of the obtained results with the result of simulation of the k22 with the studied proteins showed that atv and prz are suitable inhibitors for these proteins, especially wild type t and Delta variant, respectively. Thus, we found that atv and prz are the best candidate for inhibition of wild type and Delta variant of the spike protein. Also, atv can be an appropriate inhibitor for the Lambda variant. Obtained in silico results may help the development of new anti-COVID-19 drugs.

Understanding the mutational frequency in SARS-CoV-2 proteome using structural features.

The prolonged transmission of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus in the human population has led to demographic divergence and the emergence of several location-specific clusters of viral strains. Although the effect of mutation(s) on severity and survival of the virus is still unclear, it is evident that certain sites in the viral proteome are more/less prone to mutations. In fact, millions of SARS-CoV-2 sequences collected all over the world have provided us a unique opportunity to understand viral protein mutations and develop novel computational approaches to predict mutational patterns. In this study, we have classified the mutation sites into low and high mutability classes based on viral isolates count containing mutations. The physicochemical features and structural analysis of the SARS-CoV-2 proteins showed that features including residue type, surface accessibility, residue bulkiness, stability and sequence conservation at the mutation site were able to classify the low and high mutability sites. We further developed machine learning models using above-mentioned features, to predict low and high mutability sites at different selection thresholds (ranging 5-30% of topmost and bottommost mutated sites) and observed the improvement in performance as the selection threshold is reduced (prediction accuracy ranging from 65 to 77%). The analysis will be useful for early detection of variants of concern for the SARS-CoV-2, which can also be applied to other existing and emerging viruses for another pandemic prevention.

Functional mutations of SARS-CoV-2: implications to viral transmission, pathogenicity and immune escape.

ABSTRACT: The pandemic of coronavirus disease 2019 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to major public health challenges globally. The increasing viral lineages identified indicate that the SARS-CoV-2 genome is evolving at a rapid rate. Viral genomic mutations may cause antigenic drift or shift, which are important ways by which SARS-CoV-2 escapes the human immune system and changes its transmissibility and virulence. Herein, we summarize the functional mutations in SARS-CoV-2 genomes to characterize its adaptive evolution to inform the development of vaccination, treatment as well as control and intervention measures.

Molecular detection of omicron SARS-CoV-2 variant is achieved by RT-LAMP despite genomic mutations.

BACKGROUND: Severe acute respiratory syndrome coronavirus (SARS-CoV-2) omicron variant was first detected in South Africa in November 2021. Since then, the number of cases due to this variant increases enormously every day in different parts of the world. Mutations within omicron genome may impair the molecular detection resulting in false negative results during Coronavirus disease 19 (COVID-19) diagnosis. OBJECTIVES: To verify if colorimetric reverse transcription loop-mediated isothermal amplification (RT-LAMP) targeting N and E genes would work efficiently to detect omicron SARS-CoV-2 variant and its sub-lineages. METHODS: SARS-CoV-2 reverse transcription quantitative polymerase chain reaction (RT-qPCR) positive samples were sequenced by next generation DNA sequencing. The consensus sequences generated were submitted to Pangolin tool for SARS-CoV-2 lineage identification. RT-LAMP reactions were performed at 65ºC/30 min targeting N and E. FINDINGS: SARS-CoV-2 omicron can be detected by RT-LAMP targeting N and E genes despite the genomic mutation of this more transmissible lineage. Omicron SARS-CoV-2 sub-lineages were tested and efficiently detected by RT-LAMP. We demonstrated that this test is very sensitive in detecting omicron variant, with LoD as low as 0.4 copies/µL. MAIN CONCLUSIONS: Molecular detection of omicron SARS-CoV-2 variant and its sub-lineages can be achieved by RT-LAMP despite the genomic mutations as a very sensitive surveillance tool for COVID-19 molecular diagnosis.

Drivers of adaptive evolution during chronic SARS-CoV-2 infections.

In some immunocompromised patients with chronic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, considerable adaptive evolution occurs. Some substitutions found in chronic infections are lineage-defining mutations in variants of concern (VOCs), which has led to the hypothesis that VOCs emerged from chronic infections. In this study, we searched for drivers of VOC-like emergence by consolidating sequencing results from a set of 27 chronic infections. Most substitutions in this set reflected lineage-defining VOC mutations; however, a subset of mutations associated with successful global transmission was absent from chronic infections. We further tested the ability to associate antibody evasion mutations with patient-specific and virus-specific features and found that viral rebound is strongly correlated with the emergence of antibody evasion. We found evidence for dynamic polymorphic viral populations in most patients, suggesting that a compromised immune system selects for antibody evasion in particular niches in a patient's body. We suggest that a tradeoff exists between antibody evasion and transmissibility and that extensive monitoring of chronic infections is necessary to further understanding of VOC emergence.

Mutations in the SARS-CoV-2 RNA-dependent RNA polymerase confer resistance to remdesivir by distinct mechanisms.

The nucleoside analog remdesivir (RDV) is a Food and Drug Administration-approved antiviral for treatment of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. Thus, it is critical to understand factors that promote or prevent RDV resistance. We passaged SARS-CoV-2 in the presence of increasing concentrations of GS-441524, the parent nucleoside of RDV. After 13 passages, we isolated three viral lineages with phenotypic resistance as defined by increases in half-maximal effective concentration from 2.7- to 10.4-fold. Sequence analysis identified nonsynonymous mutations in nonstructural protein 12 RNA-dependent RNA polymerase (nsp12-RdRp): V166A, N198S, S759A, V792I, and C799F/R. Two lineages encoded the S759A substitution at the RdRp Ser759-Asp-Asp active motif. In one lineage, the V792I substitution emerged first and then combined with S759A. Introduction of S759A and V792I substitutions at homologous nsp12 positions in murine hepatitis virus demonstrated transferability across betacoronaviruses; introduction of these substitutions resulted in up to 38-fold RDV resistance and a replication defect. Biochemical analysis of SARS-CoV-2 RdRp encoding S759A demonstrated a roughly 10-fold decreased preference for RDV-triphosphate (RDV-TP) as a substrate, whereas nsp12-V792I diminished the uridine triphosphate concentration needed to overcome template-dependent inhibition associated with RDV. The in vitro-selected substitutions identified in this study were rare or not detected in the greater than 6 million publicly available nsp12-RdRp consensus sequences in the absence of RDV selection. The results define genetic and biochemical pathways to RDV resistance and emphasize the need for additional studies to define the potential for emergence of these or other RDV resistance mutations in clinical settings.

Tracking SARS-CoV-2 Omicron diverse spike gene mutations identifies multiple inter-variant recombination events.

The current pandemic of COVID-19 is fueled by more infectious emergent Omicron variants. Ongoing concerns of emergent variants include possible recombinants, as genome recombination is an important evolutionary mechanism for the emergence and re-emergence of human viral pathogens. In this study, we identified diverse recombination events between two Omicron major subvariants (BA.1 and BA.2) and other variants of concern (VOCs) and variants of interest (VOIs), suggesting that co-infection and subsequent genome recombination play important roles in the ongoing evolution of SARS-CoV-2. Through scanning high-quality completed Omicron spike gene sequences, 18 core mutations of BA.1 (frequency >99%) and 27 core mutations of BA.2 (nine more than BA.1) were identified, of which 15 are specific to Omicron. BA.1 subvariants share nine common amino acid mutations (three more than BA.2) in the spike protein with most VOCs, suggesting a possible recombination origin of Omicron from these VOCs. There are three more Alpha-related mutations in BA.1 than BA.2, and BA.1 is phylogenetically closer to Alpha than other variants. Revertant mutations are found in some dominant mutations (frequency >95%) in the BA.1. Most notably, multiple characteristic amino acid mutations in the Delta spike protein have been also identified in the "Deltacron"-like Omicron Variants isolated since November 11, 2021 in South Africa, which implies the recombination events occurring between the Omicron and Delta variants. Monitoring the evolving SARS-CoV-2 genomes especially for recombination is critically important for recognition of abrupt changes to viral attributes including its epitopes which may call for vaccine modifications.

Long-Term Evolution of SARS-CoV-2 in an Immunocompromised Patient with Non-Hodgkin Lymphoma.

Recent studies have shown that persistent SARS-CoV-2 infections in immunocompromised patients can trigger the accumulation of an unusual high number of mutations with potential relevance at both biological and epidemiological levels. Here, we report a case of an immunocompromised patient (non-Hodgkin lymphoma patient under immunosuppressive therapy) with a persistent SARS-CoV-2 infection (marked by intermittent positivity) over at least 6 months. Viral genome sequencing was performed at days 1, 164, and 171 to evaluate SARS-CoV-2 evolution. Among the 15 single-nucleotide polymorphisms (SNPs) (11 leading to amino acid alterations) and 3 deletions accumulated during this long-term infection, four amino acid changes (V3G, S50L, N87S, and A222V) and two deletions (18-30del and 141-144del) occurred in the virus Spike protein. Although no convalescent plasma therapy was administered, some of the detected mutations have been independently reported in other chronically infected individuals, which supports a scenario of convergent adaptive evolution. This study shows that it is of the utmost relevance to monitor the SARS-CoV-2 evolution in immunocompromised individuals, not only to identify novel potentially adaptive mutations, but also to mitigate the risk of introducing "hyper-evolved" variants in the community. IMPORTANCE Tracking the within-patient evolution of SARS-CoV-2 is key to understanding how this pandemic virus shapes its genome toward immune evasion and survival. In the present study, by monitoring a long-term COVID-19 immunocompromised patient, we observed the concurrent emergence of mutations potentially associated with immune evasion and/or enhanced transmission, mostly targeting the SARS-CoV-2 key host-interacting protein and antigen. These findings show that the frequent oscillation in the immune status in immunocompromised individuals can trigger an accelerated virus evolution, thus consolidating this study model as an accelerated pathway to better understand SARS-CoV-2 adaptive traits and anticipate the emergence of variants of concern.

Co-mutation modules capture the evolution and transmission patterns of SARS-CoV-2.

The rapid spread and huge impact of the COVID-19 pandemic caused by the emerging SARS-CoV-2 have driven large efforts for sequencing and analyzing the viral genomes. Mutation analyses have revealed that the virus keeps mutating and shows a certain degree of genetic diversity, which could result in the alteration of its infectivity and pathogenicity. Therefore, appropriate delineation of SARS-CoV-2 genetic variants enables us to understand its evolution and transmission patterns. By focusing on the nucleotides that co-substituted, we first identified 42 co-mutation modules that consist of at least two co-substituted nucleotides during the SARS-CoV-2 evolution. Then based on these co-mutation modules, we classified the SARS-CoV-2 population into 43 groups and further identified the phylogenetic relationships among groups based on the number of inconsistent co-mutation modules, which were validated with phylogenetic trees. Intuitively, we tracked tempo-spatial patterns of the 43 groups, of which 11 groups were geographic-specific. Different epidemic periods showed specific co-circulating groups, where the dominant groups existed and had multiple sub-groups of parallel evolution. Our work enables us to capture the evolution and transmission patterns of SARS-CoV-2, which can contribute to guiding the prevention and control of the COVID-19 pandemic. An interactive website for grouping SARS-CoV-2 genomes and visualizing the spatio-temporal distribution of groups is available at https://www.jianglab.tech/cmm-grouping/.

Genome-scale deconvolution of RNA structure ensembles.

RNA structure heterogeneity is a major challenge when querying RNA structures with chemical probing. We introduce DRACO, an algorithm for the deconvolution of coexisting RNA conformations from mutational profiling experiments. Analysis of the SARS-CoV-2 genome using dimethyl sulfate mutational profiling with sequencing (DMS-MaPseq) and DRACO, identifies multiple regions that fold into two mutually exclusive conformations, including a conserved structural switch in the 3' untranslated region. This work may open the way to dissecting the heterogeneity of the RNA structurome.

Analysis of SARS-CoV-2 mutations in the United States suggests presence of four substrains and novel variants.

SARS-CoV-2 has been mutating since it was first sequenced in early January 2020. Here, we analyze 45,494 complete SARS-CoV-2 geneome sequences in the world to understand their mutations. Among them, 12,754 sequences are from the United States. Our analysis suggests the presence of four substrains and eleven top mutations in the United States. These eleven top mutations belong to 3 disconnected groups. The first and second groups consisting of 5 and 8 concurrent mutations are prevailing, while the other group with three concurrent mutations gradually fades out. Moreover, we reveal that female immune systems are more active than those of males in responding to SARS-CoV-2 infections. One of the top mutations, 27964C > T-(S24L) on ORF8, has an unusually strong gender dependence. Based on the analysis of all mutations on the spike protein, we uncover that two of four SASR-CoV-2 substrains in the United States become potentially more infectious.

Structure-altering mutations of the SARS-CoV-2 frameshifting RNA element.

With the rapid rate of COVID-19 infections and deaths, treatments and cures besides hand washing, social distancing, masks, isolation, and quarantines are urgently needed. The treatments and vaccines rely on the basic biophysics of the complex viral apparatus. Although proteins are serving as main drug and vaccine targets, therapeutic approaches targeting the 30,000 nucleotide RNA viral genome form important complementary approaches. Indeed, the high conservation of the viral genome, its close evolutionary relationship to other viruses, and the rise of gene editing and RNA-based vaccines all argue for a focus on the RNA agent itself. One of the key steps in the viral replication cycle inside host cells is the ribosomal frameshifting required for translation of overlapping open reading frames. The RNA frameshifting element (FSE), one of three highly conserved regions of coronaviruses, is believed to include a pseudoknot considered essential for this ribosomal switching. In this work, we apply our graph-theory-based framework for representing RNA secondary structures, "RAG (or RNA-As-Graphs)," to alter key structural features of the FSE of the SARS-CoV-2 virus. Specifically, using RAG machinery of genetic algorithms for inverse folding adapted for RNA structures with pseudoknots, we computationally predict minimal mutations that destroy a structurally important stem and/or the pseudoknot of the FSE, potentially dismantling the virus against translation of the polyproteins. Our microsecond molecular dynamics simulations of mutant structures indicate relatively stable secondary structures. These findings not only advance our computational design of RNAs containing pseudoknots, they pinpoint key residues of the SARS-CoV-2 virus as targets for antiviral drugs and gene editing approaches.

Variant analysis of SARS-CoV-2 genomes in the Middle East.

BACKGROUND: Coronavirus (COVID-19) was introduced into society in late 2019 and has now reached over 88 million cases and 1.9 million deaths. The Middle East has a death toll of ~80,000 and over 35000 of these are in Iran, which has over 1.2 million confirmed cases. We expect that Iranian cases caused outbreaks in the neighbouring countries and that variant mapping and phylogenetic analysis can be used to prove this. We also aim to analyse the variants of severe acute respiratory syndrome coronavirus-2 (SARS -CoV-2) to characterise the common genome variants and provide useful data in the global effort to prevent further spread of COVID-19. METHODS: The approach uses bioinformatics approaches including multiple sequence alignment, variant calling and annotation and phylogenetic analysis to identify the genomic variants found in the region. The approach uses 122 samples from the 13 countries of the Middle East sourced from the Global Initiative on Sharing All Influenza Data (GISAID). FINDINGS: We identified 2200 distinct genome variants including 129 downstream gene variants, 298 frame shift variants, 789 missense variants, 1 start lost, 13 start gained, 1 stop lost, 249 synonymous variants and 720 upstream gene variants. The most common, high impact variants were 10818delTinsG, 2772delCinsC, 14159delCinsC and 2789delAinsA. These high impact variant ultimately results in 36 number of mutations on spike glycoprotein. Variant alignment and phylogenetic tree generation indicates that samples from Iran likely introduced COVID-19 to the rest of the Middle East. INTERPRETATION: The phylogenetic and variant analysis provides unique insight into mutation types in genomes. Initial introduction of COVID-19 was most likely due to Iranian transmission. Some countries show evidence of novel mutations and unique strains. Increased time in small populations is likely to contribute to more unique genomes. This study provides more in depth analysis of the variants affecting in the region than any other study.

Molecular characterization of canine coronaviruses: an enteric and pantropic approach.

Canine coronavirus (CCoV) generally causes an infection with high morbidity and low mortality in dogs. In recent years, studies on coronaviruses have gained a momentum due to coronavirus outbreaks. Mutations in coronaviruses can result in deadly diseases in new hosts (such as SARS-CoV-2) or cause changes in organ-tissue affinity, as occurred with feline infectious peritonitis virus, exacerbating their pathogenesis. In recent studies on different types of CCoV, the pantropic strains characterized by hypervirulent and multi-systemic infections are believed to be emerging, in contrast to classical enteric coronavirus infections. In this study, we investigated emerging hypervirulent and multi-systemic CCoV strains using molecular and bioinformatic analysis, and examined differences between enteric and pantropic CCoV strains at the phylogenetic level. RT-PCR was performed with specific primers to identify the coronavirus M (membrane) and S (spike) genes, and samples were then subjected to DNA sequencing. In phylogenetic analysis, four out of 26 samples were classified as CCoV-1. The remaining 22 samples were all classified as CCoV-2a. In the CCoV-2a group, six samples were in branches close to enteric strains, and 16 samples were in the branches close to pantropic strains. Enteric and pantropic strains were compared by molecular genotyping of CCoV in dogs. Phylogenetic analysis of hypervirulent pantropic strains was carried out at the amino acid and nucleotide sequence levels. CCoV was found to be divergent from the original strain. This implies that some CCoV strains have become pantropic strains that cause multisystemic infections, and they should not be ruled out as the cause of severe diarrhea and multisystemic infections.

Multiplex bead binding assays using off-the-shelf components and common flow cytometers.

The ability to quantify protein-ligand interactions in an accurate and high-throughput manner is important in diverse areas of biology and medicine. Multiplex bead binding assays (MBBAs) are powerful methods that allow for simultaneous analysis of many protein-ligand interactions. Although there are a number of well-established MBBA platforms, there are few platforms suitable for research and development that offer rapid experimentation at low costs and without the need for specialized reagents or instruments dedicated for MBBA. Here, we describe a MBBA method that uses low-cost reagents and standard cytometers. The key innovation is the use of the essentially irreversible biotin-streptavidin interaction. We prepared a biotin-conjugated fluorescent dye and used it to produce streptavidin-coated magnetic beads that are labeled at distinct levels of fluorescence. We show the utility of our method in characterization of phage-displayed antibodies against multiple antigens of SARS-CoV-2, which substantially improves the throughput and dramatically reduces antigen consumption compared with conventional phage ELISA methods. This approach will make MBBAs more broadly accessible.

Chicken Egg Yolk Antibodies (IgYs) block the binding of multiple SARS-CoV-2 spike protein variants to human ACE2.

The SARS-CoV-2 virus is still spreading worldwide, and there is an urgent need to effectively prevent and control this pandemic. This study evaluated the potential efficacy of Egg Yolk Antibodies (IgY) as a neutralizing agent against the SARS-CoV-2. We investigated the neutralizing effect of anti-spike-S1 IgYs on the SARS-CoV-2 pseudovirus, as well as its inhibitory effect on the binding of the coronavirus spike protein mutants to human ACE2. Our results show that the anti-Spike-S1 IgYs showed significant neutralizing potency against SARS-CoV-2 pseudovirus, various spike protein mutants, and even SARS-CoV in vitro. It might be a feasible tool for the prevention and control of ongoing COVID-19.