Mutational spectrum of SARS-CoV-2 during the global pandemic

Natural selection shapes codon usage and host adaptation of NS1 in mosquito-borne pathogenic flaviviruses

The NS1 protein of nine mosquito-borne flaviviruses, including Dengue virus 1-4, Japanese encephalitis virus, West Nile virus, Yellow fever virus, Tembusu virus, and Zika virus, shows distinct codon usage and evolutionary traits. Codon usage analysis shows notable base composition bias and non-conservatism in NS1, with distinct evolutionary traits from its ORF. Analysis of relative synonymous codon usage (RSCU) indicates that the NS1 genes exhibit non-conservative RSCU patterns within different mosquito-borne pathogenic flaviviruses. Principal component analysis (PCA) based on the RSCU values, effective number of codons (ENC)-GC3, and parity rule 2 analysis (PR2) plot analyses demonstrate the similarity in codon usage patterns of NS1 genes among different mosquito-borne pathogenic flaviviruses. The ENC-GC3 and PR2 results, along with neutrality and selection pressure analyses, confirm that natural selection, especially purifying selection, plays a primary role in shaping NS1 codon usage. In addition, NS1 is subject to stronger positive selection than ORF, resulting in higher host adaptability in its codon bias, such as higher CAI index, hydrophilicity, aromaticity, and low CpG usage. These features indicate that the codon usage pattern of NS1 plays a crucial role in viral adaptation and immune evasion mechanisms, supporting the design and optimization of NS1-based vaccines.

Accurate predictions of SARS-CoV-2 infectivity from comprehensive analysis

An unprecedented amount of SARS-CoV-2 data has been accumulated compared with previous infectious diseases, enabling insights into its evolutionary process and more thorough analyses. This study investigates SARS-CoV-2 features as it evolved to evaluate its infectivity. We examined viral sequences and identified the polarity of amino acids in the receptor binding motif (RBM) region. We detected an increased frequency of amino acid substitutions to lysine (K) and arginine (R) in variants of concern (VOCs). As the virus evolved to Omicron, commonly occurring mutations became fixed components of the new viral sequence. Furthermore, at specific positions of VOCs, only one type of amino acid substitution and a notable absence of mutations at D467 were detected. We found that the binding affinity of SARS-CoV-2 lineages to the ACE2 receptor was impacted by amino acid substitutions. Based on our discoveries, we developed APESS, an evaluation model evaluating infectivity from biochemical and mutational properties. In silico evaluation using real-world sequences and in vitro viral entry assays validated the accuracy of APESS and our discoveries. Using Machine Learning, we predicted mutations that had the potential to become more prominent. We created AIVE, a web-based system, accessible at https://ai-ve.org to provide infectivity measurements of mutations entered by users. Ultimately, we established a clear link between specific viral properties and increased infectivity, enhancing our understanding of SARS-CoV-2 and enabling more accurate predictions of the virus.

Viral N protein hijacks deaminase-containing RNA granules to enhance SARS-CoV-2 mutagenesis

Host cell-encoded deaminases act as antiviral restriction factors to impair viral replication and production through introducing mutations in the viral genome. We sought to understand whether deaminases are involved in SARS-CoV-2 mutation and replication, and how the viral factors interact with deaminases to trigger these processes. Here, we show that APOBEC and ADAR deaminases act as the driving forces for SARS-CoV-2 mutagenesis, thereby blocking viral infection and production. Mechanistically, SARS-CoV-2 nucleocapsid (N) protein, which is responsible for packaging viral genomic RNA, interacts with host deaminases and co-localizes with them at stress granules to facilitate viral RNA mutagenesis. N proteins from several coronaviruses interact with host deaminases at RNA granules in a manner dependent on its F17 residue, suggesting a conserved role in modulation of viral mutagenesis in other coronaviruses. Furthermore, mutant N protein bearing a F17A substitution cannot localize to deaminase-containing RNA granules and leads to reduced mutagenesis of viral RNA, providing support for its function in enhancing deaminase-dependent viral RNA editing. Our study thus provides further insight into virus-host cell interactions mediating SARS-CoV-2 evolution.

The evolutionary features and roles of single nucleotide variants and charged amino acid mutations in influenza outbreaks during NPI period

The epidemic and outbreaks of influenza B Victoria lineage (Bv) during 2019-2022 led to an analysis of genetic, epitopes, charged amino acids and Bv outbreaks. Based on the National Influenza Surveillance Network (NISN), the Bv 72 strains isolated during 2019-2022 were selected by spatio-temporal sampling, then were sequenced. Using the Compare Means, Correlate and Cluster, the outbreak data were analyzed, including the single nucleotide variant (SNV), amino acid (AA), epitope, evolutionary rate (ER), Shannon entropy value (SV), charged amino acid and outbreak. With the emergence of COVID-19, the non-pharmaceutical interventions (NPIs) made Less distant transmission and only Bv outbreak. The 2021-2022 strains in the HA genes were located in the same subset, but were distinct from the 2019-2020 strains (P < 0.001). The codon G → A transition in nucleotide was in the highest ratio but the transversion of C → A and T → A made the most significant contribution to the outbreaks, while the increase in amino acid mutations characterized by polar, acidic and basic signatures played a key role in the Bv epidemic in 2021-2022. Both ER and SV were positively correlated in HA genes (R = 0.690) and NA genes (R = 0.711), respectively, however, the number of mutations in the HA genes was 1.59 times higher than that of the NA gene (2.15/1.36) from the beginning of 2020 to 2022. The positively selective sites 174, 199, 214 and 563 in HA genes and the sites 73 and 384 in NA genes were evolutionarily selected in the 2021-2022 influenza outbreaks. Overall, the prevalent factors related to 2021-2022 influenza outbreaks included epidemic timing, Tv, Ts, Tv/Ts, P137 (B → P), P148 (B → P), P199 (P → A), P212 (P → A), P214 (H → P) and P563 (B → P). The preference of amino acid mutations for charge/pH could influence the epidemic/outbreak trends of infectious diseases. Here was a good model of the evolution of infectious disease pathogens. This study, on account of further exploration of virology, genetics, bioinformatics and outbreak information, might facilitate further understanding of their deep interaction mechanisms in the spread of infectious diseases.

SARS-CoV-2 and innate immunity: the good, the bad, and the "goldilocks"

An ancient conflict between hosts and pathogens has driven the innate and adaptive arms of immunity. Knowledge about this interplay can not only help us identify biological mechanisms but also reveal pathogen vulnerabilities that can be leveraged therapeutically. The humoral response to SARS-CoV-2 infection has been the focus of intense research, and the role of the innate immune system has received significantly less attention. Here, we review current knowledge of the innate immune response to SARS-CoV-2 infection and the various means SARS-CoV-2 employs to evade innate defense systems. We also consider the role of innate immunity in SARS-CoV-2 vaccines and in the phenomenon of long COVID.

Mutational signature dynamics indicate SARS-CoV-2's evolutionary capacity is driven by host antiviral molecules

The COVID-19 pandemic has been characterised by sequential variant-specific waves shaped by viral, individual human and population factors. SARS-CoV-2 variants are defined by their unique combinations of mutations and there has been a clear adaptation to more efficient human infection since the emergence of this new human coronavirus in late 2019. Here, we use machine learning models to identify shared signatures, i.e., common underlying mutational processes and link these to the subset of mutations that define the variants of concern (VOCs). First, we examined the global SARS-CoV-2 genomes and associated metadata to determine how viral properties and public health measures have influenced the magnitude of waves, as measured by the number of infection cases, in different geographic locations using regression models. This analysis showed that, as expected, both public health measures and virus properties were associated with the waves of regional SARS-CoV-2 reported infection numbers and this impact varies geographically. We attribute this to intrinsic differences such as vaccine coverage, testing and sequencing capacity and the effectiveness of government stringency. To assess underlying evolutionary change, we used non-negative matrix factorisation and observed three distinct mutational signatures, unique in their substitution patterns and exposures from the SARS-CoV-2 genomes. Signatures 1, 2 and 3 were biased to C→T, T→C/A→G and G→T point mutations. We hypothesise assignments of these mutational signatures to the host antiviral molecules APOBEC, ADAR and ROS respectively. We observe a shift amidst the pandemic in relative mutational signature activity from predominantly Signature 1 changes to an increasingly high proportion of changes consistent with Signature 2. This could represent changes in how the virus and the host immune response interact and indicates how SARS-CoV-2 may continue to generate variation in the future. Linkage of the detected mutational signatures to the VOC-defining amino acids substitutions indicates the majority of SARS-CoV-2's evolutionary capacity is likely to be associated with the action of host antiviral molecules rather than virus replication errors.

SARS-CoV-2 Orphan Gene ORF10 Contributes to More Severe COVID-19 Disease

The orphan gene of SARS-CoV-2, ORF10, is the least studied gene in the virus responsible for the COVID-19 pandemic. Recent experimentation indicated ORF10 expression moderates innate immunity in vitro. However, whether ORF10 affects COVID-19 in humans remained unknown. We determine that the ORF10 sequence is identical to the Wuhan-Hu-1 ancestral haplotype in 95% of genomes across five variants of concern (VOC). Four ORF10 variants are associated with less virulent clinical outcomes in the human host: three of these affect ORF10 protein structure, one affects ORF10 RNA structural dynamics. RNA-Seq data from 2070 samples from diverse human cells and tissues reveals ORF10 accumulation is conditionally discordant from that of other SARS-CoV-2 transcripts. Expression of ORF10 in A549 and HEK293 cells perturbs immune-related gene expression networks, alters expression of the majority of mitochondrially-encoded genes of oxidative respiration, and leads to large shifts in levels of 14 newly-identified transcripts. We conclude ORF10 contributes to more severe COVID-19 clinical outcomes in the human host.

N4-hydroxycytidine, the active compound of Molnupiravir, promotes SARS-CoV-2 mutagenesis and escape from a neutralizing nanobody

N4-hydroxycytidine (NHC), the active compound of the drug Molnupiravir, is incorporated into SARS-CoV-2 RNA, causing false base pairing. The desired result is an "error catastrophe," but this bears the risk of mutated virus progeny. To address this experimentally, we propagated the initial SARS-CoV-2 strain in the presence of NHC. Deep sequencing revealed numerous NHC-induced mutations and host-cell-adapted virus variants. The presence of the neutralizing nanobody Re5D06 selected for immune escape mutations, in particular p.E484K and p.F490S, which are key mutations of the Beta/Gamma and Omicron-XBB strains, respectively. With NHC treatment, nanobody resistance occurred two passages earlier than without. Thus, within the limitations of this purely in vitro study, we conclude that the combined action of Molnupiravir and a spike-neutralizing antagonist leads to the rapid emergence of escape mutants. We propose caution use and supervision when using Molnupiravir, especially when patients are still at risk of spreading virus.

The race to understand immunopathology in COVID-19: Perspectives on the impact of quantitative approaches to understand within-host interactions

The COVID-19 pandemic has revealed the need for the increased integration of modelling and data analysis to public health, experimental, and clinical studies. Throughout the first two years of the pandemic, there has been a concerted effort to improve our understanding of the within-host immune response to the SARS-CoV-2 virus to provide better predictions of COVID-19 severity, treatment and vaccine development questions, and insights into viral evolution and the impacts of variants on immunopathology. Here we provide perspectives on what has been accomplished using quantitative methods, including predictive modelling, population genetics, machine learning, and dimensionality reduction techniques, in the first 26 months of the COVID-19 pandemic approaches, and where we go from here to improve our responses to this and future pandemics.

Analysis of 3.5 million SARS-CoV-2 sequences reveals unique mutational trends with consistent nucleotide and codon frequencies

BACKGROUND

Since the onset of the SARS-CoV-2 pandemic, bioinformatic analyses have been performed to understand the nucleotide and synonymous codon usage features and mutational patterns of the virus. However, comparatively few have attempted to perform such analyses on a considerably large cohort of viral genomes while organizing the plethora of available sequence data for a month-by-month analysis to observe changes over time. Here, we aimed to perform sequence composition and mutation analysis of SARS-CoV-2, separating sequences by gene, clade, and timepoints, and contrast the mutational profile of SARS-CoV-2 to other comparable RNA viruses.

METHODS

Using a cleaned, filtered, and pre-aligned dataset of over 3.5 million sequences downloaded from the GISAID database, we computed nucleotide and codon usage statistics, including calculation of relative synonymous codon usage values. We then calculated codon adaptation index (CAI) changes and a nonsynonymous/synonymous mutation ratio (dN/dS) over time for our dataset. Finally, we compiled information on the types of mutations occurring for SARS-CoV-2 and other comparable RNA viruses, and generated heatmaps showing codon and nucleotide composition at high entropy positions along the Spike sequence.

RESULTS

We show that nucleotide and codon usage metrics remain relatively consistent over the 32-month span, though there are significant differences between clades within each gene at various timepoints. CAI and dN/dS values vary substantially between different timepoints and different genes, with Spike gene on average showing both the highest CAI and dN/dS values. Mutational analysis showed that SARS-CoV-2 Spike has a higher proportion of nonsynonymous mutations than analogous genes in other RNA viruses, with nonsynonymous mutations outnumbering synonymous ones by up to 20:1. However, at several specific positions, synonymous mutations were overwhelmingly predominant.

CONCLUSIONS

Our multifaceted analysis covering both the composition and mutation signature of SARS-CoV-2 gives valuable insight into the nucleotide frequency and codon usage heterogeneity of SARS-CoV-2 over time, and its unique mutational profile compared to other RNA viruses.

L-shaped distribution of the relative substitution rate (c/μ) observed for SARS-COV-2's genome, inconsistent with the selectionist theory, the neutral theory and the nearly neutral theory but a near-neutral balanced selection theory: Implication on "neutralist-selectionist" debate

The genomic substitution rate (GSR) of SARS-CoV-2 exhibits a molecular clock feature and does not change under fluctuating environmental factors such as the infected human population (10°-107), vaccination etc. The molecular clock feature is believed to be inconsistent with the selectionist theory (ST). The GSR shows lack of dependence on the effective population size, suggesting Ohta's nearly neutral theory (ONNT) is not applicable to this virus. Big variation of the substitution rate within its genome is also inconsistent with Kimura's neutral theory (KNT). Thus, all three existing evolution theories fail to explain the evolutionary nature of this virus. In this paper, we proposed a Segment Substitution Rate Model (SSRM) under non-neutral selections and pointed out that a balanced mechanism between negative and positive selection of some segments that could also lead to the molecular clock feature. We named this hybrid mechanism as near-neutral balanced selection theory (NNBST) and examined if it was followed by SARS-CoV-2 using the three independent sets of SARS-CoV-2 genomes selected by the Nextstrain team. Intriguingly, the relative substitution rate of this virus exhibited an L-shaped probability distribution consisting with NNBST rather than Poisson distribution predicted by KNT or an asymmetric distribution predicted by ONNT in which nearly neutral sites are believed to be slightly deleterious only, or the distribution that is lack of nearly neutral sites predicted by ST. The time-dependence of the substitution rates for some segments and their correlation with the vaccination were observed, supporting NNBST. Our relative substitution rate method provides a tool to resolve the long standing "neutralist-selectionist" controversy. Implications of NNBST in resolving Lewontin's Paradox is also discussed.

Attenuation and Degeneration of SARS-CoV-2 Despite Adaptive Evolution

The evolution of severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) has followed similar trends as other RNA viruses, such as human immunodeficiency virus type 1 and the influenza A virus. Rapid initial diversification was followed by strong competition and a rapid succession of dominant variants. Host-initiated RNA editing has been the primary mechanism for introducing mutations. A significant number of mutations detrimental to viral replication have been quickly purged. Fixed mutations are mostly diversifying mutations selected for host adaptation and immune evasion, with the latter accounting for the majority of the mutations. However, immune evasion often comes at the cost of functionality, and thus, optimal functionality is still far from being accomplished. Instead, selection for antibody-escaping variants and accumulation of near-neutral mutations have led to suboptimal codon usage and reduced replicative capacity, as demonstrated in non-respiratory cell lines. Beneficial adaptation of the virus includes reduced infectivity in lung tissues and increased tropism for the upper airway, resulting in shorter incubation periods, milder diseases, and more efficient transmission between people.

A Computer Simulation of SARS-CoV-2 Mutation Spectra for Empirical Data Characterization and Analysis

It is very important to compute the mutation spectra, and simulate the intra-host mutation processes by sequencing data, which is not only for the understanding of SARS-CoV-2 genetic mechanism, but also for epidemic prediction, vaccine, and drug design. However, the current intra-host mutation analysis algorithms are not only inaccurate, but also the simulation methods are unable to quickly and precisely predict new SARS-CoV-2 variants generated from the accumulation of mutations. Therefore, this study proposes a novel accurate strand-specific SARS-CoV-2 intra-host mutation spectra computation method, develops an efficient and fast SARS-CoV-2 intra-host mutation simulation method based on mutation spectra, and establishes an online analysis and visualization platform. Our main results include: (1) There is a significant variability in the SARS-CoV-2 intra-host mutation spectra across different lineages, with the major mutations from G- > A, G- > C, G- > U on the positive-sense strand and C- > U, C- > G, C- > A on the negative-sense strand; (2) our mutation simulation reveals the simulation sequence starts to deviate from the base content percentage of Alpha-CoV/Delta-CoV after approximately 620 mutation steps; (3) 2019-NCSS provides an easy-to-use and visualized online platform for SARS-Cov-2 online analysis and mutation simulation.

On the Evolutionary Trajectory of SARS-CoV-2: Host Immunity as a Driver of Adaptation in RNA Viruses

Host immunity can exert a complex array of selective pressures on a pathogen, which can drive highly mutable RNA viruses towards viral escape. The plasticity of a virus depends on its rate of mutation, as well as the balance of fitness cost and benefit of mutations, including viral adaptations to the host's immune response. Since its emergence, SARS-CoV-2 has diversified into genetically distinct variants, which are characterised often by clusters of mutations that bolster its capacity to escape human innate and adaptive immunity. Such viral escape is well documented in the context of other pandemic RNA viruses such as the human immunodeficiency virus (HIV) and influenza virus. This review describes the selection pressures the host's antiviral immunity exerts on SARS-CoV-2 and other RNA viruses, resulting in divergence of viral strains into more adapted forms. As RNA viruses obscure themselves from host immunity, they uncover weak points in their own armoury that can inform more comprehensive, long-lasting, and potentially cross-protective vaccine coverage.

"Mutation blacklist" and "mutation whitelist" of SARS-CoV-2

Over the past two years, scientists throughout the world have completed more than 6 million SARS-CoV-2 genome sequences. Today, the number of SARS-CoV-2 genomes exceeds the total number of all other viral genomes. These genomes are a record of the evolution of SARS-CoV-2 in the human host, and provide information on the emergence of mutations. In this study, analysis of these sequenced genomes identified 296,728 de novo mutations (DNMs), and found that six types of base substitutions reached saturation in the sequenced genome population. Based on this analysis, a "mutation blacklist" of SARS-CoV-2 was compiled. The loci on the "mutation blacklist" are highly conserved, and these mutations likely have detrimental effects on virus survival, replication, and transmission. This information is valuable for SARS-CoV-2 research on gene function, vaccine design, and drug development. Through association analysis of DNMs and viral transmission rates, we identified 185 DNMs that positively correlated with the SARS-CoV-2 transmission rate, and these DNMs where classified as the "mutation whitelist" of SARS-CoV-2. The mutations on the "mutation whitelist" are beneficial for SARS-CoV-2 transmission and could therefore be used to evaluate the transmissibility of new variants. The occurrence of mutations and the evolution of viruses are dynamic processes. To more effectively monitor the mutations and variants of SARS-CoV-2, we built a SARS-CoV-2 mutation and variant monitoring and pre-warning system (MVMPS), which can monitor the occurrence and development of mutations and variants of SARS-CoV-2, as well as provide pre-warning for the prevention and control of SARS-CoV-2 (https://www.omicx.cn/). Additionally, this system could be used in real-time to update the "mutation whitelist" and "mutation blacklist" of SARS-CoV-2.

Prediction of Recurrent Mutations in SARS-CoV-2 Using Artificial Neural Networks

Predicting SARS-CoV-2 mutations is difficult, but predicting recurrent mutations driven by the host, such as those caused by host deaminases, is feasible. We used machine learning to predict which positions from the SARS-CoV-2 genome will hold a recurrent mutation and which mutations will be the most recurrent. We used data from April 2021 that we separated into three sets: a training set, a validation set, and an independent test set. For the test set, we obtained a specificity value of 0.69, a sensitivity value of 0.79, and an Area Under the Curve (AUC) of 0.8, showing that the prediction of recurrent SARS-CoV-2 mutations is feasible. Subsequently, we compared our predictions with updated data from January 2022, showing that some of the false positives in our prediction model become true positives later on. The most important variables detected by the model's Shapley Additive exPlanation (SHAP) are the nucleotide that mutates and RNA reactivity. This is consistent with the SARS-CoV-2 mutational bias pattern and the preference of some host deaminases for specific sequences and RNA secondary structures. We extend our investigation by analyzing the mutations from the variants of concern Alpha, Beta, Delta, Gamma, and Omicron. Finally, we analyzed amino acid changes by looking at the predicted recurrent mutations in the M-pro and spike proteins.

Evolutionary Pattern Comparisons of the SARS-CoV-2 Delta Variant in Countries/Regions with High and Low Vaccine Coverage

It has been argued that vaccine-breakthrough infections of SARS-CoV-2 would likely accelerate the emergence of novel variants with immune evasion. This study explored the evolutionary patterns of the Delta variant in countries/regions with relatively high and low vaccine coverage based on large-scale sequences. Our results showed that (i) the sequences were grouped into two clusters (L and R); the R cluster was dominant, its proportion increased over time and was higher in the high-vaccine-coverage areas; (ii) genetic diversities in the countries/regions with low vaccine coverage were higher than those in the ones with high vaccine coverage; (iii) unique mutations and co-mutations were detected in different countries/regions; in particular, common co-mutations were exhibited in highly occurring frequencies in the areas with high vaccine coverage and presented in increasing frequencies over time in the areas with low vaccine coverage; (iv) five sites on the S protein were under strong positive selection in different countries/regions, with three in non-C to U sites (I95T, G142D and T950N), and the occurring frequencies of I95T in high vaccine coverage areas were higher, while G142D and T950N were potentially immune-pressure-selected sites; and (v) mutation at the N⁶-methyladenosine site 4 on ORF7a (C27527T, P45L) was detected and might be caused by immune pressure. Our study suggested that certain variation differences existed between countries/regions with high and low vaccine coverage, but they were not likely caused by host immune pressure. We inferred that no extra immune pressures on SARS-CoV-2 were generated with high vaccine coverage, and we suggest promoting and strengthening the uptake of the COVID-19 vaccine worldwide, especially in less developed areas.

Massive-scale genomic analysis reveals SARS-CoV-2 mutation characteristics and evolutionary trends

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic resulted in significant societal costs. Hence, an in-depth understanding of SARS-CoV-2 virus mutation and its evolution will help determine the direction of the COVID-19 pandemic. In this study, we identified 296,728 de novo mutations in more than 2,800,000 high-quality SARS-CoV-2 genomes. All possible factors affecting the mutation frequency of SARS-CoV-2 in human hosts were analyzed, including zinc finger antiviral proteins, sequence context, amino acid change, and translation efficiency. As a result, we proposed that when adenine (A) and tyrosine (T) bases are in the context of AM (M stands for adenine or cytosine) or TA motif, A or T base has lower mutation frequency. Furthermore, we hypothesized that translation efficiency can affect the mutation frequency of the third position of the codon by the selection, which explains why SARS-CoV-2 prefers AT3 codons usage. In addition, we found a host-specific asymmetric dinucleotide mutation frequency in the SARS-CoV-2 genome, which provides a new basis for determining the origin of the SARS-CoV-2. Finally, we summarize all possible factors affecting mutation frequency and provide insights into the mutation characteristics and evolutionary trends of SARS-CoV-2.

Genome sequence diversity of SARS-CoV-2 obtained from clinical samples in Uzbekistan

Tracking temporal and spatial genomic changes and evolution of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are among the most urgent research topics worldwide, which help to elucidate the coronavirus disease 2019 (COVID-19) pathogenesis and the effect of deleterious variants. Our current study concentrates genetic diversity of SARS-CoV-2 variants in Uzbekistan and their associations with COVID-19 severity. Thirty-nine whole genome sequences (WGS) of SARS-CoV-2 isolated from PCR-positive patients from Tashkent, Uzbekistan for the period of July-August 2021, were generated and further subjected to further genomic analysis. Genome-wide annotations of clinical isolates from our study have revealed a total of 223 nucleotide-level variations including SNPs and 34 deletions at different positions throughout the entire genome of SARS-CoV-2. These changes included two novel mutations at the Nonstructural protein (Nsp) 13: A85P and Nsp12: Y479N, which were unreported previously. There were two groups of co-occurred substitution patterns: the missense mutations in the Spike (S): D614G, Open Reading Frame (ORF) 1b: P314L, Nsp3: F924, 5`UTR:C241T; Nsp3:P2046L and Nsp3:P2287S, and the synonymous mutations in the Nsp4:D2907 (C8986T), Nsp6:T3646A and Nsp14:A1918V regions, respectively. The “Nextstrain” clustered the largest number of SARS-CoV-2 strains into the Delta clade (n = 32; 82%), followed by two Alpha-originated (n = 4; 10,3%) and 20A (n = 3; 7,7%) clades. Geographically the Delta clade sample sequences were grouped into several clusters with the SARS-CoV genotypes from Russia, Denmark, USA, Egypt and Bangladesh. Phylogenetically, the Delta isolates in our study belong to the two main subclades 21A (56%) and 21J (44%). We found that females were more affected by 21A, whereas males by 21J variant (χ2 = 4.57; p ≤ 0.05, n = 32). The amino acid substitution ORF7a:P45L in the Delta isolates found to be significantly associated with disease severity. In conclusion, this study evidenced that Identified novel substitutions Nsp13: A85P and Nsp12: Y479N, have a destabilizing effect, while missense substitution ORF7a: P45L significantly associated with disease severity.

A Paradigm Shift in the Combination Changes of SARS-CoV-2 Variants and Increased Spread of Delta Variant (B.1.617.2) across the World

Since September 2020, the SARS-CoV-2 variants have gained their dominance worldwide, especially in Kenya, Italy, France, the UK, Turkey, Indonesia, India, Finland, Ireland, Singapore, Denmark, Germany, and Portugal. In this study, we developed a model on the frequency of delta variants across 28 countries (R²= 0.1497), displaying the inheritance of mutations during the generation of the delta variants with 123,526 haplotypes. The country-wise haplotype network showed the distribution of haplotypes in USA (10,174), Denmark (5,637), India (4,089), Germany (2,350), Netherlands (1,899), Sweden (1,791), Italy (1,720), France (1,293), Ireland (1,257), Belgium (1,207), Singapore (1,193), Portugal (1,184) and Spain (1,133). Our analysis shows the highest haplotype in Europe with 84% and the lowest in Australia with 0.00001%. A model of scatter plot was generated with a regression line which provided the estimated rate of mutation, including 24.048 substitutions yearly. Our study concluded that the high global prevalence of the delta variants is due to a high frequency of infectivity, supporting the paradigm shift of the viral variants.

Characteristic analysis of Omicron-included SARS-CoV-2 variants of concern

In view of the rapid development of the COVID-19 pandemic and SARS-CoV-2 mutation, we characterized the emerging SARS-CoV-2 variants of concern (VOCs) by both bioinformatics methods and experiments. The representative genomic sequences of SARS-CoV-2 VOCs were first downloaded from NCBI, including the prototypic strain, Alpha (B.1.1.7) strain, Beta (B.1.351) strain, Delta (B.1.617.2), and Omicron (B1.1.529) strain. Bioinformatics analysis revealed that the D614G mutation led to formation of a protruding spike (S) in the tertiary structure of spike protein, which could be responsible for the enhanced binding to angiotensin-converting enzyme 2 (ACE2) receptor. The epitope analysis further showed that the S protein antigenicity of the Omicron variant changed dramatically, which was possibly associated with its enhanced ability of immune escape. To verify the bioinformatics results, we performed experiments of pseudovirus infection and protein affinity assay. Notably, we found that the spike protein of Omicron variant showed the weakest infectivity and binding ability among all tested strains. Finally, we also proved this through virus infection experiments, and found that the cytotoxicity of Omicron seems to be not strong enough. The results in this study provide guidelines for prevention and control of COVID-19.

Decreased and Heterogeneous Neutralizing Antibody Responses Against RBD of SARS-CoV-2 Variants After mRNA Vaccination

The rapid spread of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) emerging variants raises concerns about their capacity to evade immune protection provided by natural infection or vaccination. The receptor-binding domain (RBD) of the viral spike protein is the major target of neutralizing antibodies, and viral variants accumulate mutations in this region. In this study, we determined the antibody neutralization capacity against the RBD of SARS-CoV-2 variants Alpha (B.1.1.7), Gamma (P.1), Epsilon (B.1.427), Kappa (B.1.617.1), and Delta (B.1.617.2) in a cohort of healthcare workers naturally infected or receiving COVID-19 mRNA vaccines from Moderna or Pfizer-BioNTech. We show that the five RBD variants displayed an augmented binding to ACE2 compared to the original Wuhan strain. The most significant increase was observed in variants Epsilon and Delta, containing mutation L452R. Using a flow cytometry cell-based assay, we found that SARS-CoV-2-infected subjects presented low levels of RBD-specific neutralizing antibodies against all variants analyzed, except Alpha. However, the neutralizing activity incremented considerably after a subsequent mRNA-vaccine dose, to levels significantly higher than those in naïve individuals receiving two vaccine doses. Importantly, we observed partially impaired neutralizing responses against most variants in fully vaccinated individuals. Variants Gamma and Kappa encompassing RBD E484K/Q mutations presented the highest neutralizing resistance. Furthermore, a wide heterogeneity in the magnitude of RBD-specific neutralizing responses against all tested SARS-CoV-2 variants following both mRNA vaccines was detected. Altogether, our findings provide important knowledge regarding SARS-CoV-2 vaccine-induced immunity, and should be very useful to guide future vaccination regimens and personalized vaccine approaches.

Mutation rate of SARS-CoV-2 and emergence of mutators during experimental evolution

Background and objectives

To understand how organisms evolve, it is fundamental to study how mutations emerge and establish. Here, we estimated the rate of mutation accumulation of SARS-CoV-2 in vitro and investigated the repeatability of its evolution when facing a new cell type but no immune or drug pressures.

Methodology

We performed experimental evolution with two strains of SARS-CoV-2, one carrying the originally described spike protein (CoV-2-D) and another carrying the D614G mutation that has spread worldwide (CoV-2-G). After 15 passages in Vero cells and whole genome sequencing, we characterized the spectrum and rate of the emerging mutations and looked for evidences of selection across the genomes of both strains.

Results

From the frequencies of the mutations accumulated, and excluding the genes with signals of selection, we estimate a spontaneous mutation rate of 1.3 × 10 ^-6 ± 0.2 × 10^-6 per-base per-infection cycle (mean across both lineages of SARS-CoV-2 ± 2SEM). We further show that mutation accumulation is larger in the CoV-2-D lineage and heterogeneous along the genome, consistent with the action of positive selection on the spike protein, which accumulated five times more mutations than the corresponding genomic average. We also observe the emergence of mutators in the CoV-2-G background, likely linked to mutations in the RNA-dependent RNA polymerase and/or in the error-correcting exonuclease protein.

Conclusions and implications

These results provide valuable information on how spontaneous mutations emerge in SARS-CoV-2 and on how selection can shape its genome toward adaptation to new environments. Lay Summary: Each time a virus replicates inside a cell, errors (mutations) occur. Here, via laboratory propagation in cells originally isolated from the kidney epithelium of African green monkeys, we estimated the rate at which the SARS-CoV-2 virus mutates-an important parameter for understanding how it can evolve within and across humans. We also confirm the potential of its Spike protein to adapt to a new environment and report the emergence of mutators-viral populations where mutations occur at a significantly faster rate.

Effects of Casirivimab/Imdevimab Monoclonal Antibody Treatment among Vaccinated Patients Infected by SARS-CoV-2 Delta Variant

There is a growing interest in using monoclonal antibodies (mAbs) in the early stages of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection to prevent disease progression. Little is known about the efficacy of mAbs against the delta variant of concern and its clinical presentations. We evaluated the effect of casirivimab/imdevimab treatment among five delta vaccine breakthrough patients. Symptomatic non-hospitalized vaccinated patients were submitted to nasopharyngeal swabs for the detection of SARS-CoV-2 and Next-Generation Sequencing (NGS). Blood analysis and chest Computed Tomography were also performed. A cocktail of casirivimab/imdevimab was administrated, and patients were monitored weekly. Clinical evolution was evaluated by the regression of the symptoms, negative results by real-time RT-PCR, and by the need of hospitalization: these aspects were considered as significant outcomes. In four cases, symptom reversion and viral load reduction were observed within 2 days and 7 days after mAbs treatment, respectively. Only one case, suffering from thymoma, was hospitalized 2 days later because of respiratory failure, which reverted within 18 days. mAbs treatment seems to be safe and effective against the delta variant and its clinical manifestations.

Continuous genomic diversification of long polynucleotide fragments drives the emergence of new SARS-CoV-2 variants of concern

Highly transmissible or immuno-evasive SARS-CoV-2 variants have intermittently emerged, resulting in repeated COVID-19 surges. With over 6 million SARS-CoV-2 genomes sequenced, there is unprecedented data to decipher the evolution of fitter SARS-CoV-2 variants. Much attention has been directed to studying the functional importance of specific mutations in the Spike protein, but there is limited knowledge of genomic signatures shared by dominant variants. Here, we introduce a method to quantify the genome-wide distinctiveness of polynucleotide fragments (3- to 240-mers) that constitute SARS-CoV-2 sequences. Compared to standard phylogenetic metrics and mutational load, the new metric provides improved separation between Variants of Concern (VOCs; Reference = 89, IQR: 65-108; Alpha = 166, IQR: 149-181; Beta 131, IQR: 114-149; Gamma = 164, IQR: 150-178; Delta = 235, IQR: 217-255; and Omicron = 459, IQR: 395-521). Omicron's high genomic distinctiveness may confer an advantage over prior VOCs and the recently emerged and highly mutated B.1.640.2 (IHU) lineage. Evaluation of 883 lineages highlights that genomic distinctiveness has increased over time (R ² = 0.37) and that VOCs score significantly higher than contemporary non-VOC lineages, with Omicron among the most distinctive lineages observed. This study demonstrates the value of characterizing SARS-CoV-2 variants by genome-wide polynucleotide distinctiveness and emphasizes the need to go beyond a narrow set of mutations at known sites on the Spike protein. The consistently higher distinctiveness of each emerging VOC compared to prior VOCs suggests that monitoring of genomic distinctiveness would facilitate rapid assessment of viral fitness.

Evolutionary history of the SARS-CoV-2 Gamma variant of concern (P.1): a perfect storm

Our goal was to describe in more detail the evolutionary history of Gamma and two derived lineages (P.1.1 and P.1.2), which are part of the arms race that SARS-CoV-2 wages with its host. A total of 4,977 sequences of the Gamma strain of SARS-CoV-2 from Brazil were analyzed. We detected 194 sites under positive selection in 12 genes/ORFs: Spike, N, M, E, ORF1a, ORF1b, ORF3, ORF6, ORF7a, ORF7b, ORF8, and ORF10. Some diagnostic sites for Gamma lacked a signature of positive selection in our study, but these were not fixed, apparently escaping the action of purifying selection. Our network analyses revealed branches leading to expanding haplotypes with sites under selection only detected when P.1.1 and P.1.2 were considered. The P.1.2 exclusive haplotype H_5 originated from a non-synonymous mutational step (H3509Y) in H_1 of ORF1a. The selected allele, 3509Y, represents an adaptive novelty involving ORF1a of P.1. Finally, we discuss how phenomena such as epistasis and antagonistic pleiotropy could limit the emergence of new alleles (and combinations thereof) in SARS-COV-2 lineages, maintaining infectivity in humans, while providing rapid response capabilities to face the arms race triggered by host immuneresponses.

Personal care formulations demonstrate virucidal efficacy against multiple SARS-CoV-2 variants of concern: Implications for hand hygiene and public health

Despite considerable progress being made on vaccine roll out, practicing proper hand hygiene has been advocated as a consistent precautionary intervention against the circulating and emerging variants of SARS-CoV-2. Two variants of concern, namely beta and delta, have been shown to exhibit enhanced transmissibility, high viral load, and ability to escape antibody-mediated neutralization. In this report we have empirically determined the efficacy of selected personal care formulations from Unilever in inactivating the beta and delta variants of SARS-CoV-2 under simulated real-life conditions. All the formulations demonstrated greater than 99.9% reduction in viral infective titres which is comparable to inactivation of the original strain of SARS-CoV-2 virus tested under the same conditions. Therefore, it can be concluded that well-designed personal care formulations when tested under consumer-centric conditions, and with proven efficacy against the parent strain of SARS-CoV-2 will continue to be effective against extant and emerging variants of SARS-CoV-2.