Ongoing global and regional adaptive evolution of SARS-CoV-2

Structural insight of cell surface sugars in viral infection and human milk glycans as natural antiviral substance

Viral infections are caused by the adhesion of viruses to host cell receptors, including sialylated glycans, glycosaminoglycans, and human blood group antigens (HBGAs). Atomic-level structural information on the interactions between viral particles or proteins with glycans can be determined to provide precise targets for designing antiviral drugs. Milk glycans, existing as free oligosaccharides or glycoconjugates, have attracted increasing attention; milk glycans protect infants against infectious diseases, particularly poorly manageable viral infections. Furthermore, several glycans containing structurally distinct sialic acid/fucose/sulfate modifications in human milk acting as a "receptor decoy" and serving as the natural antiviral library, could interrupt virus-receptor interaction in the first line of defense for viral infection. This review highlights the basis of virus-glycan interactions, presents specific glycan receptor binding by gastroenterovirus viruses, including norovirus, enteroviruses, and the breakthroughs in the studies on the antiviral properties of human milk glycans, and also elucidates the role of glycans in respiratory viruses infection. In addition, recent advances in methods for performing virus/viral protein-glycan interactions were reported. Finally, we discuss the prospects and challenges of the studies on the clinical application of human milk glycan for viral interventions.

Early mutational signatures and transmissibility of SARS-CoV-2 Gamma and Lambda variants in Chile

Genomic surveillance (GS) programmes were crucial in identifying and quantifying the mutating patterns of SARS-CoV-2 during the COVID-19 pandemic. In this work, we develop a Bayesian framework to quantify the relative transmissibility of different variants tailored for regions with limited GS. We use it to study the relative transmissibility of SARS-CoV-2 variants in Chile. Among the 3443 SARS-CoV-2 genomes collected between January and June 2021, where sampling was designed to be representative, the Gamma (P.1), Lambda (C.37), Alpha (B.1.1.7), B.1.1.348, and B.1.1 lineages were predominant. We found that Lambda and Gamma variants' reproduction numbers were 5% (95% CI: [1%, 14%]) and 16% (95% CI: [11%, 21%]) larger than Alpha's, respectively. Besides, we observed a systematic mutation enrichment in the Spike gene for all circulating variants, which strongly correlated with variants' transmissibility during the studied period (r = 0.93, p-value = 0.025). We also characterised the mutational signatures of local samples and their evolution over time and with the progress of vaccination, comparing them with those of samples collected in other regions worldwide. Altogether, our work provides a reliable method for quantifying variant transmissibility under subsampling and emphasises the importance of continuous genomic surveillance.

Modulation of biophysical properties of nucleocapsid protein in the mutant spectrum of SARS-CoV-2

Genetic diversity is a hallmark of RNA viruses and the basis for their evolutionary success. Taking advantage of the uniquely large genomic database of SARS-CoV-2, we examine the impact of mutations across the spectrum of viable amino acid sequences on the biophysical phenotypes of the highly expressed and multifunctional nucleocapsid protein. We find variation in the physicochemical parameters of its extended intrinsically disordered regions (IDRs) sufficient to allow local plasticity, but also observe functional constraints that similarly occur in related coronaviruses. In biophysical experiments with several N-protein species carrying mutations associated with major variants, we find that point mutations in the IDRs can have nonlocal impact and modulate thermodynamic stability, secondary structure, protein oligomeric state, particle formation, and liquid-liquid phase separation. In the Omicron variant, distant mutations in different IDRs have compensatory effects in shifting a delicate balance of interactions controlling protein assembly properties, and include the creation of a new protein-protein interaction interface in the N-terminal IDR through the defining P13L mutation. A picture emerges where genetic diversity is accompanied by significant variation in biophysical characteristics of functional N-protein species, in particular in the IDRs.

Complexity and Diversity of the Neurological Spectrum of SARS-CoV-2 over Three Waves of COVID-19

Background/Objectives: SARS-CoV-2 continually mutates, with five identified variants. Many neurological manifestations were observed during the COVID-19 pandemic, with differences between virus variants. The aim of this study is to assess the frequency and characteristics of neurological manifestations during COVID-19 in hospitalized patients over three waves in Poland with comparison and analysis correlation with the course of infection. Methods: This retrospective single-center study included 600 consecutive adults with confirmed COVID-19, hospitalized during 3 waves (pre-Delta, Delta and Omicron) in Poland. Demographic and clinical information and neurological manifestations were collected and compared across three periods. Results: The median age of the study group was 68, lower during the Delta wave. In the Omicron period, the disease severity at admission and inflammatory markers concentration were the lowest. Neurological manifestations were observed in 49%. The most common were altered mentation, headache, myalgia, mood disorder, ischemic stroke and encephalopathy. Smell and taste disturbances (STDs) were less frequent in the Omicron period. Neurological complications were predominant in the pre-Delta and Omicron periods. Ischemic stroke was observed more often in pre-Delta period. Altered mentation was related to higher severity at admission, worse lab test results, higher admission to ICU and mortality, while headache reduced mortality. Pre-existing dementia was related to higher mortality. Conclusions: Neurological manifestations of COVID-19 are frequent, with a lower rate of STDs in the Omicron period and more often cerebrovascular diseases in the pre-Delta period. Headache improves the course of COVID-19, while altered mentation, stroke and neurological comorbidities increase severity and mortality.

Some mechanistic underpinnings of molecular adaptations of SARS-COV-2 spike protein by integrating candidate adaptive polymorphisms with protein dynamics

We integrate evolutionary predictions based on the neutral theory of molecular evolution with protein dynamics to generate mechanistic insight into the molecular adaptations of the SARS-COV-2 spike (S) protein. With this approach, we first identified candidate adaptive polymorphisms (CAPs) of the SARS-CoV-2 S protein and assessed the impact of these CAPs through dynamics analysis. Not only have we found that CAPs frequently overlap with well-known functional sites, but also, using several different dynamics-based metrics, we reveal the critical allosteric interplay between SARS-CoV-2 CAPs and the S protein binding sites with the human ACE2 (hACE2) protein. CAPs interact far differently with the hACE2 binding site residues in the open conformation of the S protein compared to the closed form. In particular, the CAP sites control the dynamics of binding residues in the open state, suggesting an allosteric control of hACE2 binding. We also explored the characteristic mutations of different SARS-CoV-2 strains to find dynamic hallmarks and potential effects of future mutations. Our analyses reveal that Delta strain-specific variants have non-additive (i.e., epistatic) interactions with CAP sites, whereas the less pathogenic Omicron strains have mostly additive mutations. Finally, our dynamics-based analysis suggests that the novel mutations observed in the Omicron strain epistatically interact with the CAP sites to help escape antibody binding.

Concepts and methods for predicting viral evolution

The seasonal human influenza virus undergoes rapid evolution, leading to significant changes in circulating viral strains from year to year. These changes are typically driven by adaptive mutations, particularly in the antigenic epitopes, the regions of the viral surface protein haemagglutinin targeted by human antibodies. Here we describe a consistent set of methods for data-driven predictive analysis of viral evolution. Our pipeline integrates four types of data: (1) sequence data of viral isolates collected on a worldwide scale, (2) epidemiological data on incidences, (3) antigenic characterization of circulating viruses, and (4) intrinsic viral phenotypes. From the combined analysis of these data, we obtain estimates of relative fitness for circulating strains and predictions of clade frequencies for periods of up to one year. Furthermore, we obtain comparative estimates of protection against future viral populations for candidate vaccine strains, providing a basis for pre-emptive vaccine strain selection. Continuously updated predictions obtained from the prediction pipeline for influenza and SARS-CoV-2 are available on the website previr.app .

Concepts and methods for predicting viral evolution

The seasonal human influenza virus undergoes rapid evolution, leading to significant changes in circulating viral strains from year to year. These changes are typically driven by adaptive mutations, particularly in the antigenic epitopes, the regions of the viral surface protein haemagglutinin targeted by human antibodies. Here we describe a consistent set of methods for data-driven predictive analysis of viral evolution. Our pipeline integrates four types of data: (1) sequence data of viral isolates collected on a worldwide scale, (2) epidemiological data on incidences, (3) antigenic characterization of circulating viruses, and (4) intrinsic viral phenotypes. From the combined analysis of these data, we obtain estimates of relative fitness for circulating strains and predictions of clade frequencies for periods of up to one year. Furthermore, we obtain comparative estimates of protection against future viral populations for candidate vaccine strains, providing a basis for pre-emptive vaccine strain selection. Continuously updated predictions obtained from the prediction pipeline for influenza and SARS-CoV-2 are available on the website previr.app.

Prediction of Prospective Mutational Landscape of SARS-CoV-2 Spike ssRNA and Evolutionary Basis of Its Host Interaction

Booster doses are crucial against severe COVID-19, as rapid virus mutations and variant emergence prolong the pandemic crisis. The virus's quick evolution, short generation-time, and adaptive changes impact virulence and evolvability, helping predictions about variant of concerns' (VOCs') landscapes. Here, in this study, we used a new computational algorithm, to predict the mutational pattern in SARS-CoV-2 ssRNA, proteomics, structural identification, mutation stability, and functional correlation, as well as immune escape mechanisms. Interestingly, the sequence diversity of SARS Coronavirus-2 has demonstrated a predominance of G- > A and C- > U substitutions. The best validation statistics are explored here in seven homologous models of the expected mutant SARS-CoV-2 spike ssRNA and employed for hACE2 and IgG interactions. The interactome profile of SARS-CoV-2 spike with hACE2 and IgG revealed a strong correlation between phylogeny and divergence time. The systematic adaptation of SARS-CoV-2 spike ssRNA influences infectivity and immune escape. Data suggest higher propensity of Adenine rich sequence promotes MHC system avoidance, preferred by A-rich codons. Phylogenetic data revealed the evolution of SARS-CoV-2 lineages' epidemiology. Our findings may unveil processes governing the genesis of immune-resistant variants, prompting a critical reassessment of the coronavirus mutation rate and exploration of hypotheses beyond mechanical aspects.

Early detection of emerging viral variants through analysis of community structure of coordinated substitution networks

The emergence of viral variants with altered phenotypes is a public health challenge underscoring the need for advanced evolutionary forecasting methods. Given extensive epistatic interactions within viral genomes and known viral evolutionary history, efficient genomic surveillance necessitates early detection of emerging viral haplotypes rather than commonly targeted single mutations. Haplotype inference, however, is a significantly more challenging problem precluding the use of traditional approaches. Here, using SARS-CoV-2 evolutionary dynamics as a case study, we show that emerging haplotypes with altered transmissibility can be linked to dense communities in coordinated substitution networks, which become discernible significantly earlier than the haplotypes become prevalent. From these insights, we develop a computational framework for inference of viral variants and validate it by successful early detection of known SARS-CoV-2 strains. Our methodology offers greater scalability than phylogenetic lineage tracing and can be applied to any rapidly evolving pathogen with adequate genomic surveillance data.

Properties and Mechanisms of Deletions, Insertions, and Substitutions in the Evolutionary History of SARS-CoV-2

SARS-CoV-2 has accumulated many mutations since its emergence in late 2019. Nucleotide substitutions leading to amino acid replacements constitute the primary material for natural selection. Insertions, deletions, and substitutions appear to be critical for coronavirus's macro- and microevolution. Understanding the molecular mechanisms of mutations in the mutational hotspots (positions, loci with recurrent mutations, and nucleotide context) is important for disentangling roles of mutagenesis and selection. In the SARS-CoV-2 genome, deletions and insertions are frequently associated with repetitive sequences, whereas C>U substitutions are often surrounded by nucleotides resembling the APOBEC mutable motifs. We describe various approaches to mutation spectra analyses, including the context features of RNAs that are likely to be involved in the generation of recurrent mutations. We also discuss the interplay between mutations and natural selection as a complex evolutionary trend. The substantial variability and complexity of pipelines for the reconstruction of mutations and the huge number of genomic sequences are major problems for the analyses of mutations in the SARS-CoV-2 genome. As a solution, we advocate for the development of a centralized database of predicted mutations, which needs to be updated on a regular basis.

Some mechanistic underpinnings of molecular adaptations of SARS-COV-2 spike protein by integrating candidate adaptive polymorphisms with protein dynamics

We integrate evolutionary predictions based on the neutral theory of molecular evolution with protein dynamics to generate mechanistic insight into the molecular adaptations of the SARS-COV-2 Spike (S) protein. With this approach, we first identified Candidate Adaptive Polymorphisms (CAPs) of the SARS-CoV-2 Spike protein and assessed the impact of these CAPs through dynamics analysis. Not only have we found that CAPs frequently overlap with well-known functional sites, but also, using several different dynamics-based metrics, we reveal the critical allosteric interplay between SARS-CoV-2 CAPs and the S protein binding sites with the human ACE2 (hACE2) protein. CAPs interact far differently with the hACE2 binding site residues in the open conformation of the S protein compared to the closed form. In particular, the CAP sites control the dynamics of binding residues in the open state, suggesting an allosteric control of hACE2 binding. We also explored the characteristic mutations of different SARS-CoV-2 strains to find dynamic hallmarks and potential effects of future mutations. Our analyses reveal that Delta strain-specific variants have non-additive (i.e., epistatic) interactions with CAP sites, whereas the less pathogenic Omicron strains have mostly additive mutations. Finally, our dynamics-based analysis suggests that the novel mutations observed in the Omicron strain epistatically interact with the CAP sites to help escape antibody binding.

The most exposed regions of SARS-CoV-2 structural proteins are subject to strong positive selection and gene overlap may locally modify this behavior

The SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) pandemic that emerged in 2019 has been an unprecedented event in international science, as it has been possible to sequence millions of genomes, tracking their evolution very closely. This has enabled various types of secondary analyses of these genomes, including the measurement of their sequence selection pressure. In this work, we have been able to measure the selective pressure of all the described SARS-CoV-2 genes, even analyzed by sequence regions, and we show how this type of analysis allows us to separate the genes between those subject to positive selection (usually those that code for surface proteins or those exposed to the host immune system) and those subject to negative selection because they require greater conservation of their structure and function. We have also seen that when another gene with an overlapping reading frame appears within a gene sequence, the overlapping sequence between the two genes evolves under a stronger purifying selection than the average of the non-overlapping regions of the main gene. We propose this type of analysis as a useful tool for locating and analyzing all the genes of a viral genome when an adequate number of sequences are available.IMPORTANCEWe have analyzed the selection pressure of all severe acute respiratory syndrome coronavirus 2 genes by means of the nonsynonymous (Ka) to synonymous (Ks) substitution rate. We found that protein-coding genes are exposed to strong positive selection, especially in the regions of interaction with other molecules (host receptor and genome of the virus itself). However, overlapping coding regions are more protected and show negative selection. This suggests that this measure could be used to study viral gene function as well as overlapping genes.

Predicting the spread of SARS-CoV-2 variants: An artificial intelligence enabled early detection

During more than 3 years since its emergence, SARS-CoV-2 has shown great ability to mutate rapidly into diverse variants, some of which turned out to be very infectious and have spread throughout the world causing waves of infections. At this point, many countries have already experienced up to six waves of infections. Extensive academic work has focused on the development of models to predict the pandemic trajectory based on epidemiological data, but none has focused on predicting variant-specific spread. Moreover, important scientific literature analyzes the genetic evolution of SARS-CoV-2 variants and how it might functionally affect their infectivity. However, genetic attributes have not yet been incorporated into existing epidemiological modeling that aims to capture infection trajectory. Thus, this study leverages variant-specific genetic characteristics together with epidemiological information to systematically predict the future spread trajectory of newly detected variants. The study describes the analysis of 9.0 million SARS-CoV-2 genetic sequences in 30 countries and identifies temporal characteristic patterns of SARS-CoV-2 variants that caused significant infection waves. Using this descriptive analysis, a machine-learning-enabled risk assessment model has been developed to predict, as early as 1 week after their first detection, which variants are likely to constitute the new wave of infections in the following 3 months. The model's out-of-sample area under the curve (AUC) is 86.3% for predictions after 1 week and 90.8% for predictions after 2 weeks. The methodology described in this paper could contribute more broadly to the development of improved predictive models for variants of other infectious viruses.

An engineered bispecific nanobody in tetrameric secretory IgA format confers broad neutralization against SARS-CoV-1&2 and most variants

SARS-CoV-2, a type of respiratory virus, has exerted a great impact on global health and economy over the past three years. Antibody-based therapy was initially successful but later failed due to the accumulation of mutations in the spike protein of the virus. Strategies that enable antibodies to resist virus escape are therefore of great significance. Here, we engineer a bispecific SARS-CoV-2 neutralizing nanobody in secretory Immunoglobulin A (SIgA) format, named S2-3-IgA2m2, which shows broad and potent neutralization against SARS-CoV-1, SARS-CoV-2 and its variants of concern (VOCs) including XBB and BQ.1.1. S2-3-IgA2m2 is ∼1800-fold more potent than its parental IgG counterpart in neutralizing XBB. S2-3-IgA2m2 is stable in mouse lungs at least for three days when administrated by nasal delivery. In hamsters infected with BA.5, three intranasal doses of S2-3-IgA2m2 at 1 mg/kg significantly reduce viral RNA loads and completely eliminate infectious particles in the trachea and lungs. Notably, even at single dose of 1 mg/kg, S2-3-IgA2m2 prophylactically administered through the intranasal route drastically reduces airway viral RNA loads and infectious particles. This study provides an effective weapon combating SARS-CoV-2, proposes a new strategy overcoming the virus escape, and lays strategic reserves for rapid response to potential future outbreaks of "SARS-CoV-3".

Gut commensals and their metabolites in health and disease

Purpose of review

This review comprehensively discusses the role of the gut microbiome and its metabolites in health and disease and sheds light on the importance of a holistic approach in assessing the gut.

Recent findings

The gut microbiome consisting of the bacteriome, mycobiome, archaeome, and virome has a profound effect on human health. Gut dysbiosis which is characterized by perturbations in the microbial population not only results in gastrointestinal (GI) symptoms or conditions but can also give rise to extra-GI manifestations. Gut microorganisms also produce metabolites (short-chain fatty acids, trimethylamine, hydrogen sulfide, methane, and so on) that are important for several interkingdom microbial interactions and functions. They also participate in various host metabolic processes. An alteration in the microbial species can affect their respective metabolite concentrations which can have serious health implications. Effective assessment of the gut microbiome and its metabolites is crucial as it can provide insights into one's overall health.

Summary

Emerging evidence highlights the role of the gut microbiome and its metabolites in health and disease. As it is implicated in GI as well as extra-GI symptoms, the gut microbiome plays a crucial role in the overall well-being of the host. Effective assessment of the gut microbiome may provide insights into one's health status leading to more holistic care.

Sequencing of SARS-CoV-2 RNA Fragments in Wastewater Detects the Spread of New Variants during Major Events

The sequencing of SARS-CoV-2 RNA in wastewater is an unbiased method to detect the spread of emerging variants and to track regional infection dynamics, which is especially useful in case of limited testing and clinical sequencing. To test how major international events influence the spread of new variants we have sequenced SARS-CoV-2 RNA in the wastewater samples of Davos, Landquart, Lostallo, and St. Moritz in the Swiss canton of Grisons in the time around the international sports competitions in Davos and St. Moritz in December 2021, and additionally in May 2022 and January 2023 in Davos and St. Moritz during the World Economic Forum (WEF) in Davos. The prevalence of the variants identified from the wastewater sequencing data showed that the Omicron variant BA.1 had spread in Davos and St. Moritz during the international sporting events hosted there in December 2021. This spread was associated with an increase in case numbers, while it was not observed in Landquart and Lostallo. Another instance of new variant spread occurred during the WEF in January 2023, when the Omicron variant BA.2.75 arrived in Davos but not in St. Moritz. We can therefore conclude that major international events promote the spread of new variants in the respective host region, which has important implications for the protective measures that should be taken.

Cryo-electron microscopy in the fight against COVID-19-mechanism of virus entry

Cryogenic electron microscopy (cryo-EM) and electron tomography (cryo-ET) have become a critical tool for studying viral particles. Cryo-EM has enhanced our understanding of viral assembly and replication processes at a molecular resolution. Meanwhile, in situ cryo-ET has been used to investigate how viruses attach to and invade host cells. These advances have significantly contributed to our knowledge of viral biology. Particularly, prompt elucidations of structures of the SARS-CoV-2 spike protein and its variants have directly impacted the development of vaccines and therapeutic measures. This review discusses the progress made by cryo-EM based technologies in comprehending the severe acute respiratory syndrome coronavirus-2 (SARS-Cov-2), the virus responsible for the devastating global COVID-19 pandemic in 2020 with focus on the SARS-CoV-2 spike protein and the mechanisms of the virus entry and replication.

A bioengineered pseudovirus nanoparticle displaying SARS-CoV 2 RBD fully protects mice from mortality and weight loss caused by SARS-CoV 2 challenge

The COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused considerable morbidity and mortality worldwide. Although authorized COVID-19 vaccines have been shown highly effective, their significantly lower efficacy against heterologous variants, and the rapid decrease of vaccine-elicited immunity raises serious concerns, calling for improved vaccine tactics. To this end, a pseudovirus nanoparticle (PVNP) displaying the receptor binding domains (RBDs) of SARS-CoV-2 spike, named S-RBD, was generated and shown it as a promising COVID-19 vaccine candidate. The S-RBD PVNP was produced using both prokaryotic and eukaryotic systems. A 3D structural model of the S-RBD PVNPs was built based on the known structures of the S60 particle and RBDs, revealing an S60 particle-based icosahedral symmetry with multiple surface-displayed RBDs that retain authentic conformations and receptor-binding functions. The PVNP is highly immunogenic, eliciting high titers of RBD-specific IgG and neutralizing antibodies in mice. The S-RBD PVNP demonstrated exceptional protective efficacy, and fully (100%) protected K18-hACE2 mice from mortality and weight loss after a lethal SARS-CoV-2 challenge, supporting the S-RBD PVNPs as a potent COVID-19 vaccine candidate. By contrast, a PVNP displaying the N-terminal domain (NTD) of SARS-CoV-2 spike exhibited only 50% protective efficacy. Since the RBD antigens of our PVNP vaccine are adjustable as needed to address the emergence of future variants, and various S-RBD PVNPs can be combined as a cocktail vaccine for broad efficacy, these non-replicating PVNPs offer a flexible platform for a safe, effective COVID-19 vaccine with minimal manufacturing cost and time.

Paired associated SARS-CoV-2 spike variable positions: a network analysis approach to emerging variants

Amino acids in variable positions of proteins may be correlated, with potential structural and functional implications. Here, we apply exact tests of independence in R × C contingency tables to examine noise-free associations between variable positions of the SARS-CoV-2 spike protein, using as a paradigm sequences from Greece deposited in GISAID (N = 6,683/1,078 full length) for the period 29 February 2020 to 26 April 2021 that essentially covers the first three pandemic waves. We examine the fate and complexity of these associations by network analysis, using associated positions (exact P ≤ 0.001 and Average Product Correction ≥ 2) as links and the corresponding positions as nodes. We found a temporal linear increase of positional differences and a gradual expansion of the number of position associations over time, represented by a temporally evolving intricate web, resulting in a non-random complex network of 69 nodes and 252 links. Overconnected nodes corresponded to the most adapted variant positions in the population, suggesting a direct relation between network degree and position functional importance. Modular analysis revealed 25 k-cliques comprising 3 to 11 nodes. At different k-clique resolutions, one to four communities were formed, capturing epistatic associations of circulating variants (Alpha, Beta, B.1.1.318), but also Delta, which dominated the evolutionary landscape later in the pandemic. Cliques of aminoacidic positional associations tended to occur in single sequences, enabling the recognition of epistatic positions in real-world virus populations. Our findings provide a novel way of understanding epistatic relationships in viral proteins with potential applications in the design of virus control procedures. IMPORTANCE Paired positional associations of adapted amino acids in virus proteins may provide new insights for understanding virus evolution and variant formation. We investigated potential intramolecular relationships between variable SARS-CoV-2 spike positions by exact tests of independence in R × C contingency tables, having applied Average Product Correction (APC) to eliminate background noise. Associated positions (exact P ≤ 0.001 and APC ≥ 2) formed a non-random, epistatic network of 25 cliques and 1-4 communities at different clique resolutions, revealing evolutionary ties between variable positions of circulating variants and a predictive potential of previously unknown network positions. Cliques of different sizes represented theoretical combinations of changing residues in sequence space, allowing the identification of significant aminoacidic combinations in single sequences of real-world populations. Our analytic approach that links network structural aspects to mutational aminoacidic combinations in the spike sequence population offers a novel way to understand virus epidemiology and evolution.

Evolution of transient RNA structure-RNA polymerase interactions in respiratory RNA virus genomes

RNA viruses are important human pathogens that cause seasonal epidemics and occasional pandemics. Examples are influenza A viruses (IAV) and coronaviruses (CoV). When emerging IAV and CoV spill over to humans, they adapt to evade immune responses and optimize their replication and spread in human cells. In IAV, adaptation occurs in all viral proteins, including the viral ribonucleoprotein (RNP) complex. RNPs consist of a copy of the viral RNA polymerase, a double-helical coil of nucleoprotein, and one of the eight segments of the IAV RNA genome. The RNA segments and their transcripts are partially structured to coordinate the packaging of the viral genome and modulate viral mRNA translation. In addition, RNA structures can affect the efficiency of viral RNA synthesis and the activation of host innate immune response. Here, we investigated if RNA structures that modulate IAV replication processivity, so-called template loops (t-loops), vary during the adaptation of pandemic and emerging IAV to humans. Using cell culture-based replication assays and in silico sequence analyses, we find that the sensitivity of the IAV H3N2 RNA polymerase to t-loops increased between isolates from 1968 and 2017, whereas the total free energy of t-loops in the IAV H3N2 genome was reduced. This reduction is particularly prominent in the PB1 gene. In H1N1 IAV, we find two separate reductions in t-loop free energy, one following the 1918 pandemic and one following the 2009 pandemic. No destabilization of t-loops is observed in the influenza B virus genome, whereas analysis of SARS-CoV-2 isolates reveals destabilization of viral RNA structures. Overall, we propose that a loss of free energy in the RNA genome of emerging respiratory RNA viruses may contribute to the adaption of these viruses to the human population.

Evolution of transient RNA structure-RNA polymerase interactions in respiratory RNA virus genomes

RNA viruses are important human pathogens that cause seasonal epidemics and occasional pandemics. Examples are influenza A viruses (IAV) and coronaviruses (CoV). When emerging IAV and CoV spill over to humans, they adapt to evade immune responses and optimize their replication and spread in human cells. In IAV, adaptation occurs in all viral proteins, including the viral ribonucleoprotein (RNP) complex. RNPs consists of a copy of the viral RNA polymerase, a double-helical coil of nucleoprotein, and one of the eight segments of the IAV RNA genome. The RNA segments and their transcripts are partially structured to coordinate the packaging of the viral genome and modulate viral mRNA translation. In addition, RNA structures can affect the efficiency of viral RNA synthesis and the activation of host innate immune response. Here, we investigated if RNA structures that modulate IAV replication processivity, so called template loops (t-loops), vary during the adaptation of pandemic and emerging IAV to humans. Using cell culture-based replication assays and in silico sequence analyses, we find that the sensitivity of the IAV H3N2 RNA polymerase to t-loops increased between isolates from 1968 and 2017, whereas the total free energy of t-loops in the IAV H3N2 genome was reduced. This reduction is particularly prominent in the PB1 gene. In H1N1 IAV, we find two separate reductions in t-loop free energy, one following the 1918 pandemic and one following the 2009 pandemic. No destabilization of t-loops is observed in the IBV genome, whereas analysis of SARS-CoV-2 isolates reveals destabilization of viral RNA structures. Overall, we propose that a loss of free energy in the RNA genome of emerging respiratory RNA viruses may contribute to the adaption of these viruses to the human population.

Long-range linkage effects in adapting sexual populations

In sexual populations, closely-situated genes have linked evolutionary fates, while genes spaced far in genome are commonly thought to evolve independently due to recombination. In the case where evolution depends essentially on supply of new mutations, this assumption has been confirmed by mathematical modeling. Here I examine it in the case of pre-existing genetic variation, where mutation is not important. A haploid population with [Formula: see text] genomes, [Formula: see text] loci, a fixed selection coefficient, and a small initial frequency of beneficial alleles [Formula: see text] is simulated by a Monte-Carlo algorithm. When the number of loci, L, is larger than a critical value of [Formula: see text] simulation demonstrates a host of linkage effects that decrease neither with the distance between loci nor the number of recombination crossovers. Due to clonal interference, the beneficial alleles become extinct at a fraction of loci [Formula: see text]. Due to a genetic background effect, the substitution rate varies broadly between loci, with the fastest value exceeding the one-locus limit by the factor of [Formula: see text] Thus, the far-situated parts of a long genome in a sexual population do not evolve as independent blocks. A potential link between these findings and the emergence of new Variants of Concern of SARS-CoV-2 is discussed.

Ghosts of the past: Elemental composition, biosynthesis reactions and thermodynamic properties of Zeta P.2, Eta B.1.525, Theta P.3, Kappa B.1.617.1, Iota B.1.526, Lambda C.37 and Mu B.1.621 variants of SARS-CoV-2

From the perspectives of molecular biology, genetics and biothermodynamics, SARS-CoV-2 is the among the best characterized viruses. Research on SARS-CoV-2 has shed a new light onto driving forces and molecular mechanisms of viral evolution. This paper reports results on empirical formulas, biosynthesis reactions and thermodynamic properties of biosynthesis (multiplication) for the Zeta P.2, Eta B.1.525, Theta P.3, Kappa B.1.617.1, Iota B.1.526, Lambda C.37 and Mu B.1.621 variants of SARS-CoV-2. Thermodynamic analysis has shown that the physical driving forces for evolution of SARS-CoV-2 are Gibbs energy of biosynthesis and Gibbs energy of binding. The driving forces have led SARS-CoV-2 through the evolution process from the original Hu-1 to the newest variants in accordance with the expectations of the evolution theory.

Transmission of SARS-CoV-2 in free-ranging white-tailed deer in the United States

SARS-CoV-2 is a zoonotic virus with documented bi-directional transmission between people and animals. Transmission of SARS-CoV-2 from humans to free-ranging white-tailed deer (Odocoileus virginianus) poses a unique public health risk due to the potential for reservoir establishment where variants may persist and evolve. We collected 8,830 respiratory samples from free-ranging white-tailed deer across Washington, D.C. and 26 states in the United States between November 2021 and April 2022. We obtained 391 sequences and identified 34 Pango lineages including the Alpha, Gamma, Delta, and Omicron variants. Evolutionary analyses showed these white-tailed deer viruses originated from at least 109 independent spillovers from humans, which resulted in 39 cases of subsequent local deer-to-deer transmission and three cases of potential spillover from white-tailed deer back to humans. Viruses repeatedly adapted to white-tailed deer with recurring amino acid substitutions across spike and other proteins. Overall, our findings suggest that multiple SARS-CoV-2 lineages were introduced, became enzootic, and co-circulated in white-tailed deer.

The Sea Cucumber Thyonella gemmata Contains a Low Anticoagulant Sulfated Fucan with High Anti-SARS-CoV-2 Actions against Wild-Type and Delta Variants

In this work, we isolated two new sulfated glycans from the body wall of the sea cucumber Thyonella gemmata: one fucosylated chondroitin sulfate (TgFucCS) (17.5 ± 3.5% kDa) and one sulfated fucan (TgSF) (383.3 ± 2.1% kDa). NMR results showed the TgFucCS backbone composed of [→3)-β-N-acetylgalactosamine-(1→4)-β-glucuronic acid-(1→] with 70% 4-sulfated and 30% 4,6-disulfated GalNAc units and one-third of the GlcA units decorated at the C3 position with branching α-fucose (Fuc) units either 4-sulfated (65%) or 2,4-disulfated (35%) and the TgSF structure composed of a tetrasaccharide repeating unit of [→3)-α-Fuc2,4S-(1→2)-α-Fuc4S-(1→3)-α-Fuc2S-(1→3)-α-Fuc2S-(1→]n. Inhibitory properties of TgFucCS and TgSF were investigated using SARS-CoV-2 pseudovirus coated with S-proteins of the wild-type (Wuhan-Hu-1) or the delta (B.1.617.2) strains and in four different anticoagulant assays, comparatively with unfractionated heparin. Molecular binding to coagulation (co)-factors and S-proteins was investigated by competitive surface plasmon resonance spectroscopy. Among the two sulfated glycans tested, TgSF showed significant anti-SARS-CoV-2 activity against both strains together with low anticoagulant properties, indicating a good candidate for future studies in drug development.

Evolutionary implications of SARS-CoV-2 vaccination for the future design of vaccination strategies

Once the first SARS-CoV-2 vaccine became available, mass vaccination was the main pillar of the public health response to the COVID-19 pandemic. It was very effective in reducing hospitalizations and deaths. Here, we discuss the possibility that mass vaccination might accelerate SARS-CoV-2 evolution in antibody-binding regions compared to natural infection at the population level. Using the evidence of strong genetic variation in antibody-binding regions and taking advantage of the similarity between the envelope proteins of SARS-CoV-2 and influenza, we assume that immune selection pressure acting on these regions of the two viruses is similar. We discuss the consequences of this assumption for SARS-CoV-2 evolution in light of mathematical models developed previously for influenza. We further outline the implications of this phenomenon, if our assumptions are confirmed, for the future design of SARS-CoV-2 vaccination strategies.

Highly Networked SARS-CoV-2 Peptides Elicit T Cell Responses with Enhanced Specificity

Identifying SARS-CoV-2-specific T cell epitope-derived peptides is critical for the development of effective vaccines and measuring the duration of specific SARS-CoV-2 cellular immunity. In this regard, we previously identified T cell epitope-derived peptides within topologically and structurally essential regions of SARS-CoV-2 spike and nucleocapsid proteins by applying an immunoinformatics pipeline. In this study, we selected 30 spike- and nucleocapsid-derived peptides and assessed whether these peptides induce T cell responses and avoid major mutations found in SARS-CoV-2 variants of concern. Our peptide pool was highly specific, with only a single peptide driving cross-reactivity in people unexposed to SARS-COV-2, and immunogenic, inducing a polyfunctional response in CD4+ and CD8+ T cells from COVID-19 recovered individuals. All peptides were immunogenic and individuals recognized broad and diverse peptide repertoires. Moreover, our peptides avoided most mutations/deletions associated with all four SARS-CoV-2 variants of concern while retaining their physicochemical properties even when genetic changes are introduced. This study contributes to an evolving definition of individual CD4+ and CD8+ T cell epitopes that can be used for specific diagnostic tools for SARS-CoV-2 T cell responses and is relevant to the development of variant-resistant and durable T cell-stimulating vaccines.

Significant Broad-Spectrum Antiviral Activity of Bi121 against Different Variants of SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has so far infected 762 million people with over 6.9 million deaths worldwide. Broad-spectrum viral inhibitors that block the initial stages of infection by reducing virus binding and proliferation, thereby reducing disease severities, are still an unmet global medical need. We studied Bi121, which is a standardized polyphenolic-rich compound isolated from Pelargonium sidoides, against recombinant vesicular stomatitis virus (rVSV)-pseudotyped SARS-CoV-2S (mutations in the spike protein) of six different variants of SARS-CoV-2. Bi121 was effective at neutralizing all six rVSV-ΔG-SARS-CoV-2S variants. The antiviral activity of Bi121 was also assessed against SARS-CoV-2 variants (USA WA1/2020, Hongkong/VM20001061/2020, B.1.167.2 (Delta), and Omicron) in Vero cells and HEK-ACE2 cell lines using RT-qPCR and plaque assays. Bi121 showed significant antiviral activity against all the four SARS-CoV-2 variants tested, suggesting a broad-spectrum activity. Bi121 fractions generated using HPLC showed antiviral activity in three fractions out of eight against SARS-CoV-2. The dominant compound identified in all three fractions using LC/MS/MS analysis was Neoilludin B. In silico structural modeling studies with Neoilludin B showed that it has a novel RNA-intercalating activity toward RNA viruses. In silico findings and the antiviral activity of this compound against several SARS-CoV-2 variants support further evaluation as a potential treatment of COVID-19.

Web Resources for SARS-CoV-2 Genomic Database, Annotation, Analysis and Variant Tracking

The SARS-CoV-2 genomic data continue to grow, providing valuable information for researchers and public health officials. Genomic analysis of these data sheds light on the transmission and evolution of the virus. To aid in SARS-CoV-2 genomic analysis, many web resources have been developed to store, collate, analyze, and visualize the genomic data. This review summarizes web resources used for the SARS-CoV-2 genomic epidemiology, covering data management and sharing, genomic annotation, analysis, and variant tracking. The challenges and further expectations for these web resources are also discussed. Finally, we highlight the importance and need for continued development and improvement of related web resources to effectively track the spread and understand the evolution of the virus.

Divergent mutations of Delta and Omicron variants: key players behind differential viral attributes across the COVID-19 waves

The third SARS-CoV-2 pandemic wave causing Omicron variant has comparatively higher replication rate and transmissibility than the second wave-causing Delta variant. The exact mechanism behind the differential properties of Delta and Omicron in respect to infectivity and virulence is not properly understood yet. This study reports the analysis of different mutations within the receptor binding domain (RBD) of spike glycoprotein and non-structural protein (nsp) of Delta and Omicron strains. We have used computational studies to evaluate the properties of Delta and Omicron variants in this work. Q498R, Q493R and S375F mutations of RBD showed better docking scores for Omicron compared to Delta variant of SARS-CoV-2, whereas nsp3_L1266I with PARP15 (7OUX), nsp3_L1266I with PARP15 (7OUX), and nsp6_G107 with ISG15 (1Z2M) showed significantly higher docking score. The findings of the present study might be helpful to reveal the probable cause of relatively milder form of COVID-19 disease manifested by Omicron in comparison to Delta variant of SARS-CoV-2 virus.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13337-023-00823-0.

The changing health impact of vaccines in the COVID-19 pandemic: A modeling study

Much of the world's population had already been infected with COVID-19 by the time the Omicron variant emerged at the end of 2021, but the scale of the Omicron wave was larger than any that had come before or has happened since, and it left a global imprinting of immunity that changed the COVID-19 landscape. In this study, we simulate a South African population and demonstrate how population-level vaccine effectiveness and efficiency changed over the course of the first 2 years of the pandemic. We then introduce three hypothetical variants and evaluate the impact of vaccines with different properties. We find that variant-chasing vaccines have a narrow window of dominating pre-existing vaccines but that a variant-chasing vaccine strategy may have global utility, depending on the rate of spread from setting to setting. Next-generation vaccines might be able to overcome uncertainty in pace and degree of viral evolution.

S:D614G and S:H655Y are gateway mutations that act epistatically to promote SARS-CoV-2 variant fitness

SARS-CoV-2 variants bearing complex combinations of mutations that confer increased transmissibility, COVID-19 severity, and immune escape, were first detected after S:D614G had gone to fixation, and likely originated during persistent infection of immunocompromised hosts. To test the hypothesis that S:D614G facilitated emergence of such variants, S:D614G was reverted to the ancestral sequence in the context of sequential Spike sequences from an immunocompromised individual, and within each of the major SARS-CoV-2 variants of concern. In all cases, infectivity of the S:D614G revertants was severely compromised. The infectivity of atypical SARS-CoV-2 lineages that propagated in the absence of S:D614G was found to be dependent upon either S:Q613H or S:H655Y. Notably, Gamma and Omicron variants possess both S:D614G and S:H655Y, each of which contributed to infectivity of these variants. Among sarbecoviruses, S:Q613H, S:D614G, and S:H655Y are only detected in SARS-CoV-2, which is also distinguished by a polybasic S1/S2 cleavage site. Genetic and biochemical experiments here showed that S:Q613H, S:D614G, and S:H655Y each stabilize Spike on virions, and that they are dispensable in the absence of S1/S2 cleavage, consistent with selection of these mutations by the S1/S2 cleavage site. CryoEM revealed that either S:D614G or S:H655Y shift the Spike receptor binding domain (RBD) towards the open conformation required for ACE2-binding and therefore on pathway for infection. Consistent with this, an smFRET reporter for RBD conformation showed that both S:D614G and S:H655Y spontaneously adopt the conformation that ACE2 induces in the parental Spike. Data from these orthogonal experiments demonstrate that S:D614G and S:H655Y are convergent adaptations to the polybasic S1/S2 cleavage site which stabilize S1 on the virion in the open RBD conformation and act epistatically to promote the fitness of variants bearing complex combinations of clinically significant mutations.

Rapid assembly of SARS-CoV-2 genomes reveals attenuation of the Omicron BA.1 variant through NSP6

Although the SARS-CoV-2 Omicron variant (BA.1) spread rapidly across the world and effectively evaded immune responses, its viral fitness in cell and animal models was reduced. The precise nature of this attenuation remains unknown as generating replication-competent viral genomes is challenging because of the length of the viral genome (~30 kb). Here, we present a plasmid-based viral genome assembly and rescue strategy (pGLUE) that constructs complete infectious viruses or noninfectious subgenomic replicons in a single ligation reaction with >80% efficiency. Fully sequenced replicons and infectious viral stocks can be generated in 1 and 3 weeks, respectively. By testing a series of naturally occurring viruses as well as Delta-Omicron chimeric replicons, we show that Omicron nonstructural protein 6 harbors critical attenuating mutations, which dampen viral RNA replication and reduce lipid droplet consumption. Thus, pGLUE overcomes remaining barriers to broadly study SARS-CoV-2 replication and reveals deficits in nonstructural protein function underlying Omicron attenuation.

Vaccines Alone Cannot Slow the Evolution of SARS-CoV-2

The rapid emergence of immune-evading viral variants of SARS-CoV-2 calls into question the practicality of a vaccine-only public-health strategy for managing the ongoing COVID-19 pandemic. It has been suggested that widespread vaccination is necessary to prevent the emergence of future immune-evading mutants. Here, we examined that proposition using stochastic computational models of viral transmission and mutation. Specifically, we looked at the likelihood of emergence of immune escape variants requiring multiple mutations and the impact of vaccination on this process. Our results suggest that the transmission rate of intermediate SARS-CoV-2 mutants will impact the rate at which novel immune-evading variants appear. While vaccination can lower the rate at which new variants appear, other interventions that reduce transmission can also have the same effect. Crucially, relying solely on widespread and repeated vaccination (vaccinating the entire population multiple times a year) is not sufficient to prevent the emergence of novel immune-evading strains, if transmission rates remain high within the population. Thus, vaccines alone are incapable of slowing the pace of evolution of immune evasion, and vaccinal protection against severe and fatal outcomes for COVID-19 patients is therefore not assured.

A conserved oligomerization domain in the disordered linker of coronavirus nucleocapsid proteins

The nucleocapsid (N-)protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has a key role in viral assembly and scaffolding of the viral RNA. It promotes liquid-liquid phase separation (LLPS), forming dense droplets that support the assembly of ribonucleoprotein particles with as-of-yet unknown macromolecular architecture. Combining biophysical experiments, molecular dynamics simulations, and analysis of the mutational landscape, we describe a heretofore unknown oligomerization site that contributes to LLPS, is required for the assembly of higher-order protein-nucleic acid complexes, and is coupled to large-scale conformational changes of N-protein upon nucleic acid binding. The self-association interface is located in a leucine-rich sequence of the intrinsically disordered linker between N-protein folded domains and formed by transient helices assembling into trimeric coiled-coils. Critical residues stabilizing hydrophobic and electrostatic interactions between adjacent helices are highly protected against mutations in viable SARS-CoV-2 genomes, and the oligomerization motif is conserved across related coronaviruses, thus presenting a target for antiviral therapeutics.

Within-host genetic diversity of SARS-CoV-2 lineages in unvaccinated and vaccinated individuals

Viral and host factors can shape SARS-CoV-2 evolution. However, little is known about lineage-specific and vaccination-specific mutations that occur within individuals. Here, we analysed deep sequencing data from 2,820 SARS-CoV-2 respiratory samples with different viral lineages to describe the patterns of within-host diversity under different conditions, including vaccine-breakthrough infections. In unvaccinated individuals, variant of Concern (VOC) Alpha, Delta, and Omicron respiratory samples were found to have higher within-host diversity and were under neutral to purifying selection at the full genome level compared to non-VOC SARS-CoV-2. Breakthrough infections in 2-dose or 3-dose Comirnaty and CoronaVac vaccinated individuals did not increase levels of non-synonymous mutations and did not change the direction of selection pressure. Vaccine-induced antibody or T cell responses did not appear to have significant impact on within-host SARS-CoV-2 sequence diversification. Our findings suggest that vaccination does not increase exploration of SARS-CoV-2 protein sequence space and may not facilitate emergence of viral variants.

Faster SARS-CoV-2 sequence validation and annotation for GenBank using VADR

In 2020 and 2021, >1.5 million SARS-CoV-2 sequences were submitted to GenBank. The initial version (v1.0) of the VADR (Viral Annotation DefineR) software package that GenBank uses to automatically validate and annotate incoming viral sequences is too slow and memory intensive to process many thousands of SARS-CoV-2 sequences in a reasonable amount of time. Additionally, long stretches of ambiguous N nucleotides, which are common in many SARS-CoV-2 sequences, prevent VADR from accurate validation and annotation. VADR has been updated to more accurately and rapidly annotate SARS-CoV-2 sequences. Stretches of consecutive Ns are now identified and temporarily replaced with expected nucleotides to facilitate processing, and the slowest steps have been overhauled using blastn and glsearch, increasing speed, reducing the memory requirement from 64Gb to 2Gb per thread, and allowing simple, coarse-grained parallelization on multiple processors per host. VADR is now nearly 1000 times faster than it was in early 2020 SARS-CoV-2 sequence processing. It has been used to screen and annotate more than 1.5 million SARS-CoV-2 sequences since June 2020, and it is now efficient enough to cope with the current rate of hundreds of thousands of submitted sequences per month.

Genetic variety of ORF3a shapes SARS-CoV-2 fitness through modulation of lipid droplet

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection leads to the accumulation of lipid droplets (LD), the central hubs of the lipid metabolism, in vitro or in type II pneumocytes and monocytes from coronavirus disease 19 (COVID-19) patients and blockage of LD formation by specific inhibitors impedes SARS-CoV-2 replication. Here, we showed that ORF3a is necessary and sufficient to trigger LD accumulation during SARS-CoV-2 infection, leading to efficient virus replication. Although highly mutated during evolution, ORF3a-mediated LD modulation is conserved in most SARS-CoV-2 variants except the Beta strain and is a major difference between SARS-CoV and SARS-CoV-2 that depends on the genetic variations on the amino acid position 171, 193, and 219 of ORF3a. Importantly, T223I substitution in recent Omicron strains (BA.2-BF.8) impairs ORF3a-Vps39 association and LD accumulation, leading to less efficient replication and potentially contributing to lower pathogenesis of the Omicron strains. Our work characterized how SARS-CoV-2 modulates cellular lipid homeostasis to benefit its replication during virus evolution, making ORF3a-LD axis a promising drug target for the treatment of COVID-19.

Global landscape of SARS-CoV-2 mutations and conserved regions

BACKGROUND

At the end of December 2019, a novel strain of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) disease (COVID-19) has been identified in Wuhan, a central city in China, and then spread to every corner of the globe. As of October 8, 2022, the total number of COVID-19 cases had reached over 621 million worldwide, with more than 6.56 million confirmed deaths. Since SARS-CoV-2 genome sequences change due to mutation and recombination, it is pivotal to surveil emerging variants and monitor changes for improving pandemic management.

METHODS

10,287,271 SARS-CoV-2 genome sequence samples were downloaded in FASTA format from the GISAID databases from February 24, 2020, to April 2022. Python programming language (version 3.8.0) software was utilized to process FASTA files to identify variants and sequence conservation. The NCBI RefSeq SARS-CoV-2 genome (accession no. NC_045512.2) was considered as the reference sequence.

RESULTS

Six mutations had more than 50% frequency in global SARS-CoV-2. These mutations include the P323L (99.3%) in NSP12, D614G (97.6) in S, the T492I (70.4) in NSP4, R203M (62.8%) in N, T60A (61.4%) in Orf9b, and P1228L (50.0%) in NSP3. In the SARS-CoV-2 genome, no mutation was observed in more than 90% of nsp11, nsp7, nsp10, nsp9, nsp8, and nsp16 regions. On the other hand, N, nsp3, S, nsp4, nsp12, and M had the maximum rate of mutations. In the S protein, the highest mutation frequency was observed in aa 508-635(0.77%) and aa 381-508 (0.43%). The highest frequency of mutation was observed in aa 66-88 (2.19%), aa 7-14, and aa 164-246 (2.92%) in M, E, and N proteins, respectively.

CONCLUSION

Therefore, monitoring SARS-CoV-2 proteomic changes and detecting hot spots mutations and conserved regions could be applied to improve the SARS-CoV-2 diagnostic efficiency and design safe and effective vaccines against emerging variants.

An inactivated SARS-CoV-2 vaccine induced cross-neutralizing persisting antibodies and protected against challenge in small animals

Vaccines have relieved the public health burden of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and globally inactivated vaccines are most widely used. However, poor vaccination accessibility and waning immunity maintain the pandemic, driving emergence of variants. We developed an inactivated SARS-CoV-2 (I-SARS-CoV-2) vaccine based on a viral isolate with the Spike mutation D614G, produced in Vero cells in a scalable bioreactor, inactivated with β-propiolactone, purified by membrane-based steric exclusion chromatography, and adjuvanted with MF59-like adjuvant AddaVax. I-SARS-CoV-2 and a derived split vaccine induced persisting neutralizing antibodies in mice; moreover, lyophilized antigen was immunogenic. Following homologous challenge, I-SARS-CoV-2 immunized hamsters were protected against disease and lung pathology. In contrast with reports for widely used vaccines, hamster plasma similarly neutralized the homologous and the Delta (B.1.617.2) variant viruses, whereas the Omicron (B.1.1.529) variant was neutralized less efficiently. Applied bioprocessing approaches offer advantages regarding scalability and production, potentially benefitting worldwide vaccine coverage.

Rapid assembly of SARS-CoV-2 genomes reveals attenuation of the Omicron BA.1 variant through NSP6

Although the SARS-CoV-2 Omicron variant (BA.1) spread rapidly across the world and effectively evaded immune responses, its viral fitness in cell and animal models was reduced. The precise nature of this attenuation remains unknown as generating replication-competent viral genomes is challenging because of the length of the viral genome (30kb). Here, we designed a plasmid-based viral genome assembly and resc ue strategy (pGLUE) that constructs complete infectious viruses or noninfectious subgenomic replicons in a single ligation reaction with >80% efficiency. Fully sequenced replicons and infectious viral stocks can be generated in 1 and 3 weeks, respectively. By testing a series of naturally occurring viruses as well as Delta-Omicron chimeric replicons, we show that Omicron nonstructural protein 6 harbors critical attenuating mutations, which dampen viral RNA replication and reduce lipid droplet consumption. Thus, pGLUE overcomes remaining barriers to broadly study SARS-CoV-2 replication and reveals deficits in nonstructural protein function underlying Omicron attenuation.

Molecular Evolution of SARS-CoV-2 during the COVID-19 Pandemic

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) produced diverse molecular variants during its recent expansion in humans that caused different transmissibility and severity of the associated disease as well as resistance to monoclonal antibodies and polyclonal sera, among other treatments. In order to understand the causes and consequences of the observed SARS-CoV-2 molecular diversity, a variety of recent studies investigated the molecular evolution of this virus during its expansion in humans. In general, this virus evolves with a moderate rate of evolution, in the order of 10-3-10-4 substitutions per site and per year, which presents continuous fluctuations over time. Despite its origin being frequently associated with recombination events between related coronaviruses, little evidence of recombination was detected, and it was mostly located in the spike coding region. Molecular adaptation is heterogeneous among SARS-CoV-2 genes. Although most of the genes evolved under purifying selection, several genes showed genetic signatures of diversifying selection, including a number of positively selected sites that affect proteins relevant for the virus replication. Here, we review current knowledge about the molecular evolution of SARS-CoV-2 in humans, including the emergence and establishment of variants of concern. We also clarify relationships between the nomenclatures of SARS-CoV-2 lineages. We conclude that the molecular evolution of this virus should be monitored over time for predicting relevant phenotypic consequences and designing future efficient treatments.

Molecular determinants associated with temporal succession of SARS-CoV-2 variants in Uttar Pradesh, India

The emergence and rapid evolution of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) caused a global crisis that required a detailed characterization of the dynamics of mutational pattern of the viral genome for comprehending its epidemiology, pathogenesis and containment. We investigated the molecular evolution of the SASR-CoV-2 genome during the first, second and third waves of COVID-19 in Uttar Pradesh, India. Nanopore sequencing of the SARS-CoV-2 genome was undertaken in 544 confirmed cases of COVID-19, which included vaccinated and unvaccinated individuals. In the first wave (unvaccinated population), the 20A clade (56.32%) was superior that was replaced by 21A Delta in the second wave, which was more often seen in vaccinated individuals in comparison to unvaccinated (75.84% versus 16.17%, respectively). Subsequently, 21A delta got outcompeted by Omicron (71.8%), especially the 21L variant, in the third wave. We noticed that Q677H appeared in 20A Alpha and stayed up to Delta, D614G appeared in 20A Alpha and stayed in Delta and Omicron variants (got fixed), and several other mutations appeared in Delta and stayed in Omicron. A cross-sectional analysis of the vaccinated and unvaccinated individuals during the second wave revealed signature combinations of E156G, F157Del, L452R, T478K, D614G mutations in the Spike protein that might have facilitated vaccination breach in India. Interestingly, some of these mutation combinations were carried forward from Delta to Omicron. In silico protein docking showed that Omicron had a higher binding affinity with the host ACE2 receptor, resulting in enhanced infectivity of Omicron over the Delta variant. This work has identified the combinations of key mutations causing vaccination breach in India and provided insights into the change of [virus's] binding affinity with evolution, resulting in more virulence in Delta and more infectivity in Omicron variants of SARS-CoV-2. Our findings will help in understanding the COVID-19 disease biology and guide further surveillance of the SARS-CoV-2 genome to facilitate the development of vaccines with better efficacies.

Correlated substitutions reveal SARS-like coronaviruses recombine frequently with a diverse set of structured gene pools

Quantifying SARS-like coronavirus (SL-CoV) evolution is critical to understanding the origins of SARS-CoV-2 and the molecular processes that could underlie future epidemic viruses. While genomic analyses suggest recombination was a factor in the emergence of SARS-CoV-2, few studies have quantified recombination rates among SL-CoVs. Here, we infer recombination rates of SL-CoVs from correlated substitutions in sequencing data using a coalescent model with recombination. Our computationally-efficient, non-phylogenetic method infers recombination parameters of both sampled sequences and the unsampled gene pools with which they recombine. We apply this approach to infer recombination parameters for a range of positive-sense RNA viruses. We then analyze a set of 191 SL-CoV sequences (including SARS-CoV-2) and find that ORF1ab and S genes frequently undergo recombination. We identify which SL-CoV sequence clusters have recombined with shared gene pools, and show that these pools have distinct structures and high recombination rates, with multiple recombination events occurring per synonymous substitution. We find that individual genes have recombined with different viral reservoirs. By decoupling contributions from mutation and recombination, we recover the phylogeny of non-recombined portions for many of these SL-CoVs, including the position of SARS-CoV-2 in this clonal phylogeny. Lastly, by analyzing >400,000 SARS-CoV-2 whole genome sequences, we show current diversity levels are insufficient to infer the within-population recombination rate of the virus since the pandemic began. Our work offers new methods for inferring recombination rates in RNA viruses with implications for understanding recombination in SARS-CoV-2 evolution and the structure of clonal relationships and gene pools shaping its origins.

Characterizing SARS-CoV-2 Spike Sequences Based on Geographical Location

With the rapid spread of COVID-19 worldwide, viral genomic data are available in the order of millions of sequences on public databases such as GISAID. This Big Data creates a unique opportunity for analysis toward the research of effective vaccine development for current pandemics, and avoiding or mitigating future pandemics. One piece of information that comes with every such viral sequence is the geographical location where it was collected-the patterns found between viral variants and geographical location surely being an important part of this analysis. One major challenge that researchers face is processing such huge, highly dimensional data to obtain useful insights as quickly as possible. Most of the existing methods face scalability issues when dealing with the magnitude of such data. In this article, we propose an approach that first computes a numerical representation of the spike protein sequence of SARS-CoV-2 using k-mers (substrings) and then uses several machine learning models to classify the sequences based on geographical location. We show that our proposed model significantly outperforms the baselines. We also show the importance of different amino acids in the spike sequences by computing the information gain corresponding to the true class labels.

Variability in the Clinical Course of COVID-19 in a Retrospective Analysis of a Large Real-World Database

The COVID-19 pandemic proceeds in waves, with variable characteristics of the clinical picture resulting from the evolution of the SARS-CoV-2 virus. This study aimed to compare the epidemiological characteristics, symptomatology, and outcomes of the disease in patients hospitalized for COVID-19 during periods of different variants dominance. Comparing the periods of dominance of variants preceding the Delta variant, the Delta period was characterized by a higher share of hospitalized females, less frequent comorbidities among patients, and a different age distribution. The lowest need for oxygen therapy and mechanical ventilation was observed under Omicron dominance. The triad of classic COVID-19 symptoms, cough, fever, dyspnoea, and fatigue, were most prevalent during the Delta period, and significantly less common under the Omicron dominance. During the Omicron period, nearly twice as many patients as in the previous periods could be discharged from the hospital within 7 days; the overall 28-day mortality was significantly lower compared to that of the Delta period. It also did not differ between periods that were dominated by the BA.1 and BA.2 subvariants. The study indicates that the Omicron SARS-CoV-2 variant that dominated between January and June 2022 caused a disease which resembled the common cold, and was caused by seasonal alpha and beta-coronaviruses with a low pathogenicity for humans. However, one should note that this effect may not only have been related to biological features of the Omicron lineage, but may additionally have been driven by the increased levels of immunization through natural infections and vaccinations, for which we could not account for due to a lack of sufficient data.

Impact of antigenic evolution and original antigenic sin on SARS-CoV-2 immunity

Infections with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and vaccinations targeting the spike protein (S) offer protective immunity against coronavirus disease 2019 (COVID-19). This immunity may further be shaped by cross-reactivity with common cold coronaviruses. Mutations arising in S that are associated with altered intrinsic virus properties and immune escape result in the continued circulation of SARS-CoV-2 variants. Potentially, vaccine updates will be required to protect against future variants of concern, as for influenza. To offer potent protection against future variants, these second-generation vaccines may need to redirect immunity to epitopes associated with immune escape and not merely boost immunity toward conserved domains in preimmune individuals. For influenza, efficacy of repeated vaccination is hampered by original antigenic sin, an attribute of immune memory that leads to greater induction of antibodies specific to the first-encountered variant of an immunogen compared with subsequent variants. In this Review, recent findings on original antigenic sin are discussed in the context of SARS-CoV-2 evolution. Unanswered questions and future directions are highlighted, with an emphasis on the impact on disease outcome and vaccine design.

Coordinated evolution at amino acid sites of SARS-CoV-2 spike

SARS-CoV-2 has adapted in a stepwise manner, with multiple beneficial mutations accumulating in a rapid succession at origins of VOCs, and the reasons for this are unclear. Here, we searched for coordinated evolution of amino acid sites in the spike protein of SARS-CoV-2. Specifically, we searched for concordantly evolving site pairs (CSPs) for which changes at one site were rapidly followed by changes at the other site in the same lineage. We detected 46 sites which formed 45 CSP. Sites in CSP were closer to each other in the protein structure than random pairs, indicating that concordant evolution has a functional basis. Notably, site pairs carrying lineage defining mutations of the four VOCs that circulated before May 2021 are enriched in CSPs. For the Alpha VOC, the enrichment is detected even if Alpha sequences are removed from analysis, indicating that VOC origin could have been facilitated by positive epistasis. Additionally, we detected nine discordantly evolving pairs of sites where mutations at one site unexpectedly rarely occurred on the background of a specific allele at another site, for example on the background of wild-type D at site 614 (four pairs) or derived Y at site 501 (three pairs). Our findings hint that positive epistasis between accumulating mutations could have delayed the assembly of advantageous combinations of mutations comprising at least some of the VOCs.

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.