The Emergence of SARS-CoV-2 Variants of Concern Is Driven by Acceleration of the Substitution Rate

SARS-CoV-2 epidemiology, kinetics, and evolution: A narrative review

Since winter 2019, SARS-CoV-2 has emerged, spread, and evolved all around the globe. We explore 4 y of evolutionary epidemiology of this virus, ranging from the applied public health challenges to the more conceptual evolutionary biology perspectives. Through this review, we first present the spread and lethality of the infections it causes, starting from its emergence in Wuhan (China) from the initial epidemics all around the world, compare the virus to other betacoronaviruses, focus on its airborne transmission, compare containment strategies ("zero-COVID" vs. "herd immunity"), explain its phylogeographical tracking, underline the importance of natural selection on the epidemics, mention its within-host population dynamics. Finally, we discuss how the pandemic has transformed (or should transform) the surveillance and prevention of viral respiratory infections and identify perspectives for the research on epidemiology of COVID-19.

Variable rates of SARS-CoV-2 evolution in chronic infections

An important feature of the evolution of the SARS-CoV-2 virus has been the emergence of highly mutated novel variants, which are characterised by the gain of multiple mutations relative to viruses circulating in the general global population. Cases of chronic viral infection have been suggested as an explanation for this phenomenon, whereby an extended period of infection, with an increased rate of evolution, creates viruses with substantial genetic novelty. However, measuring a rate of evolution during chronic infection is made more difficult by the potential existence of compartmentalisation in the viral population, whereby the viruses in a host form distinct subpopulations. We here describe and apply a novel statistical method to study within-host virus evolution, identifying the minimum number of subpopulations required to explain sequence data observed from cases of chronic infection, and inferring rates for within-host viral evolution. Across nine cases of chronic SARS-CoV-2 infection in hospitalised patients we find that non-trivial population structure is relatively common, with five cases showing evidence of more than one viral population evolving independently within the host. The detection of non-trivial population structure was more common in severely immunocompromised individuals (p = 0.04, Fisher's Exact Test). We find cases of within-host evolution proceeding significantly faster, and significantly slower, than that of the global SARS-CoV-2 population, and of cases in which viral subpopulations in the same host have statistically distinguishable rates of evolution. Non-trivial population structure was associated with high rates of within-host evolution that were systematically underestimated by a more standard inference method.

JUNIPER: Reconstructing Transmission Events from Next-Generation Sequencing Data at Scale

Transmission reconstruction-the inference of who infects whom in disease outbreaks-offers critical insights into how pathogens spread and provides opportunities for targeted control measures. We developed JUNIPER (Joint Underlying Network Inference for Phylogenetic and Epidemiological Reconstructions), a highly-scalable pathogen outbreak reconstruction tool that incorporates intrahost variation, incomplete sampling, and algorithmic parallelization. Central to JUNIPER is a statistical model for within-host variant frequencies observed by next generation sequencing, which we validated on a dataset of over 160,000 deep-sequenced SARS-CoV-2 genomes. Combining this within-host variation model with population-level evolutionary and transmission models, we developed a method for inferring phylogenies and transmission trees simultaneously. We benchmarked JUNIPER on computer-generated and real outbreaks in which transmission links were known or epidemiologically confirmed. We demonstrated JUNIPER's real-world utility on two large-scale datasets: over 1,500 bovine H5N1 cases and over 13,000 human COVID-19 cases. Based on these analyses, we quantified the elevated H5N1 transmission rates in California and identified high-confidence transmission events, and demonstrated the efficacy of vaccination for reducing SARS-CoV-2 transmission. By overcoming computational and methodological limitations in existing outbreak reconstruction tools, JUNIPER provides a robust framework for studying pathogen spread at scale.

JUNIPER: Reconstructing Transmission Events from Next-Generation Sequencing Data at Scale

Transmission reconstruction--the inference of who infects whom in disease outbreaks--offers critical insights into how pathogens spread and provides opportunities for targeted control measures. We developed JUNIPER (Joint Underlying Network Inference for Phylogenetic and Epidemiological Reconstructions), a highly-scalable pathogen outbreak reconstruction tool that incorporates intrahost variation, incomplete sampling, and algorithmic parallelization. Central to JUNIPER is a statistical model for within-host variant frequencies observed by next generation sequencing, which we validated on a dataset of over 160,000 deep-sequenced SARS-CoV-2 genomes. Combining this within-host variation model with population-level evolutionary and transmission models, we developed a method for inferring phylogenies and transmission trees simultaneously. We benchmarked JUNIPER on computer-generated and real outbreaks in which transmission links were known or epidemiologically confirmed. We demonstrated JUNIPER's real-world utility on two large-scale datasets: over 1,500 bovine H5N1 cases and over 13,000 human COVID-19 cases. Based on these analyses, we quantified the elevated H5N1 transmission rates in California and identified high-confidence transmission events, and demonstrated the efficacy of vaccination for reducing SARS-CoV-2 transmission. By overcoming computational and methodological limitations in existing outbreak reconstruction tools, JUNIPER provides a robust framework for studying pathogen spread at scale.

Evolutionary Mechanisms of the Emergence of the Variants of Concern of SARS-CoV-2

The evolutionary origin of the variants of concern (VOCs) of SARS-CoV-2, characterized by a large number of new substitutions and strong changes in virulence and transmission rate, is intensely debated. The leading explanation in the literature is a chronic infection in immunocompromised individuals, where the virus evolves before returning into the main population. The present article reviews less-investigated hypotheses of VOC emergence with transmission between acutely infected hosts, with a focus on the mathematical models of stochastic evolution that have proved to be useful for other viruses, such as HIV and influenza virus. The central message is that understanding the acting factors of VOC evolution requires the framework of stochastic multi-locus evolution models, and that alternative hypotheses can be effectively verified by fitting results of computer simulation to empirical data.

Rapid spread of the SARS-CoV-2 Omicron XDR lineage derived from recombination between XBB and BA.2.86 subvariants circulating in Brazil in late 2023

Recombination plays a crucial role in the evolution of SARS-CoV-2. The Omicron XBB* recombinant lineages are a noteworthy example, as they have been the dominant SARS-CoV-2 variant worldwide in the first half of 2023. Since November 2023, a new recombinant lineage between Omicron subvariants XBB and BA.2.86, designated XDR, has been detected mainly in Brazil. In this study, we reconstructed the spatiotemporal dynamics and estimated the absolute and relative transmissibility of the XDR lineage. The XDR lineage displayed a recombination breakpoint in the ORF1a-coding region, and the most closely related sequences to the 5' and 3' ends of the recombinant correspond to JD.1.1 and JN.1.1 lineages, respectively. The first XDR sequences were detected in November 2023 in the Northeastern Brazilian region, and their prevalence rapidly surged from <1% to 25% by February 2024. The Bayesian phylogeographic analysis supports that the XDR lineage likely emerged in the Northeastern Brazilian region around late October 2023 and rapidly disseminated within and outside Brazilian borders from mid-November onward. The median effective reproductive number of the XDR lineage in Brazil during the initial expansion phase was estimated to be around 1.5, and the average relative instantaneous reproduction numbers of XDR and JN* lineages were estimated to be 1.37 and 1.29 higher than that of co-circulating XBB* lineages. In summary, these findings support that the recombinant lineage XDR arose in the Northeastern Brazilian region in October 2023, shortly after the first detection of JN.1 sequences in the country. In Brazil, the XDR lineage exhibited a higher transmissibility level than its parental XBB.* lineages and is spreading at a rate similar to or slightly faster than the JN.1* lineages.IMPORTANCEThis study highlights the emergence and rapid dissemination of the recombinant SARS-CoV-2 XDR lineage, derived from the Omicron lineages JD.1.1 and JN.1.1. The XDR lineage exhibited equivalent transmissibility to its JN.1* parental lineages and quickly spread across Brazil in late 2023. The findings underscore the critical role of real-time genomic surveillance in detecting novel variants with higher transmission potential. By utilizing phylogenetic and epidemiological methods, this research provides important insights into the molecular dynamics of XDR, which could inform public health responses and vaccine composition updates. The study's significance lies in its ability to document the impact of recombination on viral evolution, offering valuable information to the field of virology and pandemic preparedness.

Routes of importation and spatial dynamics of SARS-CoV-2 variants during localized interventions in Chile

Human mobility is strongly associated with the spread of SARS-CoV-2 via air travel on an international scale and with population mixing and the number of people moving between locations on a local scale. However, these conclusions are drawn mostly from observations in the context of the global north where international and domestic connectivity is heavily influenced by the air travel network; scenarios where land-based mobility can also dominate viral spread remain understudied. Furthermore, research on the effects of nonpharmaceutical interventions (NPIs) has mostly focused on national- or regional-scale implementations, leaving gaps in our understanding of the potential benefits of implementing NPIs at higher granularity. Here, we use Chile as a model to explore the role of human mobility on disease spread within the global south; the country implemented a systematic genomic surveillance program and NPIs at a very high spatial granularity. We combine viral genomic data, anonymized human mobility data from mobile phones and official records of international travelers entering the country to characterize the routes of importation of different variants, the relative contributions of airport and land border importations, and the real-time impact of the country's mobility network on the diffusion of SARS-CoV-2. The introduction of variants which are dominant in neighboring countries (and not detected through airport genomic surveillance) is predicted by land border crossings and not by air travelers, and the strength of connectivity between comunas (Chile's lowest administrative divisions) predicts the time of arrival of imported lineages to new locations. A higher stringency of local NPIs was also associated with fewer domestic viral importations. Our analysis sheds light on the drivers of emerging respiratory infectious disease spread outside of air travel and on the consequences of disrupting regular movement patterns at lower spatial scales.

SARS-CoV-2 Evolution: Immune Dynamics, Omicron Specificity, and Predictive Modeling in Vaccinated Populations

Host immunity is central to the virus's spread dynamics, which is significantly influenced by vaccination and prior infection experiences. In this work, we analyzed the co-evolution of SARS-CoV-2 mutation, angiotensin-converting enzyme 2 (ACE2) receptor binding, and neutralizing antibody (NAb) responses across various variants in 822 human and mice vaccinated with different non-Omicron and Omicron vaccines is analyzed. The link between vaccine efficacy and vaccine type, dosing, and post-vaccination duration is revealed. The classification of immune protection against non-Omicron and Omicron variants is co-evolved with genetic mutations and vaccination. Additionally, a model, the Prevalence Score (P-Score) is introduced, which surpasses previous algorithm-based models in predicting the potential prevalence of new variants in vaccinated populations. The hybrid vaccination combining the wild-type (WT) inactivated vaccine with the Omicron BA.4/5 mRNA vaccine may provide broad protection against both non-Omicron variants and Omicron variants, albeit with EG.5.1 still posing a risk. In conclusion, these findings enhance understanding of population immunity variations and provide valuable insights for future vaccine development and public health strategies.

Clockor2: Inferring Global and Local Strict Molecular Clocks Using Root-to-Tip Regression

Molecular sequence data from rapidly evolving organisms are often sampled at different points in time. Sampling times can then be used for molecular clock calibration. The root-to-tip (RTT) regression is an essential tool to assess the degree to which the data behave in a clock-like fashion. Here, we introduce Clockor2, a client-side web application for conducting RTT regression. Clockor2 allows users to quickly fit local and global molecular clocks, thus handling the increasing complexity of genomic datasets that sample beyond the assumption of homogeneous host populations. Clockor2 is efficient, handling trees of up to the order of 104 tips, with significant speed increases compared with other RTT regression applications. Although clockor2 is written as a web application, all data processing happens on the client-side, meaning that data never leave the user's computer. Clockor2 is freely available at https://clockor2.github.io/.

Combining Molecular, Macroevolutionary, and Macroecological Perspectives on the Generation of Diversity

Charles Darwin presented a unified process of diversification driven by the gradual accumulation of heritable variation. The growth in DNA databases and the increase in genomic sequencing, combined with advances in molecular phylogenetic analyses, gives us an opportunity to realize Darwin's vision, connecting the generation of variation to the diversification of lineages. The rate of molecular evolution is correlated with the rate of diversification across animals and plants, but the relationship between genome change and speciation is complex: Mutation rates evolve in response to life history and niche; substitution rates are influenced by mutation, selection, and population size; rates of acquisition of reproductive isolation vary between populations; and traits, niches, and distribution can influence diversification rates. The connection between mutation rate and diversification rate is one part of the complex and varied story of speciation, which has theoretical importance for understanding the generation of biodiversity and also practical impacts on the use of DNA to understand the dynamics of speciation over macroevolutionary timescales.

High-resolution epidemiological landscape from ~290,000 SARS-CoV-2 genomes from Denmark

Vast amounts of pathogen genomic, demographic and spatial data are transforming our understanding of SARS-CoV-2 emergence and spread. We examined the drivers of molecular evolution and spread of 291,791 SARS-CoV-2 genomes from Denmark in 2021. With a sequencing rate consistently exceeding 60%, and up to 80% of PCR-positive samples between March and November, the viral genome set is broadly whole-epidemic representative. We identify a consistent rise in viral diversity over time, with notable spikes upon the importation of novel variants (e.g., Delta and Omicron). By linking genomic data with rich individual-level demographic data from national registers, we find that individuals aged  < 15 and  > 75 years had a lower contribution to molecular change (i.e., branch lengths) compared to other age groups, but similar molecular evolutionary rates, suggesting a lower likelihood of introducing novel variants. Similarly, we find greater molecular change among vaccinated individuals, suggestive of immune evasion. We also observe evidence of transmission in rural areas to follow predictable diffusion processes. Conversely, urban areas are expectedly more complex due to their high mobility, emphasising the role of population structure in driving virus spread. Our analyses highlight the added value of integrating genomic data with detailed demographic and spatial information, particularly in the absence of structured infection surveys.

Characterization of Treatment Resistance and Viral Kinetics in the Setting of Single-Active Versus Dual-Active Monoclonal Antibodies Against Severe Acute Respiratory Syndrome Coronavirus 2

BACKGROUND

Monoclonal antibodies (mAbs) represent a crucial antiviral strategy for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, but it is unclear whether combination mAbs offer a benefit over single-active mAb treatment. Amubarvimab and romlusevimab significantly reduced the risk of hospitalizations or death in the ACTIV-2/A5401 trial. Certain SARS-CoV-2 variants are intrinsically resistant against romlusevimab, leading to only single-active mAb therapy with amubarvimab in these variants. We evaluated virologic outcomes in individuals treated with single- versus dual-active mAbs.

METHODS

Participants were nonhospitalized adults at higher risk of clinical progression randomized to amubarvimab plus romlusevimab or placebo. Quantitative SARS-CoV-2 RNA levels and targeted S-gene next-generation sequencing was performed on anterior nasal samples. We compared viral load kinetics and resistance emergence between individuals treated with effective single- versus dual-active mAbs depending on the infecting variant.

RESULTS

Study participants receiving single- or dual-active mAbs had similar demographics, baseline nasal viral load, symptom score, and symptom duration. Compared with single-active mAb treatment, treatment with dual-active mAbs led to faster viral load decline at study days 3 (P < .001) and 7 (P < .01). Treatment-emergent resistance mutations were more likely to be detected after amubarvimab plus romlusevimab treatment than with placebo (2.6% vs 0%; P < .001) and were more frequently detected in the setting of single-active compared with dual-active mAb treatment (7.3% vs 1.1%; P < .01). Single-active and dual-active mAb treatment resulted in similar decrease in rates of hospitalizations or death.

CONCLUSIONS

Compared with single-active mAb therapy, dual-active mAbs led to similar clinical outcomes but significantly faster viral load decline and a lower risk of emergent resistance.

Persistence of SARS-CoV-2 infection and viral intra- and inter-host evolution in COVID-19 hospitalized patients

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) persistence in COVID-19 patients could play a key role in the emergence of variants of concern. The rapid intra-host evolution of SARS-CoV-2 may result in an increased transmissibility, immune and therapeutic escape which could be a direct consequence of COVID-19 epidemic currents. In this context, a longitudinal retrospective study on eight consecutive COVID-19 patients with persistent SARS-CoV-2 infection, from January 2022 to March 2023, was conducted. To characterize the intra- and inter-host viral evolution, whole genome sequencing and phylogenetic analysis were performed on nasopharyngeal samples collected at different time points. Phylogenetic reconstruction revealed an accelerated SARS-CoV-2 intra-host evolution and emergence of antigenically divergent variants. The Bayesian inference and principal coordinate analysis analysis showed a host-based genomic structuring among antigenically divergent variants, that might reflect the positive effect of containment practices, within the critical hospital area. All longitudinal antigenically divergent isolates shared a wide range of amino acidic (aa) changes, particularly in the Spike (S) glycoprotein, that increased viral transmissibility (K417N, S477N, N501Y and Q498R), enhanced infectivity (R346T, S373P, R408S, T478K, Q498R, Y505H, D614G, H655Y, N679K and P681H), caused host immune escape (S371L, S375F, T376A, K417N, and K444T/R) and displayed partial or complete resistance to treatments (G339D, R346K/T, S371F/L, S375F, T376A, D405N, N440K, G446S, N460K, E484A, F486V, Q493R, G496S and Q498R). These results suggest that multiple novel variants which emerge in the patient during persistent infection, might spread to another individual and continue to evolve. A pro-active genomic surveillance of persistent SARS-CoV-2 infected patients is recommended to identify genetically divergent lineages before their diffusion.

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.

Targeted accurate RNA consensus sequencing (tARC-seq) reveals mechanisms of replication error affecting SARS-CoV-2 divergence

RNA viruses, like SARS-CoV-2, depend on their RNA-dependent RNA polymerases (RdRp) for replication, which is error prone. Monitoring replication errors is crucial for understanding the virus's evolution. Current methods lack the precision to detect rare de novo RNA mutations, particularly in low-input samples such as those from patients. Here we introduce a targeted accurate RNA consensus sequencing method (tARC-seq) to accurately determine the mutation frequency and types in SARS-CoV-2, both in cell culture and clinical samples. Our findings show an average of 2.68 × 10-5 de novo errors per cycle with a C > T bias that cannot be solely attributed to APOBEC editing. We identified hotspots and cold spots throughout the genome, correlating with high or low GC content, and pinpointed transcription regulatory sites as regions more susceptible to errors. tARC-seq captured template switching events including insertions, deletions and complex mutations. These insights shed light on the genetic diversity generation and evolutionary dynamics of SARS-CoV-2.

Kidney organoids reveal redundancy in viral entry pathways during ACE2-dependent SARS-CoV-2 infection

With a high incidence of acute kidney injury among hospitalized COVID-19 patients, considerable attention has been focussed on whether SARS-CoV-2 specifically targets kidney cells to directly impact renal function, or whether renal damage is primarily an indirect outcome. To date, several studies have utilized kidney organoids to understand the pathogenesis of COVID-19, revealing the ability for SARS-CoV-2 to predominantly infect cells of the proximal tubule (PT), with reduced infectivity following administration of soluble ACE2. However, the immaturity of standard human kidney organoids represents a significant hurdle, leaving the preferred SARS-CoV-2 processing pathway, existence of alternate viral receptors, and the effect of common hypertensive medications on the expression of ACE2 in the context of SARS-CoV-2 exposure incompletely understood. Utilizing a novel kidney organoid model with enhanced PT maturity, genetic- and drug-mediated inhibition of viral entry and processing factors confirmed the requirement for ACE2 for SARS-CoV-2 entry but showed that the virus can utilize dual viral spike protein processing pathways downstream of ACE2 receptor binding. These include TMPRSS- and CTSL/CTSB-mediated non-endosomal and endocytic pathways, with TMPRSS10 likely playing a more significant role in the non-endosomal pathway in renal cells than TMPRSS2. Finally, treatment with the antihypertensive ACE inhibitor, lisinopril, showed negligible impact on receptor expression or susceptibility of renal cells to infection. This study represents the first in-depth characterization of viral entry in stem cell-derived human kidney organoids with enhanced PTs, providing deeper insight into the renal implications of the ongoing COVID-19 pandemic.

IMPORTANCE

Utilizing a human iPSC-derived kidney organoid model with improved proximal tubule (PT) maturity, we identified the mechanism of SARS-CoV-2 entry in renal cells, confirming ACE2 as the sole receptor and revealing redundancy in downstream cell surface TMPRSS- and endocytic Cathepsin-mediated pathways. In addition, these data address the implications of SARS-CoV-2 exposure in the setting of the commonly prescribed ACE-inhibitor, lisinopril, confirming its negligible impact on infection of kidney cells. Taken together, these results provide valuable insight into the mechanism of viral infection in the human kidney.

VIPERA: Viral Intra-Patient Evolution Reporting and Analysis

Viral mutations within patients nurture the adaptive potential of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) during chronic infections, which are a potential source of variants of concern. However, there is no integrated framework for the evolutionary analysis of intra-patient SARS-CoV-2 serial samples. Herein, we describe Viral Intra-Patient Evolution Reporting and Analysis (VIPERA), a new software that integrates the evaluation of the intra-patient ancestry of SARS-CoV-2 sequences with the analysis of evolutionary trajectories of serial sequences from the same viral infection. We have validated it using positive and negative control datasets and have successfully applied it to a new case, which revealed population dynamics and evidence of adaptive evolution. VIPERA is available under a free software license at https://github.com/PathoGenOmics-Lab/VIPERA.

Exploration of low-frequency allelic variants of SARS-CoV-2 genomes reveals coinfections in Mexico occurred during periods of VOCs turnover

A total of 14 973 alleles in 29 661 sequenced samples collected between March 2021 and January 2023 by the Mexican Consortium for Genomic Surveillance (CoViGen-Mex) and collaborators were used to construct a thorough map of mutations of the Mexican SARS-CoV-2 genomic landscape containing Intra-Patient Minor Allelic Variants (IPMAVs), which are low-frequency alleles not ordinarily present in a genomic consensus sequence. This additional information proved critical in identifying putative coinfecting variants included alongside the most common variants, B.1.1.222, B.1.1.519, and variants of concern (VOCs) Alpha, Gamma, Delta, and Omicron. A total of 379 coinfection events were recorded in the dataset (a rate of 1.28 %), resulting in the first such catalogue in Mexico. The most common putative coinfections occurred during the spread of Delta or after the introduction of Omicron BA.2 and its descendants. Coinfections occurred constantly during periods of variant turnover when more than one variant shared the same niche and high infection rate was observed, which was dependent on the local variants and time. Coinfections might occur at a higher frequency than customarily reported, but they are often ignored as only the consensus sequence is reported for lineage identification.

Proposing lead compounds for the development of SARS-CoV-2 receptor-binding inhibitors

The COVID-19 pandemic has had deleterious effects on the world and demands urgent measures to find therapeutic agents to combat the current and related future outbreaks. The entry of SARS-CoV-2 into the host's cell is facilitated by the interaction between the viral spike receptor-binding domain (sRBD) and the human angiotensin-converting enzyme 2 (hACE2). Although the interface of sRBD involved in the sRBD-hACE2 interaction has been projected as a primary vaccine and drug target, currently no small-molecule drugs have been approved for covid-19 treatment targeting sRBD. Herein structure-based virtual screening and molecular dynamics (MD) simulation strategies were applied to identify novel potential small-molecule binders of the SARS-CoV-2 sRBD from an sRBD-targeted compound library as leads for the development of anti-COVID-19 drugs. The library was initially screened against sRBD by using the GOLD docking program whereby 19 compounds were shortlisted based on docking scores after using a control compound to set the selection cutoff. The stability of each compound in MD simulations was used as a further standard to select four hits namely T4S1820, T4589, E634-1449, and K784-7078. Analyses of simulations data showed that the four compounds remained stably bound to sRBD for ≥ 80 ns with reasonable affinities and interacted with pharmacologically important amino acid residues. The compounds exhibited fair solubility, lipophilicity, and toxicity-propensity characteristics that could be improved through lead optimization regimes. The overall results suggest that the scaffolds of T4S1820, E634-1449, and K784-7078 could serve as seeds for developing potent small-molecule inhibitors of SARS-CoV-2 receptor binding and cell entry.Communicated by Ramaswamy H. Sarma.

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.

Sequence analysis of the Spike, RNA-dependent RNA polymerase, and protease genes reveals a distinct evolutionary pattern of SARS-CoV-2 variants circulating in Yogyakarta and Central Java provinces, Indonesia

During the Covid-19 pandemic, the resurgence of SARS-CoV-2 was due to the development of novel variants of concern (VOC). Thus, genomic surveillance is essential to monitor continuing evolution of SARS-CoV-2 and to track the emergence of novel variants. In this study, we performed phylogenetic, mutation, and selection pressure analyses of the Spike, nsp12, nsp3, and nsp5 genes of SARS-CoV-2 isolates circulating in Yogyakarta and Central Java provinces, Indonesia from May 2021 to February 2022. Various bioinformatics tools were employed to investigate the evolutionary dynamics of distinct SARS-CoV-2 isolates. During the study period, 213 and 139 isolates of Omicron and Delta variants were identified, respectively. Particularly in the Spike gene, mutations were significantly more abundant in Omicron than in Delta variants. Consistently, in all of four genes studied, the substitution rates of Omicron were higher than that of Delta variants, especially in the Spike and nsp12 genes. In addition, selective pressure analysis revealed several sites that were positively selected in particular genes, implying that these sites were functionally essential for virus evolution. In conclusion, our study demonstrated a distinct evolutionary pattern of SARS-CoV-2 variants circulating in Yogyakarta and Central Java provinces, Indonesia.

Genomic epidemiology and evolutionary analysis during XBB.1.16-predominant periods of SARS-CoV-2 omicron variant in Bangkok, Thailand: December 2022-August 2023

The growing occurrence of novel recombinants, such as XBB.1.16, has emerged and become predominant, raising concerns about the impact of genomic recombination on the evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This study investigated the molecular epidemiological trends and evolution of the Omicron XBB.1.16 epidemic in Bangkok between December 2022 and August 2023. Partial spike and complete genome sequencing of SARS-CoV-2 samples collected from collaborating hospitals were performed. The analysis of 491 partial spike sequences identified 15 distinct lineages, with XBB.1.16 dominating the lineages beginning in March 2023. Phylogenetic analysis revealed at least four distinct XBB.1.16 lineages, suggesting multiple independent introductions into Bangkok. The estimated emergence of XBB.1.16 occurred approximately in January 2022, with an evolutionary rate of 0.79 × 10-3 substitutions per site per year. Monitoring the genomic epidemiology and evolution of XBB.1.16 is vital for the early detection of new strains or emerging variants, which may guide vaccine design and the inclusion of new vaccine strains.

Two-Stage Recognition Mechanism of the SARS-CoV-2 Receptor-Binding Domain to Angiotensin-Converting Enzyme-2 (ACE2)

The SARS-CoV-2 virus, commonly known as COVID-19, occurred in 2019. It is a highly contagious illness with effects ranging from mild symptoms to severe illness. It is also one of the best-known pathogens since more than 200,000 scientific papers occurred in the last few years. With the publication of the SARS-CoV-2 (SARS-CoV-2-CTD) spike (S) protein in a complex with human ACE2 (hACE2) (PDB (6LZG)), the molecular analysis of one of the most crucial steps on the infection pathway was possible. The aim of this manuscript is to simulate the most widely spread mutants of SARS-CoV-2, namely Alpha, Beta, Gamma, Delta, Omicron, and the first recognized variant (natural wild type). With the wide search of the hypersurface of the potential energy performed using the UNRES force field, the intermediate state of the ACE2-RBD complex was found. R403, K/N/T417, L455, F486, Y489, F495, Y501, and Y505 played a crucial role in the protein recognition mechanism. The intermediate state cannot be very stable since it will prevent the infection cascade.

A review of the immunogenicity and safety of booster doses of omicron variant-containing mRNA-1273 COVID-19 vaccines in adults and children

INTRODUCTION

Vaccination against SARS-CoV-2 is an integral pillar of the public health approach to COVID-19. With the emergence of variants of concern that increase transmissibility and escape from vaccine- or infection-induced protection, vaccines have been developed to more closely match the newly circulating SARS-CoV-2 strains to improve protection. The safety and immunogenicity of multiple authorized messenger RNA (mRNA)-based COVID-19 vaccines targeting the omicron sublineage (BA.1, BA.4/BA.5, and XBB.1.5) have been demonstrated in several clinical trials among adults and children.

AREAS COVERED

This review will comprehensively detail the available evidence (published through July 2024) from ongoing clinical trials on omicron variant-containing mRNA-1273 vaccines administered as additional doses in previously vaccinated target demographics.

EXPERT OPINION

Across three clinical trials, omicron variant-containing mRNA-1273 vaccines induced immune responses to vaccine-matched omicron strains as well as ancestral SARS-CoV-2, with a safety and reactogenicity profile comparable to the original mRNA-1273 vaccine. Combined with pivotal data demonstrating the safety, efficacy, and effectiveness of the original mRNA-1273 vaccine, these findings support the use of variant-containing mRNA-1273 vaccines and provide confidence that expeditious development of updated vaccines using this established mRNA platform can maintain protection against COVID-19.

Tracing the origin of virulence

Microbial genomes from ancient chickens uncover the drivers of pathogenicity.

Spatiotemporal evolution of SARS-CoV-2 in the Bangkok metropolitan region, Thailand, 2020-2022: implications for future outbreak preparedness

Thailand experienced five waves of coronavirus disease 2019 (COVID-19) between 2020 and 2022, with the Bangkok Metropolitan Region (BMR) being at the centre of all outbreaks. The molecular evolution of the causative agent of the disease, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has previously been characterized in Thailand, but a detailed spatiotemporal analysis is still lacking. In this study, we comprehensively reviewed the development and timelines of the five COVID-19 outbreaks in Thailand and the public health responses, and also conducted a phylogenetic analysis of 27 913 SARS-CoV-2 genomes from Thailand, together with 7330 global references, to investigate the virus's spatiotemporal evolution during 2020 and 2022, with a particular focus on the BMR. Limited cross-border transmission was observed during the first four waves in 2020 and 2021, but was common in 2022, aligning well with the timeline of change in the international travel restrictions. Within the country, viruses were mostly restricted to the BMR during the first two waves in 2020, but subsequent waves in 2021 and 2022 saw extensive nationwide transmission of the virus, consistent with the timeline of relaxation of disease control measures employed within the country. Our results also suggest frequent epidemiological connections between Thailand and neighbouring countries during 2020 and 2021 despite relatively stringent international travel controls. The overall sequencing rate of the viruses circulating in the BMR was ~0.525 %, meeting the recommended benchmark, and our analysis supports that this is sufficient for tracking of the trend of the virus burden and genetic diversity. Our findings reveal insights into the local transmission dynamics of SARS-CoV-2 in Thailand, and provide a valuable reference for planning responses to future outbreaks.

Reconstructing relative transmission rates in Bayesian phylodynamics: Two-fold transmission advantage of Omicron in Berlin, Germany during December 2021

Phylodynamic methods have lately played a key role in understanding the spread of infectious diseases. During the coronavirus disease (COVID-19) pandemic, large scale genomic surveillance has further increased the potential of dynamic inference from viral genomes. With the continual emergence of novel severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) variants, explicitly allowing transmission rate differences between simultaneously circulating variants in phylodynamic inference is crucial. In this study, we present and empirically validate an extension to the BEAST2 package birth-death skyline model (BDSKY), BDSKY[Formula: see text], which introduces a scaling factor for the transmission rate between independent, jointly inferred trees. In an extensive simulation study, we show that BDSKY[Formula: see text] robustly infers the relative transmission rates under different epidemic scenarios. Using publicly available genome data of SARS-CoV-2, we apply BDSKY[Formula: see text] to quantify the transmission advantage of the Omicron over the Delta variant in Berlin, Germany. We find the overall transmission rate of Omicron to be scaled by a factor of two with pronounced variation between the individual clusters of each variant. These results quantify the transmission advantage of Omicron over the previously circulating Delta variant, in a crucial period of pre-established non-pharmaceutical interventions. By inferring variant- as well as cluster-specific transmission rate scaling factors, we show the differences in transmission dynamics for each variant. This highlights the importance of incorporating lineage-specific transmission differences in phylodynamic inference.

Lineage replacement and evolution captured by 3 years of the United Kingdom Coronavirus (COVID-19) Infection Survey

The Office for National Statistics Coronavirus (COVID-19) Infection Survey (ONS-CIS) is the largest surveillance study of SARS-CoV-2 positivity in the community, and collected data on the United Kingdom (UK) epidemic from April 2020 until March 2023 before being paused. Here, we report on the epidemiological and evolutionary dynamics of SARS-CoV-2 determined by analysing the sequenced samples collected by the ONS-CIS during this period. We observed a series of sweeps or partial sweeps, with each sweeping lineage having a distinct growth advantage compared to their predecessors, although this was also accompanied by a gradual fall in average viral burdens from June 2021 to March 2023. The sweeps also generated an alternating pattern in which most samples had either S-gene target failure (SGTF) or non-SGTF over time. Evolution was characterized by steadily increasing divergence and diversity within lineages, but with step increases in divergence associated with each sweeping major lineage. This led to a faster overall rate of evolution when measured at the between-lineage level compared to within lineages, and fluctuating levels of diversity. These observations highlight the value of viral sequencing integrated into community surveillance studies to monitor the viral epidemiology and evolution of SARS-CoV-2, and potentially other pathogens.

SARS-CoV-2: An Update on the Biological Interplay with the Human Host

Coronavirus Disease 2019 (COVID-19) is an infectious respiratory illness caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The disease, first identified in the Chinese city of Wuhan in November 2019, has since spread worldwide, is the latest human pandemic and has officially infected over 800 million people and has caused nearly seven million deaths to date. Although SARS-CoV-2 belongs to the large family of coronaviruses, it has some unique biological characteristics in its interplay with the human host. Therefore, this narrative review aims to provide an up-to-date overview of the structure of the virus, incubation and shedding in the human host, infectivity and biological evolution over time, as well as the main mechanisms for invading human host cells and replicating within. We also proffer that ongoing epidemiological surveillance of newly emerged variants must always be accompanied by biological studies aimed at deciphering new advantageous traits that may contribute to increasing virulence and pathogenicity, such that the most appropriate strategies for establishing a (relatively) safe coexistence with the human host can be implemented.

A Proofreading Mutation with an Allosteric Effect Allows a Cluster of SARS-CoV-2 Viruses to Rapidly Evolve

The RNA-dependent RNA polymerase of the severe acute respiratory syndrome coronavirus 2 virus is error prone, with errors being corrected by the exonuclease (NSP14) proofreading mechanism. However, the mutagenesis and subsequent evolutionary trajectory of the virus is mediated by the delicate interplay of replicase fidelity and environmental pressures. Here, we have shown that a single, distal mutation (F60S) in NSP14 can have a profound impact upon proofreading with an increased accumulation of mutations and elevated evolutionary rate being observed. Understanding the implications of these changes is crucial, as these underlying mutational processes may have important implications for understanding the population-wide evolution of the virus. This study underscores the urgent need for continued research into the replicative mechanisms of this virus to combat its continued impact on global health, through the re-emergence of immuno-evasive variants.

Detecting Episodic Evolution through Bayesian Inference of Molecular Clock Models

Molecular evolutionary rate variation is a key aspect of the evolution of many organisms that can be modeled using molecular clock models. For example, fixed local clocks revealed the role of episodic evolution in the emergence of SARS-CoV-2 variants of concern. Like all statistical models, however, the reliability of such inferences is contingent on an assessment of statistical evidence. We present a novel Bayesian phylogenetic approach for detecting episodic evolution. It consists of computing Bayes factors, as the ratio of posterior and prior odds of evolutionary rate increases, effectively quantifying support for the effect size. We conducted an extensive simulation study to illustrate the power of this method and benchmarked it to formal model comparison of a range of molecular clock models using (log) marginal likelihood estimation, and to inference under a random local clock model. Quantifying support for the effect size has higher sensitivity than formal model testing and is straight-forward to compute, because it only needs samples from the posterior and prior distribution. However, formal model testing has the advantage of accommodating a wide range molecular clock models. We also assessed the ability of an automated approach, known as the random local clock, where branches under episodic evolution may be detected without their a priori definition. In an empirical analysis of a data set of SARS-CoV-2 genomes, we find "very strong" evidence for episodic evolution. Our results provide guidelines and practical methods for Bayesian detection of episodic evolution, as well as avenues for further research into this phenomenon.

Intra-host mutation rate of acute SARS-CoV-2 infection during the initial pandemic wave

SARS-CoV-2 mutation is minimized through a proofreading function encoded by NSP-14. Most estimates of the SARS-CoV-2 mutation rate are derived from population based sequence data. Our understanding of SARS-CoV-2 evolution might be enhanced through analysis of intra-host viral mutation rates in specific populations. Viral genome analysis was performed between paired samples and mutations quantified at allele frequencies (AF) ≥ 0.25, ≥ 0.5 and ≥ 0.75. Mutation rate was determined employing F81 and JC69 evolution models and compared between isolates with (ΔNSP-14) and without (wtNSP-14) non-synonymous mutations in NSP-14 and by patient comorbidity. Forty paired samples with median interval of 13 days [IQR 8.5-20] were analyzed. The estimated mutation rate by F81 modeling was 93.6 (95%CI 90.8-96.4], 40.7 (95%CI 38.9-42.6) and 34.7 (95%CI 33.0-36.4) substitutions/genome/year at AF ≥ 0.25, ≥ 0.5, ≥ 0.75 respectively. Mutation rate in ΔNSP-14 were significantly elevated at AF ≥ 0.25 vs wtNSP-14. Patients with immune comorbidities had higher mutation rate at all allele frequencies. Intra-host SARS-CoV-2 mutation rates are substantially higher than those reported through population analysis. Virus strains with altered NSP-14 have accelerated mutation rate at low AF. Immunosuppressed patients have elevated mutation rate at all AF. Understanding intra-host virus evolution will aid in current and future pandemic modeling.

Immune evasion and ACE2 binding affinity contribute to SARS-CoV-2 evolution

Mutations in the SARS-CoV-2 genome could confer resistance to pre-existing antibodies and/or increased transmissibility. The recently emerged Omicron subvariants exhibit a strong tendency for immune evasion, suggesting adaptive evolution. However, because previous studies have been limited to specific lineages or subsets of mutations, the overall evolutionary trajectory of SARS-CoV-2 and the underlying driving forces are still not fully understood. Here we analysed all open-access SARS-CoV-2 genomes (up to November 2022) and correlated the mutation incidence and fitness changes with the impacts of mutations on immune evasion and ACE2 binding affinity. Our results show that the Omicron lineage had an accelerated mutation rate in the RBD region, while the mutation incidence in other genomic regions did not change dramatically over time. Mutations in the RBD region exhibited a lineage-specific pattern and tended to become more aggregated over time, and the mutation incidence was positively correlated with the strength of antibody pressure. Additionally, mutation incidence was positively correlated with changes in ACE2 binding affinity, but with a lower correlation coefficient than with immune evasion. In contrast, the effect of mutations on fitness was more closely correlated with changes in ACE2 binding affinity than with immune evasion. Our findings suggest that immune evasion and ACE2 binding affinity play significant and diverse roles in the evolution of SARS-CoV-2.

Rational design of a booster vaccine against COVID-19 based on antigenic distance

Current COVID-19 vaccines are highly effective against symptomatic disease, but repeated booster doses using vaccines based on the ancestral strain offer limited additional protection against SARS-CoV-2 variants of concern (VOCs). To address this, we used antigenic distance to in silico select optimized booster vaccine seed strains effective against both current and future VOCs. Our model suggests that a SARS-CoV-1-based booster vaccine has the potential to cover a broader range of VOCs. Candidate vaccines including the spike protein from ancestral SARS-CoV-2, Delta, Omicron (BA.1), SARS-CoV-1, or MERS-CoV were experimentally evaluated in mice following two doses of the BNT162b2 vaccine. The SARS-CoV-1-based booster vaccine outperformed other candidates in terms of neutralizing antibody breadth and duration, as well as protective activity against Omicron (BA.2) challenge. This study suggests a unique strategy for selecting booster vaccines based on antigenic distance, which may be useful in designing future booster vaccines as new SARS-CoV-2 variants emerge.

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.

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.

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.

Enhancing SARS-CoV-2 Surveillance through Regular Genomic Sequencing in Spain: The RELECOV Network

Millions of SARS-CoV-2 whole genome sequences have been generated to date. However, good quality data and adequate surveillance systems are required to contribute to meaningful surveillance in public health. In this context, the network of Spanish laboratories for coronavirus (RELECOV) was created with the main goal of promoting actions to speed up the detection, analyses, and evaluation of SARS-CoV-2 at a national level, partially structured and financed by an ECDC-HERA-Incubator action (ECDC/GRANT/2021/024). A SARS-CoV-2 sequencing quality control assessment (QCA) was developed to evaluate the network's technical capacity. QCA full panel results showed a lower hit rate for lineage assignment compared to that obtained for variants. Genomic data comprising 48,578 viral genomes were studied and evaluated to monitor SARS-CoV-2. The developed network actions showed a 36% increase in sharing viral sequences. In addition, analysis of lineage/sublineage-defining mutations to track the virus showed characteristic mutation profiles for the Delta and Omicron variants. Further, phylogenetic analyses strongly correlated with different variant clusters, obtaining a robust reference tree. The RELECOV network has made it possible to improve and enhance the genomic surveillance of SARS-CoV-2 in Spain. It has provided and evaluated genomic tools for viral genome monitoring and characterization that make it possible to increase knowledge efficiently and quickly, promoting the genomic surveillance of SARS-CoV-2 in Spain.

Contact-number-driven virus evolution: A multi-level modeling framework for the evolution of acute or persistent RNA virus infection

Viruses evolve in infected host populations, and host population dynamics affect viral evolution. RNA viruses with a short duration of infection and a high peak viral load, such as SARS-CoV-2, are maintained in human populations. By contrast, RNA viruses characterized by a long infection duration and a low peak viral load (e.g., borna disease virus) can be maintained in nonhuman populations, and the process of the evolution of persistent viruses has rarely been explored. Here, using a multi-level modeling approach including both individual-level virus infection dynamics and population-scale transmission, we consider virus evolution based on the host environment, specifically, the effect of the contact history of infected hosts. We found that, with a highly dense contact history, viruses with a high virus production rate but low accuracy are likely to be optimal, resulting in a short infectious period with a high peak viral load. In contrast, with a low-density contact history, viral evolution is toward low virus production but high accuracy, resulting in long infection durations with low peak viral load. Our study sheds light on the origin of persistent viruses and why acute viral infections but not persistent virus infection tends to prevail in human society.

Border Control for Infectious Respiratory Disease Pandemics: A Modelling Study for H1N1 and Four Strains of SARS-CoV-2

Post-pandemic economic recovery relies on border control for safe cross-border movement. Following the COVID-19 pandemic, we investigate whether effective strategies generalize across diseases and variants. For four SARS-CoV-2 variants and influenza A-H1N1, we simulated 21 strategy families of varying test types and frequencies, quantifying expected transmission risk, relative to no control, by strategy family and quarantine length. We also determined minimum quarantine lengths to suppress relative risk below given thresholds. SARS-CoV-2 variants showed similar relative risk across strategy families and quarantine lengths, with at most 2 days' between-variant difference in minimum quarantine lengths. ART-based and PCR-based strategies showed comparable effectiveness, with regular testing strategies requiring at most 9 days. For influenza A-H1N1, ART-based strategies were ineffective. Daily ART testing reduced relative risk only 9% faster than without regular testing. PCR-based strategies were moderately effective, with daily PCR (0-day delay) testing requiring 16 days for the second-most stringent threshold. Viruses with high typical viral loads and low transmission risk given low viral loads, such as SARS-CoV-2, are effectively controlled with moderate-sensitivity tests (ARTs) and modest quarantine periods. Viruses with low typical viral loads and substantial transmission risk at low viral loads, such as influenza A-H1N1, require high-sensitivity tests (PCR) and longer quarantine periods.

Comparative epidemic expansion of SARS-CoV-2 variants Delta and Omicron in the Brazilian State of Amazonas

The SARS-CoV-2 variants of concern (VOCs) Delta and Omicron spread globally during mid and late 2021, respectively. In this study, we compare the dissemination dynamics of these VOCs in the Amazonas state, one of Brazil's most heavily affected regions. We sequenced the virus genome from 4128 patients collected in Amazonas between July 1st, 2021, and January 31st, 2022, and investigated the viral dynamics using a phylodynamic approach. The VOCs Delta and Omicron BA.1 displayed similar patterns of phylogeographic spread but different epidemic dynamics. The replacement of Gamma by Delta was gradual and occurred without an upsurge of COVID-19 cases, while the rise of Omicron BA.1 was extremely fast and fueled a sharp increase in cases. Thus, the dissemination dynamics and population-level impact of new SARS-CoV-2 variants introduced in the Amazonian population after mid-2021, a setting with high levels of acquired immunity, greatly vary according to their viral phenotype.

The evolution of SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused millions of deaths and substantial morbidity worldwide. Intense scientific effort to understand the biology of SARS-CoV-2 has resulted in daunting numbers of genomic sequences. We witnessed evolutionary events that could mostly be inferred indirectly before, such as the emergence of variants with distinct phenotypes, for example transmissibility, severity and immune evasion. This Review explores the mechanisms that generate genetic variation in SARS-CoV-2, underlying the within-host and population-level processes that underpin these events. We examine the selective forces that likely drove the evolution of higher transmissibility and, in some cases, higher severity during the first year of the pandemic and the role of antigenic evolution during the second and third years, together with the implications of immune escape and reinfections, and the increasing evidence for and potential relevance of recombination. In order to understand how major lineages, such as variants of concern (VOCs), are generated, we contrast the evidence for the chronic infection model underlying the emergence of VOCs with the possibility of an animal reservoir playing a role in SARS-CoV-2 evolution, and conclude that the former is more likely. We evaluate uncertainties and outline scenarios for the possible future evolutionary trajectories of SARS-CoV-2.

Immunosuppression as a Hub for SARS-CoV-2 Mutational Drift

The clinical course of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), is largely determined by host factors, with a wide range of outcomes. Despite an extensive vaccination campaign and high rates of infection worldwide, the pandemic persists, adapting to overcome antiviral immunity acquired through prior exposure. The source of many such major adaptations is variants of concern (VOCs), novel SARS-CoV-2 variants produced by extraordinary evolutionary leaps whose origins remain mostly unknown. In this study, we tested the influence of factors on the evolutionary course of SARS-CoV-2. Electronic health records of individuals infected with SARS-CoV-2 were paired to viral whole-genome sequences to assess the effects of host clinical parameters and immunity on the intra-host evolution of SARS-CoV-2. We found slight, albeit significant, differences in SARS-CoV-2 intra-host diversity, which depended on host parameters such as vaccination status and smoking. Only one viral genome had significant alterations as a result of host parameters; it was found in an immunocompromised, chronically infected woman in her 70s. We highlight the unusual viral genome obtained from this woman, which had an accelerated mutational rate and an excess of rare mutations, including near-complete truncating of the accessory protein ORF3a. Our findings suggest that the evolutionary capacity of SARS-CoV-2 during acute infection is limited and mostly unaffected by host characteristics. Significant viral evolution is seemingly exclusive to a small subset of COVID-19 cases, which typically prolong infections in immunocompromised patients. In these rare cases, SARS-CoV-2 genomes accumulate many impactful and potentially adaptive mutations; however, the transmissibility of such viruses remains unclear.

Rooting and Dating Large SARS-CoV-2 Trees by Modeling Evolutionary Rate as a Function of Time

Almost all published rooting and dating studies on SARS-CoV-2 assumed that (1) evolutionary rate does not change over time although different lineages can have different evolutionary rates (uncorrelated relaxed clock), and (2) a zoonotic transmission occurred in Wuhan and the culprit was immediately captured, so that only the SARS-CoV-2 genomes obtained in 2019 and the first few months of 2020 (resulting from the first wave of the global expansion from Wuhan) are sufficient for dating the common ancestor. Empirical data contradict the first assumption. The second assumption is not warranted because mounting evidence suggests the presence of early SARS-CoV-2 lineages cocirculating with the Wuhan strains. Large trees with SARS-CoV-2 genomes beyond the first few months are needed to increase the likelihood of finding SARS-CoV-2 lineages that might have originated at the same time as (or even before) those early Wuhan strains. I extended a previously published rapid rooting method to model evolutionary rate as a linear function instead of a constant. This substantially improves the dating of the common ancestor of sampled SARS-CoV-2 genomes. Based on two large trees with 83,688 and 970,777 high-quality and full-length SARS-CoV-2 genomes that contain complete sample collection dates, the common ancestor was dated to 12 June 2019 and 7 July 2019 with the two trees, respectively. The two data sets would give dramatically different or even absurd estimates if the rate was treated as a constant. The large trees were also crucial for overcoming the high rate-heterogeneity among different viral lineages. The improved method was implemented in the software TRAD.

Propagating uncertainty about molecular evolution models and prior distributions to phylogenetic trees

Phylogenetic trees constructed from molecular sequence data rely on largely arbitrary assumptions about the substitution model, the distribution of substitution rates across sites, the version of the molecular clock, and, in the case of Bayesian inference, the prior distribution. Those assumptions affect results reported in the form of clade probabilities and error bars on divergence times and substitution rates. Overlooking the uncertainty in the assumptions leads to overly confident conclusions in the form of inflated clade probabilities and short confidence intervals or credible intervals. This paper demonstrates how to propagate that uncertainty by combining the models considered along with all of their assumptions, including their prior distributions. The combined models incorporate much more of the uncertainty than Bayesian model averages since the latter tend to settle on a single model due to the higher-level assumption that one of the models is true. Nucleotide sequence data illustrates the proposed model combination method.

Detecting punctuated evolution in SARS-CoV-2 over the first year of the pandemic

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) evolved slowly over the first year of the Coronavirus Disease 19 (COVID-19) pandemic with differential mutation rates across lineages. Here, we explore how this variation arose. Whether evolutionary change accumulated gradually within lineages or during viral lineage branching is unclear. Using phylogenetic regression models, we show that ~13% of SARS-CoV-2 genomic divergence up to May 2020 is attributable to lineage branching events (punctuated evolution). The net number of branching events along lineages predicts ~5% of the deviation from the strict molecular clock. We did not detect punctuated evolution in SARS-CoV-1, possibly due to the small sample size, and in sarbecovirus broadly, likely due to a different evolutionary process altogether. Punctuation in SARS-CoV-2 is probably neutral because most mutations were not positively selected and because the strength of the punctuational effect remained constant over time, at least until May 2020, and across continents. However, the small punctuational contribution to SARS-CoV-2 diversity is consistent with the founder effect arising from narrow transmission bottlenecks. Therefore, punctuation in SARS-CoV-2 may represent the macroevolutionary consequence (rate variation) of a microevolutionary process (transmission bottleneck).

Accelerated SARS-CoV-2 intrahost evolution leading to distinct genotypes during chronic infection

The chronic infection hypothesis for novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant emergence is increasingly gaining credence following the appearance of Omicron. Here, we investigate intrahost evolution and genetic diversity of lineage B.1.517 during a SARS-CoV-2 chronic infection lasting for 471 days (and still ongoing) with consistently recovered infectious virus and high viral genome copies. During the infection, we find an accelerated virus evolutionary rate translating to 35 nucleotide substitutions per year, approximately 2-fold higher than the global SARS-CoV-2 evolutionary rate. This intrahost evolution results in the emergence and persistence of at least three genetically distinct genotypes, suggesting the establishment of spatially structured viral populations continually reseeding different genotypes into the nasopharynx. Finally, we track the temporal dynamics of genetic diversity to identify advantageous mutations and highlight hallmark changes for chronic infection. Our findings demonstrate that untreated chronic infections accelerate SARS-CoV-2 evolution, providing an opportunity for the emergence of genetically divergent variants.

Infection dynamics, transmission, and evolution after an outbreak of porcine reproductive and respiratory syndrome virus

The present study was aimed at describing the infection dynamics, transmission, and evolution of porcine reproductive and respiratory syndrome virus (PRRSV) after an outbreak in a 300-sow farrow-to-wean farm that was implementing a vaccination program. Three subsequent batches of piglets (9-11 litters/batch) were followed 1.5 (Batch 1), 8 (Batch 2), and 12 months after (Batch 3) from birth to 9 weeks of age. The RT-qPCR analysis showed that shortly after the outbreak (Batch 1), one third of sows were delivering infected piglets and the cumulative incidence reached 80% by 9 weeks of age. In contrast, in Batch 2, only 10% animals in total got infected in the same period. In Batch 3, 60% litters had born-infected animals and cumulative incidence rose to 78%. Higher viral genetic diversity was observed in Batch 1, with 4 viral clades circulating, of which 3 could be traced to vertical transmission events, suggesting the existence of founder viral variants. In Batch 3 though only one variant was found, distinguishable from those circulating previously, suggesting that a selection process had occurred. ELISA antibodies at 2 weeks of age were significantly higher in Batch 1 and 3 compared to Batch 2, while low levels of neutralizing antibodies were detected in either piglets or sows in all batches. In addition, some sows present in Batch 1 and 3 delivered infected piglets twice, and the offspring were devoid of neutralizing antibodies at 2 weeks of age. These results suggest that a high viral diversity was featured at the initial outbreak followed by a phase of limited circulation, but subsequently an escape variant emerged in the population causing a rebound of vertical transmission. The presence of unresponsive sows that had vertical transmission events could have contributed to the transmission. Moreover, the records of contacts between animals and the phylogenetic analyses allowed to trace back 87 and 47% of the transmission chains in Batch 1 and 3, respectively. Most animals transmitted the infection to 1-3 pen-mates, but super-spreaders were also identified. One animal that was born-viremic and persisted as viremic for the whole study period did not contribute to transmission.

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.

A perspective study of the possible impact of obeticholic acid against SARS-CoV-2 infection

The causative agent of CoV disease 2019 is a new coronavirus CoV type 2, affecting the respiratory tract with severe manifestations (SARS-CoV-2). Covid-19 is mainly symptomless, with slight indications in about 85% of the affected cases. Many efforts were done to face this pandemic by testing different drugs and agents to make treatment protocols in different countries. However, the use of these proposed drugs is associated with the development of adverse events. Remarkably, the successive development of SARS-CoV-2 variants which could affect persons even they were vaccinated, prerequisite wide search to find efficient and safe agents to face SARS-CoV-2 infection. Obeticholic acid (OCA), which has anti-inflammatory effects, may efficiently treat Covid-19. Thus, the goal of this perspective study is to focus on the possible medicinal effectiveness in managing Covid-19. OCA is a powerful farnesoid X receptor (FXR) agonist possessing marked antiviral and anti-inflammatory effects. FXR is dysregulated in Covid-19 resulting in hyper-inflammation with concurrent occurrence of hypercytokinemia. Interestingly, OCA inhibits the reaction between this virus and angiotensin-converting enzyme type 2 (ACE2) receptors. FXR agonists control the expression of ACE2 and the inflammatory signaling pathways in this respiratory syndrome, which weakens the effects of Covid-19 disease and accompanied complications. Taken together, FXR agonists like OCA may reveal both direct and indirect impacts in the modulation of immune reaction in SARS-CoV-2 conditions. It is highly recommended to perform many investigations regarding different phases of the discovery of new drugs.