Convergent Evolution of Multiple Mutations Improves the Viral Fitness of SARS-CoV-2 Variants by Balancing Positive and Negative Selection

Characterization of biotinylated human ACE2 and SARS-CoV-2 Omicron BA.4/5 spike protein reference materials

Accurate diagnostic and serology assays are required for the continued management of the COVID-19 pandemic yet spike protein mutations and intellectual property concerns with antigens and antibodies used in various test kits render comparability assessments difficult. As the use of common, well-characterized reagents can help address this lack of standardization, the National Research Council Canada has produced two protein reference materials (RMs) for use in SARS-CoV-2 serology assays: biotinylated human angiotensin-converting enzyme 2 RM, ACE2-1, and SARS-CoV-2 Omicron BA.4/5 spike protein RM, OMIC-1. Reference values were assigned through a combination of amino acid analysis via isotope dilution liquid chromatography tandem mass spectrometry following acid hydrolysis, and ultraviolet-visible (UV-Vis) spectrophotometry at 280 nm. Vial-to-vial homogeneity was established using UV-Vis measurements, and protein oligomeric status, monitored by size exclusion liquid chromatography (LC-SEC), was used to evaluate transportation, storage, and freeze-thaw stabilities. The molar protein concentration in ACE2-1 was 25.3 ± 1.7 µmol L-1 (k = 2, 95% CI) and consisted almost exclusively (98%) of monomeric ACE2, while OMIC-1 contained 5.4 ± 0.5 µmol L-1 (k = 2) spike protein in a mostly (82%) trimeric form. Glycoprotein molar mass determination by LC-SEC with multi-angle light scattering detection facilitated calculation of corresponding mass concentrations. To confirm protein functionality, the binding of OMIC-1 to immobilized ACE2-1 was investigated with surface plasmon resonance and the resulting dissociation constant, KD ~ 4.4 nM, was consistent with literature values.

Biophysical evolution of the receptor-binding domains of SARS-CoVs

With hundreds of coronaviruses (CoVs) identified in bats that can infect humans, it is essential to understand how CoVs that affected the human population have evolved. Seven known CoVs have infected humans, of which three CoVs caused severe disease with high mortalities: severe acute respiratory syndrome (SARS)-CoV emerged in 2002, Middle East respiratory syndrome-CoV in 2012, and SARS-CoV-2 in 2019. SARS-CoV and SARS-CoV-2 belong to the same family, follow the same receptor pathway, and use their receptor-binding domain (RBD) of spike protein to bind to the angiotensin-converting enzyme 2 (ACE2) receptor on the human epithelial cell surface. The sequence of the two RBDs is divergent, especially in the receptor-binding motif that directly interacts with ACE2. We probed the biophysical differences between the two RBDs in terms of their structure, stability, aggregation, and function. Since RBD is being explored as an antigen in protein subunit vaccines against CoVs, determining these biophysical properties will also aid in developing stable protein subunit vaccines. Our results show that, despite RBDs having a similar three-dimensional structure, they differ in their thermodynamic stability. RBD of SARS-CoV-2 is significantly less stable than that of SARS-CoV. Correspondingly, SARS-CoV-2 RBD shows a higher aggregation propensity. Regarding binding to ACE2, less stable SARS-CoV-2 RBD binds with a higher affinity than more stable SARS-CoV RBD. In addition, SARS-CoV-2 RBD is more homogenous in terms of its binding stoichiometry toward ACE2 compared to SARS-CoV RBD. These results indicate that SARS-CoV-2 RBD differs from SARS-CoV RBD in terms of its stability, aggregation, and function, possibly originating from the diverse receptor-binding motifs. Higher aggregation propensity and decreased stability of SARS-CoV-2 RBD warrant further optimization of protein subunit vaccines that use RBD as an antigen by inserting stabilizing mutations or formulation screening.

Dynamics of water-mediated interaction effects on the stability and transmission of Omicron

SARS-Cov-2 Omicron variant and its highly transmissible sublineages amidst news of emerging hybrid variants strengthen the evidence of its ability to rapidly spread and evolve giving rise to unprecedented future waves. Owing to the presence of isolated RBD, monomeric and trimeric Cryo-EM structures of spike protein in complex with ACE2 receptor, comparative analysis of Alpha, Beta, Gamma, Delta, and Omicron assist in a rational assessment of their probability to evolve as new or hybrid variants in future. This study proposes the role of hydration forces in mediating Omicron function and dynamics based on a stronger interplay between protein and solvent with each Covid wave. Mutations of multiple hydrophobic residues into hydrophilic residues underwent concerted interactions with water leading to variations in charge distribution in Delta and Omicron during molecular dynamics simulations. Moreover, comparative analysis of interacting moieties characterized a large number of mutations lying at RBD into constrained, homologous and low-affinity groups referred to as mutational drivers inferring that the probability of future mutations relies on their function. Furthermore, the computational findings reveal a significant difference in angular distances among variants of concern due 3 amino acid insertion (EPE) in Omicron variant that not only facilitates tight domain organization but also seems requisite for characterization of mutational processes. The outcome of this work signifies the possible relation between hydration forces, their impact on conformation and binding affinities, and viral fitness that will significantly aid in understanding dynamics of drug targets for Covid-19 countermeasures. The emerging scenario is that hydration forces and hydrophobic interactions are crucial variables to probe in mutational analysis to explore conformational landscape of macromolecules and reveal the molecular origins of protein behaviors.

Amolong1Mendoza TolentinoJarel Elgin1ChenLuo1ShimizuRyo2Monira BegumM. S. T.2TakahashiOtowa2IchiharaKimiko2JonathanMichael2MugitaYuka2SuzukiSaori3SuzukiTateki4KimuraKanako4NakajimaYukari4YajimaHisano4HashimotoRina4WatanabeYukio4SakamotoAyaka4YasuharaNaoko4NagataKayoko4NomuraRyosuke4HorisawaYoshihito4TashiroYusuke4KawaiYugo4ShibataniYuki5NishiuchiTomoko5YoshidaIsao6KawabataRyoko7MatsunoKeita8NaoNaganori9SawaHirofumi9TanakaShinya10TsudaMasumi10WangLei10OdaYoshikata10FerdousZannatul10ShishidoKenji10MotozonoChihiro11ToyodaMako11UenoTakamasa11TabataKaori121Institute of Medical Science, University of Tokyo, Tokyo, Japan2Joint Research Center for Human Retrovirus infection, Kumamoto University, Kumamoto, Japan3Hokkaido University, Sapporo, Japan4Kyoto University, Kyoto, Japan5University of Miyazaki, Miyazaki, Japan6Tokyo Metropolitan Institute of Public Health, Tokyo, Japan7Hiroshima University, Hiroshima, Japan8One Health Research Center, Hokkaido University, Sapporo, Japan9International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan10Hokkaido University, Sapporo, Japan11Joint Research Center for Human Retrovirus infection, Kumamoto, Japan12Kyushu University, Fukuoka, Japan, Ito J, Shirakawa K, Takayama K, Irie T, Hashiguchi T, Nakagawa S, Fukuhara T, Saito A, Ikeda T, Sato K. Multiple mutations of SARS-CoV-2 Omicron BA.2 variant orchestrate its virological characteristics

IMPORTANCE

Most studies investigating the characteristics of emerging SARS-CoV-2 variants have been focusing on mutations in the spike proteins that affect viral infectivity, fusogenicity, and pathogenicity. However, few studies have addressed how naturally occurring mutations in the non-spike regions of the SARS-CoV-2 genome impact virological properties. In this study, we proved that multiple SARS-CoV-2 Omicron BA.2 mutations, one in the spike protein and another downstream of the spike gene, orchestrally characterize this variant, shedding light on the importance of Omicron BA.2 mutations out of the spike protein.

From De Novo Design to Redesign: Harnessing Computational Protein Design for Understanding SARS-CoV-2 Molecular Mechanisms and Developing Therapeutics

The continuous emergence of novel SARS-CoV-2 variants and subvariants serves as compelling evidence that COVID-19 is an ongoing concern. The swift, well-coordinated response to the pandemic highlights how technological advancements can accelerate the detection, monitoring, and treatment of the disease. Robust surveillance systems have been established to understand the clinical characteristics of new variants, although the unpredictable nature of these variants presents significant challenges. Some variants have shown resistance to current treatments, but innovative technologies like computational protein design (CPD) offer promising solutions and versatile therapeutics against SARS-CoV-2. Advances in computing power, coupled with open-source platforms like AlphaFold and RFdiffusion (employing deep neural network and diffusion generative models), among many others, have accelerated the design of protein therapeutics with precise structures and intended functions. CPD has played a pivotal role in developing peptide inhibitors, mini proteins, protein mimics, decoy receptors, nanobodies, monoclonal antibodies, identifying drug-resistance mutations, and even redesigning native SARS-CoV-2 proteins. Pending regulatory approval, these designed therapies hold the potential for a lasting impact on human health and sustainability. As SARS-CoV-2 continues to evolve, use of such technologies enables the ongoing development of alternative strategies, thus equipping us for the "New Normal".

Tracking the evolution of the SARS-CoV-2 Delta variant of concern: analysis of genetic diversity and selection across the whole viral genome

Background

Since 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has diversified extensively, producing five highly virulent lineages designated as variants of concern (VOCs). The Delta VOC emerged in India with increased transmission, immune evasion, and mortality, causing a massive global case surge in 2021. This study aims to understand how the Delta VOC evolved by characterizing mutation patterns in the viral population before and after its emergence. Furthermore, we aim to identify the influence of positive and negative selection on VOC evolution and understand the prevalence of different mutation types in the viral genome.

Methods

Three groups of whole viral genomes were retrieved from GISAID, sourced from India, with collection periods as follows: Group A-during the initial appearance of SARS-CoV-2; Group B-just before the emergence of the Delta variant; Group C-after the establishment of the Delta variant in India. Mutations in >1% of each group were identified with BioEdit to reveal differences in mutation quantity and type. Sites under positive or negative selection were identified with FUBAR. The results were compared to determine how mutations correspond with selective pressures and how viral mutation profiles changed to reflect genetic diversity before and after VOC emergence.

Results

The number of mutations increased progressively in Groups A-C, with Group C reporting a 2.2- and 1.9-fold increase from Groups A and B, respectively. Among all the observed mutations, Group C had the highest percentage of deletions (22.7%; vs. 4.2% and 2.6% in Groups A and B, respectively), and most mutations altered the final amino acid code, such as non-synonymous substitutions and deletions. Conversely, Group B had the most synonymous substitutions that are effectively silent. The number of sites experiencing positive selection increased in Groups A-C, but Group B had 2.4- and 2.6 times more sites under negative selection compared to Groups A and C, respectively.

Conclusion

Our findings demonstrated that viral genetic diversity continuously increased during and after the emergence of the Delta VOC. Despite this, Group B reports heightened negative selection, which potentially preserves important gene regions during evolution. Group C contains an unprecedented quantity of mutations and positively selected sites, providing strong evidence of active viral adaptation in the population.

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.

Convergent Evolution in SARS-CoV-2 Spike Creates a Variant Soup from Which New COVID-19 Waves Emerge

The first 2 years of the COVID-19 pandemic were mainly characterized by recurrent mutations of SARS-CoV-2 Spike protein at residues K417, L452, E484, N501 and P681 emerging independently across different variants of concern (Alpha, Beta, Gamma, and Delta). Such homoplasy is a marker of convergent evolution. Since Spring 2022 and the third year of the pandemic, with the advent of Omicron and its sublineages, convergent evolution has led to the observation of different lineages acquiring an additional group of mutations at different amino acid residues, namely R346, K444, N450, N460, F486, F490, Q493, and S494. Mutations at these residues have become increasingly prevalent during Summer and Autumn 2022, with combinations showing increased fitness. The most likely reason for this convergence is the selective pressure exerted by previous infection- or vaccine-elicited immunity. Such accelerated evolution has caused failure of all anti-Spike monoclonal antibodies, including bebtelovimab and cilgavimab. While we are learning how fast coronaviruses can mutate and recombine, we should reconsider opportunities for economically sustainable escape-proof combination therapies, and refocus antibody-mediated therapeutic efforts on polyclonal preparations that are less likely to allow for viral immune escape.

A Simple Epidemiologic Model for Predicting Impaired Neutralization of New SARS-CoV-2 Variants

This study is aimed at developing a simple epidemiologic model that could help predict the impaired neutralization of new SARS-CoV-2 variants. We explored the potential association between neutralization of recent and more prevalent SARS-CoV-2 sublineages belonging to the Omicron family (i.e., BA.4/5, BA.4.6, BA.2.75.2, BQ.1.1 and XBB.1) expressed as FFRNT50 (>50% suppression of fluorescent foci fluorescent focus reduction neutralization test) in recipients of four doses of monovalent mRNA-based coronavirus disease 2019 (COVID-19) vaccines, with epidemiologic variables like emergence date and number of spike protein mutations of these sublineages, cumulative worldwide COVID-19 cases and cumulative number of COVID-19 vaccine doses administered worldwide at the time of SARS-CoV-2 Omicron sublineage emergence. In the univariate analysis, the FFRNT50 value for the different SARS-CoV-2 Omicron sublineages was significantly associated with all such variables except with the number of spike protein mutations. Such associations were confirmed in the multivariate analysis, which enabled the construction of the equation: “−0.3917 × [Emergence (date)] + 1.403 × [COVID-19 cases (million)] − 121.8 × [COVID-19 Vaccine doses (billion)] + 18,250”, predicting the FFRNT50 value of the five SARS-CoV-2 Omicron sublineages with 0.996 accuracy (p = 0.013). We have shown in this work that a simple mathematical approach, encompassing a limited number of widely available epidemiologic variables, such as emergence date of new variants and number of COVID-19 cases and vaccinations, could help identifying the emergence and surge of future lineages with major propensity to impair humoral immunity.

Compensatory epistasis maintains ACE2 affinity in SARS-CoV-2 Omicron BA.1

The Omicron BA.1 variant emerged in late 2021 and quickly spread across the world. Compared to the earlier SARS-CoV-2 variants, BA.1 has many mutations, some of which are known to enable antibody escape. Many of these antibody-escape mutations individually decrease the spike receptor-binding domain (RBD) affinity for ACE2, but BA.1 still binds ACE2 with high affinity. The fitness and evolution of the BA.1 lineage is therefore driven by the combined effects of numerous mutations. Here, we systematically map the epistatic interactions between the 15 mutations in the RBD of BA.1 relative to the Wuhan Hu-1 strain. Specifically, we measure the ACE2 affinity of all possible combinations of these 15 mutations (215 = 32,768 genotypes), spanning all possible evolutionary intermediates from the ancestral Wuhan Hu-1 strain to BA.1. We find that immune escape mutations in BA.1 individually reduce ACE2 affinity but are compensated by epistatic interactions with other affinity-enhancing mutations, including Q498R and N501Y. Thus, the ability of BA.1 to evade immunity while maintaining ACE2 affinity is contingent on acquiring multiple interacting mutations. Our results implicate compensatory epistasis as a key factor driving substantial evolutionary change for SARS-CoV-2 and are consistent with Omicron BA.1 arising from a chronic infection.