S373P Mutation Stabilizes the Receptor-Binding Domain of the Spike Protein in Omicron and Promotes Binding

iHDSel software: The price equation and the population stability index to detect genomic patterns compatible with selective sweeps. An example with SARS-CoV-2

A large number of methods have been developed and continue to evolve for detecting the signatures of selective sweeps in genomes. Significant advances have been made, including the combination of different statistical strategies and the incorporation of artificial intelligence (machine learning) methods. Despite these advances, several common problems persist, such as the unknown null distribution of the statistics used, necessitating simulations and resampling to assign significance to the statistics. Additionally, it is not always clear how deviations from the specific assumptions of each method might affect the results. In this work, allelic classes of haplotypes are used along with the informational interpretation of the Price equation to design a statistic with a known distribution that can detect genomic patterns caused by selective sweeps. The statistic consists of Jeffreys divergence, also known as the population stability index, applied to the distribution of allelic classes of haplotypes in two samples. Results with simulated data show optimal performance of the statistic in detecting divergent selection. Analysis of real severe acute respiratory syndrome coronavirus 2 genome data also shows that some of the sites playing key roles in the virus's fitness and immune escape capability are detected by the method. The new statistic, called JHAC , is incorporated into the iHDSel (informed HacDivSel) software available at https://acraaj.webs.uvigo.es/iHDSel.html.

Unveiling the Dynamic Mechanism of SARS-CoV-2 Entry Host Cells at the Single-Particle Level

Understanding the dynamic features of severe acute respiratory coronavirus 2 (SARS-CoV-2) binding to the cell membrane and entry cells is crucial for comprehending viral pathogenesis and transmission and facilitating the development of effective drugs against COVID-19. Herein, we employed atomic force microscopy (AFM)-based single-molecule force spectroscopy (SMFS) to study the binding dynamics between the virus and cell membrane. Our findings revealed that the Omicron variant of SARS-CoV-2 virus-like particles (VLPs) exhibited a slightly stronger affinity for the angiotensin-converting enzyme-2 (ACE2) receptor compared with the Delta variant and was significantly higher than the wild-type (WT). Using a real-time force-tracing technique, we quantified the dynamic parameters for a single SARS-CoV-2 VLP entry into cells, showing that approximately 200 ms and 60 pN are required. The parameters aligned with the analysis obtained from coarse-grained molecular dynamics (CGMD) simulations. Additionally, the Omicron variant invades cells at a higher entry cell speed, smaller force, and higher probability. Furthermore, single-particle fluorescence tracking visually demonstrated clathrin-dependent endocytosis for SARS-CoV-2 entry into A549 cells. The dynamic features of endocytosis provide valuable insights into the SARS-CoV-2 entry mechanism and possible intervention strategies targeting the viral infection process.

Micro-second time-resolved X-ray single-molecule internal motions of SARS-CoV-2 spike variants

Single-molecule intramolecular dynamics were successfully measured for three variants of SARS-CoV-2 spike protein, alpha: B.1.1.7, delta: B.1.617, and omicron: B.1.1.529, with a time resolution of 100 μs using X-rays. The results were then compared with respect to the magnitude and directions of motions for the three variants. The largest 3-D intramolecular movement was observed for the omicron variant irrespective of ACE2 receptor binding. A more detailed analysis of the intramolecular motions revealed that the distribution state of intramolecular motion for the three variants was completely different with and without ACE2 receptor binding. The molecular dynamics for the trimeric spike protein of the omicron variant increased when ACE2 binding occurred. At that time, the diffusion constant increased from 71.0 [mrad2/ms] to 91.1 [mrad2/ms].

Spike deep mutational scanning helps predict success of SARS-CoV-2 clades

SARS-CoV-2 variants acquire mutations in the spike protein that promote immune evasion1 and affect other properties that contribute to viral fitness, such as ACE2 receptor binding and cell entry2,3. Knowledge of how mutations affect these spike phenotypes can provide insight into the current and potential future evolution of the virus. Here we use pseudovirus deep mutational scanning4 to measure how more than 9,000 mutations across the full XBB.1.5 and BA.2 spikes affect ACE2 binding, cell entry or escape from human sera. We find that mutations outside the receptor-binding domain (RBD) have meaningfully affected ACE2 binding during SARS-CoV-2 evolution. We also measure how mutations to the XBB.1.5 spike affect neutralization by serum from individuals who recently had SARS-CoV-2 infections. The strongest serum escape mutations are in the RBD at sites 357, 420, 440, 456 and 473; however, the antigenic effects of these mutations vary across individuals. We also identify strong escape mutations outside the RBD; however, many of them decrease ACE2 binding, suggesting they act by modulating RBD conformation. Notably, the growth rates of human SARS-CoV-2 clades can be explained in substantial part by the measured effects of mutations on spike phenotypes, suggesting our data could enable better prediction of viral evolution.

Mutations in the Receptor Binding Domain of Severe Acute Respiratory Coronavirus-2 Omicron Variant Spike Protein Significantly Stabilizes Its Conformation

The Omicron variant and its sub-lineages are the only current circulating SARS-CoV-2 viruses worldwide. In this study, the conformational stability of the isolated Receptor Binding Domain (RBD) of Omicron's spike protein is examined in detail. The parent Omicron lineage has over ten mutations in the ACE2 binding region of the RBD that are specifically associated with its β hairpin loop domain. It is demonstrated through biophysical molecular computations that the mutations in the β hairpin loop domain significantly increase the intra-protein interaction energies of intra-loop and loop-RBD interactions. The interaction energy increases include the formation of new hydrogen bonds in the β hairpin loop domain that help stabilize this critical ACE2 binding region. Our results also agree with recent experiments on the stability of Omicron's core β barrel domain, outside of its loop domain, and help demonstrate the overall conformational stability of the Omicron RBD. It is further shown here through dynamic simulations that the unbound state of the Omicron RBD remains closely aligned with the bound state configuration, which was not observed for the wild-type RBD. Overall, these studies demonstrate the significantly increased conformational stability of Omicron over its wild-type configuration and raise a number of questions on whether conformational stability could be a positive selection feature of SARS-CoV-2 viral mutational changes.

Mechanistic study of the transmission pattern of the SARS-CoV-2 omicron variant

The omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) characterized by 30 mutations in its spike protein, has rapidly spread worldwide since November 2021, significantly exacerbating the ongoing COVID-19 pandemic. In order to investigate the relationship between these mutations and the variant's high transmissibility, we conducted a systematic analysis of the mutational effect on spike-angiotensin-converting enzyme-2 (ACE2) interactions and explored the structural/energy correlation of key mutations, utilizing a reliable coarse-grained model. Our study extended beyond the receptor-binding domain (RBD) of spike trimer through comprehensive modeling of the full-length spike trimer rather than just the RBD. Our free-energy calculation revealed that the enhanced binding affinity between the spike protein and the ACE2 receptor is correlated with the increased structural stability of the isolated spike protein, thus explaining the omicron variant's heightened transmissibility. The conclusion was supported by our experimental analyses involving the expression and purification of the full-length spike trimer. Furthermore, the energy decomposition analysis established those electrostatic interactions make major contributions to this effect. We categorized the mutations into four groups and established an analytical framework that can be employed in studying future mutations. Additionally, our calculations rationalized the reduced affinity of the omicron variant towards most available therapeutic neutralizing antibodies, when compared with the wild type. By providing concrete experimental data and offering a solid explanation, this study contributes to a better understanding of the relationship between theories and observations and lays the foundation for future investigations.

Molecular Mechanism of Interaction between DNA Aptamer and Receptor-Binding Domain of Severe Acute Respiratory Syndrome Coronavirus 2 Variants Revealed by Steered Molecular Dynamics Simulations

The ongoing SARS-CoV-2 pandemic has underscored the urgent need for versatile and rapidly deployable antiviral strategies. While vaccines have been pivotal in controlling the spread of the virus, the emergence of new variants continues to pose significant challenges to global health. Here, our study focuses on a novel approach to antiviral therapy using DNA aptamers, short oligonucleotides with high specificity and affinity for their targets, as potential inhibitors against the spike protein of SARS-CoV-2 variants Omicron and JN.1. Our research utilizes steered molecular dynamics (SMD) simulations to elucidate the binding mechanisms of a specifically designed DNA aptamer, AM032-4, to the receptor-binding domain (RBD) of the aforementioned variants. The simulations reveal detailed molecular insights into the aptamer-RBD interaction, demonstrating the aptamer's potential to maintain effective binding in the face of rapid viral evolution. Our work not only demonstrates the dynamic interaction between aptamer-RBD for possible antiviral therapy but also introduces a computational method to study aptamer-protein interactions.

Unraveling the binding mechanisms of SARS-CoV-2 variants through molecular simulations

The emergence of SARS-CoV-2 variants like Delta (AY.29) and Omicron (EG.5) poses continued challenges for vaccines and therapeutics. Mutations in the viral spike protein are key in altering infectivity and immune evasion. This study uses computational modeling to investigate the molecular binding mechanisms between spike protein variants and the ACE2 host receptor. Using the MARTNI force field, coarse-grained molecular dynamics (CGMD) simulations and nudged elastic band (NEB) calculations explore spike-ACE2 interactions for the wild type, Delta variant, and Omicron variant. The simulations reveal Omicron has the strongest binding affinity at -128.35 ± 10.91 kcal/mol, followed by Delta and wild type. Key mutations in Delta and Omicron, like Q493R and Q498R, optimize electrostatic contacts, enhancing ACE2 interactions. The wild-type spike has the highest transition state energy barrier at 17.87 kcal/mol, while Delta has the lowest barrier at 9.21 kcal/mol. Despite slightly higher dual barriers, Omicron's increased binding energy lowers its overall barrier to rapidly bind ACE2. These findings provide residue-level insights into mutation effects on SARS-CoV-2 infectivity. The computational modeling elucidates mechanisms underlying spike-ACE2 binding kinetics, aiding the development of vaccines and therapies targeting emerging viral strains.

Single-molecule force stability of the SARS-CoV-2-ACE2 interface in variants-of-concern

Mutations in SARS-CoV-2 have shown effective evasion of population immunity and increased affinity to the cellular receptor angiotensin-converting enzyme 2 (ACE2). However, in the dynamic environment of the respiratory tract, forces act on the binding partners, which raises the question of whether not only affinity but also force stability of the SARS-CoV-2-ACE2 interaction might be a selection factor for mutations. Using magnetic tweezers, we investigate the impact of amino acid substitutions in variants of concern (Alpha, Beta, Gamma and Delta) and on force-stability and bond kinetic of the receptor-binding domain-ACE2 interface at a single-molecule resolution. We find a higher affinity for all of the variants of concern (>fivefold) compared with the wild type. In contrast, Alpha is the only variant of concern that shows higher force stability (by 17%) compared with the wild type. Using molecular dynamics simulations, we rationalize the mechanistic molecular origins of this increase in force stability. Our study emphasizes the diversity of contributions to the transmissibility of variants and establishes force stability as one of the several factors for fitness. Understanding fitness advantages opens the possibility for the prediction of probable mutations, allowing a rapid adjustment of therapeutics, vaccines and intervention measures.

Enzymatic Protein Immobilization for Nanobody Array

Antibody arrays play a pivotal role in the detection and quantification of biomolecules, with their effectiveness largely dependent on efficient protein immobilization. Traditional methods often use heterobifunctional cross-linking reagents for attaching functional residues in proteins to corresponding chemical groups on the substrate surface. However, this method does not control the antibody's anchoring point and orientation, potentially leading to reduced binding efficiency and overall performance. Another method using anti-antibodies as intermediate molecules to control the orientation can be used but it demonstrates lower efficiency. Here, we demonstrate a site-specific protein immobilization strategy utilizing OaAEP1 (asparaginyl endopeptidase) for building a nanobody array. Moreover, we used a nanobody-targeting enhanced green fluorescent protein (eGFP) as the model system to validate the protein immobilization method for building a nanobody array. Finally, by rapidly enriching eGFP, this method further highlights its potential for rapid diagnostic applications. This approach, characterized by its simplicity, high efficiency, and specificity, offers an advancement in the development of surface-modified protein arrays. It promises to enhance the sensitivity and accuracy of biomolecule detection, paving the way for broader applications in various research and diagnostic fields.

Full-spike deep mutational scanning helps predict the evolutionary success of SARS-CoV-2 clades

SARS-CoV-2 variants acquire mutations in spike that promote immune evasion and impact other properties that contribute to viral fitness such as ACE2 receptor binding and cell entry. Knowledge of how mutations affect these spike phenotypes can provide insight into the current and potential future evolution of the virus. Here we use pseudovirus deep mutational scanning to measure how >9,000 mutations across the full XBB.1.5 and BA.2 spikes affect ACE2 binding, cell entry, or escape from human sera. We find that mutations outside the receptor-binding domain (RBD) have meaningfully impacted ACE2 binding during SARS-CoV-2 evolution. We also measure how mutations to the XBB.1.5 spike affect neutralization by serum from individuals who recently had SARS-CoV-2 infections. The strongest serum escape mutations are in the RBD at sites 357, 420, 440, 456, and 473-however, the antigenic impacts of these mutations vary across individuals. We also identify strong escape mutations outside the RBD; however many of them decrease ACE2 binding, suggesting they act by modulating RBD conformation. Notably, the growth rates of human SARS-CoV-2 clades can be explained in substantial part by the measured effects of mutations on spike phenotypes, suggesting our data could enable better prediction of viral evolution.

Probing nanomechanical interactions of SARS-CoV-2 variants Omicron and XBB with common surfaces

The emergence of SARS-CoV-2 variants has further raised concerns about viral transmission. A fundamental understanding of the intermolecular interactions between the coronavirus and different surfaces is needed to address the transmission of SARS-CoV-2 through respiratory droplet-contaminated surfaces or fomites. The receptor-binding domain (RBD) of the spike protein is a key target for the adhesion of SARS-CoV-2 on the surface. To understand the effect of mutations on adhesion, atomic force microscopy-based single-molecule force spectroscopy (AFM-SMFS) was used to quantify the interactions between wild-type, Omicron, and XBB with several surfaces. The measurement revealed that RBD exhibits relatively higher forces on paper and gold surfaces, with the average force being 1.5 times greater compared to that on plastic surface. In addition, the force elevation on paper and gold surfaces for the variants can reach ∼28% relative to the wild type. These findings enhance our understanding of the nanomechanical interactions of the virus on common surfaces.

Co-Circulation of SARS-CoV-2 and Other Respiratory Pathogens in Upper and Lower Respiratory Tracts during Influenza Season 2022-2023 in Lazio Region

Lower respiratory tract infections (LRTIs) occur when there is a lower airway tract infection. They are well-known for increasing the susceptibility of patients to bacterial/fungal co-infections and super-infections. In this study, we present the results of our investigation, which involved 381 consecutive patients admitted to our hospital during the Influenza season from October 2022 to April 2023. Among the 381 specimens, 75 were bronchoalveolar (BAL), and 306 were nasopharyngeal swabs (NPSs). Notably, 34.4% of the examined samples tested positive for SARS-CoV-2. Of these, we observed that 7.96% of NPSs showed positivity only for other respiratory viruses, while a substantial percentage (77%) of BAL specimens exhibited positive results only for bacterial co-infections. The results of our study not only confirm the importance of co-infections in COVID-19 but also emphasize the significance of utilizing rapid diagnostic tests (RDTs) for the timely diagnosis of LRTIs. In fact, RDTs allow for the identification of multiple pathogens, providing clinicians with useful and timely information to establish effective therapy.