Deep Mutational Scanning of SARS-CoV-2 Receptor Binding Domain Reveals Constraints on Folding and ACE2 Binding

Deep-learning-enabled protein-protein interaction analysis for prediction of SARS-CoV-2 infectivity and variant evolution

Host-pathogen interactions and pathogen evolution are underpinned by protein-protein interactions between viral and host proteins. An understanding of how viral variants affect protein-protein binding is important for predicting viral-host interactions, such as the emergence of new pathogenic SARS-CoV-2 variants. Here we propose an artificial intelligence-based framework called UniBind, in which proteins are represented as a graph at the residue and atom levels. UniBind integrates protein three-dimensional structure and binding affinity and is capable of multi-task learning for heterogeneous biological data integration. In systematic tests on benchmark datasets and further experimental validation, UniBind effectively and scalably predicted the effects of SARS-CoV-2 spike protein variants on their binding affinities to the human ACE2 receptor, as well as to SARS-CoV-2 neutralizing monoclonal antibodies. Furthermore, in a cross-species analysis, UniBind could be applied to predict host susceptibility to SARS-CoV-2 variants and to predict future viral variant evolutionary trends. This in silico approach has the potential to serve as an early warning system for problematic emerging SARS-CoV-2 variants, as well as to facilitate research on protein-protein interactions in general.

A Comprehensive Technology Platform for the Rapid Discovery of Peptide Inhibitors against SARS-CoV-2 Pseudovirus Infection

We developed and validated a technology platform for designing and testing peptides inhibiting the infectivity of SARS-CoV-2 spike protein-based pseudoviruses. This platform integrates target evaluation, in silico inhibitor design, peptide synthesis, and efficacy screening. We generated a cyclic peptide library derived from the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein and the angiotensin-converting enzyme 2 (ACE2) receptor. The cell-free validation process by ELISA competition assays and Surface Plasmon Resonance (SPR) studies revealed that the cyclic peptide c9_05, but not its linear form, binds well to ACE2. Moreover, it effectively inhibited the transduction in HEK293, stably expressing the human ACE2 receptor of pseudovirus particles displaying the SARS-CoV-2 spike in the Wuhan or UK variants. However, the inhibitory efficacy of c9_05 was negligible against the Omicron variant, and it failed to impede the entry of pseudoviruses carrying the B.1.351 (South African) spike. These variants contain three or more mutations known to increase affinity to ACE2. This suggests further refinement is needed for potential SARS-CoV-2 inhibition. Our study hints at a promising approach to develop inhibitors targeting viral infectivity receptors, including SARS-CoV-2's. This platform also promises swift identification and evaluation of inhibitors for other emergent viruses.

Predicting evolutionary outcomes through the probability of accessing sequence variants

Natural selection can only operate on available genetic variation. Thus, determining the probability of accessing different sequence variants from a starting sequence can help predict evolutionary trajectories and outcomes. We define the concept of "variant accessibility" as the probability that a set of genotypes encoding a particular protein function will arise through mutations before subject to natural selection. This probability is shaped by the mutational biases of nucleotides and the structure of the genetic code. Using the influenza A virus as a model, we discuss how a more accessible but less fit variant can emerge as an adaptation rather than a more fit variant. We describe a genotype-accessibility landscape, complementary to the genotype-fitness landscape, that informs the likelihood of a starting sequence reaching different parts of genotype space. The proposed framework lays the foundation for predicting the emergence of adaptive genotypes in evolving systems such as viruses and tumors.

Potent pan huACE2-dependent sarbecovirus neutralizing monoclonal antibodies isolated from a BNT162b2-vaccinated SARS survivor

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern such as Omicron hampered efforts in controlling the ongoing coronavirus disease 2019 pandemic due to their ability to escape neutralizing antibodies induced by vaccination or prior infection, highlighting the need to develop broad-spectrum vaccines and therapeutics. Most human monoclonal antibodies (mAbs) reported to date have not demonstrated true pan-sarbecovirus neutralizing breadth especially against animal sarbecoviruses. Here, we report the isolation and characterization of highly potent mAbs targeting the receptor binding domain (RBD) of huACE2-dependent sarbecovirus from a SARS-CoV survivor vaccinated with BNT162b2. Among the six mAbs identified, one (E7) showed better huACE2-dependent sarbecovirus neutralizing potency and breadth than any other mAbs reported to date. Mutagenesis and cryo-electron microscopy studies indicate that these mAbs have a unique RBD contact footprint and that E7 binds to a quaternary structure-dependent epitope.

The effects of amino acid substitution of spike protein and genomic recombination on the evolution of SARS-CoV-2

Over three years' pandemic of 2019 novel coronavirus disease (COVID-19), multiple variants and novel subvariants have emerged successively, outcompeted earlier variants and become predominant. The sequential emergence of variants reflects the evolutionary process of mutation-selection-adaption of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Amino acid substitution/insertion/deletion in the spike protein causes altered viral antigenicity, transmissibility, and pathogenicity of SARS-CoV-2. Early in the pandemic, D614G mutation conferred virus with advantages over previous variants and increased transmissibility, and it also laid a conservative background for subsequent substantial mutations. The role of genomic recombination in the evolution of SARS-CoV-2 raised increasing concern with the occurrence of novel recombinants such as Deltacron, XBB.1.5, XBB.1.9.1, and XBB.1.16 in the late phase of pandemic. Co-circulation of different variants and co-infection in immunocompromised patients accelerate the emergence of recombinants. Surveillance for SARS-CoV-2 genomic variations, particularly spike protein mutation and recombination, is essential to identify ongoing changes in the viral genome and antigenic epitopes and thus leads to the development of new vaccine strategies and interventions.

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

A cluster of several newly occurring mutations on Omicron is found at the β-core region of the spike protein's receptor-binding domain (RBD), where mutation rarely happened before. Notably, the binding of SARS-CoV-2 to human receptor ACE2 via RBD happens in a dynamic airway environment, where mechanical force caused by coughing or sneezing occurs. Thus, we used atomic force microscopy-based single-molecule force spectroscopy (AFM-SMFS) to measure the stability of RBDs and found that the mechanical stability of Omicron RBD increased by ∼20% compared with the wild type. Molecular dynamics (MD) simulations revealed that Omicron RBD showed more hydrogen bonds in the β-core region due to the closing of the α-helical motif caused primarily by the S373P mutation. In addition to a higher unfolding force, we showed a higher dissociation force between Omicron RBD and ACE2. This work reveals the mechanically stabilizing effect of the conserved mutation S373P for Omicron and the possible evolution trend of the β-core region of RBD.

EvoRator2: Predicting Site-specific Amino Acid Substitutions Based on Protein Structural Information Using Deep Learning

Multiple sequence alignments (MSAs) are the workhorse of molecular evolution and structural biology research. From MSAs, the amino acids that are tolerated at each site during protein evolution can be inferred. However, little is known regarding the repertoire of tolerated amino acids in proteins when only a few or no sequence homologs are available, such as orphan and de novo designed proteins. Here we present EvoRator2, a deep-learning algorithm trained on over 15,000 protein structures that can predict which amino acids are tolerated at any given site, based exclusively on protein structural information mined from atomic coordinate files. We show that EvoRator2 obtained satisfying results for the prediction of position-weighted scoring matrices (PSSM). We further show that EvoRator2 obtained near state-of-the-art performance on proteins with high quality structures in predicting the effect of mutations in deep mutation scanning (DMS) experiments and that for certain DMS targets, EvoRator2 outperformed state-of-the-art methods. We also show that by combining EvoRator2's predictions with those obtained by a state-of-the-art deep-learning method that accounts for the information in the MSA, the prediction of the effect of mutation in DMS experiments was improved in terms of both accuracy and stability. EvoRator2 is designed to predict which amino-acid substitutions are tolerated in such proteins without many homologous sequences, including orphan or de novo designed proteins. We implemented our approach in the EvoRator web server (https://evorator.tau.ac.il).

Structural delineation and computational design of SARS-CoV-2-neutralizing antibodies against Omicron subvariants

SARS-CoV-2 Omicron subvariants have evolved to evade receptor-binding site (RBS) antibodies that exist in diverse individuals as public antibody clones. We rationally selected RBS antibodies resilient to mutations in emerging Omicron subvariants. Y489 was identified as a site of virus vulnerability and a common footprint of broadly neutralizing antibodies against the subvariants. Multiple Y489-binding antibodies were encoded by public clonotypes and additionally recognized F486, potentially accounting for the emergence of Omicron subvariants harboring the F486V mutation. However, a subclass of antibodies broadly neutralized BA.4/BA.5 variants via hydrophobic binding sites of rare clonotypes along with high mutation-resilience under escape mutation screening. A computationally designed antibody based on one of the Y489-binding antibodies, NIV-10/FD03, was able to bind XBB with any 486 mutation and neutralized XBB.1.5. The structural basis for the mutation-resilience of this Y489-binding antibody group may provide important insights into the design of therapeutics resistant to viral escape.

Mutations of SARS-CoV-2 Structural Proteins in the Alpha, Beta, Gamma, and Delta Variants: Bioinformatics Analysis

Background

COVID-19 and Middle East Respiratory Syndrome are two pandemic respiratory diseases caused by coronavirus species. The novel disease COVID-19 caused by SARS-CoV-2 was first reported in Wuhan, Hubei Province, China, in December 2019, and became a pandemic within 2-3 months, affecting social and economic platforms worldwide. Despite the rapid development of vaccines, there have been obstacles to their distribution, including a lack of fundamental resources, poor immunization, and manual vaccine replication. Several variants of the original Wuhan strain have emerged in the last 3 years, which can pose a further challenge for control and vaccine development.

Objective

The aim of this study was to comprehensively analyze mutations in SARS-CoV-2 variants of concern (VoCs) using a bioinformatics approach toward identifying novel mutations that may be helpful in developing new vaccines by targeting these sites.

Methods

Reference sequences of the SARS-CoV-2 spike (YP_009724390) and nucleocapsid (YP_009724397) proteins were compared to retrieved sequences of isolates of four VoCs from 14 countries for mutational and evolutionary analyses. Multiple sequence alignment was performed and phylogenetic trees were constructed by the neighbor-joining method with 1000 bootstrap replicates using MEGA (version 6). Mutations in amino acid sequences were analyzed using the MultAlin online tool (version 5.4.1).

Results

Among the four VoCs, a total of 143 nonsynonymous mutations and 8 deletions were identified in the spike and nucleocapsid proteins. Multiple sequence alignment and amino acid substitution analysis revealed new mutations, including G72W, M2101I, L139F, 209-211 deletion, G212S, P199L, P67S, I292T, and substitutions with unknown amino acid replacement, reported in Egypt (MW533289), the United Kingdom (MT906649), and other regions. The variants B.1.1.7 (Alpha variant) and B.1.617.2 (Delta variant), characterized by higher transmissibility and lethality, harbored the amino acid substitutions D614G, R203K, and G204R with higher prevalence rates in most sequences. Phylogenetic analysis among the novel SARS-CoV-2 variant proteins and some previously reported β-coronavirus proteins indicated that either the evolutionary clade was weakly supported or not supported at all by the β-coronavirus species.

Conclusions

This study could contribute toward gaining a better understanding of the basic nature of SARS-CoV-2 and its four major variants. The numerous novel mutations detected could also provide a better understanding of VoCs and help in identifying suitable mutations for vaccine targets. Moreover, these data offer evidence for new types of mutations in VoCs, which will provide insight into the epidemiology of SARS-CoV-2.

Waning and boosting of antibody Fc-effector functions upon SARS-CoV-2 vaccination

Since the emergence of SARS-CoV-2, vaccines targeting COVID-19 have been developed with unprecedented speed and efficiency. CoronaVac, utilising an inactivated form of the COVID-19 virus and the mRNA26 based Pfizer/BNT162b2 vaccines are widely distributed. Beyond the ability of vaccines to induce production of neutralizing antibodies, they might lead to the generation of antibodies attenuating the disease by recruiting cytotoxic and opsonophagocytic functions. However, the Fc-effector functions of vaccine induced antibodies are much less studied than virus neutralization. Here, using systems serology, we follow the longitudinal Fc-effector profiles induced by CoronaVac and BNT162b2 up until five months following the two-dose vaccine regimen. Compared to BNT162b2, CoronaVac responses wane more slowly, albeit the levels remain lower than that of BNT162b2 recipients throughout the entire observation period. However, mRNA vaccine boosting of CoronaVac responses, including response to the Omicron variant, induce significantly higher peak of antibody functional responses with increased humoral breadth. In summary, we show that vaccine platform-induced humoral responses are not limited to virus neutralization but rather utilise antibody dependent effector functions. We demonstrate that this functionality wanes with different kinetics and can be rescued and expanded via boosting with subsequent homologous and heterologous vaccination.

Modeling of ACE2 and antibodies bound to SARS-CoV-2 provides insights into infectivity and immune evasion

Given the COVID-19 pandemic, there is interest in understanding ligand-receptor features and targeted antibody-binding attributes against emerging SARS-CoV-2 variants. Here, we developed a large-scale structure-based pipeline for analysis of protein-protein interactions regulating SARS-CoV-2 immune evasion. First, we generated computed structural models of the Spike protein of 3 SARS-CoV-2 variants (B.1.1.529, BA.2.12.1, and BA.5) bound either to a native receptor (ACE2) or to a large panel of targeted ligands (n = 282), which included neutralizing or therapeutic monoclonal antibodies. Moreover, by using the Barnes classification, we noted an overall loss of interfacial interactions (with gain of new interactions in certain cases) at the receptor-binding domain (RBD) mediated by substituted residues for neutralizing complexes in classes 1 and 2, whereas less destabilization was observed for classes 3 and 4. Finally, an experimental validation of predicted weakened therapeutic antibody binding was performed in a cell-based assay. Compared with the original Omicron variant (B.1.1.529), derivative variants featured progressive destabilization of antibody-RBD interfaces mediated by a larger set of substituted residues, thereby providing a molecular basis for immune evasion. This approach and findings provide a framework for rapidly and efficiently generating structural models for SARS-CoV-2 variants bound to ligands of mechanistic and therapeutic value.

Interspecies transmission of SARS CoV-2 with special emphasis on viral mutations and ACE-2 receptor homology roles

COVID-19 outbreak was first reported in 2019, Wuhan, China. The spillover of the disease caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), to a wide range of pet, zoo, wild, and farm animals has emphasized potential zoonotic and reverse zoonotic viral transmission. Furthermore, it has evoked inquiries about susceptibility of different animal species to SARS-CoV-2 infection and role of these animals as viral reservoirs. Therefore, studying susceptible and non-susceptible hosts for SARS-CoV-2 infection could give a better understanding for the virus and will help in preventing further outbreaks. Here, we review structural aspects of SARS-CoV-2 spike protein, the effect of the different mutations observed in the spike protein, and the impact of ACE2 receptor variations in different animal hosts on inter-species transmission. Moreover, the SARS-CoV-2 spillover chain was reviewed. Combination of SARS-CoV-2 high mutation rate and homology of cellular ACE2 receptors enable the virus to transcend species barriers and facilitate its transmission between humans and animals.

Individual bat virome analysis reveals co-infection and spillover among bats and virus zoonotic potential

Bats are reservoir hosts for many zoonotic viruses. Despite this, relatively little is known about the diversity and abundance of viruses within individual bats, and hence the frequency of virus co-infection and spillover among them. We characterize the mammal-associated viruses in 149 individual bats sampled from Yunnan province, China, using an unbiased meta-transcriptomics approach. This reveals a high frequency of virus co-infection (simultaneous infection of bat individuals by multiple viral species) and spillover among the animals studied, which may in turn facilitate virus recombination and reassortment. Of note, we identify five viral species that are likely to be pathogenic to humans or livestock, based on phylogenetic relatedness to known pathogens or in vitro receptor binding assays. This includes a novel recombinant SARS-like coronavirus that is closely related to both SARS-CoV and SARS-CoV-2. In vitro assays indicate that this recombinant virus can utilize the human ACE2 receptor such that it is likely to be of increased emergence risk. Our study highlights the common occurrence of co-infection and spillover of bat viruses and their implications for virus emergence.

Stringent and complex sequence constraints of an IGHV1-69 broadly neutralizing antibody to influenza HA stem

IGHV1-69 is frequently utilized by broadly neutralizing influenza antibodies to the hemagglutinin (HA) stem. These IGHV1-69 HA stem antibodies have diverse complementarity-determining region (CDR) H3 sequences. Besides, their light chains have minimal to no contact with the epitope. Consequently, sequence determinants that confer IGHV1-69 antibodies with HA stem specificity remain largely elusive. Using high-throughput experiments, this study revealed the importance of light chain sequence for the IGHV1-69 HA stem antibody CR9114, which is the broadest influenza antibody known to date. Moreover, we demonstrated that the CDR H3 sequences from many other IGHV1-69 antibodies, including those to HA stem, were incompatible with CR9114. Along with mutagenesis and structural analysis, our results indicate that light chain and CDR H3 sequences coordinately determine the HA stem specificity of IGHV1-69 antibodies. Overall, this work provides molecular insights into broadly neutralizing antibody responses to influenza virus, which have important implications for universal influenza vaccine development.

Evolution of Sequence and Structure of SARS-CoV-2 Spike Protein: A Dynamic Perspective

Novel coronavirus (SARS-CoV-2) enters its host cell through a surface spike protein. The viral spike protein has undergone several modifications/mutations at the genomic level, through which it modulated its structure-function and passed through several variants of concern. Recent advances in high-resolution structure determination and multiscale imaging techniques, cost-effective next-generation sequencing, and development of new computational methods (including information theory, statistical methods, machine learning, and many other artificial intelligence-based techniques) have hugely contributed to the characterization of sequence, structure, function of spike proteins, and its different variants to understand viral pathogenesis, evolutions, and transmission. Laying on the foundation of the sequence-structure-function paradigm, this review summarizes not only the important findings on structure/function but also the structural dynamics of different spike components, highlighting the effects of mutations on them. As dynamic fluctuations of three-dimensional spike structure often provide important clues for functional modulation, quantifying time-dependent fluctuations of mutational events over spike structure and its genetic/amino acidic sequence helps identify alarming functional transitions having implications for enhanced fusogenicity and pathogenicity of the virus. Although these dynamic events are more difficult to capture than quantifying a static, average property, this review encompasses those challenging aspects of characterizing the evolutionary dynamics of spike sequence and structure and their implications for functions.

Differences between Omicron SARS-CoV-2 RBD and other variants in their ability to interact with cell receptors and monoclonal antibodies

SARS-CoV-2 remains a health threat with the continuous emergence of new variants. This work aims to expand the knowledge about the SARS-CoV-2 receptor-binding domain (RBD) interactions with cell receptors and monoclonal antibodies (mAbs). By using constant-pH Monte Carlo simulations, the free energy of interactions between the RBD from different variants and several partners (Angiotensin-Converting Enzyme-2 (ACE2) polymorphisms and various mAbs) were predicted. Computed RBD-ACE2-binding affinities were higher for two ACE2 polymorphisms (rs142984500 and rs4646116) typically found in Europeans which indicates a genetic susceptibility. This is amplified for Omicron (BA.1) and its sublineages BA.2 and BA.3. The antibody landscape was computationally investigated with the largest set of mAbs so far in the literature. From the 32 studied binders, groups of mAbs were identified from weak to strong binding affinities (e.g. S2K146). These mAbs with strong binding capacity and especially their combination are amenable to experimentation and clinical trials because of their high predicted binding affinities and possible neutralization potential for current known virus mutations and a universal coronavirus.Communicated by Ramaswamy H. Sarma.

Sequence Analysis of Hot Spot Regions of Spike and RNA-dependent-RNA polymerase (RdRp) Genes of SARS-CoV-2 in Kerman, Iran

Background

Mutations in the SARS-CoV-2 genome might influence pathogenicity, transmission rate, and evasion of the host immune system. Therefore, the purpose of the present study was to investigate the genetic alteration as well as assess their effects on the receptor binding domain (RBD) of the spike and the putative RNA binding site of the RdRp genes of SARS-CoV-2 using bioinformatics tools.

Materials and Method

In this cross-sectional study, 45 confirmed COVID-19 patients using qRT-PCR were included and divided into mild, severe, and critical groups based on the severity of the disease. RNA was extracted from nasopharyngeal swab samples using a commercial kit. RT-PCR was performed to amplify the target sequences of the spike and RdRp genes and sequence them by the Sanger method. Clustal OMEGA, MEGA 11 software, I-mutant tools, SWISS-MODEL, and HDOCK web servers were used for bioinformatics analyses.

Results

The mean age of the patients was 50.68±2.73. The results showed that four of six mutations (L452R, T478K, N501Y, and D614G) in RBD and three of eight in the putative RNA binding site (P314L, E1084D, V1883T) were missense. In the putative RNA binding site, another deletion was discovered. Among missense mutations, N501Y and V1883T were responsible for increasing structural stability, while others were responsible for decreasing it. The various homology models designed showed that these homologies were like the Wuhan model. The molecular docking analysis revealed that the T478K mutation in RBD had the highest binding affinity. In addition, 35 RBD samples (89.7%) and 33 putative RNA binding site samples (84.6%) were similar to the Delta variant.

Conclusion

Our results indicated that double mutations (T478K and N501Y) in the S protein might increase the binding affinity of SARS-CoV-2 to human ACE2 compared to the wild-type (WT) strain. Moreover, variations in the spike and RdRp genes might influence the stability of encoded proteins.

The End or a New Era of Development of SARS-CoV-2 Virus: Genetic Variants Responsible for Severe COVID-19 and Clinical Efficacy of the Most Commonly Used Vaccines in Clinical Practice

Although the chief of the World Health Organization (WHO) has declared the end of the coronavirus disease 2019 (COVID-19) as a global health emergency, the disease is still a global threat. To be able to manage such pandemics in the future, it is necessary to develop proper strategies and opportunities to protect human life. The data on the SARS-CoV-2 virus must be continuously analyzed, and the possibilities of mutation and the emergence of new, more infectious variants must be anticipated, as well as the options of using different preventive and therapeutic techniques. This is because the fast development of severe acute coronavirus 2 syndrome (SARS-CoV-2) variants of concern have posed a significant problem for COVID-19 pandemic control using the presently available vaccinations. This review summarizes data on the SARS-CoV-2 variants that are responsible for severe COVID-19 and the clinical efficacy of the most commonly used vaccines in clinical practice. The consequences after the disease (long COVID or post-COVID conditions) continue to be the subject of studies and research, and affect social and economic life worldwide.

Structural changes in the SARS-CoV-2 spike E406W mutant escaping a clinical monoclonal antibody cocktail

Continued evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is eroding antibody responses elicited by prior vaccination and infection. The SARS-CoV-2 receptor-binding domain (RBD) E406W mutation abrogates neutralization mediated by the REGEN-COV therapeutic monoclonal antibody (mAb) COVID-19 cocktail and the AZD1061 (COV2-2130) mAb. Here, we show that this mutation remodels the receptor-binding site allosterically, thereby altering the epitopes recognized by these three mAbs and vaccine-elicited neutralizing antibodies while remaining functional. Our results demonstrate the spectacular structural and functional plasticity of the SARS-CoV-2 RBD, which is continuously evolving in emerging SARS-CoV-2 variants, including currently circulating strains that are accumulating mutations in the antigenic sites remodeled by the E406W substitution.

Genomic screening of 16 UK native bat species through conservationist networks uncovers coronaviruses with zoonotic potential

There has been limited characterisation of bat-borne coronaviruses in Europe. Here, we screened for coronaviruses in 48 faecal samples from 16 of the 17 bat species breeding in the UK, collected through a bat rehabilitation and conservationist network. We recovered nine complete genomes, including two novel coronavirus species, across six bat species: four alphacoronaviruses, a MERS-related betacoronavirus, and four closely related sarbecoviruses. We demonstrate that at least one of these sarbecoviruses can bind and use the human ACE2 receptor for infecting human cells, albeit suboptimally. Additionally, the spike proteins of these sarbecoviruses possess an R-A-K-Q motif, which lies only one nucleotide mutation away from a furin cleavage site (FCS) that enhances infectivity in other coronaviruses, including SARS-CoV-2. However, mutating this motif to an FCS does not enable spike cleavage. Overall, while UK sarbecoviruses would require further molecular adaptations to infect humans, their zoonotic risk warrants closer surveillance.

Accurate profiling of full-length Fv in highly homologous antibody libraries using UMI tagged short reads

Deep parallel sequencing (NGS) is a viable tool for monitoring scFv and Fab library dynamics in many antibody engineering high-throughput screening efforts. Although very useful, the commonly used Illumina NGS platform cannot handle the entire sequence of scFv or Fab in a single read, usually focusing on specific CDRs or resorting to sequencing VH and VL variable domains separately, thus limiting its utility in comprehensive monitoring of selection dynamics. Here we present a simple and robust method for deep sequencing repertoires of full length scFv, Fab and Fv antibody sequences. This process utilizes standard molecular procedures and unique molecular identifiers (UMI) to pair separately sequenced VH and VL. We show that UMI assisted VH-VL matching allows for a comprehensive and highly accurate mapping of full length Fv clonal dynamics in large highly homologous antibody libraries, as well as identification of rare variants. In addition to its utility in synthetic antibody discovery processes, our method can be instrumental in generating large datasets for machine learning (ML) applications, which in the field of antibody engineering has been hampered by conspicuous paucity of large scale full length Fv data.

Investigation of the Molecular Epidemiology and Evolution of Circulating Severe Acute Respiratory Syndrome Coronavirus 2 in Thailand from 2020 to 2022 via Next-Generation Sequencing

Coronavirus disease 2019 (COVID-19) is an infectious condition caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), which surfaced in Thailand in early 2020. The current study investigated the SARS-CoV-2 lineages circulating in Thailand and their evolutionary history. Complete genome sequencing of 210 SARS-CoV-2 samples collected from collaborating hospitals and the Institute of Urban Disease Control and Prevention over two years, from December 2020 to July 2022, was performed using next-generation sequencing technology. Multiple lineage introductions were observed before the emergence of the B.1.1.529 omicron variant, including B.1.36.16, B.1.351, B.1.1, B.1.1.7, B.1.524, AY.30, and B.1.617.2. The B.1.1.529 omicron variant was subsequently detected between January 2022 and June 2022. The evolutionary rate for the spike gene of SARS-CoV-2 was estimated to be between 0.87 and 1.71 × 10^-3 substitutions per site per year. There was a substantial prevalence of the predominant mutations C25672T (L94F), C25961T (T190I), and G26167T (V259L) in the ORF3a gene during the Thailand outbreaks. Complete genome sequencing can enhance the prediction of future variant changes in viral genomes, which is crucial to ensuring that vaccine strains are protective against worldwide outbreaks.

Enhancement of SARS-CoV-2 receptor-binding domain activity by two microbial defensins

Peptide binders are of great interest to both basic and biomedical research due to their unique properties in manipulating protein functions in a precise spatial and temporal manner. The receptor-binding domain (RBD) of the SARS-CoV-2 Spike protein is a ligand that captures human angiotensin-converting enzyme 2 (ACE2) to initiate infection. The development of binders of RBDs has value either as antiviral leads or as versatile tools to study the functional properties of RBDs dependent on their binding positions on the RBDs. In this study, we report two microbe-derived antibacterial defensins with RBD-binding activity. These two naturally occurring binders bind wild-type RBD (WT RBD) and RBDs from various variants with moderate-to-high affinity (7.6-1,450 nM) and act as activators that enhance the ACE2-binding activity of RBDs. Using a computational approach, we mapped an allosteric pathway in WT RBD that connects its ACE2-binding sites to other distal regions. The latter is targeted by the defensins, in which a cation-π interaction could trigger the peptide-elicited allostery in RBDs. The discovery of the two positive allosteric peptides of SARS-CoV-2 RBD will promote the development of new molecular tools for investigating the biochemical mechanisms of RBD allostery.

Discovery and characterization of potent pan-variant SARS-CoV-2 neutralizing antibodies from individuals with Omicron breakthrough infection

The SARS-CoV-2 Omicron variant evades most currently approved neutralizing antibodies (nAbs) and caused drastic decrease of plasma neutralizing activity elicited by vaccination or prior infection, urging the need for the development of pan-variant antivirals. Breakthrough infection induces a hybrid immunological response with potentially broad, potent and durable protection against variants, therefore, convalescent plasma from breakthrough infection may provide a broadened repertoire for identifying elite nAbs. We performed single-cell RNA sequencing (scRNA-seq) and BCR sequencing (scBCR-seq) of B cells from BA.1 breakthrough-infected patients who received 2 or 3 previous doses of inactivated vaccine. Elite nAbs, mainly derived from the IGHV2-5 and IGHV3-66/53 germlines, showed potent neutralizing activity across Wuhan-Hu-1, Delta, Omicron sublineages BA.1 and BA.2 at picomolar NT50 values. Cryo-EM analysis revealed diverse modes of spike recognition and guides the design of cocktail therapy. A single injection of paired antibodies cocktail provided potent protection in the K18-hACE2 transgenic female mouse model of SARS-CoV-2 infection.

Predicting the antigenic evolution of SARS-COV-2 with deep learning

The relentless evolution of SARS-CoV-2 poses a significant threat to public health, as it adapts to immune pressure from vaccines and natural infections. Gaining insights into potential antigenic changes is critical but challenging due to the vast sequence space. Here, we introduce the Machine Learning-guided Antigenic Evolution Prediction (MLAEP), which combines structure modeling, multi-task learning, and genetic algorithms to predict the viral fitness landscape and explore antigenic evolution via in silico directed evolution. By analyzing existing SARS-CoV-2 variants, MLAEP accurately infers variant order along antigenic evolutionary trajectories, correlating with corresponding sampling time. Our approach identified novel mutations in immunocompromised COVID-19 patients and emerging variants like XBB1.5. Additionally, MLAEP predictions were validated through in vitro neutralizing antibody binding assays, demonstrating that the predicted variants exhibited enhanced immune evasion. By profiling existing variants and predicting potential antigenic changes, MLAEP aids in vaccine development and enhances preparedness against future SARS-CoV-2 variants.

Structural and computational design of a SARS-CoV-2 spike antigen with improved expression and immunogenicity

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern challenge the efficacy of approved vaccines, emphasizing the need for updated spike antigens. Here, we use an evolutionary-based design aimed at boosting protein expression levels of S-2P and improving immunogenic outcomes in mice. Thirty-six prototype antigens were generated in silico and 15 were produced for biochemical analysis. S2D14, which contains 20 computationally designed mutations within the S2 domain and a rationally engineered D614G mutation in the SD2 domain, has an ~11-fold increase in protein yield and retains RBD antigenicity. Cryo-electron microscopy structures reveal a mixture of populations in various RBD conformational states. Vaccination of mice with adjuvanted S2D14 elicited higher cross-neutralizing antibody titers than adjuvanted S-2P against the SARS-CoV-2 Wuhan strain and four variants of concern. S2D14 may be a useful scaffold or tool for the design of future coronavirus vaccines, and the approaches used for the design of S2D14 may be broadly applicable to streamline vaccine discovery.

Identification of broad, potent antibodies to functionally constrained regions of SARS-CoV-2 spike following a breakthrough infection

The antiviral benefit of antibodies can be compromised by viral escape especially for rapidly evolving viruses. Therefore, durable, effective antibodies must be both broad and potent to counter newly emerging, diverse strains. Discovery of such antibodies is critically important for SARS-CoV-2 as the global emergence of new variants of concern (VOC) has compromised the efficacy of therapeutic antibodies and vaccines. We describe a collection of broad and potent neutralizing monoclonal antibodies (mAbs) isolated from an individual who experienced a breakthrough infection with the Delta VOC. Four mAbs potently neutralize the Wuhan-Hu-1 vaccine strain, the Delta VOC, and also retain potency against the Omicron VOCs through BA.4/BA.5 in both pseudovirus-based and authentic virus assays. Three mAbs also retain potency to recently circulating VOCs XBB.1.5 and BQ.1.1 and one also potently neutralizes SARS-CoV-1. The potency of these mAbs was greater against Omicron VOCs than all but one of the mAbs that had been approved for therapeutic applications. The mAbs target distinct epitopes on the spike glycoprotein, three in the receptor-binding domain (RBD) and one in an invariant region downstream of the RBD in subdomain 1 (SD1). The escape pathways we defined at single amino acid resolution with deep mutational scanning show they target conserved, functionally constrained regions of the glycoprotein, suggesting escape could incur a fitness cost. Overall, these mAbs are unique in their breadth across VOCs, their epitope specificity, and include a highly potent mAb targeting a rare epitope outside of the RBD in SD1.

Fitness effects of mutations to SARS-CoV-2 proteins

Knowledge of the fitness effects of mutations to SARS-CoV-2 can inform assessment of new variants, design of therapeutics resistant to escape, and understanding of the functions of viral proteins. However, experimentally measuring effects of mutations is challenging: we lack tractable lab assays for many SARS-CoV-2 proteins, and comprehensive deep mutational scanning has been applied to only two SARS-CoV-2 proteins. Here we develop an approach that leverages millions of publicly available SARS-CoV-2 sequences to estimate effects of mutations. We first calculate how many independent occurrences of each mutation are expected to be observed along the SARS-CoV-2 phylogeny in the absence of selection. We then compare these expected observations to the actual observations to estimate the effect of each mutation. These estimates correlate well with deep mutational scanning measurements. For most genes, synonymous mutations are nearly neutral, stop-codon mutations are deleterious, and amino-acid mutations have a range of effects. However, some viral accessory proteins are under little to no selection. We provide interactive visualizations of effects of mutations to all SARS-CoV-2 proteins (https://jbloomlab.github.io/SARS2-mut-fitness/). The framework we describe is applicable to any virus for which the number of available sequences is sufficiently large that many independent occurrences of each neutral mutation are observed.

Large-scale antibody immune response mapping of splenic B cells and bone marrow plasma cells in a transgenic mouse model

Molecular characterization of antibody immunity and human antibody discovery is mainly carried out using peripheral memory B cells, and occasionally plasmablasts, that express B cell receptors (BCRs) on their cell surface. Despite the importance of plasma cells (PCs) as the dominant source of circulating antibodies in serum, PCs are rarely utilized because they do not express surface BCRs and cannot be analyzed using antigen-based fluorescence-activated cell sorting. Here, we studied the antibodies encoded by the entire mature B cell populations, including PCs, and compared the antibody repertoires of bone marrow and spleen compartments elicited by immunization in a human immunoglobulin transgenic mouse strain. To circumvent prior technical limitations for analysis of plasma cells, we applied single-cell antibody heavy and light chain gene capture from the entire mature B cell repertoires followed by yeast display functional analysis using a cytokine as a model immunogen. We performed affinity-based sorting of antibody yeast display libraries and large-scale next-generation sequencing analyses to follow antibody lineage performance, with experimental validation of 76 monoclonal antibodies against the cytokine antigen that identified three antibodies with exquisite double-digit picomolar binding affinity. We observed that spleen B cell populations generated higher affinity antibodies compared to bone marrow PCs and that antigen-specific splenic B cells had higher average levels of somatic hypermutation. A degree of clonal overlap was also observed between bone marrow and spleen antibody repertoires, indicating common origins of certain clones across lymphoid compartments. These data demonstrate a new capacity to functionally analyze antigen-specific B cell populations of different lymphoid organs, including PCs, for high-affinity antibody discovery and detailed fundamental studies of antibody immunity.

Sequential intrahost evolution and onward transmission of SARS-CoV-2 variants

Persistent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections have been reported in immune-compromised individuals and people undergoing immune-modulatory treatments. Although intrahost evolution has been documented, direct evidence of subsequent transmission and continued stepwise adaptation is lacking. Here we describe sequential persistent SARS-CoV-2 infections in three individuals that led to the emergence, forward transmission, and continued evolution of a new Omicron sublineage, BA.1.23, over an eight-month period. The initially transmitted BA.1.23 variant encoded seven additional amino acid substitutions within the spike protein (E96D, R346T, L455W, K458M, A484V, H681R, A688V), and displayed substantial resistance to neutralization by sera from boosted and/or Omicron BA.1-infected study participants. Subsequent continued BA.1.23 replication resulted in additional substitutions in the spike protein (S254F, N448S, F456L, M458K, F981L, S982L) as well as in five other virus proteins. Our findings demonstrate not only that the Omicron BA.1 lineage can diverge further from its already exceptionally mutated genome but also that patients with persistent infections can transmit these viral variants. Thus, there is, an urgent need to implement strategies to prevent prolonged SARS-CoV-2 replication and to limit the spread of newly emerging, neutralization-resistant variants in vulnerable patients.

Identification of conserved linear epitopes in the SARS-CoV-2 receptor-binding region using monoclonal antibodies

The ongoing coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused millions of cases of infections, leading to a global health emergency. The SARS-CoV-2 spike (S) protein plays the most important role in viral infection, and S1 subunit and its receptor-binding domain (RBD) are widely considered the most attractive vaccine targets. The RBD is highly immunogenic and its linear epitopes are important for vaccine development and therapy, but linear epitopes on the RBD have rarely been reported. In this study, 151 mouse monoclonal antibodies (mAbs) against the SARS-CoV-2 S1 protein were characterized and used to identify epitopes. Fifty-one mAbs reacted with eukaryotic SARS-CoV-2 RBD. Sixty-nine mAbs reacted with the S proteins of Omicron variants B.1.1.529 and BA.5, indicating their potential as rapid diagnostic materials. Three novel linear epitopes of RBD, R6 (³⁹¹CFTNVYADSFVIRGD⁴⁰⁵), R12 (⁴⁶³PFERDISTEIYQAGS⁴⁷⁷), and R16 (⁵¹⁰VVVLSFELLHAPAT⁵²³), were identified; these were highly conserved in SARS-CoV-2 variants of concern and could be detected in the convalescent serum of COVID-19 patients. From pseudovirus neutralization assays, some mAbs including one detecting R12 were found to possess neutralizing activity. Together, from the reaction of mAbs with eukaryotic RBD (N501Y), RBD (E484K), and S1 (D614G), we found that a single amino acid mutation in the SARS-CoV-2 S protein may cause a structural alteration, exerting substantial impact on mAb recognition. Our results could, therefore, help us better understand the function of the SARS-CoV-2 S protein and develop diagnostic tools for COVID-19.

Khosta: A Genetic and Structural Point of View of the Forgotten Virus

Bats are well-known to be natural reservoirs of various zoonotic coronaviruses, which have caused outbreaks of severe acute respiratory syndrome (SARS) and the COVID-19 pandemic in 2002 and 2019, respectively. In late 2020, two new Sarbecoviruses were found in Russia, isolated in Rhinolophus bats, i.e., Khosta-1 in R. ferrumequinum and Khosta-2 in R. hipposideros. The potential danger associated with these new species of Sarbecovirus is that Khosta-2 has been found to interact with the same entry receptor as SARS-CoV-2. Our multidisciplinary approach in this study demonstrates that Khosta-1 and -2 currently appear to be not dangerous with low risk of spillover, as confirmed by prevalence data and by phylogenomic reconstruction. In addition, the interaction between Khosta-1 and -2 with ACE2 appears weak, and furin cleavage sites are absent. While the possibility of a spillover event cannot be entirely excluded, it is currently highly unlikely. This research further emphasizes the importance of assessing the zoonotic potential of widely distributed batborne CoV in order to monitor changes in genomic composition of viruses and prevent spillover events (if any).

mutscan-a flexible R package for efficient end-to-end analysis of multiplexed assays of variant effect data

Multiplexed assays of variant effect (MAVE) experimentally measure the effect of large numbers of sequence variants by selective enrichment of sequences with desirable properties followed by quantification by sequencing. mutscan is an R package for flexible analysis of such experiments, covering the entire workflow from raw reads up to statistical analysis and visualization. The core components are implemented in C++ for efficiency. Various experimental designs are supported, including single or paired reads with optional unique molecular identifiers. To find variants with changed relative abundance, mutscan employs established statistical models provided in the edgeR and limma packages. mutscan is available from https://github.com/fmicompbio/mutscan .

MXene-Based Aptameric Fluorosensor for Sensitive and Rapid Detection of COVID-19

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-caused COVID-19 pandemic has rapidly escalated into the largest global health emergency, which pushes to develop detection kits for the detection of COVID-19 with high sensitivity, specificity, and fast analysis. Here, aptamer-functionalized MXene nanosheet is demonstrated as a novel bionanosensor that detects COVID-19. Upon binding to the spike receptor binding domain of SARS-CoV-2, the aptamer probe is released from MXene surface restoring the quenched fluorescence. The performances of the fluorosensor are evaluated using antigen protein, cultured virus, and swab specimens from COVID-19 patients. It is evidenced that this sensor can detect SARS-CoV-2 spike protein at final concentration of 38.9 fg mL^-1 and SARS-CoV-2 pseudovirus (limit of detection: 7.2 copies) within 30 min. Its application for clinical samples analysis is also demonstrated successfully. This work offers an effective sensing platform for sensitive and rapid detection of COVID-19 with high specificity.

Enhancing global preparedness during an ongoing pandemic from partial and noisy data

As the coronavirus disease 2019 spread globally, emerging variants such as B.1.1.529 quickly became dominant worldwide. Sustained community transmission favors the proliferation of mutated sub-lineages with pandemic potential, due to cross-national mobility flows, which are responsible for consecutive cases surge worldwide. We show that, in the early stages of an emerging variant, integrating data from national genomic surveillance and global human mobility with large-scale epidemic modeling allows to quantify its pandemic potential, providing quantifiable indicators for pro-active policy interventions. We validate our framework on worldwide spreading variants and gain insights about the pandemic potential of BA.5, BA.2.75, and other sub- and lineages. We combine the different sources of information in a simple estimate of the pandemic delay and show that only in combination, the pandemic potentials of the lineages are correctly assessed relative to each other. Compared to a country-level epidemic intelligence, our scalable integrated approach, that is pandemic intelligence, permits to enhance global preparedness to contrast the pandemic of respiratory pathogens such as SARS-CoV-2.

A SARS-CoV-2: Companion Animal Transmission and Variants Classification

The continuous emergence of novel viruses and their diseases are a threat to global public health as there have been three outbreaks of coronaviruses that are highly pathogenic to humans in the span of the last two decades, severe acute respiratory syndrome (SARS)-CoV in 2002, Middle East respiratory syndrome (MERS)-CoV in 2012, and novel SARS-CoV-2 which emerged in 2019. The unprecedented spread of SARS-CoV-2 worldwide has given rise to multiple SARS-CoV-2 variants that have either altered transmissibility, infectivity, or immune escaping ability, causing diseases in a broad range of animals including human and non-human hosts such as companion, farm, zoo, or wild animals. In this review, we have discussed the recent SARS-CoV-2 outbreak, potential animal reservoirs, and natural infections in companion and farm animals, with a particular focus on SARS-CoV-2 variants. The expeditious development of COVID-19 vaccines and the advancements in antiviral therapeutics have contained the COVID-19 pandemic to some extent; however, extensive research and surveillance concerning viral epidemiology, animal transmission, variants, or seroprevalence in diverse hosts are essential for the future eradication of COVID-19.

SARS-CoV-2 omicron variants harbor spike protein mutations responsible for their attenuated fusogenic phenotype

Since the emergence of the Omicron variants at the end of 2021, they quickly became the dominant variants globally. The Omicron variants may be more easily transmitted compared to the earlier Wuhan and the other variants. In this study, we aimed to elucidate mechanisms of the altered infectivity associated with the Omicron variants. We systemically evaluated mutations located in the S2 sequence of spike and identified mutations that are responsible for altered viral fusion. We demonstrated that mutations near the S1/S2 cleavage site decrease S1/S2 cleavage, resulting in reduced fusogenicity. Mutations in the HR1 and other S2 sequences also affect cell-cell fusion. Based on nuclear magnetic resonance (NMR) studies and in silico modeling, these mutations affect fusogenicity possibly at multiple steps of the viral fusion. Our findings reveal that the Omicron variants have accumulated mutations that contribute to reduced syncytial formation and hence an attenuated pathogenicity.

Markov State Models and Perturbation-Based Approaches Reveal Distinct Dynamic Signatures and Hidden Allosteric Pockets in the Emerging SARS-Cov-2 Spike Omicron Variants Complexes with the Host Receptor: The Interplay of Dynamics and Convergent Evolution Modulates Allostery and Functional Mechanisms

The new generation of SARS-CoV-2 Omicron variants displayed a significant growth advantage and the increased viral fitness by acquiring convergent mutations, suggesting that the immune pressure can promote convergent evolution leading to the sudden acceleration of SARS-CoV-2 evolution. In the current study, we combined structural modeling, extensive microsecond MD simulations and Markov state models to characterize conformational landscapes and identify specific dynamic signatures of the SARS-CoV-2 spike complexes with the host receptor ACE2 for the recently emerged highly transmissible XBB.1, XBB.1.5, BQ.1, and BQ.1.1 Omicron variants. Microsecond simulations and Markovian modeling provided a detailed characterization of the conformational landscapes and revealed the increased thermodynamic stabilization of the XBB.1.5 subvariant which is contrasted to more dynamic BQ.1 and BQ.1.1 subvariants. Despite considerable structural similarities, Omicron mutations can induce unique dynamic signatures and specific distributions of conformational states. The results suggested that variant-specific changes of conformational mobility in the functional interfacial loops of the spike receptor binding domain can be fine-tuned through cross-talk between convergent mutations thereby providing an evolutionary path for modulation of immune escape. By combining atomistic simulations and Markovian modeling analysis with perturbation-based approaches, we determined important complementary roles of convergent mutation sites as effectors and receivers of allosteric signaling involved in modulating conformational plasticity at the binding interface and regulating allosteric responses. This study also characterized the dynamics-induced evolution of allosteric pockets in the Omicron complexes that revealed hidden allosteric pockets and suggested that convergent mutation sites could control evolution and distribution of allosteric pockets through modulation of conformational plasticity in the flexible adaptable regions. Through integrative computational approaches, this investigation provides a systematic analysis and comparison of the effects of Omicron subvariants on conformational dynamics and allosteric signaling in the complexes with the ACE2 receptor.

For Table of Contents Use Only

Multiplexed on-yeast serological assay for immune escape screening of SARS-CoV-2 variants

The emergence of the SARS-CoV-2 Omicron variant altered patient risk profiles and shifted the trajectory of the COVID-19 pandemic. Therefore, sensitive serological tests capable of analyzing patient IgG responses to multiple variants in parallel are highly desirable. Here, we present an adaptable serological test based on yeast surface display and serum biopanning that characterizes immune profiles against SARS-CoV-2 Wuhan (B lineage), Delta (B.1.617.2 lineage), and Omicron (B.1.1.529 lineage) receptor-binding domain (RBD) variants. We examined IgG titers from 30 serum samples from COVID-19-convalescent and vaccinated cohorts in Switzerland, and assessed the relative affinity of polyclonal serum IgG for RBD domains. We demonstrate that serum IgGs from patients recovered from severe COVID-19 between March-June 2021 bound tightly to both original Wuhan and Delta RBD variants, but failed to recognize Omicron RBDs, representing an affinity loss of >10- to 20-fold. Our yeast immunoassay is easily tailored, expandable and parallelized with newly emerging RBD variants.

Deep Mutational Scanning of an Oxygen-Independent Fluorescent Protein CreiLOV for Comprehensive Profiling of Mutational and Epistatic Effects

Oxygen-independent, flavin mononucleotide-based fluorescent proteins (FbFPs) are promising alternatives to green fluorescent protein in anaerobic contexts. Deep mutational scanning performs systematic profiling of protein sequence-function relationships but has not been applied to FbFPs. Focusing on CreiLOV from Chlamydomonas reinhardtii, we created and analyzed two comprehensive mutant collections: (1) single-residue, site-saturation mutagenesis libraries covering all 118 residues; and (2) a full combinatorial metagenesis library among 20 mutations at 15 residues, where mutation and residue selection was based on single-site mutagenesis results. Notably, the second type of library is indispensable to study higher-order epistasis but underrepresented in the literature. Using optimized FACS-seq assays, 2,185 (>92.5%) out of 2,360 possible single-site mutants and 165,428 (>89.7%) out of 184,320 possible combinatorial mutants were reliably assigned with fitness values. We constructed statistical and machine-learning models to analyze the CreiLOV data set, enabling accurate fitness prediction of higher-order mutants using lower-order mutagenesis data. In addition, we successfully isolated CreiLOV variants with improved fluorescence quantum yield and thermostability. This work provides new empirical data and design rules to engineer combinatorial protein variants.

Clinical and laboratory features of SARS-CoV-2 variants across multiple rounds of pandemic waves in hospitalized children in an Iranian referral hospital

BACKGROUND

Since the onset of the COVID-19 pandemic, SARS-CoV-2 has evolved into independent new forms, variants of concern (VOCs). While epidemiological data showed increased transmissibility of VOCs, their impact on clinical outcomes is less clear. This study aimed to investigate the differences between the clinical and laboratory features of children infected with VOCs.

METHODS

This study included all cases with SARS-CoV-2-positive nasopharyngeal swabs obtained from patients referred to Children's Medical Center (CMC), an Iranian referral hospital, between July 2021 and March 2022. The inclusion criteria for this study included all patients, regardless of age, who had a positive test anywhere in the hospital setting. Exclusion criteria for the study included those whose data was obtained from non-hospital outpatient settings, or referred from another hospital. The SARS-CoV-2 genome area encoding the S1 domain was amplified and sequenced. The type of variant in each sample was identified based on the mutations in the S1 gene. Demographic characteristics, clinical data, and laboratory findings were collected from the patient's medical records.

RESULTS

This study included 87 pediatric cases with confirmed COVID-19, with a median age of 3.5 years (IQR: 1-8.12). Data from sequencing reveals the type of variants as 5 (5.7%) alpha, 53 (60.9%) Delta, and 29 (33.3%) Omicron. The incidence of seizure was higher in patients with Alpha and Omicron infection compared to the Delta group. A higher incidence of diarrhea was reported in Alpha-infected patients, and a higher risk of disease severity, distress, and myalgia was associated with Delta infection.

CONCLUSION

Laboratory parameters did not mostly differ among the patients infected with Alpha, Delta, and Omicron. However, these variants may manifest different clinical features. Further studies with larger sample sizes are required to fully understand the clinical manifestations of each variant.

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.

A computationally designed ACE2 decoy has broad efficacy against SARS-CoV-2 omicron variants and related viruses in vitro and in vivo

SARS-CoV-2, especially B.1.1.529/omicron and its sublineages, continues to mutate to evade monoclonal antibodies and antibodies elicited by vaccination. Affinity-enhanced soluble ACE2 (sACE2) is an alternative strategy that works by binding the SARS-CoV-2 S protein, acting as a 'decoy' to block the interaction between the S and human ACE2. Using a computational design strategy, we designed an affinity-enhanced ACE2 decoy, FLIF, that exhibited tight binding to SARS-CoV-2 delta and omicron variants. Our computationally calculated absolute binding free energies (ABFE) between sACE2:SARS-CoV-2 S proteins and their variants showed excellent agreement to binding experiments. FLIF displayed robust therapeutic utility against a broad range of SARS-CoV-2 variants and sarbecoviruses, and neutralized omicron BA.5 in vitro and in vivo. Furthermore, we directly compared the in vivo therapeutic efficacy of wild-type ACE2 (non-affinity enhanced ACE2) against FLIF. A few wild-type sACE2 decoys have shown to be effective against early circulating variants such as Wuhan in vivo. Our data suggest that moving forward, affinity-enhanced ACE2 decoys like FLIF may be required to combat evolving SARS-CoV-2 variants. The approach described herein emphasizes how computational methods have become sufficiently accurate for the design of therapeutics against viral protein targets. Affinity-enhanced ACE2 decoys remain highly effective at neutralizing omicron subvariants.

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

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

Supplementary Information

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

Balancing Functional Tradeoffs between Protein Stability and ACE2 Binding in the SARS-CoV-2 Omicron BA.2, BA.2.75 and XBB Lineages: Dynamics-Based Network Models Reveal Epistatic Effects Modulating Compensatory Dynamic and Energetic Changes

Evolutionary and functional studies suggested that the emergence of the Omicron variants can be determined by multiple fitness trade-offs including the immune escape, binding affinity for ACE2, conformational plasticity, protein stability and allosteric modulation. In this study, we systematically characterize conformational dynamics, structural stability and binding affinities of the SARS-CoV-2 Spike Omicron complexes with the host receptor ACE2 for BA.2, BA.2.75, XBB.1 and XBB.1.5 variants. We combined multiscale molecular simulations and dynamic analysis of allosteric interactions together with the ensemble-based mutational scanning of the protein residues and network modeling of epistatic interactions. This multifaceted computational study characterized molecular mechanisms and identified energetic hotspots that can mediate the predicted increased stability and the enhanced binding affinity of the BA.2.75 and XBB.1.5 complexes. The results suggested a mechanism driven by the stability hotspots and a spatially localized group of the Omicron binding affinity centers, while allowing for functionally beneficial neutral Omicron mutations in other binding interface positions. A network-based community model for the analysis of epistatic contributions in the Omicron complexes is proposed revealing the key role of the binding hotspots R498 and Y501 in mediating community-based epistatic couplings with other Omicron sites and allowing for compensatory dynamics and binding energetic changes. The results also showed that mutations in the convergent evolutionary hotspot F486 can modulate not only local interactions but also rewire the global network of local communities in this region allowing the F486P mutation to restore both the stability and binding affinity of the XBB.1.5 variant which may explain the growth advantages over the XBB.1 variant. The results of this study are consistent with a broad range of functional studies rationalizing functional roles of the Omicron mutation sites that form a coordinated network of hotspots enabling a balance of multiple fitness tradeoffs and shaping up a complex functional landscape of virus transmissibility.

Probing Conformational Landscapes of Binding and Allostery in the SARS-CoV-2 Omicron Variant Complexes Using Microsecond Atomistic Simulations and Perturbation-Based Profiling Approaches: Hidden Role of Omicron Mutations as Modulators of Allosteric Signaling and Epistatic Relationships

In this study, we systematically examine the conformational dynamics, binding and allosteric communications in the Omicron BA.1, BA.2, BA.3 and BA.4/BA.5 complexes with the ACE2 host receptor using molecular dynamics simulations and perturbation-based network profiling approaches. Microsecond atomistic simulations provided a detailed characterization of the conformational landscapes and revealed the increased thermodynamic stabilization of the BA.2 variant which is contrasted with the BA.4/BA.5 variants inducing a significant mobility of the complexes. Using ensemble-based mutational scanning of binding interactions, we identified binding affinity and structural stability hotspots in the Omicron complexes. Perturbation response scanning and network-based mutational profiling approaches probed the effect of the Omicron variants on allosteric communications. The results of this analysis revealed specific roles of Omicron mutations as "plastic and evolutionary adaptable" modulators of binding and allostery which are coupled to the major regulatory positions through interaction networks. Through perturbation network scanning of allosteric residue potentials in the Omicron variant complexes, which is performed in the background of the original strain, we identified that the key Omicron binding affinity hotspots N501Y and Q498R could mediate allosteric interactions and epistatic couplings. Our results suggested that the synergistic role of these hotspots in controlling stability, binding and allostery can enable for compensatory balance of fitness tradeoffs with conformationally and evolutionary adaptable immune-escape Omicron mutations. Through integrative computational approaches, this study provides a systematic analysis of the effects of Omicron mutations on thermodynamics, binding and allosteric signaling in the complexes with ACE2 receptor. The findings support a mechanism in which Omicron mutations can evolve to balance thermodynamic stability and conformational adaptability in order to ensure proper tradeoff between stability, binding and immune escape.

Genotype-phenotype landscapes for immune-pathogen coevolution

Our immune systems constantly coevolve with the pathogens that challenge them, as pathogens adapt to evade our defense responses, with our immune repertoires shifting in turn. These coevolutionary dynamics take place across a vast and high-dimensional landscape of potential pathogen and immune receptor sequence variants. Mapping the relationship between these genotypes and the phenotypes that determine immune-pathogen interactions is crucial for understanding, predicting, and controlling disease. Here, we review recent developments applying high-throughput methods to create large libraries of immune receptor and pathogen protein sequence variants and measure relevant phenotypes. We describe several approaches that probe different regions of the high-dimensional sequence space and comment on how combinations of these methods may offer novel insight into immune-pathogen coevolution.

Principles of antibodies with ultralong complementarity-determining regions and picobodies

In contrast to other species, cattle possess exceptional antibodies with ultra-long complementarity-determining regions (ulCDRs) that can consist of 40-70 amino acids. The bovine ulCDR is folded into a stalk and a disulfide-rich knob domain. The binding to the antigen is via the 3-6 kDa knob. There exists an immense sequence and structural diversity in the knob that enables binding to different antigens. Here we summarize the current knowledge of the ulCDR structure and provide an overview of the approaches to discover ulCDRs against novel antigens. Furthermore, we outline protein engineering approaches inspired by the natural ulCDRs. Finally, we discuss the enormous potential of using isolated bovine knobs, also named picobodies, as the smallest antigen-binding domains derived from natural antibodies.

Leveraging deep learning to improve vaccine design

Deep learning has led to incredible breakthroughs in areas of research, from self-driving vehicles to solutions, to formal mathematical proofs. In the biomedical sciences, however, the revolutionary results seen in other fields are only now beginning to be realized. Vaccine research and development efforts represent an application with high public health significance. Protein structure prediction, immune repertoire analysis, and phylogenetics are three principal areas in which deep learning is poised to provide key advances. Here, we opine on some of the current challenges with deep learning and how they are being addressed. Despite the nascent stage of deep learning applications in immunological studies, there is ample opportunity to utilize this new technology to address the most challenging and burdensome infectious diseases confronting global populations.

Identification of CDRH3 loops in the B cell receptor repertoire that can be engaged by candidate immunogens

A major goal for the development of vaccines against rapidly mutating viruses, such as influenza or HIV, is to elicit antibodies with broad neutralization capacity. However, B cell precursors capable of maturing into broadly neutralizing antibodies (bnAbs) can be rare in the immune repertoire. Due to the stochastic nature of B cell receptor (BCR) rearrangement, a limited number of third heavy chain complementary determining region (CDRH3) sequences are identical between different individuals. Thus, in order to successfully engage broadly neutralizing antibody precursors that rely on their CDRH3 loop for antigen recognition, immunogens must be able to tolerate sequence diversity in the B cell receptor repertoire across an entire vaccinated population. Here, we present a combined experimental and computational approach to identify BCRs in the human repertoire with CDRH3 loops predicted to be engaged by a target immunogen. For a given antibody/antigen pair, deep mutational scanning was first used to measure the effect of CDRH3 loop substitution on binding. BCR sequences, isolated experimentally or generated in silico, were subsequently evaluated to identify CDRH3 loops expected to be bound by the candidate immunogen. We applied this method to characterize two HIV-1 germline-targeting immunogens and found differences in the frequencies with which they are expected to engage target B cells, thus illustrating how this approach can be used to evaluate candidate immunogens towards B cell precursors engagement and to inform immunogen optimization strategies for more effective vaccine design.