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

Human coronavirus HKU1 recognition of the TMPRSS2 host receptor

The human coronavirus HKU1 spike (S) glycoprotein engages host cell surface sialoglycans and transmembrane protease serine 2 (TMPRSS2) to initiate infection. The molecular basis of HKU1 binding to TMPRSS2 and determinants of host receptor tropism remain elusive. Here, we designed an active human TMPRSS2 construct enabling high-yield recombinant production in human cells of this key therapeutic target. We determined a cryo-electron microscopy structure of the HKU1 RBD bound to human TMPRSS2 providing a blueprint of the interactions supporting viral entry and explaining the specificity for TMPRSS2 among human type 2 transmembrane serine proteases. We found that human, rat, hamster and camel TMPRSS2 promote HKU1 S-mediated entry into cells and identified key residues governing host receptor usage. Our data show that serum antibodies targeting the HKU1 RBD TMPRSS2 binding-site are key for neutralization and that HKU1 uses conformational masking and glycan shielding to balance immune evasion and receptor engagement.

A regional genomic surveillance program is implemented to monitor the occurrence and emergence of SARS-CoV-2 variants in Yubei District, China

BACKGROUND

In December 2022, Chongqing experienced a significant surge in coronavirus disease 2019 (COVID-19) epidemic after adjusting control measures in China. Given the widespread immunization of the population with the BA.5 variant, it is crucial to actively monitor severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant evolution in Chongqing's Yubei district.

METHODS

In this retrospective study based on whole genome sequencing, we collected oropharyngeal and nasal swab of native COVID-19 cases from Yubei district between January to May 2023, along with imported cases from January 2022 to January 2023. Through second-generation sequencing, we generated a total of 578 genomes.

RESULTS

Phylogenetic analyses revealed these genomes belong to 47 SARS-CoV-2 Pango lineages. BA.5.2.48 was dominant from January to April 2023, rapidly replaced by XBB* variants from April to May 2023. Bayesian Skyline Plot reconstructions indicated a higher evolutionary rate (6.973 × 10-4 subs/site/year) for the XBB.1.5* lineage compared to others. The mean time to the most recent common ancestor (tMRCA) of BA.5.2.48* closely matched BA.2.75* (May 27, 2022). Using multinomial logistic regression, we estimated growth advantages, with XBB.1.9.1 showing the highest growth advantage (1.2, 95% HPI:1.1-1.2), followed by lineage FR.1 (1.1, 95% HPI:1.1-1.2).

CONCLUSIONS

Our monitoring reveals the rapid replacement of the previously prevalent BA.5.2.48 variant by XBB and its sub-variants, underscoring the ineffectiveness of herd immunity and breakthrough BA.5 infections against XBB variants. Given the ongoing evolutionary pressure, sustaining a SARS-CoV-2 genomic surveillance program is imperative.

Studying SARS-CoV-2 interactions using phage-displayed receptor binding domain as a model protein

SARS-CoV-2 receptor binding domain (RBD) mediates viral entry into human cells through its interaction with angiotensin converting enzyme 2 (ACE2). Most neutralizing antibodies elicited by infection or vaccination target this domain. Such a functional relevance, together with large RBD sequence variability arising during viral spreading, point to the need of exploring the complex landscape of interactions between RBD-derived variants, ACE2 and antibodies. The current work was aimed at developing a simple platform to do so. Biologically active and antigenic Wuhan-Hu-1 RBD, as well as mutated RBD variants found in nature, were successfully displayed on filamentous phages. Mutational scanning confirmed the global plasticity of the receptor binding motif within RBD, highlighted residues playing a critical role in receptor binding, and identified mutations strengthening the interaction. The ability of vaccine-induced antibodies to inhibit ACE2 binding of many mutated RBD variants, albeit at different extents, was shown. Amino acid replacements which could compromise such inhibitory potential were underscored. The expansion of our approach could be the starting point for a large-scale phage-based exploration of diversity within RBD of SARS-CoV-2 and related coronaviruses, useful to understand structure-function relationships, to engineer RBD proteins, and to anticipate changes to watch during viral evolution.

Epidemiology of COVID-19

This chapter provides a detailed exploration of the epidemiology of COVID-19, focusing on several key aspects that offer valuable insights into the disease progression. A comprehensive comparison is made between the three related coronaviruses: SARS-CoV, MERS-CoV, and SARS-CoV-2, elucidating their similarities and differences in terms of transmission dynamics, clinical presentation, laboratory and radiological findings, infection mechanisms, and mortality rates. The concept of herd immunity is then discussed, exploring its relevance and potential implications for controlling the spread of COVID-19. Next, the chapter delves into the changing epidemiology of the disease, examining how various factors such as human behavior, public health interventions, and viral mutations have influenced its transmission patterns and severity over time. Finally, the timelines and evolution of COVID-19 are outlined, tracing the origins of the virus, its rapid global spread, and the emergence of new variants.

Generation of SARS-CoV-2 spike receptor binding domain mutants and functional screening for immune evaders using a novel lentivirus-based system

The emergence of rapid and continuous mutations of severe acute respiratory syndrome 2 (SARS-CoV-2) spike glycoprotein that increased with the Omicron variant points out the necessity to anticipate such mutations for conceiving specific and adaptable therapies to avoid another pandemic. The crucial target for the antibody treatment and vaccine design is the receptor binding domain (RBD) of the SARS-CoV-2 spike. It is also the site where the virus has shown its high ability to mutate and consequently escape immune response. We developed a robust and simple method for generating a large number of functional SARS-CoV-2 spike RBD mutants by error-prone PCR and a novel nonreplicative lentivirus-based system. We prepared anti-RBD wild type (WT) polyclonal antibodies and used them to screen and select for mutant libraries that escape inhibition of virion entry into recipient cells expressing human angiotensin-converting enzyme 2 and transmembrane serine protease 2. We isolated, cloned, and sequenced six mutants totally bearing nine mutation sites. Eight mutations were found in successive WT variants, including Omicron and other recombinants, whereas one is novel. These results, together with the detailed functional analyses of two mutants provided the proof of concept for our approach.

ACE2-Fc and DPP4-Fc decoy receptors against SARS-CoV-2 and MERS-CoV variants: a quick therapeutic option for current and future coronaviruses outbreaks

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and the Middle East respiratory syndrome coronavirus (MERS-CoV) are highly pathogenic human coronaviruses (CoVs). Anti-CoVs mAbs and vaccines may be effective, but the emergence of neutralization escape variants is inevitable. Angiotensin-converting enzyme 2 and dipeptidyl peptidase 4 enzyme are the getaway receptors for SARS-CoV-2 and MERS-CoV, respectively. Thus, we reformatted these receptors as Fc-fusion decoy receptors. Then, we tested them in parallel with anti-SARS-CoV (ab1-IgG) and anti-MERS-CoV (M336-IgG) mAbs against several variants using pseudovirus neutralization assay. The generated Fc-based decoy receptors exhibited a strong inhibitory effect against all pseudotyped CoVs. Results showed that although mAbs can be effective antiviral drugs, they might rapidly lose their efficacy against highly mutated viruses. We suggest that receptor traps can be engineered as Fc-fusion proteins for highly mutating viruses with known entry receptors, for a faster and effective therapeutic response even against virus harboring antibodies escape mutations.

Molecular interactions between perlecan LG3 and the SARS-CoV-2 spike protein receptor binding domain

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has caused a global health crisis with significant clinical morbidity and mortality. While angiotensin-converting enzyme 2 (ACE2) is the primary receptor for viral entry, other cell surface and extracellular matrix proteins may also bind to the viral receptor binding domain (RBD) within the SARS-CoV-2 spike protein. Recent studies have implicated heparan sulfate proteoglycans, specifically perlecan LG3, in facilitating SARS-CoV-2 binding to ACE2. However, the role of perlecan LG3 in SARS-CoV-2 pathophysiology is not well understood. In this study, we investigated the binding interactions between the SARS-CoV-2 spike protein RBD and perlecan LG3 through molecular modeling simulations and surface plasmon resonance (SPR) experiments. Our results indicate stable binding between LG3 and SARS-CoV-2 spike protein RBD, which may potentially enhance RBD-ACE2 interactions. These findings shed light on the role of perlecan LG3 in SARS-CoV-2 infection and provide insight into SARS-CoV-2 pathophysiology and potential therapeutic strategy for COVID-19.

Rapidly Evolving SARS-CoV-2: A Brief Review Regarding the Variants and their Effects on Vaccine Efficacies

Since the commencement of Corona Virus Disease 2019 (COVID-19) pandemic, which has resulted in millions of mortalities globally, the efforts to minimize the damages have equally been up to the task. One of those efforts includes the mass vaccine development initiative targeting the deadly Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). So far, vaccines have tremendously decreased the rate of transmission and infection in most parts of the world. However, the repeated resurgence of different types of mutated versions of the virus, also known as variants, has somehow created uncertainties about the efficacies of different types of vaccines. This review discusses some of the interesting SARS-CoV-2 features, including general structure, genomics, and mechanisms of variants development and their consequent immune escape. This review also focuses very briefly on antigenic drift, shift, and vaccine-developing platforms.

Repeated Omicron exposures override ancestral SARS-CoV-2 immune imprinting

The continuing emergence of SARS-CoV-2 variants highlights the need to update COVID-19 vaccine compositions. However, immune imprinting induced by vaccination based on the ancestral (hereafter referred to as WT) strain would compromise the antibody response to Omicron-based boosters1-5. Vaccination strategies to counter immune imprinting are critically needed. Here we investigated the degree and dynamics of immune imprinting in mouse models and human cohorts, especially focusing on the role of repeated Omicron stimulation. In mice, the efficacy of single Omicron boosting is heavily limited when using variants that are antigenically distinct from WT-such as the XBB variant-and this concerning situation could be mitigated by a second Omicron booster. Similarly, in humans, repeated Omicron infections could alleviate WT vaccination-induced immune imprinting and generate broad neutralization responses in both plasma and nasal mucosa. Notably, deep mutational scanning-based epitope characterization of 781 receptor-binding domain (RBD)-targeting monoclonal antibodies isolated from repeated Omicron infection revealed that double Omicron exposure could induce a large proportion of matured Omicron-specific antibodies that have distinct RBD epitopes to WT-induced antibodies. Consequently, immune imprinting was largely mitigated, and the bias towards non-neutralizing epitopes observed in single Omicron exposures was restored. On the basis of the deep mutational scanning profiles, we identified evolution hotspots of XBB.1.5 RBD and demonstrated that these mutations could further boost the immune-evasion capability of XBB.1.5 while maintaining high ACE2-binding affinity. Our findings suggest that the WT component should be abandoned when updating COVID-19 vaccines, and individuals without prior Omicron exposure should receive two updated vaccine boosters.

Mammalian Antigen Display for Pandemic Countermeasures

Pandemic countermeasures require the rapid design of antigens for vaccines, profiling patient antibody responses, assessing antigen structure-function landscapes, and the surveillance of emerging viral lineages. Cell surface display of a viral antigen or its subdomains can facilitate these goals by coupling the phenotypes of protein variants to their DNA sequence. Screening surface-displayed proteins via flow cytometry also eliminates time-consuming protein purification steps. Prior approaches have primarily relied on yeast as a display chassis. However, yeast often cannot express large viral glycoproteins, requiring their truncation into subdomains. Here, we describe a method to design and express antigens on the surface of mammalian HEK293T cells. We discuss three use cases, including screening of stabilizing mutations, deep mutational scanning, and epitope mapping. The mammalian antigen display platform described herein will accelerate ongoing and future pandemic countermeasures.

Risk assessment of SARS-CoV-2 replicating and evolving in animals

The retransmissions of SARS-CoV-2 from several mammals - primarily mink and white-tailed deer - to humans have raised concerns for the emergence of a new animal-derived SARS-CoV-2 variant to worsen the pandemic. Here, we discuss animal species that are susceptible to natural or experimental infection with SARS-CoV-2 and can transmit the virus to mates or humans. We describe cutting-edge techniques to assess the impact of a mutation in the viral spike (S) protein on its receptor and on antibody binding. Our review of spike sequences of animal-derived viruses identified nine unique amino acid exchanges in the receptor-binding domain (RBD) that are not present in any variant of concern (VOC). These mutations are present in SARS-CoV-2 found in companion animals such as dogs and cats, and they exhibit a higher frequency in SARS-CoV-2 found in mink and white-tailed deer, suggesting that sustained transmissions may contribute to maintaining novel mutations. Four of these exchanges, such as Leu452Met, could undermine acquired immune protection in humans while maintaining high affinity for the human angiotensin-converting enzyme 2 (ACE2) receptor. Finally, we discuss important avenues of future research into animal-derived viruses with public health risks.

Computational multigene interactions in virus growth and infection spread

Viruses persist in nature owing to their extreme genetic heterogeneity and large population sizes, which enable them to evade host immune defenses, escape antiviral drugs, and adapt to new hosts. The persistence of viruses is challenging to study because mutations affect multiple virus genes, interactions among genes in their impacts on virus growth are seldom known, and measures of viral fitness are yet to be standardized. To address these challenges, we employed a data-driven computational model of cell infection by a virus. The infection model accounted for the kinetics of viral gene expression, functional gene-gene interactions, genome replication, and allocation of host cellular resources to produce progeny of vesicular stomatitis virus, a prototype RNA virus. We used this model to computationally probe how interactions among genes carrying up to eleven deleterious mutations affect different measures of virus fitness: single-cycle growth yields and multicycle rates of infection spread. Individual mutations were implemented by perturbing biophysical parameters associated with individual gene functions of the wild-type model. Our analysis revealed synergistic epistasis among deleterious mutations in their effects on virus yield; so adverse effects of single deleterious mutations were amplified by interaction. For the same mutations, multicycle infection spread indicated weak or negligible epistasis, where single mutations act alone in their effects on infection spread. These results were robust to simulation in high- and low-host resource environments. Our work highlights how different types and magnitudes of epistasis can arise for genetically identical virus variants, depending on the fitness measure. More broadly, gene-gene interactions can differently affect how viruses grow and spread.

Distinctive Combinations of RBD Mutations Contribute to Antibody Evasion in the Case of the SARS-CoV-2 Beta Variant

Since its first report in 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has posed a grave threat to public health. Virus-specific countermeasures, such as vaccines and therapeutics, have been developed and have contributed to the control of the viral pandemic, which has become endemic. Nonetheless, new variants continue to emerge and could cause a new pandemic. Consequently, it is important to comprehensively understand viral evolution and the roles of mutations in viral infectivity and transmission. SARS-CoV-2 beta variant encode mutations (D614G, N501Y, E484K, and K417N) in the spike which are frequently found in other variants as well. While their individual role in viral infectivity has been elucidated against various therapeutic antibodies, it still remains unclear whether those mutations may act additively or synergistically when combined. Here, we report that N501Y mutation shows differential effect on two therapeutic antibodies tested. Interestingly, the relative importance of E484K and K417N mutations in antibody evasion varies depending on the antibody type. Collectively, these findings suggest that continuous efforts to develop effective antibody therapeutics and combinatorial treatment with multiple antibodies are more rational and effective forms of treatment.

ACIDES: on-line monitoring of forward genetic screens for protein engineering

Forward genetic screens of mutated variants are a versatile strategy for protein engineering and investigation, which has been successfully applied to various studies like directed evolution (DE) and deep mutational scanning (DMS). While next-generation sequencing can track millions of variants during the screening rounds, the vast and noisy nature of the sequencing data impedes the estimation of the performance of individual variants. Here, we propose ACIDES that combines statistical inference and in-silico simulations to improve performance estimation in the library selection process by attributing accurate statistical scores to individual variants. We tested ACIDES first on a random-peptide-insertion experiment and then on multiple public datasets from DE and DMS studies. ACIDES allows experimentalists to reliably estimate variant performance on the fly and can aid protein engineering and research pipelines in a range of applications, including gene therapy.

Evolution of the SARS-CoV-2 Omicron spike

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant of concern, first identified in November 2021, rapidly spread worldwide and diversified into several subvariants. The Omicron spike (S) protein accumulated an unprecedented number of sequence changes relative to previous variants. In this review, we discuss how Omicron S protein structural features modulate host cell receptor binding, virus entry, and immune evasion and highlight how these structural features differentiate Omicron from previous variants. We also examine how key structural properties track across the still-evolving Omicron subvariants and the importance of continuing surveillance of the S protein sequence evolution over time.

Broad receptor tropism and immunogenicity of a clade 3 sarbecovirus

Although Rhinolophus bats harbor diverse clade 3 sarbecoviruses, the structural determinants of receptor tropism along with the antigenicity of their spike (S) glycoproteins remain uncharacterized. Here, we show that the African Rhinolophus bat clade 3 sarbecovirus PRD-0038 S has a broad angiotensin-converting enzyme 2 (ACE2) usage and that receptor-binding domain (RBD) mutations further expand receptor promiscuity and enable human ACE2 utilization. We determine a cryo-EM structure of the PRD-0038 RBD bound to Rhinolophus alcyone ACE2, explaining receptor tropism and highlighting differences with SARS-CoV-1 and SARS-CoV-2. Characterization of PRD-0038 S using cryo-EM and monoclonal antibody reactivity reveals its distinct antigenicity relative to SARS-CoV-2 and identifies PRD-0038 cross-neutralizing antibodies for pandemic preparedness. PRD-0038 S vaccination elicits greater titers of antibodies cross-reacting with vaccine-mismatched clade 2 and clade 1a sarbecoviruses compared with SARS-CoV-2 S due to broader antigenic targeting, motivating the inclusion of clade 3 antigens in next-generation vaccines for enhanced resilience to viral evolution.

AlphaFold2-Enabled Atomistic Modeling of Epistatic Binding Mechanisms for the SARS-CoV-2 Spike Omicron XBB.1.5, EG.5 and FLip Variants: Convergent Evolution Hotspots Cooperate to Control Stability and Conformational Adaptability in Balancing ACE2 Binding and Antibody Resistance

In this study, we combined AI-based atomistic structural modeling and microsecond molecular simulations of the SARS-CoV-2 Spike complexes with the host receptor ACE2 for XBB.1.5+L455F, XBB.1.5+F456L(EG.5) and XBB.1.5+L455F/F456L (FLip) lineages to examine the mechanisms underlying the role of convergent evolution hotspots in balancing ACE2 binding and antibody evasion. Using the ensemble-based mutational scanning of the spike protein residues and physics-based rigorous computations of binding affinities, we identified binding energy hotspots and characterized molecular basis underlying epistatic couplings between convergent mutational hotspots. Consistent with the experiments, the results revealed the mediating role of Q493 hotspot in synchronization of epistatic couplings between L455F and F456L mutations providing a quantitative insight into the mechanism underlying differences between XBB lineages. Mutational profiling is combined with network-based model of epistatic couplings showing that the Q493, L455 and F456 sites mediate stable communities at the binding interface with ACE2 and can serve as stable mediators of non-additive couplings. Structure-based mutational analysis of Spike protein binding with the class 1 antibodies quantified the critical role of F456L and F486P mutations in eliciting strong immune evasion response. The results of this analysis support a mechanism in which the emergence of EG.5 and FLip variants may have been dictated by leveraging strong epistatic effects between several convergent revolutionary hotspots that provide synergy between the improved ACE2 binding and broad neutralization resistance. This interpretation is consistent with the notion that functionally balanced substitutions which simultaneously optimize immune evasion and high ACE2 affinity may continue to emerge through lineages with beneficial pair or triplet combinations of RBD mutations involving mediators of epistatic couplings and sites in highly adaptable RBD regions.

Age-dependent heterogeneity in the antigenic effects of mutations to influenza hemagglutinin

Human influenza virus evolves to escape neutralization by polyclonal antibodies. However, we have a limited understanding of how the antigenic effects of viral mutations vary across the human population, and how this heterogeneity affects virus evolution. Here we use deep mutational scanning to map how mutations to the hemagglutinin (HA) proteins of the A/Hong Kong/45/2019 (H3N2) and A/Perth/16/2009 (H3N2) strains affect neutralization by serum from individuals of a variety of ages. The effects of HA mutations on serum neutralization differ across age groups in ways that can be partially rationalized in terms of exposure histories. Mutations that fixed in influenza variants after 2020 cause the greatest escape from sera from younger individuals. Overall, these results demonstrate that influenza faces distinct antigenic selection regimes from different age groups, and suggest approaches to understand how this heterogeneous selection shapes viral evolution.

Early Emerging SARS-CoV-2 Spike Mutants Are Diversified in Virologic Properties but Elicit Compromised Antibody Responses

Despite the effective antivirals and vaccines, COVID-19 remains a public health concern. The mutations that occurred during the early stage of the pandemic can be valuable in assessing the viral fitness and evolutionary trajectory. In this study, we analyzed a panel of 2969 spike sequences deposited in GISAID before April 2020 and characterized nine representative spike single-point mutants in detail. Compared with the WA01/2020, most (8 out of 9) mutants demonstrated an equivalent or diminished protein expression or processing, pseudovirus infectivity, and cell-cell fusion. Interestingly, most of the mutants in native form elicited minimum antibody responses in mice despite unaltered CD4+ and CD8+ T cell responses. The mutants remained sensitive to the antisera and the type I interferon. Taken together, these data suggest that the early emerging mutants are virologically divergent, and some of which showed transmission fitness. Our findings have important implications for the retrospective tracing of the early SARS-CoV-2 transmission and future pandemic preparedness.

ProteinGym: Large-Scale Benchmarks for Protein Design and Fitness Prediction

Predicting the effects of mutations in proteins is critical to many applications, from understanding genetic disease to designing novel proteins that can address our most pressing challenges in climate, agriculture and healthcare. Despite a surge in machine learning-based protein models to tackle these questions, an assessment of their respective benefits is challenging due to the use of distinct, often contrived, experimental datasets, and the variable performance of models across different protein families. Addressing these challenges requires scale. To that end we introduce ProteinGym, a large-scale and holistic set of benchmarks specifically designed for protein fitness prediction and design. It encompasses both a broad collection of over 250 standardized deep mutational scanning assays, spanning millions of mutated sequences, as well as curated clinical datasets providing high-quality expert annotations about mutation effects. We devise a robust evaluation framework that combines metrics for both fitness prediction and design, factors in known limitations of the underlying experimental methods, and covers both zero-shot and supervised settings. We report the performance of a diverse set of over 70 high-performing models from various subfields (eg., alignment-based, inverse folding) into a unified benchmark suite. We open source the corresponding codebase, datasets, MSAs, structures, model predictions and develop a user-friendly website that facilitates data access and analysis.

Virological Characteristics of Five SARS-CoV-2 Variants, Including Beta, Delta and Omicron BA.1, BA.2, BA.5

SARS-CoV-2 variants of concern (VOCs) show increasing transmissibility and infectivity and induce substantial injuries to human health and the ecology. Therefore, it is vital to understand the related features for controlling infection. In this study, SARS-CoV-2 WIV04 (prototype) and five VOCs (Beta, Delta, Omicron BA.1, BA.2 and BA.5 variants) were inoculated in Vero cells to observe their growth activities. Apart from evaluating the environmental stability at different temperatures, residual virus titers and infectivity at different temperatures (4 °C, room temperature (RT) and 37 °C) were measured over 7 days. The experiment also assessed the infectivity for different incubation durations. The growth capacity assay suggested that the WIV04, Beta and Delta variants replicated efficiently in Vero cells compared with Omicron Variants, and BA.2 replicated more efficiently in Vero cells than BA.1 and BA.5. In addition, all variants exhibited longer survivals at 4 °C and could remain infectious after 7 days, compared to RT' survival after 5 days and at 37 °C after 1 day. The virus infection assay indicated that the Omicron variant had a weaker ability to infect cells compared to the WIV04, Beta and Delta strains, and a longer infection time was required for these strains, except for BA.2.

Bioinformatic investigation of Nipah virus surface protein mutations: Molecular docking with Ephrin B2 receptor, molecular dynamics simulation, and structural impact analysis

The SARS-CoV-2 outbreak resulted in significant challenges and loss of life. The Nipah virus, known for its high infectivity and severity, was designated an emergency concern by the World Health Organization. To understand its mutations, the Nipah virus proteins were analyzed extensively, with a focus on the essential G and F proteins responsible for viral entry into host cells. Our bioinformatics analysis unveiled multiple mutations, including simultaneous mutations within a single sequence. Notably, the G273S mutation in the F protein was identified as a potential cause of structural damage, which carries significant implications for vaccine development. Comparing the docking scores of G and F proteins with the Ephrin B2 receptor, it was found that the Y228H mutation in the G protein and the D252G mutation in the F protein likely affect virus entry into host cells. Moreover, our investigation into stability and deformability highlighted the impact of the Y228H mutation in the G protein complex. Molecular dynamics simulations revealed increased flexibility and conformational changes in the G protein complex with the Y228H mutation compared with the known complex. Furthermore, evaluating the root mean square deviation variation demonstrated greater dynamic behavior in the G protein complex and the Ephrin B2 receptor complex. This comprehensive study provides valuable insights into Nipah virus mutations, their significance for vaccine development, and the importance of understanding protein complex behavior in drug discovery. The identified mutations, especially G273S and Y228H, hold crucial implications for future research and potential interventions against the Nipah virus.

A bivalent form of a RBD-specific synthetic antibody effectively neutralizes SARS-CoV-2 variants

Coronavirus Disease 2019 (COVID-19) pandemic is severely impacting the world, and tremendous efforts have been made to deal with it. Despite many advances in vaccines and therapeutics, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants remains an intractable challenge. We present a bivalent Receptor Binding Domain (RBD)-specific synthetic antibody, specific for the RBD of wild-type (lineage A), developed from a non-antibody protein scaffold composed of LRR (Leucine-rich repeat) modules through phage display. We further reinforced the unique feature of the synthetic antibody by constructing a tandem dimeric form. The resulting bivalent form showed a broader neutralizing activity against the variants. The in vivo neutralizing efficacy of the bivalent synthetic antibody was confirmed using a human ACE2-expressing mouse model that significantly alleviated viral titer and lung infection. The present approach can be used to develop a synthetic antibody showing a broader neutralizing activity against a multitude of SARS-CoV-2 variants.

Steering and controlling evolution - from bioengineering to fighting pathogens

Control interventions steer the evolution of molecules, viruses, microorganisms or other cells towards a desired outcome. Applications range from engineering biomolecules and synthetic organisms to drug, therapy and vaccine design against pathogens and cancer. In all these instances, a control system alters the eco-evolutionary trajectory of a target system, inducing new functions or suppressing escape evolution. Here, we synthesize the objectives, mechanisms and dynamics of eco-evolutionary control in different biological systems. We discuss how the control system learns and processes information about the target system by sensing or measuring, through adaptive evolution or computational prediction of future trajectories. This information flow distinguishes pre-emptive control strategies by humans from feedback control in biotic systems. We establish a cost-benefit calculus to gauge and optimize control protocols, highlighting the fundamental link between predictability of evolution and efficacy of pre-emptive control.

Antigenicity and receptor affinity of SARS-CoV-2 BA.2.86 spike

A severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron subvariant, BA.2.86, has emerged and spread to numerous countries worldwide, raising alarm because its spike protein contains 34 additional mutations compared with its BA.2 predecessor1. We examined its antigenicity using human sera and monoclonal antibodies (mAbs). Reassuringly, BA.2.86 was no more resistant to human sera than the currently dominant XBB.1.5 and EG.5.1, indicating that the new subvariant would not have a growth advantage in this regard. Importantly, sera from people who had XBB breakthrough infection exhibited robust neutralizing activity against all viruses tested, suggesting that upcoming XBB.1.5 monovalent vaccines could confer added protection. Although BA.2.86 showed greater resistance to mAbs to subdomain 1 (SD1) and receptor-binding domain (RBD) class 2 and 3 epitopes, it was more sensitive to mAbs to class 1 and 4/1 epitopes in the 'inner face' of the RBD that is exposed only when this domain is in the 'up' position. We also identified six new spike mutations that mediate antibody resistance, including E554K that threatens SD1 mAbs in clinical development. The BA.2.86 spike also had a remarkably high receptor affinity. The ultimate trajectory of this new SARS-CoV-2 variant will soon be revealed by continuing surveillance, but its worldwide spread is worrisome.

Predicting virus Fitness: Towards a structure-based computational model

Predicting the impact of new emerging virus mutations is of major interest in surveillance and for understanding the evolutionary forces of the pathogens. The SARS-CoV-2 surface spike-protein (S-protein) binds to human ACE2 receptors as a critical step in host cell infection. At the same time, S-protein binding to human antibodies neutralizes the virus and prevents interaction with ACE2. Here we combine these two binding properties in a simple virus fitness model, using structure-based computation of all possible mutation effects averaged over 10 ACE2 complexes and 10 antibody complexes of the S-protein (∼380,000 computed mutations), and validated the approach against diverse experimental binding/escape data of ACE2 and antibodies. The ACE2-antibody selectivity change caused by mutation (i.e., the differential change in binding to ACE2 vs. immunity-inducing antibodies) is proposed to be a key metric of fitness model, enabling systematic error cancelation when evaluated. In this model, new mutations become fixated if they increase the selective binding to ACE2 relative to circulating antibodies, assuming that both are present in the host in a competitive binding situation. We use this model to categorize viral mutations that may best reach ACE2 before being captured by antibodies. Our model may aid the understanding of variant-specific vaccines and molecular mechanisms of viral evolution in the context of a human host.

Deep mutational scans of XBB.1.5 and BQ.1.1 reveal ongoing epistatic drift during SARS-CoV-2 evolution

Substitutions that fix between SARS-CoV-2 variants can transform the mutational landscape of future evolution via epistasis. For example, large epistatic shifts in mutational effects caused by N501Y underlied the original emergence of Omicron, but whether such epistatic saltations continue to define ongoing SARS-CoV-2 evolution remains unclear. We conducted deep mutational scans to measure the impacts of all single amino acid mutations and single-codon deletions in the spike receptor-binding domain (RBD) on ACE2-binding affinity and protein expression in the recent Omicron BQ.1.1 and XBB.1.5 variants, and we compared mutational patterns to earlier viral strains that we have previously profiled. As with previous deep mutational scans, we find many mutations that are tolerated or even enhance binding to ACE2 receptor. The tolerance of sites to single-codon deletion largely conforms with tolerance to amino acid mutation. Though deletions in the RBD have not yet been seen in dominant lineages, we observe tolerated deletions including at positions that exhibit indel variation across broader sarbecovirus evolution and in emerging SARS-CoV-2 variants of interest, most notably the well-tolerated Δ483 deletion in BA.2.86. The substitutions that distinguish recent viral variants have not induced as dramatic of epistatic perturbations as N501Y, but we identify ongoing epistatic drift in SARS-CoV-2 variants, including interaction between R493Q reversions and mutations at positions 453, 455, and 456, including F456L that defines the XBB.1.5-derived EG.5 lineage. Our results highlight ongoing drift in the effects of mutations due to epistasis, which may continue to direct SARS-CoV-2 evolution into new regions of sequence space.

Humoral and cellular immunity against diverse SARS-CoV-2 variants

Since the outbreak of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in late 2019, the virus has rapidly spread worldwide. This has led to an unprecedented global pandemic, marked by millions of COVID-19 cases and a significant number of fatalities. Over a relatively short period, several different vaccine platforms are developed and deployed for use globally to curb the pandemic. However, the genome of SARS-CoV-2 continuously undergoes mutation and/or recombination, resulting in the emergence of several variants of concern (VOC). These VOCs can elevate viral transmission and evade the neutralizing antibodies induced by vaccines, leading to reinfections. Understanding the impact of the SARS-CoV-2 genomic mutation on viral pathogenesis and immune escape is crucial for assessing the threat of new variants to public health. This review focuses on the emergence and pathogenesis of VOC, with particular emphasis on their evasion of neutralizing antibodies. Furthermore, the memory B cell, CD4+, and CD8+ T cell memory induced by different COVID-19 vaccines or infections are discussed, along with how these cells recognize VOC. This review summarizes the current knowledge on adaptive immunology regarding SARS-CoV-2 infection and vaccines. Such knowledge may also be applied to vaccine design for other pathogens.

Deep mutational scanning reveals the functional constraints and evolutionary potential of the influenza A virus PB1 protein

IMPORTANCE

The influenza virus polymerase is important for adaptation to new hosts and, as a determinant of mutation rate, for the process of adaptation itself. We performed a deep mutational scan of the polymerase basic 1 (PB1) protein to gain insights into the structural and functional constraints on the influenza RNA-dependent RNA polymerase. We find that PB1 is highly constrained at specific sites that are only moderately predicted by the global structure or larger domain. We identified a number of beneficial mutations, many of which have been shown to be functionally important or observed in influenza virus' natural evolution. Overall, our atlas of PB1 mutations and their fitness impacts serves as an important resource for future studies of influenza replication and evolution.

Functional and antigenic characterization of SARS-CoV-2 spike fusion peptide by deep mutational scanning

The fusion peptide of SARS-CoV-2 spike protein is functionally important for membrane fusion during virus entry and is part of a broadly neutralizing epitope. However, sequence determinants at the fusion peptide and its adjacent regions for pathogenicity and antigenicity remain elusive. In this study, we performed a series of deep mutational scanning (DMS) experiments on an S2 region spanning the fusion peptide of authentic SARS-CoV-2 in different cell lines and in the presence of broadly neutralizing antibodies. We identified mutations at residue 813 of the spike protein that reduced TMPRSS2-mediated entry with decreased virulence. In addition, we showed that an F823Y mutation, present in bat betacoronavirus HKU9 spike protein, confers resistance to broadly neutralizing antibodies. Our findings provide mechanistic insights into SARS-CoV-2 pathogenicity and also highlight a potential challenge in developing broadly protective S2-based coronavirus vaccines.

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 reveals 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 demonstrate that the CDR H3 sequences from many other IGHV1-69 antibodies, including those to the HA stem, are 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.

Beta-spike-containing boosters induce robust and functional antibody responses to SARS-CoV-2 in macaques primed with distinct vaccines

The reduced effectiveness of COVID-19 vaccines due to the emergence of variants of concern (VOCs) necessitated the use of vaccine boosters to bolster protection against disease. However, it remains unclear how boosting expands protective breadth when primary vaccine platforms are distinct and how boosters containing VOC spike(s) broaden humoral responses. Here, we report that boosters composed of recombinant spike antigens of ancestral (prototype) and Beta VOCs elicit a robust, pan-VOC, and multi-functional humoral response in non-human primates largely independent of the primary vaccine series platform. Interestingly, Beta-spike-containing boosters stimulate immunoglobulin A (IgA) with a greater breadth of recognition in protein-primed recipients when administered with adjuvant system 03 (AS03). Our results highlight the utility of a component-based booster strategy for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) for broad humoral recognition, independent of primary vaccine series. This is of high global health importance given the heterogeneity of primary vaccination platforms distributed.

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

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

SARS-CoV-2 genomics and impact on clinical care for COVID-19

The emergence and worldwide spread of SARS-CoV-2 during the COVID-19 pandemic necessitated the adaptation and rapid deployment of viral WGS and analysis techniques that had been previously applied on a more limited basis to other viral pathogens, such as HIV and influenza viruses. The need for WGS was driven in part by the low mutation rate of SARS-CoV-2, which necessitated measuring variation along the entire genome sequence to effectively differentiate lineages and characterize viral evolution. Several WGS approaches designed to maximize throughput and accuracy were quickly adopted by surveillance labs around the world. These broad-based SARS-CoV-2 genomic sequencing efforts revealed ongoing evolution of the virus, highlighted by the successive emergence of new viral variants throughout the course of the pandemic. These genomic insights were instrumental in characterizing the effects of viral mutations on transmissibility, immune escape and viral tropism, which in turn helped guide public health policy, the use of monoclonal antibody therapeutics and vaccine development strategies. As the use of direct-acting antivirals for the treatment of COVID-19 became more widespread, the potential for emergence of antiviral resistance has driven ongoing efforts to delineate resistance mutations and to monitor global sequence databases for their emergence. Given the critical role of viral genomics in the international effort to combat the COVID-19 pandemic, coordinated efforts should be made to expand global genomic surveillance capacity and infrastructure towards the anticipation and prevention of future pandemics.

Quantification of biases in predictions of protein-protein binding affinity changes upon mutations

Understanding the impact of mutations on protein-protein binding affinity is a key objective for a wide range of biotechnological applications and for shedding light on disease-causing mutations, which are often located at protein-protein interfaces. Over the past decade, many computational methods using physics-based and/or machine learning approaches have been developed to predict how protein binding affinity changes upon mutations. They all claim to achieve astonishing accuracy on both training and test sets, with performances on standard benchmarks such as SKEMPI 2.0 that seem overly optimistic. Here we benchmarked eight well-known and well-used predictors and identified their biases and dataset dependencies, using not only SKEMPI 2.0 as a test set but also deep mutagenesis data on the severe acute respiratory syndrome coronavirus 2 spike protein in complex with the human angiotensin-converting enzyme 2. We showed that, even though most of the tested methods reach a significant degree of robustness and accuracy, they suffer from limited generalizability properties and struggle to predict unseen mutations. Interestingly, the generalizability problems are more severe for pure machine learning approaches, while physics-based methods are less affected by this issue. Moreover, undesirable prediction biases toward specific mutation properties, the most marked being toward destabilizing mutations, are also observed and should be carefully considered by method developers. We conclude from our analyses that there is room for improvement in the prediction models and suggest ways to check, assess and improve their generalizability and robustness.

Accurate Characterization of Conformational Ensembles and Binding Mechanisms of the SARS-CoV-2 Omicron BA.2 and BA.2.86 Spike Protein with the Host Receptor and Distinct Classes of Antibodies Using AlphaFold2-Augmented Integrative Computational Modeling

The latest wave SARS-CoV-2 Omicron variants displayed a growth advantage and the increased viral fitness through convergent evolution of functional hotspots that work synchronously to balance fitness requirements for productive receptor binding and efficient immune evasion. In this study, we combined AlphaFold2-based structural modeling approaches with all-atom MD simulations and mutational profiling of binding energetics and stability for prediction and comprehensive analysis of the structure, dynamics, and binding of the SARS-CoV-2 Omicron BA.2.86 spike variant with ACE2 host receptor and distinct classes of antibodies. We adapted several AlphaFold2 approaches to predict both structure and conformational ensembles of the Omicron BA.2.86 spike protein in the complex with the host receptor. The results showed that AlphaFold2-predicted conformational ensemble of the BA.2.86 spike protein complex can accurately capture the main dynamics signatures obtained from microscond molecular dynamics simulations. The ensemble-based dynamic mutational scanning of the receptor binding domain residues in the BA.2 and BA.2.86 spike complexes with ACE2 dissected the role of the BA.2 and BA.2.86 backgrounds in modulating binding free energy changes revealing a group of conserved hydrophobic hotspots and critical variant-specific contributions of the BA.2.86 mutational sites R403K, F486P and R493Q. To examine immune evasion properties of BA.2.86 in atomistic detail, we performed large scale structure-based mutational profiling of the S protein binding interfaces with distinct classes of antibodies that displayed significantly reduced neutralization against BA.2.86 variant. The results quantified specific function of the BA.2.86 mutations to ensure broad resistance against different classes of RBD antibodies. This study revealed the molecular basis of compensatory functional effects of the binding hotspots, showing that BA.2.86 lineage may have primarily evolved to improve immune escape while modulating binding affinity with ACE2 through cooperative effect of R403K, F486P and R493Q mutations. The study supports a hypothesis that the impact of the increased ACE2 binding affinity on viral fitness is more universal and is mediated through cross-talk between convergent mutational hotspots, while the effect of immune evasion could be more variant-dependent.

Deep mutational scanning of proteins in mammalian cells

Protein mutagenesis is essential for unveiling the molecular mechanisms underlying protein function in health, disease, and evolution. In the past decade, deep mutational scanning methods have evolved to support the functional analysis of nearly all possible single-amino acid changes in a protein of interest. While historically these methods were developed in lower organisms such as E. coli and yeast, recent technological advancements have resulted in the increased use of mammalian cells, particularly for studying proteins involved in human disease. These advancements will aid significantly in the classification and interpretation of variants of unknown significance, which are being discovered at large scale due to the current surge in the use of whole-genome sequencing in clinical contexts. Here, we explore the experimental aspects of deep mutational scanning studies in mammalian cells and report the different methods used in each step of the workflow, ultimately providing a useful guide toward the design of such studies.

Structural insights into ACE2 interactions and immune activation of SARS-CoV-2 and its variants: an in-silico study

The initial interaction between COVID-19 and the human body involves the receptor-binding domain (RBD) of the viral spike protein with the angiotensin-converting enzyme 2 (ACE2) receptor. Likewise, the spike protein can engage with immune-related proteins, such as toll-like receptors (TLRs) and pulmonary surfactant proteins A (SP-A) and D (SP-D), thereby triggering immune responses. In this study, we utilize computational methods to investigate the interactions between the spike protein and TLRs (specifically TLR2 and TLR4), as well as (SP-A) and (SP-D). The study is conducted on four variants of concern (VOC) to differentiate and identify common virus behaviours. An assessment of the structural stability of various variants indicates slight changes attributed to mutations, yet overall structural integrity remains preserved. Our findings reveal the spike protein's ability to bind with TLR4 and TLR2, prompting immune activation. In addition, our in-silico results reveal almost similar docking scores and therefore affinity for both ACE2-spike and TLR4-spike complexes. We demonstrate that even minor changes due to mutations in all variants, surfactant A and D proteins can function as inhibitors against the spike in all variants, hindering the ACE2-RBD interaction.Communicated by Ramaswamy H. Sarma.

Integrated multiplexed assays of variant effect reveal cis-regulatory determinants of catechol-O-methyltransferase gene expression

Multiplexed assays of variant effect are powerful methods to profile the consequences of rare variants on gene expression and organismal fitness. Yet, few studies have integrated several multiplexed assays to map variant effects on gene expression in coding sequences. Here, we pioneered a multiplexed assay based on polysome profiling to measure variant effects on translation at scale, uncovering single-nucleotide variants that increase and decrease ribosome load. By combining high-throughput ribosome load data with multiplexed mRNA and protein abundance readouts, we mapped the cis-regulatory landscape of thousands of catechol-O-methyltransferase (COMT) variants from RNA to protein and found numerous coding variants that alter COMT expression. Finally, we trained machine learning models to map signatures of variant effects on COMT gene expression and uncovered both directional and divergent impacts across expression layers. Our analyses reveal expression phenotypes for thousands of variants in COMT and highlight variant effects on both single and multiple layers of expression. Our findings prompt future studies that integrate several multiplexed assays for the readout of gene expression.

Assessing the Potential Role of Cats (Felis catus) as Generators of Relevant SARS-CoV-2 Lineages during the Pandemic

Several questions regarding the evolution of SARS-CoV-2 remain poorly elucidated. One of these questions is the possible evolutionary impact of SARS-CoV-2 after the infection in domestic animals. In this study, we aimed to evaluate the potential role of cats as generators of relevant SARS-CoV-2 lineages during the pandemic. A total of 105 full-length genome viral sequences obtained from naturally infected cats during the pandemic were evaluated by distinct evolutionary algorithms. Analyses were enhanced, including a set of highly related SARS-CoV-2 sequences recovered from human populations. Our results showed the apparent high susceptibility of cats to the infection SARS-CoV-2 compared with other animal species. Evolutionary analyses indicated that the phylogenomic characteristics displayed by cat populations were influenced by the dominance of specific SARS-CoV-2 genetic groups affecting human populations. However, disparate dN/dS rates at some genes between populations recovered from cats and humans suggested that infection in these two species may suggest a different evolutionary constraint for SARS-CoV-2. Interestingly, the branch selection analysis showed evidence of the potential role of natural selection in the emergence of five distinct cat lineages during the pandemic. Although these lineages were apparently irrelevant to public health during the pandemic, our results suggested that additional studies are needed to understand the role of other animal species in the evolution of SARS-CoV-2 during the pandemic.

Characterization of intrinsic and effective fitness changes caused by temporarily fixed mutations in the SARS-CoV-2 spike E484 epitope and identification of an epistatic precondition for the evolution of E484A in variant Omicron

BACKGROUND

Intrinsic fitness costs are likely to have guided the selection of lineage-determining mutations during emergence of variants of SARS-CoV-2. Whereas changes in receptor affinity and antibody neutralization have been thoroughly mapped for individual mutations in spike, their influence on intrinsic replicative fitness remains understudied.

METHODS

We analyzed mutations in immunodominant spike epitope E484 that became temporarily fixed over the pandemic. We engineered the resulting immune escape mutations E484K, -A, and -Q in recombinant SARS-CoV-2. We characterized viral replication, entry, and competitive fitness with and without immune serum from humans with defined exposure/vaccination history and hamsters monospecifically infected with the E484K variant. We additionally engineered a virus containing the Omicron signature mutations N501Y and Q498R that were predicted to epistatically enhance receptor binding.

RESULTS

Multistep growth kinetics in Vero-, Calu-3, and NCI-H1299 were identical between viruses. Synchronized entry experiments based on cold absorption and temperature shift identified only an insignificant trend toward faster entry of the E484K variant. Competitive passage experiments revealed clear replicative fitness differences. In absence of immune serum, E484A and E484Q, but not E484K, were replaced by wildtype (WT) in competition assays. In presence of immune serum, all three mutants outcompeted WT. Decreased E484A fitness levels were over-compensated for by N501Y and Q498R, identifying a putative Omicron founder background that exceeds the intrinsic and effective fitness of WT and matches that of E484K. Critically, the E484A/Q498R/N501Y mutant and E484K have equal fitness also in presence of pre-Omicron vaccinee serum, whereas the fitness gain by E484K is lost in the presence of serum raised against the E484K variant in hamsters.

CONCLUSIONS

The emergence of E484A and E484Q prior to widespread population immunity may have been limited by fitness costs. In populations already exposed to the early immune escape epitope E484K, the Omicron founder background may have provided a basis for alternative immune escape evolution via E484A. Studies of major antigenic epitope changes with and without their epistatic context help reconstruct the sequential adjustments of intrinsic fitness versus neutralization escape during the evolution of major SARS-CoV-2 variants in an increasingly immune human population.

Epistasis and pleiotropy shape biophysical protein subspaces associated with drug resistance

Protein space is a rich analogy for genotype-phenotype maps, where amino acid sequence is organized into a high-dimensional space that highlights the connectivity between protein variants. It is a useful abstraction for understanding the process of evolution, and for efforts to engineer proteins towards desirable phenotypes. Few mentions of protein space consider how protein phenotypes can be described in terms of their biophysical components, nor do they rigorously interrogate how forces like epistasis-describing the nonlinear interaction between mutations and their phenotypic consequences-manifest across these components. In this study, we deconstruct a low-dimensional protein space of a bacterial enzyme (dihydrofolate reductase; DHFR) into "subspaces" corresponding to a set of kinetic and thermodynamic traits [k_{cat}, K_{M}, K_{i}, and T_{m} (melting temperature)]. We then examine how combinations of three mutations (eight alleles in total) display pleiotropy, or unique effects on individual subspace traits. We examine protein spaces across three orthologous DHFR enzymes (Escherichia coli, Listeria grayi, and Chlamydia muridarum), adding a genotypic context dimension through which epistasis occurs across subspaces. In doing so, we reveal that protein space is a deceptively complex notion, and that future applications to bioengineering should consider how interactions between amino acid substitutions manifest across different phenotypic subspaces.

SARS-CoV-2 evolution in the Omicron era

Since SARS-CoV-2 BA.5 (Omicron) emerged and spread in 2022, Omicron lineages have markedly diversified. Here we review the evolutionary trajectories and processes that underpin the emergence of these lineages, and identify the most prevalent sublineages. We discuss the potential origins of second-generation BA.2 lineages. Simple and complex recombination, antigenic drift and convergent evolution have enabled SARS-CoV-2 to accumulate mutations that alter its antigenicity. We also discuss the potential evolutionary trajectories of SARS-CoV-2 in the future.

Identifying promising sequences for protein engineering using a deep transformer protein language model

Protein engineers aim to discover and design novel sequences with targeted, desirable properties. Given the near limitless size of the protein sequence landscape, it is no surprise that these desirable sequences are often a relative rarity. This makes identifying such sequences a costly and time-consuming endeavor. In this work, we show how to use a deep transformer protein language model to identify sequences that have the most promise. Specifically, we use the model's self-attention map to calculate a Promise Score that weights the relative importance of a given sequence according to predicted interactions with a specified binding partner. This Promise Score can then be used to identify strong binders worthy of further study and experimentation. We use the Promise Score within two protein engineering contexts-Nanobody (Nb) discovery and protein optimization. With Nb discovery, we show how the Promise Score provides an effective way to select lead sequences from Nb repertoires. With protein optimization, we show how to use the Promise Score to select site-specific mutagenesis experiments that identify a high percentage of improved sequences. In both cases, we also show how the self-attention map used to calculate the Promise Score can indicate which regions of a protein are involved in intermolecular interactions that drive the targeted property. Finally, we describe how to fine-tune the transformer protein language model to learn a predictive model for the targeted property, and discuss the capabilities and limitations of fine-tuning with and without knowledge transfer within the context of protein engineering.

Chronicling the 3-year evolution of the COVID-19 pandemic: analysis of disease management, characteristics of major variants, and impacts on pathogenicity

Announced on December 31, 2019, the novel coronavirus arising in Wuhan City, Hubei Province resulted in millions of cases and lives lost. Following intense tracking, coronavirus disease 2019 (COVID-19) was declared a pandemic by the World Health Organization (WHO) in 2020. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was identified as the cause of COVID-19 and the continuous evolution of the virus has given rise to several variants. In this review, a comprehensive analysis of the response to the pandemic over the first three-year period is provided, focusing on disease management, development of vaccines and therapeutics, and identification of variants. The transmissibility and pathogenicity of SARS-CoV-2 variants including Alpha, Beta, Gamma, Delta, and Omicron are compared. The binding characteristics of the SARS-CoV-2 spike protein to the angiotensin-converting enzyme 2 (ACE2) receptor and reproduction numbers are evaluated. The effects of major variants on disease severity, hospitalisation, and case-fatality rates are outlined. In addition to the spike protein, open reading frames mutations are investigated. We also compare the pathogenicity of SARS-CoV-2 with SARS-CoV and Middle East respiratory syndrome coronavirus (MERS-CoV). Overall, this study highlights the strengths and weaknesses of the global response to the pandemic, as well as the importance of prevention and preparedness. Monitoring the evolution of SARS-CoV-2 is critical in identifying and potentially predicting the health outcomes of concerning variants as they emerge. The ultimate goal would be a position in which existing vaccines and therapeutics could be adapted to suit new variants in as close to real-time as possible.

Differential platelet activation through an interaction with spike proteins of different SARS-CoV-2 variants

COVID-19 disease is associated with an increased risk of thrombotic complications, which contribute to high short-term mortality. Patients with COVID-19 demonstrate enhanced platelet turnover and reactivity, which may have a role in the development of thrombotic events and disease severity. Evidence has suggested direct interaction between SARS-CoV-2 and platelets, resulting in platelets activation. Here, we compare the effect of various SARS-CoV-2 spike variants on platelet activation. Engineered lentiviral particles were pseudotyped with spike SARS-CoV-2 variants and incubated with Platelet Rich Plasma obtained from healthy individuals. The pseudotyped SARS-CoV-2 exhibiting the wild-type Wuhan-Hu spike protein stimulated platelets to increase expression of the surface CD62P and activated αIIbβ3 markers by 3.5 ± 1.2 and 3.3 ± 0.7 fold, respectively (P = 0.004 and 0.003). The Delta variant induced much higher levels of platelet activation; CD62P expression was increased by 6.6 ± 2.2 fold and activated αIIbβ3 expression was increased by 5.0 ± 1.5 fold (P = 0.005 and 0.026, respectively). The Omicron BA.1 and the Alpha variants induced the lowest level of activation; CD62P expression was increased by 1.7 ± 0.4 and 1.6 ± 0.9 fold, respectively (P = 0.003 and 0.008), and activated αIIbβ3 expression by 1.8 ± 1.1 and 1.6 ± 0.8, respectively (P = 0.003 and 0.001). The Omicron BA.2 variant induced an increase of platelets activation comparable to the Wuhan-Hu (2.8 ± 1.2 and 2.1 ± 1.3 fold for CD62P and activated αIIbβ3 markers, respectively). The results obtained for various COVID-19 variants are in correlation with the clinical severity and mortality reported for these variants.

Antibody evasion associated with the RBD significant mutations in several emerging SARS-CoV-2 variants and its subvariants

Since the origin of the wild strain of SARS-CoV-2, several variants have emerged, which were designated as VOC, VOI, and VUM from time to time. The Omicron variant is noted as the recent VOC. After the origin of the Omicron variant on November 2021, several subvariants of Omicron have originated subsequently, like BA.1/2, BA.2.75/2.75.2, BA.4/5, BF.7, BQ.1/1.1, XBB.1/1.5, etc. which are circulated throughout the globe. Scientists reported that antibody escape is a common phenomenon observed in all the previous VOCs, VOIs, including Omicron and its subvariants. The mutations in the NTD (N-terminal domain) and RBD (Receptor-binding domain) of the spike of these variants and subvariants are responsible for antibody escape. At the same time, it has been noted that spike RBD mutations have been increasing in the last few months. This review illustrates significant RBD mutations namely R346T, K417N/T, L452R, N460K E484A/K/Q, and N501Y found in the previous emerging SARS-CoV-2 variants, including Omicron and its subvariants in high frequency and their role in antibody evasion and immune evasion. The review also describes the different classes of nAb responsible for antibody escape in SARS-CoV-2 variants and the molecular perspective of the mutation in nAb escape. It will help the future researchers to develop efficient vaccines which can finally prevent the pandemic.

dms-viz: Structure-informed visualizations for deep mutational scanning and other mutation-based datasets

Understanding how mutations impact a protein's functions is valuable for many types of biological questions. High-throughput techniques such as deep-mutational scanning (DMS) have greatly expanded the number of mutation-function datasets. For instance, DMS has been used to determine how mutations to viral proteins affect antibody escape (Dadonaite et al. 2023), receptor affinity (Starr et al. 2020), and essential functions such as viral genome transcription and replication (Li et al. 2023). With the growth of sequence databases, in some cases the effects of mutations can also be inferred from phylogenies of natural sequences (Bloom and Neher 2023) (Figure 1). The mutation-based data generated by these approaches is often best understood in the context of a protein's 3D structure; for instance, to assess questions like how mutations that affect antibody escape relate to the physical antibody binding epitope on the protein. However, current approaches for visualizing mutation data in the context of a protein's structure are often cumbersome and require multiple steps and softwares. To streamline the visualization of mutation-associated data in the context of a protein structure, we developed a web-based tool, dms-viz. With dms-viz, users can straightforwardly visualize mutation-based data such as those from DMS experiments in the context of a 3D protein model in an interactive format. See https://dms-viz.github.io/ to use dms-viz.

Molecular insights and optimization strategies for the competitive binding of engineered ACE2 proteins: a multiple replica molecular dynamics study

The COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) continues to spread globally, and rapid viral evolution and the emergence of new variants pose challenges to pandemic control. During infection, the spike protein of SARS-CoV-2 interacts with the human ACE2 protein via its receptor binding domain (RBD), and it is known that engineered forms of ACE2 can compete with wild-type (WT) ACE2 for binding to inhibit infection. Here, we conducted multiple replica molecular dynamics (MRMD) simulations to study the mechanisms of the engineered ACE2 variants 3N39 and 3N94 and provide directions for optimization. Our findings reveal that engineered ACE2 is notably more efficacious in systems that show weaker binding to WT ACE2 (i.e., WT and BA.1 RBD), but also faces immune escape as the virus evolves. Moreover, by modifying residue types near the binding interface, engineered ACE2 alters the electrostatic potential distribution and reconfigures the hydrogen bonding network, which results in modified binding to the RBD. However, this structural rearrangement does not occur in all RBD variants. In addition, we identified potentially engineerable beneficial residues and potentially engineerable detrimental residues in both ACE2 and RBD. Functional conservation can thus enable the optimization of these residues and improve the binding competitiveness of engineered ACE2, which therefore provides additional immune escape prevention. Finally, we conclude that these findings have implications for understanding the mechanisms responsible for engineered ACE2 and can help us to develop engineered ACE2 proteins that show superior performance.

SARS-CoV-2 BA.2.86 ("Pirola"): Is it Pi or Just Another Omicron Sublineage?

The SARS-CoV-2 sublineage BA [...].