Shifting mutational constraints in the SARS-CoV-2 receptor-binding domain during viral evolution

Cross-reactive sarbecovirus antibodies induced by mosaic RBD nanoparticles

Broad immune responses are needed to mitigate viral evolution and escape. To induce antibodies against conserved receptor-binding domain (RBD) regions of SARS-like betacoronavirus (sarbecovirus) spike proteins that recognize SARS-CoV-2 variants of concern and zoonotic sarbecoviruses, we developed mosaic-8b RBD nanoparticles presenting eight sarbecovirus RBDs arranged randomly on a 60-mer nanoparticle. Mosaic-8b immunizations protected animals from challenges from viruses whose RBDs were matched or mismatched to those on nanoparticles. Here, we describe neutralizing mAbs isolated from mosaic-8b-immunized rabbits, some on par with Pemgarda, the only currently FDA-approved therapeutic mAb. Deep mutational scanning, in vitro selection of spike resistance mutations, and single-particle cryo-electron microscopy structures of spike-antibody complexes demonstrated targeting of conserved RBD epitopes. Rabbit mAbs included critical D-gene segment RBD-recognizing features in common with human anti-RBD mAbs, despite rabbit genomes lacking an equivalent human D-gene segment, thus demonstrating that the immune systems of humans and other mammals can utilize different antibody gene segments to arrive at similar modes of antigen recognition. These results suggest that animal models can be used to elicit anti-RBD mAbs with similar properties to those raised in humans, which can then be humanized for therapeutic use, and that mosaic RBD nanoparticle immunization coupled with multiplexed screening represents an efficient way to generate and select broadly cross-reactive therapeutic pan-sarbecovirus and pan-SARS-CoV-2 variant mAbs.

Deep mutational scanning and CRISPR-engineered viruses: tools for evolutionary and functional genomics studies

Recent advancements in synthetic biology and sequencing technologies have revolutionized the ability to manipulate viral genomes with unparalleled precision. This review focuses on two powerful methodologies: deep mutational scanning and CRISPR-based genome editing, that enable comprehensive mutagenesis and detailed functional characterization of viral proteins. These approaches have significantly deepened our understanding of the molecular determinants driving viral evolution and adaptation. Furthermore, we discuss how these advances provide transformative insights for future vaccine development and therapeutic strategies.

Deep mutational scanning of rabies glycoprotein defines mutational constraint and antibody-escape mutations

Rabies virus causes nearly 60,000 human deaths annually. Antibodies that target the rabies glycoprotein (G) are being developed as post-exposure prophylactics, but mutations in G can render such antibodies ineffective. Here, we use pseudovirus deep mutational scanning to measure how all single-amino-acid mutations to G affect cell entry and neutralization by a panel of antibodies. These measurements identify sites critical for G function and define constrained regions that are attractive epitopes for clinical antibodies, including at the apex and base of the protein. We provide complete maps of escape mutations for eight monoclonal antibodies, including some in clinical use or development. Escape mutations for most antibodies are present in some natural rabies strains. Overall, this work provides comprehensive information on the functional and antigenic effects of G mutations that can inform development of stabilized vaccine antigens and antibodies that are resilient to rabies genetic variation.

SARS-CoV-2 spike protein: structure, viral entry and variants

Coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been a devastating global pandemic for 4 years and is now an endemic disease. With the emergence of new viral variants, COVID-19 is a continuing threat to public health despite the wide availability of vaccines. The virus-encoded trimeric spike protein (S protein) mediates SARS-CoV-2 entry into host cells and also induces strong immune responses, making it an important target for development of therapeutics and vaccines. In this Review, we summarize our latest understanding of the structure and function of the SARS-CoV-2 S protein, the molecular mechanism of viral entry and the emergence of new variants, and we discuss their implications for development of S protein-related intervention strategies.

Functional and antigenic landscape of the Nipah virus receptor-binding protein

Nipah virus recurrently spills over to humans, causing fatal infections. The viral receptor-binding protein (RBP or G) attaches to host receptors and is a major target of neutralizing antibodies. Here, we use deep mutational scanning to measure how all amino-acid mutations to the RBP affect cell entry, receptor binding, and escape from neutralizing antibodies. We identify functionally constrained regions of the RBP, including sites involved in oligomerization, along with mutations that differentially modulate RBP binding to its two ephrin receptors. We map escape mutations for six anti-RBP antibodies and find that few antigenic mutations are present in natural Nipah strains. Our findings offer insights into the potential for functional and antigenic evolution of the RBP that can inform the development of antibody therapies and vaccines.

Conserved sites on the influenza H1 and H3 hemagglutinin recognized by human antibodies

Monoclonal antibodies (mAbs) targeting the influenza hemagglutinin (HA) can be used as prophylactics or templates for next-generation vaccines. Here, we isolated broad, subtype-neutralizing mAbs from human B cells recognizing the H1 or H3 HA "head" and a mAb engaging the conserved stem. The H1 mAbs bind the lateral patch epitope on HAs from 1933 to 2021 and a prepandemic swine H1N1 virus. We improved neutralization potency using directed evolution toward a contemporary H1 HA. Deep mutational scanning of four antigenically distinct H1N1 viruses identified potential viral escape pathways. For the H3 mAbs, we used cryo-electron microscopy to define their epitopes: One mAb binds the side of the HA head, accommodating the N133 glycan and a pocket underneath the receptor binding site; the other mAb recognizes an HA stem epitope that partially overlaps with previously characterized mAbs but with distinct antibody variable genes. Collectively, these mAbs identify conserved sites recognized by broadly-reactive mAbs that may be elicited by next-generation vaccines.

Structural and Energetic Insights into SARS-CoV-2 Evolution: Analysis of hACE2-RBD Binding in Wild-Type, Delta, and Omicron Subvariants

The evolution of SARS-CoV-2, particularly the emergence of Omicron variants, has raised questions regarding changes in its binding affinity to the human angiotensin-converting enzyme 2 receptor (hACE2). Understanding the impact of mutations on the interaction between the receptor-binding domain (RBD) of the spike protein and hACE2 is critical for evaluating viral transmissibility, immune evasion, and the efficacy of therapeutic strategies. Here, we used molecular dynamics (MD) simulations and binding energy calculations to investigate the structural and energetic differences between the hACE2- RBD complexes of wild-type (WT), Delta, and Omicron subvariants. Our results indicate that the Delta and the first Omicron variants showed the highest and the second-highest binding energy among the variants studied. Furthermore, while Omicron variants exhibit increased structural stability and altered electrostatic potential at the hACE2-RBD interface when compared to the ancestral WT, their binding strength to hACE2 does not consistently increase with viral evolution. Moreover, newer Omicron subvariants like JN.1 exhibit a bimodal conformational strategy, alternating between a high-affinity state for hACE2 and a low-affinity state, which could potentially facilitate immune evasion. These findings suggest that, in addition to enhanced hACE2 binding affinity, other factors, such as immune evasion and structural adaptability, shape SARS-CoV-2 evolution.

Deep mutationally scanned CHIKV E3/E2 virus library maps viral amino acid preferences and predicts viral escape mutants of neutralizing CHIKV antibodies

As outbreaks of chikungunya virus (CHIKV), a mosquito-borne alphavirus, continue to present public health challenges, additional research is needed to generate protective and safe vaccines and effective therapeutics. Prior research established a role for antibodies in mediating protection against CHIKV infection, and the early appearance of CHIKV-specific IgG or IgG neutralizing antibodies protects against progression to chronic CHIKV disease in humans. However, the importance of epitope specificity for these protective antibodies and how skewed responses contribute to the development of acute and chronic CHIKV-associated joint disease remains poorly understood. Here, we describe the deep mutational scanning of one of the dominant targets of neutralizing antibodies during CHIKV infection, the E3/E2 (also known as p62) glycoprotein complex, to simultaneously test thousands of p62 mutants against selective pressures of interest in a high throughput manner. Characterization of the virus library revealed achievement of high diversity while also selecting out nonfunctional virus variants. Furthermore, this study provides evidence that this virus library system can comprehensively map sites critical for the neutralization function of antibodies of both known and unknown p62 domain specificities.IMPORTANCEChikungunya virus (CHIKV) is a mosquito-borne alphavirus of global health concern that causes debilitating acute and chronic joint disease. Prior studies established a critical role for antibodies in protection against CHIKV infection. Here, we describe the generation of a high-throughput, functional virus library capable of identifying critical functional sites for anti-viral antibodies. This new tool can be used to better understand antibody responses associated with distinct CHIKV infection outcomes and could contribute to the development of efficacious vaccines and antibody-based therapeutics.

SFM-Net: Selective Fusion of Multiway Protein Feature Network for Predicting Binding Affinity Changes upon Mutations

Accurately predicting the effect of mutations on protein-protein interactions (PPIs) is essential for understanding the protein structure and function, as well as providing insights into disease-causing mechanisms. Many recent popular approaches based on the three-dimensional structure of proteins have been proposed to predict the changes in binding affinity caused by mutations, i.e. ΔΔG. However, how to effectively use the structural information to comprehensively exploit complex interactions within proteins and integrate multisource features remains a significant challenge. In this study, we propose SFM-Net, a powerful deep learning model constructed with GNN-based multiway feature extractors and a new context-aware selective fusion module that jointly leverages the sequence, structural, and evolutionary information. Such design enables SFM-Net to effectively and selectively use features from different sources to facilitate binding affinity change prediction. Benchmarking experiments and targeted ablation studies illustrate the effectiveness and robustness of our method for improving the binding affinity change prediction.

Increased preference for lysine over arginine in spike proteins of SARS-CoV-2 BA.2.86 variant and its daughter lineages

The COVID-19 pandemic offered an unprecedented glimpse into the evolution of its causative virus, SARS-CoV-2. It has been estimated that since its outbreak in late 2019, the virus has explored all possible alternatives in terms of missense mutations for all sites of its polypeptide chain. Spike protein of the virus exhibits the largest sequence variation in particular, with many individual mutations impacting target recognition, cellular entry, and endosomal escape of the virus. Moreover, recent studies unveiled a significant increase in the total charge on the spike protein during the evolution of the virus in the initial period of the pandemic. While this trend has recently come to a halt, we perform a sequence-based analysis of the spike protein of 2665 SARS-CoV-2 variants which shows that mutations in ionizable amino acids continue to occur with the newly emerging variants, with notable differences between lineages from different clades. What is more, we show that within mutations of amino acids which can acquire positive charge, the spike protein of SARS-CoV-2 exhibits a prominent preference for lysine residues over arginine residues. This lysine-to-arginine ratio increased at several points during spike protein evolution, most recently with BA.2.86 and its sublineages, including the recently dominant JN.1, KP.3, and XEC variants. The increased ratio is a consequence of mutations in different structural regions of the spike protein and is now among the highest among viral species in the Coronaviridae family. The impact of high lysine-to-arginine ratio in the spike proteins of BA.2.86 and its daughter lineages on viral fitness remains unclear; we discuss several potential mechanisms that could play a role and that can serve as a starting point for further studies.

Molecular basis of convergent evolution of ACE2 receptor utilization among HKU5 coronaviruses

DPP4 was considered a canonical receptor for merbecoviruses until the recent discovery of African bat-borne MERS-related coronaviruses using ACE2. The extent and diversity of ACE2 utilization among merbecoviruses and their receptor species tropism remain unknown. Here, we reveal that HKU5 enters host cells utilizing Pipistrellus abramus (P.abr) and several non-bat mammalian ACE2s through a binding mode distinct from that of any other known ACE2-using coronaviruses. We defined the molecular determinants of receptor species tropism and identified a single amino acid mutation enabling HKU5 to utilize human ACE2, providing proof of principle for machine-learning-assisted outbreak preparedness. We show that MERS-CoV and HKU5 have markedly distinct antigenicity and identified several HKU5 inhibitors, including two clinical compounds. Our findings profoundly alter our understanding of coronavirus evolution, as several merbecovirus clades independently evolved ACE2 utilization, and pave the way for developing countermeasures against viruses poised for human emergence.

Antigenic drift expands influenza viral escape pathways from recalled humoral immunity

Initial exposure to a rapidly evolving virus establishes B cell memory that biases later responses to antigenically drifted strains. This "immune imprinting" implies that subsequent exposure to a drifted strain can induce affinity maturation of memory B cells toward cross-reactivity with the drifted strain and hence toward greater overall breadth. Here, we used deep mutational scanning of H1 influenza hemagglutinins (HAs) to investigate how viruses evolve in response to these broad antibody response. We identified escape mutations from clonal antibody lineages that targeted the receptor binding site and lateral patch. By adjusting the antigen-antibody contacts, antibody affinity maturation restricted the potential escape routes for the eliciting strain. However, escape occurred readily in drifted strains. We attribute this escape-prone property of the drifted strains to epistatic networks within HA. Our data explain how the influenza virus continues to evolve in the human population by escaping even broad antibody responses.

SARS-CoV-2 Fusion Peptide-Directed Antibodies Elicited by Natural Infection Mediate Broad Sarbecovirus Neutralization

Studies have demonstrated that repeated mRNA vaccination enhances the breadth of neutralization against diverse SARS-CoV-2 variants. However, the development of antibodies capable of neutralizing across the Coronavirinae subfamily is poorly understood. In this study, we analyze serum samples to determine their neutralization breadth and potency and identify their antigenic targets. Using a cohort of older individuals and healthcare workers, we track correlates of broad neutralizing responses, including fusion peptide (FP) antibody elicitation. We find that although broadly neutralizing responses are often a result of RBD-specific antibodies, a rare subset of donors produce FP-specific broadly neutralizing responses. Interestingly, FP-specific antibodies are not observed in COVID-naive individuals irrespective of vaccination regimen, but rather, they occur following natural infection or vaccine breakthrough. This study highlights the epitope targets underpinning broadly neutralizing antibody responses to coronaviruses and suggests that existing vaccines are insufficient to promote the elicitation of FP-directed broadly neutralizing coronavirus antibodies.

The Compensatory Effect of S375F on S371F Is Vital for Maintaining the Infectivity of SARS-CoV-2 Omicron Variants

The emergence of Omicron variants dramatically changed the transmission rate and infection characteristics compared to previously prevalent strains, primarily due to spike protein mutations. However, the impact of individual mutations remained unclear. Here, we used virus-like particle (VLP) pseudotyped to investigate the functional contributions by 12 common mutations in the spike protein. We found that the S371F mutation in the receptor binding domain (RBD) of spike protein led to a 5- and 10-fold decrease of ACE2 utilization efficiency and viral infectivity, respectively, accompanied by a 5- to 11-fold reduction of neutralization sensitivity to monoclonal antibodies. However, the S375F mutation in the RBD had a compensatory effect, rescuing the infectivity of the S371F Omicron variant. Based on molecular dynamics simulations, we proposed a "tug of war" model to explain this compensation phenomenon. These results provide a comprehensive and dynamic perspective on the evolution of this important pandemic virus.

Widespread epistasis shapes RNA Polymerase II active site function and evolution

Multi-subunit RNA Polymerases (msRNAPs) are responsible for transcription in all kingdoms of life. These enzymes rely on dynamic, highly conserved active site domains such as the so-called "trigger loop" (TL) to accomplish steps in the transcription cycle. Mutations in the RNA polymerase II (Pol II) TL confer a spectrum of biochemical and genetic phenotypes that suggest two main classes, which decrease or increase catalysis or other nucleotide addition cycle (NAC) events. The Pol II active site relies on networks of residue interactions to function and mutations likely perturb these networks in ways that may alter mechanisms. We have undertaken a structural genetics approach to reveal residue interactions within and surrounding the Pol II TL - determining its "interaction landscape" - by deep mutational scanning in Saccharomyces cerevisiae Pol II. This analysis reveals connections between TL residues and surrounding domains, demonstrating that TL function is tightly coupled to its specific enzyme context.

Evolutionary rewiring of the dynamic network underpinning allosteric epistasis in NS1 of the influenza A virus

Viral proteins frequently mutate to evade host innate immune responses, yet the impact of these mutations on the molecular energy landscape remains unclear. Epistasis, the intramolecular communications between mutations, often renders the combined mutational effects unpredictable. Nonstructural protein 1 (NS1) is a major virulence factor of the influenza A virus (IAV) that activates host PI3K by binding to its p85β subunit. Here, we present a deep analysis of the impact of evolutionary mutations in NS1 that emerged between the 1918 pandemic IAV strain and its descendant PR8 strain. Our analysis reveals how the mutations rewired interresidue communications, which underlie long-range allosteric and epistatic networks in NS1. Our findings show that PR8 NS1 binds to p85β with approximately 10-fold greater affinity than 1918 NS1 due to allosteric mutational effects, which are further tuned by epistasis. NMR chemical shift perturbation and methyl-axis order parameter analyses revealed that the mutations induced long-range structural and dynamic changes in PR8 NS1, relative to 1918 NS1, enhancing its affinity to p85β. Complementary molecular dynamics simulations and graph theory-based network analysis for conformational dynamics on the submicrosecond timescales uncover how these mutations rewire the dynamic network, which underlies the allosteric epistasis. Significantly, we find that conformational dynamics of residues with high betweenness centrality play a crucial role in communications between network communities and are highly conserved across influenza A virus evolution. These findings advance our mechanistic understanding of the allosteric and epistatic communications between distant residues and provide insight into their role in the molecular evolution of NS1.

Cryptic genetic variation shapes the fate of gene duplicates in a protein interaction network

Paralogous genes are often functionally redundant for long periods of time. While their functions are preserved, paralogs accumulate cryptic changes in sequence and expression, which could modulate the impact of future mutations through epistasis. We examine the impact of mutations on redundant myosin proteins that have maintained the same binding preference despite having accumulated differences in expression levels and amino acid substitutions in the last 100 million years. By quantifying the impact of all single-amino acid substitutions in their SH3 domains on the physical interaction with their interaction partners, we show that the same mutations in the paralogous SH3s change binding in a paralog-specific and interaction partner-specific manner. This contingency is explained by the difference in promoter strength of the two paralogous myosin genes and epistatic interactions between the mutations introduced and cryptic divergent sites within the SH3s. One significant consequence of this contingency is that while some mutations would be sufficient to nonfunctionalize one paralog, they would have minimal impact on the other. Our results reveal how cryptic divergence, which accumulates while maintaining functional redundancy in cellular networks, could bias gene duplicates to specific fates.

Protein data bank: From two epidemics to the global pandemic to mRNA vaccines and Paxlovid

Structural biologists and the open-access Protein Data Bank (PDB) played decisive roles in combating the COVID-19 pandemic. Global biostructure data were turned into global knowledge, allowing scientists and engineers to understand the inner workings of coronaviruses and develop effective countermeasures. Two mRNA vaccines, initially designed with guidance from PDB structures of the SARS-CoV-1 and MERS-CoV spike proteins, prevented infections entirely or reduced the likelihood of morbidity and mortality for more than five billion individual recipients worldwide. Structure-guided drug discovery by Pfizer, Inc (facilitated by PDB structures), initiated in the 2000s in response to SARS-CoV-1 and resumed in 2020, yielded nirmatrelvir (the active ingredient of Paxlovid) -- a potent, orally-bioavailable inhibitor of the SARS-CoV-2 main protease. You've got to love the Protein Data Bank!

Paying attention to the SARS-CoV-2 dialect : a deep neural network approach to predicting novel protein mutations

Predicting novel mutations has long-lasting impacts on life science research. Traditionally, this problem is addressed through wet-lab experiments, which are often expensive and time consuming. The recent advancement in neural language models has provided stunning results in modeling and deciphering sequences. In this paper, we propose a Deep Novel Mutation Search (DNMS) method, using deep neural networks, to model protein sequence for mutation prediction. We use SARS-CoV-2 spike protein as the target and use a protein language model to predict novel mutations. Different from existing research which is often limited to mutating the reference sequence for prediction, we propose a parent-child mutation prediction paradigm where a parent sequence is modeled for mutation prediction. Because mutations introduce changing context to the underlying sequence, DNMS models three aspects of the protein sequences: semantic changes, grammatical changes, and attention changes, each modeling protein sequence aspects from shifting of semantics, grammar coherence, and amino-acid interactions in latent space. A ranking approach is proposed to combine all three aspects to capture mutations demonstrating evolving traits, in accordance with real-world SARS-CoV-2 spike protein sequence evolution. DNMS can be adopted for an early warning variant detection system, creating public health awareness of future SARS-CoV-2 mutations.

High-throughput molecular simulations of SARS-CoV-2 receptor binding domain mutants quantify correlations between dynamic fluctuations and protein expression

Prediction of protein fitness from computational modeling is an area of active research in rational protein design. Here, we investigated whether protein fluctuations computed from molecular dynamics simulations can be used to predict the expression levels of SARS-CoV-2 receptor binding domain (RBD) mutants determined in the deep mutational scanning experiment of Starr et al. [Science (New York, N.Y.) 2022, 377, 420] Specifically, we performed more than 0.7 milliseconds of molecular dynamics (MD) simulations of 557 mutant RBDs in triplicate to achieve statistical significance under various simulation conditions. Our results show modest but significant anticorrelation in the range [-0.4, -0.3] between expression and RBD protein flexibility. A simple linear regression machine learning model achieved correlation coefficients in the range [0.7, 0.8], thus outperforming MD-based models, but required about 25 mutations at each residue position for training.

Cross-reactive sarbecovirus antibodies induced by mosaic RBD-nanoparticles

Therapeutic monoclonal antibodies (mAbs) against SARS-CoV-2 become obsolete as spike substitutions reduce antibody binding. To induce antibodies against conserved receptor-binding domain (RBD) regions for protection against SARS-CoV-2 variants of concern and zoonotic sarbecoviruses, we developed mosaic-8b RBD-nanoparticles presenting eight sarbecovirus RBDs arranged randomly on a 60-mer nanoparticle. Mosaic-8b immunizations protected animals from challenges from viruses whose RBDs were matched or mismatched to those on nanoparticles. Here, we describe neutralizing mAbs from mosaic-8b-immunized rabbits, some on par with Pemgarda (the only currently FDA-approved therapeutic mAb). Deep mutational scanning, in vitro selection of spike resistance mutations, and cryo-EM structures of spike-antibody complexes demonstrated targeting of conserved epitopes. Rabbit mAbs included critical D-gene segment features in common with human anti-RBD mAbs, despite rabbit genomes lacking an equivalent human D-gene segment. Thus, mosaic RBD-nanoparticle immunization coupled with multiplexed screening represent an efficient way to generate and select therapeutic pan-sarbecovirus and pan-SARS-2 variant mAbs.

Combining Oligo Pools and Golden Gate Cloning to Create Protein Variant Libraries or Guide RNA Libraries for CRISPR Applications

Oligo pools are array-synthesized, user-defined mixtures of single-stranded oligonucleotides that can be used as a source of synthetic DNA for library cloning. While currently offering the most affordable source of synthetic DNA, oligo pools also come with limitations such as a maximum synthesis length (approximately 350 bases), a higher error rate compared to alternative synthesis methods, and the presence of truncated molecules in the pool due to incomplete synthesis. Here, we provide users with a comprehensive protocol that details how oligo pools can be used in combination with Golden Gate cloning to create user-defined protein mutant libraries, as well as single-guide RNA libraries for CRISPR applications. Our methods are optimized to work within the Yeast Toolkit Golden Gate scheme, but are in principle compatible with any other Golden Gate-based modular cloning toolkit and extendable to other restriction enzyme-based cloning methods beyond Golden Gate. Our methods yield high-quality, affordable, in-house variant libraries.

Unveiling the ghost: machine learning's impact on the landscape of virology

The complexity and speed of evolution in viruses with RNA genomes makes predictive identification of variants with epidemic or pandemic potential challenging. In recent years, machine learning has become an increasingly capable technology for addressing this challenge, as advances in methods and computational power have dramatically improved the performance of models and led to their widespread adoption across industries and disciplines. Nascent applications of machine learning technology to virus research have now expanded, providing new tools for handling large-scale datasets and leading to a reshaping of existing workflows for phenotype prediction, phylogenetic analysis, drug discovery and more. This review explores how machine learning has been applied to and has impacted the study of viruses, before addressing the strengths and limitations of its techniques and finally highlighting the next steps that are needed for the technology to reach its full potential in this challenging and ever-relevant research area.

Structural Immunology of SARS-CoV-2

The SARS-CoV-2 spike (S) protein has undergone significant evolution, enhancing both receptor binding and immune evasion. In this review, we summarize ongoing efforts to develop antibodies targeting various epitopes of the S protein, focusing on their neutralization potency, breadth, and escape mechanisms. Antibodies targeting the receptor-binding site (RBS) typically exhibit high neutralizing potency but are frequently evaded by mutations in SARS-CoV-2 variants. In contrast, antibodies targeting conserved regions, such as the S2 stem helix and fusion peptide, exhibit broader reactivity but generally lower neutralization potency. However, several broadly neutralizing antibodies have demonstrated exceptional efficacy against emerging variants, including the latest omicron subvariants, underscoring the potential of targeting vulnerable sites such as RBS-A and RBS-D/CR3022. We also highlight public classes of antibodies targeting different sites on the S protein. The vulnerable sites targeted by public antibodies present opportunities for germline-targeting vaccine strategies. Overall, developing escape-resistant, potent antibodies and broadly effective vaccines remains crucial for combating future variants. This review emphasizes the importance of identifying key epitopes and utilizing antibody affinity maturation to inform future therapeutic and vaccine design.

Evolving antibody response to SARS-CoV-2 antigenic shift from XBB to JN.1

The continuous evolution of SARS-CoV-2, particularly the emergence of the BA.2.86/JN.1 lineage replacing XBB, necessitates re-evaluation of vaccine compositions1-3. Here, we provide a comprehensive analysis of the humoral immune response to XBB and JN.1 human exposure. We demonstrate the antigenic distinctiveness of XBB and JN.1 lineages in SARS-CoV-2-naive individuals and show that infection with JN.1 elicits superior plasma neutralization against its subvariants. We highlight the strong immune evasion and receptor-binding capability of KP.3, supporting its foreseeable prevalence. Extensive analysis of the B cell receptor repertoire, in which we isolate approximately 2,000 receptor-binding-domain-specific antibodies, with targeting epitopes characterized by deep mutational scanning, underscores the superiority of JN.1-elicited memory B cells4,5. Class 1 IGHV3-53/3-66-derived neutralizing antibodies (NAbs) are important contributors to the wild-type reactivity of NAbs against JN.1. However, KP.2 and KP.3 evade a substantial subset of these antibodies, even those induced by JN.1, supporting a need for booster updates. JN.1-induced Omicron-specific antibodies also demonstrate high potency across Omicron. Escape hotspots for these NAbs have already been mutated, resulting in a higher immune barrier to escape and indicating probable recovery of escaped NAbs. In addition, the prevalence of IGHV3-53/3-66-derived antibodies and their ability to compete with all Omicron-specific NAbs suggests that they have an inhibitory effect on the activation of Omicron-specific naive B cells, potentially explaining the heavy immune imprinting in mRNA-vaccinated individuals6-8. These findings delineate the evolving antibody response to the antigenic shift of Omicron from XBB to JN.1 and highlight the importance of developing the JN.1 lineage, especially KP.2- and KP.3-based vaccine boosters.

Isolation and Preliminary Characterization of a Novel scFv against SARS-CoV-2 : an Experimental and Computational Analysis

Background

Since the initial outbreak, the SARS-CoV-2 virus has continued to circulate and mutate, resulting in the emergence of new viral sublineages. Due to the lack of effective protection and therapeutic measures against these new variants, the virus is able to further evolve and diversify. This study aimed to screen a phage antibody library to identify monoclonal antibodies in single-chain variable fragment (scFv) format that target the Receptor Binding Domain (RBD) of different SARS-CoV-2 strains. The newly discovered scFv has the potential for use as a diagnostic or therapeutic option against SARS-CoV-2.

Methods

The RBD protein was produced, purified, and used as an antigen during biopanning. Six rounds of panning enriched RBD-specific phages and the binding affinity of binders were monitored by polyclonal phage ELISA. Subsequently, monoclonal phage ELISA was employed to identify specific binders. After sequence confirmation, the reactivity of the isolated anti-RBD scFv was evaluated. Additionally, bioinformatics tools determined the interaction between selected scFv and SARS-CoV-2 strains.

Results

The ELISA analysis demonstrated that the expressed RBD retains its structural integrity and effectively interacts with antibodies present in the sera of COVID-19 patients. Through screening a phage display library, a strong-binding scFv for RBD was discovered, which can effectively neutralize SARS-CoV-2 and its novel variants.

Conclusion

The findings of this study have led to the discovery of a novel scFv that effectively neutralizes SARS-CoV-2 strains, offering immense potential for research and therapy purposes.

Deep mutational scanning of rabies glycoprotein defines mutational constraint and antibody-escape mutations

Rabies virus causes nearly 60,000 human deaths annually. Antibodies that target the rabies glycoprotein (G) are being developed as post-exposure prophylactics, but mutations in G can render such antibodies ineffective. Here, we use pseudovirus deep mutational scanning to measure how all single amino-acid mutations to G affect cell entry and neutralization by a panel of antibodies. These measurements identify sites critical for rabies G's function, and define constrained regions that are attractive epitopes for clinical antibodies, including at the apex and base of the protein. We provide complete maps of escape mutations for eight monoclonal antibodies, including some in clinical use or development. Escape mutations for most antibodies are present in some natural rabies strains. Overall, this work provides comprehensive information on the functional and antigenic effects of G mutations that can help inform development of stabilized vaccine antigens and antibodies that are resilient to rabies genetic variation.

A potent pan-sarbecovirus neutralizing antibody resilient to epitope diversification

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) evolution has resulted in viral escape from clinically authorized monoclonal antibodies (mAbs), creating a need for mAbs that are resilient to epitope diversification. Broadly neutralizing coronavirus mAbs that are sufficiently potent for clinical development and retain activity despite viral evolution remain elusive. We identified a human mAb, designated VIR-7229, which targets the viral receptor-binding motif (RBM) with unprecedented cross-reactivity to all sarbecovirus clades, including non-ACE2-utilizing bat sarbecoviruses, while potently neutralizing SARS-CoV-2 variants since 2019, including the recent EG.5, BA.2.86, and JN.1. VIR-7229 tolerates extraordinary epitope variability, partly attributed to its high binding affinity, receptor molecular mimicry, and interactions with RBM backbone atoms. Consequently, VIR-7229 features a high barrier for selection of escape mutants, which are rare and associated with reduced viral fitness, underscoring its potential to be resilient to future viral evolution. VIR-7229 is a strong candidate to become a next-generation medicine.

Structural and Functional Insights into the Evolution of SARS-CoV-2 KP.3.1.1 Spike Protein

The JN.1-sublineage KP.3.1.1 recently emerged as the globally prevalent SARS-CoV-2 variant, demonstrating increased infectivity and antibody escape. We investigated how mutations and a deletion in the KP.3.1.1 spike protein (S) affect ACE2 binding and antibody escape. Mass spectrometry revealed a new glycan site at residue N30 and altered glycoforms at neighboring N61. Cryo-EM structures showed that the N30 glycan and rearrangement of adjacent residues did not significantly change the overall spike structure, up-down ratio of the receptor-binding domains (RBDs), or ACE2 binding. Furthermore, a KP.3.1.1 S structure with hACE2 further confirmed an epistatic effect between F456L and Q493E on ACE2 binding. Our analysis shows SARS-CoV-2 variants that emerged after late 2023 are now incorporating reversions to residues found in other sarbecoviruses, including the N30 glycan, Q493E, and others. Overall, these results inform on the structural and functional consequences of the KP.3.1.1 mutations, the current SARS-CoV-2 evolutionary trajectory, and immune evasion.

Interfacial subregions of SARS-CoV-2 spike RBD to hACE2 affect intermolecular affinity by their distinct roles played in association and dissociation kinetics

SARS-CoV-2's rapid global transmission depends on spike RBD's strong affinity to hACE2. In the context of binding hot spots well defined, the work investigated how interfacial subregions of SARS-CoV-2 spike RBD to hACE2 affect intermolecular affinity and their potential distinct roles involved in association and dissociation kinetics due to their local structural characteristics. Three spatially consecutive subregions of SARS-CoV-2 RBD were structurally partitioned across RBD's receptor binding motif (RBM). Their impacts on binding affinity and kinetics were differentiated through a comprehensive SPR measurement of hACE2 binding by chimeric swap mutants of respective subdomains from SARS-CoV-2 VOCs & phylogenetically close sarbecoviruses, and further compared with those of included single mutations across RBM and around the RBD core. The data supports that the intermediate interfacial subregion of RBD involving key residue at 417 is the rate-limiting effector of association kinetics and the subregion encompassing residues at 501/498/449 is the key binding energy contributor dictating dissociation kinetics, both of which relate to SARS-CoV-2's adaptive mutational evolution and host tropism closely. The kinetic data and structural analysis of local mutations' impact on spike RBD's binding and thermal stability provide a new perspective in evaluating SARS-CoV-2 evolution and other sarbecoviruses' evolvable binding to hACE2. The inherent binding mode offers direct clues of valid epitope in designing new antibodies that the coronavirus can't elude.

Deep mutationally scanned (DMS) CHIKV E3/E2 virus library maps viral amino acid preferences and predicts viral escape mutants of neutralizing CHIKV antibodies

As outbreaks of chikungunya virus (CHIKV), a mosquito-borne alphavirus, continue to present public health challenges, additional research is needed to generate protective and safe vaccines and effective therapeutics. Prior research has established a role for antibodies in mediating protection against CHIKV infection, and the early appearance of CHIKV-specific IgG or IgG neutralizing antibodies protects against progression to chronic CHIKV disease in humans. However, the importance of epitope specificity for these protective antibodies and how skewed responses contribute to development of acute and chronic CHIKV-associated joint disease remains poorly understood. Here, we describe the deep mutational scanning of one of the dominant targets of neutralizing antibodies during CHIKV infection, the E3/E2 (also known as p62) glycoprotein complex, to simultaneously test thousands of p62 mutants against selective pressures of interest in a high throughput manner. Characterization of the virus library revealed achievement of high diversity while also selecting out non-functional virus variants. Furthermore, this study provides evidence that this virus library system can comprehensively map sites critical for the neutralization function of antibodies of both known and unknown p62 domain specificities.

PPB-Affinity: Protein-Protein Binding Affinity dataset for AI-based protein drug discovery

Prediction of protein-protein binding (PPB) affinity plays an important role in large-molecular drug discovery. Deep learning (DL) has been adopted to predict the changes of PPB binding affinities upon mutations, but there was a scarcity of studies predicting the PPB affinity itself. The major reason is the paucity of open-source dataset with PPB affinity data. To address this gap, the current study introduced a large comprehensive PPB affinity (PPB-Affinity) dataset. The PPB-Affinity dataset contains key information such as crystal structures of protein-protein complexes (with or without protein mutation patterns), PPB affinity, receptor protein chain, ligand protein chain, etc. To the best of our knowledge, this is the largest publicly available PPB affinity dataset, and we believe it will significantly advance drug discovery by streamlining the screening of potential large-molecule drugs. We also developed a deep-learning benchmark model with this dataset to predict the PPB affinity, providing a foundational comparison for the research community.

Emerging severe acute respiratory syndrome coronavirus 2 variants and their impact on immune evasion and vaccine-induced immunity

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants harboring mutations in the structural protein, especially in the receptor binding domain (RBD) of spike protein, have raised concern about potential immune escape. The spike protein of SARS-CoV-2 plays a vital role in infection and is an important target for neutralizing antibodies. The mutations that occur in the structural proteins, especially in the spike protein, lead to changes in the virus attributes of transmissibility, an increase in disease severity, a notable reduction in neutralizing antibodies generated and thus a decreased response to vaccines and therapy. The observed multiple mutations in the RBD of the spike protein showed immune escape because it increases the affinity of spike protein binding with the ACE-2 receptor of host cells and increases resistance to neutralizing antibodies. Cytotoxic T-cell responses are crucial in controlling SARS-CoV-2 infections from the infected tissues and clearing them from circulation. Cytotoxic T cells efficiently recognized the infected cells and killed them by releasing soluble mediator's perforin and granzymes. However, the overwhelming response of T cells and, subsequently, the overproduction of inflammatory mediators during severe infections with SARS-CoV-2 may lead to poor outcomes. This review article summarizes the impact of mutations in the spike protein of SARS-CoV-2, especially mutations of RBD, on immunogenicity, immune escape and vaccine-induced immunity, which could contribute to future studies focusing on vaccine design and immunotherapy.

COVID-19 vaccine hesitancy in a small rural southern state: Results of a weighted random sample survey

Objective

COVID-19 remains a significant health threat to the United States (U.S.) and the world even after the development of effective vaccines. Throughout the pandemic, rural areas have been more hesitant to be vaccinated for COVID-19 than more urban counterparts. The purpose of this study was to assess predictors of vaccine hesitancy in a small, largely rural, southern state using a multivariate model that would allow an assessment of independent predictors of COVID-19 vaccine hesitancy.

Methods

Cross-sectional survey research was conducted using data collected from a weighted random sample of 1500 individuals residing in Arkansas, U.S. Data were collected using random digit dialing of landline and cell phone numbers between July 12 and July 30, 2021. Participants were asked about their hesitancy to be vaccinated for COVID-19. Data were analyzed using bivariate odds ratios and cumulative logit model.

Results

Results found 47 % of the sample were hesitant to be vaccinated. Bivariate analysis found vaccine hesitancy to be related to age, race/ethnicity, rural residence, education, employment, and having had COVID-19. Multivariate analysis showed sex, age, rural residence, and history of having had COVID-19 were associated with hesitancy. A history of vaccination/trust in vaccines remained strongly negatively associated with hesitancy.

Conclusion

Findings suggest population diversity may account for vaccine hesitancy across jurisdictions, suggesting public health messages be tailored to a local audience. The strongest finding suggests vaccinations should be emphasized in general to build habits of being vaccinated.

Conserved sites on the influenza H1 and H3 hemagglutinin recognized by human antibodies

Monoclonal antibodies (mAbs) targeting the influenza hemagglutinin (HA) have the potential to be used as prophylactics or templates for next-generation vaccines that provide broad protection. Here, we isolated broad, subtype-neutralizing mAbs from human B cells targeting the H1 or H3 HA head as well as a unique mAb targeting the stem. The H1 mAbs target the previously defined lateral patch epitope on H1 HAs and recognize HAs from 1933 to 2021 in addition to a swine H1N1 virus with pandemic potential. Using directed evolution, we improved the neutralization potency of these H1 mAbs towards a contemporary H1 strain. Using deep mutational scanning of four antigenically distinct H1N1 viruses, we identified potential viral escape pathways. For the H3 mAbs we used cryo-EM to define the targeted epitopes: one mAb recognizes the side of the H3 head, accommodating the N133 glycan and a pocket underneath the receptor binding site. The other H3 mAb recognizes an epitope in the HA stem that overlaps with previously characterized mAbs, but with distinct antibody variable genes and mode of recognition. Collectively, these mAbs identify common sites recognized by broad, subtype-specific mAbs that may be elicited by next-generation vaccines.

Patterns of the within-host evolution of human norovirus in immunocompromised individuals and implications for treatment

BACKGROUND

Currently, there is no licensed treatment for chronic norovirus infections, but the use of intra-duodenally-delivered immunoglobulins is promising; nevertheless, varying results have limited their wide use. Little is known about the relationship between norovirus genetic diversity and treatment efficacy.

METHODS

We analyzed the norovirus within-host diversity and evolution in a cohort of 20 immunocompromised individuals using next-generation sequencing (NGS) and clone-based sequencing of the capsid (VP1) gene. Representative VP1s were expressed and their glycan receptor binding affinity and antigenicity were evaluated.

FINDINGS

The P2 domain, within the VP1, accumulated up to 30-fold more non-synonymous mutations than other genomic regions. Intra-host virus populations in these patients tended to evolve into divergent lineages that were often antigenically distinct. Several of these viruses were widely resistant to binding-blocking antibodies in immunoglobulin preparations. Notably, for one patient, a single amino-acid substitution in the P2 domain resulted in an immune-escape phenotype, and it was likely the main contributor to treatment failure. Furthermore, we found evidence for transmission of late-stage viruses between two immunocompromised individuals.

INTERPRETATION

The findings demonstrated that within-host noroviruses in chronic infections tend to evolve into antigenically distinct subpopulations. This antigenic evolution was likely caused by the remaining low immunity levels exerted by immunocompromised individuals, possibly undermining antiviral treatment. Our observations provide insights into norovirus (within-host) evolution and treatment.

FUNDING

Erasmus MC grant mRACE, the European Union's Horizon 2020 research and innovation program under grant agreement No. 874735 (VEO), and the NWO STEVIN award (Koopmans).

Deep mutational scanning of H5 hemagglutinin to inform influenza virus surveillance

H5 influenza is considered a potential pandemic threat. Recently, H5 viruses belonging to clade 2.3.4.4b have caused large outbreaks in avian and multiple nonhuman mammalian species. Previous studies have identified molecular phenotypes of the viral hemagglutinin (HA) protein that contribute to pandemic potential in humans, including cell entry, receptor preference, HA stability, and reduced neutralization by polyclonal sera. However, prior experimental work has only measured how these phenotypes are affected by a handful of the >10,000 different possible amino-acid mutations to HA. Here, we use pseudovirus deep mutational scanning to measure how all mutations to a 2.3.4.4b H5 HA affect each phenotype. We identify mutations that allow HA to better bind α2-6-linked sialic acids and show that some viruses already carry mutations that stabilize HA. We also measure how all HA mutations affect neutralization by sera from mice and ferrets vaccinated against or infected with 2.3.4.4b H5 viruses. These antigenic maps enable rapid assessment of when new viral strains have acquired mutations that may create mismatches with candidate vaccine virus, and we show that a mutation present in some recent H5 HAs causes a large antigenic change. Overall, the systematic nature of deep mutational scanning combined with the safety of pseudoviruses enables comprehensive measurements of the phenotypic effects of mutations that can inform real-time interpretation of viral variation observed during surveillance of H5 influenza.

Efficient epistasis inference via higher-order covariance matrix factorization

Epistasis can profoundly influence evolutionary dynamics. Temporal genetic data, consisting of sequences sampled repeatedly from a population over time, provides a unique resource to understand how epistasis shapes evolution. However, detecting epistatic interactions from sequence data is technically challenging. Existing methods for identifying epistasis are computationally demanding, limiting their applicability to real-world data. Here, we present a novel computational method for inferring epistasis that significantly reduces computational costs without sacrificing accuracy. We validated our approach in simulations and applied it to study HIV-1 evolution over multiple years in a data set of 16 individuals. There we observed a strong excess of negative epistatic interactions between beneficial mutations, especially mutations involved in immune escape. Our method is general and could be used to characterize epistasis in other large data sets.

Sarbecovirus RBD indels and specific residues dictating multi-species ACE2 adaptiveness

Our comprehensive understanding of the multi-species ACE2 adaptiveness of sarbecoviruses remains elusive, particularly for those with various receptor binding motif (RBM) insertions/deletions (indels). Here, we analyzed RBM sequences from 268 sarbecoviruses categorized into four RBM indel types. We examined the ability of 20 representative sarbecovirus Spike glycoproteins (S) and derivatives in utilizing ACE2 from various bats and several other mammalian species. We reveal that sarbecoviruses with long RBMs (type-I) can achieve broad ACE2 tropism, whereas viruses with single deletions in Region 1 (type-II) or Region 2 (type-III) exhibit narrower ACE2 tropism. Sarbecoviruses with double region deletions (type-IV) completely lost ACE2 usage, which is restricted by clade-specific residues within and outside RBM. Lastly, we propose the evolution of sarbecovirus RBM indels and illustrate how loop lengths, disulfide, and residue determinants shape multi-species ACE2 adaptiveness. This study provides profound insights into the mechanisms governing ACE2 usage and spillover risks of sarbecoviruses.

Mosaic sarbecovirus nanoparticles elicit cross-reactive responses in pre-vaccinated animals

Immunization with mosaic-8b (nanoparticles presenting 8 SARS-like betacoronavirus [sarbecovirus] receptor-binding domains [RBDs]) elicits more broadly cross-reactive antibodies than homotypic SARS-CoV-2 RBD-only nanoparticles and protects against sarbecoviruses. To investigate original antigenic sin (OAS) effects on mosaic-8b efficacy, we evaluated the effects of prior COVID-19 vaccinations in non-human primates and mice on anti-sarbecovirus responses elicited by mosaic-8b, admix-8b (8 homotypics), or homotypic SARS-CoV-2 immunizations, finding the greatest cross-reactivity for mosaic-8b. As demonstrated by molecular fate mapping, in which antibodies from specific cohorts of B cells are differentially detected, B cells primed by WA1 spike mRNA-LNP dominated antibody responses after RBD-nanoparticle boosting. While mosaic-8b- and homotypic-nanoparticles boosted cross-reactive antibodies, de novo antibodies were predominantly induced by mosaic-8b, and these were specific for variant RBDs with increased identity to RBDs on mosaic-8b. These results inform OAS mechanisms and support using mosaic-8b to protect COVID-19-vaccinated/infected humans against as-yet-unknown SARS-CoV-2 variants and animal sarbecoviruses with human spillover potential.

Bebtelovimab-bound SARS-CoV-2 RBD mutants: resistance profiling and validation with escape mutations, clinical results, and viral genome sequences

The dynamic evolution of SARS-CoV-2 variants necessitates ongoing advancements in therapeutic strategies. Despite the promise of monoclonal antibody (mAb) therapies like bebtelovimab, concerns persist regarding resistance mutations, particularly single-to-multipoint mutations in the receptor-binding domain (RBD). Our study addresses this by employing interface-guided computational protein design to predict potential bebtelovimab-resistance mutations. Through extensive physicochemical analysis, mutational preferences, precision-recall metrics, protein-protein docking, and energetic analyses, combined with all-atom, and coarse-grained molecular dynamics (MD) simulations, we elucidated the structural-dynamics-binding features of the bebtelovimab-RBD complexes. Identification of susceptible RBD residues under positive selection pressure, coupled with validation against bebtelovimab-escape mutations, clinically reported resistance mutations, and viral genomic sequences enhances the translational significance of our findings and contributes to a better understanding of the resistance mechanisms of SARS-CoV-2.

[The Molecular and Biological Patterns Underlying Sustained SARS-CoV-2 Circulation in the Human Population]

INTRODUCTION

For four years, SARS-CoV-2, the etiological agent of COVID-19, has been circulating among humans. By the end of the second year, an absence of immunologically naive individuals was observed, attributable to extensive immunization efforts and natural viral exposure. This study focuses on delineating the molecular and biological patterns that facilitate the persistence of SARS-CoV-2, thereby informing predictions on the epidemiological trajectory of COVID-19 toward refining pandemic countermeasures. The aim of this study was to describe the molecular biological patterns identified that contribute to the persistence of the virus in the human population.

MATERIALS AND METHODS

For over three years since the beginning of the COVID-19 pandemic, molecular genetic monitoring of SARS-CoV-2 has been conducted, which included the collection of nasopharyngeal swabs from infected individuals, assessment of viral load, and subsequent whole-genome sequencing.

RESULTS

We discerned dominant genetic lineages correlated with rising disease incidence. We scrutinized amino acid substitutions across SARS-CoV-2 proteins and quantified viral loads in swab samples from patients with emerging COVID-19 variants. Our findings suggest a model of viral persistence characterized by 1) periodic serotype shifts causing substantial diminutions in serum virus-neutralizing activity (> 10-fold), 2) serotype-specific accrual of point mutations in the receptor-binding domain (RBD) to modestly circumvent neutralizing antibodies and enhance receptor affinity, and 3) a gradually increasing amount of virus being shed in mucosal surfaces within a single serotype.

CONCLUSION

This model aptly accounts for the dynamics of COVID-19 incidence in Moscow. For a comprehensive understanding of these dynamics, acquiring population-level data on immune tension and antibody neutralization relative to genetic lineage compositions is essential.

AlphaFold2 Modeling and Molecular Dynamics Simulations of the Conformational Ensembles for the SARS-CoV-2 Spike Omicron JN.1, KP.2 and KP.3 Variants: Mutational Profiling of Binding Energetics Reveals Epistatic Drivers of the ACE2 Affinity and Escape Hotspots of Antibody Resistance

The most recent wave of SARS-CoV-2 Omicron variants descending from BA.2 and BA.2.86 exhibited improved viral growth and fitness due to convergent evolution of functional hotspots. These hotspots operate in tandem to optimize both receptor binding for effective infection and immune evasion efficiency, thereby maintaining overall viral fitness. The lack of molecular details on structure, dynamics and binding energetics of the latest FLiRT and FLuQE variants with the ACE2 receptor and antibodies provides a considerable challenge that is explored in this study. We combined AlphaFold2-based atomistic predictions of structures and conformational ensembles of the SARS-CoV-2 spike complexes with the host receptor ACE2 for the most dominant Omicron variants JN.1, KP.1, KP.2 and KP.3 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 computations of binding affinities, we identified binding energy hotspots and characterized the molecular basis underlying epistatic couplings between convergent mutational hotspots. The results suggested the existence of epistatic interactions between convergent mutational sites at L455, F456, Q493 positions that protect and restore ACE2-binding affinity while conferring beneficial immune escape. To examine immune escape mechanisms, we performed structure-based mutational profiling of the spike protein binding with several classes of antibodies that displayed impaired neutralization against BA.2.86, JN.1, KP.2 and KP.3. The results confirmed the experimental data that JN.1, KP.2 and KP.3 harboring the L455S and F456L mutations can significantly impair the neutralizing activity of class 1 monoclonal antibodies, while the epistatic effects mediated by F456L can facilitate the subsequent convergence of Q493E changes to rescue ACE2 binding. Structural and energetic analysis provided a rationale to the experimental results showing that BD55-5840 and BD55-5514 antibodies that bind to different binding epitopes can retain neutralizing efficacy against all examined variants BA.2.86, JN.1, KP.2 and KP.3. The results support the notion that evolution of Omicron variants may favor emergence of lineages with beneficial combinations of mutations involving mediators of epistatic couplings that control balance of high ACE2 affinity and immune evasion.

SARS-CoV-2 Variants from Long-Term, Persistently Infected Immunocompromised Patients Have Altered Syncytia Formation, Temperature-Dependent Replication, and Serum Neutralizing Antibody Escape

SARS-CoV-2 infection of immunocompromised individuals often leads to prolonged detection of viral RNA and infectious virus in nasal specimens, presumably due to the lack of induction of an appropriate adaptive immune response. Mutations identified in virus sequences obtained from persistently infected patients bear signatures of immune evasion and have some overlap with sequences present in variants of concern. We characterized virus isolates obtained greater than 100 days after the initial COVID-19 diagnosis from two COVID-19 patients undergoing immunosuppressive cancer therapy, wand compared them to an isolate from the start of the infection. Isolates from an individual who never mounted an antibody response specific to SARS-CoV-2 despite the administration of convalescent plasma showed slight reductions in plaque size and some showed temperature-dependent replication attenuation on human nasal epithelial cell culture compared to the virus that initiated infection. An isolate from another patient-who did mount a SARS-CoV-2 IgM response-showed temperature-dependent changes in plaque size as well as increased syncytia formation and escape from serum-neutralizing antibodies. Our results indicate that not all virus isolates from immunocompromised COVID-19 patients display clear signs of phenotypic change, but increased attention should be paid to monitoring virus evolution in this patient population.

Deep mutational scanning of SARS-CoV-2 Omicron BA.2.86 and epistatic emergence of the KP.3 variant

Deep mutational scanning experiments aid in the surveillance and forecasting of viral evolution by providing prospective measurements of mutational effects on viral traits, but epistatic shifts in the impacts of mutations can hinder viral forecasting when measurements were made in outdated strain backgrounds. Here, we report measurements of the impact of all single amino acid mutations on ACE2-binding affinity and protein folding and expression in the SARS-CoV-2 Omicron BA.2.86 spike receptor-binding domain. As with other SARS-CoV-2 variants, we find a plastic and evolvable basis for receptor binding, with many mutations at the ACE2 interface maintaining or even improving ACE2-binding affinity. Despite its large genetic divergence, mutational effects in BA.2.86 have not diverged greatly from those measured in its Omicron BA.2 ancestor. However, we do identify strong positive epistasis among subsequent mutations that have accrued in BA.2.86 descendants. Specifically, the Q493E mutation that decreased ACE2-binding affinity in all previous SARS-CoV-2 backgrounds is reversed in sign to enhance human ACE2-binding affinity when coupled with L455S and F456L in the currently emerging KP.3 variant. Our results point to a modest degree of epistatic drift in mutational effects during recent SARS-CoV-2 evolution but highlight how these small epistatic shifts can have important consequences for the emergence of new SARS-CoV-2 variants.

MuToN Quantifies Binding Affinity Changes upon Protein Mutations by Geometric Deep Learning

Assessing changes in protein-protein binding affinity due to mutations helps understanding a wide range of crucial biological processes within cells. Despite significant efforts to create accurate computational models, predicting how mutations affect affinity remains challenging due to the complexity of the biological mechanisms involved. In the present work, a geometric deep learning framework called MuToN is introduced for quantifying protein binding affinity change upon residue mutations. The method, designed with geometric attention networks, is mechanism-aware. It captures changes in the protein binding interfaces of mutated complexes and assesses the allosteric effects of amino acids. Experimental results highlight MuToN's superiority compared to existing methods. Additionally, MuToN's flexibility and effectiveness are illustrated by its precise predictions of binding affinity changes between SARS-CoV-2 variants and the ACE2 complex.

Antibodies utilizing VL6-57 light chains target a convergent cryptic epitope on SARS-CoV-2 spike protein and potentially drive the genesis of Omicron variants

Continued evolution of SARS-CoV-2 generates variants to challenge antibody immunity established by infection and vaccination. A connection between population immunity and genesis of virus variants has long been suggested but its molecular basis remains poorly understood. Here, we identify a class of SARS-CoV-2 neutralizing public antibodies defined by their shared usage of VL6-57 light chains. Although heavy chains of diverse genotypes are utilized, convergent HCDR3 rearrangements have been observed among these public antibodies to cooperate with germline VL6-57 LCDRs to target a convergent epitope defined by RBD residues S371-S373-S375. Antibody repertoire analysis identifies that this class of VL6-57 antibodies is present in SARS-CoV-2-naive individuals and is clonally expanded in most COVID-19 patients. We confirm that Omicron-specific substitutions at S371, S373 and S375 mediate escape of antibodies of the VL6-57 class. These findings support that this class of public antibodies constitutes a potential immune pressure promoting the introduction of S371L/F-S373P-S375F in Omicron variants. The results provide further molecular evidence to support that antigenic evolution of SARS-CoV-2 is driven by antibody mediated population immunity.

Molecular basis of convergent evolution of ACE2 receptor utilization among HKU5 coronaviruses

DPP4 was considered a canonical receptor for merbecoviruses until the recent discovery of African bat-borne MERS-related coronaviruses using ACE2. The extent and diversity with which merbecoviruses engage ACE2 and their receptor species tropism remain unknown. Here, we reveal that HKU5 enters host cells utilizing Pipistrellus abramus (P.abr) and several non-bat mammalian ACE2s through a binding mode distinct from that of any other known ACE2-using coronaviruses. These results show that several merbecovirus clades independently evolved ACE2 utilization, which appears to be a broadly shared property among these pathogens, through an extraordinary diversity of ACE2 recognition modes. We show that MERS-CoV and HKU5 have markedly distinct antigenicity, due to extensive genetic divergence, and identified several HKU5 inhibitors, including two clinical compounds. Our findings profoundly alter our understanding of coronavirus evolution and pave the way for developing countermeasures against viruses poised for human emergence.

Real-time identification of epistatic interactions in SARS-CoV-2 from large genome collections

BACKGROUND

The emergence of the SARS-CoV-2 virus has highlighted the importance of genomic epidemiology in understanding the evolution of pathogens and guiding public health interventions. The Omicron variant in particular has underscored the role of epistasis in the evolution of lineages with both higher infectivity and immune escape, and therefore the necessity to update surveillance pipelines to detect them early on.

RESULTS

In this study, we apply a method based on mutual information between positions in a multiple sequence alignment, which is capable of scaling up to millions of samples. We show how it can reliably predict known experimentally validated epistatic interactions, even when using as little as 10,000 sequences, which opens the possibility of making it a near real-time prediction system. We test this possibility by modifying the method to account for the sample collection date and apply it retrospectively to multiple sequence alignments for each month between March 2020 and March 2023. We detected a cornerstone epistatic interaction in the Spike protein between codons 498 and 501 as soon as seven samples with a double mutation were present in the dataset, thus demonstrating the method's sensitivity. We test the ability of the method to make inferences about emerging interactions by testing candidates predicted after March 2023, which we validate experimentally.

CONCLUSIONS

We show how known epistatic interaction in SARS-CoV-2 can be detected with high sensitivity, and how emerging ones can be quickly prioritized for experimental validation, an approach that could be implemented downstream of pandemic genome sequencing efforts.

Subsequent Waves of Convergent Evolution in SARS-CoV-2 Genes and Proteins

Beginning in 2022, following widespread infection and vaccination among the global population, the SARS-CoV-2 virus mainly evolved to evade immunity derived from vaccines and past infections. This review covers the convergent evolution of structural, nonstructural, and accessory proteins in SARS-CoV-2, with a specific look at common mutations found in long-lasting infections that hint at the virus potentially reverting to an enteric sarbecovirus type.