Probing the biophysical constraints of SARS-CoV-2 spike N-terminal domain using deep mutational scanning

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.

Omicron-specific ultra-potent SARS-CoV-2 neutralizing antibodies targeting the N1/N2 loop of Spike N-terminal domain

A multitude of functional mutations continue to emerge on the N-terminal domain (NTD) of the spike protein in SARS-CoV-2 Omicron subvariants. Understanding the immunogenicity of Omicron NTD and the properties of antibodies elicited by it is crucial for comprehending the impact of NTD mutations on viral fitness and guiding vaccine design. In this study, we find that most of NTD-targeting antibodies isolated from individuals with BA.5/BF.7 breakthrough infection (BTI) are ancestral (wild-type or WT)-reactive and non-neutralizing. Surprisingly, we identified five ultra-potent neutralizing antibodies (NAbs) that can only bind to Omicron but not WT NTD. Structural analysis revealed that they bind to a unique epitope on the N1/N2 loop of NTD and interact with the receptor-binding domain (RBD) via the light chain. These Omicron-specific NAbs achieve neutralization through ACE2 competition and blockage of ACE2-mediated S1 shedding. However, BA.2.86 and BA.2.87.1, which carry insertions or deletions on the N1/N2 loop, can evade these antibodies. Together, we provided a detailed map of the NTD-targeting antibody repertoire in the post-Omicron era, demonstrating their vulnerability to NTD mutations enabled by its evolutionary flexibility, despite their potent neutralization. These results revealed the function of the indels in the NTD of BA.2.86/JN.1 sublineage in evading neutralizing antibodies and highlighted the importance of considering the immunogenicity of NTD in vaccine design.

Understanding epistatic networks in the B1 β-lactamases through coevolutionary statistical modeling and deep mutational scanning

Throughout evolution, protein families undergo substantial sequence divergence while preserving structure and function. Although most mutations are deleterious, evolution can explore sequence space via epistatic networks of intramolecular interactions that alleviate the harmful mutations. However, comprehensive analysis of such epistatic networks across protein families remains limited. Thus, we conduct a family wide analysis of the B1 metallo-β-lactamases, combining experiments (deep mutational scanning, DMS) on two distant homologs (NDM-1 and VIM-2) and computational analyses (in silico DMS based on Direct Coupling Analysis, DCA) of 100 homologs. The methods jointly reveal and quantify prevalent epistasis, as ~1/3rd of equivalent mutations are epistatic in DMS. From DCA, half of the positions have a >6.5 fold difference in effective number of tolerated mutations across the entire family. Notably, both methods locate residues with the strongest epistasis in regions of intermediate residue burial, suggesting a balance of residue packing and mutational freedom in forming epistatic networks. We identify entrenched WT residues between NDM-1 and VIM-2 in DMS, which display statistically distinct behaviors in DCA from non-entrenched residues. Entrenched residues are not easily compensated by changes in single nearby interactions, reinforcing existing findings where a complex epistatic network compounds smaller effects from many interacting residues.

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.

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 (RBD). 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.

A library-on-library screen reveals the breadth expansion landscape of a broadly neutralizing betacoronavirus antibody

Broadly neutralizing antibodies (bnAbs) typically evolve cross-reactivity breadth through acquiring somatic hypermutations. While evolution of breadth requires improvement of binding to multiple antigenic variants, most experimental evolution platforms select against only one antigenic variant at a time. In this study, a yeast display library-on-library approach was applied to delineate the affinity maturation of a betacoronavirus bnAb, S2P6, against 27 spike stem helix peptides in a single experiment. Our results revealed that the binding affinity landscape of S2P6 varies among different stem helix peptides. However, somatic hypermutations that confer general improvement in binding affinity across different stem helix peptides could also be identified. We further showed that a key somatic hypermutation for breadth expansion involves long-range interaction. Overall, our work not only provides a proof-of-concept for using a library-on-library approach to analyze the evolution of antibody breadth, but also has important implications for the development of broadly protective vaccines.

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 perform 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 identify mutations at residue 813 of the spike protein that reduced TMPRSS2-mediated entry with decreased virulence. In addition, we show 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.

SARS-CoV-2 resistance to monoclonal antibodies and small-molecule drugs

Over four years have passed since the beginning of the COVID-19 pandemic. The scientific response has been rapid and effective, with many therapeutic monoclonal antibodies and small molecules developed for clinical use. However, given the ability for viruses to become resistant to antivirals, it is perhaps no surprise that the field has identified resistance to nearly all of these compounds. Here, we provide a comprehensive review of the resistance profile for each of these therapeutics. We hope that this resource provides an atlas for mutations to be aware of for each agent, particularly as a springboard for considerations for the next generation of antivirals. Finally, we discuss the outlook and thoughts for moving forward in how we continue to manage this, and the next, pandemic.

Landscape of T cell epitopes displays hot mutations of SARS-CoV-2 variant spikes evading cellular immunity

The continuous evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been accompanied by the emergence of viral mutations that pose a great challenge to existing vaccine strategies. It is not fully understood with regard to the role of mutations on the SARS-CoV-2 spike protein from emerging viral variants in T cell immunity. In the current study, recombinant eukaryotic plasmids were constructed as DNA vaccines to express the spike protein from multiple SARS-CoV-2 strains. These DNA vaccines were used to immunize BALB/c mice, and cross-T cell responses to the spike protein from these viral strains were quantitated using interferon-γ (IFN-γ) Elispot. Peptides covering the full-length spike protein from different viral strains were used to detect epitope-specific IFN-γ+ CD4+ and CD8+ T cell responses by fluorescence-activated cell sorting. SARS-CoV-2 Delta and Omicron BA.1 strains were found to have broad T cell cross-reactivity, followed by the Beta strain. The landscapes of T cell epitopes on the spike protein demonstrated that at least 30 mutations emerging from Alpha to Omicron BA.5 can mediate the escape of T cell immunity. Omicron and its sublineages have 19 out of these 30 mutations, most of which are new, and a few are inherited from ancient circulating variants of concerns. The cross-T cell immunity between SARS-CoV-2 prototype strain and Omicron strains can be attributed to the T cell epitopes located in the N-terminal domain (181-246 aa [amino acids], 271-318 aa) and C-terminal domain (1171-1273 aa) of the spike protein. These findings provide in vivo evidence for optimizing vaccine manufacturing and immunization strategies for current or future viral variants.

Advancing Antibody Engineering through Synthetic Evolution and Machine Learning

Abs are versatile molecules with the potential to achieve exceptional binding to target Ags, while also possessing biophysical properties suitable for therapeutic drug development. Protein display and directed evolution systems have transformed synthetic Ab discovery, engineering, and optimization, vastly expanding the number of Ab clones able to be experimentally screened for binding. Moreover, the burgeoning integration of high-throughput screening, deep sequencing, and machine learning has further augmented in vitro Ab optimization, promising to accelerate the design process and massively expand the Ab sequence space interrogated. In this Brief Review, we discuss the experimental and computational tools employed in synthetic Ab engineering and optimization. We also explore the therapeutic challenges posed by developing Abs for infectious diseases, and the prospects for leveraging machine learning-guided protein engineering to prospectively design Abs resistant to viral escape.

Multiplex Functional Characterization of Protein Variant Libraries in Mammalian Cells with Single-Copy Genomic Integration and High-Throughput DNA Sequencing

Sequencing-based, massively parallel genetic assays have enabled simultaneous characterization of the genotype-phenotype relationships for libraries encoding thousands of unique protein variants. Since plasmid transfection and lentiviral transduction have characteristics that limit multiplexing with pooled libraries, we developed a mammalian synthetic biology platform that harnesses the Bxb1 bacteriophage DNA recombinase to insert single promoterless plasmids encoding a transgene of interest into a pre-engineered "landing pad" site within the cell genome. The transgene is expressed behind a genomically integrated promoter, ensuring only one transgene is expressed per cell, preserving a strict genotype-phenotype link. Upon selecting cells based on a desired phenotype, the transgene can be sequenced to ascribe each variant a phenotypic score. We describe how to create and utilize landing pad cells for large-scale, library-based genetic experiments. Using the provided examples, the experimental template can be adapted to explore protein variants in diverse biological problems within mammalian cells.

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.

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.

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.

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.

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 variants, but whether such large 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 RBD 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 many 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 mutations like F456L that define the newly emerging 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.

Deep mutagenesis scanning using whole trimeric SARS-CoV-2 spike highlights the importance of NTD-RBD interactions in determining spike phenotype

New variants of SARS-CoV-2 are continually emerging with mutations in spike associated with increased transmissibility and immune escape. Phenotypic maps can inform the prediction of concerning mutations from genomic surveillance, however most of these maps currently derive from studies using monomeric RBD, while spike is trimeric, and contains additional domains. These maps may fail to reflect interdomain interactions in the prediction of phenotypes. To try to improve on this, we developed a platform for deep mutational scanning using whole trimeric spike. We confirmed a previously reported epistatic effect within the RBD affecting ACE2 binding, that highlights the importance of updating the base spike sequence for future mutational scanning studies. Using post vaccine sera, we found that the immune response of vaccinated individuals was highly focused on one or two epitopes in the RBD and that single point mutations at these positions can account for most of the immune escape mediated by the Omicron BA.1 RBD. However, unexpectedly we found that the BA.1 RBD alone does not account for the high level of antigenic escape by BA.1 spike. We show that the BA.1 NTD amplifies the immune evasion of its associated RBD. BA.1 NTD reduces neutralistion by RBD directed monoclonal antibodies, and impacts ACE2 interaction. NTD variation is thus an important mechanism of immune evasion by SARS-CoV-2. Such effects are not seen when pre-stabilized spike proteins are used, suggesting the interdomain effects require protein mobility to express their phenotype.

High-throughput screening of spike variants uncovers the key residues that alter the affinity and antigenicity of SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has elicited a worldwide pandemic since late 2019. There has been ~675 million confirmed coronavirus disease 2019 (COVID-19) cases, leading to more than 6.8 million deaths as of March 1, 2023. Five SARS-CoV-2 variants of concern (VOCs) were tracked as they emerged and were subsequently characterized. However, it is still difficult to predict the next dominant variant due to the rapid evolution of its spike (S) glycoprotein, which affects the binding activity between cellular receptor angiotensin-converting enzyme 2 (ACE2) and blocks the presenting epitope from humoral monoclonal antibody (mAb) recognition. Here, we established a robust mammalian cell-surface-display platform to study the interactions of S-ACE2 and S-mAb on a large scale. A lentivirus library of S variants was generated via in silico chip synthesis followed by site-directed saturation mutagenesis, after which the enriched candidates were acquired through single-cell fluorescence sorting and analyzed by third-generation DNA sequencing technologies. The mutational landscape provides a blueprint for understanding the key residues of the S protein binding affinity to ACE2 and mAb evasion. It was found that S205F, Y453F, Q493A, Q493M, Q498H, Q498Y, N501F, and N501T showed a 3-12-fold increase in infectivity, of which Y453F, Q493A, and Q498Y exhibited at least a 10-fold resistance to mAbs REGN10933, LY-CoV555, and REGN10987, respectively. These methods for mammalian cells may assist in the precise control of SARS-CoV-2 in the future.

A pseudovirus system enables deep mutational scanning of the full SARS-CoV-2 spike

A major challenge in understanding SARS-CoV-2 evolution is interpreting the antigenic and functional effects of emerging mutations in the viral spike protein. Here, we describe a deep mutational scanning platform based on non-replicative pseudotyped lentiviruses that directly quantifies how large numbers of spike mutations impact antibody neutralization and pseudovirus infection. We apply this platform to produce libraries of the Omicron BA.1 and Delta spikes. These libraries each contain ∼7,000 distinct amino acid mutations in the context of up to ∼135,000 unique mutation combinations. We use these libraries to map escape mutations from neutralizing antibodies targeting the receptor-binding domain, N-terminal domain, and S2 subunit of spike. Overall, this work establishes a high-throughput and safe approach to measure how ∼105 combinations of mutations affect antibody neutralization and spike-mediated infection. Notably, the platform described here can be extended to the entry proteins of many other viruses.

Towards Quantum-Chemical Level Calculations of SARS-CoV-2 Spike Protein Variants of Concern by First Principles Density Functional Theory

The spike protein (S-protein) is a crucial part of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), with its many domains responsible for binding, fusion, and host cell entry. In this review we use the density functional theory (DFT) calculations to analyze the atomic-scale interactions and investigate the consequences of mutations in S-protein domains. We specifically describe the key amino acids and functions of each domain, which are essential for structural stability as well as recognition and fusion processes with the host cell; in addition, we speculate on how mutations affect these properties. Such unprecedented large-scale ab initio calculations, with up to 5000 atoms in the system, are based on the novel concept of amino acid-amino acid-bond pair unit (AABPU) that allows for an alternative description of proteins, providing valuable information on partial charge, interatomic bonding and hydrogen bond (HB) formation. In general, our results show that the S-protein mutations for different variants foster an increased positive partial charge, alter the interatomic interactions, and disrupt the HB networks. We conclude by outlining a roadmap for future computational research of biomolecular virus-related systems.