Prospective mapping of viral mutations that escape antibodies used to treat COVID-19

Analysis of how antigen mutations disrupt antibody binding interactions toward enabling rapid and reliable antibody repurposing

Antibody repurposing is the process of changing a known antibody so that it binds to a mutated antigen. One of the findings to emerge from the Coronavirus Disease 2019 (COVID-19) pandemic was that it was possible to repurpose neutralizing antibodies for Severe Acute Respiratory Syndrome, a related disease, to work for COVID-19. Thus, antibody repurposing is a possible pathway to prepare for and respond to future pandemics, as well as personalizing cancer therapies. For antibodies to be successfully repurposed, it is necessary to know both how antigen mutations disrupt their binding and how they should be mutated to recover binding, with this work describing an analysis to address the first of these topics. Every possible antigen point mutation in the interface of 246 antibody-protein complexes were analyzed using the Rosetta molecular mechanics force field. The results highlight a number of features of how antigen mutations affect antibody binding, including the effects of mutating critical hotspot residues versus other positions, how many mutations are necessary to be likely to disrupt binding, the prevalence of indirect effects of mutations on binding, and the relative importance of changing attractive versus repulsive energies. These data are expected to be useful in guiding future antibody repurposing experiments.

SARS-CoV-2 epidemiology, kinetics, and evolution: A narrative review

Since winter 2019, SARS-CoV-2 has emerged, spread, and evolved all around the globe. We explore 4 y of evolutionary epidemiology of this virus, ranging from the applied public health challenges to the more conceptual evolutionary biology perspectives. Through this review, we first present the spread and lethality of the infections it causes, starting from its emergence in Wuhan (China) from the initial epidemics all around the world, compare the virus to other betacoronaviruses, focus on its airborne transmission, compare containment strategies ("zero-COVID" vs. "herd immunity"), explain its phylogeographical tracking, underline the importance of natural selection on the epidemics, mention its within-host population dynamics. Finally, we discuss how the pandemic has transformed (or should transform) the surveillance and prevention of viral respiratory infections and identify perspectives for the research on epidemiology of COVID-19.

Somatic hypermutation shapes the viral escape profile of SARS-CoV-2 neutralising antibodies

BACKGROUND

Since the onset of the COVID-19 pandemic, SARS-CoV-2 neutralising monoclonal antibodies (mAbs) are being developed for clinical use. With the appearance of new virus variants, most mAbs lost their virus-neutralising activity, highlighting the complexity of mAb development under conditions of continuous SARS-CoV-2 evolution.

METHODS

Hamsters were treated with SARS-CoV-2 neutralising mAbs and then challenged with SARS-CoV-2. Recombinant VSV expressing the spike protein of SARS-CoV-2 was utilised in an in vitro system to select for antibody escape variants. Surface plasmon resonance measurements were performed to characterise the binding affinity and epitope of various mAbs. Fc-mediated effector functions of neutralising and non-neutralising mAb combinations were determined via multiple in vitro assays.

FINDINGS

Few of the mAb treated and infected hamsters experienced breakthrough infections, which derived from mutated virus that emerged in vivo. We developed an in vitro antibody escape assay that recapitulated the in vivo situation and we found that somatic hypermutations (SHM) affected the profile of viral escape hotspots that mAbs selected for. Pairwise combination of mAbs binding non-overlapping epitopes suppressed the emergence of viral mutants. The formulation with a third, non-neutralising mAb enhanced the Fc-mediated effector functions of the mAb treatment in an additive manner.

INTERPRETATION

We conclude that treatment with single mAbs rapidly leads to the formation of novel virus variants. An important function of SHM is to suppress the emergence of viral antibody escape variants. Our data suggest that the anticipatory B cell memory can be harnessed to design combinations of SARS-CoV-2 neutralising mAbs that have a reduced risk to induce viral escape.

FUNDING

This study was supported by public funding from the German Research Foundation (DFG), the Federal Ministry of Education and Research (BMBF), the COVID-19-Research Network of the State of Lower Saxony (COFONI), the German Centre for Infection Research (DZIF), and the Helmholtz Association of German Research Centres.

Evolution of Antiviral Drug Resistance in SARS-CoV-2

The COVID-19 pandemic has had a significant impact and continues to alarm the entire world due to the rapid emergence of new variants, even after mass vaccinations. There is still an urgent need for new antivirals or strategies to combat the SARS-CoV-2 infections; however, we have success stories with nirmatrelvir. Drug repurposing and drug discovery may lead to a successful SARS-CoV-2 antiviral; however, rapid drug use may cause unexpected mutations and antiviral drug resistance. Conversely, novel variants of the SARS-CoV-2 can diminish the neutralizing efficacy of vaccines, thereby enhancing viral fitness and increasing the likelihood of drug resistance emergence. Additionally, the disposal of antivirals in wastewater also contributes to drug resistance. Overall, the present review summarizes the strategies and mechanisms involved in the development of drug resistance in SARS-CoV-2. Understanding the mechanism of antiviral resistance is crucial to mitigate the significant healthcare threat and to develop effective therapeutics against drug resistance.

Computationally designed proteins mimic antibody immune evasion in viral evolution

Recurrent waves of viral infection necessitate vaccines and therapeutics that remain effective against emerging viruses. Our ability to evaluate interventions is currently limited to assessments against past or circulating variants, which likely differ in their immune escape potential compared with future variants. To address this, we developed EVE-Vax, a computational method for designing antigens that foreshadow immune escape observed in future viral variants. We designed 83 SARS-CoV-2 spike proteins that transduced ACE2-positive cells and displayed neutralization resistance comparable to variants that emerged up to 12 months later in the COVID-19 pandemic. Designed spikes foretold antibody escape from B.1-BA.4/5 bivalent booster sera seen in later variants. The designed constructs also highlighted the increased neutralization breadth elicited by nanoparticle-based, compared with mRNA-based, boosters in non-human primates. Our approach offers targeted panels of synthetic proteins that map the immune landscape for early vaccine and therapeutic evaluation against future viral strains.

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.

Exploring Diverse Binding Mechanisms of Broadly Neutralizing Antibodies S309, S304, CYFN-1006 and VIR-7229 Targeting SARS-CoV-2 Spike Omicron Variants: Integrative Computational Modeling Reveals Balance of Evolutionary and Dynamic Adaptability in Shaping Molecular Determinants of Immune Escape

Evolution of SARS-CoV-2 has led to the emergence of variants with increased immune evasion capabilities, posing significant challenges to antibody-based therapeutics and vaccines. The cross-neutralization activity of antibodies against Omicron variants is governed by a complex and delicate interplay of multiple energetic factors and interaction contributions. In this study, we conducted a comprehensive analysis of the interactions between the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein and four neutralizing antibodies S309, S304, CYFN1006, and VIR-7229. Using integrative computational modeling that combined all-atom molecular dynamics (MD) simulations, mutational scanning, and MM-GBSA binding free energy calculations, we elucidated the structural, energetic, and dynamic determinants of antibody binding. Our findings reveal distinct dynamic binding mechanisms and evolutionary adaptation driving broad neutralization effect of these antibodies. We show that S309 targets conserved residues near the ACE2 interface, leveraging synergistic van der Waals and electrostatic interactions, while S304 focuses on fewer but sensitive residues, making it more susceptible to escape mutations. The analysis of CYFN-1006.1 and CYFN-1006.2 antibody binding highlights broad epitope coverage with critical anchors at T345, K440, and T346, enhancing its efficacy against variants carrying the K356T mutation which caused escape from S309 binding. Our analysis of broadly potent VIR-7229 antibody binding to XBB.1.5 and EG.5 Omicron variants emphasized a large and structurally complex epitope, demonstrating certain adaptability and compensatory effects to F456L and L455S mutations. Mutational profiling identified key residues crucial for antibody binding, including T345, P337, and R346 for S309, and T385 and K386 for S304, underscoring their roles as evolutionary "weak spots" that balance viral fitness and immune evasion. The results of this energetic analysis demonstrate a good agreement between the predicted binding hotspots and critical mutations with respect to the latest experiments on average antibody escape scores. The results of this study dissect distinct energetic mechanisms of binding and importance of targeting conserved residues and diverse epitopes to counteract viral resistance. Broad-spectrum antibodies CYFN1006 and VIR-7229 maintain efficacy across multiple variants and achieve neutralization by targeting convergent evolution hotspots while enabling tolerance to mutations in these positions through structural adaptability and compensatory interactions at the binding interface. The results of this study underscore the diversity of binding mechanisms employed by different antibodies and molecular basis for high affinity and excellent neutralization activity of the latest generation of antibodies.

Deep mutational learning for the selection of therapeutic antibodies resistant to the evolution of Omicron variants of SARS-CoV-2

Most antibodies for treating COVID-19 rely on binding the receptor-binding domain (RBD) of SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2). However, Omicron and its sub-lineages, as well as other heavily mutated variants, have rendered many neutralizing antibodies ineffective. Here we show that antibodies with enhanced resistance to the evolution of SARS-CoV-2 can be identified via deep mutational learning. We constructed a library of full-length RBDs of Omicron BA.1 with high mutational distance and screened it for binding to the angiotensin-converting-enzyme-2 receptor and to neutralizing antibodies. After deep-sequencing the library, we used the data to train ensemble deep-learning models for the prediction of the binding and escape of a panel of eight therapeutic antibody candidates targeting a diverse range of RBD epitopes. By using in silico evolution to assess antibody breadth via the prediction of the binding and escape of the antibodies to millions of Omicron sequences, we found combinations of two antibodies with enhanced and complementary resistance to viral evolution. Deep learning may enable the development of therapeutic antibodies that remain effective against future SARS-CoV-2 variants.

A systematic evaluation of the language-of-viral-escape model using multiple machine learning frameworks

Predicting the evolutionary patterns of emerging and endemic viruses is key for mitigating their spread. In particular, it is critical to rapidly identify mutations with the potential for immune escape or increased disease burden. Knowing which circulating mutations pose a concern can inform treatment or mitigation strategies such as alternative vaccines or targeted social distancing. In 2021, Hie B, Zhong ED, Berger B, Bryson B. 2021 Learning the language of viral evolution and escape. Science 371, 284-288. (doi:10.1126/science.abd7331) proposed that variants of concern can be identified using two quantities extracted from protein language models, grammaticality and semantic change. These quantities are defined by analogy to concepts from natural language processing. Grammaticality is intended to be a measure of whether a variant viral protein is viable, and semantic change is intended to be a measure of potential for immune escape. Here, we systematically test this hypothesis, taking advantage of several high-throughput datasets that have become available, and also comparing this model with several more recently published machine learning models. We find that grammaticality can be a measure of protein viability, though methods that are trained explicitly to predict mutational effects appear to be more effective. By contrast, we do not find compelling evidence that semantic change is a useful tool for identifying immune escape mutations.

SARS-CoV-2: The Interplay Between Evolution and Host Immunity

The persistence of SARS-CoV-2 infections at a global level reflects the repeated emergence of variant strains encoding unique constellations of mutations. These variants have been generated principally because of a dynamic host immune landscape, the countermeasures deployed to combat disease, and selection for enhanced infection of the upper airway and respiratory transmission. The resulting viral diversity creates a challenge for vaccination efforts to maintain efficacy, especially regarding humoral aspects of protection. Here, we review our understanding of how SARS-CoV-2 has evolved during the pandemic, the immune mechanisms that confer protection, and the impact viral evolution has had on transmissibility and adaptive immunity elicited by natural infection and/or vaccination. Evidence suggests that SARS-CoV-2 evolution initially selected variants with increased transmissibility but currently is driven by immune escape. The virus likely will continue to drift to maintain fitness until countermeasures capable of disrupting transmission cycles become widely available.

Few-Shot Viral Variant Detection via Bayesian Active Learning and Biophysics

The early detection of high-fitness viral variants is critical for pandemic response, yet limited experimental resources at the onset of variant emergence hinder effective identification. To address this, we introduce an active learning framework that integrates protein language model ESM3, Gaussian process with uncertainty estimation, and a biophysical model to predict the fitness of novel variants in a few-shot learning setting. By benchmarking on past SARS-CoV-2 data, we demonstrate that our methods accelerates the identification of high-fitness variants by up to fivefold compared to random sampling while requiring experimental characterization of fewer than 1% of possible variants. We also demonstrate that our framework benchmarked on deep mutational scans effectively identifies sites that are frequently mutated during natural viral evolution with a predictive advantage of up to two years compared to baseline strategies, particularly those enabling antibody escape while preserving ACE2 binding. Through systematic analysis of different acquisition strategies, we show that incorporating uncertainty in variant selection enables broader exploration of the sequence landscape, leading to the discovery of evolutionarily distant but potentially dangerous variants. Our results suggest that this framework could serve as an effective early warning system for identifying concerning SARS-CoV-2 variants and potentially emerging viruses with pandemic potential before they achieve widespread circulation.

Egress-enhancing mutation reveals inefficiency of non-enveloped virus cell exit

Viruses encounter a range of selective pressures, but inefficiencies during replication can be masked. To uncover factors that limit viral replication, we used forward genetics to enrich for a murine norovirus (MNV) mutant with faster replication. We sequentially harvested the earliest progeny in cultured cells and identified a single amino acid change in the viral NS3 protein, K40R, that was sufficient to enhance replication speed. We found that the NS3-K40R virus induced earlier cell death and viral egress compared with wild-type virus. Mechanistically, NS3-K40R protein disrupted membranes more efficiently than wild-type NS3 protein, potentially contributing to increased mitochondrial dysfunction and cell death. Mice infected with NS3-K40R virus had increased titers, suggesting that increasing egress did not reduce fitness in vivo. Overall, by using a forward genetic approach, we identified a previously unknown inefficiency in norovirus egress and provide new insights into selective pressures that influence viral replication and evolution.

Simian Immunodeficiency Virus-Based Virus-like Particles Are an Efficient Tool to Induce Persistent Anti-SARS-CoV-2 Spike Neutralizing Antibodies and Specific T Cells in Mice

Background/Objectives: Virus-like particles (VLPs) represent an attractive platform for delivering vaccine formulations, combining a high biosafety profile with a potent immune-stimulatory ability. VLPs are non-infectious, non-replicating, self-assembling nanostructures that can be exploited to efficiently expose membrane-tethered glycoproteins such as the SARS-CoV-2 Spike (S) protein, the main target of approved preventive vaccines. Here, we describe the development and preclinical validation of Simian Immunodeficiency Virus (SIV)-based GFP-labeled VLPs displaying S from the B.1.617.2 (Delta) variant (VLP/S-Delta) for inducing persistent anti-SARS-CoV-2 neutralizing antibodies (nAbs) and S-specific T cell responses in mice. Methods: SIV-derived VLP/S-Delta were produced by co-transfecting a plasmid expressing SIVGag-GFP, required for VLP assembly and quantification by flow virometry, a plasmid encoding the Delta S protein deleted in the cytoplasmic tail (CT), to improve membrane binding, and a VSV.G-expressing plasmid, to enhance VLP uptake. Recovered VLPs were titrated by flow virometry and characterized in vitro by transmission electron microscopy (TEM) and confocal microscopy (CLSM). BALB/c mice were immunized intramuscularly with VLP/S-Delta following a prime-boost regimen, and humoral and cellular immune responses were assessed. Results: VLP/S-Delta were efficiently pseudotyped with CT-truncated S-Delta. After BALB/c priming, VLP/S-Delta elicited both specific anti-RBD IgGs and anti-Delta nAbs that significantly increased after the boost and were maintained over time. The prime-boost vaccination induced similar levels of cross-nAbs against the ancestral Wuhan-Hu-1 strain as well as cross-nAbs against Omicron BA.1, BA.2 and BA.4/5 VoCs, albeit at lower levels. Moreover, immunization with VLP/S-Delta induced S-specific IFNγ-producing T cells. Conclusions: These data suggest that SIV-based VLPs are an appropriate delivery system for the elicitation of efficient and sustained humoral and cellular immunity in mice, paving the way for further improvements in the immunogen design to enhance the quality and breadth of immune responses against different viral glycoproteins.

SARS-CoV-2 drug resistance and therapeutic approaches

In light of the transition of COVID-19 from a pandemic to an endemic phase, there is still a dire need to address challenges associated with drug resistance, particularly among immunocompromised and high-risk populations. This review explores the current state of research on SARS-CoV-2 drug resistance and underscores the ongoing need for effective therapeutic strategies. It critically evaluates existing knowledge on resistance mechanisms and therapeutic options, aiming to consolidate information and highlight areas for future research. By examining the complex interactions between the virus and its host, the review advocates for a multifaceted approach, including combination therapies, targeted drug development, and continuous surveillance of viral mutations. It also emphasizes the impact of evolving viral variants on antiviral efficacy and suggests adaptive treatment protocols. This review aims to enhance our understanding of SARS-CoV-2 drug resistance and contribute to more effective management of COVID-19 through a discussion of promising strategies such as drug repurposing and combination therapies.

Long-Term Immune Consequences of Initial SARS-CoV-2 A.23.1 Exposure: A Longitudinal Study of Antibody Responses and Cross-Neutralization in a Ugandan Cohort

Background: This study assessed the long-term dynamics of neutralizing antibodies in a Ugandan cohort primarily exposed to the A.23.1 SARS-CoV-2 variant, examining how this shaped immune breadth and potency against diverse strains following infection and prototype-based vaccination. Methods: We conducted a 427-day retrospective analysis of 41 participants across multiple SARS-CoV-2 waves, assessing binding and neutralizing antibody responses using in-house ELISA and pseudotyped virus neutralization assays. We quantified immune responses to key SARS-CoV-2 variants, A.23.1, D614G, Delta, and BA.4, capturing evolving immunity across the pandemic. Results: Neutralizing antibody titers against A.23.1 remained significantly higher than those against D614G, Delta, and BA.4, highlighting the solid immune memory following A.23.1 infection. Consistently lower titers were observed for BA.4 across all time points, aligning with its strong immune-evasion capability. Correlations between neutralizing titers and spike-directed IgG (S-IgG) concentrations were significantly stronger for A.23.1 than for D614G, with no correlation for BA.4. ChAdOx1-S vaccination substantially elevated the neutralizing titers across all variants, most notably BA.4, highlighting the essential role of vaccination in boosting immunity, even in individuals with initially low titers. Conclusions: Initial exposure to the A.23.1 variant triggered potent immune responses, shaping neutralizing antibody dynamics during subsequent exposures. These findings highlight the importance of accounting for early viral exposures in vaccine development and public health planning. The distinctly lower immune response to BA.4 highlights the need for continuous antigenic monitoring and timely vaccine updates for protection against emerging variants. Vaccination remains essential for reinforcing and sustaining immunity against evolving variants.

Pooled PPIseq: Screening the SARS-CoV-2 and human interface with a scalable multiplexed protein-protein interaction assay platform

Protein-Protein Interactions (PPIs) are a key interface between virus and host, and these interactions are important to both viral reprogramming of the host and to host restriction of viral infection. In particular, viral-host PPI networks can be used to further our understanding of the molecular mechanisms of tissue specificity, host range, and virulence. At higher scales, viral-host PPI screening could also be used to screen for small-molecule antivirals that interfere with essential viral-host interactions, or to explore how the PPI networks between interacting viral and host genomes co-evolve. Current high-throughput PPI assays have screened entire viral-host PPI networks. However, these studies are time consuming, often require specialized equipment, and are difficult to further scale. Here, we develop methods that make larger-scale viral-host PPI screening more accessible. This approach combines the mDHFR split-tag reporter with the iSeq2 interaction-barcoding system to permit massively-multiplexed PPI quantification by simple pooled engineering of barcoded constructs, integration of these constructs into budding yeast, and fitness measurements by pooled cell competitions and barcode-sequencing. We applied this method to screen for PPIs between SARS-CoV-2 proteins and human proteins, screening in triplicate >180,000 ORF-ORF combinations represented by >1,000,000 barcoded lineages. Our results complement previous screens by identifying 74 putative PPIs, including interactions between ORF7A with the taste receptors TAS2R41 and TAS2R7, and between NSP4 with the transmembrane KDELR2 and KDELR3. We show that this PPI screening method is highly scalable, enabling larger studies aimed at generating a broad understanding of how viral effector proteins converge on cellular targets to effect replication.

Epitope mapping via in vitro deep mutational scanning methods and its applications

Epitope mapping is a technique employed to define the region of an antigen that elicits an immune response, providing crucial insight into the structural architecture of the antigen as well as epitope-paratope interactions. With this breadth of knowledge, immunotherapies, diagnostics, and vaccines are being developed with a rational and data-supported design. Traditional epitope mapping methods are laborious, time-intensive, and often lack the ability to screen proteins in a high-throughput manner or provide high resolution. Deep mutational scanning (DMS), however, is revolutionizing the field as it can screen all possible single amino acid mutations and provide an efficient and high-throughput way to infer the structures of both linear and three-dimensional epitopes with high resolution. Currently, more than 50 publications take this approach to efficiently identify enhancing or escaping mutations, with many then employing this information to rapidly develop broadly neutralizing antibodies, T-cell immunotherapies, vaccine platforms, or diagnostics. We provide a comprehensive review of the approaches to accomplish epitope mapping while also providing a summation of the development of DMS technology and its impactful applications.

Structure and dynamics of the interaction of Delta and Omicron BA.1 SARS-CoV-2 variants with REGN10987 Fab reveal mechanism of antibody action

Study of mechanisms by which antibodies recognize different viral strains is necessary for the development of new drugs and vaccines to treat COVID-19 and other infections. Here, we report 2.5 Å cryo-EM structure of the SARS-CoV-2 Delta trimeric S-protein in complex with Fab of the recombinant analog of REGN10987 neutralizing antibody. S-protein adopts "two RBD-down and one RBD-up" conformation. Fab interacts with RBDs in both conformations, blocking the recognition of angiotensin converting enzyme-2. Three-dimensional variability analysis reveals high mobility of the RBD/Fab regions. Interaction of REGN10987 with Wuhan, Delta, Omicron BA.1, and mutated variants of RBDs is analyzed by microscale thermophoresis, molecular dynamics simulations, and ΔG calculations with umbrella sampling and one-dimensional potential of mean force. Variability in molecular dynamics trajectories results in a large scatter of calculated ΔG values, but Boltzmann weighting provides an acceptable correlation with experiment. REGN10987 evasion of the Omicron variant is found to be due to the additive effect of the N440K and G446S mutations located at the RBD/Fab binding interface with a small effect of Q498R mutation. Our study explains the influence of known-to-date SARS-CoV-2 RBD mutations on REGN10987 recognition and highlights the importance of dynamics data beyond the static structure of the RBD/Fab complex.

Reading the repertoire: Progress in adaptive immune receptor analysis using machine learning

The adaptive immune system holds invaluable information on past and present immune responses in the form of B and T cell receptor sequences, but we are limited in our ability to decode this information. Machine learning approaches are under active investigation for a range of tasks relevant to understanding and manipulating the adaptive immune receptor repertoire, including matching receptors to the antigens they bind, generating antibodies or T cell receptors for use as therapeutics, and diagnosing disease based on patient repertoires. Progress on these tasks has the potential to substantially improve the development of vaccines, therapeutics, and diagnostics, as well as advance our understanding of fundamental immunological principles. We outline key challenges for the field, highlighting the need for software benchmarking, targeted large-scale data generation, and coordinated research efforts.

High-throughput specificity profiling of antibody libraries using ribosome display and microfluidics

In this work, we developed PolyMap (polyclonal mapping), a high-throughput method for mapping protein-protein interactions. We demonstrated the mapping of thousands of antigen-antibody interactions between diverse antibody libraries isolated from convalescent and vaccinated COVID-19 donors and a set of clinically relevant SARS-CoV-2 spike variants. We identified over 150 antibodies with a variety of distinctive binding patterns toward the antigen variants and found a broader binding profile, including targeting of the Omicron variant, in the antibody repertoires of more recent donors. We then used these data to select mixtures of a small number of clones with complementary reactivity that together provide strong potency and broad neutralization. PolyMap is a generalizable platform that can be used for one-pot epitope mapping, immune repertoire profiling, and therapeutic design and, in the future, could be expanded to other families of interacting proteins.

Isolation and escape mapping of broadly neutralizing antibodies against emerging delta-coronaviruses

Porcine delta-coronavirus (PDCoV) spillovers were recently detected in febrile children, underscoring the recurrent zoonoses of divergent CoVs. To date, no vaccines or specific therapeutics are approved for use in humans against PDCoV. To prepare for possible future PDCoV epidemics, we isolated PDCoV spike (S)-directed monoclonal antibodies (mAbs) from humanized mice and found that two, designated PD33 and PD41, broadly neutralized a panel of PDCoV variants. Cryoelectron microscopy (cryo-EM) structures of PD33 and PD41 in complex with the S receptor-binding domain (RBD) and ectodomain trimer revealed the epitopes recognized by these mAbs, rationalizing their broad inhibitory activity. We show that both mAbs competitively interfere with host aminopeptidase N binding to neutralize PDCoV and used deep-mutational scanning epitope mapping to associate RBD antigenic sites with mAb-mediated neutralization potency. Our results indicate a PD33-PD41 mAb cocktail may heighten the barrier to escape. PD33 and PD41 are candidates for clinical advancement against future PDCoV outbreaks.

Dynamic expedition of leading mutations in SARS-CoV-2 spike glycoproteins

The continuous evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which caused the recent pandemic, has generated countless new variants with varying fitness. Mutations of the spike glycoprotein play a particularly vital role in shaping its evolutionary trajectory, as they have the capability to alter its infectivity and antigenicity. We present a time-resolved statistical method, Dynamic Expedition of Leading Mutations (deLemus), to analyze the evolutionary dynamics of the SARS-CoV-2 spike glycoprotein. The proposed L -index of the deLemus method is effective in quantifying the mutation strength of each amino acid site and outlining evolutionarily significant sites, allowing the comprehensive characterization of the evolutionary mutation pattern of the spike glycoprotein.

Backstage Heroes-Yeast in COVID-19 Research

The extremely rapid development of understanding and technology that led to the containment of the COVID-19 pandemic resulted from collaborative efforts in the fields of Betacoronavirus pandemicum (SARS-CoV-2) biology, pharmacology, vaccinology, and medicine. Perhaps surprisingly, much of the research was conducted using simple and efficient yeast models. In this manuscript, we describe how yeast, eukaryotic microorganisms, have been used to research this global challenge, focusing on the therapeutic potential of the studies discussed herein. Thus, we outline the role of yeast in studying viral protein interactions with the host cell proteome, including the binding of the SARS-CoV-2 virus spike protein to the human ACE2 receptor and its modulation. The production and exploration of viral antigens in yeast systems, which led to the development of two approved COVID-19 vaccines, are also detailed. Moreover, yeast platforms facilitating the discovery and production of single-domain antibodies (nanobodies) against SARS-CoV-2 are described. Methods guiding modern and efficient drug discovery are explained at length. In particular, we focus on studies designed to search for inhibitors of the main protease (Mpro), a unique target for anti-coronaviral therapies. We highlight the adaptability of the techniques used, providing opportunities for rapid modification and implementation alongside the evolution of the SARS-CoV-2 virus. Approaches introduced in yeast systems that may have universal potential application in studies of emerging viral diseases are also described.

A protein vaccine of RBD integrated with immune evasion mutation shows broad protection against SARS-CoV-2

Variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continue to emerge and evade immunity, resulting in breakthrough infections in vaccinated populations. There is an urgent need for the development of vaccines with broad protective effects. In this study, we selected hotspot mutations in the receptor-binding domain (RBD) that contribute to immune escape properties and integrated them into the original RBD protein to obtain a complex RBD protein (cRBD), and we found cRBDs have broad protective effects against SARS-CoV-2 variants. Three cRBDs were designed in our study. Compared with the BA.1 RBD protein, the cRBDs induced the production of higher levels of broader-spectrum neutralizing antibodies, suggesting stronger and broader protective efficacy. In viral challenge experiments, cRBDs were more effective than BA.1 RBD in attenuating lung pathologic injury. Among the three constructs, cRBD3 showed optimal broad-spectrum and protective effects and is a promising candidate for a broad-spectrum SARS-CoV-2 vaccine. In conclusion, immunization with cRBDs triggered immunity against a wide range of variants, including those that emerged after we had completed designing the cRBDs. This study preliminarily explores and validates the feasibility of incorporating hotspot mutations that contribute to immune evasion into the RBD to expand the activity spectrum of antigen-induced antibodies.

Exploring the ability of the MD+FoldX method to predict SARS-CoV-2 antibody escape mutations using large-scale data

Antibody escape mutations pose a significant challenge to the effectiveness of vaccines and antibody-based therapies. The ability to predict these escape mutations with computer simulations would allow us to detect threats early and develop effective countermeasures, but a lack of large-scale experimental data has hampered the validation of these calculations. In this study, we evaluate the ability of the MD+FoldX molecular modeling method to predict escape mutations by leveraging a large deep mutational scanning dataset, focusing on the SARS-CoV-2 receptor binding domain. Our results show a positive correlation between predicted and experimental data, indicating that mutations with reduced predicted binding affinity correlate moderately with higher experimental escape fractions. We also demonstrate that higher precision can be achieved using affinity cutoffs tailored to distinct SARS-CoV-2 antibodies from four different classes rather than a one-size-fits-all approach. Further, we suggest that the quartile values of optimized cutoffs reported for each class in this study can serve as a valuable guide for future work on escape mutation predictions. We find that 70% of the systems surpass the 50% precision mark, and demonstrate success in identifying mutations present in significant variants of concern and variants of interest. Despite promising results for some systems, our study highlights the challenges in comparing predicted and experimental values. It also emphasizes the need for new binding affinity methods with improved accuracy that are fast enough to estimate hundreds to thousands of antibody-antigen binding affinities.

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.

Characterisation of the antibody-mediated selective pressure driving intra-host evolution of SARS-CoV-2 in prolonged infection

Neutralising antibodies against the SARS-CoV-2 spike (S) protein are major determinants of protective immunity, though insufficient antibody responses may cause the emergence of escape mutants. We studied the humoral immune response causing intra-host evolution in a B-cell depleted, haemato-oncologic patient experiencing clinically severe, prolonged SARS-CoV-2 infection with a virus of lineage B.1.177.81. Following bamlanivimab treatment at an early stage of infection, the patient developed a bamlanivimab-resistant mutation, S:S494P. After five weeks of apparent genetic stability, the emergence of additional substitutions and deletions within the N-terminal domain (NTD) and the receptor binding domain (RBD) of S was observed. Notably, the composition and frequency of escape mutations changed in a short period with an unprecedented dynamic. The triple mutant S:Delta141-4 E484K S494P became dominant until virus elimination. Routine serology revealed no evidence of an antibody response in the patient. A detailed analysis of the variant-specific immune response by pseudotyped virus neutralisation test, surrogate virus neutralisation test, and immunoglobulin-capture enzyme immunoassay showed that the onset of an IgM-dominated antibody response coincided with the appearance of escape mutations. The formation of neutralising antibodies against S:Delta141-4 E484K S494P correlated with virus elimination. One year later, the patient experienced clinically mild re-infection with Omicron BA.1.18, which was treated with sotrovimab and resulted in an increase in Omicron-reactive antibodies. In conclusion, the onset of an IgM-dominated endogenous immune response in an immunocompromised patient coincided with the appearance of additional mutations in the NTD and RBD of S in a bamlanivimab-resistant virus. Although virus elimination was ultimately achieved, this humoral immune response escaped detection by routine diagnosis and created a situation temporarily favouring the rapid emergence of various antibody escape mutants with known epidemiological relevance.

Yeast-based screening platforms to understand and improve human health

Detailed molecular understanding of the human organism is essential to develop effective therapies. Saccharomyces cerevisiae has been used extensively for acquiring insights into important aspects of human health, such as studying genetics and cell-cell communication, elucidating protein-protein interaction (PPI) networks, and investigating human G protein-coupled receptor (hGPCR) signaling. We highlight recent advances and opportunities of yeast-based technologies for cost-efficient chemical library screening on hGPCRs, accelerated deciphering of PPI networks with mating-based screening and selection, and accurate cell-cell communication with human immune cells. Overall, yeast-based technologies constitute an important platform to support basic understanding and innovative applications towards improving human health.

Delineating the functional activity of antibodies with cross-reactivity to SARS-CoV-2, SARS-CoV-1 and related sarbecoviruses

The recurring spillover of pathogenic coronaviruses and demonstrated capacity of sarbecoviruses, such SARS-CoV-2, to rapidly evolve in humans underscores the need to better understand immune responses to this virus family. For this purpose, we characterized the functional breadth and potency of antibodies targeting the receptor binding domain (RBD) of the spike glycoprotein that exhibited cross-reactivity against SARS-CoV-2 variants, SARS-CoV-1 and sarbecoviruses from diverse clades and animal origins with spillover potential. One neutralizing antibody, C68.61, showed remarkable neutralization breadth against both SARS-CoV-2 variants and viruses from different sarbecovirus clades. C68.61, which targets a conserved RBD class 5 epitope, did not select for escape variants of SARS-CoV-2 or SARS-CoV-1 in culture nor have predicted escape variants among circulating SARS-CoV-2 strains, suggesting this epitope is functionally constrained. We identified 11 additional SARS-CoV-2/SARS-CoV-1 cross-reactive antibodies that target the more sequence conserved class 4 and class 5 epitopes within RBD that show activity against a subset of diverse sarbecoviruses with one antibody binding every single sarbecovirus RBD tested. A subset of these antibodies exhibited Fc-mediated effector functions as potent as antibodies that impact infection outcome in animal models. Thus, our study identified antibodies targeting conserved regions across SARS-CoV-2 variants and sarbecoviruses that may serve as therapeutics for pandemic preparedness as well as blueprints for the design of immunogens capable of eliciting cross-neutralizing responses.

COVID-19 mutations: An overview

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) belongs to the genus Beta coronavirus and the family of Coronaviridae. It is a positive-sense, non-segmented single-strand RNA virus. Four common types of human coronaviruses circulate globally, particularly in the fall and winter seasons. They are responsible for 10%-30% of all mild upper respiratory tract infections in adults. These are 229E, NL63 of the Alfacoronaviridae family, OC43, and HKU1 of the Betacoronaviridae family. However, there are three highly pathogenic human coronaviruses: SARS-CoV-2, Middle East respiratory syndrome coronavirus, and the latest pandemic caused by the SARS-CoV-2 infection. All viruses, including SARS-CoV-2, have the inherent tendency to evolve. SARS-CoV-2 is still evolving in humans. Additionally, due to the development of herd immunity, prior infection, use of medication, vaccination, and antibodies, the viruses are facing immune pressure. During the replication process and due to immune pressure, the virus may undergo mutations. Several SARS-CoV-2 variants, including the variants of concern (VOCs), such as B.1.1.7 (Alpha), B.1.351 (Beta), B.1.617/B.1.617.2 (Delta), P.1 (Gamma), and B.1.1.529 (Omicron) have been reported from various parts of the world. These VOCs contain several important mutations; some of them are on the spike proteins. These mutations may lead to enhanced infectivity, transmissibility, and decreased neutralization efficacy by monoclonal antibodies, convalescent sera, or vaccines. Mutations may also lead to a failure of detection by molecular diagnostic tests, leading to a delayed diagnosis, increased community spread, and delayed treatment. We searched PubMed, EMBASE, Covariant, the Stanford variant Database, and the CINAHL from December 2019 to February 2023 using the following search terms: VOC, SARS-CoV-2, Omicron, mutations in SARS-CoV-2, etc. This review discusses the various mutations and their impact on infectivity, transmissibility, and neutralization efficacy.

Deep mutational scanning reveals functional constraints and antibody-escape potential of Lassa virus glycoprotein complex

Lassa virus is estimated to cause thousands of human deaths per year, primarily due to spillovers from its natural host, Mastomys rodents. Efforts to create vaccines and antibody therapeutics must account for the evolutionary variability of the Lassa virus's glycoprotein complex (GPC), which mediates viral entry into cells and is the target of neutralizing antibodies. To map the evolutionary space accessible to GPC, we used pseudovirus deep mutational scanning to measure how nearly all GPC amino-acid mutations affected cell entry and antibody neutralization. Our experiments defined functional constraints throughout GPC. We quantified how GPC mutations affected neutralization with a panel of monoclonal antibodies. All antibodies tested were escaped by mutations that existed among natural Lassa virus lineages. Overall, our work describes a biosafety-level-2 method to elucidate the mutational space accessible to GPC and shows how prospective characterization of antigenic variation could aid the design of therapeutics and vaccines.

Case reports of persistent SARS-CoV-2 infection outline within-host viral evolution in immunocompromised patients

BACKGROUND

SARS-CoV-2 is responsible for the ongoing global pandemic, and the continuous emergence of novel variants threatens fragile populations, such as immunocompromised patients. This subgroup of patients seems to be seriously affected by intrahost viral changes, as the pathogens, which are keen to cause replication inefficiency, affect the impaired immune system, preventing efficient clearance of the virus. Therefore, these patients may represent an optimal reservoir for the development of new circulating SARS-CoV-2 variants. The following study aimed to investigate genomic changes in SARS-CoV-2-positive immunocompromised patients over time.

METHODS

SARS-CoV-2-positive nasopharyngeal swabs were collected at different time points for each patient (patient A and patient B), extracted and then analyzed through next-generation sequencing (NGS). The resulting sequences were examined to determine mutation frequencies, describing viral evolution over time.

CASE PRESENTATION

Patient A was a 53-year-old patient with onco-hematological disease with prolonged infection lasting for 51 days from May 28th to July 18th, 2022. Three confirmed SARS-CoV-2-positive samples were collected on May 28th, June 15th and July 4th. Patient B was 75 years old and had onco-hematological disease with prolonged infection lasting for 146 days. Two confirmed positive SARS-CoV-2 samples were collected at the following time points: May 21st and August 18th.

CONCLUSION

Heat map construction provided evidence of gain and/or loss of mutations over time for both patients, suggesting within-host genomic evolution of the virus. In addition, mutation polymorphisms and changes in the SARS-CoV-2 lineage were observed in Patient B. Sequence analysis revealed high mutational pattern variability, reflecting the high complexity of viral replication dynamics in fragile patients.

SARS-CoV-2 variant replacement constrains vaccine-specific viral diversification

Coronavirus disease 2019 (COVID-19) vaccine breakthrough infections have been important for all circulating severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant periods, but the contribution of vaccine-specific SARS-CoV-2 viral diversification to vaccine failure remains unclear. This study analyzed 595 SARS-CoV-2 sequences collected from the Military Health System beneficiaries between December 2020 and April 2022 to investigate the impact of vaccination on viral diversity. By comparing sequences based on the vaccination status of the participant, we found limited evidence indicating that vaccination was associated with increased viral diversity in the SARS-CoV-2 spike, and we show little to no evidence of a substantial sieve effect within major variants; rather, we show that rapid variant replacement constrained intragenotype COVID-19 vaccine strain immune escape. These data suggest that, during past and perhaps future periods of rapid SARS-CoV-2 variant replacement, vaccine-mediated effects were subsumed with other drivers of viral diversity due to the massive scale of infections and vaccinations that occurred in a short time frame. However, our results also highlight some limitations of using sieve analysis methods outside of placebo-controlled clinical trials.

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.

Simulation-driven design of stabilized SARS-CoV-2 spike S2 immunogens

The full-length prefusion-stabilized SARS-CoV-2 spike (S) is the principal antigen of COVID-19 vaccines. Vaccine efficacy has been impacted by emerging variants of concern that accumulate most of the sequence modifications in the immunodominant S1 subunit. S2, in contrast, is the most evolutionarily conserved region of the spike and can elicit broadly neutralizing and protective antibodies. Yet, S2's usage as an alternative vaccine strategy is hampered by its general instability. Here, we use a simulation-driven approach to design S2-only immunogens stabilized in a closed prefusion conformation. Molecular simulations provide a mechanistic characterization of the S2 trimer's opening, informing the design of tryptophan substitutions that impart kinetic and thermodynamic stabilization. Structural characterization via cryo-EM shows the molecular basis of S2 stabilization in the closed prefusion conformation. Informed by molecular simulations and corroborated by experiments, we report an engineered S2 immunogen that exhibits increased protein expression, superior thermostability, and preserved immunogenicity against sarbecoviruses.

Cell-cell communication: new insights and clinical implications

Multicellular organisms are composed of diverse cell types that must coordinate their behaviors through communication. Cell-cell communication (CCC) is essential for growth, development, differentiation, tissue and organ formation, maintenance, and physiological regulation. Cells communicate through direct contact or at a distance using ligand-receptor interactions. So cellular communication encompasses two essential processes: cell signal conduction for generation and intercellular transmission of signals, and cell signal transduction for reception and procession of signals. Deciphering intercellular communication networks is critical for understanding cell differentiation, development, and metabolism. First, we comprehensively review the historical milestones in CCC studies, followed by a detailed description of the mechanisms of signal molecule transmission and the importance of the main signaling pathways they mediate in maintaining biological functions. Then we systematically introduce a series of human diseases caused by abnormalities in cell communication and their progress in clinical applications. Finally, we summarize various methods for monitoring cell interactions, including cell imaging, proximity-based chemical labeling, mechanical force analysis, downstream analysis strategies, and single-cell technologies. These methods aim to illustrate how biological functions depend on these interactions and the complexity of their regulatory signaling pathways to regulate crucial physiological processes, including tissue homeostasis, cell development, and immune responses in diseases. In addition, this review enhances our understanding of the biological processes that occur after cell-cell binding, highlighting its application in discovering new therapeutic targets and biomarkers related to precision medicine. This collective understanding provides a foundation for developing new targeted drugs and personalized treatments.

Protective non-neutralizing SARS-CoV-2 monoclonal antibodies

Recent studies show an important role for non-neutralizing anti-spike antibodies, including monoclonal antibodies (mAbs), in robustly protecting against SARS-CoV-2 infection. These mAbs use Fc-mediated functions such as complement activation, phagocytosis, and cellular cytotoxicity. There is an untapped potential for using non-neutralizing mAbs in durable antibody treatments; because of their available conserved epitopes, they may not be as sensitive to virus mutations as neutralizing mAbs. Here, we discuss evidence of non-neutralizing mAb-mediated protection against SARS-CoV-2 infection. We explore how non-neutralizing mAb Fc-mediated functions can be enhanced via novel antibody-engineering techniques. Important questions remain to be answered regarding the characteristics of protective non-neutralizing mAbs, including the models and assays used for study, the risks of ensuing detrimental inflammation, as well as the durability and mechanisms of protection.

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.

Impact of Missense Mutations on Spike Protein Stability and Binding Affinity in the Omicron Variant

The global effort to combat the COVID-19 pandemic faces ongoing uncertainty with the emergence of Variants of Concern featuring numerous mutations on the Spike (S) protein. In particular, the Omicron Variant is distinguished by 32 mutations, including 10 within its receptor-binding domain (RBD). These mutations significantly impact viral infectivity and the efficacy of vaccines and antibodies currently in use for therapeutic purposes. In our study, we employed structure-based computational saturation mutagenesis approaches to predict the effects of Omicron missense mutations on RBD stability and binding affinity, comparing them to the original Wuhan-Hu-1 strain. Our results predict that mutations such as G431W and P507W induce the most substantial destabilizations in the Wuhan-Hu-1-S/Omicron-S RBD. Notably, we postulate that mutations in the Omicron-S exhibit a higher percentage of enhancing binding affinity compared to Wuhan-S. We found that the mutations at residue positions G447, Y449, F456, F486, and S496 led to significant changes in binding affinity. In summary, our findings may shed light on the widespread prevalence of Omicron mutations in human populations. The Omicron mutations that potentially enhance their affinity for human receptors may facilitate increased viral binding and internalization in infected cells, thereby enhancing infectivity. This informs the development of new neutralizing antibodies capable of targeting Omicron's immune-evading mutations, potentially aiding in the ongoing battle against the COVID-19 pandemic.

Mammalian cell display with automated oligo design and library assembly allows for rapid residue level conformational epitope mapping

Precise epitope determination of therapeutic antibodies is of great value as it allows for further comprehension of mechanism of action, therapeutic responsiveness prediction, avoidance of unwanted cross reactivity, and vaccine design. The golden standard for discontinuous epitope determination is the laborious X-ray crystallography method. Here, we present a combinatorial method for rapid mapping of discontinuous epitopes by mammalian antigen display, eliminating the need for protein expression and purification. The method is facilitated by automated workflows and tailored software for antigen analysis and oligonucleotide design. These oligos are used in automated mutagenesis to generate an antigen receptor library displayed on mammalian cells for direct binding analysis by flow cytometry. Through automated analysis of 33930 primers an optimized single condition cloning reaction was defined allowing for mutation of all surface-exposed residues of the receptor binding domain of SARS-CoV-2. All variants were functionally expressed, and two reference binders validated the method. Furthermore, epitopes of three novel therapeutic antibodies were successfully determined followed by evaluation of binding also towards SARS-CoV-2 Omicron BA.2. We find the method to be highly relevant for rapid construction of antigen libraries and determination of antibody epitopes, especially for the development of therapeutic interventions against novel pathogens.

Structural basis of broad SARS-CoV-2 cross-neutralization by affinity-matured public antibodies

Descendants of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant now account for almost all SARS-CoV-2 infections. The Omicron variant and its sublineages have spike glycoproteins that are highly diverged from the pandemic founder and first-generation vaccine strain, resulting in significant evasion from monoclonal antibody therapeutics and vaccines. Understanding how commonly elicited antibodies can broaden to cross-neutralize escape variants is crucial. We isolate IGHV3-53, using "public" monoclonal antibodies (mAbs) from an individual 7 months post infection with the ancestral virus and identify antibodies that exhibit potent and broad cross-neutralization, extending to the BA.1, BA.2, and BA.4/BA.5 sublineages of Omicron. Deep mutational scanning reveals these mAbs' high resistance to viral escape. Structural analysis via cryoelectron microscopy of a representative broadly neutralizing antibody, CAB-A17, in complex with the Omicron BA.1 spike highlights the structural underpinnings of this broad neutralization. By reintroducing somatic hypermutations into a germline-reverted CAB-A17, we delineate the role of affinity maturation in the development of cross-neutralization by a public class of antibodies.

Biophysical principles predict fitness of SARS-CoV-2 variants

SARS-CoV-2 employs its spike protein's receptor binding domain (RBD) to enter host cells. The RBD is constantly subjected to immune responses, while requiring efficient binding to host cell receptors for successful infection. However, our understanding of how RBD's biophysical properties contribute to SARS-CoV-2's epidemiological fitness remains largely incomplete. Through a comprehensive approach, comprising large-scale sequence analysis of SARS-CoV-2 variants and the identification of a fitness function based on binding thermodynamics, we unravel the relationship between the biophysical properties of RBD variants and their contribution to viral fitness. We developed a biophysical model that uses statistical mechanics to map the molecular phenotype space, characterized by dissociation constants of RBD to ACE2, LY-CoV016, LY-CoV555, REGN10987, and S309, onto an epistatic fitness landscape. We validate our findings through experimentally measured and machine learning (ML) estimated binding affinities, coupled with infectivity data derived from population-level sequencing. Our analysis reveals that this model effectively predicts the fitness of novel RBD variants and can account for the epistatic interactions among mutations, including explaining the later reversal of Q493R. Our study sheds light on the impact of specific mutations on viral fitness and delivers a tool for predicting the future epidemiological trajectory of previously unseen or emerging low-frequency variants. These insights offer not only greater understanding of viral evolution but also potentially aid in guiding public health decisions in the battle against COVID-19 and future pandemics.

SARS-CoV-2 journey: from alpha variant to omicron and its sub-variants

The COVID-19 pandemic has affected hundreds of millions of individuals and caused more than six million deaths. The prolonged pandemic duration and the continual inter-individual transmissibility have contributed to the emergence of a wide variety of SARS-CoV-2 variants. Genomic surveillance and phylogenetic studies have shown that substantial mutations in crucial supersites of spike glycoprotein modulate the binding affinity of the evolved SARS-COV-2 lineages to ACE2 receptors and modify the binding of spike protein with neutralizing antibodies. The immunological spike mutations have been associated with differential transmissibility, infectivity, and therapeutic efficacy of the vaccines and the immunological therapies among the new variants. This review highlights the diverse genetic mutations assimilated in various SARS-CoV-2 variants. The implications of the acquired mutations related to viral transmission, infectivity, and COVID-19 severity are discussed. This review also addresses the effectiveness of human neutralizing antibodies induced by SARS-CoV-2 infection or immunization and the therapeutic antibodies against the ascended variants.

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

Immunization with mosaic-8b [60-mer 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 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 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.

Exploring the ability of the MD+FoldX method to predict SARS-CoV-2 antibody escape mutations using large-scale data

Antibody escape mutations pose a significant challenge to the effectiveness of vaccines and antibody-based therapies. The ability to predict these escape mutations with computer simulations would allow us to detect threats early and develop effective countermeasures, but a lack of large-scale experimental data has hampered the validation of these calculations. In this study, we evaluate the ability of the MD+FoldX molecular modeling method to predict escape mutations by leveraging a large deep mutational scanning dataset, focusing on the SARS-CoV-2 receptor binding domain. Our results show a positive correlation between predicted and experimental data, indicating that mutations with reduced predicted binding affinity correlate moderately with higher experimental escape fractions. We also demonstrate that better performance can be achieved using affinity cutoffs tailored to distinct antibody-antigen interactions rather than a one-size-fits-all approach. We find that 70% of the systems surpass the 50% precision mark, and demonstrate success in identifying mutations present in significant variants of concern and variants of interest. Despite promising results for some systems, our study highlights the challenges in comparing predicted and experimental values. It also emphasizes the need for new binding affinity methods with improved accuracy that are fast enough to estimate hundreds to thousands of antibody-antigen binding affinities.

Nanobody repertoire generated against the spike protein of ancestral SARS-CoV-2 remains efficacious against the rapidly evolving virus

To date, all major modes of monoclonal antibody therapy targeting SARS-CoV-2 have lost significant efficacy against the latest circulating variants. As SARS-CoV-2 omicron sublineages account for over 90% of COVID-19 infections, evasion of immune responses generated by vaccination or exposure to previous variants poses a significant challenge. A compelling new therapeutic strategy against SARS-CoV-2 is that of single-domain antibodies, termed nanobodies, which address certain limitations of monoclonal antibodies. Here, we demonstrate that our high-affinity nanobody repertoire, generated against wild-type SARS-CoV-2 spike protein (Mast et al., 2021), remains effective against variants of concern, including omicron BA.4/BA.5; a subset is predicted to counter resistance in emerging XBB and BQ.1.1 sublineages. Furthermore, we reveal the synergistic potential of nanobody cocktails in neutralizing emerging variants. Our study highlights the power of nanobody technology as a versatile therapeutic and diagnostic tool to combat rapidly evolving infectious diseases such as SARS-CoV-2.

Interaction analysis of SARS-CoV-2 omicron BA1 and BA2 of RBD with fifty monoclonal antibodies: Molecular dynamics approach

This report provides detailed insights into the interaction of fifty monoclonal antibodies with two recent Omicron variants, BA1 and BA2. It has been observed that numerous mutations in the receptor binding domain (RBD) result in significant structural changes in Omicron, enhancing its ability to mediate viral infections compared to other variants of concern. The following antibodies, namely JX3S304, 7KMG, 7CH4, 7BELCOVOX45, 7CDJ, 7C01, 7JX3S2H14, 6XCA, 7CDI, 7JMO, 7B3O, 6ZER, 6XC7CR3022, JX3S309, 6XC7CC123, 7CM4, 7KMI, 7L7EAZD8895, exhibit a superior binding affinity towards the Spike when compared to the reference CR3022. Four best-docked systems were subjected to further testing through molecular dynamics (MD) simulations. The MM/GBSA free energy for the top-scored complexes of BA1 variant are BA1_JX3S3O4, BA1_7KMI, BA1_7CH4, and BA1_7KMG, with respective values of -56.120 kcal/mol, -41.30 kcal/mol, -17.546 kcal/mol, and -8.527 kcal/mol; and of BA2 variant are BA2_JX3S3O4, BA2_7CM4, BA2_KMG, and BA2_7CH4, with respective values of -40.903 kcal/mol, -23.416 kcal/mol, -17.350 kcal/mol, and -5.460 kcal/mol. Detailed structural/energetic parameters, principal component analysis, and free energy landscape (FEL) studies reveal a significant decrease in antibody resistance due to the disappearance of numerous hydrogen bond interactions and various metastable states. We believe that these crucial mechanistic insights will contribute to breakthroughs in SARS-CoV-2 research.

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.

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.

CovEpiAb: a comprehensive database and analysis resource for immune epitopes and antibodies of human coronaviruses

Coronaviruses have threatened humans repeatedly, especially COVID-19 caused by SARS-CoV-2, which has posed a substantial threat to global public health. SARS-CoV-2 continuously evolves through random mutation, resulting in a significant decrease in the efficacy of existing vaccines and neutralizing antibody drugs. It is critical to assess immune escape caused by viral mutations and develop broad-spectrum vaccines and neutralizing antibodies targeting conserved epitopes. Thus, we constructed CovEpiAb, a comprehensive database and analysis resource of human coronavirus (HCoVs) immune epitopes and antibodies. CovEpiAb contains information on over 60 000 experimentally validated epitopes and over 12 000 antibodies for HCoVs and SARS-CoV-2 variants. The database is unique in (1) classifying and annotating cross-reactive epitopes from different viruses and variants; (2) providing molecular and experimental interaction profiles of antibodies, including structure-based binding sites and around 70 000 data on binding affinity and neutralizing activity; (3) providing virological characteristics of current and past circulating SARS-CoV-2 variants and in vitro activity of various therapeutics; and (4) offering site-level annotations of key functional features, including antibody binding, immunological epitopes, SARS-CoV-2 mutations and conservation across HCoVs. In addition, we developed an integrated pipeline for epitope prediction named COVEP, which is available from the webpage of CovEpiAb. CovEpiAb is freely accessible at https://pgx.zju.edu.cn/covepiab/.