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

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/.

SARS-CoV-2 outbreak: role of viral proteins and genomic diversity in virus infection and COVID-19 progression

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection is the cause of coronavirus disease 2019 (COVID-19); a severe respiratory distress that has emerged from the city of Wuhan, Hubei province, China during December 2019. COVID-19 is currently the major global health problem and the disease has now spread to most countries in the world. COVID-19 has profoundly impacted human health and activities worldwide. Genetic mutation is one of the essential characteristics of viruses. They do so to adapt to their host or to move to another one. Viral genetic mutations have a high potentiality to impact human health as these mutations grant viruses unique unpredicted characteristics. The difficulty in predicting viral genetic mutations is a significant obstacle in the field. Evidence indicates that SARS-CoV-2 has a variety of genetic mutations and genomic diversity with obvious clinical consequences and implications. In this review, we comprehensively summarized and discussed the currently available knowledge regarding SARS-CoV-2 outbreaks with a fundamental focus on the role of the viral proteins and their mutations in viral infection and COVID-19 progression. We also summarized the clinical implications of SARS-CoV-2 variants and how they affect the disease severity and hinder vaccine development. Finally, we provided a massive phylogenetic analysis of the spike gene of 214 SARS-CoV-2 isolates from different geographical regions all over the world and their associated clinical implications.

Clearance of persistent SARS-CoV-2 associates with increased neutralizing antibodies in advanced HIV disease post-ART initiation

SARS-CoV-2 clearance requires adaptive immunity but the contribution of neutralizing antibodies and T cells in different immune states is unclear. Here we ask which adaptive immune responses associate with clearance of long-term SARS-CoV-2 infection in HIV-mediated immunosuppression after suppressive antiretroviral therapy (ART) initiation. We assembled a cohort of SARS-CoV-2 infected people in South Africa (n = 994) including participants with advanced HIV disease characterized by immunosuppression due to T cell depletion. Fifty-four percent of participants with advanced HIV disease had prolonged SARS-CoV-2 infection (>1 month). In the five vaccinated participants with advanced HIV disease tested, SARS-CoV-2 clearance associates with emergence of neutralizing antibodies but not SARS-CoV-2 specific CD8 T cells, while CD4 T cell responses were not determined due to low cell numbers. Further, complete HIV suppression is not required for clearance, although it is necessary for an effective vaccine response. Persistent SARS-CoV-2 infection led to SARS-CoV-2 evolution, including virus with extensive neutralization escape in a Delta variant infected participant. The results provide evidence that neutralizing antibodies are required for SARS-CoV-2 clearance in HIV-mediated immunosuppression recovery, and that suppressive ART is necessary to curtail evolution of co-infecting pathogens to reduce individual health consequences as well as public health risk linked with generation of escape mutants.

5-chloro-3-(2-(2,4-dinitrophenyl) hydrazono)indolin-2-one: synthesis, characterization, biochemical and computational screening against SARS-CoV-2

Chemical prototypes with broad-spectrum antiviral activity are important toward developing new therapies that can act on both existing and emerging viruses. Binding of the SARS-CoV-2 spike protein to the host angiotensin-converting enzyme 2 (ACE2) receptor is required for cellular entry of SARS-CoV-2. Toward identifying new chemical leads that can disrupt this interaction, including in the presence of SARS-CoV-2 adaptive mutations found in variants like omicron that can circumvent vaccine, immune, and therapeutic antibody responses, we synthesized 5-chloro-3-(2-(2,4-dinitrophenyl)hydrazono)indolin-2-one (H2L) from the condensation reaction of 5-chloroisatin and 2,4-dinitrophenylhydrazine in good yield. H2L was characterised by elemental and spectral (IR, electronic, Mass) analyses. The NMR spectrum of H2L indicated a keto-enol tautomerism, with the keto form being more abundant in solution. H2L was found to selectively interfere with binding of the SARS-CoV-2 spike receptor-binding domain (RBD) to the host angiotensin-converting enzyme 2 receptor with a 50% inhibitory concentration (IC50) of 0.26 μM, compared to an unrelated PD-1/PD-L1 ligand-receptor-binding pair with an IC50 of 2.06 μM in vitro (Selectivity index = 7.9). Molecular docking studies revealed that the synthesized ligand preferentially binds within the ACE2 receptor-binding site in a region distinct from where spike mutations in SARS-CoV-2 variants occur. Consistent with these models, H2L was able to disrupt ACE2 interactions with the RBDs from beta, delta, lambda, and omicron variants with similar activities. These studies indicate that H2L-derived compounds are potential inhibitors of multiple SARS-CoV-2 variants, including those capable of circumventing vaccine and immune responses.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11696-023-03274-5.

Divergent pathogenetic outcomes in BALB/c mice following Omicron subvariant infection

Following the emergence of B.1.1.529 Omicron, the SARS-CoV-2 virus evolved into a significant number of sublineage variants that possessed numerous mutations throughout the genome, but particularly within the spike glycoprotein (S) gene. For example, the BQ.1.1 and the XBB.1 and XBB.1.5 subvariants contained 34 and 41 mutations in S, respectively. However, these variants elicited largely replication only or mild disease phenotypes in mice. To better model pathogenic outcomes and measure countermeasure performance, we developed mouse adapted versions (BQ.1.1 MA; XBB.1 MA; XBB.1.5 MA) that reflect more pathogenic acute phase pulmonary disease symptoms of SARS-CoV-2, as well as derivative strains expressing nano-luciferase (nLuc) in place of ORF7 (BQ.1.1 nLuc; XBB.1 nLuc; XBB.1.5 nLuc). Amongst the mouse adapted (MA) viruses, a wide range of disease outcomes were observed including mortality, weight loss, lung dysfunction, and tissue viral loads in the lung and nasal turbinates. Intriguingly, XBB.1 MA and XBB.1.5 MA strains, which contained identical mutations throughout except at position F486S/P in S, exhibited divergent disease outcomes in mice (Ao et al., 2023). XBB.1.5 MA infection was associated with significant weight loss and ∼45 % mortality across two independent studies, while XBB.1 MA infected animals suffered from mild weight loss and only 10 % mortality across the same two independent studies. Additionally, the development and use of nanoluciferase expressing strains provided moderate throughput for live virus neutralization assays. The availability of small animal models for the assessment of Omicron VOC disease potential will enable refined capacity to evaluate the efficacy of on market and pre-clinical therapeutics and interventions.

Genetic characteristics of SARS-CoV-2 virus variants observed upon three waves of the COVID-19 pandemic in Ukraine between February 2021-January 2022

The aim

of our study was to identify and characterize the SARS-CoV-2 variants in COVID-19 patients' samples collected from different regions of Ukraine to determine the relationship between SARS-CoV-2 phylogenetics and COVID-19 epidemiology.

Patients and methods

Samples were collected from COVID-19 patients during 2021 and the beginning of 2022 (401 patients). The SARS-CoV-2 genotyping was performed by parallel whole genome sequencing.

Results

The obtained SARS-CoV-2 genotypes showed that three waves of the COVID-19 pandemic in Ukraine were represented by three main variants of concern (VOC), named Alpha, Delta and Omicron; each VOC successfully replaced the earlier variant. The VOC Alpha strain was presented by one B.1.1.7 lineage, while VOC Delta showed a spectrum of 25 lineages that had different prevalence in 19 investigated regions of Ukraine. The VOC Omicron in the first half of the pandemic was represented by 13 lines that belonged to two different clades representing B.1 and B.2 Omicron strains. Each of the three epidemic waves (VOC Alpha, Delta, and Omicron) demonstrated their own course of disease, associated with genetic changes in the SARS-CoV-2 genome. The observed epidemiological features are associated with the genetic characteristics of the different VOCs, such as point mutations, deletions and insertions in the viral genome. A phylogenetic and transmission analysis showed the different mutation rates; there were multiple virus sources with a limited distribution between regions.

Conclusions

The evolution of SARS-CoV-2 virus and high levels of morbidity due to COVID-19 are still registered in the world. Observed multiple virus sourses with the limited distribution between regions indicates the high efficiency of the anti-epidemic policy pursued by the Ministry of Health of Ukraine to prevent the spread of the epidemic, despite the low level of vaccination of the Ukrainian population.

Within-host evolution of SARS-CoV-2: how often are de novo mutations transmitted from symptomatic infections?

Despite a relatively low mutation rate, the large number of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections has allowed for substantial genetic change, leading to a multitude of emerging variants. Using a recently determined mutation rate (per site replication), as well as within-host parameter estimates for symptomatic SARS-CoV-2 infection, we apply a stochastic transmission-bottleneck model to describe the survival probability of de novo SARS-CoV-2 mutations as a function of bottleneck size and selection coefficient. For narrow bottlenecks, we find that mutations affecting per-target-cell attachment rate (with phenotypes associated with fusogenicity and ACE2 binding) have similar transmission probabilities to mutations affecting viral load clearance (with phenotypes associated with humoral evasion). We further find that mutations affecting the eclipse rate (with phenotypes associated with reorganization of cellular metabolic processes and synthesis of viral budding precursor material) are highly favoured relative to all other traits examined. We find that mutations leading to reduced removal rates of infected cells (with phenotypes associated with innate immune evasion) have limited transmission advantage relative to mutations leading to humoral evasion. Predicted transmission probabilities, however, for mutations affecting innate immune evasion are more consistent with the range of clinically estimated household transmission probabilities for de novo mutations. This result suggests that although mutations affecting humoral evasion are more easily transmitted when they occur, mutations affecting innate immune evasion may occur more readily. We examine our predictions in the context of a number of previously characterized mutations in circulating strains of SARS-CoV-2. Our work offers both a null model for SARS-CoV-2 mutation rates and predicts which aspects of viral life history are most likely to successfully evolve, despite low mutation rates and repeated transmission bottlenecks.

Deep mutational scanning reveals functional constraints and antigenic variability 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 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 use pseudovirus deep mutational scanning to measure how nearly all GPC amino-acid mutations affect cell entry and antibody neutralization. Our experiments define functional constraints throughout GPC. We quantify how GPC mutations affect neutralization by a panel of monoclonal antibodies and show that all antibodies are escaped by mutations that exist 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 design of therapeutics and vaccines.

Analysis of SARS-CoV-2 genome evolutionary patterns

The spread of SARS-CoV-2 virus accompanied by public availability of abundant sequence data provides a window for the determination of viral evolutionary patterns. In this study, SARS-CoV-2 genome sequences were collected from seven countries in the period January 2020-December 2022. The sequences were classified into three phases, namely, pre-vaccination, post-vaccination, and recent period. Comparison was performed between these phases based on parameters like mutation rates, selection pressure (dN/dS ratio), and transition to transversion ratios (Ti/Tv). Similar comparisons were performed among SARS-CoV-2 variants. Statistical significance was tested using Graphpad unpaired t-test. The analysis showed an increase in the percent genomic mutation rates post-vaccination and in recent periods across all countries from the pre-vaccination sequences. Mutation rates were highest in NSP3, S, N, and NSP12b before and increased further after vaccination. NSP4 showed the largest change in mutation rates after vaccination. The dN/dS ratios showed purifying selection that shifted toward neutral selection after vaccination. N, ORF8, ORF3a, and ORF10 were under highest positive selection before vaccination. Shift toward neutral selection was driven by E, NSP3, and ORF7a in the after vaccination set. In recent sequences, the largest dN/dS change was observed in E, NSP1, and NSP13. The Ti/Tv ratios decreased with time. C→U and G→U were the most frequent transitions and transversions. However, U→G was the most frequent transversion in recent period. The Omicron variant had the highest genomic mutation rates, while Delta showed the highest dN/dS ratio. Protein-wise dN/dS ratio was also seen to vary across the different variants.IMPORTANCETo the best of our knowledge, there exists no other large-scale study of the genomic and protein-wise mutation patterns during the time course of evolution in different countries. Analyzing the SARS-CoV-2 evolutionary patterns in view of the varying spatial, temporal, and biological signals is important for diagnostics, therapeutics, and pharmacovigilance of SARS-CoV-2.

Predicting potential SARS-CoV-2 mutations of concern via full quantum mechanical modelling

Ab initio quantum mechanical models can characterize and predict intermolecular binding, but only recently have models including more than a few hundred atoms gained traction. Here, we simulate the electronic structure for approximately 13 000 atoms to predict and characterize binding of SARS-CoV-2 spike variants to the human ACE2 (hACE2) receptor using the quantum mechanics complexity reduction (QM-CR) approach. We compare four spike variants in our analysis: Wuhan, Omicron, and two Omicron-based variants. To assess binding, we mechanistically characterize the energetic contribution of each amino acid involved, and predict the effect of select single amino acid mutations. We validate our computational predictions experimentally by comparing the efficacy of spike variants binding to cells expressing hACE2. At the time we performed our simulations (December 2021), the mutation A484K which our model predicted to be highly beneficial to ACE2 binding had not been identified in epidemiological surveys; only recently (August 2023) has it appeared in variant BA.2.86. We argue that our computational model, QM-CR, can identify mutations critical for intermolecular interactions and inform the engineering of high-specificity interactors.

Integrating artificial intelligence-based epitope prediction in a SARS-CoV-2 antibody discovery pipeline: caution is warranted

BACKGROUND

SARS-CoV-2-neutralizing antibodies (nABs) showed great promise in the early phases of the COVID-19 pandemic. The emergence of resistant strains, however, quickly rendered the majority of clinically approved nABs ineffective. This underscored the imperative to develop nAB cocktails targeting non-overlapping epitopes.

METHODS

Undertaking a nAB discovery program, we employed a classical workflow, while integrating artificial intelligence (AI)-based prediction to select non-competing nABs very early in the pipeline. We identified and in vivo validated (in female Syrian hamsters) two highly potent nABs.

FINDINGS

Despite the promising results, in depth cryo-EM structural analysis demonstrated that the AI-based prediction employed with the intention to ensure non-overlapping epitopes was inaccurate. The two nABs in fact bound to the same receptor-binding epitope in a remarkably similar manner.

INTERPRETATION

Our findings indicate that, even in the Alphafold era, AI-based predictions of paratope-epitope interactions are rough and experimental validation of epitopes remains an essential cornerstone of a successful nAB lead selection.

FUNDING

Full list of funders is provided at the end of the manuscript.

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, Fridy 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.

Soluble Angiotensin-Converting Enzyme 2 Protein Improves Survival and Lowers Viral Titers in Lethal Mouse Model of Severe Acute Respiratory Syndrome Coronavirus Type 2 Infection with the Delta Variant

Severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) utilizes angiotensin-converting enzyme 2 (ACE2) as its main receptor for cell entry. We bioengineered a soluble ACE2 protein termed ACE2 618-DDC-ABD that has increased binding to SARS-CoV-2 and prolonged duration of action. Here, we investigated the protective effect of this protein when administered intranasally to k18-hACE2 mice infected with the aggressive SARS-CoV-2 Delta variant. k18-hACE2 mice were infected with the SARS-CoV-2 Delta variant by inoculation of a lethal dose (2 × 104 PFU). ACE2 618-DDC-ABD (10 mg/kg) or PBS was administered intranasally six hours prior and 24 and 48 h post-viral inoculation. All animals in the PBS control group succumbed to the disease on day seven post-infection (0% survival), whereas, in contrast, there was only one casualty in the group that received ACE2 618-DDC-ABD (90% survival). Mice in the ACE2 618-DDC-ABD group had minimal disease as assessed using a clinical score and stable weight, and both brain and lung viral titers were markedly reduced. These findings demonstrate the efficacy of a bioengineered soluble ACE2 decoy with an extended duration of action in protecting against the aggressive Delta SARS-CoV-2 variant. Together with previous work, these findings underline the universal protective potential against current and future emerging SARS-CoV-2 variants.

Adaptation of SARS-CoV-2 to ACE2H353K mice reveals new spike residues that drive mouse infection

The Coronavirus Disease 2019 (COVID-19) pandemic continues to cause extraordinary loss of life and economic damage. Animal models of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) infection are needed to better understand disease pathogenesis and evaluate preventive measures and therapies. While mice are widely used to model human disease, mouse angiotensin converting enzyme 2 (ACE2) does not bind the ancestral SARS-CoV-2 spike protein to mediate viral entry. To overcome this limitation, we "humanized" mouse Ace2 using CRISPR gene editing to introduce a single amino acid substitution, H353K, predicted to facilitate S protein binding. While H353K knockin Ace2 (mACE2H353K) mice supported SARS-CoV-2 infection and replication, they exhibited minimal disease manifestations. Following 30 serial passages of ancestral SARS-CoV-2 in mACE2H353K mice, we generated and cloned a more virulent virus. A single isolate (SARS2MA-H353K) was prepared for detailed studies. In 7-11-month-old mACE2H353K mice, a 104 PFU inocula resulted in diffuse alveolar disease manifested as edema, hyaline membrane formation, and interstitial cellular infiltration/thickening. Unexpectedly, the mouse-adapted virus also infected standard BALB/c and C57BL/6 mice and caused severe disease. The mouse-adapted virus acquired five new missense mutations including two in spike (K417E, Q493K), one each in nsp4, nsp9, and M and a single nucleotide change in the 5' untranslated region. The Q493K spike mutation arose early in serial passage and is predicted to provide affinity-enhancing molecular interactions with mACE2 and further increase the stability and affinity to the receptor. This new model and mouse-adapted virus will be useful to evaluate COVID-19 disease and prophylactic and therapeutic interventions.IMPORTANCEWe developed a new mouse model with a humanized angiotensin converting enzyme 2 (ACE2) locus that preserves native regulatory elements. A single point mutation in mouse ACE2 (H353K) was sufficient to confer in vivo infection with ancestral severe acute respiratory syndrome-coronavirus-2 virus. Through in vivo serial passage, a virulent mouse-adapted strain was obtained. In aged mACE2H353K mice, the mouse-adapted strain caused diffuse alveolar disease. The mouse-adapted virus also infected standard BALB/c and C57BL/6 mice, causing severe disease. The mouse-adapted virus acquired five new missense mutations including two in spike (K417E, Q493K), one each in nsp4, nsp9, and M and a single nucleotide change in the 5' untranslated region. The Q493K spike mutation arose early in serial passage and is predicted to provide affinity-enhancing molecular interactions with mACE2 and further increase the stability and affinity to the receptor. This new model and mouse-adapted virus will be useful to evaluate COVID-19 disease and prophylactic and therapeutic interventions.

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 discovery 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 binding constants of RBD to ACE2, LY-CoV016, LY-CoV555, REGN10987, and S309, onto a 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.

Using big sequencing data to identify chronic SARS-Coronavirus-2 infections

The evolution of SARS-Coronavirus-2 (SARS-CoV-2) has been characterized by the periodic emergence of highly divergent variants. One leading hypothesis suggests these variants may have emerged during chronic infections of immunocompromised individuals, but limited data from these cases hinders comprehensive analyses. Here, we harnessed millions of SARS-CoV-2 genomes to identify potential chronic infections and used language models (LM) to infer chronic-associated mutations. First, we mined the SARS-CoV-2 phylogeny and identified chronic-like clades with identical metadata (location, age, and sex) spanning over 21 days, suggesting a prolonged infection. We inferred 271 chronic-like clades, which exhibited characteristics similar to confirmed chronic infections. Chronic-associated mutations were often high-fitness immune-evasive mutations located in the spike receptor-binding domain (RBD), yet a minority were unique to chronic infections and absent in global settings. The probability of observing high-fitness RBD mutations was 10-20 times higher in chronic infections than in global transmission chains. The majority of RBD mutations in BA.1/BA.2 chronic-like clades bore predictive value, i.e., went on to display global success. Finally, we used our LM to infer hundreds of additional chronic-like clades in the absence of metadata. Our approach allows mining extensive sequencing data and providing insights into future evolutionary patterns of SARS-CoV-2.

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.

COV2Var, a function annotation database of SARS-CoV-2 genetic variation

The COVID-19 pandemic, caused by the coronavirus SARS-CoV-2, has resulted in the loss of millions of lives and severe global economic consequences. Every time SARS-CoV-2 replicates, the viruses acquire new mutations in their genomes. Mutations in SARS-CoV-2 genomes led to increased transmissibility, severe disease outcomes, evasion of the immune response, changes in clinical manifestations and reducing the efficacy of vaccines or treatments. To date, the multiple resources provide lists of detected mutations without key functional annotations. There is a lack of research examining the relationship between mutations and various factors such as disease severity, pathogenicity, patient age, patient gender, cross-species transmission, viral immune escape, immune response level, viral transmission capability, viral evolution, host adaptability, viral protein structure, viral protein function, viral protein stability and concurrent mutations. Deep understanding the relationship between mutation sites and these factors is crucial for advancing our knowledge of SARS-CoV-2 and for developing effective responses. To fill this gap, we built COV2Var, a function annotation database of SARS-CoV-2 genetic variation, available at http://biomedbdc.wchscu.cn/COV2Var/. COV2Var aims to identify common mutations in SARS-CoV-2 variants and assess their effects, providing a valuable resource for intensive functional annotations of common mutations among SARS-CoV-2 variants.

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

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

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.

Computational Modeling Insights into Extreme Heterogeneity in COVID-19 Nasal Swab Data

Throughout the COVID-19 pandemic, an unprecedented level of clinical nasal swab data from around the globe has been collected and shared. Positive tests have consistently revealed viral titers spanning six orders of magnitude! An open question is whether such extreme population heterogeneity is unique to SARS-CoV-2 or possibly generic to viral respiratory infections. To probe this question, we turn to the computational modeling of nasal tract infections. Employing a physiologically faithful, spatially resolved, stochastic model of respiratory tract infection, we explore the statistical distribution of human nasal infections in the immediate 48 h of infection. The spread, or heterogeneity, of the distribution derives from variations in factors within the model that are unique to the infected host, infectious variant, and timing of the test. Hypothetical factors include: (1) reported physiological differences between infected individuals (nasal mucus thickness and clearance velocity); (2) differences in the kinetics of infection, replication, and shedding of viral RNA copies arising from the unique interactions between the host and viral variant; and (3) differences in the time between initial cell infection and the clinical test. Since positive clinical tests are often pre-symptomatic and independent of prior infection or vaccination status, in the model we assume immune evasion throughout the immediate 48 h of infection. Model simulations generate the mean statistical outcomes of total shed viral load and infected cells throughout 48 h for each "virtual individual", which we define as each fixed set of model parameters (1) and (2) above. The "virtual population" and the statistical distribution of outcomes over the population are defined by collecting clinically and experimentally guided ranges for the full set of model parameters (1) and (2). This establishes a model-generated "virtual population database" of nasal viral titers throughout the initial 48 h of infection of every individual, which we then compare with clinical swab test data. Support for model efficacy comes from the sampling of infection dynamics over the virtual population database, which reproduces the six-order-of-magnitude clinical population heterogeneity. However, the goal of this study is to answer a deeper biological and clinical question. What is the impact on the dynamics of early nasal infection due to each individual physiological feature or virus-cell kinetic mechanism? To answer this question, global data analysis methods are applied to the virtual population database that sample across the entire database and de-correlate (i.e., isolate) the dynamic infection outcome sensitivities of each model parameter. These methods predict the dominant, indeed exponential, driver of population heterogeneity in dynamic infection outcomes is the latency time of infected cells (from the moment of infection until onset of viral RNA shedding). The shedding rate of the viral RNA of infected cells in the shedding phase is a strong, but not exponential, driver of infection. Furthermore, the unknown timing of the nasal swab test relative to the onset of infection is an equally dominant contributor to extreme population heterogeneity in clinical test data since infectious viral loads grow from undetectable levels to more than six orders of magnitude within 48 h.

Continued selection on cryptic SARS-CoV-2 observed in Missouri wastewater

Deep sequencing of wastewater to detect SARS-CoV-2 has been used during the COVID-19 pandemic to monitor viral variants as they appear and circulate in communities. SARS-CoV-2 lineages of an unknown source that have not been detected in clinical samples, referred to as cryptic lineages, are sometimes repeatedly detected from specific locations. We have continued to detect one such lineage previously seen in a Missouri site. This cryptic lineage has continued to evolve, indicating continued selective pressure similar to that observed in Omicron lineages.

Protein Engineering and High-Throughput Screening by Yeast Surface Display: Survey of Current Methods

Yeast surface display (YSD) is a powerful tool in biotechnology that links genotype to phenotype. In this review, the latest advancements in protein engineering and high-throughput screening based on YSD are covered. The focus is on innovative methods for overcoming challenges in YSD in the context of biotherapeutic drug discovery and diagnostics. Topics ranging from titrating avidity in YSD using transcriptional control to the development of serological diagnostic assays relying on serum biopanning and mitigation of unspecific binding are covered. Screening techniques against nontraditional cellular antigens, such as cell lysates, membrane proteins, and extracellular matrices are summarized and techniques are further delved into for expansion of the chemical repertoire, considering protein-small molecule hybrids and noncanonical amino acid incorporation. Additionally, in vivo gene diversification and continuous evolution in yeast is discussed. Collectively, these techniques enhance the diversity and functionality of engineered proteins isolated via YSD, broadening the scope of applications that can be addressed. The review concludes with future perspectives and potential impact of these advancements on protein engineering. The goal is to provide a focused summary of recent progress in the field.

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.

Evolutionary trajectory of SARS-CoV-2 genome shifts during widespread vaccination and emergence of Omicron variant

Understanding the adaptation of SARS-CoV-2 is critical for the development of effective treatments against this exceptionally successful human pathogen. To predict the emergence of new variants that may escape host immunity or increase virulence, it is important to characterize the biological forces driving its evolution. We conducted a comprehensive population genetic study of over thirteen million SARS-CoV-2 genome sequences, collected over a timeframe of ~3 years, to investigate these forces. Our analysis revealed that during the first year of the pandemic (2020 to 2021), the SARS-CoV-2 genome was subject to strong conservation, with only 3.6% of sites under diversifying pressure in the receptor binding domain (RBD) of the Spike protein. However, we observed a sharp increase in the diversification of the RBD during 2021 (8.1% of sites under diversifying pressure up to 2022), indicating selective pressures that promote the accumulation of mutations. This period coincided with broad viral infection and adoption of vaccination worldwide, and we observed the acquisition of mutations that later defined the Omicron lineages in independent SARS-CoV-2 strains, suggesting that diversifying selection at these sites could have led to their fixation in Omicron lineages by convergent evolution. Since the emergence of Omicron, we observed a further decrease in the conservation of structural genes, including M, N, and the spike proteins (13.1% of RBD sites under diversifying pressure up to 2023), and identified new sites defining future potential emerging strains. Our results exhibit that ongoing rapid antigenic evolution continues to produce new high-frequency functional variants. Sites under selection are critical for virus fitness, and currently known T cell epitope sequences are highly conserved. Altogether, our study provides a comprehensive dynamic map of sites under selection and conservation across the entirety of the SARS-CoV-2 genome.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Antibody-mediated spike activation promotes cell-cell transmission of SARS-CoV-2

The COVID pandemic fueled by emerging SARS-CoV-2 new variants of concern remains a major global health concern, and the constantly emerging mutations present challenges to current therapeutics. The spike glycoprotein is not only essential for the initial viral entry, but is also responsible for the transmission of SARS-CoV-2 components via syncytia formation. Spike-mediated cell-cell transmission is strongly resistant to extracellular therapeutic and convalescent antibodies via an unknown mechanism. Here, we describe the antibody-mediated spike activation and syncytia formation on cells displaying the viral spike. We found that soluble antibodies against receptor binding motif (RBM) are capable of inducing the proteolytic processing of spike at both the S1/S2 and S2' cleavage sites, hence triggering ACE2-independent cell-cell fusion. Mechanistically, antibody-induced cell-cell fusion requires the shedding of S1 and exposure of the fusion peptide at the cell surface. By inhibiting S1/S2 proteolysis, we demonstrated that cell-cell fusion mediated by spike can be re-sensitized towards antibody neutralization in vitro. Lastly, we showed that cytopathic effect mediated by authentic SARS-CoV-2 infection remain unaffected by the addition of extracellular neutralization antibodies. Hence, these results unveil a novel mode of antibody evasion and provide insights for antibody selection and drug design strategies targeting the SARS-CoV-2 infected cells.

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

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

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

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

Insights into next generation sequencing guided antibody selection strategies

Therapeutic antibody discovery often relies on in-vitro display methods to identify lead candidates. Assessing selected output diversity traditionally involves random colony picking and Sanger sequencing, which has limitations. Next-generation sequencing (NGS) offers a cost-effective solution with increased read depth, allowing a comprehensive understanding of diversity. Our study establishes NGS guidelines for antibody drug discovery, demonstrating its advantages in expanding the number of unique HCDR3 clusters, broadening the number of high affinity antibodies, expanding the total number of antibodies recognizing different epitopes, and improving lead prioritization. Surprisingly, our investigation into the correlation between NGS-derived frequencies of CDRs and affinity revealed a lack of association, although this limitation could be moderately mitigated by leveraging NGS clustering, enrichment and/or relative abundance across different regions to enhance lead prioritization. This study highlights NGS benefits, offering insights, recommendations, and the most effective approach to leverage NGS in therapeutic antibody discovery.

Collaborative effects of 2019-nCoV-Spike mutants on viral infectivity

Background

The emerging mutants of the 2019-nCoV coronavirus are posing unprecedented challenges to the pandemic prevention. A thorough, understanding of the mutational characterization responsible for the pathogenic mechanisms of mutations in 2019-nCoV-Spike is indispensable for developing effective drugs and new vaccines.

Methods

We employed computational methods and viral infection assays to examine the interaction pattern and binding affinity between ACE2 and both single- and multi-mutants of the Spike proteins.

Results

Using data from the CNCB-NGDC databank and analysis of the 2019-nCoV-Spike/ACE2 interface crystal structure, we identified 31 amino acids that may significantly contribute to viral infectivity. Subsequently, we performed molecular dynamics simulations for 589 single-mutants that emerged from the nonsynonymous substitutions of the aforementioned 31 residues. Ultimately, we discovered 8 single-mutants that exhibited significantly higher binding affinities (<-65.00 kcal/mol) to ACE2 compared with the wild-type Spike protein (-55.07 kcal/mol). The random combination of these 8 single-mutants yielded 184 multi-mutants, of which 60 multi-mutants exhibit markedly enhanced binding affinities (<-65.00 kcal/mol). Moreover, the binding free energy analyses of all 773 mutants (including 589 single- and 184 multi-mutants) revealed that Y449R and S494R had a synergistic effect on the binding affinity with other mutants, which were confirmed by virus infection assays of six randomly selected multi-mutants. More importantly, the findings of virus infection assay further validated a strong association between the binding free energy of Spike/ACE2 complex and the viral infectivity.

Conclusions

These findings will greatly contribute to the future surveillance of viruses and rational design of therapeutics.

Comparative Study of the Mutations Observed in the SARS-CoV-2 RBD Variants of Concern and Their Impact on the Interaction with the ACE2 Protein

SARS-CoV-2 strains have made an appearance across the globe, causing over 757 million cases and over 6.85 million deaths at the time of writing. The emergence of these variants shows the amplitude of genetic variation to which the wild-type strains have been subjected. The rise of the different SARS-CoV-2 variants resulting from such genetic modification has significantly affected COVD-19's major impact on proliferation, virulence, and clinics. With the emergence of the variants of concern, the spike protein has been identified as a possible therapeutic target due to its critical role in binding to human cells and pathogenesis. These mutations could be linked to functional heterogeneity and use a different infection strategy. For example, the Omicron variant's multiple mutations should be carefully examined, as they represent one of the most widely spread strains and hint to us that there may be more genetic changes in the virus. As a result, we applied a common protocol where we reconstructed SARS-CoV-2 variants of concern and performed molecular dynamics simulations to study the stability of the ACE2-RBD complex in each variant. We also carried out free energy calculations to compare the binding and biophysical properties of the different SARS-CoV-2 variants when they interact with ACE2. Therefore, we were able to obtain consistent results and uncover new crucial residues that were essential for preserving a balance between maintaining a high affinity for ACE2 and the capacity to evade RBD-targeted antibodies. Our detailed structural analysis showed that SARS-CoV-2 variants of concern show a higher affinity for ACE2 compared to the Wuhan strain. Additionally, residues K417N and E484K/A might play a crucial role in antibody evasion, whereas Q498R and N501Y are specifically mutated to strengthen RBD affinity to ACE2 and, thereby, increase the viral effect of the COVID-19 virus.

Learning from prepandemic data to forecast viral escape

Effective pandemic preparedness relies on anticipating viral mutations that are able to evade host immune responses to facilitate vaccine and therapeutic design. However, current strategies for viral evolution prediction are not available early in a pandemic-experimental approaches require host polyclonal antibodies to test against1-16, and existing computational methods draw heavily from current strain prevalence to make reliable predictions of variants of concern17-19. To address this, we developed EVEscape, a generalizable modular framework that combines fitness predictions from a deep learning model of historical sequences with biophysical and structural information. EVEscape quantifies the viral escape potential of mutations at scale and has the advantage of being applicable before surveillance sequencing, experimental scans or three-dimensional structures of antibody complexes are available. We demonstrate that EVEscape, trained on sequences available before 2020, is as accurate as high-throughput experimental scans at anticipating pandemic variation for SARS-CoV-2 and is generalizable to other viruses including influenza, HIV and understudied viruses with pandemic potential such as Lassa and Nipah. We provide continually revised escape scores for all current strains of SARS-CoV-2 and predict probable further mutations to forecast emerging strains as a tool for continuing vaccine development ( evescape.org ).

Variations in O-Glycosylation Patterns Influence Viral Pathogenicity, Infectivity, and Transmissibility in SARS-CoV-2 Variants

The highly glycosylated S protein plays a vital role in host cell invasion, making it the principal target for vaccine development. Differences in mutations observed on the spike (S) protein of SARS-CoV-2 variants may result in distinct glycosylation patterns, thus influencing immunological evasion, infectivity, and transmissibility. The glycans can mask key epitopes on the S1 protein and alter its structural conformation, allowing the virus to escape the immune system. Therefore, we comprehensively characterize O-glycosylation in eleven variants of SARS-CoV-2 S1 subunits to understand the differences observed in the biology of the variants. In-depth characterization was performed with a double digestion strategy and an efficient LC-MS/MS approach. We observed that O-glycosylation is highly conserved across all variants in the region between the NTD and RBD, whereas other domains and regions exhibit variation in O-glycosylation. Notably, omicron has the highest number of O-glycosylation sites on the S1 subunit. Also, omicron has the highest level of sialylation in the RBD and RBM functional motifs. Our findings may shed light on how differences in O-glycosylation impact viral pathogenicity in variants of SARS-CoV-2 and facilitate the development of a robust vaccine with high protective efficacy against the variants of concern.

Viral Evolution Shaped by Host Proteostasis Networks

Understanding the factors that shape viral evolution is critical for developing effective antiviral strategies, accurately predicting viral evolution, and preventing pandemics. One fundamental determinant of viral evolution is the interplay between viral protein biophysics and the host machineries that regulate protein folding and quality control. Most adaptive mutations in viruses are biophysically deleterious, resulting in a viral protein product with folding defects. In cells, protein folding is assisted by a dynamic system of chaperones and quality control processes known as the proteostasis network. Host proteostasis networks can determine the fates of viral proteins with biophysical defects, either by assisting with folding or by targeting them for degradation. In this review, we discuss and analyze new discoveries revealing that host proteostasis factors can profoundly shape the sequence space accessible to evolving viral proteins. We also discuss the many opportunities for research progress proffered by the proteostasis perspective on viral evolution and adaptation.

Immunogenicity and safety of NVX-CoV2373 as a booster: A phase 3 randomized clinical trial in adults

BACKGROUND

To combat the SARS-CoV-2 pandemic, multiple vaccines using different manufacturing platforms have been developed, including NVX-CoV2373 (an adjuvanted recombinant protein vaccine). As SARS-CoV-2 variants have emerged, some of which evade vaccine-induced immunity, introduction of vaccine booster doses has become critical. Employing different vaccine types for primary series vaccination and boosting could expand vaccine coverage and access. This study assessed whether NVX-CoV2373 would induce robust responses when used as a booster.

METHODS

The 2019nCoV-307 study was a phase 3, randomized, observer-blinded trial evaluating immunogenicity and safety of NVX-CoV2373 in previously vaccinated adults aged 18-49 years in the United States (NCT05463068). Participants were randomized 1:1:1 to receive one intramuscular injection of NVX-CoV2373 from one of three different manufacturing lots. Immunogenicity was assessed by immunoglobulin G (IgG) and neutralizing antibodies (NAb). These responses were compared for the three lots, and for participants with primary series with or without a prior booster dose of the mRNA-1273, BNT162b2, Ad26.COV2.S, or NVX-CoV2373 COVID-19 vaccines.

RESULTS

A total of 911 participants were randomized between July 11 and 13, 2022, with 905 being assessed for safety and 848 for immunogenicity. Immunogenicity of NVX-CoV2373 met prespecified equivalence criteria between lots, and the booster dose was well-tolerated. NVX-CoV2373 induced robust IgG and NAb responses when used as a first or later booster dose, regardless of primary series vaccine type. Seroconversion rates were also similar across previous vaccine types. Induced antibodies were strongly reactive, even to the immune-evasive Omicron BA.1 and BA.5 variants.

CONCLUSIONS

NVX-CoV2373 showed consistent immunogenicity between lots, with no new safety signals identified. Use of NVX-CoV2373 as a booster dose (first or later) is supported.

An In Silico Design of Peptides Targeting the S1/S2 Cleavage Site of the SARS-CoV-2 Spike Protein

SARS-CoV-2, responsible for the COVID-19 pandemic, invades host cells via its spike protein, which includes critical binding regions, such as the receptor-binding domain (RBD), the S1/S2 cleavage site, the S2 cleavage site, and heptad-repeat (HR) sections. Peptides targeting the RBD and HR1 inhibit binding to host ACE2 receptors and the formation of the fusion core. Other peptides target proteases, such as TMPRSS2 and cathepsin L, to prevent the cleavage of the S protein. However, research has largely ignored peptides targeting the S1/S2 cleavage site. In this study, bioinformatics was used to investigate the binding of the S1/S2 cleavage site to host proteases, including furin, trypsin, TMPRSS2, matriptase, cathepsin B, and cathepsin L. Peptides targeting the S1/S2 site were designed by identifying binding residues. Peptides were docked to the S1/S2 site using HADDOCK (High-Ambiguity-Driven protein-protein DOCKing). Nine peptides with the lowest HADDOCK scores and strong binding affinities were selected, which was followed by molecular dynamics simulations (MDSs) for further investigation. Among these peptides, BR582 and BR599 stand out. They exhibited relatively high interaction energies with the S protein at -1004.769 ± 21.2 kJ/mol and -1040.334 ± 24.1 kJ/mol, respectively. It is noteworthy that the binding of these peptides to the S protein remained stable during the MDSs. In conclusion, this research highlights the potential of peptides targeting the S1/S2 cleavage site as a means to prevent SARS-CoV-2 from entering cells, and contributes to the development of therapeutic interventions against COVID-19.

Binding of synthetic nanobodies to the SARS-CoV-2 receptor-binding domain: the importance of salt bridges

In this study, five different SARS-CoV-2 receptor-binding domain (RBD) models were created based on the crystal structures of RBD complexes with two synthetic nanobodies (Sb16 and Sb45). Microsecond all-atom MD simulations revealed that Sb16 and Sb45 substantially stabilized the flexible RBD loop (residues GLU471-SER494) due to the salt bridges and hydrogen bonding interactions between RBD and the synthetic nanobodies. However, the calculation of binding free energy displayed that Sb45 had a higher binding affinity to RBD than Sb16, in agreement with the experimental result. This is because Sb45 has stronger electrostatic attraction to RBD as compared to Sb16. In particular, the salt bridge GLU484-ARG33 in Sb45-RBD is stronger than the GLU484-LYS32 in Sb16-RBD. Furthermore, by comparing the binding affinity of Sb16 for two RBD mutants (E484K and K417N), we found that E484K mutation substantially reduced the binding affinity to Sb16, and K417N mutation had no significant effect, qualitatively in agreement with experimental studies. According to the binding free energy calculation, the strong electrostatic repulsion between LYS32 and LYS484 caused by E484K mutation destroys the salt bridge between LYS32 and GLU484 in the RBD wild type (WT). In contrast, the binding of the K417N mutant to Sb16 effectively maintains the salt bridge between LYS32 and GLU484. Therefore, our research suggests that the salt bridges between RBD and synthetic nanobodies are crucial for binding synthetic nanobodies to RBD, and a SARS-CoV-2 variant can escape neutralization from nanobodies by creating electrostatic repulsion between them.

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.

Characterization of SARS-CoV-2 Convalescent Patients' Serological Repertoire Reveals High Prevalence of Iso-RBD Antibodies

While our understanding of SARS-CoV-2 pathogenesis and antibody responses following infection and vaccination has improved tremendously since the outbreak in 2019, the sequence identities and relative abundances of the individual constituent antibody molecules in circulation remain understudied. Using Ig-Seq, we proteomically profiled the serological repertoire specific to the whole ectodomain of SARS-CoV-2 prefusion-stabilized spike (S) as well as to the receptor binding domain (RBD) over a 6-month period in four subjects following SARS-CoV-2 infection before SARS-CoV-2 vaccines were available. In each individual, we identified between 59 and 167 unique IgG clonotypes in serum. To our surprise, we discovered that ∼50% of serum IgG specific for RBD did not recognize prefusion-stabilized S (referred to as iso-RBD antibodies), suggesting that a significant fraction of serum IgG targets epitopes on RBD inaccessible on the prefusion-stabilized conformation of S. On the other hand, the abundance of iso-RBD antibodies in nine individuals who received mRNA-based COVID-19 vaccines encoding prefusion-stabilized S was significantly lower (∼8%). We expressed a panel of 12 monoclonal antibodies (mAbs) that were abundantly present in serum from two SARS-CoV-2 infected individuals, and their binding specificities to prefusion-stabilized S and RBD were all in agreement with the binding specificities assigned based on the proteomics data, including 1 iso-RBD mAb which bound to RBD but not to prefusion-stabilized S. 2 of 12 mAbs demonstrated neutralizing activity, while other mAbs were non-neutralizing. 11 of 12 mAbs also bound to S (B.1.351), but only 1 maintained binding to S (B.1.1.529). This particular mAb binding to S (B.1.1.529) 1) represented an antibody lineage that comprised 43% of the individual's total S-reactive serum IgG binding titer 6 months post-infection, 2) bound to the S from a related human coronavirus, HKU1, and 3) had a high somatic hypermutation level (10.9%), suggesting that this antibody lineage likely had been elicited previously by pre-pandemic coronavirus and was re-activated following the SARS-CoV-2 infection. All 12 mAbs demonstrated their ability to engage in Fc-mediated effector function activities. Collectively, our study provides a quantitative overview of the serological repertoire following SARS-CoV-2 infection and the significant contribution of iso-RBD antibodies, demonstrating how vaccination strategies involving prefusion-stabilized S may have reduced the elicitation of iso-RBD serum antibodies which are unlikely to contribute to protection.

Multi-omics for COVID-19: driving development of therapeutics and vaccines

The ongoing COVID-19 pandemic caused by SARS-CoV-2 has raised global concern for public health and economy. The development of therapeutics and vaccines to combat this virus is continuously progressing. Multi-omics approaches, including genomics, transcriptomics, proteomics, metabolomics, epigenomics and metallomics, have helped understand the structural and molecular features of the virus, thereby assisting in the design of potential therapeutics and accelerating vaccine development for COVID-19. Here, we provide an up-to-date overview of the latest applications of multi-omics technologies in strategies addressing COVID-19, in order to provide suggestions towards the development of highly effective knowledge-based therapeutics and vaccines.

PRO-2000 exhibits SARS-CoV-2 antiviral activity by interfering with spike-heparin binding

Here, we report on the anti-SARS-CoV-2 activity of PRO-2000, a sulfonated polyanionic compound. In Vero cells infected with the Wuhan, alpha, beta, delta or omicron variant, PRO-2000 displayed EC50 values of 1.1 μM, 2.4 μM, 1.3 μM, 2.1 μM and 0.11 μM, respectively, and an average selectivity index (i.e. ratio of cytotoxic versus antiviral concentration) of 172. Its anti-SARS-CoV-2 activity was confirmed by virus yield assays in Vero cells, Caco2 cells and A549 cells overexpressing ACE2 and TMPRSS2 (A549-AT). Using pseudoviruses bearing the SARS-CoV-2 spike (S), PRO-2000 was shown to block the S-mediated pseudovirus entry in Vero cells and A549-AT cells, with EC50 values of 0.091 μM and 1.6 μM, respectively. This entry process is initiated by interaction of the S glycoprotein with angiotensin-converting enzyme 2 (ACE2) and heparan sulfate proteoglycans. Surface Plasmon Resonance (SPR) studies showed that PRO-2000 binds to the receptor-binding domain (RBD) of S with a KD of 1.6 nM. Similar KD values (range: 1.2 nM-2.1 nM) were obtained with the RBDs of the alpha, beta, delta and omicron variants. In an SPR neutralization assay, PRO-2000 had no effect on the interaction between the RBD and ACE2. Instead, PRO-2000 was proven to inhibit binding of the RBD to a heparin-coated sensor chip, yielding an IC50 of 1.1 nM. To conclude, PRO-2000 has the potential to inhibit a broad range of SARS-CoV-2 variants by blocking the heparin-binding site on the S protein.

Design of a bifunctional pan-sarbecovirus entry inhibitor targeting the cell receptor and viral fusion protein

Development of highly effective antivirals that are robust to viral evolution is a practical strategy for combating the continuously evolved severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Inspired by viral multistep entry process, we here focus on developing a bispecific SARS-CoV-2 entry inhibitor, which acts on the cell receptor angiotensin converting enzyme 2 (ACE2) and viral S2 fusion protein. First, we identified a panel of diverse spike (S) receptor-binding domains (RBDs) and found that the RBD derived from Guangdong pangolin coronavirus (PCoV-GD) possessed the most potent antiviral potency. Next, we created a bispecific inhibitor termed RBD-IPB01 by genetically linking a peptide fusion inhibitor IPB01 to the C-terminal of PCoV-GD RBD, which exhibited greatly increased antiviral potency via cell membrane ACE2 anchoring. Promisingly, RBD-IPB01 had a uniformly bifunctional inhibition on divergent pseudo- and authentic SARS-CoV-2 variants, including multiple Omicron subvariants. RBD-IPB01 also showed consistently cross-inhibition of other sarbecoviruses, including SARS-CoV, PCoV-GD, and Guangxi pangolin coronavirus (PCoV-GX). RBD-IPB01 displayed low cytotoxicity, high trypsin resistance, and favorable metabolic stability. Combined, our studies have provided a tantalizing insight into the design of broad-spectrum and potent antiviral agent. IMPORTANCE Ongoing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) evolution and spillover potential of a wide variety of sarbecovirus lineages indicate the importance of developing highly effective antivirals with broad capability. By directing host angiotensin converting enzyme 2 receptor and viral S2 fusion protein, we have created a dual-targeted virus entry inhibitor with high antiviral potency and breadth. The inhibitor receptor-binding domain (RBD)-IPB01 with the Guangdong pangolin coronavirus (PCoV-GD) spike RBD and a fusion inhibitor IPB01 displays bifunctional cross-inhibitions on pseudo- and authentic SARS-CoV-2 variants including Omicron, as well as on the sarbecoviruses SARS-CoV, PCoV-GD, and Guangxi pangolin coronavirus. RBD-IPB01 also efficiently inhibits diverse SARS-CoV-2 infection of human Calu-3 cells and blocks viral S-mediated cell-cell fusion with a dual function. Thus, the creation of such a bifunctional inhibitor with pan-sarbecovirus neutralizing capability has not only provided a potential weapon to combat future SARS-CoV-2 variants or yet-to-emerge zoonotic sarbecovirus, but also verified a viable strategy for the designing of antivirals against infection of other enveloped viruses.

Evolutionary safety of lethal mutagenesis driven by antiviral treatment

Nucleoside analogs are a major class of antiviral drugs. Some act by increasing the viral mutation rate causing lethal mutagenesis of the virus. Their mutagenic capacity, however, may lead to an evolutionary safety concern. We define evolutionary safety as a probabilistic assurance that the treatment will not generate an increased number of mutants. We develop a mathematical framework to estimate the total mutant load produced with and without mutagenic treatment. We predict rates of appearance of such virus mutants as a function of the timing of treatment and the immune competence of patients, employing realistic assumptions about the vulnerability of the viral genome and its potential to generate viable mutants. We focus on the case study of Molnupiravir, which is an FDA-approved treatment against Coronavirus Disease-2019 (COVID-19). We estimate that Molnupiravir is narrowly evolutionarily safe, subject to the current estimate of parameters. Evolutionary safety can be improved by restricting treatment with this drug to individuals with a low immunological clearance rate and, in future, by designing treatments that lead to a greater increase in mutation rate. We report a simple mathematical rule to determine the fold increase in mutation rate required to obtain evolutionary safety that is also applicable to other pathogen-treatment combinations.

Towards a post-pandemic future for global pathogen genome sequencing

Pathogen genome sequencing has become a routine part of our response to active outbreaks of infectious disease and should be an important part of our preparations for future epidemics. In this Essay, we discuss the innovations that have enabled routine pathogen genome sequencing, as well as how genome sequences can be used to understand and control the spread of infectious disease. We also explore the impact of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic on the field of pathogen genomics and outline the challenges we must address to further improve the utility of pathogen genome sequencing in the future.

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.

Systematic Analyses of the Resistance Potential of Drugs Targeting SARS-CoV-2 Main Protease

Drugs that target the main protease (Mpro) of SARS-CoV-2 are effective therapeutics that have entered clinical use. Wide-scale use of these drugs will apply selection pressure for the evolution of resistance mutations. To understand resistance potential in Mpro, we performed comprehensive surveys of amino acid changes that can cause resistance to nirmatrelvir (Pfizer), and ensitrelvir (Xocova) in a yeast screen. We identified 142 resistance mutations for nirmatrelvir and 177 for ensitrelvir, many of which have not been previously reported. Ninety-nine mutations caused apparent resistance to both inhibitors, suggesting likelihood for the evolution of cross-resistance. The mutation with the strongest drug resistance score against nirmatrelvir in our study (E166V) was the most impactful resistance mutation recently reported in multiple viral passaging studies. Many mutations that exhibited inhibitor-specific resistance were consistent with the distinct interactions of each inhibitor in the substrate binding site. In addition, mutants with strong drug resistance scores tended to have reduced function. Our results indicate that strong pressure from nirmatrelvir or ensitrelvir will select for multiple distinct-resistant lineages that will include both primary resistance mutations that weaken interactions with drug while decreasing enzyme function and compensatory mutations that increase enzyme activity. The comprehensive identification of resistance mutations enables the design of inhibitors with reduced potential of developing resistance and aids in the surveillance of drug resistance in circulating viral populations.

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

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

The anti-SARS-CoV-2 effect and mechanism of Chiehyuan herbal oral protection solution

The Chiehyuan herbal oral protection solution (GB-2) is a herbal mixture commonly utilized in Taiwan for combating severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) as per traditional Chinese medicine practices. This study assessed the clinical impact of GB-2 through prospective clinical trials. With twice-daily use for a week, GB-2 was shown to diminish the expression of angiotensin-converting enzyme 2 (ACE2) in oral mucosal cells. Moreover, after two weeks of use, it could reduce transmembrane protease, serine 2 (TMRPSS2) expression in these cells. Additionally, in vitro experiments demonstrated that GB-2 lessened the entry efficiency of the Omicron, L452R-D614G, T478K-D614G, and L452R-T478K-D614G variants of the SARS-CoV-2 pseudotyped lentivirus. It also impeded the interaction between ACE2 and the receptor-binding domain (RBD) presenting N501Y-K417N-E484A-G339D-Q493R-G496S-Q498R and L452R-T478K mutations. Glycyrrhizic acid, a major compound in GB-2, also hindered the entry of the Omicron variant (BA.1) of the SARS-CoV-2 pseudotyped lentivirus by obstructing the binding between ACE2 and the RBD presenting the N501Y-K417N-E484A-G339D-Q493R-G496S-Q498R mutation. To sum up, these findings suggest that GB-2 can decrease ACE2 and TMPRSS2 expression in oral mucosal cells. Both glycyrrhizic acid and GB-2 were found to reduce the entry efficiency of the Omicron variant (BA.1) of the SARS-CoV-2 pseudotyped lentivirus and block the binding between ACE2 and the RBD with the N501Y-K417N-E484A-G339D-Q493R-G496S-Q498R mutation. This evidence implies that GB-2 might be a potential candidate for further study as a preventative measure against SARS-CoV-2 infection.