ABSTRACT
Over the past few decades, the development of potent and safe immune-activating adjuvant technologies has become the heart of intensive research in the constant fight against highly mutative and immune evasive viruses such as influenza, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and human immunodeficiency virus (HIV). Herein, we developed a highly modular saponin-based nanoparticle platform incorporating Toll-like receptor agonists (TLRas) including TLR1/2a, TLR4a, and TLR7/8a adjuvants and their mixtures. These various TLRa-saponin nanoparticle adjuvant constructs induce unique acute cytokine and immune-signaling profiles, leading to specific T helper responses that could be of interest depending on the target disease for prevention. In a murine vaccine study, the adjuvants greatly improved the potency, durability, breadth, and neutralization of both COVID-19 and HIV vaccine candidates, suggesting the potential broad application of these adjuvant constructs to a range of different antigens. Overall, this work demonstrates a modular TLRa-SNP adjuvant platform that could improve the design of vaccines and affect modern vaccine development.
Subject(s)
Adjuvants, Immunologic , COVID-19 Vaccines , Nanoparticles , SARS-CoV-2 , Saponins , Toll-Like Receptor Agonists , Animals , Humans , Mice , Adjuvants, Immunologic/pharmacology , Adjuvants, Vaccine/chemistry , AIDS Vaccines/immunology , COVID-19/prevention & control , COVID-19/immunology , COVID-19/virology , COVID-19 Vaccines/immunology , Cytokines/metabolism , Nanoparticles/chemistry , Saponins/pharmacology , Saponins/chemistry , Saponins/immunology , SARS-CoV-2/immunologyABSTRACT
Both protein nanoparticle and mRNA vaccines were clinically de-risked during the COVID-19 pandemic1-6. These vaccine modalities have complementary strengths: antigen display on protein nanoparticles can enhance the magnitude, quality, and durability of antibody responses7-10, while mRNA vaccines can be rapidly manufactured11 and elicit antigen-specific CD4 and CD8 T cells12,13. Here we leverage a computationally designed icosahedral protein nanoparticle that was redesigned for optimal secretion from eukaryotic cells14 to develop an mRNA-launched nanoparticle vaccine for SARS-CoV-2. The nanoparticle, which displays 60 copies of a stabilized variant of the Wuhan-Hu-1 Spike receptor binding domain (RBD)15, formed monodisperse, antigenically intact assemblies upon secretion from transfected cells. An mRNA vaccine encoding the secreted RBD nanoparticle elicited 5- to 28-fold higher levels of neutralizing antibodies than an mRNA vaccine encoding membrane-anchored Spike, induced higher levels of CD8 T cells than the same immunogen when delivered as an adjuvanted protein nanoparticle, and protected mice from vaccine-matched and -mismatched SARS-CoV-2 challenge. Our data establish that delivering protein nanoparticle immunogens via mRNA vaccines can combine the benefits of each modality and, more broadly, highlight the utility of computational protein design in genetic immunization strategies.
ABSTRACT
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.
ABSTRACT
Epstein-Barr virus (EBV) is associated with several malignancies, neurodegenerative disorders and is the causative agent of infectious mononucleosis. A vaccine that prevents EBV-driven morbidity and mortality remains an unmet need. EBV is orally transmitted, infecting both B cells and epithelial cells. Several virally encoded proteins are involved in entry. The gH/gL glycoprotein complex is essential for infectivity irrespective of cell type, while gp42 is essential for infection of B cells. gp350 promotes viral attachment by binding to CD21 or CD35 and is the most abundant glycoprotein on the virion. gH/gL, gp42 and gp350, are known targets of neutralizing antibodies and therefore relevant immunogens for vaccine development. Here, we developed and optimized the delivery of several alphavirus-derived replicon RNA (repRNA) vaccine candidates encoding gH/gL, gH/gL/gp42 or gp350 delivered by a cationic nanocarrier termed LION™. The lead candidate, encoding full-length gH/gL, elicited high titers of neutralizing antibodies that persisted for at least 8 months and a vaccine-specific CD8+ T cell response. Transfer of vaccine-elicited IgG protected humanized mice from EBV-driven tumor formation and death following high-dose viral challenge. These data demonstrate that LION/repRNA-gH/gL is an ideal candidate vaccine for preventing EBV infection and/or related malignancies in humans.
ABSTRACT
Evolution of SARS-CoV-2 alters the antigenicity of the immunodominant spike (S) receptor-binding domain and N-terminal domain, undermining the efficacy of vaccines and antibody therapies. To overcome this challenge, we set out to develop a vaccine focusing antibody responses on the highly conserved but metastable S2 subunit, which folds as a spring-loaded fusion machinery. We describe a strategy for prefusion-stabilization and high yield recombinant production of SARS-CoV-2 S2 trimers with native structure and antigenicity. We demonstrate that our design strategy is broadly generalizable to sarbecoviruses, as exemplified with the SARS-CoV-1 (clade 1a) and PRD-0038 (clade 3) S2 subunits. Immunization of mice with a prefusion-stabilized SARS-CoV-2 S2 trimer elicits broadly reactive sarbecovirus antibodies and neutralizing antibody titers of comparable magnitude against Wuhan-Hu-1 and the immune evasive XBB.1.5 variant. Vaccinated mice were protected from weight loss and disease upon challenge with XBB.1.5, providing proof-of-principle for fusion machinery sarbecovirus vaccines.
Subject(s)
Antibodies, Neutralizing , Antibodies, Viral , COVID-19 , SARS-CoV-2 , Spike Glycoprotein, Coronavirus , Animals , Mice , Antibodies, Neutralizing/immunology , Antibodies, Viral/immunology , Spike Glycoprotein, Coronavirus/immunology , SARS-CoV-2/immunology , Humans , COVID-19/prevention & control , COVID-19/immunology , COVID-19/virology , Female , COVID-19 Vaccines/immunology , COVID-19 Vaccines/administration & dosage , Mice, Inbred BALB CABSTRACT
Carbohydrates and glycoproteins modulate key biological functions. However, experimental structure determination of sugar polymers is notoriously difficult. Computational approaches can aid in carbohydrate structure prediction, structure determination, and design. In this work, we developed a glycan-modeling algorithm, GlycanTreeModeler, that computationally builds glycans layer-by-layer, using adaptive kernel density estimates (KDE) of common glycan conformations derived from data in the Protein Data Bank (PDB) and from quantum mechanics (QM) calculations. GlycanTreeModeler was benchmarked on a test set of glycan structures of varying lengths, or "trees". Structures predicted by GlycanTreeModeler agreed with native structures at high accuracy for both de novo modeling and experimental density-guided building. We employed these tools to design de novo glycan trees into a protein nanoparticle vaccine to shield regions of the scaffold from antibody recognition, and experimentally verified shielding. This work will inform glycoprotein model prediction, glycan masking, and further aid computational methods in experimental structure determination and refinement.
Subject(s)
Algorithms , Computational Biology , Glycoproteins , Models, Molecular , Polysaccharides , Polysaccharides/chemistry , Computational Biology/methods , Glycoproteins/chemistry , Databases, Protein , Software , Carbohydrate ConformationABSTRACT
H5 influenza is a potential pandemic threat. Previous studies have identified molecular phenotypes of the viral hemagglutinin (HA) protein that contribute to pandemic risk, including cell entry, receptor preference, HA stability, and reduced neutralization by polyclonal sera. Here we use pseudovirus deep mutational scanning to measure how all mutations to a clade 2.3.4.4b H5 HA affect each phenotype. We identify mutations that allow HA to better bind a2-6-linked sialic acids, and show that some viruses already carry mutations that stabilize HA. We also identify recent viral strains with reduced neutralization to sera elicited by candidate vaccine virus. Overall, the systematic nature of deep mutational scanning combined with the safety of pseudoviruses enables comprehensive characterization of mutations to inform surveillance of H5 influenza.
ABSTRACT
Programming protein nanomaterials to respond to changes in environmental conditions is a current challenge for protein design and is important for targeted delivery of biologics. Here we describe the design of octahedral non-porous nanoparticles with a targeting antibody on the two-fold symmetry axis, a designed trimer programmed to disassemble below a tunable pH transition point on the three-fold axis, and a designed tetramer on the four-fold symmetry axis. Designed non-covalent interfaces guide cooperative nanoparticle assembly from independently purified components, and a cryo-EM density map closely matches the computational design model. The designed nanoparticles can package protein and nucleic acid payloads, are endocytosed following antibody-mediated targeting of cell surface receptors, and undergo tunable pH-dependent disassembly at pH values ranging between 5.9 and 6.7. The ability to incorporate almost any antibody into a non-porous pH-dependent nanoparticle opens up new routes to antibody-directed targeted delivery.
ABSTRACT
Middle East respiratory syndrome coronavirus (MERS-CoV) is a zoonotic betacoronavirus that causes severe and often lethal respiratory illness in humans. The MERS-CoV spike (S) protein is the viral fusogen and the target of neutralizing antibodies, and has therefore been the focus of vaccine design efforts. Currently there are no licensed vaccines against MERS-CoV and only a few candidates have advanced to Phase I clinical trials. Here we developed MERS-CoV vaccines utilizing a computationally designed protein nanoparticle platform that has generated safe and immunogenic vaccines against various enveloped viruses, including a licensed vaccine for SARS-CoV-2. Two-component protein nanoparticles displaying MERS-CoV S-derived antigens induced robust neutralizing antibody responses and protected mice against challenge with mouse-adapted MERS-CoV. Electron microscopy polyclonal epitope mapping and serum competition assays revealed the specificities of the dominant antibody responses elicited by immunogens displaying the prefusion-stabilized S-2P trimer, receptor binding domain (RBD), or N-terminal domain (NTD). An RBD nanoparticle vaccine elicited antibodies targeting multiple non-overlapping epitopes in the RBD, whereas anti-NTD antibodies elicited by the S-2P- and NTD-based immunogens converged on a single antigenic site. Our findings demonstrate the potential of two-component nanoparticle vaccine candidates for MERS-CoV and suggest that this platform technology could be broadly applicable to betacoronavirus vaccine development.
ABSTRACT
Toll-like Receptor 3 (TLR3) is a pattern recognition receptor that initiates antiviral immune responses upon binding double-stranded RNA (dsRNA). Several nucleic acid-based TLR3 agonists have been explored clinically as vaccine adjuvants in cancer and infectious disease, but present substantial manufacturing and formulation challenges. Here, we use computational protein design to create novel miniproteins that bind to human TLR3 with nanomolar affinities. Cryo-EM structures of two minibinders in complex with TLR3 reveal that they bind the target as designed, although one partially unfolds due to steric competition with a nearby N-linked glycan. Multimeric forms of both minibinders induce NF-κB signaling in TLR3-expressing cell lines, demonstrating that they may have therapeutically relevant biological activity. Our work provides a foundation for the development of specific, stable, and easy-to-formulate protein-based agonists of TLRs and other pattern recognition receptors.
ABSTRACT
The design of protein-protein interfaces using physics-based design methods such as Rosetta requires substantial computational resources and manual refinement by expert structural biologists. Deep learning methods promise to simplify protein-protein interface design and enable its application to a wide variety of problems by researchers from various scientific disciplines. Here, we test the ability of a deep learning method for protein sequence design, ProteinMPNN, to design two-component tetrahedral protein nanomaterials and benchmark its performance against Rosetta. ProteinMPNN had a similar success rate to Rosetta, yielding 13 new experimentally confirmed assemblies, but required orders of magnitude less computation and no manual refinement. The interfaces designed by ProteinMPNN were substantially more polar than those designed by Rosetta, which facilitated in vitro assembly of the designed nanomaterials from independently purified components. Crystal structures of several of the assemblies confirmed the accuracy of the design method at high resolution. Our results showcase the potential of deep learning-based methods to unlock the widespread application of designed protein-protein interfaces and self-assembling protein nanomaterials in biotechnology.
Subject(s)
Nanostructures , Proteins , Models, Molecular , Proteins/chemistry , Amino Acid Sequence , Biotechnology , Protein ConformationABSTRACT
Continuously evolving influenza viruses cause seasonal epidemics and pose global pandemic threats. Although viral neuraminidase (NA) is an effective drug and vaccine target, our understanding of the NA antigenic landscape still remains incomplete. Here, we describe NA-specific human antibodies that target the underside of the NA globular head domain, inhibit viral propagation of a wide range of human H3N2, swine-origin variant H3N2, and H2N2 viruses, and confer both pre- and post-exposure protection against lethal H3N2 infection in mice. Cryo-EM structures of two such antibodies in complex with NA reveal non-overlapping epitopes covering the underside of the NA head. These sites are highly conserved among N2 NAs yet inaccessible unless the NA head tilts or dissociates. Our findings help guide the development of effective countermeasures against ever-changing influenza viruses by identifying hidden conserved sites of vulnerability on the NA underside.
Subject(s)
Influenza Vaccines , Influenza, Human , Orthomyxoviridae Infections , Humans , Animals , Mice , Swine , Viral Proteins/genetics , Neuraminidase , Influenza A Virus, H3N2 Subtype , Antibodies, Monoclonal , Antibodies, ViralABSTRACT
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.
ABSTRACT
Self-assembling protein nanoparticles are a promising class of materials for targeted drug delivery. Here, the use of a computationally designed, two-component, icosahedral protein nanoparticle is reported to encapsulate multiple macromolecular cargoes via simple and controlled self-assembly in vitro. Single-stranded RNA molecules between 200 and 2500 nucleotides in length are encapsulated and protected from enzymatic degradation for up to a month with length-dependent decay rates. Immunogenicity studies of nanoparticles packaging synthetic polymers carrying a small-molecule TLR7/8 agonist show that co-delivery of antigen and adjuvant results in a more than 20-fold increase in humoral immune responses while minimizing systemic cytokine secretion associated with free adjuvant. Coupled with the precise control over nanoparticle structure offered by computational design, robust and versatile encapsulation via in vitro assembly opens the door to a new generation of cargo-loaded protein nanoparticles that can combine the therapeutic effects of multiple drug classes.
Subject(s)
Nanoparticles , Nanoparticles/chemistry , Animals , Mice , Proteins/chemistry , Toll-Like Receptor 8/metabolism , Toll-Like Receptor 8/agonists , Toll-Like Receptor 8/chemistry , Toll-Like Receptor 7/metabolism , Toll-Like Receptor 7/agonistsABSTRACT
The receptor-binding domain (RBD) of influenza virus hemagglutinin (HA) elicits potently neutralizing yet mostly strain-specific antibodies. Here, we evaluate the ability of several immunofocusing techniques to enhance the functional breadth of vaccine-elicited immune responses against the HA RBD. We present a series of "trihead" nanoparticle immunogens that display native-like closed trimeric RBDs from the HAs of several H1N1 influenza viruses. The series includes hyperglycosylated and hypervariable variants that incorporate natural and designed sequence diversity at key positions in the receptor-binding site periphery. Nanoparticle immunogens displaying triheads or hyperglycosylated triheads elicit higher hemagglutination inhibition (HAI) and neutralizing activity than the corresponding immunogens lacking either trimer-stabilizing mutations or hyperglycosylation. By contrast, mosaic nanoparticle display and antigen hypervariation do not significantly alter the magnitude or breadth of vaccine-elicited antibodies. Our results yield important insights into antibody responses against the RBD and the ability of several structure-based immunofocusing techniques to influence vaccine-elicited antibody responses.
Subject(s)
Influenza A Virus, H1N1 Subtype , Influenza Vaccines , Influenza, Human , Orthomyxoviridae Infections , Humans , Hemagglutinins , Broadly Neutralizing Antibodies , Hemagglutinin Glycoproteins, Influenza Virus , Antibodies, Viral , Antibodies, NeutralizingABSTRACT
Immunogen design approaches aim to control the specificity and quality of antibody responses elicited by next-generation vaccines. Here, we use computational protein design to generate a nanoparticle vaccine platform based on the receptor-binding domain (RBD) of influenza hemagglutinin (HA) that enables precise control of antigen conformation and spacing. HA RBDs are presented as either monomers or native-like closed trimers that are connected to the underlying nanoparticle by a rigid linker that is modularly extended to precisely control antigen spacing. Nanoparticle immunogens with decreased spacing between trimeric RBDs elicit antibodies with improved hemagglutination inhibition and neutralization potency as well as binding breadth across diverse H1 HAs. Our "trihead" nanoparticle immunogen platform provides insights into anti-HA immunity, establishes antigen spacing as an important parameter in structure-based vaccine design, and embodies several design features that could be used in next-generation vaccines against influenza and other viruses.
Subject(s)
Influenza Vaccines , Influenza, Human , Nanoparticles , Orthomyxoviridae Infections , Humans , Influenza, Human/prevention & control , Antibodies, Viral , Antibody Formation , Hemagglutinin Glycoproteins, Influenza Virus , Vaccination , HemagglutininsABSTRACT
Controlling the biodistribution of protein- and nanoparticle-based therapeutic formulations remains challenging. In vivo library selection is an effective method for identifying constructs that exhibit desired distribution behavior; library variants can be selected based on their ability to localize to the tissue or compartment of interest despite complex physiological challenges. Here, we describe further development of an in vivo library selection platform based on self-assembling protein nanoparticles encapsulating their own mRNA genomes (synthetic nucleocapsids or synNCs). We tested two distinct libraries: a low-diversity library composed of synNC surface mutations (45 variants) and a high-diversity library composed of synNCs displaying miniproteins with binder-like properties (6.2 million variants). While we did not identify any variants from the low-diversity surface library that yielded therapeutically relevant changes in biodistribution, the high-diversity miniprotein display library yielded variants that shifted accumulation toward lungs or muscles in just two rounds of in vivo selection. Our approach should contribute to achieving specific tissue homing patterns and identifying targeting ligands for diseases of interest.
Subject(s)
Peptide Library , Proteins , Tissue Distribution , Nucleocapsid , MutationABSTRACT
Although Rhinolophus bats harbor diverse clade 3 sarbecoviruses, the structural determinants of receptor tropism along with the antigenicity of their spike (S) glycoproteins remain uncharacterized. Here, we show that the African Rhinolophus bat clade 3 sarbecovirus PRD-0038 S has a broad angiotensin-converting enzyme 2 (ACE2) usage and that receptor-binding domain (RBD) mutations further expand receptor promiscuity and enable human ACE2 utilization. We determine a cryo-EM structure of the PRD-0038 RBD bound to Rhinolophus alcyone ACE2, explaining receptor tropism and highlighting differences with SARS-CoV-1 and SARS-CoV-2. Characterization of PRD-0038 S using cryo-EM and monoclonal antibody reactivity reveals its distinct antigenicity relative to SARS-CoV-2 and identifies PRD-0038 cross-neutralizing antibodies for pandemic preparedness. PRD-0038 S vaccination elicits greater titers of antibodies cross-reacting with vaccine-mismatched clade 2 and clade 1a sarbecoviruses compared with SARS-CoV-2 S due to broader antigenic targeting, motivating the inclusion of clade 3 antigens in next-generation vaccines for enhanced resilience to viral evolution.
Subject(s)
Chiroptera , Severe acute respiratory syndrome-related coronavirus , Animals , Humans , Angiotensin-Converting Enzyme 2 , SARS-CoV-2/genetics , Tropism , Spike Glycoprotein, Coronavirus , Antibodies, ViralABSTRACT
Many naturally occurring protein assemblies have dynamic structures that allow them to perform specialized functions. For example, clathrin coats adopt a wide variety of architectures to adapt to vesicular cargos of various sizes. Although computational methods for designing novel self-assembling proteins have advanced substantially over the past decade, most existing methods focus on designing static structures with high accuracy. Here we characterize the structures of three distinct computationally designed protein assemblies that each form multiple unanticipated architectures, and identify flexibility in specific regions of the subunits of each assembly as the source of structural diversity. Cryo-EM single-particle reconstructions and native mass spectrometry showed that only two distinct architectures were observed in two of the three cases, while we obtained six cryo-EM reconstructions that likely represent a subset of the architectures present in solution in the third case. Structural modeling and molecular dynamics simulations indicated that the surprising observation of a defined range of architectures, instead of non-specific aggregation, can be explained by constrained flexibility within the building blocks. Our results suggest that deliberate use of structural flexibility as a design principle will allow exploration of previously inaccessible structural and functional space in designed protein assemblies.
ABSTRACT
Multivalent antigen display is a fast-growing area of interest toward broadly protective vaccines. Current nanoparticle-based vaccine candidates demonstrate the ability to confer antibody-mediated immunity against divergent strains of notably mutable viruses. In coronaviruses, this work is predominantly aimed at targeting conserved epitopes of the receptor binding domain. However, targeting conserved non-RBD epitopes could limit the potential for antigenic escape. To explore new potential targets, we engineered protein nanoparticles displaying coronavirus prefusion-stabilized spike (CoV_S-2P) trimers derived from MERS-CoV, SARS-CoV-1, SARS-CoV-2, hCoV-HKU1, and hCoV-OC43 and assessed their immunogenicity in female mice. Monotypic SARS-1 nanoparticles elicit cross-neutralizing antibodies against MERS-CoV and protect against MERS-CoV challenge. MERS and SARS nanoparticles elicit S1-focused antibodies, revealing a conserved site on the S N-terminal domain. Moreover, mosaic nanoparticles co-displaying distinct CoV_S-2P trimers elicit antibody responses to distant cross-group antigens and protect male and female mice against MERS-CoV challenge. Our findings will inform further efforts toward the development of pan-coronavirus vaccines.