Immunogenicity and protection of a variant nanoparticle vaccine that confers broad neutralization against SARS-CoV-2 variants.

SARS-CoV-2 variants have emerged with elevated transmission and a higher risk of infection for vaccinated individuals. We demonstrate that a recombinant prefusion-stabilized spike (rS) protein vaccine based on Beta/B.1.351 (rS-Beta) produces a robust anamnestic response in baboons against SARS-CoV-2 variants when given as a booster one year after immunization with NVX-CoV2373. Additionally, rS-Beta is highly immunogenic in mice and produces neutralizing antibodies against WA1/2020, Beta/B.1.351, and Omicron/BA.1. Mice vaccinated with two doses of Novavax prototype NVX-CoV2373 (rS-WU1) or rS-Beta alone, in combination, or heterologous prime-boost, are protected from challenge. Virus titer is undetectable in lungs in all vaccinated mice, and Th1-skewed cellular responses are observed. We tested sera from a panel of variant spike protein vaccines and find broad neutralization and inhibition of spike:ACE2 binding from the rS-Beta and rS-Delta vaccines against a variety of variants including Omicron. This study demonstrates that rS-Beta vaccine alone or in combination with rS-WU1 induces antibody-and cell-mediated responses that are protective against challenge with SARS-CoV-2 variants and offers broader neutralizing capacity than a rS-WU1 prime/boost regimen alone. Together, these nonhuman primate and murine data suggest a Beta variant booster dose could elicit a broad immune response to fight new and future SARS-CoV-2 variants.

Spray Drying and Particle Engineering in Dosage Form Design for Global Vaccines.

Vaccines are a very important tool in the effort to reduce the global burden of infectious diseases. Modern vaccines can be formulated in several ways to induce specific immunity, including through the use of live bacteria, subunit antigens, and even genetic material. However, vaccines typically need to be transported and stored under controlled refrigerated or frozen conditions to maintain potency. This strict temperature control is incompatible with the available infrastructure in many developing countries. One method of improving the thermostability of a vaccine is through drying of a liquid presentation into a dry dosage form. In addition to enhancing the capability for distribution in resource-poor settings, these dry vaccine forms are more suitable for long-term stockpiling. Spray drying is a drying method that has been successfully used to stabilize many experimental vaccines into a dry form for storage above refrigerated temperatures. Additionally, the use of spray drying allows for the production of engineered particles suitable for respiratory administration. These particles can be further designed for increased out-of-package robustness against high humidity. Furthermore, there are already commercial dry powder delivery devices available that can be used to safely deliver vaccines to the respiratory system. The research in this field demonstrates that the resources to develop highly stable vaccines in flexible dosage forms are available and that these presentations offer many advantages for global vaccination campaigns.

Characterization of nanoparticles-based vaccines for COVID-19.

Several vaccines against COVID-19 use nanoparticles to protect the antigen cargo (either proteins or nucleic acids), increase the immunogenicity and ultimately the efficacy. The characterization of these nanomedicines is challenging due to their intrinsic complexity and requires the use of multidisciplinary techniques and competencies. The accurate characterization of nanovaccines can be conceptualized as a combination of physicochemical, immunological and toxicological assays. This will help to address key challenges in the preclinical characterization, will guide the rapid development of safe and effective vaccines for current and future health crises, and will streamline the regulatory process.

COVID-19 vaccine design using reverse and structural vaccinology, ontology-based literature mining and machine learning.

Rational vaccine design, especially vaccine antigen identification and optimization, is critical to successful and efficient vaccine development against various infectious diseases including coronavirus disease 2019 (COVID-19). In general, computational vaccine design includes three major stages: (i) identification and annotation of experimentally verified gold standard protective antigens through literature mining, (ii) rational vaccine design using reverse vaccinology (RV) and structural vaccinology (SV) and (iii) post-licensure vaccine success and adverse event surveillance and its usage for vaccine design. Protegen is a database of experimentally verified protective antigens, which can be used as gold standard data for rational vaccine design. RV predicts protective antigen targets primarily from genome sequence analysis. SV refines antigens through structural engineering. Recently, RV and SV approaches, with the support of various machine learning methods, have been applied to COVID-19 vaccine design. The analysis of post-licensure vaccine adverse event report data also provides valuable results in terms of vaccine safety and how vaccines should be used or paused. Ontology standardizes and incorporates heterogeneous data and knowledge in a human- and computer-interpretable manner, further supporting machine learning and vaccine design. Future directions on rational vaccine design are discussed.

Immunization practices and risk of anaphylaxis: a current update, comprehensive of COVID-19 vaccination data.

PURPOSE OF REVIEW: This review aims to provide an updated report in regards to the correlation between vaccines and anaphylaxis and the related risk in the population. RECENT FINDINGS: Initial reports showed higher incidence of anaphylaxis following messenger RNA COVID-19 vaccines compared with 'routine' vaccinations, likely influenced by the great attention paid to these 'new' vaccines. However, anaphylaxis has still to be considered quite rare and its incidence will be systematically reconsidered in the light of additional data collected. SUMMARY: Adverse reactions to vaccines are commonly reported but most of them are nonspecific mild events, whereas vaccine-related anaphylaxis is considered a rare event, with an incidence rate equal to 1.3 cases per million vaccine doses administered. As anaphylaxis reports usually start to be reported to passive pharmacovigilance during postmarketing surveillance, the first data are used to be influenced by under- and over-reporting and lack of denominators and following studies are needed to confirm the causal relationship. This might create an initial overcautiously approach to new immunization practices but, being anaphylaxis a potential life-threatening event, every suspected contraindication has to be deepened to maximize effectiveness and safety profile and constantly redefined not to exclude an overestimated population group who could receive the vaccine uneventfully.

Lipid-Based Nanoparticles for Delivery of Vaccine Adjuvants and Antigens: Toward Multicomponent Vaccines.

Despite the many advances that have occurred in the field of vaccine adjuvants, there are still unmet needs that may enable the development of vaccines suitable for more challenging pathogens (e.g., HIV and tuberculosis) and for cancer vaccines. Liposomes have already been shown to be highly effective as adjuvant/delivery systems due to their versatility and likely will find further uses in this space. The broad potential of lipid-based delivery systems is highlighted by the recent approval of COVID-19 vaccines comprising lipid nanoparticles with encapsulated mRNA. This review provides an overview of the different approaches that can be evaluated for the design of lipid-based vaccine adjuvant/delivery systems for protein, carbohydrate, and nucleic acid-based antigens and how these strategies might be combined to develop multicomponent vaccines.

Lipopeptides for Vaccine Development.

The development of lipopeptides (lipidated peptides) for vaccines is discussed, including their role as antigens and/or adjuvants. Distinct classes of lipopeptide architectures are covered including simple linear and ligated constructs and lipid core peptides. The design, synthesis, and immunological responses of the important class of glycerol-based Toll-like receptor agonist lipopeptides such as Pam3CSK4, which contains three palmitoyl chains and a CSK4 hexapeptide sequence, and many derivatives of this model immunogenic compound are also reviewed. Self-assembled lipopeptide structures including spherical and worm-like micelles that have been shown to act as vaccine agents are also described. The work discussed includes examples of lipopeptides developed with model antigens, as well as for immunotherapies to treat many infectious diseases including malaria, influenza, hepatitis, COVID-19, and many others, as well as cancer immunotherapies. Some of these have proceeded to clinical development. The research discussed highlights the huge potential of, and diversity of roles for, lipopeptides in contemporary and future vaccine development.

Can We AlphaFold Our Way Out of the Next Pandemic?

The announcement of the outstanding performance of AlphaFold 2 in the CASP 14 protein structure prediction competition came at the end of a long year defined by the COVID-19 pandemic. With an infectious organism dominating the world stage, the developers of Alphafold 2 were keen to play their part, accurately predicting novel structures of two proteins from SARS-CoV-2. In their blog post of December 2020, they highlighted this contribution, writing "we've also seen signs that protein structure prediction could be useful in future pandemic response efforts". So, what role does structural biology play in guiding vaccine immunogen design and what might be the contribution of AlphaFold 2?

Vaxign2: the second generation of the first Web-based vaccine design program using reverse vaccinology and machine learning.

Vaccination is one of the most significant inventions in medicine. Reverse vaccinology (RV) is a state-of-the-art technique to predict vaccine candidates from pathogen's genome(s). To promote vaccine development, we updated Vaxign2, the first web-based vaccine design program using reverse vaccinology with machine learning. Vaxign2 is a comprehensive web server for rational vaccine design, consisting of predictive and computational workflow components. The predictive part includes the original Vaxign filtering-based method and a new machine learning-based method, Vaxign-ML. The benchmarking results using a validation dataset showed that Vaxign-ML had superior prediction performance compared to other RV tools. Besides the prediction component, Vaxign2 implemented various post-prediction analyses to significantly enhance users' capability to refine the prediction results based on different vaccine design rationales and considerably reduce user time to analyze the Vaxign/Vaxign-ML prediction results. Users provide proteome sequences as input data, select candidates based on Vaxign outputs and Vaxign-ML scores, and perform post-prediction analysis. Vaxign2 also includes precomputed results from approximately 1 million proteins in 398 proteomes of 36 pathogens. As a demonstration, Vaxign2 was used to effectively analyse SARS-CoV-2, the coronavirus causing COVID-19. The comprehensive framework of Vaxign2 can support better and more rational vaccine design. Vaxign2 is publicly accessible at http://www.violinet.org/vaxign2.

Linear B-Cell Epitope Prediction for In Silico Vaccine Design: A Performance Review of Methods Available via Command-Line Interface.

Linear B-cell epitope prediction research has received a steadily growing interest ever since the first method was developed in 1981. B-cell epitope identification with the help of an accurate prediction method can lead to an overall faster and cheaper vaccine design process, a crucial necessity in the COVID-19 era. Consequently, several B-cell epitope prediction methods have been developed over the past few decades, but without significant success. In this study, we review the current performance and methodology of some of the most widely used linear B-cell epitope predictors which are available via a command-line interface, namely, BcePred, BepiPred, ABCpred, COBEpro, SVMTriP, LBtope, and LBEEP. Additionally, we attempted to remedy performance issues of the individual methods by developing a consensus classifier, which combines the separate predictions of these methods into a single output, accelerating the epitope-based vaccine design. While the method comparison was performed with some necessary caveats and individual methods might perform much better for specialized datasets, we hope that this update in performance can aid researchers towards the choice of a predictor, for the development of biomedical applications such as designed vaccines, diagnostic kits, immunotherapeutics, immunodiagnostic tests, antibody production, and disease diagnosis and therapy.

Advancements in protein nanoparticle vaccine platforms to combat infectious disease.

Infectious diseases are a major threat to global human health, yet prophylactic treatment options can be limited, as safe and efficacious vaccines exist only for a fraction of all diseases. Notably, devastating diseases such as acquired immunodeficiency syndrome (AIDS) and coronavirus disease of 2019 (COVID-19) currently do not have vaccine therapies. Conventional vaccine platforms, such as live attenuated vaccines and whole inactivated vaccines, can be difficult to manufacture, may cause severe side effects, and can potentially induce severe infection. Subunit vaccines carry far fewer safety concerns due to their inability to cause vaccine-based infections. The applicability of protein nanoparticles (NPs) as vaccine scaffolds is promising to prevent infectious diseases, and they have been explored for a number of viral, bacterial, fungal, and parasitic diseases. Many types of protein NPs exist, including self-assembling NPs, bacteriophage-derived NPs, plant virus-derived NPs, and human virus-based vectors, and these particular categories will be covered in this review. These vaccines can elicit strong humoral and cellular immune responses against specific pathogens, as well as provide protection against infection in a number of animal models. Furthermore, published clinical trials demonstrate the promise of applying these NP vaccine platforms, which include bacteriophage-derived NPs, in addition to multiple viral vectors that are currently used in the clinic. The continued investigations of protein NP vaccine platforms are critical to generate safer alternatives to current vaccines, advance vaccines for diseases that currently lack effective prophylactic therapies, and prepare for the rapid development of new vaccines against emerging infectious diseases. This article is categorized under: Therapeutic Approaches and Drug Discovery > Nanomedicine for Infectious Disease Biology-Inspired Nanomaterials > Protein and Virus-Based Structures.