Emerging concepts in the science of vaccine adjuvants

Adjuvants are vaccine components that enhance the magnitude, breadth and durability of the immune response. Following its introduction in the 1920s, alum remained the only adjuvant licensed for human use for the next 70 years. Since the 1990s, a further five adjuvants have been included in licensed vaccines, but the molecular mechanisms by which these adjuvants work remain only partially understood. However, a revolution in our understanding of the activation of the innate immune system through pattern recognition receptors (PRRs) is improving the mechanistic understanding of adjuvants, and recent conceptual advances highlight the notion that tissue damage, different forms of cell death, and metabolic and nutrient sensors can all modulate the innate immune system to activate adaptive immunity. Furthermore, recent advances in the use of systems biology to probe the molecular networks driving immune response to vaccines ('systems vaccinology') are revealing mechanistic insights and providing a new paradigm for the vaccine discovery and development process. Here, we review the 'known knowns' and 'known unknowns' of adjuvants, discuss these emerging concepts and highlight how our expanding knowledge about innate immunity and systems vaccinology are revitalizing the science and development of novel adjuvants for use in vaccines against COVID-19 and future pandemics.

mRNA vaccine for cancer immunotherapy

mRNA vaccines have become a promising platform for cancer immunotherapy. During vaccination, naked or vehicle loaded mRNA vaccines efficiently express tumor antigens in antigen-presenting cells (APCs), facilitate APC activation and innate/adaptive immune stimulation. mRNA cancer vaccine precedes other conventional vaccine platforms due to high potency, safe administration, rapid development potentials, and cost-effective manufacturing. However, mRNA vaccine applications have been limited by instability, innate immunogenicity, and inefficient in vivo delivery. Appropriate mRNA structure modifications (i.e., codon optimizations, nucleotide modifications, self-amplifying mRNAs, etc.) and formulation methods (i.e., lipid nanoparticles (LNPs), polymers, peptides, etc.) have been investigated to overcome these issues. Tuning the administration routes and co-delivery of multiple mRNA vaccines with other immunotherapeutic agents (e.g., checkpoint inhibitors) have further boosted the host anti-tumor immunity and increased the likelihood of tumor cell eradication. With the recent U.S. Food and Drug Administration (FDA) approvals of LNP-loaded mRNA vaccines for the prevention of COVID-19 and the promising therapeutic outcomes of mRNA cancer vaccines achieved in several clinical trials against multiple aggressive solid tumors, we envision the rapid advancing of mRNA vaccines for cancer immunotherapy in the near future. This review provides a detailed overview of the recent progress and existing challenges of mRNA cancer vaccines and future considerations of applying mRNA vaccine for cancer immunotherapies.

Changing Priorities in Vaccinology: Antibiotic Resistance Moving to the Top

Antimicrobial resistance (AMR) is currently the most alarming issue for human health. AMR already causes 700,000 deaths/year. It is estimated that 10 million deaths due to AMR will occur every year after 2050. This equals the number of people dying of cancer every year in present times. International institutions such as G20, World Bank, World Health Organization (WHO), UN General Assembly, European Union, and the UK and USA governments are calling for new antibiotics. To underline this emergency, a list of antibiotic-resistant "priority pathogens" has been published by WHO. It contains 12 families of bacteria that represent the greatest danger for human health. Resistance to multiple antibiotics is particularly relevant for the Gram-negative bacteria present in the list. The ability of these bacteria to develop mechanisms to resist treatment could be transmitted with genetic material, allowing other bacteria to become drug resistant. Although the search for new antimicrobial drugs remains a top priority, the pipeline for new antibiotics is not promising, and alternative solutions are needed. A possible answer to AMR is vaccination. In fact, while antibiotic resistance emerges rapidly, vaccines can lead to a much longer lasting control of infections. New technologies, such as the high-throughput cloning of human B cells from convalescent or vaccinated people, allow for finding new protective antigens (Ags) that could not be identified with conventional technologies. Antibodies produced by convalescent B cell clones can be screened for their ability to bind, block, and kill bacteria, using novel high-throughput microscopy platforms that rapidly capture digital images, or by conventional technologies such as bactericidal, opsono-phagocytosis and FACS assays. Selected antibodies expressed by recombinant DNA techniques can be used for passive immunization in animal models and tested for protection. Antibodies providing the best protection can be employed to identify new Ags and then used for generating highly specific recombinant Fab fragments. Co-crystallization of Ags bound to Fab fragments will allow us to determine the structure and characteristics of new Ags. This structure-based Ag design will bring to a new generation of vaccines able to target previously elusive infections, thereby offering an effective solution to the problem of AMR.

Immunoinformatics and structural vaccinology driven prediction of multi-epitope vaccine against Mayaro virus and validation through in-silico expression

The Mayaro virus (MAYV) belongs to genus "Alphavirus" and family "Togaviridae". MAYV has distribution in the Amazonia, Central and Northeastern regions of Brazil. The abundance of mosquito vector Haemagogus janthinomys has major role in the outbreaks of arthralgia disease in Brazil. Vaccination or immunization is an alternative approach for the protection against this disease. To search the effective candidate for vaccine against Mayaro virus, various immunoinformatics tools were used to predict both the B and T cell epitopes from five structural polyproteins (capsid, E2, 6K, E3and E1). A multi subunit vaccine was designed and the final sequence was modeled for docking with TLR-3. Human b defensin based on previous studies was used as linker. The docked complexes of vaccine-TLR-3 were then subjected to dynamics stability and RMSD and RMSF results suggested that the complexes are stable. Further, to validate our final vaccine construct, in silico cloning was carried out using E. coli as host. The CAI value of 0.96 suggests that the vaccine construct properly expresses in the host. The current findings will be useful for the future experimental validations to ratify the immunogenicity and safety of the supposed structure of vaccine, and ultimately to treat the Mayaro virus, associated infections.

The immunology of SARS-CoV-2 infections and vaccines

SARS-CoV-2, the virus that causes COVID-19, emerged in late 2019, and was declared a global pandemic on March 11th 2020. With over 50 million cases and 1.2 million deaths around the world, to date, this pandemic represents the gravest global health crisis of our times. Thus, the race to develop a COVID-19 vaccine is an urgent global imperative. At the time of writing, there are over 165 vaccine candidates being developed, with 33 in various stages of clinical testing. In this review, we discuss emerging insights about the human immune response to SARS-CoV-2, and their implications for vaccine design. We then review emerging knowledge of the immunogenicity of the numerous vaccine candidates that are currently being tested in the clinic and discuss the range of immune defense mechanisms that can be harnessed to develop novel vaccines that confer durable protection against SARS-CoV-2. Finally, we conclude with a discussion of the potential role of a systems vaccinology approach in accelerating the clinical testing of vaccines, to meet the urgent needs posed by the pandemic.

Reverse vaccinology assisted designing of multiepitope-based subunit vaccine against SARS-CoV-2

BACKGROUND

Coronavirus disease 2019 (COVID-19) linked with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cause severe illness and life-threatening pneumonia in humans. The current COVID-19 pandemic demands an effective vaccine to acquire protection against the infection. Therefore, the present study was aimed to design a multiepitope-based subunit vaccine (MESV) against COVID-19.

METHODS

Structural proteins (Surface glycoprotein, Envelope protein, and Membrane glycoprotein) of SARS-CoV-2 are responsible for its prime functions. Sequences of proteins were downloaded from GenBank and several immunoinformatics coupled with computational approaches were employed to forecast B- and T- cell epitopes from the SARS-CoV-2 highly antigenic structural proteins to design an effective MESV.

RESULTS

Predicted epitopes suggested high antigenicity, conserveness, substantial interactions with the human leukocyte antigen (HLA) binding alleles, and collective global population coverage of 88.40%. Taken together, 276 amino acids long MESV was designed by connecting 3 cytotoxic T lymphocytes (CTL), 6 helper T lymphocyte (HTL) and 4 B-cell epitopes with suitable adjuvant and linkers. The MESV construct was non-allergenic, stable, and highly antigenic. Molecular docking showed a stable and high binding affinity of MESV with human pathogenic toll-like receptors-3 (TLR3). Furthermore, in silico immune simulation revealed significant immunogenic response of MESV. Finally, MEV codons were optimized for its in silico cloning into the Escherichia coli K-12 system, to ensure its increased expression.

CONCLUSION

The MESV developed in this study is capable of generating immune response against COVID-19. Therefore, if designed MESV further investigated experimentally, it would be an effective vaccine candidate against SARS-CoV-2 to control and prevent COVID-19.

PanRV: Pangenome-reverse vaccinology approach for identifications of potential vaccine candidates in microbial pangenome

BACKGROUND

A revolutionary diversion from classical vaccinology to reverse vaccinology approach has been observed in the last decade. The ever-increasing genomic and proteomic data has greatly facilitated the vaccine designing and development process. Reverse vaccinology is considered as a cost-effective and proficient approach to screen the entire pathogen genome. To look for broad-spectrum immunogenic targets and analysis of closely-related bacterial species, the assimilation of pangenome concept into reverse vaccinology approach is essential. The categories of species pangenome such as core, accessory, and unique genes sets can be analyzed for the identification of vaccine candidates through reverse vaccinology.

RESULTS

We have designed an integrative computational pipeline term as "PanRV" that employs both the pangenome and reverse vaccinology approaches. PanRV comprises of four functional modules including i) Pangenome Estimation Module (PGM) ii) Reverse Vaccinology Module (RVM) iii) Functional Annotation Module (FAM) and iv) Antibiotic Resistance Association Module (ARM). The pipeline is tested by using genomic data from 301 genomes of Staphylococcus aureus and the results are verified by experimentally known antigenic data.

CONCLUSION

The proposed pipeline has proved to be the first comprehensive automated pipeline that can precisely identify putative vaccine candidates exploiting the microbial pangenome. PanRV is a Linux based package developed in JAVA language. An executable installer is provided for ease of installation along with a user manual at https://sourceforge.net/projects/panrv2/ .

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.

Immunoinformatics design of a novel epitope-based vaccine candidate against dengue virus

Dengue poses a global health threat, which will persist without therapeutic intervention. Immunity induced by exposure to one serotype does not confer long-term protection against secondary infection with other serotypes and is potentially capable of enhancing this infection. Although vaccination is believed to induce durable and protective responses against all the dengue virus (DENV) serotypes in order to reduce the burden posed by this virus, the development of a safe and efficacious vaccine remains a challenge. Immunoinformatics and computational vaccinology have been utilized in studies of infectious diseases to provide insight into the host-pathogen interactions thus justifying their use in vaccine development. Since vaccination is the best bet to reduce the burden posed by DENV, this study is aimed at developing a multi-epitope based vaccines for dengue control. Combined approaches of reverse vaccinology and immunoinformatics were utilized to design multi-epitope based vaccine from the sequence of DENV. Specifically, BCPreds and IEDB servers were used to predict the B-cell and T-cell epitopes, respectively. Molecular docking was carried out using Schrödinger, PATCHDOCK and FIREDOCK. Codon optimization and in silico cloning were done using JCAT and SnapGene respectively. Finally, the efficiency and stability of the designed vaccines were assessed by an in silico immune simulation and molecular dynamic simulation, respectively. The predicted epitopes were prioritized using in-house criteria. Four candidate vaccines (DV-1-4) were designed using suitable adjuvant and linkers in addition to the shortlisted epitopes. The binding interactions of these vaccines against the receptors TLR-2, TLR-4, MHC-1 and MHC-2 show that these candidate vaccines perfectly fit into the binding domains of the receptors. In addition, DV-1 has a better binding energies of - 60.07, - 63.40, - 69.89 kcal/mol against MHC-1, TLR-2, and TLR-4, with respect to the other vaccines. All the designed vaccines were highly antigenic, soluble, non-allergenic, non-toxic, flexible, and topologically assessable. The immune simulation analysis showed that DV-1 may elicit specific immune response against dengue virus. Moreover, codon optimization and in silico cloning validated the expressions of all the designed vaccines in E. coli. Finally, the molecular dynamic study shows that DV-1 is stable with minimum RMSF against TLR4. Immunoinformatics tools are now applied to screen genomes of interest for possible vaccine target. The designed vaccine candidates may be further experimentally investigated as potential vaccines capable of providing definitive preventive measure against dengue virus infection.

Biology of Infection and Disease Pathogenesis to Guide RSV Vaccine Development

Respiratory syncytial virus (RSV) is a leading cause of severe lower respiratory tract disease in young children and a substantial contributor to respiratory tract disease throughout life and as such a high priority for vaccine development. However, after nearly 60 years of research no vaccine is yet available. The challenges to developing an RSV vaccine include the young age, 2-4 months of age, for the peak of disease, the enhanced RSV disease associated with the first RSV vaccine, formalin-inactivated RSV with an alum adjuvant (FI-RSV), and difficulty achieving protection as illustrated by repeat infections with disease that occur throughout life. Understanding the biology of infection and disease pathogenesis has and will continue to guide vaccine development. In this paper, we review the roles that RSV proteins play in the biology of infection and disease pathogenesis and the corresponding contribution to live attenuated and subunit RSV vaccines. Each of RSV's 11 proteins are in the design of one or more vaccines. The G protein's contribution to disease pathogenesis through altering host immune responses as well as its role in the biology of infection suggest it can make a unique contribution to an RSV vaccine, both live attenuated and subunit vaccines. One of G's potential unique contributions to a vaccine is the potential for anti-G immunity to have an anti-inflammatory effect independent of virus replication. Though an anti-viral effect is essential to an effective RSV vaccine, it is important to remember that the goal of a vaccine is to prevent disease. Thus, other effects of the infection, such as G's alteration of the host immune response may provide opportunities to induce responses that block this effect and improve an RSV vaccine. Keeping in mind the goal of a vaccine is to prevent disease and not virus replication may help identify new strategies for other vaccine challenges, such as improving influenza vaccines and developing HIV vaccines.

Identification of vaccine targets in pathogens and design of a vaccine using computational approaches

Antigen identification is an important step in the vaccine development process. Computational approaches including deep learning systems can play an important role in the identification of vaccine targets using genomic and proteomic information. Here, we present a new computational system to discover and analyse novel vaccine targets leading to the design of a multi-epitope subunit vaccine candidate. The system incorporates reverse vaccinology and immuno-informatics tools to screen genomic and proteomic datasets of several pathogens such as Trypanosoma cruzi, Plasmodium falciparum, and Vibrio cholerae to identify potential vaccine candidates (PVC). Further, as a case study, we performed a detailed analysis of the genomic and proteomic dataset of T. cruzi (CL Brenner and Y strain) to shortlist eight proteins as possible vaccine antigen candidates using properties such as secretory/surface-exposed nature, low transmembrane helix (< 2), essentiality, virulence, antigenic, and non-homology with host/gut flora proteins. Subsequently, highly antigenic and immunogenic MHC class I, MHC class II and B cell epitopes were extracted from top-ranking vaccine targets. The designed vaccine construct containing 24 epitopes, 3 adjuvants, and 4 linkers was analysed for its physicochemical properties using different tools, including docking analysis. Immunological simulation studies suggested significant levels of T-helper, T-cytotoxic cells, and IgG1 will be elicited upon administration of such a putative multi-epitope vaccine construct. The vaccine construct is predicted to be soluble, stable, non-allergenic, non-toxic, and to offer cross-protection against related Trypanosoma species and strains. Further, studies are required to validate safety and immunogenicity of the vaccine.

The Future of Flu: A Review of the Human Challenge Model and Systems Biology for Advancement of Influenza Vaccinology

Objectives: Novel approaches to advance the field of vaccinology must be investigated, and are particularly of importance for influenza in order to produce a more effective vaccine. A systematic review of human challenge studies for influenza was performed, with the goal of assessing safety and ethics and determining how these studies have led to therapeutic and vaccine development. A systematic review of systems biology approaches for the study of influenza was also performed, with a focus on how this technology has been utilized for influenza vaccine development. Methods: The PubMed database was searched for influenza human challenge studies, and for systems biology studies that have addressed both influenza infection and immunological effects of vaccination. Results: Influenza human challenge studies have led to important advancements in therapeutics and influenza immunization, and can be performed safely and ethically if certain criteria are met. Many studies have investigated the use of systems biology for evaluating immune response to influenza vaccine, and several promising molecular signatures may help advance our understanding of pathogenesis and be used as targets for influenza interventions. Combining these methodologies has the potential to lead to significant advances in the field of influenza vaccinology and therapeutics. Conclusions: Human challenge studies and systems biology approaches are important tools that should be used in concert to advance our understanding of influenza infection and provide targets for novel therapeutics and immunizations.

Multi-epitope chimeric vaccine design against emerging Monkeypox virus via reverse vaccinology techniques- a bioinformatics and immunoinformatics approach

The emerging monkeypox virus (MPXV) is a zoonotic orthopoxvirus that causes infections in humans similar to smallpox. Since May 2022, cases of monkeypox (MPX) have been increasingly reported by the World Health Organization (WHO) worldwide. Currently, there are no clinically validated treatments for MPX infections. In this study, an immunoinformatics approach was used to identify potential vaccine targets against MPXV. A total of 190 MPXV-2022 proteins were retrieved from the ViPR database and subjected to various analyses including antigenicity, allergenicity, toxicity, solubility, IFN-γ, and virulence. Three outer membrane and extracellular proteins were selected based on their respective parameters to predict B-cell and T-cell epitopes. The epitopes are conserved among different strains of MPXV and the population coverage is 100% worldwide, which will provide broader protection against various strains of the virus globally. Nine overlapping MHC-I, MHC-II, and B-cell epitopes were selected to design multi-epitope vaccine constructs linked with suitable linkers in combination with different adjuvants to enhance the immune responses of the vaccine constructs. Molecular modeling and structural validation ensured high-quality 3D structures of vaccine constructs. Based on various immunological and physiochemical properties and docking scores, MPXV-V2 was selected for further investigation. In silico cloning revealed a high level of gene expression for the MPXV-V2 vaccine within the bacterial expression system. Immune and MD simulations confirmed the molecular stability of the MPXV-V2 construct, with high immune responses within the host cell. These results may aid in the development of experimental vaccines against MPXV with increased potency and improved safety.

Designing a novel multi‑epitope vaccine against Ebola virus using reverse vaccinology approach

Ebola virus (EBOV) is a dangerous zoonotic infectious disease. To date, more than 25 EBOV outbreaks have been documented, the majority of which have occurred in Central Africa. The rVSVG-ZEBOV-GP vaccine (ERVEBO), a live attenuated vaccine, has been approved by the US Food and Drug Administration (FDA) to combat EBOV. Because of the several drawbacks of live attenuated vaccines, multi-epitope vaccines probably appear to be safer than live attenuated vaccines. In this work, we employed immunoinformatics tools to design a multi-epitope vaccine against EBOV. We collected sequences of VP35, VP24, VP30, VP40, GP, and NP proteins from the NCBI database. T-cell and linear B-cell epitopes from target proteins were identified and tested for antigenicity, toxicity, allergenicity, and conservancy. The selected epitopes were then linked together in the vaccine's primary structure using appropriate linkers, and the 50S ribosomal L7/L12 (Locus RL7 MYCTU) sequence was added as an adjuvant to the vaccine construct's N-terminal. The physicochemical, antigenicity, and allergenicity parameters of the vaccine were all found to be satisfactory. The 3D model of the vaccine was predicted, refined, and validated. The vaccine construct had a stable and strong interaction with toll-like receptor 4 (TLR4) based on molecular docking and molecular dynamic simulation (MD) analysis. The results of codon optimization and in silico cloning revealed that the proposed vaccine was highly expressed in Escherichia coli (E. coli). The findings of this study are promising; however, experimental validations should be carried out to confirm these findings.

Designing a multi-epitope vaccine against Mycobacteroides abscessus by pangenome-reverse vaccinology

Mycobacteroides abscessus (Previously Mycobacterium abscessus) is an emerging microorganism of the newly defined genera Mycobacteroides that causes mainly skin and tissue diseases in humans. The recent availability of total 34 fully sequenced genomes of different strains belonging to this species has provided an opportunity to utilize this genomics data to gain novel insights and guide the development of specific antimicrobial therapies. In the present study, we collected collectively 34 complete genome sequences of M. abscessus from the NCBI GenBank database. Pangenome analysis was conducted on these genomes to understand the genetic diversity and to obtain proteins associated with its core genome. These core proteins were then subjected to various subtractive filters to identify potential antigenic targets that were subjected to multi-epitope vaccine design. Our analysis projected the open pangenome of M. abscessus containing 3443 core genes. After applying various stepwise filtration steps on the core proteins, a total of four potential antigenic targets were identified. Utilizing their constituent CD4 and CD8 T-cell epitopes, a multi-epitope based subunit vaccine was computationally designed. Sequence-based analysis as well as structural characterization revealed the immunological effectiveness of this designed vaccine. Further molecular docking, molecular dynamics simulation and binding free energy estimation with Toll-like receptor 2 indicated strong structural associations of the vaccine with the immune receptor. The promising results are encouraging and need to be validated by additional wet laboratory studies for confirmation.

Exploring the Papillomaviral Proteome to Identify Potential Candidates for a Chimeric Vaccine against Cervix Papilloma Using Immunomics and Computational Structural Vaccinology

The human papillomavirus (HPV) 58 is considered to be the second most predominant genotype in cervical cancer incidents in China. HPV type-restriction, non-targeted delivery, and the highcost of existing vaccines necessitate continuing research on the HPV vaccine. We aimed to explore the papillomaviral proteome in order to identify potential candidates for a chimeric vaccine against cervix papilloma using computational immunology and structural vaccinology approaches. Two overlapped epitope segments (23⁻36) and (29⁻42) from the N-terminal region of the HPV58 minor capsid protein L2 are selected as capable of inducing both cellular and humoral immunity. In total, 318 amino acid lengths of the vaccine construct SGD58 contain adjuvants (Flagellin and RS09), two Th epitopes, and linkers. SGD58 is a stable protein that is soluble, antigenic, and non-allergenic. Homology modeling and the structural refinement of the best models of SGD58 and TLR5 found 96.8% and 93.9% favored regions in Rampage, respectively. The docking results demonstrated a HADDOCK score of -62.5 ± 7.6, the binding energy (-30 kcal/mol) and 44 interacting amino acid residues between SGD58-TLR5 complex. The docked complex are stable in 100 ns of simulation. The coding sequences of SGD58 also show elevated gene expression in Escherichia coli with 1.0 codon adaptation index and 59.92% glycine-cysteine content. We conclude that SGD58 may prompt the creation a vaccine against cervix papilloma.

Reverse vaccinology and subtractive genomics-based putative vaccine targets identification for Burkholderia pseudomallei Bp1651

The Burkholderia pseudomallei is a unique bio-threat and causative agent of melioidosis. The B. pseudomallei Bp1651 strain has been isolated from a chronic cystic fibrosis patient. The genome-level DNA sequences information of this strain has recently been published. Unfortunately, there is no commercial vaccine available till date to combat B. pseudomallei infection. The genome-wide prioritization approaches are widely used for the identification of potential therapeutic candidates against pathogens. In the present study, we utilized the recently available annotated genomic information of B. pseudomallei Bp1651 through subtractive genomics and reverse-vaccinology strategies to identify its potential vaccine targets. The analyses identified more than 60 pathogen-specific, human host non-homologous proteins that may prioritize in future studies to investigate therapeutic targets for B. pseudomallei Bp1651. The potential B and T-cells antigenic determinant peptides from these pathogen-specific proteins were cataloged using antigenicity and epitope prediction tools. The analyses unveiled a promising antigenic peptide "FQWEFSLSV" from protein-export membrane protein (SecF) of Bp1651 strain, which was predicted to interact with multiple class I and class II MHC alleles with IC₅₀ value < 100 nM. The molecular docking analysis verified favorable molecular interaction of this lead antigenic peptide with the ligand-binding pocket residues of HLA A*02:06 human host immune cell surface receptor. This peptide is predicted to be a suitable epitope capable to elicit the cell-mediated immune response against the B. pseudomallei pathogen. The putative epitopes and proteins identified in this study may be promising vaccine targets against Bp1651 as well as other pathogenic strains of B. pseudomallei.

A library of recombinant Babesia microti cell surface and secreted proteins for diagnostics discovery and reverse vaccinology

Human babesiosis is an emerging tick-borne parasitic disease and blood transfusion-transmitted infection primarily caused by the apicomplexan parasite, Babesia microti. There is no licensed vaccine for B. microti and the development of a reliable serological screening test would contribute to ensuring the safety of the donated blood supply. The recent sequencing of the B. microti genome has revealed many novel genes encoding proteins that can now be tested for their suitability as subunit vaccine candidates and diagnostic serological markers. Extracellular proteins are considered excellent vaccine candidates and serological markers because they are directly exposed to the host humoral immune system, but can be challenging to express as soluble recombinant proteins. We have recently developed an approach based on a mammalian expression system that can produce large panels of functional recombinant cell surface and secreted parasite proteins. Here, we use the B. microti genome sequence to identify 54 genes that are predicted to encode surface-displayed and secreted proteins expressed during the blood stages, and show that 41 (76%) are expressed using our method at detectable levels. We demonstrate that the proteins contain conformational, heat-labile, epitopes and use them to serologically profile the kinetics of the humoral immune responses to two strains of B. microti in a murine infection model. Using sera from validated human infections, we show a concordance in the host antibody responses to B. microti infections in mouse and human hosts. Finally, we show that BmSA1 expressed in mammalian cells can elicit high antibody titres in vaccinated mice using a human-compatible adjuvant but these antibodies did not affect the pathology of infection in vivo. Our library of recombinant B. microti cell surface and secreted antigens constitutes a valuable resource that could contribute to the development of a serological diagnostic test, vaccines, and elucidate the molecular basis of host-parasite interactions.

Synthetic self-assembling ADDomer platform for highly efficient vaccination by genetically encoded multiepitope display

Self-assembling virus-like particles represent highly attractive tools for developing next-generation vaccines and protein therapeutics. We created ADDomer, an adenovirus-derived multimeric protein-based self-assembling nanoparticle scaffold engineered to facilitate plug-and-play display of multiple immunogenic epitopes from pathogens. We used cryo-electron microscopy at near-atomic resolution and implemented novel, cost-effective, high-performance cloud computing to reveal architectural features in unprecedented detail. We analyzed ADDomer interaction with components of the immune system and developed a promising first-in-kind ADDomer-based vaccine candidate to combat emerging Chikungunya infectious disease, exemplifying the potential of our approach.

Exploring the Prospects of Engineered Newcastle Disease Virus in Modern Vaccinology

Many traditional vaccines have proven to be incapable of controlling newly emerging infectious diseases. They have also achieved limited success in the fight against a variety of human cancers. Thus, innovative vaccine strategies are highly needed to overcome the global burden of these diseases. Advances in molecular biology and reverse genetics have completely restructured the concept of vaccinology, leading to the emergence of state-of-the-art technologies for vaccine design, development and delivery. Among these modern vaccine technologies are the recombinant viral vectored vaccines, which are known for their incredible specificity in antigen delivery as well as the induction of robust immune responses in the vaccinated hosts. Although a number of viruses have been used as vaccine vectors, genetically engineered Newcastle disease virus (NDV) possesses some useful attributes that make it a preferable candidate for vectoring vaccine antigens. Here, we review the molecular biology of NDV and discuss the reverse genetics approaches used to engineer the virus into an efficient vaccine vector. We then discuss the prospects of the engineered virus as an efficient vehicle of vaccines against cancer and several infectious diseases of man and animals.

The Application of Single-Cell RNA Sequencing in Vaccinology

Single-cell RNA sequencing allows highly detailed profiling of cellular immune responses from limited-volume samples, advancing prospects of a new era of systems immunology. The power of single-cell RNA sequencing offers various opportunities to decipher the immune response to infectious diseases and vaccines. Here, we describe the potential uses of single-cell RNA sequencing methods in prophylactic vaccine development, concentrating on infectious diseases including COVID-19. Using examples from several diseases, we review how single-cell RNA sequencing has been used to evaluate the immunological response to different vaccine platforms and regimens. By highlighting published and unpublished single-cell RNA sequencing studies relevant to vaccinology, we discuss some general considerations how the field could be enriched with the widespread adoption of this technology.

A novel approach of virulome based reverse vaccinology for exploring and validating peptide-based vaccine candidates against the most troublesome nosocomial pathogen: Acinetobacter baumannii

Acinetobacter baumannii is one of the major cause of nosocomial infections around the globe. The emergence of hyper-virulent strains of the pathogen greatly narrows down therapeutic options for patients infected with this red alert superbug. Development of a peptide-based vaccine can offers an alternative, attractive, and cost-effective remedy for multidrug-resistant A. baumannii associated complications. Herein, we introduced a novel virulome based Reverse Vaccinology for screening peptide based vaccine candidates against A. baumannii and its validation using a negative control. The pipeline screened "FYLNDQPVS" of polysaccharide export outer membrane protein (EpsA) and "LQNNTRRMK" of chaperone-usher pathway protein B (CsuB) as broad-spectrum peptides for induction of targeted immune responses. The 9-mer epitope of both proteins was rendered virulent, antigenic, non-allergen, and highly conserved among thirty-four completely annotated strains. Interactome examination unravels peptides protein direct and indirect interactions with biological significant pathways, essential for A. baumannii pathogenesis and survival. Protein-peptide docking aids in addition by unveiling deep binding of the epitopes in the active site of the most prevalent binding allele in the human population-the DRB1*0101. Both the proteins till to date are not characterized for immunoprotective efficacy and desirable to be deciphered experimentally. The designed series of in silico filters rejected few recently reported peptide and non-peptide vaccine targets and has delivered outcomes, which we believe will enrich the existing knowledge of vaccinology against this life-threatening human pathogen.

A Glimmer of Hope: Recent Updates and Future Challenges in Zika Vaccine Development

The emergence and rapid spread of Zika virus (ZIKV) on a global scale as well as the establishment of a causal link between Zika infection and congenital syndrome and neurological disorders triggered unprecedented efforts towards the development of a safe and effective Zika vaccine. Multiple vaccine platforms, including purified inactivated virus, nucleic acid vaccines, live-attenuated vaccines, and viral-vectored vaccines, have advanced to human clinical trials. In this review, we discuss the recent advances in the field of Zika vaccine development and the challenges for future clinical efficacy trials. We provide a brief overview on Zika vaccine platforms in the pipeline before summarizing the vaccine candidates in clinical trials, with a focus on recent, promising results from vaccine candidates that completed phase I trials. Despite low levels of transmission during recent years, ZIKV has become endemic in the Americas and the potential of large Zika outbreaks remains real. It is important for vaccine developers to continue developing their Zika vaccines, so that a potential vaccine is ready for deployment and clinical efficacy trials when the next ZIKV outbreak occurs.

Computational Methods in Immunology and Vaccinology: Design and Development of Antibodies and Immunogens

The design of new biomolecules able to harness immune mechanisms for the treatment of diseases is a prime challenge for computational and simulative approaches. For instance, in recent years, antibodies have emerged as an important class of therapeutics against a spectrum of pathologies. In cancer, immune-inspired approaches are witnessing a surge thanks to a better understanding of tumor-associated antigens and the mechanisms of their engagement or evasion from the human immune system. Here, we provide a summary of the main state-of-the-art computational approaches that are used to design antibodies and antigens, and in parallel, we review key methodologies for epitope identification for both B- and T-cell mediated responses. A special focus is devoted to the description of structure- and physics-based models, privileged over purely sequence-based approaches. We discuss the implications of novel methods in engineering biomolecules with tailored immunological properties for possible therapeutic uses. Finally, we highlight the extraordinary challenges and opportunities presented by the possible integration of structure- and physics-based methods with emerging Artificial Intelligence technologies for the prediction and design of novel antigens, epitopes, and antibodies.

Identification of vaccine and drug targets in Shigella dysenteriae sd197 using reverse vaccinology approach

Shigellosis is characterized as diarrheal disease that causes a high mortality rate especially in children, elderly and immunocompromised patients. More recently, the World Health Organization advised safe vaccine designing against shigellosis due to the emergence of Shigella dysenteriae resistant strains. Therefore, the aim of this study is to identify novel drug targets as well as the design of the potential vaccine candidates and chimeric vaccine models against Shigella dysenteriae. A computational based Reverse Vaccinology along with subtractive genomics analysis is one of the robust approaches used for the prioritization of drug targets and vaccine candidates through direct screening of genome sequence assemblies. Herein, a successfully designed peptide-based novel highly antigenic chimeric vaccine candidate against Shigella dysenteriae sd197 strain is proposed. The study resulted in six epitopes from outer membrane WP_000188255.1 (Fe (3+) dicitrate transport protein FecA) that ultimately leads to the construction of twelve vaccine models. Moreover, V9 construct was found to be highly immunogenic, non-toxic, non-allergenic, highly antigenic, and most stable in terms of molecular docking and simulation studies against six HLAs and TLRS/MD complex. So far, this protein and multiepitope have never been characterized as vaccine targets against Shigella dysenteriae. The current study proposed that V9 could be a significant vaccine candidate against shigellosis and to ascertain that further experiments may be applied by the scientific community focused on shigellosis.