Putative new combination vaccine candidates identified by reverse vaccinology and genomic approaches to control enteric pathogens.

OBJECTIVES: The pathogenic microorganisms that cause intestinal diseases can significantly jeopardize people's health. Currently, there are no authorized treatments or vaccinations available to combat the germs responsible for intestinal disease. METHODS: Using immunoinformatics, we developed a potent multi-epitope Combination (combo) vaccine versus Salmonella and enterohemorrhagic E. coli. The B and T cell epitopes were identified by performing a conservancy assessment, population coverage analysis, physicochemical attributes assessment, and secondary and tertiary structure assessment of the chosen antigenic polypeptide. The selection process for vaccine development included using several bioinformatics tools and approaches to finally choose two linear B-cell epitopes, five CTL epitopes, and two HTL epitopes. RESULTS: The vaccine had strong immunogenicity, cytokine production, immunological properties, non-toxicity, non-allergenicity, stability, and potential efficacy against infections. Disulfide bonding, codon modification, and computational cloning were also used to enhance the stability and efficacy of expression in the host E. coli. The vaccine's structure has a strong affinity for the TLR4 ligand and is very durable, as shown by molecular docking and molecular modeling. The results of the immunological simulation demonstrated that both B and T cells had a heightened response to the vaccination component. CONCLUSIONS: The comprehensive in silico analysis reveals that the proposed vaccine will likely elicit a robust immune response against pathogenic bacteria that cause intestinal diseases. Therefore, it is a promising option for further experimental testing.

Designing an mRNA Vaccine against P. jirovecii Involved in Fatal Pneumonia Infections via Comparative Proteomics and Reverse Vaccinology Approaches.

BACKGROUND: Pneumocystis jirovecii is the most emerging life-threating health problem that causes acute and fatal pneumonia infection. It is rare and more contagious for patients with leukemia and immune-deficiency disorders. Until now there is no treatment available for this infection therefore, it is needed to develop any treatment against this pathogen. METHODS: In this work, we used comparative proteomics, robust immune-informatics, and reverse vaccinology to create an mRNA vaccine against Pneumocystis jirovecii by targeting outer and transmembrane proteins. Using a comparative subtractive proteomic analysis of two Pneumocystis jirovecii proteomes, a distinct non-redundant Pneumocystis jirovecii (strain SE8) proteome was chosen. Seven Pneumocystis jirovecii transmembrane proteins were chosen from this proteome based on hydrophilicity, essentiality, virulence, antigenicity, pathway interaction, protein-protein network analysis, and allergenicity. OBJECTIVE: The reverse vaccinology approach was used to predict the immunogenic and antigenic epitopes of major histocompatibility complex (MHC) I, II and B-cells from the selected proteins on the basis of their antigenicity, toxicity and allergenicity. These immunogenic epitopes were linked together to construct the mRNA-based vaccine. To enhance the immunogenicity, suitable adjuvant, linkers (GPGPG, KK, and CYY), and PRDRE sequences were used. RESULTS: Through predictive modeling and confirmation via the Ramachandran plot, we assessed secondary and 3D structures. The adjuvant RpfE was incorporated to enhance the vaccine construct's immunogenicity (GRAVY index: -0.271, instability index: 39.53, antigenicity: 1.0428). The physiochemical profiling of vaccine construct was predicted it an antigenic, efficient, and potential vaccine. Notably, strong interactions were observed between the vaccine construct and TLR-3/TLR-4 (-1301.7 kcal/mol-1 and -1374.7 kcal/mol-1). CONCLUSIONS: The results predicted that mRNA-based vaccines trigger a cellular and humoral immune response, making the vaccine potential candidate against Pneumocystis jirovecii and it is more suitable for in-vitro analysis and validation to prove its effectiveness.

Leveraging artificial intelligence in vaccine development: A narrative review.

Vaccine development stands as a cornerstone of public health efforts, pivotal in curbing infectious diseases and reducing global morbidity and mortality. However, traditional vaccine development methods are often time-consuming, costly, and inefficient. The advent of artificial intelligence (AI) has ushered in a new era in vaccine design, offering unprecedented opportunities to expedite the process. This narrative review explores the role of AI in vaccine development, focusing on antigen selection, epitope prediction, adjuvant identification, and optimization strategies. AI algorithms, including machine learning and deep learning, leverage genomic data, protein structures, and immune system interactions to predict antigenic epitopes, assess immunogenicity, and prioritize antigens for experimentation. Furthermore, AI-driven approaches facilitate the rational design of immunogens and the identification of novel adjuvant candidates with optimal safety and efficacy profiles. Challenges such as data heterogeneity, model interpretability, and regulatory considerations must be addressed to realize the full potential of AI in vaccine development. Integrating emerging technologies, such as single-cell omics and synthetic biology, promises to enhance vaccine design precision and scalability. This review underscores the transformative impact of AI on vaccine development and highlights the need for interdisciplinary collaborations and regulatory harmonization to accelerate the delivery of safe and effective vaccines against infectious diseases.

The Application of Newcastle Disease Virus (NDV): Vaccine Vectors and Tumor Therapy.

Newcastle disease virus (NDV) is an avian pathogen with an unsegmented negative-strand RNA genome that belongs to the Paramyxoviridae family. While primarily pathogenic in birds, NDV presents no threat to human health, rendering it a safe candidate for various biomedical applications. Extensive research has highlighted the potential of NDV as a vector for vaccine development and gene therapy, owing to its transcriptional modularity, low recombination rate, and lack of a DNA phase during replication. Furthermore, NDV exhibits oncolytic capabilities, efficiently eliciting antitumor immune responses, thereby positioning it as a promising therapeutic agent for cancer treatment. This article comprehensively reviews the biological characteristics of NDV, elucidates the molecular mechanisms underlying its oncolytic properties, and discusses its applications in the fields of vaccine vector development and tumor therapy.

mRNA-based vaccines - global approach, challenges, and could be a promising wayout for future pandemics.

mRNA-based vaccines are assured to significantly boost biopharmaceuticals since outbreak of coronavirus disease- 2019. Respiratory infections, such as influenza, SARS, MERS, COVID-19, and respiratory syncytial virus, often have high transmission rates due to their airborne spread. Respiratory infections can lead to severe illness and death. These outbreaks can cause substantial economic and social disruption, as seen with the COVID-19 pandemic. In our interconnected world, respiratory diseases can spread rapidly across borders. mRNA-based vaccines (e.g. mRNA-1283) can reduce the transmission by creating immunity in the population, thus lowering the incidence and spread of these diseases. Vaccines are crucial for global health security, helping to prevent local outbreaks from becoming global pandemics. Nevertheless, various concerns remain such as intracellular delivery, susceptibility to degradation by catalytic hydrolysis, and instability due to several physiological conditions. Therefore, an hour needed to address these challenges and opportunities for attaining high-quality and stable mRNA-based vaccines with novel drug delivery systems. The authors contributed an extensive review of the mRNA-based clinical development, progress in stability, and delivery challenges to mitigate market needs. In addition, the authors discuss crucial advances in the growth of mRNA-based vaccines to date; which dominate an extensive scope of therapeutic implementation. Finally, recent mRNA-based vaccines in clinical trials, adjuvant benefits, and prospects are discussed.

Evaluation of the precision of the Plasmodium knowlesi growth inhibition assay for Plasmodium vivax Duffy-binding protein-based malaria vaccine development.

Recent data indicate increasing disease burden and importance of Plasmodium vivax (Pv) malaria. A robust assay will be essential for blood-stage Pv vaccine development. Results of the in vitro growth inhibition assay (GIA) with transgenic P. knowlesi (Pk) parasites expressing the Pv Duffy-binding protein region II (PvDBPII) correlate with in vivo protection in the first PvDBPII controlled human malaria infection (CHMI) trials, making the PkGIA an ideal selection tool once the precision of the assay is defined. To determine the precision in percentage of inhibition in GIA (%GIA) and in GIA50 (antibody concentration that gave 50 %GIA), ten GIAs with transgenic Pk parasites were conducted with four different anti-PvDBPII human monoclonal antibodies (mAbs) at concentrations of 0.016 to 2 mg/mL, and three GIAs with eighty anti-PvDBPII human polyclonal antibodies (pAbs) at 10 mg/mL. A significant assay-to-assay variation was observed, and the analysis revealed a standard deviation (SD) of 13.1 in the mAb and 5.94 in the pAb dataset for %GIA, with a LogGIA50 SD of 0.299 (for mAbs). Moreover, the ninety-five percent confidence interval (95 %CI) for %GIA or GIA50 in repeat assays was calculated in this investigation. The error range determined in this study will help researchers to compare PkGIA results from different assays and studies appropriately, thus supporting the development of future blood-stage malaria vaccine candidates, specifically second-generation PvDBPII-based formulations.

Enhancing tuberculosis vaccine development: a deconvolution neural network approach for multi-epitope prediction.

Tuberculosis (TB) a disease caused by Mycobacterium tuberculosis (Mtb) poses a significant threat to human life, and current BCG vaccinations only provide sporadic protection, therefore there is a need for developing efficient vaccines. Numerous immunoinformatic methods have been utilized previously, here for the first time a deep learning framework based on Deconvolutional Neural Networks (DCNN) and Bidirectional Long Short-Term Memory (DCNN-BiLSTM) was used to predict Mtb Multiepitope vaccine (MtbMEV) subunits against six Mtb H37Rv proteins. The trained model was used to design MEV within a few minutes against TB better than other machine learning models with 99.5% accuracy. The MEV has good antigenicity, and physiochemical properties, and is thermostable, soluble, and hydrophilic. The vaccine's BLAST search ruled out the possibility of autoimmune reactions. The secondary structure analysis revealed 87% coil, 10% beta, and 2% alpha helix, while the tertiary structure was highly upgraded after refinement. Molecular docking with TLR3 and TLR4 receptors showed good binding, indicating high immune reactions. Immune response simulation confirmed the generation of innate and adaptive responses. In-silico cloning revealed the vaccine is highly expressed in E. coli. The results can be further experimentally verified using various analyses to establish a candidate vaccine for future clinical trials.

Leishmania vaccine development: A comprehensive review.

Infectious diseases like leishmaniasis, malaria, HIV, tuberculosis, leprosy and filariasis are responsible for an immense burden on public health systems. Among these, leishmaniasis is under the category I diseases as it is selected by WHO (World Health Organization) on the ground of diversity and complexity. High cost, resistance and toxic effects of Leishmania traditional drugs entail identification and development of therapeutic alternative. Since the natural infection elicits robust immunity, consistence efforts are going on to develop a successful vaccine. Clinical trials have been conducted on vaccines like Leish-F1, F2, and F3 formulated using specific Leishmania antigen epitopes. Current strategies utilize individual or combined antigens from the parasite or its insect vector's salivary gland extract, with or without adjuvant formulation for enhanced efficacy. Promising animal data supports multiple vaccine candidates (Lmcen-/-, LmexCen-/-), with some already in or heading for clinical trials. The crucial challenge in Leishmania vaccine development is to translate the research knowledge into affordable and accessible control tools that refines the outcome for those who are susceptible to infection. This review focuses on recent findings in Leishmania vaccines and highlights difficulties facing vaccine development and implementation.

[Application of seamless phase â ¡/â ¢ design in vaccine clinical trials].

The seamless phase Ⅱ/Ⅲ design integrates independent phase Ⅱ and phase Ⅲ clinical trials into a continuous, phased adaptive clinical trial design. Compared with traditional independent phase Ⅱ and phase Ⅲ clinical trials, the seamless design offers significant advantages in accelerating drug or vaccine development and improving clinical trial efficiency. Currently, the application of this design in anti-tumor drug research is becoming increasingly mature, and it is gradually expanding to clinical trials of vaccines, including the 9-valent human papillomavirus vaccine, sabin strain inactivated polio vaccine, and others. This paper aims to clarify the seamless phase Ⅱ/Ⅲ design concept and offer valuable insights into its implementation. It accomplishes this by presenting a clinical trial example featuring a phase Ⅱ/Ⅲ seamless design for a 9-valent human papillomavirus vaccine. The article delves into the specific considerations and potential challenges related to implementing the seamless design, aiming to provide valuable insights for optimizing vaccine clinical trials within our country.

Positive-unlabeled learning identifies vaccine candidate antigens in the malaria parasite Plasmodium falciparum.

Malaria vaccine development is hampered by extensive antigenic variation and complex life stages of Plasmodium species. Vaccine development has focused on a small number of antigens, many of which were identified without utilizing systematic genome-level approaches. In this study, we implement a machine learning-based reverse vaccinology approach to predict potential new malaria vaccine candidate antigens. We assemble and analyze P. falciparum proteomic, structural, functional, immunological, genomic, and transcriptomic data, and use positive-unlabeled learning to predict potential antigens based on the properties of known antigens and remaining proteins. We prioritize candidate antigens based on model performance on reference antigens with different genetic diversity and quantify the protein properties that contribute most to identifying top candidates. Candidate antigens are characterized by gene essentiality, gene ontology, and gene expression in different life stages to inform future vaccine development. This approach provides a framework for identifying and prioritizing candidate vaccine antigens for a broad range of pathogens.

Accelerate vaccine development using seamless phase 2/3 trial designs.

BACKGROUND: Traditional vaccine development, often a lengthy and costly process of three separated phases. However, the swift development of COVID-19 vaccines highlighted the critical importance of accelerating the approval of vaccines. This article showcases a seamless phase 2/3 trial design to expedite the development process, particularly for multi-valent vaccines. RESEARCH DESIGN AND METHODS: This study utilizes simulation to compare the performance of seamless phase 2/3 design with that of conventional trial design, specifically by re-envisioning a 9-valent HPV vaccine trial. Across three cases, several key performance metrics are evaluated: overall power, type I error rate, average sample size, trial duration, the percentage of early stop, and the accuracy of dose selection. RESULTS: On average, when the experimental vaccine was assumed to be effective, the seamless design that performed interim analyses based solely on efficacy saved 555.73 subjects, shortened trials by 10.29 months, and increased power by 3.70%. When the experimental vaccine was less effective than control, it saved an average of 887.73 subjects while maintaining the type I error rate below 0.025. CONCLUSION: The seamless design proves to be a compelling strategy for vaccine development, given its versatility in early stopping, re-estimating sample sizes, and shortening trial durations.

mRNA vaccine platforms to prevent bacterial infections.

Bacterial infections are an urgent public health priority. The application of mRNA vaccine technology to prevent bacterial infections is a promising therapeutic strategy undergoing active development. This article discusses recent advances and limitations of mRNA vaccines to prevent bacterial diseases and provides perspectives on future research directions.

Considerations on the Design of Lipid-based mRNA Vaccines Against Cancer.

Throughout the last decades, mRNA vaccines have been developed as a cancer immunotherapeutic and the technology recently gained momentum during the COVID-19 pandemic. Recent promising results obtained from clinical trials investigating lipid-based mRNA vaccines in cancer therapy further highlighted the potential of this therapy. Interestingly, while the technologies being used in authorized mRNA vaccines for the prevention of COVID-19 are relatively similar, mRNA vaccines in clinical development for cancer vaccination show marked differences in mRNA modification, lipid carrier, and administration route. In this review, we describe findings on how these factors can impact the potency of mRNA vaccines in cancer therapy and provide insights into the complex interplay between them. We discuss how lipid carrier composition can affect passive targeting to immune cells to improve the efficacy and safety of mRNA vaccines. Finally, we summarize strategies that are established or still being explored to improve the efficacy of mRNA cancer vaccines and include next-generation vaccines that are on the horizon in clinical development.

Using Species a Rotavirus Reverse Genetics to Engineer Chimeric Viruses Expressing SARS-CoV-2 Spike Epitopes.

Species A rotavirus (RVA) vaccines based on live attenuated viruses are used worldwide in humans. The recent establishment of a reverse genetics system for rotoviruses (RVs) has opened the possibility of engineering chimeric viruses expressing heterologous peptides from other viral or microbial species in order to develop polyvalent vaccines. We tested the feasibility of this concept by two approaches. First, we inserted short SARS-CoV-2 spike peptides into the hypervariable region of the simian RV SA11 strain viral protein (VP) 4. Second, we fused the receptor binding domain (RBD) of the SARS-CoV-2 spike protein, or the shorter receptor binding motif (RBM) nested within the RBD, to the C terminus of nonstructural protein (NSP) 3 of the bovine RV RF strain, with or without an intervening Thosea asigna virus 2A (T2A) peptide. Mutating the hypervariable region of SA11 VP4 impeded viral replication, and for these mutants, no cross-reactivity with spike antibodies was detected. To rescue NSP3 mutants, we established a plasmid-based reverse genetics system for the bovine RV RF strain. Except for the RBD mutant that demonstrated a rescue defect, all NSP3 mutants delivered endpoint infectivity titers and exhibited replication kinetics comparable to that of the wild-type virus. In ELISAs, cell lysates of an NSP3 mutant expressing the RBD peptide showed cross-reactivity with a SARS-CoV-2 RBD antibody. 3D bovine gut enteroids were susceptible to infection by all NSP3 mutants, but cross-reactivity with SARS-CoV-2 RBD antibody was only detected for the RBM mutant. The tolerance of large SARS-CoV-2 peptide insertions at the C terminus of NSP3 in the presence of T2A element highlights the potential of this approach for the development of vaccine vectors targeting multiple enteric pathogens simultaneously. IMPORTANCE We explored the use of rotaviruses (RVs) to express heterologous peptides, using SARS-CoV-2 as an example. Small SARS-CoV-2 peptide insertions (<34 amino acids) into the hypervariable region of the viral protein 4 (VP4) of RV SA11 strain resulted in reduced viral titer and replication, demonstrating a limited tolerance for peptide insertions at this site. To test the RV RF strain for its tolerance for peptide insertions, we constructed a reverse genetics system. NSP3 was C-terminally tagged with SARS-CoV-2 spike peptides of up to 193 amino acids in length. With a T2A-separated 193 amino acid tag on NSP3, there was no significant effect on the viral rescue efficiency, endpoint titer, and replication kinetics. Tagged NSP3 elicited cross-reactivity with SARS-CoV-2 spike antibodies in ELISA. We highlight the potential for development of RV vaccine vectors targeting multiple enteric pathogens simultaneously.

An Update on the Status of Vaccine Development for SARS-CoV-2 Including Variants. Practical Considerations for COVID-19 Special Populations.

The progress in the development of various vaccine platforms against SARS-CoV-2 have been rather remarkable owing to advancement in molecular and biologic sciences. Most of the current vaccines and those in development focus on targeting the viral spike proteins by generating antibodies of varying spectrum. These vaccines represent a variety of platforms including whole virus vaccines, viral vector vaccines, nucleic acid vaccines representing RNA, DNA, and their hybrid forms.The therapeutic efficacy of these vaccines varies owing to their pharmacodynamic individualities. COVID-19 variants are capable of inducing different pathologic responses and some of which may be resistant to antibodies generated by current vaccines. The current clinical use of these vaccines has been through emergency use authorization until recently. Moreover, the efficacy and safety of these vaccines have been tested in substantial numbers of individuals but studies in special populations that better reflect the global population are pending results. These specialized populations include young children, immunocompromised patients, pregnant individuals, and other specialized groups. Combination approaches, molecularly modified vaccination approaches, and vaccines conferring longer periods of immunity are being currently being investigated, as well as pharmacovigilance studies.The continual transformation of SARS-CoV-2 and its variants are of concern along with the breakthrough infections. These considerations pose new challenges for the development of vaccination platforms. For this purpose, booster doses, combination vaccine approaches, and other modalities are being discussed. This review provides an updated account of currently available vaccines and those in advanced development with reference to their composition and mechanisms of action.A discussion on the use of vaccines in special populations including immunocompromised patients, pregnant women and other specialized populations are also included.

A Novel Prophylaxis Strategy Using Liposomal Vaccine Adjuvant CAF09b Protects against Influenza Virus Disease.

The SARS-CoV-2 pandemic caused a massive health and societal crisis, although the fast development of effective vaccines reduced some of the impact. To prepare for future respiratory virus pandemics, a pan-viral prophylaxis could be used to control the initial virus outbreak in the period prior to vaccine approval. The liposomal vaccine adjuvant CAF®09b contains the TLR3 agonist polyinosinic:polycytidylic acid, which induces a type I interferon (IFN-I) response and an antiviral state in the affected tissues. When testing CAF09b liposomes as a potential pan-viral prophylaxis, we observed that intranasal administration of CAF09b liposomes to mice resulted in an influx of innate immune cells into the nose and lungs and upregulation of IFN-I-related gene expression. When CAF09b liposomes were administered prior to challenge with mouse-adapted influenza A/Puerto Rico/8/1934 virus, it protected from severe disease, although the virus was still detectable in the lungs. However, when CAF09b liposomes were administered after influenza challenge, the mice had a similar disease course to controls. In conclusion, CAF09b may be a suitable candidate as a pan-viral prophylactic treatment for epidemic viruses, but must be administered prior to virus exposure to be effective.

Peptide-Based Vaccines for Tuberculosis.

Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis. As a result of the coronavirus disease 2019 (COVID-19) pandemic, the global TB mortality rate in 2020 is rising, making TB prevention and control more challenging. Vaccination has been considered the best approach to reduce the TB burden. Unfortunately, BCG, the only TB vaccine currently approved for use, offers some protection against childhood TB but is less effective in adults. Therefore, it is urgent to develop new TB vaccines that are more effective than BCG. Accumulating data indicated that peptides or epitopes play essential roles in bridging innate and adaptive immunity and triggering adaptive immunity. Furthermore, innovations in bioinformatics, immunoinformatics, synthetic technologies, new materials, and transgenic animal models have put wings on the research of peptide-based vaccines for TB. Hence, this review seeks to give an overview of current tools that can be used to design a peptide-based vaccine, the research status of peptide-based vaccines for TB, protein-based bacterial vaccine delivery systems, and animal models for the peptide-based vaccines. These explorations will provide approaches and strategies for developing safer and more effective peptide-based vaccines and contribute to achieving the WHO's End TB Strategy.

A Perspective on the Roles of Adjuvants in Developing Highly Potent COVID-19 Vaccines.

Several countries have made unremitting efforts to develop an optimal vaccine in the fight against coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). With the increasing occurrence of SARS-CoV-2 variants, current vaccines show decreased neutralizing activities, especially towards the Omicron variant. In this context, adding appropriate adjuvants to COVID-19 vaccines can substantially reduce the number of required doses and improve efficacy or cross-neutralizing protection. We mainly focus on research progress and achievements associated with adjuvanted COVID-19 subunit and inactivated vaccines. We further compare the advantages and disadvantages of different adjuvant formulations in order to provide a scientific reference for designing an effective strategy for future vaccine development.

A vaccine built from potential immunogenic pieces derived from the SARS-CoV-2 spike glycoprotein: A computational approximation.

Coronavirus Disease 2019 (COVID-19) represents a new global threat demanding a multidisciplinary effort to fight its etiological agent-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this regard, immunoinformatics may aid to predict prominent immunogenic regions from critical SARS-CoV-2 structural proteins, such as the spike (S) glycoprotein, for their use in prophylactic or therapeutic interventions against this highly pathogenic betacoronavirus. Accordingly, in this study, an integrated immunoinformatics approach was applied to identify cytotoxic T cell (CTC), T helper cell (THC), and Linear B cell (BC) epitopes from the S glycoprotein in an attempt to design a high-quality multi-epitope vaccine. The best CTC, THC, and BC epitopes showed high viral antigenicity and lack of allergenic or toxic residues, as well as CTC and THC epitopes showed suitable interactions with HLA class I (HLA-I) and HLA class II (HLA-II) molecules, respectively. Remarkably, SARS-CoV-2 receptor-binding domain (RBD) and its receptor-binding motif (RBM) harbour several potential epitopes. The structure prediction, refinement, and validation data indicate that the multi-epitope vaccine has an appropriate conformation and stability. Four conformational epitopes and an efficient binding between Toll-like receptor 4 (TLR4) and the vaccine model were observed. Importantly, the population coverage analysis showed that the multi-epitope vaccine could be used globally. Notably, computer-based simulations suggest that the vaccine model has a robust potential to evoke and maximize both immune effector responses and immunological memory to SARS-CoV-2. Further research is needed to accomplish with the mandatory international guidelines for human vaccine formulations.