Designing multi-epitope-based vaccine targeting surface immunogenic protein of Streptococcus agalactiae using immunoinformatics to control mastitis in dairy cattle

Construction and validation of a novel multi-epitope in silico vaccine design against the paramyosin protein of Opisthorchis viverrini using immunoinformatics analyses

Liver fluke infection caused by Opisthorchis viverrini (O. viverrini) remains a significant but neglected health threat across Southeastern Asia. The early infective anabolic growth stage of O. viverrini expresses and exposes proteins integral for the growth and maturation of immature worms to the adult catabolic stage. Among these proteins, paramyosin emerged as a distinct immunogenic protein during opisthorchiasis. The functional region of the paramyosin protein known as myosin tail was selected to design a multi-epitope vaccine (MEV) to elicit T and B cell immune responses in susceptible human hosts utilizing various immunoinformatics and in silico vaccinology tools. The vaccine candidate had several B- and T-cell epitopes that stimulate both humoral and cellular immune responses. Moreover, in silico structural, docking, and dynamic analyses showed that the construct interacted with target immune receptors effectively, which may result in sufficient immunological stimulation. Analysis of simulated coverage efficacy also supports vaccine application in the field. Cloning and expression of the vaccine candidate were determined to be viable based on physicochemical and in silico assessments. These results reveal that the vaccine candidate developed herein is stable and potentially useful in addressing opisthorchiasis. The promising result of this study establishes a strong platform for initiating laboratory and efficacy trials for the vaccine candidate.

Structural insight into the mechanisms and interacting features of endocrine disruptor Bisphenol A and its analogs with human estrogen-related receptor gamma

Bisphenol A (BPA) is a very important chemical from the commercial perspective. Many useful products are made from it, so its production is increasing day by day. It is widely known that Bisphenol A (BPA) and its analogs are present in the environment and that they enter our body through various routes on a daily basis as we use things made of this chemical in our daily lives. BPA has already been reported to be an endocrine disruptor. Studies have shown that BPA binds strongly to the human estrogen-related receptor gamma (ERRγ) and is an important target of it. This study seeks to understand how it interacts with ERRγ. Molecular docking of BPA and its analogs with ERRγ was performed, and estradiol was taken as a reference. Then, physico-chemical and toxicological analysis of BPA compounds was performed. Subsequently, the dynamic behavior of ERRγ and ERRγ-BPA compound complexes was studied by molecular dynamics simulations over 500 ns, and using this simulated data, their binding energies were again calculated using the MM-PBSA method. We observed that the binding affinity of BPA and its analogs was much higher than that of estradiol, and apart from being toxic, they can be easily absorbed in our body as their physicochemical properties are similar to those of oral medicines. Therefore, this study facilitates the understanding of the structure-activity relationship of ERRγ and BPA compounds and provides information about the key amino acid residues of ERRγ that interact with BPA compounds, which can be helpful to design competitive inhibitors so that we can interrupt the interaction of BPA with ERRγ. In addition, it provides information on BPA and its analogs and will also be helpful in developing new therapeutics.

Immunoinformatics design of novel multi-epitope vaccine against Trueperella Pyogenes using collagen adhesion protein, fimbriae, and pyolysin

Trueperella pyogenes (T. pyogenes) is an opportunistic pathogen that causes infertility, mastitis, and metritis in animals. T. pyogenes is also a zoonotic disease and is considered an economic loss agent in the livestock industry. Therefore, vaccine development is necessary. Using an immunoinformatics approach, this study aimed to construct a multi-epitope vaccine against T. pyogenes. The collagen adhesion protein, fimbriae, and pyolysin (PLO) sequences were initially retrieved. The HTL, CTL, and B cell epitopes were predicted. The vaccine was designed by binding these epitopes with linkers. To increase vaccine immunogenicity, profilin was added to the N-terminal of the vaccine construct. The antigenic features and safety of the vaccine model were investigated. Docking, molecular dynamics simulation of the vaccine with immune receptors, and immunological simulation were used to evaluate the vaccine's efficacy. The vaccine's sequence was then optimized for cloning. The vaccine construct was designed based on 18 epitopes of T. pyogenes. The computational tools validated the vaccine as non-allergenic, non-toxic, hydrophilic, and stable at different temperatures with acceptable antigenic features. The vaccine model had good affinity and stability to bovine TLR2, 4, and 5 as well as stimulation of IgM, IgG, IL-2, IFN-γ, and Th1 responses. This vaccine also increased long-lived memory cells, dendritic cells, and macrophage population. In addition, codon optimization was done and cloned in the E. coli K12 expression vector (pET-28a). For the first time, this study introduced a novel multi-epitope vaccine candidate based on collagen adhesion protein, fimbriae, and PLO of T. pyogenes. It is expected this vaccine stimulates an effective immune response to prevent T. pyogenes infection.

Veterinary systems biology for bridging the phenotype-genotype gap via computational modeling for disease epidemiology and animal welfare

Veterinary systems biology is an innovative approach that integrates biological data at the molecular and cellular levels, allowing for a more extensive understanding of the interactions and functions of complex biological systems in livestock and veterinary science. It has tremendous potential to integrate multi-omics data with the support of vetinformatics resources for bridging the phenotype-genotype gap via computational modeling. To understand the dynamic behaviors of complex systems, computational models are frequently used. It facilitates a comprehensive understanding of how a host system defends itself against a pathogen attack or operates when the pathogen compromises the host's immune system. In this context, various approaches, such as systems immunology, network pharmacology, vaccinology and immunoinformatics, can be employed to effectively investigate vaccines and drugs. By utilizing this approach, we can ensure the health of livestock. This is beneficial not only for animal welfare but also for human health and environmental well-being. Therefore, the current review offers a detailed summary of systems biology advancements utilized in veterinary sciences, demonstrating the potential of the holistic approach in disease epidemiology, animal welfare and productivity.

In silico analysis of virulence factors of Streptococcus uberis for a chimeric vaccine design

Streptococcus uberis is one of the causative agents of bovine mastitis, which has detrimental effects on animal health and the dairy industry. Despite decades of research, the requirement for effective vaccines against the disease remains unmet. The goal of this study was to create a multi-epitope vaccine using five virulence factors of S. uberis through the reverse vaccinology approach, which has been employed due to its high efficiency and applicability. Plasminogen activator A (PauA), glyceraldehyde-3-phosphate dehydrogenase C (GapC), C5a peptidase, S. uberis adhesion molecule (SUAM), and sortase A (SrtA) were selected for the T cytotoxic (CTL) and B cell epitope analyses as they were extensively studied in S. uberis or other pathogens. Eighteen CTL and ten B cell epitopes that were antigenic, non-toxic, and non-allergenic were selected in order to design a chimeric vaccine candidate that in silico analysis revealed to be potentially immunogenic, non-allergenic, and stable. Molecular docking analysis of the vaccine candidate with Toll-like receptor (TLR) 2 and TLR 4 revealed stable interactions between the candidate and the immune receptors. Meanwhile, the stability of the docked complexes was confirmed using normal mode analysis. Additionally, in silico immune simulation of the vaccine candidate demonstrated the stimulation of primary immune responses, indicating that the chimeric protein can hold promise as a viable vaccine candidate for preventing S. uberis mastitis. Moreover, the current study can provide a background for designing epitope-based vaccines based on the explored epitopes.

A nanocarrier immersion vaccine encoding surface immunogenic protein confers cross-immunoprotection against Streptococcus agalactiae and Streptococcus iniae infection in tilapia

Streptococcosis is a highly contagious aquatic bacterial disease that poses a significant threat to tilapia. Vaccination is a well-known effective measure to prevent and control fish bacterial diseases. Among the various immunization methods, immersion vaccination is simple and can be widely used in aquaculture. Besides, nanocarrier delivery technology has been reported as an effective solution to improve the immune effect of immersion vaccine. In this study, the surface immunogenic protein (Sip) was proved to be conserved and potential to provide cross-immunoprotection for both Streptococcus agalactiae (S. agalactiae) and Streptococcus iniae (S. iniae) by multiple sequences alignment and Western blotting analysis. On this basis, we expressed and obtained the recombinant protein rSip and connected it with functionalized carbon nanotubes (CNT) to construct the nanocarrier vaccine system CNT-rSip. After immersion immunization, the immune effect of CNT-rSip against above two streptococcus infections was evaluated in tilapia based on some aspects including the serum specific antibody level, non-specific enzyme activities, immune-related genes expression and relative percent survival (RPS) after bacteria challenge. The results showed that compared with control group, CNT-rSip significantly (P < 0.05) increased the serum antibody levels, related enzyme activities including acid phosphatase, alkaline phosphatase, lysozyme and total antioxidant capacity activities, as well as the expression levels of immune-related genes from 2 to 4 weeks post immunization (wpi), and all these indexes peaked at 3 wpi. Besides, the above indexes of CNT-rSip were higher than those of rSip group with different extend during the experiment. Furthermore, the challenge test indicated that CNT-rSip provided cross-immunoprotection against S. agalactiae and S. iniae infection with RPS of 75 % and 72.41 %, respectively, which were much higher than those of other groups. Our study indicated that the nanocarrier immersion vaccine CNT-rSip could significantly improve the antibody titer and confer cross-immuneprotection against S. agalactiae and S. iniae infection in tilapia.

Computational design and evaluation of mRNA- and protein-based conjugate vaccines for influenza A and SARS-CoV-2 viruses

BACKGROUND

Israel confirmed the first case of "flurona"-a co-infection of seasonal flu (IAV) and SARS-CoV-2 in an unvaccinated pregnant woman. This twindemic has been confirmed in multiple countries and underscores the importance of managing respiratory viral illnesses.

RESULTS

The novel conjugate vaccine was designed by joining four hemagglutinin, three neuraminidase, and four S protein of B-cell epitopes, two hemagglutinin, three neuraminidase, and four S proteins of MHC-I epitopes, and three hemagglutinin, nine neuraminidase, and five S proteins of MHC-II epitopes with linkers and adjuvants. The constructed conjugate vaccine was found stable, non-toxic, non-allergic, and antigenic with 0.6466 scores. The vaccine contained 14.87% alpha helix, 29.85% extended strand, 9.64% beta-turn, and 45.64% random coil, which was modeled to a 3D structure with 94.7% residues in the most favored region of the Ramachandran plot and Z-score of -3.33. The molecular docking of the vaccine with TLR3 represented -1513.9 kcal/mol of binding energy with 39 hydrogen bonds and 514 non-bonded contacts, and 1.582925e-07 of eigenvalue complex. Immune stimulation prediction showed the conjugate vaccine could activate T and B lymphocytes to produce high levels of Th1 cytokines and antibodies.

CONCLUSION

The in silico-designed vaccine against IAV and SARS-CoV-2 showed good population coverage and immune response with predicted T- and B-cell epitopes, favorable molecular docking, Ramachandran plot results, and good protein expression. It fulfilled safety criteria, indicating potential for preclinical studies and experimental clinical trials.

Immunoinformatic-guided designing and evaluating protein and mRNA-based vaccines against Cryptococcus neoformans for immunocompromised patients

BACKGROUND

Cryptococcus neoformans is a fungal pathogen that can cause serious meningoencephalitis in individuals with compromised immune systems due to HIV/AIDS (human immunodeficiency virus/acquired immunodeficiency syndrome), liver cirrhosis, and transplantation. Mannoproteins (MPs), glycoproteins in the C. neoformans capsule, crucially impact virulence by mediating adhesion to lung cells and modulating immune response via cytokine induction and phagocytosis influence. Therefore, creating a vaccine that can generate targeted antibodies to fight infection and prevent fungal illnesses is essential.

RESULTS

This research aims to create a unique, stable, and safe vaccine through bioinformatics methodologies, aiming at epitopes of T and B cells found in the MP of C. neoformans. Based on toxicity, immunogenicity, and antigenicity, this research predicted novel T cells (GNPVGGNVT, NPVGGNVTT, QTSYARLLS, TSVGNGIAS, WVMPGDYTN, AAATGSSSSGSTGSG, GSTGSGSGSAAAGST, SGSTGSGSGSAAAGS, SSGSTGSGSGSAAAG, and SSSGSTGSGSGSAAA) and B cell (ANGSTSTFQQRYTGTYTNGDGSLGTWTQGETVTPQTAYSTPATSNCKTYTSVGNGIASLALSNAGSNSTAAATNSSSGGASAAATGSSSSGSTGSGSGSAAAGSTAAASSSGDSSSSTSAAMSNGI, HGATGLGNPVGGNVTT, TMGPTNPSEPTLGTAI, GNPVGGNVTTNATGSD, and NSTAAATNSSSGGASA) epitopes for a multiple-epitope vaccine and constructed a vaccine subunit with potential immunogenic properties. The present study used four linkers (AAY, GPGPG, KK, and EAAAK linkers) to connect the epitopes and adjuvant. After constructing the vaccine, it was confronted with receptor docking and simulation analysis. Subsequently, the vaccine was cloned into the vector of Escherichia coli pET-28a ( +) by ligation process for the expression using the SnapGene tool, which confirmed a significant immune response. To assess the constructed vaccine's properties, multiple computational tools were employed. Based on the MP sequence, the tools evaluated the antigenicity, immunogenicity, cytokine-inducing capacity, allergenicity, toxicity, population coverage, and solubility.

CONCLUSION

Eventually, the results revealed a promising multi-epitope vaccine as a potential candidate for addressing global C. neoformans infection, particularly in immunocompromised patients. Yet, additional in vitro and in vivo investigations are necessary to validate its safety and effectiveness.

Identification of histidine kinase inhibitors through screening of natural compounds to combat mastitis caused by Streptococcus agalactiae in dairy cattle

BACKGROUND

Mastitis poses a major threat to dairy farms globally; it results in reduced milk production, increased treatment costs, untimely compromised genetic potential, animal deaths, and economic losses. Streptococcus agalactiae is a highly virulent bacteria that cause mastitis. The administration of antibiotics for the treatment of this infection is not advised due to concerns about the emergence of antibiotic resistance and potential adverse effects on human health. Thus, there is a critical need to identify new therapeutic approaches to combat mastitis. One promising target for the development of antibacterial therapies is the transmembrane histidine kinase of bacteria, which plays a key role in signal transduction pathways, secretion systems, virulence, and antibiotic resistance.

RESULTS

In this study, we aimed to identify novel natural compounds that can inhibit transmembrane histidine kinase. To achieve this goal, we conducted a virtual screening of 224,205 natural compounds, selecting the top ten based on their lowest binding energy and favorable protein-ligand interactions. Furthermore, molecular docking of eight selected antibiotics and five histidine kinase inhibitors with transmembrane histidine kinase was performed to evaluate the binding energy with respect to top-screened natural compounds. We also analyzed the ADMET properties of these compounds to assess their drug-likeness. The top two compounds (ZINC000085569031 and ZINC000257435291) and top-screened antibiotics (Tetracycline) that demonstrated a strong binding affinity were subjected to molecular dynamics simulations (100 ns), free energy landscape, and binding free energy calculations using the MM-PBSA method.

CONCLUSION

Our results suggest that the selected natural compounds have the potential to serve as effective inhibitors of transmembrane histidine kinase and can be utilized for the development of novel antibacterial veterinary medicine for mastitis after further validation through clinical studies.

Design of multi-epitope vaccine candidate against Brucella type IV secretion system (T4SS)

Brucellosis is a common zoonosis, which is caused by Brucella infection, and Brucella often infects livestock, leading to abortion and infertility. At present, human brucellosis remains one of the major public health problems in China. According to previous research, most areas in northwest China, including Xinjiang, Tibet, and other regions, are severely affected by Brucella. Although there are vaccines against animal Brucellosis, the effect is often poor. In addition, there is no corresponding vaccine for human Brucellosis infection. Therefore, a new strategy for early prevention and treatment of Brucella is needed. A multi-epitope vaccine should be developed. In this study, we identified the antigenic epitopes of the Brucella type IV secretion system VirB8 and Virb10 using an immunoinformatics approach, and screened out 2 cytotoxic T lymphocyte (CTL) epitopes, 9 helper T lymphocyte (HTL) epitopes, 6 linear B cell epitopes, and 6 conformational B cell epitopes. These advantageous epitopes are spliced together through different linkers to construct a multi-epitope vaccine. The silico tests showed that the multi-epitope vaccine was non-allergenic and had a strong interaction with TLR4 molecular docking. In immune simulation results, the vaccine construct may be useful in helping brucellosis patients to initiate cellular and humoral immunity. Overall, our findings indicated that the multi-epitope vaccine construct has a high-quality structure and suitable characteristics, which may provide a theoretical basis for the development of a Brucella vaccine.

Exploring the Immunoprotective Potential of a Nanocarrier Immersion Vaccine Encoding Sip against Streptococcus Infection in Tilapia (Oreochromis niloticus)

Tilapia, as one of the fish widely cultured around the world, is suffering severe impact from the streptococcus disease with the deterioration of the breeding environment and the increasing of breeding density, which brings serious economic loss to tilapia farming. In this study, the surface immunogenic protein (Sip) of Streptococcus agalactiae (S. agalactiae) was selected as the potential candidate antigen and connected with bacterial nano cellulose (BNC) to construct the nanocarrier subunit vaccine (BNC-rSip), and the immersion immune effects against S. agalactiae and Streptococcus iniae (S. iniae) in Nile tilapia were evaluated on the basis of the serum antibody level, non-specific enzyme activity, the immune-related gene expression and relative percent survival (RPS). The results indicated that Sip possessed the expected immunogenicity according to the immunoinformatic analysis. Compared with the rSip group, BNC-rSip significantly induced serum antibody production and improved the innate immunity level of tilapia. After challenge, the RPS of BNC-rSip groups were 78.95% (S. agalactiae) and 67.86% (S. iniae), which were both higher than those of rSip groups,31.58% (S. agalactiae) and 35.71% (S. iniae), respectively. Our study indicated that BNC-rSip can induce protective immunity for tilapia through immersion immunization and may be an ideal candidate vaccine for controlling tilapia streptococcal disease.

Targeting the PEDV 3CL protease for identification of small molecule inhibitors: an insight from virtual screening, ADMET prediction, molecular dynamics, free energy landscape, and binding energy calculations

BACKGROUND

The porcine epidemic diarrhea virus (PEDV) represents a major health issue for piglets worldwide and does significant damage to the pork industry. Thus, new therapeutic approaches are urgently needed to manage PEDV infections. Due to the current lack of a reliable remedy, this present study aims to identify novel compounds that inhibit the 3CL protease of the virus involved in replication and pathogenesis.

RESULTS

To identify potent antiviral compounds against the 3CL protease, a virtual screening of natural compounds (n = 97,999) was conducted. The top 10 compounds were selected based on the lowest binding energy and the protein-ligand interaction analyzed. Further, the top five compounds that demonstrated a strong binding affinity were subjected to drug-likeness analysis using the ADMET prediction, which was followed by molecular dynamics simulations (500 ns), free energy landscape, and binding free energy calculations using the MM-PBSA method. Based on these parameters, four putative lead (ZINC38167083, ZINC09517223, ZINC04339983, and ZINC09517238) compounds were identified that represent potentially effective inhibitors of the 3CL protease.

CONCLUSION

Therefore, these can be utilized for the development of novel antiviral drugs against PEDV. However, this requires further validation through in vitro and in vivo studies.

Annotation of Potential Vaccine Targets and Designing of mRNA-Based Multi-Epitope Vaccine against Lumpy Skin Disease Virus via Reverse Vaccinology and Agent-Based Modeling

Lumpy skin disease is a fatal emerging disease of cattle, which has started to gain extensive attention due to its rapid incursions across the globe. The disease epidemic causes economic loss and cattle morbidity. Currently, there are no specific treatments and safe vaccines against the lumpy skin disease virus (LSDV) to halt the spread of the disease. The current study uses genome-scan vaccinomics analyses to prioritize promiscuous vaccine candidate proteins of the LSDV. These proteins were subjected to top-ranked B- and T-cell epitope prediction based on their antigenicity, allergenicity, and toxicity values. The shortlisted epitopes were connected using appropriate linkers and adjuvant sequences to design multi-epitope vaccine constructs. Three vaccine constructs were prioritized based on their immunological and physicochemical properties. The model constructs were back-translated to nucleotide sequences and codons were optimized. The Kozak sequence with a start codon along with MITD, tPA, Goblin 5′, 3′ UTRs, and a poly(A) tail sequences were added to design a stable and highly immunogenic mRNA vaccine. Molecular docking followed by MD simulation analysis predicted significant binding affinity and stability of LSDV-V2 construct within bovine immune receptors and predicted it to be the top-ranked candidate to stimulate the humeral and cellular immunogenic responses. Furthermore, in silico restriction cloning predicted feasible gene expression of the LSDV-V2 construct in a bacterial expression vector. It could prove worthwhile to validate the predicted vaccine models experimentally and clinically against LSDV.

Vetinformatics from functional genomics to drug discovery: Insights into decoding complex molecular mechanisms of livestock systems in veterinary science

Having played important roles in human growth and development, livestock animals are regarded as integral parts of society. However, industrialization has depleted natural resources and exacerbated climate change worldwide, spurring the emergence of various diseases that reduce livestock productivity. Meanwhile, a growing human population demands sufficient food to meet their needs, necessitating innovations in veterinary sciences that increase productivity both quantitatively and qualitatively. We have been able to address various challenges facing veterinary and farm systems with new scientific and technological advances, which might open new opportunities for research. Recent breakthroughs in multi-omics platforms have produced a wealth of genetic and genomic data for livestock that must be converted into knowledge for breeding, disease prevention and management, productivity, and sustainability. Vetinformatics is regarded as a new bioinformatics research concept or approach that is revolutionizing the field of veterinary science. It employs an interdisciplinary approach to understand the complex molecular mechanisms of animal systems in order to expedite veterinary research, ensuring food and nutritional security. This review article highlights the background, recent advances, challenges, opportunities, and application of vetinformatics for quality veterinary services.