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Brucellosis is a zoonotic infectious disease caused by bacteria of the genusBrucella.Brucella melitensis,Brucella abortus, andBrucella suisare the most pathogenic species of this genus causing the majority of human and domestic animal brucellosis. There is a need to develop a safe and potent subunit vaccine to overcome the serious drawbacks of the live attenuatedBrucellavaccines. The aim of this work was to discover antigen candidates conserved among the three pathogenic species. In this study, we employed a reverse vaccinology strategy to compute the core proteome of 90 completed genomes: 55B. melitensis, 17B. abortus, and 18B. suis. The core proteome was analyzed by a metasubcellular localization prediction pipeline to identify surface-associated proteins. The identified proteins were thoroughly analyzed using variousin silicotools to obtain the most potential protective antigens. The number of core proteins obtained from analyzing the 90 proteomes was 1939 proteins. The surface-associated proteins were 177. The number of potential antigens was 87; those with adhesion score ≥ 0.5 were considered antigen with “high potential,” while those with a score of 0.4–0.5 were considered antigens with “intermediate potential.” According to a cumulative score derived from protein antigenicity, density of MHC-I and MHC-II epitopes, MHC allele coverage, and B-cell epitope density scores, a final list of 34 potential antigens was obtained. Remarkably, most of the 34 proteins are associated with bacterial adhesion, invasion, evasion, and adaptation to the hostile intracellular environment of macrophages which is adjusted to depriveBrucellaof required nutrients. Our results provide a manageable list of potential protective antigens for developing a potent vaccine against brucellosis. Moreover, our elaborated analysis can provide further insights into novelBrucellavirulence factors. Our next step is to test some of these antigens using an appropriate antigen delivery system.

One of the most effective strategies for eliminating new and emerging infectious diseases is effective immunization. The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) warrants the need for a maximum coverage vaccine. Moreover, mutations that arise within the virus have a significant impact on the vaccination strategy. Here, we built a comprehensive in silico workflow pipeline to identify B-cell- and T-cell-stimulating antigens of SARS-CoV-2 viral proteins. Our in silico reverse vaccinology (RV) approach consisted of two parts: (1) analysis of the selected viral proteins based on annotated cellular location, antigenicity, allele coverage, epitope density, and mutation density and (2) analysis of the various aspects of the epitopes, including antigenicity, allele coverage, IFN-γ induction, toxicity, host homology, and site mutational density. After performing a mutation analysis based on the contemporary mutational amino acid substitutions observed in the viral variants, 13 potential epitopes were selected as subunit vaccine candidates. Despite mutational amino acid substitutions, most epitope sequences were predicted to retain immunogenicity without toxicity and host homology. Our RV approach using an in silico pipeline may potentially reduce the time required for effective vaccine development and can be applicable for vaccine development for other pathogenic diseases as well.