During the current era of the COVID-19 pandemic, the dissemination of Mucorales has been reported globally, with elevated rates of infection in India, and because of the high rate of mortality and morbidity, designing an effective vaccine against mucormycosis is a major health priority, especially for immunocompromised patients. In the current study, we studied shared Mucorales proteins, which have been reported as virulence factors, and after analysis of several virulent proteins for their antigenicity and subcellular localization, we selected spore coat (CotH) and serine protease (SP) proteins as the targets of epitope mapping. The current study proposes a vaccine constructed based on top-ranking cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL), and B cell lymphocyte (BCL) epitopes from filtered proteins. In addition to the selected epitopes, β-defensins adjuvant and PADRE peptide were included in the constructed vaccine to improve the stimulated immune response. Computational tools were used to estimate the physicochemical and immunological features of the proposed vaccine and validate its binding with TLR-2, where the output data of these assessments potentiate the probability of the constructed vaccine to stimulate a specific immune response against mucormycosis. Here, we demonstrate the approach of potential vaccine construction and assessment through computational tools, and to the best of our knowledge, this is the first study of a proposed vaccine against mucormycosis based on the immunoinformatics approach.

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Streptomyces are factories of antimicrobial secondary metabolites. We isolated a Streptomyces species associated with the Pelargonium graveolens rhizosphere. Its total metabolic extract exhibited potent antibacterial and antifungal properties against all the tested pathogenic microbes. Whole genome sequencing and genome analyses were performed to take a look at its main characteristics and to reconstruct the metabolic pathways that can be associated with biotechnologically useful traits. AntiSMASH was used to identify the secondary metabolite gene clusters. In addition, we searched for known genes associated with plant growth-promoting characteristics. Finally, a comparative and pan-genome analysis with three closely related genomes was conducted. It was identified as Streptomyces vinaceusdrappus strain AC-40. Genome mining indicated the presence of several secondary metabolite gene clusters. Some of them are identical or homologs to gene clusters of known metabolites with antimicrobial, antioxidant, and other bioactivities. It also showed the presence of several genes related to plant growth promotion traits. The comparative genome analysis indicated that at least five of these gene clusters are highly conserved through rochei group genomes. The genotypic and phenotypic characteristics of S. vinaceusdrappus strain AC-40 indicate that it is a promising source of beneficial secondary metabolites with pharmaceutical and biotechnological applications.