Abstract

Clostridium chauvoei, the causative agent of blackleg disease in cattle, presents significant economic and health challenges due to its high mortality rates and rapid disease progression. This study focuses on the in silico genomic characterization of C. chauvoei strain SBP 07/09 Swiss Bovine Pathogen, referring to a strain isolated in July 2009. The study identified and annotated pathogenic islands (PIs) contributing to the bacterium’s virulence and adaptability. Using IslandViewer4, eight distinct PIs were identified, and 81 genes were detected using GeneMark. hmm-P across these PIs. The genes are categorized as 60 functional genes, 20 hypothetical proteins, and one gene with no assigned function. Functional annotation of genes using tools such as Basic Local Alignment Search Tool (BLASTp), InterPro, and BlastKOALA revealed that these genes are implicated in essential processes, including stress response, metabolism, genetic mobility, DNA repair, and anaerobic survival. Pathway analysis was performed using Kyoto Encyclopedia of Genes and Genomes (KEGG) Mapper and BioCyc Pathway Tools, utilizing KO identifiers assigned by BlastKOALA and whole genome data, respectively. This analysis revealed several key metabolic and regulatory pathways associated with the detected genes. These include nutrient transport, energy production, cofactor biosynthesis, and environmental adaptation. These pathways will likely contribute significantly to the organism’s adaptability, anaerobic lifestyle, and survival within the host environment. Key findings include the identification of genes facilitating nutrient uptake, energy production, and genomic integrity maintenance. All of which enhance C. chauvoei’s virulence and survival in hostile host environments. These insights offer valuable targets for developing preventative and therapeutic strategies to combat blackleg disease, reducing its economic burden on cattle farming.

Key words: Clostridium chauvoei, Blackleg disease, pathogenic islands, gene prediction, functional annotation, metabolic pathway prediction