In silico epitope analysis of Shigella dysenteriae for the design of immunogens in food contaminant detection

Shigella dysenteriae is an intracellular bacterium responsible for shigellosis, a disease prevalent in developing countries with a reported mortality rate of 10–15%. Transmission typically occurs through contaminated food. In addition to maintaining hygiene during food handling and preparation, verifying that food ingredients are free from S. dysenteriae is critical for preventing its spread. Immunoassay-based methods are commonly used for such authentication and rely on the availability of specific antibodies targeting S. dysenteriae. The production of these antibodies requires the identification of specific immunogenic epitopes. In this study, we conducted an in silico analysis to identify a potential epitope of S. dysenteriae using bioinformatics tools. Protein sequence data were obtained from UniProtKB (https://www.uniprot.org/) and analysed with the VaxiJen v2.0 server (https://www.ddg-pharmfac.net/vaxijen/VaxiJen/VaxiJen.html). This analysis revealed a candidate immunogenic epitope with the amino acid sequence LAKLTNNNAQGEITDIIALAY. While these findings are promising, further in vivo validation is necessary to determine whether this epitope can effectively elicit antibody production for use in immunoassay development aimed at detecting S. dysenteriae contamination in food.