Protein Interaction Network Analysis to Investigate Stress Response, Virulence, and Antibiotic Resistance Mechanisms in .

is a deadly and costly foodborne pathogen that has a high fatality rate in the elderly, pregnant women, and people with weakened immunity. It can survive under various stress conditions and is a significant concern for the food industry. In this work, a data analysis approach was developed with existing tools and databases and used to create individual and combined protein interaction networks to study stress response, virulence, and antimicrobial resistance and their interaction with . The networks were analyzed, and 28 key proteins were identified that may serve as potential targets for new strategies to combat . Five of the twenty-eight proteins (i.e., sigB, flaA, cheA, cheY, and lmo0693) represent the most promising targets because they are highly interconnected within the combined network. The results of this study provide a new set of targets for future work to identify new strategies to improve food preservation methods and treatments for .