Network Analysis of Virulence Gene Interactions in Human Clinical Salmonella Typhimurium Isolates

Globally, Salmonella enterica serovar Typhimurium ( S. Typhimurium) is a main bacterial enteric pathogen associated with human gastroenteritis. Individual virulence genes have been extensively studied; however, studies are needed to assess networks of gene-gene and protein-protein interactions. Clinical isolate data for S. Typhimurium from the NCBI Pathogen Detection database were assessed using network analysis to characterize virulence gene co-occurrence patterns. Across the isolates, 38 virulence genes were reported, and on average, each isolate carried 10.52 virulence genes. The highest prevalence was identified for invA (99.85%), lpfB (99.85%), iroB (99.24%), sinH (98.93%), iroC (98.75%), and sodC1 (98.11%). The network comprised 22 nodes and 176 edges, representing a highly connected virulence system that suggests a coordinated or synergistic role of multiple genes. The network's diameter was 2, with a radius of 1, and a characteristic path length of 1.238, suggesting a compact structure with closely associated genes. Based on centrality analysis, 10 hub genes, invA, iroB, iroC, avrA, lpfB, sinH, sodC1, sseK2, sspH2, and gtgA, were identified. The Maximal Clique Centrality (MCC) algorithm prioritization determined avrA, invA, and sodC1 as top-ranked virulence genes. Overall, our network-based analysis provided a framework for identifying important virulence determinants, which can be used for drug design, vaccine strategies, epidemiological monitoring, and targeted intervention to combat human salmonellosis.