In recent years, Salmonella infection is a major global public health concern, particularly in food safety. This study analyzed the genomes of 102 Salmonella strains isolated between 2016 and 2023 from food, foodborne disease patients, and food poisoning incidents, focusing on their molecular characteristics, antibiotic resistance genes (ARGs), and virulence genes. S. enterica serovar Enteritidis (37.3%) and S. enterica serovar Typhimurium (21.6%, including its monophasic variant 1,4,[5],12:i:-) were the main strains among 22 serotypes. Multilocus sequence typing revealed 23 sequence types (STs), with ST11, ST19, and ST34 as the most prevalent. All strains carried at least 24 ARGs. Detection rates for aac(6′)-Iy, blaTEM-1, and sul2 ranged from 44.1% to 63.7%, mainly in S. Enteritidis and S. Typhimurium. Rates for qnrS1, sul1, and aadA were 12.8% to 16.7%, while mcr-1 appeared in one ST34 S. Typhimurium strain. All strains contained at least 98 virulence genes. The genes pefABCD, mig-5, and spvBCD were in 48.0% of strains, while rck was found in 36.3%, mainly linked to S. Enteritidis and S. Typhimurium. The tssM gene was found in 37.3% of the strains, exclusively in S. Enteritidis. Core genome single nucleotide polymorphisms (cgSNPs) analysis grouped the strains into nine clusters, with 75.5% belonging to three major groups. Food poisoning event 1 was correlated with cluster 3, while events 2 and 3 were linked to cluster 1. Across events, SNP differences among strains were ≤6. Strains with SNP differences ≤10 were also found in other clusters. This method is promising for tracking sporadic cases and identifying potential foodborne safety incidents. Salmonella strains in the region exhibit substantial genetic diversity, demonstrating the efficacy of cgSNPs analysis for source tracking. Ongoing surveillance is essential given the prevalence of ARGs and virulence genes. This study provides a data foundation for local Salmonella epidemiology.
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