Abstract
Global surveillance of Salmonella enterica reveals dynamic evolutionary forces shaping pathogenicity and antimicrobial resistance (AMR), yet the integration of serotyping, multilocus sequence typing (MLST), and phenotypic landscapes remains unexplored. Here, we dissect 935 Salmonella isolates, collected from both clinical and food chain sources, through integrated genomics and phenomics to resolve population structure, spatiotemporal dynamics, and evolutionary drivers. Salmonella Typhimurium (18.7%) and Salmonella Enteritidis (17.1%) dominate the serotype landscape, while MLST uncovers ST34 (20.7%) as the pivotal sequence type bridging multiple serotypes. Temporal tracking (2018–2022) exposes alarming AMR trajectories: ciprofloxacin resistance doubled (15.3% to 30.4%) by 2020, and tetracycline resistance peaked at 77.3%. The serotype-specific epidemiology reveals that S. Typhimurium declined and then stabilized, S. Enteritidis fluctuated due to vaccination, and S. Derby emerged persistently (+69%). Network analysis reveals two evolutionary clusters: one anchored by S. Typhimurium/S. Enteritidis-ST34/ST11 and another harboring diverse STs associated with S. Derby. Notably, ST34 acts as a genetic backbone for serotype switching. Notably, S. Typhimurium exhibits the highest AMR gene burden (median: 4.2 genes/ isolate) and virulence arsenal (spvB: 85.1%; pefA: 75.4%), which correlates with invasive disease. Geographic heterogeneity results in distinct serotype distributions: S. Enteritidis dominates in Xinyu (28.4%), S. Typhimurium prevails in Shangrao (31.5%), and Ganzhou exhibits balanced diversity. Our findings establish that clonal expansion, horizontal gene transfer, and regional ecologies are key factors jointly driving Salmonella evolution. This necessitates genotype-phenotype-integrated surveillance to preempt the emergence and widespread dissemination of resistance and virulence.
Cite
CITATION STYLE
Hong, W., Yang, Z., Wu, G., Liu, C., Wang, Y., & Liao, N. (2025). Integrating serotyping, MLST, and phenotypic data: decoding the evolutionary drivers of Salmonella pathogenicity and drug resistance. Applied and Environmental Microbiology, 91(10). https://doi.org/10.1128/aem.01511-25
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