BACKGROUND

From July 23 to 24, 2022, Qingxu People's Hospital in Taiyuan reported an increase in acute gastroenteritis cases among individuals who had dined together.An investigation was initiated to identify factors associated with acute intestinal infection and to prevent further illness.

METHODS

To isolate, cultivate, and identify pathogens, we collected samples from patients, food, and the environment. The isolated strains underwent multiple tests, including antimicrobial susceptibility testing, pulsed-field gel electrophoresis (PFGE), and whole-genome sequencing (WGS). Based on the WGS data, analyses were conducted, including serotype prediction, resistance gene prediction, multilocus sequence typing (MLST), core genome multilocus sequence typing (cgMLST), single nucleotide polymorphism (SNP) analysis, and phylogenetic analysis.

RESULTS

A total of 11 samples were collected from Patient 1's residence and the supermarket. These included 2 samples of leftover food from a family gathering, 4 samples of the supermarket environment, and 5 stool samples from 5 patients. Among these, two strains of Salmonella were isolated from the food, and three strains were isolated from the patients' stools. All five strains of Salmonella were identified as Salmonella Agona (S. Agona) and were susceptible to the 15 antibiotics tested. The PFGE banding patterns were identical among the strains. Bioinformatics analysis revealed that the isolated strains were all S. Agona of sequence type ST13 and cgMLST type cgST164980. They all carried the resistance genes aac(6')-laa and fosA7. SNP disparities ranged from 0 to 2. In the phylogenetic tree, the five strains of S. Agona isolated clustered closely together.

CONCLUSIONS

In this investigation of a food poisoning outbreak caused by S. Agona, we employed two key molecular techniques: Pulsed-Field Gel Electrophoresis (PFGE) and Whole Genome Sequencing (WGS). PFGE provided initial high-resolution DNA fingerprinting to identify bacterial strains and establish their clonal relatedness, offering preliminary but crucial insights into understanding the microbial causes of the epidemic. Subsequently, WGS delivered comprehensive genetic information with unparalleled precision, confirming that the pathogen was S. Agona and revealing its genomic characteristics. The integration of PFGE and WGS results provided strong evidence proving the epidemic was related to S. Agona. This comprehensive approach not only confirmed the etiology of the food poisoning event but also highlighted the power of molecular and genomic tools in modern epidemiological investigations. Our findings emphasize the importance of these techniques in rapidly and accurately identifying pathogens, thereby enabling timely public health interventions and reinforcing food safety measures to prevent similar outbreaks in the future.